bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Neuroactive Steroids in Analgesia and Anesthesia: An Interesting Comeback?
Authors: Jevtovic-Todorovic Vesna , Todorovic Slobodan M.
Published: November 2023

Published evidence over the past few decades suggests that general anesthetics could be neurotoxins especially when administered at the extremes of age. The reported pathology is not only at the morphological level when examined in very young and aged brains, given that, importantly, newly developing evidence suggests a variety of behavioral impairments. Since anesthesia is unavoidable in certain clinical settings, we should consider the development of new anesthetics. A promising and safe solution could be a new family of anesthetics referred to as neuroactive steroids. In this review, we summarize the currently available evidence regarding their anesthetic and analgesic properties.
Intercellular Molecular Crosstalk Networks within Invasive and Immunosuppressive Tumor Microenvironment Subtypes Associated with Clinical Outcomes in Four Cancer Types
Authors: Wei Jinfen , Yu Wenqi , Wu Lei , Chen Zixi , Huang Guanda , Hu Meiling , Du Hongli
Published: November 2023

Heterogeneity is a critical basis for understanding how the tumor microenvironment (TME) contributes to tumor progression. However, an understanding of the specific characteristics and functions of TME subtypes (subTMEs) in the progression of cancer is required for further investigations into single-cell resolutions. Here, we analyzed single-cell RNA sequencing data of 250 clinical samples with more than 200,000 cells analyzed in each cancer datum. Based on the construction of an intercellular infiltration model and unsupervised clustering analysis, four, three, three, and four subTMEs were revealed in breast, colorectal, esophageal, and pancreatic cancer, respectively. Among the subTMEs, the immune-suppressive subTME (subTME-IS) and matrix remodeling with malignant cells subTME (subTME-MRM) were highly enriched in tumors, whereas the immune cell infiltration subTME (subTME-ICI) and precancerous state of epithelial cells subTME (subTME-PSE) were less in tumors, compared with paracancerous tissues. We detected and compared genes encoding cytokines, chemokines, cytotoxic mediators, PD1, and PD-L1. The results showed that these genes were specifically overexpressed in different cell types, and, compared with normal tissues, they were upregulated in tumor-derived cells. In addition, compared with other subTMEs, the expression levels of PDCD1 and TGFB1 were higher in subTME-IS. The Cox proportional risk regression model was further constructed to identify possible prognostic markers in each subTME across four cancer types. Cell-cell interaction analysis revealed the distinguishing features in molecular pairs among different subTMEs. Notably, ligand–receptor gene pairs, including COL1A1-SDC1, COL6A2-SDC1, COL6A3-SDC1, and COL4A1-ITGA2 between stromal and tumor cells, associated with tumor invasion phenotypes, poor patient prognoses, and tumor advanced progression, were revealed in subTME-MRM. C5AR1-RPS19, LGALS9-HAVCR2, and SPP1-PTGER4 between macrophages and CD8+ T cells, associated with CD8+ T-cell dysfunction, immunosuppressive status, and tumor advanced progression, were revealed in subTME-IS. The spatial co-location information of cellular and molecular interactions was further verified by spatial transcriptome data from colorectal cancer clinical samples. Overall, our study revealed the heterogeneity within the TME, highlighting the potential pro-invasion and pro-immunosuppressive functions and cellular infiltration characteristics of specific subTMEs, and also identified the key cellular and molecular interactions that might be associated with the survival, invasion, immune escape, and classification of cancer patients across four cancer types.
Association between SMAD4 Mutations and GATA6 Expression in Paired Pancreatic Ductal Adenocarcinoma Tumor Specimens: Data from Two Independent Molecularly-Characterized Cohorts
Authors: Greendyk Joshua D. , Allen William E. , Alexander H. Richard , Beninato Toni , Eskander Mariam F. , Grandhi Miral S. , Kennedy Timothy J. , Langan Russell C. , Maggi Jason C. , De Subhajyoti , Court Colin M. , Ecker Brett L.
Published: November 2023

Several molecular biomarkers have been identified to guide induction treatment selection for localized pancreatic ductal adenocarcinoma (PDAC). SMAD4 alterations and low GATA6 expression/modified “Moffitt” basal-like phenotype have each been associated with inferior survival uniquely for patients receiving 5-FU-based therapies. SMAD4 may directly regulate the expression of GATA6 in PDAC, pointing to a common predictive biomarker. To evaluate the relationship between SMAD4 mutations and GATA6 expression in human PDAC tumors, patients with paired SMAD4 mutation and GATA6 mRNA expression data in the TCGA and CPTAC were identified. In 321 patients (TCGA: n = 180; CPTAC: n = 141), the rate of SMAD4 alterations was 26.8%. The rate of SMAD4 alteration did not vary per tertile of normalized GATA6 expression (TCGA: p = 0.928; CPTAC: p = 0.828). In the TCGA, SMAD4 alterations and the basal-like phenotype were each associated with worse survival (log rank p = 0.077 and p = 0.080, respectively), but their combined presence did not identify a subset with uniquely inferior survival (p = 0.943). In the CPTAC, the basal-like phenotype was associated with significantly worse survival (p < 0.001), but the prognostic value was not influenced by the combined presence of SMAD4 alterations (p = 0.960). SMAD4 alterations were not associated with poor clinico-pathological features such as poor tumor grade, advanced tumor stage, positive lymphovascular invasion (LVI), or positive perineural invasion (PNI), compared with SMAD4-wildtype. Given that SMAD4 mutations were not associated with GATA6 expression or Moffitt subtype in two independent molecularly characterized PDAC cohorts, distinct biomarker-defined clinical trials are necessary.
Gut–Kidney–Heart: A Novel Trilogy
Authors: Caldarelli Mario , Franza Laura , Rio Pierluigi , Gasbarrini Antonio , Gambassi Giovanni , Cianci Rossella
Published: November 2023

