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To provide diverse in-home services like elderly care, versatile activity recognition technology is essential. Radio-based methods, including WiFi CSI, RFID, and backscatter communication, are preferred due to their minimal privacy intrusion, reduced physical burden, and low maintenance costs. However, these methods face challenges, including environmental dependence, proximity limitations between the device and the user, and untested accuracy amidst various radio obstacles such as furniture, appliances, walls, and other radio waves. In this paper, we propose a frequency-shift backscatter tag-based in-home activity recognition method and test its feasibility in a near-real residential setting. Consisting of simple components such as antennas and switches, these tags facilitate ultra-low power consumption and demonstrate robustness against environmental noise because a context corresponding to a tag can be obtained by only observing frequency shifts. We implemented a sensing system consisting of SD-WiFi, a software-defined WiFi AP, and physical switches on backscatter tags tailored for detecting the movements of daily objects. Our experiments demonstrate that frequency shifts by tags can be detected within a 2 m range with 72% accuracy under the line of sight (LoS) conditions and achieve a 96.0% accuracy (F-score) in recognizing seven typical daily living activities with an appropriate receiver/transmitter layout. Furthermore, in an additional experiment, we confirmed that increasing the number of overlaying packets enables frequency shift-detection even without LoS at distances of 3–5 m.

Thermal images are widely used for various healthcare applications and advanced research. However, thermal images captured by smartphone thermal cameras are not accurate for monitoring human body temperature due to the small body that is vulnerable to temperature change. In this paper, we propose ThermalWrist, a dynamic offset correction method for thermal images captured by smartphone thermal cameras. We fully utilize the characteristic that is specific to thermal cameras: the relative temperatures in a single thermal image are highly reliable, although the absolute temperatures fluctuate frequently. To correct the offset error, ThermalWrist combines thermal images with a reliable absolute temperature obtained by a wristband sensor based on the above characteristic. The evaluation results in an indoor air-conditioned environment shows that the mean absolute error and the standard deviation of face temperature measurement error decrease by 49.4% and 64.9%, respectively. In addition, Pearson’s correlation coefficient increases by 112%, highlighting the effectiveness of ThermalWrist. We also investigate the limitation with respect to the ambient temperature where ThermalWrist works effectively. The result shows ThermalWrist works well in the normal office environment, which is 22.91 °C and above.

The authors present metasurface‐inspired maintenance‐free Internet of things (IoT) tags that can be characterised not only by frequency‐domain profiles but also by time‐domain profiles. In particular, time‐domain characterisation is made possible by implementing the waveform‐selective mechanisms of recently developed circuit‐based metasurfaces that behave differently, even at the same frequency, in accordance with the pulse duration of the incident wave. The proposed designs are numerically and experimentally validated and potentially contribute to accommodating an increasing number of IoT tags within a single wireless network while reducing maintenance effort. Proposed metasurface‐inspired maintenance‐free IoT tags are characterised not only in frequency domain but also in time domain. The use of both frequency‐ and time‐domain profiles enables us to increase the number of IoT tags accommodated within a single wireless network without replacement of batteries.

IoT sensors are crucial for visualizing multidimensional and multimodal information and enabling future IT applications/services such as cyber-physical spaces, digital twins, autonomous driving, smart cities and virtual/augmented reality (VR or AR). However, IoT sensors need to be battery-free to realistically manage and maintain the growing number of available sensing devices. Here, we provide a novel sensor design approach that employs metasurfaces to enable multifunctional sensing without requiring an external power source. Importantly, unlike existing metasurface-based sensors, our metasurfaces can sense multiple physical parameters even at a fixed frequency by breaking classic harmonic oscillations in the time domain, making the proposed sensors viable for usage with limited frequency resources. Moreover, we provide a method for predicting physical parameters via the machine learning-based approach of random forest regression. The sensing performance was confirmed by estimating the temperature and light intensity, and excellent determination coefficients larger than 0.96 were achieved. Our study affords new opportunities for sensing multiple physical properties without relying on an external power source or requiring multiple frequencies, which markedly simplifies and facilitates the design of next-generation wireless communication systems.Metasurface-based sensors provide a battery-free sensing solution for maintaining numerous IoT devices with little human resources. However, the conventional method exploited resonant mechanisms associated with multiple physical parameters through different frequencies, although available frequencies were strictly limited. We report the first sensor design approach using circuit-based metasurfaces that offer a higher degree of freedom to design time-varying scattering profiles associated with multiple physical properties at a single frequency. Our prototype detects light intensity and temperature with an excellent determination coefficient above 0.96 via a machine-learning technique.

Background: Fruits and vegetables are generally rich in antioxidants such as carotenoids. Consumption of carotenoids is expected to have benefits on cognitive functions in humans. However, previous randomized controlled trials (RCT) using carotenoids have reported inconsistent results. Therefore, this systematic review (SR) aimed to summarize the effect of carotenoid intake on cognitive functions in humans. Method: PubMed, Cochrane Library, Web of Science, and PsychoINFO were searched for research papers on carotenoid intake with the criteria that 1) oral carotenoid intake was evaluated using RCTs, 2) participants were healthy young, middle-aged, or older, and 3) cognitive functions were measured using RCTs. Results: Five studies using lutein and two studies using astaxanthin met the inclusion criteria. Consumption of lutein and its isomer showed consistent results in selective improvement of visual episodic memory in young and middle-aged adults while inhibition was observed in middle-aged and older adults. One of the two included astaxanthin studies reported a significant improvement of verbal episodic memory performance in middle-aged adults. Conclusion: This SR showed that the 10 mg lutein per day for twelve months can lead to improvement of cognitive functions. Due to the small number of studies, it is difficult to conclude whether astaxanthin would have a positive effect on cognitive functions.

