Machine learning ensures rapid and precise selection of gold sea-urchin-like nanoparticles for desired light-to-plasmon resonance

Sustainable energy strategies, particularly solar-to-hydrogen production, are anticipated to overcome the global reliance on fossil fuels. Thereby, materials enabling the production of green hydrogen from water and sunlight are continuously designed,; e.g.; , ZnO nanostructures coated by gold sea-urchin-like nanoparticles, which employ the light-to-plasmon resonance to realize photoelectrochemical water splitting. But such light-to-plasmon resonance is strongly impacted by the size, the species, and the concentration of the metal nanoparticles coating on the ZnO nanoflower surfaces. Therefore, a precise prediction of the surface plasmon resonance is crucial to achieving an optimized nanoparticle fabrication of the desired light-to-plasmon resonance. To this end, we synthesized a substantial amount of metal (gold) nanoparticles of different sizes and species, which are further coated on ZnO nanoflowers. Subsequently, we utilized a genetic algorithm neural network (GANN) to obtain the synergistically trained model by considering the light-to-plasmon conversion efficiencies and fabrication parameters, such as multiple metal species, precursor concentrations, surfactant concentrations, linker concentrations, and coating times. In addition, we integrated into the model's training the data of nanoparticles due to their inherent complexity, which manifests the light-to-plasmon conversion efficiency far from the coupling state. Therefore, the trained model can guide us to obtain a rapid and automatic selection of fabrication parameters of the nanoparticles with the anticipated light-to-plasmon resonance, which is more efficient than an empirical selection. The capability of the method achieved in this work furthermore demonstrates a successful projection of the light-to-plasmon conversion efficiency and contributes to an efficient selection of the fabrication parameters leading to the anticipated properties

Prescriptions of Chinese Herbal Medicines for Insomnia in Taiwan during 2002

Chinese herbal medicine (CHM) has been commonly used for treating insomnia in Asian countries for centuries. The aim of this study was to conduct a large-scale pharmaco-epidemiologic study and evaluate the frequency and patterns of CHM use in treating insomnia. We obtained the traditional Chinese medicine (TCM) outpatient claims from the National Health Insurance in Taiwan for the year 2002. Patients with insomnia were identified from the diagnostic code of International Classification of Disease among claimed visiting files. Corresponding prescription files were analyzed, and an association rule was applied to evaluate the co-prescription of CHM. Results showed that there were 16 134 subjects who visited TCM clinics for insomnia in Taiwan during 2002 and received a total of 29 801 CHM prescriptions. Subjects between 40 and 49 years of age comprised the largest number of those treated (25.3%). In addition, female subjects used CHMs for insomnia more frequently than male subjects (female : male = 1.94 : 1). There was an average of 4.8 items prescribed in the form of either an individual Chinese herb or formula in a single CHM prescription for insomnia. Shou-wu-teng (Polygonum multiflorum) was the most commonly prescribed single Chinese herb, while Suan-zao-ren-tang was the most commonly prescribed Chinese herbal formula. According to the association rule, the most commonly prescribed CHM drug combination was Suan-zao-ren-tang plus Long-dan-xie-gan-tang, while the most commonly prescribed triple drug combination was Suan-zao-ren-tang, Albizia julibrissin, and P. multiflorum. Nevertheless, further clinical trials are needed to evaluate the efficacy and safety of these CHMs for treating insomnia

A Chip Architecture for Compressive Sensing Based Detection of IC Trojans

We present a chip architecture for a compressive sensing based method that can be used in conjunction with the JTAG standard to detect IC Trojans. The proposed architecture compresses chip output resulting from a large number of test vectors applied to a circuit under test (CUT). We describe our designs in sensing leakage power, computing random linear combinations under compressive sensing, and piggybacking these new functionalities on JTAG. Our architecture achieves approximately a 10× speedup and 1000× reduction in output bandwidth while incurring a small area overhead.Engineering and Applied Science

Photothermal responsivity of van der Waals material-based nanomechanical resonators

Nanomechanical resonators made from van der Waals materials (vdW NMRs) provide a new tool for sensing absorbed laser power. The photothermal response of vdW NMRs, quantified from the resonant frequency shifts induced by optical absorption, is enhanced when incorporated in a Fabry-Perot (FP) interferometer. Along with the enhancement comes the dependence of the photothermal response on NMR displacement, which lacks investigation. Here, we address the knowledge gap by studying electromotively driven niobium diselenide drumheads fabricated on highly reflective substrates. We use a FP-mediated absorptive heating model to explain the measured variations of the photothermal response. The model predicts a higher magnitude and tuning range of photothermal responses on few-layer and monolayer NbSe$_{2}$ drumheads, which outperform other clamped vdW drum-type NMRs at a laser wavelength of $532\,$nm. Further analysis of the model shows that both the magnitude and tuning range of NbSe$_{2}$ drumheads scale with thickness, establishing a displacement-based framework for building bolometers using FP-mediated vdW NMRs.Comment: 7 pages, 4 figure

Physical ergonomics in peripheral nerve block

The understanding of ergonomics is a vital competency for all peripheral nerve block operators. The essence of physical ergonomics for peripheral nerve block procedures can be summarised into three significant components: brain, musculoskeletal and needling. The first component includes strategies to optimise visuospatial neuroprocessing using equipment configuration. The second component reflects the careful planning of posture and position to improve procedural technique and reduce physical fatigue. The final component focuses on strategies to achieve needle beam alignment for optimal needle visualisation

Effects of and satisfaction with short message service reminders for patient medication adherence: a randomized controlled study

BACKGROUND: Medication adherence is critical for patient treatment. This study involved evaluating how implementing Short Message Service (SMS) reminders affected patient medication adherence and related factors. METHODS: We used a structured questionnaire to survey outpatients at three medical centers. Patients aged 20 years and older who were prescribed more than 7 days of a prescription medication were randomized into SMS intervention or control groups. The intervention group received daily messages reminding them of aspects regarding taking their medication; the control group received no messages. A phone follow-up was performed to assess outcomes after 8 days. Data were collected from 763 participants in the intervention group and 435 participants in the control group. RESULTS: After participants in the intervention group received SMS reminders to take medication or those in the control group received no messages, incidences of delayed doses were decreased by 46.4 and 78.8% for those in the control and intervention groups, respectively. The rate of missed doses was decreased by 90.1% for participants in the intervention group and 61.1% for those in the control group. We applied logistic regression analysis and determined that participants in the intervention group had a 3.2-fold higher probability of having a decrease in delayed doses compared with participants in the control group. Participants in the intervention group also showed a 2.2-fold higher probability of having a decrease in missed doses compared with participants in the control group. CONCLUSIONS: Use of SMS significantly affected the rates of taking medicine on schedule. Therefore, daily SMS could be useful for reminding patients to take their medicine on schedule