bluuebunny/crossref_metadata_2025 huggingface dataset:
Genetic and Genomic Resources for Soybean Breeding Research
Authors: Petereit Jakob , Marsh Jacob I. , Bayer Philipp E. , Danilevicz Monica F. , Thomas William J. W. , Batley Jacqueline , Edwards David
Published: April 2022

Soybean (Glycine max) is a legume species of significant economic and nutritional value. The yield of soybean continues to increase with the breeding of improved varieties, and this is likely to continue with the application of advanced genetic and genomic approaches for breeding. Genome technologies continue to advance rapidly, with an increasing number of high-quality genome assemblies becoming available. With accumulating data from marker arrays and whole-genome resequencing, studying variations between individuals and populations is becoming increasingly accessible. Furthermore, the recent development of soybean pangenomes has highlighted the significant structural variation between individuals, together with knowledge of what has been selected for or lost during domestication and breeding, information that can be applied for the breeding of improved cultivars. Because of this, resources such as genome assemblies, SNP datasets, pangenomes and associated databases are becoming increasingly important for research underlying soybean crop improvement.
Hydrodynamic Characteristics and Conformational Parameters of Ferrocene-Terpyridine-Based Polymers
Authors: Gubarev Alexander S. , Lezov Alexey A. , Mikusheva Nina G. , Perevyazko Igor , Senchukova Anna S. , Lezova Alexandra A. , Podsevalnikova Anna N. , Rogozhin Vyacheslav B. , Enke Marcel , Winter Andreas , Schubert Ulrich S. , Tsvetkov Nikolai V.
Published: April 2022

Nowadays, the study of metallopolymers is one of the fastest growing areas of polymer science. Metallopolymers have great potential for application in multiple technological and various biomedical processes. The macromolecules with the possibility of varying the number and type of metal ions along the entire length of the polymer chain are of particular interest. In this regard, this study presents results on two successfully synthesized homopolymers, random and block copolymers based on PMMA, containing ferrocene and terpyridine moieties in the side chain. Different architectures of copolymers may attribute interesting properties when creating complexes with various metal ions. A detailed hydrodynamic study of these structures was carried out, the consistency of hydrodynamic data was established using the concept of a hydrodynamic invariant, the absolute values of the molar masses of the studied objects were calculated, and the conformational parameters of macromolecules were determined. Using the Fixman–Stockmayer theory, the equilibrium rigidities of the studied systems were calculated and the relationship between the chemical structure and conformational characteristics was established. The studied copolymers can be attributed to the class of flexible-chain macromolecules. An increase in the equilibrium rigidity value with an increase of the side chain, which is characteristic of comb-shaped polymers, was determined.
Performance Evaluation of Nonacosan-10-ol-Based Polyethylene Packaging Material Using Molecular Dynamics Simulations
Authors: Madhuranthakam Chandra Mouli R. , Pandiyan Sudharsan , Penlidis Alexander
Published: April 2022

Packaging material has a significant role in maintaining or altering the shelf life of different products. Polymer materials are extensively used as packaging materials for different perishable and non-perishable products both during transportation and storage. This article aims at developing a new polymer composite which can be used as packaging material. This new composite addresses the challenge of controlling oxygen diffusion rates during the storage of perishable goods such as vegetables, meat and produce, etc. The proposed new composite primarily consists of nonacosan-10-ol and polyethylene. Molecular dynamics simulations (MDS) are performed by mixing 5.2%, 17.1%, 29.2%, 40.8% and 45.2% (wt/wt) of nonacosan-10-ol to amorphous polyethylene. Mechanical properties such as Young’s modulus/glass transition temperature, and gas transport properties such as diffusion coefficient and diffusion volume are estimated from the MDS and diffusion related simulations consisting of different oxygen concentrations in polyethylene-alone system and polyethylene- nonacosan-10-ol blends. The impact of adding different weight percent of nonacosan-10-ol to polyethylene is quantitatively assessed and optimal composition of the proposed additive is suggested corresponding to minimal oxygen diffusion rate, high elastic modulus and good thermal stability.
Physical Properties of Betaine-1,2-Propanediol-Based Deep Eutectic Solvents
Authors: Chen Qicheng , He Nan , Fan Jing , Song Fenhong
Published: April 2022

Due to their splendid advantages, deep eutectic solvents have attracted high attention and are considered as analogues of ionic liquids. Deep eutectic solvents (DESs) are homogeneous mixtures formed by two or three green and cheap components through hydrogen bond, which is divided into hydrogen bond acceptors (HBA) and hydrogen bond donors (HBD). Recently, Betaine has been widely used as a hydrogen bond acceptor. In this work, four DESs were synthesized by blending betaine as HBA and 1,2-propanediol as HBD in four molar ratios (1:3.5, 1:4, 1:5, 1:6). Then, the physical properties of these DESs were measured. The density values were measured within the temperature range (293.15 K to 363.15 K) at atmospheric pressure, whereas the surface tension and viscosity data were determined in four and seven temperatures between 293.15 K and 353.15 K. The relationship between the density and surface tension with temperature have been analyzed and have been fitted as a linear function. The commonly used Arrhenius model was used to describe the dependence between viscosity and temperature. The results of this study are important not only for the DESs’ industrial applications but also for the research on their synthesis mechanism and microstructure.
Calcined Co(II)-Chelated Polyazomethine as Cathode Catalyst of Anion Exchange Membrane Fuel Cells
Authors: Cheng Yu-Wei , Hsieh Tar-Hwa , Huang Yu-Chang , Tseng Po-Hao , Wang Yen-Zen , Ho Ko-Shan , Huang Yue-Jie
Published: April 2022

