Comparative Analysis of Lunge Techniques: Forward, Reverse, Walking Lunge

The study aims to find the basis for the efficiency of lunge and risk of injury by comparing mechanical variables in various lunges (forward lunge, reverse lunge, and walking lunge). Four participants who were familiar with the three lunge movements were recruited to achieve the purpose of the study. The resultant hip joint moment, resultant knee joint moment, and resultant knee joint force were analyzed during the three lunge movements. Eight muscle of lower extremity were also analyzed using EMG. In conclusion, reverse lunge movement was found to be favorable in achieving the primary goal of lunge exercise, which is the development of gluteus maximus and quadriceps femoris, as it resulted in higher agonist muscle activities with relatively low momentary maximum knee shearing force compared to the other lunge techniques

Personalized probiotic strategy considering bowel habits: impacts on gut microbiota composition and alleviation of gastrointestinal symptoms via Consti-Biome and Sensi-Biome

Personalized probiotic regimens, taking into account individual characteristics such as stool patterns, have the potential to alleviate gastrointestinal disorders and improve gut health while avoiding the variability exhibited among individuals by conventional probiotics. This study aimed to explore the efficacy of personalized probiotic interventions in managing distinct stool patterns (constipation and diarrhea) by investigating their impact on the gut microbiome and gastrointestinal symptoms using a prospective, randomized, double-blind, placebo-controlled clinical trial design. This research leverages the multi-strain probiotic formulas, Consti-Biome and Sensi-Biome, which have previously demonstrated efficacy in alleviating constipation and diarrhea symptoms, respectively. Improvement in clinical symptoms improvement and compositional changes in the gut microbiome were analyzed in participants with predominant constipation or diarrhea symptoms. Results indicate that tailored probiotics could improve constipation and diarrhea by promoting Erysipelotrichaceae and Lactobacillaceae, producers of short-chain fatty acids, and regulating inflammation and pain-associated taxa. These findings suggest the potential of tailored probiotic prescriptions and emphasize the need for personalized therapeutic approaches for digestive disorders.Clinical trial registration: https://cris.nih.go.kr/cris/index/index.do, identifier KCT0009111

A Study on the Enhancement of Detection Performance of Space

Radar sensors are used for space situational awareness (SSA) to determine collision risk and detect re-entry of space objects. The capability of SSA radar system includes radar sensitivity such as the detectable radar cross-section as a function of range and tracking capability to indicate tracking time and measurement errors. The time duration of the target staying in a range cell is short; therefore, the signal-to-noise ratio cannot be improved through the pulse integration method used in pulse-Doppler signal processing. In this study, a method of improving the signal-to-noise ratio during range migration is presented. The improved detection performance from signal processing gains realized in this study can be used as a basis for comprehensively designing an SSA radar system

Microbiome of Saliva and Plaque in Children According to Age and Dental Caries Experience

Dental caries are one of the chronic diseases caused by organic acids made from oral microbes. However, there was a lack of knowledge about the oral microbiome of Korean children. The aim of this study was to analyze the metagenome data of the oral microbiome obtained from Korean children and to discover bacteria highly related to dental caries with machine learning models. Saliva and plaque samples from 120 Korean children aged below 12 years were collected. Bacterial composition was identified using Illumina HiSeq sequencing based on the V3-V4 hypervariable region of the 16S rRNA gene. Ten major genera accounted for approximately 70% of the samples on average, including Streptococcus, Neisseria, Corynebacterium, and Fusobacterium. Differential abundant analyses revealed that Scardovia wiggsiae and Leptotrichia wadei were enriched in the caries samples, while Neisseria oralis was abundant in the non-caries samples of children aged below 6 years. The caries and non-caries samples of children aged 6-12 years were enriched in Streptococcus mutans and Corynebacterium durum, respectively. The machine learning models based on these differentially enriched taxa showed accuracies of up to 83%. These results confirmed significant alterations in the oral microbiome according to dental caries and age, and these differences can be used as diagnostic biomarkers

