Miracle-dz/UniFAR-FTUs huggingface dataset:
A Trusted Supply Chain Management System Based on Permissioned Blockchains

At present, the supply chain system has many problems, such as a large number of scattered participants, which make it difficult to centralize management and operation. Also, it is difficult to integrate data and information, and establish trust relationships between parties. To address these problems, we propose a trusted supply chain management (SCM) system based on permissioned blockchains (BCs) to making the transaction information between alliance companies which is transparent enough to establish mutual trust. We design and develop a supply chain prototype system based on permissioned BCs, smart contract and internet of things (IoT). Use IoT technologies, such as quick response code (QRC), radio frequency identification (RFID) and near field communication (NFC), to realize the automatic upload of entities data of the supply chain. The dual-BCs system architecture is designed to ensure the high throughput and scalability of the system. The smart contracts to making the supply chain system more automated, more secure and credible. Finally, the effectiveness of the design scheme is demonstrated by combining the specific application scenario with the practical case.
Concurrent Algorithms in Transactional Data Structures

Software transactional memory (STM) simplifies the challenging, yet increasingly critical task of parallel programming. Using STM allows programmers to reason about concurrent operations in terms of transactions—groups of operations guaranteed to have atomic effect. Our STM system, STO (Software Transactional Objects), outperforms previous STM systems, but its performance still falls short of that of the fastest concurrent programming techniques. This work aims to make STO as fast as these techniques, and, when this appears impossible, to characterize precisely why. We implement and benchmark the most performant concurrent programming algorithms for abstract datatypes within STO’s transactional framework. Our results indicate that certain concurrent datatype algorithms lose their scalability and performance in a transactional setting, while other algorithms successfully support transactions without incurring a crippling performance loss. We claim that this discrepancy arises because various concurrent algorithms have different levels of dependency on operation commutativity, and suffer different amounts of commutativity loss in a transactional setting. To support this claim, we pose an alternative operation interface that allows for greater operation commutativity, and, with this interface, re-implement a concurrent datatype whose performance is crippled in a transactional setting. This concurrent datatype is then able to retain its performance and scalability in a transactional setting. We conclude that examining both a datatype’s dependency on operation commutativity, and the loss of commutativity of a particular datatype interface in a transactional setting, is enough to determine whether a concurrent, non-transactional data structure will achieve high scalability and performance when integrated with STO.
Millimeter-wave wireless signal discrimination device using electro-optic modulator with antenna-coupled electrodes and polarization-reversed structures of ferroelectric optical crystal

Millimeter-wave space-division-multiplexing signals were discriminated by a newly-developed electro-optic modulator using an array of antenna-coupled electrodes and polarization-reversed structures of ferroelectric optical crystals. Channel isolation over 13dB was obtained for two 38GHz wireless signals with an irradiation angle difference of 15 degrees by use of a fabricated device 30mm in length. In this paper, the device structure, operation principle, analysis, and experimental demonstrations are presented.
Trapezius muscle EMG as predictor of mental stress

Stress is a growing problem in society and can, amongst others, induce musculoskeletal complaints, related to sustained muscle tension. The ability to measure stress with a wireless system would be useful in the prevention of stress-related health problems. The aim of this experiment was to derive stress levels of subjects from electromyography (EMG) signals of the upper trapezius muscle. Two new stress tests were designed for this study, which aimed at creating circumstances that are similar to work stress. An experiment is described in which EMG signals of the upper trapezius muscle were measured during three different stressful situations. Stress tests included a calculation task (the Norinder test), a logical puzzle task and a memory task, of which the last two were newly designed. The results show significantly higher amplitudes of the EMG signals during stress compared to rest and fewer gaps (periods of relaxation) during stress. Also, mean and median frequencies were significantly lower during stress than during rest. The differences in EMG features between rest and stress conditions indicate that EMG is a useful parameter to detect stress. These results show opportunities for the inclusion of EMG sensors in a wireless system for ambulatory monitoring of stress levels.
Methodology for rotor angle transient stability assessment in parameter space

