bluuebunny/crossref_metadata_2025 huggingface dataset:
Mesenchymal Stem Cell-Derived Extracellular Vesicles as Non-Coding RNA Therapeutic Vehicles in Autoimmune Diseases
Authors: Martinez-Arroyo Olga , Ortega Ana , Forner Maria J. , Cortes Raquel
Published: March 2022

Autoimmune diseases (ADs) are characterized by the activation of the immune system against self-antigens. More common in women than in men and with an early onset, their incidence is increasing worldwide, and this, combined with their chronic nature, is contributing to an enlarged medical and economic burden. Conventional immunosuppressive agents are designed to alleviate symptoms but do not constitute an effective therapy, highlighting a need to develop new alternatives. In this regard, mesenchymal stem cells (MSCs) have demonstrated powerful immunosuppressive and regenerative effects. MSC-derived extracellular vesicles (MSC-EVs) have shown some advantages, such as less immunogenicity, and are proposed as novel therapies for ADs. In this review, we summarize current perspectives on therapeutic options for ADs based on MSCs and MSC-EVs, focusing particularly on their mechanism of action exerted through their non-coding RNA (ncRNA) cargo. A complete state-of-the-art review was performed, centralized on some of the most severe ADs (rheumatoid arthritis, autoimmune type 1 diabetes mellitus, and systemic lupus erythematosus), giving evidence that a promising field is evolving to overcome the current knowledge and provide new therapeutic possibilities centered on MSC-EVs and their role as ncRNA delivery vehicles for AD gene therapy.
Sound Insulation Properties of Hollow Polystyrene Spheres/Polyethylene Glycol/Epoxy Composites
Authors: Shi Xuejun , Shi Guangling , Li Songtian , Du Xiangxiang , Han Yongjun
Published: March 2022

The generation of noise requires a noise source, transmission path, and passive acceptance target of noise, all of which are indispensable. Blocking the propagation path of noise is one of the available means when the existence of the noise source and passive receiving target cannot be addressed. This is an effective way to prevent noise pollution, often using sound insulation materials to block the path of noise transmission. In this work, composites with excellent sound insulation properties were designed and prepared. These composites, using epoxy resin (EP) as the matrix, polyethylene glycol (PEG), and hollow polystyrene spheres (HPS), were added to epoxy resin as a toughening agent and functional filler to prepare the ternary HPS/PEG/EP composites. The soundproofing results showed that when the thickness of the sample was 3 mm, the average sound transmission loss (STL) value of the neat EP and the HPS/PEG/EP composites with an HPS 32 vol% was up to 19.0 dB and 42.1 dB, and the STL values of the composites were increased by approximately 120% compared to the pure epoxy. When the sample was 10 mm thick, the average STL value of the HPS/PEG/EP composites with HPS 32 vol% contents was enhanced to 55.7 dB.
Flexural Performance of Concrete Beams Reinforced with Continuous FRP Bars and Discrete Steel Fibers under Cyclic Loads
Authors: Zhu Haitang , Li Chuanchuan , Cheng Shengzhao , Yuan Jiansong
Published: March 2022

This research investigated the flexural behavior of high-strength concrete beams reinforced with continuous basalt fiber-reinforced polymer (BFRP) bars and discrete steel fibers. Five concrete beams with the dimensions of 150 × 300 × 2100 mm3 were constructed and tested to failure under four-point bending cyclic loading. The specimens consisted of four BFRP-reinforced concrete beams with various reinforcement ratios (ρf), namely, 0.56%, 0.77%, 1.15%, and 1.65%, and one conventional steel-reinforced concrete beam for comparison purposes. The cracking behavior, failure modes, load-deflection behavior, residual deformation, and stiffness degradation of the beams were studied. Additionally, a deformation-based approach was used to analyze the deformability of the beams. The results show that an increase in the ρf effectively restrained the crack widths, deflections, and residual deformation while also enhancing the flexural bearing capacity of the beams. In comparison to the first displacement cycle, the bearing capacity dropped by 10% on average in the third cycle. The stiffness exhibited a fast to slow degradation trend until failure. The residual stiffnesses were higher in beams with a higher ρf. The over-reinforced beams had superior deformability than the under-reinforced beams, according to the deformability factors.
The Staring Mode Properties and Performance of Geo-SAR Satellite with Reflector Antenna
Authors: Zhao Bingji , Zhang Qingjun
Published: March 2022

Geosynchronous synthetic aperture radar (Geo-SAR) with a short revisit time can obtain wide-area images. This paper advances a new two-dimensional pitch and roll squint controlling (2D-PRSC) method that can make satellites continuously stare at any scene in the whole orbital period. The maximum attitude steering angle is less than ±7.6 degrees, and the attitude controlling time can be greatly shortened compared with the yaw steering method. Furthermore, a Geo-SAR staring mode model is illustrated and compared with that of low earth orbital SAR (Leo-SAR). Finally, Geo-SAR’s ambiguity property is discussed. The simulation results illuminate that the cross-term ambiguity to signal ratio (CASR) also needs to be considered in addition to the azimuth and range ambiguity to signal ratio (AASR, RASR), and the whole orbital ergodic analysis should be carried out. To ensure that RASR, AASR, and CASR meet the requirement of −20 dB, it is necessary to select an appropriate PRF in the range of a few hundred Hertz.
Tracking of Maneuvering Extended Target Using Modified Variable Structure Multiple-Model Based on Adaptive Grid Best Model Augmentation
Authors: Sun Lifan , Zhang Jinjin , Yu Haofang , Fu Zhumu , He Zishu
Published: March 2022

