bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Lethal Bronzing Disease in Cabbage Palms (Sabal palmetto) Using a Low-Cost Electronic Nose
Authors: Oates Martin J. , Abu-Khalaf Nawaf , Molina-Cabrera Carlos , Ruiz-Canales Antonio , Ramos Jose , Bahder Brian W.
Published: November 2020

Lethal Bronzing Disease (LB) is a disease of palms caused by the 16SrIV-D phytoplasma. A low-cost electronic nose (eNose) prototype was trialed for its detection. It includes an array of eight Taguchi-type (MQ) sensors (MQ135, MQ2, MQ3, MQ4, MQ5, MQ9, MQ7, and MQ8) controlled by an Arduino NANO® microcontroller, using heater voltages that vary sinusoidally over a 2.5 min cycle. Samples of uninfected, early symptomatic, moderate symptomatic, and late symptomatic infected palm leaves of the cabbage palm were processed and analyzed. MQ sensor responses were subjected to a 256 element discrete Fourier transform (DFT), and harmonic component amplitudes were reviewed by principal component analysis (PCA). The experiment was repeated three times, each showing clear evidence of differences in sensor responses between the samples of uninfected leaves and those in the early stages of infection. Within each experiment, four groups of responses were identified, demonstrating the ability of the unit to repeatedly distinguish healthy leaves from diseased ones; however, detection of the severity of infection has not been demonstrated. By selecting appropriate coefficients (here demonstrated with plots of MQ5 Cos1 vs. MQ8 Sin3), it should be possible to build a ruleset classifier to identify healthy and unhealthy samples.
Fatal Status Epilepticus in Dravet Syndrome
Authors: De Liso Paola , Pironi Virginia , Mastrangelo Massimo , Battaglia Domenica , Craiu Dana , Trivisano Marina , Specchio Nicola , Nabbout Rima , Vigevano Federico
Published: November 2020

Dravet Syndrome (DS) is burdened by high epilepsy-related premature mortality due to status epilepticus (SE). We surveyed centres within Europe through the Dravet Italia Onlus and EpiCARE network (European Reference Network for Rare and Complex Epilepsies). We collated responses on seven DS SCN1A+ patients who died following refractory SE (mean age 6.9 year, range 1.3–23.4 year); six were on valproate, clobazam, and stiripentol. All patients had previous SE. Fatal SE was always triggered by fever: either respiratory infection or one case of hexavalent vaccination. SE lasted between 80 min and 9 h and all patients received IV benzodiazepines. Four patients died during or within hours of SE; in three patients, SE was followed by coma with death occurring after 13–60 days. Our survey supports the hypothesis that unresponsive fever is a core characteristic feature of acute encephalopathy. We highlight the need for management protocols for prolonged seizures and SE in DS.
A Dynamic Model Incorporated with Delay Estimation and Variable Selection for Control of SCR De-NOx Process
Authors: Dong Ze , Li Ling , Yan Laiqing , Sun Ming , Li Jinsong
Published: November 2020

In order to control NH3 injection for the selective catalytic reduction of nitrogen oxide (NOx) denitration (SCR de-NOx) process, a model that can accurately and quickly predict outlet NOx emissions is required. This paper presents a dynamic kernel partial least squares (KPLS) model incorporated with delay estimation and variable selection for outlet NOx emission and investigated control strategy for NH3 injection. First, k-nearest neighbor mutual information (KNN_MI) was used for delay estimation, and the effect of historical data lengths on KNN_MI was taken into account. Bidirectional search based on the change rate of KNN_MI (KNN_MI_CR) was used for variable selection. Delay–time difference update algorithm and feedback correction strategy were proposed. Second, the NH3 injection compensator (NIC) and the outlet NOx emission model constituted a correction controller. Then, its output and the output of the existing controller are added up to suitable NH3 injection. Finally, the KNN_MI_CR method was compared with different algorithms by benchmark dataset. The field data results showed that the KNN_MI_CR method could improve model accuracy for reconstructed samples. The final model can predict outlet NOx emissions in different operating states accurately. The control result not only meets the NOx emissions standard (50 mg/m3) but also keeps high de-NOx efficiency (80%). NH3 injection and NH3 escape are reduced by 11% and 39%.
Perlecan Facilitates Neuronal Nitric Oxide Synthase Delocalization in Denervation-Induced Muscle Atrophy
Authors: Nakada Satoshi , Yamashita Yuri , Machida Shuichi , Miyagoe-Suzuki Yuko , Arikawa-Hirasawa Eri
Published: November 2020

