bluuebunny/crossref_metadata_2025 huggingface dataset:
Synapsin-Promoted Caveolin-1 Overexpression Maintains Mitochondrial Morphology and Function in PSAPP Alzheimer’s Disease Mice
Authors: Wang Shanshan , Ichinomiya Taiga , Terada Yuki , Wang Dongsheng , Patel Hemal H. , Head Brian P.
Published: September 2021

Mitochondrial dysfunction plays a pivotal role in the Alzheimer’s Disease (AD) pathology. Disrupted mitochondrial dynamics (i.e., fusion/fission balance), which are essential for normal mitochondria structure and function, are documented in AD. Caveolin-1 (Cav-1), a membrane/lipid raft (MLR) scaffolding protein regulates metabolic pathways in several different cell types such as hepatocytes and cancer cells. Previously, we have shown decreased expression of Cav-1 in the hippocampus of 9-month (m) old PSAPP mice, while hippocampal overexpression of neuron-targeted Cav-1 using the synapsin promoter (i.e., SynCav1) preserved cognitive function, neuronal morphology, and synaptic ultrastructure in 9 and 12 m PSAPP mice. Considering the central role of energy production in maintaining normal neuronal and synaptic function and survival, the present study reveals that PSAPP mice exhibit disrupted mitochondrial distribution, morphometry, and respiration. In contrast, SynCav1 mitigates mitochondrial damage and loss and enhances mitochondrial respiration. Furthermore, by examining mitochondrial dynamics, we found that PSAPP mice showed a significant increase in the phosphorylation of mitochondrial dynamin-related GTPase protein (DRP1), resulting in excessive mitochondria fragmentation and dysfunction. In contrast, hippocampal delivery of SynCav1 significantly decreased p-DRP1 and augmented the level of the mitochondrial fusion protein, mitofusin1 (Mfn1) in PSAPP mice, a molecular event, which may mechanistically explain for the preserved balance of mitochondria fission/fusion and metabolic resilience in 12 m PSAPP-SynCav1 mice. Our data demonstrate the critical role for Cav-1 in maintaining normal mitochondrial morphology and function through affecting mitochondrial dynamics and explain a molecular and cellular mechanism underlying the previously reported neuroprotective and cognitive preservation induced by SynCav1 in PSAPP mouse model of AD.
Non-Local Patch Regression Algorithm-Enhanced Differential Photoacoustic Methodology for Highly Sensitive Trace Gas Detection
Authors: Zhang Le , Liu Lixian , Huan Huiting , Yin Xukun , Zhang Xueshi , Mandelis Andreas , Shao Xiaopeng
Published: September 2021

A non-local patch regression (NLPR) denoising-enhanced differential broadband photoacoustic (PA) sensor was developed for the high-sensitive detection of multiple trace gases. Using the edge preservation index (EPI) and signal-to-noise ratio (SNR) as a dual-criterion, the fluctuation was dramatically suppressed while the spectral absorption peaks were maintained by the introduction of a NLPR algorithm. The feasibility of the broadband framework was verified by measuring the C2H2 in the background of ambient air. A normalized noise equivalent absorption (NNEA) coefficient of 6.13 × 10−11 cm−1·W·Hz−1/2 was obtained with a 30-mW globar source and a SNR improvement factor of 23. Furthermore, the simultaneous multiple-trace-gas detection capability was determined by measuring C2H2, H2O, and CO2. Following the guidance of single-component processing, the NLPR processed results showed higher EPI and SNR compared to the spectra denoised by the wavelet method and the non-local means algorithm. The experimentally determined SNRs of the C2H2, H2O, and CO2 spectra were improved by a factor of 20. The NNEA coefficient reached a value of 7.02 × 10−11 cm−1·W·Hz−1/2 for C2H2. The NLPR algorithm presented good performance in noise suppression and absorption peak fidelity, which offered a higher dynamic range and was demonstrated to be an effective approach for trace gas analysis.
NSAID Use and Effects on Pediatric Bone Healing: A Review of Current Literature
Authors: Choo Stephanie , Nuelle Julia A. V.
Published: September 2021

This systematic review evaluates and synthesizes the available peer-reviewed evidence regarding the impact of non-steroidal anti-inflammatory drugs (NSAIDs) on fracture healing in skeletally immature patients. Evidence supports the use of NSAIDs in this patient population for adequate pain control without increasing the risk of nonunion, particularly in long bone fractures and pseudoarthrosis after spine fusion. However, further clinical studies are needed to fill remaining gaps in knowledge, specifically with respect to the spectrum of available NSAIDs, dosage, and duration of use, in order to make broad evidence-based recommendations regarding the optimal use of NSAIDs during bone healing in skeletally immature patients.
Gender Differences in Attention Adaptation after an 8-Week FIFA 11+ for Kids Training Program in Elementary School Children
Authors: Chen Chia-Hui , Rekik Ghazi , Belkhir Yosra , Huang Ya-Ling , Chen Yung-Sheng
Published: September 2021

