bluuebunny/crossref_metadata_2025 huggingface dataset:
A Polarization-Based Method for Maritime Image Dehazing
Authors: Ma Rui , Zhang Zhenduo , Zhang Shuolin , Wang Zhen , Liu Shuai
Published: May 2024

The accurate identification of target imagery in the presence of sea fog is essential for the precise detection and comprehension of targets situated at sea. To overcome the issues encountered when applying traditional polarimetric dehazing methods to sea fog imagery, this paper proposes an improved polarimetric dehazing method. Initially, the methodology employs quartile-based selection on polarization difference images to ascertain atmospheric light at an infinite distance. Subsequently, the study describes a segmentation approach for sea–sky background images based on the degree of polarization. The results show that the image information entropy of the segmentation process improves by more than 6% compared to that of alternative methodologies, and the local contrast of the image is increased by more than 30% compared to that of the original foggy image. These outcomes confirm the effectiveness of the proposed dehazing methodology in addressing the challenges associated with sea fog imagery.
Micro- and Nano-Pollutants from Tires and Car Brakes Generated in the Winter Season in the Poznan City Urban Environment
Authors: Przekop Robert E. , Sztorch Bogna , Pakuła Daria , Romańczuk-Ruszuk Eliza , Konieczna Roksana , Frydrych Miłosz
Published: May 2024

This research, focusing on the environmental impact of tire and brake disc pad wear, constitutes a significant area of transport-related studies. These two key vehicle components are not only the most frequently worn but also generate micro- and nano-pollutants (i.e., rubber, metal oxides) that potentially harm the environment. Over half of the globally produced natural and synthetic rubbers, which amounted to about 30 million tons in 2022, are used for tire production. This work focuses on the study of roadside snow, sand, and standing water deposits from various locations in the urban agglomeration (Poznań, Poland) during the winter season, determining their qualitative composition and the quantitative content of pollutants originating from tire abrasion. In addition, the method of washing nano- and micro-rubber particles and their full characteristics was also presented. Fourier-transform infrared (FT-IR) and nuclear magnetic resonance (NMR) spectroscopic studies, optical and scanning electron microscopy (SEM-EDS), particle size studies using a dynamic light scattering (DLS) particle analyzer, and thermogravimetric analysis (TGA) were conducted for a detailed characterization of the pollutants in the environment. The conducted particle separation methods allowed for the extraction of a fraction mainly containing gum residues with particle sizes less than 2 µm. The results of these tests make it possible to estimate the level of contamination with rubber and metal residues during the abrasion of tires, pads, and brake discs while driving, which is crucial for understanding the impact of vehicle part exploitation on the environment.
Study of Biocomposite Films Based on Cassava Starch and Microcrystalline Cellulose Derived from Cassava Pulp for Potential Medical Packaging Applications
Authors: Jeencham Rachasit , Chiaoketwit Nantawat , Numpaisal Piya-on , Ruksakulpiwat Yupaporn
Published: May 2024

This study aimed to develop biocomposite films based on cassava starch and microcrystalline cellulose (MCC) derived from cassava pulp for potential medical packaging applications. MCC was extracted from cassava pulp, and its structure and chemical composition, crystallinity, and thermal properties were characterized. The MCC showed a yield of 14.92% and crystallinity of 46.91%. Different MCC contents (1%, 3%, and 5% w/w of starch) were incorporated into cassava starch films. The effects of MCC contents on film properties, including morphology, thickness, mechanical strength, chemical interactions, moisture content, surface wettability, and water activity index, were studied. The effects of UV-C sterilization on the disinfection of starch/MCC on film properties were determined. Results showed that all starch/MCC films exhibited good transparency and thickness ranging from 127 to 144 µm. As MCC content increased from 1 to 5%, Young’s modulus and tensile strength of the films improved significantly from 112.12 to 488.89 MPa and 3.21 to 11.18 MPa, respectively, while elongation at break decreased from 44.74 to 4.15%. Incorporating MCC also reduced film surface wettability, with the water contact angle increasing from 69.17° to 102.82°. The starch/3%MCC holds promise as a biocomposite film for medical packaging applications, offering advantages in terms of good transparency, mechanical properties, and surface hydrophobicity. Furthermore, the absence of microbial growth in the sterilized gauze pad with sealing in the sterilized starch/3%MCC film confirms that the UV-C sterilization, 30 min for each side at 254 nm effectively eliminated any microorganisms present on the starch/3%MCC film without damaging the film properties. This finding highlights a reliable approach to ensuring the sterility of starch/MCC films for medical packaging applications.
Genetic Engineering of Filamentous Fungi: Prospects for Obtaining Fourth-Generation Biological Products
Authors: Oliveira Lorena Resende , Gonçalves Ariany Rosa , Quintela Eliane Dias , Colognese Leandro , Cortes Marcio Vinicius de C. Barros , de Filippi Marta Cristina Corsi
Published: May 2024

