bluuebunny/crossref_metadata_2025 huggingface dataset:
A Kalman Filter Scheme for the Optimization of Low-Cost Gas Sensor Measurements
Authors: Christakis Ioannis , Tsakiridis Odysseas , Kandris Dionisis , Stavrakas Ilias
Published: December 2023

Air pollution, which is mainly caused by industrialization, intensive transportation, and the heating of buildings, is one of the most important problems in large cities because it seriously harms the health and the quality of life of their citizens. This is why air quality is monitored not only by governmental organizations and official research institutions through the use of sophisticated monitoring systems but also by citizens through the use of low-cost air quality measurement devices. However, the reliability of the measurements derived from low-cost sensors is questionable, so the measurement errors must be eliminated. This study experimentally investigated the impact of the use of a Kalman filter on the accuracy of the measurements of low-cost air quality sensors. Specifically, measurements of air pollutant gases were carried out in the field in real ambient air conditions. This study demonstrates not only the optimization of the measurements through the application of a Kalman filter but also the behavior of the filter coefficients and their impact on the predicted values.
Exploring the Landscape of AI-SDN: A Comprehensive Bibliometric Analysis and Future Perspectives
Authors: Sahran Firdaus , Altarturi Hamza H. M. , Anuar Nor Badrul
Published: December 2023

The rising influence of artificial intelligence (AI) enables widespread adoption of the technology in every aspect of computing, including Software-Defined Networking (SDN). Technological adoption leads to the convergence of AI and SDN, producing solutions that overcome limitations present in traditional networking architecture. Although numerous review articles discuss the convergence of these technologies, there is a lack of bibliometric trace in this field, which is important for identifying trends, new niches, and future directions. Therefore, this study aims to fill the gap by presenting a thorough bibliometric analysis of AI-related SDN studies, referred to as AI-SDN. The study begins by identifying 474 unique documents in the Web of Science (WoS) database published from 2009 until recently. The study uses bibliometric analysis to identify the general information, countries, authorship, and content of the selected articles, thereby providing insights into the geographical and institutional landscape shaping AI-SDN research. The findings provide a robust roadmap for further investigation in this field, including the background and taxonomy of the AI-SDN field. Finally, the article discusses several challenges and the future of AI-SDN in academic research.
New Method for Logarithmic Analogue-to-Digital Conversion Using Switched Capacitors with a Variable Logarithmic Base
Authors: Mychuda Zynoviy , Mykyichuk Mykola , Zhuravel Igor , Mychuda Lesia , Szcześniak Adam , Szcześniak Zbigniew
Published: December 2023

This article is devoted to the development of a new method of logarithmic analogue-to-digital conversion using switched capacitors with a variable logarithmic base. The essence of the method and its implementation are presented. Mathematical models have been developed, analysis has been carried out and errors have been assessed. It has been demonstrated that the developed converters, using the proposed method, significantly outperform known analogous converters: for input voltages ranging from 1 mV to 10 V, the processing error does not exceed 0.001% with a processing time not greater than 105 µs (microseconds).
PhishTransformer: A Novel Approach to Detect Phishing Attacks Using URL Collection and Transformer
Authors: Asiri Sultan , Xiao Yang , Li Tieshan
Published: December 2023

Phishing attacks are a major threat to online security, resulting in millions of dollars in losses. These attacks constantly evolve, forcing the cyber security community to improve detection systems. One major problem with current detection systems is that they cannot detect new phishing attacks, such as Browser in the Browser (BiTB) and malvertising attacks. These attacks hide behind legitimate Uniform Resource Locators (URLs) and can evade detection systems that only analyze a web page URL without exploring the page content. To address this problem, we propose PhishTransformer, a deep-learning model that can detect phishing attacks by analyzing URLs and page content. We propose only using URLs embedded within a webpage, such as hyperlinks and JFrames, to train PhishTransformer. This helps reduce the number of features that need to be extracted from the page content, which makes training the model more efficient. PhishTransformer combines convolutional neural networks and transformer encoders to extract features from website URLs and page content. These features are then used to train a classifier that can distinguish between phishing attacks and legitimate websites. We tested PhishTransformer on a dataset of 10,000 URLs. Our results show that PhishTransformer can achieve an F1-score of 99%, precision of 99%, and recall of 99%. This result suggests that PhishTransformer is a promising new approach to phishing detection.
SitPAA: Sitting Posture and Action Recognition Using Acoustic Sensing
Authors: Qu Yanxu , Gao Wei , Liu Chao
Published: December 2023