School-based exercise intervention is recognized as an optimal tool for enhancing attentional performance in healthy school children. However, gender differences in the training adaptation regarding attentional capacities have not been elucidated clearly in the current literature. This study aimed to investigate the effects of an 8-week Fédération Internationale de Football Association (FIFA) 11+ for Kids training program on attentional performance in schoolboys and girls. Based on a quasi-experimental design, fifty-two children registered in year five of elementary school were assigned into the following groups: training boys (n = 13), training girls (n = 13), control boys (n = 13), and control girls (n = 13). The training groups undertook an 8-week FIFA 11+ Kids intervention with a training frequency of five times per week, whereas the control groups were deprived of any exercise during the study period. All the participants maintained their regular physical activity and weekly physical education (PE) lessons (two 50-min lessons per week of school curriculum) during the training period. The Chinese version of the Attention Scale for Elementary School Children (ASESC) test was used for attentional assessment at the baseline and one week after the interventional period. The Kruskal–Wallis H test was used for between-group comparison, whereas the Wilcoxon signed-rank test was used for within-group comparison. Significant differences in total scale, focused attention, selective attention, and alternating attention were found in group comparisons (p < 0.001). Furthermore, the training children significantly increased their values in relation to total scale, focused attention, sustained attention, and selective attention (p < 0.05). Only training girls significantly improved their divided attention after the training period (p < 0.001, MD = −0.77, ES = −0.12). In conclusion, the FIFA 11+ for Kids is an effective school-based exercise intervention for attentional improvement in school children. The schoolgirls demonstrated a positive outcome regarding divided attention after the interventional period.
Modifications of Rect-Spring to Enhance the Engagement of Ectopically Entrapped Molars with 2 Case Reports
Authors: Song Min Sun , Kang Chung-Min , Song Je Seon , Choi Hyung-Jun , Lee Jaeho , Kim Seong-Oh
Published: September 2021

The Rect-spring appliance, used for the management of ectopically erupting molars, shows weak retention on mesially tilted molars. We present three modifications of the appliance for better engagement and their advantages. We describe cases of two 7-year-old patients with ectopically erupting maxillary first molars with a 2.2 mm and 2.5 mm depth of entrapment, respectively. The modified Rect-spring (mRS) was inserted between the ectopically erupting first molar and adjacent primary second molar, and exerted a distalization force with an interproximal wedging effect at the same time. After 3 months, the ectopically erupting first molars were successfully brought into proper occlusion. No discomfort was reported. The mRS is suitable for various locking cases except for severely tilted molars without requiring any laboratory procedures. We suggest it as the first choice for unlocking the first molars.
Comparative Study on the Separate Extraction of Interface and Bulk Trap Densities in Indium Gallium Zinc Oxide Thin-Film Transistors Using Capacitance–Voltage and Current–Voltage Characteristics
Authors: Lee Dong-Ho , Kim Dae-Hwan , Jeong Hwan-Seok , Hwang Seong-Hyun , Lee Sunhee , Kim Myeong-Ho , Lim Jun Hyung , Kwon Hyuck-In
Published: September 2021

The interface and bulk trap densities were separately extracted from self-aligned top-gate (SA-TG) coplanar indium gallium zinc oxide (IGZO) thin-film transistors (TFTs) using the low-frequency capacitance–voltage (C–V) characteristics and space-charge-limited current (SCLC) under the flat-band condition. In the method based on the C–V curve, the energy distribution of the interface trap density was extracted using the low-frequency C–V characteristics, and that of the bulk trap density was obtained by subtracting the density of interface trap states from the total subgap density of states (DOS) at each energy level. In the SCLC-based method, the energy distribution of the bulk trap density was extracted using the SCLC under the flat-band condition at high drain-to-source voltages, and that of the interface trap density was obtained by subtracting the density of bulk trap components from the total subgap DOS at each energy level. In our experiments, the two characterization techniques provided very similar interface and bulk trap densities and showed that approximately 60% of the subgap states originate from the IGZO/SiO2 interface at the conduction band edge in the fabricated IGZO TFTs, although the two characterization techniques are based on different measurement data. The results of this study confirm the validity of the characterization techniques proposed to separately extract the interface and bulk trap densities in IGZO TFTs. Furthermore, these results show that it is important to reduce the density of interface trap states to improve the electrical performance and stability of fabricated SA-TG coplanar IGZO TFTs.
Three-Dimensional Carbon-Coated LiFePO4 Cathode with Improved Li-Ion Battery Performance
Authors: Wang Can , Yuan Xunlong , Tan Huiyun , Jian Shuofeng , Ma Ziting , Zhao Junjie , Wang Xuewen , Chen Dapeng , Dong Yifan
Published: September 2021

