Miracle-dz/UniFAR-FTUs huggingface dataset:
Population Dynamics of Emerging Spider Mite Pest Tetranychus Udaipurensis gupta & Gupta

Temperature related development and demography of emerging spider mite pest Tetranychus udaipurensis Gupta and Gupta were studied on two vegetable host plants ridge gourd and French bean at four different temperature (22º-34ºC)and humidity conditions (67-80%). Development of T. udaipurensis female was faster-7.31 days on French bean and 7.42 days on ridge gourd, respectively at 34ºC. For reproduction (female longevity, fecundity and sex ratio) and demography, the favourable temperature range was 26º-30ºC. Chief demographic parameters viz., mean generation time, doubling time, net reproduction rate and intrinsic rate of natural increase on the preferred host French bean was 16 to 20 and 2.98 to 3.80, 42 to 48 mites and 0.200 to 0.248 female offsprings/ day, respectively. Under the consequence of changing climatic conditions, T.udaipurensis might emerge as potential pest of vegetable crops, more particularly of French bean.
Banach Random Walk in the Unit Ball S ⊂ l 2 and Chaotic Decomposition of l 2 (S, P)

A Banach random walk in the unit ball S inl 2 is defined, and we show that theintegralintroducedbyBanach(Theoryoftheintegral.Warszawa-Lwow,1937)can be expressed as the expectation with respect to the measure P induced by this walk. A decomposition l 2 (S, P) = � ∞=0 Bi in terms of what we call Banach chaoses is given.
COVID-19 PANDEMIC AND NIGERIA’S ECONOMIC GROWTH: A COMPARATIVE ANALYSIS OF PRE AND P0ST 2020

The outbreak of covid-19 pandemic affected the global economy, Nigeria inclusive. As a result, economic forecasts predicted a global recession for the year 2020 and possibly beyond. Hence, this study aims to examine the extent to which covid-19 pandemic has affected the growth of the Nigerian economy by doing a comparative analysis of pre and post 2020 covid-19. Monthly time series data was employed from the period January 2018 through October 2022. The model specified used real gross domestic product as the dependent variable while the regressors were agricultural output, industrial output and services sector output. Covid-19 was used as an economic growth interruption variable rather than a real quantitative variable and its effect in the model was evaluated using the Chow break-point test. The stated hypotheses were tested using the t-test, F-test and coefficient of multiple determination (R2). Other tests conducted were stationarity test and the ARDL Bounds test for co-integration. The Chow test revealed that structural break existed at the specified break point period of May 2020. Hence, we estimated the model parameters before and after the break-point period. The result revealed that the agricultural sector increased real GDP significantly before and after the month of May 2020. The industrial sector’s output was positive but not significant before the pandemic, it became significant after the pandemic. The services sector did not significantly increase real GDP before the pandemic, but afterwards, the sector’s contribution to GDP slipped to negative. The study concluded that the Nigerian economy has obviously been largely affected by the covid-19 pandemic with the services sector being highly affected. It was recommended that government should make deliberate favourable policies that will further enhance the agricultural and industrial sectors output and that the government should serve as encouragers in the services sector as this will make young entrepreneurs to invest more in myriads of services available in the services sector in this period of post covid-19 recovery.
Eulerian models and three-dimensional numerical simulation of polydisperse sprays

