Maternal outcome of primigravida patient with term pregnancy with engaged versus unengaged foetal head at onset of labour

Background: The primigravida are a group at risk as their capacity of child bearing has never put to the test, “primigravida is a dark and untired horse". The potential for future child bearing is determined by outcome of first labour. Hence, if first pregnancy results in normal healthy child, patient is mentally better prepared for subsequent pregnancies. Foetal head is said to be engaged when its biparietal diameter, the greatest diameter in an occiput presentation, passes through the pelvic inlet. Unengagement of head in primigravida has long been considered a possible sign of cephalopelvic disproportion.Methods: The study had 220 primigravida of which 110 had unengaged head as study group and 110 engaged head as controls. Data collection was done and the course of labour in all the patients recorded on partograph and all the patients were studied in detail. Engagement of the head was defined on the basis of Second Pawlik’s grip and Crichton’s fifth’s formula.Results: Our study shows that higher age group had more number of cases with unengaged head. The patient with engaged head had higher number of vaginal delivery than study group with unengaged head. More number of LSCS i.e. about 39.1% in study group as compared to 21% of controls is statistically significant difference (p value 0.05).Conclusions: We can conclude that primigravida with unengaged foetal head at onset of labour may deliver vaginally with minimal maternal morbidity, if proper   monitoring and maintenance of partogram is done

A Brief on Home Automation Using IoT

With the recent advances in automation worldwide, items that are widely available to every person of the country are crucial to keeping their rapidly developing environment up to date. We are delighted to showcase our investigation using these items on an IOT-based home automation device designed, implemented and produced in India. Energy efficiency conservation is becoming a major challenge in developing countries worldwide, in particular. A key cause is the lack of knowledge among end-users (or customers), which may help mitigate the above-mentioned problem, of the employment of new and developing techniques and technologies e.g. Internet-of-things (IoT). This research presented the most advanced technology in the literature on IoT-compatible energy conservation methods. This study also points out aspects of the infrastructure and communication models utilised to create IoT-enabled applications in the literature

T-MARS: Improving Visual Representations by Circumventing Text Feature Learning

Large web-sourced multimodal datasets have powered a slew of new methods for learning general-purpose visual representations, advancing the state of the art in computer vision and revolutionizing zero- and few-shot recognition. One crucial decision facing practitioners is how, if at all, to curate these ever-larger datasets. For example, the creators of the LAION-5B dataset chose to retain only image-caption pairs whose CLIP similarity score exceeded a designated threshold. In this paper, we propose a new state-of-the-art data filtering approach motivated by our observation that nearly 40% of LAION's images contain text that overlaps significantly with the caption. Intuitively, such data could be wasteful as it incentivizes models to perform optical character recognition rather than learning visual features. However, naively removing all such data could also be wasteful, as it throws away images that contain visual features (in addition to overlapping text). Our simple and scalable approach, T-MARS (Text Masking and Re-Scoring), filters out only those pairs where the text dominates the remaining visual features -- by first masking out the text and then filtering out those with a low CLIP similarity score of the masked image. Experimentally, T-MARS outperforms the top-ranked method on the "medium scale" of DataComp (a data filtering benchmark) by a margin of 6.5% on ImageNet and 4.7% on VTAB. Additionally, our systematic evaluation on various data pool sizes from 2M to 64M shows that the accuracy gains enjoyed by T-MARS linearly increase as data and compute are scaled exponentially. Code is available at https://github.com/locuslab/T-MARS

An Integrative Approach Towards Recommending Farming Solutions for Sustainable Agriculture

Sustainable Agriculture is rapidly emerging as an important discipline to meet societal needs for food and other resources by adopting paradigms of conserving natural resources while maximizing productivity benefits. This paper proposes an integrative methodological approach for critically analyzing Precision Farming (PF) paradigms and Zero Budget Natural Farming (ZBNF), providing sustainable farming solutions and achieving productivity and profitability. This paper analyses the productivity of crops in PF using various machine learning (ML) algorithms based on different soil and climatic factors to identify sustainable agricultural practices for maximizing crop production and generating recommendations for the farmers. When implemented on the collected dataset from various Indian states, the Random Forest (RF) model produced the best results with an AUC-ROC of 95.7%. The Juxtaposition of ZBNF and non-ZBNF is evinced. ZBNF is statistically (p<0.05) observed to be a cost-efficient and more profitable alternative. The impact of ZBNF on soil microbial diversity and micro-nutrients is also discussed

Pediatric Group Well Care within the Maternal Treatment Education & Research (MATER) Program

Introduction: This project aims to develop and implement group well care for mothers and infants receiving care for opioid use disorder (OUD). Groups would be composed of 5-7 mothers and infants of similar age with extension of sessions to allow group activities and parenting discussions. To evaluate acceptability and feasibility of this care model, we sought to examine attitudes and beliefs from these mothers, in particular the impacts of the COVID-19 pandemic. Methods: A qualitative interview study of women receiving treatment for OUD at Maternal Addiction Treatment Education and Research at Thomas Jefferson University from October – December 2020 was conducted. Participants were eligible if they had a child \u3c 2 years of age. Study procedures including recruitment, consent, and data collection were conducted by telephone. Participants were administered a 24-item survey to asses demographic and clinical information. This was followed by a semi-structured, open-ended interview to collect information on (1) priorities for pediatric care (2) attitudes toward a group care, and (3) potential barriers– including COVID-19. Percentages from survey items were calculated. Thematic analysis is planned to identify meaningful patterns in interview responses. Results: Among the 22 participants with completed data collection, 40.9% were “very likely” and 18.2% “likely” to bring their child to participate. Themes describing mother’s feelings towards group-care during the COVID-19 pandemic will be identified upon study completion. Conclusion: In a sample of mothers in treatment for OUD, interest in group well care was identified. Further thematic analysis will assess attitudes and beliefs towards the intervention related to COVID-19

