bluuebunny/crossref_metadata_2025 huggingface dataset:
High-Dose Vitamin D Supplementation Improves Microcirculation and Reduces Inflammation in Diabetic Neuropathy Patients
Authors: Karonova Tatiana , Stepanova Anna , Bystrova Anna , Jude Edward B.
Published: August 2020

We assessed the effect of different doses of vitamin D supplementation on microcirculation, signs and symptoms of peripheral neuropathy and inflammatory markers in patients with type 2 diabetes (T2DM). Sixty-seven patients with T2DM and peripheral neuropathy (34 females) were randomized into two treatment groups: Cholecalciferol 5000 IU and 40,000 IU once/week orally for 24 weeks. Severity of neuropathy (NSS, NDS scores, visual analogue scale), cutaneous microcirculation (MC) parameters and inflammatory markers (ILs, CRP, TNFα) were assessed before and after treatment. Vitamin D deficiency/insufficiency was detected in 78% of the 62 completed subjects. Following treatment with cholecalciferol 40,000 IU/week, a significant decrease in neuropathy severity (NSS, p = 0.001; NDS, p = 0.001; VAS, p = 0.001) and improvement of cutaneous MC were observed (p < 0.05). Also, we found a decrease in IL-6 level (2.5 pg/mL vs. 0.6 pg/mL, p < 0.001) and an increase in IL-10 level (2.5 pg/mL vs. 4.5 pg/mL, p < 0.001) after 24 weeks of vitamin D supplementation in this group. No changes were detected in the cholecalciferol 5000 IU/week group. High-dose cholecalciferol supplementation of 40,000 IU/week for 24 weeks was associated with improvement in clinical manifestation, cutaneous microcirculation and inflammatory markers in patients with T2DM and peripheral neuropathy.
Potential Cardiovascular and Metabolic Beneficial Effects of ω-3 PUFA in Male Obesity Secondary Hypogonadism Syndrome
Authors: Noce Annalisa , Marrone Giulia , Di Daniele Francesca , Di Lauro Manuela , Pietroboni Zaitseva Anna , Wilson Jones Georgia , De Lorenzo Antonino , Di Daniele Nicola
Published: August 2020

Long-chain ω-3 polyunsaturated fatty acids (PUFAs) are fundamental biocomponents of lipids and cell membranes. They are involved in the maintenance of cellular homeostasis and they are able to exert anti-inflammatory and cardioprotective actions. Thanks to their potential beneficial effects on the cardiovascular system, metabolic axis and body composition, we have examined their action in subjects affected by male obesity secondary hypogonadism (MOSH) syndrome. MOSH syndrome is characterized by the presence of obesity associated with the alteration of sexual and metabolic functions. Therefore, this review article aims to analyze scientific literature regarding the possible benefits of ω-3 PUFA administration in subjects affected by MOSH syndrome. We conclude that there are strong evidences supporting ω-3 PUFA administration and/or supplementation for the treatment and management of MOSH patients.
The Effect of Acute Hypohydration on Indicators of Glycemic Regulation, Appetite, Metabolism and Stress: A Systematic Review and Meta-Analysis
Authors: Zaplatosch Mitchell E. , Adams William M.
Published: August 2020

Evidence synthesizing the effects of acute body water losses on various markers of glycemic regulation, appetite, metabolism, and stress is lacking. Thus, the purpose of this review was to summarize the response of various hormonal changes involved in these physiologic functions to dehydration. A comprehensive literature search for peer-reviewed research in the databases PubMed, Scopus, CINAHL, and SportDiscus was conducted. Studies were included if they contained samples of adults (>18 years) and experimentally induced dehydration as measured by acute body mass loss. Twenty-one articles were eligible for inclusion. Findings suggested cortisol is significantly elevated with hypohydration (standard mean difference [SMD] = 1.12, 95% CI [0.583, 1.67], p < 0.0001). Testosterone was significantly lower in studies where hypohydration was accompanied by caloric restriction (SMD= −1.04, 95% CI [−1.93, −0.14], p = 0.02), however, there were no changes in testosterone in studies examining hypohydration alone (SMD = −0.17, 95% CI [−0.51 0.16], p = 0.30). Insulin and ghrelin were unaffected by acute total body water losses. Acute hypohydration increases markers of catabolism but has a negligible effect on markers of glycemic regulation, appetite, anabolism and stress. Given the brevity of existing research, further research is needed to determine the impact of hydration on glucagon, leptin, peptide YY and the subsequent outcomes relevant to both health and performance.
Gaining Insight into Exclusive and Common Transcriptomic Features Linked to Drought and Salinity Responses across Fruit Tree Crops
Authors: Benny Jubina , Marchese Annalisa , Giovino Antonio , Marra Francesco Paolo , Perrone Anna , Caruso Tiziano , Martinelli Federico
Published: August 2020

