bluuebunny/crossref_metadata_2025 huggingface dataset:
The Presence of Virus Neutralizing Antibodies Is Highly Associated with Protection against Virulent Challenge in Domestic Pigs Immunized with ASFV live Attenuated Vaccine Candidates
Authors: Silva Ediane B. , Krug Peter W. , Ramirez-Medina Elizabeth , Valladares Alyssa , Rai Ayushi , Espinoza Nallely , Gladue Douglas P. , Borca Manuel V.
Published: November 2022

African swine fever virus (ASFV) is currently producing a pandemic affecting a large area of Eurasia, and more recently, the Dominican Republic in the Western Hemisphere. ASFV is a large and structurally complex virus with a large dsDNA genome encoding for more than 150 genes. Live attenuated virus strains can induce protection in domestic swine against disease produced by homologous virulent parental viruses. The roles of the different immune mechanisms induced by the attenuated strains in protection still need to be understood. In particular, the role of ASFV neutralizing antibody in protection still is an important controversial issue to be elucidated. Here we present the development of a novel methodology to detect virus neutralizing antibodies based on the reduction of virus infectivity in a Vero cell adapted ASFV strain. The described method was used to assess levels of virus neutralizing antibodies in domestic swine inoculated with live attenuated ASFV. Results demonstrated a high association between the presence of virus neutralizing antibodies and protection in 84 animals immunized with the recombinant vaccine candidates ASFV-G-Δ9GL/ΔUK or ASFV-G-ΔI177L. To our knowledge, this is the first report demonstrating an association between virus neutralizing antibodies and protection against virulent challenge in such a large number of experimental individuals.
Phytochemical Characterization and Biological Evaluation of Origanum vulgare L. Essential Oil Formulated as Polymeric Micelles Drug Delivery Systems
Authors: Bora Larisa , Burkard Tobias , Juan Martina Herrero San , Radeke Heinfried H. , Muț Ana Maria , Vlaia Lavinia Lia , Magyari-Pavel Ioana Zinuca , Diaconeasa Zorița , Socaci Sonia , Borcan Florin , Kis Brigitta , Muntean Delia , Dehelean Cristina Adriana , Danciu Corina
Published: November 2022

This study presents phytochemical characterization and biological evaluation of Origanum vulgare L. essential oil (OEO) formulated as polymeric micelles drug delivery systems as a possible non-invasive approach for the management of skin tags. GC-MS analysis of Romanian OEO revealed the identification and quantification of 43 volatile compounds (thymol and carvacrol being the main ones). The antioxidant activity was shown by four consecrated methods: CUPRAC, ABTS, ORAC and DPPH. OEO was incorporated by micellar solubilization into a binary hydrogel based on a Pluronic F 127/L 31 block-copolymers mixture. The pH, consistency, spreadability, particle size, polydispersity index and zeta potential of the OEO-loaded poloxamer-based binary hydrogel (OEO-PbH) were investigated. OEO-PbH was skin compatible in terms of pH and exhibited adequate spreadability and consistency. The minimal inhibitory concentrations of the tested OEO were similar to those obtained for the formulation, lower (2.5 µg/mL) for yeast and higher (40–80 µg/mL) for Gram-negative bacilli. As keratinocytes are among main components of skin tags, an in vitro evaluation was conducted in order to see the effect of the formulation against HaCaT human keratinocytes. OEO-PbH decreased HaCaT cells migration and proliferation and elicited a cytotoxic and pro-apoptotic effect in a dose- and time-dependent manner. No harmful effect on the viability of dendritic cells (DCs) was detected following the incubation with different concentrations (0–200 µg/mL) of the 5% formulation. Treatment in inflammatory DCs (+LPS) indicated a decrease in cytokine production of IL-6, TNF-α and IL-23 but no significant effect on IL-10 in any of the tested concentrations.
PAD4 and Its Inhibitors in Cancer Progression and Prognosis
Authors: Zhu Di , Lu Yu , Wang Yanming , Wang Yuji
Published: November 2022

The systemic spread of malignancies and the risk of cancer-associated thrombosis are major clinical challenges in cancer therapy worldwide. As an important post-translational modification enzyme, peptidyl arginine deiminase 4 (PAD4) could mediate the citrullination of protein in different components (including nucleus and cytoplasm, etc.) of a variety of cells (tumor cells, neutrophils, macrophages, etc.), thus participating in gene regulation, neutrophil extracellular trap (NET) and macrophage extracellular trap (MET). Thereby, PAD4 plays an important role in enhancing the growth of primary tumors and facilitating the distant metastasis of cancer cells. In addition, it is related to the formation of cancer-associated thrombosis. Therefore, the development of PAD4-specific inhibitors may be a promising strategy for treating cancer, and it may improve patient prognosis. In this review, we describe PAD4 involvement in gene regulation, protein citrullination, and NET formation. We also discuss its potential role in cancer and cancer-associated thrombosis, and we summarize the development and application of PAD4 inhibitors.
Control Strategy for Excipient Variability in the Quality by Design Approach Using Statistical Analysis and Predictive Model: Effect of Microcrystalline Cellulose Variability on Design Space
Authors: Kim Ji Yeon , Choi Du Hyung
Published: November 2022

