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Abstract Background The Surgical Tool for Auditing Records scoring system [STAR] focuses on surgical record auditing with promising outcomes. It offers a structured approach to evaluating the quality of surgical notes. Aims and objectives This study aimed to assess the effectiveness of the STAR in evaluating oral surgical records and identifying areas for improvement in documentation practices. Materials and methods The data was obtained from the Dental Information Archival Software (DIAS) of our institution. The sample size was determined using G*Power 3.1.9.4 software. Fifty consecutive oral surgery clinical records of oral squamous cell carcinoma patients were evaluated using STAR. Each record was reviewed for adherence to documentation standards including Initial Assessment (10 points), Follow-up Entries (8 points), Consent Documentation (7 points), Anesthesia Report (7 points), Surgical Log (9 points), and Discharge Synopsis (9 points). compiling a total STAR score (50 points). The data was tabulated in Google Sheets. The descriptive statistics with inter-observer agreement and the mean score were recorded. Results We observed that each of the 50 records received a score of 49/50 points on the STAR. Deductions were necessary in the Operative record section due to the lack of information regarding the sutures used. Conclusion To summarize, this study emphasizes the effectiveness of the STAR scoring system in evaluating the quality of oral surgical records. Identifying deficiencies, particularly in documenting operative details, can improve the completeness and accuracy of patient records. It can ultimately enhance patient care and facilitate better communication among healthcare professionals.

Abstract Adaptive information seeking is essential for humans to effectively navigate complex and dynamic environments. Here, we developed a gaze-contingent eye-tracking paradigm to examine the early emergence of adaptive information-seeking. Toddlers (N = 60, 18-36 months) and adults (N = 42) either learnt that an animal was equally likely to be found in any of four available locations, or that it was most likely to be found in one particular location. Afterwards, they were given control of a torchlight, which they could move with their eyes to explore the otherwise pitch-black task environment. Eye-movement data and Markov models show that, from 24 months of age, toddlers become more exploratory than adults, and start adapting their exploratory strategies to the information structure of the task. These results show that toddlers’ search strategies are more sophisticated than previously thought, and identify the unique features that distinguish their information search from adults’.

Background: The COVID-19 pandemic has exacerbated mental health challenges among medical students, already a vulnerable group to mental health disorders. Recent evidence underscores a significant rise in anxiety, depression, and stress among this demographic globally, necessitating a deeper understanding of their mental health status and effective interventions. Objective: This study aims to assess the socio-demographic profile, prevalence rates of depression, anxiety, and stress, as well as coping strategies employed by medical students during the COVID-19 pandemic, with a focus on identifying effective interventions for managing their mental health crises. Methods: A cross-sectional study was conducted among 1st to 4th year MBBS students at ACSR Government Medical College, Nellore, during August and September 2020. Data were collected online using Google Forms, incorporating demographic details and the Depression, Anxiety, and Stress Scale (DASS-21). Descriptive statistics and chi-square tests were utilized for data analysis. Results: The study included 400 participants, 57% of whom were female, with a mean age of 23 ± 2 years. Significant proportions reported experiencing depression (20.2%), anxiety (13%), or stress (51.3%), with notable rates of past psychiatric symptoms. Coping mechanisms included video chatting (35%) and online entertainment (32.2%), while professional help utilization was low (5.5%). COVID-19 repercussions extended beyond mental health, impacting various facets of daily life. Conclusion: This study found various mental health challenges faced by medical students during the pandemic, emphasising the need for ongoing monitoring and psychological support. Additionally, a low rate of seeking professional help was found. Early training in handling pandemic-like situations and mental health is recommended. However, further research is necessary to track mental health progression and ensure accurate diagnosis through individual clinical assessments.

