bluuebunny/crossref_metadata_2025 huggingface dataset:
Interreligious Dialogue in Public Service Broadcasting. A Case Study in Catalonia (Spain)
Authors: Huertas Bailén Amparo
Published: August 2020

This text addresses how the media deals with interreligious dialogue based on the case study of the Catalan public television stations. Our theoretical framework revolves around the concept of mediation, which is regarded as a communicative concept that emphasizes the socializing power of the mass media as well as its potential contribution to social cohesion. A quantitative and qualitative analysis is presented of a sample of 41 multi-religious audiovisual pieces broadcast between 2015 and 2018, which were located in the Corporation’s on-demand online service. The religious diversity that currently exists in European cities is reflected in the media content. Although it is true that the Catholic religion features in 63% of the sample, it only becomes the focal point on less than half of the occasions in which it appears. The religious options with more presence are Catholicism in relation to Islam and atheism in relation to Catholicism, but these cases only account for 26.8% of the sample. Interreligious dialogue appears as the main focus of the discourse in only 14.6% of the sample and, in general, the tendency towards a Euro-Catholic-centric discourse has been detected.
Artificial Neural Networks to Retrieve Land and Sea Skin Temperature from IASI
Authors: Safieddine Sarah , Parracho Ana Claudia , George Maya , Aires Filipe , Pellet Victor , Clarisse Lieven , Whitburn Simon , Lezeaux Olivier , Thépaut Jean-Noël , Hersbach Hans , Radnoti Gabor , Goettsche Frank , Martin Maria , Doutriaux-Boucher Marie , Coppens Dorothée , August Thomas , Zhou Daniel K. , Clerbaux Cathy
Published: August 2020

Surface skin temperature (Tskin) derived from infrared remote sensors mounted on board satellites provides a continuous observation of Earth’s surface and allows the monitoring of global temperature change relevant to climate trends. In this study, we present a fast retrieval method for retrieving Tskin based on an artificial neural network (ANN) from a set of spectral channels selected from the Infrared Atmospheric Sounding Interferometer (IASI) using the information theory/entropy reduction technique. Our IASI Tskin product (i.e., TANN) is evaluated against Tskin from EUMETSAT Level 2 product, ECMWF Reanalysis (ERA5), SEVIRI observations, and ground in situ measurements. Good correlations between IASI TANN and the Tskin from other datasets are shown by their statistic data, such as a mean bias and standard deviation (i.e., [bias, STDE]) of [0.55, 1.86 °C], [0.19, 2.10 °C], [−1.5, 3.56 °C], from EUMETSAT IASI L-2 product, ERA5, and SEVIRI. When compared to ground station data, we found that all datasets did not achieve the needed accuracy at several months of the year, and better results were achieved at nighttime. Therefore, comparison with ground-based measurements should be done with care to achieve the ±2 °C accuracy needed, by choosing, for example, a validation site near the station location. On average, this accuracy is achieved, in particular at night, leading to the ability to construct a robust Tskin dataset suitable for Tskin long-term spatio-temporal variability and trend analysis.
Combined Migrations and Time-Depth Conversions in GPR Prospecting: Application to Reinforced Concrete
Authors: Persico Raffaele , Morelli Gianfranco
Published: August 2020

In this paper, we propose the combination of different migration results achieved on the same data in order to account for different values of the propagation velocities of the electromagnetic waves within the considered Ground Penetrating Radar (GPR) profile. These different values can be the result of a variable lithological composition or (more probably for short Bscans) the results of different moisture levels, or both. Here, we separately consider the two cases of horizontal or vertical variability of the propagation velocity with a transition zone between two zones with constant propagation velocity. Moreover, we also propose a time-depth conversion accounting for these different values of the propagation velocity along the considered GPR Bscan. The method is applied to real data gathered in the field with regard to a concrete coverage containing liner layers.
Crop Type Classification Using Fusion of Sentinel-1 and Sentinel-2 Data: Assessing the Impact of Feature Selection, Optical Data Availability, and Parcel Sizes on the Accuracies
Authors: Orynbaikyzy Aiym , Gessner Ursula , Mack Benjamin , Conrad Christopher
Published: August 2020

Crop type classification using Earth Observation (EO) data is challenging, particularly for crop types with similar phenological growth stages. In this regard, the synergy of optical and Synthetic-Aperture Radar (SAR) data enables a broad representation of biophysical and structural information on target objects, enhancing crop type mapping. However, the fusion of multi-sensor dense time-series data often comes with the challenge of high dimensional feature space. In this study, we (1) evaluate how the usage of only optical, only SAR, and their fusion affect the classification accuracy; (2) identify the combination of which time-steps and feature-sets lead to peak accuracy; (3) analyze misclassifications based on the parcel size, optical data availability, and crops’ temporal profiles. Two fusion approaches were considered and compared in this study: feature stacking and decision fusion. To distinguish the most relevant feature subsets time- and variable-wise, grouped forward feature selection (gFFS) was used. gFFS allows focusing analysis and interpretation on feature sets of interest like spectral bands, vegetation indices (VIs), or data sensing time rather than on single features. This feature selection strategy leads to better interpretability of results while substantially reducing computational expenses. The results showed that, in contrast to most other studies, SAR datasets outperform optical datasets. Similar to most other studies, the optical-SAR combination outperformed single sensor predictions. No significant difference was recorded between feature stacking and decision fusion. Random Forest (RF) appears to be robust to high feature space dimensionality. The feature selection did not improve the accuracies even for the optical-SAR feature stack with 320 features. Nevertheless, the combination of RF feature importance and time- and variable-wise gFFS rankings in one visualization enhances interpretability and understanding of the features’ relevance for specific classification tasks. For example, by enabling the identification of features that have high RF feature importance values but are, in their information content, correlated with other features. This study contributes to the growing domain of interpretable machine learning.
A Constrained Sparse-Representation-Based Spatio-Temporal Anomaly Detector for Moving Targets in Hyperspectral Imagery Sequences
Authors: Li Zhaoxu , Ling Qiang , Wu Jing , Wang Zhengyan , Lin Zaiping
Published: August 2020

