bluuebunny/crossref_metadata_2025 huggingface dataset:
Review of Magnetic Properties and Texture Evolution in Non-Oriented Electrical Steels
Authors: Du Yizhou , O’Malley Ronald , Buchely Mario F.
Published: May 2023

Electrical steels can be classified into two groups: grain-oriented (GO) and non-oriented (NGO) electrical steel. NGO electrical steels are mainly considered as core materials for different devices, such as electric motors, generators, and rotating machines. The magnetic properties and texture evolution of NGO electrical steels depend on multiple factors (such as chemical content, heat-treatment, and rolling process) making the development of new products a complex task. In this review, studies on the magnetic properties of NGO electrical steels and the corresponding texture evolution are summarized. The results indicate that further research is required for NGO electrical steels to ensure high permeability and low core loss properties.
Mechanical Resistance of Different Implant Suprastructures: A Laboratory Study
Authors: Iliev Georgi , Filtchev Dimitar , Trifković Branka , Jevremović Danimir , Pavlova Zhanina , Slavkov Svetoslav , Stoeva Daniela
Published: May 2023

Background: Appropriate abutment selection according to the individual specificities of each patient is a leading factor in achieving high aesthetic results. Standardized titanium abutments are the most widely used due to their easy use and low cost. It is considered that customized abutments can eliminate many of the complications seen with factory abutments in prosthetic treatment. The purpose of this study is to evaluate whether customized abutments have better mechanical behavior in laboratory settings than standard ones. The null hypothesis is that customized abutments have better resistance to cyclic load and compression than factory abutments. Methods: The study model includes thirty implant suprastructure samples, fabricated digitally, divided into three groups according to the type of implant abutment and the used material: Group A (control group) comprised monolithic implant crowns made of zirconium dioxide and a titanium base; Group B (test group) comprised monolithic implant crowns made of zirconia implant crowns and a customized titanium alloy abutment; and Group C (test group) comprised monolithic implant crowns made of lithium disilicate and a customized titanium alloy abutment. The samples were subjected to dynamic load in a computer-controlled 2-axis machine that simulated masticatory movements, Chewing Simulator CS-4 (SD-Mechatronik, Westerham, Germany), for 250,000 cycles at a frequency of 2 Hz. The samples were then subjected to compressive strength testing in an Instron M 1185 universal testing machine. A metal steel disc was used as an antagonist, exerting pressure at a rate of 2 mm/min at room temperature on each sample. After conducting the laboratory tests, the samples were examined by an experienced expert under a Carl Zeiss microscope (Carl Zeiss Microscopy GmbH, Jena, Germany). Results: All samples were found to have passed the fatigue test in the masticatory simulator without any of the listed complications. The average value of the compressive strength at which the structures in each group fracture is as follows: Group A, 5669.2; Group B, 3126.5; and Group C, 1850.6. Based on the average values, it can be concluded that the combination of materials used in Group A has the greatest resistance. Conclusion: The weak link in the prosthetic complex consisting of a crown and abutment seems to be the crown. No abutment failure was found regardless of the type. However, monolithic zirconia crowns over standard titanium abutments withstand higher mechanical forces compared with zirconia and lithium disilicate crowns over customized ones. Detailed studies in clinical settings may provide more in-depth information on this issue.
A Comprehensive Methodology for Investment Project Assessment Based on Monte Carlo Simulation
Authors: Fabianová Jana , Janeková Jaroslava , Fedorko Gabriel , Molnár Vieroslav
Published: May 2023

This article presents a methodology for assessing investment projects representing the sequence of steps necessary for a comprehensive assessment and optimization of an investment project. The assessment process starts with the quantitative forecasting of stochastic input factors, with the selection of risk factors and the definition of their uncertainty. That is followed by the design of a mathematical model for calculating the criterion of economic efficiency of investment, its calculation mathematically, and forecasting by Monte Carlo simulation. The simulation output is assessed from the point of view of risk, and in case of an unacceptable result, the possibilities for project optimization are proposed. Finally, the proposed methodology was applied to an investment project model, where individual principles are practically demonstrated.
MKBQA: Question Answering over Knowledge Graph Based on Semantic Analysis and Priority Marking Method
Authors: Wang Xiang , Li Yanchao , Wang Huiyong , Lv Menglong
Published: May 2023

In the field of question answering-based knowledge graphs, due to the complexity of the construction of knowledge graphs, a domain-specific knowledge graph often cannot contain some common-sense knowledge, which makes it impossible to answer questions that involve common-sense and domain knowledge at the same time. Therefore, this study proposes a knowledge graph-based question answering method in the computer science domain, which facilitates obtaining complete answers in this domain. In order to solve the problem of natural language problems being difficult to match with structured knowledge, a series of logic rules are first designed to convert natural language into triples of the question. Then, a semantic query expansion strategy based on WordNet is proposed and a priority marking algorithm is proposed to mark the order of triples of the question. Finally, when a question triple corresponds to multiple triples in the knowledge graph, it can be solved by the proposed SimCSE-based similarity method. The designed logic rules can deal with each type of question in a targeted manner according to the different question words and can effectively transform the question text into question triples. In addition, the proposed priority marking algorithm can effectively mark the order in the triple of the question. MKBQA can answer not only computer science-related questions but also extended open domain questions. In practical applications, answering a domain question often cannot rely solely on one knowledge graph. It is necessary to combine domain knowledge and common-sense knowledge. The MKBQA method provides a new idea and can be easily migrated from the field of computer science to other fields. Experiment results on real-world data sets show that, as compared to baselines, our method achieves significant improvements to question answering and can combine common-sense and domain-specific knowledge graphs to give a more complete answer.
Structure Design, Kinematics Analysis, and Effect Evaluation of a Novel Ankle Rehabilitation Robot
Authors: Qu Shuwei , Li Ruiqin , Yao Wei , Ma Chunsheng , Guo Zhihong
Published: May 2023

