Miracle-dz/UniFAR-FTUs huggingface dataset:
Interventions to Reduce Child Exposure to Indoor Air Pollution in Developing Countries: Behavioral Opportunities and Research Needs

Abstract:Indoor air pollution caused by the indoor burning of biomass fuels has been associated with increased risk of acute respiratory infections among children less than five years old in developing countries. Enough evidence of this association exists to support the design, implementation and evaluation of interventions to reduce child exposure to indoor air pollution. This paper reviews the published literature on three technical intervention options: access to cleaner burning fuels, improved cook stoves and modification to housing characteristics. It highlights the sustainability challenges related to the uptake and maintenance of technical interventions and discusses the potential for behavioral interventions to reduce child exposure to indoor air pollution in contexts where technical interventions are least likely to succeed in the short term. It further highlights the need for technical interventions to be inclusive of and sensitive to behavioral outcomes and processes and also discusses both quantitative and qualitative research needs in relation to evaluation options.
Toward a New Balance in Social Policy: The Future Role of Guaranteed Annual Income within the Safety Net

Guaranteed Annual Incomes (GAI) proposals attracted much support in the 1960s and early 70s but, for a variety of reasons, they slipped off mainstream policy agendas in the following decades. They were too expensive given new budgetary priorities and implementation was difficult for jurisdictional reasons. Over time, the concept of poverty shifted away from focusing on lack of income towards the lack of resources that cause exclusion and that prevent people from developing their capacities to fully participate in society. Concerns increasingly focused on siloed programs that provided one-size-fits-all benefits, ignoring individual and family diversity. New research paints a different picture of poverty, one where traditional GAI programs are less useful than had been previously assumed. In particular, most periods of lowincome are relatively short, requiring supports that can only be awkwardly met by traditional tax-based GAI designs. As well, for the minority of low-income people who are persistently poor, the best solutions involve integrated mixes of income supports and, often, a variety of services. Yet, despite all the factors above, interest in GAI schemes has increased in recent years. This Commentary briefly reviews current proposals and explains that the resurgence of interest in them likely lies in a deep desire to make things better, in the lack of progress to date in fighting poverty, and in frustration with the inability of existing policy tools to get results. However, the Commentary argues that the effective, and affordable, way ahead lies not in big GAI programs taken in isolation, but rather in the use of newly available technology and data sources to steadily improve three kinds of programming: 1) integrated services tailored to individual needs, such as skill-enhancing programs that are intended to address unique needs of those who are persistently poor; 2) supporting people who can save for occasional periods of low-income by allowing more flexible access to income supports over the course of one’s life; and, 3) GAI programming that extends existing measures, such as supports directed to children, seniors and those with disabilities. This bottom-up reform based on an evidence-driven approach would have a better chance of succeeding if GAIs are realigned to support this vision.
3D structure of the H ii region Sh2-235 from tunable-filter optical observations

We present observations of the H-alpha, H-beta, [SII] 6716, 6731 and [NII] 6583 emission lines in the galactic HII region Sh2-235 with the Mapper of Narrow Galaxy Lines (MaNGaL), a tunable filter at the 1-m telescope of Special Astrophysical Observatory of the Russian Academy of Sciences. We show that the HII region is obscured by neutral material with AV = 2-4 mag. The area with the highest AV is situated to the south-west from the ionizing star and coincides with a maximum detected electron density of >=300 cm(-3). The combination of these results with archive AKARI far-infrared data allows us to estimate the contribution of the front and rear walls to the total column density of neutral material in S235, and explain the three-dimensional structure of the region. The HII region consist of a denser, more compact portion deeply embedded in the neutral medium and the less dense and obscured gas. The front and rear walls of the HII region are inhomogeneous, with the material in the rear wall having a higher column density. We find a two-sided photodissociation region in the dense clump S235 East 1, illuminated by a UV field with G0=50-70 and 200 Habing units in the western and eastern parts, respectively.
BAS: An Answer Selection Method Using BERT Language Model

