Miracle-dz/UniFAR-FTUs huggingface dataset:
Smart Network Maintenance in an Edge Cloud Computing Environment: An Adaptive Model Compression Algorithm Based on Model Pruning and Model Clustering

With the rapid development of communication networks, there are more stringent requirements for maintenance management. To carry out smart network maintenance automatically and effectively, this paper uses wearable devices, robots, and Unmanned Aerial Vehicles (UAVs) to collect on-site video data and detect defects in real-time. However, the deep learning models deployed in these devices should have fewer model parameters and less storage space. Therefore, we propose a model compression algorithm based on model pruning and model clustering in smart network maintenance. First, model pruning combines channel pruning and layer pruning and uses deep reinforcement learning to determine the pruning ratio of each layer automatically. This method can effectively compress the width and depth of the model while maintaining the accuracy of the model. Second, although the pruning operation greatly reduces the redundancy of the number of weight parameters, the number of bits of floating-point weights is still redundant. We propose an adaptive model clustering method to cluster the remaining nonzero parameter weights and compress the model. It combines advanced balanced iterative reducing and clustering using hierarchies (BIRCH) clustering and K-meansII clustering and takes the result k value of BIRCH clustering as the input of K-meansII. It can avoid limitations of prior knowledge and reduce clustering time. Simulation results show that the target detection model can reduce parameter redundancy, save storage space, and simplify calculation using the proposed algorithm. In addition, it can be better applied in the smart network maintenance environment.
Drying-off practices on Swiss dairy farms: Status quo and adoption potential of integrating incomplete milking.

Drying-off practices to reduce milk production before dry-off are gaining attention because high milk yields at dry-off are becoming more common and increase the risk to cow health and welfare during the dry period. Incomplete milking for the last days before dry-off is one approach for reducing milk production. We conducted an online survey to determine the currently used drying-off practices on Swiss dairy farms and to identify the adoption potential of integrating incomplete milking before dry-off. In March 2021, the online survey was sent to a representative sample of 1,974 Swiss dairy farmers. A total of 518 completed questionnaires were analyzed. The mean number of dairy cows per farm was 39 (range: 11-140 cows). Thirty-five percent of cows produced considerable quantities of milk (>15 kg/d) at dry-off, and milk yield at dry-off increased with increasing annual milk yield. Abrupt dry-off was applied on 45% of the farms. The participants reported observing behavioral changes of cows such as increased vocalizations and decreased lying time associated with dry-off. Selective dry cow therapy was applied on 74% of the farms, and 44% of the participants indicated the use of antibiotics at dry-off as being "rather often," "often," or "always. " Correlation analysis revealed that with increasing annual milk yields, the frequency of observed behavioral changes and antibiotic use at dry-off increased as well. Therefore, drying-off approaches that reduce milk production while supporting cow welfare are needed. We found that farmers showed an interest in testing the presented drying-off approach of incomplete milking. In addition, the farmers indicated that they would be more willing to test incomplete milking before dry-off if it became available for automated use in milking parlors or robots. Uncertainties regarding udder health appeared to be the main barrier for the adoption potential of this approach.
Cognitive and Metacognitive Strategy Use in Reading: The Case of Iranian EFL Students’ Test Performance

Individual characteristics and differences, namely strategy-use behavior have been gaining much attention among researchers due to influences that they may have on test takers’ performance on reading tests. From a language testing perspective, however, further experimental studies are needed in this regard. This study investigated the relationship between test-takers’ strategy-use behavior and their reading test performance. Five hundred and twenty Iranian English as a Foreign Language (EFL) learners (both male and female) participated in this study. They were assigned to high- and the low-reading ability groups based on their scores on a teacher-made reading comprehension test. They were also required to sit for a teacher-made TOEFL-based reading comprehension test and answer the adapted version of Phakiti’s (2008) Cognitive and Metacognitive Strategy Questionnaire with 30 items immediately after the test. The reliability of both instruments was approved through Cronbach alpha and the validity was assured through content and construct evidences of validity. Confirmatory Factor Analysis (CFA) on the questionnaire indicated that three factors were identified as cognitive (comprehension, retrieval, memory) and three as metacognitive strategies (planning, monitoring, evaluation) for both ability groups. Moreover, Structural Equation Modeling (SEM) analysis showed that metacognitive strategies had a regulating function on cognitive strategies in both groups. Furthermore, the results showed that in the high ability group Comprehension (COM) and Memory (MEM) strategies and in the low-ability group, Retrieval (RET) strategies were the best predictors of reading test performance. Finally, some implications and suggestions for further research are presented.
The asymptotic behaviour of the weights and the degrees in an N-interactions random graph model

