bluuebunny/crossref_metadata_2025 huggingface dataset:
The Orexin/Hypocretin System, the Peptidergic Regulator of Vigilance, Orchestrates Adaptation to Stress
Authors: Jászberényi Miklós , Thurzó Balázs , Bagosi Zsolt , Vécsei László , Tanaka Masaru
Published: February 2024

The orexin/hypocretin neuropeptide family has emerged as a focal point of neuroscientific research following the discovery that this family plays a crucial role in a variety of physiological and behavioral processes. These neuropeptides serve as powerful neuromodulators, intricately shaping autonomic, endocrine, and behavioral responses across species. Notably, they serve as master regulators of vigilance and stress responses; however, their roles in food intake, metabolism, and thermoregulation appear complementary and warrant further investigation. This narrative review provides a journey through the evolution of our understanding of the orexin system, from its initial discovery to the promising progress made in developing orexin derivatives. It goes beyond conventional boundaries, striving to synthesize the multifaceted activities of orexins. Special emphasis is placed on domains such as stress response, fear, anxiety, and learning, in which the authors have contributed to the literature with original publications. This paper also overviews the advancement of orexin pharmacology, which has already yielded some promising successes, particularly in the treatment of sleep disorders.
Can Combining Hyaluronic Acid and Physiotherapy in Knee Osteoarthritis Improve the Physicochemical Properties of Synovial Fluid?
Authors: Onu Ilie , Gherghel Robert , Nacu Isabella , Cojocaru Florina-Daniela , Verestiuc Liliana , Matei Daniela-Viorelia , Cascaval Dan , Serban Ionela Lacramioara , Iordan Daniel Andrei , Tucaliuc Alexandra , Galaction Anca-Irina
Published: February 2024

Known as the degenerative disease of the knee with the highest prevalence, knee osteoarthritis (KOA) is characterized by a gradual destructive mechanism that, in severe cases, can provoke the need for total knee substitution. As the disease progresses, various enzymatic, immunological, and inflammatory processes abnormally degrade hyaluronic acid (HA), SF’s main component, and affect the concentrations of specific proteins, with the final results seriously endangering synovial fluid (SF)’s rheological and tribological features and characteristics. No effective treatments have been found to stop the progression of KOA, but the injection of HA-based viscoelastic gels has been considered (alone or combined with physiotherapy (PT)) as an alternative to symptomatic therapies. In order to evaluate the effect of viscosupplementation and PT on the characteristics of SF, SF aspirated from groups treated for KOA (HA Kombihylan® and groups that received Kombihylan® and complex PT) was analyzed and compared from analytical, spectrophotometrical, and rheological perspectives. In the patients treated with PT, the SF extracted 6 weeks after viscosupplementation had a superior elastic modulus (G′) and viscous moduli (G″), as well as a homogeneous distribution of proteins and polysaccharides. The viscosupplementation fluid improved the bioadhesive properties of the SF, and the use of the viscosupplementation fluid in conjunction with PT was found to be favorable for the distribution of macromolecules and phospholipids, contributing to the lubrication process and the treatment of OA-affected joints.
The Anterior Inferior Cerebral Artery Variability in the Context of Neurovascular Compression Syndromes: A Narrative Review
Authors: Kościołek Dawid , Kobierecki Mateusz , Tokarski Mikołaj , Szalbot Konrad , Kościołek Aleksandra , Malicki Mikołaj , Wanibuchi Sora , Wiśniewski Karol , Piotrowski Michał , Bobeff Ernest J. , Szmyd Bartosz M. , Jaskólski Dariusz J.
Published: February 2024

The anterior inferior cerebellar artery (AICA) is situated within the posterior cranial fossa and typically arises from the basilar artery, usually at the pontomedullary junction. AICA is implicated in various clinical conditions, encompassing the development of aneurysms, thrombus formation, and the manifestation of lateral pontine syndrome. Furthermore, owing to its close proximity to cranial nerves within the middle cerebellopontine angle, AICA’s pulsatile compression at the root entry/exit zone of cranial nerves may give rise to specific neurovascular compression syndromes (NVCs), including hemifacial spasm (HFS) and geniculate neuralgia concurrent with HFS. In this narrative review, we undertake an examination of the influence of anatomical variations in AICA on the occurrence of NVCs. Significant methodological disparities between cadaveric and radiological studies (CTA, MRA, and DSA) were found, particularly in diagnosing AICA’s absence, which was more common in radiological studies (up to 36.1%) compared to cadaver studies (less than 5%). Other observed variations included atypical origins from the vertebral artery and basilar-vertebral junction, as well as the AICA-and-PICA common trunk. Single cases of arterial triplication or fenestration have also been documented. Specifically, in relation to HFS, AICA variants that compress the facial nerve at its root entry/exit zone include parabola-shaped loops, dominant segments proximal to the REZ, and anchor-shaped bifurcations impacting the nerve’s cisternal portion.
The Tissue Engineering Revolution: From Bench Research to Clinical Reality
Authors: De Chiara Francesco , Ferret-Miñana Ainhoa , Fernández-Costa Juan M. , Ramón-Azcón Javier
Published: February 2024

