Miracle-dz/UniFAR-FTUs huggingface dataset:
Model-Based Test Sequence Generation and Prioritization Using Ant Colony Optimization

The paper presents an approach to generate and optimize test sequences from the input UML activity diagram. For this, an algorithm is proposed called “Unified Modelling Language for Test Sequence Generation" (UMLTSG) that uses a search-based algorithm, named “Test Sequence Prioritization using Ant Colony Optimization" (TSP ACO) to generate and optimize test sequences. The algorithms overcome the existing limitations of handling complex decision-making activity such as conditional activity, fork activity, and join the activity. The optimization process helps to reduce the number of processing nodes that leads to minimizing the time and cost. The proposed approach experiments on a well-known application “Railway Ticket Reservation System" (RTRS). APFD metric measures the effectiveness of our approach and found that the prioritized order of test sequences achieved 20% higher APFD score. Apart from this, we have also experimented on six real life case studies and obtained an average of 52.16% reduction in redundant test paths.
Lightweight Challenge-Response Authentication in SDN-Based UAVs Using Elliptic Curve Cryptography

Unmanned aerial vehicles (UAVs) (also known as drones) are aircraft that do not require the presence of a human pilot to fly. UAVs can be controlled remotely by a human operator or autonomously by onboard computer systems. UAVs have many military uses, including battlefield surveillance, effective target tracking and engagement in air-to-ground warfare, and situational awareness in challenging circumstances. They also offer a distinct advantage in various applications such as forest fire monitoring and surveillance. Surveillance systems are developed using advanced technologies in the modern era of communications and networks. As a result, UAVs require enhancements to control and manage systems efficiently. Network security is a critical concern with respect to UAVs due to the risk of surveillance information theft and physical misuse. Although several new tools have been introduced to secure networks, attackers can use more advanced methods to get into a UAV network and create problems that pose an organizational threat to the entire system. Security mechanisms also reduce the performance of systems because some restrictive measures prevent users from accessing specific resources, but a few techniques and tools have overcome the problem of performance reduction in various scenarios. There are many types of attacks, i.e., denial of service attacks (DOS), distributed denial of service attacks (DDOS), address resolution protocol (ARP) spoofing, sniffing, etc., that make it challenging to maintain a UAV network. This research paper proposes a lightweight challenge-response authentication that can overcome the previously mentioned problems. As security is provided by utilizing a minimum number of bits in memory, this technique offers the same security features while using fewer network resources, low computing resources, and low power consumption.
Virtual Glasses Try-on System

Virtual Glasses Try-on System Siyu Quan Recent advances in data-driven modeling have enabled the simulation of wearing the glasses virtually based on 2D images (web-camera). For real-life glasses wearing, it needs not only suitable for appearance, but also comfort. Although the simulations based on 2D images can bring out certain conveniences for customers who want to try on glasses online first, there are still many challenging problems ahead because of the high complexity of simulations for wearing glasses. Obviously, it can hardly tell if the glasses are comfortable or can seat on the customer’s nose correctly. Furthermore, customers may want to take a look from different angle to make sure that the glasses selected are perfect. Such requirements cannot be met by using the simulations based on 2D images so we present an interactive real-time system with simulations for wearing glasses, providing users with a high degree of simulation quality including physics application. With our system the user uses the Kinect sensor or the common web camera as input device to acquire the result of wearing the preferred glasses virtually, which is real-time. Input device captures the user’s face and generate a geometry face-mesh which is expected to be aligned to the face-mesh template we pre-set manually. The 3D data captured from Kinect dramatically improve user’s experience by constructing geometry face mesh.
Data‐limited approach to the management and conservation of the pelagic thresher shark in the Northwest Pacific

The pelagic thresher shark is among the most heavily exploited shark species in the commercial fisheries of the tropical Indo‐Pacific oceans. Despite this severe exploitation, little is known about pelagic thresher population dynamics, particularly the species' life history traits, and overall stock status. The pelagic thresher exhibits slow growth and extremely low fecundity, indicating the need for reassessment of the population status of this globally threatened shark. Because information on catch and effort of this bycatch species is scarce, several data‐limited methods—quantitative demographic methods, per‐recruit analysis, and risk assessment—were employed in this study to provide an accurate measurement of the status of pelagic thresher shark stocks. For each sex, the composite risk assessments indicated that the probability of the current fishing mortality increasing beyond any level of yield‐per‐recruit (YPR) was approximately zero given the biological reference points (BRPs). Moreover, the current spawning potential ratio (SPR) was found to be significantly below the target reference point of SPR60%, but slightly above the limit reference point of SPR40%. However, because SPR‐based BRPs are much less sensitive to input parameter uncertainties than YPR‐based BRPs, results derived from the SPR model are more suitable for species management. Management strategy simulations based on demographic two‐sex models indicated that without mortality from fishing, female pelagic threshers have a higher population growth rate than males. However, the stock status of female pelagic thresher shark is poorer than that of males under current conditions. The findings suggest that sex‐specific management decisions must be made to achieve the sustainable utilization of this species. Overall, both the sex‐specific per‐recruit and demographic models determined that recruitment overfishing has occurred in the female pelagic thresher population of the Northwest Pacific Ocean, indicating that close monitoring of female sharks is urgent and necessary to ensure that stocks remain sustainable.
Macrophage-like Cells Are Responsive to Titania Nanotube Intertube Spacing—An In Vitro Study

