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1
Medarevic, Jelena, Marija Novicic, and Marko Markovic. "Feasibility test of activity index summary metric in human hand activity recognition." Serbian Journal of Electrical Engineering 19, no. 2 (2022): 225–38. http://dx.doi.org/10.2298/sjee2202225m.
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Activity monitoring is a technique for assessing the physical activity that a person undertakes over some time. Activity Index (AI) is a metric that summarizes the raw measurements from tri-axial accelerometers, often used for measuring physical activity. Our research compared the Activity Index for different activity groups and hand usage [1]. We also tested this metric as a classification feature, and how different data acquisition and segmentation parameter configurations influence classification accuracy. Data acquisition was done with a previously developed system that includes a smartwatch on each wrist and a smartphone placed in the subject?s pocket; raw data from smartwatch accelerometers was used for the analysis. We calculated the Activity Index for labeled data segments and used ANOVA1 statistical test with Bonferroni correction. Significant differences were found between cases of hand usage (left, right, none, both). In the next analysis phase, the Activity Index was used as the classification feature with three supervised machine learning algorithms-Support Vector Machine, k-Nearest Neighbors, and Random Forest. The best accuracy (measured by F1 score) of classifying hand usage was achieved by using the Random Forest algorithm, 50 Hz sampling frequency, and a window of 10 s without overlap for AI calculation, and it was 97%. On the other hand, the classification of activity groups had a low accuracy, which indicated that a specific activity group can?t be identified by using only one simple feature.
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Senyurek, Volkan, Masudul Imtiaz, Prajakta Belsare, Stephen Tiffany, and Edward Sazonov. "Electromyogram in Cigarette Smoking Activity Recognition." Signals 2, no. 1 (February 9, 2021): 87–97. http://dx.doi.org/10.3390/signals2010008.
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In this study, information from surface electromyogram (sEMG) signals was used to recognize cigarette smoking. The sEMG signals collected from lower arm were used in two different ways: (1) as an individual predictor of smoking activity and (2) as an additional sensor/modality along with the inertial measurement unit (IMU) to augment recognition performance. A convolutional and a recurrent neural network were utilized to recognize smoking-related hand gestures. The model was developed and evaluated with leave-one-subject-out (LOSO) cross-validation on a dataset from 16 subjects who performed ten activities of daily living including smoking. The results show that smoking detection using only sEMG signal achieved an F1-score of 75% in person-independent cross-validation. The combination of sEMG and IMU improved reached the F1-score of 84%, while IMU alone sensor modality was 81%. The study showed that using only sEMG signals would not provide superior cigarette smoking detection performance relative to IMU signals. However, sEMG improved smoking detection results when combined with IMU signals without using an additional device.
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Ramirez, Heilym, Sergio A. Velastin, Paulo Aguayo, Ernesto Fabregas, and Gonzalo Farias. "Human Activity Recognition by Sequences of Skeleton Features." Sensors 22, no. 11 (May 25, 2022): 3991. http://dx.doi.org/10.3390/s22113991.
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In recent years, much effort has been devoted to the development of applications capable of detecting different types of human activity. In this field, fall detection is particularly relevant, especially for the elderly. On the one hand, some applications use wearable sensors that are integrated into cell phones, necklaces or smart bracelets to detect sudden movements of the person wearing the device. The main drawback of these types of systems is that these devices must be placed on a person’s body. This is a major drawback because they can be uncomfortable, in addition to the fact that these systems cannot be implemented in open spaces and with unfamiliar people. In contrast, other approaches perform activity recognition from video camera images, which have many advantages over the previous ones since the user is not required to wear the sensors. As a result, these applications can be implemented in open spaces and with unknown people. This paper presents a vision-based algorithm for activity recognition. The main contribution of this work is to use human skeleton pose estimation as a feature extraction method for activity detection in video camera images. The use of this method allows the detection of multiple people’s activities in the same scene. The algorithm is also capable of classifying multi-frame activities, precisely for those that need more than one frame to be detected. The method is evaluated with the public UP-FALL dataset and compared to similar algorithms using the same dataset.
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Ray, Sujan, Khaldoon Alshouiliy, and Dharma P. Agrawal. "Dimensionality Reduction for Human Activity Recognition Using Google Colab." Information 12, no. 1 (December 23, 2020): 6. http://dx.doi.org/10.3390/info12010006.
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Human activity recognition (HAR) is a classification task that involves predicting the movement of a person based on sensor data. As we can see, there has been a huge growth and development of smartphones over the last 10–15 years—they could be used as a medium of mobile sensing to recognize human activity. Nowadays, deep learning methods are in a great demand and we could use those methods to recognize human activity. A great way is to build a convolutional neural network (CNN). HAR using Smartphone dataset has been widely used by researchers to develop machine learning models to recognize human activity. The dataset has two parts: training and testing. In this paper, we propose a hybrid approach to analyze and recognize human activity on the same dataset using deep learning method on cloud-based platform. We have applied principal component analysis on the dataset to get the most important features. Next, we have executed the experiment for all the features as well as the top 48, 92, 138, and 164 features. We have run all the experiments on Google Colab. In the experiment, for the evaluation of our proposed methodology, datasets are split into two different ratios such as 70–10–20% and 80–10–10% for training, validation, and testing, respectively. We have set the performance of CNN (70% training–10% validation–20% testing) with 48 features as a benchmark for our work. In this work, we have achieved maximum accuracy of 98.70% with CNN. On the other hand, we have obtained 96.36% accuracy with the top 92 features of the dataset. We can see from the experimental results that if we could select the features properly then not only could the accuracy be improved but also the training and testing time of the model.
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Gao, Zhiqiang, Dawei Liu, Kaizhu Huang, and Yi Huang. "Context-Aware Human Activity and Smartphone Position-Mining with Motion Sensors." Remote Sensing 11, no. 21 (October 29, 2019): 2531. http://dx.doi.org/10.3390/rs11212531.
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Today’s smartphones are equipped with embedded sensors, such as accelerometers and gyroscopes, which have enabled a variety of measurements and recognition tasks. In this paper, we jointly investigate two types of recognition problems in a joint manner, e.g., human activity recognition and smartphone on-body position recognition, in order to enable more robust context-aware applications. So far, these two problems have been studied separately without considering the interactions between each other. In this study, by first applying a novel data preprocessing technique, we propose a joint recognition framework based on the multi-task learning strategy, which can reduce computational demand, better exploit complementary information between the two recognition tasks, and lead to higher recognition performance. We also extend the joint recognition framework so that additional information, such as user identification with biometric motion analysis, can be offered. We evaluate our work systematically and comprehensively on two datasets with real-world settings. Our joint recognition model achieves the promising performance of 0.9174 in terms of F 1 -score for user identification on the benchmark RealWorld Human Activity Recognition (HAR) dataset. On the other hand, in comparison with the conventional approach, the proposed joint model is shown to be able to improve human activity recognition and position recognition by 5.1 % and 9.6 % respectively.
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Guo, Jiang, Jun Cheng, Yu Guo, and Jian Xin Pang. "A Real-Time Dynamic Gesture Recognition System." Applied Mechanics and Materials 333-335 (July 2013): 849–55. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.849.
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In this paper, we present a dynamic gesture recognition system. We focus on the visual sensory information to recognize human activity in form of hand movements from a small, predefined vocabulary. A fast and effective method is presented for hand detection and tracking at first for the trajectory extraction. A novel trajectory correction method is applied for simply but effectively trajectory correction. Gesture recognition is achieved by means of a matching technique by determining the distance between the unknown input direction code sequence and a set of previously defined templates. A dynamic time warping (DTW) algorithm is used to perform the time alignment and normalization by computing a temporal transformation allowing the two signals to be matched. Experiment results show our proposed gesture recognition system achieve well result in real time.
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Bieck, Richard, Reinhard Fuchs, and Thomas Neumuth. "Surface EMG-based Surgical Instrument Classification for Dynamic Activity Recognition in Surgical Workflows." Current Directions in Biomedical Engineering 5, no. 1 (September 1, 2019): 37–40. http://dx.doi.org/10.1515/cdbme-2019-0010.
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AbstractWe introduce a wearable-based recognition system for the classification of natural hand gestures during dynamic activities with surgical instruments. An armbandbased circular setup of eight EMG-sensors was used to superficially measure the muscle activation signals over the broadest cross-section of the lower arm. Instrument-specific surface EMG (sEMG) data acquisition was performed for 5 distinct instruments. In a first proof-of-concept study, EMG data were analyzed for unique signal courses and features, and in a subsequent classification, both decision tree (DTR) and shallow artificial neural network (ANN) classifiers were trained. For DTR, an ensemble bagging approach reached precision and recall rates of 0.847 and 0.854, respectively. The ANN network architecture was configured to mimic the ensemble-like structure of the DTR and achieved 0.952 and 0.953 precision and recall rates, respectively. In a subsequent multi-user study, classification achieved 70 % precision. Main errors potentially arise for instruments with similar gripping style and performed actions, interindividual variations in the acquisition procedure as well as muscle tone and activation magnitude. Compared to hand-mounted sensor systems, the lower arm setup does not alter the haptic experience or the instrument gripping, which is critical, especially in an intraoperative environment. Currently, drawbacks of the fixed consumer product setup are the limited data sampling rate and the denial of frequency features into the processing pipeline.
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Bragin, A. D., and V. G. Spitsyn. "Motor imagery recognition in electroencephalograms using convolutional neural networks." Computer Optics 44, no. 3 (June 2020): 482–87. http://dx.doi.org/10.18287/2412-6179-co-669.
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Electroencephalography is a widespread method to record brain signals with the use of electrodes located on the surface of the head. This method of recording the brain activity has become popular because it is relatively cheap, compact, and does not require implanting the electrodes directly into the brain. The article is devoted to a problem of recognition of motor imagery by electroencephalogram signals. The nature of such signals is complex. Characteristics of electroencephalograms are individual for every person, also depending on their age and mental state, as well as the presence of noise and interference. The multitude of these parameters should be taken into account when analyzing encephalograms. Artificial neural networks are a good tool for solving this class of problems. Their application allows combining the tasks of extracting, selecting and classifying features in one signal processing unit. Electroencephalograms are time signals and we note that Gramian Angular Fields and Markov Transition Field transforms are used to represent time series in the form of images. The article shows the possibility of using the Gramian Angular Fields and Markov Transition Field transformations of the electroencephalogram (EEG) signal for motor imagery recognition using examples of imaginary movements with the right and left hand, also studying the effect of the resolution of Gramian Angular Fields and Markov Transition Field images on the classification accuracy. The best classification accuracy of the EEG signal into the motion and state-of-rest classes is about 99%. In future, the research results can be applied in constructing the brain-computer interface.
