Evidence of Information Asymmetry and Herding Behaviour – The Swiss Franc Unpegging Event in Perspective

The paper aims to find the impact of financial events that occurred in one country on another. Taking the case of the Swiss Franc Unpegging of 2015 in Switzerland, the paper observes its impact on the Indian economy. This is done by studying the information asymmetry and herding behaviour in Indian market on the day of the event. The study uses two sets of data, (i) high frequency data and (ii) 3 years index data of both countries. The Ganger Causality test has been conducted to study the cause and effect relationship between the economies, which helps determine the impact on any of the countries. The study found that herding behaviour and information asymmetry in Indian market are now linked to each other in such a way that the country is affected even if the event has not occurred in the economy itself, however, only for a short duration of time. There also seems to be a huge gap between information available amongst all investors

DiffPrompter: Differentiable Implicit Visual Prompts for Semantic-Segmentation in Adverse Conditions

Semantic segmentation in adverse weather scenarios is a critical task for autonomous driving systems. While foundation models have shown promise, the need for specialized adaptors becomes evident for handling more challenging scenarios. We introduce DiffPrompter, a novel differentiable visual and latent prompting mechanism aimed at expanding the learning capabilities of existing adaptors in foundation models. Our proposed $\nabla$HFC image processing block excels particularly in adverse weather conditions, where conventional methods often fall short. Furthermore, we investigate the advantages of jointly training visual and latent prompts, demonstrating that this combined approach significantly enhances performance in out-of-distribution scenarios. Our differentiable visual prompts leverage parallel and series architectures to generate prompts, effectively improving object segmentation tasks in adverse conditions. Through a comprehensive series of experiments and evaluations, we provide empirical evidence to support the efficacy of our approach. Project page at https://diffprompter.github.io

Study on role of rural health training centre (RHTC) as a supporting component to a primary health care system for NRHM programme in district Muzaffarnagar (UP)

Background:The role of RHTC set up under MCI requirement of medical colleges is rising in implementation of NRHM phase 2 programme (2012 onwards); as private medical colleges are expanding in India and they can be an important supporter in public-private partnership for national health programmes.Objective of current study was to assess the role of rural health training centre as a supporting component to a primary health care system for NRHM programme.Methods:The present study was carried out by comparative evaluation of the rural health and training centre of a private medical college with a sub-centre (Muzaffarnagar) on key RCH services of NRHM: a) Family planning materials distribution, b) ANC services and c) Immunization services. Inclusion criteria: Proper ethical approval from both primary health care system and private medical college authorities were obtained for the study. Study design: Prospective evaluation based study on ANM in SC & SN in RHTC in NRHM programme for 1 year duration from 1st January 2013 to 31st December 2013. Data analysis: The statistical data was analysed by Epi-info version 7.1.3.  Results:The ANC services, family planning services and immunization services delivered under NRHM programme was found to statistically significantly contributed (P <0.05) by SN of RHTC as compared to ANM of SC in area of Bilaspur, Muzaffarnagar (Uttar Pradesh).Conclusion:RHTC of a private medical college in Muzaffarnagar (UP) is significantly contributing and supporting in RCH services of NRHM programme for primary health care system. RHTC of medical colleges can be an asset for public private partnership in NRHM programme.

The Role of SGLT2 Inhibitors in Heart Failure: A Systematic Review and Meta-Analysis.

