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An investigation was carried out to extract polyphenols from the peel of kinnow (Citrus reticulate L.) by maceration and ultrasound-assisted extraction (UAE) techniques. The antioxidant potential of these polyphenols was evaluated using ferric reducing antioxidant power (FRAP), 2,2-diphenyl-1-picrylhydrazyl (DPPH), and superoxide radical scavenging assays; and their antimicrobial activity was assessed against bacterial strains Staphyloccoccus aureus, Bacillus cereus, and Salmonella typhimurium. The highest extraction yield was obtained through the solvent ethanol at 80% concentration level, whereas UAE was a more efficient technique and yielded comparatively higher polyphenol contents than maceration. Maximum polyphenols were extracted with 80% methanol [32.48 mg gallic acid equivalent (GAE)/g extract] using UAE, whereas minimum phenolics (8.64 mg GAE/g extract) were obtained with 80% ethyl acetate through the maceration technique. Elevated antioxidant activity of kinnow peel extracts was exhibited in three antioxidant assays, where 80% methanolic extracts showed the highest antioxidant activity (27.67±1.11mM/100 g for FRAP) and the highest scavenging activity, 72.83±0.65% and 64.80±0.91% for DPPH and superoxide anion radical assays, respectively. Strong correlations between total polyphenols and antioxidant activity were recorded. Eleven phenolic compounds—including five phenolic acids and six flavonoids—were identified and quantified by high performance liquid chromatography. Ferulic acid and hesperidin were the most abundant compounds whereas caffeic acid was the least abundant phenolic compound in kinnow peel extracts. Maximum inhibition zone was recorded against S. aureus (16.00±0.58 mm) whereas minimum inhibition zone was noted against S. typhimurium (9.00±1.16 mm). It was concluded that kinnow mandarin peels, being a potential source of phenolic compounds with antioxidant and antimicrobial properties, may be used as an ingredient for the preparation of functional foods. [Display omitted]

The purpose of the study is to test the role of green bond financing on energy efficiency investment and economic growth. To achieve the study objective, fuzzy decision-making modeling technique is applied. The results revealed that bank loans are now the main source of financing for energy efficiency projects. Project-based financing might be replaced with Energy Performance Contracts (EPC) warranting energy efficiency investment. Moreover, green banks invest both public and private funds in energy efficiency promoting economic growth. The usage of green bonds for financing environmentally beneficial projects or companies is limitless. Providing for screening energy efficiency investment proposals with small payback hurdle rates might have large opportunity costs. Green bonds can be used to remove the financing barriers for green finance and sustainability tool. On this, study provides policy implications to key stakeholders; if suggested policy suggestions implemented successfully, these would help to enhance scope of green bond financing to uplift energy efficiency financing and green growth successfully.

This article presents a general framework for predicting acoustic wave scattering in ducted systems with expansion chambers and dissipative linings, as commonly encountered in engineering noise-control devices. The method represents the acoustic field in each duct segment through orthogonal modal expansions consistent with the local boundary conditions and enforces continuity conditions at the interfaces to determine the reflected and transmitted wave content. Model verification is carried out using representative benchmark configurations excited by a piston-type source. The results show that acoustic linings substantially impact propagation and resonance behavior through changes in modal wavenumbers and coupling between modes. Parametric comparisons between single- and double-lined expansion chamber designs demonstrate that introducing an additional lined cavity strengthens modal interactions, shifts resonance features, and improves attenuation over a broader frequency range. The proposed formulation is computationally efficient, physically interpretable, and readily adaptable to practical duct geometries and lining specifications, making it suitable for the design and optimization of waveguide-based noise mitigation components in applications such as HVAC networks, exhaust systems, and aero-engine ducting.

