bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis and Characterization of Stiff, Self-Crosslinked Thermoresponsive DMAA Hydrogels
Authors: Rueda Juan Carlos , Santillán Fátima , Komber Hartmut , Voit Brigitte
Published: June 2020

Stiff thermosensitive hydrogels (HG) were synthesized by self-crosslinking free radical polymerization of N,N-dimethylacrylamide (DMAA) and N-isopropylacrylamide (NIPAAm), adjusting the degree of swelling by carboxylate-containing sodium acrylate (NaAc) or a 2-oxazoline macromonomer (MM). The formation of hydrogels was possible due to the self-crosslinking property of DMAA when polymerized with peroxodisulfate initiator type. The MM was synthetized by the ring-opening cationic polymerization of 2-methyl-2-oxazoline (MeOxa) and methyl-3-(oxazol-2-yl)-propionate (EsterOxa), and contained a polymerizable styryl endgroup. After ester hydrolysis of EsterOxa units, a carboxylate-containing MM was obtained. The structure of the hydrogels was confirmed by 1H high-resolution (HR)-MAS NMR spectroscopy. Suitable conditions and compositions of the comonomers have been found, which allowed efficient self-crosslinking as well as a thermoresponsive swelling in water. Incorporation of both the polar comonomer and the macromonomer, in small amounts furthermore allowed the adjustment of the degree of swelling. However, the macromonomer was better suited to retain the thermoresponsive behavior of the poly (NIPAAm) due to a phase separation of the tangling polyoxazoline side chains. Thermogravimetric analysis determined that the hydrogels were stable up to ~ 350 °C, and dynamic mechanical analysis characterized a viscoelastic behavior of the hydrogels, properties that are required, for example, for possible use as an actuator material.
The Competition of Termination and Shielding to Evaluate the Success of Surface-Initiated Reversible Deactivation Radical Polymerization
Authors: Arraez Francisco J. , Van Steenberge Paul H. M. , D’hooge Dagmar R.
Published: June 2020

One of the challenges for brush synthesis for advanced bioinspired applications using surface-initiated reversible deactivation radical polymerization (SI-RDRP) is the understanding of the relevance of confinement on the reaction probabilities and specifically the role of termination reactions. The present work puts forward a new matrix-based kinetic Monte Carlo platform with an implicit reaction scheme capable of evaluating the growth pattern of individual free and tethered chains in three-dimensional format during SI-RDRP. For illustration purposes, emphasis is on normal SI-atom transfer radical polymerization, introducing concepts such as the apparent livingness and the molecular height distribution (MHD). The former is determined based on the combination of the disturbing impact of termination (related to conventional livingness) and shielding of deactivated species (additional correction due to hindrance), and the latter allows structure-property relationships to be identified, starting at the molecular level in view of future brush characterization. It is shown that under well-defined SI-RDRP conditions the contribution of (shorter) hindered dormant chains is relevant and more pronounced for higher average initiator coverages, despite the fraction of dead chains being less. A dominance of surface-solution termination is also put forward, considering two extreme diffusion modes, i.e., translational and segmental. With the translational mode termination is largely suppressed and the living limit is mimicked, whereas with the segmental mode termination occurs more and the termination front moves upward alongside the polymer layer growth. In any case, bimodalities are established for the tethered chains both on the level of the chain length distribution and the MHD.
Thermodynamic Characterization of Free and Surface Water of Colloidal Unimolecular Polymer (CUP) Particles Utilizing DSC
Authors: Geng Peng , Zore Ashish , Van De Mark Michael R.
Published: June 2020

Colloidal Unimolecular Polymer (CUP) particles are spheroidal, 3–9 nm with charged groups on the surface and a hydrophobic core, which offer a larger surface water fraction to improve the analysis of its characteristics. Differential scanning calorimetry (DSC) was performed to determine the characteristics of surface water. These properties include the amount of surface water, the layer thickness, density, specific heat of the surface water above and below the freezing point of water, melting point depression of free water, effect of charge density and particle size. The charge density on the CUP surface was varied as well as the molecular weight which controls the particle diameter. The surface water is proportional to the weight fraction of CUP <20%. Analogous to recrystallization the CUP particles were trapped in the ice when rapidly cooled but slow cooling excluded the CUP, causing inter-molecular counterion condensation and less surface water. The density of surface water was calculated to be 1.023 g/mL to 1.056 g/mL depending on the surface charge density. The thickness of surface water increased with surface charge density. The specific heat of surface water was found to be 3.04 to 3.07 J/g·K at 253.15 K and 3.07 to 3.09 J/g·K at 293.15 K. The average area occupied by carboxylate and ester groups on the CUP surface were determined.
Rapid and Enhanced Liquefaction of Pulp from Mango (Mangifera indica L.) cv. Totapuri Using Ultrasound-Assisted Enzyme Pretreatment
Authors: Reddy Lebaka Veeranjaneya , Kim Young-Min , Wee Young-Jung
Published: June 2020

