bluuebunny/crossref_metadata_2025 huggingface dataset:
A Classification Method of Earthquake Ground Motion Records Based on the Results of K-Means Clustering Analysis
Authors: Ding Yanqiong , Nie Minggang , Xu Yazhou , Miao Huiquan
Published: June 2024

This paper presents a classification method for earthquake ground motion records utilizing the results of K-means cluster analysis. The moment magnitude and Joyner–Boore distance are utilized as the primary parameters for clustering the earthquake ground motion records. The classification boundaries are established through an examination of moment magnitude ranges, Joyner–Boore distance ranges, and spectral characteristics within each cluster. In this study, a comprehensive dataset comprising 7627 horizontal earthquake acceleration records was meticulously curated for analysis. The data were subjected to separate clustering and grouping procedures, allowing for insightful comparisons between the resultant clusters. Significant disparities in spectral characteristics across the classification groups were demonstrated. These differences become particularly pronounced when a moment magnitude threshold of 6 and a Joyner–Boore distance threshold of 140 km are employed to categorize the ground motion records. The approach underscores the substantial impact of classification based on earthquake ground motion spectral characteristics, while also mitigating the potential instabilities inherent in cluster analysis results. A refined and quantitatively robust framework for understanding and categorizing earthquake ground motions is provided, offering valuable insights for seismic data analysis and contributing to more accurate and reliable assessments of seismic activity.
A Comparison Analysis of Buildings as per Norwegian and Ethiopia ES-EN1998-1 Seismic Code
Authors: Abate Mistreselasie , Evangelista Ana Catarina Jorge , Tam Vivian W. Y.
Published: June 2024

An earthquake is one of the most significant and shocking natural disasters ever documented anywhere on the planet. Throughout history, it has claimed millions of lives and wreaked devastation on infrastructure. Because earthquake forces are spontaneous and unpredictable, engineering methods must be honed to investigate buildings under the impact of these forces. The dynamic and static computations of four RC multistory structure prototypes with various elevations in a high seismic zone are compared in this paper. The project under review is modeled as a 3, 6, 12, and 18-story establishment, and it is analyzed employing ETABS vs. 2019. The Equivalent Lateral Force (ELF) Procedure is used for static experimentation, while the Response Spectrum (RS) Procedure is employed for dynamic investigation. Both calculations are performed as per the EUROCODE 8-2004 recommendation. The ELF seismic load practice utilized was for the country of Norway, which has similar parameters to the ES-EN 8-15 seismic regulation Type I target RS, with ag/g = 0.1, spectrum type = I, soil factor S = 1.3 ground type, spectrum period (Tb, Tc, and Td) 0.1 s, 0.25 s, and 1.5 s. For the RS investigation, the parameters employed are as per ESEN-2015, ag/g = 0.1, and the spectrum type = I and ground type = B parameters were involved in the same manner for the RS analysis. The soil factor was set to 1.35; the spectrum period was set to (Tb, Tc, and Td) 0.05 s, 0.25 s, and 1.2 s. The behavior factor = 3.8, the lower bound factor = 0.2, and the damping ratio = 0.05. The results are then compared by employing different components such as displacement, story drift, story stiffness, base story shear, and story moment. Ultimately, a comparison of static and dynamic investigations has been carried out. Compared to the RS approach, the ELF technique produces more additional displacement, total drift, and base shear. As per the findings of this paper, for high-rise and tall buildings, dynamic analysis such as RS should be used rather than static analysis (ELF).
A Stakeholder Needs Analysis in Cybersecurity: A Systemic Approach to Enhancing Digital Infrastructure Resilience
Authors: Katrakazas Panagiotis , Papastergiou Spyros
Published: June 2024

The escalating complexity and sophistication of cyber threats necessitate advanced solutions that not only counteract these threats but also proactively adapt to the evolving needs of diverse stakeholders involved in digital infrastructures, such as telecom operators, cloud service providers, and end-users in sectors like healthcare and finance. This research addresses a crucial gap by focusing on a systemic, AI-powered approach to stakeholder needs analysis in cybersecurity. By aligning closely with stakeholder requirements, the proposed framework aims to offer dynamic, responsive cybersecurity solutions that enhance the resilience of digital infrastructures against evolving cyber threats. This research systematically maps the landscape of stakeholder needs in cybersecurity across different sectors through qualitative methods like interviews and focus groups, supplemented by data from the CyberSecDome project’s pilot cases and open calls. Requirements for an AI-driven framework are then formulated based on these data to identify patterns and predict stakeholder needs. The analysis reveals critical challenges faced by stakeholders, including limited threat intelligence sharing, insufficient automation in incident response, and regulatory hurdles related to data protection laws and evolving cybersecurity legislation. There is a strong interest in leveraging AI for enhanced intrusion detection, real-time threat intelligence sharing, and privacy-preserving information exchange.
P18: Novel Anticancer Peptide from Induced Tumor-Suppressing Cells Targeting Breast Cancer and Bone Metastasis
Authors: Cui Changpeng , Huo Qingji , Xiong Xue , Na Sungsoo , Mitsuda Masaru , Minami Kazumasa , Li Baiyan , Yokota Hiroki
Published: June 2024

