Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanistic Study on Magnetite Nanoparticle Formation by Thermal Decomposition and Coprecipitation Routes

The synthesis of poly (acrylic acid) [PAA]-coated superparamagnetic Fe3O4 nanoparticles was carried out in two ways, either by thermal decomposition of an organometallic iron precursor or by coprecipitation of aqueous solutions of ferrous and ferric chloride salts. PAA-coated particles obtained in the former route were spherical, isolated, and nearly monodisperse, whereas aggregates of coated particles formed in the latter route. A nanoparticle formation mechanism is proposed to explain such contrasting morphology. It is based on estimated time scales of different individual steps in the synthesis routes, diffusion of Fe3O4 nanoparticle over a PAA polymer chain, Brownian collision, and coagulation of particles and experimental aging time. We find that the coagulation time scale is smaller in the thermal decomposition route and is hence essentially complete within the experimental aging time. This results in formation of PAA-coated, isolated Fe3O4 nanoparticles. In contrast, the coagulation time scale in c.
Leaning into the Crisis: Managing COVID-19 in Social Services and Behavioral Health Agencies

ABSTRACT In early 2020, the COVID-19 pandemic hit the United States causing significant disruptions in daily life including disruptions for social service and behavioral health agencies. This qualitative, phenomenological study interviewed thirty-seven directors or managers of social service or behavioral health agencies. Agency managers described challenges related to the pandemic and shut down, but they also described opportunities for innovation and change. Agency managers discussion fell into eight themes: funding, employees, space, supplies, policies/protocols, partnerships, mission, and innovation/leaning into the crisis. Implications for administrative practice and policy will be discussed.
Benzo[a]pyrene osteotoxicity and the regulatory roles of genetic and epigenetic factors: A review

Abstract As a ubiquitous environmental pollutant, benzo[a]pyrene (BaP) has been extensively studied for over 80 years. While much research has focused on its genotoxic and carcinogenic effects, considerably less attention has been paid to the osteotoxicity of BaP. Notably, environmental exposure to BaP is associated with skeletal malformation and bone impairment. Recent studies indicated that ancestral BaP exposure can cause transgenerational osteotoxicity in the unexposed F3 offspring. The consequences of environmental BaP/PAH pollution are thus likely to be severe and require re-assessment. We have reviewed the research status of BaP osteotoxicity, and a summary of genetic and epigenetic factors in the regulation of bone metabolism is provided as the basis for elucidating the mechanisms underlying transgenerational BaP osteotoxicity. Based on published studies on this topic, we propose that the transgenerational inheritance of osteotoxicity in fish induced by ancestral BaP exposure is mediated via epigenetically dysregulated bone miRNAs/genes. Two possible epigenetic regulatory circuits of BaP on bone miRNAs and genes are proposed: (i) bone miRNAs are dysregulated via altered DNA methylation and/or histone modifications, affecting target gene expression/activity; (ii) dysregulation of bone genes through altered DNA methylation and/or histone modifications. Our proposed mode of action (MOA) intends to serve as a basis for hypothesis testing in further in-depth studies. We emphasize that future works must verify the proposed MOA to assess its human relevance, and to decipher the underlying mechanism(s) of transgenerational BaP osteotoxicity. Graphical abstract
A process‐oriented, multilevel, multidimensional conceptual framework of work–life balance support: A multidisciplinary systematic literature review and future research agenda

Work–life balance is shaped not only by how individuals manage their personal demands and resources, but also by stressors and work–life balance support mechanisms from external environment encompassing multilevel social systems. Our systematic literature review focuses particularly on the role of work– life balance support , drawing on 384 journal articles and book chapters published between 1960 and 2019 across five research disciplines, including management, applied psychology, industrial relations, family studies and sociology. We make four major contributions to the literature, including: (1) conceptualizing work– life balance support from a process-oriented perspective pertinent to a virtuous cycle of resource investment and return, drawing on the conservation of resources theory and the personal resource allocation framework ; (2) adopting a multilevel approach that construes the interactions in terms of resource changes between individuals’ work–life experiences and their surrounding social systems nested at multiple levels, applying the socio-ecological systems theory ; (3) proposing a multidimensional typology that differentiates the role of actual existence versus subjective perception of support mechanisms as inspired by social support literature; and (4) advocating a pluralist , multi-stakeholder approach to compre-hending and reconciling multiple stakeholders’ shared and competing interests around provision/utilization of support mechanisms based on insights from multidisciplinary literature. Our process-oriented, multilevel and multidimensional framework conceptualizes the critical role of work–life balance support in iterative interactions between individuals and their multilevel social environment through resource changes
Theoretical Study of the Input Impedance and Electromagnetic Field Distribution of a Dipole Antenna Printed on an Electrical/Magnetic Uniaxial Anisotropic Substrate

