bluuebunny/crossref_metadata_2025 huggingface dataset:
Parametric Analysis Using CFD to Study the Impact of Geometric and Numerical Modeling on the Performance of a Small Scale Horizontal Axis Wind Turbine
Authors: Siddiqui Muhammad Salman , Khalid Muhammad Hamza , Badar Abdul Waheed , Saeed Muhammed , Asim Taimoor
Published: January 2022

The reliance on Computational Fluid Dynamics (CFD) simulations has drastically increased over time to evaluate the aerodynamic performance of small-scale wind turbines. With the rapid variability in customer demand, industrial requirements, economic constraints, and time limitations associated with the design and development of small-scale wind turbines, the trade-off between computational resources and the simulation’s numerical accuracy may vary significantly. In the context of wind turbine design and analysis, high fidelity simulation under full geometric and numerical complexity is more accurate but pose significant demands from a computational standpoint. There is a need to understand and quantify performance deterioration of high fidelity simulations under reduced geometric or numerical approximation on a single small scale turbine model. In the present work, the flow past a small-scale Horizontal Axis Wind Turbine (HAWT) was simulated under various geometric and numerical configurations. The geometric complexity was varied based on stationary and rotating turbine conditions. In the stationary case, simple 2D airfoil, 2.5D blade, 3D blade sections are evaluated, while rotational effects are introduced for the configuration 3D blade, rotor only, and the full-scale wind turbine with and without the inclusion of a nacelle and tower. In terms of numerical complexity, the Single Reference Frame (SRF), Multiple Reference Frames (MRF), and the Sliding Meshing Interface (SMI) is analyzed over Tip Speed Ratios (TSR) of 3, 6, 10. The quantification of aerodynamic coefficients of the blade (Cl, Cd) and turbine (Cp, Ct) was conducted along with the discussion on wake patterns in comparison with experimental data.
Influence of Sweat on Joint and Sensor Reliability of E-Textiles
Authors: Hirman Martin , Navratil Jiri , Radouchova Michaela , Stulik Jiri , Soukup Radek
Published: January 2022

This article addresses reliability under the sweat of interconnection techniques for the mounting surface mounted device (SMD) components and fully printed humidity sensors onto conductive stretchable textile ribbons. Samples underwent testing for the effect of ageing by artificial sweat on their electrical resistance using both alkaline and acidic artificial sweat. The best results in terms of electrical resistance change were obtained for samples soldered to the conductive fibers interwoven in the ribbon. However, this method can damage the ribbon due to the high temperature during soldering and significantly reduce the mechanical properties and flexibility of the ribbon, which can lead to a limited service life of samples. On the other hand, adhesive bonding is a very interesting alternative, where the above-mentioned properties are preserved, but there is a significant effect of sweat ageing on electrical resistance. The results of fully printed graphene-based humidity sensors show that, for the intended use of these sensors (i.e., detection of changes in moisture on the human body), usage of the samples is possible, and the samples are sufficiently reliable in the case of sweat degradation. In addition, the response of the sensor to humidity is quite high: 98% at a relative humidity of 98%.
Artificial Intelligence Techniques for Power System Transient Stability Assessment
Authors: Sarajcev Petar , Kunac Antonijo , Petrovic Goran , Despalatovic Marin
Published: January 2022

The high penetration of renewable energy sources, coupled with decommissioning of conventional power plants, leads to the reduction of power system inertia. This has negative repercussions on the transient stability of power systems. The purpose of this paper is to review the state-of-the-art regarding the application of artificial intelligence to the power system transient stability assessment, with a focus on different machine, deep, and reinforcement learning techniques. The review covers data generation processes (from measurements and simulations), data processing pipelines (features engineering, splitting strategy, dimensionality reduction), model building and training (including ensembles and hyperparameter optimization techniques), deployment, and management (with monitoring for detecting bias and drift). The review focuses, in particular, on different deep learning models that show promising results on standard benchmark test cases. The final aim of the review is to point out the advantages and disadvantages of different approaches, present current challenges with existing models, and offer a view of the possible future research opportunities.
Partial Discharge Diagnostics: Data Cleaning and Feature Extraction
Authors: Soh Donny , Krishnan Sivaneasan Bala , Abraham Jacob , Xian Lai Kai , Jet Tseng King , Yongyi Jimmy Fu
Published: January 2022

Detection of partial discharge (PD) in switchgears requires extensive data collection and time-consuming analyses. Data from real live operational environments pose great challenges in the development of robust and efficient detection algorithms due to overlapping PDs and the strong presence of random white noise. This paper presents a novel approach using clustering for data cleaning and feature extraction of phase-resolved partial discharge (PRPD) plots derived from live operational data. A total of 452 PRPD 2D plots collected from distribution substations over a six-month period were used to test the proposed technique. The output of the clustering technique is evaluated on different types of machine learning classification techniques and the accuracy is compared using balanced accuracy score. The proposed technique extends the measurement abilities of a portable PD measurement tool for diagnostics of switchgear condition, helping utilities to quickly detect potential PD activities with minimal human manual analysis and higher accuracy.
Asymptomatic Patients and Immune Subjects
Authors: Veronese Sheila , Sbarbati Andrea
Published: January 2022

