Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-tier web programming for curated databases: A case study

Curated databases have become important sources of information across several scientific disciplines, and as the result of manual work of experts, often become important reference works. Features such as provenance tracking, archiving, and data citation are widely regarded as important features for the curated databases, but implementing such features is challenging, and small database projects often lack the resources to do so. A scientific database application is not just the relational database itself, but also an ecosystem of web applications to display the data, and applications which allow data curation. Supporting advanced curation features requires changing all of these components, and there is currently no way to provide such capabilities in a reusable way. Cross-tier programming languages allow developers to write a web application in a single, uniform language. Consequently, database queries and updates can be written in the same language as the rest of the program, and it should be possible to provide curation features via program transformations. As a step towards this goal, it is important to establish that realistic curated databases can be implemented in a cross-tier programming language. In this article, we describe such a case study: reimplementing the web frontend of a realworld scientific database, the IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb), in the Links cross-tier programming language. We show how programming language features such as language-integrated query simplify the development process, and rule out common errors. Through an automated functional correctness evaluation, we show that the Links implementation correctly implements the functionality of the official version. Through a comparative performance evaluation, we show that the Links implementation performs fewer database queries, while the time neededto handle the queries is comparable to the official Java version. Furthermore, while there is some overhead to using Links because of its comparative immaturity compared to Java, the Links version is usable as a proof-of-concept case study of cross-tier programming for curated databases.
System Level Analysis of Millimetre-wave GaN-based MIMO Radar for Detection of Micro Unmanned Aerial Vehicles

The detection of Unmanned Aerial Vehicles (UAVs) of micro/nano dimensions, is becoming a hot topic, due to their large diffusion, and represents a challenging task from both the system architecture and components point of view. The Frequency Modulated Continuous Wave (FMCW) radar architecture in a Multi-Input Multi-Output configuration has been identified as the most suitable solution for this purpose, due to both its inherent short-range detection capability and compact implementation. This paper describes the operation and technology challenges inherent to the development of a millimeter-wave FMCW MIMO radar for small UAVs detection. In particular it analyzes the sub-systems specifications and the expected system performance with respect to a chip set designed and developed in GaN at 37.5 GHz applications.
Stability of Least Squares for the Solution of an Ill-posed Inverse Problem of Reconstructing Real Value of the Pcrrnittivity of a Dielectric Layer in a Rectangular Waveguide

We use the solution to Maxwell's equations in a rectangular single-mode waveguide with multi-mode boundary conditions at its flanges to determine the parameters of the inclusion. The well-posedness of the inverse problem is studied using explicit expressions for the S-parameters of the waveguide when the inclusion is a plane-parallel dielectric slab. The methods of reconstructing permittivity from the measured (experimental) data must be stable and well-conditioned. The importance of these demands is discussed taking as an example the determination of real permittivity from noisy measurement data of the transmission coefficient of the principal waveguide mode. Generally, this problem is unsolvable because the range of the function to be inverted forms a set of measure zero on the complex plane. In addition, the occurrence of self-intersections of the parametric curve leads to non-uniqueness of the solution to the inverse problem. Therefore, approximate methods of the permittivity reconstruction in the vicinity of such points may be unstable or ill-conditioned. In our study, we present several examples of such algorithms. We demonstrate that the method of least squares applied for reconstructing permittivity of the inclusion from multi-frequency measurement data is a stable algorithm for the solution to this inverse problem. This approach does not use a priori estimates for the sought parameter and information about the location of singularities of the parametric curve. We determine the interval of variation of the condition number for the method of least squares and show that this quantity decreases as one of the following parameters increases: the width of the dielectric layer, the measurement frequency band, or its distance to the lower cutoff value. Using these results, we estimate the rate of convergence of the approximate solution to the exact value of the sought parameter when the quality of the measurement data is improved and show how to choose optimal parameters of the experiment and the measurement setup.
LI-FI TECHNOLOGY BASED AUDIO AND TEXT TRANSMISSION

The focal objective of this paper is to develop improvements in the modern communication due to the emergence of wireless technology; there is a vast growth in the devices with the need to access the internet. Congestion is the major evident complication created due to it. It is the need of the hour to find another means of communication. Light fidelity is such a technology which can be used as an alternative as it uses visible light communication. It has high durability, high data transmission rate with its additional quality of long- life expectancy which is an appreciative quality of the Light Emitting Diodes (LEDs) which are being used here as the source of light. In the proposed paper, An innovative concept Light Fidelity (Li-FI) is used to transmit the data in order to demonstrate the use the case study of Light Fidelity technology. Here, two types of data transmission i.e Audio and text is carried out using Li - Fi. We are also implementing an application of how this above concept can be implied for indoor Location Based Services for the visually challenged.
Adaptive output regulation of a class of nonlinear output feedback systems with unknown high frequency gain

