Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Neural Control of a Kinematically Redundant Exoskeleton Robot Using Brain–Machine Interfaces

In this paper, a closed-loop control has been developed for the exoskeleton robot system based on brain–machine interface (BMI). Adaptive controllers in joint space, a redundancy resolution method at the velocity level, and commands that generated from BMI in task space have been integrated effectively to make the robot perform manipulation tasks controlled by human operator’s electroencephalogram. By extracting the features from neural activity, the proposed intention decoding algorithm can generate the commands to control the exoskeleton robot. To achieve optimal motion, a redundancy resolution at the velocity level has been implemented through neural dynamics optimization. Considering human–robot interaction force as well as coupled dynamics during the exoskeleton operation, an adaptive controller with redundancy resolution has been designed to drive the exoskeleton tracking the planned trajectory in human brain and to offer a convenient method of dynamics compensation with minimal knowledge of the dynamics parameters of the exoskeleton robot. Extensive experiments which employed a few subjects have been carried out. In the experiments, subjects successfully fulfilled the given manipulation tasks with convergence of tracking errors, which verified that the proposed brain-controlled exoskeleton robot system is effective.
Characterization of Corneoscleral Geometry Using Fourier Transform Profilometry in the Healthy Eye

Objective: To characterize peculiarities of the corneoscleral geometry in healthy eyes. Methods: This is a prospective case series including 88 healthy eyes of 88 patients with an age ranging from 21 to 73 years. A complete ocular examination was performed with emphasis on the analysis of the corneoscleral topographic profile with the Fourier transform profilometer Eye Surface Profiler (Eaglet-Eye BV, Houten, the Netherlands). The distribution of different topographic parameters was evaluated, as well as the correlations between corneal and scleroconjunctival parameters. Results: Mean values of 8.64±0.37 (range, 7.81–9.50 mm), 6.06±0.52 (4.88–7.63 mm) and 11.93±1.32 mm (8.17–15.89 mm) were obtained for inner, limbal, and outer best-fit sphere, respectively. Mean values of 8.54±0.38 (7.86–9.66 mm) and 13.35±1.29 mm (11.05–17.31 mm) were obtained for mean corneal and scleral radius, respectively. Regarding tangent angles at limbus, mean values of 35.31±6.55°, 38.76±5.90°, 32.75±7.04°, and 25.91±8.99° were obtained for nasal, temporal, superior, and inferior angles, respectively. Mean difference between temporal and nasal sagittal heights increased from −1.48±120.70 &mgr;m for a chord of 11 mm to 73.53±236.55 &mgr;m for a chord of 14 mm. A weak but statistically significant correlation was found between corneal and scleral radii (r=0.325, P=0.004). The maximum sagittal height for a diameter of 12 mm was significantly correlated with flattest keratometry, astigmatism, corneal diameter, and corneal eccentricity (R2: 0.77, P<0.001). Conclusions: The scleroconjunctival surface in the healthy eye presents some level of nasotemporal asymmetry that is higher with increasing diameters of analysis.
AC Calibration Methods of Magnetic Flux Density Coil Standard up to 100 kHz

The frequency dependence of the constant of the coil magnetic flux density standard is needed in order to generate the AC magnetic flux density with precision. This paper presents an analysis of methods that can be used for calibration of the frequency dependence of the coil magnetic flux density standard up to 100 kHz. In addition, experimental results with expanded uncertainty up to 0.25 % in the whole frequency range are compared with the simulated and calculated frequency dependence.
Sample-Free Learning of Input Grammars for Comprehensive Software Fuzzing

Generating valid test inputs for a program is much easier if one knows the input language. We present first successes for a technique that, given a program P without any input samples or models, learns an input grammar that represents the syntactically valid inputs for P -- a grammar which can then be used for highly effective test generation for P . To this end, we introduce a test generator targeted at input parsers that systematically explores parsing alternatives based on dynamic tracking of constraints; the resulting inputs go into a grammar learner producing a grammar that can then be used for fuzzing. In our evaluation on subjects such as JSON, URL, or Mathexpr, our PYGMALION prototype took only a few minutes to infer grammars and generate thousands of valid high-quality inputs.
Decision Support in Management of Hardware-Software Complex Functional Safety on the Basis of Ontological Engineering

The problem of functional safety is closely related to the increase in the complexity of hardware-software complexes, external threat danger and the growth in the number of internal causes of emergency situation occurrence. Decision taking support shall facilitate the operational efficiency upgrade, provide for the improved accuracy and feasibility of management solutions in terms of the emergency situation resolving and the recovery of a normal hardware-software complex function. The authors considered the example of hybrid ontology in functional safety management in hardware-software complex.
A Fast and Efficient Method for the Composite Scattering of a Coated Object Above 3D Random Rough Surfaces