The microbiota represents a key factor in determining health and disease. Its role in inflammation and immunological disorders is well known, but it is also involved in several complex conditions, ranging from neurological to psychiatric, from gastrointestinal to cardiovascular diseases. It has recently been hypothesized that the gut microbiota may act as an intermediary in the close interaction between kidneys and the cardiovascular system, leading to the conceptualization of the “gut–kidney–heart” axis. In this narrative review, we will discuss the impact of the gut microbiota on each system while also reviewing the available data regarding the axis itself. We will also describe the role of gut metabolites in this complex interplay, as well as potential therapeutical perspectives.
Proteomic Profiling of Early Secreted Proteins in Response to Lipopolysaccharide-Induced Vascular Endothelial Cell EA.hy926 Injury
Authors: Songjang Worawat , Paiyabhroma Nitchawat , Jumroon Noppadon , Jiraviriyakul Arunya , Nernpermpisooth Nitirut , Seenak Porrnthanate , Kumphune Sarawut , Thaisakun Siriwan , Phaonakrop Narumon , Roytrakul Sittiruk , Pankhong Panyupa
Published: November 2023

Sepsis is a crucial public health problem with a high mortality rate caused by a dysregulated host immune response to infection. Vascular endothelial cell injury is an important hallmark of sepsis, which leads to multiple organ failure and death. Early biomarkers to diagnose sepsis may provide early intervention and reduce risk of death. Damage-associated molecular patterns (DAMPs) are host nuclear or cytoplasmic molecules released from cells following tissue damage. We postulated that DAMPs could potentially be a novel sepsis biomarker. We used an in vitro model to determine suitable protein–DAMPs biomarkers for early sepsis diagnosis. Low and high lipopolysaccharide (LPS) doses were used to stimulate the human umbilical vein endothelial cell line EA.hy926 for 24, 48, and 72 h. Results showed that cell viability was reduced in both dose-dependent and time-dependent manners. Cell injury was corroborated by a significant increase in lactate dehydrogenase (LDH) activity within 24 h in cell-conditioned medium. Secreted protein–DAMPs in the supernatant, collected at different time points within 24 h, were characterized using shotgun proteomics LC-MS/MS analysis. Results showed that there were 2233 proteins. Among these, 181 proteins from the LPS-stimulated EA.hy926 at 1, 12, and 24 h were significantly different from those of the control. Twelve proteins were up-regulated at all three time points. Furthermore, a potential interaction analysis of predominant DAMPs-related proteins using STITCH 5.0 revealed the following associations with pathways: response to stress; bacterium; and LPS (GO:0080134; 0009617; 0032496). Markedly, alpha-2-HS-glycoprotein (AHSG or fetuin-A) and lactotransferrin (LTF) potentially presented since the first hour of LPS stimulation, and were highly up-regulated at 24 h. Taken together, we reported proteomic profiling of vascular endothelial cell-specific DAMPs in response to early an in vitro LPS stimulation, suggesting that these early damage-response protein candidates could be novel early biomarkers associated with sepsis.
Nonlinear Dynamic Stability of Cylindrical Reticulated Shells with Initial Damage
Authors: Li Lei , Li Guangfeng , Uddin Nasim , Tian Limin , Zhu Zhibing , Bai Chong , Shen Chen
Published: November 2023

As large-span structures, reticulated shells are widely used in large-scale public building and act as emergency shelters in the event of sudden disasters. However, spatial reticulated shells are dynamic-sensitive structures; the effect of the initial structural damage on dynamic stability should be considered. In this study, a new nonlinear dynamic model of cylindrical reticulated shells with initial damage is proposed to investigate the effect of initial damage accurately. Firstly, the damage constitutive relations of the building steels are built based on the irreversible thermodynamic theory; furthermore, its fundamental equations are obtained using simulated shell methods. Then, the nonlinear vibration differential equations with damage are obtained and studied with support. Meanwhile, the nonlinear natural vibration frequency with initial damage is derivatized. After that, a bifurcation problem with initial damage is studied by using Flouquet Index, and the dynamic stability state at the equilibrium point is analyzed in depth. It is found that the local dynamic stability of the system is determined via its initial condition, geometric parameters, and initial damage. Moreover, the initial damage dominates over other influence factors due to its strong randomness and uncertainty for the same structure. The damage accumulation results in the transition of the equilibrium point. In addition, the nonlinear natural vibration frequency decreases to zero with the accumulation of the damage reaching 0.618; the local stability of cylindrical reticulated shells fails and they even lose whole stability. This study provides a theoretical foundation for the future investigation of whole stability with initial damage.
Analysis of Natural Vibration Characteristics of Metal Roof Panel of Large-Span Standing-Seam Metal Roof System
Authors: Xie Zhen , Zhang Yongshan
Published: November 2023

