Assessing the Burden of Unnecessary Central Venous Catheters in Patients on Medical-Surgical Floors

Project goals: Our project goals are to: a) assess the burden of unnecessary PICCs and other non-tunneled central lines on med-surg units at TJUH and b) understand the underlying reasons behind the problem. In the first phase of our project we conducted an audit of med-surg unit PICCs and other non-tunneled central lines with the goal of obtaining a rough estimate of the number of line days that are unnecessary. SMART AIM By December 31, 2017, the TJUH medical-surgical floors will reduce the number of unnecessary PICC lines by 30%.https://jdc.jefferson.edu/patientsafetyposters/1024/thumbnail.jp

Prototype of a Biogas Anaerobic Digester from the Hostel Mess Kitchen Wastes

Biogas is a non-exhaustible of energy which can be formed from anaerobic fermentation of different types of biodegradable waste such as food waste, plant waste, animal waste sewage and other organic waste. The typical composition of Biogas includes CH4 (50–70%) which is responsible for maximum energy content along with CO2 (25–50%) that can be collected, stored and supplied. Biogas acts as a multipurpose and an eco- friendly sustainable resource of energy which can be utilized for cooking, electricity generation, lightning, heating etc. Biodegradable waste specifically produced in large amounts as a kitchen waste. In modern society, the solid waste per capita has been consistently increasing as of increase in population and change in socio-economic-cultural habits. The biogas production through the kitchen waste thereof provides a solution of disposal of solid waste. The bio gas production through anaerobic degradation pathways can be controlled and enhanced with the help of certain microorganisms and advancements of new technologies. In this research work, an attempt is being made to produce the biogas from kitchen and food waste collected from hostel mess of Chitkara University, Punjab and a novel method of production of microorganism has been also proposed for fast degradation of waste. Under this project, a survey for the estimation of daily production of organic waste from hostel mess has also been done for fifteen day.&nbsp

IITK at SemEval-2024 Task 1: Contrastive Learning and Autoencoders for Semantic Textual Relatedness in Multilingual Texts

This paper describes our system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness. The challenge is focused on automatically detecting the degree of relatedness between pairs of sentences for 14 languages including both high and low-resource Asian and African languages. Our team participated in two subtasks consisting of Track A: supervised and Track B: unsupervised. This paper focuses on a BERT-based contrastive learning and similarity metric based approach primarily for the supervised track while exploring autoencoders for the unsupervised track. It also aims on the creation of a bigram relatedness corpus using negative sampling strategy, thereby producing refined word embeddings.Comment: Accepted at SemEval 2024, NAACL 2024; 6 page

A Comprehensive Review of Hexapod Robots: Advancements, Challenges, and Applications

Hexapod robots, characterized by their six-legged locomotion inspired by the agility of insects, have gained significant attention in robotics research due to their versatility and adaptability in various environments. This review paper presents an in-depth analysis of the state-of-the-art in hexapod robot technology, exploring the evolution of their design, control strategies, locomotion capabilities, and diverse applications. The review begins by tracing the historical development of hexapod robots, from their early inception to recent advancements. It discusses the emergence of hexapod robots as a distinct class of robots and highlights key milestones in their evolution. The paper then delves into the fundamental mechanical design principles used in hexapod robots, examining various leg configurations, joint mechanisms, materials, and kinematic arrangements that have contributed to their enhanced mobility and stability

A Comprehensive Analysis of the Relationship Between Polycystic Ovary Syndrome and Anxiety

Background: Polycystic Ovary Syndrome (PCOS) is a reproductive, metabolic, and psychiatric endocrine disorder. The increasing evidence points toward the firm relationship between PCOS and anxiety but does not identify the underlying relationships.Aim: To investigate the relationship between PCOS and anxiety, evaluating potential causative factors including hormonal deregulation, metabolic imbalance, and markers of inflammation.Methods: The research involved 250 women participants were recruited, 150 with PCOS (experimental group) and 100 controls. Anxiety was measured by a validated questionnaire for anxiety. Hormonal and metabolic variables, such as insulin resistance (HOMA-IR), testosterone, BMI, and C-reactive protein (CRP), were measured and correlated with anxiety scores. Statistical tests were utilized to establish significant differences and correlations.Results: The evidence favours hormonal dysregulation, metabolic derangement, and systemic inflammation as the etiopathogenic factors in anxiety in PCOS patients. Hyperandrogenism and insulin resistance are associated with neuro-chemical alterations in mood control, while systemic inflammation is associated with increased psychological distress. These physiological changes could be the intrinsic factors for increased incidence of anxiety in PCOS.Conclusion: The research identifies a high level of correlation between PCOS and anxiety, with insulin resistance, elevated testosterone, BMI, and inflammation being significant contributory factors. Intervention in these variables is helpful in improving mental health outcomes among PCOS patients. Longitudinal trends and possible therapeutic options for decreasing anxiety in this group should be the focus of future studies

