Miracle-dz/UniFAR-FTUs huggingface dataset:
How do youth innovate to make agriculture gainful? Challenges and youth entrepreneurs in mid-western Uganda

The global population is expected to increase to 9 billion by 2050, with the youth accounting for 14 per cent of this total. While the world's youth population is expected to grow, employment and entrepreneurial opportunities for youth, particularly those living in low and middle-income countries remain limited, poorly remunerated and of poor quality. The Ugandan population, in particular, is largely comprised of a high youthful population with 78 percent below the age of thirty. Evidence reveals that youth engagement in agriculture is declining, and in recognition of the agricultural sector's potential to serve as a source of livelihood opportunities, this study assesses the factors impeding youth engagement and the drivers of innovation among the youth engaged in agricultural enterprises in Mid-Western Uganda. Anchoring in the Agricultural Innovation System (AIS), cross-sectional survey and case study research designs were employed to establish the innovativeness of youth, and the factors impeding engagement in agricultural enterprises from the youth's perspective. A pairwise ranking of the factors was also independently done. The findings reveal that the significant factors restraining youth engagement in agricultural enterprises as enhancing soil productivity, access to relevant technical knowledge and information, and access to land for production. The major innovations for successful youth engagement in agriculture are irrigation to reduce risks of dependence on rain, mechanization to reduce labour struggle, and market linkages. The case studies' innovation index portrays a high potential of innovativeness of youth to revolutionize and make agriculture gainful and attractive to the youth. Int. J. Agril. Res. Innov. Tech. 12(1): 39-44, June 2022
The periods of the Volterra-Lotka system.

We give a short review of some literature. Frame [2] calculates the power series for the energy-period function we get s a consequence of Stirling's formula in Lemma 3 below. Grasman and Veling [3] give an asymptotic expansion for the period of large oscillations of an extremely asymmetric model, i.e. E—> oo, μ — » oo, μλ = l in our notation. Schaaf [6] proves monotonicity of the periods in the special Symmetrie case μ = λ. Hsu [4] gives a proof of our result which contains an essential mistake. To clarify this point we have added Theorem 2 and some remarks at the end of this note.
Probabilistic interpretation of electrical impedance tomography

In this paper, we give probabilistic interpretations of both, the forward and the inverse problem of electrical impedance tomography with possibly anisotropic, merely measurable conductivities: Using the theory of symmetric Dirichlet spaces, Feynman-Kac type formulae corresponding to different electrode models on bounded Lipschitz domains are derived. Moreover, we give a probabilistic interpretation of the Calder\'on inverse conductivity problem in terms of reflecting diffusion processes and their corresponding boundary trace processes.
The Dynamics of Cow Farmer Group towards the Development of Feed Canning Technology

Malang Raya area as a contributor of livestock product which is dairy cow's milk, do not escape from problem of increasing the number of farmers but not accompanied by an increase in milk production. This can be influenced by two kinds of factors such as genetic factors and external environmental factors such as feed. The above problems certainly underpinned renewal, to improve feed quality such as feed canning techniques, where the dynamics level of a group influenced the level of adaptation and distribution of these innovations. This research aimed to determine the dynamics of dairy farmers in Malang Raya Regency and the influence of group dynamics on the development of forage canning technology. The research location was determined purposively, where the location chosen would represent Malang Raya Regency with the majority of the people working as dairy farmers. The number of respondents in this research was 62 people who were determined by the purposive random sampling method. The research method used was descriptive analysis and case studies. Methods of collecting data used interviews, questionnaires, observations and documentation, to obtain primary and secondary data. The results showed that the dynamics of the majority group were in the moderate category, while group pressure was the only aspect that occupied the high category, in which 74.6%. Group pressure had a big influence on the motivation in performing activities to realize group goals, and the pressure was expected can change behavior, attitudes, ideas and mutual trust between members
Comprehensive Analysis of Gene Signatures of m6ARNA Methylation Regulators in Lung Adenocarcinoma and Development of a Risk Scoring System

