Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimates of matrix solutions of operator equations with random parameters under uncertainties

We investigate problems of estimating solutions of linear operator equations with random parameters under conditions of uncertainty. We establish that the guaranteed rms estimates of the matrices are found as solutions of special optimization problems under certain observations of the system state. As the output signals of the system, we have observations that are described by linear functions from the solutions of such equations with random right-hand sides, which have unknown second moments. Under the condition that the observation second moments of the right-hand parts and errors belong to certain sets, it is proved that the guaranteed estimates are expressed through solutions of operator equation systems. When the linear operator is given by the scalar product of rectangular matrices, a quasi-minimax estimate and its error are constructed. It is shown that the quasi-minimax estimation error tends to zero when the number of observations tends to infinity. An example of calculating the guaranteed rms estimate of the matrix's trace, which is a solution of a matrix equation with a random parameter, is given.
A low volume flexible CPW‐fed elliptical‐ring with split‐triangular patch dual‐band antenna

In this article, the intensive investigations are carried out on a low volume compact flexible antenna for wireless applications with a novel structure model. The proposed model has considered as an elliptical‐ring with split‐triangular patch (ERSTP) antenna with the coplanar waveguide feeding to achieve dual‐bands. The ERSTP antenna is designed with polyimide material having the volume (L a × W a × h) 99 mm3. The ERSTP antenna resonates with 2.60 GHz and 3.48 GHz frequencies with a reflection coefficient of −21.92 dB and −32.14 dB and a gain of 2.39 dBi and 1.75, dBi respectively. The impedance bandwidths are 100 MHz and 330 MHz observed at two frequency bands. The proposed ERSTP antenna has operated on mobile‐worldwide interoperability for microwave access (M‐WiMAX) and worldwide interoperability for microwave access (WiMAX) bands respectively. The simulated and measured results of ERSTP antenna are in good agreement.
Opinions and Competencies of the Elderly and Disabled towards the Use of Mobile Devices and Applications

Many mobile applications have been developed for the elderly and disabled in recent years. The elderly and disabled can check their health information and access health services easier through mHealth (Mobile Health) applications. The aim of this study is to determine the competencies and opinions of the elderly and disabled towards these mobile devices and the NEU-LIFE ASSIST ANDROID application developed by researchers. In this context, the frequency with which the elderly and disabled use these devices and the effectivity of these devices has been researched. Therefore, the competencies of the elderly and disabled using mHealth applications can be determined and this data can be used in further studies. When the study findings regarding whether the elderly and disabled perceive themselves to be competent in using mobile devices are examined, it is observed that they can call, message and access information through the internet faster. When their opinions are considered, they stated that mobile devices and the NEU-LIFE ASSIST ANDROID application made their lives easier and improved their ability to communicate. Individuals who stated they could easily meet their needs at home using their mobile devices thought it would be more beneficial for mobile applications that enable this to be developed. Future studies should consider the development of more mobile applications that can be used in the field of health and investigate the effectivity of such applications.
Ultrasound-Guided Bilateral Erector Spinae Plane Block vs. Ultrasound-Guided Bilateral Posterior Quadratus Lumborum Block for Postoperative Analgesia after Caesarean Section: An Observational Closed Mixed Cohort Study

ESP block (ESPB) and posterior Quadratus Lumborum Block (pQLB) have been proposed as opioid-sparing techniques for the management of pain after abdominal surgery. Between December 2021 and October 2022, we conducted a retrospective comparative study at the delivery suite of Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy, to compare the efficacy of ESPB and pQLB in preventing postoperative pain after an elective caesarean section (CS). The primary outcome was total morphine consumption in the first 24 h. Secondary outcomes were time to first opioid request; Numerical Pain Rating Scale (NPRS) at 0, 2, 6, 12 and 24 h; vital signs; adverse events. Fifty-two women were included. The total cumulative dose of morphine was not significantly different between the two groups of patients (p = 0.897). Time to first dose of morphine, NPRS values and haemodynamic parameters were not statistically different between the two groups. NPRS values significantly increased (p < 0.001) at the different time intervals considered. The need for rescue doses of morphine was lower in the ESPB group compared to the pQLB group (hazard ratio of 0.51, 95% CI (0.27 to 0.95), p = 0.030). No adverse event was reported. ESPB seems to be as effective as pQLB in providing analgesia after CS.
DSGCN: A Degree Strength Graph Convolution Network for Identifying Influential Nodes in Complex Networks

