bluuebunny/crossref_metadata_2025 huggingface dataset:
From Data to Insights: A Bibliometric Assessment of Agent-Based Modeling Applications in Transportation
Authors: Domenteanu Adrian , Delcea Camelia , Chiriță Nora , Ioanăș Corina
Published: November 2023

This paper presents a bibliometric analysis within the research domain dedicated to the utilization of agent-based modeling (ABM) in the field of transportation. By employing specific keywords related to both agent-based modeling and transportation, we have identified and extracted 1016 scholarly papers from the ISI Web of Science database, spanning the period from 2002 to 2023. Through the application of bibliometric methods, we have systematically examined key contributors, affiliations of academic institutions, influential publications, and renowned journals within this domain. Our analysis reveals a consistent and robust growth in scholarly interest pertaining to agent-based modeling in the field of transportation throughout the considered period. Notably, within approximately four decades of ABM’s application in transportation, a distinct upward trajectory began in 2008, culminating in the year 2021. The entire considered period witnessed a remarkable surge in paper production, characterized by an annual growth rate of 21.67%. Furthermore, employing an n-gram analysis, we have delineated and discussed the principal areas within transportation that have progressively benefited from the advancements in agent-based modeling. Prominently, the domains of air transport and road transport have exhibited substantial development over time, while the implications of climate change have emerged as a persistent concern throughout the entire study period.
Personalized Privacy Protection Based on Space Grid in Mobile Crowdsensing
Authors: Gao Hengfei , Zhang Ziqing , Zhao Hongwei
Published: November 2023

The rapid proliferation of handheld intelligent devices and the advent of 5G technology have brought about convenient and fast services for people. In perception-oriented application services, participating users will upload sensitive mobile data in order to obtain benefits. While devising privacy protection strategies to ensure data security, it is crucial to accomplish task perception related to data collection to the fullest extent possible. To address this challenge, this paper proposes a personalized data privacy protection algorithm based on an adaptive dynamic adjustment grid and the minimum wage task allocation strategy. According to the different levels of users’ needs for privacy protection, combined with the privacy budget allocation strategy, we design a different-level differential privacy protection mechanism and consider the reward mechanism in task allocation to balance the effectiveness and security of the location data uploaded by users. Experiments show that the strategy proposed in this paper can not only protect the data but also enable users to freely choose the level of privacy protection.
Analysis of the Development Status of eLoran Time Service System in China
Authors: Yang Chaozhong , Li Shifeng , Hu Zhaopeng
Published: November 2023

This article introduces the eLoran timing system principle, the characteristics of the eLoran and GNSS systems, and the current development status of eLoran in China. This article elaborates on the significance and scale of this high-precision ground time service system currently being constructed in China and describes the technical methods used in the high-precision ground time service system. Finally, it analyzes and elaborates on the signal and data channels of the eLoran time service system.
Experimental Investigation on the Destruction Features and Acoustic Characteristics of a Brittle Rock Sample Containing Both 2D and 3D Preset Flaws
Authors: Luo Tao , Chen Siyu , Li Binglei
Published: November 2023

Original fracture structures always present discontinuity in the real rock mass, and many invisible fractures hide inside the rock mass, which may cause serious engineering safety issues. To mimic the true 3D fracture structures through the experimental method, the gypsum rock-like samples containing both 2D through-type and 3D internal-type preset flaws are prepared, and multiple sets of inclination angles of the twin parallel flaws are set in the test. By applying the AE and DIC monitoring technologies during the uniaxial compression tests, the main results are as follows: (1) The flaw inclination angle presents a direct influence on the surface cracks distribution, maximum principal strain field, and the density of secondary failure in the middle rock; (2) AE events initially distribute around the internal 3D preset flaw, while the gradient inclination angle shows a slight impact on the events’ location before reaching the UCS status of samples; (3) mutations in b-values and S values can serve as evidence for predicting local damage, and the final failures quickly form at various scales and energy levels; (4) when the statistical analysis grid is divided sufficiently, the data window width and moving step length have little impact on the evaluation results, while the recommended bin width of event magnitude is 0.5 or 1.0.
High-Capacity Reversible Data Hiding in Encrypted Images Based on Pixel Prediction and QuadTree Decomposition
Authors: Alqahtani Muhannad , Masmoudi Atef
Published: November 2023

Over the past few years, a considerable number of researchers have shown great interest in reversible data hiding for encrypted images (RDHEI). One popular category among various RDHEI methods is the reserving room before encryption (RRBE) approach, which leverages data redundancy in the original image before encryption to create space for data hiding and to achieve high embedding rates (ERs). This paper introduces an RRBE-based RDHEI method that employs pixel prediction, quadtree decomposition, and bit plane reordering to provide high embedding capacity and error-free reversibility. Initially, the content owner predicts the error image using a prediction method, followed by mapping it to a new error image with positive pixel values and a compressed binary label map is generated for overhead pixels. Subsequently, quadtree decomposition is applied to each bit plane of the mapped prediction error image to identify homogeneous blocks, which are then reordered to create room for data embedding. After generating the encrypted image with the encryption key, the data hider employs the data hiding key to embed the data based on the auxiliary information added to each embeddable bit plane’s beginning. Finally, the receiver is able to retrieve the secret message without any error, decrypt the image, and restore it without any loss or distortion. The experimental results demonstrate that the proposed RDHEI method achieves significantly higher ERs than previous competitors, with an average ER exceeding 3.6 bpp on the BOSSbase and BOWS-2 datasets.
Composing Multiple Online Exams: The Bees Algorithm Solution
Authors: Hosny Manar , Hayel Rafa , Altwaijry Najwa
Published: November 2023

