bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of Advances in Fabrication Methods and Assistive Technologies of Micro-Structured Surfaces
Authors: Ma Yuting , Zhang Guoqing , Cao Shuaikang , Huo Zexuan , Han Junhong , Ma Shuai , Huang Zejia
Published: April 2023

Micro-structured surfaces possess excellent properties of friction, lubrication, drag reduction, antibacterial, and self-cleaning, which have been widely applied in optical, medical, national defense, aerospace fields, etc. Therefore, it is requisite to study the fabrication methods of micro-structures to improve the accuracy and enhance the performance of micro-structures. At present, there are plenty of studies focusing on the preparation of micro-structures; therefore, systematic review of the technologies and developing trend on the fabrication of micro-structures are needed. In present review, the fabrication methods of various micro-structures are compared and summarized. Specially, the characteristics and applications of ultra-precision machining (UPM) technology in the fabrication of micro-structures are mainly discussed. Additionally, the assistive technologies applied into UPM, such as fast tool servo (FTS) technology and slow tool servo (STS) technology to fabricate micro-structures with different characteristics are summarized. Finally, the principal characteristics and applications of fly cutting technology in manufacturing special micro-structures are presented. From the review, it is found that by combining different machining methods to prepare the base layer surface first and then fabricate the sublayer surface, the advantages of different machining technologies can be greatly exerted, which is of great significance for the preparation of multi-layer and multi-scale micro-structures. Furthermore, the combination of ultra-precision fly cutting and FTS/STS possess advantages in realizing complex micro-structures with high aspect ratio and high resolution. However, residual tool marks and material recovery are still the key factors affecting the form accuracy of machined micro-structures. This review provides advances in fabrication methods and assistive technologies of micro-structured surfaces, which serves as the guidance for both fabrication and application of multi-layer and multi-scale micro-structures.
Integration of Multiple Bayesian Optimized Machine Learning Techniques and Conventional Well Logs for Accurate Prediction of Porosity in Carbonate Reservoirs
Authors: Alatefi Saad , Abdel Azim Reda , Alkouh Ahmad , Hamada Ghareb
Published: April 2023

The accurate estimation of reservoir porosity plays a vital role in estimating the amount of hydrocarbon reserves and evaluating the economic potential of a reservoir. It also aids decision making during the exploration and development phases of oil and gas fields. This study evaluates the integration of artificial intelligence techniques, conventional well logs, and core analysis for the accurate prediction of porosity in carbonate reservoirs. In general, carbonate reservoirs are characterized by their complex pore systems, with the wide spatial variation and highly nonlinear nature of their petrophysical properties. Therefore, they require detailed well-log interpretations to accurately estimate their properties, making them good candidates for the application of machine learning techniques. Accordingly, a large database of (2100) well-log records and core-porosity measurements were integrated with four state-of-the-art machine learning techniques (multilayer perceptron artificial neural network, MLP-ANN; Gaussian process regression, GPR; least squares gradient boosting ensemble, LS-Boost; and radial basis function neural network, RBF-NN) for the prediction of reservoir porosity. The well-log data used in this study include sonic acoustic travel time, Gamma-ray, and bulk density log records, which were carefully collected from five wells in a carbonate reservoir. This study revealed that all the artificial intelligence models achieved high accuracy, with R-squared values exceeding 90% during both the training and blind-testing phases. Among the AI models examined, the GPR model outperformed the others in terms of the R-squared values, root-mean-square error (RMSE), and coefficient of variation of the root-mean-square error (CVRMSE). Furthermore, this study introduces an artificially intelligent AI-based correlation for the estimation of reservoir porosity from well-log data; this correlation was developed using an in-house, Fortran-coded MLP-ANN model presented herein. This AI-based correlation gave a promising level of accuracy, with R-squared values of 92% and 90% for the training and blind-testing datasets, respectively. This correlation can serve as an accurate and easy-to-use tool for porosity prediction without any prior experience in utilizing or implementing machine learning models.
Deep Learning Based Methods for Molecular Similarity Searching: A Systematic Review
Authors: Nasser Maged , Yusof Umi Kalsom , Salim Naomie
Published: April 2023