Identifying influential nodes in complex networks is crucial for applications such as information control, viral marketing, and pricing strategy analysis. However, traditional centrality methods have limitations when applied to weighted networks with varying connection intensities. To address this challenge, we introduce Degree Strength (DS) based Graph Convolution Network (DSGCN). This GCN model integrates node degree and strength as features to accurately identify influential nodes in weighted networks. We conducted a performance analysis, comparing the effectiveness of DS with traditional centrality methods. Additionally, we evaluated the $GCN$-based approach that integrates DS and traditional centrality methods as features to assess its performance. The experimental analysis demonstrates that leveraging $GCN$ on D S outperforms existing methods to capture ranking similarity and accurately identify influential spreaders in complex weighted networks. Evaluation metrics such as Kendall $\tau$ correlation and improvement percentage consistently show the superiority of DSGCN. By effectively handling connected and disconnected networks, DSGCN provides valuable insights into understanding influence dynamics in real-world scenarios.
Upper-Level Winds over Southern Ontario: O-QNet Wind Profiler and NARR Comparisons

ABSTRACT Upper-level winds are primarily measured by tracking the position of radiosonde balloons as they rise through the atmosphere. Radiosondes are released from a global network at 0000 utc and 1200 utc each day, and data are quickly available to the world's weather services, as well as to the public. The network is relatively coarse spatially, and there are normally only two soundings per day. In an endeavour to provide better spatial and temporal upper-level regional wind measurements, the O-QNet (a demonstration very high frequency wind profiler network for Ontario and Quebec) was installed and has been operated by York, Western, and McGill Universities with support from Mardoc Inc., The Weather Network, and Environment and Climate Change Canada. Initial funding was provided by the Canada Foundation for Innovation, the Ontario Innovation Trust, and Mardoc Inc. The present paper reports primarily on comparisons between winds measured by the O-QNet profilers and the winds reported in the North American Regional Reanalysis (NARR). There is good agreement between the two, which provides support for the use of NARR data to investigate longer term variations in upper-level winds associated with climate change for this region.
Comment changer? Quelques pistes de réflexion d’un point de vue syndical

De nouvelles opportunités s’offrent au mouvement syndical. La rareté de la main-d’oeuvre et la situation économique (inflation) procurent une conjoncture favorable aux organisations syndicales leur permettant de regagner du terrain perdu. De plus, outre la récente décision de la Cour d’appel du Québec concernant les travailleurs et travailleuses étudiants d’ABI - qui reconnait que ceux-ci ne peuvent pas être payés moins pour accomplir des tâches équivalentes - de récents changements législatifs rendent plus difficiles l’adoption de clauses de disparité de traitement et commandent l’obligation d’une rémunération équivalente pour les travailleurs et travailleuses d’agence. Reconnaissant la nécessité du changement organisationnel, thématique de ce numéro, pour les différentes parties prenantes du monde du travail, les auteur.es posent alors cette question : comment les organisations syndicales pourraient saisir l’occasion qui se présente? Dit autrement, comment pourraient-elles contribuer à réduire la précarité en emploi tout en assurant la pérennité des organisations ? Après cinq décennies de « vent de face », les astres sont alignés pour que le mouvement syndical reprenne l’offensive et travaille à renverser la vapeur de la précarisation du travail, Pour se faire, il faut sortir du carcan de leur corporatisme syndical, et surtout ne pas « surfer » sur la satisfaction des membres. Il faut au contraire des actions d’éducation, de mobilisation et de sécurisation, afin de contrer la précarisation du marché du travail. Cette conjoncture favorable doit aussi bénéficier aux travailleurs et travailleuses précaires, une telle opportunité ne se représentera pas souvent!
Network Analysis of Publicly Available RNA-seq Provides Insights into the Molecular Mechanisms of Plant Defense against Multiple Fungal Pathogens in Arabidopsis thaliana

Fungal pathogens can have devastating effects on global crop production, leading to annual economic losses ranging from 10% to 23%. In light of climate change-related challenges, researchers anticipate an increase in fungal infections as a result of shifting environmental conditions. However, plants have developed intricate molecular mechanisms for effective defense against fungal attacks. Understanding these mechanisms is essential to the development of new strategies for protecting crops from multiple fungi threats. Public omics databases provide valuable resources for research on plant–pathogen interactions; however, integrating data from different studies can be challenging due to experimental variation. In this study, we aimed to identify the core genes that defend against the pathogenic fungi Colletotrichum higginsianum and Botrytis cinerea in Arabidopsis thaliana. Using a custom framework to control batch effects and construct Gene Co-expression Networks in publicly available RNA-seq dataset from infected A. thaliana plants, we successfully identified a gene module that was responsive to both pathogens. We also performed gene annotation to reveal the roles of previously unknown protein-coding genes in plant defenses against fungal infections. This research demonstrates the potential of publicly available RNA-seq data for identifying the core genes involved in defending against multiple fungal pathogens.
Multi-objective Reinforcement Learning with Path Integral Policy Improvement

