bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling Conceptual Framework for Implementing Barriers of AI in Public Healthcare for Improving Operational Excellence: Experiences from Developing Countries
Authors: Joshi Sudhanshu , Sharma Manu , Das Rashmi Prava , Rosak-Szyrocka Joanna , Żywiołek Justyna , Muduli Kamalakanta , Prasad Mukesh
Published: September 2022

This study work is among the few attempts to understand the significance of AI and its implementation barriers in the healthcare systems in developing countries. Moreover, it examines the breadth of applications of AI in healthcare and medicine. AI is a promising solution for the healthcare industry, but due to a lack of research, the understanding and potential of this technology is unexplored. This study aims to determine the crucial AI implementation barriers in public healthcare from the viewpoint of the society, the economy, and the infrastructure. The study used MCDM techniques to structure the multiple-level analysis of the AI implementation. The research outcomes contribute to the understanding of the various implementation barriers and provide insights for the decision makers for their future actions. The results show that there are a few critical implementation barriers at the tactical, operational, and strategic levels. The findings contribute to the understanding of the various implementation issues related to the governance, scalability, and privacy of AI and provide insights for decision makers for their future actions. These AI implementation barriers are encountered due to the wider range of system-oriented, legal, technical, and operational implementations and the scale of the usage of AI for public healthcare.
Impact of Environmental Regulations on High-Quality Development of Energy: From the Perspective of Provincial Differences
Authors: Guo Quan , Hong Jun , Rong Jing , Ma Haiyan , Lv Mengnan , Wu Mengyang
Published: September 2022

Environmental regulation plays an important role in the green development of energy, and there are different classifications of environmental regulations in academic circles. This paper attempts to divide environmental regulation into “pure” formal environmental regulations and informal environmental regulations. By selecting the official statistical data samples of 30 provinces, autonomous regions and municipalities in China from 2005 to 2020, and by referring to the Malmquist productivity index method and the mediation effect model, we explore pure environmental regulations. By analyzing the influence mechanism of “pure” formal environmental regulations and informal environmental regulation on energy green development, it is concluded that: (1) Informal environmental regulations have direct and indirect roles in promoting the energy green development index. (2) There is a “U-shaped” relationship between “pure” formal environmental regulations and green energy development. Based on the above conclusions, relevant suggestions are put forward. At the same time, through this division of environmental regulations, on the one hand, it provides a basis for the government to accurately formulate environmental policies, and on the other hand, it provides strong support for the government to scientifically implement environmental policies.
Intermodal Green p-Hub Median Problem with Incomplete Hub-Network
Authors: Ibnoulouafi El Mehdi , Oudani Mustapha , Aouam Tarik , Ghogho Mounir
Published: September 2022

In the literature, hub-networks have often been modeled such as only one mode is considered for all transportation. Also, the consolidated demand flows are assumed to be transferred directly between each origin-destination hub pairs. The previous assumptions impose restrictions on the practical applications of such hub-networks. In fact, various transport modes are usually retained for freight transport, and intermodal terminals (e.g., rail terminals) may not realistically be fully connected. Thus, to assist decision makers, we investigate if the appropriate use of more eco-friendly transportation modes in incomplete networks may contribute to the accomplishment of the significant global reduction goals in carbon emissions. In this paper, we study the intermodal green p-hub median problem with incomplete hub-network. For each p located hub nodes, the hub-network is connected by at most q hub-links. The objective is to minimize the total transportation-based CO2 emission costs incurred through the road- and rail-transportation of each o-d demand flows. We present a MILP formulation for the studied problem and propose a novel genetic algorithm to solve it. A penalty cost is considered on solutions where train capacity is exceeded. Additionally, we present a best-path construction heuristic to generate the initial population. Furthermore, we develop a demand flows routing heuristic to efficiently determine the partition of demand flows in the incomplete road-rail network. And we implement novel crossover and mutation operators to produce new off-springs. Extensive computational experiments show that the proposed solution approach outperforms the exact solver CPLEX. Also, we perform a comparison between the unimodal and intermodal cases, and offer a discussion on the tuning of freight trains.
Improving Computational Thinking and Teamwork by Applying Balanced Scorecard for Sustainable Development
Authors: Chang Lung-Chun , Lin Wen-Cheng
Published: September 2022

This work aimed to analyze the concept of a balance scorecard (BSC) tool integrated with computational thinking (CT) in university education. An experiential approach to learning about the CT through the study of a BSC performance evaluation tool has been reported. The BSC project offers students hands-on experience with the team-based, cross-functional, and strategic aspects of conceptual thinking. This study integrates the four aspects of the BSC into CT to evaluate students through four perspectives. The experiential approach requires each student to compose a team, find information about their motivation, and develop BSC concepts that apply learning performance in a computational thinking course. The conclusion suggests that the BSC project had a positive impact on the students who participated, indicating their overall knowledge and understanding of functional areas and relationships within the teamwork cooperation were enhanced. Our paper reports an experiential method of learning CT by studying BSC performance evaluation tools. The application example can enhance students’ logical thinking, what is indispensable and essential in maintaining competitiveness.
Potentials for Sponge City Implementation in Sub-Saharan Africa
Authors: Thoms Anna , Köster Stephan
Published: September 2022

