Cluster Analysis of Subjective Shoulder Stiffness and Muscle Hardness: Associations with Central Sensitization-Related Symptoms.

: Understanding the relationships between subjective shoulder stiffness, muscle hardness, and various factors is crucial. Our cross-sectional study identified subgroups of shoulder stiffness based on symptoms and muscle hardness and investigated associated factors. : measures included subjective stiffness, pain, muscle hardness, and factors like physical and psychological conditions, pressure pain threshold, postural alignment, heart rate variability, and electroencephalography in 40 healthy young individuals.

The Impact of Stretching Intensities on Neural and Autonomic Responses: Implications for Relaxation.

Stretching is an effective exercise for increasing body flexibility and pain relief. This study investigates the relationship between stretching intensity and relaxation effects, focusing on brainwaves and autonomic nervous system (ANS) activity. We used a crossover design with low- and high-intensity conditions to elucidate the impact of varying stretching intensities on neural activity associated with relaxation in 19 healthy young adults.

Large-Scale Molecular Dynamics Simulation for Ground and Excited States Based on Divide-and-Conquer Long-Range Corrected Density-Functional Tight-Binding Method.

In this study, divide-and-conquer (DC) based density-functional tight-binding (DFTB) and time-dependent density-functional tight-binding (TD-DFTB) methods were developed using long-range correction (LC), which resolved the underestimation of energy gaps between the highest occupied molecular orbital and lowest unoccupied molecular orbital. We implemented the LC term by the entrywise product for the effective utilization of the math kernel library. Test calculations of formaldehyde in explicit water molecules demonstrate the efficiency of the developed method.

GPU-Accelerated Large-Scale Excited-State Simulation Based on Divide-and-Conquer Time-Dependent Density-Functional Tight-Binding.

The present study implemented the divide-and-conquer time-dependent density-functional tight-binding (DC-TDDFTB) code on a graphical processing unit (GPU). The DC method, which is a linear-scaling scheme, divides a total system into several fragments. By separately solving local equations in individual fragments, the DC method could reduce slow central processing unit (CPU)-GPU memory access, as well as computational cost, and avoid shortfalls of GPU memory.

Development of Large-Scale Excited-State Calculations Based on the Divide-and-Conquer Time-Dependent Density Functional Tight-Binding Method.

In this study, the divide-and-conquer (DC) method was extended to time-dependent density functional tight-binding (TDDFTB) theory to enable excited-state calculations of large systems and is denoted by DC-TDDFTB. The efficient diagonalization algorithms of TDDFTB and DC-TDDFTB methods were implemented into our in-house program. Test calculations of polyethylene aldehyde and p-coumaric acid, a pigment in photoactive yellow protein, in water demonstrate the high accuracy and efficiency of the developed DC-TDDFTB method.