This paper presents an output feedback design approach based on the adaptive control scheme developed for nonlinearly parameterized systems, to achieve global output regulation for a class of nonlinear systems in output feedback form. We solve the output regulation problem without the knowledge of the sign and the value of the high frequency gain a priori. It is not necessary to have both the limiting assumptions that the exogenous signal w and the unknown parameter μ belong to a prior known compact set and the high frequency gain has a determinate lower and upper bounds. The effectiveness of the proposed algorithm is shown with the help of an example.
Emerging therapeutic strategies for sarcoglycanopathy

ABSTRACT Introduction: Sarcoglycanopathy is the name shared by four rare autosomal recessive muscular dystrophies (LGMD2 C-F) that are usually characterized by early onset and rapid progression and an accompanying loss of independent walking since adolescence. Respiratory problems are frequent, and dilated cardiomyopathy may occur, although milder forms have also been described. However, sarcoglycanopathy is currently incurable, and we herein aim to describe the state of the art in the field of treatments for this disease. Areas covered: We summarize the pathogenesis of sarcoglycanopathy, with particular emphasis on the molecular mechanism(s) underlying the disease. We describe the very few published cases of symptomatic treatment with steroids and the gene therapy approaches that have entered phase I/II clinical trials. We then present emerging novel therapeutic strategies explored at the preclinical stage that are expected to replace the defective gene (cell therapy), address general effects of the disease, or address the primary events of the pathogenic mechanism (small molecule-based therapy). Expert opinion: Anti-inflammatory strategies, which are at present empirically applied, warrant further exploration. Although promising and currently being evaluated in clinical trials, gene therapy remains associated with concerns and requires additional confirmation. Thus, novel strategies targeting different aspects of the disease pathogenic mechanism are highly anticipated.
UAV-Assisted Multi-Access Edge Computing System: An Energy-Efficient Resource Management Framework

Unmanned Aerial Vehicles (UAVs) have been deployed to enhance the network capacity and provide services to mobile users with and without infrastructure coverage. At the same time, due to the exponential growth of the internet of things devices (IoTDs), more and more data-oriented applications are coming up. However, as IoTDs have limited computation capacity and power, it is challenging to process collected data locally at the IoTDs. Motivated by the aforementioned facts, we propose, in this work, a UAV-assisted mobile edge computing system. Specifically, the objective of this work is to minimize the energy consumption of IoTDs, including local computation energy and uplink transmission energy, and UAV energy consumption. To achieve that, we formulate an optimization problem that optimizes the task offloading, bandwidth resource allocation, local computation resource allocation, and UAV computation resource allocation subject to the latency constraint of all IoTDs and the limitation of communication and computation capacity resources. Although the formulated problem is a non-convex problem, it is composed of convex subproblems, i.e., the formulated optimization problem in the form of a multi-convex optimization problem. Therefore, we decompose the formulated problem into convex subproblems and then alternately solve them till converge to the desired solution by using the Block Coordinate Descent (BCD) algorithm. Simulation results show that the proposed approach significantly saves the system power consumption compared to other existing schemes.
Analytical Assessment of the Modulation Depth of Photoplethysmographic Signal Based on the Modified Beer-Lambert Law

The model for estimation of the amplitude modulation depth of photoplethysmographic (PPG) signal based on the modified Beer-Lambert law was developed. It was analytically confirmed that the modulation depth of PPG signal depends on the wavelength and illumination geometry. The modulation depth is directly proportional to the distance between the light source and the detector. The sensitivity of green light (525 nm) to blood volume changes is approximately 6-9 times greater than that for red (640 nm) and IR (805 nm) light. It was found that in case of green light, the main contribution to the modulation of PPG signal is made by absorption coefficient changes while in case of red and IR light, the modulation is mainly caused by scattering coefficient changes.
A Self-organized Reciprocal Control Method for Multi-Agent Coverage

Multi-agent coverage problem is an active issue of how to cover an accessible region of interest by agents. In this paper, a self-organized reciprocal control method is proposed, which is directly optimized in velocity space, different from the traditional method modeled in configuration space. The method considers the reciprocal of neighboring agents that is ignored by most other methods. And the motion of each agent is collision-free motivated by this method. The simulation results corroborate that the proposed method has higher coverage rate, faster convergence rate and less deadweight loss than other traditional methods.
Fuzzy Logic-Feedback Linearization Control for a Three-Cell Flying Capacitor Converter