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Liu, Dan, Mao Ye, and Jianwei Zhang. "Improving Action Recognition Using Sequence Prediction Learning." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 12 (March 20, 2020): 2050029. http://dx.doi.org/10.1142/s0218001420500299.
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Skeleton-based action recognition distinguishes human actions using the trajectories of skeleton joints, which can be a good representation of human behaviors. Conventional methods usually construct classifiers with hand-crafted or the learned features to recognize human actions. Different from constructing a direct action classifier for action recognition task, this paper attempts to identify human actions based on the development trends of behavior sequences. Specifically, we first utilize the memory neural network to construct action predictors for each kind of activity. These action predictors can then output the action trends at the next time step. According to the predictions of these action predictors at each time step and the removal rule, the poor predictors can be eliminated step by step, and the IDentity(ID) number of the last predictor left is considered as the label of the action sequence to be categorized. We compare the proposed action recognition algorithm using sequence prediction learning with other methods on two publicly available datasets. Our experimental results consistently demonstrate the feasibility and effectiveness of the suggested method. It also proves the importance of prediction learning for action recognition.
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Yin, Guanghao, Shouqian Sun, Dian Yu, Dejian Li, and Kejun Zhang. "A Multimodal Framework for Large-Scale Emotion Recognition by Fusing Music and Electrodermal Activity Signals." ACM Transactions on Multimedia Computing, Communications, and Applications 18, no. 3 (August 31, 2022): 1–23. http://dx.doi.org/10.1145/3490686.
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Considerable attention has been paid to physiological signal-based emotion recognition in the field of affective computing. For reliability and user-friendly acquisition, electrodermal activity (EDA) has a great advantage in practical applications. However, EDA-based emotion recognition with large-scale subjects is still a tough problem. The traditional well-designed classifiers with hand-crafted features produce poorer results because of their limited representation abilities. And the deep learning models with auto feature extraction suffer the overfitting drop-off because of large-scale individual differences. Since music has a strong correlation with human emotion, static music can be involved as the external benchmark to constrain various dynamic EDA signals. In this article, we make an attempt by fusing the subject’s individual EDA features and the external evoked music features. And we propose an end-to-end multimodal framework, the one-dimensional residual temporal and channel attention network (RTCAN-1D). For EDA features, the channel-temporal attention mechanism for EDA-based emotion recognition is first involved in mine the temporal and channel-wise dynamic and steady features. The comparisons with single EDA-based SOTA models on DEAP and AMIGOS datasets prove the effectiveness of RTCAN-1D to mine EDA features. For music features, we simply process the music signal with the open-source toolkit openSMILE to obtain external feature vectors. We conducted systematic and extensive evaluations. The experiments on the current largest music emotion dataset PMEmo validate that the fusion of EDA and music is a reliable and efficient solution for large-scale emotion recognition.
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Chodubski, Andrzej. "Nauka wobec wyzwań współczesnej rzeczywistości społeczno-politycznej." Cywilizacja i Polityka 14, no. 14 (October 30, 2016): 21–29. http://dx.doi.org/10.5604/01.3001.0010.0237.
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It is indicated in the lecture that science, as human activity that aims at the objective recognition of a person and his universe, is nowadays perceived as a fundamental power that generates the cultural and civilizational nature of mankind and the world around it. The widening horizon of cultural life has been changing and still changes the scientific and research challenges, including the way, in which science is defined. At present, scientific and technological progress, legal solutions, educational requirements, constantly generate new challenges for science and make it a productive force. The role of social and political sciences that until recently strived to make their ways to achieve the title of science that is a methodologically structured knowledge about human, society and the world, has been changing.At present, the place of social and political reality in the sphere of scientific cognition is perceived as dichotomous – on the one hand, due to the methodology of researches, including attempts to compare them with exact sciences, their scientific separateness is assessed critically; however, on the other hand, taking into account the worked out methods and ways of defining cultural and civilizational reality, explantation of occurrences, processes, humanistic and social values, they are set in the classical science studies, as a whole.
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Heo, Youngjun, and Sunggu Lee. "Supervised Contrastive Learning for Voice Activity Detection." Electronics 12, no. 3 (January 31, 2023): 705. http://dx.doi.org/10.3390/electronics12030705.
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The noise robustness of voice activity detection (VAD) tasks, which are used to identify the human speech portions of a continuous audio signal, is important for subsequent downstream applications such as keyword spotting and automatic speech recognition. Although various aspects of VAD have been recently studied by researchers, a proper training strategy for VAD has not received sufficient attention. Thus, a training strategy for VAD using supervised contrastive learning is proposed for the first time in this paper. The proposed method is used in conjunction with audio-specific data augmentation methods. The proposed supervised contrastive learning-based VAD (SCLVAD) method is trained using two common speech datasets and then evaluated using a third dataset. The experimental results show that the SCLVAD method is particularly effective in improving VAD performance in noisy environments. For clean environments, data augmentation improves VAD accuracy by 8.0 to 8.6%, but there is no improvement due to the use of supervised contrastive learning. On the other hand, for noisy environments, the SCLVAD method results in VAD accuracy improvements of 2.9% and 4.6% for “speech with noise” and “speech with music”, respectively, with only a negligible increase in processing overhead during training.
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Pradhap, S., Dr J. Sreerambabu, and N. Santhosh. "Real Time Video Recognition of Signs for Deaf and Dump Using Deep Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 8 (August 31, 2022): 936–38. http://dx.doi.org/10.22214/ijraset.2022.46318.
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Abstract: To pass the message is one of the essential prerequisites for endurance in the general public. Gesture based communication is a typical specialized technique for hard of hearing stupid local area. It makes out of an assortment scope of motions, activities and, surprisingly, facial feelings.Gesture based communication is utilized by 70 million individuals all over the planet. Understanding communication via gestures is one of the essential empowering influences in assisting clients of gesture-based communication with speaking with the remainder of the general public. The hard of hearing and dump local area moves back with regards to the intelligent part with ordinary individuals. This makes a tremendous hole among hard of hearing and dump individuals and ordinary individuals. Since our local area have no clue about communication through signing. In this project an application is created which will fill in as a learning instrument first of all in communication via gestures that includes hand recognition. Application is made to change gesture-based communication over to message. An application which makes an interpretation of Sign language to message, which utilizes the portable camera to catch the picture of the hand motion. Then, at that point, the caught picture goes through the series of activity. The CNN model is utilized to extricate the elements of the caught picture and makes an interpretation of it into text.
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KATZOURIS, NIKOS, ALEXANDER ARTIKIS, and GEORGIOS PALIOURAS. "Online learning of event definitions." Theory and Practice of Logic Programming 16, no. 5-6 (September 2016): 817–33. http://dx.doi.org/10.1017/s1471068416000260.
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AbstractSystems for symbolic event recognition infer occurrences of events in time using a set of event definitions in the form of first-order rules. The Event Calculus is a temporal logic that has been used as a basis in event recognition applications, providing among others, direct connections to machine learning, via Inductive Logic Programming (ILP). We present an ILP system for online learning of Event Calculus theories. To allow for a single-pass learning strategy, we use the Hoeffding bound for evaluating clauses on a subset of the input stream. We employ a decoupling scheme of the Event Calculus axioms during the learning process, that allows to learn each clause in isolation. Moreover, we use abductive-inductive logic programming techniques to handle unobserved target predicates. We evaluate our approach on an activity recognition application and compare it to a number of batch learning techniques. We obtain results of comparable predicative accuracy with significant speed-ups in training time. We also outperform hand-crafted rules and match the performance of a sound incremental learner that can only operate on noise-free datasets.
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Jabbar, Ambreen, Saud Altaf, Saqib Majeed, and Muhammad Waseem Soomro. "WI-FI-BASED CHANNEL STATE INFORMATION APPROACH FOR SENSING AND HUMAN WALKING ACTIVITY RECOGNITION IN INDOOR ENVIRONMENT." Journal of Southwest Jiaotong University 57, no. 6 (December 30, 2022): 360–70. http://dx.doi.org/10.35741/issn.0258-2724.57.6.34.
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Many studies have demonstrated that Wireless Fidelity (Wi-Fi) networks can detect human behavior due to the development of wireless devices and detecting methodologies. Human activity recognition applied Channel State Information (CSI) in commercial Wi-Fi devices, which has many practical applications. This paper aims to present a method for recognizing human activity that uses enhanced Wi-Fi-based CSI signals. At first, researchers examined how various perceptive antennas detect motion caused by humans. The proposed algorithm for selecting antennas considers the sensitivity of each antenna concerning the task at hand. Long short-term memory (LSTM) and Inception Time-based classification model was developed and fine-tuned for experiments. This study also suggested two basic power methods to retrieve the effective interval associated with human activity, one of which can solidify the active signals while weakening the inactive signals. Last but not least, an algorithm has been developed for segmenting activity to identify initiation and termination times. An efficient outliers removal technique was used to remove the edges. The results show that using commonplace Wi-Fi routers can accurately categorize human actions 87% of the time. To validate and evaluate these methods, immense experiments were conducted in exquisite indoor environments. As demonstrated by experiments, the proposed methods can mitigate the disturbance caused by inert and non-responsive signals and enhance accuracy rates while improving efficiency and processing time.
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Li, Hao, and Meng Xu. "Application of Accelerometer to Monitor Students’ Exercise Load in 50 m Round Trip." Computational Intelligence and Neuroscience 2022 (June 29, 2022): 1–11. http://dx.doi.org/10.1155/2022/3142677.