An asymptomatic patient is someone who contracts a disease but shows no symptoms. An immune subject is a person who is free from virus infection. Both of these categories of people experience the limitations of government imposed by a pandemic situation, with one important difference. Probably only the first subjects contribute, in spite of themselves, to the spread of the disease and to the contagion of the people most susceptible to the virus. This implies that their detection is essential to limit infections. Therefore, knowing the characteristics of these people and those immune to the virus can be extremely useful in mitigating the effects of the disease and/or defeating it.
The Application of Computer Techniques to ECG Interpretation
Authors: Macfarlane Peter W.
Published: January 2022

It is over 120 years since Einthoven introduced the electrocardiogram [...]
Religion and Death in the United States: A Meta-Regression Comparative Assessment of Between-County Mortality Heterogeneity in the United States
Authors: Sissamis Frances , Villalba Karina , Garcia Jordan , Melus Vickie , Markentell Emily J. , Perez Ligia D. , Ramirez Gilbert
Published: January 2022

Religion can have a favorable impact on individual-level health. The influence of religion on population health, however, remains less clear. This study investigated the association between religion and mortality at the population-level. Using county data, a meta-regression was performed to examine between-county mortality heterogeneity. The percent heterogeneity associated with religion variables were compared to demographics (i.e., place, race, language, age, and gender) and health factors (i.e., individual behaviors, clinical care, social and economic, and physical environment) as predictors of mortality. Religion was measured in terms of adherence (i.e., prevalence attending/belonging to a congregation), congregation density, and the diversity of adherents and congregation by denominations. Results showed counties with lower mortality were associated with higher proportions of religion adherents and a greater diversity of adherents and congregations. Counties with higher mortality were associated with higher religion congregation density. Religion, as a parsimonious multivariate model with all demographic and health factor predictors, had less added value when controlled for individual variables or constructs. The direction of association between religion and mortality was consistent, even when controlling for demographics and health factors, and thus merits further consideration as a population health determinant, as it may play a critical role in understanding other population health outcomes.
Staying Physically Active Is Associated with Better Mental Health and Sleep Health Outcomes during the Initial Period of COVID-19 Induced Nation-Wide Lockdown in Jordan
Authors: Al-Ajlouni Yazan A. , Park Su Hyun , Alawa Jude , Dodin Ban , Shamaileh Ghaith , Makarem Nour , Keyes Katherine M. , Duncan Dustin T.
Published: January 2022

Jordan, a Middle Eastern country, initially responded to an outbreak of COVID-19 cases within its own borders by imposing a 7-week strict lockdown and closure of international and domestic travel. Such measures drastically influenced lifestyle behaviors of the population. This study aimed to investigate the prevalence of physical activity, and its association with mental and sleep health outcomes among Jordanians during a period of COVID-19 induced lockdown. Validated questionnaires were administered using a web-based platform to evaluate moderate-to-vigorous physical activity (MVPA), anxiety and depressive symptoms, sleep health, and sociodemographic characteristics. A modified Poisson regression model with robust error variance was used to estimate adjusted prevalence ratios (aPRs) and 95% confidence intervals (CIs). Compared to participants who met the guidelines, those who did not had significantly higher prevalence of moderate or severe anxiety symptoms than that of minimal or mild anxiety symptoms and increased depressive symptoms. Insufficient MVPA was associated with higher prevalence of poor sleep quality, short sleep duration (<7 h) and sleep problems. Overall, sufficient MVPA was associated with better mental and sleep health during the COVID-19 induced nation-wide lockdown in Jordan. While further research is necessary, promoting physical activity during the lockdown could potentially improve mental and sleep health outcomes among the population.
Criterion Validity and Applicability of Motor Screening Instruments in Children Aged 5–6 Years: A Systematic Review
Authors: van Dokkum Nienke H. , Reijneveld Sijmen A. , de Best Judith Th. B. W. , Hamoen Marleen , te Wierike Sanne C. M. , Bos Arend F. , de Kroon Marlou L. A.
Published: January 2022

The detection of motor developmental problems, especially developmental coordination disorder, at age 5–6 contributes to early interventions. Here, we summarize evidence on (1) criterion validity of screening instruments for motor developmental problems at age 5–6, and (2) their applicability. We systematically searched seven databases for studies assessing criterion validity of these screening instruments using the M-ABC as reference standard. We applied COSMIN criteria for systematic reviews of screening instruments to describe the correlation between the tests and the M-ABC. We extracted information on correlation coefficients or area under the receiver operating curve, sensitivity and specificity, and applicability in practice. We included eleven studies, assessing eight instruments: three performance-based tests (MAND, MOT 4–6, BFMT) and five questionnaires (DCD-Q, PQ, ASQ-3, MOQ-T-FI, M-ABC-2-C). The quality of seven studies was fair, one was good, and three were excellent. Seven studies reported low correlation coefficients or AUC (<0.70), four did not report these. Sensitivities ranged from 21–87% and specificities from 50–96%, with the MOT4–6 having the highest sensitivity and specificity. The DCD-Q, PQ, ASQ-3, MOQ-T-FI, and M-ABC-2-C scored highest on applicability. In conclusion, none of the instruments were sufficiently valid for motor screening at age 5–6. More research is needed on screening instruments of motor delay at age 5–6.
Retrofittable Solutions Capability for Gas Turbine Compressors
Authors: Ricci Martina , Mosele Stefano Gino , Benvenuto Marcello , Astrua Pio , Pacciani Roberto , Marconcini Michele
Published: January 2022

