bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Research of the Structure Condition Using Geodetic Methods and Crackmeter
Authors: Sztubecki Jacek , Topoliński Szymon , Mrówczyńska Maria , Bağrıaçık Baki , Beycioğlu Ahmet
Published: July 2022

The article presents an approach to monitoring the structure’s condition with two measurement methods: the SHM-X crackmeter and the classic geodetic method of determining displacements, supplemented with additional information on the condition of the external environment obtained from thermal images. The study aimed to propose an approach combining geodetic and non-geodetic methods of assessing the condition of a structure and its effectiveness in practical application. The research facility is a public utility building of the Bydgoszcz University of Technology with a reinforced concrete structure. Objects of this type require periodic tests of their constancy. Interpreting the test results and identifying possible dangerous states that may indicate the risk of a construction failure is extremely important. The results presented in the article are an extension of the previous ones, in which several factors that could have a destructive effect on the structure were excluded. Observation of the object showed that only the reinforced construction plate is deformed. The only factor influencing the change in structure geometry is thermal changes. As part of the tests in places where cracks were noticed, the SHM-X crackmeter was used to measure the cracks’ opening. In the geodetic research, measurements of the measurement and control network displacement were carried out, in which the TDRA6000 laser station measurement technology was used. The control points were also placed in places where the width of the cracks was directly observed. The proposed approach, with the applied calculation scheme and supplementing the information with the temperature measurement with thermal images, showed the submillimeter accuracy of the determined 3D displacements of the controlled points. Additionally, the parallel application of these methods gives a complete picture of changes in the structure elements, in which signs of destruction appear under the influence of stress.
Quantitative Characterization of Micro-Scale Pore-Throat Heterogeneity in Tight Sandstone Reservoir
Authors: Dong Fengjuan , Sun Zeyong , Gao Zhanwu , Lu Xuefei , Chen Yue , Huang Hai , Ren Dazhong
Published: July 2022

Nanoscale pore-throat systems are widely developed in the pore-throat of tight reservoirs. The pore-throat structures of different microscales are complex and diverse with obvious microscale effects. Taking the Chang 63 tight sandstone reservoir of the Huaqing area in Ordos basin as an example, under the guidance of information entropy theory, the quantitative characterization model of pore-throat micro-scale heterogeneity in a tight oil reservoir is established based on casting thin sections, physical properties analysis, constant velocity mercury injection, and NMR technology. Moreover, the correlation between pore-throat heterogeneity and porosity, permeability and movable fluid saturation is analyzed. The results show that there are obvious differences in pore-throat heterogeneity between different reservoirs, and the throat uniformity of macro pore-fine-throat reservoir, macro pore–micro throat reservoir, and macro pore–micro throat reservoir becomes worse, successively. There is a negative correlation between porosity uniformity and porosity, permeability and movable fluid saturation. However, there is a positive correlation between throat uniformity and combined pore throat uniformity and porosity, permeability and movable fluid saturation. Therefore, the uniformity of the throat controls the seepage capacity and fluid mobility in the pore system of the Chang 63 tight sandstone reservoir in the study area. This has important theoretical and practical significance to enhance oil recovery and promote the efficient development of a tight oil and gas reservoir.
Automatic False Alarm Detection Based on XAI and Reliability Analysis
Authors: Lee Eungyu , Lee Yongsoo , Lee Teajin
Published: July 2022

Many studies attempt to apply artificial intelligence (AI) to cyber security to effectively cope with the increasing number of cyber threats. However, there is a black box problem such that it is difficult to understand the basis for AI prediction. False alarms for malware or cyberattacks can cause serious side effects. Due to this limitation, all AI predictions must be confirmed by an expert, which is a considerable obstacle to AI expansion. Compared to the increasing number of cyberattack alerts, the number of alerts that can be analyzed by experts is limited. This paper provides explainability through an interpretation of AI prediction results and a reliability analysis of AI predictions based on explainable artificial intelligence (XAI). In addition, we propose a method for screening high-quality data that can efficiently detect false predictions based on reliability indicators. Through this, even a small security team can quickly respond to false predictions. To validate the proposed method, experiments were conducted using the IDS dataset and the malware dataset. AI errors were detected better than they could be by the existing AI models, with about 262% in the IDS dataset and 127% in the malware dataset from the top 10% of analysis targets. Therefore, the ability to respond to cyberattacks can be improved using the proposed method.
Tracking Heme-Protein Interactions in Healthy and Pathological Human Serum in Native Conditions by Miniaturized FFF-Multidetection
Authors: Marassi Valentina , Giordani Stefano , Reschiglian Pierluigi , Roda Barbara , Zattoni Andrea
Published: July 2022