This paper presents a novel ankle rehabilitation (2-CRS+PU)&R hybrid mechanism, which can meet the size requirements of different adult lower limbs based on the three-movement model of the ankle. This model is related to three types of movement modes of the ankle movement, without axis offset, which can cover the ankle joint movements. The inverse and forward position/kinematics results analysis of the mechanism is established based on the closed-loop vector method and using the optimization of particle groups algorithm. Four groups of position solutions of the mechanism are obtained. The kinematics simulation is analyzed using ADAMS software. The variations of the velocity and acceleration of all limbs are stable, without any sudden changes, which can effectively ensure the safety and comfort of the ankle model end-user. The dexterity of the mechanism is analyzed based on the transport function, and the results indicate that the mechanism has an excellent transfer performance in yielding the structure parameters. Finally, the rehabilitation evaluation is conducted according to the three types of movement modes of the ankle joint. The results show that this ankle rehabilitation mechanism can provide a superior rehabilitation function.
WASP—A Web Application to Support Syntactically and Semantically Correct SNOMED CT Postcoordination
Authors: Drenkhahn Cora , Ohlsen Tessa , Wiedekopf Joshua , Ingenerf Josef
Published: May 2023

Expressive clinical terminologies are of utmost importance for achieving a semantically interoperable data exchange and reuse in healthcare. SNOMED CT, widely respected as the most comprehensive terminology in medicine, provides formal concept definitions based on description logic which not only allows for advanced querying of SNOMED-CT-coded data but also for flexibly augmenting its 350,000 concepts by allowing a controlled combination of these. This ability for postcoordination largely increases the expressivity of the terminology but correlates with an intrinsic complexity. Complicated by the current lack of tooling support, postcoordination is widely either ignored or applied in an error-prone way. To help facilitate the adoption of postcoordination, we implemented a web application that guides users through the creation of postcoordinated expressions (PCEs) while ensuring adherence to syntactic and semantic constraints. Our approach was largely facilitated by making use of the extensive SNOMED CT specifications as well as advanced HL7 FHIR Terminology Services. Qualitative evaluations confirmed the usability of the developed application and the correctness of the PCEs created with it.
LFDC: Low-Energy Federated Deep Reinforcement Learning for Caching Mechanism in Cloud–Edge Collaborative
Authors: Zhang Xinyu , Hu Zhigang , Zheng Meiguang , Liang Yang , Xiao Hui , Zheng Hao , Xu Aikun
Published: May 2023

The optimization of caching mechanisms has long been a crucial research focus in cloud–edge collaborative environments. Effective caching strategies can substantially enhance user experience quality in these settings. Deep reinforcement learning (DRL), with its ability to perceive the environment and develop intelligent policies online, has been widely employed for designing caching strategies. Recently, federated learning, when combined with DRL, has been in gaining popularity for optimizing caching strategies and protecting data training privacy from eavesdropping attacks. However, online federated deep reinforcement learning algorithms face high environmental dynamics, and real-time training can result in increased training energy consumption despite improving caching efficiency. To address this issue, we propose a low-energy federated deep reinforcement learning strategy for caching mechanisms (LFDC) that balances caching efficiency and training energy consumption. The LFDC strategy encompasses a novel energy efficiency model, a deep reinforcement learning mechanism, and a dynamic energy-saving federated policy. Our experimental results demonstrate that the proposed LFDC strategy significantly outperforms existing benchmarks in terms of energy efficiency.
Parametric, Semiparametric, and Semi-Nonparametric Estimates of the Kinetic Energy of Ordered Air Motion and Wind Outliers in the Atmospheric Boundary Layer from Minisodar Measurements
Authors: Simakhin Valerii Anan’evich , Potekaev Alexander Ivanovich , Cherepanov Oleg Sergeevich , Shamanaeva Liudmila Grigor’evna
Published: May 2023

In the present work, we analyze the spatiotemporal dynamics of the kinetic wind energy with and without allowance for the kinetic energy of outliers. We first separated the contributions of the mean kinetic energy and the kinetic energy of the outliers and estimated the latter using robust parametric, semiparametric, and semi-nonparametric algorithms developed by the authors. The kinetic wind energy was estimated by the postprocessing of minisodar measurements of three wind velocity components and their variances in the lower 200 m layer of the atmosphere. By the outliers, we mean wind velocities, including wind gusts, the distribution of which deviates from the prior distribution of the majority of observations. A nonmonotonic increase in the kinetic energy of the outliers with sounding altitude was established. Physically, this can be explained by a nonmonotonic increase in the turbulent kinetic energy of local air vortices in the atmospheric boundary layer (ABL). The vertical extension of the outlier layers was of the order of 10–20 m.
Nanobiomaterials Revolutionizing Biomedical Science: Special Issue—“Nanotechnology for Biomedical Applications”
Authors: Sardo Carla
Published: May 2023

