bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Anomaly Network Detection Based on Self-Attention Mechanism
Authors: Hu Wanting , Cao Lu , Ruan Qunsheng , Wu Qingfeng
Published: May 2023

Network traffic anomaly detection is a key step in identifying and preventing network security threats. This study aims to construct a new deep-learning-based traffic anomaly detection model through in-depth research on new feature-engineering methods, significantly improving the efficiency and accuracy of network traffic anomaly detection. The specific research work mainly includes the following two aspects: 1. In order to construct a more comprehensive dataset, this article first starts from the raw data of the classic traffic anomaly detection dataset UNSW-NB15 and combines the feature extraction standards and feature calculation methods of other classic detection datasets to re-extract and design a feature description set for the original traffic data in order to accurately and completely describe the network traffic status. We reconstructed the dataset DNTAD using the feature-processing method designed in this article and conducted evaluation experiments on it. Experiments have shown that by verifying classic machine learning algorithms, such as XGBoost, this method not only does not reduce the training performance of the algorithm but also improves its operational efficiency. 2. This article proposes a detection algorithm model based on LSTM and the recurrent neural network self-attention mechanism for important time-series information contained in the abnormal traffic datasets. With this model, through the memory mechanism of the LSTM, the time dependence of traffic features can be learned. On the basis of LSTM, a self-attention mechanism is introduced, which can weight the features at different positions in the sequence, enabling the model to better learn the direct relationship between traffic features. A series of ablation experiments were also used to demonstrate the effectiveness of each component of the model. The experimental results show that, compared to other comparative models, the model proposed in this article achieves better experimental results on the constructed dataset.
Antiperspirant and Antibacterial Activities of Curcuma xanthorrhiza Extract as a Potential Alternative Treatment for Hyperhidrosis
Authors: Sidek Nurliyana A. M. , Husain Khairana , Buang Fhataheya , Mohd Said Mazlina
Published: May 2023

Hyperhidrosis is a condition characterized by excessive sweating that affects at least 5% of the world’s population. It is normally associated with unpleasant body odour which requires continuous maintenance throughout life. Antiperspirants and deodorants are the first-line treatments for hyperhidrosis. However, association of this class of product with the risk of other diseases has increased the search for an effective antiperspirant from natural sources. This study aimed to investigate the antibacterial and antiperspirant activities of Curcuma xanthorrhiza Roxb. Using an in vitro microbial assay against specific bacteria responsible for body odour and rat foot pad analysis. Quality control of the fractionated extract was conducted using reversed-phase HPLC based on two active markers: xanthorrhiza and curcumin. Toxicity tests were conducted based on the OECD guidelines (50–2000 mg/kg). Inhibition zone, MIC, and MBC values of the hexane fraction of C. xanthorrhiza showed equivalent antibacterial activity to positive control (p > 0.05). No swelling, redness, or rashes were observed at the injection area throughout the study. Treatment with 40, 80, and 160 mg/kg of the extract significantly decreased the sweat excretion up to 79.34% (p < 0.05) after 15 min compared to negative control. Histopathology analysis showed the reduced size of the secretory units in plantar sweat glands post treatment compared to negative control. In conclusion, the hexane fraction of C. xanthorrhiza is able to reduce sweat excretion in a rat model and inhibit the growth of bacteria causing body odour.
Sustainable and Rapid Determination of Two Halogenated Pesticides in a Commercial Formulation by Solid Phase Microextraction and Liquid Phase Chemical Ionization Mass Spectrometry
Authors: Marittimo Nicole , Grasselli Genny , Arigò Adriana , Famiglini Giorgio , Palma Pierangela , Saeed Mansoor , Perry Simon , Navarro Pablo , Clarke Phil , Brittin Mark , Cappiello Achille
Published: May 2023

This work presents a sustainable and rapid method for halogenated pesticide analysis without chromatographic separation. The system is composed of a microfluidic open interface (MOI) for solid-phase microextraction (SPME) liquid phase desorption, connected to a liquid electron ionization mass spectrometry interface (LEI-MS). Either a triple quadrupole mass spectrometer (QQQ-MS/MS, (low-resolution) or a quadrupole-time-of-flight tandem MS (QTOF-MS/MS, high-resolution) were employed, each operating in negative chemical ionization (NCI) conditions. The flow rate used (100 µL/min) to rapidly empty the MOI chamber (approximately 2.5 µL) is reduced to the working flow rate of the LEI interface (500 nL/min) by a passive flow splitter (PFS). NCI is an appropriate ionization technique for electrophilic compounds, increasing specificity and reducing background noise. Two halogenated pesticides, dicamba and tefluthrin, were extracted simultaneously from a commercial formulation matrix (CF) using a C18 fiber by direct immersion (3 min under vortex agitation). Analyte desorption occurred in static conditions inside MOI filled with acidified acetonitrile (ACN) (0.2% phosphoric acid, PA). Extraction and desorption steps were optimized to increase efficiency and accelerate the process. No chromatographic separation was involved; therefore, the system fully exploited MS/MS selectivity and HRMS accuracy demonstrating good linearity, repeatability and limits of detection (LODs) and limits of quantification (LOQs) in the pg/mL range (50 and 500 pg/mL, respectively). Low-resolution experiments showed that matrix effects (ME) did not affect the results. The fast workflow (5 min) makes the system suitable for high-throughput analysis observing the principles of green analytical chemistry (GAC).
The Riddle of Community Resilience: Neighborhood Struggles for and against Clearance in Israel 1950s–1970s
Authors: Kabalo Paula
Published: May 2023

