Chronic myeloid leukemia (CML) has a bcr-abl chimera gene producing constitutive tyrosine kinase activity and leading to tumor formation. Tyrosine kinase inhibitor (TKI) is effective at treatment of CML; however, a long-term use of this drug is associated with appearance of TKI-resistant clones. Autophagy degrades the BCR-ABL chimeric proteins, a major culprit of CML growth, whereas inflammation inhibits the normal differentiation of hematopoietic stem cells (HSCs) into red blood cells (RBC) leading to myelodysplastic syndrome. Flavonoids are known to inhibit inflammation and activate autophagy. Thus, we investigated the effect of flavonoids, such as apigenin and hesperidin, on the differentiation of CML cells into RBC. In addition to flavonoids, we also examined the effects of the commonly used NSAIDs ethenzamide. Apigenin and hesperidin induced RBC differentiation and autophagy with or without sodium butyrate (NAB), an erythroid differentiation inducer. Apigenin and hesperidin are known to inhibit the production of prostaglandins. Moreover, hesperidin induced acid beta-glucosidase (GBA) in differentiated CML cells. Hesperidin could differentiate CML into RBC by maintaining autophagy flux and by inhibiting production of prostaglandin.

Daily eating of an apple can supplement lacking nutritional elements. Since the apple's peel also contains polyphenols and antioxidants, eating an apple with its peel provides a greater variety of nutrients. Therefore, it is essential to control the texture quality of apples when eaten with their peel. We propose a simple method to automatically evaluate the texture quality of the region between the peel and inner pulp, considering the “load” and “sound” generated when a wedge-formed probe pierces an apple through the peel. To evaluate the texture of apples, we employed a neural network model, which is widely used in the field of artificial intelligence. In the evaluation experiment, three brands of apples were prepared, and their textures were compared. Although the characteristics of load and sound between the three brands overlapped, the authors confirmed that the neural network model distinguished each brand with high accuracy. Herein, we provide an overview of the texture measurement equipment, neural network model, experiment method, results analysis, and an outlook on the prospect.

Although communication is a source of motivation for the elderly, it has been pointed out that the elderly must concentrate on maneuvering their electric wheelchairs, making it difficult for them to communicate with their companions. Therefore, based on WHILL's Model CR, we developed an electric wheelchair that automatically moves at a 45° angle behind the companion to facilitate communication with the companion. A depth camera mounted on the armrest was rotated 45° to the left to determine the position of the companion relative to the electric wheelchair. A deep learning microcontroller was installed in the foot space. The deep learning PC performed human image detection using Yolo from RGB images transmitted from the depth camera. The electric wheelchair was programmed to maintain a distance of 1 m and an angle of 45 degrees to the companion according to the distance D and angle Θ between the recognized bounding box and the companion obtained from the depth camera. As a result, the system successfully maintained a distance between the companion and the wheelchair in the range of 1 m to 2 m for 70% of the 20-meter run. Additionally, the angle was successfully maintained 84% of the time with a margin of error of ±10 degrees.

The implantation of ions into SiC is an indispensable process in semiconductor fabrication, which is the base material. Conventional ion implantation methods require high voltages to accelerate ions. Therefore, we aim to generate quadruply charged aluminum ions (Al4+) using an electron cyclotron resonance (ECR) ion source, which is relatively inexpensive and capable of generating multi-charged ions. The experiments were conducted using magnesium, which can evaporate at lower temperatures than aluminum. To improve the charge state of the generated multi-charged ions, we increased the amount of beam current of the multi-charged ions via the gas mixing method using helium gas as the process gas, which is lighter than the magnesium ions generated. Moreover, the bias disk method, in which a negative voltage is applied to an aluminum plate in the plasma chamber, was carried out. Quadruply charged magnesium ions (Mg4+) were detected at 863 nA. Since Mg4+ and Al4+ have similar ionization energies, we believe that Al4+ can be generated by increasing the temperature of the ceramic electric tube furnace to the evaporation temperature of aluminum using the existing experimental method.

Monitoring the tea plant pest population is critical for researchers and farmers. Pseudaulacaspis pentagona, a mulberry scale insect species, has been a severe pest for these plants. The short time window for spraying pesticides makes the species difficult to control. Therefore, monitoring is required to predict the optimal timing for control. The present study aimed at identifying the insect species and automatically counting the number of individuals. The dataset for the study included scanned images of sticky traps that captured the pest insects as well as their parasite wasps (Thomsonisca amathus). Two methods were used depending on the density of the captured insects. The object detection algorithm YOLOv4 was used for the RGB images. Accuracy was evaluated in terms of precision, recall, and F-measure, and for low-density insects their respective values were 0.89, 0.87, and 0.88 for P. pentagona, and 0.93, 0.93, and 0.93 for T. amathus. For high-density insects, the respective values were 0.68, 0.40, and 0.50 for P. pentagona, and 0.94, 0.90, and 0.92 for T. amathus. For high-density insects, a linear regression analysis was applied to the binarized images. RMSE, relative RMSE, bias, and relative bias were evaluated as 1.2  102, 1.1  10%, 5.1  10, and 4.7%, respectively. Combining the YOLOv4 and linear regression analysis successfully achieved insect species detection and population counting, which will increase monitoring capabilities for trap-captured pests and their natural enemies in tea gardens.