The present study examines inner and outer suburban ring attainment outcomes among racial and ethnic groups residing in the nation’s metropolitan areas. The main objective is to evaluate the extent to which the relationship between racial and ethnic group’s socioeconomic status characteristics and residence between inner and outer suburban rings conforms to the tenets of the spatial assimilation model. Using micro-level data from the 5-year 2012-2016 American Community Survey, the author calculates multinomial logistic regression models to determine the effects of SES and other relevant predictors on residence within the nation’s metropolitan area’s suburban inner and outer rings. The results both confirm and contradict the main tenets of the spatial assimilation model. To the extent that income, education, and homeownership are positively related to residence in both suburban rings, the findings also suggest that access to inner and outer rings is hierarchically stratified by race and ethnicity.

In this paper, carbon nanotubes modified screen-printed electrode (CNTs/SPE) was prepared and the CNTs/SPE was employed for the electrochemical determination of antioxidant substance Chlorogenic acids (CGAs). A pair of well-defined redox peak of CGA was observed at the CNTs/SPE in 0.10 mol∙L^-1 acetic acid-sodium acetate buffer (pH 6.2) and electrode process is adsorption-controlled. Cyclic voltammetry (CV) and differential pulse voltammetry (DPV) method for the determination of CGA were proposed based on the CNTs/SPE. Under the optimal conditions, the proposed method exhibited linear ranges from 4.73×10^-7 to 4.45×10^-5 mol∙L^-1, the linear regression equation was Ipa(µA) = 4.1993 C (mol∙L^-1)+1.1039 (r = 0.9976) and the detection limit for CGA could reach 3.25×10^-6 mol∙L^-1. The recovery of matrine was 94.74~106.65% (RSD = 2.92%) in coffe beans. The proposed method is quick, sensitive, reliable, and can be used for the determination of CGA.

Thoracic aortic aneurysms (TAAs) pose critical health risks, often asymptomatic until a rupture or dissection occurs. Guidelines recommend surgical repair based on specific aortic diameters and risk factors, emphasizing the importance of early detection and intervention. Despite established clinical risk factors for early detection in TAAs, the influence of racial and ethnic disparities on TAAs remains underexplored. This study aims to provide a comprehensive summary of existing research on racial and ethnic disparities in the presentation and outcomes of TAAs. Methods: This literature review was conducted using a systematic search strategy, in order to explore racial and ethnic differences in the presentation and surgical outcomes of patients with TAAs. Results: The findings demonstrated that black patients were younger at presentation and had a higher incidence of ruptured TAAs than non-black patients. Furthermore, compared to non-black patients, black patients had higher rates of cardiac arrhythmia and COPD, as well as comorbidities such as diabetes, hypertension, and renal insufficiency. For black patients undergoing open surgery, the surgical results showed improved 5-year survival rates after repair but higher perioperative mortality rates. All-cause or in-hospital mortality did not significantly differ between the racial groups, according to four studies. Discussion: This review highlights significant racial and ethnic disparities in TAA presentation and outcomes, underscoring the need for personalized risk stratification models. Standardized racial and ethnic definitions are essential for consistent and reliable research. Future studies should focus on refining risk assessment models to enhance diagnostic and therapeutic strategies, ultimately improving patient outcomes across diverse populations.

53% of adults in the US acknowledge racial bias as a significant issue, 23% of Asian adults experience cultural and ethnic bias, and more than 60% conceal their cultural heritage after racial abuse. AI models like ChatGPT and Google Bard, trained on historically biased data, inadvertently amplify racial and ethnic bias and stereotypes. This paper addresses the issue of racial bias in AI models using scientific, evidence-based analysis and auditing processes to identify biased responses from AI models and develop a mitigation tool. The methodology involves creating a comprehensive database of racially biased questions, terms, and phrases from thousands of legal cases, Wikipedia, and surveys, and then testing them on AI Models and analyzing the responses through sentiment analysis and human evaluation, and eventually creation of an 'AI-BiasAudit,' tool having a racial-ethnic database for social science researchers and AI developers to identify and prevent racial bias in AI models.

Background: This study delves into the examination of racial and ethnic disparities in the distribution of the Monkeypox (MPOX) virus vaccine within the United States, offering a critical healthcare perspective on an emerging public health concern. It particularly focuses on the demographic patterns associated with MPOX transmission and the allocation of vaccines. Methods: A comprehensive analysis was conducted, drawing on a wide array of data sources to understand the vaccine distribution and demographic trends in the United States. The study scrutinized three main aspects: MPOX cases by race and ethnicity, vaccine administration across different racial and gender categories, and the potential disparities therein. Results: The findings reveal significant disparities in the distribution of vaccine doses, with males, particularly gay, bisexual, and other Men who have sex with men (MSM), receiving the majority of doses. Moreover, substantial variations in MPOX cases are observed among different racial and ethnic groups, emphasizing the need for culturally sensitive public health strategies. Conclusions: The study underscores the urgent need for targeted public health interventions to address disparities and safeguard the well-being of those at higher risk, particularly MSM. It highlights the importance of equity in vaccine distribution and culturally sensitive approaches, and serves as a foundation for shaping effective public health policies and strategies to mitigate the spread of MPOX. This research advances our understanding of healthcare disparities in the context of an emerging viral infection, providing valuable insights for future public health initiatives.

Developmental, clinical, and epidemiological research have demonstrated the salience of perceived racial discrimination (PRD) as a contributor to negative mental health outcomes in adolescence. This article summarizes secondary analyses of cross-sectional data from a large-scale youth survey within a predominantly rural state to estimate the prevalence and strength of association between PRD and serious psychological distress, suicidal ideation, and prior suicidal attempts. Data from 93,812 students enrolled in Grades 6, 8, 10, and 12 within 129 school districts across Kentucky were examined to determine prevalence rates for subgroups within the cohort. Logistic regression analyses assessed differences and established comparative strength of association among these variables for racial/ethnic subgroups. PRD was self-reported at high rates across several demographic subgroups and was most evident among Black (24.5%) and Asian (22.1%) students. Multiracial students experienced the highest rates of both SPD and suicidality. Both for the entire cohort and for each racial/ethnic subgroup, PRD was significantly associated with increased likelihood of negative mental health outcomes, although the strength of these associations varied across subgroups and developmental levels. Implications for early intervention and prevention are discussed.

There is a disproportionate increase in the incidence of diet-related cardiometabolic disorders in racial and ethnic minority groups. This systematic review examines the extent to which diet-induced changes in health outcomes have been discussed by race or ethnicity in randomized controlled trials recruiting both minority and non-Hispanic White groups. Databases i.e. PubMed, Cochrane library and Web of Science were searched up to November 2019. Studies that discussed effects of defined dietary interventions on health outcomes by racial or ethnic minority group vs. non-Hispanic Whites (n=29) were included in the review. Most studies were conducted in Black vs. White people testing effects of energy restriction, macronutrient modification, sodium reduction, or variations of the Dietary Approaches to Stop Hypertension (DASH) diet on cardiometabolic outcomes. There was limited focus on other minority groups. Evidence suggests greater blood pressure reduction for Black people compared to Whites particularly on DASH (or similar) diets. Overall, there was limited consideration for group-specific eating patterns and diet acceptability in most studies. Adequately powered studies are needed for accurate interpretation of race by diet effects. With emerging precision nutrition initiatives, it is imperative to ensure adequate representation of racial and ethnic subgroups for addressing nutrition-related health disparities.

Introduction Prostate Cancer (PCa) exhibits one of the widest racial and socioeconomic disparities. PCa disparities have also been widely linked to location as living in more deprived regions was associated with lower healthcare access and worse outcomes. This study aims to examine PCa survival across various US counties in function of different socioeconomic profiles and discuss the role of potential intermediary factors. Methods The SEER database linked to county-level SES was utilized. Five-year PCa-specific survival using the Kaplan Meier method was performed for 5 racial/ethnic categories in function of SES quintiles. Multilevel Cox proportional hazards regression was performed to assess the relationship between county-level SES and PCa survival. Multivariate regression analysis was performed to examine the role of healthcare utilization and severity. Results 279,000 PCa records were extracted, 5-year PCa-specific survival was 94%. Overall, living in counties with worst poverty/income quintile and highest proportions of foreign-born/language-isolated increased PCa mortality by 23% each. No association was observed with county-level High-School education, while Bachelor’s-level education decreased mortality risk by 23%. Associations varied considerably upon racial/ethnic stratification. Multilevel analyses showed varying contributions of individual and area-level factors to survival within minorities. The relationship between SES and PCa survival appeared to be influenced by healthcare utilization and disease stage/grade. Discussion Racial/ethnic categories responded differently under similar county-level SES and individual-level factors to the point where disparities reversed in Hispanics. The inclusion of Healthcare utilization and severity factors may provide partial early support for their role as intermediaries. Healthcare access (insurance) might not necessarily be associated with better PCa survival, through performing biopsy and or/surgery. County-level education plays an important role in PCa decision-making as it might elucidate discussions of other non-invasive management options. Conclusion Findings of this study demonstrate that interventions need to be tailored according to each group's needs. This potentially informs the focus of public health efforts in terms of planning and prioritizing. This study could also direct further research delving into pathways between area-level characteristics with PCa survival.

Recent clinical SARS-CoV-2 studies link diabetes, cardiovascular disease, and hypertension to increased disease severity. In the US, racial and ethnic minorities and low socioeconomic status (SES) individuals are more likely to have increased rates of these comorbidities, lower baseline health, limited access to care, increased perceived discrimination, and limited resources, all of which increase their vulnerability to severe disease and poor health outcomes from SARS-CoV-2. Previous studies demonstrated the disproportionate impact of pandemic and seasonal influenza on these populations, due to these risk factors. This paper reviews increased health risks and documented health disparities of racial and ethnic minorities and low SES individuals in the US. Pandemic response must prioritize these marginalized communities to minimize the negative, disproportionate impacts of SARS-CoV-2 on them and manage spread throughout the entire population. This paper concludes with recommendations applicable to healthcare facilities and public officials at various government levels.

To ensure consumers can purchase high-quality rice, accurate identification of rice varieties is particularly important. Methods: This article conducts research based on machine learning algorithms from the perspectives of image, spectrum, and spectrogram fusion. Six types of hyperspectral image data of rice were preprocessed using convolutional smoothing (SG) and multiple scatter correction (MSC). Texture information of the images was extracted using gray-level co-occurrence matrix. Spectra, texture, and spectrogram data were fused into a new matrix. Spectral, texture, and spectrogram fusion data were used as inputs for the model, and support vector machines (SVM), logistic regression (LR), and K-nearest neighbors (KNN) classification models were constructed and compared. Results: From the classification results, the spectrogram fusion classification performance was better than classification models using only spectra or texture. Conclusion: The research results showed that the accuracy of SVM and LR classification models exceeded 90%, and the LR model performed the best, effectively classifying rice varieties.

Sepsis, a syndrome characterized by systemic inflammation during infection, continues to be one of the most common causes of patient mortality in hospitals across the United States. While standardized treatment protocols have been implemented, wide variability in clinical outcomes persist across racial groups. Specifically, Black and Hispanic populations are frequently associated with higher rates of morbidity and mortality in sepsis compared to the Caucasian population. While this is often attributed to systemic bias against minority groups, a growing body of literature has found patient, community, and hospital-based factors to be driving racial differences. In this article, we provide a focused review on some of the factors driving racial disparities in sepsis. We also suggest potential interventions aimed at reducing health disparities in the prevention, early identification, and clinical management of sepsis.

Keywords: pelvic ultrasound, follicle number per ovary, FNPO, ovarian volume, PCOM, upper normal limits, referral population

The Roma population constitutes the largest ethnic minority in Europe, however, data regarding the prevalence of non- communicable diseases are still scarce in the medical literature. The aim of this study was to assess the clinical and metabolic particularities of a Roma population with diabetes, in comparison with a group of Romanian Caucasians. We conducted an observational, transversal study and evaluated 808 adult patients with diabetes mellitus, from a tertiary hospital providing diabetes care, aged between 18 and 89 years old, of whom the majority were men (52.84%). Most of them had type 2 diabetes mellitus (T2DM), reaching 95.1% the Caucasian group and 87.8% among the Roma patients. 81.1% of the Caucasian patients had hypertension, approximately 15% higher than the Roma group, while more than half of the patients in both groups had obesity. There were no differences concerning myocardial infarction, however, the number of patients with history of stroke was 2.1 times higher in the Roma group compared to Caucasians. Chronic kidney disease was present in 22.1% of the Roma patients, 33.25% had retinopathy, and 72.7% presented polyneuropathy. The prevalence of cardiovascular risk factors, cardiovascular disease and microvascular complications among the study Roma population are quite significant, underscoring the importance of ethnic disparities in approaching healthcare management strategies.