Metal roof systems are widely used in various landmark buildings. Understanding the natural vibration characteristics and primary influence of the roof system is useful for improving the roof system’s service life and maintaining the project’s safety. In addition, it is helpful to analyze the vibration force of the structure under earthquake and wind load. In this paper, the experimental investigation of the natural vibration characteristics (NVC) of two commonly used structural forms of standing-seam metal roof systems is carried out, and the influence of different boundary conditions, specimen width, panel width, and other parameters on the NVC are considered. The influence of different factors on the NVC of the roof system is analyzed in detail, and the main influencing factors and secondary influencing factors are studied. The research results show apparent differences in the NVC of the side and middle span of the roof panel under different parameters. The structural form has the most significant influence on the NVC of the roof panel, and the maximum influence on the peak acceleration (PA) and the fundamental frequency (FF) of the roof panel are 83.7% and 60%, respectively. The width of the specimen has a minor influence on the FF of the roof panel, and the minimum influence range is 6.9%. The influence of structural form, constraint form, specimen width, and panel width on the PA of the roof panel is far more significant than it is on the FF, with the difference between the two reaching 44.2%.
Off-Site Manufacturing: Determining Decision-Making Factors
Authors: Kosbar Mohamed M. , Elbeltagi Emad , Mahdi Ibrahim , Kassem Mahmoud , Ehab A.
Published: November 2023

New technologies like modular construction are expected to increase the market share in developing countries with a high annual growth rate such as in Egypt. Modular construction solutions that have content depending on the process of off-site construction and on-site transportation gained prominence over recent years due to several benefits, especially their positive impact on the environment. Off-site manufacturing (OSM) and traditional technologies like on-site ones differ in many aspects of design, requirements, logistics, engineering, and others. Many researchers studied modular construction and they fall short of investigating modular construction processes comprehensively and completely. In this paper, the barriers and benefits of using off-site manufacturing (OSM) are collected from the previous studies (that focused on mega projects, high quality, and fast-track projects) to be analyzed using a social network analysis (SNA) to promote the implementation of this new technology mainly in high-annual-growth-rate countries. A survey was used to solicit the opinions of construction practitioners to identify the most significant barriers and obstacles, as well as the benefits of using OSM. Also, due to the capabilities of Building Information Modeling (BIM) to manage shared information and increase the cooperation among project parties, the integration of OSM and BIM is investigated as a promising approach to overcome OSM barriers and enhance its utilization. Analyzing the main barriers’ density and finding out the main solution are involved. Applying this case to a real project in Egypt to study the impact of using (OSM) on-site and exporting the data are also involved. With some results related to the other results and disadvantages that were deduced, the most important advantages and most disadvantages emerged, as well as finding ways to solve them and practical application on the ground.
Study on Construction Mechanical Effect and Optimization of Large-Span Variable Cross-Section of Railway Tunnel
Authors: Song Sensen , Li Shuguang , Liang Yanling , Huo Runke , Song Zhanping , Miao Zizhen , Song Ziyi
Published: November 2023

During the excavation process of a large-span variable cross-section of a tunnel, the deformation and stress characteristics of the surrounding rock supporting the structure are complex, and construction control is difficult. Based on an actual tunnel project, the mechanical effect and deformation characteristics of the surrounding rock and support structure of a large-span variable cross-section tunnel during its excavation and support process were studied via numerical simulation. The construction method, using the bench method to excavate and set up the transition section in the variable cross-section, was proposed. Based on the numerical simulation results, two optimized excavation schemes were proposed and analyzed to address the construction method conversion problems in constructing large-span variable cross-section tunnels. The rationality of the optimized construction scheme was verified through a comparison with field monitoring data. The research results show that the three-bench temporary inverted arch method supported by the temporary vertical portal frame has good applicability in constructing the large-span variable cross-section tunnel. This scheme can effectively control the stress concentration and excessive deformation of the surrounding rock in the large-span variable cross-section tunnel. The numerical simulation results agree with the field monitoring data, which verifies the rationality of analyzing the construction mechanical effects of variable cross-section tunnels and selecting construction schemes through numerical simulation. The research results can provide reference for the construction of similar tunnel projects.
The Diverse Genomic Landscape of Diamond–Blackfan Anemia: Two Novel Variants and a Mini-Review
Authors: Pelagiadis Iordanis , Kyriakidis Ioannis , Katzilakis Nikolaos , Kosmeri Chrysoula , Veltra Danai , Sofocleous Christalena , Glentis Stavros , Kattamis Antonis , Makis Alexandros , Stiakaki Eftichia
Published: November 2023