Wheat (Triticum aestivum L.) is one of the world’s primary food crops, and timely and accurate yield prediction is essential for ensuring food security. There has been a growing use of remote sensing, climate data, and their combination to estimate yields, but the optimal indices and time window for wheat yield prediction in arid regions remain unclear. This study was conducted to (1) assess the performance of widely recognized remote sensing indices to predict wheat yield at different growth stages, (2) evaluate the predictive accuracy of different yield predictive machine learning models, (3) determine the appropriate growth period for wheat yield prediction in arid regions, and (4) evaluate the impact of climate parameters on model accuracy. The vegetation indices, widely recognized due to their proven effectiveness, used in this study include the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and the Atmospheric Resistance Vegetation Index (ARVI). Moreover, four machine learning models, viz. Decision Trees (DTs), Random Forest (RF), Gradient Boosting (GB), and Bagging Trees (BTs), were evaluated to assess their predictive accuracy for wheat yield in the arid region. The whole wheat growth period was divided into three time windows: tillering to grain filling (December 15–March), stem elongation to grain filling (January 15–March), and heading to grain filling (February–March 15). The model was evaluated and developed in the Google Earth Engine (GEE), combining climate and remote sensing data. The results showed that the RF model with ARVI could accurately predict wheat yield at the grain filling and the maturity stages in arid regions with an R2 > 0.75 and yield error of less than 10%. The grain filling stage was identified as the optimal prediction window for wheat yield in arid regions. While RF with ARVI delivered the best results, GB with EVI showed slightly lower precision but still outperformed other models. It is concluded that combining multisource data and machine learning models is a promising approach for wheat yield prediction in arid regions.

•48.3% children are fully vaccinated in the super-high-risk union councils districts of Pakistan.•Vaccination coverage varies considerably across the super-high-risk union council districts.•Dropout rate between vaccine visits is as higher as 60.5% and as low as 4.9% in the districts.•Full immunization is associated with parental education level. The current polio epidemiology in Pakistan poses a unique challenge for global eradication as the country is affected by ongoing endemic poliovirus transmission. Across the country, 40 union councils (UCs) which serve as core reservoirs for poliovirus with continuous incidences of polio cases are categorized as super-high-risk union councils (SHRUCs). A cross-sectional survey was conducted in 39 SHRUCs using a two-stage stratified cluster sampling technique. 6,976 children aged 12–23 months were covered. A structured questionnaire was used for data collection. Data were analyzed using STATA version 17. Based on both vaccination records and recall, 48.3% of children were fully-, 35.4 % were partially-, and 16.3% were non-vaccinated in the SHRUC districts. A child is considered fully vaccinated when h/she completed vaccination for BCG, OPV0, OPV 1-3, Penta 1-3, PCV 1-3, IPV, and MCV1. Vaccination cards were seen for over half of the children in the SHRUC districts of Khyber Pakhtunkhwa (KP) and the majority of the SHRUC districts in Sindh, except for the SHRUC district of Malir the districts of Balochistan. Results for polio vacancies show that 60.9% of children from the SHRUC districts were vaccinated with at least three doses of OPV and one dose of IPV, while 20.4% were vaccinated with any OPV doses or IPV and 18.7% of children did not receive any polio vaccines. The dropout rate between vaccine visits was higher than the WHO-recommended cutoff point of 10% for all vaccine doses in the SHRUC districts. The likelihood of being fully vaccinated was higher among the children of educated parents. Full vaccination was found significant among the children of any SHRUC districts compared to district Killa Abdullah. Context-specific strategies with more focus on community engagement and targeted mobilization, along with robust monitoring mechanisms, would help address the underlying challenges of under-immunization in the SHRUCs.

The homogenization of the banking segment has made it difficult for banking institutions to practice the quality of services that are needed in order to retain consumers. Thus, these days, finding ways to increase consumer loyalty—especially green loyalty—has become a challenge for the banking industry around the planet. Research has long acknowledged that corporate social responsibility (CSR) is a strategic concern that could help organizations to increase consumer loyalty. However, the impact of CSR practices on green consumer loyalty is rarely addressed in the extant literature. Hence, the present research investigated the impact of CSR on green consumer loyalty with the mediating effect of co-creation in the banking industry of Pakistan. The study also introduced green banking initiatives as a moderator between the mediated relation of CSR and green consumer loyalty, with the intention that such a moderator would strengthen this indirect relationship. The structural equation modeling technique was used for the data analysis. The results confirm that CSR enhances consumer loyalty, and that co-creation partially mediates this relationship. Furthermore, green banking initiatives further strengthen this relation. The results of the current survey could help banking institutions learn how they can develop core strategic considerations based on the integration of CSR co-creation and green banking initiatives.

The purpose of this study is to examine the relationship between renewable energy sources and economic growth of the South Asian Association for regional cooperation (SAARC) countries. This study uses three main renewable energy sources, namely geothermal, hydro, and wind.This study collects data set from SAARC countries from 1995 to 2018 and applies a fixed effect test and panel vector error correction model (PVECM) for data analysis. The overall results show that all three renewable energy sources have a positive significant impact on economic development among SAARC countries’ economies. Moreover, hydropower renewable energy has more effects and influences on economic growth as compared to the other two individual sources of renewable energy.

