Miracle-dz/UniFAR-FTUs huggingface dataset:
New Constructions of Binary MDS Array Codes with Optimal Repair Bandwidth

Maximum distance separable codes are commonly used in large-scale distributed storage systems since they achieve the maximum fault tolerance for some given redundancy. In this paper, we focus on the repair problem of MDS codes. By stacking multiple Blaum-Roth code instances of which the parity-check matrices are judiciously designed, we construct three families of binary MDS array codes with optimal repair bandwidth for single-node failure. Specifically, codes in the first family achieve the lower bound on repair bandwidth where the number of helper nodes d is n − 1; The second family of codes are optimal-repair for any fixed d and the third are for multiple values of d simultaneously. Moreover, the last two also possess error-resilient capability and can achieve the corresponding optimal repair bandwidth. All the codes in this paper are constructed on a particular polynomial ring over binary field. Consequently, computation operations involved in node repair and file reconstruction for these codes are only XORs and cyclic shifts, avoiding complex multiplications and divisions over large finite fields.
An effective hybrid approach for the synthesis of pencil beams and shaped beams through 4D linear antenna arrays with constrained DRR

ABSTRACT In this work, a novel hybrid approach combining differential evolution (DE) algorithm and convex programming (CP) is proposed for the synthesis of four-dimensional (4D) antenna arrays. To achieve ultra-low sidelobe level while suppressing sideband radiations simultaneously, the hybrid approach is applied to optimize static excitation coefficients and switch-on duration time separately. In particular, the hybrid approach fully makes use of the partial convexity of the problem with respect to the static excitation coefficients. CP is used to optimize static excitation coefficients for each set of switch-on duration time generated by the DE algorithm, while the DE algorithm is used to optimize the switch-on duration time only. Consequently, fewer optimization variables are needed and less iterations are required. The approach converges faster as compared to stochastic algorithms including all the optimization variables, especially for large arrays. Several numerical examples of the 4D antenna arrays are presented to demonstrate the effectiveness of the proposed hybrid approach.
Perceptions of high-involvement work practices and burnout: the mediating role of job demands

This study examined the impact of perceived high involvement work practices (HIWPs) on job demands (role conflict, role overload and role ambiguity) and burnout (emotional exhaustion and depersonalisation). The study was conducted in a Canadian general hospital. Findings from structural equation modelling ( N = 545) revealed that perceived HIWPs were significantly and negatively related to job demands and burnout. Role conflict and role overload have a significant positive association with emotional exhaustion and depersonalisation. Finally, role conflict and role overload partially mediate the relationship between perceived HIWPs and burnout. We discuss the theoretical and managerial implications of these findings for our understanding of how HIWPs influence the job demands and burnout of employees.
Perceptions of high involvement work practices , person-organization fit and burnout : a time lagged study of health care

Previous research demonstrates that high involvement work practices (HIWPs) may be associated with burnout (emotional exhaustion and depersonalization); however, to date, the process through which HIWPs influence burnout is not clear. This article examined the impact of HIWPs on long term burnout (emotional exhaustion and depersonalization) by considering the mediating role of person-organization fit (P-O fit) in this relationship. The study used a time lagged design and was conducted in a Canadian general hospital amongst health care personnel. Findings from structural equation modeling (N = 185) revealed that perceived HIWPs were positively associated with P-O fit. There was no direct effect of HIWPs on burnout; rather, P-O fit fully mediated the relationship between employee perceptions of HIWPs and burnout. This study fills a void in the HR and burnout literature by demonstrating the role that P-O fit has in explaining how HIWPs alleviates emotional exhaustion and depersonalization.
Perceptions of high involvement work practices, person-organization fit and burnout: a time lagged study of health care employees

