Miracle-dz/UniFAR-FTUs huggingface dataset:
Early childhood preservice teachers’ self-efficacy related to inclusion and professional roles via a co-taught field-based course

ABSTRACT This study focuses on the self-efficacy of preservice teachers enrolled in a co-taught early childhood education course on special education. The course was developed to increase awareness and access to special education through a field-based co-taught practicum course. Instructors from general education and special education shared planning and teaching roles to model collaborative practices for future early childhood educators. Data from focus groups, interviews, and a post-then-pre instrument were used to explore preservice teachers’ self-efficacy related to comfort with inclusion, perspective-taking, and professional roles as well as their experiences participating in the co-taught course. Recommendations for research related to supporting self-efficacy and teacher education are shared.
Poly-diagnostic study of low pressure microwave plasmas

The axial dependency of the central-axis value of the heavy particle density and temperature of surface-wave produced plasmas is studied using Rayleigh scattering (RyS). The plasma is generated at a frequency of 2.45 GHz in argon by a surfatron operating under the standard settings of an absorbed power of 45 W, a flow rate of 50 sccm and a gas pressure ranging between 0.5-100 mbar. By using a two dimensional intensified CCD array the influence of false stray light could be eliminated; a major disturbing factor in the determination of the Rayleigh signal. In order to trace the energy fluxes that determine the gas temperature Thomson scattering (TS) is performed to determine the properties of the electron gas. It is found that the gas temperature, Tg, depends on the wall temperature and the product of the gas pressure and the electron pressure. The later implies that Tg follows the electron density axially, meaning that it is highest at the launcher and decreases monotonically in the wave propagation direction. For the gas pressure of 20 mbar the maximum gas temperature is around Tg = 750 K close to the launcher, for lower pressures Tg is lower. The extrapolation of Tg toward the end of the plasma column leads to a temperature of about 350 K. This study reveals that, for the argon plasmas under study, the central-axis values of the gas temperature are determined by the balance between the heating of the gas by means of elastic electron collisions and the cooling due to heat conduction from the center to the wall. Based on "Rayleigh scattering on a microwave surfatron plasma to obtain axial profiles of the atom density and temperature. " S. Hübner, E. Iordanova, J.M. Palomares Linares, E.A.D. Carbone and J.J.A.M. van der Mullen, (2012), EPJ Applied Physics, 58(02), 20802-1/10. [30, 67]. Rayleigh Scattering on a Surfatron plasma
Quantitative investigation on the impact of injection timing on soot formation in a GDI engine with a customized sectional method

Soot engine-out emissions are no longer a prerogative of Diesel engines. Emission regulations related to Gasoline units aim to curb the soot emissions along with other pollutants. In this scenario, Computational Fluid Dynamics (CFD) is a very promising research and development tool to explore the influence of engine design and operational parameters, as well as of the fuel chemical nature, on the particulate matter formation. Among the soot models, the Sectional Method is an advanced resource to provide information on Particle Number, Particulate Mass and Particle Size Distribution. In this study, the Sectional Method is applied in conjunction with a customized soot library, where the source terms governing the soot sections transport equations are stored. The library is computed via chemical kinetics simulation of a 0D constant pressure reactor, which provides fuel-related coefficients for each individual source term over the entire range of conditions experienced by the 3D-CFD model. 3D-CFD simulations are then carried out for three different injection timings without case-by-case tuning. Numerical results are then compared to the experimental dataset by using a consistent methodology. A satisfactory agreement between 3D-CFD results and experimental measurements is reached for soot mass and particle numbers, while the particle size distribution function is only partially reproduced. Soot-related quantities are thoroughly analyzed for each of the examined injection strategies to understand the mechanisms leading to soot formation and emissions.
An Enhanced Adaptive Bernstein Collocation Method for Solving Systems of ODEs

