bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of Lower-Limb Motor Tasks via Brain–Computer Interfaces: A Topical Overview
Authors: Asanza Víctor , Peláez Enrique , Loayza Francis , Lorente-Leyva Leandro L. , Peluffo-Ordóñez Diego H.
Published: March 2022

Recent engineering and neuroscience applications have led to the development of brain–computer interface (BCI) systems that improve the quality of life of people with motor disabilities. In the same area, a significant number of studies have been conducted in identifying or classifying upper-limb movement intentions. On the contrary, few works have been concerned with movement intention identification for lower limbs. Notwithstanding, lower-limb neurorehabilitation is a major topic in medical settings, as some people suffer from mobility problems in their lower limbs, such as those diagnosed with neurodegenerative disorders, such as multiple sclerosis, and people with hemiplegia or quadriplegia. Particularly, the conventional pattern recognition (PR) systems are one of the most suitable computational tools for electroencephalography (EEG) signal analysis as the explicit knowledge of the features involved in the PR process itself is crucial for both improving signal classification performance and providing more interpretability. In this regard, there is a real need for outline and comparative studies gathering benchmark and state-of-art PR techniques that allow for a deeper understanding thereof and a proper selection of a specific technique. This study conducted a topical overview of specialized papers covering lower-limb motor task identification through PR-based BCI/EEG signal analysis systems. To do so, we first established search terms and inclusion and exclusion criteria to find the most relevant papers on the subject. As a result, we identified the 22 most relevant papers. Next, we reviewed their experimental methodologies for recording EEG signals during the execution of lower limb tasks. In addition, we review the algorithms used in the preprocessing, feature extraction, and classification stages. Finally, we compared all the algorithms and determined which of them are the most suitable in terms of accuracy.
The Movesense Medical Sensor Chest Belt Device as Single Channel ECG for RR Interval Detection and HRV Analysis during Resting State and Incremental Exercise: A Cross-Sectional Validation Study
Authors: Rogers Bruce , Schaffarczyk Marcelle , Clauß Martina , Mourot Laurent , Gronwald Thomas
Published: March 2022

The value of heart rate variability (HRV) in the fields of health, disease, and exercise science has been established through numerous investigations. The typical mobile-based HRV device simply records interbeat intervals, without differentiation between noise or arrythmia as can be done with an electrocardiogram (ECG). The intent of this report is to validate a new single channel ECG device, the Movesense Medical sensor, against a conventional 12 channel ECG. A heterogeneous group of 21 participants performed an incremental cycling ramp to failure with measurements of HRV, before (PRE), during (EX), and after (POST). Results showed excellent correlations between devices for linear indexes with Pearson’s r between 0.98 to 1.0 for meanRR, SDNN, RMSSD, and 0.95 to 0.97 for the non-linear index DFA a1 during PRE, EX, and POST. There was no significant difference in device specific meanRR during PRE and POST. Bland–Altman analysis showed high agreement between devices (PRE and POST: meanRR bias of 0.0 and 0.4 ms, LOA of 1.9 to −1.8 ms and 2.3 to −1.5; EX: meanRR bias of 11.2 to 6.0 ms; LOA of 29.8 to −7.4 ms during low intensity exercise and 8.5 to 3.5 ms during high intensity exercise). The Movesense Medical device can be used in lieu of a reference ECG for the calculation of HRV with the potential to differentiate noise from atrial fibrillation and represents a significant advance in both a HR and HRV recording device in a chest belt form factor for lab-based or remote field-application.
Impact of Ag on the Limit of Detection towards NH3-Sensing in Spray-Coated WO3 Thin-Films
Authors: Anusha  , Ani Aninamol , Poornesh P. , Antony Albin , Bhaghyesh  , Shchetinin Igor V. , Nagaraja K. K. , Chattopadhyay Saikat , Vinayakumar K. B.
Published: March 2022

Ag-doped WO3 (Ag–WO3) films were deposited on a soda-lime glass substrate via a facile spray pyrolysis technique. The surface roughness of the films varied between 0.6 nm and 4.3 nm, as verified by the Atomic Force Microscopy (AFM) studies. Ammonia (NH3)-sensing measurements of the films were performed for various concentrations at an optimum sensor working temperature of 200 °C. Enrichment of oxygen vacancies confirmed by X-ray Photoelectron Spectroscopy (XPS) in 1% Ag–WO3 enhanced the sensor response from 1.06 to 3.29, approximately 3 times higher than that of undoped WO3. Limit of detection (LOD) up to 500 ppb is achieved for 1% Ag–WO3, substantiating the role of Ag in improving sensor performance.
Analysis of Job Failure and Prediction Model for Cloud Computing Using Machine Learning
Authors: Jassas Mohammad S. , Mahmoud Qusay H.
Published: March 2022