The present study aimed at identifying and mapping key genes expressed in root tissues involved in drought and salinity tolerance/resistance conserved among different fruit tree species. Twenty-six RNA-Seq samples were analyzed from six published studies in five plant species (Olea europaea, Vitis riparia Michx, Prunus mahaleb, Prunus persica, Phoenix dactylifera). This meta-analysis used a bioinformatic pipeline identifying 750 genes that were commonly modulated in three salinity studies and 683 genes that were commonly regulated among three drought studies, implying their conserved role in resistance/tolerance/response to these environmental stresses. A comparison was done on the genes that were in common among both salinity and drought resulted in 82 genes, of which 39 were commonly regulated with the same trend of expression (23 were upregulated and 16 were downregulated). Gene set enrichment and pathway analysis pointed out that pathways encoding regulation of defense response, drug transmembrane transport, and metal ion binding are general key molecular responses to these two abiotic stress responses. Furthermore, hormonal molecular crosstalk plays an essential role in the fine-tuning of plant responses to drought and salinity. Drought and salinity induced a different molecular “hormonal fingerprint”. Dehydration stress specifically enhanced multiple genes responsive to abscisic acid, gibberellin, brassinosteroids, and the ethylene-activated signaling pathway. Salt stress mostly repressed genes encoding for key enzymes in signaling proteins in auxin-, gibberellin-(gibberellin 2 oxidase 8), and abscisic acid-related pathways (aldehyde oxidase 4, abscisic acid-responsive element-binding protein 3). Abiotic stress-related genes were mapped into the chromosome to identify molecular markers usable for the improvement of these complex quantitative traits. This meta-analysis identified genes that serve as potential targets to develop cultivars with enhanced drought and salinity resistance and/or tolerance across different fruit tree crops in a biotechnological sustainable way.
Genome-Wide Analysis of the PIN Auxin Efflux Carrier Gene Family in Coffee
Authors: Huang Xing , Bai Xuehui , Guo Tieying , Xie Zhouli , Laimer Margit , Du Dengxiang , Gbokie Thomas , Zhang Zhirun , He Chunping , Lu Ying , Wu Weihuai , Yi Kexian
Published: August 2020

Coffee is one of the most popular beverages around the world, which is mainly produced from the allopolyploid Coffea arabica. The genomes of C. arabica and its two ancestors C. canephora and C. eugenioides have been released due to the development of next generation sequencing. However, few studies on C. arabica are related to the PIN-FORMED (PIN) auxin efflux transporter despite its importance in auxin-mediated plant growth and development. In the present study, we conducted a genome-wide analysis of the PIN gene family in the three coffee species. Totals of 17, 9 and 10 of the PIN members were characterized in C. Arabica, C. canephora and C. eugenioides, respectively. Phylogenetic analysis revealed gene loss of PIN1 and PIN2 homologs in C. arabica, as well as gene duplication of PIN5 homologs during the fractionation process after tetraploidy. Furthermore, we conducted expression analysis of PIN genes in C. arabica by in silico and qRT-PCR. The results revealed the existence of gene expression dominance in allopolyploid coffee and illustrated several PIN candidates in regulating auxin transport and homeostasis under leaf rust fungus inoculation and the tissue-specific expression pattern of C. arabica. Together, this study provides the basis and guideline for future functional characterization of the PIN gene family.
The Effect of Natural Additives on the Composting Properties of Aliphatic Polyesters
Authors: Latos-Brozio Malgorzata , Masek Anna
Published: August 2020

Compounds of plant origin are used with polymers as functional additives. However, these substances often have biological (antimicrobial) activity. The bactericidal and fungicidal properties of natural additives can affect the composting process of biodegradable polymers. The scientific novelty of the manuscript is the investigation of the effect of the addition of herbal antimicrobial functional substances on the composting process of green polymers. The aim of the study is to analyze composting processes of biodegradable polymers polylactide (PLA) and polyhydroxyalkanoate (PHA) containing β-carotene, juglone, morin, and curcumin. As part of the research, six-month composting of materials was performed. At time intervals of one month, the weight loss of samples, surface energy, colour change, mechanical properties, and carbonyl indices (based on FTIR spectroscopy) of composted materials were examined. The research results showed that the addition of selected plant substances slightly slowed down the process of polymer composting. Slower degradation of samples with plant additives was confirmed by the results of mechanical strength tests and the analysis of changes in carbonyl index (CI). The CI analysis showed that PLA and PHA containing a natural additive degrade a month later than reference samples. However, PLA and PHA polyesters with β-carotene, juglone, morin, and curcumin were still very biodegradable.
Tensile Behavior of High-Density Polyethylene Including the Effects of Processing Technique, Thickness, Temperature, and Strain Rate
Authors: Amjadi Mohammad , Fatemi Ali
Published: August 2020

