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In the version of this article initially published, Lena Dolman's second affiliation was given as Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK. The correct second affiliation is Ontario Institute for Cancer Research, Toronto, Ontario, Canada. The error has been corrected in the HTML and PDF versions of the article.

This study focuses on Diabetic Retinopathy (DR), a disease caused by diabetes that affects the retina of the eye and eventually leads to blindness. Diabetes development progresses to retinopathy and must be addressed at an early stage for effective treatment. Currently, DR is classified as Non-Proliferative DR (NPDR) and Proliferative DR (PDR). This study proposes an Enhanced DR (P-EDR) method based on CNN using a high-resolution dataset benchmark of retinal images. Initially, the data were preprocessed by normalization, augmentation, and resizing to improve image quality and feature extraction. Evaluation was based on accuracy, specificity, sensitivity, and AUC-ROC. The proposed CNN-based P-EDR outperformed advanced ML strategies such as Support Vector Machine (SVM), Random Forest (RF), Probabilistic Neural network (PNN), and Gradient Boosting Machine (GBM) that were executed and compared to diagnose and classify DR. The proposed P-EDR extracts features such as a hemorrhage of the NPDR retina image to identify the disease using image processing for classification. P-EDR provides significant features from images in detection and classification, making it a successful model for diagnosing DR with improved accuracy of 93%, sensitivity of 92%, specificity of 94%, and AUC-ROC of 0.97%. These results highlight the potential of a P-EDR-based machine learning model to support ophthalmologists with the early and precise detection of DR, eventually helping with appropriate treatment and prevention of vision loss. [ABSTRACT FROM AUTHOR]

This paper aims to establish some basic properties and generalized unique fixed point (FP) theorems on generalized fuzzy metric spaces (GFM-spaces) by using the rectangular property of the generalized fuzzy metric without the continuity of self-mappings. In support of our results, we present nontrivial illustrative unique FP examples for single-valued contractive type mappings on complete GFM-spaces. This work can be further improved and extend for different types of single-valued mappings on GFM-spaces with supportive trivial and nontrivial illustrative examples. [ABSTRACT FROM AUTHOR]

Background: The use of Polysulfone (PSf) as membrane material for dialysis therapy is becoming more common. However, the PSf membrane can cause the adsorption of blood proteins followed by the adhesion of platelets, destruction of red blood cells, and thrombus formation. One of the biggest challenges in creating membranes for hemodialysis (HD) applications is ensuring biocompatibility. Therefore, to maintain the biocompatibility of PSf membranes, further modifications are necessary. Methods: In this study, the performance and biocompatibility of PSf membranes were improved by the impregnation of TiO2‐hydroxyapatite composite as an additive. The TiO2‐hydroxyapatite composite was first synthesized via sintering at 1200°C, and then a dope solution composed of pristine PSf polymer solution in N‐Methyl‐2‐pyrrolidone solvent (NMP) and different wt% ratios of the synthesized composite were prepared, and resultant membranes were fabricated using a film applicator via a phase inversion scheme using water as a non‐solvent exchange medium. The synthesized composite was characterized using SEM, EDX, and XRD techniques. Results: The FTIR analysis confirmed the weak interaction of PSf polymer with the hydroxyapatite moiety of the composite. The interaction of the synthesized composite within the membrane matrix was evaluated via leaching ratio results. The hydrophilicity, pore profile, and pure water permeation flux rates were also determined. The results of the biocompatibility study showed that membranes based on TiO2‐hydroxyapatite composite had reduced adsorption of BSA protein by 34.41% as well as less than 5% hemolysis ratio. Additionally, the study displayed thrombus formation ranging from 2.08% to 8.69%, respectively. The dialysis results indicated that compared with the original PSf membrane, the TiO2‐hydroxyapatite composite showed high clearance rates for urea (73.81%) and creatinine (72.13%) solutes, respectively. Conclusion: Therefore, blending TiO2‐hydroxyapatite composite in the PSf membrane significantly improved the biocompatibility and removal ability of uremic solutes. [ABSTRACT FROM AUTHOR]

Purpose: Developing on the base of theory of planned behaviour (TPB), the purpose of this paper is to investigate the relationship between perceived social support (SS) from one's social network and entrepreneurial intention (EI). Moreover, mediating effect of other constructs of TPB, i.e., attitude towards entrepreneurship (ATE), subjective norms (SN) and perceived behavioural control (PBC) is also examined in this study. Design/methodology/approach: This study involves a variance-based partial least square-structural equation modelling approach for analysing responses from 381 fresh business graduates. Findings: Findings of this study revealed that SS positively influences EI and also that this relationship is fully mediated by ATE, SN and PBC. Research limitations/implications: Due to limited resources, cross cultural comparison and multi-group analysis were not performed, which are considered as a limitation of this study. Practical implications: It is expected that the findings of this study can help policy makers, researchers and academicians in better understanding of critical role of SS for understanding the intentions of nascent entrepreneurs. Social implications: Further, findings of this study suggest that academicians and policy makers need to take heed towards relatively less explored phenomenon of SS to enhance the attractiveness of entrepreneurial career in fresh business graduates. Originality/value: This study has proposed a model for assessing impact of SS on EI. By doing so, this study extends TPB in the context of EI. Moreover, findings of this study are a unique step forward, and offer a new insight towards better understanding of the determinants of EI in fresh business graduates.