Despite the growing interest in implementing sponge cities (SPC), their potential is not yet being tapped in many fast-growing Sub-Saharan African cities. This is remarkable because SPC interventions can contribute considerably to increasing water safety and availability in a city. By means of a three-stage potential assessment, this study provides the first analysis of what concrete options can be identified for implementing the SPC concept in Sub-Saharan cities. The methodology was filled with information obtained especially from expert interviews, literature reviews, and satellite imagery. Thus, the analysis also considers what obstacles impede SPC implementation, and, in particular, what technical and socioeconomic constraints need to be taken into account. The cities of Hawassa (Ethiopia), Beira (Mozambique), Kigali (Rwanda), Ouagadougou (Burkina Faso), and Cotonou (Benin) are examined in detail. Additionally, a local SPC implementation was conceptualized and evaluated for two districts in Ouagadougou and Cotonou. The first finding is that, when geographical and socioeconomic aspects such as climatic patterns, migration flows, health risks, and existing infrastructure are sufficiently taken into account, SPC interventions would massively help African cities to mitigate current and urgent challenges such as water scarcity and urban flooding. In terms of water safety, the second key finding is that rainwater harvesting solutions at the household level could be implemented quickly; however, there would be substantial difficulties such as lack of financing and maintenance as well as claims of ownership, especially in informal settlements and slums. Thus, it seems quite promising to directly strive for a rapid “centralization” of SPC implementation in individual neighborhoods. This neighborhood approach paves the way for SPC measures to receive public acceptance and constant maintenance. When this mosaic of implementations comes together, many individual instances of SPC implementation can help to improve urban resilience and living conditions for the city dwellers as is here demonstrated for the districts in Cotonou and Ouagadougou.
Elemental Composition and Freezing Tolerance in High Arctic Fishes and Invertebrates
Authors: Singh Shiv , Tsuji Masaharu , Singh Purnima , Mulik Ravindra
Published: September 2022

The elemental composition in different Arctic fishes and invertebrates was investigated using Inductively Coupled Plasma Mass Spectrophotometer (ICPMS). Nineteen elements such as Arsenic (As), Barium (Ba), Bismuth (Bi), Cadmium (Cd), Cesium (Cs), Chromium (Cr), Cobalt (Co), Copper (Cu), Iron (Fe), Lead (Pb), Manganese (Mn), Nickel (Ni), Rubidium (Rb), Selinium (Se), Silver (Ag), Strontium (Sr), Uranium (U), Vanadium (V), and Zinc (Zn) were analyzed in six species of fishes (Anarhichas lupus, Gadus ogac, Gadus morhu, Gymnocanthus tricuspis, Liparis sp., Myoxocephalus scorpius) and four benthic invertebrates (Ophiura albida, O. Sarsii, Strongylocentrotus droebachiensis, Polychaete). Elemental data revealed that the invertebrates accumulate higher concentrations of elements than the fishes. The high concentration of elements including Sr, As, and Zn indicated anthropogenic contribution and may affect the fish community in the fragile ecosystem of the High Arctic. The movement of tourists and logistics must be regulated to prevent serious change in Svalbard. Most of the fishes have shown strong antifreeze protein (AFP) activity, and this potential helps fishes to survive in the cold Arctic environment. This is the first study of elemental concentrations and AFPs in fishes and benthic invertebrates filling the knowledge gap from the High Arctic.
Positive Psychology Applied to Education in Practicing Teachers during the COVID-19 Pandemic: Personal Resources, Well-Being, and Teacher Training
Authors: García-Álvarez Diego , Soler María José , Cobo-Rendón Rubia , Hernández-Lalinde Juan
Published: September 2022

Teaching has often been linked to psychosocial problems, and is an occupation in which the implementation of strategies for the improvement, updating and promotion of the mental health of those involved is essential. Accordingly, this study assessed the effectiveness of a program aimed at improving psychological well-being, optimism, self-efficacy, and self-esteem as well as at reducing psychological distress in teachers. The study was quasi-experimental and comprised 24 teachers from technical, secondary, and elementary schools in Uruguay. The constructs were measured before and after the program, which was conducted during the COVID-19 pandemic and comprised 12 modules in a multicomponent intervention format. The results indicate a significantly low magnitude increase in well-being (F = 5.36, p = 0.033, Cohen’s d = 0.47) and a moderate increase in self-efficacy (F = 9.14, p = 0.008, Cohen’s d = 0.62). Similarly, a significant decrease was observed in psychological distress of mild effect (F = 5.80, p = 0.028, Cohen’s d = 0.49). To conclude, interventions based on positive psychology improve teachers’ well-being, enhance other psychological resources, and reduce psychosocial risks such as discomfort. Thus, these interventions can be devices for career development and teacher updating.
An Experimental Method to Determine Rock Joint Stiffness under Constant Normal Load Conditions
Authors: Li Dong , An Guanfeng , Chen Xiangsheng , Dang Wengang , Li Dongyang
Published: September 2022

