bluuebunny/crossref_metadata_2025 huggingface dataset:
Self-Contained Reference Sensors to Reduce Nuisance Alarm Rate in φ-OTDR-Based Fence Intrusion Detection System
Authors: Zhang Hailiang , Dong Hui , Hu Dora Juan Juan , Ng Jun Hong
Published: May 2023

Nuisance alarm rate (NAR) is one of the key performance parameters in a phase-sensitive optical time domain reflectometry (φ-OTDR)-based fence intrusion detection system. Typically, the vibrations caused by ambient environmental conditions, such as heavy rain, strong wind, and passing vehicles, easily result in many nuisance alarms. Significant research efforts have been undertaken to suppress the NAR. In this paper, we propose to utilize short segments of the sensing fiber as reference sensors for significant reduction in the NAR in φ-OTDR for the first time, to the best of our knowledge. According to our field trial results, the proposed approach can reduce the NAR by more than 90%. The proposed approach is very simple, practical, and cost-effective, which can be easily integrated with the existing methods of reducing NAR and act as an additional level of decision-making algorithm for triggering alarms.
Assessment of Aptamer as a Potential Drug Targeted Delivery for Retinal Angiogenesis Inhibition
Authors: Moreira David , Lopes-Nunes Jéssica , Santos Fátima Milhano , Campello Maria Paula Cabral , Oliveira Maria Cristina , Paulo António , Tomaz Cândida , Cruz Carla
Published: May 2023

AT11-L0 is an aptamer derivative of AS1411 composed of G-rich sequences that can adopt a G-quadruplex (G4) structure and target nucleolin (NCL), a protein that acts as a co-receptor for several growth factors. Hence, this study aimed to characterize the AT11-L0 G4 structure and its interaction with several ligands for NCL targeting and to evaluate their capacity to inhibit angiogenesis using an in vitro model. The AT11-L0 aptamer was then used to functionalize drug-associated liposomes to increase the bioavailability of the aptamer-based drug in the formulation. Biophysical studies, such as nuclear magnetic resonance, circular dichroism, and fluorescence titrations, were performed to characterize the liposomes functionalized with the AT11-L0 aptamer. Finally, these liposome formulations with the encapsulated drugs were tested on the human umbilical vein endothelial cell (HUVEC) model to assess their antiangiogenic capacity. The results showed that the AT11-L0 aptamer–ligand complexes are highly stable, presenting melting temperatures from 45 °C to 60 °C, allowing for efficient targeting of NCL with a KD in the order of nM. The aptamer-functionalized liposomes loaded with ligands C8 and dexamethasone did not show cytotoxic effects in HUVEC cells compared with the free ligands and AT11-L0, as assessed by cell viability assays. AT11-L0 aptamer-functionalized liposomes encapsulating C8 and dexamethasone did not present a significant reduction in the angiogenic process when compared with the free ligands. In addition, AT11-L0 did not show anti-angiogenic effects at the concentrations tested. However, C8 shows potential as an angiogenesis inhibitor, which should be further developed and optimized in future experiments.
Fighting Illicit Trafficking of Cultural Goods—The ENIGMA Project
Authors: Patias Petros , Georgiadis Charalampos
Published: May 2023

Cultural heritage is a testimony of past human activity, and, as such, cultural objects exhibit great variety in their nature, size, and complexity, from small artefacts and museum items to cultural landscapes, and from historic buildings and ancient monuments to city centers and archaeological sites. Cultural heritage around the globe suffers from wars, natural disasters, and human negligence. More specifically, cultural goods and artefacts are put at risk through several anthropogenic actions: Anthropogenic threats take various dimensions, ranging from theft from museums, private collections, and religious buildings, smuggling of and illicit trade in cultural goods, the irremediable looting and demolition of archaeological sites by clandestine excavators, or simply neglect of heritage sites. Illicit trading has expanded dramatically recently, especially in areas affected by armed conflicts and natural disasters, either aiming at destroying collective memory and dismembering people’s identity or mostly motivated by the pursuit of profit. Moreover, the illicit trafficking of cultural goods contributes to the funding of terrorism, organized crime, and money laundering. The mission of ENIGMA, a EUR 4 million EU funded project, is to achieve excellence in the protection of cultural goods and artefacts from man-made threats by contributing to their identification, traceability, and provenance research, as well as by safeguarding and monitoring endangered heritage sites. ENIGMA objectives are designed to help the involved stakeholders better respond to this complex and multi-dimensional problem and leverage active collaboration by fostering and enabling interlinking of databases, and evidence-based deployment of preventative measures.
Multilevel Feature Aggregated Network with Instance Contrastive Learning Constraint for Building Extraction
Authors: Li Shiming , Bao Tingrui , Liu Hui , Deng Rongxin , Zhang Hui
Published: May 2023

