Uterine Arteriovenous Malformation As A Rare Cause Of Menorrhagia

Uterine arterio venous malformation is uncommon cause of menorrhagia. We report a rare case of arteriovenous malformation diagnosed after 18 years of suffering from menorrhagi

Congruence of genomic and ethnolinguistic affinities among five tribal populations of Madhya Pradesh (India)

The central Indian state of Madhya Pradesh is home to a large number of tribal populations of diverse linguistic and ethnic backgrounds. With a view to examining how well genomic affinities among tribal populations of this state correspond with their ethnic and linguistic affinities, we analysed DNA samples of individuals drawn from five tribes with diverse, but reasonably well-documented, ethnohistorical and linguistic backgrounds. Each DNA sample was scored at 16 biallelic DNA marker loci. On the basis of these data, genomic affinities among these populations were estimated. We have found an extremely good correspondence between the genomic and ethnolinguistic affinities

Towards Generating Functionally Correct Code Edits from Natural Language Issue Descriptions

Large language models (LLMs), such as OpenAI's Codex, have demonstrated their potential to generate code from natural language descriptions across a wide range of programming tasks. Several benchmarks have recently emerged to evaluate the ability of LLMs to generate functionally correct code from natural language intent with respect to a set of hidden test cases. This has enabled the research community to identify significant and reproducible advancements in LLM capabilities. However, there is currently a lack of benchmark datasets for assessing the ability of LLMs to generate functionally correct code edits based on natural language descriptions of intended changes. This paper aims to address this gap by motivating the problem NL2Fix of translating natural language descriptions of code changes (namely bug fixes described in Issue reports in repositories) into correct code fixes. To this end, we introduce Defects4J-NL2Fix, a dataset of 283 Java programs from the popular Defects4J dataset augmented with high-level descriptions of bug fixes, and empirically evaluate the performance of several state-of-the-art LLMs for the this task. Results show that these LLMS together are capable of generating plausible fixes for 64.6% of the bugs, and the best LLM-based technique can achieve up to 21.20% top-1 and 35.68% top-5 accuracy on this benchmark

Fundamental genomic unity of ethnic India is revealed by analysis of mitochondrial DNA

Mitochondrial DNA (mtDNA) profiles of 23 ethnic populations of India drawn from diverse cultural, linguistic and geographical backgrounds are presented. There is extensive sharing of a small number of mtDNA haplotypes, reconstructed on the basis of restriction fragment length polymorphisms, among the populations. This indicates that Indian populations were founded by a small number of females, possibly arriving on one of the early waves of out-of-Africa migration of modern humans; ethnic differentiation occurred subsequently through demographic expansions and geographic dispersal. The Asian-specific haplogroup M is in high frequency in most populations, especially tribal populations and Dravidian populations of southern India. Populations in which the frequencies of haplogroup M are relatively lower show higher frequencies of haplogroup U; such populations are primarily caste populations of northern India. This finding is indicative of a higher Caucasoid admixture in northern Indian populations. By examining the sharing of haplotypes between Indian and south-east Asian populations, we have provided evidence that south-east Asia was peopled by two waves of migration, one originating in India and the other originating in southern China. These findings have been examined and interpreted in the light of inferences derived from previous genomic and historical studies

Intertwining personal and reward relevance: evidence from the drift-diffusion model.

In their seminal paper 'Is our self nothing but reward', Northoff and Hayes (Biol Psychiatry 69(11):1019-1025, Northoff, Hayes, Biological Psychiatry 69(11):1019-1025, 2011) proposed three models of the relationship between self and reward and opened a continuing debate about how these different fields can be linked. To date, none of the proposed models received strong empirical support. The present study tested common and distinct effects of personal relevance and reward values by de-componenting different stages of perceptual decision making using a drift-diffusion approach. We employed a recently developed associative matching paradigm where participants (N = 40) formed mental associations between five geometric shapes and five labels referring personal relevance in the personal task, or five shape-label pairings with different reward values in the reward task and then performed a matching task by indicating whether a displayed shape-label pairing was correct or incorrect. We found that common effects of personal relevance and monetary reward were manifested in the facilitation of behavioural performance for high personal relevance and high reward value as socially important signals. The differential effects between personal and monetary relevance reflected non-decisional time in a perceptual decision process, and task-specific prioritization of stimuli. Our findings support the parallel processing model (Northoff & Hayes, Biol Psychiatry 69(11):1019-1025, Northoff, Hayes, Biological Psychiatry 69(11):1019-1025, 2011) and suggest that self-specific processing occurs in parallel with high reward processing. Limitations and further directions are discussed