The effect of ultrasound and enzyme pretreatment (with pectinase, amylase, and cellulase) on the physicochemical properties (yield, viscosity, total soluble solids, and total phenolics) of mango juice was evaluated through a set of six experiments. Ultrasonication treatment alone showed no influence on juice yield (54.6 ± 1.1%). However, the combined uses of ultrasonication with a pectinase or the enzyme mixture significantly increased the yield (94.1 ± 1.4% and 80.0 ± 2.1%, respectively) and decreased the enzyme pretreatment time (from 2 h to 1 h). Pectinase treatment assisted by ultrasonication was more effective with regard to juice yield, viscosity reduction, and the clarity of the juice than the enzyme mixture treatment with ultrasonication. Ultrasonication alone significantly increased the amount of total phenolics (65.5 ± 1.0 mg/100 mL) and showed a slight reduction of viscosity and improvement of clarity compared to the control.
Mathematical Modeling of RNA Virus Sensing Pathways Reveals Paracrine Signaling as the Primary Factor Regulating Excessive Cytokine Production
Authors: Weaver Jordan J. A. , Shoemaker Jason E.
Published: June 2020

RNA viruses, such as influenza and Severe Acute Respiratory Syndrome (SARS), invoke excessive immune responses; however, the kinetics that regulate inflammatory responses within infected cells remain unresolved. Here, we develop a mathematical model of the RNA virus sensing pathways, to determine the intracellular events that primarily regulate interferon, an important protein for the activation and management of inflammation. Within the ordinary differential equation (ODE) model, we incorporate viral replication, cell death, interferon stimulated genes’ antagonistic effects on viral replication, and virus sensor protein (TLR and RIG-I) kinetics. The model is parameterized to influenza infection data using Markov chain Monte Carlo and then validated against infection data from an NS1 knockout strain of influenza, demonstrating that RIG-I antagonism significantly alters cytokine signaling trajectory. Global sensitivity analysis suggests that paracrine signaling is responsible for the majority of cytokine production, suggesting that rapid cytokine production may be best managed by influencing extracellular cytokine levels. As most of the model kinetics are host cell specific and not virus specific, the model presented provides an important step to modeling the intracellular immune dynamics of many RNA viruses, including the viruses responsible for SARS, Middle East Respiratory Syndrome (MERS), and Coronavirus Disease (COVID-19).
Elastic Constants Prediction of 3D Fiber-Reinforced Composites Using Multiscale Homogenization
Authors: Shah S. Z. H. , Megat Yusoff Puteri S. M. , Karuppanan Saravanan , Sajid Zubair
Published: June 2020

This paper presents a multi-scale-homogenization based on a two-step methodology (micro-meso and meso-macro homogenization) to predict the elastic constants of 3D fiber-reinforced composites (FRC). At each level, the elastic constants were predicted through both analytical and numerical methods to ascertain the accuracy of predicted elastic constants. The predicted elastic constants were compared with experimental data. Both methods predicted the in-plane elastic constants “ E x ” and “ E y ” with good accuracy; however, the analytical method under predicts the shear modulus “ G x y ”. The elastic constants predicted through a multiscale homogenization approach can be used to predict the behavior of 3D-FRC under different loading conditions at the macro-level.
Food Waste Composting and Microbial Community Structure Profiling
Authors: Palaniveloo Kishneth , Amran Muhammad Azri , Norhashim Nur Azeyanti , Mohamad-Fauzi Nuradilla , Peng-Hui Fang , Hui-Wen Low , Kai-Lin Yap , Jiale Looi , Chian-Yee Melissa Goh , Jing-Yi Lai , Gunasekaran Baskaran , Razak Shariza Abdul
Published: June 2020

Over the last decade, food waste has been one of the major issues globally as it brings a negative impact on the environment and health. Rotting discharges methane, causing greenhouse effect and adverse health effects due to pathogenic microorganisms or toxic leachates that reach agricultural land and water system. As a solution, composting is implemented to manage and reduce food waste in line with global sustainable development goals (SDGs). This review compiles input on the types of organic composting, its characteristics, physico-chemical properties involved, role of microbes and tools available in determining the microbial community structure. Composting types: vermi-composting, windrow composting, aerated static pile composting and in-vessel composting are discussed. The diversity of microorganisms in each of the three stages in composting is highlighted and the techniques used to determine the microbial community structure during composting such as biochemical identification, polymerase chain reaction denaturing gradient gel electrophoresis (PCR-DGGE), terminal restriction fragment length polymorphism (T-RFLP) and single strand-conformation polymorphism (SSCP), microarray analysis and next-generation sequencing (NGS) are discussed. Overall, a good compost, not only reduces waste issues, but also contributes substantially to the economic and social sectors of a nation.
The Neural Network Revamping the Process’s Reliability in Deep Lean via Internet of Things
Authors: Abed Ahmed M. , Elattar Samia , Gaafar Tamer S. , Alrowais Fadwa Moh.
Published: June 2020