Building footprint extraction from remotely sensed imagery is a critical task in the field of illegal building discovery, urban dynamic monitoring, and disaster emergency response. Recent research has made significant progress in this area by utilizing deep learning techniques. However, it remains difficult to efficiently balance the spatial detail and rich semantic features. In particular, the extracted building edge is often inaccurate, especially in areas where the buildings are densely distributed, and the boundary of adjacent building instances is difficult to distinguish accurately. Additionally, identifying buildings with varying scales remains a challenging problem. To address the above problems, we designed a novel framework that aggregated multilevel contextual information extracted from multiple encoders. Furthermore, we introduced an instance constraint into contrastive learning to enhance the robustness of the feature representation. Experimental results demonstrated that our proposed method achieved 91.07% and 74.58% on the intersection over union metric on the WHU and Massachusetts datasets, respectively, outperforming the most recent related methods. Notably, our method significantly improved the accuracy of building boundaries, especially at the building instance level, and the integrity of multi-scale buildings.
Imaging Cultural Heritage at Different Scales: Part I, the Micro-Scale (Manufacts)
Authors: Piroddi Luca , Abu Zeid Nasser , Calcina Sergio Vincenzo , Capizzi Patrizia , Capozzoli Luigi , Catapano Ilaria , Cozzolino Marilena , D’Amico Sebastiano , Lasaponara Rosa , Tapete Deodato
Published: May 2023

Applications of non-invasive sensing techniques to investigate the internal structure and surface of precious and delicate objects represent a very important and consolidated research field in the scientific domain of cultural heritage knowledge and conservation. The present article is the first of three reviews focused on contact and non-contact imaging techniques applied to surveying cultural heritage at micro- (i.e., manufacts), meso- (sites) and macro-scales (landscapes). The capability to infer variations in geometrical and physical properties across the inspected surfaces or volumes is the unifying factor of these techniques, allowing scientists to discover new historical sites or to image their spatial extent and material features at different scales, from landscape to artifact. This first part concentrates on the micro-scale, i.e., inspection, study and characterization of small objects (ancient papers, paintings, statues, archaeological findings, architectural elements, etc.) from surface to internal properties.
German Extermination Camps on WWII Reconnaissance Photographs. Orthorectification Process for Archival Aerial Images of Cultural Heritage Sites
Authors: Różycki Sebastian , Karwel Artur Karol , Kurczyński Zdzisław
Published: May 2023

Aerial photographs taken over the past 80 years are often the only record of topography and events that have been destroyed or obliterated. However, the lack of camera certificates for many historical photographs, and their physical degradation, often makes it challenging to correct them geometrically. In this paper, we present the process of orthorectifying archival Luftwaffe aerial photographs of the area of the Treblinka extermination camp from May 1944, based on a computer vision-based process and preprocessing techniques. Low-cost and easily accessible software was used, which allowed for the generation of a fully metric orthophotomap in a repeatable and accurate way. This process can be repeated for archival aerial photographs from other dates (for the Treblinka camp) and other extermination camps (Belzec and Sobibor).
Novel Weigh-in-Motion Pavement Sensor Based on Self-Sensing Nanocomposites for Vehicle Load Identification: Development, Performance Testing, and Validation
Authors: Liang Ming , Zhang Yunfeng , Jiao Yuepeng , Wang Jianjiang , Su Linping , Yao Zhanyong
Published: May 2023

The development of the transportation industry has led to an increasing number of overloaded vehicles, which reduces the service life of asphalt pavements. Currently, the traditional vehicle weighing method not only involves heavy equipment but also has a low weighing efficiency. To deal with the defects in the existing vehicle weighing system, this paper developed a road-embedded piezoresistive sensor based on self-sensing nanocomposites. The sensor developed in this paper adopts an integrated casting and encapsulation technology, in which an epoxy resin/MWCNT nanocomposite is used for the functional phase, and an epoxy resin/anhydride curing system is used for the high-temperature resistant encapsulation phase. The compressive stress-resistance response characteristics of the sensor were investigated by calibration experiments with an indoor universal testing machine. In addition, the sensors were embedded in the compacted asphalt concrete to validate the applicability to the harsh environment and back-calculate the dynamic vehicle loads on the rutting slab. The results show that the response relationship between the sensor resistance signal and the load is in accordance with the GaussAmp formula. The developed sensor not only survives effectively in asphalt concrete but also enables dynamic weighing of the vehicle loads. Consequently, this study provides a new pathway to develop high-performance weigh-in-motion pavement sensors.
Detection and Reconstruction of Poor-Quality Channels in High-Density EMG Array Measurements
Authors: Farago Emma , Chan Adrian D. C.
Published: May 2023

