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Spekreijse, Henk. "Pre-attentive and attentive mechanisms in vision." Vision Research 40, no. 10-12 (June 2000): 1179–82. http://dx.doi.org/10.1016/s0042-6989(00)00060-2.
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Yin, Wenpeng, and Hinrich Schütze. "Attentive Convolution: Equipping CNNs with RNN-style Attention Mechanisms." Transactions of the Association for Computational Linguistics 6 (December 2018): 687–702. http://dx.doi.org/10.1162/tacl_a_00249.
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In NLP, convolutional neural networks (CNNs) have benefited less than recurrent neural networks (RNNs) from attention mechanisms. We hypothesize that this is because the attention in CNNs has been mainly implemented as attentive pooling (i.e., it is applied to pooling) rather than as attentive convolution (i.e., it is integrated into convolution). Convolution is the differentiator of CNNs in that it can powerfully model the higher-level representation of a word by taking into account its local fixed-size context in the input text t x. In this work, we propose an attentive convolution network, ATTCONV. It extends the context scope of the convolution operation, deriving higher-level features for a word not only from local context, but also from information extracted from nonlocal context by the attention mechanism commonly used in RNNs. This nonlocal context can come (i) from parts of the input text t x that are distant or (ii) from extra (i.e., external) contexts t y. Experiments on sentence modeling with zero-context (sentiment analysis), single-context (textual entailment) and multiple-context (claim verification) demonstrate the effectiveness of ATTCONV in sentence representation learning with the incorporation of context. In particular, attentive convolution outperforms attentive pooling and is a strong competitor to popular attentive RNNs. 1
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Von Grünau, M. W. "Attentive mechanisms in visual search." Spatial Vision 17, no. 4 (2004): 353–71. http://dx.doi.org/10.1163/1568568041920177.
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Tervaniemi, Mari. "215 Pre-attentive and attentive brain mechanisms of complex-sound perception." International Journal of Psychophysiology 30, no. 1-2 (September 1998): 85. http://dx.doi.org/10.1016/s0167-8760(98)90215-x.
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Jaaskelainen, Iiro P., Giorgio Bonmassar, Hennifer Melcher, Steve Stufflebeam, Monica Hawley, Patrick May, Lawrence Wald, Hannu Tiitinen, and John W. Belliveau. "Cortical mechanisms of pre-attentive auditory “Gating”." NeuroImage 13, no. 6 (June 2001): 321. http://dx.doi.org/10.1016/s1053-8119(01)91664-7.
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Milanese, Ruggero. "Attentive mechanisms for dynamic and static scene analysis." Optical Engineering 34, no. 8 (August 1, 1995): 2428. http://dx.doi.org/10.1117/12.205668.
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YU, YUANLONG, GEORGE K. I. MANN, and RAYMOND G. GOSINE. "A SINGLE-OBJECT TRACKING METHOD FOR ROBOTS USING OBJECT-BASED VISUAL ATTENTION." International Journal of Humanoid Robotics 09, no. 04 (December 2012): 1250030. http://dx.doi.org/10.1142/s0219843612500302.
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It is a quite challenging problem for robots to track the target in complex environment due to appearance changes of the target and background, large variation of motion, partial and full occlusion, motion of the camera and so on. However, humans are capable to cope with these difficulties by using their cognitive capability, mainly including the visual attention and learning mechanisms. This paper therefore presents a single-object tracking method for robots based on the object-based attention mechanism. This tracking method consists of four modules: pre-attentive segmentation, top-down attentional selection, post-attentive processing and online learning of the target model. The pre-attentive segmentation module first divides the scene into uniform proto-objects. Then the top-down attention module selects one proto-object over the predicted region by using a discriminative feature of the target. The post-attentive processing module then validates the attended proto-object. If it is confirmed to be the target, it is used to obtain the complete target region. Otherwise, the recovery mechanism is automatically triggered to globally search for the target. Given the complete target region, the online learning algorithm autonomously updates the target model, which consists of appearance and saliency components. The saliency component is used to automatically select a discriminative feature for top-down attention, while the appearance component is used for bias estimation in the top-down attention module and validation in the post-attentive processing module. Experiments have shown that this proposed method outperforms other algorithms without using attention for tracking a single target in cluttered and dynamically changing environment.
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Himabindu, Dakshayani D., and Praveen S. Kumar. "A Streamlined Attention Mechanism for Image Classification and Fine-Grained Visual Recognition." MENDEL 27, no. 2 (December 21, 2021): 59–67. http://dx.doi.org/10.13164/mendel.2021.2.059.
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In the recent advancements attention mechanism in deep learning had played a vital role in proving better results in tasks under computer vision. There exists multiple kinds of works under attention mechanism which includes under image classification, fine-grained visual recognition, image captioning, video captioning, object detection and recognition tasks. Global and local attention are the two attention based mechanisms which helps in interpreting the attentive partial. Considering this criteria, there exists channel and spatial attention where in channel attention considers the most attentive channel among the produced block of channels and spatial attention considers which region among the space needs to be focused on. We have proposed a streamlined attention block module which helps in enhancing the feature based learning with less number of additional layers i.e., a GAP layer followed by a linear layer with an incorporation of second order pooling(GSoP) after every layer in the utilized encoder. This mechanism has produced better range dependencies by the conducted experimentation. We have experimented our model on CIFAR-10, CIFAR-100 and FGVC-Aircrafts datasets considering finegrained visual recognition. We were successful in achieving state-of-the-result for FGVC-Aircrafts with an accuracy of 97%.
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Kalaska, John F. "Central Neural Mechanisms of Touch and Proprioception." Canadian Journal of Physiology and Pharmacology 72, no. 5 (May 1, 1994): 542–45. http://dx.doi.org/10.1139/y94-078.
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The argument is made that somesthesia is not a strictly passive process, and its central neuronal mechanisms cannot be studied in all their complexity and subtlety by applying passive stimuli to uninterested or unconscious animals. The case is clear for kinesthesia. Peripheral proprioceptive signals are altered by active muscle contractions, and the central mechanisms of kinesthetic sensations should be studied during active movements. A similar case can be made for tactile discrimination. Ascending tactile afferents are subject to modulation during movement. Moreover, the generation of a central neural representation of the mechanical stimulus is only part of the tactile perceptual process. It is also influenced by the behavioral, attentive, and motivational state of the animal, whose effects can only be revealed in awake animals actively participating in discrimination tasks.Key words: tactile discrimination, proprioception, gating, attention, active touch.
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Liu, Yichu, Haifeng Hu, and Dihu Chen. "Attentive Part-Based Alignment Network for Vehicle Re-Identification." Electronics 11, no. 10 (May 19, 2022): 1617. http://dx.doi.org/10.3390/electronics11101617.
