Day-ahead generation scheduling is conducted by solving security-constrained unit commitment (SCUC) problem. Fast-growing inverter-based resources dramatically reduces grid inertia, compromising system dynamic stability. Traditional SCUC (T-SCUC), without any inertia requirements, may no longer be effective for renewables-dominated grids. To address this, we propose the active linearized sparse neural network-embedded SCUC (ALSNN-SCUC) model, utilizing machine learning (ML) to incorporate system dynamic performance. A multi-output deep neural network (DNN) model is trained offline on strategically-selected data samples to accurately predict fre-quency stability metrics: locational RoCoF and frequency nadir. Structured sparsity and active ReLU linearization are imple-mented to prune redundant DNN neurons, significantly reducing its size while ensuring prediction accuracy even at high sparsity levels. By embedding this ML-based frequency stability predictor into SCUC as constraints, the proposed ALSNN-SCUC model minimizes its computational complexity while ensuring frequency stability following G-1 contingency. Case studies show that the proposed ALSNN-SCUC can enforce pre-specified frequency requirements without being overly conservative, outperforming five benchmark models including T-SCUC, two physics-based SCUC, and two ML-based SCUC. The proposed sparsification and active linearization strategies can reduce the DNN-SCUC computing time by over 95% for both IEEE 24-bus and 118-bus systems, demonstrating the effectiveness and scalability of the proposed ALSNN-SCUC model.

Alongshan virus in the virome of Ixodes hexagonus ticks in the United Kingdom.

Construction of dual-mode sensing platforms based on MPC-B(OH)2 nanozyme: Colorimetric/electrochemical detection and portable smartphone sensing for foodborne contaminant detection.

Ultrasensitive colorimetric/fluorescence dual-mode sensing platform based on quasi-NENU-5 for specific detection of glyphosate.

Ancient DNA (aDNA) and protein analysis of human remains enables reconstructions of population history, kinship, diet, health and social structure of ancient communities. Ancient DNA yields important genetic information, nonetheless its extraction requires sampling, which is an important concern especially for rare and valuable samples. Furthermore, poor preservation of aDNA results to low endogenous DNA yield, and considering that analyses are costly and time-consuming, efficient pre-screening methods are needed to identify samples with higher probability of aDNA survival. Here, we present an in situ, non-invasive micro-Raman spectroscopy approach as a screening tool capable of predicting DNA preservation in ancient teeth. Because aDNA tends to persist in teeth preserving part of their proteinaceous (primarily collagen) component, the relative abundance of protein to mineral provides an indirect indication for DNA preservation. A set of 49 ancient teeth, dated from 8800 BCE to 1941 CE, were analyzed using for sample classification the amide-to-phosphate [AmI/P] index, defined as the intensity ratio of the amide I band (1666 cm − 1 ) over the phosphate band (PO₄ 3− , 957 cm − 1 ). Measurements on the cementum area of the teeth, known to be protein-rich, revealed a weak but clear correlation between [AmI/P] and endogenous DNA amounts, independently determined via standard aDNA analysis. Among 25 aDNA-rich teeth, 23 were correctly identified (92% acceptance), and 13 of 20 aDNA-poor teeth were indicated to be so (65% rejection). Overall, Raman spectroscopy provides a valid, in situ, non-invasive pre-screening strategy for prioritizing ancient teeth with higher collagen content and greater likelihood of yielding endogenous human DNA. • Raman spectroscopy provides a fully non-invasive, in-situ method to pre-screen ancient teeth for DNA preservation. • The amide-to-phosphate Raman index [Am/P] reflects the proteinaceous content relative to the hydroxyapatite matrix. • The approach correctly identified 92% of aDNA-rich and 65% of aDNA-poor samples. • Raman spectroscopy can guide sample selection, reducing destruction of archaeological remains and prioritize samples with greater likelihood of yielding endogenous human DNA