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With the further advancement of microelectronics innovation and sensors, sensors can be broadly implanted in cell phone gadgets, compact gadgets, and so forth. The utilization of speed increase sensors for human running checking has expansive application possibilities. From one perspective, the everyday development of the human body is firmly connected with the physical and emotional wellness of the person. Observing the day-to-day developments of the human body is of incredible importance in planning a logical running activity plan and working on actual wellbeing. On the other hand, it is also of practical value to monitor human abnormal movements. This kind of abnormal movement caused by accidental falls can bring certain harm to the human body. Real-time monitoring of the fall can provide timely assistance to the person and reduce the risk brought by the fall. This article analyzes and summarizes the research theories and common research methods in the field of 50 m round-trip movement monitoring based on the acceleration sensor. According to the process of 50 m round-trip movement pattern recognition, the data collection, preprocessing, feature extraction, and selection of 50 m round-trip movement are evaluated. The classification and recognition of each module were analyzed. This article proposes a human body motion recognition mechanism based on acceleration sensors by looking at the three trademark upsides, the wavefront edge, wavefront limit, and time stretch between the pinnacle and valley of the speed increase sensor vertical information waveform, and joining the rule of choice tree order to accomplish the activities of hunching down, taking off, and running. To get an accurate recognizable proof and recognize ways of behaving, a human fall identification calculation is proposed. This calculation removes human movement attributes throughout the fall and focuses on four sorts of falls: forward fall, reverse fall, left fall, and right fall by utilizing the connection of the three tomahawks of the speed increase sensor. The trial results show that the normal right acknowledgment pace of the human body’s 50 m full-circle running way of behaviour is more than 90%, which has specific useful application esteem.
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Vavilin, Evgeniy V. "The status of artificial intelligence: from object to the subject of legal relations." Vestnik Tomskogo gosudarstvennogo universiteta. Pravo, no. 45 (2022): 147–58. http://dx.doi.org/10.17223/22253513/45/10.
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Artificial intelligence systems (AI), being, on the one hand, an object of law, in the course of their vital activity, can gain independence and perform legally significant actions without human participation. This testifies in favor of giving AI the status of a subject of law, since it requires the establishment of appropriate mechanisms of responsibility, the limits of implementation and protection of AI rights. In the light of the posed problem, the controversy about the recognition of AI as the author of the works created by it is indicative. Most foreign legal orders do not recognize the authorship of "non-human" creativity, giving the status of authors to AI developers. Domestic researchers, as a rule, also insist on the impossibility or absence of the need to recognize AI as the subject of relations in using the results of intellectual activity of AI. In case the works created by AI are recognized as public domain, the developers are deprived of the incentive, and the objects themselves - of potential negotiability. When the possessor of exclusive rights to the results created by artificial intelligence systems is recognized as its owner or tenant at the time of creation of the work, several problems associated with both the monopolization of this sphere and possible abuses of rights arise. Regarding such entities, it can only be a question of special legal personality because of the competences of electronic persons, their importance and role in civil circulation. The solution in this case may be the development of a legal regime in which the developers of units capable of creating works are recognized as the authors of the unit and receive remuneration for its creation and use, but copyright and exclusive rights to the works created by them must be assigned to the electronic person, along with the obligation of mandatory tax deductions from the profits received and compensation for the losses caused to them, if they occur. Thus, when deciding on the legal status of AI, it is necessary to recognize, on the one hand, an artificial intellectual system as an object of copyright, on the other hand, its direct functioning by a relatively independent participant in civil law relations, since it has signs that allow it to be endowed with the status of a subject. AI, being at the stage of creation an object of intellectual property of software developers, after appropriate certification and state registration, can be endowed with the status of a subject of law. Attention should be paid to the special nature of the legal capacity and legal competency of an electronic person. The author declares no conflicts of interests.
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Hein, Jonas, Matthias Seibold, Federica Bogo, Mazda Farshad, Marc Pollefeys, Philipp Fürnstahl, and Nassir Navab. "Towards markerless surgical tool and hand pose estimation." International Journal of Computer Assisted Radiology and Surgery 16, no. 5 (April 21, 2021): 799–808. http://dx.doi.org/10.1007/s11548-021-02369-2.
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Abstract Purpose: Tracking of tools and surgical activity is becoming more and more important in the context of computer assisted surgery. In this work, we present a data generation framework, dataset and baseline methods to facilitate further research in the direction of markerless hand and instrument pose estimation in realistic surgical scenarios. Methods: We developed a rendering pipeline to create inexpensive and realistic synthetic data for model pretraining. Subsequently, we propose a pipeline to capture and label real data with hand and object pose ground truth in an experimental setup to gather high-quality real data. We furthermore present three state-of-the-art RGB-based pose estimation baselines. Results: We evaluate three baseline models on the proposed datasets. The best performing baseline achieves an average tool 3D vertex error of 16.7 mm on synthetic data as well as 13.8 mm on real data which is comparable to the state-of-the art in RGB-based hand/object pose estimation. Conclusion: To the best of our knowledge, we propose the first synthetic and real data generation pipelines to generate hand and object pose labels for open surgery. We present three baseline models for RGB based object and object/hand pose estimation based on RGB frames. Our realistic synthetic data generation pipeline may contribute to overcome the data bottleneck in the surgical domain and can easily be transferred to other medical applications.
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Sneddon, Robert, William Rodman Shankle, Junko Hara, Anthony Rodriquez, Donald Hoffman, and Utpal Saha. "EEG Detection of Early Alzheimer's Disease Using Psychophysical Tasks." Clinical EEG and Neuroscience 36, no. 3 (July 2005): 141–50. http://dx.doi.org/10.1177/155005940503600304.
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In this study, we hypothesized that a quantitative EEG (qEEG) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment (MCI) or mild dementia due to Alzheimer's Disease and Related Disorders (ADRD). The cross-sectional sample consisted of 48 subjects (32 normal aging and 16 ADRD: n=3 mild dementia, n=13 MCI FAST stage 3). During EEG recording, subjects performed two visual, delayed recognition memory tasks as well as a task that tested their ability to perceive structure-from-motion (SFM). These EEG data were used to compute qEEG measures of the (normalized) variance of posterior cortical activity during the first 150 milliseconds (ms) after stimulus onset and the variance of anterior cortical activity during the second 150 ms epoch. The ratio, anterior/posterior cerebral qEEG value, was then computed for each subject, and the optimal cutoff value identified to discriminate normal from impaired subjects. An optimal qEEG cutoff value for the delayed recognition memory tasks correctly discriminated 30 of the 32 normal aging subjects (94% specificity) and 14 of 16 MCI-to-mild ADRD subjects (88% sensitivity). On the other hand, the application of this qEEG measure to EEG data recorded while subjects performed a SFM task did not distinguish between ADRD and normal aging any better than chance. In conclusion, this qEEG measure is specific to the psychophysical task being performed by the subject. When it was combined with delayed recognition memory tasks, it yielded results that are comparable to the accuracies reported by PET scan studies of normal aging vs. AD with mild cognitive impairment. These results warrant further evaluation.
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Favorskaya, M., D. Novikov, and Y. Savitskaya. "HUMAN ACTION POSELETS ESTIMATION VIA COLOR G-SURF IN STILL IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-5/W6 (May 18, 2015): 51–58. http://dx.doi.org/10.5194/isprsarchives-xl-5-w6-51-2015.
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Human activity is a persistent subject of interest in the last decade. On the one hand, video sequences provide a huge volume of motion information in order to recognize the human active actions. On the other hand, the spatial information about static human poses is valuable for human action recognition. Poselets were introduced as latent variables representing a configuration for mutual locations of body parts and allowing different views of description. In current research, some modifications of Speeded-Up Robust Features (SURF) invariant to affine geometrical transforms and illumination changes were tested. First, a grid of rectangles is imposed on object of interest in a still image. Second, sparse descriptor based on Gauge-SURF (G-SURF) invariant to color/lighting changes is constructed for each rectangle separately. A common Spatial POselet Descriptor (SPOD) aggregates the SPODs of rectangles with following random forest classification in order to receive fast classification results. The proposed approach was tested on samples from PASCAL Visual Object Classes (VOC) Dataset and Challenge 2010 providing accuracy 61-68% for all possible 3D poses locations and 82-86% for front poses locations regarding to nine action categories.
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Komańda, Marcin. "Was it Doomsday? First Wave of the COVID-19 Pandemic Impact on the Polish Cultural Industry." Economics and Culture 19, no. 1 (June 1, 2022): 98–107. http://dx.doi.org/10.2478/jec-2022-0009.
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Abstract Research purpose. The COVID-19 pandemic has become a theme of the research on the functioning of the economy and particular industries. The same concerns were raised regarding the issue of the cultural industry. Therefore, the content of this paper was dictated by the recognition of the impact of the first wave of the Covid-19 pandemic on the activities of the cultural industry in Poland. The formulated research question reads: “How did the beginning of the Covid-19 pandemic impact the economic standing of the Polish cultural industry?” Design / Methodology / Approach. The conducted literature review, whose purpose was to recognise the threads of the scientific discourse on the pandemic and cultural industry together with the cultural issues of business activity in a broad sense, was based on the use of the VOSviewer software, based on the data obtained from the Web of Science Core Collection. This concerned publications from January 1, 2020, to April 4, 2022. The part of the paper that leads to answering the research question uses the inductive method. It is based on the analysis of the quantitative data and information obtained from Statistics Poland (GłównyUrządStatystyczny), research reports as well as media releases. Findings. It was determined that in the first year of the pandemic, the number of cultural events, as well as the number of their participants, drastically decreased. There was also a change in the structure and value of expenditures of the citizens of Poland. This caused a drastic fall in revenues from the activity conducted by cultural institutions at the beginning of 2020. The situation improved after the disbursement of the government aid. However, even one year after the first lockdown, the increased debt of the art industry can be pointed out. Originality / Value / Practical implications. Determining in a broad way the impact of the first wave of the pandemic on the cultural industry in Poland concerning the economic standing is a novel approach. The previous studies focused on the situation of particular types of cultural institutions and possibly on the people associated with them. Due to its specificity, the conducted research also makes it possible to identify potential research problems relating to this industry. On the one hand, these potential studies are in line with the research threads represented in world literature. On the other hand, they concerned the specificity of the Polish cultural industry.
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Czarnecki, D., D. Skalski, and I. Grygus. "Free time of elderly people in terms of physical activity." Quality in Sport 8, no. 4 (November 28, 2022): 33–38. http://dx.doi.org/10.12775/qs.2022.08.04.003.
