bluuebunny/crossref_metadata_2025 huggingface dataset:
Nano Hard Carbon Anodes for Sodium-Ion Batteries
Authors: Kim Dae-Yeong , Kim Dong-Hyun , Kim Soo-Hyun , Lee Eun-Kyung , Park Sang-Kyun , Lee Ji-Woong , Yun Yong-Sup , Choi Si-Young , Kang Jun
Published: May 2019

A hindrance to the practical use of sodium-ion batteries is the lack of adequate anode materials. By utilizing the co-intercalation reaction, graphite, which is the most common anode material of lithium-ion batteries, was used for storing sodium ion. However, its performance, such as reversible capacity and coulombic efficiency, remains unsatisfactory for practical needs. Therefore, to overcome these drawbacks, a new carbon material was synthesized so that co-intercalation could occur efficiently. This carbon material has the same morphology as carbon black; that is, it has a wide pathway due to a turbostratic structure, and a short pathway due to small primary particles that allows the co-intercalation reaction to occur efficiently. Additionally, due to the numerous voids present in the inner amorphous structure, the sodium storage capacity was greatly increased. Furthermore, owing to the coarse co-intercalation reaction due to the surface pore structure, the formation of solid-electrolyte interphase was greatly suppressed and the first cycle coulombic efficiency reached 80%. This study shows that the carbon material alone can be used to design good electrode materials for sodium-ion batteries without the use of next-generation materials.
Probiotic Lactobacillus casei: Effective for Managing Childhood Diarrhea by Altering Gut Microbiota and Attenuating Fecal Inflammatory Markers
Authors: Lai Hung-Hsiang , Chiu Cheng-Hsun , Kong Man-Shan , Chang Chee-Jen , Chen Chien-Chang
Published: May 2019

Background: Acute diarrhea is a major cause of childhood morbidity and an economic burden for families. The aim of this study is to explore the effect of probiotics on clinical symptoms, intestinal microbiota, and inflammatory markers during childhood diarrhea. Methods: Children (n = 81) aged six months to six years (mean age 2.31 years) hospitalized for acute diarrhea were randomized to receive probiotics (Lactobacillus casei variety rhamnosus; n = 42) or no probiotics (n = 39) orally twice daily for seven days. Feces samples were also collected to evaluate microbial content using a traditional agar plate and next-generation sequencing. Immunoglobulin A (IgA), lactoferrin, and calprotectin were determined by enzyme-linked immunosorbent assay (ELISA) and compared in different groups. Other clinical symptoms or signs, including fever, vomiting, diarrhea, abdominal pain, bloated abdomen, daily intake, appetite, and body weight were also assessed. Results: Data were collected from 81 individuals across three different time points. Total fecal IgA levels in fecal extracts of the probiotics group were higher than those in the control group, reaching statistical significance (p < 0.05). Concentrations of fecal lactoferrin and calprotectin were significantly downregulated in patients with probiotic Lactobacillus casei variety rhamnosus (Lc) consumption compared to those of the control (p < 0.05). Probiotic Lc administration may be beneficial for gut-microbiota modulation, as shown by the data collected at one week after enrollment. Counts of Bifidobacteria and Lactobacillus species were elevated in stool culture of the probiotic group. Appetite and oral intake, body-weight gain, abdominal pain, bloating, as well as bowel habits (diarrhea) were much better in children receiving probiotics compared with those in the control group. Conclusion: Fecal IgA increased during acute diarrhea under Lc treatment; in contrast, fecal lactoferrin and calprotectin were downregulated during acute diarrhea under Lc treatment. Probiotic Lc may be a useful supplement for application in children during acute diarrhea to reduce clinical severity and intestinal inflammatory reaction.
Satiating Effect of a Ketogenic Diet and Its Impact on Muscle Improvement and Oxidation State in Multiple Sclerosis Patients
Authors: Benlloch María , López-Rodríguez María Mar , Cuerda-Ballester María , Drehmer Eraci , Carrera Sandra , Ceron Jose Joaquin , Tvarijonaviciute Asta , Chirivella Javier , Fernández-García David , de la Rubia Ortí Jose Enrique
Published: May 2019

Background: It was previously established that Multiple sclerosis (MS) generates energy alterations at the mitochondrial level related to the loss of muscle mass. Ketone bodies, mainly beta-hydroxybutyrate (BHB), re-establish this energy alteration causing satiety, changes in body composition and a decrease in hormone-dependant hunger, such as ghrelin. The aim of this study was to establish possible improvements in body composition and the level of oxidation in patients with MS, by means of the satiating effect of a ketogenic diet. Methods: A pilot study was carried out with 27 MS patients who were given a Mediterranean isocaloric and ketogenic diet for 4 months. Anthropometric measurements, as well as satiety and hunger perception (VAS scale), were taken. In addition, BHB and paraoxonase 1 (PON1), as an oxidation marker, were measured by spectrophotometric automated assays, and ghrelin was determined by an enzyme immunoassay in the serum. All measurements were taken before and after the intervention. Results: A significant increase in satiety perception at lunch and dinner and of BHB in the blood was obtained. Hunger perception decreased significantly at lunch and dinner with similar levels of ghrelin. In addition, an important increase in lean mass and PON1 was observed. To our knowledge, this is the first study addressing improvements in body composition, oxidation state and metabolism in MS patients, based on the satiating effect of a Mediterranean isocaloric diet. Conclusion: A ketogenic diet increases lean mass and decreases inflammation and oxidation possibly as a consequence of an increase in satiety and decrease in hunger in MS patients.
Innovative Techniques of Processing Human Milk to Preserve Key Components
Authors: Wesolowska Aleksandra , Sinkiewicz-Darol Elena , Barbarska Olga , Bernatowicz-Lojko Urszula , Borszewska-Kornacka Maria Katarzyna , van Goudoever Johannes B.
Published: May 2019