Multi-objective reinforcement learning (MORL) for robot motion learning is a challenging problem not only because of the scarcity of the data but also of the high-dimensional and continuous state and action spaces. Most existing MORL algorithms are inadequate in this regard. However, in single-objective reinforcement learning, policy-based algorithms have solved the problem of high-dimensional and continuous state and action spaces. Among such algorithms is policy improvement with path integral (PI2), which has been successful in robot motion learning. P$\mathrm{I}^{2}$ is similar to evolution strategies (ES), and multi-objective optimization is a hot topic in ES algorithms. This paper proposes a MORL algorithm based on P$\mathrm{I}^{2}$ and multi-objective ES, which can handle the problem related to robot motion learning. The effectiveness is shown via numerical simulations.
Optimizing Anesthetic Practices for Mud Crab: A Comparative Study of Clove Oil, MS-222, Ethanol, and Magnesium Chloride

Anesthesia serves as an effective method to mitigate the stress response in aquatic animals during aquaculture and product transportation. In this study, we assessed the anesthetic efficacy of clove oil, tricaine methane-sulfonate (MS-222), ethanol, and magnesium chloride by anesthesia duration, recovery time, 24-hour survival rate, and the behavior of mud crabs (Scylla paramamosain). Additionally, the optimal anesthetic concentration for varying body weights of mud crabs was also investigated. The results revealed that clove oil emerged as the optimal anesthetic for mud crabs, with a 24-hour survival rate surpassing those observed in MS-222 and magnesium chloride treatments. Ethanol caused amputation and hyperactivity in mud crabs. Regression analyses between the optimal anesthetic concentration of clove oil and the weight categories of 0.03–27.50 g and 27.50–399.73 g for mud crabs yielded the following equations: y = 0.0036 x3 − 0.1629 x2 + 1.7314 x + 4.085 (R2 = 0.7115) and y = 0.0437 x + 2.9461 (R2 = 0.9549). Clove oil exhibited no significant impact on serum cortisol, glucose, lactate content, aspartate aminotransferase (AST), alanine aminotransferase (ALT) activities, or superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-Px), and malondialdehyde (MDA) levels in mud crabs across different treatment groups. Anesthesia induced by clove oil in mud crabs resulted in an increase in inhibitory neurotransmitters such as glycine. However, the recovery from anesthesia was associated with elevated levels of the excitatory neurotransmitters L-aspartic acid and glutamate. In conclusion, clove oil proves to be a safe and optimal anesthetic agent for mud crabs, exerting no physiological stress on the species.
Physical and psychological consequences of serious road traffic injuries, deliverable 7.2 of the H2020 project SafetyCube

SafetyCube aims to develop an innovative road safety Decision Support System (DSS) that will enable policy-makers and stakeholders to select the most appropriate strategies, measures and cost-effective approaches to reduce casualties of all road user types and all severities. Work Package 7 of SafetyCube is dedicated to serious road traffic injuries, their health impacts and their costs. This Deliverable discusses health impacts of (serious) road traffic injuries.
Impact of Industrial Effluent Discharge on Physico-Chemical Characteristics of Agricultural Soil

Rapid industrialization affects the environment in different ways by discharging the large amount of effluent as waste water in the surrounding water bodies, causing the serious problems to environment. Due to lack of irrigation water in the present study area canal water was used in which effluents from various industries were being discharged. Canal water was containing high COD, BOD values and higher heavy metal content and the soil irrigated with this water was showing the poor status of the nutrients and high contamination of heavy metals. The present study was to evaluate the various adverse effects on the soil characteristics irrigated with discharged water.
Prediction of vertical distribution of SPAD values within maize canopy based on unmanned aerial vehicles multispectral imagery

Real-time monitoring of canopy chlorophyll content is significant in understanding crop growth status and guiding precision agricultural management. Remote sensing methods have demonstrated great potential in this regard. However, the spatiotemporal heterogeneity of chlorophyll content within crop canopies poses challenges to the accuracy and stability of remote sensing estimation models. Hence, this study aimed to develop a novel method for estimating canopy chlorophyll content (represented by SPAD values) in maize (Zea mays L.) canopies. Firstly, we investigated the spatiotemporal distribution patterns of maize canopy SPAD values under varying nitrogen application rates and different growth stages. The results revealed a non-uniform, “bell-shaped” curve distribution of maize canopy SPAD values in the vertical direction. Nitrogen application significantly influenced the distribution structure of SPAD values within the canopy. Secondly, we achieved satisfactory results by fitting the Lorentz peak distribution function to the SPAD values of different leaf positions in maize. The fitting performance, evaluated using R2 and RMSE, ranged from 0.69 to 0.98 and 0.45 to 3.59, respectively, for the year 2021, and from 0.69 to 0.77 and 2.38 to 6.51, respectively, for the year 2022.Finally, based on the correlation between canopy SPAD values and vegetation indices (VIs) at different growth stages, we identified the sensitive leaf positions for the selected CCCI (Canopy Chlorophyll Index) in each growth stage. The 6th (r = 0.662), 4th (r = 0.816), 12th (r = 0.722), and 12th (r = 0.874) leaf positions exhibited the highest correlations. Compared to the estimation model using canopy wide SPAD values, the model based on sensitive leaf positions showed improved accuracy, with increases of 34%, 3%, 20%, and 3% for each growth stage, respectively. In conclusion, the findings of this study contribute to the enhancement of chlorophyll content estimation models in crop canopies and provide valuable insights for the integration of crop growth models with remote sensing methods.
Whole-genome sequencing and comparative genome analysis of Xanthomonas fragariae YM2 causing angular leaf spot disease in strawberry