Resilience is a concept of concern to researchers of humanitarian disasters and crises as well as relief organizations and agencies. Compelling findings in recent studies demonstrate the centrality of social networks and connections, among individuals and groups, in powering rehabilitation processes after disasters and crises. Derived from this perspective is the concept of community resilience, based on Ozawa’s definition as groups and individuals working together to minimize the adverse consequences of crisis. This study aims to demonstrate that the postulate that communities can attain their objectives if only they “work together”, irrespective of their material resources, remains valid in situations of protracted crisis such as economic distress or lengthy struggle against economically or politically powerful elements. I wish to substantiate and prove this hypothesis by micro-historical reconstruction and analysis that sheds light on practices used by local neighborhood committees in view of protracted crises resulting from severe poverty and clearance plans. The article is based on two case studies harvested from the history of Israel. The first looks at Nahalat Ahim, a neighborhood in the southern segment of the Nahlaot cluster of neighborhoods in central Jerusalem, and the second, at the Shemen Beach (Hof Shemen) neighborhood of Haifa. The advantage of historical research, which by nature deals with matters already concluded, lies in its retrospective gaze on ways members of a community in crisis coped. An after-the-fact contemplation such as this, allows us to identify additional variables that may enhance our understanding of the community-resilience phenomenon in current contexts as well.
The Concept and Measurement of Violence and Abuse in Health and Justice Fields: Toward a Framework Aligned with the UN Sustainable Development Goals
Authors: Blom Niels , Fadeeva Anastasia , Barbosa Estela Capelas
Published: May 2023

Violence reduction is a United Nations (UN) sustainable development goal (SDG) and is key to both public health and criminology. The collaboration between these fields has the potential to create and improve prevention strategies but has been hampered by the usage of different definitions and measurements. This paper explores the definitions and measurements of violence by the World Health Organization, UN, and Council of Europe to arrive at a harmonized framework aligned with the SDGs. Violence and abuse are defined by these organizations as intentional actions that (are likely to) lead to harm, irrespective of physicality or legality. When recording violence and abuse, health- and justice-based administrative systems use different codes which cannot directly be translated without resorting to broad overarching categories. Additionally, the identification of the number of victims, perpetrators, and events is challenging in these systems due to repeat victimization/offending, multiple victims/perpetrators, and multiple engagements with services associated with a single event. Furthermore, additional information on the victims (e.g., ethnicity) and events needs to be registered to evaluate progress toward the SDGs. We propose a framework to record violence that includes individual and event identifiers, forms of violence and abuse (including physical, sexual, and psychological), harm, and individual and event characteristics.
Old but Gold: The Surgeon’s Affair to Manage Inguinal Hernia
Authors: Giuffrida Mario , Nita Gabriela Elisa , Biolchini Federico
Published: May 2023

Purpose: Inguinal hernia repair is a common surgical procedure. It was widely reported worldwide during the COVID-19 pandemic. To manage the lack of anesthesiologists, we have introduced a new protocol to manage inguinal hernia repair. Methods: This protocol is the result of a strong collaboration between surgeons and anesthesiologists. It was based on EHS recommendations and the well-described percutaneous ilioinguinal–iliohypogastric and genitofemoral nerves block. Results: More than 400 patients have been treated at our institution. The application of the protocol has led to a sensible reduction in initially planned spinal anesthesia. The complications traditionally related to spinal anesthesia have not been reported in 80% of the patients. Only three patients required the infusion of atropine or flumazenil without the need to involve anesthesiologist. Conclusion: The application of our protocol seems promising. Preliminary results have shown the safety and efficacy of percutaneous ilioinguinal–iliohypogastric and genitofemoral nerves block. The combination of this kind of anesthesia with wound protector and adequate postoperative pain control can lead to a reproducible system avoiding the not strictly necessary presence of an anesthesiologist. The changes that have occurred in the healthcare system in recent years should be new opportunities for the improvement of resources and results.
The Antarctic Scallop Adamussium colbecki Is Unable to Transcriptomically Respond to Captivity and Moderate Thermal Stress
Authors: Greco Samuele , Gaetano Anastasia Serena , Manfrin Chiara , Capanni Francesca , Santovito Gianfranco , Pallavicini Alberto , Giulianini Piero Giulio , Gerdol Marco
Published: May 2023

