bluuebunny/crossref_metadata_2025 huggingface dataset:
Faktor-Faktor Yang Berhubungan Dengan Pemanfaatan Layanan Rawat Jalan
Authors: Valentina Risnawati , Pujianto
Published: May 2020

Perkembangan jaminan kesehatan mulai berkembang dengan adanya Jaminan Kesehatan Nasional (JKN) sejak tahun 2014 yang dilaksanakan oleh Badan Penyelenggaraan Jaminan Sosial (BPJS) Kesehatan. Pemanfaatan layanan rawat jalan juga mengalami peningkatan baik rawat jalan maupun rawat inap. Oleh sebab itu, tujuan penelitian ini adalah melihat distribusi perilaku perokok, pelayanan rawat jalan, dan faktor- faktor yang berhubungan dengan pemanfaatan layanan rawat jalan di Indonesia. Penelitian ini menggunakan data Indonesia Family Life Survey 5 (IFLS 5) tahun 2014-2015 dengan desain penelitian cross-sectional dan pendekatan kuantitatif di mana pengukuran variabel independen dan variabel dependen yang dilakukan pada Maret 2019. Teori pemanfaatan layanan kesehatan oleh Andersen mencakup predisposing (umur dan jenis kelamin), enabling (ke pemilikan jaminan kesehatan), dan need (status perokok dan penyakit yang berhubungan dengan perilaku merokok). Hasil yang diperoleh  adalah distribusi frekuensi pemanfaatan layanan rawat jalan selama empat minggu sebesar 1.600 (13,4%), distribusi frekuensi perilaku merokok sebesar 10.396 (86,9%), dan variabel umur, jenis kelamin, ke pemilikan jaminan kesehatan, status perokok dan penyakit yang berhubungan dengan perilaku merokok berhubungan signifikan dengan pemanfaatan layanan rawat jalan dengan p value = 0,00. Pemanfaatan layanan rawat jalan dipengaruhi oleh faktor dalam dan luar diri
Perbandingan Efektifitas Teknik Relaksasi Dan Genggaman Jari Terhadap Penurunan Nyeri Pada Pasien Post Operasi Sectio Caesare Di Rumah Sakit Undata Provinsi Sulawesi Tengah
Authors: Misnawati
Published: May 2020

Teknik relaksasi dan genggaman jari merupakan suatu bentuk terapi relaksasi untuk menyeimbangkan energi tubuh yang dapat membantu pasien dalam menggontrol diri ketika timbulnya perasaan kurang menyenangkan yang dapat menimbulkan  nyeri, stres fisik serta emosi. Penelitian dalam hal ini bertujuan  mengidentifikasi perbandingan efektifitas teknik relaksasi dan genggaman jari terhadap penurunan nyeri pada pasien post operasi sectio caesarea di ruangan Matahari Rumah Sakit Umum Daerah Undata Provinsi Sulawesi Tengah. Dalam Penelitian ini digunakan desain quasy exsperiment (pre and post test without control) dengan metode kuantitatif. Penelitian ini dilakukan tanggal  25 Juli  sampai dengan 27 Agustus  2018. Semua pasien post operasi sectio caesarea merupakan Populasi dalam penelitian ini selama penelitian berlangsung. Jumlah sampel dihitung dengan menggunakan rumus rerata uji hipotesis two tail dengan nilai σ2=5,36, μo=5,07, μa=1,80, α=1,96 dan β= 0,84 sehingga jumlah sampel adalah 8 responden dipilih dengan teknik quota sampling. Data dihitung dengan menggunakan uji Wilcoxon dengan didapatkan nilai p=0,011(α≤=0,05) pada tingkat kemaknaan  α=0,05 atau 95%). Pada hasil penelitian pretest didapatkan lebih banyak responden mengatakan nyeri berat terkontrol dan posttest didapatkan lebih sedikit responden mengatakan nyeri ringan. Kesimpulan dari penelitian ini yaitu terdapat perbandingan efektifitas teknik relaksasi dan genggaman jari terhadap penurunan nyeri pada pasien post operasi sectio caesarea di ruangan Matahari Rumah Sakit Umum Daerah Undata Provinsi Sulawesi Tengah. Oleh karena itu, peneliti menyarankan agar perawat dapat menerapkan teknik relaksasi dan genggam jari selama 20 menit sebagai salah satu manajemen nyeri.
PUB-SalNet: A Pre-Trained Unsupervised Self-Aware Backpropagation Network for Biomedical Salient Segmentation
Authors: Chen Feiyang , Jiang Ying , Zeng Xiangrui , Zhang Jing , Gao Xin , Xu Min
Published: May 2020

Salient segmentation is a critical step in biomedical image analysis, aiming to cut out regions that are most interesting to humans. Recently, supervised methods have achieved promising results in biomedical areas, but they depend on annotated training data sets, which requires labor and proficiency in related background knowledge. In contrast, unsupervised learning makes data-driven decisions by obtaining insights directly from the data themselves. In this paper, we propose a completely unsupervised self-aware network based on pre-training and attentional backpropagation for biomedical salient segmentation, named as PUB-SalNet. Firstly, we aggregate a new biomedical data set from several simulated Cellular Electron Cryo-Tomography (CECT) data sets featuring rich salient objects, different SNR settings, and various resolutions, which is called SalSeg-CECT. Based on the SalSeg-CECT data set, we then pre-train a model specially designed for biomedical tasks as a backbone module to initialize network parameters. Next, we present a U-SalNet network to learn to selectively attend to salient objects. It includes two types of attention modules to facilitate learning saliency through global contrast and local similarity. Lastly, we jointly refine the salient regions together with feature representations from U-SalNet, with the parameters updated by self-aware attentional backpropagation. We apply PUB-SalNet for analysis of 2D simulated and real images and achieve state-of-the-art performance on simulated biomedical data sets. Furthermore, our proposed PUB-SalNet can be easily extended to 3D images. The experimental results on the 2d and 3d data sets also demonstrate the generalization ability and robustness of our method.
Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon Regulation
Authors: Turki Sadok , Sahraoui Soulayma , Sauvey Christophe , Sauer Nathalie
Published: May 2020