High-density electromyography (HD-EMG) arrays allow for the study of muscle activity in both time and space by recording electrical potentials produced by muscle contractions. HD-EMG array measurements are susceptible to noise and artifacts and frequently contain some poor-quality channels. This paper proposes an interpolation-based method for the detection and reconstruction of poor-quality channels in HD-EMG arrays. The proposed detection method identified artificially contaminated channels of HD-EMG for signal-to-noise ratio (SNR) levels 0 dB and lower with ≥99.9% precision and ≥97.6% recall. The interpolation-based detection method had the best overall performance compared with two other rule-based methods that used the root mean square (RMS) and normalized mutual information (NMI) to detect poor-quality channels in HD-EMG data. Unlike other detection methods, the interpolation-based method evaluated channel quality in a localized context in the HD-EMG array. For a single poor-quality channel with an SNR of 0 dB, the F1 scores for the interpolation-based, RMS, and NMI methods were 99.1%, 39.7%, and 75.9%, respectively. The interpolation-based method was also the most effective detection method for identifying poor channels in samples of real HD-EMG data. F1 scores for the detection of poor-quality channels in real data for the interpolation-based, RMS, and NMI methods were 96.4%, 64.5%, and 50.0%, respectively. Following the detection of poor-quality channels, 2D spline interpolation was used to successfully reconstruct these channels. Reconstruction of known target channels had a percent residual difference (PRD) of 15.5 ± 12.1%. The proposed interpolation-based method is an effective approach for the detection and reconstruction of poor-quality channels in HD-EMG.
Electrochemical DNA-Sensor Based on Macrocyclic Dendrimers with Terminal Amino Groups and Carbon Nanomaterials
Authors: Kulikova Tatjana , Shamagsumova Rezeda , Rogov Alexey , Stoikov Ivan , Padnya Pavel , Shiabiev Igor , Evtugyn Gennady
Published: May 2023

The assembling of thiacalix[4]arene-based dendrimers in cone, partial cone, and 1,3-alternate configuration on the surface of a glassy carbon electrode coated with carbon black or multiwalled carbon nanotubes has been characterized using cyclic voltammetry, electrochemical impedance spectroscopy, and scanning electron microscopy. Native and damaged DNA were electrostatically accumulated on the modifier layer. The influence of the charge of the redox indicator and of the macrocycle/DNA ratio was quantified and the roles of the electrostatic interactions and of the diffusional transfer of the redox indicator to the electrode interface indicator access were established. The developed DNA sensors were tested on discrimination of native, thermally denatured, and chemically damaged DNA and on the determination of doxorubicin as the model intercalator. The limit of detection of doxorubicin established for the biosensor based on multi-walled carbon nanotubes was equal to 1.0 pM with recovery from spiked human serum of 105–120%. After further optimization of the assembling directed towards the stabilization of the signal, the developed DNA sensors can find application in the preliminary screening of antitumor drugs and thermal damage of DNA. They can also be applied for testing potential drug/DNA nanocontainers as future delivery systems.
Contrastive Learning-Based Anomaly Detection for Actual Corporate Environments
Authors: An Gi-taek , Park Jung-min , Lee Kyung-soon
Published: May 2023

Information systems play an important role in business management, especially in personnel, budget, and financial management. If an anomaly ensues in an information system, all operations are paralyzed until their recovery. In this study, we propose a method for collecting and labeling datasets from actual operating systems in corporate environments for deep learning. The construction of a dataset from actual operating systems in a company’s information system involves constraints. Collecting anomalous data from these systems is challenging because of the need to maintain system stability. Even with data collected over a long period, the training dataset may have an imbalance of normal and anomalous data. We propose a method that utilizes contrastive learning with data augmentation through negative sampling for anomaly detection, which is particularly suitable for small datasets. To evaluate the effectiveness of the proposed method, we compared it with traditional deep learning models, such as the convolutional neural network (CNN) and long short-term memory (LSTM). The proposed method achieved a true positive rate (TPR) of 99.47%, whereas CNN and LSTM achieved TPRs of 98.8% and 98.67%, respectively. The experimental results demonstrate the method’s effectiveness in utilizing contrastive learning and detecting anomalies in small datasets from a company’s information system.
Bragg Curve Detection of Low-Energy Protons by Radiophotoluminescence Imaging in Lithium Fluoride Thin Films
Authors: Montereali Rosa Maria , Nigro Valentina , Piccinini Massimo , Vincenti Maria Aurora , Ampollini Alessandro , Nenzi Paolo , Ronsivalle Concetta , Nichelatti Enrico
Published: May 2023

Lithium fluoride (LiF) crystals and thin films are utilized as radiation detectors for energy diagnostics of proton beams. This is achieved by analyzing the Bragg curves in LiF obtained by imaging the radiophotoluminescence of color centers created by protons. In LiF crystals, the Bragg peak depth increases superlinearly with the particle energy. A previous study has shown that, when 35 MeV protons impinge at grazing incidence onto LiF films deposited on Si(100) substrates, the Bragg peak in the films is located at the depth where it would be found in Si rather than in LiF due to multiple Coulomb scattering. In this paper, Monte Carlo simulations of proton irradiations in the 1–8 MeV energy range are performed and compared to experimental Bragg curves in optically transparent LiF films on Si(100) substrates. Our study focuses on this energy range because, as energy increases, the Bragg peak gradually shifts from the depth in LiF to that in Si. The impact of grazing incidence angle, LiF packing density, and film thickness on shaping the Bragg curve in the film is examined. At energies higher than 8 MeV, all these quantities must be considered, although the effect of packing density plays a minor role.
Low-Profile Antenna System for Cognitive Radio in IoST CubeSat Applications
Authors: Aljaloud Khaled , Sultan Kamel , Ikram Muhammad , Alqahtani Ali H. , Abbasi Qammar Hussain , Hussain Rifaqat
Published: May 2023

