Challenges in setting up a large population-based prospective cohort study in India – learnings from the LoCARPoN cohort

Population-based prospective cohort studies can yield vital new evidence. However, they are difficult to setup especially in non-western contexts such as India. We describe our experience in establishing the Longitudinal Cognition and Aging Research on Population of the National Capital Region (LoCARPoN) cohort, which was the first-of-its-kind public-funded study with target sample size of 15,000, 3 sites, and funds of approx. US$ five million for eight years (2014–2022). LoCARPoN aimed to study incident stroke and dementia in adults aged ≥50 years in urban and rural populations of north India. Among the numerous challenges encountered, important were inadequate funding, lack of adequate space for medical and field sites, difficulty in hiring manpower, lack of IT infrastructure, non-availability of storage facility for biological samples, and absence of dedicated MRI machines. Meticulous planning, adequate funding, trained personnel, institutional and community support are critical for establishing such cohorts in the non-western contexts. Funding: The LoCARPoN cohort study was funded by the Department of Biotechnology (Grant No. BT/IN/Netherlands/03/KP/2012 dated 14/02/2014); and Department of Health Research (Grant No. R.11012/15/2018-HR, dated 09/08/2018), Government of India. The Erasmus component was funded through the Erasmus Medical Centre, Rotterdam, The Netherlands, and the Erasmus University, Rotterdam ( Alzheimer Nederland WE.15-2014-09).</p

Effect of amyloids on the vesicular machinery: Implications for somatic neurotransmission

Certain neurodegenerative diseases are thought to be initiated by the aggregation of amyloidogenic proteins. However, the mechanism underlying toxicity remains obscure. Most of the suggested mechanisms are generic in nature and do not directly explain the neuron-type specific lesions observed in many of these diseases. Some recent reports suggest that the toxic aggregates impair the synaptic vesicular machinery. This may lead to an understanding of the neuron-type specificity observed in these diseases. A disruption of the vesicular machinery can also be deleterious for extra-synaptic, especially somatic, neurotransmission (common in serotonergic and dopaminergic systems which are specifically affected in Alzheimer's disease (AD) and Parkinson's disease (PD), respectively), though this relationship has remained unexplored. In this review, we discuss amyloid-induced damage to the neurotransmitter vesicular machinery, with an eye on the possible implications for somatic exocytosis. We argue that the larger size of the system, and the availability of multi-photon microscopy techniques for directly visualizing monoamines, make the somatic exocytosis machinery a more tractable model for understanding the effect of amyloids on all types of vesicular neurotransmission. Indeed, exploring this neglected connection may not just be important, it may be a more fruitful route for understanding AD and PD

Plant Recognition Using Morphological Feature Extraction and Transfer Learning over SVM and AdaBoost

Plant species recognition from visual data has always been a challenging task for Artificial Intelligence (AI) researchers, due to a number of complications in the task, such as the enormous data to be processed due to vast number of floral species. There are many sources from a plant that can be used as feature aspects for an AI-based model, but features related to parts like leaves are considered as more significant for the task, primarily due to easy accessibility, than other parts like flowers, stems, etc. With this notion, we propose a plant species recognition model based on morphological features extracted from corresponding leaves’ images using the support vector machine (SVM) with adaptive boosting technique. This proposed framework includes the pre-processing, extraction of features and classification into one of the species. Various morphological features like centroid, major axis length, minor axis length, solidity, perimeter, and orientation are extracted from the digital images of various categories of leaves. In addition to this, transfer learning, as suggested by some previous studies, has also been used in the feature extraction process. Various classifiers like the kNN, decision trees, and multilayer perceptron (with and without AdaBoost) are employed on the opensource dataset, FLAVIA, to certify our study in its robustness, in contrast to other classifier frameworks. With this, our study also signifies the additional advantage of 10-fold cross validation over other dataset partitioning strategies, thereby achieving a precision rate of 95.85%

