bluuebunny/crossref_metadata_2025 huggingface dataset:
Micro-Process of Open Innovation in Megaprojects Under Sense-Making Perspective
Authors: Li Fei , Liu Quanle , Fang Kai
Published: October 2024

Compared with traditional closed innovation, open innovation brings more new ideas, technologies, and resources to megaprojects, which is becoming increasingly important in the face of growing complexity and sustainability. Drawing on the application of sense-making theory in organizational change, this study conducts an empirical case study to explore how open innovation is carried out in megaprojects, as well as how to explain the processes at the micro level. The Changchun Metropolitan Circle Ring Expressway phase II project was selected as the analytical case and grounded coding technology was adopted to analyze the realization process of open innovation. The results revealed that managers as organizers first completed their own sense making and then influenced others’ sense making via sense giving to unify understanding and complete innovation mode transformation. Moreover, managers need to adjust sense making for themselves and sense giving for others according to interactive feedback. This study illustrated that open innovation strategies need to enact some new relevant routines in order for a cognitive reorientation to take place. A multi-level and multi-dimensional micro-mechanism and process was proposed to guide open innovation behavior in megaprojects.
Research on the Impact of Managers’ Safety Perception on Construction Workers’ Safety Behaviors
Authors: Liu Kongling , Luo Xun , Feng Jing , Li Hujun , Liu Baijian , Jian Yu
Published: October 2024

The construction industry is replete with significant safety risks, underscoring the necessity to comprehend the factors that shape workers’ safety behaviors for efficacious accident prevention. This study aims to investigate the impact of managers’ safety perception (MSP) on construction workers’ safety behaviors (WSBs), while also exploring the mediating roles of workers’ safety awareness (WSA) and workers’ safety competency (WSC). Utilizing a structural equation model (SEM), data were collected from 248 construction workers through a validated questionnaire. The findings indicate that MSP has a direct influence on WSBs (mean effect size = 0.065, p < 0.01) and an indirect effect on WSBs through enhanced WSA (effect size = 0.386, p < 0.01) and WSC (effect size = 0.392, p < 0.01). This research makes a contribution to the existing literature in several ways. First, it introduces a new measurement scale for MSP. Second, it highlights the direct and indirect effects on WSBs. Third, it emphasizes the importance of fostering safety awareness and competency among workers. In addition, the study offers practical implications for construction managers seeking to improve safety outcomes on-site.
Probabilistic Prediction and Assessment of Train-Induced Vibrations Based on Mixture Density Model
Authors: Tao Ziyu , He Lingshan , Tu Desi , Zou Chao
Published: October 2024

This study presents a probabilistic prediction method for train-induced vibrations by combining a deep neural network (DNN) with the mixture density model in a cascade fashion, referred to as the DNN-RMDN model in this paper. A benchmark example is conducted to demonstrate and evaluate the prediction performance of the DNN-RMDN model. Subsequently, the model is applied to a case study to investigate and compare the uncertainties of train-induced vibrations in the throat area and testing line area of a metro depot. After training, the model is capable of accurately predicting the probability density function (PDF) of train-induced vibrations at different distances from the track and at different frequencies. Utilizing the predicted PDF, probabilistic assessments can be performed to ascertain the likelihood of surpassing predefined limits. By employing a mixture density model instead of a single Gaussian distribution, the DNN-RMDN model achieves more accurate prediction of the PDF for train-induced vibrations. The proposed probabilistic assessment framework can effectively assist in vibration screening during the planning phase and in selecting and designing vibration mitigation measures of appropriate levels.
Study on Dynamic Factors of Damped Beam Members Under Exponential Attenuation Loading
Authors: Hong Xin , Geng Shaobo , Feng Rui
Published: October 2024

Blast loading is characterized as an impact loading with exponential attenuation, while damping serves as an intrinsic parameter that affects the vibration effect of beam members. The linear attenuation for simplified blast loading and undamped situation for beam members is often adopted by most scholars or codes for the calculation of dynamic factors. These assumptions that do not conform to the actual situation can lead to deviations in the results of the dynamic factor. In this study, the implicit solutions for the dynamic factors of both flexible and rigid beam members were derived by the exponential attenuation loading and damping of beam members. The dynamic response verification of an H-shaped steel beam blast test was completed using LS-DYNA software. The comparison calculation of the theoretical solutions of dynamic factors in this paper with the Chinese blast-resistant design code and finite element simulation was carried out. The results show that the dynamic factor will be higher when the blast loading is simplified to linear attenuation loading for undamped beams. The shape parameter of the exponential attenuation loading and the damping ratio of beam members both reduce the effect of the dynamic factor, with the damping ratio having a more significant effect.
Experimental Study on the Influence of Sidewall Excavation Width and Rock Wall Slope on the Stability of the Surrounding Rock in Hanging Tunnels
Authors: Zhang Hao , Luo Tianyu , Xiang Zhao , Cai Zhiwei , Wu Tongqing , Zhang Dong , Liu Bing , Feng Hu
Published: October 2024