Sensitivity Analysis of Simulation-Based Inference for Galaxy Clustering

Simulation-based inference (SBI) is a promising approach to leverage high fidelity cosmological simulations and extract information from the non-Gaussian, non-linear scales that cannot be modeled analytically. However, scaling SBI to the next generation of cosmological surveys faces the computational challenge of requiring a large number of accurate simulations over a wide range of cosmologies, while simultaneously encompassing large cosmological volumes at high resolution. This challenge can potentially be mitigated by balancing the accuracy and computational cost for different components of the the forward model while ensuring robust inference. To guide our steps in this, we perform a sensitivity analysis of SBI for galaxy clustering on various components of the cosmological simulations: gravity model, halo-finder and the galaxy-halo distribution models (halo-occupation distribution, HOD). We infer the $\sigma_8$ and $\Omega_m$ using galaxy power spectrum multipoles and the bispectrum monopole assuming a galaxy number density expected from the luminous red galaxies observed using the Dark Energy Spectroscopy Instrument (DESI). We find that SBI is insensitive to changing gravity model between $N$-body simulations and particle mesh (PM) simulations. However, changing the halo-finder from friends-of-friends (FoF) to Rockstar can lead to biased estimate of $\sigma_8$ based on the bispectrum. For galaxy models, training SBI on more complex HOD leads to consistent inference for less complex HOD models, but SBI trained on simpler HOD models fails when applied to analyze data from a more complex HOD model. Based on our results, we discuss the outlook on cosmological simulations with a focus on applying SBI approaches to future galaxy surveys.Comment: 11 pages, 5 figures. Comments welcom

CHARM: Creating Halos with Auto-Regressive Multi-stage networks

To maximize the amount of information extracted from cosmological datasets, simulations that accurately represent these observations are necessary. However, traditional simulations that evolve particles under gravity by estimating particle-particle interactions (N-body simulations) are computationally expensive and prohibitive to scale to the large volumes and resolutions necessary for the upcoming datasets. Moreover, modeling the distribution of galaxies typically involves identifying virialized dark matter halos, which is also a time- and memory-consuming process for large N-body simulations, further exacerbating the computational cost. In this study, we introduce CHARM, a novel method for creating mock halo catalogs by matching the spatial, mass, and velocity statistics of halos directly from the large-scale distribution of the dark matter density field. We develop multi-stage neural spline flow-based networks to learn this mapping at redshift z=0.5 directly with computationally cheaper low-resolution particle mesh simulations instead of relying on the high-resolution N-body simulations. We show that the mock halo catalogs and painted galaxy catalogs have the same statistical properties as obtained from $N$-body simulations in both real space and redshift space. Finally, we use these mock catalogs for cosmological inference using redshift-space galaxy power spectrum, bispectrum, and wavelet-based statistics using simulation-based inference, performing the first inference with accelerated forward model simulations and finding unbiased cosmological constraints with well-calibrated posteriors. The code was developed as part of the Simons Collaboration on Learning the Universe and is publicly available at \url{https://github.com/shivampcosmo/CHARM}.12 pages and 8 figures. This is a Learning the Universe Publicatio

Prototype of a Biogas Anaerobic Digester from the Hostel Mess Kitchen Wastes

Biogas is a non-exhaustible of energy which can be formed from anaerobic fermentation of different types of biodegradable waste such as food waste, plant waste, animal waste sewage and other organic waste. The typical composition of Biogas includes CH4 (50–70%) which is responsible for maximum energy content along with CO2 (25–50%) that can be collected, stored and supplied. Biogas acts as a multipurpose and an eco- friendly sustainable resource of energy which can be utilized for cooking, electricity generation, lightning, heating etc. Biodegradable waste specifically produced in large amounts as a kitchen waste. In modern society, the solid waste per capita has been consistently increasing as of increase in population and change in socio-economic-cultural habits. The biogas production through the kitchen waste thereof provides a solution of disposal of solid waste. The bio gas production through anaerobic degradation pathways can be controlled and enhanced with the help of certain microorganisms and advancements of new technologies. In this research work, an attempt is being made to produce the biogas from kitchen and food waste collected from hostel mess of Chitkara University, Punjab and a novel method of production of microorganism has been also proposed for fast degradation of waste. Under this project, a survey for the estimation of daily production of organic waste from hostel mess has also been done for fifteen day. </jats:p

A Review on Recent Research Development on Electric Discharge Machining (EDM)

Out of all the machining processes used worldwide, Electrical discharge machining (EDM) is one of the most commonly used processes for material removal from a surface. It is a process for shaping hard metals and forming deep holes by subsequent erosion, which can be done in all kinds of materials which can conduct electricity. In this process, erosion occurs when electric discharge takes place in a small gap between the work piece and the electrode; this removes the unwanted material from the parent metal through melting and vaporizing in presence of dielectric fluid. In recent years, researchers have explored a number of ways to improve Electrical Discharge Machining process parameters such as Electrical parameters, Non-Electrical Parameters, Tool based parameters and Powder based parameters. This paper reviews and outlines the research work carried out in the recent years and also discusses the scope for future research work in the field.</jats:p