Miracle-dz/UniFAR-FTUs huggingface dataset:
Psychosocial Distress and Exposure to Sexually Explicit Materials as Correlates of Sexual Intercourse among Adolescents in Dodoma–Tanzania

Background: Adolescents’ sexuality is topical in public health discussions owing to its ability to increase the risk of HIV infection and other sexually transmitted diseases. Research shows that adolescents’ sexual behavior, psychosocial distress, and exposure to sexually explicit material(SEM) are interconnected in that they need collective health interventions for adolescents. Although mental health factors, such as psychological distress, are common in developing and middle-income countries, including Tanzania, these factors are less considered in HIV research. Thus, there is a need to raise awareness on the role of mental health factors in HIV epidemic. This study is, therefore, a response to this requirement by examining the contribution of psychosocial distress and exposure to sexually explicit materials on sexual intercourse among adolescents in Dodoma Region of Tanzania.Methods: A cross-sectional survey was conducted in five villages of Chamwino District from April to June 2017 among 1,226 adolescents of 10-19 years’ age. A stratified random sampling technique was used to select the respondents. A weighted logistic regression model was used to examine the independent contribution of psychosocial distress and exposure to sexually explicit materials on sexual intercourse while accounting for study design.Results: The overall lifetime prevalence of adolescent sexuality was 20.38%. The prevalence was observed to be higher among males (32.15%) as compared to females (10.92%). Adolescent sexuality was significantly associated with both psychosocial distress and exposure to sexually explicit materials. The odds ratios showed that adolescents reported psychosocially distressed (AOR=1.61, 95 %CI: 1.32- 1.96) and those exposed to sexually explicit materials (AOR=4.26, 95% CI: 3.65- 4.97) were at higher risk of having sexual intercourse. Other variables associated with sexual intercourse were age, sex, alcohol use, and current schooling status.Conclusion: The analysis made through this study came to the conclusion that as HIV risk continues to be a serious concern among adolescents, adolescent sexuality, psychosocial distress, and exposure to sexually explicit materials are interconnected. This calls for upfront interventions on school health education and services, particularly on the ventures to lower psychosocial distress and avert exposure on sexually explicit materials to prevent the spread of HIV and other sexually transmitted diseases.
Bioflocculation: Implications for Activated Sludge Properties and Wastewater Treatment

ABSTRACT Studies were conducted to determine the role of bioflocculation in the activatedsludge unit processes. Laboratory and full-scale studies revealed that bioflocculation isimportant in determining settling, dewatering, effluent and digested sludge properties(activated sludge properties) and may be vital to the function of all processes related tothe above properties. In these studies, it was shown that divalent cations such as calciumand magnesium improved activated sludge properties, whereas monovalent cations suchas sodium, potassium and ammonium ions were detrimental to these properties. Thedivalent cations promoted bioflocculation through charge bridging mechanisms withnegatively charged biopolymers (mainly protein and polysaccharide). It was found thatoxidized iron plays a major role in bioflocculation and determination of activated sludgeproperties through surface interactions between iron and biopolymers. Oxidized iron waseffective in removing colloidal biopolymers from solution in coagulation andconditioning studies. The research included experiments evaluating effects of potassiumand ammonium ions on settling and dewatering properties; effects of magnesium onsettling properties; effects of sodium, potassium, calcium and magnesium on effluentquality; effect of solids retention time on effluent quality; and evaluation of flocproperties during aerobic and thermophilic digestion. A floc model is proposed in whichcalcium, magnesium and iron are important to bioflocculation and the functionality ofaeration tanks, settling tanks, dewatering equipment and aerobic or anaerobic digesters.It is shown that activated sludge floc properties affect wastewater treatment efficiency.
Physical transformations of the active pharmaceutical ingredient BN83495: enantiotropic and monotropic relationships. Access to several polymorphic forms by using various solvation–desolvation processes

BN83495 is an API in development, used in the treatment of hormone dependent cancers. This molecule exhibits an interesting polymorphic landscape consisting of three polymorphic forms (I, II, and III), three 〈1:1〉 DMSO solvate polymorphs, and one 1,4-dioxane hemi-solvate. Among the three DMSO solvates, one can only be obtained in the presence of an inorganic impurity: the letovicite. Between the two polymorphic forms I and III, an enantiotropic transition has been highlighted. This solid–solid transition (Form I → Form III) seems to be controlled by the mosaicity of the particles, where both polymorphic form domains cohabit and this could remain unchanged for months. The reverse transition has not been detected in the solid state; slurrying in a solvent appears necessary to return to Form I. Each of the three polymorphs can be obtained by soaking in cold water the appropriate solvated compound. The crystal structure of each phase was determined from single crystal X-ray diffraction, except for Form II (the monotropic form under normal pressure). The analyses of the starting and final crystal structures involved in a desolvation process led to the proposal of mechanisms with and without transmission of structural information from the mother phase (i.e. the initial solvate) to the daughter phase. The presence of direct hydrogen bonds between BN83495 molecules in DMSO-I and 1,4-dioxane hemi-solvate seems to ensure the structural filiations during the desolvation mechanisms leading respectively to Form III and Form II.
Aberrant KIF23 expression is associated with adverse clinical outcome and promotes cellular malignant behavior through the Wnt/β-catenin signaling pathway in Colorectal Cancer

