bluuebunny/crossref_metadata_2025 huggingface dataset:
Temperature Dependence Study of Electrical and Electro-Optical Performances of Midwave Infrared Ga-Free T2SL Barrier Photodetector
Authors: Bouschet Maxime , Arounassalame Vignesh , Ramiandrasoa Anthony , Ribet-Mohamed Isabelle , Perez Jean-Philippe , Péré-Laperne Nicolas , Christol Philippe
Published: October 2022

In this paper, we report on temperature dependence performances of a midwave infrared (MWIR) Ga-free InAs/InAsSb type-II superlattice (T2SL) barrier (XBn) photodetector grown by molecular beam epitaxy on n-type GaSb substrate. The T2SL structure, with a 3 µm thick active region, was processed in a mesa device in order to perform dark current measurements and spectral photoresponse as a function of temperature. Analyses of these temperature dependence characterizations help us to improve the design of Ga-free T2SL MWIR XBn detectors.
Fatigue Reliability Design Method for Large Aviation Planetary System Considering the Flexibility of the Ring Gear
Authors: Li Ming , Luo Yuan , Xie Liyang
Published: October 2022

As the foundation and core of various heavy aircraft transmission systems, the reliability level of large-scale aviation planetary mechanism restricts the economic affordability and service safety for the aircraft to a great extent. This paper takes the heavy helicopter planetary mechanism as the research object, and aims to improve the fatigue reliability level of the system. The fatigue load history of the gear teeth under the coupling of global elastic behavior of the system is calculated using a hierarchical finite element method, and the fatigue strength distribution of gear teeth is fitted based on the gear low circumference fatigue test with the minimum order statistics transformation method to provide cost-effective load and strength input variables for the system reliability prediction model. Based on this, a mapping path from the key structural elements of large-scale aviation planetary mechanism to the system reliability indexes is established, and then a new method of reliability-driven multi-objective optimization design for planetary mechanism structural dimensions is proposed. Finally, the influence law of ring gear rim thickness on the fatigue reliability of the planetary gear train is analyzed and the NSGA-Ⅱ genetic algorithm is used to determine the optimal stiffness matching result of the rim size of the designated type of large aviation planetary system. The stiffness potential of the core structural elements is maximized as a way to balance the contradiction between reliability and lightweight requirements of a large aviation planetary system.
Few-Shot Continuous Authentication for Mobile-Based Biometrics
Authors: Wagata Kensuke , Teoh Andrew Beng Jin
Published: October 2022

The rapid growth of smartphone financial services raises the need for secure mobile authentication. Continuous authentication is a user-friendly way to strengthen the security of smartphones by implicitly monitoring a user’s identity through sessions. Mobile continuous authentication can be viewed as an anomaly detection problem in which models discriminate between one genuine user and the rest of the impostors (anomalies). In practice, complete impostor profiles are hardly available due to the time and monetary cost, while leveraging genuine data alone yields poorly generalized models due to the lack of knowledge about impostors. To address this challenge, we recast continuous mobile authentication as a few-shot anomaly detection problem, aiming to enhance the inference robustness of unseen impostors by using partial knowledge of available impostor profiles. Specifically, we propose a novel deep learning-based model, namely a local feature pooling-based temporal convolution network (LFP-TCN), which directly models raw sequential mobile data, aggregating global and local feature information. In addition, we introduce a random pattern mixing augmentation to generate class-unconstrained impostor data for the training. The augmented pool enables characterizing various impostor patterns from limited impostor data. Finally, we demonstrate practical continuous authentication using score-level fusion, which prevents long-term dependency or increased model complexity due to extended re-authentication time. Experiments on two public benchmark datasets show the effectiveness of our method and its state-of-the-art performance.
XOR-Based Meaningful (n, n) Visual Multi-Secrets Sharing Schemes
Authors: Huang Sheng-Yao , Lo An-hui , Juan Justie Su-Tzu
Published: October 2022

The basic visual cryptography (VC) model was proposed by Naor and Shamir in 1994. The secret image is encrypted into pieces, called shares, which can be viewed by collecting and directly stacking these shares. Many related studies were subsequently proposed. The most recent advancement in visual cryptography, XOR-based VC, can address the issue of OR-based VC’s poor image quality of the restored image by lowering hardware costs. Simultaneous sharing of multiple secret images can reduce computational costs, while designing shared images into meaningful unrelated images helps avoid attacks and is easier to manage. Both have been topics of interest to many researchers in recent years. This study suggests ways for XOR-based VCS that simultaneously encrypts several secret images and makes each share separately meaningful. Theoretical analysis and experimental results show that our methods are secure and effective. Compared with previous schemes, our scheme has more capabilities.
Research on Hand-Transmitted Vibration Prediction Model of the Handheld EVA Power Tool
Authors: Fu Hao , Chen Yang , Yu Yang , Jin Minghe
Published: October 2022

