bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment of Cranial Deformation Indices by Automatic Smartphone-Based Photogrammetric Modelling
Authors: Baselga Sergio , Mora-Navarro Gaspar , Lerma José Luis
Published: November 2022

This paper presents research carried out to assess the accuracy of a fully automatic smartphone-based photogrammetric solution (PhotoMeDAS) to obtain a cranial diagnostic based on the 3D head model. The rigorous propagation of the coordinate measurement uncertainty to the infant’s derived cranial deformation indices is demonstrated. The cranial anthropometric parameters and cranial deformation indices that PhotoMeDAS calculates automatically were analysed based on the estimated accuracy and uncertainty. To obtain both accuracy and uncertainty, a dummy head was measured 54 times under different conditions. The same head was measured with a top-of-the-line coordinate-measuring machine (CMM), and the results were used as ground-truth data. It is demonstrated that the PhotoMeDAS 3D models are an average of 1.01 times bigger than the corresponding ground truth, and the uncertainties are around 1 mm. Even assuming uncertainties in the coordinates of up to 1.5 mm, the error in the derived deformation index uncertainties is around 1%. In conclusion, the PhotoMeDAS solution improves the uncertainty obtained in an ordinary paediatric consultation and can be recommended as a tool for doctors to establish an adequate medical diagnosis based on comprehensive cranial deformation indices, which is much more precise and complete than the information obtained by existing analogue devices (measuring tapes and callipers) and easier to use and less expensive than radiological imaging (CT and MRI).
Design of Static Random-Access Memory Cell for Fault Tolerant Digital System
Authors: Yoon Taehwan , Park Jihwan , Jeong Hanwool
Published: November 2022

This paper comparatively analyzes the static random-access memory (SRAM) cell designs for fault tolerance. Since SRAM cells are sensitive to radiation-induced single event upsets, various circuit-level approaches have been applied. Compared to the conventional SRAM cell circuits, one possibility is adding redundant storage nodes by means of additional transistors. The strength and weakness of the SRAM cells in terms of various performance aspects—speed, area, power, stability, fault tolerance, etc.—according to the design approaches are compared analytically and discussed. The discussion concludes that, in the future, it is paramount to develop an SRAM cell design with a mitigated trade-off between read/write performance and SEU tolerance.
Identification of the Kinetic Parameters of Thermal Micro-Organisms Inactivation
Authors: Bondarchuk Ivan , Perevozkin Valery , Bondarchuk Sergey , Vorozhtsov Alexander
Published: November 2022

A mathematical model for estimating the characteristics of the process of thermal inactivation of vegetative bacterial cells and their spores is presented. The model relates the change rate of the number of living cells as a nonlinear kinetic dependence of the p-th order, and the temperature constant of their inactivation rate is the Arrhenius function. A method for solving the inverse kinetic problem of identifying the parameters of this model from experimental data is proposed. The method is implemented through the minimization of the original functional, which reduces the number of variable parameters. The solution results of inverse problems for determining the kinetic model parameters based on the experimental data of thermal inactivation of bacterial spores B. subtilis and B. anthracis are presented. The obtained parameters are used to solve the direct problems of the dynamics of micro-organism inactivation. The calculation results represent the dependence on the time of the change number of inactivated micro-organisms, and the thermal exposure time for 99% of their deaths at different temperatures. A comparison of the results with other authors’ calculations and experimental data confirms the adequacy of the model, the high accuracy of the new solution method and the algorithm for its implementation. The developed model of thermal sterilization can be used for the selective deactivation of pathogens in the food products.
OADC: An Obstacle-Avoidance Data Collection Scheme Using Multiple Unmanned Aerial Vehicles
Authors: Rahman Shakila , Akter Shathee , Yoon Seokhoon
Published: November 2022