Background: The skeletal system is a common site for metastasis from breast cancer. In our prior work, we developed induced tumor-suppressing cells (iTSCs) capable of secreting a set of tumor-suppressing proteins. In this study, we examined the possibility of identifying anticancer peptides (ACPs) from trypsin-digested protein fragments derived from iTSC proteomes. Methods: The efficacy of ACPs was examined using an MTT-based cell viability assay, a Scratch-based motility assay, an EdU-based proliferation assay, and a transwell invasion assay. To evaluate the mechanism of inhibitory action, a fluorescence resonance energy transfer (FRET)-based GTPase activity assay and a molecular docking analysis were conducted. The efficacy of ACPs was also tested using an ex vivo cancer tissue assay and a bone microenvironment assay. Results: Among the 12 ACP candidates, P18 (TDYMVGSYGPR) demonstrated the most effective anticancer activity. P18 was derived from Arhgdia, a Rho GDP dissociation inhibitor alpha, and exhibited inhibitory effects on the viability, migration, and invasion of breast cancer cells. It also hindered the GTPase activity of RhoA and Cdc42 and downregulated the expression of oncoproteins such as Snail and Src. The inhibitory impact of P18 was additive when it was combined with chemotherapeutic drugs such as Cisplatin and Taxol in both breast cancer cells and patient-derived tissues. P18 had no inhibitory effect on mesenchymal stem cells but suppressed the maturation of RANKL-stimulated osteoclasts and mitigated the bone loss associated with breast cancer. Furthermore, the P18 analog modified by N-terminal acetylation and C-terminal amidation (Ac-P18-NH2) exhibited stronger tumor-suppressor effects. Conclusions: This study introduced a unique methodology for selecting an effective ACP from the iTSC secretome. P18 holds promise for the treatment of breast cancer and the prevention of bone destruction by regulating GTPase signaling.
Molecular and Histopathological Characterization of Metastatic Cutaneous Squamous Cell Carcinomas: A Case–Control Study
Authors: Paganelli Alessia , Zaffonato Marco , Donati Benedetta , Torricelli Federica , Manicardi Veronica , Lai Michela , Spadafora Marco , Piana Simonetta , Ciarrocchi Alessia , Longo Caterina
Published: June 2024

Background: A subset of patients affected by cutaneous squamous cell carcinoma (cSCC) can exhibit locally invasive or metastatic tumors. Different staging classification systems are currently in use for cSCC. However, precise patient risk stratification has yet to be reached in clinical practice. The study aims to identify specific histological and molecular parameters characterizing metastatic cSCC. Methods: Patients affected by metastatic and non-metastatic cSCC (controls) were included in the present study and matched for clinical and histological characteristics. Skin samples from primary tumors were revised for several histological parameters and also underwent gene expression profiling with a commercially available panel testing 770 different genes. Results: In total, 48 subjects were enrolled in the study (24 cases, 24 controls); 67 genes were found to be differentially expressed between metastatic and non-metastatic cSCC. Most such genes were involved in immune regulation, skin integrity, angiogenesis, cell migration and proliferation. Conclusion: The combination of histological and molecular profiles of cSCCs allows the identification of features specific to metastatic cSCC, with potential implications for more precise patient risk stratification.
Gut Microbiota—Adversary or Ally? Its Role and Significance in Colorectal Cancer Pathogenesis, Progression, and Treatment
Authors: Chawrylak Katarzyna , Leśniewska Magdalena , Mielniczek Katarzyna , Sędłak Katarzyna , Pelc Zuzanna , Pawlik Timothy M. , Polkowski Wojciech P. , Rawicz-Pruszyński Karol
Published: June 2024

In 2022, colorectal cancer (CRC) was the third most prevalent malignancy worldwide. The therapeutic approach for CRC typically involves a multimodal regimen. The human gut microbiota comprises over 35,000 bacterial species. The composition of the gut microbiota is influenced by dietary intake, which plays a crucial role in food absorption, nutrient extraction, and the development of low-grade inflammation. Dysbiosis in the gut microbiota is a key driver of inflammation and is strongly associated with CRC development. While the gut microbiome influences CRC initiation and progression, emerging evidence suggests a role for the gut microbiome in modulating the efficacy and toxicity of cancer treatments. Therapeutic strategies targeting the gut microbiome, such as probiotics, hold promise as effective interventions in the modern therapeutical approach to CRC. For example, Microbiota Implementation to Reduce Anastomotic Colorectal Leaks (MIRACLe) implementation has resulted in improvements in clinical outcomes, including reduced incidence of anastomotic leakage (AL), surgical site infections (SSIs), reoperation, as well as shorter recovery times and hospital stays compared with the control group. Therefore, this review aims to describe the current state of knowledge regarding the involvement of the gut microbiota in CRC pathogenesis and its potential therapeutic implications to treat CRC.
Arterial Thrombosis in Patients with Cancer
Authors: Xu Yan , Carrier Marc , Kimpton Miriam
Published: June 2024

Patients with cancer are at increased risk of arterial thromboembolic disease due to the presence of risk factors common to both the development of cancer and arterial thrombosis, the cancer itself, and the treatments provided to treat cancer. We review here the epidemiology and pathophysiology of arterial thromboembolic disease in cancer, along with its prevention and treatment strategies. We also propose a generalized approach for the management of arterial thromboembolic disease in this patient population.
Pancreatic Ductal Adenocarcinoma (PDAC): A Review of Recent Advancements Enabled by Artificial Intelligence
Authors: Mukund Ashwin , Afridi Muhammad Ali , Karolak Aleksandra , Park Margaret A. , Permuth Jennifer B. , Rasool Ghulam
Published: June 2024