Modern applications, such as smart cities, home automation, and eHealth, demand a new approach to improve cloud application dependability and availability. Due to the enormous scope and diversity of the cloud environment, most cloud services, including hardware and software, have encountered failures. In this study, we first analyze and characterize the behaviour of failed and completed jobs using publicly accessible traces. We have designed and developed a failure prediction model to determine failed jobs before they occur. The proposed model aims to enhance resource consumption and cloud application efficiency. Based on three publicly available traces: the Google cluster, Mustang, and Trinity, we evaluate the proposed model. In addition, the traces were also subjected to various machine learning models to find the most accurate one. Our results indicate a significant correlation between unsuccessful tasks and requested resources. The evaluation results also revealed that our model has high precision, recall, and F1-score. Several solutions, such as predicting job failure, developing scheduling algorithms, changing priority policies, or limiting re-submission of tasks, can improve the reliability and availability of cloud services.
Detection of Airborne Nanoparticles through Enhanced Light Scattering Images
Authors: Ye Yan , Ou Qisheng , Chen Weiqi , Cao Qingfeng , Kwak Dong-Bin , Kuehn Thomas , Pui David Y. H.
Published: March 2022

A new method is proposed in this paper to detect airborne nanoparticles, detecting the light scattering caused by both the particle and the surrounding molecules, which can surpass the limitations of conventional laser optical methods while maintaining simplicity and cost-effectiveness. This method is derived from a mathematical analysis that describes the particle light scattering phenomenon more exactly by including the influence of light scattered from surrounding gas molecules. The analysis shows that it is often too much of a simplification to consider only light scattering from the detected nanoparticle, because light scattering from the surrounding gas molecules, whether visible or invisible to the sensor, is important for nanoparticle detection. An image detection approach utilizing the light scattering from surrounding air molecules is described for the detection of airborne nanoparticles. Tests using monodisperse nanoparticles confirm that airborne particles of around 50 nm in size can even be detected using a low-cost testing device. This shows further that even when using a simple image processing code, captured particle light scattering images can be converted digitally into instantaneous particle counts or concentrations. The factors limiting conventional pulse detection are further discussed. This new method utilizes a simple static light scattering (SLS) approach to enable the development of new devices with better detection capabilities, paving the way for the further development of nanoparticle detection technology.
Intelligent Diagnosis of Rolling Element Bearing Based on Refined Composite Multiscale Reverse Dispersion Entropy and Random Forest
Authors: Liu Aiqiang , Yang Zuye , Li Hongkun , Wang Chaoge , Liu Xuejun
Published: March 2022

Rolling bearings are the vital components of large electromechanical equipment, thus it is of great significance to develop intelligent fault diagnoses for them to improve equipment operation reliability. In this paper, a fault diagnosis method based on refined composite multiscale reverse dispersion entropy (RCMRDE) and random forest is developed. Firstly, rolling bearing vibration signals are adaptively decomposed by variational mode decomposition (VMD), and then the RCMRDE values of 25 scales are calculated for original signal and each decomposed component as the initial feature set. Secondly, based on the joint mutual information maximization (JMIM) algorithm, the top 15 sensitive features are selected as a new feature set and feed into random forest model to identify bearing health status. Finally, to verify the effectiveness and superiority of the presented method, actual data acquisition and analysis are performed on the bearing fault diagnosis experimental platform. These results indicate that the presented method can precisely diagnose bearing fault types and damage degree, and the average identification accuracy rate is 97.33%. Compared with the refine composite multiscale dispersion entropy (RCMDE) and multiscale dispersion entropy (MDE), the fault diagnosis accuracy is improved by 2.67% and 8.67%, respectively. Furthermore, compared with the RCMRDE method without VMD decomposition, the fault diagnosis accuracy is improved by 3.67%. Research results prove that a better feature extraction technique is proposed, which can effectively overcome the deficiency of existing entropy and significantly enhance the ability of fault identification.
Design and Implementation of a UAV-Based Airborne Computing Platform for Computer Vision and Machine Learning Applications
Authors: Douklias Athanasios , Karagiannidis Lazaros , Misichroni Fay , Amditis Angelos
Published: March 2022