Despite Sorghum ( Sorghum bicolor ) potential to enhance food security and livelihoods, the commercialisation of sorghum remains limited, with most production occurring under subsistence farming systems. Our study evaluates determinants of the decision to participate in the sorghum market and the intensity of participation among smallholder farmers in Western Kenya. We conducted a cross-sectional survey of 300 farming households. Using the Heckman two-step sample selection model, our study evaluated the propensity to participate in the market and the intensity of participation. Out of the 300 households sampled, 103 (34%) participated in sorghum markets. We found that education (β = 0.63, p = 0.048), hired labour (β = 1.20, p < 0.001), log land size (β = 0.62, p = 0.070), group membership (β = 1.19, p < 0.001), occupation (β = 0.86, p = 0.018), market information (β = 2.06, p < 0.001), radio ownership (β = 0.0.51, p = 0.049), mobile ownership (β = 0.65, p = 0.045), distance to market (β = -0.35, p = 0.037), and geographical location (β = 1.18, p < 0.001) significantly determined market participation level. The intensity of participation was significantly predicted by education (β = 0.135, p < 0.001), log age (β = -0.53, p = 0.043), log family size (β = -0.267, p < 0.001), hired labour (β = 0.111, p = 0.002), radio ownership (β = 0.156, p < 0.001), mobile ownership (β = 0.213, p < 0.001) and distance to market (β = -0.160, p = 0.002). Our findings suggest that enhancing access to market information and promoting group membership can increase sorghum market participation and improve commercialisation. Policies aimed at improving rural infrastructure, strengthening agricultural cooperatives, and expanding educational opportunities for farmers are crucial for enhancing market access and supporting sorghum commercialisation. • The Heckman two-step model used to assess market participation and intensity • Sorghum market participation is driven by education, labor, and land size • Access to market information and group membership enhances market participation • Larger family size negatively impacts the intensity of sorghum market participation

Optimizing calibration sample selection in infrared spectroscopy

Purpose This study examines the valuation of European-listed real estate companies by assessing the value relevance of accounting-based performance metrics – earnings per share (EPS), return on equity (ROE) and dividend per share (DPS) – as complementary or alternative indicators to the traditionally dominant net asset value (NAV). Design/methodology/approach Using a panel dataset of 102 firms from 2005 to 2024, the study applies three regression models – share price, price change and share return – alongside a difference-in-differences (DiD) approach to capture structural shifts during the 2008–09 financial crisis and the 2021–23 COVID-19 and interest rate hike period. Findings The findings reveal that EPS and DPS are the most consistent and significant predictors of share prices, with DPS showing the highest explanatory power, particularly during the COVID-19 and interest rate hike period. ROE is the strongest predictor of share returns, especially in times of economic stress. Sectoral effects are generally weak, indicating that firm-level financial performance outweighs industry classification in explaining market valuation. Research limitations/implications The study is subject to potential biases in sample selection such as firm size, geographic and market classification, language. The sample is representative of large, liquid and internationally oriented firms, the findings may not generalize to smaller, less liquid or emerging market companies. Practical implications For analysts, integrating accounting metrics alongside NAV enhances valuation accuracy and comparability. For generalist investors, understanding which factors consistently influence prices can inform long-term valuation models, portfolio construction and risk assessment. For practitioners, it provides a robust, multi-metric valuation framework that enhances decision-making by integrating familiar financial indicators with traditional asset-based measure. Originality/value The DiD framework is employed to capture how investor responds to financial metrics shift across crisis and COVID-19 and interest rate hike periods (2008–2009 and 2021–2023). Use of three regression models – share price, share price change and share return – isolates the explanatory power of each financial metric under varying market conditions. Sector-level analysis offers insights into performance heterogeneity. For academic research, it fills a gap in European real estate literature by empirically testing the relevance of accounting metrics in stock valuation, an area previously dominated by NAV-based approaches.

Very long baseline interferometry (VLBI) measurements of the sizes of compact extragalactic radio sources, jetted active galactic nuclei, provide data for probing the angular size--redshift relation, offering a classical cosmological test complementary to other distance--redshift methods. Aiming to update and extend previous studies conducted in the 1990s, we analyse a significantly expanded and improved dataset to reassess the angular size--redshift relation and its potential for constraining cosmological model parameters, focusing on the matter density parameter, Ω_ m , in a flat Λ cold dark matter Universe. This is the first major update of the compact-source angular size test in the past quarter of a century, using a dataset an order of magnitude larger than in previous studies. We performed a Markov chain Monte Carlo analysis on real data and on multiple mock catalogues with varying Gaussian noise levels (10%,,20%,, 50%) to evaluate parameter constraints in the presence of observational scatter. In addition, we conducted a test with 100 randomized catalogues created by shuffling redshifts while preserving other observables to explore the statistical significance of the angular size--redshift dependence. We also explored how astrophysical parameters depend on fixed cosmological models with different m values. The randomization test showed that the posterior distributions from randomized data do not overlap with those from real observations, with significant deviations, confirming that the measured angular size--redshift relation is physically meaningful and not a chance alignment. The astrophysical model parameter that describes the redshift dependence of the source angular size exhibits strong sensitivity and degeneracy with Ω_ m . Simulated mock catalogues indicate that the method is able to constrain Ω_ m if the data scatter is below sim20%, but current real data noise levels are too high for reaching competitive cosmological constraints. Scaling estimates suggest that high-quality data of samples of several thousands to ∼ 100,000 sources, a standardization calibration approach, and/or refining sample selection criteria are needed to fully exploit the potential of the angular size--redshift test with this type of object.

