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In recent years, rapidly changing disease profile patterns, shortage & uneven utilization of healthcare professionals contributed massive burden on the Indian healthcare system, which resulted in varying, fragmented, inconsistent healthcare delivery to the patients and poor patient management. Patients often face and experience many challenges like lack of accessibility, poor patient–healthcare provider relationships, and inadequate quality of care, resulting in unnecessary economic burden in managing their health conditions. Thus Indian healthcare reform is essential in enhancing its capacity to fulfill patients' health needs that can be addressed by focusing on key sustainable strategies and initiatives meant for enhancing coordination of care, expanding services accessibility, redeveloping healthcare infrastructure, implementing workforce innovation and strong governance with the incorporation of core principles such as patient-centeredness, integrated care and collaborative care approaches. The clinical and ambulatory pharmacy practice are fragment of the healthcare delivery which delivers pharmaceutical care and fulfils the needs of patients across healthcare settings. This paper focuses on the present & future perspectives of ambulatory pharmacy practice in India and the factors to be considered for implementing it in patient care.

Solar PV has become increasingly popular in the past decade, both for standalone and grid-connected systems. Solar PV systems exhibit non-linear output characteristics due to weather fluctuations, which can substantially impact the overall PV system’s output. Consequently, selecting the optimal MPPT technique for a given PV system is a complex task, as each method has different strengths and weaknesses. Therefore, conducting a comprehensive examination of these techniques is crucial. A survey of academic publications on ‘Google Scholar’ spanning the past seven years (2015-2022) revealed a total of seventy-one review articles addressing various MPPT techniques. Among the studies, seven have directed their attention toward non-uniform solar irradiance, while four have dedicated their focus to uniform conditions. Surprisingly, none have ventured into the realm of hybrid optimization MPPT techniques. Moreover, several of these reviews have covered a restricted range of MPPT methods, and none have delivered an all-encompassing assessment that encompasses both online and offline strategies for uniform conditions, alongside an evaluation of hybrid MPPT techniques in the context of non-uniform solar irradiance conditions. Unfortunately, there have been minimal efforts in this direction. Consequently, the need of the hour is a comprehensive review paper that encompasses nearly all known MPPT techniques within a single publication. This paper places its primary emphasis on categorizing MPPT algorithms into offline, hybrid, and online optimization techniques, addressing both non-uniform and uniform irradiance scenarios. It serves as a comprehensive resource by consolidating diverse MPPT techniques, presenting their mathematical formulations, operational principles, and visual representations through block diagrams and flowcharts. The objective of this research endeavor is to provide a valuable reference for strategists, researchers, and energy engineers, offering them a roadmap to steer future research endeavors and practical implementations in the realm of optimization of MPPT.

Agriculture faces significant challenges due to climate change and unpredictable environmental factors, which impact crop yields and threaten food security. This study proposes a novel approach to crop yield prediction and risk assessment using neutrosophic logic and least squares regression. By integrating these methods, we aim to improve accuracy in predicting crop losses under uncertain conditions. The model classifies crops based on profitability and environmental risks, utilizing the independence test to evaluate the relationships between crop attributes. Our approach leverages deep learning techniques, such as restricted Boltzmann machines (RBM), to enhance the analysis of crop data and provide farmers with actionable insights for decisionmaking. The results demonstrate that the proposed method effectively estimates crop yield damage with the ability to assess risk under varying conditions, such as extreme weather. This approach can help farmers optimize crop management strategies, minimize losses, and improve overall productivity. Future work will explore the application of this method to other crops and farming systems to expand its utility. [ABSTRACT FROM AUTHOR]

Introduction: Low back pain is one of the most common complaints in clinical practice with life time prevalence ranging from 65-80%. Lumbar disc herniation is the cause for less than 5 % of back pain problems but is the most common cause of sciatica. Absolute indication for surgery includes cauda equine syndrome and progressive neurological weakness. More often, surgery is done to provide more rapid pain relief and disability in those patients whose recovery is unacceptably low with non-operative treatment. Materials and methods: A prospective study was conducted in the Department of Orthopedics, Maharaja Institute of Medical Sciences, Nellimarla, Vizianagaram from January 2023 till December 2023. A patient case report form was designed to collect patient related informaton. Informed written consent was taken from the entire patient prior to interviewing the patient. All patients aged more than 18 years, who presented to the outpatient clinic of the Department of Orthopedics, Maharaja Institute of Medical Sciences, Nellimarla, Vizianagaram with complaints of leg or back pain, or other neurological symtoms, supported by Magnetic Resonance Imaging (MRI) suggestive of disc herniation, were included in the study. Results: We included 106 patients during the study period, average age was 40.17 ± 8.5 years. 64 patients were males. Most of the patients have had symptoms for less than 6 months. L4-L5 was the most commonly level involved. None of the patients had any post-operative infections. 40% of the patients had 5 to 6 days of hospital stay, followed by 32% having 7 to 10 days of hospital stay. We assessed the patients using the Macnab's criteria postoperatively at the time of surgery, 1 month, 3 months and 6 months after surgery. 57% of the patients reported excellent level of well being at the end of 6 months as compared to only 4% at the time of surgery. 35% reported good level of well being and no patient reported poor level of well being at the end of 6 months postoperatively. Conclusion: Microdiscectomy, as demonstrated by our outcome scores, has a high success rate for patients with lumbar disc herniations who have failed a period of conservative management. Findings of our study demonstrate that minimally invasive lumbar microdiscectomy cause very few postoperative complications, shorter stays in hospital, improve objective functionality scores postoperatively and patients rate well being assesment scores as good to excellent. [ABSTRACT FROM AUTHOR]

A 37-year-old male presented with left-sided hydropneumothorax. After drainage of fluid and air from the pleural cavity, chest radiograph and computed tomography of chest showed characteristic radiological image of ruptured hydatid cyst. The diagnosis was supported by positive echinococcal serology.