Polyazomethine (PAM) prepared from the polycondensation between p-phenylene diamine (PDA) and p-terephthalaldehyde (PTAl) via Schiff reaction can physically crosslink (complex) with Co ions. Co-complexed PAM (Co-PAM) in the form of gel is calcined to become a Co, N-co-doped carbonaceous matrix (Co-N-C), acting as cathode catalyst of an anion exchange membrane fuel cell (AEMFC). The obtained Co-N-C catalyst demonstrates a single-atom structure with active Co centers seen under the high-resolution transmission electron microscopy (HRTEM). The Co-N-C catalysts are also characterized by XRD, SEM, TEM, XPS, BET, and Raman spectroscopy. The Co-N-C catalysts demonstrate oxygen reduction reaction (ORR) activity in the KOH(aq) by expressing an onset potential of 1.19–1.37 V vs. RHE, a half wave potential of 0.70–0.92 V, a Tafel slope of 61–89 mV/dec., and number of exchange electrons of 2.48–3.79. Significant ORR peaks appear in the current–voltage (CV) polarization curves for the Co-N-C catalysts that experience two-stage calcination higher than 900 °C, followed by double acid leaching (CoNC-1000A-900A). The reduction current of CoNC-1000A-900A is comparable to that of commercial Pt-implanted carbon (Pt/C), and the max power density of the single cell using CoNC-1000A-900A as cathode catalyst reaches 275 mW cm−2.
Functionalized Nanomembranes and Plasma Technologies for Produced Water Treatment: A Review
Authors: Manakhov Anton , Orlov Maxim , Grokhovsky Vyacheslav , AlGhunaimi Fahd I. , Ayirala Subhash
Published: April 2022

The treatment of produced water, associated with oil & gas production, is envisioned to gain more significant attention in the coming years due to increasing energy demand and growing interests to promote sustainable developments. This review presents innovative practical solutions for oil/water separation, desalination, and purification of polluted water sources using a combination of porous membranes and plasma treatment technologies. Both these technologies can be used to treat produced water separately, but their combination results in a significant synergistic impact. The membranes functionalized by plasma show a remarkable increase in their efficiency characterized by enhanced oil rejection capability and reusability, while plasma treatment of water combined with membranes and/or adsorbents could be used to soften water and achieve high purity.
Improvement of Oil and Water Barrier Properties of Food Packaging Paper by Coating with Microcrystalline Wax Emulsion
Authors: Liu Dongyang , Duan Yuqing , Wang Shumei , Gong Murong , Dai Hongqi
Published: April 2022

Studies have shown that fluorinated oil repellents are potentially harmful to humans and the environment, and therefore, the development of non-toxic, green, and environmentally friendly oil repellents has become inevitable. Microcrystalline wax is a branched saturated alkane with a molecular weight of 580–700 Da, which has a lower surface tension than edible oil. Herein, microcrystalline wax emulsion (fluorine-free oil repellent) was prepared by mechanical stirring–homogenization, the effects of emulsifier ratio and dosage on the emulsion performance were systematically investigated, and the resultant stable microcrystalline wax emulsions were applied to the paper surface to explore the oil and water resistance and water vapor barrier performance. The results showed that stabilized microcrystalline wax emulsion was obtained at the emulsifier Span-80/Tween-80 ratio of 5:5, and the emulsifier dosage was 20% (relative to the microcrystalline wax). When 6 g/m2 of microcrystalline wax was applied to the surface of starch pretreated paper, the kit rating value of the paper was high, at up to 10/12, the Cobb60 value decreased to 12.5 g/m2, the overall migration of paper was less than 10 mg/dm2, and the water vapor permeability was reduced by 81.9%, which met the requirements of oil and water resistance performance of food packaging paper.
Polyvinyl Alcohol/Polyaniline/Carboxylated Graphene Oxide Nanocomposites for Coating Protection of Cast Iron in Simulated Seawater
Authors: Elessawy Noha A. , Gouda Marwa H. , Elnouby Mohamed , Taha Nahla A. , Youssef M. Elsayed , Santos Diogo M. F.
Published: April 2022