In this paper, an efficient methodology to assess Rotor Angle Stability (RAS) in parameter-space has been proposed. This methodology maps deformations of the power system RAS region under operational changes to a security region in parameter-space that can be assessed on-line. In order to choose the proper parametrization, security boundaries have been constructed using polynomial regression models with coefficients obtained from Ordinary Least Squares (OLS). The identification of suitable parametrization has been carried out, and the newly introduced sensitivity of a Single Machine Equivalent (SIME) has been employed to describe the behaviour of a power system along different parameter-space directions. For the chosen parametrization, Constrained Least Squares (CLS) optimization set up as a Quadratic Programming (QP) problem has been used in order to keep the estimates inside the security region. The case study has been carried out using small test systems in two and three-dimensional parameter-spaces.
Predictors of eGFR progression, stabilisation or improvement after chronic renal impairment in HIV-positive individuals.

OBJECTIVES The objectives of this analysis were to investigate predictors of progression, stabilisation or improvement in eGFR after development of chronic renal impairment (CRI) in HIV-positive individuals. DESIGN Prospective observational study. METHODS D:A:D study participants progressing to CRI defined as confirmed, ≥3 months apart, eGFR≤70 mL/min/1.73m were included in the analysis. The median of all eGFRs measured 24-36 months post-CRI was compared to the median eGFR defining CRI, and changes were grouped into: improvement (>+10 mL/min/1.73m), stabilisation (-10 to +10 mL/min/1.73m) and progression (<-10 mL/min/1.73m). Adjusted polynomial regression models assessed odds of better eGFR outcomes after CRI, assuming eGFR improvement is better than stabilisation which in turn is better than progression. RESULTS Of 2006 individuals developing CRI, 21% subsequently improved eGFR, 67% stabilised and 12% progressed. Individuals remaining on TDF or boosted atazanavir (ATV/r) 24 months post-CRI had worse eGFR outcomes compared to those unexposed (TDF: 0.47 [0.35-0.63], ATV/r: 0.63 [0.48-0.82]). Individuals off TDF for 12-24 months (0.75 [0.50-1.13]) or off ATV/r for >12 months (1.17 [0.87-1.57]) had similar eGFR outcomes as those unexposed to these ARVs. Older age, hypertension, later date of CRI and diabetes were associated with worse eGFR outcomes. CONCLUSION Current TDF and ATV/r use after a diagnosis of CRI was associated with worse eGFR outcomes. In contrast, TDF and ATV/r discontinuation lead to similar longer-term eGFR outcomes as in those unexposed suggesting these drug- associated eGFR declines may be halted or reversed after their cessation.
Spatiotemporal limits of optogenetic manipulations in cortical circuits

Neuronal inactivation is commonly used to assess the involvement of groups of neurons in specific brain functions. Optogenetic tools allow manipulations of genetically and spatially defined neuronal populations with excellent temporal resolution. However, the targeted neurons are coupled with other neural populations over multiple length scales. As a result, the effects of localized optogenetic manipulations are not limited to the targeted neurons, but produces spatially extended excitation and inhibition with rich dynamics. Here we benchmarked several optogenetic silencers in transgenic mice and with viral gene transduction, with the goal to inactivate excitatory neurons in small regions of neocortex. We analyzed the effects of the perturbations in vivo using electrophysiology. Channelrhodopsin activation of GABAergic neurons produced more effective photoinhibition of pyramidal neurons than direct photoinhibition using light-gated ion pumps. We made transgenic mice expressing the light-dependent chloride channel GtACR under the control of Cre-recombinase. Activation of GtACR produced the most potent photoinhibition. For all methods, localized photostimuli produced photoinhibition that extended substantially beyond the spread of light in tissue, although different methods had slightly different resolution limits (radius of inactivation, 0.5 mm to 1 mm). The spatial profile of photoinhibition was likely shaped by strong coupling between cortical neurons. Over some range of photostimulation, circuits produced the “paradoxical effect”, where excitation of inhibitory neurons reduced activity in these neurons, together with pyramidal neurons, a signature of inhibition-stabilized neural networks. The offset of optogenetic inactivation was followed by rebound excitation in a light dose-dependent manner, which can be mitigated by slowly varying photostimuli, but at the expense of time resolution. Our data offer guidance for the design of in vivo optogenetics experiments and suggest how these experiments can reveal operating principles of neural circuits.
Development of a hybrid MEMS BLDC micromotor