The hand-transmitted vibration generated by extravehicular activity (EVA) power tools has an important impact on the health of astronauts and the efficient completion of maintenance tasks when astronauts use EVA power tools for on-orbit maintenance. Based on the hand-transmitted vibration zero-gravity simulation test platform to measure the vibration response of the EVA power tool to human hands. Given the influence of the length of the operating rod and the number of non-detaching fastening devices on daily vibration exposure when astronauts wear extravehicular spacesuit gloves, a second-order polynomial model and a quadratic cumulative nonlinear model of daily vibration exposure are established. The experimental results show that the second-order polynomial model is more explanatory and predictive of the test data in the scope of the test. The R-values of the palm and opisthenar prediction model are 0.9930 and 0.9940 respectively, and the RMSEs are 7.973×10−4 m/s2 and 1.034×10−3 m/s2. The quadratic cumulative nonlinear model can accurately predict the vibration exposure of the hand outside the scope of the test. This study can provide theoretical reference and data support for the prediction of vibration exposure generated by astronauts using the EVA power tools during on-orbit maintenance.
Hierarchical Segmentation Method for Generating Road Intersections from Crowdsourced Trajectory Data
Authors: Zhang Yunfei , Tang Gengbiao , Fang Xiaoliang , Chen Tao , Zhou Fangbin , Luo Yabo
Published: October 2022

Maintaining the data freshness and completeness of road intersection information is the key task of urban road map production and updating. Compared to professional surveying methods, crowdsourced trajectory data provide a low-cost, wide-coverage and real-time data resource for road map construction. However, there may exist the problems of spatio-temporal heterogeneity and uneven density distribution in crowdsourced trajectory data. Hence, in light of road hierarchies, the paper proposes a hierarchical segmentation method to generate road intersections from crowdsourced trajectories. The proposed method firstly implements an adaptive density homogenization processing on raw trajectory data in order to decrease the uneven density discrepancy. Then, a hierarchical segmentation strategy is developed to extract multi-level road intersection elements from coarse scale to fine scale. Finally, the structural models of road intersections are delineated by an iterative piecewise fitting method. Experimental results show that the proposed method can accurately and completely extract road intersections of different shapes and scales, with an accuracy of about 87–90%. Particularly, the precision and recall of road intersection detection are obviously increased by about 7% and 20% by adaptive density homogenization, indicating the advantages of dealing with uneven trajectory data.
CFD Analysis on the Heat Dissipation of a Dry-Lubricated Gear Stage
Authors: Hildebrand Lucas , Dangl Florian , Paschold Constantin , Lohner Thomas , Stahl Karsten
Published: October 2022

Power losses in gearboxes result in frictional heating. Sufficient heat transfer from the gearbox to the environment is required for reliable operation. The heat dissipation from gears is linked to their interaction with fluids in the gearbox. Recent research has demonstrated the use of Computational Fluid Dynamics (CFD) to predict the gearbox fluid flow and no-load losses in an isothermal manner. This study focuses on a numerical analysis of the heat dissipation within a dry-lubricated gearbox under atmospheric conditions. Spur gears and helical gears are investigated. The air flow in the gearbox as well as the heat dissipation over the gear surfaces are evaluated in detail. The results show that the gear geometry and the circumferential speed have a strong impact on the air flow. Especially, the axial inflow of air to the gears has a great influence on the heat dissipation. Conveying effects of helical gears lead to a multidirectional airflow, resulting in higher values of the heat transfer coefficient on the gear surface compared to spur gears.
Combining Security and Reliability of Critical Infrastructures: The Concept of Securability
Authors: Maglaras Leandros , Janicke Helge , Ferrag Mohamed Amine
Published: October 2022

The digital revolution has made people more dependent on ICT technology to perform everyday tasks, whether at home or at work [...]
A Novel Convolutional Adversarial Framework for Multivariate Time Series Anomaly Detection and Explanation in Cloud Environment
Authors: Wen Peian , Yang Zhenyu , Wu Lei , Qi Sibo , Chen Juan , Chen Peng
Published: October 2022

Anomaly detection is critical to ensure cloud infrastructures’ quality of service. However, due to the complexity of inconspicuous (indistinct) anomalies, high dynamicity, and the lack of anomaly labels in the cloud environment, multivariate time series anomaly detection becomes more difficult. The existing approaches are rarely effective in meeting these challenges. In this paper, we propose a novel convolutional adversarial model, convolutional-adversarial-training-based integrated anomaly detection with explanation framework (CAT-IADEF), for multivariate time series anomaly detection in the cloud. We adopt three convolutional neural networks to learn sequence features and adversarial training to amplify “slight” anomalies while enhancing the robustness of the model. The dynamic threshold is determined in real time by the peaks over threshold (POT) method to improve detection accuracy. In addition, anomaly explanation is also conducted efficiently by analyzing anomaly score vectors. Experiments with seven data subsets from various public datasets show that CAT-IADEF outperforms state-of-the-art methods. The average F1 score on the seven datasets is 0.907, which is 6.5% higher than the state-of-the-art model and up to 22.1% higher than the baseline method. Furthermore, the proposed anomaly explanation framework is also integrated into various models to verify its effectiveness on the experimental datasets.
Nonthermal Plasma Multi-Reactor Scale-Up Using Pulse Capacitive Power Supplies
Authors: Burlica Radu , Cretu Daniel-Eusebiu , Beniuga Oana , Astanei Dragos
Published: October 2022