The field of nanotechnology applied to biomedicine has witnessed unprecedented growth in recent years owing to the development of new nanobiomaterials and the exploration of novel strategies for tackling medical problems at the nanoscale [...]
HoloForkNet: Digital Hologram Reconstruction via Multibranch Neural Network
Authors: Svistunov Andrey S. , Rymov Dmitry A. , Starikov Rostislav S. , Cheremkhin Pavel A.
Published: May 2023

Reconstruction of 3D scenes from digital holograms is an important task in different areas of science, such as biology, medicine, ecology, etc. A lot of parameters, such as the object’s shape, number, position, rate and density, can be extracted. However, reconstruction of off-axis and especially inline holograms can be challenging due to the presence of optical noise, zero-order image and twin image. We have used a deep-multibranch neural network model, which we call HoloForkNet, to reconstruct different 2D sections of a 3D scene from a single inline hologram. This paper describes the proposed method and analyzes its performance for different types of objects. Both computer-generated and optically registered digital holograms with resolutions up to 2048 × 2048 pixels were reconstructed. High-quality image reconstruction for scenes consisting of up to eight planes was achieved. The average structural similarity index (SSIM) for 3D test scenes with eight object planes was 0.94. The HoloForkNet can be used to reconstruct 3D scenes consisting of micro- and macro-objects.
Modeling of Organic Aerosol in Seoul Using CMAQ with AERO7
Authors: Park Hyeon-Yeong , Hong Sung-Chul , Lee Jae-Bum , Cho Seog-Yeon
Published: May 2023

The Community Multiscale Air Quality (CMAQ) model with the 7th generation aerosol module (AERO7) was employed to simulate organic aerosol (OA) in Seoul, Korea, for the year 2016. The goal of the present study includes the 1-year simulation of OA using WRF-CMAQ with recently EPA-developed AERO7 with pcVOC (potential VOC from combustion) scale factor revision and analysis of the seasonal behavior of OA surrogate species in Seoul. The AERO7, the most recent version of the aerosol module of the CMAQ model, includes a new secondary organic aerosol (SOA) species, pcSOA (potential SOA from combustion), to resolve the inherent under-prediction problem of OA. The AERO7 classified OA into three groups: primary organic aerosol (POA), anthropogenic SOA (ASOA), and biogenic SOA (BSOA). Each OA group was further classified into 6~15 individual OA surrogate species according to volatility and oxygen content to model the aging of OA and the formation of SOA. The hourly emissions of POA and SOA precursors were compiled and fed into the CMAQ to successfully simulate seasonal variations of OA compositions and ambient organic-matter to organic-carbon ratios (OM/OC). The model simulation showed that the POA and ASOA were major organic groups in the cool months (from November to March) while BSOA was a major organic group in the warm months (from April to October) in Seoul. The simulated OM/OCs ranged from 1.5~2.1 in Seoul, which agreed well with AMS measurements in Seoul in May 2016.
β-TCP/S53P4 Scaffolds Obtained by Gel Casting: Synthesis, Properties, and Biomedical Applications
Authors: Amaral Suelen Simões , Lima Beatriz Samara de Sousa , Avelino Sarah Oliveira Marco , Spirandeli Bruno Roberto , Campos Tiago Moreira Bastos , Thim Gilmar Patrocínio , Trichês Eliandra de Sousa , Prado Renata Falchete do , Vasconcellos Luana Marotta Reis de
Published: May 2023

The objective of this study was to investigate the osteogenic and antimicrobial effect of bioactive glass S53P4 incorporated into β-tricalcium phosphate (β-TCP) scaffolds in vitro and the bone neoformation in vivo. β-TCP and β-TCP/S53P4 scaffolds were prepared by the gel casting method. Samples were morphologically and physically characterized through X-ray diffraction (XRD) and scanning electron microscope (SEM). In vitro tests were performed using MG63 cells. American Type Culture Collection reference strains were used to determine the scaffold’s antimicrobial potential. Defects were created in the tibia of New Zealand rabbits and filled with experimental scaffolds. The incorporation of S53P4 bioglass promotes significant changes in the crystalline phases formed and in the morphology of the surface of the scaffolds. The β-TCP/S53P4 scaffolds did not demonstrate an in vitro cytotoxic effect, presented similar alkaline phosphatase activity, and induced a significantly higher protein amount when compared to β-TCP. The expression of Itg β1 in the β-TCP scaffold was higher than in the β-TCP/S53P4, and there was higher expression of Col-1 in the β-TCP/S53P4 group. Higher bone formation and antimicrobial activity were observed in the β-TCP/S53P4 group. The results confirm the osteogenic capacity of β-TCP ceramics and suggest that, after bioactive glass S53P4 incorporation, it can prevent microbial infections, demonstrating to be an excellent biomaterial for application in bone tissue engineering.
Imaging Phenotypes and Evolution of Hepatic Langerhans Cell Histiocytosis on CT/MRI: A Retrospective Study of Clinical Cases and Literature Review
Authors: Hao Luwen , Li Yuanqiu , Xiong Ziman , Jiang Yuchen , Hu Xuemei , Hu Daoyu , Li Zhen , Shen Yaqi
Published: May 2023