The recent application of targeted immunotherapy has greatly improved the clinical outcomes of patients with lung adenocarcinoma (LUAD), but drug resistance continues to emerge, and to evaluate and to improve patient prognosis are arduous. The diagnostic and prognostic value of N6-methyladenosine (M6A) in LUAD has attracted increasing attention. We systematically studied correlations among important M6A methylation regulators, tumor mutational burden (TMB), and immune infiltration in clinical and sequencing data from the LUAD cohort of the cancer genome map (TCGA). The molecular subtype clusters 1 and 2 were identified by the consensus clustering of 16 M6A regulatory factors. Clinical prognosis, M6A regulatory factor expression, TMB, pathway enrichment, and immune cell infiltration significantly differed between clusters 1 and 2. Compared with other clinical traits, a prognostic risk score system constructed using the M6A regulatory factors HNRNPA2B1 and HNRNPC can serve as an independent prognostic method for LUAD, with higher predictive sensitivity and specificity. Risk scores were significantly higher for cluster 2 than 1, which was consistent with the trend towards a better prognosis in cluster 1. Overall, our findings revealed an important role of M6A methylation regulators in LUAD, and our risk scoring system involving these regulators might help to screen groups at high risk for LUAD and provide important theoretical bioinformatic support for evaluating the prognosis of such patients.
Bromine Crossover in Operando Analysis of Proton Exchange Membranes in Hydrogen−Bromate Flow Batteries

The manuscript deals with the fundamental problem of platinum hydrogen oxidation catalyst poisoning of the hybrid chemical power source based on bromate electroreduction and hydrogen electro-oxidation reactions. The poisoning is caused by the crossover of bromine-containing species through the proton exchange membrane separating compartments of the flow cell. Poisoning results in a drastic decrease in the flow cell performance. This paper describes the results of the direct measurement of bromine-containing species’ crossover through perfluorosulfonic acid membranes of popular vendors in a hydrogen−bromate flow cell and proposes corresponding scenarios for the flow battery charge−discharge operation based on the electrolyte’s control of the pH value. The rate of the crossover of the bromine-containing species through the membrane is found to be inversely proportional to the membrane thickness.
Learning Orientation Information From Frequency-Domain for Oriented Object Detection in Remote Sensing Images

Object detection in remote sensing images (RSIs) poses great difficulties due to arbitrary orientations, various scales, and dense location of the targets over the ground. Recent evidence suggests that encoding the orientation information is of great use for training an accurate object detector for oriented object detection (OOD). In this article, we propose a new frequency-domain orientation learning (FDOL) module with two main components: the frequency-domain feature extraction (FFE) network and an orientation enhanced self-attention layer (OES-Layer). The FFE network models the interactions among spatial locations in the frequency domain to determine the frequency of spatial features. Then, these features are fed into our OES-Layer to learn the orientation information. Moreover, the orientation weights are adopted to guide the feature selection in a self-attention (SA) architecture, using them as a control gate to emphasize the spatial responses of target instances. Considering that the original similarity weights (calculated by the SA algorithm) do not distinctly model the orientation variation, the considered orientation weights provide an efficient asset to emphasize the orientation of objects. Extensive experiments on the DOTA and HRSC2016 datasets demonstrate that our method achieves state-of-the-art performance among single-scale methods while achieving competitive performance over multiscale methods.
Sex Differences between Urinary Phthalate Metabolites and Metabolic Syndrome in Adults: A Cross-Sectional Taiwan Biobank Study