Due to environmental concerns, firms are under increasing pressure to comply with legislations and to take up environmental strategies. This leads researchers and firms to develop new sustainable supply chains, where a new area has emerged for a manufacturing and reconditioning system. The originality of this work consists in simultaneously considering carbon emissions strategies, carbon tax and mandatory emission in a manufacturing-reconditioning system. The proposed system is composed of two parallel machines, a manufacturing stock, a reconditioning stock and a recovery inventory. In order to make the proposed green manufacturing system more realistic, it is assumed that manufactured (new products) and reconditioned products are distinguishable. The quantity of worn products (used products) depends on the sales in the previous periods, and the repair periods of the machines are stochastic and independent. The aim of this work is to determine the optimal capacities of manufacturing and reconditioning stocks that maximize the total profit, as well as the optimal value of worn products under two carbon emissions’ limitations. An evolutionary algorithm is developed, along with an efficient improvement method, to find the optimal value of decision variables. Ultimately, numerical results are provided to show the impact of the period of carbon limit and the worn products (returned products) on decision variables.
Pt/Re/CeO2 Based Catalysts for CO-Water–Gas Shift Reaction: from Powders to Structured Catalyst
Authors: Palma Vincenzo , Gallucci Fausto , Pullumbi Pluton , Ruocco Concetta , Meloni Eugenio , Martino Marco
Published: May 2020

This work focuses on the development of a Pt/Re/CeO2-based structured catalyst for a single stage water–gas shift process. In the first part of the work, the activity in water–gas shift reactions was evaluated for three Pt/Re/CeO2-based powder catalysts, with Pt/Re ratio equal to 1/1, 1/2 ad 2/1 and total loading ≈ 1 wt%. The catalysts were prepared by sequential dry impregnation of commercial ceria, with the salts precursors of rhenium and platinum; the activity tests were carried out by feeding a reacting mixture with a variable CO/H2O ratio, equal to 7/14, 7/20 and 7/24, and the kinetic parameters were determined. The model which better described the experimental results involves the water–gas shift (WGS) reaction and CO as well as CO2 methanation. The preliminary tests showed that the catalyst with the Pt/Re ratio equal to 2/1 had the best performance, and this was selected for further investigations. In the second part of the work, a structured catalyst, obtained by coating a commercial aluminum alloy foam with the chosen catalytic formulation, was prepared and tested in different reaction conditions. The results demonstrated that a single stage water–gas shift process is achievable, obtaining a hydrogen production rate of 18.7 mmol/min at 685 K, at τ = 53 ms, by feeding a simulated reformate gas mixture (37.61 vol% H2, 9.31 vol% CO2, 9.31 vol% CO, 42.19 vol% H2O, 1.37 vol% CH4).
NiO, Fe2O3, and MoO3 Supported over SiO2 Nanocatalysts for Asphaltene Adsorption and Catalytic Decomposition: Optimization through a Simplex–Centroid Mixture Design of Experiments
Authors: Arias-Madrid Daniela , Medina Oscar E. , Gallego Jaime , Acevedo Sócrates , Correa-Espinal Alexander A. , Cortés Farid B. , Franco Camilo A.
Published: May 2020

The main objective of this study was to evaluate the effect of functionalized silica nanoparticles with Fe2O3, NiO, and MoO3 metal oxides on the decomposition of asphaltenes, through an experimental simplex–centroid mixture design for surface area, asphaltene adsorption, and activation energy. The experimental nanoparticle surface area was measured by adsorption of N2. Adsorption isotherms, and the subsequent oxidation process of asphaltenes, were performed through batch adsorption experiments and thermogravimetric analysis, respectively. Among the monometallic systems, the presence of iron increased the affinity between the nanoparticle and the asphaltenes, and a higher metal oxide load increased the adsorptive capacity of the system. For the pairings evaluated, there was better synergy between iron and nickel, with the participation of the former being slightly superior. In the mixture design that included three transition elements, the participation of molybdenum was not significant, and the adsorption of asphaltenes was dominated by the active sites formed by the other two transition element oxides. The mixture design created to minimize the activation energy showed that the interaction of the three transition elements is important and can be evidenced in the interaction coefficients.
Dynamical Complexity of the 2015 St. Patrick’s Day Magnetic Storm at Swarm Altitudes Using Entropy Measures
Authors: Papadimitriou Constantinos , Balasis Georgios , Boutsi Adamantia Zoe , Daglis Ioannis A. , Giannakis Omiros , Anastasiadis Anastasios , Michelis Paola De , Consolini Giuseppe
Published: May 2020