In agricultural scenario, chitosan, a naturally occurring biopolymer derived from chitins, has the ability to function as both a bio-stimulant and an elicitor. Chitosan is produced from chitins. It is suitable for a wide range of uses because it is non-toxic, does not contaminate the environment, and is biocompatible with living things. It improves physiological reactions and lessens the negative effects of abiotic stimuli through the stress transduction pathway and the use of secondary messengers. Through nitric oxide and hydrogen peroxide-based signalling pathways, chitosan treatment activates antioxidant enzymes. Additionally, it stimulates the production of organic acids, carbohydrates, amino acids, and other metabolites needed for osmotic regulation, stress signalling, and other processes. Additionally, it can combine with heavy metals to produce compounds, and it is used in both phytoremediation and biological remediation of polluted soil. Additionally, this is applied topically to a variety of plants as an anti-transpirant agent, which reduces the quantity of water needed while also providing protection from other negative effects. Due of chitosan's exceptional properties and the way the climate is changing, sustainable farming practises are increasingly incorporating it. Our study is a compendium of current chitosan research that emphasises abiotic stress reactions. These responses could be helpful in upcoming initiatives to increase crop productivity.

Key Clinical Message This case demonstrates an atypical presentation of choledochal cysts (CDCs) and elaborates on the diagnostic challenges encountered when presented with CDCs in adulthood, as it principally presents in children. Abstract A choledochal cyst is a rare congenital anomaly characterized by cystic dilations in the extrahepatic and intrahepatic biliary trees. These cysts are classified according to their location and characteristics. This case study aims to demonstrate how nonspecific clinical features can pose a diagnostic dilemma when presented in adults. Additionally, the case report provides an overview of diagnostic methods and treatment options. In this case, we discuss a 50‐year‐old female who presented with a 2‐ to 3‐day history of severe colicky pain in the right upper quadrant of her abdomen without any other symptoms or abnormal laboratory tests. In addition to ultrasonography evidence of CBD dilation and cholelithiasis, MRCP results confirmed the diagnosis. She underwent surgical intervention involving cyst excision, a Roux‐en‐Y hepatojejunostomy, and a cholecystectomy. The postoperative period was without significant complications. The case presented here illustrates the potential outcomes for individuals who present with choledochal cysts during adulthood. Often, these cases present with vague symptoms or as the underlying cause of a more severe condition. This case contributes to the existing knowledge of choledochal cysts by providing insight into the clinical presentation, diagnostic methods, and treatment options.

Nanofabrication is an integral part of the realization of advanced functional devices ranging from optical displays to memory devices. Focused-ion beam (FIB) milling is one of the most widely used nanofabrication methods. Conventionally, FIB milling has been carried out for patterning single-phase stable thin films. However, the influence of FIB milling on the phase separation of metastable alloy films during subsequent treatments has not been reported. Here, we show how FIB milling of Ag–Cu thin films influences the separation process and microstructure formation during post-milling annealing. The phase-separated microstructure of the film consists of fine, randomly distributed Ag-rich and Cu-rich domains, whereas adjacent to milled apertures (cylindrical holes), we observe two distinctly coarser rings. A combination of imaging and analysis techniques reveals Cu-rich islands dispersed in Ag-rich domains in the first ring next to the aperture, while the second ring constitutes mostly of Ag-rich grains. Copper silicide is observed to form in and around apertures through reaction with the Si-substrate. This substrate interaction, in addition to known variables like composition, temperature, and capillarity, appears to be a key element in drastically changing the local microstructure around apertures. Thus, the current study introduces new avenues to locally modulate the composition and microstructure through an appropriate choice of the film-substrate system. Such an ability can be exploited further to tune device functionalities for possible applications in plasmonics, catalysis, microelectronics, and magnetics.

Background Menstrual cup is a reusable, cost-effective, user-friendly and environmentally friendly menstrual hygiene management method which can become a sustainable alternative to disposable sanitary pads. But its use is less among women due to lack of awareness and availability. The objective of this study is i) to assess the awareness of menstrual cup among reproductive age women ii) to estimate the proportion of menstrual cup users among the participants and iii) to assess the perception about menstrual cup among users and non-users.

