bluuebunny/crossref_metadata_2025 huggingface dataset:
How Does Multiverse Proposal Affect the Design Argument?
Authors: Chan Man Ho
Published: October 2022

Recent observations suggest that many fundamental physical constants and conditions in our universe are fine-tuned for life to exist. This provides an important piece of evidence to support the Design Argument and the existence of God in the philosophy of religion. However, the proposal of multiverse provides a naturalistic account of the fine-tuning phenomena which apparently challenges the Design Argument. In general, most of the multiverse models have specific features and they have to satisfy empirical and logical constraints. Therefore, they may be intrinsically dependent on theistic proposal under the probabilistic Bayesian framework. In this article, I present a Bayesian framework to show how multiverse proposal affects the Design Argument. I show that there exist two specific scenarios in which the inclusion of multiverse proposal can indirectly increase the credence of the Design Argument.
Big Geospatial Data and Data-Driven Methods for Urban Dengue Risk Forecasting: A Review
Authors: Li Zhichao , Dong Jinwei
Published: October 2022

With advancements in big geospatial data and artificial intelligence, multi-source data and diverse data-driven methods have become common in dengue risk prediction. Understanding the current state of data and models in dengue risk prediction enables the implementation of efficient and accurate prediction in the future. Focusing on predictors, data sources, spatial and temporal scales, data-driven methods, and model evaluation, we performed a literature review based on 53 journal and conference papers published from 2018 to the present and concluded the following. (1) The predominant predictors include local climate conditions, historical dengue cases, vegetation indices, human mobility, population, internet search indices, social media indices, landscape, time index, and extreme weather events. (2) They are mainly derived from the official meteorological agency satellite-based datasets, public websites, department of health services and national electronic diseases surveillance systems, official statistics, and public transport datasets. (3) Country-level, province/state-level, city-level, district-level, and neighborhood-level are used as spatial scales, and the city-level scale received the most attention. The temporal scales include yearly, monthly, weekly, and daily, and both monthly and weekly are the most popular options. (4) Most studies define dengue risk forecasting as a regression task, and a few studies define it as a classification task. Data-driven methods can be categorized into single models, ensemble learning, and hybrid learning, with single models being further subdivided into time series, machine learning, and deep learning models. (5) Model evaluation concentrates primarily on the quantification of the difference/correlation between time-series observations and predicted values, the ability of models to determine whether a dengue outbreak occurs or not, and model uncertainty. Finally, we highlighted the importance of big geospatial data, data cloud computing, and other deep learning models in future dengue risk forecasting.
Characteristics of Snow Depth and Snow Phenology in the High Latitudes and High Altitudes of the Northern Hemisphere from 1988 to 2018
Authors: Yue Shanna , Che Tao , Dai Liyun , Xiao Lin , Deng Jie
Published: October 2022

Snow cover is an important part of the Earth’s surface and its changes affect local and even global climates due to the high albedo and heat insulation. However, it is difficult to directly compare the results of previous studies on changes in snow cover in the Northern Hemisphere mainland (NH) due to the use of different datasets, research methods, or study periods, and a lack comparison in terms of the differences and similarities at high latitudes and high altitudes. By using snow depth datasets, we analyzed the spatio-temporal distributions and variations in snow depth (SD) and snow phenology (SP) in the NH and nine typical areas. This study revealed that SD in the NH generally decreased significantly (p < 0.01) from 1988 to 2018, with a rate of −0.55 cm/decade. Changes in SD were insignificant at high altitudes, but significant decreases were found at high latitudes. With regard to SP, the snow cover onset day (SCOD) advanced in 31.57% of the NH and was delayed in 21.10% of the NH. In typical areas such as the Rocky Mountains, the West Siberian Plain, and the Central Siberian Plateau, the SCOD presented significant advancing trends, while a significant delay was the trend observed in the Eastern European Plain. The snow cover end day (SCED) advanced in 37.29% of the NH and was delayed in 14.77% of the NH. Negative SCED trends were found in most typical areas. The snow cover duration (SCD) and snow season length (SSL) showed significant positive trends in the Rocky Mountains, while significant negative trends were found in the Qinghai–Tibet Plateau. The results of this comprehensive comparison showed that most typical areas were characterized by decreased SD, advanced SCOD and SCED, and insignificantly increasing SCD and SSL trends. The SCD and SSL values were similar at high latitudes, while the SSL value was larger than the SCD value at high altitudes. The SD exhibited similar interannual fluctuation characteristics as the SCD and SSL in each typical area. The SCD and SSL increased (decreased) with advanced (delayed) SCODs.
Spatial Sampling and Grouping Information Entropy Strategy Based on Kernel Fuzzy C-Means Clustering Method for Hyperspectral Band Selection
Authors: Zhang Zhou , Wang Degang , Sun Xu , Zhuang Lina , Liu Rong , Ni Li
Published: October 2022