The continuously expanding toolbox of nonlinear time series analysis techniques has recently highlighted the importance of dynamical complexity to understand the behavior of the complex solar wind–magnetosphere–ionosphere–thermosphere coupling system and its components. Here, we apply new such approaches, mainly a series of entropy methods to the time series of the Earth’s magnetic field measured by the Swarm constellation. We show successful applications of methods, originated from information theory, to quantitatively study complexity in the dynamical response of the topside ionosphere, at Swarm altitudes, focusing on the most intense magnetic storm of solar cycle 24, that is, the St. Patrick’s Day storm, which occurred in March 2015. These entropy measures are utilized for the first time to analyze data from a low-Earth orbit (LEO) satellite mission flying in the topside ionosphere. These approaches may hold great potential for improved space weather nowcasts and forecasts.
Detecting Malware with Information Complexity
Authors: Alshahwan Nadia , Barr Earl T. , Clark David , Danezis George , Menéndez Héctor D.
Published: May 2020

Malware concealment is the predominant strategy for malware propagation. Black hats create variants of malware based on polymorphism and metamorphism. Malware variants, by definition, share some information. Although the concealment strategy alters this information, there are still patterns on the software. Given a zoo of labelled malware and benign-ware, we ask whether a suspect program is more similar to our malware or to our benign-ware. Normalized Compression Distance (NCD) is a generic metric that measures the shared information content of two strings. This measure opens a new front in the malware arms race, one where the countermeasures promise to be more costly for malware writers, who must now obfuscate patterns as strings qua strings, without reference to execution, in their variants. Our approach classifies disk-resident malware with 97.4% accuracy and a false positive rate of 3%. We demonstrate that its accuracy can be improved by combining NCD with the compressibility rates of executables using decision forests, paving the way for future improvements. We demonstrate that malware reported within a narrow time frame of a few days is more homogeneous than malware reported over two years, but that our method still classifies the latter with 95.2% accuracy and a 5% false positive rate. Due to its use of compression, the time and computation cost of our method is nontrivial. We show that simple approximation techniques can improve its running time by up to 63%. We compare our results to the results of applying the 59 anti-malware programs used on the VirusTotal website to our malware. Our approach outperforms each one used alone and matches that of all of them used collectively.
New Evidence of the Marginal Predictive Content of Small and Large Jumps in the Cross-Section
Authors: Yu Bo , Mizrach Bruce , Swanson Norman R.
Published: May 2020

We investigate the marginal predictive content of small versus large jump variation, when forecasting one-week-ahead cross-sectional equity returns, building on Bollerslev et al. (2020). We find that sorting on signed small jump variation leads to greater value-weighted return differentials between stocks in our highest- and lowest-quintile portfolios (i.e., high–low spreads) than when either signed total jump or signed large jump variation is sorted on. It is shown that the benefit of signed small jump variation investing is driven by stock selection within an industry, rather than industry bets. Investors prefer stocks with a high probability of having positive jumps, but they also tend to overweight safer industries. Also, consistent with the findings in Scaillet et al. (2018), upside (downside) jump variation negatively (positively) predicts future returns. However, signed (large/small/total) jump variation has stronger predictive power than both upside and downside jump variation. One reason large and small (signed) jump variation have differing marginal predictive contents is that the predictive content of signed large jump variation is negligible when controlling for either signed total jump variation or realized skewness. By contrast, signed small jump variation has unique information for predicting future returns, even when controlling for these variables. By analyzing earnings announcement surprises, we find that large jumps are closely associated with “big” news. However, while such news-related information is embedded in large jump variation, the information is generally short-lived, and dissipates too quickly to provide marginal predictive content for subsequent weekly returns. Finally, we find that small jumps are more likely to be diversified away than large jumps and tend to be more closely associated with idiosyncratic risks. This indicates that small jumps are more likely to be driven by liquidity conditions and trading activity.
Greenhouse Gas Reduction Effect of Solar Energy Systems Applicable to High-rise Apartment Housing Structures in South Korea
Authors: Park Chang-Hyun , Ko Yu-Jin , Kim Jong-Hyun , Hong Hiki
Published: May 2020

In South Korea, we are aiming for net zero energy use apartment home structures. Since the apartment structure in South Korea is generally a high-rise of 10 or more floors, the types of renewable energy applicable are limited to photovoltaic (PV) panels, solar collectors installed on the wall, or a photovoltaic thermal (PVT) hybrid panel combining both. In this study, the effect of PV, ST (Solar Thermal), and PVT systems on greenhouse gas reduction was analyzed using TRNSYS18. All three systems showed maximum CO2 reductions at 35° facing south. PV, ST, and PVT showed CO2 reductions of 67.4, 114.6, and 144.7 kg_CO2/m2·year, respectively. Compared to those values, when installed on a wall (slope of 90°), CO2 reduction is about 35–40% less and about 20% less at a slope of 75°. ST and PVT installed on the vertical wall have a greater greenhouse gas reduction effect than the PV installed at the optimal slope of 35°. Since the CO2 reduction difference among SW, SE, and azimuthal S is within 10%, ST and PVT are recommended for installation on high-rise apartment structure walls or balconies with the azimuthal angle of ± 45° with respect to south.
A Publicly Available Simulation of Battery Electric, Hybrid Electric, and Gas-Powered Vehicles
Authors: Fulton Lawrence
Published: May 2020