(1) Background: pathological changes in hepatic Langerhans cell histiocytosis (LCH) have been observed; however, corresponding imaging findings can appear vague to physicians and radiologists. The present study aimed to comprehensively illustrate the imaging findings of hepatic LCH and to investigate the evolution of LCH-associated lesions. (2) Methods: LCH patients with liver involvement treated at our institution were retrospectively reviewed along with prior studies in PubMed. Initial and follow-up computed tomography (CT) and magnetic resonance imaging (MRI) were systematically reviewed, and three imaging phenotypes were created based on the lesion distribution pattern. Clinical features and prognoses were compared among the three phenotypes. Liver fibrosis was evaluated visually on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) values of the fibrotic areas were measured. Descriptive statistics and a comparative analysis were used to analyze the data. (3) Results: based on the lesion distribution pattern on CT/MRI scans, patients with liver involvement were categorized as the disseminated lesion phenotype, scattered lesion phenotype, and central periportal lesion phenotype. Patients with scattered lesion phenotype were typically adults, and only a few of them had hepatomegaly (npresent = 1, 1/6, 16.7%) and liver biochemical abnormalities (npresent = 2, 2/6, 33.3%); patients with central periportal lesion phenotype were typically young children, and hepatomegaly and biochemical abnormalities were more apparent in these patients than those with another phenotype; and those with the disseminated lesion phenotype were found in all age groups, and the lesions evolved rapidly on medical imaging. Follow-up MRI scans show more details and can better document the evolution of lesions than CT. T2-hypointense fibrotic changes, including the periportal halo sign (npresent = 2, 2/9, 22.2%), patchy liver parenchyma changes (npresent = 6, 6/9, 66.7%), and giant hepatic nodules close to the central portal vein (npresent = 1, 1/9, 11.1%), were found, while fibrotic changes were not observed in patients with the scattered lesion phenotype. The mean ADC value for the area of liver fibrosis in each patient was lower than the optimal cutoff for significant fibrosis (METAVIR Fibrosis Stage ≥ 2) in a previous study that assessed liver fibrosis in chronic viral hepatitis. (4) Conclusions: The infiltrative lesions and liver fibrosis of hepatic LCH can be well characterized on MRI scans with DWI. The evolution of these lesions was well demonstrated on follow-up MRI scans.
Wnt Signaling in Brain Tumors: A Challenging Therapeutic Target
Authors: Manfreda Lorenzo , Rampazzo Elena , Persano Luca
Published: May 2023

The involvement of Wnt signaling in normal tissue homeostasis and disease has been widely demonstrated over the last 20 years. In particular, dysregulation of Wnt pathway components has been suggested as a relevant hallmark of several neoplastic malignancies, playing a role in cancer onset, progression, and response to treatments. In this review, we summarize the current knowledge on the instructions provided by Wnt signaling during organogenesis and, particularly, brain development. Moreover, we recapitulate the most relevant mechanisms through which aberrant Wnt pathway activation may impact on brain tumorigenesis and brain tumor aggressiveness, with a particular focus on the mutual interdependency existing between Wnt signaling components and the brain tumor microenvironment. Finally, the latest anti-cancer therapeutic approaches employing the specific targeting of Wnt signaling are extensively reviewed and discussed. In conclusion, here we provide evidence that Wnt signaling, due to its pleiotropic involvement in several brain tumor features, may represent a relevant target in this context, although additional efforts will be needed to: (i) demonstrate the real clinical impact of Wnt inhibition in these tumors; (ii) overcome some still unsolved concerns about the potential systemic effects of such approaches; (iii) achieve efficient brain penetration.
Correction: Masi et al. Araufuranone: A New Phytotoxic Tetrasubstituted Dihydrofuro[3,2-b]furan-2(5H)-One Isolated from Ascochyta araujiae. Biomolecules 2022, 12, 1274
Authors: Masi Marco , Boari Angela , Sautua Francisco , Carmona Marcelo Anibal , Vurro Maurizio , Evidente Antonio
Published: May 2023

In the original article [...]
Clusterin and Its Isoforms in Oral Squamous Cell Carcinoma and Their Potential as Biomarkers: A Comprehensive Review
Authors: Zhang Qinyi , Teow Jun Yao , Kerishnan Jesinda Pauline , Abd Halim Adyani Azizah , Chen Yeng
Published: May 2023

Oral squamous cell carcinoma (OSCC) is a prevalent type of head and neck cancer, ranked as the sixth most common cancer worldwide, accounting for approximately 300,000 new cases and 145,000 deaths annually. Early detection using biomarkers significantly increases the 5-year survival rate of OSCC by up to 80–90%. Clusterin (CLU), also known as apolipoprotein J, is a sulfated chaperonic glycoprotein expressed in all tissues and human fluids and has been reported to be a potential biomarker of OSCC. CLU has been implicated as playing a vital role in many biological processes such as apoptosis, cell cycle, etc. Abnormal CLU expression has been linked with the development and progression of cancers. Despite the fact that there are many studies that have reported the involvement of CLU and its isoforms in OSCC, the exact roles of CLU and its isoforms in OSCC carcinogenesis have not been fully explored. This article aims to provide a comprehensive review of the current understanding of CLU structure and genetics and its correlation with OSCC tumorigenesis to better understand potential diagnostic and prognostic biomarker development. The relationship between CLU and chemotherapy resistance in cancer will also be discussed to explore the therapeutic application of CLU and its isoforms in OSCC.
COVID-19: A Possible Contribution of the MAPK Pathway
Authors: Cusato Jessica , Manca Alessandra , Palermiti Alice , Mula Jacopo , Costanzo Martina , Antonucci Miriam , Trunfio Mattia , Corcione Silvia , Chiara Francesco , De Vivo Elisa Delia , Ianniello Alice , Ferrara Micol , Di Perri Giovanni , De Rosa Francesco Giuseppe , D’Avolio Antonio , Calcagno Andrea
Published: May 2023

