Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy-Based Optimization and Control of a Soft Exosuit for Compliant Robot–Human–Environment Interaction

Many previous studies of soft exosuits improved human locomotion performance. However, there is no example to control a soft exosuit using human ankle impedance adaption in assistance tasks compliantly. In this article, the human–environment interaction information is exploited into the exosuit control. A novel fuzzy-based optimization and control method of soft exosuit is proposed to provide plantarflexion assistance for human walking by changing the human–robot interaction. In particular, a fuzzy neurodynamics optimization is developed to learn the unknown human ankle impedance parameters automatically. A fuzzy approximation technique is applied to improve the control performance of the exosuit when a human is walking with unknown human–robot interaction model parameters. This control scheme guarantees that the human–robot dynamics follows a target human ankle impedance model to obtain the compliant interaction performance. Experiments on different participants verify the effectiveness of the control scheme. Results show that a compliant human–robot interaction is achieved by learning the human–environment interaction parameters, i.e., the human ankle parameters. It indicates that our proposed method can facilitate exosuit control to achieve compliant robot–human–environment interaction.
Design for lifecycle robustness of fastening systems

The future requirements on faster and automated construction, improved life‐cycle performance and sustainability of infrastructure in general increasingly promote the use of fastening technology. This paper addresses the concept of lifecycle robustness by introducing an ensemble of technical and management measures, covering the entire life span from design, construction, operation and decommissioning. Although a significant research on robustness and performance indicators has been performed in related areas, such as bridges or nuclear power plants, a framework for the quantification of lifecycle robustness of fastening systems is still not available. The presented proposals are based on the synthesis of theoretical and technological progress, established engineering design approaches and communication procedures, and experimental evidence, all originating from in‐house research and industrial partners. Rather than discussing particular technical aspects, this paper focuses on the uncertainty management and hazard mitigation policies through the entire life span of the fastening systems.
Estimating Incident Duration Considering the Unobserved Heterogeneity of Risk Factors for Trucks Transporting HAZMAT on Expressways

Traffic accidents involving vehicles transporting hazardous materials (HAZMAT) on expressways not only delay traffic flow but can also cause large-scale casualties and socio-economic losses. Therefore, rapid response to and prevention of these accidents is important to minimize such loss. To ensure more efficient accident response, this study applied a random parameter hazard-based Weibull modeling approach to measure the relationship between crash characteristics and accident duration for trucks transporting HAZMAT. The study focuses on finding the key factors that have an impact on the accident duration of these vehicles as well as a statistical method to estimate the accident duration. The analysis is based on raw crash data from 2007 to 2017, obtained from the Korea Expressway Corporation, of crashes that involved HAZMAT trucks. The study found that crashes occurring during peak times of the day; crashes occurring on segments at the mainline, ramp, and roadways with a guardrail; and the number of vehicles involved in a crash, result in random parameters. In addition, the weather, season, crash severity, truck size, crash location, type of accident report, roadside features (e.g., guardrails), and status after a crash, can be used to explain the accident duration. The random parameters hazard-based model is found to have a better fit than a fixed model since it is able to capture the unobserved heterogeneity in the hazard function.
A 4.5-mW 22-nm CMOS Label-Free Frequency-Shift 3 × 3 × 2 3-D Biosensor Array Using Vertically Stacked 60-GHz LC Oscillators

