An application of ordinal regression to extract social dysfunction levels through behavioral problems

Psychological problems are complex in nature and accurate identification of these problems is important. For the identification of psychological problems, one of the preliminary tools is the use of interviews/questionnaires. Questionnaires are preferred over interviews if the group under study is large. A strengths and difficulties questionnaire (SDQ) is one of the most widely used and powerful questionnaires to identify behavioral problems and distresses being faced by the respondents, affecting their day-to-day lives (responsible for social dysfunction). This study was held on college/university students in India, with the objective of examining if the extent of social dysfunction as measured by an impact score can be extracted from behavioral problems which are the components of the difficulty score of SDQ. Two surveys were conducted during the COVID-19 pandemic period, between the months of May–June 2020 and October 2020–February 2021 for the study. Only those responses were considered who felt distressed (“yes” to item 26 of SDQ). The numbers of such responses were 772/1020 and 584/743, respectively, in the two surveys. Distress levels were treated as ordered variables and three categories of distress level, viz., “Normal”, “Borderline”, and “Abnormal” were estimated through behavioral problems using ordinal regression (OR) methods with a negative log-log link function. The fitting of OR models was tested and accepted using Cox and Snell, Nagelkerke, and McFadden test. Hyperactivity-inattention and emotional symptoms were significant contributors to estimating levels of distress among respondents in survey 1 (p < 0.05). In addition to these components, in survey 2, peer problems were also significant. OR models were good at estimating the extreme categories; however, the “Borderline” category was not estimated well. One of the reasons was the use of qualitative and complex data with the least wide “Borderline” category, both for the “Difficulty” and the “Impact” scores

Improved ECG watermarking technique using curvelet transform

Hiding data in electrocardiogram signals are a big challenge due to the embedded information that can hamper the accuracy of disease detection. On the other hand, hiding data into ECG signals provides more security for, and authenticity of, the patient\u27s data. Some recent studies used non-blind watermarking techniques to embed patient information and data of a patient into ECG signals. However, these techniques are not robust against attacks with noise and show a low performance in terms of parameters such as peak signal to noise ratio (PSNR), normalized correlation (NC), mean square error (MSE), percentage residual difference (PRD), bit error rate (BER), structure similarity index measure (SSIM). In this study, an improved blind ECG-watermarking technique is proposed to embed the information of the patient\u27s data into the ECG signals using curvelet transform. The Euclidean distance between every two curvelet coefficients was computed to cluster the curvelet coefficients and after this, data were embedded into the selected clusters. This was an improvement not only in terms of extracting a hidden message from the watermarked ECG signals, but also robust against image-processing attacks. Performance metrics of SSIM, NC, PSNR and BER were used to measure the superiority of presented work. KL divergence and PRD were also used to reveal data hiding in curvelet coefficients of ECG without disturbing the original signal. The simulation results also demonstrated that the clustering method in the curvelet domain provided the best performance-even when the hidden messages were large size

Loss of genetic diversity and inbreeding in Kashmir red deer (Cervus elaphus hanglu) of Dachigam National Park, Jammu & Kashmir, India

BACKGROUND: Hangul (Cervus elaphus hanglu), the eastern most subspecies of red deer, is now confined only to the mountains in the Kashmir region of Jammu & Kashmir State of India. It is of great conservation significance as this is the last and only hope for Asiatic survivor of the red deer species in India. Wild population of free ranging hangul deer inhabiting in and around Dachigam National Park was genetically assessed in order to account for constitutive genetic attributes of hangul population using microsatellite markers. RESULTS: In a pool of 36 multi-locus genotypes, 30 unique individuals were identified based on six microsatellite loci. The estimated cumulative probability of identity assuming all individuals were siblings (P(ID) sibs) was 0.009 (9 in 1000). Altogether, 49 different alleles were observed with mean (± s.e.) allelic number of 8.17 ± 1.05, ranging from 5 to 11 per locus. The observed heterozygosity ranged between 0.08 and 0.83, with mean 0.40 ± 0.11 and the inbreeding coefficient ranged between −0.04 and 0.87 with mean 0.38 ± 0.15. Majority of loci (5/6) were found to be informative (PIC value > 0.5). All loci deviated from Hardy-Weinberg equilibrium except Ca-38 (P > 0.05) and none of the pairs of loci showed significant linkage disequilibrium except the single pair of Ca-30 and Ca-43 (P < 0.05). CONCLUSIONS: The preliminary findings revealed that hangul population is significantly inbred and exhibited a low genetic diversity in comparison to other deer populations of the world. We suggest prioritizing the potential individuals retaining high heterozygosity for ex situ conservation and genetic monitoring of the hangul population should be initiated covering the entire distribution range to ensure the long term survival of hangul. We speculate further ignoring genetics attributes may lead to a detrimental effect which can negatively influence the reproductive fitness and survivorship of the hangul population in the wild

Cloud-based framework to mitigate the impact of COVID-19 on seafarers' mental health.

n/

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Image Watermarking in Curvelet Domain Using Edge Surface Blocks

Digital image watermarking aims to protect the information in an image without significantly affecting visual quality. In this paper, a new image watermarking technique has been proposed that uses Gaussian filters and first-order partial differential matrix to extort the edge surface of a host image. This paper influence on the edge surface curvelet coefficients as human eyes are not equally sensitive to a smooth and an edged surface. To preserve the quality of the artwork and to increase the resistance against attacks, the author utilizes the edge surface area of an image, coarse levels of curvelet transform, and strength parameters. The selection of host coefficients are conforming to the human visual system (HVS) is the uniqueness of the research. The exploitation of the Gaussian filters and first-order partial differential coarse curvelet coefficients and the watermark strength parameter offers robustness against image processing attacks. The standard visual quality perception of HVS evaluation metrics are used to measure the superiority of the presented work

Cross-sectional Study on Prevalence of Betel Nut Chewing among the Youth of Meghalaya, North East Region of India: Development of Multifaceted Prevention Strategy

Introduction: Betel (Areca) nut intake, one of the most common oral chewing habits in the world, has been linked to the development of oral cancer, with India having an alarming situation with the highest number of registered oral cancer cases in the world. Method: A cross-sectional analysis was done among the young population of Meghalaya in the North Eastern Region of India, where this habit is prevalent. A questionnaire for on-ground data collection was administered to a total of n = 315 participants of both sexes from institutions in and near Shillong, Meghalaya. The relationship of this habit with social structure, knowledge, attitude, and risk perception was done. Result: A high prevalence rate of 78.09% was found among the school and undergraduate students from Shillong urban and adjoining rural areas for betel nut (BN) chewing with a higher female to male BN chewing ratio. This habit usually starts at the school level and persists for life. Peer pressure, lack of awareness, habituated families, and strong cultural linkage encourage children and adolescents to start chewing BN at an age as early as of 10 years. Lack of adequate awareness programs highlighting the ill-effects of BN and associated masticatory substances adds to the problem. Conclusion: Strategic, structured region-specific multifaceted awareness programs highlighting the potential health risks from uncontrolled, habitual usage of Areca nut has been proposed to prevent initiation of this habit