Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of Health Insurance Status Among Young Adults

This study evaluates the determinants of insurance coverage in the 18–24- year-old population using the National Medical Care Utilization and Expenditure Survey. Three specific issues are addressed: 1) the characteristics of the insured versus uninsured, 2) the reason given by the uninsured for not having coverage, and 3) the role of employment status and other variables in determining insurance status. An important consideration is whether age or usual activity is more important in its effect on insurance status. The results show that employment is the strongest predictor of insurance status in all age and usual activity subgroups. Generally, permanent/full-time workers are most likely to be insured. An exception to this trend is found for those attending school who are also permanent/part-time workers. These individuals are more likely to be insured than permanent full-time workers who are in school. Furthermore, young adults with lower incomes, less education, rural residence, not married, hispanic ethnicity, and Western geography are the least likely to be insured. The findings of this analysis can be used by policymakers to identify the mechanisms that can best enhance insurance coverage among young adults.
Intelligent preliminary diagnosis system for diseases with similar clinical presentation

Accurately identifying diseases with similar symptoms, especially in resource-limited medical settings, is a key challenge to diagnostic accuracy. This paper presents a preliminary diagnostic system to address the challenge of diagnosing diseases with similar symptoms. The system has been implemented using the PyQt5 library and employs a unique symptom identification algorithm developed in Python. Furthermore, to carry out the diagnosis, it uses comma-separated values (CSV) and excel files as databases where the diseases and their respective symptoms are stored. The results show that the system has a precision of 95%, a sensitivity of 90%, and a specificity of 93% after evaluating 35 clinical cases covering seven diseases with similar initial symptoms, namely: dengue, zika, chikungunya, COVID-19, influenza, monkey-pox, and the common cold. Furthermore, the positive evaluation of the technical performance of the system by experts supports its practical feasibility and its potential as a valuable tool in medical practice. In conclusion, the system diagnoses diseases by analyzing the symptoms of the information file, highlighting its usefulness in improving the diagnostic accuracy of similar cases and optimizing medical care for the benefit of patients.
Use and effectiveness of health impact assessment in the energy and natural resources sector in the United States, 2007 – 2016

ABSTRACT Decisions made in the energy and natural resources sector can affect public health. This report reviews the characteristics and assesses the effectiveness of health impact assessments (HIAs) conducted in this sector. A total of 30 HIAs conducted in 14 states in the United States were identified using a targeted literature search. Five HIAs illustrative of the different source and sub-sector categories, and with identifiable impacts on decision-making processes were selected for review. An existing conceptual framework (Wismar) was used to assess the effectiveness of the five selected HIAs on decision-making related to non-renewable energy, renewable energy, mining, and energy conservation. The 30 HIAs were performed for a variety of projects and assessed health impacts ranging from metabolic disorders to community livability. Eight of the 30 reports were incorporated into environmental impact assessments. All five selected HIAs were generally effective and raised awareness of the health effects of the projects being assessed; four were directly effective and led to changes in final project decisions. Their variable effectiveness may be related to the extent of community engagement and consideration of equity issues, differences in the details and quality of monitoring and evaluation plans devised as part of the HIA process, and whether the outcomes of monitoring and evaluation are reported.
Peloruside A, an Antimitotic Agent, Specifically Decreases Tumor Necrosis Factor-α Production by Lipopolysaccharide-Stimulated Murine Macrophages