Humans tend to become angry whenever a reward they were expecting is 'unfairly' taken away. We presently tested whether situational anger induced by unfair reward omissions may influence (pre-existing) racial biases across self-identified Liberals (n = 119) and Conservatives (n = 115). In the study, participants were exposed to a frustration induction task (or a control variant), followed by implicit and explicit evaluations of White and Black male targets. Frustrated Conservatives were more likely to exhibit implicit anti-Black bias relative to non-frustrated Conservatives, but not significantly so (p's > .2). Frustrated Liberals became significantly anti-White relative to both non-frustrated Liberals and Frustrated Conservatives (p's < .006). Both Liberals and Conservatives became equally angered following reward omissions, but only the former became significantly anti-White. The present work highlights Liberals are more likely to exhibit frustration-augmented racial bias relative to Conservatives.

Glaucoma is undoubtedly a major worldwide disease and cause of blindness. The term glaucoma however encompasses a group of disorders with differing age of incidence, intraocular pressures and varying degrees of hereditability in which vision loss occurs through a characteristic mode of retinal ganglion cell death. There are also significant differences in frequencies of incidence and gene associations for this group of disorders amongst different groups of populations. The current literature often states definitive trends in incidence for ethnic groups that fail to take into account an overall genetic fine structure for these groups. The present review intends to present an overview of some of the background necessary to discuss the genetic basis of glaucoma before describing some of the literature concerning the illness in Gypsy, Japanese, Scandinavian, Latino (Mexican and Brazilian) and Sub-Saharan African populations. It is intended that this review will give the reader a clearer picture of the diversity of worldwide glaucoma presentation which perhaps prove to question the current Ethnic view.

Breast cancer poses a global health challenge, yet the influence of ethnicity on the tumor microenvironment (TME) remains understudied. In this investigation, we examined immune cell infiltration in 230 breast cancer samples, emphasizing diverse ethnic populations. Leveraging tissue microarrays (TMAs) and core samples, we applied multiplex immunofluorescence (mIF) to dissect immune cell subtypes across TME regions. Our analysis revealed distinct immune cell distribution patterns, particularly enriched in aggressive molecular subtypes triple-negative and HER2-positive tumors. We observed significant correlations between immune cell abundance and key clinicopathological parameters, including tumor size, lymph node involvement, and patient overall survival. Notably, immune cell location within different TME regions showed varying correlations with clinicopathologic parameters. Additionally, ethnicities exhibited diverse distributions of cells, with certain ethnicities showing higher abundance compared to others. In TMA samples, patients of Chinese and Caribbean origin displayed significantly lower numbers of B cells, TAMs, and FOXP3-positive cells. These findings highlight the intricate interplay between immune cells and breast cancer progression, with implications for personalized treatment strategies. Moving forward, integrating advanced imaging techniques, and exploring immune cell heterogeneity in diverse ethnic cohorts can uncover novel immune signatures and guide tailored immunotherapeutic interventions, ultimately improving breast cancer management.

The mutation databases have vital importance in detecting genetic mutation and their corresponding phenotypes. The emergence of next generation sequencing genetic technologies has accelerated this process, and the growth of genetic disease identification has created a need for quality control and documentation of mutation-related information. Ethnic-specific mutation databases offer valuable information for researchers, and the article evaluates the homogeneity and effectiveness of these databases. The aim to raise awareness of NEMDBs to healthcare professionals, the general public, and researchers studying genetic disorders. The article also recommendations to improve the effectiveness of these databases.

Atopic dermatitis (AD) is a common chronic inflammatory skin disease with high prevalence worldwide, including countries from Asia, Africa and Latin America, and in different ethnic groups. In recent years, more attention on AD heterogeneity associated on multiple factors, including patient’s ethnic background, has been posed, resulting in an increasing body of clinical, genetic, epidemiologic, and immune-phenotypic evidence that delineate differences among racial groups with AD. Filaggrin (FLG) mutations, the strongest genetic risk factor for the development of AD, are detected in up to 50% of European and 27% of Asian AD patients, while very rarely in Africans. The Th2 activation is a common attribute of all ethnic groups, though the Asian endotype of AD is also characterized by an increased Th17-mediated signal whereas African Americans own a strong Th2/Th22 signature and the absence of Th1/Th17 skewing. In addition, the ethnic heterogeneity may own important therapeutic implications as the genetic predisposition may affect treatment response and, thereby, a tailored strategy that better targets the dominant immunologic pathways in each ethnic subgroup may be envisaged. Nevertheless, white patients with AD represent the largest ethnicity enrolled and tested in clinical trials and the most treated in a real-world setting, limiting the investigation about safety and efficacy across different ethnicities. The purpose of this review is to describe the heterogeneity of pathophysiology across ethnicities and its potential therapeutic implications.

Introduction: This analysis is conducted as a part of a quality improvement project aiming at identifying racial disparity in inpatient stroke quality of care. Methods: Get With The Guidelines (GWTG) database was used to identify all patients discharged with any stroke diagnosis between January and December 2021. Additional chart review was conducted to ensure the accuracy of racial/ethnic categorization. The sample was dichotomized to White vs non-White groups and compared with univariate analysis. Results: The study sample comprised 1,408 encounters (1,347 patients). Mean age 71±15 years, 51% women, 82% White patients, 15% non-White patients, 72% acute ischemic stroke (AIS); 15% transient ischemic attack (TIA), 9% intracerebral hemorrhage (ICH), 3% subarachnoid hemorrhage (SAH), and 1% stroke not otherwise specified. Non-White patients were younger, had fewer concomitant diagnoses, lower proportion of TIA and higher proportion of ICH (p=0.004). In AIS cohort, compared to White patients, non-White patients had less frequent ambulance (p=0.009), arrived to the hospital later than White patients (7.7 hours longer ; p<0.001), had more severe stroke, and had less frequent IV thrombolysis utilization (7% vs 13%; p=0.042). Similarly in the TIA cohort, non-White patients’ utilization of EMS was lower than White patients and their hospital arrival was delayed. In the ICH cohort, non-White patients were younger, had lower frequency of atrial fibrillation, and a non-significant trend towards higher disease severity. The SAH cohort had only 8 non-White patients, 6 of which were transferred to higher level of care hospital within a few hours of arrival, therefore. Importantly, the hospital-based quality metrics such as door-to-CT time, door-to-needle time, and the Joint Commission stroke quality metrics were similar between the two groups. Conclusion: There is a racial disparity in the pre-hospital phase of the stroke chain of survival of non-White patients impacting the IV thrombolysis utilization. The younger age and worse lipid profile and hemoglobin A1C of non-White patients suggest the need for better preventative care starting at young age.

Papillary thyroid carcinoma (PTC) presents a significant health concern, particularly among Hispanic women in the United States, who exhibit a disproportionately higher chance of developing an advanced disease when compared to the non-Hispanic population. Emerging evidence suggests coagulation factor X, encoded by F10 gene, has a potential role in inhibiting cancer cell migration. However, comprehensive investigations into the differential expression patterns of F10 in Hispanic versus non-Hispanic females remain limited. RNA-sequencing data was acquired from the TCGA database for white female patients, 166 non-Hispanic and 25 Hispanic. A statistically significant (p &lt; 0.05) 2.06-fold increase in F10 expression levels was detected in disease-free tumors compared to recurrent PTC tumors. Furthermore, an increase in F10 gene expression levels was also observed corresponding to approximately a 1.74-fold increase in non-Hispanic patients compared to Hispanic patients. The probability of tumor recurrence was 1.82 times higher in the cohort with low expression of F10 compared to the high expression cohort, correlating with the lower disease-free rates observed in Hispanic patients’ cohort when compared to non-Hispanics. This finding underscores the relevance of ethnic disparities in molecular profiles for understanding cancer susceptibility. Identifying F10 as a potential prognostic biomarker highlights avenues for targeted interventions and contributes to improving diagnostic and treatment strategies for diverse patient populations.

Trust is a cornerstone for fostering positive social interactions and catalyzing a thriving economy. Various demographic and cultural determinants shape the levels of trust among individuals and communities, thereby influencing the overall trust landscape within a population. Nigeria, characterized by its rich tapestry of ethnicities, religious diversity, and ongoing inter-ethnic tensions, offers a unique lens through which to explore the dynamics of generalized trust in a multifaceted social setting.This study delves into the interplay between generalized trust, religious affiliations, and ethnic backgrounds within the Nigerian context. Utilizing data from the most recent wave of the World Values Survey (WVS) conducted in 2012, which encompassed 1,759 participants, we scrutinized the religious and ethnic variables correlated with generalized trust levels, while controlling for other pertinent factors. Our findings reveal that both group membership and cultural traits are significantly linked to levels of generalized trust. By unpacking the variables that shape social trust, this study contributes valuable insights into the complex social fabric of multicultural societies.

Parental stresses are normal responses to raising children. They are affected by stresses parents and children accumulate and bring to their interrelations. Background factors like economic difficulties or the relations between the parents may affect parental stresses as well as demographic and environmental factors like noise and access to urban parks. Most studies on parental stress are based on a verified psychological questionnaire. We suggest using frequency domain heart rate variability index (HRV) to measure parental stress enabling, by thus, the measurement of physiological aspects of stress and risk to health. Parental stress is measured as the difference between HRV accumulated at home while staying with the children and without the husband and HRV measured in the neighborhood while staying without the children and the husband. We use the index to compare differences among Muslim and Jewish mothers in exposure to maternal stress at their homes and to expose the factors that predict differences in maternal stress. We found that Muslim mothers suffer from home-related maternal stress while Jewish mother do not. Number of children and ethnically related environmental aspects predict differences in maternal stress between Muslim and Jewish mothers. Muslims' lower access to parks stems from lack of home garden and parks in their neighborhoods in the Arab towns but mainly by restrictions on Muslim women's' freedom of movement to parks. Despite differences in levels of noise at home and in the status of the mother in the household, these factors did not predict differences in parental stress. Instead, the study highlights the crucial role of greenery and freedom of movement to parks in moderating home-related maternal stress.

Racial and ethnic disparities exist in diabetes prevalence, health services utilization, and out-comes including disabling and life-threatening complications. Home health care may especially benefit older adults with diabetes through individualized education, advocacy, care coordina-tion, and psychosocial support for patients and their caregivers. This study examined factors as-sociated with hospital discharge to home health care and subsequent utilization of home health care among a cohort of Medicare beneficiaries with diabetes, age 50 and older, living in the United States. The cohort (n=786,758) was followed for 14 days after a diabetes-related index hospitalization, using linked Medicare administrative, claims, and assessment data (2014-2016). Multivariate logistic regression models included patient demographics, comorbidities, hospital length of stay, geographic region, neighborhood area deprivation, and rural/urban setting. In ful-ly adjusted models, hospital discharge to home health care was significantly less likely among Hispanic (OR 0.8, 95% CI 0.8-0.8) and American Indian (OR 0.8, CI 0.8-0.8) compared to white patients. Among those discharged to home health care, all racial/ethnic minority patients were less likely to receive services within 14-days. Further work should focus on eliminating systemic racism in home health care referral and systemic barriers to receiving home health care services.

This study investigates the effect of perceived discrimination on the mental health of Afghan refugees, and secondly, tests the distress moderating effects of pre-migration traumatic experiences and post-resettlement adjustment factors. In a cross-sectional design, 259 Afghans completed surveys assessing perceived discrimination and a number of other factors using scales developed through inductive techniques. Multivariate analyses consisted of a series of hierarchical regressions testing the effect of perceived discrimination on distress, followed by a sequential analysis of moderator variables. Perceived discrimination was significantly associated with higher distress, and this relationship was stronger among those with a strong intra-ethnic identity, high civic engagement, and high pre-resettlement traumatic experiences. Discrimination is a significant source of stress for Afghan refugees, which may exacerbate stresses associated with other post-migration stressors. Future research is needed to tailor interventions that can help mitigate the stress associated with discrimination among this highly vulnerable group.

