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Endpoint Detection and Response (EDR) solutions are pivotal in modern cybersecurity strategies, enabling organizations to detect, investigate, and respond to cyber threats effectively. This detailed examination of EDR technology traces its development from inception to its current state. It delves into the core concepts of EDR, highlighting its importance in endpoint security and threat identification. The document explores the historical background and driving forces behind EDR's advancement, emphasizing technological progressions like machine learning, behavioral analytics, and threat intelligence that enhance EDR capabilities. It also addresses challenges faced by EDR solutions, such as scalability, performance issues, and evasion tactics by sophisticated adversaries. Through case studies and industry trends analysis, the paper showcases EDR's efficacy in combating cyber threats and its integration into broader cybersecurity frameworks. Furthermore, it discusses the future outlook of EDR technology, considering the impact of emerging technologies like artificial intelligence, automation, and decentralized architectures. By consolidating insights from academic studies, industry analyses, and practical applications, this paper provides a comprehensive overview of the evolution of EDR in cybersecurity.

Due to climate change the drop in spring-water discharge poses a serious issue in the Himalayan region, especially in the higher section of Himachal Pradesh. This study used different climatic factors along with long-term rainfall data to understand the decreasing trend in spring-water discharge. It was determined which climate parameter was most closely correlated with spring discharge volumes using a general as well as partial correlation plot. Based on 40 years (1981–2021) of daily average rainfall data, a rainfall-runoff model was utilised to predict and assess trends in spring-water discharge using the MIKE 11 NAM hydrological model. The model’s effectiveness was effectively proved by the validation results (NSE = 0.79, R2 = 0.944, RMSE = 0.23, PBIAS = 32%). Model calibration and simulation revealed that both observed and simulated spring-water runoff decreased by almost 29%, within the past 40 years. Consequently, reduced spring-water discharge is made sensitive to the hydrological (groundwater stress, base flow, and stream water flow) and environmental entities (drinking water, evaporation, soil moisture, and evapotranspiration). This study will help researchers and policymakers to think and work on the spring disappearance and water security issues in the Himalayan region.

Multiple lines of research have led to the hypothesis that antimicrobial peptides (AMPs) are an important component of the innate immune response, playing a vital role in the defense against a wide range of infectious diseases. In this review, we explore the occurrence and availability of antimicrobial proteins and peptides across various species, highlighting their natural abundance and evolutionary significance. The design of AMPs has been driven by the identification of key structural and functional features, which are essential for optimizing their antimicrobial activity and reducing toxicity to host cells. We discuss various approaches, including rational design, high-throughput screening, and computational modeling, that have been employed to develop novel AMPs with enhanced efficacy. A particular focus is given to the identification and characterization of peptide fragments derived from naturally occurring host defense proteins, which offer a promising avenue for the discovery of new AMPs. The incorporation of artificial intelligence (AI) and machine learning (ML) tools into AMP research has further accelerated the identification, optimization, and application of these peptides. This review also discusses the current status and therapeutic potential of AMPs, emphasizing their role in addressing the growing issue of antibiotic resistance. The conclusion highlights the importance of continued research and innovation in AMP development to fully harness their potential as next-generation antimicrobial agents.

Background: PBL (problem based learning) is new active learning educational strategy that has been extensively tested and used in recent years. Patan Academy of Health Sciences (PAHS) is one of medical schools from Nepal, a Low Income Country (LIC) implementing PBL for undergraduate medical education. This study aims to compare PAHS students' understanding and knowledge retention when taught through PBL and lecture-based classes and compare students' perceptions of PBL and lectures in medical education. Methods: This is a cross-sectional study of medical students of a PBL based medical school in Nepal, a non-Western low-income country. Ethical approval was given by the institutional research committee of the Patan Academy of Health Sciences. Understanding and knowledge retention was assessed with 50 vignette-based multiple-choice questions, half of which were taught through PBL sessions, and the remaining half were taught in didactic lectures during basic science years of medical school. A separate pre-validated perception questionnaire was used to assess students' preferences regarding PBL and lectures. Results: Out of 107 students, 99 participated in the understanding and knowledge retention questionnaires and 107 completed perception questionnaires. Understanding and knowledge retention of students was found to be the same for topics taught by PBL and lectures, with median scores of 17 and s16, respectively. PBL were mostly preferred for the physiology (59.81%), pathology (51.40%) and pharmacology (53.27%) concepts, and lectures were mostly preferred for the anatomy (78.50%), biochemistry (45.79%), and microbiology (42.99%) topics. Students wanted the same concepts to be taught through both PBL and lectures, especially for anatomy. Conclusions: Understanding and knowledge retention is the same for topics taught by either PBL or lectures during the basic science years of undergraduate medical education. Students prefer PBL for physiology, pathology, and pharmacology-related concepts, conventional didactic lecture for physiology and microbiology, and a combination of lecture and PBL sessions for anatomy.