The clinical management of oral cancer is often frequented with challenges that arise from relapse, recurrence, invasion and resistance towards the cornerstone chemo and radiation therapies. The recent conceptual advancement in oncology has substantiated the role of cancer stem cells (CSC) as a predominant player of these intricacies. CSC are a sub-group of tumor population with inherent adroitness to self-renew with high plasticity. During tumor evolution, the structural and functional reprogramming persuades the cancer cells to acquire stem-cell like properties, thus presenting them with higher survival abilities and treatment resistance. An appraisal on key features that govern the stemness is of prime importance to confront the current challenges encountered in oral cancer. The nurturing niche of CSC for maintaining its stemness characteristics is thought to be modulated by complex multi-layered components encompassing neoplastic cells, extracellular matrix, acellular components, circulatory vessels, various cascading signaling molecules and stromal cells. This review focuses on recapitulating both intrinsic and extrinsic mechanisms that impart the stemness. There are contemplating evidences that demonstrate the role of transcription factors (TF) in sustaining the neoplastic stem cell’s pluripotency and plasticity alongside the miRNA in regulation of crucial genes involved in the transformation of normal oral mucosa to malignancy. This review illustrates the interplay between miRNA and various known TF of oral cancer such as c-Myc, SOX, STAT, NANOG and OCT in orchestrating the stemness and resistance features. Further, the cross-talks involved in tumor micro-environment inclusive of cytokines, macrophages, extra cellular matrix, angiogenesis leading pathways and influential factors of hypoxia on tumorigenesis and CSC survival have been elucidated. Finally, external factorial influence of oral microbiome gained due to the dysbiosis is also emphasized. There are growing confirmations of the possible roles of microbiomes in the progression of oral cancer. Given this, an attempt has been made to explore the potential links including EMT and signaling pathways towards resistance and stemness. This review provides a spectrum of understanding on stemness and progression of oral cancers at various regulatory levels along with their current therapeutic knowledge. These mechanisms could be exploited for future research to expand potential treatment strategies.

Electric vehicles (EVs) are crucial for reducing greenhouse gas emissions and promoting sustainable transportation. However, optimizing energy management in EVs is challenging due to the variability in driving conditions and the impact of battery degradation. This paper proposes an advanced energy management and control strategy that accounts for these factors, aiming to enhance both vehicle performance and battery longevity. We integrate real-time data on driving conditions with detailed battery degradation models to develop a comprehensive control framework. Our methodology employs a combination of rule-based and optimization-based algorithms to dynamically adjust energy usage, ensuring optimal performance under diverse driving scenarios. Our strategy significantly improves energy efficiency and mitigates battery degradation compared to conventional approaches. Specifically, findings show an increase in overall driving range and a reduction in battery wear. Additionally, a sensitivity analysis underscores the robustness of our approach across different driving conditions and battery states. This research offers critical insights for the development of next-generation EV energy management systems, promoting longer-lasting and more efficient electric vehicles. Future work will focus on real-world testing and further refinement of the control algorithms to ensure practical applicability and enhanced performance in varied driving environments.

Mental health issues can be adverse to an individual, especially for students who are involved in numerous activities on a daily basis. Students today frequently experience stress. 4 in 5 college students report frequent stress, according to the American Institute of Stress. There are several indications of stress, including sweating, headaches, difficulty concentrating, changes in appetite, reduced immune system, difficulty sleeping, etc. Long-term effects of stress may be chronic. Chronic stress has negative effects on health, including memory loss, hypertension, and it may have negative it's overlooked, cardiovascular disease. If psychological and physical consequences to addiction, that depression, suicide, etc. In order to prevent further effects, it is crucial to identify it early. The proposed system is to design a PCB for the wristband that detects whether the student is experiencing stress or not based on various physiological parameters like heart rate, temperature of the human body, mobility and skin response. Real time data is collected from Electrocardiogram (ECG), Galvanic Skin Response (GSR), Accelerometer sensors etc. An ESP32 microcontroller processes and analyzes the data gathered from various sensors to continuously detect stress.