At its core, tissue engineering involves the use of a scaffold for the formation of new viable tissue for medical purposes [...]
Characterization of Novel RHD Allele Variants and Their Implications for Routine Blood Group Diagnostics
Authors: Matzhold Eva M. , Bemelmans Maria , Polin Helene , Körmöczi Günther F. , Schönbacher Marlies , Wagner Thomas
Published: February 2024

The Rh system, including the highly immunogenic D antigen, is one of the clinically most important blood group systems in transfusion medicine. Numerous alleles of the RHD gene are associated with variant RhD phenotypes. In case of Rh incompatibility, some of them can induce hemolytic transfusion reactions and hemolytic disease of the fetus and newborn. Thus, accurate blood group diagnostics are critical for safe transfusion therapy. We characterized phenotypes of four individuals revealing weakened D expression during routine pre-transfusion testing. Standard gel card matrix techniques with monoclonal and polyclonal anti-D antibodies were used for serological typing, complemented using D epitope and antigen density analysis. Genotyping employing PCR with sequence-specific primers, genomic and allele-specific Sanger sequencing and in silico protein analysis were performed. Four novel RHD alleles associated with weak D or partial D phenotypes were identified. One of the mutations is predicted to disrupt the terminal stop codon and result in an elongated translation of the mutant D protein that phenotypically exhibits a loss of D epitopes. Furthermore, a hybrid gene formed with the homologue RHCE gene is described. The presented data enhances the understanding of the Rh system and may contribute to continued advances in blood group diagnostics.
The Hemorrhagic Side of Primary Angiitis of the Central Nervous System (PACNS)
Authors: Zedde Marialuisa , Napoli Manuela , Moratti Claudio , Pezzella Francesca Romana , Seiffge David Julian , Tsivgoulis Georgios , Caputi Luigi , Salvarani Carlo , Toni Danilo , Valzania Franco , Pascarella Rosario
Published: February 2024

Primary Angiitis of the Central Nervous System (PACNS) is a rare cerebrovascular disease involving the arteries of the leptomeninges, brain and spinal cord. Its diagnosis can be challenging, and the current diagnostic criteria show several limitations. Among the clinical and neuroimaging manifestations of PACNS, intracranial bleeding, particularly intracerebral hemorrhage (ICH), is poorly described in the available literature, and it is considered infrequent. This review aims to summarize the available data addressing this issue with a dedicated focus on the clinical, neuroradiological and neuropathological perspectives. Moreover, the limitations of the actual data and the unanswered questions about hemorrhagic PACNS are addressed from a double point of view (PACNS subtyping and ICH etiology). Fewer than 20% of patients diagnosed as PACNS had an ICH during the course of the disease, and in cases where ICH was reported, it usually did not occur at presentation. As trigger factors, both sympathomimetic drugs and illicit drugs have been proposed, under the hypothesis of an inflammatory response due to vasoconstriction in the distal cerebral arteries. Most neuroradiological descriptions documented a lobar location, and both the large-vessel PACNS (LV-PACNS) and small-vessel PACNS (SV-PACNS) subtypes might be the underlying associated phenotypes. Surprisingly, amyloid beta deposition was not associated with ICH when histopathology was available. Moreover, PACNS is not explicitly included in the etiological classification of spontaneous ICH. This issue has received little attention in the past, and it could be addressed in future prospective studies.
Muscle Dysfunction and Functional Status in COVID-19 Patients during Illness and after Hospital Discharge
Authors: Psenicka Otakar , Brutvan Tomas , Kratky Jan , Krizova Jarmila
Published: February 2024

Background: COVID-19 pneumonia is associated with SIRS and hypercatabolism. The aim of this study was to determine muscle loss during the acute phase of COVID-19 pneumonia and evaluate long-term sequelae in discharged patients. Methods: A total of 16 patients with COVID-19 pneumonia and respiratory insufficiency were included in the study. Selected parameters (weight, BMI, LBM = lean body mass, albumin, CRP, NLR = neutrophil-to-lymphocyte ratio, ultrasound measured thickness of rectus femoris muscle = US RF and rectus femoris + vastus intermedius = US RF + VI, handgrip strength, quality of life = EQ-5D questionnaire, and activities of daily living = Barthel’s ADLs) were recorded on admission, discharge, and 1, 3, and 6 months after discharge. Results: The most significant changes were between hospital admission and discharge: US RF and RF + VI (−1.28 ± 1.97 mm, p = 0.046; −1.76 ± 2.94 mm, p = 0.05), EQ-5D score (14.6 ± 19.2, p = 0.02), and ADLs (17.1 ± 22.6; p = 0.02). There was a significant positive correlation between US RF + VI and handgrip strength (p = 0.014) and a negative correlation between weight and Barthel index (p = 0.012). There was an association between muscle function with an EQ-5D score and ADLs during outpatient check-ups, most noticeably between handgrip strength, US RF+VI, and ADLs (p = 0.08; p = 0.1, respectively). Conclusions: In patients with COVID-19 pneumonia, there is a significant reduction of health-related quality of life, impaired even 6 months after hospital discharge, influenced mainly by muscle loss. During the hospital stay, there was a significant muscle mass reduction. Ultrasound measurement of thigh muscle thickness may be a useful method to monitor muscle loss.
High-Throughput Bacteriophage Testing with Potency Determination: Validation of an Automated Pipetting and Phage Drop-Off Method
Authors: Dufour Nicolas , Delattre Raphaëlle , Debarbieux Laurent
Published: February 2024