Diamond–Blackfan anemia (DBA) is a ribosomopathy characterized by bone marrow erythroid hypoplasia, which typically presents with severe anemia within the first months of life. DBA is typically attributed to a heterozygous mutation in a ribosomal protein (RP) gene along with a defect in the ribosomal RNA (rRNA) maturation or levels. Besides classic DBA, DBA-like disease has been described with variations in 16 genes (primarily in GATA1, followed by ADA2 alias CECR1, HEATR3, and TSR2). To date, more than a thousand variants have been reported in RP genes. Splice variants represent 6% of identifiable genetic defects in DBA, while their prevalence is 14.3% when focusing on pathogenic and likely pathogenic (P/LP) variants, thus highlighting the impact of such alterations in RP translation and, subsequently, in ribosome levels. We hereby present two cases with novel pathogenic splice variants in RPS17 and RPS26. Associations of DBA-related variants with specific phenotypic features and malignancies and the molecular consequences of pathogenic variations for each DBA-related gene are discussed. The determinants of the spontaneous remission, cancer development, variable expression of the same variants between families, and selectivity of RP defects towards the erythroid lineage remain to be elucidated.
Auditory Cortex Maturation and Language Development in Children with Hearing Loss and Additional Disabilities
Authors: Lamminmäki Satu , Cormier Kayla , Davidson Hanna , Grigsby Jim , Sharma Anu
Published: November 2023

A significant portion of hearing-impaired children have additional disabilities, but data about the maturation of their auditory cortex are scarce. In these children, behavioral tests are often unreliable, and objective tests are needed for diagnostics and follow-up. This study aimed to explore auditory cortical maturation and language development, and the usability of an objective electroencephalogram-based biomarker in children with multiple disabilities. In 65 hearing aid and cochlear implant users (36 females; 36 with multiple disabilities; 44.3 ± 18.5 months of age, mean ± SD), auditory processing was examined using the P1 cortical auditory evoked response biomarker, and language development with the Preschool Language Scales 5th edition (PLS-5). During the study, all of the children received intensive extra language therapy for six months. No significant differences were found between the groups in P1 latency development, the proportion of abnormal P1 latencies, or the number of children whose P1 latencies changed from abnormal to normal during the study. The PLS-5 total language scores, auditory comprehension scores, or expressive communication scores did not differ between groups either. The P1 latencies showed meaningful negative correlations with the language scores. The results suggest that auditory cortex development is similar in hearing-impaired children with/without additional disabilities, and the P1 biomarker is a feasible tool to evaluate central auditory maturation in children with multiple disabilities.
Indices of Narrative Language Associated with Disability
Authors: Almubark Norah M. , Silva-Maceda Gabriela , Foster Matthew E. , Spencer Trina D.
Published: November 2023

Narratives skills are associated with long-term academic and social benefits. While students with disabilities often struggle to produce complete and complex narratives, it remains unclear which aspects of narrative language are most indicative of disability. In this study, we examined the association between a variety of narrative contents and form indices and disability. Methodology involved drawing 50 K-3 students with Individual Education Programs (IEP) and reported language concerns from a large diverse sample (n = 1074). Fifty typically developing (TD) students were matched to the former group using propensity score matching based on their age, gender, grade, mother’s education, and ethnicity. Narrative retells and generated language samples were collected and scored for Narrative Discourse and Sentence Complexity using a narrative scoring rubric. In addition, the number of different words (NDW), subordination index (SI), and percentage of grammatical errors (%GE) were calculated using computer software. Results of the Mixed effect model revealed that only Narrative Discourse had a significant effect on disability, with no significant effect revealed for Sentence Complexity, %GE, SI, and NDW. Additionally, Narrative Discourse emerged as the sole significant predictor of disability. At each grade, there were performance gaps between groups in the Narrative Discourse, Language Complexity, and SI. Findings suggest that difficulty in Narrative Discourse is the most consistent predictor of disability.
Neuroimaging Techniques in Differentiating Parkinson’s Disease from Drug-Induced Parkinsonism: A Comprehensive Review
Authors: Pitton Rissardo Jamir , Caprara Ana Letícia Fornari
Published: November 2023

Neuroimaging can provide significant benefits in evaluating patients with movement disorders associated with drugs. This literature review describes neuroimaging techniques performed to distinguish Parkinson’s disease from drug-induced parkinsonism. The dopaminergic radiotracers already reported to assess patients with drug-induced parkinsonism are [123I]-FP-CIT, [123I]-β-CIT, [99mTc]-TRODAT-1, [18F]-DOPA, [18F]-AV-133, and [18F]-FP-CIT. The most studied one and the one with the highest number of publications is [123I]-FP-CIT. Fludeoxyglucose (18F) revealed a specific pattern that could predict individuals susceptible to developing drug-induced parkinsonism. Another scintigraphy method is [123I]-MIBG cardiac imaging, in which a relationship between abnormal cardiac imaging and normal dopamine transporter imaging was associated with a progression to degenerative disease in individuals with drug-induced parkinsonism. Structural brain magnetic resonance imaging can be used to assess the striatal region. A transcranial ultrasound is a non-invasive method with significant benefits regarding costs and availability. Optic coherence tomography only showed abnormalities in the late phase of Parkinson’s disease, so no benefit in distinguishing early-phase Parkinson’s disease and drug-induced parkinsonism was found. Most methods demonstrated a high specificity in differentiating degenerative from non-degenerative conditions, but the sensitivity widely varied in the studies. An algorithm was designed based on clinical manifestations, neuroimaging, and drug dose adjustment to assist in the management of patients with drug-induced parkinsonism.
Global Dynamics of a Within-Host Model for Usutu Virus
Authors: Nali Ibrahim , Dénes Attila
Published: November 2023

