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Retracted: Background: To enhance the duration of sensory anaesthesia and to prolong the duration of post-operative pain relief during spinal anaesthesia, various adjuvants have been tried along with local anaesthetic agent. The present study was undertaken to evaluate and compare the onset and duration of sensory block, motor block and duration of post-operative pain relief by using intrathecal 0.5% Hyperbaric bupivacaine with fentanyl 25µg versus only 0.5% Hyperbaric bupivacaine selected groups.Methods: We enrolled 70 ASA Ι & ΙΙ patients undergoing surgeries below umbilicus level for our Prospective Randomized trial. Those who met our inclusion criteria were randomized using simple random sampling technique, after obtaining informed consent. Patients in Group A received fentanyl 25µg with 0.5% Hyperbaric Bupivacaine and patients in Group B received only 0.5% Hyperbaric Bupivacaine intrathecally. Parameters like onset and duration of sensory and motor block and postoperative pain relief were observed. In postoperative period, VAS score was monitored & time for rescue analgesia was noted, when VAS exceeded 5 or above.Results: It was found that Patients in Group A had significantly prolonged duration of postoperative analgesia as compared to Group B (Z value 17.35). Results of Onset & Duration of sensory and motor block were suggesting insignificant result. Post-operative complication was insignificant in our study.Conclusion: Addition of Fentanyl 25µg with 0.5% Hyperbaric Bupivacaine in Spinal anaesthesia have insignificant effect on duration of sensory and motor blockade and prolongs postoperative pain relief.

In the classification of cancer data sets, we note that they contain a number of additional features that influence the classification accuracy. There are many evolutionary algorithms that are used to define the feature and reduce dimensional patterns such as the gray wolf algorithm (GWO) after converting it from a continuous space to a discrete space. In this paper, a method of feature selection was proposed through two consecutive stages in the first stage, the fuzzy mutual information (FMI) technique is used to determine the most important feature selection of diseases dataset through a fuzzy model that was built based on the data size. In the second stage, the binary gray wolf optimization (BGWO) algorithm is used to determine a specific number of features affecting the process of classification, which came from the first stage. The proposed algorithm, FMI_BGWO, describes efficiency and effectiveness by obtaining a higher classification accuracy and a small number of selected genes compared to other competitor algorithms.

Introduction: The HRMT (Human Resting Myofasial Tone) factor plays an important role to initiate the trigger the inflammation at the disease site in Ankylosing spondylitis (AS) as in all spondyloarthropathies. The incidence of fibromyalgia is higher in AS and a limiting factor to undergo the exercise program. Aim of the study: To know the effectiveness of soft tissue mobilisation in patients with Ankylosing Spondylitis when it used as an adjuncts to the conventional exercises. Methodology: 40 subjects were randomly assigned in to experimental and conventional group. Experimental group (n=20) received conventional exercises along with soft tissue mobilisation and the conventional group (n=20) received only conventional exercises (flexibility exercises, aerobic exercise and breathing exercise) for a period of 4 weeks, 5days/week. Results: The result of the study showed that both the conventional and experimental groups improved significantly in stiffness, pain and physical function aspects after treatment. However the experimental group had a greater change as compared to conventional group. Conclusion: The study demonstrates that soft tissue mobilisation has an effect when it used before the conventional exercise in patients with ankylosing spondylitis.

A preliminary laboratory study was conducted using upflow anaerobic sludge blanket (UASB) reactor to investigate the potential of methane generation from brewery wastewater. Brewery wastewater from a local brewery company was collected and used in the experiments. The experiments were run for 15 days. The rate of methane production was about 5.32 L per kg of chemical oxygen demand (COD) removed per day. The pH reduction in the experimental reactor limited the ability of gas production and is likely the result of the temperature at which the experiments were conducted.

Magnusiomyces capitatus is a rare cause of invasive fungal infection in immuno-compromised patients. We report the case of magnusiomyces infection of the central nervous system, the lungs and sinus with a palatal lesion, in a patient treated for acute myeloid leukemia. While Magnusiomyces infections pose diagnostic and therapeutic challenges, a comprehensive understanding of their epidemiology, clinical manifestations, and microbiological aspects is essential to guide effective management. The patient improved under antifungal treatments despite a reduced sensitivity of the different antifungals to the antifungogram. The important delays between chemotherapy cycles and its reduced intensity due to the Magnusiomyces infection has made managing the anticancer treatment more challenging.

Geosynthetics used in landfills provides a technical and economic advantages over traditional clay liners. It may create stability issue and even lead to landfill failure due to its low interface or internal shear strength if improperly designed and/or constructed. The most common failure mechanism in geosynthetic-lined landfills is transitional failure involving waste and bottom liner (deep-seated failure) or only final cover system (shallow failure). Shear strengths of geosynthetic-geosynthetic and geosynthetic-soil have a wide range of variations. Shear strengths of interface from literature may be used in preliminary design. For final design, site-specific interface shear strengths shall be used. Internal shear strengths of unreinforced geosynthetic clay liner (GCL) are less than those of reinforced GCLs. Unreinforced GCLs are not recommended for slopes steeper than 1:10 (1 Vertical and 10 Horizontal). Peak shear strength of interface and internal GCLs can be used in bottom liner; residual shear strength of interface and internal GCLs shall be used for geosynthetic placed along the slopes. Site-specific shear strengths of waste are recommended to be used in the design. Landfill failure could be triggered by static loadings including excessive leachate, pore pressure above the bottom liners, gas pressure, and excessive wetness of the geomembrane-GCL, and earthquake loading. The factor of safety of 1.5 is recommended for static loading and 1.0 for earthquake loading. A higher factor of safety is recommended if a failure could have a catastrophic effect on human health or the environment, and if large uncertainty exists in input parameters to calculate the factors of safety. The main objective of this review article is to provide a comprehensive knowledge of slope failure mechanisms, causes, and probable remedies in one place.