Providing accurate simulations of polydisperse evaporating sprays dynamics in unsteady gaseous flows with large scale vortical structures is both a crucial issue for industrial applications and a challenge for modeling and scientific computing. The usual Lagrangian approaches developed in polydisperse unsteady configurations require tremendous computational costs and may lead to a low level of resolution if not enough numerical parcels are used. Besides, they induce coupling issues due to the different kind of description of the two phases that are involved. A large range of Eulerian models have been recently developed to describe the dispersed liquid phase with a lower cost and an easier coupling with a carrier gaseous phase. Among these models, the multi-fluid model allows a detailed description of polydispersity and size/velocity correlations of droplets of various sizes. It has been studied in depth from a mathematical and numerical point of view and validated through comparisons versus Lagrangian simulations and experimental measurements in 2D and 2D-axisymmetrical configurations. However, the validation in three-dimensional unsteady configurations still remains to be done. In this work, we study the non-evaporating droplet segregation in three-dimensional Homogeneous Isotropic Turbulence (HIT) using a reference Lagrangian spray model versus the Eulerian multi-fluid model. A spectral Direct Numerical Simulation solver is used to describe the evolution of the turbulent carrier phase, whose characteristic properties remain statistically stationary due to a semi-deterministic forcing scheme. We focus on the optimization via a parallel implementation of the multi-fluid model and dedicated numerical methods which demonstrates the ability of the Eulerian DNS model to be used in complex configurations. We provide qualitative comparisons between the Euler-Lagrange and the Euler-Euler descriptions for two different values of the Stokes number based on the initial fluid Kolmogorov time scale, Stokes=0.17 and 1.05. A very good agreement is found between the mesoscopic Eulerian and Lagrangian predictions. We go further with first quantitative comparisons of the segregation effect of the vortices on the spray mass density distribution showing the accuracy and ability of the multi-fluid model to be used in 3D complex configurations from the tracer limit to unity.
Constructive neural network design for the solution of two-state classification problems with application to channel equalization

Describes a deterministic algorithm for designing a MLP for the solution of a two-state classification problem. The Slab Algorithm was motivated by the problem of reconstructing digital signals which have been passed through a real linear dispersive channel of finite impulse response and corrupted with additive noise. The authors' algorithm is designed to separate two finite disjoint sets of points by constructing a MLP with one hidden layer and a single output node. In the linearly separable case, no hidden layer is constructed. The parameters of the network are identified by standard linear programming techniques. The performance of the channel equalizer constructed by the Slab Algorithm is compared with that of a Bayesian optimal equalizer.
Computational modeling of small molecules

Computational chemistry lies at the intersection of chemistry, physics, mathematics, and computer science, and can be used to explain the behavior of atoms and molecules, as well as to augment experiment. In this work, computational chemistry methods are used to predict structural and energetic properties of small molecules, i.e. molecules with less than 60 atoms. Different aspects of computational chemistry are examined in this work. The importance of examining the converged orbitals obtained in an electronic structure calculation is explained. The ability to more completely describe the orbital space through the extrapolation of energies obtained at increasing quality of basis set is investigated with the use of the Sapporo-nZP-2012 family of basis set. The correlation consistent Composite Approach (ccCA) is utilized to compute the enthalpies of formation of a set of molecules and the accuracy is compared with the target method, CCSD(T,FC1)/aug-cc-pCV∞Z-DK. Both methodologies are able to produce computed enthalpies of formation that are typically within 1 kcal mol-1 of reliable experiment. This demonstrates that ccCA can be used instead of much more computationally intensive methods (in terms of memory, processors, and time required for a calculation) with the expectation of similar accuracy yet at a reduced computational cost. The enthalpies of formation for systems containing s-block elements have been computed using the multireference variant of ccCA (MR-ccCA), which is designed specifically for systems that require an explicit treatment of nondynamical correlation. Density functional theory (DFT) has been used for the prediction of the structural properties of a set of lanthanide trihalide molecules as well as the reaction energetics for the rearrangement of diphosphine ligands around a triosmium cluster.
Word and action: the many routes through Jesús Martín-Barbero

ABSTRACT The articles in this special issue address some of the conceptual innovations and controversies raised by the late Jesús Martín-Barbero's (1937–2021) combative and generous spirit. These introductory remarks provide an overview of Martín-Barbero's academic and public intellectual contributions. Specifically, we examine his personal, political, intellectual and cultural trajectories as they lead us to a core category in his thinking: mediations. We also present the essays in this issue to show how Martín-Barbero's work is valuable and fundamental to understanding the contemporary moment in Latin America, the Caribbean and perhaps beyond.
A multivariate pattern analysis study of the HIV-related white matter anatomical structural connections alterations

