Discrimination Factors Research Articles

Tissue characteristics of residual lesion in patients with acute coronary syndrome caused by plaque rupture versus plaque erosion: a single-center, retrospective, observational study.

Patients with acute coronary syndrome (ACS), frequently caused by plaque rupture (PR), often have vulnerable plaques in residual lesions as well as in culprit lesions. However, whether this occurs in patients with plaque erosion (PE) as well is unknown. We retrospectively analyzed the data of 88 patients with ACS who underwent both optimal coherence tomography (OCT) and intravascular ultrasound (IVUS). Based on plaque morphology of the culprit lesions identified using OCT, patients were classified into PE (n=23) and PR (n=35) groups. The tissue characteristics of residual lesions evaluated using integrated backscatter IVUS were compared between both groups after percutaneous coronary intervention. The PE group had a significantly lower percent lipid volume and a higher percent fibrous volume than the PR group (35.0±17.8% vs 49.2±13.4%, p<0.001; 63.2±17.1% vs 50.3±13.1%, p=0.002, respectively). Receiver operating characteristic curve analysis revealed that percent lipid volume in the residual lesions was a significant discriminant factor in estimating the plaque morphology of the culprit lesion (optimal cut-off value, <43.5%; sensitivity and specificity values were 73.9% and 68.6%, respectively). In conclusion, patients with PE had a significantly lower percent lipid volume and a significantly higher percent fibrous volume in the residual lesions than those with PR, suggesting that the nature of coronary plaques in patients with PE is different from that of those with PR.

A Prediction Nomogram for No-Reflow in Acute Myocardial Infarction Patients after Primary Percutaneous Coronary Intervention.

The coronary no-reflow (NR) phenomenon is an independent predictor of major adverse cardiac events (MACEs). This study aimed to establish a clinical and comprehensive nomogram for predicting NR in acute myocardial infarction (AMI) patients after primary percutaneous coronary intervention (pPCI). The multivariable logistic regression analysis was performed to determine the NR-related factors. A nomogram was established via several clinical and biochemical factors, and the performance was evaluated via discrimination, calibration, and clinical factors. The study consisted of 3041 AMI patients after pPCI, including 2129 patients in the training set (70%) and 912 patients in the validation set (30%). The NR event was 238 in the training set and 87 in the validation set. The level of N-terminal prohormone B-type natriuretic peptide (NT-proBNP), basophil count (BASO), neutrophil count (NEUBC), D-dimer, hemoglobin (Hb), and red blood cell distribution width (RDW.CV) in NR patients showed statistically significant differences. In the training set, the C-index was 0.712, 95% CI 0.677 to 0.748. In the validation set, the C-index was 0.663, 95% CI 0.604 to 0.722. A nomogram that may predict NR in AMI patients undergoing pPCI was established and validated. We hope this nomogram can be used for NR risk assessment and clinical decision-making and significantly prevent potentially impaired reperfusion associated with NR.

Clinical value of neuroimaging indicators of intracranial hypertension in patients with cerebral venous thrombosis

PurposeIntracranial hypertension (IH) frequently complicates cerebral venous thrombosis (CVT). Distinct neuroimaging findings are associated with IH, yet their discriminative power, reversibility and factors favoring normalization in prospective CVT patients are unknown. We determined test performance measures of neuroimaging signs in acute CVT patients, their longitudinal change under anticoagulation, association with IH at baseline and with recanalization at follow-up.MethodsWe included 26 consecutive acute CVT patients and 26 healthy controls. Patients were classified as having IH based on CSF pressure > 25 cmH2O and/or papilledema on ophthalmological examination or ocular MRI. We assessed optic nerve sheath diameter (ONSD), optic nerve tortuousity, bulbar flattening, lateral and IVth ventricle size, pituitary configuration at baseline and follow-up, and their association with IH and venous recanalization.Results46% of CVT patients had IH. ONSD enlargement > 5.8 mm, optic nerve tortuousity and pituitary grade ≥ III had highest sensitivity, ocular bulb flattening and pituitary grade ≥ III highest specificity for IH. Only ONSD reliably discriminated IH at baseline. Recanalization was significantly associated with regressive ONSD and pituitary grade. Other neuroimaging signs tended to regress with recanalization. After treatment, 184.9 ± 44.7 days after diagnosis, bulbar flattening resolved, whereas compared with controls ONSD enlargement (p < 0.001) and partially empty sella (p = 0.017), among other indicators, persisted.ConclusionONSD and pituitary grading have a high diagnostic value in diagnosing and monitoring CVT-associated IH. Given their limited sensitivity during early CVT and potentially persistent alterations following IH, neuroimaging indicators can neither replace CSF pressure measurement in diagnosing IH, nor determine the duration of anticoagulation.