In this brief, a label-free <inline-formula> <tex-math notation="LaTeX">$\mathbf {3\times 3\times 2}$ </tex-math></inline-formula> three-dimensional frequency-shift biosensor array with vertically-stacked 60-GHz on-chip LC oscillators is presented. The 60-GHz LC oscillators function as sensor front-end since the frequency downward shifts due to dielectric derived from biomedical sensing targets. The proposed array element consists of the two vertically-stacked LC oscillators and 15-stage dividers necessary for extracting high-frequency output signals with a long distance. The proposed circuit was designed with Spectre RF simulation and the test chip was fabricated in 22-nm CMOS technology. The whole and element chip size is 0.04 mm2 and 0.0035 mm2 respectively. The measurement with thick and thin silicon resin samples successfully demonstrated their vertical and horizontal detection on the same chip while the prior works only achieved two-dimensional detection. The 22-nm CMOS prototype also showed high spatial resolution <inline-formula> <tex-math notation="LaTeX">$60 ~\mu {\mathrm{ m}} \times 60 ~\mu {\mathrm{ m}} \times 4 ~\mu {\mathrm{ m}}$ </tex-math></inline-formula> and high fill factor 73% while consuming 4.5 mW under 1.2 V per the single-element.
Risk Perception of COVID-19, Religiosity, and Subjective Well-Being in Emerging Adults: The Mediating Role of Meaning-Making and Perceived Stress

The pressured experienced due to COVID-19 for young people has become clearly visible in the domain of well-being. Although the psychological effects of the COVID-19 pandemic on emerging adults have been examined, little is known about the role played by risk perception and religiosity for their well-being. In addition, the mediating effects of meaning-making and perceived stress still need to be investigated. A total of 316 emerging adults (143 males and 173 females) participated in the present study. Using structural equation modeling (SEM) analysis, we showed that the relationship of risk perception of COVID-19 and religiosity with subjective well-being was largely mediated by meaning-making and perceived stress. However, their mediational roles were different and depended on the interplay of perceptual and religious factors, which can be more fully understood within the meaning-making model. Emerging adults tend to rely on both their personal evaluation of COVID-related risks and religious beliefs to the extent that it helps them understand current life situations and restore cognitive and emotional balance.
Molecular Fingerprinting of the Omicron Variant Genome of SARS-CoV-2 by SERS Spectroscopy

The continuing accumulation of mutations in the RNA genome of the SARS-CoV-2 virus generates an endless succession of highly contagious variants that cause concern around the world due to their antibody resistance and the failure of current diagnostic techniques to detect them in a timely manner. Raman spectroscopy represents a promising alternative to variants detection and recognition techniques, thanks to its ability to provide a characteristic spectral fingerprint of the biological samples examined under all circumstances. In this work we exploit the surface-enhanced Raman scattering (SERS) properties of a silver dendrite layer to explore, for the first time to our knowledge, the distinctive features of the Omicron variant genome. We obtain a complex spectral signal of the Omicron variant genome where the fingerprints of nucleobases in nucleosides are clearly unveiled and assigned in detail. Furthermore, the fractal SERS layer offers the presence of confined spatial regions in which the analyte remains trapped under hydration conditions. This opens up the prospects for a prompt spectral identification of the genome in its physiological habitat and for a study on its activity and variability.
Exploring Carrier Sense Multiple Access with Collision Avoidance Techniques for Resource Sharing in Broadband Power Line Communications

A resource sharing in power line communications (PLC) for the home network is restricted by the channel assignment techniques which decide who has the right to gain access to send data. The channel assignment techniques include contention-free and contention-based. The former requires high synchronization due to the deterministic round-trip time. Besides, contention-based utilizes CSMA/CA techniques that allow stations in a network to compete for channel access and are suitable for decentralized network topology. However, a trade-off exists between the number of stations required to gain access versus system efficiency. Whilst some research has been carried out on CSMA/CA resource sharing techniques that allow only one user to transmit, there is very little work done on multiuser access to optimize system efficiency and reduce collisions in a network. The purpose of the current study was to review the CSMA/CA techniques for resource sharing to improve system efficiency in power line communications. In carrying out this study, a systematic literature review methodology to evaluate different related works and determine the most suitable approach to allow multiuser channel access was used. The study further demonstrated the impact multichannel access has on system efficiency. In addition, the study provides recommendations for future research. Keywords: CSMA/CA; Medium access control; OFDMA; power line; resource sharing;
Incorporating Human Preferences in Decision Making for Dynamic Multi-Objective Optimization in Model Predictive Control

