Miracle-dz/UniFAR-FTUs huggingface dataset:
Adoption of Pressure Irrigation Systems and Scientific Irrigation Scheduling Practices by U.S. Farmers: An Application of Multilevel Models

Water scarcity is becoming more acute, necessitating better understanding of farmer adoption of improved irrigation technologies. Using data from the national 2013 Farm and Ranch Irrigation Survey, this study employs a multilevel modeling approach to analyze irrigation decisions. The variation in pressure irrigation adoption is mainly accounted for by state-level factors, while adoption of scientific scheduling practices is more associated with farm-level factors. Adoption increases with larger acreage, groundwater use, information sources other than neighbors, and recent higher temperatures. Adoption is negatively associated with on-farm surface water and barriers related to increased costs, management time, and time horizon.
Dynamic Allocation of Computing and Communication Resources in Multi-Access Edge Computing for Mobile Users

The Multi-Access Edge Computing (MEC) constitutes computing over virtualized resources distributed at the edge of mobile network. For mobile users, an optimal allocation of communication and computing resources changes over time and space, and the resource allocation becomes a complex problem. Moreover, for delay constrained applications, the resource allocation to mobile users cannot be solved by approaches designed for static users, as a solution would not be obtained within a desired time. Thus, in this paper, we propose a low-complexity computing and communication resource allocation for offloading of real-time computing tasks generated with a high arrival rate by the mobile users. We exploit probabilistic modeling of the users’ movement to pre-allocate the computing resources at base stations and to select suitable communication paths between the users and the base station with the pre-allocated computing resources. The simulations show that the proposed algorithm keeps the offloading delay below 100 ms for the small tasks even with the arrival rate of five tasks per second per user, while the state-of-the-art algorithms can handle only up to 0.5 tasks per second per user. Thus, the proposal enables an exploitation of the MEC for various real-time applications even if the users are moving.
Brain Cancer Tumor Classification from Motion-Corrected MRI Images Using Convolutional Neural Network

: Detection of brain tumors in MRI images is the first step in brain cancer diagnosis. The accuracy of the diagnosis depends highly on the exper-tise of radiologists. Therefore, automated diagnosis of brain cancer from MRI is receiving a large amount of attention. Also, MRI tumor detection is usually followed by a biopsy (an invasive procedure), which is a medical procedure for brain tumor classification. It is of high importance to devise automated methods to aid radiologists in brain cancer tumor diagnosis without resorting to invasive procedures. Convolutional neural network (CNN) is deemed to be one of the best machine learning algorithms to achieve high-accuracy results in tumor identification and classification. In this paper, a CNN-based technique for brain tumor classification has been developed. The proposed CNN can distinguish between normal (no-cancer), astrocytoma tumors, gliomatosis cerebri tumors, and glioblastoma tumors. The implemented CNN was tested on MRI images that underwent a motion-correction procedure. The CNN was evaluated using two performance measurement procedures. The first one is a k -fold cross-validation testing method, in which we tested the dataset using k = 8, 10, 12, and 14. The best accuracy for this procedure was 96.26% when k = 10. To overcome the over-fitting problem that could be occurred in the k -fold testing method, we used a hold-out testing method as a second evaluation procedure. The results of this procedure succeeded in attaining 97.8% accuracy, with a specificity of 99.2% and a sensitivity of 97.32%. With this high accuracy, the developed CNN architecture could be considered an effective automated diagnosis method for the classification of brain tumors from MRI images.
Theoretical Study of Evaporation Heat Transfer in Horizontal Microfin Tubes : Stratified Flow Model