Maneuvering extended target tracking, an important but challenging research field, has attracted increasing attention in the field of radar signal processing. Variable structure multiple-model (VSMM) estimation is the current mainstream tracking algorithm, it possesses high tracking performance but depends largely on the model set used. However, the existing model set design methods still cannot offer higher tracking performance due to the complex maneuverability of the target. The current best model augmentation (BMA) algorithm is an efficient and universal model set design method, but it cannot adapt well to complex maneuvering situations because of its fixed basic and candidate model set. Hence, this paper proposes a modified BMA algorithm for VSMM based on adaptive grid, it can make full use of the previous information to realize an adaptation and time variation of the model set. Overall, two different scenarios were considered, wherein the digital simulation shows that the proposed method can provide a more reliable estimation of the kinematic state and shape of the extended target.
Mothership-Cubesat Radioscience for Phobos Geodesy and Autonomous Navigation
Authors: Chen Hongru , Rambaux Nicolas , Lainey Valéry , Hestroffer Daniel
Published: March 2022

The knowledge of the interior structure (e.g., homogeneous, porous, or fractured) of Martian moons will lead to a better understanding of their formation as well as the early solar system. One approach to inferring the interior structure is via geodetic characteristics, such as gravity field and libration. Geodetic parameters can be derived from radiometric tracking measurements. A feasible mothership-CubeSat mission is proposed in this study with following purposes, (1) performing inter-sat Doppler measurements, (2) improving the understanding of Phobos as well as the dynamic model, (3) securing the mothership as well as the primary mission, and (4) supporting autonomous navigation, given the long distance between the Earth and Mars. This study analyzes budgets of volume, mass, power, deployment Δv, and link, and the Doppler measurement noise of the system, and gives a feasible design for the CubeSat. The accuracy of orbit determination and geodesy is revealed via the Monte-Carlo simulation of estimation considering all uncertainties. Under an ephemeris error of the Mars-Phobos system ranging from 0 to 2 km, the autonomous orbit determination delivers an accuracy ranging from 0.2 m to 21 m and 0.05 mm/s to 0.4 cm/s. The geodesy can return 2nd-degree gravity coefficients at an accuracy of 1‰, even in the presence of an ephemeris error of 2 km. The achieved covariance of gravity coefficients and libration amplitude indicates an excellent possibility to distinguish families of interior structures.
Predicting Species and Structural Diversity of Temperate Forests with Satellite Remote Sensing and Deep Learning
Authors: Hoffmann Janik , Muro Javier , Dubovyk Olena
Published: March 2022

Anthropogenically-driven climate change, land-use changes, and related biodiversity losses are threatening the capability of forests to provide a variety of valuable ecosystem services. The magnitude and diversity of these services are governed by tree species richness and structural complexity as essential regulators of forest biodiversity. Sound conservation and sustainable management strategies rely on information from biodiversity indicators that is conventionally derived by field-based, periodical inventory campaigns. However, these data are usually site-specific and not spatially explicit, hampering their use for large-scale monitoring applications. Therefore, the main objective of our study was to build a robust method for spatially explicit modeling of biodiversity variables across temperate forest types using open-access satellite data and deep learning models. Field data were obtained from the Biodiversity Exploratories, a research infrastructure platform that supports ecological research in Germany. A total of 150 forest plots were sampled between 2014 and 2018, covering a broad range of environmental and forest management gradients across Germany. From field data, we derived key indicators of tree species diversity (Shannon Wiener Index) and structural heterogeneity (standard deviation of tree diameter) as proxies of forest biodiversity. Deep neural networks were used to predict the selected biodiversity variables based on Sentinel-1 and Sentinel-2 images from 2017. Predictions of tree diameter variation achieved good accuracy (r2 = 0.51) using Sentinel-1 winter-based backscatter data. The best models of species diversity used a set of Sentinel-1 and Sentinel-2 features but achieved lower accuracies (r2 = 0.25). Our results demonstrate the potential of deep learning and satellite remote sensing to predict forest parameters across a broad range of environmental and management gradients at the landscape scale, in contrast to most studies that focus on very homogeneous settings. These highly generalizable and spatially continuous models can be used for monitoring ecosystem status and functions, contributing to sustainable management practices, and answering complex ecological questions.
High Spatiotemporal Resolution PM2.5 Concentration Estimation with Machine Learning Algorithm: A Case Study for Wildfire in California
Authors: Cui Qian , Zhang Feng , Fu Shaoyun , Wei Xiaoli , Ma Yue , Wu Kun
Published: March 2022

