Journal articles on the topic 'Sequential controlled sensing'

A 1,2,3-triazole-based chemosensor is used for selective switching in logic gate operations through colorimetric and fluorometric response mechanisms. The molecular probe synthesized via “click chemistry” resulted in a non-fluorescent 1,4-diaryl-1,2,3-triazole with a phenol moiety (PTP). However, upon sensing fluoride, it TURNS ON the molecule’s fluorescence. The TURN-OFF order occurs through fluorescence quenching of the sensor when metal ions, e.g., Cu2+, and Zn2+, are added to the PTP-fluoride ensemble. A detailed characterization using Nuclear Magnetic Resonance (NMR) spectroscopy in a sequential titration study substantiated the photophysical characteristics of PTP through UV-Vis absorption and fluorescence profiles. A combination of fluorescence OFF-ON-OFF sequences provides evidence of 1,2,3-triazoles being controlled switches applicable to multimodal logic operations. The “INH” gate was constructed based on the fluorescence output of PTP when the inputs are F− and Zn2+. The “IMP” and “OR” gates were created on the colorimetric output responses using the probe’s absorption with multiple inputs (F− and Zn2+ or Cu2+). The PTP sensor is the best example of the “Write-Read-Erase-Read” mimic.

An optical real-time pneumatic-and-centrifugal controlled microfluidic detection system for dynamic information acquisition is developed based on the quasi-stationary imaging technique. The programmable airflow applied on the centrifugal microstructures for improving efficiency in samples separation. The dynamic characteristic of a loaded disc is stable with vibrating under 0.3 mm at a speed of 1000 rpm by applying 3 bar-induced pneumatic forces on a 12 cm-diameter disc. A conversion model for converting RGB images into CIEL*a*b*color space have been used to enhance the inspection images. A linear relationship between threshold frequency and sample density is 167 rpm/g/cm3. The pressures between 0.1 and 0.5 bars are applied to bias microflow from 15° to 80°. The conduction angles between 30° and 90° have better pneumatic control. The control efficiency observed up to 89% and the largest microflow biased angle reached 80°. The pneumatic force dominates microfluidic behaviors when the force is greater than 10 times the centrifugal force. A sequential of triple-reservoir tests has been verified by analyzing enhanced optical images in separation using arranged acid-base indicators for pH reactions.

ABSTRACT Vibrio fischeri possesses two quorum-sensing systems, ain and lux, using acyl homoserine lactones as signaling molecules. We have demonstrated previously that the ain system activates luminescence gene expression at lower cell densities than those required for lux system activation and that both systems are essential for persistent colonization of the squid host, Euprymna scolopes. Here, we asked whether the relative contributions of the two systems are also important at different colonization stages. Inactivation of ain, but not lux, quorum-sensing genes delayed initiation of the symbiotic relationship. In addition, our data suggest that lux quorum sensing is not fully active in the early stages of colonization, implying that this system is not required until later in the symbiosis. The V. fischeri luxI mutant does not express detectable light levels in symbiosis yet initiates colonization as well as the wild type, suggesting that ain quorum sensing regulates colonization factors other than luminescence. We used a recently developed V. fischeri microarray to identify genes that are controlled by ain quorum sensing and could be responsible for the initiation defect. We found 30 differentially regulated genes, including the repression of a number of motility genes. Consistent with these data, ain quorum-sensing mutants displayed an altered motility behavior in vitro. Taken together, these data suggest that the sequential activation of these two quorum-sensing systems with increasing cell density allows the specific regulation of early colonization factors (e.g., motility) by ain quorum sensing, whereas late colonization factors (e.g., luminescence) are preferentially regulated by lux quorum sensing.

The assembly of artificial nanostructured and microstructured materials which display structures and functionalities that mimic nature’s complexity requires building blocks with specific and directional interactions, analogous to those displayed at the molecular level. Despite remarkable progress in synthesizing “patchy” particles encoding anisotropic interactions, most current methods are restricted to integrating up to two compositional patches on a single “molecule” and to objects with simple shapes. Currently, decoupling functionality and shape to achieve full compositional and geometrical programmability remains an elusive task. We use sequential capillarity-assisted particle assembly which uniquely fulfills the demands described above. This is a new method based on simple, yet essential, adaptations to the well-known capillary assembly of particles over topographical templates. Tuning the depth of the assembly sites (traps) and the surface tension of moving droplets of colloidal suspensions enables controlled stepwise filling of traps to “synthesize” colloidal molecules. After deposition and mechanical linkage, the colloidal molecules can be dispersed in a solvent. The template’s shape solely controls the molecule’s geometry, whereas the filling sequence independently determines its composition. No specific surface chemistry is required, and multifunctional molecules with organic and inorganic moieties can be fabricated. We demonstrate the “synthesis” of a library of structures, ranging from dumbbells and triangles to units resembling bar codes, block copolymers, surfactants, and three-dimensional chiral objects. The full programmability of our approach opens up new directions not only for assembling and studying complex materials with single-particle-level control but also for fabricating new microscale devices for sensing, patterning, and delivery applications.