Fluorescent carbon dots for labeling of bacteria: mechanism and prospects-a review.

The search for bacteria-labeling agents that are more efficient and less toxic compared to existing staining dyes is ongoing. Fluorescent quantum dots and carbon dots (CDs) have been extensively researched for various bioimaging applications. Priority is given to CDs due to several advantages, including lower toxicity, versatility in tuning their properties, and better photostability compared to metal-based quantum dots. Although significant progress is still needed to replace existing dyes with CDs for bacteria labeling, they offer promising potential for further improvement in efficiency. Surface charges and functional groups have been reported as decisive factors for bacterial discrimination and live/dead assays; however, a complete guideline for preparing CDs with optimum properties for efficient staining and predicting their labeling performance is lacking. In this review, we discuss the application of fluorescent CDs for bacterial labeling and the underlying mechanisms and principles. We primarily focus on the application and mechanism of CDs for Gram differentiation, live imaging, live/dead bacteria differentiation, bacterial viability testing, biofilm imaging, and the challenges associated with application of CDs. Based on proposed mechanisms of bacterial labeling and ambiguous results reported, we provide our view and guidelines for the researchers in this field to overcome the challenges associated with bacteria labeling using fluorescent CDs.

Species-specific trophic discrimination factors can reduce the uncertainty of stable isotope analyses

Stable isotope analysis has been broadly used to study food webs, but often relies on inaccurate assumptions of trophic isotopic discriminations, which could lead to misinterpretation of obtained results. While many taxa exhibit similar trophic discrimination factors (TDFs), crayfish, exhibit omnivorous feeding strategies, yet TDFs are missing. In this study, we determined TDFs and tissue biokinetic parameters of the marbled crayfish Procambarus virginalis as a model species. Moreover, we compared commonly used TDFs and those determined from this study and applied them across species and ecosystems as a first attempt to compare the effect of species-specific TDFs in Bayesian trophic mixing models. Our results revealed differences between the TDFs of different tissues and biokinetic parameters of crayfish. Our result also revealed TDFs differences between crayfish relying mostly on plants versus those relying on an animal diet. We found differences of TDF suitability among species and ecosystems, highlighting the need for specific TDFs for different crayfish species. This study improves our understanding and the need for species-calibrated TDFs for robust statistical analysis of stable isotope data. Our approach is widely applicable across taxa and ecosystems to reduce the bias introduced by using unspecific TDFs in Bayesian mixing models.

피지컬 리터러시(Physical Literacy) 측정 도구 PPLI(Perceived Physical Literacy Instrument)의 타당성 연구: 한국 중학생 대상