Visual sensing of the environment is crucial for flying an unmanned aerial vehicle (UAV) and is a centerpiece of many related applications. The ability to run computer vision and machine learning algorithms onboard an unmanned aerial system (UAS) is becoming more of a necessity in an effort to alleviate the communication burden of high-resolution video streaming, to provide flying aids, such as obstacle avoidance and automated landing, and to create autonomous machines. Thus, there is a growing interest on the part of many researchers in developing and validating solutions that are suitable for deployment on a UAV system by following the general trend of edge processing and airborne computing, which transforms UAVs from moving sensors into intelligent nodes that are capable of local processing. In this paper, we present, in a rigorous way, the design and implementation of a 12.85 kg UAV system equipped with the necessary computational power and sensors to serve as a testbed for image processing and machine learning applications, explain the rationale behind our decisions, highlight selected implementation details, and showcase the usefulness of our system by providing an example of how a sample computer vision application can be deployed on our platform.
FT-NIR Spectroscopy for the Non-Invasive Study of Binders and Multi-Layered Structures in Ancient Paintings: Artworks of the Lombard Renaissance as Case Studies
Authors: Longoni Margherita , Genova Beatrice , Marzanni Alessia , Melfi Daniela , Beccaria Carlotta , Bruni Silvia
Published: March 2022

This work deals with the identification of natural binders and the study of the complex stratigraphy in paintings using reflection FT-IR spectroscopy, a common diagnostic tool for cultural heritage materials thanks to its non-invasiveness. In particular, the potential of the near-infrared (NIR) spectral region, dominated by the absorption bands due to CH, CO, OH and NH functional groups, is successfully exploited to distinguish a lipid binder from a proteinaceous one, as well as the coexistence of the two media in laboratory-made model samples that simulate the complex multi-layered structure of a painting. The combination with multivariate analysis methods or with the calculation of indicative ratios between the intensity values of characteristic absorption bands is proposed to facilitate the interpretation of the spectral data. Furthermore, the greater penetration depth of NIR radiation is exploited to obtain information about the inner layers of the paintings, focusing in particular on the preparatory coatings of the supports. Finally, as proof of concept, FT-NIR analyses were also carried out on six paintings by artists working in Lombardy at the end of the 15th century, that exemplify different pictorial techniques.
Application of Untargeted Metabolomics to Determine Volatile Compounds from the Spanish Plant Arctostaphylos uva-ursi Used as Tea
Authors: Wrona Magdalena , Pezo Davinson , Rovito Maria Anna , Vera Paula , Nerín Cristina , Asensio Esther
Published: March 2022

One-hundred and seven different volatile compounds were identified in the samples of Arctostaphylos uva-ursi collected from nine locations in Spain. This plant is commonly brewed and used as tea. Volatile compounds profile was detected using solid-phase microextraction gas chromatography-mass spectrometry. The most interesting compounds detected from an antioxidant capacity point of view were esters, phenols, and aromatics compounds. All samples were discriminated by principal component analysis. The insolation and altitude of harvest areas, and latent structures were considered for interpretation of results. Discriminant analysis was applied to control the type and concentration of metabolites and determine the best plant antioxidant profiles of volatile compounds from plant origin. Moreover, a heatmap displayed correlations between detected compounds. The discriminant analysis led to 20 quality markers being identified for the analysed plants. The strongest antioxidant capacity was obtained in the samples from Pina de Montalgrao and Loarre (collected in September) for ORAC (33.11 ± 0.61 g Trolox/g sample) and DPPH (IC50 = 711 ± 12 µg/g) methods, respectively. The plant with the highest total phenolic content was Loarre collected in September (171.9 ± 19.4 mg GAE/g DW) and November (177.1 ± 11.0 mg GAE/g DW).
The ENRICH Marital Satisfaction (EMS) Scale: A Psychometric Study in a Sample of Portuguese Parents
Authors: Nunes Cristina , Martins Cátia , Leal Andreia , Pechorro Pedro , Ferreira Laura Inês , Ayala-Nunes Lara
Published: March 2022

Marital satisfaction is a key construct in the assessment of a couple’s relationship, and it encompasses aspects such as the feelings of affection, trust, and companionship that arise from the exchanges between spouses. The ENRICH Marital Satisfaction (EMS) Scale has been widely used as a reliable measure to assess marital satisfaction. In the present study, we aimed to analyze the psychometric properties and the factor structure of the EMS Scale in a sample of Portuguese parents. A total of 205 mothers and fathers participated; 107 were women (52%), and 98 were men (48%), and the mean age was 38.39 years (SD = 5.85). The majority were two-parent families (89.3%), with children between the ages of 1 and 13 years (M = 6.90), 53% of whom were boys. The participants completed the EMS Scale together with the Parenting Stress Index Short Form and the Parenting Alliance Inventory. The results from a confirmatory factor analysis corroborate the two-dimensional structure of the instrument, with internal validity and reliability values that were suitable for application in the Portuguese population. The EMS Scale can be an important resource, with good psychometric quality, for professionals and researchers, which can be used in assessment and intervention programs, both at the individual and couple levels.
Agricultural Insurance and Agricultural Fertilizer Non-Point Source Pollution: Evidence from China’s Policy-Based Agricultural Insurance Pilot
Authors: Niu Ziheng , Yi Feng , Chen Chen
Published: March 2022

