Repair of avulsion flap injury of heel by multiple point anchorage using Kirschner wires-a case series

The heel pad is a dense band of fibrous tissue with complex anatomy. Injuries to heel pad are uncommon but very challenging due to its precarious blood supply. In this study we tried fixing acute heel pad avulsion injuries using multiple Kirschner wires and results were evaluated according to the American orthopedic foot and ankle society hind foot score. Results were excellent for 3 -out of 9 patients and good for 6 patients according to the AOFAHS scoring system. Anchorage of acute heel pad avulsion injuries using multiple Kirschner wires is an effective and reliable treatment modality

IMPACT OF COVID-19 AND ONLINE EDUCATION ON THE MENTAL HEALTH OF MEMBERS OF EDUCATIONAL SPHERE-A CASE STUDY

Coronavirus disease 2019(COVID-19), the enormously transmissible disease resulting due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as the causative agent, instigated a dreadful outcome ensuing worldwide emergency with its rapid spread and greater mortality rate resulting in grievous disruptions. It arose as the greatest substantial world-wide health catastrophe ever since the period of influenza pandemic of 1918, causing more than 3.7 million deaths worldwide. The influence of this pandemic was ascertained in every arena of life on a worldwide level. COVID-19 has devastated many countries, thrashing our health care system besides having a major impact on the academic sector encompassing an enormous number of students, teachers along with staff members. With the implementation of the lock-down the offline classes were substituted for the online mode not only in India but globally. This has chiefly prompted an effect on the mental health of people apart from their physical health. Mental well-being has a vital significance and the spread of pandemic has accelerated a series of mental disorders ranging from anxiety, stress to depressive disorders. This review, based on questionnaires prepared using the perceived stress scale method compiles the response data of how COVID-19 has affected the mental health of students and members of the educational sphere. Not only this but it shows a contrast between the offline and the new tech-friendly online classes. Thus, this survey study reflects on creating a framework for the academic sector to aid in resolving and helping people manifested with mental health issues so as to lead a normal healthy lifestyle

AdANNS: A Framework for Adaptive Semantic Search

Web-scale search systems learn an encoder to embed a given query which is then hooked into an approximate nearest neighbor search (ANNS) pipeline to retrieve similar data points. To accurately capture tail queries and data points, learned representations typically are rigid, high-dimensional vectors that are generally used as-is in the entire ANNS pipeline and can lead to computationally expensive retrieval. In this paper, we argue that instead of rigid representations, different stages of ANNS can leverage adaptive representations of varying capacities to achieve significantly better accuracy-compute trade-offs, i.e., stages of ANNS that can get away with more approximate computation should use a lower-capacity representation of the same data point. To this end, we introduce AdANNS, a novel ANNS design framework that explicitly leverages the flexibility of Matryoshka Representations. We demonstrate state-of-the-art accuracy-compute trade-offs using novel AdANNS-based key ANNS building blocks like search data structures (AdANNS-IVF) and quantization (AdANNS-OPQ). For example on ImageNet retrieval, AdANNS-IVF is up to 1.5% more accurate than the rigid representations-based IVF at the same compute budget; and matches accuracy while being up to 90x faster in wall-clock time. For Natural Questions, 32-byte AdANNS-OPQ matches the accuracy of the 64-byte OPQ baseline constructed using rigid representations -- same accuracy at half the cost! We further show that the gains from AdANNS translate to modern-day composite ANNS indices that combine search structures and quantization. Finally, we demonstrate that AdANNS can enable inference-time adaptivity for compute-aware search on ANNS indices built non-adaptively on matryoshka representations. Code is open-sourced at https://github.com/RAIVNLab/AdANNS.Comment: 25 pages, 15 figures. NeurIPS 2023 camera ready publicatio

Predictors of urinary retention in benign prostate hyperplasia

Background: Acute urinary retention (AUR) is one of the most significant complications or long-term outcomes of benign prostatic hyperplasia (BPH). Because of the high prevalence of BPH and its effect on the patient's quality of life, additional research is needed to better predict the risk factors of AUR. The study was aimed to find out the incidence and factors responsible for retention of urine in BPH.Methods: It was a prospective study, conducted at a medical college after the approval from IEC. The study included the patients admitted to the surgical wards admitted with the symptoms of lower urinary tract symptom and presented with acute urinary retention. Duration of the study was 2 months. A total 40 patients were studied over this duration. The outcome of the study was analyzed by these factors: Age in years, Symptom severity, Prostate Volume on DRE and USG Grade.Results: The mean age of presentation was 64.87±7.85 with median age of 65 years (range 45-82 years) with mean IPSS score of 17.45and the mean PVR was 110.80 ± 85.52 with median 110 (range 0-500). Maximum number of patients having Grade 3 and 4 enlargements had PSA level 9-12 ng/ml. The PSA levels and the grade of enlargement on USG were statistically significant (p-0.004).Conclusions: Out of the four factors considered to be the independent risk factors, all of them have positive correlation with the symptom of acute urinary retention. None of these four factors i.e. age in years, symptom severity, prostate Volume on DRE and USG grade could establish significant correlation.