Filamentous fungi exhibit unparalleled potential as cell factories for protein production, owing to their adeptness in protein secretion and remarkable proficiency in post-translational modifications. This review delineates the role of filamentous fungi in bio-input technology across different generations and explores their capacity to generate secondary metabolites. Our investigation highlights filamentous fungi as frontrunners in the production of bioactive compounds, emphasizing the imperative nature of elucidating their metabolic repertoire. Furthermore, we delve into common strategies for genetic transformation in filamentous fungi, elucidating the underlying principles, advantages, and drawbacks of each technique. Taking a forward-looking approach, we explore the prospects of genome engineering, particularly the CRISPR-Cas9 technique, as a means to propel protein secretion in filamentous fungi. Detailed examination of the protein secretion pathways in these fungi provides insights into their industrial applications. Notably, extensive research within the scientific community has focused on Aspergillus and Trichoderma species for the industrial production of proteins and enzymes. This review also presents practical examples of genetic engineering strategies aimed at augmenting enzyme secretion in filamentous fungi for various industrial applications. These findings underscore the potential of filamentous fungi as versatile platforms for protein production and highlight avenues for future research and technological advancement in this field.
Correction: de Mazancourt et al. Updated Checklist of the Freshwater Shrimps (Decapoda: Caridea: Atyidae) of Mindoro Island, the Philippines, with a Description of a New Species of Caridina. Arthropoda 2023, 1, 374–397
Authors: de Mazancourt Valentin , Freitag Hendrik , von Rintelen Kristina , Manuel-Santos Marivene , von Rintelen Thomas
Published: May 2024

There was a mistake in Supplementary Table S1 as published in the original publication [...]
Hierarchical Predictions of Fine-to-Coarse Time Span and Atmospheric Field Reconstruction for Typhoon Track Prediction
Authors: Yan Shengye , Zhang Zhendong , Zheng Wei
Published: May 2024

The prediction of typhoon tracks in the Northwest Pacific is key to reducing human casualties and property damage. Traditional numerical forecasting models often require substantial computational resources, are high-cost, and have significant limitations in prediction speed. This research is dedicated to using deep learning methods to address the shortcomings of traditional methods. Our method (AFR-SimVP) is based on a large-kernel convolutional spatio-temporal prediction network combined with multi-feature fusion for forecasting typhoon tracks in the Northwest Pacific. In order to more effectively suppress the effect of noise in the dataset to enhance the generalization ability of the model, we use a multi-branch structure, incorporate an atmospheric reconstruction subtask, and propose a second-order smoothing loss to further improve the prediction ability of the model. More importantly, we innovatively propose a multi-time-step typhoon prediction network (HTAFR-SimVP) that does not use the traditional recurrent neural network family of models at all. Instead, through fine-to-coarse hierarchical temporal feature extraction and dynamic self-distillation, multi-time-step prediction is achieved using only a single regression network. In addition, combined with atmospheric field reconstruction, the network achieves integrated prediction for multiple tasks, which greatly enhances the model’s range of applications. Experiments show that our proposed network achieves optimal performance in the 24 h typhoon track prediction task. Our regression network outperforms previous recurrent network-based typhoon prediction models in the multi-time-step prediction task and also performs well in multiple integration tasks.
Extremal Bicyclic Graphs with Respect to Permanental Sums and Hosoya Indices
Authors: Wu Tingzeng , Bai Yinggang , Xu Shoujun
Published: May 2024

Graph polynomials is one of the important research directions in mathematical chemistry. The coefficients of some graph polynomials, such as matching polynomial and permanental polynomial, are related to structural properties of graphs. The Hosoya index of a graph is the sum of the absolute value of all coefficients for the matching polynomial. And the permanental sum of a graph is the sum of the absolute value of all coefficients of the permanental polynomial. In this paper, we characterize the second to sixth minimal Hosoya indices of all bicyclic graphs. Furthermore, using the results, the second to sixth minimal permanental sums of all bicyclic graphs are also characterized.
First Pangenome of Corynebacterium rouxii, a Potentially Toxigenic Species of Corynebacterium diphtheriae Complex
Authors: Prates Fernanda Diniz , Araújo Max Roberto Batista , Sousa Eduarda Guimarães , Ramos Juliana Nunes , Viana Marcus Vinícius Canário , Soares Siomar de Castro , dos Santos Louisy Sanches , Azevedo Vasco Ariston de Carvalho
Published: May 2024

Corynebacterium rouxii is one of the recently described species of the Corynebacterium diphtheriae complex. As this species can potentially infect different hosts and harbor the tox gene, producing diphtheria toxin, we present its first pangenomic analysis in this work. A total of fifteen genomes deposited in online databases were included. After confirming the taxonomic position of the isolates by genomic taxonomy, the genomes were submitted to genomic plasticity, gene synteny, and pangenome prediction analyses. In addition, virulence and antimicrobial resistance genes were investigated. Finally, epidemiological data were obtained through molecular typing, clustering, and phylogenetic analysis. Our data demonstrated genetic diversity within the species with low synteny. However, the gene content is extensively conserved, and the pangenome is composed of 2606 gene families, of which 1916 are in the core genome and 80 are related to unique genes. Prophages, insertion sequences, and genomic islands were found. A type I-E CRISPR-Cas system was also detected. Besides the tox gene, determinants involved in adhesion and iron acquisition and two putative antimicrobial resistance genes were predicted. These findings provide valuable insight about this species’ pathogenicity, evolution, and diversity. In the future, our data can contribute to different areas, including vaccinology and epidemiology.
Antioxidant and Anti-Inflammatory Properties of Hydrolyzed Royal Jelly Peptide in Human Dermal Fibroblasts: Implications for Skin Health and Care Applications
Authors: Yan Chang-Yu , Zhu Qian-Qian , Guan Cheng-Xi , Xiong Gui-Lan , Chen Xin-Xing , Gong Hai-Biao , Li Jia-Wei , Ouyang Shu-Hua , Kurihara Hiroshi , Li Yi-Fang , He Rong-Rong
Published: May 2024