Although various quality by design (QbD) approaches have been used to establish a design space to obtain robust drug formulation and process parameters, the effect of excipient variability on the design space and drug product quality is unclear. In this study, the effect of microcrystalline cellulose (MCC) variability on drug product quality was examined using a design space for immediate-release tablets of amlodipine besylate. MCC variability was assessed by altering the manufacturer and grade. The formulation was developed by employing the QbD approach, which was optimized using a D-optimal mixture design. Using 36 different MCCs, the effect of MCC variability on the design space was assessed. The design space was shifted by different manufacturers and grades of MCC, which resulted in associations between the physicochemical properties of MCC and critical quality attributes (CQAs). The correlation between the physicochemical properties of MCCs and CQAs was assessed through a statistical analysis. A predictive model correlating the physicochemical properties of MCCs with dissolution was established using an artificial neural network (ANN). The ANN model accurately predicted dissolution with low absolute and relative errors. The present study described a comprehensive QbD approach, statistical analysis, and ANN to comprehend and manage the effect of excipient variability on the design space.
Optical Design for Aberration Correction of Ultra-Wide Spectral Range Echelle Spectrometer
Authors: Wang Yuming , Qu Youshan , Zhao Hui , Fan Xuewu
Published: November 2022

The echelle grating spectrometer, with a wide spectral range and high-resolution spectral analysis, is one of the best tools for fine spectral measurement. Nevertheless, it suffers from excessive residual aberrations and a large overall size. In this study, the design and implementation of a novel asymmetric Czerny–Turner ultra-wide spectral range achromatic echelle spectrometer are described. The echelle spectrometer has three channels, and it uses an off-axis parabolic mirror to obtain collimated light without aberrations. Three sets of gratings and dispersive prisms with different coatings are utilized as cross-dispersion elements to acquire two-dimensional images containing spectral information. Suitable detectors are selected according to the requirements of each channel, and three sets of coaxial focusing lenses are designed separately to minimize the aberration. The results of the simulation analysis by ZEMAX indicate that in the entire operating band (200–1100 nm), the root mean square radius of the dispersion spots is ≤ 2.2 μm, all of which are located within the limited range of the size of the detector, thus ensuring that the system’s spectral resolution reaches 0.02 nm at 200 nm, 0.04 nm at 650 nm, and 0.1 nm at 1100 nm.
Chemical Composition and Phytotoxic and Antibiofilm Activity of the Essential Oils of Eucalyptus bicostata, E. gigantea, E. intertexta, E. obliqua, E. pauciflora and E. tereticornis
Authors: Polito Flavio , Kouki Habiba , Khedhri Sana , Hamrouni Lamia , Mabrouk Yassine , Amri Ismail , Nazzaro Filomena , Fratianni Florinda , De Feo Vincenzo
Published: November 2022

Eucalyptus species are characterized by their richness in essential oils (EOs) with a great diversity of biological activities. This study reports the chemical composition and the phytotoxic and antibiofilm activities of the EOs of six Eucalyptus species growing in Tunisia: E. bicostata, E. gigantea, E. intertexta, E. obliqua, E. pauciflora and E. tereticornis. Four EOs were rich above all in oxygenated monoterpenes (25.3–91.4%), with eucalyptol as the main constituent. However, in the EOs of E. pauciflora and E. tereticornis, sesquiterpene hydrocarbons (28.8–54.0%) were the main class of constituents; piperitone was the main constituent of both EOs. The phytotoxicity of the EOs was tested against germination and radicle elongation of the weeds Sinapis arvensis and Lolium multiflorum and the crop Raphanus sativus, resulting in the different inhibition of seed germination and radicle elongation depending on both chemical composition and the seed tested, with remarkable phytotoxicity towards S. arvensis and R. sativus. Furthermore, almost all EOs showed antibacterial potential, resulting in significant inhibition of bacterial biofilm formation and the metabolism of Gram-positive (Staphylococcus aureus subsp. aureus and Listeria monocytogenes) and Gram-negative (Acinetobacter baumannii, Pseudomonas aeruginosa and Escherichia coli) bacterial strains, in addition to acting on mature biofilms. The EOs were inhibitory against all bacterial strains tested and usually reluctant to undergo the action of conventional antibiotics. Therefore, these EOs may be considered for applications both as herbicides and in food and health fields.
The Structural Evolution and Mechanical Properties of Semi-Aromatic Polyamide 12T after Stretching
Authors: Shang Yuting , Lou Hongchuan , Zhao Wei , Zhang Yuancheng , Cui Zhe , Fu Peng , Pang Xinchang , Zhang Xiaomeng , Liu Minying
Published: November 2022