The development of bacteriophages (phages) as active pharmaceutical ingredients for the treatment of patients is on its way and regulatory agencies are calling for reliable methods to assess phage potency. As the number of phage banks is increasing, so is the number of phages that need to be tested to identify therapeutic candidates. Currently, assessment of phage potency on a semi-solid medium to observe plaque-forming units is unavoidable and proves to be labor intensive when considering dozens of phage candidates. Here, we present a method based on automated pipetting and phage drop-off performed by a liquid-handling robot, allowing high-throughput testing and phage potency determination (based on phage titer and efficiency of plaquing). Ten phages were tested, individually and assembled into one cocktail, against 126 Escherichia coli strains. This automated method was compared to the reference one (manual assay) and validated in terms of reproducibility and concordance (ratio of results according to the Bland and Altman method: 0.99; Lin’s concordance correlation coefficient: 0.86). We found that coefficients of variation were lower with automated pipetting (mean CV: 13.3% vs. 24.5%). Beyond speeding up the process of phage screening, this method could be used to standardize phage potency evaluation.
Long-Term Outcomes of COVID-19 in Hospitalized Type 2 Diabetes Mellitus Patients
Authors: Khamidullina Zemfira , Avzaletdinova Diana , Gareeva Diana , Morugova Tatyana , Lakman Irina , Kopp Kristen , Fiedler Lukas , Motloch Lukas J. , Zagidullin Naufal
Published: February 2024

With the onset of the coronavirus pandemic, it has become clear that patients with diabetes are at risk for more severe and fatal COVID-19. Type 2 diabetes mellitus (T2D) is a major risk factor for adverse COVID-19 outcomes. The goal of study was to assess the characteristics and outcomes of hospitalized patients with COVID-19 with or without T2D in the hospital and at 10-month follow-up (FU). Methods: A total of 2486 hospitalized patients in the first wave of COVID-19 were analyzed according to the absence/presence of T2D, with 2082 (84.1%) patients in the control COVID-19 group and 381 (15.5%) in the T2D group. Twenty-three patients had other types of diabetes and were therefore excluded from the study. In-hospital mortality and cardiovascular endpoints (myocardial infarction, stroke, cardiovascular deaths and hospitalizations and composite endpoints) at the 10-month follow-up were analyzed. To remove bias in patients’ characteristics disproportion, Propensity Score Matching (PSM) was used for hospital and follow-up endpoints. Results. Hospital mortality was considerably greater in T2D than in the control COVID-19 group (13.89% vs. 4.89%, p < 0.0001), and the difference remained after PSM (p < 0.0001). Higher glucose-level T2D patients had a higher mortality rate (p = 0.018). The most significant predictors of hospital death in T2D patients were a high CRP, glucose, neutrophils count, and Charlson Comorbidity Index. The follow-up of patients over 10 months showed a non-significant increase for all endpoints in the T2D group (p > 0.05), and significant increase in stroke (p < 0.042). After the PSM, the difference decreased in stroke (p = 0.090), but became significant in cardiovascular hospitalizations (p = 0.023). Conclusion. In T2D patients with COVID-19, an increase in hospital mortality, stroke and cardiovascular hospitalizations rates in the follow-up was observed.
The Impact of Physical Exercise on microRNAs in Hemodialysis Patients: A Review and a Protocol for an Ancillary Study
Authors: Elia Rossella , Piva Giovanni , Bulighin Francesca , Lamberti Nicola , Manfredini Fabio , Gambaro Giovanni , Di Maria Alessio , Salvagno Gianluca , Carbonare Luca Giuseppe Dalle , Storari Alda , Valenti Maria Teresa , Battaglia Yuri
Published: February 2024

Physical inactivity is considered a significant risk factor for mortality and morbidity among chronic hemodialysis (HD) patients. Therefore, physical exercise is recommended in the treatment of HD patients. Although the beneficial effects of physical exercise in HD patients are well-described in the literature, the underlying physiological mechanisms still need to be fully understood. Recently, microRNAs (miRNAs) have emerged as potential mediators of the therapeutic effects of physical exercise in healthy individuals. miRNAs are short, single-stranded, noncoding RNAs involved in gene expression regulation. Specifically, upon forming the RNA-induced silencing complex, miRNAs selectively bind to specific miRNAs within cells, reducing gene expression. miRNAs can be secreted by cells in an accessible form or enclosed within exosomes or extracellular vesicles. They can be detected in various body fluids, including serum (circulating miRNAs), facilitating the study of their diverse expression. Currently, there is no available data regarding the impact of physical exercise on the expression of miRNAs involved in osteogenic differentiation, a fundamental mechanism in the development of vascular calcification, for HD patients. Therefore, we have designed an observational and longitudinal case-control study to evaluate the expression of miR-9 and miR-30b in HD patients participating in a 3-month interdialytic physical exercise program. This paper aims to present the study protocol and review the expression of circulating miRNAs in HD patients and their modulation through physical exercise.
Design and Synthesis of Immunoadjuvant QS-21 Analogs and Their Biological Evaluation
Authors: Yuan Wei , Wang Ziming , Zou Yening , Zheng Guojun
Published: February 2024