At present, small dim moving target detection in hyperspectral imagery sequences is mainly based on anomaly detection (AD). However, most conventional detection algorithms only utilize the spatial spectral information and rarely employ the temporal spectral information. Besides, multiple targets in complex motion situations, such as multiple targets at different velocities and dense targets on the same trajectory, are still challenges for moving target detection. To address these problems, we propose a novel constrained sparse representation-based spatio-temporal anomaly detection algorithm that extends AD from the spatial domain to the spatio-temporal domain. Our algorithm includes a spatial detector and a temporal detector, which play different roles in moving target detection. The former can suppress moving background regions, and the latter can suppress non-homogeneous background and stationary objects. Two temporal background purification procedures maintain the effectiveness of the temporal detector for multiple targets in complex motion situations. Moreover, the smoothing and fusion of the spatial and temporal detection maps can adequately suppress background clutter and false alarms on the maps. Experiments conducted on a real dataset and a synthetic dataset show that the proposed algorithm can accurately detect multiple targets with different velocities and dense targets with the same trajectory and outperforms other state-of-the-art algorithms in high-noise scenarios.
Pyroclastic Density Current Hazard Assessment and Modeling Uncertainties for Fuego Volcano, Guatemala
Authors: Flynn Ian T. W. , Ramsey Michael S.
Published: August 2020

On 3 June 2018, Fuego volcano experienced a VEI = 3 eruption, which produced a pyroclastic density current (PDC) that devastated the La Réunion resort and the community of Los Lotes, resulting in over 100 deaths. To evaluate the potential hazard to the population centers surrounding Fuego associated with future PDC emplacement, we used an integrated remote sensing and flow modeling-based approach. The predominate PDC travel direction over the past 15 years was investigated using thermal infrared (TIR) data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument validated with ground reports from the National Institute of Seismology, Volcanology, Meteorology, and Hydrology (INSIVUMEH), the government agency responsible for monitoring. Two different ASTER-derived digital elevation model (DEM) products with varying levels of noise were also used to assess the uncertainty in the VolcFlow model results. Our findings indicate that the recent historical PDC travel direction is dominantly toward the south and southwest. Population centers in this region of Fuego that are within ~2 km of one of the volcano’s radial barrancas are at the highest risk during future large eruptions that produce PDCs. The ASTER global DEM (GDEM) product has the least random noise and where used with the VolcFlow model, had a significant improvement on its accuracy. Results produced longer flow runout distances and therefore better conveys a more accurate perception of risk. Different PDC volumes were then modeled using the GDEM and VolcFlow to determine potential inundation areas in relation to local communities.
A Comparative Study on the Oxidation of Label-Free Silver Triangular Nanoplates by Peroxides: Main Effects and Sensing Applications
Authors: Furletov Aleksei , Apyari Vladimir , Garshev Alexey , Dmitrienko Stanislava
Published: August 2020

Nowadays, analytical systems based on silver triangular nanoplates (AgTNPs) have been shown as good prospects for chemical sensing. However, they still remain relatively poorly studied as colorimetric probes for sensing various classes of compounds. This study shows that these nanoparticles are capable of being oxidized by peroxides, including both hydrogen peroxide and its organic derivatives. The oxidation was found to result in a decrease in the AgTNPs’ local surface plasmon resonance band intensity at 620 nm. This was proposed for peroxide-sensitive spectrophotometric determination. Five peroxides differing in their structure and number of functional groups were tested. Three of them easily oxidized AgTNPs. The effects of a structure of analytes and main exterior factors on the oxidation are discussed. The detection limits of peroxides in the selected conditions increased in the series peracetic acid < hydrogen peroxide < tert-butyl hydroperoxide, coming to 0.08, 1.6 and 24 μmol L−1, respectively. tert-Butyl peroxybenzoate and di-tert-butyl peroxide were found to have no effect on the spectral characteristics of AgTNPs. By the example of hydrogen peroxide, it was found that the determination does not interfere with 100–4000-fold quantities of common inorganic ions. The proposed approach was successfully applied to the analysis of drugs, cosmetics and model mixtures.
A Blockchain-Based Authentication and Dynamic Group Key Agreement Protocol
Authors: Xu Zisang , Li Feng , Deng Han , Tan Minfu , Zhang Jixin , Xu Jianbo
Published: August 2020

