Miracle-dz/UniFAR-FTUs huggingface dataset:
AoI Minimization in RIS-Aided SWIPT Systems

This paper studies the age of information (AoI) minimization design in a reconfigurable intelligent surface (RIS)-aided simultaneous wireless information and power transfer (SWIPT) system. The non-orthogonal multiple access (NOMA) scheme is adopted in the uplink (UL) phase. We formulate an AoI minimization problem to optimize the transmit/receive beamformers, phase shift vector, information-user (IU) selection, UL/downlink (DL) time allocation and decoding order subject to the power budget constraint of the base station, the unit-modulus constraints of the reflecting elements and the energy harvesting (EH) constraints of the energy users. The considered problem is decomposed into three subproblems, and then solved by a proposed alternating optimization-based algorithm. The computational complexity of the proposed algorithm is analyzed. Simulation results demonstrate the impacts on AoI by adopting RIS and NOMA as well as the system parameters. Besides, the trade-off between information freshness and the EH is revealed through the impact of EH requirement on the IU selection and UL/DL time allocation.
Etude experimentale des proprietes electriques et dielectriques des materiaux argileux consolides

L'objectif de cette these est de contribuer a une meilleure comprehension des phenomenes de conduction electrique et de polarisation dielectrique dans les materiaux argileux, et devrait aider par la suite a exploiter la mesure de ces parametres sur le terrain pour suivre la fracturation, la saturation ou l'infiltration de polluants (sites de stockage de dechets en particulier). Nous avons realise des mesures en laboratoire sur des echantillons synthetiques d'argile compactee (kaolinite et smectique), a differentes teneurs en eau, porosites et compositions mineralogiques, sur une tres large gamme de frequences (avec trois dispositifs differents). Puis des argilites naturelles (Andra) ont ete etudiees. La reponse des argiles compactees est principalement controlee par leur teneur en eau sur toute la gamme de frequences ; nous avons egalement observe deux polarisations distinctes, attribuees a un phenomene de Maxwell-Wagner et a une polarisation de la double couche electrique autour des particules d'argile. La reponse des argilites naturelles est plus complexe ; elle est controlee par la teneur en eau ainsi que la microstructure de la roche. Dans ces roches, les anisotropies electriques et dielectriques sont fortes ; elles ont egalement ete mises en evidence pour les echantillons synthetiques Les modeles theoriques existants predisent bien la reponse a haute frequence des materiaux etudies, mais la reponse a basse frequence (<1 MHz) doit etre mieux comprise.
Inégalités régionales et développement économique: le cas français (1850-2000)

Since the seminal work of WILLIAMSON (1965), suggesting that inter-regional income disparities successively increase and decrease during the development process, several empirical studies have shown that the concentration level in the central region tends to raise during the economic take-off and the industrialisation stage, and later decreases after reaching a per capita income of about $ 5000 (of 1985). We propose an original analysis of the French case, showing how regional disparities have accompanied economic development since the mid XIXth century. The concentration stage seems to have developed markedly until the 1950's (when France reached a per capita income of $ 5000), but this scheme can't be reduced to a simple center/periphery pattern. Its most striking feature is a double inter-regional inequality movement: indeed, there is an asymmetric evolution between the Paris region and the provinces on the one hand, and between the East and the West of France on the other. The reduction of regional inequalities that occured in the latter part of the XXth century seems to be much complex than some empirical studies have suggested.
Altered gut microbiota and metabolites in untreated myasthenia gravis patients