The high spectral resolution of hyperspectral images (HSIs) provides rich information but causes data redundancy, which imposes a computational burden on practical applications. Band selection methods can select a subset of HSI without changing the main information to reduce the spectral dimension. Clustering-based methods can reduce band correlation significantly, but traditional clustering methods are mostly hard clustering and are not accurate enough to partition the bands. An unsupervised band selection method based on fuzzy c-means clustering (FCM) was introduced to tackle this problem. However, FCM can easily obtain the local optimal solution and take a long time to process high-dimensional data. Hence, this work applies kernel function and a sampling strategy to reduce calculation time, and information entropy is used to initialize the cluster center. A kernel FCM algorithm based on spatial sampling and a grouping information entropy strategy is proposed and called SSGIE-KFCM. This method not only optimizes the calculation process and reduces the amount of computation data, accelerating the calculation efficiency, but also adopts grouping information entropy to improve the probability of obtaining a global optimal solution. Classification experiments on two public HSI datasets show that: (1) The classification performance of the whole band can be achieved or even exceeded by using only a small number of bands to achieve the purpose of dimensionality reduction. (2) The classification accuracy can be improved compared with the FCM method. (3) With the introduction of sampling strategy and kernel function, the computational speed is at least 24 times faster than that of FCM. It has been proven that the SSGIE-KFCM method can significantly reduce the amount of HSI while retaining the primary information of the original data, which further promotes the research and application of HSI in the remote sensing area.
A Fast Registration Method for Optical and SAR Images Based on SRAWG Feature Description
Authors: Wang Zhengbin , Yu Anxi , Zhang Ben , Dong Zhen , Chen Xing
Published: October 2022

Due to differences in synthetic aperture radar (SAR) and optical imaging modes, there is a considerable degree of nonlinear intensity difference (NID) and geometric difference between the two images. The SAR image is also accompanied by strong multiplicative speckle noise. These phenomena lead to what is known as a challenging task to register optical and SAR images. With the development of remote sensing technology, both optical and SAR images equipped with sensor positioning parameters can be roughly registered according to geographic coordinates in advance. However, due to the inaccuracy of sensor parameters, the relative positioning accuracy is still as high as tens or even hundreds of pixels. This paper proposes a fast co-registration method including 3D dense feature description based on a single-scale Sobel and the ratio of exponentially weighted averages (ROEWA) combined with the angle-weighted gradient (SRAWG), overlapping template merging, and non-maxima suppressed template search. In order to more accurately describe the structural features of the image, the single-scale Sobel and ROEWA operators are used to calculate the gradients of optical and SAR images, respectively. On this basis, the 3 × 3 neighborhood angle-weighted gradients of each pixel are fused to form a pixel-wise 3D dense feature description. Aiming at the repeated feature description in the overlapping template and the multi-peak problem on the search surface, this paper adopts the template search strategy of overlapping template merging and non-maximum suppression. The registration results obtained on seven pairs of test images show that the proposed method has significant advantages over state-of-the-art methods in terms of comprehensive registration accuracy and efficiency.
Habitat Prediction of Northwest Pacific Saury Based on Multi-Source Heterogeneous Remote Sensing Data Fusion
Authors: Han Yanling , Guo Junyan , Ma Zhenling , Wang Jing , Zhou Ruyan , Zhang Yun , Hong Zhonghua , Pan Haiyan
Published: October 2022

Accurate habitat prediction is important to improve fishing efficiency. Most of the current habitat-prediction studies use the single-source datasets and the sequence model based on single-source datasets, which, to a certain extent, limits the further improvement of prediction accuracy. In this paper, we propose a habitat-prediction method based on the multi-source heterogeneous remote-sensing data fusion, using product-level remote-sensing data and L1B-level original remote-sensing data. We designed a heterogeneous data feature extraction model based on a Convolution Neural Network (CNN) and Long and Short-Term Memory network (LSTM), and we designed a decision-fusion model based on multi-source heterogeneous data feature extraction. In the habitat prediction for the Northwest Pacific Saury, the mean R2 of the model reaches 0.9901 and the RMSE decreases to 0.01588 in the model validation experiment. It is significantly better than the results of other models, with the single datasets as input. Moreover, the model performs well in the generalization experiment because we limited the prediction error to less than 8%. Compared with the single-source sequence network model in the existing literature, the proposed method in this paper solves the problem of ineffective fusion caused by the differences in the structure and size of heterogeneous data through multilevel feature fusion and decision fusion, and it deeply explores the features of remote-sensing fishery data with different data structures and sizes. It can effectively improve the accuracy of fishery prediction, proving the feasibility and advancement of using multi-source remote-sensing data for habitat prediction. It also provides new methods and ideas for future research in the field of habitat prediction.
A Narrow Optical Pulse Emitter Based on LED: NOPELED
Authors: Real Diego , Calvo David , Díaz Antonio , Salesa Greus Francisco , Sánchez Losa Agustín
Published: October 2022