Objectives The purpose of this study was to investigate validation of the Korean PPLI questionnaire, which can measure an individual’s perceived Physical Literacy, for middle school students in South Korea.&#x0D; Methods The subjects consisted of 608 students (male: 317 and female: 291) from the 1st to 3rd grade at five public middle schools in D Metropolitan City of Korea. The Korean PPLI scale for this study was completed through translation, reverse translation, and content review by expert groups. For data analysis, descriptive statistics, confirmatory factor analysis, construct validity analysis were performed, using SPSS 26 and AMOS 27 statistical program.&#x0D; Results The results showed that first, the total score of the study participants ranged from 10 to 44 points, with a mean of 33.11 and male students had higher average scores than female one in all sub-factors. Second, the results of CFA, Chi-square (x2=146.233, df=24, p&lt;.001), RMSEA=0.092, RMR=0.51, GFI=0.948. IFI=0.947, TLI=0..921, CFI=0.947 showed acceptable model fit. And as a result of examining the factor structures, the three-factor model outperformed alternative models. Third, as a result of the convergent validity analysis, the factor loading (0.59-0.91) of all items meet the criterion (&gt;0.5), AVE value ranged from 0.361 to 0.651, and CR value ranged from 0.629 to 0.847. And as a result of the discriminant validity analysis, factor 1 and factor 3 were judged appropriate under the two discriminant conditions, but factor 2 was judged inappropriate due to the low AVE value in the first discrimination condition (AVE&gt;r 2).&#x0D; Conclusions Based on the results of this study, the Korean PPLI questionnaire scale was a valid and reliable measurement tool among Korean adolescents. Therefore, it is expected to be used as a useful tool for understanding the perceived Physical Literacy of Korean adolescents.&#x0D;

Assessment of food safety risk using machine learning-assisted hyperspectral imaging: Classification of fungal contamination levels in rice grain

A rapid and nondestructive assessment of food safety risk using machine learning-assisted hyperspectral imaging was developed for classification of fungal contamination in brown rice grain. Brown rice was inoculated with Penicillium. The fungal infected rice was then mixed with healthy rice to obtain 0 %, 5 %, 25 %, 50 % and 100 % (w/w) contamination of infected rice. Volatile compounds including pentamethyl-heptane, decane, dodecane, 3-octanone, and 1-octen-3-ol were found in fungal infected rice, as analyzed using gas chromatography-mass spectrometry. The HSI system was used to collect spectral reflectance and spatial data of the samples covering the wavelength range of 400–1000 nm. The hypercubed data were analyzed using machine learning algorithms, including principal component analysis (PCA), discriminant factor analysis (DFA) and support vector machine (SVM). Using PCA for data reduction, 3 principal components were extracted with a cumulative variance of 90.53 %. DFA (linear and quadratic algorithms) and SVM (linear, quadratic, cubic, and Gaussian algorithms) were then used to classify the samples. HSI integrated with Gaussian SVM gave 93.4% accuracy which was best for classifying rice with different percentages of contamination. The image analysis gave a pseudo-color distribution map which facilitated the visualization of the contaminated rice by presenting data in an uncomplicated image. The machine learning-assisted HSI can be used as a rapid, nondestructive and chemical-free tool for an assessment of food safety risk for rice grain.

Controlled generation of OAM-switchable vortex beams at 639 nm from a Pr3+: YLF laser

In this paper, we reported and demonstrated a blue LD-pumped Pr3+: YLF laser for the controlled generation of orbital angular momentum (OAM) switchable vortex beams at 639 nm. To begin with, the quantitative tilt imbalance of the resonator was introduced to select the higher-order Hermite-Gaussian (HG) modes by utilizing the eigenvector method and introducing the concept of mode discriminant factor. Moreover, the mode converter, composed of two cylindrical mirrors, was applied to convert the Hermite- Gaussian (HG) modes into the Laguerre-Gaussian (LG) modes with the OAM. Then, the experiment setup was built to validate the correctness and effectiveness of the quantitative tilt imbalance. The results showed that the vortex beams with OAM of 0 to ±14 at 639 nm can be obtained by adjusting the tilted angle of the output mirror, which agreed well with the simulation results, and the slope efficiencies of the vortex beams with OAM = 1, 2, and 3 are 11.64%, 8.01%, and 6.05%, respectively. The method provided a viable solution for the generation of visible vortex beams with switchable OAM from the Pr3+: YLF laser.