Deep lean is a novel approach that is concerned with the profound analysis for waste’s behavior at hidden layers in manufacturing processes to enhance processes’ reliability level at the upstream. Ideal Standard Co. for bathtubs suffered from defects and cost losses in the spraying section, due to differences in the painting cover thickness due to bubbles, caused by eddies, which move toward the bathtubs through hoses. These bubbles and their movement are considered as a form of lean’s waste. The spraying liquid inside the tanks and hoses must move with uniform velocity, viscosity, pressure, feed rate and suitable Reynolds circulation values to eliminate the eddy causes. These factors are tackled through the adoption Internet of Things (IoT) technologies that are aided by neural networks (NN) when an abnormal flow rate is detected using sensor data in real-time that can reduce the defects. The NN aimed at forecasting eddies’ movement lines that carry bubbles and works on being blasted before entering the hoses through using Design of Experiment (DOE). This paper illustrates a deep lean perspective as driven by the define, measure, analysis, improvement and control (DMAIC) methodology to improve reliability. The eddy moves downstream slowly with an anti-clockwise flow for some of the optimal values for the influencing factors, whereas the circulation of Ω increases, whether for vertical or horizontal travel.
Approaches in Design of Laboratory-Scale UASB Reactors
Authors: Pererva Yehor , Miller Charles D. , Sims Ronald C.
Published: June 2020

Up-flow Anaerobic Sludge Blanket (UASB) reactors are popular tools in wastewater treatment systems due to the ability to work with high feed rates and wastes with high concentration of organic contaminants. While full-scale industrial applications of UASB reactors are developed and described in the available literature, laboratory-scale designs utilized for treatability testing are not well described. The majority of published studies do not describe the laboratory UASB construction details or do use reactors that already had developed a trophic network in microbial consortia under laboratory environment and therefore are more stable. The absence of defined guidelines for geometry design, selection of materials, construction, operation rules, and, especially, the start-up conditions, significantly hamper researchers who desire to conduct treatability testing using UASB reactors in laboratory scale. In this article, we compiled and analyzed the information available in the refereed literature concerning UASB reactors used in laboratory environment, where information on geometry and/or operational conditions were provided in detail. We utilized the information available in the literature and the experience gained in our laboratory (Sustainable Waste to Bioproducts Engineering Center) to suggest a unified operation flowchart and for design, construction, operation, and monitoring for a laboratory-scale UASB reactors.
Evaluation of a Novel Polymeric Flocculant for Enhanced Water Recovery of Mature Fine Tailings
Authors: Lister Kyle C. , Kaminsky Heather , Hutchinson Robin A.
Published: June 2020

The novel cationic flocculant, poly(lactic acid) choline iodide ester methacrylate (poly(PLA4ChMA)), has been shown to provide improved flocculation of 5.0 wt.% mature fine tailings (MFT) diluted in deionized water compared to commercial anionic polymers, with continued dewatering of the sediment occurring as the polymer undergoes partial hydrolytic degradation. However, the elevated dosages (10,000 ppm) required would make the polymer costly to implement on an industrial scale. With this motivation, the impact of MFT loading and the use of process water is explored while comparing the settling performance of poly(PLA4ChMA) to available commercial alternatives such as anionic FLOPAM A3338. Improved consolidation of 5.0 wt.% MFT diluted with process water could be achieved at reduced dosages (500 ppm) with poly(PLA4ChMA). However, the final compaction levels after polymer degradation were similar to those achieved with the nondegradable commercial flocculants. Flocculation-filtration experiments with undiluted MFT are also conducted to compare the performance of the polymers. Significantly faster rates of water release were observed with the cationic flocculants compared to FLOPAM A3338, but no improvement in the overall tailings compaction was found either before or after poly(PLA4ChMA) degradation. Thus, the improved dewatering observed with poly(PLA4ChMA) in dilute MFT suspensions does not extend to conditions that would be encountered in the field.
Optimal Scheduling of Island Microgrid with Seawater-Pumped Storage Station and Renewable Energy
Authors: Liang Ning , Li Pengcheng , Liu Zhijian , Song Qi , Luo Linlin
Published: June 2020

The rapid development of renewable energy, represented by wind and photovoltaic, provides a new solution for island power supplies. However, due to the intermittent and random nature of renewable energy, a microgrid needs energy-storage components to stabilize its power supply when coupled with them. The emergence of seawater-pumped storage stations provides a new method to offset the shortage of island power supply. In this study, an optimal scheduling of island microgrid is proposed, which uses seawater-pumped storage station as the energy storage equipment to cooperate with wind, photovoltaic and diesel generator. First, a mathematic formulation of seawater-pumped storage station with renewable energy is presented. Then, to reach the goal of economic dispatch, an optimal scheduling model of island microgrid is established with the consideration of both respective operation constraints and island load requirements. Finally, the effectiveness of the proposed model is verified by an island microgrid over two typical seasons. The simulation results show that the proposed framework not only increases the usage of renewable energy, but also improves the operational reliability and economy of island microgrids.
Evaluation of the Consistency of Simultaneously Acquired Sentinel-2 and Landsat 8 Imagery on Plastic Covered Greenhouses
Authors: Aguilar Manuel Ángel , Jiménez-Lao Rafael , Nemmaoui Abderrahim , Aguilar Fernando José , Koc-San Dilek , Tarantino Eufemia , Chourak Mimoun
Published: June 2020