The scale up of nonthermal plasma (NTP) reactors requires the simultaneous operation in parallel of a large number of units supplied from the same power supply. The present paper aims to demonstrate the feasibility of parallel operation of multiple mini-NTP reactors. In order to demonstrate the parallel operation of a large number of NTP reactors, three different types of power supplies are considered. In addition to the most simple and common solution, which involves the use of individual, independent power supply for each reactor (an ignition coil driven by a pulse generator), two other configurations of supplies (capacitive AC and capacitive DC), simpler and less expensive, are tested. The capacitive pulsed power supplies allow the generation of HV pulses by an AC power supply (usually an AC transformer), as well as by a DC power supply using an R–C circuit. For the DC resistive–capacitive configuration, the frequency can be adjusted. For all configurations, the power of the discharge can be modified by changing the value of capacitors or resistors. The feasibility of the proposed systems was demonstrated by assessing the concentration of hydrogen peroxide induced in water after plasma treatment. The obtained results reveal that the proposed capacitive AC and DC power supplies allow a large number of plasma reactors to operate in parallel independently.
The Prevention and Treatment of Medical Diseases in Vulnerable Populations
Authors: Palaia Gaspare , Bruscolini Alice , Ralli Massimo
Published: October 2022

Vulnerability, as a phenomenon of analysis, has long been the subject of extensive social and economic policy reflections, aimed at planning social welfare interventions to support the areas most exposed to the effects of the economic crisis, especially with reference to the presence of potentially weaker segments of the population [...]
Methodology for the Prediction of Water Gushing in Tunnels in Igneous Fracture Tectonic Zones: A Case Study of a Tunnel in Guangdong Province, China
Authors: Zhang Weifeng , Zhou Xuemin , Wang Baoyong , Cheng Xiaoyong , Wei Wei
Published: October 2022

The disaster of water gushing is very liable to occur when tunnels are built in the water-rich fracture structures in igneous rock areas. Different sources of water gushing result in different sizes of disaster. The safety of human life and property are in danger. For the prediction of water gushing in tunnels, the fuzzy clustering method was used to determine the source of the water gushing in this paper. The problem of subjectivity in traditional identification methods was solved by this method. On the basis of the fuzzy clustering method, dynamically changing parameters of the effective radius of the water gushing were introduced and regressed with the dynamic monitoring data and the hydrogeological survey results in an improved method for predicting water gushing. Then, an improved method for predicting water gushing, considering the source, was proposed. A deep underground, extra-long tunnel under construction in the igneous region of southern China was used to verify the soundness of this improved method. Research results showed that the water gushing into the tunnel had a low correlation with surface water with a similarity index of λmin=0.3967 in the results of the second test. The water came mainly from within the rock mass. The effective radius were jointly determined by the average thickness of the rock aquifer and water gushing time, together with a positive correlation. The period of water gushing was divided into three stages. The predictions had a good accuracy rate with an error of 10% or less. These results could provide a reference and theoretical support for site construction.
AWMC: Abnormal-Weather Monitoring and Curation Service Based on Dynamic Graph Embedding
Authors: Gu Yuxuan , Gu Jiakai , Li Gen , Yun Heeseung , Jung Jason J. , An Sojung , Camacho David
Published: October 2022

This paper presents a system, namely, the abnormal-weather monitoring and curation service (AWMC), which provides people with a better understanding of abnormal weather conditions. The service can analyze a set of multivariate weather datasets (i.e., 7 meteorological datasets from 18 cities in Korea) and show (i) which dates are mostly abnormal in a certain city, and (ii) which cities are mostly abnormal on a certain date. In particular, the dynamic graph-embedding-based anomaly detection method was employed to measure anomaly scores. We implemented the service and conducted evaluations. Regarding the results of monitoring abnormal weather, AWMC shows that the average precision was approximately 90.9%, recall was 93.2%, and F1 score was 92.1% for all the cities.
Binary Dense SIFT Flow Based Position-Information Added Two-Stream CNN for Pedestrian Action Recognition
Authors: Park Sang Kyoo , Chung Jun Ho , Pae Dong Sung , Lim Myo Taeg
Published: October 2022

Pedestrian behavior recognition in the driving environment is an important technology to prevent pedestrian accidents by predicting the next movement. It is necessary to recognize current pedestrian behavior to predict future pedestrian behavior. However, many studies have recognized human visible characteristics such as face, body parts or clothes, but few have recognized pedestrian behavior. It is challenging to recognize pedestrian behavior in the driving environment due to the changes in the camera field of view due to the illumination conditions in outdoor environments and vehicle movement. In this paper, to predict pedestrian behavior, we introduce a position-information added two-stream convolutional neural network (CNN) with multi task learning that is robust to the limited conditions of the outdoor driving environment. The conventional two-stream CNN is the most widely used model for human-action recognition. However, the conventional two-stream CNN based on optical flow has limitations regarding pedestrian behavior recognition in a moving vehicle because of the assumptions of brightness constancy and piecewise smoothness. To solve this problem for a moving vehicle, the binary descriptor dense scale-invariant feature transform (SIFT) flow, a feature-based matching algorithm, is robust in moving-pedestrian behavior recognition, such as walking and standing, in a moving vehicle. However, recognizing cross attributes, such as crossing or not crossing the street, is challenging using the binary descriptor dense SIFT flow because people who cross the road or not act the same walking action, but their location on the image is different. Therefore, pedestrian position information should be added to the conventional binary descriptor dense SIFT flow two-stream CNN. Thus, learning biased toward action attributes is evenly learned across action and cross attributes. In addition, YOLO detection and the Siamese tracker are used instead of the ground-truth boundary box to prove the robustness in the action- and cross-attribute recognition from a moving vehicle. The JAAD and PIE datasets were used for training, and only the JAAD dataset was used as a testing dataset for comparison with other state-of-the-art research on multitask and single-task learning.
Molecular Hydrogen: The Postharvest Use in Fruits, Vegetables and the Floriculture Industry
Authors: Hancock John T. , Russell Grace , Stratakos Alexandros Ch.
Published: October 2022