Introduction: Tetanus is an acute onset neurological disease that is often lethal. It has a high disease burden in low and middle-income countries. Tetanus is caused by a toxin made by spores of the bacterium Clostridium tetani, which are found in soil, dust, and animal feces. The toxin impairs the motor neurons leading to muscle stiffness. However, with the development of a toxoid vaccine, the incidence has sharply declined and is now categorized as a vaccine-preventable disease. The treatment of tetanus is primarily supportive and focuses on managing the complications until the effects of toxins resolve.Case Report: We report the case of a 67-year-old farmer who previously sustained a laceration injury approximately 45 days prior to presenting to the emergency department with abdominal pain and rigidity. After a comprehensive evaluation to rule out other items in the differential diagnoses, he was diagnosed with tetanus based on clinical symptoms and ultimately required mechanical ventilation. The patient was then managed in the intensive care unit and later made an uneventful recovery.Conclusion: This case illustrates an uncommon presentation of tetanus and the latency of the infectious process. Often when patients present with atypical symptoms, it poses a diagnostic dilemma to the clinicians. Thus, it is very important to carefully elicit a history of contaminated injury. This case also highlights the importance of prophylactic vaccine in low and middle-income countries, which can reduce disease-related mortality and morbidity.

With advancements in computational technology, data assimilation techniques, high-resolution remote sensing, and complex climate models, numerous precipitation products are available with different spatiotemporal resolutions; however, their evaluation, especially in the Himalayan region, is unexplored. Therefore, this study attempts to assess four sources (gridded observation dataset, reanalysis, satellite, and numerical weather prediction models) of precipitation through hydrological modelling for the catastrophic 2013 floods of Uttarakhand, India. The Upper Ganga Basin located in Western Himalayas is selected as the study area consisting of Alaknanda and Bhagirathi streams in the eastern and western parts. The Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) is employed for rainfall-runoff modelling. The rainfall from IMD, ERA-5, GPM-IMERG-Final, and WRF model outputs are forced into the calibrated HEC-HMS model for assessing their performance in hydrological simulations. The correlation coefficient of IMD, ERA-5, GPM-IMERG-Final, and WRF simulations with respect to the observed flow is 0.89, 0.88, 0.55, and 0.89, respectively, whereas their corresponding Modified Kling-Gupta Efficiency (KGE) is 0.66, 0.72, 0.48, and 0.71. Flash flood prioritization of the sub-watersheds based on morphometric characteristics suggests that the Alaknanda basin is relatively more vulnerable to flash floods due to their elongated nature, highest relative relief, and high mean slope.

“Digitalization of forest”, as this phrase itself suggests the sustainable implementation of cutting-edge technologies into forests for improving the current trends that are being used for forest environment monitoring, data acquisition, and analysis in the field of research and development. Technologies that can be used effectively for achieving these objectives include the Internet of Things, Wireless Sensor Networks, Internet of Trees, Deep Learning, etc. In this study, we will be exploring and assimilating the limitless possibilities for technological interventions in forests to drastically improve their ecosystem. Intelligent systems for sensing, monitoring, and methods for analysis to be used in applications such as forest fire incidents, illegal logging of trees, poaching, etc. have been discussed briefly. In addition to that, generalized architectures have been proposed which can be used directly in the future for advancements in research and development related to data collection and processing applications like flora analysis, forest fire predictions, etc. without the need for any changes in forest deployment systems. Various methods for enhancement of tribal livelihood, high yield marketing of minor forest produces, and wildlife monitoring is also discussed relating to the areas concentric on the forest environment. Effective connectivity, sustained deployment of real-time sensing systems, and energy harvesting are some of the vital recommendations included and addressed in this study for aiding the proper implementation of digital networks in the forest ecosystem.

Background: Chronic suppurative otitis media (CSOM) is a persistent middle ear disease with high risk of irreversible complications in absence of timely management. It is a massive health problem in India having the highest prevalence rate (>4%) requiring urgent attention. Aims and Objectives: The aim of the study was to find out risk factors, microbiological profile, with their susceptibility pattern, and of ear discharge in CSOM patients to provide guidelines for the empirical treatment. Materials and Methods: Ear discharge samples from 135 clinically diagnosed CSOM patients were collected and processed. Microbial isolates were identified and drug susceptibility testing was conducted using Kirby-Bauer disc diffusion method. Results: Pseudomonas species (59/135, 43.70%) was the predominant isolate followed by Staphylococcus species (37/135, 27.40%) while Aspergillus species (10/12, 83.33%) was the predominant fungus isolated. No anaerobic bacteria were isolated on culture. Gram-negative bacilli were most susceptible to Meropenem (100%) and Amikacin (100%) while Pseudomonas species was to Imipenem (98.35%). Gram-positive cocci showed 100% susceptibility to Vancomycin, Linezolid, and Doxycycline. Conclusion: A continuous and periodic evaluation of microbiological pattern of CSOM and antimicrobial sensitivity of isolates is necessary for forming the basis of empirical treatment which shall aid in decreasing the potential risk of complications. Further, accurate and timely identification, knowledge of the pathogens, and judicious use of antibiotics are the need of the hour.