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Gerontological issues will gain more and more recognition, both in the social and medical aspect. The reason for this is the sharp increase in the percentage of the elderly population, which is related to a decline in birth rates on the one hand and an increase in life expectancy on the other. The aging of the population of Europe and Poland is probably the most important health and socio-political challenge in the coming years. In 2050, people aged 60-79 are expected to make up a quarter of the entire population of the European Union. Maintaining the appropriate level of health, independence and independence of the elderly becomes a great challenge. This is not only a public health challenge, but also a huge socio-economic problem. A typical situation in old age is the occurrence of several diseases at the same time. In addition, the situation is complicated by the procedure of a number of degenerative changes affecting almost all systems and functions of the system, deteriorating the possibility of functioning and rehabilitation. Taking up issues related to seniors becomes important for at least several reasons. The most important ones include: the increasing number of elderly people, the widespread cult of a financially efficient and independent person (completely different from the geriatric reality), the need to educate professionals to help or support those in need, and the need for mental changes in society regarding the aging process and old age itself. The aim of this article is to present the problem of leisure time of elderly people from the perspective of physical activity. The starting point for the considerations was the explanation of the concepts of "old age" and "aging". Next, the most important issues concerning human activity in late adulthood are presented and the main assumptions of the theory of activity are presented. Then the concept of free time was defined, the features of free time activity were discussed, and the functions of free time were also indicated. Attention was also paid to the structure of seniors' time budget and the types of free-time activity that dominate among them. Next, the problem of free time of old people is presented in the context of the theory of activity, paying particular attention to the issues related to the activation of seniors.
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Szamosi, Szilvia, László Váróczy, and Zoltán Szekanecz. "Immunmoduláló antitestek alkalmazása – az onkológia új fejezete." Orvosi Hetilap 157, Supplement 2 (June 2016): 9–16. http://dx.doi.org/10.1556/oh.2016.30507.
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In the past decade major advances in tumor immunology, a better understanding of antigen recognition by T-cells likewise discovering the regulatory inhibitory signals resulted in the development of new immunotherapies with promising durable responses in various solid tumor types and in hematologic malignancies. This review focuses on immunomodulatory antibodies, namely immune checkpoint inhibitor therapy. The prototype of this new class of immune stimulating agents was cytotoxic T-lymphocyte antigen-4 (CTLA-4) antagonists. After demonstrating enhanced survival, ipilimumab was approved first in the United States in 2011, further on in the European Union for second-line (2011) and for first-line therapy (2013) of metastatic melanoma. Additional T-cell intrinsic pathways were identified and targeted for clinical development. Antibodies blocking the PD-1 pathway also showed promising clinical activity and objective tumor response in several types of tumors, including metastatic melanoma, non-small- cell lung cancer. On the other hand antitumor activity is frequently accompanied by significant reversible immune-related adverse events. To explore potential new immune checkpoint targets bring forth several challanges. Future clinical development will involve identifying potential biomarkers anticipating responsiveness to pathway blockade and additional tumor types likely to respond to the therapy. Furthermore, combination strategies, immune checkpoint inhibitors combined with cancer vaccines, targeted inhibitors and traditional chemotherapies are being evaluated in pre-clinical studies. Orv. Hetil., 2016, 157(Suppl. 2), 9–16.
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Guenard, Daniel, Francoise Gueritte-Voegelein, and Francois Lavelle. "Taxoids: A New Class of Antimitotic Compounds." Current Pharmaceutical Design 1, no. 1 (June 1995): 95–112. http://dx.doi.org/10.2174/1381612801666220524192845.
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Paclitaxel (Taxol®) and docetaxel (Taxotere®) are the first representatives of taxoids , a new class of antitumor compounds. These two taxoids are clinically active against breast, ovarian and lung cancers. Taxoids are highly complex diterpenoids from natural origin. Preclinical and clinical develop-ments have been made possible after a long and sustained chemical effort : paclitaxel is extracted from the barks of the Pacific yew tree Taxus brevifolia whereas docetaxel is prepared by hemisynthesis starting from 10-deacetyl-baccatin ill, a non cytotoxic precursor found in the needles of the European yew tree Taxus baccata . These two drugs are active in various in vitro and in vivo preclinical models (cell lines, cloning of human tumor stem cells, murine grafted tumors , human xenografts). Taxoids constitute anew class of antimitotic agents different from vinca-alkaloids: on the one hand, paclitaxel and docetaxel can be considered as inhibitors of the reaction of depolymerization of microtubules into tubulin ; on the other hand, vinca-a!kaloids inhibit the reaction of polymerization of tubulin into microtubules. An active program of medicinal chemistry is done in various pharmaceutical and academic Institutions with two objectives: knowledge of structure-activity relationships and selection of new candidates for clinical trials. With the taxoid series, a variety of analogs have been prepared for their antitubulin and biological properties . Concerning the tubulin binding, some important structure activity relationships have been proposed. In this review the contribution of each functional group of docetaxel will be discussed following the evolution of antitubulin activity, going from docetaxel to taxoids possessing the minimum requirement of recognition by tubulin . The conformation of docetaxel and analogs will be compared taking into account the contribution and relevance of X-rays, NMR and molecular modelling studies in determining the molecular shape of active and inactive compounds.
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Polishchuk, Olena. "The problem of high school students’ profession choice: theoretical discourse." Scientific bulletin of South Ukrainian National Pedagogical University named after K. D. Ushynsky 2020, no. 4 (133) (December 24, 2020): 117–27. http://dx.doi.org/10.24195/2617-6688-2020-4-15.
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The problem of readiness for profession choice in the process of profession-related self-determination of high school students in Ukraine is quite relevant. The real situation requires a person to constantly choose life goals and means to achieve them. The current situation in society requires the simultaneous manifestation of two functions: individual psychological characteristics, social lability, flexibility on the one hand; and on the other hand, the development of person’s identity, which forms an inner "core", which is an indicator of readiness for profession choice. In this regard, social and psychological support is needed to form the readiness of high school students to make a conscious choice of profession. In recent years, there has been a reassessment of the "prestige" of professions, as well as socio-economic changes in the country have increased the concern of young people: "What to be?". Practice shows that a certain percentage of graduates still does not see a bright life path, does not imagine their professional career, cannot adequately assess their professional prospects. This is due to the fact that high school students do not have sufficient information about the needs of the labour market, do not know how to consider the socio-economic conditions that determine the type and nature of profession-n related activity; they have no idea about the nature of work. Most young people strive to achieve the desired way of life, to obtain some professional recognition; however, specific professional activities are not considered by them as part of the future way of life. The purpose of the article is a theoretical analysis of the scientific problem of high school students’ profession choice. Research methods: analysis of psychological and pedagogical literature; comparative-historical method of foreign and domestic experience in forming socio-psychological readiness of high school students to join the Free Economic Zone. The analysis of the psychological and pedagogical literature shows that the study of the problem regarding profession choice considers this process as purposeful, which consists of motivating and appropriately structured actions.
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Abebe, Girmaw, and Andrea Cavallaro. "Hierarchical modeling for first-person vision activity recognition." Neurocomputing 267 (December 2017): 362–77. http://dx.doi.org/10.1016/j.neucom.2017.06.015.
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Zwerenz, Dirk. "Performance Incentives To Increase Motivation; Potentials Of Meaningful Activities In Project Management." SocioEconomic Challenges 4, no. 4 (2020): 95–118. http://dx.doi.org/10.21272/sec.4(4).95-118.2020.
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Authors: Dirk Zwerenz, ORCID: https://orcid.org/0000-0001-8677-6050 PhD Candidate, University Kaposvár, Hungary; Head of Major Project Service, German Doka formwork technology GmbH, Maisach, Germany Pages: 95-118 Language: English DOI: https://doi.org/10.21272/sec.4(4).95-118.2020 Download: Views: Downloads: 57 31 Abstract Performance incentives to increase motivation; potentials for meaningful activities in project management, the author will concretize this with meaningful activities in project management. The ideal project leader is described by Mark Twain in his novel “The Adventures of Tom Sawyer” (Twain, 1876) in the episode of Tom Sawyer painting the fence. Tom is able to motivate his friends for the actually boring activity in a way that they are willing to support him voluntarily. Regarding the law of human action discovered by Tom Sawyer, Mark Twain states: “To awaken a person’s desire, all that is needed is to make the object difficult to reach” (Twain, 1876). In 2006 Ariely, Loewenstein and Prelec examined the rules of irrational action described by Twain. They conclude that individuals make decisions based on their intrinsic motivation and sometimes not on “what is reasonable” (Ariely, Loewenstein, & Prelec, 2006). This enthusiasm of a project leader is transformed in this article and is reflected as a component “project brand strength” in the performance assessment of a project leader (Zwerenz, 2019). The author’s experience as a project leader in the implementation of several major projects also takes up this enthusiasm and expands it to include the identification of the project teams with themselves and the aspect of meaningful activities as an incentive in project management. That identification and motivation are on the one hand necessary to enjoy one’s profession seems understandable, on the other hand the boundaries between vocation and exhaustion are quickly crossed. Schmalenbach describes this in the article “Sacrifice of passion” in “DIE ZEIT”, issue 2-2019 with the provocative sentence “If you break down, you are a better person”. Committed project managers develop a very similar passion for “their” project and thus a comparable identification with their profession. The tension between income, recognition and prosperity is discussed. Furthermore, the dependencies of meaningfulness, recognition and income are derived from the literature and presented as factors influencing personal well-being. Finally, this article contributes to the design of a motivating variable remuneration system for project managers and other exposed occupational groups. Keywords: variable compensation, value management, development of individual competences, knowledge management, team management, management of individuals – development, motivation and reward, leadership, management of stakeholders, management of human resources, engineering and construction, research theory on project management.
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Rimmer, Mark. "Can You Hear Me Now? Musical Values, Education and ‘Voice’." Media International Australia 148, no. 1 (August 2013): 135–44. http://dx.doi.org/10.1177/1329878x1314800115.
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This article addresses a number of questions concerning the use of music by young people. In particular, the argument presented seeks to bring to the fore a set of concerns whose significance is often overlooked or downplayed in debates about young people's engagements with music. These relate to music's capacity to function, on the one hand, in a way that reflects and embodies ethical and ideological commitments of varying kinds and, on the other, as a vehicle of expression through which people might ‘give an account’ of themselves. The article first surveys some of the ways in which scholars have conceived of the relation between forms of musical activity and their broader social force before turning to recent research and policy developments concerned with school-based music education in Britain and considering the ways in which certain forms and dimensions of young people's expressive musical activity are granted legitimacy and state support while others are ignored or marginalised. The final part of the article reflects upon the foregoing discussion and introduces the concepts of ‘voice’ (Couldry, 2010) and ‘recognition’ (Honneth, 1995), to consider how the promotion of some musical values to the detriment of others has important implications for the ways in which young people understand the extent to which their claims – and not just cultural ones – are taken seriously within society.
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Ryoo, M. S., and Larry Matthies. "First-Person Activity Recognition: Feature, Temporal Structure, and Prediction." International Journal of Computer Vision 119, no. 3 (August 2, 2015): 307–28. http://dx.doi.org/10.1007/s11263-015-0847-4.