Purpose: The aim of the present study was to reveal the clinicopathological significance and prognostic role of kinesin family member 23 (KIF23) in colorectal cancer (CRC) and characterize its biological function and the underlying mechanisms. Methods: Bioinformatics analysis, immunohistochemistry, Western blot and qRT-PCR were utilized to investigate the expression of KIF23 in CRC tissues. The CCK-8 assay, wound healing assay and Matrigel assay were used to detect cell proliferation, migration and invasion in vitro. Western blot, immunofluorescence staining and cell function experiment were performed to explore the underlying mechanism. Results: The overexpression of KIF23 was associated with T stage, N stage, M stage and TNM stage, and CRC patients with high KIF23 expression had a worse prognosis. KIF23 knockdown inhibits CRC cells proliferation, migration and invasion in vitro. The mechanism study determined that KIF23 activates the Wnt/β-catenin signaling pathway by promoting the nuclear translocation of β-catenin to regulate the malignant behavior of CRC cells. Conclusion: These results suggest that KIF23 may act as a putative oncogene and a potential therapeutic target in CRC.
NO Signaling Fonctions in the Biotic and Abiotic Stress Responses

In the lace 1990s, NO became an increasingly popular target of investigation in plants. As in mammals, NO fulfils a broad spectrum of signaling functions in pathophysiological processes in plants. Here, we summerize studies published in recent years that provide novel insights into the Signaling functions of NO produced by plant cells exposed to abiotic stresses and biotic stress (pathogen-derived elicitors). Particularly, we report chat NO emerges as a key messenger governing the overall control of Ca homeostasis. Although the precise signaling functions of NO are poorly understood, its capacity to modulate Ca homeostasis provides an extraordinary and remarkably effective way of conveying information.
Fe3O4@MOF core–shell magnetic microspheres with a designable metal–organic framework shell

A novel kind of porous microsphere with a magnetic core and a tunable metal–organic framework (MOF) shell has been successfully fabricated utilizing a versatile step-by-step assembly strategy. The structure, composition, and function of the microspheres can be judiciously tailored by choosing various metal ions and polyfunctional organic ligands or tuning the assembly processes. Our results provide a valuable methodology for rationally designing novel core–shell architectures and MOF-based porous magnetic platforms.
Performance Analysis of Deep Learning and Statistical Models on Enhancing Stock Market Portfolio

: Time series data is considered very useful in the domains of business, finance and economics. Stock market data specifically is generated at high volumes and excessively used for forecasting purposes for gaining wealth. The problem is challenging due to the dynamic nature of stock market fluctuations. Conventional techniques for prediction of next lag of time series data have been successful to an extent with statistical algorithms such as Exponential Smoothing and Autoregressive Integrated Moving Average (ARIMA). With the advent of deep learning architectures and advanced computational processors, we analyze the performance of such techniques for stock market forecasting. The paper presents performance comparison of Exponential Smoothing, ARIMA, Vanilla LSTMs and Stacked LSTM models. The empirical analysis concludes the superior performance of deep learning techniques with RMSE score as low as 3.208 on daily closing price stock data for a period of ten years. Furthermore, we also propose a portfolio optimization method to calculate returns and maintain profits while trading in stock market. The development process should go through relevant data selection, data preprocessing to eliminate noise and missing values to create the prediction model. Study of the right algorithm, accompanied by model assessment. The study presented in this paper uses the LSTM to forecast the stock market exchange activity. The findings indicate that advanced versions of LSTM appear to provide more detailed results than standard algorithms. It can be shown that this paradigm is efficient for both private traders and corporate investors. They will obtain the potential actions of the movement of consumer rates and take the correct decision to make a profit. Different characteristics and facets of the industry should be addressed in future work to make forecasts more reliable. We also plan to use consumer feedback on the product to forecast the market shift.
Gas and Vapor Transport in Mixed Matrix Membranes Based on Amorphous Teflon AF1600 and AF2400 and Fumed Silica