Molecular hydrogen (H2) has been found to have significant effects in a range of organisms, from plants to humans. In the biomedical arena it has been found to have positive effects for neurodegenerative disease and even for treatment of COVID-19. In plants H2 has been found to improve seed germination, foliar growth, and crops: effects being most pronounced under stress conditions. It has also been found that treatment with H2 can improve the postharvest preservation of fruits, vegetables and flowers. Therefore, H2-based treatments may be useful for the storage and transport of food products. H2 can be delivered in a range of manners, from the use of the gas to creating H2-enriched solutions, such as hydrogen-rich water (HRW) or hydrogen nanobubble water (HNW). The exact action of H2 at a biochemical level has yet to be established. Despite this, H2 appears to be safe. Treatments of food with H2 would leave no harmful residues, and H2 itself is safe to use, as exemplified by its biomedical use. With H2 production and transport being developed for other industries, H2 is likely to become cheaper and its use for postharvest maintenance of food may be beneficial to explore further.
Characterization of Cytokines and Proliferation Marker Ki-67 in Chronic Rhinosinusitis with Recurring Nasal Polyps
Authors: Viksne Rudolfs , Sumeraga Gunta , Pilmane Mara
Published: October 2022

Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a chronic inflammation of the mucosa of the nose and paranasal sinuses with the presence of polyps, affecting between 2.7% and 4.4% of the population. Cytokine analysis has become important in research on inflammatory mechanisms in CRSwNP. Therefore, our aim is to investigate the complex appearance, relative distribution, and interlinks of IL-1, IL-4, IL-6, IL-7, IL-8, IL-10, IL-12, and Ki-67 in CRSwNP. Methods: Samples of nasal polyps were obtained from 19 patients with previously diagnosed CRSwNP and the recurrence of polyps after previous surgeries. The control group consisted of samples from 17 otherwise healthy individuals with isolated nasal septum deviations. Tissues were stained for previously mentioned cytokines and Ki-67 immunohistochemically. Results: Polyp samples showed an increased presence of cytokines in subepithelial connective tissue and a decreased appearance in epithelium when compared to controls. There were several very strong, strong, and moderate correlations among factors. Conclusions: IL-6 strongly correlates with other cytokines as well as with the proliferation marker Ki-67, which suggests significant stimulation of this regulatory cytokine and its possible involvement in the pathogenesis of recurrent nasal polyps. IL-4, IL-7, IL-10, and IL-12 correlate with Ki-67, which suggests the possible involvement of these cytokines in tissue cell proliferation in the case of recurrent nasal polyps.
Radon Transport, Accumulation Patterns, and Mitigation Techniques Applied to Closed Spaces
Authors: Sicilia Isabel , Aparicio Sofía , González Margarita , Anaya José Javier , Frutos Borja
Published: October 2022

In this study, different techniques for the mitigation of radon gas in indoor spaces were investigated. For this purpose, two different scenarios of a public building were analyzed: two symmetrical facility galleries and a reverberation chamber. Although most workplaces in this building have low radon levels, the complex structure houses spaces have very high radon concentrations. The study also included the surrounding areas of these spaces. The radon concentration and differential pressures were measured, and different mitigation techniques were applied: sealing, balanced ventilation, pressurization with the introduction of fresh air, and depressurization over each space. The pressurization solution was proven to be the most effective way to reduce radon concentration in both scenarios. The introduction of fresh air diluted the radon concentration, and the slight increase in the pressure reduced the entry of gas by the advection mechanism. On the other hand, the depressurization technique was the least effective mitigation technique, as it generated a negative pressure gradient that facilitated a higher radon flux from the source. Therefore, before applying any mitigation technique, it is necessary not only to study the space to be remediated but also the possible impact on neighboring spaces.
Moisture Transport and Contribution to the Continental Precipitation
Authors: Yang Yazhu , Liu Chunlei , Ou Niansen , Liao Xiaoqing , Cao Ning , Chen Ni , Jin Liang , Zheng Rong , Yang Ke , Su Qianye
Published: October 2022