In rational drug design, the concept of molecular similarity searching is frequently used to identify molecules with similar functionalities by looking up structurally related molecules in chemical databases. Different methods have been developed to measure the similarity of molecules to a target query. Although the approaches perform effectively, particularly when dealing with molecules with homogenous active structures, they fall short when dealing with compounds that have heterogeneous structural compounds. In recent times, deep learning methods have been exploited for improving the performance of molecule searching due to their feature extraction power and generalization capabilities. However, despite numerous research studies on deep-learning-based molecular similarity searches, relatively few secondary research was carried out in the area. This research aims to provide a systematic literature review (SLR) on deep-learning-based molecular similarity searches to enable researchers and practitioners to better understand the current trends and issues in the field. The study accesses 875 distinctive papers from the selected journals and conferences, which were published over the last thirteen years (2010–2023). After the full-text eligibility analysis and careful screening of the abstract, 65 studies were selected for our SLR. The review’s findings showed that the multilayer perceptrons (MLPs) and autoencoders (AEs) are the most frequently used deep learning models for molecular similarity searching; next are the models based on convolutional neural networks (CNNs) techniques. The ChEMBL dataset and DrugBank standard dataset are the two datasets that are most frequently used for the evaluation of deep learning methods for molecular similarity searching based on the results. In addition, the results show that the most popular methods for optimizing the performance of molecular similarity searching are new representation approaches and reweighing features techniques, and, for evaluating the efficiency of deep-learning-based molecular similarity searching, the most widely used metrics are the area under the curve (AUC) and precision measures.
Nozzle Jet Deviation from Bucket Pitch Circle’s Effect on the Stability and Efficiency of Pelton Turbine
Authors: Deng Huiming , Song Ke , Deng Fangxiong , Huang Yu , Luo Tao , Zhou Yijin , Qin Bei , Zeng Yongzhong , Yu Zhishun , Pang Jiayang , Liu Xiaobing
Published: April 2023

During the operation of a Pelton turbine, the centerline of the nozzle jet may deviate from the bucket pitch circle due to the low installation and maintenance accuracy, which will reduce the operating efficiency and the stability of the turbine and even cause severe vibrations and damages. Based on the VOF (Volume of Fluid) two-phase flow model and the SST k-ω turbulence model, the flow characteristics of a Pelton turbine were simulated with the nozzle jet deviating from the bucket pitch circle. The pressure pulsation inside the bucket and the force distribution of the runner were obtained, the turbine oscillation and efficiency were measured before and after the jet deviation, and the effects of the radial and axial deviations on the stability and efficiency of the Pelton turbine were analyzed. The results show that both the radial and axial deviations of the jet cause a significant increase in the axial force and the pressure pulsation amplitude of the turbine; the radial and tangential forces on the runner are slightly reduced; the maximum axial force on the runner is increased by 4 times and 2 times, respectively, after the axial and radial deviations within the maximum value allowed by the industry standard; and the efficiency of the turbine is reduced by 0.4% and 0.3%, respectively. The maximum relative amplitude of pressure pulsation in the radial offset case appears in the center of the bucket blade, while the axial offset case causes uneven pressure distribution on both sides of the diverter blade, uneven force on the bucket blade of the runner, and fatigue damage. By comparing the operation of the runner under the two offset cases, we can find that the axial offset of the jet has a greater impact on the stability of the runner than the radial offset, and the unit is more prone to vibration, increasing the risk of the unit lifting.
Food Waste (Beetroot and Apple Pomace) as Sorbent for Lead from Aqueous Solutions—Alternative to Landfill Disposal
Authors: Šoštarić Tatjana , Simić Marija , Lopičić Zorica , Zlatanović Snežana , Pastor Ferenc , Antanasković Anja , Gorjanović Stanislava
Published: April 2023

This article presents studies, whose main goal was to minimize food waste. To achieve this goal, it is necessary to expand the scope of their application, for example, for the purification of polluted water from heavy metals. Millions of tons of waste from the fruit and vegetable industry, including pomace of apples and beetroots, are thrown into landfills, posing a danger to the environment. In order to solve the problems with the disposal of these wastes, the authors investigated their sorption potential for the removal of lead from wastewater. The sorbents, dried apple (AP), and beetroots (BR) pomaces were characterized by various methods (study of composition, zeta potential, FTIR-ATR, and SEM-EDX). Various models of sorption kinetics and sorption isotherms were analyzed. Kinetical studies under optimal conditions showed that the sorption process occurs through complexation and ion exchange and the determining stage limiting the rate of sorption is the diffusion of lead ions in the sorbent. The maximum sorption capacity was 31.7 and 79.8 mg/g for AP and BR, respectively. The thermodynamic data revealed the spontaneous sorption of lead ions by sorbents. The temperature rise contributes to the sorption increase by the AP sorbent, while for the BR sorbent, the opposite effect is observed. The obtained results showed that apple and beetroots pomaces can serve as effective renewable materials for the preparation of sorbents, contributing to the solution of complex environmental problems.
Enhanced Treatment of Basic Red 46 by Ozonation in a Rotating Packed Bed with Liquid Detention
Authors: Xu Peng , Wu Tianyang , Xiang Yang , Yun Jimmy , Shao Lei
Published: April 2023