With the introduction of a new interdisciplinary field, osteoimmunology, today, it is well acknowledged that biomaterial-induced inflammation is modulated by immune cells, primarily macrophages, and can be controlled by nanotopographical cues. Recent studies have investigated the effect of surface properties in modulating the immune reaction, and literature data indicate that various surface cues can dictate both the immune response and bone tissue repair. In this context, the purpose of the present study was to investigate the effects of titanium dioxide nanotube (TNT) interspacing on the response of the macrophage-like cell line RAW 264.7. The cells were maintained in contact with the surfaces of flat titanium (Ti) and anodic TNTs with an intertube spacing of 20 nm (TNT20) and 80 nm (TNT80), under standard or pro-inflammatory conditions. The results revealed that nanotube interspacing can influence macrophage response in terms of cell survival and proliferation, cellular morphology and polarization, cytokine/chemokine expression, and foreign body reaction. While the nanostructured topography did not tune the macrophages’ differentiation into osteoclasts, this behavior was significantly reduced as compared to flat Ti surface. Overall, this study provides a new insight into how nanotubes’ morphological features, particularly intertube spacing, could affect macrophage behavior.
A Poisson Process Generator Based on Multiple Thermal Noise Amplifiers for Parallel Stochastic Simulation of Biochemical Reactions

In this paper, we propose a novel Poisson process generator that uses multiple thermal noise amplifiers (TNAs) as a source of randomness and controls its event rate via a frequency-locked loop (FLL). The increase in the number of TNAs extends the effective bandwidth of amplified thermal noise and hence enhances the maximum event rate the proposed architecture can generate. Verilog-A simulation of the proposed Poisson process generator shows that its maximum event rate can be increased by a factor of 26.5 when the number of TNAs increases from 1 to 10. In order to realize parallel stochastic simulations of the biochemical reaction network, we present a fundamental reaction building block with continuous-time multiplication and addition using an AND gate and a 1-bit current-steering digital-to-analog converter, respectively. Stochastic biochemical reactions consisting of the fundamental reaction building blocks are simulated in Verilog-A, demonstrating that the simulation results are consistent with those of conventional Gillespie algorithm. An increase in the number of TNAs to accelerate the Poisson events and the use of digital AND gates for robust reaction rate calculations allow for faster and more accurate stochastic simulations of biochemical reactions than previous parallel stochastic simulators.
Shared Control of a Robot Arm Using BCI and Computer Vision

Brain-Computer Interface (BCI) is a device that can transform human thoughts into control commands. However, BCI aggravates the common problems of robot teleoperation due to its low-dimensional and noisy control commands, particularly when utilized to control high-DOF robots. Thus, a shared control strategy can enhance the BCI performance and reduce the workload for humans. This paper presents a shared control scheme that assists disabled people to control a robotic arm through a non-invasive Brain-Computer Interface (BCI) for reach and grasp activities. A novel algorithm is presented which generates a trajectory (position and orientation) for the end-effector to reach and grasp an object based on a specially designed color-coded tag placed on the object. A single camera is used for tag detection. The simulation is performed using the CoppeliaSim robot simulator in conjunction with MATLAB to implement the tag detection algorithm and Python script to receive the commands from the BCI. The human-in-the-loop simulation results prove the effectiveness of the proposed algorithm to reach and grasp objects.
An Embedded System Using Convolutional Neural Network Model for Online and Real-Time ECG Signal Classification and Prediction

This paper presents an automatic ECG signal classification system that applied the Deep Learning (DL) model to classify four types of ECG signals. In the first part of our work, we present the model development. Four different classes of ECG signals from the PhysioNet open-source database were selected and used. This preliminary study used a Deep Learning (DL) technique namely Convolutional Neural Network (CNN) to classify and predict the ECG signals from four different classes: normal, sudden death, arrhythmia, and supraventricular arrhythmia. The classification and prediction process includes pulse extraction, image reshaping, training dataset, and testing process. In general, the training accuracy achieved up to 95% after 100 epochs. However, the prediction of each ECG single type shows a differentiation. Among the four classes, the results show that the predictions for sudden death ECG waveforms are the highest, i.e., 80 out of 80 samples are correct (100% accuracy). In contrast, the lowest is the prediction for normal sinus ECG waveforms, i.e., 74 out of 80 samples are correct (92.5% accuracy). This is due to the image features of normal sinus ECG waveforms being almost similar to the image features of supraventricular arrhythmia ECG waveforms. However, the model has been tuned to achieve an optimal prediction. In the second part, we presented the hardware implementation with the predictive model embedded in an NVIDIA Jetson Nanoprocessor for the online and real-time classification of ECG waveforms.
Significance of Lipid Fatty Acid Composition for Resistance to Winter Conditions in Asplenium scolopendrium

