Miracle-dz/UniFAR-FTUs huggingface dataset:
Monitoring Variables Influence on Random Forest Models to Forecast Injuries in Short-Track Speed Skating

Injuries limit the athletes' ability to participate fully in their training and competitive process. They are detrimental to performance, affecting the athletes psychologically while limiting physiological adaptations and long-term development. This study aims to present a framework for developing random forest classifier models, forecasting injuries in the upcoming 1 to 7 days, to assist the performance support staff in reducing injuries and maximizing performance within the Canadian National Female Short-Track Speed Skating Program. Forty different variables monitored daily over two seasons (2018–2019 and 2019–2020) were used to develop two sets of forecasting models. One includes only training load variables (TL), and a second (ALL) combines a wide array of monitored variables (neuromuscular function, heart rate variability, training load, psychological wellbeing, past injury type, and location). The sensitivity (ALL: 0.35 ± 0.19, TL: 0.23 ± 0.03), specificity (ALL: 0.81 ± 0.05, TL: 0.74 ± 0.03) and Matthews Correlation Coefficients (MCC) (ALL: 0.13 ± 0.05, TL: −0.02 ± 0.02) were computed. Paired T-test on the MCC revealed statistically significant (p < 0.01) and large positive effects (Cohen d > 1) for the ALL forecasting models' MCC over every forecasting window (1 to 7 days). These models were highly determined by the athletes' training completion, lower limb and trunk/lumbar injury history, as well as sFatigue, a training load marker. The TL forecasting models' MCC suggests they do not bring any added value to forecast injuries. Combining a wide array of monitored variables and quantifying the injury etiology conceptual components significantly improve the injury forecasting performance of random forest models. The ALL forecasting models' performances are promising, especially on one time windows of one or two days, with sensitivities and specificities being respectively above 0.5 and 0.7. They could add value to the decision-making process for the support staff in order to assist the Canadian National Female Team Short-Track Speed Skating program in reducing the number of incomplete training days, which could potentially increase performance. On longer forecasting time windows, ALL forecasting models' sensitivity and MCC decrease gradually. Further work is needed to determine if such models could be useful for forecasting injuries over three days or longer.
A Flower-Shaped Miniaturized UWB-MIMO Antenna with High Isolation

An ultra-wideband (UWB) multiple-input, multiple-output (MIMO) antenna with a reasonably compact size of 30 × 18 × 1.6 mm3 is presented in this paper. The proposed antenna contains two radiating components, each of which is made up of three elliptically shaped patches situated 60 degrees apart, and resembles the shape of a flower. Moreover, the proposed antenna design incorporates a T-like ground branch that functions as a decoupling structure, and is composed of two modified inverted-L branches and an I-shaped stub, offering an isolation of more than 20 dB over the whole operation band (4.3–15.63 GHz). Furthermore, the proposed antenna system was fabricated and tested, and the envelope correlation coefficient (ECC), diversity gain (DG), and total active reflection coefficient (TARC), as well as the radiation characteristics and MIMO performance, were analyzed. The proposed UWB-MIMO antenna may be a suitable candidate for diverse UWB applications, based on the simulated and measured results of this study.
Membership Inference Attacks on Aggregated Time Series with Linear Programming

: Aggregating data is a widely used technique to protect privacy. Membership inference attacks on aggregated data aim to infer whether a specific target belongs to a given aggregate. We propose to study how aggregated time series data can be susceptible to simple membership inference privacy attacks in the presence of adversarial background knowledge. We design a linear programming attack that strongly benefits from the number of data points published in the series and show on multiple public datasets how vulnerable the published data can be if the size of the aggregated data is not carefully balanced with the published time series length. We perform an extensive experimental evaluation of the attack on multiple publicly available datasets. We show the vulnerability of aggregates made of thousands of time series when the aggregate length is not carefully balanced with the published length of the time series.
Impact of coal mining on land use changes, deforestation, biomass, and C losses in Central India: Implications for offsetting CO2 emissions