This paper presents a fast and efficient method that combines physical optics with physical optics to solve the composite scattering problem of a coated object above 3-D random rough surfaces. The object coated with lossy electric or magnetic radar absorbing materials is modeled as a stratified structure, and 3-D random rough surfaces are generated using Monte Carlo method with Gaussian spectrum. The proposed method utilizes fast and efficient physical optics as a solution for the coated object and the underlying random rough surface. Then a reradiation physical optics method based on Huyghens’ principle is used as a solution for coupling scattering between the coated object and the underlying rough surface. The proposed method is numerically validated by comparing it with the commercial software FEKO and a multihybrid Kirchhoff approximation with the hybrid finite element-boundary integral algorithm. Runtime and memory consumption are also compared. Our method is found to reduce considerable time and memory while maintaining sufficient accuracy. The difference scattering radar cross section of a coated sphere above a 3-D perfectly electric conductor rough surface is numerically simulated. Furthermore, the dependence of difference scattering characteristic on the object coating parameters and the underlying rough surface parameters under different polarizations is discussed.
MicroRNAs as prognostic markers in prostate cancer

Prostate cancer (PCa) is the most commonly diagnosed malignancy in men who are especially over the age of 50 years in the western countries. Currently used therapeutic modalities mostly fail to give positive clinical outcomes and nearly 30% of the PCa patients eventually develop clinical recurrence. Therefore, understanding the underlying mechanisms of PCa progression is of paramount importance to help determining the course of disease. In this study, we aimed at profiling the differentially expressed microRNAs in recurrent PCa samples.
Next of kin's motives for psychosocial consultation—Oncology social workers' perceptions of 54 next of kin cases

Although oncology social workers (OSWs) have emerged as a core profession in the provision of psychosocial services, there is a lack of empirical studies that describe their daily clinical work with next of kin (NOK). The overall aim of this study was to explore NOK's motives for consulting an OSW. This can provide us with insights into what types of skills OSWs need to have in order to fulfil their duties.
Optimization of Concentric Circular Arrays Using a Crossover Improved Genetic Algorithm

Concentric circular antenna array is one of the widely used antenna array configuration in the field of communications due to its capability to scan an all-azimuth and has a beam pattern which is invariant in nature. This paper presents a technique for optimizing the excitation amplitudes of a concentric circular array. The well-known soft computing technique, the Genetic Algorithm (GA) having an improved crossover has been employed to minimize the side lobes levels. The crossover improved GA (CIGA) echoes the motion of fireflies used in the Firefly Algorithm (FA). Simulation results obtained will ensure the productiveness of the proposed method.
5.9 GHz High Sensitivity Rectenna for Low Power Wireless Transmission Application

This paper presents the analysis and the design of a high sensitivity rectenna operating at 5.9 GHz and -5 dBm for microwave power transfer applications. Closed form equations are given to evaluate the output rectifier characteristics as a function of RF input power. A diode parametric analysis using the theoretical model is proposed to evaluate their impact on the circuit performances. The rectifier circuit has been designed and optimised with KEYSIGHT ADS Software. The proposed rectenna has been realised and experimentally characterised. Measurement results validate the design methodology and show an efficiency of 30 % and an output DC voltage around 1 V for a 10 kΩ DC load.
Peritoneal dialysis in Sichuan province of China – report from the Chinese National Renal Data System

Abstract Background: Peritoneal dialysis (PD) is one of the important treatment strategies for end stage renal disease (ESRD). In this study, we aimed to study the patients on PD of Sichuan province in the registry system and to explore the risk factors. Methods: This was a retrospective study based on data from the Chinese National Renal Data System (CNRDS). The outcomes were prevalence and incidence of patients receiving PD, all-cause mortality, technical failure, end events and peritonitis. Results: This study included 2654 patients between 1 January 2010 and 31 December 2016. From 2010 to 2016, despite there were increasing numbers of patients requiring PD. Primary and secondary glomerular diseases were the main causes of ESRD. Erythropoietin, iron and antihypertensive agents were the most commonly used medications in this cohort. 12.43% of patients died and the most important cause of death was cardiac events (30.30%). The incidences of peritonitis were 0.09, 0.16, 0.11, 0.09, 0.08, 0.12 and 0.06 per patient-year, respectively. The most common etiological agent of peritonitis was staphylococcus. We divided the patients into four groups according to the incident months of peritonitis. Compared with <20 months group, the level of calcium and platelet in >60 months group were higher, and the level of ferritin in >60 months group was lower. Conclusion: Our results, representing the first largest report of peritoneal dialysis in the Southwest of China, indicated increasing numbers of patients receiving peritoneal dialysis, which will require need for medical resource.
Reliable Code Disseminations Through Opportunistic Communication in Vehicular Wireless Networks