Matryoshka Representation Learning

Learned representations are a central component in modern ML systems, serving a multitude of downstream tasks. When training such representations, it is often the case that computational and statistical constraints for each downstream task are unknown. In this context rigid, fixed capacity representations can be either over or under-accommodating to the task at hand. This leads us to ask: can we design a flexible representation that can adapt to multiple downstream tasks with varying computational resources? Our main contribution is Matryoshka Representation Learning (MRL) which encodes information at different granularities and allows a single embedding to adapt to the computational constraints of downstream tasks. MRL minimally modifies existing representation learning pipelines and imposes no additional cost during inference and deployment. MRL learns coarse-to-fine representations that are at least as accurate and rich as independently trained low-dimensional representations. The flexibility within the learned Matryoshka Representations offer: (a) up to 14x smaller embedding size for ImageNet-1K classification at the same level of accuracy; (b) up to 14x real-world speed-ups for large-scale retrieval on ImageNet-1K and 4K; and (c) up to 2% accuracy improvements for long-tail few-shot classification, all while being as robust as the original representations. Finally, we show that MRL extends seamlessly to web-scale datasets (ImageNet, JFT) across various modalities -- vision (ViT, ResNet), vision + language (ALIGN) and language (BERT). MRL code and pretrained models are open-sourced at https://github.com/RAIVNLab/MRL.Comment: 35 pages, 12 figures. NeurIPS 2022 camera ready publicatio

Population history and genome wide association studies of birth weight in a native high altitude Ladakhi population

Pathological low birth weight due to fetal growth restriction (FGR) is an important predictor of adverse obstetric and neonatal outcomes. It is more common amongst native lowlanders when gestating in the hypoxic environment of high altitude, whilst populations who have resided at high altitude for many generations are relatively protected. Genetic study of pregnant populations at high altitude permits exploration of the role of hypoxia in FGR pathogenesis, and perhaps of FGR pathogenesis more broadly. We studied the umbilical cord blood DNA of 316 neonates born to pregnant women managed at the Sonam Norboo Memorial Hospital, Ladakh (altitude 3540m) between February 2017 and January 2019. Principal component, admixture and genome wide association studies (GWAS) were applied to dense single nucleotide polymorphism (SNP) genetic data, to explore ancestry and genetic predictors of low birth weight. Our findings support Tibetan ancestry in the Ladakhi population, with subsequent admixture with neighboring Indo-Aryan populations. Fetal growth protection was evident in Ladakhi neonates. Although no variants achieved genome wide significance, we observed nominal association of seven variants across genes (ZBTB38, ZFP36L2, HMGA2, CDKAL1, PLCG1) previously associated with birthweight

Hydrogel-Based Drug Delivery Nanosystems for the Treatment of Brain Tumors: A Systematic Review

The limitations and negative effects of current therapeutic techniques for brain tumors necessitate the selection of alternative therapeutic options. Therapeutic hydrogel systems that are monitored by magnetic resonance imaging (MRI) are one alternative for neurosurgical treatment of brain tumors that does not need any invasive procedures. There is a significant deal of potential for the treatment of brain tumors that can be attributed to the specific physical and chemical properties that hydrogels possess. The ability to encapsulate therapeutic molecules, provide regulated and sustained drug release, and successfully pass the blood-brain barrier are some of the properties that are included in this category. By combining hydrogel systems with magnetic resonance imaging (MRI) capabilities, it is possible to design therapeutic approaches that provide regulated release of therapeutic medications and real-time monitoring possibilities. Despite the fact that surgical resection is still extremely important, there is a growing demand for alternatives that can supplement or even replace it. Within the scope of this narrative review, the therapeutic hydrogel systems that are monitored by magnetic resonance imaging (MRI) will be evaluated to determine their potential for the non-surgical treatment of brain tumors