bluuebunny/crossref_metadata_2025 huggingface dataset:
Production of Oil and Phenolic-Rich Extracts from Mauritia flexuosa L.f. Using Sequential Supercritical and Conventional Solvent Extraction: Experimental and Economic Evaluation
Authors: Best Ivan , Cartagena-Gonzales Zaina , Arana-Copa Oscar , Olivera-Montenegro Luis , Zabot Giovani
Published: February 2022

Mauritia flexuosa L.f. is a palm from the Amazon. Pulp and oil are extracted from its fruits, with a high content of bioactive compounds. This study presents the economic evaluation of two extraction processes: (a) Conventional solvent extraction (CSE) with 80% ethanol for the recovery of phenolic-rich extracts; and (b) Supercritical fluid extraction (SFE) followed by CSE to obtain oil and phenolic-rich extracts. The objective of this study was to compare the feasibility of both extraction processes. The economic evaluation and the sensitivity study were evaluated using the SuperPro Designer 9.0® software at an extraction volume of 2000 L. Similar global extraction yields were obtained for both processes; however, 8.4 and 2.4 times more total polyphenol and flavonoid content were extracted, respectively, using SFE+CSE. Cost of manufacturing (COM) was higher in SFE+CSE compared to CSE, USD 193.38/kg and USD 126.47/kg, respectively; however, in the first process, two by-products were obtained. The sensitivity study showed that the cost of the raw material was the factor that had the highest impact on COM in both extraction processes. SFE+CSE was the most economically viable process for obtaining bioactive compounds on an industrial scale from M. flexuosa L.f.
Micro-Motion Classification of Flying Bird and Rotor Drones via Data Augmentation and Modified Multi-Scale CNN
Authors: Chen Xiaolong , Zhang Hai , Song Jie , Guan Jian , Li Jiefang , He Ziwen
Published: February 2022

Aiming at the difficult problem of the classification between flying bird and rotary-wing drone by radar, a micro-motion feature classification method is proposed in this paper. Using K-band frequency modulated continuous wave (FMCW) radar, data acquisition of five types of rotor drones (SJRC S70 W, DJI Mavic Air 2, DJI Inspire 2, hexacopter, and single-propeller fixed-wing drone) and flying birds is carried out under indoor and outdoor scenes. Then, the feature extraction and parameterization of the corresponding micro-Doppler (m-D) signal are performed using time-frequency (T-F) analysis. In order to increase the number of effective datasets and enhance m-D features, the data augmentation method is designed by setting the amplitude scope displayed in T-F graph and adopting feature fusion of the range-time (modulation periods) graph and T-F graph. A multi-scale convolutional neural network (CNN) is employed and modified, which can extract both the global and local information of the target’s m-D features and reduce the parameter calculation burden. Validation with the measured dataset of different targets using FMCW radar shows that the average correct classification accuracy of drones and flying birds for short and long range experiments of the proposed algorithm is 9.4% and 4.6% higher than the Alexnet- and VGG16-based CNN methods, respectively.
Joint Estimation of Azimuth and Distance for Far-Field Multi Targets Based on Graph Signal Processing
Authors: Liao Kefei , Yu Zerui , Xie Ningbo , Jiang Junzheng
Published: February 2022

Target position estimation is one of the important research directions in array signal processing. In recent years, the research of target azimuth estimation based on graph signal processing (GSP) has sprung up, which provides new ideas for the Direction of Arrival (DoA) application. In this article, by extending GSP-based DOA to joint azimuth and distance estimation and constructing a fully connected graph signal model, a multi-target joint azimuth and distance estimation method based on GSP is proposed. Firstly, the fully connection graph model is established related to the phase information of a linear array. For the fully connection graph, the Fourier transform method is used to solve the estimated response function, and the one-dimensional estimation of azimuth and distance is completed, respectively. Finally, the azimuth and distance estimation information are combined, and the false points in the merging process are removed by using CLEAN algorithm to complete the two-dimensional estimation of targets. The simulation results show that the proposed method has a smaller mean square error than the Multiple Signal Classification (MUSIC) algorithm in azimuth estimation under the condition of a low signal-to-noise ratio and more accurate response values than the MUSIC algorithm in distance estimation under any signal-to-noise ratio in multi-target estimation.
Mapping Forest Aboveground Biomass Using Multisource Remotely Sensed Data
Authors: Ehlers Dekker , Wang Chao , Coulston John , Zhang Yulong , Pavelsky Tamlin , Frankenberg Elizabeth , Woodcock Curtis , Song Conghe
Published: February 2022