The present work considers the investigation of the effects of both electrical and magnetic uniaxial anisotropies on the input impedance, resonant length, and fields distribution of a dipole printed on an anisotropic grounded substrate. In this study, the associated integral equation, based on the derivation of the Green’s functions in the spectral domain, is numerically solved employing the method of moments. In order to validate the computing method and the evaluated calculation code, numerical results are compared with available data in the literature treating particular cases of electrical uniaxial anisotropy; reasonable agreements are reported. Novel results of the magnetic uniaxial anisotropy effects on the input impedance and the evaluated electromagnetic field are presented and discussed. This work will serve as a stepping stone for further works for a better understanding of the electromagnetic field behavior in complex anisotropic and bi-anisotropic media.
Analysis of Aircraft Delay Factors at Jeju International Airport

Jeju International Airport is experiencing heavy congestion and delays due to the rapid increase of passengers. As of 2019, delays occurred in 24,052 aircraft, which account for over 14% of all flights operated. This delay rate is about 1.5 times higher than the average delay rate of 9% at domestic airports. The factors which bring delays at Jeju International Airport may include saturation of runway capacity, poor weather conditions, and limitations in facility layout. However, there are insufficient empirical studies on how these factors have affected aircraft delays. This study analyzed the effects of airport operation characteristics, weather conditions, and aircraft operation characteristics on aircraft delay using tower-log data of Jeju International Airport and Aeronautical Climatological Statistics of Jeju International Airport of Aviation Meteorological Office. The result of the analysis shows, aircraft movements per day, aircraft movements per hour, time of day, wind, route and aircraft occupancy rate have a statistically significant effect on aircraft delay, and the relative importance of variables appeared in the order of aircraft movements per day, wind, visual, and aircraft occupancy rate. In addition, these variables were analyzed to have a statistically significant effect on the delay time of aircraft. The results of this research are expected to be used as a basic data for aircraft delay management in airport planning and operation, and contribute to improve methodology of the feasibility study for airport projects.
DESIGN AND DEVELOPMENT OF TETOS APPLICATION FOR LOCATION DETECTION IN SUPPORTING DISASTER VICTIM SEARCHING BASED ON GLOBAL POSITIONING SYSTEM (GPS)

Indonesia is a country with a high level of disasters where during 2005-2015 there were 11,648 hydrometeorological disasters and 3810 geological disasters. In terms of technology, Indonesia is using mobile devices with high growth according to data from the Ministry of Communication and Information. One of the ways to increase the use of mobile devices in assisting disaster management in Indonesia can be developed in the location-based discovery of disaster victims. The location in a mobile device uses a Global Positioning System (GPS) where the existing data is in the form of Latitude and Longitude data. The aim of this research is that the application is expected to assist in the discovery of disaster victims based on the last GPS location. This study focuses on developing a disaster victim search application based on the Android operating system. Development uses the Agile Model by using Black-box Testing and White-Box Testing techniques, where the type of testing uses Unit Testing, Integration Testing, and Acceptance Testing with qualitative data. The results of the research obtained an application in the form of a prototype where there are several corrective inputs obtained from Acceptance Testing. This study is then expected that the application can be applied in disaster management systems in Indonesia which of course can be supported by binding rules so that the data obtained can be utilized optimally.
Short-Term Load Forecasting Using Encoder-Decoder WaveNet: Application to the French Grid

The prediction of time series data applied to the energy sector (prediction of renewable energy production, forecasting prosumers’ consumption/generation, forecast of country-level consumption, etc.) has numerous useful applications. Nevertheless, the complexity and non-linear behaviour associated with such kind of energy systems hinder the development of accurate algorithms. In such a context, this paper investigates the use of a state-of-art deep learning architecture in order to perform precise load demand forecasting 24-h-ahead in the whole country of France using RTE data. To this end, the authors propose an encoder-decoder architecture inspired by WaveNet, a deep generative model initially designed by Google DeepMind for raw audio waveforms. WaveNet uses dilated causal convolutions and skip-connection to utilise long-term information. This kind of novel ML architecture presents different advantages regarding other statistical algorithms. On the one hand, the proposed deep learning model’s training process can be parallelized in GPUs, which is an advantage in terms of training times compared to recurrent networks. On the other hand, the model prevents degradations problems (explosions and vanishing gradients) due to the residual connections. In addition, this model can learn from an input sequence to produce a forecast sequence in a one-shot manner. For comparison purposes, a comparative analysis between the most performing state-of-art deep learning models and traditional statistical approaches is presented: Autoregressive-Integrated Moving Average (ARIMA), Long-Short-Term-Memory, Gated-Recurrent-Unit (GRU), Multi-Layer Perceptron (MLP), causal 1D-Convolutional Neural Networks (1D-CNN) and ConvLSTM (Encoder-Decoder). The values of the evaluation indicators reveal that WaveNet exhibits superior performance in both forecasting accuracy and robustness.
Evaluation of Long‐Term Temperature Trend and Variability in CMIP6 Multimodel Ensemble