Volatility in energy markets has made the purchase of battery electric vehicles (BEV) or hybrid vehicles (HEVs) attractive versus internal combustion engine vehicles (ICEVs). However, the total cost of ownership (TCO) and true environmental effects, are difficult to assess. This study provides a publicly available, user-driven simulation that estimates the consumer and environmental costs for various vehicle purchase options, supporting policymaker, producer, and consumer information requirements. It appears to be the first to provide a publicly available, user interactive simulation that compares two purchase options simultaneously. It is likely that the first paper to simulate the effects of solar recharging of electric vehicles (EV) on both cost-benefit for the consumer and environmental benefit (e.g., carbon dioxide, oxides of nitrogen, non-methane organic gasses, particulate matter, and formaldehyde) simultaneously, demonstrating how, as an example, solar-based charging of BEVs and HEVs reduces carbon emissions over grid-based charging. Two specific scenarios are explicated, and the results of show early break-even for both BEV and Plug-in HEV (PHEV) options over ICEV (13 months, and 12 months, respectively) with CO2 emissions about ½ that of the gasoline option (including production emissions.) The results of these simulations are congruent with previous research that identified quick break-even for HEVs versus ICEV.
Machine Learning Modeling of Horizontal Photovoltaics Using Weather and Location Data
Authors: Pasion Christil , Wagner Torrey , Koschnick Clay , Schuldt Steven , Williams Jada , Hallinan Kevin
Published: May 2020

Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal solar panels using 14 months of data collected from 12 northern-hemisphere locations. We performed our data collection and analysis in the absence of irradiation data—an approach not commonly found in prior literature. Using latitude, month, hour, ambient temperature, pressure, humidity, wind speed, and cloud ceiling as independent variables, a distributed random forest regression algorithm modeled the combined dataset with an R2 value of 0.94. As a comparative measure, other machine learning algorithms resulted in R2 values of 0.50–0.94. Additionally, the data from each location was modeled separately with R2 values ranging from 0.91 to 0.97, indicating a range of consistency across all sites. Using an input variable permutation approach with the random forest algorithm, we found that the three most important variables for power prediction were ambient temperature, humidity, and cloud ceiling. The analysis showed that machine learning potentially allowed for accurate power prediction while avoiding the challenges associated with modeled irradiation data.
Inspection of PN, CO2, and Regulated Gaseous Emissions Characteristics from a GDI Vehicle under Various Real-World Vehicle Test Modes
Authors: Kim Kangjin , Chung Wonyong , Kim Myungsoo , Kim Charyung , Myung Cha-Lee , Park Simsoo
Published: May 2020

Although the chassis dynamometer type approval test considers real-world conditions, there are a few limitations to the experimental test environment that may affect gaseous or particulate emissions such as road conditions, traffic, decreasing tire pressure, or fluctuating ambient temperature. Furthermore, the real driving emission (RDE) test takes a long time, and it is too long to repeat under different experimental conditions. The National Institute of Environmental Research (NIER) test modes that reflect the driving pattern of Korea are not certification test modes, but can be used to evaluate the influence of traffic conditions because these modes consist of a total of 15 test modes that vary according to average speed. The use of the NIER #03, #09, and #13 modes as low-, medium-, and high-speed modes allow for gaseous and particulate emissions to be measured and analyzed. Additionally, the worldwide harmonized light-duty vehicle test procedure (WLTP), the certification mode of Europe, is used to test cycles to investigate the difference under cold- and hot-engine start conditions. The engine operating parameters are also measured to evaluate the relationships between the various test conditions and test cycles. The regulated and greenhouse gas levels decrease under various driving conditions, but the particle number (PN) emission level shows a different trend with gaseous emissions. While the PN and CO2 results dramatically increase when the air conditioner is on, tire pressure conditions show different PN size distributions: a large-sized PN fraction, which contains particles larger than 100 nm, increases and a sub-23 nm-sized PN fraction decreases. Under cold-start conditions in the WLTP modes, there are much higher PN emissions than that of an engine under hot-start conditions, and the sub-23-nm-sized PN fraction also increases.
Small Vessel with Inboard Engine Retrofitting Concepts; Real Boat Tests, Laboratory Hybrid Drive Tests and Theoretical Studies
Authors: Leśniewski Wojciech , Piątek Daniel , Marszałkowski Konrad , Litwin Wojciech
Published: May 2020

The development of modern technologies and their increasing availability, as well as the falling costs of highly efficient propulsion systems and power sources, have resulted in electric or hybrid propulsions systems’ growing popularity for use on watercraft. Presented in the paper are design and lab tests of a prototype parallel hybrid propulsion system. It describes a concept of retrofitting a conventionally powered nine meter-long vessel with the system, and includes results of power and efficiency measurements, as well as calculations of the vessel’s operating range under the propulsion of its electric motor. The concept of adding of a solar panels array was studied.
Modeling and Control of a Multifunctional Three-Phase Converter for Bidirectional Power Flow in Plug-In Electric Vehicles
Authors: Sabzehgar Reza , Roshan Yaser M. , Fajri Poria
Published: May 2020