The majority of the aboveground biomass on the Earth’s land surface is stored in forests. Thus, forest biomass plays a critical role in the global carbon cycle. Yet accurate estimate of forest aboveground biomass (FAGB) remains elusive. This study proposed a new conceptual model to map FAGB using remotely sensed data from multiple sensors. The conceptual model, which provides guidance for selecting remotely sensed data, is based on the principle of estimating FAGB on the ground using allometry, which needs species, diameter at breast height (DBH), and tree height as inputs. Based on the conceptual model, we used multiseasonal Landsat images to provide information about species composition for the forests in the study area, LiDAR data for canopy height, and the image texture and image texture ratio at two spatial resolutions for tree crown size, which is related to DBH. Moreover, we added RaDAR data to provide canopy volume information to the model. All the data layers were fed to a Random Forest (RF) regression model. The study was carried out in eastern North Carolina. We used biomass from the USFS Forest Inventory and Analysis plots to train and test the model performance. The best model achieved an R2 of 0.625 with a root mean squared error (RMSE) of 18.8 Mg/ha (47.6%) with the “out-of-bag” samples at 30 × 30 m spatial resolution. The top five most important variables include the 95th, 85th, 75th, and 50th percentile heights of the LiDAR points and their standard deviations of 85th heights. Numerous features from multiseasonal Sentinel-1 C-Band SAR, multiseasonal Landsat 8 imagery along with image texture features from very high-resolution imagery were selected. But the importance of the height metrics dwarfed all other variables. More tests of the conceptual model in places with a broader range of biomass and more diverse species composition are needed to evaluate the importance of other input variables.
A Flexible Multi-Temporal and Multi-Modal Framework for Sentinel-1 and Sentinel-2 Analysis Ready Data
Authors: Upadhyay Priti , Czerkawski Mikolaj , Davison Christopher , Cardona Javier , Macdonald Malcolm , Andonovic Ivan , Michie Craig , Atkinson Robert , Papadopoulou Nikela , Nikas Konstantinos , Tachtatzis Christos
Published: February 2022

The rich, complementary data provided by Sentinel-1 and Sentinel-2 satellite constellations host considerable potential to transform Earth observation (EO) applications. However, a substantial amount of effort and infrastructure is still required for the generation of analysis-ready data (ARD) from the low-level products provided by the European Space Agency (ESA). Here, a flexible Python framework able to generate a range of consistent ARD aligned with the ESA-recommended processing pipeline is detailed. Sentinel-1 Synthetic Aperture Radar (SAR) data are radiometrically calibrated, speckle-filtered and terrain-corrected, and Sentinel-2 multi-spectral data resampled in order to harmonise the spatial resolution between the two streams and to allow stacking with multiple scene classification masks. The global coverage and flexibility of the framework allows users to define a specific region of interest (ROI) and time window to create geo-referenced Sentinel-1 and Sentinel-2 images, or a combination of both with closest temporal alignment. The framework can be applied to any location and is user-centric and versatile in generating multi-modal and multi-temporal ARD. Finally, the framework handles automatically the inherent challenges in processing Sentinel data, such as boundary regions with missing values within Sentinel-1 and the filtering of Sentinel-2 scenes based on ROI cloud coverage.
Towards the Combination of C2RCC Processors for Improving Water Quality Retrieval in Inland and Coastal Areas
Authors: Soriano-González Jesús , Urrego Esther Patricia , Sòria-Perpinyà Xavier , Angelats Eduard , Alcaraz Carles , Delegido Jesús , Ruíz-Verdú Antonio , Tenjo Carolina , Vicente Eduardo , Moreno José
Published: February 2022

Sentinel-2 offers great potential for monitoring water quality in inland and coastal waters. However, atmospheric correction in these waters is challenging, and there is no standardized approach yet, but different methods coexist under constant development. The atmospheric correction Case 2 Regional Coast Colour (C2RCC) processor has been recently updated with the C2X-COMPLEX (C2XC). This study is one of the first attempts at exploring its performance, in comparison with C2RCC and C2X, in inland and coastal waters in the east of the Iberian Peninsula, in retrieving water surface reflectance and estimating chlorophyll-a ([Chl-a]), total suspended matter ([TSM]), and Secchi disk depth (ZSD). The relationship between in situ ZSD and Kd_z90max product (i.e., the depth of the water column from which 90% of the water-leaving irradiance is derived) of the C2RCC processors demonstrated the potential of this product for estimating water clarity (r > 0.75). However, [TSM] and [Chl-a] derived from the different processors with default calibration factors were not suitable within the targeted scenarios, requiring recalibration based on optical water types or a shift to dynamic algorithm blending approaches. This would benefit from switching between C2RCC and C2XC, which extends the potential for improving surface reflectance estimates to a wide range of scenarios and suggests a promising future for C2-Nets in operational monitoring of water quality.
A Combined Convolutional Neural Network for Urban Land-Use Classification with GIS Data
Authors: Yu Jie , Zeng Peng , Yu Yaying , Yu Hongwei , Huang Liang , Zhou Dongbo
Published: February 2022

