bluuebunny/crossref_metadata_2025 huggingface dataset:
Increased Stress Levels in Caged Honeybee (Apis mellifera) (Hymenoptera: Apidae) Workers
Authors: Lattorff H. Michael G.
Published: September 2022

Honeybees, Apis mellifera, usually live in large colonies consisting of thousands of individuals. Within the colony, workers interact with their social environment frequently. The large workforce, division of labour, and other features may promote the ecological success of honeybees. For decades, artificial mini colonies in cages within the laboratory have become the gold standard, especially in experiments related to toxicology, effects of pesticides and pathogens. Experiments using caged bees and full-sized colonies yielded contradictory results. Here, the effect of cage experiments on the stress level of individual bees is analysed. Two different stress response were targeted, the heat shock response and the mobilization of energetic resources. While no differences were found for varying group sizes of bees, very strong effects emerged by comparing caged workers with bees from natural colonies. Caged workers showed increased levels of hsp expression and reduced haemolymph titres for trehalose, the energy storage sugar. These results reveal that the lack of the social environment (e.g., lack of queen, lack of sufficient group size) induce stress in caged bees, which might act synergistically when bees are challenged by additional stressors (e.g., pesticides, pathogens) resulting in higher mortality than observed under field conditions.
The Uptake of Container Deposit Schemes: A Case Study in Perth, Western Australia
Authors: O’Dwyer Ciara , Zaman Atiq , Breadsell Jessica K.
Published: September 2022

The environmental impacts of single-use plastics are increasing worldwide due to the continual rise in consumption and a lack of appropriate collection and management systems in many countries. Various programs, known as container deposit schemes (CDS), have been implemented to improve the collection and recycling of single-use plastic containers. This research investigated the drivers and barriers of CDS uptake in Perth, Western Australia. The study surveyed over 400 individuals within Perth regarding their engagement with and usage of the local CDS, known as “Containers for Change”, which was implemented in October 2020. This research found that there is a high level of public awareness (98%) of the scheme, and it has been widely adopted across Perth within the first year of its implementation; however, logistical challenges and container eligibility were found to be key barriers to the uptake of the scheme. It was noted that there is some skepticism toward waste management practices in Australia, and knowledge of the benefits of CDS appears to be lacking. Recommendations for improving the functionality and uptake of the Containers for Change scheme are to increase the range of bottles accepted within the scheme, create more accessible and convenient drop-off locations for containers, and improve/increase education regarding the benefits of the scheme. This research is limited by a response rate that was dominated by individuals living in stand-alone houses; however, with the majority of Perth residents living in stand-alone houses, this research remains valuable. There is scope for further research into skepticism regarding waste management practices in Australia, as well as the logistical challenges of CDS uptake by apartment dwellers.
The Effect of Product Complexity on Servitization and Deservitization: A Multi-Country Quantitative Analysis
Authors: Prester Jasna , Bikfalvi Andrea , Palčič Iztok
Published: September 2022

Servitization is often based on technology, with the producer not selling products but rather offering product-related services. While servitization had been steadily gaining interest until relatively recently, a new trend called deservitization, the outsourcing of service provision, has seen a slow uptake in the scientific literature. This work analyses why servitization is not always beneficial. We analyze the effect of product complexity on servitization and deservitization in three Southern European countries. Due to high competition and knowledge leaking, manufacturers of complex products tend to servitize with their own resources, thus avoiding deservitization or outsourcing of service provision. The analysis is performed using two-step OLS regression. The results confirm that the hypotheses and the model are significant and that manufacturers of simple products tend to deservitize, while manufacturers of complex products tend to servitize. Managerial implications refer to alternatives as to when to enter the servitization arena and when it is more beneficial to deservitize.
Sustainable Careers and Flourishing Organizations
Authors: Manuti Amelia , Giancaspro Maria Luisa , Callea Antonino
Published: September 2022

The idea of this Special Issue emerged within the last two years that (exclusively focusing on the impact of the pandemic on working life) will pass to history as one of the most complex times for individuals and organizations [...]
The Effects of True Triaxial Loading and Unloading Rates on the Damage Mechanical Properties of Sandstone
Authors: Wang Man , Du Weihang , Wang Yingwei , Li Xinjian , Qiu Liming , Yu Beichen , Niu Zehua , Zhang Dongming
Published: September 2022

