Miracle-dz/UniFAR-FTUs huggingface dataset:
EFFECT OF MANAGERIAL SKILLS ON THE DEVELOPMENT OF DAIRY COOPERATIVES IN KIAMBU COUNTY

Cooperatives societies are part and parcel of an increasing number of people in formal and informal employment the world over. The study sought to examine how managerial skills affect the development of Dairy Cooperatives in Kiambu County. Grounded on the Social Capital and Resource-Based Theory, this study adopted the descriptive research design. In this study, the target population was 59,635 registered Dairy Cooperative members while the sample size was 398 respondents who were picked via stratified random sampling. Data collection involved questionnaires that contained 5-point scale Likert-type statements. Descriptive and inferential statistics were carried out. In this case, tests such as central tendency (mean), frequencies, percentages, and standard deviation in addition to Pearson and regression analysis were utilized. The findings show that managerial skills had a significant influence on the development of dairy cooperatives. This is evidenced by a positive and statistically significant relationship between managerial skills & leadership (r=.156, p<0.001) and the development of dairy cooperatives. These findings lead to the conclusion that the kind of managerial skills and leadership in dairy cooperatives affected their development. The skills deployed by the managerial team would thus determine the level of development in dairy cooperatives. As such, there was a need for dairy Cooperatives to have robust management teams staffed with highly competent and experienced managers. The integrity of the firms should be established and regularly assessed to avoid corruption and mismanagement of the finances. Training is also necessary to enhance the capacity of managers and employees. This could be done in-house or sponsored by institutions of learning.
N-parameter Fibonacci AF C*-Algebras

An n-parameter Fibonacci AF-algebra is determined by a constant incidence matrix K of a special form. The form of the matrix K is defined by a given nparameter Fibonacci sequence. We compute the K-theory of certain Fibonacci AF-algebra, and relate their K-theory to the K-theory of an AF-algebra defined by incidence matrices that are the transpose of K. Abstract Approved: Thesis SupervisorApproved: Thesis Supervisor Title and Department
One vendor and multiple retailers system in vendor managed inventory problem with stochastic demand

In many supply networks, the retailers are reluctant to share information about demand and inventory level to the vendor. This might lead to many difficulties for the vendor in establishing his own order/production plan. Vendor managed inventory (VMI) policy can help to solve that problem. By applying VMI, information sharing is not really a problem for the vendor anymore and this policy have been proven to help reduce total inventory cost as well as improve customer service level in the supply network. In this research, a VMI model for the system with one vendor and multiple retailers will be developed. The main target of the model is to determine the retailer's lot size, the vendor's lot size, the retailer cycle time, and the number of replenishments in a vendor cycle so as to minimise the total system cost. For solution purpose, simulation-optimisation technique using genetic algorithm is employed to help find optimal solutions for the decision variables. Numerical experiments are conducted to show the applicability of the proposed model. Sensitivity analysis is also conducted to examine the effects of some input parameters on the optimal solution.
Postoperative Hormone Replacement Therapy and Survival in Women with Ovarian Cancer

Simple Summary Previous studies have reported that hormone replacement therapy (HRT) after surgery for ovarian cancer has no significant effect on survival. However, a prospective study and a randomized controlled study showed that HRT administration provided survival benefits. Therefore, this study aimed to investigate the impact of postoperative HRT on survival in women with ovarian cancer using the nationwide cohort study. This cohort study was conducted on 1784 women aged ≤60 and diagnosed with ovarian cancer. Overall survival was significantly greater for women that received HRT than for women that did not after a mean follow-up of 5.6 ± 2.9 years (85.3% vs. 76.6%, respectively). Postoperative HRT may be considered a maintenance therapy in women diagnosed with ovarian cancer at ≤60 years of age. Abstract The effect of postoperative hormone replacement therapy (HRT) on survival in women with ovarian cancer remains unclear. This study aimed to investigate the impact of postoperative HRT on survival in women with ovarian cancer using the nationwide cohort study. Women aged ≤60 and diagnosed with ovarian cancer that received primary surgery were followed-up for 5.6 ± 2.9 years. Mean ages of women administered HRT (the HRT group; n = 263) or not administered HRT (the control group; n = 1521) were 41.5 ± 8.5 and 41.0 ± 11.4 years, respectively. After adjustment for covariables, OS was significantly greater in the HRT group (HR 0.618; 95% CI 0.414–0.922; p = 0.018). Kaplan–Meier curve analysis showed OS was significantly higher in the HRT group (85.3% vs. 76.6%; p = 0.016). The ratio of women with HRT to women without HRT increased significantly with time (restricted mean survival times for OS, p < 0.001). In addition, OS was significantly greater for those that received HRT for >5 years than for those that received HRT for ≤0.5 years (HR 0.234; 95% CI 0.059–0.936; p = 0.040). Postoperative HRT improved survival among women with ovarian cancer. The impact of HRT on survival increased with time and treatment duration.
Identifying Endogenous Cellular Proteins Destabilizing the Propagation of Swi1 Prion upon Overproduction