Being physical mechanical parameters of joints, normal and shear stiffnesses are indispensable components of the numerical simulation and theoretical analysis of the behavior of joints. The objective of this work is to put forward an experimental method to determine joint stiffness under constant normal load (CNL) conditions. For this purpose, joint closure and direct shear tests under CNL conditions were conducted. Normal stiffness was determined by the ratio of normal stress increment and the corresponding normal displacement; the shear stiffness was calculated by the ratio of shear stress increment to the relative shear displacement. The average and instantaneous shear stiffness were distinguished. Experimental results showed that joint normal and shear stiffness are time and spatially varying parameters during direct shearing. With increasing normal stress, average shear stiffness, maximum instantaneous shear stiffness, and normal stiffness increases. Normal stiffness was about 26–28 times higher than the average shear stiffness under one normal stress level. Average shear stiffness was little influenced by shear velocity. Instantaneous shear stiffness shows the velocity-dependent behavior. Maximum instantaneous shear stiffness decreases rapidly with increasing shear rate. At lower shear velocity, maximum instantaneous shear stiffness is higher than normal stiffness; minimum instantaneous shear stiffness can be negative and the absolute value also decreases with faster shear velocity. These findings provide a reference for selecting the appropriate value of normal and shear stiffness for evaluation of the mechanical response of interface.
Performance Measurement in R&D Projects: Relevance of Indicators Based on US and German Experts
Authors: Zemlickienė Vaida , Turskis Zenonas
Published: September 2022

To turn technologies into successful products, it is necessary to understand the development process from ideas to the market and to know how to measure performance. Performance measurement is critical for technology developers and investors in monitoring whether performance meets expectations to make decisions about actions for improving R&D characteristics. This article emphasizes indicators for R&D project performance measurement, especially relevant for measuring project performance in company, start-up and spin-off companies, where the project is perceived as an independent business unit. A clear set of indicators for measuring and controlling the performance of R&D projects for policy representatives would allow them to identify problematic areas in the implementation of R&D projects and to make well-aimed decisions for the promotion and financing of technology development. What indicators should be used to measure the performance of R&D projects? Attempts to find the answer to the question in science were unsuccessful. This article aims to select indicators for measuring the performance of R&D projects and identify and compare their relevance among US and German experts. Research is carried out in different countries, and their results create opportunities for mutual learning and more intensive international cooperation in technological development. In order to achieve a goal, essential decision-making points in R&D projects were identified, and a general set of R&D performance evaluation indicators were prepared based on a literature analysis. Later, two groups of experts from the US and Germany selected from the general list indicators suitable only for evaluating R&D projects and evaluated their relevance. The obtained evaluation results of the US and German experts were processed using the MCDM method and compared.
Stimuli-Responsive Macromolecular Self-Assembly
Authors: Jiang Chunqiang , Xu Guohe , Gao Jianping
Published: September 2022

Macromolecular self-assembly has great potential for application in the field of the design of molecular machines, in molecular regulation, for biological tissue, and in biomedicine for the optical, electrical, and biological characteristics that the assembly unit does not possess. In this paper, the progress in macromolecular self-assembly is systematically reviewed, including its conception, processes and mechanisms, with a focus on macromolecular self-assembly by stimuli. According to the difference in stimuli, macromolecular self-assembly can be classified into temperature-responsive self-assembly, light-responsive self-assembly, pH-responsive self-assembly, redox-responsive self-assembly, and multi-responsive self-assembly. A preliminary study on constructing dynamic macromolecular self-assembly based on a chemical self-oscillating reaction is described. Furthermore, the problems of macromolecular self-assembly research, such as the extremely simple structure of artificial self-assembly and the low degree of overlap between macromolecular self-assembly and life sciences, are analyzed. The future development of stimuli-responsive macromolecular self-assembly should imitate the complex structures, processes and functions in nature and incorporate the chemical-oscillation reaction to realize dynamic self-assembly.
Analyzing Spatio-Temporal Change in Ecosystem Quality and Its Driving Mechanism in Henan Province, China, from 2010 to 2020
Authors: Ren Xiaoyun , Zhang Mingkong , Qian Juncheng , Li Shuangquan , Wang Jingxu , Du Jun
Published: September 2022

