Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing Student Wellbeing Through Social Prescribing: A Rapid Realist Review

Objectives: A Rapid Realist Review of social prescribing in Higher Education (HE) was undertaken to determine what works, for whom, how, why, and within what circumstances. The review resulted in the development of a Realist Programme Theory articulating the way in which social prescribing can be implemented within the HE environment. Methods: Searches of 12 electronic databases were supplemented by citation chaining and grey literature surfaced by the Project Advisory Group. The RAMESES Quality Standards for Realist Review were followed, and the retrieved articles were systematically screened and iteratively analysed to develop Context-Mechanism-Outcome Configurations (CMOCs) and an overarching Realist Programme Theory. Results: A total of 57 documents were included. The overarching programme theory was developed from the analysis of these documents and comprised of a social prescribing pathway with the following components: (1) An Accessible Gateway, (2) A Skilled Peer, (3) Trusted-Safe-Credible Resources, and (4) A Healthy Setting. Conclusion: A Realist Programme Theory was developed—this model and associated principles will provide a theoretical basis for the implementation of social prescribing pathways within higher education. Whilst the direct project outputs are of particular significance to the UK HE audience, the underpinning principles can support practice within the global arena.
Generalized Additive Modelling of Dependent Frequency and Severity Distributions for Aggregate Claims

Abstract This paper examines the problem of accurately estimating the expected value and variance of aggregate claims for each policyholder. Through an appropriate statistical model to estimate the pure premium, an insurer can find niche markets to operate competitively and profitably. To this end, the framework of generalized linear models (GLMs) for aggregate claims is extended to encompass a species of frequentist generalized additive models (GAMs) based on cubic penalized regression splines. The new structure could allow for the incorporation of more flexible nonlinear and/or nonparametric trend terms for the marginal claim frequency, conditional claim severity, and finally for Tweedie modelling as well. This nonparametric approach is illustrated through simulation and applied to an automobile insurance dataset. A juxtaposition of hypothesis test results, AIC values, and attendant graphical diagnostics effectively demonstrate that the GAMs under both the independent and dependent settings give a better fit than the GLM approach. JEL classification numbers: C14, G22. Keywords: Premium, Generalized Additive Models, Dependence, Splines, Frequency, Severity.
Sensitive, non-immunogenic in vivo imaging of cancer metastases and immunotherapy response

Non-invasive imaging of tumors expressing reporter transgenes is a popular preclinical method for studying tumor development and response to therapy in vivo due to its ability to distinguish signal from tumors over background noise. However, the utilized transgenes, such as firefly luciferase, are immunogenic and, therefore, impact results when expressed in immune-competent hosts. This represents an important limitation, given that cancer immunology and immunotherapy are currently among the most impactful areas of research and therapeutic development. Here we present a non-immunogenic preclinical tumor imaging approach. Based on the expression of murine sodium iodide symporter (mNIS), it facilitates sensitive, non-invasive detection of syngeneic tumor cells in immune-competent tumor models without additional immunogenicity arising from exogenous transgenic protein or selection marker expression. NIS-expressing tumor cells internalize the gamma-emitting [99mTc]pertechnetate ion and so can be detected by SPECT (single photon emission computed tomography). Using a mouse model of pancreatic ductal adenocarcinoma hepatic metastases in immune-competent C57BL/6 mice, we demonstrate that the technique enables the detection of very early metastatic lesions and longitudinal assessment of immunotherapy responses using precise and quantifiable whole-body SPECT/CT imaging.
The relationship between fall and loneliness among older people in China: the mediating role of personality trait