Perlecan is an extracellular matrix molecule anchored to the sarcolemma by a dystrophin–glycoprotein complex. Perlecan-deficient mice are tolerant to muscle atrophy, suggesting that perlecan negatively regulates mechanical stress-dependent skeletal muscle mass. Delocalization of neuronal nitric oxide synthase (nNOS) from the sarcolemma to the cytosol triggers protein degradation, thereby initiating skeletal muscle atrophy. We hypothesized that perlecan regulates nNOS delocalization and activates protein degradation during this process. To determine the role of perlecan in nNOS-mediated mechanotransduction, we used sciatic nerve transection as a denervation model of gastrocnemius muscles. Gastrocnemius muscle atrophy was significantly lower in perinatal lethality-rescued perlecan-knockout (Hspg2−/−-Tg) mice than controls (WT-Tg) on days 4 and 14 following surgery. Immunofluorescence microscopy showed that cell membrane nNOS expression was reduced by denervation in WT-Tg mice, with marginal effects in Hspg2−/−-Tg mice. Moreover, levels of atrophy-related proteins—i.e., FoxO1a, FoxO3a, atrogin-1, and Lys48-polyubiquitinated proteins—increased in the denervated muscles of WT-Tg mice but not in Hspg2−/−-Tg mice. These findings suggest that during denervation, perlecan promotes nNOS delocalization from the membrane and stimulates protein degradation and muscle atrophy by activating FoxO signaling and the ubiquitin–proteasome system.
Risk and Resilience Factors Impacting Treatment Compliance and Functional Impairment among Adolescents Participating in an Outpatient Interdisciplinary Pediatric Chronic Pain Management Program
Authors: Aggarwal Dutta Richa , Salamon Katherine S.
Published: November 2020

Recurrent pain is a common experience in childhood and adolescence and can result in significant disability in youth, including poor quality of life, school absences, and reduced social activities. Evidence has linked adolescent risk and resilience factors with treatment outcomes. However, less research has focused on examining risk and resilience factors that may influence or predict adolescents’ compliance to treatment within an interdisciplinary pediatric chronic pain management program. Participants included 64 adolescents (M = 15.00 ± 1.69 years); 85.9% female, 84.4% Caucasian who presented to an initial evaluation in an interdisciplinary pediatric pain management program with their caregiver. Youth completed a series of questionnaires at the initial evaluation targeting pain acceptance, self-efficacy, pain catastrophizing, parental responses, pain intensity, and functional disability. Treatment compliance was measured at 3 and 6 months post-intake. Findings indicated that higher levels of adolescent-reported self-efficacy predict decreased treatment session attendance, whereas lower levels of acceptance and parental encouragement/monitoring of symptoms predict increased treatment compliance overall. Several adolescent-reported risk factors were associated with increased functional impairment among this sample. Results highlight the unique importance of risk and resilience factors within the developmental context of adolescence, while also emphasizing the need for further investigation of other relevant influences towards treatment compliance and functional impairment.
Modified Constraint-Induced Movement Therapy at Home—Is It Possible? Families and Children’s Experience
Authors: Palomo-Carrión Rocío , Romay-Barrero Helena , Romero-Galisteo Rita-Pilar , Pinero-Pinto Elena , López-Muñoz Purificación , Martínez-Galán Inés
Published: November 2020

Modified constraint-induced movement therapy (mCIMT) is efficient at improving upper limb non-use. The experiences of families and children with mCIMT could allow researchers to understand how it influences their day-to-day life and to improve the function of the affected upper limb without altering family life and avoiding frustration. In this qualitative study, we aimed to collect the experiences of parents and their children (aged 4–8 years) who did mCIMT at home regarding the application of low-intensity modified constraint-induced movement therapy to improve the affected upper limb functionality in infantile hemiplegia with moderate manual ability. Individual semi-structured interviews were performed to obtain insights into their experience with mCIMT. The experiences of parents and children were described in thematic sections. Eight children with hemiplegia (six years, standard deviation, SD: 1.77) and their parents were asked about their experiences after applying 50 h of mCIMT at home. Three main themes emerged from the children’s interview data: (1) the experience of wearing the containment in the modified constraint-induced movement therapy (CIMT) intervention, (2) the reaction to performing the therapy at home with his/her family, and (3) learning of the affected upper limb. In the parents’ interview data, there were two main themes: (1) the difficulty of executing an intensive therapy protocol (mCIMT: 50 h) at home and (2) the feeling of not wanting to finish the intervention. The experiences of the parents and their children regarding mCIMT allowed us to understand the facilitators and barriers that affect the execution of mCIMT at home, and this understanding allows us to improve its future application.
Is It Possible for Children in Duchenne Muscular Dystrophy to Preserve Cardiac Function with Medical Assistance?
Authors: Kim Han Geul , Eun Lucy Youngmin , Park Han Ki
Published: November 2020

In patients with Duchenne muscular dystrophy (DMD), death secondary to cardiac or respiratory failure typically occurs in the second or third decade without treatment. Although cardiac dysfunction is treated with standard heart-failure strategies, it remains insufficient in DMD children. The purpose of this study was to evaluate the efficiency of cardiac medication and noninvasive ventilator support in DMD cardiomyopathy children with analyzing echocardiographic data. Forty-eight DMD children patients were included and divided into 2 groups by left ventricular (LV) ejection fraction (EF) at the time of initial treatment. Group 1: LV EF ≥ 45% and Group 2: LV EF < 45%. p-values were calculated using a Linear mixed model to estimate the association between cardiac medications and echocardiographic measurements. Before and after cardiac medications, the change values were significantly different in interventricular septal thickness at end diastole (IVSd), interventricular septal thickness at end systole (IVSs), left ventricular internal diameter end systole (LVIDs), left ventricular posterior wall thickness end diastole (LVPWd), ejection fraction (EF), fractional shortening (FS), deceleration time (DT), DT slope, Lat A’ and Lat E/E’ (p < 0.05). Group 2 patients revealed to take more kinds of cardiac medications than Group 1 (p < 0.05) including ACEIs, beta-blocker, and inotropics, then LV EF was better preserved in Group 2 than Group 1. It is certainly helpful to take individualized medical combination therapy including inotropic agents for cardiomyopathy in DMD children patients with EF < 45%.
Climate Change and Its Possible Impact in Groundwater Resource of the Kankai River Basin, East Nepal Himalaya
Authors: Silwal Champak Babu , Pathak Dinesh , Adhikari Drona , Adhikari Tirtha Raj
Published: November 2020