Previous research demonstrates that high involvement work practices (HIWPs) may be associated with burnout (emotional exhaustion and depersonalization); however, to date, the process through which HIWPs influence burnout is not clear. This article examined the impact of HIWPs on long term burnout (emotional exhaustion and depersonalization) by considering the mediating role of person-organization fit (P-O fit) in this relationship. The study used a time lagged design and was conducted in a Canadian general hospital amongst health care personnel. Findings from structural equation modeling (N = 185) revealed that perceived HIWPs were positively associated with P-O fit. There was no direct effect of HIWPs on burnout; rather, P-O fit fully mediated the relationship between employee perceptions of HIWPs and burnout. This study fills a void in the HR and burnout literature by demonstrating the role that P-O fit has in explaining how HIWPs alleviates emotional exhaustion and depersonalization.
Bayesian spatio-temporal modelling for forecasting ground level ozone concentration levels

Accurate, instantaneous and high resolution spatial air-quality information can better inform the public and regulatory agencies of the air pollution levels that could cause adverse health effects. The most direct way to obtain accurate air quality information is from measurements made at surface monitoring stations across a study region of interest. Typically, however, air monitoring sites are sparsely and irregularly spaced over large areas. That is why, it is now very important to develop space-time models for air pollution which can produce accurate spatial predictions and temporal forecasts. This thesis focuses on developing spatio-temporal models for interpolating and forecasting ground level ozone concentration levels over a vast study region in the eastern United States. These models incorporate output from a computer simulation model known as the Community Multi-scale Air Quality (Eta-CMAQ) forecast model that can forecast up to 24 hours in advance. However, these forecasts are known to be biased. The models proposed here are shown to improve upon these forecasts for a two-week study period during August 2005. The forecasting problems in both hourly and daily time units are investigated in detail. A fast method, based on Gaussian models is constructed for instantaneous interpolation and forecasts of hourly data. A more complex dynamic model, requiring the use of Markov chain Monte Carlo (MCMC) techniques, is developed for forecasting daily ozone concentration levels. A set of model validation analyses shows that the prediction maps that are generated by the aforementioned models are more accurate than the maps based solely on the Eta-CMAQ forecast data. A non-Gaussian measurement error model is also considered when forecasting the extreme levels of ozone concentration. All of the methods presented are based on Bayesian methods and MCMC sampling techniques are used in exploring posterior and predictive distributions.
Subfield Attack on NTRU by using symmetric function map

We describe a subfield attack for NTRU problem by using the symmetric function map Sk, which is a generalization of results presented by Albrecht, Bai and Ducas [1] and Cheon, Jeong and [2]. At first, we prove that Sk with an appropriate k can fits for more cases compared with previous related works while maintaining the same or better efficiency. Then we show the subfield attack has its advantage compared with the subring attack described in [3]. At last we present a method to make the subfield attack algorithm more efficient.
Determination of Contaminants in Some Iranian Popular Herbal

Introduction: Medicinal plants have been used therapeutically all around the world, being an important aspect of various traditional medicine systems. However, the use of phytotherapy according to the efficacy and safety criteria is not sufficient to guarantee the quality of both the herbal medicine and its use. Objective : The aim of this study was to determine the level of Cd, Pb, Ni, Cu , Hg and pesticide residues in some commonly used herbal medicines and herbal plants to assess the relative safety of these products based on world standard limits and potential health risk to local inhabitants. Materials & Methods: 6 different medicinal herbal products and 6 herbal plants were purchased from Tehran's market. Certain weight of each samples were digested with nitric acid by wet digestion method for determining of toxic metals. Atomic absorption spectrometry (AA) was used for the determination of the concentration of Pb, Cd, Ni, Cu and an automated continuous - flow hydride vapor generation system was used for Hg and pesticide residues were analyzed by gas-chromatography - mass spectrometry after extraction performed using solid - phase micro extraction technique. Results: Results were compared with the permissible limits (Pl), acceptable daily intake (ADI) and provisional maximum tolerable daily intake (PMTDI) as set by world health organization (WHO), Food and Drug administration (FDA). Mercury, Lead and Cadmium were highly present in the majority of samples. In 100% of medicinal plant samples which brought randomly from the markets, the amounts of Diazinon, Fenitrothion, Malathion was higher than the allowed limits when compared to the MRL scale. Conclusion: By a comparison between acceptable global standards and the level of Hg, Cd and Pb on investigated herbal medicine and medicinal plants, our results showed that the majority of medicinal plants samples had higher level of these heavy metals. Due to lack of research data and technical limitations at present, more research is needed in order to establish the scientific criteria for herbal medicines.
THE EASTERN SLOPES OF MOUNT KENYA