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Maszczyńska, Dominika. "Nannette and Johann Andreas Streicher - their role in shaping musical life in Vienna in the early 19th century." Notes Muzyczny 1, no. 13 (June 9, 2020): 49–80. http://dx.doi.org/10.5604/01.3001.0014.1937.
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Nannette and Andreas Streicher were important figures in the musical life of Vienna in the early 19th century. The article introduces their profiles, describes the history of their company, their social, cultural and teaching activity as well as different types of artistic activity. It also explains how keyboard instruments shaped sound and aesthetics-related piano ideals at the turn of the 19th century. The versatile activity of the Streichers, which first of all included instrument building, piano play- ing, composition, teaching and organisation of musical life, made a great contribution to Europe’s cultural heritage. We can notice their numerous connections with outstanding figures of musical life of that time, one that deserves particular attention is their acquaintance with Beethoven. Nannette Streicher was an extremely talented builder who not only coped with the typically masculine craft at that time, but she was also significantly successful in that field. Her instruments were popular, earning general recognition, and the innovative solutions introduced by her also influenced the work of other builders and further development of the piano. Their marriage became the basis for a very fruitful cooperation. Andreas’s numerous connections and his familiarity with the community became an important part of the activity of the company and contributed to its development. Nannette and Andreas shared their passion and passed it on to their son Johann Baptist, who successfully continued their piano making tradition and introduced further improvements, earning a great reputation as well. Social, cultural and teaching activities of the Streichers also played an important role in the musical life of Vienna. Andreas Streicher taught his students the secrets of piano technique and apart from that he shaped their musical and aesthetical awareness. His Kurze Bemerkungen are a valuable source of knowledge also for modern-time performers who can – thanks to this text – learn more about the piano playing aesthetics at the turn of the 19th century as well as a number of universal music and performance topics, which remain accurate to this day. Concerts organised in their house had an educational function too, on the one hand they shaped the tastes of music lovers and supported composers, allowing them to present their latest pieces, and on the other hand they contributed to the promotion of young performers for whom concerts there were often the first step leading towards Vienna’s professional musical stage. The development of the topic of the article in this issue of “Notes Muzyczny” is the trans- lation of the text by Andreas Streicher entitled: Some observations on the playing, tuning and maintenance of pianos built in Vienna by Nannette Streicher nee Stein.
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Elola, Andoni, Elisabete Aramendi, Unai Irusta, Artzai Picón, Erik Alonso, Pamela Owens, and Ahamed Idris. "Deep Neural Networks for ECG-Based Pulse Detection during Out-of-Hospital Cardiac Arrest." Entropy 21, no. 3 (March 21, 2019): 305. http://dx.doi.org/10.3390/e21030305.
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The automatic detection of pulse during out-of-hospital cardiac arrest (OHCA) is necessary for the early recognition of the arrest and the detection of return of spontaneous circulation (end of the arrest). The only signal available in every single defibrillator and valid for the detection of pulse is the electrocardiogram (ECG). In this study we propose two deep neural network (DNN) architectures to detect pulse using short ECG segments (5 s), i.e., to classify the rhythm into pulseless electrical activity (PEA) or pulse-generating rhythm (PR). A total of 3914 5-s ECG segments, 2372 PR and 1542 PEA, were extracted from 279 OHCA episodes. Data were partitioned patient-wise into training (80%) and test (20%) sets. The first DNN architecture was a fully convolutional neural network, and the second architecture added a recurrent layer to learn temporal dependencies. Both DNN architectures were tuned using Bayesian optimization, and the results for the test set were compared to state-of-the art PR/PEA discrimination algorithms based on machine learning and hand crafted features. The PR/PEA classifiers were evaluated in terms of sensitivity (Se) for PR, specificity (Sp) for PEA, and the balanced accuracy (BAC), the average of Se and Sp. The Se/Sp/BAC of the DNN architectures were 94.1%/92.9%/93.5% for the first one, and 95.5%/91.6%/93.5% for the second one. Both architectures improved the performance of state of the art methods by more than 1.5 points in BAC.
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Brzezinski, Krzysztof. "S-adenosyl-l-homocysteine Hydrolase: A Structural Perspective on the Enzyme with Two Rossmann-Fold Domains." Biomolecules 10, no. 12 (December 16, 2020): 1682. http://dx.doi.org/10.3390/biom10121682.
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S-adenosyl-l-homocysteine hydrolase (SAHase) is a major regulator of cellular methylation reactions that occur in eukaryotic and prokaryotic organisms. SAHase activity is also a significant source of l-homocysteine and adenosine, two compounds involved in numerous vital, as well as pathological processes. Therefore, apart from cellular methylation, the enzyme may also influence other processes important for the physiology of particular organisms. Herein, presented is the structural characterization and comparison of SAHases of eukaryotic and prokaryotic origin, with an emphasis on the two principal domains of SAHase subunit based on the Rossmann motif. The first domain is involved in the binding of a substrate, e.g., S-adenosyl-l-homocysteine or adenosine and the second domain binds the NAD+ cofactor. Despite their structural similarity, the molecular interactions between an adenosine-based ligand molecule and macromolecular environment are different in each domain. As a consequence, significant differences in the conformation of d-ribofuranose rings of nucleoside and nucleotide ligands, especially those attached to adenosine moiety, are observed. On the other hand, the chemical nature of adenine ring recognition, as well as an orientation of the adenine ring around the N-glycosidic bond are of high similarity for the ligands bound in the substrate- and cofactor-binding domains.
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Klymenko, Oleksiy, Viktor Ustymenko, Konstantin Kolobov, Sergey Rychok, Mykolay Gora, and Nila Naumenko. "ANALYSIS OF THE STUDIES RESULTS OF EMISSIONS OF POLLUTANTS BY USED CARS IMPORTED INTO UKRAINE FROM THE USA." Avtoshliakhovyk Ukrayiny, no. 1 (257)’ 2019 (March 29, 2019): 2–11. http://dx.doi.org/10.33868/0365-8392-2019-1-257-2-11.
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It`s given an analysis of the distribution of wheeled vehicles regarding values of mass specific emissions of pollutants obtained from the results of tests in the European driving cycle (NEDC) the group of 1109 used (second-hand) vehicles of category M1 of various brands (equipped with gasoline engines, which at the time of production were in accordance with federal environmental requirements of the USA), and imported into Ukraine from North America. The analysis included in particular distribution of pollutants specific mass emission vs. total mileage of 3 main vehicle`s brands of tested group consisted mainly of VW, Mazda and Ford. It`s also included statistical frequency distribution of whole tested group and for aforementioned brands individually in comparison with EU (“Euro-5”) and US (T2B5) emission limits, used for type approval and as OBD thresholds, including Ukrainian limits used for second-hand vehicles that does not approved in accordance to EU legislation or within the 1958 Agreement concerning the Adoption of Uniform Conditions of Approval and Reciprocal Recognition of Approval for Motor Vehicle Equipment and Parts. The analysis gives opportunity of comparison of established in tested group of one of the key European, Japan and US manufacturers of passenger vehicles regarding its emission values distribution based on NEDC test procedure results. It`s given the rationale for amending the current procedure for assessing conformity of this category of vehicles (“Approval of the design of vehicles, their parts and equipment”, approved by order of the Ministry of Infrastructure of Ukraine No. 521 dated 17/08/2012), taking into account cancellation at the end of 2018 (according to the Law of Ukraine No. 2612-VIII dated 11/08/2018) of "Euro-5" standards as the minimum requirements for the first registration in Ukraine of used (second-hand) vehicles of heading 8703 of the Ukrainian classification of goods of foreign economic activity. Keywords: wheeled vehicles, passenger cars, emission of pollutants, regulation, setting of norms, certification, import of vehicles from the USA.
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Kahani, Reza, Alireza Talebpour, and Ahmad Mahmoudi-Aznaveh. "A correlation based feature representation for first-person activity recognition." Multimedia Tools and Applications 78, no. 15 (March 30, 2019): 21673–94. http://dx.doi.org/10.1007/s11042-019-7429-3.
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Samofalov, L. P., and О. L. Samofalov. "Сoncepts and elements of judicial enforcement." ScientifiScientific Herald of Sivershchyna. Series: Law 2021, no. 2 (October 5, 2021): 33–45. http://dx.doi.org/10.32755/sjlaw.2021.02.033.
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The problems of judicial enforcement are considered in the article. It is emphasized that judicial enforcement is a legal form of state functions implementation. The need to study this legal category is emphasized. This need is related to the harmonization of legislation with international standards, judicial reform, and increased protection of human rights. Different points of view of legal scholars concerning judicial enforcement are investigated. It is concluded that the judicial application of the law is based on the rules of positive law. A judge may not refuse to hear a case due to gaps in the law. Judicial enforcement is associated not only with the application of the law, but also with their interpretation, and sometimes lawmaking. On the one hand, the judiciary is a manifestation of power, and on the other it is the most rational and effective form of control over the activities of state power. It is stated in the article that justice, as a court activity carried out in the form of civil, administrative, criminal, economic and constitutional proceedings, takes place in the procedural forms established by law. Law enforcement activity of the court is a long, complex and systematic process. It has a specific purpose, that is a clearly defined value, which includes recognition of a person, their life, health, honor and dignity, inviolability and security. It is stated that law enforcement cannot be carried out beyond the principles of law, as they go through all the rules of law and are the basis of the legal system. The components of the rule of law are recognized by the international community. In particular, they are: – the right to appeal against the actions of public authorities; – free assessment by the court of the circumstances of the case; – independence and impartiality of judges; – independent judicial procedure, which covers fairness, openness, reasonable time for consideration of the case, availability of legal aid; – binding nature of court decisions. In order to ensure the proper judicial system functioning, it is proposed to amend the current legislation in the process of judicial reform. The conclusions to the article stipulate that the court performs both law enforcement and law-making functions. The essence of the administration of justice and judicial activity is reduced to the application of law. In the process of administering justice, the judiciary acts in clearly defined procedural forms. Judicial power, as a subject of constitutional regulation, is exercised precisely in justice, and justice is administered and administered by the court through judicial enforcement. Key words: judicial enforcement, justice, judicial activity, judicial power, judicial proceedings, judicial lawmaking.