The increasing introduction of renewable energy capacity has changed the perspective on the operation of conventional power plants, introducing the necessity of reaching extreme off-design conditions. There is a strong interest in the development and optimization of technologies that can be retrofitted to an existing power plant to enhance flexibility as well as increase performance and lower emissions. Under the framework of the European project TURBO-REFLEX, a typical F-class gas turbine compressor designed and manufactured by Ansaldo Energia has been studied. Numerical analyses were performed using the TRAF code, which is a state-of-the-art 3D CFD RANS/URANS flow solver. In order to assess the feasibility of lower minimum environmental load operation, by utilizing a reduction in the compressor outlet mass-flow rate, with a safe stability margin, two different solutions have been analyzed: blow-off extractions and extra-closure of Variable Inlet Guide Vanes. The numerical steady-state results are compared and discussed in relation to an experimental campaign, which was performed by Ansaldo Energia. The purpose is to identify the feasibility of the technologies and implementation opportunity in the existing thermal power plant fleet.
Low-Cost Inventions and Patents
Authors: Salmerón-Manzano Esther , Manzano-Agugliaro Francisco
Published: January 2022

Inventions have been the technological advances of mankind [...]
Role of Solvent Polarity on Dispersion Quality and Stability of Functionalized Carbon Nanotubes
Authors: Rajendran Dhivakar , Ramalingame Rajarajan , Adiraju Anurag , Nouri Hanen , Kanoun Olfa
Published: January 2022

Dispersion of carbon nanotubes (CNT) in solvents and/or polymers is essential to reach the full potential of the CNTs in nanocomposite materials. Dispersion of CNTs is especially challenging due to the van-der-Waals attraction forces between the CNTs, which let them tend to re-bundle and/or re-aggregate. This paper presents a brief analysis of the quality and stability of functionalized multiwalled carbon nanotubes (fMWCNT) dispersion on polar solvents. A comparative study of functionalized CNT dispersion in water, methyl, and alcohol-based organic solvents has been carried out and the dispersion has been characterized by UV-VIS spectroscopy, electrochemical characterization such as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). Visual analysis of the dispersion has been investigated for up to 14 days to assess the dispersion’s stability. Based on the material characterization, it was observed that the degree of affinity fMWCNT with -COOH group highly depends on the polarity of the solvent, where the higher the polarity, the better the interaction of fMWCNT with solvents.
Tensile Deformation and Fracture Behavior of API-5L X70 Line Pipe Steel
Authors: Lobanov Mikhail L. , Khotinov Vladislav A. , Urtsev Vladimir N. , Danilov Sergey V. , Urtsev Nikolay V. , Platov Sergey I. , Stepanov Stepan I.
Published: January 2022

Thermo-mechanical controlled processing (TMCP) is employed to obtain the required level of mechanical properties of contemporary HSLA steel plates utilized for gas and oil pipeline production. The strength and crack resistance of pipeline steels are mainly determined by its microstructure and crystallographic texture. In this study, the influence of the structural and textural states of industrially produced API-5L X70-X80 pipeline steels on tensile mechanical properties was analyzed. TMCP routes with different hot rolling temperatures and cooling rates were employed. The texture of steel was assessed using the Taylor factor, which was calculated based on electron backscatter diffraction (EBSD). The decrease in rolling temperature resulted in the sharper texture characterized by {001} planes banding (cleavage planes in the bcc lattice) parallel to rolling direction. The tensile deformation behavior at the stage of necking was determined by the crystallographic and morphological texture of the material and demonstrated significant anisotropy. Rupture of all investigated samples was accompanied by the development of splitting on the fracture surface. The splitting was localized in the rolling plane similar to the splitting in standard Charpy tests of pipeline steels.
ZnO@Bi5O7I Heterojunction Derived from ZIF-8@BiOI for Enhanced Photocatalytic Activity under Visible Light
Authors: Tang Jijun , Duan Zhengzhou , Xu Qinyun , Li Chuwen , Hou Dongmei , Gao Guicheng , Luo Weiqi , Wang Yujia , Zhu Yu
Published: January 2022

