bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Automotive Test Parameters on Dry Friction Fiber-Reinforced Clutch Facing Surface Microgeometry and Wear—Part 3 Tribological Parameter Correlations and Simulation of Thermo-Mechanical Tribological Contact Behavior
Authors: Kalácska Gábor , Biczó Roland
Published: March 2023

Correlations among previously determined tribological properties, such as the coefficient of friction values, wear and surface roughness differences of hybrid composite dry friction clutch facings are revealed after pin-on-disk test apparatus examinations under three pv loads, where samples are cut from a reference, unused, and several differently aged and dimensioned, used—according to two different trends: dry friction fiber-reinforced hybrid composite clutch facings. In ‘normal use’ facings, increasing specific wear trend is detected as a function of activation energy according to a second-degree function, while a logarithmic trend line can be fitted to the values of the clutch killer facings, showing that even at low activation energy levels, significant (~3%) wear occurs. The specific wear rate also varies as a function of the radius of the friction facing, with the relative wear values measured on the working friction diameter being higher regardless of the usage trend. In terms of surface roughness variation measured in the radial direction, normal use facings show a varying roughness difference according to a third-degree function, while clutch killer facings follow a second-degree or logarithmic trend depending on the diameter (di or dw). From the statistical analysis of the steady-state, we find three different clutch engagement phase characterizing pv level pin-on-disk tribological test results for the specific wear of the clutch killer and normal use facings, and significantly different trend curves with three different sets of functions were obtained, showing that the wear intensity can be described as a function of the pv value and the friction diameter. In terms of radial direction surface roughness difference, the values of clutch killer and normal use samples can be described by three different sets of function showing the effects of the friction radius and pv.
Emerging Scholars in Academia: An Analysis of the Impact of IAPSS Politikon in the Academic Careers of Its Authors
Authors: Figueroa Ana Magdalena , Chukwuma Nzube , Ngcayisa Lumanyano
Published: March 2023

This paper analyzes students, recent graduates, and emerging scholars’ involvement in academic publishing, specifically by studying the impact of their publications in Politikon, the International Association for Political Science Students’ Journal, and their academic careers. The results of a standardized self-administered survey serve to assess authors’ motivations and impact of publish ing with IAPSS Politikon. The data show that publishing with Politikon has helped emerging researchers get more experience concerning the publication process and has improved their research, writing, and analyzing skills. Additionally, an essential part of them said they increased their educational background or obtained a new higher position after publishing with Politikon. In fact, 50 per cent of these scholars said they were promoted after publishing with the journal. Furthermore, Politikon, establishes a platform for Global South scholarship to be at the forefront of Political Science/International Relations debates and knowledge production. This implies the importance of Politikon in the early career of scholars by giving them the right tools to develop professionally and by reaching scholars from all around the world, especially from the Global South in an effort to contribute to global international relations and global governance reform.
Evaluating the Eco-Intensity Dynamics of the Mining Industry in Russia: Towards a Circular Economy
Authors: Elokhova Irina , Vyatkin Kirill , Ilyushin Pavel , Krutova Aleksandra , Pepelyaeva Anna , Sliusar Natalia
Published: March 2023

One of the main tasks of the circular economy is the decoupling between economic growth and natural resource consumption at the input and the volume of generated waste at the output. The effectiveness of this process can be assessed by the dynamics of the eco-intensity indicators at the macro-, meso- and micro-levels. The article presents the assessment results of the decoupling and growth color of the mining sector in Russia, which show the dynamics of eco-intensity indicators and may reflect the trend towards a circular economy. For the period 2010–2021, it was revealed that negative expansion decoupling and “Black” growth have been observed in terms of generated waste and atmospheric pollution, strong decoupling and “Green” growth in terms of hydrosphere pollution, weak decoupling and “Brown” growth in terms of electricity consumption, and according to water intake from natural water bodies, expansion coupling and “Black” growth. During the study period, the gross value added (GVA) of the mining industry in Russia in comparable prices increased by 77%, while the industry’s negative impact on the atmosphere increased by 34%; the volume of production and consumption waste generation increased by 131%, and the negative impact on the hydrosphere decreased by 51%. The growth of the environmental and economic efficiency of any system can be achieved by influencing the drivers and barriers to moving towards a circular economy, so it is important to identify the most significant factors of influence for a particular industry, region or country in the current conditions. Using the ordinary least squares (OLS) method, it was revealed that factors reflecting innovative activities of the mining industry have a significant impact on reducing eco-intensity in the field of electricity consumption and water intake from natural water bodies. The significance of these factors’ influence has been confirmed not only at the macro-level, but also at the micro-level.
Madhyamaka vs. Yogācāra: A Previously Unknown Dispute in Vimalamitra’s Commentary on the Heart Sūtra
Authors: Horiuchi Toshio
Published: March 2023