Adamussium colbecki is a scallop endemic of the Antarctic Ocean, the only modern survivor of the Adamussiini tribe and one of the few bivalves living in polar environments. Compared with other Antarctic animals, very little is known concerning the evolutionary adaptations which allow this species to thrive at sub-zero temperatures. Due to its local abundance and sensitivity to environmental changes, A. colbecki is an interesting model for studying the effects of pollution and climate change in the Antarctic Ocean. Here, we report, for the first time, the application of transcriptomic tools to the study of the effects of a short-to-medium term exposure to a +1.5 °C water temperature increase on three tissues. Although this approach did not highlight any significant change in response to thermal stress, we observed slight alterations in energetic metabolism and nutrient adsorption in the digestive gland, most likely linked with stabling in experimental tanks. The results of our study suggest that A. colbecki may be particularly vulnerable to the effects of climate change due to its complete inability to adapt to temperature increase at the transcriptomic level.
Does Wolf Management in Latvia Decrease Livestock Depredation? An Analysis of Available Data
Authors: Šuba Jurģis , Žunna Agrita , Bagrade Guna , Done Gundega , Ornicāns Aivars , Pilāte Digna , Stepanova Alda , Ozoliņš Jānis
Published: May 2023

In Latvia, livestock depredation by wolves has increased during the last two decades. Most of the attacks occur in summer and autumn during wolf hunting season. Use of effective preventive measures in Latvia is low, and farmers primarily rely on wolf hunting as a depredation reduction measure. The total numbers of wolf attacks and number of affected sheep per year in regional forest management units were analyzed in relation to the estimated wolf density, extent of culling, and proportion of juveniles, as well as the sheep density and estimated number of wild prey animals. The response variables (number of attacks and affected sheep per year) were modelled using a negative binomial regression, testing the effects of every covariate separately and building models from the significant covariates. The depredation level was related to sheep density and estimated wolf population size. No reducing effect was found for culling, and an even greater depredation rate was expected when the proportion of culled wolves increased. In addition, no significant effect was associated with the other covariates. However, greater numbers of affected sheep were expected at higher red deer density, suggesting increased opportunistic livestock depredation when red deer locally outcompete roe deer, the preferred wolf prey in Latvia.
The Impact of Ownership Structure on Technological Innovation and Energy Intensity: Evidence from China
Authors: Zhang Xiekui , Yu Baocheng
Published: May 2023

Environmental pollution and climate warming have become global issues affecting human life, and the burning of fossil fuels is a major source of greenhouse gases. Ownership structure is related to energy efficiency and a change in ownership structure has a significant potential for energy saving. However, few papers have studied the impact of ownership structure on energy intensity from the perspective of technological innovation in the past. Based on panel data from 29 Chinese provinces from 2005 to 2020, we systematically investigate the impact of industrial department ownership structure on energy intensity and study the function of technological innovation in this relationship from the perspective of ownership heterogeneity by using empirical models including ordinary least squares, two-way fixed effects and random effects. The empirical results of this study reveal three findings. First, as the proportion of state-owned industrial enterprises increases by one unit, energy intensity increases by 0.803 units. However, as the proportion of Hong Kong, Macao and Taiwan-invested industrial enterprises, private industrial enterprises and foreign-invested industrial enterprises increases by one unit, energy intensity decreases by 0.847 units and 0.549 units. Second, R&D activities, FDI, capital intensity and exports can significantly reduce energy intensity, but imports can increase energy intensity. Third, the ownership structure can affect energy intensity by influencing R&D expenditure. The increase in the proportion of state-owned industrial enterprises can reduce R&D expenditure, but results in the opposite situation in private firms. Foreign-invested enterprises can reduce energy intensity by making more use of the parent company’s technology. Based on the above empirical results, we propose suggestions to reduce energy intensity, which can provide reference for government to formulate more effective energy policies and realize sustainable development.
Acceptance of Mobile Learning Technology by Teachers: Influencing Mobile Self-Efficacy and 21st-Century Skills-Based Training
Authors: Dahri Nisar Ahmed , Al-Rahmi Waleed Mugahed , Almogren Abeer S. , Yahaya Noraffandy , Vighio Muhammad Saleem , Al-maatuok Qusay , Al-Rahmi Ali Mugahed , Al-Adwan Ahmad Samed
Published: May 2023

This study aimed to investigate the factors influencing the acceptance of mobile learning technology for 21st-century skills-based training among teachers in Saudi Arabia and Pakistan. This study adopted the Unified Theory of Acceptance and Use of Technology (UTAUT) model, which included constructs such as performance expectancy, effort expectancy, facilitating conditions, social influence, mobile self-efficacy, student self-efficacy, behavioural intention, 21st-century skills-based training, and creative thinking skills. A survey was conducted with 619 teachers from Saudi Arabia and Pakistan who participated in a two-week mobile learning-based training session. The data were analysed using structural equation modeling (SEM). The results show that all hypotheses were supported, indicating a positive relationship between the constructs and the acceptance and use of mobile learning technology for 21st-century skills-based training. This study’s findings suggest that by emphasising factors such as performance expectancy, effort expectancy, facilitating conditions, social influence, mobile self-efficacy, and student self-efficacy when designing mobile learning interventions, teachers will be more likely to accept and use mobile learning technology for 21st-century skills-based training and contributed to sustainability by providing increased access to quality education.
MCDM-Based Ranking and Prioritization of Fisheries’ Risks: A Case Study of Sindh, Pakistan
Authors: Mehak Ana , Mu Yongtong , Mohsin Muhammad , Zhang Xing-Can
Published: May 2023