Online education has gained increasing importance in recent years due to its flexibility and ability to cater to a diverse range of learners. The COVID-19 pandemic has further emphasized the significance of online education as a means to ensure continuous learning during crisis situations. With the disruption of traditional in-person exams, online examinations have become the new norm for universities worldwide. Among the popular formats for online tests are multiple-choice questions, which are drawn from a large question bank. However, creating online tests often involves meeting specific requirements, such as minimizing the overlap between exams, grouping related questions, and determining the desired difficulty level. The manual selection of questions from a sizable question bank while adhering to numerous constraints can be a laborious task. Additionally, traditional search methods that evaluate all possible solutions are impractical and time-consuming for such a complex problem. Consequently, approximate methods like metaheuristics are commonly employed to achieve satisfactory solutions within a reasonable timeframe. This research proposes the application of the Bees Algorithm (BA), a popular metaheuristic algorithm, to address the problem of generating online exams. The proposed solution entails creating multiple exam forms that align with the desired difficulty level specified by the educator, while considering other identified constraints. Through extensive testing and comparison with four rival methods, the BA demonstrates superior performance in achieving the primary objective of matching the desired difficulty level in most test cases, as required by the educator. Furthermore, the algorithm exhibits robustness, indicated by minimal standard deviation across all experiments, which suggests its ability to generalize, adapt, and be practically applicable in real-world scenarios. However, the algorithm does have limitations related to the number of successful solutions and the achieved overlap percentage. These limitations have also been thoroughly discussed and highlighted in this research.
Studying Corrosion Failure Prediction Models and Methods for Submarine Oil and Gas Transport Pipelines
Authors: Cui Junguo , Wu Yuyin , Lu Zhongqi , Xiao Wensheng
Published: November 2023

To predict the corrosion failure of carbon steel oil and gas pipelines more accurately, a new corrosion failure prediction model for submarine oil and gas transport pipelines was constructed. A corrosion failure prediction management system was also developed based on the constructed model. To construct the model, corrosion experiments were carried out to analyze the influences of temperature, partial pressure of CO2, pH value, and flow rate acting on the corrosion rate. Based on the analysis results and the corrosion experiment data, a new corrosion failure prediction model containing the time and flow rate for oil and gas pipelines was constructed. The model is based on the existing corrosion prediction model and has a determination coefficient, R2, of 0.9573, which indicates good prediction accuracy. A machine learning prediction model was also used to predict, and the prediction results are compared with that of the proposed model, which further verifies the accuracy and feasibility of the proposed model. A corrosion failure prediction management system for carbon steel oil and gas pipelines was developed based on the constructed model, which makes corrosion failure prediction more convenient and faster and provides a reference for the accurate prediction and efficient control of oil and gas pipeline corrosion failure.
Comparison of the Performance of Convolutional Neural Networks and Vision Transformer-Based Systems for Automated Glaucoma Detection with Eye Fundus Images
Authors: Alayón Silvia , Hernández Jorge , Fumero Francisco J. , Sigut Jose F. , Díaz-Alemán Tinguaro
Published: November 2023

Glaucoma, a disease that damages the optic nerve, is the leading cause of irreversible blindness worldwide. The early detection of glaucoma is a challenge, which in recent years has driven the study and application of Deep Learning (DL) techniques in the automatic classification of eye fundus images. Among these intelligent systems, Convolutional Neural Networks (CNNs) stand out, although alternatives have recently appeared, such as Vision Transformers (ViTs) or hybrid systems, which are also highly efficient in image processing. The question that arises in the face of so many emerging methods is whether all these new techniques are really more efficient for the problem of glaucoma diagnosis than the CNNs that have been used so far. In this article, we present a comprehensive comparative study of all these DL models in glaucoma detection, with the aim of elucidating which strategies are significantly better. Our main conclusion is that there are no significant differences between the efficiency of both DL strategies for the medical diagnostic problem addressed.
Proposal and Evaluation of a Robot to Improve the Cognitive Abilities of Novice Baseball Spectators Using a Method for Selecting Utterances Based on the Game Situation
Authors: Mamada Keita , Miyamoto Tomoki , Katagami Daisuke
Published: November 2023