AN EFFICIENT AXI2.0 BASED APB BRIDGE BETWEEN HIGH PERFORMANCE AND LOW PERIPHERAL DEVICES

ABSTRACT Today&apos;s scenario of SOC deals with integrity and sharing of information or data with various level of communication. AMBA bus protocol has been proposed by ARM community to justify the uneven demand of integrity .In this paper functional description and implementation of high peripheral devices supporting protocol AXI2.0 and its interface between low peripheral devices has been proposed. The connection named as bridge take care of the protocol mismatch and operates on data transfer for uneven speed demand. Asynchronous FIFO has been considered to avoid the complex handshaking mechanism. The design has been implemented within VHDL and implemented on Xilinx Virtex 4

An Affordable Insole-Sensor-Based Trans-Femoral Prosthesis for Normal Gait

This paper proposes a novel and an affordable lower limb prosthesis to enable normal gait kinematics for trans-femoral amputees. The paper details the design of a passive prosthesis with magneto-rheological (MR) damping system and electronic control. A new control approach based on plantar insole feedback was employed here. Strategically placed sensors on the plantar insole provide required information about gait cycle to a finite state controller for suitable action. A proportional integral (PI) based current controller controls the required current for necessary damping during gait. The prosthesis was designed and developed locally in India keeping in view the cost, functionality, socio-economic, and aesthetic requirements. The prototype was experimentally tested on a trans-femoral amputee and the results are presented in this work. The implementation of the proposed design and control scheme in the prototype successfully realizes the notion that normal gait kinematics can be achieved at a low cost comparable to passive prostheses. The incurring cost and power expenditure of the proposed prosthesis are evaluated against passive and active prostheses, respectively. The commercial implications for the prosthesis were explored on the basis of recommendations of ISPO Consensus Conference on Appropriate Prosthetic Technology in Developing Countries. The key objective of this work is to enable lucid design for development of an affordable prosthesis in a low-resource setting

Estimation of recent changes in thickness and mass balance of the Patsio glacier in the Great Himalayan region using geodetic technique and ancillary data

An understanding of glacier mass budget in the Himalayas is important for regional water resource management. This study presents a detailed estimation of mass budget of the Patsio glacier (The Great Himalaya) using SRTM-X (2000), Cartosat-1 (2005) and TanDEM-X (2013) DEMs. Geodetic findings indicate an overall mass loss by −0.26±0.11 m.w.e/yr,−0.30±0.10 m.w.e/yr and −0.16±0.11 m.w.e/yr during 2000-2013, 2000-2005 and 2005–2013 respectively. Maximum downwasting was observed in the terminus area of the glacier during the period 2000–2013. The observed lower rate of mass loss between 2005 and 2013 was attributed to declining temperature during that period. However, long-term temperature trends depict warming, so was exhibited by mass loss during 2000–2013. Geodetic based findings were found to be concordant with GPR based estimation. This study confirms the suitability of geodetic mass balance technique for mountainous glaciers, which will be useful to evaluate future changes in the glacial extent and runoff study

Adaptive Flower Pollination Algorithm-Based Energy Efficient Routing Protocol for Multi-Robot Systems

The exploration and mapping of unknown environments, where the reliable exchange of data between the robots and the base station (BS) also plays a pivotal role, are some of the fundamental problems of mobile robotics. The maximum energy of a robot is utilized for navigation and communication. The communication between the robots and the BS is limited by the transmission range and the battery capacity. This situation inflicts constraints while designing an effective communication strategy for a multi-robot system (MRS). The biggest challenge lies in designing a unified framework for navigation and communication of the robots. The underlying notion is to utilize the minimum energy for communication (without limiting the range/efficiency of communication) to ensure that the maximum energy can be used for navigation (for larger area coverage). In this work, we present a communication strategy by using adaptive flower pollination optimization algorithm for MRS in conjunction with simultaneous localization and mapping (SLAM) technique for navigation and map making. The proposed strategy has been compared with multiple routing algorithms in terms of network life time and energy efficiency. The proposed strategy performs 4&#x0025; better compared with harmony search algorithm (HSA) and approximately 10&#x0025; better compared with distance aware residual energy-efficient stable election protocol (DARE-SEP) in terms of the total network lifetime when 50&#x0025; of robots are alive. The performance drastically improves by 20&#x0025; till the last robot is alive compared with HSA and approximately 26&#x0025; compared with DARE-SEP. Hence, the energy saved during communication with the utilization of proposed strategy helps the robots explore more areas, which ultimately elevates the efficacy of the whole system