Large numbers of software-defined sensor devices have formed a basic infrastructure for data collection. One of the challenges is how to update the program codes of devices in a low-cost and reliable style. This paper figures that the vehicular wireless networks (VWNs), combined with a base station (BS) platform, can play a significant role in disseminating program codes in a smart city. A code dissemination algorithm that selects vehicles as disseminators is proposed to accomplish the coverage ratio of codes and benefits of vehicular disseminators in a reliable manner and to reduce the costs of the BS. The algorithm targets to make the disseminators to achieve more coverage regions of a code. The benefit distribution method, which targets the improvement of benefits in suburban regions and encourages vehicle owners, is redefined and differs from previous benefit distribution schemes. Through disseminating, the vehicles can obtain more benefits, and the costs of the BS can be reduced. We ultimately simulate the performances of the selection algorithms with GPS datasets to prove the progressiveness of the “Code Disseminations through Opportunistic Communication in Vehicular Wireless Networks” (CD-VWNs) scheme in terms of coverage and benefits. The benefit-ratio performance criterion can be improved by 21.078% over other models. The coverage-ratio performance criterion can result in an improvement of 31.94% over other selection schemes. The evaluation metric ${\mathcal {Z}}_{r}$ performance criterion can result in an improvement of approximately 25.256%. With the CD-VWNs scheme, loss of codes can be decreased, and the dissemination system remains reliable and survivable.
Minimum Bayes-Risk Phrase Table Pruning for Pivot-Based Machine Translation in Internet of Things

Machine translation, which will be used widely in human–computer interaction services to Internet of Things (IoT), is a key technology in artificial intelligence field. This paper presents a minimum Bayes-risk (MBR) phrase table pruning method for pivot-based statistical machine translation (SMT). The SMT system requires a great amount of bilingual data to build a high-performance translation model. For some language pairs, such as Chinese–English, massive bilingual data are available on the web. However, for most language pairs, large-scale bilingual data are hard to obtain. Pivot-based SMT is proposed to solve the data scarcity problem: it introduces a pivot language to bridge the source language and the target language. Therefore, a source-target translation model based on well-trained source-pivot and pivot-target translation models can be derived with the pivot-based approach. However, due to the ambiguities of the pivot language, source and target phrases with different meanings may be wrongly matched. Consequently, the derived source-target phrase table may contain incorrect phrase pairs. To alleviate this problem, we apply the MBR method to prune the phrase table. The MBR pruning method removes the phrase pairs with the lowest risk from the phrase table. Experimental results on Europarl data show that the proposed method can both reduce the size of phrase tables and improve the performance of translations. This study also gives a useful reference to many IoT research field and smart web services.
Multidisciplinary exhibit design in a Science Centre: a participatory action research approach

Abstract In this paper we highlight the issues and opportunities of a participatory action research (PAR) and co-design project, currently being undertaken as engaged research between academics at Durham University and practitioners at the UK’s International Centre for Life in Newcastle-Upon-Tyne (CfL; see creativescienceatlife.com for more information and developments). The focus is on the use of PAR to enable university researchers and Science Centre professionals to co-design Informal Science Learning exhibits that enhance creativity and innovation in young people. We define the principles of PAR and explore reasons for adopting the approach. An account is provided of the iterative co-design and piloting of a novel exhibit within a new exhibition space at the CfL. Reflections collated independently by the practitioners and the academics involved highlighting the development of ideas and insights over the course of the PAR process. We discuss how PAR enabled effective engagement with and creation of enriched knowledge, and innovation, in both the academy and science-learning professionals. The added value of PAR and co-production to our project aligns with current calls for a redefining of how societal impact of academic research is considered.
Modeling Power Vertical High-k MOS Device With Interface Charges via Superposition Methodology-Breakdown Voltage and Specific ON-Resistance

An analytical model for the power vertical MOS device with a high-k insulating dielectric (HKMOS) is derived via the superposition methodology on the condition of punchthrough. Considering three portions—the superjunction part, the p-i-n diode, and the interface charges at the heterointerface based on the conservation of electric displacement, the HKMOS device could be modeled well as verified by the 2-D simulation results.
Enhanced elevations of hypo-osmotic shock-induced cytosolic and nucleic calcium concentrations in tobacco cells by pretreatment with dimethyl sulfoxide

ABSTRACT Dimethyl sulfoxide (DMSO) is a dipolar aprotic solvent widely used in biological assays. Here, we observed that DMSO enhanced the hypo-osmotically induced increases in the concentration of Ca2+ in cytosolic and nucleic compartments in the transgenic cell-lines of tobacco (BY-2) expressing aequorin.
CVABS: Moving Object Segmentation with Common Vector Approach for Videos