Background: COVID-19 is characterized by an uncontrolled inflammatory response with high pro-inflammatory cytokine production through the activation of intracellular pathways, such as mitogen-activated protein kinase (MAPK). Viruses are able to exploit the MAPK pathway to their advantage; this pathway relevance to severe COVID-19 is poorly described. The aim of this study was to quantify biomarkers involved in the MAPK pathway and to clarify its possible role in affecting some COVID-19-related clinical features. Methods: H-RAS, C-RAF, MAPK1, MAPK2, and ERK were quantified through ELISA, and genetic polymorphisms were evaluated through real-time PCR. Results: We prospectively recruited 201 individuals (158 positive and 43 negative for SARS-CoV-2): 35 were male, and their median age was 65 years. MAPK-related biomarker levels were increased in SARS-CoV-2-positive participants (n = 89) compared to negative ones (n = 29). Dyspnea was reported by 48%; this symptom was associated with PBMC C-RAF levels in positive participants (p = 0.022) and type of ventilation (p = 0.031). The highest degree of ventilation was used by 8% for invasive ventilation and 41% for continuous positive airway pressure (CPAP). Conclusions: This is the first study that showed a possible contribution of MAPK-related biomarkers in affecting COVID-19 clinical features, and this may be relevant for identifying COVID-19 positive participants at risk of serious complications.
A Self-Powered Multifunctional Bracelet for Pulse Monitoring and Personal Rescue
Authors: Sun Wei , Xue Jiangtao , Tan Puchuan , Shi Bojing , Zou Yang , Li Zhou
Published: May 2023

For outdoor workers or explorers who may be exposed to extreme or wild environments for a long time, wearable electronic devices with continuous health monitoring and personal rescue functions in emergencies could play an important role in protecting their lives. However, the limited battery capacity leads to a limited serving time, which cannot ensure normal operation anywhere and at any time. In this work, a self-powered multifunctional bracelet is proposed by integrating a hybrid energy supply module and a coupled pulse monitoring sensor with the inherent structure of the watch. The hybrid energy supply module can harvest rotational kinetic energy and elastic potential energy from the watch strap swinging simultaneously, generating a voltage of 69 V and a current of 87 mA. Meanwhile, with a statically indeterminate structure design and the coupling of triboelectric and piezoelectric nanogenerators, the bracelet enables stable pulse signal monitoring during movement with a strong anti-interference ability. With the assistance of functional electronic components, the pulse signal and position information of the wearer can be transmitted wirelessly in real-time, and the rescue light and illuminating light can be driven directly by flipping the watch strap slightly. The universal compact design, efficient energy conversion, and stable physiological monitoring demonstrate the wide application prospects of the self-powered multifunctional bracelet.
Does Musicality Assist Foreign Language Learning? Perception and Production of Thai Vowels, Consonants and Lexical Tones by Musicians and Non-Musicians
Authors: Götz Antonia , Liu Liquan , Nash Barbara , Burnham Denis
Published: May 2023

The music and spoken language domains share acoustic properties such as fundamental frequency (f0, perceived as pitch), duration, resonance frequencies, and intensity. In speech, the acoustic properties form an essential part in differentiating between consonants, vowels, and lexical tones. This study investigated whether there is any advantage of musicality in the perception and production of Thai speech sounds. Two groups of English-speaking adults—one comprising formally trained musicians and the other non-musicians—were tested for their perception and production of Thai consonants, vowels, and tones. For both groups, the perception and production accuracy scores were higher for vowels than consonants and tones, and in production, there was also better accuracy for tones than consonants. Between the groups, musicians (defined as having more than five years of formal musical training) outperformed non-musicians (defined as having less than two years of formal musical training) in both the perception and production of all three sound types. Additional experiential factors that positively influenced the accuracy rates were the current hours of practice per week and those with some indication of an augmentation due to musical aptitude, but only in perception. These results suggest that music training, defined as formal training for more than five years, and musical training, expressed in hours of weekly practice, facilitate the perception and production of non-native speech sounds.
Performance Evaluation of Polypropylene Fiber-Reinforced Pavement Quality Concrete Made with Waste Granite Powder
Authors: Murthi Palanisamy , Lavanya Velpula , Bahrami Alireza , Poongodi Kolandasamy
Published: May 2023