The fisheries sector in developing countries, including Pakistan, faces various risks that have not been comprehensively studied and addressed through policy measures. This study aims to analyze fisheries’ risks in Pakistan by following a risk management process and using statistical analysis. The data was collected through structured questionnaire surveys, and subsequently, fuzzy analytic hierarchy process (fuzzy AHP) and importance performance analysis (IPA) were utilized to analyze the data. The study ranked the top five risks in order of importance as management, technical, economic, environmental, and occupational risks. The study also identified high-importance, low-performance sub-factors, including inadequate legislative implementation, overexploitation, and infrastructure shortages. It was found that there is low risk perception and inadequate management regulations in the sector. The findings suggest that risk management strategies, such as risk avoidance and risk transfer, can be used to mitigate fisheries’ risks. The study highlights the need for policy measures to revitalize the fisheries sector in Pakistan and provides recommendations for further research.
Institutional Collective Actions for Culture and Heritage-Led Urban Regeneration: A Qualitative Comparative Analysis
Authors: Piperno Alessandro , Iaione Christian , Kappler Luna
Published: May 2023

Institutional collective actions (ICAs) provide a fascinating framework for comprehending collaborative urban initiatives. We defined ICAs as groups of people and organizations working together to promote a shared goal they could not pursue on their own. This study provides an empirical justification of why particular characteristics support the success of ICAs and why others fail. We restrict our analysis to culture-and-heritage-led urban regeneration initiatives and analyze the combinations of conditions under which these initiatives achieve their objectives. Adopting an integrated strategy, we studied prerequisites and critical elements that affect the success of collaborative actions, such as entrepreneurship, the enabling role of institutional capacity, multi-stakeholder involvement, and co-governance. Therefore, we compared sixteen culture-and-heritage-led urban regeneration initiatives in Europe as examples of ICAs in the urban context. We utilized fsQCA, fuzzy set qualitative comparative analysis, as a method that enabled us to define the configurations (combinations of factors) that determine the performances of urban regeneration actions. The results demonstrate that a variety of elements are necessary for developing collaborative initiatives and that three different recipes can be developed. In addition, this study contributes to the body of knowledge on institutional collective actions in two ways: (1) by providing empirical evidence of why specific conditions need to be considered when developing collective actions and (2) by showing how specific conditions interact and explain the performance of ICAs.
The Spatio-Temporal Distribution of the Freshwater Bivalves Corbicula fluminea and Dreissena polymorpha in the Lower Sector of the Danube River and the Danube Delta
Authors: Pavel Ana Bianca , Gheablau Catalin , Kreuter Sylvain , Catianis Irina , Scrieciu Albert , Enache Alin
Published: May 2023

The objective of this study is to provide an updated account of the distribution history of two invasive molluscs, Corbicula fluminea and Dreissena polymorpha, both in Europe and worldwide. In addition to this, the study also intends to review their ecological requirements to gain a better understanding of their invasive potential and distribution dynamics. Specifically, the study focuses on updating the distribution and ecological characteristics of these freshwater bivalves in the lower sector of the Danube River and the lakes of the Danube Delta. The purpose is to better understand their invasive and distribution dynamics and to develop effective measures to limit their spread in the future. To achieve this, environmental proxies such as sediment particle size and Total Organic Carbon (TOC) concentrations were used to assess their tolerances. However, the results did not show a significant correlation between the densities of these bivalves and the analyzed environmental parameters. Despite this, the species were found in high densities and formed well-developed benthic communities in some stations. The study contributes to the understanding of the invasiveness of these bivalve species and their distribution range dynamics. Nonetheless, further investigation is required to fully comprehend the role of environmental parameters in their distribution. The study covers the period between 2010 and 2020 and focuses on the lower Danube River sector and Danube Delta.
Research on the Impact of Energy Price on Carbon Emission Intensity of China—An Empirical Study Based on LMDI Decomposition and Econometric Models
Authors: Du Xiaolu , Sun Yingshan , Zhang Xiaoyi , Zhang Rui
Published: May 2023