Peloruside A (peloruside) is a naturally occurring compound isolated from a New Zealand marine sponge that, like the anticancer drug paclitaxel, stabilizes microtubules and inhibits mitosis. Paclitaxel is known to induce a proinflammatory response in murine macrophages; whereas, peloruside has never been tested for its immunomodulatory effects in these cells. Although the antimitotic effects of the two drugs appear to be similar, we found that peloruside, unlike paclitaxel, does not induce murine macrophages to produce the proinflammatory mediators interleukin-12p40 (IL-12p40), tumor necrosis factor-α (TNF-α), and nitric oxide. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) reduction assay confirmed that the absence of cytokine production was not caused by cytotoxicity in these nondividing cells. Additionally, there was no effect on unstimulated splenocytes; whereas, both compounds inhibited proliferation after concanalavin A (Con A) stimulation. Finally, there was a significant decrease in TNF-α and nitric oxide but not IL-12p40 when macrophages were cultured with lipopolysaccharide (LPS) and either paclitaxel or peloruside. These results suggest that peloruside may prove to be an effective anti-inflammatory treatment, since it does not induce the production of proinflammatory mediators yet can downregulate TNF-α and nitric oxide production by LPS-stimulated macrophages, as well as inhibit lymphocyte proliferation.
EFFECT OF CURRENT RATIO (CR), RETURN ON ASSET (ROA), DEBT TO EQUITY RATIO (DER), EARNING PER SHARE (EPS) ON STOCK PRICES OF BUILDING CONSTRUCTION SUBSECTOR COMPANIES (J211 IDX-IC) LISTED ON THE IDX IN 2016-2021

Investment activities in the company are supporting factors that can affect the sustainability of the company in the future. The nominal size of the stock price will be a consideration for investors in making investments. This study aims to analyze whether or not there is an influence of fundamental factors including ROA (return on Assets), ROE (return on equity), DER (debt equity ratio), EPS (earnings per share), and CR (current ratio) on stock prices in building construction subsector companies listed on the Indonesia Stock Exchange in 2016-2021. This research is included in the type of quantitative research using secondary data. The sample data collection technique uses the purposive sampling method where a sample of 24 companies from a population of 55 companies was obtained. The results showed that between 2016 and 2021, the share price of building sub-construction companies listed on the IDX was largely and partly influenced by the Return on Assets (ROA). Further, the share price of IDX-listed building sub-construction companies was significantly and partly influenced by the current ratio (CR). The share prices of building companies engaged in sub-construction were significantly and partially influenced by the debt equity ratio (DER). In addition, EPS will have a positive and significant impact on the share price of building sub-construction companies listed on the IDX.
Using filtering agents to improve prediction quality in the GroupLens research collaborative filtering system

Collaborative filtering systems help address information overload by using the opinions of users in a community to make personal recommendations for documents to each user. Many collaborative filtering systems have few user opinions relative to the large number of documents available. This sparsity problem can reduce the utility of the filtering system by reducing the number of documents for which the system can make recommendations and adversely affecting the quality of recommendations. This paper defines and implements a model for integrating content-based ratings into a collaborative filtering system. The filterbot model allows collaborative filtering systems to address sparsity by tapping the strength of content filtering techniques. We identify and evaluate metrics for assessing the effectiveness of filterbots specifically, and filtering system enhancements in general. Finally, we experimentally validate the filterbot approach by showing that even simple filterbots such as spell checking can increase the utility for users of sparsely populated collaborative filtering systems.
Impacts of Multiple Stresses on Water Demand and Supply Across the Southeastern United States 1

Abstract: Assessment of long‐term impacts of projected changes in climate, population, and land use and land cover on regional water resource is critical to the sustainable development of the southeastern United States. The objective of this study was to fully budget annual water availability for water supply (precipitation − evapotranspiration + groundwater supply + return flow) and demand from commercial, domestic, industrial, irrigation, livestock, mining, and thermoelectric uses. The Water Supply Stress Index and Water Supply Stress Index Ratio were developed to evaluate water stress conditions over time and across the 666 eight‐digit Hydrologic Unit Code basins in the 13 southeastern states. Predictions from two Global Circulation Models (CGC1 and HadCM2Sul), one land use change model, and one human population model, were integrated to project future water supply stress in 2020. We found that population increase greatly stressed water supply in metropolitan areas located in the Piedmont region and Florida. Predicted land use and land cover changes will have little effect on water quantity and water supply‐water demand relationship. In contrast, climate changes had the most pronounced effects on regional water supply and demand, especially in western Texas where water stress was historically highest in the study region. The simulation system developed by this study is useful for water resource planners to address water shortage problems such as those experienced during 2007 in the study region. Future studies should focus on refining the water supply term to include flow exchanges between watersheds and constraints of water quality and environmental flows to water availability for human use.
Predicting response to breast cancer neoadjuvant chemotherapy using diffuse optical spectroscopy