In this paper, we introduce two new methods to solve systems of ordinary differential equations. The first method is constituted of the generalized Bernstein functions, which are obtained by Bernstein polynomials, and operational matrix of differentiation with collocation method. The second method depends on tau method, the generalized Bernstein functions and operational matrix of differentiation. These methods produce a series which is obtained by non-polynomial functions set. We give the standard Bernstein polynomials to explain the generalizations for both methods. By applying the residual correction procedure to the methods, one can estimate the absolute errors for both methods and may obtain more accurate results. We apply the methods to some test examples including linear system, non-homogeneous linear system, nonlinear stiff systems, non-homogeneous nonlinear system and chaotic Genesio system. The numerical shows that the methods are efficient and work well. Increasing m yields a decrease on the errors for all methods. One can estimate the errors by using the residual correction procedure.
Profiles of U.S. Law Enforcement Officers’ Physical, Psychological, and Behavioral Health: Results From a Nationally Representative Survey of Officers 

Law enforcement officers’ health and wellness is important at the individual and community levels in terms of maintaining a fit workforce to uphold the mission of public safety. The current study was designed to assess officer wellness across the U.S. From a nationally representative random sample of 1,135 local and state agencies, a random, probability-based sample of officers was selected, oversampling for female officers. Latent class analyses were conducted to assess wellness profiles based on a set of eleven physical, psychological, and behavioral health indicators for 2,232 officers. Personal and professional characteristics were included as auxiliary variables in models of the resulting classes. Results from this sample indicated that over two-thirds of officers fit a healthy profile, whereas one in four officers presents with moderate health concerns and nearly 6% are classified in a profile of broad health concerns. In this sample, sexual assault in childhood, greater exposure to critical incidents, working a current rotation schedule, and being female were characteristics associated with broad health concerns. Emotional and/or physical assault in childhood, greater exposure to critical incidents, and being female were characteristics associated with moderate health concerns, whereas older age and being Hispanic were protective factors. In sum, full-time sworn law enforcement officers across the U.S. are reasonably healthy but their exposures to stressful situations put them at increased risk particularly in terms of post-traumatic stress, risky drinking, and suicidality. These results are important for agency administrators and policymakers to consider in terms of wellness programs, prevention efforts and budget allocations.
A hybrid deep transfer learning-based approach for COVID-19 classification in chest X-ray images

The COVID-19 pandemic is a severe public health hazard. Hence, proper and early diagnosis is necessary to control infection progression. We can diagnose this disease by employing a chest X-ray (CXR) screening, which is ordinarily cheaper and less harmful than a Computed Tomography scan (CT scan) and is continuously accessible in small or rustic hospitals. Since the COVID-19 dataset is inadequate and cannot be strictly distinguished from CXR, Deep Transfer Learning (DTL) models can be used to diagnose coronavirus even with access to a small number of images. In this paper, we presented an approach to diagnosis COVID-19 using CXR images based on the concatenated features vector of the three DTL structures and soft-voting feature selection procedure, including Receiver of Curve (ROC), Entropy, and signal-to-noise ratio (SNR) techniques. Our hybrid model reduces the feature vector size and classifies it in optimize manner to improve the decision-making process. A collection of 2,863 CXR images comprising normal, bacterial, viral, and COVID-19 cases were prepared in JPEG format from the Medical Imaging Center of Vasei Hospital, Sabzevar, Iran. The proposed approach obtained an Accuracy of 99.34%, Sensitivity of 99.48%, Specificity of 99.27% while having a far fewer number of trainable parameters in contrast to its counterparts. Compared to the latest similar methods, the diagnosis accuracy has increased from 1.5 to 2.2%. The comparative experiment reveals the advantage of the suggested COVID-19 classification pattern based on DTL over other competing schemes.
A REVIEW OF SUPERVISED MACHINE LEARNING ALGORITHMS TO CLASSIFY DONORS FOR CHARITY