Hydrolyzed royal jelly peptide (RJP) has garnered attention for its health-promoting functions. However, the potential applications of RJP in skincare have not been fully explored. In this study, we prepared RJP through the enzymatic hydrolysis of royal jelly protein with trypsin and investigated its antioxidant and anti-inflammatory properties on primary human dermal fibroblasts (HDFs). Our results demonstrate that RJP effectively inhibits oxidative damage induced by H2O2 and lipid peroxidation triggered by AAPH and t-BuOOH in HDFs. This effect may be attributed to the ability of RJP to enhance the level of glutathione and the activities of catalase and glutathione peroxidase 4, as well as its excellent iron chelating capacity. Furthermore, RJP modulates the NLRP3 inflammasome-mediated inflammatory response in HDFs, suppressing the mRNA expressions of NLRP3 and IL-1β in the primer stage induced by LPS and the release of mature IL-1β induced by ATP, monosodium urate, or nigericin in the activation stage. RJP also represses the expressions of COX2 and iNOS induced by LPS. Finally, we reveal that RJP exhibits superior antioxidant and anti-inflammatory properties over unhydrolyzed royal jelly protein. These findings suggest that RJP exerts protective effects on skin cells through antioxidative and anti-inflammatory mechanisms, indicating its promise for potential therapeutic avenues for managing oxidative stress and inflammation-related skin disorders.
Paired Primary and Recurrent Rhabdoid Meningiomas: Cytogenetic Alterations, BAP1 Gene Expression Profile and Patient Outcome
Authors: Garrido Ruiz Patricia Alejandra , Rodriguez Álvaro Otero , Corchete Luis Antonio , Zelaya Huerta Victoria , Pasco Peña Alejandro , Caballero Martínez Cristina , González-Carreró Fojón Joaquín , Catalina Fernández Inmaculada , López Duque Juan Carlos , Zaldumbide Dueñas Laura , Mosteiro González Lorena , Astudillo María Aurora , Hernández-Laín Aurelio , Camacho Urkaray Emma Natalia , Viguri Diaz María Amparo , Orfao Alberto , Tabernero María Dolores
Published: May 2024

Rhabdoid meningiomas (RM) are a rare meningioma subtype with a heterogeneous clinical course which is more frequently associated with recurrence, even among tumors undergoing-complete surgical removal. Here, we retrospectively analyzed the clinical-histopathological and cytogenetic features of 29 tumors, from patients with recurrent (seven primary and 14 recurrent tumors) vs. non-recurrent RM (n = 8). Recurrent RM showed one (29%), two (29%) or three (42%) recurrences. BAP1 loss of expression was found in one third of all RM at diagnosis and increased to 100% in subsequent tumor recurrences. Despite both recurrent and non-recurrent RM shared chromosome 22 losses, non-recurrent tumors more frequently displayed extensive losses of chromosome 19p (62%) and/or 19q (50%), together with gains of chromosomes 20 and 21 (38%, respectively), whereas recurrent RM (at diagnosis) displayed more complex genotypic profiles with extensive losses of chromosomes 1p, 14q, 18p, 18q (67% each) and 21p (50%), together with focal gains at chromosome 17q22 (67%). Compared to paired primary tumors, recurrent RM samples revealed additional losses at chromosomes 16q and 19p (50% each), together with gains at chromosomes 1q and 17q in most recurrent tumors (67%, each). All deceased recurrent RM patients corresponded to women with chromosome 17q gains, although no statistical significant differences were found vs. the other RM patients.
MedicalCLIP: Anomaly-Detection Domain Generalization with Asymmetric Constraints
Authors: Hua Liujie , Luo Yueyi , Qi Qianqian , Long Jun
Published: May 2024

Medical data have unique specificity and professionalism, requiring substantial domain expertise for their annotation. Precise data annotation is essential for anomaly-detection tasks, making the training process complex. Domain generalization (DG) is an important approach to enhancing medical image anomaly detection (AD). This paper introduces a novel multimodal anomaly-detection framework called MedicalCLIP. MedicalCLIP utilizes multimodal data in anomaly-detection tasks and establishes irregular constraints within modalities for images and text. The key to MedicalCLIP lies in learning intramodal detailed representations, which are combined with text semantic-guided cross-modal contrastive learning, allowing the model to focus on semantic information while capturing more detailed information, thus achieving more fine-grained anomaly detection. MedicalCLIP relies on GPT prompts to generate text, reducing the demand for professional descriptions of medical data. Text construction for medical data helps to improve the generalization ability of multimodal models for anomaly-detection tasks. Additionally, during the text–image contrast-enhancement process, the model’s ability to select and extract information from image data is improved. Through hierarchical contrastive loss, fine-grained representations are achieved in the image-representation process. MedicalCLIP has been validated on various medical datasets, showing commendable domain generalization performance in medical-data anomaly detection. Improvements were observed in both anomaly classification and segmentation metrics. In the anomaly classification (AC) task involving brain data, the method demonstrated a 2.81 enhancement in performance over the best existing approach.
Time- and Region-Specific Selection of Reference Genes in the Rat Brain in the Lithium–Pilocarpine Model of Acquired Temporal Lobe Epilepsy
Authors: Schwarz Alexander P. , Zakharova Maria V. , Kovalenko Anna A. , Dyomina Alexandra V. , Zubareva Olga E. , Zaitsev Aleksey V.
Published: May 2024

