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Factory machine diagnosis is important for preventive maintenance. Diagnosis equipment needs to be reliable and easy to handle, and the diagnostic results should be easily recognizable. An equipment that meets the above conditions is developed; it comprises a laser beam source, leaf spring with a mirror and a magnet as a position-adjustable mass, a copper plate, and a remote switch, if necessary. The principle is based on optical lever and mechanical vibration resonance. The laser spot vibration trajectory is irradiated onto the wall, ceiling, floor of a factory, or the housing of a machine as a screen. An equipment (29 mm $\times35$ mm $\times22$ mm) placed on the vibrating machine irradiates a laser beam and the magnified vibration is displayed on the screen. In this paper, the theoretical model and the equipment are presented, and the measured vibrations for a test vibrator and an actual machine are shown. A peak-to-peak vibration of 0.006 mm measured by a vibrometer is magnified to the 115 mm laser beam spot trajectory. The magnification is 38,333 times (91.6 dB), which is even larger on screens placed farther away. The calculation results by the theoretical model are in good agreement with the measurements.

This paper describes a novel level sensor that is noninvasive to nonmetallic tanks and noncontact to materials stored in them. It detects the materials from the outside of a tank by the use of microwave Doppler modules. The output AC component of Doppler modules has been used as moving object detectors. Here, we focus on the output DC component, which is proportional to the intensity of the reflected microwave signals from the stored material. We propose a sensor to detect the level of very low dielectric materials. We build a theoretical model based on multiple reflections of microwaves from the surfaces between different dielectric materials and demonstrate the sensor’s theoretical potential. Experiments were carried out using the sensor to verify its feasibility. The sensor detected levels of Styrene foam with dielectric constant 1.02 from the outside of a 3.0 mm thick acrylic resin tank under optimal conditions. Furthermore, the S/N ratio of the Styrene foam measurement was over 19 dB for the drift noise caused by the change in environmental temperature from 20 °C to 80 °C. The S/N ratio of the change in tap-water’s temperature ranging from 0.5 °C to 77 °C was 18 dB at the reference of 23 °C, and for the change in conductivity ranging from 0.35 to 26 mS/cm was 33 dB.

We investigated the switching dynamics of optical modulators consisting of a Si waveguide with a VO2 cladding layer by utilizing the photothermal effect, which induces a metal–insulator transition in VO2. The devices exhibited stable optical switching with a high extinction ratio exceeding 16 dB. The switching time of the insulator-to-metal transition (heating process) ranged from tens of nanoseconds to microseconds depending on the incident light power, and that of the metal-to-insulator transition (cooling process) was several microseconds regardless of the incident light power. The heat transfer in the devices was numerically simulated to reproduce the switching characteristics and revealed that the temperature change in the first few micrometers of the VO2/Si waveguide governed the switching time. The thermal structural design of the device is thus of key importance to improve the switching speed of the device.

Background As elsewhere in low- and middle-income countries, due to limited fiscal resources, universal health coverage (UHC) remains a challenge in Cambodia. Since 2016, the National Social Security Fund (NSSF) has implemented a social health insurance scheme with a contributory approach for formal sector workers. However, informal sector workers and dependents of formal sector workers are still not covered by this insurance because it is difficult to set an optimal amount of contribution for such individuals as their income levels are inestimable. The present study aims to develop and validate an efficient household income-level assessment model for Cambodia. We aim to help the country implement a financially sustainable social health insurance system in which the insured can pay contributions according to their ability. Methods This study will use nationally representative data collected by the Cambodia Socio-Economic Survey (CSES), covering the period from 2009 to 2019, and involving a total of 50,016 households. We will employ elastic net regression analysis, with per capita disposable income based on purchasing power parity as the dependent variable, and individual and community-level socioeconomic and demographic characteristics as independent variables. These analyses aim to create efficient income-level assessment models for health insurance contribution estimation. To fully capture socioeconomic heterogeneity, sub-group analyses will be conducted to develop separate income-level assessment models for urban and rural areas, as well as for each province. Discussion This research will help Cambodia implement a sustainable social health insurance system by collecting optimal amount of contributions from each socioeconomic group of the society. Incorporation of this approach into existing NSSF schemes will enhance the country’s current efforts to prevent impoverishing health expenditure and to achieve UHC.

A vertically-curved-waveguide surface optical coupler for coupling with a 10-µm-MFD standard single-mode optical fiber was developed. The fabricated coupler showed 1-dB bandwidths of >160 nm and >120 nm and coupling losses of 3.9 dB and 4.0 dB for TE and TM polarization.