Vimalamitra’s (ca. the 8th–9th cent.) *Āryaprajñāpāramitāhṛdayaṭīkā (hereafter the PHT) sparks interest not only because of its detailed verbal commentary on the Prajñāpāramitāhṛdaya or the Heart Sūtra but also because it developed various philosophical arguments. However, these arguments have not always been clear due to the difficulty surrounding Tibetan translation and the complexity of the discussion. For instance, in 2021, Mathes, who examined some passages of the PHT, suggested that Vimalamitra endorsed the Yogācāra idea that the perfect nature exists ultimately as the dharmakāya—an idea that can be traced back to 1996, Lopez. However, a close reading of the relevant passages of the PHT through consultation with the commentary on the Saptaśatikā Prajñāpāramitā by Vimalamitra himself, a sub-commentary on the PHT by rNgog blo ldan shes rab (1059–1109), and a reading of the Tibetan translation (the only translation preserved) conjecturing the underlying original Sanskrit reveals that the opposite is true: there is a fierce and complex debate between Madhyamaka and Yogācāra on the passage, with Vimalamitra sharply criticizing the latter’s views as a Mādhyamika. Thus, this paper will reveal for the first time the previously unknown details of the dispute between Yogācāra and Madhyamaka in the PHT. This will offer new evidence for the confrontation between the two around the eighth and ninth centuries.
Grade and Tonnage Comparison of Anthropogenic Raw Materials and Ores for Cu, Zn, and Pb Recovery
Authors: Nedkvitne Eirik Nøst , Eriksen Dag Øistein , Omtvedt Jon Petter
Published: March 2023

Primary metal production operates with large tonnages and takes advantage of economies of scale. Metal recycled from low-value waste streams, competing in the same global metal market as primary production, will be more competitive by also taking advantage of up-scaling. However, an overview of metal tonnages in low-value waste streams to see upscaling potential needs to be provided in the literature. In response, this study provides estimates of copper, zinc, and lead metal tonnages in waste incineration ash—A major waste stream going to landfills. Metal concentrations and tonnages are compared to tonnages and concentration grades found in ores. Copper, zinc, and lead concentration averages are about 3–5 times lower in ash compared to the worldwide average head grade of ores. Tonnages of metal in the ash generated from waste incineration in European countries bordering the Baltic and the North Sea are about 1/3 of mining metal output from Sweden, a leading mining country in the region. Therefore, incineration ash should be considered a significant potential Cu, Zn, and Pb metal source.
Competitiveness of Namibia’s Agri-Food Commodities: Implications for Food Security
Authors: Bahta Yonas T. , Mbai Salomo
Published: March 2023

The global literature widely uses Revealed Comparative Advantage (RCA), Lafay Index (LFI), Export Diversification (EDI), Hirschman (HI), and Major Export Category (MEC) to analyze international trade flows, though agricultural trade, specifically agri-food commodities consisting of food and feed commodities, is neglected in empirical works. Furthermore, the determinants of Revealed Comparative Advantages and the Lafay Index have received little attention, with little focus on the relationships between food insecurity as measured by the Household Food Insecurity Access Scale (HFIAS) and the aforementioned factors, including the RCA and LFI indices as explanatory variables with other macroeconomic variables. The purpose of this study was to ascertain the competitiveness of Namibia’s agri-food products, the factors that influence it, and their implication for food security. This study attempts to answer which factors affect agri-food comparative advantage, which agri-food commodities have a comparative advantage and disadvantage, and what the implications are to food security. The study employed regression analysis, the Household Food Insecurity Access Scale, and various indices. Revealed Comparative Advantage and Lafay Index indicated a mixed result during the study period. Export Diversification and Hirschman indices indicated a less concentrated trade structure throughout the study period. The results of the market structure of the international agri-food market estimated by the Major Export Category revealed that Namibia was unduly dependent on agri-food commodities incorporated in this study. The regression result showed a significant negative influence of labor and land productivity on the aggregated RCA and LFI for agri-food commodities. Land productivity and GDP per capita impact the degree of food insecurity in Namibia. The study concludes that Namibia was not dependent on international trade of agri-food commodities and had little bearing on food security. These analyses enlighten policymakers about the competitiveness of the agri-food business and its implications for food security through evidence-based policy development.
A Simple Controller for Omnidirectional Trotting of Quadrupedal Robots: Command Following and Waypoint Tracking
Authors: Bhounsule Pranav A. , Yang Chun-Ming
Published: March 2023

For autonomous legged robots to be deployed in practical scenarios, they need to perform perception, motion planning, and locomotion control. Since robots have limited computing capabilities, it is important to realize locomotion control with simple controllers that have modest calculations. The goal of this paper is to create computational simple controllers for locomotion control that can free up computational resources for more demanding computational tasks, such as perception and motion planning. The controller consists of a leg scheduler for sequencing a trot gait with a fixed step time; a reference trajectory generator for the feet in the Cartesian space, which is then mapped to the joint space using an analytical inverse; and a joint controller using a combination of feedforward torques based on static equilibrium and feedback torque. The resulting controller enables velocity command following in the forward, sideways, and turning directions. With these three velocity command following-modes, a waypoint tracking controller is developed that can track a curve in global coordinates using feedback linearization. The command following and waypoint tracking controllers are demonstrated in simulation and on hardware.
Rice Yield Prediction in Hubei Province Based on Deep Learning and the Effect of Spatial Heterogeneity
Authors: Zhou Shitong , Xu Lei , Chen Nengcheng
Published: March 2023