Early sensing of pathogenic bacteria by the host immune system is important to develop effective mechanisms to kill the invader. Microbial recognition, activation of signaling pathways, and effector mechanisms are sequential events that must be highly controlled to successfully eliminate the pathogen. Host recognizes pathogens through pattern-recognition receptors (PRRs) that sense pathogen-associated molecular patterns (PAMPs). Some of these PRRs include Toll-like receptors (TLRs), nucleotide-binding oligomerization domain-like receptors (NLRs), retinoic acid-inducible gene-I- (RIG-I-) like receptors (RLRs), and C-type lectin receptors (CLRs). TLRs and NLRs are PRRs that play a key role in recognition of extracellular and intracellular bacteria and control the inflammatory response. The activation of TLRs and NLRs by their respective ligands activates downstream signaling pathways that converge on activation of transcription factors, such as nuclear factor-kappaB (NF-κB), activator protein-1 (AP-1) or interferon regulatory factors (IRFs), leading to expression of inflammatory cytokines and antimicrobial molecules. The goal of this review is to discuss how the TLRs and NRLs signaling pathways collaborate in a cooperative or synergistic manner to counteract the infectious agents. A deep knowledge of the biochemical events initiated by each of these receptors will undoubtedly have a high impact in the design of more effective strategies to control inflammation.

The type IV pili (T4P) system is a supermolecular machine observed in prokaryotes. Cells repeat the cycle of T4P extension, surface attachment, and retraction to drive twitching motility. Although the properties of T4P as a motor have been scrutinized with biophysics techniques, the mechanism of regulation remains unclear. Here we provided the framework of the T4P dynamics at the single-cell level inSynechocystissp. PCC6803, which can recognize light direction. We demonstrated that the dynamics was detected by fluorescent beads under an optical microscope and controlled by blue light that induces negative phototaxis; extension and retraction of T4P was activated at the forward side of lateral illumination to move away from the light source. Additionally, we directly visualized each pilus by fluorescent labeling, allowing us to quantify their asymmetric distribution. Finally, quantitative analyses of cell tracking indicated that T4P was generated uniformly within 0.2 min after blue-light exposure, and within the next 1 min the activation became asymmetric along the light axis to achieve directional cell motility; this process was mediated by the photo-sensing protein, PixD. This sequential process provides clues toward a general regulation mechanism of T4P system, which might be essentially common between archaella and other secretion apparatuses.

Dynamic Controlled Atmosphere (DCA) is beneficial in maintaining specific quality parameters but, due to the extreme oxygen levels applied, can cause adverse effects on the fruit by inducing excessive anaerobic metabolism and the production of off-flavors. The metabolic adaptation and responses of apples (Malus domestica Borkh.) cv. Red Delicious to static or dynamic oxygen concentrations (0.3 and 0.8%, with sequential shifts) during cold storage for 7 months were studied by monitoring quality parameters and the expression of genes involved in sugar, fermentative metabolism, and ethylene physiology. Ethanol content reached the highest levels (around 400 mg/kg FW) under 0.3% oxygen concentration and fruit firmness appeared to be reduced in samples accumulating the highest levels of ethanol. Oxygen switch was effective in reducing the ethanol concentrations with timing-dependent variable effects. The expression of fermentative (alcohol dehydrogenase, lactate dehydrogenase, pyruvate decarboxylase) and sugar metabolism (β-amylase; phosphofructokinase; sucrose synthase) genes resulted to be differently affected by the hypoxic conditions imposed, in particular during the early stages of storage. Sucrose synthase expression appeared to be highly sensitive to changes in low oxygen concentration. Ethylene biosynthesis (ACC synthase and oxidase) genes showed marked differences in their expression in relation to the static and dynamic protocols and the hypoxic conditions, as well as six Ethylene Responsive Factors (ERF) genes, some of them possibly involved in the oxygen sensing mechanism operating in fruit tissues.

<p>The increasing negative effects of climate change and the emergence of invasive species in forests around the world require the development of innovative methods to monitor and quantitatively measure the health status of woodlands. These effects are especially notable in the Mediterranean area, where the decline of stands due to recurrent droughts has increased the damage caused by secondary pests whose populations would otherwise be in balance. Remote sensing technologies allow us to work on large surfaces with reasonable precision. In particular, new spectral indices obtained from high-resolution hyperspectral and thermal images have been shown to be good predictors for the early detection of physiological changes related to diseases. In this pilot study developed in a stand of Pinus halepensis in the Comunitat Valenciana, a controlled simulation of a decay is carried out by means of sequential girdling of trees, making a subsequent field monitoring of the caused decay. Through a hyperspectral camera, the spectral information of each of these trees is analyzed in relation to their discoloration and state of observed decay. The proposed methodology allows the detection of affected trees three months before the appearance of visual symptoms, obtaining a precision higher than 0.9 with Random Forest and Support Vector Machine classifiers. The vegetation indices with better results were PRI, VGO1, VGO2, GM1 and OSAVI. This pilot study allows us to think that some of these indices can be used in the early detection of general pine wilt and, therefore, have application in the monitoring of the main threats to European forests, borer pests or quarantine organisms such as <em>Bursaphelenchus xylophilus.</em></p>

Abstract Results are presented from a decade-long assimilation run with a 64-member OGCM ensemble in a global configuration. The assimilation system can be used to produce ocean initial conditions for seasonal forecasts. The ensemble is constructed with the Max Planck Institute Ocean Model, where each member is forced by differently perturbed 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis atmospheric fields over sequential 10-day intervals. Along-track altimetric data from the European Remote Sensing and the Ocean Topography Experiment (TOPEX)/Poseidon satellites, as well as quality-controlled subsurface temperature and salinity profiles, are subsequently assimilated using the standard formulation of the ensemble Kalman filter. The applied forcing perturbation method and data selection and processing procedures are described, as well as a framework for the construction of appropriate data constraint error models for all three data types. The results indicate that the system is stable, does not experience a tendency toward ensemble collapse, and provides smooth analyses that are closer to withheld data than an unconstrained control run. Subsurface bias and time-dependent errors are reduced by the assimilation but not entirely removed. Time series of assimilation and ensemble statistics also indicate that the model is not very strongly constrained by the data because of an overspecification of the data errors. A comparison of equatorial zonal velocity profiles with in situ current meter data shows mixed results. A shift in the time-mean profile in the central Pacific is primarily associated with an assimilation-induced bias. The use of an adaptive bias correction scheme is suggested as a solution to this problem.