In the study, ZIF-8@BIOI composites were synthesized by the hydrothermal method and then calcined to acquire the ZnO@Bi5O7I composite as a novel composite for the photocatalytic deterioration of the antibiotic tetracycline (TC). The prepared ZnO@Bi5O7I composites were physically and chemically characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), Brunauer–Emmet–Teller (BET) surface area, UV–Vis diffuse reflectance spectroscopy (DRS), emission fluorescence spectra, transient photocurrent response, electrochemical impedance spectra and Mott–Schottky. Among the composites formed an n–n heterojunction, which increased the separation efficiency of electrons and holes and the efficiency of charge transfer. After the photocatalytic degradation test of TC, it showed that ZnO@Bi5O7I (2:1) had the best photodegradation effect with an 86.2% removal rate, which provides a new approach to the treatment of antibiotics such as TC in wastewater.
Strength Tests and Numerical Simulations of Loess Modified by Desulfurization Ash and Fly Ash
Authors: Cheng Zhi , Cheng Xinrong , Xie Yuchao , Ma Zhe , Liu Yuhao
Published: January 2022

Desulfurization ash and fly ash are solid wastes discharged from boilers of power plants. Their utilization rate is low, especially desulfurization ash, most of which is stored. In order to realize their resource utilization, they are used to modify loess in this paper. Nine group compaction tests and 32 group direct shear tests are done in order to explore the influence law of desulfurization ash and fly ash on the strength of the loess. Meanwhile, FLAC3D software is used to numerically simulate the direct shear test, and the simulation results and the test results are compared and analyzed. The results show that, with the increase of desulfurization ash’s amount, the shear strength of the modified loess increases first and then decreases. The loess modified by the fly ash has the same law with that of the desulfurization ash. The best mass ratio of modified loess is 80:20. When the mass ratio is 80:20, the shear strength of loess modified by the desulfurization ash is 12.74% higher than that of the pure loess on average and the shear strength of loess modified by fly ash is 3.59% higher than that of the pure loess on average. The effect of the desulfurization ash on modifying the loess is better than that of the fly ash. When the mass ratio is 80:20, the shear strength of loess modified by the desulfurization ash is 9.15% higher than that of the fly ash on average. Comparing the results of the simulation calculation with the actual test results, the increase rate of the shear stress of the FLAC3D simulation is larger than that of the actual test, and the simulated shear strength is about 8.21% higher than the test shear strength.
Mechanisms and Critical Technologies of Transport Inhibitor Agent (TIA) throughout C-S-H Nano-Channels
Authors: Luo Qi , Huang Jiale
Published: January 2022

The critical issue of the durability of marine concrete lies in the continuous penetration and rapid enrichment of corrosive ions. Here a new ion transfer inhibitor, as TIA, with calcium silicate hydrate (C-S-H) interfacial affinity and hydrophobicity is proposed through insights from molecular dynamics into the percolation behavior of the ion solution in C-S-H nano-channels and combined with molecular design concepts. One side of the TIA can be adsorbed on the surface of the cement matrix and can form clusters of corrosive ions to block the gel pores so as to resist the ion solution percolation process. Its other side is structured as a hydrophobic carbon chain, similar to a door hinge, which can stick to the matrix surface smoothly before the erosion solution is percolated. It can then change into a perpendicular chain shape to reduce the percolation channel’s diameter and thereby inhibit the percolation when ions meet the inhibitor. Therefore, once the erosion solution contacts TIA, it can quickly chelate with calcium ions and erosion ions at the interface to form clusters and compact pores. In addition, the water absorption, chloride migration coefficient, and chloride content of concrete samples decreased significantly after adding TIA, proving that TIA can effectively enhance the durability of cement-based materials. The structure–activity relationship of ion transfer that is proposed can provide new ideas for solving the critical problems of durability of cement-based materials and polymer molecular design.
Asphalt Binder Modification with Plastomeric Compounds Containing Recycled Plastics and Graphene
Authors: D’Angelo Simone , Ferrotti Gilda , Cardone Fabrizio , Canestrari Francesco
Published: January 2022

Polymer-modified bitumens are usually employed for enhancing the mixture performance against typical pavement distresses. This paper presents an experimental investigation of bitumens added with two plastomeric compounds, containing recycled plastics and graphene, typically used for asphalt concrete dry modification. The goal was to study the effects of the compounds on the rheological response of the binder phase, as well the adhesion properties, in comparison with a reference plain bitumen. The blends (combination of bitumen and compounds) were evaluated through dynamic viscosity tests, frequency sweep tests, and multiple stress creep recovery (MSCR) tests. Moreover, the bitumen bond strength (BBS) test was performed to investigate the behavior of the systems consisting of blends and aggregate substrates (virgin and pre-coated). The rheological tests indicated that both blends performed better than the plain bitumen, especially at high temperature, showing an enhanced rutting resistance. In terms of bond strength, comparable results were found between the blends and reference bitumen. Moreover, no performance differences were detected between the two types of blends.
Characterization and Calculation of the Dynamic Recrystallization Texture in Fe-3.0 Wt.% Si Alloy
Authors: Shao Guangshuai , Sha Yuhui , Chen Xi , Chang Songtao , Zhang Fang , Zuo Liang
Published: January 2022