A random graph evolution based on the interactions of N vertices is studied. During the evolution both the preferential attachment method and the uniform choice of vertices are allowed. The weight of a vertex means the number of its interactions. The asymptotic behaviour of the weight and the degree of a fixed vertex, moreover the limit of the maximal weight and the maximal degree are described. The proofs are based on martingale methods.
Effect of Moods on Perception of Organizational Justice

Objectives This study aimed to identify the effect of mood on perceptions of organizational justice (distributional, procedural, interpersonal, and informational), expecting that those with pleasant moods tend to perceive a work situation as more fair, and those with unpleasant moods are more likely to see work events as less fair. Methods The sample consisted of 180 Kuwaiti employees divided evenly among the three experimental groups (pleasant, unpleasant, and neutral groups). Each group watched either positive, negative, or neutral film. The study used the Organizational Justice Measure and the Brief Mood Introspection Survey. Results The repeated measures ANCOVA for the effects of mood on the justice measure, after controlling for pre-mood and the pre-justice scores, showed a significant difference among the three mood groups. The pleasant group had a higher justice mean than the unpleasant and neutral groups. However, no significant difference was found between the unpleasant and neutral groups. Also, there was no significant interaction between the justice type (distributional, procedural, interpersonal, and informational) and mood group (pleasant, unpleasant, and neutral). Conclusions A pleasant mood may have a stronger effect on justice perception than an unpleasant mood. Suggesting that mood affects justice in a consistent way regardless of justice type. Justice perceptions are inherently subjective and are receptive to the effects of internal states. And that mood states that have no logical relationship with the justice of the situation may serve as inputs in the justice judgment process, highlighting the subjective quality of justice perception.
The Factors Influencing Older Adults’ Decisions Surrounding Adoption of Technology: Quantitative Experimental Study

Background The rapid diffusion of technology apps may support older adults’ independence and improve the quality of their lives. Models for predicting technology acceptance in older adults are sparse, based on broad questions related to general technology acceptance, and largely not grounded in theories of aging. Objective This study aimed to use a mixed methods approach involving 5 technologies to comprehensively assess the causal relationships among factors that influence older adults’ willingness to adopt the technologies. Methods In total, 187 men and women aged 65 to 92 years participated in the study. Participants were given presentations on 5 different technologies spanning domains that included transportation, leisure, health, and new learning and provided ratings of each technology on various measures hypothesized to influence adoption. They were also administered other instruments to collect data on their actual and self-assessed cognitive abilities, rates of discounting of the technologies with respect to willingness to invest time to attain higher skills in the technologies, general technology experience, and attitudes toward technology. We used the machine learning technique of k-fold cross-validated regressions to select variables that predicted participants’ willingness to adopt the technologies. Results Willingness to adopt technologies was most impacted by 3 variables: perceived value of the technologies (β=.54), perceived improvement in quality of life attainable from the technologies (β=.24), and confidence in being able to use the technologies (β=.15). These variables, in turn, were mostly facilitated or inhibited by the perceived effort required to learn to use the technologies, a positive attitude toward technology as reflected in the optimism component of the technology readiness scale, the degree to which technologies were discounted, and the perceived help needed to learn to use the technologies. Conclusions Our findings demonstrate that participants’ willingness to adopt technologies is mainly determined by perceptions of 3 aspects of the technologies; these aspects possibly mediate many relationships with willingness to adopt. We discuss the implications of these findings for the design and marketing of technology products for older consumers.
Antibiotics Resistance Pattern of Food-Borne Bacteria Isolated from Ice Cream in Bangladesh: A Multidisciplinary Study