With the rapid development of mobile networks, there are more and more application scenarios that require group communication. For example, in mobile edge computing, group communication can be used to transmit messages to all group members with minimal resources. The group key directly affects the security of the group communication. Most existing group key agreement protocols are often flawed in performance, scalability, forward or backward secrecy, or single node failure. Therefore, this paper proposes a blockchain-based authentication and dynamic group key agreement protocol. With our protocol, each group member only needs to authenticate its left neighbor once to complete the authentication, which improved authentication efficiency. In addition, our protocol guarantees the forward secrecy of group members after joining the group and the backward secrecy of group members after leaving the group. Based on blockchain technology, we solve the problem of single node failure. Furthermore, we use mathematics to prove the correctness and security of our protocol, and the comparison to related protocols shows that our protocol reduces computation and communication costs.
Experimental Evidence of the Viability of Thermoelectric Generators to Power Volcanic Monitoring Stations
Authors: Catalan Leyre , Garacochea Amaia , Casi Alvaro , Araiz Miguel , Aranguren Patricia , Astrain David
Published: August 2020

Although there is an important lack of commercial thermoelectric applications mainly due to their low efficiency, there exist some cases in which thermoelectric generators are the best option thanks to their well-known advantages, such as reliability, lack of maintenance and scalability. In this sense, the present paper develops a novel thermoelectric application in order to supply power to volcanic monitoring stations, making them completely autonomous. These stations become indispensable in any volcano since they are able to predict eruptions. Nevertheless, they present energy supply difficulties due to the absence of power grid, the remote access, and the climatology. As a solution, this work has designed a new integral system composed of thermoelectric generators with high efficiency heat exchangers, and its associated electronics, developed thanks to Internet of Things (IoT) technologies. Thus, the heat emitted from volcanic fumaroles is transformed directly into electricity with thermoelectric generators with passive heat exchangers based on phase change, leading to a continuous generation without moving parts that powers different sensors, the information of which is emitted via LoRa. The viability of the solution has been demonstrated both at the laboratory and at a real volcano, Teide (Canary Islands, Spain), where a compact prototype has been installed in an 82 °C fumarole. The results obtained during more than eight months of operation prove the robustness and durability of the developed generator, which has been in operation without maintenance and under several kinds of meteorological conditions, leading to an average generation of 0.49 W and a continuous emission over more than 14 km.
CNN Training with Twenty Samples for Crack Detection via Data Augmentation
Authors: Wang Zirui , Yang Jingjing , Jiang Haonan , Fan Xueling
Published: August 2020

The excellent generalization ability of deep learning methods, e.g., convolutional neural networks (CNNs), depends on a large amount of training data, which is difficult to obtain in industrial practices. Data augmentation is regarded commonly as an effective strategy to address this problem. In this paper, we attempt to construct a crack detector based on CNN with twenty images via a two-stage data augmentation method. In detail, nine data augmentation methods are compared for crack detection in the model training, respectively. As a result, the rotation method outperforms these methods for augmentation, and by an in-depth exploration of the rotation method, the performance of the detector is further improved. Furthermore, data augmentation is also applied in the inference process to improve the recall of trained models. The identical object has more chances to be detected in the series of augmented images. This trick is essentially a performance–resource trade-off. For more improvement with limited resources, the greedy algorithm is adopted for searching a better combination of data augmentation. The results show that the crack detectors trained on the small dataset are significantly improved via the proposed two-stage data augmentation. Specifically, using 20 images for training, recall in detecting the cracks achieves 96% and Fext(0.8), which is a variant of F-score for crack detection, achieves 91.18%.
A Multiscale Recognition Method for the Optimization of Traffic Signs Using GMM and Category Quality Focal Loss
Authors: Gao Mingyu , Chen Chao , Shi Jie , Lai Chun Sing , Yang Yuxiang , Dong Zhekang
Published: August 2020

Effective traffic sign recognition algorithms can assist drivers or automatic driving systems in detecting and recognizing traffic signs in real-time. This paper proposes a multiscale recognition method for traffic signs based on the Gaussian Mixture Model (GMM) and Category Quality Focal Loss (CQFL) to enhance recognition speed and recognition accuracy. Specifically, GMM is utilized to cluster the prior anchors, which are in favor of reducing the clustering error. Meanwhile, considering the most common issue in supervised learning (i.e., the imbalance of data set categories), the category proportion factor is introduced into Quality Focal Loss, which is referred to as CQFL. Furthermore, a five-scale recognition network with a prior anchor allocation strategy is designed for small target objects i.e., traffic sign recognition. Combining five existing tricks, the best speed and accuracy tradeoff on our data set (40.1% mAP and 15 FPS on a single 1080Ti GPU), can be achieved. The experimental results demonstrate that the proposed method is superior to the existing mainstream algorithms, in terms of recognition accuracy and recognition speed.
On the Use of a Rotatable ECT Sensor to Investigate Dense Phase Flow: A Feasibility Study
Authors: Wajman Radosław , Banasiak Robert , Babout Laurent
Published: August 2020