The purpose of this study was to determine the effect of compensation and competence on job satisfaction of employees at the Palembang City Personnel and Human Resources Development Agency. This study employed an associative quantitative method and a questionnaire as the data collection method. The subjects of this study were 82 Civil Servants (PNS) working at the Palembang City Personnel and Human Resources Development Agency. The sample selection technique used saturated sampling, which involves selecting all members of the population as samples, so that the number of respondents equals the population. Data analysis techniques used multiple regression analysis, correlation coefficient analysis, coefficient of determination analysis, partial and simultaneous tests, and data processing using SPSS. The results showed that the compensation variable significantly impacted employee job satisfaction, while the competency variable significantly impacted employee job satisfaction. The simultaneous test showed that compensation and competence significantly impacted employee job satisfaction, with a significance value of 0.000 for each. Simultaneously, these two variables also have a significant effect on job satisfaction with a significance value of 0.000 and a coefficient of determination value of 0.744, which means that 74.4% of the variation in job satisfaction can be explained by compensation and competence.

This paper focuses on Early Roman thin-walled (ThW) pottery from the agora and Fabrika Hill in Nea Paphos, Cyprus. The material was examined macroscopically, and a selection of samples was subjected to elemental analysis (WD-XRF) and thin-section petrography to trace their provenance. The results revealed the presence of local production as well as off-island imports. They also show the low consumption of ThW pottery at the site as well as the dominance of the imports from Asia Minor over local production. These support the interpretation that external cultural influence, although present, had little effect on the islanders, who apparently were conservative in their choice of vessels and practices. The paper thus aims to contribute to a broader scholarly debate on the influence of Roman traditions on local productions and on processes of globalisation in antiquity. Furthermore, it discusses the phenomenon of the production of ThW vessels in the eastern provinces of the Roman Empire.

This study aims to examine the effect of population, financial efficiency and cost of goods and services on the financial condition of local governments in Indonesia in the period 2020 to 2022. This study is a quantitative study. The type of data used is secondary data obtained from BPK and BPS throughout the provinces in Indonesia. The sample selection method in this study uses a purposive sampling method with a total sample of 32 provinces. Measurement of Financial Conditions is based on the Regulation of the Minister of Home Affairs of the Republic of Indonesia Number 19 of 2020. The data analysis used is multiple linear regression analysis, with the help of the SPSS 30 program. The results of the study show that population, financial efficiency and cost of goods and services have a significant positive effect on the financial condition of local governments

This research boldly investigates how inflation, interest rates, and exchange rates influence the stock returns of consumer non-cyclicals firms in the food and beverage sector listed on the Indonesia Stock Exchange from 2021 to 2024. Utilizing a quantitative methodology, the study relies on secondary data sourced from corporate financial disclosures and authoritative macroeconomic reports. The sample selection employed purposive sampling and was rigorously analyzed using multiple linear regression, including evaluations of classical assumptions, t-tests, F-tests, and assessments of the coefficient of determination. The findings reveal that inflation has a positive and significant effect on stock returns, suggesting that moderate inflation may signal a recovery in demand and firms' ability to adapt their pricing. In contrast, interest rates demonstrate a negative and significant impact on stock returns, suggesting that increased capital costs and the appeal of risk-free assets tend to hinder stock performance. The exchange rate positively and significantly affects stock returns, indicating that the market perceived currency fluctuations during the study period as opportunities to enhance competitiveness and industrial adaptation. These results affirm that macroeconomic elements critically shape investor expectations and stock performance in defensive sectors, making them vital considerations for investment strategies and corporate management decisions.