Diffuse optical spectroscopy (DOS) and imaging are emerging diagnostic techniques that quantitatively measure the concentration of deoxy-hemoglobin (ctHHb), oxy-hemoglobin (ctO2Hb), water (ctH2O), and lipid in cm-thick tissues. In early-stage clinical studies, diffuse optical imaging and DOS have been used to characterize breast tumor biochemical composition and monitor therapeutic response in stage II/III neoadjuvant chemotherapy patients. We investigated whether DOS measurements obtained before and 1 week into a 3-month adriamycin/cytoxan neoadjuvant chemotherapy regimen can predict final, postsurgical pathological response. Baseline DOS measurements of 11 patients before therapy revealed significant increases in tumor ctHHb, ctO2Hb, ctH2O, and spectral scattering slope, and decreases in bulk lipids, relative to normal breast tissue. Tumor concentrations of ctHHb, ctO2Hb, and ctH2O dropped 27 ± 15%, 33 ± 7%, and 11 ± 15%, respectively, within 1 week (6.5 ± 1.4 days) of the first treatment for pathology-confirmed responders (n = 6), whereas nonresponders (n = 5) and normal side controls showed no significant changes in these parameters. The best single predictor of therapeutic response 1 week posttreatment was ctHHb (83% sensitivity, 100% specificity), while discrimination analysis based on combined ctHHb and ctH2O changes classified responders vs. nonresponders with 100% sensitivity and specificity. In addition, the pretreatment tumor-to-normal ctO2Hb ratio was significantly higher in responders (2.82 ± 0.44) vs. nonresponders (1.82 ± 0.49). These results highlight DOS sensitivity to tumor cellular metabolism and biochemical composition and demonstrate its potential for predicting and monitoring an individual's response to treatment.
Graph-based surface reconstruction using structures in scattered point sets

The authors present an algorithm for the reconstruction of a surface from an unorganized set of points in space. The point data may be obtained from a laser range scanner or any other digitizing tool to describe the shape of the object(s). The basic idea of the algorithm is to construct some kind of wire frame for the surface, the so-called surface description graph. This is performed by applying several steps. In the final part of the algorithm this wire frame is then filled with triangles. Each step uses rules for the reconstruction which are based on human knowledge in geometric structures. These rules are designed to allow the reconstruction of artificial objects as well as natural objects and are extendable in many aspects for ongoing research. As a result of this approach, the algorithm is able to reconstruct surfaces in data sites with changing point density as well as high curvature of the surface. In addition, it automatically recognizes the number of objects covered in the point set. Several examples are given to demonstrate its features.
Neural Correlates of Stereotype Application

Recent research has focused on the disparate mechanisms that support the human ability to “mentalize” about the thoughts and feelings of others. One such process may rely on precompiled, semantic beliefs about the characteristics common to members of a social group, that is, on stereotypes; for example, judging that a woman may be more likely than a man to have certain interests or opinions. In the current study, we identified a pattern of neural activity associated with the use of stereotypes to judge another person's psychological characteristics. During fMRI scanning, participants mentalized about the likely responses of a female and male target to a series of questions, some of which were related to gender stereotypes (e.g., “enjoys shopping for new clothes”). Trials on which participants applied a stereotype were segregated from those on which participants avoided stereotype use. The BOLD response in an extensive region of the right frontal cortex differentiated stereotype-applied from -unapplied trials. Moreover, this neural difference was correlated with a behavioral index of gender associations—the Implicit Association Test—administered after scanning. Results suggest that stereotype application may draw on cognitive processes that more generally subserve semantic knowledge about categories.
The extended hippocampal‐diencephalic memory system: Enriched housing promotes recovery of the flexible use of spatial representations after anterior thalamic lesions