The interaction of heme with blood serum proteins plays an important role in many physiological and pathological processes involving enzyme activity, gene expression and cell proliferation. The mechanisms underlying these interactions are; however, not yet fully understood. New analytical methods able to investigate protein-heme binding in native, biologically representative conditions are thus required. In this work, we present a method based on miniaturized, hollow-fiber flow field-flow fractionation with multiple spectrophotometric and light-scattering detection for size separation of high-abundance serum proteins and selective detection of heme-bound subpopulations. Heme is found to mainly interact with serum albumin, whereas a low amount also binds to other proteins such as IgM. The ability to bind heme in physiological conditions is also investigated for individual serum proteins. IgG is found unable to bind heme at clinically relevant concentrations. The proposed method allows separation, quantitation, and mass/size characterization of serum high-abundance proteins, providing information of heme-protein complex stability and preferred heme-clearing pathways. The same approach could be in perspective extended to the investigation of specific heme-antibody binding, and to further studies involving other molecules of pharmaceutical/clinical interest.
The Restored Premolars Biomechanical Behavior: FEM and Experimental Moiré Analyses
Authors: Valin Rivera Jose Luis , Gonçalves Edison , Vinicius Soares Paulo , Milito Giovana , Ricardo Perez Jorge Octavio , Palacios Roque Guillermo Francisco , Valin Fernández Meylí , Figueredo Losada Henry , Araújo Pereira Fabrícia , Garcia del Pino Gilberto , Rodriguez Soto Alexander
Published: July 2022

This study applied the finite element method (FEM) and the moiré strip projection method to evaluate the biomechanical behavior of healthy and endodontic-treated premolar teeth. The finite element method and the moiré strip projection method were applied to evaluate the influence of restored materials in association with cervical lesions and were considered as strain estimates for a tooth sample with 21 units, under loads of 25, 50, 75, and 100 N, frontal and oblique applied. The focused cases were: tooth H healthy; tooth A-MOD amalgam; tooth AL-MOD amalgam + lesion; tooth ALR-MOD amalgam + injury restored; tooth R-MOD resin; tooth RL-MOD resin + lesion; tooth RLR-MOD resin + injury restored. The results obtained by FEM simulation can be considered perfectly validated by the results presented by the experimental moiré projection analysis, demonstrating that the FEM numerical analysis can be used to evaluate the biomechanical behavior of healthy and endodontically treated teeth. Developing an alternative protocol to generate FEM three-dimensional models will lead to a ready and inexpensive tool since there is no need for costly equipment for tooth extraction prognosis.
Test Suite Prioritization Based on Optimization Approach Using Reinforcement Learning
Authors: Waqar Muhammad , Imran  , Zaman Muhammad Atif , Muzammal Muhammad , Kim Jungsuk
Published: July 2022

Regression testing ensures that modified software code changes have not adversely affected existing code modules. The test suite size increases with modification to the software based on the end-user requirements. Regression testing executes the complete test suite after updates in the software. Re-execution of new test cases along with existing test cases is costly. The scientific community has proposed test suite prioritization techniques for selecting and minimizing the test suite to minimize the cost of regression testing. The test suite prioritization goal is to maximize fault detection with minimum test cases. Test suite minimization reduces the test suite size by deleting less critical test cases. In this study, we present a four-fold methodology of test suite prioritization based on reinforcement learning. First, the testers’ and users’ log datasets are prepared using the proposed interaction recording systems for the android application. Second, the proposed reinforcement learning model is used to predict the highest future reward sequence list from the data collected in the first step. Third, the proposed prioritization algorithm signifies the prioritized test suite. Lastly, the fault seeding approach is used to validate the results from software engineering experts. The proposed reinforcement learning-based test suite optimization model is evaluated through five case study applications. The performance evaluation results show that the proposed mechanism performs better than baseline approaches based on random and t-SANT approaches, proving its importance for regression testing.
A Nonlinear Energy Sink Design to Attenuate the Torsional Oscillations of Lightly Loaded Gear Pairs
Authors: Friskney Brett , Alevras Panagiotis , Londhe Sourabh , Theodossiades Stephanos , McFarland Donald Michael
Published: July 2022

Nonlinear energy sinks (NES) have recently attracted significant interest for the suppression of unwanted vibrations in a variety of mechanical systems. The key advantage in employing this (vibration absorber) approach is the broadband nature of the interactions with a primary system for which vibration energy dissipation is required. Thus, the effectiveness of the NES is decoupled from the need of tuning to specific frequencies. Nevertheless, NES for rotational fluctuations of powertrains have received limited attention in the literature. In this work, a design for a rotational NES to mitigate speed fluctuations in gear trains is presented and tested experimentally. The development of the proposed system is underpinned by previous optimisation studies conducted by the authors, where a disk was utilised as an inerter NES. A set of beams couple the inerter with the wheel gear of a spur gear pair with a nonlinear restoring torque, which is designed to approach the desired essential nonlinearity within realistic practical tolerances. Static and dynamic identification is conducted to confirm the desired characteristics. Despite uncertainties in the prototype testing, the approach is found to reduce the speed fluctuations on the gear pair output shaft, with appropriate predictability established for the model and the design procedure.
Design and Optimization of Cluster-Based DSRC and C-V2X Hybrid Routing
Authors: Zhang Yi , Zhang Jixian
Published: July 2022