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Vehicle Re-identification (Re-ID) has become a research hotspot along with the rapid development of video surveillance. Attention mechanisms are utilized in vehicle Re-ID networks but often miss the attention alignment across views. In this paper, we propose a novel Attentive Part-based Alignment Network (APANet) to learn robust, diverse, and discriminative features for vehicle Re-ID. To be specific, in order to enhance the discrimination of part features, two part-level alignment mechanisms are proposed in APANet, consisting of Part-level Orthogonality Loss (POL) and Part-level Attention Alignment Loss (PAAL). Furthermore, POL aims to maximize the diversity of part features via an orthogonal penalty among parts whilst PAAL learns view-invariant features by means of realizing attention alignment in a part-level fashion. Moreover, we propose a Multi-receptive-field Attention (MA) module to adopt an efficient and cost-effective pyramid structure. The pyramid structure is capable of employing more fine-grained and heterogeneous-scale spatial attention information through multi-receptive-field streams. In addition, the improved TriHard loss and Inter-group Feature Centroid Loss (IFCL) function are utilized to optimize both the inter-group and intra-group distance. Extensive experiments demonstrate the superiority of our model over multiple existing state-of-the-art approaches on two popular vehicle Re-ID benchmarks.
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Coco, Marinella, Andrea Buscemi, Matej Tušak, Vincenzo Perciavalle, Alfio Nifosì, Paolo Cavallari, Donatella Di Corrado, and Valentina Perciavalle. "Attentive Processes and Blood Lactate in the Sambo." International Journal of Environmental Research and Public Health 19, no. 3 (January 20, 2022): 1113. http://dx.doi.org/10.3390/ijerph19031113.
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Background: Sambo is a martial art and combat sport that originated in the Soviet Union. There are two main stiles, Sport Sambo and Combat Sambo which resembles modern mixed martial arts. Very little literature is available about physiological aspects of Sambo and, in particular, on the possible effects on cognitive domains. The purpose of the present research was to determine if there is a correlation between a blood lactate increase and the intensity and/or selectivity of attentions. Methods: Sixteen male athletes practicing Sambo for at least 5 years participated voluntarily in the study. Each athlete had to sustain, with an interval of one week, both a Sport Sambo match and a Combat Sambo match, each lasting 5 min. Blood lactate levels as well as attentive capacities were evaluated at three different times: at rest, i.e., 5 min before the start of the session (pre), at end of the session and 15 min after its conclusion. Reaction time protocol was used to evaluate the intensity of attention, whereas divided attention was assessed for analyzing the selectivity of attention together with errors and omissions. Results: Concerning Sport Sambo, blood lactate was 1.66 mmol/L (±0.55 SD) before the session, reached a mean value of 3.40 mmol/L (±0.45 SD) at the end of the session (end) and returned to values similar to initial ones (a mean value of 1.98 mmol/L (±0.37 SD) after 15 min (15-end). None of the attentive parameters examined, showed statistically significant differences. Conversely, for Combat Sambo, it was found a significant increase in blood lactate levels that went from 1.66 mmol/L (±0.55 SD) before the session (pre), to 4.76 mmol/L (±0.60 SD) at the end (end) and then back to values similar to those observed before the session 15 min after its conclusion (15-end), i.e., 1.97 mmol/L (±0.37 SD); however, after a Combat Sambo session increases in blood lactate were associated with significant worsening of attentional mechanisms. Conclusions: In conclusion, in all the participants, the worsening of attentional mechanisms was observed only after the Combat Sambo session in which blood lactate values exceeded 4 mmol/L. This figure, also known as the Onset of Blood Lactate Accumulation (OBLA), is commonly used to determine the anaerobic threshold.
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Zhaoping, Li. "Pre–attentive segmentation and correspondence in stereo." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 357, no. 1428 (December 29, 2002): 1877–83. http://dx.doi.org/10.1098/rstb.2002.1158.
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Traditional stereo grouping models have focused on the problem of stereo correspondence between monocular inputs. Recent physiological data revealed that the disparity selective V2 cells increase their responses when (random–dot stereograms) stimuli within their receptive fields are at or near the boundary of a depth surface. Such highlights to depth (non–luminance) edges are seemingly not computationally required for the correspondence problem. Computationally, these highlights make the boundaries of a depth surface more salient, serving pre–attentive segmentation (between depth planes) and attracting visual attention. In special cases, they enable the psychophysically observed perceptual pop–out of a target from a background of visually identical distractors at a different depth. To achieve the highlights, mutual inhibition between disparity selective cells that are tuned to the same or similar depths is required. However, such mutual inhibition would impede the computation for the correspondence problem, which requires mutual excitation between the same cells. In this work, I introduce a computational model that, I believe, is the first to address both stereo correspondence and pre–attentive stereo segmentation. The computational mechanisms in the model are based on intracortical interactions in V2. I will demonstrate that the model captures the following physiological and psychophysical phenomena: (i) depth–edge highlighting; (ii) disparity capture; (iii) pop–out; and (iv) transparency.
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Gross, Neil. "The Structure of Causal Chains." Sociological Theory 36, no. 4 (December 2018): 343–67. http://dx.doi.org/10.1177/0735275118811377.
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Sociologists are increasingly attentive to the mechanisms responsible for cause-and-effect relationships in the social world. But an aspect of mechanistic causality has not been sufficiently considered. It is well recognized that most phenomena of interest to social science result from multiple mechanisms operating in sequence. However, causal chains—sequentially linked mechanisms and their enabling background conditions—vary not just substantively, by the kind of causal work they do, but also structurally, by their formal properties. In this article, the author examines the nature of causal chains, identifies major structural dimensions along which they differ, and makes a case that a mechanism-based explanation would be enhanced if causal chains and their structures were brought to the analytical forefront.
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Tiwari, Prayag, Amit Kumar Jaiswal, Sahil Garg, and Ilsun You. "SANTM: Efficient Self-attention-driven Network for Text Matching." ACM Transactions on Internet Technology 22, no. 3 (August 31, 2022): 1–21. http://dx.doi.org/10.1145/3426971.
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Self-attention mechanisms have recently been embraced for a broad range of text-matching applications. Self-attention model takes only one sentence as an input with no extra information, i.e., one can utilize the final hidden state or pooling. However, text-matching problems can be interpreted either in symmetrical or asymmetrical scopes. For instance, paraphrase detection is an asymmetrical task, while textual entailment classification and question-answer matching are considered asymmetrical tasks. In this article, we leverage attractive properties of self-attention mechanism and proposes an attention-based network that incorporates three key components for inter-sequence attention: global pointwise features, preceding attentive features, and contextual features while updating the rest of the components. Our model follows evaluation on two benchmark datasets cover tasks of textual entailment and question-answer matching. The proposed efficient Self-attention-driven Network for Text Matching outperforms the state of the art on the Stanford Natural Language Inference and WikiQA datasets with much fewer parameters.
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Chen, Yining, Laura E. Matheson, and Jon T. Sakata. "Mechanisms underlying the social enhancement of vocal learning in songbirds." Proceedings of the National Academy of Sciences 113, no. 24 (May 31, 2016): 6641–46. http://dx.doi.org/10.1073/pnas.1522306113.
