Multi-Effects Coupled Nanogenerators for Simultaneously Harvesting Solar, Thermal, and Mechanical Energies

As a result of the widespread use of small-scale and low-power electronic devices, the demand for micro-energy sources has increased, in particular the potential to harvest the wide variety of energy sources present in their surrounding environment. In this paper, a novel coupled nanogenerator that can realize energy harvesting for multiple energy sources is reported. Based on the unique electrical properties of ferroelectric Bi 0.5Na 0.5TiO 3 (BNT) materials, it is possible to combine a photovoltaic cell, pyroelectric nanogenerator, and triboelectric-piezoelectric nanogenerator in a single element to harvest light, heat, and mechanical energy simultaneously. To evaluate the effectiveness of coupling for different materials, a Yang coupling factor (k C,Q) is defined in terms of transferred charge, where BNT has the largest k C,Q of 1.29 during heating, indicating that BNT has the best coupling enhancement compared to common ferroelectric materials. This new criterion and novel device structure therefore provide a new basis for the future development of coupled nanogenerators which are capable of harvesting multiple sources of energy.</p

Delays in hospital admissions in patients with fractures across 18 low-income and middle-income countries (INORMUS): a prospective observational study

© 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Background: The Lancet Commission on Global Surgery established the Three Delays framework, categorising delays in accessing timely surgical care into delays in seeking care (First Delay), reaching care (Second Delay), and receiving care (Third Delay). Globally, knowledge gaps regarding delays for fracture care, and the lack of large prospective studies informed the rationale for our international observational study. We investigated delays in hospital admission as a surrogate for accessing timely fracture care and explored factors associated with delayed hospital admission. Methods: In this prospective observational substudy of the ongoing International Orthopaedic Multicenter Study in Fracture Care (INORMUS), we enrolled patients with fracture across 49 hospitals in 18 low-income and middle-income countries, categorised into the regions of China, Africa, India, south and east Asia, and Latin America. Eligible patients were aged 18 years or older and had been admitted to a hospital within 3 months of sustaining an orthopaedic trauma. We collected demographic injury data and time to hospital admission. Our primary outcome was the number of patients with open and closed fractures who were delayed in their admission to a treating hospital. Delays for patients with open fractures were defined as being more than 2 h from the time of injury (in accordance with the Lancet Commission on Global Surgery) and for those with closed fractures as being a delay of more than 24 h. Secondary outcomes were reasons for delay for all patients with either open or closed fractures who were delayed for more than 24 h. We did logistic regression analyses to identify risk factors of delays of more than 2 h in patients with open fractures and delays of more than 24 h in patients with closed fractures. Logistic regressions were adjusted for region, age, employment, urban living, health insurance, interfacility referral, method of transportation, number of fractures, mechanism of injury, and fracture location. We further calculated adjusted relative risk (RR) from adjusted odds ratios, adjusted for the same variables. This study was registered with ClinicalTrials.gov, NCT02150980, and is ongoing. Findings: Between April 3, 2014, and May 10, 2019, we enrolled 31 255 patients with fractures, with a median age of 45 years (IQR 31–62), of whom 19 937 (63·8%) were men, and 14 524 (46·5%) had lower limb fractures, making them the most common fractures. Of 5256 patients with open fractures, 3778 (71·9%) were not admitted to hospital within 2 h. Of 25 999 patients with closed fractures, 7141 (27·5%) were delayed by more than 24 h. Of all regions, Latin America had the greatest proportions of patients with delays (173 [88·7%] of 195 patients with open fractures; 426 [44·7%] of 952 with closed fractures). Among patients delayed by more than 24 h, the most common reason for delays were interfacility referrals (3755 [47·7%] of 7875) and Third Delays (cumulatively interfacility referral and delay in emergency department: 3974 [50·5%]), while Second Delays (delays in reaching care) were the least common (423 [5·4%]). Compared with other methods of transportation (eg, walking, rickshaw), ambulances led to delay in transporting patients with open fractures to a treating hospital (adjusted RR 0·66, 99% CI 0·46–0·93). Compared with patients with closed lower limb fractures, patients with closed spine (adjusted RR 2·47, 99% CI 2·17–2·81) and pelvic (1·35, 1·10–1·66) fractures were most likely to have delays of more than 24 h before admission to hospital. Interpretation: In low-income and middle-income countries, timely hospital admission remains largely inaccessible, especially among patients with open fractures. Reducing hospital-based delays in receiving care, and, in particular, improving interfacility referral systems are the most substantial tools for reducing delays in admissions to hospital. Funding: National Health and Medical Research Council of Australia, Canadian Institutes of Health Research, McMaster Surgical Associates, and Hamilton Health Sciences