Several applications have recently been found in renewable energy systems, industrial applications and active filters that utilize flying capacitors converters. Thanks to their unique ability to generate multiple voltage levels. These converters reduce voltage constraints among cells. This reduces the transmission losses, high switching frequencies and provides a better harmonic content. However, it is necessary to choose a good control to reach all these advantages. To ensure optimum operation of the multicellular converter it is essential to keep the voltages of the flying capacitors at their target operating levels. This paper proposes a fuzzy logic-feedback linearization control for three cells flying capacitor chopper. This control maintains simultaneously the capacitor’s voltages and the output current to their references. Simulation results carried out accomplished utilizing Matlab / Simulink software verify the robustness of the suggested law during disturbances. The command law is compared to the natural balanced control based on pulse width modulation (PWM) control to confirm its good performances.
Social Support for Medication Adherence among Thai People with Post-Acute Myocardial Infarction: Factor Analysis

Background: The aim of this study was to modify the Enhancing Recovery in Coronary Heart Disease (ENRICHD) Social Support Instrument (ESSI) in order to obtain assessment of social support for medication, because, whereas ESSI assesses general social support, a specific tool is needed for assessing social support for medication adherence, including assessment of the validity and reliability of this adapted version of the questionnaire. Methods: Responses to the 12-item modified version of ESSI were collected from 348 Thais with postacute myocardial infarction. None of 12-items violated any assumption for the factor analysis. The appropriateness of data for factor analysis was tested and then factor analysis was performed. Results: Factor analysis comprised two components for determining the social support for medication adherence: the emotional and information support (nine items; items 1, 2,3,4,5,6,7,8, and 9) and the instrumental and appraisal support (three items; item 9, 10, and 12). The instrument used showed adequate validity and reliability. Conclusion: The modified ESSI showed acceptable validity and reliability. This instrument may be used to evaluate social support for adherence to medications among Thais with post-acute myocardial infarction.
Max-Maximum Likelihood Detection And Performance Analysis For Mimo Decode-And-Forward Relaying Systems

In this paper, we focus on the detection in the cooperative multiple-input-multiple-output systems with decode-andforward relaying. To avoid the computational difficulty in the exhaustive search of the statistically optimal maximum likelihood detection, we develop the max-maximum likelihood detection (max-MLD) scheme for the one-way relaying network, which is based on the max-log approximation. The solution to the max-MLD is found with the use of the branch-and-bound algorithm. Then, the performance of the max-MLD is evaluated in terms of the symbol error rate. The simulation results demonstrate the superiority of the proposed detection scheme in comparison with other schemes.
An IMU/Visual Odometry Integrated Navigation Method Based on Measurement Model optimization

In order to improve the accuracy and reliability of the positioning and navigation system of the intelligent-motion objects in complex environment, and to solve the precision reduction problem of the integrated navigation system caused by the error accumulation of the visual odometry (VO) with motion and the inaccurate modeling of VO noise, an IMU/visual odometry integrated navigation method based on measurement model optimization is proposed. With Kalman filter as the framework, we constructs the state equation by the error recurrence model of strapdown inertial navigation system (SINS), and based on the characteristics of the relative pose output of VO, we consider VO as an angular velocity, line velocity and position sensor to construct the measurement equation. The method has been evaluated by KITTI odometry benchmark and the results indicate that comparing to traditional integration of position and attitudes, the measurement model of this method is more consistent with the noise characteristics of VO and thus can improve the accuracy and reliability of the integrated navigation system.
Height Varying Humanoid Robot Walking through Model Predictive Control

The present paper proposes the application of Model Predictive Control (MPC) to the bipedal walking problem. Classically, bipedal robots maintains constant height of the center of mass (CoM) during walking, since this constraint makes the underlying dynamical system linear. Nevertheless, researches show that vertical CoM motion is one of many mechanisms humans use to reduce energetic cost during walking. In this paper, we show that if the height is modified through a predefined function, the system becomes linear time-varying, which may be handled by MPC techniques. By means of simulations, the stability behavior of the robot is verified. Finally, a high-fidelity simulation model based on the Gazebo simulator is used to validate the energetic cost reduction due to the vertical CoM motion.
Absolute Positioning Based on the Sun for Mars Rover

Absolute positioning plays an important role in Mars rover’s attitude determination and safe driving. This paper dedicates to improve the absolute positioning accuracy based on the sun observations. Firstly, calibration and alignment model for sun sensor and inclinometer are put forward. Then Sobel operator and Zernike moment operator are combined together to detect the sub-pixel edge of the sun image, and general ellipse fitting algorithm is adopted to extract the centroid of the sun image. A novel celestial positioning algorithm without initial value and iteration (NIVI) is derived by introducing anti-symmetric matrix. At last, two field tests on the earth are introduced, and three positioning algorithms including NIVI are compared. Results of the tests prove early success of the paper, and 30-minute observation time produces mean positioning error of 1.6km. When the observation time is extended to 90 minutes, positioning error drops to 0.82km $\sim 1.15$ km.
Real-Time Motion Planning for Quadrotor MAVs in Three-dimensional Complex Environment