Despite the continuous growth in renewable sources of energy, coal remains the primary source of energy security in developing countries and accounted for 1.1 Gt of CO2 annually. The present study was conducted to examine the dynamic land cover changes, deforestation, and carbon (C) emissions in the mined landscape of Central India. Geospatial techniques coupled with field measurements were conjunctively employed for quantifying land use and vegetation changes from the period of 2001 to 2020. The unchecked mining (6.4–30 km2) along with the rapid expansion of agriculture (586.7–642.5 km2) were identified as major drivers of deforestation, which resulted in the net loss of 115.3 km2 area under intact sal (Shorea robusta) dominated forest. The mining and associated activities increased the fragmentation of intact forest that had not only decreased density, basal area, and diversity of vegetation but also a huge loss of biomass of ~2.5 Tg that contributed to a net loss of 1.08 Tg C (~3.98 Tg of CO2) in the past 20 years. The study explored the use of land management options and confirmed that C offset ensued from land use changes without hampering coal production for the next two decades. The scenarios will provide valuable information to the policymakers for devising sustainable coal mining by underpinning the ecological compensation for deforestation while promoting cleaner production technologies through decarbonization to counteract emissions, which could help in achieving ambitious goals set by India for planned C reduction targets as Intended Nationally Determined Commitments under the Paris Agreement (2015).
Acute Neuromuscular and Hormonal Responses to Power, Strength, and Hypertrophic Protocols and Training Background

This study investigated how two slightly different athlete groups would differ in acute neuromuscular and endocrine responses to specific resistance exercise loadings and recovery compared to untrained participants. Power athletes (PA, n = 8), strength athletes (SA, n = 8) and non-athletes (NA, n = 7) performed power (PL, 7 × 6 × 50% of 1RM), maximal strength (MSL, 7 × 3 × 3RM), and hypertrophic (HL, 5 × 10 × 10RM) loadings in Smith-machine back-squat. Neuromuscular performance, serum testosterone, growth hormone, and cortisol concentrations, and blood lactate (BL) were measured before (Pre), at Mid and after (Post) loading, and after recovery for 24 and 48 h. All loadings led to acute decreases in neuromuscular performance and elevations in hormone concentrations and BL. During PL, a significant group × time interactions occurred in maximal isometric force [F(4, 40) = 4.189, p = 0.006, ηp2 = 0.295] indicating a greater decrease in PA compared to SA from Pre to Mid (p < 0.05), and in countermovement jump height [F(4, 40) = 2.895, p = 0.034, ηp2 = 0.224] indicating a greater decrease in NA compared to SA from Pre to Mid (p < 0.05). During HL, growth hormone was higher in Mid and Post in SA compared to NA (p < 0.05). No significant interactions were found during recovery. The differences during PL and HL suggest that the training background may enhance acute responses during the present loadings, whereas it seemed to have a limited effect on the recovery.
Ultrasonic Vocalizations in Adult C57BL/6J Mice: The Role of Sex Differences and Repeated Testing

Ultrasonic vocalizations (USVs) are a major tool for assessing social communication in laboratory mice during their entire lifespan. At adulthood, male mice preferentially emit USVs toward a female conspecific, while females mostly produce ultrasonic calls when facing an adult intruder of the same sex. Recent studies have developed several sophisticated tools to analyze adult mouse USVs, especially in males, because of the increasing relevance of adult communication for behavioral phenotyping of mouse models of autism spectrum disorder (ASD). Little attention has been instead devoted to adult female USVs and impact of sex differences on the quantitative and qualitative characteristics of mouse USVs. Most of the studies have also focused on a single testing session, often without concomitant assessment of other social behaviors (e.g., sniffing), so little is still known about the link between USVs and other aspects of social interaction and their stability/variations across multiple encounters. Here, we evaluated the USVs emitted by adult male and female mice during 3 repeated encounters with an unfamiliar female, with equal or different pre-testing isolation periods between sexes. We demonstrated clear sex differences in several USVs' characteristics and other social behaviors, and these were mostly stable across the encounters and independent of pre-testing isolation. The estrous cycle of the tested females exerted quantitative effects on their vocal and non-vocal behaviors, although it did not affect the qualitative composition of ultrasonic calls. Our findings obtained in B6 mice, i.e., the strain most widely used for engineering of transgenic mouse lines, contribute to provide new guidelines for assessing ultrasonic communication in male and female adult mice.
An overview of the main circRNA databases