Human milk not only contains all nutritional elements that an infant requires, but is also the source of components whose regulatory role was confirmed by demonstrating health-related deficiencies in formula-fed children. A human milk diet is especially important for premature babies in the neonatal intensive care unit (NICU). In cases where breastfeeding is not possible and the mother’s own milk is insufficient in volume, the most preferred food is pasteurized donor milk. The number of human milk banks has increased recently but their technical infrastructure is continuously developing. Heat treatment at a low temperature and long time, also known as holder pasteurization (62.5 °C, 30 min), is the most widespread method of human milk processing, whose effects on the quality of donor milk is well documented. Holder pasteurization destroys vegetative forms of bacteria and most viruses including human immunodeficiency virus (HIV) herpes and cytomegalovirus (CMV). The macronutrients remain relatively intact but various beneficial components are destroyed completely or compromised. Enzymes and immune cells are the most heat sensitive elements. The bactericidal capacity of heat-pasteurized milk is lower than that of untreated milk. The aim of the study was for a comprehensive comparison of currently tested methods of improving the preservation stage. Innovative techniques of milk processing should minimize the risk of milk-borne infections and preserve the bioactivity of this complex biological fluid better than the holder method. In the present paper, the most promising thermal pasteurization condition (72 °C–75 °C,) and a few non-thermal processes were discussed (high pressure processing, microwave irradiation). This narrative review presents an overview of methods of human milk preservation that have been explored to improve the safety and quality of donor milk.
Established and Emerging Strategies for Drug Delivery Across the Blood-Brain Barrier in Brain Cancer
Authors: Parodi Alessandro , Rudzińska Magdalena , Deviatkin Andrei , Soond Surinder , Baldin Alexey , Zamyatnin Andrey
Published: May 2019

Brain tumors are characterized by very high mortality and, despite the continuous research on new pharmacological interventions, little therapeutic progress has been made. One of the main obstacles to improve current treatments is represented by the impermeability of the blood vessels residing within nervous tissue as well as of the new vascular net generating from the tumor, commonly referred to as blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB), respectively. In this review, we focused on established and emerging strategies to overcome the blood-brain barrier to increase drug delivery for brain cancer. To date, there are three broad strategies being investigated to cross the brain vascular wall and they are conceived to breach, bypass, and negotiate the access to the nervous tissue. In this paper, we summarized these approaches highlighting their working mechanism and their potential impact on the quality of life of the patients as well as their current status of development.
Effect of Organic Inputs and Solarization for the Suppression of Rhizoctonia solani in Woody Ornamental Plant Production
Authors: Baysal-Gurel Fulya , Kabir Md Niamul , Liyanapathiranage Prabha
Published: May 2019

Soilborne diseases are the most economically significant problem faced by Southern region nursery producers. The goal of this research was to improve Rhizoctonia root rot disease management through the use of soil solarization alone and in combination with biofumigant cover crops—arugula ‘Astro’ (Eruca vesicaria ssp. sativa), mustard green ‘Amara’ (Brassica carinata), and turnip ‘Purple top forage’ (B. rapa); good quality compost and mustard meal amendment. The experiments were established as on-farm trials in 2016 and 2017 with prevalent Rhizoctonia solani population in propagation beds. All three biofumigant cover crops, arugula ‘Astro’, mustard green ‘Amara’, and turnip ‘Purple top forage’ in combination with solarization were able to reduce the Rhizoctonia root rot in flowering cherry ‘Kwanzan’ plants in nursery propagation beds. Compost amendment increased the flowering cherry rooted cuttings growth (plant weight, root weight, and plant height) compared to other treatments. Soil solarization in combination with cover crops and organic inputs could be used as part of an integrated approach to manage Rhizoctonia root rot in nursery crop propagation beds.
A Scenario-Based Optimization Model for Planning Sustainable Water-Resources Process Management under Uncertainty
Authors: Miao Hongchang , Li Donglin , Zuo Qiting , Yu Lei , Fei Xiaoxia , Hao Lingang
Published: May 2019

