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Abstract Background: Globally, over a million people commit suicide every year. Although suicide rates are more in high-income countries, many countries do not report suicide cases regularly to the World Health Organization (WHO). Therefore, this study aimed to determine the factor associated with suicide and self-harm in Pakistan. Method: This cross-sectional study was conducted at Peoples Medical College Hospital (PMCH) in Shaheed Benazirabad, Sindh, Pakistan, from July to December 2019. A total of 131 cases of suicide/self-harm were included using a convenience sampling technique. Data were collected on a predesigned questionnaire consisting of 14 close-ended questions. A chi-square test was used to determine the association between different categorical variables. Results: The majority of the subjects were males (53.4%), young adults aged between 16 and 30 years (69.5%), single (51.9%), and uneducated (57.3%). More than half (51.9%) of the subjects who attempted suicide or self-harm were unemployed. There was a significant association between education level ( χ 2 =13.149, P = 0.001) and age groups ( χ 2 = 15.554, P = 0.001) with health outcomes (suicide or self-harm) only. Moreover, gender ( χ 2 = 20.776, P = 0.004), marital status ( χ 2 = 69.047, P < 0.001), level of education ( χ 2 = 63.144, P < 0.001), age groups ( χ 2 = 69.848, P < 0.001), and employment status ( χ 2 = 28.677, P = 0.012) were also associated with the reasons of suicide and self-harm. Conclusion: Our study concluded that mostly single, unemployed males with low literacy and with marital and family issues are determined as factors associated with a high risk of self-harm and suicide.

Abstract In recent days researchers have tried to handle the maximum information and use those techniques and methods in which there is no chance of data loss or loss of information is minimum. The structure like fuzzy set and complex fussy set cannot discuss the upper and lower approximations. Moreover, we can observe that a fuzzy rough set cannot discuss the second dimension and in this case, there is a chance of data loss. To cover all these issues in previous ideas, the notion of a complex fuzzy rough set in Cartesian form is the demand of the day because this structure can discuss the second dimension as well as upper and lower approximations. For this purpose, in this manuscript, we have developed the theory of complex fuzzy relation and complex fuzzy rough set in Cartesian form. Moreover, we have initiated the fundamental laws for complex fuzzy rough numbers based on Frank t-norm and t-conorm. The fundamental tools that can convert the overall input into a single output are called aggregation operators (AOs). So based on the characteristics of AOs, we have defined the notion of complex fuzzy rough Frank average and complex fuzzy rough Frank geometric AOs. The utilization of the developed theory is necessary to show the importance and validity of the delivered approach. So based on developed notions, we have defined an algorithm for this purpose along with an illustrative example. We have utilized the introduced structure for the classification of AI tools for civil engineering. Moreover, the comparative analysis of the delivered approach shows the advancement of the introduced structure as compared to existing notions.

Abstract Toxic heavy metal lead enters in the environment due to industrial and anthropogenic activity threatens ecosystems and public health. Natural garlic extract (GE) exhibits antioxidant properties and various applications against several ailments. Therefore, this study scrutinized the protective effects of tocopherol polyethylene glycol succinate-coated garlic selenium (TPGS-GSNP) against lead acetate (LA) toxicity in rabbits. Sixty-four mature male rabbits were involved and divided into 8 equal groups. They received distilled water (negative control; T1), 30 mg/kg bw of LA (positive control; T2), 800 mg/kg bw of GE (T3), GE + LA (T4), 1 mg/kg bw of TPGS-Selenium (T5), TPGS-S + LA (T6), 1 mg/kg bw of TPGS-GSNP (T7), and TPGS-GSNP + LA (T8). Consequently, treatments were administered three times a week for 12 weeks. Following the treatment period, serum oxidant-antioxidant, protein, and lipid profiles, liver and kidney function, histopathological findings of the adrenal, liver, and kidneys, femur bone marrow chromosomal aberrations, and mitotic activity were collected and analysed. LA exposure showed significant reductions in antioxidant levels, organ weights, and mitotic activity while increasing oxidative stress, corticosteroid levels, and chromosomal aberrations. Importantly, TPGS-GSNP administration significantly improved these markers compared to the LA group. In addition, histological analysis revealed structural improvements of the studied organs in the TPGS-GSNP group compared to the LA group, which displayed high cellular necrotic and degenerative changes. In conclusion, synthetic TPGS-GSNP demonstrated higher protective efficacy against LA-induced toxicity compared to natural GE or selenium alone. However, more future studies could be conducted to explore the potential of TPGS-GSNP as an anticancer or immunomodulatory agent.

In recent scenarios, we cannot ignore the importance of artificial intelligence in many fields like medical diagnosis, computer science, economics and agriculture, etc. In 1960, Schweizer and Sklar developed the concept of Schweizer-Sklar (SS) t-norm and t-conorm by incorporating a parameter which is more flexible and helpful in handling complex and unclear data. If we put parameter then the information of the Hamacher and Lukasiewicz t-norms is simply derived. The primary goal of this study is to develop the fundamental Schweizer-Sklar operational laws for bipolar fuzzy numbers. Additionally, we have defined the notion of bipolar fuzzy Schweizer-Sklar power average and bipolar fuzzy Schweizer-Sklar power geometric aggregation operators. Moreover, we have elaborated on the basic characteristics of these developed notions. We have initiated the algorithm to demonstrate the actual use of this work in artificial neural networking. We have also compared our work with some prevailing theories.

