Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationships between the planetary boundary layer height and surface pollutants derived from lidar observations over China: regional pattern and influencing factors

Abstract. The frequent occurrence of severe air pollution episodes in China has been a great concern and thus the focus of intensive studies. Planetary boundary layer height (PBLH) is a key factor in the vertical mixing and dilution of near-surface pollutants. However, the relationship between PBLH and surface pollutants, especially particulate matter (PM) concentration across China, is not yet well understood. We investigate this issue at ∼1600 surface stations using PBLH derived from space-borne and ground-based lidar, and discuss the influence of topography and meteorological variables on the PBLH–PM relationship. Albeit the PBLH–PM correlations are roughly negative for most cases, their magnitude, significance, and even sign vary considerably with location, season, and meteorological conditions. Weak or even uncorrelated PBLH–PM relationships are found over clean regions (e.g., Pearl River Delta), whereas nonlinearly negative responses of PM to PBLH evolution are found over polluted regions (e.g., North China Plain). Relatively strong PBLH–PM interactions are found when the PBLH is shallow and PM concentration is high, which typically corresponds to wintertime cases. Correlations are much weaker over the highlands than the plains regions, which may be associated with lighter pollution loading at higher elevations and contributions from mountain breezes. The influence of horizontal transport on surface PM is considered as well, manifested as a negative correlation between surface PM and wind speed over the whole nation. Strong wind with clean upwind air plays a dominant role in removing pollutants, and leads to obscure PBLH–PM relationships. A ventilation rate is used to jointly consider horizontal and vertical dispersion, which has the largest impact on surface pollutant accumulation over the North China Plain. As such, this study contributes to improved understanding of aerosol–planetary boundary layer (PBL) interactions and thus our ability to forecast surface air pollution.
Evaluation of Illinois Bridge Deterioration Models

The National Bridge Inventory bridge inspection system ranks the condition of bridge components on a scale of zero to nine. The resulting condition ratings represent an important element considered in deciding measures for bridge maintenance, repair, and rehabilitation. Thus, forecasting future condition ratings well is critical to reliable planning for these activities and estimating the costs. The Illinois Department of Transportation currently has deterministic models for this purpose. This study’s objective is to review the current models using condition rating histories gathered from 1980 to 2020 in Illinois for the following bridge components: deck, superstructure, substructure, culvert, and deck beam. The results show the current Illinois Department of Transportation models are inadequate in forecasting condition ratings, producing overestimates of the transition times between two condition rating levels for these components / systems, except for the deck beam, which is underestimated. It is recommended that the mean transition times found in this study from condition rating histories are used to replace the current models as a short-term solution. Further research is recommended to develop probabilistic models as a long-term solution to address observed significant variation or uncertainty in condition rating and transition times between condition rating levels.
Non-Parametric Bayesian Subspace Models for Acoustic Unit Discovery

This work investigates subspace non-parametric models for the task of learning a set of acoustic units from unlabeled speech recordings. We constrain the base-measure of a Dirichlet-Process mixture with a phonetic subspace—estimated from other source languages—to build an educated prior, thereby forcing the learned acoustic units to resemble phones of known source languages. Two types of models are proposed: (i) the Subspace HMM (SHMM) which assumes that the phonetic subspace is the same for every language, (ii) the Hierarchical-Subspace HMM (H-SHMM) which relaxes this assumption and allows to have a language-specific subspace estimated on the unlabeled target data. These models are applied on 3 languages: English, Yoruba and Mboshi and they are compared with various competitive acoustic units discovery baselines. Experimental results show that both subspace models outperform other systems in terms of clustering quality and segmentation accuracy. Moreover, we observe that the H-SHMM provides results superior to the SHMM supporting the idea that language-specific priors are preferable to language-agnostic priors for acoustic unit discovery.
Growing Racial Resilience: The Impact of Mindsets on the Development of Prejudice