Since the CubeSats have become inherently used for the Internet of space things (IoST) applications, the limited spectral band at the ultra-high frequency (UHF) and very high frequency should be efficiently utilized to be sufficient for different applications of CubeSats. Therefore, cognitive radio (CR) has been used as an enabling technology for efficient, dynamic, and flexible spectrum utilization. So, this paper proposes a low-profile antenna for cognitive radio in IoST CubeSat applications at the UHF band. The proposed antenna comprises a circularly polarized wideband (WB) semi-hexagonal slot and two narrowband (NB) frequency reconfigurable loop slots integrated into a single-layer substrate. The semi-hexagonal-shaped slot antenna is excited by two orthogonal +/−45° tapered feed lines and loaded by a capacitor in order to achieve left/right-handed circular polarization in wide bandwidth from 0.57 GHz to 0.95 GHz. In addition, two NB frequency reconfigurable slot loop-based antennas are tuned over a wide frequency band from 0.6 GHz to 1.05 GH. The antenna tuning is achieved based on a varactor diode integrated into the slot loop antenna. The two NB antennas are designed as meander loops to miniaturize the physical length and point in different directions to achieve pattern diversity. The antenna design is fabricated on FR-4 substrate, and measured results have verified the simulated results.
Fused Triazole-Azepine Hybrids as Potential Non-Steroidal Antiinflammatory Agents
Authors: Demchenko Sergii , Lesyk Roman , Yadlovskyi Oleh , Holota Serhii , Yarmoluk Sergii , Tsyhankov Sergii , Demchenko Anatolii
Published: May 2023

Non-steroidal anti-inflammatory drugs (NSAIDs) are one of the oldest and most widely used groups of drugs nowadays. However, the problem of searching for and creating new NSAIDs remains open, primarily due to the risks owing to their short- and long-term use. In this context, triazole-azepine hybrid molecules are attractive and prospective objects for the rational design of novel potential NSAIDs. In the present work studies of 3-aryl-6,7,8,9-tetrahydro-5H-[1,2,4]triazolo[4,3-a]azepines as potential non-steroidal anti-inflammatory agents are reported. Evaluation of drug-like properties for all tested triazole-azepine hybrids was performed in silico using SwissADME. The screening of analgesic and anti-inflammatory activities was performed in vivo using acid-induced writhing and carrageenin-induced hind paw oedema models in mice. Derivatives with activity levels more potent compared with reference drugs ketorolac and diclofenac sodium were identified. Preliminary SAR was performed based on the screening results.
Diallyldimethylammonium Chloride (DADMAC) in Water Treated with Poly-Diallyldimethylammonium Chloride (PDADMAC) by Reversed-Phase Ion-Pair Chromatography—Electrospray Ionization Mass Spectrometry
Authors: Di Gaudio Francesca , Barreca Salvatore , Orecchio Santino
Published: May 2023

Poly-diallyldimethylammonium (PDADMAC) chloride is a flocculant agent extensively used in water clarification treatments. Commercial polyelectrolyte formulations often contain residual monomer (DADMAC), reaction by-products and other reactants as contaminants that could potentially affect human health. In the present study, we optimized an analytical method based on reversed-phase ion-pair chromatography coupled with mass spectrometry for quantifying ultra-trace levels of DADMAC, without preliminary treatments, in drinking water distributed by the Palermo aqueduct. The method was validated in terms of accuracy (recovery between 80 to 120%), precision (RSD < 10%), linearity range (from 0.5 to 15 µg/L), limit of quantification and limit of detection (LOQ 0.42 µg/L and LOD 0.12 µg/L). DADMAC was detected in all analysed water samples and the concentration ranged from 1.2 to 3.8 µg/L whit a mean value of 1.7 µg/L. To the best of our knowledge, this paper represents the first study concerning DADMAC concentration in water samples collected in Italy and, in this context, this paper can be considered very interesting when comparing future data on DADMAC monitoring in water. Moreover, this is one of a few cases where DADMAC was found in drinking water.
A Case Study on Applications of the Hook Model in Software Products
Authors: Lukyanchikova Elena , Askarbekuly Nursultan , Aslam Hamna , Mazzara Manuel
Published: May 2023

The Hook model is used in digital products to engage and retain users through the mechanism of habit formation. This paper explores the use of Hook model techniques in two mobile applications, one being a popular taxi service (Uber taxi) and the other a social network (Instagram). The goal of this paper is to explore the Hook cycle patterns in the two products, and to identify commonalities and differences in how they are applied. Our results suggest that Hook cycle patterns appear with similar frequency; however, Instagram includes more internal Trigger calls. Uber uses fewer triggers to encourage usage, most probably because users already have a specific need for the application. For the same reason, Uber has less opportunity to fail in the reward delivery, while Instagram can use the failure (in providing a reward) as another trigger if the usage habit is already established. In addition, we introduce two types of Hook cycle patterns: internal (within a single use case) and external (transition between use cases). The insights obtained through the case studies serve as a practical reference for developing engaging and retention-focused applications.
Role of Hormones and the Potential Impact of Multiple Stresses on Infertility
Authors: Ramya Shanmugam , Poornima Prasad , Jananisri Arumugam , Geofferina Irudhayaraj Peatrise , Bavyataa Venkataramanaravi , Divya Murugan , Priyanga Palanisamy , Vadivukarasi Jeganathan , Sujitha Senthil , Elamathi Selvarasu , Anand Arumugam Vijaya , Balamuralikrishnan Balasubramanian
Published: May 2023