Taking the data of various sectors and three industries from 1980 to 2019 as the research object, the LMDI-I (Logarithmic Mean Divisia Index) multiplicative decomposition model, which is based on the principle of decomposing the change in energy consumption into the contribution of each factor, was used to decompose the carbon emission intensity into technological progress effect and economic structure changing effect. Meanwhile, quantitative econometric models of energy price, economic growth, energy consumption structure, and the two effects were also established. The empirical results showed that energy price, economic growth, and energy consumption structure significantly influenced the reduction in carbon emission intensity. A positive U-shaped relationship between energy prices and carbon emission intensity was overserved, and the rise of energy prices mainly drive the decline of carbon emission intensity through the effect of technological progress. However, the effect of economic structure driven by the rise of energy prices was limited; thus, further optimization of economic structure is needed. Additionally, the proportion of coal consumption was positively correlated with the technological progress effect and economic structure change effect, while the decrease in coal consumption proportion promoted the decline of carbon emission intensity. Finally, three recommendations based on the analysis were proposed.
The Identification of Intersection Entrance Accidents Based on Autoencoder
Authors: Du Yingcui , Sun Feng , Jiao Fangtong , Liu Benxing , Wang Xiaoqing , Zhao Pengsheng
Published: May 2023

Traffic collisions are one of the leading causes of traffic congestion. In the case of urban intersections, traffic accidents can even result in widespread traffic paralysis. To solve this problem, we developed an autoencoder-based model for identifying intersection entrance accidents by analyzing the characteristics of traffic volume. The model uses the standard deviation of the intersection entrance lanes’ traffic volume as an input parameter and identifies intersection entrance accidents by comparing predicted data to actual measured data. In this paper, the detection rate and average detection time are chosen to evaluate the effectiveness of algorithms. The detection rate of the autoencoder model reaches 94.33%, 95.47%, and 81.64% during the morning peak, evening peak, and daylight off-peak periods, respectively. Compared to the support vector machine and the random forest, autoencoder has better performance. It is evident that the research presented in this paper can effectively enhance the detection effect and has a shorter detection time of intersection entrance accidents.
Enhancing Efficiency of Grid-Connected Solar Photovoltaic System with Particle Swarm Optimization & Long Short-Term Memory Hybrid Technique
Authors: Jena Ramakanta , Dash Ritesh , Reddy Kalvakurthi Jyotheeswara , Parida Prasanta Kumar , Dhanamjayulu Chittathuru , Swain Sarat Chandra , Muyeen S. M.
Published: May 2023

Maximum Power Point Tracking (MPPT) is a technique used in photovoltaic (PV) systems to maximize the power output from the solar panel by constantly tracking and adjusting the optimal operating point. To achieve this, various algorithms have been developed, with Particle Swarm Optimization (PSO) being a widely used method. By adjusting the control system’s parameters, PSO can determine the optimal operating point of the solar panel and improve its overall performance. PSO employs swarm intelligence by simulating the behavior of particles to find the best solution for a given problem. Long Short-Term Memory (LSTM) belongs to the family of Recurrent Neural Networks (RNN) in machine learning and is designed to address the limitations of traditional RNNs in capturing long-term dependencies that exist in sequential data. The combination of PSO and LSTM techniques can result in an efficient MPPT algorithm that leverages the benefits of both. PSO is utilized to optimize the control parameters of the MPPT algorithm, while LSTM is used to predict the solar panel’s power output based on historical data. Consequently, this integration can lead to an accurate and efficient MPPT algorithm that can effectively track the solar panel’s maximum power point. In this research article, an effort has been made to control the duty cycle of the converter by suitably controlling the system gain. A Matlab-based Simulink model in conjunction with Python programming has been used to make the system more robust.
Calculation and Analysis of Unbalanced Magnetic Pull of Rotor under Motor Air Gap Eccentricity Fault
Authors: Zhu Rui , Tong Xin , Han Qingpeng , He Keyuan , Wang Xinrou , Wang Xuechao
Published: May 2023

Due to various factors such as manufacturing, assembly and operation, the motor air gap will be uneven in the circumferential direction, resulting in the air gap eccentricity having a longer air gap on one side and a shorter air gap on the other side, which affects the normal operation and service life of the motor. This paper analyzed and compared the applicability of linear and nonlinear calculation methods of unbalanced magnetic pull. Based on the method of finite element analysis, the unbalanced magnetic pull of motor rotor under static eccentricity, dynamic eccentricity and compound eccentricity faults were calculated, and the influence of eccentricity on unbalanced magnetic pull was compared, respectively. The results showed that when the motor has static eccentricity, the main components of unbalanced magnetic pull on the rotor are zero frequency and twice the electrical frequency. When the motor has dynamic eccentricity, the unbalanced magnetic tension component of the rotor is mainly frequency conversion. When the motor has two faults at the same time, the unbalanced magnetic pull has zero frequency, rotating frequency and double electric frequency components at the same time. With the increase in the relative eccentricity, the frequency components of the unbalanced magnetic pull under the three faults increase. An air gap eccentricity fault widely exists in motor equipment. When the unbalanced magnetic pull increases to a certain extent, the rotor will be pulled towards the stator, causing the occurrence of rub-impact phenomenon, and seriously threatening the safe operation of the system. In this paper, the numerical analysis method and finite meta-computing method were used for the first time to analyze and compare the unbalanced magnetic pull on the rotor of permanent magnet synchronous motor under three kinds of air gap eccentricity faults. The results showed that the characteristic frequency amplitude of the unbalanced magnetic pull calculated by the two methods is relatively close. Therefore, it is of great significance to carry out calculation and analysis of the unbalanced magnetic pull force under the air gap eccentric fault of the motor.
Modeling the Neighborhood Wellbeing of Townships in South Africa
Authors: Moghayedi Alireza , Mehmood Abid , Michell Kathy , Ekpo Christiana Okobi
Published: May 2023