Discrepancies between water demand and supply are intensifying and creating a need for sustainable water resource process management associated with rapid economic development, population growth, and urban expansion. In this study, a scenario-based interval fuzzy-credibility constrained programming (SIFCP) method is developed for planning a water resource management system (WRMS) that can handle uncertain information by using interval values, fuzzy sets, and scenario analysis. The SIFCP-WRMS model is then applied to plan the middle route of the South-to-North Water Diversion Project (SNWDP) in Henan Province, China. Solutions of different water distribution proportion scenarios and varied credibility levels are considered. Results reveal that different water-distribution proportion scenarios and uncertainties used in the SIFCP-WRMS model can lead to changed water allocations, sewage discharges, chemical oxygen demand (COD) emissions, and system benefits. Results also indicate that the variation of scenarios (i.e., from S2 to S3) can result in a change of 9% over the planning horizon for water allocation in the industrial sector. Findings can help decision-makers resolve conflicts among economic objective, water resource demand, and sewage discharge, as well as COD emissions.
A Methodology to Monitor Urban Expansion and Green Space Change Using a Time Series of Multi-Sensor SPOT and Sentinel-2A Images
Authors: Deng Jinsong , Huang Yibo , Chen Binjie , Tong Cheng , Liu Pengbo , Wang Hongquan , Hong Yang
Published: May 2019

Monitoring urban expansion and greenspace change is an urgent need for planning and decision-making. This paper presents a methodology integrating Principal Component Analysis (PCA) and hybrid classifier to undertake this kind of work using a sequence of multi-sensor SPOT images (SPOT-2,3,5) and Sentinel-2A data from 1996 to 2016 in Hangzhou City, which is the central metropolis of the Yangtze River Delta in China. In this study, orthorectification was first applied on the SPOT and Sentinel-2A images to guarantee precise geometric correction which outperformed the conventional polynomial transformation method. After pre-processing, PCA and hybrid classifier were used together to enhance and extract change information. Accuracy assessment combining stratified random and user-defined plots sampling strategies was performed with 930 reference points. The results indicate reasonable high accuracies for four periods. It was further revealed that the proposed method yielded higher accuracy than that of the traditional post-classification comparison approach. On the whole, the developed methodology provides the effectiveness of monitoring urban expansion and green space change in this study, despite the existence of obvious confusions that resulted from compound factors.
The Comparison of Different Methods of Texture Analysis for Their Efficacy for Land Use Classification in Satellite Imagery
Authors: Kupidura Przemysław
Published: May 2019

The paper presents a comparison of the efficacy of several texture analysis methods as tools for improving land use/cover classification in satellite imagery. The tested methods were: gray level co-occurrence matrix (GLCM) features, Laplace filters and granulometric analysis, based on mathematical morphology. The performed tests included an assessment of the classification accuracy performed based on spectro-textural datasets: spectral images with the addition of images generated using different texture analysis methods. The class nomenclature was based on spectral and textural differences and included the following classes: water, low vegetation, bare soil, urban, and two (coniferous and deciduous) forest classes. The classification accuracy was assessed using the overall accuracy and kappa index of agreement, based on the reference data generated using visual interpretation of the images. The analysis was performed using very high-resolution imagery (Pleiades, WorldView-2) and high-resolution imagery (Sentinel-2). The results show the efficacy of selected GLCM features and granulometric analysis as tools for providing textural data, which could be used in the process of land use/cover classification. It is also clear that texture analysis is generally a more important and effective component of classification for images of higher resolution. In addition, for classification using GLCM results, the Random Forest variable importance analysis was performed.
Long-Term Monitoring of Cropland Change near Dongting Lake, China, Using the LandTrendr Algorithm with Landsat Imagery
Authors: Zhu Lihong , Liu Xiangnan , Wu Ling , Tang Yibo , Meng Yuanyuan
Published: May 2019

Tracking cropland change and its spatiotemporal characteristics can provide a scientific basis for assessments of ecological restoration in reclamation areas. In 1998, an ecological restoration project (Converting Farmland to Lake) was launched in Dongting Lake, China, in which original lake areas reclaimed for cropland were converted back to lake or to poplar cultivation areas. This study characterized the resulting long-term (1998–2018) change patterns using the LandTrendr algorithm with Landsat time-series data derived from the Google Earth Engine (GEE). Of the total cropland affected, ~447.48 km2 was converted to lake and 499.9 km2 was converted to poplar cultivation, with overall accuracies of 87.0% and 83.8%, respectively. The former covered a wider range, mainly distributed in the area surrounding Datong Lake, while the latter was more clustered in North and West Dongting Lake. Our methods based on GEE captured cropland change information efficiently, providing data (raster maps, yearly data, and change attributes) that can assist researchers and managers in gaining a better understanding of environmental influences related to the ongoing conversion efforts in this region.
Identifying Dry-Season Rice-Planting Patterns in Bangladesh Using the Landsat Archive
Authors: Shew Aaron M. , Ghosh Aniruddha
Published: May 2019

