Lump-like Structures in Scalar-field Models

In this work we investigate the presence of lump-like solutions in models described by a single real scalar field. We take advantage of a procedure recently used to describe explicit analytical solutions and we study several distinct models, showing how the parameters can be used to control the specific features of the lump-like structures. The proposed models are of direct interest to the construction of q-balls, to induce tachyonic excitations and gravitating structures of nontopological profile on braneworld models with a single extra dimension, to map solitons in optical fibers, and to describe collective excitations in Bose-Einstein condensates.Comment: 7 pages, 11 figure

Price signals across onion markets in Tamil Nadu

This research investigates price volatility and market integration within select small onion markets across Tamil Nadu, India. Using monthly wholesale price data from the Dindigul, Chennai, Coimbatore, and Idukki markets for the period 2014 to 2023, the study employs an array of econometric methods to analyze price dynamics and market interconnections. The ARCHGARCH model analysis revealed high price volatility persistence in selected small onion markets with the Coimbatore market displaying the highest levels of volatility. The Augmented Dickey-Fuller test established stationarity within the price series, while cointegration tests indicated a long-term equilibrium relationship across the markets analyzed in Tamil Nadu. Further examination through the Granger causality test revealed that price movements in the Coimbatore market had a causal impact on the Dindigul market. Additionally, the markets in Coimbatore, Dindigul, and Chennai were shown to exert influence over the Idukki market in Kerala. The Vector Error Correction Model (VECM) analysis demonstrated that in response to disequilibrium across the Coimbatore, Chennai, Dindigul, and Idukki markets, short -run price adjustments occurred at rates of 41%, 45%, 46%, and 48%, respectively, working towards restoring long-run equilibrium. In the Dindigul market, price adjustments with a one-month lag had a notable influence on current prices within Coimbatore, Chennai, and Dindigul. These findings underscore the interconnected nature of small onion markets within the region and shed light on price behavior patterns. Insights derived from this study could inform policy measures aimed at stabilizing prices and enhancing market efficiency in the small onion markets

EFFECT OF GLYCAEMIC CONTROL (HBA1C) ON PULMONARY FUNCTION TESTS (SPIROMETRY) IN PATIENTS WITH TYPE 2 DIABETES MELLITUS

BACKGROUND Diabetes mellitus is a metabolic disorder affecting almost all the organs by its micro and macrovascular complications. Like other organs the respiratory system is also affected by diabetic complications like microangiopathy. Very few studies investigated the complications and the relationship with the duration of the diabetes and glycaemic status. So in this point of view, we planned to study the effect of pulmonary function in our type 2 diabetic patients. AIMS AND OBJECTIVES To study the influence of glycaemic control (based on HbA1c levels) on pulmonary function tests and the correlation between spirometric abnormalities and duration of diabetes in type 2 diabetic patients. MATERIALS AND METHODS 55 type 2 diabetic patients who gave informed consent were recruited. History regarding duration of diabetes, treatment, history suggestive of complications like neuropathy, retinopathy, nephropathy, regular sugar monitoring, exercise, etc. were recorded. BMI was calculated. Chest x-ray was taken for all patients. They underwent spirometry and the predicted and measured values of FEV1, FVC, FEV1/FVC, PEFR, FEF 25-75 for all the patients were recorded. After spirometry, HbA1c estimation was done using ion exchange resin method. Oneway ANOVA, correlation, paired and unpaired-t-test were used for analysis. RESULTS There was significant difference between the mean predicted FVC, FEV1, PEFR, and FEF 25-75, and measured values. The mean of measured spirometric values decreases as the HbA1c increases. There was reducing trend of the spirometric values as HbA1c increases, this was not statistically significant. The incidence of restrictive pattern was more common among the male patients compared with female patients but this was not statistically significant. DISCUSSION AND CONCLUSION: Restrictive pattern was more with increase in duration of diabetes. Out of 55 patients, 33 had probable restriction, 5 had moderate obstruction and 1 had severe obstruction. This may be due to underlying obstructive airway disease and they might have concealed smoking or other history which may attribute to obstruction. Our studies show that increase in HbA1c % values were associated with reduced spirometric values

Effectiveness of clonidine as a preanesthetic drug on intra operative blood loss in oral and maxillofacial surgery: A systematic review

Controlled hypotension during a surgical procedure is a way to decrease blood pressure and subsequently to improve the field of operation. Clonidine is an antihypertensive drug which acts through facilitation of Alph-2 post-synaptic receptors and in addition to its antihypertensive, anti-anxiety and analgesic effects, its beneficial effects in reducing the bleeding during. Correction of maxillomandibular discrepancies may necessitate performing osteotomy on both the jaws in several cases. Bimaxillary orthognathic surgery and rhinoplasty are procedures associated with significant blood making proper hemostasis essential for a surgical field that is free of excessive blood, reduced postoperative swelling, and appropriate surgical results. The aim of this systematic review is to assess the effectiveness of Clonidine as a pre-anesthetic drug on intraoperative blood loss in maxillofacial surgery. The Databases of PubMed, Cochrane and Google scholar were searched for the related topics along with a complimentary manual search of all oral surgery journals till January 2021. Articles were selected based on the inclusion criteria, which included all RCTs. From this study it is concluded that clonidine premedication is effective in reducing intraoperative blood loss as well as providing hemodynamic stability in patients undergoing different maxillofacial surgeries