The primary goal of this study was to investigate the monotonic tensile behavior of high-density polyethylene (HDPE) in its virgin, regrind, and laminated forms. HDPE is the most commonly used polymer in many industries. A variety of tensile tests were performed using plate-type specimens made of rectangular plaques. Several factors can affect the tensile behavior such as thickness, processing technique, temperature, and strain rate. Testing temperatures were chosen at −40, 23 (room temperature, RT), 53, and 82 °C to investigate temperature effect. Tensile properties, including elastic modulus, yield strength, and ultimate tensile strength, were obtained for all conditions. Tensile properties significantly reduced by increasing temperature while elastic modulus and ultimate tensile strength linearly increased at higher strain rates. A significant effect of thickness on tensile properties was observed for injection molding specimens at 23 °C, but no thickness effect was observed for compression molded specimens at either 23 or 82 °C. The aforementioned effects and discussion of their influence on tensile properties are presented in this paper. Polynomial relations for tensile properties, including elastic modulus, yield strength, and ultimate tensile strength, were developed as functions of temperature and strain rate. Such relations can be used to estimate tensile properties of HDPE as a function of temperature and/or strain rate for application in designing parts with this material.
Design and Preparation of Polysulfide Flexible Polymers Based on Cottonseed Oil and Its Derivatives
Authors: Chen Yurong , Liu Yanxia , Chen Yidan , Zhang Yagang , Zan Xingjie
Published: August 2020

Polysulfide-derived polymers with a controllable density and mechanical strength were designed and prepared successfully using bio-based cottonseed oil (CO) and its derivatives, including fatty acid of cottonseed oil (COF) and sodium soap of cottonseed oil (COS). The reaction features of CO, COF and COS for polysulfide polymers were investigated and compared. Based on the free radical addition mechanism, COF reacts with sulfur to generate serials of polysulfide-derived polymers. COF strongly influences the density and tensile strength of these polymer composites. Whereas COS was not involved in the reaction with sulfur, as a filler, it could increase the density and tensile strength of polysulfide-derived polymers. Moreover, the results showed that these samples had an excellent reprocessability and recyclability. These polysulfide-based polymers, with an adjustable density and mechanical strength based on CO and derivatives, could have potential applications as bio-based functional supplementary additives.
Application of Polysaccharide Biopolymer in Petroleum Recovery
Authors: Xia Shunxiang , Zhang Laibao , Davletshin Artur , Li Zhuoran , You Jiahui , Tan Siyuan
Published: August 2020

Polysaccharide biopolymers are biomacromolecules derived from renewable resources with versatile functions including thickening, crosslinking, adsorption, etc. Possessing high efficiency and low cost, they have brought wide applications in all phases of petroleum recovery, from well drilling to wastewater treatment. The biopolymers are generally utilized as additives of fluids or plugging agents, to correct the fluid properties that affect the performance and cost of petroleum recovery. This review focuses on both the characteristics of biopolymers and their utilization in the petroleum recovery process. Research on the synthesis and characterization of polymers, as well as controlling their structures through modification, aims to develop novel recipes of biopolymer treatment with new application realms. The influences of biopolymer in many petroleum recovery cases were also evaluated to permit establishing the correlations between their physicochemical properties and performances. As their performance is heavily affected by the local environment, screening and testing polymers under controlled conditions is the necessary step to guarantee the efficiency and safety of biopolymer treatments.
Simulation-Based Optimization of a Two-Echelon Continuous Review Inventory Model with Lot Size-Dependent Lead Time
Authors: Alharkan Ibrahim , Saleh Mustafa , Ghaleb Mageed , Farhan Abdulsalam , Badwelan Ahmed
Published: August 2020

This study analyzes a stochastic continuous review inventory system (Q,r) using a simulation-based optimization model. The lead time depends on lot size, unit production time, setup time, and a shop floor factor that represents moving, waiting, and lot size inspection times. A simulation-based model is proposed for optimizing order quantity (Q) and reorder point (r) that minimize the total inventory costs (holding, backlogging, and ordering costs) in a two-echelon supply chain, which consists of two identical retailers, a distributor, and a supplier. The simulation model is created with Arena software and validated using an analytical model. The model is interfaced with the OptQuest optimization tool, which is embedded in the Arena software, to search for the least cost lot sizes and reorder points. The proposed model is designed for general demand distributions that are too complex to be solved analytically. Hence, for the first time, the present study considers the stochastic inventory continuous review policy (Q,r) in a two-echelon supply chain system with lot size-dependent lead time L(Q). An experimental study is conducted, and results are provided to assess the developed model. Results show that the optimized Q and r for different distributions of daily demand are not the same even if the associated total inventory costs are close to each other.
Land Cover Classification in Mangrove Ecosystems Based on VHR Satellite Data and Machine Learning—An Upscaling Approach
Authors: Bihamta Toosi Neda , Soffianian Ali Reza , Fakheran Sima , Pourmanafi Saeied , Ginzler Christian , T. Waser Lars
Published: August 2020