The present study was conducted to check the growth performance and body composition of Labeo rohita fed with two different levels of fish meal replacement with bone meal. The trial was carried out in glass aquaria for a period of 8 weeks. Ten (n=10) fingerlings of L. rohita were reared per aquaria having capacity of 80-L water. Feed having 100% fish meal was considered as T1 and diets having 30% and 60% replacement of fish meal by bone meal as main protein source was considered as T2 and T3, respectively. Results showed that replacement of 30% and 60% fish meal with bone meal has better effect on growth of L. rohita analysed whole body composition revealed that lower values of total fat there was observed no significant differences in carbohydrates and moisture content of fish was observed. Bone meal could replace fish meal as an acceptable protein source to promote growth of L. rohita without any negative effects on growth and body composition. [ABSTRACT FROM AUTHOR]

Ticks (Acari: ixodid) are notorious blood sucking ecto-parasites of wide range of animals which serve as vector of different types of pathogens like viruses, bacteria, rickettsia and protozoa and cause mortality in humans and animals. This study was focused on morphological and molecular identification of ixodid ticks, using morphological keys and an internal transcribed spacer (ITS-2) Deoxyribonucleic acid (DNA). Moreover, the presence of Babesia and Theileria species was also investigated in ticks using 18S rRNA gene. Identification of ticks collected from 384 cattle and 384 buffaloes screened revealed three tick genera and six tick species: Rhipicephalus microplus, Rhipicephalus decoloratus, Rhipicephalus annulatus, Hyalomma anatolicum anatolicum, Hyalomma anatolicum excavatum and Haemaphysalis punctata. Of those four species were confirmed on morphological basis, two ticks species Rhipicephalus microplus and Hyalomma anatolicum anatolicum whose morphological feature were overlapping with other identified species, were confirmed through molecular tools amplifying ITS-2 gene. Ticks DNA were then examined by PCR employing a genetic marker that target (18S rRNA gene), for the presence of Babesia and Theileria species in identified ticks. The most common pathogen species observed in ticks was Theileria annulata. This study exposed different hard tick species are prevalent in the study area and these ticks are playing major role in transmission of protozoa (Theileria annulata). On the basis of finding of present study an area-wise control strategy for ticks and ticks borne protozoan species have been suggestive. [ABSTRACT FROM AUTHOR]

This study examined how environmental greenwashing moderates the link between "green supply chain management" (GSCM) practices and green brand association. Using the natural resource-based (NRBV), this research creates a model to better understand GSCMP and GBA fashion brand in Pakistan. This study included fashion brand customers, selected using nonprobability purposive sampling. The cross-sectional study included 15 fashion brand mall customers from six of Pakistan's largest cities: Bahawalpur, Islamabad, Multan, Faisalabad, Karachi, and Lahore. The study used 446 responses. Statistics were done using SPSS and "SmartPLS partial least square, structural equation modelling" (PLS-SEM). A structural model was developed to test hypotheses. The proposed GSCMPs correlated to GBA. GW's negative moderation affects between GBP and GBA significantly. GBD and GBA are negatively moderated by GW. Managers and policymakers should heed current studies to achieve green brand association. First empirical study to use NRBV framework with GW as a moderator. [ABSTRACT FROM AUTHOR]

This research focuses on specific models of health and illness, explored by many researchers across the world. The sequential variations and critic of each model is summed up by researcher and the relevant theoretical orientations of beta thalassemia major have been tried to integrate. Beta thalassemia major is a common genetic disorder, due to abnormalities in human globin (alpha or beta). The highest prevalence rate of disease has been seen in Saudi Arabia, Jordon, India, Bangladesh and Pakistan, due to repeated cousin marriages, strong beliefs of cultural and traditional practices and lack of knowledge for the prevention and management of beta thalassemia major. The focus of epidemiologists remained on genetic causes and ignored the social, cultural, religious and psychological factors which preponderate over biological aspects of health. The academician and health experts lacked to focus the theoretical orientations of beta thalassemia major, this paper elucidates the models of health and illness and provides and logical theoretical itinerary for beta thalassemia major.