Coal is the main energy source in China. In the process of coal resource mining, the surrounding rock of roadways is often in the complex stress environment of “three heights and one disturbance”. At the same time, rocks in the stratum are often in a three-way unequal pressure state under the action of geological structure, and conventional rock mechanics tests cannot study the mechanical properties of rocks under actual stress conditions; thus, this is based on the self-developed true triaxial multifunctional fluid–structure coupling test system to study the damage mechanical Properties of Sandstone. The results are shown as follows: With an increase in loading rate, the peak damage Dcr of sandstone decreases, but the initial damage Da increases in the elastic stage, and the brittleness of sandstone weakens. With the increase in the unloading rate, Dcr increases, but Da decreases in the elastic stage, and the sandstone brittleness increases first, then decreases. In addition, the peak maximum principal strain ε1maxfirst decreases rapidly and then slowly; the peak minimum principal strain ε3max increases first, then decreases slowly, and increases slowly; the peak intermediate principal strain ε2max decreases slowly; and the peak volume strain εvmax increases rapidly first and then slowly with increases in the loading rate. With an increase in the unloading rate, ε1max increases rapidly first, then decreases slowly, then increases rapidly and finally increases slowly; ε3max first decreases slowly, then increases slowly, and finally decreases slowly; and ε2max increases slowly then decreases slowly. εvmax decreases rapidly first and then increases slowly with increasing loading rate.
The State-of-the-Art Progress on the Forms and Modes of Hydrogen and Ammonia Energy Utilization in Road Transportation
Authors: Shi Ruifeng , Chen Xiaoxi , Qin Jiajun , Wu Ping , Jia Limin
Published: September 2022

The crisscross progress of transportation and energy carries the migrating track of human society development and the evolution of civilization, among which the decarbonization strategy is a key issue. Traffic carbon emissions account for 16.2% of total energy carbon emissions, while road traffic carbon emissions account for 11.8% of total energy carbon emissions. Therefore, road traffic is a vital battlefield in attaining the goal of decarbonization. Employing clean energy as an alternative fuel is of great significance to the transformation of the energy consumption structure in road transportation. Hydrogen and ammonia are renewable energy with the characteristics of being widely distributed and clean. Both exist naturally in nature, and the products of complete combustion are substances (water and nitrogen) that do not pollute the atmosphere. Because it can promote agricultural production, ammonia has a long history in human society. Both have the potential to replace traditional fossil fuel energy. An overview of the advantages of hydrogen and ammonia, as well as their development in different countries such as the United States, the European Union, Japan, and other major development regions is presented in this paper. Related research topics of hydrogen and ammonia’s production, storage and transferring technology have also been analyzed and collated to stimulate the energy production chain for road transportation. The current cost of green hydrogen is between $2.70–$8.80 globally, which is expected to approach $2–$6 by 2030. Furthermore, the technical development of hydrogen and ammonia as a fuel for engines and fuel cells in road transportation is compared in detail, and the tests, practical applications and commercial popularization of these technologies are summarized, respectively. Opportunities and challenges coexist in the era of the renewable energy. Based on the characteristics and development track of hydrogen and ammonia, the joint development of these two types of energy is meant to be imperative. The collaborative development mode of hydrogen and ammonia, together with the obstacles to their development of them are both compared and discussed. Finally, referring to the efforts and experiences of different countries in promoting hydrogen and ammonia in road transportation, corresponding constructive suggestions have been put forward for reference. At the end of the paper, a framework diagram of hydrogen and ammonia industry chains is provided, and the mutual promotion development relationship of the two energy sources is systematically summarized.
The Modeling and Simplification of a Thermal Model of a Planar Transformer Based on Internal Power Loss
Authors: Shen Zhan , Xu Bingxin , Liu Chenglei , Hu Cungang , Liu Bi , Xu Zhike , Jin Long , Chen Wu
Published: September 2022

With the development of high-performance wide-band-gap devices and increasing converter frequency, planar transformers are widely used in high-frequency and high-power-density power conversions. Due to the skin effect and proximity effect, accurate thermal analysis and a simplified thermal model of planar transformers are needed for quick thermal verification as well as system design. This paper proposes two thermal simplification models based on the planar transformer’s thermal impedance network. The internal power loss and thermal coupling between each component are first analyzed. Then, based on thermal radiation theory, the simplified thermal model of the planar transformer is presented. It only requires the input of the total power loss of the planar transformer to calculate the temperature rise, and it does not need the power loss of each component. Finally, the simulation and experimental verification are carried out on a MHz prototype.
Terminal Cooling Load Forecasting Model Based on Particle Swarm Optimization
Authors: Song Lifei , Gao Weijun , Yang Yongwen , Zhang Liting , Li Qifen , Dong Ziwen
Published: September 2022

With the development of the civil aviation industry, the passenger throughput of airports has increased explosively, and they need to carry a large number of passengers every day and maintain operations for a long time. These factors cause the large space buildings in the airport to have higher energy consumption than ordinary buildings and have energy-saving potential. In practical engineering, there are problems such as low accuracy of prediction results due to inability to provide accurate building parameters and design parameters, some scholars oversimplify the large space building load forecasting model, and the prediction results have no reference significance. Therefore, establishing a load forecasting model that is closer to the actual operating characteristics and laws of large space buildings has become a research difficulty. This paper analyzes and compares the building and load characteristics of airport large space buildings, which are different from general large space buildings. The factors influencing large space architecture are divided into time characteristics and space characteristics, and the influencing reasons and characteristics of each factor are discussed. The Pearson analysis method is used to eliminate the influence parameters that have a very low connection with the cooling load, and then the historical data that affect the cooling load parameters are input. The MATLAB software is used to select a variety of neural network models for training and prediction. On this basis, the particle swarm optimization algorithm is used to optimize the prediction model. The results show that the prediction effect of the gated recurrent neural network based on particle swarm optimization algorithm is the best, the average absolute percentage error is only 0.7%, and the prediction accuracy is high.
Method for the Automated Inspection of the Surfaces of Photovoltaic Modules
Authors: Kuznetsov Pavel , Kotelnikov Dmitry , Yuferev Leonid , Panchenko Vladimir , Bolshev Vadim , Jasiński Marek , Flah Aymen
Published: September 2022