Background: Herbal medications, due to their various biologically active components and less toxic profile, have been popular amongst researchers since decades. One good example is Linum usitatissimum (Lu) commonly known as Flaxseeds. The aim of present study was to assess the anti hyperglycemic and anti dyslipidemic activities of ethanolic extract of flax seeds (Linum usitatissimum) in streptozotocin induced diabetic rat model. Methods: The ethanolic extract of flax seeds (Linum usitatissimum) at a dose of 200 mg/kg and 400mg/kg were given to the streptozotocin-induced diabetic rats for the period of 28 days. FBS, insulin, HbA1c, lipid profile and serum amylase were evaluated and were compared with positive and negative controls and standard drugs like Glimepiride 0.1 mg/kg b.w., Metformin 10mg/kg b.w. and Rosuvastatin 10mg/kg/day b.w. Results: Both doses of flax seeds 200 mg/kg and 400 mg/kg (Linum usitatissimum) extracts demonstrated significant (p

Child marriage is an internationally recognised human rights issue that has been extensively studied by various Non-Governmental Organisations and the United Nations. In response to this problem, many countries have implemented social policies aimed at addressing child marriage and several international treaties are dedicated to combatting it. This study focuses on examining the factors contributing to child marriage within refugee populations. The research methodology involved conducting in-depth interviews with ten young wives aged between 16 and 22, facilitating focus group discussions with their husbands and parents residing in Domiz Camps 1 and 2 in Kurdistan, as well as interviewing key informants who work in child protection services and social policy development. Thematic analysis was employed to identify prominent themes and subthemes based on the perspectives of participants. The research revealed that child marriage is driven by factors such as the need for safety, preservation of family honour, and economic challenges. Similar safety concerns were observed among Syrian refugees in this study, as well as in previous studies conducted on Jordanian refugees and Rohingya refugees in Bangladesh. This study takes a comprehensive approach by considering perspectives from young wives, their parents, husbands, and key informants when examining factors related to child marriage. Ultimately, the findings of this study will contribute to a deeper understanding of refugee issues and efforts towards protecting children’s rights within the refugee context.

All modifications to regular fuzzy sets with three-dimensional membership functions are intended to provide a more detailed definition of decision-makers and experts’ opinions. The Spherical Fuzzy Soft Set (SFSS) is the new extension of the Picture Fuzzy Soft Set (PFSS) that can cover more advanced information than PFSS. Moreover, human opinion can never be restricted to two-dimensional membership functions like yes or no, but it can be yes, abstain, no, and refusal. It means that all notions like Intuitionistic Fuzzy Soft Sets (IFSS) and Pythagorean Fuzzy Soft Sets (PyFSS) lack the property of considering three-dimensional membership functions. So, the SFSS is a more general apparatus and free from all those complexities faced by IFSS and PyFSS. The major contribution of this study is the definition of the basic operational laws for SFSSs. Aggregation Operators (AOs) are basic mathematical tools to aggregate the overall information into a single value. Consequently, we aim to introduce some new SFS geometric AOs. Additionally, the fundamental characteristics of these well-established operators are thoroughly examined and an algorithm is introduced along with numerical examples to deal with Multi-criteria Decision Making (MCDM) problems that show the advantages of the established method. In the end, a comparative analysis is carried out to reveal the superiority and authenticity of the introduced method.

The practice of adding new features or changing current features to enhance a machine-learning model’s performance is known as feature engineering. It increases the prediction potential of machine learning and aids in revealing the data’s underlying patterns. Different soft structures can be utilized to reach a decision where we have to decide the best alternative among the given choices. The structure of a ring is an algebraic structure that plays a vital role due to its characteristics. Moreover, a soft set is a valuable structure that can consider the parameterization tool. Also T-bipolar soft set is a parameterization tool that can consider the positive and negative aspects. Based on these observations we have developed the theory of lattice-ordered T-bipolar soft rings (LOTBSRs) and anti-lattice-ordered T-bipolar soft rings (ALOTBSRs). Moreover, we have defined the notions of OR product, extended union, and restricted union for LOTBSRs. Furthermore, the ideas of AND product, restricted intersection, and extended intersection are defined. To analyze the whole theory, we have proved some results related to these ideas. To construct the applications part of these developed notions, we have defined an algorithm and utilized these ideas in the decision-making scenarios for the classification of feature engineering techniques. In the end, we have some conclusion remarks.

Two-dimensional approach is very important in real-life scenarios. To address situations where two-dimensional information is involved, the theory of complex fuzzy set (CFS) is a reliable and applicable structure. The CFS gives a more expressive structure for modeling uncertainty and imprecision where 2nd dimension is included. On the other hand, the notion of rough set is interpreted by two components that is upper and lower approximation, that provide more space in decision-making dilemmas. To get the benefits and advantages of the CFS and rough set, in this manuscript, we interpret the theory of a complex fuzzy rough set (CFRS) by employing complex fuzzy relations. We also devise the operations such as addition, product, scalar product, scalar power, union, intersection and complement for the theory of CFRS. Further, in the structure of CFRS, we devise the aggregation operators that are complex fuzzy rough weighted averaging, complex fuzzy rough ordered weighted averaging, complex fuzzy rough weighted geometric and complex fuzzy rough ordered weighted geometric. We initiate a technique identified as “weighted aggregates sum product assessment” (WAPAS) by employing devised aggregation operators in the environment of CFRS. After that, to reveal the applicability of the anticipated theory and WASPAS technique, we identify and order digital marketing for business growth. Finally, to demonstrate the superiority of the introduced concept, we compare our work to some already-existing ideas.

The release of harmful materials into the environment is called pollution and the harmful materials are called pollutants. There are four basic categories of pollution: land, water, noise, and air pollution. All forms of pollution often have severe consequences on human health as well as the environment and wildlife. There are certain decision-making scenarios like the phenomenon of voting where we have to utilize the third grade called abstinence grade along with membership grade and non-membership grade. Many remarkable fuzzy structures like the intuitionistic fuzzy set, Pythagorean fuzzy set and q-rung orthopair fuzzy set can never discuss abstinence grades that show their flaws. Moreover, we can observe that the parametrization tool is a remarkable instrument used in soft set theory and all above-mentioned structures fail to cover the parametrization as well. Moreover, Einstein operations comprise Einstein product and Einstein sum, which serve as excellent substitutes for algebraic product and algebraic sum. So keeping in view the characteristics of the parametrization tool, the more advanced structure of the picture fuzzy soft set and Einstein operational rules, in this article, we have established Einstein operational laws for picture fuzzy soft numbers. Moreover, we have elaborated the basic notion of Einstein-weighted average operators and Einstein-weighted geometric aggregation operators. Furthermore, we have discussed the basic properties of these introduced notions. Moreover, we have discussed the algorithm for the application of these aggregation operators in the identification of types of pollution that mostly affect the environment. We have provided a comparison of these introduced works for the superiority of these introduced conceptions.