The technologies associated with recognizing human sitting posture and actions primarily involve computer vision, sensors, and radio frequency (RF) methods. These approaches often involve handling substantial amounts of data, pose privacy concerns, and necessitate additional hardware deployment. With the emergence of acoustic perception in recent times, acoustic schemes have demonstrated applicability in diverse scenarios, including action recognition, object recognition, and target tracking. In this paper, we introduce SitPAA, a sitting posture and action recognition method based on acoustic waves. Notably, our method utilizes only a single speaker and microphone on a smart device for signal transmission and reception. We have implemented multiple rounds of denoising on the received signal and introduced a new feature extraction technique. These extracted features are fed into static and dynamic-oriented networks to achieve precise classification of five distinct poses and four different actions. Additionally, we employ cross-domain recognition to enhance the universality of the classification results. Through extensive experimental validation, our method has demonstrated notable performance, achieving an average accuracy of 92.08% for posture recognition and 95.1% for action recognition. This underscores the effectiveness of our approach in providing robust and accurate results in the challenging domains of posture and action recognition.
YOLOv8-CGRNet: A Lightweight Object Detection Network Leveraging Context Guidance and Deep Residual Learning
Authors: Niu Yixing , Cheng Wansheng , Shi Chunni , Fan Song
Published: December 2023

The growing need for effective object detection models on mobile devices makes it essential to design models that are both accurate and have fewer parameters. In this paper, we introduce a YOLOv8 Res2Net Extended Network (YOLOv8-CGRNet) approach that achieves enhanced precision under standards suitable for lightweight mobile devices. Firstly, we merge YOLOv8 with the Context GuidedNet (CGNet) and Residual Network with multiple branches (Res2Net) structures, augmenting the model’s ability to learn deep Res2Net features without adding to its complexity or computational demands. CGNet effectively captures local features and contextual surroundings, utilizing spatial dependencies and context information to improve accuracy. By reducing the number of parameters and saving on memory usage, it adheres to a ‘deep yet slim’ principle, lessening channel numbers between stages. Secondly, we explore an improved pyramid network (FPN) combination and employ the Stage Partial Spatial Pyramid Pooling Fast (SimPPFCSPC) structure to further strengthen the network’s capability in processing the FPN. Using a dynamic non-monotonic focusing mechanism (FM) gradient gain distribution strategy based on Wise-IoU (WIoU) in an anchor-free context, this method effectively manages low-quality examples. It enhances the overall performance of the detector. Thirdly, we introduce Unifying Object Detection Heads with Attention, adapting to various input scenarios and increasing the model’s flexibility. Experimental datasets include the commonly used detection datasets: VOC2007, VOC2012, and VisDrone. The experimental results demonstrate a 4.3% improvement in detection performance by the proposed framework, affirming superior performance over the original YOLOv8 model in terms of accuracy and robustness and providing insights for future practical applications.
Applied Research on Electronic Documentation and 3D Product Model Deployment in Production and Assembly Processes
Authors: Kirpes Carl , Sly Dave , Hu Guiping
Published: December 2023

The three-dimensional (3D) product model has become a tool that has transitioned from a legacy instrument, used in design, to an emerging technology applied to production and assembly processes. As this evolution has occurred, the need has developed to understand the value of deploying the 3D product model beyond the design phase. This research answers the question and solves the problem, does electronic documentation inclusive of the 3D product model add to the production workers’ ability to complete the production task? To answer this question, the methods used were that the research team tested how accurately and quickly a production and assembly team could build the product using interactive, electronic documentation, including the 3D product model, as a means to understand the design intent as opposed to printed bills of materials (BOMs) and two-dimensional (2D) paper drawings. The conclusions that can be drawn from this research are that the research found statistically significant improvements in the production throughput time (~10%), reductions in the direct labor hours per unit (~14%), and retained quality levels, when deploying electronic documentation, including the 3D product model, into the production and assembly processes. Through the deployment of the interactive 3D product model electronic documentation to the production floor, the organization also took a step towards creating a digital twin of the produced product and laid a foundation for the further adoption of Industry 4.0 practices. The novelty of the work and the areas where it goes beyond previous efforts in the literature concerns the current body of knowledge that does not demonstrate a repeatable methodology through which industry and other researchers can replicate the experiment on demonstrating economic value when deploying the 3D product model to production and assembly processes. In this paper, the authors aim to build on prior work to demonstrate a repeatable methodology for determining the economic value of 3D product model deployment in production and assembly processes through applied research.
Contemporary Fire Safety Engineering in Timber Structures: Challenges and Solutions
Authors: Zang Xiaowei , Liu Wei , Wu Dali , Pan Xuhai , Zhang Wei , Bian Haitao , Shen Ruiqi
Published: December 2023

As environmental conservation and sustainability gain prominence globally, modern timber structures are receiving increased focus. Nonetheless, the combustible nature of timber raises significant fire safety concerns. This review explores the recent advancements in fire safety engineering for timber structures, emphasizing both contemporary high-rise buildings and historical timber constructions. It covers topics like inherently safer design principles, fire risk prediction, and evacuation methodologies. The review emphasizes the criticality of selecting suitable materials, structural design, firefighting systems, and advanced sensor technologies for early fire detection. Additionally, we analyze and compares various evacuation strategies, offering insights into the challenges and future directions for fire safety in modern timber structures.
In Silico Evaluation of the PCR Performance of Different Tests for Detection of WSSV
Authors: Sánchez-Paz Arturo , Encinas-García Trinidad , Mendoza-Cano Fernando
Published: December 2023