As an aggregate of suspended particulate matter in the air, atmospheric aerosols can affect the regional climate. With the help of satellite remote sensing technology to retrieve AOD (aerosol optical depth) on a global or regional scale, accurate estimation of PM2.5 concentration has become an important task to quantify the spatiotemporal distribution of AOD and PM2.5. However, due to the limitations of satellite platforms, sensors, and inversion algorithms, the spatiotemporal resolution of current major AOD products is still relatively low. Meanwhile, for the impact of cloud, the AOD products often have a serious data gap problem, which also objectively limits the spatiotemporal coverage of predicted PM2.5 concentration. Therefore, how to effectively improve the spatiotemporal resolution and coverage of PM2.5 concentration under the requisite accuracy is still a grand challenge. In this study, the fused high spatial-temporal resolution AOD data in our previous study were used to estimate the ground PM2.5 concentration through machine learning algorithms, the deep belief network (DBN). The PM2.5 data had spatiotemporal autocorrelation in geostatistics and followed the Gaussian kernel distribution. Hence, the autocorrelation model modified by Gaussian kernel function integrated with DBN algorithm, named Geoi-DBN, was used to estimate PM2.5 concentration. The cross-validation results showed that the Geoi-DBN (R2 = 0.86, RMSE = 6.84 µg m−3) performed better than the original DBN (R2 = 0.67, RMSE = 10.46 µg m−3). The final high quality PM2.5 concentration data can be applied for urban air quality monitoring and related PM2.5 exposure risk assessment such as wildfire.
Self-Supervised Stereo Matching Method Based on SRWP and PCAM for Urban Satellite Images
Authors: Chen Wen , Chen Hao , Yang Shuting
Published: March 2022

In this paper, we propose a self-supervised stereo matching method based on superpixel random walk pre-matching (SRWP) and parallax-channel attention mechanism (PCAM). Our method is divided into two stages, training and testing. First, in the training stage, we obtain pre-matching results of stereo images based on superpixel random walk, and some matching points with high confidence are selected as labeled samples. Then, a stereo matching network is constructed to describe the matching correlation by calculating the attention scores of any two points between different images through the parallax-channel attention mechanism, superimposing the scores of each layer to calculate the disparity. The network is trained using the labeled samples and some unsupervised constraint criteria. Finally, in the testing stage, the trained network is used to obtain stereo matching relations of stereo images. The proposed method does not need manually labeled training samples and is more suitable for 3D reconstruction under mass satellite remote sensing data. Comparative experiments on multiple datasets show that our method has a stereo matching EPE of 2.44 and a 3D reconstruction RMSE of 2.36 m. Especially in the weak texture and parallax abrupt change regions, we can achieve more advanced performance than other methods.
Mapping Soil Properties with Fixed Rank Kriging of Proximally Sensed Soil Data Fused with Sentinel-2 Biophysical Parameter
Authors: Karapetsas Nikolaos , Alexandridis Thomas K. , Bilas George , Munnaf Muhammad Abdul , Guerrero Angela P. , Calera Maria , Osann Anna , Gobin Anne , Rezník Tomáš , Moshou Dimitrios , Mouazen Abdul Mounem
Published: March 2022

Soil surveys with line-scanning platforms appear to have great advantages over the traditional methods used to collect soil information for the development of field-scale soil mapping and applications. These carry VNIR (visible and near infrared) spectrometers and have been used in recent years extensively for the assessment of soil fertility at the field scale, and the delineation of site-specific management zones (MZ). A challenging feature of VNIR applications in precision agriculture (PA) is the massiveness of the derived datasets that contain point predictions of soil properties, and the interpolation techniques involved in incorporating these data into site-specific management plans. In this study, fixed-rank kriging (FRK) geostatistical interpolation, which is a flexible, non-stationary spatial interpolation method especially suited to handling huge datasets, was applied to massive VNIR soil scanner data for the production of useful, smooth interpolated maps, appropriate for the delineation of site-specific MZ maps. Moreover, auxiliary Sentinel-2 data-based biophysical parameters NDVI (normalized difference vegetation index) and fAPAR (fraction of photosynthetically active radiation absorbed by the canopy) were included as covariates to improve the filtering performance of the interpolator and the ability to generate uniform patterns of spatial variation from which it is easier to receive a meaningful interpretation in PA applications. Results from the VNIR prediction dataset obtained from a pivot-irrigated field in Albacete, southeastern Spain, during 2019, have shown that FRK variants outperform ordinary kriging in terms of filtering capacity, by doubling the noise removal metrics while keeping the computation cost reasonably low. Such features, along with the capacity to handle a large volume of spatial information, nominate the method as ideal for PA applications with massive proximal and remote sensing datasets.
A High-Performance Convolutional Neural Network for Ground-Level Ozone Estimation in Eastern China
Authors: Wang Sichen , Huo Yanfeng , Mu Xi , Jiang Peng , Xun Shangpei , He Binfang , Wu Wenyu , Liu Lin , Wang Yonghong
Published: March 2022

