bluuebunny/crossref_metadata_2025 huggingface dataset:
The Prospect and Challenges of Repurposing Established Drugs in Pulmonary Arterial Hypertension
Authors: Sener Sila Ozlem , Nasim Rateep , Nasim Talat
Published: September 2024

Pulmonary arterial hypertension (PAH) is a progressive disorder caused by the narrowing of small blood vessels in the lungs, which, in the absence of therapies, leads to right heart failure and premature death. No cure for this devastating disorder is known. Current management therapies aim to improve symptoms, and hence, there is a need to identify novel therapeutic interventions. The major objectives of this review are to critically evaluate current treatment strategies and highlight the challenges and prospects of established drugs and natural products for the resolution of PAH.
Effects of Technique Asymmetry on 500 m Speed Skating Performance
Authors: Liu Zimeng , Ding Meilin , Zhang Masen , Yu Bing , Liu Hui
Published: September 2024

This study aimed to determine the effects of technique asymmetry on 500 m straight-track speed skating performance. We analyzed 20 elite skaters, measuring their joint angles, center of mass shift, and times and speeds during the gliding and push-off phases. The technique asymmetry index (ASI) was calculated for each parameter, and paired t-tests were used to compare bilateral asymmetry. Spearman correlation coefficients assessed the relationship between the ASI and both the average straight track speed and overall performance. Significant bilateral asymmetries in the knee, push-off, trunk, and hip angles were found in both male and female participants (p < 0.05). The male participants demonstrated a higher right push-off speed (p = 0.029) and a longer left gliding time (p = 0.048). Significant asymmetry was also observed in the lateral shift of the center of mass during each phase of the straight-track skating gait cycle (p < 0.001). No significant correlation was found between the ASIs and the overall performance (p ≥ 0.067). These findings indicate that while elite speed skaters demonstrated significant bilateral technique asymmetry in straight track skating, these asymmetries did not significantly impact their overall performance.
Achieving Real-Time Prediction of Paroxysmal Atrial Fibrillation Onset by Convolutional Neural Network and Sliding Window on R-R Interval Sequences
Authors: Chen Wenjing , Zheng Peirong , Bu Yuxiang , Xu Yuanning , Lai Dakun
Published: September 2024

Early diagnosis of paroxysmal atrial fibrillation (PAF) could prompt patients to receive timely interventions in clinical practice. Various PAF onset prediction algorithms might benefit from accurate heart rate variability (HRV) analysis and machine learning classification but are challenged by real-time monitoring scenarios. The aim of this study is to present an end-to-end deep learning-based PAFNet model that integrates a sliding window technique on raw R-R intervals of electrocardiogram (ECG) segments to achieve a real-time prediction of PAF onset. This integration enables the deep convolutional neural network (CNN) to be customized as a light-weight architecture that accommodates the size of sliding windows simply by altering the input layer, and specifically its effectiveness in making a new prediction with each new heartbeat. Catering to the potential influence of input sizes, three CNN models were trained using 50, 100, and 200 R-R intervals, respectively. For each model, the performance of the automated algorithms was evaluated for PAF prediction using a ten-fold cross-validation. As a results, a total of 56,381 PAFN-type and 56,900 N-type R-R interval segments were collected from publicly accessible ECG databases, and a promising prediction performance of the automated algorithm with 100 R-R intervals was achieved, with a sensitivity of 97.12%, a specificity of 97.77%, and an accuracy of 97.45%, respectively. Importantly, the automated algorithm with a sliding window step of 1 could process one sample in only 23.1 milliseconds and identify the onset of PAF at least 45 min in advance. The present results suggest that the sliding window technique on raw R-R interval sequences, along with deep learning-based algorithms, may offer the possibility of providing an accurate, real-time, end-to-end clinical tool for mass monitoring of PAF.
Using Electrical Muscle Stimulation to Enhance Electrophysiological Performance of Agonist–Antagonist Myoneural Interface
Authors: Huang Jianping , Wang Ping , Wang Wei , Wei Jingjing , Yang Lin , Liu Zhiyuan , Li Guanglin
Published: September 2024

