A study of psychiatric co-morbidity among alcohol dependents

Background: The alcohol use disorders are frequently associated with other co-morbid psychiatric disorders. The aim of this study was to describe the demographic variables, drinking history and psychiatric co-morbidity in alcohol dependent subjects.Methods: In this study, 40 consecutive patients were enrolled. After a minimum 1 month of sobriety, patients who fulfilled ICD-10 criteria of alcohol dependence were interviewed for data collection using Alcohol Use Disorders Identification Test (AUDIT), MINI-International Neuropsychiatric Interview (MINI) (Version-6.0) and a specially designed sociodemographic and clinical interview proforma. Subjects with substance use except tobacco were excluded from study. Main group comparison used chi-square test for categorical variables and the t-test for continuous variables.Results: Most of the patients studied were >40 years of age. Majority were employed (92%), lived in nuclear families (78%) and came from rural background (77.5%). Forty five percent of the patients initiated alcohol drinking between 16-25 years and reported peer pressure (50%) as most significant factor responsible for initiation of drinking alcohol. Mean age of developing alcohol dependence was 25.12 years (SD=4.28). Mean AUDIT score for subjects was 27.7 (SD=4.73). Lifetime psychiatric co-morbid disorders were detected in 45%. Psychiatric disorders most frequently associated with alcohol dependence were major depressive disorder (10%), bipolar affective disorder (7.5%), dysthymia (5%), anxiety disorders (7.5%) and antisocial personality disorder (5%).Conclusion: The study indicates that psychiatric disorders are prevalent in alcohol dependents and mood disorders are the most prevalent ones. It was also observed that co-morbid psychiatric disorders are associated with more severe alcohol problems

Fundamentals of Stellar Parameters Estimation through CMD of Star Clusters: Open (NGC2360) and Globular (NGC 5272)

The fundamentals of estimating essential stellar parameters of an open cluster-NGC 2360 and globular clusters-NGC 5272 are presented extensively in this work. Here, the evaluation of stellar parameters, by manually fitting the appropriate isochrones on the color magnitude diagrams (CMDs), of the selected star clusters is discussed comprehensively. Aperture photometry and PSF fitting photometry are conducted on g, r, and i standard band filter images of Sloan Digital Sky Survey (SDSS) using the aperture photometry tool (APT) to obtain the respective CMDs. Further, to achieve the stellar parameters, isochrone fitting is described in detail. This work on stellar parameters evaluation has attained the following results: age of NGC 2360 is found to be 708 Myrs with metallicity, [Fe/H], of -0.15, whereas NGC 5272 is having age of 11.56 Gyrs with metallicity, [Fe/H], of -1.57. Additionally, the interstellar reddening, E(B-V), and distance modulus, DM, for NGC 2360 are obtained as 0.12 and 11.65, respectively. While, for NGC 5272, the interstellar reddening is attained as E(B-V)=0.015, and the distance modulus is DM=15.1. The values of these stellar parameters are found to be in close approximation with the results provided in the literature based on the IRAF analysis technique. The distribution of radii, masses, and temperatures are included along with the initial mass function (IMF) for both the start clusters. Thus, this article would aid in providing insight into the evaluation of stellar parameters by the astronomical photometry analysis which would successively upsurge the understanding of our universe. It should be noted that the cleaning of cluster population on the CMDs from the foreground/background stars, clearing of spurious objects, error estimations and the membership determination are not carried out in this work and are considered as separate project for analysis.Comment: 17 pages, 12 figures, Journal: Bulgarian Astronomical Journa

Fundamentals of Differential and All-Sky Aperture Photometry Analysis for an Open Cluster