POH (Peri Orbital Hyperpigmentation) represents a minor clinical entity that attracts immense aesthetic damages and it generates social integration difficulties. This review focuses on the etiopathogenic causes of this entity, differentiating and reclassifying this defect as having, on the one hand, genetic causes of melanic hyperproduction – for Fitzpatrick cutaneous phototypes IV and V – and, on the other hand, both genetic and acquired vascular causes, in individuals with light-coloured skin phototypes. Hence, there is a big difference in the field of pathogenic treatment, for the two entities. In addition, this study notes the direct relationship between skin aging and POH, especially for aquired vascular causes. In this reasoning, other aesthetic deficiencies of the skin in the palpebral area should be also considered, like: blepharochalasis, wrinkles, the anatomical causes of the lower eyelid shading, symmetrical or asymmetric suborbital oedema. All of these issues will complicate the therapeutic decision and subsidiary, the pharmaceutical advice. In this context, the review shows the guidelines for a honest councelling of the patients, pointing the efficiency limit for the topical pharmaceutical medication (depigmentants, exfoliants) versus the necessity of minimally invasive or/ and surgical treatments (in blefarochalasis).

Abstract: Objective: The aim of the study was to identify dietary patterns and its association with socio-economic, dietary and lifestyle practices among adolescents in Malaysia. Methods: A validated food frequency questionnaire was used to assess dietary patterns. Results: Multivariate analyses show that age and physical activity (PA) levels were emerged as positive determinants of healthy-based food pattern in Malay (All, p<0.001), whereas higher consumption of eating-out from home (EatOut) and fast food (All, p<0.05) were negative determinants. High weekly breakfast skipping (p<0.001) and EatOut (p<0.01) were positively associated with a western-based pattern, whereas age (p<0.001) and household income (p<0.05) were negative determinants. Higher frequency of daily snacking (p<0.05) was emerged as positive determinant of local-based food pattern. For Chinese adolescents, age (p<0.001), PA levels (p<0.001) and maternal education level (p<0.05) emerged as positive determinants for the healthy-based pattern, whereas high EatOut and fast food intakes (All, p<0.01) were negative determinants. Higher weekly consumption of EatOut (p<0.01), fast food (p<0.05) and carbonated beverages (p<0.05), and daily snacking practice (p<0.01) were positively associated with higher western-based food pattern, whereas age (p<0.01) was inversely associated. Conclusion: These findings suggest that unhealthy dietary and lifestyle practices could increase the risk of adherence to unhealthy western-based food pattern that is high in fat, sugar and salt contents, and consequently increase the risk of developing obesity and metabolic-related disorders during these critical years of growth.

ABSTRACTIntroduction:Human Immunodeficiency Virus (HIV) is a global health problem that is almost recorded in every country. The long-term and long-term negative impacts of HIV cases are stigma and discrimination in people with HIV (PLHIV). The purpose of this study is to find out the stigma and discrimination felt by PLHIV.Method:This study design of systematic review from 4 electronic databases namely Scopus ScienceDirect, Sage and ProQuest by using keywords tailored to Medical Subject Headings (MeSH) including "Stress", "covid", "nursing", "hospital". This study uses PICOS framework to prevent research bias and analysed using descriptive analysis.Results:The results of the analysis of the article showed from 761 articles have been identified title, abstract and full-text so that recorded 15 articles that can be reviewed. The article consists of various designs, namely RCT, cross sectional and qualitative studies. Analysis shows that stigma and discrimination are social phenomena that manifest in several social areas.Conclusion:Stigma and discrimination in people with HIV (PLHIV) is still common, stigma is carried out by the wider community to their own families. The family approach is necessary to improve well-being as well as improve the social community of the family.

In this study, we investigate how dataset composition influences the performance and bias of age estimation models across different ethnic groups. We utilized pre-trained Convolutional Neural Networks (CNNs) such as VGG19, fine-tuning them on two datasets: UTKFace and APPA-REAL. UTKFace comprises 23,705 samples (12,391 males, 11,314 females) including 10,078 White, 4,526 Black, and 3,434 Asian individuals. APPA-REAL consists of 7,591 samples (3,818 males, 3,773 females) with 6,686 White, 231 Black, and 674 Asian individuals. We adjusted dataset composition by oversampling minority groups and reducing samples from the majority group to evaluate effects on model performance, measured using Mean Absolute Error (MAE) and standard deviation. Our findings demonstrate that oversampling alone does not guarantee equitable performance across ethnicities; reducing samples from the majority group often resulted in more balanced performance, evidenced by lower MAE standard deviations. These results underscore the importance of a nuanced approach to achieve fairness, including combining various sampling techniques. This study emphasizes the critical need for tailored dataset compositions to mitigate bias and suggests exploring more refined data processing methods and algorithmic adjustments for enhanced model fairness and accuracy in facial recognition technologies.

Cymbidium goeringii, locally known as the spring orchid in Korea, is one of the most important and popular horticultural species in the family Orchidaceae. C. goeringii cultivars were originated from plants with rare phenotypes in wild mountains where pine trees commonly grow. This study aimed to determine the cultivar-specific combined genotypes (CGs) of short sequence repeats (SSRs) by analyzing multiple samples per cultivar of C. goeringii. In this study, we collected more than 4,000 samples from 67 cultivars and determined the genotypes of 12 SSRs. Based on the most frequent combined genotypes (CG1s), the average observed allele number and combined matching probability were 11.8 per marker and 3.118×10-11, respectively. Frequencies of the CG1 in 50 cultivars (n ≥ 10) ranged from 40.9% to 100.0%, with an average of 70.1%. Assuming that individuals with the CG1 are genuine in the corresponding cultivars, approximately 30% of C. goeringii on the farms and markets may be not genuine. The dendrogram of the phylogenetic tree and principal coordinate analysis largely divided the cultivars into three groups according to their countries of origin; however, the genetic distances were not distant among the cultivars. In conclusion, this dataset of C. goeringii cultivar-specific SSR profiles could be used for ecogenetic studies and forensic authentication. This study suggests that genetic authentication should be introduced for the sale of expensive C. goeringii cultivars. We believe that this study will help establish a genetic method for the forensic authentication of C. goeringii cultivars.

The current echocardiography reference values are derived primarily from populations in North America and Europe. It becomes necessary to study ethnically different groups of the population, which often have different living conditions, food habits and lifestyle. The aim of the study was to compare echocardiography indicators in urbanized patients with arterial hypertension of the Shor and non-indigenous ethnic groups living in the Gornaya Shoria region. The study included patients with arterial hypertension: 58 Shors (20 men and 38 women) and 50 non-indigenous residents (15 men and 35 women) of Gornaya Shoria. All underwent an echocardiographic study with an assessment of the left heart parameters. We assessed the left ventricular hypertrophy (LVH) severity, LV geometry and diastolic function in the ethnic and sex groups. Shor with hypertension no showed a significant difference in left ventricular dimensions compared to Caucasian. Severe abnormal LVH was associated in the Shors with glucose levels (OR 3.24, 95%CI 1.56-6.7, p=0,001), and in Caucasians with systolic (p=0.021) and diastolic (p=0.011) blood pressure, and heart rate (p=0.033). The Shor men were more likely to have normal LV diastolic function (p=0.029) and LV concentric remodeling (p=0.023), and less often to have normal LV geometry (p=0.015) compared to non-indigenous men. Thus, this study can be useful in assessing the impact of the development of arterial hypertension, as well as the impact of changing the lifestyle of the Shors when moving to the city from rural areas on ethnic differences in echocardiography.

Brain-computer interfaces (BCI) from electroencephalography (EEG) provide a practical approach to support human-technology interaction. In particular, motor imagery (MI) is a widely-used BCI paradigm that guides the mental trial of motor tasks without physical movement. Here, we present a deep learning methodology, named Kernel-based Regularized EEGNet (KREEGNet), leveled on Centered Kernel Alignment and Gaussian Functional Connectivity, explicitly designed for EEG-based MI classification. The approach proactively tackles the challenge of intra-subject variability brought on by noisy EEG records and the lack of spatial interpretability within end-to-end frameworks applied for MI classification. KREEGNet is a refinement of the widely accepted EEGNet architecture, featuring an additional kernel-based layer for regularized Gaussian functional connectivity estimation based on CKA. The superiority of KREEGNet is evidenced by our experimental results from binary and multi-class MI classification databases, outperforming the baseline EEGNet and other state-of-the-art methods. Further exploration of our model’s interpretability is conducted at individual and group levels, utilizing classification performance measures and pruned functional connectivities. Our approach is a suitable alternative for interpretable end-to-end EEG-BCI based on deep learning.

While visual assessment is the standard technique for burn evaluation, computer-aided diagnosis is increasingly sought due to high number of incidences globally. Patients are increasingly facing challenges which are not limited to shortage of experienced clinicians, lack of accessibility to healthcare facilities, and high diagnostic cost. Certain number of studies were proposed in discriminating burn and healthy skin using machine learning leaving a huge and important gap unaddressed; whether burns and related skin injuries can be effectively discriminated using machine learning techniques. Therefore, we specifically use pre-trained deep learning models due to deficient dataset to train a new model from scratch. Experiments were extensively conducted using three state-of-the-art pre-trained deep learning models that includes ResNet50, ResNet101 and ResNet152 for image patterns extraction via two transfer learning strategies: fine-tuning approach where dense and classification layers were modified and trained with features extracted by base layers, and in the second approach support vector machine (SVM) was used to replace top-layers of the pre-trained models, trained using off-the-shelf features from the base layers. Our proposed approach records near perfect classification accuracy of approximately 99.9%.

A nanostructured electrochemical bi-sensor system for analysis of milks has been developed using the Layer by Layer technique. The non-enzymatic sensor [CHI+IL/CuPcS]2, is a layered material containing a negative film of the anionic sulfonated copper phthalocyanine (CuPcS) acting as electrocatalytic material, and a cationic layer containing a mixture of an ionic liquid (IL) (1-butyl-3-methylimidazolium tetrafluoroborate) that enhances the conductivity and chitosan (CHI) that facilitates the enzyme immobilization. The biosensor ([CHI+IL/CuPcS]2-GAO) results from the immobilization of galactose oxidase on the top of the LbL layers. FTIR, UV-vis and AFM have confirmed the proposed structure and cyclic voltammetry has demonstrated the amplification caused by the combination of materials in the film. Sensors have been combined to form an electronic tongue for milk analysis. Principal Component Analysis has revealed the ability of the sensor system to discriminate between milk samples with different lactose content. Using PLS-1 calibration models, correlations have been found between the voltammetric signals and chemical parameters measured by classical methods. PLS-1 models provide excellent correlations with lactose content. Additional information about other components such as fats, proteins and acidity can also be obtained. The method developed is simple and the short response time permits its use in assaying milk samples on-line.

Objectives: Isolated mild neutropenia is a common clinical problem. The current study aims to validate our previous findings regarding the high prevalence of isolated neutropenia in Southern and Southwestern Saudi Arabia and explore the effect of altitude or regional differences. Methods: In this retrospective cross-sectional study, laboratory results of a commercial laboratory were screened over a period of 5 years (2016–2020) in seven different cities in South and southwestern Saudi Arabia. Participants’ laboratory investigations were reviewed and excluded for any ab-normal complete blood count, renal profile, liver profile, lipid profile, thyroid function test, fasting blood glucose, or HbA1c findings. Descriptive analysis and 95th percentile range were calculated using standard statistical methods. Results: A total of 91,880 complete blood count results were included in the final analysis. isolated neutropenia is common laboratory finding, with a prevalence ranging from 11-23%. The 2.5th percentile of the neutrophil count was lower than 1.5×109/L in all seven cities. Conclusions: Mild to moderate neutropenia is common in Southern and Southwestern Saudi Arabia. Benign ethnic neutropenia (BEN) may explain this high prevalence. Since BEN has no clinical significance, the reference range for normal neutrophil counts needs to be adjusted to reflect the effect of BEN.

In Thailand, thousands of children living with perinatal HIV have been exposed to HIV-related stigma/discrimination but its frequency and expressions have been little studied. Our objective was to assess stigma/discrimination prevalence, associated risks factors and its expressions among adolescents. All caregivers of adolescents aged 12-19 years living with perinatal HIV and receiving antiretrovirals in 20 hospitals throughout Thailand were invited to complete a face-to-face questionnaire on their adolescent’s life and medical history. Of the 572 adolescents living in family settings, 464 had their HIV-status known in the community. The overall stigma/discrimination prevalence was 46%. Factors associated included living in the north-east region (OR: 2.80, 95%CI: 1.19-4.96), having a low intellectual ability (OR:2.68, 95%CI: 1.45-5.16), a lower Body Mass Index (BMI) (OR BMI &gt; 18.5: 0.61, 95%CI: 0.37-0.98), conflicts with caregivers (OR: 1.86, 95%CI: 1.26-2.76) and caregivers being members of a support group (OR: 2.34, 95%CI: 1.58-3.48). Expressions of stigma/discrimination included bullying, social isolation, behavioral discrimination and public disclosure. The prevalence of stigma/discrimination among adolescents living with perinatal HIV is high. Despite existing policies, stigma eradication remains necessary to normalize their life as they grow into adulthood.