(1) Background: Numerous prions exist in the budding yeast, including [SWI+], the prion form of Swi1—a subunit of the chromatin-remodeling complex SWI/SNF. Despite decades of research, the molecular mechanisms underlying prion initiation and propagation are not fully understood. In this study, we aimed to identify endogenous cellular proteins that destabilize [SWI+]. (2) Methods: We screened the MoBY-ORF 2.0 library for proteins that destabilize [SWI+] upon overproduction. We further explored the effects of the identified candidates against other yeast prions and analyzed their potential prion-curing mechanisms. (3) Results: Eighty-two [SWI+] suppressors were identified, and their effects were shown to be [SWI+]-specific. Interestingly, a few documented [SWI+] suppressors were not among the identified hits. Further experiments indicate that, for some of these [SWI+] suppressors, their overproduction, and thus their prion-curing activities, are regulated by environmental conditions. Bioinformatics analyses show that our identified [SWI+] suppressors are involved in diverse biological functions, with gene ontology term enrichments specifically for transcriptional regulation and translation. Competition for Swi1 monomers between [SWI+] and Swi1 interactors, including the SWI/SNF complex, is a potential prion-curing mechanism. (4) Conclusions: We identified a number of [SWI+]-specific suppressors that highlight unique features of [SWI+] in maintaining its self-perpetuating conformations.
Wireless Powering and Telemetry of Deep-Body Ingestible Bioelectronic Capsule

In this paper, a complete and efficient wireless power transfer (WPT) system, consisting of a full-duplex antenna, a half-wave rectifier and a WPT transmitter (Tx), is designed and validated for deep-body ingestible biomedical capsules. A two-port full-duplex antenna is adopted to perform seamless telemetry and to act as a receiver for WPT Tx without using a multiplexer circuit. The full-duplex implantable antenna operates at 915 MHz (Port 1) and 1300 MHz (Port 2), and occupies compact dimensions of 8×8×0.13 mm3. It maintains high isolation of > 30 dB and peak realized gains of -19.3 dBi at 915 MHz and -17.7 dBi at 1300 MHz. The miniaturization of this antenna is achieved using semi-circular slots on the patch and circular slots on the ground plane while mutual coupling between the ports is reduced by a series of metallic vias. Moreover, a low-profile and efficient rectifier is designed at 1300 MHz and integrated with port 2 of the antenna. The suggested rectifier achieves a radio frequency (RF) to direct current (DC) conversion efficiency of 80.4% at an input power of 1 dBm. Furthermore, a patterned patch antenna is designed that acts as a WPT Tx for the biomedical capsule. After examining the individual performance of the antenna, rectifier and WPT Tx, the overall WPT system is then validated by placing the capsule (rectifier integrated antenna) inside minced pork meat and powered by the WPT Tx. This WPT system is suitable for modern capsule devices due to its features, such as compact size, high gains, high RF-DC conversion efficiency, simultaneous wireless powering and telemetry, and high power transfer efficiency (PTE).
Project Managers’ Competences

This article investigates the individual competences of project managers through a methodological approach that combines a systematic literature review and an analysis of employment opportunities. A comparative analysis of project manager’s competences from the literature and the job advertisements was done. The systematic literature review was the first stage of the research and consisted of adopting methods of bibliometrics and content analysis. The second stage included an analysis of project managers’ competences in the selection process. Thus, five Brazilian recruitment websites and the selection of employees were investigated. Through literature review, it was possible to classify and code competences in four categories (contextual, managerial, technical, and behavioral). The analysis of job advertisements allowed us to identify core competence requirements in the job descriptions and to develop a project manager profile expected by Brazilian organizations.
A Systematic Review and Bayesian Network Meta-Analysis Investigating the Effectiveness of Psychological Short-Term Interventions in Inpatient Palliative Care Settings

This paper reviews and summarises the evidence of short-term psychosocial interventions (up to 12 sessions delivered within less than eight weeks) on anxiety, depression, and emotional distress in palliative patients in inpatient settings. We screened publications from the following five databases, Embase, PubMed, PsycINFO, Web of Science, and CINAHL, from their inception to 10 September 2021. The eligible studies included controls receiving standard palliative care, actively treated controls, and wait-list controls. Nine studies met the eligibility criteria and reported the effects of five psychosocial interventions in a total of N = 543 patients. We followed PRISMA-guidelines for outcome reporting and the Cochrane Risk of Bias Assessment Tool for assessing study quality. This paper used the network meta-analysis to compare multiple treatments by providing greater statistical power and the cross-validation of observed treatment effects, using the R package BUGSnet. Compared to control groups, the following psychosocial interventions in inpatient settings showed to be superior: life review interventions were the best ranked treatment for improving anxiety and distress, while the top ranked treatment for reducing depression was outlook intervention. The short-term psychosocial interventions investigated in this meta-analysis, especially life review intervention, are feasible and can potentially improve anxiety, depression, and distress in palliative inpatients and should therefore be offered in inpatient settings.
Comparative Analysis of Millimeter-Wave Transceivers for 5G Applications