In this study, the primers of different protocols for the detection of White Spot Syndrome Virus (WSSV) were analyzed in silico to evaluate their potential performance in PCR. As with any biological entity, this virus evolves constantly. Thus, this analysis showed that a few primers, including those recommended by the World Organization for Animal Health (WOAH), might mismatch with some isolates of WSSV, specially with isolates more recently sequenced. Furthermore, a set of primers recommended by WOAH, showed the potential to self-dimer and form hairpin loop structures, which could affect the efficiency of PCR, resulting in an inaccurate diagnostic result. From our perspective, and considering the evolutionary trajectory of this virus, it may be time for the WOAH to update the PCR protocols recommended for WSSV detection, which remains as a highly prevalent and lethal virus.
The Optimization of Assay Conditions and Characterization of the Succinic Semialdehyde Dehydrogenase Enzyme of Germinated Tartary Buckwheat
Authors: Yang Yuchan , Liu Jiashang , Li Nan , Guo Yu , Ye Hua , Li Zhanming , Wang Dongxu , Guo Yuanxin
Published: December 2023

In this study, the conditions for optimizing the determination of succinic semialdehyde dehydrogenase (SSADH, EC 1.2.1.79) activity in germinated Tartary buckwheat were investigated. Based on a single-factor test, the effects of temperature, pH, and succinic semialdehyde (SSA) concentration on the enzyme activity of germinated buckwheat SSADH were investigated by using the response surface method, and optimal conditions were used to study the enzymatic properties of germinated buckwheat SSADH. The results revealed that the optimum conditions for determining SSADH enzyme activity are as follows: temperature—30.8 °C, pH—8.7, and SSA concentration—0.3 mmol/L. Under these conditions, SSADH enzyme activity was measured as 346 ± 9.61 nmol/min. Furthermore, the thermal stability of SSADH was found to be superior at 25 °C, and its pH stability remained comparable at pH levels of 7.6, 8.1, and 8.6 in germinated Tartary buckwheat samples; however, a decline in stability was observed at pH 9.1. Cu2+, Co2+, and Ni2+ exhibited an activating effect on SSADH activity in germinating Tartary buckwheat, with Cu2+ having the greatest influence (p < 0.05), which was 1.21 times higher than that of the control group. Zn2+, Mn2+, and Na+ inhibited SSADH activity in germinating Tartary buckwheat, with Zn2+ showing the strongest inhibitory effect (p < 0.05). On the other hand, the Km and Vmax of SSADH for SSA in germinated Tartary buckwheat were 0.24 mmol/L and 583.24 nmol/min. The Km and Vmax of SSADH for NAD+ in germinated Tartary buckwheat were 0.64 mmol/L and 454.55 nmol/min.
Study of the Antioxidant Capacity and Oxidation Products of Resveratrol in Soybean Oil
Authors: Yao Yunping , Yuan Huiping , Chen Chen , Liang Jia , Li Changmo
Published: December 2023

Resveratrol (3,5,4′-trihydroxystilbene), a naturally occurring polyphenol that is widely utilized in functional food due to its antioxidant, anti-inflammatory, anti-cancer and anti-aging properties. In the present study, the antioxidant capacity and oxidation products of resveratrol in soybean oil were investigated. The antioxidant activity of resveratrol was evaluated by employing various in vitro antioxidant assays such as DPPH scavenging activities, ferric reducing abilities (FRAP) and oxygen radical absorbance capacity (ORAC). Furthermore, monitoring the peroxide value and the acid value of soybean oil with the addition of 200–1000 μg/g of resveratrol at 60 and 180 °C. It was found that when the concentration of resveratrol in soybean oil was 600 µg/g, the antioxidant capacity was most effective. Resveratrol and its thermal degradation products were identified using liquid chromatography–mass spectrometry (LC–MS) and gas chromatography–mass spectrometry (GC–MS). There were seven nonvolatile oxidation products with mass-to-charge ratios of 138.03, 171.04, 185.10, 157.03, 436.13, 244.07 and 306.09 kg/C and two volatile oxidation products with mass-to-charge ratios of 100.05 and 158.13 kg/C were identified. The research findings may provide essential information for the development of resveratrol as functional oils in future.
Spatiotemporal Patterns and Socioeconomic Influences on Host Participation in Short-Term Rental Markets: Airbnb in San Francisco
Authors: Sarkar Avijit , Pick James B. , Jabeen Shaista
Published: December 2023

