Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing Stress Detection: A Comprehensive Approach through rPPG Analysis and Deep Learning Techniques

Stress has emerged as a major concern in modern society, significantly impacting human health and well-being. Statistical evidence underscores the extensive social influence of stress, especially in terms of work-related stress and associated healthcare costs. This paper addresses the critical need for accurate stress detection, emphasising its far-reaching effects on health and social dynamics. Focusing on remote stress monitoring, it proposes an efficient deep learning approach for stress detection from facial videos. In contrast to the research on wearable devices, this paper proposes novel Hybrid Deep Learning (DL) networks for stress detection based on remote photoplethysmography (rPPG), employing (Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), 1D Convolutional Neural Network (1D-CNN)) models with hyperparameter optimisation and augmentation techniques to enhance performance. The proposed approach yields a substantial improvement in accuracy and efficiency in stress detection, achieving up to 95.83% accuracy with the UBFC-Phys dataset while maintaining excellent computational efficiency. The experimental results demonstrate the effectiveness of the proposed Hybrid DL models for rPPG-based-stress detection.
Statistical physics of learning and inference

The exchange of ideas between statistical physics and computer science has been very fruitful and is currently gaining momentum as a consequence of the revived interest in neural networks, machine learning and inference in general. Statistical physics methods complement other approaches to the theoretical understanding of machine learning processes and inference in stochastic modeling. They facilitate, for instance, the study of dynamical and equilibrium properties of randomized training processes in model situations. At the same time, the approach inspires novel and efficient algorithms and facilitates interdisciplinary applications in a variety of scientific and technical disciplines.
Research on the Application of Broadband IC-Stripline Cell Radiation Emission

With the continuous improvement of chip integration, the problem of integrated circuit (IC) electromagnetic compatibility (EMC) is becoming more and more prominent. The continuous improvement of the working frequency of ICs requires a wider band of IC-EMC measurement equipment. IC-Stripline cell is important measurement equipment in the field of IC-EMC. And in recent years, several new types of broadband IC-Stripline cells have emerged, such as standard IC-Stripline cell, dielectric IC-Stripline cell and slotted septum IC-Stripline cell. Based on standards, the paper compares the radiation emission test results of three types IC-Stripline cells and analyzes the reasons for test errors.
Artificial Intelligence-Enabled Customer Value Proposition Capability and Market Performance: The Moderating Role of Environmental Heterogeneity

Although artificial intelligence (AI) is becoming increasingly commonplace, many firms are still struggling to develop viable AI initiatives. Drawing on the dynamic capabilities theory, this article proposes a new framework to explore the relationships among AI-enabled customer value proposition capability (AI-CVPC), two customer response capabilities (i.e., response speed and response expertise), environmental heterogeneity, and market performance. The results from 400 Chinese firms across various sectors reveal that response speed and response expertise are two key mediators that link the positive association between AI-CVPC and market performance. More interestingly, environmental heterogeneity enhances the mediating role of response expertise, rather than the mediating role of response speed. This article contributes to the current AI-related business literature by developing a new moderated mediation model that explains the association between AI-CVPC and market performance. These findings also shed fresh light on the areas that firms should prioritize when developing their AI initiatives.
Efficient and Robust Controller Design Automation for Power Converters

The global penetration of power electronics (PE) has increased significantly, creating a pressing need for efficient and cost-effective design automation tool for PE controllers. However, the conventional controller design approach remains largely a trial-and-error process, making it challenging to meet the current design requirements. This paper presents a new design method based on model-free control (MFC) technique, enabling the identification of optimal control parameters efficiently while considering manufacturing aspects such as component tolerances and variation. The proposed method also offers superior dynamics and robustness performance compared to conventional control methods. A case study of a 25-W buck converter, accounting for circuit parameter variations, demonstrates that the proposed controller design method significantly reduces the design run time by two orders of magnitude compared to the conventional design method, while achieving faster dynamics and greater robustness than the PI controller. We anticipate that this new approach will substantially reduce the time and cost for future PE controller design, facilitating the mass and quick uptake of PE.
Current crustal deformation of the Taiwan orogen reassessed by cGPS strain-rate estimation and focal mechanism stress inversion