High data rate and low latency are the key parameters of a fifth-generation (5G) mobile network. Millimeter-wave transceiver integrated circuits (IC) are the important building blocks of a remote radio unit that determine the commination distance and consume the significant value of power. Transceiver ICs include beamformer and frequency converter paths. Active phased antenna arrays with a size of up to 256 elements are employed to improve radio channel efficiencies such as data rate and operating range. In this work, a brief review of the 5G beamformer millimeter-wave transceivers ICs implemented in SiGe BiCMOS and CMOS processes is presented. A variety of examples of transceivers IC with a frequency range from 24 to 30 GHz are compared in terms of the Figure of merit (FOM). It’s shown that the CMOS transceiver ICs has a maximum FOM of $1.2 \cdot 10^{18}$Hz/W.
A Consensus-Based Distributed Temperature Priority Control of Air Conditioner Clusters for Voltage Regulation in Distribution Networks

High penetration of Photovoltaic (PV) to the distribution network may bring under-voltage and over-voltage issues, limiting the PV hosting capacity. Air conditioners (AC) in grid-interactive buildings can support voltage regulation by manipulating flexible energy consumption. This paper developed a novel voltage control strategy to regulate the AC clusters’ on/off states for distribution network voltage regulation under high PV penetrations. The novelty lies in the distributed formulation of temperature priority-based on/off control (TPC) of AC clusters and the strategic selection and permutation of demand response technologies, including the real-time optimal demand response resources dispatch, distributed sensing of ACs based on average consensus algorithm, and the local implementation of TPC strategy and trial calculation scheme for flexibility capacity estimation. Finally, the distributed TPC is validated to be effective for system rebalancing with no comfort violations and an acceptable ON/OFF switching frequency. The theoretical and numerical analysis also proves its scalability and robustness to communication delays and link failures. It is then incorporated into a novel hierarchical control framework for smart grid voltage control in a four-bus three-phase test grid, considering the voltage sensitivities to power injections in different locations and phases.
Comparative Analysis of Teaching at Public Universities in Sinaloa during Confinement Due to COVID-19

The COVID-19 pandemic has affected educational institutions around the world. One partial solution for students and teachers to continue the academic process involved the use of software and hardware technologies via the internet. The main objective of this research was to analyze the actions carried out by computer science teachers (and teachers who taught related degrees) in Sinaloa, Mexico, during the COVID-19 confinement period, to determine if the working conditions were different at all educational institutions. Based on quantitative, descriptive–explanatory, correlational, field, and cross-sectional approaches to data collection—a survey was designed and sent to teachers who taught classes in computer science and related careers. The results showed that although teachers felt prepared in designing and implementing virtual courses (90.73%), 68.5% believed that virtual classes were not enough for students (i.e., regarding replacing the training being offered). Likewise, teachers observed that only 27.8% of their students showed real commitment to online classes. In the hypothesis test, a chi-squared value of 3.84 was obtained, with a significance (p-value) of 0.137. There was a probability of error of 13.7%; this is high, considering that the level of significance must be 0.05 (5%) or less. It was concluded that teachers must be permanently trained in the use of new digital technologies; in addition, they must continuously produce academic material and make it available to the educational community. It is necessary for universities to design plans for the regulated use of applications and devices for academic purposes, update study plans and programs, and train teachers and students beyond conventional education.
Effects of “Mindfulness Acceptance Insight Commitment” Training on Flow State and Mental Health of College Swimmers: A Randomized Controlled Experimental Study

This research explores the intervention effect of the mindfulness acceptance insight commitment (MAIC) training program on the mindfulness level, flow state, and mental health of college swimmers. A sample of 47 college swimmers from a regular university was recruited and randomly divided into two groups before the intervention. Independent variables between groups are psychological training mode (MAIC training/no training), and the independent variable within group was time (pre-test, post-test, and continuity test). The dependent variables are mindfulness level, flow state, and mental health (anxiety, depression, training, and competition satisfaction). Results show that after the intervention of MAIC training, the mindfulness level of athletes’ flow state has been significantly improved, whereas anxiety and depression significantly decreased. In addition, the satisfaction with training and competition significantly improved. In the continuous stage after the intervention, the mindfulness level, flow state, and mental health of athletes are still significantly higher than those in the pre-test. The comparison of the post-test and continuity test show no significant differences in the mindfulness level, flow state, depression, and training and competition satisfaction of athletes. Still, the anxiety level shows an upward trend with a significant difference. This study demonstrates that the MAIC mindfulness training program can significantly improve the mindfulness level, flow state, anxiety, depression, and training and competition satisfaction of college swimmers with a good continuity effect. Thus, the athletes’ sports experience can be improved, and good psychological benefits can be attained.
High accuracy transient finite difference and finite element algorithms in computational electromagnetics