Dysbiosis of the oral microbiome has been implicated in the onset and progression of periodontal diseases. An altered oral microbiome can significantly affect the concentration and composition ratio of bacterial-derived metabolites, thereby contributing to disease development. However, there is limited research on the role of metabolites derived from the oral microbiota. This study aimed to identify specific bacteria-derived metabolites and their contributions to pathogenicity. Mouth-rinsed water was collected from 24 patients with periodontal disease and 22 healthy individuals. We conducted a correlation analysis between periodontal disease-associated bacteria and metabolites present in mouth-rinsed water. We evaluated the effects of these metabolites on human gingival epithelial cells analysis of oral bacteria culture supernatants confirmed the origin of these metabolites. We identified 20 metabolites associated with bacteria that are significantly more prevalent in periodontal disease. Notably, propionate, succinate, citrulline, and homoserine—metabolites derived from the oral microbiome—were identified as being associated with periodontal disease. These results suggested that metabolites derived from the oral microbiota are involved in periodontal disease.

Background Acetaminophen (APAP) overdose induces severe oxidative stress followed by hepatocyte apoptosis/necrosis. Previous studies have indicated that endoplasmic reticulum (ER) stress is involved in the cell death process. Therefore, we investigated the effect of the chemical chaperone 4-phenyl butyric acid (PBA) on APAP-induced liver injury in mice. Methods Eight-week-old male C57Bl6/J mice were given a single intraperitoneal (i.p.) injection of APAP (450 mg/kg body weight), following which some were repeatedly injected with PBA (120 mg/kg body weight, i.p.) every 3 h starting at 0.5 h after the APAP challenge. All mice were then serially euthanized up to 12 h later. Results PBA treatment dramatically ameliorated the massive hepatocyte apoptosis/necrosis that was observed 6 h after APAP administration. PBA also significantly prevented the APAP-induced increases in cleaved activating transcription factor 6 and phosphorylation of c-Jun N-terminal protein kinase and significantly blunted the increases in mRNA levels for binding immunoglobulin protein, spliced X-box binding protein-1, and C/EBP homologous protein. Moreover, PBA significantly prevented APAP-induced Bax translocation to the mitochondria, and the expression of heme oxygenase-1 mRNA and 4-hydroxynonenal. By contrast, PBA did not affect hepatic glutathione depletion following APAP administration, reflecting APAP metabolism. Conclusions PBA prevents APAP-induced liver injury even when an APAP challenge precedes its administration. The underlying mechanism of action most likely involves the prevention of ER stress-induced apoptosis/necrosis in the hepatocytes during APAP intoxication.

Background Oral dysfunctions that affect masticatory function, such as tooth loss, reportedly lead to malnutrition, which contributes to cognitive decline and the onset and progression of dementia. Previous studies on oral dysfunction have focused on older people already in need of nursing care. Therefore, we conducted a study of older people able to travel independently or with minor assistance to examine the relationship between oral and cognitive function in memory clinic study participants classified as cognitively normal, with mild cognitive impairment, or with dementia. Methods Participants were 178 study participants (median age: 79.0 years, 49.4% female) attending the memory clinic at the National Center for Geriatrics and Gerontology, Japan. Following provision of informed consent, cognitive function was assessed using clinical dementia ratings and oral function assessed using number of present teeth, occlusal force, oral diadochokinesis, repetitive salivary swallowing test, and tongue pressure. The relationships between cognitive and oral function were evaluated using multivariable logistic regression analyses. Results Of the participants, 25, 92, and 61 were classified as cognitively normal, with mild cognitive impairment, and with dementia, respectively. Oral diadochokinesis /ka/ was associated with a high risk of mild cognitive impairment: adjusted odds ratio, 6.930 (95% confidence interval: 1.284–37.402, P  = 0.024). Repetitive salivary swallowing test score was associated with a high-risk tendency for dementia: adjusted odds ratio, 4.171 (95% confidence interval: 0.981–17.736, P for trend = 0.053). Number of present teeth, occlusal force, and tongue pressure were not associated with mild cognitive impairment or dementia. Conclusion Oral diadochokinesis /ka/ was independently associated with mild cognitive impairment. A well-designed cohort study is needed to clarify the causal relationships between cognitive decline and oral diadochokinesis. The ability to identify study participants with possible mild cognitive impairment through regular dental examinations would help to prevent dementia. Trial registration This study was registered to UMIN Clinical Trials Registry (UMIN000048126) at 2022–06-21.

Background Endoscopy is an important form of clinical gastroenterology education because it gives students the opportunity to learn about diagnosis procedures and even treatment. During the COVID-19 pandemic, medical students were observed from outside the endoscopy room due to the risk of airborne infection. In this study, we investigated the efficacy of combining endoscopy education with doctor’s-eye-view videos of the procedure obtained using live-action cameras (GoPro®). Methods From February to May 2021, endoscopists wore GoPro Hero8 cameras on their heads to display a doctor’s-eye view video outside the room. The efficacy of the GoPro videos in combination with endoscopic monitoring was evaluated by 15 participating medical students. The participants rated the efficacy on a 5-point scale and commented on the positive and negative points. Results A total of 78.6% of participants evaluated the GoPro as good; 57.2% answered that it increased their understanding, with 71.4% stating that it increased their understanding of procedures in particular. A total of 85.7% of the students answered that their interest in endoscopy had increased, and 85.7% evaluated the benefit of the GoPro videos as good. In addition, 64.3% answered that the method was effective in preventing COVID-19 infection. Education using GoPro videos enabled students to feel as if they were conducting the endoscopy themselves and enabled them to concentrate on learning. Conclusions Practical endoscopic education using a GoPro is an effective educational tool that not only increases understanding of endoscopic practice but also stimulates students’ interest and awareness of their future as doctors.