bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic Smart Numbering of Modular Cargo Containers
Authors: Aksentijević Saša , Tijan Edvard , Kapidani Nexhat , Žgaljić Dražen
Published: July 2022

In this paper, the authors identify the existence of container imbalance that occurs in different types of ports, depending on the type of inbound and outbound cargo they serve. The authors further analyze international trade realities and maritime companies’ requirements and identified inefficiencies. A comprehensive review of the relevant container regulations and identification standards is performed. Based on their findings, a paradigm change is proposed in the form of a modular container solution that uses disruptive digital technologies to ensure dynamic container identification (numbering) that can be exploited to overcome such inefficiencies. The technical requirements for coupling and decoupling operations are identified, along with detailed analysis of the requirements for embedded electronic components. Considering the strict container data exchange rules, the required changes in global container tracking systems are identified and explained. Coupling, decoupling, and serial number assignment procedures are proposed along with analysis of the measured lead times. Modularization and dynamic smart numbering are identified as viable disruptive technologies to address the global container imbalance. The authors contribute to the existing research on maritime transport sustainability by proposing a modular container solution, exploiting disruptive digital technologies, and clearly defining the prerequisites for the global introduction of the solution as a part of the digital transformation portfolio of involved stakeholders managing global container movements.
Textile and Product Development from End-of-Use Cotton Apparel: A Study to Reclaim Value from Waste
Authors: Cao Huantian , Cobb Kelly , Yatvitskiy Michelle , Wolfe Megan , Shen Hongqing
Published: July 2022

The textile and apparel production and consumption generate a huge amount of solid textile waste. Mechanical recycling is one main method to recycle cotton waste; however, shredding in mechanical recycling shortens fiber length and reduces fiber quality. As a result, the application of mechanically recycled textiles may be limited. This research investigated mechanical methods to recycle post-consumer cotton textile waste and designed and developed second-life products. This study applied research through design methodology and documented step-by-step textile and product development practices to communicate the results. Using the textiles from deconstructed end-of-use garments with a high cotton content (80% or higher), combined with other materials, the researchers developed yarns, and nonwoven, woven, quilted, tufted fabrics. The researchers tested textile properties such as “yarn” tensile strength and elongation, fabric thickness, thermal resistance, air permeability, and stiffness. Using fabrics developed from end-of-use cotton waste, the researchers designed and developed high-value products such as bags, decorative textile, a hat, cell phone and glasses cases, and garments to contribute to the sustainability and circularity of cotton.
Design and Repair Strategies Based on Product–Service System and Remanufacturing for Value Preservation
Authors: Arredondo-Soto Karina Cecilia , Jiménez-Zaragoza Alejandro , Miranda-Ackerman Marco Augusto , Blanco-Fernández Julio , García-Lechuga Alejandra , Hernández-Escobedo Guadalupe , García-Alcaraz Jorge Luis
Published: July 2022

Remanufacturing is a production practice that requires the work of producers, consumers, and the government. There are benefits associated with this production model, such as improving the environment, opportunities for cost savings, and others. However, it is essential to identify the factors that affect the possibility of acceptance of this production model. This research proposes a model based on different analysis methodologies and techniques of SEM (Structural Equations Modeling) and the method of PLS (Partial Least Squares). A total of 403 responses to the survey were collected from 1 November 2021 to 15 January 2022. For the data treatment, SPSS, Excel, and WarpPLS software were used to identify the variables, factors, and their direct and indirect effects among the latent variables, referring to a scheme focused on consumer perception based on the acquisition remanufactured products. This created model served as a reference to create and develop a design and repair strategy for White goods or similar products in handling, logistics, and repair. This design strategy was transformed into a business model based on a circular economy, particularly on a Product–Service System with social, economic, and environmental benefits for producers and consumers.
Short-Term Forecast of OD Passenger Flow Based on Ensemble Empirical Mode Decomposition
Authors: Cao Yi , Hou Xiaolei , Chen Nan
Published: July 2022

