bluuebunny/crossref_metadata_2025 huggingface dataset:
Environmental Performance of Alternative Hospital Waste Management Strategies Using Life Cycle Assessment (LCA) Approach
Authors: Mushtaq Muhammad Hammad , Noor Fahad , Mujtaba M. A. , Asghar Salman , Yusuf Abdulfatah Abdu , Soudagar Manzoore Elahi M. , Hussain Abrar , Badran Mohamed Fathy , Shahapurkar Kiran
Published: November 2022

The growing population in urban areas generates large volumes of hospital waste which intensifies the problem of hospital waste management in developing countries. This study is designed to evaluate environmental impacts associated with hospital waste management scenarios using life cycle assessment (LCA) approach. Two scenarios were designed to describe the current practices: (scenario A) and an integrated approach (scenario B), which includes segregation and recycling of hospital waste. Data were collected from five public hospitals located in the district of Sheikhupura, Pakistan. The collected hospital waste was quantified and categorized on a daily basis for five consecutive months (October 2020 to February 2021). The functional unit was defined as one tonne of hospital waste. System boundaries for two scenarios include segregation, transportation, treatment and disposal of hospital waste. After defining functional unit and system boundaries, LCA was conducted using the IGES-GHG simulator. The scenarios were evaluated using common parameter, i.e., greenhouse gas (GHG) emissions. Scenario A and scenario B resulted in net GHG emissions of 1078.40 kg CO2-eq. per tonne of waste and 989.31 kg CO2-eq. per tonne of waste, respectively. Applying an integrated approach, it would be possible to mitigate GHG emissions of 37,756.44 kg CO2-eq. per tonne of waste annually and to recover some materials such as glass, paper, plastic and metals. Therefore, implementing an integrated approach for the management of hospital waste will progress the entire system towards sustainability. The findings of this study can be used for future research and policymaking.
Assessment of Yield and Nitrogen Utilization of the Mixed CRU and Urea in Wheat–Maize Production in a 5-Year Field Trial
Authors: Liu Jing , Zhu Guoliang , Shi Guifang , Yi Wenping , Xiao Qiang
Published: November 2022

To identify the general pattern of impact of the application of the mixed controlled-release urea (CRU) with urea (C-U) on grain yield, plant characteristics, NUE and soil nitrogen contents in wheat–maize production, a 5-year field trial with three release longevity and four ratios of CRU in C-U and common urea alone (U) was carried out in the North China Plain. Results with meta-analysis revealed that C-U had significant effects on grain yield and plant characteristics, NUE and soil NO3−-N contents in wheat–maize production positively with the release longevity of CRU and the ratio of CRU-N in C-U. The application of C-U with 60 d or 90 d CRU for wheat and maize had the best overall effects, while C-U treatment with 30 d CRU had a significant inhibitory effect. For maize, C-U with 30% CRU-N had the largest increase rate on yield, 1000-grain weight, plant height, dry weight and NUE by 5.13%, 1.61%, 3.70%, 11.33%, and 8.63%, respectively, while C-U with 40% CRU-N had the largest reduction soil NO3−-N. For wheat, the application of C-U with 40% CRU-N had a significant effect on yield, sterile spikelet number, and NUE by 4.45%, −9.76%, and −8.04%, respectively. To conclude, the use of the C-U with appropriate release longevity and the ratio of CRU has great potential to proliferate wheat–maize yields and reduce fertilizer loss especially for maize that not only provides an effective generic methodology for agriculture to improve measures but also ensures profitability.
Factors Influencing Farmers’ Willingness and Behaviors in Organic Agriculture Development: An Empirical Analysis Based on Survey Data of Farmers in Anhui Province
Authors: Zhou Xiaohong , Ding Donghong
Published: November 2022

Organic agriculture is currently the dominant method used for the sustainable development of modern agriculture. As the main component in agricultural production, farmers and their willingness and behaviors are important to the overall progress of the organic agriculture industry. Based on survey data from 306 farmers in the Anhui Province, we applied a bivariate probit model to analyze the relevant factors influencing farmers’ willingness and behaviors in organic agriculture. The findings showed that a correlation existed between farmers’ willingness to engage in organic agriculture and their behaviors. Factors such as farmer education level, political status, family disposable income, and their understanding of organic agriculture and environmental hazards considerably influenced the farmers’ willingness to engage in organic agriculture. The variables of age, no-agricultural employment, and other factors played a substantial inhibitory role. This conclusion has certain value for further understanding of farmers’ willingness to be engaged in organic agriculture and their behaviors and so contributed to the structural reform of the agricultural supply side and the implementation of the “Rural Revitalization” strategy.
Rainfall Spatial-Temporal Variability and Trends in the Thamirabharani River Basin, India: Implications for Agricultural Planning and Water Management
Authors: Mohan Kumar Shanmugam , Geethalakshmi Vellingiri , Ramanathan Subbiah , Senthil Alagarsamy , Senthilraja Kandasamy , Bhuvaneswari Kulanthaivel , Gowtham Ramasamy , Kannan Balaji , Priyanka Shanmugavel
Published: November 2022