Herein, an engineering method is developed to improve spectators’ sports-watching abilities. We present an interactive robot that supports the cognitive abilities of baseball novices in sports spectating. The robot watches a game with a person and utters words applicable to the game situation. We propose two methods to support cognitive watching: five categories of utterances (confirmation, information, prediction, emotion, and evaluation) and utterance rules for player participation and game scenes. We also propose a method for generating utterances for each category. To evaluate the generated utterances, we conducted an experiment whereby spectators watched baseball footage with the robot. The results of the experiment showed that the robot’s utterances could support the cognitive ability sub-factor of individual game intelligence, specifically “Spectating while knowing the player’s strengths.” In addition, the feeling of heaviness that occurs when watching alone could potentially be reduced by watching with a robot. This study is the first to attempt to support and improve spectators’ abilities to watch sports using the human–robot interaction approach. We anticipate that this approach will be used in the future to build a relationship (increase intimacy) with an agent (robot) and to support and improve cognitive abilities regardless of the type of sport.
Correlations in Compositional Data without Log Transformations
Authors: Monich Yury V. , Nechipurenko Yury D.
Published: November 2023

This article proposes a method for determining the p-value of correlations in compositional data, i.e., those data that arise as a result of dividing original values by their sum. Data organized in this way are typical for many fields of knowledge, but there is still no consensus on methods for interpreting correlations in such data. In the second decade of the new millennium, almost all newly emerging methods for solving this problem have become based on the log transformation of data. In the method proposed here, there are no log transformations. We return to the early stages of attempting to solve the problem and rely on negative shifts in correlations in the multinomial distribution. In modeling the data, we use a hybrid method that combines the hypergeometric distribution with the distribution of any other law. During our work on the calculation method, we found that the number of degrees of freedom in compositional data measures discretely only when all normalizing sums are equal and that it decreases when the sums are not equal, becoming a continuously varying quantity. Estimation of the number of degrees of freedom and the strength of its influence on the magnitude of the shift in the distribution of correlation coefficients is the basis of the proposed method.
Synthesis of sEMG Signals for Hand Gestures Using a 1DDCGAN
Authors: Gouda Mohamed Amin , Hong Wang , Jiang Daqi , Feng Naishi , Zhou Bin , Li Ziyang
Published: November 2023

The emergence of modern prosthetics controlled by bio-signals has been facilitated by AI and microchip technology innovations. AI algorithms are trained using sEMG produced by muscles during contractions. The data acquisition procedure may result in discomfort and fatigue, particularly for amputees. Furthermore, prosthetic companies restrict sEMG signal exchange, limiting data-driven research and reproducibility. GANs present a viable solution to the aforementioned concerns. GANs can generate high-quality sEMG, which can be utilised for data augmentation, decrease the training time required by prosthetic users, enhance classification accuracy and ensure research reproducibility. This research proposes the utilisation of a one-dimensional deep convolutional GAN (1DDCGAN) to generate the sEMG of hand gestures. This approach involves the incorporation of dynamic time wrapping, fast Fourier transform and wavelets as discriminator inputs. Two datasets were utilised to validate the methodology, where five windows and increments were utilised to extract features to evaluate the synthesised sEMG quality. In addition to the traditional classification and augmentation metrics, two novel metrics—the Mantel test and the classifier two-sample test—were used for evaluation. The 1DDCGAN preserved the inter-feature correlations and generated high-quality signals, which resembled the original data. Additionally, the classification accuracy improved by an average of 1.21–5%.
Comprehensive Exploration of the Growth and Lipid Synthesis Phases of T. oleaginosus Cultures Implementing Design of Experiments and Response Surface Methodology
Authors: Parisis Vasileios , Tsave Olga , Papanikolaou Christina , Pantazopoulou Erasmia , Chatzidoukas Christos
Published: November 2023

Trichosporon oleaginosus is an unconventional oleaginous yeast distinguished by its remarkable capacity to accumulate lipids in excess of 70% of its dry weight, particularly when cultivated in nitrogen-restricted conditions with ample carbon sources. A pivotal question that arises pertains to the nutrient dynamics in the culture medium, which give rise to both the excessive lipid content and corresponding lipid concentration. While previous research has predominantly focused on evaluating the impact of the initial carbon-to-nitrogen (C/N) ratio on lipid production, the precise critical thresholds of glucose and ammonium sulfate ((NH4)2SO4) at which growth and intracellular lipid production are either stimulated or impeded remain inadequately defined. This study employs an experimental design and response surface methodology to investigate the complex mechanism of lipid accumulation and its interaction with cellular growth. Application of the aforementioned methodologies resulted in the production of 10.6 g/L of microbial oil in batch cultures under conditions that correspond to a C/N ratio of 76. However, the primary objective is to generate knowledge to facilitate the development of efficient fed-batch cultivation strategies that optimize lipid production exclusively employing inorganic nitrogen sources by finely adjusting carbon and nitrogen levels. The intricate interaction between these levels is comprehensively addressed in the present study, while it is additionally revealed that as glucose levels rise within a non-inhibitory range, lipid-free biomass production decreases while lipid accumulation simultaneously increases. These findings set the stage for further exploration and the potential development of two-stage cultivation approaches, aiming to fully decouple growth and lipid production. This advancement holds the promise of bringing microbial oil production closer to commercial viability.
Simulating Interclonal Interactions in Diffuse Large B-Cell Lymphoma
Authors: Ganesh Siddarth R. , Roth Charles M. , Parekkadan Biju
Published: November 2023

