Enhancing Weather Recognition Using Transfer Learning Approach

This research highlights the crucial role of accurate weather classification in industries such as autonomous vehicles and intelligent transportation. Manual classification methods are often time-consuming and prone to errors, while online weather forecasts may not provide real-time accuracy. To address these challenges, the study harnesses the power of Convolutional Neural Networks (CNNs) with the invaluable technique of transfer learning. By using transfer learning, pre-trained models (MobileNetV2 and VGG19) are fine-tuned to classify weather images into categories like Shine, Rain, Sunrise, and Cloudy.   The key significance of transfer learning lies in its ability to leverage knowledge from large datasets, such as ImageNet, to enhance the accuracy and efficiency of weather classification. The results of this study affirm the potential of transfer learning, with MobileNetV2 achieving an impressive accuracy rate of 94.65%, and VGG19 performing strongly at 92.88%. This underscores the critical role of transfer learning in improving weather classification, ultimately providing more reliable weather information for diverse applications and industries. In essence, transfer learning contributes to advancing autonomous systems, outdoor vision solutions, and intelligent transportation, thereby enhancing the quality of life and safety for individuals and communities

Impact of Terrorism on Exclusive Indian Economy

The objective of this study is to investigate at what extent Indian economy becomes the victim of terrorism activities. However, we didn’t find any comprehensive study on this issue, who used time series data for casual investigation between terrorism and economic growth. This study used time series data from 1994 to 2017 to examine the impact of terrorism attacks and their impact on Indian economy. The data analysis has done through auto regressor distributed lags (ARDL) method. The long run results revealed that terrorism, interest rate and unemployment have negative impact on economic growth, whereas net trade and foreign direct investment have positive impact on growth level. While in short run only terrorism has negative relationship on Indian economy and rest of all variables are statistically significant. Furthermore, error correction mechanism and stability tests indicate that model is consistence and efficient. The overall results through F-test concluded with these remarks that model is statistically significant

Low-field magnetic resonance imaging in a boy with intracranial bolt after severe traumatic brain injury: Illustrative case

Background: Conventional magnetic resonance imaging (cMRI) is sensitive to motion and ferromagnetic material, leading to suboptimal images and image artifacts. In many patients with neurological injuries, an intracranial bolt (ICB) is placed for monitoring intracranial pressure (ICP). Repeated imaging (computed tomography [CT] or cMRI) is frequently required to guide management. A low-field (0.064-T) portable magnetic resonance imaging (pMRI) machine may provide images in situations that were previously considered contraindications for cMRI.Observations: A 10-year-old boy with severe traumatic brain injury was admitted to the pediatric intensive care unit, and an ICB was placed. Initial head CT showed a left-sided intraparenchymal hemorrhage with intraventricular dissection and cerebral edema with mass effect. Repeated imaging was required to assess the brain structure because of continually fluctuating ICP. Transferring the patient to the radiology suite was risky because of his critical condition and the presence of an ICB; hence, pMRI was performed at the bedside. Images obtained were of excellent quality without any ICB artifact, guiding the decision to continue to manage the patient conservatively. The child later improved and was discharged from the hospital.Lessons: pMRI can be used to obtain excellent images at the bedside in patients with an ICB, providing useful information for better management of patients with neurological injuries

RPA-Based colorimetric detection of SARS-Cov-2 (Covid-19) and its physiological effects

The SARS-CoV-2 coronavirus outbreak is extremely concerning and poses a threat to the public health system. SARS-CoV-2 is a pathogen that affects people and caused fever, dry cough, dizziness and severe respiratory disease. By media time, greater than 662 million people were infected and 6.6 million people were died globally. The pandemic coronavirus was hurt the third world countries due to weak health infrastructure. A timely response is crucial for commercially and easily accessible resources since an actual pandemic emergency does not provide the necessary timescale for the test of innovative ways. Coronavirus SARS-CoV-2 was infected individuals without any indication and could still transfer the virus to others. The success of the quarantine effort during the SARS-CoV-2 eruption depended heavily on the identification of the infectious agent. It is thus urgent to develop a rapid and accurate detection method for coronavirus SARS-CoV-2 and control the disease spreading. Here demonstrated an isothermal based SARS-CoV-2 amplification with quick colorimetric detection. The inorganic phosphate (Pi) was detected via colorimetric technique from SARS-CoV-2 after amplification by using the basic recombinase polymerase amplification (RPA) technique.&nbsp

The Critical Role of Zinc in Plants Facing the Drought Stress

Drought stress affects plant growth and development by altering physiological and biochemical processes resulting in reduced crop productivity. Zinc (Zn) is an essential micronutrient that plays fundamental roles in crop resistance against the drought stress by regulating various physiological and molecular mechanisms. Under drought stress, Zn application improves seed germination, plant water relations, cell membrane stability, osmolyte accumulation, stomatal regulation, water use efficiency and photosynthesis, thus resulting in significantly better plant performance. Moreover, Zn interacts with plant hormones, increases the expression of stress proteins and stimulates the antioxidant enzymes for counteracting drought effects. To better appraise the potential benefits arising from optimum Zn nutrition, in the present review we discuss the role of Zn in plants under drought stress. Our aim is to provide a complete, updated picture in order to orientate future research directions on this topic

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population.The aim of this study was to inform vaccination prioritization by modelling the impact of vaccination on elective inpatient surgery. The study found that patients aged at least 70 years needing elective surgery should be prioritized alongside other high-risk groups during early vaccination programmes. Once vaccines are rolled out to younger populations, prioritizing surgical patients is advantageous