Hanging tunnels are a unique type of highway constructed on hard cliffs and towering mountains, renowned for their steep and distinctive characteristics. Compared to traditional full tunnels or open excavations, hanging tunnels offer significant advantages in terms of cost and construction time. However, the engineering design and construction cases of such tunnels are rarely reported, and concerns about construction safety and surrounding rock stability have become focal points. Taking the Shibanhe hanging tunnel as a case study, this paper focuses on the stability of the surrounding rock during the excavation of limestone hanging tunnels using physical analog model (PAM) experiments and numerical calculation. Firstly, based on the similarity principle and orthogonal experiments, river sand, bentonite, gypsum and P.O42.5 ordinary Portland cement were selected as the raw materials to configure similar materials from limestone. Secondly, according to the characteristics of hanging tunnels, geological models were designed, and excavation experiments with three different sidewall excavation widths and rock wall slopes were carried out. The effects of these variables on the stress and displacement behavior of the surrounding rock were analyzed, and the laws of their influence on the stability of the surrounding rock were explored. Finally, numerical simulations were employed to simulate the tunnel excavation, and the results of the numerical simulations and PAM experiments were compared and analyzed to verify the reliability of the PAM experiment. The results showed that the vertical stress on the rock pillars was significantly affected by the sidewall excavation widths, with a maximum increase rate of 53.8%. The displacement of the sidewall opening top was greatly influenced by the sidewall excavation widths, while the displacement of the sidewalls was more influenced by the rock wall slope. The experimental results of the PAM are consistent with the displacement and stress trends observed in the numerical simulation results, verifying their reliability. These findings can provide valuable guidance and reference for the design and construction of hanging tunnels.
The Flexural Behavior of Reinforced Ultra-High Performance Engineering Cementitious Composite (UHP-ECC) Beams Fabricated with Polyethylene Fiber (Numerical and Analytical Study)
Authors: Yassin Ahmed M. , Hafez Mohamed Ahmed , Mohie Eldin Mohammad
Published: October 2024

Ultra-high performance engineered cementitious composite (UHP-ECC), which is a new and ductile version of concrete, has attracted researchers recently due to its exceptional mechanical properties: its very high compressive strength (from 100 to 200 MPa) and very high tensile strain capacity (not less than 3% and up to 8%). However, the available experimental literature is small due to its very high cost. To overcome the high cost of the experiments of UHP-ECC, the finite element modeling package ANSYS was used to create a new modeling technique using the Menetrey–Willam constitutive model, recently added to ANSYS. This technique was validated using previous experimental results for UHP-ECC beams and found to be accurate and effective. The previous FE model was used to conduct a parametric study and the variables—the compressive strength of the concrete, the percentage of the volume content of polyethylene fibers, the tensile reinforcement ratio, and the span-to-depth ratio—were found to be effective upon the flexure behavior of the reinforced UHP-ECC beams. As the analysis and design of UHP-ECC beams fabricated with polyethylene fiber are not available yet through design codes, an analytical model including some equations was deduced to calculate the flexure capacity of such beams. The results of the parametric study were used to investigate the validity and accuracy of the analytical model. The proposed equations demonstrated a good estimation compared with the numerical analysis results.
Sustainability Performance Differences of Industrial Heritage Regeneration Implementation Modes
Authors: Chu Tong , Zhou Minghao , Wu Jiang
Published: October 2024

In high-density cities around the world, the contradiction of sustaining development and limited resources has become more evident. Transforming historic industrial buildings, through both functional and spatial adjustments, has emerged as a key strategy to manage these challenges effectively. There is a significant demand for the quick regeneration of industrial heritage districts, resulting in the emergence of various implementation modes (IMs). While the Sustainable Development Goals (SDGs) have gained widespread acceptance, the integration of sustainability principles into urban regeneration practices has strengthened globally. However, in many regions, approaches to achieving sustainable regeneration are still unclear, with a lack of evaluation and adjustment of sustainability performance (SP). This paper combines qualitative analysis and a quantitative assessment of indicators to compare three representative case studies with different IMs. It explores whether there is a connection between the chosen IM and SP, examines the mechanisms of impact, and discusses how to select the most suitable IM for industrial heritage regeneration. The study confirms the practicality of an SP evaluation system and identifies key factors within IMs that affect SP. Future research is expected to produce tools that support the promotion of sustainability in industrial heritage regeneration efforts.
Enhancing Functional Properties and Mold Resistance of Gypsum Plasters with Caffeine
Authors: Kobetičová Klára , Krejsová Jitka , Keppert Martin , Pommer Vojtěch , Burianová Ivana , Böhm Martin , Černý Robert
Published: October 2024

Caffeine is a proven bioactive substance against fungi for internal use, without any observed negative effects on properties of wood materials. However, its addition to other building materials for internal use has not yet been tested. For this reason, the effects of caffeine’s addition on selected properties of gypsum plasters were studied. Two experimental approaches were applied in the present study: (A) using an aqueous caffeine solution (20 g/L) for the preparation of gypsum plaster; and (B) immersing the gypsum plaster in the same caffeine concentration. The results showed a significant increase in the compressive strength of the plaster after 7 days of curing in laboratory conditions (variant A—46%, variant B—16%). The application of caffeine led to a substantial improvement in the water resistance of gypsum. Gypsum plasters were also exposed to a mixture of air molds. The plasters directly mixed with caffeine were about 72% less attacked by molds than the control, while immersed samples showed only a 20% reduction in mold coverage. The main conclusions of the study are that caffeine is a suitable additive for the improvement of gypsum’s compressive strength, and its addition leads to a higher resistance of gypsum against humidity and mold attacks.
A Calculation Study on the Escape of Incident Solar Radiation in Buildings with Glazing Facades
Authors: Lu Shunyao , Wang Zhengzhi , Chen Tao
Published: October 2024