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Social processes profoundly influence speech and language acquisition. Despite the importance of social influences, little is known about how social interactions modulate vocal learning. Like humans, songbirds learn their vocalizations during development, and they provide an excellent opportunity to reveal mechanisms of social influences on vocal learning. Using yoked experimental designs, we demonstrate that social interactions with adult tutors for as little as 1 d significantly enhanced vocal learning. Social influences on attention to song seemed central to the social enhancement of learning because socially tutored birds were more attentive to the tutor’s songs than passively tutored birds, and because variation in attentiveness and in the social modulation of attention significantly predicted variation in vocal learning. Attention to song was influenced by both the nature and amount of tutor song: Pupils paid more attention to songs that tutors directed at them and to tutors that produced fewer songs. Tutors altered their song structure when directing songs at pupils in a manner that resembled how humans alter their vocalizations when speaking to infants, that was distinct from how tutors changed their songs when singing to females, and that could influence attention and learning. Furthermore, social interactions that rapidly enhanced learning increased the activity of noradrenergic and dopaminergic midbrain neurons. These data highlight striking parallels between humans and songbirds in the social modulation of vocal learning and suggest that social influences on attention and midbrain circuitry could represent shared mechanisms underlying the social modulation of vocal learning.
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Chen, Yin. "An Alzheimer’s Disease Identification and Classification Model Based on the Convolutional Neural Network with Attention Mechanisms." Traitement du Signal 38, no. 5 (October 31, 2021): 1557–64. http://dx.doi.org/10.18280/ts.380533.
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MRI image analysis of brain regions based on deep learning can effectively reduce the workload of doctors in reading films and improve the accuracy of diagnosis. Therefore, deep learning models have great application prospects in the classification and prediction of Alzheimer’s patients and normal people. However, the existing research has ignored the correlation between small abnormalities in local brain regions and changes in brain tissues. To this end, this paper studies an Alzheimer’s disease identification and classification model based on the convolutional neural network (CNN) with attention mechanisms. In this paper, the attention mechanisms were introduced from the regional level and the feature level, and the information of brain MRI images was fused from multiple levels to find out the correlation between the slices in brain MRI images. Then, a spatio-temporal graph CNN with dual attention mechanisms was constructed, which made the network model more attentive to the salient channel features while eliminating the impact of certain noise features. The experimental results verified the effectiveness of the constructed model in identification and classification of Alzheimer’s disease.
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Falleti, Tulia G., and Julia F. Lynch. "Context and Causal Mechanisms in Political Analysis." Comparative Political Studies 42, no. 9 (April 21, 2009): 1143–66. http://dx.doi.org/10.1177/0010414009331724.
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Political scientists largely agree that causal mechanisms are crucial to understanding causation. Recent advances in qualitative and quantitative methodology suggest that causal explanations must be contextually bounded. Yet the relationship between context and mechanisms and this relationship's importance for causation are not well understood. This study defines causal mechanisms as portable concepts that explain how and why a hypothesized cause, in a given context, contributes to a particular outcome. In turn, it defines context as the relevant aspects of a setting in which an array of initial conditions leads to an outcome of a defined scope and meaning via causal mechanisms. Drawing from these definitions is the argument that credible causal explanation can occur if and only if researchers are attentive to the interaction between causal mechanisms and context, regardless of whether the methods employed are small-sample, formal, statistical, or interpretive.
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Demiris, Yiannis, and Bassam Khadhouri. "Content-based control of goal-directed attention during human action perception." Interaction Studies 9, no. 2 (May 26, 2008): 353–76. http://dx.doi.org/10.1075/is.9.2.10dem.
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During the perception of human actions by robotic assistants, the robotic assistant needs to direct its computational and sensor resources to relevant parts of the human action. In previous work we have introduced HAMMER (Hierarchical Attentive Multiple Models for Execution and Recognition) (Demiris and Khadhouri, 2006), a computational architecture that forms multiple hypotheses with respect to what the demonstrated task is, and multiple predictions with respect to the forthcoming states of the human action. To confirm their predictions, the hypotheses request information from an attentional mechanism, which allocates the robot’s resources as a function of the saliency of the hypotheses. In this paper we augment the attention mechanism with a component that considers the content of the hypotheses’ requests, with respect to the content’s reliability, utility and cost. This content-based attention component further optimises the utilisation of the resources while remaining robust to noise. Such computational mechanisms are important for the development of robotic devices that will rapidly respond to human actions, either for imitation or collaboration purposes.
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Fu, Junwei, and Jun Liang. "Virtual View Generation Based on 3D-Dense-Attentive GAN Networks." Sensors 19, no. 2 (January 16, 2019): 344. http://dx.doi.org/10.3390/s19020344.
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A binocular vision system is a common perception component of an intelligent vehicle. Benefiting from the biomimetic structure, the system is simple and effective. Which are extremely snesitive on external factors, especially missing vision signals. In this paper, a virtual view-generation algorithm based on generative adversarial networks (GAN) is proposed to enhance the robustness of binocular vision systems. The proposed model consists of two parts: generative network and discriminator network. To improve the quality of a virtual view, a generative network structure based on 3D convolutional neural networks (3D-CNN) and attentive mechanisms is introduced to extract the time-series features from image sequences. To avoid gradient vanish during training, the dense block structure is utilized to improve the discriminator network. Meanwhile, three kinds of image features, including image edge, depth map and optical flow are extracted to constrain the supervised training of model. The final results on KITTI and Cityscapes datasets demonstrate that our algorithm outperforms conventional methods, and the missing vision signal can be replaced by a generated virtual view.
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Knight, Carly R., and Isaac Ariail Reed. "Meaning and Modularity: The Multivalence of “Mechanism” in Sociological Explanation." Sociological Theory 37, no. 3 (August 29, 2019): 234–56. http://dx.doi.org/10.1177/0735275119869969.
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Mechanisms are ubiquitous in sociological explanation. Recent theoretical work has sought to extend mechanistic explanation further still: into cultural and interpretative analysis. Yet it is not clear that the concept of mechanism can coherently unify interpretation and causal explanation within a single explanatory framework. We note that sociological mechanistic explanation is marked by a crucial disjuncture. Specifically, we identify two conflicting mechanistic approaches: Modular mechanism models depict counterfactual dependence among independent causal chains, whereas meaningful mechanism models depict relational interdependence among semiotic assemblages. This disjuncture, we argue, is grounded in incompatible causal foundations and entails mechanistic models with distinct and conflicting evidentiary standards. We conclude by proposing a way forward: a sociological pluralism that is attentive to the productive incongruity of our distinct explanatory models.
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Avanesi, Vino. "Second-screen subsumption: Aesthetics of control and the second-screen facilitation of hyper-attentive watching-labour." Convergence: The International Journal of Research into New Media Technologies 26, no. 2 (June 24, 2018): 369–85. http://dx.doi.org/10.1177/1354856518781650.
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The article at hand theorizes the political economic shift between the aesthetic strategies deployed by network television in the broadcast-era and those deployed in the matrix-era. It argues that where in the former era certain strategies allowed for the disciplining of viewers’ sensory dimensions and in turn allowed for the ‘factory’ process of watching-labour to penetrate the private lives of people, in the latter era this factory process has not only collapsed into the home but also into viewers’ sensoria. And, that this is due to the nature of the control mechanisms embedded in the new aesthetic strategies deployed by media-capital through second-screen technologies. This article concludes by theorizing said set of mechanisms as an iteration of a society-wide aesthetic of control essential to the operation of contemporary capitalism.
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Ames, Justin, Dustin Bluhm, James Gaskin, and Kalle Lyytinen. "The impact of moral attentiveness on manager’s turnover intent." Society and Business Review 15, no. 3 (August 10, 2020): 189–209. http://dx.doi.org/10.1108/sbr-03-2020-0025.