Effectiveness of clonidine as a preanesthetic drug on intra operative blood loss in oral and maxillofacial surgery

Controlled hypotension during a surgical procedure is a way to decrease blood pressure and subsequently to improve the field of operation. Clonidine is an antihypertensive drug which acts through facilitation of Alph-2 post-synaptic receptors and in addition to its antihypertensive, anti-anxiety and analgesic effects, its beneficial effects in reducing the bleeding during. Correction of maxillomandibular discrepancies may necessitate performing osteotomy on both the jaws in several cases. Bimaxillary orthognathic surgery and rhinoplasty are procedures associated with significant blood making proper hemostasis essential for a surgical field that is free of excessive blood, reduced postoperative swelling, and appropriate surgical results. The aim of this systematic review is to assess the effectiveness of Clonidine as a pre-anesthetic drug on intraoperative blood loss in maxillofacial surgery. The Databases of PubMed, Cochrane and Google scholar were searched for the related topics along with a complimentary manual search of all oral surgery journals till January 2021. Articles were selected based on the inclusion criteria, which included all RCTs. From this study it is concluded that clonidine premedication is effective in reducing intraoperative blood loss as well as providing hemodynamic stability in patients undergoing different maxillofacial surgeries.</jats:p

Deep Learning Applications and Intelligent Decision Making in Engineering

Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great impact on the decision-making process.Deep Learning Applications and Intelligent Decision Making in Engineering is a pivotal reference source that provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is ideally designed for engineers, computer scientists, programmers, software engineers, research scholars, IT professionals, academicians, and postgraduate students seeking current research on the implementation of automation and deep learning in various engineering disciplines.Глубокое обучение включает в себя подмножество машинного обучения для обработки неконтролируемых данных с помощью функций искусственной нейронной сети. Основным преимуществом глубокого обучения является обработка больших объемов данных для лучшего анализа и самоадаптивные алгоритмы для обработки большего объема данных. Применительно к инженерному делу глубокое обучение может оказать огромное влияние на процесс принятия решений. Приложения глубокого обучения и интеллектуальное принятие решений в инженерии - это ключевой справочный источник, который обеспечивает практическое применение глубокого обучения для улучшения методов принятия решений и создания интеллектуальных сред. Освещая такие темы, как интеллектуальный транспорт, электронная коммерция и киберфизические системы, эта книга идеально предназначена для инженеров, специалистов по информатике, программистов, разработчиков программного обеспечения, научных работников, ИТ-специалистов, академиков и аспирантов, которые ищут актуальные исследования по внедреИспользуемые программы Adobe Acroba

Superior thyroid artery injury following foreign body ingestion in an intellectually disabled patient: A case report

This case report highlights complexities in an intellectually disabled adult who ingested a chicken bone, resulting in a rare complication—superior thyroid artery injury. Presentation, diagnostic challenges, and a multidisciplinary approach are detailed. Initial attempts at esophagoscopy under general anesthesia were hindered by blood coughing, leading to a change of plan. Subsequent findings revealed mucosal edema and continuous bleeding from the site. Challenges in anesthetizing intellectually disabled individuals are emphasized, stressing tailored induction methods. The case concluded with successful embolization but developed neurological complication which was successfully managed showcasing the significance of a collaborative and adaptable approach

Predictive analysis, data visualization and artificial intelligence tools for agricultural research and communication

Data Science offers powerful tools that predict and promise to enhance crop yields, optimize the farm resource utilization. Artificial Intelligence (AI) can perform tasks that typically require human intelligence, which encompasses a wide range of applications in agriculture starting from seed selection to robotic harvest. Synergy between data science and AI will grow strong to drive technological advancements and shape the future of agriculture sector. This paper presents application of few data science and AI tools in agriculture. Trends, patterns and variations in cost, benefit and returns from crop like Paddy, Groundnut, Sugarcane, Cotton and Maize across different states from 2011 to 2020 were analysed through data visualization. An experimental attempt was also made through web scrapping to understand the United States consumer preference towards the brands (Spice Train, Tellicherry), quantity (11 and 14 oz) and price (15-25 USD package) of pepper. Predictive modeling had shown that the export of pepper may fluctuate over the years while export of basmati rice, cashew nuts and tea will gradually increase for the next few years. High-definition images of tomatoes of different shape, colour, size were used to train the algorithm and tested for identification and classification of tomatoes and images of FAW infested maize were trained and tested for deduction accuracy, which was 82.5 %. Prediction accuracy will increase when the algorithm is trained with large number of images. AI avatars are widely used in social communication for various purposes like short communications, storytelling and documentation, which will be also used effectively for agricultural research communication and learning purposes