Any real-time control application run by a digital computer (or any sequential machine) demands a very fast processor in order to make the time-lag from data sensing to issuance of a control action closest to zero. In some instances, the algorithm used requires a relatively large primary memory which is crucial especially when implemented in a microcontroller. This paper presents a novel implementation of a multi-output fuzzy controller (which is known in this paper as MultiOFuz), which utilizes lesser memory and executes faster than a type of an existing multiple single-output fuzzy logic controllers. The design and implementation of the developed controller employed the object-oriented approach with program level code optimizations. MultiOFuz is a reusable software component and the simplicity of how to interface this to control applications is presented. Comparative analyses of algorithms, memory usage and simulations are presented to support our claim of increased efficiency in both execution time and storage use. Future directions of MultiOFuz are also discussed.

SUMMARYWe present the synthesis and analysis of distributed ensemble control policies to enable a team of robots to control their distribution across a collection of tasks. We assume that individual robot controllers are modeled as a sequential composition of individual task controllers. A macroscopic description of the team dynamics is then used to synthesize ensemble feedback control strategies that maintain the desired distribution of robots across the tasks. We present a distributed implementation of the ensemble feedback strategy that can be implemented with minimal communication requirements. Different from existing strategies, the approach results in individual robot control policies that maintain the desired mean and the variance of the robot populations at each task. We present the stability properties of the ensemble feedback strategy, verify the feasibility of the distributed ensemble controller through high-fidelity simulations, and examine the robustness of the strategy to sensing and/or actuation failures. Specifically, we consider the case when robots are subject to estimation and navigation errors resulting from lossy inter-agent wireless communication links and localization errors.

In thermal manufacturing processes performed by a localized, sequentially moving heat source, simultaneous regulation of multiple thermal quality characteristics requires real-time control of the temperature field developed through the distributed heat input on the part surface. Such control of the thermal field to a desired distribution employs infrared sensing and feedback of the surface temperature hill, to modulate the torch power and motion in-process. The torch trajectory is guided in real time by an efficient optimization algorithm based on the concept of moving complexes. This distributed-parameter control strategy is developed using a numerical simulation model of thermal processing, and its performance is evaluated experimentally in heat treatment of thin stainless steel plates. The thermal controller is applied to the new scan welding process, in which it drives the torch in a reciprocating motion along the weld, yielding a uniform and smooth temperature field, and thus a favorable material structure and mechanical properties. Application of such thermal control to various other material processing methods is also investigated.

An on-line identification and control algorithm is developed based on the properties of collocated sensing and actuation. The feedback control law consists of second-order compensators that achieve equivalent damping in both the filter dynamics and resonant structural dynamics, thus maximizing the damping in the structure and controller. Optimal design of the feedback compensator is obtained using a pole placement algorithm applied to a single, undamped resonant mode. Numerical analysis indicates that multiple modes and structural damping do not appreciably change the damping achieved using the optimal parameters. The pole placement analysis demonstrates that only the pole-zero spacing and DC gain of the collocated transfer function are required to choose the optimal parameters. An on-line identification procedure is developed that sequentially determines the DC gain and pole-zero spacing and automatically designs the feedback compensator. This forms the basis for the autonomous control algorithm. Experimental results on a flexible beam demonstrate that the procedure can accurately identify the pole-zero spacing and automatically design the feedback compensator. A fivefold increase in damping is achieved in the first mode and a twofold increase in damping is achieved in the second mode. Discrepancies between predicted and measured damping are attributed to phase lags due to signal conditioning and low-pass filtering of the sensor signal.

Methane (CH4) display spectral features in several regions of the infrared range (0.75–14 µm), which can be used for the remote mapping of emission sources through the detection of CH4 plumes from natural seeps and leaks. Applications of hyperspectral remote sensing techniques for the detection of CH4 in the near and shortwave infrared (NIR-SWIR: 0.75–3 µm) and longwave infrared (LWIR: 7–14 µm) have been demonstrated in the literature with multiple sensors and scenarios. However, the acquisition and processing of hyperspectral data in the midwave infrared (MWIR: 3–5 µm) for this application is rather scarce. Here, a controlled field experiment was used to evaluate the potential for CH4 plume detection in the MWIR based on hyperspectral data acquired with the SEBASS airborne sensor. For comparison purposes, LWIR data were also acquired simultaneously with the same instrument. The experiment included surface and undersurface emission sources (ground stations), with flow rates ranging between 0.6–40 m3/h. The data collected in both ranges were sequentially processed using the same methodology. The CH4 plume was detected, variably, in both datasets. The gas plume was detected in all LWIR images acquired over nine gas leakage stations. In the MWIR range, the plume was detected in only four stations, wherein 18 m3/h was the lowest flux sensed. We demonstrate that the interference of target reflectance, the low contrast between plume and background and a low signal of the CH4 feature in the MWIR at ambient conditions possibly explain the inferior results observed for this range when compared to LWIR. Furthermore, we show that the acquisition time and weather conditions, including specific limits of temperature, humidity, and wind speed, proved critical for plume detection using daytime MWIR hyperspectral data.