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Purpose With the rise in public awareness of corporate social responsibility, business leaders are increasingly expected to recognize the needs and demands of multiple stakeholders. There may, however, be unintended consequences of this expectation for organizational managers who engage these needs and demands with a high level of moral attentiveness. This study aims to investigate the indirect effect of managerial moral attentiveness on managerial turnover intent, serially mediated by moral dissonance and moral stress. Design/methodology/approach Multi-phase survey data were collected from 130 managers within a large sales organization regarding experiences of moral dissonance and moral stress. The authors analyzed the relation of these experiences to measures of moral attentiveness and turnover intent using structural equation modeling. Findings Results support a serial mediation model, with a positive, indirect effect between moral attentiveness and turnover intent among managers through moral dissonance and moral stress. Overall, the results suggest that expecting business leaders to be morally attentive may result in greater moral dissonance and moral stress, potentially impacting their intentions to stay with the organization. Practical implications Implementing positive practices toward processing moral dissonance and reducing moral stress may be a mechanism toward retaining ethically inclined organizational leaders. Originality/value This study is the first to identify moral attentiveness as an antecedent to turnover intent within managers. It also establishes the serial mechanisms of moral dissonance and moral stress and provides suggestions on how to retain morally attentive managers by actively managing those mechanisms.
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Wu, Wenqing, Zhenfang Zhu, Qiang Lu, Dianyuan Zhang, and Qiangqiang Guo. "Introducing External Knowledge to Answer Questions with Implicit Temporal Constraints over Knowledge Base." Future Internet 12, no. 3 (March 5, 2020): 45. http://dx.doi.org/10.3390/fi12030045.
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Knowledge base question answering (KBQA) aims to analyze the semantics of natural language questions and return accurate answers from the knowledge base (KB). More and more studies have applied knowledge bases to question answering systems, and when using a KB to answer a natural language question, there are some words that imply the tense (e.g., original and previous) and play a limiting role in questions. However, most existing methods for KBQA cannot model a question with implicit temporal constraints. In this work, we propose a model based on a bidirectional attentive memory network, which obtains the temporal information in the question through attention mechanisms and external knowledge. Specifically, we encode the external knowledge as vectors, and use additive attention between the question and external knowledge to obtain the temporal information, then further enhance the question vector to increase the accuracy. On the WebQuestions benchmark, our method not only performs better with the overall data, but also has excellent performance regarding questions with implicit temporal constraints, which are separate from the overall data. As we use attention mechanisms, our method also offers better interpretability.
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Chen, Long, Ziyu Guan, Wei Zhao, Wanqing Zhao, Xiaopeng Wang, Zhou Zhao, and Huan Sun. "Answer Identification from Product Reviews for User Questions by Multi-Task Attentive Networks." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 45–52. http://dx.doi.org/10.1609/aaai.v33i01.330145.
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Online Shopping has become a part of our daily routine, but it still cannot offer intuitive experience as store shopping. Nowadays, most e-commerce Websites offer a Question Answering (QA) system that allows users to consult other users who have purchased the product. However, users still need to wait patiently for others’ replies. In this paper, we investigate how to provide a quick response to the asker by plausible answer identification from product reviews. By analyzing the similarity and discrepancy between explicit answers and reviews that can be answers, a novel multi-task deep learning method with carefully designed attention mechanisms is developed. The method can well exploit large amounts of user generated QA data and a few manually labeled review data to address the problem. Experiments on data collected from Amazon demonstrate its effectiveness and superiority over competitive baselines.
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Ladinig, Olivia, Henkjan Honing, Gáábor Hááden, and Istváán Winkler. "Probing Attentive and Preattentive Emergent Meter in Adult Listeners without Extensive Music Training." Music Perception 26, no. 4 (April 1, 2009): 377–86. http://dx.doi.org/10.1525/mp.2009.26.4.377.
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BEAT AND METER INDUCTION ARE CONSIDERED important structuring mechanisms underlying the perception of rhythm. Meter comprises two or more levels of hierarchically ordered regular beats with different periodicities. When listening to music, adult listeners weight events within a measure in a hierarchical manner. We tested if listeners without advanced music training form such hierarchical representations for a rhythmical sound sequence under different attention conditions (Attend, Unattend, and Passive). Participants detected occasional weakly and strongly syncopated rhythmic patterns within the context of a strictly metrical rhythmical sound sequence. Detection performance was better and faster when syncopation occurred in a metrically strong as compared to a metrically weaker position. Compatible electrophysiological differences (earlier and higher-amplitude MMN responses) were obtained when participants did not attend the rhythmical sound sequences. These data indicate that hierarchical representations for rhythmical sound sequences are formed preattentively in the human auditory system.
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Obermeyer, Jessica A., and Lisa A. Edmonds. "Attentive Reading With Constrained Summarization Adapted to Address Written Discourse in People With Mild Aphasia." American Journal of Speech-Language Pathology 27, no. 1S (March 2018): 392–405. http://dx.doi.org/10.1044/2017_ajslp-16-0200.
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Purpose The purpose of this study was to examine the preliminary efficacy of Attentive Reading and Constrained Summarization–Written (ARCS-W) in people with mild aphasia. ARCS-W adapts an existing treatment, ARCS (Rogalski & Edmonds, 2008), to address discourse level writing in mild aphasia. ARCS-W focuses on the cognitive and linguistic skills required for discourse production. Method This study was a within-subject pre–postdesign. Three people with mild aphasia participated. ARCS-W integrates attentive reading or listening with constrained summarization of discourse level material in spoken and written modalities. Outcomes included macro- (main concepts) and microlinguistic (correct information units, complete utterances) discourse measures, confrontation naming, aphasia severity, and functional communication. Results All 3 participants demonstrated some generalization to untrained spoken and written discourse at the word, sentence, and text levels. Reduced aphasia severity and/or increased functional communication and confrontation naming were also observed in some participants. Conclusions The findings of this study provide preliminary evidence of the efficacy of ARCS-W to improve spoken and written discourse in mild aphasia. Different generalization patterns suggest different mechanisms of improvement. Further research and replication are required to better understand how ARCS-W can impact discourse abilities.
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Alimi, Eitan, Lorenzo Bosi, and Chares Demetriou. "Relational Dynamics and Processes of Radicalization: A Comparative Framework." Mobilization: An International Quarterly 17, no. 1 (February 1, 2012): 7–26. http://dx.doi.org/10.17813/maiq.17.1.u7rw348t8200174h.
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We propose an explanatory framework for the comparative study of radicalization that focuses on its "how" and "when" questions. We build on the relational tradition in the study of social movements and contentious politics by expanding on a mechanism-process research strategy. Attentive to similarities as well as to dissimilarities, our comparative framework traces processes of radicalization by delineating four key arenas of interaction—between movement and political environment, among movement actors, between movement activists and state security forces, and between the movement and a countermovement. Then, we analyze how four similar corresponding general mechanisms—opportunity/threat spirals, competition for power, outbidding, and object shift—combine differently to drive the process. Last, we identify a set of submechanisms for each general mechanism. The explanatory utility of our framework is demonstrated through the analysis of three ethnonational episodes of radicalization: the enosis-EOKA movement in Cyprus (1950-1959), the Provisional Irish Republican Army in Northern Ireland (1969-1972), and the Fatah-Tanzim in Palestine (1995-2001).