Reverse transcription followed by quantitative polymerase chain reaction (RT-qPCR) is a commonly used tool for gene expression analysis. The selection of stably expressed reference genes is required for accurate normalization. The aim of this study was to identify the optimal reference genes for RT-qPCR normalization in various brain regions of rats at different stages of the lithium–pilocarpine model of acquired epilepsy. We tested the expression stability of nine housekeeping genes commonly used as reference genes in brain research: Actb, Gapdh, B2m, Rpl13a, Sdha, Ppia, Hprt1, Pgk1, and Ywhaz. Based on four standard algorithms (geNorm, NormFinder, BestKeeper, and comparative delta-Ct), we found that after pilocarpine-induced status epilepticus, the stability of the tested reference genes varied significantly between brain regions and depended on time after epileptogenesis induction (3 and 7 days in the latent phase, and 2 months in the chronic phase of the model). Pgk1 and Ywhaz were the most stable, while Actb, Sdha, and B2m demonstrated the lowest stability in the analyzed brain areas. We revealed time- and region-specific changes in the mRNA expression of the housekeeping genes B2m, Actb, Sdha, Rpl13a, Gapdh, Hprt1, and Sdha. These changes were more pronounced in the hippocampal region during the latent phase of the model and are thought to be related to epileptogenesis. Thus, RT-qPCR analysis of mRNA expression in acquired epilepsy models requires careful selection of reference genes depending on the brain region and time of analysis. For the time course study of epileptogenesis in the rat lithium–pilocarpine model, we recommend the use of the Pgk1 and Ywhaz genes.
The Expression of TP63 as a Biomarker of Early Recurrence in Resected Esophageal Squamous Cell Carcinoma after Neoadjuvant Chemoradiotherapy
Authors: Lin Chih-Hung , Cheng Po-Liang , Chuang Cheng-Yeh , Kang Yu-Ting , Lee Li-Wen , Hsiao Tzu-Hung , Hsu Chung-Ping
Published: May 2024

Esophageal cancer ranks among the ten most common cancers worldwide. Despite the adoption of neoadjuvant concurrent chemoradiotherapy (nCCRT) followed by surgery as the standard treatment approach in recent years, the local recurrence rate remains high. In this study, we employed RNA-seq to investigate distinctive gene expression profiles in esophageal squamous cell carcinoma (ESCC) with or without recurrence following a standard treatment course. Our findings indicate that recurrent ESCC exhibits heightened keratinizing and epidermis development activity compared to non-recurrent ESCC. We identified TP63 as a potential candidate for distinguishing clinical outcomes. Furthermore, immunohistochemistry confirmed the trend of TP63 overexpression in ESCC recurrence. Patients with elevated TP63 expression had poorer overall survival and lower 3-year recurrence-free survival. This study underscores the potential of TP63 as a biomarker for detecting cancer recurrence and suggests its role in guiding future treatment options.
Cancer Classification from Gene Expression Using Ensemble Learning with an Influential Feature Selection Technique
Authors: Tabassum Nusrath , Kamal Md Abdus Samad , Akhand M. A. H. , Yamada Kou
Published: May 2024

Uncontrolled abnormal cell growth, known as cancer, may lead to tumors, immune system deterioration, and other fatal disability. Early cancer identification makes cancer treatment easier and increases the recovery rate, resulting in less mortality. Gene expression data play a crucial role in cancer classification at an early stage. Accurate cancer classification is a complex and challenging task due to the high-dimensional nature of the gene expression data relative to the small sample size. This research proposes using a dimensionality-reduction technique to address this limitation. Specifically, the mutual information (MI) technique is first utilized to select influential biomarker genes. Next, an ensemble learning model is applied to the reduced dataset using only the most influential features (genes) to develop an effective cancer classification model. The bagging method, where the base classifiers are Multilayer Perceptrons (MLPs), is chosen as an ensemble technique. The proposed cancer classification model, the MI-Bagging method, is applied to several benchmark gene expression datasets containing distinctive cancer classes. The cancer classification accuracy of the proposed model is compared with the relevant existing methods. The experimental results indicate that the proposed model outperforms the existing methods, and it is effective and competent for cancer classification despite the limited size of gene expression data with high dimensionality. The highest accuracy achieved by the proposed method demonstrates that the proposed emerging gene-expression-based cancer classifier has the potential to help in cancer treatment and lead to a higher cancer survival rate in the future.
A Comprehensive Review of the Impact of Machine Learning and Omics on Rare Neurological Diseases
Authors: Alganmi Nofe
Published: May 2024