In recent years, Question Answering systems have become more popular and widely used by users. Despite the increasing popularity of these systems, the their performance is not even sufficient for textual data and requires further research. These systems consist of several parts that one of them is the Answer Selection component. This component detects the most relevant answer from a list of candidate answers. The methods presented in previous researches have attempted to provide an independent model to undertake the answer-selection task. An independent model cannot comprehend the syntactic and semantic features of questions and answers with a small training dataset. To fill this gap, language models can be employed in implementing the answer selection part. This action enables the model to have a better understanding of the language in order to understand questions and answers better than previous works. In this research, we will present the "BAS" (BERT Answer Selection) that uses the BERT language model to comprehend language. The empirical results of applying the model on the TrecQA Raw, TrecQA Clean, and WikiQA datasets demonstrate that using a robust language model such as BERT can enhance the performance. Using a more robust classifier also enhances the effect of the language model on the answer selection component. The results demonstrate that language comprehension is an essential requirement in natural language processing tasks such as answer-selection.
Evaluation of animal performance, feed intake, and economic losses in sheep experimentally infected with Trypanosoma vivax

O Trypanosoma vivax e um protozoario originario do Continente Africano que mesmo nao completando seu ciclo biologico na America do Sul, devido a ausencia da mosca tse-tse, pode levar ruminantes a obito. O presente trabalho teve por objetivo verificar, em ovinos infectados, os efeitos do T. vivax em medidas e indices que caracterizam o desempenho animal, bem como perdas economicas em animais de abate. Para tanto foram utilizados vinte ovinos adultos, machos, inteiros com idade e peso aproximados, criados em confinamento, submetidos ao mesmo manejo e alimentacao, sendo esta balanceada e suplementada com minerais adequados. Os animais foram divididos em dois grupos: o grupo controle (GC) e o grupo infectado (GI) que foi alcancado pela inoculacao endovenosa de 1,3 x 105 tripomastigotas de T. vivax. O consumo de racao foi verificado diariamente, enquanto a conversao alimentar (CA), o indice de eficiencia alimentar (IEA) e o ganho de peso foram obtidos semanalmente. O ganho de peso total (GPT) foi obtido ao final de 70 dias pos-infeccao. A perda economica foi obtida subtraindo do valor esperado (GC) do valor obtido (GI), e a diferenca exposta em porcentagem. O delineamento utilizado foi o de blocos casualizados, para isolar o efeito do peso inicial, foi aplicado o teste “t” de Student a 5% para comparacao de medias. A taxa de letalidade do T. vivax em ambiente experimental controlado foi de 10%, taxa muito inferior ao verificado em surtos naturais. Quanto ao consumo de racao, os grupos apresentaram consumo identico durante todo o periodo, todavia, o GPT do grupo infectado foi significativamente inferior, 50,7% menor quando comparado ao GC. Do mesmo modo, o ganho de peso diario (GPD), conversao alimentar (CA) e o indice de eficiencia alimentar (IEA) do GI foram significantemente inferiores ao GC. Alem disso, os piores indices de CA e IEA coincidiram com os picos parasitemicos e recidivas, provavelmente pela demanda imunologica, e de reparos teciduais. A circunferencia abdominal dos animais infectados foi estatisticamente inferior ao GC, o que pode estar relacionado diretamente a mobilizacao de gordura, alem de possivel efeito negativo na capacidade digestiva. As perdas economicas apenas sobre o peso foram de 24,07%, podendo alcancar 31,66% do valor do lote na ocorrencia de obito. A infeccao por T. vivax afetou negativamente os indices de desempenho animal, ainda que bem nutridos. O T. vivax em ovinos destinados ao abate causou perdas economicas de 31,66%, devido a diminuicao do desempenho e a taxa de obito verificado no grupo infectado.
Atomic scale engineering of carbon nanotubes