With the continuous development of connected and automated vehicles (CAVs) and Internet of Vehicle (IoV) technologies, various application scenarios have put forward higher requirements for vehicular communications. On the one hand, applications related to vehicle driving safety require lower latency and higher throughput. On the other hand, users who use cellular vehicle-to-everything (C-V2X) to transfer data will have to face high communication fees due to the increasing amount of data. Therefore, from the perspective of balancing quality of service (QoS) and user communication costs, this paper integrates dedicated short-range communication (DSRC) and C-V2X, two vehicular communication technologies with their own advantages, into a framework called cluster-based traffic differentiated hybrid routing (CTDHR), to provide services for in-vehicle communication. A vehicle clustering method based on hierarchical clustering is proposed to solve problems (e.g., the communication linking being difficult to maintain and the frequent cell handover due to high-speed movement of vehicles). The CTDHR framework is modeled on the resulting clusters and an objective equation was established. Finally, since the obtained objective equation is a nonlinear integer programming problem, we propose a heuristic algorithm to solve this optimization problem. In the simulation experiments, CTDHR shows better communication performance than the existing DSRC and C-V2X hybrid models. The experimental results show that CTDHR can reduce the communication costs of users while satisfying QoS.
Revisiting the Decomposition Process of Tetrahydrate Co(II) Acetate: A Sample’s Journey through Temperature
Authors: Gutiérrez-Martín Daniel , Varela Aurea , González-Calbet José M. , Matesanz Emilio , Parras Marina
Published: July 2022

Cobalt oxides, CoO and Co3O4, were obtained from Co (II) acetate tetrahydrate. The thermal decomposition pathway of the starting product was followed by combining thermogravimetric analysis and in situ X-ray thermodiffraction. Under a nitrogen atmosphere, cobalt monoxide with Zn-blende and rocksalt polymorphs could be obtained almost as single phases at 330 and 400 °C, respectively. In addition to these oxides, a Co (II) oxyacetate, Co3O(CH3COO)4, was stabilized as an intermediate phase. Under an air atmosphere, Co3O4 (spinel structure type) was obtained as the only final product. The involved phases in this thermal decomposition process were characterized with scanning and transmission electron microscopy (SEM and TEM, respectively).
The Impact of Scale-Aware Parameterization on the Next-Generation Global Prediction System in Taiwan for Front Predictions
Authors: Lin Chang-Hung , Yang Ming-Jen , Hsiao Ling-Feng , Chen Jen-Her
Published: July 2022

In order to improve the precipitation forecast of the next-generation Global Prediction System with the Finite-Volume Cubed-Sphere Dynamical Core in Taiwan’s Central Weather Bureau, this study modified the convective processes in the New Simplified Arakawa-Schubert scheme based on the methodology of scale-aware parameterization developed in Kwon and Hong (2017) and investigated its impacts on a front event, which propagated across Taiwan and produced heavy rainfall in late May of 2020. Results show that the modified scale-aware parameterization has significantly improved the intensity and the spatial distribution of frontal precipitation forecasts due to the proper definition of convective updraft fraction. However, the synoptic-scale features perform a larger warm bias with the modified scale-aware parameterization. Therefore, further modification of the scale-aware capability of convective cloud water detrainment is proposed to reduce the heating from microphysical processes and result in a better overall performance for the medium-range weather forecasts.
A Spherical Fuzzy Multi-Criteria Decision-Making Model for Industry 4.0 Performance Measurement
Authors: Ozdemir Yavuz Selim
Published: July 2022

In recent years, efficient processes have become increasingly important because of high-level competition in the production industry. The concept of Industry 4.0 is a relatively new and effective method for managing production processes. Because the Industry 4.0 implementation process includes connections between objects, humans, and systems, it is quite difficult to evaluate and measure the performance. At this stage, performance criteria can be applied. However, linguistic evaluation of criteria makes the problem too complicated to solve. The purpose of this paper is to present a novel fuzzy performance measurement model for Industry 4.0 in small and medium-sized manufacturing firms. A hybrid spherical fuzzy analytic hierarchy process (SF-AHP)—weighted score methodology (WSM) is proposed for the performance measurement and scoring process. In the application part of this paper, the propounded methodology was applied to five companies. The results of this study can be used as a reference for experts in the performance measurement of the Industry 4.0 process.
Microcarrier-Based Culture of Human Pluripotent Stem-Cell-Derived Retinal Pigmented Epithelium
Authors: Faynus Mohamed A. , Bailey Jeffrey K. , Pennington Britney O. , Katsura Mika , Proctor Duncan A. , Yeh Ashley K. , Menon Sneha , Choi Dylan G. , Lebkowski Jane S. , Johnson Lincoln V. , Clegg Dennis O.
Published: July 2022