Properties of the hot intracluster and intragroup medium are mostly set by the underlying gravitational potential well, although complex astrophysical processes at play during their buildup may leave a significant imprint. Observational constraints on the degree and scales of such nongravitational processes require well-selected samples of objects and deep observations of their gas content. We aim to study the scaling relation between two global properties of the hot gas, namely its soft-band X-ray luminosity (L_X) and its temperature (T), by studying a sample of low-mass systems associated with precise redshifts, simultaneously accounting for sample selection biases and associated measurement uncertainties. This work takes as input a large catalog of X-ray-selected galaxy clusters (X-CLASS). We performed a thorough revision of the redshifts of sources using deep photometric data from the Legacy Surveys and our own tailored spectroscopic follow-up of 52 low-redshift systems. We devised a spectroscopically complete sample of 155 low-redshift (0.07&lt;z&lt;0.2) systems, and we measured properties of their X-ray emitting gas, with median overline T =1.7 keV and median overline L_X =10^ 43 -1 $. We inferred the relation between L_X and $T in a Bayesian framework. Our sample of groups and clusters with a median total mass of ∼ 6 M_⊙ reveals a relation L_X-T steeper than that predicted by the self-similar model, with a slope of B=3.2 ± 0.1. This result fits well within recent studies that together indicate a trend of an increasing slope with decreasing median halo mass. 10^ 13 This work supports a scenario of a stronger decrease in luminosity with decreasing mass in the group regime than for massive galaxy clusters. This effect is possibly due to strong and sustained feedback expelling gas efficiently from their shallower potential wells. We release the list of updated redshifts (photometric and spectroscopic) for the full X-CLASS sample and the gas properties of the low-redshift sample. The cluster photometric redshift code presented in the paper photXclus is made publicly available .

This study aims to analyze the effect of the liquidity ratio proxied by the Current Ratio (CR), the Profitability ratio proxied by the Earning per Share (EPS), the Solvency ratio proxied by the Debt to Equity Ratio, and the market ratio proxied by Price to Book Value. In financial sector companies listed on the Indonesia Stock Exchange. The research period is five years, namely 2019-2023. The research population includes all financial companies listed on the Indonesia Stock Exchange during the observation period of 2019-2023 totaling 106 companies. The sample selection technique uses a purposive sampling method. Based on the purposive sampling method, 65 financial companies were obtained as research samples. The data analysis method used is Multiple Linear Regression. The results show that the Current Ratio, Earning per Share have a negative and significant effect on stock prices. Debt to Equity Ratio, Price to Book Value have a positive and significant effect on stock prices. The ability of the independent variables, namely Current Ratio, Earnings per Share, Debt to Equity Ratio, and Price to Book Value, to explain the dependent variable, Stock Price, is 0.360 or 36%, while the remaining 64% is influenced by other factors outside the research model.

This study aimed to comparatively evaluate the conventional hepatitis B surface antigen (HBsAg) assay and the next-generation HBsAg NEXT (HBsAgNx) assay in samples with low-level HBsAg positivity and in cases of occult hepatitis B infection (OBI). A total of 497 individuals were included in the study, comprising 300 individuals with low-level HBsAg positivity, 100 OBI cases (64 seropositive and 36 seronegative) and 97 healthy controls. Serum samples were analyzed using the Abbott ARCHITECT HBsAg Qualitative II assay (Abbott Diagnostics, Wiesbaden, Germany) and the Abbott Alinity i HBsAg NEXT assay (Abbott Diagnostics, Wiesbaden, Germany). The presence of HBV DNA was confirmed by real-time polymerase chain reaction (Rt-PCR) using the COBAS AmpliPrep/COBAS TaqMan HBV test v2.0 (Roche Diagnostics, Mannheim, Germany). HBV DNA (Rt-PCR) was accepted as the gold standard reference for diagnostic performance evaluation. To minimize potential bias arising from sample selection, individuals with lowlevel HBsAg positivity and OBI cases were analyzed separately. In the low-level HBsAg-positive group, semi-quantitative S/CO values of the assays were compared, whereas in the OBI group, only the detection rates of HBV DNA-positive cases were evaluated. A total of 17 OBI cases (17%) were identified that were tested negative by the conventional assay but positive by the HBsAgNx assay. Differences between the assays were evaluated using the McNemar test and p< 0.05 was considered statistically significant. Median values obtained with the HBsAgNx assay were significantly higher than those obtained with the conventional assay (p< 0.001). The HBsAgNx assay provides clinically significant contributions particularly in the OBI group, by detecting cases that cannot be identified by conventional assays. These findings indicate that the integration of high-sensitivity HBsAg assays into current HBV diagnostic algorithms would increase case detection and contribute to both transfusion safety and the clinical management of OBI.