Infertility has a remarkable global impact affecting approximately about 48 million couples worldwide. One of the most contended concerns in reproductive biology is the prospective influence of psychological stress on pregnancy rates. Individuals struggling to conceive face a stupendous amount of emotional turbulence and have a greater risk for psychological vulnerability. Both stress and infertility reinforce the impact of each other; hence, there exists a reciprocal relationship. Stress may be the major contributor to subsequent infertility. Infertility treatments may enhance stress levels as well as reduce treatment outcomes. The biological mechanisms that interlink stress and infertility are the outcome of the hormonal actions at the brain level, where they stimulate or suppress the hypothalamic-pituitary-adrenal axis (HPA) and have a potential influence on the secretion of the respective hormone by the reproductive organs and the pregnancy outcomes. Sex hormones play an essential role in reproductive biology as well as in general physiology where they generate the cycle and provide a potential environment for pregnancy. This article reviews the impact of stress on reproductive rates and the implications of sex hormones on infertility. Additionally, it suggests strategies to overcome the stress conditions and the scenarios that may lead to stress.
Challenges to the Implementation of BIM for the Risk Management of Oil and Gas Construction Projects: Structural Equation Modeling Approach
Authors: Waqar Ahsan , Othman Idris , González-Lezcano Roberto Alonso
Published: May 2023

Building Information Modeling (BIM) has become increasingly popular in the construction industry as a way to enhance risk management. However, little attention has been paid to the challenges of using BIM for safety management in Malaysia’s oil and gas construction sector, which is particularly hazardous and requires effective safety management to complete projects successfully. This study aims to identify the obstacles to using BIM for safety management in Malaysia’s oil and gas construction sector and to understand the root causes of resistance to its adoption. Exploratory factor analysis and structural equation modeling were conducted on survey data collected from industry professionals. The study found that knowledge obstacles, creative hurdles, technical barriers, supervisory barriers, and functional barriers are the most significant challenges hindering the widespread adoption of BIM for safety management. These challenges were confirmed to significantly affect BIM adoption for safety management. The study’s findings have important implications for policymakers, industry practitioners, and academics seeking to improve safety management in Malaysia’s oil and gas construction sector through the use of BIM. Future research could explore additional variables that may impact BIM adoption for safety management in this sector.
Extractions of Protein-Rich Alaria esculenta and Lemna minor by the Use of High-Power (Assisted) Ultrasound
Authors: Inguanez Lara , Zhu Xianglu , de Oliveira Mallia Jefferson , Tiwari Brijesh K. , Valdramidis Vasilis P.
Published: May 2023

Plant nutrients extracted from sustainable sources, namely Alaria esculenta and Lemna minor, have been evaluated for their nutritional value in an attempt to identify their potential as protein-rich sources. The implementation of green technologies such as high-power ultrasound to extract nutrients from these alternative biomasses was studied and compared to more traditional techniques. Probe sonicators fared better than bath sonicators in extracting bioactive compounds while ultrasound assisted with enzymes was more efficient than conventional or alkali extraction methods. Lemna minor was found to have the greatest extraction yield of nutrients.
Do Unprecedented Gasoline Prices Affect the Consumer Switching to New Energy Vehicles? An Integrated Social Cognitive Theory Model
Authors: Chen Long , Liu Xiaokun , Jing Peng
Published: May 2023

From 2020 to 2022, the price of gasoline in China rose sharply, which may cause consumers to adopt new energy vehicles. However, the government subsidies in the yearly retreat for 2023 were completely abolished, which could hinder consumers’ switching behavior. The combination of these factors may affect consumer decision-making, making accurate analysis of consumer willingness to switch to new energy vehicles crucial for the development of this industry. The current study aims to investigate consumers’ vehicle switching intentions affected by multiple factors such as fuel prices, and we attempt to analyze these by combining personal and environmental factors from social cognitive theory. Data were collected through an online platform survey using developed reliable scales. The 464 responses were then synthesized using structural equation modeling and Bayesian networks, and the results showed that approximately 51% of consumers had high-level switching intentions to new energy vehicles; attitude, self-efficacy, environmental consciousness, and infrastructure barriers had the strongest effect on consumers’ vehicle switching intentions. This study assists in identifying the psychological demands of consumers switching to new energy vehicles and provides ideas for vehicle manufacturers and governments in terms of marketing strategies and policy formulation at crucial stages when new energy vehicles are in accelerated development.
Does China–Europe Railway Express Improve Green Total Factor Productivity in China?
Authors: Wang Xiao , Li Jiaojiao , Shi Jingming , Li Jia , Liu Jianxu , Sriboonchitta Songsak
Published: May 2023