LiFePO4 (LFPO)has great potential as the cathode material for lithium-ion batteries; it has a high theoretical capacity (170 m·A·h·g−1), high safety, low toxicity and good economic benefits. However, low conductivity and a low diffusion rate inhibit its future development. To overcome these weaknesses, three-dimensional carbon-coated LiFePO4 that incorporates a high capacity, superior conductivity and low volume expansion enables faster electron transport channels. The use of Cetyltrimethyl Ammonium Bromid (CTAB) modification only requires a simple water bath and sintering, without the need to add a carbon source in the LFPO synthesis process. In this way, the electrode shows excellent reversible capacity, as high as 159.8 m·A·h·g−1 at 2 C, superior rate capability with 97.3 m·A·h·g−1 at 5 C and good cycling ability, preserving ~84.2% capacity after 500 cycles. By increasing the ion transport rate and enhancing the structural stability of LFPO nanoparticles, the LFPO-positive electrode achieves excellent initial capacity and cycle life through cost-effective and easy-to-implement carbon coating. This simple three-dimensional carbon-coated LiFePO4 provides a new and simple idea for obtaining comprehensive and high-performance electrode materials in the field of lithium cathode materials.
Differential Expression of Non-Coding RNA Signatures in Thyroid Cancer between Two Ethnic Groups
Authors: Rood Kristiana , Begum Khodeza , Wang Hanmin , Wangworawat Yan C. , Davis Ryan , Yamauchi Celina R. , Perez Mia C. , Simental Alfred A. , Laxa Ria T. , Wang Charles , Roy Sourav , Khan Salma
Published: September 2021

Filipino Americans show higher thyroid cancer recurrence rates compared to European Americans. Although they are likely to die of this malignancy, the molecular mechanism has not yet been determined. Recent studies demonstrated that small non-coding RNAs could be utilized to assess thyroid cancer prognosis in tumor models. The goal of this study is to determine whether microRNA (miRNA) signatures are differentially expressed in thyroid cancer in two different ethnic groups. We also determined whether these miRNA signatures are related to cancer staging. This is a retrospective study of archival samples from patients with thyroid cancer (both sexes) in the pathology division from the last ten years at Loma Linda University School of Medicine, California. Deidentified patient demographics were extracted from the patient chart. Discarded formalin-fixed paraffin-embedded tissues were collected post-surgeries. We determined the differential expressions of microRNA in archival samples from Filipino Americans compared to European Americans using the state-of-the-art technique, HiSeq4000. By ingenuity pathway analysis, we determined miRNA targets and the pathways that those targets are involved in. We validated their expressions by real-time quantitative PCR and correlated them with the clinicopathological status in a larger cohort of miRNA samples from both ethnicities. We identified the differentially upregulated/downregulated miRNA clusters in Filipino Americans compared to European Americans. Some of these miRNA clusters are known to target genes that are linked to cancer invasion and metastasis. In univariate analysis, ethnicity and tumor staging were significant factors predicting miR-4633-5p upregulation. When including these factors in a multivariate logistic regression model, ethnicity and tumor staging remained significant independent predictors of miRNA upregulation, whereas the interaction of ethnicity and tumor staging was not significant. In contrast, ethnicity remained an independent predictor of significantly downregulated miR-491-5p and let-7 family. We provide evidence that Filipino Americans showed differentially expressed tumor-tissue-derived microRNA clusters. The functional implications of these miRNAs are under investigation.
Assessing Ecological Indicators for Remnant Vegetation Strips as Functional Biological Corridors in Chilean Vineyards
Authors: Díaz-Forestier Javiera , Abades Sebastián , Pohl Nélida , Barbosa Olga , Godoy Karina , Svensson Gabriella L. , Undurraga María I. , Bravo Camila , García Camila , Root-Bernstein Meredith , Armesto Juan J. , Celis-Diez Juan L.
Published: September 2021

Mediterranean central Chile is globally recognized as a hotspot for terrestrial biodiversity due to its high endemism and massive habitat loss. However, within the rural landscape of central Chile, significant extents of natural areas remain, especially on less productive, steep slopes, and vegetation strips extending from the surrounding hills to agricultural areas. Accordingly, vegetation strips or corridors, within lowland farms, constitute key elements to support the conservation of biodiversity in rural landscapes. To assess the ecological performance of corridors in 22 commercials vineyards in central Chile, we characterized them in terms of width-, length-, area-, and perimeter-to-area ratios, as well as the number of connections with natural areas. Based on a set of previously defined ecological indicators (species, functional groups, and structural components), we compared their occurrence in corridors within vineyards and in the surrounding natural areas. We evaluated the effects of corridor attributes on the occurrence of the selected ecological indicators, using a generalized linear mixed model with each vineyard as a random factor. The area, width, and length of vegetation corridors varied widely (1.2–86.3 ha, 10.5–95 m, and 380–5000 m, respectively). We found significant differences in the occurrence of indicators between corridors and natural areas. All sampled ecological indicators in corridors showed a negative relationship with the distance to the nearest natural area. Vegetation strips within vineyards represent important opportunities for biodiversity conservation that significantly enhance habitat quality in the agricultural landscape for biodiversity and habitat connectivity.
Taxonomy of the Cryptocephalus heraldicus Group (Coleoptera: Chrysomelidae, Cryptocephalinae) from China
Authors: Duan Wenyuan , Wang Fengyan , Zhou Hongzhang
Published: September 2021