Background: The spread of COVID-19 infection paved way to many admissions into hospitals worldwide exhausting the healthcare systems. A simple test for immediate stratification of risk in patients with infection by COVID 19 virus is important. Aim in this study was to know the prognostic value of neutrophil to lymphocyte ratio (NLR) in determination of the severity of infection in COVID-19 infected patients. Methods: This study was conducted in a tertiary care institute, Mandya. Clearance from Institutional Ethical committee was taken. Data from 108 COVID-19 infected hospitalized patients between April 2021 and June 2021 were collected retrospectively from hospital records. Patients in the study were grouped into two groups as Intensive Care Unit (ICU) and Ward (Non ICU) patients, based on admission into ICU. The patient’s demographic characteristics, comorbidities, clinical manifestations, medications used and investigations done initially during admission were noted from the hospital files for both groups. Chi-square test/ Fisher's exact test was used for comparison of categorical outcomes. Statistical significance was noted if P value < 0.05. Results: Of 108 patients, 25 patients (23.15%) had ICU admission. Patients aged >55years had more ICU admission (44%) than non-ICU admissions (22.89%). In patients

Background: Mental health of a medical student remains affected throughout training due to long study and working hours, extensive course content, examinations, peer competition, uninspiring environments, sleep deprivation. Objectives of this study is to estimate the proportion of Depression, Anxiety and Stress among Women medical undergraduate students and to determine the association between the Depression, Anxiety, Stress and Socio demographic factors among Women medical undergraduate students. Materials and methods: This were a cross sectional Study conducted among First, second, third and fourth year MBBS students of SVIMS - Sri Padmavathi Medical College for Women, Tirupati, Andhra Pradesh. Medical students who were present and willing to participate voluntarily on the day of data collection were included. Sample size calculated was 375. Information collected was socio-demographic details and Depression Anxiety Stress scale [DASS 42] was used to assess depression, anxiety and stress levels. Results: The present study assessed Depression, Anxiety and Stress among 588 medical undergraduates, by using DASS 42 scale which revealed prevalence of depression was 34.7%, anxiety 44% and stress 30.3% and their association year of study, not satisfied, partially satisfied with own education, less consumption water, less sleeping hours and hours of usage of gadgets. Conclusion: The present study found that prevalence of depression 34.7%, anxiety 44% and stress 30.3% among medical undergraduates. Medical students under strain are either unaware of their situation or reluctant to seek help.

Zero-crossing point detection in a sinusoidal signal is essential in the case of various power systems and power electronics applications like power system protection and power converters controller design. In this paper, 96 data sets are created from a distorted sinusoidal signal based on MATLAB simulation. Distorted sinusoidal signals are generated in MATLAB with various noise and harmonic levels. In this paper, a decision tree classifier is used to predict the zero crossing point in a distorted signal based on input features like slope, intercept, correlation and Root Mean Square Error (RMSE). Decision tree classifier model is trained and tested in the Google Colab environment. As per simulation results, it is observed that decision tree classifier is able to predict the zero-crossing points in a distorted signal with maximum accuracy of 98.3 % for noise signals and 100 % for harmonic distorted signals.

Interphotoreceptor retinoid-binding protein (IRBP) is an abundant glycoprotein in the subretinal space bound by the photoreceptor (PR) outer segments and the processes of the retinal pigmented epithelium (RPE). IRBP binds retinoids, including 11-cis-retinal and all-trans-retinol. In this study, visual function for demanding visual tasks was assessed in IRBP knock-out (KO) mice. Surprisingly, IRBP KO mice showed no differences in scotopic critical flicker frequency (CFF) compared to wildtype (WT). However, they did have lower photopic CFF than WT. IRBP KO mice had reduced scotopic and photopic acuity and contrast sensitivity compared to WT. IRBP KO mice had a significant reduction in outer nuclear layer (ONL) thickness, PR outer and inner segment, and full retinal thickness (FRT) compared to WT. There were fewer cones in IRBP KO mice. Overall, these results confirm substantial loss of rods and significant loss of cones within 30 days. Absence of IRBP resulted in cone circuit damage, reducing photopic flicker, contrast sensitivity, and spatial frequency sensitivity. The c-wave was reduced and accelerated in response to bright steps of light. This result also suggests altered retinal pigment epithelium activity. There appears to be a compensatory mechanism such as higher synaptic gain between PRs and bipolar cells since the loss of the b-wave did not linearly follow the loss of rods, or the a-wave. Scotopic CFF is normal despite thinning of ONL and reduced scotopic electroretinogram (ERG) in IRBP KO mice, suggesting either a redundancy or plasticity in circuits detecting (encoding) scotopic flicker at threshold even with substantial rod loss.