For a long time, the relationship between agricultural insurance and the input of chemical fertilizer has been controversial. Since the pilot of policy-based agricultural insurance in China, most scholars have only paid attention to the role of the policy in ensuring farmers’ income and reducing farmers’ poverty, but its possible negative impact on the agricultural ecological environment is often ignored. If the pilot of this policy motivates farmers to apply more chemical fertilizers, which in turn causes more serious environmental problems, this would be contrary to the goals of the policy itself. Using the panel data of 31 provinces from 2000 to 2020 in China, this paper regards the pilot of policy-based agricultural insurance as a quasi-natural experiment and uses a difference-in-difference model to evaluate the impact of policy-based agricultural insurance on agricultural fertilizer non-point source pollution. The research results show that the pilot of policy-based agricultural insurance has aggravated the non-point source pollution of agricultural fertilizers in China. After a series of robustness tests, the research conclusion is still valid. At the same time, the effect of policy-based agricultural insurance aggravating agricultural fertilizer non-point source pollution had a lasting impact for 4 years during the pilot period and did not disappear until the policy-based agricultural insurance was fully covered. In addition, the heterogeneity results show that farmers in eastern China and high-disaster areas have a higher probability of moral hazard with overuse after purchasing policy-based agricultural insurance.
Exogenous Caffeine (1,3,7-Trimethylxanthine) Application Diminishes Cadmium Toxicity by Modulating Physio-Biochemical Attributes and Improving the Growth of Spinach (Spinacia oleracea L.)
Authors: Emanuil Naila , Akram Muhammad Sohail , Ali Shafaqat , Majrashi Ali , Iqbal Muhammad , El-Esawi Mohamed A. , Ditta Allah , Alharby Hesham F.
Published: March 2022

Leafy vegetables usually absorb and retain heavy metals more readily than most of the other crop plants, and thus contribute ≥70% of the total cadmium (Cd) intake of humans. Caffeine mediates plant growth and has proved to be beneficial against pathogens and insects. Therefore, it was hypothesized that foliar applications of caffeine could alter metabolism and reduce Cd toxicity in spinach (Spinacia oleracea L.). Seven-day old spinach seedlings were provided with Cd (0, 50, and 100 µM) stress. Caffeine (0, 5, or 10 mM) foliar spray was given twice at after 20 days of seeds germination with an interval of one week. In results, Cd stress reduced photosynthetic pigments biosynthesis, increased oxidative stress, imbalanced nutrient retention, and inhibited plant growth. On the other hand, the caffeine-treated spinach plants showed better growth owing to the enhanced biosynthesis of chlorophylls, better oxidative defense systems, and lower accumulation and transport of Cd within the plant tissues. Furthermore, caffeine application enhanced the accumulation of the proline and ascorbic acid, but reduced MDA and H2O2 contents and Cd in plant leaves, and ultimately improved mineral nutrition of spinach plants exposed to different Cd regimes. In conclusion, exogenous application of caffeine significantly diminishes Cd stress by modulating physiological, biochemical, and growth attributes of spinach (Spinacia oleracea L.)
Evaluation and Influencing Factors of China’s Agricultural Productivity from the Perspective of Environmental Constraints
Authors: Chen Yanling , Fu Weiwei , Wang Jingyun
Published: March 2022

Based on provincial panel data for the past 15 years in China, the SBM-ML index method was used to measure agricultural productivity under the environmental-constraint perspective with agricultural surface source pollution as the non-desired output. A dynamic panel regression model was used to empirically analyze the factors influencing agricultural productivity to provide a reference for formulating policies to alleviate the conflict between economic development and environmental pollution. The results show that the green total factor productivity of Chinese agriculture exhibits a slow, incremental trend year by year. The growth of green total factor productivity in agriculture mainly comes from the increase in the rate of green technological progress. In terms of geographical disparity, the eastern, central, and western regions show a high-to-low gradient of agricultural green total factor productivity. Agricultural green total factor productivity showed a significant positive spatial correlation in some years. As for the influencing factors, foreign trade in agricultural products is conducive to enhancing green total factor productivity in agriculture, whereas foreign direct investment in agriculture and agricultural technology input inhibit the growth of green total factor productivity in agriculture. This research also found a significant U-shaped relationship between environmental management inputs and green total factor productivity in agriculture. Accordingly, suggestions are provided to optimize the international trade structure of agricultural products, selectively introduce high-quality green foreign investment projects, drive the efficiency of R&D investment through digital technology, and increase investment in special funds for agricultural pollution control.
The Effects of the In-Flight Safety Information Characteristics on the Safety Behavioral Intention of Airline Passengers
Authors: Kim Hayoung , Lee Namryoung
Published: March 2022