Previous studies have indicated a strong link between lay theories and the development of prejudice. The purpose of this article is to review past studies that have examined the relation between a specific lay theory (mindset) and the development of prejudice, as well as highlight areas for future research that will contribute to our theoretical understanding of mindsets (and their relation to prejudice). Specifically, we highlight the need for future studies to examine mindsets from the target’s perspective, to explore how contextual cues may influence the development of mindsets over time, and to observe how mindsets motivate collective action among majority group members. Future studies focused on these areas will deepen the field’s theoretical understanding of the impact of mindsets on the development of prejudice. Such knowledge, in turn, can inform the construction of future mindset interventions that foster sustainable and concrete improvements in interracial relations and ultimately promote racial equity.
Free and Fair? The Differential Experiences of Voting Barriers and Voting Policies in American Midterm Elections

In this research note, we provide evidence about burdens people face when voting and who benefits from policies designed to mitigate those burdens. Using pre-and-post 2018 midterm elections panel surveys in Wisconsin, we show that Black voters estimate greater time getting to the polls and Hispanic voters report longer wait times once they are there. Regarding who takes advantage of policies purported to ease these burdens on voting—early voting, voting by mail, and absentee voting—our analysis reveals that that those facing temporal disadvantages are not the groups benefiting from these electoral policy affordances. Free and fair elections require, at minimum, equitable voting processes that do not unduly burden particular groups of people. In the United States, this fundamental democratic condition depends upon what happens in thousands of polling locations across the nation on Election Day. Voter experiences on the way to—and at—their polling locations depend largely upon the resources and regulatory infrastructure provided by state and local governments. Not only are people who live further away from their polling place less likely to vote (Dyck & Gimpel, 2005 ) but also members of groups who wait longer in line once they get there are less likely to turnout to vote (Gimpel &
Examination anxiety: a school-based intervention

ABSTRACT The general issue of children’s mental health has become a growing concern in the UK in recent decades. There has been a specific concern about the increased stringency and pressure of formal educational assessments with some students reported as, experiencing high levels of test anxiety. This paper investigated a school-based test anxiety intervention Beating Exam Anxiety Together (BEAT) developed by educational psychologists from Kent EPS and delivered to two secondary (high) schools in the North-West of England for students aged 15–16 years. No comparison group was used, instead single participant cases were observed at two points: one before the delivery of BEAT and another after the intervention. A mixed methods approach was employed to provide a rich account on how the intervention was delivered. Quantitative data from the experimental study, using the Revised Test Anxiety Scale (RTA), show that 13 out of 14 participants reported a reduction in test anxiety post intervention. Qualitative data strongly support the quantitative findings, highlighting that participants feel better equipped to manage their test anxiety levels and feel better prepared to cope in an exam situation. Implications for pastoral staff supporting in schools, and future research, are considered.
Architectural acoustic design: Observation of use cases including audio-only and multimodal auralizations

Auralization technology has reached a satisfactory level of ecological validity, enabling its use in architectural acoustic design. Only recently have the actual uses of auralization in the consulting community been explored, resulting in the identification of a variety of uses, including (1) to present to clients, (2) to test design ideas, (3) as a verification tool, (4) as a verification tool, (5) as a marketing tool, and (6) to improve internal company discussions. Taking advantage of methodologies from ergonomics research, the present study investigates effective uses through the observation of a collaboration project between an acoustic research team and an acoustic consultant, as a case study. Two spaces have been auralized in the context of the conception of a new skyscraper during the design phase of the project. The two spaces faced different problematics: an Atrium for which three different acoustic treatment options were suggested and experienced through multi-modal auralizations and audio-only auralizations of an Auditorium where an intrusive noise was to be acoustically treated. The ergonomic observation and analysis of this project revealed key impediments to the integration of auralization in common acoustic design practices.
MMI-GAN: Multi Medical Imaging Translation using Generative Adversarial Network