AIMS: Recent randomised controlled trials (RCTs) have shown a significant prognostic benefit of sodium-glucose cotransporter 2 (SGLT2) inhibitors in the cardiovascular (CV) profile of patients with diabetes. This systematic review and meta-analysis aim to provide a concise evaluation of all the available evidence for the use of these agents in patients with heart failure (HF) regardless of their baseline diabetes status. METHODS AND RESULTS: PubMed, Web of Science, and Cochrane library databases were systematically searched from inception until November 20th 2020. Eight studies consisting of 13,275 patients were included in the meta-analysis. For the total population, SGLT2 inhibitors reduced the risk of all-cause mortality (HR: 0.83; 95% CI: 0.75-0.91; I 2 0%), hospitalisation for HF (HR: 0.68; 95% CI: 0.61-0.75; I 2: 0%), CV death (HR: 0.82; 95% CI: 0.74-0.92; I 2: 0%), and hospitalisation for HF or CV death (HR: 0.72; 95% CI: 0.66-0.78; I 2: 0%). Subgroup analyses of the total population according to the diabetes status showed that SGLT2 inhibitors significantly reduced the risk of hospitalisation for HF (HR: 0.68; 95% CI: 0.61, 0.75; I 2: 0%), as well as the risk of hospitalisation for HF or CV death (HR: 0.72; 95% CI: 0.66, 078; I 2: 0%) and CV death (HR: 0.82; 95% CI: 0.74, 0.91; I 2: 0%). CONCLUSIONS: The results of this meta-analysis confirm the growing evidence in the literature of the favourable profile of SGLT2 inhibitors in cardiovascular outcomes and mortality in patients with heart failure regardless of the baseline diabetes status. This systematic review has been registered with PROSPERO (CRD42021224777)

A novel approach for optimal weight factor of DT-CWT coefficients for land cover classification using MODIS data.

International audiencePresently, there is a need to explore the possibility to maximize the use of MODIS (Moderate Resolution Imaging Spectroradiometer) data as it has very good spectral (36 bands) and temporal resolution whereas its spatial resolution is moderate i.e. 250m, 500m, and 1km. Because of its moderate spatial resolution, its application for land cover classification is limited. Therefore, in this paper, an attempt has been made to enhance its spatial resolution and utilize the information contained in the different bands together to achieve good land cover classification accuracy, so that, in future, MODIS data can be used more effectively. For resolution enhancement, modified dual tree complex wavelet transform (DT-CWT) has been employed, where DT-CWT has been modified by critically analyzing the effect of weight factor of the DT-CWT coefficients on land cover classification. For this purpose, image statistics parameter like Mean of the image has also been considered. The proposed technique has been applied on the six bands of MODIS data which have spatial resolution of 500m. It is observed that weight factor of the high-frequency sub-bands is quite sensitive for computation of classification accuracy. Index Terms— DT-CWT, Resolution enhancement, wavelets, weights, MODIS 1.INTRODUCTION Satellite images are being used in various applications such as geoscience studies, astronomy and geographical information systems where their resolution plays a critical role but on the other hand, directly obtaining a high resolution data is an another herculean task because of high cost of sensor. Land cover classification from satellite data is a central topic in satellite imaging applications. Therefore, it becomes a necessity to develop and utilize a reliable resolution enhancement technique to obtain accurate information as much as possible as per application from the freely available moderate resolution satellite data. In this regard, many image resolution enhancement techniques have been developed which are interpolations (nearest neighbor, bilinear and bicubic) and wavelets (DWT, SWT, WZP etc.) based. Interpolation techniques [1] have been widely used for resolution enhancement but it results in loss of edges (i.e., high frequency components) of an image. Nowadays, resolution enhancement is being carried out in the wavelet domain. There are many wavelet transforms which have acquired the place. Discrete wavelet transform (DWT) [2] has also been widely used in order to preserve the high-frequency components of the image but its disadvantage is that it ends up with some ringing artifacts into the image since it is not found to be shift-invariant because of decimations and suppression of wavelet coefficients exploited by DWT. It basically suffers from four shortcomings i.e., oscillations, shift variance, aliasing and lack of directionality which can lead to some artifacts in the image and difficulties in signal modeling. Hence, the DWT has somewhat disappointed the researchers for satellite images. Therefore, in order to alleviate all these drawbacks of DWT [2,3], a new kind of wavelet was introduced by Kingsbury which is known as DT-CWT (Dual tree complex wavelet transform) [1,3]. It possesses shift-invariant property and has the capability of improving directional resolution (because of good directional sensitivity) as compared to that of the decimated DWT. That's why, DT-CWT has been employed in this paper for resolution enhancement of moderate resolution satellite images. It is foremost to discover the possibility of maximizing the use of freely available satellite data like MODIS. It consists of several bands in which different information is present, but has certain limitations as well like low spatial resolution i.e. 500m which is a major obstacle in obtaining that information accurately. Many researchers have worked on resolution enhancement techniques for visualization enhancement whereas in this paper, main motive is to enhance the land cover classification accuracy which is not reported much for satellite images like MODIS yet. Variance minimization [4] has also been explored by several researchers for weights optimization but it is somewhat 4528 978-1-5090-3332-4/16/$31.0