We present a new two-step approach for automatized a posteriori decision making in multi-objective optimization problems, i.e., selecting a solution from the Pareto front. In the first step, a knee region is determined based on the normalized Euclidean distance from a hyperplane defined by the furthest Pareto solution and the negative unit vector. The size of the knee region depends on the Pareto front’s shape and a design parameter. In the second step, preferences for all objectives formulated by the decision maker, e.g., 50–20–30 for a 3D problem, are translated into a hyperplane which is then used to choose a final solution from the knee region. This way, the decision maker’s preference can be incorporated, while its influence depends on the Pareto front’s shape and a design parameter, at the same time favorizing knee points if they exist. The proposed approach is applied in simulation for the multi-objective model predictive control (MPC) of the two-dimensional rocket car example and the energy management system of a building.
A Rare Case of New-Onset Ulcerative Colitis in a Nonagenarian

Ulcerative colitis (UC) is one of two major types of inflammatory bowel disease (IBD). It is defined as a chronic idiopathic inflammatory disease limited to the colorectal mucosal layer and characterized by relapsing and remitting episodes of inflammation. UC almost invariably involves the rectum and extends proximally in a continuous distribution to part or the entire colon. Development of disease after 75 years of age is uncommon, with new-onset over the age of 80 accounting only for 1% of all new diagnoses. We present a case of a new onset UC in a 90-year-old patient presenting with painless hematochezia.
Hybrid PWM Strategy for Power Efficiency Improvement of 5-Level TNPC Inverter and Current Distortion Compensation Method

This paper proposes a pulse width modulation (PWM) strategy for improving the efficiency of a 5-level H-bridge T-type neutral point clamped (TNPC) inverter. In the case of the proposed PWM strategy, unlike the conventional PWM strategy in which both of the switching legs of the H-bridge inverter operate at a high frequency, one switching leg of the inverter operates at a low frequency. As the switching frequency is lowered, the switching loss is reduced, this improving the efficiency of the system. The duty references for the switching legs and the operating principle of the inverter are described in detail. The proposed PWM strategy, however, causes distortion of the output filter inductor current. The cause of the distortion has been analyzed and a compensation method is proposed to mitigate the distortion of the current. The effect of the proposed PWM strategy can be predicted through the loss calculation of the inverter for each modulation strategy. Furthermore, current distortion mitigation obtained by compensation method is confirmed through the simulation. In order to verify the effectiveness of the proposed strategy, a 2 kW H-bridge TNPC inverter prototype is implemented and tested. The simulation and experimental results show that the efficiency of the inverter is improved when the proposed PWM strategy is applied.
Experimental realization of boundary-obstructed topological insulators using acoustic two-dimensional Su–Schrieffer–Heeger network

Topological insulators that can host special symmetry-protected boundary states and corner states have attracted increasing intention in acoustic engineering. Recently, the concept of the boundary-obstructed topological (BOT) phases has defined a class of topological phases without bulk energy band closing around zero energy, which greatly broadens the applications of the topological states. In this work, based on the two-dimensional Su–Schrieffer–Heeger network, we show that the band degeneracies around zero energy can be removed to open a complete bandgap by judiciously tuning the hopping terms to break [Formula: see text] symmetry down to [Formula: see text] symmetry but with the topological phase invariant, which can be directly characterized by the BOT phase. Furthermore, we experimentally propose a rigorous acoustic sample to visualize the hierarchy of the in-gap higher-order topological states exactly. Crucially, by designedly connecting the lattice with outside environment, we show that these spectrally isolated states still response to the specific frequencies robustly. Our results are expected to be helpful for manipulating wave propagation and sound energy harvesting.
Physical Layer Framework for the Multi-Gigabit Copper-Fiber Access Networks