Rainfall is critical to agricultural and drinking water supply in the Thamirabharani river basin. The upper catchment areas of the Thamirabharani basin are located in high-elevated forest regions, and rainfall variability affects dam inflow and outflow. The well-known methods for rainfall analysis such as the coefficient of variation (CV), the precipitation concentration index (PCI), and trend analysis by Mann-Kendall and Sen’s slope test, as well as the Sen’s graphical innovative trend method (ITA) recently reported in several studies, were used. Rainfall data from gauge stations and the satellite-gridded Multisource Weighted Ensemble Precipitation (MSWEP) dataset were chosen for analysis at the annual and four-season time scales, namely, the Southwest Monsoon, Northeast Monsoon, winter, and summer seasons from 1991 to 2020. The mean annual PCI value reflects irregular monthly rainfall distribution (PCI > 20) in all gauge stations. The spatial monthly rainfall distribution of PCI values remarkedly shows a moderate distribution in the western and an anomalous distribution in the eastern part of the basin. The annual mean rainfall ranges from 718.4 to 2268.6 mm/year, decreasing from the high altitude zone in the west to the low plains and coastal regions in the east. Seasonal rainfall contributes about 42% from the NEM, 30.6% from the SWM, 22.8% from summer, and 3.9% from winter, with moderate variability (CV less than 30%). Ground stations experienced extremely high interannual variability in rainfall (more than 60%). Trend analysis by the MK, TFPW-MK, and ITA methods shows increasing annual rainfall in the plains and coastal regions of the basin; particularly, more variations among the seasons were observed in the Lower Thamirabharani sub-basin. The NEM and summer season rainfall are statistically significant and contribute to the increasing trend in annual rainfall. The ITA method performed better in the annual and seasonal scale for detecting the rainfall trend than the MK and TFPW-MK test. The Lower Thamirabharani sub-basin in the eastern part of the basin receives more rain during the NEM than in other areas. To summarize, the low plains in the central and coastal regions in the southeast part experience an increase in rainfall with irregular monthly distribution. This study helps farmers, governments, and policymakers in effective agricultural crop planning and water management.
Residents’ Perceptions and Behavioral Intentions towards Mega-Sports Events: A Case Study of Beijing 2022 Olympic Winter Games
Authors: Xu Zhuyan , Wu Chengzhong , Li Xuefei
Published: November 2022

Despite growing research on the impacts of mega-sports events, comparative studies of the value perceptions of residents in host and non-host cities are rare. Residents’ perceptions are effective indicators of their behavioral intentions, which are crucial for the success of events and for the place marketing of hosting cities. To fill this gap, this study constructed a model linking residents’ expected impacts, perceived value and behavioral intentions for mega-sports events. Informed by Social Exchange Theory, this study employed Structural Equation Modeling (SEM) to analyze 1527 valid questionnaires collected in mainland China (412 in host cities, 1115 in non-host cities). The results reveal that non-host-city residents have more substantial expectations of impacts, perceptions of value, and behavioral intentions than host-city residents. Residents in Northeast China had the highest perceptions and behavioral intentions toward the Beijing 2022 Winter Olympics, implying that the geographical location of the non-host cities is an influencing factor. Researchers and practitioners should pay attention to those differences in research design and event planning to promote the sustainable development of mega-sports events.
Review of Strategic Agility: A Holistic Framework for Fresh Produce Supply Chain Disruptions
Authors: Yawson David Eshun , Yamoah Fred A.
Published: November 2022

The influence of the rapidly changing business environment due to the COVID-19 global pandemic presents an important organizational challenge to fresh produce export supply chains in developing countries such as Ghana. Such an inimical supply chain problem highlights the relevance of supply chain agility as a potent methodological framework to measure, monitor and evaluate these challenges in stable as well as turbulent times. This review paper focuses on the applicability of a framework for Supply Chain Agility as a methodological framework in stable (pre-COVID-19) versus turbulent (COVID-19) business environments. We argue and propose that Supply Chain Agility Framework is a holistic framework which is efficacious in both stable and unstable supply chain environments. This is amply supported by the central plank of our proposition that the Supply Chain Agility Framework offers an adaptable tool that can serve as a panacea to fresh produce supply chain challenges not only in a stable (pre-COVID-19) business environment but also effective and applicable in a turbulent business environment, such as experienced during the COVID-19 pandemic. The implications of this proposition for the fresh produce export supply chain industry and relevant stakeholders are duly presented.
Increasing Quantity or Improving Quality: Can Soil Pollution Control Promote Green Innovation in China’s Industrial and Mining Enterprises?
Authors: Du Zhengke , Zhu Chengcheng , Zhou Yuxin
Published: November 2022

This paper uses the provisions of the Soil Pollution Prevention and Control Action Plan for industrial and mining enterprises as a quasi-natural experiment and constructs a difference-in-differences (DID) model to study its effect on increasing the quantity and improving the quality of green innovation based on a panel of 453 industrial and mining enterprises in Shanghai and Shenzhen A-shares in China from 2011 to 2020. The results show that the Soil Plan can significantly promote the increase of green innovation and the quality of industrial and mining enterprises, and the results are still valid after a series of robustness tests. The mechanism test shows that the Soil Plan promotes the quality of green innovation by alleviating the financing constraints of industrial and mining enterprises, but the impact on their incremental quantity is not significant. The heterogeneity analysis shows that the effect of the Soil Plan on the quality of green innovation is stronger in the sample with a more independent board of directors and a digital mine transformation. This paper enriches the results in the field of soil pollution prevention and industrial and mining enterprises, and has important implications for the practice of promoting green innovation in Chinese enterprises.
Fundamental Shifts of Cruise Shipping in the Post-COVID-19 Era
Authors: Lau Yui-yip , Yip Tsz Leung , Kanrak Maneerat
Published: November 2022