This paper presents the feasibility study of dynamic flow measurements using the concept of a rotatable electrical capacitance tomography (ECT) sensor. The experiment considered horizontal flow in a pneumatic conveying flow loop in the case of dense phase flow. Slugs and settled layers were imaged and a comparison was made between no rotation or rotation of the sensor for two image reconstruction schemas: linear back projection (LBP) and non-linear iterative back projection. Data were evaluated both qualitatively and quantitatively by estimating the solids concentration level for different hue levels.
Effect of Adding Drinking Water Treatment Sludge on Excess Activated Sludge Digestion Process
Authors: Wu Yanxia , Du Haixia , Li Fusheng , Su Haoning , Bhat Sartaj Ahmad , Hudori Hudori , Rosadi Maulana Yusup , Arsyad Faisal , Lu Yanqiu , Wu Huifang
Published: August 2020

Drinking water treatment sludge (DWTS) is a waste by-product from water treatment plants where aluminum and iron salts are the most commonly used coagulants. DWTS was reused to investigate the effects of DWTS on the digestion liquid quality and microorganism activity of excess activated sludge (EAS). DWTS with four suspended solid (SS) concentrations (0%, 2%, 5% and 10%) was added to EAS which was sampled during aerobic and anaerobic digestion processes, then batch tests were carried out which followed the coagulation-flocculation process. It was found that DWTS can improve total dissolved nitrogen (TDN) and dissolved phosphorus (DP) removal efficiencies for anaerobic EAS. The highest removal efficiency of TDN (29.97%) as well as DP (55.38%) was observed when DWTS dosage was SS = 10%. The release of dissolved organic matter (DOM) by DWTS could increase dissolved organic carbon (DOC) concentration and lead to the accumulation of non-biodegradable humic acid-like substance in aerobic and anaerobic digestion liquid. The dehydrogenase activity (DHA) values of anaerobic EAS were higher than aerobic EAS. DWTS could reduce DHA for both EAS. These results indicate that potential risk of release of DOM should be considered when reusing DWTS in future research.
Numerical Analysis of a Solar Tower Receiver Novel Design
Authors: Hazmoune Messaoud , Aour Benaoumeur , Chesneau Xavier , Debbache Mohammed , Ciupageanu Dana-Alexandra , Lazaroiu Gheorghe , Hadjiat Mohamed Mondji , Hamidat Abderrahmane
Published: August 2020

Efficient operation of thermal solar power plants is strongly dependent on the central receiver design. In particular, as the receiver tube determines the temperature behavior inside the receiver, its geometry proves to be the main factor affecting the solar tower receiver performances. This paper investigates the effect of several 3D geometric concepts on both temperature evolution and velocity of the working fluid at the receiver, in order to obtain an enhanced design, with augmented efficiency. A novel receiver tube with helical fins is proposed, aiming an increased heat exchange surface and improved thermal conduction. Extensive numerical simulation is carried out in ANSYS CFX (CFD) to assess the performances of the proposed solar tower receiver design. An unstructured mesh, generated by a computation machine, and (k-ε) turbulence model are employed to this regard. The results show that the tubes with helical fins for solar tower receivers give a very important increase in the outlet temperature, which can reach up to 1050 K.
A Virtual Assistant for Natural Interactions in Museums
Authors: Duguleană Mihai , Briciu Victor-Alexandru , Duduman Ionuț-Alexandru , Machidon Octavian Mihai
Published: August 2020

Artificial Intelligence (AI) and its real-life applications are among the most effervescent research topics of the last couple of years. In the past decade, stakeholders such as private companies, public institutions, non-profit entities, and even individuals, have developed and used various AI algorithms to solve a wide range of problems. Given the extended applicability and the disruption potential of this technology, it was just a matter of time until it connected to the field of cultural heritage. This paper presents the development of an intelligent conversational agent which was built to improve the accessibility to information inside a history museum. We present the cultural context, the application architecture, the implementation challenges, and the visitors’ feedback. We created a smart virtual agent that interacts with users in natural spoken language. This involved the design and implementation of the artificial intelligence-based core responsible for understanding the Romanian language. A short survey regarding the tourist acceptance of the system was conducted at the premises of our partners, the Museum “Casa Mureșenilor” from Brașov, shows good acceptance levels from both visitors and museum staff. Given the flexibility of the implementation, the system can be used by a large array of stakeholders with minor modifications.
Dynamic Development of the Global Organic Food Market and Opportunities for Ukraine
Authors: Bazaluk Oleg , Yatsenko Olha , Zakharchuk Oleksandr , Ovcharenko Anna , Khrystenko Olga , Nitsenko Vitalii
Published: August 2020