Understanding the water cycle change under a warming climate is essential, particularly the ocean to land moisture transport, which affects the precipitation over land areas and influences society and the ecosystem. Using ERA5 data from 1988 to 2020, the time series of moisture transport and the trend across the boundary of each continent, including Eurasia, Africa, North America, South America, Antarctic, Australia, and Greenland, have been investigated. The inflow and outflow sections of the moisture have been identified for each continent. The trends of moisture convergence over Eurasia, Africa, North America, and Antarctic are all positive, with the values of 2.59 ± 3.12, 2.60 ± 3.17, 12.98 ± 2.28, and 0.32 ± 0.47 (in 106 kg/s/decade), respectively, but only the trend over North America is statistically significant at a 0.1 significance level. The moisture convergence trend of −0.59 ± 3.63 (in 106 kg/s/decade) over South America is negative but insignificant. The positive trend of 0.10 ± 0.35 (in 106 kg/s/decade) over Greenland is very weak. The precipitation, evaporation, and moisture convergence are well balanced at middle and low latitudes, but the combination of moisture convergence and evaporation is systematically lower than the precipitation over Antarctic and Greenland. Contributions of evaporation and moisture convergence (or transport) to the continental precipitation vary with the continent, but the moisture convergence dominates the precipitation variability over all continents, and the significant correlation coefficients between the anomaly time series of continental mean moisture convergence and precipitation are higher than 0.8 in all continents.
PM2.5 Pollution in Six Major Chinese Urban Agglomerations: Spatiotemporal Variations, Health Impacts, and the Relationships with Meteorological Conditions
Authors: Li Zhuofan , Zhang Xiangmin , Liu Xiaoyong , Yu Bin
Published: October 2022

To investigate the spatiotemporal patterns of fine particulate matter (PM2.5) under years of control measures in China, a comprehensive analysis including statistical analysis, geographical analysis, and health impact assessment was conducted on millions of hourly PM2.5 concentrations data during the period of 2017–2020 in six typical major urban agglomerations. During the period of 2017–2020, PM2.5 concentrations in the Beijing–Tianjin–Hebei urban agglomeration (BTH-UA), Central Plains urban agglomeration (CP-UA), Yangtze River Delta urban agglomeration (YRD-UA), Triangle of Central China urban agglomeration (TC-UA), Chengdu–Chongqing urban agglomeration (CY-UA), and Pearl River Delta urban agglomeration (PRD-UA) decreased at a rate of 6.69, 5.57, 5.45, 3.85, 4.66, and 4.1 µg/m3/year, respectively. PM2.5 concentration in BTH-UA decreased by 30.5% over four years, with an annual average of 44.6 µg/m3 in 2020. CP-UA showed the lowest reduction ratio (22.1%) among the six regions, making it the most polluted urban agglomeration. In southern BTH-UA, northeastern CP-UA, and northwestern TC-UA, PM2.5 concentrations with high levels formed a high–high agglomeration, indicating pollution caused by source emission in these areas was high and hard to control. Atmospheric temperature, pressure, and wind speed have important influences on PM2.5 concentrations. RH has a positive correlation with PM2.5 concentration in north China but a negative correlation in south China. We estimated that meteorological conditions can explain 16.7–63.9% of the PM2.5 changes in 129 cities, with an average of 33.4%, indicating other factors including anthropogenic emissions dominated the PM2.5 changes. Among the six urban agglomerations, PM2.5 concentrations in the CP-UA were most influenced by the meteorological change. Benefiting from the reduction in PM2.5 concentration, the total respiratory premature mortalities in six regions decreased by 73.1%, from 2017 to 2020. The CP-UA had the highest respiratory premature mortality in six urban agglomerations. We suggested that the CP-UA needs more attention and stricter pollution control measures.
Magnetic Signatures of Large-Scale Electric Currents in the Earth’s Environment at Middle and Low Latitudes
Authors: Amory-Mazaudier Christine
Published: October 2022

The purpose of space weather is the systemic study of the Sun–Earth system, in order to determine the impact of solar events on the electromagnetic environment of the Earth. This article proposes a new transdisciplinary approach of the Sun–Earth system based on the universal physical process of the dynamo. The dynamo process is based on two important parameters of the different plasmas of the Sun–Earth system, the motion and the magnetic field. There are four permanent dynamos in the Sun–Earth system: the solar dynamo, the Earth dynamo, the solar wind-magnetosphere dynamo, and the ionospheric dynamo. These four permanent dynamos are part of different scientific disciplines. This transdisciplinary approach links all of these dynamos in order to understand the variations in the Earth’s magnetic field. During a magnetic disturbed period, other dynamos exist. We focused on the ionospheric disturbed dynamo generated by Joule energy dissipated in the high latitude ionosphere during magnetic storms. Joule heating disrupts the circulation of thermospheric winds and in turn generates disturbances in the Earth’s magnetic field. This systemic approach makes it possible to understand magnetic disturbances previously not well understood.
A New First Order Expansion Formula with a Reduced Remainder
Authors: Chaskalovic Joel , Jamshidipour Hessam
Published: October 2022

This paper is devoted to a new first order Taylor-like formula, where the corresponding remainder is strongly reduced in comparison with the usual one, which appears in the classical Taylor’s formula. To derive this new formula, we introduce a linear combination of the first derivative of the concerned function, which is computed at n+1 equally spaced points between the two points, where the function has to be evaluated. We show that an optimal choice of the weights in the linear combination leads to minimizing the corresponding remainder. Then, we analyze the Lagrange P1- interpolation error estimate and the trapezoidal quadrature error, in order to assess the gain of the accuracy we obtain using this new Taylor-like formula.
Intelligent Security Model for Password Generation and Estimation Using Hand Gesture Features
Authors: Mahdi Bashar Saadoon , Hadi Mustafa Jasim , Abbas Ayad Rodhan
Published: October 2022

