Miracle-dz/UniFAR-FTUs huggingface dataset:
University And Personal Factors That Hinder Or Assist Women In Completing A Degree In Engineering

Research on women in engineering confirms the presence of gender barriers that affect their recruitment and retention. These barriers stop some women from choosing engineering as a field of study, and impede some women from completing a degree in engineering. However, there are some young female students who complete their engineering education despite the presence of obstacles throughout their college years. This study addressed the university and personal factors that have hindered, motivated, and assisted women who were graduating with a degree in engineering. By studying and understanding the barriers that hinder women in completing a degree in engineering, as well as the factors that assist and encourage them, we can learn how to break down the barriers and how to facilitate the educational journey of female engineering students.
Dynamics of an Integrated PV/Battery System for EV Charging in a Microgrid

Author(s): Martinez de Novoa, Laura | Advisor(s): Brouwer, Jack | Abstract: Electric Vehicles (EVs) are emerging to play a key role in mitigating fossil fuel reliance and the environmental impacts brought on by the transportation sector. In parallel, it is essential that this growing electricity demand be met mostly with renewable sources. This study, as part of the Irvine Smart Grid Demonstration (ISGD) project, analyzes the effects of a renewable solar photovoltaic (PV) nanogrid — a small-scale, autonomous power system, that ultimately ties into the central electrical distribution grid — for EV charging associated with a controllable battery energy storage system, deployed in a primary circuit on the UCI (University of California, Irvine) Microgrid. The system’s dynamic behavior is characterized for different control algorithms that govern battery dispatch, creating four different energy management strategies.Power quality aspects of EV charging are also investigated, with a focus on harmonic distortion. A robust system design using delta-wye grounded transformers was shown to prevent any excessive harmonic currents from flowing upstream into the microgrid. Additionally, a diversity of EV charging loads promotes favorable harmonic cancellation. A power flow model of the nanogrid was developed in a commercial power flow software (ETAP) and verified against smart meter data, which were used as inputs for the ETAP Real-Time module.Lastly, a linear program was developed for optimally sizing nanogrid assets in the context of minimizing operation costs for the microgrid operator. The combination of an 80 kW PV array and a 95 kWh/45 kW battery energy storage system was shown to be the best option to power 20 Level-2 (7.2 kVA) EV chargers deployed at one of the university campus parking structures.
RELATION OF KINEMATICS AND CONTACT FORCES IN THREE-BODY SYSTEMS WITH A LIMITED NUMBER OF PARTICLES

In many tribological systems, an intermediate layer of a limited number of abrasive particles exist. Thereby, the resulting wear and friction phenomena are desirable in many manufacturing processes, such as lapping or polishing, whereas in machine elements, they are unwanted due to reducing lifetime or performance.For a better understanding of the contact phenomena and the interaction of tribological systems with an intermediate layer of a limited number of particles, fundamental investigations are carried out on a tribometer test rig. For this purpose, two test scenarios are investigated, a) the kinematics and contact forces of single geometrically defined particles such as dodecahedron, icosahedron and hexahedron, and b) the contact forces and surface roughness of a layer of silicon carbide particles of different sizes.The measured ratio of tangential to normal force can be used as an indicator of the dominating kinematics of the particles and of the generated surface roughness, respectively. The higher the force ratio, the higher the tendency to slide for a given particle type and paring of particle and counter body.For one geometrically defined particle the short-time Fourier transform additionally helps to distinguish the state of motion since the excited frequencies during rolling are reduced. For a layer of silicon carbide particles, the velocity and particle size have the strongest influence on the overall motion and the surface roughness produced. Larger particles tend to slide and create more scratches, while smaller particles tend to roll and create indentations in the counter body. Furthermore, for the same particle size, an increase in velocity causes a transition from sliding to rolling, resulting in an increased surface roughness.
Computing at the Belle II experiment