We propose a within-host mathematical model for the dynamics of Usutu virus infection, incorporating Crowley–Martin functional response. The basic reproduction number R0 is found by applying the next-generation matrix approach. Depending on this threshold, parameter, global asymptotic stability of one of the two possible equilibria is also established via constructing appropriate Lyapunov functions and using LaSalle’s invariance principle. We present numerical simulations to illustrate the results and a sensitivity analysis of R0 was also completed. Finally, we fit the model to actual data on Usutu virus titers. Our study provides new insights into the dynamics of Usutu virus infection.
Buckling Assessment in the Dynamics Mechanisms, Stewart Platform Case Study: In the Context of Loads and Joints, Deflection Positions Gradient
Authors: Hassanian Reza , Riedel Morris
Published: November 2023

This study introduces an approach for modeling an arm of a Stewart platform to analyze the location of sections with a high deflection among the arms. Given the dynamic nature of the Stewart platform, its arms experience static and dynamic loads. The static loads originate from the platform’s own weight components, while the dynamic loads arise from the movement or holding of equipment in a specific position using the end-effector. These loads are distributed among the platform arms. The arm encompasses various design categories, including spring-mass, spring-mass-damper, mass-actuator, and spring-mass-actuator. In accordance with these designs, joint points should be strategically placed away from critical sections where maximum buckling or deformation is prominent. The current study presents a novel model employing Euler’s formula, a fundamental concept in buckling analysis, to propose this approach. The results align with experimental and numerical reports in the literature that prove the internal force of the platform arm is affecting the arm stiffness. The equal stiffness of an arm is related to its internal force and its deflection. The study demonstrates how higher levels of dynamic loading influence the dynamic platform, causing variations in the maximum arm’s buckling deflection, its precise location, and the associated deflection slope. Notably, in platform arms capable of adjusting their tilt angles relative to the vertical axis, the angle of inclination directly correlates with deflection and its gradient. The assumption of linearity in Euler’s formula seems to reveal distinctive behavior in deflection gradients concerning dynamic mechanisms.
Superconvergence Analysis of Discontinuous Galerkin Methods for Systems of Second-Order Boundary Value Problems
Authors: Temimi Helmi
Published: November 2023

In this paper, we present an innovative approach to solve a system of boundary value problems (BVPs), using the newly developed discontinuous Galerkin (DG) method, which eliminates the need for auxiliary variables. This work is the first in a series of papers on DG methods applied to partial differential equations (PDEs). By consecutively applying the DG method to each space variable of the PDE using the method of lines, we transform the problem into a system of ordinary differential equations (ODEs). We investigate the convergence criteria of the DG method on systems of ODEs and generalize the error analysis to PDEs. Our analysis demonstrates that the DG error’s leading term is determined by a combination of specific Jacobi polynomials in each element. Thus, we prove that DG solutions are superconvergent at the roots of these polynomials, with an order of convergence of O(hp+2).
Design Recommendations for Immersive Virtual Reality Application for English Learning: A Systematic Review
Authors: Esteves Jessica Rodrigues , Cardoso Jorge C. S. , Gonçalves Berenice Santos
Published: November 2023

The growing popularity of immersive virtual reality (iVR) technologies has opened up new possibilities for learning English. In the literature, it is possible to find several studies focused on the design, development, and evaluation of immersive virtual reality applications. However, there are no studies that systematize design recommendations for immersive virtual reality applications for English learning. To fill this gap, we present a systematic review that aims to identify design recommendations for immersive virtual reality English learning applications. We searched the ACM Digital Library, ERIC, IEEE Xplore, Scopus, and Web of Science (1 January 2010 to April 2023) and found that 24 out of 847 articles met the inclusion criteria. We identified 18 categories of design considerations related to design and learning and a design process used to create iVR applications. We also identified existing trends related to universities, publications, devices, human senses, and development platforms. Finally, we addressed study limitations and future directions for designing iVR applications for English learning.
Detectability and Volumetric Accuracy of Pulmonary Nodules in Low-Dose Photon-Counting Detector Computed Tomography: An Anthropomorphic Phantom Study
Authors: Hop Joost F. , Walstra Anna N. H. , Pelgrim Gert-Jan , Xie Xueqian , Panneman Noor A. , Schurink Niels W. , Faby Sebastian , van Straten Marcel , de Bock Geertruida H. , Vliegenthart Rozemarijn , Greuter Marcel J. W.
Published: November 2023

