bluuebunny/crossref_metadata_2025 huggingface dataset:
A Hybrid Model to Assess the Remaining Useful Life of Proton Exchange Membrane Fuel Cells
Authors: Du Qing , Zhan Zhigang , Wen Xiaofei , Zhang Heng , Tan Yaowen , Li Shang , Pan Mu
Published: May 2023

Durability and remaining useful life (RUL) prediction techniques are ones of the key issues for proton exchange membrane fuel cell (FC) commercialization. Herein, the performance degradation of an FC is analyzed based on the whole lifetime experimental data (up to 6500 h). The voltage model with different patterns is developed based on the voltage data, which can be easily measured. The mechanism model is developed based on the evolution of degradation indices reflecting the degradation state. However, the former is sensitive to the local and periodic changes in the voltage curve, leading to a large prediction error, and the latter requires aging data from complex and high-cost characterization, limiting the practical applications. Therefore, a hybrid prediction model combining the voltage and mechanism model is proposed where the respective weight of each model is dynamically determined based on their local prediction errors. The results reveal that the maximum errors in RUL prediction are 9.72%, 3.90% and 2.01% for the voltage, mechanism and hybrid model, respectively, and the RUL prediction results of the hybrid model are close to actual RUL when those of the voltage model are far from the accuracy zone, indicating that the hybrid model provides credible RUL predictions with the highest accuracy.
Research on the Control Strategy of Urban Integrated Energy Systems Containing the Fuel Cell
Authors: Wang Yuelong , Wang Weiqing
Published: May 2023

As a new type of energy with the advantages of high efficiency, clean and pollution-free, fuel cells have attracted the attention of many experts and scholars. The efficient utilization of fuel cells will certainly become the mainstay of energy transformation and environmental protection. However, fuel cells have low power density, soft electrical output characteristics, and significantly delayed response to sudden load changes. When fuel cells are used as power supply energy alone, the output voltage fluctuates greatly, and the power supply reliability could be higher. To increase the fuel cell’s service life in real world applications, a DC converter and an appropriate auxiliary energy storage power supply are combined to form a fuel cell hybrid power supply system that makes efficient use of the auxiliary energy storage system’s availability, enhances the power supply system’s adaptability through dynamic reconfiguration, and provides better flexibility overall. This work proposes a method for managing the energy produced by an urban integrated power supply system that includes fuel cells, supercapacitors, and solar cells. Applying the IF-THEN rule of load power and the state of charge of the supercapacitors, the power balance is adjusted between the su-percapacitors, photovoltaic cells, and fuel cells according to the defined fuzzy logic control. The intermittent nature of solar power production and the erratic nature of fuel cell output may both be mitigated using this technique, allowing the load power to operate more reliably. The simulation results show that the control strategy adopted in this paper is able to not only meet the load requirements but also reasonably allocate the functional requirements and improve the working efficiency of the system, resulting in a clear optimization effect on the system’s control. In this paper, we focus on the fuel cell hybrid power supply system design, and then we use the idea of fuzzy logic control energy management to build the structure of the fuzzy logic control system, design the fuzzy controller, determine the functions, and verify the solutions through simulation and experimentation.
“Human Trafficking Is Modern Day Slavery”: Rev. Margaret Fowler, Sex Work and Trafficking
Authors: Perkins Anna K. , Lewis Dane C.
Published: May 2023

The late Rev. Margaret Fowler, United Church Minister, was a key supporter of LGBTQ rights and a vocal advocate against human trafficking in Jamaica. As the founder of the Theodora Project, Rev. Fowler served many persons coerced into sex work or subject to sexual exploitation. She argued that human trafficking is a complex connection of economy, gender, social dynamics, law, and foreign relations. She called for the Church to be involved in anti-trafficking work as to do nothing risks “the very real possibility of Jamaica becoming another major area of sex tourism”. As we celebrate her life and ministry, we are given the opportunity to carefully excavate her perspective on the nexus among trafficking, slavery, and sex work. It does appear that her discourse follows the traditional Church line, which conflates slavery, trafficking and sex work in a fashion that views sex work as wholly coerced. In exploring the arguments that validated her important ministry in Negril, this chapter centres sex positive approaches to sex work and questions the slavery and exploitation framing that is normal in Christian discourse.
“Once upon a Time”—So What? The Importance of Place in Buddhist Narratives
Authors: Deeg Max
Published: May 2023

This paper deals with the aspect of place (space) in Buddhist narratives. Starting from the observation that narrated time is often vaguely indicated in Buddhist narratives, but places and sites of the narrated events are quite specific—although frequently introduced in a stereotypical way (“Once the Buddha dwelled in Śrāvastī …” “Once when Brahmadatta was king in Vārāṇasī …”)—the question is asked why a place is so important for and in Buddhist narratives. Based on selected examples, the argument is made that it is the “blueprint” of “early” Buddhist biographical sources, with the Buddha acting/preaching at specific places, which made these places accessible spaces where merit could be gained through “contact” with soteriologically important events in the past.
Desiring the Sweet Perfume of Closeness in the Oscillating Tawajjuh of the Letter Rāʾ
Authors: Ramlan Kris , Ludovico Ana
Published: May 2023