In many countries, in situ agricultural data is not available and cost-prohibitive to obtain. While remote sensing provides a unique opportunity to map agricultural areas and management characteristics, major efforts are needed to expand our understanding of cropping patterns and the potential for remotely monitoring crop production because this could support predictions of food shortages and improve resource allocation. In this study, we demonstrate a new method to map paddy rice using Google Earth Engine (GEE) and the Landsat archive in Bangladesh during the dry (boro) season. Using GEE and Landsat, dry-season rice areas were mapped at 30 m resolution for approximately 90,000 km2 annually between 2014 and 2018. The method first reconstructs spectral vegetation indices (VIs) for individual pixels using a harmonic time series (HTS) model to minimize the effect of any sensor inconsistencies and atmospheric noise, and then combines the time series indices with a rule-based algorithm to identify characteristics of rice phenology to classify rice pixels. To our knowledge, this is the first time an annual pixel-based time series model has been applied to Landsat at the national level in a multiyear analysis of rice. Findings suggest that the harmonic-time-series-based vegetation indices (HTS-VIs) model has the potential to map rice production across fragmented landscapes and heterogeneous production practices with comparable results to other estimates, but without local management or in situ information as inputs. The HTS-VIs model identified 4.285, 4.425, 4.645, 4.117, and 4.407 million rice-producing hectares for 2014, 2015, 2016, 2017, and 2018, respectively, which correlates well with national and district estimates from official sources at an average R-squared of 0.8. Moreover, accuracy assessment with independent validation locations resulted in an overall accuracy of 91% and a kappa coefficient of 0.83 for the boro/non-boro stable rice map from 2014 to 2018. We conclude with a discussion of potential improvements and future research pathways for this approach to spatiotemporal mapping of rice in heterogeneous landscapes.
An Adaptive Framework for Multi-Vehicle Ground Speed Estimation in Airborne Videos
Authors: Li Jing , Chen Shuo , Zhang Fangbing , Li Erkang , Yang Tao , Lu Zhaoyang
Published: May 2019

With the rapid development of unmanned aerial vehicles (UAVs), UAV-based intelligent airborne surveillance systems represented by real-time ground vehicle speed estimation have attracted wide attention from researchers. However, there are still many challenges in extracting speed information from UAV videos, including the dynamic moving background, small target size, complicated environment, and diverse scenes. In this paper, we propose a novel adaptive framework for multi-vehicle ground speed estimation in airborne videos. Firstly, we build a traffic dataset based on UAV. Then, we use the deep learning detection algorithm to detect the vehicle in the UAV field of view and obtain the trajectory in the image through the tracking-by-detection algorithm. Thereafter, we present a motion compensation method based on homography. This method obtains matching feature points by an optical flow method and eliminates the influence of the detected target to accurately calculate the homography matrix to determine the real motion trajectory in the current frame. Finally, vehicle speed is estimated based on the mapping relationship between the pixel distance and the actual distance. The method regards the actual size of the car as prior information and adaptively recovers the pixel scale by estimating the vehicle size in the image; it then calculates the vehicle speed. In order to evaluate the performance of the proposed system, we carry out a large number of experiments on the AirSim Simulation platform as well as real UAV aerial surveillance experiments. Through quantitative and qualitative analysis of the simulation results and real experiments, we verify that the proposed system has a unique ability to detect, track, and estimate the speed of ground vehicles simultaneously even with a single downward-looking camera. Additionally, the system can obtain effective and accurate speed estimation results, even in various complex scenes.
Remotely Sensed Vegetation Indices to Discriminate Field-Grown Olive Cultivars
Authors: Avola Giovanni , Di Gennaro Salvatore Filippo , Cantini Claudio , Riggi Ezio , Muratore Francesco , Tornambè Calogero , Matese Alessandro
Published: May 2019

The application of spectral sensors mounted on unmanned aerial vehicles (UAVs) assures high spatial and temporal resolutions. This research focused on canopy reflectance for cultivar recognition in an olive grove. The ability in cultivar recognition of 14 vegetation indices (VIs) calculated from reflectance patterns (green520–600, red630–690 and near-infrared760–900 bands) and an image segmentation process was evaluated on an open-field olive grove with 10 different scion/rootstock combinations (two scions by five rootstocks). Univariate (ANOVA) and multivariate (principal components analysis—PCA and linear discriminant analysis—LDA) statistical approaches were applied. The efficacy of VIs in scion recognition emerged clearly from all the approaches applied, whereas discrimination between rootstocks appeared unclear. The results of LDA ascertained the efficacy of VI application to discriminate between scions with an accuracy of 90.9%, whereas recognition of rootstocks failed in more than 68.2% of cases.
FSF: Applying Machine Learning Techniques to Data Forwarding in Socially Selfish Opportunistic Networks
Authors: Souza Camilo , Mota Edjair , Soares Diogo , Manzoni Pietro , Cano Juan-Carlos , Calafate Carlos T. , Hernández-Orallo Enrique
Published: May 2019