Background and study aims Data are lacking on the natural history of gastrointestinal tract schwannomas. We aimed to study the natural history of all gastrointestinal schwannomas including location, diagnosis, management, and long-term outcomes. Patients and methods Patients with a pathological diagnosis of gastrointestinal schwannoma between January 2000 and March 2020 were identified. Data on baseline demographics, presentations, associated malignancies, malignant transformation, treatment, and recurrence were collected. Results Our cohort consisted of 44 patients with a mean age of 58.6 years, with 63.6 % women and 84.1 % White. The stomach (38.6 %) was the most common location followed by the colorectum (31.8 %). Only 22.7 % of patients were symptomatic and 22.0 % had a personal history of other malignancies. Tissue diagnosis was obtained via endoscopy in 47.7 % and from surgical pathology in 52.3 %. On histology, 65.9 % of the tumors were solid, 11.4 % had mixed features, and 2.3 % had necrosis. SP100 was tested in all but one patient and was positive in all. Mean Ki-67 in 12 patients with tumors measuring ≥ 2 cm was 3.0 % indicating a low proliferation rate. Of the patients, 77.3 % had surgery and 18.2 % underwent endoscopic resection. At a mean follow-up of 5.0 ± 4.31 years, there was no malignant transformation, recurrence or mortality associated with gastrointestinal schwannomas. Conclusions Gastrointestinal schwannomas are diagnosed in the fifth to sixth decade with predominance in women and Whites. They are benign, mostly asymptomatic, and diagnosed incidentally. Asymptomatic gastrointestinal schwannomas including lesions ≥ 2 cm in size do not appear to need further monitoring or intervention. Patients with them should be counseled to remain up to date with routine screening guidelines pertaining to the colon, breast, and lung cancer due to the high incidence of concomitant malignancy.

Background: Dysmenorrhoea is a common problem during menses in adolescent girls which affects their quality of life, academic activities, cannot attend social functions and use over the counter medicines which may lead to dangerous adverse effects and infertility. Objectives: 1. To study the prevalence of dysmenorrhea in adolescent girls studying in government municipal high schools of Tirupati. 2.To determine the significant factors related to menstrual distress in adolescent girls. Methodology: A cross-sectional study conducted among 320 adolescent girls studying in the selected government high schools of Tirupati, India. The study investigated symptoms, related factors and consequences of menstrual distress in adolescent girls with dysmenorrhea. Four instruments were used to collect data: Questionnaires on Demographic Data, Menstrual Distress Questionnaire, A Questionnaire related to Menstrual characters and A Short Form McGill Pin Questionnaire. Results: Prevalence of dysmenorrhoea among adolescent girls was found 67.7%. Regression analysis indicated that the best subset for predicting menstrual distress in adolescent girls included MPQ-SF, menstrual cycle in days, socioeconomic status and education. Conclusions: Majority (67.7%) of the adolescent girls were suffering with dysmenorrhoea. Menstrual distress is significantly correlated with impact on daily activities, absence from class, and analgesic usage.