The development of metro systems can be a good solution to many problems in urban transport and promote sustainable urban development. A metro system plays an important role in urban public transit, and the passenger-flow forecasting is fundamental to assisting operators in establishing an intelligent transport system (ITS). In order to accurately predict the passenger flow of urban metros in different periods and provide a scientific basis for schedule planning, a short-term metro passenger-flow prediction model is constructed by integrating ensemble empirical mode decomposition (EEMD) and long short-term memory neural network (LSTM) to solve the problem that the existing empirical mode decomposition (EMD) is prone to modal aliasing. According to the processed metro-card data, the time series of historical OD data of metro passenger flow is obtained. After EEMD modal decomposition, several intrinsic mode functions sub-items and residual items are obtained. Then, an LSTM network is constructed for prediction. The time step of the network is decided according to the partial autocorrelation functions. The prediction results of intrinsic mode function (IMF) and residual items are integrated to obtain prediction results. The station is classified according to the land types around the station, and the model is tested by using the metro automatic fare collection (AFC) data. In order to test the actual prediction, a different number of training set samples are selected to predict. The measured data of the next day is continuously added to the original training set to compare the prediction accuracy. The results show that the mean absolute percentage error (MAPE) and root mean square error (RMSE) of the EEMD-LSTM model are better than the EMD-LSTM in predicting the OD value of commercial–residential stations and scenic–residential stations. Compared with the EMD-LSTM model, the EEMD-LSTM model showed an average reduction by 3.112% in MAPE values and 15.889 in RMSE, indicating that the EEMD-LSTM has higher prediction accuracy, and EEMD-LSTM model has higher accuracy in short-term metro passenger-flow prediction. The average MAPE for the 35-to-42-day historical data sample decreased from 13.02% to 10.39% with a decreasing trend. It shows that the prediction accuracy keeps improving as the training set samples increase.
Decarbonization of Nitrogen Fertilizer: A Transition Engineering Desk Study for Agriculture in Germany
Authors: Ahrens Florian , Land Johann , Krumdieck Susan
Published: July 2022

The use of fossil fuel and artificial nitrogen fertilizer in German agriculture is a wicked problem. The incumbent system allows access to nutrition, but relies on unsustainable fossil fuel, produces greenhouse gas emissions along the whole production chain, and nitrogen pollution. This article uses the Interdisciplinary Transition Innovation, Engineering, and Management (InTIME) method for German agriculture systems with data from FAO and the German Ministry For Food And Agriculture. The purpose of this article is a rigorous analysis of the complex agriculture system and the development of feasible opportunities for sustainable carbon downshifting. Sustainability indicators are biodiversity loss, fossil-fuel use, mineral depletion, energy use, carbon emissions and eutrophication. The results indicate that the technology-based solution of “green hydrogen” as a substitute for fossil hydrogen in the fertilizer production decreases the sustainability of the agriculture system. The most promising results arise from shifting consumption of meat and animal-based products to a more plant based diet, and transitioning to organic agriculture. Net-zero sustainability goals and a reduction in eutrophication are achieved by 75% downshift of animal products and the upscaling of organic agriculture. Strategic scenarios to achieve the results are developed and recommendations for policy implementation to ease the transition are examined.
Explosion Risks during Firefighting Operations in Storage Rooms and the Transport of Ammonium Nitrate-Based Fertilizers
Authors: Wolny Paweł , Tuśnio Norbert , Mikołajczyk Filip
Published: July 2022

Ammonium nitrate (AN) is a strong oxidizer that undergoes phase transitions and thermal decomposition at relatively low temperatures. This—as verified by historical facts—constitutes a challenge for the fire department during rescue operations. AN is also a highly reactive material widely used for the production of, i.a., fertilizers and explosives. The latter are popular not only in military applications but also in industrial ones, such as mining. They include ammonites and amatols utilized in coal mining, as well as Ammonium Nitrate Fuel Oil (ANFO) utilized in, i.a., rock mining. As a simple and cheap material, ANFO also tends to be used by terrorists. The spontaneous formation of an AN and polymers mixture—similar to ANFO in terms of composition and explosion force—was observed in fire conditions during previous research. At individual stages (from creation to exploitation), AN often comes into direct contact with various polymers. Polyolefins, in particular polyethylene (PE) and polypropylene (PP), are among the most popular groups of such materials. They are used for the production of, i.a., foil packaging and flexible intermediate bulk containers for the storage and transport of fertilizers. Despite the frequent mutual contact of these materials, there is little information in the literature on the interaction of AN and its polymer-made packaging in fire conditions. For this reason, it was decided to conduct a series of thermal analyses using Differential Scanning Calorimetry (DSC) to study the material behavior under the influence of high temperature. As it turns out in practice, the spontaneous formation of a mixture similar to ANFO—in terms of composition and explosion force—can be observed in fire conditions. Due to the results indicating a potentially explosive course of the reaction, laboratory tests on the macro scale were also carried out. The performed observations show that it may be necessary to create a procedure containing several different test methods in order to predict a mixture’s behavior during a fire and to define the appropriate guidelines for firefighting teams. Such guidelines would enable firefighters to prepare the right equipment during a firefighting operation and to develop a strategy based on the observed course of events.
An Experimental Study on the Dynamic Evolution Characteristics of Soil Arching and the Rational Spacing of Anti-Slide Piles
Authors: Zhong Wei , Zhang Shuai , He Na
Published: July 2022