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Wang, Dong, Bing Liu, Yong Zhou, Mingming Liu, Peng Liu, and Rui Yao. "Separate Syntax and Semantics: Part-of-Speech-Guided Transformer for Image Captioning." Applied Sciences 12, no. 23 (November 22, 2022): 11875. http://dx.doi.org/10.3390/app122311875.
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Transformer-based image captioning models have recently achieved remarkable performance by using new fully attentive paradigms. However, existing models generally follow the conventional language model of predicting the next word conditioned on the visual features and partially generated words. They treat the predictions of visual and nonvisual words equally and usually tend to produce generic captions. To address these issues, we propose a novel part-of-speech-guided transformer (PoS-Transformer) framework for image captioning. Specifically, a self-attention part-of-speech prediction network is first presented to model the part-of-speech tag sequences for the corresponding image captions. Then, different attention mechanisms are constructed for the decoder to guide the caption generation by using the part-of-speech information. Benefiting from the part-of-speech guiding mechanisms, the proposed framework not only adaptively adjusts the weights between visual features and language signals for the word prediction, but also facilitates the generation of more fine-grained and grounded captions. Finally, a multitask learning is introduced to train the whole PoS-Transformer network in an end-to-end manner. Our model was trained and tested on the MSCOCO and Flickr30k datasets with the experimental evaluation standard CIDEr scores of 1.299 and 0.612, respectively. The qualitative experimental results indicated that the captions generated by our method conformed to the grammatical rules better.
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Sinigaglia, Alessandro, Elektra Peta, Silvia Riccetti, Seshasailam Venkateswaran, Riccardo Manganelli, and Luisa Barzon. "Tuberculosis-Associated MicroRNAs: From Pathogenesis to Disease Biomarkers." Cells 9, no. 10 (September 24, 2020): 2160. http://dx.doi.org/10.3390/cells9102160.
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Tuberculosis (TB) caused by Mycobacterium tuberculosis is one of the most lethal infectious diseases with estimates of approximately 1.4 million human deaths in 2018. M. tuberculosis has a well-established ability to circumvent the host immune system to ensure its intracellular survival and persistence in the host. Mechanisms include subversion of expression of key microRNAs (miRNAs) involved in the regulation of host innate and adaptive immune response against M. tuberculosis. Several studies have reported differential expression of miRNAs during active TB and latent tuberculosis infection (LTBI), suggesting their potential use as biomarkers of disease progression and response to anti-TB therapy. This review focused on the miRNAs involved in TB pathogenesis and on the mechanism through which miRNAs induced during TB modulate cell antimicrobial responses. An attentive study of the recent literature identifies a group of miRNAs, which are differentially expressed in active TB vs. LTBI or vs. treated TB and can be proposed as candidate biomarkers.
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Moura, Aline A. "On Emotion: Exchanges Between Neurosciences and Literary Studies." Scripta 26, no. 57 (November 21, 2022): 222–42. http://dx.doi.org/10.5752/p.2358-3428.2022v26n57p222-242.
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Taking into consideration an intellectual atmosphere attentive to the interchanges between embodied cognition and literature, the objective of this paper is to introduce definitions, mechanisms, and functionalities of bodily reactions to human existence and the production of knowledge based mainly on the investigations of the Portuguese neuroscientist Antonio Damasio. He has published several books and is one of the most influential researchers on the reciprocity among body, brain, mind, and situated experiences. By analyzing his investigations, it becomes possible to develop theoretical and analytical repertoires capable of contemplating emotion resulting from contact with literary fictions as relevant to their understanding.
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Imbriaco, Raffaele, Clint Sebastian, Egor Bondarev, and Peter de With. "Aggregated Deep Local Features for Remote Sensing Image Retrieval." Remote Sensing 11, no. 5 (February 28, 2019): 493. http://dx.doi.org/10.3390/rs11050493.
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Remote Sensing Image Retrieval remains a challenging topic due to the special nature of Remote Sensing imagery. Such images contain various different semantic objects, which clearly complicates the retrieval task. In this paper, we present an image retrieval pipeline that uses attentive, local convolutional features and aggregates them using the Vector of Locally Aggregated Descriptors (VLAD) to produce a global descriptor. We study various system parameters such as the multiplicative and additive attention mechanisms and descriptor dimensionality. We propose a query expansion method that requires no external inputs. Experiments demonstrate that even without training, the local convolutional features and global representation outperform other systems. After system tuning, we can achieve state-of-the-art or competitive results. Furthermore, we observe that our query expansion method increases overall system performance by about 3%, using only the top-three retrieved images. Finally, we show how dimensionality reduction produces compact descriptors with increased retrieval performance and fast retrieval computation times, e.g., 50% faster than the current systems.
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GOOD, MARION. "Acute Pain." Annual Review of Nursing Research 17, no. 1 (January 1999): 107–32. http://dx.doi.org/10.1891/0739-6686.17.1.107.
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The review of acute pain describes the problem of unresolved pain and its effects on the neural, autonomic, and immune systems. Conceptualizations and mechanisms of pain are reviewed as well as theories of pain management. Descriptive studies of patient and nurse factors that inhibit effective pain management are discussed, followed by studies of pharmacological and nonpharmacological interventions. Critical analysis reveals that most studies were atheoretical, and therefore, this proliferation of information lacked conceptual coherence and organization. Furthermore, the nature and extent of barriers to pain management were described, but few intervention studies have been devised, as yet, to modify the knowledge, beliefs, and attitudes of nurses and patients that are barriers to pain management. Although some of the complementary therapies have sufficient research sup port to be used in clinical pain management, the physiological mechanisms and outcomes need to be studied. It is critical at this time to design studies of interventions to improve assessment, decision making, attentive care, and patient teaching.
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Schwartze, Michael, and Sonja A. Kotz. "The Timing of Regular Sequences: Production, Perception, and Covariation." Journal of Cognitive Neuroscience 27, no. 9 (September 2015): 1697–707. http://dx.doi.org/10.1162/jocn_a_00805.
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The temporal structure of behavior provides information that allows the tracking of temporal regularity in the sensory and sensorimotor domains. In turn, temporal regularity allows the generation of predictions about upcoming events and to adjust behavior accordingly. These mechanisms are essential to ensure behavior beyond the level of mere reaction. However, efficient temporal processing is required to establish adequate internal representations of temporal structure. The current study used two simple paradigms, namely, finger-tapping at a regular self-chosen rate (spontaneous motor tempo) and ERPs of the EEG (EEG/ERP) recorded during attentive listening to temporally regular and irregular “oddball” sequences to explore the capacity to encode and use temporal regularity in production and perception. The results show that specific aspects of the ability to time a regular sequence of events in production covary with the ability to time a regular sequence in perception, probably pointing toward the engagement of domain-general mechanisms.
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Al-Shaiji, Tariq F., Mai Banakhar, and Magdy M. Hassouna. "Pelvic Electrical Neuromodulation for the Treatment of Overactive Bladder Symptoms." Advances in Urology 2011 (2011): 1–7. http://dx.doi.org/10.1155/2011/757454.
