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The purpose of the investigation was to examine the influence of resistance training (RT) with equal volume and varying load on glycemic control, inflammation, and body composition in non-obese prediabetic older adults. Non-obese older adults with prediabetes were randomized into 2 groups, high-load (80% of 1RM) and low-load (40% of 1RM) RT (n = 12/group), both with the same training volume. Oral glucose tolerance test (OGTT) and blood samples were collected at baseline and again after 10 weeks of RT. Fasting blood glucose (103.8 vs. 99.9 mg/dL) and the area under the curve (AUC) of OGTT (0–30 min) decreased significantly in older adults with prediabetes after 10 weeks of volume-matched RT (p < 0.05). Serum levels of MCP-1 (138.7 vs. 98.5 pg/mL) and TNF-α (1.8 vs. 1.3 pg/mL) showed significant decrease after 10 weeks of high-load RT (p < 0.05). There were no changes in IL-10, IL-6, and CRP levels in both groups. Leptin showed significant decrease after 10 weeks of low-load RT (p < 0.05). Changes in fasting glucose and AUC of OGTT (0–120 min) were positively correlated with changes in MCP-1 and TNF-α (p < 0.05). Lean body mass (39.6 vs. 40.3 kg) increased significantly after 10 weeks of volume-matched RT (p < 0.05). Results indicate that equal-volume RT at different loads is beneficial to glycemic control and muscle growth, and high-load RT shows more prominent anti-inflammatory effects. Novelty: Short-term high-load resistance training can help older adults bring their blood sugar level back to normal. High-load resistance training attenuates aging-associated chronic inflammation.

Although the effect of continuous aerobic exercise on the appetite has been widely explored, the influence of resistance exercise (RE) with different variables, including training loads, training volume, and inter-set rest, on appetite responses requires further investigation. This study examined the importance of training load in RE-induced appetite regulation, with the total training volume and inter-set rest equalized. In total, 11 healthy young men (age = 23 ± 2 years, body mass index = 22 ± 2 kg/m

This study presents the design, implementation, and characterization of 1D resonant type micro-electro-mechanical-systems (MEMS) piezoelectric scanning mirrors with different actuator designs to investigate their influences on the figure of merits (FoMs) for automotive light detection and ranging application. The MEMS scanning mirrors are driven by lead zirconate titanate (PZT) thin film in this study owing to its outstanding piezoelectric properties. Three different beam-type piezoelectric actuators are designed, including the reference meander straight-beam actuator design, and the proposed meander curved-beam and straight-curved tapered beam actuator designs. Simulations show the scan angle enhancement for two proposed designs, yet the resonant scanning frequency of meander curved-beam design dropped to below the 2 kHz requirement. To evaluate the designs, scanning mirrors with two proposed actuators are fabricated and tested. Measurements show that the resonant frequencies for the two proposed MEMS scanning mirrors are 1735 Hz and 2578 Hz, respectively. Two proposed designs respectively have the maximum optical angles of 48.1° and 50.6° at the 20 Vpp driving voltage. Due to the much higher stress on the beam structure induced by the misalignment of PZT film, the actuator could not reach the predicted scanning angle of near 80°. In comparison of the two proposed designs, the straight-curved tapered beam actuator design could enhance the FoM for about 56%. In summary, the performances of piezoelectric MEMS scanning mirror can be improved by varying the designs of length and shape of actuator, and the distribution of PZT film on the suspended actuator is also a critical design concern.

The mechanism that underlies the dysregulation of glucose metabolism in older adults without obesity has yet to be thoroughly understood. This study investigated the risk of developing Type 2 diabetes (T2D) in older adults without obesity (BMI: 18.5 to25 kg/m

LEAP (Liquefaction Experiments and Analysis Projects) is an effort to formalize the process and provide data needed for validation of numerical models designed to predict liquefaction phenomena. For LEAP-GWU-2015, one project within LEAP, an experiment was repeated at 6 centrifuge facilities (Cambridge University, Kyoto University, University of California Davis, National Central University, Rensselaer Polytechnic Institute, and Zhejiang University) and the results were shared and archived for the purposes of validation of numerical models. This paper describes the specifications for the LEAP-GWU-2015 experiment and compares the experimental results from the six facilities. The specified experiment was for uniform medium dense sand with a 5 degree slope in a rigid container subject to a ramped, 1 Hz sine wave base motion. The experiment was meant to be relatively simple to enable different facilities to produce comparable experiments. Although it cannot be claimed that identical experiments were precisely replicated on different centrifuges, it is argued that the results are similar enough that each experiment lends veracity to the set of results. A benefit of variability between experiments is that the variety enables a more general validation. Important lessons with regard to specification of future experiments for validation of numerical models are summarized. LEAP-GWU-2015 has demonstrated an approach that is a useful reference for future validation studies.