Considering the insufficient usage of natural resources, ecological crisis, rising population and limitations of the traditional food system in the 21st century, it is extremely important to search for methods to achieve sustainable development. In this context, the search for alternative methods of farming and the transformation of typical food consumption is relevant; the organic market and its features are of particular interest. Based on the above, this article is dedicated to understanding what the development opportunities for the production and export of Ukrainian organic products within the global market are. To achieve this objective, it became necessary to study the specificities of the dynamic growth of the global organic food market, which includes identifying the dominant factors of its development, peculiarities of its regulation, evaluation of the current state, main trends and prospects. The study provides the characteristics of the top competitors in the global market, consumer segmentation and experience of the implementation of global and national organic sector development and support programs. As a result of the study, it was found that Ukraine has unrealized export potential that can be realized using a combination of practices used abroad (the active use of marketing tools, state support for the organic sector and increasing organic production by uniting producers into clusters and creating cooperatives).
Response Surface Methodology Optimization and Kinetics of Diesel Degradation by a Cold-Adapted Antarctic Bacterium, Arthrobacter sp. Strain AQ5-05
Authors: Abdulrasheed Mansur , Zulkharnain Azham , Zakaria Nur Nadhirah , Roslee Ahmad Fareez Ahmad , Abdul Khalil Khalilah , Napis Suhaimi , Convey Peter , Gomez-Fuentes Claudio , Ahmad Siti Aqlima
Published: August 2020

Petroleum hydrocarbons, notably diesel oil, are the main energy source for running amenities in the Antarctic region and are the major cause of pollution in this area. Diesel oil spills are one of the major challenges facing management of the Antarctic environment. Bioremediation using bacteria can be an effective and eco-friendly approach for their remediation. However, since the introduction of non-native organisms, including microorganisms, into the Antarctic or between the distinct biogeographical regions within the continent is not permitted under the Antarctic Treaty, it is crucial to discover native oil-degrading, psychrotolerant microorganisms that can be used in diesel bioremediation. The primary aim of the current study is to optimize the conditions for growth and diesel degradation activity of an Antarctic local bacterium, Arthrobacter sp. strain AQ5-05, using the Plackett-Burman approach and response surface method (RSM) via a central composite design (CCD) approach. Based on this approach, temperature, pH, and salinity were calculated to be optimum at 16.30 °C, pH 7.67 and 1.12% (w/v), respectively. A second order polynomial regression model very accurately represented the experimental figures’ interpretation. These optimized environmental conditions increased diesel degradation from 34.5% (at 10 °C, pH 7.00 and 1.00% (w/v) salinity) to 56.4%. Further investigation of the kinetics of diesel reduction by strain AQ5-05 revealed that the Teissier model had the lowest RMSE and AICC values. The calculated values for the Teissier constants of maximal growth rate, half-saturation rate constant for the maximal growth, and half inhibition constants (μmax, Ks, and Ki), were 0.999 h−1, 1.971% (v/v) and 1.764% (v/v), respectively. The data obtained therefore confirmed the potential application of this cold-tolerant strain in the bioremediation of diesel-contaminated Antarctic soils at low temperature.
Impact of COVID-19 on Food Behavior and Consumption in Qatar
Authors: Ben Hassen Tarek , El Bilali Hamid , Allahyari Mohammad S.
Published: August 2020

The government of Qatar took strong containment measures to prevent the spread of COVID-19 with restrictions on daily living such as social distancing and the closing of businesses and schools. While these measures are essential to stop the virus spreading, several voices came to warn of their potential disruptive impact on the agri-food system. Therefore, this paper investigates the immediate impacts of COVID-19 on Qatari consumer awareness, attitudes, and behaviors related to food consumption. The study is based on an online survey in Qatar using a structured questionnaire that was administered in the Arabic language through the Survey Monkey platform from 24 May until 14 June 2020. The results reveal clear changes in the way consumers are eating, shopping, and interacting with food. Indeed, the survey results suggested (i) a shift toward healthier diets; (ii) an increase in the consumption of domestic products due to food safety concerns; (iii) a change in the modality of acquiring food (with a surge in online grocery shopping); (iv) an increase in culinary capabilities; and (v) the absence of panic buying and food stockpiling in Qatar. The results are expected to inform current emergency plans as well as long-term food-related strategies in Qatar.
The Role of CSR on Social Entrepreneurship: An International Analysis
Authors: Buendía-Martínez Inmaculada , Carrasco Monteagudo Inmaculada
Published: August 2020

The increase in the weight of social entrepreneurship (SE) in the economy has driven the increase in research on the subject. Within the set of approaches developed by scholars to analyse SE, the institutional approach has recently acquired greater relevance. Following this research trend, this article seeks to expand the empirical research on SE by focusing on the informal factors that are less studied in the literature and using a cross-national base. Using the New Institutional Economics and partial least squares–structural equation modelling (PLS-SEM), our findings show the influence of cultural context on the SE dimension. In addition, this influence occurs through two groups of variables led by social capital and corporate social responsibility, although their impacts show opposite signs. These factors have important implications for policy makers in charge of fostering SE development.
A Life Cycle Assessment of Biomass Production from Energy Crops in Crop Rotation Using Different Tillage System
Authors: Vatsanidou Anna , Kavalaris Christos , Fountas Spyros , Katsoulas Nikolaos , Gemtos Theofanis
Published: August 2020