Townships in South Africa are characterized by underdeveloped urban neighborhoods on the periphery of cities, where their inhabitants suffer from a poor quality of life. Given the relative lack of empirical research on the wellbeing of people living in townships in South Africa, this study attempts to fill the gap by understanding and modeling the relationships between household socioeconomic characteristics, housing and neighborhood conditions, and individual and community wellbeing to develop and empirically validate a neighborhood wellbeing framework. The hypothesized associations from the wellbeing framework were tested using 389 household interviews of the three largest townships in South Africa. The findings identify the challenges associated with adequate housing and lack of infrastructure in townships and how these affect the wellbeing of individuals and communities. The conclusion demonstrates how the neighborhood wellbeing framework, as an interdisciplinary approach, can improve the quality of life of inhabitants and communities in urban neighborhoods in general.
Exploring Energy Literacy in Italian Social Housing: A Survey of Inhabitants Preparing the Ground for Climate Transition
Authors: Marchi Lia , Felicioni Licia , Sabatini Francesca , Errante Lidia
Published: May 2023

A low level of energy literacy can hamper the adoption of climate-responsive solutions in the built environment. This is often the case of social housing neighborhoods, where the implementation of improvement measures such as those from the EU Recovery Plan (PNRR in Italy) may become difficult because of the specific socio-cultural and economic criticalities. Here, inhabitants are more prone to misinformation as well as energy poverty. Therefore, understanding the level of knowledge and willingness to implement certain design actions at both site and building levels is of utmost importance to make the transition as effective and just as needed. The article presents a pilot survey conducted in two Italian social housing neighborhoods to assess residents’ understanding and preparedness to implement climate-responsive strategies, as well as literacy gaps about energy transition and related public fundings. This can prepare the ground for developing effective solutions to improve the livability of the built environment based on local needs and features that can be combined synergistically with financial incentives. The survey results are discussed, in addition to the upscaling potential.
Integrated Methods for Selecting Construction Foundation Type Based on Using a Value Engineering Principle
Authors: Alsanabani Naif M. , Al-Gahtani Khalid S. , Bin Mahmoud Abdulrahman A. , Aljadhai Saad I.
Published: May 2023

The cost of constructing foundations, on average, ranges from 10% to 15% of a project’s total cost. Therefore, selecting the appropriate type of foundation may result in a significant reduction in project costs. In this study, a value engineering (VE) approach was applied to select the best foundation type from seven alternatives that covered shallow and deep foundations. Selection was dependent on ten important criteria, which were classified into safety, buildability, flexibility of architectural design, and environmental impact. Foundation construction experts used the stepwise weight assessment ratio analysis (SWARA) method to determine the weights of these ten properties for six identified cases based on structure type and soil type. In addition, the weighted aggregated sum product assessment (WASPAS) method was used to determine the quality weight for each foundation option. The results show that adaptable architectural design requirements were more critical in selecting the foundation than the safety criteria for a bridge project. Additionally, the criteria for environmental impacts in the case of high-rise buildings have a more significant impact on foundation choice than low-rise buildings. The outcomes of this study may improve the adaptability of architectural design and the environmental impact of future structures and building codes in the construction industry.
Developing a Wine Tourism Destination Image Measurement Scale
Authors: Sekhniashvili Gvantsa , Bujdosó Zoltán
Published: May 2023

Wine tourism plays an important role in the positioning strategies of wine destinations. As the competitiveness is high among wine destinations, it is important to identify the main factors that affect wine tourists’ decision making. One of the most important factors is the wine tourism destination’s image. To measure the image of a wine region, there is a need for a scale that is adapted to the characteristics of wine tourism destinations. Our purpose is to develop a scale that can measure any wine region’s image. We used a literature review and focus group interviews to collect scale attributes. We gathered responses using an online survey. Our respondents were mostly non-visitors. We used FA to analyze the data. We also tested the reliability of this scale using Cronbach’s Alpha. As a result, we developed a reliable scale with six factors. This can be further tested and used by any wine tourism destination to measure the people’s perceptions about them. The developed scale can have various purposes. It can be used by destination management organizations or marketing agencies. Measured images of wine region can be used in the planning of future positioning strategies and promotions. The scale can be used to compare the images of competitor wine regions. Images can also be studied during a period and any changes can be observed.
An Maximum Power Point Tracker of Photovoltaic Module Arrays Based on Improved Firefly Algorithm
Authors: Chao Kuei-Hsiang , Zhang Shu-Wei
Published: May 2023

