Are Methylaluminoxane Activators Sheets?

Density functional theory calculations on neutral sheet models for methylaluminoxane (MAO) indicate that these structures, containing 5-coordinate and 4-coordinate Al, are likely precursors to ion-pairs seen during the hydrolysis of trimethylaluminum (Me3Al) in the presence of donors such as octamethyltrisiloxane (OMTS). Ionization by both methide ([Me](-)) and [Me2Al](+) abstraction, involving this donor, were studied by polarizable continuum model calculations in fluorobenzene (PhF) and o-difluorobenzene (DFB) media. These studies suggest that low MW, 5-coordinate sheets ionize by [Me2Al](+) abstraction, while [Me](-) abstraction from Me3Al-OMTS is the likely process for higher MW 4-coordinate sheets. Further, comparison of anion stabilities per mole of aluminoxane repeat unit (MeAlO)(n), suggest that anions such as [(MeAlO)(7)(Me3Al)(4)Me](-)=[7,4](-) are especially stable compared to higher homologues, even though their neutral precursors are unstable.Peer reviewe

Evaluating XGBoost for Balanced and Imbalanced Data: Application to Fraud Detection

This paper evaluates XGboost's performance given different dataset sizes and class distributions, from perfectly balanced to highly imbalanced. XGBoost has been selected for evaluation, as it stands out in several benchmarks due to its detection performance and speed. After introducing the problem of fraud detection, the paper reviews evaluation metrics for detection systems or binary classifiers, and illustrates with examples how different metrics work for balanced and imbalanced datasets. Then, it examines the principles of XGBoost. It proposes a pipeline for data preparation and compares a Vanilla XGBoost against a random search-tuned XGBoost. Random search fine-tuning provides consistent improvement for large datasets of 100 thousand samples, not so for medium and small datasets of 10 and 1 thousand samples, respectively. Besides, as expected, XGBoost recognition performance improves as more data is available, and deteriorates detection performance as the datasets become more imbalanced. Tests on distributions with 50, 45, 25, and 5 percent positive samples show that the largest drop in detection performance occurs for the distribution with only 5 percent positive samples. Sampling to balance the training set does not provide consistent improvement. Therefore, future work will include a systematic study of different techniques to deal with data imbalance and evaluating other approaches, including graphs, autoencoders, and generative adversarial methods, to deal with the lack of labels.Comment: 17 pages, 8 figures, 9 tables, Presented at NVIDIA GTC, The Conference for the Era of AI and the Metaverse, March 23, 2023. [S51129

Vision-Language Models can Identify Distracted Driver Behavior from Naturalistic Videos

Recognizing the activities, causing distraction, in real-world driving scenarios is critical for ensuring the safety and reliability of both drivers and pedestrians on the roadways. Conventional computer vision techniques are typically data-intensive and require a large volume of annotated training data to detect and classify various distracted driving behaviors, thereby limiting their efficiency and scalability. We aim to develop a generalized framework that showcases robust performance with access to limited or no annotated training data. Recently, vision-language models have offered large-scale visual-textual pretraining that can be adapted to task-specific learning like distracted driving activity recognition. Vision-language pretraining models, such as CLIP, have shown significant promise in learning natural language-guided visual representations. This paper proposes a CLIP-based driver activity recognition approach that identifies driver distraction from naturalistic driving images and videos. CLIP's vision embedding offers zero-shot transfer and task-based finetuning, which can classify distracted activities from driving video data. Our results show that this framework offers state-of-the-art performance on zero-shot transfer and video-based CLIP for predicting the driver's state on two public datasets. We propose both frame-based and video-based frameworks developed on top of the CLIP's visual representation for distracted driving detection and classification task and report the results.Comment: 15 pages, 10 figure