The classification of urban land-use information has become the underlying database for a variety of applications including urban planning and administration. The lack of datasets and changeable semantics of land-use make deep learning methods suffer from low precision, which prevent improvements in the effectiveness of using AI methods for applications. In this paper, we first used GIS data to produce a well-tagged and high-resolution urban land-use image dataset. Then, we proposed a combined convolutional neural network named DUA-Net for complex and diverse urban land-use classification. The DUA-Net combined U-Net and Densely connected Atrous Spatial Pyramid Pooling (DenseASPP) to extract Remote Sensing Imagers (RSIs) features in parallel. Then, channel attention was used to efficiently fuse the multi-source semantic information from the output of the double-layer network to learn the association between different land-use types. Finally, land-use classification of high-resolution urban RSIs was achieved. Experiments were performed on the dataset of this paper, the publicly available Vaihingen dataset and Potsdam dataset with overall accuracy levels reaching 75.90%, 89.71% and 89.91%, respectively. The results indicated that the complex land-use types with heterogeneous features were more difficult to extract than the single-feature land-cover types. The proposed DUA-Net method proved suitable for high-precision urban land-use classification, which will be of great value for urban planning and national land resource surveying.
Do Spatially Structured Soil Variables Influence the Plant Diversity in Tabuk Arid Region, Saudi Arabia?
Authors: Al-Mutairi Khalid Awadh
Published: February 2022

Plant diversity is affected by spatial variables as well as soil physical and chemical variables. In this study, plant species and soil variables were investigated in five sites of Tabuk Province (Saudi Arabia), namely Aldesah, Alzetah, Alawz, Harra and Sharma, to understand if the spatially structured soil variables (pH, electric conductivity (EC), soil texture, calcium, potassium, phosphorus, phosphate, total organic matter (OM), bicarbonate and sodium) influence the plant diversity. A total of 163 plant species belong to 41 families and 124 genera were reported from the 5 sites. Diversity indices including the species richness (alpha), evenness, Brillouin, Menhinick, Margalef, equitability and estimated Chao-1 were significantly different among the studied sites with pronounced high values in Sharma and Aldesah. The highest value of beta diversity was reported in Aldesah (0.253) followed by Sharma (0.171). According to the principal coordinates of neighbourhood matrix (PCNM) analysis, 11 positive spatial vectors (variables) were found. However, after running the forward selection procedures (using 2 stopping criteria), only 3 spatial vectors were retained (PCNM 1 (adj–R2 = 0.043, F = 5.201, p = 0.004), PCNM 2 (adj–R2 = 0.027, F = 3.97, p = 0.006) and PCNM 3 (adj–R2 = 0.019, F = 3.36, p = 0.007)). The linear models between the selected spatial variables (PCNM vectors) and soil variables were produced to investigate their spatial structure. In the first model, the first PCNM 1 axis showed significant relationship with pH and potassium (adj–R2 = 0.175, p = 0.046). In the second model, the second PCNM 2 axis had a significant relationship with OM and sodium (adj–R2 = 0.561, p < 0.001). Lastly, sodium was the only factor significantly correlated with the third PCNM 3 axis (adj–R2 = 0.365, p = 0.002). In conclusion, the spatially structured variables of soil did not show strong influence on plant diversity except pH and potassium, which were correlated with PCNM 1, OM and sodium, which were correlated with PCNM 2, and sodium, which was correlated with PCNM 3.
Engaging Smallholders in Flower Agribusiness for Inclusive Rural Development: The Case of Yunnan, China
Authors: Zhu Jieming , Chen Chen , You Lie
Published: February 2022

Serious farmland scarcities make smallholders a default mode for China’s agriculture, which makes efficient and equitable rural development a great challenge. Tensions lead to alternation between autonomous family farming and coordinated collective agriculture. Rapid urbanization since the 1980s has strongly stimulated flower-growing and agribusiness in Yunnan, China. The organization for commercial flower-farming is, however, an issue. Officially promoted for collective farming, voluntary cooperatives are wrecked by the free-riding problem. Grower associations nevertheless spontaneously emerge, with the flexible entry and exit of members without binding joint-assets and joint-ownership, which is facilitated by technological changes to the transaction. Empirical investigation in Tonghai, Yunnan, unveiled the institution of agribusiness–smallholder partnership for inclusive rural development. Smallholders have actively participated in flower agriculture, which has contributed significantly to the development of rural economies. The high casualty of micro-smallholders suggests that farm size is an important and crucial factor for sustainable farming. Effective rural development has to be supported by endogenous non-agricultural jobs so that farm size can be increased.
The Utilization of Modified Zeolite for the Removal of Cs Ions in an Aqueous Solution: Adsorption Capacity, Isotherms, Kinetics and Microscopic Studies
Authors: Sun Junfang , Chen Ji , Peng Xiang , Zhang Yu , Mo Jialin , Liao Xin , Tang Qiang
Published: February 2022