It’s widely known that HIV infection would cause white matter integrity impairments. Nevertheless, it is still unclear that how the white matter anatomical structural connections are affected by HIV infection. In the current study, we employed a multivariate pattern analysis to explore the HIV-related white matter connections alterations. Forty antiretroviraltherapy- naïve HIV patients and thirty healthy controls were enrolled. Firstly, an Automatic Anatomical Label (AAL) atlas based white matter structural network, a 90 × 90 FA-weighted matrix, was constructed for each subject. Then, the white matter connections deprived from the structural network were entered into a lasso-logistic regression model to perform HIV-control group classification. Using leave one out cross validation, a classification accuracy (ACC) of 90% (P=0.002) and areas under the receiver operating characteristic curve (AUC) of 0.96 was obtained by the classification model. This result indicated that the white matter anatomical structural connections contributed greatly to HIV-control group classification, providing solid evidence that the white matter connections were affected by HIV infection. Specially, 11 white matter connections were selected in the classification model, mainly crossing the regions of frontal lobe, Cingulum, Hippocampus, and Thalamus, which were reported to be damaged in previous HIV studies. This might suggest that the white matter connections adjacent to the HIV-related impaired regions were prone to be damaged.
Regional involvement in EU trade policy: what remains after politicization?

ABSTRACT Wallonia demonstrated the importance of regional actors for EU trade policy. What remains, however, of regional involvement when politicization subsides, as after CETA and TTIP? Our paper provides a framework that allows a prediction of involvement after politicization. It posits that the interaction of three factors is decisive: politicization (short-term), preferences (medium-term), institutions (long-term). The more regional actors dispose of institutionalised channels of voice and the more they develop endogenous preferences, the less impact for politicization. We demonstrate this interplay in the cases of Austria, Germany, Belgium, Spain, and Italy. Whereas regional involvement in Spain and Italy is driven near-exclusively by politicization, the German and Austrian Länder will remain cooperatively involved even in its absence. The Belgian regions, in turn, are in a process of gradual institutionalization. Our study demonstrates that regional actors remain a force to be reckoned with in EU trade policy, but some more so than others.
NONPARALLEL HYPERPLANES SUPPORT VECTOR REGRESSOR

Motivated by nonparallel hyperplanes support vector machine (NHSVM), a new regression method of data, named as nonparallel hyperplanes support vector regression (NHSVR), is proposed in this paper. The advantages of NHSVR have two aspects, one is considering the minimization of structure risk by introducing a regularization term in objective function, and another is finding two nonparallel hyperplanes by solving a combined quadratic programming problem. In order to verify the effectiveness of the propose method, a series of comparative experiments are performed with TSVR, LTSVR, and TSVR e on five evaluation indexes. The experiment results show that the proposed NHSVR is an effective and efficient algorithm for regression of data.
Language and technological inclusion among immigrant low-income Latina mothers: A feminist action research intervention

Summary Although Latinx families comprise the largest growing population in the United States, research has not examined how the lack of social inclusion (e.g., multidimensional term comprising economic, political, and cultural dimensions, among others) influences the lives of low-income Latina mothers. Social inclusion, which is a term born as a counterpart to social exclusion, has been overlooked as an alternative construct that allows the development of personal agency. Contrary to social exclusion paradigms which often focus on deficits, social inclusion focuses on recognizing inherit strengths among vulnerable families. The first purpose of this research is to explore social inclusion (a strength perspective) as a much-needed alternative to social exclusion (deficit view). The second is to describe the experiences of low social inclusion among low-income urban Latina mothers via two interviews, a focus group, recollection of artifacts from participants, and reflective journaling, which were documented within a context of a feminist action research intervention. Participants consisted of 12 low-income Latina mothers (N = 12) who participated in a financial literacy intervention. Findings Via thematic analysis, findings confirmed two new dimensions of low social inclusion not found in traditional literature: low language and technological inclusion. Applications Recommendations for social work practitioners and future research include developing culturally relevant interventions among minoritized communities and families, for instance, by promoting bilingual curricula and implementing technology in current interventions, which can have significant positive effects on the social inclusion of vulnerable communities.
Factors Influencing the Accuracy of Sonography-estimated Fetal Weight: A Retrospective Cohort Study in the Chinese Population