This article delves into the concept of tawajjuh through a poem and a prayer ascribed to the Arabic letter rāʾ, which expresses key themes in the Akbarian tradition. Using the hermeneutical approach of Ibn ʿArabī to interpret word polysemy in the texts, the article sheds light on the science of letters and key metaphysical ideas cultivated in this tradition. The letter rāʾ represents various aspects of cosmic duality and hence a strong desire for intimacy. The Arabic word tawajjuh, meaning the projection of spiritual energy, orientation, or attentiveness, refers to turning to face God. There is contemplation and continuous turning, like the phases of the moon facing the sun.
Boosting Adversarial Transferability with Shallow-Feature Attack on SAR Images
Authors: Lin Gengyou , Pan Zhisong , Zhou Xingyu , Duan Yexin , Bai Wei , Zhan Dazhi , Zhu Leqian , Zhao Gaoqiang , Li Tao
Published: May 2023

Adversarial example generation on Synthetic Aperture Radar (SAR) images is an important research area that could have significant impacts on security and environmental monitoring. However, most current adversarial attack methods on SAR images are designed for white-box situations by end-to-end means, which are often difficult to achieve in real-world situations. This article proposes a novel black-box targeted attack method, called Shallow-Feature Attack (SFA). Specifically, SFA assumes that the shallow features of the model are more capable of reflecting spatial and semantic information such as target contours and textures in the image. The proposed SFA generates ghost data packages for input images and generates critical features by extracting gradients and feature maps at shallow layers of the model. The feature-level loss is then constructed using the critical features from both clean images and target images, which is combined with the end-to-end loss to form a hybrid loss function. By fitting the critical features of the input image at specific shallow layers of the neural network to the target critical features, our attack method generates more powerful and transferable adversarial examples. Experimental results show that the adversarial examples generated by the SFA attack method improved the success rate of single-model attack under a black-box scenario by an average of 3.73%, and 4.61% after combining them with ensemble-model attack without victim models.
Simulation Analysis of the Geometric Positioning Accuracy for MEO- and HEO-SAR Satellites
Authors: Zhao Ruishan , Yang Ning , Zhang Guo , Pei Liang , Dai Jiguang , Zhang Bing
Published: May 2023

Due to the long synthetic aperture time, the large squint angle, and the large imaging width of medium Earth orbit (MEO) and high Earth orbit (HEO) SAR satellites, it is difficult to simulate the geometric positioning accuracy of MEO- and HEO-SAR satellites through the SAR image simulation methods. In this paper, one non-zero Doppler simulation method of geometric positioning accuracy was proposed without simulating SAR images. In order to simulate the geometric positioning accuracy under different errors and imaging observation conditions, the virtual simulation geometric model was constructed by the simulated satellite ephemeris and the coordinates of ground control points (GCPs). On this basis, one geometric accuracy simulation method based on mean value compensation was proposed to simulate the geometric positioning accuracy with GCPs. The experimental results showed that the impact of Doppler center frequency error and velocity error of MEO- and HEO-SAR satellites on geometric positioning accuracy is significant compared with the LEO-SAR satellites, and the maximum error they affect can reach about 1597 m. In addition, the geometric positioning accuracies of MEO- and HEO-SAR satellites with GCPs can be achieved to 1~10 m and 7~29 m, respectively.
An Improved Mutual Information Feature Selection Technique for Intrusion Detection Systems in the Internet of Medical Things
Authors: Alalhareth Mousa , Hong Sung-Chul
Published: May 2023

In healthcare, the Internet of Things (IoT) is used to remotely monitor patients and provide real-time diagnoses, which is referred to as the Internet of Medical Things (IoMT). This integration poses a risk from cybersecurity threats that can harm patient data and well-being. Hackers can manipulate biometric data from biosensors or disrupt the IoMT system, which is a major concern. To address this issue, intrusion detection systems (IDS) have been proposed, particularly using deep learning algorithms. However, developing IDS for IoMT is challenging due to high data dimensionality leading to model overfitting and degraded detection accuracy. Feature selection has been proposed to prevent overfitting, but the existing methods assume that feature redundancy increases linearly with the size of the selected features. Such an assumption does not hold, as the amount of information a feature carries about the attack pattern varies from feature to feature, especially when dealing with early patterns, due to data sparsity that makes it difficult to perceive the common characteristics of selected features. This negatively affects the ability of the mutual information feature selection (MIFS) goal function to estimate the redundancy coefficient accurately. To overcome this issue, this paper proposes an enhanced feature selection technique called Logistic Redundancy Coefficient Gradual Upweighting MIFS (LRGU-MIFS) that evaluates candidate features individually instead of comparing them with common characteristics of the already-selected features. Unlike the existing feature selection techniques, LRGU calculates the redundancy score of a feature using the logistic function. It increases the redundancy value based on the logistic curve, which reflects the nonlinearity of the relationship of the mutual information between features in the selected set. Then, the LRGU was incorporated into the goal function of MIFS as a redundancy coefficient. The experimental evaluation shows that the proposed LRGU was able to identify a compact set of significant features that outperformed those selected by the existing techniques. The proposed technique overcomes the challenge of perceiving common characteristics in cases of insufficient attack patterns and outperforms existing techniques in identifying significant features.
Robotic Intracellular Pressure Measurement Using Micropipette Electrode
Authors: Li Minghui , Qiu Jinyu , Li Ruimin , Liu Yuzhu , Du Yue , Liu Yaowei , Sun Mingzhu , Zhao Xin , Zhao Qili
Published: May 2023

