Quantitative Kinetic Energy Estimated from Disdrometer Signal

The kinetic energy of the rain drops was predicted in a relation between the rain rate and rain quantity, derived directly from the rain drop size distribution (DSD), which had been measured by a disdrometer located in the eastern state of Alagoas-Brazil. The equation in the form of exponential form suppressed the effects of large drops at low rainfall intensity observed at the beginning and end of the rainfall. The kinetic energy of the raindrop was underestimated in almost rain intensity ranges and was considered acceptable by the performance indicators such as coefficient of determination, average absolute error, percent relative error, mean absolute error, root mean square error, Willmott's concordance index and confidence index

Data pipeline for real-time energy consumption data management and prediction

With the increasing utilization of data in various industries and applications, constructing an efficient data pipeline has become crucial. In this study, we propose a machine learning operations-centric data pipeline specifically designed for an energy consumption management system. This pipeline seamlessly integrates the machine learning model with real-time data management and prediction capabilities. The overall architecture of our proposed pipeline comprises several key components, including Kafka, InfluxDB, Telegraf, Zookeeper, and Grafana. To enable accurate energy consumption predictions, we adopt two time-series prediction models, long short-term memory (LSTM), and seasonal autoregressive integrated moving average (SARIMA). Our analysis reveals a clear trade-off between speed and accuracy, where SARIMA exhibits faster model learning time while LSTM outperforms SARIMA in prediction accuracy. To validate the effectiveness of our pipeline, we measure the overall processing time by optimizing the configuration of Telegraf, which directly impacts the load in the pipeline. The results are promising, as our pipeline achieves an average end-to-end processing time of only 0.39 s for handling 10,000 data records and an impressive 1.26 s when scaling up to 100,000 records. This indicates 30.69–90.88 times faster processing compared to the existing Python-based approach. Additionally, when the number of records increases by ten times, the increased overhead is reduced by 3.07 times. This verifies that the proposed pipeline exhibits an efficient and scalable structure suitable for real-time environments

Response of different cultivation substrates on the chilling injury symptom of sweet pepper grown in hydroponics

This study determined the chilling injury interactions of sweet peppers with their hydroponic growth substrate. The treatments were cocopeat, perlite, and a mixture of 50:50 cocopeat and perlite (coco-perlite). The fruits, when harvested, were stored for 50 days using the modified atmosphere package (MAP) at 5 °C. The results revealed no significant interactions between the growth substrate and the chilling injury indicators (respiration and ethylene production rates, electrolyte leakage, malondialdehyde), even though a significant interaction existed with the chilling injury index (a water-soaked area). This is believed to be due to the growth substrate’s significant interactions with soluble solids and dry matter, which aided cellular balance and increased chilling injury tolerance in perlite and coco-perlite treatment. Weight loss rate and firmness loss were insignificant in all treatments, and cocopeat treatment may be considered the worst of all treatments

Stimulation of the Migration and Expansion of Adult Mouse Neural Stem Cells by the FPR2-Specific Peptide WKYMVm

Neural stem cells (NSCs) are multipotent cells capable of self-renewal and differentiation into different nervous system cells. Mouse NSCs (mNSCs) are useful tools for studying neurogenesis and the therapeutic applications of neurodegenerative diseases in mammals. Formyl peptide receptor 2 (FPR2), expressed in the central nervous system and brain, is involved in the migration and differentiation of murine embryonic-derived NSCs. In this study, we explored the effect of FPR2 activation in adult mNSCs using the synthetic peptide Trp-Lys-Tyr-Met-Val-D-Met-NH2 (WKYMVm), an agonist of FPR2. After isolation of NSCs from the subventricular zone of the adult mouse brain, they were cultured in two culture systems—neurospheres or adherent monolayers—to demonstrate the expression of NSC markers and phenotypes. Under different conditions, mNSCs differentiated into neurons and glial cells such as astrocytes, microglia, and oligodendrocytes. Treatment with WKYMVm stimulated the chemotactic migration of mNSCs. Moreover, WKYMVm-treated mNSCs were found to promote proliferation; this result was confirmed by the expansion of mNSCs in Matrigel and the increase in the number of Ki67-positive cells. Incubation of mNSCs with WKYMVm in a supplement-free medium enhanced the survival rate of the mNSCs. Together, these results suggest that WKYMVm-induced activation of FPR2 stimulates cellular responses in adult NSCs. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.1

Application of Computational Lower Extremity Model to Investigate Different Muscle Activities and Joint Force Patterns in Knee Osteoarthritis Patients during Walking

Many experimental and computational studies have reported that osteoarthritis in the knee joint affects knee biomechanics, including joint kinematics, joint contact forces, and muscle activities, due to functional restriction and disability. In this study, differences in muscle activities and joint force patterns between knee osteoarthritis (OA) patients and normal subjects during walking were investigated using the inverse dynamic analysis with a lower extremity musculoskeletal model. Extensor/flexor muscle activations and torque ratios and the joint contact forces were compared between the OA and normal groups. The OA patients had higher extensor muscle forces and lateral component of the knee joint force than normal subjects as well as force and torque ratios of extensor and flexor muscles, while the other parameters had little differences. The results explained that OA patients increased the level of antagonistic cocontraction and the adduction moment on the knee joint. The presented findings and technologies provide insight into biomechanical changes in OA patients and can also be used to evaluate the postoperative functional outcomes of the OA treatments