: Circular RNAs (circRNAs) are a family of non-coding RNAs, whose head 3’ and tail 5’ ends covalently bond together to lead to a circular form. To date, thousands of circRNAs in human, mouse, rat, as well as other animals have been reported by computational analysis of sequencing data, and the numbers are likely to grow. Recently, great efforts have been paid in the circRNA study. Thus, building a comprehensive circRNA database becomes more and more imperative. So far, several databases of circRNA have been provided such as circBase, circRNADb, circ2traits, deepBase, circInteractome and circNet. In this review, we listed the frequently-used databases for circRNA research and described their features, respectively.
A Bio-Inspired Endogenous Attention-Based Architecture for a Social Robot

A robust perception system is crucial for natural human–robot interaction. An essential capability of these systems is to provide a rich representation of the robot’s environment, typically using multiple sensory sources. Moreover, this information allows the robot to react to both external stimuli and user responses. The novel contribution of this paper is the development of a perception architecture, which was based on the bio-inspired concept of endogenous attention being integrated into a real social robot. In this paper, the architecture is defined at a theoretical level to provide insights into the underlying bio-inspired mechanisms and at a practical level to integrate and test the architecture within the complete architecture of a robot. We also defined mechanisms to establish the most salient stimulus for the detection or task in question. Furthermore, the attention-based architecture uses information from the robot’s decision-making system to produce user responses and robot decisions. Finally, this paper also presents the preliminary test results from the integration of this architecture into a real social robot.
Geospatial Artificial Intelligence (GeoAI) in the Integrated Hydrological and Fluvial Systems Modeling: Review of Current Applications and Trends

This paper reviews the current GeoAI and machine learning applications in hydrological and hydraulic modeling, hydrological optimization problems, water quality modeling, and fluvial geomorphic and morphodynamic mapping. GeoAI effectively harnesses the vast amount of spatial and non-spatial data collected with the new automatic technologies. The fast development of GeoAI provides multiple methods and techniques, although it also makes comparisons between different methods challenging. Overall, selecting a particular GeoAI method depends on the application’s objective, data availability, and user expertise. GeoAI has shown advantages in non-linear modeling, computational efficiency, integration of multiple data sources, high accurate prediction capability, and the unraveling of new hydrological patterns and processes. A major drawback in most GeoAI models is the adequate model setting and low physical interpretability, explainability, and model generalization. The most recent research on hydrological GeoAI has focused on integrating the physical-based models’ principles with the GeoAI methods and on the progress towards autonomous prediction and forecasting systems.
Bias and representativeness in digitized newspaper collections: Introducing the environmental scan

This article introduces the ‘Environmental Scan’ as answer to the question of hidden biases in digital heritage collections. Its substantive focus is digitized nineteenth-century British provincial newspapers, and in particular the JISC corpus, a popular, publicly-funded resource for scholars. While multiple papers have meticulously investigated the genesis of such newspaper collections, in the process highlighting the often unacknowledged politics of collection, preservation and dissemination via microfilm and now digitization, our aim is to explore questions of representativeness and bias in new ways by enriching computational analysis of digital corpora with the historical insights that can be derived from a contemporaneous reference source: namely, the Victorian newspaper press directories.
Pendekatan Text Analysis Terhadap Ulasan Pengunjung Hotel: Apa yang Mempengaruhi Kepuasan Pelanggan?