The agonist–antagonist myoneural interface (AMI), a surgical method to reinnervate physiologically-relevant proprioceptive feedback for control of limb prostheses, has demonstrated the ability to provide natural afferent sensations for limb amputees when actuating their prostheses. Following AMI surgery, one potential challenge is atrophy of the disused muscles, which would weaken the reinnervation efficacy of AMI. It is well known that electrical muscle stimulus (EMS) can reduce muscle atrophy. In this study, we conducted an animal investigation to explore whether the EMS can significantly improve the electrophysiological performance of AMI. AMI surgery was performed in 14 rats, in which the distal tendons of bilateral solei donors were connected and positioned on the surface of the left biceps femoris. Subsequently, the left tibial nerve and the common peroneus nerve were sutured onto the ends of the connected donor solei. Two stimulation electrodes were affixed onto the ends of the donor solei for EMS delivery. The AMI rats were randomly divided into two groups. One group received the EMS treatment (designated as EMS_on) regularly for eight weeks and another received no EMS (designated as EMS_off). Two physiological parameters, nerve conduction velocity (NCV) and motor unit number, were derived from the electrically evoked compound action potential (CAP) signals to assess the electrophysiological performance of AMI. Our experimental results demonstrated that the reinnervated muscles of the EMS_on group generated higher CAP signals in comparison to the EMS_off group. Both NCV and motor unit number were significantly elevated in the EMS_on group. Moreover, the EMS_on group displayed statistically higher CAP signals on the indirectly activated proprioceptive afferents than the EMS_off group. These findings suggested that EMS treatment would be promising in enhancing the electrophysiological performance and facilitating the reinnervation process of AMI.
Prognostic Value of Circulating Fibrosis Biomarkers in Dilated Cardiomyopathy (DCM): Insights into Clinical Outcomes
Authors: Kayvanpour Elham , Sedaghat-Hamedani Farbod , Li Daniel Tian , Miersch Tobias , Weis Tanja , Hoefer Imo , Frey Norbert , Meder Benjamin
Published: September 2024

Background: Dilated cardiomyopathy (DCM) involves myocardial remodeling, characterized by significant fibrosis and extracellular matrix expansion. These changes impair heart function, increasing the risk of heart failure and sudden cardiac death. This study investigates the prognostic value of circulating fibrosis biomarkers as a less invasive method in DCM patients. Methods: Plasma samples from 185 patients with confirmed DCM were analyzed to measure 13 circulating biomarkers using Luminex bead-based multiplex assays and ELISA. The prognostic value of these biomarkers was evaluated concerning heart failure-associated events and all-cause mortality. Results: Elevated MMP-2 levels (>1519.3 ng/mL) were linked to older age, higher diabetes prevalence, lower HDL, increased NT-proBNP and hs-TnT levels, and severe systolic dysfunction. High TIMP-1 levels (>124.9 ng/mL) correlated with elevated NT-proBNP, more atrial fibrillation, reduced exercise capacity, and larger right ventricles. Increased GDF-15 levels (>1213.9 ng/mL) were associated with older age, systemic inflammation, renal impairment, and poor exercise performance. Elevated OPN levels (>81.7 ng/mL) were linked to higher serum creatinine and NT-proBNP levels. Over a median follow-up of 32.4 months, higher levels of these biomarkers predicted worse outcomes, including increased risks of heart failure-related events and mortality. Conclusions: Circulating fibrosis biomarkers, particularly MMP-2, TIMP-1, GDF-15, and OPN, are valuable prognostic tools in DCM. They reflect the severity of myocardial remodeling and systemic disease burden, aiding in risk stratification and therapeutic intervention. Integrating these biomarkers into clinical practice could improve DCM management and patient prognosis.
Oxyresveratrol Enhances the Anti-Cancer Effect of Cisplatin against Epithelial Ovarian Cancer Cells through Suppressing the Activation of Protein Kinase B (AKT)
Authors: Thaklaewphan Phatarawat , Wikan Nitwara , Potikanond Saranyapin , Nimlamool Wutigri
Published: September 2024

Epithelial ovarian carcinoma poses a significant challenge due to its resistance to chemotherapy and propensity for metastasis, thereby reducing the effectiveness of conventional treatments. Hence, the identification of novel compounds capable of augmenting the anti-cancer efficacy of platinum-based chemotherapy is imperative. Oxyresveratrol (OXY), a derivative of resveratrol, has been demonstrated to possess antiproliferative and apoptosis-inducing effects across various cancer cell lines. Notably, OXY appears to exert its effects by inhibiting the PI3K/AKT/mTOR signaling pathway. However, the synergistic potential of OXY in combination with cisplatin against epithelial ovarian cancer has not yet been elucidated. The current study investigated the synergistic effects of OXY and cisplatin on the ovarian cancer cell lines SKOV3 and TOV21G. We found that OXY significantly enhanced cisplatin’s ability to reduce cell viability, induce apoptosis, induce cell cycle arrest, and increase the proportion of cells in the sub-G1 phase. Furthermore, OXY treatment alone dose-dependently inhibited the production of anti-apoptotic proteins including Mcl-1, Bcl-xL, and XIAP under EGF activation. Mechanistically, OXY suppressed the PI3K/AKT/mTOR signaling pathway by reducing phosphorylated AKT, while having no discernible effect on the MAPK pathway. These findings highlight OXY’s potential to enhance ovarian cancer cell sensitivity to chemotherapy, suggesting its development as a pharmaceutical adjunct for clinical use in combination therapies.
Investigation of High Frequency Irreversible Electroporation for Canine Spontaneous Primary Lung Tumor Ablation
Authors: Hay Alayna N. , Aycock Kenneth N. , Lorenzo Melvin F. , David Kailee , Coutermarsh-Ott Sheryl , Salameh Zaid , Campelo Sabrina N. , Arroyo Julio P. , Ciepluch Brittany , Daniel Gregory , Davalos Rafael V. , Tuohy Joanne
Published: September 2024