Opportunistic networks are becoming a solution to provide communication support in areas with overloaded cellular networks, and in scenarios where a fixed infrastructure is not available, as in remote and developing regions. A critical issue, which still requires a satisfactory solution, is the design of an efficient data delivery solution trading off delivery efficiency, delay, and cost. To tackle this problem, most researchers have used either the network state or node mobility as a forwarding criterion. Solutions based on social behaviour have recently been considered as a promising alternative. Following the philosophy from this new category of protocols, in this work, we present our “FriendShip and Acquaintanceship Forwarding” (FSF) protocol, a routing protocol that makes its routing decisions considering the social ties between the nodes and both the selfishness and the device resources levels of the candidate node for message relaying. When a contact opportunity arises, FSF first classifies the social ties between the message destination and the candidate to relay. Then, by using logistic functions, FSF assesses the relay node selfishness to consider those cases in which the relay node is socially selfish. To consider those cases in which the relay node does not accept receipt of the message because its device has resource constraints at that moment, FSF looks at the resource levels of the relay node. By using the ONE simulator to carry out trace-driven simulation experiments, we find that, when accounting for selfishness on routing decisions, our FSF algorithm outperforms previously proposed schemes, by increasing the delivery ratio up to 20%, with the additional advantage of introducing a lower number of forwarding events. We also find that the chosen buffer management algorithm can become a critical element to improve network performance in scenarios with selfish nodes.
The Effect of UVB Irradiation and Oxidative Stress on the Skin Barrier—A New Method to Evaluate Sun Protection Factor Based on Electrical Impedance Spectroscopy
Authors: Hernández Aura Rocio , Vallejo Bibiana , Ruzgas Tautgirdas , Björklund Sebastian
Published: May 2019

Sunlight is vital for several biochemical processes of the skin organ. However, acute or chronic exposure to ultraviolet radiation (UVR) has several harmful effects on the skin structure and function, especially in the case of the failing function of antioxidative enzymes, which may lead to substantial tissue damage due to the increased presence of reactive oxygen species (ROS). The aim of this work was to investigate the combined effect of ultraviolet B (UVB) irradiation and oxidative stress on the skin barrier integrity. For this, we employed electrical impedance spectroscopy (EIS) to characterize changes of the electrical properties of excised pig skin membranes after various exposure conditions of UVB irradiation, oxidative stress, and the inhibition of antioxidative enzymatic processes. The oxidative stress was regulated by adding hydrogen peroxide (H2O2) as a source of ROS, while sodium azide (NaN3) was used as an inhibitor of the antioxidative enzyme catalase, which is naturally present throughout the epidermis. By screening for the combined effect of UVB and oxidative stress on the skin membrane electrical properties, we developed a new protocol for evaluating these parameters in a simple in vitro setup. Strikingly, the results show that exposure to extreme UVB irradiation does not affect the skin membrane resistance, implying that the skin barrier remains macroscopically intact. Likewise, exposure to only oxidative stress conditions, without UVB irradiation, does not affect the skin membrane resistance. In contrast to these observations, the combination of UVB irradiation and oxidative stress conditions results in a drastic decrease of the skin membrane resistance, indicating that the integrity of the skin barrier is compromised. Further, the skin membrane effective capacitance remained more or less unaffected by UVB exposure, irrespective of simultaneous exposure of oxidative stress. The EIS results were concluded to be associated with clear signs of macroscopic tissue damage of the epidermis as visualized with microscopy after exposure to UVB irradiation under oxidative stress conditions. Finally, the novel methodology was tested by performing an assessment of cosmetic sunscreen formulations with varying sun protection factor (SPF), with an overall successful outcome, showing good correlation between SPF value and protection capacity in terms of skin resistance change. The results from this study allow for the development of new skin sensors based on EIS for the detection of skin tissue damage from exposure to UVB irradiation and oxidative stress and provide a new, more comprehensive methodology, taking into account both the influence of UVB irradiation and oxidative stress, for in vitro determination of SPF in cosmetic formulations.
A Lighted Deep Convolutional Neural Network Based Fault Diagnosis of Rotating Machinery
Authors: Ma Shangjun , Cai Wei , Liu Wenkai , Shang Zhaowei , Liu Geng
Published: May 2019

To improve the fault diagnosis performance for rotating machinery, an efficient, noise-resistant end-to-end deep learning (DL) algorithm is proposed based on the advantages of the wavelet packet transform in vibration signal processing (the capability to extract multiscale information and more spectral distribution features) and deep convolutional neural networks (good classification performance, data-driven design and high transfer-learning ability). First, a vibration signal is subjected to pyramid wavelet packet decomposition, and each sub-band coefficient is used as the input for each channel of a deep convolutional network (DCN). Then, based on the lightweight modeling requirements and techniques, a new DCN structure is designed for the fault diagnosis. The proposed algorithm is compared with the support vector machine algorithm and the published DL algorithms based on a bearing dataset produced by Case Western Reserve University. The experimental results show that the proposed algorithm is superior to the existing algorithms in terms of accuracy, memory space, computational complexity, noise resistance, and transfer performance, producing good results.
Data Stream Mining Applied to Maximum Wind Forecasting in the Canary Islands
Authors: Sánchez-Medina Javier J. , Guerra-Montenegro Juan Antonio , Sánchez-Rodríguez David , Alonso-González Itziar G. , Navarro-Mesa Juan L.
Published: May 2019

