bluuebunny/crossref_metadata_2025 huggingface dataset:
Emerging Prevention and Treatment Strategies to Control COVID-19
Authors: Singh Vipul K. , Mishra Abhishek , Singh Shubhra , Kumar Premranjan , Singh Manisha , Jagannath Chinnaswamy , Khan Arshad
Published: June 2020

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), has now become a serious global threat after inflicting more than 8 million infections and 425,000 deaths in less than 6 months. Currently, no definitive treatment or prevention therapy exists for COVID-19. The unprecedented rise of this pandemic has rapidly fueled research efforts to discover and develop new vaccines and treatment strategies against this novel coronavirus. While hundreds of vaccines/therapeutics are still in the preclinical or early stage of clinical development, a few of them have shown promising results in controlling the infection. Here, in this review, we discuss the promising vaccines and treatment options for COVID-19, their challenges, and potential alternative strategies.
Clinical Features Associated with Strongyloidiasis in Migrants and the Potential Impact of Immunosuppression: A Case Control Study
Authors: Martinez-Pérez Angela , Soriano-Pérez Manuel , Salvador Fernando , Gomez-Junyent Joan , Villar-Garcia Judith , Santin Miguel , Muñoz Carme , González-Cordón Ana , Salas-Coronas Joaquín , Sulleiro Elena , Somoza Dolors , Treviño Begoña , Pecorelli Rosángela , Llaberia-Marcual Jaume , Lozano-Serrano Ana , Quinto Llorenç , Muñoz Jose , Requena-Méndez Ana ,   on behalf of the STRONG-SEMTSI working group
Published: June 2020

Strongyloides stercoralis is a widely distributed nematode more frequent in tropical areas and particularly severe in immunosuppressed patients. The aim of this study was to determine factors associated with strongyloidiasis in migrants living in a non-endemic area and to assess the response to treatment and follow-up in those diagnosed with the infection. We performed a multicenter case-control study with 158 cases and 294 controls matched 1:2 by a department service. Participants were recruited simultaneously at six hospitals or clinics in Spain. A paired-match analysis was then performed looking for associations and odds ratios in sociodemographic characteristics, pathological background, clinical presentation and analytical details. Cases outcomes after a six-month follow-up visit were also registered and their particularities described. Most cases and controls came from Latin America (63%–47%) or sub-Saharan Africa (26%–35%). The number of years residing in Spain (9.9 vs. 9.8, p = 0.9) and immunosuppression status (30% vs. 36.3%, p = 0.2) were also similar in both groups. Clinical symptoms such as diffuse abdominal pain (21% vs. 13%, p = 0.02), and epigastralgia (29% vs. 18%, p < 0.001); along with a higher eosinophil count (483 vs. 224 cells/mL in cases and controls, p < 0.001) and the mean total Immunoglobulin E (IgE) (354 U/L vs. 157.9 U/L; p < 0.001) were associated with having strongyloidiasis. Finally, 98.2% percent of the cases were treated with ivermectin in different schedules, and 94.5% met the cure criteria at least six months after their first consultation. Abdominal pain, epigastralgia, eosinophilia, increased levels of IgE and Latin American origin remain the main features associated with S. stercoralis infection, although this association is less evident in immunosuppressed patients. The appropriate follow-up time to evaluate treatment response based on serology titers should be extended beyond 6 months if the cure criteria are not achieved.
Rural Drinking Water Safety under Climate Change: The Importance of Addressing Physical, Social, and Environmental Dimensions
Authors: Kohlitz Jeremy , Chong Joanne , Willetts Juliet
Published: June 2020

This paper explores the physical, social, and environmental dimensions of how climate change impacts affect drinking water safety in a rural context in developing countries. Climate impacts, such as contamination or the reduced availability of preferred drinking water sources due to climate-related hazards, threaten water safety in rural areas and these impacts will likely worsen as climate change accelerates. We qualitatively examined these impacts in a community in rural Vanuatu using three approaches side-by-side: adaptation, vulnerability, and resilience. We employed a mixed methods case study methodology that combined semi-structured interviews, technological and environmental surveys, and observations. We demonstrate the influence of physical infrastructure design, social structures mediating water access, and the availability of multiple sustainable water resources on water safety with respect to climate impacts. We also show how the initial problematization of how climate affects water safety can influence subsequent actions to address, or overlook, issues of infrastructure design and maintenance, social equity, and natural resource management for water access. Improvements to rural drinking water safety management in the context of climate change should take a pluralistic approach, informed by different conceptualizations of climate impacts, to account for the varied causal pathways of reduced water safety for different members of a community.
Position-Domain Non-Gaussian Error Overbounding for ARAIM
Authors: Zhao Lin , Zhang Jie , Li Liang , Yang Fuxin , Liu Xiaosong
Published: June 2020