A tradução de imagens médicas é considerada uma nova fronteira no campo da análise de imagens médicas, com grande potencial de aplicação. No entanto, as abordagens existentes têm escalabilidade e robustez limitadas no manuseio de mais de dois domínios de imagens. Para resolver essas limitações, desenvolvemos a MMI-GAN, uma nova abordagem para tradução entre múltiplos domínios de imagem, capaz de traduzir imagens intermodais (TC e RM) e intramodais (PD, T1 e T2) usando apenas um gerador e um discriminador. As imagens traduzidas pela MMI-GAN conseguiram obter MAE de 5.79, PSNR de 27.39, MI de 1.43 e SSIM de 0.90. Os seus resultados foram por muitas vezes estaticamente equiparáveis ou superiores ao estado da arte.
The Impact of Physical Education Classes on Health and Quality of Life during the COVID-19

The purpose of this study was to examine the effects of the COVID-19 pandemic on the well-being and the quality of life of college students participating in physical education classes. We consider this study to be relevant because during the COVID-19 pandemic we tested whether the boost in effective activity among physical education class participants affected well-being and quality of life. A sectional questionnaire survey was conducted across Taiwan in 2019–2020. Data were collected in two stages within 6 months from a sample of 1011 university students in Taiwan (328 male, 683 female). A series of one-way ANOVAs was adopted to examine each outcome across groups and time phases. The results provide support for a positive relationship between well-being (β = 0.25, p < 0.001), and quality of life (β = 0.92, p < 0.001), supporting our expectations. Findings from our study suggest that physical activity was positively associated with mental health; and participation in physical activity had an effect on the well-being and quality of life in college students.
0D/1D Heterojunction Implant with Electro‐Mechanobiological Coupling Cues Promotes Osteogenesis

Mimicking the natural bone extracellular matrix containing intrinsic topography and electrical signals is an effective way to modulate bone regeneration. However, simultaneously coupling of the intrinsic mechanobiology and electrical cues of implant to modulate bone regeneration remains ignored. Here, the authors report in situ designation of titanium dioxide (TiO2) nanocone/bismuth oxide (Bi2O3) nanodot heterojunctions on bone implant surface to electro‐biomechanically trigger osseointegration at bone/implant interface. TiO2 nanocone/Bi2O3 nanodot heterojunctions exhibit built‐in electric field at the nanoscale interface and elastic modulus equivalent to that of bone tissue. The nano‐heterojunctions significantly promoted the attachment, spreading, and osteogenic differentiation of bone marrow mesenchymal stem cells in vitro, and the osteogenesis in vivo. The authors also show that the effects of nano‐heterojunctions on osteogenesis are mediated by yes‐associated protein biomechanical signal pathway and intracellular enrichment induced Phosphatidylinositol 3‐kinase signal pathway. Their findings highlight the coupling of topographical and electric parameters of biomaterials for modulating cell behaviors.
Impact of Novel Image Preprocessing Techniques on Retinal Vessel Segmentation

Segmentation of retinal vessels plays a crucial role in detecting many eye diseases, and its reliable computerized implementation is becoming essential for automated retinal disease screening systems. A large number of retinal vessel segmentation algorithms are available, but these methods improve accuracy levels. Their sensitivity remains low due to the lack of proper segmentation of low contrast vessels, and this low contrast requires more attention in this segmentation process. In this paper, we have proposed new preprocessing steps for the precise extraction of retinal blood vessels. These proposed preprocessing steps are also tested on other existing algorithms to observe their impact. There are two steps to our suggested module for segmenting retinal blood vessels. The first step involves implementing and validating the preprocessing module. The second step applies these preprocessing stages to our proposed binarization steps to extract retinal blood vessels. The proposed preprocessing phase uses the traditional image-processing method to provide a much-improved segmented vessel image. Our binarization steps contained the image coherence technique for the retinal blood vessels. The proposed method gives good performance on a database accessible to the public named DRIVE and STARE. The novelty of this proposed method is that it is an unsupervised method and offers an accuracy of around 96% and sensitivity of 81% while outperforming existing approaches. Due to new tactics at each step of the proposed process, this blood vessel segmentation application is suitable for computer analysis of retinal images, such as automated screening for the early diagnosis of eye disease.
Attachment, Rejection Sensitivity, Support, Psychological Capital and Alcohol Dependency in Students