Having a high-quality historical air pollutant dataset is critical for environmental and epidemiological research. In this study, a novel deep learning model based on convolutional neural network architecture was developed to estimate ground-level ozone concentrations across eastern China. A high-resolution maximum daily average 8-h (MDA8) surface ground ozone concentration dataset was generated with the support of the total ozone column from the satellite Tropospheric Monitoring Instrument, meteorological data from the China Meteorological Administration Land Data Assimilation System, and simulations of the WRF-Chem model. The modeled results were compared with in situ measurements in five cities that were not involved in model training, and the mean R2 of predicted ozone with observed values was 0.9, indicating the good robustness of our model. In addition, we compared the model results with some widely used machine learning techniques (e.g., random forest) and recently published ozone datasets, showing that the accuracy of our model is higher and that the spatial distributions of predicted ozone are more coherent. This study provides an efficient and exact method to estimate ground-level ozone and offers a new perspective for modeling spatiotemporal air pollutants.
SkySat Data Quality Assessment within the EDAP Framework
Authors: Saunier Sebastien , Karakas Gizem , Yalcin Ilyas , Done Fay , Mannan Rubinder , Albinet Clement , Goryl Philippe , Kocaman Sultan
Published: March 2022

Cal/Val activities within the Earthnet Data Assessment Pilot (EDAP) Project of the European Space Agency (ESA) cover several Earth Observation (EO) satellite sensors, including Third-Party Missions (TPMs). As part of the validation studies of very-high-resolution (VHR) sensor data, the geometric and radiometric quality of the images and the mission compliance of the SkySat satellites owned by Planet were evaluated in this study. The SkySat constellation provides optical images with a nominal spatial resolution of 50 cm, and has the capacity for multiple visits of any place on Earth each day. The evaluations performed over several test sites for the purpose of the EDAP Maturity Matrix generation show that the high resolution requirement is fulfilled with high geometric accuracy, although various systematic and random errors could be observed. The 2D and 3D information extracted from SkySat data conform to the quality expectations for the given resolution, although improvements to the vendor-provided rational polynomial coefficients (RPCs) are essential. The results show that the SkySat constellation is compliant with the specifications and the accuracy results are within the ranges claimed by the vendor. The signal-to-noise ratio assessments revealed that the quality is high, but variations occur between the different sensors.
Biophysical Impact of Sunflower Crop Rotation on Agricultural Fields
Authors: Kussul Nataliia , Deininger Klaus , Shumilo Leonid , Lavreniuk Mykola , Ali Daniel Ayalew , Nivievskyi Oleg
Published: March 2022

Crop rotation is an important determining factor of crop productivity. Sustainable agriculture requires correct rules of crop rotation. Failure to comply with these rules can lead to deterioration of soil biochemical characteristics and land degradation. In Ukraine as well as in many other countries, sunflower monocropping is common practice and the impact of this fact should be studied to find the most precise rules to save the economic potential of land and minimize land degradation factors. This research provides an evaluation of the sunflower monocropping effect on the vegetation indices obtained from MODIS vegetation indices datasets for Ukraine as one of the countries with the biggest sunflower export in Europe. The crop rotation schemes are represented by their area proportions at the village level calculated based on the crop classification maps for 2016 to 2020. This representation gives the possibility to use regression models and f-test feature importance analysis to measure the impact of 3-year and 5-year crop rotation sequences. For these purposes, we use several models: a four-year binary representation model (model A1) and a model with all possible three-year crop rotation scheme representations (model B). These models gave the possibility to evaluate crop rotation schemes based on their biophysical impact on the next sunflower plantings and found that sunflower planting with an interval of three or more years is optimal in terms of the sustainability of soil fertility.
A Sustainable Intermodal Location-Routing Optimization Approach: A Case Study of the Bohai Rim Region
Authors: Han Bing , Shi Shanshan , Gao Haotian , Hu Yan
Published: March 2022

The optimal intermodal nodes and routes are two of the most challenging issues for intermodal participants. We present a two-phase approach that includes the fuzzy c-means clustering method (FCM) and a multi-objective optimization model to solve intermodal location-routing issues. A weighted sum technique and a genetic algorithm (GA) are designed to address this model. The two-phase approach is beneficial in meeting different market demand preferences of intermodal participants. It also has applications in solving the sustainable intermodal location-routing problems, further solving the network optimization problem in large-scale scenarios. A typical intermodal transport network in the Bohai Rim region is used to verify the effectiveness of this approach. The results provide references for the participants in the Bohai Rim region to choose the optimal intermodal nodes and routes. The findings also offer theoretical insights for optimizing intermodal networks in other regions of China, with goals of improving sustainable transport efficiencies.
Toward the Sustainable Use of Groundwater Springs: A Case Study from Namibia
Authors: Soetaert Fanny , Wanke Heike , Dupuy Alain , Lusuekikio Vanessa , Gaucher Eric C. , Bordmann Vincent , Fleury Jean-Marc , Franceschi Michel
Published: March 2022