Diffuse large B-cell lymphoma (DLBCL) is one of the most common types of cancers, accounting for 37% of B-cell tumor cases globally. DLBCL is known to be a heterogeneous disease, resulting in variable clinical presentations and the development of drug resistance. One underexplored aspect of drug resistance is the evolving dynamics between parental and drug-resistant clones within the same microenvironment. In this work, the effects of interclonal interactions between two cell populations—one sensitive to treatment and the other resistant to treatment—on tumor growth behaviors were explored through a mathematical model. In vitro cultures of mixed DLBCL populations demonstrated cooperative interactions and revealed the need for modifying the model to account for complex interactions. Multiple best-fit models derived from in vitro data indicated a difference in steady-state behaviors based on therapy administrations in simulations. The model and methods may serve as a tool for understanding the behaviors of heterogeneous tumors and identifying the optimal therapeutic regimen to eliminate cancer cell populations using computer-guided simulations.
Local Crystallographic Texture of a Nummulite (Foraminifera) Test from the Eocene Deposits of the Crimea Peninsula
Authors: Pakhnevich Alexey , Nikolayev Dmitry , Lychagina Tatiana
Published: November 2023

Unicellular protozoa form calcium carbonate tests. It is important to understand the features and mechanisms of its formation. This may shed light on the processes of shell formation in metazoans. One of the most important characteristics of the Protozoa carbonate test is the degree of crystal ordering that can be described by crystallographic texture. The crystallographic texture data of calcite in the foraminifera Nummulites distans (Deshayes) test from the Eocene deposits (Cenozoic, Paleogene) of the Crimea Peninsula are obtained using X-ray diffraction. A very strict orientation of the crystals is revealed. The calcite texture sharpness is several times greater than in the shells of the bivalve mollusk Placuna placenta (Linnaeus), measured by the same method. It also exceeds the crystallographic texture and sharpness of the same mineral in the shells of the bivalves of Mytilus galloprovincialis (Lamarck), studied by neutron diffraction. It is concluded that a high level of control during test formation is already characteristic of protozoa. Studying the processes involved in the formation of a very sharp crystallographic texture can become an important direction for creating nature-like materials with desired properties.
RETRACTED: Maifata et al. Role of Serum and Urine Biomarkers (PLA2R and THSD7A) in Diagnosis, Monitoring and Prognostication of Primary Membranous Glomerulonephritis. Biomolecules 2020, 10, 319
Authors:   Biomolecules Editorial Office
Published: November 2023

It has come to our attention that an error occurred in the “Methods and Materials” section of this manuscript [...]
Hydrogen Inhalation Reduces Lung Inflammation and Blood Pressure in the Experimental Model of Pulmonary Hypertension in Rats
Authors: Kuropatkina Tatyana , Atiakshin Dmitrii , Sychev Fedor , Artemieva Marina , Samoilenko Tatyana , Gerasimova Olga , Shishkina Viktoriya , Gufranov Khaydar , Medvedeva Natalia , LeBaron Tyler W. , Medvedev Oleg
Published: November 2023

Hydrogen has been shown to exhibit selective antioxidant properties against hydroxyl radicals, and exerts antioxidant and anti-inflammatory effects. The monocrotaline-induced model of pulmonary hypertension is suitable for studying substances with antioxidant activity because oxidative stress is induced by monocrotaline. On day 1, male Wistar rats were subcutaneously injected with a water–alcohol solution of monocrotaline or a control with an only water–alcohol solution. One group of monocrotaline-injected animals was placed in a plastic box that was constantly ventilated with atmospheric air containing 4% of molecular hydrogen, and the two groups of rats, injected with monocrotaline or vehicle, were placed in boxes ventilated with atmospheric air. After 21 days, hemodynamic parameters were measured under urethane narcosis. The results showed that, although hydrogen inhalation had no effect on the main markers of pulmonary hypertension induced by monocrotaline injection, there was a reduction in systemic blood pressure due to its systolic component, and a decrease in TGF-β expression, as well as a reduction in tryptase-containing mast cells.
Natural Compounds of Salvia L. Genus and Molecular Mechanism of Their Biological Activity
Authors: Zhumaliyeva Gaziza , Zhussupova Aizhan , Zhusupova Galiya E. , Błońska-Sikora Ewelina , Cerreto Antonella , Omirbekova Nargul , Zhunusbayeva Zhazira , Gemejiyeva Nadezhda , Ramazanova Madina , Wrzosek Małgorzata , Ross Samir A.
Published: November 2023