This is a study on the leaf beetle subgenus Cryptocephalus Geoffroy, 1762 from China, with the particular emphasis upon the species-group classification of the subgenus and the taxonomy of the Cryptocephalus heraldicus species group. A new key is compiled to all the species groups found in China. Four new species are described from China: Cryptocephalus (Cryptocephalus) biordopunctatus sp. nov. from Yunnan, C. hani sp. nov. from Shanxi, Hubei, Shaanxi and Gansu, C. incisodentatus sp. nov. from Sichuan and Yunnan, and C. nigroflavusiventerus sp. nov. from Yunnan. Three species are found for the first time in China: C. lacosus Pic, 1922, C. nigriceps Allard, 1891 and C. rajah Jacoby, 1908. The species C. nigrolimbatus Jacoby, 1890 is transferred from the subgenus Burlinius Lopatin to this subgenus and assigned to the Cryptocephalus heraldicus group. The species number of this group is now 30 in total according to our result of taxonomic review. A key to all the mainland China species of this species group is provided as well as high quality color images and line drawings of adult habitus, aedeagus, and other important structures. All the types of the new species are deposited in the collection of Institute of Zoology, Chinese Academy of Sciences (IZ-CAS).
A Novel Dehumidification Strategy to Reduce Liquid Fraction and Condensation Loss in Steam Turbines
Authors: Yang Yan , Peng Haoping , Wen Chuang
Published: September 2021

Massive droplets can be generated to form two-phase flow in steam turbines, leading to erosion issues to the blades and reduces the reliability of the components. A condensing two-phase flow model was developed to assess the flow structure and loss considering the nonequilibrium condensation phenomenon due to the high expansion behaviour in the transonic flow in linear blade cascades. A novel dehumidification strategy was proposed by introducing turbulent disturbances on the suction side. The results show that the Wilson point of the nonequilibrium condensation process was delayed by increasing the inlet superheated level at the entrance of the blade cascade. With an increase in the inlet superheated level of 25 K, the liquid fraction and condensation loss significantly reduced by 79% and 73%, respectively. The newly designed turbine blades not only remarkably kept the liquid phase region away from the blade walls but also significantly reduced 28.1% averaged liquid fraction and 47.5% condensation loss compared to the original geometry. The results provide an insight to understand the formation and evaporation of the condensed droplets inside steam turbines.
Pedagogies of Discomfort and Care: Balancing Critical Tensions in Delivering Gender-Related Violence Training to Youth Practitioners
Authors: Cullen Fin , Whelan Michael
Published: September 2021

This reflective paper explores the emotions, ethics, and challenges of facilitating training for youth practitioners to tackle gender-related violence (GRV). This paper draws on insights from a training intervention that emerged from an EU-funded feminist project (UK GAPWORK project), which sought to bring together approaches to tackle violence against women and girls with challenging heteronormativity and homophobia. Drawing on accounts from facilitators and participants, the aim of this paper is to identify tensions, opportunities and strategies in developing training to support critically engaged practice around sensitive topics such as GRV, and to consider the significance of working with discomfort within any such training intervention. We reflect on how discomfort presented within the training space and the challenges presented. This paper examines how Boler’s theoretical work on pedagogy of discomfort can be operationalised to think productively about designing and delivering training for informal educators on sensitive issues with ethical integrity.
Towards Cooperative Perception Services for ITS: Digital Twin in the Automotive Edge Cloud
Authors: Tihanyi Viktor , Rövid András , Remeli Viktor , Vincze Zsolt , Csonthó Mihály , Pethő Zsombor , Szalai Mátyás , Varga Balázs , Khalil Aws , Szalay Zsolt
Published: September 2021

We demonstrate a working functional prototype of a cooperative perception system that maintains a real-time digital twin of the traffic environment, providing a more accurate and more reliable model than any of the participant subsystems—in this case, smart vehicles and infrastructure stations—would manage individually. The importance of such technology is that it can facilitate a spectrum of new derivative services, including cloud-assisted and cloud-controlled ADAS functions, dynamic map generation with analytics for traffic control and road infrastructure monitoring, a digital framework for operating vehicle testing grounds, logistics facilities, etc. In this paper, we constrain our discussion on the viability of the core concept and implement a system that provides a single service: the live visualization of our digital twin in a 3D simulation, which instantly and reliably matches the state of the real-world environment and showcases the advantages of real-time fusion of sensory data from various traffic participants. We envision this prototype system as part of a larger network of local information processing and integration nodes, i.e., the logically centralized digital twin is maintained in a physically distributed edge cloud.
The Reporting of Sustainable Energy Action Plans of Municipalities: Methodology and Results of Case Studies from the Abruzzo Region
Authors: Di Battista Davide , Barchiesi Chiara , Di Paolo Luca , Abbate Simona , Sorvillo Sara , Cinocca Andrea , Carapellucci Roberto , Ciamponi Dario , Cardone Dina , Corroppolo Salvatore , Cipollone Roberto
Published: September 2021