Henan Province is an important ecological barrier in the middle and lower reaches of the Yellow River. It is of great significance to study its ecosystem quality and the driving mechanisms behind this in order to realize ecological conservation and high-quality development in the Yellow River Basin. In this study, from the perspective of physical elements, socioeconomic elements, and policy adjustments, multi-source data on land use, population density, forestry engineering, and other indicators were selected to construct an index system of the driving factors of ecosystem quality in Henan Province. The characteristics of spatio-temporal change and the formation mechanism of ecosystem quality in Henan Province from 2010 to 2020 were analyzed by comprehensively using the gravity center analysis method and a geo-detector tool. The results showed the following: (1) The ecosystem quality of Henan Province in 2020 has increased by 27.7% compared with that in 2010, and the center of gravity of ecosystem quality continued to move to the northwest of Henan Province. The quality of ecosystems in the hilly region of Western Henan, Tongbai, and Nanyang was better than that in the northern Loess Platform Hilly Area and the Yellow River Plain, and it presented a spatial pattern in which the quality of the south was higher than that of the north, while the east and west were equal; (2) From 2010 to 2020, the average GDP and population density in Henan Province were the most important factors affecting the quality of its ecosystem. The effect of land-use diversity on ecosystem quality in the hilly region of Henan Province was stronger than that in the central and eastern plains; and (3) The interactions among the driving factors were mainly nonlinear enhancement and double factor enhancement, in which the interaction between socio-economic elements and natural environmental elements was the dominant interaction mode and could enhance the impact on the quality of the regional ecological environment. The results of this study indicate that attention should be paid to generating targeted industrial economy layout and land use policies in different natural domains. Moreover, forestry protection engineering policies should be further strengthened to improve the resilience of ecosystem quality to human activities.
Effect of Carboxylic Acids on Corrosion of Type 410 Stainless Steel in Pyrolysis Bio-Oil
Authors: Sulejmanovic Dino , Keiser James R. , Su Yi-Feng , Kass Michael D. , Ferrell Jack R. , Olarte Mariefel V. , Wade John E. , Jun Jiheon
Published: September 2022

Biomass-derived oils are renewable fuel sources and commodity products and are proposed to partially or entirely replace fossil fuels in sectors generally considered difficult to decarbonize such as aviation and maritime propulsion. Bio-oils contain a range of organic compounds with varying functional groups which can lead to polarity-driven phase separation and corrosion of containment materials during processing and storage. Polar compounds, such as organic acids and other oxygenates, are abundant in bio-oils and are considered corrosive to structural alloys, particularly to those with a low-Cr content. To study the corrosion effects of small carboxylic acids present in pyrolysis bio-oils, type 410 stainless steel (SS410) specimens were exposed in bio-oils with varying formic, acetic, propionic and hexanoic acid contents at 50 °C during 48 h exposures. The specific mass change data show a linear increase in mass loss with increasing formic acid concentration. Interestingly, a mild corrosion inhibition effect on the corrosion of SS410 specimens was observed with the addition of acetic, propionic and hexanoic acids in the bio-oil.
Tab2vox: CNN-Based Multivariate Multilevel Demand Forecasting Framework by Tabular-To-Voxel Image Conversion
Authors: Lee Euna , Nam Myungwoo , Lee Hongchul
Published: September 2022

Since demand is influenced by a wide variety of causes, it is necessary to decompose the explanatory variables into different levels, extract their relationships effectively, and reflect them in the forecast. In particular, this contextual information can be very useful in demand forecasting with large demand volatility or intermittent demand patterns. Convolutional neural networks (CNNs) have been successfully used in many fields where important information in data is represented by images. CNNs are powerful because they accept samples as images and use adjacent voxel sets to integrate multi-dimensional important information and learn important features. On the other hand, although the demand-forecasting model has been improved, the input data is still limited in its tabular form and is not suitable for CNN modeling. In this study, we propose a Tab2vox neural architecture search (NAS) model as a method to convert a high-dimensional tabular sample into a well-formed 3D voxel image and use it in a 3D CNN network. For each image representation, the 3D CNN forecasting model proposed from the Tab2vox framework showed superior performance, compared to the existing time series and machine learning techniques using tabular data, and the latest image transformation studies.
A Novel Production Scheduling Approach Based on Improved Hybrid Genetic Algorithm
Authors: Dai Lili , Lu He , Hua Dezheng , Liu Xinhua , Chen Hongming , Glowacz Adam , Królczyk Grzegorz , Li Zhixiong
Published: September 2022

Due to the complexity of the production shop in discrete manufacturing industry, the traditional genetic algorithm (GA) cannot solve the production scheduling problem well. In order to enhance the GA-based method to solve the production scheduling problem effectively, the simulated annealing algorithm (SAA) is used to develop an improved hybrid genetic algorithm. Firstly, the crossover probability and mutation probability of the genetic operation are adjusted, and the elite replacement operation is adopted for simulated annealing operator. Then, a mutation method is used for the comparison and replacement of the genetic operations to obtain the optimal value of the current state. Lastly, the proposed hybrid genetic algorithm is compared with several scheduling algorithms, and the superiority and efficiency of the proposed method are verified in solving the production scheduling.
Do Education and Employment Play a Role in Youth’s Poverty Alleviation? Evidence from Morocco
Authors: Yassine Abderrahman , Bakass Fatima
Published: September 2022