In this study, the feasibility of treating canine primary lung tumors with high-frequency irreversible electroporation (H-FIRE) was investigated as a novel lung cancer treatment option. H-FIRE is a minimally invasive tissue ablation modality that delivers bipolar pulsed electric fields to targeted cells, generating nanopores in cell membranes and rendering targeted cells nonviable. In the current study, canine patients (n = 5) with primary lung tumors underwent H-FIRE treatment with an applied voltage of 2250 V using a 2-5-2 µs H-FIRE waveform to achieve partial tumor ablation prior to the surgical resection of the primary tumor. Surgically resected tumor samples were evaluated histologically for tumor ablation, and with immunohistochemical (IHC) staining to identify cell death (activated caspase-3) and macrophages (IBA-1, CD206, and iNOS). Changes in immunity and inflammatory gene signatures were also evaluated in tumor samples. H-FIRE ablation was evident by the microscopic observation of discrete foci of acute hemorrhage and necrosis, and in a subset of tumors (n = 2), we observed a greater intensity of cleaved caspase-3 staining in tumor cells within treated tumor regions compared to adjacent untreated tumor tissue. At the study evaluation timepoint of 2 h post H-FIRE, we observed differential gene expression changes in the genes IDO1, IL6, TNF, CD209, and FOXP3 in treated tumor regions relative to paired untreated tumor regions. Additionally, we preliminarily evaluated the technical feasibility of delivering H-FIRE percutaneously under CT guidance to canine lung tumor patients (n = 2). Overall, H-FIRE treatment was well tolerated with no adverse clinical events, and our results suggest H-FIRE potentially altered the tumor immune microenvironment.
Differences between Tuberous Sclerosis Complex Patients with and without Epilepsy: The Results of a Quantitative Diffusion Tensor Imaging Study
Authors: Marcinkowska Anna B. , Jóźwiak Sergiusz , Sabisz Agnieszka , Tarasewicz Agnieszka , Rutkowska Beata , Dębska-Ślizień Alicja , Szurowska Edyta
Published: September 2024

Introduction: Tuberous sclerosis complex (TSC) is a neurocutaneous disease with a high incidence of epilepsy and damaging effects on cognitive development. To understand the mechanisms leading to abnormal cognitive development, diffusion tensor imaging (DTI) techniques have begun to be used in recent years. The present study is the first to investigate differences in the microstructure and integrity of white matter tracts in adult patients with TSC and with and without epilepsy. Method: A total of 37 patients with TSC (18 with epilepsy, median age 36 years; 19 without epilepsy, median age 35 years) without intellectual disability and autism spectrum disorder were included in the study. The control group (median age 34 years) comprised 37 individuals without psychiatric or neurodevelopmental disorders and neurological and cardiovascular diseases, diabetes, or addictions. A magnetic resonance imaging (MRI) DTI sequence was applied. Results: There were differences in the average values of DTI parameters between patients with TSC and epilepsy and patients with TSC but without epilepsy in five white matter bands. When comparing the average values of DTI parameters between patients with TSC and epilepsy and healthy controls, we found differences in 15 of 20 analysed white matter fibres. White matter tracts in patients with TSC and epilepsy had more abnormalities than in patients with TSC but without epilepsy. The former group presented abnormalities in longer white matter fibres, especially in the left hemisphere. However, the latter group presented abnormalities in more medial and shorter white matter fibres. Conclusion: This DTI study documents the changes in the brain white matter of patients with TSC associated with the presence of epilepsy.
Is Arterial Stiffness Interconnected with Cardiovascular Drug Prescription Patterns, Body Composition Parameters, and the Quality of Blood Pressure Regulation in Hypertensive Patients?
Authors: Radić Josipa , Vučković Marijana , Đogaš Hana , Gelemanović Andrea , Belančić Andrej , Radić Mislav
Published: September 2024

Background: Arterial hypertension (AH) is a significant risk factor for cardiovascular disease and is associated with increased arterial stiffness, particularly as measured by pulse wave velocity (PWV). This study aims to explore the relationships between age groups, antihypertensive and new oral antidiabetic drugs, body composition, and arterial stiffness parameters in hypertensive patients. Methods: A single-center cross-sectional study was conducted including 584 participants who underwent 24 h ambulatory blood pressure monitoring (including central blood pressure (BP) and PWV measurement), body composition analysis, and provided medical history and current pharmacotherapy data. Results: The study found that PWV was significantly higher in patients with poorly regulated BP in those aged 65 years and older. Significant PWV predictors included systolic BP, heart rate, peripheral mean arterial pressure, peripheral pulse pressure, augmentation index, calcium channel blockers, moxonidine, sodium–glucose co-transporter 2 inhibitors, urapidil, and statin prescription. Also, statistically significant negative correlations were found between PWV and visceral fat level, fat-free mass, and the percentage of muscle mass. Conclusions: The findings suggest that arterial stiffness is interconnected with peripheral and central blood pressure parameters, body composition parameters, and prescribed hypertensive and new antidiabetic drugs.
New Onset of Acute and Chronic Hepatic Diseases Post-COVID-19 Infection: A Systematic Review
Authors: Lebbe Ahamed , Aboulwafa Ali , Bayraktar Nuran , Mushannen Beshr , Ayoub Sama , Sarker Shaunak , Abdalla Marwan Nour , Mohammed Ibrahim , Mushannen Malik , Yagan Lina , Zakaria Dalia
Published: September 2024