The stratified flow model of evaporation heat transfer in horizontal microfin tubes has been developed. The profile of stratified liquid was determined by a theoretical model previously developed for condensation in horizontal microfin tubes. For the region above the stratified liquid, the meniscus profile in the groove between adjacent fins was determined by a force balance between the gravity and surface tension forces. The thin film evaporation model was applied to predict heat transfer in the thin film region of the meniscus. Heat transfer through the stratified liquid was estimated by using an empirical correlation proposed by Mori et al. The theoretical predictions of circumferential average heat transfer coefficient were compared with available experimental data for four tubes and three refrigerants. A good agreement was obtained for the case of Fr0<2.5 as long as the partial dry out of tube did not occur.
Transformer-Based Language-Person Search With Multiple Region Slicing

Language-person search is an essential technique for applications like criminal searching, where it is more feasible for a witness to provide language descriptions of a suspect than providing a photo. Most existing works treat the language-person pair as a black-box, neither considering the inner structure in a person picture, nor the correlations between image regions and referring words. In this work, we propose a transformer-based language-person search framework with matching conducted between words and image regions, where a person picture is vertically separated into multiple regions using two different ways, including the overlapped slicing and the key-point-based slicing. The co-attention between linguistic referring words and visual features are evaluated via transformer blocks. Besides the obtained outstanding searching performance, the proposed method enables to provide interpretability by visualizing the co-attention between image parts in the person picture and the corresponding referring words. Without bells and whistles, we achieve the state-of-the-art performance on the CUHK-PEDES dataset with Rank-1 score of 57.67% and the PA100K dataset with mAP of 22.88%, with simple yet elegant design. Code is available on https://github.com/detectiveli/T-MRS.
Electrochemical Model-Based Fast Charging: Physical Constraint-Triggered PI Control

This paper proposes a new fast chargingstrategy for lithium-ion (Li-ion) batteries. The approach relies on an experimentally validated high-fidelity model describing battery electrochemical and thermal dynamics that determine the fast charging capability. Such a high-dimensional nonlinear dynamic model can be intractable to compute in real-time if it is fused with the extended Kalman filter or the unscented Kalman filter that is commonly used in the community of battery management. To significantly save computational efforts and achieve rapid convergence, the ensemble transform Kalman filter (ETKF) is selected and tailored to estimate the nonuniform Li-ion battery states. Then, a health- and safety-aware charging protocol is proposed based on successively applied proportional-integral (PI) control actions. The controller regulates charging rates using online battery state information and the imposed constraints, in which each PI control action automatically comes into play when its corresponding constraint is triggered. The proposed physical constraint-triggered PI charging control strategy with the ETKF is evaluated and compared with several prevalent alternatives. It shows that the derived controller can achieve close to the optimal solution in terms of charging time and trajectory, as determined by a nonlinear model predictive controller, but at a drastically reduced computational cost.
Non-Canonical Amino Acids as Minimal Tags for Investigating Protein Organization and Turnover

The burgeoning field of genetic code expansion provides new tools for specifically labeling proteins for a variety of applications. Clickable non-canonical amino acids (ncAA) have been refined for almost-quantitative and highly selective reactions with complementary probes. In my thesis work I have adapted genetic code expansion for two biological questions. First, I used ncAA incorporation and click reaction to test the effect of fluorescent protein (FP) tagging on the nanoscale organization of target proteins. Second, I used these tools to generate a genetically-encoded scheme for specific protein labeling in non-optical nanoscale imaging. Protein localization and behavior has been regularly tested using FPs. Conventional imaging experiments using FPs are simple and efficient, which renders FPs attractive also for super-resolution microscopy (nanoscopy). Nevertheless, FPs have been claimed to induce the nanoscale aggregation of target proteins. Therefore, the effects of FP-tagging on the nanoscale organization behavior of the target proteins needed to be tested, in an unbiased fashion, using a reporter that is smaller and less artifact-prone than the FPs. I relied on the specific incorporation of the ncAA propargyl-L-lysine (PRK) into the FP chimeras of 26 proteins of interest, both cytosolic and membrane attached. The proteins were coupled via click chemistry to fluorescent probes suitable for either stimulated emission depletion microscopy (STED) or ground state depletion followed by individual molecule return (GSDIM). Analysis of the resulting images showed that FP tagging has negligible effects on most proteins, and therefore supported the use of FPs in nanoscale imaging. Optical microscopy is not the only nanoscale imaging approach that can be used at the moment. Nanoscale secondary mass spectrometry (NanoSIMS) relies on isotope measurements to reach a similar resolution domain. However, it lacks genetically encoded, FP-like tools. For this purpose I developed a novel labeling scheme, for specific protein isotopic and fluorescence labeling (SPILL). It involves the incorporation of ncAA PRK followed by the reaction with two novel probes containing isotopes that are not normally abundant in cells, 19F and 15N. These isotopic probes can be imaged in SIMS akin to GFP in optical microscopy, and enable the high resolution imaging of many cellular parameters, including protein turnover.
Manchar Lake’s Hypothetical Restoration and Willingness of Fishing Communities to Switch Back To Fishing