The non-Gaussian observation error is a threat for advanced receiver autonomous integrity monitoring (ARAIM), because the protection level of ARAIM based on the Gaussian distribution assumption is insufficient to envelope the positioning error (PE), and the probability of hazardously misleading information (PHMI) is difficult to be satisfied. The traditional non-Gaussian overbounding method is limited by the correlation among observation errors, and the deteriorated continuity risk resulting from the conservative inflation factor for overbounding, simultaneously. We propose an enhanced ARAIM method by position-domain non-Gaussian error overbounding. Furthermore, the upper bound of the inflation factor is imposed to release the conservativeness of overbounding. The simulation and the real-world data are utilized to test the proposed method. The simulation experiment has shown that the global worldwide availability level can be increased to 99.99% by using the proposed method. The real-word data experiment reveals that the proposed method can simultaneously satisfy the integrity risk and continuity risk with the boundary of the inflation factor.
Monitoring Agricultural Fields Using Sentinel-1 and Temperature Data in Peru: Case Study of Asparagus (Asparagus officinalis L.)
Authors: Silva-Perez Cristian , Marino Armando , Cameron Iain
Published: June 2020

This paper presents the analysis and a methodology for monitoring asparagus crops from remote sensing observations in a tropical region, where the local climatological conditions allow farmers to grow two production cycles per year. We used the freely available dual-polarisation GRD data provided by the Sentinel-1 satellite, temperature from a ground station and ground truth from January to August of 2019 to perform the analysis. We showed how particularly the VH polarisation can be used for monitoring the canopy formation, density and the growth rate, revealing connections with temperature. We also present a multi-output machine learning regression algorithm trained on a rich spatio-temporal dataset in which each output estimates the number of asparagus stems that are present in each of the pre-defined crop phenological stages. We tested several scenarios that evaluated the importance of each input data source and feature, with results that showed that the methodology was able to retrieve the number of asparagus stems in each crop stage when using information about starting date and temperature as predictors with coefficients of determination ( R 2 ) between 0.84 and 0.86 and root mean squared error (RMSE) between 2.9 and 2.7. For the multitemporal SAR scenario, results showed a maximum R 2 of 0.87 when using up to 5 images as input and an RMSE that maintains approximately the same values as the number of images increased. This suggests that for the conditions evaluated in this paper, the use of multitemporal SAR data only improved mildly the retrieval when the season start date and accumulated temperature are used to complement the backscatter.
Global Calibration and Error Estimation of Altimeter, Scatterometer, and Radiometer Wind Speed Using Triple Collocation
Authors: Ribal Agustinus , Young Ian R.
Published: June 2020

The accuracy of wind speed measurements is important in many applications. In the present work, error standard deviations of wind speed measured by satellites and National Data Buoy Center (NDBC) buoys were estimated using triple collocation. The satellites included six altimeters, three scatterometers, and four radiometers. The six altimeters were TOPEX, ERS-2, JASON-1, ENVISAT, JASON-2, and CRYOSAT-2, whilst the three scatterometers were QUIKSCAT, METOP-A, and METOP-B and the four radiometers included SSMI-F15, AMSR-2, WINDSAT, and GMI. Hence, a total of 14 platform measurements, including NDBC buoy data, were used and the error standard deviations of each estimated. It was found that altimeters have the smallest error standard deviations for wind speed measurements followed by scatterometers and then radiometers. NDBC buoys have the largest error standard deviation. Since triple collocation can simultaneously perform error estimation as well as calibration for a given reference, this method enables us to perform intercalibration between platform measurements including NDBC buoy. In addition, the calibration relations obtained from triple collocation were compared with the calibrations obtained from the widely used reduced major axis (RMA) regression approach. This method, to some extent, can accommodate measurements in which both platforms contain errors. The results showed that calibration relations obtained from RMA and triple collocation are very similar, as indicated by statistical parameters such as RMSE, correlation coefficient, scatter index, and bias.
Airborne Validation Experiment of 1.57-μm Double-Pulse IPDA LIDAR for Atmospheric Carbon Dioxide Measurement
Authors: Zhu Yadan , Yang Juxin , Chen Xiao , Zhu Xiaopeng , Zhang Junxuan , Li Shiguang , Sun Yanguang , Hou Xia , Bi Decang , Bu Lingbing , Zhang Yang , Liu Jiqiao , Chen Weibiao
Published: June 2020