The SARS-CoV-2 virus caused a pandemic in the 2020s, which affected almost every aspect of life. As the world is recovering from the effect of the coronavirus, the concept of post-COVID-19 syndrome has emerged. Multiple organ systems have been implicated, including the liver. We aim to identify and analyze the reported cases of severe and long-term parenchymal liver injury post-COVID-19 infection. Several databases were used to conduct a comprehensive literature search to target studies reporting cases of severe and long-term parenchymal liver injury post-COVID-19 infection. Screening, data extraction, and cross checking were performed by two independent reviewers. Only 22 studies met our inclusion criteria. Our results revealed that liver steatosis, non-alcoholic fatty liver disease (NAFLD), and cirrhosis were the most reported liver associated complications post-COVID-19 infection. Moreover, complications like acute liver failure, hepatitis, and liver hemorrhage were also reported. The mechanism of liver injury post-COVID-19 infection is not fully understood. The leading proposed mechanisms include the involvement of the angiotensin-converting enzyme-2 (ACE-2) receptor expressed in the liver and the overall inflammatory state caused by COVID-19 infection. Future studies should incorporate longer follow-up periods, spanning several years, for better insight into the progression and management of such diseases.
Prognostic Protein Biomarker Screening for Thyroid Carcinoma Based on Cancer Proteomics Profiles
Authors: Xie Pu , Yin Qinglei , Wang Shu , Song Dalong
Published: September 2024

Thyroid carcinoma (THCA) ranks among the most prevalent cancers globally. Integrating advanced genomic and proteomic analyses to construct a protein-based prognostic model promises to identify effective biomarkers and explore new therapeutic avenues. In this study, proteomic data from The Cancer Proteomics Atlas (TCPA) and clinical data from The Cancer Genome Atlas (TCGA) were utilized. Using Kaplan–Meier, Cox regression, and LASSO penalized Cox analyses, we developed a prognostic risk model comprising 13 proteins (S100A4, PAI1, IGFBP2, RICTOR, B7-H3, COLLAGENVI, PAR, SNAIL, FAK, Connexin-43, Rheb, EVI1, and P90RSK_pT359S363). The protein prognostic model was validated as an independent predictor of survival time in THCA patients, based on risk curves, survival analysis, receiver operating characteristic curves and independent prognostic analysis. Additionally, we explored the immune cell infiltration and tumor mutational burden (TMB) related to these features. Notably, our study proved a novel approach for predicting treatment responses in THCA patients, including those undergoing chemotherapy and targeted therapy.
Optimizing Lung Condition Categorization through a Deep Learning Approach to Chest X-ray Image Analysis
Authors: Sanida Theodora , Sanida Maria Vasiliki , Sideris Argyrios , Dasygenis Minas
Published: September 2024

Background: Evaluating chest X-rays is a complex and high-demand task due to the intrinsic challenges associated with diagnosing a wide range of pulmonary conditions. Therefore, advanced methodologies are required to categorize multiple conditions from chest X-ray images accurately. Methods: This study introduces an optimized deep learning approach designed for the multi-label categorization of chest X-ray images, covering a broad spectrum of conditions, including lung opacity, normative pulmonary states, COVID-19, bacterial pneumonia, viral pneumonia, and tuberculosis. An optimized deep learning model based on the modified VGG16 architecture with SE blocks was developed and applied to a large dataset of chest X-ray images. The model was evaluated against state-of-the-art techniques using metrics such as accuracy, F1-score, precision, recall, and area under the curve (AUC). Results: The modified VGG16-SE model demonstrated superior performance across all evaluated metrics. The model achieved an accuracy of 98.49%, an F1-score of 98.23%, a precision of 98.41%, a recall of 98.07% and an AUC of 98.86%. Conclusion: This study provides an effective deep learning approach for categorizing chest X-rays. The model’s high performance across various lung conditions suggests its potential for integration into clinical workflows, enhancing the accuracy and speed of pulmonary disease diagnosis.
Computational Strategies to Enhance Cell-Free Protein Synthesis Efficiency
Authors: Kathirvel Iyappan , Gayathri Ganesan Neela
Published: September 2024