A nonlinear sliding-mode controller for a three-phase converter, utilized in plug-in electric vehicles (PEVs), is proposed in this paper. The proposed controller enables the utilized converter to perform multiple functions during different operating modes of the vehicle, i.e., grid-to-vehicle (G2V) and vehicle-to-grid (V2G) modes. The bidirectional three-phase converter and the proposed controller operate as a power factor correction circuit, bridgeless boost converter, and rectifier during G2V mode (i.e., plug-in charging), and it operates as a conventional single-stage inverter during V2G mode. The stability analysis of the proposed controller is performed by defining a proper Lyapunov function. The functionality of the proposed nonlinear controller is first evaluated through simulation studies. The feasibility and effectiveness of the proposed control strategy is then validated using an industrial control card through a hardware-in-the-loop (HIL) experimental testbed.
Post-Closure Safety Calculations for the Disposal of Spent Nuclear Fuel in a Generic Horizontal Drillhole Repository
Authors: Finsterle Stefan , Muller Richard A. , Grimsich John , Apps John , Baltzer Rod
Published: May 2020

The post-closure performance of a generic horizontal drillhole repository for the disposal of spent nuclear fuel (SNF) is quantitatively evaluated using a physics-based numerical model that accounts for coupled thermal-hydrological flow and radionuclide transport processes. The model incorporates most subcomponents of the repository system, from individual waste canisters to the geological far field. The main performance metric is the maximum annual dose to an individual drinking potentially contaminated water taken from a well located above the center of the repository. Safety is evaluated for a wide range of conditions and alternative system evolutions, using deterministic simulations, sensitivity analyses, and a sampling-based uncertainty propagation analysis. These analyses show that the estimated maximum annual dose is low (on the order of 10−4 mSv yr−1, which is 1000 times smaller than a typical dose standard), and that the conclusions drawn from this dose estimate remain valid even if considerable changes are made to key assumptions and property values. The depth of the repository and the attributes of its configuration provide the main safety function of isolation from the accessible environment. Long-term confinement of radionuclides in the waste matrix and slow, diffusion-dominated transport leading to long migration times allow for radioactive decay to occur within the repository system. These preliminary calculations suggest that SNF can be safely disposed in an appropriately sited and carefully constructed and sealed horizontal drillhole repository.
Characteristics and Predictors of Heavy Episodic Drinking (HED) among Young People Aged 16–25: The International Alcohol Control Study (IAC), Tshwane, South Africa
Authors: Harker Nadine , Londani Mukhethwa , Morojele Neo , Petersen Williams Petal , Parry Charles DH
Published: May 2020

In South Africa, little is known about alcohol consumption patterns, such as drinks consumed, container size, salience of alcohol price, affordability and availability, and perceptions of alcohol policies as potential predictors of heavy episodic alcohol (HED) use among young people. This paper examines predictors of HED among young people with specific consideration given to these alcohol consumption patterns. This study conducted in the Tshwane Metropole in 2014 employed multi-stage stratified cluster random sampling. Participants were between the ages 16–25 years. A structured questionnaire was used to collect data. Of the 287 (n = 678) participants who had used alcohol in the past six months and for whom we had complete consumption data, almost half were identified as heavy episodic drinkers (HEDs) and were significantly more likely to consume alcohol on a daily basis (p = 0.001). Having nightclub as the primary drinking location (p = 0.023) and drinking from a container size bigger than one standard drink (p = 0.014) were significant predictors for HED. HEDs were also more likely to have a perception that most people consume alcohol (p = 0.047). The results point to HED of alcohol among young people who drink in South Africa, highlighting the need for multicomponent interventions.
Physical and Psychological Factors Associated with Poor Self-Reported Health Status in Older Adults with Falls
Authors: Kim Jiyeon , Byun Mikyong , Kim Moonho
Published: May 2020

Background: Previous studies have proposed various physical tests for screening fall risk in older adults. However, older adults may have physical or cognitive impairments that make testing difficult. This study describes the differences in individual, physical, and psychological factors between adults in good and poor self-rated health statuses. Further, we identified the physical or psychological factors associated with self-rated health by controlling for individual variables. Methods: Data from a total of 1577 adults aged 65 years or over with a history of falls were analyzed, using the 2017 National Survey of Older Persons in South Korea. Self-reported health status was dichotomized as good versus poor using the 5-point Likert question: “poor” (very poor and poor) and “good” (fair, good, and very good). Results: Visual/hearing impairments, ADL/IADL restriction, poor nutrition, and depression were more frequently observed in the group with poor self-rated health. Multivariable logistic regression revealed that poor self-reported health was significantly associated with hearing impairments (OR: 1.51, 95% CI 1.12–2.03), ADL limitation (OR: 1.77, 95% CI 1.11–2.81), IADL limitation (OR: 2.27, 95% CI 1.68–3.06), poor nutrition (OR: 1.36, 95% CI 1.05–1.77), and depression (OR 3.77, 95% CI 2.81–5.06). Conclusions: Auditory impairment, ADL/IADL limitations, poor nutrition, and depression were significantly associated with poor self-reported health. A self-rated health assessment could be an alternative tool for older adults who are not able to perform physical tests.
Physical Fitness and Activity Levels among Chinese People with Schizophrenia: A Cross-Sectional Study with Matched Case-Control Comparison
Authors: Bressington Daniel , Li Yan , Hulbert Sabina , Mak Yim Wah
Published: May 2020