A series of novel immunoadjuvant QS-21 analogs were synthesized, and their effects on the in vitro hemolysis of red blood cells were evaluated using QS-21 as a control and hemolytic properties as an index. Our results show that all the QS-21 analogs had lower hemolytic effects than QS-21, and their concentrations exhibited a certain quantitative effect relationship with the hemolysis rate. Notably, saponin compounds L1–L8 produced minimal hemolysis and showed lower hemolytic effects, warranting further investigation.
Women’s Special Issue Series: Biomedicines
Authors: Polito Letizia
Published: February 2024

Following the invitation of Biomedicines, we decided to accept the project of this Special Issue because we believe that in many situations gender prejudices still exist and put women in a disadvantaged position for the dissemination of their research, preventing the scientific community from benefiting from a plurality of voices in the interpretation of scientific research [...]
Machine Learning and Texture Analysis of [18F]FDG PET/CT Images for the Prediction of Distant Metastases in Non-Small-Cell Lung Cancer Patients
Authors: Hakkak Moghadam Torbati Armin , Pellegrino Sara , Fonti Rosa , Morra Rocco , De Placido Sabino , Del Vecchio Silvana
Published: February 2024

The aim of our study was to predict the occurrence of distant metastases in non-small-cell lung cancer (NSCLC) patients using machine learning methods and texture analysis of 18F-labeled 2-deoxy-d-glucose Positron Emission Tomography/Computed Tomography {[18F]FDG PET/CT} images. In this retrospective and single-center study, we evaluated 79 patients with advanced NSCLC who had undergone [18F]FDG PET/CT scan at diagnosis before any therapy. Patients were divided into two independent training (n = 44) and final testing (n = 35) cohorts. Texture features of primary tumors and lymph node metastases were extracted from [18F]FDG PET/CT images using the LIFEx program. Six machine learning methods were applied to the training dataset using the entire panel of features. Dedicated selection methods were used to generate different combinations of five features. The performance of selected machine learning methods applied to the different combinations of features was determined using accuracy, the confusion matrix, receiver operating characteristic (ROC) curves, and area under the curve (AUC). A total of 104 and 78 lesions were analyzed in the training and final testing cohorts, respectively. The support vector machine (SVM) and decision tree methods showed the highest accuracy in the training cohort. Seven combinations of five features were obtained and introduced in the models and subsequently applied to the training and final testing cohorts using the SVM and decision tree. The accuracy and the AUC of the decision tree method were higher than those obtained with the SVM in the final testing cohort. The best combination of features included shape sphericity, gray level run length matrix_run length non-uniformity (GLRLM_RLNU), Total Lesion Glycolysis (TLG), Metabolic Tumor Volume (MTV), and shape compacity. The combination of these features with the decision tree method could predict the occurrence of distant metastases with an accuracy of 74.4% and an AUC of 0.63 in NSCLC patients.
Animal Models for Understanding the Mechanisms of Beta Cell Death during Type 2 Diabetes Pathogenesis
Authors: Covington Brittney A. , Chen Wenbiao
Published: February 2024

Type 2 diabetes (T2D) has become a worldwide epidemic, primarily driven by obesity from overnutrition and sedentariness. Recent results reveal there is heterogeneity in both pathology and treatment responses in T2D patients. Therefore, a variety of T2D animal models are necessary to obtain a mechanistic understanding of distinct disease processes. T2D results from insufficient insulin, either due to beta cell loss or inborn deficiency. Although decreases in beta cell mass can occur through loss of identity or cell death, in this review, we will highlight the T2D animal models that display beta cell death, including the Zucker Diabetic Fatty Rat, sand rat, db/db mouse, and a novel diabetic zebrafish model, the Zebrafish Muscle Insulin-Resistant (zMIR) fish. Procuring a mechanistic understanding of different T2D progression trajectories under a variety of contexts is paramount for developing and testing more individualized treatments.
Enhancing Calprotectin’s Predictive Power as a Biomarker of Endoscopic Activity in Ulcerative Colitis: A Machine Learning Use Case
Authors: Dranga Mihaela , Mihai Cătălina , Gavrilescu Otilia , Cijevschi Prelipcean Cristina , Popa Iolanda Valentina
Published: February 2024

Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by periods of exacerbation and remission, making disease monitoring and management challenging. Endoscopy, the gold standard for assessing disease activity and severity, involves invasive procedures and is associated with patient discomfort and risks. Using machine learning (ML) to combine fecal calprotectin with other clinical or biological tests can significantly enhance the non-invasive prediction of endoscopic disease activity (EDA) in UC. Aim: To prove that by fusing fecal calprotectin with other clinical data into an ML model, the performance of the non-invasive prediction of EDA can be significantly improved. Methods: We conducted a prospective, observational, single-center study encompassing 103 patients diagnosed with UC. We employed multilayer perceptron models as the core ML algorithm for predicting EDA. For the constructed models, we utilized the varImp function from the caret library in R to assess the significance of each variable in predicting the outcome. Results: Calprotectin as a sole predictor obtained an accuracy of 70% and an area under the curve (AUC) of 0.68. Combining calprotectin with the list of selected predictors that were fed to the MLP models improved accuracy and the AUC. The accuracy of the algorithm on the test set was 85%. Similarly, the AUC increased to 0.93. This is the first study to propose the use of calprotectin as a predictor in an ML model to estimate UC endoscopic disease activity. Conclusion: The deployment of this ML model can furnish doctors and patients with valuable evaluation of endoscopic disease activity which can be highly beneficial for individuals with UC who need long-term treatment.
Multi-Modal Enhancement Transformer Network for Skeleton-Based Human Interaction Recognition
Authors: Hu Qianshuo , Liu Haijun
Published: February 2024

Skeleton-based human interaction recognition is a challenging task in the field of vision and image processing. Graph Convolutional Networks (GCNs) achieved remarkable performance by modeling the human skeleton as a topology. However, existing GCN-based methods have two problems: (1) Existing frameworks cannot effectively take advantage of the complementary features of different skeletal modalities. There is no information transfer channel between various specific modalities. (2) Limited by the structure of the skeleton topology, it is hard to capture and learn the information about two-person interactions. To solve these problems, inspired by the human visual neural network, we propose a multi-modal enhancement transformer (ME-Former) network for skeleton-based human interaction recognition. ME-Former includes a multi-modal enhancement module (ME) and a context progressive fusion block (CPF). More specifically, each ME module consists of a multi-head cross-modal attention block (MH-CA) and a two-person hypergraph self-attention block (TH-SA), which are responsible for enhancing the skeleton features of a specific modality from other skeletal modalities and modeling spatial dependencies between joints using the specific modality, respectively. In addition, we propose a two-person skeleton topology and a two-person hypergraph representation. The TH-SA block can embed their structural information into the self-attention to better learn two-person interaction. The CPF block is capable of progressively transforming the features of different skeletal modalities from low-level features to higher-order global contexts, making the enhancement process more efficient. Extensive experiments on benchmark NTU-RGB+D 60 and NTU-RGB+D 120 datasets consistently verify the effectiveness of our proposed ME-Former by outperforming state-of-the-art methods.
Fluorometric and Colorimetric Method for SARS-CoV-2 Detection Using Designed Aptamer Display Particles
Authors: Park Ki Sung , Choi Anna , Park Tae-In , Pack Seung Pil
Published: February 2024

SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has spurred the urgent need for practical diagnostics with high sensitivity and selectivity. Although advanced diagnostic tools have emerged to efficiently control pandemics, they still have costly limitations owing to their reliance on antibodies or enzymes and require high-tech equipment. Therefore, there is still a need to develop rapid and low-cost diagnostics with high sensitivity and selectivity. In this study, we generated aptamer display particles (AdP), enabling easy fabrication of a SARS-CoV-2 detection matrix through particle PCR, and applied it to diagnosis using fluorometric and colorimetric assays. We designed two AdPs, C1-AdP and C4-AdP, displayed with SpS1-C1 and SpS1-C4 aptamers, respectively, and showed their high binding ability against SARS-CoV-2 spike protein with a concentration-dependent fluorescence increase. This enabled detection even at low concentrations (0.5 nM). To validate its use as a diagnostic tool for SARS-CoV-2, we designed a sandwich-type assay using two AdPs and high-quality aptamers targeting SARS-CoV-2 pseudoviruses. The fluorometric assay achieved a detection limit of 3.9 × 103 pseudoviruses/mL. The colorimetric assay using an amplification approach exhibited higher sensitivity, with a detection limit of 1 × 101 pseudoviruses/mL, and a broad range of over four orders of magnitude was observed.
Crack Width Recognition of Tunnel Tube Sheet Based on YOLOv8 Algorithm and 3D Imaging
Authors: Xu Xunqian , Li Qi , Li Shue , Kang Fengyi , Wan Guozhi , Wu Tao , Wang Siwen
Published: February 2024