Increasing evidence of changing climate patterns is being observed, and the impact of this change on groundwater has a direct impact on the livelihood and economy of the region. The research focuses on the impacts of global temperature increase and changing precipitation on the groundwater resources of part of the Himalayan river system. The spatial and temporal variations of the hydro-meteorological data of the Kankai River Basin in East Nepal were analyzed using non-parametric Mann–Kendall tests and Sen’s Slope methods, whereas CanESM2 was used to predict the future precipitation scenarios, and an attempt has been made to evaluate the possible impacts on groundwater systems in the region. The temperature shows a significant warming trend (0.14–0.64 °C/decade); however, the precipitation trends suggest remarkable variation mostly at higher elevation. The average annual precipitation suggests a decrease of 1.82 mm/year and a similar decrement has been projected for the future. The groundwater in the region has been influenced by the changing climate and the condition may further be exaggerated by reduced recharge and increased evapotranspiration. This understanding of the impacts and climate scenarios will help the planners with better adaptation strategies, plans, and programs for a better society.
Angular and Spectral Bandwidth Considerations in BRDF Measurements of Interference- and Diffraction-Based Coatings
Authors: Ferrero Alejandro , Campos Joaquín
Published: November 2020

The Bidirectional Reflectance Distribution Function (BRDF) of iridescent (or goniochromatic) surfaces may vary notably with both spectral and angular variables, and, therefore, finite spectral bandwidth and collection solid angles inherent to any measuring instrument introduce a deviation from the correct value. Experimental data of highly goniochromatic samples are used to analyse their impact on measurement uncertainty. The results indicate that it is advisable to standardize spectral and angular bandwidths because the systematic error is not negligible for typical measuring systems. The 95th percentile of the error distribution of the measurement of the BRDF due to these finite bandwidths, and also the 95th percentile of the calculated resulting color differences, are used as criteria to establish recommended values of spectral and angular bandwidths. The impact of the bandwidth is more critical in the measurement of the BRDF of diffraction-based than of interference-based coatings.
Colored Paints Containing NIR-Reflective Pigments Exposed to Accelerated Ultraviolet Radiation Aging with Possible Application as Roof Coatings
Authors: Rossi Stefano , Lindmark Hampus , Fedel Michele
Published: November 2020

This study aims to evaluate the difference in thermal behavior among paints with the presence of traditional and NIR pigments by means of a simple and cheap laboratory-scale test. Considering these goals, the thermal and esthetical properties of two different cool coatings were assessed, highlighting their positive and limited aspects. Two different complex near-infrared inorganic reflective (NIR) pigments with yellow and black respectably colors were mixed in an acrylic waterborne copolymer binder. The paint formulations were applied on steel panels. The thermal performance of the coatings was investigated in the NIR-region of the light spectrum by exposing the samples to an IR-lamp. The outer and inner surface temperatures of the painted panels were recorded using thermocouples and an IR camera. The samples were aged by artificial UV-B light exposure. Color and specular gloss changes at different exposure times were evaluated. The behavior of the cool coatings was compared with that of conventional coatings with similar color characteristics. The black cool coating achieved a maximum temperature decrease, compared to the conventional black one, of approximately 12 °C. The stability for the cool coatings was very similar to that of the conventional coating, indicating that black pigment could be a potential candidate for cool-coating applications. The yellow cool coatings did not show a significant decrease in temperature compared to the conventional paint. The gloss and color changes resulted as influenced by the types and amount of pigments.
Degradation Resistance and In Vitro Cytocompatibility of Iron-Containing Coatings Developed on WE43 Magnesium Alloy by Micro-Arc Oxidation
Authors: Zhang Rongfa , Zhang Zeyu , Zhu Yuanyuan , Zhao Rongfang , Zhang Shufang , Shi Xiaoting , Li Guoqiang , Chen Zhiyong , Zhao Ying
Published: November 2020

Iron (Fe) is an important trace element for life and plays vital functions in maintaining human health. In order to simultaneously endow magnesium alloy with good degradation resistance, improved cytocompatibility, and the proper Fe amount for the body accompanied with degradation of Mg alloy, Fe-containing ceramic coatings were fabricated on WE43 Mg alloy by micro-arc oxidation (MAO) in a nearly neutral pH solution with added 0, 6, 12, and 18 g/L ferric sodium ethylenediaminetetraacetate (NaFeY). The results show that compared with the bare Mg alloy, the MAO samples with developed Fe-containing ceramic coatings significantly improve the degradation resistance and in vitro cytocompatibility. Fe in anodic coatings is mainly present as Fe2O3. The increased NaFeY concentration favorably contributes to the enhancement of Fe content but is harmful to the degradation resistance of MAO coatings. Our study reveals that the developed Fe-containing MAO coating on Mg alloy exhibits potential in clinical applications.
Feasibility of Four Interventions to Improve Treatment Adherence in Migrants Living with HIV in The Netherlands
Authors: Been Sabrina K. , van de Vijver David A.M.C. , Smit Jannigje , Bassant Nadine , Pogány Katalin , Stutterheim Sarah E. , Verbon Annelies
Published: November 2020