This paper examines spatiotemporal patterns and socioeconomic influences on host participation in Airbnb’s short-term rental (STR) marketplace in San Francisco during the years 2019–2022, a four-year period that spans the COVID-19 pandemic. This provides the motivation for the study to examine how San Francisco’s demographic and socioeconomic fluctuations influenced Airbnb hosts to rent their properties on the platform. To do so, Airbnb property densities, indicators of host participation, are estimated at the census tract level and subsequently mapped in a GIS along with points of interest (POIs) located all over the city. Mapping unveils spatiotemporal patterns and changes in Airbnb property densities, which are also analyzed for spatial autocorrelation using Moran’s I. Clusters and outliers of property densities are identified using K-means clustering and geostatistical methods such as local indicators of spatial association (LISA) analysis. Locationally, San Francisco’s Airbnb hotspots are not located in the city’s core, unlike other major Airbnb markets in metropolitan areas. Instead, such hotspots are in the city’s northeastern neighborhoods around ethnic enclaves, in close proximity to POIs that are frequented by visitors, and have a higher proportion of hotel and lodging employment and lower median household income. A conceptual model posits associations of Airbnb property densities with sixteen demographic, socioeconomic factors, indicators of trust, social capital, and sustainability, along with proximity to points of interest. Ordinary least squares (OLS) regressions reveal that occupation in professional, scientific, and technical services, hotel and lodging employment, proximity to POIs, and proportion of Asian population are the dominant factors influencing host participation in San Francisco’s shared accommodation economy. The occupational influences are novel findings for San Francisco. These influences vary somewhat for two main types of properties—entire home/apartment and private rooms. Implications of these findings are discussed in relation to supply side motivations of Airbnb hosts to participate in San Francisco’s STR marketplace.
Dynamic Changes of Phenolic Composition, Antioxidant Capacity, and Gene Expression in ‘Snow White’ Loquat (Eriobotrya japonica Lindl.) Fruit throughout Development and Ripening
Authors: Zhang Kun , Zhou Jiayun , Song Panhui , Li Xinyu , Peng Xuemei , Huang Yong , Ma Qiaoli , Liang Dong , Deng Qunxian
Published: December 2023

The newly released ‘Snow White’ (SW), a white-fleshed loquat (Eriobotrya japonica Lindl.) cultivar, holds promise for commercial production. However, the specifics of the phenolic composition in white-fleshed loquats, along with the antioxidant substances and their regulatory mechanisms, are not yet fully understood. In this study, we examined the dynamic changes in the phenolic compounds, enzyme activities, antioxidant capacity, and gene expression patterns of SW during the key stages of fruit development and ripening. A total of 18 phenolic compounds were identified in SW, with chlorogenic acid, neochlorogenic acid, and coniferyl alcohol being the most predominant. SW demonstrated a stronger antioxidant capacity in the early stages of development, largely due to total phenolics and flavonoids. Neochlorogenic acid may be the most significant antioxidant contributor in loquat. A decline in enzyme activities corresponded with fruit softening. Different genes within a multigene family played distinct roles in the synthesis of phenolics. C4H1, 4CL2, 4CL9, HCT, CCoAOMT5, F5H, COMT1, CAD6, and POD42 were implicated in the regulation of neochlorogenic acid synthesis and accumulation. Consequently, these findings enhance our understanding of phenolic metabolism and offer fresh perspectives on the development of germplasm resources for white-fleshed loquats.
Deep Learning-Based Steel Bridge Corrosion Segmentation and Condition Rating Using Mask RCNN and YOLOv8
Authors: Ameli Zahra , Nesheli Shabnam Jafarpoor , Landis Eric N.
Published: December 2023

The application of deep learning (DL) algorithms has become of great interest in recent years due to their superior performance in structural damage identification, including the detection of corrosion. There has been growing interest in the application of convolutional neural networks (CNNs) for corrosion detection and classification. However, current approaches primarily involve detecting corrosion within bounding boxes, lacking the segmentation of corrosion with irregular boundary shapes. As a result, it becomes challenging to quantify corrosion areas and severity, which is crucial for engineers to rate the condition of structural elements and assess the performance of infrastructures. Furthermore, training an efficient deep learning model requires a large number of corrosion images and the manual labeling of every single image. This process can be tedious and labor-intensive. In this project, an open-source steel bridge corrosion dataset along with corresponding annotations was generated. This database contains 514 images with various corrosion severity levels, gathered from a variety of steel bridges. A pixel-level annotation was performed according to the Bridge Inspectors Reference Manual (BIRM) and the American Association of State Highway and Transportation Officials (AASHTO) regulations for corrosion condition rating (defect #1000). Two state-of-the-art semantic segmentation algorithms, Mask RCNN and YOLOv8, were trained and validated on the dataset. These trained models were then tested on a set of test images and the results were compared. The trained Mask RCNN and YOLOv8 models demonstrated satisfactory performance in segmenting and rating corrosion, making them suitable for practical applications.
Sentinel Lymph Node Staging in Early-Stage Cervical Cancer: A Comprehensive Review
Authors: Margioula-Siarkou Chrysoula , Almperis Aristarchos , Gullo Giuseppe , Almperi Emmanouela-Aliki , Margioula-Siarkou Georgia , Nixarlidou Eleni , Mponiou Konstantina , Papakotoulas Pavlos , Sardeli Chrysanthi , Guyon Frederic , Dinas Konstantinos , Petousis Stamatios
Published: December 2023