This paper addresses the design of a new hybrid MEMS micromotor. It is a small 3-phases axial flux BLDC motor. The stator is realized following the almost CMOS technology rules used for MEMS manufacture and the coils have two copper layers. The rotor is made of a standard ring permanent magnet assembled over the stator chip. The stator design has been performed using an analytical model also presented in the paper. The microfabrication of the first prototypes is discussed before their characterization. With a Joule efficiency of about 31% for an input power lower then 400 nW, this MEMS micromotor has very good performances and demonstrates the potential of electromagnetic systems at this scale.
Decoding the Urban Landscape

The paper presents the results of several studies concerning urban landscape (types and evolution tendencies) based on case study of various Romanian tourist cities. The study outlines that the natural and architectural urban tourist resource is generated by different urban landscape elements, not only the main tourist resource itself. One of the conclusions of the survey is that the landscape is one of the most important existent resources, but despite that is the most transformed element due to urban development pressures, especially within the existent urban landscape frame. In accordance with present development trends, the study outlines the main features that can characterise a landscape at urban level and the transformations that affected Romanian tourist destinations in the latest years. A very important aspect of urban landscape is its complexity – being in the same time society’s living environment, a cultural, historical and economical context and further development matrix – spatially expressed at territorial level. The paper wants to formulate the main development principles that should be included in urban development policies in order to preserve the main landscape and architectural features of these tourist towns.
Numerical analysis of heat transfer in air-water heat exchanger with microchannel coil

This paper presents numerical analysis of fluid flow and heat transfer in the heat exchanger with microchannel coil (MCHX). In accordance with previously published experimental results, 3D mathematical model has been defined and appropriate numerical simulation of heat transfer has been performed. Geometry and working parameters of cross-flow air-water heat exchanger with microchannel coil, installed in an open circuit wind tunnel and used in experimental investigations, have been applied in numerical analysis in order to validate the mathematical model. 3D model with air and water fluid flow and heat transfer domains has been used, as it gives more precise results compared to models that assume constant temperatures or constant heat fluxes on the pipe walls. Developed model comprised full length of air and water flows in the heat exchanger. Due to limitations of computational capacity, domain has been divided in multiple computational blocks in the water flow direction and then solved successively using CFD solver Fluent. Good agreement between experimentally measured and numerically calculated results has been obtained. The influence of various working parameters on heat transfer in air-water heat exchanger has been studied numerically, followed with discussion and final conclusions.
Degradation Prediction of PEM Fuel Cell Stack Based on Multiphysical Aging Model With Particle Filter Approach

In this paper, a novel degradation prediction model for proton-exchange-membrane fuel cell (PEMFC) performance is proposed based on a multiphysical aging model with particle filter (PF) and extrapolation approach. The proposed multiphysical aging model considers major internal physical aging phenomena of fuel cells, including fuel cell ohmic losses, reaction activity losses, and reactants mass transfer losses. Furthermore, in order to obtain accurate values of electrochemical activation losses under a variable load profile, a bisection solver is presented to solve the implicit Butler–Volmer equation. The proposed aging model is initialized at first by fitting the PEMFC polarization curve at the beginning of lifetime. During the prediction process, the aging dataset is then divided into two parts, learning and prediction phases. The PF framework is used to study the degradation characteristics and update the aging parameters during the learning phase. The suitable fitting curve functions are then selected to satisfy the degradation trends of trained aging parameters, and used to further extrapolate the future values of aging parameters in the prediction phase. By using these extrapolated aging parameters, the prediction results are thus obtained from the proposed aging model. Three experimental validations with different aging testing profiles have been performed. The results demonstrate the robustness and advantages of the proposed prediction method.
Genotyping of strains by Multilocus VNTR Analysis