We evaluated the feasibility and efficacy of four existing interventions to improve adherence to them in migrants living with HIV (MLWH): directly administered antiretroviral therapy (DAART), group medical appointments (GMA), early detection and treatment of psychological distress, and peer support by trained MLWH. At baseline and after the interventions, socio-demographic characteristics, psychosocial variables, and data on HIV treatment adherence were collected. The two questionnaires were completed by 234/301 (78%) MLWH included at baseline. Detectable HIV RNA decreased (from 10.3 to 6.8%) as did internalized HIV-related stigma (from 15 to 14 points), and self-reported adherence increased (between 5.5 and 8.3%). DAART and GMA were not feasible interventions. Screening of psychological distress was feasible; however, follow-up diagnostic screening and linkage to psychiatric services were not. Peer support for and by MLWH was feasible. Within this small intervention group, results on HIV RNA < 400 copies/mL (decrease of 23.6%) and outpatient clinic attendance (up to 20.4% kept more appointments) were promising.
A Discretization Approach for the Nonlinear Fractional Logistic Equation
Authors: Izadi Mohammad , Srivastava Hari
Published: November 2020

The present study aimed to develop and investigate the local discontinuous Galerkin method for the numerical solution of the fractional logistic differential equation, occurring in many biological and social science phenomena. The fractional derivative is described in the sense of Liouville-Caputo. Using the upwind numerical fluxes, the numerical stability of the method is proved in the L∞ norm. With the aid of the shifted Legendre polynomials, the weak form is reduced into a system of the algebraic equations to be solved in each subinterval. Furthermore, to handle the nonlinear term, the technique of product approximation is utilized. The utility of the present discretization technique and some well-known standard schemes is checked through numerical calculations on a range of linear and nonlinear problems with analytical solutions.
Thermodynamic Formalism in Neuronal Dynamics and Spike Train Statistics
Authors: Cofré Rodrigo , Maldonado Cesar , Cessac Bruno
Published: November 2020

The Thermodynamic Formalism provides a rigorous mathematical framework for studying quantitative and qualitative aspects of dynamical systems. At its core, there is a variational principle that corresponds, in its simplest form, to the Maximum Entropy principle. It is used as a statistical inference procedure to represent, by specific probability measures (Gibbs measures), the collective behaviour of complex systems. This framework has found applications in different domains of science. In particular, it has been fruitful and influential in neurosciences. In this article, we review how the Thermodynamic Formalism can be exploited in the field of theoretical neuroscience, as a conceptual and operational tool, in order to link the dynamics of interacting neurons and the statistics of action potentials from either experimental data or mathematical models. We comment on perspectives and open problems in theoretical neuroscience that could be addressed within this formalism.
Does Deep Learning Work Well for Categorical Datasets with Mainly Nominal Attributes?
Authors: Hayashi Yoichi
Published: November 2020

Given the complexity of real-world datasets, it is difficult to present data structures using existing deep learning (DL) models. Most research to date has concentrated on datasets with only one type of attribute: categorical or numerical. Categorical data are common in datasets such as the German (-categorical) credit scoring dataset, which contains numerical, ordinal, and nominal attributes. The heterogeneous structure of this dataset makes very high accuracy difficult to achieve. DL-based methods have achieved high accuracy (99.68%) for the Wisconsin Breast Cancer Dataset, whereas DL-inspired methods have achieved high accuracy (97.39%) for the Australian credit dataset. However, to our knowledge, no such method has been proposed to classify the German credit dataset. This study aimed to provide new insights into the reasons why DL-based and DL-inspired classifiers do not work well for categorical datasets, mainly consisting of nominal attributes. We also discuss the problems associated with using nominal attributes to design high-performance classifiers. Considering the expanded utility of DL, this study's findings should aid in the development of a new type of DL that can handle categorical datasets consisting of mainly nominal attributes, which are commonly used in risk evaluation, finance, banking, and marketing.
Hybrid Power System Optimization in Mission-Critical Communication
Authors: Leva Sonia , Grimaccia Francesco , Rozzi Marco , Mascherpa Matteo
Published: November 2020

One of the common problems faced by Telecommunication (TLC) companies is the lack of power supply, usually for those appliances with scarce chances of grid connection often placed in remote zones. This issue is more and more critical if the radio network has the specific task of guaranteeing the so-called “mission-critical communications”. This manuscript aims to propose and assess a viable solution to optimize the power supply and maintenance operations required to assure the proper functionality in such critical and remote sites. In particular, the main goals are defining a method to select the critical sites in an extensive and composite radio system and designing the hybrid power system in a way to improve the service availability and technical-economic benefits of the whole mission-critical TLC system. Finally, the proposed method and related procedures are tested and validated in a real scenario.
Reverse Conduction Loss Minimization in GaN‑Based PMSM Drive
Authors: Skarolek Pavel , Frolov Filipp , Lipcak Ondrej , Lettl Jiri
Published: November 2020