The COVID-19 pandemic has seriously influenced cruise tourism and global businesses, which is a new variant that poses unpredictable issues for the cruise industry. This study investigates fundamental shifts in cruise shipping after the pandemic using the CRUISE PORT framework by conducting 18 semi-structured and in-depth interviews. The results show that port connectivity is the most significant factor in promoting ports as hubs. Regional competitiveness is important to sustain the cruise industry. Some ports face a low utilization rate due to cruise lines changing their itineraries and visiting low-risk ports. Cruise ports can rebuild competitiveness by improving their infrastructures. Security became the prime concern, while environmental management is not the main priority and the deciding factor in reviving the industry. A port of call is a significant factor in fostering the industry’s development. The pandemic does not generate any significant issues for cruise lines in terms of ocean conditions. Recreational activities can help cruise lines to attract more passengers, and cruise traffic is a driving force to improve port competitiveness. The findings are drawn implications for the cruise sector, port authorities, and stakeholders to improve their operations and services.
Spatio Prediction of Soil Capability Modeled with Modified RVFL Using Aptenodytes Forsteri Optimization and Digital Soil Assessment Technique
Authors: Alnaimy Manal A. , Shahin Sahar A. , Afifi Ahmed A. , Ewees Ahmed A. , Junakova Natalia , Balintova Magdalena , Abd Elaziz Mohamed
Published: November 2022

To meet the needs of Egypt’s rising population, more land must be cultivated. Land evaluation is vital to achieving sustainable agricultural production. To determine the soil capability in the northeast Nile Delta region of Egypt, the present study introduces a new form of integration between the Agriculture Land Evaluation System (ALES Arid) model and the machine learning (ML) approach. The soil capability indicators required for the ALES Arid model were determined for the 47 collected soil profiles covering the study area. These indicators include soil pH, soil salinity, the sodium adsorption ratio (SAR), the exchangeable sodium percentage (ESP), the organic matter (OM) content, the calcium carbonate (CaCO3) content, the gypsum content, the clay percentage, and the slope. The ALES Arid model was run using these indicators, and soil capability indexes were obtained. Using GIS, these indexes helped to classify the study area into four capability classes, ranging from good to very poor soils. To predict the soil capability, three machine learning algorithms named traditional RVFL, sine cosine algorithm (SCA), and AFO were also applied to the same soil criteria. The developed ML method aims to enhance the prediction of soil capability. This method depends on improving the performance of Random Vector Functional Link (RVFL) using an optimization technique named Aptenodytes Forsteri Optimization (AFO). The operators of AFO were used to determine the best parameters of RVFL since traditional RVFL is sensitive to parameters. To assess the performance of the developed AFO-RVFL method, a set of real collected data was used. The experimental results illustrate the high efficacy of AFO-RVFL in the spatial prediction of soil capability. The correlations found in this study are critical for understanding the overall techniques for predicting soil capability.
Exploring the Cyber Technology Critical Success Factors for Sustainable Building Projects: A Stationary Analysis Approach
Authors: Oke Ayodeji Emmanuel , Kineber Ahmed Farouk , Ekundayo Damilola , Tunji-Olayeni Patience , Edwards David J.
Published: November 2022

We sought to identify and examine the critical success factors (CSFs) necessary for incorporating cyber technology into residential building projects to augment operational performance and sustainability. An iterative two-stage approach was adopted to explore the phenomena under investigation. General CSFs for cyber technology were first identified from the extant literature, and subsequently explored using primary questionnaire survey data accrued from professionals within the Nigerian building industry. The survey results illustrated that the availability of sensors, good communication networks, mobile devices, and device layers and the creation of workable virtual modes are the main critical success factors for adopting cyber technology. Moreover, Gini’s mean difference measure of dispersion showed that the success factor in stationary cyber technology adoption is government support. The study’s findings guide building industry stakeholders to embrace cyber technology to improve cost and sustainability performance in the Nigerian building industry. Due to the originality of the findings of this study, a strong basis is provided for critically evaluating and analyzing the many vital aspects of cyber technology success.
Optimal Contract Design in Contract Farming under Asymmetric Effort Information
Authors: Tang Chunhua , Zhang Huiyuan , Xie Jiamuyan
Published: November 2022