Timely and accurate crop yield information can ensure regional food security. In the field of predicting crop yields, deep learning techniques such as long short-term memory (LSTM) and convolutional neural networks (CNN) are frequently employed. Many studies have shown that the predictions of models combining the two are better than those of single models. Crop growth can be reflected by the vegetation index calculated using data from remote sensing. However, the use of pure remote sensing data alone ignores the spatial heterogeneity of different regions. In this paper, we tested a total of three models, CNN-LSTM, CNN and convolutional LSTM (ConvLSTM), for predicting the annual rice yield at the county level in Hubei Province, China. The model was trained by ERA5 temperature (AT) data, MODIS remote sensing data including the Enhanced Vegetation Index (EVI), Gross Primary Productivity (GPP) and Soil-Adapted Vegetation Index (SAVI), and a dummy variable representing spatial heterogeneity; rice yield data from 2000–2019 were employed as labels. Data download and processing were based on Google Earth Engine (GEE). The downloaded remote sensing images were processed into normalized histograms for the training and prediction of deep learning models. According to the experimental findings, the model that included a dummy variable to represent spatial heterogeneity had a stronger predictive ability than the model trained using just remote sensing data. The prediction performance of the CNN-LSTM model outperformed the CNN or ConvLSTM model.
People Flow Trend Estimation Approach and Quantitative Explanation Based on the Scene Level Deep Learning of Street View Images
Authors: Zhao Chenbo , Ogawa Yoshiki , Chen Shenglong , Oki Takuya , Sekimoto Yoshihide
Published: March 2023

People flow trend estimation is crucial to traffic and urban safety planning and management. However, owing to privacy concerns, the collection of individual location data for people flow statistical analysis is difficult; thus, an alternative approach is urgently needed. Furthermore, the trend in people flow is reflected in streetscape factors, yet the relationship between them remains unclear in the existing literature. To address this, we propose an end-to-end deep-learning approach that combines street view images and human subjective score of each street view. For a more detailed people flow study, estimation and analysis were implemented using different time and movement patterns. Consequently, we achieved a 78% accuracy on the test set. We also implemented the gradient-weighted class activation mapping deep learning visualization and L1 based statistical methods and proposed a quantitative analysis approach to understand the land scape elements and subjective feeling of street view and to identify the effective elements for the people flow estimation based on a gradient impact method. In summary, this study provides a novel end-to-end people flow trend estimation approach and sheds light on the relationship between streetscape, human subjective feeling, and people flow trend, thereby making an important contribution to the evaluation of existing urban development.
An Ensemble Approach of Feature Selection and Machine Learning Models for Regional Landslide Susceptibility Mapping in the Arid Mountainous Terrain of Southern Peru
Authors: Kumar Chandan , Walton Gabriel , Santi Paul , Luza Carlos
Published: March 2023

This study evaluates the utility of the ensemble framework of feature selection and machine learning (ML) models for regional landslide susceptibility mapping (LSM) in the arid climatic condition of southern Peru. A historical landslide inventory and 24 different landslide influencing factors (LIFs) were prepared using remotely sensed and auxiliary datasets. The LIFs were evaluated using multi-collinearity statistics and their relative importance was measured to select the most discriminative LIFs using the ensemble feature selection method, which was developed using Chi-square, gain ratio, and relief-F methods. We evaluated the performance of ten different ML algorithms (linear discriminant analysis, mixture discriminant analysis, bagged cart, boosted logistic regression, k-nearest neighbors, artificial neural network, support vector machine, random forest, rotation forest, and C5.0) using different accuracy statistics (sensitivity, specificity, area under curve (AUC), and overall accuracy (OA)). We used suitable combinations of individual ML models to develop different ensemble ML models and evaluated their performance in LSM. We assessed the impact of LIFs on ML performance. Among all individual ML models, the k-nearest neighbors (sensitivity = 0.72, specificity = 0.82, AUC = 0.86, OA = 78%) and artificial neural network (sensitivity = 0.71, specificity = 0.85, AUC = 0.87, OA = 79%) algorithms showed the best performance using the top five LIFs, while random forest, rotation forest, and C5.0 (sensitivity = 0.76–0.81, specificity = 0.87, AUC = 0.90–0.93, OA = 82–84%) outperformed other models when developed using all twenty-four LIFs. Among ensemble models, the ensemble of k-nearest neighbors and rotation forest, k-nearest neighbors and artificial neural network, and artificial neural network and rotation forest outperformed other models (sensitivity = 0.72–0.73, specificity = 0.83–0.84, AUC = 0.86, OA = 79%) using the top five LIFs. The landslide susceptibility maps derived using these models indicate that ~2–3% and ~10–12% of the total study area fall within the “very high” and “high” susceptibility. The obtained susceptibility maps can be efficiently used to prioritize landslide mitigation activities.
Radiometric Re-Compensation of Sentinel-1 SAR Data Products for Artificial Biases due to Antenna Pattern Changes
Authors: Schmidt Kersten , Schwerdt Marco , Hajduch Guillaume , Vincent Pauline , Recchia Andrea , Pinheiro Muriel
Published: March 2023