Background: Phthalates are widely used in consumer products, food packaging, and personal care products, so exposure is widespread. Several studies have investigated the association of phthalate exposure with obesity, insulin resistance, and hypertension. However, little is known about the associations of phthalate exposure with sex, age, and menopausal status in metabolic syndrome (MetS). The purpose of this study was to investigate the association between 11 urinary phthalate metabolite concentrations and metabolic syndrome in adults. Methods: We conducted a cross-sectional analysis of 1337 adults aged 30–70 years from the Taiwan Biobank 2016–2020. Prevalence odds ratios (POR) and 95% confidence intervals (CIs) were calculated using logistic regression and stratified by sex, age, and menopausal status. Results: Participants with MetS comprised 16.38%. Higher concentrations of MEP metabolites were associated with more than two- to three-fold increased odds of MetS in males and males ≥ 50 years (adj. POR Q3 vs. Q1 = 2.13, 95% CI: 1.01, 4.50; p = 0.047 and adj. POR Q2 vs. Q1 = 3.11, 95% CI: 0.13, 8.63; p = 0.029). When assessed by menopausal status, postmenopausal females with higher ∑DEHP concentrations had more than nine-fold higher odds of MetS compared with postmenopausal females with the lowest ∑DEHP concentrations (adj. POR Q3 vs. Q1 = 9.58, 95% CI: 1.18, 77.75; p = 0.034). Conclusions: The findings suggest differential associations between certain phthalate metabolites and MetS by sex, age, and menopausal status.
Risk-sensitive filtering and smoothing for jump Markov non-linear systems based on unscented transform [Brief Paper]

This study is concerned with risk-sensitive filtering and smoothing for a class of discrete-time jump Markov non-linear systems. Using the so-called reference probability method, the authors present a general theoretical framework to yield recursions for deriving filtered and smoothed estimates through identifying the approximations made by the interacting multiple model (IMM) estimation approach. A suboptimal risk-sensitive filtering algorithm is developed by applying the unscented transform (UT) technique and the one-step fixed-lag smoothing result is also presented for such systems. The effectiveness of the proposed algorithms is demonstrated via a manoeuvering target tracking simulation study.
Development of Carbon Nanotube (CNT)-Reinforced Mg Alloys: Fabrication Routes and Mechanical Properties

Properties such as superior specific strength, being imponderous, and the ability to reprocess are the key features that have drawn attention to magnesium. In the last few years, applications such as automotive, aerospace, and medical applications have been seeking light-weight equipment, and light-weight materials are required for making them. These demands were matched by developing metal matrix composites with magnesium as a base and reinforced with carbon nanotubes (CNTs), grapheme nanoplatelets (GNPs), or ceramic nanoparticles. CNTs have been adopted for developing high-strength metal matrix composites (MMCs) because of their delicately superior thermal conductivity, surface-to-volume ratio, and tensile strength, but lower density. In developing high-performance light-weight magnesium-based MMCs, a small number of CNTs result in refined properties. However, making Mg-based MMCs has specific challenges, such as achieving uniform reinforcement distribution, which directly relates to the processing parameters. The composition of CNT, CNT sizes, their uniform distribution, Mg-CNT interfacial bonding, and their in-between alignment are the characteristic deciding factors of Mg-CNT MMCs. The current review article studies the modern methods to develop Mg-CNT MMCs, specifications of the developed MMCs, and their vital applications in various fields. This review focuses on sifting and summarizing the most relevant studies carried out on the methods to develop Mg-CNT metal matrix composites. The article consists of the approach to subdue the tangled situations in highlighting the Mg-CNT composites as imminent fabrication material that is applicable in aerospace, medical, and automotive fields.
A Review of Factors Affecting SCC Initiation and Propagation in Pipeline Carbon Steels