Pancreatic Ductal Adenocarcinoma (PDAC) remains one of the most formidable challenges in oncology, characterized by its late detection and poor prognosis. Artificial intelligence (AI) and machine learning (ML) are emerging as pivotal tools in revolutionizing PDAC care across various dimensions. Consequently, many studies have focused on using AI to improve the standard of PDAC care. This review article attempts to consolidate the literature from the past five years to identify high-impact, novel, and meaningful studies focusing on their transformative potential in PDAC management. Our analysis spans a broad spectrum of applications, including but not limited to patient risk stratification, early detection, and prediction of treatment outcomes, thereby highlighting AI’s potential role in enhancing the quality and precision of PDAC care. By categorizing the literature into discrete sections reflective of a patient’s journey from screening and diagnosis through treatment and survivorship, this review offers a comprehensive examination of AI-driven methodologies in addressing the multifaceted challenges of PDAC. Each study is summarized by explaining the dataset, ML model, evaluation metrics, and impact the study has on improving PDAC-related outcomes. We also discuss prevailing obstacles and limitations inherent in the application of AI within the PDAC context, offering insightful perspectives on potential future directions and innovations.
Novel Targets and Advanced Therapies in Diffuse Large B Cell Lymphomas
Authors: D’Alò Francesco , Bellesi Silvia , Maiolo Elena , Alma Eleonora , Bellisario Flaminia , Malafronte Rosalia , Viscovo Marcello , Campana Fabrizia , Hohaus Stefan
Published: June 2024

Since the introduction of rituximab in the late 1990s, significant progress has been made in advancing targeted therapies for B cell lymphomas, improving patients’ chance of being cured and clinicians’ therapeutic armamentarium. A better understanding of disease biology and pathogenic pathways, coupled with refinements in immunophenotypic and molecular diagnostics, have been instrumental in these achievements. While traditional chemotherapy remains fundamental in most cases, concerns surrounding chemorefractoriness and cumulative toxicities, particularly the depletion of the hemopoietic reserve, underscore the imperative for personalized treatment approaches. Integrating targeted agents, notably monoclonal antibodies, alongside chemotherapy has yielded heightened response rates and prolonged survival. A notable paradigm shift is underway with innovative-targeted therapies replacing cytotoxic drugs, challenging conventional salvage strategies like stem cell transplantation. This review examines the landscape of emerging targets for lymphoma cells and explores innovative therapies for diffuse large B cell lymphoma (DLBCL). From Chimeric Antigen Receptor-T cells to more potent monoclonal antibodies, antibody–drug conjugates, bispecific antibodies, checkpoint inhibitors, and small molecules targeting intracellular pathways, each modality offers promising avenues for therapeutic advancement. This review aims to furnish insights into their potential implications for the future of DLBCL treatment strategies.
The Impact of Urine-Sample HPV Testing on the Effectiveness of Screening for Cervical Cancer: An Umbrella Review
Authors: Miazga Wojciech , Tatara Tomasz , Wnuk Katarzyna , Gujski Mariusz , Pinkas Jarosław , Religioni Urszula
Published: June 2024

Background: The aim of the study was to evaluate the impact of urine-sample HPV (human papillomavirus) testing on the effectiveness of screening for cervical cancer. Methods: The analysis was based on the results of a systematic review. Secondary studies were searched in the following medical databases: Medline, Embase, and the Cochrane Library. The results of the statistical tests presented in the article originate from research conducted by the authors of the included articles. Results: From a total of 1869 citations, 5 studies were included in this review. Sensitivity and specificity for the detection of any HPV from first-void urine samples were 87% [95% CI: (0.74; 0.94)] and 89% [95% CI: (0.81; 0.93)], respectively. Moreover, participants in the analyzed studies had indicated that they felt comfortable with urine testing. Conclusions: The development of methods to detect HPV infection in first-void urine samples and the application of this sampling method in widely available screening tests could significantly increase patients’ willingness to participate in testing.
Pt/CB-Catalyzed Chemoselective Hydrogenation Using In Situ-Generated Hydrogen by Microwave-Mediated Dehydrogenation of Methylcyclohexane under Continuous-Flow Conditions
Authors: Sakurada Naoya , Kitazono Takanori , Ikawa Takashi , Yamada Tsuyoshi , Sajiki Hironao
Published: June 2024

Hydrogen gas (H2) has attracted attention as a next-generation clean energy source. Its efficient and safe preparation and utilization are crucial in both the industry and organic chemistry research. In this study, a Pt/CB (platinum on carbon bead)-catalyzed MW-mediated continuous-flow hydrogenation reaction was developed using methylcyclohexane (MCH) as the reducing agent (hydrogen carrier). Alkynes, alkenes, nitro groups, benzyl esters, and aromatic chlorides were chemoselectively hydrogenated using Pt/CB under MW-assisted continuous-flow conditions. This methodology represents a safe and energy-efficient hydrogenation process, as it eliminates the need for an external hydrogen gas supply or heating jackets as a heating medium. The further application of MW-mediated continuous-flow hydrogenation reactions is a viable option for the efficient generation and utilization of sustainable energy.
Design and Optimization of Critical-Raw-Material-Free Electrodes towards the Performance Enhancement of Microbial Fuel Cells
Authors: Nisa Khair Un , da Silva Freitas Williane , D’Epifanio Alessandra , Mecheri Barbara
Published: June 2024