The Canary Islands are a well known tourist destination with generally stable and clement weather conditions. However, occasionally extreme weather conditions occur, which although very unusual, may cause severe damage to the local economy. The ViMetRi-MAC EU funded project has among its goals, managing climate-change-associated risks. The Spanish National Meteorology Agency (AEMET) has a network of weather stations across the eight Canary Islands. Using data from those stations, we propose a novel methodology for the prediction of maximum wind speed in order to trigger an early alert for extreme weather conditions. The methodology proposed has the added value of using an innovative kind of machine learning that is based on the data stream mining paradigm. This type of machine learning system relies on two important features: models are learned incrementally and adaptively. That means the learner tunes the models gradually and endlessly as new observations are received and also modifies it when there is concept drift (statistical instability), in the modeled phenomenon. The results presented seem to prove that this data stream mining approach is a good fit for this kind of problem, clearly improving the results obtained with the accumulative non-adaptive version of the methodology.
Sliding to Reverse Ableism: An Ethnographic Exploration of (Dis)ability in Sitting Volleyball
Authors: Silva Carla Filomena , Howe P. David
Published: May 2019

This paper illuminates the potential of diversely embodied sporting cultures to challenge ableism, the ideology of ability. Ableism constructs the able body as conditional to a life worth living, thus devaluing all those perceived as ‘dis’-abled. This hegemonic ideology develops into a ‘logic of practice’ through a cultural appropriation of body’s lived complexity, by reducing it to symbolic dichotomies (able/disabled). The path to challenge ableism is then to restore body’s complexity, by turning attention toward its lived embodied existence. Drawing upon an ethnographic study of a sitting volleyball (SV) community, we condense multiple data sources into a sensuous creative non-fiction vignette to translate the physical embodied culture of the sport. In exploring SV physicality through the ethnographic vignette, it is our intention to activate the readers’ own embodiment when interpreting and co-creating this text. By placing the reader in the lived reality of playing SV, we hope that the potential of this physical culture to destabilize engrained ableist premises becomes apparent. Ultimately, our goal is to promote a shift from ableism towards an appreciation and celebration of differently able bodies. This cultural shift is crucial for long lasting social empowerment for people with disabilities.
Heart Rate Variability and Stress Recovery Responses during a Training Camp in Elite Young Canoe Sprint Athletes
Authors: Coelho André , Nakamura Fábio , Morgado Micaela , Holmes Clifton , Di Baldassarre Angela , Esco Michael , Rama Luis
Published: May 2019

Training camps are typical in elite Canoeing preparation, during which, the care to assure adaptation to avoid undesired fatigue is not always present. This study aimed identifying a specific sex response in perceived training loads, recovery and stress balance, and cardiac autonomic responses. Twenty-one elite athletes (11 males and 10 females) of the Portuguese Canoeing National team participated in the investigation. The daily HRV (lnRMSSD) was monitored. The (RESTQ-52) questionnaire was used to access the recovery and stress state. The 10-day training camp was composed of two consecutive 5-day periods (P1 and P2). Data analyses were performed using confidence limits, effect size, and magnitude-based inference. In the females, Session rating of perceived exertion (sRPE), lnRMSSD, and its coefficient of variation did not change between P1 and P2. However, in males, lnRMSSD showed a small reduction from P1 to P2. Also, sRPE was higher in males over the training period, with a possibly small difference at P2. Regarding RESTQ-52, total stress most likely increased with large and very large differences in males and moderate differences in females during the training period. Male canoeists undertook higher perceived training loads than females, with a consequent higher level of total perceived stress and lnRMSSD during a 10-day training camp.
Improved Agricultural Products Drying Through a Novel Double Collector Solar Device
Authors: Camas-Nafate Monica Patricia , Alvarez-Gutiérrez Peggy , Valenzuela-Mondaca Edgar , Castillo-Palomera Roger , Perez-Luna Yolanda del Carmen
Published: May 2019

Backyard agricultural systems are frequently used for food production in rural tropical regions all over the world. The implementation of these systems has been used as a strategy to increase food security, to preserve the phyto and zoo diversity and to provide an alternative income for poorer rural families. Nevertheless, the absence of appropriate preservation mechanisms and nonrenewable energies can lead to significant production losses that could be prevented by the implementation of solar drying devices. The objective of this project was to design, build and validate a double collector solar device for improved drying performance. To evaluate the double collector solar device, four backyard products frequently used in the Mexico Southwest regional diet were used: carrots, chayote squash, tomatoes, and oyster mushrooms. The results showed that the solar device achieved drying efficiencies between 22.8 and 37.9% by reaching moisture values below the 12.30% threshold, which according to the international standards is considered as “Low Moisture Food”. The evaluation of the double collector solar drier is demonstrated to be an easy-to-apply and environmentally friendly method for food preservation in tropical rural regions by taking advantage of domestic renewable energy resources.
Food Festivals and the Development of Sustainable Destinations. The Case of the Cheese Fair in Trujillo (Spain)
Authors: Folgado-Fernández José Antonio , Di-Clemente Elide , Hernández-Mogollón José Manuel
Published: May 2019