Remote sensing techniques based on medium resolution satellite imagery are being widely applied for mapping plastic covered greenhouses (PCG). This article aims at testing the spectral consistency of surface reflectance values of Sentinel-2 MSI (S2 L2A) and Landsat 8 OLI (L8 L2 and the pansharpened and atmospherically corrected product from L1T product; L8 PANSH) data in PCG areas located in Spain, Morocco, Italy and Turkey. The six corresponding bands of S2 and L8, together with the normalized difference vegetation index (NDVI), were generated through an OBIA approach for each PCG study site. The coefficient of determination (r2) and the root mean square error (RMSE) were computed in sixteen cloud-free simultaneously acquired image pairs from the four study sites to evaluate the coherence between the two sensors. It was found that the S2 and L8 correlation (r2 > 0.840, RMSE < 9.917%) was quite good in most bands and NDVI. However, the correlation of the two sensors fluctuated between study sites, showing occasional sun glint effects on PCG roofs related to the sensor orbit and sun position. Moreover, higher surface reflectance discrepancies between L8 L2 and L8 PANSH data, mainly in the visible bands, were always observed in areas with high-level aerosol values derived from the aerosol quality band included in the L8 L2 product (SR aerosol). In this way, the consistency between L8 PANSH and S2 L2A was improved mainly in high-level aerosol areas according to the SR aerosol band.
Monitoring of Surface Temperature on Parco delle Biancane (Italian Geothermal Area) Using Optical Satellite Data, UAV and Field Campaigns
Authors: Silvestri Malvina , Marotta Enrica , Buongiorno Maria Fabrizia , Avvisati Gala , Belviso Pasquale , Bellucci Sessa Eliana , Caputo Teresa , Longo Vittorio , De Leo Vito , Teggi Sergio
Published: June 2020

The purpose of this study is to analyze the surface temperature and the distribution of thermal signatures on Tuscany’s geothermal districts using data obtained through three separate surveys via satellite and an unmanned aerial vehicle (UAV). The analysis considers the highest available spatial resolution ranging from hundreds of meters per pixel of the satellite thermal images and the tenths/hundreds of centimeters per pixel of the thermal images acquired by the UAV. The surface temperature maps obtained by satellite data acquired at suitable spatial resolution and the thermal measurements obtained by the thermal camera installed on the UAV were orthorectified and geocoded. This allowed, for example, following the evolution of thermal anomalies, which may represent a modification of the current state of the geothermal field and a possible hazard for both the population and industrial assets. Here, we show the results obtained in three field campaigns during which the simultaneous acquisition of Landsat 8 satellite and UAV (FlyBit octocopter, IDS, Rome, Italy) thermal data were analyzed. By removing the atmosphere contribution from Landsat 8 data, we have produced three surface temperature maps that are compared with the ground field measurements and the surface temperature maps elaborated by FLIR VUE PRO-R on the UAV.
Study on Spectral Response and Estimation of Grassland Plants Dust Retention Based on Hyperspectral Data
Authors: Zhao Yibo , Lei Shaogang , Yang Xingchen , Gong Chuangang , Wang Cangjiao , Cheng Wei , Li Heng , She Changchao
Published: June 2020

Accurate monitoring of plant dust retention can provide a basis for dust pollution control and environmental protection. The aims of this study were to analyze the spectral response features of grassland plants to mining dust and to predict the spatial distribution of dust retention using hyperspectral data. The dust retention content was determined by an electronic analytical balance and a leaf area meter. The leaf reflectance spectrum was measured by a handheld hyperspectral camera, and the airborne hyperspectral data were obtained using an imaging spectrometer. We analyzed the difference between the leaf spectral before and after dust removal. The sensitive spectra of dust retention on the leaf- and the canopy-scale were determined through two-dimensional correlation spectroscopy (2DCOS). The competitive adaptive reweighted sampling (CARS) algorithm was applied to select the feature bands of canopy dust retention. The estimation model of canopy dust retention was built through random forest regression (RFR), and the dust distribution map was obtained based on the airborne hyperspectral image. The results showed that dust retention enhanced the spectral reflectance of leaves in the visible wavelength but weakened the reflectance in the near-infrared wavelength. Caused by the canopy structure and multiple scattering, a slight difference in the sensitive spectra on dust retention existed between the canopy and leaves. Similarly, the sensitive spectra of leaves and the canopy were closely related to dust and plant physiological parameters. The estimation model constructed through 2DCOS-CARS-RFR showed higher precision, compared with genetic algorithm-random forest regression (GA-RFR) and simulated annealing algorithm-random forest regression (SAA-RFR). Spatially, the amount of canopy dust increased and then decreased with increasing distance from the mining area, reaching a maximum within 300–500 m. This study not only demonstrated the importance of extracting feature bands based on the response of plant physical and chemical parameters to dust, but also laid a foundation for the rapid and non-destructive monitoring of grassland plant dust retention.
Evaluating the Preconditions of Two Remote Sensing SWE Retrieval Algorithms over the US
Authors: Oveisgharan Shadi , Esteban-Fernandez Daniel , Waliser Duane , Friedl Randall , Nghiem Son , Zeng Xubin
Published: June 2020