Parotid swellings presenting with facial nerve palsy usually imply that the swelling is malignant in nature. In rare cases, it has been reported to have occurred in the setting of benign parotid swellings and parotid abscesses. Our case is one of bilateral parotid abscesses in a reverse transcription polymerase chain reaction negative, CORADS five patients, with left-sided lower motor neuron type of facial nerve palsy with near-total recovery of the facial nerve palsy after resolution of abscess. The likely mechanisms behind the development of facial nerve palsy in case of parotid abscess include perineuritis, ischemia, and direct virulence of the pathogen. Furthermore, coronavirus has a propensity for affecting salivary glands, and parotitis could be an atypical presentation of the COVID 19. In most cases, as in ours, there has been improvement of facial nerve palsy with resolution of the abscess after combined conservative, surgical, and supportive treatment.

With the emergence of novel thermally accelerated methods, the area of material science has undergone a paradigm shift, opening up previously unimaginable possibilities for the creation of next-generation materials with improved properties and functionalities. In order to shape the materials of the future, this paper explores the ground-breaking uses of thermally accelerated techniques such quick thermal annealing, spark plasma sintering, and laser-assisted deposition. Due to sluggish diffusion rates and incomplete reactions, traditional materials synthesis and processing processes frequently have trouble producing materials with the appropriate characteristics. This allows for accurate atomic-level manipulation of material microstructures. The engineering of materials with specific mechanical, electrical, thermal, and optical properties is made possible by the fine-tuning of microstructures. The importance of thermally accelerated processes in a variety of material classes, including metals, ceramics, polymers, and composites, is highlighted in this research. The use of thermally enhanced processes shows potential in promoting sustainable practises, as materials play a crucial part in addressing global concerns. These procedures help to reduce waste and conserve resources by enabling the effective recycling and upcycling of materials through controlled thermal treatments. The report also highlights the potential effects of thermally enhanced techniques on future industries such as flexible electronics, renewable energy systems, and medicinal devices, where specialised materials with outstanding performance are crucial.

Background and Aim The United Kingdom‐primary biliary cholangitis (UK‐PBC) and global primary biliary cholangitis group (GLOBE) prognostic models have been recently developed to predict long‐term outcomes in primary biliary cholangitis (PBC). However, these predictive scores have not yet been well evaluated in the U.S. population. Methods We retrospectively reviewed newly diagnosed PBC patients at the Cleveland Clinic between November 1998 and February 2017. Adverse events were defined as liver transplantation, liver‐related mortality, and all‐cause mortality. Transplant‐free survival (TFS) was estimated using the Kaplan–Meier method. Predictive performances of all prognostic models were evaluated using the C‐statistic. Results We identified 352 patients who used ursodeoxycholic acid therapy. Of them, 311 (88.4%) only had PBC, while 41 (11.6%) were diagnosed with PBC‐autoimmune hepatitis overlap. A total of 22 (6%), 47 (13%), and 55 (16%) patients had adverse events within 5, 10, and 15 years after diagnosis, respectively. In patients with PBC only, the C‐statistic in predicting 15‐year adverse events was 0.75 per GLOBE compared to 0.74 per UK‐PBC (P = 0.94), 0.73 per Rotterdam (P = 0.44), 0.66 per Barcelona (P = 0.004), 0.65 per Paris 1 (P = 0.005), 0.62 per Paris 2 (P

Background: “Self-adhering composite resins,” are claimed to eliminate the need for a separate acid etching and bonding agent application step, thus simplifying the direct restorative procedure, both regarding the technique sensitivity and the duration of treatment. Aim: The aim of this study is to evaluate the marginal adaptation of self-adhering flowable composite (Dyad flow) in comparison to the conventional flowable composite (Tetric N-flow) under scanning electron microscope (SEM). Settings and Design: This in vitro study was conducted on 44 extracted human maxillary premolars. Materials and Methods: Box-only Class II cavities on the distal surface were prepared with the dimensions of 4 mm buccolingual width, 2 mm mesiodistal depth, and gingival margin at the cementoenamel junction. They were divided into two groups of 22 teeth each and were restored accordingly: Group I – Gingival floor lined with Tetric N-Flow and were restored with Tetric N-Ceram; Group II – Gingival floor lined with Dyad flow and were restored with Herculite Precis. After thermal cycling, the sectioned tooth-restoration interfaces were evaluated for the marginal adaptation under SEM at ×200 magnification. Statistical Analysis Used: The resultant data were statistically analyzed by applying Chi-square test, using the SPSS (version 16.0) software. Results and Conclusion: There was no statistically significant difference between the study groups regarding the marginal adaptation. The marginal adaptation of the self-adhering flowable composite when used as a liner in Class II restorations was comparable to that of the conventional flowable composite.

