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Artificial Intelligence (AI) and the constant paradigm shift in road traffic have led to a need for significant improvement in road safety to minimize traffic accidents. LiFi helps minimize accidents by transmitting data between multiple vehicles (i.e. Vehicle-to-Vehicle (V2V)) and between vehicles and infrastructure (i.e. Vehicle-to-Infrastructure (V2I)) without interference. LiFi uses light to transmit data between devices or vehicles, which ensures efficient data transmission speed and is therefore considered a safe technology. A method called Deep Jacobian Regression and Tate Bryant Euler Recommendation (DJR-TBER) is proposed in this paper based on V2V and V2I autonomous vehicle communication. The proposed method DJR-TBER consists of an input layer, four hidden layers and finally an output layer. Sensors are first used to obtain the information. A linear regression-based speed evaluation model is developed and followed by a Jacobi matrix-based distance evaluation model in the hidden layer. The third hidden layer by developing a distance evaluation model. The use of Laplacian function ensures secure V2I communication for the autonomous vehicle. Finally, a Tate-Bryant-Euler angle-based model for emergency handling is proposed in the hidden layer to optimally consider the aspect of braking in emergency situations and thus increase driving safety.

BACKGROUND: Medical imaging techniques have improved to the point where security has become a basic requirement for all applications to ensure data security and data transmission over the internet. However, clinical images hold personal and sensitive data related to the patients and their disclosure has a negative impact on their right to privacy as well as legal ramifications for hospitals. OBJECTIVE: In this research, a novel deep learning-based key generation network (Deep-KEDI) is designed to produce the secure key used for decrypting and encrypting medical images. METHODS: Initially, medical images are pre-processed by adding the speckle noise using discrete ripplet transform before encryption and are removed after decryption for more security. In the Deep-KEDI model, the zigzag generative adversarial network (ZZ-GAN) is used as the learning network to generate the secret key. RESULTS: The proposed ZZ-GAN is used for secure encryption by generating three different zigzag patterns (vertical, horizontal, diagonal) of encrypted images with its key. The zigzag cipher uses an XOR operation in both encryption and decryption using the proposed ZZ-GAN. Encrypting the original image requires a secret key generated during encryption. After identification, the encrypted image is decrypted using the generated key to reverse the encryption process. Finally, speckle noise is removed from the encrypted image in order to reconstruct the original image. CONCLUSION: According to the experiments, the Deep-KEDI model generates secret keys with an information entropy of 7.45 that is particularly suitable for securing medical images. [ABSTRACT FROM AUTHOR]

Objectives: Obsessive–compulsive disorder (OCD) is estimated to be the 10th leading cause of disability in the world with a point prevalence of OCD at 3.3%. The present study was aimed at understanding the role of insight and self-efficacy in OCD and the relationship between these variables with OCD severity. Materials and Methods: It was a cross-sectional correlational study. The sample consisted of 100 males and females with a diagnosis of OCD. The variables were measured using the Yale-Brown Obsessive–Compulsive Scale (Y-BOCS) Symptom Checklist, Y-BOCS II, Brown Assessment of Beliefs Scale, and Self-Efficacy Scale. Results: The study revealed that a large portion of the patients fell in the “Severe”' range on Y-BOCS. Females reported a higher percentage of contamination and ordering obsessions as compared to males. Thirty-seven percent (37%) of the patients scored “Average” on self-efficacy results. A positive correlation between OCD severity and insight was found. Conclusion: Findings have important implications in clinical settings and can be used in the development of more focused, brief intervention strategies based on insight and self-efficacy. The primary limitation of the study was that data were obtained in a tertiary care hospital from an urban setting.