The development of semi-aromatic polyamides with excellent mechanical properties has always been a popular research avenue. In this work, the semi-aromatic polyamide 12T (PA12T) with the maximum tensile strength of 465.5 MPa was prepared after stretching at 210 °C 4.6 times. Wide-angle X-ray diffraction (WAXD) and small-angle X-ray scattering (SAXS) were used to characterize the structural evolution of semi-aromatic polyamide 12T (PA12T) after stretching at different stretching temperatures and stretching ratios. The formation mechanism of this change in mechanical properties was investigated from different aspects of the aggregated structure such as crystal morphology, crystal orientation and crystallinity. The relevant characterization results show that the crystal structure, crystal orientation and crystallinity of PA12T were the highest when the sample was pre-stretched at 210 °C, which is crucial for improving the mechanical properties of PA12T. These findings will provide important guidance for the preparation of polymer materials with excellent mechanical properties.
Silk Fibroin Hydrogels Incorporated with the Antioxidant Extract of Stryphnodendron adstringens Bark
Authors: de Brito Vivian P. , de Souza Ribeiro Maurício M. , Viganó Juliane , de Moraes Mariana A. , Veggi Priscilla C.
Published: November 2022

Barbatimão (Stryphnodendron adstringens) is a Brazilian medicinal plant known for its pharmacological properties, including healing activity related to its phenolic composition, which is chiefly given by tannins. In order to preserve its stability and bioactivity, barbatimão extracts can be incorporated into (bio-)polymeric matrixes, of which silk fibroin stands out due to its versatility and tunable properties. This work aimed to obtain barbatimão bark extract rich in phenolic compounds and evaluate its incorporation in fibroin hydrogels. From the extraction process, it was observed that the PG (propylene glycol) extract presented a higher global yield (X0) and phenolic compounds (TPC) than the ET (ethanol) extract. Furthermore, the antioxidant activity (ORAC and FRAP) was similar between both extracts. Regarding the hydrogels, morphological, chemical, thermal, and mechanical characterizations were performed to understand the influence of the barbatimão extract and the solvent on the fibroin hydrogel properties. As a result, the hydrogels containing the barbatimão PG extract (BT/PG hydrogels) showed the better physical–chemical and structural performance. Therefore, these hydrogels should be further investigated regarding their potential in medical and pharmaceutical applications, especially in wound healing.
Sensitive Organic Vapor Sensors Based on Flexible Porous Conductive Composites with Multilevel Pores and Thin, Rough, Hollow-Wall Structure
Authors: Kong Ting-Ting , Zhou Jia-Hai , Nie Feng , Zhang Chao , Shen Fei-Xiang , Dai Shou-Wei , Pan Hong-Tao , Gong Li-Xiu , Zhao Li
Published: November 2022

Advanced organic vapor sensors that simultaneously have high sensitivity, fast response, and good reproducibility are required. Herein, flexible, robust, and conductive vapor-grown carbon fibers (VGCFs)-filled polydimethylsiloxane (PDMS) porous composites (VGCFs/PDMS sponge (CPS)) with multilevel pores and thin, rough, and hollows wall were prepared based on the sacrificial template method and a simple dip-spin-coating process. The optimized material showed outstanding mechanical elasticity and durability, good electrical conductivity and hydrophobicity, as well as excellent acid and alkali tolerance. Additionally, CPS exhibited good reproducible sensing behavior, with a high sensitivity of ~1.5 × 105 s−1 for both static and flowing organic vapor, which was not affected in cases such as 20% squeezing deformation or environment humidity distraction (20~60% RH). Interestingly, both the reproducibility and sensitivity of CPS were better than those of film-shaped VGCFs/PDMS (CP), which has a thickness of two hundred microns. Therefore, the contradiction between the reproducibility and high sensitivity was well-solved here. The above excellent performance could be ascribed to the unique porous structures and the rough, thin, hollow wall of CPS, providing various gas channels and large contact areas for organic vapor penetration and diffusion. This work paves a new way for developing advanced vapor sensors by optimizing and tailoring the pore structure.
God and Evil—Systematic-Theological Reflections on the Doctrine of God
Authors: Danz Christian
Published: November 2022

Against the background of the current debates about God and evil, the article elaborates in three stages of argumentation the thesis that statements about God must not be understood as factual or representational statements, but as descriptive elements of the reflexive structure of the Christian religious communication. On this basis, a new perspective on God’s relationship to evil in the world emerges, which, in contrast to the so-called theodicy debates, includes the self-view of the religious practitioners.
The Buddhist Impact on the Last Testaments of Women in Medieval China
Authors: Jiang Aihua , Lang Lang
Published: November 2022

Through a comparative study of last testaments documented in epitaphs of the Tang period, this article offers a glimpse into people’s outlooks on life and their concerns in the face of death. The thoughts expressed in last testaments have been neglected in the studies of Buddhism in the Tang Dynasty, with research restricted to compilations of materials. In-depth analyses of such materials are rare. Through a study of the last testaments in the epitaphs, several trends in attitudes towards death and burial can be discerned: a turn from burial to cremation; the simplification of ritual and its procedures; a greater prevalence of separate, rather than joint spousal interment. The last testaments from the Tang period exhibit these different features under the influence of Buddhist ideas prevalent during those times.
Quantifying the Effect of River Ice Surface Roughness on Sentinel-1 SAR Backscatter
Authors: Palomaki Ross T. , Sproles Eric A.
Published: November 2022