More and more modern buildings are using glass curtain walls as their building envelope. The large area of window leads to a significant increase in solar heat gain, resulting in an increase in the cooling load and energy consumption of the building envelope. In the calculation of building cooling load, the thermal performance parameter of windows, the solar heat gain coefficient, is used to calculate the solar radiation heat gain of the windows. The window-to-wall ratio of buildings with glazing facades is large, and the phenomenon of escape of incident solar radiation cannot be ignored. In order to calculate the solar radiation escape rate, a dynamic model of solar radiation escape rate incorporating the solar path tracking model is developed in this research, which can achieve big data simulation analysis based on actual meteorological conditions. The model is programmed and simulated using MATLAB R2024a software. Five representative cities from different climate regions in China are selected and the variation rule of solar radiation escape rate are analyzed on three different time scales: day, month, and year. The influence of building orientation was also calculated and analyzed. The numerical calculation results indicate that the escape solar radiation rate varies with the incident angle of solar radiation at different times. It was found that the smaller the solar azimuth angle and solar altitude angle, the smaller the escape rate of solar radiation. The latitude of a city has a significant impact on the solar radiation escape rate. The weighted average of the solar radiation escape rates for each city were calculated for both summer and winter. Regardless of the season, the city’s location, and the orientation of the room, the value of solar radiation escape rate varies from 8.64% to 10.33%, which indicates that the solar radiation escape phenomenon cannot be ignored in glass curtain wall buildings. The results can be used as a reference value of solar radiation escape rate for the correction of actual solar heat gain of buildings in different climate regions.
Design Principles and Applications of Fluorescent Kinase Inhibitors for Simultaneous Cancer Bioimaging and Therapy
Authors: Ganai Ab Majeed , Vrettos Eirinaios I. , Kyrkou Stavroula G. , Zoi Vasiliki , Khan Pathan Tabasum , Karpoormath Rajshekhar , Bouziotis Penelope , Alexiou George A. , Kastis George A. , Protonotarios Nicholas E. , Tzakos Andreas G.
Published: October 2024

Kinase inhibitors are potent therapeutic agents in cancer treatment, but their effectiveness is frequently restricted by the inability to image the tumor microenvironment. To address this constraint, kinase inhibitor–fluorophore conjugates have emerged as promising theranostic agents, allowing for simultaneous cancer diagnosis and treatment. These conjugates are gaining attention for their ability to visualize malignant tissues and concurrently enhance therapeutic interventions. This review explores the design principles governing the development of multimodal inhibitors, highlighting their potential as platforms for kinase tracking and inhibition via bioimaging. The structural aspects of constructing such theranostic agents are critically analyzed. This work could shed light on this intriguing field and provide adequate impetus for developing novel theranostic compounds based on small molecule inhibitors and fluorophores.
Grad-CAM Enabled Breast Cancer Classification with a 3D Inception-ResNet V2: Empowering Radiologists with Explainable Insights
Authors: Talaat Fatma M. , Gamel Samah A. , El-Balka Rana Mohamed , Shehata Mohamed , ZainEldin Hanaa
Published: October 2024

Breast cancer (BCa) poses a severe threat to women’s health worldwide as it is the most frequently diagnosed type of cancer and the primary cause of death for female patients. The biopsy procedure remains the gold standard for accurate and effective diagnosis of BCa. However, its adverse effects, such as invasiveness, bleeding, infection, and reporting time, keep this procedure as a last resort for diagnosis. A mammogram is considered the routine noninvasive imaging-based procedure for diagnosing BCa, mitigating the need for biopsies; however, it might be prone to subjectivity depending on the radiologist’s experience. Therefore, we propose a novel, mammogram image-based BCa explainable AI (BCaXAI) model with a deep learning-based framework for precise, noninvasive, objective, and timely manner diagnosis of BCa. The proposed BCaXAI leverages the Inception-ResNet V2 architecture, where the integration of explainable AI components, such as Grad-CAM, provides radiologists with valuable visual insights into the model’s decision-making process, fostering trust and confidence in the AI-based system. Based on using the DDSM and CBIS-DDSM mammogram datasets, BCaXAI achieved exceptional performance, surpassing traditional models such as ResNet50 and VGG16. The model demonstrated superior accuracy (98.53%), recall (98.53%), precision (98.40%), F1-score (98.43%), and AUROC (0.9933), highlighting its effectiveness in distinguishing between benign and malignant cases. These promising results could alleviate the diagnostic subjectivity that might arise as a result of the experience-variability between different radiologists, as well as minimize the need for repetitive biopsy procedures.
GNAQ/GNA11-Related Benign and Malignant Entities—A Common Histoembriologic Origin or a Tissue-Dependent Coincidence
Authors: Pilch Justyna , Mizera Jakub , Tota Maciej , Donizy Piotr
Published: October 2024