(C.) is the causative agent of ovine enzootic abortion with zoonotic potential whose epidemiology has been held back because of the obligate intracellular habitat of the bacterium. In the present study we report on a molecular typing method termed Multiple Loci Variable Number of Tandem Repeats (VNTR) Analysis (MLVA) for exploring the diversity of . An initial analysis performed with 34 selected genetic loci on 34 ruminant strains including the variant Greek strains LLG and POS resulted in the identification of 5 polymorphic loci, confirming the widely held notion that is a very homogeneous species. Analysis of additional 111 samples with the selected 5 loci resulted in the classification of all strains into 6 genotypes with distinct molecular patterns termed genotypes [1] through [6]. Interestingly, the classification of the isolates in the 6 genotypes was partly related to their geographical origin. Direct examination of clinical samples proved the MLVA to be suitable for direct typing. Analysis of the genomic sequences in 6 prototypes of amplicons generated with each of the 5 selected VNTR primers revealed that variation between genotypes was caused by the presence or absence of coding tandem repeats in 3 loci. Amplification of reference strains with the 5 selected VNTR primers and of the 6 prototype strains with the 8 VNTR primers established for the typing of (Laroucau ., 2008) showed that both MLVA typing systems were species-specific when all respective VNTR primer sets were used.
A wireless propagation channel model with meteorological quantities using neural networks

Deterministic channel modeling approaches are slow to run, require a detailed description of the environment (which is sometimes expensive or even impossible to obtain) and may be difficult to implement. A new approach for the modeling of wireless propagation in LOS environment is presented. We treat the meteorological conditions by weather variations through using neural networks. The aim of the paper is to propose a neural model for understanding the relation between the path loss, the propagation delay and the atmosphere parameters such as humidity, pressure, temperature. It is clarified the propagation factors affecting the wireless channel in the frequency range 300 MHz to 100 GHz. We use grey box approach based on fundamental principles of radio wave propagation physics and measurement data. To verify the accuracy of the model, evaluation and validation of the model are performed by simulating the channel using different sets of actual data from different situations. It is shown that this model can handle unusual atmosphere conditions and the model can be applied to better calculate the delay propagation.
A Simplification Method for Power Device Thermal Modeling With Quantitative Error Analysis

To evaluate the reliability of power electronic systems, it is necessary to estimate the junction temperatures of power devices under periodic power loss profiles due to the fundamental-frequency current. However, a large number of periodic power loss profiles under long-term reliability evaluation (e.g., 1 year) are challenging to compute quickly. On the other hand, in order to improve computational efficiency, unvalidated simplified thermal analysis methods may impair the confidence of the reliability outcome. Therefore, this paper proposes an analytical model for power semiconductors with a compromise of the thermal estimation accuracy and computational efficiency. With the proposed model, it is indicated that minimum computation efforts can be obtained for thermal estimation under a maximum allowable error. The proposed method, thus, enables computation-efficient thermal stress analysis for power semiconductor devices with a preset modeling error. The effectiveness of the proposed method has been verified by simulations and experiments on a power electronic system with 1200-V/50-A insulated gate bipolar transistor (IGBT) modules.
Spatially-explicit simulation of two-way coupling of complex socio-environmental systems: Socio-hydrological risk and decision making in Mexico City