This study investigated the use of ozone in a rotating packed bed (RPB) with liquid detention for the treatment of Basic Red 46 (BR-46). Liquid detention means that liquid accumulates at the lower section to a certain level in the RPB, which leads to longer liquid residence time and greater liquid holdup in the packing and cavity in the RPB. The experimental results showed that the presence of liquid detention in the RPB significantly enhanced the BR-46 treatment effect and ozone absorption rate. With 200 mL of liquid detention in the RPB, the decolorization rate, COD degradation rate, and ozone absorption rate were 34.7%, 62.8%, and 80.0% higher than those without liquid detention. The effects of the rotational speed of the RPB, ozone concentration, initial BR-46 concentration, liquid and gas flow rates on BR-46 degradation were also investigated, and it was found that the high-gravity environment is beneficial to the degradation of BR-46. These results suggest that with the utilization of the liquid detention phenomena in the high-gravity devices, the applications of the high-gravity technology can be extended to the processes where a long liquid residence time is required.
Junction Temperature Prediction Model for GaAs HBT Devices Based on ASO-ELM
Authors: Sun Xiaohong , Yang Yijun , Zhang Chaoran
Published: April 2023

In this study, an accurate temperature prediction model is proposed for GaAs HBT, which considers both the bias voltage and current rather than power consumption only. The increase in temperature is closely related to the heat source property, which leads to a complex interaction between the lattice vibration and the uneven distribution of the electric field and current density. To improve the accuracy and stability of the temperature prediction model, a machine learning method of Extreme Learning Machine (ELM) optimized with an Atomic Search Algorithm (ASO) is introduced. The validity of the model is verified by comparing it with experimental observations by the QFI InfraScope TM temperature mapping system. The predicted temperatures for an 8 × 8 HBT power cell fabricated with 2 μm GaAs technology show good agreement with the measurement results, with a ±2 °C error and a relative error deviation below 3%. This demonstrates the superior performance of the proposed model in accurately predicting the temperature of GaAs HBT.
Improvement of the Learning Strategies of University Students through a Program Based on Service-Learning
Authors: Hervás Torres Mirian
Published: April 2023

Background: Currently, educational attainment has risen significantly among young people, causing changes in the labor market where skills have become more important. Thus, tertiary education has become an “essential vehicle” to develop high-level skills that would boost students’ professional, social, and personal lives. Methods: The aim of the survey is to study the effects of an intervention program based on two methodologies, service-learning and peer mentoring, to enhance the learn-to-learn and social skills of undergraduate students. The sample was composed of 69 undergraduate students of four different degrees. The methodological design adopted was quasi-experimental pretest–posttest. The intervention consisted of 955 mentoring sessions (878 one-to-one and 77 in groups) among the undergraduate students and students in compulsory education. The undergraduate students participated as mentors. Before, they had three sessions of training. Weekly mentoring sessions were spread out during out-of-school time for 90 min each. Results: The results show a few statistically significant differences in favor of the posttest phase in strategies for the learning and social skills of the participants. Conclusions: Although the program did not obtain the expected results, these outcomes agree with the other studies that investigate intervention programs that use service-learning and peer mentoring methodologies.
Adaptation and Validation of the Arabic Version of the University Student Engagement Inventory (A-USEI) among Sport and Physical Education Students
Authors: Tannoubi Amayra , Quansah Frank , Hagan John Elvis , Srem-Sai Medina , Bonsaksen Tore , Chalghaf Nasr , Boussayala Ghada , Azaiez Chiraz , Snani Haifa , Azaiez Fairouz
Published: April 2023

The present study validated the University Student Engagement Inventory (USEI) in the Arabic language (A) by assessing its factor structure, construct validity, reliability, and concurrent validity. A total of 864 Tunisian Physical Education and Sport students provided data which was used to perform exploratory and confirmatory factor analyses, using samples comprising 366 (aged 19–25 years) and 498 (aged 19–26 years) students, respectively. The A-USEI, grade-point average (GPA), and Physical Education Grit (PE–Grit) scales were completed via online surveys. The exploratory factor analysis revealed that the A-USEI had three dimensions. The confirmatory factor analysis indicated that the second-order model was more suitable than the first-order multi-factor model. Using the indicators for the second-order model, the three factors showed good reliability, with their average variance extracted (AVE) values reflecting sufficient validity. The correlation analyses between the two scales’ scores and the A-USEI scores showed a moderate correlation, confirming the adapted scale’s concurrent validity. The study concludes that A-USEI is a valid tool for assessing student engagement among Arabic students. In addition, the practical implications and directions for future research are discussed.
How Everett Solved the Probability Problem in Everettian Quantum Mechanics
Authors: Lazarovici Dustin
Published: April 2023

A longstanding issue in the Everettian (Many-Worlds) interpretation is to justify and make sense of the Born rule that underlies the statistical predictions of standard quantum mechanics. The paper offers a reappraisal of Everett’s original account in light of the recent literature on the concept of typicality. It argues that Everett’s derivation of the Born rule is sound and, in a certain sense, even an optimal result, and defends it against the charge of circularity. The conclusion is that Everett’s typicality argument can successfully ground post-factum explanations of Born statistics, while questions remain about the predictive power of the Many-Worlds interpretation.
Twentieth-Century Hasidic-Zionist Homiletics: The Case of Netivot Shalom by “the Rebbe Painter”, Avraham Ya‘akov Shapira of Drohobych
Authors: Sachs-Shmueli Leore
Published: April 2023