Uveal melanoma (UM), recognized as the most prevalent primary intraocular malignancy in adults, is primarily driven by mutations in the GNAQ and GNA11 genes. These genetic alterations are also implicated in other conditions, which exhibit distinct morphological characteristics. In this article, we investigate the role of GNAQ and GNA11 mutations across varied disorders (e.g., UM, skin blue nevi, and hemangiomas), emphasizing the shared pathogenic mechanisms that connect them despite their differing clinical manifestations. By investigating the molecular pathways affected by these mutations, we provide insights into the potential for targeted therapies that could address not only UM but also other disorders associated with GNAQ/GNA11 mutations. Moreover, we discuss the role of SOX10-positive perivascular cells that may be implicated in the complex pathophysiology of GNAQ/GNA11-related entities. Understanding the common molecular foundation of these conditions opens new ways for research and treatment opportunities, potentially leading to more effective, personalized therapeutic strategies.
Paraneoplastic Resolution Holds Prognostic Utility in Patients with Metastatic Renal Cell Carcinoma
Authors: Palmateer Gregory , Nicaise Edouard H. , Goodstein Taylor , Schmeusser Benjamin N. , Patil Dattatraya , Imtiaz Nahar , Shapiro Daniel D. , Abel Edwin J. , Joshi Shreyas , Narayan Vikram , Ogan Kenneth , Master Viraj A.
Published: October 2024

Background/Objectives: The presence of paraneoplastic syndromes (PNS) in patients with renal cell carcinoma (RCC) is associated with worse survival; however, little is known about whether resolution of PNS after intervention has any prognostic value. We sought to determine if resolution of PNS by one year after cytoreductive nephrectomy was significantly associated with improved overall survival (OS) and cancer-specific survival (CSS). Methods: We retrospectively reviewed a prospectively maintained nephrectomy database for patients with any histology metastatic RCC (mRCC) who underwent nephrectomy between 2000 and 2022. Patients with the necessary laboratory studies available within 90 days before and by one year after surgery were included for study. PNS resolution was defined as an abnormal value compared to established laboratory cutoffs by one year after surgery. Multiple PNS in one patient was allowed, and resolution of each PNS was measured separately. OS and CSS were assessed using Kaplan–Meier curves and Cox proportional hazards models. Results: A total of 253 patients met inclusion criteria. A total of 177 patients (70.0%) met criteria for at least one PNS resolution by one year. Five-year OS and CSS rates were 15.7% and 36.2% for no PNS resolved, 24.5% and 31.6% for 1 PNS resolved, and 43.0% and 58.2% for ≥2 PNS resolved, respectively (p < 0.001). On multivariable analysis, no PNS resolution was associated with worse OS (HR 2.75, p < 0.001) and CSS (HR 2.62, p < 0.001) compared to ≥2 PNS resolved. Conclusions: Resolution of preoperative PNS abnormalities by one year following surgery is associated with improved OS and CSS in patients with mRCC.
Genome-Wide CRISPR Screen Identifies Genes Involved in Metastasis of Pancreatic Ductal Adenocarcinoma
Authors: Oktriani Risky , Pirona Anna Chiara , Kalmár Lili , Rahadian Ariani S. , Miao Beiping , Bauer Andrea S. , Hoheisel Jörg D. , Boettcher Michael , Du Haoqi
Published: October 2024

Background/Objectives: Early and aggressive metastasis is a major feature of pancreatic ductal adenocarcinoma. Understanding the processes underlying metastasis is crucial for making a difference to disease outcome. Towards these ends, we looked in a comprehensive manner for genes that are metastasis-specific. Methods: A genome-wide CRISPR-Cas9 gene knockout screen with 259,900 single guide RNA constructs was performed on pancreatic cancer cell lines with very high or very low metastatic capacity, respectively. Functional aspects of some of the identified genes were analysed in vitro. The injection of tumour cells with or without a gene knockout into mice was used to confirm the effect on metastasis. Results: The knockout of 590 genes—and, with higher analysis stringency, 67 genes—affected the viability of metastatic cells substantially, while these genes were not vital to non-metastasizing cells. Further evaluations identified different molecular processes related to this observation. One of the genes was MYBL2, encoding for a well-known transcription factor involved in the regulation of cell survival, proliferation, and differentiation in cancer tissues. In our metastasis-focussed study, no novel functional activity was detected for MYBL2, however. Instead, a metastasis-specific transformation of its genetic interaction with FOXM1 was observed. The interaction was synergistic in cells of low metastatic capacity, while there was a strong switch to a buffering mode in metastatic cells. In vivo analyses confirmed the strong effect of MYBL2 on metastasis. Conclusions: The genes found to be critical for the viability of metastatic cells form a basis for further investigations of the processes responsible for triggering and driving metastasis. As shown for MYBL2, unexpected processes of regulating metastasis might also be involved.
Deciphering the Tumor Microenvironment in Prostate Cancer: A Focus on the Stromal Component
Authors: Pakula Hubert , Pederzoli Filippo , Fanelli Giuseppe Nicolò , Nuzzo Pier Vitale , Rodrigues Silvia , Loda Massimo
Published: October 2024