Carbon nanotubes, seamless cylinders made from carbon atoms, have outstanding characteristics: inherent nano-size, record-high Young’s modulus, high thermal stability and chemical inertness. They also have extraordinary electronic properties: in addition to extremely high conductance, they can be both metals and semiconductors without any external doping, just due to minute changes in the arrangements of atoms. As traditional silicon-based devices are reaching the level of miniaturisation where leakage currents become a problem, these properties make nanotubes a promising material for applications in nanoelectronics. However, several obstacles must be overcome for the development of nanotube-based nanoelectronics. One of them is the ability to modify locally the electronic structure of carbon nanotubes and create reliable interconnects between nanotubes and metal contacts which likely can be used for integration of the nanotubes in macroscopic electronic devices. In this thesis, the possibility of using ion and electron irradiation as a tool to introduce defects in nanotubes in a controllable manner and to achieve these goals is explored. Defects are known to modify the electronic properties of carbon nanotubes. Some defects are always present in pristine nanotubes, and naturally are introduced during irradiation. Obviously, their density can be controlled by irradiation dose. Since different types of defects have very different effects on the conductivity, knowledge of their abundance as induced by ion irradiation is central for controlling the conductivity. In this thesis, the response of single walled carbon nanotubes to ion irradiation is studied. It is shown that, indeed, by energy selective irradiation the conductance can be controlled. Not only the conductivity, but the local electronic structure of single walled carbon nanotubes can be changed by the defects. The presented studies show a variety of changes in the electronic structures of semiconducting single walled nanotubes, varying from individual new states in the band gap to changes in the band gap width. The extensive simulation results for various types of defect make it possible to unequivocally identify defects in single walled carbon nanotubes by combining electronic structure calculations and scanning tunneling spectroscopy, offering a reference data for a wide scientific community of researchers studying nanotubes with surface probe microscopy methods.
Detection of Speech Events and Speaker Characteristics through Photo-Plethysmographic Signal Neural Processing

The use of photoplethysmogram signal (PPG) for heart and sleep monitoring is commonly found nowadays in smart-phones and wrist wearables. Besides common usages, it has been proposed and reported that person information can be extracted from PPG for other uses, like biometry tasks. In this work, we explore several end-to-end convolutional neural network architectures for detection of human’s characteristics such as gender or person identity. In addition, we evaluate whether speech/non-speech events may be inferred from PPG signal, where speech might translate in fluctuations into the pulse signal. The obtained results are promising and clearly show the potential of fully end-to-end topologies for automatic extraction of meaningful biomarkers, even from a noisy signal sampled by a low-cost PPG sensor. The AUCs for best architectures put forward PPG wave as biological discriminant, reaching 79% and 89.0%, respectively for gender and person verification tasks. Furthermore, speech detection experiments reporting AUCs around 69% encourage us for further exploration about the feasibility of PPG for speech processing tasks.
Employee Job Satisfaction and Organizational Commitment in Nigeria Manufacturing Organizations

This study investigated the relationship between employee job satisfaction and organizational commitment in selected manufacturing firms in Edo state of Nigeria. The sample for this study consisted of 106 employee from the selected manufacturing firms. The data for this research was collected using triangulation of methodologies of both quantitative and qualitative analysis. The Spearman Rank-order correlation coefficient statistical tool was adopted to test the relationships between the variables under review while the multiple regression analysis was adopted to evaluate the moderating effects of corporate culture on the relationship between employee job satisfaction and organizational commitment. Findings from the study revealed that there is a positive and significant relationship between all the dimensions of job satisfaction tested (i.e. pay, promotion, working conditions) and organizational commitment. Based on the findings, it was concluded that employee job satisfaction enhances organizational commitment. Key w ords: Employee, Job Satisfaction, Organizational Commitment, Pay, Promotion, Working Conditions, Affective Commitment, Continuance Commitment, Normative Commitment.
Spectral properties and detectability of supermassive stars in protoglobular clusters at high redshift