Dry age-related macular degeneration (AMD) is estimated to impact nearly 300 million individuals globally by 2040. While no treatment options are currently available, multiple clinical trials investigating retinal pigmented epithelial cells derived from human pluripotent stem cells (hPSC-RPE) as a cellular replacement therapeutic are currently underway. It has been estimated that a production capacity of >109 RPE cells annually would be required to treat the afflicted population, but current manufacturing protocols are limited, being labor-intensive and time-consuming. Microcarrier technology has enabled high-density propagation of many adherent mammalian cell types via monolayer culture on surfaces of uM-diameter matrix spheres; however, few studies have explored microcarrier-based culture of RPE cells. Here, we provide an approach to the growth, maturation, and differentiation of hPSC-RPE cells on Cytodex 1 (C1) and Cytodex 3 (C3) microcarriers. We demonstrate that hPSC-RPE cells adhere to microcarriers coated with Matrigel, vitronectin or collagen, and mature in vitro to exhibit characteristic epithelial cell morphology and pigmentation. Microcarrier-grown hPSC-RPE cells (mcRPE) are viable; metabolically active; express RPE signature genes including BEST1, RPE65, TYRP1, and PMEL17; secrete the trophic factors PEDF and VEGF; and demonstrate phagocytosis of photoreceptor outer segments. Furthermore, we show that undifferentiated hESCs also adhere to Matrigel-coated microcarriers and are amenable to directed RPE differentiation. The capacity to support hPSC-RPE cell cultures using microcarriers enables efficient large-scale production of therapeutic RPE cells sufficient to meet the treatment demands of a large AMD patient population.
Phylogenomics Resolves the Phylogeny of Theaceae by Using Low-Copy and Multi-Copy Nuclear Gene Makers and Uncovers a Fast Radiation Event Contributing to Tea Plants Diversity
Authors: Cheng Lin , Li Mengge , Han Qunwei , Qiao Zhen , Hao Yanlin , Balbuena Tiago Santana , Zhao Yiyong
Published: July 2022

Tea is one of the three most popular nonalcoholic beverages globally and has extremely high economic and cultural value. Currently, the classification, taxonomy, and evolutionary history of the tea family are largely elusive, including phylogeny, divergence, speciation, and diversity. For understanding the evolutionary history and dynamics of species diversity in Theaceae, a robust phylogenetic framework based on 1785 low-copy and 79,103 multi-copy nuclear genes from 91 tea plant genomes and transcriptome datasets had been reconstructed. Our results maximumly supported that the tribes Stewartieae and Gordonieae are successive sister groups to the tribe Theeae from both coalescent and super matrix ML tree analyses. Moreover, in the most evolved tribe, Theeae, the monophyletic genera Pyrenaria, Apterosperma, and Polyspora are the successive sister groups of Camellia. We also yield a well-resolved relationship of Camellia, which contains the vast majority of Theaceae species richness. Molecular dating suggests that Theaceae originated in the late L-Cretaceous, with subsequent early radiation under the Early Eocene Climatic Optimal (EECO) for the three tribes. A diversification rate shift was detected in the common ancestors of Camellia with subsequent acceleration in speciation rate under the climate optimum in the early Miocene. These results provide a phylogenetic framework and new insights into factors that likely have contributed to the survival of Theaceae, especially a successful radiation event of genus Camellia members to subtropic/tropic regions. These novel findings will facilitate the efficient conservation and utilization of germplasm resources for breeding cultivated tea and oil-tea. Collectively, these results provide a foundation for further morphological and functional evolutionary analyses across Theaceae.
Regulating Phase Transition in Neurodegenerative Diseases by Nuclear Import Receptors
Authors: Girdhar Amandeep , Guo Lin
Published: July 2022

RNA-binding proteins (RBPs) with a low-complexity prion-like domain (PLD) can undergo aberrant phase transitions and have been implicated in neurodegenerative diseases such as ALS and FTD. Several nuclear RBPs mislocalize to cytoplasmic inclusions in disease conditions. Impairment in nucleocytoplasmic transport is another major event observed in ageing and in neurodegenerative disorders. Nuclear import receptors (NIRs) regulate the nucleocytoplasmic transport of different RBPs bearing a nuclear localization signal by restoring their nuclear localization. NIRs can also specifically dissolve or prevent the aggregation and liquid–liquid phase separation of wild-type or disease-linked mutant RBPs, due to their chaperoning activity. This review focuses on the LLPS of intrinsically disordered proteins and the role of NIRs in regulating LLPS in neurodegeneration. This review also discusses the implication of NIRs as therapeutic agents in neurogenerative diseases.
High Energy Channeling and Malleable Transition States: Molecular Dynamics Simulations and Free Energy Landscapes for the Thermal Unfolding of Protein U1A and 13 Mutants
Authors: Dang Na Le , Baranger Anne M. , Beveridge David L.
Published: July 2022

The spliceosome protein U1A is a prototype case of the RNA recognition motif (RRM) ubiquitous in biological systems. The in vitro kinetics of the chemical denaturation of U1A indicate that the unfolding of U1A is a two-state process but takes place via high energy channeling and a malleable transition state, an interesting variation of typical two-state behavior. Molecular dynamics (MD) simulations have been applied extensively to the study of two-state unfolding and folding of proteins and provide an opportunity to obtain a theoretical account of the experimental results and a molecular model for the transition state ensemble. We describe herein all-atom MD studies including explicit solvent of up to 100 ns on the thermal unfolding (UF) of U1A and 13 mutants. Multiple MD UF trajectories are carried out to ensure accuracy and reproducibility. A vector representation of the MD unfolding process in RMSD space is obtained and used to calculate a free energy landscape for U1A unfolding. A corresponding MD simulation and free energy landscape for the protein CI2, well known to follow a simple two state folding/unfolding model, is provided as a control. The results indicate that the unfolding pathway on the MD calculated free energy landscape of U1A shows a markedly extended transition state compared with that of CI2. The MD results support the interpretation of the observed chevron plots for U1A in terms of a high energy, channel-like transition state. Analysis of the MDUF structures shows that the transition state ensemble involves microstates with most of the RRM secondary structure intact but expanded by ~14% with respect to the radius of gyration. Comparison with results on a prototype system indicates that the transition state involves an ensemble of molten globule structures and extends over the region of ~1–35 ns in the trajectories. Additional MDUF simulations were carried out for 13 U1A mutants, and the calculated φ-values show close accord with observed results and serve to validate our methodology.
Acetylcholinesterase Biosensor Based on Functionalized Renewable Carbon Platform for Detection of Carbaryl in Food
Authors: Nunes Erik W. , Silva Martin K. L. , Rascón Jesús , Leiva-Tafur Damaris , Lapa Rainer M. L. , Cesarino Ivana
Published: July 2022

