Fuzzy logic (FL) has emerged as a pivotal component within the realm of Expert Systems, demonstrating its efficacy in addressing real-life challenges that had previously eluded resolution. Its versatile applications span a multitude of domains, with this paper specifically delving into the successful utilization of fuzzy logic methods to tackle various agricultural issues. This comprehensive review explores instances where fuzzy logic has been seamlessly integrated into expert systems to provide innovative solutions within the field of agricultural sciences. The examined applications encompass a spectrum of challenges encountered in agriculture, showcasing the adaptability and effectiveness of fuzzy logic in addressing complex issues. This paper serves not only as an insightful examination of existing applications but also as a valuable contribution to the literature survey, laying the groundwork for future research endeavours. Particularly, it provides a foundational reference for those undertaking research aimed at developing expert systems tailored for specific crops in designated regions of our country. As a part of the broader landscape, this study acts as a cornerstone, offering a starting point for further investigations and advancements in the intersection of fuzzy logic and agricultural sciences.

One of the key elements in the analysis of HIV infection is the estimation of the period until seroconversion. The seroconversion time is a crucial element of the seroconversion distribution in the analysis of the HIV epidemic. Elements that speed up the process of seroconversion include homo or hetero sexual interactions, the use of non-sterile needles, etc. Given that the timing of HIV conversion is unpredictable, one would anticipate that the distribution of seroconversion would have a significant influence on how the HIV pandemic develops. The intervals between sexual encounters were pointed out as a probable factor. To investigate the non-linear damage process affecting the immune system, we suggest a stochastic model. Alpha Poisson distribution has been derived keeping the Mittag-Leffler distribution as the inter-arrival time of the infection. A three-parameter Weibull distribution for the seroconversion time distribution is also introduced. HIV's seroconversion time's mean and variation are calculated. To demonstrate the seroconversion rates of HIV transmission, a numerical example is provided. The means and variance of seroconversion time decreases as the HIV intensity of the infected partner rises. The practical implication of the finding is that HIV spreads more quickly as immune system intensity decreases.

One of the key elements in the analysis of HIV infection is the estimation of the period until seroconversion. The seroconversion time is a crucial element of the seroconversion distribution in the analysis of the HIV epidemic. Elements that speed up the process of seroconversion include homo or hetero sexual interactions, the use of non-sterile needles, etc. Given that the timing of HIV conversion is unpredictable, one would anticipate that the distribution of seroconversion would have a significant influence on how the HIV pandemic develops. The intervals between sexual encounters were pointed out as a probable factor. To investigate the non-linear damage process affecting the immune system, we suggest a stochastic model. Alpha Poisson distribution has been derived keeping the Mittag-Leffler distribution as the inter-arrival time of the infection. A three-parameter Weibull distribution for the seroconversion time distribution is also introduced. HIV's seroconversion time's mean and variation are calculated. To demonstrate the seroconversion rates of HIV transmission, a numerical example is provided. The means and variance of seroconversion time decreases as the HIV intensity of the infected partner rises. The practical implication of the finding is that HIV spreads more quickly as immune system intensity decreases.

Depression is a diverse syndrome in which some underlying presentations may share a common phenomenology but have different etiologies. Despite considerable work on the etiology of depression including neurobiological, genetic, and psychological studies, no reliable classificatory system has emerged that links either to the underlying etiology or has proven strongly predictive of response to treatment. Reactive and endogenous depression, melancholia, typical depression, depression with a seasonal pattern/seasonal affective illness, and dysthymia are only a few of the classification systems/subgroupings that have been employed. These have been based on a variety of factors, including the type, quantity, intensity, pattern, and duration of the symptoms, as well as in some cases, the presumptive cause. We adopted the Beck Depression Inventory (BDI)-II as the instrument, and outpatients of a psychiatric clinic were recruited as samples, as well as undergraduates as a non-clinical sample, to achieve the goal of studying the classification of depression disorders using fuzzy theory. The elements in the BDI were presented, and percentages were given to each one. We have the option to pick from many membership levels, and the total percentages for the selected category might reach 100%. To categorize the severity of depression, we use probability-based categorization Wald's and k-means together with fuzzy C-Means. We categorize the FCM, Wald's, and k-means percentages using clustering analysis. Finally, we conclude that FCM performed better than the other two probabilities-based techniques.

Topological indices are numerical descriptors that may be produced from a molecular graph to thoroughly analyze the medications. They are frequently employed in the analysis and forecasting of the physicochemical features of several pharmaceuticals. Numerous forms of polynomials and topological indices are computed, which serves as representations of chemical structure, and are crucial to chemical graph theory. The findings already obtained may be improved, and there may be a greater link to the various physical features of chemical substances, as a consequence of modifications and generalizations of the conventional topological indices. We suggest seven brand-new distance-based topological indices in this communication. We further investigate these suggested topological indices for several frequently occurring chemical structures from chemical graph theory.

The theory of interval-valued set is to concentrate the single membership functions. The manuscript aims to develop the concept of interval-valued Fuzzy normal subnearrings of a near ring (i-v FNSN). Based on these concepts, we analyzed some properties and results for the development of the theorem. We also initiate the study of homomorphism, union, and some algebraic properties. The concept of intersection is also proved. The results are beneficial to researchers.

A numerical descriptor is a mathematical instrument that uses information about the chemical compound's structure to examine and explore a molecule's physicochemical attributes without the need for expensive and time-consuming laboratory tests. It is a true number that contains or provides a great deal of useful information about a chemical substance. Topological indices come in a variety of forms, including degree-based, neighbourhood degree-based, distance-based, and eigen value-based indices. Utilizing indices that correlate with biological activities and other aspects of the respective chemical compounds, property and activity-based models are applied. Numerous topological indices have been constructed taking into account each atom's level of hybridization inside the molecule. We concentrate on some distance-based topological indices of various alkane structures in this work. The proposed topological indices and the QSPR investigation for alkane are also established.

The irregularity-based topological indices are applied for computational evaluation of non-ordinary molecular graphs. The improvement of irregularity-primarily based total indices is associated at the conversion of a structural graph into a complete matter describing the irregularity of the molecular layout at the map. In structural science and chemistry, it is critical to be aware of how uncommon a molecular structure is in particular contexts and difficulties. In this paper, we discuss the QSPR analysis of sixteen irregularity indices and certain alkane structures.

The potential energy field produced by a given charge or mass density distribution is described using the Poisson equation. This study presents a numerical solution to the Poisson equation using a wavelet-based multi-grid approach. The proposed method is superior to the existing method in terms of fast convergence and reduced processing time. Some of the problems are used to show the method's applicability and validity.