The water supply in drylands mainly relies on groundwater, making it a crucial resource. Springs in southern Africa are often underutilized, and are neither protected nor monitored. Thus, the aim of this study was to evaluate their quality in a sample area in northwestern Namibia and to propose solutions for the sustainable use of springs. In total, 35 springs and hot springs were evaluated in the study area located in the drier part of Namibia (Pmean = 150–400 mm/year), an area highly impacted by ongoing climate change with longer and more frequent drought seasons. The springs there are mostly uncaptured and the discharge is in the form of surface runoff, which is mainly lost to the atmosphere by evaporation. Most of the studied springs were perennial, despite a severe drought period. Local communities rely on the springs mainly for livestock and human consumption, as well as for irrigation. However, 71% of the springs do not have any protective measures. The temperature, pH, conductivity and alkalinity were tested in situ. In total, 20 samples were collected and analyzed for major ions (boron, fluoride, silica and strontium) and total dissolved solids (TDS). The physical and inorganic results mostly indicated good and excellent quality water for human consumption, while the hot springs tended to have poor water quality in terms of Namibian standards, indicating that the water was not fit for human consumption.
Level of Satisfaction among University Students Using Various Transport Modes
Authors: Bouhouras Efstathios , Basbas Socrates , Mintsis Georgios , Taxiltaris Christos , Miltiadou Marios , Nikiforiadis Andreas , Konstantinidou Maria Natalia , Mavropoulou Eleni
Published: March 2022

The level of satisfaction arising from a person’s transportation is an important factor, surely, for the provider of transport services, but its calculation is a rather complex case. Each attempt towards this objective has to be well designed and organized, thus requiring in most cases a significant amount of resources and time. The present paper presents the key findings of a questionnaire-based survey addressed to students at the Aristotle University of Thessaloniki (AUTH) regarding their level of satisfaction on the usage of the available transport modes in the Thessaloniki Metropolitan Area, Greece, and primarily public transport, which was conducted in the framework of the EN.I.R.I.S.S.T. project (a collaboration of 16 research teams representing 11 universities and research centers in Greece). Based on the collected data, a descriptive as well as in-depth statistical analyses were conducted identifying the attributes of the participants’ transportation. Furthermore, by using an algorithm developed in the framework of European research activities, the levels of satisfaction among the university students concerning various transport modes were calculated, emphasizing that a private car is more preferable than public transport, revealing the “weaknesses” of each mode in relation to their provided services, and out of which arises the necessity for measures to deal with them and a need to promote sustainable mobility by policy makers.
Early Sowing of Quinoa Cultivars, Benefits from Rainy Season and Enhances Quinoa Development, Growth, and Yield under Arid Condition in Morocco
Authors: Taaime Nawal , El Mejahed Khalil , Moussafir Mariam , Bouabid Rachid , Oukarroum Abdallah , Choukr-Allah Redouane , El Gharous Mohamed
Published: March 2022

Quinoa is a highly nutritious and gluten-free crop. It is a good alternative crop to cereals in the context of climate change. In the process of introducing quinoa to an arid region of Morocco (Rehamna), late sowing results in stunted plants and low yields due to insufficient precipitations and high temperatures around the flowering stage. Early sowing of short-cycle cultivars constitutes a good strategy to enhance growth and yields. A field experiment was conducted in the Rehamna region in 2020–2021 to investigate the effect of the sowing date on quinoa growth, development, and yield. Two cultivars, ICBA-Q5 and Titicaca, and five sowing dates from 15 November to 15 March were evaluated. Results showed that December sowing enhanced plant height, total leaf area, the number and dry weight of branches, leaves, and panicles, and enhanced quinoa productivity, due to high precipitations, optimal temperatures, and a short photoperiod. The highest grain yield (0.84 t ha−1) was obtained with ICBA-Q5. Late sowing decreased the yield and growth and reduced the number of days to panicle emergence, flowering, and maturity for both cultivars. Early sowing of ICBA-Q5 is recommended to increase quinoa yield in arid regions of Morocco.
Exploring the Multisensory Interaction between Luminous, Thermal and Auditory Environments through the Spatial Promenade Experience: A Case Study of a University Campus in an Oasis Settlement
Authors: Berkouk Djihed , Bouzir Tallal Abdel Karim , Boucherit Samiha , Khelil Sara , Mahaya Chafik , Matallah Mohamed Elhadi , Mazouz Said
Published: March 2022

This paper aimed to develop a multisensory approach in a university campus, based on quantitative and qualitative approaches, investigating sense walk experiences (thermo-visual sound walk) under interactions of luminous, thermal, and auditory environments. The study was conducted in October 2021, in Chetma university campus in Biskra city, southern Algeria, which remains a famous oasis settlement of arid regions over the country. A comparative and correlation analysis was performed between the physical dimensions collected through a walking experience in three campus routes (outdoor, semi-outdoor and indoor). In addition, a multisensory survey of the walking experience on perceptual dimensions was evaluated in parallel to the empirical contribution. The paper shows that walkers’ thermal levels were balanced between neural and slightly hot in different spatial aspects. The glare was almost unperceived regarding the luminous conditions in the study site. The auditory experience reveals that the conducted points were generally quiet and well placed for educational requirements. Findings also show a strong relationship between the physical dimensions of the luminous and auditory environment. Furthermore, the findings suggest that the thermal and luminous environments are more perceptible than the auditory environment for the walkers of the outdoor and indoor routes. In contrast, the semi-outdoor route is often perceptible by the perceptual dimensions of the luminous and auditory environments. The findings on sensorial thresholds and spatial adaption are essential for the educational practices’ architectural and urban strategies for the Saharan cities and oasis settlements.
Romanian Wine Tourism—A Paved Road or a Footpath in Rural Tourism?
Authors: Tănase Mihail Ovidiu , Dina Răzvan , Isac Florin-Lucian , Rusu Sergiu , Nistoreanu Puiu , Mirea Cosmin Nicolae
Published: March 2022