Mangrove forests grow in the inter-tidal areas along coastlines, rivers, and tidal lands. They are highly productive ecosystems and provide numerous ecological and economic goods and services for humans. In order to develop programs for applying guided conservation and enhancing ecosystem management, accurate and regularly updated maps on their distribution, extent, and species composition are needed. Recent advances in remote sensing techniques have made it possible to gather the required information about mangrove ecosystems. Since costs are a limiting factor in generating land cover maps, the latest remote sensing techniques are advantageous. In this study, we investigated the potential of combining Sentinel-2 and Worldview-2 data to classify eight land cover classes in a mangrove ecosystem in Iran with an area of 768 km2. The upscaling approach comprises (i) extraction of reflectance values from Worldview-2 images, (ii) segmentation based on spectral and spatial features, and (iii) wall-to-wall prediction of the land cover based on Sentinel-2 images. We used an upscaling approach to minimize the costs of commercial satellite images for collecting reference data and to focus on freely available satellite data for mapping land cover classes of mangrove ecosystems. The approach resulted in a 65.5% overall accuracy and a kappa coefficient of 0.63, and it produced the highest accuracies for deep water and closed mangrove canopy cover. Mapping accuracies improved with this approach, resulting in medium overall accuracy even though the user’s accuracy of some classes, such as tidal zone and shallow water, was low. Conservation and sustainable management in these ecosystems can be improved in the future.
Woody Aboveground Biomass Mapping of the Brazilian Savanna with a Multi-Sensor and Machine Learning Approach
Authors: Bispo Polyanna da Conceição , Rodríguez-Veiga Pedro , Zimbres Barbara , do Couto de Miranda Sabrina , Henrique Giusti Cezare Cassio , Fleming Sam , Baldacchino Francesca , Louis Valentin , Rains Dominik , Garcia Mariano , Del Bon Espírito-Santo Fernando , Roitman Iris , Pacheco-Pascagaza Ana María , Gou Yaqing , Roberts John , Barrett Kirsten , Ferreira Laerte Guimaraes , Shimbo Julia Zanin , Alencar Ane , Bustamante Mercedes , Woodhouse Iain Hector , Eyji Sano Edson , Ometto Jean Pierre , Tansey Kevin , Balzter Heiko
Published: August 2020

The tropical savanna in Brazil known as the Cerrado covers circa 23% of the Brazilian territory, but only 3% of this area is protected. High rates of deforestation and degradation in the woodland and forest areas have made the Cerrado the second-largest source of carbon emissions in Brazil. However, data on these emissions are highly uncertain because of the spatial and temporal variability of the aboveground biomass (AGB) in this biome. Remote-sensing data combined with local vegetation inventories provide the means to quantify the AGB at large scales. Here, we quantify the spatial distribution of woody AGB in the Rio Vermelho watershed, located in the centre of the Cerrado, at a high spatial resolution of 30 metres, with a random forest (RF) machine-learning approach. We produced the first high-resolution map of the AGB for a region in the Brazilian Cerrado using a combination of vegetation inventory plots, airborne light detection and ranging (LiDAR) data, and multispectral and radar satellite images (Landsat 8 and ALOS-2/PALSAR-2). A combination of random forest (RF) models and jackknife analyses enabled us to select the best remote-sensing variables to quantify the AGB on a large scale. Overall, the relationship between the ground data from vegetation inventories and remote-sensing variables was strong (R2 = 0.89), with a root-mean-square error (RMSE) of 7.58 Mg ha−1 and a bias of 0.43 Mg ha−1.
Evaluating a Suitable Aquaculture Site Selection Model for Cobia (Rachycentron canadum) during Extreme Events in the Inner Bay of the Penghu Islands, Taiwan
Authors: Wu Yan-Lun , Lee Ming-An , Chen Lu-Chi , Chan Jui-Wen , Lan Kuo-Wei
Published: August 2020

Despite numerous studies on the effect of a cold weather disaster on fisheries in 2008, no operational systems have been developed to monitor the threat of such an event to mariculturists in the Penghu Islands (PHI) region of Taiwan. The present study employed a suitable aquaculture site selection map of the inner bay of the PHI to reduce aquaculture losses and mortality rates of cobia (Rachycentron canadum) during extreme events. Daily marine environmental data, including sea surface temperature (SST), chlorophyll-a concentration (chl-a), and wind speed in the winter, were collected. An extreme event was defined as a period of over 11 days in a month of strong winds (>6 m/s). Four parameters in the PHI inner bay, including SST, cold-water intrusion days, chl-a, and offshore distance to the PHI coastline, were used to evaluate suitable aquaculture sites for cobia culture. The results indicated that La Niña events could not be used as a factor to detect cold-water intrusion events and select suitable aquaculture sites in the PHI. The evaluated suitable aquaculture site selection map, obtained using an arithmetic mean model and a geometric mean model, revealed that the avoidance sites during extreme events were concentrated in the northern and northwestern PHI. Suitable areas were concentrated in the southeastern areas. We further suggested that commercial cobia aquaculture operations in the PHI inner bay could be moved to the suitable sites in southeastern PHI during extreme events.
An Effective Lunar Crater Recognition Algorithm Based on Convolutional Neural Network
Authors: Wang Song , Fan Zizhu , Li Zhengming , Zhang Hong , Wei Chao
Published: August 2020