High-temperature plane-strain compression tests were performed on Fe-3.0 wt.% Si alloy from 900 °C to 1150 °C at strain rates of 5 s−1 to 1 s−1, and the texture development from different initial textures was investigated by means of electron backscattered diffraction. Dynamic recrystallization occurs by strain-induced boundary migration, and the evolutions of the microstructure and different texture components vary with the initial texture. The critical orientation boundary separating the weakened and enhanced texture components moves with the initial texture, and a quantitative relationship is established to represent the dependence of the critical Taylor factor on the instantaneous texture. A model is proposed to describe the dynamic recrystallization texture by incorporating the oriented nucleation probability with a variable critical Taylor factor. The present work could improve the accuracy of hot deformation texture prediction based on strain-induced boundary migration.
Wear Mechanism of Multilayer Coated Carbide Cutting Tool in the Milling Process of AISI 4340 under Cryogenic Environment
Authors: Muhamad Shalina Sheik , Ghani Jaharah A. , Che Haron Che Hassan , Yazid Hafizal
Published: January 2022

Cryogenic technique is the use of a cryogenic medium as a coolant in machining operations. Commonly used cryogens are liquid nitrogen (LN2) and carbon dioxide (CO2) because of their low cost and non-harmful environmental impact. In this study, the effects of machining conditions and parameters on the wear mechanism were analysed in the milling process of AISI 4340 steel (32 HRC) under cryogenic conditions using a multilayer coated carbide cutting tool (TiAlN/AlCrN). A field emission scanning electron microscope with energy-dispersive X-ray analysis was used to examine the wear mechanisms comprehensively. At low machining parameters, abrasion and adhesion were the major wear mechanisms which occurred on the rake face. Machining at high machining parameters caused the removal of the coating material on the rake face due to the high temperature and cutting force generated during the cutting process. In addition, it was found that continuously adhered material on the rake face would lead to crater wear. Furthermore, the phenomenon of oxidation was also observed when machining at high cutting speed, which resulted in diffusion wear and increase in the crater wear. Based on the relationship between the cutting force and cutting temperature, it can be concluded that these machining outputs are significant in affecting the progression of tool wear rate, and tool wear mechanism in the machining of AISI 4340 alloy steel.
Reutilizing Waste Iron Tailing Powders as Filler in Mortar to Realize Cement Reduction and Strength Enhancement
Authors: Cui Liyun , Chen Peiyuan , Wang Liang , Xu Ying , Wang Hao
Published: January 2022

Recently, the massive accumulation of waste iron tailings powder (WITP) has resulted in significant environmental pollution. To solve this problem, this paper proposes an original mortar replacement (M) method to reuse waste solids and reduce cement consumption. In the experiment, the author employed an M method which replaces water, cement, and sand with WITP under constant water/cement and found that the strength development can be significantly improved. Specifically, a mortar with 20% WITP replacement can obtain a 30.95% improvement in strength development. To study the internal mechanism, we performed experiments such as thermogravimetric analysis (TGA), mercury intrusion porosimetry (MIP), and SEM. The results demonstrate that the nucleation effect and pozzolanic effect of WITP can help promote cement hydration, and MIP reveals that WITP can effectively optimize pore structure. In addition, 1 kg 20% WITP mortar reduced cement consumption by 20%, which saves 19.98% of the economic cost. Comprehensively, our approach achieves the effective utilization of WITP and provides a favorable reference for practical engineering.
Diverse Multiple Lump Analytical Solutions for Ion Sound and Langmuir Waves
Authors: Alruwaili Abdulmohsen D. , Seadawy Aly R. , Rizvi Syed T. R. , Beinane Sid Ahmed O.
Published: January 2022

In this work, we study a time-fractional ion sound and Langmuir waves system (FISLWS) with Atangana–Baleanu derivative (ABD). We use a fractional ABD operator to transform our system into an ODE. We investigate multiwaves, periodic cross-kink, rational, and interaction solutions by the combination of rational, trigonometric, and various bilinear functions. Furthermore, 3D, 2D, and relevant contour plots are presented for the natural evolution of the gained solutions under the selection of proper parameters.
Case of Patient with AML with Complex Karyotype including Ultra-Rare t(4;8)(q32;q13), t(4;11)(q21;p15) and Familial Aggregation of Myeloid Malignancies
Authors: Milczarek Sławomir , Studniak Ewa , Baumert Bartłomiej , Janowski Michał , Bonda Wioleta , Pietrzak Joanna , Łanocha Aleksandra , Paczkowska Edyta , Zdziarska Barbara , Machaliński Bogusław
Published: January 2022

We present a unique case of a young woman with acute myeloid leukemia (AML) with complex karyotype. The presence of the t(4;11)(q23;p15) is extremely rare in myeloid leukemias, while t(4;8)(q32;q13) has not yet been described in any leukemia reference. Another interesting issue is the familial aggregation of myeloid malignancies and worse course of the disease in each subsequent generation, as well as an earlier onset of the disease. Our report emphasizes the need for thorough pedigree examination upon myeloid malignancy diagnosis as there are relatives for whom counseling, gene testing, and surveillance may be highly advisable.
An Electrochemiluminescence Biosensor for the Detection of Alzheimer’s Tau Protein Based on Gold Nanostar Decorated Carbon Nitride Nanosheets
Authors: Jalili Roghayeh , Chenaghlou Salimeh , Khataee Alireza , Khalilzadeh Balal , Rashidi Mohammad-Reza
Published: January 2022

