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This study was designed to explore the impact of intrinsic (breed of foal, age of dam, and age of foal at weaning) and extrinsic (season of birth and housing type) factors on the growth and survival of foals in the subtropical conditions of Pakistan. For the growth study, retrospective data analysis of foals (n = 150) born from purebred brood mares of Thoroughbred, Arabs, and Percheron breeds (n 1 , n 2 , and n 3 = 50 each) was made. Six hundred and twenty-four (n = 624) foals born between 2020 to 2022 were observed for the study of foal survival rate. The survival of these foals till the age of one year was considered. To study the growth and development of foals, height, bone, and girth measurements were taken at multiple developmental stages (3, 6, 9, 12, 15, and 18 months of age). Statistical analysis revealed that late-weaned foals demonstrated superior growth metrics compared to early-weaned foals (P = 0.001) and sheltered housing conditions markedly enhanced growth parameters across all breeds and measurement intervals ( P = 0.002). However, no significant effect of season ( P > 0 . 05 ) on the growth measurements across breeds was found. Arab and Thoroughbred breeds demonstrated significant early growth advantages in foals from middle-aged dams, with marked differences in height, bone width, and girth; however, by 15 months, these differences were not statistically significant ( P > 0 . 05 ). In contrast, Percheron foals showed consistent growth regardless of the dam’s age, suggesting breed-specific developmental influences ( P = 0.885). Regarding the effects of extrinsic and intrinsic factors on foal survival, environmental conditions, and maternal age significantly impacted survival rates. Extreme winter conditions were associated with a notably lower survival probability ( P = 0.002), and middle-aged dams exhibited significantly enhanced survival odds ( P = 0.03). However, the influences of housing conditions and weaning age on survival were not statistically significant ( P > 0 . 05 ), indicating these factors do not substantially affect foal survival within the first year. These results underscore the critical roles of weaning age, housing conditions, and age of dams in influencing foal growth and survival, highlighting the importance of tailored management practices in optimizing outcomes for the growth and development of young equines under subtropics.

Development of highly efficient and stable bi-functional electrocatalyst towards both hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) by engaging the earth abundant precursors has attracted much research attention. In this study, a highly efficient, durable and stable amine functionalized MOF based bi-functional electrocatalyst CuO@NH 2 -UiO-66 has been facilely synthesized via in-situ incorporation of pre-synthesized CuO nanoparticles into amine functionalized Zr-MOF NH 2 -UiO-66. It is observed that CuO@NH 2 -UiO-66 exhibits excellent bi-functional electrocatalytic activity towards HER as well as OER and delivers the benchmark of 10 mA cm −2 current density at just 166 and 283 mV overpotential, respectively, which is better than several previously, reported Cu-based, different transition metals and MOF based HER and OER catalysts. It also exhibits lower Tafel slope value 87 and 113 mV dec −1 towards HER and OER, respectively which indicates faster and better charge transfer during catalytic activity. CuO@NH 2 -UiO-66 exhibits significant stability and generates constant current density upto 6000 s during water electrolysis experiments. Furthermore, SEM and P-XRD techniques are used to investigate the stability of working electrode after the electrocatalytic studies and it is observed that CuO@NH 2 -UiO-66 maintains its integrity and chemical structure, after many hours of electrocatalytic activity. This study encourages the development of more earth abundant transition metals and MOFs based electrocatalysts for efficient electrochemical studies. Graphic Abstract

This paper aims to introduce the novel concept of the bipolar picture fuzzy set (BPFS) as a hybrid structure of bipolar fuzzy set (BFS) and picture fuzzy set (PFS). BPFS is a new kind of fuzzy sets to deal with bipolarity (both positive and negative aspects) to each membership degree (belonging-ness), neutral membership (not decided), and non-membership degree (refusal). In this article, some basic properties of bipolar picture fuzzy sets (BPFSs) and their fundamental operations are introduced. The score function, accuracy function and certainty function are suggested to discuss the comparability of bipolar picture fuzzy numbers (BPFNs). Additionally, the concept of new distance measures of BPFSs is presented to discuss geometrical properties of BPFSs. In the context of BPFSs, certain aggregation operators (AOs) named as \"bipolar picture fuzzy weighted geometric (BPFWG) operator, bipolar picture fuzzy ordered weighted geometric (BPFOWG) operator and bipolar picture fuzzy hybrid geometric (BPFHG) operator\" are defined for information aggregation of BPFNs. Based on the proposed AOs, a new multicriteria decision-making (MCDM) approach is proposed to address uncertain real-life situations. Finally, a practical application of proposed methodology is also illustrated to discuss its feasibility and applicability.