Background Angular leaf spot disease caused by plant pathogenic bacterium Xanthomonas fragariae seriously threatens strawberry crop production globally. Methods In this study, we sequenced the whole genome of X. fragariae YM2, isolated from Yunnan Province, China. In addition, we performed a comparative genome analysis of X. fragariae YM2 with two existing strains of X. fragariae YL19 and SHQP01 isolated from Liaoning and Shanghai, respectively. Results The results of Nanopore sequencing showed that X. fragariae YM2 comprises one single chromosome with a contig size of 4,263,697 bp, one plasmid contig size of 0.39 Mb, a GC content ratio of 62.27%, and 3,958 predicted coding genes. The genome of YM2 comprises gum, hrp, rpf, and xps gene clusters and lipopolysaccharide (LPS), which are typical virulence factors in Xanthomonas species. By performing a comparative genomic analysis between X. fragariae strains YM2, YL19, and SHQP01, we found that strain YM2 is similar to YL19 and SHQP01 regarding genome size and GC contents. However, there are minor differences in the composition of major virulence factors and homologous gene clusters. Furthermore, the results of collinearity analysis demonstrated that YM2 has lower similarity and longer evolutionary distance with YL19 and SHQP01, but YL19 is more closely related to SHQP01. Conclusions The availability of this high-quality genetic resource will serve as a basic tool for investigating the biology, molecular pathogenesis, and virulence of X. fragariae YM2. In addition, unraveling the potential vulnerabilities in its genetic makeup will aid in developing more effective disease suppression control measures.
Health Behavior Models and Regular Exercise Levels Among Workers in Taiwan

Purpose The present study aims to examine the disparate effects of health behavior models, namely exercise self-efficacy (ESE), health belief model (HBM), and planned behavior theory (PBT), applied to clarify the degree of regular exercise among workers in Taiwan. Methods A cross-sectional research design was adopted. A questionnaire was distributed to obtain information pertaining to regular exercise level, demographic characteristics, and the scores of ESE, HBM, and PBT. In total, 400 full-time workers voluntarily participated in this study. Results The results showed that only 20.5% of the participants exercised regularly, 37.3% exercised irregularly, and 42.3% did not exercise currently. “Perceived benefits” and “perceived barriers” pertaining to HBM; “attitude” and “perceived behavioral control” pertaining to PBT; and ESE were associated with regular exercise level in the multiple linear regression analyses of each health behavior model. When all three models were considered simultaneously, ESE provided the greatest explanation of the variances for regular exercise levels. PBT total made a smaller contribution in the prediction of regular exercise level, while the effect of HBM did not show statistical significance. In order to explore the practicality of moving beyond theoretical models and focusing on the components across health behavior models to enhance workers’ exercise behavior, the components showing statistical significance in separate analysis were put into the multiple linear regression simultaneously. The results showed that ESE, perceived barriers of health behavior, attitude, and perceived behavioral control were significantly associated with regular exercise level. Conclusion A low percentage of workers exercising regularly should be a notable issue for workplace health promotion. Neither utilizing cues to exercise nor advertising health threats of physical inactivity is sufficient to enable workers to exercise regularly. Enhancing workers’ ESE and behavior control and removing the exercise barriers would constitute efficient strategies for maintaining the exercise habit of workers.
A Particle Swarm Optimization Fault Location Method Considering Terminal Reflection Phase Shift

This paper investigates how the accuracy of fault location is affected by the terminal reflection uncertainty and proposes a full-transient fault location method based on particle swarm optimization (PSO) algorithm to solve the location uncertainty bias. The LCC-HVDC system is taken as the research object, the maximum relative location error reach 9.3% and 17.96% for hundreds of kilometers line due to the uncertainty of the reflection coefficient of the converter station. The PSO algorithm is proposed to optimize the phase shift of the power transmission line boundary reflection coefficient, make the simulation natural frequency being closest to the real natural frequency which will erase the location further. The simulation result illustrates that the proposed method has a better robust ability to the terminal phase shift from the incomplete modeling whose maximum location error is less than 1%.