A three-year experiment was carried out in Central Greece to assess the use of different tillage practices (Conventional, Reduced, and No tillage) for seedbed preparation, in a double cropping per year rotation of irrigated and rainfed energy crops for biomass production for first- and second-generation biofuel production. A life cycle assessment (LCA) study was performed for the first year of crop rotation to evaluate the environmental impact of using different tillage practices, identifying the processes with greater influence on the overall environmental burden (hotspots) and demonstrating the potential environmental benefits from the land management change. LCA results revealed that fertilizer application and diesel fuel consumption, as well as their production stages, were the hot-spot processes for each treatment. In the present study, different tillage treatments compared using mass- and area-based functional unit (FU), revealing that reduced tillage, using strip tillage for spring crop and disc harrow for winter crops, and no tillage treatment had the best environmental performance, respectively. Comparison between the prevailing in the area monoculture cotton crop with the proposed double energy crop rotation adopting conservation tillage practices, using mass and energy value FU, showed that cotton crop had higher environmental impact.
An Assessment of Tourism Climate Comfort in the China–Pakistan Economic Corridor
Authors: Zeng Di , Wu Jinkui , Mu Yaqiong , Li Hongyuan , Deng Mingshan , Wei Yanqiang , Sun Weibing
Published: August 2020

Pleasant climates can be divided into two types: the comfortable summer climate and the comfortable winter climate, but existing studies rarely pay attention to the distribution characteristics and differences between the two types of climate. This study investigates the spatial distribution of comfortable summer and winter climates in the China–Pakistan Economic Corridor (CPEC) and their differences based on the European Centre for Medium-Range Weather Forecasts Re-Analysis-Interim (ERA-interim) reanalysis data from 1979 to 2018. The Universal Thermal Climate Index was used to analyze climatic suitability. The findings are as follows. First, the comfortable summer climate regions of the CPEC were mainly distributed in Khyber Pakhtunkhwa in Pakistan and some regions of Xinjiang in China and also sporadically distributed in high altitude mountains, such as the western plateau area. The comfortable winter climate regions were mainly distributed in vast areas except for Karakoram and nearby areas. Second, there are a few regions with dual attributes of comfortable summer and winter climates in CPEC. Third, according to the calculation and comparison of the regional area of different climate comfort levels in summer and winter, it is found that the comfortable summer climate is scarcer in CPEC and is a monopoly resource. The comfortable winter climate is widely distributed, belonging to the ubiquitous resources. These findings can be helpful for the tourism development of local climate resources.
Constraints and Consequences of Online Teaching
Authors: Obrad Ciprian
Published: August 2020

In Romania, like in many other European countries, schools and universities were closed and classes were transferred entirely online at the beginning of March 2020, due to the new coronavirus SARS-CoV-2 (COVID-19) outbreak, declared as a pandemic by the World Health Organization (WHO). In the context of drastic changes and uncertainty, teachers across Romania had to face the challenges of transferring lectures online. The small window of time left to adapt to new technologies, along with other stressors, called into question their work engagement and performance, as key factors for the sustainability of the educational system. An approach based on the dimensions of induced stress, resilience behavior, professional support, and work engagement was implemented to highlight the impact of socio-professional changes during the COVID-19 on the activity of 400 teachers from Romania. The designed construct was validated and subsequently a model was proposed, by using factor analysis and Structural Equation Modeling (SEM). The article brings updated information on the complex relationship between stress and resilience in the case of employees from the area of education. Among other results, the present research highlights the structure of work engagement and the mediating role of professional support in the relationship between stressors and resilience mechanisms.
The Split Delivery Vehicle Routing Problem with Three-Dimensional Loading and Time Windows Constraints
Authors: Chen Zongyi , Yang Mingkang , Guo Yijun , Liang Yu , Ding Yifan , Wang Li
Published: August 2020

Besides routing and packing plans, synthetically considering the requirements of customers about service time is absolutely necessary. An order split delivery plan can not only better satisfy the service time requirements, but also improve the full-load rate of vehicles. The split delivery vehicle routing problem with three-dimensional loading constraints (3L-SDVRP) combines vehicle routing and three-dimensional loading with additional packing constraints. In the 3L-SDVRP splitting deliveries of customers is basically possible, i.e., a customer can be visited in two or more tours. The vehicle routing problem with three-dimensional loading constraints that are based on the time window and considering split delivery of orders (3L-CVRPTWSDO) and its optimization algorithm are studied in this paper. We established mathematical model of the problem and designed the tabu search algorithm. Based on the examples used in Gendreau et al. (2006), examples was constructed to test our algorithm. The experimental results have expressed that, in the 3L-CVRP problem, the results of split delivery is better than those of non-split delivery, and it is easier to satisfy the time window constraints. The algorithm in this paper generates high quality solutions, it provides a effective method to solve the 3L-CVRPTWSDO problems.
Preliminary Studies on Fungal Contamination of Two Rupestrian Churches from Matera (Southern Italy)
Authors: Mang Stefania Mirela , Scrano Laura , Camele Ippolito
Published: August 2020