Prior work has suggested that discrimination and immigration-related stress may impede mental health care seeking and utilization among Latinx populations. These effects may be more nuanced as both discrimination and immigration-related stress may increase symptomology, particularly posttraumatic stress disorder (PTSD) and depression. Both symptoms may in turn prompt attempts to seek care. The current study examined the direct effects of discrimination and immigration-related stress on care access, as well as potentially indirect effects with PTSD and depression symptoms as mediators. Interviews and online surveys were completed with 234 Latinx residents of the Midwest assessing everyday discrimination, discrimination in healthcare, PTSD symptoms, depression symptoms, current mental health utilization, and previous unsuccessful attempts to seek care. Direct effects of discrimination and immigration-related stress were largely unrelated to care access variables. Discrimination in healthcare settings predicted both unsuccessful attempts to seek care and current use, but this effect was positive. The indirect effect was largely supported, but only for PTSD symptoms and not depression. Results indicate further investigation is necessary to understand the direct effects of discrimination on care access. Further, discrimination and immigration-related stress may indirectly prompt attempts to seek mental health care.

The identification of an action principle for directing basic system energy exchanges can be used in a general framework for the study of dynamics in systems. The application of such action principles using Lagrangian procedures has become a very powerful methodology for the analysis of complicated problems in modern physics. This form of analytics has recently been considered as the mapping of the system state information in the context of system constraints. The process of translating perceived information into adaptive responses is considered to be the driving action dynamic for the living system. Reconciliation processes that provide for a minimization of the divergence of this information signature from a state of system stability are preferred. Such a state is naturally that of maximal entropy in the context of the operational constraints of the open living system. A mathematical expression incorporating inferential information entropy processing into biologic replicator dynamics describes the mechanics of the perception-action adaptive processes of living systems. From this framework, Kullback’s Principle of Minimum Information Discrimination is identified as the innate axiomatic action principle for guiding the dynamics of biological systems.

Multiple Sclerosis (MS) is a progressive neurodegenerative disease that affects more than 2 million people worldwide. Increasing knowledge about MS in different populations has advanced our understanding of disease epidemiology and variation in the natural history of MS among White and minority populations. In addition to differences in incidence, African American (AA) and Hispanic patients have greater disease burden and disability in earlier stages of disease compared to White patients. To further characterize MS in AA and Hispanic populations, we conducted a retrospective chart analysis of 112 patients treated at an MS center in Houston, Texas. Here, we describe differences in clinical presentation, MRI findings, treatment regimens, disability progression, and relapse rate. We found that patients who were evaluated by a neurologist at symptom onset had significantly decreased odds of greater disability [defined as Expanded Disability Status Scale (EDSS) &gt; 4.5] at last presentation compared to patients who were not evaluated by a neurologist (OR: 0.04, 95% CI: 0.16-0.9). We also found that active smokers had significantly increased odds of greater disability both at diagnosis and at last clinical encounter compared to nonsmokers (OR: 2.44, 95% CI: 1.10-7.10, OR= 2.44, 95% CI: 1.35-6.12, p= 0.01, respectively). Assessment of the degree of brain atrophy and progression over time along with enumeration of T1, T2, and gadolinium-enhancing brain lesions did not reveal differences across groups.

The combined ecological, geophysical, climatic, and social factors of the Northeast of Russia influence the organism from the early childhood being too intense for the functional systems. The purpose of the research is to study the emotional characteristics of adolescents of different ethnic groups in the northeast of Russia. Presented in the paper are results of the study that covered 826 adolescents (445 females and 381 males) at the age of 15–17, different by ethnic origin. We used standard methods of psycho-diagnostics. Our study has showed that the formation of the adolescents’ emotional sphere in the North is undoubtedly influenced not only by the climatic and socio-economic environmental factors but also by ethnic features. There are intergroup differences in the aggressiveness profile of older adolescents living in the remote settlement vs. the regional center. It is shown that high school students in the remote settlement of Evensk, compared to their peers in Magadan, regardless of gender and ethnicity, are characterized by more pronounced hostile and auto-aggressive reactions. In adolescents of the Aboriginal population, as compared with their age mate Caucasians, the indicators of impairment in the field of Neuro Psychic Adaptation, Situational and Personal Anxiety, and Social Frustration are significantly more pronounced.

This paper considers two types of Protestant ethnic groups of some areas of Urals and Western Siberia. The first type consist of representatives of members of different ethnic groups consisting of well-educated professionals, incorporated into industrial society and associated with the intellectualism of Protestantism. The second type is represented by the indigenous peoples of the Polar Urals and Western Siberia, who use the Protestant religious organizations as tool for restoring life-sustaining elements of the native peoples’ traditional economy. I employed the inductive approach and the comparison method; during the fieldwork I used ethnographic participant observations, sociological structured interviews and closed-ended questionnaires. The empirical data have been collected in the Southern, Middle and Polar Urals and Western Siberia.

The agricultural sector is currently confronting multifaceted challenges such as an increased food demand, a slow adoption of sustainable farming, a need for climate-resilient food systems, resource inequity, and protection of the small-scale farmers’ practices, all issues integral to food security and environmental health. Remote sensing technologies can assist precision agriculture to effectively address these complex problems, by providing farmers with a high-resolution lens. The use of vegetation indices (VIs) is an essential component of remote sensing, which combine the variability of spectral reflectance value (derived from remote sensing data) with the growth stage of crops. Currently a wide array of VIs is available that could be used to provide a classification and an evaluation of the state and health of crops. However precisely this high number leads to difficulties in selecting the best VI and combination of VIs for a specific objective. Without a thorough documentation and analysis of appropriate VIs, users might be confronted with difficulties in using remote sensing data or even with a very low accuracy of the results. Thus, the objective of this review is to conduct a critical analysis of the existing state of the art on the most important features related to the effective use of VIs for the discrimination and monitoring of the most important agricultural crops (wheat, corn, sunflower, soybean, rape, potatoes, and forage crops), grasslands and meadows. This data could be highly useful for all the stakeholders involved in agricultural activities (from farmers, researchers up to institutions dealing with the centralization and monitoring of agricultural crops).

(1) Background: Substantial evidence that neural timing deficits are prevalent in developmental disorders, aging, and concussions resulting from a mild Traumatic Brain Injury (mTBI) is presented. We show that if timing deficits are remediated using low-level movement discrimination training, then high-level cognitive skills, including reading, attention, processing speed, and working memory improve substantially. (2) Methods: Two case studies are presented using MEG source imaging on an adult dyslexic, and a healthy older adult observed before and after training on movement discrimination two times/week for 8 weeks for adult dyslexic. (3) Results: We found improvements in reading, attention, processing speed, and working memory on neuropsychological tests. Substantial MEG signal increases in visual Motion Networks (V1, V3, MT, MST), Attention Networks (ACC, dlPFC, vlPFC and precuneous/ PCC areas) and Memory Networks (dlPFC). (4) Conclusions: Improving neural timing deficits before cognitive exercises to improve specific cognitive skills provides a rapid and effective method to improve cognitive skills. Improving the timing and sensitivity of low-level dorsal pathways, improving feedforward and feedback pathways, is essential to improve high-level cognitive skills. This adaptive training with substantial feedback shows cognitive transfer to tasks not trained on, significantly improving a person’s quality of life rapidly and effectively.

How perceptual limits can be overcome has long been examined by psychologists. This study investigated whether visual cues, blindfolding, visual-auditory synesthetic experience and music training could facilitate a smaller frequency difference limen (FDL) in a gliding frequency discrimination test. It was hoped that the auditory limits could be overcome through visual facilitation, visual deprivation, involuntary cross-modal sensory experience or music practice. Ninety university students, with no visual or auditory impairment, were recruited for this one-between (blindfold/visual cue) and one-within (control/experimental session) designed study. A MATLAB program was prepared to test their FDL by an alternative forced-choice task (gliding upwards/gliding downwards/no change) and two questionnaires (Vividness of Mental Imagery Questionnaire & Projector-Associator Test) were used to assess their tendency to synesthesia. Participants with music training showed a significantly smaller FDL; on the other hand, being blindfolded, being provided with visual cues or having synesthetic experience before could not significantly reduce the FDL. However, the result showed a trend of reduced FDLs through blindfolding. This indicated that visual deprivation might slightly expand the limits in auditory perception. Overall, current study suggests that the inter-sensory perception can be enhanced through training but not though reallocating cognitive resources to certain modalities. Future studies are recommended to verify the effects of music practice on other perceptual limits.

The measurement of discrimination in employment is a key variable in understanding dynamics in the nature of and change in ‘race relations’. Measuring such discrimination using ‘situation’ and ‘correspondence’ tests was influenced by John Rex’s sociological analyses, begun in in England in the 1960s, and replicated in Europe and America in later decades. This literature is reviewed, and the methodologies of testing for employment discrimination are discussed. Recent work in Britain and The Netherlands is considered in detail in the light of changing social structures, and the rise of Islamophobia. Manchester, apparently the city manifesting the most discrimination in Britain, is considered for a special case study, with a focus on one individual, a Muslim woman seeking intermediate level accountancy employment. Her vita was matched with that of a manifestly indigenous, white Briton. Submitted vitas (to 1,043 potential employers) indicated significant discrimination against the Muslim woman candidate. Results are discussed within the context of Manchester’s micro-sociology, and Muslim women’s employment progress in broader contexts, drawing on our work in Jordan and Palestine. We conclude with the critical realist comment that the “hidden racism” of employment discrimination shows that capitalist societies continue to be institutionally racist, and the failure to reward legitimate aspirations of minorities pushes ethnic minorities into a permanent precariat, with implications for social justice and social control, which denies minority efforts to “integrate” in society’s employment systems.

Authors present The First Results of the National Extended Newborn Screening (ENS) in Slovakia in the majority (M) and the Roma (R ) ethnic populations. The follow-up of the ethnicity has been introduced in Newborn Screening for Cystic Fibrosis (NSCF) and after to entire ENS program comprising of 23 Hereditary Metabolic Disorders (HMD). Results: In 2013-2015, a total of 165,648 newborns were investigated in ENS, 23,321 of them (15,3%) were the R ethnic group, a total of 313 positive cases were discovered (total ENS prevalence = 1:529, M=1:758, R=1:198). In the R ethnic group, there was slightly higher prevalence in cong. hypothyreosis (CH), only one case of CF, and no cases of CAH in the R ethnic group. The ENS prevalence of HMD detected by MS/MS was expressively higher in the R ethnic group than in M group (M=1:1670 vs. R=1:234, OR:7,13). Significant differences in the prevalence of individual types of HMD were found. Whereas the PKU and spectrum of aminoaciduria and organic acidurias dominate in the M group, the fatty acids oxidation disorders (MCAD, SCAD) and carnitine defects (CUD) were frequent in the R newborn group. Conclusion: Despite the presented results are preliminary, the ethnic approach to ENS is enabling the recording of the ethnic differences in the screening prevalence of individual disorders, which would be missing during unitary approach.

Acne vulgaris is a chronic skin disease, which occurs due to inflammation of the hair follicles and sebum producing (sebaceous) glands of the skin called pilosebaceous unit and the anaerobic propionic acne bacterium, P.acne. Human sebum is dominantly made up of 57.5% of triglycerides and fatty acids, 26%wax esters, 12% Squalene and 4.5% Cholesterol. The increased level Androgen hormone, sebum lipid composition, P.acne over growth which induces monocytes and pro inflammatory cytokines attracts neutrophils, basophils, and T cells to the pilosebaceous unit and drive epithelial hyper proliferation i.e., Acne vulgaris. The actual biomolecular changes due to acne vulgaris disease are present in the blood, in the sebum, and in the noninvasive sample of human scalp hair follicles. The main objectives of the present study are to analyze human scalp hair follicles samples using FTIR-ATR spectroscopy to compare and discriminate the spectral signatures of acne vulgaris and healthy scalp hair tissue samples through acne biomarkers Protein, Amide I, Amide II and Squalene (LDL), using the method of internal ratio parameters. This work represents a first step in the development of an analytical tool for future drug development.