Background: In medical research and survival analysis, it is common for an individual or item's failure to be attributable to multiple causes, also known as competing risks. This article focuses on examining the competing risks model as the data increasingly becomes type II censored and randomly removed. The model assumes that the causes of failure are independent and that the lifetimes of individuals are described by the Cox model. At each failure time, the number of items or people removed follows a binomial distribution. The article derives estimators for the indefinite parameters in the model. The study presents a set of detailed data and includes a simulation study that also illustrates the results. Methods: Different reasons, frequently known as competing risks, are frequently embroiled in an individual's or an item's failure in medical research survival analysis. The competing risks shown under sort II dynamic censoring with random removals are the subject of this research. We get the maximum likelihood and inexact most extreme probability estimators of the obscure parameters. The asymptotic distribution of the maximum probability estimators is utilized to decide the CIs. Then, Monte Carlo simulations were applied to demonstrate the approach. The analyses were performed utilizing R 4.0.4 software. Results: For stroke, systolic blood pressure (SBP) and hypertension status are the only significant variables. In contrast, gender, body mass index (BMI), smoking status, the logarithm of urinary albumin and creatinine ratio, and diabetes status are significant variables for coronary heart disease (CHD) and other cardiovascular diseases (CVDs). The results suggest that significant risk factors differ for different types of CVD events. Conclusion: The outcomes of the simulation study indicate that progressively right-censored type II sampling designs outperformed the usual censored type II sampling designs. Therefore, the estimated parameters on the defined pattern setting are recommended. They can be used in many practical situations when competing risks occur, and progressive censoring could be considered.

Aczel-Alsina t-norm and t-conorm are great substitutes for sum and product and recently various scholars developed notions based on the Aczel-Alsina t-norm and t-conorm. The theory of bipolar complex fuzzy set that deals with ambiguous and complex data that contains positive and negative aspects along with a second dimension. So, based on Aczel-Alsina operational laws and the dominant structure of the bipolar complex fuzzy set, we develop the notion of bipolar complex fuzzy Aczel-Alsina weighted geometric, bipolar complex fuzzy Aczel Alsina ordered weighted geometric and bipolar complex fuzzy Aczel Alsina hybrid geometric operators. Moreover, multi-attribute border approximation area comparison technique is a valuable technique that can cover many decision-making situations and have dominant results. So, based on bipolar complex fuzzy Aczel-Alsina aggregation operators, we demonstrate the notion of a multi-attribute border approximation area comparison approach for coping with bipolar complex fuzzy information. After that, we take a numerical example by taking artificial data for various types of operating systems and determining the finest operating system for a computer. In the end, we compare the deduced multi-attribute border approximation area comparison approach and deduced aggregation operators with numerous prevailing works.

The problem of finding the cyclic decomposition (c.d.) for the groups ), where prime upper than 9 is determined in this work. Also, we compute the Artin characters (A.ch.) and Artin indicator (A.ind.) for the same groups, we obtain that after computing the conjugacy classes, cyclic subgroups, the ordinary character table (o.ch.ta.) and the rational valued character table for each group.

In this paper, we apply a mathematical model based on cooperative game theory to model cooperation among producers in waste management. Then, we use the Shapely value as a solution concept in a cooperative game to evaluate the cooperation existing among producers, in order to show the potential cost to the waste producers in the case of cooperation and reduce the overall costs of processing non-recyclable waste during the cooperation. Thus, this study concludes that all producers divide sanitary landfills or incineration of non-recyclable waste, meaning that for each producer who earns more, there will be a greater contribution to the disposal or treatment of non-recyclable waste.

The study aimed to discover the role of vitamin D in improving the respiratory function in sickle cell disease patients. In this prospective study, 188 adults were enrolled, drawn from the out-patients unit of Thalassemia Cente The collected data were categorized into three groups: group 1 included the data of 100 healthy individuals of age range of 18-50 years as control; group 2 included the data of 88 (40 males and 48 females) sickle cell disease patients in steady state before supplementation of vitamin D; group 3 represented the data of the same 88 sickle cell disease patients as measured and recorded after 6 weeks of vitamin D supplementation. Laboratory measurements including pulmonary function tests and hematological parameters, while vitamin D levels were estimated for all groups to compare the data before and after supplementation of vitamin We found significant differences in the pulmonary function tests when comparing groups. Mean value of FEV1 revealed significant differences between group 1 and 2 (p >0.05), while vitamin D supplement created a significant difference between group 2 and 3 (p >0.05). The improvement in FEV1 did not reach to that of healthy (group 1), as referred by the significant variation between group 1 and group 3 (p>0.05). The same findings were indicative within most pulmonary function tests, and the percentages of combined cases (restrictive and obstructive) were also deceased in group 3. Conclusion: supplement of vitamin D in SCD patients could result in relative improvement in lung function.

The game theory has been applied to all situations where agents’ (people or companies) actions are utility-maximizing, and the collaborative offshoot of game theory has proven to be a robust tool for creating effective collaboration strategies in a broad range of applications. In this paper first, we employ the Banzhaf values to show the potential cost to waste producers in the case of a cooperation and to reduce the overall costs of processing non-recyclable waste during cooperation between producers. Secondly, we propose an application of the methodology to study a case for five waste producers' waste management in the Al-Mahmudiya factory with the aim of displaying the potential cost to waste producers in case of cooperation. Lastly, the obtained results of the proposed framework will strongly help professionals to formulate and improve well-organized strategies for the waste management system of the future.

The focus of the interdisciplinary and scientific discipline of robotics is to design, maintain and use mechanical robotics. There exist many issues faced by the robotic industry but there are some factors that can cover these complexities effectively. Handling vague and imprecise data is a difficult task nowadays. So there is a need to define such kind of effective and valuable tool that can handle complex and vague data more dominantly. The evaluation based on distance from average solution (EDAS) method is a very useful tool that can handle complex data more effectively. The best alternative can be chosen based on distance from the average solution. The EDAS method is relatively simple to use and provide a quick evaluation of alternative based on multiple criteria. Yager t-norm and t-conorm are two fuzzy logic operators proposed by Yager. So based on the importance of Yager t-norm and t-conorm, initially, in this article, we have proposed the basic operative laws for intuitionistic fuzzy rough numbers. Based on these developed operational laws, we have developed some new intuitionistic fuzzy rough aggregation operators called intuitionistic fuzzy rough Yager average (weighted, ordered weighted, hybrid) aggregation operators and intuitionistic fuzzy rough Yager geometric (weighted, ordered weighted, hybrid) aggregation operators. Moreover, we have proposed the EDAS technique based on intuitionistic fuzzy rough Yager aggregation operators and used these notions for the selection of suitable factors that play a vital role in the robotic industry. Also, to show the effective use of these introduced notions, we have proposed an algorithm for the EDAS method based on intuitionistic fuzzy rough Yager aggregation operators along with a descriptive example. To show the superiority of the introduced work we have developed a comparative analysis.