Food security in Sahelian countries is increasingly threatened by climate variability, rapid population growth, and dependence on monoculture staples. Indigenous Fruits and Vegetables (IFVs) are underutilized resources with potential to improve nutrition and resilience. This study examines IFV consumption patterns in Burkina Faso and Niger, focusing on nutritional benefits and socio-demographic determinants. Structured surveys were conducted with 458 respondents across both countries. Data were analyzed using descriptive statistics and the Heckman two-stage model to assess consumption and expenditure patterns, while correcting for sample selection bias. IFV consumption was associated with greater dietary diversity among households. Average expenditures were higher in Burkina Faso (3,904 CFA) compared to Niger (1,961 CFA). Gender, education, and religion significantly influenced consumption, while occupation and consumer characteristics affected expenditure levels. Nutritional knowledge was a major driver in Burkina Faso (76.6% of respondents) but less so in Niger (23.4%).Findings highlight IFVs as valuable contributors to nutrition and food security in the Sahel, though disparities in knowledge and socio-demographic factors limit utilization. Strengthening market infrastructure, promoting nutritional awareness, and adopting culturally sensitive, gender-inclusive policies are recommended to increase equitable access and maximize IFV potential.

Facial recognition systems have achieved remarkable success in recent years; however, they continue to suffer from demographic bias, often leading to unequal performance across different population groups. This study presents a novel bias mitigation framework that simultaneously improves both accuracy and fairness, challenging the widely held assumption of a trade-off between these two objectives. The proposed approach integrates uncertainty-based sample selection, human-in-the-loop expert labelling, and continual learning with prior preservation to address bias in a targeted and adaptive manner. The framework focuses on identifying and correcting uncertain predictions, which are frequently associated with underrepresented groups, thereby enhancing performance without degrading accuracy on well-represented populations. Experimental results demonstrate the effectiveness of the proposed method. On the FairFace dataset, accuracy improved from 92.58% to 96.47%, while the Degree of Bias (DoB) was reduced from 3.86 to 1.16, representing a reduction of approximately 70%. Notably, significant performance gains were observed for underrepresented groups, such as an improvement in accuracy for black females from 80.2% to 90.86%, while maintaining strong performance for already well-represented groups. These findings confirm that fairness and accuracy can be improved simultaneously through targeted, data-driven interventions. The proposed framework offers a practical and scalable solution for developing more equitable and reliable facial recognition systems suitable for real-world deployment

Muna Regency is one of the livestock and agricultural centres in Southeast Sulawesi. It has excellent potential as a renewable energy source through by-products of livestock commodity production. This study aims to identify the magnitude of the potential and distribution of biogas raw materials derived from livestock waste in Muna Regency and to evaluate the feasibility of its development with an individual or group approach to livestock farmers. This study uses a survey method, with sample selection carried out by accidental sampling. The analysis results show that the biogas installation project has an NPV value of IDR 24.259,444 for a 5-year development period with an interest rate of 12%. The Net B/C value reaches 2,76, while the gross B/C is 1,17. The IRR value was recorded at 58,53%, which indicates that the return on investment in biogas development can reach 58,51% per year. Based on the results of the analysis, it can be concluded that the utilization of livestock waste as an alternative energy source in Muna Regency is financially feasible and has the potential to provide significant benefits if invested.

Background One of the significant determinants of teaching and learning outcomes in students is teacher efficacy. Clinical teaching plays an educational role in nursing as the connecting link between theory and practice. Nevertheless, the effectiveness of clinical nursing education is usually affected by the abilities, readiness, and the skill of nursing educators. Despite the fact that a number of teacher efficacy scales have been designed across various nations, there is a paucity of situation-specific scales to assess teaching efficacy in clinical nursing education in India. Aim To design a Teaching Efficacy Scale (TES) and a module to measure the clinical nursing instructions provided by teachers in a few nursing colleges of Northern India. Methods Both quantitative and methodological cross-sectional design are applied. The research is undertaken in the nursing colleges of Haryana, Punjab and the Delhi-NCR. Stratified proportionate random sample selection is used to choose a total of 500 B.Sc. Nursing students in 2nd, 3rd and 4th years. Delphi technique is sampled by the experts. The TES is created in a threestep, ten-step process that involves specification of content domain, item pool generation, content validity evaluation, questionnaire development, pilot study, dimensionality evaluation, reliability evaluation, and construct validation. Data analysis is done through SPSS where descriptive and inferential statistics are used. Results The Teaching Efficacy Scale is likely to measure various aspects such as pedagogical learning environment, role of teacher and evaluation components. The psychometric characteristics of the scale will be determined by reliability and validity testing. Conclusion The TES is a universal tool for assessing the effectiveness of clinical teaching and pinpointing levels of weakness in clinical nursing education, thus making a contribution to the enhancement of nursing education and the advancement of clinical competency.