Abstract: Petrol is considered the most common fire accelerant. However, the identification and classification of petrol sources through the years has been proven to be a challenging field in the investigation of fire debris analysis. This research explored the possibility of identifying petrol sources by high field NMR methods accompanied by ML (Machine Learning). The automated identification and classification of petrol brands were achieved for first time based on the ML clas-sification model developed in this research. A hierarchical classification model was constructed using local classifiers to categorize neat or weathered petrol into its sources.

In this work, we studied light-output properties, efficiency function as well as PSD capability of p-Terphenyl scintillator. The selected solid cylindrical scintillation detector has a size of (45 x 45) mm with PSD properties. Recently presented studies of light-output functions have been meas-ured only for low neutron energies. Our motivation has been to determine more accurate the light output function for p-Terphenyl scintillator over a wider neutron energy range. The measurements have been carried out with mono-energetic neutron beams in the wide energy range from 2.5 to 19 MeV. The neutron-gamma spectrometric system, which we developed has been used for the measurement. The input analogue signal from the detector is digitized with fast 12-bits analogue to digital converter with sampling frequency of 1 GHz. Measured data from the detector are processed into gamma and neutron spectra. The light output function for protons has been determined by finding the position of the protons for given neutron energies. The more accurate light output function for p-Therphenyl scintillator has been calculated. The pulse-shape discrimination capability as well as efficiency of p-Terphenyl scintillator in comparison with NE-213 equivalent detector is lower.

During Sep. 2011, forty-four Leymus chinensis culms with stroma development were collected from Inner Mongolia. Stromata surrounded the flag leaf sheathes, white, at the final stage of development. Perithecium but not asci were observed under microscope. Nine epichloid endophyte strains were obtained from Tongliao subdivision, and sixteen from Horqin. Morphological and phylogenetic properties of these strains were investigated. Morphological properties of these strains were similar among these 27 strains. Colonies could grow to 28.5~41.1 mm/21d at 25℃; phialides 24.1~26.4 μm long, 2.1~2.5 μm at base, tapering to less than 1.0 μm at tip; conidia reniform to elliptical, 4.7~5.5×2.8~3.5 μm, indicating typical properties of Epichloë endophytes. Based on the sequences of tefA and tubB gene fragments, strains isolated from Inner Mongolia formed a distinct subclade in E. bromolica/ E. yangzii clade, with a bootstrap value of 66% and 64% respectively. Considering morphological and phylogenetic properties, we tend to determine strains isolated from Leymus chinensis as a new taxon. The detailed taxonomic position of this taxon needs further investigations on hybridization or genomic sequence.

The weighted K-nearest neighbors (WKNN) algorithm has been widely used in indoor fingerprint localization, which utilizes fingerprint distance (FD) of pairwise positions to discriminate the physical distance (PD) between them. However, due to the varied states of different wireless access points (APs), their contribution to FD discrimination capability varies. In our study, we analyzed several critical causes that affect APs’ contribution, including AP’s health state, the distance, and the direction between APs and position pairs. Inspired by these insights, a threshold was set for all sample RSS to eliminate the impact of abnormal APs on FD, and a correction quantity for each RSS was provided by the distance between APs and sample positions to reduce the strong signal influence on FD. Furthermore, a priority weight was designed by RSS differences (RSSD) to further optimize FD’s capability to discriminate PD. Integrating the above policies, a new indoor fingerprint localization technique is redefined, referred to FD’s discrimination capability improvement WKNN (FDDC-WKNN), which is suitable for indoor scenes with a large number of APs that are not uniformly managed. Our simulation results show that the correlation and consistency between FD and PD are well improved, with strong correlation increasing from 0 to 76% and high consistency increasing from 26% to 99%, which confirms that the proposed policies can greatly enhance FD’s discrimination capabilities to PD, and we also found that abnormal APs can cause significant impact on FDs’ discrimination Capability. Further, by implementing the FDDC-WKNN algorithm in experiments, we obtained the optimal K value in both the simulation scene and real library scene, under which the average localization errors have been reduced from 2.2732m to 1.2183m and from 3.4295m to 2.2068m, respectively. In addition, compared to not using the FDDC-WKNN, the cumulative distribution function (CDF) of the localization errors curve converged faster and the errors fluctuation is smaller, which demonstrate FDDC-WKNN having stronger robustness and more stable localization performance to the state of APs in indoor environments.

Views of aging include peoples’ assessment of their own aging process and their subjective age. Positive aging views relate to good psychological well-being which predicts better physical and mental health. While these were substantially studied, the moderating roles of self-aging attitudes and psychological well-being in the subjective age-age discrimination connection have been much less explored. The current study used a convenience sample of 568 participants (mean = 66.21y, SD = 11.95, age range 50-95), 55.8% women, 67.1% employed. In line with the hypotheses, young subjective age and psychological well-being were connected to less age discrimination in the workplace and higher psychological well-being mitigated the subjective age-age discrimination at work connection. When the perception of old age as a period of loss was added to the model, adults who perceived old age as a period of loss and reported lower levels of psychological well-being, demonstrated the strongest relationship between an increase in subjective age and an increase in age-related discrimination at work. The findings emphasize the importance of the psychological well-being of older employees as a resource for improving their attitudes to their last years at work.

In this work we demonstrate the proof-of-concept of real-time discrimination between patches of serine or isoleucine monomers in the primary structure of custom-engineered, macro-dipole-like peptides, at uni-molecular level. We employed single-molecule recordings to examine the ionic current through the α-hemolysin (α-HL) nanopore, when hydrophilic serine or hydrophobic isoleucine residues, flanked by segments of oppositely charged arginine and glutamic amino acids functioning as a voltage-dependent ‘molecular brake’ on the peptide, were driven at controllable rates across the nanopore. The observed differences in the ionic currents blockades through the nanopore, visible at time resolutions corresponding to peptide threading through the α-HL’s constriction region, was explained by a simple model of the volumes of electrolyte excluded by either amino acid species, as groups of three serine or isoleucine monomers transiently occupy the α-HL. To provide insights into the conditions ensuring optimal throughput of peptide readout through the nanopore, we probed the sidedness-dependence of peptide association to and dissociation from the electrically and geometrically asymmetric α-HL.

Durum wheat is an important staple food used to obtain several products. At first the wheat is milled to obtain different products: bran, semolina and flour. These products are the base of several artifacts with varying properties both from a nutritional point of view and flavoring characteristics. It is known that most elements concentrate in the outer layers of the wheat seed (pericarp and aleurone) so that the content of the elements vary a lot in the ground products. The present study investigates the characterizing elements of the milled products and the effect of cultivation protocol applied. We measured, by ICP-OES, the concentration of 28 elements in the whole seed and in any grinding products; the results show that only few elements characterize each product. Few elements, but different for each product, permit to disclose the kind of agri-cultural method used: organic or conventional protocol. Five elements: B, Cd, Cu, K, Se, are the most important to distinguish between organic and conventional agriculture by PCA and PLS analysis; these elements also permit some differentiation of products.

Glioblastoma (GBM) is one of the most aggressive solid tumors, particularly due to the presence of cancer stem cells (CSCs). Today the characterization of this type of cells with an efficient, fast and low-cost method remains an issue. Hence, we have developed a microfluidic lab-on-a-chip based on dielectrophoresis (DEP) single cell electro-manipulation to measure the two crossover frequencies: f_x01 in low frequency range (below 500 kHz) and f_x02 in Ultra High Frequency range (UHF, above 50 MHz). First, in vitro conditions were investigated. U87-MG cell lines were cultured in different conditions in order to induce an undifferentiated phenotype. Then, ex vivo GBM cells from patients’ primary cell culture, were passed through the developed microfluidic system and characterized in order to reflect clinical conditions. This article demonstrates that the usual exploitation of low frequency range DEP does not allow the discrimination of the undifferentiated from the differentiated phenotypes of GBM cells. However, the presented study highlights the use of UHF-DEP as a relevant discriminant parameter. The proposed microfluidic lab-on-a-chip is able to follow the kinetic of U87-MG phenotype transformation in a CSC enrichment medium and their cancer stem cells phenotype acquirement.

Machine learning (ML) has a large capacity to learn and analyze a large volume of data. This study aimed to train different algorithms to discriminate between healthy and pathologic corneal images by evaluating digitally processed spectral-domain optical coherence tomography (SD-OCT) corneal images. A set of 22 SD-OCT images belonging to a random set of corneal pathologies was compared to 71 healthy corneas (control group). A binary classification method was applied; three approaches of ML were used. Once all images were analyzed, representative areas from every digital image were also processed and analyzed for a statistical feature comparison between healthy and pathologic corneas. The best performance was obtained from transfer learning - support vector machine (TL-SVM) (AUROC = 0.94, SPE 88%, SEN 100%) and transfer learning – random forest (TL- RF) method (AUROC = 0.92, SPE 84%, SEN 100%), followed by convolutional neural network (CNN) (AUROC = 0.84, SPE 77%, SEN 91%) and random forest (AUROC = 0.77, SPE 60%, SEN 95%). The highest diagnostic accuracy in classifying corneal images was achieved with the TL-SVM and the TL-RF models. In image classification, CNN was a strong predictor. This pilot experimental study developed a systematic mechanized system to discern pathologic from healthy corneas.

MALDI-TOF (Matrix-Assisted Laser Desorption/Ionization Time-of Flight) is a type of mass spectrometry (MS) that has been widely implemented for the rapid identification of microorganisms over the last decade. The accuracy and flexibility of this method has encouraged researchers to implement the analysis of protein spectra obtained by MALDI-TOF for the discrimination of close-related species and bacterial typing. In this study, a standardized methodology based on the detection of species-specific protein peaks from the spectra obtained with MALDI-TOF is described. The methodology was applied to a collection of Cryptococcus spp. (n=70) previously characterized by Amplified Fragment Length Polymorphism (AFLP) and sequencing of the ITS1-5.8S-ITS2 region. An expanded ad-hoc database was also built for their discrimination with MALDI-TOF. This approach did not allow the discrimination of the interspecies hybrids. However, the performance of peak analysis with the application of the PLS-DA and SVM algorithms in a two-step analysis allowed 96.95% and 96.55% correct discrimination of C. neoformans from the interspecies hybrids, respectively. Besides, PCA analysis prior to SVM provided 98.45% correct discrimination of the 3 analyzed species in a one-step analysis. The method is cost-efficient, rapid and user-friendly. The procedure can also be automatized for an optimized implementation in the laboratory routine.

To investigate the intricate dynamics of brain activity when interacting with a dynamic environment, it is imperative to continuously generate and update expectations regarding forthcoming events and their corresponding sensory and motor responses. This study aims to explore the interconnectivity in time perception across predictable and unpredictable conditions. The necessary data for this study were acquired from EEG signals, sourced from an existing database that involved an experiment conducted on a group of healthy participants. The individuals were subjected to two distinct conditions, predictable and unpredictable, encompassing various time delays. The functional connectivity between brain regions was estimated using a method known as the phase lag index. This method was employed to discern disparities in time perception between the two conditions. A comprehensive comparison of the two conditions across different delays demonstrated noteworthy variations, particularly in the gamma, beta, and theta frequency bands. The differences between delays were more pronounced in the predictable condition. Subsequently, an in-depth analysis was conducted to scrutinize the dissimilarities between the conditions within each delay. Notably, significant differences were observed across all delays. In the unpredictable condition, an increase in connectivity was detected within the alpha band during the 400-ms delay, specifically between occipital and temporal regions. Moreover, the mean connectivity in the unpredictable condition surpassed that of the predictable condition. In the delta band, distinct connectivity patterns were observed across different delays, involving connections between central and frontal regions. Specifically, a heightened connectivity between central and prefrontal regions was noted during the 83-ms delay. Notably, the right hemisphere of the prefrontal cortex played a vital role in time perception. Furthermore, a decline in connectivity across the delta, theta, and beta bands was observed in both conditions during the longest delay (800 ms) when compared to other delays

Negative work behavior (NWB) threatens employee well-being. There are numerous constructs that reflect NWBs, such as bullying, aggression, and discrimination and they are often examined in isolation of each other, limiting scientific integration of these studies. We aim to contribute to this research field by developing a diagnostic tool with content validity on the full spectrum of NWBs. First, we provide a full description of how we tapped and organized content from 44 existing NWB measurement instruments and 48 studies. Second, we discussed our results with experts (N = 3) in this research field to check for missing studies and to discuss our integration results. This two-stage process yielded a questionnaire measuring physical, material, psychological, sociocultural, and digital NWB. Furthermore, the questions include a range of potential actors of NWB, namely internal (employees, managers) and external actors (clients, customers, public, family members) at work and their roles (i.e., target, perpetrator, perpetrator's assistant, target's defender, outsider, and witness of NWBs). Finally, the questionnaire measures what type of harm is experienced (i.e., bodily, material, mental, and social harm).