Prostate cancer progression is significantly affected by its tumor microenvironment, in which mesenchymal cells play a crucial role. Stromal cells are modified by cancer mutations, response to androgens, and lineage plasticity, and in turn, engage with epithelial tumor cells via a complex array of signaling pathways and ligand–receptor interactions, ultimately affecting tumor growth, immune interaction, and response to therapy. The metabolic rewiring and interplay in the microenvironment play an additional role in affecting the growth and progression of prostate cancer. Finally, therapeutic strategies and novel clinical trials with agents that target the stromal microenvironment or disrupt the interaction between cellular compartments are described. This review underscores cancer-associated fibroblasts as essential contributors to prostate cancer biology, emphasizing their potential as prognostic indicators and therapeutic targets.
Breast Cancer and Mental Health: Incidence and Influencing Factors—A Claims Data Analysis from Germany
Authors: von Au Alexandra , Dannehl Dominik , Dijkstra Tjeerd Maarten Hein , Gutsfeld Raphael , Scholz Anna Sophie , Hassdenteufel Kathrin , Hahn Markus , Hawighorst-Knapstein Sabine , Isaksson Alexandra , Chaudhuri Ariane , Bauer Armin , Wallwiener Markus , Wallwiener Diethelm , Brucker Sara Yvonne , Hartkopf Andreas Daniel , Wallwiener Stephanie
Published: October 2024

Background/Objectives: With breast cancer (BC) survival improving due to optimized therapy, enhancing quality of life has become increasingly important. Both diagnosis and treatment, with their potential side effects, pose risks to mental well-being. Our study aimed to analyze the incidence and potential risk factors for mental disorders in BC patients. Methods: This retrospective analysis used claims data from AOK Baden-Wuerttemberg, including 11,553 BC patients diagnosed via ICD code C50 between 2010 and 2020 and 31,944 age-matched controls. Patients with mental disorders in the 12 months prior to diagnosis were excluded. Mental disorders were categorized into eight groups based on ICD codes: anxiety, obsessive compulsive disorder, adjustment disorder, dissociative disorder, hypochondriac disorder, affective disorder, mania, and other neuroses. Results: Mental disorders were significantly more common in BC patients than in controls (64.2% vs. 38.1%, p < 0.01, OR 2.91, 95%CI [2.79, 3.04]). In particular, hypochondriac, anxiety, affective, and adjustment disorders occurred significantly more often in BC patients. No differences were found for mania, bipolar disease, other neuroses, obsessive compulsive-, or dissociative disorders. Furthermore, endocrine therapy was associated with psychological comorbidities (OR 1.69, p < 0.001, 95%CI [1.53, 1.86]), while primarily metastasized patients (stage C) had a lower risk than adjuvant patients in stage A (OR 0.55, p < 0.0001, 95%CI [0.49, 0.61]). Regarding surgical treatment, mastectomy patients showed lower rates of mental illnesses (61.2%) than those with breast-conserving treatment (71.6%), or especially breast reconstruction (78.4%, p < 0.01). Breast reconstruction was also associated with more hypochondriac (p < 0.01) and adjustment disorders (p < 0.01). Conclusions: So, BC patients experience significantly more mental disorders than controls, particularly when treated with endocrine therapy and breast reconstructive surgery.
AI-Guided Cancer Therapy for Patients with Coexisting Migraines
Authors: Olawade David B. , Teke Jennifer , Adeleye Khadijat K. , Egbon Eghosasere , Weerasinghe Kusal , Ovsepian Saak V. , Boussios Stergios
Published: October 2024

Background: Cancer remains a leading cause of death worldwide. Progress in its effective treatment has been hampered by challenges in personalized therapy, particularly in patients with comorbid conditions. The integration of artificial intelligence (AI) into patient profiling offers a promising approach to enhancing individualized anticancer therapy. Objective: This narrative review explores the role of AI in refining anticancer therapy through personalized profiling, with a specific focus on cancer patients with comorbid migraine. Methods: A comprehensive literature search was conducted across multiple databases, including PubMed, Scopus, and Google Scholar. Studies were selected based on their relevance to AI applications in oncology and migraine management, with a focus on personalized medicine and predictive modeling. Key themes were synthesized to provide an overview of recent developments, challenges, and emerging directions. Results: AI technologies, such as machine learning (ML), deep learning (DL), and natural language processing (NLP), have become instrumental in the discovery of genetic and molecular biomarkers of cancer and migraine. These technologies also enable predictive analytics for assessing the impact of migraine on cancer therapy in comorbid cases, predicting outcomes and provide clinical decision support systems (CDSS) for real-time treatment adjustments. Conclusions: AI holds significant potential to improve the precision and effectiveness of the management and therapy of cancer patients with comorbid migraine. Nevertheless, challenges remain over data integration, clinical validation, and ethical consideration, which must be addressed to appreciate the full potential for the approach outlined herein.
Mechanism of Marinobufagenin-Induced Hyperpermeability of Human Brain Microvascular Endothelial Cell Monolayer: A Potential Pathogenesis of Seizure in Preeclampsia
Authors: Pantho Ahmed F. , Singh Manisha , Afroze Syeda H. , Kelso Kelsey R. , Ehrig Jessica C. , Vora Niraj , Kuehl Thomas J. , Lindheim Steven R. , Uddin Mohammad N.
Published: October 2024