A large amount of fresh water resources are stored in the snowpack, which is the primary source of water for streamflow in many places at middle-to-high latitude areas. Therefore, snow water equivalent (SWE) is a key parameter in the water cycle. Active and passive microwave remote sensing methods have been used to retrieve SWE due to relatively poor resolution of current in situ interpolated maps with good accuracy. However, estimation of SWE has proved challenging, despite several decades of efforts to develop retrieval approaches. Active sensors provide higher-resolution observations. Two recent promising retrieval algorithms using active data are dual frequency dual polarization backscattered power and differential interferometry. These retrieval algorithms have some restrictions on snow characteristics, the environment, and instrument properties. The restrictions limit the snow that is suitable for the specific retrieval algorithm. In order to better understand how much of the snowpack satisfies the precondition of these retrieval approaches, we use a 4 km gridded snowpack product over the contiguous US for years 1997 and 2015. We use a simple scattering model to simulate the scattering characteristics of snow. The snow property maps, simulated scattering characteristics of snow, and environmental conditions are used to filter the suitable snow for each retrieval algorithm. We show that snow wetness and vegetation coverage are the two main limiting conditions for these retrieval algorithms. We show that 39% and 44% of the grid-points with snow satisfy the preconditions of dual polarization dual frequency retrieval algorithms at 13.5 GHz (one of the recommended frequencies for this algorithm in the literature) in 1997 and 2015, respectively. The most important limiting factors for dual polarization dual frequency retrieval method are dryness of snow, penetration depth, and vegetation-free constraints. The backscattered power in dual polarization dual frequency method is more sensitive to snow density and grain radius rather than to snow depth. We also show that 55% and 53% of the grid-points with snow satisfy the precondition of differential interferometry retrieval algorithms at 1 GHz (one of the recommended frequencies for this algorithm in the literature) in 1997 and 2015, respectively. The most important precondition-limiting factors for differential interferometry are dryness of snow and vegetation-free constraints. The differential interferometry phase retrieval algorithm is equally sensitive to snow height and snow density variations and is independent of snow grain radius.
Long-Term Trends in Root-Zone Soil Moisture across CONUS Connected to ENSO
Authors: Tobin Kenneth J. , Torres Roberto , Bennett Marvin E. , Dong Jianzhi , Crow Wade T.
Published: June 2020

Root zone soil moisture (RZSM) is one of the least-monitored variables within the hydrologic cycle. Given the importance of RZSM to agriculture, more effort is needed to understand the potential impacts of the El Niño southern oscillation (ENSO), Pacific decadal oscillation (PDO), and Atlantic multidecadal oscillation (AMO) on this critical variable. This study focused on the CONtiguous United States (CONUS) RZSM (0 to 40 cm depth) over nearly three decades (1992 to 2018). Basic trend analysis with the Mann–Kendall test and wavelet transform coherence (WTC) was utilized. The RZSM product examined was Soil MERGE (SMERGE 2.0). More CONUS pixels exhibited drying (56 to 75%) versus wetting (25 to 44%) trends between 1992 and 2018. Seasonal wetting trends were observed particularly during winter in the Southwest and Northwest regions associated with El Nino and La Nina episodes, respectively. The noted long-term RZSM trends are more clearly attributable to oceanic-atmospheric teleconnections than global climate change. The most significant result was the strong drying trend in central CONUS reflected a shift to La Nina and cool PDO conditions during the 2000s, further amplified by a change to positive AMO corresponding with this period.
Robust Parking Path Planning with Error-Adaptive Sampling under Perception Uncertainty
Authors: Lee Seongjin , Lim Wonteak , Sunwoo Myoungho
Published: June 2020

In automated parking systems, a path planner generates a path to reach the vacant parking space detected by a perception system. To generate a safe parking path, accurate detection performance is required. However, the perception system always includes perception uncertainty, such as detection errors due to sensor noise and imperfect algorithms. If the parking path planner generates the parking path under uncertainty, problems may arise that cause the vehicle to collide due to the automated parking system. To avoid these problems, it is a challenging problem to generate the parking path from the erroneous parking space. To solve this conundrum, it is important to estimate the perception uncertainty and adapt the detection error in the planning process. This paper proposes a robust parking path planning that combines an error-adaptive sampling of generating possible path candidates with a utility-based method of making an optimal decision under uncertainty. By integrating the sampling-based method and the utility-based method, the proposed algorithm continuously generates an adaptable path considering the detection errors. As a result, the proposed algorithm ensures that the vehicle is safely located in the true position and orientation of the parking space under perception uncertainty.
Artificial Neural Network for Atrial Fibrillation Identification in Portable Devices
Authors: Marinucci Daniele , Sbrollini Agnese , Marcantoni Ilaria , Morettini Micaela , Swenne Cees A. , Burattini Laura
Published: June 2020