This study conducts a robust assessment of the Coupled Model Intercomparison Project Phase 6 to capture the observed temperature trends and variability at global and regional scales. The warming rate in the second half of the twentieth century (0.19°C/decade) is twice as large as in the full analysis period (1901–2014; 0.10°C/decade). Multidecadal climate variability results in considerable uncertainties in the regional temperature trend, but the multidecadal variability does not represent a statistically significant trend. Globally, the spatial pattern of trends is most similar among ensemble members of the same model, then among climate models, and the least similar between models and observations. The structural uncertainty and internal variability of climate models provide a range of temperature trends that generally encompass the regional scale observations. Some single model large ensembles also have variability comparable to the multimodel large ensemble, encompassing the regional scale observations.
Dose-rate conversion factors: update

In the field of luminescence and electron spin resonance dating, dose rate conversion factors are widely used to convert concentrations of radioactive isotopes to dose rate values. These factors are derived from data provided by the National Nuclear Data Center of the Brookhaven National Laboratory, which are compiled in Evaluated Nuclear Structure Data Files (ENSDF) and Nuclear Wallet Cards. The recalculated dose rate conversion factors are a few percent higher than those previously published, except for beta and gamma emissions of the isotopes of the U-series decay chains.
Literature analysis of artificial intelligence in biomedicine

Artificial intelligence (AI) refers to the simulation of human intelligence in machines, using machine learning (ML), deep learning (DL) and neural networks (NNs). AI enables machines to learn from experience and perform human-like tasks. The field of AI research has been developing fast over the past five to ten years, due to the rise of ‘big data’ and increasing computing power. In the medical area, AI can be used to improve diagnosis, prognosis, treatment, surgery, drug discovery, or for other applications. Therefore, both academia and industry are investing a lot in AI. This review investigates the biomedical literature (in the PubMed and Embase databases) by looking at bibliographical data, observing trends over time and occurrences of keywords. Some observations are made: AI has been growing exponentially over the past few years; it is used mostly for diagnosis; COVID-19 is already in the top-3 of diseases studied using AI; China, the United States, South Korea, the United Kingdom and Canada are publishing the most articles in AI research; Stanford University is the world’s leading university in AI research; and convolutional NNs are by far the most popular DL algorithms at this moment. These trends could be studied in more detail, by studying more literature databases or by including patent databases. More advanced analyses could be used to predict in which direction AI will develop over the coming years. The expectation is that AI will keep on growing, in spite of stricter privacy laws, more need for standardization, bias in the data, and the need for building trust.
Apparent formation constants of Pu(IV) and Th(IV) with humic acids determined by solvent extraction method

Abstract Apparent formation constants of Pu(IV) and Th(IV) with two kinds of humic acids were determined in 0.1 M NaClO4 at 25 ºC using a solvent extraction method with thenoyltrifluoroacetone in xylene. The acid dissociation constants of humic acids were also measured by potentiometric titration and used as the degree of dissociation for calculating the formation constants. The effect of solution conditions, such as the pH, the initial metal and humic acid concentrations, and the ionic strength, on the formation constants was examined. The obtained data were compared with the ones in the literature.
Analysis, control, and modeling of the three‐port converter without port voltage constraint for photovoltaic/battery system application

For a photovoltaic (PV)/battery power system consisting of PV module, energy storage system, and local load, using a three‐port converter (TPC) instead of several single‐input converters is more desirable, such as simpler circuit, higher efficiency, lower cost, and centralized control without communication circuit. In this paper, a TPC is proposed and analyzed, which includes operating modes, steady‐state performance, and parameter design. Compared with other converters, the proposed TPC has a low cost, compact structure, and a more flexible voltage relationship among all ports. Moreover, energy management and control methods are further proposed for PV/battery systems based on the proposed converter, which can achieve maximum power point tracking (MPPT) of PV module and constant output voltage. In order to design the control loop and realize multivariable optimal control, a small‐signal model of the converter is obtained in each operation mode. Then a detailed decoupling design approach based on a small‐signal model is provided to allow a separate controller design for the proposed converter. Finally, the validity of the proposed converter and its energy management and control method are verified by experimental results.
Modeled 3D-Structures of Proteobacterial Transglycosylases from Glycoside Hydrolase Family 17 Give Insight in Ligand Interactions Explaining Differences in Transglycosylation Products