Food-based events and festivals are being increasingly organized around the world, both in large cities and in small towns with the aim of attracting the many benefits they provide to the destinations where they are held. While the impact of mega events is sufficiently studied in scientific literature, the works that address the effects of small events are still scarce. To close this gap, this research investigates the significance of small food-based events for tourism and the sustainable development of destinations. An exhaustive study of a renowned festival based on cheese was carried out in the Spanish city of Trujillo. A survey was used to ask non-local attendants and it explored their motivations, the event itself, the assessment of the permanent elements of the destination, and loyalty to the festival. The impact of these small festivals is not only relevant for the tourism sector and the sustainable positioning of the destination, however it is also relevant for the local economy due to the consumption of local gastronomic products. Given their role in attracting visitors, these small festivals as tourist motivators must be integrated into the communication campaigns of those destinations that seek to enhance their sustainability.
The Influence of Buyer Power on Supply Chain Pricing with Downstream Competition
Authors: Zhao Qiu
Published: May 2019

This paper aims to investigate the impact of buyer power on the wholesale price and retail price of, in the case, downstream competition. Based on a summary of the competitive characteristics of China’s retail market, a model of a vertical market was constructed to examine the influence of buyer power on the pricing decisions of manufacturers and retailers, and to analyze the mechanism of price decisions. The results showed that the buyer power of national retailers reduced the wholesale price, but the impact on local retailers remained uncertain. Although increasing buyer power initially increased the local retailer’s wholesale price and caused the ‘waterbed effect’, we found that this effect reverted when the buyer power reached a point at which the ‘anti-waterbed effect’ appeared. The opposite was true of the retail price. However, buyer power reduced the average retail price, and consumer welfare improved.
Measurement Scale Development and Validation of Female Employees’ Career Expectations in Mainland China
Authors: Liu Ting , Shen Huawen , Chau Ka Yin , Wang Xin
Published: May 2019

This paper aimed to develop a measurement scale for female hotel employees’ career expectations. Both qualitative and quantitative research methodologies were applied. In-depth interviews were first conducted to collect primary data of career expectation activities, and then the main survey was conducted nationwide to collect representative data. After a series of exploratory factor analysis, two dimensions were extracted, namely career rewards and career development. The results of confirmatory factor analysis indicated that the measurement items developed were both reliable and valid. Of the two factors of female hotel employees’ career expectations, career rewards was an important factor. Both academic and practical implications were discussed to provide valuable insights for human resource management of hotels in China. The paper concludes with the discussion of limitation and suggestions for future research.
Inhibition of Photosynthetic Activity in Wastewater-Borne Microalgal–Bacterial Consortia under Various Light Conditions
Authors: Kang Donghan , Kim Keug Tae , Heo Tae-Young , Kwon Gyutae , Lim Chaeseung , Park Jungsu
Published: May 2019

Microalgal–bacterial consortia are considered an alternative method to conventional wastewater treatment processes with several benefits, such as low oxygen production cost and reduced emission of carbon dioxide resulting from photosynthetic activity. Besides, microalgae effectively remove various emerging contaminants and heavy metals that are hardly removed by conventional wastewater treatment processes. The purpose of this study is finding optimal operation conditions (e.g., light wavelengths, light intensity, microalgal–bacterial consortia biomass) when applying microalgae in wastewater treatment system. Firstly, reduced transmittance was monitored at four different wavelengths (i.e., blue, green, red, and white light) and at various concentrations of microalgal–bacterial consortia. Light transmittance rates were rapidly reduced as the biomass increased, where the highest transmittance was observed in green light. Secondly, the reduction of oxygen production over time, by the inhibition of the photosynthetic activity, was tested as the light intensity increased at four different wavelengths and at low (100 mg L−1) and high (500 mg L−1) concentrations of microalgal–bacterial consortia. The observations and subsequent statistical analyses verify that microalgal–bacterial consortia show the strongest resistance to the inhibition of the photosynthetic activity in green light, with white coming next, when the intensity of light is increased.
Assessing Tourists’ Preferences of Negative Externalities of Environmental Management Programs: A Case Study on Invasive Species in Shei-Pa National Park, Taiwan
Authors: Liu Tzu-Ming , Tien Chia-Mei
Published: May 2019

This study uses discrete choice experiments to evaluate and reduce the environmental impact of negative externalities of managing invasive alien species (IAS), such as “ecological shock”, “health risk”, “waiting time” “tour range” and “prevention and control fee”, on the support of IAS prevention and control. We used data from Taiwan’s Shei-Pa National Park and its visitors for the case study and obtained 602 valid questionnaires. The results indicate that visitors consider that each unit of externality of IAS prevention and control measures significantly reduces their utility, and the magnitude equals the estimated value of externality. However, although negative externalities are inevitable, the support for IAS prevention and control measures could be maximized by adjusting the types and proportions of negative externalities. For example, visitors are willing to sacrifice up to 1.41% of the tour range in exchange for a 1% reduction in ecological shock. This study summarizes the negative externalities of IAS prevention and control measures and proposes to adjust the combination of negative externalities to reduce the shocks of those IAS prevention and control measures on the public, so as to increase the public support for IAS policies and increase the sustainability of tourism.
Analysis of the Relationship between Emotional Intelligence, Resilience, and Family Functioning in Adolescents’ Sustainable Use of Alcohol and Tobacco
Authors: Molero Jurado María del Mar , Pérez-Fuentes María del Carmen , Barragán Martín Ana Belén , del Pino Salvador Rosa María , Gázquez Linares José Jesús
Published: May 2019

