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This study investigated the impact of clothing on robot appearance, particularly in scenarios where a single robot performs multiple tasks. Clothing depicts an individual’s role and capability toward others. Applying this effect to robot appearance design can enable an individual robot to express roles and capabilities suitable for multiple tasks. This makes it a potentially effective approach to robot appearance design. Our experiments first investigated the user acceptance of robots wearing clothing. Subsequently, we investigated the impact of robot attire on user behavior and impressions in a shared workspace. Our results indicate that users prefer robots to wear clothing only during cooking. In addition, in scenarios wherein robots and users share a workspace while performing different tasks, robot clothing is associated with negative user impressions. These observations indicate that even when users express a preference for clothed robots, the actual effect may not be positive and can vary depending on the task and context of use. Therefore, the decision to clothe a robot requires cautious consideration.

Understanding the growth status of fruits can enable precise growth management and improve the product quality. Previous studies have rarely used deep learning to observe changes over time, and manual annotation is required to detect hidden regions of fruit. Thus, additional research is required for automatic annotation and tracking fruit changes over time. We propose a system to record the growth characteristics of individual apples in real time using Mask R-CNN. To accurately detect fruit regions hidden behind leaves and other fruits, we developed a region detection model by automatically generating 3000 composite orchard images using cropped images of leaves and fruits. The effectiveness of the proposed method was verified on a total of 1417 orchard images obtained from the monitoring system, tracking the size of fruits in the images. The mean absolute percentage error between the true value manually annotated from the images and detection value provided by the proposed method was less than 0.079, suggesting that the proposed method could extract fruit sizes in real time with high accuracy. Moreover, each prediction could capture a relative growth curve that closely matched the actual curve after approximately 150 elapsed days, even if a target fruit was partially hidden.

Since the aggregation-induced emission (AIE) phenomenon was first reported by Tang et al., much effort has been devoted to the development of solid-state luminescent molecules by chemists worldwide. Our group successfully developed fluorinated tolanes as novel compact π-conjugated luminophores with blue photoluminescence (PL) in the crystalline state. Moreover, we reported the yellow-green PL molecules based on their electron-density distributions. In the present study, we designed and synthesized fluorinated tolanes with various amine-based donors and evaluated their photophysical properties. The carbazole-substituted fluorinated tolane exhibited strong PL in the solution state, whereas piperidine- or phenothiazine-substituted fluorinated tolanes showed a dramatic decrease in PL efficiency. Notably, fluorinated tolanes with piperidine or phenothiazine substituents displayed yellow-to-orange PL in the crystalline state; this may have occurred because these tolanes exhibited tightly packed structures formed by intermolecular interactions, such as H···F hydrogen bonds, which suppressed the non-radiative deactivation process. Moreover, fluorinated tolanes with amine-based donors exhibited AIE characteristics. We believe that these yellow-to-orange solid PL molecules can contribute to the development of new solid luminescent materials.

The development of organic light-emitting devices has driven demand for new luminescent materials, particularly after the 2001 discovery of aggregation-induced emission. This study focuses on fluorinated diphenylacetylene-based luminescent molecules, revealing that specific molecular modifications can enhance fluorescence and achieve a wide range of photoluminescence colors. A simple and effective luminescence color-tuning method is proposed to investigate the photoluminescence behavior of two-component polymer dispersion films blended with two types of fluorinated diphenylacetylenes, namely blue- and yellow- or red-fluorescent fluorinated diphenylacetylenes. It is confirmed that if blue and green–yellow or yellow fluorophores are blended in appropriate ratios, a binary blend with color coordinates (0.20, 0.32) can be achieved, which approaches the white point of pure white emission. These findings contribute to the development of effective lighting and display devices as new white-light-emitting materials.

Photo-induced rapid control of molecular assemblies, such as micelles and vesicles, enables effective and on-demand release of drugs or active components, with applications such as drug delivery systems (DDS) and cosmetics. Thus far, no attempts to optimize the responsiveness of photoresponsive molecular assemblies have been published. We previously reported photoresponsive surfactants bearing a lophine dimer moiety that exhibit fast photochromism in confined spaces, such as inside a molecular assembly. However, rapid control of the micelle structures and solubilization capacity have not yet been demonstrated. In the present work, photo-induced morphological changes in micelles were monitored using in-situ small-angle neutron scattering (SANS) and UV/Vis absorption spectroscopy. An amphiphilic lophine dimer (3TEG-LPD) formed elliptical micelles. These were rapidly elongated by ultraviolet light irradiation, which could be reversed by dark treatment, both within 60 s. For a solution of 3TEG-LPD micelles solubilizing calcein as a model drug molecule, fluorescence and SANS measurements indicated rapid release of the incorporated calcein into the bulk solvent under UV irradiation. Building on these results, we investigated rapid controlled release via hierarchical chemical processes: photoisomerization, morphological changes in the micelles, and drug release. This rapid controlled release system allows for effective and on-demand DDS.