The demand for greenhouse gas measurement has increased dramatically due to global warming. A 1.57-μm airborne double-pulse integrated-path differential absorption (IPDA) light detection and ranging (LIDAR) system for CO2 concentration measurement was developed. The airborne field experiments of this IPDA LIDAR system were conducted at a flight altitude of approximately 7 km, and the weak echo signal of the ocean area was successfully received. The matched filter algorithm was applied to the retrieval of the weak signals, and the pulse integration method was used to improve the signal-to-noise ratio. The inversion results of the CO2 column-averaged dry-air mixing ratio (XCO2) by the scheme of averaging after log (AVD) and the scheme of averaging signals before log were compared. The AVD method was found more effective for the experiment. The long-term correlation between the changing trends of XCO2 retrieved by the IPDA LIDAR system and CO2 dry-air volume mixing ratio measured by the in-situ instrument reached 92%. In the steady stage of the open area (30 km away from the coast), which is almost unaffected by the residential areas, the mean value of XCO2 retrieved by the IPDA LIDAR system was 414.69 ppm, with the standard deviation being 1.02 ppm. Compared with the CO2 concentration measured by the in-situ instrument in the same period, bias was 1.30 ppm. The flight path passed across the ocean, residential, and mountainous areas, with the mean value of XCO2 of the three areas being 419.35, 429.29, and 422.52 ppm, respectively. The gradient of the residential and ocean areas was 9.94 ppm, with that of the residential and mountainous areas being 6.77 ppm. Obvious gradients were found in different regions.
Generating Elevation Surface from a Single RGB Remotely Sensed Image Using Deep Learning
Authors: Panagiotou Emmanouil , Chochlakis Georgios , Grammatikopoulos Lazaros , Charou Eleni
Published: June 2020

Generating Digital Elevation Models (DEM) from satellite imagery or other data sources constitutes an essential tool for a plethora of applications and disciplines, ranging from 3D flight planning and simulation, autonomous driving and satellite navigation, such as GPS, to modeling water flow, precision farming and forestry. The task of extracting this 3D geometry from a given surface hitherto requires a combination of appropriately collected corresponding samples and/or specialized equipment, as inferring the elevation from single image data is out of reach for contemporary approaches. On the other hand, Artificial Intelligence (AI) and Machine Learning (ML) algorithms have experienced unprecedented growth in recent years as they can extrapolate rules in a data-driven manner and retrieve convoluted, nonlinear one-to-one mappings, such as an approximate mapping from satellite imagery to DEMs. Therefore, we propose an end-to-end Deep Learning (DL) approach to construct this mapping and to generate an absolute or relative point cloud estimation of a DEM given a single RGB satellite (Sentinel-2 imagery in this work) or drone image. The model has been readily extended to incorporate available information from the non-visible electromagnetic spectrum. Unlike existing methods, we only exploit one image for the production of the elevation data, rendering our approach less restrictive and constrained, but suboptimal compared to them at the same time. Moreover, recent advances in software and hardware allow us to make the inference and the generation extremely fast, even on moderate hardware. We deploy Conditional Generative Adversarial networks (CGAN), which are the state-of-the-art approach to image-to-image translation. We expect our work to serve as a springboard for further development in this field and to foster the integration of such methods in the process of generating, updating and analyzing DEMs.
Assessment of Tuff Sea Cliff Stability Integrating Geological Surveys and Remote Sensing. Case History from Ventotene Island (Southern Italy)
Authors: Daniela Ruberti , Ermanno Marino , Antonio Pignalosa , Pasquale Romano , Marco Vigliotti
Published: June 2020

This study provides a detailed integrated analysis of the erosional processes affecting the volcanoclastic headlands of a pocket beach, of a typical Tyrrhenian volcanic island (Ventotene, south Italy). It compares the survey carried out in 2012 and the recent landslides that occurred in 2018–2020. The studied tuff cliff is characterised by steep, up to overhanging walls affected by a fracture network, which locally isolates blocks in precarious equilibrium. The stability conditions of the southern Cala Nave Bay sea cliff were evaluated by integrating a geological field survey, structural analysis of discontinuities, and a detailed topographic survey consisting of a terrestrial laser scanner (TLS) and photogrammetry data acquisition and processing, providing a three-dimensional (3D) model of the sea cliff. The 3D model of the area affected by the recent landslides was created using proximity photogrammetry, the Structure for Motion (SfM) methodology. The fracture network was represented by using high-resolution digital models and projected to realize geostructural vertical mapping of the cliff. The data acquired in 2012 were more recently compared with further surveys carried out, following rock failures that occurred in winter 2019–2020. The detachment planes and failure modalities coincide perfectly with the ones previously assessed. The applied techniques and the comparison with the recent rock failures have proven to be important in defining these conditions to address risk mitigation interventions.
Supporting Urban Weed Biosecurity Programs with Remote Sensing
Authors: Sheffield Kathryn , Dugdale Tony
Published: June 2020

Weeds can impact many ecosystems, including natural, urban and agricultural environments. This paper discusses core weed biosecurity program concepts and considerations for urban and peri-urban areas from a remote sensing perspective and reviews the contribution of remote sensing to weed detection and management in these environments. Urban and peri-urban landscapes are typically heterogenous ecosystems with a variety of vectors for invasive weed species introduction and dispersal. This diversity requires agile systems to support landscape-scale detection and monitoring, while accommodating more site-specific management and eradication goals. The integration of remote sensing technologies within biosecurity programs presents an opportunity to improve weed detection rates, the timeliness of surveillance, distribution and monitoring data availability, and the cost-effectiveness of surveillance and eradication efforts. A framework (the Weed Aerial Surveillance Program) is presented to support a structured approach to integrating multiple remote sensing technologies into urban and peri-urban weed biosecurity and invasive species management efforts. It is designed to support the translation of remote sensing science into operational management outcomes and promote more effective use of remote sensing technologies within biosecurity programs.
Post-Earthquake Night-Time Light Piecewise (PNLP) Pattern Based on NPP/VIIRS Night-Time Light Data: A Case Study of the 2015 Nepal Earthquake
Authors: Gao Shengjun , Chen Yunhao , Liang Long , Gong Adu
Published: June 2020