In order to analyse the dynamic evolution characteristics of soil arching during sliding processes, we conducted a series of model push-pile and direct shear tests. The tests’ results were used to design a relative displacement monitoring system and to introduce two dimensionless parameters (the push–compaction ratio (e) and the different degrees of push–compaction (t)) to investigate the degree of uneven soil deformation during the sliding processes. This innovative method was used to analyse the rational spacing between adjacent anti-slide piles. The results revealed that there was a push-to-compaction effect in sliding soil during the sliding process. Firstly, in terms of space, the gradual transfer characteristics of the landslide thrust and push-to-compaction effect, rather than a uniform deformation over the entire area, were revealed. In terms of time, the results demonstrated a law for the variation in push-to-compaction ratios: The expansion of e occurred earlier in the rear sliding body than in the front e, while the growth rate of front e was faster than that of e in the rear sliding body. The dynamic evolution process was divided into three stages: an elastic formation stage, a plastic development stage, and a failure stage. Secondly, during the sliding process, the shear strength parameters of the sliding soil did not have constant values but underwent a dynamic process of strengthening, and cohesion responded more efficiently than friction. Finally, the degree of mobilisation of the anti-sliding effect of the sliding soil can be used as a new means of quantitative analysis for rational spacing. The results indicated that the rational spacing between adjacent piles should be five times the width of the pile.
Global Challenges and Prospects of Photovoltaic Materials Disposal and Recycling: A Comprehensive Review
Authors: Yu Hui Fang , Hasanuzzaman Md. , Rahim Nasrudin Abd , Amin Norridah , Nor Adzman Noriah
Published: July 2022

The considerable amount of waste PV modules expected to emerge from recent widespread of solar photovoltaic (PV) systems is a cause of concern, especially in sustainability terms. Currently, most end-of-life (EoL) PV modules are either disposed of in landfills or bulk recycled in existing recycling facilities. Although these approaches are easier in execution as less efforts are directed at sustainable management of these modules, they can potentially cause environmental issues including loss of valuable resources and leakage of toxic materials. Hence, high-value closed-loop recycling is much preferred for its environmental merits, although its implementation brings forward challenges that this paper attempts to shed light on. This review paper aims to provide an overview of the EoL management of PV modules, concentrating on the challenges faced in PV recycling. Additionally, PV waste-related regulatory frameworks implemented in different countries are discussed. Recommendations to improve the EoL management of PV modules and trade-offs arising from conflicting solutions are proposed. To establish a sustainable PV waste management framework, legislations promoting the extended producer responsibility (EPR) principle, presence of suitable infrastructure, research and development (R&D) and cooperation of various governmental and private bodies are highly needed.
Geospatial Analysis of Land Use/Cover Change and Land Surface Temperature for Landscape Risk Pattern Change Evaluation of Baghdad City, Iraq, Using CA–Markov and ANN Models
Authors: Al-Hameedi Wafaa Majeed Mutashar , Chen Jie , Faichia Cheechouyang , Nath Biswajit , Al-Shaibah Bazel , Al-Aizari Ali
Published: July 2022

Understanding future landscape risk pattern change (FLRPC) scenarios will help people manage and utilize natural resources. In this study, we have selected a variety of landscape and anthropogenic factors as risk parameters for FLRPC assessment. Land use/cover change (LUCC) and land surface temperature (LST) are regarded as significant factors that have resulted in large-scale environmental changes. Result analysis of the previous LUCC from 1985 to 2020 showed that construction land and water body (WB) increased by 669.09 and 183.16 km2, respectively. The study continues to predict future LUCC from 2030 to 2050, in which the result has shown that a large land use conversion occurred during the future prediction period. In addition, the LST forecasting analysis illustrated that the previous LST maximum and minimum are 38 °C and 15 °C, which will be increased to 40.83 °C and 26.25 °C in the future, respectively. Finally, the study used the weighted overlay method for the FLRPC analysis, which applies analytic hierarchy process techniques for risk evaluation. The FLRPC result demonstrated that Baghdad City is in the low-risk and medium-risk to high-risk categories from 2020 to 2050, while AL and BL are in the very-high-risk categories. Meanwhile, WB and NG have always been safe, falling into the very-low-risk and low-risk categories from 2020 to 2050. Therefore, this study has successfully assessed the Baghdad metropolitan area and made recommendations for future urban development for a more safe, resilient, and sustainable development.
Impact of the Light-Duty Vehicles’ Storage and Travel Demand on the Sustainable Exploitation of Available Resources and Air Pollution Abatement
Authors: Machedon-Pisu Mihai , Borza Paul Nicolae
Published: July 2022

Light-duty vehicles are the predominant means of road transport. As the world population is expected to increase significantly in the following decades, so too will the car fleet. Due to the rising population, and the implicitly higher travel demand, the energy demand of cars will increase too, and this will put a strain on current resources, with negative effects on the supply chain, possibly leading to more pollution. Many of the current sustainable transport models and frameworks attempt to predict the vehicle market share for different powertrains and the resulting impact based on scenarios that cater to the automotive market and industry demands. At the same time, most neglect aspects regarding resources’ depletion and storage demand. In this sense, this study proposes a coherent testing methodology based on the ratio between demand and supply in order to address the limitations of these studies, mainly related to the sustainable exploitation of available resources, which are analyzed herein in correlation with the current predictions. A sensitivity analysis is provided in order to evaluate the uncertainty of utilized predictions. As a result of this analysis, two novel scenarios for assessing the evolution of the vehicle market share are proposed by the authors. When compared to similar scenarios, it was shown that the proposed scenarios lead to noticeable benefits in reducing dependency on the resources associated with a demand of energy and raw materials and in mitigating air pollution, including related costs.
Synergistic Effects between Carbonation and Cracks in the Hardened Cement Paste
Authors: Varzina Anna , Phung Quoc Tri , Perko Janez , Jacques Diederik , Maes Norbert , Cizer Özlem
Published: July 2022