Objective The homeostasis of the immune system is influenced by the gut microbiota. Previous studies have reported dysbiosis in the gut microbiota of myasthenia gravis (MG) patients. To investigate potential alterations in gut microbiota and metabolites in newly diagnosed and untreated MG patients, we conducted a case-control study. Methods Fecal samples were collected from 11 newly diagnosed and untreated MG patients as well as 11 age-and sex-matched healthy controls. These samples underwent analysis for gut microbiota using 16S ribosomal RNA (rRNA) gene sequencing, while fecal metabolome was analyzed using liquid chromatography-electrospray tandem mass spectrometry system (LC-ESI-MS/MS). Results The microbial community richness (observed species) and diversity (Shannon and Simpson indices) were significantly lower in the MG group compared to the control group. Microbiota composition analysis revealed significant differences between the MG and control groups at phylum, family, and genus levels. Linear discriminant analysis effect size (LEfSe) analysis showed a substantial decrease in abundance of the genus Faecalibacterium within the MG group. Fecal metabolome analysis identified three up-regulated metabolites involved in amino acid metabolism (taurine, creatinine, L-carnitine), one up-regulated metabolite involved in lipid metabolism (oleic acid), with correlation analysis indicating a positive association between Faecalibacterium abundance and creatinine levels. Conclusion Our findings suggest that dysbiosis already exists in newly diagnosed and untreated MG patients, implying that dysbiosis within the gut microbiota may be an initiating factor contributing to MG pathogenesis. Furthermore, F. prausnitzii may hold promise as a probiotic for treating MG.
The independent domination numbers of strong product of two cycles

Abstract Let γi(Cm ⎕ Cn) denote the independent domination number of the strong product of the graphs Cm, the cycle of length m, m ≥ 3 and the graph Cn, the cycle of length n, n ≥ 3. In this paper, we determine the exact values of the independent domination numbers of Cm ⎕ Cn with m ≤ n when 3 ≤ m ≤ 8 and n arbitrary large.
Vasculitis Activity-Predicting Ability of IL-12 Family Cytokines in Patients with Microscopic Polyangiitis and Granulomatosis with Polyangiitis

Purpose The present study investigated and compared the antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) activity-predicting ability of the serum concentrations of the four interleukin (IL)-12 family cytokines including IL-23, IL-27, IL-35, and IL-39 in patients with microscopic polyangiitis (MPA) and granulomatosis with polyangiitis (GPA). Materials and Methods The present study included 70 patients with MPA and GPA. Clinical and laboratory data, particularly Birmingham Vasculitis Activity Score (BVAS), at the time of blood collection were obtained. The serum concentrations of IL-23, IL-27, IL-35, and IL-37 were measured using sera stored at -80℃. Patients were divided into two groups: the upper half of BVAS (BVAS ≥12) and the lower half of BVAS (BVAS <12). Results The serum concentrations of IL-23 and IL-27 reflected AAV activity. Patients with the upper half of BVAS exhibited significantly higher serum concentrations of IL-23 and IL-27 than those without. Patients with the serum concentrations of IL-23 ≥132.1 pg/mL or IL-27 ≥684.7 pg/mL exhibited higher frequency and risk for the upper half of BVAS than those without [relative risks (RR) 5.143 and RR 4.091, respectively]. The serum concentrations of IL-27 were associated with age ≥65 years and proteinase 3-ANCA (or C-ANCA) negativity, whereas, those of IL-23 were associated with MPA. However, the serum concentrations of IL-35 and IL-39 were not useful in predicting AAV activity in this study. Conclusion The present study is the first to demonstrate that among the various members of IL-12 family cytokines, the serum concentrations of IL-23 and IL-27 possess AAV activity-predicting ability.
Minor changes of water conservation capacity in 50 years of forest growth : analysis with data from the Ananomiya Experimental Forest, Japan

Forest planting and growth over 50 years have not produced significant water conservation in an experimental watershed in Japan. Comparisons of hydrological responses between two periods (1930-1937, and 1983-1990) showed that the afforested watershed had increased annual evapotranspiration by 12% and water storage of soil by 15%, and reduced flood flows by about 20%. However, annual runoff from the watershed was reduced by 8.5% and low flows became even smaller, which was unfavourable for both water conservation and water supply. The minor increase in soil storage capacity produced a very limited water conservation effect and so flood reduction. In contrast, the increased evaporative consumption made annual runoff and low flows smaller.
Enhancing Cross-Subject Motor Imagery Classification in EEG-Based Brain–Computer Interfaces by Using Multi-Branch CNN