Ice cream is one of the most popular food items consumed during the summer season in Bangladesh by all ages but mostly school-going students. Due to the ingredients and handling process of ice cream, it acts as a good shelter for pathogenic and nonpathogenic microorganisms. Therefore, we aimed to investigate the microbial count, prevalence, isolate and characterize multidrug-resistant bacteria in ice cream samples collected from nearby shops of schools in Tangail district, Bangladesh. Ice-cream consumer and nonconsumer students were selected by providing questionnaires. Total viable count (TVC) and total coliform count (TCC) were determined by pour plate methods, where conventional methods were performed for bacterial identification. The Kirby-Bauer disk diffusion method was used to determine the antimicrobial susceptibility of bacterial isolates. Kado and Liu method, with some modifications, was used to extract plasmid from the isolated bacteria and visualized through gel electrophoresis. The demographic characteristics showed that the degree of symptoms regarding microorganisms mediated disorders and rate of antibiotics intake in ice cream consumers were significantly higher than the nonconsumers. The range of TVC and TCC in the ice cream samples was found 0–9.9 × 109 CFU/ml and 0–900 CFU/ml, respectively. Interestingly, 93.75% of the total ice cream samples also showed fungal positive. A total of 12 different bacterial species were identified, including Proteus spp, E. coli, V.cholera, Pseudomonas spp, Shigella spp, Klebsiella spp, Aeromonas spp, V. Parahemolyticus. Salmonella paratyphi, Citrobacterspp, Plesiomonasspp, and Staphylococcus aureus. The antimicrobial susceptibility assay showed the multiple resistance frequency of these isolates to different antimicrobial drugs. All individual isolates were screened for plasmid DNA, and we found that seven strains harbored a single or more than two plasmids sized approximately between 1.9 and 140 MDa, indicating a possible connection between resistance phenotype pattern and genotype.
Laser emission from low-loss cladding waveguides in Pr:YLF by femtosecond laser helical inscription

Depressed cladding waveguides are fabricated in Pr:LiYF 4 (YLF) crystal by femtosecond laser inscription following a helical scheme. With the optimized parameters, the propagation loss of the waveguide is around 0.12 dB/cm for multimode guiding. Under optical pumping with InGaN laser diodes at 444 nm, efficient waveguide lasers in the orange around 604 nm ( π -polarized) are achieved with minimum lasing threshold of 119.8 mW, maximum slope efficiency of 16.6%, and maximum output power of 120.6 mW. Benefiting from their optimized performances, the waveguides produced in this work are promising for applications as compact orange laser sources.
Algebraic K-Theory and Its Applications

Algebraic K-Theory plays an important role in many areas of modern mathematics: most notably algebraic topology, number theory, and algebraic geometry, but even including operator theory. The broad range of these topics has tended to give the subject an aura of inapproachability. This book, based on a course at the University of Maryland in the fall of 1990, is intended to enable graduate students or mathematicians working in other areas not only to learn the basics of algebraic K-Theory, but also to get a feel for its many applications. The required prerequisites are only the standard one-year graduate algebra course and the standard introductory graduate course on algebraic and geometric topology. Many topics from algebraic topology, homological algebra, and algebraic number theory are developed as needed. The final chapter gives a concise introduction to cyclic homology and its interrelationship with K-Theory.
Synthesis and Application of Positively Charged and Magnetically Separable Magnetite/Silica-Ammonium as an Effective Platinum(IV) Adsorbent