Atrial fibrillation (AF) is a common cardiac disorder that can cause severe complications. AF diagnosis is typically based on the electrocardiogram (ECG) evaluation in hospitals or in clinical facilities. The aim of the present work is to propose a new artificial neural network for reliable AF identification in ECGs acquired through portable devices. A supervised fully connected artificial neural network (RSL_ANN), receiving 19 ECG features (11 morphological, 4 on F waves and 4 on heart-rate variability (HRV)) in input and discriminating between AF and non-AF classes in output, was created using the repeated structuring and learning (RSL) procedure. RSL_ANN was created and tested on 8028 (training: 4493; validation: 1125; testing: 2410) annotated ECGs belonging to the “AF Classification from a Short Single Lead ECG Recording” database and acquired with the portable KARDIA device by AliveCor. RSL_ANN performance was evaluated in terms of area under the curve (AUC) and confidence intervals (CIs) of the received operating characteristic. RSL_ANN performance was very good and very similar in training, validation and testing datasets. AUC was 91.1% (CI: 89.1–93.0%), 90.2% (CI: 86.2–94.3%) and 90.8% (CI: 88.1–93.5%) for the training, validation and testing datasets, respectively. Thus, RSL_ANN is a promising tool for reliable identification of AF in ECGs acquired by portable devices.
Passive Sensing of Prediction of Moment-To-Moment Depressed Mood among Undergraduates with Clinical Levels of Depression Sample Using Smartphones
Authors: Jacobson Nicholas C. , Chung Yeon Joo
Published: June 2020

Prior research has recently shown that passively collected sensor data collected within the contexts of persons daily lives via smartphones and wearable sensors can distinguish those with major depressive disorder (MDD) from controls, predict MDD severity, and predict changes in MDD severity across days and weeks. Nevertheless, very little research has examined predicting depressed mood within a day, which is essential given the large amount of variation occurring within days. The current study utilized passively collected sensor data collected from a smartphone application to future depressed mood from hour-to-hour in an ecological momentary assessment study in a sample reporting clinical levels of depression (N = 31). Using a combination of nomothetic and idiographically-weighted machine learning models, the results suggest that depressed mood can be accurately predicted from hour to hour with an average correlation between out of sample predicted depressed mood levels and observed depressed mood of 0.587, CI [0.552, 0.621]. This suggests that passively collected smartphone data can accurately predict future depressed mood among a sample reporting clinical levels of depression. If replicated in other samples, this modeling framework may allow just-in-time adaptive interventions to treat depression as it changes in the context of daily life.
Risk Perception and Its Influencing Factors among Construction Workers in Malawi
Authors: Chaswa Esther Nkhawazawo , Kosamu Ishmael Bobby Mphangwe , Kumwenda Save , Utembe Wells
Published: June 2020

This study employed a deductive research approach and a survey strategy to assess risk perception and its influencing factors among construction workers in Malawi. Three specific construction hazards and their associated risks were selected. The hazards were “working at height (WAH)” “manual handling of loads (MHL)” and “heavy workload or intense pressure to be more productive (HWP).” The study engaged multistage sampling of 376 subjects. Univariate analysis, factor analysis and multiple linear regressions were performed in order to determine the main influencing factors among the independent variables. The study established that workers were aware of risks posed by their work. The majority perceived the risk associated with WAH, MHL and HWP as very high (62.7%, =8.80 ± 1.95); (48.5%, =8.10 ± 2.38); (57.9%, =8.49 ± 2.22) respectively. The study identified six factors as variables that showed a significant effect on workers’ perception of risk (p < 0.05). These factors were: “dreaded factor,” “avoidability and controllability,” “expert knowledge,” “personal knowledge,” “education level,” and “age”. It is concluded that contractors in the Malawian construction industry should integrate analysis of behaviors and risk perception of the workers and other players to guide the identification of better health and safety interventions at their worksites.
Rice as a Determinant of Vietnamese Economic Sustainability
Authors: Maitah Kamil , Smutka Luboš , Sahatqija Jeta , Maitah Mansoor , Phuong Anh Nguyen
Published: June 2020

