Forest fires are a potential threat to life, as they contribute to reducing forest areas, impact on the services we expect from ecosystems, the health of the inhabitants is affected by smoke and the economic costs for the recovery of affected areas is high. The objective of the study is to apply fuzzy logic to model the risk of forest fires in the Cajamarca-Peru region, incorporating variables that represent biological, topographic, socioeconomic, and meteorological factors. The analysis was based on the acquisition, editing and rasterization of the database, application of fuzzy membership functions and image fuzzification, fuzzy superposition and spatial reclassification of forest fire risk. The results obtained show that 71.68% of the area is under very low or medium forest fire risk. However, 28.32% of the study area has a high to very high fire risk, which makes the occurrence of fires susceptible to the lack of rain and water in the soil. It was found that biological, topographic, and socioeconomic factors with their respective variables are directly influenced by meteorological factor variables such as temperature, rainfall and water availability. Fuzzy logic offered flexibility in modeling wildfire risk in the region, proving to be a useful tool for predicting and mapping wildfire risk.

The 1,3,4-Oxadiazole is an aromatic heterocyclic moiety recognized in drug research for its low lipophilicity. The multiple functionalities, heterocyclic azinane, sulfonamide, 1,3,4-oxadiazole and acetamide, are combined collectively to enhance the bioactivity potential of synthesized molecules. All the compounds were acquired by following microwave assisted and conventional techniques in a comparative way. The synthesized derivatives were screened for their antibacterial and enzyme inhibition potential. Furthermore, BSA binding analysis was executed to infer about the interaction with serum albumin. The spectral data of IR, EI-MS, ¹H-NMR and ¹³C-NMR were used to elucidate the final structures of compounds. The synthesized compounds had a modest antibacterial potential. Compound 8f bearing 2-methyl-4,5-dinitrophenyl group was the most active one against all the bacterial strains taken into account and α-glucosidase enzyme. Compound 8d bearing 4-nitrophenyl group was the best acetyl cholinesterase inhibitor and 8i bearing phenylethyl group was the best urease inhibitor.

This article briefly explains the simultaneous spatial durbin panel (SSDP) model. The study of the SSDP model is substantial because it can explain the interaction between geographic units, is more informative, diverse, efficient, exhaustive, and accurate in reaching conclusions that influence the policy determination. This article’s intention is to derive a parameter estimation method from the SSDP model using a modified generalized estimating equation approach, which is then used to model economic growth in ASEAN nations. This article compares the SSDP model with rook contiguity, 2-nearest neighbors, and a customized spatial weighted matrix in relation to an independent, first-order autoregressive, exchangeable working correlation structure. To model economic growth in ASEAN countries, a customized weighted matrix with first-order autoregressive and exchangeable working correlations is chosen based on the CIC value. The parameter analysis outcomes indicate: 1) it is a significant spatial dependence among ASEAN countries; 2) it is a significant simultaneous interaction among the gross domestic product (GDP) and foreign direct investment (FDI); 3) GDP has a greater influence on FDI than FDI does on GDP; 4) The economic growth is directly affected by the labor force total; and 5) trade openness has a direct effect on FDI.

Condensation product of o-aminophenol and pyrrole-2-carboxylaldehyde behaves as a fluorescent sensor for Fe³⁺ and Sn²⁺ ions in aqueous medium over the other metal ions like Na⁺, K⁺, Mg²⁺, Zn²⁺, Cd²⁺, Hg²⁺, Mn²⁺ and Cr³⁺. In aqueous solution, Fe³⁺ and Sn²⁺ ions coordinate to the receptor through a NON binding site which induces a strong fluorescence enhancement. Receptor can be applied as fluorescence enhanced probes for transition metal ions due to the inhibition of photo induced electron transfer (PET) mechanism.

Many researchers are attracted to Chitosan based blends due to its properties and potential applications in various fields. The advanced development of Chitosan blends integrates the science and technology of blended materials. The present experimentation is reporting the preparation of Chitosan and Agar-Agar blends (CCA) by chemical mixing of these materials at different compositions. The thermal studies of the prepared blends were studied by differential scanning colorimeter (DSC) and thermogravimetric analysis (TGA) tools. Thermal studies reveal that the lowest degradation temperatures of blends might be attributed to the partial miscibility of CAA blends at particular composition and miscibility due to single glass transition temperature (T_g) between Chitosan and Agar-agar. Bonding nature of sample blends were carried out by Fourier transform infrared (FT-IR) instrumentation. This study reveals the interaction between Chitosan and Agar-agar is partial miscibility. Morphological study reveals that a few aggregated particles, which suggest the partial miscibility of CAA blends. Homogeneity of blend compositions and specific intermolecular interactions of hydrogen bonding type is also observed.

