Prediction short-term photovoltaic power using improved chicken swarm optimizer - Extreme learning machine model

Photovoltaic power generation is greatly affected by weather conditions while the photovoltaic power has a certain negative impact on the power grid. The power sector takes certain measures to abandon photovoltaic power generation, thus limiting the development of clean energy power generation. This study is to propose an accurate short-term photovoltaic power prediction method. A new short-term photovoltaic power output prediction model is proposed Based on extreme learning machine and intelligent optimizer. Firstly, the input of the model is determined by correlation coefficient method. Then the chicken swarm optimizer is improved to strengthen the convergence. Secondly, the improved chicken swarm optimizer is used to optimize the weights and the extreme learning machine thresholds to improve the prediction effect. Finally, the improved chicken swarm optimizer extreme learning machine model is used to predict the photovoltaic power under different weather conditions. The testing results show that the average mean absolute percentage error and root mean square error of improved chicken swarm optimizer - extreme learning machine model are 5.54% and 3.08%. The proposed method is of great significance for the economic dispatch of power systems and the development of clean energy

Sources of springtime surface black carbon in the Arctic: an adjoint analysis for April 2008

We quantify source contributions to springtime (April 2008) surface black carbon (BC) in the Arctic by interpreting surface observations of BC at five receptor sites (Denali, Barrow, Alert, Zeppelin, and Summit) using a global chemical transport model (GEOS-Chem) and its adjoint. Contributions to BC at Barrow, Alert, and Zeppelin are dominated by Asian anthropogenic sources (40–43 %) before 18 April and by Siberian open biomass burning emissions (29–41 %) afterward. In contrast, Summit, a mostly free tropospheric site, has predominantly an Asian anthropogenic source contribution (24–68 %, with an average of 45 %). We compute the adjoint sensitivity of BC concentrations at the five sites during a pollution episode (20–25 April) to global emissions from 1 March to 25 April. The associated contributions are the combined results of these sensitivities and BC emissions. Local and regional anthropogenic sources in Alaska are the largest anthropogenic sources of BC at Denali (63 % of total anthropogenic contributions), and natural gas flaring emissions in the western extreme north of Russia (WENR) are the largest anthropogenic sources of BC at Zeppelin (26 %) and Alert (13 %). We find that long-range transport of emissions from Beijing–Tianjin–Hebei (also known as Jing–Jin–Ji), the biggest urbanized region in northern China, contribute significantly (∼ 10 %)to surface BC across the Arctic. On average, it takes ∼ 12 days for Asian anthropogenic emissions and Siberian biomass burning emissions to reach the Arctic lower troposphere, supporting earlier studies. Natural gas flaring emissions from the WENR reach Zeppelin in about a week. We find that episodic transport events dominate BC at Denali (87 %), a site outside the Arctic front, which is a strong transport barrier. The relative contribution of these events to surface BC within the polar dome is much smaller (∼ 50 % at Barrow and Zeppelin and ∼ 10 % at Alert). The large contributions from Asian anthropogenic sources are predominately in the form of chronic pollution (∼ 40 % at Barrow, 65 % at Alert, and 57 % at Zeppelin) on about a 1-month timescale. As such, it is likely that previous studies using 5- or 10-day trajectory analyses strongly underestimated the contribution from Asia to surface BC in the Arctic

Whole-body vibration training effect on physical performance and obesity in mice

The purpose of this study was to verify the beneficial effects of whole-body vibration (WBV) training on exercise performance, physical fatigue and obesity in mice with obesity induced by a high-fat diet (HFD). Male C57BL/6 mice were randomly divided into two groups: normal group (n=6), fed standard diet (control), and experimental group (n=18), fed a HFD. After 4-week induction, followed by 6-week WBV of 5 days per week, the 18 obese mice were divided into 3 groups (n=6 per group): HFD with sedentary control (HFD), HFD with WBV at relatively low-intensity (5.6 Hz, 0.13 g) (HFD+VL) or high-intensity (13 Hz, 0.68 g) (HFD+VH). A trend analysis revealed that WBV increased the grip strength in mice. WBV also dose-dependently decreased serum lactate, ammonia and CK levels and increased glucose level after the swimming test. WBV slightly decreased final body weight and dose-dependently decreased weights of epididymal, retroperitoneal and perirenal fat pads and fasting serum levels of alanine aminotransferase, CK, glucose, total cholesterol and triacylglycerol. Therefore, WBV could improve exercise performance and fatigue and prevent fat accumulation and obesity-associated biochemical alterations in obese mice. It may be an effective intervention for health promotion and prevention of HFD-induced obesity