Alcohol dependence evolves from problematic social relations hinged on attachment difficulties and fear of social rejection. This study sought to test an attachment-rejection-relationship model of the development of alcohol dependency. Emerging adults (N=762) of which 69.8%, were female, ranging in age from 18-63 years, took part in an online survey measuring adult attachment, rejection sensitivity, loneliness, social support, psychological capital, and alcohol consumption. Analysis supports the model and shows that individuals with insecure and anxious attachment, fear of social rejection, who experience loneliness and lack of social support, and whose psychological resources are less effective, are more likely to be at risk for alcohol dependency. The role of attachment, rejection and social relations in alcohol consumption point to social problem-solving interventions. Given the childhood origins of attachment problems and fear of social rejection there is a strong case for prevention using social problem-solving.
Light-Induced Photoluminescence Quenching and Degradation in Quasi 2D Perovskites Film of (C6H5C2H4NH3)2 (CH3NH3)2[Pb3I10]

Quasi-two-dimensional (2D) perovskites recently came into the focus because of their moisture stability. In addition to ambient air, light illumination could also cause degradation for the film of 2D perovskites; however, few studies have investigated their photostability. Here, we work on light-induced photoluminescence quenching, as well as the degradation of quasi-2D perovskites of PEA2MAn−1PbnI3n+1 (n = 3 nominally, PEA+ = C6H5(CH2)2NH3+, MA+ = CH3NH3+). Light-induced photoluminescence (PL) quenching generally happens with different speeds, depending on the wavelength and intensity of the laser as well as the film’s environment. With red light (635 nm) illumination, the film does not decompose into ambient air with an intensity below ~500 mW/cm2, although in general, a higher laser intensity and/or higher photon energy (447 nm) could render the decomposition process easier and faster. On the other hand, when the film is in a vacuum, both light-induced PL quenching and film degradation are significantly suppressed. Furthermore, we find that the multiphase of n = 1, 2, 3 in the PEA2MA2Pb3I10 film decomposes together and that the degradation processes begin with the collapses of the crystalline structures.
Spatial mapping of soil respiration using auxiliary variables. A small scale study

Soil respiration is a significant contributor to the global emissions of CO2 and is governed by many soil factors. Reliable estimates of CO2 emission on different scales (e.g., field, regional level) are hard to obtain due to the expressed spatial and temporal variability of the CO2 flux. This study aims to investigate the spatial variability of CO2 flux and soil properties in soybean cropland on Fluvisols (Croatia). The field measurements and soil samples were taken in a regular sampling grid (2 × 2 m) with 44 points in total and the spatial variability was assessed using the kriging and cokriging techniques. The soil CO2 flux showed relatively high spatial heterogeneity, ranging from 0.03 mg/m2s to 0.40 mg/m2s. The soil organic matter content (SOM), soil water content (SWC), and soil temperature (ST) had the lower variability ranging from 2.09% to 2.52%, from 27.7% to 46.8%, and from 13.7 °C to 18.2 °C, respectively. The spatial dependence was high for CO2 flux and ST, moderate for SOM, and low for SWC. The incorporation of the auxiliary variables increased the precision of the estimations for CO2 flux, SOM, and SWC. Kriging was the most accurate method for the spatial prediction of ST. The SWC was associated as the most important factor of the CO2 fluxes, indicated by their significant negative correlation, and the highest increase of the prediction precision during spatial modeling. However, more robust co-variates should be incorporated in future models to further increase the precision.
Compact balanced tri‐band bandpass filter based on stub loaded resonator with high selectivity