SAR data products for Sentinel-1 have been freely available and delivered operationally on behalf of the European Space Agency since the routine operation of Sentinel-1A in 2014. These products were delivered using the best knowledge at their processing time, in particular with respect to the radiometric calibration. As reprocessing of SAR data products is not foreseen in the nominal processing chain of Sentinel-1, changes of applied processing parameters impact the SAR data quality and can be a disturbing factor for long-term monitoring of radiometric features. In particular, antenna pattern updates produce artificial radiometric steps which are visible in radar backscatter time series, especially in case of monitoring radiometric stable reference targets. This paper introduces a method for correcting changes due to such updates without the need of reprocessing SAR data products. The method was applied to long-lasting time series of data acquisitions which are used to monitor the radiometric performance with reference targets at the DLR calibration site. It has been shown that artificial steps due to antenna pattern updates disappear in backscatter timelines after correct application. Furthermore, the derived absolute radiometric accuracy was improved for the joint observation period of S1A and S1B for almost five years until December 2021.
Analysis of Geological Hazard Susceptibility of Landslides in Muli County Based on Random Forest Algorithm
Authors: Wu Xiaoyi , Song Yuanbao , Chen Wei , Kang Guichuan , Qu Rui , Wang Zhifei , Wang Jiaxian , Lv Pengyi , Chen Han
Published: March 2023

Landslides seriously threaten human life and property. The rapid and accurate prediction of landslide geological hazard susceptibility is the key to disaster prevention and mitigation. Traditional landslide susceptibility evaluation methods have disadvantages in terms of factor classification and subjective weight determination. Based on this, this paper uses a random forest model built using Python language to predict the landslide susceptibility of Muli County in western Sichuan and outputs the factor weight and model accuracy. The results show that (1) the three most important factors are elevation, distance from the road, and average annual rainfall, and the sum of their weights is 67.54%; (2) the model’s performance is good, with ACC = 99.43%, precision = 99.3%, recall = 99.48%, and F1 = 99.39%; (3) the landslide development and susceptibility zoning factors are basically the same. Therefore, this model can effectively and accurately evaluate regional landslide susceptibility. However, there are some limitations: (1) the landslide information statistical table is incomplete; (2) there are demanding requirements in terms of training concentration relating to the definition of landslide and non-landslide point sets, and the landslide range should be accurately delineated according to field surveys.
Harmonic Loss Analysis of Low-Voltage Distribution Network Integrated with Distributed Photovoltaic
Authors: Yuan Wenqian , Yuan Xiang , Xu Longwei , Zhang Chao , Ma Xinsheng
Published: March 2023

In a power system with highly proportional renewable energy integration, the power generated by photovoltaic (PV) of high permeability and high proportion needs to be connected to the distribution network through the power electronic inverter. The inverters can generate the low-order harmonic and high-order harmonic near the switching frequency. Harmonic power will be generated when the harmonic current flows through the power grid with the harmonic voltage of the same frequency, and the additional harmonic losses caused should not be neglected. To effectively analyze the voltage quality and calculate the harmonic loss of the low-voltage distribution network integrated with distributed PV, based on the harmonic loss factor of resistance proposed, the harmonic impedance modeling and harmonic loss calculation method for the key equipment of the power grid, such as lines and transformers, are introduced in this paper firstly. Next, a decoupling algorithm of harmonic power flow is proposed, and the influence of the access capacity of PV on voltage quality and line loss of the distribution network is analyzed. Finally, a harmonic loss calculation method based on measured harmonic data of the distribution network is proposed. It is found that the harmonic loss of the low-voltage distribution network accounts for about 0.6% of the total network loss. Therefore, voltage quality can be improved and line loss can be reduced effectively by reasonable access to PV and reducing harmonic order and the current harmonic distortion.
Agroecological Approaches in the Context of Innovation Hubs
Authors: Lianu Costin , Simion Violeta-Elena , Urdes Laura , Bucea-Manea-Țoniș Rocsana , Radulescu Irina Gabriela , Lianu Cosmin
Published: March 2023