The dissipation and side-effect of metribuzin (MBZ) were studied with various factors; two soil types (clay loam and sandy loam), soil amendment (wheat straw and without amendment), two temperature levels (25 and 50°C), sterilization (sterilized and unsterilized soil) and time of incubation (15 and 30 days) and designed by Windows version of MINITAB software package to reduce the time and the cost as well as increased the precision. Determination of MBZ by HPLC with recoveries ranged from 50.85 to 108.09%. The MBZ residues were detected in all samples up to 60 days of storage, respectively with decline in their concentrations with the time of incubation. The clay loam soil showed higher dissipation than the sandy loam soil. The different factors in the present study confirmed that the wheat straw amendment, non-sterilization and incubation at 50°C caused higher dissipation of MBZ than without wheat straw, sterilization and incubation at 25°C. The dissipation was described mathematically by a first order equation with t0.5 was ranged from 9.62 to 16.82 days in clay loam soil and from 10.01 to 16.04 days in sandy loam soil. The side-effect of MBZ was tested on soil dehydrogenase activity that can be considered as an indicator of the biological activity and microbial degradation. The result proved that the enzyme activity was significantly decreased in all treatments compared with the controls at 1 and 3 days of incubation then it was gradually increased at 7, 10, 15 and 30 days of incubation. Treatments of wheat straw, non-sterilized and incubated at 25°C or 50°C showed the lowest enzyme inhibition among all treatments.

Traditionally, endemic diseases such as dengue, diarrhea, and tuberculosis are modeled separately, which leads to a limited understanding of current disease dynamics and an inaccurate evaluation of the parameters of the different models. In this study, we propose a joint spatiotemporal model to predict the risks of multiple endemic diseases and identify hotspots. The model includes spatial shared component random effects and a covariate for healthy behavior. The model was applied to the joint modeling of dengue, diarrhea, and tuberculosis in thirty districts in Bandung, Indonesia over a five-year period. Our findings show that the joint model was effective in understanding the characteristics of the diseases. One potential advantage of using shared component models is that they can identify diseases with spatial or temporal distribution patterns and consider shared risk factors that may be spatially correlated, such as climate. It is recommended to conduct exploratory analyses to determine the correlation between the risks of the diseases being studied and the reference disease before using this type of model.

In the present work, we have discussed the synthesis of a series of 1-((2'-(2-(2-(substitutedphenyl))-2-oxoethyl)-2H-tetrazol-5-yl)-[1,1'-biphenyl]-4-yl)methyl)piperidine-4-carboxylic acid derivatives by the reaction of 1-((2'-(2H-tetrazol-5-yl)-[1,1'-biphenyl]-4-yl)methyl)piperidine-4-carboxylic acid with phenacyl bromides using potassium carbonate. The structures of synthesized derivatives have been characterized using different spectroscopic techniques like FT-IR, ¹H-NMR, ¹³C-NMR, and Mass. Synthesized compounds were screened for their antibacterial and anti-TB activities all the compounds have found better activity against selected pathogenic strains. In addition, in silco molecular docking studies were carried out on targeted enzymes DNA gyrase and 3-oxoacyl-ACP reductase with ADME-toxicology studies.

Life insurance is designed to reduce the risk of financial loss due to unforeseen consequences related to the insured's death. In life insurance, the insurer provides death benefits as a claim when the insured suffers death. The claim is the compensation for a risk loss. Individual claim in one-period insurance is called aggregation claim, while aggregation claim is a collective risk. Collective risk is usually measured using a variance. However, the variance risk measure cannot often accommodate any event risk because there is a risk of claims beyond the amount of variance. Using the proposed method CVaR and confidence level are taken from α = 0.25% until 4%. This study found that the proposed method CVaR scored more fairly than Collective Risk. In conclusion, this study indicated that the collective risk model is just included using mean and variance without any confidence level. Therefore, only one result for the Collective Risk model, which automatically shows the model using mean, variance and standard deviation, could not accommodate all risk events.

It is not a secret that road accidents cause significant suffering. Those accidents can last from wounded to dead people, negatively impacting a country. A bunch of recent investigations tried to tie road accidents with the quality of roads. Therefore, in a country with a significant infrastructure gap, it is necessary to analyze the relationship between the different kinds of roads and the severity of car accidents. The current research examined such a relationship by employing the Multi logit regression. It was found that the significance of different car accidents will vary among the road types. Moreover, with the help of probability analysis, it was discovered that speeding, emergency services availability, and road security seemed to have a crucial impact on road accidents.