Platinum is a valuable metal that is widely used in industry, electronics, and catalysts. The use of Platinum has a significant impact on the production of waste, necessitating effective metal recovery. This study investigated Platinum (IV) recovery from wastewater using a positively charged and magnetically separable Magnetite/Silica-Ammonium (MSA). The MSA was prepared by co-precipitation procedure of silica-decorated quaternary ammonium in the Fe3+/Fe2+ solution. The characterization result of the MSA by FT-IR, X-ray diffraction (XRD), SEM-EDX, and Vibration Sample Magnetometer (VSM) demonstrated the success of MSA synthesis. The application of MSA to the Pt (IV) solution occurred at pH optimum 6,0 with the easy and quick retraction of MSA-loaded Pt (IV) by 29.3 emu/g magnetic strength of an external magnet. The adsorption isotherm study followed the Freundlich model (R2=0.9895) with the KF=2.57×10-2 mol/g. The monolayer capacity by Langmuir showed the remarkable performance of 139.09 mg/g adsorption capacity through the ion exchange interaction mechanism based on the Dubinin-Radushkevich energy (ED-R=8,3 kJ/mol). The kinetics study was fitted well to the Pseudo-second-order model indicated the fast adsorption of Pt (IV) into the MSA surface.
Economic Evaluations of Magnetic Resonance Image-Guided Radiotherapy (MRIgRT): A Systematic Review

Objectives: This review systematically summarizes the evidence on the economic impact of magnetic resonance image-guided RT (MRIgRT). Methods: We systematically searched INAHTA, MEDLINE, and Scopus up to March 2022 to retrieve health economic studies. Relevant data were extracted on study type, model inputs, modeling methods and economic results. Results: Five studies were included. Two studies performed a full economic assessment to compare the cost-effectiveness of MRIgRT with other forms of image-guided radiation therapy. One study performed a cost minimization analysis and two studies performed an activity-based costing, all comparing MRIgRT with X-ray computed tomography image-guided radiation therapy (CTIgRT). Prostate cancer was the target condition in four studies and hepatocellular carcinoma in one. Considering the studies with a full economic assessment, MR-guided stereotactic body radiation therapy was found to be cost effective with respect to CTIgRT or conventional or moderate hypofractionated RT, even with a low reduction in toxicity. Conversely, a greater reduction in toxicity is required to compete with extreme hypofractionated RT without MR guidance. Conclusions: This review highlights the great potential of MRIgRT but also the need for further evidence, especially for late toxicity, whose reduction is expected to be the real added value of this technology.
Valorization of Brewery Waste through Polyhydroxyalkanoates Production Supported by a Metabolic Specialized Microbiome

Simple Summary Raw brewers’ spent grain, a by-product of beer production, is produced at a large scale and is usually used as animal feed or is landfilled. However, its composition shows that this feedstock has the potential for other applications, such as bioplastics production (e.g., polyhydroxyalkanoates). In this way, the aim of this work was to assess the use of raw brewers’ spent grain for polyhydroxyalkanoates production, adding new value to this feedstock. The results confirm the potential of raw brewers’ spent grain to produce polyhydroxyalkanoates, as the population was enriched in the microorganisms able to accumulate these biopolymers. These results will contribute to society’s knowledge and competence via the development of a treatment process for brewery waste of both environmental (productive waste treatment) and economic interest (production of biopolymers), which will certainly attract its application to the brewery industry worldwide. Abstract Raw brewers’ spent grain (BSG), a by-product of beer production and produced at a large scale, presents a composition that has been shown to have potential as feedstock for several biological processes, such as polyhydroxyalkanoates (PHAs) production. Although the high interest in the PHA production from waste, the bioconversion of BSG into PHA using microbial mixed cultures (MMC) has not yet been explored. This study explored the feasibility to produce PHA from BSG through the enrichment of a mixed microbial culture in PHA-storing organisms. The increase in organic loading rate (OLR) was shown to have only a slight influence on the process performance, although a high selectivity in PHA-storing microorganisms accumulation was reached. The culture was enriched on various PHA-storing microorganisms, such as bacteria belonging to the Meganema, Carnobacterium, Leucobacter, and Paracocccus genera. The enrichment process led to specialization of the microbiome, but the high diversity in PHA-storing microorganisms could have contributed to the process stability and efficiency, allowing for achieving a maximum PHA content of 35.2 ± 5.5 wt. % (VSS basis) and a yield of 0.61 ± 0.09 CmmolPHA/CmmolVFA in the accumulation assays. Overall, the production of PHA from fermented BSG is a feasible process confirming the valorization potential of the feedstock through the production of added-value products.
Allosteric Integrase Inhibitor Influences on HIV-1 Integration and Roles of LEDGF/p75 and HDGFL2 Host Factors