Toward the start of data taking with the beam provided by the SuperKEKB accelerator in 2017, the Belle II, the next-generation flavor factory experiment in Japan, is establishing the computing system based on a distributed computing technologies. The system was examined in the periodical simulation mass production campaigns and was improved according to constructive feedback. In parallel, the data transfer challenges were performed with the transpacific and transatlantic network which plays an essential role in success of the Belle II experiment in the next decade. In this paper, the Belle II computing model and recent activities are presented.
Effects of Instrument Assisted Soft-Tissue Mobilization on Dynamic Balance in Those with Chronic Ankle Instability

Our objective was to examine the effectiveness of IASTM application to the FL on dynamic balance in individuals with CAI. Fifteen individuals (seven females, eight males, age = 26.07 ± 9.18 years, mass = 87.33 ± 24.07 kg, height = 178.83 ± 12.83 cm) with CAI, as determined by the Ankle Instability Instrument (AII) volunteered to participate. Participants completed two counterbalanced sessions (experimental and control), and we recorded measurements at two time points (pre- and post-). The application of IASTM to the FL muscle was carried out using Técnica Gavilán® instruments for 90 s during the intervention, and participants sat for 2 min during the control session. Dynamic balance was assessed using the Y-balance test (YBT). The interaction between session and time for anterior reach was significant (F1,14 = 5.26, p = 0.04, η2 = 0.27). Post-hoc tests revealed farther reach distances at post-test (71.02 ± 9.45 cm) compared to pre-test (66.57 ± 10.87 cm) when IASTM was applied (p = 0.02, Mean Difference = 4.45 cm, CI95 = 0.71–8.19 cm, Cohen’s d = 0.44). The interaction between session and time was not significant for posteromedial (F1,14 = 0.25, p = 0.62, η2 = 0.02, 1 − β = 0.08) or posterolateral reaches (F1,14 = 1.17, p = 0.30, η2 = 0.08, 1 − β = 0.17). The application of IASTM to the FL improved anterior reach of the YBT, but not posterolateral or posteromedial reaches in individuals with CAI. However, the 4.45 cm increase in anterior reach could have clinical implications for improved function.
Prediction of the Yield Performance and Failure Mode of RC Columns under Cyclic-Load by PSO-BP Neural Network

The yield performances and failure mode of reinforced concrete (RC) columns, which are critical structural performances to the design and research of engineering structures, have a significant impact on the dynamic response, the performance level, and the design of seismic ductility. The traditional empirical theoretical method used to predict the yield performances and failure mode leads to large dispersions in most cases. To better estimate the yield performances and failure mode of RC columns, this paper developed a novel neural network method. Empirical theoretical models are used to determine the input parameters of the neural network by analyzing the factors that affect the yield performance and failure mode of RC columns, and the rationality of these parameters is verified by sensitivity analysis. The back-propagation (BP) neural network method was adopted. The influence of the number of hidden neurons was studied to improve the model accuracy. Comparative analysis revealed that the prediction results of the neural network are in good agreement with the experimental results and are more accurate than other traditional empirical theoretical models. The initial parameters were optimized using particle swarm optimization (PSO), which has been proven to be superior to the genetic algorithm (GA) and sparrow search algorithm (SSA) optimization methods in terms of effectiveness and computation time. The high generalization ability of the prediction model was calibrated using the test and validation sets and another eight additional sets of experimental data. The proposed method provides a new way to predict the structural performance under seismic actions when experimental data are insufficient.
Local abundances of terrestrial mammal and bird species around indigenous villages in Suriname

Hunting is an important threat to tropical wildlife, yet many people are dependent on forest fauna for protein provisioning. We analyzed abundances of terrestrial mammal and bird species around four indigenous villages in the south of Suriname, using camera trap data and the Royle–Nichols abundance model. We hypothesized that hunting pressure increases with decreasing distance to a village and with increasing village size (expressed as cropland area). We detected 24 animal species in all villages combined, including several rare species. For 11 of the 24 species, we were able to examine if and how distance to a village and village size related to local abundances and found a positive effect of distance to village on local abundances in five species, and a negative effect of village size in one species. Because villages, and thus hunting, affect local abundances of terrestrial bird and mammal species in our study, we recommend monitoring forest fauna in areas where people are highly dependent on animals for food provisioning.
Kajian Kebutuhan Air dan Produktivitas Air Padi Sawah dengan Sistem Pemberian Air Secara SRI dan Konvensional Menggunakan Irigasi Pipa