One of the most important conditions for the efficient operation of solar power plants with a large installed capacity is to ensure the systematic monitoring of the surface condition of the photovoltaic modules. This procedure is aimed at the timely detection of external damage to the modules, as well as their partial shading. The implementation of these measures solely through visual inspection by the maintenance personnel of the power plant requires significant labor intensity due to the large areas of the generation fields and the operating conditions. Authors propose an approach aimed at increasing the energy efficiency of high-power solar power plants by automating the inspection procedures of the surfaces of photovoltaic modules. The solution is based on the use of an unmanned aerial vehicle with a payload capable of video and geospatial data recording. To perform the procedures for detecting problem modules, it is proposed to use “object-detection” technology, which uses neural network classification methods characterized by high adaptability to various image parameters. The results of testing the technology showed that the use of a neural network based on the R-CNN architecture with the learning algorithm—Inception v2 (COCO)—allows detecting problematic photovoltaic modules with an accuracy of more than 95% on a clear day.
Interaction of Soil Nutrients and Arsenic (As) in Paddy Soil in a Long-Term Fertility Experiment
Authors: Qaswar Muhammad , Yiren Liu , Liu Kailou , Zhenzhen Lv , Hongqian Hou , Lan Xianjin , Jianhua Ji , Ahmed Waqas , Lisheng Liu , Mouazen Abdul M. , Huimin Zhang
Published: September 2022

In this study, we examined the interaction between arsenic (As) and nutrients in paddy soil which received pig manure and chemical fertilizers for 36 years (since 1984). The treatments consisted of: CK (without fertilization); NPK (chemical nitrogen, phosphorus and potassium fertilization); NPK30%M (70% NPK plus 30% manure); NPK50%M (50% NPK plus 50% manure); and NPK70%M (30% NPK plus 70% manure). The combined application of pig manure and chemical fertilizer improved grain yield, soil pH and nutrient levels compared to chemical fertilizer application treatment. In comparison to CK, grain yield increased by 55.9%, 75.0%, 74.9% and 71.9%, respectively under the NPK, NPK30%M, NPK50%M and NPK70%M treatments. Soil As concentration increased by increasing the amount of manure input, and the highest concentration of As was 0.64 mg kg−1 found in the NPK70%M treatment. Increasing the rate of manure application decreased the As bioaccumulation coefficient (BAC) for rice grain. SOC, total N and P showed a positive correlation with the soil-available As concentration and negative correlation with BAC. Furthermore, the partial least square model (PLS) showed that the soil pH and SOC were the most influencing factors on BAC among the different properties of soil, which explained the 75.4% and 17.6% of total variations, respectively. This study concluded that the addition of pig manure together with chemical fertilizers can increase crop production by supplying essential nutrients, but the concentration of As in manure should be monitored to reduce soil and food contamination.
360° Retail Business Analytics by Adopting Hybrid Machine Learning and a Business Intelligence Approach
Authors: Alqhatani Abdulmajeed , Ashraf Muhammad Shoaib , Ferzund Javed , Shaf Ahmad , Abosaq Hamad Ali , Rahman Saifur , Irfan Muhammad , Alqhtani Samar M.
Published: September 2022

Business owners and managers need strategic information to plan and execute their decisions regarding business operations. They work in a cyclic plan of execution and evaluation. In order to run this cycle smoothly, they need a mechanism that should access the entire business performance. The sole purpose of this study is to assist them through applied research framework-based analysis to obtain effective results. The backbone of the purposed framework is a hybrid mechanism that comprises business intelligence (BI) and machine learning (ML) to support 360-degree organization-wide analysis. BI modeling gives descriptive and diagnostic analysis via interactive reports with quick ad hoc analysis which can be performed by executives and managers. ML modeling predicts the performance and highlights the potential customers, products, and time intervals. The whole mechanism is resource-efficient and automated once it binds with the operational data pipeline and presented results in a highly efficient manner. Data analysis is far more efficient when it is applied to the right data at the right time and presents the insights to the right stakeholders in a friendly, usable environment. The results are beneficial to viewing the past, current, and future performance with self-explanatory graphical interpretation. In the proposed system, a clear performance view is possible by utilizing the sales transaction data. By exploring the hidden patterns of sales facts, the impact of the business dimensions is evaluated and presented on a dynamically filtered dashboard.
Determination of Green Building Awareness: A Study in Turkey
Authors: Keleş Abdullah Emre , Önen Ecem , Górecki Jarosław
Published: September 2022