Feeding behaviour is a complex behaviour in the present daily life which is regulated by many mechanisms. So many factors influence the feeding behaviour, among the most common one, is stress. So in the present review authors tried to explain about feeding behaviour, factors regulating it, stress and its probable causes.

Ulcerative colitis (UC) is a chronic systemic inflammatory condition primarily involving the large bowel mucosa with relapsing and remitting episodes. It is also associated with multiple extra-intestinal manifestations [EIM], including skeletal muscle involvement which is rare. Review of the literature reported only a few cases of inflammatory myositis in association with UC. We report an unusual presentation of recurrent inflammatory myositis of lower extremities in a 28-year-old male with quiescent UC and on long-term mesalamine therapy.

World Health Organization (WHO) reported that indoor air pollution is one of the ten avoidable risk factors. People believe that air pollution is an outside urban phenomenon, but some of the uppermost concentration occurs in the opposite situation i.e., countryside and in the house. Such levels are due to the high proportion of countryside/less developed countries population relies on unprocessed biomass fuels (like wood, crop residues, dung) which have high pollutant emission factors, in simple small scale burning devices such as household cooking. Domestic cooking is one among the major activities of the rural Indian house wives. Cooking is carried out in an enclosed space with poor ventilation and inefficient stoves. Long duration of exposure to biomass fuel mostly affects women, young girls and children. In most of the developing countries biomass fuel is used for cooking. Girls start cooking at very early age and spend minimum 4-6 hours daily in kitchen for almost 30-40 years which is equivalent to 60,000 hours of exposure. Indoor air pollution occurs primarily by usage of biomass fuels which attributes 1.5-2 million deaths/year.

Crop yield forecasting mainly focus on the domain of agriculture research which has a great impact on making decisions like import-export, pricing and distribution of respective crops. Accurate predictions with well timed forecasts is very important and is a tremendously challenging task due to numerous complex factors. Mainly crops like wheat, rice, peas, pulses, sugarcane, tea, cotton, green houses etc. can be used for crop yield prediction. Climatic changes and unpredictability influence mainly on crop production and maintenance. Forecasting crop yield well before harvest time can help farmers for selling and storage. Agriculture deals with large datasets and knowledge process. Many techniques are there to predict the crop yield. Farmers are benefited commercially by these predictions. Factors such as Geno type, Environment, Climatic conditions and Soil types used in predicting the Yield. For predicting accurately we need to know the fundamental understanding and relationship between the interactive factors and the yield to reveal the relationships between the datasets which are comprehensive and powerful algorithms. Based on the study of various survey papers it has been found that in all the crop predictions, various deep learning, machine learning and ANN algorithms implemented to predict yield forecast and the results are analyzed.

Today we all are suffering from Covid-19, a novel virus and it is the most harmful disease across the world which mainly comes under the domain of health care research. Healthcare system gives importance to health states of the population or individual. Healthcare plays a vital role in promoting physical and mental health and well- being of people around the world. Efficient health care system leads to country’s economy, industrialization and development. Corona virus is dangerous animal and human pathogens and it is threatening people by spreading all over the world. Corona virus patients mostly suffer from lung infection studies have shown it clinically. We proposed detailed analysis on how to predict the expected death, recovered and confirmed cases based on the available data across the world using various machine learning models. Especially we constructed linear regression model (LRM), support vector machine model (SVMM) and polynomial regression models (PRM) and predicted future expected cases over a period of next 15 days. The error between the predicted model and official data curve is quite small in the process of transmission in data modeling. Compare to other models Polynomial regression model performs best prediction of corona positive cases. Forward prediction and backward inference of the epidemic helps to take decisions for necessary actions during Covid-19 propagation.