Earthquakes are unpredictable and potentially destructive natural disasters that take a long time to recover from. Monitoring post-earthquake human activity (HA) is of great significance to recovery and reconstruction work. There is a strong correlation between night-time light (NTL) and HA, which aid in the study of spatiotemporal changes in post-earthquake human activities. However, seasonal and noise impact from National Polar-Orbiting Partnership Satellite Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) data greatly limits their application. To tackle these issues, random noise and seasonal fluctuation of NPP/VIIRS from January 2014 to December 2018 is removed by adopting the seasonal-trend decomposition procedure based on loess (STL). Based on the theory of post-earthquake recovery model, a post-earthquake night-time light piecewise (PNLP) pattern is explored by employing the National Polar-Orbiting Partnership Satellite Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) monthly data. PNLP indicators, including pre-earthquake development rate (kp), recovery rate (kr1), reconstruction rate (kr2), development rate (kd), relative reconstruction rate (krp) and loss (S), are defined to describe the PNLP pattern. Furthermore, the 2015 Nepal earthquake is chosen as a case study and the spatiotemporal changes in different areas are analyzed. The results reveal that: (1) STL is an effective algorithm for obtaining HA trend from the time series of denoising NTL; (2) the PNLP pattern, divided into four phases, namely the emergency phase (EP), recovery phase (RP-1), reconstruction phase (RP-2), and development phase (DP), aptly describes the variation in post-earthquake HA; (3) PNLP indicators are capable of evaluating the recovery differences across regions. The main socio-economic factors affecting the PNLP pattern and PNLP indicators are energy source for lighting, type of building, agricultural economy, and human poverty index. Based on the NPP/VIIRS data, the PNLP pattern can reflect the periodical changes of HA after earthquakes and provide an effective means for the analysis and evaluation of post-earthquake recovery and reconstruction.
Combination of Cross- and Inter-Band Radiometric Calibrations for a Hyperspectral Sensor Using Model-Based Spectral Band Adjustment
Authors: Mizuochi Hiroki , Tsuchida Satoshi , Obata Kenta , Yamamoto Hirokazu , Yamamoto Satoru
Published: June 2020

Recently, the growing number of hyperspectral satellite sensors have increased the demand for a flexible and robust approach to their calibration. This paper proposes an operational method for the simultaneous correction of inter-sensor and inter-band biases in hyperspectral sensors via the soil line concept for spectral band adjustment. Earth Observing-1 Hyperion was selected as an example, with the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) as a reference. The results over the Railroad Valley Playa calibration site indicated that the discrepancy in the analogous bands between Hyperion and MODIS during 2001–2008 was approximately 4–6% and 7–9% of the root-mean-square error in the top-of-atmosphere (TOA) radiance at the visible and near-infrared region and shortwave infrared region, respectively. For all Hyperion bands, the relative cross-calibration coefficients during this period were calculated (typically ranging from 0.9 to 1.1) to correct the Hyperion TOA radiance to be consistent with the MODIS and the other Hyperion bands. The application of the proposed approach could allow for more flexible cross-calibration of irregular-orbit sensors aboard the International Space Station.
Improved Ice Velocity Measurements with Sentinel-1 TOPS Interferometry
Authors: Andersen Jonas Kvist , Kusk Anders , Boncori John Peter Merryman , Hvidberg Christine Schøtt , Grinsted Aslak
Published: June 2020

In recent years, the Sentinel-1 satellites have provided a data archive of unprecedented volume, delivering C-band Synthetic Aperture Radar (SAR) acquisitions over most of the polar ice sheets with a repeat-pass period of 6–12 days using Interferometric Wide swath (IW) imagery acquired in Terrain Observation by Progressive Scans (TOPS) mode. Due to the added complexity of TOPS-mode interferometric processing, however, Sentinel-1 ice velocity measurements currently rely exclusively on amplitude offset tracking, which generates measurements of substantially lower accuracy and spatial resolution than would be possible with Differential SAR Interferometry (DInSAR). The main difficulty associated with TOPS interferometry lies in the spatially variable azimuth phase contribution arising from along-track motion within the scene. We present a Sentinel-1 interferometric processing chain, which reduces the azimuth coupling to the line-of-sight phase signal through a spatially adaptive coregistration refinement incorporating azimuth velocity measurements. The latter are based on available ice velocity mosaics, optionally supplemented by Burst-Overlap Multi-Aperture Interferometry. The DInSAR processing chain is demonstrated for a large drainage basin in Northeast Greenland, encompassing the Northeast Greenland Ice Stream (NEGIS), and integrated with state-of-the-art offset tracking measurements. In the ice sheet interior, the combined DInSAR and offset tracking ice velocity product provides a spatial resolution of 50 × 50 m and 1-sigma accuracies of 0.18 and 0.44 m/y in the x and y components respectively, compared to GPS.
Recognition of EEG Signal Motor Imagery Intention Based on Deep Multi-View Feature Learning
Authors: Xu Jiacan , Zheng Hao , Wang Jianhui , Li Donglin , Fang Xiaoke
Published: June 2020