Much has been written about the theological, cultural, and social foundations of the Zionist movement and its historical development. While scholars have discussed the immigration of the first Hasidim to the Land of Israel in the late eighteenth century, little attention has been paid to the Hasidic leaders who were active in Mandatory Palestine between the two World Wars, some of whom had a positive attitude toward Zionism. My article addresses this scholarly gap and focuses on one figure: the Rebbe painter (Admor ha-Tsayar) Avraham Yaakov Shapira (1886–1962) of the Drohobych dynasty. In this first academic study examining his sermon book Netivot Shalom, I will show how he coherently used the Hasidic homiletic style, as well as textual and oral traditions, to reinforce a commitment to the settlement of Zion and cultivate a positive attitude toward the Jewish people, including the secular settlers. Following in his father’s footsteps, he fervently taught that the way to the hearts of secular settlers was not through rebuke, but through peace, shared mission, and unity. He viewed the activists’ approach to settling Zion as an act of divine action revealing the “new Torah”, and saw their success as a miracle manifested through nature.
Developing a System for Monitoring Human Resource Risks in a Digital Economy
Authors: Babkin Ivan , Pulyaeva Valentina , Ivanova Irina , Veys Yulya , Makhmudova Guljakhon
Published: April 2023

Human resource (HR) risks are significant negative aspects of any organization. The main problem in the theory and practice of modern organizations is that there is no complex model and algorithm for managing HR risks. To define the essence of HR risks and basic approaches to their management, the authors conducted a survey of employees concerning the HR sphere. The authors used cluster and correlation–regression analysis to process the results of the survey conducted among employees about HR risks. Relying on general scientific research methods, data from open sources, including the review of scientific papers of foreign and national researchers and practitioners, and considering the opinions of the sociological survey respondents, the authors concluded that there is a need for carrying out close work with personnel to prevent conflicts in the working environment, increase the motivation for work, and involve the management team in regulating labor relationships. The scientific novelty of the study is that it considers the process of managing HR risks from a systemic perspective, while they are monitored based on the conceptual model suggested in the study. The models developed by the authors can be used in reality for managing HR risks faced by economic entities.
Relationships between Landscape Patterns and Hydrological Processes in the Subtropical Monsoon Climate Zone of Southeastern China
Authors: Wei Chong , Dong Xiaohua , Ma Yaoming , Leng Menghui , Zhao Wenyi , Zhang Chengyan , Yu Dan , Su Bob
Published: April 2023

With rapid economic development, extensive human activity has changed landscape patterns (LPs) dramatically, which has further influenced hydrological processes. However, the effects of LPs changes on hydrological processes, especially for the streamflow–sediment relationship in the subtropical monsoon climate zone, have not been reported. In our study, 10 watersheds with different sizes in the subtropical monsoon climate zone of southeastern China were chosen as the study area, and the effect of the 14 most commonly used landscape metrics (LMs) on 4 typical hydrological indices (water yields (WY), the runoff coefficient (RC), the soil erosion modulus (SEM), and the suspended sediment concentration (SSC)) were analyzed based on land use maps and hydrological data from 1990 to 2019. The results reveal that the LP characteristics within the study area have changed significantly. The number of patches and landscape shape indices were significantly positively correlated with watershed size (p < 0.01). For most watersheds, the largest patch index was negatively correlated with WY, RC, and SEM, and the perimeter area fractal dimension was positively correlated with WY, RC, SEM, and SSC. The effects of several LMs on the hydrological indices had scale effects. WY/RC and the interspersion and juxtaposition index were negatively correlated in most larger watersheds but were positively correlated in most smaller watersheds. Similar results were found for Shannon’s diversity/evenness index and SEM. In general, an increase in a small patch of landscape and in landscape diversity would increase WY, the fragmentation of LPs would result in more soil erosion, and LPs would affect the relationship between streamflow and sediment yield. As a result, a proper decrease in landscape fragmentation and physical connectivity in the subtropical monsoon climate zone of southeastern China would benefit soil erosion prevention. These results enhance the knowledge about the relationship between LPs and hydrological processes in the subtropical monsoon climate zone of southeastern China and benefit local water and soil conservation efforts.
Artificial Ducts Created via High-Power HF Radio Waves at EISCAT
Authors: Blagoveshchenskaya Nataly F. , Borisova Tatiana D. , Kalishin Alexey S. , Egorov Ivan M.
Published: April 2023