Applying systems thinking to identify enablers and challenges to scale-up interventions for hypertension and diabetes in low-income and middle-income countries: protocol for a longitudinal mixed-methods study.

INTRODUCTION: There is an urgent need to reduce the burden of non-communicable diseases (NCDs), particularly in low-and middle-income countries, where the greatest burden lies. Yet, there is little research concerning the specific issues involved in scaling up NCD interventions targeting low-resource settings. We propose to examine this gap in up to 27 collaborative projects, which were funded by the Global Alliance for Chronic Diseases (GACD) 2019 Scale Up Call, reflecting a total funding investment of approximately US$50 million. These projects represent diverse countries, contexts and adopt varied approaches and study designs to scale-up complex, evidence-based interventions to improve hypertension and diabetes outcomes. A systematic inquiry of these projects will provide necessary scientific insights into the enablers and challenges in the scale up of complex NCD interventions. METHODS AND ANALYSIS: We will apply systems thinking (a holistic approach to analyse the inter-relationship between constituent parts of scaleup interventions and the context in which the interventions are implemented) and adopt a longitudinal mixed-methods study design to explore the planning and early implementation phases of scale up projects. Data will be gathered at three time periods, namely, at planning (TP), initiation of implementation (T0) and 1-year postinitiation (T1). We will extract project-related data from secondary documents at TP and conduct multistakeholder qualitative interviews to gather data at T0 and T1. We will undertake descriptive statistical analysis of TP data and analyse T0 and T1 data using inductive thematic coding. The data extraction tool and interview guides were developed based on a literature review of scale-up frameworks. ETHICS AND DISSEMINATION: The current protocol was approved by the Monash University Human Research Ethics Committee (HREC number 23482). Informed consent will be obtained from all participants. The study findings will be disseminated through peer-reviewed publications and more broadly through the GACD network

DEM analysis of passive failure in structured sand ground behind a retaining wall

Assessment of active and passive earth pressures is of crucial importance in design of retaining structures. This paper aims to explore the progressive failure mechanism towards the passive state of natural sand ground, and to quantify the lateral earth pressure, resultant force and overturning moment on the retaining wall under both translational and rotational movement modes. A numerical modelling using the two-dimensional (2D) Discrete Element Method (DEM) is conducted with an advanced micro contact model considering the inter-particle bond strength of natural sand. Rankine theory based semi-analytical solutions of the lateral earth pressure and resultant force/moment have been proposed and compared with the numerical data. The results show that not only the wall movement mode but also the inter-particle bond strength has significant effects on the progressive formation of shear failure zone and mobilization characteristics of earth pressure. The larger the inter-particle bond strength is, the higher the lateral earth pressure can be mobilized, and hence more significant post-peak softening can be produced. The proposed solution can well describe the progressive mobilization of earth pressure towards the passive state and the post-peak softening state at rotational movement modes, potentially optimizing the design of retaining structures

Characteristics of Flow Movement in Complex Canal System and Its Influence on Sudden Pollution Accidents