ABSTRACT In future, Internet access speeds beyond 1 Gbit/s will be required, which is mainly provided by fiber connections in the fixed access network. A high-performance copper-based transmission technology can enable fiber to the building and fiber to the home installations in a cost-effective copper/fiber hybrid network. ITU has started a project for multi-gigabit copper access (MGfast), as a successor of the G.fast technology with the goal to provide symmetric services with 10 Gbit/s aggregated rate for each subscriber. Besides the use of higher bandwidth up to 424 MHz or 848 MHz, full duplex transmission with echo cancellation is another major improvement in MGfast. Line bonding and frequency bonding allow the use of the same physical layer architecture for different media types. This paper discusses network topologies for the hybrid network and technology options for copper transmission to achieve the desired rate and reach.
Silicon Photonic Modulators for High-Capacity Coherent Transmissions

We discuss system-orientated design and optimization of all-silicon modulators for high-baud-rate (up to 84GBaud) coherent transmissions. We achieved single-carrier net-600Gb/s DP-32QAM and DP-16QAM over 1520km; and 800Gb/s super-channel using a silicon-modulator optical frequency comb.
A Recognition Method of Athletes' Mental State in Sports Training Based on Support Vector Machine Model

Athletes participate in competitive competitions, and the ultimate goal is to better display their personal competitive level in the competition so as to achieve the goal of defeating their opponents and winning the competition. In all types of competitions, most matches are instantaneous, and opportunities are fleeting. The instantaneous nature and fierce competition of sports competitions require athletes who participate in sports competitions to have a high psychological quality. It can be seen that the quality of the mental state directly determines the performance of the athletes in usual training and competition. In the process of sports, if athletes can obtain real-time changes in their mental states when they encounter various situations, they can formulate more targeted and effective training or competition strategies according to the athletes’ states. For the opponent, by analyzing the opponent’s psychological state during exercise, the game strategy can be adjusted in real time in a targeted manner, and the probability of winning the game can be provided. Based on this background, this paper proposes to use support vector machine (SVM) to identify the mental state of athletes during exercise. This paper first collects the data of body movements and facial expressions of athletes during training or competition. Use multimodal data to train an SVM model. Output the emotional state of athletes at different stages based on test data. In order to verify the applicability of the method in this paper to the athlete subjects, several comparative models were used in the experiment to verify the performance of the used models. The experimental results show that the accuracy rate of emotion recognition obtained by this method is more than 80%. This shows that the research in this paper has certain application value.
President Obama’s Humble Face: An Authentic or a Socially Desirable Posturing? A Study on Reactions to Obama’s Autobiographical Self-Disclosures

Referring to the mainstream studies based on the personalization’s hypothesis, which positively evaluates signals of dominance shown by leaders, the analysis of Obama’s rhetoric stays a relevant exception. His risky recall, during his political talks, of his social difficulties as a child of a mixed couple was in fact one of the more surprising aspects of his success. Nevertheless, reactions to his autobiographical sharing were scarcely explored. Based on the idea that these self-disclosures signal his responsivity toward the audience of low social condition and can, therefore, be defined as a sign of humility, this research aims to test if coherence between Obama’s words and his facial expressions of contempt, due to the seriousness of social injustices endured in his childhood, may influence the receivers’ perception of such unexpected communication. Before reading a brief autobiographical sharing taken from a “Back-to-school” speech, a highly ritualized monolog the US President addresses each year to students, 175 Italian participants were presented with a photo of Obama displaying either an expression of contempt (taken from the video of the speech) or a neutral expression. Comparisons between self-assessments of perceptions and reactions of participants assigned to the two experimental conditions show that a facial expression of contempt, coherent with words describing his school difficulties, has been crucial for perceiving this humble political discourse as authentic and not as a simple socially desirable posturing. More studies seem to be needed, however, to understand how humble speech could enhance the positive face of leaders or backfire against them.
Pareto: Fair Congestion Control With Online Reinforcement Learning