Background: Rare diseases, predominantly caused by genetic factors and often presenting neurological manifestations, are significantly underrepresented in research. This review addresses the urgent need for advanced research in rare neurological diseases (RNDs), which suffer from a data scarcity and diagnostic challenges. Bridging the gap in RND research is the integration of machine learning (ML) and omics technologies, offering potential insights into the genetic and molecular complexities of these conditions. Methods: We employed a structured search strategy, using a combination of machine learning and omics-related keywords, alongside the names and synonyms of 1840 RNDs as identified by Orphanet. Our inclusion criteria were limited to English language articles that utilized specific ML algorithms in the analysis of omics data related to RNDs. We excluded reviews and animal studies, focusing solely on studies with the clear application of ML in omics data to ensure the relevance and specificity of our research corpus. Results: The structured search revealed the growing use of machine learning algorithms for the discovery of biomarkers and diagnosis of rare neurological diseases (RNDs), with a primary focus on genomics and radiomics because genetic factors and imaging techniques play a crucial role in determining the severity of these diseases. With AI, we can improve diagnosis and mutation detection and develop personalized treatment plans. There are, however, several challenges, including small sample sizes, data heterogeneity, model interpretability, and the need for external validation studies. Conclusions: The sparse knowledge of valid biomarkers, disease pathogenesis, and treatments for rare diseases presents a significant challenge for RND research. The integration of omics and machine learning technologies, coupled with collaboration among stakeholders, is essential to develop personalized treatment plans and improve patient outcomes in this critical medical domain.
Validation of a New Ankle Brachial Index Measurement System Using Pulse Wave Velocity
Authors: Romero-Ante Juan David , Chicharro-Luna Esther , Manrique-Córdoba Juliana , Vicente-Samper José María , Gracia-Sánchez Alba , Sabater-Navarro José María
Published: May 2024

Peripheral artery disease (PAD) is a common circulatory disorder characterized by the accumulation of fats, cholesterol, and other substances in the arteries that restrict blood flow to the extremities, especially the legs. The ankle brachial index (ABI) is a highly reliable and valid non-invasive test for diagnosing PAD. However, the traditional method has limitations. These include the time required, the need for Doppler equipment, the training of clinical staff, and patient discomfort. PWV refers to the speed at which an arterial pressure wave propagates along the arteries, and this speed is conditioned by arterial elasticity and stiffness. To address these limitations, we have developed a system that uses electrocardiogram (ECG) and photoplethysmography (PPG) signals to calculate pulse wave velocity (PWV). We propose determining the ABI based on this calculation. Validation was performed on 22 diabetic patients, and the results demonstrate the accuracy of the system, maintaining a margin of ±0.1 compared with the traditional method. This confirms the correlation between PWV and ABI and positions this technique as a promising alternative to overcome some of the limitations of the conventional method.
The Construction and Application of a New Screening Method for Phosphodiesterase Inhibitors
Authors: Gao Chunhua , Wang Zhe , Liu Xiaojing , Sun Rongzhen , Ma Shengyao , Ma Zongchen , Wang Qi , Li Guoqiang , Zhang Han-Ting
Published: May 2024

Phosphodiesterases (PDEs), a superfamily of enzymes that hydrolyze cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP), are recognized as a therapeutic target for various diseases. However, the current screening methods for PDE inhibitors usually experience problems due to complex operations and/or high costs, which are not conducive to drug development in respect of this target. In this study, a new method for screening PDE inhibitors based on GloSensor technology was successfully established and applied, resulting in the discovery of several novel compounds of different structural types with PDE inhibitory activity. Compared with traditional screening methods, this method is low-cost, capable of dynamically detecting changes in substrate concentration in live cells, and can be used to preliminarily determine the type of PDEs affected by the detected active compounds, making it more suitable for high-throughput screening for PDE inhibitors.
Assessment of Adoption and Acceptance of Building Information Modeling for Building Construction among Industries in Qatar
Authors: Vitente Louiesito S. , Ong Ardvin Kester S. , German Josephine D.
Published: May 2024

Building information modeling (BIM) has become a vital tool in the construction industry, especially in Qatar, where remarkable infrastructural growth and innovation have taken place. This study looked into the factors influencing the adoption and acceptability of BIM in the Qatari construction industry using the Information System Success Model (ISSM), the Technology Acceptability Model (TAM), and structural equation modeling (SEM). Survey information gathered from project managers, contractors, engineers, architects, suppliers, and BIM specialists with direct BIM expertise was examined. The results showed that intentions to adopt BIM have a significant influence on its Perceived Usefulness and ease of use. The adoption of BIM is also significantly impacted by ISSM elements, including the Total Quality, Organizational Efficiency, Innovativeness, and Financial Aspects. This study illustrates the complex interactions between organizational influences and personal perspectives by demonstrating the direct and indirect effects of these factors on BIM adoption. These results provide a complete picture of the dynamics influencing BIM adoption in Qatar’s construction sector. As a result, this study makes connections between individual technology acceptance and the larger socio-technical environment of BIM implementation, providing essential information for building sector stakeholders, policymakers, and industry leaders. By using these insights to create strategies to boost BIM’s adoption and acceptability, the construction industries may be further aligned with global best practices in project management and delivery.
Research on the Digital Preservation of Architectural Heritage Based on Virtual Reality Technology
Authors: Zheng Haohua , Chen Leyang , Hu Hui , Wang Yihan , Wei Yangyang
Published: May 2024