In this paper, an improved firefly algorithm (FA) was proposed for application on photovoltaic module arrays (PVMAs) with partial modules under shading so that the maximum power point tracking (MPPT) could be implemented. Firstly, a new model of high voltage step-up converter was developed for executing the MPPT of the PVMA. For the energy storage inductor of the developed converter, the architecture of the coupled inductor was adopted so that the converter switch did not need to operate under an excessive duty cycle, which could increase the voltage gain and reduce the ripple of the output voltage at the same time. To prevent shading on the partial modules within the PVMA and generate more than one peak on the power-voltage (P-V) output characteristic curve, where the conventional MPPT could only track the local maximum power point (LMPP) and reduce the output power of the PVMA, the maximum power tracker, based on the improved FA, was proposed in this paper. Such a tracker could perform an automatic online adjustment on the FA iteration parameters, according to the slope of the P-V output characteristic curve, for the PVMA and, at the same time, perform at 0.8 times of the maximum power point (MPP) voltage for the module array under standard test condition (STC), serving as the initial tracking voltage for implementing the global maximum power point tracking (GMPPT). Lastly, the actual test results were applied to verify that the proposed converter indeed contained a high voltage step-up and low-ripple output voltage. The improved FA could also track GMPP faster and further improve the power-generating efficiency of the PVMA.
Damage Detection of High-Speed Railway Box Girder Using Train-Induced Dynamic Responses
Authors: Wang Xin , Zhuo Yi , Li Shunlong
Published: May 2023

This paper proposes a damage detection method based on the train-induced responses of high-speed railway box girders. Under the coupling effects of bending and torsion, the traditional damage detection method based on the Euler beam theory cannot be applied. In this research, the box girder section is divided into different components based on the plate element analysis method. The strain responses were preprocessed based on the principal component analysis (PCA) method to remove the influence of train operation variation. The residual error of the autoregressive (AR) model was used as a potential index of damage features. The optimal order of the model was determined based on the Bayesian information criterion (BIC) criterion. Finally, the confidence boundary (CB) of damage features (DF) constituting outliers can be estimated by the Gaussian inverse cumulative distribution function (ICDF). The numerical simulation results show that the proposed method in this paper can effectively identify, locate and quantify the damage, which verifies the accuracy of the proposed method. The proposed method effectively identifies the early damage of all components on the key section by using four strain sensors, and it is helpful for developing effective maintenance strategies for high-speed railway box girders.
Sustainable Development Goals (SDGs) in Latin-American Universities
Authors: Fuchs Paulo Guilherme , Finatto Carla Patrícia , Birch Robert Samuel , de Aguiar Dutra Ana Regina , de Andrade Guerra José Baltazar Salgueirinho Osório
Published: May 2023

Higher education institutions (HEIs) are notable promoters of sustainable development (SD). Thus, it is understood that the sustainable development goals 2015–2030 (SDGs) need to be substantially operationalized in these institutions. Based on this idea, the QualEnv (quality and environment) consortium of universities stands out for having as its main objective the increase in contribution to sustainable development (SD) by universities through the implementation of systematic environmental practices and quality processes in line with the SDGs. The objective of this article is to present how the QualEnv consortium of HEIs adopts the SDGs and demonstrates their contribution to SD. For this purpose, a qualitative analysis was performed based on documentary research, a systematic review of the literature, and notes collected from participant observations. The results show that the adoption of the SDGs in the QualEnv consortium was enhanced by the contribution of the social relations within the partnership, which promoted the exchange of experiences and synergy between participants that promoted improvements in the necessary strategies. Along with the highlighted actions and concentration of different axes with dispersed interventions, a potential for central cohesion and focus on evolution in each SDG was noted. The adoption of the same indicators involves the unification of the actions planned for the SD and the common objective of involving communities more consistently, which impacts mainly SDG 04. This article discusses the practical implications in HEIs and the need to integrate the SDGs into their activities, as it demonstrates how universities belonging to the QualEnv consortium have been creating their own strategies to achieve the 2030 agenda and adopt the SDGs.
Scope of the Literature on Efforts to Reduce the Carbon Footprint of Seaports
Authors: Issa Zadeh Seyed Behbood , López Gutiérrez José Santos , Esteban M. Dolores , Fernández-Sánchez Gonzalo , Garay-Rondero Claudia Lizette
Published: May 2023