Satellite-based C-band synthetic aperture radar (SAR) imagery is an effective tool to map and monitor river ice on regional scales because the SAR backscatter is affected by various physical properties of the ice, including roughness, thickness, and structure. Validation of SAR-based river ice classification maps is typically performed using expert interpretation of aerial or ground reference images of the river ice surface, using visually apparent changes in surface roughness to delineate different ice classes. Although many studies achieve high classification accuracies using this qualitative technique, it is not possible to determine if the river ice information contained within the SAR backscatter data originates from the changes in surface roughness used to create the validation data, or from some other ice property that may be more relevant for ice jam forecasting. In this study, we present the first systematic, quantitative investigation of the effect of river ice surface roughness on C-band Sentinel-1 backscatter. We use uncrewed aerial vehicle-based Structure from Motion photogrammetry to generate high-resolution (0.03 m) digital elevation models of river ice surfaces, from which we derive measurements of surface roughness. We employ Random Forest models first to repeat previous ice classification studies, and then as regression models to explore quantitative relationships between ice surface roughness and Sentinel-1 backscatter. Classification accuracies are similar to those reported in previous studies (77–96%) but poor regression performance for many surface roughness metrics (5–113% mean absolute percentage errors) indicates a weak relationship between river ice surface roughness and Sentinel-1 backscatter. Additional work is necessary to determine which physical ice properties are strong controls on C-band SAR backscatter.
Improving Building Extraction by Using Knowledge Distillation to Reduce the Impact of Label Noise
Authors: Xu Gang , Deng Min , Sun Geng , Guo Ya , Chen Jie
Published: November 2022

Building extraction using deep learning techniques has advantages but relies on a large number of clean labeled samples to train the model. Complex appearance and tilt shots often cause many offsets between building labels and true locations, and these noises have a considerable impact on building extraction. This paper proposes a new knowledge distillation-based building extraction method to reduce the impact of noise on the model and maintain the generalization of the model. The method can maximize the generalizable knowledge of large-scale noisy samples and the accurate supervision of small-scale clean samples. The proposed method comprises two similar teacher and student networks, where the teacher network is trained by large-scale noisy samples and the student network is trained by small-scale clean samples and guided by the knowledge of the teacher network. Experimental results show that the student network can not only alleviate the influence of noise labels but also obtain the capability of building extraction without incorrect labels in the teacher network and improve the performance of building extraction.
A Catalogue of Machine Learning Algorithms for Healthcare Risk Predictions
Authors: Mavrogiorgou Argyro , Kiourtis Athanasios , Kleftakis Spyridon , Mavrogiorgos Konstantinos , Zafeiropoulos Nikolaos , Kyriazis Dimosthenis
Published: November 2022

Extracting useful knowledge from proper data analysis is a very challenging task for efficient and timely decision-making. To achieve this, there exist a plethora of machine learning (ML) algorithms, while, especially in healthcare, this complexity increases due to the domain’s requirements for analytics-based risk predictions. This manuscript proposes a data analysis mechanism experimented in diverse healthcare scenarios, towards constructing a catalogue of the most efficient ML algorithms to be used depending on the healthcare scenario’s requirements and datasets, for efficiently predicting the onset of a disease. To this context, seven (7) different ML algorithms (Naïve Bayes, K-Nearest Neighbors, Decision Tree, Logistic Regression, Random Forest, Neural Networks, Stochastic Gradient Descent) have been executed on top of diverse healthcare scenarios (stroke, COVID-19, diabetes, breast cancer, kidney disease, heart failure). Based on a variety of performance metrics (accuracy, recall, precision, F1-score, specificity, confusion matrix), it has been identified that a sub-set of ML algorithms are more efficient for timely predictions under specific healthcare scenarios, and that is why the envisioned ML catalogue prioritizes the ML algorithms to be used, depending on the scenarios’ nature and needed metrics. Further evaluation must be performed considering additional scenarios, involving state-of-the-art techniques (e.g., cloud deployment, federated ML) for improving the mechanism’s efficiency.
Electrogastrogram-Derived Features for Automated Sickness Detection in Driving Simulator
Authors: Jakus Grega , Sodnik Jaka , Miljković Nadica
Published: November 2022

The rapid development of driving simulators for the evaluation of automated driving experience is constrained by the simulator sickness-related nausea. The electrogastrogram (EGG)-based approach may be promising for immediate, objective, and quantitative nausea assessment. Given the relatively high EGG sensitivity to noises associated with the relatively low amplitude and frequency spans, we introduce an automated procedure comprising statistical analysis and machine learning techniques for EGG-based nausea detection in relation to the noise contamination during automated driving simulation. We calculate the root mean square of EGG amplitude, median and dominant frequencies, magnitude of Power Spectral Density (PSD) at dominant frequency, crest factor of PSD, and spectral variation distribution along with newly introduced parameters: sample and spectral entropy, autocorrelation zero-crossing, and parameters derived from the Poincaré diagram of consecutive EGG samples. Results showed outstanding robustness of sample entropy with moderate robustness of autocorrelation zero-crossing, dominant frequency, and its median. Machine learning reached an accuracy of 88.2% and revealed sample entropy as one of the most relevant and robust parameters, while linear analysis highlighted spectral entropy, spectral variation distribution, and crest factor of PSD. This study clearly indicates the need for customized feature selection in noisy environments, as well as a complementary approach comprising machine learning and statistical analysis for efficient nausea detection.
Verifiable, Secure Mobile Agent Migration in Healthcare Systems Using a Polynomial-Based Threshold Secret Sharing Scheme with a Blowfish Algorithm
Authors: Kumar Pradeep , Banerjee Kakoli , Singhal Niraj , Kumar Ajay , Rani Sita , Kumar Raman , Lavinia Cioca Adriana
Published: November 2022