A q-rung orthopair fuzzy set (q-ROFS), an extension of the Pythagorean fuzzy set (PFS) and intuitionistic fuzzy set (IFS), is very helpful in representing vague information that occurs in real-world circumstances. The intention of this article is to introduce several aggregation operators in the framework of q-rung orthopair fuzzy numbers (q-ROFNs). The key feature of q-ROFNs is to deal with the situation when the sum of the qth powers of membership and non-membership grades of each alternative in the universe is less than one. The Einstein operators with their operational laws have excellent flexibility. Due to the flexible nature of these Einstein operational laws, we introduce the q-rung orthopair fuzzy Einstein weighted averaging (q-ROFEWA) operator, q-rung orthopair fuzzy Einstein ordered weighted averaging (q-ROFEOWA) operator, q-rung orthopair fuzzy Einstein weighted geometric (q-ROFEWG) operator, and q-rung orthopair fuzzy Einstein ordered weighted geometric (q-ROFEOWG) operator. We discuss certain properties of these operators, inclusive of their ability that the aggregated value of a set of q-ROFNs is a unique q-ROFN. By utilizing the proposed Einstein operators, this article describes a robust multi-criteria decision making (MCDM) technique for solving real-world problems. Finally, a numerical example related to integrated energy modeling and sustainable energy planning is presented to justify the validity and feasibility of the proposed technique.

For environment friendly water splitting, development of highly efficient and stable oxygen evolution reaction (OER) catalyst composed of earth abundant elements is very challenging. Herein, highly efficient OER catalysts TMS@MOF-5 have been prepared by in-situ incorporation of pre-synthesized various transition metal sulfide (TMS = MnS, FeS, CoS, NiS, CuS and ZnS) nanoparticles into MOF-5. Structure, morphology and composition of prepared samples have been analyzed by powder X-ray diffraction, Fourier Transform Infrared Spectroscopy, Raman Spectroscopy, Scanning Electron Microscopy, Energy Dispersive X-ray Spectroscopy, Elemental Mapping and Ultraviolet–Visible Spectroscopy. OER activity of all these samples was determined by coating them on Ni-foam to form TMS@MOF-5/NF as working electrode through cyclic voltammetry. Among all the samples, NiS@MOF-5/NF exhibited excellent stability and OER catalytic activity as it required just 174 mV overpotential to achieve the 10mAcm −2 current density, which is better than many other 3d transition metal based and Ni-based OER catalysts. Present study provides new way to design more efficient Ni-based catalysts for electrochemical water splitting applications. Graphic Abstract

We detected Crimean-Congo hemorrhagic fever virus infections in 4 provinces of Pakistan during 2017-2018. Overall, seroprevalence was 2.7% in humans and 36.2% in domestic livestock. Antibody prevalence in humans was highest in rural areas, where increased contact with animals is likely.

The share of electronic transactions in the global payments continues to increase all around the globe. In the recent years, cryptocurrencies (also known as a system of electronic transaction) have caught significant attention from governments, policymakers, and practitioners worldwide. Cryptocurrencies as an innovative method of exchanges without any physical form boast several potential benefits such as speedy transactions, cross-border usage, low transaction fee, transparency, high security, anonymity, and privacy, and thus are expected to bring huge revolution in the future economic system. This study aims to investigate the adoption factors of Bitcoin, a most known cryptocurrency in China. Based on Technology Acceptance Model, a research framework has been developed to test the proposed hypotheses. The data have been collected via a survey questionnaire from 385 Chinese respondents. The findings show that the perceived ease of use and the perceived usefulness have a positive relationship with the intention to use Bitcoin. The perceived usefulness mediates the relationship between the perceived ease of use and the intention to use Bitcoin. Furthermore, the results reveal that the transaction processing and the perceived ease of use have significant impacts on the perceived usefulness. However, the security and control shows an insignificant effect on the perceived usefulness. This study contributes to the growing literature of Bitcoin and offers valuable information to individual users (payees), fund managers (investors), and companies/businesses (receiving Bitcoin as a payment method). Research implications and limitations are also discussed.