Pipelines have been installed and operated around the globe to transport oil and gas for decades. They are considered to be an effective, economic and safe means of transportation. The major concern in their operation is corrosion. Among the different forms of corrosion, stress corrosion cracking (SCC), which is caused by stresses induced by internal fluid flow or other external forces during the pipeline’s operation, in combined action with the presence of a corrosive medium, can lead to pipeline failure. In this paper, an extensive review of different factors affecting SCC of pipeline steels in various environmental conditions is carried out to understand their impact. Several factors such as temperature, presence of oxidizers (O2, CO2, H2S, etc.), composition and concentration of medium, pH, applied stress, and microstructure of the metal/alloy have been established to affect the SCC of pipeline steels. SCC susceptibility of a steel at a particular temperature strongly depends on the type and composition of the corrosive medium and microstructure. It was observed that pipeline steels with water quenched and quenched and tempered heat treatments, such as those that consist of acicular ferrite or bainitic ferrite grains, are more susceptible to SCC irrespective of solution type and composition. Applied stress, stress concentration and fluctuating stress facilitates SCC initiation and propagation. In general, the mechanisms for crack initiation and propagation in near-neutral solutions are anodic dissolution and hydrogen embrittlement.
Developing Artificial Neural Network Based on Visual Studio for Dance Assessment

The dance assessment test still uses a manual system that tend to have frequent errors in the calculation for the final results thus it requires a system that accelerate the assessment process with an accurate result. This study aimed at: (1) designing an artificial neural network application based on visual studio for the dance assessment. (2) examining the performance of the artificial neural network application based on visual studio for the dance assessment. The design method consists of (1) system design (2) interface design (3) database design for artificial neural network system. (4) design of artificial neural network model. (5) programming (6) system testing. The design of visual studio artificial neural network application for the dance assessment has two stages: main program and supporting program. This research built a system by implementing visual studio and artificial neural network to assess dance examination which can give the final result to each participant directly. The application of the dance assessment can assess 3 types of dance with a training set of at least 10 pairs to undertake learning that produces the load to be used in the assessment. Besides assessing, this application can also delete, repair, and store data in the form of . xls. Based on the test results, it can be concluded that the application operates effectively for determining the final load, data input and data storage.
Large amplitude nonlinear waves in Venus magnetosheath

Large‐amplitude variations of the magnetic field in the Venusian magnetosheath are observed when the distance between the bow shock and the magnetic pileup boundary is small, of the order of the ion convective gyroradius. It is proposed that these oscillations are nonlinear standing waves. A theoretical model is developed within one‐dimensional two‐fluid hydrodynamics, which is in good agreement with the observed features of the structure.
The approximate solution of large queueing network models

In this thesis we investigate the problem of obtaining solutions for large, separable queueing network models of computer systems. To this end, we begin with a detailed analysis of the time and space requirements of the two major solution techniques. Subsequently, we develop three approximations based on aggregation of network components: aggregation of classes, aggregation of customers, and aggregation of service centers. Each approximation technique reduces the cost of solving the network (approximately) by reducing the number of some component in it that contributes to the high cost of solution. In general, the approximations transform a large separable network into a smaller, also separable network (using aggregation) that reflects the behavior of the original network. The exact solution for this reduced model is then obtained using standard techniques, and estimates of the performance measures of the full network are made from those of the reduced network. We present with each technique an explanation of its relation to the state space of the full network. This formal study is augmented by example solutions using the approximations for representative sets of models to gain some insight into the error behavior of the techniques. Finally, we discuss an alternative approximation technique not based on aggregation. A comparison of all techniques is given, with the problem of selecting an appropriate technique for a given network in mind.
Survival and Long-Term Biochemical Cure in Medullary Thyroid Carcinoma in Denmark 1997-2014 A Nationwide Study