Territorial energetic and environmental planning provides operational solidity to the concept of sustainable development, in particular in energy-related issues, where recent attention to and social awareness of climate change are driving actions and policies at local and international levels. The goals of the United Nations Agenda 2030 can be reached through the strategy of glocalization, giving more responsibility to local administrations like municipalities. In this work, a scientific methodology is developed and validated to revise Sustainable Energy Action Plans (SEAP) and the monitoring phase of municipalities. The methodology starts from measured data in the territory considered and makes use of specific statistical models in order to estimate the needed data. The methodology considers the energy consumption of the main sectors: residential, transportation, tertiary, and commercial, with a particular focus on municipal competences (public lighting, urban transport, municipal fleet, etc.). Renewable energy is also considered due to its importance in local energy production. In order to go deeper into SEAPs, in this paper, the authors describe the quantitative analysis of the Baseline Emission Inventory, the quantification of the SEAP planning actions, and the definition of the Monitoring Emission Inventory, which is the final step of the planning process. This step was done for nine municipalities of the Abruzzo region with different characteristics (size, population, climate, geographical position, economy, etc.) in order to widen the results of the analysis and test the robustness of the methodology. Indeed, it gave a quantitative dimension to the primary energy consumption and CO2 emissions for 2018, compared with the 2005 baseline values, and the final results are related to the reduction commitments planned for 2020. All the municipalities were considered to have achieved this goal, surpassing the 20% emissions reduction. This validated methodology is also the basis for the development of the Sustainable Energy and Climate Action Plans (SECAPs), which integrate adaptation actions and mitigation ones.
Digital Twin in Electrical Machine Control and Predictive Maintenance: State-of-the-Art and Future Prospects
Authors: Falekas Georgios , Karlis Athanasios
Published: September 2021

State-of-the-art Predictive Maintenance (PM) of Electrical Machines (EMs) focuses on employing Artificial Intelligence (AI) methods with well-established measurement and processing techniques while exploring new combinations, to further establish itself a profitable venture in industry. The latest trend in industrial manufacturing and monitoring is the Digital Twin (DT) which is just now being defined and explored, showing promising results in facilitating the realization of the Industry 4.0 concept. While PM efforts closely resemble suggested DT methodologies and would greatly benefit from improved data handling and availability, a lack of combination regarding the two concepts is detected in literature. In addition, the next-generation-Digital-Twin (nexDT) definition is yet ambiguous. Existing DT reviews discuss broader definitions and include citations often irrelevant to PM. This work aims to redefine the nexDT concept by reviewing latest descriptions in broader literature while establishing a specialized denotation for EM manufacturing, PM, and control, encapsulating most of the relevant work in the process, and providing a new definition specifically catered to PM, serving as a foundation for future endeavors. A brief review of both DT research and PM state-of-the-art spanning the last five years is presented, followed by the conjunction of core concepts into a definitive description. Finally, surmised benefits and future work prospects are reported, especially focused on enabling PM state-of-the-art in AI techniques.
Forecasting and Assessment of the Energy Security Risk in Fuzzy Environment
Authors: Ziemba Paweł , Becker Aneta , Becker Jarosław
Published: September 2021

Energy security is of key importance for states and international organizations. An important issue in energy security is the assessment of current and future energy security methods. While the assessment of the current methods is relatively easy, since it is based on recent information, the assessment of the future methods is burdened with uncertainty and is therefore much more difficult. Therefore, the aim of the article is to develop a new approach for assessing current and future energy security issues based on a complex security index, supported by the computationally transparent fuzzy multi-criteria decision analysis (MCDA) method. The use of the fuzzy MCDA methods allows one to capture the uncertainty of assessments and forecasts, and the forecasts themselves were based on the Holt’s method; the international energy security risk index (IESRI) was used as the source of the data to generate the forecasts. The research compared two data sources for forecasts (IESRI categories and metrics) and two methods of forecast fuzzification. As a result, the forecasted assessments and rankings of energy security for the 2020–2030 period were obtained. On the basis of these forecasts, general trends shaping energy security were also indicated.
Magnetic FEA Direct Optimization of High-Power Density, Halbach Array Permanent Magnet Electric Motors
Authors: Grenier Jean-Michel , Pérez Ramón , Picard Mathieu , Cros Jérôme
Published: September 2021