Microbial fuel cells (MFCs) are sustainable energy recovery systems because they use organic waste as biofuel. Using critical raw materials (CRMs), like platinum-group metals, at the cathode side threatens MFC technology’s sustainability and raises costs. By developing an efficient electrode design for MFC performance enhancement, CRM-based cathodic catalysts should be replaced with CRM-free materials. This work proposes developing and optimizing iron-based air cathodes for enhancing oxygen reduction in MFCs. By subjecting iron phthalocyanine and carbon black pearls to controlled thermal treatments, we obtained Fe-based electrocatalysts combining high surface area (628 m2 g−1) and catalytic activity for O2 reduction at near-neutral pH. The electrocatalysts were integrated on carbon cloth and carbon paper to obtain gas diffusion electrodes whose architecture was optimized to maximize MFC performance. Excellent cell performance was achieved with the carbon-paper-based cathode modified with the Fe-based electrocatalysts (maximum power density-PDmax = 1028 mWm−2) compared to a traditional electrode design based on carbon cloth (619 mWm−2), indicating the optimized cathodes as promising electrodes for energy recovery in an MFC application.
Synthesis and Characterization of New Bases Derived from Nitrophenylpyrazoles, Coordination to Palladium and Antifungal Activity and Catalytic Activity in Mizoroki–Heck Reactions
Authors: Londoño-Salazar Jennifer , Restrepo-Acevedo Andrés , Torres John Eduard , Abonia Rodrigo , Svetaz Laura , Zacchino Susana A. , Le Lagadec Ronan , Cuenú-Cabezas Fernando
Published: June 2024

In this study, we report the synthesis of eight Schiff bases (3–10) type N-heterocycle (N-het) using conventional refluxing conditions as well as different eco-friendly techniques such as grinding, thermal fusion, microwave irradiation (MWI) and ultrasound, all of them in the presence of a catalytic amount of acetic acid. These procedures had the additional advantage of being environmentally friendly and high-yield, making these protocols an alternative for Schiff-base syntheses. The obtained Schiff bases were coordinated to palladium, generating new complexes of type [Pd2Cl4(N-het)2]. Complexes [Pd2Cl4(5)2] and [Pd2Cl4(9)2] showed high activity and selectivity for a model Mizoroki–Heck C-C coupling reaction of styrene with iodobenzene and bromobenzaldehydes. All compounds and complexes were evaluated for antifungal activity against clinically important fungi such as Candida albicans and Cryptococcus neoformans. Although the Schiff bases (3–10) showed low antifungal activity against both fungi, some of their palladium complexes such as [Pd2Cl4(3)2], [Pd2Cl4(5)2], [Pd2Cl4(8)2] and [Pd2Cl4(10)2] showed comparatively higher antifungal effects mainly against C. neoformans. The product of the Mizoroki–Heck-type C-C coupling reactions, 4-styrylbenzaldehyde, was isolated and purified to be later used in the synthesis of four new nitrophenylpyrazole derivatives of styrylimine, which also displayed antifungal activity, especially against C. neoformans.
Recent Advances in Layered MX2-Based Materials (M = Mo, W and X = S, Se, Te) for Emerging Optoelectronic and Photo(electro)catalytic Applications
Authors: Pinto Felipe M. , de Conti Mary C. M. D. , Pereira Wyllamanney S. , Sczancoski Júlio C. , Medina Marina , Corradini Patricia G. , de Brito Juliana F. , Nogueira André E. , Góes Márcio S. , Ferreira Odair P. , Mascaro Lucia H. , Wypych Fernando , La Porta Felipe A.
Published: June 2024

Transition metal dichalcogenides (TMDCs), represented by MX2 (where M = Mo, W and X = S, Se, and Te), and more recently, their moiré superlattices (i.e., formed by superimposing layers of TMDCs with different rotation angles) have attracted considerable interest due to their excellent physical properties and unique nanoscale functionalities. Compared to graphene, the literature indicates that TMDCs offer a competitive advantage in optoelectronic technologies, primarily owing to their compositionally controlled non-zero bandgap. These two-dimensional (2D) nanostructured single or multiple layers exhibit remarkable properties that differ from their bulk counterparts. Moreover, stacking different TMDC monolayers also forms heterostructures and introduces unique quantum effects and extraordinary electronic properties, which is particularly promising for next-generation optoelectronic devices and photo(electro)catalytic applications. Therefore, in this review, we also highlight the new possibilities in the formation of 2D/2D heterostructures of MX2-based materials with moiré patterns and discuss the main critical challenges related to the synthesis and large-scale applications of layered MX2 and MX2-based composites to spur significant advances in emerging optoelectronic and photo(electro)catalytic applications.
On-Site Determination of Soil Organic Carbon Content: A Photocatalytic Approach
Authors: Abu El Haija Karam , Chiang Yi Wai , Santos Rafael M.
Published: June 2024