Context. Globular clusters (GCs) contain multiple stellar populations with peculiar chemical compositions. Pollution of the intracluster gas by an early population of fast-evolving stars is the most common scenario for explaining the observations. Stars with masses in excess of 1000 M⊙ have recently been suggested as potential polluters. Aims. We investigate the spectral properties of proto-GCs that would host a supermassive star (SMS). Our main goal is to quantify how such a star would affect the integrated light of the cluster, and to study the detectability of such objects. Methods. We computed nonlocal thermal equilibirum atmosphere models for SMS with various combinations of stellar parameters (luminosity, effective temperature, and mass) and metallicities appropriate for GCs, and we predict their emergent spectra. Using these spectra, we calculated the total emission of young proto-GCs with SMS as predicted in a previously reported scenario, and we computed synthetic photometry in UV, optical, and near-IR bands, in particular for the James Webb Space Telescope (JWST). Results. At an effective temperature of 10 000 K, the spectrum of SMSs shows a Balmer break in emission. This feature is due to strong nonlocal thermal equilibrium effects (implied by the high luminosity) and is not observed in “normal” stars. The hydrogen lines also show a peculiar behavior, with Balmer lines in emission while higher series lines are in absorption. At 7000 K, the Balmer break shows a strong absorption. At high effective temperatures, the Lyman break is found in emission. Cool and luminous SMSs are found to dominate the integrated spectrum of the cluster, except for the UV range. The predicted magnitudes of these proto-GCs are magAB ∼ 28 − 30 between 0.7 and 8 μm and for redshifts z ∼ 4 − 10, which is detectable with the JWST. The peculiar observational features of cool SMSs imply that they might in principle be detected in color-color diagrams that probe the spectral energy distribution below and above the Balmer break. Conclusions. Our results show that SMSs should be detectable in proto-GCs if they are luminous and relatively cool. They may be found through deep imaging with the JWST.
The use of tracheal wash and bronchoalveolar lavage in the clinical examination of coughing horses

Our hypothesis is that coughing horses have airway inflammation. Fifty horses – 36 coughing (Co Group)and 14 control (C Group) – of different gender, age, and function were evaluated. Physical and endoscopicexaminations, and cytological analyses of tracheal wash (TW) and bronchoalveolar lavage (BAL) fluids wereundertaken. Higher grades of tracheal mucus were observed in coughing horses. TW fluid neutrophil countwas higher (46.4% ± 30.8% vs. 19.5% ± 22.9%, p=0.003) in the Co group than the C group. In BAL fluid,neutrophil count was higher in the Co group than in the C group (30.3% ± 27.3% vs. 5.0% ± 4.2%, p=0.001,respectively). BAL fluid cytological profile compatible with inflammatory airway disease (IAD), recurrentairway obstruction (RAO), and normal were evidenced in 14 (38.9%), 17 (47.2%), and 5 (13.9%) of theevaluated coughing horses. IAD was diagnosed in 6 horses of the C group. Cough is a clinical sign of airwayinflammation in horses.
Deep Variational Semi-Supervised Novelty Detection

In anomaly detection (AD), one seeks to identify whether a test sample is abnormal, given a data set of normal samples. A recent and promising approach to AD relies on deep generative models, such as variational autoencoders (VAEs), for unsupervised learning of the normal data distribution. In semi-supervised AD (SSAD), the data also includes a small sample of labeled anomalies. In this work, we propose two variational methods for training VAEs for SSAD. The intuitive idea in both methods is to train the encoder to `separate' between latent vectors for normal and outlier data. We show that this idea can be derived from principled probabilistic formulations of the problem, and propose simple and effective algorithms. Our methods can be applied to various data types, as we demonstrate on SSAD datasets ranging from natural images to astronomy and medicine, and can be combined with any VAE model architecture. When comparing to state-of-the-art SSAD methods that are not specific to particular data types, we obtain marked improvement in outlier detection.
B2 agonist (Salbutamol) modulate skin wound healing processes