Aims We aimed to explore the role of personality traits between fall and loneliness. Methods A questionnaire survey was used to investigate falls, the big five personality traits, and loneliness among older people (≥ 60 years old) in China mainland. Results A total of 4,289 older people participated in the survey. There are significant differences in age, marital status, education level, residence, solitariness, and fall in relation to loneliness among older people. Falls, especially when they occurred one time increase the loneliness of older people. Agreeableness, conscientiousness, and neuroticism were significant mediating effects between falls and loneliness. Conclusion This study implied that agreeableness, conscientiousness, and neuroticism were meditating factors between falls and loneliness. In the future, we should consider the big five personality traits more to understand loneliness and offer older people interventions for reducing their loneliness. The study design was cross-sectional, so the temporal precedence of mediators and causality could not be tested. Because the data were collected retrospectively, current loneliness is likely to have confounding effects on retrospective recall.
Sustainable Environmental Monitoring via Energy and Information Efficient Multinode Placement

The Internet of Things (IoT) is gaining traction for sensing and monitoring outdoor environments, such as water bodies, forests, or agricultural lands. Sustainable deployment of sensors for environmental sampling is a challenging task because of the spatial and temporal variation of the environmental attributes to be monitored, the lack of the infrastructure to power the sensors for uninterrupted monitoring, and the large continuous target environment despite the sparse and limited sampling locations. In this article, we present an environment monitoring framework that deploys a network of sensors and gateways connected through low-power, long-range networking to perform reliable data collection. The three objectives correspond to the optimization of information quality, communication capacity, and sustainability. Therefore, the proposed environment monitoring framework consists of three main components: 1) to maximize the information collected, we propose an optimal sensor placement method based on QR decomposition that deploys sensors at information- and communication-critical locations; 2) to facilitate the transfer of big streaming data and alleviate the network bottleneck caused by low bandwidth, we develop a gateway configuration method with the aim to reduce the deployment and communication costs; and 3) to allow sustainable environmental monitoring, an energy-aware optimization component is introduced. We validate our method by presenting a case study for monitoring the water quality of the Ergene River in Turkey. Detailed experiments subject to real-world data show that the proposed method is both accurate and efficient in monitoring a large environment and catching up with dynamic changes.
DISCERNING Intra-Metropolitan Patterns of Producer Service Establishment Location using Geographic Information Systems

Title of Dissertation: DISCERNING INTRA-METROPOLITAN PATTERNS OF PRODUCER SERVICE ESTABLISHMENT LOCATION USING GEOGRAPHIC INFORMATION SYSTEMS Francis E. Lindsay, Doctor of Philosophy, 2005 Dissertation directed by: Dr. Martha Geores Department of Geography This research presented in this dissertation explores the spatial distribution of producer service establishments in the Washington DC area for 1997. Producer services are a distinct and important segment of the US industrial economy. These businesses provide the intermediary goods and services that are used as inputs for many other industrial sectors. Producer service employment and sales have grown substantially during the 1990s in relation to other portions of the overall US economy, surpassing growth in most sectors including other types of services. The majority of producer service research tends to focus on these services at the national scale or comparative studies of whole metropolitan areas. This work presents the findings for two complementary producer service research problems pertinent to intra-metropolitan spatial scale research, the contribution of face-to-face interaction to the spatial concentration of these services using sales between particular producer services, and the entropy (or diversity) of services within postal code areas and how this measure correlates to the presence or absence of particular producer services. The findings indicate that there is empirical evidence of a relationship between the strength of intra-sector trade and the degree of spatial concentration of producer service establishments. This analysis also demonstrates that some producer service sectors known to have weak trade relations to other producer services do locate in areas with a lower diversity of services. The results of this research add to a growing body of research and theory that centers on interpreting the role of producer services in shaping metropolitan economies. The spatial component of producer service establishment location in research is often neglected entirely or is superficially referenced. This geographic research provides the spatial dimension of producer service activities occurring at very fine scales within a metropolitan spatial economy. The results are only applicable to the study area but the methodology is useful and offers a potential for broader utility in producer service research endeavors.
The Use of Faba Bean Cover Crop to Enhance the Sustainability and Resiliency of No-Till Corn Silage Production and Soil Characteristics