Limited water availability for agricultural land may cause decrease in rice production. The increase of crop production currently become a top priority in agricultural development. Productivity can be assessed through a subsystem of soil, water, and land patterns to use in certain periods. The applications of pipe irrigation with the combination of System of Rice Intensification (SRI) was capable to use water efficiently. Therefore, research concerning the calculation of water productivity of paddy rice which uses input pipe irrigation with conventional water supply system and SRI system is important to be conducted. The research steps were direct observation in the field, measurement of evapotranspiration, percolation, net field requirements and calculation of water productivity. The results showed that the production of rice was higher in water delivery system of SRI. Water productivity of paddy with SRI system also higher, where the water needs with a combination of pipe irrigation and water delivery systems in SRI were the best treatment. Water productivity in conventional rice fields was 0.82 kg/m3 and SRI 1.12 kg/m3. The combination of pipe irrigation and SRI systems showed high water productivity and efficient use of water.
Above‐ and belowground drivers of intraspecific trait variability across subcontinental gradients for five ubiquitous forest plants in North America

Intraspecific trait variability (ITV) provides the material for species' adaptation to environmental changes. To advance our understanding of how ITV can contribute to species' adaptation to a wide range of environmental conditions, we studied five widespread understorey forest species exposed to both continental‐scale climate gradients, and local soil and disturbance gradients. We investigated the environmental drivers of between‐site leaf and root trait variation, and tested whether higher between‐site ITV was associated with increased trait sensitivity to environmental variation (i.e. environmental fit). We measured morphological (specific leaf area: SLA, specific root length: SRL) and chemical traits (Leaf and Root N, P, K, Mg, Ca) of five forest understorey vascular plant species at 78 sites across Canada. A total of 261 species‐by‐site combinations spanning ~4300 km were sampled, capturing important abiotic and biotic environmental gradients (neighbourhood composition, canopy structure, soil conditions, climate). We used multivariate and univariate linear mixed models to identify drivers of ITV and test the association of between‐site ITV with environmental fit. Between‐site ITV of leaf traits was primarily driven by canopy structure and climate. Comparatively, environmental drivers explained only a small proportion of variability in root traits: these relationships were trait specific and included soil conditions (Root P), canopy structure (Root N) and neighbourhood composition (SRL, Root K). Between‐site ITV was associated with increased environmental fit only for a minority of traits, primarily in response to climate (SLA, Leaf N, SRL). Synthesis. By studying how ITV is structured along environmental gradients among species adapted to a wide range of conditions, we can begin to understand how individual species might respond to environmental change. Our results show that generalisable trait–environment relationships occur primarily aboveground, and only accounted for a small proportion of variability. For our group of species with broad ecological niches, variability in traits was only rarely associated with higher environmental fit, and primarily along climatic gradients. These results point to promising research avenues on the various ways in which trait variation can affect species' performance along different environmental gradients.
Event-VPR: End-to-End Weakly Supervised Deep Network Architecture for Visual Place Recognition Using Event-Based Vision Sensor