Recognition of motor imagery intention is one of the hot current research focuses of brain-computer interface (BCI) studies. It can help patients with physical dyskinesia to convey their movement intentions. In recent years, breakthroughs have been made in the research on recognition of motor imagery task using deep learning, but if the important features related to motor imagery are ignored, it may lead to a decline in the recognition performance of the algorithm. This paper proposes a new deep multi-view feature learning method for the classification task of motor imagery electroencephalogram (EEG) signals. In order to obtain more representative motor imagery features in EEG signals, we introduced a multi-view feature representation based on the characteristics of EEG signals and the differences between different features. Different feature extraction methods were used to respectively extract the time domain, frequency domain, time-frequency domain and spatial features of EEG signals, so as to made them cooperate and complement. Then, the deep restricted Boltzmann machine (RBM) network improved by t-distributed stochastic neighbor embedding(t-SNE) was adopted to learn the multi-view features of EEG signals, so that the algorithm removed the feature redundancy while took into account the global characteristics in the multi-view feature sequence, reduced the dimension of the multi-visual features and enhanced the recognizability of the features. Finally, support vector machine (SVM) was chosen to classify deep multi-view features. Applying our proposed method to the BCI competition IV 2a dataset we obtained excellent classification results. The results show that the deep multi-view feature learning method further improved the classification accuracy of motor imagery tasks.
Porous Graphene Oxide Decorated Ion Selective Electrode for Observing Across-Cytomembrane Ion Transport
Authors: Hu Shihui , Zhang Rong , Jia Yunfang
Published: June 2020

The technology for measuring cytomembrane ion transport is one of the necessities in modern biomedical research due to its significance in the cellular physiology, the requirements for the non-invasive and easy-to-operate devices have driven lots of efforts to explore the potential electrochemical sensors. Herein, we would like to evidence the exploitation of the porous graphene oxide (PGO) decorated ion selective electrode (ISE) as a detector to capture the signal of cytomembrane ion transport. The tumor cells (MDAMB231, A549 and HeLa) treated by iodide uptake operation, with and without the sodium-iodide-symporter (NIS) expression, are used as proofs of concept. It is found that under the same optimized experimental conditions, the changed output voltages of ISEs before and after the cells’ immobilization are in close relation with the NIS related ion’s across-membrane transportation, including I−, Na+ and Cl−. The explanation for the measured results is proposed by clarifying the function of the PGO scaffold interfacial micro-environment (IME), that is, in this spongy-like micro-space, the NIS related minor ionic fluctuations can be accumulated and amplified for ISE to probe. In conclusion, we believe the integration of the microporous graphene derivatives-based IME and ISE may pave a new way for observing the cytomembrane ionic activities.
Spectral Analysis of Macro-Fiber Composites Measured Vibration of Double-Panel Structure Coupled with Solenoids
Authors: Chraponska Anna , Rzepecki Jaroslaw , Isaac Chukwuemeke William , Mazur Krzysztof , Pawelczyk Marek
Published: June 2020

Noise may have a negative impact on humans health and well being. Noise is a direct result of the vibration of structures. Many industrial workers and people using household appliances may be exposed to these harmful factors. To minimize their negative consequences, different approaches to noise and vibration reduction may be applied, e.g., active, semi-active or passive methods. In this research, a semi-active approach to vibration reduction of a cubic rigid casing enclosing a noise- and vibration-generating device is presented. One of the casing walls consists of double thin steel panels, coupled with the use of electromagnetic dampers—solenoids installed in the space between the panels. Other casing walls are built of single plywood panels. Vibrations of the outer (radiating) panel of the wall are measured by Macro-Fiber Composite patches. Spectral analysis of structure vibration is carried out to identify the benefits of the proposed coupling solution in terms of vibration reduction of the wall. The frequency range, where vibration reduction is observed, depends on the number of activated solenoids and the duty cycle of a Pulse Width Modulation (PWM) signal. Advantages and drawbacks of the proposed method are discussed and future improvements of the examined setup are suggested.
A Federated Derivative Cubature Kalman Filter for IMU-UWB Indoor Positioning
Authors: He Chengyang , Tang Chao , Yu Chengpu
Published: June 2020