The study of medicinal plants is important, as they are the natural reserve of potent biologically active compounds. With wide use in traditional medicine and the inclusion of several species (as parts and as a whole plant) in pharmacopeia, species from the genus Salvia L. are known for the broad spectrum of their biological activities. Studies suggest that these plants possess antioxidant, anti-inflammatory, antinociceptive, anticancer, antimicrobial, antidiabetic, antiangiogenic, hepatoprotective, cognitive and memory-enhancing effects. Phenolic acids, terpenoids and flavonoids are important phytochemicals, which are primarily responsible for the medicinal activity of Salvia L. This review collects and summarizes currently available data on the pharmacological properties of sage, outlining its principal physiologically active components, and it explores the molecular mechanism of their biological activity. Particular attention was given to the species commonly found in Kazakhstan, especially to Salvia trautvetteri Regel, which is native to this country.
VEGFR2 Expression Correlates with Postnatal Development of Brain Arteriovenous Malformations in a Mouse Model of Type I Hereditary Hemorrhagic Telangiectasia
Authors: Han Chul , Nguyen Candice L. , Scherschinski Lea , Schriber Tyler D. , Arthur Helen M. , Lawton Michael T. , Oh Suk Paul
Published: November 2023

Brain arteriovenous malformations (BAVMs) are a critical concern in hereditary hemorrhagic telangiectasia (HHT) patients, carrying the risk of life-threatening intracranial hemorrhage. While traditionally seen as congenital, the debate continues due to documented de novo cases. Our primary goal was to identify the precise postnatal window in which deletion of the HHT gene Endoglin (Eng) triggers BAVM development. We employed SclCreER(+);Eng2f/2f mice, enabling timed Eng gene deletion in endothelial cells via tamoxifen. Tamoxifen was given during four postnatal periods: P1–3, P8–10, P15–17, and P22–24. BAVM development was assessed at 2–3 months using latex dye perfusion. We examined the angiogenic activity by assessing vascular endothelial growth factor receptor 2 (VEGFR2) expression via Western blotting and Flk1-LacZ reporter mice. Longitudinal magnetic resonance angiography (MRA) was conducted up to 9 months. BAVMs emerged in 88% (P1–3), 86% (P8–10), and 55% (P15–17) of cases, with varying localization. Notably, the P22–24 group did not develop BAVMs but exhibited skin AVMs. VEGFR2 expression peaked in the initial 2 postnatal weeks, coinciding with BAVM onset. These findings support the “second hit” theory, highlighting the role of early postnatal angiogenesis in initiating BAVM development in HHT type I mice.
Preclinical Evidence for the Role of the Yin/Yang Angiotensin System Components in Autism Spectrum Disorder: A Therapeutic Target of Astaxanthin
Authors: Samra Ayat I. , Kamel Ahmed S. , Abdallah Dalaal M. , El Fattah Mai A. Abd , Ahmed Kawkab A. , El-Abhar Hanan S.
Published: November 2023

Autism spectrum disorder (ASD) prevalence is emerging with an unclear etiology, hindering effective therapeutic interventions. Recent studies suggest potential renin–angiotensin system (RAS) alterations in different neurological pathologies. However, its implications in ASD are unexplored. This research fulfills the critical gap by investigating dual arms of RAS and their interplay with Notch signaling in ASD, using a valproic acid (VPA) model and assessing astaxanthin’s (AST) modulatory impacts. Experimentally, male pups from pregnant rats receiving either saline or VPA on gestation day 12.5 were divided into control and VPA groups, with subsequent AST treatment in a subset (postnatal days 34–58). Behavioral analyses, histopathological investigations, and electron microscopy provided insights into the neurobehavioral and structural changes induced by AST. Molecular investigations of male pups’ cortices revealed that AST outweighs the protective RAS elements with the inhibition of the detrimental arm. This established the neuroprotective and anti-inflammatory axes of RAS (ACE2/Ang1-7/MasR) in the ASD context. The results showed that AST’s normalization of RAS components and Notch signaling underscore a novel therapeutic avenue in ASD, impacting neuronal integrity and behavioral outcomes. These findings affirm the integral role of RAS in ASD and highlight AST’s potential as a promising treatment intervention, inviting further neurological research implications.
The Granular Size Concept in Avian Ecology: A Critical Analysis of eBird Data Bias Using the Bird Rank Abundance Distribution
Authors: Da Silva Sergio , Matsushita Raul , Esquierro Leon
Published: November 2023

In previous studies using eBird citizen data, bird abundance rankings followed a power law distribution. Our research delves into the “granular size” concept within these power laws, likening birds to firms. We identified 13 bird species as being the granular size, representing species with significant ecosystem impact, akin to major corporations in an economy. In particular, these species are urban, raising concerns about the eBird database’s sampling bias. Using the economic concept of granular size, we argue that the eBird database may be inherently unreliable.
Big Data, Data Science, and Artificial Intelligence for Project Management in the Architecture, Engineering, and Construction Industry: A Systematic Review
Authors: Zabala-Vargas Sergio , Jaimes-Quintanilla María , Jimenez-Barrera Miguel Hernán
Published: November 2023

