Motor control is a critical process for muscle contraction, which is initiated by nerve impulses governed by the motor cortex. This process is vital for performing activities of daily living (ADLs). Consequently, a disruption in communication between the brain and muscles, as seen in various chronic conditions and diseases, can impair bodily movement and ADLs. Evaluating the interaction between brain function and motor control is significant for the diagnosis and treatment of motor control disorders; moreover, it can contribute to the development of brain-computer interfaces (BCIs). The purpose of this study is to investigate brain activation in designed upper extremity motor control tasks in regulating the pushing force in different brain regions; and develop investigation methods to assess motor control tasks and brain activation using a robotic arm to guide upper extremity force and motor control. Eighteen healthy young adults were asked to perform upper extremity motor control tasks and recorded the hemodynamic signals. Functional Near-Infrared Spectroscopy (fNIRs) and robotic arms were used to assess brain activation and the regulation of pushing force and extremity motor control. Two types of motion, static and dynamic, move along a designated trajectory in both forward and backward directions, and three different force levels selected from a range of ADLs, including 4, 12, and 20 N, were used as force-regulating upper extremity motor control tasks. The hemodynamic responses were measured in specific regions of interest, namely the primary motor cortex (M1), premotor cortex (PMC), supplementary motor area (SMA), and prefrontal cortex (PFC). Utilizing a two-way repeated measures ANOVA with Bonferroni correction (p < 0.00625) across all regions, we observed no significant interaction effect between force levels and movement types on oxygenated hemoglobin (HbO) levels. However, in both contralateral (c) and ipsilateral (i) PFC, movement type—static versus dynamic—significantly affected brain activation. Additionally, cM1, iPFC, and PMC showed a significant effect of force level on brain activation.
This observational study aims to investigate the relationship between brain activation in specific regions and various motor tasks involving upper extremity movement with force control. Utilizing fNIRs, the research will monitor hemodynamic changes in four key brain areas: the prefrontal cortex (PFC), premotor cortex (PMC), supplementary motor area (SMA), and primary motor cortex (M1) during task performance. The primary population for this investigation consists of healthy young adults, allowing for a clearer understanding of how force control affects brain activation. The scope of the study includes assessing brain activation measured by fNIRs during upper extremity motor and force control tasks, as well as examining how upper extremity movements and force control influence brain activation.
คณะวิทยาศาสตร์
With the development of space technology, wide-field sky surveys using telescopes have expanded the range of new data available for time-domain astronomical research. Traditional data analysis methods can no longer respond quickly and accurately enough to the growing volume of data. Thus, classifying time-series data, such as light curves, has become a significant challenge in the era of big data. In modern times, analyzing light curves has become essential for using machine learning techniques to handle and filter through massive amounts of data. Machine learning algorithms can be divided into two categories: shallow learning and deep learning. Numerous researchers have proposed and developed a variety of algorithms for light curve classification. In this study, we experimented with Support Vector Machine (SVM) and XGBoost, which are shallow machine learning algorithms, as well as 1D-CNN and Long Short-Term Memory (LSTM), which are deep learning algorithms, which are branches of deep machine learning, to classify variable stars. The training and testing data used in this study were from the Optical Gravitational Lensing Experiment-III (OGLE-III), consisting of variable star data from the Large Magellanic Cloud (LMC), categorized into five main classes: Classical Cepheids, δ Scutis, eclipsing binaries, RR Lyrae stars, and Long-period variables. The results demonstrate the performance analysis of each machine learning algorithm type applied to light curve data, while also highlighting the accuracy and statistical metrics of the algorithms used in the experiments.
คณะวิทยาศาสตร์
Listeriosis is a severe foodborne illness characterized by a fatality rate exceeding 30%, attributed to the pathogen Listeria monocytogenes. This study evaluated 160 lactic acid bacteria (LAB) isolated from Thai pickled crabs for their potential as agents against L. monocytogenes and for their probiotic properties and probiogenomic characteristics. Among these strains, strain DRC3-2 exhibited activity through the synthesis of bacteriocin DRC3-2, which significantly inhibited L. monocytogenes ATCC 19115 in spot-on-lawn assays. Phenotypic and whole-genome analyses revealed that strain DRC3-2 thrived in environments with 2-6% NaCl, pH values ranging from 3 to 9, and temperatures between 25 and 45°C. Based on average nucleotide identity (ANI) and digital DNA‒DNA hybridization (dDDH) values, strain DRC3-2 was taxonomically classified as Lactococcus lactis subsp. hordinae. The production of bacteriocin DRC3-2 peaked during the late stationary phase, following its synthesis in the early exponential growth phase. BAGEL4 analysis identified the putative novel bacteriocin DRC3-2 as lactococcin A and B, with respective bit-scores of 40.05 and 36.58. In silico safety assessments confirmed the nonpathogenic nature of strain DRC3-2 in humans, highlighting its absence of antibiotic resistance genes. Finally, this investigation underscores the novel bacteriocin DRC3-2 for application in the prevention and treatment of L. monocytogenes infections.
คณะสถาปัตยกรรม ศิลปะและการออกแบบ
This conceptual model, titled "DeHome", incorporates the principles of Deconstructivism in architectural design. It deconstructs the fundamental elements of a house—roof, columns, doors, windows, and bricks—separating them and reassembling them in a way that conveys fragmentation, contradiction, and movement. This design challenges the traditional concept of structural stability by enlarging key elements such as doors, windows, and columns, emphasizing distortion and the dynamic force of transformation. Beyond merely dismantling the physical structure of a house, this project reinterprets the very concept of "home" within the context of contemporary architecture.