The inertial measurement unit and ultra-wide band signal (IMU-UWB) combined indoor positioning system has a nonlinear state equation and a linear measurement equation. In order to improve the computational efficiency and the localization performance in terms of the estimation accuracy, the federated derivative cubature Kalman filtering (FDCKF) method is proposed by combining the traditional Kalman filtering and the cubature Kalman filtering. By implementing the proposed FDCKF method, the observations of the UWB and the IMU can be effectively fused; particularly, the IMU can be continuously calibrated by UWB so that it does not generate cumulative errors. Finally, the effectiveness of the proposed algorithm is demonstrated through numerical simulations, in which FDCKF was compared with the federated cubature Kalman filter (FCKF) and the federated unscented Kalman filter (FUKF), respectively.
Sustainable Growth in the Agro-Food Cooperatives of Castilla-La Mancha (Spain)
Authors: Hernández-Perlines Felipe , Ariza-Montes Antonio , Araya-Castillo Luis
Published: June 2020

The present study aims at analysing the sustainable growth in the agro-food cooperatives of Castilla-La Mancha (Spain). To this end, the study examines the impact of the corporate social responsibility (hereinafter CSR) on the performance of the agro-food cooperatives. CSR is analysed based on the three dimensions suggested by the triple bottom line approach: Economic dimension, social dimension, and environmental dimension. Results are analysed using a partial least squares regression (PLS-SEM). The main contributions are as follows: (1) The measurement of the CSR through the triple bottom line approach has proven to be appropriate for the agro-food cooperatives of Castilla-la Mancha, as it presents adequate values of reliability and validity; (2) these dimensions make up the CSR, although the environmental dimension is the most relevant one for the agro-food cooperatives of Castilla-La Mancha; and (3) CSR positively and significantly affects the performance of agro-food cooperatives, as it explains 39.2% of their variance, thus confirming a sustainable growth model for the agro-food cooperatives of Castilla-La Mancha.
What Influences the Servitization Process the Most? A Perspective of Polish Machinery Manufacturers
Authors: Kozlowska Justyna
Published: June 2020

The servitization of manufacturing is an increasingly popular way to win market competition and maintain this advantage as well as to ensure more sustainable development of the manufacturing sector. To make this strategy effective, many aspects should be considered. This study mainly aims to identify the most significant factors influencing the process of servitization in the manufacturing sector. An additional research problem that emerged in the research process was aimed at determining the factors perceived by entrepreneurs as more important compared to others, and, correspondingly, the reasons behind such differences of opinion. This article is supported by the results of a literature review, the outcomes of a questionnaire survey (conducted with 150 Polish machinery manufacturers), and the findings of in-depth interviews with experts. In the light of the results of the quantitative research, the most important aspects that determine the servitization process are customer requirements and preferences; economic and financial aspects; added value for the customer and the company; and also the relations, stakeholders and partners of the service processes. More specific determinants, such as long-lasting and stronger relationships, organizational strategy, legal regulations regarding the provision of long-term services, and the economic benefits of service recipients, were indicated by experts as crucial in product–service integration. Also, employees’ competencies were emphasized as vital for extending the service activity of manufacturing companies. The contribution of this study is twofold. First, it identifies the most important aspects for the analysis of a manufacturer starting out on the servitization path. Second, the study reveals differences in the perception of the importance of certain factors that appear to be related to the experience related to the provision of services by machine manufacturers. Hence, some practical guidelines may be drawn for managers of manufacturing companies who plan to extend their service offer.
Sustainability Management of Organic Food Organizations: A Case Study of Azerbaijan
Authors: Guliyeva Aygun E. , Lis Marcin
Published: June 2020

Potentially, sustainable development can lead to the global alignment of goals and values, such as social justice and environmental balance. This study examines the supplier sustainability management programs that exist in the food industry and combine economic, environmental, and social priorities using sustainability theory. The study aims to identify sustainability priorities and develops recommendations for Azerbaijani agrifood policy in order to ensure the dynamic sustainable development of the national food industry and economy. The analytic hierarchy process (AHP) model and the priority theory enabled the identification of global priorities in relation to Ganja Agribusiness Association (GABA). These priorities include climatic conditions issues, certification standards and labels, possibility of acquiring land in private ownership, price of land, and qualification characteristics of the workforce.
The Possibility of Sustainable Urban Horticulture Based on Nature Therapy
Authors: Lu Na , Song Chorong , Kuronuma Takanori , Ikei Harumi , Miyazaki Yoshifumi , Takagaki Michiko
Published: June 2020

Population growth and increased stress caused by urbanization have led to social problems that are predicted to intensify in the future. In these conditions, the recently established ”nature therapy” has revealed that an environment rich in various plant life significantly contributes to the relief of physical and mental stress. Meanwhile, from the perspective of reduction in the energy required for transportation and the retention of plant freshness, urban horticulture, in which plant life exists harmoniously with the city, has attracted considerable attention. Interactions between humans and plants in urban horticulture are considered to contribute to the good health and wellbeing of people. Therefore, we incorporate human-centered thinking based on nature therapy into horticultural produce-centered thinking based on conventional urban horticulture. By introducing a pioneering urban horticulture plant factory as an example, we propose the possibility of sustainable urban horticulture based on nature therapy.
Why Italy First? Health, Geographical and Planning Aspects of the COVID-19 Outbreak
Authors: Murgante Beniamino , Borruso Giuseppe , Balletto Ginevra , Castiglia Paolo , Dettori Marco
Published: June 2020