Abstrak. Pengguna internet telah memenuhi dunia digital dengan konten buatan pengguna (UGC) seperti teks, gambar, atau video. Konten tersebut mewakili pendapat, preferensi dan pengalaman terkait dengan produk yang mereka gunakan. Dibandingkan dengan gambar dan video, format teks UGC adalah jenis yang paling mudah diakses untuk dikumpulkan dan dianalisis. Sampai saat ini belum ada analisis teks yang memadai tentang ulasan hotel di Sumatera Barat. Tujuan dari penelitian ini adalah untuk mengidentifikasi pola ulasan elektronik hotel untuk mengetahui faktor-faktor yang membuat pengunjung hotel merasa puas. Penelitian ini menggunakan 482 ulasan berbahasa Inggris dengan penilaian 4 dan 5 hotel terbaik di Sumatera Barat di Tripadvisor. Berdasarkan pengujian faktual dan pendekatan teoritis yang dilakukan, penelitian ini mengungkapkan bahwa kebersihan kamar merupakan faktor utama kepuasan pelanggan hotel ditambah dengan aspek makanan dan pelayanan yang ramah. Kata kunci: Analisis teks, ulasan hotel, user-generated content Abstract. Internet users have populated the digital world with user-generated content (UGCs) such as text, pictures or videos. Those contents represent their opinion, preferences and experience related to the product that they use. In comparison with pictures and videos, the text format of UGC is the most accessible type to collect and analyse. To date, there has not been an adequate text analysis related to hotel review in West Sumatera. The purpose of this study is to identify hotel electronic review patterns to find out the factors that make hotel visitors satisfied. This study used 482 English reviews with a rating of 4 and 5 on the best West Sumatra hotels on Tripadvisor. Based on factual testl and theoritical approach, this study reveals that room cleanliness is the main generator of hotel customer satisfaction coupled with aspects of food and friendly service. Keywords: Text analysis, hotel review, user-generated content
Quarter-Circle Shaped Plane Cavity Resonator for Skew-Free and Low Jitter Clock Distribution Network

This paper proposes a quarter-circle shaped plane resonator for skew-free and low jitter clock distribution network (CDN). A cavity resonator consists of the embedded planes in a package or PCB and an inductive load. The resonant frequency can be controlled by the inductance of the load and quarter-circle shaped plane can make all edge having the same phase and also same amplitude. We have successfully demonstrated a 1.35 GHz clock delivery network with a skew of 0.5 ps, and suppressed jitter through modeling and simulation.
Genetic Diversity of Chanos Chanos (Forsskål, 1775) from Natural Populations in Vietnam

The genetic diversity of five natural populations of milkfish (Chanos chanos) collected in Nghe An, Quang Binh, Binh Dinh, Phu Yen, Khanh Hoa provinces in Vietnam was examined using COI gene sequence analysis. Twelve haplotypes were noted from a total of 50 sequences along with 12 variable sites and 6 parsimony informative sites. The Quang Binh milkfish population had the highest haplotype (0.889 ± 0.060) and nucleotide diversities (0.00301 ± 0.00049). Overall, haplotype and nucleotide diversities were 0.804 ± 0.036 and 0.00212 ± 0.00026, respectively. Genetic differentiation (FST) was high between the milkfish populations of Nghe An – Quang Binh (0.21744) and Nghe An - Phu Yen (0.26215). Haplotype network analysis indicated that milkfish populations shared common haplotypes and each population had its own private haplotypes. Population structure and demographic expansion were not evident for all populations except for Quang Binh. This is the first principal endeavor to understand genetic information of milkfish in Vietnam, thereby providing information for scientists, managers, and the general public to establish timely strategies to explore, protect, and develop milkfish genetic resources in the future.
Impact of Metabolic Dysfunction Associated Fatty Liver Disease on the Prognosis of Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma Based on Propensity Score Matching Analysis