The potential of unidentified microorganisms for academic and other applications is limitless. Plants have diverse microbial communities associated with their biomes. However, few studies have focused on the microbial community structure relevant to tree bark. In this report, the microbial community structure of bark from the broad-leaved tree was analyzed. Both a culture-independent approach using polymerase chain reaction (PCR) amplification and next generation sequencing, and bacterial isolation and sequence-based identification methods were used to explore the bark sample as a source of previously uncultured microorganisms. Molecular phylogenetic analyses based on PCR-amplified 16S rDNA sequences were performed. At the phylum level, and were relatively abundant in the bark. In addition, microorganisms from the phyla , , , , and candidate division FBP, which contain many uncultured microbial species, existed in the bark. Of the 30 genera present at relatively high abundance in the bark, some genera belonging to the phyla mentioned were detected. A total of 70 isolates could be isolated and cultured using the low-nutrient agar media DR2A and PE03. Strains belonging to the phylum were isolated most frequently. In addition, the newly identified bacterial strain IAP-33, presumed to belong to , was isolated on PE03 medium. Of the isolated bacteria, 44 strains demonstrated less than 97% 16S rDNA sequence-similarity with type strains. Molecular phylogenetic analysis of IAD-21 showed the lowest similarity (79%), and analyses suggested it belongs to candidate division FBP. Culture of the strain IAD-21 was deposited in Japan Collection of Microorganisms (JCM) and Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ) as JCM 32665 and DSM 108248, respectively. Our results suggest that a variety of uncultured microorganisms exist in bark. Microorganisms acquirable from the bark may prove valuable for academic pursuits, such as studying microbial ecology, and the bark might be a promising source of uncultured bacterial isolates.

To establish a safer and more efficient treatment strategy with mini-endoscopic combined intrarenal surgery (ECIRS), the present study aimed to develop models to predict the outcomes of mini-ECIRS in patients with renal and/or ureteral stones. We retrospectively analysed consecutive patients with renal and/or ureteral stones who underwent mini-ECIRS at three Japanese tertiary institutions. Final treatment outcome was evaluated by CT imaging at 1 month postoperatively and stone free (SF) was defined as completely no residual stone or residual stone fragments ≤ 2 mm. Three prognostic models (multiple logistic regression, classification tree analysis, and machine learning-based random forest) were developed to predict surgical outcomes using preoperative clinical factors. Clinical data from 1432 ECIRS were pooled from a database registered at three institutions, and 996 single sessions of mini-ECIRS were analysed in this study. The overall SF rate was 62.3%. The multiple logistic regression model consisted of stone burden ( P  < 0.001), number of involved calyces ( P  < 0.001), nephrostomy prior to mini-ECIRS ( P  = 0.091), and ECOG-PS ( P  = 0.110), wherein the area under the curve (AUC) was 70.7%. The classification tree analysis consisted of the number of involved calyces with an AUC of 61.7%. The random forest model showed that the top predictive variable was the number of calyces involved, with an AUC of 91.9%. Internal validation revealed that the AUCs for the multiple logistic regression model, classification tree analysis and random forest models were 70.4, 69.6 and 85.9%, respectively. The number of involved calyces, and a smaller stone burden implied a SF outcome. The machine learning-based model showed remarkably high accuracy and may be a promising tool for physicians and patients to obtain proper consent, avoid inefficient surgery, and decide preoperatively on the most efficient treatment strategies, including staged mini-ECIRS.

Mini-endoscopic combined intrarenal surgery (ECIRS) offers improved advantages in the treatment of renal stones. However, the factors influencing the operative time remain poorly understood. This study aimed to identify the factors that enhance treatment planning and minimize complications. Clinical data from consecutive patients who underwent mini-ECIRS for renal stones and achieved a stone-free status between 2015 and 2021 at three high-volume centers in Japan were analyzed. The final treatment outcome was evaluated by computed tomography imaging at postoperative 1 month, and a successful outcome was defined as complete stone-free or residual stone fragments < 4 mm. Logistic and linear regression models were used to predict the operative duration of mini-ECIRS. An operative time of ≥ 120 min was significantly associated with punctured pole and body mass index (BMI), and septic shock was only observed in patients with operative times of ≥ 120 min. The multivariate model for the operative time for mini-ECIRS identified five clinical factors: punctured pole, number of stones, number of involved calyces, BMI, and preoperative nephrostomy. We believe these findings will help surgeons and patients plan suitable treatment strategies, predict the additional need for a second mini-ECIRS or retrograde intrarenal surgery alone, and avoid severe complications.

The significance of “L” score in the radius (R), exophytic/endophytic (E), nearness (N), anterior/posterior (A), location (L); RENAL nephrometry scoring system remains unestablished compared to other subscores. This study assessed the influence of the “L” score on surgical and functional outcomes of RAPN, dividing renal tumors into medial and lateral relative to the kidney’s central line, to explore its impact on “L” score utility. A retrospective analysis was conducted on 668 RAPN patients, with 405 having medial and 263 lateral renal tumors. Patients who underwent RAPN were retrospectively analyzed, including 405 with medial renal tumors and 263 with lateral renal tumors. In medial tumors, the “L” score independently predicted non-achievement of trifecta ( P  = 0.011) and pentafecta ( P  = 0.032). In lateral tumors, the “L” score did not predict non-achievement of these outcomes. In conclusion, significance of the “L” score on surgical outcomes differs between medial and lateral tumors and it is strongly associated with outcomes in medial tumors, whereas its predictive value in lateral tumors is less marked. The RENAL nephrometry score lacks differentiation between medial and lateral tumors; therefore, surgeons should interpret “L” scores with caution.

Research on stress related to the COVID-19 pandemic has been dominated by the cases of healthcare workers, students, patients, and their stress during the COVID-19 pandemic. This study examined the relationship between the amount of stress change under the COVID-19 pandemic and demographic factors (age, sex, occupation, etc.) in residents of a large city and a rural area of Japan. A total of 1331 valid responses were received in June 2020 from residents of Tokyo, Osaka, and Nagano registered with a private research firm. We were able to identify 15 statistically significant variables out of 36 explanatory variables, which explained the significant increase in stress compared to the pre-pandemic period. Multiple-factor analysis showed that the relationship with people is a more significant explanatory variable for the level of increase in stress than the difference in environment between big cities (Tokyo, Osaka) and rural areas (Nagano), the type of housing, and the decrease in income compared to the pre-pandemic period.