Abstract. To investigate the atmospheric aerosols of the Himalayas and Tibetan Plateau (HTP), an observation network was established within the region's various ecosystems, including at the Ngari, Qomolangma (QOMS), Nam Co, and Southeastern Tibetan (SET) stations. In this paper we illustrate aerosol mass loadings by integrating in situ measurements with satellite and ground-based remote sensing datasets for the 2011–2013 period, on both local and large scales. Mass concentrations of these surface atmospheric aerosols were relatively low and varied with land cover, showing a general tendency of Ngari and QOMS (barren sites) > Nam Co (grassland site) > SET (forest site). Daily averages of online PM2.5 (particulates with aerodynamic diameters below 2.5 µm) at these sites were sequentially 18.2 ± 8.9, 14.5 ± 7.4, 11.9 ± 4.9 and 11.7 ± 4.7 µg m−3. Correspondingly, the ratios of PM2.5 to total suspended particles (TSP) were 27.4 ± 6.65, 22.3 ± 10.9, 37.3 ± 11.1 and 54.4 ± 6.72 %. Bimodal mass distributions of size-segregated particles were found at all sites, with a relatively small peak in accumulation mode and a more notable peak in coarse mode. Diurnal variations in fine-aerosol masses generally displayed a bi-peak pattern at the QOMS, Nam Co and SET stations and a single-peak pattern at the Ngari station, controlled by the effects of local geomorphology, mountain-valley breeze circulation and aerosol emissions. Dust aerosol content in PM2.1 samples gave fractions of 26 % at the Ngari station and 29 % at the QOMS station, or ∼ 2–3 times that of reported results at human-influenced sites. Furthermore, observed evidence confirmed the existence of the aerodynamic conditions necessary for the uplift of fine particles from a barren land surface. Combining surface aerosol data and atmospheric-column aerosol optical properties, the TSP mass and aerosol optical depth (AOD) of the Multi-angle Imaging Spectroradiometer (MISR) generally decreased as land cover changed from barren to forest, in inverse relation to the PM2.5 ratios. The seasonality of aerosol mass parameters was land-cover dependent. Over forest and grassland areas, TSP mass, PM2.5 mass, MISR-AOD and fine-mode AOD were higher in spring and summer, followed by relatively lower values in autumn and winter. At the barren site (the QOMS station), there were inconsistent seasonal patterns between surface TSP mass (PM2.5 mass) and atmospheric column AOD (fine-mode AOD). Our findings implicate that HTP aerosol masses (especially their regional characteristics and fine-particle emissions) need to be treated sensitively in relation to assessments of their climatic effect and potential role as cloud condensation nuclei and ice nuclei.

