Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated calibration method for RLG IMU

To solve the problem in using low-accuracy turntable to calibrate the high-precision ring laser gyroscope inertial measurement unit, a new integrated calibration method is proposed. At first, a static analytical calibration method is applied to coarsely calibrate the initial values of IMU system parameters. Then, based on the error function of strapdown inertial navigation algorithm, an extended Kalman filter is established to refine the obtained coarse parameters. The experiment results show that, the proposed method is able to acquire high-precision calibrated results by using low-accuracy turntable, which decreases the calibration cost of IMU and satisfies the precision requirement of RLG IMU.
Is music listening an effective intervention for reducing anxiety? A systematic review and meta-analysis of controlled studies

Anxiety is the most commonly diagnosed mental health disorder in the EU and 18% of the US population experiences an anxiety disorder at any one time. However, only 20% of individuals experiencing anxiety receive a formally administered intervention, highlighting a need for evidence-based interventions that can be self-administered. Music listening can be flexibly self-administered and may be useful for anxiety reduction, but further evidence is needed. The current paper addressed this by conducting the first systematic review and meta-analysis of controlled studies testing music listening interventions for naturally occurring state anxiety. A protocol was registered on PROSPERO ID: CRD42018104308. Searches were carried out of the Cochrane Library, Ovid MEDLINE, PsycINFO, Embase, Web of Science and CINAHL databases, yielding 6208 records. After screening for eligibility, 24 controlled studies were included in the review and 21 were included in the meta-analysis. Results of the meta-analyses showed that music listening had an overall significant large effect on alleviating anxiety (d = −0.77 [95% CI = −1.26, −0.28], k = 21). It was concluded that music listening is effective for reducing anxiety in a range of groups. Further research should focus on clinical groups with diagnosed mental health problems.
Design of a Damping Controller Using a Metaheuristic Algorithm for Angle Stability Improvement of an MIB System

Low frequency oscillations in large power systems may result in system instability under large disturbances. Power system stabilisers (PSS) play an effective role in damping these low frequency oscillations by injecting a modulating signal in the excitation loop of a synchronous machine. A new metaheuristic optimisation algorithm termed the sine cosine algorithm (SCA) was proposed for optimising PSS controller parameters to obtain an optimal solution with the damping ratio as an objective function. The SCA technique was examined on a single machine infinite bus (SMIB) system under distinct loading situations and matched with a moth flame optimisation technique and evolutionary programming to design a robust controller of PSS. The simulation was accomplished using a linearised mathematical model of the SMIB. The performance of a designed lead lag-controller of PSS was demonstrated using eigenvalue analysis with simulations, showing promising results. The dynamic performance was validated with respect to the damping ratio, the eigenvalue’s location in the s-plane and rotor angle deviation response to demonstrate system stability.
The Early Immune Response of Lymphoid and Myeloid Head-Kidney Cells of Rainbow Trout (Oncorhynchus mykiss) Stimulated with Aeromonas salmonicida

The teleost head kidney is a highly relevant immune organ, and myeloid cells play a major role in this organ’s innate and adaptive immune responses. Because of their complexity, the early phases of the innate immune reaction of fish against bacteria are still poorly understood. In this study, naïve rainbow trout were stimulated with inactivated A. salmonicida and sampled at 12 h, 24 h and 7 d poststimulation. Cells from the head kidney were magnetically sorted with a monoclonal antibody mAB21 to obtain one (MAb21-positive) fraction enriched with myeloid cells and one (MAb21-negative) fraction enriched with lymphocytes and thrombocytes. The gene expression pattern of the resulting cell subpopulations was analysed using a panel of 43 immune-related genes. The results show an overall downregulation of the complement pathway and cytokine production at the considered time points. Some of the selected genes may be considered as parameters for diagnosing bacterial furunculosis of rainbow trout.
Surface Activation of High Performance Polymer Fibers: A Review

Abstract High performance polymer fibers, such as polyester, aliphatic and aromatic polyamides, are well established in several technical applications, including personal protection equipment, sport, automotive or aerospace. This is due to their excellent thermal, mechanical and chemical properties. In the emerging field of textile based high performance composites and intelligent textiles, polymer fibers are often utilized in hybrids, i.e., in combination with other materials such as polymer matrices or metal coatings. In such cases, the step of activating or functionalizing the fibers is essential to enhance interface strength in the hybrid systems. This review provides a broad overview on recently applied activation and functionalization techniques on high performance polymer fibers including wet chemical and physicochemical treatments (e.g., hydrolysis, oxidation, complexation, deposition, flame, plasma treatment). The main objective is to review possible modification mechanisms, elaborate the effect of the modification on the fiber properties, and address possible applications of these techniques. The review also includes a comparison of the different techniques, thereby providing a better understanding of their potentials and restrictions. While the techniques differ in terms of versatility, handling, and environmental impact they all can, given the right choice of process parameters, provide well-defined fiber surface properties for the intended application.
Lower Extremity Kinetics and Kinematics in Runners with Patellofemoral Pain: A Retrospective Case–Control Study Using Musculoskeletal Simulation