People with schizophrenia have an increased risk of developing cardiometabolic diseases and a reduced life expectancy. Studies conducted mainly in Western settings report low amounts of activity and poor levels of fitness in this population. This study aims to compare physical fitness and activity levels between people with schizophrenia/healthy matched controls and investigate potential associations between these variables. A cross-sectional study was conducted with 57 community-dwelling people with schizophrenia and 57 age-, gender- and body mass index (BMI)-matched controls. Participants completed the international physical activity questionnaire and the Young Men’s Christian Association (YMCA) fitness assessment protocol with accompanying cardiovascular/lung function tests. Cardiorespiratory fitness was significantly better in healthy matched controls than individuals with schizophrenia in all areas (all p < 0.05, d = 0.38 to 1.06). Performance in best trunk flexion, half sit-ups and one-minute pulse recovery following the three-min step test were significantly worse in the schizophrenia group (all p < 0001, d = 0.76 to 1.04). Higher levels of weekly moderate activity (t = −2.66, p = 0.009) and total weekly activity levels (t = −2.013, p = 0.047) were reported by the healthy controls. Levels of vigorous activity were significantly correlated with some areas of lung functioning in the schizophrenia group (all p < 0.05). The findings show that Chinese people with schizophrenia have significantly poorer fitness than matched healthy controls, demonstrating the need to provide timely effective exercise-based interventions as a matter of routine to attenuate the risk of developing chronic physical illnesses.
Spatial Co-Clustering of Cardiovascular Diseases and Select Risk Factors among Adults in South Africa
Authors: Darikwa Timotheus B. , Manda Samuel O.
Published: May 2020

Background: Cardiovascular diseases (CVDs) are part of the leading causes of mortality and morbidity in developing countries, including South Africa, where they are a major public health issue. Understanding the joint spatial clustering of CVDs and associated risk factors to determine areas in need of enhanced integrated interventions would help develop targeted, cost-effective and productive mediations. We estimated joint spatial associations and clustering patterns of 2 CVDs (stroke and heart attack) and 3 risk factors (hypertension, high blood cholesterol (HBC) and smoking) among adults in South Africa. Methods: We used cross-sectional secondary adult (15–64-year olds) health data from the South African Demographic Health Survey 2016. Age and gender standardized disease incidence ratios were analyzed using joint spatial global and local bivariate Moran’s Index statistics. Results: We found significantly positive univariate spatial clustering for stroke (Moran; s Index = 0.128), smoking (0.606) hypertension (0.236) and high blood cholesterol (0.385). Smoking and high blood cholesterol (0.366), smoking and stroke (0.218) and stroke and high blood cholesterol (0.184) were the only bivariate outcomes with significant bivariate clustering. There was a joint stroke-smoking local “hot spots” cluster among four districts in the urban western part of the country (City of Cape Town; Cape Winelands; Overberg and Eden) and a joint “cold spots” cluster in the rural north-western part of the country. Similar joint “hot spots” clustering was found for stroke and high blood cholesterol, which also had “cold spots” cluster in the rural east-central part of the country. Smoking and high blood cholesterol had a “hot spots” cluster among five districts in the urban western part of the country (City of Cape Town; Cape Winelands; Overberg; Eden, and West Coast) and “cold spots” around the rural districts in east-southern parts of the country. Conclusions: Our study showed that districts tended to co-cluster based on the rates of CVDs and risk factors, where higher rates were found in urban places than in rural areas. These findings are suggestive of a more contagious and spatial diffusion process among interdependent districts in urban districts. Urbanization or rurality needs to be considered when intervention initiatives are implemented with more general approaches in rural areas. The finding of “hot spot” co-clusters in urban areas means that integrated intervention programmes aimed at reducing the risk of CVDs and associated risk factors would be cost-effective and more productive.
Dynamic Floating Stations Model for Emergency Medical Services with a Consideration of Traffic Data
Authors: Sun Chih-Hong , Cheng Chen-Yang , Wang Cheng-Hui , Hsiao Po-Huan
Published: May 2020

To equally distribute the workload and minimize the travel distance for fire departments, we developed a new dynamic floating stations model (DFSM) to target traffic-related emergency medical services (EMS) during peak hours. This study revealed that traffic-related EMS incidents have different characteristics to other EMS incidents. The number of floating stations was determined by the number of available ambulances at a given time. The optimum floating station location was identified by using the given capacity to establish the smallest service radius. In DFSM simulations using floating stations with a capacity of 100 and 150 EMS incidents, the result shows significant improvements in comparison to the current situation.
Prenatal Exposure to Valproic Acid Affects Microglia and Synaptic Ultrastructure in a Brain-Region-Specific Manner in Young-Adult Male Rats: Relevance to Autism Spectrum Disorders
Authors: Gąssowska-Dobrowolska Magdalena , Cieślik Magdalena , Czapski Grzegorz Arkadiusz , Jęśko Henryk , Frontczak-Baniewicz Małgorzata , Gewartowska Magdalena , Dominiak Agnieszka , Polowy Rafał , Filipkowski Robert Kuba , Babiec Lidia , Adamczyk Agata
Published: May 2020

Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental conditions categorized as synaptopathies. Environmental risk factors contribute to ASD aetiology. In particular, prenatal exposure to the anti-epileptic drug valproic acid (VPA) may increase the risk of autism. In the present study, we investigated the effect of prenatal exposure to VPA on the synaptic morphology and expression of key synaptic proteins in the hippocampus and cerebral cortex of young-adult male offspring. To characterize the VPA-induced autism model, behavioural outcomes, microglia-related neuroinflammation, and oxidative stress were analysed. Our data showed that prenatal exposure to VPA impaired communication in neonatal rats, reduced their exploratory activity, and led to anxiety-like and repetitive behaviours in the young-adult animals. VPA-induced pathological alterations in the ultrastructures of synapses accompanied by deregulation of key pre- and postsynaptic structural and functional proteins. Moreover, VPA exposure altered the redox status and expression of proinflammatory genes in a brain region-specific manner. The disruption of synaptic structure and plasticity may be the primary insult responsible for autism-related behaviour in the offspring. The vulnerability of specific synaptic proteins to the epigenetic effects of VPA may highlight the potential mechanisms by which prenatal VPA exposure generates behavioural changes.
Pollen Proteases Play Multiple Roles in Allergic Disorders
Authors: Gaspar Ricardo , de Matos Mafalda Ramos , Cortes Luísa , Nunes-Correia Isabel , Todo-Bom Ana , Pires Euclides , Veríssimo Paula
Published: May 2020