Unmanned aerial vehicles (UAVs) are used widely for data collection in wireless sensor networks (WSNs). UAVs visit the sensors to collect the data. UAV-aided data collection is a challenging problem because different paths of a UAV, i.e., visiting orders of sensors, affect energy consumption and data delivery times. The problem becomes more difficult when there are obstacles in the path of the UAV. Thus, the UAV needs to take a detour to avoid them, resulting in different travel distances and times. Therefore, this study formulated the obstacle-aware path planning problem of UAVs, i.e., the obstacle-constrained distance minimization (OCDM) problem, as an integer linear programming problem (ILP) to minimize the total traveling distances of all UAVs while considering the UAVs’ flight time constraints. First, a possible detour-points-selection algorithm called vector rotation-angle-based obstacle avoidance (VRAOA) is proposed to find the detour points around each obstacle in the environment. Then, a genetic algorithm with VRAOA (GA w/VRAOA)is developed to find the trajectories of the UAVs, using the VRAOA and Dijkstra algorithm to find a detour path if there is an obstacle between any two sensors. Finally, simulations were performed for algorithm variants, where GA w/VRAOA outperformed others.
Robust Near-Optimal Aerocapture Guidance Method Based on Saturation Function
Authors: Chen Jilin , Han Hongwei , Teng Rui , Qin Tong
Published: November 2022

Aerocapture maneuvers refer to a single atmospheric crossing to deplete orbital energy and establish a closed orbit. During the atmospheric flight, adjusting the spacecraft’s vertical lift component in an optimal manner, bang-bang bank control, will minimize the propulsion fuel consumption required to establish the target orbit. However, such methods have been suffering from the performance’s oversensitivity to the control’s instantaneous switching time and poor robustness. To address these problems, we propose a new numerical predictor-corrector guidance algorithm based on the saturation function profile in this paper. The saturation function is used to basically simulate the bang-bang control structure, which enhances the algorithm’s robustness by reducing its dependence on the relevant parameters without losing too much optimality. Monte Carlo simulations in both Earth and Mars scenarios demonstrate the robustness, accuracy, and near-optimal performance of the proposed guidance method.
OTSU Multi-Threshold Image Segmentation Based on Improved Particle Swarm Algorithm
Authors: Zheng Jianfeng , Gao Yinchong , Zhang Han , Lei Yu , Zhang Ji
Published: November 2022

In view of the slow convergence speed of traditional particle swarm optimization algorithms, which makes it easy to fall into local optimum, this paper proposes an OTSU multi-threshold image segmentation based on an improved particle swarm optimization algorithm. After the particle swarm completes the iterative update speed and position, the method of calculating particle contribution degree is used to obtain the approximate position and direction, which reduces the scope of particle search. At the same time, the asynchronous monotone increasing social learning factor and the asynchronous monotone decreasing individual learning factor are used to balance global and local search. Finally, chaos optimization is introduced to increase the diversity of the population to achieve OTSU multi-threshold image segmentation based on improved particle swarm optimization (IPSO). Twelve benchmark functions are selected to test the performance of the algorithm and are compared with the traditional meta-heuristic algorithm. The results show the robustness and superiority of the algorithm. The standard dataset images are used for multi-threshold image segmentation experiments, and some traditional meta-heuristic algorithms are selected to compare the calculation efficiency, peak signal to noise ratio (PSNR), structural similarity (SSIM), feature similarity (FSIM), and fitness value (FITNESS). The results show that the running time of this paper is 30% faster than other algorithms in general, and the accuracy is also better than other algorithms. Experiments show that the proposed algorithm can achieve higher segmentation accuracy and efficiency.
Few-Layer Graphene as an Efficient Buffer for GaN/AlN Epitaxy on a SiO2/Si Substrate: A Joint Experimental and Theoret-ical Study
Authors: Borisenko Denis Petrovich , Gusev Alexander Sergeevich , Kargin Nikolay Ivanovich , Dobrokhotov Petr Leonidovich , Timofeev Alexey Afanasievich , Labunov Vladimir Arkhipovich , Mikhalik Mikhail Mikhailovich , Katin Konstantin Petrovich , Maslov Mikhail Mikhailovich , Dzhumaev Pavel Sergeevich , Komissarov Ivan Vladimirovich
Published: November 2022

