Integrated assessment of irrigation and agriculture management challenges in Nepal: An interdisciplinary perspective.

Agriculture plays a critical role in ensuring food and nutrition security, livelihood, and rural employment in Nepal. Despite substantial investments and institutional reforms, irrigation projects have faced consistently low performance. While existing studies have shed light on technical aspects of irrigation performance, they often focus on specific themes rather than holistic evaluations of sustainability. This research systematically assesses barriers and challenges to effective irrigation water management in Nepal by assessing and ranking the challenges faced by three irrigation systems in western Nepal: Mahakali, Rani Jamara Kulariya, and Babai. To investigate these challenges, we collected data from 449 households, which provided insights into 33 indicators representing key barriers to effective irrigation and agricultural management. The identified challenges were categorized into four broad thematic areas: physical and structural, agricultural and water, socioeconomic and market, and gender and governance. A comprehensive evaluation was conducted to compare these challenges among the three irrigation schemes, different thematic areas, and various locations within each scheme (namely, the head, mid, and tail sections of the system). The findings revealed that timely access and availability of fertilizers, spring water availability and fair market prices of agricultural products are the most significant challenges. The Babai irrigation system faced the most substantial challenges among the three systems, particularly in the mid section. These findings emphasize the interconnectedness of these challenges, highlighting the need for a holistic approach to planning, implementation, and management. Integrated strategies are essential to address socioeconomic, market, and endogenous farming issues, ensuring reliable irrigation water availability for sustainable agricultural production.

A precision functional atlas of personalized network topography and probabilities.

Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases-the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.

Multi-echo Acquisition and Thermal Denoising Advances Infant Precision Functional Imaging.

The characterization of individual functional brain organization with Precision Functional Mapping has provided important insights in recent years in adults. However, little is known about the ontogeny of inter-individual differences in brain functional organization during human development, but precise characterization of systems organization during periods of high plasticity might be most influential towards discoveries promoting lifelong health. Collecting and analyzing precision fMRI data during early development has unique challenges and emphasizes the importance of novel methods to improve data acquisition, processing, and analysis strategies in infant samples. Here, we investigate the applicability of two such methods from adult MRI research, multi-echo (ME) data acquisition and thermal noise removal with Noise reduction with distribution corrected principal component analysis (NORDIC), in precision fMRI data from three newborn infants. Compared to an adult example subject, T2* relaxation times calculated from ME data in infants were longer and more variable across the brain, pointing towards ME acquisition being a promising tool for optimizing developmental fMRI. The application of thermal denoising via NORDIC increased tSNR and the overall strength of functional connections as well as the split-half reliability of functional connectivity matrices in infant ME data. While our findings related to NORDIC denoising are coherent with the adult literature and ME data acquisition showed high promise, its application in developmental samples needs further investigation. The present work reveals gaps in our understanding of the best techniques for developmental brain imaging and highlights the need for further developmentally-specific methodological advances and optimizations, towards precision functional imaging in infants.