The lunar crater recognition plays a key role in lunar exploration. Traditional crater recognition methods are mainly based on the human observation that is usually combined with classical machine learning methods. These methods have some drawbacks, such as lacking the objective criterion. Moreover, they can hardly achieve desirable recognition results in small or overlapping craters. To address these problems, we propose a new convolutional neural network termed effective residual U-Net (ERU-Net) to recognize craters from lunar digital elevation model (DEM) images. ERU-Net first detects crater edges in lunar DEM data. Then, it uses template matching to compute the position and size of craters. ERU-Net is based on U-Net and uses the residual convolution block instead of the traditional convolution, which combines the advantages of U-Net and residual network. In ERU-Net, the size of the input image is the same as that of the output image. Since our network uses residual units, the training process of ERU-Net is simple, and the proposed model can be easily optimized. ERU-Net gets better recognition results when its network structure is deepened. The method targets at the rim of the crater, and it can recognize overlap craters. In theory, our proposed network can recognize all kinds of impact craters. In the lunar crater recognition, our model achieves high recall (83.59%) and precision (84.80%) on DEM. The recall of our method is higher than those of other deep learning methods. The experiment results show that it is feasible to exploit our network to recognize craters from the lunar DEM.
A Monitoring System for Online Fault Detection and Classification in Photovoltaic Plants
Authors: Lazzaretti André Eugênio , Costa Clayton Hilgemberg da , Rodrigues Marcelo Paludetto , Yamada Guilherme Dan , Lexinoski Gilberto , Moritz Guilherme Luiz , Oroski Elder , Goes Rafael Eleodoro de , Linhares Robson Ribeiro , Stadzisz Paulo Cézar , Omori Júlio Shigeaki , Santos Rodrigo Braun dos
Published: August 2020

Photovoltaic (PV) energy use has been increasing recently, mainly due to new policies all over the world to reduce the application of fossil fuels. PV system efficiency is highly dependent on environmental variables, besides being affected by several kinds of faults, which can lead to a severe energy loss throughout the operation of the system. In this sense, we present a Monitoring System (MS) to measure the electrical and environmental variables to produce instantaneous and historical data, allowing to estimate parameters that ar related to the plant efficiency. Additionally, using the same MS, we propose a recursive linear model to detect faults in the system, while using irradiance and temperature on the PV panel as input signals and power as output. The accuracy of the fault detection for a 5 kW power plant used in the test is 93.09%, considering 16 days and around 143 hours of faults in different conditions. Once a fault is detected by this model, a machine-learning-based method classifies each fault in the following cases: short-circuit, open-circuit, partial shadowing, and degradation. Using the same days and faults applied in the detection module, the accuracy of the classification stage is 95.44% for an Artificial Neural Network (ANN) model. By combining detection and classification, the overall accuracy is 92.64%. Such a result represents an original contribution of this work, since other related works do not present the integration of a fault detection and classification approach with an embedded PV plant monitoring system, allowing for the online identification and classification of different PV faults, besides real-time and historical monitoring of electrical and environmental parameters of the plant.
Joint Demosaicing and Denoising Based on Interchannel Nonlocal Mean Weighted Moving Least Squares Method
Authors: Kim Yeahwon , Ryu Hohyung , Lee Sunmi , Lee Yeon Ju
Published: August 2020

Nowadays, the sizes of pixel sensors in digital cameras are decreasing as the resolution of the image sensor increases. Due to the decreased size, the pixel sensors receive less light energy, which makes it more sensitive to thermal noise. Even a small amount of noise in the color filter array (CFA) can have a significant effect on the reconstruction of the color image, as two-thirds of the missing data would have to be reconstructed from noisy data; because of this, direct denoising would need to be performed on the raw CFA to obtain a high-resolution color image. In this paper, we propose an interchannel nonlocal weighted moving least square method for the noise removal of the raw CFA. The proposed method is our first attempt of applying a two dimensional (2-D) polynomial approximation to denoising the CFA. Previous works make use of 2-D linear or directional 1-D polynomial approximations. The reason that 2-D polynomial approximation methods have not been applied to this problem is the difficulty of the weight control in the 2-D polynomial approximation method, as a small amount of noise can have a large effect on the approximated 2-D shape. This makes CFA denoising more important, as the approximated 2-D shape has to be reconstructed from only one-third of the original data. To address this problem, we propose a method that reconstructs the approximated 2-D shapes corresponding to the RGB color channels based on the measure of the similarities of the patches directly on the CFA. By doing so, the interchannel information is incorporated into the denoising scheme, which results in a well-controlled and higher order of polynomial approximation of the color channels. Compared to other nonlocal-mean-based denoising methods, the proposed method uses an extra reproducing constraint, which guarantees a certain degree of the approximation order; therefore, the proposed method can reduce the number of false reconstruction artifacts that often occur in nonlocal-mean-based denoising methods. Experimental results demonstrate the performance of the proposed algorithm.
A New Real-Time Pinch Detection Algorithm Based on Model Reference Kalman Prediction and SRMS for Electric Adjustable Desk
Authors: Gu Minming , Wei Yajie , Pan Haipeng , Ying Yujia
Published: August 2020