The building sector is the world’s most significant energy consumer. In addition to that, water consumption and increased waste are some of the most significant issues. Owing to the need to find a solution to this problem, the concept of green buildings has emerged. Green buildings are building types that consume less energy and are constructed with recyclable materials, in harmony with nature. The adoption of the concept of green building in societies is very important in this regard. This study aimed to understand the awareness level of people about green buildings. Its scope was to determine the level of awareness of people living in buildings with and without an energy identity certificate in Adana. The results were created in Microsoft Excel, and the survey questions were measured using SPSS. Data analysis was performed by the WEKA tool using the association rule mining method. According to the result, most of the participants did not have sufficient information about the subjects. The results show that nowadays, most people do not understand this building type and what it means to the next generation.
Soil Liquefaction Prediction Based on Bayesian Optimization and Support Vector Machines
Authors: Zhang Xuesong , He Biao , Sabri Mohanad Muayad Sabri , Al-Bahrani Mohammed , Ulrikh Dmitrii Vladimirovich
Published: September 2022

Liquefaction has been responsible for several earthquake-related hazards in the past. An earthquake may cause liquefaction in saturated granular soils, which might lead to massive consequences. The ability to accurately anticipate soil liquefaction potential is thus critical, particularly in the context of civil engineering project planning. Support vector machines (SVMs) and Bayesian optimization (BO), a well-known optimization method, were used in this work to accurately forecast soil liquefaction potential. Before the development of the BOSVM model, an evolutionary random forest (ERF) model was used for input selection. From among the nine candidate inputs, the ERF selected six, including water table, effective vertical stress, peak acceleration at the ground surface, measured CPT tip resistance, cyclic stress ratio (CSR), and mean grain size, as the most important ones to predict the soil liquefaction. After the BOSVM model was developed using the six selected inputs, the performance of this model was evaluated using renowned performance criteria, including accuracy (%), receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC). In addition, the performance of this model was compared with a standard SVM model and other machine learning models. The results of the BOSVM model showed that this model outperformed other models. The BOSVM model achieved an accuracy of 96.4% and 95.8% and an AUC of 0.93 and 0.98 for the training and testing phases, respectively. Our research suggests that BOSVM is a viable alternative to conventional soil liquefaction prediction methods. In addition, the findings of this research show that the BO method is successful in training the SVM model.
Prey Identification of the Little Tern, Sternula albifrons (Pallas, 1764), by Applying DNA Barcoding to Fecal Materials
Authors: Jo Hyunbin , Jang Ji-Deok , Jeong Keon-Young , Gim Jeong-An , Joo Gea-Jae , Jeong Kwang-Seuk
Published: September 2022

This study describes the prey DNA fragments found in the feces of a migratory bird species, the little tern, Sternula albifrons (Pallas, 1764), based on a DNA barcoding approach. This species is found in Nakdong Estuary, South Korea, and is a species designated as ‘Least Concern’ (IUCN Red List). Prey identification is a central issue of population conservation, and we applied DNA barcoding (using cytochrome oxidase I; COI) to fecal materials from little tern individuals. We successfully identified prey consumed by little tern individuals. All prey items comprised one phylum including three classes, six orders, and eight families based on a robust dual certification scheme (combined analysis of BLASTn searches and phylogenetic tree construction). Even though the success of identification was largely dependent on the degree of completion of the database in the genebank or BOLD systems, an increased resolution of prey identification to species level is important in predator–prey research. The current study used a small number of fecal samples to evaluate the applicability of the COI barcoding region to avifaunal feces, and more fecal samples are expected to convey increased information that can be used to infer the range of the prey species of little terns.
A Profit Framework Model for Digital Platforms Based on Value Sharing and Resource Complementarity
Authors: Deng Tianyu , Qiao Limeng , Yao Xun , Chen Shuangying , Tang Xiaowo
Published: September 2022

With the advent of the smart economy, Chinese digital platform companies have begun the process of digital innovation. The sudden outbreak of the COVID-19 epidemic in early 2020 has added a strong impulse to the acceleration of this process, highlighting the unique characteristics of the platform economy in resource allocation. Although digital platforms have already entered people’s daily lives, the profit mechanism of digital platforms remains a black box to be cracked for the industry. The main contribution of this paper is to propose a framework model for the profit mechanism of digital platforms, which to a certain extent solves the problems essential to the digital realm faced by many traditional enterprises in the Internet age—knowing that the profit theory of traditional monopolies is not suitable for the rapidly changing internet economy, but that most of the time people still must use it. In this new profit framework, we first use the symbiotic logic of value sharing to explain the underlying logic of platform profitability; secondly, from the perspective of resource complementarity, we find that the key to digital platform companies’ profitability lies in the symbiotic synergy between platform companies and massive userbases; lastly, our study finds that the profit condition of platform enterprises is digital capability, not system possession. This article will analyze the bottom layer of the digital economy and, by identifying the various drawbacks of the traditional industrial economic monopoly theory, propose three key factors for the profitability of platform companies in the digital age: flexible strategy, digital capabilities, and symbiotic synergy capabilities. On this basis, a theoretical model of the profit of a digital platform is constructed. Research shows that the hybrid structure of digital platforms and the need for external diversification together lead to a platform’s resilience strategy. The realization process of the platform’s strategic flexibility and the process of consumers obtaining the residual value will lead to an explosion in network effects, causing the platform and users to complete value co-creation and realize value sharing. The implementation of a flexible platform strategy also promotes the further development of a differentiation strategy and a more-refined division of labor for manufacturers, lowers the barriers-to-entry in the industry, and enables the platform and the manufacturers to realize value co-creation. On the one hand, platform enterprises can obtain greater market performance; on the other hand, users’ personalized needs can be more satisfied.
The Measurement of Shear Characteristics of Paddy Soil in Poyang Lake Area
Authors: Xue Long , Li Lan , Zeng Jianhui , Huang Bohan , Zeng Yuqi , Liu Muhua , Li Jing
Published: September 2022