Internet of Things (IoT) is regarded as a next-generation wave of Information Technology (IT) after the widespread emergence of the Internet and mobile communication technologies. IoT supports information exchange and networked interaction of appliances, vehicles and other objects, making sensing and actuation possible in a low-cost and smart manner. On the other hand, cyber-physical systems (CPS) are described as the engineered systems which are built upon the tight integration of the cyber entities (e.g., computation, communication, and control) and the physical things (natural and man-made systems governed by the laws of physics). The IoT and CPS are not isolated technologies. Rather it can be said that IoT is the base or enabling technology for CPS and CPS is considered as the grownup development of IoT, completing the IoT notion and vision. Both are merged into closed-loop, providing mechanisms for conceptualizing, and realizing all aspects of the networked composed systems that are monitored and controlled by computing algorithms and are tightly coupled among users and the Internet. That is, the hardware and the software entities are intertwined, and they typically function on different time and location-based scales. In fact, the linking between the cyber and the physical world is enabled by IoT (through sensors and actuators). CPS that includes traditional embedded and control systems are supposed to be transformed by the evolving and innovative methodologies and engineering of IoT. Several applications areas of IoT and CPS are smart building, smart transport, automated vehicles, smart cities, smart grid, smart manufacturing, smart agriculture, smart healthcare, smart supply chain and logistics, etc. Though CPS and IoT have significant overlaps, they differ in terms of engineering aspects. Engineering IoT systems revolves around the uniquely identifiable and internet-connected devices and embedded systems; whereas engineering CPS requires a strong emphasis on the relationship between computation aspects (complex software) and the physical entities (hardware). Engineering CPS is challenging because there is no defined and fixed boundary and relationship between the cyber and physical worlds. In CPS, diverse constituent parts are composed and collaborated together to create unified systems with global behaviour. These systems need to be ensured in terms of dependability, safety, security, efficiency, and adherence to real‐time constraints. Hence, designing CPS requires knowledge of multidisciplinary areas such as sensing technologies, distributed systems, pervasive and ubiquitous computing, real-time computing, computer networking, control theory, signal processing, embedded systems, etc. CPS, along with the continuous evolving IoT, has posed several challenges. For example, the enormous amount of data collected from the physical things makes it difficult for Big Data management and analytics that includes data normalization, data aggregation, data mining, pattern extraction and information visualization. Similarly, the future IoT and CPS need standardized abstraction and architecture that will allow modular designing and engineering of IoT and CPS in global and synergetic applications. Another challenging concern of IoT and CPS is the security and reliability of the components and systems. Although IoT and CPS have attracted the attention of the research communities and several ideas and solutions are proposed, there are still huge possibilities for innovative propositions to make IoT and CPS vision successful. The major challenges and research scopes include system design and implementation, computing and communication, system architecture and integration, application-based implementations, fault tolerance, designing efficient algorithms and protocols, availability and reliability, security and privacy, energy-efficiency and sustainability, etc. It is our great privilege to present Volume 21, Issue 3 of Scalable Computing: Practice and Experience. We had received 30 research papers and out of which 14 papers are selected for publication. The objective of this special issue is to explore and report recent advances and disseminate state-of-the-art research related to IoT, CPS and the enabling and associated technologies. The special issue will present new dimensions of research to researchers and industry professionals with regard to IoT and CPS. Vivek Kumar Prasad and Madhuri D Bhavsar in the paper titled "Monitoring and Prediction of SLA for IoT based Cloud described the mechanisms for monitoring by using the concept of reinforcement learning and prediction of the cloud resources, which forms the critical parts of cloud expertise in support of controlling and evolution of the IT resources and has been implemented using LSTM. The proper utilization of the resources will generate revenues to the provider and also increases the trust factor of the provider of cloud services. For experimental analysis, four parameters have been used i.e. CPU utilization, disk read/write throughput and memory utilization. Kasture et al. in the paper titled "Comparative Study of Speaker Recognition Techniques in IoT Devices for Text Independent Negative Recognition" compared the performance of features which are used in state of art speaker recognition models and analyse variants of Mel frequency cepstrum coefficients (MFCC) predominantly used in feature extraction which can be further incorporated and used in various smart devices. Mahesh Kumar Singh and Om Prakash Rishi in the paper titled "Event Driven Recommendation System for E-Commerce using Knowledge based Collaborative Filtering Technique" proposed a novel system that uses a knowledge base generated from knowledge graph to identify the domain knowledge of users, items, and relationships among these, knowledge graph is a labelled multidimensional directed graph that represents the relationship among the users and the items. The proposed approach uses about 100 percent of users' participation in the form of activities during navigation of the web site. Thus, the system expects under the users' interest that is beneficial for both seller and buyer. The proposed system is compared with baseline methods in area of recommendation system using three parameters: precision, recall and NDGA through online and offline evaluation studies with user data and it is observed that proposed system is better as compared to other baseline systems. Benbrahim et al. in the paper titled "Deep Convolutional Neural Network with TensorFlow and Keras to Classify Skin Cancer" proposed a novel classification model to classify skin tumours in images using Deep Learning methodology and the proposed system was tested on HAM10000 dataset comprising of 10,015 dermatoscopic images and the results observed that the proposed system is accurate in order of 94.06\% in validation set and 93.93\% in the test set. Devi B et al. in the paper titled "Deadlock Free Resource Management Technique for IoT-Based Post Disaster Recovery Systems" proposed a new class of techniques that do not perform stringent testing before allocating the resources but still ensure that the system is deadlock-free and the overhead is also minimal. The proposed technique suggests reserving a portion of the resources to ensure no deadlock would occur. The correctness of the technique is proved in the form of theorems. The average turnaround time is approximately 18\% lower for the proposed technique over Banker's algorithm and also an optimal overhead of O(m). Deep et al. in the paper titled "Access Management of User and Cyber-Physical Device in DBAAS According to Indian IT Laws Using Blockchain" proposed a novel blockchain solution to track the activities of employees managing cloud. Employee authentication and authorization are managed through the blockchain server. User authentication related data is stored in blockchain. The proposed work assists cloud companies to have better control over their employee's activities, thus help in preventing insider attack on User and Cyber-Physical Devices. Sumit Kumar and Jaspreet Singh in paper titled "Internet of Vehicles (IoV) over VANETS: Smart and Secure Communication using IoT" highlighted a detailed description of Internet of Vehicles (IoV) with current applications, architectures, communication technologies, routing protocols and different issues. The researchers also elaborated research challenges and trade-off between security and privacy in area of IoV. Deore et al. in the paper titled "A New Approach for Navigation and Traffic Signs Indication Using Map Integrated Augmented Reality for Self-Driving Cars" proposed a new approach to supplement the technology used in self-driving cards for perception. The proposed approach uses Augmented Reality to create and augment artificial objects of navigational signs and traffic signals based on vehicles location to reality. This approach help navigate the vehicle even if the road infrastructure does not have very good sign indications and marking. The approach was tested locally by creating a local navigational system and a smartphone based augmented reality app. The approach performed better than the conventional method as the objects were clearer in the frame which made it each for the object detection to detect them. Bhardwaj et al. in the paper titled "A Framework to Systematically Analyse the Trustworthiness of Nodes for Securing IoV Interactions" performed literature on IoV and Trust and proposed a Hybrid Trust model that seperates the malicious and trusted nodes to secure the interaction of vehicle in IoV. To test the model, simulation was conducted on varied threshold values. And results observed that PDR of trusted node is 0.63 which is higher as compared to PDR of malicious node which is 0.15. And on the basis of PDR, number of available hops and Trust Dynamics the malicious nodes are identified and discarded. Saniya Zahoor and Roohie Naaz Mir in the paper titled "A Parallelization Based Data Management Framework for Pervasive IoT Applications" highlighted the recent studies and related information in data management for pervasive IoT applications having limited resources. The paper also proposes a parallelization-based data management framework for resource-constrained pervasive applications of IoT. The comparison of the proposed framework is done with the sequential approach through simulations and empirical data analysis. The results show an improvement in energy, processing, and storage requirements for the processing of data on the IoT device in the proposed framework as compared to the sequential approach. Patel et al. in the paper titled "Performance Analysis of Video ON-Demand and Live Video Streaming Using Cloud Based Services" presented a review of video analysis over the LVS \& VoDS video application. The researchers compared different messaging brokers which helps to deliver each frame in a distributed pipeline to analyze the impact on two message brokers for video analysis to achieve LVS & VoS using AWS elemental services. In addition, the researchers also analysed the Kafka configuration parameter for reliability on full-service-mode. Saniya Zahoor and Roohie Naaz Mir in the paper titled "Design and Modeling of Resource-Constrained IoT Based Body Area Networks" presented the design and modeling of a resource-constrained BAN System and also discussed the various scenarios of BAN in context of resource constraints. The Researchers also proposed an Advanced Edge Clustering (AEC) approach to manage the resources such as energy, storage, and processing of BAN devices while performing real-time data capture of critical health parameters and detection of abnormal patterns. The comparison of the AEC approach is done with the Stable Election Protocol (SEP) through simulations and empirical data analysis. The results show an improvement in energy, processing time and storage requirements for the processing of data on BAN devices in AEC as compared to SEP. Neelam Saleem Khan and Mohammad Ahsan Chishti in the paper titled "Security Challenges in Fog and IoT, Blockchain Technology and Cell Tree Solutions: A Review" outlined major authentication issues in IoT, map their existing solutions and further tabulate Fog and IoT security loopholes. Furthermore, this paper presents Blockchain, a decentralized distributed technology as one of the solutions for authentication issues in IoT. In addition, the researchers discussed the strength of Blockchain technology, work done in this field, its adoption in COVID-19 fight and tabulate various challenges in Blockchain technology. The researchers also proposed Cell Tree architecture as another solution to address some of the security issues in IoT, outlined its advantages over Blockchain technology and tabulated some future course to stir some attempts in this area. Bhadwal et al. in the paper titled "A Machine Translation System from Hindi to Sanskrit Language Using Rule Based Approach" proposed a rule-based machine translation system to bridge the language barrier between Hindi and Sanskrit Language by converting any test in Hindi to Sanskrit. The results are produced in the form of two confusion matrices wherein a total of 50 random sentences and 100 tokens (Hindi words or phrases) were taken for system evaluation. The semantic evaluation of 100 tokens produce an accuracy of 94\% while the pragmatic analysis of 50 sentences produce an accuracy of around 86\%. Hence, the proposed system can be used to understand the whole translation process and can further be employed as a tool for learning as well as teaching. Further, this application can be embedded in local communication based assisting Internet of Things (IoT) devices like Alexa or Google Assistant. Anshu Kumar Dwivedi and A.K. Sharma in the paper titled "NEEF: A Novel Energy Efficient Fuzzy Logic Based Clustering Protocol for Wireless Sensor Network" proposed a a deterministic novel energy efficient fuzzy logic-based clustering protocol (NEEF) which considers primary and secondary factors in fuzzy logic system while selecting cluster heads. After selection of cluster heads, non-cluster head nodes use fuzzy logic for prudent selection of their cluster head for cluster formation. NEEF is simulated and compared with two recent state of the art protocols, namely SCHFTL and DFCR under two scenarios. Simulation results unveil better performance by balancing the load and improvement in terms of stability period, packets forwarded to the base station, improved average energy and extended lifetime.