This paper presents a new algorithm based on model reference Kalman torque prediction algorithm combined with the sliding root mean square (SRMS). It is necessary to improve the accuracy and reliability of the pinch detection for avoiding collision with the height adjustable desk and accidents on users. Motors need to regulate their position and speed during the operation using different voltage by PWM (Pulse Width Modulation) to meet the requirement of position synchronization. It causes much noise and coupling information in the current sampling signal. Firstly, to analyze the working principle of an electric height adjustable desk control system, a system model is established with consideration of the DC (Direct Current) motor characteristics and the coupling of the system. Secondly, to precisely identify the load situation, a new model reference Kalman perdition method is proposed. The load torque signal is selected as a pinch state variable of the filter by comparing the current signal. Thirdly, to meet the need of the different loads of the electric table, the sliding root means square (SRMS) of the torque is proposed to be the criterion for threshold detection. Finally, to verify the effectiveness of the algorithm, the experiments are carried out in the actual system. Experimental results show that the algorithm proposed in this paper can detect the pinched state accurately under different load conditions.
Stochastic Power Consumption Model of Wireless Transceivers
Authors: Kryszkiewicz Paweł , Kliks Adrian , Kułacz Łukasz , Bossy Bartosz
Published: August 2020

Energy efficiency is a key aspect when designing and optimizing contemporary wireless networks and transceivers. Assessment of energy efficiency requires proper energy consumption models. The most common solutions are to measure a single device and propose a device-specific model or to propose a simplified model for many transceivers but not reflecting all phenomena visible in a given transceiver energy consumption. Therefore, it has to be selected to accurately model a single transceiver or coarsely model a wide group of transceivers. This paper proposes a new approach, where a fixed energy consumption model is used but with parameters being random variables. This reflects variability between various transceivers from various vendors. First the model parameters are adjusted separately for each of 14 measured WiFi modems. These devices are treated as samples of a wider population of devices and their parameters are used for stochastic parameters modeling, i.e., choosing the random variables’ distributions, their parameters, and the correlation among parameters. The proposed model can be used, e.g., for system-level network design where variability among transceivers power consumption can be used as a new degree of freedom. The paper presents simulation results for a simple multi-hop link whose energy consumption is characterized in much more detail thanks to the proposed stochastic power consumption model.
Lab-On-Fiber Technology: A Roadmap toward Multifunctional Plug and Play Platforms
Authors: Pisco Marco , Cusano Andrea
Published: August 2020

This review presents an overview of the “lab-on-fiber technology” vision and the main milestones set in the technological roadmap to achieve the ultimate objective of developing flexible, multifunctional plug and play fiber-optic platforms designed for specific applications. The main achievements, obtained with nanofabrication strategies for unconventional substrates, such as optical fibers, are discussed here. The perspectives and challenges that lie ahead are highlighted with a special focus on full spatial control at the nanoscale and high-throughput production scenarios. The rapid progress in the fabrication stage has opened new avenues toward the development of multifunctional plug and play platforms, discussed here with particular emphasis on new functionalities and unparalleled figures of merit, to demonstrate the potential of this powerful technology in many strategic application scenarios. The paper also analyses the benefits obtained from merging lab-on-fiber (LOF) technology objectives with the emerging field of optomechanics, especially at the microscale and the nanoscale. We illustrate the main advances at the fabrication level, describe the main achievements in terms of functionalities and performance, and highlight future directions and related milestones. All achievements reviewed and discussed clearly suggest that LOF technology is much more than a simple vision and could play a central role not only in scenarios related to diagnostics and monitoring but also in the Information and Communication Technology (ICT) field, where optical fibers have already yielded remarkable results.
Images of Roman Imperial Denarii: A Curated Data Set for the Evaluation of Computer Vision Algorithms Applied to Ancient Numismatics, and an Overview of Challenges in the Field
Authors: Arandjelović Ognjen , Zachariou Marios
Published: August 2020

Automatic ancient Roman coin analysis only recently emerged as a topic of computer science research. Nevertheless, owing to its ever-increasing popularity, the field is already reaching a certain degree of maturity, as witnessed by a substantial publication output in the last decade. At the same time, it is becoming evident that research progress is being limited by a somewhat veering direction of effort and the lack of a coherent framework which facilitates the acquisition and dissemination of robust, repeatable, and rigorous evidence. Thus, in the present article, we seek to address several associated challenges. To start with, (i) we provide a first overview and discussion of different challenges in the field, some of which have been scarcely investigated to date, and others which have hitherto been unrecognized and unaddressed. Secondly, (ii) we introduce the first data set, carefully curated and collected for the purpose of facilitating methodological evaluation of algorithms and, specifically, the effects of coin preservation grades on the performance of automatic methods. Indeed, until now, only one published work at all recognized the need for this kind of analysis, which, to any numismatist, would be a trivially obvious fact. We also discuss a wide range of considerations which had to be taken into account in collecting this corpus, explain our decisions, and describe its content in detail. Briefly, the data set comprises 100 different coin issues, all with multiple examples in Fine, Very Fine, and Extremely Fine conditions, giving a total of over 650 different specimens. These correspond to 44 issuing authorities and span the time period of approximately 300 years (from 27 BC until 244 AD). In summary, the present article should be an invaluable resource to researchers in the field, and we encourage the community to adopt the collected corpus, freely available for research purposes, as a standard evaluation benchmark.
Environmental Education in the Preparation of Students of Tourism and Finance and Management in the Czech Republic
Authors: Krpálek Pavel , Berková Kateřina , Krpálková Krelová Katarína , Kubišová Andrea , Frendlovská Dagmar , Szabo Stanislav
Published: August 2020