Based on the tunnel crack width identification, there are operating time constraints, limited operating space, high equipment testing costs, and other issues. In this paper, a large subway tunnel is a research object, and the tunnel rail inspection car is an operating platform equipped with industrial cameras in order to meet the requirements of the tunnel tube sheet crack width recognition of more than 0.2 mm, with the measuring instrument to verify that the tunnel rail inspection car in the state of uniform motion camera imaging quality has the reliability through the addition of laser rangefinders, the accurate measurement of the object distance and the calculation of the imaging plane and the angle of the plane to be measured, to amend the three-dimensional cracks. The pixel resolution of the image is corrected, the images imaged by the industrial camera are preprocessed, the YOLOv8 algorithm is used for the intelligent extraction of crack morphology, and finally, the actual width is calculated from the spacing between two points of the crack. The crack detection width obtained by image processing using the YOLOv8 algorithm is basically the same as the value of crack width obtained by manual detection, and the error rate of crack width detection ranges from 0% to 11%, with the average error rate remaining below 4%. Compared with the crack detection error rate of the Support Vector Machine (SVM), the crack extraction model is reduced by 1%, so using the tunnel inspection vehicle as a platform equipped with an industrial camera, YOLOv8 is used to realize the recognition of the shape and width of the cracks on the surface of the tunnel tube sheet to meet the requirements of a higher degree of accuracy. The number of pixels and the detection error rate are inversely proportional to each other. The angle between the imaging plane and the plane under test is directly proportional to the detection error rate. The angle between the vertical axis where the lens midpoint is located and the line connecting the shooting target and the lens center point is αi and the angle θi between the measured plane and the imaging plane is reciprocal, i.e., αi + θi = 90°. Therefore, using the inspection vehicle as a mobile platform equipped with an industrial camera and based on the YOLOv8 algorithm, the crack recognition of the tunnel tube sheet has the feasibility and the prospect of wide application, which provides a reference method for the detection of cracks in the tunnel tube sheet.
Temporary Structural Health Monitoring of Historical Széchenyi Chain Bridge
Authors: Kövesdi Balázs , Kollár Dénes , Dunai László
Published: February 2024

A temporary monitoring system was installed on the 175-year-old historical Széchenyi Chain Bridge during its reconstruction. The bridge is in the downtown area in the capital city of Hungary and plays a significant role in the city life of Budapest. Six-month-long measurements were conducted during the reconstruction process of the bridge, yielding crucial insights into the structural behaviour of the historical structure. The measurement results were evaluated; the findings encompass the rotation capacity of the pins between the chain elements and the structural response to temperature changes. This information helped the decision-making between 2021 and 2023 by the designers and construction company during the reconstruction. For instance, daily temperature fluctuations resulted in increased bending moments in the chain elements, rising up to 158% compared to the values observed during a proof load test in 2018. Furthermore, the measurements reveal an approximate 42% increase in normal forces compared to the proof load test, which highlights the high sensitivity of chain bridges to temperature fluctuations, where geometric stiffness plays a crucial role. Reconstruction, namely reducing self-weight, notably intensifies the impact on normal forces and bending moments. These outcomes strongly emphasize the dominance of the dead load and self-weight in the case of chain bridges.
Performance and Heavy Metal Analysis of Graphite Tailings Cured Using Cementitious Materials
Authors: Jiang Ruixin , Wang Zhengjun
Published: February 2024

The massive accumulation of graphite tailings causes serious environmental pollution, mainly from heavy metal pollution. Therefore, this article introduces a method of using graphite tailings as a high-content main material, cement as a small component of the auxiliary cementitious material, and clay as a substitute for cement. The compressive strength and permeability of graphite tailing–solidified material (GT, GT–Clay) were tested, and the effect of clay partially replacing cement as an auxiliary cementitious agent on GT–Clay performance was compared. In addition, inductively coupled plasma mass spectrometry (ICP) was used to analyze the effect of the graphite tailing placement time on the heavy metal content, as well as the changes in the GT heavy metal leaching concentration and its heavy metal content under outdoor freeze–thaw conditions. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) were used to elucidate the microstructural changes in the GT–Clay. The experimental results show that, as the substitution of clay for cement increased from 0 to 50%, the compressive strength of the 90% GT–Clay gradually decreased, and the permeability also increased. The compressive strength of 95% GT–Clay did not show significant changes, but the permeability increased, and when mixed with quicklime, gypsum, and silica fume, the permeability decreased. The Ni and As in graphite tailings fluctuated significantly with the placement time. The heavy metal leaching concentrations of the 90% GT and 95% GT were below the standard limit, and Cd, As, and Ni in GT were potential sources of pollution. The analysis of the microscopic test results showed that the hydration products of the GT–Clay included ettringite, Ca(OH)2, and calcium silicate hydrates. The hydration product stabilized and filled the gaps between the tailing particles, thereby cementing them together. Not only did it improve the mechanical strength of GT, it also reduced the permeability and heavy metal leaching rate. This study provides a new analytical approach to applying graphite tailings for environmental treatment.
Integration of Building Information Modeling (BIM) with Transportation and Facilities: Recent Applications and Future Perspectives
Authors: Liu Yi , Deng Yiting , Liu Zhen , Osmani Mohamed
Published: February 2024

At present, increased modes of transport have facilitated daily life. Building information modeling (BIM) integration has become a key strategy to foster efficiency, collaboration, and sustainability in the fields of buildings, transport, and facilities. Currently, there is a scarcity of comprehensive examinations of the performance of integrated BIM with transport facilities and applications to help identify potential prospects for sustainable development. Hence, this research paper attempts to scrutinize the integration of BIM, transportation, and facilities (T and Fs) by highlighting future directions and trends, revealing the existing status and hotspots of research in the field, and clarifying the developmental pulse of research as well as emerging areas in the future. A quantitative research technique is utilized in this study, using VOSviewer and CiteSpace software, and the Web of Science Core Collection (WoSCC) database. The study findings suggest that the hot keywords for the integration of BIM and T and Fs are predominantly concentrated on construction, framework, system, design, and management. In addition, over the previous 34 years (years 1989 to 2023), the applications of point cloud, digital twin, and life cycle assessment have been the current hot topics, and these emerging technologies can offer more innovative breakthroughs for the future. Furthermore, the integration of BIM and T and Fs represents an important trend that is essential for improving the efficiency, sustainability, and intelligence of buildings and infrastructure, from which the three domains can create synergies that contribute to the better planning, construction, and management of building and infrastructure projects.
Synergistic Relationship, Agent Interaction, and Knowledge Coupling: Driving Innovation in Intelligent Construction Technology
Authors: Chen Wei , Yu Mingyu , Hou Jia
Published: February 2024