Intracellular pressure, a key physical parameter of the intracellular environment, has been found to regulate multiple cell physiological activities and impact cell micromanipulation results. The intracellular pressure may reveal the mechanism of these cells’ physiological activities or improve the micro-manipulation accuracy for cells. The involvement of specialized and expensive devices and the significant damage to cell viability that the current intracellular pressure measurement methods cause significantly limit their wide applications. This paper proposes a robotic intracellular pressure measurement method using a traditional micropipette electrode system setup. First, the measured resistance of the micropipette inside the culture medium is modeled to analyze its variation trend when the pressure inside the micropipette increases. Then, the concentration of KCl solution filled inside the micropipette electrode that is suitable for intracellular pressure measurement is determined according to the tested electrode resistance–pressure relationship; 1 mol/L KCl solution is our final choice. Further, the measurement resistance of the micropipette electrode inside the cell is modeled to measure the intracellular pressure through the difference in key pressure before and after the release of the intracellular pressure. Based on the above work, a robotic measurement procedure of the intracellular pressure is established based on a traditional micropipette electrode system. The experimental results on porcine oocytes demonstrate that the proposed method can operate on cells at an average speed of 20~40 cells/day with measurement efficiency comparable to the related work. The average repeated error of the relationship between the measured electrode resistance and the pressure inside the micropipette electrode is less than 5%, and no observable intracellular pressure leakage was found during the measurement process, both guaranteeing the measurement accuracy of intracellular pressure. The measured results of the porcine oocytes are in accordance with those reported in related work. Moreover, a 90% survival rate of operated oocytes was obtained after measurement, proving limited damage to cell viability. Our method does not rely on expensive instruments and is conducive to promotion in daily laboratories.
Enhanced Optical Response of SnS/SnS2 Layered Heterostructure
Authors: Lin Der-Yuh , Hsu Hung-Pin , Liu Kuang-Hsin , Wu Po-Hung , Shih Yu-Tai , Wu Ya-Fen , Wang Yi-Ping , Lin Chia-Feng
Published: May 2023

The SnS/SnS2 heterostructure was fabricated by the chemical vapor deposition method. The crystal structure properties of SnS2 and SnS were characterized by X-ray diffraction (XRD) pattern, Raman spectroscopy, and field emission scanning electron microscopy (FESEM). The frequency dependence photoconductivity explores its carrier kinetic decay process. The SnS/SnS2 heterostructure shows that the ratio of short time constant decay process reaches 0.729 with a time constant of 4.3 × 10−4 s. The power-dependent photoresponsivity investigates the mechanism of electron–hole pair recombination. The results indicate that the photoresponsivity of the SnS/SnS2 heterostructure has been increased to 7.31 × 10−3 A/W, representing a significant enhancement of approximately 7 times that of the individual films. The results show the optical response speed has been improved by using the SnS/SnS2 heterostructure. These results indicate an application potential of the layered SnS/SnS2 heterostructure for photodetection. This research provides valuable insights into the preparation of the heterostructure composed of SnS and SnS2, and presents an approach for designing high-performance photodetection devices.
A Framework for Cybersecurity Requirements Management in the Automotive Domain
Authors: Luo Feng , Jiang Yifan , Wang Jiajia , Li Zhihao , Zhang Xiaoxian
Published: May 2023