Cervical cancer (CC) continues to be a significant global public health concern, even with preventive measures in place. In women with early-stage CC, the status of lymph nodes is of paramount importance, not only for the final prognosis but also for determining the best therapeutic strategy. According to main international guidelines, pelvic full lymphadenectomy (PLND) is recommended for lymph node staging. However, in these early stages of CC, sentinel lymph node biopsy (SLNB) has emerged as a precise technique for evaluating lymph node involvement, improving its morbidity profile. We performed a literature review through PubMed articles about progress on the application of SLNB in women with early-stage CC focusing on the comparison with PET/CT and PLND in terms of oncological outcomes and diagnostic accuracy. While the superiority of SLNB is clear compared to radiologic modalities, it demonstrates no clear oncologic inferiority over PLND, given the higher detection rate of positive lymph nodes and predominance of no lymph node recurrences. However, due to a lack of prospective evidence, particularly concerning long-term oncological safety, SLNB is not the current gold standard. With careful patient selection and adherence to straightforward protocols, a low false-negative rate can be ensured. The aim of the ongoing prospective trials is to address these issues.
Non-Invasive Imaging Assessment in Patients with Aortic Coarctation: A Contemporary Review
Authors: Leo Isabella , Sabatino Jolanda , Avesani Martina , Moscatelli Sara , Bianco Francesco , Borrelli Nunzia , De Sarro Rosalba , Leonardi Benedetta , Calcaterra Giuseppe , Surkova Elena , Di Salvo Giovanni ,   on behalf of the Working Group on Congenital Heart Disease, Cardiovascular Prevention in Paediatric Age of the Italian Society of Cardiology (SIC)
Published: December 2023

Coarctation of the aorta (CoA) is a congenital abnormality characterized by a narrowing of the aortic lumen, which can lead to significant morbidity and mortality if left untreated. Even after repair and despite significant advances in therapeutic management, these patients have overall reduced long-term survival due to the consequences of chronic afterload increase. Cardiovascular imaging is key from the first diagnosis to serial follow-up. In recent years, novel imaging techniques have emerged, increasing accessibility to advanced imaging modalities and enabling early and non-invasive identification of complications after repair. The aim of this paper is to provide a comprehensive review of the role of different imaging techniques in the evaluation and management of patients with native or repaired CoA, highlighting their unique strengths and limitations.
Keratosis Pilaris-like Eruption during Treatment of Chronic Myeloid Leukemia with Tyrosine Kinase Inhibitors: Literature Review and Report of a Case Related to Imatinib
Authors: Ambrogio Francesca , Poli Melita Anna , Lospalluti Lucia , Lettini Teresa , Cassano Nicoletta , Vena Gino Antonio , Ingravallo Giuseppe , Cazzato Gerardo , Foti Caterina
Published: December 2023

The advent of tyrosine kinase inhibitors (TKIs) blocking BCR-ABL activity has revolutionized the therapeutic management of patients with chronic myeloid leukemia (CML). Adverse cutaneous reactions (ACRs) are common nonhematologic adverse events associated with the use of BCR-ABL TKIs. A characteristic pattern of eruption resembling keratosis pilaris (KP) has been described in patients treated with these drugs, especially nilotinib and dasatinib. The pathogenesis of this ACR is still unknown. This type of reaction appears to be uncommon with imatinib. Here, we report the case of an elderly patient with an asymptomatic KP-like eruption, which appeared one month after starting treatment with imatinib for CML. The case presentation is accompanied by a review of similar reactions in patients with CML treated with BCR-ABL inhibitors, attempting to make an excursus on the molecular targets of such drugs and possible mechanisms underlying this ACR.
Cell Reprogramming and Differentiation Utilizing Messenger RNA for Regenerative Medicine
Authors: Inagaki Masahito
Published: December 2023

The COVID-19 pandemic generated interest in the medicinal applications of messenger RNA (mRNA). It is expected that mRNA will be applied, not only to vaccines, but also to regenerative medicine. The purity of mRNA is important for its medicinal applications. However, the current mRNA synthesis techniques exhibit problems, including the contamination of undesired 5′-uncapped mRNA and double-stranded RNA. Recently, our group developed a completely capped mRNA synthesis technology that contributes to the progress of mRNA research. The introduction of chemically modified nucleosides, such as N1-methylpseudouridine and 5-methylcytidine, has been reported by Karikó and Weissman, opening a path for the practical application of mRNA for vaccines and regenerative medicine. Yamanaka reported the production of induced pluripotent stem cells (iPSCs) by introducing four types of genes using a retrovirus vector. iPSCs are widely used for research on regenerative medicine and the preparation of disease models to screen new drug candidates. Among the Yamanaka factors, Klf4 and c-Myc are oncogenes, and there is a risk of tumor development if these are integrated into genomic DNA. Therefore, regenerative medicine using mRNA, which poses no risk of genome insertion, has attracted attention. In this review, the author summarizes techniques for synthesizing mRNA and its application in regenerative medicine.
CO2 Marine Transportation from a Techno-Energetic Perspective
Authors: Pérez-Bódalo Eduardo , d’Amore-Domenech Rafael , Leo Teresa J.
Published: December 2023