As a representative of the scientific and technological achievements of the new era, the overall development of virtual reality (VR) technology is becoming increasingly refined, which provides new development ideas and technical support in the field of ancient building restoration and architectural heritage preservation. In this context, digital conservation and the practice of architectural heritage have become important focuses of application in the industry. This paper starts from the core concept of VR technology, analyzes the value of the application of VR technology in the protection of ancient architecture, puts forward relevant suggestions and technical application methods, and takes Red Pagoda in Fuliang County as an example. In this sense, virtual reality technology is used to restore and protect the buildings, forming a digital heritage of ancient architecture. This study first utilizes a three-dimensional laser scanning instrument to collect point cloud data, and then the plane graph is drawn by measurement. Then, an Architectural Heritage Building Information Model is created, and comprehensive information on historical buildings is integrated. Finally, VR technology is used to show the effect of digital display and preservation. This study transforms architectural cultural heritage into a shareable and renewable digital form through restoration and reproduction, interpreting and utilizing it from a new perspective and providing new ideas and methods for architectural heritage conservation.
A Multiphysics Simulation Study of the Thermomechanical Coupling Response of Energy Piles
Authors: Xu Chang , Wang Yawen , Meng Xiaolin , Lv Qihang , Chen Hui , Wu Qingdong
Published: May 2024

The global demand for energy is on the rise, accompanied by increasing requirements for low-carbon environmental protection. In recent years, China’s “double carbon action” initiative has brought about new development opportunities across various sectors. The concept of energy pile foundation aims to harness geothermal energy, aligning well with green, low-carbon, and sustainable development principles, thus offering extensive application prospects in engineering. Drawing from existing research globally, this paper delves into four key aspects impacting the thermodynamic properties of energy piles: the design of buried pipes, pile structure, heat storage materials within the pipe core, and soil treatment around the pile using carbon fiber urease mineralization. Leveraging the innovative mineralization technique known as urease-induced carbonate mineralization precipitation (EICP), this study employs COMSOL Multiphysics simulation software to analyze heat transfer dynamics and establish twelve sets of numerical models for energy piles. The buried pipe design encompasses two types, U-shaped and spiral, while the pile structure includes concrete solid energy piles and tubular energy piles. Soil conditions around the pile are classified into undisturbed sand and carbon fiber-infused EICP mineralized sand. Different inner core heat storage materials such as air, water, unaltered sand, and carbon fiber-based EICP mineralized sand are examined within tubular piles. Key findings indicate that spiral buried pipes outperform U-shaped ones, especially when filled with liquid thermal energy storage (TES) materials, enhancing temperature control of energy piles. The carbon fiber urease mineralization technique significantly improves heat exchange between energy piles and surrounding soil, reducing soil porosity to 4.9%. With a carbon fiber content of 1.2%, the ultimate compressive strength reaches 1419.4 kPa. Tubular energy piles mitigate pile stress during summer temperature fluctuations. Pile stress distribution varies under load and temperature stresses, with downward and upward friction observed at different points along the pile length. Overall, this research underscores the efficacy of energy pile technologies in optimizing energy efficiency while aligning with sustainable development goals.
Microscopic Mechanism and Reagent Activation of Waste Glass Powder for Solidifying Soil
Authors: Hong Yuze , Xu Xinyi , Zhang Chaojie , Cheng Zehai , Yang Guanshe
Published: May 2024

Glass waste products represent a significant environmental concern, with an estimated 1.4 billion tons being landfilled globally and 200 million tons annually. This results in a significant use of land resources. Therefore, it would be highly advantageous to develop a new method for disposing of waste glass. Waste glass can be recycled and ground into waste glass powder (WGP) for use in solidified soil applications as a sustainable resource. This study is based on solidified soil research, wherein NaOH, Ca(OH)2, and Na2SO4 were incorporated as activators to enhance the reactivity of WGP. The optimal solidified soil group was determined based on unconfined compressive strength tests, which involved varying the activator concentrations and WGP content in combination with cement. X-ray diffraction (XRD) was used to study the composition of solidified soil samples. Microscopic pore characteristics were investigated using scanning electron microscopy (SEM), and the Image J software was employed to quantify the number and size of pores. Fourier-transform infrared spectroscopy (FTIR) was employed to examine the activation effect of waste glass powder. This study investigated the solidification mechanism and porosity changes. The results demonstrate that the addition of activated WGP to solidified soil enhances its strength, with a notable 12% increase in strength achieved using a 6% Ca(OH)2 solution. The use of 2% concentration of Na2SO4 and NaOH also shows an increase in strength of 7.6% and 8.6%, respectively, compared to the sample without WGP. The XRD and SEM analyses indicate that activated WGP enhances the content of hydrates, reduces porosity, and fosters the formation of a more densely packed solidified soil structure.
Influence of Pile Spacing on the Compressive Bearing Performance of CEP Groups
Authors: Qian Yongmei , Cao Qingzhi , Yang Yang , Teng Da , Zhou Tingting
Published: May 2024