Perceived Discrimination and Other Factors Influencing Self-Esteem in Persons with Albinism in North Central Nigeria

Perceived Discrimination and Other Factors Influencing Self-Esteem in Persons with Albinism in North Central Nigeria

Diet–tissue discrimination factors and turnover rates of carbon and nitrogen stable isotopes in the mottled skate Beringraja pulchra based on diet-switching experiments

Stable isotope analysis is robust tool to elucidate the diet, trophic position, and migration of typically large, highly mobile marine predators such as elasmobranchs. However, it is necessary to understand the diet–tissue discrimination factors and isotopic turnover rates of target animals. In this study, diet-switching experiments were conducted on the mottled skate (Beringraja pulchra (Liu, 1932)), caught off Sarufutsu, Hokkaido, Japan, to elucidate the diet–tissue discrimination factors and isotopic turnover rates for carbon and nitrogen stable isotopes. Ninety juvenile skates were fed Euphausia superba (C:N ratio = 3.9 ± 0.06, δ15N = 3.7±0.26‰ and δ13C = –25.9±0.15‰) to satiation at intervals of 2–3 days, and their muscle and liver tissues were serially sampled during 400 experimental days and used for stable isotope analysis. Both carbon and nitrogen stable isotopes reached steady state within the experimental days, and the estimated diet–tissue discrimination factors based on the fitting models were Δ13C = 1.5‰ and Δ15N = 2.3‰ for liver tissues and Δ13C = 3.4‰ and Δ15N = 3.5‰ for muscle tissues. The estimated turnover rates were 0.034 day–1 for δ13C and 0.039 day–1 for δ15N for liver tissues and were higher than those for muscle tissues (0.021 day–1 for δ13C and 0.019 day–1 for δ15N). In addition, the growth-based isotopic turnover rate model comprising juvenile skates revealed that the contribution of growth rate to the isotopic turnover rate was low.

Investigating the metabolite signature of an altered oral microbiota as a discriminant factor for multiple sclerosis: a pilot study

In multiple sclerosis (MS), alterations of the gut microbiota lead to inflammation. However, the role of other microbiomes in the body in MS has not been fully elucidated. In a pilot case-controlled study, we carried out simultaneous characterization of faecal and oral microbiota and conducted an in-depth analysis of bacterial alterations associated with MS. Using 16S rRNA sequencing and metabolic inference tools, we compared the oral/faecal microbiota and bacterial metabolism pathways in French MS patients (n = 14) and healthy volunteers (HV, n = 21). A classification model based on metabolite flux balance was established and validated in an independent German cohort (MS n = 12, HV n = 38). Our analysis revealed decreases in diversity indices and oral/faecal compartmentalization, the depletion of commensal bacteria (Aggregatibacter and Streptococcus in saliva and Coprobacter and Roseburia in faeces) and enrichment of inflammation-associated bacteria in MS patients (Leptotrichia and Fusobacterium in saliva and Enterobacteriaceae and Actinomyces in faeces). Several microbial pathways were also altered (the polyamine pathway and remodelling of bacterial surface antigens and energetic metabolism) while flux balance analysis revealed associated alterations in metabolite production in MS (nitrogen and nucleoside). Based on this analysis, we identified a specific oral metabolite signature in MS patients, that could discriminate MS patients from HV and rheumatoid arthritis patients. This signature allowed us to create and validate a discrimination model on an independent cohort, which reached a specificity of 92%. Overall, the oral and faecal microbiomes were altered in MS patients. This pilot study highlights the need to study the oral microbiota and oral health implications in patients with autoimmune diseases on a larger scale and suggests that knowledge of the salivary microbiome could help guide the identification of new pathogenic mechanisms associated with the microbiota in MS patients.