Planning a feasible and flyable path for a micro air vehicle (MAV) operating in a dynamic and cluttered environment is a very canonical and challenging problem in the field of robotics. And there is a variety of exploration in this area. Closed-loop rapidly-exploring random tree (CL-RRT), as a typical randomized algorithm considering the dynamic constraints and instantaneity, has made key contributions to build a real-time planning framework. This paper builds upon these efforts and gives depth discussions on the implementation plans of CL-RRT based motion planning algorithm in a complex closed environment. Simulation examples involving a quadrotor are presented and discussed.
Learning-based Dot-Grid Alignment for Projection Distortion Correction

In the most of the exist methods dot-grid alignment problem has been addressed using rule-based approach, but it is time-consuming and requires lots of engineer's efforts to manually define each rules. Moreover, the engineer may suffer to modify the algorithm when a new distortion pattern is observed. In this paper, We propose CNN-based dot-grid alignment method to address the limitation of the rule-based approaches. For this purpose, we formulate the dot-grid alignment task in terms of image restoration problem, and present suitable model structure and training strategy. The experiment results confirm the feasibility of the proposed method.
Semantic Bridge for Resolving Healthcare Data Interoperability

Data Interoperability is a critical part of achieving healthcare interoperability. In this paper, we present a novel methodology for automating the schema matching process at attribute level, among three non-standard and serialized schemas. We achieved 71.8% mappings, using a four stage process with string matching, longest common substring matching using suffix tree, and ConceptNet lookup.
Indoor Multi-Floor 3D Target Tracking Based on the Multi-Sensor Fusion

In recent years, indoor target tracking based on pedestrian dead reckoning (PDR) and the built-in inertial sensors of smartphone has become a research hotspot in location-based services (LBS). However, indoor 3D target tracking using smartphone inertial measurement unit (IMU) mainly face challenges of error accumulation caused by the heading drift of sensors and height fluctuation caused by the instability of barometer. This paper proposes a multi-floor 3D target tracking system based on the built-in inertial sensors of smartphone. We first establish a 2D PDR movement model by raw sensor data and then 2D PDR position is corrected in real time by rebuilding the particle filter model and refining the calculation method of particle weight to reduce the accumulated errors. A height displacement measurement method based on Kalman filter and floor change detection (FCD) algorithm is proposed to extend the 2D PDR tracking to 3D space. We first skillfully use Kalman filter to fuse the data of barometer and accelerometer, after that, the FCD algorithm is proposed to evaluate and modify the output height of the Kalman filter, evaluating the floor change state and maintaining steady height. The 3D target tracking, which consists of real-time 2D trajectory information and height information, is provided to the pedestrian. Experimental results demonstrate that the proposed method based on the fusion of various technologies can effectively maintain track stability and smoothness with low cost and high positioning accuracy. Moreover, additional peripheral devices need not be arranged in advance.
Fabrication of UTC-PDs Integrated with THz Antenna

The design and fabrication of waveguide-fed antenna integrated uni-traveling carrier photodiode(UTC-PD) are presented. It is found that compared with a PD having a smaller size, though a PD with a larger size has smaller response bandwidth, a notably larger THz wave power can be obtained from the larger PD device. For two devices having the same PD sizes but different bandwidths resulted from different absorber layer thickness, a larger response bandwidth leads only to a higher THz power at high frequencies.
Dynamic Channel Allocation for Satellite Internet of Things via Deep Reinforcement Learning

Dynamic channel allocation is one of the most attractive and important issues to realize flexibility and efficiency of data transmission in satellite Internet of Things. However, the traditional random access methods are inefficient for the scenarios when the number of sensors exceeds certain limits and it also results in low transmission success rates. Moreover, existing heuristics resource allocation algorithms are not practical for such scenarios due to high computational complexity. To address these matters, we propose a centralized dynamic channel allocation method based on deep reinforcement learning (DRL), which is called CA-DRL. CA- DRL develops a novel representation for the channel allocation problem in satellite Internet of Things. It minimizes the average transmission latency of all the sensors by making smart allocation decisions with the powerful representation ability of deep neural networks through constant learning of allocation policies. We demonstrate high efficiency of CA-DRL in a simulated network environment and show that our proposed method can reduce data transmission latency by at least 87.4% compared with the current state-of-the-art channel allocation algorithms. As a consequence, it also results in significantly higher transmission success rates.