Based on the panel data of 284 prefecture-level cities in China from 2005 to 2019, this paper adopts a time-varying difference-in-differences model as a quasi-natural experiment to empirically test the impact and mechanism of the operation of the China–Europe Railway Express on green total factor productivity. The empirical results show that China–Europe Railway Express can significantly improve urban green total factor productivity. In addition, the heterogeneity test manifests that the promotion of green total factor productivity is more significant in the northern regions, the group of cities with low support from the “Belt and Road” policy and high level of their own green development. The results of the mechanism test unveil that the technological innovation effect, industrial upgrading effect and financial development effect brought by the opening of China–Europe Railway Express are the main forces boosting urban green total factor productivity. Furthermore, we found that the optimization of transportation costs, the development of multi-modal transportation and sustainable development are conducive to promoting the high-quality development of freight trains, which helps to strengthen the promotion of green total factor productivity. In brief, this paper provides a new perspective for the study of the economic potential of the China–Europe Railway Express, as well as provides a reference for optimizing the operation mode of China–Europe Railway Express.
Enacting Remote and Flexible Learning Placements during a Global Pandemic—A Case Report
Authors: O’Brien Siobhan
Published: May 2023

The global pandemic significantly affected teacher training programs, specifically professional experience in schools. The past two years of teacher education have necessitated the innovation and adaption of traditional programs to ensure pre-service teachers’ preparation and readiness to enter schools as graduates in Australia. This case report explores the creation and implementation of three innovations that were used to support pre-service teachers who undertook a remote and flexible learning placement due to school closures. The report presents the process implemented to best support the pre-service teachers and school mentors to deal with the disruption to professional experience caused.
Evaluation of Railway Systems: A Network Approach
Authors: Cornaro Alessandra , Grechi Daniele
Published: May 2023

Resilience and the efficiency of transportation systems are crucial for the economic development of geographical areas, and network analysis applied to railways can provide insight into the importance of branch lines and their impacts on the entire system. This paper explores the behavior of the ERC measure, a local robustness measure, on the railway network in Lombardy, Italy, and analyzes the impacts of deactivating stations or journeys on the network’s robustness. Changes in the topological properties of the network were studied by simulating potential external disturbances and analyzing the impact of deleting the most connected stations or railway lines. The numerical results show how the measures provided effectively identify critical stations and journeys within the network structure and outperform classical topological metrics. Since ERC measures take into account all of the alternative paths present in the network, they can provide valuable information for rerouting traffic along alternative paths in case of failures or disruptions. The paper’s original contribution lies in demonstrating the effectiveness of the ERC measure in identifying critical stations and journeys within the network structure.
SUNFIT: A Machine Learning-Based Sustainable University Field Training Framework for Higher Education
Authors: Gollapalli Mohammed , Rahman Atta , Alkharraa Mariam , Saraireh Linah , AlKhulaifi Dania , Salam Asiya Abdus , Krishnasamy Gomathi , Alam Khan Mohammad Aftab , Farooqui Mehwash , Mahmud Maqsood , Hatab Rehan
Published: May 2023

With the rapid advances in Information Technology (IT), the focus on engaging computing students to gain practical experience in the IT industry before graduation is becoming increasingly complex without incorporating pedagogical strategies of success in curricula. The goal is to enable computing major students to gain in-depth knowledge and practical understanding of the IT working environment before graduating through essential industry-driven practical skills based on international standards and best practices. Unfortunately, tracking and analyzing students’ practical skills performance during their IT field training programs, which are conducted primarily off-campus at various public and private organizations, before, during, and after the training period, is a daunting task for both the college instructors and the industry trainers. To overcome these challenges, this paper introduces a Sustainable University Field Training (SUNFIT) framework, which is a pedagogical approach towards mining the educational data using machine learning to integrate and measure the field training programs against the internationally recognized accreditation standards such as Accreditation Board for Engineering and Technology (ABET). The study employs machine learning models aimed at continuously measuring and monitoring international ABET accreditation requirements on computing major courses’ academic data, elucidating student performance across various semesters, integrating best practices, and producing an evidence-based rationale approach for evaluating weak learning outcomes (LOs) with minimal manual intervention, as well as preventing faculty-specific portfolio errors. The proposed approach could be easily developed by academics, researchers, or even students, and for a variety of purposes, including enhancing poor student outcomes (SOs). In addition, various data mining and machine learning approaches have been investigated over field training assessment data for successful prediction in subsequent cycles. The results are promising, with Naïve Bayes obtaining the highest accuracy of 90.54% followed by J48 and PART algorithms at 87.83%.
Study on Deformation Characteristics of Retaining Structures under Coupled Effects of Deep Excavation and Groundwater Lowering in the Affected Area of Fault Zones
Authors: Niu Yungang , Zou Liang , Wang Qiongyi , Ma Fenghai
Published: May 2023