The high volume of information produced by project management and its quality have become a challenge for organizations. Due to this, emerging technologies such as big data, data science and artificial intelligence (ETs) have become an alternative in the project life cycle. This article aims to present a systematic review of the literature on the use of these technologies in the architecture, engineering, and construction industry. A methodology of collection, purification, evaluation, bibliometric, and categorical analysis was used. A total of 224 articles were found, which, using the PRISMA method, finally generated 57 articles. The categorical analysis focused on determining the technologies used, the most common methodologies, the most-discussed project management areas, and the contributions to the AEC industry. The review found that there is international leadership by China, the United States, and the United Kingdom. The type of research most used is quantitative. The areas of knowledge where ETs are most used are Cost, Quality, Time, and Scope. Finally, among the most outstanding contributions are as follows: prediction in the development of projects, the identification of critical factors, the detailed identification of risks, the optimization of planning, the automation of tasks, and the increase in efficiency; all of these to facilitate management decision making.
Sustainability of Temporary Housing in Post-Disaster Scenarios: A Requirement-Based Design Strategy
Authors: Montalbano Giammarco , Santi Giovanni
Published: November 2023

Disasters, whether natural or man-made, pose inevitable global challenges. Events such as COVID-19, earthquakes, extreme climatic conditions, and conflicts underscore the urgent demand for effective temporary housing solutions. These temporary housing units (THUs) serve as an aid in assisting displaced people to rebuild their lives as the recovery process unfolds. However, numerous temporary housing units present environmental, economic, and social issues that hinder their sustainability. This paper investigates the underlying causes of these issues, defines the essential requirements that temporary housing units must meet, and proposes an initial design to fulfill these requirements. The methodology comprises three key phases: case study analysis, requirement identification, and the integration of these requirements into the design process. The main findings highlight that the construction of sustainable temporary housing units necessitates a meticulous consideration of various parameters to achieve a balanced equilibrium between economic, social, and environmental impacts. Possible future research directions are emphasized, including the use of digital tools and BIM models to promote the adoption of circular economy practices and the validation of the design solution through value analysis. Possible improvements in the user’s well-being are also taken into consideration.
In Situ Preparation of 0D/2D Zn-Ag-In-S Quantum Dots/RGO Heterojunctions for Efficient Photocatalytic Hydrogen Production
Authors: Deng Bangya , Yang Yalin , Khan Afaq Ullah , Chen Qitao , Wang Xianjin , Ren Tong , Li Jiaji , Liu Yanhong , Li Lixia , Mao Baodong
Published: November 2023

The creation of junctions between 0D and 2D materials can be an efficient strategy to enhance charge separation for solar hydrogen production. In this study, a simple in situ growth method has been used to synthesize a series of 0D/2D Zn-Ag-In-S quantum dots/reduced graphene oxide (ZAIS QDs/RGO) heterojunctions. The developed heterojunctions were characterized for structural characteristics, morphology, and photocatalytic performance, while varying the content of RGO. We observed that photocatalytic hydrogen production reached a maximum at an RGO content of 30 μL (342.34 µmol g−1 h−1), surpassing that of pure ZAIS QDs (110.38 µmol g−1 h−1) by 3.1 times, while maintaining excellent stability. To understand this enhancement, we performed time-resolved fluorescence and electrochemical impedance spectroscopy. The fluorescence lifetime of RGO loaded at 30 μL (417.76 ns) was significantly higher than that of pure ZAIS QDs (294.10 ns) and had the fastest charge transfer, which can be attributed to the charge transfer and storage capacity of RGO to extend the lifetime of photogenerated carriers and improve the charge separation efficiency. This study offers a simple synthesis method for constructing 0D/2D QDs/RGO heterojunction structures and provides a valuable reference for further enhancing the activity and stability of I-III-VI sulfide QDs.
A CoFe Bimetallic Catalyst for the Direct Conversion of Syngas to Olefins
Authors: Wang Xinxing , Lin Tiejun , Lv Dong , An Yunlei , Qi Xingzhen , Gong Kun , Zhong Liangshu
Published: November 2023

Syngas conversion is a useful technology for converting nonpetroleum carbon resources into chemicals such as olefins. Iron- and cobalt-based catalysts, as two major categories, have been extensively studied in Fischer–Tropsch synthesis to olefins (FTO) reactions. Although both iron and cobalt catalysts have shown distinct merits and shortcomings, they are also complementary in their properties and catalytic performances when combined with each other. Herein, Na-modified CoFe bimetallic catalysts were fabricated using a co-precipitation method. It was found that there was a synergistic effect between Co and Fe that promoted a CO dissociation rate and carburization, and an appropriate Co/Fe ratio was conducive to improvements in their catalytic performances. The desired olefins selectivity reached 66.1 C% at a CO conversion of 37.5% for a Co2Fe1 catalyst, while the methane selectivity was only 4.3 C%. In addition, no obvious deactivation was found after nearly 160 h, indicating their potential industrial application.
Chromosomal Instability-Driven Cancer Progression: Interplay with the Tumour Microenvironment and Therapeutic Strategies
Authors: Zheng Siqi , Guerrero-Haughton Erika , Foijer Floris
Published: November 2023