This investigation presents a new approach for evaluating soil organic carbon (SOC) content in farming soils using a photocatalytic chemical oxygen demand (PeCOD) analyzer combined with geographic information system (GIS) technology for spatial analysis. Soil samples were collected at various sites throughout Canada and were analyzed using sieve analysis, followed by further SOC evaluation using three distinct techniques: loss on ignition (LOI), Walkley-Black, and PeCOD. The PeCOD system, which relies on the photochemical oxidation of organic carbon, showed an exciting correlation between its evaluations and SOC content, making it a prompt and reliable method to evaluate SOC. In this investigation, finer materials such as clayey soils (soil fractions of (<50 µm)) demonstrated high SOC content compared to coarser ones (soil fractions of (>75 µm)) and decreased SOC content with increased soil depth, generally below the 30 cm mark. It should be noted that this investigation revealed that other variables, such as land management practices, precipitation, and atmospheric temperature, have drastic effects on the formation and residence time of SOC. GIS georeferencing еnablеd mapping of the SOC distribution and identification of hotspot areas with high SOC content. The results of this study have implications for sustainable farming, climate change mitigation, and soil health operations by providing farmers with schemes that amplify carbon sequestration while simultaneously improving soil health.
Effect of Chain Orientation on Coupling of Optical and Mechanical Anisotropies of Polymer Films
Authors: Samadi-Dooki Aref , Lamontia Mark A. , Londoño Juan David , Williamson Curtis , Burch Heidi E. , Yahyazadehfar Mobin , Carbajal Leopoldo A. , Kourtakis Kostantinos
Published: June 2024

Polymer films have broad applications in different industries with specific requirements for their optical and mechanical properties. In mass production, processing conditions during film formation that apply forces and motions in various directions to the film tend to manifest preferred molecular chain orientation in the film microstructure, which unavoidably produces optical and mechanical anisotropies. In this paper, we investigate the effect of such macromolecular orientations on the optical and mechanical anisotropies of several polymer films, including polystyrene, poly(methyl methacrylate), poly(ethylene terephthalate), poly(ethylene naphthalate), poly(ether ether ketone), poly(ether sulfones), poly(ethylene chlorotrifluoroethylene), poly(phenylsulfone), and polycarbonate, at temperatures well below their respective glass transitions (Tg). The film mechanical responses, including elasticity, yielding, and post-yield behaviors, were obtained for the in- and out-of-plane directions utilizing tensile and nanoindentation testing methods, respectively. In addition, the net chain orientation within the films was evaluated by birefringence through analyzing the film optical refractive indices, which were verified and complemented by wide-angle X-ray scattering (WAXS) measurements. The results reveal a considerable quantitative correlation between the birefringence and the degree of elastic anisotropy and a qualitative correlation between the chain orientation and the film post-yield tensile instability (necking). These observations corroborate the interrelationship between the microstructure of polymer films and their optical and mechanical properties. In addition, they emphasize that process conditions can be selected to tune the optical and mechanical anisotropies to best serve the material performance in specific devices. We also propose an empirical equation to approximate the out-of-plane film stiffness based upon the optical and in-plane mechanical properties.
Influence of Current Duty Cycle and Voltage of Micro-Arc Oxidation on the Microstructure and Composition of Calcium Phosphate Coating
Authors: Mamaeva Axaule , Kenzhegulov Aidar , Panichkin Aleksander , Abdulvaliyev Rinat , Fischer Dametken , Bakhytuly Nauryzbek , Toiynbaeva Nazgul
Published: June 2024

The micro-arc oxidation (MAO) technique was employed to produce calcium phosphate coatings on titanium surfaces using an electrolyte composed of hydroxyapatite and calcium carbonate in an aqueous solution of orthophosphoric acid. The coatings’ morphology and composition were regulated by adjusting electrical parameters, specifically the duty cycle and voltage. This study examined the effects of the duty cycle and voltage during the MAO process on the microstructure and composition of calcium phosphate coatings on VT1–0 titanium substrates. Scanning electron microscopy (SEM) was utilized to analyze the microstructure and thickness of the coatings, while X-ray diffraction (XRD) was employed to determine their phase composition. The findings reveal that the surface morphology of the calcium phosphate coatings transitions from a porous, sponge-like structure to flower-like formations as the duty cycle and voltage increase. A linear increase in the voltage within the applied duty cycles led to a rise in the size of the forming particles of amorphous/crystalline structures containing phases of monetite (CaPO3(OH)), monocalcium phosphate monohydrate (Ca(H2PO4)2·H2O), and calcium pyrophosphate (γ–Ca2P2O7).
Study of Ceramic Hollow Buoyant Balls Prepared Based on Slip Mold Casting and Brazing Process
Authors: Lei Yu , Zhou Jian , Liu Guizhen , Wang Lin , Ding Zhongjun
Published: June 2024

In the domain of deep-sea buoyancy material applications, hollow ceramic spheres, known for their high strength and low mass-to-drainage ratio, contribute to increased buoyancy and payload capacity enhancement for deep submersibles, constituting buoyancy materials of exceptional overall performance. This study entails the brazing of two ceramic hemispherical shells, obtained through slurry molding, to form a ceramic float. This process, which integrates slurry molding and ceramic brazing, facilitates buoyancy provision. Further refinement involves welding a ceramic connector onto the ceramic shell, incorporating a top opening to create a ceramic float equipped with an observation window seat. The ceramic float maintains uniform wall thickness, while the observation window facilitates external environmental observation in deep-sea research. Two pressure-resistant spherical shells, produced using this process, underwent testing, revealing the wall thickness of the prepared alumina ceramic hollow spheres to be 1.00 mm, with a mass-to-drainage ratio of 0.47 g/cm3 and a buoyancy coefficient of 53%. The resultant ceramic hollow floating ball can withstand hydrostatic pressure of 120 MPa, while the pressure-resistant ball shell with an observation window seat can endure hydrostatic pressure of 100 MPa, ensuring safe operation at depths of 5000–6000 m. This process provides a production method for subsequent large-scale ceramic float manufacturing for the transportation of objects or personnel.
Beyond the Classroom: An Analysis of Internal and External Factors Related to Students’ Love of Learning and Educational Outcomes
Authors: Burke Charles M. , Montross Lori P. , Dianova Vera G.
Published: June 2024