Objective: To evaluate the accuracy of sonography-estimated fetal weight (EFW) and to determine the potential factors influencing EFW accuracy in the Chinese population. Methods: Eleven widely used formulae were chosen to evaluate the accuracy of EFW in 7016 cases in a retrospective cohort study. Nine potential factors (prenatal body mass index [BMI], gestational age [GA], birth weight [BW], fetal sex, fetal presentation, amniotic fluid volume [AFV], seniority of sonographers, the time interval between ultrasonic measurement and delivery, and diabetes mellitus) were analyzed by binary logistic regression to determine whether they influenced sonography-EFW. Results: All 11 models had high correlation coefficients between EFW and BW (r = 0.819–0.843). Model 3 was the most accurate formula for the Chinese population. Compared to fetuses with EFW of 2500–3999 g, the accuracy of EFW decreased by 69.10% (P <0.001) for fetuses less than 2500 g, and decreased by 54.10% (P <0.001) for fetuses larger than 4000 g. The accuracy of EFW in female fetuses decreased by 12.70% compared with male fetuses (P = 0.021). Compared to the EFW calculated 1-3 days before delivery, the accuracy of the EFW performed 4–7 days before delivery showed a significant decrease (P = 0.014). The accuracy of EFW was influenced by the individual measurement accuracy of the sonographers. Maternal BMI, DM, GA, fetal presentation, and AFV did not influence the accuracy of EFW after adjustment. Conclusion: Model 3 was the most accurate model for the Chinese population. The BW, fetal sex, time interval, and technique of the sonographers had different influences on the accuracy of EFW.
GENERALIZED CONFIRMATORY FACTOR ANALYSIS FOR KNOWING IMPACT OF KNOWLEDGE, ATTITUDES, AND BEHAVIORAL FACTORS HIV/AIDS IN INDONESIA

The cumulative number of detected HIV/AIDS cases in the January – March 2021 period is 9,327, consisting of 7,650 HIV and 1,677 AIDS reported by 498 districts and cities from 514 districts and cities in Indonesia. Human Immunodeficiency Virus (HIV) is the virus that causes Acquired Immunodeficiency Syndrome (AIDS). Several factors that influence the spread of HIV/AIDS include knowledge, attitudes and behavior about HIV/AIDS. Someone who gains knowledge about HIV/AIDS will have high self-confidence and a positive outlook on life and be more optimistic in taking HIV/AIDS prevention actions. The main objective of this study is to determine the influence of external factors which include demographic, social and economic aspects, as well as internal factors which include knowledge, attitudes and behavior to the level of transmission of HIV/AIDS. By using the CFA approach, it can be seen which indicators have the greatest influence on the latent variables of knowledge, attitudes, and behavior or called loading factors. The data used is secondary data from a 5-year survey from the Central Statistics Agency, namely the 2017 Indonesian Demographic and Health Survey (IDHS) published at the end of 2018. The CFA results show that the P11 variable (about known infections) has the largest loading factor value, which is 0.613 in the variable. hidden. knowledge. In the latent variable of attitude, the S1 variable (about identifying how the respondent knows someone is infected with HIV-AIDS) has the largest loading factor value of 0.514. While the behavioral latent variable, the variable R8 (whether men have been infected with sexually transmitted diseases (STI) with symptoms) has the largest loading factor value, which is 0.954.
Approach Methods of Processing by Non-pns Islamic Leader in Simokerto District Towards Religiosity in Elderly Congratulations at Assembly Taklim Al-Hidayah