Patellofemoral pain (PFP) is a common atraumatic knee pathology in runners, with a complex multifactorial aetiology influenced by sex differences. This retrospective case–control study therefore aimed to evaluate lower limb kinetics and kinematics in symptomatic and control male and female runners using musculoskeletal simulation. Lower extremity biomechanics were assessed in 40 runners with PFP (15 females and 25 males) and 40 controls (15 females and 25 males), whilst running at a self-selected velocity. Lower extremity biomechanics were explored using a musculoskeletal simulation approach. Four intergroup comparisons—(1) overall PFP vs. control; (2) male PFP vs. male control; (3) female PFP vs. female control; and (4) male PFP vs. female PFP—were undertaken using linear mixed models. The overall (stress per mile: PFP = 1047.49 and control = 812.93) and female (peak stress: PFP = 13.07 KPa/BW and control = 10.82 KPa/BW) comparisons showed increased patellofemoral joint stress indices in PFP runners. A significantly lower strike index was also shown in PFP runners in the overall (PFP = 17.75% and control = 33.57%) and female analyses (PFP = 15.49% and control = 40.20%), revealing a midfoot strike in control, and a rearfoot pattern in PFP runners. Peak rearfoot eversion and contralateral pelvic drop range of motion (ROM) were shown to be greater in PFP runners in the overall (eversion: PFP = −8.15° and control = −15.09°/pelvic drop ROM: PFP = 3.64° and control = 1.88°), male (eversion: PFP = −8.05° and control = −14.69°/pelvic drop ROM: PFP = 3.16° and control = 1.77°) and female (eversion: PFP = 8.28° and control = −15.75°/pelvic drop ROM: PFP = 3.64° and control = 1.88°) PFP runners, whilst female PFP runners (11.30°) exhibited a significantly larger peak hip adduction compared to PFP males (7.62°). The findings from this investigation highlight biomechanical differences between control and PFP runners, as well as demonstrating distinctions in PFP presentation for many parameters between sexes, highlighting potential risk factors for PFP that may be addressed through focused intervention modalities, and also the need, where appropriate, for sex-specific targeted treatment approaches.
How to re-enchant workplaces and organizations? An introduction to the special issue

Enchanting work is a polysemic term that can account for multiple interpretations. It can be defined as a feeling of being connected in an affirmative way to existence. In organizational terms, enchanted workplaces are places of wonder that allow people to be active agents, who can impact on their environment, find meaning in their work, and flourish. In this context, enchantment has been operationalized in organizational and managerial literature in a variety of ways, including being resourceful, happy, resilient, passionate, motivated, or healthy at work, among others. The main purpose of this special issue was to highlight those elements that may promote enchanting work environments, and the processes through which (re-)enchantment may be achieved. Also, we were interested in understanding re-enchantment as an internal process. JEL CLASSIFICATION: M50
Computer development based embedded systems in precision agriculture: tools and application

ABSTRACT Precision agriculture (PA) research aims to design decision systems based on agricultural site control and management. These systems consist of observing fields and measuring metrics to optimize yields and investments while preserving resources. The corresponding applications can be found on large agricultural areas based on satellites, unmanned aerial vehicles (UAVs), and sol robots. All these applications based on various algorithms that are complex in terms of processing time. If these algorithms are evaluated offline on work-stations or desktops, this is not the case for algorithms that need to be embedded and should operate and help make real-time decisions. We, therefore, need an advanced study using hardware-software co-design approach to design decision systems to embed different algorithms, including sensor data acquisition and processing units. In this work, we propose a review in processing information tools-based embedded systems in PA algorithms with different applications: weed detection, numerical counting, monitoring of plant indexes, and disease detection. This review has been based on more than 100 papers to extract useful information on the different techniques used and the information processing systems. The elaborated study presents the various tools, databases, and systems in order to extract the advantages and disadvantages of system and application.
Relationship between Mood Improvement and Questioning to Evaluate Automatic Thoughts in Cognitive Restructuring with a Virtual Agent