Enzymatic electrochemical biosensors play an important role in the agri-food sector due to the need to develop sustainable, low-cost, and easy-to-use analytical devices. Such biosensors can be used to monitor pathogens, endocrine disruptors, and pesticides, such as carbaryl, widely used in many crops. The use of renewable carbon (RC) sources, provided from biomass pyrolysis has been often applied in the fabrication of such sensors. This material is a great candidate for biosensor fabrication due to the presence of surface functional groups, porosity, and moderate surface area. This work describes the functionalization of RC material through an acid treatment with a sulfonitric solution HNO3/H2SO4 (1:3) and the resulting material was characterized by scanning electron microscopy. The obtained RC functionalized (RCF) and the acetylcholinesterase enzyme (AChE) were applied in the construction of the electrochemical biosensor on glassy carbon (GC) electrode and used to detect carbaryl in apple samples. The GC/RCF/AChE biosensor was able to detect the carbaryl pesticide from 5.0 to 30.0 nmol L−1, displaying a LOD of 4.5 nmol L−1. The detection of carbaryl in apple samples presented recoveries between 102.5 to 118.6% through the standard addition method. The proposed biosensor is a promising renewable tool for food safety.
Investigating the Effects of Organonitrogen Types on Hydrodearomatization Reactions over Commercial NiMoS Catalyst
Authors: Venuti Björkman Jacob , Hruby Sarah L. , Pettersson Lars J. , Kantarelis Efthymios
Published: July 2022

The hydrogenation of polyaromatic compounds (PACs) present in mineral oils is of great importance when it comes to the desired product properties and the minimization of health hazards; however, the presence of organonitrogen inhibits the conversion of these compounds. In this study, the inhibition effects of different types of organonitrogen compounds (acridine (ACR) and carbazole (CBZ)-basic and nonbasic organonitrogen) on the hydrodearomatization (HDA) of phenanthrene over a sulfided commercial NiMo/Al2O3 catalyst were investigated in a microflow trickle-bed reactor at a temperature range of 280 to 320 °C and at a total pressure of 120 barg. Analysis of the experimental results shows that the hydrogenation of phenanthrene is significantly decreased in the presence of organonitrogen, with acridine showing stronger inhibiting effects. The extent of hydrodenitrogenation (HDN) is shown to correlate with the inhibition degree with a higher extent of HDN being achieved for carbazole than for acridine. Results from co-feeding different nitrogen types (acridine and carbazole) indicate that basic nitrogen is the dominating type of organonitrogen inhibitor. Recovery of catalyst activity in the absence of organonitrogen indicates fully reversible deactivation suggesting that inhibition relates to competitive adsorption and slower reaction rate of HDN compared to HDA.
Can NT-proBNP Levels Be an Early Biomarker of Reduced Left Ventricular Ejection Fraction in Preterm Infants?
Authors: Lin Ya-Lan , Hung Yi-Li , Shen Chung-Min , Chen Yung-Chuan , Hsieh Wu-Shiun
Published: July 2022

Background/Objective: N-terminal pro-B-type natriuretic peptide (NT-proBNP) is a cardiac natriuretic hormone that cardiomyocytes release in response to ventricular stretch. It helps with the diagnosis of heart failure in adults, but this application in preterm infants has rarely been reported. This study aimed to evaluate whether NT-proBNP could be used for the early detection of reduced cardiac ejection fraction in preterm infants and the optimal timing for NT-proBNP assessment. Design/Methods: This prospective, single-center, observational study enrolled all preterm infants with NT-proBNP measurements from October 2014 to February 2022. They underwent echocardiographic examinations within 48 h of the NT-proBNP measurements. Reduced left ventricular ejection fraction was defined as below 60%. Receiver operator characteristic (ROC) curves were generated to assess the optimal NT-proBNP cutoff point for the early prediction of reduced cardiac ejection fraction. Results: A total of 68 preterm infants were enrolled, with a total of 134 NT-proBNP measurements being available for analysis. Reduced left ventricular ejection fraction was present in seven infants (10.3%) due to various underlying diseases. The NT-proBNP cutoff level for detecting reduced left ventricular ejection fraction was 9248 pg/mL, with 71.4% sensitivity and 60.8% specificity; the area under the curve was 0.623 (95% CI: 0.487~0.760). The threshold for the optimal postnatal age for applying NT-proBNP to detect reduced left ventricular ejection fraction was >2 days of life (AUC: 0.682; 95% CI: 0.518~0.845), with 70% sensitivity and 67.1% specificity. Conclusions: Although the NT-proBNP levels declined dramatically after birth, a NT-proBNP serum level of 9248 pg/mL might be helpful for the early detection of reduced ejection fraction in preterm infants, and the optimal age for detection was after 2 days of life.
Lower-Limb Amputation in Children and Adolescents—A Rare Encounter with Unique and Special Challenges
Authors: Horsch Axel , Gleichauf Svenja , Lehner Burkhard , Ghandour Maher , Koch Julian , Alimusaj Merkur , Renkawitz Tobias , Putz Cornelia
Published: July 2022