This paper studies the contract design, optimal financing, and pricing decision of the leading agricultural enterprise when the level of effort of the farmer is private information. We use buyer direct finance and add agricultural income insurance to transfer risks to overcome the farmer’s loan difficulty and contract default caused by information asymmetry. We design four kinds of contracts, including the uninsured and symmetric information contract (SN contract), the uninsured and asymmetric information contract (AN contract), the insured and symmetric information contract (SY contract), and the insured and asymmetric information contract (AY contract). Through comparative analysis of the different types of contracts, several results are obtained. First, when there is no insurance, supervision of the leading enterprise can improve the farmer’s level of effort; but supervision costs are incurred, and incentive contracts can avoid the farmer’s moral hazard. Second, agricultural income insurance improves the farmer’s level of effort when information is asymmetric, which transfers risks and saves costs for all the game participants. Third, the leading enterprise prefers an asymmetric information contract and the farmer prefers AN contract when the probability of loan repayment is high.
Detecting Nontechnical Losses in Smart Meters Using a MLP-GRU Deep Model and Augmenting Data via Theft Attacks
Authors: Kabir Benish , Qasim Umar , Javaid Nadeem , Aldegheishem Abdulaziz , Alrajeh Nabil , Mohammed Emad A.
Published: November 2022

The current study uses a data-driven method for Nontechnical Loss (NTL) detection using smart meter data. Data augmentation is performed using six distinct theft attacks on benign users’ samples to balance the data from honest and theft samples. The theft attacks help to generate synthetic patterns that mimic real-world electricity theft patterns. Moreover, we propose a hybrid model including the Multi-Layer Perceptron and Gated Recurrent Unit (MLP-GRU) networks for detecting electricity theft. In the model, the MLP network examines the auxiliary data to analyze nonmalicious factors in daily consumption data, whereas the GRU network uses smart meter data acquired from the Pakistan Residential Electricity Consumption (PRECON) dataset as the input. Additionally, a random search algorithm is used for tuning the hyperparameters of the proposed deep learning model. In the simulations, the proposed model is compared with the MLP-Long Term Short Memory (LSTM) scheme and other traditional schemes. The results show that the proposed model has scores of 0.93 and 0.96 for the area under the precision–recall curve and the area under the receiver operating characteristic curve, respectively. The precision–recall curve and the area under the receiver operating characteristic curve scores for the MLP-LSTM are 0.93 and 0.89, respectively.
Exchange Rate Appreciations and the Distribution of Productivity: Is Importing Inputs Sustainable for Emerging Countries?
Authors: Jiang Chun , Wu Fan , Yan Huan
Published: November 2022

A static model is used to investigate how the exchange rate movement affect the distribution of productivity within an industry. Quantile regression is then used to empirically test the effects of RMB exchange rate appreciation on the distribution of labor productivity within industries. Based on China’s manufacturing micro-enterprise survey data from 1998 to 2007, we characterize how exchange rate changes affect the distribution of productivity through three mechanisms. We find that the exchange rate appreciation increases the dispersion of the productivity distribution and decrease the efficiency of resource allocation and aggregate productivity. The distribution of the import intensity may be the main cause for the increase in the productivity dispersion and the deterioration of the industrial resource allocation efficiency, which implies that foreign inputs improve the mean productivity of firms but decrease the resource allocation efficiency. China should tradeoff the gain in productivity and loss in allocation efficiency when it aims to implement a more elastic RMB exchange rate regime.
Can Climate Change Awaken Ecological Consciousness? A Neuroethical Approach to Green Consumption
Authors: Yin Meiling , Choi Hanna , Lee Eun-Ju
Published: November 2022

Climate change is a major threat to humanity and endangers our way of life. If a critical mass of consumers can consider the consequences of the daily consumption choices they make, we could hope for a better future. From a neuroethical viewpoint, we examined how a consumer’s ecological consciousness can be awakened, leading to eco-friendly consumption. This study used the neuroscientific method of event-related potentials (ERP) to explore the neural mechanisms underlying climate change. Both frontal N300 and posterior P300 ERP components occur under climate change conditions which is a neural representation of ecological consciousness. Consumers who exhibited simultaneous frontal N300 and posterior P300 activation were more likely than those who did not to make eco-friendly product choices during the consumption tasks. Using these neurobehavioral findings, marketers can promote eco-friendly consumption based on ecological consciousness.
A Study on the Impact of Built Environment Elements on Satisfaction with Residency Whilst Considering Spatial Heterogeneity
Authors: Chen Qi , Yan Yibo , Zhang Xu , Chen Jian
Published: November 2022

The built environment, as perceived and felt by human beings, can shape and affect residential satisfaction. From the perspective of municipal administrators, understanding the building environment and its relationship with people’s residential satisfaction is crucial to improving people’s living environment. This study examines the correlation between built environment elements and residential satisfaction using the consideration of spatial heterogeneity of such a correlation. Machine vision technology is introduced to quantify the design dimension of the built environment. The method of multiscale geographically weighted regression is used to evaluate the relationship between built environment and residential satisfaction and to analyze the spatial heterogeneity in the influencing effects. This empirical study draws on 399 collected samples from the residents of Zhengzhou, China. The results show that elements of the built environment, including street space design features, have a significant effect on people’s residential satisfaction in Zhengzhou City. The factors of functional diversity and distance to the city center show spatial heterogeneity in influencing effects on residential satisfaction. The results of this study could help municipal managers to improve people’s residential satisfaction in Zhengzhou City through the development of urban renewal policies.
Remote Sensing Monitoring of Durum Wheat under No Tillage Practices by Means of Spectral Indices Interpretation: A Preliminary Study
Authors: Calcagno Federico , Romano Elio , Furnitto Nicola , Jamali Arman , Failla Sabina
Published: November 2022