Human Tau protein is the most reliable biomarker for the prediction of Alzheimer’s disease (AD). However, the assay to detect low concentrations of tau protein in serum is a great challenge for the early diagnosis of AD. This paper reports an electrochemiluminescence (ECL) immunosensor for Tau protein in serum samples. Gold nanostars (AuNSs) decorated on carbon nitride nanosheets (AuNS@g-CN nanostructure) show highly strong and stable ECL activity compared to pristine CN nanosheets due to the electrocatalytic and surface plasmon effects of AuNSs. As a result of the strong electromagnetic field at branches, AuNSs showed a better ECL enhancement effect than their spherical counterpart. For the fabrication of a specific immunosensor, immobilized AuNSs were functionalized with a monoclonal antibody specific for Tau protein. In the presence of Tau protein, the ECL intensity of the immunosensor decreased considerably. Under the optimal conditions, this ECL based immunosensor exhibits a dynamic linear range from 0.1 to 100 ng mL−1 with a low limit of detection of 0.034 ng mL−1. The LOD is less than the Tau level in human serum; thus, this study provides a useful method for the determination of Tau. The fabricated ECL immunosensor was successfully applied to the detection of Tau, the biomarker in serum samples. Therefore, the present approach is very promising for application in diagnosing AD within the early stages of the disease.
Correction: Lehtonen et al. The Potentials of Tangible Technologies for Learning Linear Equations. Multimodal Technol. Interact. 2020, 4, 77
Authors: Lehtonen Daranee , Machado Lucas , Joutsenlahti Jorma , Perkkilä Päivi
Published: January 2022

In the original publication, there was a mistake in Table 3 as published [...]
Dip-Coating Self-Assembly Fabrication and Polarization Sensitive Photoresponse of Aligned Single-Walled Carbon Nanotube Film
Authors: Zhang Jiazhen , Yang Luhan , Xu Huang , Zhou Jie , Sang Yuxiang , Cui Zhuangzhuang , Liu Changlong , Liu Jingjing , Guo Tianle , Wang Xingjun , Wang Lin , Chen Gang , Chen Xiaoshuang
Published: January 2022

It is challenging to obtain wafer-scaled aligned films for completely exploiting the promising properties of semiconducting single-walled carbon nanotubes (s-SWCNTs). Aligned s-SWCNTs with a large area can be obtained by combining water evaporation and slow withdrawal-induced self-assembly in a dip-coating process. Moreover, the tunability of deposition morphology parameters such as stripe width and spacing is examined. The polarized Raman results show that s-SWCNTs can be aligned in ±8.6°. The derived two terminal photodetector shows both a high negative responsivity of 41 A/W at 520 nm and high polarization sensitivity. Our results indicate that aligned films with a large area may be useful to electronics- and optoelectronics-related applications.
Efficient Ray Tracing of Large 3D Scenes for Mobile Distributed Computing Environments
Authors: Seo Woong , Park Sanghun , Ihm Insung
Published: January 2022

Cluster computing has attracted much attention as an effective way of solving large-scale problems. However, only a few attempts have been made to explore mobile computing clusters that can be easily built using commodity smartphones and tablets. To investigate the possibility of mobile cluster-based rendering of large datasets, we developed a mobile GPU ray tracer that renders nontrivial 3D scenes with many millions of triangles at an interactive frame rate on a small-scale mobile cluster. To cope with the limited processing power and memory space, we first present an effective 3D scene representation scheme suitable for mobile GPU rendering. Then, to avoid performance impairment caused by the high latency and low bandwidth of mobile networks, we propose using a static load balancing strategy, which we found to be more appropriate for the vulnerable mobile clustering environment than a dynamic strategy. Our mobile distributed rendering system achieved a few frames per second when ray tracing 1024 × 1024 images, using only 16 low-end smartphones, for large 3D scenes, some with more than 10 million triangles. Through a conceptual demonstration, we also show that the presented rendering scheme can be effectively explored for augmenting real scene images, captured or perceived by augmented and mixed reality devices, with high quality ray-traced images.
Using Sensor Graphs for Monitoring the Effect on the Performance of the OTAGO Exercise Program in Older Adults
Authors: Friedrich Björn , Lübbe Carolin , Steen Enno-Edzard , Bauer Jürgen Martin , Hein Andreas
Published: January 2022