The ever growing population and the need for more food make the knowledge of soil properties essential to maximise agricultural production on the currently available land. High costs of soil survey and laboratory measurements are among the major reasons for lack of sufficient soil information, which is important for proper land management. In this research, an innovative approach, comprising an optimized soil sampling design, a rapid and cost-efficient mid-infrared spectroscopy (MIR) and geostatistics was applied to provide necessary soil data for proper land management in the eastern slopes of Mt. Kenya. Conditional Latin hypercube method was used to develop a sampling design that ensured full coverage of environmental variables. Topographic variables were extracted from the digital elevation model, soil attributes from the Kenya Soil and Terrain (KENSOTER) database, and vegetation characteristics from the Normalized difference vegetation index generated from Landsat 8 imagery. The developed sampling scheme conserved the distribution of environmental covariates using box plots to validate. Soil spectra for the 232 samples collected from 77 georeferenced locations were measured using MIR spectroscopic methods at wavelength range of 4000 – 400/cm. To select the calibration samples from the MIR spectral database, principal component analysis and Kennard-Stone algorithm were used. Random forest regression was used to calibrate laboratory measurements to the soil MIR spectra. Good spectral prediction model performance was achieved as follows: soil organic carbon,
Microbiome structure of a wild Drosophila community along tropical 1 elevational gradients and comparison to laboratory lines 2

25 While the biogeography of free-living microbial communities is well-studied, community 26 turnover along environmental gradients in host-associated communities is not well 27 understood. In particular, patterns of host-microbiome diversity along elevational gradients 28 remain largely uncharacterized. Because elevational gradients may serve as natural proxies 29 for climate change, understanding these temperature-influenced patterns can inform our 30 understanding of the threats facing hosts and their microbes in a warming world. In this study, 31 we analysed microbiomes from pupae & adults of four Drosophila species native to Australian 32 tropical rainforests. We sampled wild individuals at high and low elevation along two 33 mountain gradients, to determine natural diversity patterns, and sampled laboratory-reared 34 individuals from isofemale lines established from the same localities, to see if any natural 35 patterns would be retained in the lab. In both environments, we controlled for diet to help 36 elucidate other deterministic patterns of microbiome composition. Microbiome community 37 composition differed radically between laboratory-reared and field-caught flies but did not 38 significantly differ across elevation. We found some notable taxonomic differences in 39 Drosophila microbiomes between different species and elevations. We also found similar 40 microbiome composition from both types of provided food, and we therefore suggest the 41 significant differences in richness are the products of environments with different bacterial 42 species pools. We conclude that elevational differences in temperature are not a major factor 43 in determining Drosophila microbiome composition and we caution against determining 44 microbiome composition from lab-only specimens, particularly long-term cultures. 45
Prospects of the sugarcane expansion in Brazil: impacts on direct and indirect land use changes.