Abstract Energy storage is a way of storing energy to reduce imbalances between demand and energy production. The ability to store electricity and use it later is one of the keys to reaching large quantities of renewable energy on the grid. There are several methods to store energy such as mechanical, electrical, chemical, electrochemical, and thermal energy. Regarding their operation, storage, and cost, the choice of these energy storage techniques appears to be interesting. This issue becomes very serious when there involves uncertainty. To consider this kind of uncertain information, a picture fuzzy soft set is found to be a more appropriate parameterization tool to deal with imprecise data. Based on the advanced structure of picture fuzzy soft set, here in this article, firstly, we have developed the notions of basic operational laws for picture fuzzy soft numbers. Then based on these developed operational laws, we have established the notions of picture fuzzy soft power average $$\left({\mathrm{PFS}}_{\mathrm{ft}}\mathrm{PA}\right)$$ PFS ft PA , weighted picture fuzzy soft power average $$\left({\mathrm{WPFS}}_{\mathrm{ft}}\mathrm{PA}\right)$$ WPFS ft PA and ordered weighted picture fuzzy soft power average $$\left({\mathrm{OWPFS}}_{\mathrm{ft}}\mathrm{PA}\right)$$ OWPFS ft PA aggregation operators. Moreover, we have introduced the notions for picture fuzzy soft power geometric $$\left({\mathrm{PFS}}_{\mathrm{ft}}\mathrm{PG}\right)$$ PFS ft PG , weighted picture fuzzy soft power geometric $$\left({\mathrm{WPFS}}_{\mathrm{ft}}\mathrm{PG}\right)$$ WPFS ft PG and ordered weighted picture fuzzy soft power geometric $$\left({\mathrm{OWPFS}}_{\mathrm{ft}}\mathrm{PG}\right)$$ OWPFS ft PG aggregation operators. Furthermore, we have established the application of picture fuzzy soft power aggregation operators for the selection of thermal energy storage techniques. For this, we have developed a decision-making approach along with an explanatory example to show the effective use of the developed theory. Furthermore, a comparative analysis of the introduced work shows the advancement of developed notions.

In recent days, due to the complexities of different diseases of similar types, it becomes very difficult to diagnose an accurate type of disease, and so medical diagnosis becomes a difficult task for the experts working in health departments. Many researchers try to develop new methods and techniques to over the difficulties that come across in the way of medical diagnosis. In this paper, we try to develop some novel techniques that will help experts to diagnose diseases accurately. Based on a more advanced structure of intuitionistic fuzzy rough sets, in this article, we establish confidence-level intuitionistic fuzzy average/geometric aggregation operators to incorporate the familiarity degree of experts with evaluated objects for an initial assessment while intuitionistic fuzzy rough average/geometric aggregation operators cannot do so. Moreover, we have given some basic properties of the initiated operators. To show the effective use of these operators we have proposed an algorithm with an illustrative example. Furthermore, based on the intuitionistic fuzzy rough model, we have also established a medical diagnosis model to incorporate the difficulty that occurs in the diagnosis of disease. Furthermore, a comparative analysis demonstrates the efficiency of our proposed methods.

In the context of decision support systems, bi-capacities were introduced as an extension of classical capacities. Many bipolar fuzzy integrals related to the bi-capacities have been presented in recent years. One of these integrals is the Sugeno integral concerning aggregation on bipolar scales. The paper aims to build an equivalent representation of the bipolar Sugeno integral. Therefore, we first employ in this paper the framework based on a ternary-criterion set for proposing an alternative formula of the bipolar Sugeno integral to be suitable for bipolar scales. Then, we discuss some basic properties and give an illustrative example of this representation. This representation is consistent as an extension of the representation concerning the classical capacities and aggregation on the Sugeno integral unipolar scales.

In this study, copper oxide (CuO) specimens were successfully prepared by the hydrothermal process at altered calcination temperatures; 350, 450, and 550°C. The synthesized samples were analyzed through X-ray powder diffraction (XRD), scanning electron microscope (SEM), Raman, Fourier-transform infrared spectroscopy (FTIR), and UV-Vis spectroscopy to analyze the impact of calcination temperature on the structural, morphological, vibration spectra, functional group, and optical properties of CuO for optoelectronic device applications. XRD confirms the pure single-phase monoclinic structure of synthesized samples with no impurity phases and has good crystallinity with the development in calcination temperature. The average crystalline size, lattice constant, and porosity were found in the range of 3.98–5.06 nm; a = 3.4357 Å, b = 3.9902 Å, c = 4.8977 Å – a = 3.0573 Å, b = 3.9573 Å, c = 4.6892 Å; and 3.37–1.03%, respectively. SEM exhibited a variation in morphology by increasing calcination temperature. Raman spectra revealed that the CuO sample calcinated at 550°C with a stone-like shape having a large grain size of 3.25 μm exhibited that Raman peak intensity and the multiphonon band became stronger and sharper and exhibited higher intensity compared to the samples calcinated at 350 and 450°C. FTIR spectra confirmed that these synthesized specimens exhibited the peaks associated with the typical stretching vibrations of the Cu–O bond between 400 and 500 cm−1 exhibiting the formation of CuO. The energy bandgap was slightly reduced from 1.61 to 1.43 eV with the increase in the calcination temperature. The optical studies revealed that the calcination temperature of 550°C improves the optical properties of CuO by tuning its optical bandgap. The modified structural, morphological, and optical characteristics of the prepared CuO samples make them an appropriate candidate for optoelectronic device applications.