A compact balanced microstrip tri‐band bandpass filter (BPF) using short and open stubs loaded resonators (SOSLRs) is achieved in this article. Three differential‐mode (DM) passbands can be adjusted by properly controlling the dimensions of the loaded short and open stubs, and the first and third DM center frequencies can be implemented independently. By introducing interdigital coupling microstrip lines, five transmission zeros (TZ) are implemented to achieve a higher selectivity. The positions of TZs can be controlled by adjusting the coupling gaps between SOSLRs and interdigital coupling microstrip lines. In addition, balanced microstrip line to slotline transformation structures is introduced as the feed structure, which can be used to block the common‐mode (CM) transmission inherently. Therefore, the DM performances are independent from the CM responses, which can simplify the design procedure significantly. For demonstration, a balanced tri‐band BPF centered at 1.57, 2.45, and 3.5 GHz was fabricated and measured. Comparison with other reported balanced BPFs indicates that the proposed design exhibits the advantages of high selectivity and good CM suppression responses.
Food and Beverage Innovative Product Development Model

The research aimed to develop the process of the innovative products that can be applied to food and beverage products with a systematic review of the literature, considering various ideas and theories. The study found that they are discussed in a wide gap. Next, the study aimed to explore the acceptance of the food and beverage innovative product development model. Nowadays, the product life cycle cannot go on as the market changes, so there are limitations, led to create the model which is divided into 3 Phases, Phase 1 Product Design Development, Phase 2 Prototype and Phase 3 Industry Scale and Commercialization. Then, the research results explore that the acceptance of the model using the focus group method. It is known that many entrepreneurs of Small and Medium Enterprise (SME) did not develop a systematic product, made it failed in a situation with a lot of competitors in the market and difficulty adapting and solving problems. When entrepreneurs have studied step by step of the food and beverage innovative product development model, it makes easier to understand and have more direction for product development to bring about new products or processes in lower costs and increased income. There is a proper use of time and save resources, including raw materials, personnel, as well as reducing environmental destruction and using full efficiency resources. This model is role as a circle can be made more products line from the same resources which is back to create from the detail of the product design and also, can be start a new thing on the concept development.
Seasonal variations of indoor aerosols (PM2.5) in urban households of Jammu (J&K), India

Indoor pollution is more harmful as people spend more than 90% of their time indoors getting enhanced chances of penetrating aerosols (PM2.5) deeply into the lungs. In the present investigation, an attempt has been made to study seasonal variations of indoor aerosols (PM2.5) in urban households of Jammu(J&K). in the northern region of India. The status of indoor aerosols (PM2.5) and their seasonal variations due to temperature and humidity conditions have been studied for the first time in urban households of Jammu (J&K). The two year study period (2017-2019.) revealed that all types of households of urban areas with non-wood fuel as well as wood fuel burning practices exhibited significantly (p<0.05) higher values of indoor PM 2.5 during summer season (74.36 µg/m3 and 156.46 µg/m3 ) followed by winter season (62.77 µg/m3 and 143.5µg/m3 ) and lower values during the rainy season (58.47 µg/m3 and 132.52 µg/m3 ). All these values were observed to be above the CPCB prescribed annual limit of 40 µg/m3, thereby exposing the residents to diseases of the respiratory and cardiovascular systems. The data generated in the present study will act as baseline data for future studies pertaining to indoor aerosols (PM2.5) as well as suggesting mitigation measures.
Measurement of Magnetic Field Induced by Spin-Accumulated Electrons in a FeCoB Nanomagnet

The spins, which are accumulated at a boundary of a nanomagnet due to the spin Hall effect, induce a magnetic field, which tilts the nanomagnet magnetization out of its easy axis. Even though this magnetic field is relatively small (about 20 G), it can reverse the magnetization of the nanomagnet if it is modulated in resonance with the magnetization precession and the conditions of the parametric resonance are met. Therefore, such magnetic field can be used to optimize the recording mechanism and to minimize the recording energy for MRAM. A high-precession measurement method of the spin-accumulation-induced magnetic field is developed. The magnetic field is measured in a FeCoB nanomagnet and its properties are studied.