The emerging advancements in separation and classification of various biological matters (e.g., living cells and proteins) using magnetic levitation (MagLev) technology have proven to be effective for improving disease diagnostics. MagLev technique has the capacity to detect and separate useful diagnostic biomarkers from biocomplex environments (e.g., blood and plasma), minimizing the unpleasant daunting task of sample preparations and labeling procedures. Here, we demonstrate the capability of this technique combined with image analysis and machine learning approaches for discriminating the various types of multiple sclerosis (MS) as an important model disease. To arrive at a systematic expert system, we combined robust statistical analysis with machine learning to (1) detect and remove outliers from the raw MagLev image datasets; then (2) process the images and output a low dimensional representation of massive data without losing the main statistical features; and finally (3) predict the MS clinical disease type (Relapsing-Remitting, Primary–Progressive, or Secondary–Progressive) using a classifier. This is expected to improve MS diagnostics since the current practices rely solely on clinical observation and central nervous system imaging, making management approaches are often reactional and inefficient. Thus, there is a need to identify the disease type early on. MagLev is expected to improve MS diagnostics, thereby aiding in prognosis and guiding adequate treatment choices before the patient exhibits signs of permanent neurological deficits.

Nowadays, the combination of fingerprinting methodology with friendly environmental and economical analytical instrumentation are becoming increasingly relevant in the food sector. In this study, a highly versatile portable analyser based on Spatially Offset Raman Spectroscopy (SORS) to obtain the edible vegetable oils (sunflower and olive oils) fingerprints was used to evaluate the capability of such fingerprints, obtained quickly, reliable and without any sample treatment, to discriminate/classify the analysed samples. After data treatment, not only HCA and PCA as unsupervised pattern recognition techniques but also SVM, kNN and SIMCA as supervised pattern recognition techniques, showed that the main effect over the discrimination/classification was associated to those regions of RAMAN fingerprint related to the free fatty acids content, especially oleic and linoleic acid. These facts allowed the discrimination attending to the original raw material used in the oil's elaboration. In all the model established, reliable qualimetric parameters were obtained.

Optical “fingerprints” are widely used in chemometrics-assited recognition of samples of different nature. An emerging trend in this area is the transition from obtaining "static" spectral data to reactions occurring over time. The indicator reactions are usually carried out in aqueous solutions; in this study we have developed the reactions that occur in an organic solvent, which makes it possible to recognize fat-soluble samples. In this capacity, we used 5W40, 10W40 and 5W30 motor oils of 4 manufacturers, totally 6 samples. The procedure involved mixing of the dye, sample, and reagents (HNO3, HCl, or t-butyl hydroperoxide) in ethanolic solution in a 96-well plate and measuring absorbance or near-IR fluorescence intensity every several minutes during 20–55 min. The obtained photographic images were processed by linear discriminant analysis (LDA) and k-nearest neighbors algorithm (kNN). The discrimination accuracy was evaluated by using the validation procedure. Reaction of oxidation of a dye with nitric acid allowed to recognize all 6 samples with 100% accuracy by LDA. Merging data of 4 reactions that did not provide complete discrimination ensured an accuracy of 93% by kNN technique. The developed indicator systems have good prospects for the discrimination of other fat-soluble samples. Overall, the results confirm the viability of the kinetic-based discrimination strategy.

Purposes: To provide abdominal contrast-enhanced MR image synthesis, we developed an image gradient regularized multi-modal multi-discrimination sparse-attention fusion generative adversarial network (GRMM-GAN) to avoid repeated contrast injections to patients and facilitate adaptive monitoring. Methods: With IRB approval, 165 abdominal MR studies from 61 liver cancer patients were retrospectively solicited from our institutional database. Each study included T2, T1 pre-contrast (T1pre), and T1 contrast-enhanced (T1ce) images. The GRMM-GAN synthesis pipeline consists of a sparse attention fusion network, an image gradient regularizer (GR), and a generative adversarial network with multi-discrimination. The studies were randomly divided into 115 for training, 20 for validation, and 30 for testing. The two pre-contrast MR modalities, T2 and T1pre images, were adopted as inputs in the training phase. The T1ce image at the portal venous phase was used as an output. The synthesized T1ce images were compared with the ground truth T1ce images. The evaluation metrics include peak signal-to-noise ratio (PSNR), structural-similarity-index (SSIM), and mean-squared-error (MSE). A Turing test and experts’ contours evaluated the image synthesis quality. Results: The proposed GRMM-GAN model achieved a PSNR of 28.56, an SSIM of 0.869, and an MSE of 83.27. The proposed model showed statistically significant improvements in all metrics tested with p-values <0.05 over the state-of-the-art model comparisons. The average Turing test score was 52.33%, close to random guessing, supporting the model's effectiveness for clinical application. In the tumor-specific region analysis, the average tumor contrast-to-noise ratio (CNR) of the synthesized MR images was not statistically significant from the real MR images. The average DICE from real vs. synthetic images was 0.90, compared to the inter-operator DICE of 0.91. Conclusion: We demonstrated the function of a novel multi-modal MR image synthesis neural network, GRMM-GAN, for T1ce MR synthesis based on pre-contrast T1 and T2 MR images. GRMM-GAN shows promise for avoiding repeated contrast injections during radiation therapy treatment.

Eating and drinking difficulties are common in dementia, but little is known about the experiences of ethnic minority groups managing these difficulties at home. We undertook qualitative semi-structured interviews, exploring the meaning of food, the impact of dementia on eating and drinking and carers’ experiences of support. Interviews were audio-recorded and transcribed verbatim. We interviewed 17 carers and people with dementia from ethnic minority backgrounds, using reflexive thematic analysis to analyse data. Food/drink had strong links to identity, culture and emotions. Providing culturally familiar foods, celebrating traditional festivals and supporting previous food-related roles promoted reminiscence, which encouraged people with dementia to eat and drink, as did social interactions. However, these strategies sometimes led to distress in those with more advanced dementia. Food choices were also influenced by carer strain, generational differences and the impact of health conditions. Despite a strong sense of duty to care for relatives at home, there was low awareness of community support services. Carers expressed a need for culturally tailored support for managing dementia-related eating and drinking difficulties at home. Healthcare professionals must provide contextually relevant advice to carers, being mindful of how cultural backgrounds can affect dietary choices.

Aim: Ectopic lipid accumulation, including pancreatic steatosis, exacerbates type 2 diabetes risk in susceptible individuals. Dysregulated circulating microRNAs (miRNAs) have been identified to correlate with clinical measures of pancreatitis, pancreatic cancer, and type 1 diabetes. The aim of the current study was, therefore, to examine the association between circulating abundances of candidate miRNAs and pancreatic and liver fat deposition as quantified using magnetic resonance imaging (MRI) and spectroscopy (MRS). Methods: Asian Chinese (n=34; BMI=26.7±4.2 kg/m2) and European Caucasian (n=34; BMI=28.0±4.5 kg/m2) females from the TOFI_Asia cohort underwent MRI and MRS analysis of pancreas (MR-%pancreas) and liver (MR-%liver fat) respectively to quantify ectopic lipid deposition. Plasma miRNA abundances of a subset of circulatory miRNAs associated with pancreatic and liver steatosis were quantified by qRT-PCR. Results: miR-21-3p and miR-320a-5p correlated with MR-%pancreas fat, plasma insulin and HOMA2-IR but not MR-%liver fat. MR-%pancreas fat remained associated with decreasing miR-21-3p abundance following multivariate regression analysis. Conclusions: miR-21-3p and miR-320a were demonstrated to be negatively correlated with MR-%pancreas fat, independent of ethnicity. For miR-21-3p, this relationship persists with the inclusion of MR-%liver fat in the model, suggesting the potential for wider application as a specific circulatory correlate of pancreatic steatosis.

The Black population, often treated as ethnically homogenous, faces a constant challenge in accessing and utilizing healthcare services. This study examines the intragroup differences in health-seeking behavior among the multiple ethnic subgroups that comprise the Black community. A cross-sectional study was conducted among 239 adults ≥18 years who self-identified as Black in the United States and Canada. A multiple logistic regression model was fitted to evaluate the relationship between health-seeking behaviors and ethnic origin controlling for selected social and health related factors. The mean age of participants was 38.6 years, 31% were male, and 20% were unemployed. Sixty-one percent reported very good or excellent health status, and 59.7% reported not being treated for chronic disease at the time of the survey. Aging (OR=1.05, CI:1.01–1.09) and being female (OR= 0.30, CI: 0.14–0.65) were associated with favorable health-seeking behaviors. Compared with participants who had earned high school diplomas only, those who reported having earned graduate degrees were 75% less likely to have engaged in favorable health-seeking behavior (OR=0.25, 95% CI: 0.07–0.86). In the Black community of our sample, regardless of ethnic origins or country of birth, the factors associated with health-seeking behavior were age, gender, and educational attainment. Keywords: African American; African; Caribbean; Healthcare Utilization; Ethnic Disparities; Health-seeking behavior; intragroup difference, black populations, ethnic subgroups

Lifestyle physical activity (PA) and nutrition are known to be effective interventions in preventing and managing obesity related comorbidities is adult populations, but less so in children and adolescents. We examined the effectiveness of lifestyle interventions in children from minority ethnic populations in western high-income countries. Our systematic review included 53 studies involving 26045 children from minority ethnic populations within western countries, who followed lifestyle intervention programs lasting between 8 weeks and 5 years with an aim to prevent and/or manage childhood obesity and associated comorbidities, including adiposity and cardiometabolic risks. Studies were heterogenous in terms of lifestyle intervention components (nutrition, PA, behavioural counselling) and settings (community vs. schools and after schools). Our meta-analysis included 31 eligible studies and showed no significant effects of lifestyle interventions when they focused on body weight and body mass index (BMI) outcomes [pooled BMI mean change = -0.09 (95% CI -0.19, 0.01), p=0.09]. This was irrespective of the intervention program duration (< 6 months vs. ≥ 6 months), type (PA vs nutrition/combined intervention) and weight status (overweight or obese vs no normal weight), all showed no significant effects in the sensitivity analysis. Nonetheless, 19 of the 53 studies reported reduction in BMI, BMI z scores and body fat percentage. However, majority of lifestyle interventions adopting a quasi-design with a combined primary and secondary obesity measures (11 out of 15 studies), were effective in reducing obesity comorbidities of cardiometabolic risks including metabolic syndrome, insulin sensitivity, and blood pressure in children with overweight and obesity. Preventing childhood obesity and associated comorbidities in children from high-risk ethnic minority groups is best achieved using a combined PA and nutrition intervention approach, which jointly target preventing obesity and cardiometabolic disease primary and secondary outcomes, especially measures of diabetes, hypertension, and cardiovascular disease.

The initial development of seahorse juveniles is characterized by low digestion capabilities. Stable isotope analysis is an effective tool in studies of trophic food webs and animal feeding patterns. The present study provides new insights for the understanding of growth and food assimilation in early developing seahorses following a laboratory diet switch. The study was performed in early life stages of the seahorse Hippocampus reidi by assessing the influence of diet shift on changes and turnovers in carbon (δ13C) and nitrogen (δ15N) stable isotope in juveniles. Newborn seahorses were fed for 60 days following two feeding schedules (A6 and A11) based initially on copepods Acartia tonsa and subsequently on Artemia nauplii (since days 6 and 11, respectively). After prey shift, we determined δ13C and δ15N turnover rates as functions of change in either body mass (fitting model G) and days of development (fitting model D), contributions of metabolism and growth to those turnover rates, and diet-tissue discrimination factors. Survival, final dry weight and final standard length for diet A11 were higher compared to diet A6. The shift from copepods to Artemia lead to fast initial enrichments in δ13C and δ15N. Afterwards, the enrichment was gradually reduced until reaching the isotopic equilibrium with diet. In most cases, both fitting models performed similarly. The isotopic analysis revealed that 100% of tissue turnover was attributed to growth in diet A11, whereas 19-25% was endorsed to metabolism in diet A6. Diet-tissue discrimination factors were estimated for the first time in seahorse juveniles, resulting in higher estimates for diet A11 (2.9 ± 0.7‰ for δ13C; 2.5 ± 0.2‰ for δ15N) than in diet A6 (1.8 ± 0.1‰ for δ13C; 1.9 ± 0.1‰ for δ15N). This study highlights the relevance of feeding on copepods and their effect on isotopic patterns and discrimination factors in seahorse juveniles after a dietary shift. Regarding the application of the results achieved to feeding schedules in the rearing of H. reidi, a long period of feeding on copepods during the first days of development is highly recommended.