Abstract--Machine Learning has several supervised algorithms which have the capability for potential prediction based on the data collected from external or internal sources. Different supervised algorithms are employed to find the best-chosen algorithms based on the preliminary results and then optimized further to find the best outcomes. Non-profit organization survives on donations and predicting the individual’s income helps to identify how big a donation can be made by the individuals. Therefore, it helps whether to approach to the individuals or not based on their income. With the help of this paper, different algorithms are constructed and discussed based on their accuracy, complexity, speed, and overfitting to choose the best candidate model. Best optimized model helps to predict the individual’s income efficiently and help making decision whether to reach out to them or not which helps in the non-profit organization survival.
Meteorological Environments Associated With California Wildfires and Their Potential Roles in Wildfire Changes During 1984–2017

California has experienced more wildfires in recent years, resulting in huge economic losses and threatening human health. Clarifying the meteorological environments of wildfires is foundational to improving the understanding and prediction of wildfires and their impacts. Here, 1,535 California wildfires during 1984–2017 are systematically investigated. Based on two key meteorological factors—temperature and moisture anomalies—all wildfires are classified into four groups: hot‐dry, hot‐wet, cold‐dry, cold‐wet. Most (∼60%) wildfires occurred on hot‐dry days. Compositing the meteorological environments of the four groups shows that persistent high pressure and strong northeasterly wind descending from inland favor hot‐dry conditions for wildfires. Self‐organizing map analysis lends confidence in the large‐scale meteorological pattern dominating hot‐dry wildfires in California. Meteorological anomalies also influence wildfire size through their magnitudes, with moisture anomaly explaining the largest fraction (∼69%) of variability in wildfire sizes. In addition, 12.2% of wildfires occurred on hot‐wet days, which may be related with lightning flashes. More lightning tends to trigger wildfires, but the wet condition helps to suppress the wildfire sizes. Total burned area by wildfires has significantly increased by ∼3.6% per year, indicating a doubling of burned area in 2017 relative to 1984, mainly dominated by hot‐dry wildfires in summer. Drying and warming in conjunction with strengthening of the high pressure in summer and fall have the potential to support more frequent and larger hot‐dry wildfires in California during the past several decades.
Protein intake and loss of proteostasis in the eldery

Ageing is a process of declining bodily function and a major risk factor of chronic diseases. The declining bodily function in ageing can cause loss of proteostasis (protein homeostasis), which is a balance between protein synthesis, folding, modification and degradation. For the elderly, adequate protein intake is necessary to prevent sarcopenia, frailty, fracture and osteoporosis as well as reduced resistance to infection. However, increasing the protein intake can enhance the risk of oxidized protein formation, loss of proteostasis and degenerative disorder occurrence. On the other hand, several studies show that protein restriction would increase longevity. The aim of this review was to explain the importance of determining the right amount and composition of protein intake for the elderly. Oxidative stress and molecular mechanism of proteostasis loss in ageing cells as well as its suppression pathway by protein restriction are discussed in this review. Keywords: ageing, dietary proteins, mTOR, oxidative stress, proteostasis loss
Relationship between Financial Factors and Access to Health Care and Quality of Life for HIV / AIDS Patients

Introduction: Patients with HIV-AIDS experience various problems, one of which is related to financial factors and access to health services, this will also affect the patient's quality of life. The purpose of this study was to analyze the relationship between financial factors and access to health services. Method: This was a cross-sectional study with a sample size of 101 respondents who were selected using simple random sampling technique. The independent variable in this study is income and access to services, while the dependent variable in this study is quality of life. The instrument used was a demographic questionnaire and Health-Related Quality of Life, the data were analyzed using chi square with a significance level of p <0.05. Results: The results showed that there was a significant relationship between income (p = 0.044) and the availability of infrastructure (p = 0.003) with the quality of life of HIV-AIDS patients. Conclusion: The financial and access to healthcare factors are related to the quality of life of clients with HIV-AIDS, so that patients with good quality of life will show that the level of fulfillment of needs and access to health services is also good.
Design and experimental verification of compact dual‐element quasi‐self‐complementary ultra‐wideband multiple‐input multiple‐output antenna for wireless applications