In our daily lives and product manufacturing, metal corrosion causes significant economic losses. Numerous polymeric composite coatings have been shown to be resistant to harsh environments, such as those found in marine environments. In this study, a composite of polyvinyl alcohol/polyaniline blend loaded with carboxylated graphene was explored in the search for long-lasting coatings to resist electrochemical deterioration of cast iron in desalination systems of saltwater. Polyvinyl alcohol/polyaniline/carboxylated graphene oxide nanocomposite was spin-coated onto cast iron samples. Electrochemical impedance spectroscopy (EIS) and electrochemical DC corrosion testing with a three-electrode system were used to study corrosion resistance in uncoated and coated cast iron samples. The results exhibit effective corrosion protection properties. The EIS data indicated better capacitance and higher impedance values for coated samples than bare metal, depicting enhanced corrosion resistance against the saline environment. Tafel analysis confirmed a significant decrease in the corrosion rate of the PVA/PANI/GO-COOH coated sample.
Large-Scale Production of Size-Adjusted β-Cell Spheroids in a Fully Controlled Stirred-Tank Reactor
Authors: Petry Florian , Salzig Denise
Published: April 2022

For β-cell replacement therapies, one challenge is the manufacturing of enough β-cells (Edmonton protocol for islet transplantation requires 0.5–1 × 106 islet equivalents). To maintain their functionality, β-cells should be manufactured as 3D constructs, known as spheroids. In this study, we investigated whether β-cell spheroid manufacturing can be addressed by a stirred-tank bioreactor (STR) process. STRs are fully controlled bioreactor systems, which allow the establishment of robust, larger-scale manufacturing processes. Using the INS-1 β-cell line as a model for process development, we investigated the dynamic agglomeration of β-cells to determine minimal seeding densities, spheroid strength, and the influence of turbulent shear stress. We established a correlation to exploit shear forces within the turbulent flow regime, in order to generate spheroids of a defined size, and to predict the spheroid size in an STR by using the determined spheroid strength. Finally, we transferred the dynamic agglomeration process from shaking flasks to a fully controlled and monitored STR, and tested the influence of three different stirrer types on spheroid formation. We achieved the shear stress-guided production of up to 22 × 106 ± 2 × 106 viable and functional β-cell spheroids per liter of culture medium, which is sufficient for β-cell therapy applications.
Development of a Mobile Robot for Mine Exploration
Authors: Topolsky Dmitry , Topolskaya Irina , Plaksina Iuliia , Shaburov Pavel , Yumagulov Nikolay , Fedorov Dmitry , Zvereva Elena
Published: April 2022

This study focuses on aspects specific to adaptive mobile robotic systems. These include providing flexibility, high performance, the use of widely available element bases and others. The science intensity and technical level of the development of mobile robots are constantly growing. The element base of robots is constantly updated. In the presented article, the direction of research is related to the problems specific to mining robots. The use of research robots makes it possible to ensure safety of work in hard-to-reach places, monitor the status of active and idle mines, and find new minerals in idle mines, the processing of which was previously impossible. The article discusses the issues of ensuring the versatility of the design, the need to miniaturize robots, reducing the cost of the robot while maintaining high performance, achieving the required level of protection from environmental influences in mines, and compatibility with control systems. Various ways of navigating robots in a limited space are analyzed. The results of the development and testing of a mobile robot prototype are presented. When looking for ways to implement a robot, the emphasis is on an effective combination of hardware and software.
Digital Twin for HIV-Gag VLP Production in HEK293 Cells
Authors: Hengelbrock Alina , Helgers Heribert , Schmidt Axel , Vetter Florian Lukas , Juckers Alex , Rosengarten Jamila Franca , Stitz Jörn , Strube Jochen
Published: April 2022

The development and adoption of digital twins (DT) for Quality-by-Design (QbD)-based processes with flexible operating points within a proven acceptable range (PAR) and automation through Advanced Process Control (APC) with Process Analytical Technology (PAT) instead of conventional process execution based on offline analytics and inflexible process set points is one of the great challenges in modern biotechnology. Virus-like particles (VLPs) are part of a line of innovative drug substances (DS). VLPs, especially those based on human immunodeficiency virus (HIV), HIV-1 Gag VLPs, have very high potential as a versatile vaccination platform, allowing for pseudotyping with heterologous envelope proteins, e.g., the S protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As enveloped VLPs, optimal process control with minimal hold times is essential. This study demonstrates, for the first time, the use of a digital twin for the overall production process of HIV-1 Gag VLPs from cultivation, clarification, and purification to lyophilization. The accuracy of the digital twins is in the range of 0.8 to 1.4% in depth filtration (DF) and 4.6 to 5.2% in ultrafiltration/diafiltration (UFDF). The uncertainty due to variability in the model parameter determination is less than 4.5% (DF) and less than 3.8% (UFDF). In the DF, a prediction of the final filter capacity was demonstrated from as low as 5.8% (9mbar) of the final transmembrane pressure (TMP). The scale-up based on DT in chromatography shows optimization potential in productivity up to a factor of 2. The schedule based on DT and PAT for APC has been compared to conventional process control, and hold-time and process duration reductions by a factor of 2 have been achieved. This work lays the foundation for the short-term validation of the DT and PAT for APC in an automated S7 process environment and the conversion from batch to continuous production.
Intercomparison of Real and Simulated GEDI Observations across Sclerophyll Forests
Authors: Huettermann Sven , Jones Simon , Soto-Berelov Mariela , Hislop Samuel
Published: April 2022