The use of alcohol and tobacco is related to several variables, which act as risk or protective factors depending on the circumstances. The objectives of this study were to analyze the relationship between emotional intelligence, resilience, and family functioning in adolescent use of alcohol and tobacco, and to find emotional profiles for their use with regard to self-concept. The sample was made up of 317 high school students aged 13 to 18, who filled out the Brief Emotional Intelligence Inventory, the Resilience Scale for Adolescents, the APGAR Scale, the Alcohol Expectancy Questionnaire–Adolescents, and the Five-Factor Self-Concept Questionnaire. The results revealed that emotional intelligence and resilience, specifically stress management and family cohesion, were significant in the group of non-users. Family functioning acts as a predictor for the onset of use of tobacco and alcohol. Positive expectancies about drinking alcohol were found to be a risk factor, and the intrapersonal factor was found to be protective. Both stress management and family cohesion were protective factors against smoking. Furthermore, cluster analysis revealed the emotional profiles for users of both substances based on self-concept. Finally, the importance of the direction of the relationship between the variables studied for intervention in this problem should be mentioned. Responsible use by improving adolescent decision-making is one of the results expected from this type of intervention.
A Comprehensive Framework for the Analysis of Industry 4.0 Value Domains
Authors: Martínez-Olvera César , Mora-Vargas Jaime
Published: May 2019

Industry 4.0 aims to ensure the future competitiveness of the manufacturing industry by providing Companies with the ability to react to rapid product changes and disturbances, efficiently and reliably, through re-configurability. In this paper, we explore the value creation process within Industry 4.0, with special emphasis on its relationship with mass customization and the sustainability issue. Based on the identified research gaps and opportunities derived from a literature review of relevant concepts, we propose the development of the Customer-Product-Process-Resource (CPPR) 4.0, a comprehensive framework that puts the value proposition-creation-capture cycle proper of an Industry 4.0 environment, in the context of a manufacturing organization’s customer-product-process-resources views. The usefulness of the proposed framework is exemplified by using it to derive system dynamics model of the mass customization paradigm. A discussion of the managerial implications of the obtained results for both the sustainability and the case of Small-to-Medium Enterprises (SMEs) is offered at the end of the paper.
Extracting Information from an Urban Network by Combining a Visibility Index and a City Data Set
Authors: Agryzkov Taras , Oliver José Luis , Tortosa Leandro , Vicent José F.
Published: May 2019

Cities can be represented by spatial networks, and the mathematical structure that defines a spatial network is a graph. Taking into account this premise, this paper is focused on analysing information on an urban scale by combining a new ray-casting visibility index with a data set of the urban street network. The visibility index provides information about the most visible buildings or areas. We relate this index with other data extracted from the city, with the aim of generating and analysing information about urban elements. To corroborate this idea, real data are analysed. The dataset is related to the heritage conservation of the buildings of the Villaflora suburb, located in the city of Quito (Ecuador). This information is processed, together with the visibility index, with the aim of determining the conservation degree of the urban areas most visually exposed to pedestrians or visitors. The combination of both values—heritage conservation and visibility index—is carried out by means of two new indices, I P and I N , which are defined using two-variable exponential functions.
Multi-Criteria Fuzzy-Stochastic Diffusion Model of Groundwater Control System Selection
Authors: Polomčić Dušan , Gligorić Zoran , Bajić Dragoljub , Gligorić Miloš , Negovanović Milanka
Published: May 2019

When considering data and parameters in hydrogeology, there are often questions of uncertainty, vagueness, and imprecision in terms of the quantity of spatial distribution. To overcome such problems, certain data may be subjectively expressed in the form of expert judgment, whereby a heuristic approach and the use of fuzzy logic are required. In this way, decision-making criteria relating to an optimal groundwater control system do not always have a numerical value. Groundwater control scenarios (alternatives) are identified through hydrodynamic modeling of the aquifer, providing an indication of their effectiveness. The paper develops a fuzzy-stochastic multi-criteria decision-making model to deal with a topical problem: selection of the most suitable groundwater control system for an open-cast mine. Both real numerical and linguistic variables are used to express the values of all criteria that affect the final decision. In particular, it should be pointed out that the values of the criteria are varied over a predefined time horizon. For mathematical calculations, fuzzy dynamic TOPSIS and the stochastic diffusion process—geometric Brownian motion—were used. The proposed method is tested in a case study: the selection of an optimal groundwater control system for an open-cast mine.
Some Identities of Fully Degenerate Bernoulli Polynomials Associated with Degenerate Bernstein Polynomials
Authors: Lee Jeong Gon , Kim Wonjoo , Jang Lee-Chae
Published: May 2019

In this paper, we investigate some properties and identities for fully degenerate Bernoulli polynomials in connection with degenerate Bernstein polynomials by means of bosonic p-adic integrals on Z p and generating functions. Furthermore, we study two variable degenerate Bernstein polynomials and the degenerate Bernstein operators.