Due to its advantages, remote sensing monitoring has been used in various applications and made noteworthy contributions to understanding soil and plant processes, as well as in the agriculture sector. The aim of the work is to compare the return of durum wheat crops in conservative agricultural practices in Mediterranean climate conditions by analysing the data from the Sentinel2 satellite through three spectral indices. The analysed spectral indices have different interpretations and therefore have been studied in different periods: (i) NDVI (normalized difference vegetation index) for the evaluation of the vegetative vigour from January to June; (ii) NDWI (normalized difference water index) for the moisture of covered soil from January to June and of bare soil after harvesting from June to August; and (iii) NMDI (normalized multi-band drought index) for the variability of bare soil moisture from June to August. With reference to the machines used in cultivation practices, a further purpose of the study is to investigate the effects of automatic guidance versus manual guidance on production yields and on the spectral indices considered. The first results show that the NDVI follows crop phenological stages by reaching the maximum values in correspondence with the stem elongation and booting stages. Additionally, the NDWI showed the same trend as the NDVI during the current crop. After harvesting, the NDWI showed higher values in the plots cultivated under conservation tillage practices. In the same period, the NMDI showed the same results as the NDWI and a positive correlation, confirming that tillage practices could imply a lower ability to retain water in drought time.
Board Gender Diversity and Corporate Green Innovation: Evidence from China
Authors: Lin Xin , Yu Lina , Zhang Jinhong , Lin Suxu , Zhong Qiming
Published: November 2022

A green economy is the current trend of sustainable development for the global economy. Using Chinese A-share listed enterprises from 2010 to 2020, this study examines how board gender diversity affects green innovation. Results show that board gender diversity significantly promotes the number and quality of green innovations and that R&D and governments support, as essential intermediary mechanisms have positive effects on the relationship between female directors and green innovation. Moreover, heterogeneous analyses show that high levels of ESG, gender diversity of directorial boards of state-owned enterprises, and large enterprises have a more significant role in promoting green innovation. The study provides empirical evidence for the development of green innovation and theoretical support for the transformation of corporate strategic thinking with more women participating in executive decision-making.
The Influence of a Song on School Children’s Knowledge Growth for Sustainable Malaria Prevention: Teacher Perspectives
Authors: Anderson Chad , Kruger Taneshka , Eloff Irma
Published: November 2022

Music as a potential prevention strategy can play a pivotal role in developing behavioural changes and creating awareness about malaria and malaria prevention. The study was conducted in a moderate-risk malaria district in sub-Saharan Africa. A comparative analysis and pre-and post-intervention evaluation of three teaching intervention methods to teach and educate young children about malaria, e.g., song intervention, drama intervention, and song-and-drama combination, was evaluated. Data were collected by means of pre-and post-intervention interviews with Grade 3 primary school children and teachers, as well as a post-intervention questionnaire with teachers, parents, guardians, and caregivers. The purpose of the study was to investigate knowledge gains on malaria in relation to malaria awareness interventions. The results revealed that the song-only intervention was the most effective learning intervention strategy in this population and that behavioural changes and knowledge growth occurred regarding malaria and malaria prevention in this population. Independent of the teaching styles of each teacher in teaching the song to the children, the findings established that culturally and age-appropriate songs contributed to increasing children’s knowledge growth regarding sustainable malaria prevention.
Response and Application of Full-Space Numerical Simulation Based on Finite Element Method for Transient Electromagnetic Advanced Detection of Mine Water
Authors: Guo Changfang , Tan Tingjiang , Ma Liuzhu , Chang Shuai , Chen Yiding , Zhao Ke
Published: November 2022

The issue of water hazards has led to the restriction of safe and efficient coal mine production in China. The transient electromagnetic method (TEM) is one of the most effective means of detecting the hidden dangers of water hazards in coal mines. However, the current understanding of the whole-space transient electromagnetic response of mine water is only on the general law due to the late start of the forward research. Therefore, this paper established multiple sets of simulation models in the whole area in order to study the rules and factors of transient electromagnetic responses. Subsequently, these laws are used to explain the detection data of TEM in the field. According to the simulation results, the electric properties, distance, and size had the greatest influence on the transient electromagnetic response of regular anomalous geological bodies, while the electromagnetic field projection area also had an impact on irregular ones. Furthermore, field application demonstrated that the response law and TEM’s affecting factors are acceptable for directing the detection of transient electromagnetic in coal mines. This research can advance the TEM’s data processing and interpretation technology and offer a theoretical basis for detailed investigation.
A Robust and Anonymous Three-Factor Authentication Scheme Based ECC for Smart Home Environments
Authors: Wang Xiong , Teng Yuan , Chi Yaping , Hu Hongbo
Published: November 2022