This research aims to explore the effects that In-flight Safety Information Characteristics of airlines have on attitude, customer satisfaction, customer trust, and safety behavioral intentions. A total of 477 passengers with air travel experience were surveyed and responses were analyzed using a structural equation model. Among four in-flight safety information characteristics, reliability, informative, utility turned out to have positive effects on attitude, interactivity are not significant antecedents of attitude. In turn, Attitude had a positive effect on customer satisfaction, customer trust, and safety behavioral intentions. It is believed that this research can serve as a starting point for future studies on the diverse servicescapes of airport facilities. It is believed that this research can serve as an important basic data and strategy for securing passenger safety and efficient measures for airlines’ in-flight safety information operation.
Research on Green Finance and Green Development Based Eco-Efficiency and Spatial Econometric Analysis
Authors: Ye Tifang , Xiang Xiuli , Ge Xiangyu , Yang Keling
Published: March 2022

During the “14th Five-Year Plan” period, a question worth exploring in depth would be how China promotes green development through green finance to realize the goal of financially supporting the construction of ecological civilization. This paper builds a super-efficiency SBM window model to evaluate the comparable eco-efficiency of 30 provincial administrative regions in Mainland China (except Tibet) as a measurement of green development, and constructs an evaluation system for the green finance index, as a measurement of regional green finance development levels in China from 2007 to 2019. This paper also constructs spatial econometric models to study the effects of green finance on green development, and the influence of green finance on green development through supporting green technological innovation. Moreover, this paper analyzes the mechanisms of the spatial spillover effects and the heterogeneity in eastern, central, and western regions of China. The results of the study show that green finance only has a positive effect on green development in eastern regions, while in central and western regions, it fails to effectively support green development. The positive effect of green finance on green development by supporting green technological innovation is only in eastern regions, but it is not significant in the central region, while negative effect in the western region. Finally, according to the research conclusions, it is proposed to implement differentiated policies of green finance and the integration policies of green finance and green technological innovation policies in different regions of China.
The Effect of Governance Rules Application Controls and the Accrual Basis Application Controls on Quality of Financial Reporting: Applying to Jouf University
Authors: Ibrahim Taha Khairy Taha , Al-Matari Ebrahim Mohammed
Published: March 2022

The issue of governance and its applications in Saudi universities is one of the most important issues that has an effective impact on achieving excellence in performance, and achieving societal development for Saudi society. The application of governance rules works to enhance the values of justice, equality, the rule of law, combating corruption, transparency and accountability to contribute to the province on public funds and achieving quality and excellence in performance. So, this study aims to study the impact of the application of governance rules and the accrual basis on the quality of financial reports in Jouf university (Saudi Universities). A total of 348 questionnaires were issued to respondents, with 242 being returned. To put the hypothesized model to the test, structural equation modeling was used. The major findings confirmed the effect of governance rules and accrual foundation of application controls on the quality of Jouf University’s financial reporting. The findings have numerous practical ramifications, including the ability to assist managers in making sound decisions when selecting whether to establish governance rules and accrual basis of application controls in their organization. This is a rare and one-of-a-kind empirical study that investigates the impact of governance rules and accrual basis of application controls on the quality of financial reporting at Saudi universities such as Jouf University. This is the first study to give empirical evidence on the relationship between governance rules, the accrual basis of application controls, and financial reporting quality in the context of universities.
Geometric and Material Variability of the Probability of Landward Slope Failure for Homogeneous River Levees
Authors: Schwiersch Niklas , Stamm Jürgen
Published: March 2022

Holistic flood risk management (FRM) aims at minimizing the flood risk (FR) for an entire river basin. To this end, the probability of flooding and its consequences must also be taken into account in the planning of flood risk management measures. If the FR is to be limited by the flooding probability value (e.g., by changing the structural reliability), knowledge of the variability of the limit state is required. As an example, this study quantifies for the first time the variability of the probability of a landside slope failure on homogeneous river levees, using the Monte Carlo simulation. In the slip circle method developed by Krey that is used for this purpose, four geometric and six material input parameters are included as being uncertain, of which four emerge in the result as being relevant influencing variables of the failure probability. These analyses extend our understanding of landward slope failure by the variability of the limit state; the results allow a targeted adjustment of the local failure probability to limit the flood risk. In the future, the methodology presented is to be supplemented by the integration of parameter dependencies and, once in use, expanded to include structured cross-sections or additional failure mechanisms.
Performance Implications of Organizational and Technological Innovation: An Integrative Perspective
Authors: Todorovic Tanja , Medic Nenad , Delic Milan , Zivlak Nikola , Gracanin Danijela
Published: March 2022