Cell-free protein synthesis (CFPS) has emerged as a powerful tool for protein production, with applications ranging from basic research to biotechnology and pharmaceutical development. However, enhancing the efficiency of CFPS systems remains a crucial challenge for realizing their full potential. Computational strategies offer promising avenues for optimizing CFPS efficiency by providing insights into complex biological processes and enabling rational design approaches. This review provides a comprehensive overview of the computational approaches aimed at enhancing CFPS efficiency. The introduction outlines the significance of CFPS and the role of computational methods in addressing efficiency limitations. It discusses mathematical modeling and simulation-based approaches for predicting protein synthesis kinetics and optimizing CFPS reactions. The review also delves into the design of DNA templates, including codon optimization strategies and mRNA secondary structure prediction tools, to improve protein synthesis efficiency. Furthermore, it explores computational techniques for engineering cell-free transcription and translation machinery, such as the rational design of expression systems and the predictive modeling of ribosome dynamics. The predictive modeling of metabolic pathways and the energy utilization in CFPS systems is also discussed, highlighting metabolic flux analysis and resource allocation strategies. Machine learning and artificial intelligence approaches are being increasingly employed for CFPS optimization, including neural network models, deep learning algorithms, and reinforcement learning for adaptive control. This review presents case studies showcasing successful CFPS optimization using computational methods and discusses applications in synthetic biology, biotechnology, and pharmaceuticals. The challenges and limitations of current computational approaches are addressed, along with future perspectives and emerging trends, such as the integration of multi-omics data and advances in high-throughput screening. The conclusion summarizes key findings, discusses implications for future research directions and applications, and emphasizes opportunities for interdisciplinary collaboration. This review offers valuable insights and prospects regarding computational strategies to enhance CFPS efficiency. It serves as a comprehensive resource, consolidating current knowledge in the field and guiding further advancements.
Foundational Engineering of Artificial Blood Vessels’ Biomechanics: The Impact of Wavy Geometric Designs
Authors: Yilmaz Galip
Published: September 2024

The design of wavy structures and their mechanical implications on artificial blood vessels (ABVs) have been insufficiently studied in the existing literature. This research aims to explore the influence of various wavy geometric designs on the mechanical properties of ABVs and to establish a foundational framework for advancing and applying these designs. Computer-aided design (CAD) and finite element method (FEM) simulations, in conjunction with physical sample testing, were utilized. A geometric model incorporating concave and convex curves was developed and analyzed with a symbolic mathematical tool. Subsequently, a total of ten CAD models were subjected to increasing internal pressures using a FEM simulation to evaluate the expansion of internal areas. Additionally, physical experiments were conducted further to investigate the expansion of ABV samples under pressure. The results demonstrated that increased wave numbers significantly enhance the flexibility of ABVs. Samples with 22 waves exhibited a 45% larger area under 24 kPa pressure than those with simple circles. However, the increased number of waves also led to undesirable high-pressure gradients at elevated pressures. Furthermore, a strong correlation was observed between the experimental outcomes and the simulation results, with a notably low error margin, ranging from 19.88% to 3.84%. Incorporating wavy designs into ABVs can effectively increase both vessel flexibility and the internal area under pressure. Finally, it was found that expansion depending on the wave number can be efficiently modeled with a simple linear equation, which could be utilized in future designs.
Investigation of a Camera-Based Contactless Pulse Oximeter with Time-Division Multiplex Illumination Applied on Piglets for Neonatological Applications
Authors: Thull René , Goedicke-Fritz Sybelle , Schmiech Daniel , Marnach Aly , Müller Simon , Körbel Christina , Laschke Matthias W. , Tutdibi Erol , Nourkami-Tutdibi Nasenien , Kaiser Elisabeth , Weber Regine , Zemlin Michael , Diewald Andreas R.
Published: September 2024

(1) Objective: This study aims to lay a foundation for noncontact intensive care monitoring of premature babies. (2) Methods: Arterial oxygen saturation and heart rate were measured using a monochrome camera and time-division multiplex controlled lighting at three different wavelengths (660 nm, 810 nm and 940 nm) on a piglet model. (3) Results: Using this camera system and our newly designed algorithm for further analysis, the detection of a heartbeat and the calculation of oxygen saturation were evaluated. In motionless individuals, heartbeat and respiration were separated clearly during light breathing and with only minor intervention. In this case, the mean difference between noncontact and contact saturation measurements was 0.7% (RMSE = 3.8%, MAE = 2.93%). (4) Conclusions: The new sensor was proven effective under ideal animal experimental conditions. The results allow a systematic improvement for the further development of contactless vital sign monitoring systems. The results presented here are a major step towards the development of an incubator with noncontact sensor systems for use in the neonatal intensive care unit.
Ternary Moral Empathy Model from the Perspective of Intersubjective Phenomenology
Authors: Zhao Zhihui , Ma Xiangzhen
Published: September 2024

The phenomenon of empathy is an intersubjective process of feeling and a particular form of intentionality. Moral empathy refers to a type of empathy that can trigger moral action, with the embodied intersubjectivity laying the foundation for its emergence. This paper attempts to propose a comprehensive theoretical model of moral empathy from the perspective of intersubjective phenomenology, which includes the following. (1) The moral dimension of perceptual empathy: at the subpersonal, unconscious, and perceptual–motor level, embodied empathic practices are essential for the formation of moral consciousness and the emergence of moral empathy. (2) The moral dimension of situational empathy: following the development of shared attention mechanisms, children can direct towards the intentional objects of others through embodied situational cues to perceive the psychological state of others and generate the moral empathy of “ought”, leading to dyadic morality that promotes cooperative behavior. (3) The moral dimension of narrative empathy: the narrative practices of moral empathy refer to the processes by which children could perceive and understand the moral situation of characters within an embodied narrative structure, subsequently generate prosocial motives such as empathic concern, and then accept the “objective” moral norms of the group consciousness embedded in the narrative.
Unraveling Investor Behavior: The Role of Hyperbolic Discounting in Panic Selling Behavior on the Global COVID-19 Financial Crisis
Authors: Lal Sumeet , Nguyen Trinh Xuan Thi , Bawalle Aliyu Ali , Khan Mostafa Saidur Rahim , Kadoya Yoshihiko
Published: September 2024