Single-layer (SLG)/few-layer (FLG) and multilayer graphene (MLG) (>15 layers) samples were obtained using the CVD method on high-textured Cu foil catalysts. In turn, plasma-assisted molecular beam epitaxy was applied to carry out the GaN graphene-assisted growth. A thin AlN layer was used at the initial stage to promote the nucleation process. The effect of graphene defectiveness and thickness on the quality of the GaN epilayers was studied. The bilayer graphene showed the lowest strain and provided optimal conditions for the growth of GaN/AlN. Theoretical studies based on the density functional theory have shown that the energy of interaction between graphene and AlN is almost the same as between graphite sheets (194 mJ/m2). However, the presence of vacancies and other defects as well as compression-induced ripples and nitrogen doping leads to a significant change in this energy.
A Novel Fluorescent-Material-Based Simple Method for Sunscreen Evaluation
Authors: Nakamura Kae , Kono Takahiro , Rajagopalan Uma Maheswari , Yamada Jun
Published: November 2022

ISO standards exist for evaluating sunscreens, such as those based on visual inspection. This assessment yields subjective results and is thus unreliable. Therefore, to verify the results of the visual assessment of sunscreens, quantitative evaluation methods are necessary. These methods require the measurement of the total radiation energy that is diffusely transmitted in all directions. For the measurements, although an integrating sphere is widely used to measure diffusely transmitted radiation, a simpler measurement would contribute to the easy usage of quantitative and objective evaluation. We propose the use of fluorescent materials as an alternative method to characterize sunscreens. In this method, a layer containing a fluorescent material is placed behind the sunscreen, and when the excitation radiation transmitted through the sunscreen reaches the fluorescent layer, it emits fluorescence. The feasibility of this measurement method was evaluated through numerical analysis and it demonstrated that hemispheric transmittance can be measured when the fluorescent layer is of high concentration or thick. Additionally, a prototype fluorescent layer was fabricated, and also the results were compared with the amount of diffusely transmitted UV from several commercial sunscreens. This pilot evaluation measurement method showed that the UV shielding index shown on the package does not necessarily truly reflect the amount of UV energy transmitted through the sunscreen, thus failing to provide the expected protection.
Enhancement of Question Answering System Accuracy via Transfer Learning and BERT
Authors: Duan Kai , Du Shiyu , Zhang Yiming , Lin Yanru , Wu Hongzhuo , Zhang Quan
Published: November 2022

Entity linking and predicate matching are two core tasks in the Chinese Knowledge Base Question Answering (CKBQA). Compared with the English entity linking task, the Chinese entity linking is extremely complicated, making accurate Chinese entity linking difficult. Meanwhile, strengthening the correlation between entities and predicates is the key to the accuracy of the question answering system. Therefore, we put forward a Bidirectional Encoder Representation from Transformers and transfer learning Knowledge Base Question Answering (BAT-KBQA) framework, which is on the basis of feature-enhanced Bidirectional Encoder Representation from Transformers (BERT), and then perform a Named Entity Recognition (NER) task, which is appropriate for Chinese datasets using transfer learning and the Bidirectional Long Short-Term Memory-Conditional Random Field (BiLSTM-CRF) model. We utilize a BERT-CNN (Convolutional Neural Network) model for entity disambiguation of the problem and candidate entities; based on the set of entities and predicates, a BERT-Softmax model with answer entity predicate features is introduced for predicate matching. The answer ultimately chooses to integrate entities and predicates scores to determine the definitive answer. The experimental results indicate that the model, which is developed by us, considerably enhances the overall performance of the Knowledge Base Question Answering (KBQA) and it has the potential to be generalizable. The model also has better performance on the dataset supplied by the NLPCC-ICCPOL2016 KBQA task with a mean F1 score of 87.74% compared to BB-KBQA.
3D Model Retrieval Algorithm Based on DSP-SIFT Descriptor and Codebook Combination
Authors: Hu Yuefan , Zhang Haoxuan , Gao Jing , Li Nan
Published: November 2022