Predicting customer lifetime value for hypermarket private label products

This study develops a model to predict customer lifetime value for hypermarket private label products. It examines the relationships among store awareness, store image variables (i.e., service quality, price/value, convenience, and product quality), private label image, repurchase intention, and customer lifetime value and investigates the moderating role of image fit. The originality of this study lies in filling the gap of previous research on antecedents of private label customers’ behavior by considering store awareness, image fit, and customer lifetime value. Partial least squares structural equation modeling was used to analyze data. The results indicate the following. Store image variables (except product quality) and store awareness affect repurchase intention directly or indirectly through private label image. Image fit moderates the relationships between store image variables (except product quality) and private label image. Private label image facilitates customer lifetime value. This study provides several theoretical and practical implications for hypermarket private label product developments

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

Extremity Exercise Program in Breast Cancer Survivors Suffering from Chemotherapy-Induced Peripheral Neuropathy: A Feasibility Pilot Study

Objectives: To evaluate the feasibility of implementation of an extremity exercise program and to examine its preliminary effects in breast cancer survivors suffering from chemotherapy-induced peripheral neuropathy (CIPN). Sample & Setting: Thirteen breast cancer survivors from one hospital in northern Taiwan. Methods and Variables: A single group with repeated measures, and a quasi-experimental design. The intervention program was a four week, home-based extremity exercise program that was comprised of 10 skilled hand exercises and Buerger-Allen exercises. The Total Neuropathy Scale (clinical version), Functional Assessment of Cancer Therapy/Gynecologic Oncology Group, Neurotoxicity (13-Item Version), Identification Pain Questionnaire, and pain Visual Analogue Scale were used to measure CIPN before exercise (T1), during (T2~T4), and after exercise (T5). Qualitative data were also collected at each time point. Data were analyzed by using descriptive statistics, generalized estimating equations, and directed content analysis. Results: None of the participants reported adverse events during the study period. The extremity exercise program significantly improved patient-reported CIPN after intervention at T4 or T5 but was insignificant on clinician-assessed CIPN. The qualitative data of participant experience indicated that this program is feasible and easy to follow. Conclusion: The extremity exercise program is feasible but needs to increase the sample size and prolong the intervention period for confirmation

Benchmarking of eight recurrent neural network variants for breath phase and adventitious sound detection on a self-developed open-access lung sound database-HF_Lung_V1

A reliable, remote, and continuous real-time respiratory sound monitor with automated respiratory sound analysis ability is urgently required in many clinical scenarios-such as in monitoring disease progression of coronavirus disease 2019-to replace conventional auscultation with a handheld stethoscope. However, a robust computerized respiratory sound analysis algorithm has not yet been validated in practical applications. In this study, we developed a lung sound database (HF_Lung_V1) comprising 9,765 audio files of lung sounds (duration of 15 s each), 34,095 inhalation labels, 18,349 exhalation labels, 13,883 continuous adventitious sound (CAS) labels (comprising 8,457 wheeze labels, 686 stridor labels, and 4,740 rhonchi labels), and 15,606 discontinuous adventitious sound labels (all crackles). We conducted benchmark tests for long short-term memory (LSTM), gated recurrent unit (GRU), bidirectional LSTM (BiLSTM), bidirectional GRU (BiGRU), convolutional neural network (CNN)-LSTM, CNN-GRU, CNN-BiLSTM, and CNN-BiGRU models for breath phase detection and adventitious sound detection. We also conducted a performance comparison between the LSTM-based and GRU-based models, between unidirectional and bidirectional models, and between models with and without a CNN. The results revealed that these models exhibited adequate performance in lung sound analysis. The GRU-based models outperformed, in terms of F1 scores and areas under the receiver operating characteristic curves, the LSTM-based models in most of the defined tasks. Furthermore, all bidirectional models outperformed their unidirectional counterparts. Finally, the addition of a CNN improved the accuracy of lung sound analysis, especially in the CAS detection tasks.Comment: 48 pages, 8 figures. To be submitte

Acupuncture Effects on Cardiac Functions Measured by Cardiac Magnetic Resonance Imaging in a Feline Model

The usefulness of acupuncture (AP) as a complementary and/or alternative therapy in animals is well established but more research is needed on its clinical efficacy relative to conventional therapy, and on the underlying mechanisms of the effects of AP. Cardiac magnetic resonance imaging (CMRI), an important tool in monitoring cardiovascular diseases, provides a reliable method to monitor the effects of AP on the cardiovascular system. This controlled experiment monitored the effect electro-acupuncture (EA) at bilateral acupoint Neiguan (PC6) on recovery time after ketamine/xylazine cocktail anesthesia in healthy cats. The CMRI data established the basic feline cardiac function index (CFI), including cardiac output and major vessel velocity. To evaluate the effect of EA on the functions of the autonomic nervous and cardiovascular systems, heart rate, respiration rate, electrocardiogram and pulse rate were also measured. Ketamine/xylazine cocktail anesthesia caused a transient hypertension in the cats; EA inhibited this anesthetic-induced hypertension and shortened the post-anesthesia recovery time. Our data support existing knowledge on the cardiovascular benefits of EA at PC6, and also provide strong evidence for the combination of anesthesia and EA to shorten post-anesthesia recovery time and counter the negative effects of anesthetics on cardiac physiology