Due to more advanced features of the picture fuzzy soft set and valuable characteristics of aggregation operators, in this article, we present the notion of picture fuzzy soft Bonferroni mean aggregation operators and weighted picture fuzzy soft Bonferroni mean aggregation operators. Moreover, some basic properties of these introduced aggregation operators have been given. As cancer is one of the most rapidly increasing diseases globally. But due to different kinds of cancer diseases, it is very difficult to say which type of cancer disease is increasing rapidly. So to reduce this difficulty in the medical field, we have applied our work to medical diagnosis problems to ensure that fuzzy ideas can also help in the medical field. Also, an algorithm along with a descriptive example is established that conforms to the authenticity of initiated work. Furthermore, a comparative analysis of the introduced work has been given to show how this work is more efficient and dominant than other existing theories.

In many decision-making situations, we are not restricted to two kinds of aspects, such as membership degree or nonmembership degree, and sometimes we need to include the abstinence degree (AD). However, many fuzzy set theories fail to cover issues, such as an intuitionistic fuzzy soft set, Pythagorean fuzzy soft set and q-rung orthopair fuzzy soft set. All the above notions can only consider membership degree and a nonmembership degree in their structures. The spherical fuzzy soft set compensates for these drawbacks in its structure. Moreover, the Dombi t-norm and Dombi t-conorm are the fundamental apparatuses to generalize the basic operational laws of sum and product. Therefore, in this article, based on the dominant features of spherical fuzzy soft sets and valuable features of the Dombi t-norm and Dombi t-conorm, we initially developed the basic Dombi operational laws for spherical fuzzy soft numbers. Moreover, based on these newly developed operational laws, we introduced aggregation operators called spherical fuzzy soft Dombi average (weighted, ordered weighted, hybrid) aggregation operators. We discussed the basic properties of these aggregation operators. Additionally, we have developed a multiple criteria decision making (MCDM) approach using an explanatory example via our approach to show its effective utilization. Furthermore, a comparative study of our approach shows the superiority of our introduced notions.

This research paper investigates the repercussions of ocean acidification on marine ecosystems, focusing on the sensitivity of diverse taxa to changing pH stages. Drawing from recent research, we discover the complicated interaction among climate change, contaminant accumulation, and atmosphere dynamics, with a particular emphasis on coastal regions reliant on fisheries. Through a complete assessment, we recognize substantial differences in sensitivity amongst calcifying taxa, highlighting the implications for each polar and temperate/tropical region. Furthermore, we propose tailored management techniques relying on distinct climate zones and taxonomic groups to mitigate the destructive effects of ocean acidification. Our sensitivity analyses monitoring of capability shifts in Species Sensitivity Distributions (SSDs) under preindustrial pH situations, underscoring the importance of historic baselines in predicting future influences. This paper contributes to our understanding of how ocean acidification threatens marine biodiversity and underscores the urgency of implementing efficient conservation measures.

In this paper, the process for formulating the competition between stable and mutated cells is introduced. The fitness for each stable and mutated cells are employed to determine which type of cell will win in the competition. The numerical solution of the dynamical system for this model which we got is identical with the fitness cells results.

Among the schools of ancient Greece, Aristotelian thought is the most systematic philosophical school and one of its important features is the special attention to the field of practice. But at the same time, in the Orient, some Indian schools were active with the benefit of various epistemological sources, including the Vedas and the Upanishads. Among these, the Sankehiyeh school seems to be more systematic than other Hindu schools in that it lays down specific metaphysical foundations, especially in the case of Purusha (the intangible soul in pure consciousness) and Prakriti (the primordial matter of the universe). Since practical wisdom in each of these two systems of thought is based on parts of their metaphysical views, the present study takes a historical approach to philosophy and to the background and analysis of philosophical terms widely used by Aristotle and Sankehiyeh. He tries to compare their psychological principles based on the relationship between theoretical wisdom and practical wisdom. The important finding of the research is that the different perceptions of these two schools of the characteristics of the human soul and its relationship with the body are the main reason for distinguishing their goals from the discussion of practical wisdom. Aristotle's intellectual backgrounds are much more complex than those of Capilla; Aristotle's practical wisdom includes the family and society, but the teachings of Sankehiyeh are only concerned with the individual conduct of human beings; "Moderation" is the key concept for understanding Aristotle's practical wisdom but in the Sankhya system.

Background and Objectives: The analyses of genotype × environment interaction in multi-environment yield trials are very important for evaluation, selection and recommendation of crop varieties. The purpose of this study was to identify high yielding and stable barley lines for introduction in different regions of warm climates of the Iran.Materials and Methods: 17 barley promising lines (with two checks Auxin and WB-94-3) will be evaluated in two years (2017 – 2019) using RCBD with three replications in five stations of warm zone including Ahvaz, Darab, Zabol, Gonbad and Moghan.Results: The results of variance analysis showed that the effects of location, genotype and genotype × location, genotype × year and genotype × year × location interactions were significant at the 0.01 probability level. The polygon-view of GGE biplot led to the identification of four superior lines (G18, G10, G19, and G17), six poor lines and three mega-environments. Among the test locations, Gonbad had a high discriminating ability to show differences between the genotypes and Moghan showed the least of discriminating; Also, Gonbad showed the highest amount of broad sense heritability of grain yield (0.780) and Moghan showed the lowest amount of broad sense heritability of grain yield (0.018).Conclusion: Comparison of the studied lines with the ideal genotype showed that lines G18, G10, G19 and G17 were the closest lines to the ideal genotype with high yield and relative yield stability. Finally, these four lines were selected as the top lines for additional studies.

Data mining evaluation is very critical in the sense that it determines how well a classification model performs and how well it can generate accurate predictions on brand-new, unexplored data. It is especially important for classification tasks. There are several methods for evaluating classification models, and the choice of evaluation strategies depends on the particular situation, the available data, and the desired outcomes. The notion of a T-bipolar soft set (TBSS) is a valuable parameterization tool and is closer to the concept of bipolarity. Moreover, algebraic structures like groups, rings, and modules, etc., are basic tools that can be helpful not only in mathematics but also in other scientific areas due to their symmetric properties. In this article, based on the novelty of TBSS and the characteristics of rings, we have generalized these two notions to deliver and introduce the notion of T-bipolar soft rings (TBSRs). Additionally, the concepts of AND product, OR product, extended union, extended intersection, restricted union, and restricted intersection for two TBSRs is introduced, and the related results are conferred. To support these proposed notions, we have delivered examples related to these ideas. For the applicability of the developed approach, an algorithm is defined based on the delivered approach. An illustrative example regarding the classification of data mining techniques is developed to show the applications of the introduced work. We can see that there are four alternatives, and their score values are, respectively, given by −4, 42, 0, and −32. Based on these results, we can evaluate the best data mining technique. So, the defined algorithm makes it easy for us to classify the data mining techniques. Further asymmetric data are frequently employed for selecting the best alternative in decision-making problems because the information regarding alternatives is not necessarily always symmetric. Therefore, asymmetric information can be discussed using these proposed concepts.