Higher education includes space for creating cross-cutting competence profiles of future professionals aimed at addressing key sustainability challenges in increasingly complex and global contexts. The research seeks to identify and evaluate the level of engagement in environmental education in study programmes at a career-oriented higher education institution in the Czech Republic. The research sample consisted of 3680 students of the Tourism and Finance and Management study programmes of the College of Polytechnics Jihlava, who participated in work placements in the course of their studies. An educational analysis was applied for qualitative research and evaluation of the level of implementation of the environmental educational component. Quantitative research was based on a questionnaire method, with tests to verify hypotheses being performed at a significance level of 5%. It was proven that the inclusion of an environmental component was influenced by the study programme. This influence was confirmed for the Tourism study programme, while for Finance and Management it was not verified. The environmental component in the Tourism study programme is developed through work placements; however, with regards to major study subjects taught, qualitative research analysing the inclusion of environmental aspects in these subjects proved the opposite. The Finance and Management study programme does not currently use the potential for environmental education development. The research revealed certain drawbacks and uncovered the potential to streamline environmental education at the career-oriented higher education institution.
A Hybrid MADM Model for Product Design Evaluation and Improvement
Authors: Chen Tien-Li , Chen Chin-Chuan , Chuang Yen-Ching , Liou James J. H.
Published: August 2020

Global warming and climate change are the most pressing issues in the world. This is the inevitable result of human beings pursuing a better quality of life and materials. If the green design concept is used in the design and manufacture of products, the impact of production on the environment will be greatly reduced. Because of this, green product design assessment and improvement activities play an important role in achieving the 2030 sustainable development goals. Product design is the forefront of the entire product development process, and it plays a very critical role. The purpose of this study is to develop a decision-making model for helping decision makers to evaluate and improve the performance of product design systematically. The model combines the design standard of the iF world design guide and multi-attribute decision-making methods. First, the DEMATEL-based analytic network process is used to establish the influential relationship and weights of attributes. Next, the VlseKriterijumska Optimizacija I Kompromisno with aspiration-level method is used to obtain the gap between each evaluation attribute and the aspiration level of each design. Finally, this evaluation result uses the influential network relationship map (INRM) to propose various improvement strategies with causal influence. This study uses products from a Taiwanese furniture design company as an empirical case, which is a leading brand and benchmark in Taiwan’s furniture industry. The research results show that the proposed model can help decision makers to choose the most appropriate design scheme (i.e., the design with the smallest gap from expectations); designers can also improve the gap between product design and expectations.
A Large-Scale Nature-Based Solution in Agriculture for Sustainable Water Management: The Lake Karla Case
Authors: Panagopoulos Yiannis , Dimitriou Elias
Published: August 2020

This study demonstrates a new nature-based solution (NBS) project in agriculture, the ‘Karla’ reservoir in Central Greece, a unique example at European scale, of a lake ecosystem which was dried and is now restored with the purpose to maximize the efficiency of water provision in agriculture and biodiversity enhancement. In this article, we present: (a) The historical developments from the existence of the old natural Lake Karla until the reconstruction of the homonymous artificial reservoir, (b) the environmental and economic benefits that the new project delivers, and (c) the governance and management mechanisms that can ensure the efficient operation of the project. The analysis shows that the reconstructed Lake Karla can serve as a multi-purpose project to combat water scarcity, achieving a twofold crop yield production and respective agricultural income in the surrounding area, securing the coverage of the water supply needs of the closest city, improving the status of groundwater resources, developing a natural shelter for biodiversity and emerging recreation and touristic opportunities. At the same time, its construction and operation costs can be recovered, and the proposed governance plan can ensure the viability of the whole project inspiring similar multi-purpose water retention projects for investment in agriculture and the environment in southern Europe but also in other water scarce regions.
An Experimental Investigation of the Hydraulics and Pollutant Dispersion Characteristics of a Model Beaver Dam
Authors: Hart James , Rubinato Matteo , Lavers Tom
Published: August 2020