Recently, extensive research efforts have been dedicated to view-based 3D object retrieval, owing to its advantage of using a set of 2D images to represent 3D objects. Some existing image processing technologies can be employed. In this paper, we adopt Bag-of-Words for view-based 3D object retrieval. Instead of SIFT, DSP-SIFT is extracted from all images as object features. Moreover, two codebooks of the same size are generated by approximate k-means. Then, we combine two codebooks to correct the quantization artifacts and improve recall. Bayes merging is applied to address the codebook correlation (overlapping among different vocabularies) and to provide the benefit of high recall. Moreover, Approximate Nearest Neighbor (ANN) is used to quantization. Experimental results on ETH-80 datasets show that our method improves the performance significantly compared with the state-of-the-art approaches.
From Neuroimaging to Computational Modeling of Burnout: The Traditional versus the Fuzzy Approach—A Review
Authors: Mikołajewska Emilia , Prokopowicz Piotr , Chow YeeKong , Masiak Jolanta , Mikołajewski Dariusz , Wójcik Grzegorz Marcin , Wallace Brian , Eugene Andy R. , Olajossy Marcin
Published: November 2022

Occupational burnout, manifested by emotional exhaustion, lack of a sense of personal achievement, and depersonalization, is not a new phenomenon, but thusfar, there is no clear definition or diagnostic guidelines. The aim of this article wasto summarize all empirical studies to date that have used medical neuroimaging techniques to provide evidence or links regarding changes in brain function in occupational burnout syndrome from a neuroscientific perspective, and then use these to propose a fuzzy-based computational model of burnout.A comprehensive literature search was conducted in two major databases (PubMed and Medline Complete). The search period was 2006–2021, and searches were limited to the English language. Each article was carefully reviewed and appropriately selected on the basis of raw data, validity of methods used, clarity of results, and scales for measuring burnout. The results showed that the brain structures of patients with job burnout that are associated with emotion, motivation, and empathy weresignificantly different from healthy controls. These altered brain regions included the thalamus, hippocampus, amygdala, caudate, striatum, dorso-lateral prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex, anterior insula, inferior frontal cingulate cortex, middle frontal cingulate cortex, temporoparietal junction, and grey matter. Deepening our understanding of how these brain structures are related to burnout will pave the way for better approaches fordiagnosis and intervention. As an alternative to the neuroimaging approach, the paper presents a late proposal of the PLUS (personal living usual satisfaction) parameter. It is based on a fuzzy model, wherein the data source is psychological factors—the same or similar to the neuroimaging approach. As the novel approach to searching for neural burnout mechanisms, we have shown that computational models, including those based on fuzzy logic and artificial neural networks, can play an important role in inferring and predicting burnout. Effective computational models of burnout are possible but need further development to ensure accuracy across different populations. There is also a need to identify mechanisms and clinical indicators of chronic fatigue syndrome, stress, burnout, and natural cognitive changes associated with, for example, ageing, in order to introduce more effective differential diagnosis and screening.
Experimental Research to Determine the Effect of Ultrasound in Drying Bo Chinh Ginseng by Ultrasound-Assisted Heat Pump Drying Method
Authors: Nguyen Hay , Le Quang-Huy , Le Thanh-Dat , Pham Van-Kien
Published: November 2022