The aim of this phantom study was to assess the detectability and volumetric accuracy of pulmonary nodules on photon-counting detector CT (PCD-CT) at different low-dose levels compared to conventional energy-integrating detector CT (EID-CT). In-house fabricated artificial nodules of different shapes (spherical, lobulated, spiculated), sizes (2.5–10 mm and 5–1222 mm3), and densities (−330 HU and 100 HU) were randomly inserted into an anthropomorphic thorax phantom. The phantom was scanned with a low-dose chest protocol with PCD-CT and EID-CT, in which the dose with PCD-CT was lowered from 100% to 10% with respect to the EID-CT reference dose. Two blinded observers independently assessed the CT examinations of the nodules. A third observer measured the nodule volumes using commercial software. The influence of the scanner type, dose, observer, physical nodule volume, shape, and density on the detectability and volumetric accuracy was assessed by a multivariable regression analysis. In 120 CT examinations, 642 nodules were present. Observer 1 and 2 detected 367 (57%) and 289 nodules (45%), respectively. With PCD-CT and EID-CT, the nodule detectability was similar. The physical nodule volumes were underestimated by 20% (range 8–52%) with PCD-CT and 24% (range 9–52%) with EID-CT. With PCD-CT, no significant decrease in the detectability and volumetric accuracy was found at dose reductions down to 10% of the reference dose (p > 0.05). The detectability and volumetric accuracy were significantly influenced by the observer, nodule volume, and a spiculated nodule shape (p < 0.05), but not by dose, CT scanner type, and nodule density (p > 0.05). Low-dose PCD-CT demonstrates potential to detect and assess the volumes of pulmonary nodules, even with a radiation dose reduction of up to 90%.
Elevation of White Blood Cell Subtypes in Adult Trauma Patients with Stress-Induced Hyperglycemia
Authors: Rau Cheng-Shyuan , Kuo Spencer Chia-Hao , Tsai Ching-Hua , Chou Sheng-En , Su Wei-Ti , Hsu Shiun-Yuan , Hsieh Ching-Hua
Published: November 2023

Background: Blood immune cell subset alterations following trauma can indicate a patient′s immune–inflammatory status. This research explored the influence of stress-induced hyperglycemia (SIH) on platelet counts and white blood cell (WBC) subtypes, including the derived indices of the monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), in trauma patients. Methods: We studied 15,480 adult trauma patients admitted from 1 January 1998 to 31 December 2022. They were categorized into four groups: nondiabetic normoglycemia (NDN, n = 11,602), diabetic normoglycemia (DN, n = 1750), SIH (n = 716), and diabetic hyperglycemia (DH, n = 1412). A propensity score-matched cohort was formed after adjusting for age, sex, and comorbidities, allowing for comparing the WBC subtypes and platelet counts. Results: Patients with SIH exhibited significantly increased counts of monocytes, neutrophils, and lymphocytes in contrast to NDN patients. However, no significant rise in platelet counts was noted in the SIH group. There were no observed increases in these cell counts in either the DN or DH groups. Conclusions: Our results demonstrated that trauma patients with SIH showed significantly higher counts of monocytes, neutrophils, and lymphocytes when compared to NDN patients, whereas the DN and DH groups remained unaffected. This underscores the profound association between SIH and elevated levels of specific WBC subtypes.
The Role of Erythrocyte Sedimentation Rate (ESR) in Myeloproliferative and Lymphoproliferative Diseases: Comparison between DIESSE CUBE 30 TOUCH and Alifax Test 1
Authors: Pelagalli Martina , Tomassetti Flaminia , Nicolai Eleonora , Giovannelli Alfredo , Codella Silvia , Iozzo Mariannina , Massoud Renato , Secchi Roberto , Venditti Adriano , Pieri Massimo , Bernardini Sergio
Published: November 2023

(1) Background: The erythrocyte sedimentation rate (ESR) is widely diffused in hematology laboratories to monitor inflammatory statuses, response to therapies (such as antibiotics), and oncologic diseases. However, ESR is not a specific diagnostic marker but needs to be contextualized and compared with clinical and other laboratory findings. This study aimed to investigate the performance of two automated instruments, namely the DIESSE CUBE 30 TOUCH (DIESSE, Siena, Italy) and the Alifax Test 1 (Alifax Srl, Polverara, Italy), in comparison with the gold standard, the Westergren method, in lymphoproliferative and myeloproliferative patients. (2) Methods: 97 EDTA samples were selected from the hematology department of Roma Tor Vergata Hospital and analyzed. Statistical analysis was applied. (3) A good correlation between CUBE 30 TOUCH and the gold standard was observed in the overall sample (R2 = 0.90), as well as in patients with lymphoproliferative diseases (R2 = 0.90) and myeloproliferative diseases (R2 = 0.90). The correlation between Test 1 and the gold standard was observed in the overall sample (R2 = 0.68), as well as in patients with lymphoproliferative diseases (R2 = 0.79) and myeloproliferative diseases (R2 = 0.53). (4) Conclusions: The CUBE 30 TOUCH appears to be a more trustworthy tool for evaluating ESR in these pathologies.
Enhancing Predictability Assessment: An Overview and Analysis of Predictability Measures for Time Series and Network Links
Authors: Bezbochina Alexandra , Stavinova Elizaveta , Kovantsev Anton , Chunaev Petr
Published: November 2023