The rapid development of intelligent connected vehicles has increased the attack surface of vehicles and made the complexity of vehicle systems unprecedented. Original equipment manufacturers (OEMs) need to accurately represent and identify threats and match corresponding security requirements. Meanwhile, the fast iteration cycle of modern vehicles requires development engineers to quickly obtain cybersecurity requirements for new features in their developed systems in order to develop system code that meets cybersecurity requirements. However, existing threat identification and cybersecurity requirement methods in the automotive domain cannot accurately describe and identify threats for a new feature while also quickly matching appropriate cybersecurity requirements. This article proposes a cybersecurity requirements management system (CRMS) framework to assist OEM security experts in conducting comprehensive automated threat analysis and risk assessment and to help development engineers identify security requirements prior to software development. The proposed CRMS framework enables development engineers to quickly model their systems using the UML-based (i.e., capable of describing systems using UML) Eclipse Modeling Framework and security experts to integrate their security experience into a threat library and security requirement library expressed in Alloy formal language. In order to ensure accurate matching between the two, a middleware communication framework called the component channel messaging and interface (CCMI) framework, specifically designed for the automotive domain, is proposed. The CCMI communication framework enables the fast model of development engineers to match with the formal model of security experts for threat and security requirement matching, achieving accurate and automated threat and risk identification and security requirement matching. To validate our work, we conducted experiments on the proposed framework and compared the results with the HEAVENS approach. The results showed that the proposed framework is superior in terms of threat detection rates and coverage rates of security requirements. Moreover, it also saves analysis time for large and complex systems, and the cost-saving effect becomes more pronounced with increasing system complexity.
WM–STGCN: A Novel Spatiotemporal Modeling Method for Parkinsonian Gait Recognition
Authors: Zhang Jieming , Lim Jongmin , Kim Moon-Hyun , Hur Sungwook , Chung Tai-Myoung
Published: May 2023

Parkinson’s disease (PD) is a neurodegenerative disorder that causes gait abnormalities. Early and accurate recognition of PD gait is crucial for effective treatment. Recently, deep learning techniques have shown promising results in PD gait analysis. However, most existing methods focus on severity estimation and frozen gait detection, while the recognition of Parkinsonian gait and normal gait from the forward video has not been reported. In this paper, we propose a novel spatiotemporal modeling method for PD gait recognition, named WM–STGCN, which utilizes a Weighted adjacency matrix with virtual connection and Multi-scale temporal convolution in a Spatiotemporal Graph Convolution Network. The weighted matrix enables different intensities to be assigned to different spatial features, including virtual connections, while the multi-scale temporal convolution helps to effectively capture the temporal features at different scales. Moreover, we employ various approaches to augment skeleton data. Experimental results show that our proposed method achieved the best accuracy of 87.1% and an F1 score of 92.85%, outperforming Long short-term memory (LSTM), K-nearest neighbors (KNN), Decision tree, AdaBoost, and ST–GCN models. Our proposed WM–STGCN provides an effective spatiotemporal modeling method for PD gait recognition that outperforms existing methods. It has the potential for clinical application in PD diagnosis and treatment.
Joint Modal Alignment and Feature Enhancement for Visible-Infrared Person Re-Identification
Authors: Lin Ronghui , Wang Rong , Zhang Wenjing , Wu Ao , Bi Yihan
Published: May 2023

Visible-infrared person re-identification aims to solve the matching problem between cross-camera and cross-modal person images. Existing methods strive to perform better cross-modal alignment, but often neglect the critical importance of feature enhancement for achieving better performance. Therefore, we proposed an effective method that combines both modal alignment and feature enhancement. Specifically, we introduced Visible-Infrared Modal Data Augmentation (VIMDA) for visible images to improve modal alignment. Margin MMD-ID Loss was also used to further enhance modal alignment and optimize model convergence. Then, we proposed Multi-Grain Feature Extraction (MGFE) Structure for feature enhancement to further improve recognition performance. Extensive experiments have been carried out on SYSY-MM01 and RegDB. The result indicates that our method outperforms the current state-of-the-art method for visible-infrared person re-identification. Ablation experiments verified the effectiveness of the proposed method.
Use and Design of Chatbots for the Circular Economy
Authors: Zota Răzvan Daniel , Cîmpeanu Ionuț Alexandru , Dragomir Denis Alexandru
Published: May 2023

The fact that advanced technologies and their economic applications have generated increasing resource costs justifies the transition from a linear approach to a circular one in order to control these costs. From this perspective, this study presents how artificial intelligence can help achieve this goal. Therefore, at the beginning of this article, we begin with an introduction and brief review of the literature on the subject. Our research procedure involved the combination of qualitative and quantitative forms of research using mixed methods. In this study, we presented and analyzed five chatbot solutions used in the field of the circular economy. The analysis of these five chatbots helped us design, in the second part of this paper, the procedures for data collection, training, development, and testing of a chatbot using various natural language processing (NLP) and deep processing (DP) techniques. Additionally, we include discussions and some conclusions regarding all aspects of the subject to see how they can help us in future studies. Furthermore, our future research with this topic will have as the goal the effective construction of a chatbot dedicated to the circular economy.
Deep Learning Aided Neuroimaging and Brain Regulation
Authors: Xu Mengze , Ouyang Yuanyuan , Yuan Zhen
Published: May 2023