In Morocco, youth represent a large segment of society, but there are multiple structural constraints, such as unemployment, particularly among graduates, which exposes them to a great risk of poverty. Using data from the Household Consumption and Expenditure National Survey 2014, this article explores the determinants of youth poverty, focusing on the role of education and employment. Two indicators of poverty are used. The first one is a binary short-term indicator showing whether the young in a given household are poor or not at the threshold of 60% of the median annual expenditure. The second is a poverty measure of the long-term economic status or what is called the Wealth Index, computed using the Principal Component Analysis method. The results from both the logit and the quantile regressions show that being more educated constitutes a rampart against poverty for young people. By contrast, access to employment is not enough to guarantee a decent level of well-being. Moreover, there are no gender differences, but poverty seems higher among rural young and those between 15 and 19 years old compared to those who reside in the urban areas and who are between 20 and 29 years old, respectively. Youth poverty is also significantly associated with family/household characteristics such as education and employment of the other members and household size.
A Study on the Sustainable Development of Historic District Landscapes Based on Place Attachment among Tourists: A Case Study of Taiping Old Street, Taiwan
Authors: Zhu Xiaoyang , Chiou Shang-Chia
Published: September 2022

Historic districts should be sustainably developed by preserving historic architectural landscapes and developing tourism. Researchers have found that attachment to a place positively influences pro-tourism and pro-environment behaviors among tourists, indicating that exploring the landscape planning of historic districts from the perspective of place attachment is a noteworthy topic of sustainability. However, there are few studies on how historic district landscapes ignite tourists’ place attachment. Using a historical district named Taiping Old Street in Taiwan as an example, we investigated the association between tourists’ landscape evaluation and place attachment in historic districts. This study mainly adopted questionnaire surveys and used partial least squares structural (PLS) equation modeling for survey data analysis. (1) The study identified three dimensions of tourists’ landscape evaluation of historic districts: visual preference, cultural heritage value, and authenticity. (2) The stimulus–organism–response (SOR) model was combined with the studies by previous scholars and a conceptual model put forward for the relationship between tourists’ landscape evaluation, destination image, and place attachment. (3) The model was verified, and we found that (i) tourists’ landscape evaluation in terms of cultural heritage values and authenticity had significant positive effects on destination image; (ii) tourists’ visual preference, evaluation of authenticity, and destination image had significant positive effects on place attachment; and (iii) tourists’ destination image influenced the impact of authenticity and cultural heritage values on place attachment. This study provides both theoretical references for the formation process of place attachment from a landscape perspective and suggestions for landscape planning in the sustainable development of historic districts of a similar type.
Winter Tolerance Potential of Genetically Diverse Sugarcane Clones under Subtropical Climate of Northern India
Authors: Kumar Ravinder , Meena Mintu , Dhansu Pooja , Karuppaiyan R. , Appunu C. , Kulshreshtha Neeraj , Kaushik Prashant , Ram Bakshi
Published: September 2022

The low temperature (LT) conditions that prevail during winter in subtropical regions of India drastically affect the growth and yield of sugarcane. To identify low-temperature-tolerant agronomical acceptable genotypes for immediate deployment as donor parents in the subtropical sugarcane breeding program, 34 sugarcane clones belonging to 7 genetically diverse groups were evaluated under three crop environments, viz., spring planting, winter ratoon and spring ratoon, during 2015–2016 and 2016–2017. In the winter ratoon crop, commercial cane sugar and cane yield were reduced, whereas sucrose % was increased over the spring planted crop and the spring ratoon crop. The wild species and introgressed hybrid groups showed improvement for yield and quality traits in the winter ratoon crop, whereas commercial and near commercial groups showed reduction for these traits over the plant and spring ratoon crops. The tropical cultivars group was the poorest performer irrespective of the traits and crops. Yield per se under a stress environment was adjudged as the best selection criteria. For classification of sugarcane clones according to their low temperature tolerance, an index named winter tolerance index (WTI) is proposed which takes into account the winter sprouting index (WSI), winter growth and yield per se of the winter ratoon crop. The WTI had significant positive association with WSI, cane yield, millable cane population and cane length. As per the WTI ratings, the wild species of Saccharum complex and introgressed hybrid groups were rated as excellent WT clones. Subtropical commercial or advanced generation groups were poor WT clones, and tropical commercial cultivars group were winter sensitive clones. Clones such as AS04-635, AS04-1687, IK76-48, GU07-2276, IND00-1040, IND00-1038 and IND00-1039 had excellent tolerance, and GU07-3849, AS04-245, Co 0238, AS04-2097 and GU07-3774 had good WTI scores. The variety, Co 0238, may be continued for cultivation under LT regions with prophylactic measurers for red rot, while other clones listed above may be utilized in subtropical breeding programs.
Utilization of Colored Extracts for the Formulation of Ecological Friendly Plant-Based Green Products
Authors: Adeel Shahid , Habiba Maryam , Kiran Shumaila , Iqbal Sarosh , Abrar Shazia , Hassan Ch Moazzam
Published: September 2022

