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Introduction: Scabies affects 200–300 million individuals annually around the globe and it is a serious public health issue causing social stigmatisation in patients. With this background and its substantial impact on morbidity, this study was undertaken with the objective to find the demographic profile, clinical morphology and quality of life in patients suffering from scabies in urban slums of Ludhiana. MATERIALS AND METHODS: A cross-sectional, time-bound hospital-based study was carried out for a period of 2 months. A total of 173 patients with a diagnosis of scabies comprising all adults and children >5 years of age attending skin outpatient department were included in the study. The collected information was entered in Microsoft Excel sheet and analysed using SPSS. Results: The mean age of the study population was 34.85 ± 17.48 years. The most affected age groups were 18–40 years (46.9%), followed by 41–60 years (26.0%) and 17.9% in children. The majority of patients had difficulty in working and feelings of embarrassment, and in three-fifths of patients, their sexual relationship was affected due to scabies. In children, more than half experienced teasing and feeling of embarrassment and their routine activities such as playing were affected. Conclusion: In the present study, scabies moderately affected the quality of life of the patients in the form of embarrassment and stigma associated with disease. As it is a contagious disease, early diagnosis and prompt treatment can be helpful in the prevention and control of disease.

A middle-aged woman presented with history of fatigue, low mood, swelling of limbs, and facial puffiness. On detailed history taking, she also complained of salt craving, secondary amenorrhea, and loss of libido for almost a decade. Investigations revealed pan-hypopituitarism. She was started on appropriate hormonal therapy which saw a rapid resolution of symptoms within 2 weeks. Sheehan’s syndrome may have an acute presentation or chronic. The symptoms may be subtle like fatigue or overt like hypotension and syncope. A high degree of suspicion of Sheehan’s syndrome is essential for its timely management, and goes a long way in preserving the quality of life.

This research article delves into the development of a reinforcement learning (RL)-based continuous authentication system utilizing behavioral biometrics for user identification on computing devices. Keystroke dynamics are employed to capture unique behavioral biometric signatures, while a reward-driven RL model is deployed to authenticate users throughout their sessions. The proposed system augments conventional authentication mechanisms, fortifying them with an additional layer of security to create a robust continuous authentication framework compatible with static authentication systems. The methodology entails training an RL model to discern atypical user typing patterns and identify potentially suspicious activities. Each user’s historical data are utilized to train an agent, which undergoes preprocessing to generate episodes for learning purposes. The environment involves the retrieval of observations, which are intentionally perturbed to facilitate learning of nonlinear behaviors. The observation vector encompasses both ongoing and summarized features. A binary and minimalist reward function is employed, with principal component analysis (PCA) utilized for encoding ongoing features, and the double deep Q-network (DDQN) algorithm implemented through a fully connected neural network serving as the policy net. Evaluation results showcase training accuracy and equal error rate (EER) ranging from 94.7% to 100% and 0 to 0.0126, respectively, while test accuracy and EER fall within the range of approximately 81.06% to 93.5% and 0.0323 to 0.11, respectively, for all users as encoder features increase in number. These outcomes are achieved through RL’s iterative refinement of rewards via trial and error, leading to enhanced accuracy over time as more data are processed and incorporated into the system.