Currently, deep learning aided medical imaging is becoming the hot spot of AI frontier application and the future development trend of precision neuroscience. This review aimed to render comprehensive and informative insights into the recent progress of deep learning and its applications in medical imaging for brain monitoring and regulation. The article starts by providing an overview of the current methods for brain imaging, highlighting their limitations and introducing the potential benefits of using deep learning techniques to overcome these limitations. Then, we further delve into the details of deep learning, explaining the basic concepts and providing examples of how it can be used in medical imaging. One of the key strengths is its thorough discussion of the different types of deep learning models that can be used in medical imaging including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial network (GAN) assisted magnetic resonance imaging (MRI), positron emission tomography (PET)/computed tomography (CT), electroencephalography (EEG)/magnetoencephalography (MEG), optical imaging, and other imaging modalities. Overall, our review on deep learning aided medical imaging for brain monitoring and regulation provides a referrable glance for the intersection of deep learning aided neuroimaging and brain regulation.
Channel Characterization and Modeling for 6G UAV-Assisted Emergency Communications in Complicated Mountainous Scenarios
Authors: Zhang Zhaolei , Liu Yu , Huang Jie , Zhang Jingfan , Li Jingquan , He Ruisi
Published: May 2023

Regarding the new demands and challenges of sixth-generation (6G) mobile communications, wireless networks are undergoing a significant shift from traditional terrestrial networks to space-air-ground-sea-integrated networks. Unmanned aerial vehicle (UAV) communications in complicated mountainous scenarios are typical applications and have practical implications, especially in emergency communications. In this paper, the ray-tracing (RT) method was applied to reconstruct the propagation scenario and then acquire the wireless channel data. Channel measurements are also conducted in real mountainous scenarios for verification. By setting different flight positions, trajectories, and altitudes, channel data in the millimeter wave (mmWave) band was obtained. Important statistical properties, such as the power delay profile (PDP), Rician K-factor, path loss (PL), root mean square (RMS) delay spread (DS), RMS angular spreads (ASs), and channel capacity were compared and analyzed. The effects of different frequency bands on channel characteristics at 3.5 GHz, 4.9 GHz, 28 GHz, and 38 GHz bands in mountainous scenarios were considered. Furthermore, the effects of extreme weather, especially different precipitation, on the channel characteristics were analyzed. The related results can provide fundamental support for the design and performance evaluation of future 6G UAV-assisted sensor networks in complicated mountainous scenarios.
Experimental Demonstration of a Visible Light Communications System Based on Binary Frequency-Shift Keying Modulation: A New Step toward Improved Noise Resilience
Authors: Beguni Cătălin , Done Adrian , Căilean Alin-Mihai , Avătămăniței Sebastian-Andrei , Zadobrischi Eduard
Published: May 2023

Visible light communications (VLC) are an emerging technology that is increasingly demonstrating its ability to provide wireless communications in areas where radio frequency (RF) technology might have some limitations. Therefore, VLC systems offer possible answers to various applications in outdoor conditions, such as in the road traffic safety domain, or even inside large buildings, such as in indoor positioning applications for blind people. Nevertheless, several challenges must still be addressed in order to obtain a fully reliable solution. One of the most important challenges is focused on further improving the immunity to optical noise. Different from most works, where on–off keying (OOK) modulation and Manchester coding have been the preferred choices, this article proposes a prototype based on a binary frequency-shift keying (BFSK) modulation and non-return-to-zero (NRZ) coding, for which the resilience to noise is compared to that of a standard OOK VLC system. The experimental results showed an optical noise resilience improvement of 25% in direct exposure to incandescent light sources. The VLC system using BFSK modulation was able to maintain a maximum noise irradiance of 3500 µW/cm2 as compared with 2800 µW/cm2 for the OOK modulation, and an improvement of almost 20% in indirect exposure to the incandescent light sources. The VLC system with BFSK modulation was able to maintain the active link in an equivalent maximum noise irradiance of 65,000 µW/cm2, as opposed to the equivalent 54,000 µW/cm2 for the OOK modulation. Based on these results, one can see that based on a proper system design, VLC systems are able to provide impressive resilience to optical noise.
Intercultural Opportunities to Evoke Empathy toward Minority Citizens: Online Contact with Chinese International Students at a Japanese Women’s University
Authors: Sugino Chie
Published: May 2023

Exchanges with Chinese students in Japan, who comprise the majority of international students, may be a worthwhile intercultural experience for Japanese students. However, because of the lack of contact between Chinese and Japanese students on campus, many Japanese students tend to form impressions of China through the media. This study aims to explore the factors influencing Japanese students’ positive attitudes toward Chinese students and the former’s awareness of stereotypes based on an online interview in Japanese conducted during an elective political science course. This study adopts a qualitative research methodology to analyze students’ written reflections contextually. The content analysis revealed that Chinese students’ “Japaneseness”, characterized by Japanese language fluency, affected the perceptions of Japanese students, who changed their attitudes toward Chinese people and intercultural exchanges. Further discussion is necessary to determine whether Japanese students’ preferences for “Japanese-like” international students may create new stereotypes rather than enhance diversity benefits. The findings illustrate the need for future research and practice on how students with no experience in communicating with minority citizens can overcome ethnocentric perspectives and embrace diversity.
Home Birth in Portugal—A Comprehensive Analysis Based on Official Statistical Data
Authors: Pintassilgo Sónia , Santos Mário J. D. S. , Trindade Inês , Neves Dulce Morgado
Published: May 2023