Agroecology is a sustainable alternative to agricultural science, aiming at balancing the environment-plant-animal-man complex in an equitable way. Different players in the food system across the world are engaging in the practice and promotion of agroecology. Their experience serves as input for agroecology innovation hubs, thus assisting and accelerating the adoption of agroecological practices. Based on existing experience in implementation of innovation ecosystems and living labs in Romania, the study discusses critical factors required for a successful transformation of agriculture, with the aim to fill existing research gaps on agroecological techniques. The authors are also emphasizing the role of new business models in this area. The study used an anonymous survey with Likert scale ratings, and structural equation modeling, PLS. The study results were indicative of a certain degree of enthusiasm for agroecological practice adoption, particularly among organic farmers and business owners. The chances that these practices are adopted by farmers can be enhanced provided there is a systematic exchange of knowledge among the farmers. Clusters of farmers based on community of practice could create innovation ecosystems providing this accelerates its adoption. Correlation with the economic and political processes of the country is necessary, as emphasized by the farmers interviewed during the study. Through innovation hubs, agroecology must move from the currently smaller scale to larger scale practices such as agroecosystems and agri-food systems. These forms of organization should also take due account of relevant socio-economic, cultural, and political factors.
Adjustment of Measurement Error Effects on Dispersion Control Chart with Distribution-Free Quality Variable
Authors: Yang Su-Fen , Chen Li-Pang , Lin Cheng-Kuan
Published: March 2023

In industrial processes, control charts are useful tools to monitor the quality of products and detect possibly out-of-control processes. While many types of control charts have been available for data analysts, they were developed by assuming that the variables are precisely measured. In applications, however, measurement error is ubiquitous when data are falsely recorded by investigators or imprecisely collected by unadjusted machines. Even though the impacts of measurement error for different types of control charts have been explored, error-corrected control charts are still unavailable. In this study, we propose a new dispersion control chart with error correction to fill out this research gap. Our key idea is to convert the observed distribution-free process variables into a flexible sign statistic, and then adopt a function to adjust the measurement error effects on the sign statistic. Finally, we develop an exponentially weight-moving average dispersion control chart with measurement error correction based on the corrected sign statistic. The proposed error-corrected dispersion control chart not only eliminates measurement error effects, but also provides more reliable control limits for monitoring process dispersion. Throughout the numerical examination, we find that the proposed error-corrected dispersion control chart is effective in handling moderate and large levels of measurement error and shows good out-of-control detection performance. Finally, the proposed error-corrected dispersion control chart is implemented in the semiconductor data.
Fully Distributed Water Balance Modelling in Large Agricultural Areas—The Pinios River Basin (Greece) Case Study
Authors: Pisinaras Vassilios , Herrmann Frank , Panagopoulos Andreas , Tziritis Evangelos , McNamara Ian , Wendland Frank
Published: March 2023

Robust assessments of variations in freshwater availability are essential for current and future water resource management in the Pinios River Basin (PRB), which is one of the most productive basins of Greece in terms of agriculture. To support sustainable water resources management in the PRB, we set up and calibrated the mGROWA hydrological model at a high spatial (100 m) and temporal (daily) resolution for the period 1971–2000, with particular attention given to deriving crop-specific irrigation requirements. We developed and implemented a comprehensive methodological framework to overcome data scarcity constraints in the PRB, thus enabling the derivation of high-resolution spatially continuous estimates of many input variables required for the mGROWA model. We generated estimates of spatiotemporal variations in the water balance components actual evapotranspiration, irrigation requirements, total runoff, and groundwater recharge for the PRB. In addition, through the calculation of indices, such as the potential irrigation to groundwater recharge ratio (PIQR), we demonstrate a way to identify potential unsustainable water use in irrigated agriculture. The established mGROWA model can be used both as a hydrological reference model providing continuous decision support for water resources management, focusing on irrigation water use, and a basis for climate impact studies for the PRB.
Investigation of a Compound Parabolic Collector with a Flat Glazing
Authors: Bellos Evangelos , Korres Dimitrios N. , Tzivanidis Christos
Published: March 2023

The compound parabolic concentrator is a promising technology for efficient solar irradiation exploitation at low- and medium-temperature levels. This collector type can be used in a series of applications, such as solar cooling, desalination, and industrial process heat applications. This work presents a novel compound parabolic concentrator that presents satisfying efficiency and low cost due to the use of flat glazing and not an evacuated tube receiver. More specifically, the goal of the present investigation is based on the energy and exergy analysis of a compound parabolic collector with flat glazing, which has a concentration ratio of 2.81. The collector is examined thermally and exegetically, aiming to calculate the efficiency of different operating inlet temperatures. Moreover, the solar unit is studied by a developed computational fluid dynamics model in the SolidWorks Flow Simulation tool. Emphasis is given to the calculation of the convection losses of the receiver tube with the internal air inside the collector. The heat convection coefficient is calculated, and the distribution of the thermal losses, convection, and radiation is presented. Furthermore, the temperature levels of the absorber, the cover glass, and the top thermal loss coefficient are found. The thermal efficiency of the solar unit was 77.4% for inlet temperature at 10 °C and 32.6% for inlet temperature at 110 °C. It was calculated that the maximum exergetic performance of the solar unit is 10.19% for operation at 90 °C, while the thermal efficiency for this case is 41.57%. Additionally, the temperature distributions for different cases are included in the present work.
Creative Economy and Sustainable Development: Shaping Flexible Cultural Governance Model for Creativity
Authors: Yan Wen-Jie , Liu Shu-Tang
Published: March 2023