Sustainable corn production requires a dramatic shift toward natural soil fertility rather than relying solely on synthetic fertilizers. Cover crops play an important role in improving the productivity of subsequent row crops through improving soil properties. The main goal of this study was to investigate if increasing cover crop biomass through applying a higher density can enhance soil characteristics in the short term and contribute more nitrogen to succeeding corn silage. In a two-year field study (2018–2019), the influence of faba bean (Vicia faba L.) as a cover crop on soil characteristics and corn silage (Zea mays L.) production was evaluated. Treatments consisted of five levels of faba bean density (0, 25, 35, 40, and 80 plants m−2) and four application rates of urea-based nitrogen fertilizer (0, 100, 200, and 300 kg ha−1) in a no-till system. The measured soil characteristics were not significantly affected through increasing cover crop density to 80 plants m−2. The faba bean roots comprised 33% of total biomass in densities ranging from 25–40 plants m−2. The highest total N yield (root + shoot) was 133 kg N ha−1, obtained from 40 faba bean plants m−2. The faba bean root decomposed faster than the shoot, and the addition of N to the corn accelerated 50% N release from the roots but had no significant effect on shoot decomposition. Corn planted after 40 plants m−2 faba bean yielded 28% more than the corn with no faba bean. Corn yielded less in no-cover-crop fields even when it received the highest synthetic N rate (300 kg N ha−1), indicating the value of including faba bean in rotation with corn.
The effect of Jendrassik maneuver on the persistence of the peroneal nerve F-wave

Objectives This study investigated whether peroneal nerve F-wave persistence increased when the Jendrassik maneuver (JM) was performed, aiming to obtain information about the physiology of F-waves and JM. Patients and methods Thirty healthy individuals (HIs; 17 females, 13 males; mean age: 33.6±8.2 years; range, 23-50 years) were included in the prospective experimental study conducted between June 15, 2021, and December 15, 2021. Nerve conduction studies of peroneal, superficial peroneal, posterior tibial, and sural nerves were performed in one extremity of each HI. The peroneal nerve F-wave study was performed at rest (Study 1), during JM (Study 2), and after JM (Study 3). F-wave persistence of the peroneal nerve, maximum F-wave amplitude (ampF-wavemax), mean F-wave amplitude (ampF-wavemean), minimum F-wave latency, and the ratio of ampF-wavemean to maximum M amplitude (F/M ratio) were analyzed. Results The mean peroneal nerve F-wave persistence in Study 1, Study 2, and Study 3 was 28.7±23.9%, 52.3±32.1%, and 34.7±29.0%, respectively. F-wave persistence in Study 2 was higher compared to Studies 1 and 3 (p<0.001 and p<0.001, respectively). Moreover, ampF-wavemax, ampF-wavemean, and F/M ratio in Study 2 were higher than Studies 1 and 3 (p=0.026 and p=0.021 for ampF-wavemean; p=0.015 and p=0.003 for ampF-wavemax; p=0.033 and p=0.015 for F/M ratio, respectively). F-wave persistence in Study 2 was positively correlated with ampF-wavemax and ampF-wavemean (p<0.001, r= 0.717; p<0.001, r=0.786, respectively). Conclusion This study demonstrated that JM increased F-wave persistence and amplitude. Jendrassik maneuver may show its effect through motor neuron excitability.
A Direct Shear Apparatus With Vibrational Loading

For some geotechnical design projects where soils are exposed to dynamic loads (vibrations), it becomes necessary to evaluate the strength and deformation characteristics of the soil under existing and/or anticipated vibrations. In order to investigate the effect of the vibrations on the strength and deformation properties of soils, representative samples should be collected and tested in laboratories and subjected to vibration of expected magnitudes. In this case, it is important that the laboratory equipment used is able to simulate field conditions as close as possible to provide the necessary parameters that can successfully be used in the design. A vibrational direct shear apparatus has been developed based on the conventional direct shear apparatus to evaluate the strength and deformation characteristics of soils (granular and cohesive) under a wide range of vibrational accelerations and frequencies. The apparatus makes it possible to test soils in both stress and displacement controlled modes. The design of the apparatus is such that it allows modification of the most commonly used direct shear apparatuses into the vibrational ones. The new apparatus was built and tested to prove its performance and reliability.
SPR Sensor Based on a Concave Photonic Crystal Fiber Structure with MoS2/Au Layers