This article provides detailed description on the fundamentals of aperture photometry analysis. The differential and all-sky aperture photometry techniques are described thoroughly to depict the difference between the two techniques and their selection for determining the stars' magnitudes and their respective magnitude errors. The crucial calibration parameters required for the all-sky photometry analysis such as atmospheric extinctioncoefficient, air-mass, zero point, color term and color index are discussed comprehensively with their extraction from the Sloan Digital Sky Survey (SDSS) archive. The all-sky aperture photometry technique is applied on the stars of an open cluster NGC 2420 to determine their calibrated magnitudes and magnitude errors in the g, r, and i bands. The images required for the analysis are extracted from data release DR12 of SDSS III archive. Herein, the photometry analysis is performed by the Makali'i: SUBARU Image Processor, a Windows-based software. This software has a simple yet effective GUI and it provides the starlight minus the background sky light value with a single click. This article would aid in providing the insight into the physics of aperture photometry by manually scanning the astronomical images. In addition, the g, r, and i magnitudes are transformed to B, V, and R band magnitudes of Johnson-Cousins UBVRI photometric system. The color magnitude diagram for both the standard photometry systems are also provided.Comment: 16 pages, 5 figures, Journal: Bulgarian Astronomical Journa

Undergraduate nursing students’ attitude towards mental illness: a cross sectional study

Background: People suffering from mental illness commonly face stigma, bias, and discrimination by general public. Health care professionals are not immune to social biases and share the public's attitude meted out to people with mental illness. Nursing students are future health manpower. There are only few studies conducted on medical students’ attitude towards people with mental illnesses in India. We have planned this study to examine the undergraduate nursing students’ attitude towards people suffering from mental illnesses.Methods: It was a cross-sectional study. A total of 220 undergraduate nursing students were selected randomly with their consent to complete the Attitude Scale for Mental Illness (ASMI).Results: The nursing students were found to have a significant positive attitude towards mental illness in five of the six attitudes factors: Restrictiveness (8.42), benevolence (28.6) and stigmatization (7.3), separatism (15.6) and stereotype (9.4) However, these students had negative attitude in pessimistic predictions (12.5) domain as they rated this domain slightly on the higher side.Conclusions: Academic education in this field must be conceptualized and planned in order to favor the change of the attitudes that includes greater utilization of those teaching strategies that challenge beliefs and assumptions and promote a commitment to provide holistic care to people with mental illness

Prevalence of depression and its associated factors among medical students: a study using beck depression inventory

Background: Medical education carries with it a great burden of stress that can result in depression. This study was conducted to assess the prevalence of depression in medical students and various factors contributing to depression in the institute.Methods: A stratified random sample of 280 students was evaluated using Beck Depression Inventory by investigators. Associations between depression and year of study, addiction like alcohol use, family problems, family history of depression and staying away from home were analysed by univariate analysis.Results: The overall prevalence of depression was found to be 30.0%. Among those with depression, a majority (93%) had mild and moderate degree of depression. The study depicted that 41.6% (35) of the depressed were females and 58.3% (49) were males. As per the cut-off scores, 196 students (69.9%) scored as normal (0-9), 60 (21.4%) as mild (10-18), 18 (6.4%) as moderate (19-29), 4 (1.4%) as severe (30-40) and 2 (0.7%) as very severe (>40) depression. The prevalence of depression was comparatively less among 1st and 2nd year medical students (17.1%) and the difference between the grade of depression and year of study was found to be not significant (χ2=148, P=0.13). The prevalence was found more among those with family problems and family history of depression.Conclusions: In our study, depression was quite prevalent among medical students of the region. Our findings stressed the importance of broad screening and psychiatric counselling of this vulnerable population more meticulously

Assessment of burn-out among staff nurses working in a tertiary care health centre in North India