Preeclampsia (preE) is a hypertensive disorder in pregnancies. It is the third leading cause of mortality among pregnant women and fetuses worldwide, and there is much we have yet to learn about its pathophysiology. One complication includes cerebral edema, which causes a breach of the blood–brain barrier (BBB). Urinary marinobufagenin (MBG) is elevated in a preE rat model prior to developing hypertension and proteinuria. We investigated what effect MBG has on the endothelial cell permeability of the BBB. Human brain microvascular endothelial cells (HBMECs) were utilized to examine the permeability caused by MBG. The phosphorylation of ERK1/2, Jnk, p38, and Src was evaluated after the treatment with MBG. Apoptosis was evaluated by examining caspase 3/7. MBG ≥ 1 nM inhibited the proliferation of HBMECs by 46–50%. MBG induced monolayer permeability, causing a decrease in the phosphorylation of ERK1/2 and the activated phosphorylation of Jnk, p38, and Src. MBG increased the caspase 3/7 expression, indicating the activation of apoptosis. Apoptotic signaling or the disruption of endothelia tight junction proteins was not observed when using the p38 inhibitor as a pretreatment in MBG-treated cells. The MBG-induced enhancement of the HBMEC monolayer permeability occurs by the downregulation of ERK1/2, the activation of Jnk, p38, Src, and apoptosis, resulting in the cleavage of tight junction proteins, and are attenuated by p38 inhibition.
Old Passengers as New Drivers: Chromosomal Passenger Proteins Engage in Translesion Synthesis
Authors: Falke Katharina , Schröder Elisabeth , Mosel Stefanie , Yürük Cansu N. , Feldmann Sophie , Gül Désirée , Stahl Paul , Stauber Roland H. , Knauer Shirley K.
Published: October 2024

Survivin is known for its dual biological role in apoptosis inhibition and mitotic progression. In addition to its being part of the chromosomal passenger complex (CPC), recent findings suggest additional roles for Survivin in the DNA damage response, further contributing to therapy resistance. In this study, we investigated the role of Survivin and the CPC proteins in the cellular response to irradiation with a focus on DNA replication processes. As is known, ionizing radiation leads to an increased expression of Survivin and its accumulation in nuclear foci, which we now know to be specifically localized to centromeric heterochromatin. The depletion of Survivin and Aurora B increases the DNA damage marker γH2AX, indicative of an impaired repair capacity. The presence of Survivin and the CPC in nuclear foci that we already identified during the S phase co-localize with the proliferating cell nuclear antigen (PCNA), further implying a potential role during replication. Indeed, Survivin knockdown reduced replication fork speed as assessed via DNA fiber assays. Mechanistically, we identified a PIP-box motif in INCENP mediating the interaction with PCNA to assist in managing damage-induced replication stress. Survivin depletion forces cells to undergo unphysiological genome replication via mitotic DNA synthesis (MiDAS), resulting in chromosome breaks. Finally, we revealed that Aurora B kinase liberates Pol η by phosphorylating polymerase delta-interacting protein 2 (POLDIP2) to resume the replication of damaged sites via translesion synthesis. In this study, we assigned a direct function to the CPC in the transition from stalled replication forks to translesion synthesis, further emphasizing the ubiquitous overexpression of Survivin particularly in tumors. This study, for the first time, assigns a direct function to the chromosomal passenger complex, CPC, including Survivin, Aurora B kinase, Borealin, and INCENP, in the transition from stalled replication forks (involving PCNA binding) to translesion synthesis (liberating Pol η by phosphorylating POLDIP2), and thus in maintaining genomic integrity.
Correlation Between Physical Activity and Learning Concentration, Self-Management, and Interpersonal Skills Among Korean Adolescents
Authors: Kwon Jeonga , Roh Su-Yeon , Kwon Daekeun
Published: October 2024

This study aimed to investigate the association between physical activity participation and key developmental competencies—learning concentration, self-management, and interpersonal skills—among Korean adolescents. Data were drawn from the 2021 Study on the State of Play Culture of Children and Adolescents and Measures to Support Growth, conducted by the Korea Adolescent Policy Institute. The study participants included elementary, middle, and high school students in Korea, consisting of 1507 males (53.3%) and 1322 females (46.7%), totaling 2829. We analyzed the data using frequency distribution, chi-square test, and multivariate logistic regression. The results revealed a significant sex difference in the duration of physical activity, with boys spending more time engaging in physical activity than girls. In addition, time spent on physical activities decreased as the school grade level increased. Notably, the more time Korean adolescents spent engaging in daily physical activity, the higher they rated their learning concentration, self-management, and interpersonal skills. These findings suggest the need to promote greater physical activity among adolescents—particularly among girls—which can help improve learning concentration, self-management, and interpersonal skills.
Preparation of Chromium Carbide-Strengthened Ni-W Coatings by Electrodeposition and the Corresponding Anticorrosion Behavior in CO2-Saturated NaCl Solution
Authors: Li Hongjie , Zhang Weizhi , Yuan Xi , Li Puzhi , Han Weilei , Huang Hongbing
Published: October 2024