This research was conducted to evaluate the influence of waste granite powder (WGP) and polypropylene (PP) fibers on the performance of M35-grade pavement quality concrete (PQC). WGP was mixed in PQC as replacement for cement and was varied from 0% to 25%. The pozzolanic concert of WGP was examined by the strength activity index. The performance of PP fibers in PQC was assessed after the addition of fibers from 0.25% to 1.25% by volume of concrete. The mechanical properties of PQC were evaluated including the compressive strength, flexural strength, and various durability related properties such as the acid attack, absorption test, sorptivity test, and chloride penetration depth test. The results showed that PQC blended with WGP enhanced the strength slightly up to the replacement level of 15%. The addition of PP fibers rooted the reduction of the slump value; however, it improved the mechanical properties up to the presence of 0.5% PP fibers in PQC. The relationship between the compressive strength and flexural strength of WGP blended with PP fiber-reinforced PQC was established.
Design Efficacy and Exploration Behavior of Student Architect-Engineer Design Teams in Shared Parametric Environments
Authors: Bunt Stephanie , Brown Nathan C.
Published: May 2023

Increasingly, architects and building engineers use parametric modeling programs to explore design solutions as professionals and as students. However, little is known about their combined efficacy and exploration in these tools when working in mixed design teams. While disciplinarily diverse teams of designers have been shown to develop more creative design solutions, this occurs primarily when there is a conducive environment and a shared understanding of design goals. Because architects and engineers are traditionally taught to use different tools and processes to address their professional goals, indicators of students’ combined efficacy in parametric tools are unclear. In response, this research uses a conceptual design experiment to study aspects of design efficacy and the exploration behavior of student architect-architect, engineer-engineer, and architect-engineer pairs within a live parametric modeling tool. The dimensions of their collaborative exploration within the tool were recorded, and their success at achieving the desired criteria was rated by professionals. Noticeable performance differences between team types were expected, including that the mixed design teams would better balance all goals and that the homogenous teams would better address their own disciplinary criteria. However, this was not the case when working in a shared, multidisciplinary digital environment, as the teams performed similarly despite having different member composition. We discuss several factors, such as the effect of digital design feedback and the still-developing student design process, which may have relationships with the design efficacy of the teams when using the study’s parametric modeling tool. Future research can further investigate the effect of mutually approachable working environments on design team performance.
Development of an IRMO-BPNN Based Single Pile Ultimate Axial Bearing Capacity Prediction Model
Authors: Jin Liangxing , Ji Yujie
Published: May 2023

The ultimate axial bearing capacity (UABC) of a single pile is an important parameter in pile design. BP neural network (BPNN) has a strong nonlinear mapping ability and can effectively predict the UABC of a single pile. However, frequent immersion in unstable search results with local vibration leads BPNN to a less usable solution. The weights and biases of the BPNN model are optimized using the improved radial movement optimization (IRMO) algorithm in this study, and a new method named the IRMO-BP neural network (IRMO-BPNN) is proposed to predict the UABC of a single pile. The IRMO-BPNN model was developed from a database of 196 static load test (SLT) samples, and model hyper-parameter analysis was carried out to determine the optimal number of hidden nodes, population size, and the number of iterations. The prediction accuracy and stability of the IRMO-BPNN model are verified by comparing it with the GA-based ANN model, ANFIS-GMDH-PSO model, and RBFANN model. The results show that the IRMO-BPNN model can accurately predict the UABC of a single pile and improves the situation that the BPNN model is easy to fall into local optimal values and its search results are unstable. The IRMO-BPNN model has significant advantages over other models.
Survival in Kidney and Bladder Cancers in Four Nordic Countries through a Half Century
Authors: Tichanek Filip , Försti Asta , Hemminki Akseli , Hemminki Otto , Hemminki Kari
Published: May 2023

Kidney and bladder cancers share etiology and relatively good recent survival, but long-term studies are rare. We analyzed survival for these cancers in Denmark, Finland, Norway (NO), and Sweden (SE) over a 50-year period (1971–2020). Relative 1- and 5-year survival data were obtained from the NORDCAN database, and we additionally calculated conditional 5/1-year survival. In 2016–2020, 5-year survivals for male kidney (79.0%) and bladder (81.6%) cancers were best in SE. For female kidney cancer, NO survival reached 80.0%, and for bladder cancer, SE survival reached 76.1%. The magnitude of 5-year survival improvements during the 50-year period in kidney cancer was over 40% units; for bladder cancer, the improvement was over 20% units. Survival in bladder cancer was worse for women than for men, particularly in year 1. In both cancers, deaths in the first year were approximately as many as in the subsequent 4 years. We could document an impressive development for kidney cancer with tripled male and doubled female 5-year survival in 50 years. Additionally, for bladder cancer, a steady improvement was recorded. The current challenges are to curb early mortality and target treatment to reduce long-term mortality.
Long-Term Clinical Results of MR-Guided Stereotactic Body Radiotherapy of Liver Metastases
Authors: Weykamp Fabian , Hoegen Philipp , Regnery Sebastian , Katsigiannopulos Efthimios , Renkamp C. Katharina , Lang Kristin , König Laila , Sandrini Elisabetta , Meixner Eva , Rippke Carolin , Buchele Carolin , Liermann Jakob , Debus Jürgen , Klüter Sebastian , Hörner-Rieber Juliane
Published: May 2023