Elastic Shape Models for Face Analysis Using Curvilinear Coordinates

International audienceThis paper studies the problem of analyzing variability in shapes of facial surfaces using a Rie- mannian framework, a fundamental approach that allows for joint matchings, comparisons, and deformations of faces under a chosen metric. The starting point is to impose a curvilinear coordinate system, named the Darcyan coordinate system, on facial surfaces; it is based on the level curves of the surface distance function measured from the tip of the nose. Each facial surface is now represented as an indexed collection of these level curves. The task of finding optimal deformations, or geodesic paths, between facial surfaces reduces to that of finding geodesics between level curves, which is accomplished using the theory of elastic shape analy- sis of 3D curves. Elastic framework allows for nonlinear matching between curves and between points across curves. The resulting geodesics provide optimal elastic deformations between faces and an elastic metric for comparing facial shapes. We demonstrate this idea using examples from FSU face databas

Experimental Studies of Active and Passive Flow Control Techniques Applied in a Twin Air-Intake

The flow control in twin air-intakes is necessary to improve the performance characteristics, since the flow traveling through curved and diffused paths becomes complex, especially after merging. The paper presents a comparison between two well-known techniques of flow control: active and passive. It presents an effective design of a vortex generator jet (VGJ) and a vane-type passive vortex generator (VG) and uses them in twin air-intake duct in different combinations to establish their effectiveness in improving the performance characteristics. The VGJ is designed to insert flow from side wall at pitch angle of 90 degrees and 45 degrees. Corotating (parallel) and counterrotating (V-shape) are the configuration of vane type VG. It is observed that VGJ has the potential to change the flow pattern drastically as compared to vane-type VG. While the VGJ is directed perpendicular to the side walls of the air-intake at a pitch angle of 90 degree, static pressure recovery is increased by 7.8% and total pressure loss is reduced by 40.7%, which is the best among all other cases tested for VGJ. For bigger-sized VG attached to the side walls of the air-intake, static pressure recovery is increased by 5.3%, but total pressure loss is reduced by only 4.5% as compared to all other cases of VG

Pre-operative Prediction of Difficult Laparoscopic Cholecystectomy

Introduction: Laparoscopic cholecystectomy is one of the most common operation performed. Though LC have become safer and easier at times it can be difficult. Difficult cases can result in prolonged operative time, bleeding, bile spillage, conversion to open technique and bile duct injury resulting in unplanned prolonged hospital stay, increase in estimated cost to the patients and for the surgeon it leads to increased stress during operation and time pressure to complete the operative list. . Identification of difficult cases has potential advantages for surgeons, patients and their relatives. We aim to develop and validate a scoring system to predict difficult LC preoperatively. Methods: Prospective study. History, physical examination, abdominal ultrasound and biochemical parameters were included to develop a scoring system. Hundred patients undergoing LC were included and preoperative scores were calculated preoperatively to predict difficult LC which was compared with operative assessment. Results: Sensitivity and specificity of the preoperative scoring for difficult case was 53.8 % and 89.2 % respectively with PPV of 63.64 % and NPV of 84.62%. Only three parameters (history of acute cholecystitis, gall bladder wall thickness and contracted gall bladder) were statistically significant to predict difficult LC individually. Area under ROC curve was 0.779 (95 % CI, 0.657-0.883). Conclusions: Preoperative scoring system can be used to predict difficult LC. Surgeons can plan operation based on predicted difficulty. Patients and relatives can be counselled preoperatively for the possibility of difficult operation, prolonged hospital stay and increased cost in predicted difficult case. Keywords: difficult cholecystectomy; laparoscopic cholecystectomy; symptomatic cholelithiasis

Evaluating the clinical effectiveness of the NHS Health Check programme: a prospective analysis in the Genetics and Vascular Health Check (GENVASC) study