Ducts (field-aligned plasma density enhancements) provide a link into the magnetosphere and can guide whistler waves. Inside ducts, wave-particle interactions occur efficiently; therefore, their presence contributes to the removal of energetic particles from the magnetosphere. We present experimental results concerning the characteristics, behavior, and excitation thresholds of ducts induced by extraordinary (X-mode) polarized high-power HF radio waves emitted towards the magnetic zenith (MZ) into the upper ionosphere at EISCAT (European Incoherent SCATter). The features and behavior of ducts were diagnosed by the EISCAT incoherent scatter radar (ISR) at Tromsø and the CUTLASS (SuperDARN) Finland radar at Hankasalmi. The state of the ionosphere was monitored by the Dynasonde in Tromsø. It was found that the electron density Ne enhancements inside ducts were of 50–80% above the background Ne values and their transverse size (normal to the magnetic flux tube) corresponded to about 3–4° in the north–south direction. They were generated during magnetically quiet periods and extended from ~300 to 320 km up to the upper altitude limit of the EISCAT radar measurements (600–700 km), when heater frequencies were both below and above the critical frequency of the F2 layer (fH ≤ foF2 and fH > foF2), regardless of whether HF-induced plasma and ion lines were generated or not. Comparing the O-/X-mode effects from the EISCAT radar observations, it was shown that the creation of the strong Ne ducts is a typical characteristic of the X-mode pulses. As a rule, electron density enhancements were not observed during O-mode pulses. A plausible mechanism for the creation of X-mode artificial ducts is discussed.
Using a Vegetation Index as a Proxy for Reliability in Surface Reflectance Time Series Reconstruction (RTSR)
Authors: Kempeneers Pieter , Claverie Martin , d’Andrimont Raphaël
Published: April 2023

Time series of optical remote sensing data are instrumental for monitoring vegetation dynamics, but are hampered by missing or noisy observations due to varying atmospheric conditions. Reconstruction methods have been proposed, most of which focus on time series of a single vegetation index. Under the assumption that relatively high vegetation index values can be considered as trustworthy, a successful approach is to adjust the smoothed value to the upper envelope of the time series. However, this assumption does not hold for surface reflectance in general. Clouds and cloud shadows result in, respectively, high and low values in the visible and near infrared part of the electromagnetic spectrum. A novel spectral Reflectance Time Series Reconstruction (RTSR) method is proposed. Smoothed values of surface reflectance values are adjusted to approach the trustworthy observations, using a vegetation index as a proxy for reliability. The Savitzky–Golay filter was used as the smoothing algorithm here, but different filters can be used as well. The RTSR was evaluated on 100 sites in Europe, with a focus on agriculture fields. Its potential was shown using different criteria, including smoothness and the ability to retain trustworthy observations in the original time series with RMSE values in the order of 0.01 to 0.03 in terms of surface reflectance.
Mechanical and Thermal Insulation Properties of rGFRP Fiber-Reinforced Lightweight Fly-Ash-Slag-Based Geopolymer Mortar
Authors: Zhang Mo , Qiu Xinxin , Shen Si , Wang Ling , Zang Yongquan
Published: April 2023

As a lightweight cementitious material for thermal insulation, the mechanical performance of foamed geopolymer is always compromised by its density reduction. In this study, recycled-glass-fiber-reinforced plastic (rGFRP) fiber was used to reinforce the fly ash-slag based foamed geopolymer, and vitrified micro bubbles (VMB) were applied to further decrease the thermal conductivity and modify the resistance of the lightweight mortar against drying shrinkage. The results revealed that the density, compressive strength, and thermal conductivity of the foamed geopolymer with/without VMB decreased with the increase in foaming agent content. By adding 2~6% of rGFRP fiber, the compressive strength was increased by 25~165%, and the drying shrinkage was reduced the most, by 55%. After the addition of 10% of VMB, the density, thermal conductivity, and drying shrinkage of foamed geopolymer mortar were further decreased, with the highest reductions of 8%, 26%, and 64%, respectively, due to the reduced pore volume and increase proportion of closed pores. With 6% of rGFRP fiber and 25% of foaming agent, the lightweight geopolymer mortar had the optimum performance, with compressive strength of 1.343 MPa, thermal conductivity of 0.134 W/(m·K), and drying shrinkage of 0.095%. This study developed a sustainable lightweight mortar with multiple types of industrial by-products, which benefit both the development of thermal insulation materials and reuse of solid wastes.
Assessment of Walkability of Large Parking Lots on University Campuses Using Walking Infrastructure and User Behavior as an Assessment Method for Promoting Sustainability
Authors: Alhajaj Nawaf
Published: April 2023

Car-dominated university campuses allocate large areas of land for parking lots, which are major hubs for users to start and end their daily walking trips. However, studies on the walkability of large parking lots are limited, and there is a study gap in the assessment of existing constructed walking infrastructures and their usage and effectiveness in facilitating walking. In this study, a method is developed that can assess both the walking infrastructure and its usage, then applied in five large campus parking lots based on observational strategies. The results indicate that the orientation of a walking path perpendicular to a destination (which provides short-distance walks), availability of proper access to walking paths and designated crossing areas that connect between walking paths, proper implementation of effective traffic calming strategies, and presence of a single entrance and exit for vehicles all play important roles in promoting the use of existing walking infrastructure and creating pedestrian-friendly parking lots. Additionally, this study method extends the walkability assessment of built environments, particularly in large parking lots. This study promotes the creation of sustainable university campuses, thereby enhancing the quality of life of students and staff who use the facilities.
Developing a Digital Business Incubator Model to Foster Entrepreneurship, Business Growth, and Academia–Industry Connections
Authors: Vaz Roberto , de Carvalho João Vidal , Teixeira Sandrina Francisca
Published: April 2023