CCUS (Carbon Capture, Utilization, and Storage) is a cornerstone of most proposed carbon dioxide (CO2) emissions strategies, as it is necessary to keep atmospheric CO2 concentrations below 450 parts per million by the year 2100 and, as such, prevent global warming. The Intergovernmental Panel on Climate Change (IPCC) predicts a removal capacity of 12 GtCO2/yr by 2050, whereas the present capability is 41 MtCO2/yr. Decarbonization may not be able to proceed quickly enough to reach net-zero emissions without CCUS technologies. In the maritime sector, CCUS serves a dual purpose: capturing CO2 from fossil fuel combustion and transporting the captured CO2 for its storage or utilization. This paper examines the importance of vessels as liquid CO2 carriers, emphasizing the transportation conditions associated with CO2. A techno-energetic analysis is carried out by studying various combinations of temperature and pressure. From a transport viewpoint, the findings indicate that reducing CO2 pressure is more cost-effective. In terms of pre-processing, higher CO2 pressures may lead to energy and, potentially, cost savings. However, the optimal pressure in the entire logistical chain remains uncertain. Further research is advised to broaden the scope of the chain to be analyzed.
Improvement in Spatiotemporal Chl-a Data in the South China Sea Using the Random-Forest-Based Geo-Imputation Method and Ocean Dynamics Data
Authors: Li Ao , Shao Tiantai , Zhang Zhen , Fang Weiwei , Li Wenjie , Xu Jinrun , Jiang Yujie , Shu Chan
Published: December 2023

The accurate estimation of the spatial and temporal distribution of chlorophyll-a (Chl-a) concentrations in the South China Sea (SCS) is crucial for understanding marine ecosystem dynamics and water quality assessment. However, the challenge of missing values in satellite-derived Chl-a data has hindered obtaining complete spatiotemporal information. Traditional methods for deriving Chl-a are based on the modeling of measured sensor data and in situ measurements. Spatiotemporal imputation of Chl-a is difficult due to the inaccessibility of the measured Chl-a. In this study, we introduce an innovative approach that incorporates an ocean dynamics dataset and utilizes the random forest algorithm for predicting the Chl-a concentration in the SCS. The method combines the spatiotemporal feature pattern of Chl-a and the main influencing factors, and it introduces ocean dynamics data, which has a high correlation with the spatiotemporal distribution of Chl-a, as the input data through feature engineering. Also, we compared Random Forest (RF) with other Machine Learning (ML) methods. The results show that (1) ocean dynamics datasets can provide important data support for Chl-a imputation by capturing the impact of dynamical processes on ecological roles in the South China Sea. (2) The RF method is the superior imputation method for the reconstruction of Chl-a in the South China Sea, with better model performance and smaller errors. This study provides valuable insight for researchers and practitioners in choosing suitable machine learning methods for the imputation of the Chl-a concentration in the SCS, facilitating a better understanding of the region’s marine ecosystems and supporting effective environmental management.
Compassion Fatigue in Chimpanzee (Pan troglodytes) Caregivers: Prevalence, Contributing Factors, and Coping Mechanisms
Authors: Leinwand Jesse G. , Vale Gillian L.
Published: December 2023

Compassion fatigue (CF) refers to the exhaustion and distress caused by the demands of caring for others. CF occurs in a variety of helping professions, including physicians, nurses, educators, social workers and animal caregivers, and is known to adversely impact both caregivers’ quality of life and the care they provide. This study assessed the prevalence, risk and protective factors, coping strategies and support programs for CF in chimpanzee caregivers (N = 123) at accredited sanctuaries and zoos in the United States. Online survey results revealed that 91.06% of chimpanzee caregivers experienced CF at some point in their careers. Common CF symptoms were exhaustion, frustration, anxiety, depression, and apathy. Perceived factors influencing CF included being understaffed, lacking resources and training, poor relationships with coworkers and supervisors, and financial insecurity. Commonly reported coping strategies were talking to someone, having pets, self-care, and getting away from work. 20.33% of caregivers reported having institutional support programs available to them, however they were rarely viewed as helpful and 32.52% of respondents were unsure about program availability. Overall, our findings suggest that, like other caregiving professionals, chimpanzee caregivers are susceptible to CF and may benefit from new or updated support programs that continue to build a ‘culture of care’ that meets employee, animal, and facility needs.
Factors Influencing Livelihood Resilience of Households Resettled from Coal Mining Areas and Their Measurement—A Case Study of Huaibei City
Authors: Wang Peijun , Wang Jing , Zhu Chunbo , Li Yan , Sun Weijun , Li Jinyi
Published: December 2023

The application of livelihood resilience theory to villages that have been resettled due to coal mining provides insights into the levels and impediments of livelihood resilience under different resettlement models. Such an exploration holds critical significance for enhancing the livelihood resilience of the resettled households and promoting sustainable development in coal mining areas. Grounded in the theoretical framework of livelihood resilience and considering the realities of mining areas, by referring to existing studies, this study devises an evaluative index system. Utilizing the TOPSIS model to calculate the level of livelihood resilience, and we delve into the impediments to livelihood resilience of households that resettled under different models using the obstacle model. The results indicate the following: (1) Overall, the level of livelihood resilience in areas resettled due to coal mining of Huaibei City is low. Significant disparities exist among the households resettled under different models in terms of buffering capacity, self-organizing ability, and learning ability. (2) Factors such as the quantity of labor, policy awareness, and participation in village collective meetings significantly influence households’ livelihood resilience, albeit to varying degrees across different resettlement models. (3) Future interventions should address the challenges faced by the four types of resettled households by increasing employment opportunities, intensifying policy advocacy, and augmenting investments in education resources to elevate the livelihood standards of various households.
Transformation of Buildings and Urban Spaces to Adapt for Future Mobility: A Systematic Literature Review
Authors: Park Sang-Jun , Kim Ju-Hyung , Maing Min-Jung , Ahn Jin-Ho , Kim Yang-Gil , Ham Nam-Hyuk , Kim Jae-Jun
Published: December 2023