COVID-19 hit Italy in February 2020 after its outbreak in China at the beginning of January. Why was Italy first among the Western countries? What are the conditions that made Italy more vulnerable and the first target of this disease? What characteristics and diffusion patterns could be highlighted and hypothesized from its outbreak to the end of March 2020, after containment measures, including a national lockdown, were introduced? In this paper, we try to provide some answers to these questions, analyzing the issue from medical, geographical and planning points of view. With reference to the Italian case, we observed the phenomenon in terms of the spatial diffusion process and by observing the relation between the epidemic and various environmental elements. In particular, we started from a hypothesis of the comparable economic, geographical, climatic and environmental conditions of the areas of Wuhan (in the Hubei Province in China, where the epidemic broke out) and the Po Valley area (in Italy) where most cases and deaths were registered. Via an ecological approach, we compared the spatial distribution and pattern of COVID-19-related mortality in Italy with several geographical, environmental and socio-economic variables at a Provincial level, analyzing them by means of spatial analytical techniques such as LISA (Local Indicators of Spatial Association). Possible evidence arose relating to COVID-19 cases and Nitrogen-related pollutants and land take, particularly in the Po Valley area.
Blockchain Application for the Paris Agreement Carbon Market Mechanism—A Decision Framework and Architecture
Authors: Schletz Marco , Franke Laura A. , Salomo Søren
Published: June 2020

This paper evaluates the suitability of blockchain technology for the Article 6.2 carbon market mechanism of the Paris Agreement. The bottom-up approach of the Paris Agreement causes challenges to the robust accounting of mitigation outcomes and information asymmetry, both of which result from a high number of heterogeneous emission accounting systems. Blockchain is an innovative technology that can act as an aggregation platform for these fragmented systems while enhancing transparency and automating accounting processes. However, this new technology is not a panacea for all problems, and the trade-offs of applying blockchain technology need to be assessed case by case. We create and apply an eight-step decision framework for testing the applicability of the technology for the Paris Agreement Article 6.2 carbon market mechanism. The analysis shows that, under current mechanism specifications, a blockchain application can enhance transparency and increase automation, thereby eliminating information asymmetry. We outline a system architecture that allows the linking of the heterogeneous systems, the integration of an Article 6.2 exchange mechanism, and the progress tracking of climate targets. This blockchain architecture offers national Parties the opportunity to co-create a decentralised system in line with the bottom-up ethos of the Paris Agreement.
Filmic Gendered Discourses in Rural Contexts: The Case of the Camino de Santiago (Spain)
Authors: Lopez Lucrezia
Published: June 2020

Rural areas have turned into multifunctional areas. They satisfy different economic and social requirements; among these, they are consolidating their position as film production locations. Becoming a film location ensures visibility and provides new forms to access sustainable economic trajectories to promoting rural areas and rural vitality. In some cases, filmic discourses present unequal gender treatment that may be associated with their locations. Considering this, the aim of this research was to explore cinematic discourses based on the symmetry or asymmetry in gendered cinematic representations that mainly occur in the rural space of the Camino de Santiago (Spain). This First European Cultural route crosses urban and rural centers that have benefited in different ways from its international recognition. By combining both the linguistic and visual codes, I engaged in a qualitative film discourse analysis concerning female pilgrims along the route. Despite of the feminization of the Camino, the results prove the permanence of gendered norms and societal roles in audio-visual productions based on a common latent ideology. The conclusions introduce the concept of social and relational sustainability as a way to achieve equal gender treatment when creating media discourses.
Local Fresh Food Products and Plant-Based Diets: An Analysis of the Relation Between Them
Authors: Arenas-Gaitán Jorge , Peral-Peral Begoña , Reina-Arroyo Jesús
Published: June 2020

Goal number 12 of the United Nations Sustainable Development Goals proposes attaining sustainable production and consumption. Public administrations, firms, and organizations must be involved in this achievement, as well as citizens as consumers. In our case, we focus on consumers and on two food-related decisions: the buying and consumption of local products, specifically vegetables and fruits, and the decision to follow a plant-based diet, concretely vegans and vegetarians. The aim is to check if there exists a relation between the two questions. We carried out empirical research in a South European city, and we found that a significant relation between these behaviors does not exist. It is necessary to increase consumer perception about the advantages of consuming local products, reducing the limitations that they come across, and transmitting clear information from administrations and industries. Greater involvement from consumers in sustainable food practices will contribute to sustainability.
Factors Determining the Development of Small Farms in Central and Eastern Poland
Authors: Hornowski Andrzej , Parzonko Andrzej , Kotyza Pavel , Kondraszuk Tomasz , Bórawski Piotr , Smutka Luboš
Published: June 2020