The Sassi, a UNESCO World Heritage Site and its rupestrian churches, are richly decorated and visited by thousands of visitors every year. It is important to preserve this heritage which shows signs of deterioration due to abiotic and/or biotic factors. Aiming to carry out in the future an environmental-friendly restoration, a screening of the fungi present on walls and frescoes of two rupestrian churches “Santa Lucia alle Malve” and “La Madonna dei derelitti” located, respectively, in the “Sasso Caveoso” and in the “Sasso Barisano” was performed. Isolation and characterization of fungal species from investigated sites was carried out. Total genomic DNA (gDNA) was extracted from pure fungal cultures and subsequently utilized in PCRs using primers that amplify a portion of the ribosomal DNA (ITS5/ITS4) or the β-tubulin gene (Bt2a/Bt2b). The amplicons were directly sequenced. Obtained nucleotide sequences were compared to those present in the GenBank (NCBI) showing a very high similarity (99–100%) with the following species: Parengyodontium album, Alternaria alternata, Cladosporium cladosporioides, Lecanicillium psalliotae, Meyerozyma guilliermondii and Botryotrichum atrogriseum. All sequences from this study were deposited in the EMBL database. Detailed knowledge about fungi isolated from stone is indispensable not only to counter/reduce the structural and aesthetic damage but also to protect the health of both guardians and visitors who may develop different pathologies due to the spores diffused in the environment.
Evaluating Potential Ground Subsidence Geo-Hazard of Xiamen Xiang’an New Airport on Reclaimed Land by SAR Interferometry
Authors: Zhuo Guanchen , Dai Keren , Huang Huina , Li Shengpeng , Shi Xianlin , Feng Ye , Li Tao , Dong Xiujun , Deng Jin
Published: August 2020

The land reclaimed from the seaside may have a long-term subsidence trend, which poses a potential geohazard in the future land use. Xiamen Xiang’an New Airport (XXNA) is built on reclaimed land since 2016. Based on the spaceborne Sentinel-1 data between January 2018 to April 2019 and the time series interferometric synthetic aperture radar (InSAR) technique, this paper analyzed the reclaimed land subsidence evolution at XXNA in this period. InSAR measurements show that XXNA is suffering from severe subsidence, mainly in three regions because of the earth and sand compacting. By analyzing the spatial subsidence characterizations of the main subsiding areas combined with historical land reclamation and future land use planning, we find the potential threat of subsidence to future land use. Correlation between subsidence and the period of reclamation was found, indicating that the consolidation and compression in dredger fill is the main cause of subsidence. By combining subsidence monitoring results with different land use types and adopting the Expectation (Ex) and Entropy (En) methods, we analyzed the key area with potential subsidence geo-hazard. This work shows that with SAR interferometry, it is possible to find the large area ground subsidence in the airport reclaimed area. The areas with potential subsidence geo-hazards are consistent with the deep reclaimed earth, which means high subsidence risk in the future.
Using Bayesian Network to Predict Online Review Helpfulness
Authors: Lee Sangjae , Lee Kun Chang , Choeh Joon Yeon
Published: August 2020

The enormous volume and largely varying quality of available reviews provide a great obstacle to seek out the most helpful reviews. While Naive Bayesian Network (NBN) is one of the matured artificial intelligence approaches for business decision support, the usage of NBN to predict the helpfulness of online reviews is lacking. This study intends to suggest HPNBN (a helpfulness prediction model using NBN), which adopts NBN for helpfulness prediction. This study crawled sample data from Amazon website and 8699 reviews comprise the final sample. Twenty-one predictors represent reviewer and textual traits as well as product traits of the reviews. We investigate how the expanded list of predictors including product, reviewer, and textual characteristics of eWOM (online word-of-mouth) has an effect on helpfulness by suggesting conditional probabilities of the binned determinants. The prediction accuracy of NBN outperformed that of the k-nearest neighbor (kNN) method and the neural network (NN) model. The results of this study can support determining helpfulness and support website design to induce review helpfulness. This study will help decision-makers predict the helpfulness of the review comments posted to their websites and manage more effective customer satisfaction strategies. When prospect customers feel such review helpfulness, they will have a stronger intention to pay a regular visit to the target website.
Limit Cycle Bifurcations Near a Cuspidal Loop
Authors: Liu Pan , Han Maoan
Published: August 2020

In this paper, we study limit cycle bifurcation near a cuspidal loop for a general near-Hamiltonian system by using expansions of the first order Melnikov functions. We give a method to compute more coefficients of the expansions to find more limit cycles near the cuspidal loop. As an application example, we considered a polynomial near-Hamiltonian system and found 12 limit cycles near the cuspidal loop and the center.
Emerging Links between Cadmium Exposure and Insulin Resistance: Human, Animal, and Cell Study Data
Authors: Buha Aleksandra , Đukić-Ćosić Danijela , Ćurčić Marijana , Bulat Zorica , Antonijević Biljana , Moulis Jean-Marc , Goumenou Marina , Wallace David
Published: August 2020