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Renard, Yann, Fabien Lotte, Guillaume Gibert, Marco Congedo, Emmanuel Maby, Vincent Delannoy, Olivier Bertrand, and Anatole Lécuyer. "OpenViBE: An Open-Source Software Platform to Design, Test, and Use Brain–Computer Interfaces in Real and Virtual Environments." Presence: Teleoperators and Virtual Environments 19, no. 1 (February 1, 2010): 35–53. http://dx.doi.org/10.1162/pres.19.1.35.
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This paper describes the OpenViBE software platform which enables researchers to design, test, and use brain–computer interfaces (BCIs). BCIs are communication systems that enable users to send commands to computers solely by means of brain activity. BCIs are gaining interest among the virtual reality (VR) community since they have appeared as promising interaction devices for virtual environments (VEs). The key features of the platform are (1) high modularity, (2) embedded tools for visualization and feedback based on VR and 3D displays, (3) BCI design made available to non-programmers thanks to visual programming, and (4) various tools offered to the different types of users. The platform features are illustrated in this paper with two entertaining VR applications based on a BCI. In the first one, users can move a virtual ball by imagining hand movements, while in the second one, they can control a virtual spaceship using real or imagined foot movements. Online experiments with these applications together with the evaluation of the platform computational performances showed its suitability for the design of VR applications controlled with a BCI. OpenViBE is a free software distributed under an open-source license.
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Gent and Muhammad. "Memorising and Reciting a Text without Understanding Its Meaning: A Multi-Faceted Consideration of this Practice with Particular Reference to the Qur’an." Religions 10, no. 7 (July 11, 2019): 425. http://dx.doi.org/10.3390/rel10070425.
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The joint activities of memorising and reciting the Arabic Qur’an are deeply embedded within Islamic tradition, culture and educational practice. Despite this, for many western non-Muslims, particularly those engaged in educational activity themselves, to learn that memorisation of the Arabic text of the Qur’an does not always—or, indeed, often—go hand-in-hand with understanding the meaning of the words can come as both a surprise and a shock. It is not uncommon to hear a response from such people to the effect that to memorise texts without understanding their meaning is pointless. There is also sometimes the implication that such practice in anachronistic: ‘behind the times’, as it were, and thus not worthy of serious consideration. This article is framed as a ‘general’ riposte to such a dismissive response in that its motivation lies not in straightforward apologetics (that is, defending the practice of memorisation without qualification and at all costs), but, rather, in bringing together a number of key elements (or factors) that cumulatively carry sufficient weight to challenge such a raw response, or at least to give pause for thought and promote a more informed consideration. Following a brief introduction that locates Qur’an memorisation and recitation within Islamic faith and practice, five facets will be explored: first, the growing recognition that there is not just one legitimate form of literacy but, rather, a plurality of literacies; second, the ambiguity within the concept of ‘meaning’ itself; third, an acknowledgement that memorisation has not only held an esteemed place in western history, but remains valued in some aspects of contemporary life and culture; fourth, a recognition of the emotional power of high-quality recitation, irrespective of a literal comprehension of the words being recited; and, finally, the growing body of research evidence that suggests that the involvement of Muslim children and young people in Qur’anic memorisation and recitation might very well equip them with valuable social and educational capital. The article will end with a brief personal account showing the complex position that a contemporary British Muslim ‘insider’—as individual, teacher and parent—has adopted towards his own and others’ practice of memorising the Qur’an. This account has been included to show that, within the Muslim community itself, different opinions are held about the weight and meaning to be placed on memorisation in general and on Qur’anic memorisation and recitation in particular.
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Jeon, Moon-Jin, Sang Wan Lee, and Zeungnam Bien. "Hand Gesture Recognition Using Multivariate Fuzzy Decision Tree and User Adaptation." International Journal of Fuzzy System Applications 1, no. 3 (July 2011): 15–31. http://dx.doi.org/10.4018/ijfsa.2011070102.
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As an emerging human-computer interaction (HCI) technology, recognition of human hand gesture is considered a very powerful means for human intention reading. To construct a system with a reliable and robust hand gesture recognition algorithm, it is necessary to resolve several major difficulties of hand gesture recognition, such as inter-person variation, intra-person variation, and false positive error caused by meaningless hand gestures. This paper proposes a learning algorithm and also a classification technique, based on multivariate fuzzy decision tree (MFDT). Efficient control of a fuzzified decision boundary in the MFDT leads to reduction of intra-person variation, while proper selection of a user dependent (UD) recognition model contributes to minimization of inter-person variation. The proposed method is tested first by using two benchmark data sets in UCI Machine Learning Repository and then by a hand gesture data set obtained from 10 people for 15 days. The experimental results show a discernibly enhanced classification performance as well as user adaptation capability of the proposed algorithm.
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Noreen, Iram, Muhammad Hamid, Uzma Akram, Saadia Malik, and Muhammad Saleem. "Hand Pose Recognition Using Parallel Multi Stream CNN." Sensors 21, no. 24 (December 18, 2021): 8469. http://dx.doi.org/10.3390/s21248469.
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Recently, several computer applications provided operating mode through pointing fingers, waving hands, and with body movement instead of a mouse, keyboard, audio, or touch input such as sign language recognition, robot control, games, appliances control, and smart surveillance. With the increase of hand-pose-based applications, new challenges in this domain have also emerged. Support vector machines and neural networks have been extensively used in this domain using conventional RGB data, which are not very effective for adequate performance. Recently, depth data have become popular due to better understating of posture attributes. In this study, a multiple parallel stream 2D CNN (two-dimensional convolution neural network) model is proposed to recognize the hand postures. The proposed model comprises multiple steps and layers to detect hand poses from image maps obtained from depth data. The hyper parameters of the proposed model are tuned through experimental analysis. Three publicly available benchmark datasets: Kaggle, First Person, and Dexter, are used independently to train and test the proposed approach. The accuracy of the proposed method is 99.99%, 99.48%, and 98% using the Kaggle hand posture dataset, First Person hand posture dataset, and Dexter dataset, respectively. Further, the results obtained for F1 and AUC scores are also near-optimal. Comparative analysis with state-of-the-art shows that the proposed model outperforms the previous methods.
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Abebe, Girmaw, Andrea Cavallaro, and Xavier Parra. "Robust multi-dimensional motion features for first-person vision activity recognition." Computer Vision and Image Understanding 149 (August 2016): 229–48. http://dx.doi.org/10.1016/j.cviu.2015.10.015.
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Zapata-Lamana, Rafael, Jaume F. Lalanza, Josep-Maria Losilla, Eva Parrado, and Lluis Capdevila. "mHealth technology for ecological momentary assessment in physical activity research: a systematic review." PeerJ 8 (March 26, 2020): e8848. http://dx.doi.org/10.7717/peerj.8848.
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Objective To systematically review the publications on ecological momentary assessment (EMA) relating to physical activity (PA) behavior in order to classify the methodologies, and to identify the main mHealth technology-based tools and procedures that have been applied during the first 10 years since the emergence of smartphones. As a result of this review, we want to ask if there is enough evidence to propose the use of the term “mEMA” (mobile-based EMA). Design A systematic review according to PRISMA Statement (PROSPERO registration: CRD42018088136). Method Four databases (PsycINFO, CINALH, Medline and Web of Science Core Collection) were searched electronically from 2008 to February 2018. Results A total of 76 studies from 297 potential articles on the use of EMA and PA were included in this review. It was found that 71% of studies specifically used “EMA” for assessing PA behaviors but the rest used other terminology that also adjusted to the inclusion criteria. Just over half (51.3%) of studies (39) used mHealth technology, mainly smartphones, for collecting EMA data. The majority (79.5%) of these studies (31 out of 39) were published during the last 4 years. On the other hand, 58.8% of studies that only used paper-and-pencil were published during the first 3 years of the 10-year period analyzed. An accelerometer was the main built-in sensor used for collecting PA behavior by means of mHealth (69%). Most of the studies were carried out on young-adult samples, with only three studies in older adults. Women were included in 60% of studies, and healthy people in 82%. The studies lasted between 1 and 7 days in 57.9%, and between three and seven assessments per day were carried out in 37%. The most popular topics evaluated together with PA were psychological state and social and environmental context. Conclusions We have classified the EMA methodologies used for assessing PA behaviors. A total of 71% of studies used the term “EMA” and 51.3% used mHealth technology. Accelerometers have been the main built-in sensor used for collecting PA. The change of trend in the use of tools for EMA in PA coincides with the technological advances of the last decade due to the emergence of smartphones and mHealth technology. There is enough evidence to use the term mEMA when mHealth technology is being used for monitoring real-time lifestyle behaviors in natural situations. We define mEMA as the use of mobile computing and communication technologies for the EMA of health and lifestyle behaviors. It is clear that the use of mHealth is increasing, but there is still a lot to be gained from taking advantage of all the capabilities of this technology in order to apply EMA to PA behavior. Thus, mEMA methodology can help in the monitoring of healthy lifestyles under both subjective and objective perspectives. The tendency for future research should be the automatic recognition of the PA of the user without interrupting their behavior. The ecological information could be completed with voice messages, image captures or brief text selections on the touch screen made in real time, all managed through smartphone apps. This methodology could be extended when EMA combined with mHealth are used to evaluate other lifestyle behaviors.
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Dimiccoli, Mariella, and Petia Radeva. "Visual Lifelogging in the Era of Outstanding Digitization." Digital Presentation and Preservation of Cultural and Scientific Heritage 5 (September 30, 2015): 59–64. http://dx.doi.org/10.55630/dipp.2015.5.4.