The core driving force behind innovation in intelligent construction technology is synergistic relationships. It has become common practice to promote synergistic innovation through agent interaction and knowledge coupling in the development of intelligent construction technology. Drawing upon synergetics, social network theory, and the knowledge base view as theoretical frameworks, this research examines the impact of synergistic relationship, agent interaction, and knowledge coupling on innovation in intelligent construction technology. An empirical analysis of 186 questionnaires revealed the following: (1) regarding synergistic relationships, both horizontal synergy and vertical synergy significantly positively impact innovation in intelligent construction technology. (2) Concerning agent interaction, strong interaction serves as a mediator between horizontal synergy and innovation in intelligent construction technology, while weak interaction serves as a mediator between vertical synergy and innovation in intelligent construction technology. (3) Knowledge coupling has a positive moderating effect on innovation in intelligent construction technology under a strong interaction and a negative moderating effect on innovation in intelligent construction technology under a weak interaction. This study contributes to expanding the theory of synergistic relationships and its application in the context of intelligent construction technology. Furthermore, it provides practical insights and guidance for construction companies seeking to enhance innovation in intelligent construction technology through the utilization of agent interaction and knowledge coupling.
Review of the Short-Term Properties of Confined Seawater Sea Sand Concrete Columns under Compression
Authors: Shrivastava Chitransh , Ramli Sulong Nor Hafizah , Zahra Tatheer , Elchalakani Mohamed , Gamage Kumari , Fawzia Sabrina
Published: February 2024

The environmental concerns raised by the over-exploitation of fresh water and river sand have driven researchers to explore seawater sea sand concrete (SWSSC) as a substitute for conventional concrete in structural columns. With numerous investigations on this in the past, there is a need to systematically classify and comprehensively understand the response of confined SWSSC columns to promote their usage as structural columns. Consequently, the objective of this review is to summarise and analyse the experimental work conducted so far on confined SWSSC under different compressive loadings. Confined SWSSC columns are classified into five confinement schemes based on the cross-section of the specimens: single-skin, single-skin multilayered, single-skin with additional reinforcement, double-skin, and double-tube-confined SWSSC columns. Based on the findings of the reviewed studies, it can be concluded that the compressive strength and the ductility of the SWSSC can be enhanced through confinement, with effectiveness majorly depending on the material and geometrical properties of the confinement providing material. The existing research work on SWSSC confinement lays out a strong base for future investigations in this area, which will eventually facilitate the acceptance of SWSSC as structural columns, especially for coastal and marine infrastructure.
The Consequences of Dimension Reduction for Open Graded Friction Course (OGFC) Asphalt Mixtures: Morphological Characteristics and Finite Element Model (FEM) Simulation
Authors: Li Kai , Liu Quan , Tian Yuan , Du Cong , Xu Zhixiang
Published: February 2024

Asphalt mixtures exhibit complex mechanical behaviors due to their multiphase internal structures. To provide better characterizations of asphalt pavements under various forms of potential distress, a two-dimensional (2D) finite element simulation based on images of asphalt mixtures can be used to increase computational efficiency and reduce labor consumption. Nonetheless, using a representative image to eliminate the influence of dimension reduction from three dimensions to two dimensions is of great significance for attaining a reliable simulation result. Therefore, in this study, we investigated the consequence of dimension reduction for open-graded asphalt mixtures (denoted as OGFC-16), including a comprehensive characterization of these 2D models in terms of their morphologies and the similarities between them. This study aimed to reveal the variation in a 2D finite element simulation when applied to open-graded asphalt mixtures. Structural compositions, gradations, the aspect ratios of aggregates, and aggregate orientations were counted and calculated. In addition, the cosine similarity and structural similarity index measure (SSIM) were also calculated. Consequently, we performed a statistical analysis on the aforementioned indicators to quantitatively identify the discrepancy in the 2D images caused by dimension reduction. The results demonstrate that this 2D simulation might not be sufficient for representing the realistic mechanical performance of asphalt mixtures due to the remarkable variations in the image morphologies in different 2D images. However, the basic rules of stress behavior within structures can be accurately simulated. A compensative methodology for conducting a 2D simulation of open-graded asphalt mixtures should be based on a morphological characterization, considering structural compositions and the structural similarity index measure.
Revealing Urban Color Patterns via Drone Aerial Photography—A Case Study in Urban Hangzhou, China
Authors: Li Rushi , Wu Mincheng
Published: February 2024