Traditional visual place recognition (VPR) methods generally use frame-based cameras, which will easily fail due to rapid illumination changes or fast motion. To overcome this, we propose an end-to-end VPR network using event cameras, which can achieve good recognition performance in challenging environments (e.g., large-scale driving scenes). The key idea of the proposed algorithm is first to characterize the event streams with the EST voxel grid representation, then extract features using a deep residual network, and, finally, aggregate features using an improved VLAD network to realize end-to-end VPR using event streams. To verify the effectiveness of the proposed algorithm, on the event-based driving datasets (MVSEC, DDD17, and Brisbane-Event-VPR) and the synthetic event datasets (Oxford RobotCar and CARLA), we analyze the performance of our proposed method on large-scale driving sequences, including cross-weather, cross-season, and illumination changing scenes, and then, we compare the proposed method with the state-of-the-art event-based VPR method (Ensemble-Event-VPR) to prove its advantages. Experimental results show that the performance of the proposed method is better than that of the event-based ensemble scheme in challenging scenarios. To the best of our knowledge, for the VPR task, this is the first end-to-end weakly supervised deep network architecture that directly processes event stream data.
Effects of Tick-Control Interventions on Tick Abundance, Human Encounters with Ticks, and Incidence of Tickborne Diseases in Residential Neighborhoods, New York, USA

Tickborne diseases (TBDs) such as Lyme disease result in ≈500,000 diagnoses annually in the United States. Various methods can reduce the abundance of ticks at small spatial scales, but whether these methods lower incidence of TBDs is poorly understood. We conducted a randomized, replicated, fully crossed, placebo-controlled, masked experiment to test whether 2 environmentally safe interventions, the Tick Control System (TCS) and Met52 fungal spray, used separately or together, affected risk for and incidence of TBDs in humans and pets in 24 residential neighborhoods. All participating properties in a neighborhood received the same treatment. TCS was associated with fewer questing ticks and fewer ticks feeding on rodents. The interventions did not result in a significant difference in incidence of human TBDs but did significantly reduce incidence in pets. Our study is consistent with previous evidence suggesting that reducing tick abundance in residential areas might not reduce incidence of TBDs in humans.
DNA barcoding for biodiversity assessment: Croatian stoneflies (Insecta: Plecoptera)

Background The hemi-metabolous aquatic order Plecoptera (stoneflies) constitutes an indispensable part of terrestrial and aquatic food webs due to their specific life cycle and habitat requirements. Stoneflies are considered one of the most sensitive groups to environmental changes in freshwater ecosystems and anthropogenic changes have caused range contraction of many species. Given the critical threat to stoneflies, the study of their distribution, morphological variability and genetic diversity should be one of the priorities in conservation biology. However, some aspects about stoneflies, especially a fully resolved phylogeny and their patterns of distribution are not well known. A study that includes comprehensive field research and combines morphological and molecular identification of stoneflies has not been conducted in Croatia so far. Thus, the major aim of this study was to regenerate a comprehensive and taxonomically well-curated DNA barcode database for Croatian stoneflies, to highlight the morphological variability obtained for several species and to elucidate results in light of recent taxonomy. Methods A morphological examination of adult specimens was made using basic characteristics for distinguishing species: terminalia in males and females, head and pronotum patterns, penial morphology, and egg structures. DNA barcoding was applied to many specimens to help circumscribe known species, identify cryptic or yet undescribed species, and to construct a preliminary phylogeny for Croatian stoneflies. Results Sequences (658 bp in length) of 74 morphospecies from all families present in Croatia were recovered from 87% of the analysed specimens (355 of 410), with one partial sequence of 605 bp in length for Capnopsis schilleri balcanica Zwick, 1984. A total of 84% morphological species could be unambiguously identified using COI sequences. Species delineation methods confirmed the existence of five deeply divergent genetic lineages, with monophyletic origin, which also differ morphologically from their congeners and represent distinct entities. BIN (Barcode Index Number) assignment and species delineation methods clustered COI sequences into different numbers of operational taxonomic units (OTUs). ASAP delimited 76 putative species and achieved a maximum match score with morphology (97%). ABGD resulted in 62 and mPTP in 61 OTUs, indicating a more conservative approach. Most BINs were congruent with traditionally recognized species. Deep intraspecific genetic divergences in some clades highlighted the need for taxonomic revision in several species-complexes and species-groups. Research has yielded the first molecular characterization of nine species, with most having restricted distributions and confirmed the existence of several species which had been declared extinct regionally.
Predictive Value of Plasma Atherogenic Index for Microalbuminuria in Newly Diagnosed Patients with Type 2 Diabetes Mellitus