The development of smart cities has led to transforming modern city operations by applying emerging technologies from the fourth industrial revolution such as the Internet of Things, BIM and machine learning. To prepare for the future development of cities, it is necessary to investigate the current status of city development, research topics and the direction toward future cities. In this study, a systematic literature review was conducted following the combination of literature review guides by Kitchenham and the PRISMA statement. The review identified 141 peer-reviewed academic papers from web-based archives, such as Web of Science and SCOPUS, that were categorized into five topics related to smart cities and urban areas. The technologies applied in the research were analyzed to determine the direction future cities should take based on current smart cities and emerging technologies that will shape individuals’ daily lives. However, it was discovered that research papers on critical areas, such as mobility and management, were lacking compared to those on building design and urban planning. This paper concludes with an example of a future urban area that has been transformed due to adoption of future mobility technology to address the shortcomings of the reviewed literature on building and urban environments.
ChatGPT and L2 Written Communication: A Game-Changer or Just Another Tool?
Authors: Zadorozhnyy Artem , Lai Wan Yee Winsy
Published: December 2023

The development of English language written communication skills across many contexts has been hindered by factors such as examination-oriented cultures, anxiety associated with both oral and written communication, limited opportunities for engaging in authentic communication, and a lack of individualized, personalized feedback. Multiple studies throughout the last decade have explored chatbot integration as a means to address these issues and enhance students’ language learning toolkits. This paper delves into the potential benefits and roles of advanced Generative AI (GenAI) chatbots (e.g., ChatGPT) in enhancing second language (L2) communicative practices. We evaluate findings associated with various types of chatbots and present pedagogical strategies for their application of GenAI in both in-class and out-of-class spaces to support students’ language learning experiences. We also propose future research directions, emphasizing the necessity to explore the ethical use of AI tools, their impact on L2 communication, and the comparative effectiveness of retrieval-based and GenAI-powered chatbots in language education.
The Effect of Replacing Ni with Mn on the Microstructure and Properties of Al2O3-Forming Austenitic Stainless Steels: A Review
Authors: Chen Guoshuai , Du Shang , Zhou Zhangjian
Published: December 2023

Al2O3-forming austenitic steel (AFA steel) is an important candidate material for advanced reactor core components due to its excellent corrosion resistance and high temperature strength. Al is a strong ferrite-forming element. Therefore, it is necessary to increase the Ni content to stabilize austenite. Ni is expensive and highly active, and so increasing the Ni content not only increases the costs but also damages the radiation resistance. Mn is a low-cost austenitic stable element. Its substitution for Ni will not only help to improve the irradiation resistance of austenitic steel, but also reduce the cost. In order to explore the feasibility of Mn-substituted Ni-stabilized austenite in AFA steel, this paper summarized the research progress of Mn-added AFA steels, whilst the research status of traditional Mn-added austenitic steels are also referred to and compared herein. The effect of the addition of Mn on the microstructure and properties of AFA steel was analyzed. The results show that Mn can promote the precipitation of the M23C6 phase and inhibit the precipitation of the B2-NiAl phase and secondary NbC phase. With the increase in Mn content, the strength of AFA steel at room temperature and high temperature decreased slightly, the room temperature elongation increased slightly, while the high temperature elongation and creep resistance decreased obviously. In addition, for austenitic steel free of Al, the addition of Mn will destroy the oxide layer of Cr2O3, which will decrease the oxidation resistance of the steel. But the preliminary study shows that Mn has little effect on the Al2O3 oxide layer. It is worth studying the effect of Mn-substituted Ni on the oxidation resistance of AFA steel. In summary, more efforts are necessary to investigate the optimal Mn content to balance the advantages and disadvantages of introducing Mn instead of Ni.
A Novel Superhard, Wear-Resistant, and Highly Conductive Cu-MoSi2 Coating Fabricated by High-Speed Laser Cladding Technique
Authors: Li Yanmiao , Zhao Xiaojun , Zhai Pengyuan , Fan Pengyu , Xu Jiahui , Xu Yuefan , Yu Zengkai , Li Muyang , Zhang Yongtong , Gao Dawei , Liu Sainan , Cai Zhenyang , Xiao Lairong
Published: December 2023