The chiral recognition of enantiomers is a topic of great importance. In this study, a straightforward and effective chiral detection strategy was developed for distinguishing between tryptophan (TRP) enantiomers. The approach involved the preparation of a magnetic molecularly imprinted chitosan (MMIC) for the sample preparation, which was combined with a nitrocellulose membrane (paper-based analytical device, PAD) integrated with D-TRP covalently-grafted polymethacrylic acid (PAD_PMA_D-TRP). The discrimination between TRP enantiomers was achieved using AuNPs as a colorimetric probe. Indeed, the presence of D-TRP rapidly induced the aggregation of AuNPs due to its strong affinity to PAD-PMA_D-TRP, resulting in a noticeable color change of the AuNPs from red to purple. On the other hand, L-TRP did not induce any color change. The chiral analysis could be easily performed with the naked eye and/or a smartphone. The developed method exhibited a detection limit of 3.3 µM and it was successfully applied to detect D-TRP in serum samples, demonstrating good recovery rates. The proposed procedure is characterized by its simplicity, cost-effectiveness, rapidity, and ease of operation.

In this paper, a multi-mode waveguide-based optical resonator is proposed for an integrated optical refractive index sensor. Conventional optical resonators have been studied for single-mode waveguide-based resonators to enhance the performance, but mass production is limited owing to the high fabrication costs of nano-scale structures. To overcome this problem, we designed an S-bend resonator based on a micro-scale multi-mode waveguide. In general, multi-mode waveguides cannot be utilized as optical resonators, because of a performance degradation resulting from modal dispersion and an output transmission with multi-peaks. Therefore, we exploited the mode discrimination phenomenon using the bending loss, and the resulting S-bend resonator yielded an output transmission without multi-peaks. This phenomenon is utilized to remove higher-order modes efficiently using the difference in the effective refractive index between the higher-order and fundamental modes. As a result, the resonator achieved a Q-factor and sensitivity of 2.3x10³ and 52 nm/RIU, respectively, using the variational finite-difference time-domain method. These results show that the multi-mode waveguide-based S-bend resonator with a wide line width can be utilized as a refractive index sensor.

In recent decades, attention has been directed at anemia classification for various medical purposes, such as thalassemia screening and predicting iron deficiency anemia (IDA). In this study, a new method has been successfully tested for discrimination between IDA and β-thalassemia trait (β-TT). The method is based on a Dynamic Harmony Search (DHS). Complete blood count (CBC), a fast and inexpensive laboratory test, is used as the input of the system. Other models, such as a genetic programming method called structured representation on genetic algorithm in non-linear function fitting (STROGANOFF), an artificial neural network (ANN), an adaptive neuro-fuzzy inference system (ANFIS), a support vector machine (SVM), k-nearest neighbor (KNN), and certain traditional methods, are compared with the proposed method.

Background: Polycystic ovary syndrome (PCOS) is a common endocrinopathy that is highly prevalent in women of Indian ethnicity. Clinical practice guidelines do not adequately consider ethnic-cultural differences in the care of women with PCOS. This study aimed to explore ethnic Indian women’s experiences with PCOS diagnosis and management, their concerns and it’s impact on their quality of life (QoL). Methods: Global online survey of ethnic Indian women of reproductive age living with PCOS. Results: Respondents (n=4409) had a mean age of 26.8 (SD 5.5) years and the majority were diagnosed with one or more co-morbidities (anxiety/depression being the most common). Women waited one year on average before seeking treatment following symptom onset. Irregular periods, cysts on the ovaries and excess unwanted facial hair growth were their three major concerns. Weight and emotional concerns had the greatest impact on QoL. One-third did not receive information on long-term complications, appropriate behavioral advice to improve diet or exercise, or emotional support following diagnosis. Among those who received information at diagnosis, the majority were dissatisfied. Conclusions: Ethnic Indian women wait for a considerable time before seeking medical help for PCOS, have poor QoL relating to weight and mental health and are dissatisfied with the information and support provided at diagnosis. These gaps in care should be addressed in clinical practice and future research.

As a traditional Muslim country, the problem of gender discrimination in employment among women in Pakistan is more common. If we let it develop without taking measures, it will seriously restrict the speed and quality of Pakistan’s domestic economic development in the long run. In this study, the author obtained the first-hand information on the employment status of professional women in the Rahim Yar Khan region of Pakistan through questionnaire survey, supplemented by the public data of the Federal Statistical Office of Pakistan, and combined with the existing research results of the predecessors. Sex discrimination in employment of professional women in Pakistan. Through the collection of the data obtained from the questionnaire, the author found that economic factors are one of the main factors that cause local women to encounter gender discrimination in employment. Specifically, it includes the imbalance of labor supply and demand and the pursuit of maximum profits. At the same time, the traditional Muslim culture, women's own literacy and the imperfect legal system in Pakistan are also the key factors that cause female employees in the local area to encounter gender discrimination in employment. Women’s gender discrimination in employment is a universal problem. In any country in the world, gender discrimination may exist as long as women are involved in the work. Based on Pakistan's basic national conditions and relevant professional knowledge, the author provides several suggestions for eliminating the problem of gender discrimination in employment for local female employees in Pakistan. 1) The Pakistani government should further promote the domestic economic growth, increase the number of jobs, and ease the imbalance between the supply and demand of labor. At the same time, encourage self-employment and provide corresponding policy support. A variety of measures are also intended to address local gender discrimination in employment for women. 2) The government's leadership accelerates the transformation of the concept of the whole society. On the one hand, it requires the whole society to correctly understand the social status and social contribution of women, and strives to bring the concept of equality between men and women into the hearts of the people. It is intended to encourage qualified women to go out of the family to participate in social work. At the same time, correctly guide corporate values. Enterprises should not unilaterally pursue the maximization of interests, and should take the initiative to assume social responsibilities. 3) Women should also actively and consciously improve their literacy. Including not only active learning advanced cultural knowledge and professional skills. For the professional skills that have already been mastered, you must study harder and make yourself more and more progressive. At the same time, families should guarantee that girls of the appropriate age receive the education they deserve, so that they can gather their strengths in the workplace in the future.

Multi-sensor data fusion of E-tongue and E-nose can provide a more comprehensive and more accurate analysis results. However, it also brings some redundant information, it is a hot issue to reduce the feature dimension for pattern recognition. In this paper, the taste-olfactory data fusion based on E-tongue and E-nose combined with Support Vector Machine (SVM) was used to classify five different beers. First, the taste and olfactory feature information were obtained based on E-tongue and E-nose. Second, the original feature data of single system were fused, then Principal Component Analysis (PCA) was applied to extract principal components, Genetic Algorithm-Partial Least Squares (GA-PLS) was used to select the characteristic variables, 20 subsets were generated with those variables based on the best Variable Importance of Projection (VIP) score. Finally, the classification models based on SVM were established, also c and g of SVM were calculated by Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), the classification results of all subsets were obtained. The results showed that the classification accuracy using data fusion was much higher over single E-tongue and single E-nose, and the variable selection method by VIP had the best classification performance in #12 subset coupled with GA-SVM.

Non-timber forest products (NTFP) have contributed in various ways to the living, livelihoods, and trading of households and communities who live in rural and urban areas all over the world. This paper analyses the value chain of Jiaogulan (Gynostemma pentaphyllum) in the Cao Bang Geopark, Vietnam. 106 actors were surveyed using a semi-structured questionnaire: experts (agricultural extension officers, farmers' associations), harvesters, traders, primary processors, processors, distributors, and consumers. The results show that a map of Jiaogulan value chain, value added of households in main market channels, and impact of value added and distribution of Jiaogulan products on household income.

People from Black and Asian backgrounds are more likely to die from Covid-19 but less likely to be vaccinated, threatening to exacerbate health inequalities already experienced by ethnic minority groups. Literature suggests that mistrust rooted in structural inequality may be a key barrier to Covid-19 vaccine uptake. We need to better understand how structural inequalities influence vaccine confidence. Understanding and addressing these processes is likely to lead to longer-term impacts than information alone. We draw on health and sociological theories of structure and agency to inform our understanding of structural factors. We conducted qualitative interviews and focus groups with 22 people from London and surrounding areas in December 2021 to March 2022. Fifteen participants were members of the public from ethnic minority backgrounds and 7 were professionals working with the public to address concerns and encourage vaccine uptake. Our findings suggest that people from ethnic minority backgrounds make decisions regarding Covid-19 vaccination based on a combination of how they experience external social structures (including political authority, social positioning and racial inequality) and internal processes (what they believe and understand about Covid-19 vaccines). We may be able to support knowledge accumulation through the provision of reliable and accessible information, particularly through primary and community care. But we recommend a number of changes to research, policy and practice which address structural inequalities. These include working with communities to improve ethnicity data collection, increasing funding allocation to health conditions where ethnic minority communities experience poorer outcomes, greater transparency and public engagement in the vaccine development process, and culturally adapted research recruitment processes.

Rationale: Major depressive disorder (MDD) is characterized by signaling aberrations in interleukin (IL)-6, IL-10, beta-endorphins as well as mu (MOR) and kappa (KOR) opioid receptors. Here we examined whether these biomarkers may aid in the classification of unknown subjects into the target class MDD.Methods: The aforementioned biomarkers were assayed in 60 first-episode, drug-naïve depressed patients and 30 controls. We analyzed the data using joint principal component analysis (PCA) performed on all subjects to check whether subjects cluster by classes; support vector machine (SVM) with 10-fold validation; and linear discriminant analysis (LDA) and SIMCA performed on calibration and validation sets and we computed the figures of merit and learnt from the data. Results: PCA shows that both groups were well separated using the first three PCs, while correlation loadings show that all 5 biomarkers have discriminatory value. SVM and LDA yielded an accuracy of 100% in validation samples. Using SIMCA there was a highly significant discrimination of both groups (model-to-model distance=87.5); all biomarkers showed a significant discrimination and modeling power, while 10% of the patients were identified as outsiders and no aliens could be identified.Discussion: We have delineated that MDD is a distinct class with respect to neuro-immune and opioid biomarkers and that future unknown subjects can be authenticated as having MDD using this SIMCA fingerprint. Precision psychiatry should employ SIMCA a) to authenticate patients as belonging to the claimed target class and identify other subjects as outsiders, members of another class or aliens; and b) to acquire knowledge through learning from the data by constructing a biomarker fingerprint of the target class.

Evidence was brought forward in England and the USA that Black, Asian, Latino and Minority Ethnic people exhibit higher mortality risk from COVID-19 than White people. While socioeconomic factors were suggested to contribute to this trend, they arguably do not explain the range of the differences observed, allowing for possible genetic implications. Almost concurrently, the analysis of a cohort in Chinese COVID-19 patients proposed an association between the severity of the disease and the presence of the minor allele of rs12252 of the Interferon-induced transmembrane protein 3 (IFITM3) gene. This SNP, together with rs34481144, are the two most studied polymorphisms of IFITM3 and have been associated in the past with increased severity in Influenza, Dengue, Ebola, and HIV viruses. IFITM3 is an immune effector protein that is pivotal for the restriction of viral replication, but also for the regulation of cytokine production. Following up to these two developments in the ongoing SARS-CoV-2 pandemic, the present study investigates a possible association between the differences in mortality of ethnic groups in England and the combined haplotypes of rs12252 and rs34481144. The respective allele frequencies were collected for 26 populations from 1000 Genomes Project and subgroups were pooled wherever possible to create correspondences with ethnic groups in England. A significant correlation (r=0.9687, p= 0.0003) was observed between the reported Standardized Mortality Ratios and the frequency of the combined haplotype of both reference alleles, suggesting that the combination of reference alleles of the specific SNPs may be implicated in more severe outcomes of COVID-19. This study calls for further focus on the role of IFITM3 variants in the mechanism of cellular invasion of SARS-CoV-2, their impact in COVID-19 severity and their possible implications in vaccination efficacy.