PurposeThis study, based on social exchange theory, aims to explore knowledge hiding behavior in relation to shared goals of individuals working in teams and trust (cognitive-based trust and affective-based trust) as a boundary condition on shared goals and knowledge hiding relationship.Design/methodology/approachA total sample of 270 reliable questionnaires are collected from university students in China. SPSS and AMOS are employed for the data analysis of the proposed model.FindingsFindings of the study have indicated that shared goals are negatively associated with knowledge hiding behavior. Furthermore, trust (cognitive-based trust and affective-based trust) moderates the relationship between shared goals and knowledge hiding behavior.Practical implicationsThis study has provided empirical proof and in-depth understanding and recommendations for supervisors and administrative authorities to form the culture of groups/teams with shared goals to reduce the undesirable individual behaviors.Originality/valueThis study, among the first empirical studies investigating the relationship between shared goals and knowledge hiding behavior, trust as a moderator, enriches the existing academic literature of and provides valuable insight into the research on knowledge hiding and knowledge management.

The linear Diophantine fuzzy set (LDFS) has been proved to be an efficient tool in expressing decision maker (DM) evaluation values in multicriteria decision-making (MCDM) procedure. To more effectively represent DMs’ evaluation information in complicated MCDM process, this paper proposes a MCDM method based on proposed novel aggregation operators (AOs) under linear Diophantine fuzzy set (LDFS). A q-Rung orthopair fuzzy set (q-ROFS), Pythagorean fuzzy set (PFS), and intuitionistic fuzzy set (IFS) are rudimentary concepts in computational intelligence, which have diverse applications in modeling uncertainty and MCDM. Unfortunately, these theories have their own limitations related to the membership and nonmembership grades. The linear Diophantine fuzzy set (LDFS) is a new approach towards uncertainty which has the ability to relax the strict constraints of IFS, PFS, and q–ROFS by considering reference/control parameters. LDFS provides an appropriate way to the decision experts (DEs) in order to deal with vague and uncertain information in a comprehensive way. Under these environments, we introduce several AOs named as linear Diophantine fuzzy Einstein weighted averaging (LDFEWA) operator, linear Diophantine fuzzy Einstein ordered weighted averaging (LDFEOWA) operator, linear Diophantine fuzzy Einstein weighted geometric (LDFEWG) operator, and linear Diophantine fuzzy Einstein ordered weighted geometric (LDFEOWG) operator. We investigate certain characteristics and operational laws with some illustrations. Ultimately, an innovative approach for MCDM under the linear Diophantine fuzzy information is examined by implementing suggested aggregation operators. A useful example related to a country’s national health administration (NHA) to create a fully developed postacute care (PAC) model network for the health recovery of patients suffering from cerebrovascular diseases (CVDs) is exhibited to specify the practicability and efficacy of the intended approach.

This study examines the utilisation of sophisticated predictive methodologies to enhance the energy efficiency and comfort of residential structures. The ASHRAE Global Thermal Comfort Database II was employed to construct and evaluate machine learning models that were designed to predict thermal comfort levels while optimising energy consumption. Air temperature, garment insulation, metabolic rate, air velocity, and humidity were identified as critical comfort determinants. Numerous predictive models were assessed, and XGBoost demonstrated improved performance as a result of hyperparameter optimisation (R2 = 0.9394, MSE = 0.0224). The study underscores the ability of sophisticated algorithms to clarify the complex relationships between environmental factors and occupant comfort. This sophisticated modelling methodology provides a practical approach to enhancing the efficiency of residential energy consumption while simultaneously ensuring the comfort of the occupants, thereby promoting more sustainable and comfortable living environments.