Environmental and anthropogenic changes in lakes have implications for fishers’ livelihoods in form of their forced migration and occupational change. Those advocating lake restorations often face a dilemma whenasked if lake restoration will also restore the lost livelihoods. Answering such questions are difficult because most people are not programmed for frequent changes in their livelihood structures. Using the case study of Manchar Lake fishers who seemingly have faced such transition, this study brings insights on this broad question. We developed an in-person survey based on Contingent Valuation Method (CVM) to study 300 fishers’ responses to a hypothetical situation whereby they were asked to “Switch Back” to Manchar Lake assuming that it has been restored to provide various ecosystem services. Results show that complete transformation in the livelihoods of fishing communities has taken place with remarkable variation in their access to assets and livelihood outcomes. Despite increase in their access to physical capital such as school, hospital, roads, and markets, the communities are still vulnerable to income shocks and rarely enjoy privileges such as house ownership. The comparative state of current and past livelihoods and asset possessions determine ones’ willingness to switch back to fishing in Manchar Lake. Those who may have performed better in the said transition are less likely to return to their erstwhile occupations even if the lake is restored and vice-versa. We conclude that satisfaction with current livelihood outcomes is low and willingness to switch back to fishing in Manchar Lake is high since many had been poor performers in the transition. While the environmental rationale for the Manchar Lake’s ecological restoration already exists, this study suggests that there also exists a socioeconomic rationale albeit in a way that restoration also supports contemporary ecological services such as tourism.
The impact of the oxidative status on the reproduction of cows and the calves’ health – a review

The profitability of cattle farming is largely determined by ensuring high-quality breeding animals for replacement and longevity in production. The provision of breeding animals requires adequate fertility of the cowherd and then intensive weight gain in the calf rearing period. For ensuring these demands, many management aspects must be considered. Continuous monitoring of the herd’s health status, including redox status, is essential. This review aims to provide a summary of relevant scientific data published in the last few decades regarding the role of oxidative stress (OS) in infertility of dairy cows and developmental diseases in calves, the major predisposing factors, and possible prevention.
Does Good Governance Matter? Kazakhstan’s Economic Growth and Worldwide Governance Indicators

Good governance is generally believed to improve country’s economic performance. This paper studies the relationship between the World Bank’s Worldwide Governance Indicators (Voice and Accountability, Political Stability and Absence of Violence, Government Effectiveness, Regulatory Quality, Rule of Law, Control of Corruption) and economic growth in terms of GDP per capita in Kazakhstan. The findings of the research indicate that there is a significant positive relationship between good governance and economic performance of Kazakhstan. Specifically, results show that the Control of Corruption has the strongest impact on GDP per capita.
LILRA3 is increased in IBD patients and functions as an anti-inflammatory modulator