Computer security depends mainly on passwords to protect human users from attackers. Therefore, manual and alphanumerical passwords are the most frequent type of computer authentication. However, creating these passwords has significant drawbacks. For example, users often tend to choose passwords based on personal information so that they can be memorable and therefore weak and guessable. In contrast, it is often difficult to remember if the password is difficult to guess. We propose an intelligent security model for password generation and estimation to address these problems using the ensemble learning approach and hand gesture features. This paper proposes two intelligent stages: the first is the password generation stage based on the ensemble learning approach and the proposed S-Box. The second is the password strength estimation stage, also based on the ensemble learning approach. Four well-known classifiers are used: Multi-Layer Perceptron (MLP), Support Vector Machine (SVM), Random Forest Tree (RFT), and AdaBoost applied on two datasets: MNIST images dataset and password strength dataset. The experimental results showed that the hand gesture and password strength classification processes accurately performed at 99% in AUC, Accuracy, F1-measures, Precision, and Recall. As a result, the extracted features of hand gestures will directly impact the complexity of generated passwords, which are very strong, hard to guess, and memorable.
3D Printed Skull Cap and Benchtop Fabricated Microwire-Based Microelectrode Array for Custom Rat Brain Recordings
Authors: Yi Dongyang , Hartner Jeremiah P. , Ung Brian S. , Zhu Harrison L. , Watson Brendon O. , Chen Lei
Published: October 2022

Microwire microelectrode arrays (MEAs) have been a popular low-cost tool for chronic electrophysiological recordings and are an inexpensive means to record the electrical dynamics crucial to brain function. However, both the fabrication and implantation procedures for multi-MEAs on a single rodent are time-consuming and the accuracy and quality are highly manual skill-dependent. To address the fabrication and implantation challenges for microwire MEAs, (1) a computer-aided designed and 3D printed skull cap for the pre-determined implantation locations of each MEA and (2) a benchtop fabrication approach for low-cost custom microwire MEAs were developed. A proof-of-concept design of a 32-channel 4-MEA (8-wire each) recording system was prototyped and tested through Sprague Dawley rat recordings. The skull cap design, based on the CT-scan of a single rat conforms well with multiple Sprague Dawley rats of various sizes, ages, and weight with a minimal bregma alignment error (A/P axis standard error of the mean = 0.25 mm, M/L axis standard error of the mean = 0.07 mm, n = 6). The prototyped 32-channel system was able to record the spiking activities over five months. The developed benchtop fabrication method and the 3D printed skull cap implantation platform would enable neuroscience groups to conduct in-house design, fabrication, and implantation of customizable microwire MEAs at a lower cost than the current commercial options and experience a shorter lead time for the design modifications and iterations.
Culturing of Cardiac Fibroblasts in Engineered Heart Matrix Reduces Myofibroblast Differentiation but Maintains Their Response to Cyclic Stretch and Transforming Growth Factor β1
Authors: Ploeg Meike C. , Munts Chantal , Seddiqi Tayeba , ten Brink Tim J. L. , Breemhaar Jonathan , Moroni Lorenzo , Prinzen Frits. W. , van Nieuwenhoven Frans. A.
Published: October 2022

Isolation and culturing of cardiac fibroblasts (CF) induces rapid differentiation toward a myofibroblast phenotype, which is partly mediated by the high substrate stiffness of the culture plates. In the present study, a 3D model of Engineered Heart Matrix (EHM) of physiological stiffness (Youngs modulus ~15 kPa) was developed using primary adult rat CF and a natural hydrogel collagen type 1 matrix. CF were equally distributed, viable and quiescent for at least 13 days in EHM and the baseline gene expression of myofibroblast-markers alfa-smooth muscle actin (Acta2), and connective tissue growth factor (Ctgf) was significantly lower, compared to CF cultured in 2D monolayers. CF baseline gene expression of transforming growth factor-beta1 (Tgfβ1) and brain natriuretic peptide (Nppb) was higher in EHM-fibers compared to the monolayers. EHM stimulation by 10% cyclic stretch (1 Hz) increased the gene expression of Nppb (3.0-fold), Ctgf (2.1-fold) and Tgfβ1 (2.3-fold) after 24 h. Stimulation of EHM with TGFβ1 (1 ng/mL, 24 h) induced Tgfβ1 (1.6-fold) and Ctgf (1.6-fold). In conclusion, culturing CF in EHM of physiological stiffness reduced myofibroblast marker gene expression, while the CF response to stretch or TGFβ1 was maintained, indicating that our novel EHM structure provides a good physiological model to study CF function and myofibroblast differentiation.
Latitude-Induced and Behaviorally Thermoregulated Variations in Upper Thermal Tolerance of Two Anuran Species
Authors: Kim Ye Inn , Chuang Ming-Feng , Borzée Amaël , Kwon Sera , Jang Yikweon
Published: October 2022