Manufacturing firms engage in various innovation activities to achieve a sustainable competitive advantage. Although technological innovation is considered one of the key performance drivers, organizational innovation has become increasingly prominent. This study analyzes the relationship between organizational and technological innovation and examines their effect on firm performance in the manufacturing context. The empirical evidence is based on the European Manufacturing Survey (EMS)—Serbian data set gathered in 2018. Hypotheses on the relationship between organizational and technological innovations and firm performance are tested by structural equation modeling using data from 240 Serbian manufacturing firms. The results have shown that technological concepts strongly mediate the impact of organizational factors on firm performance (return on sales—ROS). Moreover, it could be said that, in contrast to the individual approach, to foster a ROS, a synergic effect of organizational and technological concepts is needed, implying the need for an integrative perspective in the process of innovation.
Software-Defined Mobile Supply Chains: Rebalancing Resilience and Efficiency in Production Systems
Authors: Alarcon-Gerbier Eduardo , Chokparova Zarina , Ghondaghsaz Nassim , Zhao Wanqi , Shahmoradi-Moghadam Hani , Aßmann Uwe , Oruç Orçun
Published: March 2022

The miniaturization and modularization of production capacity brings with it not only greater agility and efficiency, but also increased flexibility in the form of mobility. This flexibility allows production capacity to be moved when and where it is most needed, generating new business opportunities, e.g., allowing modular units to be rented, leased, or shared. This flexibility, however, requires information and control systems that ensure a correct and secure flow of information between different stakeholders of the supply chain. Based on this, the present article characterizes the concept of software-defined mobile supply chains, presenting its main requirements, opportunities, and limitations. In addition, we present two case studies in which the proposed concept is evaluated in order to demonstrate its applicability. Here, due to the new optimization problems that arise when considering mobile facilities, special interest is given to the planning and control of the required operations, as well as the difficulties associated with the exchange of physical and intellectual assets between different stakeholders.
Measurement of Street Network Structure in Strip Cities: A Case Study of Lanzhou, China
Authors: Li Xin , Qian Yongsheng , Zeng Junwei , Wei Xuting , Guang Xiaoping
Published: March 2022

As the foundation and skeleton of urban space, the street network is significant to the urban travel environment and socio-economic activities. To reveal the structural characteristics of the street network, this paper proposes a measurement index system to study the street network structure and urban travel characteristics. To illustrate the relationship between spatial accessibility of streets in strip cities and residents’ travel and service demands, we take Lanzhou, a typical strip city, as an example for network analysis and study the hierarchical structure of physical, functional, and environmental characteristics of the street topological network. The results show that Lanzhou City has formed a radial network structure with traffic-oriented streets as the backbone and interconnected living streets. However, the development of old and new urban areas is still uneven. In terms of street function distribution, streets with a high degree of diversity are more attractive to population clustering and show a polycentric clustering feature in space related to the regional functional orientation and travel characteristics. Much of the structural difference in the centrality core-periphery of the street network under pedestrian and vehicular travel patterns are influenced by the street’s type and function. In addition, as part of the contribution, we provide an evaluation methodology that enables the analysis of street network centrality. These findings advance our understanding of strip city development.
Extending the Life Cycle of EEE—Findings from a Repair Study in Germany: Repair Challenges and Recommendations for Action
Authors: Rudolf Sina , Blömeke Steffen , Niemeyer Jan Felix , Lawrenz Sebastian , Sharma Priyanka , Hemminghaus Sven , Mennenga Mark , Schmidt Kerstin , Rausch Andreas , Spengler Thomas S. , Herrmann Christoph
Published: March 2022

The increasing amount of waste from electrical and electronic equipment and the resulting environmental issues are challenging, since product life cycles are too short, and companies continue to rely on linear (business) models. The Circular Economy is an approach to meet these challenges by extending the product lifetime. One way to extend the product lifetime is to repair them. However, since there has been no detailed research on the repair sector yet, this article aims at conducting a repair study in Germany to understand the repair process and get insights into typical failure patterns. Therefore, we analyze the repair sector’s current barriers from different perspectives, especially of customers and businesses. We discuss the results of the repair study, where 382 repair attempts were conducted, with a total success rate of 55%. Moreover, the participants were interviewed to understand their barriers and motivation for repair. Based on the study’s interim findings, recommendations for action are given to make the repair services more attractive for the repairer and customer. Based on the findings, an interdisciplinary approach to improve repair processes by using a digital repair portal is derived.
Ensuring Sustainability during a Crisis Using an Innovative Flexible Methodology
Authors: Pastarmadzhieva Daniela Dobreva , Angelova Mina Nikolaeva , Raychev Stefan Atanasov , Madzhurova Blaga Petrova , Desev Kiril Valkov
Published: March 2022