Light sources emitting short pulses are needed in many particle physics experiments using optical sensors as they can replicate the light produced by the particles being detected and are also an important calibration and test element. This work presents NOPELED, a light source based on LEDs emitting short optical pulses with typical rise times of less than 3 ns and Full Width at Half Maximum lower than 7 ns. The emission wavelength depends on the model of LED used. Several LED models have been characterized in the range from 405 to 532 nm, although NOPELED can work with LED emitting wavelengths outside of that region. While the wavelength is fixed for a given LED model, the intensity and the frequency of the optical pulse can be controlled. NOPELED, which also has low cost and simple operation, can be operated remotely, making it appropriate for either different physics experiments needing in-place light sources such as astrophysical neutrino detectors using photo-multipliers or positron emission tomography devices using scintillation counters, or, beyond physics, applications needing short pulses of light such as protein fluorescence or chemodetection of heavy metals.
Multi-Path Routing Algorithm for Wireless Sensor Network Based on Semi-Supervised Learning
Authors: Guo Yiping , Hu Guyu , Shao Dongsheng
Published: October 2022

Multi-path transmission can well solve the data transmission reliability problems and life cycle problems caused by single-path transmission. However, the accuracy of the routing scheme generated by the existing multi-path routing algorithms is difficult to guarantee. In order to improve the accuracy of the multi-path routing scheme, this paper innovatively proposes a multi-path routing algorithm for a wireless sensor network (WSN) based on the evaluation. First, we design and implement the real-time evaluation algorithm based on semi-supervised learning (RESL). We prove that RESL is better in evaluation time and evaluation accuracy through comparative experiments. Then, we combine RESL to design and implement the multi-path routing algorithm for wireless sensor networks based on semi-supervised learning (MRSSL). Then, we prove that MRSSL has advantages in improving the accuracy of the multi-path routing scheme through comparative experiments.
Information Security and Privacy in Railway Transportation: A Systematic Review
Authors: López-Aguilar Pablo , Batista Edgar , Martínez-Ballesté Antoni , Solanas Agusti
Published: October 2022

Intelligent transportation systems will play a key role in the smart cities of the future. In particular, railway transportation is gaining attention as a promising solution to cope with the mobility challenges in large urban areas. Thanks to the miniaturisation of sensors and the deployment of fast data networks, the railway industry is being augmented with contextual, real-time information that opens the door to novel and personalised services. Despite the benefits of this digitalisation, the high complexity of railway transportation entails a number of challenges, particularly from security and privacy perspectives. Since railway assets are attractive targets for terrorism, coping with strong security and privacy requirements such as cryptography and privacy-preserving methods is of utmost importance. This article provides a thorough systematic literature review on information security and privacy within railway transportation systems, following the well-known methodology proposed by vom Brocke et al. We sketch out the most relevant studies and outline the main focuses, challenges and solutions described in the literature, considering technical, societal, regulatory and ethical approaches. Additionally, we discuss the remaining open issues and suggest several research lines that will gain relevance in the years to come.
Virtual Traffic Light Implementation on a Roadside Unit over 802.11p Wireless Access in Vehicular Environments
Authors: Wong Robert , White Jack , Gill Sumanjit , Tayeb Shahab
Published: October 2022

Blind intersections have high accident rates due to the poor visibility of oncoming traffic, high traffic speeds, and lack of infrastructure (e.g., stoplights). These intersections are more commonplace in rural areas, where traffic infrastructure is less developed. The Internet of Vehicles (IoV) aims to address such safety concerns through a network of connected and autonomous vehicles (CAVs) that intercommunicate. This paper proposes a Road-Side Unit-based Virtual Intersection Management (RSU-VIM) over 802.11p system consisting of a Field-Programmable Gate Array (FPGA) lightweight RSU that is solar power-based and tailored to rural areas. The RSU utilizes the proposed RSU-VIM algorithm adapted from existing virtual traffic light methodologies to communicate with vehicles over IEEE 802.11p and facilitate intersection traffic, minimizing visibility issues. The implementation of the proposed system has a simulated cloud delay of 0.0841 s and an overall system delay of 0.4067 s with 98.611% reliability.
Production of Bovine Collagen Hydrolysate with Antioxidant Activity; Optimized by Response Surface Methodology
Authors: Pakbin Babak , Allahyari Samaneh , Dibazar Shaghayegh Pishkhan , Brück Wolfram Manuel , Vahidi Roghayeh , Mahmoudi Razzagh , Khanjari Ali
Published: October 2022