The Al- Hidayah taklim assembly activities in Simokerto district are held every Thursday afternoon from 15.00 Wib to 16.00 Wib. Consisting of congregations, most are elderly and are fostered by non-PNS Islamic religious instructors in the Simokerto district. The problem in this study is how are the characteristic of the elderly congregation and the model of the dakwah approach used by non-PNS Islamic religious instructors in conducting dakwah to the elderly assemblies. The method used in this study uses qualitative methods: data collection techniques, namely, observation, interview, and documentation. Meanwhile, in data processing, there are several ways: data reduction, selecting data, data analysis, data presentation, and drawing conclusions. The dakwah approach model used by non-PNS Islamic religious instructors in Simokerto District for the elderly congregation in the Al-Hidayah assembly uses a social approach model (bi al hal), an education approach model, a cultural education model, a personal approach model (kardiya) and a personal approach model (kardiya), group ja,' yah.
Comparing estimation approaches for generalized additive mixed models with binary outcomes

Generalized additive mixed models (GAMMs) extend generalized linear mixed models (GLMMs) to allow the covariates to be nonparametrically associated with the response. Estimation of such models for correlated binary data is challenging and estimation techniques often yield contrasting results. Via simulations, we compared the performance of the Bayesian and likelihood-based methods for estimating the components of GAMMs under a wide range of conditions. For the Bayesian method, we also assessed the sensitivity of the results to the choice of prior distributions of the variance components. In addition, we investigated the effect of multicollinearity among covariates on the estimation of the model components. We then applied the methods to the Bangladesh Demographic Health Survey data to identify the factors associated with the malnutrition of children in Bangladesh. While no method uniformly performed best in estimating all components of the model, the Bayesian method using half-Cauchy priors for variance components generally performed better, especially for small cluster size. The overall curve fitting performance was sensitive to the prior selection for the Bayesian methods and also to the extent of multicollinearity.
Examination of the parameters controlling the triple oxygen isotope composition of grass leaf water and phytoliths at a Mediterranean site: a model–data approach

Abstract. Triple oxygen isotopes (17O-excess) of water are useful to trace evaporation at the soil–plant–atmosphere interface. The 17O-excess of plant silica, i.e., phytoliths, inherited from leaf water, was previously calibrated in growth chambers as a proxy of atmospheric relative humidity (RH). Here, using a model–data approach, we examine the parameters that control the triple oxygen isotope composition of bulk grass leaf water and phytoliths in natura, at the O3HP experimental platform located in the French Mediterranean area. A grass plot was equipped to measure for 1 year, all environmental and plant physiological parameters relevant for modeling the isotope composition of the grass leaf water. In particular, the triple oxygen and hydrogen isotope composition of atmospheric water vapor above the grass was measured continuously using a cavity ring-down spectrometer, and the grass leaf temperature was monitored at plot scale using an infrared (IR) radiometer. Grass leaves were collected in different seasons of the year and over a 24 h period in June. Grass leaf water was extracted by cryogenic vacuum distillation and analyzed by isotope ratio mass spectrometry (IRMS). Phytoliths were analyzed by IR–laser fluorination–IRMS after chemical extraction. We showed that the traditional Craig–Gordon steady-state model modified for grass leaves reliably predicts the triple oxygen isotope composition of leaf water during daytime but is sensitive to uncertainties on the leaf-to-air temperature difference. Deviations from isotope steady state at night are well represented in the triple oxygen isotope system and predictable by a non-steady-state model. The 17O-excess of phytoliths confirms the applicability of the 17O-excessphyto vs. RH equation established in previous growth chamber experiments. Further, it recorded average daytime RH over the growth period rather than daily RH, related to low transpiration and silicification during the night. This model–data approach highlights the utility of the triple oxygen isotope system to improve the understanding of water exchange at the soil–plant–atmosphere interface. The in natura experiment underlines the applicability of 17O-excess of phytoliths as a RH proxy.