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Overactive bladder syndrome negatively affects the daily life of many people. First-line conservative treatments, such as antimuscarinics, do not always lead to sufficient improvement of the complaints and/or are often associated with disabling adverse effects leading to treatment failure. Electrical stimulation of the sacral nerves has emerged as an alternative and attractive treatment for refractory cases of bladder overactivity. Few theories attempted to explain its mechanism of action which remains elusive. It involves percutaneous posterior tibial nerve stimulation and more commonly sacral neuromodulation. For the latter, temporary sacral nerve stimulation is the first step. If the test stimulation is successful, a permanent device is implanted. The procedure is safe and reversible. It carries a durable success rate. The technique should be combined with careful followup and attentive adjustments of the stimulation parameters in order to optimize the clinical outcomes. This paper provides a review on the indications, possible mechanisms of action, surgical aspects and possible complications, and safety issues of this technique. The efficacy of the technique is also addressed.
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Chan, Agnes S., Yvonne M. Y. Han, Sophia L. Sze, Queenie Y. Wong, and Mei-chun Cheung. "A Randomized Controlled Neurophysiological Study of a ChineseChan-Based Mind-Body Intervention in Patients with Major Depressive Disorder." Evidence-Based Complementary and Alternative Medicine 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/812096.
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Our previous studies have reported the therapeutic effects of 10-session ChineseChan-basedDejianmind-body interventions (DMBI) in reducing the intake of antidepressants, improving depressive symptoms, and enhancing the attentional abilities of patients with depression. This study aims to explore the possible neuroelectrophysiological mechanisms underlying the previously reported treatment effects of DMBI in comparison with those of cognitive behavioral therapy (CBT). Seventy-five age-, gender-, and education-matched participants with depression were randomly assigned to receive either CBT or DMBI or placed on a waitlist. Eyes-closed resting EEG data were obtained individually before and after 10 weeks. After intervention, the DMBI group demonstrated significantly enhanced frontal alpha asymmetry (an index of positive mood) and intra- and interhemispheric theta coherence in frontoposterior and posterior brain regions (an index of attention). In contrast, neither the CBT nor the waitlist group showed significant changes in EEG activity patterns. Furthermore, the asymmetry and coherence indices of the DMBI group were correlated with self-reported depression severity levels and performance on an attention test, respectively. The present findings provide support for the effects of a ChineseChan-based mind-body intervention in fostering human brain states that can facilitate positive mood and an attentive mind.
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Ahnaou, A., R. Biermans, and W. H. I. M. Drinkenburg. "Cholinergic Mechanisms of Target Oddball Stimuli Detection: The Late “P300-Like” Event-Related Potential in Rats." Neural Plasticity 2018 (October 16, 2018): 1–15. http://dx.doi.org/10.1155/2018/4270263.
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Event-related potentials (ERPs) and oscillations (EROs) provide powerful tools for studying the brain’s synaptic function underlying information processing. The P300 component of ERPs indexing attention and working memory shows abnormal amplitude and latency in neurological and psychiatric diseases that are sensitive to pharmacological agents. In the active auditory oddball discriminant paradigm, behavior and auditory-evoked potentials (AEPs) were simultaneously recorded in awake rats to investigate whether P300-like potentials generated in rats responding to rare target oddball tones are sensitive to subcutaneous modulation of the cholinergic tone by donepezil (1 mg/kg) and scopolamine (0.64 mg/kg). After operant training, rats consistently discriminate rare target auditory stimuli from frequent irrelevant nontarget auditory stimuli by a higher level of correct lever presses (i.e., accuracy) in target trials associated with a food reward. Donepezil attenuated the disruptive effect of scopolamine on the level of accuracy and premature responses in target trials. Larger P300-like peaks with early and late components were revealed in correct rare target stimuli trials as compared to frequent tones. Donepezil enhanced the peak amplitude of the P300-like component to target stimuli and evoked slow theta and gamma oscillations, whereas scopolamine altered the amplitude of the P300-like component and EROs to target stimuli. Pretreatment with donepezil attenuated effects of scopolamine on the peak amplitude of the P300-like component and on EROs. This study provides evidence that AEP P300-like responses can be elicited by rats engaged in attentive and memory processing of target stimuli and outline the relevance of the cholinergic system in stimulus discrimination processing. The findings highlight the sensitivity of this translational index for investigating brain circuits and/or novel pharmacological agents, which modulate cholinergic transmission associated with increased allocation of attentional resources.
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Luberadzka, Joanna, Hendrik Kayser, and Volker Hohmann. "Making sense of periodicity glimpses in a prediction-update-loop—A computational model of attentive voice tracking." Journal of the Acoustical Society of America 151, no. 2 (February 2022): 712–37. http://dx.doi.org/10.1121/10.0009337.
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Humans are able to follow a speaker even in challenging acoustic conditions. The perceptual mechanisms underlying this ability remain unclear. A computational model of attentive voice tracking, consisting of four computational blocks: (1) sparse periodicity-based auditory features (sPAF) extraction, (2) foreground-background segregation, (3) state estimation, and (4) top-down knowledge, is presented. The model connects the theories about auditory glimpses, foreground-background segregation, and Bayesian inference. It is implemented with the sPAF, sequential Monte Carlo sampling, and probabilistic voice models. The model is evaluated by comparing it with the human data obtained in the study by Woods and McDermott [Curr. Biol. 25(17), 2238–2246 (2015)], which measured the ability to track one of two competing voices with time-varying parameters [fundamental frequency ( F0) and formants ( F1, F2)]. Three model versions were tested, which differ in the type of information used for the segregation: version (a) uses the oracle F0, version (b) uses the estimated F0, and version (c) uses the spectral shape derived from the estimated F0 and oracle F1 and F2. Version (a) simulates the optimal human performance in conditions with the largest separation between the voices, version (b) simulates the conditions in which the separation in not sufficient to follow the voices, and version (c) is closest to the human performance for moderate voice separation.
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Seedat, Mohamed. "Psychology and humanism in the democratic South African imagination." South African Journal of Psychology 47, no. 4 (December 2017): 520–30. http://dx.doi.org/10.1177/0081246317737943.
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Attentive to a psychology underlying South Africa’s democratic imaginations, I describe how Nelson Mandela’s intervention at a critical moment of conflict management, along with mechanisms such as at the Truth and Reconciliation Commission and the Moral Regeneration Movement, invoked and enacted a humanising ethos. Centred on the ideas of restraint, empathy, emotional proximity, witnessing, and fluid generative subjectivities, the humanising ethos was awakened to support the process of reconciliation, social justice, and the making of inclusive and socially just communities. Inspired by a decolonial attitude, and in part successfully enacted in support of the country’s liberal democratic ideals, the elaboration of this psychology has been limited by ongoing socio-economic disparities and a ruling psychology that naturalises extractive relations.
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Weng, Weihao, Xin Zhu, Lei Jing, and Mianxiong Dong. "Attention Mechanism Trained with Small Datasets for Biomedical Image Segmentation." Electronics 12, no. 3 (January 29, 2023): 682. http://dx.doi.org/10.3390/electronics12030682.