In this article, a compact dual‐element quasi‐self‐complementary (QSC) multiple‐input multiple‐output (MIMO) antenna for ultra‐wideband (UWB) communication is presented. The overall area of the antenna is 32 × 39 mm2 (0.26 λl × 0.31 λl, where, λl is at lowest cutoff frequency) which is designed on low cost FR‐4 substrate. It has two half‐cut flower shaped (HCFS) radiators on its top which is formed by merging four ellipses of same eccentricity and then splitted in two halves at the center. On the other side, quasi‐self‐complementary phenomenon is introduced via etching slots which are complement to the radiator's shape. Also, a rectangular slit on the ground plane just below the feed line improves impedance matching. The proposed antenna operates in the range of frequencies 2.43GHz to 11.2GHz with high inter‐port isolation of greater than ‐19 dB over entire frequency of interest. Moreover, the stability of the design is validated in terms of diversity parameters [envelop correlation coefficients (ECC), channel capacity loss (CCL), mean effective gain (MEG), and Effective diversity gain (EDG)] and radiation parameters which makes it suitable for UWB‐MIMO wireless application.
Defying Europe? The Euroscepticism of radical right and radical left voters in Western Europe

ABSTRACT Radical Left Parties (RLPs) and Radical Right Parties (RRPs) parties have adopted similar platforms over EU economic integration, rejecting further budgetary/economic authority transfers towards the EU. During the Euro crisis, EU-led management of the recession, constraining budgetary independency, may have worsened public concerns over the loss of state sovereignty on economic prerogatives. Although RLPs and RRPs have conveyed to voters anti-EU budgetary messages, we do not know if the electors have responded to this cueing activity. Thus, this paper seeks to understand whether, during the Euro crisis, voters supported the RLPs and RRPs due to anti-EU budgetary positions or not in Western Europe. On the one hand, we show that voters have electorally rewarded RRPs on the anti-EU budgetary issues, profiling themselves as Euro-rejectionists. On the other hand, we found that voters have not significantly matched RLP anti-EU budgetary stances, perhaps expressing favourable orientations towards the EU inter-state solidarity.
Small-Medium Enterprises Stickiness on the Traditional Accounting Systems

This study aims to identify the causes of the limited absorption of the accounting information system (AIS) in SMEs that are members of the UPPKS (Upaya Peningkatan Pendapatan Keluarga Sejahtera -in English: Business to Increase Prosperous Family Income) Program in Medan City. This research is necessary because, inpreliminary research observations, the researcher found that 81.30% of SMEs who are members of the UPPKS Medan City have not used AIS in accounting records. Eventhough in this digital era, the use of information technology is regular in every activity. The sample of this research is the SMEs that are members of the UPPKS in Medan City. UPPKS is a family empowerment program to maximize economic income through entrepreneurial activities. The program is organized by the Government of the Republic of Indonesia through the National Population and Family Planning Agency. The data collection in this study was using an electronic questionnaire collected using the snowball method. With simple random sampling, this study managed to collect 122 data. The entire data was then analyzed using descriptive statistics. The results showed that the SMEs that were members of the UPPKS in Medan City experienced Knowledge Stickiness. This condition hinders the performance of SMEs in utilizing AIS to achieve its competitive advantage. This study recommends UPPKS administrators to be able to manage SMEs' knowledge to be able to absorb knowledge from external parties and exploit it to produce measurable innovations. The innovation in question can generate increased economic benefits among SMEs.
Predicting mean annual and mean monthly streamflow in Colorado ungauged basins