This study explores the multifaceted factors influencing student learning motivations and educational outcomes. Utilizing a diverse student body from Franklin University Switzerland, the study emphasizes the impact of internal factors, such as the psychological state of flow and a self-reported love of learning, alongside GPA and student cohort influences like year of study, academic discipline, country of origin, and academic travel. Through a cross-sectional survey of 112 students, the study evaluates how these factors correlate with and diverge from each other and student GPAs, aiming to dissect the influences of intrinsic motivations, demographic variables, and educational experiences. Our analysis revealed significant correlations between students’ self-reported love of learning, experiences of flow, and academic performance. Conversely, academic travel did not show a significant direct impact, suggesting that while such experiences are enriching, they do not necessarily translate into a greater love of learning, flow, or higher academic achievement in the short term. However, demographic factors, particularly discipline of study and country of origin, significantly influenced the students’ love of learning, indicating varied motivational drives across different cultural and educational backgrounds. This study provides valuable insights for educational policymakers and institutions aiming to cultivate more engaging and fulfilling learning environments.
Predicting Tumor Dynamics Post-Staged GKRS: Machine Learning Models in Brain Metastases Prognosis
Authors: Trofin Ana-Maria , Buzea Călin Gh. , Buga Răzvan , Agop Maricel , Ochiuz Lăcrămioara , Iancu Dragos Teodor , Eva Lucian
Published: June 2024

This study assesses the predictive performance of six machine learning models and a 1D Convolutional Neural Network (CNN) in forecasting tumor dynamics within three months following Gamma Knife radiosurgery (GKRS) in 77 brain metastasis (BM) patients. The analysis meticulously evaluates each model before and after hyperparameter tuning, utilizing accuracy, AUC, and other metrics derived from confusion matrices. The CNN model showcased notable performance with an accuracy of 98% and an AUC of 0.97, effectively complementing the broader model analysis. Initial findings highlighted that XGBoost significantly outperformed other models with an accuracy of 0.95 and an AUC of 0.95 before tuning. Post-tuning, the Support Vector Machine (SVM) demonstrated the most substantial improvement, achieving an accuracy of 0.98 and an AUC of 0.98. Conversely, XGBoost showed a decline in performance after tuning, indicating potential overfitting. The study also explores feature importance across models, noting that features like “control at one year”, “age of the patient”, and “beam-on time for volume V1 treated” were consistently influential across various models, albeit their impacts were interpreted differently depending on the model’s underlying mechanics. This comprehensive evaluation not only underscores the importance of model selection and hyperparameter tuning but also highlights the practical implications in medical diagnostic scenarios, where the accuracy of positive predictions can be crucial. Our research explores the effects of staged Gamma Knife radiosurgery (GKRS) on larger tumors, revealing no significant outcome differences across protocols. It uniquely considers the impact of beam-on time and fraction intervals on treatment efficacy. However, the investigation is limited by a small patient cohort and data from a single institution, suggesting the need for future multicenter research.
Left Ventricular Papillary Muscle: Anatomy, Pathophysiology, and Multimodal Evaluation
Authors: Li Shiying , Wang Zhen , Fu Wenpei , Li Fangya , Gu Hui , Cui Nan , Lin Yixia , Xie Mingxing , Yang Yali
Published: June 2024

As an integral part of the mitral valve apparatus, the left ventricle papillary muscle (PM) controls mitral valve closure during systole and participates in the ejection process during left ventricular systole. Mitral regurgitation (MR) is the most immediate and predominant result when the PM is structurally or functionally abnormal. However, dysfunction of the PM is easily underestimated or overlooked in clinical interventions for MR-related diseases. Therefore, adequate recognition of PM dysfunction and PM-derived MR is critical. In this review, we systematically describe the normal anatomical variations in the PM and the pathophysiology of PM dysfunction-related diseases and summarize the commonly used parameters and the advantages and disadvantages of various noninvasive imaging modalities for the structural and functional assessment of the PM.
Early Detection of Inflammation and Malnutrition and Prediction of Acute Events in Hemodialysis Patients through PINI (Prognostic Inflammatory and Nutritional Index)
Authors: Cordos Monica , Martu Maria-Alexandra , Vlad Cristiana-Elena , Toma Vasilica , Ciubotaru Alin Dumitru , Badescu Minerva Codruta , Goriuc Ancuta , Foia Liliana
Published: June 2024