In the last decades, wine tourism (WT) has been a topic of study, especially for researchers from large producer countries. The relationship between wine tourism and rural tourism (RT) has been approached from many angles in the past. Ranking sixth in Europe in having its surface cultivated with vines, Romania is one of the major players in the Old World of wine producers. In Romania, the scientific literature on wine tourism is scarce and has a limited coverage on the subject. The present paper, by its main purpose, raises the curtain of Romanian wine tourism drawing a consumer profile and analyzes the relationship between WT and RT. Through quantitative research with 850 valid wine tourist respondents and a margin of error of 3.36%, we discovered that people who know what wine tourism means are 1.85 times more confident that it will contribute to the development of rural tourism compared to those who know less about the subject. A high number of visits leads to a decrease in the confidence that rural tourism can be developed through wine tourism due to the poor diversification of leisure activities offered by wine cellars and a weak connection between economic activity and local space. In the end, we draw some practical implications for wine cellars. By developing local-based leisure activities, vineyards can contribute to the sustainable development of the local community. Due to the COVID-19 impact on tourism, there are some limitations to our study. Future studies are needed to cover the changes and evolution of this type of tourism.
Characteristics of Overburden and Ground Failure in Mining of Shallow Buried Thick Coal Seams under Thick Aeolian Sand
Authors: Liu Guangchun , Zou Youfeng , Zhang Wenzhi , Chen Junjie
Published: March 2022

Mining can lead to overburden failure and ground damage, which are more severe in mining shallow buried thick coal seams (SBTCS) under thick aeolian sand (TAS). We attempted to discover characteristics of mining in this particular geological condition through theoretical derivation and numerical simulation, and field monitoring. Theoretical methods, combined with numerical simulation and field monitoring methods, reveal the essence of the development and distribution of surface cracks caused by mining SBTCS and depth to thickness ratio (DTR) to be 13.43, less than 15. The findings show that, when mining SBTCS, the overburden breaks down periodically, the initial collapse distance is greater than the collapse step, approximately 55 m on average, and the collapse step is approximately 45 m, on average, in the Daliuta Coal Mine. The collapsed blocks are stacked into goaf and form “masonry beams”, and many cracks and pores are generated between the blocks. The weak stress of the aeolian sand layer causes the movement angle in the aeolian sand layer to be smaller than that in the bedrock, and leads to much sheer, tension and compression failure on the ground, and the main forms of cracks are compression uplift, tensile cracking, shear step.
A Review on Global Emissions by E-Products Based Waste: Technical Management for Reduced Effects and Achieving Sustainable Development Goals
Authors: Ghosh Bablu K. , Mekhilef Saad , Ahmad Shameem , Ghosh Swapan K.
Published: March 2022

In the 21st century, a great amount of electrical and electronic waste (e-waste) has accumulated, and the unregulated nature of its disposal and recycling represents a particular hazard in a global context. For the purposes of e-waste management, there must be more emphasis on the scientific processes for recycling, reusing and remanufacturing precious materials. Resource management is related to energy management; therefore, the harvesting of costly materials from e-waste is important for both energy management and sustainable development. At present, a lack of scientific recycling of a significant amount of e-waste is a source of environmental pollution and health hazards that are having a detrimental effect on sustainable development goals. It is necessary to find a process for recovering valuable materials from e-waste with the minimum possible environmental impact. At present, it is essential to modify the process of electrical and electronic products (e-products) becoming e-waste, and the subsequent process of e-waste recycling, in order to lessen the impact in terms of pollution. E-waste scientific recycling initiatives can reduce the environmental impact of the process, which in turn can support a shift from the current linear flow of costly materials to a more sustainable circular flow. Furthermore, internal consumption loss, emissions, and heating loss from e-products are the main factors contributing to the loss of energy efficiency in the process, which in turn contributes to environmental pollution. Promoting green innovation in the manufacturing process of e-products, as well as their reuse, can reduce the environmental impact of e-waste in near future. Both of these pathways are imperative for a less polluted, low-toxic environment and sustainable development. However, the sustainable development initiative of the United Nation Environmental Programme (UNEP) policy framework is the ultimate goal. This is expected to support the management of environmental pollution, maintaining it at an acceptable level, while also preventing hazardous risks to human health. Hence, this review examines the prospects for achievable environmental sustainability through technological developments.
Hybrid Data-Driven Models for Hydrological Simulation and Projection on the Catchment Scale
Authors: Gharbia Salem , Riaz Khurram , Anton Iulia , Makrai Gabor , Gill Laurence , Creedon Leo , McAfee Marion , Johnston Paul , Pilla Francesco
Published: March 2022