To date, there are no comprehensive analyses of the official data on home births in Portugal that consider other determinants beyond place of birth, such as the conditions in which births occur or the mothers’ social profiles. The aims of this article were: (1) to describe the characteristics of childbirth in Portugal according to the place of birth, and (2) to analyse the association between home birth assistance and perinatal, neonatal, and infant mortality rates. We performed a descriptive, correlational analysis of the official datasets of live births in Portugal (census-based) produced by the National Institute of Statistics. In 2020, home births had more similarities with hospital births than to births occurring in any “other place”. Furthermore, considering the 1995–2020 timeframe, home births with specialised assistance were negatively correlated with perinatal, neonatal, and infant mortality, and home births with non-specialised professional assistance or those that were unassisted showed a positive correlation with these mortality rates. Home births are heterogenous, and merely referencing the place of birth does not provide enough information. Although it recommended further investigation, this analysis pointed to the need to assure a specific, systematic evaluation of the quality of care in home births that allows for the consistent assessment and improvement of its safety.
Balancing Thermal Comfort and Energy Consumption in Residential Buildings of Desert Areas: Impact of Passive Strategies
Authors: Khechiba Abir , Djaghrouri Djamila , Benabbas Moussadek , Leccese Francesco , Rocca Michele , Salvadori Giacomo
Published: May 2023

Modern building materials using reinforced concrete are considered the most popular in the production of housing in Algeria, specifically in desert areas such as the city of Ouargla, which is characterized by its hot and arid climate. These dwellings must be more adaptable to this difficult climate. An example is the Ouargla Ksar, which contains traditional dwellings that have proven their effectiveness in terms of the heat problem, as has been revealed in several previously conducted studies, but these dwellings have decreased in demand as they are not suitable for contemporary urban life. Therefore, the aim of this study is to improve the performance of the most recognized house typologies in the city of Ouargla in terms of thermal comfort and energy consumption by using passive strategies. In this regard, we used a research methodology based on field measurements and model simulations wherein we adopted TRNSYS 17 to determine the most often encountered problems. The simulated model was validated by statistical correlation; afterward, a simulation of a full year was run, during which many aspects of construction were studied and compared, such as insulation, the mass of the roof and walls, dimensions and types of windows, orientation, and solar shading. The results show that the studied modern house can be considered inappropriate for a desert climate, and the use of solar shading combined with insulated walls and roof allows for an increase of 35% in annual thermal comfort hours (−0.5 ≤ PMV ≤0.5) and for a 22.73% reduction in the energy consumption. We then compared the simulated scenarios with a traditional house characterized by a bioclimatic architectural design that we used as a reference building. The obtained results may be useful in guiding both refurbishment interventions on existing buildings and the design of new ones. Although the simulated interventions have been widely studied in the literature, it is very important to determine their impact on the perception of the indoor environment and on the energy consumption in this specific geographic area.
The Climate-Proof Planning towards the Ecological Transition: Isola Sacra—Fiumicino (Italy) between Flood Risk and Urban Development Prospectives
Authors: Mariano Carmela , Marino Marsia
Published: May 2023

The increasing concentration of people and economic activities in urban areas intensifies the pressure on the urban environment and hastens environmental degradation processes. Therefore, addressing the impact of climate change on cities is an urgent matter that demands the immediate attention of policymakers, researchers, and the general public, not only for its environmental but also socioeconomic ramifications. Within this framework, the research focuses on the effects of climate change on coastal cities and aims to define guidelines for the innovation of urban planning tools from a climate-proof perspective. Specifically, the study analyses the effects of two phenomena related to climate change: heavy rainfall, river overflow, and sea-level rise, to establish a replicable approach for updating the documents that constitute the cognitive framework of the Local Urban Plan through the preparation of a multi-risk map (that considers different time horizons) and consequently the prescriptive apparatus of the Plan through the definition of a toolkit of site-specific design actions oriented towards urban adaptation. The proposed methodology is tested on the case study of Isola Sacra, Fiumicino (Italy), and is intended to apply to other territorial contexts. The aim of this study, in accordance with the principles of the Disaster Risk Reduction (DRR) framework, is to furnish theoretical-methodological and operational guidelines to translate risk knowledge, despite its limitations due to variables and uncertainties in measurements, into effective urban adaptation measures.
The Green Consumption Behavior Process Mechanism of New Energy Vehicles Driven by Big Data—From a Metacognitive Perspective
Authors: Chen Jingyang , Liu Qin
Published: May 2023

