Automated Method for Tracking Human Muscle Architecture on Ultrasound Scans during Dynamic Tasks

Existing approaches for automated tracking of fascicle length (FL) and pennation angle (PA) rely on the presence of a single, user-defined fascicle (feature tracking) or on the presence of a specific intensity pattern (feature detection) across all the recorded ultrasound images. These prerequisites are seldom met during large dynamic muscle movements or for deeper muscles that are difficult to image. Deep-learning approaches are not affected by these issues, but their applicability is restricted by their need for large, manually analyzed training data sets. To address these limitations, the present study proposes a novel approach that tracks changes in FL and PA based on the distortion pattern within the fascicle band. The results indicated a satisfactory level of agreement between manual and automated measurements made with the proposed method. When compared against feature tracking and feature detection methods, the proposed method achieved the lowest average root mean squared error for FL and the second lowest for PA. The strength of the proposed approach is that the quantification process does not require a training data set and it can take place even when it is not possible to track a single fascicle or observe a specific intensity pattern on the ultrasound recording

Genomic-Assisted Enhancement in Stress Tolerance for Productivity Improvement in Sorghum

Sorghum [Sorghum bicolor (L.) Moench], the fifth most important cereal crop in the world after wheat, rice, maize, and barley, is a multipurpose crop widely grown for food, feed, fodder, forage, and fuel, vital to the food security of many of the world’s poorest people living in fragile agroecological zones. Globally, sorghum is grown on ~42 million hectares area in ~100 countries of Africa, Asia, Oceania, and the Americas. Sorghum grain is used mostly as food (~55%), in the form of flat breads and porridges in Asia and Africa, and as feed (~33%) in the Americas. Stover of sorghum is an increasingly important source of dry season fodder for livestock, especially in South Asia. In India, area under sorghum cultivation has been drastically come down to less than one third in the last six decades but with a limited reduction in total production suggesting the high-yield potential of this crop. Sorghum productivity is far lower compared to its genetic potential owing to a limited exploitation of genetic and genomic resources developed in the recent past. Sorghum production is challenged by various abiotic and biotic stresses leading to a significant reduction in yield. Advances in modern genetics and genomics resources and tools could potentially help to further strengthen sorghum production by accelerating the rate of genetic gains and expediting the breeding cycle to develop cultivars with enhanced yield stability under stress. This chapter reviews the advances made in generating the genetic and genomics resources in sorghum and their interventions in improving the yield stability under abiotic and biotic stresses to improve the productivity of this climate-smart cereal

Analysis of Attacks and Security Requirements for Wireless Body Area Networks-A Systematic Literature Review

Wireless Body Area Networks are gaining popularity in healthcare applications due to recent advances in sensor technology, integrated circuits, and wireless communication. These systems need to ensure that data is protected during collection, transmission, processing and storage. Currently, no complete solution exists for ensuring data is protected while also meeting regulatory security requirements for wireless body area network applications. To develop effective solutions, it is necessary to explore the attacks and security requirements of wireless body area network applications. There is no comprehensive list of attacks and security requirements. This paper will present a systematic literature review of potential attacks and security requirements for ensuring data security in wireless body area networks