This paper investigates the synergistic interaction between carbonation and microcracks in hardened cement pastes. Ordinary Portland cement pastes with three different water/cement ratios of 0.4, 0.5 and 0.6, hydrated for 28 days with crack apertures ranging from 10 to 150 μm were subjected to accelerated carbonation in a climate chamber that controls the targeted relative humidity (65 and 75%), CO2 concentration (0.3 vol.% and 1 vol.%) and temperature (20 °C). Mercury intrusion porosimetry, N2-adsorption and thermogravimetry analysis were used to quantify the carbonation-induced changes in pore size distribution, porosity and phase assemblages. Additionally, the changes in crack apertures were followed during carbonation. The results indicated that cracks within the investigated range facilitate the carbonation along the crack surface due to a faster gas diffusion process. The cracks with apertures below 50 μm increase the carbonation depth at least by a factor of two for all studied w/c and environmental conditions. We observed a constant increase in crack openings during carbonation and its linear relationship with the amount of precipitated calcium carbonate. Due to depletion of CH and decalcification of C-S-H close to the sample surface, the crack aperture increase becomes limited. Therefore, the crack apertures do not increase further after the material around the crack is carbonated. It was also found that the densification of the carbonated cement matrix coexists with large capillary pores (>50 nm) or cracks, especially for the low w/c samples. The shift in pore size distribution from about 100 nm towards smaller pores (4.5–50 nm) and a decrease in gel pore fractions after 28 days of carbonation also indicate a simultaneous calcium carbonate precipitation in meso/capillary pores and decalcification of C-S-H at the nanoscale.
Machine-Learning-Based System for the Detection of Entanglement in Dyeing and Finishing Processes
Authors: Wang Chien-Chih , Li Yu-Hsun
Published: July 2022

Many dyeing and finishing factories generally use old-fashioned dyeing machines. A key issue when using these machines is that the dyeing tank cannot detect entanglement problems, which may result in a lower dyeing quality. In this paper, imbalanced data with ensemble machine learning, such as Extreme Gradient Boosting (XGBoost) and random forest (RF), are integrated to predict the possible states of a dyeing machine, including normal operation, entanglement warning, and entanglement occurrence. To verify the results obtained using the proposed method, we worked with industry−academia collaborators. We collected 1,750,977 pieces of data from 1848 batches. The results obtained from the analysis show that after employing the Borderline synthetic minority oversampling technique and the Tomek link to deal with the data imbalance, combined with the model established by XGBoost, the prediction accuracy of the normal operation states, entanglement warning, and entanglement occurrence were 100%, 94%, and 96%, respectively. Finally, the proposed entanglement detection system was connected with the factory’s central control system using a web application programming interface and machine real-time operational parameter data. Thus, a real-time tangle anomaly warning and monitoring system was developed for the actual operating conditions.
Application of Remote-Sensing-Based Hydraulic Model and Hydrological Model in Flood Simulation
Authors: Xu Chaowei , Yang Jiashuai , Wang Lingyue
Published: July 2022

Floods are one of the main natural disaster threats to the safety of people’s lives and property. Flood hazards intensify as the global risk of flooding increases. The control of flood disasters on the basin scale has always been an urgent problem to be solved that is firmly associated with the sustainable development of water resources. As important nonengineering measures for flood simulation and flood control, the hydrological and hydraulic models have been widely applied in recent decades. In our study, on the basis of sufficient remote-sensing and hydrological data, a hydrological (Xin’anjiang (XAJ)) and a two-dimensional hydraulic (2D) model were constructed to simulate flood events and provide support for basin flood management. In the Chengcun basin, the two models were applied, and the model parameters were calibrated by the parameter estimation (PEST) automatic calibration algorithm in combination with the measured data of 10 typical flood events from 1990 to 1996. Results show that the two models performed well in the Chengcun basin. The average Nash–Sutcliffe efficiency (NSE), percentage error of peak discharge (PE), and percentage error of flood volume (RE) were 0.79, 16.55%, and 18.27%, respectively, for the XAJ model, and those values were 0.76, 12.83%, and 11.03% for 2D model. These results indicate that the models had high accuracy, and hydrological and hydraulic models both had good application performance in the Chengcun basin. The study can a provide decision-making basis and theoretical support for flood simulation, and the formulation of flood control and disaster mitigation measures in the basin.
Rural Residents’ Perceptions, Attitudes, and Environmentally Responsible Behaviors towards Garbage Exchange Supermarkets: An Example from Huangshan City in China
Authors: Lu Song , Zhou Zehui , Lu Yingfan
Published: July 2022