Sugarcane has been an important crop since the initial colonization period of Brazil and is nowadays expanding considerably its cultivated area, particularly due to strong ethanol demand. Ethanol demand has been increasing in the internal market since 2003 due to the expansion of the ! ex-fuel car ! eet and is also facing good perspectives in the international market. From 2000 to 2007 the cultivated sugarcane area increased by about 3 million ha, reaching about 7.9 million ha based on information from IBGE (2008a). "e South-Central region was responsible for 95.7% of this total growth.
AI-Enabled Big Data Pipeline for Plant Phenotyping and Application in Cotton Bloom Detection and Counting

With a rapidly growing global population, meeting increasing agricultural demands has become imperative. Smart farming, powered by machine learning, has the potential to address this issue but faces hurdles in managing big data with high velocity. In this study, we implement a comprehensive big data pipeline for cotton bloom detection that utilizes Azure cloud computing resources and employs YOLOv5 for real-time and batch processing. The model achieves a high mean Average Precision (mAP) score of 0.96 for cotton bloom classification using 2021 data. We also explore the use of Principal Component Analysis (PCA) as a compression method to optimize pipeline execution time and storage space. Rigorously tested for scalability on distinct 2022 data, our pipeline incorporates downsampling with masking as an effective pre-processing step to reduce computational overhead while preserving accuracy. This research underscores the potential of cloud computing in driving efficient big data processing in precision agriculture, enabling accurate crop yield prediction through advanced plant phenotyping techniques. Index words: Big Data Pipeline, Lambda Architecture, Plant Phenotyping, Cotton Bloom Detection, Computer Vision, Principal Component Analysis AI-Enabled Big Data Pipeline for Plant Phenotyping and Application in Cotton Bloom Detection and Counting
Nutrient digestion and absorption during chemotherapy-induced intestinal muscositis in the rat

Background Patients with chemotherapy ‐ induced gastrointestinal mucositis suffer from anorexia, diarrhea and stomach pain, often causing weight loss and malnutrition. When the intestinal function during mucositis would be known, a rational feeding strategy might improve the nutritional state, accelerate recuperation and increase survival of mucositis patients. Methods We developed a methotrexate (MTX) ‐ induced mucositis rat model to study nutrient digestion and absorption. To determine lactose digestion and absorption of its derivative glucose during mucositis, we injected Wistar rats intravenously with MTX (60 mg/kg) or NaCl 0.9% (controls). Four days later, we orally administered trace amounts of [1 ‐ 13 C]lactose and [U ‐ 13 C]glucose and quantified appearance of labeled glucose in the blood for 3 h. Finally, we determined plasma citrulline level and harvested the small intestine to assess histology, myeloperoxidase level, glycohydrolase activity, immunohistochemical protein and mRNA expression. Results MTX ‐ treated rats showed profound villus atrophy and epithelial damage. During the experimental period, the absorption of lactose ‐ derived [1 ‐ 13 C]glucose was 4.2 ‐ fold decreased in MTX ‐ treated rats, as compared with controls (p<0.01). Lactose ‐ derived [1 ‐ 13 C]glucose absorption correlated strongly with villus length (rho=0.86, p<0.001) and with plasma citrulline level (rho=0.81, p<0.001). MTX treatment decreased jejunal lactase activity (19.5 ‐ fold, p<0.01), immunohistochemical protein ‐ and mRNA expression (39.7 ‐ fold, p<0.01), as compared with controls. Interestingly, MTX treatment did not affect the absorption of [U ‐ 13 C]glucose during the experimental period. Conclusions We conclude that lactose digestion is severely decreased during mucositis while glucose absorption is still intact, when supplied in trace amounts. Plasma citrulline level might be a useful objective, noninvasive marker for lactose maldigestion during mucositis in clinic.
Research Online

Resistance training has been shown to be the most effective exercise mode to induce anabolic adaptations in older men and women. Advances in imaging techniques and histochemistry have increased the ability to detect such changes, confirming the high level of adaptability that remains in aging skeletal muscle. This brief review presents a summary of the resistance-training studies that directly compare chronic anabolic responses to training in older (>60 years) men and women. Sixteen studies are summarized, most of which indicate similar relative anabolic responses between older men and women after resistance training. Relatively small sample sizes in most of the interventions limited their ability to detect significant sex differences and should be considered when interpreting these studies. Future research should incorporate larger sample sizes with multiple measurement time points for anabolic responses.
Synthesis of Poly(aniline-co-benzene)-Based Hypercrosslinked Polymer for Hg(II) Ions Removal from Polluted Water: Kinetic and Thermodynamic Studies