Background: This descriptive, cross sectional study identified the occurrence of burnout and some associated factors among nurses working in various departments at Indira Gandhi Medical College, Shimla, Himachal Pradesh, India which is a tertiary care health centre in the state.Methods: A total of 257 nurses screened in the hospital out of which 81 completed the study. Eighty-one nurses answered a self-administered questionnaire (sociodemographic aspects, working conditions, and Maslach Burnout Inventory). Mean scores were compared using ANOVA test. Student T-test was applied to compare mean scores between the groups.Results: All the participants were females (100%), with up to five years’ experience. High levels of emotional stress (45.7%) and depersonalization (24.7%) were identified, as well as low professional fulfilment (6.2%), and 8.6% presented burnout. The following factors were associated: high levels of emotional stress and always perform tasks very quickly (p=0.04) and receiving a salary incompatible to the effort employed (p=0.03); high levels of depersonalization and with up to five years’ experience (p=0.02) and often perform tasks very quickly (p=0.008). For 19.0%, at least two of the three dimensions pointed to high propensity to the syndrome.Conclusions: Searching for personal solutions for work problems must draw our attention, since it discourages health and work performance. Professionals may feel more fulfilled and satisfied by adjusting their work expectations. However, on a long-term basis, persisting in stressful work conditions enhances emotional exhaustion, depersonalization and feelings of low fulfilment at work

MLPerf Inference Benchmark

Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded. Over 100 organizations are building ML inference chips, and the systems that incorporate existing models span at least three orders of magnitude in power consumption and five orders of magnitude in performance; they range from embedded devices to data-center solutions. Fueling the hardware are a dozen or more software frameworks and libraries. The myriad combinations of ML hardware and ML software make assessing ML-system performance in an architecture-neutral, representative, and reproducible manner challenging. There is a clear need for industry-wide standard ML benchmarking and evaluation criteria. MLPerf Inference answers that call. In this paper, we present our benchmarking method for evaluating ML inference systems. Driven by more than 30 organizations as well as more than 200 ML engineers and practitioners, MLPerf prescribes a set of rules and best practices to ensure comparability across systems with wildly differing architectures. The first call for submissions garnered more than 600 reproducible inference-performance measurements from 14 organizations, representing over 30 systems that showcase a wide range of capabilities. The submissions attest to the benchmark's flexibility and adaptability.Comment: ISCA 202

Association of SUMOlation Pathway Genes With Stroke in a Genome-wide Association Study in India

OBJECTIVE: To undertake a genome-wide association study (GWAS) to identify genetic variants for stroke in an Indian population. METHODS: In a hospital-based case-control study, 8 teaching hospitals in India recruited 4,088 participants, including 1,609 stroke cases. Imputed genetic variants were tested for association with stroke subtypes using both single-marker and gene-based tests. Association with vascular risk factors was performed with logistic regression. Various databases were searched for replication, functional annotation, and association with related traits. Status of candidate genes previously reported in the Indian population was also checked. RESULTS: Associations of vascular risk factors with stroke were similar to previous reports and show modifiable risk factors such as hypertension, smoking, and alcohol consumption as having the highest effect. Single-marker–based association revealed 2 loci for cardioembolic stroke (1p21 and 16q24), 2 for small vessel disease stroke (3p26 and 16p13), and 4 for hemorrhagic stroke (3q24, 5q33, 6q13, and 19q13) at p < 5 × 10(−8). The index single nucleotide polymorphism of 1p21 is an expression quantitative trait locus (p(lowest) = 1.74 × 10(−58)) for RWDD3 involved in SUMOylation and is associated with platelet distribution width (1.15 × 10(−9)) and 18-carbon fatty acid metabolism (p = 7.36 × 10(−12)). In gene-based analysis, we identified 3 genes (SLC17A2, FAM73A, and OR52L1) at p < 2.7 × 10(−6). Eleven of 32 candidate gene loci studied in an Indian population replicated (p < 0.05), and 21 of 32 loci identified through previous GWAS replicated according to directionality of effect. CONCLUSIONS: This GWAS of stroke in an Indian population identified novel loci and replicated previously known loci. Genetic variants in the SUMOylation pathway, which has been implicated in brain ischemia, were identified for association with stroke