Growing evidence shows that a homozygous 6.7-kb deletion of the novel anti-inflammatory molecule leukocyte immunoglobulin like receptor A3 (LILRA3) is associated with many autoimmune disorders. However, its effects on pathogenesis of inflammatory bowel disease (IBD) have not been clarified yet. LILRA3 is mainly expressed in monocytes, whereas its effects on biological behaviors of monocytes have not been systematically reported. To investigate the association between LILRA3 polymorphism and IBD susceptibility, LILRA3 polymorphism was assessed in 378 IBD patients and 509 healthy controls in our study, quantitative real-time PCR (qRT-PCR), western blot and immunohistochemistry (IHC) were employed to detect the LILRA3 expression in IBD patient blood and intestinal samples. Despite no association of the polymorphism with IBD development was found, LILRA3 expression was markedly increased in IBD patients compared with healthy controls. Human U937 monocyte cell line was employed to establish LILRA3-overexpressing cells and the effects of LILRA3 on the biological behaviors of U937 cells were systematically explored. We found that overexpression of LILRA3 in monocytes led to significant decreases in secretion of interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α) and interleukin 6 (IL-6). Additionally, LILRA3 abated monocyte migration by reducing the expression of several chemokines and enhanced monocyte phagocytosis by increasing CD36 expression. Furthermore, LILRA3 promoted monocyte proliferation through a combination of Akt and MEK/Erk signaling pathways. We report for the first time that LILRA3 is related to IBD and functions as an anti-inflammatory modulator in U937 cells.
Feasibility and acceptability of financial incentives and peer-led life skills training for improving adherence to antiretroviral therapy among adolescents living with HIV in Rwanda: A pilot study

Background The Human Immunodeficiency Virus (HIV) is the leading cause of death among adolescents in sub-Saharan Africa. Despite the long-term benefits of antiretroviral therapy (ART), adherence remains low among adolescents due to challenges related to cost, acquisition, and treatment regimen. Sub-optimal adherence to ART is associated with the development of viral resistance, treatment failure, and increased morbidity and mortality. Financial incentives and life skills training interventions have shown early promise in motivating protective behaviors, however, gaps still remain around effective and innovative ways to motivate adolescents to stay in HIV care. In partnership with youth, we developed an intervention to address their social and financial pressures in order to promote adherence. Methods A human-centered design approach was utilized to engage adolescents in the initial design of the intervention. Through random sampling, 72 adolescents ages 12–19 were then recruited from two clinics in Rwanda for the pilot study. Adolescents participated in three monthly peer-led life skills trainings at clinics and received financial incentives via mobile money upon clinic attendance and demonstration of suppressed viral load. Semi-structured interviews were then conducted with adolescents, healthcare workers, and caregivers to understand their experiences with the intervention. Results Participants responded favorably to the intervention because of the psychosocial, financial, and health benefits it provided. Caregivers felt that adolescents’ moods, attitudes, and overall well-being improved over time. Adolescents used funds to purchase school supplies and save for investments, thus mitigating their financial burdens. Additionally, we learned that logistical challenges such as SIM card registration and mobile phone access must be considered for scale-up of the intervention. Conclusions To our knowledge, this is the first intervention designed in partnership with youth in sub-Saharan Africa aimed at removing financial barriers to ART adherence. The findings suggest that involving youth in the design of programs, providing them with financial incentives, and training them to use and invest their money wisely has a positive effect on them and their families. Thus, to improve adherence to ART and retention in care among HIV-positive youth, it is critical to address their socioeconomic and psychosocial needs.
Changing public policy on expenditure in Namibia after independence and its impact on healthcare and education

: In this paper, we examined whether changes in fiscal measures through increasing government expenditure on education and healthcare services adopted after independence has made significant impact on the welfare of the Namibian people. Time series data from Ministry of Finance, Ministry of Education of Government of Namibia, Namibia Statistics Agency and World Bank during the period between 1980 and 2015 has been used for the purpose of analysis. A comparison of growth in such expenditures, GDP and other human development indicators has been made between the pre-and post-independence periods. Finally, impacts of changes in healthcare and education expenditure on reduction in mortality, increase in life expectancy at birth, rising literacy and growth of people acquiring higher/technical education, etc. have been examined by using regression analysis. It is revealed that the Namibian people are better off now as compared to the pre-independence era. However, policy changes adopted at the time of independence has not been highly successful in transforming life of the Namibian people as expected. There are still a lot of scopes for the improvement of fiscal management in the country.
PRODUCTION OF Candida BIOMASSES FOR HEAVY METAL REMOVAL FROM WASTEWATERS