Background: Defects in methylenetetrahydrofolate dehydrogenase 1-like (MTHFD1L) expression have earlier been examined in only a few human cancers. Objectives: Multi-omics profiling of MTHFD1L as a shared biomarker in distinct subtypes of human cancers. Methods: In the current study, for the multi-omics analysis of MTHFD1L in 24 major subtypes of human cancers, a comprehensive in silico approach was adopted to mine different open access online databases including UALCAN, Kaplan–Meier (KM) plotter, LOGpc, GEPIA, Human Protein Atlas (HPA), Gene Expression across Normal and Tumor tissue (GENT2), MEXPRESS, cBioportal, STRING, DAVID, TIMER, and Comparative Toxicogenomics Database (CTD). Results: We noticed that the expression of MTHFD1L was significantly higher in all the analyzed 24 subtypes of human cancers as compared with the normal controls. Moreover, MTHDF1L overexpression was also found to be significantly associated with the reduced overall survival (OS) duration of Bladder urothelial cancer (BLCA), Head and neck cancer (HNSC), Kidney renal papillary cell carcinoma (KIRP), Lung adenocarcinoma (LUAD), and Uterine corpus endometrial carcinoma (UCEC). This implies that MTHFD1L plays a significant role in the development and progression of these cancers. We further noticed that MTHFD1L was also overexpressed in BLCA, HNSC, KIRP, LUAD, and UCEC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of MTHFD1L-associated genes in five diverse pathways. We also explored few interesting correlations between MTHFD1L expression and its promoter methylation, genetic alterations, CNVs, and between CD8+ T immune cells level. Conclusion: In conclusion, our results elucidated that MTHFD1L can serve as a shared diagnostic and prognostic biomarker in BLCA, HNSC, KIRP, LUAD, and UCEC patients of different clinicopathological features.

The main purpose of this research is to examine the impact of board gender diversity and foreign institutional investors on the corporate social responsibility engagement of Chinese listed companies by considering a sample from the China Stock Market and Accounting Research (CSMAR) database of all non-financial firms listed on the Shanghai stock exchange and the Shenzhen stock exchange during the period from 2008–2015. The CSR is engaged by using the data from the CSMAR database at the firm level, and ranks the CSR disclosures of Chinese companies separately. The recent CSR promotion in China produced a visible increase in attracting female members on the board and members as foreign institutional investors by Chinese listed companies. The findings also showed that the greater the presence of female directors on the board, the stronger the CSR engagement would be. According to critical mass theory and team dynamics, these findings further broaden the accounts that emphasize social networks based on gender. Hence, female members on the board of directors emerged to be significant as a gender mix with extending CSR change. Therefore, our results added a new aspect to the emerging literature on CSR-engagement and gender especially in China. Due to intense political forces and networks in the Chinese listed entities, foreign institutional investors (FIIS) have less incentive to enhance CSR engagement further. Thus, the impact of foreign institutional investors on CSR engagement is as yet unknown, but we improved our knowledge about how the international aspects affect CSR in China. Furthermore, our results are robust, which concern control variables under consideration.

The contemporary literature has largely addressed corporate social responsibility (CSR) at the macro or institutional level, whereas its effect at the micro-level is largely ignored. In addition, contemporary researchers have also ignored the importance of employee pro-environmental behavior to reduce the environmental footprint of small and medium enterprises (SMEs). With this background, the present study attempts to decrease the environmental footprint of the SME sector of China by implementing CSR at the micro-level through the involvement of employees because employees spend a significant amount of their time at workplaces, and hence their environment-related behavior may significantly contribute to improve the natural environment. In this regard, here we examined the impact of the micro-foundation of CSR on SMEs’ environmental performance with mediating effect of employees’ pro-environmental behavior. The data were collected from the different organizations in China. Our sample constitutes a supervisor–subordinate dyad from which we collected 562 filled questionnaires (281 from each). We used the structural equation modeling technique using AMOS software for data analysis, the results show that CSR, directly and indirectly, through employee’s pro-environmental behavior affects the environmental performance of SMEs, and employee pro-environmental behavior partially mediates this relationship. The findings of the present study are helpful for policymakers of the SME sector of China to address widespread environmental issues caused by their business operations.