Chromosomal instability (CIN) is a prevalent characteristic of solid tumours and haematological malignancies. CIN results in an increased frequency of chromosome mis-segregation events, thus yielding numerical and structural copy number alterations, a state also known as aneuploidy. CIN is associated with increased chances of tumour recurrence, metastasis, and acquisition of resistance to therapeutic interventions, and this is a dismal prognosis. In this review, we delve into the interplay between CIN and cancer, with a focus on its impact on the tumour microenvironment—a driving force behind metastasis. We discuss the potential therapeutic avenues that have resulted from these insights and underscore their crucial role in shaping innovative strategies for cancer treatment.
Innate Immunity and CKD: Is There a Significant Association?
Authors: Plonsky-Toder Moran , Magen Daniella , Pollack Shirley
Published: November 2023

Chronic kidney disease (CKD) constitutes a worldwide epidemic, affecting approximately 10% of the global population, and imposes significant medical, psychological, and financial burdens on society. Individuals with CKD often face elevated morbidity and mortality rates, mainly due to premature cardiovascular events. Chronic inflammation has been shown to play a significant role in the progression of CKD, as well as in the acceleration of CKD-related complications, including atherosclerosis, cardiovascular disease (CVD), protein–energy wasting, and the aging process. Over the past two decades, a substantial body of evidence has emerged, identifying chronic inflammation as a central element of the uremic phenotype. Chronic inflammation has been shown to play a significant role in the progression of CKD, as well as in the acceleration of CKD-related complications in dialysis patients, including atherosclerosis, CVD, protein–energy wasting, and the aging process. Remarkably, chronic inflammation also impacts patients with CKD who have not yet required renal replacement therapy. While extensive research has been conducted on the involvement of both the adaptive and innate immune systems in the pathogenesis of CKD-related complications, this wealth of data has not yet yielded well-established, effective treatments to counteract this ongoing pathological process. In the following review, we will examine the established components of the innate immune system known to be activated in CKD and provide an overview of the current therapeutic approaches designed to mitigate CKD-related chronic inflammation.
Pllans−II: Unveiling the Action Mechanism of a Promising Chemotherapeutic Agent Targeting Cervical Cancer Cell Adhesion and Survival Pathways
Authors: Montoya-Gómez Alejandro , Tonello Fiorella , Spolaore Barbara , Massimino Maria Lina , Montealegre-Sánchez Leonel , Castillo Andrés , Rivera Franco Nelson , Sevilla-Sánchez María José , Solano-Redondo Luis Manuel , Mosquera-Escudero Mildrey , Jiménez-Charris Eliécer
Published: November 2023

Despite advances in chemotherapeutic drugs used against cervical cancer, available chemotherapy treatments adversely affect the patient’s quality of life. For this reason, new molecules from natural sources with antitumor potential and few side effects are required. In previous research, Pllans−II, a phospholipase A2 type-Asp49 from Porthidium lansbergii lansbergii snake venom, has shown selective attack against the HeLa and Ca Ski cervical cancer cell lines. This work suggests that the cytotoxic effect generated by Pllans−II on HeLa cells is triggered without affecting the integrity of the cytoplasmic membrane or depolarizing the mitochondrial membranes. The results allow us to establish that cell death in HeLa is related to the junction blockage between α5β1 integrins and fibronectin of the extracellular matrix. Pllans−II reduces the cells’ ability of adhesion and affects survival and proliferation pathways mediated by intracellular communication with the external environment. Our findings confirmed Pllans−II as a potential prototype for developing a selective chemotherapeutic drug against cervical cancer.
Chemistry: A Place to Publish Your Creative Multidisciplinary Research
Authors: Alabugin Igor V.
Published: November 2023

It is my pleasure to welcome you to Chemistry (ISSN: 2624-8549), an open access peer-reviewed journal that publishes both primary reports and reviews highlighting important advances in fundamental areas of chemistry and/or illustrating the central role of chemistry in bridging the physical and life sciences [...]
Linguistic Skills and Socioeconomic Status: Two Oft Forgotten Factors in Child Metaphor Comprehension
Authors: Pouscoulous Nausicaa , Perovic Alexandra
Published: November 2023

Metaphor understanding can be tricky for children until mid-childhood, yet some research suggests that pre-schoolers are already competent. Many factors have been proposed to play a role in the development of metaphor comprehension. In this study we focus on two obvious contenders that have been overlooked in recent years: general language skills and socioeconomic status (SES). Two-hundred and seventy-two children, aged from 2;11 to 11;04 (146 girls) were recruited from 21 British schools and nurseries. Their SES was established using a composite measure linked to school location, while general language skills were assessed using a standardised measure of vocabulary comprehension. Novel metaphor comprehension was tested with a simple reference assignment task. Our study confirms that children interpret novel metaphors confidently from the age of 4. Our findings indicate that novel metaphor understanding is associated with age and, importantly, that it is linked to vocabulary skills, as well as SES, but not gender. These two factors should therefore be considered in future research on metaphor development, as well as intervention and education.
Does the Association between Preschool Media Use and Language Difficulties at School Entry Vary by First Language of the Child and Parental Education?
Authors: Hammrich Chiara Maria , Götz Simon , Daseking Monika , Weyers Simone
Published: November 2023