Societal determinants of health are of recognized importance for understanding the causal association of society and health of an individual. Iron deficiency anemia (IDA) is a challenging public health problem across the globe instigating from a broader sociocultural background. It is more prevalent among pregnant women, children under the age of five years, and adolescent girls. Adolescent girls are vulnerable to develop IDA because of additional nutritional demand of the body needed for growth spurt, blood loss due to onset of menarche, malnourishment, and poor dietary iron intake. In this study, we explore the societal determinants of anemia among adolescent girls in Azad Jammu and Kashmir (AJK), Pakistan. A cross-sectional study was conducted in the Muzaffarabad division of AJK on randomly selected 626 adolescent girls. The data were collected using a pretested self-administered interview schedule comprising mainly closed-ended questions with a few open-ended questions. Descriptive statistics was computed for describing the data, and bivariate regression and logistic regression were used to determine the association of anemia with its societal determinants. Multiple linear regression is used to determine the relationship of different determinants (independent variables) with the hemoglobin level (dependent variable) of the respondents. The prevalence of anemia among adolescent girls is 47.9%, of which 47.7% have mild anemia, 51.7% have moderate anemia, and 5.7% have severe anemia, which reveals that anemia is a severe public health problem among adolescent girls in the study area. The findings aver that anemia occurrence was significantly associated with the respondent’s and her parental education, economic well-being, prevalence of communicable diseases, menstrual disorder, exercise habits, meals regularity, and type of sewerage system.

Agricultural products are a fundamental necessity for every country. When plants are afflicted with diseases, it influences the country's agricultural productivity, as well as its economic resources. Diseases are an important problem for potato plants, causing potatoes to be rejected and resulting in financial losses. Viruses and diseases in potatoes and field plants can be missed with the naked eye, particularly in the early stages of cultivation. The use of modern instruments and technology at an early stage of disease diagnosis dramatically reduces costs. This study used deep learning techniques to categorize and detect plant leaf diseases in photos taken from the Plant Village dataset. The dataset consists of 20,636 photos of plants and their diseases. This study focused on potato plants because it is the most common type of plant in the world, particularly in Pakistan. Convolutional Neural Network (CNN) methods were used to categorize plant leaf diseases into 15 classes, including three classes for healthy leaves and classes for several plant diseases such as fungal and bacterial infections, among others. The proposed models were trained and tested, achieving 98.29 and 98.029% accuracy, respectively. [ABSTRACT FROM AUTHOR]

Introduction: The Trifecta bioprosthetic valve has been commonly used for surgical aortic valve replacement (SAVR). Multiple studies have been done to define the rate of structural valve degeneration (SVD) and failure (SVF), but the outcomes are still debatable. Therefore, we aim to conduct this single-center study to estimate the rate and predictors of SVD/SVF. Methodology: This retrospective observational cohort single-center study was conducted between 2014 and 2019 among Trifecta SAVR patients. Data were patient's characteristics collected from electronic medical records at baseline and follow-up (3-5 years). Statistical analysis was performed with a significance level of P = 0.05. Results: A total of 271 eligible patients were identified. Most of our sample were males (57.9%), with a mean age of 71.1 ± 10.6 years. The mean baseline preoperative ejection fraction (EF) was 53.0%, with no change (P = 0.88) in the immediate postoperative EF (53.6%). A most recent follow-up EF revealed a significant increase of EF (55.2%), P = 0.01. Furthermore, there was a significant increase from peak velocity to PVMRE (mean difference [MD] ± standard error of mean (SEM) [0.15 ± 0.04], P < 0.01), an increase in pressure gradient (PGIPE) to PGMRE (MD ± SEM [1.70 ± 0.49], P < 0.01), and a decrease in Doppler velocity index (DVIIPE) to DVIMRE (MD ± SEM [-0.037 ± 0.01], P = 0.01). Regarding the SVF rate, 13 (4.8%) patients had failed valves requiring replacement throughout the study period. Conclusions: Over a 5-year follow-up period, 4.8% had SVF with an SVD of 23.2%, with the majority of SVD not being clinically significant except in six patients. These results corroborate with a previously published study suggesting a bad clinical outcome of Trifecta valve placement. [ABSTRACT FROM AUTHOR]

Decentralized energy generation systems based on renewable sources have significant potential to assist in the sustainable development of developing countries. The small-scale integration of hybrid renewable energy systems in off-grid communities has not been thoroughly researched. The primary objective is to develop a preliminary design for a PV/biogas hybrid system that can meet the energy needs of an off-grid community center. A survey was conducted to calculate the energy demands of an off-grid community center and a hybrid renewable system has been designed to supply the electricity. The optimum designed system is evaluated by the PVSYST simulation software and SuperPro Designer software. The annual production of the PV system is 34428 kWh/year, specific production is 1118 kWh/kWp/year, and the performance ratio is 81.72%. All the factors that contribute to energy loss are considered in designing a PV system. The average operating efficiency of the inverter is 92.6%, and global inverter losses are 2752.4 kWh. The biogas simulation findings show an adequate match with the composition of conventional biogas and contains 89.64% methane and 5.99% carbon dioxide content. Two sensitivity analyses of biogas based on hydraulic retention time and moisture content have been performed. Measurements readings of hourly data are used to analyse the performance of PV, biogas system as well as the hybrid system performance. At day time, the maximum power generation of the hybrid PV/Biogas and the maximum load demand of the community at that time are 25.2 kW and 24.31 kW, respectively. At night time, the maximum power generation of the hybrid system and the maximum load demand are 9 kW and 8.3 kW, respectively. The power factor (PF) of the system fluctuates between 0.92 and 0.98 and the frequency of the system is constant at 50 HZ. [ABSTRACT FROM AUTHOR]