Antioxidants are widely used in pharmaceutical industries. Gelatin is a byproduct of the meat industry and its hydrolysates showed several functionalities, such as antioxidant activity. The purpose of this study was to describe and optimize the enzymatic hydrolysis conditions including time, temperature, pH, and enzyme/substrate ratio (E/S) to produce protein hydrolysate with antioxidant functionality from bovine gelatin by RSM; the scavenging activity was evaluated using the DPPH method. The model observed was fitted with desirable adequacy and sufficiency. We found that the antioxidant activity increased significantly (p < 0.05) with the increase in pH value, E/S ratio, and time of enzymatic process; however, the temperature had no significant (p < 0.05) effect on the antioxidant activity of the hydrolysate. The optimum hydrolysis conditions were observed at a temperature of 35.3 °C, pH of 8.0, and E/S ratio at 2.5 after 2 h hydrolysis by trypsin enzyme. The results showed that the hydrolysate under these conditions, optimized by RSM, could be more effective on antioxidant activity. Regarding the antioxidant potential, gelatin hydrolysate can be used as an antioxidant supplement in pharmaceutical industries.
Evaluation of Pulsed Electric Field-Assisted Extraction on the Microstructure and Recovery of Nutrients and Bioactive Compounds from Mushroom (Agaricus bisporus)
Authors: Calleja-Gómez Mara , Castagnini Juan Manuel , Carbó Ester , Ferrer Emilia , Berrada Houda , Barba Francisco J.
Published: October 2022

Pulsed electric field (PEF) is a sustainable innovative technology that allows for the recovery of nutrients and bioactive compounds from vegetable matrices. A. bisporus was chosen for its nutritional value and the effect of PEF pretreatment was evaluated using different conditions of electric field (2–3 kV/cm), specific energy (50–200 kJ/kg) and extraction time (0–6 h) to obtain the best conditions for nutrient and bioactive compound extraction. Spectrophotometric methods were used to evaluate the different compounds, along with an analysis of mineral content by inductively coupled plasma mass spectrometry (ICP-MS) and the surface was evaluated using scanning electron microscopy (SEM). In addition, the results were compared with those obtained by conventional extraction (under constant shaking without PEF pretreatment). After evaluating the extractions, the best extraction conditions were 2.5 kV/cm, 50 kJ/kg and 6 h which showed that PEF extraction increased the recovery of total phenolic compounds in 96.86%, carbohydrates in 105.28%, proteins in 11.29%, and minerals such as P, Mg, Fe and Se. These results indicate that PEF pretreatment is a promising sustainable technology to improve the extraction of compounds and minerals from mushrooms showing microporation on the surface, positioning them as a source of compounds of great nutritional interest.
Analysis on the Effect of the Targeted Poverty Alleviation Policy on Narrowing the Urban-Rural Income Gap: An Empirical Test Based on 124 Counties in Yunnan Province
Authors: Yang Renyi , Zhong Changbiao , Yang Zisheng , Wu Qiuju
Published: October 2022

China’s targeted poverty-alleviation policy has eliminated absolute poverty and become the focus of world attention. However, a relative-poverty problem still exists in China, and the large urban–rural income gap is an important issue. Whether the implementation of the targeted poverty-alleviation policy has narrowed the urban–rural income gap, along with its specific effects, requires an accurate analysis, which is particularly critical in order for China to implement a rural-revitalization strategy and further eliminate relative poverty in the future. Given the problems and shortcomings of the existing studies, such as not passing the parallel trend test to overestimate the policy effect, in this study we refer to the previous results, and our analyses divide the 124 counties in Yunnan province into four categories: non-poverty counties and counties with grade-I, grade-II, and grade-III poverty. We selected the panel data of the urban–rural income ratio of each county along with eight influencing factors from 2011 to 2020 for difference-in-difference model (DID) analysis. In this study, we compare the four types of counties level-by-level, and we construct a full-sample spatial DID model. The estimated results, after excluding the impact of COVID-2019, are significant. In addition, we perform robustness and placebo tests and other work on the DID model. All of the results show that the implementation of the targeted poverty-alleviation policy has effectively reduced the urban–rural income ratio in areas experiencing poverty. Finally, we use the intermediary effect analysis method to explore the reasons for the findings: driven by the targeted poverty-alleviation policy, the financial investment in poor areas has substantially increased, further increasing the income level of rural residents in poor areas and thus promoting a notable reduction in the income gap between urban and rural residents in poor areas. We suggest that, although China has achieved comprehensive success in targeted poverty-alleviation, assistance investment still needs to be increased, policies must be adjusted, and income growth must be accelerated to achieve industrial prosperity.
Evolutionary Game Analysis on Innovation Behavior of Digital Financial Enterprises under the Dynamic Reward and Punishment Mechanism of Government
Authors: Fu Hao , Liu Yue , Cheng Pengfei , Cheng Sijie
Published: October 2022

Digital financial innovation is a new impetus for economic and social development. However, lack of regulation will also have a huge impact on economic and social development. In this paper, an evolutionary game model of digital finance innovation is constructed, the evolutionary strategies of both sides of the game are discussed, and a simulation analysis is carried out, based on the dynamic reward and punishment mechanism of the government. The results show that the system can achieve evolutionary stability under the dynamic reward and punishment mechanism, and that the evolutionarily stable strategy is unique. We also find that when the punishment of regulators increases, the probability of compliance innovation of digital financial enterprises will increase, and the probability of active supervision of regulatory agencies will decrease. When regulators increase incentives, the probability of the compliance innovation of digital financial enterprises will decrease. Similarly, the probability of active supervision by regulators will also decrease and the decrease will be more obvious. To achieve the win-win development of digital financial innovation and regulation, it is necessary to continuously improve the regulatory capacity and level, reduce regulatory costs, and build a dynamic reward and punishment mechanism. Our research contributes to enhancing compliance innovation in digital financial enterprises.
Assessment of Drinking Water Quality and Associated Socio-Economic Impacts in Arid Mountainous Regions
Authors: Saeed Muhammad Asif , Murtaza Ghulam , Ali Shafaqat , Aziz Humera , Albeshr Mohammed F. , Mahboob Shahid , Manzoor Irfan , Farooqi Zia Ur Rahman , Sabir Muhammad , Ahmad Hamaad Raza , Abdul Qadir Ayesha , Sajjad ur Rehman Muhammad
Published: October 2022