The African wild pygmy hedgehog has been domesticated and widely used in scientific experiments. Anesthesia of hedgehogs appear to be challenging, commonly associated with perianesthetic mortality. Inhalant anaesthetics are the agents of choice while injectable agents are seldom used and there are no reports on the use of alfaxalone. Thus the aim of this study was to evaluate two anaesthesia protocols of alfaxalone combined with a fixed dose of xylazine in hedgehog. Two groups consisting of 10 hedgehogs each were used in the study. The first group received 8mg/kg dose while the second group received 12mg/kg dose of alfaxalone with xylazine premedication maintained at 1mg/kg. All drugs were administered intramuscularly. Induction time, duration of anaesthesia and pain reflexes were monitored and recorded. Cardinal Health parameters were recorded just before, and at the 10th and 20th minutes post injection of anaesthetics. The two doses (8mg/kg and 12mg/kg) of alfaxalone used showed no differences on the induction time but induced profound anaesthesia that differed significantly (P≤0.05) and lasted for 37±14.72 and 54.4±17.35 minutes respectively with spontaneous and uneventful recovery. The two doses maintained respiration rates within the ranges of pre injection values while significant depression was noted on heart rates and rectal temperatures. The two tested doses of alfaxalone were well tolerated and appear to be safe for induction of short duration anaesthesia in hedgehogs. However, further study involving several doses to evaluate the cardiopulmonary dynamics and temperature regulation effects of the drug in question is recommended. [ABSTRACT FROM AUTHOR]

The clinical presentation of spinal or extraspinal neurofibroma is radiculopathy or myelopathy, pain, and motor weakness. Extraspinal neurofibroma presenting with acute-onset monoparesis and Horner's syndrome is very rare. We report the case of a 55-year-old female who presented with acute-onset monoparesis of the left upper limb along with left-side drooping of the eyelid. Imaging revealed C6–D2 extraspinal solitary mass lesion lateral to spinous process with bleed without intraspinal component. The patient underwent an anterior cervical approach and excision of the tumor. Final biopsy report was a neurofibroma. At 3-year follow-up, she recovered from motor weakness, and Horner's syndrome subsided. Extraspinal neurofibroma can present with acute bleed, and surgical outcome is superior in early intervention.

Background: The role of craving in alcohol dependence and its relationship with relapse has been studied widely in the past decade. The present study was undertaken to assess the role of craving in short-term relapse of patients seeking treatment for alcohol dependence and changes in craving score at the end of detoxification and at follow-up. Materials and Methods: A total of 34 male individuals with alcohol dependence (excluding comorbid drug dependence, organic or psychiatric disorder), after detoxification and discharge, consented. No anticraving medicine, aversive or psychotherapy, was advised. They were diagnosed on the International Statistical Classification of Diseases-10 using Diagnostic Interview for Genetic Studies. Severity of Alcohol Dependence Questionnaire (SADQ) and Clinical Institute Withdrawal Assessment Scale–Alcohol-Revised (CIWA-AR) were administered at the time of admission. Penn Alcohol Craving Scale (PACS) was applied at the time of discharge and follow-up to measure craving for alcohol. Results: Out of a total of thirty patients analyzed after dropout, 21 relapsed at the end of 1 month. On comparing PACS scores between relapsed and nonrelapsed patients, the difference was significant at both time points, i.e., at discharge and follow-up (t = 4.15, P < 0.0001 and t = 4.01, P < 0.001, respectively). In the total sample, SADQ and CIWA-AR scores were positively correlated (r = 0.47, P = 0.009). PACS at discharge was compared with PACS at follow-up, of which the correlation was high (r = 0.832, P < 0.0001). Conclusion: Craving seems to be a main factor related to relapse. Its measurement with PACS can be a useful tool to predict subsequent drinking and to identify individual risk for relapse during treatment.

Introduction: High cervical myelopathy can be rarely caused by the developmental anomalies of atlas. Patients with C1 arch stenosis can present in early childhood or later in life. In symptomatic patients, posterior decompression at atlas is mandatory. We report the first clinical series of 20 patients of C1 arch stenosis in the English literature. Materials and Methods: This is retrospective case series having a cohort of 20 patients with congenital C1 arch stenosis. Results: There were 12 pediatric (age

Cloud computing is a technology that holds great promise and has potential to revolutionize the healthcare sector. Many security and privacy issues are brought up by the cloud's centralization of data for both patients and healthcare professionals. There is a need for maintaining secrecy in communication in exchanging medical data between the sender and the receiver, which can be done by cryptography. This article presents a cryptographic algorithm (encryption and decryption) to have a secure communication of digital health care confidential data using DNA cryptography and Huffman coding. The interesting property is the cipher size obtained from our algorithm is equal to the size of the cipher obtained from the character set of given data. Security analysis is provided to show the security of data when stored and transmitted to the cloud. The cryptographic requirements, key space analysis, key and plain text sensitivity, sensitive score analysis, sensitivity and specificity, optimal threshold, randomness analysis, uniqueness of implementation, entropies of binary bits, DNA bases, DNA bases with Huffman code, Huffman encoded binary bits and cloud service provider's risk are analyzed. The method proposed is compared with other cryptographic methods and results that it is more secure and stronger than other methods. [ABSTRACT FROM AUTHOR]