This study aimed to determine the split ratio, flow-field structure, and effect of different shaped channels to sudden pollution accidents in a generalized complex canal system of a wetland park, both experimentally and numerically. The three-dimensional instantaneous velocities at a typical section of each channel in the generalized model were measured experimentally using an acoustic Doppler velocimeter. The results showed that the split ratio calculation formula of three parallel channels could be derived under the condition of considering the frictional head and the local head losses. The water depth, velocities, and pollutant diffusion were widely influenced by changes in the cross-sectional shape and channel plane shape. The pollutants were trapped by stable vortices and transverse circulation due to shear force and secondary flow, thus delaying the diffusion of pollutants. The research results reported herein can help provide technical support for the normal operation of complex canal systems

Research on Short-Time Wind Speed Prediction in Mountainous Areas Based on Improved ARIMA Model

In rugged mountain areas, the lateral aerodynamic force and aerodynamic lift caused by strong winds are the main reasons for the lateral overturning of trains and the destruction of buildings and structures along the railroad line. Therefore, it is important to build a strong wind alarm system along the railroad line, and a reasonable and accurate short-time forecast of a strong wind is the basis of it. In this research, two methods of constructive function and time-series decomposition are proposed to pre-process the input wind speed for periodic strong winds in mountainous areas. Then, the improved Auto-Regressive Integrated Moving Average model time-series model was established through the steps of a white noise test, data stationarity test, model recognition, and order determination. Finally, the effectiveness of the improved wind speed prediction was examined. The results of the research showed that rational choice of processing functions has a large impact on wind speed prediction results. The prediction accuracy of the improved ARIMA model proposed in this paper is better than the results of the traditional Seasonal Auto-Regressive Integrated Moving Average model, and it can quickly and accurately realize the short-time wind speed prediction along the railroad line in rugged mountains. In addition, the improved ARIMA model has verified its universality in different mountainous places

Analysis of influenza surveillance results in Jingzhou， Hubei Province from 2016 to 2021

ObjectiveTo understand the epidemiological characteristics of influenza in Jingzhou from 2016 to 2021， so as to provide scientific evidence for the formulation of influenza prevention and control policies in this region， and effectively protect people's health.MethodsData of influenza-like illness （ILI） and pathogen surveillance in Jingzhou during 2016‒2021 were collected and statistically analyzed.ResultsA total of 46 272 ILI cases were reported from two hospitals in Jingzhou City from 2016 to 2021. The difference in the constituent ratio of ILI was statistically significant among different age groups （P<0.05）. A total of 12 812 specimens were collected from two hospitals for influenza surveillance. A total of 1 513 cases were RNA positive，and the positive rate of influenza virus nucleic acid detection was 11.81％. The RNA positive specimens were mainly B （Victoria）， accounting for 39.33％. There were statistically significant differences in the positive rate of influenza virus nucleic acids and different types of influenza virus nucleic acids among different years （P<0.05）.ConclusionThe influenza epidemic in Jingzhou peaks in winter and spring， and the new A （H1），A （H3）， B （Victoria） and B （Yamagata） types alternate and mixed epidemics dominate

Research on Short-Time Wind Speed Prediction in Mountainous Areas Based on Improved ARIMA Model

In rugged mountain areas, the lateral aerodynamic force and aerodynamic lift caused by strong winds are the main reasons for the lateral overturning of trains and the destruction of buildings and structures along the railroad line. Therefore, it is important to build a strong wind alarm system along the railroad line, and a reasonable and accurate short-time forecast of a strong wind is the basis of it. In this research, two methods of constructive function and time-series decomposition are proposed to pre-process the input wind speed for periodic strong winds in mountainous areas. Then, the improved Auto-Regressive Integrated Moving Average model time-series model was established through the steps of a white noise test, data stationarity test, model recognition, and order determination. Finally, the effectiveness of the improved wind speed prediction was examined. The results of the research showed that rational choice of processing functions has a large impact on wind speed prediction results. The prediction accuracy of the improved ARIMA model proposed in this paper is better than the results of the traditional Seasonal Auto-Regressive Integrated Moving Average model, and it can quickly and accurately realize the short-time wind speed prediction along the railroad line in rugged mountains. In addition, the improved ARIMA model has verified its universality in different mountainous places