Understanding the shear characteristics of paddy fields is of great significance for the design of high-trafficability paddy wheels and to improve the trafficability of the tiller in paddy fields. Taking the paddy soil in Poyang Lake area of Jiangxi Province as the research object, a simple, self-designed bevameter was constructed to measure the apparent cohesion c and apparent internal friction angle φ of paddy soil with water content of 37% by weight using an annular shear plate. The effects of different shear speeds, shear grouser heights, and shear plate diameters on the measured c and φ were investigated. The measured values of c and φ were 1.89–2.35 kPa and 10.2–11.4°(deg), respectively. With the increase in shear speed, shear plate diameter, and grouser height, the value of c increased. Shear plate diameter and shear speed had small effect on c, whose change rate did not exceed 7.8%. However, shear grouser height had a greater influence on c, and the measured c increased by 24.5%. The influence of the three factors on φ followed the order: shear speed > shear plate diameter > shear grouser height, but the variation in φ did not exceed 1.2°(deg). The optimal operational conditions were: shear plate diameter of 250 mm with inner diameter of 150 mm, shear grouser height of 10 mm, with a shear speed of π/120 rad/s, and the apparent cohesion and apparent internal friction angle are 1887.8 pa and 11.06° (deg), respectively.
Introducing the Special Issue on Urban Sustainability Futures
Authors: Thornbush Mary J.
Published: September 2022

The city represents a focus of study that could be utilized to compile sustainability research [...]
Nitrogen Influence to the Independent Invasion and the Co-Invasion of Solidago canadensis and Conyza canadensis via Intensified Allelopathy
Authors: Zhou Jialong , Xu Zhelun , Zhong Shanshan , Yu Youli , Xu Zhongyi , Du Daolin , Wang Congyan
Published: September 2022

The allelopathy of alien plants is critical to their successful invasion. In nature, two alien plants can co-invade the same habitat. Changes in the forms of nitrogen may have the potential to alter the invasion process of alien plants by causing alterations in their allelopathy. This study aimed to evaluate the individual and combined allelopathy of two alien plants from the Asteraceae family, Solidago canadensis L. and Conyza canadensis (L.) Cronq. This study examined the effects of aqueous leaf extracts of the two alien plants with different nitrogen forms (NO3−N, NH4−N, and CO(NH2)2−N, and the mixed nitrogen forms at a 1:1:1 ratio) on the seed germination and seedling growth of the horticultural Asteraceae species Lactuca sativa L. using a germination bioassay. The allelopathy of the two alien plants significantly reduced the seed germination and seedling growth of L. sativa. Extracts from S. canadensis produced stronger allelopathy on the seed germination and seedling growth of L. sativa compared with those from C. canadensis. The mixture of extracts from the two alien plants produced an antagonistic effect when compared with the effects of extracts from each plant species. The addition of nitrogen intensified the allelopathy of the two alien plants on the seed germination and seedling growth of L. sativa. The degree of influence of nitrogen on the individual and combined allelopathy of the two alien plants was similar. Thus, nitrogen deposition may facilitate the independent invasion and co-invasion of the two alien plants via intensified allelopathy.
How Environmental Regulation Affects Green Investment of Heavily Polluting Enterprises: Evidence from Steel and Chemical Industries in China
Authors: Du Mo , Chai Shanglei , Li Shu , Sun Zejing
Published: September 2022