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In this paper, we give an overview on the emerging trend of the digitized self, focusing on visual lifelogging through wearable cameras. This is about continuously recording our life from a first-person view by wearing a camera that passively captures images. On one hand, visual lifelogging has opened the door to a large number of applications, including health. On the other, it has also boosted new challenges in the field of data analysis as well as new ethical concerns. While currently increasing efforts are being devoted to exploit lifelogging data for the improvement of personal well-being, we believe there are still many interesting applications to explore, ranging from tourism to the digitization of human behavior. 1 Introduction We are already living in the world, where digitization affects our daily lives and socio-economic models thoroughly, from education and art to the industry. In essence, digitization is about implementing new ways to put together physical and digital resources for creating more competitive models. Recently, lifelogging appeared just as another powerful manifestation of this digitization process embraced by people at different extents. Lifelogging refers to the process of automatically, passively and digitally recording our own daily experience, hence, connecting digital resource and daily life for a variety of purposes. In the last century, there has been a small number of dedicated individuals, who actively tried to log their lives. Today, thanks to the advancements in sensing technology and the significant reduction of computer storage cost, one’s personal daily life can be recorded efficiently, discretely and in hand-free fashion (see Fig. 1). The most common way of lifelogging, commonly called visual lifelogging, is through a wearable camera that captures images at a reduced framerate, ranging from 2 fpm of the Narrative Clip to 35 fps of the GoPro. The first commercially available wearable camera, called SenseCam, was presented by Microsoft in 2005 and during the last decade, it has been largely deployed in health research. As summarized in a collection of studies published in a special theme issue of the American Journal of Preventive Medicine [5], information collected by a wearable camera over long periods of time has large number of potential applications, both at individual and population level. At individual level, lifelogging can aid in contrast dementia by cognitive training based on digital memories or in improving well-being by monitoring lifestyle. At population level, lifelogging could be used as an objective tool for 60 understanding and tracking lifestyle behavior, hence enabling a better understanding of the causal relations between noncommunicable diseases and unhealthy trends and risky profiles (such as obesity, depression, etc.) Fig. 1. Evolution of wearable camera technology. From left to right: Mann (1998), GoPro (2002), SenseCam (2005), Narrative Clip (2013). However, the huge potential of these applications is currently strongly limited by technical challenges and ethical concerns. The large amount of data generated, the high variability of object appearance and the free motion of the camera, are some of the difficulties to be handled for mining information from and for managing lifelogging data. On the other hand, legality and social acceptance are the major ethical challenges to be faced. This paper discusses these issues and it is organized as follows: in the next section, we give an overview of potential applications; in section 3, we analyze technical challenges and current solutions. Section 4 is devoted to ethical issues and, finally, in section 5, we draw some conclusions. 2 Potential Applications Humans have always been interested in recording their life experiences for future reference and for storytelling purposes. Therefore, a natural application would be summarizing lifelog collections into a story that will be shared with other people, most likely through a social network. Since the end-users may have very different tastes, storytelling algorithms should incorporate some knowledge of the social context surrounding the photos, such as who the user and the target audience are. However, lifelogging technology allows capturing our entire life, not only those moments that we would like to share with others (see Fig. 2). This offers a great potential to make people aware of their lifestyle, understood as a pattern of behavioral choices that an individual makes in a period of time. This feedback could provide education and motivation to improve health trends, detecting risky profiles, with a personal trainer “in-the-loop”. Indeed, by providing a symbiosis between health professionals and wearable technology, it could be possible to design and implement individualized strategies for changing behavior. Considering that physical activity and poor diet are major risk factors for heart diseases, obesity and leading causes of premature mortality, this social impact of applications will be huge. On the other hand, lifelogging could be useful in monitoring patients affected by neurological disorders such as depression or bipolar disorder by aiding in predicting crisis. 61 Fig. 2. Images recorded by a Narrative Clip: From left to right and from the 1st to the 2nd row: in a bus, biking, attending a seminar, having lunch, in a market, in a shop, in the street, working. Finally, digital memories could be used as a tool for cognitive training for people affected by Mild Cognitive Impairment (MCI), a condition that represents a window for novel intervention tools against the Alzheimer disease. Although the emphasis nowadays is on the use of wearable cameras for health applications, its potential spreads to many other domains ranging from tourism to digitization of intangible heritage. For instance, data collected during a long trip could be used to make short and original photostreams for storytelling purposes and be shared in a network of visitors of a country. On the other hand, probably in the next century, these data would be useful for people interested in comparing how transportation and landscape have changed over time. During the last few decades, there has been an increasing interest in the use of digital media in the preservation, management, interpretation, and representation of cultural heritage. Intangible cultural heritage consists of nonphysical aspects of a particular culture, among which folklore, traditions, behavior. The intangible aspects of our cultural heritage represent a treasure of significant historical and socio-economic importance. Naturally, intangible cultural heritage is more difficult to preserve than physical objects. The digital documentation of intangible cultural heritage represents a huge market potential, which is largely unexplored. Wearable cameras could be used in this field to collect, preserve and make available digitally part of the intangible cultural heritage of the 21th century, such as human behavior. 62 3 Technical Challenges Wearing a camera over a long period of time generates a large amount of data (up to 70.000 images per month), making difficult the problem of retrieving specific information. Beside data organization, the high variability of object appearance in the real world and the free motion of the camera make state of the art object recognition algorithms to fail. In Fig. 3 are shown two sequences acquired by wearing a Narrative Clip (2fpm): one can appreciate the frequency of abrupt changes of the field of view even in temporally adjacent images that makes motion estimation unreliable and frequent occlusions that cause important drop in object recognition performances. Fig. 3. Example of photostreams captured by a Narrative CLip while (first row) biking and having a coffee (second row). As shown in [2], the interest of the computer vision community is rapidly increasing and this trend is expected to continue in the next years. Most available works have been conceived to analyze data captures by high temporal resolution wearable cameras, such as GoPro or Google Glasses and they can be broadly classified depending on the task, they try to solve in: activity-recognition [15, 11, 10, 13, 6], social interaction analysis [1, 3, 19], summarization [4, 16, 12]. Activity recognition usually relies on cues such ego-motion [15, 10], object-hand interaction [11, 10] or attention [13, 6]. Generally, the major difficult to be faced in the task of activity recognition are the large variability of objects and hands and the free motion of the camera that make it very difficult to estimate body movements and attention. Social interaction detection is based on the concept of F-formation that models orientation relationships of groups of people in space. F-formations require estimating pose and 3D-location of people, which are challenging tasks due the continuous changes of aspect ratio, scale and orientation. A common approach to summarization is to try to maximize the relevance of the selected images and minimize the redundancy. Relevancy can be captured by relying on mid-level or high-level features. Mid level features may be motion, global CNN features [4, 16], whereas high-level features may be important objects [12] or topics [18]. 63 4 Ethical Issues Lifelog technology can be considered still in its infancy and assuring that the related ethical issues receive full consideration at this moment is crucial for a responsible development of the field. In the last few years, a number of papers has tried to inquiry into the ethical aspects of lifelogs held by individuals [17, 7, 14], discussing issues to do with privacy, autonomy, and beneficence. Images captured by a wearable camera clearly impact the privacy of lifeloggers as well as of bystanders captured in such images. In [7], the authors identified various factors to make a photo sensitive and proposed to embed into the devices an algorithm that use these factors to automatically delete sensitive images. The most general meaning of autonomy is to be a law to oneself. The authors of [8] recognize that lifelogging offers a great opportunity towards autonomy, since it allows to better understand ourselves. Moreover, they provide recommendations and guidelines to meet the challenges that lifelogs poses towards autonomy. Beneficence concerns with the responsibility to do good by maximizing the benefits to an individual or to society, while minimizing harm to the individual. A critical component is informed consent that should be signed by participant to research projects or clinical projects. More general specifications for wearable camera research are provided in [9], proposing an ethical framework for health research. 5 Conclusions This paper has reviewed some of the most important aspects of visual lifelogging, focusing on the technical and ethical challenges it arises, and on its potential applications. We believe that a responsible development of the field could be highly beneficial for the society. In order to become widely used technology, a large amount of effort should be invested in the development of efficient information retrieval systems, to allow fast and easy access to lifelogging content at a semantic level. Further advances in the field of deep learning will allow filling this semantic gap. Acknowledgments This work was partially founded by TIN2012-38187-C03-01 and SGR 1219. M. Dimiccoli is supported by a Beatriu de Pinos grant (Marie-Curie COFUND action).
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Kosiewicz, Jerzy. "Western Sport and Spiritualism." Physical Culture and Sport. Studies and Research 62, no. 1 (June 1, 2014): 73–82. http://dx.doi.org/10.2478/pcssr-2014-0013.
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Abstract Sport activity of achievement-oriented (professional, Olympic, spectacular character) is first of all exposition of rivalry and striving for variously understood sports success (resulting from measurable or discretionary criteria). It refers to winning a competition or taking another expected place as well as to other forms of satisfaction, such as financial gratification or social (political, ethnic, professional) recognition. Spirituality is here neither an aim, nor an expected value - it constitutes rather an additional or redundant quality. A competitor focuses his/her attention first of all on the main aim assumed in planned or current rivalry. Emotional sensations which are experienced by athletes before, during or after competitions testify to mental and emotional stress which accompanies sports combat. It is also difficult to associate spirituality or spiritualism with sport for all - like, for example, that of health-oriented character - sport of the disabled, physical education, sport of playful character or physical recreation. That difficulty results from the fact that neither spiritualism, nor spirituality inspires for physical activity in the abovementioned fields; neither spiritualism, nor spirituality is the outcome of activity in the realm of sport for all. Exceptions are constituted by ancient Olympic Games as well as by some experiences connected with recreational forms of tourism mediated through achievement-oriented sport (also by pre-Columbian Native American societies and Maoris aboriginal population of New Zealand). For example Hellenic Olympic Games were a highly spiritualized form of sports rivalry - including also rivalry in the field of art, and especially in the field of theatre. They were one of numerous forms of religious cult - of worshipping chosen gods from the Olympic pantheon. On the other hand, during mountain hiking and mountain climbing there can appear manifestations of deepened spirituality characteristic for the object of spiritualization of non-religious, quasi-religious or strictly religious qualities. I would like to explain - at the end of this short abstract - that spiritualism (which should not be confused with spiritism) is - generally speaking - first of all a philosophical term assuming, in ontological and axiological sense, that spiritual reality, self-knowledge, consciousness or mental experiences are components of the human being - components of a higher order having priority over matter. They constitute, in the anthropological context, beings of a higher order than the body. Spiritualism according to its popular interpretation means spirituality. Qualities which are ascribed to that notion in particular societies can be determined on the basis of empirically oriented sociological research. They make it possible to determine various ways of interpreting and understanding that notion as well as views or attitudes connected with it.
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Kosiewicz, Jerzy. "Prolegomena for Considerations on Western Sport and Spiritualism." Physical Culture and Sport. Studies and Research 47, no. 1 (December 1, 2009): 79–88. http://dx.doi.org/10.2478/v10141-009-0034-9.