Gallium nitride (GaN) devices are becoming more popular in power semiconductor converters. Due to the absence of the freewheeling substrate diode, the reverse conduction region is used in GaN transistors to conduct the freewheeling current. However, the voltage drop across the device in the reverse conduction mode is relatively high, causing additional power losses. These losses can be optimized by adequately adjusting the dead-time issued by the microcontroller. The dead-time loss minimization strategies presented in the literature have the common disadvantage that either additional hardware or specific converter data are needed for their proper operation. Therefore, this paper’s motivation is to present a novel dead-time loss minimization method for GaN-based high-frequency switching converters for electric drives that does not impose additional requirements on the hardware design phase and converter data acquisition. The method is based on optimizing the current controllers’ output with a simple perturb-and-observe tracker. The experimental results show that the proposed approach can minimize the dead-time losses over the whole drive’s operating range at the cost of only a moderate increase in software complexity.
Two Step Random Access Latency Improvement in Congested beyond 5G Networks
Authors: Agiwal Mamta , Maheshwari Mukesh Kumar , Toor Waqas Tariq
Published: November 2020

It has been recently proposed to enhance the performance of random access procedure (RAP) by downsizing the current four step RAP (4s-RAP) to two step RAP (2s-RAP) in order to address ultra reliable low latency communications (URLLC) in 5G and beyond 5G wireless networks. 2s-RAP reduces latency and signaling overhead by manifesting only one round trip between gNB (5G base station) and the UE (user equipment). However, the low latency goal of 2s-RAP is challenged by the increase in the number of UEs in the future wireless networks. Numerous UEs competing for limited random access resources would result in frequent collisions followed by multiple random access reattempts, resulting in increased delay. In this paper, we propose novel algorithms to improve the performance of 2s-RAP in a congested environment. In the proposed algorithms, the UEs can perform RAP reattempts in either 2s-RAP or 4s-RAP based on the channel conditions such that the chances of RAP failure due to poor channels are reduced. They can also transit to 4s-RAP from the initially selected 2s-RAP in order to alleviate the congestion in 2s-RAP. The proposed algorithms are probabilistically analyzed based on collision probabilities and success rates. We employ our derived mathematical equations, as well as carry out simulation evaluations, to present the performance results effectively.
Design, Valuation and Comparison of Demand Response Strategies for Congestion Management
Authors: Agbonaye Osaru , Keatley Patrick , Huang Ye , Bani Mustafa Motasem , Hewitt Neil
Published: November 2020

Decarbonisation of heat and transport will cause congestion issues in distribution networks. To avoid expensive network investments, demand flexibility is necessary to move loads from peak to off-peak periods. We provide a method and metric for assessing and selecting the optimal demand response strategy for a given network congestion scenario and applied it to a case study network in Coleraine, Northern Ireland. We proposed a Price Approximation/Mean Grouping strategy to deal with the issue of congestions occurring at the lowest-price period in real-time pricing schemes. The Mean Grouping strategy increased the average lowest-price hours from 1.32 to 3.76. We show that a three-cluster tariff is effective in solving medium congestion issues in Northern Ireland and could save consumers an average of £117/year on their heating bill. However, for networks with low headroom suffering from serious congestion issues, a smart control strategy is needed.
Biogas Upgrading Approaches with Special Focus on Siloxane Removal—A Review
Authors: Nyamukamba Pardon , Mukumba Patrick , Chikukwa Evernice Shelter , Makaka Golden
Published: November 2020

Biogas, a product of anaerobic digestion process that consists mainly of methane and carbon dioxide is a suitable alternative fuel if unwanted impurities are removed as they have a negative impact on the equipment. The most significant technologically troublesome trace compounds that must be removed are siloxanes since they are converted into silica on gas surface engines and turbines resulting in equipment damage. The quality of the gas is certainly improved by reducing the amount of impurities and the end use determines the extent of biogas cleaning needed. The major aim of this study was to compile information that can assist researchers or even designers in selecting a suitable technology to remove siloxanes. Siloxane removal definitely can be achieved using different methods and the effectiveness of each method relies on careful consideration of the characteristics of both biogas and siloxane, as well as the technological aspects of the method. Herein, we review on different cleaning techniques for siloxanes in raw biogas, the negative effects they have, their levels and technologies to reduce their concentrations. This review also incorporates the sources of the siloxanes, the progress to date on their removal and possible ways of regenerating adsorbents. The reviewed literature suggests that biogas upgrading technology should be promoted and encouraged especially in siloxane removal as it has detrimental effects on engines. The parameters and effectiveness of adsorption processes are discussed, and individual adsorbents are compared.
A Parametric Study of Wave Energy Converter Layouts in Real Wave Models
Authors: Amini Erfan , Golbaz Danial , Amini Fereidoun , Majidi Nezhad Meysam , Neshat Mehdi , Astiaso Garcia Davide
Published: November 2020