Protein-energy wasting and inflammation are major risk factors for complications in hemodialysis patients. As these risk factors are triggered by a pro-inflammatory state, oxidative stress and hemodynamic dysfunction, which overlap in hemodialyzed subjects, we aimed to assess the efficacy of a cost-effective and straightforward screening tool, the Prognostic Inflammatory and Nutritional Index (PINI), in regularly screening maintenance hemodialysis (MHD) patients, to detect early signs of inflammation and malnutrition. A 12-month follow-up was carried out on a cohort of 102 adult patients undergoing maintenance dialysis, during which the Prognostic Inflammatory and Nutritional Index (PINI) was calculated using the formula alpha1-Acid Glycoprotein (AGP) × C-reactive protein (CRP)/albumin (ALB) × transthyretin (TTR). A PINI score < 1 was considered normal. The patients were stratified based on their PINI score: 66 patients (64.70%) had a normal score, below 1, while 36 patients (35.30%) had a PINI score ≥ 1. Despite the absence of clinical evidence of inflammation at enrollment, the latter group exhibited higher levels of CRP. During the follow-up period, all patients with a PINI score ≥ 1 experienced at least one acute event, compared to only 6% of patients with a normal PINI score, which presented COVID-19 infection as an acute event. The evaluation of the PINI can effectively identify the silent malnutrition–inflammation syndrome and predict the risk of acute events. This straightforward test appears to be a rapid tool that is independent of the examiner’s experience and subjectivity, thereby potentially reducing hospitalization costs.
Topographic and Surgical Risk Factors for Early Myopic Regression between Small Incision Lenticule Extraction and Laser In Situ Keratomileusis
Authors: Lee Chia-Yi , Jeng Yu-Ting , Yang Shun-Fa , Huang Chin-Te , Chao Chen-Cheng , Lian Ie-Bin , Huang Jing-Yang , Chang Chao-Kai
Published: June 2024

Our objective was to evaluate the topographic and surgical factors of early myopic regression between laser in situ keratomileusis (LASIK) and small-incision lenticule extraction (SMILE). A retrospective case–control study was conducted, and 368 and 92 eyes were enrolled in the LASIK and SMILE groups via propensity score matching (PSM). Visual acuity, refractive status, axial length, and topographic/surgical parameters were collected. Multiple linear regression was applied to the yield coefficient and the 95% confidence interval (CI) of the parameters. The cumulative incidence of early myopic regression was higher in the LASIK group (p < 0.001). In the SMILE group, a lower central corneal thickness (CCT) thinnest value and a higher corneal cylinder associated with early myopic regression were observed; meanwhile, in the LASIK group, a lower CCT thinnest value, a higher steep corneal curvature, a larger optic zone, and a lower flap thickness related to early myopic regression were observed (all p < 0.05). In the SMILE group, a higher CCT difference correlated with early myopic regression was observed compared to the LASIK group (p = 0.030), and higher steep corneal curvature and lower cap/flap thickness (both p < 0.05) correlated with early myopic regression were observed in the LASIK group compared to the SMILE group. In conclusion, CCT differences significantly influence early myopic regression in the SMILE group; meanwhile, corneal curvature and flap thickness affect early myopic regression principally in the LASIK group.
Whole-Exome Sequencing Revealed a Pathogenic Germline Variant in the Fumarate Hydratase Gene, Leading to the Diagnosis of Hereditary Leiomyomatosis and Renal Cell Cancer
Authors: Nagashima Akari , Morimura Sohshi , Hamada Toshihisa , Shiomi Takayuki , Mori Ichiro , Sato Naoko , Nomoto Junko , Tanaka Masaki , Tsuji Shoji , Sugaya Makoto
Published: June 2024

The diagnosis of hereditary skin tumors is difficult for “old” diagnostic tools such as immunohistochemistry. Whole-exome sequencing analysis as a “new” diagnostic tool enables us to make a final diagnosis in spite of unknown hereditary diseases in the past. Hereditary leiomyomatosis and renal cell cancer are autosomal dominant hereditary cancer syndromes characterized by uterine myomas, cutaneous leiomyomas, and aggressive renal cell cancer. The syndrome is associated with pathogenic germline variants in the fumarate hydratase gene. Herein, we demonstrate a pathogenic germline variant of the fumarate hydratase gene in a 60-year-old woman with multiple cutaneous leiomyomas, leading to the diagnosis of hereditary leiomyomatosis and renal cell cancer. Whole-exome sequencing analysis using genomic DNA extracted from peripheral blood leukocytes revealed one germline variant in the FH gene on chromosome 1 (c.290G>A, p.Gly97Asp). She received total hysterectomy due to uterine myoma, which strongly supported the diagnosis. No tumor was detected in her kidney by computed tomography and ultrasound examination. Genetic examination for the mutation of the fumarate hydratase gene is important in order to reach the correct diagnosis and to detect renal cancer at its early stage.
Diagnostic Performance of Plasma SP-D, KL-6, and CC16 in Acutely Hospitalised Patients Suspected of Having Community-Acquired Pneumonia—A Diagnostic Accuracy Study
Authors: Heltborg Anne , Mogensen Christian B. , Andersen Eline S. , Cartuliares Mariana B. , Petersen Eva R. B. , Skovsted Thor A. , Posth Stefan , Graumann Ole , Lorentzen Morten J. , Hertz Mathias A. , Brasen Claus L. , Skjøt-Arkil Helene
Published: June 2024

Community-acquired pneumonia is a common cause of acute hospitalisation. Identifying patients with community-acquired pneumonia among patients suspected of having the disease can be a challenge, which causes unnecessary antibiotic treatment. We investigated whether the circulatory pulmonary injury markers surfactant protein D (SP-D), Krebs von den Lungen-6 (KL-6), and Club cell protein 16 (CC16) could help identify patients with community-acquired pneumonia upon acute admission. In this multi-centre diagnostic accuracy study, SP-D, KL-6, and CC16 were quantified in plasma samples from acutely hospitalised patients with provisional diagnoses of community-acquired pneumonia. The area under the receiver operator characteristics curve (AUC) was calculated for each marker against the following outcomes: patients’ final diagnoses regarding community-acquired pneumonia assigned by an expert panel, and pneumonic findings on chest CTs. Plasma samples from 339 patients were analysed. The prevalence of community-acquired pneumonia was 63%. AUCs for each marker against both final diagnoses and chest CT diagnoses ranged between 0.50 and 0.56. Thus, SP-D, KL-6, and CC16 demonstrated poor diagnostic performance for community-acquired pneumonia in acutely hospitalised patients. Our findings indicate that the markers cannot readily assist physicians in confirming or ruling out community-acquired pneumonia.
A Comparative Study of Different CFD Codes for Fluidized Beds
Authors: Kusriantoko Parindra , Daun Per Fredrik , Einarsrud Kristian Etienne
Published: June 2024