Green or sustainable cosmetics are products that contain natural ingredients obtained from renewable raw materials. Fruit peels represent a sustainable source of bioactive compounds. Polyphenols, e.g., flavonoids, have the ability to scavenge free radicals; thus they exhibit antioxidant activity. Recently, natural antioxidants have been in the limelight as being safe, effective, and versatile. In this study, antioxidant effects and the sun protection ability of apple (Malus domestica), banana (Musa sapientum), and orange (Citrus reticulata) peel extracts were evaluated in skincare formulations. The extraction of phenolic compounds was performed in three different solvents, i.e., ethanol, methanol, and acetone. Total phenolic contents, antioxidant activity, and sun protection factor were determined for the fruit peel extracts. The acetone extract of apple and ethanol extract of banana peels contained polyphenols, i.e., 24.3 ± 1.5 and 26.7 ± 0.6 mg GAE per gram of the extracts, respectively. These extracts showed DPPH radical scavenging activity and were incorporated into oil-in-water (O/W) cosmetic emulsions. All the formulated samples were found to be stable when subjected to centrifuging and thermal stress. Antioxidant activities of cream samples were above 80%, and the sun protection factor was above 15. The results have confirmed the applications of fruit peel waste in the formulation of photostable, antioxidant, and sun screen formulations. These creams would help to maintain skin health, protect it from UV radiation, and reduce the aging effect. Thus, fruit peel waste could present an ecofriendly and sustainable source of natural antioxidants for the personal care industry.
Analysis and Sizing of Charging Stations in Kota City
Authors: Verma Rohan , Sharma Santosh Kumar , Singh Pushpendra , Bhutto Javed Khan , Alharbi Abdul Rahman Abdullah
Published: September 2022

This paper focuses on optimization of charging station capacities and locations. The proliferation of electric vehicles is inextricably linked to the deployment of charging infrastructure. Currently, there are issues with locating and sizing when it comes to the building of electric vehicle charging stations. In order to find out the capacity of charging stations, a mathematical model was developed, which includes a site survey, EV density, electricity demand analysis, load modeling, costing analysis, EV battery charging time and power quality. The proposed approach was tested in MATLAB/Simulink environment.
Exploring the Spatiotemporal Characteristics and Causes of Rear-End Collisions on Urban Roadways
Authors: Zhang Wenhui , Liu Tuo , Yi Jing
Published: September 2022

Rear-end collisions are caused by drivers misjudging urgent risks while following vehicles ahead in most cases. However, compared with other accident types, rear-end collisions have higher preventability. This study aims to reveal the prone segments and hours of rear-end collisions. First, we extracted 1236 cases from traffic accident records in Harbin from 2015 to 2019. These accidents are classified as property damage accidents, injury accidents and fatal accidents according to the collision severity. Second, density analysis in GIS was used to demonstrate the spatial distribution of rear-end collisions. The collision spots considering the density and severity were visually displayed. We counted the hourly and seasonal distribution characteristics according to the statistical data. Finally, LightGBM and random forest classifier models were used to evaluate the substantial factors affecting accident severity. The results have potential practical value in rear-end collision warning and prevention.
Multi-Variable Governance Index Modeling of Government’s Policies, Legal and Institutional Strategies, and Management for Climate Compatible and Sustainable Agriculture Development
Authors: Iqbal Kanwar Muhammad Javed , Akhtar Nadia , Amir Sarah , Khan Muhammad Irfan , Shah Ashfaq Ahmad , Tariq Muhammad Atiq Ur Rehman , Ullah Wahid
Published: September 2022

Agriculture has a very strong nexus with water and energy sectors due to their complex interdependence and interplay in the context of adaptation, resilience, mitigation, and low carbon development to cope with the increasing effects of a changing climate. The situation demands a comprehensive response in terms of policies, legal instruments, institutional strategies, and management in the national, sub-national, and local contexts of the governance for climate compatibility, environmental security, and sustainable agriculture development; particularly in developing countries, as they are at the forefront of a high vulnerability risk and severe environmental insecurity due to a business-as-usual complex and weak governance. Therefore, the present study aimed to assess the adequacy of the climate response vis-à-vis policies, legal and other appropriate arrangements in place for agriculture governance by reviewing the high vulnerability case of Pakistan. Considering the need, the assessment model was developed using the first climate principle, nine criteria, and 43 composite indicators. A multi-criteria decision analysis method along with Simple Multi Attribute Rating Technique (SMART) on a ratio scale, combining qualitative and quantitative data and employing rule-based and rights-based governance approaches were adopted to collect and analyze a dataset of 357 observations from 17 locations, which were validated through Pearson Correlation, Regression, and KW H-Tests. The findings reveal significant gaps at the federal, provincial, and district levels in policies, legal and institutional strategies to step forward the climate agenda in Pakistan’s agriculture sector. However, the inadequacy is not homogenous at all levels of governance. The overall situation is similar to what has been reported in developing countries in the United Nations Report on Sustainable Development Goals (SDGs) 2020. Provincial climate strategies are required along with enhanced coordination and capacities for execution at all tiers of constituencies.
Strength Deterioration Model of Soft Rock Considering Mesoscopic Bonding–Expansion Coupling Mechanism under Freeze–Thaw Cycles
Authors: Xia Chang , Liu Zhen , Zhou Cuiying
Published: September 2022