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Prolegomena for Considerations on Western Sport and SpiritualismSport activity of achievement-oriented (professional, Olympic, spectacular character) is first of all exposition of rivalry and striving for variously understood sports success (resulting from measurable or discretionary criteria). It refers to winning a competition or taking another expected place as well as to other forms of satisfaction, such as financial gratification or social (political, ethnic, professional) recognition. Spirituality is here neither an aim, nor an expected value — it constitutes rather an additional or redundant quality. A competitor focuses his/her attention first of all on the main aim assumed in planned or current rivalry. Emotional sensations which are experienced by athletes before, during or after competitions testify to mental and emotional stress which accompanies sports combat.It is also difficult to associate spirituality or spiritualism with sport for all — like, for example, that of health-oriented character — sport of the disabled, physical education, sport of playful character or physical recreation. That difficulty results from the fact that neither spiritualism, nor spirituality inspires for physical activity in the abovementioned fields; neither spiritualism, nor spirituality is the outcome of activity in the realm of sport for all.Exceptions are constituted by ancient Olympic Games as well as by some experiences connected with recreational forms of tourism mediated through achievement-oriented sport (also by pre-Columbian Native American societies and Maoris aboriginal population of New Zealand).For example Hellenic Olympic Games were a highly spiritualized form of sports rivalry — including also rivalry in the field of art, and especially in the field of theatre. They were one of numerous forms of religious cult — of worshipping chosen gods from the Olympic pantheon. On the other hand, during mountain hiking and mountain climbing there can appear manifestations of deepened spirituality characteristic for the object of spiritualization of non-religious, quasi-religious or strictly religious qualities.I would like to explain — at the end of this short abstract - that spiritualism (which should not be confused with spiritism) is — generally speaking — first of all a philosophical term assuming, in ontological and axiological sense, that spiritual reality, self-knowledge, consciousness or mental experiences are components of the human being — components of a higher order having priority over matter. They constitute, in the anthropological context, beings of a higher order than the body.Spiritualism according to its popular interpretation means spirituality. Qualities which are ascribed to that notion in particular societies can be determined on the basis of empirically oriented sociological research. They make it possible to determine various ways of interpreting and understanding that notion as well as views or attitudes connected with it.
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Chauhan, Aman, Arun Kumar Arumugam Raajasekar, Zin Myint, Leaundra Murray, and Lowell Brian Anthony. "Capecitabine and temozolomide (CAPTEM) in neuroendocrine tumor of unknown primary." Journal of Clinical Oncology 35, no. 15_suppl (May 20, 2017): e15691-e15691. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.e15691.
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e15691 Background: Better diagnostics, recognition and knowledge of neuroendocrine tumors (NETs) have led to consistent growth in incidence and prevalence of the disease. Being an orphan disease, therapeutic options are limited. Scarce data exists regarding use of Capecitabine and Temozolomide (CAPTEM) in neuroendocrine tumors. There are no published data on use of CAPTEM in neuroendocrine tumors of unknown primary. NETs of unknown primary accounts for 10-15 % of NETs. Historically NETs with unknown primary are thought to be relatively aggressive, conferring a poorer prognosis. Methods: Patients with neuroendocrine tumor with unknown primary were identified from Markey Cancer Center database over a five-year period (2012-2016). Patients treated with CAPTEM regimen were analyzed for radiological response in first scan, time to progression on treatment and toxicity. IRB approval was obtained. Results: 56 patients with neuroendocrine tumors of unknown primary were identified. 12 patients were treated with CAPTEM. Median age of study cohort was 62 years. 6/12 were females. Seven patients were grade II, 4 were grade III and only one was grade I NET. CAPTEM was used as front line systemic therapy in 9 patients. Mean duration of treatment before progression was 10.8 months. 6 patients showed reduction in metastatic tumor volume at first q 3 monthly CT scan. 3 patients had stable disease and 3 patients showed disease progression at first surveillance scan. Following were the rates of common side-effects. Grade 2 thrombocytopenia (n = 4), Grade 1 lymphocytopenia (n = 3), hand/foot syndrome Grade 1 (n = 1), Grade 3(n = 1), Fatigue, Grade 1 (n = 6) Conclusions: CAPTEM shows activity in neuroendocrine tumor of unknown primary. Currently FDA approved treatment options for grade I and grade II GI NETs includes somatostatin analogs and everolimus. Both of which are cytostatic and of limited use in case of visceral crisis or bulky disease where disease shrinkage is required. CAPTEM should be considered for grade II NETS of unknown primary.
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Houser, Mei C. Q., Yuliia Turchyna, Florian Perrin, Lori Chibnik, Oksana Berezovska, and Masato Maesako. "Limited Substrate Specificity of PS/γ-Secretase Is Supported by Novel Multiplexed FRET Analysis in Live Cells." Biosensors 11, no. 6 (May 26, 2021): 169. http://dx.doi.org/10.3390/bios11060169.
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Presenilin (PS)/γ-secretase is an aspartyl protease that processes a wide range of transmembrane proteins such as the amyloid precursor protein (APP) and Notch1, playing essential roles in normal biological events and diseases. However, whether there is a substrate preference for PS/γ-secretase processing in cells is not fully understood. Structural studies of PS/γ-secretase enfolding a fragment of APP or Notch1 showed that the two substrates engage the protease in broadly similar ways, suggesting the limited substrate specificity of PS/γ-secretase. In the present study, we developed a new multiplexed imaging platform that, for the first time, allowed us to quantitatively monitor how PS/γ-secretase processes two different substrates (e.g., APP vs. Notch1) in the same cell. In this assay, we utilized the recently reported, spectrally compatible visible and near-infrared (NIR)-range Förster resonance energy transfer (FRET) biosensors that permit quantitative recording of PS/γ-secretase activity in live cells. Here, we show that, overall, PS/γ-secretase similarly cleaves Notch1 N100, wild-type APP C99, and familial Alzheimer’s disease (FAD)-linked APP C99 mutants in Chinese hamster ovary (CHO) cells, which further supports the limited PS/γ-secretase substrate specificity. On the other hand, a cell-by-cell basis analysis demonstrates a certain degree of variability in substrate recognition and processing by PS/γ-secretase among different cells. Our new multiplexed FRET assay could be a useful tool to better understand how PS/γ-secretase processes its multiple substrates in normal and disease conditions in live, intact cells.
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Hartnoll, Susannah H., and T. David Punt. "Yoga practice is associated with superior motor imagery performance." International Journal of Yoga Therapy 27, no. 1 (November 1, 2017): 81–86. http://dx.doi.org/10.17761/1531-2054-27.1.81.
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Abstract Yoga is an activity that aims to integrate physical, mental and spiritual elements and is an increasingly popular approach to enhancing physical fitness. The integration of imagery within yoga practice is considered an important component and may be critical in contributing to the benefits of yoga that have been reported. In this study, we tested whether individuals who practice yoga demonstrate superior performance on an objective measure of implicit motor imagery. Thirty-six participants (18 yoga, 18 non-yoga) matched for age, sex and handedness, undertook the hand laterality recognition task; an objective measure of implicit motor imagery performance. Accuracy and response times were gathered and analysed to determine any group differences as well as any differences relating to the typical hallmarks of imagery (i.e. dominance and awkwardness effects) on the task. Response Times (RTs) in the yoga group were significantly faster than controls (p < 0.05) and there was also a trend towards greater accuracy for the Yoga group (p = 0.073). Dominance effects (faster responses to images corresponding with the dominant limb) and Awkwardness effects (faster responses to images corresponding with natural compared with awkward postures) were evident across groups, supporting the participants' use of motor imagery in undertaking the task. Additionally, a Group × Awkwardness interaction (p < 0.05) revealed that the enhanced imagery performance for the yoga group was most pronounced for awkward postures. This is the first study to show that yoga practice is associated with superior motor imagery performance; an association that may be important in explaining the established rehabilitative value of yoga for chronic pain.
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Palmirski, Tomasz. "KONIEC MORSZTYNA. PRZYCZYNEK DO DZIEJÓW PRAWA RZYMSKIEGO W POLSCE." Zeszyty Prawnicze 3, no. 1 (March 29, 2017): 163. http://dx.doi.org/10.21697/zp.2003.3.1.06.
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THE END OF MORSZTYN. A CONTRIBUTION TO THE HISTORY OF THE ROMAN LAW IN POLANDSummary The lawsuit of Jan Andrzej Morsztyn at the Diet Court in 1690, and first of all, the issue of applying the rules provided by the Roman law with regard to the judicial oath of the sued party, has been discussed in the literature of the subject. However, the researchers have limited themselves to the statement that this fact took place. They did not prove that the Roman law, and precisely, the Justinian law, knew the concept of an oath made in writing, to which persons acting as Morsztyn’s substitutes in the lawsuit referred to. The author, considering relevant regulations comes to a conclusion that the Justinian law did not provide for a possibility to take an oath in writing. On the other hand, Polish law did not provide for such a possibility either since an oath taken in land cases always assumed a form of an oral oath. Therefore, taking into account the political situation in which the lawsuit against Morsztyn, king Jan Sobieski IITs opponent, took place, it should be assumed that the decision which allowed a written form of an oath was a sign of the judges’ common sense (rejecting the recognition of the written form in the context of restitution of the crown’s jewels by the accused, could only increase the number of Morsztyn’s followers) and the law-making activity of the Diet Court rather than an example of applying the Justinian law.
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Ning, Zhuang, Qiang Zhang, Yang Shen, Zefan Li, Bingbing Ni, and Wenjun Zhang. "Long term activity prediction in first person viewpoint." Pattern Recognition Letters 125 (July 2019): 708–14. http://dx.doi.org/10.1016/j.patrec.2019.07.020.
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Yuan, Hangjie, and Dong Ni. "Learning Visual Context for Group Activity Recognition." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 4 (May 18, 2021): 3261–69. http://dx.doi.org/10.1609/aaai.v35i4.16437.
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Group activity recognition aims to recognize an overall activity in a multi-person scene. Previous methods strive to reason on individual features. However, they under-explore the person-specific contextual information, which is significant and informative in computer vision tasks. In this paper, we propose a new reasoning paradigm to incorporate global contextual information. Specifically, we propose two modules to bridge the gap between group activity and visual context. The first is Transformer based Context Encoding (TCE) module, which enhances individual representation by encoding global contextual information to individual features and refining the aggregated information. The second is Spatial-Temporal Bilinear Pooling (STBiP) module. It firstly further explores pairwise relationships for the context encoded individual representation, then generates semantic representations via gated message passing on a constructed spatial-temporal graph. On their basis, we further design a two-branch model that integrates the designed modules into a pipeline. Systematic experiments demonstrate each module's effectiveness on either branch. Visualizations indicate that visual contextual cues can be aggregated globally by TCE. Moreover, our method achieves state-of-the-art results on two widely used benchmarks using only RGB images as input and 2D backbones.