Background: Survival of medullary thyroid carcinoma (MTC) subgroups in relation to the general population is poorly described. Data on the factors predicting long-term biochemical cure in MTC patients are nonexistent at a population level. A nationwide retrospective cohort study of MTC in Denmark from 1997 to 2014 was conducted, aiming to detect subgroups with survival similar to that of the general population and to identify prognostic factors for disease-speciﬁc survival and long-term biochemical cure. Methods: The study included 220 patients identiﬁed from the nationwide Danish MTC cohort between 1997 and 2014. As a representative sample of the general population, a reference population matched 50:1 to the MTC cohort was used. Results: Patients diagnosed with hereditary MTC by screening (hazard ratio [HR] = 1.5 [conﬁdence interval (CI) 0.5– 4.3]), patients without regional metastases (HR = 1.4 [CI 0.9–2.3]), and patients with stage I (HR = 1.3 [CI 0.6–3.1]), stage II (HR = 1.1 [CI 0.6–2.3]), and III (HR = 1.3 [CI 0.4–4.2]) disease had an overall survival similar to the reference population. On multivariate analysis, the presence of distant metastases (HR = 12.3 [CI 6.0–25.0]) predicted worse disease-speciﬁc survival, while the absence of regional lymph node metastases (odds ratio = 40.1 [CI 12.0–133.7]) was the only independent prognostic factor for long-term biochemical cure. Conclusions: Patients with hereditary MTC diagnosed by screening, patients without regional metastases, and patients with stages I, II, and III disease may have similar survival as the general population. The presence of distant metastases predictedworsedisease-speciﬁcsurvival,whiletheabsenceofregionalmetastasespredictedlong-termbiochemicalcure. data for 194 patients.
EFFECT OF STATE MINDFULNESS ON EMPLOYEE JOB SATISFACTION AND WELL-BEING: ROLE OF WORK-FAMILY BALANCE

This study aims to know how; committed and satisfied employee is an asset to an organization. How’ Scan help the organization to compete and grow aggressively in a dynamic global environment. Therefore, state m unless is a factor that increases employee job satisfaction and well-being by ensuring work-life balance as a mediator which is vital for organizational productivity and profitability. Quantitative data from 400 respondents of the telecom and banking sector of Pakistan has been collected through self-admin red questionnaires for analysis. The collected data has been analyzed through IBM SPSS 23 to explore the relationship among independent and dependent variables and the mediating effect of work-life balance has also been substantiated. Testing of mode confirms the positive impact of state mindfulness on employee job satisfaction and well-being by ensuring work-life balance as a mediator. This research is providing a theoretical and empirical foundation to link state mindfulness with employee job satisfaction and wellbeing of employees. This study also adds to the limited stick of knowledge, providing a mediating link of work-family balance between state mindfulness and job satisfaction and employee well-being. This study also broadens previous research findings.
Peri-urban transformation in the Global South: a comparative socio-spatial analytics approach

ABSTRACT This research advances our understanding of peri-urban dynamics in the Global South through an innovative comparative socio-spatial analytics approach combining geospatial and qualitative fieldwork-based methods. Drawing on three cases in China, Ghana and India, the comparison is operationalized through two pairs of conceptual lenses developed inductively. We argue that heterogeneous peri-urban morphologies in the Global South, which share several common features, notably fragmentation and bypass, albeit with differing degrees, are shaped by three key processes: (1) market- and speculation-driven property development; (2) state-led development strategies, often expressed through large-scale projects; and (3) fragmented planning and development practices.
The prime-to-p part of etale fundamental groups of curves

The previous version of this paper relied on a paper by another author whose proof appears to be invalid in a fundamental way. In arXiv:1707.00649 the author, together with Jeff Yelton, came up with a new proof of almost identical results. (See Remark 1.4 of arXiv:1707.00649.)
NONPARAMETRIC KERNEL REGRESSION SUBJECT TO MONOTONICITY CONSTRAINTS

We suggest a method for monotonizing general kernel-type estimators, for example local linear estimators and Nadaraya-Watson estimators. Attributes of our approach include the fact that it produces smooth estimates, indeed with the same smoothness as the unconstrained estimate. The method is applicable to a particularly wide range of estimator types, it can be trivially modified to render an estimator strictly monotone and it can be employed after the smoothing step has been implemented. Therefore, an experimenter may use his or her favorite kernel estimator, and their favorite bandwidth selector, to construct the basic nonparametric smoother and then use our technique to render it monotone in a smooth way. Implementation involves only an off-the-shelf programming routine. The method is based on maximizing fidelity to the conventional empirical approach, subject to monotonicity. We adjust the unconstrained estimator by tilting the empirical distribution so as to make the least possible change, in the sense of a distance measure, subject to imposing the constraint of monotonicity.