A brain–computer interface (BCI) is a computer-based system that allows for communication between the brain and the outer world, enabling users to interact with computers using neural activity. This brain signal is obtained from electroencephalogram (EEG) signals. A significant obstacle to the development of BCIs based on EEG is the classification of subject-independent motor imagery data since EEG data are very individualized. Deep learning techniques such as the convolutional neural network (CNN) have illustrated their influence on feature extraction to increase classification accuracy. In this paper, we present a multi-branch (five branches) 2D convolutional neural network that employs several hyperparameters for every branch. The proposed model achieved promising results for cross-subject classification and outperformed EEGNet, ShallowConvNet, DeepConvNet, MMCNN, and EEGNet_Fusion on three public datasets. Our proposed model, EEGNet Fusion V2, achieves 89.6% and 87.8% accuracy for the actual and imagined motor activity of the eegmmidb dataset and scores of 74.3% and 84.1% for the BCI IV-2a and IV-2b datasets, respectively. However, the proposed model has a bit higher computational cost, i.e., it takes around 3.5 times more computational time per sample than EEGNet_Fusion.
FairBayRank: A Fair Personalized Bayesian Ranker

Recommender systems are data-driven models that successfully provide users with personalized rankings of items (movies, books.). Meanwhile, for user minority groups, those systems can be unfair in predicting users’ expectations due to biased data. Consequently, fairness remains an open challenge in the ranking prediction task. To address this issue, we propose in this paper FairBayRank, a fair Bayesian personalized ranking algorithm that deals with both fairness and ranking performance requirements. FairBayRank evaluation on real-world datasets shows that it efficiently alleviates unfairness issues while ensuring high prediction performances.
Results of hydrologic research at a low-level radioactive-waste disposal site near Sheffield, Illinois

The purpose of the report is to present results and implications of approximately 10 years of hydrologic research conducted by the U.S. Geological Survey at a commercial low-level radioactive-waste disposal site. Hydrologic research at the site, located near Sheffield, Illinois, has included studies of microclimate, evapotranspiration, and tritium release by plants; runoff and land modification; water movement through a trench cover; water and tritium movement in the unsaturated zone; gases in the unsaturated zone; water and tritium movement in the saturated zone; and water chemistry.
MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods

Recent research in decoding methods for Natural Language Generation (NLG) tasks has shown that MAP decoding is not optimal, because model probabilities do not always align with human preferences. Stronger decoding methods, including Quality Estimation (QE) reranking and Minimum Bayes' Risk (MBR) decoding, have since been proposed to mitigate the model-perplexity-vs-quality mismatch. While these decoding methods achieve state-of-the-art performance, they are prohibitively expensive to compute. In this work, we propose MBR finetuning and QE finetuning which distill the quality gains from these decoding methods at training time, while using an efficient decoding algorithm at inference time. Using the canonical NLG task of Neural Machine Translation (NMT), we show that even with self-training, these finetuning methods significantly outperform the base model. Moreover, when using an external LLM as a teacher model, these finetuning methods outperform finetuning on human-generated references. These findings suggest new ways to leverage monolingual data to achieve improvements in model quality that are on par with, or even exceed, improvements from human-curated data, while maintaining maximum efficiency during decoding.
Treatment of the acute phase of stroke based on the theory of Ying and Wei and internal and external wind

: Stroke disease is characterized by high morbidity, mortality, disability, and recurrence, which seriously endangers human life and health. At present, clinical western medicine has certain effect on the treatment of ischemic stroke, but the treatment of its acute phase still has deficiencies such as strict time window limitation or leading to the risk of bleeding. In the author's opinion, loss of harmony between Ying and Wei is one of the basic pathogenic mechanisms in the acute phase of stroke, and harmonization of Ying and Wei is one of the important treatment rules for the acute phase of stroke. In this article, the author will expand the exploration on the basis of the existing pathological mechanisms and evidence types to provide new ideas for the treatment of acute phase of stroke in Chinese medicine.
The Validation and Psychometric Properties of the Gaming Instinctual Motivation Scale