In this study, we have prepared Ni-W/Cr3C2 composite electrodeposits through the diffuse reinforcement mechanism of chromium carbide nanoparticles. These electrodeposits exhibit excellent corrosion resistance and are designed to effectively protect the structural materials of pipe columns under the harsh CO2 corrosion environments faced by carbon sequestration and utilization technologies. A systematic investigation was conducted into the micro-morphology, profile undulation, phase composition, and surface chemical state of the electrodeposits. Furthermore, the corrosion-resistant behavior of Ni-W/Cr3C2 composite electrodeposits was investigated in simulated corrosive environments (i.e., brine solution containing 3.5 wt% NaCl and CO2-saturated brine). We then evaluated their corrosion response under the aforementioned conditions using electrochemical methods. In addition, the EIS of electrodeposited coatings revealed that the dense oxide film layer formed on the surface of the deposits, which acted as a primary barrier against corrosion, playing a pivotal role in maintaining the overall corrosion resistance of the material.
The Anti-Flyaway/Frizz Effect by Inducing the α-Helical Structure Transition of Hair
Authors: Song Sang-Hun , Lim Byung Tack , Son Seong Kil
Published: October 2024

In order to reduce chronic hair flyaways/frizz, both reducing and oxidizing agents have to be used, leaving aside the hair damage issues. This study presents changes in hair morphology caused by treatment with a shampoo containing only reducing agents, excluding oxidizing agents that affect critical hair damages. As a result of flyaway/frizz improvement rates calculated through monitoring of the area of light transmittance in the hair tresses, reducing agents, such as ammonium thioglycolate (ATG), L-cysteine, and sodium sulfite were found to be effective in decreasing hair flyaway/frizz. Additionally, the methods to maintain homeostasis and control damage caused by oxidation during washing were also used to see flyaway/frizz improvement rates. Measurements using electrostatic force microscopy (EFM) showed that the surface charge of hair tresses treated with shampoo containing reducing agents was lowered. Using Raman spectroscopic analysis, it has been suggested that these treatments with reducing agents induced a 3D structural transition of the hair from an α-helix to a random coil. In addition, this structural release was confirmed, identifying the reduction in the enthalpy of the α-helix using differential scanning calorimetry (DSC). Furthermore, we verified that this change causes no hair damage through a tensile strength test. Therefore, the formulation of shampoo with reducing agents can be used as an effective strategy to care for hair flyaway/frizz without hair damage issues.
Discovery and Analysis of Key Core Technology Topics in Proton Exchange Membrane Fuel Cells Through the BERTopic Model
Authors: Gou Yurong , Chen Qimei
Published: October 2024

As a core component of clean energy technology, proton exchange membrane fuel cells (PEMFC) play a crucial role in promoting the evolution of energy structures and realizing sustainable development, representing an environmentally friendly energy conversion strategy. This paper identifies the key core technology themes in the field of the proton exchange membrane fuel cells by constructing patent and paper datasets in the field, applying the BERTopic model for theme identification, and calculating the key core technology scores of each theme using the importance, innovativeness, and high competitiveness barriers to identify the key core technology themes in the field, so as to provide guidance and references for the relevant research and practice. The results of the study show that patent documents and academic papers show obvious differentiation in technical themes: the key core technologies identified in patent texts include ‘battery separator materials’, ‘rubber sealing materials’, and ‘porous carbon fibre materials’. The key core technologies identified in the academic paper of the thesis include ‘palladium-based electrocatalys’, ‘graphene oxide composite film’, and ‘platinum-graphene oxide catalyst’.
Economical, Innovative, or Ecological? What Are the Green Energy Users?
Authors: Lubiński Kamil , Grębosz-Krawczyk Magdalena
Published: October 2024

Green energy sources play a vital role in mitigating environmental impacts and reducing dependence on energy imports. Growing concerns over climate change, coupled with public policies promoting the expansion of green energy, have notably shaped consumer attitudes and behaviours. This study aims to address the knowledge gap by examining the impact of a sustainable lifestyle, consumer innovativeness, and economic attitudes on the intention to adopt green energy sources. The research was conducted on 580 Polish consumers using an online survey. The results of structural equation modelling revealed that pro-environmental self-identity (PESI) and consumer innovativeness (CI) have a positive impact on consumer behaviour toward green energy sources. Pro-environmental self-identity (PESI) is the strongest determinant of consumer behaviour toward green energy sources. Our research on Polish consumer behaviour could serve as a frame of reference for other countries, particularly in Central and Eastern Europe. From a theoretical standpoint, this research enhances the understanding of pro-environmental self-identity (PESI) and its link to consumer innovativeness while also offering insights into consumer behaviour related to green energy sources, based on the experiences from the Polish market. The conclusions derived from this study may provide valuable guidance for managers and policymakers in formulating strategies to promote the adoption of green energy sources across Europe effectively.
Reinforcement Learning-Enhanced Adaptive Scheduling of Battery Energy Storage Systems in Energy Markets
Authors: Liu Yang , Lu Qiuyu , Yu Zhenfan , Chen Yue , Yang Yinguo
Published: October 2024