Nuclear energy is a double-edged technology, which has a significant role in the chemical industry, but may bring about radioactivity and destruction. The 2011 Fukushima nuclear power plant accident caused by a tsunami, which flooded and led to tens of millions of disaster debris and tsunami deposits, severely disrupted the electricity supply in Japan and induced USD 211 billion worth of direct economic losses. Cs+ was easily dissolved in this accident, had a high chemical activity, and thus required an appropriate adsorption method. Zeolite is an effective removal adsorbent, which is suitable to be investigated. The present study uses natural zeolite and three inorganic modified zeolites. Furthermore, the effects of various factors are investigated. Kinetic models and the isothermal adsorption mechanism are also conducted. For microscale studies for the adsorption mechanism, scanning electron microscope (SEM) and X-ray diffraction (XRD) were involved in the study. The results indicate that the optimal dosage is 1.1 g and the maximum adsorption rate is around 80%. An alkaline environment is more conducive to the occurrence of adsorption. As for the isotherm and kinetic studies, the data fits better with the Redlich–Peterson isothermal model and intragranular diffusion model. In this small-scale experiment, the highest adsorption capacity was for Mg-zeolite at 6.53 mg/g. Finally, Mg-Zeolite presents the best adsorption capacity.
Organizational Life Cycle Sustainability Assessment (OLCSA) for a Higher Education Institution as an Organization: A Systematic Review and Bibliometric Analysis
Authors: Wafa Wafaurahman , Sharaai Amir Hamzah , Matthew Nitanan Koshy , Ho Sabrina Abdullah J , Akhundzada Noor Ahmad
Published: February 2022

Life cycle sustainability assessment (LCSA) is an approach utilized for products to analyze their sustainability indicators. However, no definite study has determined the sustainability of an organization using the LCA approach. This review focuses on a systematic review and bibliometric analysis of the OLCSA in University. The literature was searched in the Scopus online database considering PRISMA guidelines, and VOSviewer software was used for three types of bibliometric analysis, i.e., co-authorship, co-occurrence, and co-citation were analyzed with their units of analysis. The results show that there is no specific study that has found or assessed the LCSA of an organization. However, 17 articles on O-LCA and 2 on SO-LCA were found, and there were numerous articles available about ELCC in the literature. Researchers mostly used UNEP guidelines for O-LCA, in line with ISO standards. However, they used NPV for E-LCC. Based on VOSviewer software, Matthias Finkbeiner, Forin, Martínez-Blanco Julia, Berger Markus, Lehman, Loss, Manzardo, Scipion, Hall, and Weldu are co-authors. The keyword of “life cycle” was broadly used, and the most cited source was the “International Journal of Life Cycle Assessment”. Adoption of the LCSA framework is recommended for O-LCSA studies to estimate organizations’ sustainability, and to ensure quality education contributing the fourth SDGs.
Exploring the Influence of Land Titling on Farmland Transfer-Out Based on Land Parcel Data
Authors: Ye Ting , He Wenjian , Liu Zhiyong
Published: February 2022

Existing literature about the impact of farmland titling on farmland transfer takes no account of farmland plot characteristics, which makes them unable to effectively identify the causal relationship between farmland titling and farmland transfer. After the theoretical analysis, based on land plot level micro-survey data, we adopt the instrumental variable (IV) and conditional mixed process (CMP) methods to ease the endogeneity problem in the model and conduct a quantitative analysis. The results show that the land titling program has significant and positive effects on the transfer-out of farmland. Through a heterogeneity test, we observe a more pronounced promotional effect in regions with a higher economic development level and in farmland transfer deals with government facilitation. Moreover, the further application of a mediating effect model shows that the land titling program increases the net income from farmland transfer-out through increasing the value of farmland and reducing the transaction costs, thus promoting the transferring out of farmland. The findings contribute to providing empirical evidence for how the government may facilitate and support the attaining of more efficient scale operations of farmland.
Guidelines to Establish an Office of Student Accessibility Services in Higher Education Institutions
Authors: Mendoza-González Ricardo , Luján-Mora Sergio , Otón-Tortosa Salvador , Sánchez-Gordón Mary , Rodríguez-Díaz Mario Alberto , Reyes-Acosta Ricardo Emmanuel
Published: February 2022

The objective of this paper is to propose a set of guidelines to establish an office of Student Accessibility Services (SAS) in Higher Education Institutions (HEIs). The proposed guidelines help to integrate disjointed knowledge to facilitate its interpretation and implementation during deployment of basic support services in favor of students with disability. These guidelines can help to mitigate complexity in providing SAS for the first time in HEIs. These guidelines cover both the design and implementation of an office of SAS and its management. Knowledge was found through a multivocal literature review (MLR), which allowed to capture not only academic approaches but also vantage points and experiences from practice. Key concepts and aspects were organized into eight components (five related to the design and implementation, and three associated with the management context). An expert appraisal method was used as a proof of concept, which complemented a previously performed preliminary implementation example. Obtained results demonstrated the pertinence of the conceptual proposal and confirmed guidelines capability for full implementation in a real-world scenario.
Role of Environment Variables in Spatial Distribution of Soil C, N, P Ecological Stoichiometry in the Typical Black Soil Region of Northeast China
Authors: Chen Qianqian , Shi Zhou , Chen Songchao , Gou Yuxuan , Zhuo Zhiqing
Published: February 2022