In financial markets, irrational behaviors such as hyperbolic discounting and panic selling are prevalent. However, their widespread empirical associations remain unexplored. Numerous behavioral theories discuss how cognitive biases exacerbate panic selling through the lens of immediate loss aversion, a phenomenon in which individuals exhibit impulsive decision-making tendencies due to an intense fear of financial loss during market upheaval. Despite the theoretical elucidation, empirical investigations of these dynamics are lacking. Using a robust dataset comprising 121,293 active investors sourced from a collaborative effort between Hiroshima University and Rakuten Securities Inc., this study used mean comparison tests and probit regression to analyze hyperbolic discounting’s role in panic selling behavior on the global COVID-19 financial crisis. The findings reveal that hyperbolic discounting plays a central role in triggering investors’ impulsive panic selling behavior, which is driven primarily by fear of potential losses. Other factors that influence panic selling behavior include age, male gender, low education level, financial literacy, household income, household assets, risk aversion, and overconfidence in financial knowledge. Our study explicates the need to address cognitive biases in financial decision making during market crises through strategies such as targeted financial education, regulatory interventions against market manipulation, and the provision of professional advice to investors.
Life Cycle Sustainability Assessment: An Index System for Building Energy Retrofit Projects
Authors: Song Pei , Wu Lingyu , Zhao Wenbo , Ma Wenting , Hao Jianli
Published: September 2024

As a major contributor to global energy consumption and greenhouse gas emissions, the building sector is crucial in shaping energy and climate change policies. Understanding building energy consumption is essential for developing effective policies, and comprehensive datasets and analyses are increasingly important. This paper outlines a structured methodology for developing a sustainability assessment index for building energy efficiency retrofits throughout a building’s life cycle, covering the design, construction, use, and out-of-use phases. It highlights the interdependencies among these phases, with the design plan influencing energy efficiency and material selection, the construction plan ensuring these goals are met, and the plans for energy management, demolition, and resource recovery focusing on sustainable practices. The keys to energy-efficient retrofits are sustainable materials, energy-efficient equipment, and green technologies, which help reduce energy consumption, emissions, and operating costs. Oversight and regulation are necessary to maintain standards. This research combines a literature review, surveys, interviews, the Delphi method, and an analytic hierarchy process (AHP) to develop a comprehensive evaluation system, categorizing 20 factors across a building’s life cycle and assigning weights based on environmental, economic, and social dimensions. The system provides a scientific basis for assessing the sustainability of energy efficiency programs, validated through consistency testing.
Study on Influence Mechanism of Tunnel Construction on Adjacent Pile Foundation and Resilience Assessment
Authors: Zhou Jun , Han Kaihang , Chen Weitao
Published: September 2024

To guarantee the safety of tunnel construction and the continued use of nearby structures, it is crucial to accurately forecast the size and extent of the plastic region that may occur due to tunnel excavation, as well as examine the impact on resilience. In this paper, the influence mechanism of tunnel construction on adjacent pile foundation and resilience assessment is investigated. Firstly, the stratum deformation and stress induced by tunnel construction are derived based on the thin-walled theory considering the influence of tunnel structure stiffness. Moreover, the resilience assessment based on the characteristics of the stratum plastic region is proposed to describe the degree of disturbance caused by tunnel construction to the adjacent pile foundation. Then, a comparison with a numerical simulation is conducted to verify the correctness of the prediction method of the stratum plastic region proposed in this paper. Finally, parameter sensitivity analysis is carried out, which indicates that pile parameters, soil parameters, and different tunnel outline conditions have a great influence on the prediction results. In order to reasonably control the impact of tunnel construction on the surrounding environment, safety control techniques, including advance grouting reinforcement and grouting uplift, need to be carefully designed.
Influence of the Diameter Size on the Deformation and Failure Mechanism of Shield Precast Segmental Tunnel Lining under the Same Burial Depth
Authors: Zhou Jun , Han Kaihang , Chen Weitao
Published: September 2024