Battery Energy Storage Systems (BESSs) play a vital role in modern power grids by optimally dispatching energy according to the price signal. This paper proposes a reinforcement learning-based model that optimizes BESS scheduling with the proposed Q-learning algorithm combined with an epsilon-greedy strategy. The proposed epsilon-greedy strategy-based Q-learning algorithm can efficiently manage energy dispatching under uncertain price signals and multi-day operations without retraining. Simulations are conducted under different scenarios, considering electricity price fluctuations and battery aging conditions. Results show that the proposed algorithm demonstrates enhanced economic returns and adaptability compared to traditional methods, providing a practical solution for intelligent BESS scheduling that supports grid stability and the efficient use of renewable energy.
Reinforcement Learning for EV Fleet Smart Charging with On-Site Renewable Energy Sources
Authors: Li Handong , Dai Xuewu , Goldrick Stephen , Kotter Richard , Aslam Nauman , Ali Saleh
Published: October 2024

In 2020, the transportation sector was the second largest source of carbon emissions in the UK and in Newcastle upon Tyne, responsible for about 33% of total emissions. To support the UK’s target of reaching net zero emissions by 2050, electric vehicles (EVs) are pivotal in advancing carbon-neutral road transportation. Optimal EV charging requires a better understanding of the unpredictable output from on-site renewable energy sources (ORES). This paper proposes an integrated EV fleet charging schedule with a proximal policy optimization method based on a framework for deep reinforcement learning. For the design of the reinforcement learning environment, mathematical models of wind and solar power generation are created. In addition, the multivariate Gaussian distributions derived from historical weather and EV fleet charging data are utilized to simulate weather and charging demand uncertainty in order to create large datasets for training the model. The optimization problem is expressed as a Markov decision process (MDP) with operational constraints. For training artificial neural networks (ANNs) through successive transition simulations, a proximal policy optimization (PPO) approach is devised. The optimization approach is deployed and evaluated on a real-world scenario comprised of council EV fleet charging data from Leicester, UK. The results show that due to the design of the rewards function and system limitations, the charging action is biased towards the time of day when renewable energy output is maximum (midday). The charging decision by reinforcement learning improves the utilization of renewable energy by 2–4% compared to the random charging policy and the priority charging policy. This study contributes to the reduction in battery charging and discharging, electricity sold to the grid to create benefits and the reduction in carbon emissions.
Towards Sustainable Decarbonization: Addressing Challenges in Electric Vehicle Adoption and Infrastructure Development
Authors: Adamashvili Nino , Thrassou Alkis
Published: October 2024

The transition to electric vehicles (EVs) plays a pivotal role in achieving decarbonization within the transportation sector. However, the widespread adoption of EVs faces multifaceted challenges, particularly concerning infrastructure development. This paper investigates the intersection of sustainability, decarbonization, and EV adoption, with a focus on identifying and analyzing the challenges associated with infrastructure deployment. Strictly adhering to the methodological principles and process of systematic literature reviews, this paper analyzes research spanning the fields of engineering, energy, computer science, environmental science, social sciences, and others to elucidate the barriers hindering EV adoption, ranging from technological limitations to regulatory complexities and market dynamics. Furthermore, it examines the critical role of infrastructure, encompassing charging networks, grid integration, and supportive policies, in facilitating EV uptake and maximizing environmental benefits. The findings are finally used to present the implications for theory, practice, and policies and to highlight the avenues for future research.
Micro Gas Turbines in the Global Energy Landscape: Bridging the Techno-Economic Gap with Comparative and Adaptive Insights from Internal Combustion Engines and Renewable Energy Sources
Authors: Weerakoon A. H. Samitha , Assadi Mohsen
Published: October 2024

This paper investigates the potential of Micro Gas Turbines (MGTs) in the global shift towards low-carbon energy systems, particularly focusing on their integration within microgrids and distributed energy generation systems. MGTs, recognized for their fuel flexibility and efficiency, have yet to achieve the commercialization success of rival technologies such as Internal Combustion Engines (ICEs), wind turbines, and solar power (PV) installations. Through a comprehensive review of recent techno-economic assessment (TEA) studies, we highlight the challenges and opportunities for MGTs, emphasizing the critical role of TEA in driving market penetration and technological advancement. Comparative analysis with ICE and RES technologies reveals significant gaps in TEA activities for MGTs, which have hindered their broader adoption. This paper also explores the learning and experience effects associated with TEA, demonstrating how increased research activities have propelled the success of ICE and RES technologies. The analysis reveals a broad range of learning and experience effects, with learning rates (α) varying from 0.1 to 0.25 and experience rates (β) from 0.05 to 0.15, highlighting the significant role these effects play in reducing the levelized cost of energy (LCOE) and improving the net present value (NPV) of MGT systems. Hybrid systems integrating MGTs with renewable energy sources (RESs) and ICE technologies demonstrate the most substantial cost reductions and efficiency improvements, with systems like the hybrid renewable energy CCHP with ICE achieving a learning rate of α = 0.25 and significant LCOE reductions from USD 0.02/kWh to USD 0.017/kWh. These findings emphasize the need for targeted TEA studies and strategic investments to unlock the full potential of MGTs in a decarbonized energy landscape. By leveraging learning and experience effects, stakeholders can predict cost trajectories more accurately and make informed investment decisions, positioning MGTs as a competitive and sustainable energy solution in the global energy transition.