Early differences in auditory processing relate to Autism Spectrum Disorder traits in infants with Neurofibromatosis Type I.

BackgroundSensory modulation difficulties are common in children with conditions such as Autism Spectrum Disorder (ASD) and could contribute to other social and non-social symptoms. Positing a causal role for sensory processing differences requires observing atypical sensory reactivity prior to the emergence of other symptoms, which can be achieved through prospective studies.MethodsIn this longitudinal study, we examined auditory repetition suppression and change detection at 5 and 10 months in infants with and without Neurofibromatosis Type 1 (NF1), a condition associated with higher likelihood of developing ASD.ResultsIn typically developing infants, suppression to vowel repetition and enhanced responses to vowel/pitch change decreased with age over posterior regions, becoming more frontally specific; age-related change was diminished in the NF1 group. Whilst both groups detected changes in vowel and pitch, the NF1 group were largely slower to show a differentiated neural response. Auditory responses did not relate to later language, but were related to later ASD traits.ConclusionsThese findings represent the first demonstration of atypical brain responses to sounds in infants with NF1 and suggest they may relate to the likelihood of later ASD

PLAS-5k: Dataset of Protein-Ligand Affinities from Molecular Dynamics for Machine Learning Applications

Computational methods and recently modern machine learning methods have played a key role in structure-based drug design. Though several benchmarking datasets are available for machine learning applications in virtual screening, accurate prediction of binding affinity for a protein-ligand complex remains a major challenge. New datasets that allow for the development of models for predicting binding affinities better than the state-of-the-art scoring functions are important. For the first time, we have developed a dataset, PLAS-5k comprised of 5000 protein-ligand complexes chosen from PDB database. The dataset consists of binding affinities along with energy components like electrostatic, van der Waals, polar and non-polar solvation energy calculated from molecular dynamics simulations using MMPBSA (Molecular Mechanics Poisson-Boltzmann Surface Area) method. The calculated binding affinities outperformed docking scores and showed a good correlation with the available experimental values. The availability of energy components may enable optimization of desired components during machine learning-based drug design. Further, OnionNet model has been retrained on PLAS-5k dataset and is provided as a baseline for the prediction of binding affinities

Neuroanatomical correlates of working memory performance in Neurofibromatosis 1

Introduction: Neurofibromatosis 1 (NF1) is a single-gene disorder associated with cognitive impairments, particularly with deficits inworking memory. Prior research indicates that brain structure is affected in NF1, but it is unclear how these changes relate to aspectsof cognition.Methods: 29 adolescents aged 11-17 years were compared to age and sex-matched controls. NF1 subjects were assessed using detailedmultimodal measurements of working memory at baseline followed by a 3T MR scan. A voxel-based morphometry approach was usedto estimate the total and regional gray matter(GM) volumetric differences between the NF1 and control groups. The working memory metrics were subjected to a principal component analysis (PCA) approach.Results: The NF1 groups showed increased gray matter volumes in the thalamus, corpus striatum, dorsal midbrain and cerebellumbilaterally in the NF1 group as compared to controls. Principal component analysis on the working memory metrics in the NF1 groupyielded three independent factors ref lecting high memory load, low memory load and auditory working memory. Correlation analysesrevealed that increased volume of posterior cingulate cortex, a key component of the default mode network (DMN) was significantlyassociated with poorer performance on low working memory load tasks.Conclusion: These results are consistent with prior work showing larger subcortical brain volumes in the NF1 cohort. The strongassociation between posterior cingulate cortex volume and performance on low memory load conditions supports hypotheses of deficient DMN structural development, which in turn may contribute to the cognitive impairments in NF1