The article describes the gamma activation analysis method used to determine the gold content in rock samples using the Aura measuring complex. The physicochemical basis of gold extraction in the process of cyanide leaching is considered. The technology for extracting gold from solutions of tailing waste “ponds” of tailings dumps of hydrometallurgical plants of the Joint Stock Company “Navoi Mining and Metallurgical Combine” (JSC NMMC) is presented. It has been shown that in the dynamic mode of sorption of tailing waste solutions acidified to pH = 3.3÷3.5 through AM-2B and VP-1P ion exchange resins, gold is sorbed on the AM-2B anion exchanger up to 3.9 mg/g and on the VP-1P anion exchanger up to 1.5 mg/g. It has been shown that when solutions of tailing waste are exposed to ammonia, ammonia complex compounds of base metal impurities are formed, which decompose, while the gold cyanide complex does not decompose and is sorbed on the AM-2B ion exchange resin up to 3.0 mg/g. The mechanisms of the chemical reactions of the process of extracting gold from tailing waste and the technological scheme of the installation for extracting gold from solutions of the tailing waste “pond” are presented.

This study explores the effectiveness of Homeopathy in managing infectious diseases, focusing on its integration with nanoscience. The key objectives include assessing the role of homoeopathic treatments in reducing morbidity and mortality from various infections, such as respiratory, gastrointestinal, and mosquito-borne diseases, and examining the scientific mechanisms behind its therapeutic effects.Key findings from the study include evidence of nanoparticles in highly diluted homoeopathic solutions, suggesting that these remedies may retain measurable amounts of the original substances. This nanoparticulate perspective bridges traditional homoeopathic practices with modern nanomedicine. Historical evidence, such as Hahnemann’s work on scarlet fever and recent studies during the 2006 Chikungunya epidemic, supports the effectiveness of homoeopathic treatments, demonstrating improved recovery rates and reduced complications with integrated homoeopathic and allopathic approaches.The main conclusion of the study is that Homeopathy, particularly when combined with nanoscience, holds significant promise as a complementary approach in the management of infectious diseases. The presence of nanoparticles in homoeopathic remedies may explain their therapeutic effects, positioning Homeopathy as a valuable component of holistic healthcare strategies, especially in developing countries.

In 1955, nutrient malabsorption following upper gut surgery was shown to be related to altered upper gut microbiome. In individuals with abdominal symptoms after Roux-en-Y gastric bypass, we have reported that small intestinal glucose malabsorption is associated with upper gut bacterial overgrowth. We hypothesize that individuals with abdominal symptoms after vertical sleeve gastrectomy have glucose malabsorption associated with upper gut bacterial overgrowth, and to test this hypothesis, bacterial overgrowth and potential glucose malabsorption are examined after sleeve gastrectomy. This is a retrospective study of individuals with medically-complicated obesity who underwent sleeve gastrectomy from 2013 to 2016 with subsequent glucose hydrogen breath testing to evaluate abdominal symptoms. A fasting breath hydrogen or methane of ≥10 PPM or rise of ≥8 PPM ≤45 minutes after oral glucose is bacterial overgrowth, while glucose malabsorption is a second rise of ≥8 PPM at >45 minutes. Seven females (mean age: 48.0 years; mean body mass index at surgery: 45.7 kg/m2) are described. Five subjects (71%) have an early rise in hydrogen or methane, while three (43%) have a second rise in hydrogen or methane >45 minutes after glucose. The mean percent excess weight loss at one year was 40% in three individuals with a second peak and 46% in four subjects without a second peak. After sleeve gastrectomy, subjects have glucose malabsorption associated with the presence of bacterial overgrowth. Completion of a larger prospective study is needed to confirm and expanding upon these findings. Further work should examine the potential effects of bacterial overgrowth on expression of intestinal glucose transporters.

A significant obstacle to agricultural productivity that jeopardizes the availability of food is crop diseases and farmer livelihoods by reducing crop yields. Traditional visual assessment methods for disease diagnosis are effective but complex, often requiring expert observers. Recent advancements in deep learning indicate the potential for increasing accuracy and automating disease identification. Developing accessible diagnostic tools, such as web applications leveraging CNNs, can provide farmers with efficient and accurate disease identification, especially in regions with limited access to advanced diagnostic technologies. The main goal is to develop a productive system that can recognize tomato plant diseases. The model was trained on a collection of images of healthy and damaged tomato leaves from PlantVillage using transfer learning techniques. The images from the dataset were cleansed by resizing them from 256 × 256 to 224 × 224 to match the dimensions used in pre-trained models using min-max normalization. An evaluation of VGG16, VGG19, and DenseNet121 models based on performance accuracy and loss value for 7 categories of tomatoes guided the selection of the most effective model for practical application. VGG16 achieved 84.54% accuracy, VGG19 achieved 84.62%, and DenseNet121 achieved 98.28%, making DenseNet121 the chosen model due to its highest performance accuracy. The web application development based on the DenseNet121 architecture was integrated using the Django web framework, which is built on Python. This enables real-time disease diagnosis for uploaded images of tomato leaves. The proposed system allows early detection and diagnosis of tomato plant diseases, helping to mitigate crop losses. This supports sustainable farming practices and increases agricultural productivity.