Green consumption behavior is the embodiment of pro-environmental behavior, which is of great value to curb carbon emissions. However, the existing research on the model construction and quantitative analysis of the psychological process of green consumption behavior needs to be further explored. Therefore, on the basis of green consumption behavior and metacognitive theory, this study constructs a conceptual model of a psychological process with a psychological control source, green consumption attitude, three aspects of metacognition, and green consumption behavior and puts forward the hypothesis of an action mechanism. This study combines text mining technology and expert knowledge to establish a user review mining dictionary and mines the variables in the quantitative conceptual model through word embedding to test empirically the mechanism hypothesis. The results show that psychological control source has a significant impact on green consumption behavior, and green consumption attitude plays a partial mediating role between them. Metacognitive knowledge plays a moderating role between the psychological control source and green consumption behavior; metacognitive experience plays a moderating role between the psychological control source and green consumption attitude. Metacognitive monitoring plays a moderating role between green consumption attitude and green consumption behavior. In view of the above research results, we put forward the following countermeasures and suggestions: For organizations, it is necessary to identify green consumption groups, attach importance to green consumption experience, perform well in green marketing, and improve the competitiveness of green products; for decision makers, it is necessary to control strictly the industry standards of the green product market and perform well not only in the quality supervision of green products but also in the post-market construction of green products.
Grid-Following Inverter-Based Resource: Numerical State–Space Modeling
Authors: Alassaf Abdullah , Alsaleh Ibrahim , Alateeq Ayoob , Alafnan Hamoud
Published: May 2023

In the pursuit of a sustainable electric power system, the integration of renewable energy sources and distributed energy resources is gradually replacing traditional power generation. These new resources are integrated into the grid via inverters, which, despite their efficient performance, present dynamic challenges to the power grid when implemented on a large scale. To maintain grid stability and ensure effective regulation during abnormal operations, various modeling techniques are necessary; while the dynamics of inverter-based resources (IBRs) are traditionally modeled by transfer functions, this paper sheds light on differential-algebraic equations (DAEs) modeling and numerical integration methods. The inherent limitations of transfer function modeling stem from its restricted applicability, as it is exclusively suitable for linear and time-invariant systems. In contrast, the nonlinear DAEs of the IBR system can be converted into a state–space form, which offers a versatile framework for modeling, evaluating, and designing a diverse array of systems. In addition to being compatible with time-varying systems and multiple-input multiple-output systems, the state–space technique may incorporate saturation and dead zone characteristics into the dynamic model. Our research focuses on IBR modeling in a grid-following scheme, which is current-controlled and synchronized to the grid by a phase-locked loop (PLL). The presented state–space model consists of the inverter, grid, control, and designed PLL. Beyond the discussion of its application to IBRs, the presented method holds the potential to solve a wide range of DAEs. The proposed model is compared with a benchmarked system.
Does City Honor Drive Companies to Remove the Mask of Greenwashing? Evidence from the National Civilized City Program in China
Authors: Zhou Maochun , Wu Shangrong
Published: May 2023

At present, many enterprises are facing the dilemma of green management and greenwashing behavior is becoming increasingly serious. The honor of a city is an intangible asset that can bring opportunities for city development and enhance the recognition and loyalty of stakeholders within the city. At present, there are few studies on the impact of city reputation on corporate green behavior. This paper collected data on Chinese A-share listed enterprises from 2009 to 2019 and explored the relationship between the two using a double-difference model. The robustness of the hypotheses was verified by using the parallel trend test, placebo test, and PSM-DID. It was finally concluded that city honor inhibits corporate greenwashing behavior through two pathways, strengthening environmental regulation and stimulating corporate social responsibility, and it has a spillover effect between regions. Moreover, this effect is more obvious in regions with a high economic development level and a high degree of marketization, and it also shows a significant role in state-owned enterprises and enterprises with high total assets. This paper provides a theoretical basis for studying the relationship between city honor and corporate greenwashing behavior, and it also acts as a reference for standardizing enterprises’ environmental behavior and improving the quality of environmental information disclosure of enterprises.
Parameter Extraction of Solar Photovoltaic Modules Using a Novel Bio-Inspired Swarm Intelligence Optimisation Algorithm
Authors: Vais Ram Ishwar , Sahay Kuldeep , Chiranjeevi Tirumalasetty , Devarapalli Ramesh , Knypiński Łukasz
Published: May 2023

For extracting the equivalent circuit parameters of solar photovoltaic (PV) panels, a unique bio-inspired swarm intelligence optimisation algorithm (OA) called the dandelion optimisation algorithm (DOA) is proposed in this study. The suggested approach has been used to analyse well-known single-diode (SD) and double-diode (DD) PV models for several PV module types, including monocrystalline SF430M, polycrystalline SG350P, and thin-film Shell ST40. The DOA is adopted by minimizing the sum of the squares of the errors at three locations (short-circuit, open-circuit, and maximum power points). Different runs are conducted to analyse the nature of the extracted parameters and the V–I characteristics of the PV panels under consideration. Obtained results show that for Mono SF430M, the error in the SD model is 2.5118e-19, and the error in the DD model is 2.0463e-22; for Poly SG350P, the error in the SD model is 9.4824e-21, and the error in the DD model is 2.1134e-20; for thin-film Shell ST40, the error in the SD model is 1.7621e-20, and the error in DD model is 7.9361e-22. The parameters produced from the suggested method yield the least amount of error across several executions, which suggests its better implementation in the current situation. Furthermore, statistical analysis of the SD and DD models using DOA is also carried out and compared with two hybrid OAs in the literature. Statistical results show that the standard deviation, sum, mean, and variance of various PV panels using DOA are lower compared to those of the other two hybrid OAs.
Examining the Relationship between Transportation Infrastructure, Urbanization Level and Rural-Urban Income Gap in China
Authors: Chanieabate Meseret , He Hai , Guo Chuyue , Abrahamgeremew Betelhem , Huang Yuanji
Published: May 2023