River managers often need estimates of streamflow for ungauged streams. These estimates can be used in water rights acquisitions, in‐stream flow management, habitat assessment, water quality planning, and stream hazard identification. This publication describes new regression models for predicting mean annual and mean monthly streamflow in Colorado. Unlike previous regional regression studies, the new models incorporate snow persistence (SP), the fraction of time a watershed remains snow covered. Models were developed using streamflow data from 131 watersheds with drainage areas <1,500 km2, no transbasin diversions, and <10% urban area. In addition to SP, topographic, climate, geologic, and hydrologic region variables were used in model predictions. All new models had very good performance, with <6% absolute bias and stronger performance compared to current regional regression models in StreamStats. The mean annual model had the strongest performance, with Nash‐Sutcliffe efficiency coefficient (NSE) of 0.93 and <2% absolute bias. Mean monthly models had best performance during snowmelt runoff months (May‐Jul; NSE ≥0.79; absolute % bias ≤ 4) and weaker performance during low flow months (Aug‐Apr; NSE ≥ 0.59; % bias ≤ 5). Tests of the mean annual model using decadal average streamflow from 1910s to 2000s show very good performance (NSE > 0.75), but predictions were biased low by 14–28% in wetter decades. All equations and coefficients needed to run the models are presented in the publication appendix, and the associated data release includes the spatial data and model code, which can be applied using R or within an R‐based Shiny web app.
Teaching Journalists About Violence Against Women Best Reportage Practices: An Australian Case Study

ABSTRACT Media reporting of violence against women (VAW) has the potential to contribute to improving the community’s understanding and response to this social problem. However, journalists are not immune to gender biases and myths concerning VAW. Both can affect how the subject is framed. We look at an Australian training programme implemented to improve VAW news reporting practices such as including social context, family violence experts and help-seeking information for survivors, challenging myths and avoiding perpetrator exoneration and victim-blaming. We compare journalists’ reporting before and after training and also compare the trained reporters’ content with a matched comparison sample written by untrained journalists to see if training translates into best practice reporting. We conclude that reportage practices have improved overall in recent years and that the training model, in which participants were selected to take part, appears to be effective in improving some key elements of best practice reporting, but some areas of concern remain. We recommend more targeted programmes with curriculum additions to better address some reporting deficiencies we identify.
Changes in the Tree-Ring Width-Derived Cumulative Normalized Difference Vegetation Index over Northeast China during 1825 to 2013 CE

Vegetation coverage is very important in terrestrial ecosystems and climate systems. However, the observational record of the normalized difference vegetation index (NDVI), which started in the 1980s when satellites became widely used, is too short to investigate the history of variation in vegetation coverage beyond the modern observation period. Here, we present a 189 y vegetation coverage series based on a total of 349 Mongolian pine (Pinus sylvestris var. mongolica Litv) cores from seven locations from the central–western Da Hinggan Mountains (CW–DHM), northeastern China. We found a significant relationship between tree-ring width and the regional cumulative normalized difference vegetation index (CNDVI). The correlation between the ring-width chronology and the regional June–July CNDVI (CNDVIJJ) was significant, with r = 0.68 (n = 32, p < 0.001) and an explained variance of 45.8% (44.0% after the adjustment for the loss of the degree of freedom). On this basis, we designed a transfer function to reconstruct the CNDVIJJ for the CW–DHM region from 1825 to 2013 CE (Common Era). During the last 189 years, there were 28 years with high CNDVIJJ values, and another 28 years with low values. We also observed CNDVIJJ fluctuations at the inter-annual and decadal time scales, including eight low value periods and nine high value periods. Based on our analysis, the variation in CNDVI is associated with climatic factors, such as temperature, precipitation and the Palmer Drought Severity Index (PDSI), which combines both temperature and precipitation. From 1950 to 2002 CE, the CNDVI showed a noticeable decreasing trend in the CW–DHM region, whereas after 2003 CE, the CNDVI exhibited an apparent increase, which has also been observed in southern Central Siberia, eastern Mongolia and northeastern and eastern China, indicating that the CNDVI change in the CW–DHM is related to climate change in the local region and in some parts of Asia.