The numerical modeling of transient electromagnetic phenomena has received increasing attention in recent years. Efforts have been made in scattering and coupling studies using a broad spectrum of numerical techniques. Much of this time-domain computational research has made use of the Yee time-domain finite difference algorithm. However, Yee's algorithm suffers from numerical dispersion limiting its usefulness on problems with fast rise-time transient excitations on large grids. The research herein investigates time-domain numerical methodologies that have not previously been applied to electromagnetic problems with the goal being to develop techniques that are capable of resolving time-domain electromagnetic pulses with steep wavefronts. The techniques of this research have their origins in computational fluid dynamics where they have been used with success. The focus of the research is on time-domain finite-difference and finite-element solutions in conjunction with the method of flux-corrected transport.
Positioning in 5G and 6G Networks—A Survey

Determining the position of ourselves or our assets has always been important to humans. Technology has helped us, from sextants to outdoor global positioning systems, but real-time indoor positioning has been a challenge. Among the various solutions, network-based positioning became an option with the arrival of 5G mobile networks. The new radio technologies, minimized end-to-end latency, specialized control protocols, and booming computation capacities at the network edge offered the opportunity to leverage the overall capabilities of the 5G network for positioning—indoors and outdoors. This paper provides an overview of network-based positioning, from the basics to advanced, state-of-the-art machine-learning-supported solutions. One of the main contributions is the detailed comparison of machine learning techniques used for network-based positioning. Since new requirements are already in place for 6G networks, our paper makes a leap towards positioning with 6G networks. In order to also highlight the practical side of the topic, application examples from different domains are presented with a special focus on industrial and vehicular scenarios.
-Chains During Development a Receptor-Specific Allelic Exclusion of TCRV

Expression of a single Ag receptor on lymphocytes is maintained via allelic exclusion that generates cells with a clonal receptor repertoire. We show in normal mice and mice expressing functionally rearranged TCR ab transgenes that allelic exclusion at the TCR a locus is not operational in immature thymocytes, whereas most mature T cells express a single TCRV a -chain. TCRV a allelic exclusion in mature thymocytes is regulated through a CD45 tyrosine phosphatase-mediated signal during positive selection. Using functional and genetic systems for selection of immature double TCRV a 1 thymocytes, we show that peptide-speciﬁc ligand recognition provides the signal for allelic exclusion, i.e., mature T cells maintain expression of the ligand-speciﬁc TCRV a -chain, but lose the nonfunctional receptor. Whereas activation of TCRV b -chains or CD3 e leads to receptor internalization, TCRV a ligation promotes retention of the TCR on the cell surface. Although both TCRV a - and TCRV b -chains trigger phosphotyrosine signaling, only the TCRV b -chain mediates membrane recruitment of the GTPase dynamin. These data indicate that TCRV a directed signals for positive selection control allelic exclusion in T cells, and that developmental signals can select for single receptor usage. The Journal of Immunology, 1998, 161: 1718–1727.
LOKI: A Practical Data Poisoning Attack Framework Against Next Item Recommendations

Due to the openness of the online platform, recommendation systems are vulnerable to data poisoning attacks, where malicious samples are injected into the training set of the recommendation system to manipulate its recommendation results. Existing attack approaches are either based on heuristic rules or designed against specific recommendation approaches. The former suffers unsatisfactory performance, while the latter requires strong knowledge of the target system. In this paper, we propose a practical poisoning attack approach named LOKI against blackbox recommendation systems. The proposed LOKI utilizes the reinforcement learning algorithm to train the attack agent, which can be used to generate user behavior samples for data poisoning. In real-world recommendation systems, the cost of retraining recommendation models is high, and the interaction frequency between users and a recommendation system is restricted. Thus, we propose to let the agent interact with a recommender simulator instead of the target recommendation system and leverage the transferability of the generated adversarial samples to poison the target system. We also use the influence function to efficiently estimate the influence of injected samples on recommendation results, without re-training the models. Extensive experiments on multiple datasets against four representative recommendation models show that the proposed LOKI outperformances existing method. We also discuss the characteristics of vulnerable users/items, and evaluate whether anomaly detection methods can be used to mitigate the impact of data poisoning attacks.