Fluidized beds are pivotal in the process industry and chemical engineering, with Computational Fluid Dynamics (CFD) playing a crucial role in their design and optimization. Challenges in CFD modeling stem from the scarcity or inconsistency of experimental data for validation, along with the uncertainties introduced by numerous parameters and assumptions across different CFD codes. This study navigates these complexities by comparing simulation results from the open-source MFIX and OpenFOAM, and the commercial ANSYS FLUENT, against experimental data. Utilizing a Eulerian–Eulerian framework and the kinetic theory of granular flow (KTGF), the investigation focuses on solid-phase properties through the classical drag laws of Gidaspow and Syamlal–O’Brien across varied parameters. Findings indicate that ANSYS Fluent, MFiX, and OpenFOAM can achieve reasonable agreement with experimental benchmarks, each showcasing distinct strengths and weaknesses. The study also emphasizes that both the Syamlal–O’Brien and Gidaspow drag models exhibit reasonable agreement with experimental benchmarks across the examined CFD codes, suggesting a moderated sensitivity to the choice of drag model. Moreover, analyses were also carried out for 2D and 3D simulations, revealing that the dimensional approach impacts the predictive accuracy to a certain extent, with both models adapting well to the complexities of each simulation environment. The study highlights the significant influence of restitution coefficients on bed expansion due to their effect on particle–particle collisions, with a value of 0.9 deemed optimal for balancing simulation accuracy and computational efficiency. Conversely, the specularity coefficient, impacting particle–wall interactions, exhibits a more subtle effect on bed dynamics. This finding emphasizes the critical role of carefully choosing these coefficients to effectively simulate the nuanced behaviors of fluidized beds.
Generating Innovative Ideas for School Improvement: An Examination of School Principals
Authors: Gonzales Miguel M. , Garza Tiberio , Leon-Zaragoza Elizabeth
Published: June 2024

The purpose of this exploratory study was to examine school principals’ tendencies and practices that bring forth innovative ideas for school improvement. School principals (N = 124) responded to a survey, which included an open-ended question, on their innovative practices toward school improvement. With the Innovator’s DNA framework as a basis for generating innovation for school improvement, path analysis was used to assess how well school principals’ thinking and practices aligned with the framework. School principals believed it was important to help generate innovation through idea networking, being open-minded, and challenging the status quo. However, through path analysis, school principals’ improvement areas associated with the Innovator’s DNA framework were identified. School systems should help principals develop innovative problem-solving skills for school improvement by applying the Innovator’s DNA framework in their professional development opportunities. More research is needed that examines if and how school systems foster school innovation leadership for principals.
Examining Relationships between Technology and Critical Thinking: A Study of South Korean EFL Learners
Authors: Schenck Andrew
Published: June 2024

Little research has been conducted to examine how technology shapes values concerning critical thinking (CT) in English as a Foreign Language (EFL) contexts. Due to the need for further research, this study was designed to examine the relationships between perceptions of technology and attitudes about CT. A total of 80 EFL students were given two Likert surveys and two optional qualitative questions concerning CT and technology. Likert surveys were compared using Spearman’s rank correlation, whereas qualitative data were evaluated using reflexive thematic analysis. Quantitative results revealed that support for engagement with tech and laptops, along with support for using technology for career goals or IT skills development, positively correlated to a learner’s understanding and value for CT. In contrast, learners who favored using technology did not tend to value CT and were more likely to skip class if materials were provided online. Qualitative results also suggest that prosocial behaviors for engagement and clear goals promote positive attitudes toward CT, whereas overreliance on technology hampers the cultivation of CT in EFL classrooms. Implications for pedagogy have been proposed.
Hybrid Approach to Predicting Learning Success Based on Digital Educational History for Timely Identification of At-Risk Students
Authors: Kustitskaya Tatiana A. , Esin Roman V. , Vainshtein Yuliya V. , Noskov Mikhail V.
Published: June 2024

Student retention is a significant challenge for higher education institutions (HEIs). The fact that a considerable number of dropouts from universities are primarily due to academic underperformance motivates universities to develop learning analytics tools based on models for predicting learning success. However, the scalability of such models is limited since students’ academic performance and engagement, as well as the factors influencing them, are largely determined by the educational environment. The article proposes a hybrid approach to forecasting success in completing an academic semester, which involves creating a set of predictive models. Some of the models use historical student data, while others are intended to refine the forecast using current data on student performance and engagement, which are regularly extracted from available sources. Based on this approach, we developed an ensemble of machine learning models and the Markov-process model that simultaneously address the tasks of forecasting success in mastering a course and success in completing a semester. The models utilize digital footprint data, digital educational history, and digital personality portraits of students extracted from the databases of Siberian Federal University, and the resulting ensemble demonstrates a high quality of the forecast. The proposed approach can be utilized by other HEIs as a framework for creating mutually complementary forecasting models based on different types of accessible educational data.