Peer-Assessment Academic Integrity Scale (PAAIS-24)

This study aims to develop an academic integrity scale to help lecturers evaluate the academic integrity of university students with peer-assessment learning experiences using the ADDIE research and development method. Twenty-four items were designed using the concepts of academic integrity; honesty, trust, fairness, respect, responsibility, and courage validated by six raters and tested on 520 students from various universities in Indonesia. Testing content validity using the Aiken-V formula, construct validity testing using discriminant indexes, factor analysis (Exploratory and Confirmatory Factor Analysis), and concurrent validity testing by correlating PAAIS-24 with the developed Academic Integrity Scale. While the reliability test used Cronbach's alpha formula. The study results proved that each item of content validity meets with an Aiken value &gt;0.80; on construct validity testing, the discriminant index value is &gt;0.50, and the EFA and CFA loading factor values are &gt;0.50. In addition, the model is appropriate because the theoretical model of PAAIS-24 is in accordance with empirical data. Whereas in reliability testing, Cronbach's alpha value is 0.95. Lastly, PAAIS-24 is one of the credible instruments. It contributes to developing knowledge that assists lecturers in measuring, assessing, and evaluating student academic integrity based on peer-assessment to promote increased academic performance. Doi: 10.28991/ESJ-2024-08-02-09 Full Text: PDF

Effect of unpowered ventilation caps and shaft parameters on fire smoke spread in the natural ventilation tunnel with shafts

Shaft-type natural ventilation offer a sustainable and cost-effective alternative to mechanical systems for the mitigation of smoke hazards. This study investigated the behavior of smoke with the application of unpowered ventilation caps in 1/15 scale shallow-buried urban road tunnels with shafts, and analyzed parameters such as the shaft axis wheelbase, shaft width, shaft width-to-height ratio, and heat release rate (HRR). The results show that the dimensionless HRR as an independent relationship with the dimensionless ceiling temperature rise in both the presence and absence of the unpowered ventilation cap. According to the experimental results, dimensionless length of smoke backlayering increases significantly with the increase of the HRR. In addition, the smoke backlayering length is positively correlated with the shaft width, and the backlayering length decreases and then increases with increases of the axis wheelbase. Moreover, the chimney effect is facilitated with the shaft height increase, which enhances exhaust effect, and the backlayering length decreases with the increase in the shaft height when the aspect ratio is greater than 0.5. Once the critical shaft width-to-height ratio is reached, the change in the shaft height no longer has an effect on the backlayering length. Finally, a dimensionless backlayering length calculation model based on the shaft parameters with different shaft exhaust effects is developed by combining the discriminant factors. The findings have crucial implications for fire prevention and safety management, and provide a valuable reference for future studies and engineering applications.

Influence of Gender Discrimination on Work Performance of Female Graduates in Rural Areas of Hyderabad District

This study looks at the multifaceted problems faced by the graduate females who are working in the public or private sectors in rural areas of Hyderabad District. It was a descriptive research, using the random sampling method, 150 females who were working in different public or private sectors were selected as sample. Likert scale 5.0 was used and to ensure the construct validity of the questionnaire, factor analysis technique was applied. After ensuring all the assumptions of parametric tests, regression analysis was used to see the influence of the factors of gender discrimination on work performance of graduate females. The Null Hypothesis (Ho) was not supported with the value of R=.378 R2 = .143, F=5.454, Sig=0.002). The data analysis result revealed that the job performance of female graduates is highly influenced by the socio-cultural factors which consisted of family support, gender-based discrimination and workplace harassment. The study is significant for public and private sectors for framing the policies regarding safety and security of their female employees. The study is also significant for the communities to promote gender-inclusive settings, hence promoting the empowerment and achievement of female graduates in rural areas of Hyderabad District.