The OTAGO exercise program is effective in decreasing the risk for falls of older adults. This research investigated if there is an indication that the OTAGO exercise program has a positive effect on the capacity and as well as on the performance in mobility. We used the data of the 10-months observational OTAGO pilot study with 15 (m = 1, f = 14) (pre-)frail participants aged 84.60 y (SD: 5.57 y). Motion sensors were installed in the flats of the participants and used to monitor their activity as a surrogate variable for performance. We derived a weighted directed multigraph from the physical sensor network, subtracted the weights of one day from a baseline, and used the difference in percent to quantify the change in performance. Least squares was used to compute the overall progress of the intervention (n = 9) and the control group (n = 6). In accordance with previous studies, we found indication for a positive effect of the OTAGO program on the capacity in both groups. Moreover, we found indication that the OTAGO program reduces the decline in performance of older adults in daily living. However, it is too early to conclude causalities from our findings because the data was collected during a pilot study.
Confronting Deep-Learning and Biodiversity Challenges for Automatic Video-Monitoring of Marine Ecosystems
Authors: Villon Sébastien , Iovan Corina , Mangeas Morgan , Vigliola Laurent
Published: January 2022

With the availability of low-cost and efficient digital cameras, ecologists can now survey the world’s biodiversity through image sensors, especially in the previously rather inaccessible marine realm. However, the data rapidly accumulates, and ecologists face a data processing bottleneck. While computer vision has long been used as a tool to speed up image processing, it is only since the breakthrough of deep learning (DL) algorithms that the revolution in the automatic assessment of biodiversity by video recording can be considered. However, current applications of DL models to biodiversity monitoring do not consider some universal rules of biodiversity, especially rules on the distribution of species abundance, species rarity and ecosystem openness. Yet, these rules imply three issues for deep learning applications: the imbalance of long-tail datasets biases the training of DL models; scarce data greatly lessens the performances of DL models for classes with few data. Finally, the open-world issue implies that objects that are absent from the training dataset are incorrectly classified in the application dataset. Promising solutions to these issues are discussed, including data augmentation, data generation, cross-entropy modification, few-shot learning and open set recognition. At a time when biodiversity faces the immense challenges of climate change and the Anthropocene defaunation, stronger collaboration between computer scientists and ecologists is urgently needed to unlock the automatic monitoring of biodiversity.
Sequence Effect on the Activity of DNAzyme with Covalently Attached Hemin and Their Potential Bioanalytical Application
Authors: Kosman Joanna , Żukowski Krzysztof , Csáki Andrea , Fritzsche Wolfgang , Juskowiak Bernard
Published: January 2022

In this work we investigated the effect of a DNA oligonucleotide sequence on the activity of a DNAzyme with covalently attached hemin. For this purpose, we synthesized seven DNA-hemin conjugates. All DNA-hemin conjugates as well as DNA/hemin complexes were characterized using circular dichroism, determination of melting temperatures and pKa of hemin. We observed that hemin conjugation in most cases led to the formation of parallel G-quadruplexes in the presence of potassium and increased thermal stability of all studied systems. Although the activity of DNA-hemin conjugates depended on the sequence used, the highest activity was observed for the DNA-hemin conjugate based on a human telomeric sequence. We used this DNAzyme for development of “sandwich” assay for detection of DNA sequence. For this assay, we used electric chip which could conduct electricity after silver deposition catalyzed by DNAzyme. This method was proved to be selective towards DNA oligonucleotides with mismatches and could be used for the detection of the target. To prove the versatility of our DNAzyme probe we also performed experiments with streptavidin-coated microplates. Our research proved that DNAzyme with covalently attached hemin can be used successfully in the development of heterogeneous assays.
A New Wearable System for Sensing Outdoor Environmental Conditions for Monitoring Hyper-Microclimate
Authors: Cureau Roberta Jacoby , Pigliautile Ilaria , Pisello Anna Laura
Published: January 2022

The rapid urbanization process brings consequences to urban environments, such poor air quality and the urban heat island issues. Due to these effects, environmental monitoring is gaining attention with the aim of identifying local risks and improving cities’ liveability and resilience. However, these environments are very heterogeneous, and high-spatial-resolution data are needed to identify the intra-urban variations of physical parameters. Recently, wearable sensing techniques have been used to perform microscale monitoring, but they usually focus on one environmental physics domain. This paper presents a new wearable system developed to monitor key multidomain parameters related to the air quality, thermal, and visual domains, on a hyperlocal scale from a pedestrian’s perspective. The system consisted of a set of sensors connected to a control unit settled on a backpack and could be connected via Wi-Fi to any portable equipment. The device was prototyped to guarantee the easy sensors maintenance, and a user-friendly dashboard facilitated a real-time monitoring overview. Several tests were conducted to confirm the reliability of the sensors. The new device will allow comprehensive environmental monitoring and multidomain comfort investigations to be carried out, which can support urban planners to face the negative effects of urbanization and to crowd data sourcing in smart cities.
Internet of Things Concept in the Context of the COVID-19 Pandemic: A Multi-Sensor Application Design
Authors: Lavric Alexandru , Petrariu Adrian I. , Mutescu Partemie-Marian , Coca Eugen , Popa Valentin
Published: January 2022