We investigated the quality of drinking water and its possible effects on human health in the Dera Ghazi Khan (D. G. Khan) district of Pakistan. Samples were collected from three tehsils of the D. G. Khan district, namely D. G. Khan, Kot Chutta, and Taunsa. A total of 50 samples (n = 50) were collected from the study area using standard procedures. The pH of the water samples ranged from 6.52–8.75, EC 0.31–9.78 dS m−1, and TDS 105–985 mg L−1. The bacterial analysis showed that 9 out of 50 samples (18%) contained pathogenic E. coli bacterial. The results showed that the pH and EC values of some sampling sites exceeded the WHO guidelines for drinking water. It was observed that the pH of only 1 sample, and the EC of 18 samples in D. G. Khan—5 in Kot Chutta and 16 in Tehsil Taunsa—exceeded the WHO guidelines. In terms of E. coli presence and related diseases (hepatitis A, B, and C), we collected data, which were screened and belonged to the sampling sites, from 1378 patients receiving treatment related to hepatitis A, B, and C. It was revealed that 530 patients belonged to the D. G. Khan site, followed by Taunsa (460), and Kot Chutta (388). Based on the results, it was concluded that the quality of drinking water samples generally was good, except for 6% of the samples, assessed using (SAR) and Kelly’s ratio (KR), and 9 sites were positive for E. coli.
What Are Foresters Taught? An Analysis of Undergraduate Level Forestry Curricula in Türkiye
Authors: Durusoy İdris , Bahçeci Öztürk Yıldız
Published: October 2022

As the forestry profession evolved from extractive management to sustainable forest management, forestry education and curricula had to reflect these changes. While forestry education and curriculum have been extensively analyzed for different countries, no such analysis exists for Turkish forestry. This study analyzes the curriculum and course contents of all undergraduate-level forest engineering programs across Türkiye. The study employed content analysis to explore disparities among the schools. The courses are classified into disciplinary fields depending on their contents. Verbs used in learning outcomes were analyzed using Bloom’s taxonomy. Mandatory and elective requirements of forestry programs are quite similar, indicating little disparity among schools in different regions. Course categorization reveals that forestry education emphasizes biophysical and technical sciences. Learning outcomes focused heavily on the low-level thinking dimensions of Bloom. We conclude that the Turkish forestry curriculum needs a reformative change to equip students with skill sets to practice sustainable forest management.
Scale-Location Dependence Relationship between Soil Organic Matter and Environmental Factors by Anisotropy Analysis and Multiple Wavelet Coherence
Authors: Gou Yuxuan , Liu Dong , Liu Xiangjun , Zhuo Zhiqing , Shen Chongyang , Liu Yunjia , Cao Meng , Huang Yuangfang
Published: October 2022

Soil organic matter (SOM) and environmental factors have been shown to have a scale-location dependence relationship. However, few studies have considered the anisotropy, and the scale-location dependence relationship may not be fully characterized. In this study, transects with dominant directions of SOM variability in the dryland farming regions of Songliao Plain, China were extracted by anisotropy analysis. The scale-location specific multivariate relationships between SOM and environmental factors along the two transects were examined using multiple wavelet coherence. Results indicated that the scale and location-specific variations in SOM and environmental factors were direction-specific. The major direction with the most significant SOM variations was 56° east by north, while the minor direction was perpendicular to the major direction. The strongest single factor for explaining SOM variations differed between two dominant directions, sand along the major direction (average wavelet coherence (AWC) = 0.57, percentage area of significant coherence (PASC) = 40.32% at all scales) and bulk density (BD) along the minor direction (AWC = 0.66, PASC = 50.16% at all scales). The combination of mean annual temperature (MAT) and BD was the best to explain SOM variations along the major direction (AWC = 0.78, PASC = 46.23% at all scales). A two-factor combination is adequate to explain SOM variability along the major direction, whereas a single factor is sufficient for the explanation along the minor direction. More factors did not evidently increase or even decrease the percentage of scale-location domains where SOM variations were significantly explained. This work has important implications for developing future sampling strategies and preparing detailed digital soil maps.
A Review of Supply Chain Uncertainty Management in the End-of-Life Vehicle Industry
Authors: A. Rashid Fatin Amrina , Hishamuddin Hawa , Saibani Nizaroyani , Abu Mansor Mohd Radzi , Harun Zambri
Published: October 2022