Driven by the variety of available measures intended to estimate predictability of diverse objects such as time series and network links, this paper presents a comprehensive overview of the existing literature in this domain. Our overview delves into predictability from two distinct perspectives: the intrinsic predictability, which represents a data property independent of the chosen forecasting model and serves as the highest achievable forecasting quality level, and the realized predictability, which represents a chosen quality metric for a specific pair of data and model. The reviewed measures are used to assess predictability across different objects, starting from time series (univariate, multivariate, and categorical) to network links. Through experiments, we establish a noticeable relationship between measures of realized and intrinsic predictability in both generated and real-world time series data (with the correlation coefficient being statistically significant at a 5% significance level). The discovered correlation in this research holds significant value for tasks related to evaluating time series complexity and their potential to be accurately predicted.
Impacts of Digital Financial Inclusion on Urban–Rural Income Disparity: A Comparative Research of the Eastern and Western Regions in China
Authors: Liu Jing , Puah Chin-Hong , Arip Mohammad Affendy , Jong Meng-Chang
Published: November 2023

This study aims to investigate the influence of digital financial inclusion on China’s urban–rural income disparity. A comparative analysis on income differences between western and eastern regions in China was conducted in this paper. The study utilized a static panel approach as it consisted of 22 provinces in China that covered the period from 2011 to 2020. This paper employs Stata software for the data analysis. The dependent variable of this study is the urban–rural income gap. Meanwhile, the independent variables consist of the total index level, breadth of coverage, depth of use, degree of digitization, digital payment level, digital insurance level, and digital credit level. The control variables employed in this article are education level, financial support, economic transformation, technological progress, and trade openness. The empirical outcomes indicate that the seven independent variables potentially minimize the urban–rural income gap between the two regions. However, digital financial inclusion appears to have a more significant effect in lessening the urban–rural gap in the western region compared to the eastern region in China. The findings demonstrate that all the variables exhibit a higher degree of influence on the urban–rural income differences in the west than in the east, except for the credit index. The outcome reveals that the effect of the credit index in the western region (0.10%) is slightly lower than the eastern region (0.11%). In general, the present findings can provide valuable insights for policy makers in their efforts to address the urban–rural income gap in the two regions through the implementation of digital financial inclusion initiatives. The study should be conducted regularly to observe the trend of the income disparities between the western and eastern regions in China. Future studies can also focus on other regions or narrow the focus to provincial and city levels to capture more detailed information.
Evaluation of Linguistics Students’ Learning Outcomes in Peer Teaching Courses: The Effect of Altruistic and Egoistic Behaviors
Authors: Anosova Natalia , Dashkina Aleksandra , Kobicheva Aleksandra , Shostak Ekaterina , Tarkhov Dmitriy
Published: November 2023

In the current study, we evaluated the students’ foreign language lexical and grammatical skills in the course based on the peer teaching methodology and analyzed the effect of their altruistic and egoistic behaviors on learning results. This experiment was conducted in a groups of senior students majoring in linguistics. The total number of participants accounted for 197 students (101 students in reference groups and 96 in exposure groups); the difference between the reference and exposure groups was that the undergraduates in the latter were to prepare a fragment of a lesson, create exercises, and act in the capacity of a teacher during the course. To evaluate students’ foreign language lexical and grammatical skills, the diagnostic test was conducted at the beginning and at the end of the experiment. Apart from comparing the diagnostic and final tests, we also circulated a questionnaire which checked the students’ egoistic and altruistic tendencies. The data appeared to be quite noisy; therefore, we processed them with a tool which proves effective when it comes to solving such problems, i.e., neural networks. According to the results on learning outcomes, students improved their English proficiency in the exposure groups to a greater extent than in the reference groups. At the same time, the results of the psychological tests revealed that the higher the students’ training level, the less altruistic they are. Also, it was detected that the more altruistic learners’ progress in outcomes was higher than those of the more selfish students, regardless of the way in which the learning process was organized. Moreover, the statistical data proved the efficiency of the peer teaching methodology for students’ majoring in linguistics, despite their psychological characteristics.
Consistent Weighted Correlation-Based Attention for Transformer Tracking
Authors: Liu Lei , Fang Genwen , Wang Jun , Wang Shuai , Wang Chun , Shen Longfeng , Zhu Kongfen , Melo Silas N.
Published: November 2023

Attention mechanism takes a crucial role among the key technologies in transformer-based visual tracking. However, the current methods for attention computing neglect the correlation between the query and the key, which results in erroneous correlations. To address this issue, a CWCTrack framework is proposed in this study for transformer visual tracking. To balance the weights of the attention module and enhance the feature extraction of the search region and template region, a consistent weighted correlation (CWC) module is introduced into the cross-attention block. The CWC module computes the correlation score between each query and all keys. Then, the correlation multiplies the consistent weights of the other query–key pairs to acquire the final attention weights. The weights of consistency are computed by the relevance of the query–key pairs. The correlation is enhanced for the relevant query–key pair and suppressed for the irrelevant query–key pair. Experimental results conducted on four prevalent benchmarks demonstrate that the proposed CWCTrack yields preferable performances.
Face Recognition Bias Assessment through Quality Estimation Models
Authors: Lopez Paya Luis , Cordoba Pedro , Sanchez Perez Angela , Barrachina Javier , Benavent-Lledo Manuel , Mulero-Pérez David , Garcia-Rodriguez Jose
Published: November 2023