Being able to quantify gaming motivation in a valid, systematic way has important implications for game designers and gaming user experience researchers. In the present study, we aimed to develop and validate a 30-item Gaming Instinctual Motivation Scale (GIMS) based on Dillon’s 6–11 Framework on instinctual gaming motivation and Lazzaro’s gaming experience model. To validate the scale, we recruited 194 regular gamers (Mage = 22.70 years old, SD = 4.38) to complete the GIMS based on their general gaming experience and their experience playing role-laying games (RPGs), first-person shooters (FPSs), real-time strategy, puzzle, and action games. We used a cross-validation approach and performed exploratory factor analysis and confirmatory factor analysis to test the structure of the scale and the reliability and validity of the scale, respectively. The final version of the GIMS had a one-dimensional structure with 15 items. It also had good construct validity, χ2 (N = 117, df = 86) = 126.28, p = 0.003, CFI = 0.93, TLI = 0.92, and RMSEA = 0.064 (90% CI [0.04, 0.09]), and reliability (CR = 0.89), and an acceptable convergent validity (AVE = 0.35). The one-dimensional structure was generalizable to RPG and FPS games, demonstrating the applicability of the scale to these two gaming genres. Higher scores on the GIMS were also associated with a greater intention to play games.
Population effectiveness of endoscopy screening for mortality reduction in gastric cancer

Abstract Objectives No randomized controlled trials have compared endoscopic screening with no screening for gastric cancer on an intention‐to‐screen basis, and the population‐based evidence is insufficient. This study aimed to identify factors contributing to the population effectiveness of cancer screening, estimate the number needed to screen (NNS) to reduce one gastric cancer‐related death, and evaluate the expected mortality‐rate reduction in endoscopic screening for gastric cancer in 184 countries. Methods Factors contributing to the attributable risk, NNS, and mortality‐rate reduction were identified. A rapid review was performed in PubMed to estimate the pooled relative risk of endoscopic screening compared to that of no screening for mortality reduction. NNSs and mortality‐rate reduction were estimated using the pooled relative risk and GLOBOCAN data. Results The crude mortality rate, the effectiveness of the screening modality, and the screened rate contributed to the attributable risk, NNS, and mortality‐rate reduction in cancer screening. The pooled relative risk was 0.58 in endoscopy screening compared to that in no screening. NNSs and expected mortality‐rate reduction differed across countries and ranged from 2522 to 91,575 and 0.2 to 7.9 (per 100,000 individuals) for the screened rate of 20%, respectively. Conclusions In addition to the effectiveness of the used modality, the disease burden and screened rate were important in the population effectiveness of cancer screening. Regarding the high NNSs and the low expected mortality‐rate reduction, population‐based endoscopic screening seems not to be effective in many countries, and these results are meaningful in decision‐making regarding the introduction of endoscopic screening.
Advances in oligosaccharides production from brown seaweeds: extraction, characterization, antimetabolic syndrome, and other potential applications

ABSTRACT Brown seaweeds are a promising source of bioactive substances, particularly oligosaccharides. This group has recently gained considerable attention due to its diverse cell wall composition, structure, and wide-spectrum bioactivities. This review article provides a comprehensive update on advances in oligosaccharides (OSs) production from brown seaweeds and their potential health applications. It focuses on advances in feedstock pretreatment, extraction, characterization, and purification prior to OS use for potential health applications. Brown seaweed oligosaccharides (BSOSs) are extracted using various methods. Among these, enzymatic hydrolysis is the most preferred, with high specificity, mild reaction conditions, and low energy consumption. However, the enzyme selection and hydrolysis conditions need to be optimized for desirable yield and oligosaccharides composition. Characterization of oligosaccharides is essential to determine their structure and properties related to bioactivities and to predict their most suitable application. This is well covered in this review. Analytical techniques such as high-performance liquid chromatography (HPLC), gas chromatography (GC), and nuclear magnetic resonance (NMR) spectroscopy are commonly applied to analyze oligosaccharides. BSOSs exhibit a range of biological properties, mainly antimicrobial, anti-inflammatory, and prebiotic properties among others. Importantly, BSOSs have been linked to possible health advantages, including metabolic syndrome management. Metabolic syndrome is a cluster of conditions, such as obesity, hypertension, and dyslipidemia, which increase the risk of cardiovascular disease and type 2 diabetes. Furthermore, oligosaccharides have potential applications in the food and pharmaceutical industries. Future research should focus on improving industrial-scale oligosaccharide extraction and purification, as well as researching their potential utility in the treatment of various health disorders. Highlights Brown algae exhibit a great diversity to offer a wide range of OSs bioactivities. Non-enzymatic extraction yields 30-58% OSs more than enzymatic routes. Enzymatically derived OSs exhibit better bioactivity than non-enzymatic OSs. Nanofiltration/activated carbon can solve bottlenecks in large-scale purification. OSs health applications are proven at in vitro stage, clinical studies yet to be done.
Dynamic Hand Gesture-Featured Human Motor Adaptation in Tool Delivery using Voice Recognition