This study focused on the experimental drying of Bo Chinh ginseng by the ultrasound-assisted heat pump drying method, in which the effects of drying air temperature (T), ultrasonic power (P), intermittency ratio of ultrasound generator (A) on the moisture effective diffusion coefficient (Deff), saponin content (Sp) and color change (dE) during the drying process were determined. The results showed that the drying time was reduced from 12.5 h at 35 °C to 8.9 h at 40 °C and greatly reduced to 5.8 h at 55 °C. The moisture diffusion coefficient Deff and color change index increased with the increase in drying temperature. Meanwhile, from 35 °C to 45 °C, the saponin content after drying tended to increase gradually, but when the temperature continued to rise from 45 °C to 55 °C, the saponin content decreased. The effect of ultrasonic power in the drying process was in particular as follows. The drying time of 8.8 h at 40 W ultrasonic power reduced to 7.8 h at 80 W ultrasonic power, and reduced to 7 h at 160 W ultrasonic power. The remaining saponin content after drying tended to increase gradually at the power level of 40–120 W (from 89.2% to 95.2%) and decrease when the power increased from 120 to 160 W (from 95.2% to 90.5%). The moisture diffusion coefficient Deff also increased with the increase in ultrasonic power. Meanwhile, the color change of dried products decreased as the ultrasonic power increased in the range of 40–120 W but increased with the ultrasonic power range from 120 to 160 W. Additionally, the experimental method and Box–Behnken design were used for optimizing the drying process with the optimal drying conditions such as drying air temperature of 45.2 °C, ultrasonic power of 127.7 W and intermittency ratio of ultrasound generator of 0.18.
Cutting Force When Machining Hardened Steel and the Surface Roughness Achieved
Authors: Osička Karel , Zouhar Jan , Sliwková Petra , Chladil Josef
Published: November 2022

This article deals primarily with the problem of determining the cutting force when machining hardened steels. For this study, the steel used was 100 Cr6, number 1.3505. The secondary aspects of the study focused on the evaluation of the surface quality of machined samples and the recommendation of cutting conditions. A wide variety of components are used in engineering, the final heat treatment of which is hardening. These components are usually critical in a particular product. The quality of these components determines the correct functioning of the entire body of technical equipment, and ultimately, its service life. In our study, these are the core parts of thrust bearings, specifically the rolling elements. The subject of this experiment involves machining these components in the hardened state with cubic boron nitride tools and the continuous measurement of the cutting force using a dynamometer. The machining is carried out on a conventional lathe. A total of 12 combinations of cutting conditions were set. Specifically, for three cutting speeds of 130, 155 and 180 m·min−1, the feed rates of 0.05 and 0.1 mm·rev−1 and the cutting widths of 0.2 and 0.35 mm, were evaluated The evaluation assessed the surface quality by both touch and non-touch methods. A structural equation with the appropriate constants and exponents was then constructed from the data obtained using the dynamometer. The experiment confirmed the potential of achieving a value of the average arithmetic profile deviation Ra in the range of 0.3–0.4 when turning hardened steels with cubic boron nitride.
A Simulation and Verification Platform for Avionics Systems Based on Future Airborne Capability Environment Architecture
Authors: Du Xiaoyan , Du Chenglie , Chen Jinchao , Yang Mei , Yu Wenquan
Published: November 2022

Avionics systems, which determine the performance, stability, and safety of aircraft, are a crucial part of aircraft. With the rapid development of the aviation industry, there are many serious problems in the process of the traditional simulation and verification of avionics systems, especially in the aspects of poor reusability of the hardware and software, poor real-time data interaction, and the high cost of development. In order to solve these problems, a simulation and verification platform for avionics systems based on the Future Airborne Capability Environment (FACE) architecture has been designed by using component and memory database technology. First, a general architecture is designed by referencing the FACE architecture, which allows flexible access to software and hardware resources of avionics systems. Second, the key technologies involved in the platform are described in detail, including scheduling management, communication management, and configuration management, which provide technical support for the simulation and verification of avionics systems. Finally, the simulation and verification environment of avionics systems is established, which realizes data interaction and management of various models, and improves the efficiency of the development and implementation of avionics systems.
Management of Severe Asthma in Eosinophilic Granulomatosis with Polyangiitis with Interleukin-5-Targeted Therapies: Current Status and Report of Two Cases
Authors: Romano Ciro , Cozzolino Domenico , Sellitto Ausilia , Rinaldi Luca
Published: November 2022