The notion of the T-bipolar soft set defined by Mahmood is a novel approach that can explain bipolarity more effectively than the other notions of bipolar soft sets. But in our daily life there are some situations in which we have to discuss some order between terms like good, satisfactory, excellent, etc. For example, to order the positions of students in a certain class, the teacher ordered the grades like decent, unsatisfactory, really nice, and tremendous. This type of standing is essential to explain the order of students’ positions in a class. In these situations, the T-bipolar soft set fails because it cannot discuss the ordered between terms. So, there is a need for such a notion that can handle these kinds of limitations. Moreover, note that although the concept of lattice ordered soft set is already defined but it discusses only one dimension. The two-dimensional opinions are essential in many decision making problems for ranking some criteria of eligibility and non-eligibility options. Therefore, to cover these mentioned drawbacks, in this article, we have elaborated a new idea of lattice (anti-lattice) ordered T-bipolar soft sets that can consider the order among parameters and it is a more valuable structure for certain situations in decision-making problems. Therefore, when we define the ranking among the set of parameters, the concept of decision making becomes very helpful under the conception of lattice (anti-lattice) ordered T-bipolar soft sets. Moreover, basic operations are defined based on introduced notions like restricted union and restricted intersection. Furthermore, the extended union and the extended intersection of introduced notions have been established. To use the introduced notion to decision making problems, we have established the application in this regard. Furthermore, we have proposed a TOPSIS method that can strengthen the study of the introduced notion and verify the results obtained from introduced notions as well. The comparative analysis of introduced work show the superiority and effectiveness of established work than that of existing notions.

The objective of this article is to explore and generalize the notions of soft set and rough set along with spherical fuzzy set and to introduce the novel concept called spherical fuzzy soft rough set that is free from all those complications faced by many modern concepts like intuitionistic fuzzy soft rough set, Pythagorean fuzzy soft rough set, and q-rung orthopair fuzzy soft rough set. Since aggregation operators are the fundamental tools to translate the complete information into a distinct number, so some spherical fuzzy soft rough new average aggregation operators are introduced, such as spherical fuzzy soft rough weighted average, spherical fuzzy soft rough ordered weighted average, and spherical fuzzy soft rough hybrid average aggregation operators. Also, the basic characteristics of these introduced operators have been elaborated in detail. Furthermore, a multi-criteria decision-making (MCDM) technique has been developed and a descriptive example is given to support newly presented work. At the end of this article, a comparative study of the introduced technique has been established that shows how our work is more superior and efficient compared to the picture fuzzy soft set.

The present study was conducted to evaluate the role of age in the effectiveness of intravaginal progestin-impregnated sponges (IPIS) along with equine chorionic gonadotropin (eCG) on the multiple birth rates of Awassi ewes. One hundred mature ewes (live weight was 35–40 kg and age 2–5 years) were allocated to three groups according to their ages (n = 29, 2-3 years;n = 34, 3-4 years; and n = 37, 4-5 years). All ewes were impregnated with IPIS, injected with 20 mg cronolone, for 14 days, and eCG (400 IU, i.m.) at sponges withdrawal. All treated ewes came to estrus (100%); the highest twining rate was recorded in ewes aged 2-3 years, while the highest triple rate were found in those aged 3-4 years. A negative correlation coefficient was recorded between the age of treated ewes and the multiple births. In conclusion, the best age of Awassi ewes for estrus synchronization programs and multiple birth outcomes using IPIS along with eCG is 2–4 years.

Objective: To compare the anti-hyperglycemic and anti hyperlipidemic activities of ethanolic extract of Glycyrrhiza glabra (licorice) roots with the standard drugs metformin and glimepiride in streptozotocin induced diabetic rats. Study Design: Experimental study. Place and Duration of Study: Animal House of Basic Medical Science Institute (BMSI). Jinnah post graduate medical center (JPMC), Karachi conducted from May 2018 till August 2018. Materials and Methods: Total seven groups of Wistar albino rats comprising six rats in each were included. Study included negative control and positive control groups, to which 0.9% of sodium chloride was administered. Other five groups of streptozotocin induced diabetic rats were treated with metformin, glimepiride, rosuvastatin, ethanolic extract of Glycyrrhiza glabra (licorice) roots at a dose of 200 mg/kg and 400mg/kg, respectively. The treatment was given for 28 days followed by the laboratory estimation of fasting blood glucose (FBG), fasting serum insulin, Glycosylated Hemoglobin A1c (HbA1c), total lipid profile and serum amylase were evaluated. Results: A significant decrease was observed in all the glycemic indices at both doses of Glycyrrhiza glabra (licorice) i.e. 200 mg/kg and 400mg/kg, but a more rampant decrease is observed at the dose of 400mg/kg. Similarly, both concentrations of extract showed significant decrease in all lipidemic indices that included HDLC, VLDL-C, LDL-C, total cholesterol (TC), Triglycerides (TG) and the serum amylase levels. Conclusion: This study concludes that the licorice herb has sufficient anti hyperglycemic and anti hyperlipidemic effects in diabetic rats without any aberration in pancreatic enzymes, hence it might be beneficial as additional dietary supplements for the effective management of diabetes mellitus along with standard drugs.

In the context of the multiple-criteria decision aid (MCDA), several fuzzy integrals concerning capacities (non-additive measures) have been introduced by various researchers in the last sixty years. Recently, Lehrer has proposed a new integral for capacities known as concave integral. The concave integral is based on the decomposition of random variables into simple ingredients. The concave integral concerning capacity is defined as the maximum value obtained among all its decompositions. The paper aims to model a new integration based on the decomposition of random variables into simple ingredients for multi-criteria decision making support when underlying scales are bipolar. This paper proposes a generalization of the concave integral in terms of decompositions of the integrated function to be suitable for bipolar scales. We show that the random variable is analyzed as a combination of indicators, where each allowed decomposition has a value determined by the bi-capacity. Lastly, we illustrate our framework by a practical example.