The roles and positive impacts of business incubators, including virtual ones, in promoting entrepreneurship and innovation in multiple industries, and their consequent contributions to fostering sustainable economic growth and social development, have been highly advocated in the extant literature. Nonetheless, several authors highlight the urgent need to further carry out research concerning these structures’ operation models by involving end users, since knowledge related to this phenomenon remains scant. This study sets out to convey the third phase of a broader research and development project following a design science research methodology. Ultimately, this contributes to the field by proposing a new virtual business incubator model with immediate practical applicability. This model was cocreated and validated with 23 incubator managers and startup founders from 15 business incubation centers during focus group sessions and organized into 8 dimensions concluded as fundamental in future digital incubation programs. Moreover, this study offers knowledgeable guidelines to support academics, practitioners, organization managers, or other professionals interested in building and running virtual business incubators. The main strengths and weaknesses of the proposed model are also highlighted, and several recommendations are provided to surpass the expected challenging stages of its implementation.
Spatiotemporal Changes of Ecosystem Service Values in Response to Land Cover Dynamics in China from 1992 to 2020
Authors: Bao Jianxiong , Wang Wen , Zhao Tianqing
Published: April 2023

Global land cover changed significantly in the last several decades due to strong climate warming and intensive human activities, and those changes greatly affected ecosystem services all over the world. Using CCI-LC land cover data from 1992 to 2020, the spatiotemporal characteristics of land cover change in China were investigated, and the annual ecosystem service values (ESVs) were estimated with the equivalent factor method. The results showed that: (1) The overall accuracy and Kappa coefficient of CCI-LC products in China were 71.1% and 0.65, respectively. (2) From 1992 to 2020, the area of cropland in China increased generally first before 2004 then decreased after 2008; the area of forest land decreased before 2003 then increased after 2015; the area of grassland and bare land consistently decreased; and the area of built-up land continuously increased, with a total increase of 113,000 km2. The primary characteristics of land cover transitions in China were the mutual conversion of cropland, forestland, and grassland as well as the continuous increase of built-up land. (3) Forest land was the most significant contributor of ESV in China, making 62.9% of the total ESV by multi-year average, followed by grassland (18.5%) and water (10.3%); the ESV was roughly high in the southeast China and low in the northwest. (4) The total ESV in China decreased generally before 2015 and got stable in the last five years. The hot spots with rising ESV were mainly concentrated in the western, northern and southwestern parts of China, while the cold spots with declining ESV were mainly concentrated in the economically developed eastern and southern China. (5) Cropland, forest land, grassland, and water were the positive contributors to ESV change in China, while built-up land and bare land were the negative contributors. The findings provide a theoretical foundation for China’s harmonized socioeconomic and environmental development.
Inventory Transshipment Considering Greenhouse Gas Emissions for Sustainable Cross-Filling in Cold Supply Chains
Authors: Vu Hang Thi Thanh , Ko Jeonghan
Published: April 2023

In recent years, sustainable supply chain management has gained increasing attention, and greenhouse gas (GHG) emissions throughout supply chains have been identified as one of the most important sustainability issues. This paper presents an investigation of the problem of transshipment among distribution centers (DCs) in a cold supply chain to achieve sustainable inventory cross-filling. Although transshipment is an effective tool for supply chain pooling, the possibility of increased GHG emissions raises environmental concerns. This study establishes a sustainable cold-chain logistics model that considers GHG emissions from DC storage and transshipment trucks. The new sustainable cold-chain model also reflects laden status and cargo weights of trucks for accurate emission assessment. An optimization model is also developed to minimize both GHG emissions and costs in the cold chain. Numerical simulations are conducted for diverse problem cases to examine important problem characteristics. The result analysis identifies that inventory service levels and demand variability have a strong impact on GHG emissions in transshipment; small p-values in the statistical analysis verify the significance of this effect. The different effects of demand variability and service levels on each emission source are also analyzed. The results demonstrate that transshipment among DCs can effectively reduce both GHG emissions and costs in cold supply chains. This study provides useful models and tools to assess GHG emissions and optimize decisions for the design and operation of transshipment. The proposed models will enable the assessment of sustainable alternatives and achieve sustainability objectives effectively for cold supply chains.
A Front Advancing Adaptive Triangular Mesh Dynamic Generation Algorithm and Its Application in 3D Geological Modeling
Authors: He Liang , Li Xiaoqing , Lei Shaohua , Bi Bo , Chen Suozhong
Published: April 2023