Social class stigma and poorer health behaviors: Evidence from the eating in America study

Although the association between objective markers of low socioeconomic status (SES) and poor health is well established, one underexamined possibility is that over and above objective SES, social class stigma—experiences and anticipation of discrimination based on social class—might undermine people's ability to engage in healthy behaviors. Participants (N = 2022) were recruited between December 2019 and January 2020 via a national Qualtrics panel that was census-matched to the U.S. population in age, gender, income, race/ethnicity, and census region. Participants completed measures of class stigma, alcohol use, disordered eating, comfort eating, sleep disturbance, physical activity, and demographics. Controlling for objective SES and demographics, generalized linear regression models indicated that class stigma was associated with significantly greater alcohol use, disordered eating, greater comfort eating, and sleep disturbance but not less physical activity. Class stigma was not associated with health behaviors after full adjustment for weight/racial discrimination and psychological factors. Results from this investigation suggest that beyond one's objective SES, the stigma associated with having low class may also contribute to poorer health behaviors.

A Model Minority? Asian-White Differences in Federal Careers

The stereotype of Asians as a model minority suggests that they either do not experience discrimination or overcome it through higher education, hard work, and respect for authority. We test that stereotype for Asian Americans in the federal service using both Census data and surveys of federal employees. We examine (1) whether Asians attain the same pay levels and managerial authority as whites; (2) whether differences in education, experience, citizenship, and English ability explain differences in pay and authority; (3) whether those differences vary across Asian sub-groups; and (4) whether Asians are as satisfied with their jobs and the treatment they receive. We find moderate Asian-white pay differences, which varied substantially across national origin groups. Asian-white differences in access to managerial authority, however, are substantial across all national origin groups. Asians’ higher educational attainment and weaker English abilities contributed to differences in pay and authority, but unexplained disparities remained, potentially due to discrimination and/or unmeasured factors. Surprisingly, Asians expressed a stronger belief that the federal service allocates rewards fairly and were more satisfied than whites with their own developmental and advancement opportunities despite those pay and leadership disparities. They were, however, somewhat less satisfied with pay, co-workers, and supervisors.

Selective Quantification of Bacteria in Mixtures by Using Glycosylated Polypyrrole/Hydrogel Nanolayers.

Here, we present a covalent nanolayer system that consists of a conductive and biorepulsive base layer topped by a layer carrying biorecognition sites. The layers are built up by electropolymerization of pyrrole derivatives that either carry polyglycerol brushes (for biorepulsivity) or glycoside moieties (as biorecognition sites). The polypyrrole backbone makes the resulting nanolayer systems conductive, opening the opportunity for constructing an electrochemistry-based sensor system. The basic concept of the sensor exploits the highly selective binding of carbohydrates by certain harmful bacteria, as bacterial adhesion and infection are a major threat to human health, and thus, a sensitive and selective detection of the respective bacteria by portable devices is highly desirable. To demonstrate the selectivity, two strains of Escherichia coli were selected. The first strain carries type 1 fimbriae, terminated by a lectin called FimH, which recognizes α-d-mannopyranosides, which is a carbohydrate that is commonly found on endothelial cells. The otherE. coli strain was of a strain that lacked this particular lectin. It could be demonstrated that hybrid nanolayer systems containing a very thin carbohydrate top layer (2 nm) show the highest discrimination (factor 80) between the different strains. Using electrochemical impedance spectroscopy, it was possible to quantify in vivo the type 1-fimbriated E. coli down to an optical density of OD600 = 0.0004 with a theoretical limit of 0.00005. Surprisingly, the selectivity and sensitivity of the sensing remained the same even in the presence of a large excess of nonbinding bacteria, making the system useful for the rapid and selective detection of pathogens in complex matrices. As the presented covalent nanolayer system is modularly built, it opens the opportunity to develop a broad band of mobile sensing devices suitable for various field applications such as bedside diagnostics or monitoring for bacterial contamination, e.g., in bioreactors.

Driving factors of individual differences in broad retrieval ability: Gr is more than the sum of its parts.

