Abstract

Environmental flows play a major role in terms of quantity and quality for sustainable riverine ecosystems (Brisbane Declaration, 2007). Environmental Flows (EFs) have a variety of impacts in different regions of the world, including fisheries and other aquatic life, assimilative capacity, drinking water security, agriculture, transportation, navigation, industry, flood protection, recreation and tourism, and other cultural aspects (Iyer, 2005). The EFs are a measure of the amount and quality of water flowing in a freshwater river or stream over time. Estimation of EFs should be able to consider hydrologic, hydraulic, habitat and biodiversity, water quality, socioeconomic and cultural aspects with consideration of water regulation policies (Tennant, 1976). Estimation of EFs is generally practiced with consideration of one or multiple factors. Among these, the hydrological aspect with consideration of historical natural flow data is the most common and practiced by several river water management stakeholders (Zeiringer et al., 2018). Environmental flows based on hydrological criteria were conventionally estimated using flow indices based on a selected threshold level, which may be different for various river systems (Sharma and Dutta, 2020).

Abstract

Utilization of coal ash under a foundation of structure deals with huge quantity of its usage that solves the issue of its disposal, which is trivial in most parts of the world. Adaptability of coal ash under foundation needs to be examined on a large scale. In this study, it is attempted to investigate static and seismic response of shallow foundation resting on pond ash deposit. Two-dimensional (2D) response analysis is carried out for the ash-foundation system by employing finite element software PLAXIS 2D. It has been recognized since decades that soil-foundation interaction or ash-foundation interaction is prime factor in the seismic response of structure or portions of structure. Ash-foundation system is excited under the influence of Nepal earthquake motion (Mw: 7.8) and North East India earthquake motion (Mw: 7.5). The displacement was observed more in case of North East India earthquake, i.e. 6.028 m. However, acceleration and excess pore pressure response were high in case of Nepal earthquake, i.e. 0.152 g and 129.16 kPa, respectively. These responses can be utilized to assess the performance of ash-foundation system.

Abstract

mpact Assessment of Environmental Flows Using CORDEX Regional Climate Models: Case Study of Nagarjuna Sagar Dam, Krishna River, India

Abstract

Music sharing trends have been shown to change during times of socio-economic crises. Studies have also shown that music can act as a social surrogate, helping to significantly reduce loneliness by acting as an empathetic friend. We explored these phenomena through a novel study of online music sharing during the Covid-19 pandemic in India. We collected tweets from the popular social media platform Twitter during India’s first and second wave of the pandemic (n = 1,364). We examined the different ways in which music was able to accomplish the role of a social surrogate via analyzing tweet text using Natural Language Processing techniques. Additionally, we analyzed the emotional connotations of the music shared through the acoustic features and lyrical content and compared the results between pandemic and pre-pandemic times. It was observed that the role of music shifted to a more community focused function rather than tending to a more self-serving utility. Results demonstrated that people shared music during the Covid-19 pandemic which had lower valence and shared songs with topics that reflected turbulent times such as Hardship and Exclusion when compared to songs shared during pre-Covid times. The results are further discussed in the context of individualistic versus collectivistic cultures.

Abstract

Predicting Individual Differences from Brain Responses to Music using Functional Network Centrality

Abstract

Functional connectivity derived from functional MRI reflects the neuronal synchronization between brain regions anchored through an anatomical infrastructure of white matter pathways that can be computed from diffusion MRI. The inter-relation between the structure-function topography is of high interest in

Abstract

An electrocardiogram (ECG) monitors the electrical activity generated by the heart and is used to detect fatal cardiovascular diseases (CVDs). Conventionally, to capture the precise electrical activity, clinical experts use multiple-lead ECGs (typically 12 leads). Recently, large-scale deep learning models have been used to detect these diseases, however, they require large memory and long inference time. We propose a low-parameter model, Low Resource Heart-Network (LRH-Net), that detects ECG anomalies in a resource-constrained environment. On top, multi-level knowledge distillation (MLKD) is employed to improve model generalization. MLKD distils the dark-knowledge from higher parameter models (teachers) trained on different lead configurations to LRH-Net. The LRH-Net has 106× fewer parameters and 76% faster inference than the teacher model for detecting CVDs. Using MLKD, the performance of LRH-Net on reduced lead data was scaled up to 3.25%, making it suitable for edge devices.

Abstract

Impact due to demographic factors such as age, sex, race, etc., has been studied extensively in automated face recognition systems. However, the impact of digitally modified demographic and facial attributes on face recognition is relatively under-explored. In this work, we study the effect of attribute manipulations induced via generative adversarial networks (GANs) on face recognition performance. We conduct experiments on the CelebA dataset by intentionally modifying thirteen attributes using AttGAN and STGAN and evaluating their impact on two deep learning-based face verification methods, ArcFace and VGGFace. Our findings indicate that some attribute manipulations involving eyeglasses and digital alteration of sex cues can significantly impair face recognition by up to 73% and need further analysis. Keywords: Face recognition · Generative adversarial network (GAN) · Attribute manipulation.

Abstract

A face morph is created by strategically combining two or more face images corresponding to multiple identities. The intention is for the morphed image to match with multiple identities. Current morph attack detection strategies can detect morphs but cannot recover the images or identities used in creating them. The task of deducing the individual face images from a morphed face image is known as de-morphing. Existing work in de-morphing assume the availability of a reference image pertaining to one identity in order to recover the image of the accomplice - i.e., the other identity. In this work, we propose a novel demorphing method that can recover images of both identities simultaneously from a single morphed face image without needing a reference image or prior information about the morphing process. We propose a generative adversarial network that achieves single image-based de-morphing with a surprisingly high degree of visual realism and biometric similarity with the original face images. We demonstrate the performance of our method on landmark-based morphs and generative model-based morphs with promising results.

Abstract

Background: Association of visceral adipose tissue (VAT) with high molecular weight (HMW) adiponectin and insulin resistance (IR) is known, whereas impact of subcutaneous adipose tissue (SCAT) is unclear. Our objective was to find out association of VAT and SCAT-derived HMW adiponectin with serum HMW adiponectin and explore their impact on HOMA-IR and type 2 diabetes (T2DM). Methods: Among 51 subjects (Age-30 to 57 years), 33 subjects (women= 20, men= 13) without T2DM and 18 subjects (women= 11, men= 7) with new onset diabetes (less than 1 year) were categorized as control and T2DM respectively according to American Diabetic Association (ADA) guideline, 2010. Adipocytes were isolated and cultured from adipose tissue biopsies obtained from these subjects during their abdominal surgery. Adiponectin mRNA expression was analysed by Real-Time PCR, and HMW adiponectin …