Allergic diseases are a major health concern worldwide. Pollens are important triggers for allergic rhinitis, conjunctivitis and asthma. Proteases released upon pollen grain hydration appear to play a major role in the typical immunological and inflammatory responses that occur in patients with allergic disorders. In this study, we aimed to identify specific proteolytic activity in a set of pollens with diverse allergenic potential. Diffusates from Chenopodium album, Plantago lanceolata and Eucalyptus globulus were added to a confluent monolayer of Calu-3 cells grown in an air-liquid interface system. We identified serine proteases and metalloproteinases in all pollen diffusates investigated. Proteases found in these pollen diffusates were shown to compromise the integrity of the lung epithelial barrier by disrupting transmembrane adhesion proteins E-cadherin, claudin-1 and Occludin, as well as, the cytosolic complex zonula occludens-1 (ZO-1) resulting in a time-dependent increase in transepithelial permeability. Tight junction disruption and increased transepithelial permeability facilitates allergen exposure to epithelial sub-layers contributing to the sensitization to a wide range of allergens. These pollen extracts also induced an increase in the release of interleukin 6 (IL-6) and interleukin 8 (IL-8) cytokines measured by flow cytometry possibly as a result of the activation of protease-activated receptors 2 (PAR-2).
Revisiting Experimental Models of Diabetic Nephropathy
Authors: Giralt-López Anna , Molina-Van den Bosch Mireia , Vergara Ander , García-Carro Clara , Seron Daniel , Jacobs-Cachá Conxita , Soler Maria José
Published: May 2020

Diabetes prevalence is constantly increasing and, nowadays, it affects more than 350 million people worldwide. Therefore, the prevalence of diabetic nephropathy (DN) has also increased, becoming the main cause of end-stage renal disease (ESRD) in the developed world. DN is characterized by albuminuria, a decline in glomerular filtration rate (GFR), hypertension, mesangial matrix expansion, glomerular basement membrane thickening, and tubulointerstitial fibrosis. The therapeutic advances in the last years have been able to modify and delay the natural course of diabetic kidney disease (DKD). Nevertheless, there is still an urgent need to characterize the pathways that are involved in DN, identify risk biomarkers and prevent kidney failure in diabetic patients. Rodent models provide valuable information regarding how DN is set and its progression through time. Despite the utility of these models, kidney disease progression depends on the diabetes induction method and susceptibility to diabetes of each experimental strain. The classical DN murine models (Streptozotocin-induced, Akita, or obese type 2 models) do not develop all of the typical DN features. For this reason, many models have been crossed to a susceptible genetic background. Knockout and transgenic strains have also been created to generate more robust models. In this review, we will focus on the description of the new DN rodent models and, additionally, we will provide an overview of the available methods for renal phenotyping.
Understanding the Differentiation, Expansion, Recruitment and Suppressive Activities of Myeloid-Derived Suppressor Cells in Cancers
Authors: Lim Hui Xuan , Kim Tae Sung , Poh Chit Laa
Published: May 2020

There has been a great interest in myeloid-derived suppressor cells (MDSCs) due to their biological functions in tumor-mediated immune escape by suppressing antitumor immune responses. These cells arise from altered myelopoiesis in response to the tumor-derived factors. The most recognized function of MDSCs is suppressing anti-tumor immune responses by impairing T cell functions, and these cells are the most important players in cancer dissemination and metastasis. Therefore, understanding the factors and the mechanism of MDSC differentiation, expansion, and recruitment into the tumor microenvironment can lead to its control. However, most of the studies only defined MDSCs with no further characterization of granulocytic and monocytic subsets. In this review, we discuss the mechanisms by which specific MDSC subsets contribute to cancers. A better understanding of MDSC subset development and the specific molecular mechanism is needed to identify treatment targets. The understanding of the specific molecular mechanisms responsible for MDSC accumulation would enable more precise therapeutic targeting of these cells.
Synthesis of Fmoc-Triazine Amino Acids and Its Application in the Synthesis of Short Antibacterial Peptidomimetics
Authors: Gunasekaran Pethaiah , Kim Eun Young , Lee Jian , Ryu Eun Kyoung , Shin Song Yub , Bang Jeong Kyu
Published: May 2020