With the development of large-diameter shield tunnels, how to realize effective security and stability control of shield tunnel lining has become a significant research topic. This paper investigates the deformation and failure mechanism of lining large diameter shield tunnels in depth and discusses the deformation characteristics and influencing factors of the lining of the shield tunnel with various diameters through the software of finite element analysis ABACUS. A set of models with varying diameters is built under identical stress conditions in order to maintain control over the variable. The utilization of the elastic–plastic model is observed in the application of bolts and rebar. The utilization of the Concrete Damage Plasticity model has been taken into account for the concrete lining. For the sake of comparison, the crown displacement of the shield tunnel, strain in tension and compressive zones, bolt stress and strain, deformation and intemal force distribution around the shield tunnel, and cracks in the tension zone, are carefully studied. An in-depth analysis is conducted to elucidate the variations in damage evolution mechanisms across linings of different sizes, within the framework of plastic hinge theory. The results indicate that the convergence deformation of large-diameter tunnel lining increases significantly during loading compared with that of small-diameter tunnel. Moreover, the probability of brittle failure is higher in big-diameter shield tunnels compared to small-diameter tunnels, indicating that these larger tunnel structures are more prone to suffering geometric instability.
Flexural Behavior of Precast Rectangular Reinforced Concrete Beams with Intermediate Connection Filled with High-Performance Concrete
Authors: Hamoda Ahmed , Emara Mohamed , Ahmed Mizan , Abadel Aref A. , Patel Vipulkumar Ishvarbhai
Published: September 2024

Precast rectangular reinforced concrete (PRRC) beams are joined on construction sites using concrete in situ to achieve the desired length. Limited research exists on the effect of intermediate connection shapes and the types of infilled concrete on the flexural performance of PRRC beams. This paper presents a comprehensive experimental and numerical investigation into the performance of PRRC beams with various intermediate connection geometries and infilled materials under flexural loading. The study examines rectangular, triangular, and semi-circular intermediate connections, along with the performance of beams infilled with normal concrete (NC), engineered cementitious composites (ECC), ultra-high-performance ECC (UHPECC), and rubberized ECC (RECC). The experimental results indicate that the rectangular intermediate connection exhibits superior performance in terms of strength and energy absorption compared to the triangular and semi-circular shapes. Beams incorporating UHPECC demonstrated the most significant improvements in strength and energy absorption, outperforming those with ECC and RECC for any shape of intermediate connection. Moreover, beams with rectangular connections and UHPECC infill exhibited the most significant increase in energy absorption and ultimate load compared to the beams with ECC and RECC. The ultimate load of the beams with UHPECC and tensile reinforcement bar diameters of 10 mm and 12 mm increased by 13% and 29%, respectively, compared to the control beam. The energy absorption of the beams with tensile reinforcement bar diameters of 10 and 12 mm was found to be 75% and 184% higher, respectively, than the control beam. In addition, an increase in tensile bar diameter was found to enhance both the energy absorption and the ultimate load capacity of the beams, regardless of the type of infill concrete. Beams incorporating UHPECC demonstrated the most significant improvements in strength and energy absorption, outperforming those with ECC and RECC. In particular, beams with rectangular connections and UHPECC infill exhibited an increase in energy absorption and ultimate load of up to 184% and 29%, respectively. UHPC was calculated to be as high as 184%, and 29%, respectively, compared to the control beams. In addition, an increase in tensile bar diameter was found to enhance both energy absorption and ultimate load capacity. Finite element modeling (FEM) was developed and validated against the experimental results to ensure accuracy. A parametric study was conducted to study the effects of various concrete types in triangular and semi-circular connections, as well as the influence of intermediate connection length on semi-circular connections under flexural loads. The findings reveal that increasing the length of intermediate connections increases the ultimate load of the beams.
Evaluating Life-Cycle Unit Costs of Traditional Cement Concrete and New Polymer Concrete Manholes in Wastewater Systems
Authors: Shrestha Kishor , Shrestha Pramen P. , Batista Jacimaria
Published: September 2024

Wastewater manholes are crucial infrastructure components in sewage systems. They provide necessary access points for inspection and maintenance. However, limited studies were conducted on the life-cycle cost analysis of manholes. The primary objective of this study is to compute and compare the Life-Cycle Unit Cost (LCUC) of cement concrete and polymer concrete manholes to identify a cost-effective alternative for public agencies. To achieve the objective, this study analyzed commonly used 1.83 m diameter manhole data; 343 cement concrete manhole and 88 polymer concrete manhole cost data were collected from the Clark County Water Reclamation District (CCWRD), Las Vegas, Nevada, United States. The results show that the initial costs of polymer concrete are higher than those of traditional cement concrete. Statistical tests were conducted to determine the group differences. The findings show that the LCUCs of polymer concrete manholes are significantly cost-effective when compared to traditional cement concrete manholes. Public agencies can utilize polymer concrete manholes to save costs in future water and wastewater pipeline manhole construction projects.
Facilitating Circular Transition in the Construction Industry: Optimizing a Prefabricated Construction Site Layout Using a Novel BIM-Integrated SLP-GA Model
Authors: Wang Lin , Wang Qi , Dong Shuxiu , Cao Yue , Wang Liang
Published: September 2024