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The understanding of long-range pixel–pixel dependencies plays a vital role in image segmentation. The use of a CNN plus an attention mechanism still has room for improvement, since existing transformer-based architectures require many thousands of annotated training samples to model long-range spatial dependencies. This paper presents a smooth attention branch (SAB), a novel architecture that simplifies the understanding of long-range pixel–pixel dependencies for biomedical image segmentation in small datasets. The SAB is essentially a modified attention operation that implements a subnetwork via reshaped feature maps instead of directly calculating a softmax value over the attention score for each input. The SAB fuses multilayer attentive feature maps to learn visual attention in multilevel features. We also introduce position blurring and inner cropping specifically for small-scale datasets to prevent overfitting. Furthermore, we redesign the skip pathway for the reduction of the semantic gap between every captured feature of the contracting and expansive path. We evaluate the architecture of U-Net with the SAB (SAB-Net) by comparing it with the original U-Net and widely used transformer-based models across multiple biomedical image segmentation tasks related to the Brain MRI, Heart MRI, Liver CT, Spleen CT, and Colonoscopy datasets. Our training set was made of random 100 images of the original training set, since our goal was to adopt attention mechanisms for biomedical image segmentation tasks with small-scale labeled data. An ablation study conducted on the brain MRI test set demonstrated that every proposed method achieved an improvement in biomedical image segmentation. Integrating the proposed methods helped the resulting models consistently achieve outstanding performance on the above five biomedical segmentation tasks. In particular, the proposed method with U-Net improved its segmentation performance over that of the original U-Net by 13.76% on the Brain MRI dataset. We proposed several novel methods to address the need for modeling long-range pixel–pixel dependencies in small-scale biomedical image segmentation. The experimental results illustrated that each method could improve the medical image segmentation accuracy to various degrees. Moreover, SAB-Net, which integrated all proposed methods, consistently achieved outstanding performance on the five biomedical segmentation tasks.
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Shuwairi, Sarah M., Clayton E. Curtis, and Scott P. Johnson. "Neural Substrates of Dynamic Object Occlusion." Journal of Cognitive Neuroscience 19, no. 8 (August 2007): 1275–85. http://dx.doi.org/10.1162/jocn.2007.19.8.1275.
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In everyday environments, objects frequently go out of sight as they move and our view of them becomes obstructed by nearer objects, yet we perceive these objects as continuous and enduring entities. Here, we used functional magnetic resonance imaging with an attentive tracking paradigm to clarify the nature of perceptual and cognitive mechanisms subserving this ability to fill in the gaps in perception of dynamic object occlusion. Imaging data revealed distinct regions of cortex showing increased activity during periods of occlusion relative to full visibility. These regions may support active maintenance of a representation of the target's spatiotemporal properties ensuring that the object is perceived as a persisting entity when occluded. Our findings may shed light on the neural substrates involved in object tracking that give rise to the phenomenon of object permanence.
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Barnett, Michael. "Evolution Without Progress? Humanitarianism in a World of Hurt." International Organization 63, no. 4 (October 2009): 621–63. http://dx.doi.org/10.1017/s0020818309990087.
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AbstractMany theories of international relations contain a narrative of progress and explain that progress with reference to evolutionary imagery. This article examines critically: the relevance of Darwinian and Lamarckian models of international relations to the evolution of international ethics and institutions; and the possibility that the ethics and norms are likely to be more consistent with existing world orders than challengers to it. Specifically, this article draws from evolutionary social science and organizational theory to develop a framework to explore the initial diversity of the meaning and practices of humanitarianism; how the combination of environmental mechanisms and organizational culture led many humanitarian agencies to adapt to their environment in ways that incorporated politics; and the subsequent countermovement by some agencies who wanted to purify humanitarianism. I then apply this framework to explain the recent history of four international aid agencies. I conclude with several observations regarding how the model as applied to these cases allows us to examine critically the selection mechanisms that do and do not account for ethical change and how scholars of international norms, ethics, and progress should be attentive to how principled actors are creatures of the world they want to transform.
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Davtian, Elena N., Stepan E. Davtian, and Elena V. Uryson. "Clinical diagnostics in psychiatry — empirical and theoretical levels of knowledge (on the example of analysis of a written text)." Neurology Bulletin LII, no. 3 (January 26, 2021): 70–75. http://dx.doi.org/10.17816/nb33875.
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The paper shows correlation of empirical and theoretical levels of knowledge in psychiatry by analyzing a single text written by a patient. The patients text is analyzed three times. The first analysis performed by a linguist demonstrates how informative for a clinician can be an attentive attitude to the patients Word. The second analysis is a standard procedure for psychiatric phenomenological diagnostics. It is shown that the formulation of a clinical diagnosis from epistemological positions is equivalent to establishing a scientific fact (completion of empirical research): there is no theoretical modeling of pathological processes in psychiatry today; it all ends at the stage of recognizing the symptoms, without any attempt to understand them. The third analysis demonstrates the advantages in understanding pathological mechanisms provided by the explanatory model (interpretation of the text from the perspective of the bipersonal model of personality).
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Toropygin, A. V. "Economic and Political Aspects of the Serbia — EAEU Free Trade Area." EURASIAN INTEGRATION: economics, law, politics 14, no. 2 (July 9, 2021): 120–31. http://dx.doi.org/10.22394/2073-2929-2021-02-120-131.
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The article is devoted to the analysis of the Serbia — EAEU relations development through the prism of the Agreement on the Free Trade Area (FTA) — between the integration association and the separate economy / country. The purpose of this study is to identify the prospects of the FTA taking into account Serbia’s desire to integrate into the European Union. The author come to the conclusion that intensive interaction, primarily between Serbia and Russia through the FTA between Serbia and the EAEU, is explained, on the one hand, by Serbia’s multi-vector foreign policy, and, on the other hand, by Russia’s attentive attitude to the course of the conflict over Kosovo. Russia has economic interests in this region, as well as the region is people-related value for Russia within which it has used and will intensively utilize of soft power mechanisms.
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Davtian, Elena N., Stepan E. Davtian, and Elena V. Uryson. "Clinical diagnostics in psychiatry — empirical and theoretical levels of knowledge (on the example of analysis of a written text). Part 1." Neurology Bulletin LII, no. 2 (October 19, 2020): 89–96. http://dx.doi.org/10.17816/nb21255.
Full textAbstract:
The paper shows correlation of empirical and theoretical levels of knowledge in psychiatry by analyzing a single text written by a patient. The patients text is analyzed three times. The first analysis performed by a linguist demonstrates how informative for a clinician can be an attentive attitude to the patients Word. The second analysis is a standard procedure for psychiatric phenomenological diagnostics. It is shown that the formulation of a clinical diagnosis from epistemological positions is equivalent to establishing a scientific fact (completion of empirical research): there is no theoretical modeling of pathological processes in psychiatry today; it all ends at the stage of recognizing the symptoms, without any attempt to understand them. The third analysis demonstrates the advantages in understanding pathological mechanisms provided by the explanatory model (interpretation of the text from the perspective of the bipersonal model of personality).
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Chen, Long, Ziyu Guan, Qibin Xu, Qiong Zhang, Huan Sun, Guangyue Lu, and Deng Cai. "Question-Driven Purchasing Propensity Analysis for Recommendation." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 01 (April 3, 2020): 35–42. http://dx.doi.org/10.1609/aaai.v34i01.5331.