Successful Eradication of Porcine Epidemic Diarrhea in an Enzootically Infected Farm: A Two-Year Follow-Up Study

Porcine epidemic diarrhea virus (PEDV) has negatively affected the welfare of animals and their productivity in South Korea for three decades. A shortage of effective control measures has led to the virus becoming endemic in domestic pig populations. This study aimed to describe how our intervention measures were implemented for PEDV elimination in an enzootically infected farm. We operated a risk assessment model of PEDV recurrence to obtain information about the virus itself, herd immunity, virus circulation, and biosecurity at the farm. Next, we conducted a four-pillar-based two-track strategy to heighten sow immunity and eradicate the virus, with longitudinal monitoring of immunity and virus circulation, involving strict biosecurity, prime-boost pre-farrow L/K/K immunization, all-in-all-out and disinfection practices in farrowing houses, and disinfection and gilt management in wean-to-finish barns. In particular, we observed a high prevalence and long-term survival of PEDV in slurries, posing a critical challenge to PED eradication and highlighting the necessity for consecutive testing of barn slurry samples and for the management of infected manure to control PEDV. Genetic analysis of PEDVs in this farm indicated that genetic drift continued in the spike gene, with a substitution rate of 1.683 × 10−4 substitutions/site/year. Our study underlines the need for active monitoring and surveillance of PEDV in herds and their environments, along with the coordinated means, to eliminate the virus and maintain a negative herd. The tools described in this study will serve as a framework for regional and national PED eradication programs

Bio–Microfabrication of 2D and 3D Biomimetic Gut-on-a-Chip

Traditional goal of microfabrication was to limitedly construct nano- and micro-geometries on silicon or quartz wafers using various semiconductor manufacturing technologies, such as photolithography, soft lithography, etching, deposition, and so on. However, recent integration with biotechnologies has led to a wide expansion of microfabrication. In particular, many researchers studying pharmacology and pathology are very interested in producing in vitro models that mimic the actual intestine to study the effectiveness of new drug testing and interactions between organs. Various bio–microfabrication techniques have been developed while solving inherent problems when developing in vitro micromodels that mimic the real large intestine. This intensive review introduces various bio–microfabrication techniques that have been used, until recently, to realize two-dimensional and three-dimensional biomimetic experimental models. Regarding the topic of gut chips, two major review subtopics and two-dimensional and three-dimensional gut chips were employed, focusing on the membrane-based manufacturing process for two-dimensional gut chips and the scaffold-based manufacturing process for three-dimensional gut chips, respectively

Comparison of Deep Reinforcement Learning and PID Controllers for Automatic Cold Shutdown Operation

Many industries apply traditional controllers to automate manual control. In recent years, artificial intelligence controllers applied with deep-learning techniques have been suggested as advanced controllers that can achieve goals from many industrial domains, such as humans. Deep reinforcement learning (DRL) is a powerful method for these controllers to learn how to achieve their specific operational goals. As DRL controllers learn through sampling from a target system, they can overcome the limitations of traditional controllers, such as proportional-integral-derivative (PID) controllers. In nuclear power plants (NPPs), automatic systems can manage components during full-power operation. In contrast, startup and shutdown operations are less automated and are typically performed by operators. This study suggests DRL-based and PID-based controllers for cold shutdown operations, which are a part of startup operations. By comparing the suggested controllers, this study aims to verify that learning-based controllers can overcome the limitations of traditional controllers and achieve operational goals with minimal manipulation. First, to identify the required components, operational goals, and inputs/outputs of operations, this study analyzed the general operating procedures for cold shutdown operations. Then, PID- and DRL-based controllers are designed. The PID-based controller consists of PID controllers that are well-tuned using the Ziegler–Nichols rule. The DRL-based controller with long short-term memory (LSTM) is trained with a soft actor-critic algorithm that can reduce the training time by using distributed prioritized experience replay and distributed learning. The LSTM can process a plant time-series data to generate control signals. Subsequently, the suggested controllers were validated using an NPP simulator during the cold shutdown operation. Finally, this study discusses the operational performance by comparing PID- and DRL-based controllers