Allosteric integrase (IN) inhibitors (ALLINIs), which are promising preclinical compounds that engage the lens epithelium-derived growth factor (LEDGF)/p75 binding site on IN, can inhibit different aspects of human immunodeficiency virus 1 (HIV-1) replication. During the late phase of replication, ALLINIs induce aberrant IN hyper-multimerization, the consequences of which disrupt IN binding to genomic RNA and virus particle morphogenesis. During the early phase of infection, ALLINIs can suppress HIV-1 integration into host genes, which is also observed in LEDGF/p75-depelted cells. Despite this similarity, the roles of LEDGF/p75 and its paralog hepatoma-derived growth factor like 2 (HDGFL2) in ALLINI-mediated integration retargeting are untested. Herein, we mapped integration sites in cells knocked out for LEDGF/p75, HDGFL2, or both factors, which revealed that these two proteins in large part account for ALLINI-mediated integration retargeting during the early phase of infection. We also determined that ALLINI-treated viruses are defective during the subsequent round of infection for integration into genes associated with speckle-associated domains, which are naturally highly targeted for HIV-1 integration. Class II IN mutant viruses with alterations distal from the LEDGF/p75 binding site moreover shared this integration retargeting phenotype. Altogether, our findings help to inform the molecular bases and consequences of ALLINI action.
The Impact Of Pakserv On Customer Satisfaction And Loyalty: Study Case Grabfood Indonesia

Every business needs an excellent service quality to make customer satisfied and loyal. However, the terms of satisfaction and loyal still become the problems that should be tackled like GrabFood in Banda Aceh which should cope the food service delivery delay to the customer. This research uses PAKSERV model to give the solution for improving the service quality, the population in this research is the users of grabfood Banda Aceh and the sample 204 users with purposive sampling. This research uses SEM-PLS with the help of AMOS and SPSS software which found that Tangibility has a significant and positive impact on customer satisfaction along with other variables such as Assurance, Personalization, Sincerity, and Formality. On the other hand, Reliability in this model has not a significant impact to the customer satisfaction even-though it has a positive impact. Thus, it could be interpreted that, GrabFood Banda Aceh should pay more attention to the Tangibility, Assurance, Personalization, Sincerity and Satisfaction.
Relationship between Joint Stiffness, Limb Stiffness and Whole–Body Center of Mass Mechanical Work across Running Speeds

The lower–extremity system acts like a spring in the running stance phase. Vertical stiffness (Kvert) and leg stiffness (Kleg) reflect the whole–body center of mass (COM) and leg–spring system loading and response in running, while joint stiffness (Kjoint) represents joint–level dynamic loading and response. This study aimed to investigate whether Kjoint is associated with Kvert and Kleg across different running speeds. Twenty healthy subjects were recruited into a treadmill running study (1.8 to 3.8 m/s, with 0.4 m/s intervals). We found that Kjoint accounted for 38.4% of the variance in Kvert (p = 0.046) and 42.4% of the variance in Kleg (p = 0.028) at 1.8 m/s; Kjoint also accounted for 49.8% of the variance in Kvert (p = 0.014) and 79.3% of the variance in Kleg (p < 0.0001) at 2.2 m/s. Kknee had the strongest unique association with Kvert and Kleg at 1.8 and 2.2 m/s. Kjoint was associated with Kleg at a wider range of speeds. These findings built a connection between joint stiffness and limb stiffness within a certain range of running speeds. Kknee may need to be considered as an important factor in future limb stiffness optimization and general running performance enhancement.