Hybrid electric aero-propulsion requires high power-density electric motors. The use of a constrained optimization method with the finite element analysis (FEA) is the best way to design these motors and to find the best solutions which maximize the power density. This makes it possible to take into account all the details of the geometry as well as the non-linear characteristics of magnetic materials, the conductive material and the current control strategy. Simulations were performed with a time stepping magnetodynamic solver while taking account the rotor movement and the stator winding was connected by an external electrical circuit. This study describes the magnetic FEA direct optimization approach for the design of Halbach array permanent magnet synchronous motors (PMSMs) and its advantages. An acceptable compromise between precision and computation time to estimate the electromagnetic torque, iron losses and eddy current losses was found. The finite element simulation was paired with analytical models to compute stress on the retaining sleeve, aerodynamic losses, and copper losses. This type of design procedure can be used to find the best machine configurations and establish design rules based on the specifications and materials selected. As an example, optimization results of PM motors minimizing total losses for a 150-kW application are presented for given speeds in the 2000 rpm to 50,000 rpm range. We compare different numbers of poles and power density between 5 kW/kg and 30 kW/kg. The choice of the number of poles is discussed in the function of the motor nominal speed and targeted power density as well as the compromise between iron losses and copper losses. In addition, the interest of having the current-control strategy as an optimization variable to generate a small amount of flux weakening is clearly shown.
Stationary Hybrid Renewable Energy Systems for Railway Electrification: A Review
Authors: Mitrofanov Sergey V. , Kiryanova Natalya G. , Gorlova Anna M.
Published: September 2021

This article provides an overview of modern technologies and implemented projects in the field of renewable energy systems for the electrification of railway transport. In the first part, the relevance of the use of renewable energy on the railways is discussed. Various types of power-generating systems in railway stations and platforms along the track, as well as in separate areas, are considered. The focus is on wind and solar energy conversion systems. The second part is devoted to the analysis of various types of energy storage devices used in projects for the electrification of railway transport since the energy storage system is one of the key elements in a hybrid renewable energy system. Systems with kinetic storage, electrochemical storage batteries, supercapacitors, hydrogen energy storage are considered. Particular attention is paid to technologies for accumulating and converting hydrogen into electrical energy, as well as hybrid systems that combine several types of storage devices with different ranges of charge/discharge rates. A comparative analysis of various hybrid electric power plant configurations, depending on the functions they perform in the electrification systems of railway transport, has been carried out.
Machine Learning and Data Segmentation for Building Energy Use Prediction—A Comparative Study
Authors: Mounter William , Ogwumike Chris , Dawood Huda , Dawood Nashwan
Published: September 2021

Advances in metering technologies and emerging energy forecast strategies provide opportunities and challenges for predicting both short and long-term building energy usage. Machine learning is an important energy prediction technique, and is significantly gaining research attention. The use of different machine learning techniques based on a rolling-horizon framework can help to reduce the prediction error over time. Due to the significant increases in error beyond short-term energy forecasts, most reported energy forecasts based on statistical and machine learning techniques are within the range of one week. The aim of this study was to investigate how facility managers can improve the accuracy of their building’s long-term energy forecasts. This paper presents an extensive study of machine learning and data processing techniques and how they can more accurately predict within different forecast ranges. The Clarendon building of Teesside University was selected as a case study to demonstrate the prediction of overall energy usage with different machine learning techniques such as polynomial regression (PR), support vector regression (SVR) and artificial neural networks (ANNs). This study further examined how preprocessing training data for prediction models can impact the overall accuracy, such as via segmenting the training data by building modes (active and dormant), or by days of the week (weekdays and weekends). The results presented in this paper illustrate a significant reduction in the mean absolute percentage error (MAPE) for segmented building (weekday and weekend) energy usage prediction when compared to unsegmented monthly predictions. A reduction in MAPE of 5.27%, 11.45%, and 12.03% was achieved with PR, SVR and ANN, respectively.
Experimental and Theoretical Study on the Internal Convective and Radiative Heat Transfer Coefficients for a Vertical Wall in a Residential Building
Authors: Michalak Piotr
Published: September 2021

Experimental studies on internal convective (CHTC) and radiative (RHTC) heat transfer coefficients are very rarely conducted in real conditions during the normal use of buildings. This study presents the results of measurements of CHTC and RHTC for a vertical wall, taken in a selected room of a single-family building during its everyday use. Measurements were performed using HFP01 heat flux plates, Pt1000 sensors for internal air and wall surface temperatures and a globe thermometer for mean radiant temperature measured in 10 min intervals. Measured average CHTC and RHTC amounted to 1.15 W/m2K and 5.45 W/m2K, compared to the 2.50 W/m2K and 5.42 W/m2K recommended by the EN ISO 6946, respectively. To compare with calculated CHTC, 14 correlations based on the temperature difference were applied. Obtained values were from 1.31 W/m2K (given by Min et al.) to 3.33 W/m2K (Wilkes and Peterson), and in all cases were greater than the 1.15 W/m2K from measurements. The average value from all models amounted to 2.02 W/m2K, and was greater than measurements by 75.6%. The quality of models was also estimated using average absolute error (AAE), average biased error (ABE), mean absolute error (MAE) and mean bias error (MBE). Based on these techniques, the model of Fohanno and Polidori was identified as the best with AAE = 68%, ABE = 52%, MAE = 0.41 W/m2K and MBE = 0.12 W/m2K.
A Time-Dependent Model for Predicting Thermal Environment of Mono-Slope Solar Greenhouses in Cold Regions
Authors: Dong Shuyao , Ahamed Md Shamim , Ma Chengwei , Guo Huiqing
Published: September 2021