Although thermal tolerance along geographical gradients gives an insight into species’ response to climate change, current studies on thermal tolerance are strongly skewed towards global-scale patterns. As a result, intraspecific variations are often assumed to be constant, despite a lack of evidence. To understand population-specific responses to thermal stress, we investigated the presence of intraspecific variations in the critical thermal maximum (CTmax) of tadpoles in two anuran species, Rana uenoi and Bufo sachalinensis. The study was conducted across a five-degree latitudinal gradient in the Republic of Korea. We exposed the tadpoles to increasing temperatures and recorded the CTmax for 270 R. uenoi individuals from 11 sites, collected in rice paddies, and for 240 B. sachalinensis individuals from ten sites, collected in reservoirs. We also recorded the swimming performance and behavior of the tadpoles when placed in an experimental apparatus during CTmax measurements. We then used linear regressions to determine the relationship between abiotic factors and CTmax. In R. uenoi, we found a positive relationship between latitude and CTmax, but the tadpoles did not display specific thermoregulatory behaviors. In B. sachalinensis, none of the abiotic factors such as climate and geographic coordinates were related to CTmax, but we detected a tendency to swim close to the water surface when water temperature was increasing. For R. uenoi, we tentatively relate the CTmax variability across the latitudinal gradient to a physiological adaptive response associated with habitat characteristics that are assumed to be fluctuating, as the species inhabits small water bodies prone to drying out. In the case of B. sachalinensis, the behavior observed may be linked to oxygen depletion and thermoregulation, as it may buffer temperature changes in the absence of physiological adjustment. These findings suggest that intra-specific variations in CTmax are greater than generally accounted for, and thermal conditions of natural environments are important for understanding thermal tolerance in ectothermic species. Our results highlight that species’ specific responses to climate warmings need to be studied to better protect species against climate change.
Neonatal Subcutaneous BCG Vaccination Decreases Atherosclerotic Plaque Number and Plaque Macrophage Content in ApoE−/− Mice
Authors: Bekkering Siroon , Singh Krishan , Lu Hui , Limawan Albert P. , Nold-Petry Claudia A. , Wallace Megan J. , Curtis Nigel , Pepe Salvatore , Cheung Michael , Burgner David P. , Moss Timothy
Published: October 2022

Bacille-Calmette Guérin (BCG) modulates atherosclerosis development in experimental animals, but it remains unclear whether neonatal BCG vaccination is pro- or anti-atherogenic. Many animal models differ fundamentally from BCG administration to human infants in terms of age, vaccine preparation, dosing schedule, and route of administration. We aimed to elucidate the effect of neonatal subcutaneous BCG vaccination—analogous to human BCG vaccination—on atherosclerosis development in ApoE−/− mice. At 2 days of age, a total of 40 ApoE−/− mice received either a weight-equivalent human dose of BCG, or saline, subcutaneously. From 4 weeks onwards, the mice were fed a Western-type diet containing 22% fat. At 16 weeks of age, mice were sacrificed for the assessment of atherosclerosis. Body weight, plasma lipids, atherosclerosis lesion size and collagen content were similar in both groups. Atherosclerosis lesion number was lower in mice that received BCG. Macrophage content was 20% lower in the BCG-vaccinated mice (p < 0.05), whereas plaque lipid content was increased by 25% (p < 0.01). In conclusion, neonatal BCG vaccination reduces atherosclerosis plaque number and macrophage content but increases lipid content in a murine model of atherosclerosis. Human epidemiological and mechanistic studies are warranted to investigate whether neonatal BCG vaccination is potentially atheroprotective.
Isolation of a Novel Thermophilic Methanogen and the Evolutionary History of the Class Methanobacteria
Authors: Lv Zhenbo , Ding Jiaxin , Wang Heng , Wan Jiaxin , Chen Yifan , Liang Lewen , Yu Tiantian , Wang Yinzhao , Wang Fengping
Published: October 2022

Methanogens can produce methane in anaerobic environments via the methanogenesis pathway, and are regarded as one of the most ancient life forms on Earth. They are ubiquitously distributed across distinct ecosystems and are considered to have a thermophilic origin. In this study, we isolated, pure cultured, and completely sequenced a single methanogen strain DL9LZB001, from a hot spring at Tengchong in Southwest China. DL9LZB001 is a thermophilic and hydrogenotrophic methanogen with an optimum growth temperature of 65 °C. It is a putative novel species, which has been named Methanothermobacter tengchongensis—a Class I methanogen belonging to the class Methanobacteria. Comparative genomic and ancestral analyses indicate that the class Methanobacteria originated in a hyperthermal environment and then evolved to adapt to ambient temperatures. This study extends the understanding of methanogens living in geothermal niches, as well as the origin and evolutionary history of these organisms in ecosystems with different temperatures.
Correction: Torres et al. Twentieth-Century Paleoproteomics: Lessons from Venta Micena Fossils. Biology 2022, 11, 1184
Authors: Torres Jesús M. , Borja Concepción , Gibert Luis , Ribot Francesc , Olivares Enrique G.
Published: October 2022