To combat the escalating rise of antibacterial resistance, the development of antimicrobial peptides (AMPs) with a unique mode of action is considered an attractive strategy. However, proteolytic degradation of AMPs remains the greatest challenge in their transformation into therapeutics. Herein, we synthesized Fmoc-triazine amino acids that differ from each other by anchoring either cationic or hydrophobic residues. These unnatural amino acids were adopted for solid-phase peptide synthesis (SPPS) to synthesize a series of amphipathic antimicrobial peptidomimetics. From the antimicrobial screening, we found that the trimer, BJK-4 is the most potent short antimicrobial peptidomimetic without showing hemolytic activity and it displayed enhanced proteolytic stability. Moreover, the mechanism of action to kill bacteria was found to be an intracellular targeting.
Physical Exercise and Myokines: Relationships with Sarcopenia and Cardiovascular Complications
Authors: Barbalho Sandra Maria , Flato Uri Adrian Prync , Tofano Ricardo José , Goulart Ricardo de Alvares , Guiguer Elen Landgraf , Detregiachi Cláudia Rucco P. , Buchaim Daniela Vieira , Araújo Adriano Cressoni , Buchaim Rogério Leone , Reina Fábio Tadeu Rodrigues , Biteli Piero , Reina Daniela O. B. Rodrigues , Bechara Marcelo Dib
Published: May 2020

Skeletal muscle is capable of secreting different factors in order to communicate with other tissues. These mediators, the myokines, show potentially far-reaching effects on non-muscle tissues and can provide a molecular interaction between muscle and body physiology. Sarcopenia is a chronic degenerative neuromuscular disease closely related to cardiomyopathy and chronic heart failure, which influences the production and release of myokines. Our objective was to explore the relationship between myokines, sarcopenia, and cardiovascular diseases (CVD). The autocrine, paracrine, and endocrine actions of myokines include regulation of energy expenditure, insulin sensitivity, lipolysis, free fatty acid oxidation, adipocyte browning, glycogenolysis, glycogenesis, and general metabolism. A sedentary lifestyle accelerates the aging process and is a risk factor for developing sarcopenia, metabolic syndrome, and CVD. Increased adipose tissue resulting from the decrease in muscle mass in patients with sarcopenia may also be involved in the pathology of CVD. Myokines are protagonists in the complex condition of sarcopenia, which is associated with adverse clinical outcomes in patients with CVD. The discovery of new pathways and the link between myokines and CVD remain a cornerstone toward multifaceted interventions and perhaps the minimization of the damage resulting from muscle loss induced by factors such as atherosclerosis.
Production and Sensing of Butyrate in a Probiotic E. coli Strain
Authors: Bai Yanfen , Mansell Thomas J.
Published: May 2020

The short-chain fatty acid butyrate plays critical roles in human gut health, affecting immunomodulation, cell differentiation, and apoptosis, while also serving as the preferred carbon source for colon cells. In this work, we have engineered a model probiotic organism, E. coli Nissle 1917 (EcN, serotype O6:K5:H1), to produce butyrate from genomic loci up to approximately 1 g/L (11 mM). Then, for real-time monitoring of butyrate production in cultures, we developed a high-throughput biosensor that responds to intracellular butyrate concentrations, with green fluorescent protein as the reporter. This work provides a foundation for studies of butyrate for therapeutic applications.
A Novel Optimization Model and Application of Optimal Formula Design for CuxCo1−xFe2O4 Spinel-Based Coating Slurry in Relation to Near and Middle Infrared Radiation Strengthening
Authors: Du Haiqing , An Haifei , Zhang Jian , Ding Yuhao , Lian Chao , Bai Hao
Published: May 2020

Coating slurry, in which the infrared radiation material is the main content, is applied in industrial furnaces to improve heat transfer and raise efficiency of furnaces. In this study, a Cu x Co 1 − x Fe 2 O 4 series material with a spinel structure was prepared, and the emissivity of different formulas in two wavebands (3–5 μm and 8–14 μm) was measured. To ensure that the material delivered high emissivity, optimization models were proposed using Matlab software, and proportions of CuO, Co2O3 and Fe2O3 were found to be 16.98%, 16.73% and 66.29%, respectively, in the optimal formula. Thus, using the Cu x Co 1 − x Fe 2 O 4 series material and additives, according to mixture regression method, fifteen formulas of coating slurry were designed, prepared and the emissivities were measured. With the Matlab software optimization model, the content of coating slurry was optimized and the corresponding emissivities were measured to be 0.931 and 0.905 in two wavebands, which is in agreement with the optimized calculation.
AlxIn1−xN on Si (100) Solar Cells (x = 0–0.56) Deposited by RF Sputtering
Authors: Valdueza-Felip Sirona , Blasco Rodrigo , Olea Javier , Díaz-Lobo Alba , Braña Alejandro F. , Naranjo Fernando B.
Published: May 2020

We investigate the photovoltaic performance of solar cells based on n-AlxIn1−xN (x = 0–0.56) on p-Si (100) hetero-junctions deposited by radio frequency sputtering. The AlxIn1−xN layers own an optical bandgap absorption edge tuneable from 1.73 eV to 2.56 eV within the Al content range. This increase of Al content results in more resistive layers (≈10−4–1 Ω·cm) while the residual carrier concentration drops from ~1021 to ~1019 cm−3. As a result, the top n-contact resistance varies from ≈10−1 to 1 MΩ for InN to Al0.56In0.44N-based devices, respectively. Best results are obtained for devices with 28% Al that exhibit a broad external quantum efficiency covering the full solar spectrum with a maximum of 80% at 750 nm, an open-circuit voltage of 0.39 V, a short-circuit current density of 17.1 mA/cm2 and a conversion efficiency of 2.12% under air mass 1.5 global (AM1.5G) illumination (1 sun), rendering them promising for novel low-cost III-nitride on Si photovoltaic devices. For Al contents above 28%, the electrical performance of the structures lessens due to the high top-contact resistivity.