HighlightsA LiDAR-guided automatic airflow control system for precision sprayers was developed.Three models were built to measure the amount of airflow required for apple trees.The study confirmed that adjusting the fan inlet could control airflow penetration into tree canopies.Results suggest that the system can reduce spray drift and off-target losses. Abstract. The airflow discharged from orchard airblast sprayers is a primary component for successfully carrying spray droplets to the target trees. Because of the variation in orchard tree canopies, control of the airflow to minimize off-target loss during spray application is essential. An automatic airflow control system for precision sprayers was developed to maximize spray droplet coverage on targets and minimize off-target loss while considering the tree canopy densities. The primary component of the system was an iris damper, which was designed as a retrofit attachment on the fan inlet of a three-point airblast intelligent sprayer. A 3D light detection and ranging (LiDAR) sensor was installed at the top of the sprayer to acquire the tree canopy data. A motor was employed to control the damper opening with a micro-controller. To develop the models required for automatic airflow control, field experiments were conducted at three canopy density orchards with different cultivars (GoldRush, Gala, and Fuji). A total of 15 trees (five trees from each cultivar) were randomly selected, and five different damper openings (openings 1, 2, 3, 4, and 5) were tested for each tree. Opening 1 represented the same air inlet as a traditional precision airblast sprayer, while openings 2, 3, 4, and 5 were the sequentially reduced air inlets of the sprayer. A canopy density measurement algorithm was scripted to measure the canopy point density of individual trees. Three models were built to show relationships between (1) tree canopy point densities and airflows; (2) canopy densities and damper openings; and (3) damper opening and motor steps. The combination of the two models (2 &amp; 3) was used to assess the amount of airflow required for a specific canopy density. Field validations for medium and high-density trees showed that the system achieved adequate spray penetration at the top, middle, bottom, back-left, and back-right positions of the tree sections and reduced off-target loss at the ground and edge of next row sections using openings 4 and 2, respectively. However, the mechanical motion of the damper required 3 s to move from minimum to maximum opening, so the average canopy density was recommended to control the airflow. The overall results suggested that the automatic airflow control system could reduce spray drift and off-target losses and improve spray application efficiency in orchards. Keywords: Automation, Canopy sensing, Fan inlet, Precision spraying, Variable rate application.