In this paper, we present the design, development and implementation of an integrated system for the management of COVID-19 patient, using the LoRaWAN communication infrastructure. Our system offers certain advantages when compared to other similar solutions, allowing remote symptom and health monitoring that can be applied to isolated or quarantined people, without any external interaction with the patient. The IoT wearable device can monitor parameters of health condition like pulse, blood oxygen saturation, and body temperature, as well as the current location. To test the performance of the proposed system, two persons under quarantine were monitored, for a complete 14-day standard quarantine time interval. Based on the data transmitted to the monitoring center, the medical staff decided, after several days of monitoring, when the measured values were outside of the normal parameters, to do an RT-PCR test for one of the two persons, confirming the SARS-CoV2 virus infection. We have to emphasize the high degree of scalability of the proposed solution that can oversee a large number of patients at the same time, thanks to the LoRaWAN communication protocol used. This solution can be successfully implemented by local authorities to increase monitoring capabilities, also saving lives.
A Study on 3D Deep Learning-Based Automatic Diagnosis of Nasal Fractures
Authors: Seol Yu Jin , Kim Young Jae , Kim Yoon Sang , Cheon Young Woo , Kim Kwang Gi
Published: January 2022

This paper reported a study on the 3-dimensional deep-learning-based automatic diagnosis of nasal fractures. (1) Background: The nasal bone is the most protuberant feature of the face; therefore, it is highly vulnerable to facial trauma and its fractures are known as the most common facial fractures worldwide. In addition, its adhesion causes rapid deformation, so a clear diagnosis is needed early after fracture onset. (2) Methods: The collected computed tomography images were reconstructed to isotropic voxel data including the whole region of the nasal bone, which are represented in a fixed cubic volume. The configured 3-dimensional input data were then automatically classified by the deep learning of residual neural networks (3D-ResNet34 and ResNet50) with the spatial context information using a single network, whose performance was evaluated by 5-fold cross-validation. (3) Results: The classification of nasal fractures with simple 3D-ResNet34 and ResNet50 networks achieved areas under the receiver operating characteristic curve of 94.5% and 93.4% for binary classification, respectively, both indicating unprecedented high performance in the task. (4) Conclusions: In this paper, it is presented the possibility of automatic nasal bone fracture diagnosis using a 3-dimensional Resnet-based single classification network and it will improve the diagnostic environment with future research.
Contribution of Different Subbands of ECG in Sleep Apnea Detection Evaluated Using Filter Bank Decomposition and a Convolutional Neural Network
Authors: Yeh Cheng-Yu , Chang Hung-Yu , Hu Jiy-Yao , Lin Chun-Cheng
Published: January 2022

A variety of feature extraction and classification approaches have been proposed using electrocardiogram (ECG) and ECG-derived signals for improving the performance of detecting apnea events and diagnosing patients with obstructive sleep apnea (OSA). The purpose of this study is to further evaluate whether the reduction of lower frequency P and T waves can increase the accuracy of the detection of apnea events. This study proposed filter bank decomposition to decompose the ECG signal into 15 subband signals, and a one-dimensional (1D) convolutional neural network (CNN) model independently cooperating with each subband to extract and classify the features of the given subband signal. One-minute ECG signals obtained from the MIT PhysioNet Apnea-ECG database were used to train the CNN models and test the accuracy of detecting apnea events for different subbands. The results show that the use of the newly selected subject-independent datasets can avoid the overestimation of the accuracy of the apnea event detection and can test the difference in the accuracy of different subbands. The frequency band of 31.25–37.5 Hz can achieve 100% per-recording accuracy with 85.8% per-minute accuracy using the newly selected subject-independent datasets and is recommended as a promising subband of ECG signals that can cooperate with the proposed 1D CNN model for the diagnosis of OSA.
Dynamic Noise Reduction with Deep Residual Shrinkage Networks for Online Fault Classification
Authors: Salimy Alireza , Mitiche Imene , Boreham Philip , Nesbitt Alan , Morison Gordon
Published: January 2022

Fault signals in high-voltage (HV) power plant assets are captured using the electromagnetic interference (EMI) technique. The extracted EMI signals are taken under different conditions, introducing varying noise levels to the signals. The aim of this work is to address the varying noise levels found in captured EMI fault signals, using a deep-residual-shrinkage-network (DRSN) that implements shrinkage methods with learned thresholds to carry out de-noising for classification, along with a time-frequency signal decomposition method for feature engineering of raw time-series signals. The approach will be to train and validate several alternative DRSN architectures with previously expertly labeled EMI fault signals, with architectures then being tested on previously unseen data, the signals used will firstly be de-noised and a controlled amount of noise will be added to the signals at various levels. DRSN architectures are assessed based on their testing accuracy in the varying controlled noise levels. Results show DRSN architectures using the newly proposed residual-shrinkage-building-unit-2 (RSBU-2) to outperform the residual-shrinkage-building-unit-1 (RSBU-1) architectures in low signal-to-noise ratios. The findings show that implementing thresholding methods in noise environments provides attractive results and their methods prove to work well with real-world EMI fault signals, proving them to be sufficient for real-world EMI fault classification and condition monitoring.