Eosinophilic granulomatosis with polyangiitis (EGPA) is a systemic disorder characterized by peripheral eosinophilia, severe eosinophilic asthma, sinusitis, transient pulmonary infiltrates, and features of medium/small-vessel vasculitis. EGPA belongs to the group of anti-neutrophil cytoplasm antibody (ANCA)-associated vasculitides, although only 30 to 40% of patients display ANCA positivity, which is mainly of myeloperoxidase (MPO) specificity. Particularly, ANCA-positive patients typically show vasculitic features. Interleukin (IL)-5 has been demonstrated to play a crucial role in determining eosinophilic airway inflammation in EGPA patients. Specifically, maturation, activation, and survival of eosinophils especially depend on IL-5 availability. Therefore, blocking IL-5 biological activity may be a rewarding strategy for control of eosinophilic inflammation. Several monoclonal antibodies with the ability to interfere with the biological activity of IL-5 have been developed, namely, mepolizumab, reslizumab, and benralizumab. Here, we discuss the role of these drugs in the management of severe eosinophilic asthma in the context of EGPA and report the outcome of two EGPA patients with severe eosinophilic asthma treated at our outpatient clinic.
Supervised Learning Algorithm for Predicting Mortality Risk in Older Adults Using Cardiovascular Health Study Dataset
Authors: Navarrete Jean Paul , Pinto Jose , Figueroa Rosa Liliana , Lagos Maria Elena , Zeng Qing , Taramasco Carla
Published: November 2022

Multiple chronic conditions are an important factor influencing mortality in older adults. At the same time, cardiovascular events in older adult patients are one of the leading causes of mortality worldwide. This study aimed to design a machine learning model capable of predicting mortality risk in older adult patients with cardiovascular pathologies and multiple chronic diseases using the Cardiovascular Health Study database. The methodology for algorithm design included (i) database analysis, (ii) variable selection, (iii) feature matrix creation and data preprocessing, (iv) model training, and (v) performance analysis. The analysis and variable selection were performed through previous knowledge, correlation, and histograms to visualize the data distribution. The machine learning models selected were random forest, support vector machine, and logistic regression. The models were trained using two sets of variables. First, eight years of the data were summarized as the mode of all years per patient for each variable (123 variables). The second set of variables was obtained from the mode every three years (369 variables). The results show that the random forest trained with the second set of variables has the best performance (89% accuracy), which is better than other reported results in the literature.
In Silico Evaluation of a Physiological Controller for a Rotary Blood Pump Based on a Sensorless Estimator
Authors: Bakouri Mohsen , Alassaf Ahmad , Alshareef Khaled , AlMohimeed Ibrahim , Alqahtani Abdulrahman , Aboamer Mohamed Abdelkader , Alonazi Khalid A. , Alharbi Yousef
Published: November 2022

In this study, we present a sensorless, robust, and physiological tracking control method to drive the operational speed of implantable rotary blood pumps (IRBPs) for patients with heart failure (HF). The method used sensorless measurements of the pump flow to track the desired reference flow (Qr). A dynamical estimator model was used to estimate the average pump flow (Q^est) based on pulse-width modulation (PWM) signals. A proportional-integral (PI) controller integrated with a fuzzy logic control (FLC) system was developed to automatically adapt the pump flow. The Qr was modeled as a constant and trigonometric function using an elastance function (E(t)) to achieve a variation in the metabolic demand. The proposed method was evaluated in silico using a lumped parameter model of the cardiovascular system (CVS) under rest and exercise scenarios. The findings demonstrated that the proposed control system efficiently updated the pump speed of the IRBP to avoid suction or overperfusion. In all scenarios, the numerical results for the left atrium pressure (Pla), aortic pressure (Pao), and left ventricle pressure (Plv) were clinically accepted. The Q^est accurately tracked the Qr within an error of 0.25 L/min.
Exploring Transaction Security on Consumers’ Willingness to Use Mobile Payment by Using the Technology Acceptance Model
Authors: Tsai Shuo-Chang , Chen Chih-Hsien , Shih Keng-Chang
Published: November 2022