Changes in streamflow within catchments can have a significant impact on agricultural production, as soil moisture loss, as well as frequent drying and wetting, may have an effect on the nutrient availability of many soils. In order to predict future changes and explore the impact of different scenarios, machine learning techniques have been used recently in the hydrological sector for simulation streamflow. This paper compares the use of four different models, namely artificial neural networks (ANNs), support vector machine regression (SVR), wavelet-ANN, and wavelet-SVR as surrogate models for a geophysical hydrological model to simulate the long-term daily water level and water flow in the River Shannon hydrological system in Ireland. The performance of the models has been tested for multi-lag values and for forecasting both short- and long-term time scales. For simulating the water flow of the catchment hydrological system, the SVR-based surrogate model performs best overall. Regarding modeling the water level on the catchment scale, the hybrid model wavelet-ANN performs the best among all the constructed models. It is shown that the data-driven methods are useful for exploring hydrological changes in a large multi-station catchment, with low computational cost.
Plate Waste in School Catering in Rezekne, Latvia
Authors: Lonska Jelena , Zvaigzne Anda , Kotane Inta , Silicka Inese , Litavniece Lienite , Kodors Sergejs , Deksne Juta , Vonoga Aija
Published: March 2022

This research was conducted within the framework of a research project aimed at detecting patterns of plate waste and developing recommendations for improving catering in seven schools in Rezekne city (Latvia) by a combination of observation, physical weighing, semi-structured interview approaches and statistical analysis of variance (ANOVA). We identified plate waste (including wasted beverages), which remains after the lunch of schoolchildren in grades 1–7, examining a total of 7064 lunch samples. The originality of the research is due to the fact that a unified menu was designed for the field study, which ensured the same field study conditions in all the schools. The results of the research revealed that the average weight of plate waste per schoolchild reached 178 g, and the total weight of plate waste accounted for 28.75% of the total weight of food served. No significant differences in plate waste weight between various age groups and grades of schoolchildren were found, which was also confirmed by a one-way ANOVA test. An analysis of plate waste by food category showed that beverages accounted for the largest share of total plate waste (42.24%), followed by staple food (28.38%) and meat (11.77%). An analysis of plate waste shares of food served (%) by food category revealed a similar situation: the largest share of food served was made up of beverages (37.56%), followed by staple food (36.48%) and meat (28.77%). An analysis of the monetary value of food waste showed that the average cost of plate waste (excluding beverage) per schoolchild was EUR 0.236, which represented 16.6% of the national and municipal funding of EUR 1.42 per portion. Given the research results, the authors have concluded that in order to reduce the amount of plate waste generated by Rezekne city schools, school menus should be based not only on the requirements prescribed by relevant legal acts but also on cooking processes that meet the requirements of modern consumers (learners), e.g., by following trends in cooking practices in society to make the learners interested in consuming school food.
Load Deformation Effect of CBD Ground Cluster in Zhengzhou City
Authors: Yang Li , Liu Wenkai , Qu Jihong , Guo Wei , Qiu Jianhua
Published: March 2022

With the increase of the number of urban cluster buildings, it is bound to cause land subsidence near cluster buildings. Based on Farrell’s load deformation theory, this paper studies the surface deformation and geoid change caused by Zhengzhou CBD cluster buildings. The results show that the maximum horizontal displacement of the International Convention and Exhibition Center is 0.1 mm, the maximum vertical displacement is 0.33 mm, and the maximum geoid fluctuation is 17.4 mm; the maximum inclination of geoid is 1.89 s. In addition, the influence of independent single buildings on ground deformation is centered on the single building and diffuses outward; the influence of cluster load buildings on the ground deformation of a single building is nonlinear attenuation and superimposed with each other.
Inward and Outward Opening Properties of One-Sided Windcatchers: Experimental and Analytical Evaluation
Authors: Mohamed Mady A. A. , El-Amin Mohamed F.
Published: March 2022

Vernacular measures, such as courtyard, wind catcher “Malqaf”, wooden lattice “Mashrabia”, and lantern—which can help buildings to depend on natural energy from the sun and the wind—have started to be abandoned in the last decades. However, wind pressure and stack effects are becoming more popular in modern buildings design and the primary method in most domestic buildings to achieve the desired cross ventilation and minimize the air temperature to reach the required cooling loads. This paper aims to revive one of the vernacular measures “the windcatcher”, quantifying the effectiveness of the inward/outward opening properties on the air temperature and airflow inside the buildings. Analytical literature review, context analysis, and numerical simulations are performed. The computer fluid dynamics (CFD) is utilized to simulate both the temperature distribution and the flow field within the windcatcher model. Simulations are carried out in the fluent environment, which uses the control volume method for solving the conservation law. The Reynolds-averaged Navier–Stokes (RANS) and energy equation with the realizable k-ϵ turbulent model are employed. The research uses a parametric analysis to test different scenarios of windcatcher designs in terms of dimensions, proportions, and opening ratios. The results of this study confirm that windcatcher has a significant effect in lowering the air temperature inside the different floors. However, it is recommended to use a wind-catcher for not more than two floors, increase the area of the outward opening to 200% relative to the inward opening and apply side opening in the upper floors.
Fish Feeds in Aquaponics and Beyond: A Novel Concept to Evaluate Protein Sources in Diets for Circular Multitrophic Food Production Systems
Authors: Shaw Christopher , Knopf Klaus , Kloas Werner
Published: March 2022