(1) Background: Magnetic-resonance (MR)-guided stereotactic body radiotherapy (SBRT) allows for ablative, non-invasive treatment of liver metastases. However, long-term clinical outcome data are missing. (2) Methods: Patients received MR-guided SBRT with a MRIdian Linac between January 2019 and October 2021 and were part of an ongoing prospective observational registry. Local hepatic control (LHC), distant hepatic control (DHC), progression free survival (PFS) and overall survival (OS) were estimated with the Kaplan–Meier method. Toxicity was documented according to CTCAE (v.5.0). (3) Results: Forty patients were treated for a total of 54 liver metastases (56% with online plan adaptation). Median prescribed dose was 50 Gy in five fractions equal to a biologically effective dose (BED) (alpha/beta = 10 Gy) of 100 Gy. At 1 and 2 years, LHC was 98% and 75%, DHC was 34% and 15%, PFS was 21% and 5% and OS was 83% and 57%. Two-year LHC was higher in case of BED > 100 Gy (100% vs. 57%; log-rank p = 0.04). Acute grade 1 and 2 toxicity (mostly nausea) occurred in 26% and 7% of the patients, with no grade ≥ 3 event. (4) Conclusions: To our knowledge, this is the largest cohort of MR-guided liver SBRT. Long-term local control was promising and underscores the aim of achieving >100 Gy BED. Nonetheless, distant tumor control remains challenging.
Double-Glow Plasma Surface Alloying of BTi-62421S Alloys: Regulation of Microstructure Properties
Authors: Nie Yangjunfeng , Zhang Zhimin , Cheng Mei , Yan Zhaoming , Dong Beibei
Published: May 2023

In order to meet the design requirements of lightweight artillery and adopt the method of double-glow plasma nitriding to solve the problem of low hardness and poor abrasion resistance of Ti alloy, the BTi-62421S high-performance titanium (Ti) alloy was selected as the experimental material to replace gun steel. To study the effect of different nitrogen (N) concentrations on the heat resistance scouring performance of BTi-62421S high-performance Ti alloy and investigate the influence of alloying elements on the heat resistance scouring performance under the same parameters compared with the commonly used TC4 Ti alloy, argon was used as the protective gas by continuously increasing the N concentration (Ar/N2 = 1:1, 1:2, 1:3). It was found that the honeycomb structure on the surface of the sample and the thickness of the coating increased continuously, reaching a thickness of 15 μm, while the depth of the nitride particles extending from the coating to the substrate also increased, reaching a maximum depth of 26 μm. The orientation of TiN changed from 37° to 62°. The hardness of the coating showed a negative correlation with the coefficient of frictional abrasion, which significantly improved the heat-resistant scouring performance of BTi-62421S high-performance Ti alloy.
Enhancing ORR Catalytic Activity and Electrochemical Investigation of La1−2xBaxBixFeO3 Cathode for Low-Temperature Solid Oxide Fuel Cell
Authors: Shaheen Nusrat , Chen Zheng , Nong Yumei , Su Tao , Yousaf Muhammad , Lu Yuzheng , Li Ling
Published: May 2023

Perovskite cathodes have emerged as a promising alternative to traditional cathode materials in low-temperature solid oxide fuel cells (LT-SOFCs) due to their exceptional catalytic properties and high oxygen reduction reaction (ORR) activity. Their fast catalytic activity and chemical stability have drawn significant attention to lowering the operating temperature of SOFCs. In this study, Ba2+ and Bi3+ are doped into LaFeO3. The aim is to investigate the catalytic activity and electrochemical performance of LT-SOFCs. The presented cathode material is characterized in terms of phase structure, surface morphology, and interface studies before being applied as a cathode in SOFCs to measure electrochemical performance. The XPS study revealed that La1−2xBaxBixFeO3 (x = 0.1) exhibits enriched surface oxygen vacancies compared to La1−2xBaxBixFeO3 (x = 0.2). La1−2xBaxBixFeO3 with (x = 0.1 and 0.2) delivers a peak power density of 665 and 545 mW cm−2 at 550 °C, respectively. Moreover, impedance spectra confirmed that La1−2xBaxBixFeO3 with x = 0.1 exhibits lower electrode polarization resistance (0.33 Ω cm2) compared to La1−2xBaxBixFeO3 with x = 0.2 (0.57 Ω cm2) at 550 °C. Our findings thus confirm that LBBF cathode-based SOFCs can be considered a potential cathode to operate fuel cells at low temperatures, and it will open up another horizon in the subject of research.
Minimum-Lap-Time Planning of Multibody Vehicle Models via the Articulated-Body Algorithm
Authors: Domenighini Marcello , Bartali Lorenzo , Grabovic Eugeniu , Gabiccini Marco
Published: May 2023

Minimum lap-time planning (MLTP) is a well-established problem in the race car industry to provide guidelines for drivers and optimize the vehicle’s setup. In this paper, we tackle the 3D nature of the problem in its full extension, making no simplifying assumptions on the mechanics of the system. We propose a multibody vehicle model, described by rigorous dynamical equations. To effectively handle the resulting complexity, we devised an efficient direct dynamics computational method based on Featherstone’s articulated-body algorithm (ABA). To solve the MLTP, we employed a direct-collocation technique, discretizing the problem so that all information of the 3D track is pre-processed and directly embedded into the discrete problem. This discretization approach turns out to be perfectly compatible with our vehicle model, leading to a solution in accessible computational time frames. The high level of detail of the model makes the proposed approach most useful for in-depth vehicle dynamics analyses on complex tracks. To substantiate the analysis, we provide a comparison with the results obtained by a double-track model on the Nürburgring Nordschleife circuit. Consistently with the average trend defined by the double track, the proposed model features a more dynamically rich behavior, realistically capturing the higher-order effects elicited by the sharp corners and the highly variable slope of the track.
A Survey of COVID-19 Diagnosis Using Routine Blood Tests with the Aid of Artificial Intelligence Techniques
Authors: Abbasi Habashi Soheila , Koyuncu Murat , Alizadehsani Roohallah
Published: May 2023