Rural residents not only produce rural garbage and participate in its disposal, but are also beneficiaries of a beautiful rural environment. The garbage exchange supermarket (where garbage is exchanged for goods) is a garbage disposal method that is employed in some villages in China. It is of great significance for the improvement of rural living environment and rural residents’ awareness of environmental protection. Thus, it is necessary to explore rural residents’ perceptions and behavior regarding garbage exchange supermarkets. Based on planned behavior theory and social exchange theory, this paper develops a model of rural residents’ perceptions, attitudes, and environmentally responsible behaviors regarding garbage exchange supermarkets. Then, using Huangshan City, China, as a case study, three villages, located in the upper, middle, and lower reaches of the Xin’an River were selected. Using a stratified sampling method, 324 questionnaires were obtained from residents. The developed model was verified by the method of structural equation modeling. Findings are as follows: (1) On the whole, residents have a strong and positive perception of the benefits of garbage exchange supermarkets, with an emphasis on its environmental advantages. (2) Regarding the cost dimension in perception, the focus is spent queuing for exchange on the time and sorting garbage at home. In general, residents are still willing to spend this time going to the supermarket to exchange. (3) Environmentally responsible behavior is divided into two dimensions: compliance and promotion-type environmentally responsible behavior—the former is more apparent among rural residents. (4) Residents’ perceptions of benefits positively affect their attitudes and satisfaction towards garbage exchange supermarkets. Cost perception has no significant effect on residents’ attitudes but has a negative correlation with satisfaction, satisfaction and attitude have positive correlations with environmentally responsible behavior, and satisfaction also positively affects residents’ attitudes.
Students’ Perceptions of Active Learning Classrooms from an Informal Learning Perspective: Building a Full-Time Sustainable Learning Environment in Higher Education
Authors: Peng Lei , Jin Shitao , Deng Yuan , Gong Yichen
Published: July 2022

Under the influence of education for sustainable development, active learning classrooms, as the new learning environment in higher education, have become increasingly diversified and flexible, with a greater emphasis on student experience and engagement. Most research on these learning environments is centered on formal learning analysis and discussion, whereas empirical research on the perception of informal learning in active learning classrooms outside of class time is lacking. Based on informal learning perceptions, this study explored the strengths and weaknesses of active learning classroom spatial environments using a mixed quantitative and qualitative research approach. Through a questionnaire survey of 154 students and one-on-one semi-structured interviews with 15 students, this study found that most students were satisfied with the informal learning experience in active learning classrooms, comfortable and flexible space perception and humanized learning support facilities in active learning classrooms were critical spatial factors influencing students’ informal learning, the private environment and positive learning atmosphere in active learning classrooms could promote students’ informal learning behaviors, and for active learning classrooms, better resource management could help them develop a better quality full-time learning environment. Based on these findings, this study makes recommendations for optimizing the environment design and management of active learning classrooms.
Analysis on the Evolution and Resilience of Ecological Network Structure in Wuhan Metropolitan Area
Authors: Xu Liquan , Zhang Zhentian , Tan Gangyi , Zhou Junqing , Wang Yang
Published: July 2022

With the accelerated urbanization and frequent occurrence of climate extremes, the regional ecosystem service level has ushered in a great challenge, and the resilience of the ecological network has gradually weakened, leading to lower ecological benefits and production levels. As a core ecologically sensitive area in the middle reaches of the Yangtze River, Wuhan metropolitan area has been expanding outward with rapid urbanization, crowding out surrounding arable and ecological land, and facing serious challenges to the sustainable development of the national space, while current cross-regional ecological protection measures need to be strengthened urgently, and exploring the structural resilience of its ecological network is of great significance to promote regional stability. In this study, Wuhan metropolitan area is taken as an example, and we explore the evolution and laws of ecological network structure from the perspective of network analysis by constructing ecological networks in Wuhan metropolitan area in 2000, 2010, and 2020. Firstly, we select regions from the ecological control line developed in China as ecological source sites, and also select multivariate data to supplement them. Then, the ecological network was established using the MCR model. Finally, network analysis was applied to discuss the evolution of network structure under multiple times and propose corresponding conservation strategies. The results show that (1) the major ecological resistance of Wuhan urban area has increased by 5.24% in 20 years. (2) The centrality and connectivity of the network nodes have increased over the 20-year period, and the overall structure of the network has stabilized and the resilience of the network has increased. (3) There is a strong link between changes in the network as a whole and local resilience. The results of the study will help analyze the relationship between the network as a whole and the region, and provide reference for optimizing the ecological network and constructing the systematic management of ecological security pattern.
A Novel Interval Energy-Forecasting Method for Sustainable Building Management Based on Deep Learning
Authors: Duan Yun
Published: July 2022