Background/Aim: The pattern of lower-limb amputation, indications, complications, and revision in pediatric cases differs globally. Therefore, we conducted this study to describe the patterns of lower-limb amputation at our institution. Methods: During a set period between 2010 and 2020, adolescent patients undergoing lower-limb amputation within the orthopedic department of Heidelberg University Hospital were retrospectively collected and analyzed. The retrieved dataset included two parts: data on lower-limb amputations and data on subsequent complications and revision surgeries at the same time. Besides patients’ general information (age, gender), the dataset included data regarding amputation patterns (number, indications, and level of amputation, complications, and revision surgeries and their indications). Results: Twenty-two patients undergoing lower-limb amputation were examined, of which the majority were males (63.6%) with a mean age of 12 (5.1) years. Tumor was the most common indication for amputation (72.7%), and transfemoral amputation was the most frequent level (68.2%). Complications occurred in 10 patients, mostly due to stump impalement or bony overgrowth. Of all recorded patients requiring revision, nine were regarding bone and one case regarding soft tissue. Conclusions: Lower-limb amputation in adolescents is a rare encounter and it is commonly indicated due to bone tumors. The thigh is the most common level of amputation. Postoperative complications are frequent, mainly secondary to bony overgrowth, and often require revision surgery.
Fundamental Properties of Transition-Metals-Adsorbed Germanene: A DFT Study
Authors: Liu Hsin-Yi , Wu Jhao-Ying
Published: July 2022

The transition metal (TM)-absorbed germanene systems enriched by strong chemical bonding are investigated using first-principles calculations. Dedicated calculations include the geometry, preferable adsorption sites, atom-dominated band structure, spin–density distributions, spatial charge distribution, and the projected density of states (DOS). The strong multi-orbital chemical bonds between TMs and Ge atoms can create seriously buckled structures and a non-uniform chemical environment, which are responsible for the unusual electronic properties. Of the three chosen systems, the Fe–Ge and Co–Ge ones possess magnetic properties, while the Ni–Ge system exhibits non-magnetic behavior. The orbital-hybridization-induced characteristics are revealed in van Hove singularities of the DOS.
Effects of Static Icing on Flashover Characteristics of High-Speed Train Roof Insulators
Authors: Qi Zhibin , Zhang Ruiping , Ma Jianqiao , Wang Xiangfei , Ma Lei , Zhao Zongyu , Wu Youqiang
Published: July 2022

To study the icing flashover characteristics displayed by insulators on the roof of a high-speed train at a low-speed or static state, an environment with a low temperature and high humidity is established in the artificial climate chamber to carry out the icing flashover test of composite insulator under a static state. The results of the study indicate the presence of ice ridges bridging the sheath at the edge of the sheath when the ambient wind speed is less than 2m/s. The arc appears firstly at the end of the ice ridge, and it is likely that the arc at the adjacent tip converges in the air and then further extends to the edge of the next sheath. The arc melts the ice ridges at the end and enables it to stick to the tip of the ice ridge in the form of water droplets, and therefore the existence of droplets results in the distortion of the electric field near them. Moreover, the elongation of droplets and the bridging of ice edges accelerate the process of flashover. The research results can offer a reference to the structural optimization design of anti-icing insulators for high-speed trains in the future.
Multi-Controllers Placement Optimization in SDN by the Hybrid HSA-PSO Algorithm
Authors: Radam Neamah S. , Al-Janabi Sufyan T. Faraj , Jasim Khalid Sh.
Published: July 2022

Software-Defined Networking (SDN) is a developing architecture that provides scalability, flexibility, and efficient network management. However, optimal controller placement faces many problems, which affect the performance of the overall network. To resolve the Multi-controller SDN (MC-SDN) that is deployed in the SDN environment, we propose an approach that uses a hybrid metaheuristic algorithm that improves network performance. Initially, the proposed SDN network is constructed based on graph theory, which improves the connectivity and flexibility between switches and controllers. After that, the controller selection is performed by selecting an optimal controller from multiple controllers based on controller features using the firefly optimization algorithm (FA), which improves the network performance. Finally, multi-controller placement is performed to reduce the communication latency between the switch to controllers. Here, multiple controllers are placed by considering location and distance using a hybrid metaheuristic algorithm, which includes a harmonic search algorithm and particle swarm optimization algorithm (HSA-PSO), in which the PSO algorithm is proposed to automatically update the harmonic search parameters. The simulation of multi-controller placement is carried out by the CloudsimSDN network simulator, and the simulation results demonstrate the proposed advantages in terms of propagation latency, Round Trip Time (RTT), matrix of Time Session (TS), delay, reliability, and throughput.
The Role of PROX1 in Neoplasia: A Key Player Often Overlooked
Authors: Ntikoudi Evangelia , Pergaris Alexandros , Kykalos Stylianos , Politi Ekaterini , Theocharis Stamatios
Published: July 2022