Prefabricated construction is being developed as one of the pathways toward circularity in the construction industry. However, compared to traditional cast-in-place construction methods, the design of prefabricated construction site layouts presents unique challenges, such as managing the space for prefabricated components and lifting equipment, and coordinating the precise timing between off-site fabrication and on-site assembly. Existing research has primarily focused on traditional cast-in-place construction, leaving room for improvement in optimisation models for prefabricated site layouts. This study develops a BIM-based System Layout Planning-Genetic Algorithm (SLP-GA) model specifically tailored for prefabricated construction site optimisation. The proposed model improves the accuracy and visualisation of layout planning through BIM technology, enabling dynamic adjustments and real-time data integration. It also incorporates genetic algorithms to address complex multi-objective optimisation problems, avoiding local optima and overcoming the limitations of traditional SLP methods that rely on subjective judgements. Unlike previous studies that do not consider secondary handling, the optimisation objectives of this study focus on minimising material handling costs associated with secondary handling and maximising comprehensive relationships, including efficiency, safety and space utilisation. The application of this model in a case study shows a reduction in logistics costs of 8.58% and an improvement in comprehensive relationships of 11.61%, indicating significant improvements. This research advances optimisation methods for prefabricated construction site layouts, enriches optimisation objectives by considering secondary handling, and provides practical guidance for improving the efficiency and effectiveness of prefabricated construction projects.
Energy-Saving Optimization of HVAC Systems Using an Ant Lion Optimizer with Enhancements
Authors: Hu Bin , Guo Yuhu , Huang Wenjun , Jin Jianxiang , Zou Mingxuan , Zhu Zhikun
Published: September 2024

The complex and time-varying external climate conditions and multi-equipment variable coupling characteristics make it challenging to optimize the Heating, Ventilation, and Air Conditioning (HVAC) systems in existing buildings effectively. Additionally, the intricate energy exchange processes within HVAC systems present difficulties in developing accurate and generalizable energy consumption models. In response to these challenges, this paper proposes an Ant Lion Optimizer with Enhancements (ALOE) that can dynamically adjust the number of populations and the movement trend to improve the convergence speed and optimization ability, and randomly adjust the movement amplitude to enhance the local optimal escape ability. Finally, a case study of an office building in Hangzhou was carried out, and an overall energy consumption model of the HVAC system based on parameter identification and a general mechanism model was established. In this model, the energy-saving optimization effects of various advanced swarm intelligence optimization algorithms were compared. The experimental results demonstrate that under high, medium, and low load conditions, the ALOE algorithm achieves energy-saving rates of 28.16%, 28.26%, and 24.85%, respectively, the overall energy-saving rate for the entire day reaches 29.06%, which indicates the ALOE has significant superiority. This work will contribute to the development of energy-saving and emission-reduction technologies.
Current Advances and Challenges in the Management of Cutaneous Squamous Cell Carcinoma in Immunosuppressed Patients
Authors: Li Sophie , Townes Thomas , Na’ara Shorook
Published: September 2024

Cutaneous squamous cell carcinoma (cSCC) is the second most common skin malignancy and poses a significant risk to immunosuppressed patients, such as solid organ transplant recipients and those with hematopoietic malignancies, who are up to 100 times more likely to develop cSCC compared with the general population. This review summarizes the current state of treatment for cSCC in immunosuppressed patients, focusing on prevention, prophylaxis, surgical and non-surgical treatments, and emerging therapies. Preventative measures, including high-SPF sunscreen and prophylactic retinoids, are crucial for reducing cSCC incidence in these patients. Adjusting immunosuppressive regimens, particularly favoring mTOR inhibitors over calcineurin inhibitors, has been shown to lower cSCC risk. Surgical excision and Mohs micrographic surgery remain the primary treatments, with adjuvant radiation therapy recommended for high-risk cases. Traditional chemotherapy and targeted therapies like EGFR inhibitors have been utilized, though their efficacy varies. Immunotherapy, particularly with agents like cemiplimab and pembrolizumab, has shown promise, but its use in immunosuppressed patients requires further investigation due to potential risks of organ rejection and exacerbation of underlying conditions. Treatment of cSCC in immunosuppressed patients is multifaceted, involving preventive strategies, tailored surgical approaches, and cautious use of systemic therapies. While immunotherapy has emerged as a promising option, its application in immunosuppressed populations necessitates further research to optimize safety and efficacy. Future studies should focus on the integration of personalized medicine and combination therapies to improve outcomes for this vulnerable patient group.
Emerging Catalytic Strategies Driven by External Field for Heavy Metal Remediation
Authors: Zhang Xinyue , Chen Shanliang , Rehman Attiq Ur , Zhang Suwei , Zhang Qingzhe , Liu Yong , Li Shun
Published: September 2024

Heavy metal pollution presents significant environmental and public health risks due to its widespread occurrence and resistance to degradation. There is a pressing need for innovative solutions to address the challenge of heavy metal ion removal from water resources. In this review, we highlight recent advancements in emerging catalytic strategies for efficient heavy metal remediation, leveraging various external fields such as electric, mechanical, magnetic, and thermoelectric fields, as well as their synergetic coupling with photocatalysis technology. These novel approaches offer promising avenues for enhancing heavy metal removal efficacy and environmental sustainability. In particular, this review focuses on recent breakthroughs in new materials systems capable of functioning under diverse external fields, heralding future advancements in heavy metal remediation. Finally, we discuss the current challenges and future perspectives in this emerging research area.