The traditional advancing front technique algorithm encounters many problems due to the complex geometric characteristics of the front edge shape. These problems include poor quality, a slow algorithm, low robustness, and the inability of the mesh unit to converge. To address these problems, an optimized adaptive triangular mesh dynamic generation algorithm called R-TIN is proposed and applied to 3D engineering geological modeling in this study. Firstly, all the shapes involved in advancing the front edge inward were classified into four types, and then the optimal triangular unit was constructed by using the candidate mesh point heuristic algorithm. Then, the robustness of this algorithm could be maintained by the graded concession of the included angle threshold in the adjacent front-line segments. Finally, based on 160 engineering geological boreholes in the study area, the 3D engineering geological model was constructed and the accuracy and visualization effect of the overall geological model have been greatly improved, which can better present the spatial distribution of strata and lithological characteristics. At the same time, this algorithm can be used in geoscience information services to support the regional or national exploration of resources and energy, sustainable development and utilization, environmental protection and the prevention of geological disasters.
Impact of Disruption on Ship Emissions in Port: Case of Pandemic in Long Beach
Authors: He Zhengxin , Lam Jasmine Siu Lee , Liang Maohan
Published: April 2023

To achieve environmental sustainability on ships, stakeholders should make efforts to reduce emissions. Port authorities are crucial to attain this goal by introducing new policies. This study takes the Port of Long Beach as an example to assess port-wide ship emissions and explain the significance of shore power policy. Additionally, the study considers the impact of disruptions, such as the COVID pandemic, on ship emissions. The analysis compares data from three years before and after the pandemic to examine the relationship between ship waiting times, quantities, and emissions. The findings indicate that the majority of port-wide ship emissions are generated by berthing or anchoring vessels, from ship auxiliary engines and boilers. Furthermore, ship congestion due to reduced port productivity during the pandemic significantly increased emissions from berthing and anchoring vessels, with the emission proportion increasing from 68% to 86%. Adopting the shore power policy has effectively reduced ship emissions in port areas, and increasing the number of ships utilising shore power will be instrumental in tackling excessive ship emissions.
The Three-Dimensional Analytical and Governance Logic of China’s Digital Divide Bridging Policy
Authors: Qi Meng , Zhang Bei , Li Junjie , Liu Bangfan
Published: April 2023

In the digital era, digital technology enables political, economic and social fields. However, while the digital divide is pervasive due to the influence of population, geography, the economy and other factors, blindly pushing digital change often leads to the further expansion of the risks of social inequality. This paper constructed a three-dimensional analytical framework of digital gap-bridging policies from the perspective of policy objectives, policy tools and policy effectiveness. Based on this framework, this paper used the content analysis method to conduct a quantitative analysis of 81 digital gap-bridging policies published in China and selected the PMC index model for policy evaluation. The result shows that the policy goal of bridging the digital divide in China mainly focuses on bridging the material access gap and the technology gap, while inadequate attention was paid to the attitude gap and the use gap; in terms of policy tools, there exists an unbalanced situation regarding supply tools, environment and demand tools, with the first one being emphasized more than the others; there is still policy “fatigue” regarding weak feedback and less incentive, though the internal consistency level of the policy is good and the policy structure is reasonable. Therefore, we should optimize policy objectives and policy tools to bridge the digital divide. We should not only consider whether there is “or not” on the equipment and whether there is “or not” on the technology, but also consider whether we want to “or not” on the attitude and feel “or not” on the use; we should not only “give” unilaterally through supply-oriented policies but also “cooperate” with each other through demand-oriented and environment-oriented tools to release the maximum potential of digital empowerment.
Estimation of Rubber Yield Using Sentinel-2 Satellite Data
Authors: Bhumiphan Niwat , Nontapon Jurawan , Kaewplang Siwa , Srihanu Neti , Koedsin Werapong , Huete Alfredo
Published: April 2023

Rubber is a perennial plant grown to produce natural rubber. It is a raw material for industrial and non-industrial products important to the world economy. The sustainability of natural rubber production is, therefore, critical for smallholder livelihoods and economic development. To maintain price stability, it is important to estimate the yields in advance. Remote sensing technology can effectively provide large-scale spatial data; however, productivity estimates need to be processed from high spatial resolution data generated from satellites with high accuracy and reliability, especially for smallholder livelihood areas where smaller plots contrast with large farms. This study used reflectance data from Sentinel-2 satellite imagery acquired for the 12 months between December 2020 and November 2021. The imagery included 213 plots where data on rubber production in smallholder agriculture were collected. Six vegetation indices (Vis), namely Green Soil Adjusted Vegetation Index (GSAVI), Modified Simple Ratio (MSR), Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), Normalized Green (NR), and Ratio Vegetation Index (RVI) were used to estimate the rubber yield. The study found that the red edge spectral band (band 5) provided the best prediction with R2 = 0.79 and RMSE = 29.63 kg/ha, outperforming all other spectral bands and VIs. The MSR index provided the highest coefficient of determination, with R2 = 0.62 and RMSE = 39.25 kg/ha. When the red edge reflectance was combined with the best VI, MSR, the prediction model only slightly improved, with a coefficient determination of (R2) of 0.80 and an RMSE of 29.42 kg/ha. The results demonstrated that the Sentinel-2 data are suitable for rubber yield prediction for smallholder farmers. The findings of this study can be used as a guideline to apply in other countries or areas. Future studies will require the use of reflectance and vegetation indices derived from satellite data in combination with meteorological data, as well as the application of complex models, such as machine learning and deep learning.
Sustainable Tourism Development and Innovation: Recent Advances and Challenges
Authors: Vrana Vasiliki
Published: April 2023