Seaport activities account for 3% of global carbon emissions, and as an important industrialised economic centre, ports engage in numerous industrial and financial activities that could increase their greenhouse gas (GHG) emissions and carbon footprints (CF). The 13th sustainable development goal (SDG) states that these activities must be balanced with environmental considerations. Therefore, as critical marine infrastructure, seaports need CF reduction initiatives. This scoping review covers important ideas and ways to reduce the CF in seaports to simplify future policymaking. These approaches include energy management systems, equipment and infrastructures, and carbon emission policies and laws specific to ports. Relevant literature is classified, evaluated, and discussed. The findings are interpreted and discussed based on the current state of ports around the world, using statistical data to demonstrate that there are sufficient regulations and standards in place, but that more work is needed to replace conventional systems with intelligent ones and fossil fuels with renewable energy. Finally, the scoping review results, and scientific interpretations, thoughts, proposals, and recommendations are presented as references for related studies in the future.
Detecting Circular Economy Strategies in the Fourth Sector: Overview of the Chilean Construction Sector as Evidence of a Sustainable Business Model
Authors: Cerdá-Suárez Luis Manuel , Espinosa-Cristia Juan Felipe , Núñez-Valdés Karen , Núñez-Valdés Gerson
Published: May 2023

An essential part of the economic and social system is the existence of sustainable companies worldwide. Despite the fact that the literature has described different kinds of innovations, organizations, and models regarding this topic, there is a need to understand the dynamics that occur within the fourth sector and how strategies and practices are working. In this study, construction companies presenting sustainable projects are identified, and the way in which they serve the community, stakeholders, and consumers is analyzed. The present article presents an epistemological search to recognize the best practices and strategies, which allows an understanding of the new circular economy strategies in the fourth sector. The authors show a conceptual approach regarding these actions and a methodology on the most notable techniques of the Circular Economic Strategy of Chile based on an investigation of documentary and comparative data. Data collection considered perceptions of construction practices regarding the circular economy and the specificity of each situation and reflected the actual production systems. We used simple random sampling to collect data in the scope of the study. The findings show the importance of some relational elements between companies that structure construction projects, supporting the impact of discovering specific variables in the different layers of sustainable management. In addition, results show how those responsible for construction projects understand sustainability as a preference, amplify the role of various factors in the work of the cultural and social ecosystems under consideration. Finally, this article details and analyzes the channeling of innovative business models in the fourth sector.
Assessing the Impact of Biodiversity (Species Evenness) on the Trophic Position of an Invasive Species (Apple Snails) in Native and Non-Native Habitats Using Stable Isotopes
Authors: Scriber Kevin E. , France Christine A. M. , Jackson Fatimah L. C.
Published: May 2023

Invasive apple snails negatively impact non-native habitats and human well-being. Here, the trophic position of Pomacea canaliculata in native habitats (Maldonado, Uruguay) and non-native habitats (Hangzhou, China and Hawaii, USA) are compared. Detritus samples and tissue samples from apple snails were collected in all sites. Trophic levels were calculated as the difference between the mean δ15N values of detritus samples and corresponding apple snail tissue samples, divided by the mean δ15N fractionation for nitrogen per trophic level in freshwater habitats. The mean δ15N values of detritus in sites served as a baseline (i.e., zero trophic level), allowing direct comparisons. Linear regression analysis established a correlation between species evenness and apple snail trophic level (R2 = 0.8602) in line with a Pearson’s product-moment correlation value (−0.83) and 95% confidence interval (−0.87, −0.77). Normal quartile plots indicated two normally distributed subsets of apple snail trophic-level data: (1) a biodiverse subset containing the Uruguayan and Chinese lake sites and (2) the homogenized Hawaiian and Chinese creek sites. A precipice value for species evenness (separating biodiversity from homogenization), between (3.7) and (2.4), once descended to or surpassed separates statistically distinct, normal distributions of invasive apple snail trophic-level data from diverse versus homogenized habitats.
Investigation of Effect of Nozzle Numbers on Diesel Engine Performance Operated at Plateau Environment
Authors: Li Zhipeng , Zhang Qiang , Zhang Fujun , Liang Hongbo , Zhang Yu
Published: May 2023

The effect of nozzle number on the combustion and emission characteristics of diesel engines operating at high altitudes was investigated in this study. A three-dimensional computational fluid dynamics model was developed to simulate the spray spatial distribution, which is closely related to the nozzle number. The intake pressure was identified as the dominant factor under varying altitudes, while the fuel mass, injection timing and temperature were maintained constant. Altitudes of 3000 m were chosen to represent typical high-altitude conditions, and sea level cases were simulated for comparison. The results demonstrated that high-altitude operation reduced the air utility in the combustion chamber, leading to suppressed soot oxidization and worse soot emissions. Moreover, more injection nozzles will decrease the fuel injection pressure, resulting in inadequate fuel diffusion and detrimental effects on the combustion efficiency and soot control. However, too few nozzles may cause wall collisions and worsen the combustion conditions. The number of nozzles also influences the combustion, with a higher number of nozzles exacerbating poor combustion conditions. The optimal number of nozzles for the engine studied is determined to be six. Hence, determining the optimal nozzle number plays a vital role in achieving the optimal performance of highland diesel engines. This study provides valuable guidance for the development of diesel engines in high-altitude environments, where controlling the fuel consumption and soot emissions is challenging.