The anterior thalamic (AT) nuclei constitute an important component of an extended hippocampal‐diencephalic system, and severe persisting memory deficits are normally found after AT damage. This study examined whether postoperative enrichment promotes the recovery of the flexible use of spatial representations in rats with AT lesions. After training to swim from a single constant start position to a submerged platform in a Morris water maze, rats with AT lesions that were housed in standard cages (AT‐Std) performed poorly when required to swim to the platform from novel start positions during probe trials. By contrast, rats with AT lesions but housed in enriched environments (AT‐Enr), like sham‐lesion rats, showed relatively little disruption when tested with novel start positions. AT‐Std rats also initially showed impaired acquisition of the task, whereas AT‐Enr rats learned at a similar rate to that of the Sham‐Std group. Beneficial effects of enrichment were replicated in the subsequent standard water maze procedure that used varying start positions throughout training to acquire a new platform location. Although it is clear that AT damage can severely disrupt episodic‐like memory processes, and appear to be a core part of the interlinked neural systems subserving episodic memory, the current findings strongly encourage study on the adaptive response of the brain to thalamic lesions and prospects for the development of rehabilitation programs in cases of anterograde amnesia associated with diencephalic injury. © 2008 Wiley‐Liss, Inc.
Variations in GP–patient communication by ethnicity, age, and gender: evidence from a national primary care patient survey

Background Doctor–patient communication is a key driver of overall satisfaction with primary care. Patients from minority ethnic backgrounds consistently report more negative experiences of doctor–patient communication. However, it is currently unknown whether these ethnic differences are concentrated in one gender or in particular age groups. Aim To determine how reported GP–patient communication varies between patients from different ethnic groups, stratified by age and gender. Design and setting Analysis of data from the English GP Patient Survey from 2012–2013 and 2013–2014, including 1 599 801 responders. Method A composite score was created for doctor–patient communication from five survey items concerned with interpersonal aspects of care. Mixed-effect linear regression models were used to estimate age- and gender-specific differences between white British patients and patients of the same age and gender from each other ethnic group. Results There was strong evidence (P<0.001 for age by gender by ethnicity three-way interaction term) that the effect of ethnicity on reported GP–patient communication varied by both age and gender. The difference in scores between white British and other responders on doctor–patient communication items was largest for older, female Pakistani and Bangladeshi responders, and for younger responders who described their ethnicity as ‘Any other white’. Conclusion The identification of groups with particularly marked differences in experience of GP–patient communication — older, female, Asian patients and younger ‘Any other white’ patients — underlines the need for a renewed focus on quality of care for these groups.
Predicting survival in malignant pleural effusion: development and validation of the LENT prognostic score

Background Malignant pleural effusion (MPE) causes debilitating breathlessness and predicting survival is challenging. This study aimed to obtain contemporary data on survival by underlying tumour type in patients with MPE, identify prognostic indicators of overall survival and develop and validate a prognostic scoring system. Methods Three large international cohorts of patients with MPE were used to calculate survival by cell type (univariable Cox model). The prognostic value of 14 predefined variables was evaluated in the most complete data set (multivariable Cox model). A clinical prognostic scoring system was then developed and validated. Results Based on the results of the international data and the multivariable survival analysis, the LENT prognostic score (pleural fluid lactate dehydrogenase, Eastern Cooperative Oncology Group (ECOG) performance score (PS), neutrophil-to-lymphocyte ratio and tumour type) was developed and subsequently validated using an independent data set. Risk stratifying patients into low-risk, moderate-risk and high-risk groups gave median (IQR) survivals of 319 days (228–549; n=43), 130 days (47–467; n=129) and 44 days (22–77; n=31), respectively. Only 65% (20/31) of patients with a high-risk LENT score survived 1 month from diagnosis and just 3% (1/31) survived 6 months. Analysis of the area under the receiver operating curve revealed the LENT score to be superior at predicting survival compared with ECOG PS at 1 month (0.77 vs 0.66, p<0.01), 3 months (0.84 vs 0.75, p<0.01) and 6 months (0.85 vs 0.76, p<0.01). Conclusions The LENT scoring system is the first validated prognostic score in MPE, which predicts survival with significantly better accuracy than ECOG PS alone. This may aid clinical decision making in this diverse patient population.
Proline-directed phosphorylation and isomerization in mitotic regulation and in Alzheimer's Disease.