There is a general lack of research involving older lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ) people. This systematic review aimed to synthesize Japanese and Swedish qualitative research on LGBTQ people aged 60 years or older. PRISMA guidelines were followed. Japanese and Swedish articles, published in English-language journals, were searched across PsychINFO, Medline, CINAHL, and Sociological Abstracts databases. Additional searches were carried out to include studies written in Japanese or Swedish. There were no papers from Japan, and five from Sweden were reviewed. Four articles were included, including 48 participants aged 60–94 years. We summarized the findings using a deductive thematic synthesis. Two major themes emerged: (a) quality of life, minority joy, and resilience (positive aspects), and (b) experiences of discrimination, stigmatization, and minority stress (negative aspects). The participants described a wish to be acknowledged for their own assets and unique life histories, and to be treated as everyone else. They emphasized the importance of knowledge of LGBTQ issues among nursing staff, so that older LGBTQ people are treated in a competent and affirmative way. The study revealed several important topics for understanding older LGBTQ people’s life circumstances and the severe lack of qualitative studies in Japan and Sweden.

Smoking during pregnancy remains one of the most significant risk factors for poor birth outcomes. The Loma Linda University Health Comprehensive Tobacco Treatment Program (CTTP) is the largest maternal tobacco cessation program in San Bernardino County – the largest county in the contiguous US. CTTP is an eight week, incentivized, behavioral intervention for tobacco cessation for pregnant smokers. As part of program evaluation, we used a retrospective cohort design to assess smoking abstinence and to identify predictors of relapse/smoking after enrollment. Among CTTP cohort enrollees (n=233) from 2012-2013 we found: 1) a 28.4% 8 week point prevalence abstinence (PPA), and at a median of 9 months of follow-up after the PPA, 81.6% continued to indicate tobacco cessation, and 2) a high rate of relapse or loss to follow-up (56%). Our modeling of relapse/smoking after enrollment indicated that this was higher in young mothers, non-Hispanic mothers (White, Black), first/third trimester mothers, and rural mothers. The evaluation identified efficacy of the behavioral model at 8 weeks, but that relapse/smoking was occurring in disparity populations. Formative research is needed to expand the programmatic outreach and enrollment of mothers wanting to quit smoking.

Breast cancer is the leading cause of cancer deaths worldwide in women. This aggressive tumour can be categorized into two main groups: in situ and infiltrative, with the latter being the most common malignant lesions. The current use of Magnetic Resonance Imaging (MRI) was shown to provide highest sensitivity in the detection and discrimination between benign vs. malignant lesions, when interpreted by expert radiologists. In this article, we present the prototype of a Computer-Aided Detection/Diagnosis (CAD) system that could provide valuable assistance to the radiologist for the discrimination between in situ and infiltrating tumours. The system consists of two main processing levels: 1) Localization of possibly tumoral regions of interest (ROIs) through an iterative procedure based on intensity values (ROI Hunter) followed by a deep-feature extraction and classification method for false-positive rejection; 2) Characterization of the selected ROIs and discrimination between in situ and invasive tumour, consisting of Radiomics feature extraction and classification through a machine-learning algorithm. The CAD system was developed and evaluated using a DCE-MRI image database, containing at least one confirmed mass per image, as diagnosed by an expert radiologist. When evaluating the accuracy of the ROI Hunter procedure with respect to the radiologist-drawn boundaries, sensitivity to mass detection was found to be 75%. The AUC of the ROC curve for discrimination between in situ and infiltrative tumors was 0.70.

Background: The number of young Japanese Brazilians, who are return migrants with Japanese ancestral roots, is increasing rapidly in Japan. However, the characteristics of their mental health and the relation between mental health and a complex ethnic identity remains unclear. Methods: This cross-sectional study compared 25 Japanese-Brazilian high school students with 62 Japanese high school students living in the same area. Research using self-report questionnaires on mental health, help-seeking behavior tendencies, and ethnic identity was conducted. The Japanese-Brazilian group was also divided into high and low ethnic identity groups, and their mental health conditions were compared. Results: The Japanese-Brazilian group had significantly poorer mental health conditions and lower ethnic identities than the Japanese group and were less likely to seek help from family members and close relatives. Among the Japanese Brazilians, those with low ethnic identity had significantly poorer mental health than those with high ethnic identity. Conclusions: Young Japanese Brazilians may face conflicts of ethnic identity that can disturb their mental health. To build an inclusive society, the establishment of community services to support mental health and to help return migrants develop their ethnic identity is essential.

Background: Early diagnosis of postoperative complications is an urgent task, allowing timely prescribing of appropriate therapy and reducing the cost of patient treatment. Prognostic models based on various data could help in the early diagnosis of postoperative complications after cardiac surgery. Objectives: The purpose of the study was to determine whether an integrated approach based on clinical data along with metabolites and biomarkers had greater predictive value than the models built on less data. Methods: The study included patients (n=62) admitted for planned cardiac surgery (coronary artery bypass grafting with cardiopulmonary bypass), who were retrospectively divided into two groups depending on the presence (n=26) or absence (n=36) of postoperative complications of all types. Clinical and laboratory data on the first day after surgery were analyzed. Additionally, patients' blood samples were collected before and on the first day after surgery to determine biomarkers (interleukin-6, procalcitonin, NT-proBNP, high-sensitivity troponin T) and metabolites (8 aromatic and 2 dicarboxylic acids were detected using gas chromatography-mass spectrometry). Results: Patients before surgery, compared with healthy donors, differed in the concentration of metabolites (p &lt; 0.05), and had concentrations of a number of biomarkers exceeding the corresponding reference values. Multivariate PLS-DA models, predicting the presence or absence of postoperative complications, were built using clinical data (ROC-AUC=0.71), concentrations of metabolites and biomarkers (ROC-AUC=0.60), and the entire data set (ROC-AUC=0.75). For comparison we built univariate models using the EuroScore2 (ROC-AUC=0.59) and SOFA (ROC-AUC=0.76) scales; concentrations of lactate (ROC-AUC=0.71), the dynamic changes of 4-hydroxyphenyllactic acid (ROC-AUC=0.69), and the sum of three sepsis-associated metabolites (ROC-AUC=0.70). The proposed complex model using entire data set was comparable to the SOFA scale, which confirms the expediency of searching for new predictive models based on a variety of factors.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

The impact of interaction SS with MJO on rainfall along Java Island to East Nusa Tenggara has been studied using daily rainfall observation data from 2140 weather observation stations, which are also equipped with GSMaP, OLR, and ERA5 data. There were 61 SS events found, 17 during active MJO and 44 in inactive MJO. Rainfall increases more in the western study area when the active MJO and more in the eastern study area when the inactive MJO is due to SS. SS reduces rainfall in the Jakarta region, regardless of the activity or inactivity of the MJO. SS causes extreme rainfall to only occur in a small part of certain areas, so it tends to significantly reduce the possibility of extreme rainfall. In the southern part of the IMC, SS predominates over MJO in supporting increased water vapor transport. Large-scale synoptic circulations like the monsoon, SS, and MJO can interact with local land-sea wind circulation to produce spatiotemporal variability in rainfall on Java Island. Rainfall mostly increases in the afternoon and decreases in the morning when SS occurs, whether there is MJO or not. Convective instability analysis indicates that SS increases precipitation, most likely by lowering CIN and raising VIMFC.

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

In recent years, electroencephalogram (EEG) emotion recognition has emerged as a research hotspot in the field of artificial intelligence (AI). Despite advancements in EEG-based emotion recognition, room for enhancing performance persists due to EEG signal redundancy and limitations in feature extraction, leading to inefficient models and emotional information loss. To fully utilize EEG's emotional information and improve recognition accuracy while reducing computational costs, this paper proposes a Convolutional-Recurrent Hybrid Network with a dual-stream adaptive approach and an attention mechanism (CSA-SA-CRTNN). Firstly, the model utilizes a CSAM module to assign corresponding weights to EEG channels. Then, an adaptive dual-stream convolutional-recurrent network (SA-CRNN and MHSA-CRNN) is applied to extract local spatial-temporal features. After that, the extracted local features are concatenated and fed into a temporal convolutional network with a multi-head self-attention mechanism (MHSA-TCN) to capture global information. Finally, the extracted EEG information is used for emotion classification. We conducted binary and ternary classification experiments on the DEAP dataset, achieving 99.26% and 99.15% accuracy for arousal and valence in binary classification, and 97.69% and 98.05% in ternary classification, surpassing relevant algorithms. Additionally, the model's efficiency is significantly higher than other models, achieving better accuracy with lower resource consumption.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

Currently there are fewer depth models applied to pepper picking detection, while the existing generalized neural networks have problems such as large model parameters, long training time, and low model accuracy.In order to solve the above problems, this paper proposes a Yolo-chili target detection algorithm for chili pepper detection. First, the classical target detection algorithm yolov5 is used as a benchmark model, and an adaptive spatial feature pyramid structure combining the attention mechanism and the idea of multi-scale prediction is introduced to improve the model's detection effect on occluded peppers and small target peppers. Secondly, a three-channel attention mechanism module is introduced to improve the algorithm's long-distance recognition ability and reduce the interference of redundant testers. Finally, the quantized pruning method is used to reduce the model parameters and realize the lightweight processing of the model. Applying the method to the homemade chili pepper dataset, the AP value of chili pepper reaches 93.11%; the accuracy rate is 93.51% and the recall rate is 92.55%.The experimental results show that yolo-chili is able to achieve accurate and real-time pepper detection under complex orchards.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

Excess nitrogen in agricultural drainage poses a serious threat to the water quality safety of the Yellow River basin. Utilizing aquatic plants to modify the rhizosphere microbial community structure and facilitate nitrogen transformation is a crucial strategy for mitigating regional water eutrophication. Our results revealed that the denitrification rate (DR), dissimilatory nitrate reduction to ammonium rate (DNRAR) and nitrogen fixation rate (NFR) of rhizosphere sediments exhibited a significant increase in artificially cultivated ditch. Compared with those in natural ditches, the richness of the bacterial community and the relative abundances of Bacteroidota, Verrucomicrobiota, Firmicutes, Anaeromyxobacter and Geobacter, which are involved mainly in the nitrogen cycle, in the rhizosphere sediments of artificially cultivated ditch were significantly greater due to improvements in environmental conditions. In artificially cultivated ditch, the dominant functional genes affecting DRNARs in the rhizosphere sediments of P. australis were nrfC and nrfA, while DRs were driven mainly by norB and napA, which were influenced by the nitrogen and carbon levels; and the dominant functional genes affecting NFRs in the rhizosphere sediments of T. orientalis were nifD, nifK and nifH. Our results provide a scientific basis for the use of aquatic plants for mitigating excess nitrogen levels in agricultural drainage.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

In this paper we study a class of impulsive delayed neural networks with parameter uncertainties and reaction-diffusion terms. Using the properties of M-matrices and some inequality techniques, some sufficient conditions are derived to guarantee the global exponential stability of the given system. The results obtained are presented by simple algebraic inequalities, which are certainly more concise than previous methods. Finally, the validity and usefulness of our results are illustrated by arithmetic examples.

Pyrops candelaria is one of the common pests of fruit trees, but the research on the pathogenic microorganisms it may carry is very limited. Therefore, it is essential to reveal the pathogenic microbes it carries and their potential hazards. This study found a new virus from the transcriptome of P. candelaria, which was first reported in P. candelaria and named as PyCaV (Pyrops candelaria associated virus). RACE and bioinformatics assay revealed that the full-length of PyCaV is 10855 bp with the polyA tail, containing a single open reading frame (ORF) encoding a polyprotein consisting of 3171 amino acid (aa). The virus has a typical Iflavirus structure, including two rhv domains, a RNA helicase domain (HEL), a 3C cysteine protease domain (Pro), and a RNA-dependent RNA polymerase domain (RdRp). Further phylogenetic analysis revealed that this virus belongs to family Iflaviridae and sequence alignements analysis suggedted PyCaV is new member in unassigned genus of family Iflaviridae. Further in-depth analysis of virus-infection-part showed that PyCaV is distributing in the whole longan lanternfly, including its head, chest, and abdomen, but more PyCaV was identified in the chest. The distribution of PyCaV in different parts of P. candelaria was further explored, which showed that more PyCaV were detected in its piercing-sucking mouthparts and chest viscera. Statistical analysis showed that the PyCaV infection was affected by time and locations.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p &lt; 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.