This paper aims to examine the rice industry in Vietnam during the period 1997–2017, focusing its production and export. The total area of Vietnam is 33.121 million hectares, out of which 39.25% consists of agricultural land. The agricultural sector adds up to 24% of the gross domestic product (GDP), 20% of the total exports and over 70% of the total employment. Vietnam’s economy is highly dependent on the agricultural sector, specifically rice production, which constitutes 30% of the country’s total agricultural production value. While its production at first aimed to ensure food security in the country, to date, Vietnam is one the world’s largest exporters. While extensive research has explored the rice industry, studies looking at the production through the use of fertilizers, external factors such as the exporting price of other countries and world consumption rates are still lacking. Given the complexity of the topic, data were analyzed through descriptive, econometric and quantitative methods. For production and export analyses, two and four hypotheses were derived and examined, respectively, all based on economic theory. The model consisted of two equations: (i) the paddy production is impacted by rice’s yield and fertilizer use and (ii) in addition to internal factors, the growth of exporting rice in Vietnam depends also on external factors such as Thailand’s rice export price and world consumption rates. Based on the model, a dynamic forecasting method was employed, using the previous forecast values of the dependent variables to compute the future ones. Findings showed that 98% of Vietnam’s rice production is explained through the yield and fertilizer usage and 83% of Vietnam’s rice export is explained by the production, the price in Vietnam and Thailand and the consumption levels around the world. When it comes to forecasting, an 8% growth is predicted with a peak in quantity produced, with 49,461 thousand tons in 2023, yet with difficulties when it comes to exporting. The research predicts a stagnation in exports.
Circuit Training during Physical Education Classes to Prepare Cadets for Military Academies Tests: Analysis of an Educational Project
Authors: Invernizzi Pietro Luigi , Signorini Gabriele , Pizzoli Maurizio , Alberti Giampietro , Formenti Damiano , Bosio Andrea
Published: June 2020

Background: The aim of this study was to test the efficacy of an eight-week physical education program based on circuit training to better improve the overall physical and military-specific performance compared to a conventional physical education program in military high school students. Methods: Sixty-four students were enrolled in this study and randomly assigned to an experimental (EG, circuit training) or a control group (CG, traditional physical education program). Immediately before and after the eight-week training period, participants were tested on strength and endurance performance, circuit training tests, and military tests. Moreover, the acquisition of the educational objectives and the pleasantness of the experimental intervention were tested using a qualitative approach. Results: Despite the higher workload in EG than CG during the training period, the effect of the experimental intervention compared to the control was only possibly to likely positive for a few strength and endurance performances and circuit training tests, respectively. A trivial effect was shown in the military tests. On the contrary, the high percentage of motivation (76%), understanding (78%) and collaboration (86%) showed by the students suggests the achievement of acquisition of the educational objectives and a fair pleasantness of the lessons. Conclusions: A lack of clear and marked effect of the experimental intervention could be ascribed to an insufficient exposure time to the training and a high subjective overall workload encountered in military high school students.
A Multi-Criteria Evaluation Method of Product-Level Circularity Strategies
Authors: Alamerew Yohannes A. , Kambanou Marianna Lena , Sakao Tomohiko , Brissaud Daniel
Published: June 2020

The circular economy (CE) can drive sustainability. For companies to select and implement circularity strategies, they need to evaluate and compare the performance of these strategies both in terms of progress towards CE but also based on their feasibility and business outcomes. However, evaluation methods for circularity strategies at the product level are lacking. Therefore, this research proposes a multi-criteria evaluation method of circularity strategies at the product level which can be used by business decision-makers to evaluate and compare the initial business of the company, transformative and future circularity strategies. This multi-criteria evaluation method aims to assist business decision-makers to identify a preferred strategy by linking together a wide variety of criteria, i.e., environmental, economic, social, legislative, technical, and business, as well as by proposing relevant indicators that take into consideration, where possible, the life cycle perspective. It also allows for flexibility so that criteria, sub-criteria, and weighing factors can be altered by the business decision-makers to fit the needs of their specific case or product. Two illustrative examples based on case companies are presented to verify and illustrate the proposed method.
China’s Equine Industries in a Transitional Economy: Development, Trends, Challenges, and Opportunities
Authors: Wang Qingbin , Zou Yang
Published: June 2020

China had the most horses in the world from 1961 to 2004 but, since the market-oriented economic transition started in the late 1970s, its horse population has declined significantly and steadily, from 11.50 million in 1978 to only 3.47 million in 2018. While there are minimal studies on China’s equine industries in the literature, this paper reviews the development of China’s equine industries since 1949, identifies major factors contributing to the steady decline in its horse population since 1978, and discusses the challenges and opportunities for the development of China’s equine industries. Empirical results suggest that the changes in China’s horse population since 1949 have been closely associated with its agricultural and rural development and policies, and the key factors contributing to the declining horse population since 1978 include agricultural mechanization, a steady decrease of the agricultural sector’s share in the GDP, urbanization, improvement in rural transportation with more motor vehicles, and decreased land availability for and the lack of economic returns from horses. Together, such factors may continue to reduce China’s horse population, but, on the other hand, the rapid development in the tourism, recreation, and sport sectors may provide potential growth opportunities. Moreover, China’s horse population is likely to be more concentrated in Inner Mongolia, Xinjiang, Tibet, and the western Sichuan province, which have relatively low population density and high proportion of ethnic population with the tradition of horses in their cultural, religious, sport, and economic activities. At the same time, equestrian events and activities are expected to continue to increase at significant rates in and around large Chinese cities.
Sustainability and Real Estate Crowdfunding: Success Factors
Authors: Borrero-Domínguez Cinta , Cordón-Lagares Encarnación , Hernández-Garrido Rocío
Published: June 2020