Energy conservation in buildings has increasingly become a hot issue for the Chinese government. Compared to deterministic load prediction, probabilistic load forecasting is more suitable for long-term planning and management of building energy consumption. In this study, we propose a probabilistic load-forecasting method for daily and weekly indoor load. The methodology is based on the long short-term memory (LSTM) model and penalized quantile regression (PQR). A comprehensive analysis for a time period of a year is conducted using the proposed method, and back propagation neural networks (BPNN), support vector machine (SVM), and random forest are applied as reference models. Point prediction as well as interval prediction are adopted to roundly test the prediction performance of the proposed model. Results show that LSTM-PQR has superior performance over the other three models and has improvements ranging from 6.4% to 20.9% for PICP compared with other models. This work indicates that the proposed method fits well with probabilistic load forecasting, which could promise to guide the management of building sustainability in a future carbon neutral scenario.
Factors That Affect Digital Innovation Sustainability among SMEs in the Middle East Region
Authors: Khrais Laith T. , Alghamdi Abdullah M.
Published: July 2022

Digital innovation in small and medium-sized enterprises (SMEs) has been studied extensively over the past quarter-century. The products, processes, and/or model innovation in businesses that are viewed as novel necessitate significant alterations from consumers and are represented in or facilitated by IT; this is what it means when digital innovation is mentioned. Nonetheless, despite the unique application of digital innovation in different organizations, the factors that lead to its success are still uncertain. Therefore, this study aims at evaluating the various factors that affect the digital innovation of SMEs in the Middle East region. This research used a descriptive research design in which primary data from the SME owners and employees were used to evaluate the research objectives. Descriptive statistics, such as frequencies and structural equation models conducted through SPSS, were used to evaluate the research objectives in showing how various factors such as the Internet of Things (IoT; physical objects and things with sensors, software, and other technological techniques integrated into them for the purpose of exchanging data and connecting with other systems and devices), digital platforms, and digital orientation have influenced digital innovation sustainability in SMEs. Results showed a positive and substantial impact on digital innovation sustainability as a result of the IoT, digital platforms, and digital orientation. In conclusion, the research shows that SMEs should use digital platforms, the IoT, and digital orientation to be digitally stable.
A Method to Assess Agroecosystem Resilience to Climate Variability
Authors: Cleves Alejandro , Youkhana Eva , Toro Javier
Published: July 2022

Agroecosystems are influenced by climate variability, which puts their productivity at risk. However, they tend to maintain a functional state through their resilience. The literature presents several methods for assessing general resilience, but for specific resilience to climate variability, there are very few methods. An index is proposed that assesses the resilience of agroecosystems to climate variability, based on approaches and indicators that consider the interrelationships of agricultural systems with the environment. The index is made up of a set of multidimensional indicators, which give weight to the role that these play in the resilience of an agroecosystem. As a result, decision-making is assisted in the attempt to adapt or modify components of a farm, technology, and the culture of farmers. This index conceptually introduces structural and linkage indicators that assess ecological connections within farms and between farms and their environment. To demonstrate the effectiveness of the method, an application was implemented to evaluate the resilience to climate variability of fifty-one farms, located in Colombia, dedicated to citrus production, and it was verified that the most resilient farms were those that have the best qualified indicators, as well as being the ones with the highest level of production and profitability.
Green Public Procurement in Mission-Orientated Innovation Systems: Leveraging Voluntary Standards to Improve Sustainability Performance of Municipalities
Authors: Rainville Anne
Published: July 2022

Mission-oriented approaches such as green public procurement (GPP) are emerging as popular solutions for governments to tackle contemporary sustainability challenges. Voluntary standards are instruments that can be used in GPP to drive innovation toward sustainability goals. However, there exists a lack of understanding of how to theoretically situate and practically execute GPP and voluntary standards within missions-oriented innovation systems (MIS). To address this research gap, this paper investigates how voluntary standards can be used to help formulate and achieve missions for sustainable urban development (SUD) at the municipal level, followed by what role green public procurement can play in this process. To do so, it establishes a first theoretical synthesis of GPP and MIS. Next, focusing on the Municipality of Amsterdam, it conducts an empirical investigation of 95 SUD projects, of which 55 were public tender projects (in which the municipality is the landowner) and 40 were non-public tender projects (in which a private entity is the landowner), supplemented by stakeholder interviews. Based on this, it (1) conceptualizes six sustainability ambitions as missions and examines each for their formulation in terms of targets and associated standards (problem-solution diagnosis), and (2) it maps the various actors engaged in the process of implementing these missions through SUD projects, defining their positions and interrelations within the MIS at the municipal level (structural analysis). Conclusions and reflections are made regarding the relationship between changing standards and regulations over time, the potential for GPP to increase progress toward missions via use of voluntary standards in public tenders. Until programmatic approaches to measuring progress toward missions are fully implemented, the presence of voluntary standards is suggested as a potential metric.
Dimensionless Analysis of the Effects of Junction Angle on the Gas-Liquid Two-Phase Flow Transition and the Scaling Law of the Microbubble Generation Characteristics in Y-Junctions
Authors: Han Yu , Xu Xiaofei , Liu Fengxia , Wei Wei , Liu Zhijun
Published: July 2022