Modern-day computer networks are highly diverse and dynamic, calling for fair and adaptive network congestion control algorithms with the objective of achieving the best possible throughput, latency, and inter-flow fairness. Yet, prevailing congestion control algorithms, such as hand-tuned heuristics or those fueled by deep reinforcement learning agents, may struggle to perform well on multiple diverse networks. Besides, many algorithms are unable to adapt to time-varying real-world networking environments; and some algorithms mistakenly overlooked the need of explicitly taking inter-flow fairness into account, and just measured it as an afterthought. In this paper, we propose a new staged training process to train Pareto, a new congestion control algorithm that generalizes well to a wide variety of environments. Different from existing congestion control algorithms running reinforcement learning agents, Pareto is trained for fairness using the first multi-agent reinforcement learning framework that is communication-free. Pareto continues training online adapting to newly observed environments in the real-world. Our extensive array of experiments shows that Pareto (i) performs well in a wide variety of environments, (ii) offers the best fairness when it comes to competing with other flows sharing the same network link, and (iii) improves its performance with online learning to surpass the state-of-the-art.
DECOMPOSING THE GEOMAGNETIC FIELD BY MEANS OF EMPIRICAL ORTHOGONAL FUNCTIONS

The geomagnetic field has been highly studied starting from the first measurements and scientific papers to the present monitoring with the help of satellites. Various methods are used in order to study the characteristics of the geomagnetic field, namely fast Fourier transform (Currie, 1973; Langel et al., 1986), wavelet analysis (Alexandrescu et al., 1995 and 1996; Chambodut and Mandea, 2005; Duka et al., 2012), empirical mode decomposition (Roberts et al., 2007; Jackson and Mound, 2010; Buffet et al., 2009).
Identification of CFHR4 as a Potential Prognosis Biomarker Associated With lmmune Infiltrates in Hepatocellular Carcinoma

Background Complement factor H-related 4 (CFHR4) is a protein-coding gene that plays an essential role in multiple diseases. However, the prognostic value of CFHR4 in hepatocellular carcinoma (HCC) is unknown. Methods Using multiple databases, we investigated CFHR4 expression levels in HCC and multiple cancers. The relationship between CFHR4 expression levels and clinicopathological variables was further analyzed. Various potential biological functions and regulatory pathways of CFHR4 in HCC were identified by performing a Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA). Single-sample gene set enrichment analysis (ssGSEA) was performed to confirm the correlation between CFHR4 expression and immune cell infiltration. The correlations between CFHR4 expression levels in HCC and N6-methyladenosine (m6A) modifications and the competing endogenous RNA (ceRNA) regulatory networks were confirmed in TCGA cohort. Results CFHR4 expression levels were significantly decreased in HCC tissues. Low CFHR4 expression in HCC tissues was significantly correlated with the patients’ sex, race, age, TNM stage, pathological stage, tumor status, residual tumor, histologic grade and alpha fetal protein (AFP) level. GO and KEGG analyses revealed that differentially expressed genes related to CFHR4 may be involved in the synaptic membrane, transmembrane transporter complex, gated channel activity, chemical carcinogenesis, retinol metabolism, calcium signaling pathway, PPAR signaling pathway, insulin and gastric acid secretion. GSEA revealed that the FCGR-activated reaction, PLK1 pathway, ATR pathway, MCM pathway, cascade reactions of PI3K and FGFR1, reactant-mediated MAPK activation and FOXM1 pathway were significantly enriched in HCC with low CFHR4 expression. Moreover, CFHR4 expression was inversely correlated the levels of infiltrating Th2 cells, NK CD56bright cells and Tfh cells. In contrast, we observed positive correlations with the levels of infiltrating DCs, neutrophils, Th17 cells and mast cells. CFHR4 expression showed a strong correlation with various immunomarker groups in HCC. In addition, high CFHR4 expression significantly prolonged the overall survival (OS), disease-specific survival (DSS) and progression-free interval (PFI). We observed a substantial correlation between the expression of CFHR4 and multiple N6-methyladenosine genes in HCC and constructed potential CFHR4-related ceRNA regulatory networks. Conclusions CFHR4 might be a potential therapeutic target for improving the HCC prognosis and is closely related to immune cell infiltration.