Recent advances in facial recognition technology have achieved outstanding performance, but unconstrained face recognition remains an ongoing issue. Facial-image-quality-evaluation algorithms evaluate the quality of the input samples, providing crucial information about the accuracy of recognition decisions. By doing so, this can lead to improved results in challenging scenarios. In recent years, significant progress has been made in assessing the quality of facial images. The computation of quality scores has become highly precise and closely correlated with the model results. In this paper, we reviewed and analyzed the existing biases of cutting-edge quality-estimation techniques for face recognition. Our experimentation focused on the quality estimators developed by MagFace, FaceQNet, and SER-FIQ and were evaluated on the CelebA reference dataset. A study of bias in the face-recognition model was conducted by analyzing the quality scores presented in each article. This allowed for an examination of existing biases within both the quality estimators and the face-recognition models.
Enhancing Electrical Load Prediction Using a Bidirectional LSTM Neural Network
Authors: Pavlatos Christos , Makris Evangelos , Fotis Georgios , Vita Vasiliki , Mladenov Valeri
Published: November 2023

Precise anticipation of electrical demand holds crucial importance for the optimal operation of power systems and the effective management of energy markets within the domain of energy planning. This study builds on previous research focused on the application of artificial neural networks to achieve accurate electrical load forecasting. In this paper, an improved methodology is introduced, centering around bidirectional Long Short-Term Memory (LSTM) neural networks (NN). The primary aim of the proposed bidirectional LSTM network is to enhance predictive performance by capturing intricate temporal patterns and interdependencies within time series data. While conventional feed-forward neural networks are suitable for standalone data points, energy consumption data are characterized by sequential dependencies, necessitating the incorporation of memory-based concepts. The bidirectional LSTM model is designed to furnish the prediction framework with the capacity to assimilate and leverage information from both preceding and forthcoming time steps. This augmentation significantly bolsters predictive capabilities by encapsulating the contextual understanding of the data. Extensive testing of the bidirectional LSTM network is performed using multiple datasets, and the results demonstrate significant improvements in accuracy and predictive capabilities compared to the previous simpleRNN-based framework. The bidirectional LSTM successfully captures underlying patterns and dependencies in electrical load data, achieving superior performance as gauged by metrics such as root mean square error (RMSE) and mean absolute error (MAE). The proposed framework outperforms previous models, achieving a remarkable RMSE, attesting to its remarkable capacity to forecast impending load with precision. This extended study contributes to the field of electrical load prediction by leveraging bidirectional LSTM neural networks to enhance forecasting accuracy. Specifically, the BiLSTM’s MAE of 0.122 demonstrates remarkable accuracy, outperforming the RNN (0.163), LSTM (0.228), and GRU (0.165) by approximately 25%, 46%, and 26%, in the best variation of all networks, at the 24-h time step, while the BiLSTM’s RMSE of 0.022 is notably lower than that of the RNN (0.033), LSTM (0.055), and GRU (0.033), respectively. The findings highlight the significance of incorporating bidirectional memory and advanced neural network architectures for precise energy consumption prediction. The proposed bidirectional LSTM framework has the potential to facilitate more efficient energy planning and market management, supporting decision-making processes in power systems.
One-Dimensional Convolutional Wasserstein Generative Adversarial Network Based Intrusion Detection Method for Industrial Control Systems
Authors: Cai Zengyu , Du Hongyu , Wang Haoqi , Zhang Jianwei , Si Yajie , Li Pengrong
Published: November 2023

The imbalance between normal and attack samples in the industrial control systems (ICSs) network environment leads to the low recognition rate of the intrusion detection model for a few abnormal samples when classifying. Since traditional machine learning methods can no longer meet the needs of increasingly complex networks, many researchers use deep learning to replace traditional machine learning methods. However, when a large amount of unbalanced data is used for training, the detection performance of deep learning decreases significantly. This paper proposes an intrusion detection method for industrial control systems based on a 1D CWGAN. The 1D CWGAN is a network attack sample generation method that combines 1D CNN and WGAN. Firstly, the problem of low ICS intrusion detection accuracy caused by a few types of attack samples is analyzed. This method balances the number of various attack samples in the data set from the aspect of data enhancement to improve detection accuracy. According to the temporal characteristics of network traffic, the algorithm uses 1D convolution and 1D transposed convolution to construct the modeling framework of network traffic data of two competing networks and uses gradient penalty instead of weight cutting in the Wasserstein Generative Adversarial Network (WGAN) to generate virtual samples similar to real samples. After a large number of data sets are used for verification, the experimental results show that the method improves the classification performance of the CNN and BiSRU. For the CNN, after data balancing, the accuracy rate is increased by 0.75%, and the accuracy, recall rate and F1 are improved. Compared with the BiSRU without data processing, the accuracy of the s1D CWGAN-BiSRU is increased by 1.34%, and the accuracy, recall and F1 are increased by 7.2%, 3.46% and 5.29%.