Broad retrieval ability (Gr) posits an essential factor of human cognitive abilities. Previous literature indicates Gr is best modeled as a higher-order factor model with lower-level factors such as ideational fluency (IF), word fluency (WF), expressional fluency (EF), or figural fluency (FF). However, the dimensionality of Gr is not well studied. Furthermore, it remains unclear whether specific retrieval affordances such as differing retrieval time periods (e.g., short vs. long) can be psychometrically separated from more general retrieval affordances. Such a distinction would imply differential associations between specific retrieval, general retrieval, and other cognitive abilities, which, in turn, depict a vital part of explanatory models of individual differences in Gr. To test these assumptions, we conducted a multivariate study (N = 331) and evaluated competing latent variable measurement models for a variety of Gr tests. We then regressed the best measurement model onto working memory capacity, secondary memory, mental speed, and crystallized intelligence in order to evaluate the distinctiveness of Gr. Our results suggest that no specific retrieval affordances with regard to time periods can be distinguished. A higher-order model, with a second-order Gr factor above three first-order factors (IF, WF, EF, and FF) fitted the data best, extending previous literature by increasing construct coverage through the implementation of FF. All covariates show incremental predictive validity, beyond their communality. Summarizing, our results endorse a perspective on Gr as a strong and discriminant factor of cognitive abilities that is not affected by time constraints, and show that Gr is more than a linear combination of its parts. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Social determinants of health and diabetes: using a nationally representative sample to determine which social determinant of health model best predicts diabetes risk

ObjectivesSocial determinants of health (SDOH) research demonstrates poverty, access to healthcare, discrimination, and environmental factors influence health outcomes. Several models are commonly used to assess SDOH, yet there is limited understanding of how these models differ regarding their ability to predict the influence of social determinants on diabetes risk. This study compares the utility of four SDOH models for predicting diabetes disparities.Study designWe utilized The National Longitudinal Study of Adolescent to Adulthood (Add Health) to compare SDOH models and their ability to predict risk of diabetes and obesity.MethodsPrevious literature has identified the World Health Organization (WHO), Healthy People, County Health Rankings, and Kaiser Family Foundation as the conventional SDOH models. We used these models to operationalize SDOH using the Add Health dataset. Add Health data were used to perform logistic regressions for HbA1c and linear regressions for body mass index (BMI).ResultsThe Kaiser model accounted for the largest proportion of variance (19%) in BMI. Race/ethnicity was a consistent factor predicting BMI across models. Regarding HbA1c, the Kaiser model also accounted for the largest proportion of variance (17%). Race/ethnicity and wealth was a consistent factor predicting HbA1c across models.ConclusionPolicy and practice interventions should consider these factors when screening for and addressing the effects of SDOH on diabetes risk. Specific SDOH models can be constructed for diabetes based on which determinants have the largest predictive value.

Identification of mine water sources using a multi-dimensional ion-causative nonlinear algorithmic model

Based on the nonlinear algorithmic theory, the R-SVM water source discrimination model and prediction method were established by using the piper qualitatively to compare the differences between the ionic components and R-type factor approximation indicator input dimensions. Taking the mine water samples of Zhaogezhuang Coal Mine as an example, according to the chemical composition analysis of the water samples from different monitoring points, six indexes of Na+, Ca2+, Mg2+, Cl–, SO42– and HCO3– were selected as the discrimination factors. According to the water characteristics of each aquifer and the actual needs of discrimination, the water inrush sources in the mining area were divided into four categories: The goaf water is class I, Ordovician carbonate is class II, Sandstone fracture water from the 13 coal system is class III, and Sandstone fracture water from the 12 coal system is class IV. Taking 56 typical water inrush samples as training samples, 11 groups for prediction samples, establish the input index as typical ion content, output as water source type, using SPSS statistics and MATLAB to realize the R-SVM water source discriminant analysis model, automatically establishing the mapping relationship between the water quality indexes and the evaluation standards, which can achieve the purpose of rapid and accurate discrimination of the water sample data. The results showed that the accuracy of the R-SVM model classification was 90.90% in the verification of the water source discrimination example of Zhaogezhuang mine and the coupled model has high accuracy, good applicability and discriminant ability, and has certain guiding significance for the prevention and control of water damage and the related field work.