Purpose Both metabolic dysfunction-associated fatty liver disease (MAFLD) and hepatitis B virus (HBV) are risk factors for hepatocellular carcinoma (HCC). Although concurrent MAFLD is common in patients with HBV-related HCC, whether MAFLD increases the risk of poor prognosis in patients with HBV-related HCC remains unclear. This study aimed to investigate the impact of MAFLD on prognosis in patients with HBV-related HCC. Patients and Methods In this retrospective cohort study, 549 patients with HBV-related HCC were enrolled from January 2010 to April 2020 in Guangdong Provincial Hospital of Chinese Medicine, including 169 patients with MAFLD (MAFLD group) and 380 patients without MAFLD (Non-MAFLD group). Propensity score matching (PSM) analysis was performed to balance the baseline characteristics. Kaplan–Meier survival curves were performed to compare the prognosis between the two matched groups. A multivariate Cox proportional hazards model was used to determine the risk factors for poor prognosis. Results The median follow-up time for all patients was 20 (interquartile range 8–40) months. We found concurrent MAFLD was associated with a significantly decreased PFS rate before and after PSM analysis. The 1-year, 2-year, and 3-year PFS rates for the MAFLD and Non-MAFLD groups after PSM were 61.3% and 70.8%, 43.9% and 54.5%, 31.1% and 41.8%, respectively. Cox multivariable analysis showed that concurrent MAFLD was an independent risk factor for poor prognosis (death or progression) (HR = 1.49, P = 0.001). More interestingly, the risk of poor prognosis was significantly higher in the MAFLD subtype with metabolic components ≥2 compared to those with metabolic components <2 (HR = 1.97, P < 0.001). Conclusion Concurrent MAFLD was associated with a higher risk of poor prognosis in patients with HBV-related HCC, especially MAFLD with metabolic components ≥2.
R&D, innovations, and firms’ productivity in Ethiopia

Evidence of how R&D, innovation and productivity are intertwined in African countries like Ethiopia is quite limited. This study provides empirical evidence on the relationship between R&D, innovations, and productivity for Ethiopian firms using two rounds of the World Bank’s Enterprise Survey dataset of year 2011 and 2015. We estimate firm-level productivity using a control function method, and the link between R&D, innovations, and productivity is estimated using the General Structural Equation Model (GSEM). We estimated for product and process innovations separately and jointly. The results show that innovations have a strong and positive impact on a firm’s productivity in all estimation methods. Thus, innovative firms are more productive than their counterparts. However, the effect of R&D on innovations is positive and significant in GSEM estimation but not in other estimation methods. The findings also show that skilled labour and financial accessibility are key driving forces behind firms’ engagement in R&D and innovative activities. Thus, there is a need to find a mechanism to promote firms’ engagement in knowledge production, and design appropriate policies to enhance firm-level innovation initiatives. This study contributes to developing countries’ empirical literature in terms of modelling the relationship between R&D, innovations, and firm productivity.
Um Estudo de Caso da Detecção do Uso de Máscaras Faciais com Redes Neurais Convolucionais Regionais

Com o objetivo de desenvolver soluções para Cidades Inteligentes que colaborem na mitigação da propagação de doenças, este trabalho considerou o problema de Visão Computacional de detecção do uso de máscaras faciais, o qual foi abordado com os modelos YOLOv3 e YOLOv5 em um estudo de caso com três conjuntos de dados distintos e realísticos. Os resultados experimentais destacaram o YOLOv5 Small 6 como a solução de referência com um mAP de 92,8 % em um cenário de validação com exemplos unificados. Também foi realizada uma transferência de aprendizado desse modelo com imagens do conjunto de dados AIZOO e os resultados foram comparados com soluções da literatura, em que verificou-se competitivo com as alternativas do estado da arte e com forte potencial para ser embarcado em dispositivos computacionais com recursos limitados.
REVIEW ARTICLE: Mass flow measurement of bulk solids in pneumatic pipelines

Many types of techniques for metering the mass flow rate of bulk solids in a pneumatic pipeline have been proposed and developed during the past 20 years. This paper presents a detailed and comprehensive review of the techniques and the current state of knowledge and experience. The techniques are classified under three main categories: direct measurement of solids mass flow rates, measurement of volumetric concentrations of solids and measurement of solids velocity. Future developments and possible trends in this field are also included.