Ocean wave energy is a broadly accessible renewable energy source; however, it is not fully developed. Further studies on wave energy converter (WEC) technologies are required in order to achieve more commercial developments. In this study, four CETO6 spherical WEC arrangements have been investigated, in which a fully submerged spherical converter is modelled. The numerical model is applied using linear potential theory, frequency-domain analysis, and irregular wave scenario. We investigate a parametric study of the distance influence between WECs and the effect of rotation regarding significant wave direction in each arrangement compared to the pre-defined layout. Moreover, we perform a numerical landscape analysis using a grid search technique to validate the best-found power output of the layout in real wave models of four locations on the southern Australian coast. The results specify the prominent role of the distance between WECs, along with the relative angle of the layout to dominant wave direction, in harnessing more power from the waves. Furthermore, it is observed that a rise in the number of WECs contributed to an increase in the optimum distance between converters. Consequently, the maximum exploited power from each buoy array has been found, indicating the optimum values of the distance between buoys in different real wave scenarios and the relative angle of the designed layout with respect to the dominant in-site wave direction.
The Effect of CO2 Concentration on Children’s Well-Being during the Process of Learning
Authors: Bogdanovica Snezana , Zemitis Jurgis , Bogdanovics Raimonds
Published: November 2020

There are more than 200 thousand pupils in Latvia. Most of them are still learning in non-renovated classrooms without proper mechanical ventilation. The classrooms are often ventilated only during the breaks by opening windows. This can lead to increased CO2 levels and reduced mental performance. To test how CO2 concentration in classrooms influences student attention level and their ability to perform mental tasks, the students had to complete a short test at the start and the end of the class. At the same time CO2 concentration, temperature and relative humidity were logged. In addition, an anonymous survey on how the pupils felt regarding the overall indoor environmental quality (IEQ) in the classroom, their thermal sensation, are they fatigued, any difficulty concentrating and if they have headaches during the lesson performed. The measurements were performed in a Secondary School in Daugavpils, Latvia. The analysis of results shows that existing 10 min breaks are not enough to fully ventilate the classroom, and they must be increased to at least 15 min. At the same time, 30 min breaks can be reduced to 20 min. The correlation between CO2 concentration and test results of pupils’ performance test results is noticeable but not definitive. It indicates that at increased CO2 levels the performance lowers—when the concentration of CO2 corresponds only to the Category 3 norm, the lowest results are achieved while the best results are when the CO2 concentration level corresponds to Category 1. To improve the study, observations of CO2 concentrations must be extended throughout the school year, as well as measurements in other classrooms in the school should be made.
Composite Membranes Using Hydrophilized Porous Substrates for Hydrogen Based Energy Conversion
Authors: Lim Seohee , Park Jin-Soo
Published: November 2020

Poly(tetrafluoroethylene) (PTFE) porous substrate-reinforced composite membranes for energy conversion technologies are prepared and characterized. In particular, we develop a new hydrophilic treatment method by in-situ biomimetic silicification for PTFE substrates having high porosity (60–80%) since it is difficult to impregnate ionomer into strongly hydrophobic PTFE porous substrates for the preparation of composite membranes. The thinner substrate having ~5 μm treated by the gallic acid/(3-trimethoxysilylpropyl)diethylenetriamine solution with the incubation time of 30 min shows the best hydrophilic treatment result in terms of contact angle. In addition, the composite membranes using the porous substrates show the highest proton conductivity and the lowest water uptake and swelling ratio. Membrane-electrode assemblies (MEAs) using the composite membranes (thinner and lower proton conductivity) and Nafion 212 (thicker and higher proton conductivity), which have similar areal resistance, are compared in I–V polarization curves. The I–V polarization curves of two MEAs in activation and Ohmic region are very identical. However, higher mass transport limitation is observed for Nafion 212 since the composite membrane with less thickness than Nafion 212 would result in higher back diffusion of water and mitigate cathode flooding.
Numerical Modeling on the Fracturing and Energy Evolution of Large Deep Underground Openings Subjected to Dynamic Disturbance
Authors: Yang Chun , Zhou Keping , Li Zhichao , Xiong Xin , Lin Yun , Luo Zengwu
Published: November 2020

The exploitation of deep resources is necessary for human development. At the same time, high-stress environments that are deep underground bring about great challenges vis-à-vis resource exploitation. A large deep opening is sensitive to high ground stress, and is easily influenced by external interference, which can lead to geologically hazardous occurrences. To investigate the evolution of fracturing and energy in large, deep stopes subjected to dynamic loads, we established a numerical model of a stope in the Gaofeng mine. Using ANSYS/LS-DYNA software, we implemented an implicit solution to initial static stress and an explicit solution for dynamic analysis. Based on our numerical results, we obtained the fracture behavior and energy evolution under coupled static and dynamic loads. To determine the response of ground pressure to mining activity, a 24-channel microseismic monitoring system was designed for the Gaofeng mine based on the numerical analysis.
Electric Rickshaw Charging Stations as Distributed Energy Storages for Integrating Intermittent Renewable Energy Sources: A Case of Bangladesh
Authors: Hasan A.S.M. Mominul
Published: November 2020