A mobile agent is a software application that moves naturally among hosts in a uniform and non-uniform environment; it starts with one host and then moves onto the next in order to divide data between clients. The mobile paradigm is utilized in a wide assortment of medical care applications such as the medical information of a patient, the recovery of clinical information, the incorporation of information pertaining to their wellbeing, dynamic help, telemedicine, obtaining clinical data, patient administration, and so on. The accompanying security issues have grown in tandem with the complexity and improvements in mobile agent technologies. As mobile agents work in an insecure environment, their security is a top priority when communicating and exchanging data and information. Data integrity, data confidentiality and authentication, on-repudiation, denial of service, and access control, are all key security concerns with mobile agent migration. This paper proposes a Verifiable, Secure Mobile Agent Migration model, based on two polynomials (t, n), and an edge secret imparting plan with Blowfish encryption, to enable secure information transmission in clinical medical care.
Advances in Intelligent Vehicle Control
Authors: Cabrera Juan A.
Published: November 2022

Advanced intelligent vehicle control systems have evolved in the last few decades thanks to the use of artificial-intelligence-based techniques, the appearance of new sensors, and the development of technology necessary for their implementation [...]
Prediction of the Nitrogen Content of Rice Leaf Using Multi-Spectral Images Based on Hybrid Radial Basis Function Neural Network and Partial Least-Squares Regression
Authors: Wu Yawen , Al-Jumaili Saba , Al-Jumeily Dhiya , Bian Haiyi
Published: November 2022

This paper’s novel focus is predicting the leaf nitrogen content of rice during growing and maturing. A multispectral image processing-based prediction model of the Radial Basis Function Neural Network (RBFNN) model was proposed. Moreover, this paper depicted three primary points as the following: First, collect images of rice leaves (RL) from a controlled condition experimental laboratory and new shoot leaves in different stages in the visible light spectrum, and apply digital image processing technology to extract the color characteristics of RL and the morphological characteristics of the new shoot leaves. Secondly, the RBFNN model, the General Regression Model (GRL), and the General Regression Method (GRM) model were constructed based on the extracted image feature parameters and the nitrogen content of rice leaves. Third, the RBFNN is optimized by and Partial Least-Squares Regression (RBFNN-PLSR) model. Finally, the validation results show that the nitrogen content prediction models at growing and mature stages that the mean absolute error (MAE), the Mean Absolute Percentage Error (MAPE), and the Root Mean Square Error (RMSE) of the RFBNN model during the rice-growing stage and the mature stage are 0.6418 (%), 0.5399 (%), 0.0652 (%), and 0.3540 (%), 0.1566 (%), 0.0214 (%) respectively, the predicted value of the model fits well with the actual value. Finally, the model may be used to give the best foundation for achieving exact fertilization control by continuously monitoring the nitrogen nutrition status of rice. In addition, at the growing stage, the RBFNN model shows better results compared to both GRL and GRM, in which MAE is reduced by 0.2233% and 0.2785%, respectively.
Trend towards Helmet Usage and the Behavior of Riders While Wearing Helmets
Authors: Abid Malik Muneeb , Bano Shehar , Kumar Ashok , Iqbal Muhammad , Shahid Muhammad Laiq Ur Rahman , Javed Ahsan , Tariq Muhammad Atiq Ur Rehman
Published: November 2022

Nowadays, it is relatively common to follow traffic rules, such as wearing a helmet and fastening seat belts, but accidents are increasing daily. Concerned with these traffic safety issues, this study focuses on the psychology of bike riders. First, a brief questionnaire is prepared by filtering some significant traffic safety factors. For effective results and analysis, a questionnaire survey (i.e., interviews) is conducted across different road junctions in Sargodha, Pakistan, with the assistance of traffic police. The data is analyzed through a multiple regression analysis, forming a different model for effective outcomes. A risk compensation hypothesis theory is considered; based on the questionnaire designed and the input received from participants, three models are developed with significant variables. The first two models evaluate the physical impact of helmets on riders/cyclists, while the third observes changes (in terms of obeying traffic laws) in behavior when wearing a helmet. It has been observed that cyclists wearing helmets may follow zigzag patterns while wearing helmets, which may cause accidents. Moreover, it has been observed that cyclists wearing helmets may be more responsible regarding traffic rules. These problems should be considered in creating effective traffic safety campaigns and policy making.
Most Relevant Sustainability Criteria for Urban Infrastructure Projects—AHP Analysis for the Gulf States
Authors: Khan Kamran , Depczyńska Katarzyna Szopik , Dembińska Izabela , Ioppolo Giuseppe
Published: November 2022