In order to study the deformation characteristics of the retaining structure under the coupled effect of excavation and dewatering in the affected area of fault zones, this paper takes a deep excavation project in the F1322 fault zone influence area in Shenzhen as an example. The research methods of theoretical analysis, numerical simulation and field measurement are used to conduct in-depth research on the deformation of the retaining structure caused by the excavation and dewatering of the foundation pit. The results show that considering the coupled effect of dewatering in the foundation pit, the energy method based on elastic theory is more accurate in solving the deformation of the retaining pile. By comparing and analyzing the theoretical calculation results, numerical analysis results, and field measurement values, we found that the numerical laws of the three are basically the same. Simplified calculations that only consider rotational deformation and ignore the translational deformation of the wall lead to large deviations between the theoretical calculation results and the measured values of the wall bottom deformation. In order to reduce the deviation between numerical results and measured values, the construction of the foundation pit should strictly adopt measures such as “sectional excavation, avoiding peripheral loads, and optimizing construction deployment”, strengthen construction monitoring, and reduce the impact on the deformation of the retaining pile. The maximum deformation growth rate k (ΔSmax/Δ) of the retaining pile decreases approximately exponentially with the increase of the structural stiffness parameters (E and I) and the embedment ratio within a certain range. The sensitivity analysis of the lateral displacement of the retaining pile to different geological parameters is conducted, and the sensitivity factors of the geological parameters to the deformation of the retaining structure are obtained, namely the maximum internal friction angle, followed by the cohesion, and the elastic modulus is the smallest. Based on the original design plan, an optimization of the excavation design is proposed by reducing the stiffness of the support structure. Therefore, the research findings in this paper have significant theoretical and practical implications for the engineering design of excavation projects located in fault zones. By optimizing the excavation support system, not only can standardized construction procedures be achieved, but also investment costs can be reduced, and construction time shortened, which fully aligns with the current safety, economic, and sustainable design principles of excavation projects aiming to conserve resources.
Mapping China’s Changing Gross Domestic Product Distribution Using Remotely Sensed and Point-of-Interest Data with Geographical Random Forest Model
Authors: Deng Fuliang , Cao Luwei , Li Fangzhou , Li Lanhui , Man Wang , Chen Yijian , Liu Wenfeng , Peng Chaofeng
Published: May 2023

Accurate knowledge of the spatiotemporal distribution of gross domestic product (GDP) is critical for achieving sustainable development goals (SDGs). However, there are rarely continuous multitemporal gridded GDP datasets for China in small geographies, and less is known about the variable importance of GDP mapping. Based on remotely sensed and point-of-interest (POI) data, a geographical random forest model was employed to map China’s multitemporal GDP distribution from 2010 to 2020 and to explore the regional differences in the importance of auxiliary variables to GDP modeling. Our new GDP density maps showed that the areas with a GDP density higher than 0.1 million CNY/km2 account for half of China, mainly distributed on the southeast side of the Hu-line. The proportion of the areas with GDP density lower than 0.05 million CNY/km2 has decreased by 11.38% over the past decade and the areas with an increase of 0.01 million CNY/km2 account for 70.73% of China. Our maps also showed that the GDP density of most nonurban areas in northeast China declined, especially during 2015–2020, and the barycenter of China’s GDP moved 128.80 km to the southwest. These results indicate China’s achievements in alleviating poverty and the widening gaps between the South and the North. Meanwhile, the number of counties with the highest importance score for POI density, population density, and nighttime lights in GDP mapping accounts for 52.76%, 23.66%, and 23.56%, respectively, which suggests that they play a crucial role in GDP mapping. Moreover, the relationship between GDP and auxiliary variables displayed obvious regional differences. Our results provide a reference for the formulation of a sustainable development strategy.
Robustness of Consensus of Two-Layer Ring Networks
Authors: Li Zhijun , Gao Haiping , Shang Zhiyong , Zhang Wenming
Published: May 2023

The topology structure of multi-layer networks is highly correlated with the robustness of consensus. This paper investigates the influence of different interlayer edge connection patterns on the consensus of the two-layer ring networks. Two types of two-layer ring network models are first considered: one is a kind of two-layer ring network with two linked edges between layers (Networks-a), and the other is a kind of two-layer ring network with three linked edges between layers (Networks-b). Using the Laplacian spectrum, the consensus of the network model is derived. The simulation experiments are used to demonstrate the influence of different interlayer edge connection patterns on the consensus of networks. To determine the best edge connection pattern for Networks-a and Networks-b, the number of nodes in a single-layer ring network is denoted by n. The best edge connection pattern for Networks-a is 1 & [(n+2)/2]. Furthermore, n is subdivided into 3k,3k+1,3k+2, and the best edge connection patterns of Networks-b are near 1 & k+1 & 2k+1.
The Thermochemical Conversion of Municipal Solid Waste by Torrefaction Process
Authors: Ivanovski Maja , Goričanec Darko , Urbancl Danijela
Published: May 2023