IMPORTANCE: Identifying psychosis subgroups could improve clinical and research precision. Research has focused on symptom subgroups, but there is a need to consider a broader clinical spectrum, disentangle illness trajectories, and investigate genetic associations. OBJECTIVE: To detect psychosis subgroups using data-driven methods and examine their illness courses over 1.5 years and polygenic scores for schizophrenia, bipolar disorder, major depression disorder, and educational achievement. DESIGN, SETTING, AND PARTICIPANTS: This ongoing multisite, naturalistic, longitudinal (6-month intervals) cohort study began in January 2012 across 18 sites. Data from a referred sample of 1223 individuals (765 in the discovery sample and 458 in the validation sample) with DSM-IV diagnoses of schizophrenia, bipolar affective disorder (I/II), schizoaffective disorder, schizophreniform disorder, and brief psychotic disorder were collected from secondary and tertiary care sites. Discovery data were extracted in September 2016 and analyzed from November 2016 to January 2018, and prospective validation data were extracted in October 2018 and analyzed from January to May 2019. MAIN OUTCOMES AND MEASURES: A clinical battery of 188 variables measuring demographic characteristics, clinical history, symptoms, functioning, and cognition was decomposed using nonnegative matrix factorization clustering. Subtype-specific illness courses were compared with mixed models and polygenic scores with analysis of covariance. Supervised learning was used to replicate results in validation data with the most reliably discriminative 45 variables. RESULTS: Of the 765 individuals in the discovery sample, 341 (44.6%) were women, and the mean (SD) age was 42.7 (12.9) years. Five subgroups were found and labeled as affective psychosis (n = 252), suicidal psychosis (n = 44), depressive psychosis (n = 131), high-functioning psychosis (n = 252), and severe psychosis (n = 86). Illness courses with significant quadratic interaction terms were found for psychosis symptoms (R(2) = 0.41; 95% CI, 0.38-0.44), depression symptoms (R(2) = 0.28; 95% CI, 0.25-0.32), global functioning (R(2) = 0.16; 95% CI, 0.14-0.20), and quality of life (R(2) = 0.20; 95% CI, 0.17-0.23). The depressive and severe psychosis subgroups exhibited the lowest functioning and quadratic illness courses with partial recovery followed by reoccurrence of severe illness. Differences were found for educational attainment polygenic scores (mean [SD] partial η(2) = 0.014 [0.003]) but not for diagnostic polygenic risk. Results were largely replicated in the validation cohort. CONCLUSIONS AND RELEVANCE: Psychosis subgroups were detected with distinctive clinical signatures and illness courses and specificity for a nondiagnostic genetic marker. New data-driven clinical approaches are important for future psychosis taxonomies. The findings suggest a need to consider short-term to medium-term service provision to restore functioning in patients stratified into the depressive and severe psychosis subgroups.

Using UV adhesive mixed with glass spacer beads, vertical surface connection of optical fibers to silicon photonic chips via elephant couplers was realized with wavelength and polarization insensitiveness at temperatures from -18.5°C to 90°C.

This paper describes a novel acoustic-tube level switch that detects hot powder and finely gained bulk. The tube length $L$ is selected as $L=n\times \textit {(half wavelength)}$ and the input port of the tube is acoustically driven by a piezo sounder. When the output detection port is covered by powder and bulk, the electric impedance of the sounder increases with the increase of the acoustic impedance of the tube. The wavelength increases proportionally to the temperature, which causes a deviation from the optimal length $L$ above. However, theoretical studies showed that covering the detection port mostly influences the acoustic viscosity and robust to the temperature. As a result, the method worked well in a wide temperature range. The method operated consistently in the range ±50 °C from the reference and detected powder and bulk with 13-kg/ $\text{m}^{3}$ bulk density. In addition, the technique reliably detected the level of gravel heated to 450 °C; in short, the tube functioned as a heat radiator. Furthermore, the sound at the detection port could blow out dust accumulated in the tube. A dust filter located at the quarter-wavelength position had little influence on the normal measurement function, even for a dust layer of 26.5-mm thickness.

In this paper, we present a novel respirometer using the effect of piezo devices and show its application to triage. We found that blowing on the piezo device generated several 100 mV voltage and also synchronizes with the respiration. Our detailed investigations of the phenomena showed that it was caused by the pyroelectric effect. In general, the piezo device when used as a sensing device generates output voltage in a batteryless manner and also functions as a buzzer, which can lead to a compact, simple and low-power respirometer. Here, the piezo device was used as a base of respirometer and not only as a respirometer, but also as an alarm sound generator. Thus, the proposed respirometer was realized only by one piezo device and a low-powered microprocessor driven by a small battery. We applied the respirometer to triage and realized a triage sensing system. In the system, we employed the triage priority determination procedure defined as an international standard. The triage sensing system set in a mask detects respiration and displays its condition by turning an LED on and off, synchronizing the respiration and also generating the alarm sound when the respiration falls into the pre-specified ill conditions.

The objective of this paper is to understand the characteristics of the phenomena in piezo devices in a better manner, and to demonstrate a novel application for triage. That is, we focus not only the piezo effect, but also the pyroelectric effect of devices, which may expand the possibility of their application fields. To accomplish this, instead of the conventional equivalent electric circuit, we use a lumped-mass mathematical model of the device based on electrostatics and mechanics using a block diagram and transfer functions. The proposed model shows that the piezo device has internal feedback, indicating that it can function as a multiple-input/multiple-output sensor and/or actuator with reversible characteristics. These characteristics allow us to apply piezo devices to triage to detect the vital signs of heartbeat and respiration when the device is set inside a mask. We developed a simple and robust low-power, mask-type triage sensor that visualizes the respiration and heartbeat.

An optical-vortex multiplexer/demultiplexer using vertically curved Si waveguides was developed. Multiplexing/demultiplexing with the lowest crosstalk of 23 dB was demonstrated for five multiple optical vortices.

Silicon photonics enabling ultra-small photonic integrated circuits induces a necessity to develop efficient optical couplers that connect silicon waveguides with optical fibers or offchip other optical components. Vertical couplers are promising for both wafer-level testing and the integration of optical components on the chip surface, but so far grating couplers have been the only solution virtually. Very recently, we have developed a few-micron-scale vertically-curved silicon waveguide coupler “elephant coupler” formed by ion implantation method. This paper demonstrates that the coupler has high coupling efficiency, weak wavelength dependence, and weak incident angle dependence of wavelength window, which are not obtained by the grating couplers. The paper also demonstrates that the thermal annealing treatment can reduce optical propagation loss induced by the ion implantation.