Human-robot collaboration has benefited users with higher efficiency towards interactive tasks. Nevertheless, most collaborative schemes rely on complicated human-machine interfaces, which might lack the requisite intuitiveness compared with natural limb control. We also expect to understand human intent with low training data requirements. In response to these challenges, this paper introduces an innovative human-robot collaborative framework that seamlessly integrates hand gesture and dynamic movement recognition, voice recognition, and a switchable control adaptation strategy. These modules provide a user-friendly approach that enables the robot to deliver the tools as per user need, especially when the user is working with both hands. Therefore, users can focus on their task execution without additional training in the use of human-machine interfaces, while the robot interprets their intuitive gestures. The proposed multimodal interaction framework is executed in the UR5e robot platform equipped with a RealSense D435i camera, and the effectiveness is assessed through a soldering circuit board task. The experiment results have demonstrated superior performance in hand gesture recognition, where the static hand gesture recognition module achieves an accuracy of 94.3\%, while the dynamic motion recognition module reaches 97.6\% accuracy. Compared with human solo manipulation, the proposed approach facilitates higher efficiency tool delivery, without significantly distracting from human intents.
Gabor's “complex signal” revisited: Complexifying frames and bases

In 1946, Dennis Gabor introduced the analytic signal f+iHf$f+iHf$ for real‐valued signals f. Here, H is the Hilbert transform. This complexification of functions allows for an analysis of their amplitude and phase information and has ever since given well‐interpretable insight into the properties of the signals over time. The idea of complexification has been reconsidered with regard to many aspects: examples are the dual tree complex wavelet transform, or via the Riesz transform and the monogenic signal, that is, a multi‐dimensional version of the Hilbert transform, which in combination with multi‐resolution approaches leads to Riesz wavelets, and others. In this context, we ask two questions:
Direct – Maternal Genetic Parameters Estimated for Real-Time Ultrasound Scan Measures of Eye Muscle Area, Rib Fat Depth, and their Correlation with Body Weight in Male Philippine Riverine Buffaloes

Background: Ultrasound scanning is a non-invasive technique for evaluating animals based on carcass yield and meat quality traits. It has been incorporated into the beef cattle breeding program. However, little has been done in buffaloes. Thus, this study was conducted to estimate the genetic parameters for growth traits- body weights (BW) and a real-time ultrasound scan of eye muscle area (EMA) and rib fat (RF) to determine their suitability as a tool for selection. Methods: Four hundred thirty-eight (438) male Philippine riverine buffaloes with 1,535 BW records and 417 real-time ultrasound scans of EMA and RF scans at the 12th rib were available for the study. BW was taken and adjusted at birth, 6, 12, 18, 24, 30, and 36 months while RF and EMA scans were taken at 12 & 18 mos. Genetic parameters were estimated with a pedigree-based multi-trait animal model using ASREML software. Results: The average BW of buffaloes adjusted to 6, 12, 18, 24, 30, and 36 months of age were 135kg, 230.8kg, 323.0kg, 382.7, 453.6, and 502.4kg, respectively. The mean EMA and RF at 12 months were 29.7 cm2 and 3.2mm, respectively. Direct genetic heritabilities were 0.26±0.16, 0.29±0.12, 0.35±0.19 and 0.67±0.32 for birth, BW12mos, EMA12mos and RF12mos, respectively. Maternal genetic heritability for birth weight. was 0.12±0.09. Genetic correlations among traits were positive except between birth and RF. Conclusions: Results indicate that ultrasound scanning can be used for selection together with BW at 12mos. and suggest that early performance is an excellent predictor of performance at a later age.