Simple Summary Plants growing at temperate and polar latitudes are exposed to cold stress. With climate change, different durations of low temperatures and sometimes frost are being increasingly observed in regions at low latitudes. This can cause especially great harm to agricultural crops, the mortality of which can pose a serious challenge to the food supply for the global population. One of the factors affecting plant resistance to low and negative temperatures is specific changes in the fatty acid (FA) composition of lipids. It should be noted that most of the crops studied in this regard are angiosperms. It is known that the FA composition of angiosperms has undergone significant evolutionary changes compared to that of nonflowering vascular plants. Studying the FA composition of various taxonomic groups can shed light on and reveal new mechanisms of plant resistance. Therefore, in this paper, we focused on the rare evergreen fern Asplenium scolopendrium, whose fronds can tolerate freezing. A number of specific features of its FA composition were discovered, which, in combination with other resistance mechanisms, determine its ability to grow in temperate climate zones and safely undergo wintering. Abstract Ferns are one of the oldest land plants. Among them, there are species that, during the course of evolution, have adapted to living in temperate climates and under winter conditions. Asplenium scolopendrium is one such species whose fronds are able to tolerate low subzero temperatures in winter. It is known that the resistance of ferns to freezing is associated with their prevention of desiccation via unique properties of the xylem and effective photoprotective mechanisms. In this work, the composition of A. scolopendrium lipid fatty acids (FAs) at different times of the year was studied by gas–liquid chromatography with mass spectrometry to determine their role in the resistance of this species to low temperatures. During the growing season, the polyunsaturated FA content increased significantly. This led to increases in the unsaturation and double-bond indices by winter. In addition, after emergence from snow, medium-chain FAs were found in the fronds. Thus, it can be speculated that the FA composition plays an important role in the adaptation of A. scolopendrium to growing conditions and preparation for successful wintering.
The de novo prediction of functionally significant sequence motifs in Arabidopsis thaliana.

The de novo prediction of functionally significant sequence motifs in Arabidopsis thaliana. Ryan S. Austin Doctor of Philosophy Graduate Department of Cell & Systems Biology University of Toronto 2009 This thesis performs de novo predictions for functionally significant sequence motifs in the Arabidopsis genome under two separate contexts. Each study applies the use of genomic positional information, statistical over-representation and several biologically contextual filters to maximize the visibility of biological signal in prediction results. Numerous literature supported motifs are prevalent in the results of both studies and a number of novel motif patterns possess a strong potential for in planta significance. The first study examines the statistical over-representation of C-terminal tripeptides as a means for identifying eukaryotic conserved protein targetting signatures. Comparative genomics is applied to the analysis of tripeptide frequencies in the C-terminus of 7 eukaryotic proteomes. While biological signal is maximized through the filtering of both simple sequences and homologous sequences present across protein families. The second study introduces a methodology for the effective prediction of transcription factor binding sites in Arabidopsis. A collection of motif prediction algorithms and a novel enumerative strategy are applied to the prediction of cis-acting regulatory elements within the promoters of genes found coexpressed within distinct tissues and under specific abiotic stress treatments. Overall, the analysis identifies 4 known motifs in expected contexts, 5 known motifs in novel contexts and 7 novel motifs with a high potential for biological function.
An Investigation of Size‐Reduction Effects in High Power Density Boost Converters with a Magnetic Coupling

The dc–dc converter using integrated magnetic components that may achieve high power density has gained attention in environmentally friendly cars such as electric vehicles and hybrid electric vehicles. This paper focused on interleaved boost converters using close‐coupled inductors (CCIs) and loose‐coupled inductors (LCIs) that are the integrated magnetic components. Following, detailed electromagnetically analysis for these circuit types were conducted in order to calculate volume of inductors and capacitors that are occupied the large part of space in the converters. The total volume of inductors and capacitors in these circuits were demonstrated clearly through comparison with conventional circuits such as an interleaved boost converter and a single‐phase boost converter. As a result, it became clear that interleaved boost converter using LCIs was effective for miniaturization of total volume. Furthermore, duty ratio of the minimum volume of CCI method is different from the duty ratio of the minimum volume of LCI method.
Evaluation of Host Cell Impurity Effects on the Performance of Sterile Filtration Processes for Therapeutic Viruses