This exploratory research outlines an opportunity for increasing renewable energy share in Bangladesh by using electric rickshaws (e-rickshaws) as a catalyst. The overall objective of this research is to show how to utilise an existing opportunity, such as e-rickshaws, as energy storage options for integrating renewable energy sources. It proposes a grid-connected local energy system considering a battery swapping and charging station (BSCS) for e-rickshaws as a community battery energy storage (CBESS). This system was simulated using the HOMER Pro software. The simulation results show that such systems can help communities significantly reduce their dependency on the national grid by integrating solar PV locally. The proposed BSCS also shows an opportunity for battery demand reduction and circular battery management for electric rickshaws. The research also discusses the economies of scale of the proposed method in Bangladesh, and pathways for implementing microgrids and smart energy systems. The innovative concepts presented in this research will start a policy-level dialogue in Bangladesh for utilising local opportunities to find an alternative energy storage solution and provide momentum to the researchers for further studies.
Technological and Operational Aspects That Limit Small Wind Turbines Performance
Authors: Torres-Madroñero José Luis , Alvarez-Montoya Joham , Restrepo-Montoya Daniel , Tamayo-Avendaño Jorge Mario , Nieto-Londoño César , Sierra-Pérez Julián
Published: November 2020

Small Wind Turbines (SWTs) are promissory for distributed generation using renewable energy sources; however, their deployment in a broad sense requires to address topics related to their cost-efficiency. This paper aims to survey recent developments about SWTs holistically, focusing on multidisciplinary aspects such as wind resource assessment, rotor aerodynamics, rotor manufacturing, control systems, and hybrid micro-grid integration. Wind resource produces inputs for the rotor’s aerodynamic design that, in turn, defines a blade shape that needs to be achieved by a manufacturing technique while ensuring structural integrity. A control system may account for the rotor’s aerodynamic performance interacting with an ever-varying wind resource. At the end, the concept of integration with other renewable source is justified, according to the inherent variability of wind generation. Several commercially available SWTs are compared to study how some of the previously mentioned aspects impact performance and Cost of Electricity (CoE). Understanding these topics in the whole view may permit to identify both tendencies and unexplored topics to continue expanding SWTs market.
Effect of Concentration on the Charge Storage Kinetics of Nanostructured MnO2 Thin-Film Supercapacitors Synthesized by the Hydrothermal Method
Authors: Teli Aviraj M. , Beknalkar Sonali A. , Pawar Sachin A. , Dubal Deepak P. , Dongale Tukaram D. , Patil Dipali S. , Patil Pramod S. , Shin Jae Cheol
Published: November 2020

In this study, amorphous manganese oxide (MnO2) nanostructured thin films were synthesized by a simple hydrothermal method. It is well known that the nanostructure plays a crucial role in energy storage applications. Herein, MnO2 nanostructures ranging from plates to flakes were synthesized without the use of any hard or soft templates. The 4+ oxidation state of Mn was confirmed by X-ray photoelectron spectroscopy. The MnO2 nanoflake structure has a specific surface area of 46 m2g−1, which provides it with an excellent rate capability and an exactly rectangular cyclic voltammogram (CV) curve. The MnO2 nanoflake electrode has a high specific capacitance of about 433 Fg−1, an energy density of 60 Whkg−1 at 0.5 mAcm−2, and an excellent cyclic stability of 95% over 1000 CV cycles in 1 M aq. Na2SO4. Kinetics analysis of the charge storage in the nanoflake MnO2 sample shows a 55.6% diffusion-controlled contribution and 44.4% capacitive-controlled contribution to the total current calculated at a scan rate of 100 mVs−1 from the CV curve.
Analysis and Implementation of Multilevel Inverter for Full Electric Aircraft Drives
Authors: Patel Vidhi , Buccella Concettina , Cecati Carlo
Published: November 2020

In modern aircrafts, hydraulic or pneumatic actuators have been already replaced with electric counterparts, but the advancement of the inverter and motor technology has made possible that the propulsion system can be powered by electrical sources. These high power requirements can not be efficiently fulfilled by using a typical two level converter; the multi-level converter represents a suitable solution for this application. This paper presents a cascaded H-bridge, a 9-level permanent magnet synchronous motor drive for full electric aircrafts. Harmonic analysis is presented considering different levels of a multi-level inverter. Simulation results and experimental validation with a test-rig confirms the accuracy of the proposed system.
Study on Heat Transfer Performance of Antifreeze-R134a Heat Exchanger (ARHEx)
Authors: Pang Liping , Luo Kun , Yu Shizhao , Ma Desheng , Zhao Miao , Mao Xiaodong
Published: November 2020

In this paper, the liquid cooling and vapor compression refrigeration system based on an Antifreeze-R134a Heat Exchanger (ARHEx) was applied to the thermal management system for high-power avionics in helicopters. The heat transfer performance of the ARHEx was studied. An experimental prototype of ARHEx was designed and established. A series of experiments was carried out with a ground experimental condition. A heat transfer formula for the antifreeze side in the ARHEx was obtained by means of the coefficient of Nusselt number with experimental analysis. The performance of heat transfer and pressure drop for the refrigerant side of the ARHEx was deduced for the given condition.
Influence of MOSFET Parasitic Capacitance on the Operation of Interleaved ZVS Boost Converters
Authors: Zimoch Piotr , Kasprzak Marcin , Kierepka Kamil
Published: November 2020