With the development of cultural democratization, countries have attached increasing importance to the protection of cultural rights and the promotion of sustainable cultural development. The establishment of a flexible cultural governance model may release the transformative force of culture and creativity, gradually spread cultural values and ideas into governance, and shift activities to more sustainable behavior. This research was divided into two stages. In the first stage, CiteSpace was used to conduct a co-citation analysis of documents published between 2013 and 2022 in the Web of Science database. The results were combined with existing cultural development and value indicators from many countries to design cultural impact indicators suitable for evaluating the sustainable development of creative industries. In the second stage, a questionnaire survey was conducted on the cultural industry, the creative economy, and cultural consumption. Through statistical analysis, six dimensions were obtained, and 20 indicators were cultural sustainability, cultural democracy, cultural innovation, cultural industrialization, cultural vitality, and cultural policy systematization. The cultural governance framework of the creative economy and sustainable development was established through AMOS software. This study found that the humanistic rationality of cultural governance has a significant improvement and stable role in promoting the governance of cultural policies. Adjustable cultural impact indicators are effective cultural practices for shaping and framing creative industries, which should be invented, stabilized and improved.
An IVIF-Distance Measure and Relative Closeness Coefficient-Based Model for Assessing the Sustainable Development Barriers to Biofuel Enterprises in India
Authors: Mishra Arunodaya Raj , Rani Pratibha , Cavallaro Fausto , Hezam Ibrahim M.
Published: March 2023

Biofuel can become a favorable sustainable energy resource in India by relieving conventional fossil fuels. However, biofuel enterprises (BEs) are still in the preliminary phase because of sustainable development barriers (SDBs) in environmental, technological, economic, social, and regulatory aspects. In the paper, nineteen SDBs to biofuels are identified by studying the literature and decision experts’ (DEs’) views. Considering the involvement of multiple tangible and non-tangible barriers, the assessment of SDBs to BEs can be taken as a multi-attribute decision-analysis (MADA) problem. Since ambiguity and imprecision generally ensue in the assessment of SDBs to BEs, the doctrine of interval-valued intuitionistic fuzzy sets (IVIFSs) has been recognized as a more sensible and proficient way to tackle uncertain MADA problems. Then, an integrated approach with IVIF-distance measure and IVIF-relative closeness coefficient models is presented to form associations between the SDBs to recognize the most important SDBs. The outcomes of this study show that four SDBs, i.e., “lack of effective storage facilities (EC-2), lack of investors (EC-3), technical issues associated with conversion technologies (T-2), and lack of trust between local societies, agencies, and developers (S-4)” are the leading obstacles. The paper also discusses some policies that can be utilized as a managing stage by the DEs to articulate guidelines for the operational exclusion of SDBs to biofuel enterprises.
Development of a Long-Term Repair Allowance Estimation Model for Apartments Based on Multiple Regression Analysis in Korea
Authors: Kim Jun-Sang , Kim Young Suk
Published: March 2023

Buildings aged 20 years or older account for 63.34% of all edifices in Korea. To ensure sustainable construction, apartment managers must plan and allocate financial resources to maintain communal facilities. However, on the one hand, long-term repair allowances (LTRAs) can be underestimated relative to actual repair costs; consequently, apartments can rapidly deteriorate. On the other hand, the long-term allowance may exceed the actual repair expenditure, thus, wasting resources. Existing estimation methods do not consider the apartment management degree, equipment condition, time value, or the extent of building deterioration. Based on multiple regression, this study developed a repair budget estimation model that considers the influencing factors that include the main characteristics of apartments and the time value, thereby allowing apartment managers to estimate the appropriate long-term repair expenses. In the conducted experiments, the root mean square and mean absolute percentage errors of the estimation model were USD 144,587.38 and 25.6%, respectively. Further, ANOVA results showed a difference between the actual and estimated total long-term repair costs. The resulting model should support apartment managers in establishing reliable maintenance budgets and effectively prevent the functional degradation of buildings.
The Evolving Status of Agricultural Products in the Global Value Chain since China and Kyrgyzstan Established Diplomatic Relations
Authors: Zhang Xuehui , Zhang Wenjing , Ning Zekui
Published: March 2023