Cognitive restructuring is a therapeutic technique of cognitive behavior therapy that helps convert negative automatic thoughts to balanced thoughts. Automatic thoughts can be converted by the patient/participant's own objective evaluation from a different perspective. Human therapists ask questions intending to guide the evaluation of automatic thoughts more effectively. Virtual agents, as therapists, have a great potential to support cognitive restructuring. We investigated how a virtual agent could affect the participant's mood when asked questions to evaluate automatic thoughts in cognitive restructuring. We implemented a virtual agent that performs scenario-based dialogue with two types of dialogue scenarios: with and without questions to evaluate automatic thoughts. We conducted a dialogue experiment with 20 healthy graduate students and divided them into two groups of ten, finding that the participant's negative mood significantly improved when the virtual agent asked questions to evaluate the automatic thoughts. Furthermore, the number of helpful questions was significantly correlated with the degree of mood change (ρ=0.81). The results suggest that it is important to provide appropriate questions for cognitive restructuring and that the number of helpful questions reflects the dialogue's effectiveness.
HIV-1 Nef Protein Affects Cytokine and Extracellular Vesicles Production in the GEN2.2 Plasmacytoid Dendritic Cell Line

Plasmacytoid dendritic cells (pDCs) are a unique dendritic cell subset specialized in type I interferon production, whose role in Human Immunodeficiency Virus (HIV) infection and pathogenesis is complex and not yet well defined. Considering the crucial role of the accessory protein Nef in HIV pathogenicity, possible alterations in intracellular signalling and extracellular vesicle (EV) release induced by exogenous Nef on uninfected pDCs have been investigated. As an experimental model system, a human plasmacytoid dendritic cell line, GEN2.2, stimulated with a myristoylated recombinant NefSF2 protein was employed. In GEN2.2 cells, Nef treatment induced the tyrosine phosphorylation of STAT-1 and STAT-2 and the production of a set of cytokines, chemokines and growth factors including IP-10, MIP-1β, MCP-1, IL-8, TNF-α and G-CSF. The released factors differed both in type and amount from those released by macrophages treated with the same viral protein. Moreover, Nef treatment slightly reduces the production of small EVs, and the protein was found associated with the small (size < 200 nm) but not the medium/large vesicles (size > 200 nm) collected from GEN2.2 cells. These results add new information on the interactions between this virulence factor and uninfected pDCs, and may provide the basis for further studies on the interactions of Nef protein with primary pDCs.
On the Performance of Distributed Antenna Array Systems With Quasi-Orthogonal Pilots

In this paper, we address the problem of channel estimation in a single cell massive multiple-input multiple-output (mMIMO) system with distributed antenna arrays (DAA) under the availability of limited pilots. Specifically, we propose to use pilots that are not only orthogonal within a cluster but also minimally correlated across clusters. We show that pilot sets that form mutually unbiased orthonormal bases (MUOB) minimize both inter- and intra-cluster pilot contamination. This also allows us to optimally choose the number of pilots needed to serve a given number of user equipments (UEs) within a DAA-mMIMO system. Following this, we develop an access point (AP) centered UE clustering algorithm to optimally cluster UEs for MUOB pilot allocation. Our experiments reveal that in a DAA-mMIMO system, MUOB not only offers better fairness compared to the traditional orthogonal pilot reuse scheme in terms of channel estimation error and per-UE throughput, but also delivers a higher sum system throughput.
Attention Neural Network for Biomedical Word Sense Disambiguation

In order to improve the disambiguation accuracy of biomedical words, this paper proposes a disambiguation method based on the attention neural network. The biomedical word is viewed as the center. Morphology, part of speech, and semantic information from 4 adjacent lexical units are extracted as disambiguation features. The attention layer is used to generate a feature matrix. Average asymmetric convolutional neural networks (Av-ACNN) and bidirectional long short-term memory (Bi-LSTM) networks are utilized to extract features. The softmax function is applied to determine the semantic category of the biomedical word. At the same time, CNN, LSTM, and Bi-LSTM are applied to biomedical WSD. MSH corpus is adopted to optimize CNN, LSTM, Bi-LSTM, and the proposed method and testify their disambiguation performance. Experimental results show that the average disambiguation accuracy of the proposed method is improved compared with CNN, LSTM, and Bi-LSTM. The average disambiguation accuracy of the proposed method achieves 91.38%.
System on Chip (SoC) for Invisible Electrocardiography (ECG) Biometrics

Biometric identification systems are a fundamental building block of modern security. However, conventional biometric methods cannot easily cope with their intrinsic security liabilities, as they can be affected by environmental factors, can be easily “fooled” by artificial replicas, among other caveats. This has lead researchers to explore other modalities, in particular based on physiological signals. Electrocardiography (ECG) has seen a growing interest, and many ECG-enabled security identification devices have been proposed in recent years, as electrocardiography signals are, in particular, a very appealing solution for today’s demanding security systems—mainly due to the intrinsic aliveness detection advantages. These Electrocardiography (ECG)-enabled devices often need to meet small size, low throughput, and power constraints (e.g., battery-powered), thus needing to be both resource and energy-efficient. However, to date little attention has been given to the computational performance, in particular targeting the deployment with edge processing in limited resource devices. As such, this work proposes an implementation of an Artificial Intelligence (AI)-enabled ECG-based identification embedded system, composed of a RISC-V based System-on-a-Chip (SoC). A Binary Convolutional Neural Network (BCNN) was implemented in our SoC’s hardware accelerator that, when compared to a software implementation of a conventional, non-binarized, Convolutional Neural Network (CNN) version of our network, achieves a 176,270× speedup, arguably outperforming all the current state-of-the-art CNN-based ECG identification methods.
Not Unique, not Universal: Risk Perception and Acceptance of Online Voting Technology by Russian Citizens