The effects of environmental factors on topsoil nutrient distribution have been extensively discussed, but it remains unclear how they affect spatial characteristics of soil carbon (C), nitrogen (N), and phosphorus (P) stoichiometry at different depths. We collected 184 soil samples in the typical black soil region of northeast China. Ordinary kriging was performed to describe the spatial distribution of soil C, N, and P eco-stoichiometry. Redundancy analysis was used to explore relationships between C:N:P ratios and physicochemical characteristics. The soil classification was studied by hierarchical cluster analysis. The mean C, N, and P contents ranged from 15.67 to 20.08 g·kg−1, 1.15 to 1.51 g·kg−1, and 0.80 to 0.90 g·kg−1 within measured depths. C, N, and P concentrations and stoichiometry increased from southwest to northeast, and the Songhua River was identified as an important transition zone. At 0–20 cm, soil water content explained most of the C, N, and P content levels and ratios in cluster 1, while latitude had the highest explanatory ability in cluster 2. For 20–40 cm, soil bulk density was the main influencing factor in both clusters. Our findings contribute to an improved knowledge of the balance and ecological interactions of C, N, and P in northeast China for its sustainability.
Design and Implementation of a Workshop for Evaluation of the Role of Power in Shaping and Solving Challenges in a Smart Foodshed
Authors: Hyder Ayaz , Blatt Angela , Hollander Allan D. , Hoy Casey , Huber Patrick R. , Lange Matthew C. , Quinn James F. , Riggle Courtney M. , Sloan Ruth , Tomich Thomas P.
Published: February 2022

Current studies on data sharing via data commons or shared vocabularies using ontologies mainly focus on developing the infrastructure for data sharing yet little attention has been paid to the role of power in data sharing among food system stakeholders. Stakeholders within food systems have different interpretations of the types and magnitudes of their own and other’s level of power to solve food system challenges. Politically neutral, yet scientifically/socioeconomically accurate power classification systems are yet to be developed, and must be capable of enumerating and characterizing what power means to each stakeholder, existing power dynamics within the food system, as well as alternative forms of power not currently utilized to their full capacity. This study describes the design and implementation of a workshop, which used methods from community-based participatory modeling, to examine the role of power relative to data sharing and equitable health outcomes. Workshop participants co-created several boundary objects that described the power relationships among food system stakeholders and the changes needed to current power relationships. Our results highlight current imbalances in power relationships among food system stakeholders. The information we collected on specific relationships among broad categories of stakeholders highlighted needs for initiatives and activities to increase the types and varieties of power especially across consumers, farmers, and labor stakeholder groups. Furthermore, by utilizing this workshop methodology, food system stakeholders may be able to envision new power relationships and bring about a fundamental re-orienting of current power relationships capable of valorizing food system sustainability/resiliency, especially the health of its workers and consumers.
A Study on the Changing Architectural Properties of Mixed-Use Commercial Complexes in Seoul, Korea
Authors: Lee Sungkyun
Published: February 2022

This study conducts a chronological analysis of six mixed-use commercial complexes in the Seoul metropolitan area and examines their planning characteristics and patterns of change. The analysis reveals the following changes. The spatial composition of these complexes is shifting away from large anchor type commercial facilities to small local commercial facilities. Their circulations and arrangement are shifting to consideration for non-consumption tendencies, and circular and three-dimensional connections between each space are emphasized. Central spaces are shifting from a large single center to small multi-centers, and the utilization of central spaces for events and performances is increasing. Concepts that stimulate visitors’ interest and non-daily experiences are being expanded, which include the use of new themes, such as natural motifs, and the reproduction of classical streets in the space, corridors, colors, and material planning. Based on their changing patterns, this study predicted such complexes’ direction of change. First, they will expand their role as the center of the local community. Second, they will bolster their linkage with local streets and expand the street-type circulation plan. Third, small multi-center spaces and themed external spaces will increase. Fourth, non-consumption and non-daily planning elements will increase.
Power System Transition with Multiple Flexibility Resources: A Data-Driven Approach
Authors: Li Hao , Qiao Ying , Lu Zongxiang , Zhang Baosen
Published: February 2022

Power systems are transitioning toward having high shares of variable renewable energy (VRE) with the help of flexibility resources. However, multiple flexibility resources on the generation, storage and demand sides introduce multiple technical and economic uncertainties, making the transition hard to predict. Moreover, the benefit of these resources in the transition is unclear. To fill these gaps, this paper proposes a data-driven approach to explore the transition to a high VRE share-oriented power system with multiple flexibility resources. This approach generates a wealth of possible transition paths under multiple uncertainties and then uses them to quantitatively analyze the transition. Specifically, the proposed method includes principal component analysis-based path visualization, multiple index-based transition milestone identification, cluster and distance calculation-based key influential factor identification, marginal index-based flexibility resource benefit comparison and Pareto frontier-based path recommendation. Case studies based on the Northwest China power system, which involves wind, photovoltaics and concentrated solar plants, validate the effectiveness of the proposed approach and further indicate that flexibility resources increase rapidly with the growth of the VRE share. Of the multiple flexibility resources, storage contributes the most. Key influential factors include the capital cost of VRE and storage along with coal price. These factors should be the focus in a low-cost and low-carbon transition.
The Catalogue of Leisure Activities: A New Structured Values and Content Based Instrument for Leisure Research Usable for Social Development and Community Planning
Authors: Pospíšil Jiří , Pospíšilová Helena , Trochtová Ludmila
Published: February 2022