The development of transportation infrastructure plays a pivotal role in the regional economy from multiple dimensions. The aim of this paper is to examine the relationship between transportation infrastructure development and income inequality in urban and rural areas of China. The study utilizes panel data from 30 provinces, spanning the years 2010 to 2020, and employs the spatial Dubin model to measure and test the impact of transportation infrastructure on the urban-rural income gap. Furthermore, an intermediary effect test method is used to investigate the potential mediating effect of urbanization in this relationship. The results indicate that transportation infrastructure has a significantly negative direct, indirect, and total effect on the urban-rural income gap, with the indirect effect being greater than the direct effect. This suggests that transportation infrastructure can effectively reduce income disparities, with a noticeable spatial spillover effect. The level of urbanization plays a significant intermediary effect on the effect of transportation infrastructure on the urban-rural income gap, highlighting the role of transportation infrastructure in improving urbanization and narrowing income disparities. These findings underscore the importance of enhancing both the level of urbanization and cooperation between neighbouring regions in order to maximize the benefits of transportation infrastructure development for reducing income disparities and promoting regional balance in China.
Sustainable Thematic Investing: Identifying Opportunities Based on an Analysis of Stewardship Reports
Authors: Nel Kara , Mans-Kemp Nadia , Erasmus Pierre D.
Published: May 2023

Globally, a growing number of stakeholders recognise that sustainability determines success on multiple levels. Therefore, asset managers in developing and emerging countries increasingly focus on sustainable investment opportunities. While institutional investors largely centred on governance considerations pre-2020, the Coronavirus pandemic highlighted substantial social and environmental concerns at companies worldwide. As South Africa is the most unequal country globally according to the World Bank, decisions made by local institutional investors can have significant implications for individuals and environments where capital is invested. The objectives of this study were hence to analyse the sustainability themes on which South African asset managers focused in their stewardship reports and to explore the Sustainable Development Goals (SDGs) that they addressed through their investment mandates. A content analysis was performed on stewardship reports that were published in 2020 and 2021 to consider the impact of the Coronavirus pandemic. The findings indicate that prioritised sustainability themes include climate action, infrastructure development and social considerations. The considered asset managers accordingly focused on addressing climate action (SDG 13), decent work and economic growth (SDG 8), and affordable and clean energy (SDG 7). Promising investment opportunities in companies that address key social issues, including the health and well-being of society (SDG 3) and broadening access to quality education (SDG 4) were also highlighted. The leaders of local investee companies are thus encouraged to ensure concise, transparent reporting on these material matters to enhance communication and engagement with institutional investors and other key stakeholders. This study offers a novel perspective on sustainable thematic investing in a highly unequal society.
Outdoor Thermal Comfort Integrated with Energy Consumption for Urban Block Design Optimization: A Study of the Hot-Summer Mediterranean City of Irbid, Jordan
Authors: Khraiwesh Mohammad Mazen , Genovese Paolo Vincenzo
Published: May 2023

With an increasing awareness of urban health and well-being, this study highlights the growing importance of considering environmental quality in urban design beyond mere energy performance. This study integrates outdoor and indoor quality by investigating the effect of design parameters at an urban block scale (building form restricted to width and length as rectangular and square, building orientation, block orientation, building combination, building height, facade length, built-up percentage, setbacks, and canyon aspect ratio) on outdoor thermal comfort and energy use intensity. In addition, it explains the different correlations between outdoor thermal comfort and energy use intensity in different urban block designs in a hot-summer Mediterranean climate in Jordan. The study adopts a performance-driven approach using simulation tools of Ladybug, Honeybee, Dragonfly, and Eddy3d plugins across the grasshopper interface and evaluates 59 different urban block designs with nine different orientations (0°, 1°, 45°, 85°, 87°, 90°, 355°, 358°, and 359°). The results show that there is a positive correlation between the canyon aspect ratio and the environmental performance of the urban block designs. North–south street canyons are more effective at enhancing microclimates. Negatively increasing the street aspect ratio by more than four affected outdoor thermal comfort by increasing longwave radiation. Further results suggest a positive correlation between the compactness of urban blocks and their environmental performance, with north–south street canyons found to be more effective in enhancing microclimates. The study emphasizes the need to understand the distribution of open spaces formed by buildings and to strike a balance between day and night, as well as summer and winter conditions in outdoor spaces.