The structures of glycoside hydrolase family 17 (GH17) catalytic modules from modular proteins in the ndvB loci in Pseudomonas aeruginosa (Glt1), P. putida (Glt3) and Bradyrhizobium diazoefficiens (previously B. japonicum) (Glt20) were modeled to shed light on reported differences between these homologous transglycosylases concerning substrate size, preferred cleavage site (from reducing end (Glt20: DP2 product) or non-reducing end (Glt1, Glt3: DP4 products)), branching (Glt20) and linkage formed (1,3-linkage in Glt1, Glt3 and 1,6-linkage in Glt20). Hybrid models were built and stability of the resulting TIM-barrel structures was supported by molecular dynamics simulations. Catalytic amino acids were identified by superimposition of GH17 structures, and function was verified by mutagenesis using Glt20 as template (i.e., E120 and E209). Ligand docking revealed six putative subsites (−4, −3, −2, −1, +1 and +2), and the conserved interacting residues suggest substrate binding in the same orientation in all three transglycosylases, despite release of the donor oligosaccharide product from either the reducing (Glt20) or non-reducing end (Glt1, Gl3). Subsites +1 and +2 are most conserved and the difference in release is likely due to changes in loop structures, leading to loss of hydrogen bonds in Glt20. Substrate docking in Glt20 indicate that presence of covalently bound donor in glycone subsites −4 to −1 creates space to accommodate acceptor oligosaccharide in alternative subsites in the catalytic cleft, promoting a branching point and formation of a 1,6-linkage. The minimum donor size of DP5, can be explained assuming preferred binding of DP4 substrates in subsite −4 to −1, preventing catalysis.
Do extended school day programs affect performance in college admission tests?

We assess the effects of a Brazilian extended high school day program on college admission test scores. The program entails an increase in Math/Science and Language class time, and the introduction of extra-class activity time. We exploit variation in program implementation timing to apply a difference-in-differences strategy and an event-study approach. Results show positive large effects on test scores and suggest that these effects are likely driven by increased class and extra-class activity hours. Moreover, the program affects not only scores in subjects for which it contemplates increased class time, but also in Humanities. Finally, we are able to show that increased time dedicated to academic-related extra-class activities works as a multiplier of program effects. In fact, these additional hours spent in complementary activities make the magnitude of program effects double from 0.092-0.150 to 0.180-0.317 standard deviation.
Children and the Internet: Effects, Outcomes, and Solutions

The internet was a phenomenon introduced to the public in the early 1990s that allowed people to communicate across substantial distances. Today, the internet is used daily by millions of people worldwide. The internet is an interactive platform used for social media, online gaming, shopping, and many other outlets. The implications of the internet reach far beyond other forms of passive media such as television and radio. The powerful appeal of the internet has led many to question its consequences. The internet has been found to have the potential to change the entire way that one lives. This includes how they perceive their own health, well-being, and stress levels When considering the internet’s strong effect on adults, researchers are left questioning what impacts it can have on children. This area is beginning to see increased rates of interest, as younger people are even higher consumers of the internet than are members of older generations (Veenhof, 2006). As children are arguably the most vulnerable cohort, research on children and the internet is of high importance. The internet has become a feature of everyday living with limitless possibilities and unfiltered learning opportunities for children. Through the internet, children have access to worlds of knowledge and communication pathways. There is a controversial debate surrounding the topic of whether the benefits of the internet outweigh the harms of its use. Some believe that the internet can provide children with a cognitive advantage and excelled social skills. Others are cautious of the effect that early exposure to inappropriate content online can have on developing children (Albanese, 2020, p. 101). If left uncontrolled and unmediated, the internet has the potential to harm future generations of children because of the unfiltered nature of material posted online.
A non‐destructive approach to collect nest material data using photographs

The materials that birds use to build their nests have a profound effect on nest quality and consequently on the builder ’ s reproductive success. Given that the common method to quantify nest materials by dismantling nests takes time and limits study species, we developed a non-destructive and much quicker method for quantifying nest materials using nest photographs. Using our photographic method, the proportions of the main materials in 45 Blue Tit Cyanistes caeruleus and 20 Dartford Warbler Sylvia undata nests, including grass, heather and moss, matched those found by dismantling the nests, but the proportions of rarer animal-derived materials differed between the two methods. Provided that there is an initial calibration with the dismantling method, the photographic method offers two key advantages: a reduction in the time it takes to quantify the major components of nests, and application to previously inaccessible data, including museum collections. Together, these advantages encourage further study of nesting materials and enable a better understanding of avian nest diversi ﬁ cation.