Gas-liquid two-phase flow patterns and gas slug hydrodynamics were experimentally studied in three Y-junctions with different junction angles of 60°, 90° and 120°. Microbubbles were generated in the sodium alginate aqueous solution with the surfactant Tween20. Four main flow patterns were observed, i.e., stratified flow, annular flow, dispersed bubble flow and slug bubble flow. The formation mechanism of the bubble flow was explained by a force analysis, which was based on the dimensionless analysis regarding Capillary number, Weber number and Euler number. The transition criteria of the gas-liquid two-phase flow patterns was set up by these three dimensionless numbers. Additionally, the characteristics of the slug bubble were investigated, which made a scaling criterion for eliminating the influence of the angle factor become possible. A new scaling law (validity range within 2.88 < Re1 < 14.38, 0.0068 < We1 < 0.1723) was proposed to predict the bubble size and it showed a good agreement with the experimental results.
On the Two Categories of Modules
Authors: Popescu Marcela , Popescu Paul
Published: July 2022

A new category equivalence is proved in this paper, involving the two distinct categories of modules, the covariant and the contravariant, respectively, released by Higgins and Mackenzie. The equivalence of the two categories is given when restricting to almost finitely generated projective modules and their allowed morphisms, defined in the paper. The equivalence is expressed by using generators. In particular, we obtain the well-known equivalence of the two categories of projective finitely generated modules; thus, our main result extends this classical one.
Detection of Key Points in Mice at Different Scales via Convolutional Neural Network
Authors: Xu Zhengyang , Liu Ruiqing , Wang Zhizhong , Wang Songwei , Zhu Juncai
Published: July 2022

In this work, we propose a symmetry approach and design a convolutional neural network for mouse pose estimation under scale variation. The backbone adopts the UNet structure, uses the residual network to extract features, and adds the ASPP module into the appropriate residual units to expand the perceptual field, and uses the deep and shallow feature fusion to fuse and process the features at multiple scales to capture the various spatial relationships related to body parts to improve the recognition accuracy of the model. Finally, a set of prediction results based on heat map and coordinate offset is generated. We used our own built mouse dataset and obtained state-of-the-art results on the dataset.
Eady Baroclinic Instability of a Circular Vortex
Authors: Vic Armand , Carton Xavier , Gula Jonathan
Published: July 2022

The stability of two superposed buoyancy vortices is studied linearly in a two-level Surface Quasi-Geostrophic (SQG) model. The basic flow is chosen as two circular vortices with uniform buoyancy, coaxial, and the same radius. A perturbation with a single angular mode is added to this mean flow. The SQG equations linearized in perturbation around this basic flow form a two-dimensional ODE for which the normal and singular mode solutions are numerically computed. The instability of these two vortices depends on several parameters. The parameters varied here are: the vertical distance between the two levels and the two values of the vortex buoyancies (called vortex intensity hereafter); the other parameters remain fixed. For normal modes, the system is stable if the levels are sufficiently far from each other vertically, to prevent vertical interactions of the buoyancy patches. Stability is also reached if the layers are close to each other, but if the vortices have very different intensities, again preventing the resonance of Rossby waves around their contours. The system is unstable if the vortex intensities are similar and if the two levels are close to each other. The growth rates of the normal modes increase with the angular wave-number, also corresponding to shorter vertical distances. The growth rates of the singular modes depend more on the distance between the levels than on the ratio of the vortex intensities, at a short time; as expected, they converge towards the growth rates of the normal modes. This study remaining linear does not predict the final evolution of such unstable vortices. This nonlinear evolution will be studied in a sequel of this work.
Mortality Prediction Analysis among COVID-19 Inpatients Using Clinical Variables and Deep Learning Chest Radiography Imaging Features
Authors: Nguyen Xuan V. , Dikici Engin , Candemir Sema , Ball Robyn L. , Prevedello Luciano M.
Published: July 2022

The emergence of the COVID-19 pandemic over a relatively brief interval illustrates the need for rapid data-driven approaches to facilitate clinical decision making. We examined a machine learning process to predict inpatient mortality among COVID-19 patients using clinical and chest radiographic data. Modeling was performed with a de-identified dataset of encounters prior to widespread vaccine availability. Non-imaging predictors included demographics, pre-admission clinical history, and past medical history variables. Imaging features were extracted from chest radiographs by applying a deep convolutional neural network with transfer learning. A multi-layer perceptron combining 64 deep learning features from chest radiographs with 98 patient clinical features was trained to predict mortality. The Local Interpretable Model-Agnostic Explanations (LIME) method was used to explain model predictions. Non-imaging data alone predicted mortality with an ROC-AUC of 0.87 ± 0.03 (mean ± SD), while the addition of imaging data improved prediction slightly (ROC-AUC: 0.91 ± 0.02). The application of LIME to the combined imaging and clinical model found HbA1c values to contribute the most to model prediction (17.1 ± 1.7%), while imaging contributed 8.8 ± 2.8%. Age, gender, and BMI contributed 8.7%, 8.2%, and 7.1%, respectively. Our findings demonstrate a viable explainable AI approach to quantify the contributions of imaging and clinical data to COVID mortality predictions.
Verification of Usability of Medical Image Data Using Projective Photography for Designing Clothing for Breast Cancer Patients
Authors: Kim Youn Joo
Published: July 2022