The COVID-19 pandemic forced national governments and administrations to seek flexible solutions to deal with the emergency. Thus, the main purpose of the current study is to design a model of a flexible methodology based on detailed flexible methodologies to make decisions and measures connected to COVID-19 pandemic to be effectively applied without the loss of meaning and within a short time. For the creation of the methodology, we used comprehensive desk research based upon a literature review in the period May 2021–November 2021. As a result, an expandable set of relevant methodologies for crisis management and flexible methodologies was identified, modeled, and formalized using a broad literature review and an innovative model of a flexible methodology for crisis management was created in accordance with standardized concepts, transforming them into secondary use models. Furthermore, an algorithm for taking measures and decisions in crisis conditions was designed. The next step is to implement the methodology, which is planned for future empirical research. The findings provide an innovative model of a flexible methodology that could be used by academic and business representatives, public institutions of central and local government, and private stakeholders.
Towards Increasing Hosting Capacity of Modern Power Systems through Generation and Transmission Expansion Planning
Authors: Almalaq Abdulaziz , Alqunun Khalid , Refaat Mohamed M. , Farah Anouar , Benabdallah Fares , Ali Ziad M. , Aleem Shady H. E. Abdel
Published: March 2022

The use of renewable and sustainable energy sources (RSESs) has become urgent to counter the growing electricity demand and reduce carbon dioxide emissions. However, the current studies are still lacking to introduce a planning model that measures to what extent the networks can host RSESs in the planning phase. In this paper, a stochastic power system planning model is proposed to increase the hosting capacity (HC) of networks and satisfy future load demands. In this regard, the model is formulated to consider a larger number and size of generation and transmission expansion projects installed than the investment costs, without violating operating and reliability constraints. A load forecasting technique, built on an adaptive neural fuzzy system, was employed and incorporated with the planning model to predict the annual load growth. The problem was revealed as a non-linear large-scale optimization problem, and a hybrid of two meta-heuristic algorithms, namely, the weighted mean of vectors optimization technique and sine cosine algorithm, was investigated to solve it. A benchmark system and a realistic network were used to verify the proposed strategy. The results demonstrated the effectiveness of the proposed model to enhance the HC. Besides this, the results proved the efficiency of the hybrid optimizer for solving the problem.
Governing Value Creation in a Major Infrastructure Project Client Organization: The Case of Beijing Daxing International Airport
Authors: Xu Qixiong , Jia Guangshe , Wang Xueying , Chen Yuting
Published: March 2022

Major infrastructure projects (MIPs) are growing rapidly worldwide and have a “double-edged-sword” effect on the economy, society, and environment. Sustainability, therefore, has become a critical concern for MIPs. The sustainability of MIPs emphasizes the need to take the value creation view to scrutinize MIP practices, which calls for a deeper understanding of the value creation process of MIPs. Although research efforts have been devoted to understanding value creation in MIPs, scarce attention has been focused on the question of how a project client governs project activities, operational preparation activities, and their interplay to create value in MIPs. Based on an in-depth case analysis of the Beijing Daxing International Airport, we found that the project client adopted the three different governance arrangements of vertical blended integration, dynamic matrix integration, and continuous coupling to govern project activities, operational preparation activities, and their interplay, respectively; likewise, the hybrid values of project management value, business value, and public value were created. Following the results, we establish a conceptual framework for the governance of value creation in a project client organization of MIPs. This study not only contributes to the literature on project governance and project value, but also provides practical guidance for emerging MIPs worldwide.
Evaluation of Complexity Issues in Building Information Modeling Diffusion Research
Authors: Liao Longhui , Zhou Kaixin , Fan Cheng , Ma Yuanyuan
Published: March 2022

This study aimed to ascertain the research status of complexity issues in building information modeling (BIM) diffusion and identify future research directions in this field. A total of 366 relevant journal articles were holistically evaluated. The visualization analysis indicated that management aspects, emergent trends (such as green building, facility management, and automation), and theme clusters (such as interoperability, waste management, laser scanning, stakeholder management, and energy efficiency) are shaping BIM research towards complexity. Areas such as supply chain, cost, digital twin, and web are also essential. The manual qualitative evaluation classified the complexity issues in BIM diffusion research into three types (complexities of network-based BIM evolution, impact of BIM adoption circumstances, and BIM-based complexity reduction for informed decision making). It was concluded that BIM has been shifting towards information models and systems-based life cycle management, waste control for healthy urban environments, and complex data analysis from a big data perspective, not only in building projects but also in heritage and infrastructure, or at the city scale, for informed decision making and automatic responses. Future research should investigate the co-evolution between collaborative networks and BIM artefacts and work processes, quality improvement of BIM-based complex networks, BIM post-adoption behaviors influenced by complex environmental contexts, and BIM-based complexity reduction approaches.
Pictures Matter: How Images of Projected Sea-Level Rise Shape Long-Term Sustainable Design Decisions for Infrastructure Systems
Authors: Milovanovic Julie , Shealy Tripp , Klotz Leidy , Johnson Eric J. , Weber Elke U.
Published: March 2022