In recent years, with the increase in Fintech innovation, mobile payment has played an important role. This research is to investigate factors affecting consumers’ willingness to use mobile payment. The study found that perceived ease of use and perceived usefulness have a significant positive impact on consumer’s adoption of mobile payments. In addition, from empirical research on the mediating effect of transaction security on attitudes toward using it and behavioral intention to use, the study found that transaction security has a significant mediating effect, and empirical data shows that transaction security can strengthen consumers’ behavior towards using mobile payment intention, this also explained why the penetration rate of mobile payments in developed countries is lower than in developing countries. In summary, to encourage consumers to willingly use the new mobile payment tool, in addition to making the tool easy to use and useful, it is crucial that transaction security can assure consumers’ willingness to use mobile payment.
Assessment of Two Drought Indices to Quantify and Characterize Drought Incidents: A Case Study of the Northern Part of Burundi
Authors: Ndayiragije Jean Marie , Li Fan , Nkunzimana Athanase
Published: November 2022

Droughts are natural catastrophes that cost the health and wealth of humans due to their harmful effects on the natural environment, ecology, hydrology, and agriculture in particular. Droughts are recurring incidents that last for prolonged periods of time in the northern part of Burundi. Despite the region being prone to drought and often suffering from dry conditions, drought has not been widely investigated. For the quantification and characterization of dryness conditions, this research utilized two drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI), at 2-, 6-, 24-, and 48-month timescales, where 2-, 6-, 24-, and 48-months correspond to agricultural and hydrological droughts, respectively. The two drought indices were compared, and the difference between SPEI and SPI was illustrated by quantifying and characterizing drought incidents. The findings revealed that different types of droughts threatened the northern part of Burundi during the periods of 1993–2000 and 2002–2009. Both indices illustrated that 2005, 2006, and 2007 were extremely dry years. The drought incidents detected by the SPEI index were classified into moderate and severe categories, characterized by long duration and greater magnitude. In contrast, the drought incidents detected by SPI were classified into the “extremely dry” category, characterized by limited duration and lower magnitude but with higher intensities. This research highlighted that SPEI differs from SPI in quantifying and characterizing droughts and highly suggests the use of both SPEI and SPI when assessing droughts. The outcome of this study will be useful in drought prevention and mitigation strategies across Burundi, specifically for agricultural purposes.
Investigation of the Parameters Influencing Baseline Ozone in the Western United States: A Statistical Modeling Approach
Authors: Ninneman Matthew , Petropavlovskikh Irina , Effertz Peter , Chand Duli , Jaffe Daniel
Published: November 2022

Ground-level ozone (O3) is a key atmospheric gas that controls the oxidizing capacity of the atmosphere and has significant health and environmental implications. Due to ongoing reductions in the concentrations of O3 precursors, it is important to assess the variables influencing baseline O3 to inform pollution control strategies. This study uses a statistical model to characterize daily peak 8 h O3 concentrations at the Mount Bachelor Observatory (MBO), a rural mountaintop research station in central Oregon, from 2006–2020. The model was constrained by seven predictive variables: year, day-of-year, relative humidity (RH), aerosol scattering, carbon monoxide (CO), water vapor (WV) mixing ratio, and tropopause pressure. RH, aerosol scattering, CO, and WV mixing ratio were measured at MBO, and tropopause pressure was measured via satellite. For the full 15-year period, the model represents 61% of the variance in daily peak 8 h O3, and all predictive variables have a statistically significant (p < 0.05) impact on daily peak 8 h O3 concentrations. Our results show that daily peak 8 h O3 concentrations at MBO are well-predicted by the model, thereby providing insight into what affects baseline O3 levels at a rural site on the west coast of North America.
UAV Inspection of Compliance of Fuel Sulfur Content of Sailing Ships in the Pearl River Delta, China
Authors: Hu Jianbo , Deng Mengtao , Peng Shitao , Qi Zhaoyu
Published: November 2022