Infrastructure projects require lifecycle-based assessment, considering the interests of multiple stakeholders concerning the three pillars of sustainability. There has been a heightened curiosity in employing sustainability indicators for gauging the impacts of developmental projects. Even though the literature is abundant on sustainability assessment methods, there is no proper one for the assessment of urban infrastructure projects in the context of Gulf states. Thus, our research intends to fill in this research gap and recommend an incorporated, hierarchically coordinated approach of sustainability indicators to be employed for the sustainability assessment of urban infrastructure development projects. This aim is achieved through a questionnaire survey, by identifying the sustainability indicators related to the infrastructure projects for the cities, in the context of Gulf states. The survey uses the criteria; “Important”, “Practicality”, “Reliability”, and “Relevance” to assess those indicators. Based on expert opinions, the weights of the indicators are approximated through the analytical hierarchy process (AHP) method. Thus, the study proposes an innovative hierarchically defined structure of sustainability indicators fitting for the Gulf context. Further, it informs urban planners and policymakers, particularly in the Gulf states, about the shift in the direction of sustainability of urban infrastructure systems.
Inheritance Patterns under Cultural Ecology Theory for the Sustainable Development of Traditional Handicrafts
Authors: Yang Nan , Zang Xiaoge , Chen Cong
Published: November 2022

Culture is the fourth pillar of sustainable development. The protection of intangible cultural heritage is an important way to safeguard the transmission of intangible heritage across generations. With the help of cultural ecology theory, this paper compares cases of inheritance and development in two different handicrafts: Bai tie-dyeing and Beijing carved lacquer. The results show that under the influence of different cultural ecologies, the family inheritance pattern of Bai tie-dyeing, and the master–apprentice inheritance pattern of Beijing carved lacquer have undergone qualitative changes in modern society. This paper puts forward the distinction between representative inheritance and group inheritance and suggests a protection mechanism accordingly. This paper further suggests that a modern mentoring model should be promoted as the inheritance pattern to further aid handicraft development, and a clear division of economic interests is also appointed to apply with the premiumization development and mass development.
Natural Resources and the Tipping Points of Political Power—A Research Agenda
Authors: Dobner Petra , Finkeldey Jasper
Published: November 2022

A general assumption concerning the relationship between natural recourses and politics is that the degradation of natural resources will destabilize political regimes causing civil wars, mass migration, or the erosion of democratic systems. Despite individual attempts to explore the relationship between different political regimes and various resources in more detail, a systematic explanation of the complex relationship between natural resources and political regimes is still lacking. In this paper, we suggest a research agenda in order to better understand their interconnectedness. We start by exploring the respective potentials of Earth system science (ESS) and the logic of Earth spheres. We argue that the notion of distinct Earth spheres has its merits but also significant disadvantages. We then propose to concentrate on a resource perspective as the more expedient starting point for investigating the nature of the interconnection between the ecosphere and humans. We refine our argument by suggesting to also reflect on the socioeconomic properties of natural resources in order to estimate their implications for political regime stability. Finally, this paper proposes three different political regime types and how each organizes its relationship vis-a-vis natural resources, especially regarding sustainable resource use.
The Impact of Pyrolysis Temperature on Biochar Properties and Its Effects on Soil Hydrological Properties
Authors: Ghorbani Mohammad , Amirahmadi Elnaz , Neugschwandtner Reinhard W. , Konvalina Petr , Kopecký Marek , Moudrý Jan , Perná Kristýna , Murindangabo Yves Theoneste
Published: November 2022

Soil structure is a crucial constituent influencing soil organic richness, rooting systems, and soil moisture conservation. Adding biochar to the soil, which directly affects aggregation, can significantly alter the soil moisture status. The extent of this impact is influenced by the temperature at which pyrolysis biochar is formed. The impact of biochar derived from wheat straw made at 350, 450, 550, and 650 °C (B350, B450, B550, B650) on soil aggregation and moisture retention was evaluated in this study. Based on the results, B550 had the largest mean weight diameter, most water-stable aggregates, and highest available water content compared to the control, with increases of 235%, 39% and 166% compared to the control. On the other hand, B350 was identified as the weakest treatment, with no significant difference from the control. Using B550 and B650 significantly reduced the soil bulk density by 13% and 12% compared to the control. Therefore, the formation of micro-aggregates, the development of soil porosity, and the subsequent increase in soil available water are unavoidable during the addition of B550. The change in the hydrophilic character of biochar and the attainment of an optimal oxygen/carbon ratio with pyrolysis degradations is a critical factor in soil hydrology issues.
The Effect of the Artificial Reef on the Structure and Function of Sediment Bacterial Community
Authors: Tong Fei , Chen Guobao , Feng Xue , Liu Yan , Chen Pimao
Published: November 2022