With the rapid development of the Internet of Things (IoT) industry, the smart home is fully integrated with people’s shelter and transportation, which facilitates people’s daily life. A smart home without a security authentication mechanism will inevitably cause a series of security threats. This is essentially a problem of symmetry model worth solving. In fact, researchers have designed various authentication schemes to verify the identity of users and to ensure smart devices can be legally accessed through authorization in the smart home. In 2021, Yu proposed a three-factor anonymous authentication scheme for smart homes using lightweight symmetric encryption primitives and stated that their scheme is resistant to various known security attacks. However, after careful analysis, we found that Yu’s scheme needs further improvement in node capture attack and offline password guessing attack and that forward security cannot be guaranteed. Therefore, we first design a robust three-factor anonymous authentication scheme for smart homes based on asymmetric encryption Elliptic Curve Cryptography (ECC). Then, we perform formal and informal security analysis in which the formal analysis tools include Burrows-Abadi-Needham (BAN) logic and Scyther simulation tool to prove that the proposed scheme can achieve user anonymity, untraceability, and session key forward security. Meanwhile, mutual authentication is performed, and the scheme is resistant to all known attacks described in this article. Finally, a performance comparison is made in terms of efficiency, which shows that our scheme can have certain advantages with those newly designed schemes, achieve a delicate balance in performance and safety, and is more practical for the real smart home environment.
Identical Particles Exchange Symmetry and the Electric Dipole Moment in Molecules
Authors: Tino Guglielmo M.
Published: November 2022

Based on fundamental symmetries, molecules cannot have a permanent electric dipole moment, although it is commonly used in the literature to explain the different molecular spectra for heteronuclear and homonuclear molecules. Electric-dipole rotational and vibrational spectra can indeed be observed in heteronuclear molecules, while they are missing in molecules with identical nuclei. This paper shows that the missing spectral features can be explained as an effect of the exchange symmetry for identical particles.
A Simple Metamaterial for High-Performance Spectrum-Selective Absorption in the Visible Region
Authors: Jia Xiubo , Yin Shenwei , Tang Zhixiang
Published: November 2022

In this paper, we numerically demonstrated a simple metamaterial for wide-angle and polarization-insensitive absorption in the visible region, which simultaneously showed a strongly suppressed absorption in the near-infrared region. Numerical simulations demonstrated that under normal incidence the proposed absorber had a high absorptivity almost over 90% in the wavelength range from 340 nm to 770 nm, while a low absorptivity less than 10% from 1 μm to 2 μm. Because a small unit cell with four-fold symmetry was utilized, the selective absorption of this nanostructure was almost independent of the incident angle and polarization of the incident light. To understand the underlying physical mechanisms, the impedance and the electromagnetic field distributions in a unit cell were analyzed. Moreover, the influence of the structural geometry parameters on the absorption spectrum was systematically studied. Our results may provide a method for using a simple nanostructure to reduce the radiative heat loss for the visible light thermal conversion, or to depress the temperature rise induced by the absorption of below-bandgap photons for photovoltaic solar cells working in the visible region.
Variable Fractional-Order Equivalent Circuit Model for Lithium-Ion Battery via Chaotic Adaptive Fractional Particle Swarm Optimization Method
Authors: Wang Deshun , Wei Haikun , Xue Jinhua , Wu Fubao , Lopes António M.
Published: November 2022

A variable fractional-order equivalent circuit model is proposed to accurately describe the dynamic characteristics of lithium-ion batteries (LIBs). Firstly, a fractional impedance model (FIM) is established, such that the fractional-order (FO) is a polynomial function of the LIB state of charge (SOC). Then, a chaotic adaptive fractional particle swarm optimization (CAFPSO) method is derived to identify the parameters of the FIM. Experiments reveal the reliability of the novel approach through the root-mean-squared error (RMSE) and the mean absolute error (MAE) of the LIB terminals voltage, yielding the values 8.99 mV and 4.56 mV, respectively. This translates into accuracy improvements of 22.5% and 34.4% for the particle swarm optimization (PSO) algorithm and 57.9% and 72.8% for the adaptive fractional particle swarm optimization (AFPSO) algorithm, respectively.
Synthesis, Molecular and Supramolecular Structures of Symmetric Dinuclear Cd(II) Azido Complex with bis-Pyrazolyl s-Triazine Pincer Ligand
Authors: Dahlous Kholood A. , Soliman Saied M. , El-Faham Ayman , Massoud Raghdaa A.
Published: November 2022