Community input matters in long-term decisions related to climate change, including the development of public infrastructure. In order to assess the effect of different ways of informing the public about infrastructure projects, a sample of people in the United States (n = 630) was provided with a case study concerning the redevelopment of the San Diego Airport. Participants received the same written information about the projected future condition of the airport. In addition, participants received images either portraying current conditions or portraying conditions in 2100 based on NOAA (National Oceanic and Atmospheric Administration) sea-level rise data. Participants were asked to choose 7 out of 21 design options to implement in the redevelopment project. The framework used for the design options stemmed from the Envision rating system. We analyzed the participants’ selection of the credits using generalized linear mixed models. Those that received the images portraying the future were significantly more likely to select design options that would reduce the risk of climate change and flooding. Images portraying sea-level rise had different effects depending on participant demographics. Such images increased the selection of design elements related to the climate and risk for participants identifying as female or as Democrat. For participants identifying as male or as Republican, the same images increased their selection of design elements to enhance community public space. The results demonstrate the positive effects of portraying the future in terms of encouraging focus on long-term sustainable design decisions for infrastructure systems.
Systematic Review Analysis on Smart Building: Challenges and Opportunities
Authors: Aliero Muhammad Saidu , Asif Muhammad , Ghani Imran , Pasha Muhammad Fermi , Jeong Seung Ryul
Published: March 2022

Smart building technology incorporates efficient and automated controls and applications that use smart energy products, networked sensors, and data analytics software to monitor environmental data and occupants’ energy consumption habits to improve buildings’ operation and energy performance. Smart technologies and controls are becoming increasingly important not only in research and development (R&D) but also in industrial and commercial domains, leading to a steady growth in their application in the building sector. This study examines the literature on SBEMS published between 2010 and 2020 with a systematic approach. It examines the trend with the annual number of the published studies before exploring the classification of publications in terms of factors such as domain of SBEMS, control approaches, smart technologies, and quality attributes. Recent developments around the smart building energy management systems (SBEMS) have focused on features that provide occupants with an interface to monitor, schedule, and modify building energy consumption profiles and allow a utility to participate in a communication grid through demand response programs and automatic self-report outage functionality. The study also explores future research avenues, especially in terms of improvements in privacy and security, and interoperability. It is also suggested that the smart building technologies’ smartness can be improved with the help of solutions such as real-time data monitoring and machine learning
“Waging War” for Doing Good? The Fortune Global 500’s Framing of Corporate Responses to COVID-19 Pandemic
Authors: Uysal Nur , Aksak Emel Ozdora
Published: March 2022

This study examined corporate social responsibility (CSR) communication and pandemic responses of large corporations across multiple industries in a global context. Specifically, this research (1) described the state of CSR communication during the pandemic, and (2) identified how top global Fortune 500 corporations framed their COVID-19 pandemic responses as part of their social advocacy. An in-depth content analysis of the corporate communication messages revealed that top global corporations positioned their pandemic responses as an extension of their ongoing CSR commitment, prioritizing their philanthropic responsibilities over the ethical, legal, and economic responsibilities. They often relied on war metaphors, portraying the virus as the “common enemy” and employees as “heroes,” and highlighted their leadership role in the global “fight” against the pandemic as a “partner” of governments, “protector” of employees, and “supporter’’ of the communities. Analyzing a large data set from a global perspective, this study provides a comprehensive look at the state of CSR communication during the pandemic and demonstrates how corporations as authoritative societal actors help shape the ongoing discourse on the global COVID-19 pandemic. Thus, the study makes several practical and theoretical contributions to sustainability research and our understanding of the evolving relationship between business and society.
Pro-Environmental Messages in Job Advertisements and the Intentions to Apply—The Mediating Role of Organizational Attractiveness
Authors: Coelho Mafalda Pinto , Cesário Francisco , Sabino Ana , Moreira Ana
Published: March 2022

Environmental sustainability is a concept with increasing importance in the way organizations think and outline their cultures, practices, and business strategies to become more attractive. In this sense, the present study aims to understand whether organizations that publish job advertisements regarding sustainable culture and ecological concerns are perceived as more attractive and generate higher intentions to apply. A quantitative study was made with a sample comprising 443 participants. The results suggested that job advertisements with pro-environmental messages generate a higher organizational attractiveness. In addition, organizational attractiveness does not mediate the relationship between the type of advertisement (green vs. non-green) and intentions to apply. Additionally, the results suggested that individuals with greater individual environmental responsibility and intentions of pro-environmental behavior have a greater intention to apply, facing green job advertisements. The role of organizations in adopting green practices to attract and retain the best talent is also discussed, as well as suggestions for future studies.