French marigold () flavonoid extract-based priming ameliorates initial drought stress on var , cultivar Satabdi (IET4786): a sustainable approach to avoid initial drought stress.

Drought stress remains a serious concern in L. var , cultivar Satabdi (IET4786) production, particularly during the earliest growth phases, ultimately affecting yield due to the recent trend of delayed rain arrival in West Bengal, India. This study aimed to develop a cost-effective strategy to improve the drought tolerance capacity of rice seedlings by priming the seeds with flavonoid-enriched extract (FEE) of French marigold () petals to withstand the initial drought milieu.

ShaderNN: A Lightweight and Efficient Inference Engine for Real-time Applications on Mobile GPUs.

Inference using deep neural networks on mobile devices has been an active area of research in recent years. The design of a deep learning inference framework targeted for mobile devices needs to consider various factors, such as the limited computational capacity of the devices, low power budget, varied memory access methods, and I/O bus bandwidth governed by the underlying processor's architecture. Furthermore, integrating an inference framework with time-sensitive applications - such as games and video-based software to perform tasks like ray tracing denoising and video processing - introduces the need to minimize data movement between processors and increase data locality in the target processor.

Medication use is associated with distinct microbial features in anxiety and depression.

This study investigated the relationship between gut microbiota and neuropsychiatric disorders (NPDs), specifically anxiety disorder (ANXD) and/or major depressive disorder (MDD), as defined by Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV or V criteria. The study also examined the influence of medication use, particularly antidepressants and/or anxiolytics, classified through the Anatomical Therapeutic Chemical (ATC) Classification System, on the gut microbiota. Both 16S rRNA gene amplicon sequencing (16S) and shallow shotgun sequencing (WGS) were performed on DNA extracted from 666 fecal samples from the Tulsa-1000 and Neurocomputational Mechanisms of Affiliation and Personality Study Center for Biomedical Research Excellence (NeuroMAP CoBRE) cohorts.

Uncovering Dynamical Equations of Stochastic Decision Models Using Data-Driven SINDy Algorithm.

Decision formation in perceptual decision making involves sensory evidence accumulation instantiated by the temporal integration of an internal decision variable toward some decision criterion or threshold, as described by sequential sampling theoretical models. The decision variable can be represented in the form of experimentally observable neural activities. Hence, elucidating the appropriate theoretical model becomes crucial to understanding the mechanisms underlying perceptual decision formation.