S U M M A R Y We study internal deformation of the Taiwan orogen, a young arc-continental collision belt, which the spatial heterogeneity remains unclear. We aim to ascertain heterogeneity of the orogenic crust in depth when specifying general mechanisms of the Taiwan orogeny. To reach this goal, we used updated data of continuous GPS (cGPS) and earthquake focal mechanisms to reassess geodetic strain-rate and seismic stress fields of Taiwan, respectively. We updated the both data sets from 1990 to 2015 to provide large amount of constraints on surficial and internal deformation of the crust for a better understanding. We estimated strain-rate tensors by calculating gradient tensors of cGPS station velocities in horizontal 0.1◦-spacing grids via Delaunay triangulation. We determined stress tensors within a given horizontal and vertical grid cell of 0.1◦ and 10 km, respectively, by employing the spatial and temporal stress inversion. To minimize effects of the 1999 Mw 7.6 Chi–Chi earthquake on trends of the strain and stress, we modified observational possible bias of the cGPS velocities after the earthquake and removed the first 15-month focal mechanisms within the fault rupture zone. We also calculated the Anderson fault parameter (Aφ) based on stress ratios and rake angles to quantitatively describe tectonic regimes of Taiwan. By examining directions of seismic compressive axes and styles of faulting, our results indicate that internal deformation of the crust is presently heterogeneous in the horizontal and vertical spaces. Directions of the compressive axes are fan-shaped oriented between N10◦W and N110◦W in the western and mid-eastern Taiwan at the depths of 0–20 km and near parallel to orientations of geodetic compressional axes. The orientations agreed with predominantly reverse faulting in the western Taiwan at the same depth range, implying a brittle deformation regime against the Peikang Basement High. Orientations of the compressive axes most rotated counter-clockwise at the depths of 20–40 km, coinciding with transition of styles of faulting from reverse to strike-slip faulting along the depths as revealed by variation of the Aφ values. The features indicate that internal deformation of the upper crust is primarily driven by the same compressional mechanism. It implies that geodetic strains could detect the deformation from surface down to a maximal depth of 20 km in most regimes of Taiwan. We find that heterogeneity in orientations of compressive axes and styles of faulting is strong in two regimes at the northern and southern Central Range, coinciding to areas of the orogenic thinned/thickened crust. Conversely, the heterogeneity is weak in the central Western Foothills at surrounding area of root of the overthickened crust. This observation, coupled with regional seismological observations, may imply that vertical deformation from crustal thickening and thinning and thinning-related dynamics from mantle flows may have joint influence on degree of stress heterogeneity.
Biomechanical Effect of Distal Tibial Oblique Osteotomy: A Preliminary Finite-Element Analysis

Background: The biomechanical effect of distal tibial oblique osteotomy (DTOO) on osteoarthritic ankles has not been investigated. Using finite element (FE) models, we aimed to elucidate the effect of DTOO on the ankle contact pressure (CP) distribution. Methods: This study included two patients with ankle osteoarthritis who underwent DTOO and one asymptomatic control. Patient-specific FE models were reconstructed by matching standing radiographs with supine computed tomography scans. The joint contact area (CA) and maximum CP on the articular surface of the talus were calculated before and after DTOO and compared with those of the control. Results: In the control, the CA was 584 mm2 and the maximum CP was 2.6 MPa. In case 1, the CA increased by 125% from 166 mm2 preoperatively to 375 mm2 postoperatively, accompanied by a 36% decrease in the maximum CP from 9.8 MPa to 6.3 MPa. Similarly, in case 2, the CA increased by 46% from 301 mm2 to 439 mm2, accompanied by a 27% decrease in the maximum CP from 6.7 MPa to 4.9 MPa. Conclusions: This study suggests DTOO improves the biomechanics of the ankle, but not sufficiently compared to the control. This analytical approach may enhance understanding of ankle pathophysiology and assist in the design of the ideal corrective osteotomy.
Effects of Clostridium tyrobutyricum on Lipid Metabolism, Intestinal Barrier Function, and Gut Microbiota in Obese Mice Induced by High-Fat Diet

Obesity and its complications constitute a main threat to global human health. The purpose of this investigation was to explore the influences of Clostridium tyrobutyricum (Ct) on lipid metabolism, intestinal barrier function, and intestinal microbiome in obese mice induced by a high-fat diet (HFD). After establishing the obesity model, 107 CFU/mL and 108 CFU/mL C. tyrobutyricum were used to intervene in HFD-fed mice by gavage for six weeks, and indexes related to obesity were measured. In the liver of HFD-fed mice, the results revealed that C. tyrobutyricum reduced liver weight and the levels of triglyceride (TG), total cholesterol (TC), and nonesterified fatty acid (NEFA), along with decreasing red lipid droplets and fat vacuoles. After C. tyrobutyricum intervention, the mRNA expression of peroxisome proliferator-activated receptor-γ (PPARγ) was downregulated, and AMP-activated protein kinase (AMPK), peroxisome proliferator-activated receptor-α (PPARα), adipose triglyceride lipase (ATGL), and hormone-sensitive lipase (HSL) were upregulated in the liver. Additionally, C. tyrobutyricum alleviated intestinal morphology injury caused by HFD, decreased the expression of tumor necrosis factor-α (TNF-α), interleukin 6 (IL-6), and IL-1β in the colon, and upregulated tight junction protein expression. In addition, 16S rRNA sequencing revealed that C. tyrobutyricum increases the diversity of intestinal microbiota. Overall, C. tyrobutyricum improved HFD-induced lipid metabolism disorders, preserved the intestinal barrier’s integrity, and modulated the structure of the intestinal microbiome. These findings provide a novel insight into the role of C. tyrobutyricum as a probiotic in regulating lipid metabolism.
The test-retest reliability of the Opiate Treatment Index in nyaope users in Johannesburg