Recently, a hybrid perovskite material, ABX3 (A= Cs, CH3NH3, NH2CHNH2; B= Pb, Sn; X= Cl, Br, I), has received much attention as an active layer in new-generation solar cells. This material is usually fabricated with either a one-step or a two step process in solution. However, the surface morphology, nucleation rate and grain growth rate of the CH3NH3PbI3 perovskite light absorber prepared by the solution reaction process (SRP) are hard to control. Here, we show a fast solid-solid reaction process (SSRP), to fabricate ultraflat (roughness of approximately 12 nm) CH3NH3PbI3 perovskite thin films with large grain sizes (~947 nm). The SSRP simply involves directly contacting a lead iodide thin film (PbI2) with methylammonium iodide powder (CH3NH3I) without any chemical reagents at 120°C under a normal atmospheric environment. The SSRP reaction dynamics is investigated by an in situ heating scanning electron microscope (SEM) system. This innovative SSRP is an easy approach for the large-scale fabrication of planar heterojunction perovskite solar cells and allows us to demonstrate a power conversion efficiency of approximately 15.27% (active area of 0.16 cm2).

Background: Functional and physiological adaptations induced by resistance training have been extensively studied in older adults. However, microRNA (miRNA) as the novel regulator in protective effects remains poorly understood. Objective: The purpose of an exploratory study was to analyze the response of a panel of circulating miRNAs to adaptations mediated by resistance training. Methods: Ten healthy older adults (age: 67.6 ± 2.2 years, 7 women and 3 men) without previous experience in resistance training were recruited. Blood samples were collected at baseline and after a 12-week resistance training. Next-generation sequencing was used to determine circulating miRNA responses to chronic resistance training. Results: After the 12-week training, physical functions including grip strength, lower body strength and endurance, and walking capacity were improved in the older adults, while the serum levels of leptin (from 18.1 ± 20.0 to 14.9 ± 17.6 ng/mL, p = 0.029) and tumor necrosis factor alpha (TNFα; from 4.4 ± 0.6 to 4.0 ± 0.6 pg/mL, p < 0.001) were significantly decreased. In addition, adipogenesis-related miRNAs (miR-103a-3p, -103b, -143-5p, -146b-3p, -146b-5p, -17-5p, -181a-2-3p, -181b-5p, -199a-5p, -204-3p, and -378c), anti-adipogenesis-related miRNAs (miR-155-3p, -448, and -363-3p), myogenesis-related miRNAs (miR-125b-1-3p, -128-3p, -133a-3p, 155-3p, -181a-2-3p, -181b-5p, -199a-5p, -223-3p, and -499a-5p), and inflammation-related miRNAs (miR-146b-3p, -146b-5p, -155-3p, -181a-2-3p, and -181b-5p) were changed significantly in the older adults after training (fold change >2, p < 0.05). The log2 fold change of miRNA-125-1-3p was inversely correlated with delta walking time (R = –0.685, p = 0.029) and change in insulin-like growth factor 1 (R = –0.644, p = 0.044). Conclusions: Our results can help explain the link between specific circulating miRNAs and beneficial effects of resistance training on functional and physiological adaptations in older adults.

