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Drought is characterized by a prolonged and abnormal lack of moisture, often stemming from insufficient or uneven distribution of precipitation, resulting in water shortages in streams or reservoirs, with detrimental impacts on both natural and socioeconomic systems. The paper focuses on the climatic drought patterns within the Right Bank Main Canal Command Area of Gujarat’s Dharoi Reservoir. To evaluate drought conditions, the study employs several indices including the Standardized Precipitation Index (SPI)and Normalized Difference Vegetation Index (NDVI). Daily rainfall data, obtained from IMD gridded data and extracted using ArcGIS software, is utilized to calculate SPI values at a three-month time scale. NDVI is determined using Landsat-8 OLI data spanning from 2013 to 2022 to analyze changes in agricultural vegetation. Comparisons among NDVI and SPI reveal that the year 2018 experienced significant rainfall deficits across the region, leading to severe water scarcity. This shortage impacted agricultural practices, evident in reduced crop cultivation areas as indicated by NDVI results and validated using the crop yield data for the time series. Specifically, the NDVI analysis highlights that 33.5% of the RBMC command area exhibited signs of dryness, with an additional 64.5% showing moderate dryness. The study endeavors to pinpoint drought-affected regions utilizing precipitation data, reservoir storage information, and remote sensing methodologies.

Using wastewater for irrigation poses a significant health risk. We measured the concentration of (cobalt, chromium, copper, manganese, nickel, lead, and zinc) in wastewater, soil, and vegetation at 8 sites along a 60 km stretch of the Sabarmati River in Ahmedabad city. An evaluation of the potential danger from consuming contaminated vegetables was conducted using Estimated Daily Intake (EDI), Target Hazard Quotient (THQ), and Target Cancer danger (TCR). The average concentration of the metals Co, Cr, Cu, Mn, Ni, Pb, and Zn exceeds the maximum permitted limits for irrigation purposes as established by regulatory bodies. The heavy metals in the collected soil sample are ranked in descending order of concentration as follows: Zn > Mn > Cu > Cr > Ni > Pb > Co. The average metal concentrations in vegetables range from 0.10-11.3 µg g-1 for Co, 5.2-11.8 µg g-1 for Cr, 0.04-9.9 µg g-1 for Cu, 12.3-110 µg g-1 for Mn, 0.7-4.2 µg g-1 for Ni, 0.4-8.4 µg g-1 for Pb, and 4.4-44 µg g-1 for Zn. The mean content of heavy metals (µg g-1) in the collected vegetable samples is highest in spinach, followed by brinjal, cabbage, tomato, and cauliflower. The Hazardous Quotient (THQ) shows a high health risk for Pb (6.1) and Mn (1.02), and a medium health risk for Cr (0.9). The Target Cancer Risk (TCR) emphasized the cancer risk posed by Chromium (Cr) and Nickel (Ni), following with Lead (Pb). The study indicates a link between health risks and consuming vegetables grown in the study area. It recommends improving wastewater treatment facilities and monitoring heavy metal levels in vegetables grown in soil irrigated with wastewater at regular intervals.

Heptahelical receptors (HHRs) are generally thought to function as monomeric entities. Several HHRs such as somatostatin receptors (SSTRs), however, form homo- and heterooligomers when activated by ligand binding. By using dual fluorescent ligands simultaneously applied to live cells monotransfected with SSTR5 (R5) or SSTR1 (R1), or cotransfected with R5 and R1, we have analyzed the ligand receptor stoichiometry and aggregation states for the three receptor systems by fluorescence resonance energy transfer and fluorescence correlation spectroscopy. Both homo- and heterooligomeric receptors are occupied by two ligand molecules. We find that monomeric, homooligomeric, and heterooligomeric receptor species occur in the same cell cotransfected with two SSTRs, and that oligomerization of SSTRs is regulated by ligand binding by a selective process that is restricted to some (R5) but not other (R1) SSTR subtypes. We propose that induction by ligand of different oligomeric states of SSTRs represents a unique mechanism for generating signaling specificity not only within the SSTR family but more generally in the HHR family.

Abstract Background: Construction workers are the second largest workforce in un-organized sector of the country. They are exposed to various hazards due to work conditions. Occupational Dermatitis is one of the commonest hazards among construction workers, most commonly due to exposure to cement and other materials like paints and resins, used at construction sites. Objectives: To find out prevalence of skin morbidity and its relation with provision and practice of usage of Personal Protective Equipments (PPEs) among construction workers. Methodology: A cross sectional study among construction workers working at various sites of Sumandeep Vidyapeeth. Data was collected with the help of a pre-designed and pre-tested questionnaire for skin morbidity. Results: 20.3% of workers had skin morbidity like dermatitis and itching. Only 28(12.5%) out of 230 workers were provided the PPEs at workplace, however, only eight were using them regularly during work and it was found that prevalence of skin morbidity was less in this group compared to the group which was not using them regularly at workplace. Conclusion: Skin morbidity is one of the commonest hazards among construction workers. Morbidity is lesser among regular PPE users at workplace.

The aim of this study was to determine the prevalence and characteristics of postoperative pain after endodontic microsurgery and to identify potential predictors for severe pain. One hundred seventy-three patients who underwent endodontic microsurgery at a private practice were included in the study. The patients were asked to fill out a questionnaire to assess their postoperative pain levels for 5 days after surgery. The questionnaires were analyzed to record the changes in pain levels over time. The presence and size of preoperative lesions and bone thickness were determined on preoperative cone-beam computed tomographic scans. Statistical analyses were performed to identify predictors for developing severe pain after surgery. A binary logistic regression model was established to predict the occurrence of severe pain. Severe pain was most prevalent on day 1 (17.3%) and gradually decreased until a small increase on day 5. The average pain level also peaked on day 1 postoperatively and gradually decreased afterward. No significant difference was observed between patients who reported severe pain and those who did not report severe pain regarding tooth position (anterior vs posterior), lesion size, and presence of fenestration. However, sex, age, and bone thickness were all significant predictors of severe postoperative pain, with odds ratios of 2.8, 0.96, and 1.41, respectively. Severe pain was reported only in a small number of patients after endodontic microsurgery. Younger patients, females, and patients with thicker bone covering the apex are significantly more likely to develop severe pain. [ABSTRACT FROM AUTHOR]