Extended abstractThe present study was conducted to investigate the views of the Ash'arites of Iranian Kurdistan towards philosophy. To achieve this goal, a phenomenological-based qualitative research method was used. Twelve contemporary Kurdistan theologians were interviewed about philosophy. The questions were designed based on the research objectives. The results were as follows: 1) The Ash'arites of Kurdistan considered it sufficient to rely on the Qur'an and Sunnah and a rational view based on religious texts for designing and teaching the issues of old and new theology.2) Following a philosophy of Greek origin and its imitation were considered by them to be futile.3) To them, a philosophy could be invented based on Islamic texts. However, Ash'arite academics were more interested in philosophizing due to studying humanities and interacting with professors based on the contents of their academic philosophical courses.Therefore, considering the trend of spreading philosophy among the contemporary Ash'arites of the world, the Ash'arites of Kurdistan still try the same traditional practice of opposing philosophy. In the section of practical suggestions based on the research findings, the following recommendations could be put forward: 1) establishing philosophy with different orientations at the University of Kurdistan; 2) further training of old and new theology; 3) establishing the Institute of Philosophy and Wisdom in Kurdistan; 4) strengthening and equipping Kurdistan libraries with philosophical books; and 5) providing a more interaction between Shiite and Ash'arite theologies.In the field of research literature on contemporary Ash'arite theologians of the Islamic world, the results showed that people, such as Sheikh Mohammad Abdo (Rabbani Golpayegani, 1999: 18), Taha Abdolrahman (Miri and Parsania, 2009: 56), Nasr Hamed Abu Zayd (Abuzid 2003: 263), Mohammad Abed Jaberi (Jaberi, 2010: 375), Mohammad Arkoun (Arkon 2009, 2993, pp. 15-3), and Varshid Reza (Enayat, 1998: 157) had agreed with philosophy and only Seyyed Qutb (Savoshi, 1997: 157) had opposed it. However, among the contemporary Ash'arite theologians of Kurdistan, the findings indicated that some great figures such as Mullah Abu Bakr Chori (Baba Marduk, 2003: 148), Mullah Abdul Karim Modarresi and Mullah Mahmoud Modarres Negal (Baba Marduk, 2003, vol. 1: 147), and Malabaqir Balk ( Modarresi, 1985: 14) completely opposed philosophizing theological and religious issues and only the theologians of Takhti Mardukhi family like Sheikh Abdul Qader Mohajer, Sheikh Mohammad Sim Thani, and Sheikh Mohammad Jassim Sadr al-Ulama could teach philosophical issues due to their family powers (Abdoli, 2019: pp. 43-40). This had a significant relationship with the field results resulting from the interviewees’ views.Therefore, according to the teaching procedures and contents of traditional courses governing these scientific schools, the majority of Sunni seminary teachers and scholars followed Abolhassan Ash'ari in opposition to reason. Ghazali's views were especially in complete opposition to those of the philosophers. New doctrinal doubts were sufficient to make us rely on the Qur'an and Sunnah; thus, there was no need for Greek vague and imitative philosophy as being at the same time blasphemous. Finally, if one is to rely on philosophy in the present age, he/she must create a philosophy with Islamic text-based principles. Only a small number of the university interviewees were found to follow Ash'ari profession due to having an interaction with academics and studying in those fields. The humanities, such as sociology, law, philosophy, theology, and philosophy of education, had a positive approach to philosophy.It was expected that the Ash'arites of Kurdistan had a positive approach to philosophy like the Ash'arites in the Islamic world with the development of technology and modernity. However, the Ash'ari discourse of Kurdistan was finally found to be in opposition to philosophy.

Renewable energy is a topic that is frequently researched recently due to the negative environmental changes brought by using non-renewable energy sources such as fossil fuels. The application of the renewable energy is wide including being used to charge a battery using buck converter in general charging system. However, the problems faced by these solar charging systems is the inability to regulate and stabilize the output of the PV module, causing the loss of efficiency of PV module. A mechanism that is used to solve the problem is to develop the algorithm for maximum power point tracking in PV module. Thus, the project aims to improve the performance of battery charging system by using different MPPT algorithms and compared their performance with issues being analyzed, and helped to suggest the best algorithm to maximize the power supply and consumption effectively based on the MATLAB/Simulink results. The MPPT techniques used in the study consist of Constant Voltage (CV), Perturb and Observe (P&O), Incremental Conductance (INC) and also Hill Climbing (HC). The algorithms will be used on buck converter and compared with conventional solar battery chargers that uses PID controller for voltage regulation. The results are obtained from measurements of various parameters and they will be compared with the theoretical value with error calculation to determine the efficiency of the mechanism and also analyzed to determine the causes and effects of the simulation and for comparison. The results show that different algorithms can affect the performance of the system, such as changing transient times, power efficiency, shape of graph and so on. In conclusion, the best algorithm is Incremental Conductance due to its high-power efficiency and stable parameter output for battery charging system, in which further work done can be continued to include more weather data and constructing complex algorithm as well.

An earthquake is a natural phenomenon that occurs when two tectonic plates in the earth’s crust move against each other. This movement creates seismic waves that can cause the ground to shake, sometimes resulting in damage to buildings and infrastructure. It is important to be prepared for earthquakes, particularly if you live in an area that is at high risk for seismic activity. This includes having an emergency kit, knowing how to shut off utilities, having a plan in place for what to do in the event of an earthquake, and most importantly, constructing earthquake resistance buildings. The assessment and the ranking of structural systems to design earthquake resistance buildings is a MADM (multi-attribute decision-making) dilemma. Consequently, in this script, we initiate the method of MADM under the bipolar complex fuzzy (BCF) information. For this method, we devise BCF Dombi prioritized averaging (BCFDPA), BCF Dombi prioritized weighted averaging (BCFDPWA), BCF Dombi prioritized geometric (BCFDPG), and BCF Dombi prioritized weighted geometric (BCFDPPWG) operators by utilizing the Dombi aggregation operator (AO) with BCF information. After that, by using artificial data, we assess the structural systems to design earthquake resistance buildings with the assistance of the invented method of MADM. To exhibit the dominancy and supremacy of the elaborated work, the advantages, sensitive examination, graphical representation, and comparative study are described in this script.