The bacterial community in sediment is sensitive to artificial disturbance, and they respond differently to human disturbance, such as changing the nutrient cycling and energy flow in marine ecosystems. However, little is known about the dynamics and distribution of bacterial community structures in marine sediments and potential biogeochemical functions during the long-time succession in marine ranching. In the present study, we compared the dynamics of the bacterial composition and potential biogeochemical functions of sediment to ten years (TR) and one-year new artificial reef (NR) areas using metagenomic next-generation sequencing technology. Results revealed that NR reduces the Pielou’s evenness and Shannon index. Similarly, nonmetric multidimensional scaling showed that the beta diversity of sediment bacterial communities in NR significantly differed between TR and non-artificial reef areas. Previously, TR biomarkers were frequently associated with organic matter decomposing and assimilating in the organically enriched sediments (i.e., Acinetobacter). The soluble reactive phosphate (SRP) and total phosphorus (TP) concentrations were thought to be the primary driving forces in shaping the microbial community in sediment. Pseudomonas, Lactobacillus, and Ralstonia have a significant positive correlation with SRP, TP, nitrate, and TN, but a negative association with pH, Salinity, Hg, and depth. NR was found to have more negative correlation nodes, indicating that taxa face more competition or predation press. Vibrio served as the module-hubs in the network in all areas. In addition, chemoheterotrophy, aerobic chemoheterotrophy, and fermentation were the three most prominent functions of the three areas, accounting for 59.96% of the relative abundance of the functional annotation. Different bacteria in sediments may change the amount of biogeochemical cycle in the marine ranching ecosystem. These findings can increase our understanding of the succession of the microecosystem for the marine ranching sedimentary environment by revealing how artificial reefs affect the indigenous sediment bacterial community and their responses to environmental variation.
Anthropogenic Land Use Change and Adoption of Climate Smart Agriculture in Sub-Saharan Africa
Authors: Tione Sarah Ephrida , Nampanzira Dorothy , Nalule Gloria , Kashongwe Olivier , Katengeza Samson Pilanazo
Published: November 2022

Compelling evidence in Sub-Saharan Africa (SSA) shows that Climate-Smart Agriculture (CSA) has a positive impact on agricultural productivity. However, the uptake of CSA remains low, which is related to anthropogenic, or human-related, decisions about CSA and agricultural land use. This paper assesses households’ decisions to allocate agricultural land to CSA technologies across space and over time. We use the state-contingent theory, mixed methods, and mixed data sources. While agricultural land is increasing, forest land is decreasing across countries in SSA. The results show that household decisions to use CSA and the extent of agricultural land allocation to CSA remain low with a negative trend over time in SSA. Owned land and accessing land through rental markets are positively associated with allocating land to CSA technologies, particularly where land pressure is high. Regarding adaptation, experiencing rainfall shocks is significantly associated with anthropogenic land allocation to CSA technologies. The country policy assessment further supports the need to scale up CSA practices for adaptation, food security, and mitigation. Therefore, scaling up CSA in SSA will require that agriculture-related policies promote land tenure security and land markets while promoting climate-smart farming for food security, adaptation, and mitigation.
Empirical Assessments of the Determinants of Construction Megaprojects’ Success: Evidence from China
Authors: Wang Ting , Owusu Emmanuel Kingsford , He Qinghua , Tian Zidan , Wu Dong
Published: November 2022

This study empirically examines the success determinants that instigate or contribute to project success and empirically evaluates the levels of importance at which the ascertained determinants contribute to project success in China. Based on a literature review and interviews, a questionnaire survey used to gather a total of 129 valid responses was gathered from megaproject experts who have worked on at least a billion RMB (approximately USD 0.14 billion) worth of projects in different provinces. Moreover, factor analysis was adopted to explore and identify the underlying relationships among the identified critical success factors. The top three success factors were adequate communication and coordination among related parties, cooperation and strong support from local governments and partnering/relationships with key stakeholders. Six constructs were developed from thirty-five success variables using the Factor Analysis tool, with the topmost-ranked construct being organisational-related factors. This paper can provide valuable insights and a holistic critical success factor framework concerning construction megaproject management. Particularly, it contributes to a deepened understanding of the megaproject’s success factors and helps project stakeholders to manage megaprojects more effectively. Additionally, this study could serve as the premise for further empirical research on determining factors of megaproject success in different contexts.
Optimal Allocation of Fast Charging Station for Integrated Electric-Transportation System Using Multi-Objective Approach
Authors: Mohanty Ajit Kumar , Suresh Babu Perli , Salkuti Surender Reddy
Published: November 2022

The usage of Electric Vehicles (EVs) for transportation is expected to continue growing, which opens up new possibilities for creating new smart grids. It offers a large-scale penetration of Fast Charging Stations (FCE) in a local utility network. A severe voltage fluctuation and increased active power loss might result from the inappropriate placement of the FCE as it penetrates the Distribution System (DST). This paper proposes a multi-objective optimisation for the simultaneous optimal allocation of FCEs, Distributed Generators (DGs), and Shunted Capacitors (SCs). The proposed Pareto dominance-based hybrid methodology incorporates the advantages of the Grey Wolf Optimiser and Particle Swarm Optimisation algorithm to minimise the objectives on 118 bus radial distribution systems. The proposed method outperforms some other existing algorithms in terms of minimising (a) active power loss costs of the distribution system, (b) voltage deviations, (c) FCE development costs, (d) EV energy consumption costs, and (e) DG costs, as well as satisfying the number of FCEs and EVs in all zones based on transportation and the electrical network. The simulation results demonstrate that the simultaneous deployment technique yields better outcomes, such as the active power loss costs of the distribution system being reduced to 53.21%, voltage deviations being reduced to 68.99%, FCE development costs being reduced to 22.56%, EV energy consumption costs being reduced to 19.8%, and DG costs being reduced to 5.1%.
A Machine Learning Method for the Risk Prediction of Casing Damage and Its Application in Waterflooding
Authors: Zhang Jiqun , Wu Li , Jia Deli , Wang Liming , Chang Junhua , Li Xianing , Cui Lining , Shi Bingbo
Published: November 2022