We propose a surface plasmon resonance (SPR) sensor based on the concave photonic crystal fiber (PCF) coated with molybdenum disulfide (MoS2) and Au layers, which can detect the refractive index (RI) of the analyte. The finite element method (FEM) was used to verify our design, and the loss spectra of the fundamental mode are calculated. Compared with the SPR sensor with only a Au layer, the wavelength sensitivity can be improved by from 3700 to 4400 nm/RIU. Our proposed sensor works in near-infrared band and has a wide RI range from 1.19 to 1.40. The influences of the geometrical parameters of PCF and the thicknesses of Au and MoS2 layers on the loss spectra are discussed in detail, and the maximum wavelength sensitivity of 5100 nm/RIU can be achieved. Meanwhile, a high resolution of 1.96 × 10−5 RIU and the largest FOM of 29.143 can be obtained. It is believed that our findings show the sensor’s excellent potential in medical testing, unknown biological detection, environmental monitoring and organic chemical detection.
T-coercivity for the asymptotic analysis of scalar problems with sign-changing coefficients in thin periodic domains

We study a scalar problem in thin periodic composite media formed by two materials, a classical one and a metamaterial (also known as negative material). By applying T-coercivity methods and homogenization techniques specific to the thin periodic domains under consideration, for two geometric settings, we derive the homogenized limit problems, which both exhibit dimension-reduction effects. For more information see https://ejde.math.txstate.edu/Volumes/2021/59/abstr.html
When Eating Intuitively Is Not Always a Positive Response: Using Machine Learning to Better Unravel Eaters Profiles

Background: The aim of the present study was to identify eaters profiles using the latest advantages of Machine Learning approach to cluster analysis. Methods: A total of 317 participants completed an online-based survey including self-reported measures of body image dissatisfaction, bulimia, restraint, and intuitive eating. Analyses were conducted in two steps: (a) identifying an optimal number of clusters, and (b) validating the clustering model of eaters profile using a procedure inspired by the Causal Reasoning approach. Results: This study reveals a 7-cluster model of eaters profiles. The characteristics, needs, and strengths of each eater profile are discussed along with the presentation of a continuum of eaters profiles. Conclusions: This conceptualization of eaters profiles could guide the direction of health education and treatment interventions targeting perceptual and eating dimensions.
Acquiring bifidobacteria species from formula-fed and breast-fed newborns: identifying, quantifying and creating an antibiogram

After examining the Bifidobacterium spp. population in faeces samples from breast-fed and formula-fed infants, an antibiogram was created. The prevalence of Bifidobacterium spp. in faeces was determined using common bacterial growth media, including Man Rogos Sharpe (MRS), Brain Heart Infusion (BHI), Luria Bertani (LB) broth and Bifidobacteria agar. According to the findings, formula-fed babies had a low population of Bifidobacterium spp. in their stools while breast-fed babies had a high population. By using phylogenetic analysis of the 16S rRNA and xfp (xylose/fructose 6-phosphate phosphoketolase) genes, and RFLP mapping of Bifidobacterium isolates, it was possible to identify a new and unique Bifidobacterium species. The intensity of the reddish brown colour produced during the F6PPK (fructose 6-phosphate phosphoketolase) assay is an accurate indicator of the proportion of various bifidobacteria present. Bifidobacteria agar media produced the greatest amounts of bifidobacteria diversity and recovery. Small (SCV) and Big colony variations (BCV) were formed during growth on different media. The various antibiotic MIC values changed depending on the use of different media, growth circumstances, bile salt treatment and low pH. The findings of this study demonstrate that test conditions also impact the diversity of microbiological conditions that distinguish between resistant and susceptible bacteria.
Algoritmos de Aprendizado de Má quina Aplicados ao Reconhecimento de Usuário Baseado na Dinâ mica da Digitação: Um Estudo Comparativo