The agrarian structure in Poland is dominated by small farms; the large share of these is a result of historical consequences. The economy has pushed small farms toward economic efficiency, which in farming often translates into increasing the scale of production. The primary objective of this research was to present the directions of the changes in the number of small farms in Central and Eastern Poland and to indicate the factors determining their functioning and development. The research was based on a random sample selection from rural municipalities, villages and small farms. The researchers collected 19 completed surveys from municipal agricultural officers, 75 surveys from village mayors and 116 surveys from small and active farms. The data from the farm surveys was analysed using k-mean cluster analyses and the Principal Component Analysis (PCA) to distinguish farms into homogenous groups. Three types of farms were identified: “hobby”, “two-occupation” and “professional” farms. The research shows that in the municipalities of Central and Eastern Poland, the number of landowners (over 1 ha of arable land) paying agricultural tax increased by 9% between 2005 and 2017. A significant gap was identified between the number of “official farmers” and “active” farmers. In the farm category surveyed, “active” farmers numbered only 33% of all farming entities. The surveys confirmed that the development of small farms is particularly influenced by external factors (EU funding; national benefits), rather than internal (entrepreneurial) factors. An in-depth survey of farmers, municipal agricultural officers and village mayors shows that “professional” farmers (Cluster 0) are expected to invest, develop and innovate. Farmers managing “hobby” and “two-occupation” farms have a reserved attitude towards investment and their objective is to maximise the benefits related to the arming status. In the authors’ opinions, “professional” farms have the highest probability of being economically viable, while others tend to focus on the provision of public goods related to financial support.
Designing and Implementing Effective Campus Sustainability in Saudi Arabian Universities: An Assessment of Drivers and Barriers in a Rational Choice Theoretical Context
Authors: Alsharif Mohammad A. , Peters Michael D. , Dixon Timothy J.
Published: June 2020

Saudi Arabia is a developing country that is experiencing a rapid growth in its population and level of urbanisation. Higher education (HE) in the country has developed rapidly over the last ten years, and it is still moving through numerous major reforms. Largely, the concept of sustainability has not yet been formally adopted in public institutions in a way that could sufficiently remedy the range of activities that currently impact negatively on the environment. The central aim of this paper is to examine the extent to which planning and action for sustainability is currently being taken on university campuses in Saudi Arabia, and to review the opportunities and challenges for encouraging and enabling further progress to this end. The research that the paper draws on specifically investigated the influence of decision makers’ personal knowledge and perceptions within Facilities and Project Management (FPM) departments at selected Saudi universities, and the constraints faced by FPM decision makers with regard to the promotion of sustainability on campus. This exploration was supported by the development of a theoretical framework that draws on rational choice theory (RCT). The research revealed mixed levels of prevailing knowledge and awareness towards sustainability among FPM decision makers within the case study university campuses. Cost notably came across as a dominant influence on FPM decision makers’ choices and decisions, and it undoubtedly plays an important role in shaping the decision-making process alongside other key organisational factors. A number of barriers facing the incorporation of sustainability emerged with clarity, such as the lack of supportive leadership, the lack of sustainability knowledge and awareness among senior management and an absence of sustainability-related legislation policy or strategic direction in the HEIs concerned.
The Relationship between High Speed Rail and Tourism
Authors: Jou Rong-Chang , Chen Ke-Hong
Published: June 2020

Much research has verified that the active development of the High Speed Rail (HSR) can create business activities and promote tourism growth. However, based on the related research review, there is currently a lack of profound discussion on the development of the overall transportation system and tourism growth in Taiwan, thus, this study intends to discuss this issue and hopes to provide an important reference for future regional development. This study conducts an in-depth investigation of the relationship between HSR and tourism volume. The Difference in Difference (DID) model is used to verify the impact of HSR services on the tourism volume in Taiwan. In addition, the aggregate data of socio-economic variables and the constituent factors of the transportation mode are incorporated. Finally, the possible consequences are described through elastic analysis. The results of this study can be an important reference for the future development of counties and cities.
An Interdisciplinary Approach to the Sustainable Management of Territorial Resources in Hodh el Chargui, Mauritania
Authors: Caselle Chiara , Bonetto Sabrina Maria Rita , De Luca Domenico Antonio , Lasagna Manuela , Perotti Luigi , Bucci Arianna , Bechis Stefano
Published: June 2020

The present study proposes an analytical investigation of the natural resources and social framework of the Hodh el Chargui region (Mauritania), aiming to offer a useful instrument for planning and management to the local authorities. The situation of the region was evaluated by means of a participatory survey carried out among the local inhabitants. The obtained results include a collection of data about population, territorial organization, access to basic education and health services, infrastructure, main economic activities, and natural resources (in terms of water, both surface and groundwater, duration and intensity of rainfalls, soil types, and vegetal resources). The survey outcomes were completed with an integrated approach based on Earth Observation (EO) data supports, such as digital elevation models (DEMs) and Landsat8 imagery. The interdependence among the different data was evaluated and discussed, with regard to the influence of the availability of natural resources on the development of agricultural activities and on the general social welfare. The results are organized in the form of digital maps and a user-friendly webmap platform to facilitate access for all the technical and nontechnical actors involved in the project.