Pile spacing is an important factor affecting the bearing capacity of concrete expansion pile (CEP) groups. In this study, a pile group was simulated and analyzed using ANSYS software R19.0. The influence of pile spacing on the bearing capacity of the pile group under a vertical load was determined using three sets of four-, six-, and nine-pile models with different pile spacings. The grid division of the pile soil model adopts a mapping method, using the contact types of rigid and flexible bodies and applying surface loads to the model piles step-by-step. After vertical pressure was applied to the model pile, in-depth analysis was conducted on the displacement cloud map, pile top displacement, and other data. The different stress conditions of corner, edge, and center piles in each model group were compared and analyzed, revealing the relationship between the stress mechanism and failure law of the soil around the pile and the pile spacing. It was found that the soil displacement range of edge piles is slightly larger than that of corner piles. This phenomenon gradually decreases with increasing pile spacing. When the pile spacing increases to four times the cantilever diameter, the difference in soil displacement at different pile positions is small, and the pile spacing has little effect on the compressive bearing capacity of the pile group. Thus, it is reasonable to control the pile spacing at three to four times the cantilever diameter. In the nine-pile model, when the load is loaded to the 20-step level, the displacement value of the central pile is −72.278 mm, while the displacement values of the edge pile and corner pile are −69.012 mm and −66.806 mm. It is shown that increasing the pile spacing can effectively reduce the pile group effect and improve the bearing capacity of the pile foundation. At present, CEP pile groups are gradually being applied in practical engineering, but research on the influence of pile spacing on the compressive bearing performance of CEP pile groups is still at a very early stage. This article reinforces the influence of pile spacing on the compressive bearing performance of CEP pile groups. It provides theoretical support for its application in practical engineering.
Deciphering the Clinical Behaviour of Invasive Lobular Carcinoma of the Breast Defines an Aggressive Subtype
Authors: Makhlouf Shorouk , Atallah Nehal M. , Polotto Susanna , Lee Andrew H. S. , Green Andrew R. , Rakha Emad A.
Published: May 2024

Background: Invasive lobular carcinoma (ILC), the most common special type of breast cancer (BC), has unique clinical behaviour and is different from invasive ductal carcinoma of no special type (IDC-NST). However, ILC further comprises a diverse group of tumours with distinct features. This study aims to examine the clinicopathological and prognostic features of different variants of ILC, with a particular focus on characterising aggressive subtypes. Methods: A large (n = 7140) well-characterised and histologically reviewed BC cohort with treatment and long-term follow-up data was investigated. The cohort was classified based on the WHO classification of tumours into main histological subtypes, including ILC and IDC-NST. ILCs were further classified into variants. Clinicopathological parameters and patient outcomes in terms of BC-specific survival (BCSS) and disease-free survival (DFS) were evaluated. Results: ILC constituted 11% of the cohort. The most common non-classic ILC variants were pleomorphic (pILC) and solid (sILC), constituting 19% of ILC. Compared to classic and related variants (alveolar, trabecular, papillary, and tubulolobular; cILC), pILC and sILC variants were associated with aggressive tumour characteristics. The histologic grade of ILC was an important prognostic variable. The survival patterns identified an aggressive ILC subtype encompassing pILC and high-grade sILC. These tumours, which comprised 14% of the cases, were associated with clinicopathological characteristics of poor prognosis and had high BC-specific death and recurrence rates compared not only to cILC (p < 0.001) but also to IDC-NST (p = 0.02) patients. Contrasting this, cILC patients had significantly longer BCSS and DFS than IDC-NST patients in the first 10 to 15 years of follow-up. Adjuvant chemotherapy did not improve the outcome of patients with aggressive ILC subtypes. Conclusions: pILC and high-grade sILC variants comprise an aggressive ILC subtype associated with poor prognostic characteristics and a poor response to chemotherapy. These results warrant confirmation in randomised clinical trials.
Mixed Reality Biopsy Navigation System Utilizing Markerless Needle Tracking and Imaging Data Superimposition
Authors: Trojak Michał , Stanuch Maciej , Kurzyna Marcin , Darocha Szymon , Skalski Andrzej
Published: May 2024

Exact biopsy planning and careful execution of needle injection is crucial to ensure successful procedure completion as initially intended while minimizing the risk of complications. This study introduces a solution aimed at helping the operator navigate to precisely position the needle in a previously planned trajectory utilizing a mixed reality headset. A markerless needle tracking method was developed by integrating deep learning and deterministic computer vision techniques. The system is based on superimposing imaging data onto the patient’s body in order to directly perceive the anatomy and determine a path from the selected injection site to the target location. Four types of tests were conducted to assess the system’s performance: measuring the accuracy of needle pose estimation, determining the distance between injection sites and designated targets, evaluating the efficiency of material collection, and comparing procedure time and number of punctures required with and without the system. These tests, involving both phantoms and physician participation in the latter two, demonstrated the accuracy and usability of the proposed solution. The results showcased a significant improvement, with a reduction in number of punctures needed to reach the target location. The test was successfully completed on the first attempt in 70% of cases, as opposed to only 20% without the system. Additionally, there was a 53% reduction in procedure time, validating the effectiveness of the system.
Tumor Budding, p53, and DNA Mismatch Repair Markers in Sinonasal Intestinal-Type Adenocarcinoma: A Retrospective Study Supports the Adverse Prognostic Impact of Tumor Budding
Authors: Puccio Sebastiano , Azzarello Giuseppe , Maffeis Valeria , Laurino Licia , Mairani Edoardo , Conte Federica , Tessari Nicola , Cazzador Diego , Zanoletti Elisabetta , Politi Doriano , Emanuelli Enzo , Spinato Giacomo , Ausoni Simonetta
Published: May 2024

