Phase-matched second-harmonic generation in bulk azodye-doped polymers by all-optical poling

We demonstrate phase-matched second-harmonic generation (SHG) in bulk azodye-doped polymethylmethacrylate using an all-optical poling technique. During the seeding process, samples were irradiated simultaneously by coherent superposition of the fundamental and the second-harmonic light of a nanosecond laser. The measurements for the dependence of SHG on the sample thickness show that the SHG signals increase with the increase in thickness of the samples, indicating that a χ(2)grating that satisfies the phase-matching condition for SHG could be optically induced in the polymer samples

Data-Driven Intelligent 3D Surface Measurement in Smart Manufacturing: Review and Outlook

High-fidelity characterization and effective monitoring of spatial and spatiotemporal processes are crucial for high-performance quality control of many manufacturing processes and systems in the era of smart manufacturing. Although the recent development in measurement technologies has made it possible to acquire high-resolution three-dimensional (3D) surface measurement data, it is generally expensive and time-consuming to use such technologies in real-world production settings. Data-driven approaches that stem from statistics and machine learning can potentially enable intelligent, cost-effective surface measurement and thus allow manufacturers to use high-resolution surface data for better decision-making without introducing substantial production cost induced by data acquisition. Among these methods, spatial and spatiotemporal interpolation techniques can draw inferences about unmeasured locations on a surface using the measurement of other locations, thus decreasing the measurement cost and time. However, interpolation methods are very sensitive to the availability of measurement data, and their performances largely depend on the measurement scheme or the sampling design, i.e., how to allocate measurement efforts. As such, sampling design is considered to be another important field that enables intelligent surface measurement. This paper reviews and summarizes the state-of-the-art research in interpolation and sampling design for surface measurement in varied manufacturing applications. Research gaps and future research directions are also identified and can serve as a fundamental guideline to industrial practitioners and researchers for future studies in these areas

Use thermophysical property to quantify state of HIFU treatment for VLS

The aim of this study is to evaluate the performance of ADT methods in grading the effectiveness of HIFU treatment for VLS. High-intensity focused ultrasound has been identified as a promising treatment modality for vulvar lichen sclerosus, a common inflammatory disorder associated with an increased risk of developing vulvar carcinoma. With small probe on extensive VLS parts, the therapy was sometimes uneven, thus the total doses of HIFU machine couldn’t indicate the curative effect at each part. The current therapeutic effect was based on symptoms and skin appearance after 3 months, which was time-consuming. Until now, there has been no immediate quantitative assessment method of HIFU therapeutic response for VLS. In our study, active dynamic IR thermal (ADT) was scheduled to undergo HIFU therapy before and after treatment. The thermal time constant was calculated based on ADT images measured both before and after HIFU treatment. In the result of pig phantom measurements, with each part approximately the same thermal time constant before HIFU treatment, the change of thermal time constant was strictly positively associated with HIFU dose onto each part. This study demonstrates the clinical potential of ADT in fast and effective quantify state of HIFU treatment for VLS

Data-Driven Intelligent 3D Surface Measurement in Smart Manufacturing: Review and Outlook

High-fidelity characterization and effective monitoring of spatial and spatiotemporal processes are crucial for high-performance quality control of many manufacturing processes and systems in the era of smart manufacturing. Although the recent development in measurement technologies has made it possible to acquire high-resolution three-dimensional (3D) surface measurement data, it is generally expensive and time-consuming to use such technologies in real-world production settings. Data-driven approaches that stem from statistics and machine learning can potentially enable intelligent, cost-effective surface measurement and thus allow manufacturers to use high-resolution surface data for better decision-making without introducing substantial production cost induced by data acquisition. Among these methods, spatial and spatiotemporal interpolation techniques can draw inferences about unmeasured locations on a surface using the measurement of other locations, thus decreasing the measurement cost and time. However, interpolation methods are very sensitive to the availability of measurement data, and their performances largely depend on the measurement scheme or the sampling design, i.e., how to allocate measurement efforts. As such, sampling design is considered to be another important field that enables intelligent surface measurement. This paper reviews and summarizes the state-of-the-art research in interpolation and sampling design for surface measurement in varied manufacturing applications. Research gaps and future research directions are also identified and can serve as a fundamental guideline to industrial practitioners and researchers for future studies in these areas

The Application of Theoretical Models in the Studies of Physical Activity Behaviors of the Elderly in China

By using the method of literature review, this paper introduces the popular theoretical models which have shown to better explain physical activity behaviors at a certain degree, summarizes the dominating theoretical models in the studies of physical activity behaviors of the elderly in China. In addition, shortcomings and future prospects are pointed out at the end

Enhancing Sustainability and Energy Efficiency in Smart Factories: A Review

With the rapid development of sensing, communication, computing technologies, and analytics techniques, today’s manufacturing is marching towards a new generation of sustainability, digitalization, and intelligence. Even though the significance of both sustainability and intelligence is well recognized by academia, industry, as well as governments, and substantial efforts are devoted to both areas, the intersection of the two has not been fully exploited. Conventionally, studies in sustainable manufacturing and smart manufacturing have different objectives and employ different tools. Nevertheless, in the design and implementation of smart factories, sustainability, and energy efficiency are supposed to be important goals. Moreover, big data based decision-making techniques that are developed and applied for smart manufacturing have great potential in promoting the sustainability of manufacturing. In this paper, the state-of-the-art of sustainable and smart manufacturing is first reviewed based on the PRISMA framework, with a focus on how they interact and benefit each other. Key problems in both fields are then identified and discussed. Specially, different technologies emerging in the 4th industrial revolution and their dedications on sustainability are discussed. In addition, the impacts of smart manufacturing technologies on sustainable energy industry are analyzed. Finally, opportunities and challenges in the intersection of the two are identified for future investigation. The scope examined in this paper will be interesting to researchers, engineers, business owners, and policymakers in the manufacturing community, and could serve as a fundamental guideline for future studies in these areas

Black TiOx Films with Photothermal-Assisted Photocatalytic Activity Prepared by Reactive Sputtering

Titanium oxide is widely applied as a photocatalyst. However, its low efficiency and narrow light absorption range are two main disadvantages that severely impede its practical application. In this work, black TiOx films with different chemical compositions were fabricated by tuning target voltage and controlling O2 flow during reactive DC magnetron sputtering. The optimized TiOx films with mixed phases (TiO, Ti2O3, Ti3O5, and TiO2) exhibited fantastic photothermal and photocatalytic activity by combining high light-absorptive Ti2O3 and Ti3O5 phases with the photocatalytic TiO2 phase. The sample prepared with oxygen flow at 5.6 ± 0.2 sccm and target voltage near 400 V exhibited excellent optical absorbance of 89.29% under visible light, which could improve surface temperature to 114 °C under sunlight. This film could degrade Rhodamine-B up to 74% after 150 min of UV irradiation. In a word, this work provides a guideline for fabricating black TiOx films with photothermal-assisted photocatalytic activity by reactive DC magnetron sputtering, which could avoid the usage of hydrogen and is convenient for quantity preparation