Interaction of convective organisation with monsoon precipitation, atmosphere, surface and sea: the 2016 INCOMPASS field campaign in India

The INCOMPASS field campaign combines airborne and ground measurements of the 2016 Indian monsoon, towards the ultimate goal of better predicting monsoon rainfall. The monsoon supplies the majority of water in South Asia, but forecasting from days to the season ahead is limited by large, rapidly developing errors in model parametrizations. The lack of detailed observations prevents thorough understanding of the monsoon circulation and its interaction with the land surface: a process governed by boundary‐layer and convective‐cloud dynamics. INCOMPASS used the UK Facility for Airborne Atmospheric Measurements (FAAM) BAe‐146 aircraft for the first project of this scale in India, to accrue almost 100 h of observations in June and July 2016. Flights from Lucknow in the northern plains sampled the dramatic contrast in surface and boundary‐layer structures between dry desert air in the west and the humid environment over the northern Bay of Bengal. These flights were repeated in pre‐monsoon and monsoon conditions. Flights from a second base at Bengaluru in southern India measured atmospheric contrasts from the Arabian Sea, over the Western Ghats mountains, to the rain shadow of southeast India and the south Bay of Bengal. Flight planning was aided by forecasts from bespoke 4 km convection‐permitting limited‐area models at the Met Office and India's NCMRWF. On the ground, INCOMPASS installed eddy‐covariance flux towers on a range of surface types, to provide detailed measurements of surface fluxes and their modulation by diurnal and seasonal cycles. These data will be used to better quantify the impacts of the atmosphere on the land surface, and vice versa. INCOMPASS also installed ground instrumentation supersites at Kanpur and Bhubaneswar. Here we motivate and describe the INCOMPASS field campaign. We use examples from two flights to illustrate contrasts in atmospheric structure, in particular the retreating mid‐level dry intrusion during the monsoon onset

Interaction of convective organisation with monsoon precipitation, atmosphere, surface and sea: the 2016 INCOMPASS field campaign in India

The INCOMPASS field campaign combines airborne and ground measurements of the 2016 Indian monsoon, towards the ultimate goal of better predicting monsoon rainfall. The monsoon supplies the majority of water in South Asia, but forecasting from days to the season ahead is limited by large, rapidly developing errors in model parametrizations. The lack of detailed observations prevents thorough understanding of the monsoon circulation and its interaction with the land surface: a process governed by boundary-layer and convective-cloud dynamics. INCOMPASS used the UK Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 aircraft for the first project of this scale in India, to accrue almost 100 hours of observations in June and July 2016. Flights from Lucknow in the northern plains sampled the dramatic contrast in surface and boundary layer structures between dry desert air in the west and the humid environment over the northern Bay of Bengal. These flights were repeated in pre-monsoon and monsoon conditions. Flights from a second base at Bengaluru in southern India measured atmospheric contrasts from the Arabian Sea, over the Western Ghats mountains, to the rain shadow of southeast India and the south Bay of Bengal. Flight planning was aided by forecasts from bespoke 4km convection-permitting limited-area models at the Met Office and India's NCMRWF. On the ground, INCOMPASS installed eddy-covariance flux towers on a range of surface types, to provide detailed measurements of surface fluxes and their modulation by diurnal and seasonal cycles. These data will be used to better quantify the impacts of the atmosphere on the land surface, and vice versa. INCOMPASS also installed ground instrumentation supersites at Kanpur and Bhubaneswar. Here we motivate and describe the INCOMPASS field campaign. We use examples from two flights to illustrate contrasts in atmospheric structure, in particular the retreating mid-level dry intrusion during the monsoon onset