The aim of this work was to investigate the adsorption performance of a highly crosslinked poly(aniline-co-benzene) (PAB) copolymeric network. This hypercrosslinked polymer (HCP) was obtained via the Friedel–Craft reaction in the presence of FeCl3 as an alkylation catalyst. The HCP was characterized using FTIR, SEM, TGA-DTA-DSC thermograms, and BET surface area. The analysis revealed a major mesoporous (an average pore diameter of 4.96 nm) structure, a surface area of 987 m2/g, and adequate chemical and thermal stability, thus supporting its potential as an adsorbent. The PAB HCP capability as an adsorbent for removing mercury ions (Hg2+) from wastewater was examined, and the data obtained were kinetically and thermodynamically modeled. The data were found to fit PFO well (R2 = 0.999), suggesting a physisorption process and a rate-limiting step involving the diffusion process, as proven with IPD and LFD models. The adsorption of Hg2+ on PAB was spontaneous (ΔG° is negative; −4.41 kJ/mol at 298 K), endothermic (ΔH° is positive; 32.39 kJ/mol), and random (ΔS° is positive; 123.48 J/mol·K) at the adsorption interface. The thermodynamic analysis also suggested a physical adsorption mechanism (ΔG° between −20 and 0 kJ/mol). These findings promote the potential application of PAB HCP as an efficient adsorbent for removing Hg2+ ions and other heavy metal ions from polluted environments.
Microbiological Non-Culture-Based Methods for Diagnosing Invasive Pulmonary Aspergillosis in ICU Patients

The diagnosis of invasive pulmonary aspergillosis (IPA) in intensive care unit (ICU) patients is crucial since most clinical signs are not specific to invasive fungal infections. To detect an IPA, different criteria should be considered. Next to host factors and radiological signs, microbiological criteria should be fulfilled. For microbiological diagnostics, different methods are available. Next to the conventional culture-based approaches like staining and culture, non-culture-based methods can increase sensitivity and improve time-to-result. Besides fungal biomarkers, like galactomannan and (1→3)-β-D-glucan as nonspecific tools, molecular-based methods can also offer detection of resistance determinants. The detection of novel biomarkers or targets is promising. In this review, we evaluate and discuss the value of non-culture-based microbiological methods (galactomannan, (1→3)-β-D-glucan, Aspergillus PCR, new biomarker/targets) for diagnosing IPA in ICU patients.
Are digital natives overconfident in their privacy literacy? Discrepancy between self-assessed and actual privacy literacy, and their impacts on privacy protection behavior

Privacy literacy is recognized as a crucial skill for safeguarding personal privacy online. However, self-assessed privacy literacy often diverges from actual literacy, revealing the presence of cognitive biases. The protection motivation theory (PMT) is widely used to explain privacy protection behavior, positing that whether individuals take defensive measures depends on their cognitive evaluation of threats and coping capabilities. However, the role of cognitive biases in this process has been understudied in previous research. This study focuses on Chinese digital natives and examines the differential impacts of subjective and objective privacy literacy on privacy protection behavior, as well as the role of cognitive biases in privacy decision-making. The results show that there is no significant correlation between subjective and objective privacy literacy, and a bias exists. When privacy concern is used as a mediating variable, there are significant differences in the paths through which subjective and objective privacy literacy influence privacy protection behavior. Furthermore, privacy literacy overconfidence moderates the relationship between privacy concern and privacy protection behavior. The findings confirm the influence of cognitive biases in privacy behavior decision-making and extend the PMT. This study also calls for the government to enhance privacy literacy training for digital natives to improve their privacy protection capabilities.