The enhancement of gas and vapor transport rates induced by the addition of fumed silica nanoparticles to fluorinated glassy polymers is interpreted and quantitatively modeled considering the additional free volume created by incorporation of filler. That effect can be evaluated accurately from gas solubility data, using the NELF model. The solubility of CH4 and CO2 in matrices of Teflon AF1600 and AF2400, filled with variable amounts of fumed silica nanoparticles, was measured at 35 °C; the solubility of n-C4 and n-C5 vapors, as well as their diffusivity and the dilation induced in the same polymer matrices, was also measured at 25 °C. The fractional free volume (FFV) values, estimated on the basis of CH4 solubility data, were used to predict the solubility of the other penetrants inspected, with excellent agreement with experimental data. In addition, a single empirical correlation can be drawn, for both AF1600 and AF2400-based mixed matrices, between the infinite dilution diffusivity of vapors and the .
Implications of mercury interactions with band-gap semiconductor oxides

Titanium dioxide is a well-known photooxidation catalyst. It will oxidize mercury in the presence of ultraviolet light from the sun and oxygen and/or moisture to form mercuric oxide. Several companies manufacture self-cleaning windows. These windows have a transparent coating of titanium dioxide. The titanium dioxide is capable of destroying organic contaminants in air in the presence of ultraviolet light from the sun, thereby keeping the windows clean. The commercially available self-cleaning windows were used to sequester mercury from oxygen–nitrogen mixtures. Samples of the self-cleaning glass were placed into specially designed photo-reactors in order to study the removal of elemental mercury from oxygen–nitrogen mixtures resembling air. The possibility of removing mercury from ambient air with a self-cleaning glass apparatus is examined. The intensity of 365-nm ultraviolet light was similar to the natural intensity from sunlight in the Pittsburgh region. Passive removal of mercury from the air may re.
Oriented Vaterite CaCO3 Tablet-Like Arrays Mineralized at Air/Water Interface through Cooperative Regulation of Polypeptide and Double Hydrophilic Block Copolymer

Highly oriented vaterite CaCO 3 tablet-like arrays were formed at the air/water interface through the cooperative mineralization regulated by polypeptide and double hydrophilic block copolymer under ambient conditions. The nearly parallel arrangement of CaCO 3 vaterite tablets at the air/water interface shows the remarkable resemblance to the morphology of nacreous layers. The poly(aspartic acid) (PASP) with high molecular weight (M w = 11 000) and low solubility in water promoted the formation of vaterite tablets at the air/water interface, and stabilized the vaterite tablets by aggregation at the air/water interface and adsorption at the surface of vaterite tablets. Meanwhile, the highly hydrophilic poly(ethylene glycol)-block-poly(methacrylic acid) (PEG-b-PMAA) played an important role in regulating the arrangement and orientation of vaterite CaCO 3 tablets, leading to the oriented tablet-like arrays at the air/water interface. Detailed experiments revealed that hydrophilic PEG-b-PMAA alone did not produce any form of CaCO 3 crystals at the air/water interface, but could induce the formation of calcite CaCO 3 particles in the water phase. However, high molecular weight PASP alone led to the formation of disk-like vaterite particles composed of helically aggregated nanoplates at the air/water interface, suggesting the regulating role of PEG-b-PMAA in the growth of vaterite tablet arrays. These results reported here provide a better understanding of the growth mechanism of nacreous layers and shells in nature.
MoSe2 nanosheets and their graphene hybrids: synthesis, characterization and hydrogen evolution reaction studies

MoSe2 nanosheets and MoSe2/graphene hybrids have been prepared by a facile hydrothermal method. The number of layers of the MoSe2 nanosheets is typically <10 as confirmed directly by transmission electron microscopy and indirectly by a red shift of the characteristic A1g Raman peak. The hydrogen evolution reaction (HER) studies show that the onset potentials of MoSe2 and MoSe2/RGO hybrids are only ∼0.15 V vs. RHE and ∼0.05 V vs. RHE, respectively, about 20–30 mV lower than those of MoS2 and its graphene hybrids reported previously. Density functional theory calculations reveal that the Gibbs free energy for atomic hydrogen adsorption (ΔG0H) on MoSe2 edges is closer to thermoneutral than that on MoS2, with an H coverage of about 75% on the edge under operating conditions, which is also higher than that of MoS2 reported in the literature. The consistency between the experimental and computational results indicates that MoSe2 nanosheets have potential to be a better HER catalyst than their MoS2 counterpart.
A Simple Unified Framework for High Dimensional Bandit Problems

Stochastic high dimensional bandit problems with low dimensional structures are useful in different applications such as online advertising and drug discovery. In this work, we propose a simple uniﬁed algorithm for such problems and present a general analysis framework for the regret upper bound of our algorithm. We show that under some mild uniﬁed assumptions, our algorithm can be applied to different high-dimensional bandit problems. Our framework utilizes the low dimensional structure to guide the parameter estimation in the problem, therefore our algorithm achieves the comparable regret bounds in the LASSO bandit as a sanity check, as well as novel bounds that depend logarithmically on dimensions in the low-rank matrix bandit, the group sparse matrix bandit, and in a new problem: the multi-agent LASSO bandit.
Within-Document Event Coreference with BERT-Based Contextualized Representations