In recent decades, the global incidence of dengue has increased. Affected countries have responded with more effective surveillance strategies to detect outbreaks early, monitor the trends, and implement prevention and control measures. We have applied newly developed machine learning approaches to identify laboratory-confirmed dengue cases from 4,894 emergency department patients with dengue-like illness (DLI) who received laboratory tests. Among them, 60.11% (2942 cases) were confirmed to have dengue. Using just four input variables [age, body temperature, white blood cells counts (WBCs) and platelets], not only the state-of-the-art deep neural network (DNN) prediction models but also the conventional decision tree (DT) and logistic regression (LR) models delivered performances with receiver operating characteristic (ROC) curves areas under curves (AUCs) of the ranging from 83.75% to 85.87% [for DT, DNN and LR: 84.60% ± 0.03%, 85.87% ± 0.54%, 83.75% ± 0.17%, respectively]. Subgroup analyses found all the models were very sensitive particularly in the pre-epidemic period. Pre-peak sensitivities (, Author summary Identifying dengue cases early is crucial but challenging for healthcare professionals. This challenge is increased during large epidemics and is a particular problem in non-endemic areas with limited experienced staff. To improve dengue diagnosis, we investigated how to exploit machine learning (ML)-based prediction models and identified four key variables [age, fever, white blood cell counts (WBCs), and platelet counts], which are compatible with clinical and epidemiological knowledge. With these variables, the ML prediction models [decision tree (DT), deep neural network (DNN)] and the logistic regression model developed for identifying laboratory-confirmed dengue cases produced areas under curve (AUCs) of the receiver operating characteristic (ROC) curves ranging from 83.75% to 85.87%. This implies that the prediction models may serve as a pivotal component of an integrated dengue surveillance system and they required only a single complete blood count (CBC) examination. The sensitivities, positive prediction values, and accuracies for major risk factors in the two machine learning models were close to those of the regression models. For future applications, the DNN models with superior performance can be employed at epidemic sites with adequate computer facilities, while the DT and regression models with interpretable prediction logic can be employed at sites with limited or no computer facilities. Artificial intelligence and clinical parameters identified from this study may aid when laboratories are overwhelmed, but should never replace laboratory confirmation.

In this paper, we propose a novel transformer-less direct current (dc) converter that features low switch voltage stress and automatic uniform current sharing. An interleaved four-phase voltage divider operating from a 400 V dc bus is used to achieve a high step-down conversion ratio with a moderate duty ratio. Based on the capacitive voltage division, the proposed converter achieves two major objectives, i.e., increased voltage conversion ratio, due to energy storage in the blocking capacitors, and reduced voltage stress of active switches and diodes. As a result, the proposed converter permits the use of lower voltage rating MOSFETs to reduce both switching and conduction losses, thereby improving the overall efficiency. In addition, due to the charge balance of the capacitors, the proposed converter enables automatic uniform current sharing of the interleaved phases without adding extra circuitry or complex control methods. The operation principles and performance analyses of the proposed converter are presented, and its effectiveness is verified by a 500 W output power prototype circuit that converts 400 V input voltage into 24 V output voltage.

Many amusement parks have been operated with information and communications technologies to provide friendly and efficient tourist services. However, these systems leave various levels of decisions to tourists to make by themselves, which may incur pressure on tourists. To address this issue, we have developed a SAP system with smart tour suggestion. However, this SAP system would not be exhaustive without an attraction reservation scheme. Therefore, this paper proposes an attraction reservation system as an extension to the SAP system. The proposed system comprises three subsystems: The mobile app subsystem is an interface for tourists to make reservations for attractions, and stores the booking tickets for later verification. The central subsystem performs necessary computing and database management. The ticket-scanning subsystem scans the tourist’s booking ticket for further verification. The demonstrations of the implemented prototyping system show that the proposed system does function.

In this paper, a novel transformer-less interleaved four-phase high step-down conversion ratio dc-dc converter with low switch voltage stress is proposed. In the proposed converter, the new capacitors switching circuits are combined with interleaved four-phase buck converter in order to get a high step-down conversion ratio without adopting an extreme short duty ratio. Based on the capacitive voltage division, the main objectives of the capacitors switching circuits in the converter are both storing energy in the blocking capacitors for increasing the voltage conversion ratio and reducing voltage stresses of active switches. This will allow one to choose lower voltage rating MOSFETs to reduce both switching and conduction losses, and the overall efficiency is consequently improved. In addition, due to the charge balance of the blocking capacitor, the converter features automatic uniform current sharing characteristic of the interleaved phases without adding extra circuitry or complex control methods. The operating principle and steady-state analyses of the voltage gain are discussed. Finally, a 400-V input voltage, 24-V output voltage, and 500W output power prototype circuit is implemented in the laboratory to verify the performance.