AbstractStudying chemosensory processing desires precise chemical cue presentation, behavioral response monitoring, and large-scale neuronal activity recording. Here we present Fish-on-Chips, a set of optofluidic tools for highly-controlled chemical delivery while simultaneously imaging behavioral outputs and whole-brain neuronal activities at cellular resolution in larval zebrafish. These include a fluidics-based swimming arena and an integrated microfluidics-light sheet fluorescence microscopy (µfluidics-LSFM) system, both of which utilize laminar fluid flows to achieve spatiotemporally precise chemical cue presentation. To demonstrate the strengths of the platform, we used the navigation arena to reveal binasal input-dependent behavioral strategies that larval zebrafish adopt to evade cadaverine, a death-associated odor. The µfluidics-LSFM system enables sequential presentation of odor stimuli to individual or both nasal cavities separated by only ~100 µm. This allowed us to uncover brainwide neural representations of cadaverine sensing and binasal input summation in the vertebrate model. Fish-on-Chips is readily generalizable and will empower the investigation of neural coding in the chemical senses.

AbstractIn computer vision applications like surveillance and remote sensing, to mention a few, deep learning has had considerable success. Medical imaging still faces a number of difficulties, including intra‐class similarity, a scarcity of training data, and poor contrast skin lesions, notably in the case of skin cancer. An optimisation‐aided deep learning‐based system is proposed for accurate multi‐class skin lesion identification. The sequential procedures of the proposed system start with preprocessing and end with categorisation. The preprocessing step is where a hybrid contrast enhancement technique is initially proposed for lesion identification with healthy regions. Instead of flipping and rotating data, the outputs from the middle phases of the hybrid enhanced technique are employed for data augmentation in the next step. Next, two pre‐trained deep learning models, MobileNetV2 and NasNet Mobile, are trained using deep transfer learning on the upgraded enriched dataset. Later, a dual‐threshold serial approach is employed to obtain and combine the features of both models. The next step was the variance‐controlled Marine Predator methodology, which the authors proposed as a superior optimisation method. The top features from the fused feature vector are classified using machine learning classifiers. The experimental strategy provided enhanced accuracy of 94.4% using the publicly available dataset HAM10000. Additionally, the proposed framework is evaluated compared to current approaches, with remarkable results.

ABSTRACT Bacillus thuringiensis is a Gram-positive spore-forming bacterium pathogenic to various insect species. This property is due to the Cry toxins encoded by plasmid genes and mostly produced during sporulation. B. thuringiensis contains a remarkable number of extrachromosomal DNA molecules and a great number of plasmid rap-phr genes. Rap-Phr quorum-sensing systems regulate different bacterial processes, notably the commitment to sporulation in Bacillus species. Rap proteins are quorum sensors acting as phosphatases on Spo0F, an intermediate of the sporulation phosphorelay, and are inhibited by Phr peptides that function as signaling molecules. In this study, we characterize the Rap63-Phr63 system encoded by the pAW63 plasmid from the B. thuringiensis serovar kurstaki HD73 strain. Rap63 has moderate activity on sporulation and is inhibited by the Phr63 peptide. The rap63-phr63 genes are cotranscribed, and the phr63 gene is also transcribed from a σH-specific promoter. We show that Rap63-Phr63 regulates sporulation together with the Rap8-Phr8 system harbored by plasmid pHT8_1 of the HD73 strain. Interestingly, the deletion of both phr63 and phr8 genes in the same strain has a greater negative effect on sporulation than the sum of the loss of each phr gene. Despite the similarities in the Phr8 and Phr63 sequences, there is no cross talk between the two systems. Our results suggest a synergism of these two Rap-Phr systems in the regulation of the sporulation of B. thuringiensis at the end of the infectious cycle in insects, thus pointing out the roles of the plasmids in the fitness of the bacterium. IMPORTANCE The life cycle of Bacillus thuringiensis in insect larvae is regulated by quorum-sensing systems of the RNPP family. After the toxemia caused by Cry insecticidal toxins, the sequential activation of these systems allows the bacterium to trigger first a state of virulence (regulated by PlcR-PapR) and then a necrotrophic lifestyle (regulated by NprR-NprX); ultimately, sporulation is controlled by the Rap-Phr systems. Our study describes a new rap-phr operon carried by a B. thuringiensis plasmid and shows that the Rap protein has a moderate effect on sporulation. However, this system, in combination with another plasmidic rap-phr operon, provides effective control of sporulation when the bacteria develop in the cadavers of infected insect larvae. Overall, this study highlights the important adaptive role of the plasmid Rap-Phr systems in the developmental fate of B. thuringiensis and its survival within its ecological niche.

Real-time control of a fleet of Connected and Automated Vehicles (CAV) for Cooperative Adaptive Cruise Control (CACC) is a challenging problem concerning time delays (from sensing, communication, and computation) and actuator lag. This paper proposes a real-time predictive distributed CACC control framework that addresses time delays and actuator lag issues in the real-time networked control systems. We first formulate a Kalman Filter-based real-time current driving state prediction model to provide more accurate initial conditions for the distributed CACC controller by compensating time delays using sensing data from multi-rate onboard sensors (e.g., Radar, GPS, wheel speed, and accelerometer), and status-sharing and intent-sharing data in BSM via V2V communication. We solve the prediction model using a sequential Kalman Filter update process for multi-rate sensing data to improve computational efficiency. We propose a real-time distributed MPC-based CACC controller with actuator lag and intent-sharing information for each CAV with the delay-compensated predicted current driving states as initial conditions. We implement the real-time predictive distributed CACC control algorithms and conduct numerical analyses to demonstrate the benefits of intent-sharing-based distributed computing, delay compensation, and actuator lag consideration on string stability under various traffic dynamics.