We present here MEGADAPT (MEGAcity-ADAPTation), a hybrid, dynamic, spatially-explicit, integrated modeling approach to simulate the vulnerability of urban coupled socio-environmental systems – in our case, the vulnerability of Mexico City to socio-hydrological risk. Although vulnerability is widely understood to be influenced by human decision-making, these decisions are rarely captured as endogenous to dynamic vulnerability models. The objective of this paper is to use MEGADAPT to demonstrate a methodological approach that allows vulnerability to be simulated as a reflexive process: the result of the interplay between mental models held by influential actors and the response of the biophysical and social world to the realization of decisions based on these mental models. MEGADAPT represents Mexico City as a self-organizing system. Hence, its computational framework involves the implementation of a suite of system models, geographic information system-multicriteria decision analysis, and geosimulation. A novel contribution of this approach is the use of the Analytic Network Process to synthesize the dynamic feedback between mental models and conditions of geographic automata. In this way, MEGADAPT depicts the shift in the behavior of socio-environmental systems from one-way coupling/single-loop learning to two-way coupling/double-loop learning, with the decision-making process as an endogenous system driver.
Analysis and Design of the Stewart Platform-Based Parallel Support Bumper for Inertially Stabilized Platforms

Stewart platform-based parallel support bumpers are widely used to prevent external shocks from damaging inertial navigation systems. Aiming at a severe problem that the inertially stabilized platform becomes out of control as soon as a specified shock is posed on the base of the bumper in shock tests, analysis, and design of the 18-leg Stewart platform-based parallel support bumper are conducted in this paper. With the help of generalized coordinate definition, a kinetic model of the parallel support bumper is established, of which inertia, stiffness, and damping matrices are derived based on kinetic energy, elastic potential energy, and damping dissipation function, respectively. The stiffness matrix is subsequently calculated in detail; intensive parameter design of the 18-leg bumpers is carried out according to the principle of stiffness equality and coupled motion reduction, and the corresponding kinetics is analyzed with Laplacian transformation. Theoretical and simulation results show that a half-sinusoidal shock with a magnitude of 25 g along a horizontal axis of the bumper base can cause rotational motion along the perpendicular horizontal axis with maximum acceleration of 2.762 × 103 °/s2, velocity of 42.3 °/s, and displacement of 3.16°, which would cause the aforementioned losing control problem if the inertially stabilized platform were not reasonably designed.
Compression of CQI feedback with compressive sensing in adaptive OFDM systems

In multiuser wireless communication systems, adaptive modulation and scheduling are promising techniques for increasing the system throughput. To achieve this goal, it is necessary to feed back the information of channel quality indication (CQI). The required feedback rate can be prohibitively high in multicarrier OFDM systems and so the feedback information needs to be compressed. In this paper, a novel CQI feedback scheme is proposed based on the recently proposed compressive sensing theory, and the performance of the scheme is shown to outperform the DCT compression method which is usually considered as the best.
Global Distribution and Evolution of Mycobacterium bovis Lineages

Mycobacterium bovis is the main causative agent of zoonotic tuberculosis in humans and frequently devastates livestock and wildlife worldwide. Previous studies suggested the existence of genetic groups of M. bovis strains based on limited DNA markers (a.k.a. clonal complexes), and the evolution and ecology of this pathogen has been only marginally explored at the global level. We have screened over 2,600 publicly available M. bovis genomes and newly sequenced two wildlife M. bovis strains, gathering 823 genomes from 21 countries and 21 host-species, including humans, to complete a phylogenomic analyses. We propose the existence of four distinct global lineages of M. bovis (Lb1, Lb2, Lb3 and Lb4) underlying the current disease distribution. These lineages are not fully represented by clonal complexes and are dispersed based on geographic location rather than host species. Our data divergence analysis agreed with previous studies reporting independent archeological data of ancient M. bovis [(South Siberian infected skeletons at ∼2,000 years BP (before present)] and indicates that extant M. bovis originated during the Roman period, subsequently dispersing across the world with the discovery and settlement of the New World and Oceania, directly influenced by trades among countries.