Various uncertainties exist in the End-of-Life Vehicle (ELV) industry, which further complicates the ELV business’s growth. In order to pursue greater progress in the ELV business establishment, a comprehensive analysis of previous ELV studies with regard to the supply chain uncertainty perspective is essential. The objective of this study is aimed at categorising the existing supply chain uncertainty sources according to their end-of-life (EoL) strategies, identify the management approaches adopted to analyse the prominent research trends, and conduct a regional analysis of ELV supply chain studies for the past years, from 2016 until 2022. The content analysis method was used to extract all the essential information from previous research, and an analysis was performed to obtain the latest research trends and identify the relationship between the gathered data. The findings show that the past research focuses on three main supply chain uncertainties, namely, uncertainty in logistics and network facilities (31.8%), production and operations (30.7%), and environmental (25.0%). Furthermore, the regional analysis shows that 83% of the studies were conducted in developing countries over the past years. Lastly, several research gaps were presented to provide researchers with potential directions and the way forward to explore ELV supply chain research from the uncertainty management context.
Empirical Study on Design Trend of Taiwan (1960s–2020): The Evolution of Theme, Diversity and Sustainability
Authors: Huang Jianping , Tao Yuheng , Shi Minghong , Wu Jun
Published: October 2022

With significance in improving and developing local design culture as well as in supplementing global design history, this essay describes a study on the past and a clear prediction of the future by exploring Taiwan’s design history from approximately the 1960s to 2020 based on the evolution of theme, diversity, and sustainability. In this research, the Python programming language is used to apply three algorithms of term frequency–inverse document frequency (TF-IDF), Simpson’s diversity index (SDI), and latent Dirichlet allocation (LDA) to conduct a text exploration of design journals. The results show the following: in the 1960s–1980s, the evolution of theme focused on evaluation strategies, technical practices, and foreign cultures, on digital design, multiculturalism, and design aesthetics in the 1990s, and on emotional human factors, intelligent technology, and local culture since the beginning of the 21st century. Local culture and intelligent technology are the main driving forces of the current design industry. Regarding diversity, after a period of rapid change and stable rising, it has shown a downward trend in recent years. This indicates that current design needs to be stimulated by external environmental variations. Sustainability was focused on technology, the market, and education during the 1960s–1980s; on consumers, design education, and eco-design during the 1990s; and on integration across fields during the 2000s–2020. In order to gain a wider perspective of the complete design context of Chinese culture, the results show the current and future trends of the academic community, in addition to a reference for the study of the design histories of other areas in the world.
Investigating Adsorption-Based Atmospheric Water Harvesting Potential for Pakistan
Authors: Bilal Muhammad , Sultan Muhammad , Majeed Faizan , Farooq Muhammad , Sajjad Uzair , Ibrahim Sobhy M. , Khan Muhammad Usman , Azizi Shohreh , Javaid Muhammad Yasar , Ahmad Riaz
Published: October 2022

Atmospheric water harvesting (AWH) can provide clean and safe drinking water in remote areas. The present study provides a comprehensive review of adsorption-based AWH by using the scientometric approach. The publication types are mainly composed of articles and reviews, accounting for 75.37% and 11.19% of the total, respectively. Among these publications, ~95.1% were published in English and came from 154 different journals which demonstrates that researchers have shown a great interest in this field. However, much less contribution has been received thus far on this topic from Pakistan. Therefore, this study aims to explore a solar-driven adsorption-based AWH system in terms of varying relative humidity (RH), solar irradiance, and various types of adsorbent materials. Geospatial mapping and Monte Carlo simulations are carried out to integrate the operational parameters of the system and materials with Pakistan’s climatic conditions to forecast the AWH potential (L/m2/d). Probability distribution of 100,000 trials is performed by providing lower, mode, and upper values of the independent parameters. The possible outcomes of the adsorbed volume of water are determined by generating random values for the independent parameters within their specified distribution. It was found that MIL-101 (Cr) achieved the highest water-harvesting rate (WHR) of 0.64 to 3.14 (L/m2/d) across Pakistan, whereas the WHR was lowered to 0.58 to 1.59, 0.83 to 0.94, and 0.45 to 1.26 (L/m2/d) for COF-432, zeolite, and silica gel, respectively. Furthermore, parameter optimization and sensitivity analysis are performed to finalize the boundary conditions of the adsorption-based AWH system by ensuring the maximum volume values within the desired specification limits (1–4 L/m2/d).
The Impact of Structural Reforms on Sustainable Development Performance: Evidence from European Union Countries
Authors: Rapsikevičius Jonas , Bruneckienė Jurgita , Krušinskas Rytis , Lukauskas Mantas
Published: October 2022