Sex bias in autism spectrum disorder in neurofibromatosis type 1

BACKGROUND: Despite extensive literature, little is known about the mechanisms underlying sex bias in autism spectrum disorder (ASD). This study investigates the sex differences in ASD associated with neurofibromatosis type 1, a single-gene model of syndromic autism. METHODS: We analysed data from n = 194 children aged 4–16 years with neurofibromatosis type 1. Sex differences were evaluated across the Autism Diagnostic Interview-Revised (ADI-R), Autism Diagnostic Observation Schedule (ADOS), verbal IQ, Social Responsiveness Scale (SRS) and Conners questionnaires. RESULTS: There was 2.68:1 male:female ratio in children meeting ASD criteria on the deep phenotyping measures. On symptom profile, males with neurofibromatosis type 1 (NF1) + ASD were more impaired on reciprocal social interaction and communication domains of the ADI-R but we found no differences on the restricted, repetitive behaviours (RRBs) domain of the ADI-R and no differences on the social on the ADOS. NF1 ASD males and females were comparable on verbal IQ, and the inattention/hyperactivity domains of the Conners questionnaire. CONCLUSIONS: There is a significant male bias in the prevalence of ASD in NF1. The phenotypic profile of NF1 + ASD cases includes greater social communication impairment in males. We discuss the implications of our findings and the rationale for using NF1 as a model for investigating sex bias in idiopathic ASD

Development of the pupillary light reflex from 9 to 24 months: association with common ASD genetic liability and 3-year ASD diagnosis

Background: Although autism spectrum disorder (ASD) is heritable, the mechanisms through which genes contribute to symptom emergence remain unclear. Investigating candidate intermediate phenotypes such as the pupillary light reflex (PLR) prospectively from early in development could bridge genotype and behavioural phenotype. Methods: Using eye tracking, we longitudinally measured the PLR at 9, 14 and 24 months in a sample of infants (N = 264) enriched for a family history of ASD; 27 infants received an ASD diagnosis at 3 years. We examined the 9- to 24-month developmental trajectories of PLR constriction latency (onset; ms) and amplitude (%) and explored their relation to categorical 3-year ASD outcome, polygenic liability for ASD and dimensional 3-year social affect (SA) and repetitive/restrictive behaviour (RRB) traits. Polygenic scores for ASD (PGSASD) were calculated for 190 infants. Results: While infants showed a decrease in latency between 9 and 14 months, higher PGSASD was associated with a smaller decrease in latency in the first year (β = −.16, 95% CI = −0.31, −0.002); infants with later ASD showed a significantly steeper decrease in latency (a putative ‘catch-up’) between 14 and 24 months relative to those with other outcomes (typical: β = .54, 95% CI = 0.08, 0.99; other: β = .53, 95% CI = 0.02, 1.04). Latency development did not associate with later dimensional variation in ASD-related traits. In contrast, change in amplitude was not related to categorical ASD or genetics, but decreasing 9- to 14-month amplitude was associated with higher SA (β = .08, 95% CI = 0.01, 0.14) and RRB (β = .05, 95% CI = 0.004, 0.11) traits. Conclusions: These findings corroborate PLR development as possible intermediate phenotypes being linked to both genetic liability and phenotypic outcomes. Future work should incorporate alternative measures (e.g. functionally informed structural and genetic measures) to test whether distinct neural mechanisms underpin PLR alteration