The human PROX1 gene (Prospero homeobox gene 1) is a member of the homeobox transcription factor family. PROX1 plays a key role in the development of the lymphatic system and is primarily used as a lymphatic vessel marker. However, as the accumulating evidence indicates that PROX1 is also implicated in the tumorigenesis of various cancer types, the scientific community has attempted to elucidate its complicated function in neoplasia pathogenesis, as well as its utility in cancer diagnosis, prognosis, and therapy. PROX1 has been shown to participate in the complex molecular mechanisms affecting tumorigenesis and has been associated with a plethora of clinicopathological parameters, including tumor stage and patients’ overall survival. Depending on the specific organ affected, PROX1 has exhibited both tumor-promoting and tumor-suppressing properties, with its inhibition and reactivation representing possible novel therapeutic interventions, respectively. Moreover, researchers have reported PROX1 as a useful tool in the fields of diagnosis and prognosis assessment. The current study aims to summarize and present the existing data that render PROX1 a novel and useful diagnostic and prognostic biomarker, as well as a possible therapeutic target.
Design and Evaluation of Schemes for Replacing Multiple Member Vehicles in Vehicular Clouds
Authors: Choi Hyunseok , Nam Youngju , Shin Yongje , Jung Kwansoo , Lee Euisin
Published: July 2022

Vehicular clouds are considered an attractive approach to provide various services such as safety and entertainment applications by sharing resources between vehicles. Due to the free mobility of vehicles, vehicular clouds need to reconstruct by replacing leaving member vehicles with new member vehicles. When multiple member vehicles leave a vehicular cloud at different times, the design of an efficient member vehicle replacement scheme is a very challenging issue on determining the replacement timing. However, the research on the replacement of multiple member vehicles has little interest and is still in its infancy. Therefore, we propose three schemes to replace multiple member vehicles in vehicular clouds at three different replacement timings: MIN, MAX, and AVG. The MIN scheme replaces all of leaving member vehicles at the leaving time of the first leaving member vehicle, while the MAX scheme replaces all of leaving member vehicles at the leaving time of the last leaving member. The AVG scheme replaces all leaving member vehicles at the average time of their leaving times as a compromise between the Min and Max schemes. First, we determine the first leaving time, the last leaving time, and the average leaving time for each scheme by calculating the distance between a cloud requester vehicle and its member vehicles. Next, we choose replacement member vehicles to minimize the wasted resource at the replacement timing in each scheme. Last, we provide the process for releasing the resource of the leaving member vehicles and allocating the resource of the replacement member vehicles in each scheme. Through simulation results conducted in various environments, we compare and evaluate the performance of our three schemes in terms of the success ratio of the cloud maintenance and the amount of the wasted resources.
The Research on Harmonic Transfer Characteristics of Integrated Multi-Winding Inductive Filtering Converter Transformer and Its Filter System
Authors: Li Jianying , Xiao Yunchang , Yang Minsheng , Li Jianqi , Wan Jingying
Published: July 2022

A novel integrated multi-winding inductive filter converter and its filter system used in HVDC conversion station are proposed. Specifically, the schemes include two paralleled-connected delta filter windings with zero impedance, and the 11th and 13th tuned filtering branches are installed at the taps. On this basis, the 5th and 7th harmonic filters are eliminated and the 5th, 7th, 11th, and 13th harmonics of the valve-side are suppressed. Moreover, the cost of the filter is reduced, and the negative impact on the converter transformer body caused by the transfer of harmonic current is avoided, such as vibration, noise, and harmonic loss. In this paper, first, the mathematical models of integrated multi-winding inductive filter converter and its filter system are established. Accordingly, the current relationships between the primary winding side and two secondary winding sides are derived. Then, the transfer path of each characteristic harmonic current in the new system is analyzed and discussed. Moreover, a simulation model is established to study the operation characteristics of the system. Finally, through the designed experimental prototype, a new DC transferring system platform is constructed to testify the operation characteristics of an integrated multi-winding inductive filter converter and its filter system. The experimental results show that the total harmonic distortion rate of the grid-winding current can be reduced to 4.68% only by installing the 11th and 13th tuned filters, so the effect of active filtering is approximated realized by the passive filtering method.
WR-3.4 Overmoded Waveguide Module for the Packaging of a Linear Integrated-Circuit Array
Authors: Lee Juhee , Kim Yang Woo , Jeon Sanggeun , Kim Moonil
Published: July 2022

The performance of WR-3.4 overmoded waveguide modules containing a linear array of discrete terahertz integrated circuits is presented to verify a new power-combining technique. Custom-designed thru-line IC chips that include back-to-back broadband antenna transitions were fabricated with an area of 390 × 750 mm2 for waveguide packaging. Multiple array modules were assembled to verify the repeatability in performance. The array modules exhibited almost identical amounts of insertion losses compared with single-element modules, showing the best insertion loss of 2.6 dB over a 1 dB bandwidth of 95 GHz.
Multi-Objective Multi-Learner Robot Trajectory Prediction Method for IoT Mobile Robot Systems
Authors: Peng Fei , Zheng Li , Duan Zhu , Xia Yu
Published: July 2022