The objective of this paper is to analyze the factors influencing the success of real estate crowdfunding projects in Spain. This type of crowdfunding invests in real estate assets. We analyzed 60 projects published on the Housers platform, a kind of participative platform that uses the lending and equity crowdfunding modalities. These projects have involved around 36,623 investment decisions and have raised a total amount of almost 26 million euros. The empirical analysis is based on ordinary least squares and negative binomial regression. Our main findings reveal that success differs depending on the type of project; in fact, buy-to-sell projects are less successful than development loan projects. In addition, while total return has a positive impact on project success, in the case of risk level and project term, the impact is negative.
Formation Factors and Effects on Common Property Resource Conservation of Community Farms
Authors: Kitano Shinichi
Published: June 2020

In recent decades, there has been a global debate over who should manage common property resources (CPRs) related to agriculture. Because rational and efficient farmers only work farmland with good conditions or leave for other industries, in areas where production conditions are poor, local resources that were once collectively maintained are no longer managed. The Japanese government has positioned community farms (CFs) as an important player in local agriculture and has been striving to develop them. This study clarifies whether the formation and development of these CFs are functioning effectively for the conservation of local resources. Specifically, we use the propensity score matching method to measure the average treatment effect of CF formation and development on CPR conservation activities and the prevention of cultivation abandonment. In particular, this study tests the hypothesis that farmers are reluctant to develop CFs extensively because their effects on CPR conservation are uncertain. The results show that at the early stage, the formation of CFs has a significantly positive effect on the promotion of CPR conservation, but its wide-area development is counterproductive to CPR management, suggesting that resourceful support is needed according to local conditions.
Recent Development in Earth-Abundant Kesterite Materials and Their Applications
Authors: Nazligul Ahmet Sencer , Wang Mingqing , Choy Kwang Leong
Published: June 2020

Kesterite Cu2ZnSnS4 (CZTS) has attracted attention as an earth-abundant alternative to commercially successful CIGS solar cells. CZTS exhibits decent optoelectrical properties while having excellent stability on top of being an earth-abundant, low-cost and non-toxic material. Therefore, in recent years, there has been a significant research effort to develop CZTS-based devices. The efficiency of CZTS solar cells reached 12.6% in 2013, and this was a remarkable achievement at the time. However, the efficiency of these devices has been stagnant since then while emerging technologies, most notably perovskite solar cells, keep breaking record after record. Currently, CZTS research focuses on discovering the secrets of material properties that hinder the efficiency of CZTS solar cells while branching out to develop alternative applications for this material. In this review, we summarize the interesting properties of CZTS as well as its promising applications, which include thin-film solar cells, charge-transfer layers in perovskite solar cells, and photoelectrochemical water splitting while briefly commenting on its other possible applications.
The Mediating Role of Affects between Mind-Wandering and Happiness
Authors: Salavera Carlos , Usán Pablo
Published: June 2020

The aim of this study was to assess the mediating role of affects between mind-wandering and happiness. The study was conducted with a sample comprising 270 university students—133 men (49.26%) and 137 women (50.74%)—who filled out the Mind-Wandering Questionnaire (MWQ), the Positive and Negative Affect Questionnaire (PANAS), and the SHS subjective happiness scale. Mind-wandering was found to be negatively correlated with happiness and positive effects. Higher mind-wandering-related scores went hand in hand with scores related to both lower happiness and positive affects. Approximately half the participants yielded low mind-wandering and negative affect scores and above-average happiness and positive affects scores. In addition, one in four scored above average in terms of mind-wandering and low in terms of happiness and positive effects. Finally, the mediating role played by affects was examined. It can be concluded that although in principle mind-wandering has no direct effect on happiness, some influence can be attested when affects, both positive and negative, are taken into consideration.
Influence of Verbal Behavior Training on Performance for Sustainable Development in Childhood and Early Adolescence
Authors: Maldonado Miguel A. , Alós Francisco J. , Povedano-Díaz Amapola
Published: June 2020

The effective teaching of language is an aspect of special relevance regarding the good adjustment of children in contexts such as school, family, or community. This article performs an experimental procedure to check which language teaching methodology is most effective in a sample of children. The objective was to analyze the influence of training, Condition 1 (pure tacts more intraverbal) or Condition 2 (pure tacts more impure tacts), on emergence of two tests involving impure tacts (AB-C, AB-D) and four new complex intraverbals (BC-D, BD-C) for each of two sets of stimuli (Set 1 and Set 2). The sample comprised 54 children aged between 6 and 12 years, divided into two groups of different experimental conditions. The results revealed statistically significant differences in performance on the tests of impure tacts and complex intraverbal, obtaining highly effective results in Condition 2. This teaching method using compound stimuli (impure tacts) clearly favors the expansion of language. The practical implications of this work can be more effective language teaching methodologies implemented that favor the good psychosocial adjustment of children in contexts such as family, school, or the community in general.