Prediction of Crop yield focuses primarily on agriculture research which will have a significant effect on making decisions such as import-export, pricing and distribution of specific crops. Predicting accurately with well-timed forecasts is important, but it is a difficult task due to numerous complex factors. Mostly crops like wheat, rice, peas, pulses, sugar cane, tea, cotton, green houses, corn, and soybean can all be used to forecast crop yields. We considered corn dataset to predict the yield for 13 different states in United States. Crop development and progression are strongly affected by climatic changes and unpredictability. Predicting crop yield well before harvest time will support farmers for selling and storing their crops. Agriculture involves large datasets and knowledge processes. Factors such as Weather Components, Soil Components, Management practices, genotype and their interactions are used in predicting Corn Yield. Precise crop growth generally necessitates a complete overview of the functional correlations between yield and all these interactive variables, which necessitates the use of large datasets and complex algorithms to demonstrate. Various Machine Learning models, Deep Learning models, and Artificial Neural Network algorithms are used for predicting. Deep Neural Network Models such as Convolution Neural Networks (CNN), Spiking Neural Networks (SNN), and Recurrent Neural Networks (RNN) are used to assess corn yield. Integrating CNN, RNN and SNN models outperformed than individual model performance.

Electro mechanical impedance technique has garnered major significance in structural health monitoring field by integrating with information and sensing technology. Technical advancements in automated smart devices improved the diagnostic evaluation of this monitoring method by incorporating piezoelectric materials. The optimistic coupling property of these materials enhanced the life span of structural members by detecting damages at incipient stage. The intervention of piezoelectric transducers has created potential applications for impedance approach in assessing the structural performance with high feasibility. The present work aims at estimating the service life of simply supported smart beam using piezoelectric sensors in Abaqus Simulia software. Corrosion is deployed at a uniform rate in reinforced concrete beam with impressed current flow and the loss in diameter of rebar is calculated using Faraday’s electrochemical equation. With frequency domain based impedance technique numerical analysis is conducted on the modeled beams by exciting the sensor with an external harmonic force and the output electric responses of different piezoelectric locations are captured. The steady state dynamic responses for different cases are compared and quantified with a statistical damage algorithm in MATLAB. The resulted cross correlation indices are analyzed to prevent further deterioration of the corroded beams by setting a limit value. The proposed simulation technology is capable of estimating the residual life span of damage structures with cross correlation analysis.

Dehydrodolichyl diphosphate synthase (DHDDS) is required for protein N-glycosylation in eukaryotic cells. A K42E point mutation in the DHDDS gene causes an autosomal recessive form of retinitis pigmentosa (RP59), which has been classified as a congenital disease of glycosylation (CDG). We generated K42E Dhdds knock-in mice as a potential model for RP59. Mice heterozygous for the Dhdds K42E mutation were generated using CRISPR/Cas9 technology and crossed to generate DhddsK42E/K42E homozygous mice. Spectral domain-optical coherence tomography (SD-OCT) was performed to assess retinal structure, relative to age-matched wild type (WT) controls. Immunohistochemistry against glial fibrillary acidic protein (GFAP) and opsin (1D4 epitope) was performed on retinal frozen sections to monitor gliosis and opsin localization, respectively, while lectin cytochemistry, plus and minus PNGase-F treatment, was performed to assess protein glycosylation status. Retinas of DhddsK42E/K42E mice exhibited grossly normal histological organization from 1 to 12 months of age. Anti-GFAP immunoreactivity was markedly increased in DhddsK42E/K42E mice, relative to controls. However, opsin immunolocalization, ConA labeling and PNGase-F sensitivity were comparable in mutant and control retinas. Hence, retinas of DhddsK42E/K42E mice exhibited no overt signs of degeneration, yet were markedly gliotic, but without evidence of compromised protein N-glycosylation. These results challenge the notion of RP59 as a DHDDS loss-of-function CDG and highlight the need to investigate unexplored RP59 disease mechanisms.