Environmental protection is the top priority in the development process of all countries in the world, which directly affects public health. In response to growing environmental challenges, the government is implementing increasingly stringent industry supervision and environmental regulations. However, the impact of environmental regulation on investment has not formed a unified conclusion, and few studies have discussed this effect at the micro-enterprise level. This paper uses multiple regression analyses to investigate the effect of environmental regulation on green investments of heavily polluting enterprises in China. Using the data of listed companies in the steel and chemical industries of the Shanghai Stock Exchange and Shenzhen Stock Exchange, we find that the increasing intensity of government environmental regulation will inhibit green investments of heavily polluting enterprises. This paper further classifies the property rights of these enterprises and discusses the role of regional environmental quality. From the perspective of property rights, increased government environmental supervision will inhibit green investments of state-owned enterprises (SOEs) and promote green investments of non-state-owned enterprises (NSOEs). From the perspective of the environmental quality of the region where the company is located, government environmental regulation will inhibit green investments of heavily polluting companies, regardless of the regional environmental quality. This paper not only provides new empirical evidence about the steel and chemical industries for Porter’s hypothesis, but also compensates for the lack of research on the impact of environmental regulation on corporate green investment at the micro-level.
Groundwater Resources in a Complex Karst Environment Involved by Wind Power Farm Construction
Authors: Valente Alessio , Catani Vittorio , Esposito Libera , Leone Guido , Pagnozzi Mauro , Fiorillo Francesco
Published: September 2022

The need to produce energy from clean energy sources has caused public administrations and private companies to look for suitable places. The windiness detected in the eastern area of the Matese karst massif (southern Italy) has favored the construction of wind farms to produce electricity from clean energy sources. During the installation of the first wind turbines, some alterations in the supply of drinking water, fed by the springs of this area, were attributed by the population to this installation. Therefore, in order to assess whether there has been an impact produced by the wind farms on the quality of groundwater, a detailed hydrogeological study was developed. Karst hydrogeological features of the area were mapped, focusing on endorheic areas, sinkholes and karst springs. Artificial tracer tests were then carried out to investigate groundwater flow circulation and connection between surface karst landforms and springs. Chemical and physical characteristics of the groundwater were monitored during the construction of the wind farms and, for the following months, by infield measurements and laboratory analysis of spring water samples. This study highlights that wind farms mainly develop along the boundary of endorheic areas, which are important recharge zones for groundwater resources, and are directly connected to the major karst springs through sinkholes and a dense network of karst conduits. The results of the monitoring did not reveal any anomalies in the quality of the water and, therefore, any alterations cannot be attributed to the wind farms. Our investigation appears useful for a better understanding of the possible actual and future effects of the wind farms on both groundwater circulation and spring water quality in this karst area.
Risk Assessment of Water Inrush from Coal Seam Roof Based on Combination Weighting-Set Pair Analysis
Authors: Xie Daolei , Han Jing , Zhang Huide , Wang Kai , Du Zhongwen , Miao Tianyu
Published: September 2022

When exploiting Jurassic-era coal resources in Northwest China, there are risks of water inrush and sand burst disasters from coal seam roofs. To improve the safety of coal mining, it is imperative to accurately and objectively evaluate the water inrush risk of sandstone aquifers from coal seam roofs and to reasonably and effectively prevent and control water disasters. In this paper, the 221 mining area of the Shilawusu Coal Mine was considered. By combining the basic geological condition data, hydrogeological condition data, and drilling data in the area studied, four main control factors, including the equivalent thickness of sandstone, the lithology coefficient of sandstone, the interbedded coefficient of sand and mud, and the core recovery rate, were selected as evaluation indexes for predicting the water inrush risk from the coal seam roof. A hierarchical prediction and discrimination model of water inrush risk based on combination weighting-set pair analysis was established. The combination weighting method, which is based on the sum of squared deviations, was used to optimize the subjective and objective weight values obtained by the improved analytic hierarchy process and entropy weight methods. By applying set pair analysis theory, the comprehensive connection degree was determined using the set pair connection degree function that was constructed with 31 instances of drilling data in the study area. Then, the risk grade of each drilling data instance was evaluated by the confidence criterion of set pair analysis to calculate the water inrush risk evaluation index. Finally, the obtained index was combined with the borehole pumping test data and the discharging test data to partition the water inrush risk from the coal seam roof. The results indicated that most of the 221 mining area is safe, and the small transitional and dangerous areas are only in the central and northern regions. Based on the combination weighting-set pair analysis method, the water inrush risk from the coal seam roofs in the study area was accurately and objectively classified by a discrimination model.
Optimization of Load Balancing and Task Scheduling in Cloud Computing Environments Using Artificial Neural Networks-Based Binary Particle Swarm Optimization (BPSO)
Authors: Alghamdi Mohammed I.
Published: September 2022

As more people utilize the cloud, more employment opportunities become available. With constraints such as a limited make-span, a high utilization rate of available resources, minimal execution costs, and a rapid turnaround time for scheduling, this becomes an NP-hard optimization issue. The number of solutions/combinations increases exponentially with the magnitude of the challenge, such as the number of tasks and the number of computing resources, making the task scheduling problem NP-hard. As a result, achieving the optimum scheduling of user tasks is difficult. An intelligent resource allocation system can significantly cut down the costs and waste of resources. For instance, binary particle swarm optimization (BPSO) was created to combat ineffective heuristic approaches. However, the optimal solution will not be produced if these algorithms are not paired with additional heuristic or meta-heuristic algorithms. Due to the high temporal complexity of these algorithms, they are less useful in real-world settings. For the NP problem, the binary variation of PSO is presented for workload scheduling and balancing in cloud computing. Considering the updating and optimization constraints stated in this research, our objective function determines if heterogeneous virtual machines (VMs) Phave the most significant difference in completion time. In conjunction with load balancing, we developed a method for updating the placements of particles. According to the experiment results, the proposed method surpasses existing metaheuristic and heuristic algorithms regarding work scheduling and load balancing. This level of success has been attainable because of the application of Artificial Neural Networks (ANN). ANN has demonstrated promising outcomes in resource distribution. ANN is more accurate and faster than multilayer perceptron networks at predicting targets.
Scientific Review and Annotated Bibliography of Teaching in Higher Education Academies on Online Learning: Adapting to the COVID-19 Pandemic
Authors: Amaechi Chiemela Victor , Amaechi Ebube Charles , Oyetunji Abiodun Kolawole , Kgosiemang Irish Mpho
Published: September 2022