The reversible phosphorylation of proteins on serine/threonine residues preceding proline (Ser/Thr-Pro) is a major regulatory mechanism for the control of a series of cell cycle events. Although phosphorylation is thought to regulate protein function by inducing conformational changes, little is known about most of these conformational changes and their significance. Recent studies indicate that the conformation and function of a subset of these phosphorylated proteins are controlled by the prolyl isomerase Pin1 through isomerization of specific phosphorylated Ser/Thr-Pro bonds. Furthermore, compelling evidence supports the idea that proline-directed phosphorylation and subsequent isomerization play a critical role not only in cell cycle control, but also in the development of Alzheimer's disease, where postmitotic neurons display various cell cycle markers, especially mitotic events, prior to degeneration.
Disk Diffusion Method for Erythromycin and Ciprofloxacin Susceptibility Testing of Campylobacter jejuni and Campylobacter coli

Using the disk diffusion method, [Lehtopolku et al.][1] ([1][2]) reported diameters of 6 mm to 44 to 70 mm for susceptible, as well as resistant, Campylobacter jejuni and C. coli isolates exposed to seven and six antimicrobial agents, respectively. These results disagree with the erythromycin and
The Contribution of Increased Gamma Band Connectivity to Visual Non-Verbal Reasoning in Autistic Children: A MEG Study

Some individuals with autism spectrum (AS) perform better on visual reasoning tasks than would be predicted by their general cognitive performance. In individuals with AS, mechanisms in the brain’s visual area that underlie visual processing play a more prominent role in visual reasoning tasks than they do in normal individuals. In addition, increased connectivity with the visual area is thought to be one of the neural bases of autistic visual cognitive abilities. However, the contribution of such brain connectivity to visual cognitive abilities is not well understood, particularly in children. In this study, we investigated how functional connectivity between the visual areas and higher-order regions, which is reflected by alpha, beta and gamma band oscillations, contributes to the performance of visual reasoning tasks in typically developing (TD) (n = 18) children and AS children (n = 18). Brain activity was measured using a custom child-sized magneto-encephalograph. Imaginary coherence analysis was used as a proxy to estimate the functional connectivity between the occipital and other areas of the brain. Stronger connectivity from the occipital area, as evidenced by higher imaginary coherence in the gamma band, was associated with higher performance in the AS children only. We observed no significant correlation between the alpha or beta bands imaginary coherence and performance in the both groups. Alpha and beta bands reflect top-down pathways, while gamma band oscillations reflect a bottom-up influence. Therefore, our results suggest that visual reasoning in AS children is at least partially based on an enhanced reliance on visual perception and increased bottom-up connectivity from the visual areas.
SEMIPARAMETRIC ESTIMATION OF LONG-MEMORY MODELS

This article revises semiparametric methods of inference on different aspects of long memory time series. The main focus is on estimation of the memory parameter of linear models, analyzing bandwidth choice, bias reduction techniques and robustness properties of different estimates, with some emphasis on nonstationarity and trending behaviors. These techniques extend naturally to multivariate series, where the important issues are the estimation of the long run relationship and testing of fractional cointegration. Specific techniques for the estimation of the degree of persistence of volatility for nonlinear time series are also considered.