A new dinuclear Cd(II)-azido complex of 2,4-bis(3,5-dimethyl-1H-pyrazol-1-yl)-6-methoxy-1,3,5-triazine (PMT) pincer ligand is synthesized. Its single crystal X-ray structure reveals the dinuclear [Cd(PMT)(Cl)(N3)]2 formula. The triclinic crystal parameters are a = 9.323(4) Å, b = 10.936(5) Å, c = 11.312(6) Å, α = 112.637(10)°, β = 104.547(11)° and γ = 105.133(10)° while V = 944.1(8) Å3. Due to symmetry considerations, the asymmetric unit comprises a half [Cd(PMT)(Cl)(N3)]2 formula. The Cd(II) is hexa-coordinated with one tridentate PMT ligand in a pincer fashion mode in addition to one terminal chloride and two azide ions bridging the two Cd(II) centers in double μ(1,1) bridging mode. Unusually, the Cd-N(s-triazine) bond is not the shortest among the Cd-N interactions with the PMT pincer ligand. The supramolecular structure of the dinuclear [Cd(PMT)(Cl)(N3)]2 formula is controlled by a significant amount of Cl…H (16.4%), N…H (25.3%), H…C (9.8%) and H…H (37.2%) interactions based on Hirshfeld surface analysis. Careful inspection of the shape index map reveals the presence of some weak π-π stacking interactions between the s-triazine and pyrazolyl moieties. The percentage of C…C contacts is 1.9% where the C2…C8 (3.462 Å) is the shortest while the centroid–centroid distance is 3.686 Å. Natural charge analysis describes the charge transferences from the ligand groups to the Cd(II), while and atoms in molecules (AIM) give an indication on the properties of the Cd-N and Cd-Cl bonds.
Electrical Discharge Machining of Al2O3 Using Copper Tape and TiO2 Powder-Mixed Water Medium
Authors: Grigoriev Sergey N. , Okunkova Anna A. , Volosova Marina A. , Hamdy Khaled , Metel Alexander S.
Published: November 2022

Aluminum-based ceramics are used in industry to produce cutting tools that resist extreme mechanical and thermal load conditions during the machining of Ni-based and high-entropy alloys. There is wide field of application also in the aerospace industry. Microtexturing of cutting ceramics reduces contact loads and wear of cutting tools. However, most of the published works are related to the electrical discharge machining of alumina in hydrocarbons, which creates risks for the personnel and equipment due to the formation of chemically unstable dielectric carbides (methanide Al3C4 and acetylenide Al2(C2)3). An alternative approach for wire electrical discharge machining Al2O3 in the water-based dielectric medium using copper tape of 40 µm thickness and TiO2 powder suspension was proposed for the first time. The performance was evaluated by calculating the material removal rate for various combinations of pulse frequency and TiO2 powder concentration. The obtained kerf of 54.16 ± 0.05 µm in depth demonstrated an increasing efficiency of more than 1.5 times with the closest analogs for the workpiece thickness up to 5 mm in height. The comparison of the performance (0.0083–0.0084 mm3/s) with the closest analogs shows that the results may correlate with the electrical properties of the assisting materials.
Fifty Years of Fixed Optical Networks Evolution: A Survey of Architectural and Technological Developments in a Layered Approach
Authors: Uzunidis Dimitris , Logothetis Michael , Stavdas Alexandros , Hillerkuss David , Tomkos Ioannis
Published: November 2022

Over the past fifty years, telecommunications has transformed, in an unprecedented manner, the way we live, work and communicate. For telecommunications, fixed networks are the one pillar and wireless networks the other. The wireless networks and their generations have been extensively investigated in the literature; however, the fixed networks lack a consistent exploration of their evolution. For this purpose, our motivation is to present a review of the evolution of fixed networks in a holistic manner, from various different perspectives, which can assist engineers and students to understand, in a better way, how broadband networks developed and the main features of the current networking environment. Specifically, in this review, we aim to shed light on the most important technologies, standards and milestones of the fixed networks from various perspectives, such as the service perspective, the networking perspective (both access and core part) and the physical layer perspective. Our study follows the timeline of the five generations of fixed networks defined by the European Telecommunications Standards Institute (ETSI) F5G group and discusses the key achievements and limitations of each generation for each different infrastructure layer and segment, designating the most important issues for the most widely-adopted technologies and standards. Finally, our analysis helps to reveal the technical challenges that need to be addressed by the fixed telecom network community, such as energy efficiency, capacity scaling, cost-efficiency, etc., while also revealing potential future directions.
Modelling the Spatial and Temporal Dynamics of Paralytic Shellfish Toxins (PST) at Different Scales: Implications for Research and Management
Authors: Díaz Patricio A. , Molinet Carlos , Seguel Miriam , Niklitschek Edwin J. , Díaz Manuel , Álvarez Gonzalo , Pérez-Santos Iván , Varela Daniel , Guzmán Leonardo , Rodríguez-Villegas Camilo , Figueroa Rosa I.
Published: November 2022

Harmful algal blooms, in particular recurrent blooms of the dinoflagellate Alexandrium catenella, associated with paralytic shellfish poisoning (PSP), frequently limit commercial shellfish harvests, resulting in serious socio-economic consequences. Although the PSP-inducing species that threaten the most vulnerable commercial species of shellfish are very patchy and spatially heterogeneous in their distribution, the spatial and temporal scales of their effects have largely been ignored in monitoring programs and by researchers. In this study, we examined the spatial and temporal dynamics of PSP toxicity in the clam (Ameghinomya antiqua) in two fishing grounds in southern Chile (Ovalada Island and Low Bay). During the summer of 2009, both were affected by an intense toxic bloom of A. catenella (up to 1.1 × 106 cells L−1). Generalized linear models were used to assess the potential influence of different environmental variables on the field detoxification rates of PSP toxins over a period of 12 months. This was achieved using a four parameter exponential decay model to fit and compare field detoxification rates per sampling site. The results show differences in the spatial variability and temporal dynamics of PSP toxicity, given that greater toxicities (+10-fold) and faster detoxification (20% faster) are observed at the Ovalada Island site, the less oceanic zone, and where higher amounts of clam are annually produced. Our observations support the relevance of considering different spatial and temporal scales to obtain more accurate assessments of PSP accumulation and detoxification dynamics and to improve the efficacy of fisheries management after toxic events.
Zearalenone Exposure Affects the Keap1–Nrf2 Signaling Pathway and Glucose Nutrient Absorption Related Genes of Porcine Jejunal Epithelial Cells
Authors: Cheng Qun , Jiang Shuzhen , Huang Libo , Wang Yuxi , Yang Weiren
Published: November 2022