Since COVID-19 first appeared, e-learning has become more and more common. In order to understand gender disparities in e-learners’ self-efficacy, satisfaction, motivation, attitude, and performance globally, this study will look at these variables. Many educational institutions have been forced to close due to the sudden COVID-19 outbreak, and many students have been forced to stay at home and take online courses. With the recent COVID-19 pandemic underway, there were challenges with STEM (Science Technology Engineering and Mathematics) modules and other teaching contents due to practical laboratory sessions and workshops required. Thus, the need to understand teaching style, online learning and its role in promoting a variety of desirable academic outcomes, such as increased achievement and decreased dropout rates, as well as various well-being and life outcomes, has advanced significantly. In this paper, the scientific review on teaching in Higher Education Academies (HEA) for online learning is presented with their frontiers towards sustainable education. The current work also gives an annotated bibliography that aims to consolidate and synthesise the literature on student engagement, online learning, social media, and teacher learning/training. Some conclusions and recommendations were also made on the study.
A Markov Chain Approach to Multicriteria Decision Analysis with an Application to Offshore Decommissioning
Authors: Moraes Fernanda F. , Filho Virgílio José M. Ferreira , Infante Carlos Eduardo Durange de C. , Santos Luan , Arruda Edilson F.
Published: September 2022

This paper proposes a novel approach that makes use of continuous-time Markov chains and regret functions to find an appropriate compromise in the context of multicriteria decision analysis (MCDA). This method was an innovation in the relationship between uncertainty and decision parameters, and it allows for a much more robust sensitivity analysis. The proposed approach avoids the drawbacks of arbitrary user-defined and method-specific parameters by defining transition rates that depend only upon the performances of the alternatives. This results in a flexible and easy-to-use tool that is completely transparent, reproducible, and easy to interpret. Furthermore, because it is based on Markov chains, the model allows for a seamless and innovative treatment of uncertainty. We apply the approach to an oil and gas decommissioning problem, which seeks a responsible manner in which to dismantle and deactivate production facilities. The experiments, which make use of published data on the decommissioning of the field of Brent, account for 12 criteria and illustrate the application of the proposed approach.
Discontinuous Normals in Non-Euclidean Geometries and Two-Dimensional Gravity
Authors: Battista Emmanuele , Esposito Giampiero
Published: September 2022

This paper builds two detailed examples of generalized normal in non-Euclidean spaces, i.e., the hyperbolic and elliptic geometries. In the hyperbolic plane we define a n-sided hyperbolic polygon P, which is the Euclidean closure of the hyperbolic plane H, bounded by n hyperbolic geodesic segments. The polygon P is built by considering the unique geodesic that connects the n+2 vertices z˜,z0,z1,…,zn−1,zn. The geodesics that link the vertices are Euclidean semicircles centred on the real axis. The vector normal to the geodesic linking two consecutive vertices is evaluated and turns out to be discontinuous. Within the framework of elliptic geometry, we solve the geodesic equation and construct a geodesic triangle. Additionally in this case, we obtain a discontinuous normal vector field. Last, the possible application to two-dimensional Euclidean quantum gravity is outlined.
Cry4Aa and Cry4Ba Mosquito-Active Toxins Utilize Different Domains in Binding to a Particular Culex ALP Isoform: A Functional Toxin Receptor Implicating Differential Actions on Target Larvae
Authors: Dechkla Manussawee , Charoenjotivadhanakul Sathapat , Imtong Chompounoot , Visitsattapongse Sarinporn , Li Hui-Chun , Angsuthanasombat Chanan
Published: September 2022