Purpose This study aims to explore the predictive value of plasma atherogenic index of plasma (AIP) for microalbuminuria (MAU) in newly diagnosed patients with type 2 diabetes mellitus (T2DM). Methods This study was a retrospective study, which included 335 newly diagnosed T2DM patients. They were divided into microalbuminuria group (group A, n = 105 cases) and no microalbuminuria group (group B, n = 230 cases) according to whether microalbuminuria occurred. General information and laboratory examination indexes of patients were collected, and AIP was calculated. Multivariate logistic regression analysis was used to analyze the independent risk factors of microalbuminuria in T2DM patients, and receiver operating characteristic curve (ROC) was established to evaluate the predictive value of AIP on MAU of newly diagnosed T2DM patients. Results According to general data analysis, AIP level in group A was significantly higher than that in group B (P < 0.05). Multivariate logistic regression analysis showed that AIP was an independent risk factor for microalbuminuria (P < 0.05). The receiver operating characteristic curve showed that the area under the curve (AUC) of AIP was 0.772 (P < 0.05), which had a good predictive value for the occurrence of MAU in newly diagnosed T2DM patients. The waist-hip ratio, triglyceride, high-density lipoprotein cholesterol, fasting blood glucose, glycosylated hemoglobin and AIP were used to make a joint model, and the AUC was 0.841 (P < 0.05), which had a better predictive value for the occurrence of MAU. Conclusions AIP is an independent risk factor and could predict the occurrence of MAU in newly diagnosed T2DM patients. AIP provides clinicians a reliable basis to quickly identify high-risk patients and formulate appropriate treatment strategies.
How to Conduct Surveys: A Step-by-Step Guide. Sixth Edition.

Chapter 1. Conducting Surveys: Everyone Is Doing It Chapter 2. The Survey Form: Questions, Scales, and Appearance Chapter 3. Getting It Together: Some Practical Concerns Chapter 4. Sampling Chapter 5. Survey Design: Environmental Control Chapter 6: Analyzing and Organizing Data from Surveys Chapter 7: Presenting the Survey Results
COVID-19 Infection among Elite Football Players: A Nationwide Prospective Cohort Study

Little is known about the risk of COVID-19 infection among footballers. We aimed to investigate the incidence and characteristics of COVID-19 infection among footballers. In total, 480 football players of Super League Greece and 420 staff members participated in a prospective cohort study, which took place from May 2020 to May 2021. Nasopharyngeal swabs were collected from footballers and staff members weekly. All samples (n = 43,975) collected were tested using the reverse transcriptase polymerase chain reaction (RT-PCR) test for the detection of “SARS-CoV-2”. In total, 190 positive cases (130 among professional football players and 60 among staff) were recorded. Out of the 190 cases that turned positive, 64 (34%) cases were considered as symptomatic, and 126 (66%) cases were asymptomatic. The incidence rate of a positive test result for footballers was 0.57% (confidence interval (CI) 0.48–0.68%) and for staff members it was 0.27% (CI 0.20%, 0.34%), respectively. Footballers recorded a twofold increased risk of COVID-19 infection in comparison to staff members (relative risk = 2.16; 95% CI = 1.59–2.93; p-value < 0.001). No significant transmission events were observed during the follow-up period. We found a low incidence of COVID-19 infection among professional footballers over a long follow-up period. Furthermore, the implementation of a weekly diagnostic testing (RT-PCR) was critical to break the transmission chain of COVID-19, especially among asymptomatic football players and staff members.
Selection diversity receivers in Weibull fading: outage

Novel expressions for the probability and the cumulative density function of the signal-to-noise ratio (SNR) at the output of an L-branch selection combining receiver, operating in Weibull fading, are derived. Capitalising on these expressions, the outage probability and the average output SNR are obtained in closed-form.