Sinonasal intestinal-type adenocarcinoma (ITAC) is a very rare, closely occupational-related tumor with strong histological similarities to colorectal cancer (CRC). In the latter, tumor budding (TB) is widely recognized as a negative prognostic parameter. The aim of this study was to evaluate the prognostic role of TB in ITAC and to correlate it with other established or emerging biomarkers of the disease, such as p53 and deficient DNA mismatch repair (MMR) system status/microsatellite instability (MSI). We retrospectively analyzed 32 consecutive specimens of patients with ITAC diagnosis treated in two institutions in Northern Italy. We reviewed surgical specimens for TB evaluation (low-intermediate/high); p53 expression and MMR proteins were evaluated via immunohistochemistry. Results were retrospectively stratified using clinical data and patients’ outcomes. According to bud counts, patients were stratified into two groups: intermediate/high budding (>4 TB) and low budding (≤4 TB). Patients with high TB (>4) have an increased risk of recurrence and death compared to those with low TB, with a median survival of 13 and 54 months, respectively. On multivariate analysis, considering TB, therapy, and stage as covariates, TB emerged as an independent prognostic factor net of the stage of disease or type of therapy received. No impact of p53 status as a biomarker of prognosis was observed and no alterations regarding MMR proteins were identified. The results of the present work provide further significant evidence on the prognostic role of TB in ITAC and underline the need for larger multicenter studies to implement the use of TB in clinical practice.
Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography-Derived Radiomic Models in Prostate Cancer Prognostication
Authors: Huynh Linda My , Swanson Shea , Cima Sophia , Haddadin Eliana , Baine Michael
Published: May 2024

The clinical integration of prostate membrane specific antigen (PSMA) positron emission tomography and computed tomography (PET/CT) scans represents potential for advanced data analysis techniques in prostate cancer (PC) prognostication. Among these tools is the use of radiomics, a computer-based method of extracting and quantitatively analyzing subvisual features in medical imaging. Within this context, the present review seeks to summarize the current literature on the use of PSMA PET/CT-derived radiomics in PC risk stratification. A stepwise literature search of publications from 2017 to 2023 was performed. Of 23 articles on PSMA PET/CT-derived prostate radiomics, PC diagnosis, prediction of biopsy Gleason score (GS), prediction of adverse pathology, and treatment outcomes were the primary endpoints of 4 (17.4%), 5 (21.7%), 7 (30.4%), and 7 (30.4%) studies, respectively. In predicting PC diagnosis, PSMA PET/CT-derived models performed well, with receiver operator characteristic curve area under the curve (ROC-AUC) values of 0.85–0.925. Similarly, in the prediction of biopsy and surgical pathology results, ROC-AUC values had ranges of 0.719–0.84 and 0.84–0.95, respectively. Finally, prediction of recurrence, progression, or survival following treatment was explored in nine studies, with ROC-AUC ranging 0.698–0.90. Of the 23 studies included in this review, 2 (8.7%) included external validation. While explorations of PSMA PET/CT-derived radiomic models are immature in follow-up and experience, these results represent great potential for future investigation and exploration. Prior to consideration for clinical use, however, rigorous validation in feature reproducibility and biologic validation of radiomic signatures must be prioritized.
MR Imaging of Adverse Effects and Ocular Growth Decline after Selective Intra-Arterial Chemotherapy for Retinoblastoma
Authors: de Bloeme Christiaan M. , van Elst Sabien , Galluzzi Paolo , Jansen Robin W. , de Haan Joeka , Göricke Sophia , Moll Annette C. , Bot Joseph C. J. , Munier Francis L. , Beck-Popovic Maja , Puccinelli Francesco , Aerts Isabelle , Hadjistilianou Theodora , Sirin Selma , Koob Mériam , Brisse Hervé J. , Cardoen Liesbeth , Maeder Philippe , de Jong Marcus C. , de Graaf Pim
Published: May 2024

This retrospective multicenter study examines therapy-induced orbital and ocular MRI findings in retinoblastoma patients following selective intra-arterial chemotherapy (SIAC) and quantifies the impact of SIAC on ocular and optic nerve growth. Patients were selected based on medical chart review, with inclusion criteria requiring the availability of posttreatment MR imaging encompassing T2-weighted and T1-weighted images (pre- and post-intravenous gadolinium administration). Qualitative features and quantitative measurements were independently scored by experienced radiologists, with deep learning segmentation aiding total eye volume assessment. Eyes were categorized into three groups: eyes receiving SIAC (Rb-SIAC), eyes treated with other eye-saving methods (Rb-control), and healthy eyes. The most prevalent adverse effects post-SIAC were inflammatory and vascular features, with therapy-induced contrast enhancement observed in the intraorbital optic nerve segment in 6% of patients. Quantitative analysis revealed significant growth arrest in Rb-SIAC eyes, particularly when treatment commenced ≤ 12 months of age. Optic nerve atrophy was a significant complication in Rb-SIAC eyes. In conclusion, this study highlights the vascular and inflammatory adverse effects observed post-SIAC in retinoblastoma patients and demonstrates a negative impact on eye and optic nerve growth, particularly in children treated ≤ 12 months of age, providing crucial insights for clinical management and future research.