OBJECTIVE: The aim of the study was to assess the clinical effectiveness of the national cardiovascular disease (CVD) prevention programme-National Health Service Health Check (NHSHC) in reduction of CVD risk. DESIGN: Prospective cohort study. SETTING: 147 primary care practices in Leicestershire and Northamptonshire in England, UK. PARTICIPANTS: 27 888 individuals undergoing NHSHC with a minimum of 18 months of follow-up data. OUTCOME MEASURES: The primary outcomes were NHSHC attributed detection of CVD risk factors, prescription of medications, changes in values of individual risk factors and frequency of follow-up. RESULTS: At recruitment, 18% of participants had high CVD risk (10%-20% 10-year risk) and 4% very high CVD risk (>20% 10-year risk). New diagnoses or hypertension (HTN) was made in 2.3% participants, hypercholesterolaemia in 0.25% and diabetes mellitus in 0.9%. New prescription of stains and antihypertensive medications was observed in 5.4% and 5.4% of participants, respectively. Total cholesterol was decreased on average by 0.38 mmol/L (95% CI -0.34 to -0.41) and 1.71 mmol/L (-1.48 to -1.94) in patients with initial cholesterol >5 mmol/L and >7.5 mmol/L, respectively. Systolic blood pressure was decreased on average by 2.9 mm Hg (-2.3 to -3.7), 15.7 mm Hg (-14.1 to -17.5) and 33.4 mm Hg (-29.4 to -37.7), in patients with grade 1, 2 and 3 HTN, respectively. About one out of three patients with increased CVD risk had no record of follow-up or treatment. CONCLUSIONS: Majority of patients identified with increased CVD risk through the NHSHC were followed up and received effective clinical interventions. However, one-third of high CVD risk patients had no follow-up and therefore did not receive any treatment. Our study highlights areas of focus which could improve the effectiveness of the programme. TRIAL REGISTRATION NUMBER: NCT04417387

Establishment of reference CD4+ T cell values for adult Indian population

<p>Abstract</p> <p>Background</p> <p>CD4+ T lymphocyte counts are the most important indicator of disease progression and success of antiretroviral treatment in HIV infection in resource limited settings. The nationwide reference range of CD4+ T lymphocytes was not available in India. This study was conducted to determine reference values of absolute CD4+ T cell counts and percentages for adult Indian population.</p> <p>Methods</p> <p>A multicentric study was conducted involving eight sites across the country. A total of 1206 (approximately 150 per/centre) healthy participants were enrolled in the study. The ratio of male (N = 645) to female (N = 561) of 1.14:1. The healthy status of the participants was assessed by a pre-decided questionnaire. At all centers the CD4+ T cell count, percentages and absolute CD3+ T cell count and percentages were estimated using a single platform strategy and lyse no wash technique. The data was analyzed using the Statistical Package for the Social Scientist (SPSS), version 15) and Prism software version 5.</p> <p>Results</p> <p>The absolute CD4+ T cell counts and percentages in female participants were significantly higher than the values obtained in male participants indicating the true difference in the CD4+ T cell subsets. The reference range for absolute CD4 count for Indian male population was 381-1565 cells/μL and for female population was 447-1846 cells/μL. The reference range for CD4% was 25-49% for male and 27-54% for female population. The reference values for CD3 counts were 776-2785 cells/μL for Indian male population and 826-2997 cells/μL for female population.</p> <p>Conclusion</p> <p>The study used stringent procedures for controlling the technical variation in the CD4 counts across the sites and thus could establish the robust national reference ranges for CD4 counts and percentages. These ranges will be helpful in staging the disease progression and monitoring antiretroviral therapy in HIV infection in India.</p

A Mathematical Framework for Protein Structure Comparison

Comparison of protein structures is important for revealing the evolutionary relationship among proteins, predicting protein functions and predicting protein structures. Many methods have been developed in the past to align two or multiple protein structures. Despite the importance of this problem, rigorous mathematical or statistical frameworks have seldom been pursued for general protein structure comparison. One notable issue in this field is that with many different distances used to measure the similarity between protein structures, none of them are proper distances when protein structures of different sequences are compared. Statistical approaches based on those non-proper distances or similarity scores as random variables are thus not mathematically rigorous. In this work, we develop a mathematical framework for protein structure comparison by treating protein structures as three-dimensional curves. Using an elastic Riemannian metric on spaces of curves, geodesic distance, a proper distance on spaces of curves, can be computed for any two protein structures. In this framework, protein structures can be treated as random variables on the shape manifold, and means and covariance can be computed for populations of protein structures. Furthermore, these moments can be used to build Gaussian-type probability distributions of protein structures for use in hypothesis testing. The covariance of a population of protein structures can reveal the population-specific variations and be helpful in improving structure classification. With curves representing protein structures, the matching is performed using elastic shape analysis of curves, which can effectively model conformational changes and insertions/deletions. We show that our method performs comparably with commonly used methods in protein structure classification on a large manually annotated data set