Developing a google glass like device for environmental sensing

In today’s technologically advanced century, gadgets and software keep flooding in the market continuously. There is ever increasing research being done in company labs, universities, to make our lives easier, faster, safer, connected, convenient and fun. We want things to happen in split seconds, our messages to reach people across the globe as soon as we think it. The concept of augmented reality is one such topic that is becoming more and more ‘real’ in today’s world with each new innovative gadget and technology in market. The term Augmented Reality refers to any man made gadget that can sense the environment and supply users with information based on that. Google-Glass is such a wearable computer device with augmented reality display. It displays information in a hands-free format, while communicating with internet using natural language voice commands. All the communication and storage is carried out via Cloud services, and has complete smart-phone like functionalities such as camera, video, messages, mailing etc. This project uses a similar design and idea with limited functionalities and scope. The main objective is to implement audio sensory devices on the wearable glass device, process the signals from Microphone attached, remove unwanted elements like noise using implementation of filters, amplify, combine surround sound from various microphones strategically placed on the device to provide directional sound effects and then conduct the sound to the user’s brain directly using Bone Conduction technology. Thus, we focus on audio sensing and processing, so that the device is able to provide augmented spatial enhancement unit to hearing abilities. It can also work as a modern and stylish hearing aid with reduced cost. It will be essential to the user in noisy environments where communicating effectively can be challenging some times. The mobility and easy to use interface of the device makes it attractive and suitable for all types of users. Additional enhancement features include visual (camera) components and remote data storage capacities which are discussed in the further scope of expansion chapter of the report.Bachelor of Engineerin

Identifying High-Level Concept Clones in Software Programs Using Method’s Descriptive Documentation

Software clones are code fragments with similar or nearly similar functionality or structures. These clones are introduced in a project either accidentally or deliberately during software development or maintenance process. The presence of clones poses a significant threat to the maintenance of software systems and is on the top of the list of code smell types. Clones can be simple (fine-grained) or high-level (coarse-grained), depending on the chosen granularity of code for the clone detection. Simple clones are generally viewed at the lines/statements level, whereas high-level clones have granularity as a block, method, class, or file. High-level clones are said to be composed of multiple simple clones. This study aims to detect high-level conceptual code clones (having granularity as java methods) in java-based projects, which is extendable to the projects developed in other languages as well. Conceptual code clones are the ones implementing a similar higher-level abstraction such as an Abstract Data Type (ADT) list. Based on the assumption that “similar documentation implies similar methods”, the proposed mechanism uses “documentation” associated with methods to identify method-level concept clones. As complete documentation does not contribute to the method’s semantics, we extracted only the description part of the method’s documentation, which led to two benefits: increased efficiency and reduced text corpus size. Further, we used Latent Semantic Indexing (LSI) with different combinations of weight and similarity measures to identify similar descriptions in the text corpus. To show the efficacy of the proposed approach, we validated it using three java open source systems of sufficient length. The findings suggest that the proposed mechanism can detect methods implementing similar high-level concepts with improved recall values

Comparison of ECMO run between H1N1 acute respiratory failure vs. non H1N1 acute respiratory failure

First case of adult ECMO was reported in 1971 however after that ECMO was hardly been used in adult till 2009. The real boost to ECMO in adult respiratory failure came after 2009 mainly contributed to successful Cesar trial & an outbreak of H1N1. There are ample of papers published on H1N1 & ECMO but hardly a few papers on ECMO in non H1N1 respiratory failure. However the incidence of acute respiratory failure secondary to other tropical infections like Malaria, dengue, leptospirosis, bacterial & viral pneumonia are much higher in India & Asian countries. ECMO is underutilized for these tropical infections especially in India mainly due to financial constraints but also because of lack of awareness & lack of published data to support. We thought of publishing our own data on role of ECMO and outcome in H1N1 & non H1N1 respiratory failure. Methods: It is a Retrospective analysis of data collected of patients with acute respiratory failure managed on ECMO from January 2010 to November 2018. Results: The total 169 patients of respiratory failure were treated with ECMO during specified period. Out of this 169, 81 patients had H1N1 infection & remaining 88 were some other cause of respiratory failure all categorized under Non H1N1 group.There was not much difference in the survival in both the groups but ECMO runs remain significantly short (9.5 vs. 18.78 days) in non H1N1 group. Long run ECMO more than 30 days is seen in H1N1 with good survival (71.42%). Conclusions: ECMO is equally effective in Non H1N1 & H1N1 respiratory failure with much shorter ECMO run in Non H1N1 respiratory failure. Survival with ECMO in tropical infections like Malaria, Dengue & Leptospirosis is more than 60%. Keywords: ECMO in H1N1, Tropical disease & ECMO, Malaria, Leptospirosis, ARDS, Dengu