Traveling and tourism are now an essential part of people’s life and have a big influence on society [...]
Identification of Key Basic Parameters Involved in Carbon Emissions in Full-Scale Wastewater Treatment Plants
Authors: Gao Kuo , Yang Hong , Zhao Qingliang , Liu Haichen
Published: April 2023

In this study, carbon emissions in three full-scale wastewater treatment plants were determined by the emission factor method. Moreover, the correlation between basic parameters (influent water parameters and pollutant removal efficiency) and carbon emissions was examined via a structural equation model (SEM). The results showed a significant variation in the total carbon emission intensity of plants over time. The average total carbon emission intensity of plants A, B and C were 0.314, 0.404 and 0.363 kg eqCO2/m³, respectively. Meanwhile, the indirect carbon emission caused by energy and chemical agent consumption accounts for the majority of total carbon emissions (about 85%). Generally, statistical analysis results show that carbon emission intensity is positively correlated with pollutant removal efficiency. Notably, RTN showed the highest positive correlation with Eind, followed by RTN > RCODCr > RTP > TN > RNH3-N > NH3-N > TP. Moreover, capacity showed the greatest negative contribution to Eind, followed by CODCr. In contrast, the positive contribution to Edir was followed by the sequence of RTN > RCODCr > TN > RNH3-N > NH3-N. Notably, CODCr showed a significantly negative correlation with Edir, while TP and its removal showed little correlation with Edir.
Detection of Abnormal Data in GNSS Coordinate Series Based on an Improved Cumulative Sum
Authors: Liu Chao , Xu Qingjie , Fan Ya , Wu Hao , Chen Jian , Lin Peng
Published: April 2023

The global navigation satellite system (GNSS), as a high-time resolution and high-precision measurement technology, has been widely used in the field of deformation monitoring. Owing to the influence of uncontrollable factors, there are inevitably some abnormal data in the GNSS monitoring series. Thus, it is necessary to detect and identify abnormal data in the GNSS monitoring series to improve the accuracy and reliability of the deformation disaster law analysis and warning. Many methods can be used to detect abnormal data, among which the statistical process control theory, represented by the cumulative sum (CUSUM), is widely used. CUSUM usually constructs statistics and determines control limits based on the threshold criteria of the average run length (ARL) and then uses the control limits to identify abnormal data in CUSUM statistics. However, different degrees of the ‘trailing’ phenomenon exist in the interval of abnormal data identified by the algorithm, leading to a higher false alarm rate. Therefore, we propose an improved CUSUM method that uses breaks for additive season and trend (BFAST) instead of ARL-based control limits to identify abnormal data in CUSUM statistics to improve the accuracy of identification. The improved CUSUM method is used to detect abnormal data in the GNSS coordinate series. The results show that compared with CUSUM, the improved CUSUM method shows stronger robustness, more accurate detection of abnormal data, and a significantly lower false alarm rate.
The Impact of Institutional Quality on Sectoral Foreign Direct Investment in Pakistan: A Dynamic Simulated ARDL Approach
Authors: Khan Zafar Ullah , Khan Alam , Khan Dilawar , Magda Róbert
Published: April 2023

Capital is needed to accelerate the development process, but developing nations struggle with minimum resources. Since foreign direct investment (FDI) is essential to solve the funding shortage, developing nations make every effort to attract FDI to their countries. This study was conducted to explore the impact of institutional quality on sectoral FDI in Pakistan using time series data for the period from 1986 to 2019. To create a solid foundation for policy formulation, this study developed a single measure of institutional quality by utilizing a wide range of institutional indicators. It evaluates the impact of overall institution quality on sector-level FDI and examines the causal relationship between institutions and sectoral FDI with a clear focus on a single-country analysis. The dynamic simulated autoregressive distributed lag technique was employed to explore the impact of institutional quality and other factors on FDI. The results of the study explained that institutional quality and TO have a positive and significant effect on the FDI of the primary FDI sector at 5%, while in the case of the secondary sector, the effect of institutional quality, HDI and GDP on FDI inflow is significant at 10% and TO has a significant effect on secondary sector FDI at 5%. In addition, institutional quality and GDP have a positive relationship with tertiary sector FDI at 5%. The empirical findings show that higher institutional quality in emerging economies such as Pakistan encourages large transfers of technological advances through FDI, increasing the overall performance of the economy. This study found that institutional quality significantly increases sectoral FDI in Pakistan. Finally, this study prescribes some policy measures to increase FDI based on the findings.