ダイキボ センケイ ケイカク モンダイ ニオケル RPP アルゴリズム ノ ユウコウセイ ニツイテ

This paper presents an effective algorithm for solving a large-scale linear program. In a linear programming problem, the CPU time tends to increase remarkably according to the size of the problem. The RPP algorithm effectively candidates some constraints which constitute feasible solutions, because only about 5 to 20% of all constrants in the randomly generated problems will be tight at the optimum. We also present computational experience indicating that time savings of 84～97% (problem size 220×220-1400×1300) over the simplex method can be obtained by the RPP algorithm

ステロイドに著効を示した非特異的肉芽腫性前立腺炎の1例

A case of non-specific granulomatous prostatitis is reported. The patient, who had a history of sudden onset of high fever and acute urinary retention, had a hard prostate on digital rectal examination that gave us an impression of prostatic cancer. Since repeated biopsy specimens from the prostate showed granuloma formation with fibrinoid necrosis, the case was diagnosed as non-specific granulomatous prostatitis. Steroid therapy promptly resolved clinical symptoms along with marked histopathologic improvement

Effects of Home-Based Robotic Therapy Involving the Single-Joint Hybrid Assistive Limb Robotic Suit in the Chronic Phase of Stroke: A Pilot Study

Introduction. Robotic therapy has drawn attention in the rehabilitation field including home-based rehabilitation. A previous study has reported that home-based therapy could be more effective for increasing upper limb activity than facility-based therapy. The single-joint hybrid assistive limb (HAL-SJ) is an exoskeleton robot developed according to the interactive biofeedback theory, and several studies have shown its effectiveness for upper limb function in stroke patients. A study of home-based robotic therapy has shown to enhance rehabilitation effectiveness for stroke patient with a paretic upper limb. However, home-based therapy involving a HAL-SJ in stroke patients with paretic upper limbs has not been investigated. The present study aimed to investigate paretic upper limb activity and function with home-based robotic therapy involving a HAL-SJ in stroke patients. Materials and Methods. A home-based robotic therapy program involving a HAL-SJ was performed for 30 min per session followed by standard therapy for 30 min per session, 2 times a week, for 4 weeks (i.e., completion of all 8 sessions involved 8 h of rehabilitation), at home. After the intervention, patients were followed up by telephone and home visits for 8 weeks. The paretic upper limb activity and function were assessed using the Motor Activity Log (MAL; amount of use (AOU)), arm triaxial accelerometry (laterality index (LI)), the Fugl–Meyer assessment (FMA), and the action research arm test (ARAT), at baseline and week 4 and week 12 after the start of training. Results. The study included 10 stroke patients (5 men; mean age, 61.1 ± 7.1 years). The AOU scores and LI significantly improved at week 4 after the start of training (p<0.05). However, no significant changes were observed in the LI at week 12 (p=0.161) and the FMA scores at both week 4 and week 12 (p=0.059 and p=0.083, respectively). The ARAT scores significantly improved at both week 4 and week 12 (p<0.05). Conclusion. Home-based robotic therapy combined with conventional therapy could be a valuable approach for increasing paretic upper limb activity and maintaining paretic upper limb function in the chronic phase of stroke

A TWO-STAGE PROCEDURE FOR FIXED-SIZE CONFIDENCE REGION OF A CONDITIONAL MEAN

A two-stage procedure for constructing fixed-size confidence region of a conditional mean in multivariate normal distribution is proposed. A distribution of a statistic, which is appeared in the two-stage procedure, is approximated by an $F$-distribution. The accuracy of the approximation is examined by simulation. A numerical example is also given

A TWO-STAGE PROCEDURE FOR FIXED-SIZE CONFIDENCE REGION OF A CONDITIONAL MEAN

A two-stage procedure for constructing fixed-size confidence region of a conditional mean in multivariate normal distribution is proposed. A distribution of a statistic, which is appeared in the two-stage procedure, is approximated by an $F$-distribution. The accuracy of the approximation is examined by simulation. A numerical example is also given