Forest structure is an important variable in ecology, fire behaviour, and carbon management. New spaceborne lidar sensors, such as the Global Ecosystem Dynamics Investigation (GEDI), enable forest structure to be mapped at a global scale. Virtual GEDI-like observations can be derived from airborne laser scanning (ALS) data for given locations using the GEDI simulator, which was a tool initially developed for GEDI’s pre-launch calibration. This study compares the relative height (RH) and ground elevation metrics of real and simulated GEDI observations against ALS-derived benchmarks in southeast Australia. A total of 15,616 footprint locations were examined, covering a large range of forest types and topographic conditions. The impacts of canopy cover and height, terrain slope, and ALS point cloud density were assessed. The results indicate that the simulator produces more accurate canopy height (RH95) metrics (RMSE: 4.2 m, Bias: −1.3 m) than the actual GEDI sensor (RMSE: 9.6 m, Bias: −1.6 m). Similarly, the simulator outperforms GEDI in ground detection accuracy. In contrast to other studies, which favour the Gaussian algorithm for ground detection, we found that the Maximum algorithm performed better in most settings. Despite the determined differences between real and simulated GEDI observations, this study indicates the compatibility of both data sources, which may enable their combined use in multitemporal forest structure monitoring.
Resolution-Sensitive Added Value Analysis of CORDEX-CORE RegCM4-7 Past Seasonal Precipitation Simulations over Africa Using Satellite-Based Observational Products
Authors: Gnitou Gnim Tchalim , Tan Guirong , Hongming Yan , Nooni Isaac Kwesi , Lim Kam Sian Kenny Thiam Choy
Published: April 2022

This study adopts a two-way approach to CORDEX-CORE RegCM4-7 seasonal precipitation simulations’ Added Value (AV) analysis over Africa, which aims to quantify potential improvements introduced by the downscaling approach at high and low resolution, using satellite-based observational products. The results show that RegCM4-7 does add value to its driving Global Climate Models (GCMs) with a positive Added Value Coverage (AVC) ranging between 20 and 60% at high resolution, depending on the season and the boundary conditions. At low resolution, the results indicate an increase in the positive AVC by up to 20% compared to the high-resolution results, with an up to 8% decrease for instances where an increase is not observed. Typical climate zones such as West Africa, Central Africa, and Southern East Africa, where improvements by Regional Climate Models (RCMs) are expected due to strong dependence on mesoscale and fine-scale features, show positive AVC greater than 20%, regardless of the season and the driving GCM. These findings provide more evidence for confirming the hypothesis that the RCMs AV is influenced by their internal physics rather than being the product of a mere disaggregation of large-scale features provided by GCMs. Although the results show some dependencies to the driving GCMs relating to their equilibrium climate sensitivity nature, the findings at low resolutions similar to the native GCM resolutions make the influence of internal physics more important. The findings also feature the CORDEX-CORE RegCM4-7 precipitation simulations’ potential in bridging the quality and resolution gap between coarse GCMs and high-resolution remote sensing datasets. Even if further post-processing activities, such as bias correction, may still be needed to remove persistent biases at high resolution, using upscaled RCMs as an alternative to GCMs for large-scale precipitation studies over Africa can be insightful if the AV and other performance statistics are satisfactory for the intended application.
Spatial Negative Co-Location Pattern Directional Mining Algorithm with Join-Based Prevalence
Authors: Zhou Guoqing , Wang Zhenyu , Li Qi
Published: April 2022

It is usually difficult for prevalent negative co-location patterns to be mined and calculated. This paper proposes a join-based prevalent negative co-location mining algorithm, which can quickly and effectively mine all the prevalent negative co-location patterns in spatial data. Firstly, this paper verifies the monotonic nondecreasing property of the negative co-location participation index (PI) value as the size increases. Secondly, using this property, it is deduced that any prevalent negative co-location pattern with size n can be generated by connecting prevalent co-location with size 2 and with an n − 1 size candidate negative co-location pattern or an n − 1 size prevalent positive co-location pattern. Finally, the experiment results demonstrate that while other conditions are fixed, the proposed algorithm has an excellent efficiency level. The algorithm can eliminate the 90% useless negative co-location pattern maximumly and eliminate the useless 40% negative co-location pattern averagely.
Multi-Sonar Distributed Fusion for Target Detection and Tracking in Marine Environment
Authors: Chen Roujie , Li Tingting , Memon Imran , Shi Yifang , Ullah Ihsan , Memon Sufyan Ali
Published: April 2022