Yeasts can accumulate heavy metals and grow in acidic media. In the present study, it was shown that Candida yeasts in an aqueous solution accumulate single Cu(II) and Ni(II) cations. The effect of heavy metal ions on the specific growth rate of biomasses and the uptake of metal ions during the growth phase was investigated in a batch system. Bioaccumulation efficiency decreased with increasing metal ion concentrations at constant sucrose concentrations. Both the specific growth rate and the biomass concentration were more inhibited in the bioaccumulation media containing Ni(II) ions singly as compared with the bioaccumulation media containing Cu(II) ions singly. The maximum specific growth rate and the saturation constant of yeasts were examined with a double-reciprocal form of Monod equation. Metal uptake performance decreased from 81.68% to 46.28% with increasing Ni(II) concentration from 25 mg/L to 250 mg/L for Candida lipolytica. Candida biomasses may be an alternative way of removal of heavy metals from wastewaters and may constitute a sample to produce new biomass. The study showed that Candida yeasts can be used as economical biomass due to their metal resistance and efficient production.
ACE DD Genotype Is Associated with High Visceral Sensitivity Index Score in Healthy Student Population in Bosnia and Herzegovina

Background Visceral Sensitivity Index (VSI) questionnaire measures gastrointestinal specific anxiety a mediator of the relationship between general psychological distress measures and gastrointestinal symptom severity. Studies have shown that angiotensin converting enzyme (ACE) may be required for sympatoadrenal activation during stress. The aim of our study was to explore the relationship of ACE gene polymorphisms with the scores for self-reported visceral hypersensitivity in the sample of student population exposed to psychological distress. Methods A blood sample was taken from ninety students during exam period. DNA was isolated and genotyping of ACE polymorphism (rs1799752) was performed using PCR method. The PCR products were analysed on a 2% agarose gel. All respondents completed the VSI questionnaire and based on the scores were stratified into two comparison groups. Allele and genotype association was tested using Fisher’s Exact Test in WINPEPI. Results Respondents with total score of up to 65 were classified in the first group and with values over 65 in the second group. Increased frequencies of D allele and DD genotype were observed in the subgroup of students with higher VSI score. Conclusions Obtained results revealed statistically significant association of allele D and DD genotype with increased VSI score. Our results indicate that further genetic and genome studies of regulation of brain-gut axis and visceral hypersensitivity could be helpful in clinical interpretation of their impact on functional gastrointestinal disorders (FGID) symptoms and on development of some other acute and chronic stress related conditions in youth population.
Medical image analysis with machine learning techniques and deep learning neural networks

The recent development of computer vision machine learning algorithms will be examined and the performance of a subset of those will be studied on the skin lesion image classification task. More specifically, the performance of deep learning algorithms on image classification will be presented and tested. A specific family of convolutional neural networks called EfficientNets will be trained on the ISIC challenge dataset of 2019.
Characterization and Bio-prospecting of Fungi for Ag(I), Au(III) and Pd(II) sorption

Mineral reserves in the earth’s crust are limited but their uses are unlimited. Numerous uses of metals generate large volume of liquid wastes containing low amounts of metals. Release of heavy metals into the waste streams poses a threat of getting mixed with natural water bodies and entering the food chains. Heavy metals are toxic to flora, fauna as well as humans and can even be fatal. On the other hand, release of precious metals into the waste streams needs to be paid attention to, keeping in mind their monetary value and strategic uses.