There was an error in the original publication [...]
Effects of Atomoxetine on Motor and Cognitive Behaviors and Brain Electrophysiological Activity of Dopamine Transporter Knockout Rats
Authors: Ptukha Maria , Fesenko Zoia , Belskaya Anastasia , Gromova Arina , Pelevin Arseniy , Kurzina Natalia , Gainetdinov Raul R. , Volnova Anna
Published: October 2022

Changes in dopaminergic and noradrenergic transmission are considered to be the underlying cause of attention deficit and hyperactivity disorder (ADHD). Atomoxetine (ATX) is a selective norepinephrine transporter (NET) inhibitor that is currently used for ADHD treatment. In this study, we aimed to evaluate the effect of atomoxetine on the behavior and brain activity of dopamine transporter knockout (DAT-KO) rats, which are characterized by an ADHD-like behavioral phenotype. Prepulse inhibition (PPI) was assessed in DAT-KO and wild type rats after saline and ATX injections, as well as behavioral parameters in the Hebb–Williams maze and power spectra and coherence of electrophysiological activity. DAT-KO rats demonstrated a pronounced behavioral and electrophysiological phenotype, characterized by hyperactivity, increased number of errors in the maze, repetitive behaviors and disrupted PPI, changes in cortical and striatal power spectra and interareal coherence. Atomoxetine significantly improved PPI and decreased repetitive behaviors in DAT-KO rats and influenced behavior of wild-type rats. ATX also led to significant changes in power spectra and coherence of DAT-KO and wild type rats. Assessment of noradrenergic modulation effects in DAT-KO provides insight into the intricate interplay of monoaminergic systems, although further research is still required to fully understand the complexity of this interaction.
Lipidomics Revealed Plasma Phospholipid Profile Differences between Deceased and Recovered COVID-19 Patients
Authors: Žarković Neven , Orehovec Biserka , Baršić Bruno , Tarle Marko , Kmet Marta , Lukšić Ivica , Tatzber Franz , Wonisch Willibald , Skrzydlewska Elżbieta , Łuczaj Wojciech
Published: October 2022

Thorough understanding of metabolic changes, including lipidome alteration, associated with the development of COVID-19 appears to be crucial, as new types of coronaviruses are still reported. In this study, we analyzed the differences in the plasma phospholipid profiles of the deceased COVID-19 patients, those who recovered and healthy people. Due to identified abnormalities in plasma phospholipid profiles, deceased patients were further divided into two subgroups (D1 and D2). Increased levels of phosphatidylethanolamines (PE), phosphatidylcholines (PC) and phosphatidylserines (PS) were found in the plasma of recovered patients and the majority of deceased patients (first subgroup D1) compared to the control group. However, abundances of all relevant PE, PC and PS species decreased dramatically in the plasma of the second subgroup (D2) of five deceased patients. These patients also had significantly decreased plasma COX-2 activity when compared to the control, in contrast to unchanged and increased COX-2 activity in the plasma of the other deceased patients and recovered patients, respectively. Moreover, these five deceased patients were characterized by abnormally low CRP levels and tremendous increase in LDH levels, which may be the result of other pathophysiological disorders, including disorders of the immune system, liver damage and haemolytic anemia. In addition, an observed trend to decrease the autoantibodies against oxidative modifications of low-density lipoprotein (oLAb) titer in all, especially in deceased patients, indicate systemic oxidative stress and altered immune system that may have prognostic value in COVID-19.
Quality Evaluation of Ophiopogon japonicus from Two Authentic Geographical Origins in China Based on Physicochemical and Pharmacological Properties of Their Polysaccharides
Authors: Chen Zherui , Zhu Baojie , Peng Xin , Li Shaoping , Zhao Jing
Published: October 2022

Ophiopogon japonicus is widely used as a tonic herb in China. According to the origins, MaiDong of Chinese materia medica can be classified as Zhe MaiDong (Ophiopogon japonicus in Zhejiang), Chuan MaiDong (Ophiopogon japonicus in Sichuan), Duanting Shan MaiDong (Liriope muscari), and Hubei MaiDong (Liriope spicata). In terms of quality control, polysaccharides-based evaluations have not yet been conducted. In this study, microwave-assisted extraction (MAE) was used for the preparation of polysaccharides from 29 batches of MaiDong. HPSEC-MALLS-RID and HPAEC-PAD were employed to investigate their molecular parameters and compositional monosaccharides, respectively. The ability to scavenge ABTS radicals and immune promotion abilities, in terms of nitric oxide releasing and phagocytosis on RAW 264.7 macrophages, were also compared. The results showed that polysaccharides in different MaiDong varied in molecular parameters. All polysaccharides mainly contained fructose and glucose with small amounts of arabinose, mannose, galactose, and xylose. For polysaccharides of Zhe MaiDong and Chuan MaiDong, the molar ratio of Fru to Glc was roughly 15:1 and 14:1, respectively. Zhe MaiDong exhibited better antioxidant and immune promotion activity, and so did that of fibrous roots. The pharmacological activity, however, did not account for the variation in growth years. Finally, indicators for quality control based on multivariate statistical analysis included: yield, antioxidant activity, the content of fructose, and RI signal. It was concluded that MaiDong’s fibrous roots had similar components to the root, and their quality was not significantly affected by growth age. This may provide some guidance for the cultivation and use of MaiDong.