Event coreference continues to be a challenging problem in information extraction. With the absence of any external knowledge bases for events, coreference becomes a clustering task that relies on effective representations of the context in which event mentions appear. Recent advances in contextualized language representations have proven successful in many tasks, however, their use in event linking been limited. Here we present a three part approach that (1) uses representations derived from a pretrained BERT model to (2) train a neural classifier to (3) drive a simple clustering algorithm to create coreference chains. We achieve state of the art results with this model on two standard datasets for within-document event coreference task and establish a new standard on a third newer dataset.
A statistical measurement of the H i spin temperature in DLAs at cosmological distances

Evolution of the cosmic star formation rate (SFR) and molecular gas mass density is expected to bematched by a similarly strong evolution of the fraction of atomic hydrogen (H i) in the cold neutralmedium (CNM). We use results from a recent commissioning survey for intervening 21cm absorbers with the Australian Square Kilometre Array Pathfinder (ASKAP) to construct a Bayesian statistical model of the NHI-weighted harmonic mean spin temperature (Ts) at redshifts between z = 0.37 and 1.0. We find that Ts ≤ 274K with 95 per cent probability, suggesting that at these redshifts the typical H i gas in galaxies at equivalent DLA column densities may be colder than the Milky Way interstellar medium (Ts,MW ∼ 300K). This result is consistent with an evolving CNM fraction that mirrors the molecular gas towards the SFR peak at z ∼ 2. We expect that future surveys for H i 21-cm absorption with the current SKA pathfinder telescopes will provide constraints on the CNM fraction that are an order of magnitude greater than presented here.
Nonasymptotic bounds for suboptimal importance sampling

Importance sampling is a popular variance reduction method for Monte Carlo estimation, where a notorious question is how to design good proposal distributions. While in most cases optimal (zero-variance) estimators are theoretically possible, in practice only suboptimal proposal distributions are available and it can often be observed numerically that those can reduce statistical performance significantly, leading to large relative errors and therefore counteracting the original intention. In this article, we provide nonasymptotic lower and upper bounds on the relative error in importance sampling that depend on the deviation of the actual proposal from optimality, and we thus identify potential robustness issues that importance sampling may have, especially in high dimensions. We focus on path sampling problems for diffusion processes, for which generating good proposals comes with additional technical challenges, and we provide numerous numerical examples that support our findings.
Fortify Machine Learning Production Systems: Detect and Classify Adversarial Attacks

Production machine learning systems are consistently under attack by adversarial actors. Various deep learning models must be capable of accurately detecting fake or adversarial input while maintaining speed. In this work, we propose one piece of the production protection system: detecting an incoming adversarial attack and its characteristics. Detecting types of adversarial attacks has two primary effects: the underlying model can be trained in a structured manner to be robust from those attacks and the attacks can be potentially filtered out in real-time before causing any downstream damage. The adversarial image classification space is explored for models commonly used in transfer learning.
Information-theoretic abstractions for resource-constrained agents via mixed-integer linear programming

In this paper, a mixed-integer linear programming approach for obtaining task-relevant, multi-resolution, abstractions for resource-constrained agents is presented. The formulation leverages concepts from information-theoretic signal compression, specifically the information bottleneck (IB) method, to pose an abstraction problem as an optimal encoder search over the space of multi-resolution trees. The abstractions emerge in a task-relevant manner as a function of agent information-processing constraints, and are not provided to the system a priori. A non-trivial numerical example is presented to demonstrate the utility in employing our approach to obtain hierarchical tree abstractions for resource-limited agents.
Defense against flooding attacks using probabilistic thresholds in the internet of things ecosystem

The Internet of Things (IoT) ecosystem allows communication between billions of devices worldwide that are collecting data autonomously. The vast amount of data generated by these devices must be controlled totally securely. The centralized solutions are not capable of responding to these concerns due to security challenges problems. Thus, the Average Packet Transmission RREQ (APT‐RREQ) as an effective solution, has been employed to overcome these concerns to allow for entirely secure communication between devices. In this paper, an approach called LSFA‐IoT is proposed that protects the AODV routing protocol as well as the IoT network against flooding. The proposed method is divided into two main phases; the first phase includes a physical layer intrusion and attack detection system used to detect attacks, and the second phase involves detecting incorrect events through APT‐RREQ messages. The simulation results indicated the superiority of the proposed method in terms of False Positive Rate (FPR), False Negative Rate (FPR), Detection Rate (DR), and Packet Delivery Rate (PDR) compared to REATO and IRAD. Also, the simulation results show how the proposed approach can significantly increase the security of each thing and network security.