Comparative studies about keystroke dynamics-based user recognition with Machine Learning (ML) algorithms do not consider multiple datasets in their evaluation. Moreover, each study usually concentrates on a single and non-public dataset. Hence they cannot generalize which algorithms are, in fact, the best ones to perform this kind of recognition task. Thus, this work presents a comparative study which analyzes the performances of six popular ML algorithms applied to five different public datasets with static and predefined samples (e.g., passwords). The results of the experiments showed that Random Forest was able to outperform all the other algorithms in all datasets. Resumo. Em geral, as análises comparativas feitas em trabalhos que estudam a tarefa de reconhecimento de usuários baseada na dinâmica da digitação utilizando algoritmos de Aprendizado de Máquina (AM) se restringem à avaliação considerando apenas um único conjunto de dados especı́fico, em geral não público, o que torna difı́cil generalizar quais são, de fato, os algoritmos mais indicados para realizar tal tarefa. Assim, o presente trabalho tem como objetivo apresentar um estudo comparativo acerca do desempenho de alguns dos mais populares algoritmos de AM aplicados a tal tarefa utilizando cinco conjuntos de dados públicos compostos por amostras estáticas (textos fixos, como senhas, por ex.). Os experimentos realizados mostraram que o Random Forest foi capaz de superar os demais algoritmos em todos os conjuntos de dados analisados.
On the Design of Broadband Asymmetric Y-Junction Ferrite Circulator for 60-GHz Inter-Satellite Communication

Millimeter-wave (mmW) Y-junction ferrite circulators above 40 GHz have limited bandwidth due to the lack of ferrite materials having a high saturation magnetization above 5000 G and the simple and traditional circuit design approaches that cannot produce wideband circulators in this frequency range. To increase the bandwidth of mmW Y-junction ferrite circulators, novel design techniques for such circulators should be developed to achieve a functional circulator over a wide bandwidth at mmW frequencies. In this article, a Y-junction ferrite circulator is proposed, which is based on the WR15 waveguide standard with broadband performance for 60-GHz inter-satellite communications. An approximate design procedure for the core section of the proposed circulator is presented. The proposed Y-junction ferrite circulator achieves more than 20% bandwidth centered at 60 GHz. In addition, the effect of input power and ambient temperature on the performance of the circulator is studied for an input power of 300 W and ambient temperature in the range from −80°C to 80°C. The experimental prototype is fabricated and measured, where the measured response is in very good agreement with the numerically anticipated counterpart. The fabricated circulator achieves beyond −17 dB matching level with −15 dB isolation and 1-dB insertion loss over the entire bandwidth of interest.
A Fat Debate on Big Food? Unraveling Blogosphere Reactions

Confronted with public concerns about health and obesity, food companies are taking several initiatives. However, it is unclear to what extent they should communicate these policies. This article explores reactions in the blogosphere to health-related announcements by large food companies. Results show that taste-related announcements generate not only more reactions, but also more positive buzz than knowledge-related announcements. Valence is influenced by issue association per company type: those with highest obesity associations generate more negative blog posts. In case of low issue association, there are only limited blogosphere reactions. This analysis has important implications for managing interaction with social media.
Lessons From an Urban Teacher Residency Partnership

Facing teacher shortages, urban teacher frustration, and a lack of BIPOC representation in the teacher workforce, two urban institutions, a school district, and a university partnered to design, develop and implement a year-long clinical teacher residency program. Throughout the pilot and one subsequent year, data was collected through observation and open-ended questionnaires as three resident-mentor pairs engaged with students in two of the district’s elementary schools. The Technological, Pedagogical, and Content Knowledge (TPACK) development model (Mishra & Koehler, 2006) and Moir’s (1990) Phases of First-Year Teachers’ Attitudes Toward Teaching were used to inform program design and examine the success of program implementation. While the program did not meet the goal of increasing BIPOC representation, teachers skilled in urban education successfully entered the workforce. Valuable lessons were learned about designing residency programs that foster a sense of belonging and optimize mentor and resident development. The authors conclude clinical teacher residency shows promise as an avenue for providing novice and experienced teachers responsive support as they engage with the complex process of teacher development.