The European Union (EU) is a unique economic integration organization with standard policies that seek common goals among members, such as convergence and sustainable development. It aims to become a climate neutral economy by 2050. With structural reform implementation, each EU member country can work towards these set goals in accordance with their own welfare. However, a trade-off between the individual welfare goals of a country and the common goals of the EU should be reached. This article analyzes the impact of structural reforms on sustainable development performance in European countries. The article contributes to a gap in the literature because, to date, previous research has examined the effects of structural reforms on economic or environmental measures in groups of nations but has often lacked an adequate sustainable development context. In addition, the clustering of European Union countries according to different social policy regimes requires clarification of the perceptions and knowledge about the influence and usefulness of structural reforms for sustainable development performance. The research uses the panel data of the Heritage Index of Economic Freedom and Sustainable Development Goals agenda from the Eurostat database. The data cover 27 countries of the European Union for a period of 11 years (2010–2020). The research panel includes 297 observations. We found different results regarding the influence of structural reforms on sustainable development performance under different social policy regimes and the regulatory trap for homogeneous sustainable development in the European Union. The paper provides original empirical evidence and specifies the targets of structural reforms in relation to sustainable development. The results provide guidance for policymakers to develop more appropriate and efficient sustainable development policies.
The Impact of House Price on Urban Household Consumption: Micro Evidence from China
Authors: Sun Xiaoqin , Su Yuhai , Liu Honglei , Li Chengyou
Published: October 2022

The impact of house prices on consumption is an important concern for academics and policy makers. Several studies have documented that house price changes have an impact on consumption; however, there is far less consensus on how house price changes affect consumption in China. The purpose of this paper is to examine the impact of house prices on household consumption in urban China and to identify the mechanisms behind the impact. This study measures the impact of housing price changes on consumption at the household level, using research data from 71,548 home-owning households in the 2011–2019 China Household Finance Survey database. Our analysis shows that housing prices have a significant negative effect on consumption, with a 1% increase in the value of a household’s property causing a 0.0034% decrease in household consumption, an effect that is significant for households that own a home and for those in the eastern and central regions. We find that rising house prices cause an increase in households’ precautionary savings, which is the main mechanism through which house prices affect consumption in China. Furthermore, the impact of house prices on consumption is asymmetric, with consumption moving in the opposite direction when house prices rise but not when house prices fall. This study provides meaningful insights for policy makers on the usefulness of building a healthy and stable housing market to expand consumption and revitalize the economy.
Effect of Thermophilic Microbial Agents on Antibiotic Resistance Genes and Microbial Communities during Co-Composting of Pig Manure and Tea Stalks
Authors: Chen Xiaojia , Wu Chengjian , Li Qinyu , Zhou Peng , Chen Zheng , Han Yang , Shi Jiping , Zhao Zhijun
Published: October 2022

Antibiotic resistance caused by antibiotic resistance genes (ARGs) threatens human health. ARGs in animal manure can be degraded by composting. This study explored the changes in ARGs and microbial communities during co-composting of pig manure and tea stalks with (T) thermophilic microbial agents, including Geobacillus toebii ZF1 and Geobacillus sp. ZF2 for 15 days in a 4 L vacuum flask. Composting without thermophilic microbial agents served as control (CK). The results showed that the compost temperature of group T peaked at 72.1 °C and maintained above 70 °C for 4 days. The maximum temperature of group CK was 64.0 °C. The seed germination index showed that group T had reached maturity on day 9, while group CK reached maturity on day 15. The dominant bacteria in group CK were Bacillus. In group T, the dominant bacteria changed from Bacillus and Corynebacterium to Geobacillus. Compared with that of group CK, group T increased the removal of cmx, baeS and TaeA by 24.6%, 18.6% and 12.1%, respectively. Group T promoted and inhibited the removal of arlR and novA, respectively (p < 0.05), while group CK showed the opposite effect. Network analysis suggested that group T effectively inactivated Dietzia, Clostridium and Corynebacterium (p < 0.05) and promoted the removal of cmx and baeS. These results showed that thermophilic microbial agents could accelerate the maturation of pig manure and tea stalks, change microbial communities and promote the removal of ARGs. It is of great significance to reduce the spread of ARGs and, in turn, human health risks.
Status and Prospects of Green Building in the Middle East and North Africa (MENA) Region with a Focus on the Moroccan Context
Authors: Assadiki Redouan , Merlin Gérard , Boileau Hervé , Buhé Catherine , Belmir Fouzi
Published: October 2022

To promote the development of the Green Building (GB) concept in developing countries, this paper treated the combination of the scientometric analysis of green building research in the Middle East and North Africa (MENA) region, with investigation into the current state of deployment of GB and barriers to sustainable construction practices in the Moroccan construction industry. A scientometric method was used to analyze 159 articles published from 2000 to 2021, and a survey of 167 Moroccan professionals with green building experience was conducted to understand the stakeholders’ position. The examination of the dataset reveals the significant contribution in GB research from Gulf countries (Saudi Arabia with 27 articles). The adoption of GB in the Moroccan construction industry is not apparent. Four clusters for the twelve barriers have been identified by the clustering analysis. They were attributed to government, social and awareness barriers, design phase barriers, high initial costs, and technology barriers. This paper provides stakeholders with the necessary knowledge and understanding of the current research, its gaps, inter-regional and international cooperation, and future direction in the MENA region. This could aid practitioners and policymakers in taking the proper actions to mitigate obstacles for GB adoption.
Combining Multiple Biomarkers to Evaluate the Environmental Stress in Cyprinid Populations
Authors: Santos Regina Maria Bessa , Cortes Rui Manuel Vitor , Fernandes Luís Filipe Sanches , Pacheco Fernando António Leal , Varandas Simone Da Graça Pinto , Monteiro Sandra Mariza Veiga
Published: October 2022

