The power of Artificial Intelligence (AI) combined with the surgeons’ expertise leads to breakthroughs in surgical care, bringing new hope to patients. Utilizing deep learning-based computer vision techniques in surgical procedures will enhance the healthcare industry. Laparoscopic surgery holds excellent potential for computer vision due to the abundance of real-time laparoscopic recordings captured by digital cameras containing significant unexplored information. Furthermore, with computing power resources becoming increasingly accessible and Machine Learning methods expanding across various industries, the potential for AI in healthcare is vast. There are several objectives of AI’s contribution to laparoscopic surgery; one is an image guidance system to identify anatomical structures in real-time. However, few studies are concerned with intraoperative anatomy recognition in laparoscopic surgery. This study provides a comprehensive review of the current state-of-the-art semantic segmentation techniques, which can guide surgeons during laparoscopic procedures by identifying specific anatomical structures for dissection or avoiding hazardous areas. This review aims to enhance research in AI for surgery to guide innovations towards more successful experiments that can be applied in real-world clinical settings. This AI contribution could revolutionize the field of laparoscopic surgery and improve patient outcomes.

In marginalized ecosystem-dependent rural communities, access to ecosystem services plays a crucial role in achieving sustainable livelihoods. This study was conducted to find out the influence of various livelihood capital components on the access mechanism for forest-based Provisioning Services (PS) in some selected villages of the Gosaba Block on the fringes of the Sundarban. The contribution of the livelihood capitals to gain access to Provisioning Services (PS) was identified using factor analysis on 160 households, selected through cluster random sampling. The sustainability levels of livelihood capitals were analyzed using the Prescott-Allen method (2001). The natural, financial, social, and physical capitals were significantly below average, while the human capital was close to average. Enhancement of human, physical, financial, and social capital, ease in issuing Biometric Fisherman cards for entering forests, flexibility in borrowing loans, and ecotourism by involving local villagers must be encouraged to enhance forest-based provisioning services in the near future.

A reservoir of vegetation, wildlife, and medicinal plant abundance is represented by the Haridwar forest divisions. This study deals with the results of ethnobotanical survey of medicinal plants conducted in the Haridwar forest division during the period of December 2016 and March 2019. The information on folk medicinal use of plants were gathered by interviewing with local healers and Vaidya’s who have long been advising the folk medicines for medication of various disorders. The important folk medicinal data of 33 medicinal plants species belonging to 22 families and 33 genera practiced by tribal and local people of the study area has been recorded by the survey team of the Institute. Fabaceae followed by the Lamiacea and Asteraceae were the dominant families. The species diversity showed maximum exploration of Trees, Herbs followed by Shrubs and Climbers. Leaves, seed and root were the most prevalently used part in study followed by the stem bark, fruit, flower, stem and fruit pulp. During the study it was observed that the traditional practices of Gujjars of Uttarakhand have close relation with forests and have strong dependency on the same for food, medicine, timber and fodder etc. The information recorded for the treatment in different ailments has been presented in the paper in the pie charts and tabular form. In the recorded information most of the plants along with Plant name, Family name, Voucher Specimen No., Local Name/Unani name, Part Used, Diseases/Condition and Habitat/ICBN status so as to enrich the existing knowledge on ethnopharmacology. Many of the medications used today have their roots in traditional knowledge of medicinal plants and indigenous uses of plant material, and there are still a plethora of potentially useful pharmaceutical chemicals to be found. In this regard, more in-depth field research could aid in the discovery of novel plant species utilized in indigenous medical systems to improve patient needs. With this aim this study was conducted to explore and trace the ethnobotanical potential of flora of the Haridwar forest division so that it could prove to be immensely advantageous for both the development of new medications to treat dreadful and catastrophic illnesses as well as for the study and preservation of cultural and social variety.

Diabetic retinopathy (DR) is a major cause of blindness globally. Effective screening programs are essential to mitigate this burden. This review outlines key principles and practices in implementing DR screening programs, emphasizing the roles of technology, patient education, and healthcare system integration. Our analysis highlights key principles for establishing successful screening initiatives, including the importance of regular screenings, optimal intervals, recommended technologies, and necessary infrastructure. We emphasize the roles of healthcare providers, patients, and policymakers in ensuring the effectiveness of these programs. Our recommendations aim to support the creation of robust policies that mitigate the impact of DR, ultimately improving public health outcomes and reducing the incidence of blindness due to diabetic retinopathy.

Banana (Musa spp.) productivity is limited by sodic soils, which impairs root growth and nutrient uptake. Analyzing root traits under stress conditions can aid in identifying tolerant genotypes. This study investigates the root morphological traits of banana cultivars under sodic soil stress conditions using Rhizovision software. The pot culture experiment was laid out in a Completely Randomized Design (CRD) under open field conditions, with treatments comprising the following varieties: Poovan (AAB), Udhayam (ABB), Karpooravalli (ABB), CO 3 (ABB), Kaveri Saba (ABB), Kaveri Kalki (ABB), Kaveri Haritha (ABB), Monthan (ABB), Nendran (AAB), and Rasthali (AAB), each replicated thrice. Parameters such as the number of roots, root tips, diameter, surface area, perimeter, and volume were assessed to evaluate the performance of different cultivars. The findings reveal that Karpooravali and Udhayam cultivars exhibited superior performance in terms of root morphology compared to other cultivars under sodic soil stress. These cultivars displayed increased root proliferation, elongation, and surface area, indicating their resilience to sodic soil stress. The utilization of Rhizovision software facilitated precise measurement and analysis of root traits, providing valuable insights into the adaptation mechanisms of banana cultivars to adverse soil conditions.