Most greenhouses in the Canadian Prairies shut down during the coldest months (November to February) because of the hefty heating cost. Chinese mono-slope solar greenhouses do not primarily rely on supplemental heating; instead, they mostly rely on solar energy to maintain the required indoor temperature in winter. This study focuses on improving an existing thermal model, entitled RGWSRHJ, for Chinese-style solar greenhouses (CSGs) to increase the robustness of the model for simulating the thermal environment of the CSGs located outside of China. The modified model, entitled SOGREEN, was validated using the field data collected from a CSG in Manitoba, Canada. The results indicate that the average prediction error for indoor and relative humidity is 1.9 °C and 7.0%, and the rRMSE value is 3.3% and 11.5%, respectively. The average error for predicting the north wall and ground surface temperature is 4.2 °C and 2.3 °C, respectively. The study also conducted a case study to analyze the thermal performance of a conceptual CSG in Saskatoon, Canada. The energy analysis indicates the heating requirement of the greenhouse highly depends on the availability of solar radiation. Besides winter, the heating requirement is relatively low in March to maintain 18 °C indoor temperature when the average outdoor temperature was below –4 °C, and negligible during May–August. The results indicate that vegetable production in CSGs could save about 55% on annual heating than traditional greenhouses. Hence, CSGs could be an energy-efficient solution for ensuring food security for northern communities in Canada and other cold regions.
A Comprehensive Review of Lithium-Ion Cell Temperature Estimation Techniques Applicable to Health-Conscious Fast Charging and Smart Battery Management Systems
Authors: Samanta Akash , Williamson Sheldon S.
Published: September 2021

Highly nonlinear characteristics of lithium-ion batteries (LIBs) are significantly influenced by the external and internal temperature of the LIB cell. Moreover, a cell temperature beyond the manufacturer’s specified safe operating limit could lead to thermal runaway and even fire hazards and safety concerns to operating personnel. Therefore, accurate information of cell internal and surface temperature of LIB is highly crucial for effective thermal management and proper operation of a battery management system (BMS). Accurate temperature information is also essential to BMS for the accurate estimation of various important states of LIB, such as state of charge, state of health and so on. High-capacity LIB packs, used in electric vehicles and grid-tied stationary energy storage system essentially consist of thousands of individual LIB cells. Therefore, installing a physical sensor at each cell, especially at the cell core, is not practically feasible from the solution cost, space and weight point of view. A solution is to develop a suitable estimation strategy which led scholars to propose different temperature estimation schemes aiming to establish a balance among accuracy, adaptability, modelling complexity and computational cost. This article presented an exhaustive review of these estimation strategies covering recent developments, current issues, major challenges, and future research recommendations. The prime intention is to provide a detailed guideline to researchers and industries towards developing a highly accurate, intelligent, adaptive, easy-to-implement and computationally efficient online temperature estimation strategy applicable to health-conscious fast charging and smart onboard BMS.
Methodology for Management of the Protection System of Smart Power Supply Networks in the Context of Cyberattacks
Authors: Kotenko Igor , Saenko Igor , Lauta Oleg , Karpov Mikhail
Published: September 2021

This paper examines an approach that allows one to build an efficient system for protecting the information resources of smart power supply networks from cyberattacks based on the use of graph models and artificial neural networks. The possibility of a joint application of graphs, describing the features for the functioning of the protection system of smart power supply networks, and artificial neural in order to predict and detect cyberattacks is considered. The novelty of the obtained results lies in the fact that, on the basis of experimental studies, a methodology for managing the protection system of smart power supply networks in conditions of cyberattacks is substantiated. It is based on the specification of the protection system by using flat graphs and implementing a neural network with long short-term memory, which makes it possible to predict with a high degree of accuracy and fairly quickly the impact of cyberattacks. The issues of software implementation of the proposed approach are considered. The experimental results obtained using the generated dataset confirm the efficiency of the developed methodology. It is shown that the proposed methodology demonstrates up to a 30% gain in time for detecting cyberattacks in comparison with known solutions. As a result, the survivability of the Self-monitoring, Analysis and Reporting technology (SMART) grid (SG) fragment under consideration increased from 0.62 to 0.95.
The Bamboo Rhizome Evolution in China Is Driven by Geographical Isolation and Trait Differentiation
Authors: Gu Han-Jiao , Zhang Can-Can , Chen Fu-Sheng , Huang Ji-Hong , Wang Jin-Song , Bruelheide Helge , Trogisch Stefan , Fang Xiang-Min , Li Jian-Jun , Bu Wen-Sheng
Published: September 2021