Leisure is a phenomenon that undergoes constant change. These changes are sometimes global, but more often, they are localized. For this reason, the capturing of leisure and leisure activities poses a major challenge for researchers. In particular, they struggle to capture measurements for leisure activities in such a way that these measurement results can be compared over time, in different places, and in different communities. We have therefore identified the need for a tool that makes it possible to compare both time- and place-specific measurements. Based on our long-term research, we have created the Catalogue of Leisure Activities (CaLA), which is built on two pillars—content proximity and value consequences of leisure activities. Therefore, the CaLA allows for the capturing of the complexity of leisure activities and using the data thus measured as variables in statistical hypotheses, longitudinal comparisons of research across locations, over time, and across population groups (e.g., children, adults, etc.). It also allows measurements of other secondary characteristics (e.g., favor rate, duration, etc.) to be linked to the activities found. The results of measuring leisure activities using the CaLA can be used in research as a dependent or independent variable. As a result, we can detect many hitherto hidden relationships that significantly influence leisure experience and its quality. The CaLA also opens up many more possibilities for a wider range of applications in practice, e.g., in counseling, psychology, and coaching in support of individual development, in helping professions, social work and pedagogy when working with students and clients, and among managers when planning the development and maintaining the competitiveness of leisure facilities. Last but not least, the CaLA can be used by community leaders and politicians when designing public policies or developing a sustainable society.
Temporal and Spatial Analysis of Coastal Water Quality to Support Application of Whiteleg Shrimp Litopenaeus vannamei Intensive Pond Technology
Authors: Mustafa Akhmad , Paena Mudian , Athirah Admi , Ratnawati Erna , Asaf Ruzkiah , Suwoyo Hidayat Suryanto , Sahabuddin Sahabuddin , Hendrajat Erfan Andi , Kamaruddin Kamaruddin , Septiningsih Early , Sahrijanna Andi , Marzuki Ismail , Nisaa Khairun
Published: February 2022

The study aimed to determine the performance of whiteleg shrimp culture in relation to temporal and spatial aspects and characteristics and water quality status. Measurement and sampling of water were carried out before stocking/initial stocking of culture whiteleg shrimp (rainy season) and end of culture/after harvesting of whiteleg shrimp (dry season) at two locations in the coastal area of Bulukumba Regency, namely Bonto Bahari Subdistrict (BB) and Gantarang Subdistrict (GT), and one location as a control, namely in the coastal area of Ujung Loe Subdistrict. Variables measured and analyzed included temperature, salinity, pH, dissolved oxygen, nitrate, nitrite, ammonia, phosphate, total suspended solids, and total organic matter. Data were analyzed by descriptive statistics, multivariate statistics, and non-parametric statistics. Water quality status was determined using the Storet (Storage and Retrieval) method. The results showed that the culture of whiteleg shrimp was technology intensive with a stocking density of 110–220 ind/m2 with productivity between 13.9 and 44.4 tons/ha/cycle. The predicted waste load of N is 28.00 tons/cycle and P reaches 6.61 tons/cycle. Another result was that changes in water quality status during the rainy season were classified as moderately polluted at the BB location and complying with quality standards at the GT location. In the dry season, both locations were categorized as heavily polluted. Variables of water quality that caused the decrease in water quality status in both locations (BB and GT) were observed to increase salinity, nitrate concentration, and ammonia concentration and decreased dissolved oxygen concentration in the dry season. It is recommended to carry out proper feed management, use of probiotics, and increase the capacity and capability of wastewater treatment plants to reduce ammonia and nitrate concentrations in water in coastal areas. It is necessary to determine a more precise time for whiteleg shrimp stocking by reducing the possibility that whiteleg shrimp culture will still occur at the dry season’s peak.
Precipitation Forecasting in Northern Bangladesh Using a Hybrid Machine Learning Model
Authors: Di Nunno Fabio , Granata Francesco , Pham Quoc Bao , de Marinis Giovanni
Published: February 2022

Precipitation forecasting is essential for the assessment of several hydrological processes. This study shows that based on a machine learning approach, reliable models for precipitation prediction can be developed. The tropical monsoon-climate northern region of Bangladesh, including the Rangpur and Sylhet division, was chosen as the case study. Two machine learning algorithms were used: M5P and support vector regression. Moreover, a novel hybrid model based on the two algorithms was developed. The performance of prediction models was assessed by means of evaluation metrics and graphical representations. A sensitivity analysis was also carried out to assess the prediction accuracy as the number of exogenous inputs reduces and lag times increases. Overall, the hybrid model M5P-SVR led to the best predictions among used models in this study, with R2 values up to 0.87 and 0.92 for the stations of Rangpur and Sylhet, respectively.
Numerical Simulation of Thermocapillary Convection in a Half-Zone Liquid Bridge Model with Large Aspect Ratio under Microgravity
Authors: Fan Jungeng , Liang Ruquan
Published: February 2022