The mechanical deterioration of soft rocks under freeze–thaw cycles is caused by the accumulation of mesoscopic damage. However, the current freeze–thaw deterioration model for soft rocks does not adequately consider the multiscale correlations, which makes the strength calculation results differ greatly from the test results and cannot fully reveal the damage mechanism of soft rocks under freeze–thaw cycling conditions. In this paper, the bond damage and pore ice expansion laws are considered from the soft-rock mesoscopic bond unit and a multiscale strength deterioration model is proposed. The freeze–thaw deterioration model is extended to intact and cracked soft rocks by the Discrete Element Method (DEM). The results are validated by laboratory tests. The peak strengths of intact soft rocks are calculated within 10% error for different numbers of freeze–thaw cycles, and the macroscopic crack development simulation results are consistent with the laboratory tests. The joints have a significant effect on the damage evolution: the freeze–thaw-induced mesoscopic damage in cracked rocks accumulates at a uniform rate, while the damage in intact soft rocks grows exponentially; the freeze–thaw cracks in cracked soft rocks are distributed between 60 and 90°, with a tensile–shear damage ratio of 1:2; the freeze–thaw cracks in intact soft rocks are distributed around 90°, with a tensile–shear damage ratio of 1:3. The deterioration model proposed in this paper can fully consider the multiscale damage correlations, which renders it easy to promote the application in the freeze–thaw hazard problem of soft rock engineering.
Nexus between Cyclical Innovation in Green Technologies and CO2 Emissions in Nordic Countries: Consent toward Environmental Sustainability
Authors: Ahmed Nihal , Areche Franklin Ore , Nieto Dante Daniel Cruz , Borda Ricardo Fernando Cosio , Gonzales Berenice Cajavilca , Senkus Piotr , Siemiński Paweł , Skrzypek Adam
Published: September 2022

Several economies have acknowledged that environmental degradation poses a serious danger to worldwide sustainable production and consumption. Policy makers concur that the increased use and production of carbon-intensive technologies has intensified the detrimental consequences of carbon dioxide emissions. In response, a number of nations have reacted by enacting stringent regulations and encouraging green technology innovations across corporate and governmental organizations. Evidence that already exists suggests that research and development is a cyclical process; nevertheless, the non-linear influence of shocks in research and development and innovation in green technologies on CO2 emissions in the Nordic nations has not been well investigated. Using panel data from 1995 to 2019, this research explores the asymmetric link between innovation in green technologies and CO2 emissions. The cointegration link between the chosen variables was validated using the Westerlund cointegration test and the Johansen–Fisher panel cointegration test. The findings of both tests confirm the presence of cointegration association between dependent and independent variables. The outcomes of CS-ARDL revealed that negative shocks in creating green technologies contribute to carbon dioxide emissions during recessions. Second, the findings supported the notion that innovation in green technology may reduce carbon dioxide emissions during times of economic expansion. Thirdly, the GDP increases the CO2 emissions, but the usage of renewable energy decreases CO2 emissions. In addition, the robustness analysis validated the consistency and precision of the existing findings. In summary, the findings suggest that the link between advances in environmentally friendly technologies and levels of carbon dioxide emissions were inversely proportional.
Subjective and Objective Evaluation of Shading on Thermal, Visual, and Acoustic Properties of Indoor Environments
Authors: Yang Qing , Li Nianping
Published: September 2022

Through objective measurement, subjective measurement, and prioritization methods, this study evaluates the impacts of different shading facilities on the indoor environment of multi-story residential buildings, such as dormitories. The objective measurements mainly include the operative temperature, daylight factor, and sound pressure level. The subjective measurement is obtained from occupant votes regarding their satisfaction with the thermal uniformity, natural lighting, external noise, and the overall indoor environment. The results show that the subjective evaluations were significantly more reliable than the objective measurements for predicting indoor environmental satisfaction. The prioritization method of the ordered logistic regression was then used to evaluate the impact of perceived indoor environmental quality on overall satisfaction. The results show that the impact of the perceived indoor environmental quality on overall satisfaction varied with the shading facilities. In addition, the occupants commented on the function of items affecting their application preferences and provided recommendations for improving balconies and sunshades to provide occupants with better indoor environments.
City Corporation Activities for Creating Sustainable Population Development in the Opinion of University Students in Gdansk (Poland)
Authors: Chaberek Grażyna , Ziółkowska Julia
Published: September 2022