The multi-sonar distributed fusion system has been pervasively deployed to jointly detect and track marine targets. In the realistic scenario, the origin of locally transmitted tracks is uncertain due to clutter disturbance and the presence of multi-target. Moreover, attributed to the different sonar internal processing times and diverse communication delays between sonar and the fusion center, tracks unavoidably arrive in the fusion center with temporal out-of-sequence (OOS), both problems pose significant challenges to the fusion system. Under the distributed fusion framework with memory, this paper proposes a novel multiple forward prediction-integrated equivalent measurement fusion (MFP-IEMF) method, it fuses the multi-lag OOST with track origin uncertainty in an optimal manner and is capable to be implemented in both the synchronous and asynchronous multi-sonar tracks fusion system. Furthermore, a random central track initialization technique is also proposed to detect the randomly born marine target in time via quickly initiating and confirming true tracks. The numerical results show that the proposed algorithm achieves the same optimality as the existing OOS reprocessing method, and delivers substantially improved detection and tracking performance in terms of both ANCTT and estimation accuracy compared to the existing OOST discarding fusion method and the ANF-IFPFD method.
Estimating Running Ground Reaction Forces from Plantar Pressure during Graded Running
Authors: Honert Eric C. , Hoitz Fabian , Blades Sam , Nigg Sandro R. , Nigg Benno M.
Published: April 2022

Ground reaction forces (GRFs) describe how runners interact with their surroundings and provide the basis for computing inverse dynamics. Wearable technology can predict time−continuous GRFs during walking and running; however, the majority of GRF predictions examine level ground locomotion. The purpose of this manuscript was to predict vertical and anterior–posterior GRFs across different speeds and slopes. Eighteen recreationally active subjects ran on an instrumented treadmill while we collected GRFs and plantar pressure. Subjects ran on level ground at 2.6, 3.0, 3.4, and 3.8 m/s, six degrees inclined at 2.6, 2.8, and 3.0 m/s, and six degrees declined at 2.6, 2.8, 3.0, and 3.4 m/s. We estimated GRFs using a set of linear models and a recurrent neural network, which used speed, slope, and plantar pressure as inputs. We also tested eliminating speed and slope as inputs. The recurrent neural network outperformed the linear model across all conditions, especially with the prediction of anterior–posterior GRFs. Eliminating speed and slope as model inputs had little effect on performance. We also demonstrate that subject−specific model training can reduce errors from 8% to 3%. With such low errors, researchers can use these wearable−based GRFs to understand running performance or injuries in real−world settings.
In-Field Wheat Reflectance: How to Reach the Organ Scale?
Authors: Dandrifosse Sébastien , Carlier Alexis , Dumont Benjamin , Mercatoris Benoît
Published: April 2022

The reflectance of wheat crops provides information on their architecture or physiology. However, the methods currently used for close-range reflectance computation do not allow for the separation of the wheat canopy organs: the leaves and the ears. This study details a method to achieve high-throughput measurements of wheat reflectance at the organ scale. A nadir multispectral camera array and an incident light spectrometer were used to compute bi-directional reflectance factor (BRF) maps. Image thresholding and deep learning ear detection allowed for the segmentation of the ears and the leaves in the maps. The results showed that the BRF measured on reference targets was constant throughout the day but varied with the acquisition date. The wheat organ BRF was constant throughout the day in very cloudy conditions and with high sun altitudes but showed gradual variations in the morning under sunny or partially cloudy sky. As a consequence, measurements should be performed close to solar noon and the reference panel should be captured at the beginning and end of each field trip to correct the BRF. The method, with such precautions, was tested all throughout the wheat growing season on two varieties and various canopy architectures generated by a fertilization gradient. The method yielded consistent reflectance dynamics in all scenarios.
Estimating Long-Run Relationship between Renewable Energy Use and CO2 Emissions: A Radial Basis Function Neural Network (RBFNN) Approach
Authors: Jena Pradyot Ranjan , Majhi Babita , Majhi Ritanjali
Published: April 2022

The long-run relationship between economic growth and environmental quality has been estimated within the framework of the environmental Kuznets Curve (EKC). Several studies have estimated this relationship by using statistical models such as panel regression and time series regression. The current study argues that there is a nonlinear relationship between environmental quality indicators and economic and non-economic predictors and hence an appropriate nonlinear model is required to predict it. An adaptive and nonlinear model, namely radial basis function neural network (RBFNN) has been developed in this study. CO2 emission is used as the target output and renewable energy consumption share, real GDP, trade openness, urban population ratio, and democracy index are used as the predictors to estimate the EKC relationship for nineteen major CO2 emitting countries that account for 78% of the global emissions. The model developed in this study could predict the CO2 emissions of all the countries with more than 95% accuracy. This finding underlines the usefulness of the RBFNN model which can be used to predict emission levels of other pollution indicators at the global level. Further, comparing two models, one with all the predictors and the other excluding the renewable energy share, it was found that the model with renewable energy share predicts CO2 emissions more accurately. This reinforces the already strengthening campaign to encourage industries and governments to increase the share of renewable energy in total energy use.
Fast Seismic Assessment of Built Urban Areas with the Accuracy of Mechanical Methods Using a Feedforward Neural Network
Authors: de-Miguel-Rodríguez Jaime , Morales-Esteban Antonio , Requena-García-Cruz María-Victoria , Zapico-Blanco Beatriz , Segovia-Verjel María-Luisa , Romero-Sánchez Emilio , Carvalho-Estêvão João Manuel
Published: April 2022