The Vilariça River was restored in order to improve the fish habitat due to the construction of dams. However, due to the pressure that agriculture exerts on water resources, it is crucial to evaluate its consequences on fish health from a histological perspective. The gonad histopathological changes of two cyprinid species were assessed microscopically and evaluated with semi-quantitative analysis. Histopathological changes in the gonad, gill, and liver were used as biomarkers in the determination of the Integrated Biomarker Response (IBR), as well as to evaluate the histopathological scores between seasons. The observation of the gonad histopathological changes showed that interstitial fibrosis and macrophage aggregates were present exclusively in the Summer and more prevalent in males of large size. In addition, the histopathological scores of the three organs were higher in the Summer. In terms of the severity degree, 98% and 68% of the fish showed pronounced and severe histopathological changes in the gill and liver, respectively, while 28% of the fish showed slight histopathological changes in the gonad. The IBR showed higher values in the Summer and in the middle stream and downstream, which is in agreement with the metal concentrations. Thus, this work showed a relationship between the anomalies present in the fish organs and the quality of the water (classified as polluted). Therefore, minimization measures are presented, such as improving the irrigation methods, preserving the vegetation cover; promoting reforestation in degraded and burned areas; and improving the riparian vegetation.
A Multi-Dimensional Deep Siamese Network for Land Cover Change Detection in Bi-Temporal Hyperspectral Imagery
Authors: Seydi Seyd Teymoor , Shah-Hosseini Reza , Amani Meisam
Published: October 2022

In this study, an automatic Change Detection (CD) framework based on a multi-dimensional deep Siamese network was proposed for CD in bi-temporal hyperspectral imagery. The proposed method has two main steps: (1) automatic generation of training samples using the Otsu algorithm and the Dynamic Time Wrapping (DTW) predictor, and (2) binary CD using a multidimensional multi-dimensional Convolution Neural Network (CNN). Two bi-temporal hyperspectral datasets of the Hyperion sensor with a variety of land cover classes were used to evaluate the performance of the proposed method. The results were also compared to reference data and two state-of-the-art hyperspectral change detection (HCD) algorithms. It was observed that the proposed method relatively had higher accuracy and lower False Alarm (FA) rate, where the average Overall Accuracy (OA) and Kappa Coefficient (KC) were more than 96% and 0.90, respectively, and the average FA rate was lower than 5%.
Necessity of Post-War Renewal of University Teachers’ Potential in Terms of Sustainable Development in Ukraine
Authors: Ma Xiangfei , Gryshova Inna , Koshkalda Iryna , Suska Anastasiia , Gryshova Rymma , Riasnianska Alona , Tupchii Olga
Published: October 2022

(1) The war in Ukraine has changed the normal life of every Ukrainian, including educators. For the fourth month, the educational process has been taking place under martial law. Thus, the task of every pedagogue and every university teacher is to start the educational process not only for the sake of knowledge, because you cannot deprive children of education, but also for the sake of psychological rehabilitation. The war has given an impetus to the radical renewal of education, particularly higher education, which determines the relevance of this study. (2) It is common knowledge that the professional pedagogical activity of a university teacher is of great significance to society. It is about the formation of a future specialist, whose level of qualification considerably affects the economic, political, social, and cultural component of the sustainable development of society, something which is especially relevant in the post-war period. (3) The research hypothesis is that renewing the potential of university teachers in the post-war period will allow the improvement of the educational process in universities, will significantly increase the level of professional training of students and will ensure the sustainable development of society. To examine this hypothesis, the professional and personal potential of teachers was studied in detail with the aim of understanding radical changes in approaches to methods, techniques, and forms of education, as well as the type and style of communication between teachers and students. (4) The research methodology comprised a survey conducted by the CAWI method using a structured questionnaire based on the respondents’ place of permanent residence. The sample totality was stratified according to the regions of Ukraine where the teachers work. Teachers of Ukrainian higher education institutions took part in the study. The study sample included 350 people. The main task of the study was to analyze the potential of university teachers in the pre-war and post-war periods. The other tasks the study undertakes are to propose the concept of professional unity of students and teachers of higher educational institutions and to consider reflection as a tool; a tool which is a cross-sectional, integrating factor that structures the education system in various types of professional activity. (5) The undoubted achievement of the work is that, for the first time, the state of higher education was analyzed under war conditions and its development in the post-war period was predicted. This will aid the country’s recovery and ensure the sustainable development of society in the post-war period. This study can complement and enhance the theoretical discussion and practical experience on sustainable development from the perspective of higher education.