Background: Both media use and social background affect children’s language development. The aim of this study was to explore the association between media use and different aspects of language difficulties (grammar, auditory memory, articulation) and social background (first language (FL), parental education (PE)) in more detail. Methods: We analyzed data from 4015 children from the 2013/14 school entry examination in a Western German city. Media use, FL, and PE were assessed by social history, and language difficulties by sociopediatric screening. We calculated Prevalence Ratios with a 95% Confidence Interval for language difficulties by media use and FL/PE; compared models with and without interaction terms; and estimated the predicted prevalence of language difficulties by media use and FL/PE. Results: Children with non-German FL/low PE had a higher media use and more language difficulties. However, the gradual association between media use and grammatical abilities/recommendation of training was more pronounced in children with German FL and medium/high PE. e.g., especially in the preposition subtest. Conclusions: The association between media use and language difficulties varies regarding different aspects of social background and language difficulties. Still, extensive media use is linked with language difficulties for all children. The media competence of young families remains crucial in times of digitalization.
Associations between School-Level Disadvantage, Bullying Involvement and Children’s Mental Health
Authors: Badger Julia R. , Zaneva Mirela , Hastings Richard P. , Broome Matthew R. , Hayes Rachel , Patterson Paul , Rose Naomi , Clarkson Suzy , Hutchings Judy , Bowes Lucy
Published: November 2023

Bullying is a modifiable risk factor for poor mental health across childhood and adolescence. It is also socially patterned, with increased prevalence rates in more disadvantaged settings. The current study aimed to better understand whether school-level disadvantage is associated with different types of bullying roles, and whether it is a moderator in the association between bullying and children’s mental health. Cross-sectional data were used from 4727 children aged 6–11 years, from 57 primary schools across England and Wales. The child data included previous bullying involvement and bullying role characteristics (bully, victim, bully–victim, reinforcer, defender, outsider), and the teacher-reported data included each child’s mental health (emotional symptoms and externalizing) problems. School-level disadvantage was calculated from the proportion of children in the school eligible to receive free school meals (an indicator of disadvantage). Children in more disadvantaged schools were more likely to report being bully perpetrators, bully–victims, and engage less in defending behaviors during a bullying incident. Children from more disadvantaged schools who reported bullying others showed fewer emotional symptoms than those from less disadvantaged schools. There was no other evidence of moderation by school-level disadvantage between bullying roles and emotional and externalizing problems. The findings highlight the potential for school-based interventions targeting children’s emotional and social development, targeting bullying, and promoting defending behaviors, particularly in more disadvantaged settings.
When the Media Omits or Includes Scientific Evidence in Its Publications: Science and Battles on X about Child Sexual Abuse
Authors: Olabarria Ane , Burgués-Freitas Ana , López de Aguileta Ane , Zubiri-Esnaola Harkaitz , Torras-Gómez Elisabeth , Joanpere Mar , López de Aguileta Garazi , Álvarez-Guerrero Garazi , Aiello Emilia , Pulido Cristina , Redondo-Sama Gisela
Published: November 2023

Scientific evidence of social impact demonstrates how violence against children is successfully prevented. Currently, the scientific research on social impact has a focus on the analysis of actions that succeed in the implementation of such scientific evidence. This article is based on scientific research that looks at which media actions help or hinder the implementation of evidence-based actions to solve the most sensitive social problems. The social media analytics methodology has identified the posts and reposts generated during two consecutive days by news articles published by three newspapers about the official report on child sexual abuse in Spain. Their analyses have been made through communicative methodology, including voices of adult victims or survivors of child sexual abuse. The results indicate that media information that omits scientific evidence of social impact provokes battles between diverse ideological groups, while information based on scientific evidence of social impact generates consensus among people from different ideologies and actions oriented to overcome the problem.
Teachers’ Perceptions of Bullying in Saudi Arabian Primary Public Schools: A Small-Sample, Qualitative Case Study
Authors: Abed Mohaned G. , Abed Lowai G. , Shackelford Todd K.
Published: November 2023

Bullying among primary school students is a serious problem that often has multiple negative effects including poor academic performance and mental health problems. The current study used qualitative methodology to determine the role of communication in creating awareness and preventing bullying in a school setting through stakeholder intervention and bullying-prevention programs. If teachers are aware of bullying, then they are likely to take adequate measures to reduce or prevent future bullying. The researchers conducted semi-structured interviews with 15 teachers working in public primary schools in Jeddah, Saudi Arabia. The results provide an initial step in the Saudi Arabian context toward identifying the forms and types of school bullying, helping administrators, teachers, parents, and students reduce bullying and develop long-term plans for addressing bullying. Consideration of teachers’ perceptions may enable the development and implementation of new programs for addressing bullying in primary school students. The discussion highlights future research directions and the limitations of the current research.