Capacity curves obtained from nonlinear static analyses are widely used to perform seismic assessments of structures as an alternative to dynamic analysis. This paper presents a novel ‘en masse’ method to assess the seismic vulnerability of urban areas swiftly and with the accuracy of mechanical methods. At the core of this methodology is the calculation of the capacity curves of low-rise reinforced concrete buildings using neural networks, where no modeling of the building is required. The curves are predicted with minimal error, needing only basic geometric and material parameters of the structures to be specified. As a first implementation, a typology of prismatic buildings is defined and a training set of more than 7000 structures generated. The capacity curves are calculated through push-over analysis using SAP2000. The results feature the prediction of 100-point curves in a single run of the network while maintaining a very low mean absolute error. This paper proposes a method that improves current seismic assessment tools by providing a fast and accurate calculation of the vulnerability of large sets of buildings in urban environments.
The Potential of the Co-Recycling of Secondary Biodegradable Household Resources Including Wild Plants to Close Nutrient and Carbon Cycles in Agriculture in Germany
Authors: Fendel Veronika , Maurer Claudia , Kranert Martin , Huang Jingjing , Schäffner Benjamin
Published: April 2022

The aim of this study is to evaluate the potential for conserving natural resources (fossil resources, mineral fertilizer, fertile soil and biodiversity) with alternative circular concepts in order to contribute to the achievement of global sustainability goals. This study examines the potential contribution of substituting conventional products for three alternative circular economy concepts. This includes the household resources black water, kitchen and green waste for the production of design fertilizer, plant charcoal, biopolymers (concept 1) and biogas (concept 2), as well as the combination of household kitchen waste with wild plants for the production of biogas (concept 3). For evaluation, literature values were combined with analyzed parameters of input streams and biogas tests. The production and consumption values determined all relate to the functional unit of a person and year in Germany. Concept 1 has the highest potential for substitution in terms of the amount of recycled products. Co-recycling of organic household waste can account for 20% of NPK (nitrogen, phosphorus, potassium) mineral fertilizer, 19% of plastic consumption and 11% as a soil improving measure in soils in agriculture that are at risk of degradation. Concept 2 has the potential to contribute 12% of the final energy consumption in private households, which is an alternative solution regarding energy recovery due to the extensive practical experience. The joint recycling generates 141 kWh without, and 174 kWh with, fermentable green waste. If 75%, by weight, of fresh wild plants are added to the kitchen waste in concept 3, a wild plant area of 5 m2 is required, which could replace 41% of the biogas corn area, which is concept 3. This mix generates 193 kWh with the potential to reach 78% of corn energy production. The share of wild plants in kitchen waste of 50 or 25% by weight has the potential to achieve 115 or 104% of the corn energy yield, which is a promising concept for rural areas regarding energy recovery from an ecological point of view. The results show a considerable contribution potential of household resources in alternative cycle concepts to increase resource efficiency, and indirectly to diversify the agricultural landscape.
Analysis of Cooperation Behaviors and Crowd Dynamics during Pedestrian Evacuation with Group Existence
Authors: Ma Yaping , Liu Xiaoying , Huo Feizhou , Li Hui
Published: April 2022

At most public places where large-scale events are held, the crowd as a pedestrian particle system is a mixture of individuals and groups rather than a pure collection of individuals. The interaction behaviors of pedestrians within the same group and between different groups are significantly disparate, which makes the crowd evacuation process more complex. To address this issue, a new pedestrian evacuation model is proposed incorporating the cellular automaton model and game theory. In the model, two game theory models named prisoner’s dilemma and harmony game are applied to depict the interaction mechanism between pedestrians, and the decision-making of one pedestrian regarding route choice is subject to the environment factor and interaction payoffs between his neighbors. The influences of the intensity of interaction between pedestrians, the willingness to cooperate, the number of groups, the size of groups, and the initial distribution pattern of groups on the evacuation dynamics and cooperation evolution of the crowd are discussed. Simulation results show that it is beneficial to the evacuation efficiency and the formation of cooperation behaviors when pedestrians have a low intensity of interaction. As the willingness of large groups to cooperate is high, an increase in group’ sizes and numbers can improve the cooperation fraction of the crowd but prolongs evacuation time. Groups in the crowd gathered together initially negatively affect the evacuation efficiency of the crowd.
Transformation for Feature Upgrades or Higher Property Prices: Evidence from Industrial Land Regeneration in Shanghai
Authors: Yang Fan , Tao Peihong , Cai Xiao , Wang Jiayin
Published: April 2022

In recent years, an increasing amount of industrial land has been left idle in China. This gave rise to a wide range of urban issues hindering sustainable urban development. To solve this problem, industrial land transformation has been promoted. However, factors affecting industrial land transformation have not been adequately explored. To fill this gap, this study employs the bivariate K-function to analyze the spatial association between agglomeration patterns of industrial land parcels and living quarters. Moreover, a series of discrete choice models (i.e., the LOGIT, PROBIT, and IVPROBIT model) are adopted to examine empirically complicated relationships between industrial land transformation and its influencing factors. This study argues that the land price and its rising expectations are major determinants of industrial land transformation. The results revealed that transformation-oriented industrial land tended to be located next to accessible living quarters with higher prices. A higher-level industrial park typically had less possibilities for industrial land transformation. The findings also indicated that production efficiency served as a moderator variable to regulate the transformation process. Implications are formulated for policymakers to guide industrial land transformation in an appropriate manner.
Effects of Combining Different Collaborative Learning Strategies with Problem-Based Learning in a Flipped Classroom on Program Language Learning
Authors: Chang Yi-Hsing , Yan Yin-Chen , Lu You-Te
Published: April 2022