Manufacturing a customized mastectomy bra, using medical images obtained for breast cancer treatment, could be suggested as an alternative instead of the anthropometric method. However, the breast shape of a medical image is deformed from the anthropometric method as the measurement posture is different between the anthropometric method for making clothes and the medical image. As a breast consists of adipose tissues and a few muscles without bones, there is a possibility that a bra can be manufactured if the volume is constant. Therefore, a hypothesis was established that the volume of the breast would be constant, even if the measurement methods were different. As a result of the comparison of 3D-SIM and PPM by MRI, 18 items could be measured simultaneously. Nine items showed differences according to the measurement method. The next step in the case of 3D-SIM was calculating the volume by separating the breast shape into a cone and a hemispherical shape; in the case of MRI, an ellipsoidal volume formula was applied. A t-test was performed on the results obtained, showing no significant difference. Therefore, it was proven that the volume of the breast does not change despite the difference in the measurement and the measurement method.
Improved Therapy of B-Cell Non-Hodgkin Lymphoma by Obinutuzumab-Dianthin Conjugates in Combination with the Endosomal Escape Enhancer SO1861
Authors: Panjideh Hossein , Niesler Nicole , Weng Alexander , Fuchs Hendrik
Published: July 2022

Immunotoxins do not only bind to cancer-specific receptors to mediate the elimination of tumor cells through the innate immune system, but also increase target cytotoxicity by the intrinsic toxin activity. The plant glycoside SO1861 was previously reported to enhance the endolysosomal escape of antibody-toxin conjugates in non-hematopoietic cells, thus increasing their cytotoxicity manifold. Here we tested this technology for the first time in a lymphoma in vivo model. First, the therapeutic CD20 antibody obinutuzumab was chemically conjugated to the ribosome-inactivating protein dianthin. The cytotoxicity of obinutuzumab-dianthin (ObiDi) was evaluated on human B-lymphocyte Burkitt’s lymphoma Raji cells and compared to human T-cell leukemia off-target Jurkat cells. When tested in combination with SO1861, the cytotoxicity for target cells was 131-fold greater than for off-target cells. In vivo imaging in a xenograft model of B-cell lymphoma in mice revealed that ObiDi/SO1861 efficiently prevents tumor growth (51.4% response rate) compared to the monotherapy with ObiDi (25.9%) and non-conjugated obinutuzumab (20.7%). The reduction of tumor volume and overall survival was also improved. Taken together, our results substantially contribute to the development of a combination therapy with SO1861 as a platform technology to enhance the efficacy of therapeutic antibody-toxin conjugates in lymphoma and leukemia.
Correction: Yuhana et al. Rickettsial Infections Are Neglected Causes of Acute Febrile Illness in Teluk Intan, Peninsular Malaysia. Trop. Med. Infect. Dis. 2022, 7, 77
Authors: Yuhana Muhamad Yazli , Hanboonkunupakarn Borimas , Tanganuchitcharnchai Ampai , Sujariyakul Pimpan , Sonthayanon Piengchan , Chotivanich Kesinee , Pukrittayakamee Sasithon , Blacksell Stuart D. , Paris Daniel H.
Published: July 2022

The authors wish to make the following correction to this paper [...]
An Updated Review on SARS-CoV-2 Infection in Animals
Authors: Cui Shujuan , Liu Yimeng , Zhao Jiachen , Peng Xiaomin , Lu Guilan , Shi Weixian , Pan Yang , Zhang Daitao , Yang Peng , Wang Quanyi
Published: July 2022

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has lasted for two years and caused millions of infections and deaths in humans. Although the origin of SARS-CoV-2 infection in humans remains unknown, infection in animals has been frequently reported in varieties of animals all over the world. Both experimental and natural infections of SARS-CoV-2 in different animal species provide useful information on viral host range and pathogenicity. As the pandemic continues to evolve, SARS-CoV-2 infection in animals will be expanding. In this review, we summarized SARS-CoV-2 testing and infection in animals as well as SARS-CoV-2 strains and transmission in animals. Current data showed that at least 18 different animal species tested positive for SARS-CoV-2. These 18 animal species belong to pet, captive, farmed, and wild animals. Fifteen of the eighteen animal species were known to be positive for the Delta variant and ten animal species were infected with two different types of variants. Human-to-animal, animal-to-animal, and animal-to-human transmission events were suggested in different outbreaks involved in animal infection with SARS-CoV-2. Continued testing, immunization, and surveillance are warranted.