Urban color, primarily emanating from building façades and roofs, plays a pivotal role in shaping a city’s image and influencing people’s overall impression. Understanding the nuances of color patterns contributes significantly to unraveling the uniqueness and identity of a city. This study introduces a statistical method for the systematic analysis of urban color and macroscopic urban structure. Specifically, we employ drones to collect and extract building roof and façade colors in the main urban area of Hangzhou, mapping these colors to the HSV color space. Subsequently, we establish a random walk model and an origin–destination trip model within the urban transportation network to simulate the movement of people. Our experiments reveal robust correlations between façade and roof values and passing frequency (with the Pearson correlations reaching 0.70). Through a rigorous statistical analysis, we gain insights into the distribution of urban color and the impact of architectural structures on color variations, identifying potential patterns or trends. By integrating color data with architectural structure data, our systematic research method deepens the understanding of the visual features that define cities. Beyond theoretical exploration, this approach offers practical insights for building planning and design. This study not only sheds light on the relationship between architectural structures and urban color but also provides valuable guidance for future urban development initiatives.
Skin Heat Transfer and Thermal Sensation Coupling Model under Steady Stimulation
Authors: Zhou Yijia , Yu Hang , Luo Maohui , Zhou Xiang
Published: February 2024

Thermal sensation prediction models can help to evaluate complex thermal environments and guide the environment conditioning strategy. However, most existing models are established basing on the thermal status of the entire human body or local body parts, failing to reflect thermal sensation generating mechanism or micro-scale (centimeter-scale) thermal sensation. This study put forward a new thermal sensation predicting approach by coupling the skin heat transfer and the thermoreceptor impulse signals. The micro-scale thermal sensitivity data under steady stimuli were applied to bridging the objective heat transfer model and the subjective sensation model. The model contains a one-dimensional skin heat transfer equation and three sensation-generating equations: the thermoreceptor impulse equation, the psychosensory intensity equation, and the thermal sensation equation. The dimension of the skin heat transfer equation was determined through a skin temperature diffusion experiment, and the coefficients of the static/dynamic impulse in the thermoreceptor impulse equation and the thermal sensation equation were obtained through polynomial fitting using thermal sensitivity data. The validated mean absolute percentage error (MAPE) was 0.08 and 0.1 under cooling and heating stimuli, respectively. This new model can predict thermal sensation on the centimeter scale and be applied under different boundary conditions. In the future, the new model can be further developed by testing dynamic stimuli and other boundary conditions so that it can be applied to more complex thermal exposures.
Reducing Carbon Emissions from Prefabricated Decoration: A Case Study of Residential Buildings in China
Authors: Bian Ji , Liu Changchun , Zuo Chunyang , Hao Jianli , Ma Wenting , Duan Baoyin , Chen Congda , Liu Jixuan
Published: February 2024

Since decoration is an essential part of buildings, the carbon emissions generated by decoration work should not be ignored. In recent years, prefabricated decoration has attracted much attention as efforts are made to pursue green, low-carbon, and waste-reducing buildings. However, research on carbon emissions assessment of prefabricated buildings has focused mainly on the structural aspect of prefabricated buildings, with few studies having considered prefabricated decoration. This study therefore focuses on assessing the carbon emissions of prefabricated decoration from the life cycle perspective of a case study residential building and explores the potential for reducing carbon emissions by decorating buildings with prefabricated components. The results show that using prefabricated decoration in the case study building reduced carbon emissions by 29.08% at the building material production stage compared to traditional decoration, and using an optimized design of prefabricated decoration, the building’s energy consumption over its design life could reduce carbon emissions by 1046 kgCO2/m2. These findings demonstrate the benefits of prefabrication decoration for reducing carbon emissions. This study provides decoration companies with robust data and insights to guide future decisions and practices, helping to transform and achieve the carbon neutrality goal for the building decoration industry.
DL-SLICER: Deep Learning for Satellite-Based Identification of Cities with Enhanced Resemblance
Authors: Bissarinova Ulzhan , Tleuken Aidana , Alimukhambetova Sofiya , Varol Huseyin Atakan , Karaca Ferhat
Published: February 2024

This paper introduces a deep learning (DL) tool capable of classifying cities and revealing the features that characterize each city from a visual perspective. The study utilizes city view data captured from satellites and employs a methodology involving DL-based classification for city identification, along with an Explainable Artificial Intelligence (AI) tool to unveil definitive features of each city considered in this study. The city identification model implemented using the ResNet architecture yielded an overall accuracy of 84%, featuring 45 cities worldwide with varied geographic locations, Human Development Index (HDI), and population sizes. The portraying attributes of urban locations have been investigated using an explanatory visualization tool named Relevance Class Activation Maps (CAM). The methodology and findings presented by the current study enable decision makers, city managers, and policymakers to identify similar cities through satellite data, understand the salient features of the cities, and make decisions based on similarity patterns that can lead to effective solutions in a wide range of objectives such as urban planning, crisis management, and economic policies. Analyzing city similarities is crucial for urban development, transportation strategies, zoning, improvement of living conditions, fostering economic success, shaping social justice policies, and providing data for indices and concepts such as sustainability and smart cities for urban zones sharing similar patterns.