Traffic has increased significantly over the past few years as a result of an increase in the number of vehicles using the common routes. It has been noted that manually operating signals has grown to be difficult. The difficulties encountered during an accident are the backed-up ambulances during emergencies caused by vehicle congestion and poor weather conditions like fog and haze. Considering this, the study focuses on the outcomes of an intelligent accident detection system using Vehicular Fog Computing (VFC). Automatic identification of crash spots and free flow of ambulances on roadways at peak hours of traffic. VFC has recently gained popularity as a useful tool for assisting vehicles in computing and storing service demands. Using the built-in sensors on a smartphone to monitor vehicular collisions and report them to the closest accessible first responder, as well as providing real-time location monitoring for paramedics and emergency victims would greatly improve the odds of recovery for emergency victims while saving time and money. This computing model guarantees the optimization of traffic congestion and energy consumption in the accident and foggy environment. This method also relies on delivering medical records to the closest hospital before the ambulance arrives, so pre-treatment can begin in the hospital. [ABSTRACT FROM AUTHOR]

The research aims to study the Perceived consumer and CSR initiation taken by the organization and their influences on Brand loyalty. The study combines Carroll's CSR pyramid theory and Ovidiu's brand loyalty multidimensional model. To test the relationship between CSR and brand loyalty, especially the research intended to test the two-dimension legal and ethical aspects of Carroll's model out of four which represents the consumer perceived CSR, with the SEM method, the relationship between CSR and brand loyalty is tested. The study did two things: reviewed the FMCG initiative taken by top FMCG. And then adopted purposive sampling of 10 Indian-listed FMCG sectors and collected data through an online Google survey during the pandemic period from September 2020 to May 2021; the study got 450 valid responses. The role of corporate social responsibility creates brand loyalty is confirmed. Research also found that consumers are more attracted to the legal and ethical responsibility of the organization. The research implies a marketing strategy for gaining brand loyalty. The findings project that event marketing, media marketing, and customer loyalty programs can create more effective CSR programs, and greater satisfaction with a product will make repeated purchase behaviour among customers. [ABSTRACT FROM AUTHOR]

Context: Procrastination is defined as "a trait or behavioral disposition to postpone or delay performing a task or making decisions." It is a self‑handicapping behavior that may result in loss of productivity, poor performance, and increased stress among individuals. Aim: The aim of this study was to evaluate the prevalence of procrastination trait among undergraduate and postgraduate dental students. Materials and Methods: A cross‑sectional questionnaire‑based survey was conducted among undergraduate and postgraduate students during October- November 2022 for assessing their procrastination trait. The response rate was 100%. Lay's Procrastination Scale (LPS) - student version was used to collect the desired information. Results: The results showed that interns had significantly high procrastination prevalence (LPS score ≥60) compared to BDS final‑year students and postgraduate students. The procrastination trait among males was found to be higher compared to females. Statistical Analysis: The Kruskal- Wallis test was applied to compare the mean procrastination score, and the Chi‑square test was applied to determine the difference in procrastination extent. Conclusion: Procrastination has been consistently reported to exert an adverse influence on the academic performance of students, which would in turn affect the performance and the quality of work being delivered by the students. Therefore, certain active measures have to be enforced to help the students for effective time management, which would reduce the consequences of procrastination in dental education. [ABSTRACT FROM AUTHOR]

Over the last few years, Big Data has sparked a lot of interest in a variety of engineering and scientific fields. Despite its numerous advantages, big data presents several issues such as big data management, big data analytics, big data security, and privacy which must be addressed to improve service quality. The proposed method focuses on data preprocessing, feature extraction, and classification. At first, data preprocessing has been performed and the weights have been assigned by the automated weight assignment model. In addition, the feature extraction model applies Principal Component Analysis (PCA) which employs feature correlation at the initial level, with best Information Gain (IG) and time-series data's similarity search with Kernel Dynamic Time Wrapping (DTW) method. On this basis, an Enhanced dynamic KPCA algorithm is introduced by integrating the kernel trick, DTW algorithm, PCA, and information gain. Then Convolutional multi-layer Bi-LSTM algorithms have been applied for classification. To analyze the big data performance, 8 types of datasets such as 32-pendigits, Bank-Marketing, Click Prediction, EEG, Electricity-normalized, Jm1, Magic telescope, and Amazon employee access are used. The performances are evaluated by different metrics with existing methods of LSTM, BRNN, MFC, and DL methods. [ABSTRACT FROM AUTHOR]