Central Asia borders China and was the first stop of China’s opening to the west. Studying the evolving status of agricultural products in the global value chain since China and Kyrgyzstan established diplomatic relations in 1992 can facilitate China’s “Belt and Road” initiative and strengthen agricultural cooperation. Based on FAOSTAT and UN Comtrade data, this paper classifies agricultural products into three categories: primary agricultural products, rough-processed agricultural products, and deep-processed industrial products. An indicator system was constructed for measuring the status of agricultural products in the global value chain. Using the results of the NET trade index, this paper analyzed the evolving status of Chinese and Kyrgyzstani agricultural products in the global value from 1995 to 2020. The results showed that the status of Chinese and Kyrgyzstani primary agricultural products has continued to decline, with Kyrgyzstan slightly better than China. The status of Chinese rough-processed agricultural products was slowly declining, while Kyrgyzstan’s status dropped sharply by 2020. China has a solid foundation in deep-processed agricultural products, while Kyrgyzstan’s status was relatively low. Suggestions for future cooperation between China and Kyrgyzstan are discussed, such as strengthening agricultural technology exchanges and cooperation, expanding trade in high-quality agricultural products, etc.
Estimating Sugarcane Yield in a Subtropical Climate Using Climatic Variables and Soil Water Storage
Authors: Viana Jessica Lima , de Souza Jorge Luiz Moretti , Hoshide Aaron Kinyu , de Oliveira Ricardo Augusto , de Abreu Daniel Carneiro , da Silva Wininton Mendes
Published: March 2023

Brazil is the largest producer of sugarcane (Saccharum spp.) in the world, and this crop’s response to climate and soil water storage is essential for optimal management and genetic/yield improvements. The objective of our study was to build a multivariate model to estimate sugarcane yield in the subtropical conditions of the northwestern Paraná region using climatic and soil water storage variables. Observed yield data was used from experiments conducted at the Experimental Station of the Sugarcane Genetic Improvement Program of the Universidade Federal do Paraná. The sugarcane varieties RB72454, RB867515, RB966928, and RB036066 were analyzed in the 1998–2006, 2008, 2018 and 2019 harvest years. Stepwise multiple linear regression analysis with repeated cross-validation was developed to estimate sugarcane yield given climate and soil water storage variables for crop growth phases. The accumulated degree days in Phases I and II and soil water storage in Phase II of development significantly impacted sugarcane yield. The multiple linear regression model, with accumulated degree days and soil water storage in Phases I and II of development, successfully predicted sugarcane yield for analyzed varieties. Sugarcane production models like the one we developed can improve crop management for greater sustainability and climate change adaption in Brazil and other areas.
Towards a More Inclusive Society: The Social Return on Investment (SROI) of an Innovative Ankle–Foot Orthosis for Hemiplegic Children
Authors: Di Francesco Andrea , Pinelli Maria , Lettieri Emanuele , Toletti Giovanni , Galli Manuela
Published: March 2023

Hemiplegia is a form of disability that affects one side of the body and has a prevalence of 0.5–0.7 per 1000 live births. It has consequences not only at the medical level but also on psychological, cognitive, and social aspects, and it prevents children from social participation, especially in sports settings. The studies demonstrating the social impact of sports on the hemiplegic population and, in particular, children, are limited. In addition, previous evaluations of healthcare sports initiatives in the hemiplegic population are not available, and traditional methods of evaluation, which are mostly focused on economic outcomes, are not applicable. Thus, this article employs the social return on investment (SROI) methodology, which is able to determine the socio-economic impacts of an initiative, to evaluate the impact of an innovative ankle–foot orthosis (AFO) for hemiplegic children that was created to promote the possibility of “sports for all”. The model was designed with the involvement of stakeholders in all the phases and with mixed methods to assess the input, outcomes, and impact indicators. The final SROI, computed for a time horizon of three years and with a focus on the Lombardy Region, was equal to 3.265:1. Based on this result, the initiative turned out to be worthy of investment.
Intelligent Parametric Optimization of Building Atrium Design: A Case Study for a Sustainable and Comfortable Environment
Authors: Ji Yunzhu , Xu Minghao , Zhang Tong , He Yingdong
Published: March 2023

Building atrium design is crucial to maintaining a sustainable built environment and providing thermal comfort to occupants. This study proposes a parametric framework to optimize the atrium’s geometry for environmental performance and thermal comfort improvement. It integrates the parametric design, performance simulation, and multi-objective optimization in the Rhino and Grasshopper platform to realize automatic optimization. The atrium’s well index, shape ratio, volume ratio, position index, and inner interface window-to-wall ratio were set as optimized factors. For the optimization objectives, useful daylight illuminance (UDI), energy use intensity (EUI), and the discomfort time percentage (DTP) were chosen as metrics for the measurement of daylighting, energy use efficiency, and thermal comfort, respectively. Moreover, a geometry mapping method is developed; it can turn atrium shape into rectangular profiles. Thus, the framework can apply to general buildings. To validate the effectiveness of the proposed framework, an atrium optimization case study is conducted for a villa in Poland. According to the optimization results, the performance of the compared three objectives are improved by 43.20%, 15.52%, and 3.89%, respectively. The running time for the optimization is about 36 s per solution, which greatly reduce the human and time cost compared to the traditional working method.
Comparative Study on Socio-Spatial Structures of the Typical Plain Cities of Chengdu and Beijing in Transitional China
Authors: Xu Chan , An Qi , Guo Zichuan , Yu Xuemei , Zhang Jie , Tang Kui
Published: March 2023