Background Epidemiological studies suggest that nyaope, a heroin-based drug, is widely used in South Africa. Yet few reliable research tools are available to assess treatment outcomes of users. The Opiate Treatment Index (OTI), a tool developed in Australia, could potentially facilitate research on context-specific South African treatment outcomes. However, we know little of its test-retest reliability. Aim This study aimed to assess the test-retest reliability of the OTI among a sample of nyaope users in Johannesburg. Setting This study was conducted across three substance use treatment facilities in Johannesburg. Methods The OTI was administered to 53 nyaope users at baseline and one week later. To determine the test-retest reliability of the OTI, the intra-class correlation coefficients (ICC) and the Brennan–Prediger coefficients of the two interviews were calculated. Results The ICC of the Q-scores from the data sets along with the Brennan–Prediger coefficient for the substance use domain were calculated. The ICC for nyaope was 0.38. Brennan–Prediger coefficients were as follows: alcohol – 0.96, crack-cocaine – 0.89, cannabis – 0.92, methaqualone – 0.85 and crystal methamphetamine – 0.89. Conclusion A significant positive finding was the excellent test-retest reliability of the injecting and sexual behaviour domains and moderate reliability of the criminality, general health and social functioning domains. Contribution The results of this study provide insight into the reliability of this tool and for its use in future studies in the South African context.
Determination of iron and zinc content in food barley

The main objective of this study was to identify sources of high iron and zinc content in landraces and hulless barley grain to be used in developing new barley germplasm with improved value for human nutrition. A collection of 333 landraces from 34 countries was grown for three consecutive years at ICARDA’s research station located near Tel Hadya, in Syria. In the third year, the collection was also planted at a second ICARDA research station, near Breda. The samples were analyzed at Waite Analytical Services, University of Adelaide, Australia. A spatial analysis was carried out using GENSTAT. The heritability of iron content in the grain was 0.589 in Breda and 0.562 in Tel Hadya; the heritability of zinc content was 0.639 and 0.605 in Breda and Tel Hadya, respectively. Six landraces were identified with consistently higher iron across environments, ranging from 38.8 to 51.6 ppm. Three of these entries also have high zinc content, ranging from 37.3 to 42.5 ppm. Moroccan landraces are a very promising source of high iron and zinc content in the grain. Ethiopian, Russian and Ecuadorian landraces also have a few promising sources. During 2007, ICARDA’s micronutrient laboratory applied a dry-ashing method for the determination of iron and zinc content in hulless barley. A total of 1087 breeding lines were grown at Breda in 2005 and analyzed for iron and zinc. The iron content ranged from 22.6 to 36.7 ppm while zinc content ranged from 19.98 to 49.72 ppm. The variety Atahualpa confirmed its high iron and zinc content: it ranked first for iron and second for zinc (43.9 ppm). Both iron and zinc content were highly and positively correlated with protein content (0.56 and 0.74, respectively). The correlation coefficient between iron and zinc content was 0.64. Sample preparation for barley grain analysis is discussed for reducing contamination.
The legal landscape of cybercrime: A review of contemporary issues in the criminal justice system

This paper provides a glimpse into the complex and evolving legal terrain surrounding cybercrime and its profound impact on the criminal justice system. In the digital era, the perpetration of cybercrimes poses unprecedented challenges, necessitating a comprehensive understanding of the contemporary legal issues that law enforcement, policymakers, and the judiciary confront. The paper delves into the multifaceted aspects of cybercrime, examining challenges such as jurisdictional complexities, technological advancements outpacing legal frameworks, and the global nature of cyber threats. The analysis encompasses an exploration of the difficulties in attribution, investigation, and prosecution of cybercriminals operating across borders, emphasizing the need for enhanced international collaboration and harmonization of legal standards. Moreover, the paper sheds light on the intricacies of defining and categorizing cybercrimes, considering the dynamic nature of cyber threats that continually adapt to exploit vulnerabilities in the digital landscape. It underscores the urgency for legal frameworks to keep pace with emerging technologies, ensuring that the criminal justice system remains agile and effective in combating cyber threats. Additionally, the paper addresses the critical issue of protecting individual privacy and civil liberties in the context of cybercrime investigations, striking a delicate balance between law enforcement's need for digital evidence and preserving the rights of individuals. The paper provides a concise overview of the contemporary challenges within the legal landscape of cybercrime, urging stakeholders to adapt and innovate in the face of evolving threats. The review emphasizes the imperative of a cohesive, international legal framework to effectively combat cybercrime and uphold justice in the digital age.
The Potential Role of Genic-SSRs in Driving Ecological Adaptation Diversity in Caragana Plants