Abstract RNAs begin to fold and function during transcription. Riboswitches undergo cotranscriptional switching in the context of transcription elongation, RNA folding, and ligand binding. To investigate how these processes jointly modulate the function of the folate stress-sensing Fusobacterium ulcerans ZTP riboswitch, we apply a single-molecule vectorial folding (VF) assay in which an engineered superhelicase Rep-X sequentially releases fluorescently labeled riboswitch RNA from a heteroduplex in a 5′-to-3′ direction, at ~60 nt s−1 [comparable to the speed of bacterial RNA polymerase (RNAP)]. We demonstrate that the ZTP riboswitch is kinetically controlled and that its activation is favored by slower unwinding, strategic pausing between but not before key folding elements, or a weakened transcription terminator. Real-time single-molecule monitoring captures folding riboswitches in multiple states, including an intermediate responsible for delayed terminator formation. These results show how individual nascent RNAs occupy distinct channels within the folding landscape that controls the fate of the riboswitch.

Abstract Acoustic waves, capable of transmitting through optically opaque objects, have been widely used in biomedical imaging, industrial sensing and particle manipulation. High-fidelity wave front shaping is essential to further improve performance in these applications. An acoustic analog to the successful spatial light modulator (SLM) in optics would be highly desirable. To date there have been no techniques shown that provide effective and dynamic modulation of a sound wave and which also support scale-up to a high number of individually addressable pixels. In the present study, we introduce a dynamic spatial ultrasound modulator (SUM), which dynamically reshapes incident plane waves into complex acoustic images. Its transmission function is set with a digitally generated pattern of microbubbles controlled by a complementary metal–oxide–semiconductor (CMOS) chip, which results in a binary amplitude acoustic hologram. We employ this device to project sequentially changing acoustic images and demonstrate the first dynamic parallel assembly of microparticles using a SUM.

To investigate the atmospheric aerosols of the Himalayas and Tibetan Plateau (HTP), an observation network was established within the region’s various ecosystems, including at the Ngari, Qomolangma (QOMS), Nam Co, and Southeastern Tibetan (SET) stations. In this paper we illustrate aerosol mass loadings by integrating <i>in situ</i> measurements with satellite and ground-based remote sensing datasets for the 2011&amp;ndash;2013 period, on both local and large scales. Mass concentrations of these surface atmospheric aerosols were relatively low and varied with land cover, showing a general tendency of Ngari and QOMS (barren sites) > Nam Co (grassland site) > SET (forest site). Daily averages of online PM_2.5 (particulates with aerodynamic diameters below 2.5&amp;thinsp;μm) at these sites were sequentially 18.2&amp;thinsp;±&amp;thinsp;8.9, 14.5&amp;thinsp;±&amp;thinsp;7.4, 11.9&amp;thinsp;±&amp;thinsp;4.9 and 11.7&amp;thinsp;±&amp;thinsp;4.7&amp;thinsp;μg&amp;thinsp;m^&amp;minus;3. Correspondingly, the ratios of PM_2.5 to total suspended particles (TSP) were 27.4&amp;thinsp;±&amp;thinsp;6.65&amp;thinsp;%, 22.3&amp;thinsp;±&amp;thinsp;10.9&amp;thinsp;%, 37.3&amp;thinsp;±&amp;thinsp;11.1&amp;thinsp;% and 54.4&amp;thinsp;±&amp;thinsp;6.72&amp;thinsp;%. Bimodal mass distributions of size-segregated particles were found at all sites, with a relatively small peak in accumulation mode and a more notable peak in coarse mode. Diurnal variations in fine aerosol masses generally displayed a bi-peak pattern at the QOMS, Nam Co and SET stations and a single-peak pattern at the Ngari station, controlled by the effects of local geomorphology, mountain-valley breeze circulation and aerosol emissions. Mineral content in PM_2.1 samples gave fractions of 26&amp;thinsp;% at the Ngari station and 29&amp;thinsp;% at the QOMS station, or ~&amp;thinsp;2&amp;ndash;3 times that of reported results at human-influenced sites. Furthermore, observed evidence confirmed the existence of the aerodynamic conditions necessary for the uplift of fine particles from a barren land surface. Combining surface aerosol data and atmospheric-column aerosol optical properties, the TSP mass and aerosol optical depth (AOD) of the Multi-angle Imaging Spectroradiometer (MISR) generally decreased as land cover changed from barren to forest, in inverse relation to the PM_2.5 ratios. The seasonality of aerosol mass parameters was land-cover dependent. Over forest and grassland areas, TSP mass, PM_2.5 mass, MISR-AOD and fine-mode AOD were higher in spring and summer, followed by relatively lower values in autumn and winter. At the barren site (the QOMS station), there were inconsistent seasonal variations between surface TSP mass (PM_2.5 mass) and atmospheric column AOD (fine-mode AOD). Our findings implicate that, HTP aerosol masses (especially their regional characteristics and fine particle emissions) need to be treated sensitively in relation to any assessments of their climatic effect and potential role as cloud condensation nuclei and ice nuclei.