Beavers have influenced the world’s ecosystem for millions of years. Their dams create ponds and wetlands that provide a large range of hydraulic and ecological benefits to the natural world, including mitigation against flooding and improving water quality. As beavers are now being reintroduced to many parts of the world, it is important to fully understand the impact of their dams on the flow characteristics of the water-courses on which they are built. This paper investigates the relationship between the physical properties of a model beaver dam and its fundamental hydraulics and pollutant dispersion characteristics. The first objective of this paper was to develop a modelling framework to relate discharge to flow-depth for dams with a combination of porous and impermeable sections. The second objective was to utilize a similar framework to predict the down-stream concentration distribution of an up-stream pollution event passing through such systems. The ability to model these parameters for dams with variable lengths of porous and impermeable sections is important as the porosity of beaver dams can vary with depth, depending on which sections are constructed from branches, rocks, or compacted mud. The analysis and modelling developed in this paper show that a single, general relationship can be obtained between discharge and flow-depth regardless of the presence of sections that are both porous or impermeable, provided the relative depths of these sections are known and accounted for. It is also shown that the Nominal Residence Time and the Advection Dispersion Equation can be used to predict pollutant transport in such systems. These two equations have previously been shown to have limitations when applied to some complex systems, so demonstrating they can be applied to a porous dam with combinations of porous and impermeable sections at the relative discharges investigated is noteworthy.
The Relationship between Soil Moisture and Soil Water Repellency Persistence in Hydrophobic Soils
Authors: Bayad Mohamed , Chau Henry Wai , Trolove Stephen , Moir Jim , Condron Leo , Bouray Moussa
Published: August 2020

In this work, we modelled the response of soil water repellency (SWR) persistence to the decrease in moisture in drying soils, and we explored the implication of soil particle size distribution and specific surface area on the SWR severity and persistence. A new equation for the relationship between SWR persistence and soil moisture (θ) is described in this paper. The persistence of SWR was measured on ten different hydrophobic soils using water drop penetration time (WDPT) at decreasing levels of gravimetric water content. The actual repellency persistence showed a sigmoidal response to soil moisture decrease, where Ra(θ)=Rp/1+eδ(θ−θc). The suggested equation enables one to model the actual SWR persistence (Ra) using θ, the potential repellency (Rp) and two characteristic parameters related to the shape of the response curve. The two parameters are the critical soil moisture θc, where the Ra increase rate reaches its maximum, and the parameter δ affecting the steepness of the curve at the inflexion point of the sigmoidal curve. Data shows that both soil carbon and texture are controlling the potential SWR in New Zealand pastures.
Evaluation of Irrigation Water Resources Availability and Climate Change Impacts—A Case Study of Mwea Irrigation Scheme, Kenya
Authors: Akoko George , Kato Tasuku , Tu Le Hoang
Published: August 2020

Rice is an important cereal crop in Kenya, where it is mainly grown in the Mwea Irrigation Scheme, MIS. The serious challenges of MIS include low water use efficiency and limited available water resources. The objective of this study is to analyze the current and future irrigation water resource availability for the improvement of future water management. A Soil Water Assessment Tool (SWAT), a public domain software supported by the United States Department of Agriculture’s Agricultural Research Service in Bushland, TX, USA, was used to estimate the current and future water resources availability from the MIS’s main irrigation water supply sources (River Thiba and River Nyamindi). CropWat, a computer program developed by the Land and Water Division of the Food and Agriculture Organization (FAO), Rome, Italy, was used to estimate irrigation water requirements from 2013–2016 and into the future (2020–2060 and 2061–2099). Future climatic data for total available flow and irrigation requirement estimations were downloaded from three General Circulation Models (GCMs). The data was bias corrected and down-scaled (with observed data) using a Climate Change Toolkit, a toolkit for climate change analysis developed by the Water Weather and Energy Ecosystem, Zurich, Switzerland. The results indicated that the highest irrigation water deficits were experienced in July and August based on the existing cropping pattern. Under a proposed future pattern, estimates show that MIS will experience water deficits mainly from June to October and from January to February. This study recommends that MIS management should put into strong consideration the simulated future estimates in irrigation water availability for the improvement of water management.
Optimal Strategy to Tackle a 2D Numerical Analysis of Non-Uniform Flow over Artificial Dune Regions: A Comparison with Bibliography Experimental Results
Authors: Ahn Jungkyu , Lee Jaelyong , Park Sung Won
Published: August 2020

Flow simulation over a dune requires the proper input of roughness coefficients. This study analyzed a numerical simulation of open-channel turbulent flow over two-dimensional fixed dunes to reveal the effect of roughness on the dune bottom, and to determine the optimized combination of the turbulence scheme and the roughness height formula. The most appropriate roughness values and turbulence models were applied using Reynolds-averaged Navier–Stokes models. Seven methods were chosen to estimate the bed roughness properties at the inlet boundary section. The results of all cases calculated with the OpenFOAM toolbox were compared with laboratory experimental data for model validation. The performances of all bed roughness variations were evaluated according to the stream-wise and depth-wise directions with nondimensional values. Consequently, it was revealed that the combination of bottom roughness length scale at the inlet boundary and the k-ω shear-stress transport (SST) model was the most suitable for the flow separation zone and turbulent properties near the channel bottom.