Recent research has helped clarify the role of cadmium (Cd) in various pathological states. We have demonstrated Cd involvement in pancreatic cancer, as well as the bioaccumulation of Cd in the pancreas. Bioaccumulation and increased toxicity suggest that Cd may also be involved in other pancreas-mediated diseases, like diabetes. Cd falls into the category of “hyperglycemic” metals, i.e., metals that increase blood glucose levels, which could be due to increased gluconeogenesis, damage to β-cells leading to reduced insulin production, or insulin resistance at target tissue resulting in a lack of glucose uptake. This review addresses the current evidence for the role of Cd, leading to insulin resistance from human, animal, and in vitro studies. Available data have shown that Cd may affect normal insulin function through multiple pathways. There is evidence that Cd exposure results in the perturbation of the enzymes and modulatory proteins involved in insulin signal transduction at the target tissue and mutations of the insulin receptor. Cd, through well-described mechanisms of oxidative stress, inflammation, and mitochondrial damage, may also alter insulin production in β-cells. More work is necessary to elucidate the mechanisms associated with Cd-mediated insulin resistance.
Identification and Prevalence of Phascolarctid Gammaherpesvirus Types 1 and 2 in South Australian Koala Populations
Authors: Kasimov Vasilli , Stephenson Tamsyn , Speight Natasha , Chaber Anne-Lise , Boardman Wayne , Easther Ruby , Hemmatzadeh Farhid
Published: August 2020

To determine Phascolarctid gammaherpesviruses (PhaHV) infection in South Australian koala populations, 80 oropharyngeal swabs from wild-caught and 87 oropharyngeal spleen samples and swabs from euthanased koalas were tested using two specific PCR assays developed to detect PhaHV-1 and PhaHV-2. In wild-caught koalas, active shedding of PhaHV was determined by positive oropharyngeal samples in 72.5% (58/80) of animals, of which 44.8% (26/58) had PhaHV-1, 20.7% (12/58) PhaHV-2 and 34.5% (20/58) both viral subtypes. In the euthanased koalas, systemic infection was determined by positive PCR in spleen samples and found in 72.4% (63/87) of koalas. Active shedding was determined by positive oropharyngeal results and found in 54.0% (47/87) of koalas. Koalas infected and actively shedding PhaHV-1 alone, PhaHV-2 alone or shedding both viral subtypes were 48.9% (23/47), 14.9% (7/47) and 36.2% (17/47), respectively. Only 45.9% (40/87) were not actively shedding, of which 40.0% (16/40) of these had systemic infections. Both wild-caught and euthanased koalas actively shedding PhaHV-2 were significantly more likely to be actively shedding both viral subtypes. Active shedding of PhaHV-2 had a significant negative correlation with BCS in the euthanased cohort, and active shedding of PhaHV-1 had a significant positive relationship with age in both wild-caught and euthanased cohorts.
Transcriptome Analysis of Rice Reveals the lncRNA–mRNA Regulatory Network in Response to Rice Black-Streaked Dwarf Virus Infection
Authors: Zhang Tianze , Liang Qian , Li Chenyang , Fu Shuai , Kundu Jiban Kumar , Zhou Xueping , Wu Jianxiang
Published: August 2020

The plant genome can produce long non-coding RNAs (lncRNAs), some of which have been identified as important regulators of gene expression. To better understand the response mechanism of rice plants to Rice black-streaked dwarf virus (RBSDV) infection, we performed a comparative transcriptome analysis between the RBSDV-infected and non-infected rice plants. A total of 1342 mRNAs and 22 lncRNAs were identified to be differentially expressed after RBSDV infection. Most differentially expressed transcripts involved in the plant–pathogen interaction pathway were upregulated after RBSDV infection, indicating the activation of rice defense response by RBSDV. A network of differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) was then constructed. In this network, there are 56 plant–pathogen interaction-related DEmRNAs co-expressing with 20 DElncRNAs, suggesting these DElncRNAs and DEmRNAs may play essential roles in rice innate immunity against RBSDV. Moreover, some of the lncRNA–mRNA regulatory relationships were experimentally verified in rice calli by a quick and effective method established in this study. Three DElncRNAs were selected to be tested, and the results indicated that five mRNAs were found to be regulated by them. Together, we give a whole landscape of rice mRNAs and lncRNAs in response to RBSDV infection, and a feasible method to rapidly verify the lncRNA–mRNA regulatory relationship in rice.
Structure of the Capsid Size-Determining Scaffold of “Satellite” Bacteriophage P4
Authors: Kizziah James L. , Rodenburg Cynthia M. , Dokland Terje
Published: August 2020

P4 is a mobile genetic element (MGE) that can exist as a plasmid or integrated into its Escherichia coli host genome, but becomes packaged into phage particles by a helper bacteriophage, such as P2. P4 is the original example of what we have termed “molecular piracy”, the process by which one MGE usurps the life cycle of another for its own propagation. The P2 helper provides most of the structural gene products for assembly of the P4 virion. However, when P4 is mobilized by P2, the resulting capsids are smaller than those normally formed by P2 alone. The P4-encoded protein responsible for this size change is called Sid, which forms an external scaffolding cage around the P4 procapsids. We have determined the high-resolution structure of P4 procapsids, allowing us to build an atomic model for Sid as well as the gpN capsid protein. Sixty copies of Sid form an intertwined dodecahedral cage around the T = 4 procapsid, making contact with only one out of the four symmetrically non-equivalent copies of gpN. Our structure provides a basis for understanding the sir mutants in gpN that prevent small capsid formation, as well as the nms “super-sid” mutations that counteract the effect of the sir mutations, and suggests a model for capsid size redirection by Sid.