This study proposed combining problem-based learning (PBL) with different collaboration learning strategies in flipped classrooms to improve learners’ learning motivation and learning outcomes. The main idea was to design a teaching process based on the concept of flipped classrooms. The proposed method was adopted to design learning objectives, learning content, and group activities, thereby forming new teaching strategies for developing students’ independent learning, logical thinking, problem-solving skills, learning outcomes, and learning motivation. We used the C# programming language as the learning target and recruited 96 students from a first-year class of the Department of Information Management of the Southern Taiwan university of Science and Technology as participants. During the experiment, the participants were divided into an experimental group with heterogeneous subgroups and a control group with random subgroups, and pretest and posttest data obtained during the programming course were used to evaluate the learning effects of the proposed teaching strategies. In addition, a questionnaire was used to explore learning motivation through three aspects: flipped classroom, PBL, and collaborative learning. The results of this study indicated that the proposed teaching strategies improved the participants’ learning outcomes. The experimental group exhibited higher improvements in learning outcomes than did the control group. Significant results were obtained for all the items of the adopted questionnaire. Thus, the participants provided positive ratings to the flipped classroom model designed in this study.
How COVID-19 Affected GHG Emissions of Ferries in Europe
Authors: Mannarini Gianandrea , Salinas Mario Leonardo , Carelli Lorenzo , Fassò Alessandro
Published: April 2022

Unprecedented socioeconomic conditions during the COVID-19 pandemic impacted shipping. We combined ferry CO2 emissions in Europe (from the EU-MRV) with port call data and vessel parameters, and analysed them using mixed-effects linear models with interactions. We found a generalized reduction in unitary emissions in 2020, confirming its causal relation with COVID-19. Furthermore, for larger ferries, additional and COVID-19-related reductions between 14% and 31% occurred, with the larger reductions for those built before 1999. Ferries operating in the Baltic and Mediterranean Seas experienced comparable reductions in their unitary emissions, but in the North Sea per-ship emissions decreased by an additional 18%. Per-ship emissions at berth, while showing increases or decreases depending on ferry type, did not significantly change at the fleet level. We believe that our methodology may help assess the progress of shipping toward decarbonisation in the presence of external shocks.
Analysis of the Steps Cycle in the Action of Throwing in Competition in Men’s Elite Handball
Authors: Tuquet Jaime , Cartón Antonio , Marco-Contreras Luis A. , Mainer-Pardos Elena , Lozano Demetrio
Published: April 2022

The aim of this article was to analyze the step cycle that precedes the throwing action in elite men’s handball and its relationship with different factors, such as throwing distance, throwing technics, throw speed, whether it occurs in jump or standing, the last step, and efficiency. Twenty-four complete matches were analyzed, with a total of 1013 throws in three international elite men’s handball championships. The results show that the most used step cycle is the one performed with two steps. There is a significant relationship between the step cycle and the throw distance, with two-step throws being the most used from outside 9 m (29.8%, p < 0.001), three-step throws at a distance between 6 and 9 m (35.9%, p < 0.001), and zero- and one-step throws from 6 m (30.5%, p < 0.001). Likewise, the last step with natural footing is the most used (93.7%, p < 0.001) with a complete cycle of steps, followed by false foot with more than three steps (27.3%, p < 0.001), and two feet with zero steps (12.6%, p < 0.001). In conclusion, the skill to take advantage of the dynamic improvement offered by the mastery of the step cycle, adapting to the different situations of the game, could be an essential characteristic of the player to effectively complete the throwing action.
Systemic Risk Contributions of Financial Institutions during the Stock Market Crash in China
Authors: He Miao , Guo Yanhong
Published: April 2022

This paper investigates the systemic risk contributions of each financial institution during the stock market crash in China using systemic risk beta. Based on the FARM-Selection (Factor Adjusted Regularized Model Selection) approach, we calculate the systemic risk beta, implying the importance of each financial institution during the stock market crash. We find that security firms are the main contributors to systemic risk. In addition, some macro variables have a significant influence on systemic risk, including changes in March Treasury rates and the AAA-rated bond and 10-year Treasury credit spreads. This paper provides an important perspective to identify the SIFIs (Systemically Important Financial Institutions) during the stock market crash.
Coupling Coordination Development of the Logistics Industry, New Urbanization and the Ecological Environment in the Yangtze River Economic Belt
Authors: Ye Chong , Pi Jiawei , Chen Hanqi
Published: April 2022