Nowadays, urban areas very often attract the poor and the unemployed, leading to the creation of neighbourhoods of poverty (slums) and other economic and social problems. All over the world, cities include sustainable goals in their development strategies, but the question is, do these city development strategies also foresee activities devoted to human capital growth? The purpose of the study was an analysis of city corporation activities and of students’ perception of a city corporation’s activities that aim to encourage educated young people to study and settle in their city, using the example of Gdansk, Poland. The study was conducted in 2021–2022, based on desk research and an Internet survey. The research group comprised students at the University of Gdansk (Poland). The main conclusions from the study are: (1) cities’ sustainable policies are slightly integrated with actions meant to encourage highly educated people to settle within; (2) Gdansk students’ decisions to settle are not correlated with city corporation activities, and (3) from Gdansk students’ perspective, preferential accommodation costs are the most expected city corporation actions.
Get Rid of Marine Pollution: Bioremediation an Innovative, Attractive, and Successful Cleaning Strategy
Authors: Aliko Valbona , Multisanti Cristiana Roberta , Turani Blerta , Faggio Caterina
Published: September 2022

Aquatic environmental pollution is a rather worrying and increasingly topical problem that requires the development and promotion of innovative and ecofriendly technologies. Pollutants in water include many common substances that can reach aquatic ecosystems through several pathways including wastewater, the atmosphere, ship discharges, and many other sources. Most of these toxic compounds are internalized by aquatic organisms, leading to bioaccumulation in tissues and reaching any level of the food chain through the biomagnification process. These mechanisms can develop into adverse effects on the physiology of organisms and biochemical processes of natural ecosystems, thus affecting animals, environments, and indirectly, human health. Innovative technologies to tackle marine pollution include bioremediation: a suitable, biological, and ecological approach that enhances the ability of micro-organisms to transform waste and toxic substances into forms that can be used by other organisms. In this context, micro-organisms appear to be essential for the detoxification of aquatic systems due to their metabolic activity. This review provides a careful analysis of the characteristics of the main pollutants that affect aquatic ecosystems, with a focus on their effects on organisms and environments. It also offers clear guidance on innovative biological strategies that can be employed to prevent, limit, and remediate anthropogenic influences on aquatic environments.
Deep Learning Approach for the Detection of Noise Type in Ancient Images
Authors: Pawar Poonam , Ainapure Bharati , Rashid Mamoon , Ahmad Nazir , Alotaibi Aziz , Alshamrani Sultan S.
Published: September 2022

Recent innovations in digital image capturing techniques facilitate the capture of stationary and moving objects. The images can be easily captured via high-end digital cameras, mobile phones and other handheld devices. Most of the time, captured images vary compared to actual objects. The captured images may be contaminated by dark, grey shades and undesirable black spots. There are various reasons for contamination, such as atmospheric conditions, limitations of capturing device and human errors. There are various mechanisms to process the image, which can clean up contaminated image to match with the original one. The image processing applications primarily require detection of accurate noise type which is used as input for image restoration. There are filtering techniques, fractional differential gradient and machine learning techniques to detect and identify the type of noise. These methods primarily rely on image content and spatial domain information of a given image. With the advancements in the technologies, deep learning (DL) is a technology that can be trained to mimic human intelligence to recognize various image patterns, audio files and text for accuracy. A deep learning framework empowers correct processing of multiple images for object identification and quick decision abilities without human interventions. Here Convolution Neural Network (CNN) model has been implemented to detect and identify types of noise in the given image. Over the multiple internal iterations to optimize the results, the identified noise is classified with 99.25% accuracy using the Proposed System Architecture (PSA) compared with AlexNet, Yolo V5, Yolo V3, RCNN and CNN. The proposed model in this study proved to be suitable for the classification of mural images on the basis of every performance parameter. The precision, accuracy, f1-score and recall of the PSA are 98.50%, 99.25%, 98.50% and 98.50%, respectively. This study contributes to the development of mural art recovery.
Experimental Study on Stiffness Degradation of Organic Matter-Disseminated Sand under Cyclic Loading
Authors: Du Juan , Jiang Xingfei , Liu Bingyang , Jia Lin , Zhang Yang
Published: September 2022

Degradation of stiffness will occur in sand under cyclic loading. Organic matter-disseminated sand (OMDS) is a special sand in the northeast and western coastal region of Hainan Island. Through the stress-controlled dynamic triaxial test, the natural moisture content, vibration amplitude and consolidation ratio of OMDS under three types of cyclic loads (sine wave, triangular wave and rectangular wave) were studied. The results showed that the soil stiffness decreases with the increase in vibration times. The increase in natural moisture content and vibration amplitude, and the reduction in the consolidation ratio accelerate the softening of soil stiffness. Furthermore, based on the test results, an empirical formula was derived to reflect the rule of soil stiffness softening.
Repdigits as Sums of Four Tribonacci Numbers
Authors: Zhou Yuetong , Yang Peng , Zhang Shaonan , Zhang Kaiqiang
Published: September 2022

In this paper, we show that 66666 is the largest repdigit expressible as the sum of four tribonacci numbers. We used Binet’s formula, Baker’s theory, and a reduction method during the proving procedure. We also used the periodic properties of tribonacci number modulo 9 to deal with three individual cases.