The coupled momenta induced by thermal effects near interfaces cause complex three-dimensional flow structures, called thermocapillary flow or Marangoni convection. Thermocapillary convection is crucial for crystal growth quality, and the mainstream method used to study thermocapillary convection is the half-zone liquid bridge model. This paper designs a gas–liquid two-phase system and reports the numerical results on the instability and associated roll structures of thermocapillary convection in half-zone liquid bridge under microgravity environment. The gas and liquid transferred momentum and energy through the free surface. The geometry of interest is high aspect ratio (AR) silicone oil suspended between coaxial disks heated differentially. It was found that with the increase in AR, the vortex of thermocapillary convection gradually moves to the upper disk at the steady state. In the range of 2 < AR < 2.5, the vortex cell splits from 1 to 2, and the distance between the vortex center increases with the increase in AR. The flow field after the onset of instability exhibits a traveling wave with wave number m = 1 when AR ≤ 3 and exhibits a standing wave with wave number m = 1 when AR ≥ 3.5.
Surveillance of Coxiella burnetii Shedding in Three Naturally Infected Dairy Goat Herds after Vaccination, Focusing on Bulk Tank Milk and Dust Swabs
Authors: Bauer Benjamin U. , Schoneberg Clara , Herms T. Louise , Runge Martin , Ganter Martin
Published: February 2022

Q fever outbreaks on three dairy goat farms (A–C) were monitored after the animals had been vaccinated with an inactivated Coxiella burnetii phase I vaccine. The antibody response was measured before vaccination by serum samples with two C. burnetii phase-specific ELISAs to characterize the disease status. Shedding was determined by vaginal swabs during three kidding seasons and monthly bulk tank milk (BTM) samples. Dust swabs from one windowsill of each barn and from the milking parlors were collected monthly to evaluate the indoor exposure. These samples were analyzed by qPCR. The phase-specific serology revealed an acute Q fever infection in herd A, whereas herds B and C had an ongoing and past infection, respectively. In all three herds, vaginal shedders were present during three kidding seasons. In total, 50%, 69%, and 15% of all collected BTM samples were C. burnetii positive in herds A, B, and C, respectively. Barn dust contained C. burnetii DNA in 71%, 45%, and 50% of examined swabs collected from farms A, B, and C, respectively. The largest number of C. burnetii positive samples was obtained from the milking parlor (A: 91%, B: 72%, C: 73%), indicating a high risk for humans to acquire Q fever during milking activity.
The Nutrient and Heavy Metal Contents in Water of Tidal Creek of the Yellow River Delta, China: Spatial Variations, Pollution Statuses, and Ecological Risks
Authors: Qi Yue , Zhao Yilei , Fu Gang , Li Junsheng , Zhao Caiyun , Guan Xiao , Zhu Shuyu
Published: February 2022

In order to understand the spatial distribution, ecological risks, and pollution status of nutrients and heavy metals in the coastal tidal creek water of the Yellow River Delta (YRD), a total of 21 water samples were collected from 7 sample sites. The results indicated that along the coastline from northwest to southeast in the YRD, the concentrations of TN, TP, and NH4+-N in the water decreased and then increased; the Cu concentration increased, decreased, and then increased; and the Pb concentration decreased. The average TN/TP mass ratio indicated that the tidal creek water belonged to a potential phosphorus-restricted eutrophication state. The RI result indicated that Cu and Pb in the water were at low ecological risk, while the SSD and RQ results indicated that Cu in the water was at a high ecological risk level and had potential harm to aquatic organisms. Based on the single-factor method, the water quality of the tidal creek inside and outside the Yellow River Delta Nature Reserve belonged to Grade IV. Cu should be controlled to improve the water quality and reduce the ecological risk, especially in the Yellow River Delta Nature Reserve.
Performance Assessment of Event-Based Ensemble Landslide Susceptibility Models in Shihmen Watershed, Taiwan
Authors: Wu Chun-Yi , Lin Sheng-Yu
Published: February 2022

While multi-year and event-based landslide inventories are both commonly used in landslide susceptibility analysis, most areas lack multi-year landslide inventories, and the analysis results obtained from the use of event-based landslide inventories are very sensitive to the choice of event. Based on 24 event-based landslide inventories for the Shihmen watershed from 1996 to 2015, this study established five event-based single landslide susceptibility models employing logistic regression, random forest, support vector machine, kernel logistic regression, and gradient boosting decision tree methods. The ensemble methods, involving calculating the mean of the susceptibility indexes (PM), median of the susceptibility indexes (PME), weighted mean of the susceptibility indexes (PMW), and committee average of binary susceptibility values (CA) of the five single models were then used to establish four event-based ensemble landslide susceptibility models. After establishing nine landslide susceptibility models, using each inventory from the 24 event-based landslide inventories or a multi-year landslide inventory, we identified the differences in landslide susceptibility maps attributable to the different landslide inventories and modeling methods, and used the area under the receiver operating characteristic curve to assess the accuracy of the models. The results indicated that an ensemble model based on a multi-year inventory can obtain excellent predictive accuracy. The predictive accuracy of multi-year landslide susceptibility models is found to be superior to that of event-based models. In addition, the higher predictive accuracy of ensemble landslide susceptibility models than that of single models implied that these ensemble methods were robust for enhancing the model’s predictive performance in the study area. When employing event-based landslide inventories in modeling, PM ensemble models offer the best predictive ability, according to the Kruskal–Wallis test results. Areas with a high mean susceptibility index and low standard deviation, identified using the 24 PM ensemble models based on different event-based landslide inventories, constitute places where landslide mitigation measures should be prioritized.
Exploiting IoT and Its Enabled Technologies for Irrigation Needs in Agriculture
Authors: Ramachandran Veerachamy , Ramalakshmi Ramar , Kavin Balasubramanian , Hussain Irshad , Almaliki Abdulrazak , Almaliki Abdulrhman , Elnaggar Ashraf , Hussein Enas
Published: February 2022