Robot trajectory prediction is an essential part of building digital twin systems and ensuring the high-performance navigation of IoT mobile robots. In the study, a novel two-stage multi-objective multi-learner model is proposed for robot trajectory prediction. Five machine learning models are adopted as base learners, including autoregressive moving average, multi-layer perceptron, Elman neural network, deep echo state network, and long short-term memory. A non-dominated sorting genetic algorithm III is applied to automatically combine these base learners, generating an accurate and robust ensemble model. The proposed model is tested on several actual robot trajectory datasets and evaluated by several metrics. Moreover, different existing optimization algorithms are also applied to compare with the proposed model. The results demonstrate that the proposed model can achieve satisfactory accuracy and robustness for different datasets. It is suitable for the accurate prediction of robot trajectory.
Ground-Dwelling Arachnids and Fire Disturbance: A Case Study in Northeastern Patagonia (Argentina)
Authors: Martínez Fernando Joaquín , Cheli Germán Horacio , Grismado Cristian José , Bisigato Alejandro Jorge
Published: July 2022

Fire is one of the main disturbances in northeastern Patagonia. Wildfires are becoming more frequent and severe, threatening the sustainability of local ecosystems. Arachnids respond markedly to environmental modifications and can regulate processes linked to lower trophic levels. Assessing changes in arachnid diversity is useful to understand the effect of fire on animal assemblages and ecosystem functionality. The aim of this study was to analyze the response of the ground-dwelling arachnid assemblage to fire disturbance. Eight sampling sites were selected: four burned and four unburned. Arachnids were sampled using pitfall traps. The taxonomic and functional structure of the assemblage was found to differ between burned and unburned areas. This change was related to major taxa turnover. On the other hand, the alpha diversity did not differ significantly according to fire disturbance. The abundance of specialist spiders decreased significantly in burned areas, possibly related to post-fire changes in the composition and structure of the plant community. In addition, significant species indicators of unburned and burned sites were found. The results of this study are useful for ecosystem management and the development of biodiversity conservation strategies in northeastern Patagonia, an area severely affected by fires.
Optimal H1-Norm Estimation of Nonconforming FEM for Time-Fractional Diffusion Equation on Anisotropic Meshes
Authors: Wei Yabing , Zhao Yanmin , Lü Shujuan , Wang Fenling , Fu Yayun
Published: July 2022

In this paper, based on the L2-1σ scheme and nonconforming EQ1rot finite element method (FEM), a numerical approximation is presented for a class of two-dimensional time-fractional diffusion equations involving variable coefficients. A novel and detailed analysis of the equations with an initial singularity is described on anisotropic meshes. The fully discrete scheme is shown to be unconditionally stable, and optimal second-order accuracy for convergence and superconvergence can be achieved in both time and space directions. Finally, the obtained numerical results are compared with the theoretical analysis, which verifies the accuracy of the proposed method.
Perspectives on “Earth Observation and GIScience for Agricultural Applications”
Authors: Lupia Flavio , Arsanjani Jamal Jokar , Fonte Cidália Costa , Pulighe Giuseppe
Published: July 2022

Current and future scenarios for global agricultural systems under a changing climate require innovative approaches, novel datasets, and methods for improving environmental resource management and better data-driven decision-making [...]
Predicting Pavement Condition Index Using Fuzzy Logic Technique
Authors: Ali Abdualmtalab , Heneash Usama , Hussein Amgad , Eskebi Mohamed
Published: July 2022

The fuzzy logic technique is one of the effective approaches for evaluating flexible and rigid pavement distress. The process of classifying pavement distress is usually performed by visual inspection of the pavement surface or using data collected by automated distress measurement equipment. Fuzzy mathematics provides a convenient tool for incorporating subjective analysis, uncertainty in pavement condition index, and maintenance-needs assessment, and can greatly improve consistency and reduce subjectivity in this process. This paper aims to develop a fuzzy logic-based system of pavement condition index and maintenance-needs evaluation for a pavement road network by utilizing pavement distress data from the U.S. and Canada. Considering rutting, fatigue cracking, block cracking, longitudinal cracking, transverse cracking, potholes, patching, bleeding, and raveling as input variables, the variables were fuzzified into fuzzy subsets. The fuzzy subsets of the variables were considered to have triangular membership functions. The relationships between nine pavement distress parameters and PCI were represented by a set of fuzzy rules. The fuzzy rules relating input variables to the output variable of sediment discharge were laid out in the IF–THEN format. The commonly used weighted average method was employed for the defuzzification procedure. The coefficient of determination (R2), root mean squared error (RMSE), and mean absolute error (MAE) were used as the performance indicator metrics to evaluate the performance of analytical models.
Osteochondral Lesions of Ankle and Knee. Will Future Treatments Really Be Represented by Custom-Made Metal Implants?
Authors: Mosca Massimiliano , Grassi Alberto , Caravelli Silvio
Published: July 2022

Knee and ankle osteochondral lesions are structural defects of the cartilaginous surface and underlying subchondral bone which still represent a daily challenge for the orthopedic surgeon [...]
Emergency Ultrasound: Is It Time for Artificial Intelligence?
Authors: Boccatonda Andrea
Published: July 2022

Ultrasound is a fundamental and indispensable diagnostic method in the field of emergency medicine [...]