The pursuit of an advanced functional coating that simultaneously combines high hardness, wear resistance, and superior electrical conductivity has remained an elusive goal in the field of copper alloy surface enhancement. Traditional solid solution alloying methods often lead to a significant increase in electron scattering, resulting in a notable reduction in electrical conductivity, making it challenging to achieve a balance between high hardness, wear resistance, and high conductivity. The key lies in identifying a suitable microstructure where dislocation motion is effectively hindered while minimizing the scattering of conductive electrons. In this study, a novel Cu-MoSi2 coating was successfully fabricated on a CuCrZr alloy surface using the coaxial powder feeding high-speed laser cladding technique, with the addition of 10–30% MoSi2 particles. The coating significantly enhances the hardness and wear resistance of the copper substrate while maintaining favorable electrical conductivity. As the quantity of MoSi2 particles increases, the coating’s hardness and wear resistance gradually improve, with minimal variance in conductivity. Among the coatings, the Cu-30%MoSi2 coating stands out with the highest hardness (974.5 HV0.5) and the lowest wear amount (0.062 mg/km), approximately 15 times the hardness of the copper base material (65 HV0.5) and only 0.45% of the wear amount (13.71 mg/km). Additionally, the coating exhibits a resistivity of 0.173 × 10−6 Ω·m. The extraordinary hardness and wear resistance of these coatings can be attributed to the dispersion strengthening effect of MoxSiy particles, while the high electrical conductivity is due to the low silicon content dissolved into the copper from the released MoSi2 particles, as well as the rapid cooling rates associated with the high-speed laser cladding process.
Aging Process of Biocomposites with the PLA Matrix Modified with Different Types of Cellulose
Authors: Szatkowski Piotr , Gralewski Jacek , Suchorowiec Katarzyna , Kosowska Karolina , Mielan Bartosz , Kisilewicz Michał
Published: December 2023

In the modern world, many products are disposable or have a very short lifespan, while at the same time, those products are made from materials that will remain in the environment in the form of waste for hundreds or even thousands of years. It is a serious problem; non-biodegradable polymer wastes are part of environmental pollution and generate microplastics, which accumulate in the organisms of living beings. One of the proposed solutions is biodegradable polymers and their composites. In our work, three types of polylactide-based composites with plant-derived fillers: microcellulose powder, short flax fibers, and wood flour at 2 wt.% were prepared. Poly(lactic acid) (PLA)-based biocomposite properties were characterized in terms of mechanical and surface properties together with microscopic analysis and Fourier-transform infrared spectroscopy (FTIR), before and after a UV (ultraviolet)-light-aging process to determine the effects of each cellulose-based additive on the UV-induced degradation process. This research shows that the addition of a cellulose additive can improve the properties of the material in terms of the UV-aging process, but the form of the chosen cellulose form plays a crucial role in this case. The testing of physicochemical properties demonstrated that not only can mechanical properties be improved, but also the time of degradation under UV light exposure can be controlled by the proper selection of the reinforcing phase and the parameters of the extrusion and injection molding process. The obtained results turned out to be very interesting, not only in terms of the cost reduction of the biocomposites themselves, as mainly the waste from the wood industry was used as a low-cost filler, but also that the additive delays the aging process occurring during UV light exposure. Even a small, 2 wt.% addition of some of the tested forms of cellulose delayed surface degradation, which is one of the most important factors affecting the biodegradation process.
Adsorption of Polyetheramine-230 on Expansive Clay and Structure Properties Investigation
Authors: Qiu Yu , Lu Zheng , Yan Tingzhou , Li Jian , Hu Haixiang , Yao Hailin
Published: December 2023

Polyetheramine (PEA) is a swelling inhibitor used to address engineering challenges arising from the interaction between montmorillonite (Mt) and water. This study comprehensively investigates the adsorption characteristics of PEA on three representative expansive clay samples: Na-Mt, Ca-Mt, and engineered expansive soil. Additionally, the desorption of exchangeable ions is examined. The findings reveal that a two-stage adsorption kinetic model and a pseudo-second-order kinetic model can properly describe the adsorption kinetics of PEA on expansive clays. PEA exhibits a strong capacity for ion exchange with sodium ions, while the exchange capacity for calcium ions is limited. Both protonated and non-protonated PEA contribute to rapid adsorption processes. The adsorption isotherms are well-fitted by the Langmuir and Freundlich models, with the Langmuir model being reasonable. At lower equilibrium concentrations, a higher proportion of the adsorption amount is attributed to ion exchange compared to higher equilibrium concentrations. Ion exchange emerges as the primary factor contributing to the adsorption of PEA on Na-Mt, whereas the adsorption of PEA on Ca-Mt and expansive soil is primarily attributed to physical adsorption by non-protonated PEA. X-ray diffraction results reveal significant intercalation effects of PEA as they penetrate the interlayer space and hinder interlayer ion hydration. Fourier transform infrared spectrum results demonstrate that the adsorption of PEA minimally impacts the framework of Mt structural units but primarily reduces the adsorbed water content. Clay-PEA composites exhibit a decreased affinity for water. Zeta potential experiments indicate that the adsorption of PEA significantly diminishes the surface potential of clay-PEA composite particles, effectively inhibiting their hydration dispersion.