Background modelling is a fundamental step for several real-time computer vision applications that requires security systems and monitoring. An accurate background model helps detecting activity of moving objects in the video. In this work, we have developed a new subspace based background modelling algorithm using the concept of Common Vector Approach with Gram-Schmidt orthogonalization. Once the background model that involves the common characteristic of different views corresponding to the same scene is acquired, a smart foreground detection and background updating procedure is applied based on dynamic control parameters. A variety of experiments is conducted on different problem types related to dynamic backgrounds. Several types of metrics are utilized as objective measures and the obtained visual results are judged subjectively. It was observed that the proposed method stands successfully for all problem types reported on CDNet2014 dataset by updating the background frames with a self-learning feedback mechanism.
Minimize Temperature Effect in High Precision Optical Fiber Based Range Measurement Calibration System

A high precision calibration range measurement system based on optical fiber switches and fiber coils network is described in this paper. To reach the high measurement precision, the phase stabilized optical fiber (PSOF), is used as delay coil to minimize the temperature dependence of transmission delay time. The temperature error can be decreased by 11 times compare with using single-mode optical fiber.
New and Simplified Distributed Algorithms for Weighted All Pairs Shortest Paths

We consider the problem of computing all pairs shortest paths (APSP) and shortest paths for k sources in a weighted graph in the distributed CONGEST model. For graphs with non-negative integer edge weights (including zero weights) we build on a recent pipelined algorithm to obtain $\tilde{O}(\lambda^{1/4}\cdot n^{5/4})$ in graphs with non-negative integer edge-weight at most $\lambda$, and $\tilde{O}(n \cdot \bigtriangleup^{1/3})$ rounds for shortest path distances at most $\bigtriangleup$. Additionally, we simplify some of the procedures in the earlier APSP algorithms for non-negative edge weights in [HNS17,ARKP18]. We also present results for computing h-hop shortest paths and shortest paths from $k$ given sources. In other results, we present a randomized exact APSP algorithm for graphs with arbitrary edge weights that runs in $\tilde{O}(n^{4/3})$ rounds w.h. p. in n, which improves the previous best $\tilde{O}(n^{3/2})$ bound, which is deterministic. We also present an $\tilde{O}(n/\epsilon^2)$-round deterministic $(1+\epsilon)$ approximation algorithm for graphs with non-negative $poly(n)$ integer weights (including zero edge-weights), improving results in [Nanongkai14,LP15] that hold only for positive integer weights.
Left-Side Bias Is Observed in Sequential Matching Paradigm for Face Processing

The left-side bias refers to how a chimeric face is created from the left side of a face (from the viewer’s perspective) and its mirror image are considered more similar to the original face than a chimeric face created from the right side of the same face and its mirror image. Previous studies investigated the left-side bias by using the chimeric stimuli task, where the original face and chimeric face were presented simultaneously. However, it remains unclear whether left-side bias effect is observed when the original face and chimeric face are presented sequentially. We completed two experiments using the sequential matching paradigm to investigate this issue. The results from both Experiment 1 and 2 showed that participants judged the identical proportion of the left chimeric face and original face was significantly higher than that of the right chimeric face and original face, which implies that the left-side bias effect can be observed in the sequential matching paradigm for face processing.
Origin of the Enhanced Photoluminescence Quantum Yield in MAPbBr3 Perovskite with Reduced Crystal Size

Methylammonium lead bromide perovskite (MAPbBr3) has been widely investigated for applications in visible perovskite light-emitting diodes (LEDs). Fine-tuning of the morphology and of the crystal size, from the microscale down to the quantum confinement regime, has been used to increase the photoluminescence quantum yield (PLQY). However, the physical processes underlying the PL emission of this perovskite remain unclear. Here, we elucidate the origin of the PL emission of polycrystalline MAPbBr3 thin films by different spectroscopic techniques. We estimate the exciton binding energy, the reduced exciton effective mass, and the trap density. Moreover, we confirm the coexistence of free carriers and excitons, quantifying their relative population and mutual interaction over a broad range of excitation densities. Finally, the enhanced PLQY upon crystal size reduction to the micro- and nanometer scale in the presence of additives is attributed to favored excitonic recombination together with reduced surface .
Application of Data Mining Techniques to Predict the Length of Stay of Hospitalized Patients with Diabetes

Diabetes is one of the most critical public health conditions worldwide. It has been shown that patients with diabetes are associated with a longer length of hospital stay (LOS) and increased associated healthcare cost. The uncertainty of diabetic patients' LOS makes it difficult for hospitals to optimize their scheduling process. In this paper, we applied the stacked ensemble method, with deep learning as the meta-learning algorithm, to predict long vs. short LOS for diabetic patients. The obtained results show that stacked ensemble technique is promising in this field because stacking multiple classification learning algorithms resulted in a better predictive performance than that obtained from any of the constituent learning algorithms. Having a reasonable estimate on LOS for patients with diabetes can help in optimizing the use of hospital resources, reducing healthcare cost, and improving diabetic patient satisfaction.