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), causing a disease called COVID-19, is a class of acute respiratory syndrome that has considerably affected the global economy and healthcare system. This virus is diagnosed using a traditional technique known as the Reverse Transcription Polymerase Chain Reaction (RT-PCR) test. However, RT-PCR customarily outputs a lot of false-negative and incorrect results. Current works indicate that COVID-19 can also be diagnosed using imaging resolutions, including CT scans, X-rays, and blood tests. Nevertheless, X-rays and CT scans cannot always be used for patient screening because of high costs, radiation doses, and an insufficient number of devices. Therefore, there is a requirement for a less expensive and faster diagnostic model to recognize the positive and negative cases of COVID-19. Blood tests are easily performed and cost less than RT-PCR and imaging tests. Since biochemical parameters in routine blood tests vary during the COVID-19 infection, they may supply physicians with exact information about the diagnosis of COVID-19. This study reviewed some newly emerging artificial intelligence (AI)-based methods to diagnose COVID-19 using routine blood tests. We gathered information about research resources and inspected 92 articles that were carefully chosen from a variety of publishers, such as IEEE, Springer, Elsevier, and MDPI. Then, these 92 studies are classified into two tables which contain articles that use machine Learning and deep Learning models to diagnose COVID-19 while using routine blood test datasets. In these studies, for diagnosing COVID-19, Random Forest and logistic regression are the most widely used machine learning methods and the most widely used performance metrics are accuracy, sensitivity, specificity, and AUC. Finally, we conclude by discussing and analyzing these studies which use machine learning and deep learning models and routine blood test datasets for COVID-19 detection. This survey can be the starting point for a novice-/beginner-level researcher to perform on COVID-19 classification.
Advanced Air Mobility Operation and Infrastructure for Sustainable Connected eVTOL Vehicle
Authors: Al-Rubaye Saba , Tsourdos Antonios , Namuduri Kamesh
Published: May 2023

Advanced air mobility (AAM) is an emerging sector in aviation aiming to offer secure, efficient, and eco-friendly transportation utilizing electric vertical takeoff and landing (eVTOL) aircraft. These vehicles are designed for short-haul flights, transporting passengers and cargo between urban centers, suburbs, and remote areas. As the number of flights is expected to rise significantly in congested metropolitan areas, there is a need for a digital ecosystem to support the AAM platform. This ecosystem requires seamless integration of air traffic management systems, ground control systems, and communication networks, enabling effective communication between AAM vehicles and ground systems to ensure safe and efficient operations. Consequently, the aviation industry is seeking to develop a new aerospace framework that promotes shared aerospace practices, ensuring the safety, sustainability, and efficiency of air traffic operations. However, the lack of adequate wireless coverage in congested cities and disconnected rural communities poses challenges for large-scale AAM deployments. In the immediate recovery phase, incorporating AAM with new air-to-ground connectivity presents difficulties such as overwhelming the terrestrial network with data requests, maintaining link reliability, and managing handover occurrences. Furthermore, managing eVTOL traffic in urban areas with congested airspace necessitates high levels of connectivity to support air routing information for eVTOL vehicles. This paper introduces a novel concept addressing future flight challenges and proposes a framework for integrating operations, infrastructure, connectivity, and ecosystems in future air mobility. Specifically, it includes a performance analysis to illustrate the impact of extensive AAM vehicle mobility on ground base station network infrastructure in urban environments. This work aims to pave the way for future air mobility by introducing a new vision for backbone infrastructure that supports safe and sustainable aviation through advanced communication technology.
A Variable Structure Multiple-Model Estimation Algorithm Aided by Center Scaling
Authors: Wang Qiang , Li Guowei , Jin Weitong , Zhang Shurui , Sheng Weixing
Published: May 2023

The accuracy for target tracking using a conventional interacting multiple-model algorithm (IMM) is limited. In this paper, a new variable structure of interacting multiple-model (VSIMM) algorithm aided by center scaling (VSIMM-CS) is proposed to solve this problem. The novel VSIMM-CS has two main steps. Firstly, we estimate the approximate location of the true model. This is aided by the expected-mode augmentation algorithm (EMA), and a new method—namely, the expected model optimization method—is proposed to further enhance the accuracy of EMA. Secondly, we change the original model set to ensure the current true model as the symmetry center of the current model set, and the model set is scaled down by a certain percentage. Considering the symmetry and linearity of the system, the errors produced by symmetrical models can be well offset. Furthermore, narrowing the distance between the true model and the default model is another effective method to reduce the error. The second step is based on two theories: symmetric model set optimization method and proportional reduction optimization method. All proposed theories aim to minimize errors as much as possible, and simulation results highlight the correctness and effectiveness of the proposed methods.