Efficient downstream processing represents a significant challenge in the rapidly developing field of therapeutic viruses. While it is known that the terminal sterile filtration step can be a major cause of product loss, there is little known about the effect of host cell impurities (DNA and protein) on filtration performance. In this study, fractions of relatively pure Vero host cell protein and DNA were spiked into a highly pure preparation of vesicular stomatitis virus (VSV). Then, the resulting solutions were sterile filtered using two commercially available 0.22 µm rated microfiltration membranes. A combination of transmembrane pressure measurements, virus recovery measurements, and post-filtration microscopy images of the microfiltration membranes was used to evaluate the sterile filtration performance. It was found that increasing the amount of host cell protein from approximately 1 µg/mL (in the un-spiked VSV preparation) to 25 µg/mL resulted in a greater extent of membrane fouling, causing the VSV recovery to decrease from 89% to 65% in experiments conducted with the highly asymmetric Express PLUS PES membrane and to go as low as 48% in experiments conducted with the symmetric Durapore PVDF membrane. Similar effects were not seen when bovine serum albumin, a common model protein used in filtration studies, was spiked into the VSV preparation, which indicates that the sterile filtration performance is critically dependent on the complex composition of the mixture of host cell proteins rather than the presence of any protein. The results presented in this work provide important insights into the role of host cell impurities on the performance of sterile filtration processes for therapeutic viruses.
DUAL BAND TWO ELEMENT RIM BASED MIMO ANTENNAS WITH COUPLING MANIPULATION FOR LOW SAR MOBILE HANDSETS

In this paper, the mutual coupling from a multiple-input-multiple-output (MIMO) rim antenna has been utilized to control the level of specific absorption rate (SAR), when the mobile handset comes in close contact to the human body. The proposed antenna is capable of operating at 2.1GHz and 4.3GHz, respectively. A periodic defective ground structure (DGS) in conjunction with diodes and capacitors are used to manipulate the coupling between antenna elements. The working of the proposed dual band antenna design is validated using the characteristic mode analysis (CMA), and the current distribution. The MIMO performance is studied by using envelope correlation coefficient (ECC) and loss in capacity analysis. The effect of hand and LCD on the antenna performance is shown. The SAR analysis shows up to 30% reduction, in comparison to the baseline value of the SAR of the proposed antenna design.
Nanoscale Semiconductor Memories: Technology and Applications

Nanoscale memories are used everywhere. From your iPhone to a supercomputer, every electronic device contains at least one such type. With coverage of current and prototypical technologies, Nanoscale Semiconductor Memories: Technology and Applications presents the latest research in the field of nanoscale memories technology in one place. It also covers a myriad of applications that nanoscale memories technology has enabled. The book begins with coverage of SRAM, addressing the design challenges as the technology scales, then provides design strategies to mitigate radiation induced upsets in SRAM. It discusses the current state-of-the-art DRAM technology and the need to develop high performance sense amplifier circuitry. The text then covers the novel concept of capacitorless 1T DRAM, termed as Advanced-RAM or A-RAM, and presents a discussion on quantum dot (QD) based flash memory. Building on this foundation, the coverage turns to STT-RAM, emphasizing scalable embedded STT-RAM, and the physics and engineering of magnetic domain wall "racetrack" memory. The book also discusses state-of-the-art modeling applied to phase change memory devices and includes an extensive review of RRAM, highlighting the physics of operation and analyzing different materials systems currently under investigation. The hunt is still on for universal memory that fits all the requirements of an "ideal memory" capable of high-density storage, low-power operation, unparalleled speed, high endurance, and low cost. Taking an interdisciplinary approach, this book bridges technological and application issues to provide the groundwork for developing custom designed memory systems.
Towards sustainable electrochemical energy storage: solution-based processing of polyquinone composites

Continuous adoption of renewable energy sources and the proliferation of electric transportation technologies push towards sustainable energy storage solutions. Consequently, a solution-based up-scalable synthesis approach is developed for polymeric quinone composites with graphene. Cellulose nanocrystals play a vital role in achieving greener processing and improving the composite electrochemical energy storage performance. The synthesis method emphasizes using aqueous reaction media, incorporates low-cost and biomass-derived feedstocks, avoids critical or scarce materials, and maintains temperatures below 200 °C. Stable aqueous graphene dispersions were obtained by hydrothermal reduction of electrochemically exfoliated graphene oxide in the presence of cellulose nanocrystals. Dispersions served as a reaction medium for quinone cationic polymerization, leading to core–shell type structures of polymer-covered mono-to-few layer graphene, thanks to the nanosheet restacking prevention effect provided by cellulose nanocrystal dispersions. A sample consisting of 5 wt% cellulose nanocrystals and 5 wt% graphene achieved storage metrics of 720.5 F g−1 and 129.6 mA h g−1 at 1 A g−1, retaining over 70% of the performance after 1000 charge/discharge cycles.