Plant endemic species are the result of continuous evolution under the combined action of long-term climatic and geological conditions. There are 534 bamboo species in China, and 371 endemic species account for about 70% of all bamboo species. However, little is known about the differences in the rhizome evolution rate between endemic and non-endemic bamboos. Here, we collected morphological traits (height and leaf length) and environmental variables (including climate, space, and soil) of all 534 Chinese bamboo species to determine the relative contribution of environmental factors and traits of bamboo rhizome evolution with different endemism by structural equation modeling. We found that endemic bamboo had a higher speciation rate than non-endemic bamboo. The distribution centers of sympodial bamboos are mainly located in the mountain range of southwest China, while amphipodial and monopodial bamboos are distributed with higher latitude farther east in China. The height of non-endemic sympodial and monopodial bamboos was significantly higher than endemic sympodial and monopodial bamboos. The leaf length of non-endemic sympodial bamboos was significantly higher than endemic sympodial bamboo, while the leaf length of non-endemic amphipodial bamboo was significantly lower than endemic amphipodial bamboo. Environmental factors and traits explain 47% of the evolutionary variation of non-endemic bamboo species, while they explain 17% of that of endemic bamboo species. Longitude, latitude, and leaf length were the critical factors in the rhizome evolution of non-endemic bamboo, while longitude and height were the critical factors in the rhizome evolution of endemic bamboo. Our results imply that for higher species formation rates, endemic bamboo should be more concerned than non-endemic bamboo in the process of bamboo rhizome evolution. It will likely appear that new non-endemic bamboo species have a short leaf length in higher latitude and farther east in China (the lower Yangtze plain), as well as new endemic bamboo species with a low height farther east in China (the Wuyi Mountains). Meanwhile, ancient non-endemic bamboo with a long leaf length in Yunnan Province and ancient endemic bamboo with a high height in the Hengduan Mountains may be more likely to become extinct. Our findings highlight the importance of understanding the difference in the rhizome evolution of endemic and non-endemic bamboos, which provides new insights into the conservation of Chinese bamboo biodiversity.
Assessing the Technical Efficiency of Timber Production during the Transition from a Production-Oriented Management Model to a Multifunctional One: A Case from Poland 1990–2019
Authors: Banaś Jan , Utnik-Banaś Katarzyna , Zięba Stanisław , Janeczko Krzysztof
Published: September 2021

The present work applied a data envelopment analysis (DEA) model to assess changes in the technical efficiency of timber production at a period of transition in forest management priorities. The study material consisted of data on timber sold by Polish State Forests (PSF) and on its forest management inputs in the years 1990–2019. During the period of economic transition in Poland (1990–2003) the technical efficiency of timber production on average amounted to 0.809 and was highly variable. In the free-market period, that efficiency was much higher (on average 0.939) and more stable. This improvement was achieved by substantial layoffs in the PSF, and steady rise in the share and standing volume of mature stands, which made it possible to increase timber production while adhering to sustainable management principles. Analysis of the various categories of inputs to timber production revealed that the greatest decline, in labor costs, was attributable to a fourfold reduction in the workforce, and was accompanied by a 2.4-fold increment in timber production. On the other hand, logging costs increased due to, among other causes, the pursuit of environmentally friendly but more expensive harvesting procedures and reductions in clearcutting, which entailed more dispersed harvesting operations.
A Fusion-Based Hybrid-Feature Approach for Recognition of Unconstrained Offline Handwritten Hindi Characters
Authors: Rajpal Danveer , Garg Akhil Ranjan , Mahela Om Prakash , Alhelou Hassan Haes , Siano Pierluigi
Published: September 2021

Hindi is the official language of India and used by a large population for several public services like postal, bank, judiciary, and public surveys. Efficient management of these services needs language-based automation. The proposed model addresses the problem of handwritten Hindi character recognition using a machine learning approach. The pre-trained DCNN models namely; InceptionV3-Net, VGG19-Net, and ResNet50 were used for the extraction of salient features from the characters’ images. A novel approach of fusion is adopted in the proposed work; the DCNN-based features are fused with the handcrafted features received from Bi-orthogonal discrete wavelet transform. The feature size was reduced by the Principal Component Analysis method. The hybrid features were examined with popular classifiers namely; Multi-Layer Perceptron (MLP) and Support Vector Machine (SVM). The recognition cost was reduced by 84.37%. The model achieved significant scores of precision, recall, and F1-measure—98.78%, 98.67%, and 98.69%—with overall recognition accuracy of 98.73%.