In this work, the thermochemical properties of municipal solid waste (MSW) are studied using the torrefaction process as the main method for investigation. Torrefaction experiments were carried out using an electric laboratory furnace, at temperatures of 200, 250, and 300 °C. The residence time was set to 90 min. Proximate and ultimate analysis were performed on the torrefied MSW samples and compared with the properties of the raw MSW samples. In addition, the thermal properties of the obtained torrefied MSW samples were evaluated by thermogravimetric analysis (TGA) and derivative thermogravimetric analysis (DTG). The following could be stated: the obtained results showed that mass and energy yields (MY and EY, respectively) decrease with increasing when torrefaction temperature, while the heating values (HHV) increased under the same conditions (from 24.3 to 25.1 MJ/kg). Elemental analysis showed an increase in carbon content (C), from 45.7 ± 0.9 to 52.8 ± 1.05 wt.%, and decrease in oxygen content (O), from 45.6 ± 0.9 to 39.5 ± 0.8 wt.%, when torrefaction temperature is increased, which is consistent with the general definition of the torrefaction process. In addition, enhancement factors (EFs) and fuel ratios (FRs) were calculated, which ranged from 1.00 to 1.02 and 0.16 to 0.23, respectively. Some anomalies were observed during the thermal analysis, which are assumed to be related to the composition of the selected MSW. This study therefore shows that torrefaction pretreatment can improve the physicochemical properties of raw MSW to a level comparable to coal, and could contribute to a better understanding of the conversion of MSW into a valuable, solid biofuel.
Chagas Disease Diagnostic Testing in Two Academic Hospitals in New Orleans, Louisiana: A Call to Action
Authors: Proaño Alvaro , Dumonteil Eric , Herrera Claudia
Published: May 2023

Chagas disease, caused by the protozoa parasite Trypanosoma cruzi, is an anthropozoonosis that represents a major public health problem in the Americas, affecting 7 million people with at least 65 million at risk. We sought to assess the intensity of disease surveillance based on diagnostic test requests from hospitals in New Orleans, Louisiana. We extracted information from send-out labs at two major tertiary academic hospitals in New Orleans, Louisiana, USA, from 1 January 2018 to 1 December 2020. We found that in these three years there were 27 patients for whom Chagas disease testing was ordered. Most of these patients were male (70%), with a median age of 40 years old, and their most common ethnical background was Hispanic (74%). These findings demonstrate undertesting of this neglected disease in our region. Given the low Chagas disease surveillance, we need to increase awareness, health promotion, and education among healthcare workers.
A Review of Rickettsial Diseases Other Than Scrub Typhus in India
Authors: Krishnamoorthi Sivanantham , Goel Shriya , Kaur Jasleen , Bisht Kamlesh , Biswal Manisha
Published: May 2023

Rickettsial diseases (RD) are widely reported all over the world. Scrub typhus (ST) is a major tropical infection which is well documented all over India. Therefore, the index of suspicion of scrub typhus is high among physicians with regard to patients presenting with acute febrile illness (AFI) and acute undifferentiated febrile illness (AUFI) in India. Rickettsial diseases other than ST (non-ST RDs), which include spotted fever group (SFG) rickettsioses and typhus group (TG) rickettsioses are not uncommon in India, but the index of suspicion is not as high as ST unless there is a history of the presence of fever with rashes and/or recent arthropod bites. This review aims to look into the Indian scenario on the epidemiology of non-ST RDs, especially the SFG and TG rickettsioses based on various investigations, spectrum of clinical presentation, challenges and gaps in knowledge to suspect and diagnose these infections.
Understanding Understanding, the Foundation of Interreligious Dialogue
Authors: McGann Dominic
Published: May 2023

This paper seeks to explore the academic approach to interreligious dialogue by outlining some key features of what the author sees as its philosophical foundation: understanding. It argues that understanding what it is to understand is crucial to developing interreligious dialogue because, at its core, the goal of such dialogue is the exchange of differing religious understandings for mutual benefit. Thus, the author contends that a thorough academic perspective on interreligious dialogue can only be established if a robust account of understanding is first constructed. Having addressed this, the author outlines three key features of understanding: subjectivity, internality, and appreciation of the whole. Following this, a curious aspect of the generation of new understanding is explored, namely the seeming link between leisure, the absence of so-called “servile” work, and the generation of new insights. Whilst this collection of key features is by no means exhaustive, this paper seeks only to open a conversation on the nature of understanding that has been noticeably absent from philosophical and theological discussion in recent years. Given this, the author hopes to open avenues through which others might critique, explore, or add to the features identified in this article in order to expand the neglected field of the Philosophy of Understanding.
A Stylistic Study of Situational Elements in Selected American Creeds
Authors: Hameed Mahmoud Ayad , Husein Abd Fatah Alyaa
Published: May 2023

The study is intended to stylistically analyze a sample of three American military creeds. The study hypothesizes that American military creeds have their own stylistic properties which make them distinct texts, and that the stylistic devices employed in military creeds vary in terms of their frequencies and functions. The study also hypothesizes that military creeds are situationally based, and that the employed stylistic devices have a complementary role. They all contribute together to fulfill the creeds’ aims and convey their intended messages. To achieve the aims of the study, and verify its hypotheses, two types of procedure are followed: theoretical and practical. The theoretical part consists of presenting a theoretical framework of style and stylistics including their historical background, types, approaches, models of analysis, etc. Another theoretical framework is also presented about military discourse and creeds including their historical background, terminology, features, etc. On the other hand, the practical part consists of selecting a sample of three military creeds and analyzing them in the light of Crystal and Davy’s (1969) model which accounts for situational elements. The adopted model consists of five dimensions: individuality, discourse, status, modality, and singularity. The results of analysis show that military creeds have their own distinctive stylistic features. The results also show that the stylistic devices characterizing military creeds have a complementary role in that they all contribute together to achieve the creeds’ aims and convey their intended messages.