Interleaved zero-voltage switching boost converters have been known for over 20 years. However, the influence of parasitic capacitance of transistors has not been described. In this paper the converter is analyzed and the equation for voltage ratio is derived for any number of converter phases. First a general description of the topology, including main voltage and current waveforms, is provided. Subsequently the converter is analyzed and conditions for soft switching are derived. Next the analysis results are compared to measurements of an experimental converter setup. Discrepancies are identified and the influence of parasitic capacitance is analyzed. By considering the parasitic capacitance the difference between experimental and analytical results of voltage ratio is reduced from 0.2 to less than 0.05.
Hydrogen Fuel Cell Road Vehicles and Their Infrastructure: An Option towards an Environmentally Friendly Energy Transition
Authors: Bethoux Olivier
Published: November 2020

The latest pre-production vehicles on the market show that the major technical challenges posed by integrating a fuel cell system (FCS) within a vehicle—compactness, safety, autonomy, reliability, cold starting—have been met. Regarding the ongoing maturity of fuel cell systems dedicated to road transport, the present article examines the advances still needed to move from a functional but niche product to a mainstream consumer product. It seeks to address difficulties not covered by more traditional innovation approaches. At least in long-distance heavy-duty vehicles, fuel cell vehicles (FCVs) are going to play a key role in the path to zero-emissions in one or two decades. Hence the present study also addresses the structuring elements of the complete chain: the latter includes the production, storage and distribution of hydrogen. Green hydrogen appears to be one of the potential uses of renewable energies. The greener the electricity is, the greater the advantage for hydrogen since it permits to economically store large energy quantities on seasonal rhythms. Moreover, natural hydrogen might also become an economic reality pushing the fuel cell vehicle to be a competitive and environmentally friendly alternative to the battery electric vehicle. Based on its own functional benefits for on board systems, hydrogen in combination with the fuel cell will achieve a large-scale use of hydrogen in road transport, as soon as renewable energies become more widespread. Its market will expand from large driving range and heavy load vehicles.
Using Agent-Based Models to Generate Transformation Knowledge for the German Energiewende—Potentials and Challenges Derived from Four Case Studies
Authors: Holtz Georg , Schnülle Christian , Yadack Malcolm , Friege Jonas , Jensen Thorben , Thier Pablo , Viebahn Peter , Chappin Émile J. L.
Published: November 2020

The German Energiewende is a deliberate transformation of an established industrial economy towards a nearly CO2-free energy system accompanied by a phase out of nuclear energy. Its governance requires knowledge on how to steer the transition from the existing status quo to the target situation (transformation knowledge). The energy system is, however, a complex socio-technical system whose dynamics are influenced by behavioural and institutional aspects, which are badly represented by the dominant techno-economic scenario studies. In this paper, we therefore investigate and identify characteristics of model studies that make agent-based modelling supportive for the generation of transformation knowledge for the Energiewende. This is done by reflecting on the experiences gained from four different applications of agent-based models. In particular, we analyse whether the studies have improved our understanding of policies’ impacts on the energy system, whether the knowledge derived is useful for practitioners, how valid understanding derived by the studies is, and whether the insights can be used beyond the initial case-studies. We conclude that agent-based modelling has a high potential to generate transformation knowledge, but that the design of projects in which the models are developed and used is of major importance to reap this potential. Well-informed and goal-oriented stakeholder involvement and a strong collaboration between data collection and model development are crucial.
Optimization of a PV-Wind Hybrid Power Supply Structure with Electrochemical Storage Intended for Supplying a Load with Known Characteristics
Authors: Kasprzyk Leszek , Tomczewski Andrzej , Pietracho Robert , Mielcarek Agata , Nadolny Zbigniew , Tomczewski Krzysztof , Trzmiel Grzegorz , Alemany Juan
Published: November 2020

An important aspect of the off-grid utilization of hybrid generation systems is the integration of energy storage facilities into their structures, which allows for improved power supply reliability. However, this results in a significant increase in the cost of such systems. Therefore, it is justified to use optimization resulting in the minimization of the selected economic indicator taking into account the most important technical constraints. For this reason, this work proposes an algorithm to optimize the structure of a hybrid off-grid power distribution system (with electrochemical energy storage), designed to supply a load with known daily energy demand. The authors recommend genetic algorithm utilization as well as a modified criterion for evaluating the quality of solutions based on the Levelized Cost of Energy (LCOE) index. Several technical and economic analyses were presented, including unit costs, power distribution of the wind and solar sections, nominal battery capacity, SSSI index (System Self-Sufficiency Index), etc. The model of the system includes durability of the elements which have a significant impact on the periodic battery replacement. The tests were carried out for two types of loads and two types of electrochemical batteries (NMC—Lithium Nickel Manganese Cobalt Oxide; and PbO2—Lead-Acid Battery), taking into account the forecast of an increased lifetime of NMC type batteries and decreasing their price within five years. The proposed synthesis method of photovoltaic-wind (PV-wind) hybrid off-line systems leads to limiting the energy capacity of electrochemical storages. Based on the analyses, the authors proposed recommended methods to improve (reduce) the value of the criterion index (LCOE) for PV-wind off-grid systems while maintaining the assumed level of power supply reliability.