What is the connection between Russian citizens' perception of Internet voting and the context of its top down adoption with their readiness to use it? To investigate this question, we use Structural Equation Modeling (SEM) to account for both observed and latent indicators of technology adoption and their linkage with the Internet voting use intent. The authors use survey evidence from VCIOM (2020) and a national survey of Internet users conducted by Online Marketing Intelligence (OMI) company in 2021. This study provides some support to the application of theoretical expectations formulated in the context of Western democracies to the Russian population's voting technology attitudes. The findings indicate that the use of the Internet is not a robust measure of technology acceptance anymore, and a more nuanced approach to the experiences of Internet usage is needed. Internet users appear to be more concerned about privacy, the possibility of fraud, and external interference than the respondents drawn from the overall population. The authors suggest that it is due to acceptance of risks seeming inevitable and to bigger digital literacy and therefore awareness about the risks posed by voting online. Acknowledgments. The authors are grateful to anonymous reviewers for their astute observations and criticism. For their helpful comments, we thank our senior colleagues at HSE University: A. S. Akhremenko, K. L. Marquardt, and M. G. Mironyuk.
Investigation of Wind Tunnel and Flight Correlation Research Ideas on External-store Drop

Based on the status of external-store drop wind tunnel test, the characteristics and factors that affect real simulation of external-store drop on wind tunnel test of the three methods, including dynamic similarity, captive trajectory and grid method, were analyzed comprehensively. The ideas of correlation research of wind tunnel and flight test of externalstore drop were presented and discussed to provide the reference to the design and research of external-store drop.
The Dynamic Relationship between Air and Land Surface Temperature within the Madison, Wisconsin Urban Heat Island

The urban heat island (UHI) effect, the phenomenon by which cities are warmer than rural surroundings, is increasingly important in a rapidly urbanizing and warming world, but fine-scale differences in temperature within cities are difficult to observe accurately. Networks of air temperature (Tair) sensors rarely offer the spatial density needed to capture neighborhood-level disparities in warming, while satellite measures of land surface temperature (LST) do not reflect the air temperatures that people physically experience. This analysis combines both Tair measurements recorded by a spatially-dense stationary sensor network in Dane County, Wisconsin, and remotely-sensed measurements of LST over the same area—to improve the use and interpretation of LST in UHI studies. The data analyzed span three summer months (June, July, and August) and eight years (2012–2019). Overall, Tair and LST displayed greater agreement in spatial distribution than in magnitude. The relationship between day of the year and correlation was fit to a parabolic curve (R2 = 0.76, p = 0.0002) that peaked in late July. The seasonal evolution in the relationship between Tair and LST, along with particularly high variability in LST across agricultural land cover suggest that plant phenology contributes to a seasonally varying relationship between Tair and LST measurements of the UHI.
Generation, characterization, and protective ability of mouse monoclonal antibodies against the HA of A (H1N1) influenza virus

Influenza virus infections pose a continuous threat to human health. Although vaccines function as a preventive and protective tool, they may not be effective due to antigen drift or an inaccurate prediction of epidemic strains. Monoclonal antibodies (mAbs) have attracted wide attention as a promising therapeutic method for influenza virus infections. In this study, three hemagglutinin (HA)‐specific mAbs, named 2A1, 2H4, and 2G2, respectively, were derived from mice immunized with the HA protein from A/Michigan/45/2015(H1N1). The isolated mAbs all displayed hemagglutination inhibition activity and the 2G2 mAb exhibited the strongest neutralization effect. Two amino acid mutations (A198E and G173E), recognized in the process of selection of mAb‐resistant mutants, were located in antigenic site Sb and Ca1, respectively. In prophylactic experiments, all three mAbs could achieve 100% protection in mice infected with a lethal dose of A/Michigan/45/2015(H1N1). A dose of 1 mg/kg for 2H4 and 2G2 was sufficient to achieve a full protective effect. Therapeutic experiments showed that all three mAbs could protect mice from death if they received the mAb administration at 6 h postinfection, and 2G2 was still protective after 24 h. Our findings indicate that these three mAbs may have potential prevention and treatment value in an H1N1 epidemic, as well as in the study of antigen epitope recognition.