The increased usage of the internet and social networks generates a large volume of information. Exploring through the large collection is time-consuming and hard to find the required one, so there is a serious need for a recommendation system. Based on this context several movie recommendation (MR) systems have been recently established. In addition, they have poor data analytics capability and cannot handle changing user preferences. As a result, there are many movies listed on the recommendation page, which provides for a poor user experience is the major issue. Therefore, in this work, a novel Taymon Optimized Deep Learning network (TODL net) for recommending top best movies based on their past choices, behaviour and movie contents. The deep neural network is a combination of Dilated CNN with Bi-directional LSTM. The DiCNN-BiLSTM model eliminates the functionality pooling operations and uses a dilated convolution layer to address the issue of information loss. The DiCNN is employed to learn the movie contents by mining user behavioral pattern attributes. The BiLSTM is applied to recommend the best movies on basis of the extracted features of the movie rating sequences of users in other social mediums. Moreover, for providing better results the DiCNN-BiLSTM is optimized with Taymon optimization algorithm to recommend best movies for the users. The proposed TODL net obtains the overall accuracy of 97.24% for best movies recommendation by using TMDB and MovieLens datasets. [ABSTRACT FROM AUTHOR]

Background: The objective of the study was to investigate the burden and predictors of non-alcoholic fatty liver disease (NAFLD) in subclinical hypothyroidism (SCH) patients. Methods: A cross-sectional study was undertaken from January 2017 to December 2017 in 69 patients with SCH, visiting our tertiary care centre. Data collected included the demographic features, physical examination findings, laboratory investigations (free triiodothyronine [T3], free thyroxine (T4), serum thyroid-stimulating hormone (TSH), thyroid peroxidase antibodies, fasting plasma glucose, liver function test, fasting lipid profile and total serum cholesterol) and findings from the abdomen ultrasound and the electrocardiogram. Results: SCH was evident in 60.9% patients with SCH studied. Males showed a significantly high burden of NAFLD than females (52.4% Vs 47.61%; P = 0.005). Aspartate aminotransferase (AST), alanine aminotransferase (ALT), body weight, waist circumference (WC) and waist-hip ratio (WHR) showed a positive association with NAFLD in subclinical hypothyroidism. Conclusions: Our study provides significant evidence of a positive association between subclinical hypothyroidism and NAFLD. AST, ALT, WC and WHR may be considered the predictors of NAFLD in SCH. [ABSTRACT FROM AUTHOR]

Aim: The aim of the study was to determine the prevalence of dental caries among children of age 3-12 years based on the dental health diet score (DHDS). Settings and Design: Dental caries in children is evaluated using food score, nutrient score, and sweet score. Materials and Methods: A total of 2288 children were screened/examined, for the presence of dental caries using dmft/DMFT index, by randomly selecting 10 schools within a radius of 5 km. Informed written parental consent was obtained. A closed-ended questionnaire which included a diet chart was given 2 days before the examination. All children aged 3-12 years were included in the study. DHDS was calculated and compared with standard chart. All data obtained were tabulated and statistically analyzed using SPSS version 16 (IBM Corp.), with the P < 0.05 value considered statistically significant. Results: Dental health diet score values obtained from the present study shows that, 71.8% children were in badly need of diet counselling and diet modification, 13.7% of children were need to be educated and 15.5% of children were just need to be motivated. On comparing the DHDS score with the dental caries, the mean dmft/DMFT score of "not adequate and barely adequate" categories was 2.3 ± 1.8 and 2.4 ± 2.1, respectively. Their values were found to be statistically significant. Conclusion: Area to "Watch-out" for dental caries in children - Malnutrition. Equal emphasis is needed in both avoidance of sugary foods and maintenance of proper nutrition in children. [ABSTRACT FROM AUTHOR]