Achieving the coordinated development of the logistics industry, new urbanization and the ecological environment is significant for improving the efficiency of the logistics industry, urbanization level and environmental quality, but there are few studies that consider all three together. Based on the panel data of 11 provinces and municipalities in the Yangtze River Economic Belt from 2009 to 2019, this paper constructs the evaluation index system of the logistics industry, new urbanization and the ecological environment. The entropy method, coupled coordination degree model and exploratory spatial data analysis method are used to empirically analyze the spatial and temporal evolution patterns of the coupled coordination of the three systems in the Yangtze River Economic Belt. The results show that: (1) during the study period, the comprehensive development level of each subsystem and composite system in the Yangtze River Economic Belt has been improving, but there are some differences in the development among the systems in each region; (2) the coupling coordination degree of the three shows a smooth upward trend and an overall transition from near incoordination or basic coordination to the level of primary coordination or intermediate coordination, showing a spatial distribution pattern of downstream > midstream > upstream; (3) the spatial agglomeration characteristics show significant positive spatial correlation and agglomeration and are dominated by high–high agglomeration and low–low agglomeration. These reflect the enormous spatial and temporal differences in the coupling coordination of the three systems in the Yangtze River Economic Belt. The study takes the perspective of the coupled and coordinated development of the logistics industry, new urbanization and the ecological environment, which can provide references for enterprises and governments to make sustainable industrial and urbanization development strategies.
New Chaotic System: M-Map and Its Application in Chaos-Based Cryptography
Authors: Lawnik Marcin , Berezowski Marek
Published: April 2022

One of the applications of dynamical systems with chaotic behavior is data encryption. Chaos-based cryptography uses chaotic dynamical systems as the basis for creating algorithms. The present article discusses a new dynamical system called M-map with its analysis: fixed points, bifurcation diagram, Lyapunov exponent, and invariant density. The obtained bifurcation diagram and the plot of the Lyapunov exponent (with a minimum value of ln2 and a maximum value of ln4) suggest that the so-called robust chaos characterizes this map. Moreover, the obtained results are compared with other dynamical systems used in cryptography. Additionally, the article proposes a new image encryption algorithm. It uses, among others, cyclically shifted S-box or saving encrypted pixels on the first or last free space in the cipher-image. The conducted analysis shows that the cipher-images are characterized by an entropy value close to 8, a correlation of adjacent pixels value close to 0, or values of Number of Pixel of Change Rate (NPCR) and Unified Average Changing Intensity (UACI) measures close to 100% and 33%, respectively.
Electronic Structure Calculation of Cr3+ and Fe3+ in Phosphor Host Materials Based on Relaxed Structures by Molecular Dynamics Simulation
Authors: Ichikawa Joichiro , Kominami Hiroko , Hara Kazuhiko , Kakihana Masato , Matsushima Yuta
Published: April 2022

The electronic structures of the luminescent center ions Cr3+ and Fe3+ in the deep red phosphors LiAl5O8:Cr3+, α-Al2O3:Cr3+, and γ-LiAlO2:Fe3+ were calculated by the DV-Xα method, in which the local distortion induced by the replacement of Al3+ sites in the host crystals by the luminescent center ions was reproduced by classical molecular dynamics (MD) simulation. The MD simulations based on classical dynamics allowed for the handling of more than 1000 atoms for the lattice relaxation calculations, which was advantageous to simulate situations in which a small number of foreign atoms (ions) were dispersed in the host lattice as in phosphors, even when typical periodic boundary conditions were applied. The relaxed lattices obtained after MD indicated that the coordination polyhedra around Cr3+ and Fe3+ expanded in accordance with the size difference between the luminescent center ions and Al3+ in the host crystals. The overall profiles of the partial density of states (p-DOSs) of the isolated Cr3+ and Fe3+ 3d orbitals were not significantly affected by the lattice relaxation, whereas the widths of the energy splitting of the 3d orbitals were reduced. The electronic structure calculations for Fe–Fe pairs in γ-LiAlO2 showed that the antiferromagnetic interactions with antiparallel electron spins between the Fe3+ ions were preferred, especially when the Fe–Fe pair was on the first-nearest neighboring cation sites.
Honey Environmental DNA Can Be Used to Detect and Monitor Honey Bee Pests: Development of Methods Useful to Identify Aethina tumida and Galleria mellonella Infestations
Authors: Ribani Anisa , Taurisano Valeria , Utzeri Valerio Joe , Fontanesi Luca
Published: April 2022

Environmental DNA (eDNA) contained in honey derives from the organisms that directly and indirectly have been involved in the production process of this matrix and that have played a role in the hive ecosystems where the honey has been produced. In this study we set up PCR-based assays to detect the presence of DNA traces left in the honey by two damaging honey bee pests: the small hive beetle (Aethina tumida) and the greater wax moth (Galleria mellonella). DNA was extracted from 82 honey samples produced in Italy and amplified using two specific primer pairs that target the mitochondrial gene cytochrome oxidase I (COI) of A. tumida and two specific primer pairs that target the same gene in G. mellonella. The limit of detection was tested using sequential dilutions of the pest DNA. Only one honey sample produced in Calabria was positive for A. tumida whereas about 66% of all samples were positively amplified for G. mellonella. The use of honey eDNA could be important to establish early and effective measures to contain at the local (e.g., apiary) or regional scales these two damaging pests and, particularly for the small hive beetle, to prevent its widespread diffusion.