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Merchants of e-commerce Websites expect recommender systems to entice more consumption which is highly correlated with the customers' purchasing propensity. However, most existing recommender systems focus on customers' general preference rather than purchasing propensity often governed by instant demands which we deem to be well conveyed by the questions asked by customers. A typical recommendation scenario is: Bob wants to buy a cell phone which can play the game PUBG. He is interested in HUAWEI P20 and asks “can PUBG run smoothly on this phone?” under it. Then our system will be triggered to recommend the most eligible cell phones to him. Intuitively, diverse user questions could probably be addressed in reviews written by other users who have similar concerns. To address this recommendation problem, we propose a novel Question-Driven Attentive Neural Network (QDANN) to assess the instant demands of questioners and the eligibility of products based on user generated reviews, and do recommendation accordingly. Without supervision, QDANN can well exploit reviews to achieve this goal. The attention mechanisms can be used to provide explanations for recommendations. We evaluate QDANN in three domains of Taobao. The results show the efficacy of our method and its superiority over baseline methods.
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Dandala, Bharath, Venkata Joopudi, Ching-Huei Tsou, Jennifer J. Liang, and Parthasarathy Suryanarayanan. "Extraction of Information Related to Drug Safety Surveillance From Electronic Health Record Notes: Joint Modeling of Entities and Relations Using Knowledge-Aware Neural Attentive Models." JMIR Medical Informatics 8, no. 7 (July 10, 2020): e18417. http://dx.doi.org/10.2196/18417.
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Background An adverse drug event (ADE) is commonly defined as “an injury resulting from medical intervention related to a drug.” Providing information related to ADEs and alerting caregivers at the point of care can reduce the risk of prescription and diagnostic errors and improve health outcomes. ADEs captured in structured data in electronic health records (EHRs) as either coded problems or allergies are often incomplete, leading to underreporting. Therefore, it is important to develop capabilities to process unstructured EHR data in the form of clinical notes, which contain a richer documentation of a patient’s ADE. Several natural language processing (NLP) systems have been proposed to automatically extract information related to ADEs. However, the results from these systems showed that significant improvement is still required for the automatic extraction of ADEs from clinical notes. Objective This study aims to improve the automatic extraction of ADEs and related information such as drugs, their attributes, and reason for administration from the clinical notes of patients. Methods This research was conducted using discharge summaries from the Medical Information Mart for Intensive Care III (MIMIC-III) database obtained through the 2018 National NLP Clinical Challenges (n2c2) annotated with drugs, drug attributes (ie, strength, form, frequency, route, dosage, duration), ADEs, reasons, and relations between drugs and other entities. We developed a deep learning–based system for extracting these drug-centric concepts and relations simultaneously using a joint method enhanced with contextualized embeddings, a position-attention mechanism, and knowledge representations. The joint method generated different sentence representations for each drug, which were then used to extract related concepts and relations simultaneously. Contextualized representations trained on the MIMIC-III database were used to capture context-sensitive meanings of words. The position-attention mechanism amplified the benefits of the joint method by generating sentence representations that capture long-distance relations. Knowledge representations were obtained from graph embeddings created using the US Food and Drug Administration Adverse Event Reporting System database to improve relation extraction, especially when contextual clues were insufficient. Results Our system achieved new state-of-the-art results on the n2c2 data set, with significant improvements in recognizing crucial drug−reason (F1=0.650 versus F1=0.579) and drug−ADE (F1=0.490 versus F1=0.476) relations. Conclusions This study presents a system for extracting drug-centric concepts and relations that outperformed current state-of-the-art results and shows that contextualized embeddings, position-attention mechanisms, and knowledge graph embeddings effectively improve deep learning–based concepts and relation extraction. This study demonstrates the potential for deep learning–based methods to help extract real-world evidence from unstructured patient data for drug safety surveillance.
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Morse, Yonatan L. "The legislature as political control: change and continuity in Cameroon's National Assembly (1973–2019)." Journal of Modern African Studies 59, no. 4 (December 2021): 485–506. http://dx.doi.org/10.1017/s0022278x21000288.
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abstractA growing literature has begun to more closely examine African legislatures. However, most of this research has been attentive to emerging democratic settings, and particularly the experiences of a select number of English-speaking countries. By contrast, Cameroon is a Francophone majority country that reintroduced multiparty politics in the early 1990s but continues to exhibit significant authoritarian tendencies. This article provides a longitudinal analysis of Cameroon's National Assembly and builds on a unique biographical dataset of over 900 members of parliament between 1973 and 2019. The article describes changes in the structure and orientation of the legislature as well as the social profile of its members, in particular following the transition to multipartyism. While the legislature in Cameroon remains primarily a tool of political control, it is more dynamic, and the mechanisms used to manage elites within the context of complex multiethnic politics have evolved.
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Prudkov, Pavel N., and Olga N. Rodina. "On Altruism Toward Nonhuman Animals." Society & Animals 24, no. 4 (August 18, 2016): 321–36. http://dx.doi.org/10.1163/15685306-12341419.
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The authors studied the motivation of nonhuman animal protectors engaged in caring for homeless animals. They were compared with individuals not involved in this activity. There were two hypotheses regarding the motivation. One hypothesis proposed animal protection is a substitute for people not satisfied with their family life and/or work. Another hypothesis suggested personality traits made some individuals attentive to the plight of humans and animals. The authors gathered demographic information and used an inventory on altruism toward humans and animals. There were no distinctions in demographics. The factor analysis of the inventory revealed two factors. One factor was altruism toward animals and another factor was altruism toward humans. Animal protectors scored high on the first factor and low on the second. Non-animal protectors demonstrated the opposite distribution of scores. This is inconsistent with the second hypothesis. Altruism toward animals and altruism toward humans may result from different mechanisms.
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Xiao Lei, 肖蕾, and 蓝宗苗 Lan Zongmiao. "基于注意力机制的污水微型动物识别方法." Laser & Optoelectronics Progress 60, no. 2 (2023): 0215002. http://dx.doi.org/10.3788/lop212628.
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Ekusheva, E. V., and A. A. Komazov. "Chronic pain in elderly patients." Medical alphabet, no. 3 (March 28, 2021): 43–47. http://dx.doi.org/10.33667/2078-5631-2021-3-43-47.
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The purpose. The article is devoted to chronic pain (CP) in elderly patients and the possibilities of various therapeutic strategies for this category of patients.Basic provisions. Chronic pain and the biological aging process have similar pathophysiological (cellular and molecular) mechanisms of development. However, chronic pain is not an inevitable component of the aging process, however, it is much more common in older people, the diagnosis and therapy of which is associated with atypical clinical manifestations of pain in elderly patients and the need for a more attentive, balanced approach when assessing pharmacokinetic and pharmacodynamic changes associated with the aging process. To ensure adequate pain relief, a multidisciplinary approach and appropriate therapies are used.Conclusion. The final result of CP treatment (reduction in pain intensity, restoration of functional activity, autonomy, etc.) depends on polymorbidity, geriatric status and cognitive capabilities of the patient; therefore, it is necessary to take into account all available factors for adequate and complete pain therapy.