The electric vehicle (EV) brings such a sustainable and hopes for future generation of automobiles industries and transportation industries as well. Market of penetration of EVs in the current market is quite outstanding and has been increase drastically in the recent years. With the integration, development, and introduction of EV, it adds more challenge towards electrical engineer to identify, acknowledge the impact of EV in term of power quality issues like harmonics, voltage stability, etc. when the EV is connected to the grid system. Hence, it is essential for engineers to evaluate all potential grid impacts due to EV integration to ensure the grid operation is operating at optimum and safe condition without effecting any equipment. This paper will identify and investigate the effects of harmonics when EV is connected to the grid system and identify the most suitable method to mitigate the harmonics that occur due to the EV charging station. The scope of this paper is limited to 8 numbers of EV charging station rated at 100kW output. This paper will also be focusing more on power quality issues in context of harmonics distortion that occurs when the amount of EVs charging station is connected to the distribution system. The most economic ways to counter and mitigate the presence of harmonics with the usage of either active or passive filter in the system also been considered.

Spherical fuzzy soft sets $\left(SF{{S}_{ft}}Ss \right)$ have its importance in a situation where human opinion is not only restricted to yes or no but some kind of abstinence or refusal aspects are also involved. Moreover, the notion of $SF{{S}_{ft}}S$ is free from all that complexities which suffers the contemporary theories because parameterization toll is a more important character of $SF{{S}_{ft}}S$. Also, note that aggregation operators are very effective apparatus to convert the overall information into a single value which further helps in decision-making problems. Due to these reasons, based on a spherical fuzzy soft set $\left(SF{{S}_{ft}}S \right)$, we have first introduced basic operational laws and then based on these introduced operational laws, some new notions like spherical fuzzy soft weighted average $\left(SF{{S}_{ft}}WA \right)$ aggregation operator, spherical fuzzy soft ordered weighted average $\left(SF{{S}_{ft}}OWA \right)$ aggregation operator and spherical fuzzy soft hybrid average $\left(SF{{S}_{ft}}HA \right)$ aggregation operators are introduced. Furthermore, the properties of these aggregation operators are discussed in detail. An algorithm is established in the environment of $SF{{S}_{ft}}S$ and a numerical example are given to show the authenticity of the introduced work. Moreover, a comparative study is established with other existing methods to show the validity and superiority of the established work.

A medical diagnosis is one the most efficient processes of determining a disease based on a person’s symptoms and signs. In recent days, due to the complexities of the same type of diseases, it is very difficult to diagnose a disease by using old methods and techniques. In this way, new and efficient medical diagnosis methods can help a lot in reaching an accurate conclusion, depending upon the timing and sequences of symptoms and medical history. The physician relies on other clues like medical tests and imaging tests. So, in this way, a list of possible diagnoses can be determined, which are referred to as different diagnoses. To handle these types of issues in this manuscript, additional information is identified, and possible disease is confirmed. Under the consideration of classical data, it is a very difficult task to deal with complex and asymmetric sorts of data. Fuzzy set theory has a wide range of applications, from engineering to the medical field. Different methods and techniques have been proposed to support the decision-making process in medical fields. Picture fuzzy soft sets are more generalized structures and efficient tools to formalize the information more decently and accurately. So, devoted from this notion, in this article based on picture fuzzy soft settings, we firstly have established some basic operational laws for picture fuzzy soft number; then based on these operational laws, we have developed some aggregation operators named as picture fuzzy soft prioritized average and geometric aggregation operators. In real-world problems, these operators can be useful in analyzing uncomfortable and asymmetric information. Furthermore, some basic properties of the introduced operators have been initiated and discussed briefly. Moreover, to show the effective use of this developed approach to medical diagnoses, we have proposed an algorithm, along with a descriptive example. Additionally, a comparative analysis of the proposed work shows the superiority and effectiveness of the introduced approach.

In this study, biocompatible electrospun nanofiber scaffolds were produced using poly(-caprolactone (PCL)/chitosan (CS) and Nigella sativa (NS) seed extract, and their potential for biomedical applications was investigated. Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), total porosity measurements, and water contact angle measurements were used to evaluate the electrospun nanofibrous mats. Additionally, the antibacterial activities of Escherichia coli and Staphylococcus aureus were investigated, as well as cell cytotoxicity and antioxidant activity, using MTT and DPPH assays, respectively. The obtained PCL/CS/NS nanofiber mat was observed by SEM to have a homogeneous and bead-free morphology, with average diameters of 81.19 ± 4.38 nm. Contact angle measurements showed that the wettability of the electrospun PCL/Cs fiber mats decreased with the incorporation of NS when compared to the PCL/CS nanofiber mats. Efficient antibacterial activity against S. aureus and E. coli was displayed, and an in vitro cytotoxic assay demonstrated that the normal murine fibroblast cell line (L929 cells) remained viable after 24, 48, and 72 h following direct contact with the produced electrospun fiber mats. The results suggest that the PCL/CS/NS hydrophilic structure and the densely interconnected porous design are biocompatible materials, with the potential to treat and prevent microbial wound infections.

In a natural condition, temperature variations and phase transition of pore water are the two most effective factors on the mechanical properties of rocks. Instabilities occurred as a result of climate changes, highlight the importance of rock characteristics. This paper conducted a laboratory investigation to study the temperature-dependent mechanical behavior of rocks and to examine the quantity and quality of this relationship. In order to perform laboratory tests, a temperature-controlling apparatus was developed. Studies were conducted on 152 specimens of concrete and three types of rocks, including granite, red travertine, and walnut travertine. Then, the effect of temperature variations, from -30 to +30ºC with 10ºC intervals on the mechanical properties of the rocks, was studied. The results showed that temperature reduction, caused by pore water phase transition, improved the mechanical properties of the rocks. The maximum variation of the mean uniaxial compressive strength from +30ºC to -30ºC belonged to granite (40.1%), while the concrete specimen showed the minimum variation on the test results (33.7%). Red travertine (38.7%) and walnut travertine (34.2%) exhibited lower variations compared to granite. Also, the maximum variation in the mechanical behavior of rocks occurred between -10 and 0 °C. Additionally, variations in the mechanical properties of cracked rock samples were more than the rocks with spherical pore and the same porosity percent.