The three-domain Cry4Aa toxin produced from Bacillus thuringiensis subsp. israelensis was previously shown to be much more toxic to Culex mosquito larvae than its closely related toxin—Cry4Ba. The interaction of these two individual toxins with target receptors on susceptible larval midgut cells is likely to be the critical determinant in their differential toxicity. Here, two full-length membrane-bound alkaline phosphatase (mALP) isoforms from Culex quinquefasciatus larvae, Cq-mALP1263and Cq-mALP1264, predicted to be GPI-linked was cloned and functionally expressed in Spodoptera frugiperda (Sf9) cells as 57- and 61-kDa membrane-bound proteins, respectively. Bioinformatics analysis disclosed that both Cq-mALP isoforms share significant sequence similarity to Aedes aegypti-mALP—a Cry4Ba toxin receptor. In cytotoxicity assays, Sf9 cells expressing Cq-mALP1264, but not Cq-mALP1263, showed remarkably greater susceptibility to Cry4Aa than Cry4Ba, while immunolocalization studies revealed that both toxins were capable of binding to each Cq-mALP expressed on the cell membrane surface. Molecular docking of the Cq-mALP1264-modeled structure with individual Cry4 toxins revealed that Cry4Aa could bind to Cq-mALP1264 primarily through particular residues on three surface-exposed loops in the receptor-binding domain—DII, including Thr512, Tyr513 and Lys514 in the β10-β11loop. Dissimilarly, Cry4Ba appeared to utilize only certain residues in its C-terminal domain—DIII to interact with such a Culex counterpart receptor. Ala-substitutions of selected β10-β11loop residues (T512A, Y513A and K514A) revealed that only the K514A mutant displayed a drastic decrease in biotoxicity against C. quinquefasciatus larvae. Further substitution of Lys514 with Asp (K514D) revealed a further decrease in larval toxicity. Furthermore, in silico calculation of the binding affinity change (ΔΔGbind) in Cry4Aa-Cq-mALP1264 interactions upon these single-substitutions revealed that the K514D mutation displayed the largest ΔΔGbind value as compared to three other mutations, signifying an adverse impact of a negative charge at this critical receptor-binding position. Altogether, our present study has disclosed that these two related-Cry4 mosquito-active toxins conceivably exploited different domains in functional binding to the same Culex membrane-bound ALP isoform—Cq-mALP1264 for mediating differential toxicity against Culex target larvae.
Evaluation of Paralytic Shellfish Toxins in Marine Oyster Farming and Microalgae in the Atlantic Amazon Evidences Safety but Highlights Potential Risks of Shellfish Poisoning
Authors: Alves Francisco Arimatéia dos Santos , de Sousa Eliane Brabo , Martins Maíra Pompeu , da Silva Rocha Cássia Christina , Faustino Silvia Maria Mathes , Mendes Rosivaldo Alcântara , de Oliveira Lima Marcelo , Schneider Maria Paula Cruz
Published: September 2022

Marine phycotoxins are organic compounds synthesized by some species of microalgae, which accumulate in the tissues of filter-feeder organisms such as bivalve mollusks. These toxins can cause acute intoxication episodes in humans, a severe threat to aquaculture and fisheries. In the State of Pará, Brazil, oyster farming has community, artisanal and sustainable bases, using mangroves as cultivation environment and seed banks. In small-scale production, there are often no established methods of safeguarding the health of consumers elevating the potential risks of shellfish poisoning outbreaks. Our study evaluated the presence of phycotoxins in oysters cultivated in five municipalities in the region of the Atlantic Amazon (Pará, Brazil) assessing the quality of the final product. We further evaluated the microalgae, water quality, and the spatio-temporal variation of physicochemical factors in the same area. Diatoms dominated the microalgae composition, followed by dinoflagellates, some of which are reported to be potentially toxic and producers of paralytic shellfish toxins. For the first time, we describe the occurrence of the potentially toxic dinoflagellate Ostreopsis sp. in the Amazon region. Furthermore, for the first time, toxins were detected in oyster farming in the northeast of the State of Pará, namely GTX2,3, STX, and dc-STX nevertheless, with nontoxic values. The identified toxins represent a potential threat to shellfish consumers.
Effects of Botulinum Toxin Therapy on Health-Related Quality of Life Evaluated by the Oromandibular Dystonia Rating Scale
Authors: Yoshida Kazuya
Published: September 2022

Oromandibular dystonia (OMD) refers to a focal dystonia in the stomatognathic system. Health-related quality of life (HRQoL) in isolated dystonia is associated with non-motor symptoms such as depression, anxiety, and pain, as well as motor symptoms. To evaluate HRQoL in patients with OMD, the therapeutic effects of botulinum neurotoxin (BoNT) therapy were assessed using a recently developed and validated comprehensive measurement tool called the Oromandibular Dystonia Rating Scale (OMDRS). Altogether, 408 patients (jaw closing dystonia, n = 223; tongue (lingual) dystonia, n = 86; jaw opening dystonia, n = 50; jaw deviation dystonia, n = 23; jaw protrusion dystonia, n = 13; and lip (labial) dystonia, n = 13) were evaluated at baseline and after the end of BoNT therapy or in a stable status. The total OMDRS score reduced significantly from 149.1 to 57.6 (p < 0.001). Mean improvement was 63.1%. All examiner-rated subscales (severity, disability, and pain) and patient-rated questionnaire scores (general, eating, speech, cosmetic, social/family life, sleep, annoyance, mood, and psychosocial function) were significantly lower at the endpoint than at baseline (p < 0.001). The BoNT injection had a highly positive impact on patient HRQoL, and the OMDRS could evaluate both motor phenomena and non-motor symptoms.