In recent years, rapidly changing disease profile patterns, shortage & uneven utilization of healthcare professionals contributed massive burden on the Indian healthcare system, which resulted in varying, fragmented, inconsistent healthcare delivery to the patients and poor patient management. Patients often face and experience many challenges like lack of accessibility, poor patient-healthcare provider relationships, and inadequate quality of care, resulting in unnecessary economic burden in managing their health conditions. Thus Indian healthcare reform is essential in enhancing its capacity to fulfill patients' health needs that can be addressed by focusing on key sustainable strategies and initiatives meant for enhancing coordination of care, expanding services accessibility, redeveloping healthcare infrastructure, implementing workforce innovation and strong governance with the incorporation of core principles such as patient-centeredness, integrated care and collaborative care approaches. The clinical and ambulatory pharmacy practice are fragment of the healthcare delivery which delivers pharmaceutical care and fulfils the needs of patients across healthcare settings. This paper focuses on the present & future perspectives of ambulatory pharmacy practice in India and the factors to be considered for implementing it in patient care. [ABSTRACT FROM AUTHOR]

Solar photovoltaic (PV) plants experience performance degradation due to environmental, operational, and material factors. Therefore, conducting a degradation analysis is essential to ensure the optimal performance and longevity of a solar PV plant. The main objective of this study is to investigate the impact of degradation on solar panels in various abnormal scenarios by evaluating performance indicators and electrical parameters of the PV plant. The core novelty of this research lies in the development of an integrated real-time degradation analysis framework for grid-interfaced solar PV plants, using both an I-V curve tracer and a thermal image camera in abnormal scenarios. This approach provides a comprehensive and precise assessment of the PV system's health by capturing detailed electrical characteristics and identifying thermal anomalies indicative of degradation. The key findings include the evaluation of electrical parameters and performance indicators such as peak power (Pmax), short-circuit current (Isc), open circuit voltage (Voc), Performance Ratio (PR), Fill Factor (FF), and the annual power degradation rate in various abnormal scenarios. An error analysis for all electrical parameters of the PV plant was conducted, comparing the percentage errors for each parameter with the panel parameters measured under standard test conditions. Finally, the performance metrics of the current study were compared with previous literature. [ABSTRACT FROM AUTHOR]

One of the key components of computer vision applications like satellite and remote sensing and medical diagnosis is multi-modal image fusion. There are various multi-modal image fusion techniques, and each has advantages and disadvantages of its own. This paper proposes a new method based on multi-scale guided filtering. Initially, each source image is divided into coarse and fine layers at various scales using a guided filter. In order to fuse coarse and fine layers, two different saliency maps are used: an energy saliency map to coarse layers and a modified spatial frequency energy saliency map to fine levels. According to the simulation results, the suggested technique performs better in terms of quantitative evaluations of quality than other state-of-the-art techniques. All the simulation results are carried on a standard brain atlas database. [ABSTRACT FROM AUTHOR]

Problem considered: Apart from dispensing of medicines, the new generation community pharmacists are engaged in various extended community pharmacy services. The main endorsement of these services primarily depends on understanding the end-users’ views about the quality of care provided. However, there are no validated tools available that can assess these parameters. Methods: Therefore, we aimed to develop and validate a tool that can assess the perceptions, expectations and satisfactions of patient care services provided by the community pharmacist. Following a comprehensive literature search, a thirty-two-item scale was developed and was subjected for content validation. Results: The item level content validity index (I-CVI) and scale level content validity index (S-CVI) was found to be 80%. The Cronbach's alpha score was 0.8, suggesting a satisfactory co-efficient of reliability. Conclusion: The scale to assess the perceptions, expectations and satisfactions of patient care services provided by the community pharmacist was developed and validated.

An attempt is made in this paper to diagnose brain-related diseases like sarcoma, fatal stroke disease, cerebral disease, and Alzheimer's disease by using saliency information from magnetic resonance and computed tomography source images. The saliency information for each source image is computed using guided and median filters. The obtained saliency maps are used for computing the weight maps of each source image by using image statistics. The obtained weights are used to fuse the approximate and detailed layers of the source images by using the weighted average fusion technique. The proposed algorithm is simulated in MATLAB for various benchmark data sets of brains taken from the brain atlas provided by Harvard Medical School, available at https://www.med.harvard.edu/aanlib. In order to test the efficacy of the novel method, comparative analysis is performed in terms of image quality assessment metrics like mean, mutual information, average gradient, standard deviation, spatial frequency, etc. From the analysis, this paper concludes that the proposed algorithm improved gradient information in the fused image by 35.7%, entropy by 5.7%, spatial frequency by 32.7%, edge strength by 14.5%, and minimized the information loss by 43.6%. Therefore, the novel method of weight map computation produces a detailed and noise-free image, which is helpful for better diagnosis in clinical applications. [ABSTRACT FROM AUTHOR]