With the general objective of optimizing internal nutrient recycling, circular multitrophic food production systems, e.g., combining fish, plant, and insect larvae production, rely on the quality and composition of sustainable nutritional inputs. Therefore, differences in dissolved and solid nutrient excretion patterns produced by Nile tilapia (Oreochromis niloticus) reared in recirculating aquaculture systems (RAS) with 5% daily water exchange and fed black soldier fly meal (BSFM), poultry by-product meal (PM), poultry blood meal (PBM) and fish meal (FM) as single protein sources were investigated to evaluate the potential for creating specific fish meal-free diets. Fish fed the FM and PM diet showed the significantly best (p < 0.05) and among each other similar (p > 0.05) growth performance (specific growth rate (SGR): 2.12 ± 0.04/2.05 ± 0.11; feed conversion ratio (FCR): 0.86 ± 0.03/0.92 ± 0.01), whereas the PBM diet caused significantly reduced performance (SGR: 1.30 ± 0.02; FCR: 1.79 ± 0.05) in comparison to the FM/PM diet as well as the BSF diet (SGR: 1.76 ± 0.07; FCR: 1.11 ± 0.05). The FM and PM diet resulted in a faster increase and significantly higher dissolved nitrogen and phosphorus levels, while the BSF diet caused faster accumulation and significantly elevated levels of dissolved potassium, magnesium, and copper. The PBM diet resulted in the feces with the significantly highest nutrient density (gross energy, crude protein, and amino acids) but overall much lower dissolved nutrient levels in the water. Results are discussed with regard to implications for developing circular multitrophic food production systems.
Adaptability of MODIS Daily Cloud-Free Snow Cover 500 m Dataset over China in Hutubi River Basin Based on Snowmelt Runoff Model
Authors: Meng Xiangyao , Liu Yongqiang , Qin Yan , Wang Weiping , Zhang Mengxiao , Zhang Kun
Published: March 2022

Global warming affects the hydrological characteristics of the cryosphere. In arid and semi-arid regions where precipitation is scarce, glaciers and snowmelt water assume important recharge sources for downstream rivers. Therefore, the simulation of snowmelt water runoff in mountainous areas is of great significance in hydrological research. In this paper, taking the Hutubi River Basin in the Tianshan Mountains as the study area, we used the “MODIS Daily Cloud-free Snow Cover 500 m Dataset over China” (MODIS_CGF_SCE) to carry out the Snowmelt Runoff Model (SRM) simulation and evaluated the simulation accuracy. The results showed that: (1) The SRM preferably simulated the characteristics of the average daily flow variation of the Hutubi River from May to October, from 2003–2009. The monthly total runoff was maximum in July and minimum in October. Extreme precipitation events influenced the formation of flood peaks, and the interannual variation trend of total runoff from May to October was increased. (2) The mean value of the volume difference (DV) during the model validation period was 8.85%, and the coefficient of determination (R2) was 0.73. In general, the SRM underestimates the runoff of the Hutubi River, and the simulation accuracy is more accurate in the normal water period than in the high-water period. (3) By analyzing MODIS_CGF_SCE from 2003 to 2009, areas above 3200 m elevation in the Hutubi River Basin were classified as permanent snow areas, and areas below 3200 m were classified as seasonal snow areas. In October, the snow area in the Hutubi River Basin gradually increased, and the increase in snow cover in the permanent snow area was greater than that in the seasonal snow area. The snowmelt period was from March to May in the seasonal snow area and from May to early July in the permanent snow area, and the minimum snow cover was 0.7%.
Energy Refurbishment of Serbian School Building Stock—A Typology Tool Methodology Development
Authors: Đukanović Ljiljana , Ignjatović Dušan , Ćuković Ignjatović Nataša , Rajčić Aleksandar , Lukić Nevena , Zeković Bojana
Published: March 2022

Energy refurbishment of school buildings is a priority regarding both energy consumption in buildings and improving comfort conditions for sensitive young occupants. During 2016–18, a group of teachers and associates from the Faculty of Architecture, Mechanical Engineering, and Electrical Engineering from the University in Belgrade participated in the project “Energy efficiency in public buildings” in cooperation with GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit), University of Belgrade, Faculty of Architecture and Ministry of Mining and Energy of the Republic of Serbia. During 2016 and 2017, a comprehensive survey and database of public buildings were conducted by the local community. The focus of the research was the facilities of children’s institutions, and detailed data were collected to determine the current building stock conditions, energy consumption, and possible improvements. This paper presents the methodology of the project based on defining the typology of buildings, determining the representatives of the characteristic periods of construction, and analyzing their energy performance. Five possible scenarios were considered: designed condition, existing state, and three levels of a building improvement. The main goal of this project was to ascertain the entire fund for school buildings, indicate the potential for energy savings of this type of public building at the national level, and use this as a starting point for developing strategic decisions and further energy efficiency policies. This paper presents the complete results of the research on school buildings in Serbia, their energy performance, and possible energy savings. Key findings show that a great majority of schools are in a poor state in terms of their energy efficiency, but at the same time, there is a large potential for improvement of building envelope, HVAC, and lighting systems, which can cut the current energy need for heating to up to 80%.