This study aims to examine the impact of zearalenone (ZEA) on glucose nutrient absorption and the role of the Kelch-like erythroid cell-derived protein with CNC homology-associated protein 1 (Keap1)–nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway in zearalenone-induced oxidative stress of porcine jejunal epithelial cells (IPEC-J2). For 24 and 36 h, the IPEC-J2 cells were exposed to ZEA at concentrations of 0, 10, 20, and 40 (Control, ZEA10, ZEA20, ZEA40) mol/L. With the increase of ZEA concentration and prolongation of the action time, the apoptosis rate and malondialdehyde level and relative expression of sodium-dependent glucose co-transporter 1 (Sglt1), glucose transporter 2 (Glut2), Nrf2, quinone oxidoreductase 1 (Nqo1), and hemeoxygenase 1 (Ho1) at mRNA and protein level, fluorescence intensity of Nrf2 and reactive oxygen species increased significantly (p < 0.05), total superoxide dismutase and glutathione peroxidase activities and relative expression of Keap1 at mRNA and protein level, fluorescence intensity of Sglt1 around the cytoplasm and the cell membrane of IPEC-J2 reduced significantly (p < 0.05). In conclusion, ZEA can impact glucose absorption by affecting the expression of Sglt1 and Glut2, and ZEA can activate the Keap1-Nrf2 signaling pathway by enhancing Nrf2, Nqo1, and Ho1 expression of IPEC-J2.
SARS-CoV-2 Variants of Concern and Variations within Their Genome Architecture: Does Nucleotide Distribution and Mutation Rate Alter the Functionality and Evolution of the Virus?
Authors: Ravi Varsha , Swaminathan Aparna , Yadav Sunita , Arya Hemant , Pandey Rajesh
Published: November 2022

SARS-CoV-2 virus pathogenicity and transmissibility are correlated with the mutations acquired over time, giving rise to variants of concern (VOCs). Mutations can significantly influence the genetic make-up of the virus. Herein, we analyzed the SARS-CoV-2 genomes and sub-genomic nucleotide composition in relation to the mutation rate. Nucleotide percentage distributions of 1397 in-house-sequenced SARS-CoV-2 genomes were enumerated, and comparative analyses (i) within the VOCs and of (ii) recovered and mortality patients were performed. Fisher’s test was carried out to highlight the significant mutations, followed by RNA secondary structure prediction and protein modeling for their functional impacts. Subsequently, a uniform dinucleotide composition of AT and GC was found across study cohorts. Notably, the N gene was observed to have a high GC percentage coupled with a relatively higher mutation rate. Functional analysis demonstrated the N gene mutations, C29144T and G29332T, to induce structural changes at the RNA level. Protein secondary structure prediction with N gene missense mutations revealed a differential composition of alpha helices, beta sheets, and coils, whereas the tertiary structure displayed no significant changes. Additionally, the N gene CTD region displayed no mutations. The analysis highlighted the importance of N protein in viral evolution with CTD as a possible target for antiviral drugs.
Insights on 21 Years of HBV Surveillance in Blood Donors in France
Authors: Cappy Pierre , Boizeau Laure , Candotti Daniel , Le Cam Sophie , Martinaud Christophe , Pillonel Josiane , Tribout Martin , Maugard Claude , Relave Josiane , Richard Pascale , Morel Pascal , Laperche Syria
Published: November 2022

Hepatitis B virus (HBV) infection is the most frequent viral infection found in blood donors (BDs) in France. We analyzed the epidemiological and sero-molecular data on HBV infection gathered over the past two decades by the French haemovigilance surveillance network, blood screening laboratories, and the national reference center for transfusion infectious risks (NRC). Between 2000 and 2020, 6149 of the 58,160,984 donations (1.06/10,000) tested HBV positive, 98% of them from first-time blood donors (FTBDs). In addition, 2212 (0.0071%) of the 30,977,753 donations screened for HBV DNA tested DNA positive, of which 25 (1.1%) were positive only for this marker. HBV prevalence decreased by 2.8-fold and the residual risk for transfusion-transmitted HBV infection decreased 13-fold and was divided by 13. The major risk factor for HBV infection was the origin of donors (endemic country, 66.5%), followed by parenteral exposure (10.7%). In the whole HBV-positive BD population, genotype D was predominant (41.8%), followed by genotypes A (26.2%) and E (20.4%), reflecting the geographical origin of donors. The low and decreasing prevalence and incidence of HBV infection in French BDs, coupled with a screening strategy using three HBV markers (HBsAg, anti-HBc and DNA), ensures a high level of blood safety, further reinforced by the implementation of pathogen-reduction measures.