Caragana, a xerophytic shrub genus widely distributed in northern China, exhibits distinctive geographical substitution patterns and ecological adaptation diversity. This study employed transcriptome sequencing technology to investigate 12 Caragana species, aiming to explore genic-SSR variations in the Caragana transcriptome and identify their role as a driving force for environmental adaptation within the genus. A total of 3666 polymorphic genic-SSRs were identified across different species. The impact of these variations on the expression of related genes was analyzed, revealing a significant linear correlation (p < 0.05) between the length variation of 264 polymorphic genic-SSRs and the expression of associated genes. Additionally, 2424 polymorphic genic-SSRs were located in differentially expressed genes among Caragana species. Through weighted gene co-expression network analysis, the expressions of these genes were correlated with 19 climatic factors and 16 plant functional traits in various habitats. This approach facilitated the identification of biological processes associated with habitat adaptations in the studied Caragana species. Fifty-five core genes related to functional traits and climatic factors were identified, including various transcription factors such as MYB, TCP, ARF, and structural proteins like HSP90, elongation factor TS, and HECT. The roles of these genes in the ecological adaptation diversity of Caragana were discussed. Our study identified specific genomic components and genes in Caragana plants responsive to heterogeneous habitats. The results contribute to advancements in the molecular understanding of their ecological adaptation, lay a foundation for the conservation and development of Caragana germplasm resources, and provide a scientific basis for plant adaptation to global climate change.
DCTN: Dual-Branch Convolutional Transformer Network With Efficient Interactive Self-Attention for Hyperspectral Image Classification

Hyperspectral image (HSI) classification is an essential task in remote sensing with substantial practical significance. However, most existing convolutional neural network (CNN)-based classification methods focus only on local spatial features while neglecting global spectral dependencies. Meanwhile, Transformer-based methods exhibit robust capabilities for global spectral feature modeling but struggle to extract local spatial features effectively. To fully exploit the local spatial feature extraction capabilities of CNN-based networks and the global spectral feature extraction capabilities of Transformer-based networks, this article proposes a dual-branch convolutional Transformer method with efficient interactive self-attention (EISA) for HSI classification, namely the dual-branch convolutional transformer network (DCTN), which can aggregate local and global spatial-spectral features fully. Specifically, DCTN includes two core modules: the spatial-spectral fusion projection module (SFPM) and the EISA module. The former utilizes 3-D convolution with adaptive pooling and 2-D group convolution with residual connection to parallel extract fused and grouped spatial-spectral features, respectively. The latter performs EISA across height, width, and spectral dimensions, enabling deep fusion of spatial-spectral features. Extensive experiments on three real HSI datasets demonstrate that the proposed DCTN method outperforms existing classification methods, yielding state-of-the-art classification performance. The code is available at https://github.com/AllFever/DeepHyperX-DCTN for reproducibility.
Ad Hoc Mesh Network Localization Using Ultra-Wideband for Mobile Robotics

This article explores the implementation of high-accuracy GPS-denied ad hoc localization. Little research exists on ad hoc ultra-wideband-enabled localization systems with mobile and stationary nodes. This work aims to demonstrate the localization of bicycle-modeled robots in a non-static environment through a mesh network of mobile, stationary robots, and ultra-wideband sensors. The non-static environment adds a layer of complexity when actors can enter and exit the node’s field of view. The method starts with an initial localization step where each unmanned ground vehicle (UGV) uses the surrounding, available anchors to derive an initial local or, if possible, global position estimate. The initial localization uses a simplified implementation of the iterative multi-iteration ad hoc localization system (AHLos). This estimate was refined using an unscented Kalman filter (UKF) following a constant turn rate and velocity magnitude model (CTRV). The UKF then fuses the robot’s odometry and the range measurements from the Decawave ultra-wideband receivers stationed on the network nodes. Through this position estimation stage, the robot broadcasts its estimated position to its neighbors to help the others further improve their localization estimates and localize themselves. This wave-like cycle of nodes helping to localize each other allows the network to act as a mobile ad hoc localization network.