During the development of oilfields, casings in long-term service tend to be damaged to different degrees, leading to poor development of the oilfields, ineffective water circulation, and wasted water resources. In this paper, we propose a data-based method for predicting casing failure risk at both well and well-layer granularity and illustrate the application of the method to GX Block in an eastern oilfield of China. We first quantify the main control factors of casing damage by adopting the F-test and mutual information, such as that of the completion days, oil rate, and wall thickness. We then select the top 30 factors to construct the probability prediction model separately using seven algorithms, namely the decision tree, random forest, AdaBoost, gradient boosting decision tree, XGBoost, LightGBM, and backpropagation neural network algorithms. In terms of five evaluation indicators, namely the accuracy, precision, recall, F1-score, and area under the curve, we find that the LightGBM algorithm yields the best results at both granularities. The accuracy of the prediction model based on the preferred algorithm reaches 87.29% and 92.45% at well and well-layer granularity, respectively.
Masonry in the Context of Sustainable Buildings: A Review of the Brick Role in Architecture
Authors: Almssad Asaad , Almusaed Amjad , Homod Raad Z.
Published: November 2022

The process of combining various parts to create a structure is called building. The most effective and significant component of any construction is masonry. The Colosseum, buildings from ancient Greece and Rome, Central American buildings, and Mycenaean structures all used this material as one of their primary building elements. The oldest form is dry masonry of irregularly shaped stones. The ecological qualities of masonry, as a restorative material with a low impact on the environment, as well as the environmental control capacity of the massive wall, bring masonry back to attention as a suitable material for sustainable building in the context of current concerns for sustainable architecture. This article takes the form of a review of the journey of masonry as the primary construction material—from prehistoric structures to modern-day edifices. This article will go through the fundamentals of masonry construction to support its usage in structures throughout history and in many architectural styles, as a crucial representation of human construction in architectural history. This article aims to create a historical review, presenting masonry as an essential building material and assessing its role in the history of building materials.
Consumer Patterns of Sustainable Clothing Based on Theory of Reasoned Action: Evidence from Ecuador
Authors: Leclercq-Machado Luigi , Alvarez-Risco Aldo , García-Ibarra Verónica , Esquerre-Botton Sharon , Morales-Ríos Flavio , Anderson-Seminario Maria de las Mercedes , Del-Aguila-Arcentales Shyla , Davies Neal M. , Yáñez Jaime A.
Published: November 2022

Corporations need to understand the factors that influence purchase intention. The current study aimed to understand sustainable clothing patterns in Ecuador. A total of 343 Ecuadorian consumers completed an online survey; the results were analyzed with partial least squares structural equation modeling (PLS-SEM). As the outcome, attitude was predicted by perceived environmental knowledge (PEK) and environmental concern (EC). PEK and EC are positively correlated to attitudes towards purchasing sustainable clothing. Additionally, attitude mediated the relationship between these two variables and purchase intention. As measured by PEK, attitude is the most critical factor in determining purchase intention, based on importance performance map analysis (IPMA). The research findings may support firms’ marketing and selling strategies to demonstrate that their brands are environmentally green and generate greater consumer interest in current and future customers. The novelty of these findings is supported by the partial least squares structural equation modeling (PLS-SEM) technique results.
Artificial Neural Networks for Sustainable Development of the Construction Industry
Authors: Ahmed Mohd. , AlQadhi Saeed , Mallick Javed , Kahla Nabil Ben , Le Hoang Anh , Singh Chander Kumar , Hang Hoang Thi
Published: November 2022

Artificial Neural Networks (ANNs), the most popular and widely used Artificial Intelligence (AI) technology due to their proven accuracy and efficiency in control, estimation, optimization, decision making, forecasting, and many other applications, can be employed to achieve faster sustainable development of construction industry. The study presents state-of-the-art applications of ANNs to promote sustainability in the construction industry under three aspects of sustainable development, namely, environmental, economic, and social. The environmental aspect surveys ANNs’ applications in sustainable construction materials, energy management, material testing and control, infrastructure analysis and design, sustainable construction management, infrastructure functional performance, and sustainable maintenance management. The economic aspect covers financial management and construction productivity through ANN applications. The social aspect reviews society and human values and health and safety issues in the construction industry. The study demonstrates the wide range of interdisciplinary applications of ANN methods to support the sustainable development of the construction industry. It can be concluded that a holistic research approach with comprehensive input data from various phases of construction and segments of the construction industry is needed for the sustainable development of the construction industry. Further research is certainly needed to reduce the dependency of ANN applications on the input dataset. Research is also needed to apply ANNs in construction management, life cycle assessment of construction projects, and social aspects in relation to sustainability concerns of the construction industry.