Wound healing is a complex physiological and dynamic process required the coordination of numerous cell types and biological processes to regenerate damaged tissue and initiate repair which is dependent on a number of inter-related factors. This study was aimed to demonstrate whether the ? 2 receptor has role in wound healing and angiogenesis. A murine wild-type (in vivo), excisional skin wound model was done to demonstrate that activation of ? 2AR delay wound repair, twenty-four male albino mice were used to investigate the effect of the drug on experimental wound healing grossly, histo-pathologically and immune-histochemically compared with vehicle-only controls. The results showed that the rate of wound healing was significantly slower in salbutamol group than in control group (P
Hydrolytic ef fi ciency and isomerization during de-esteri fi cation of natural astaxanthin esters by saponi fi cation and enzymolysis

a CAS Key Laboratory of Experimental Marine Biology, Institute of Oceanology Chinese Academy of Sciences, Qingdao 266071, China b Laboratory for Marine Biology and Biotechnology, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266071, China c University of Chinese Academy of Sciences, Beijing 100049, China d National-Local Joint Engineering Research Center for Haematococcus pluvialis and Astaxanthin Products, Yunnan Alphy Biotech Co., Ltd., Chuxiong 675012, China e Shandong Analysis and Test Center, Jinan 250014, China
A Family Member or Professional Management? The Choice of a CEO and its Impact on Performance

In this study, we explore what kinds of family firms are more likely to have a family CEO or professional CEO, and investigate the performance of CEOs from different backgrounds. The results show that firms with low requirements in managerial skills and a high potential for expropriation are more likely to choose a CEO from the controlling family (nepotism). Our investigation, furthermore, shows that when a firm requires high managerial skills, using a professional CEO can help firm performance, especially if the family has low cash-flow rights and weak control. When there is large opportunity for expropriation in a family firm, the firm's performance will be better if the CEO is a family member and the family has highly persuasive cash-flow rights.
Differential rotation in convective envelopes: constraints from eclipsing binaries

Over time, tides synchronize the rotation periods of stars in a binary system to the orbital period. However, if the star exhibits differential rotation, then only a portion of it can rotate at the orbital period, so the rotation period at the surface may not match the orbital period. The difference between the rotation and orbital periods can therefore be used to infer the extent of the differential rotation. We use a simple parametrization of differential rotation in stars with convective envelopes in circular orbits to predict the difference between the surface rotation period and the orbital period. Comparing this parametrization to observed eclipsing binary systems, we find that in the surface convection zones of stars in short-period binaries there is very little radial differential rotation, with |r∂rln Ω| < 0.02. This holds even for longer orbital periods, though it is harder to say which systems are synchronized at long periods, and larger differential rotation is degenerate with asynchronous rotation.
Gathering on Rings for Myopic Asynchronous Robots with Lights

We investigate gathering algorithms for asynchronous autonomous mobile robots moving in uniform ring-shaped networks. Different from most work using the Look-Compute-Move (LCM) model, we assume that robots have limited visibility and lights. That is, robots can observe nodes only within a certain fixed distance, and emit a color from a set of constant number of colors. We consider gathering algorithms depending on two parameters related to the initial configuration: $M_{init}$, which denotes the number of nodes between two border nodes, and $O_{init}$, which denotes the number of nodes hosting robots between two border nodes. In both cases, a border node is a node hosting one or more robots that cannot see other robots on at least one side. Our main contribution is to prove that, if $M_{init}$ or $O_{init}$ is odd, gathering is always feasible with three or four colors. The proposed algorithms do not require additional assumptions, such as knowledge of the number of robots, multiplicity detection capabilities, or the assumption of towerless initial configurations. These results demonstrate the power of lights to achieve gathering of robots with limited visibility.