The increase in population growth and demand is rapidly depleting natural resources. Irrigation plays a vital role in the productivity and growth of agriculture, consuming no less than 75% of fresh water utilization globally. Irrigation, being the largest consumer of water across the globe, needs refinements in its process, and because it is implemented by individuals (farmers), the use of water for irrigation is not effective. To enhance irrigation management, farmers need to keep track of information such as soil type, climatic conditions, available water resources, soil pH, soil nutrients, and soil moisture to make decisions that resolve or prevent agricultural complexity. Irrigation, a data-driven technology, requires the integration of emerging technologies and modern methodologies to provide solutions to the complex problems faced by agriculture. The paper is an overview of IoT-enabled modern technologies through which irrigation management can be elevated. This paper presents the evolution of irrigation and IoT, factors to be considered for effective irrigation, the need for effective irrigation optimization, and how dynamic irrigation optimization would help reduce water use. The paper also discusses the different IoT architecture and deployment models, sensors, and controllers used in the agriculture field, available cloud platforms for IoT, prominent tools or software used for irrigation scheduling and water need prediction, and machine learning and neural network models for irrigation. Convergence of the tools, technologies and approaches helps in the development of better irrigation management applications. Access to real-time data, such as weather, plant and soil data, must be enhanced for the development of effective irrigation management applications.
Research on Vegetation Coverage Dynamics and Prediction in the Taitema Lake Region
Authors: Zuo Tingfang , Chen Yaning , Ding Jianli
Published: February 2022

The Tarim River is the largest inland river in China, which plays a crucial role in maintaining regional ecological security and carbon cycle/dynamic. However, the “green corridor” in the Taitema Lake region at the lower reaches of the Tarim River has unclear environmental changes and future dynamics due to the influence of the ecological water conveyance. Hence, protecting the “green corridor” at the lower reaches of the Tarim River in China is strategically important not only ecologically but also socially and economically. In this paper, the temporal and spatial features of the fractional vegetation coverage (FVC) dynamics in the Taitema Lake region at the lower reaches of the Tarim River in 2000–2018 are analyzed and calculated using Landsat TM/OLI remote sensing images and MODIS data products. Additionally, the future trend of FVC dynamics in the study region are predicted using trend analysis and the pixel-based Hurst index. The results show that FVC in the Taitema Lake region exhibit a positive development after the implementation of ecological water conveyance. Specifically, from 2000 to 2018, the areas of low, medium, and high FVC expanded from 1.28 km2 to 179.87 km2, resulting in an increase of 140.52%. Spatially, the regions around the lake entrance channel of the Tarim River saw a significant increase in FVC of 9.71%. The middle part of the study region, accounting for only 1.96% of the area, displayed relatively high and high fluctuations in FVC. In the future, the regions at the middle part of the lake and around the lake entrance channel of the Tarim River, accounting for 11.33% of the area, will likely show an increasing trend in FVC. The regions with either extremely low or low FVC are predicted to decrease to 14.16% of the overall area. Because the positive effects of ecological water conveyance were more significant on FVC in the study region than the influences of either temperature or precipitation, ecological water conveyance should remain the primary means of ecological restoration for Taitema Lake.
The Vision Zero concept is the basis of innovative technologies on the way to the highest safety in industry
Authors:   Ufa State Petroleum Technical University, Shakurova M.M.
Published: February 2022

In the Russian Federation, hundreds of thousands of people carry out activities in the field of oil and gas production. Ensuring their health and safety is the main concern of employers, regulators, trade associations, industry groups and local communities. Work in this industry includes physical labor, round-the-clock operations, heavy machinery, hazardous chemicals, often remote locations and weather conditions. All these factors increase the risk of physical harm and determine the need for special protective measures.
Safe operation of lifting systems including steel ropes
Authors:   NSTU, Novosibirsk, Ilyushov N.Ya. , Tashtanbaeva. V.O. ,   KSTU named after I. Razzakov, Bishkek
Published: February 2022

Various negative factors influence the duration of safe operation of lifting equipment, lifting devices and other systems in which steel ropes operate. The article discusses steel ropes, which belong to the main traction elements of various lifting machines. During long-term operation, they are exposed to factors, including significant stresses, friction, wear, corrosion, plastic deformation, etc. Well-planned periodic inspections of the rope and assessment of its suitability for further use make it possible to eliminate the risks of using the equipment.