China’s socioeconomic transformation and rapid urbanization since the end of the 20th Century have had an important impact on the social spatial structure of large cities. Social differentiation within cities is becoming increasingly prominent. Using detailed data gathered by the Fifth National Population Census of 2000, this study compares the social spatial structure and dynamic mechanisms of the core areas of the cities of Beijing and Chengdu. Factorial ecology analysis is used at the mesoscale to explore the following research questions: ‘How did factors shape the social spaces of two cities with similar topography but at different stages of development during China’s transition from a planned to a market economy?’; and ‘Are the traditional Western theories of socio-spatial interpretation equally applicable to China?’. The results show that Chengdu exhibits a combination of a concentric circle, fan-shaped, and multi-core socio-spatial structure, while Beijing shows a fan-shaped structure. In 2000, influenced by its overall level and stage of socioeconomic development, Beijing was experiencing a faster socio-spatial transformation than Chengdu, and the driving effect of capital on social differentiation and spatial competition was more obvious. The main dynamic mechanisms driving the formation of socio-spatial structures in Beijing and Chengdu include the natural environmental foundation, historical inheritance, urban planning, housing policies, and international influence. The three major variables in the study of traditional Western social spaces, namely economy, family, and ethnic status, were confirmed as applicable to our two case study cities with socioeconomic status as measured by occupation and housing conditions exerting the strongest effect. This perspective of comparing different cities in the same transitional period offers unique insights in identifying the key drivers of socio-spatial differentiation and polarization and their relative magnitude of effect, while enriching the catalog of empirical urban social space research both in China and in the rest of the world.
Spatial Differentiation Characteristics of Rural Areas Based on Machine Learning and GIS Statistical Analysis—A Case Study of Yongtai County, Fuzhou City
Authors: Wang Ziyuan
Published: March 2023

With the development of machine learning and GIS (geographic information systems) technology, it is possible to combine them to mine the knowledge rules behind massive spatial data. GIS, also known as geographic information systems, is a comprehensive discipline, which combines geography and cartography and has been widely used in different fields. It is a computer system for inputting, storing, querying, analyzing, and displaying geographic data. This paper mainly studies the spatial differentiation characteristics of rural areas based on machine learning (ML) and GIS statistical analysis. This paper studies 21 township units in Yongtai County. In this paper, ENVI remote sensing image processing software is used to carry out the geometric correction of Landsat-8 remote sensing data. ML is multidisciplinary and interdisciplinary, involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory, and other disciplines. It is specialized in studying how computers simulate or realize human learning behavior to obtain new knowledge or skills, and reorganize existing knowledge structures to continuously improve its own performance. The purpose of using band fusion is to provide more data information for the study and improve the accuracy of land classification results. Through the extraction of evaluation elements, this paper preliminarily confirms the evaluation index object of a rural human settlement environment evaluation system from the perspective of spatial layout rationality. This paper uses a VMD-GWO-ELM-based three-stage evolutionary extreme learning machine evaluation method to simulate the model. In the same way, when the model is trained again, extra weight is given to extract the feature points to reduce the similarity. Experimental data show that GWO-SVM has good classification performance, with the cross-validation rate reaching 91.66% and the recognition rate of test samples reaching 82.41%. The results show that GIS statistics can provide a reference for environmental protection, which is conducive to land-use planning, implementation of environmental impact assessment of land-use planning, and ultimately achieving sustainable development.
A Luminance-Based Lighting Design Method: A Framework for Lighting Design and Review of Luminance Measures
Authors: Bishop Daniel , Chase J. Geoffrey
Published: March 2023

Imaging photometers and ray-tracing software packages have made it possible to capture and model high-resolution and accurate luminance maps. However, luminance map measurement is rarely seen in professional practice, despite its ability to evaluate visual parameters accurately and directly, such as contrast, visual, size, and target brightness. Two barriers to the uptake of luminance measurement and associated design measures include (1) lack of knowledge of the range of measures available, and (2) difficulty in assessing whether a luminance-based lighting design method is a sufficient and justifiable replacement for the current illuminance-based practice. This paper reviews current practice and presents alternative luminance design measures and human needs for lighting to construct a framework for designing and comparing lighting design methods. It concludes by presenting a new luminance-based lighting method in the context of this framework to show that it is more accurate and comprehensive than current practice and can be enabled by emerging low-cost and increasingly accessible luminance measurement technologies. The overall outcomes provide the metrics and framework to bring more complete and effective luminance-based lighting design into practice.