Air pollutants emitted by ships are one of the major causes of global environmental and human health problems, especially for sulfur oxides (SO2). In this study, a mini-sniffing sensor was mounted on the unmanned aerial vehicle (UAV) to monitor the concentration relationship between CO2 and SO2 in the exhaust gas of sailing ships, then the sulfur content of the ship’s fuel oil was estimated to evaluate the compliance of the fuel sulfur content (FSC) with IMO regulations. In the experiment, the measurement results of the exhaust gas of sailing ships in the Pearl River Delta were presented, the data set from February to April 2022 was provided, and 445 ships were comprehensively analyzed from the perspectives of ship length and ship type. From the experimental results, considering the error of the sensor, the compliance rate of the FSC of sailing ships entering and leaving the Pearl River reached 93.7%. To some extent, the current situation for meeting the 0.5% (m/m) limit is basically optimistic. The results represent the effectiveness of DECA policy implementation. This paper demonstrates the effectiveness and reliability of the UAV monitoring method in monitoring emissions from ships, and in more effectively monitoring the impact of shipping on air quality. Furthermore, an accurate and non-contact monitoring method is proposed, which can allow law enforcement officers to judge in advance whether the ships sailing is suspected of illegally using high-sulfur fuels. It can improve the efficiency of law enforcement and reduce the cost of supervision.
Electron Correlations in Sequential Two-Photon Double Ionization of an Ar Atom
Authors: Lagutin Boris M. , Petrov Ivan D. , Sukhorukov Victor L. , Kilin Victor A. , Novikovskiy Nikolay M. , Demekhin Philipp V. , Ehresmann Arno
Published: November 2022

Sequential two-photon ionization is a process that is experimentally accessible due to the use of new free-electron laser sources for excitation. For the prototypical rare Ar gas atoms, a photoelectron spectrum (PES) corresponding to the second step of the sequential two-photon double ionization (2PDIII) at a photon excitation energy of 65.3 eV was studied theoretically with a focus on the consequences of electron correlations in the considered process. The calculation predicts many intense lines at low photoelectron energies, which cannot be explained on the basis of a one-electron approximation. The processes that lead to the appearance of these lines include many-electron correlations, either in the first or second step of photoionization. A significant fraction of the intensity of the low-energy part of PES is associated with the Auger decay of the excited states formed at the second step of 2PDI. The shape of the low-energy part of the 2PDIII PES is expected to be dependent on both the energy of photon excitations and the flux of the exciting beam.
Towards Optimal Robustness of Network Controllability by Nested-Edge Rectification
Authors: Yu Zhuoran , Nie Junfeng , Li Junli
Published: November 2022

When a network is attacked, the network controllability decreases and the network is at risk of collapse. A network with good controllability robustness can better maintain its own controllability while under attack to provide time for network recovery. In order to explore how to build a network with optimal controllability robustness, an exhaustive search with adding edges was executed on a given set of small-sized networks. By exhaustive search, we mean: (1) All possible ways of adding edges, except self-loops, were considered and calculated at the time of adding each edge. (2) All possible node removal sequences were taken into account. The nested ring structure (NRS) was obtained from the result of the exhaustive search. NRS has a backbone ring, and the remaining edges of each node point to the nearest nodes along the direction of the backbone ring’s edges. The NRS satisfies an empirically necessary condition (ENC) and has great ability to resist random attacks. Therefore, nested edge rectifcation (NER) was designed to optimize the network for controllability robustness by constructing NRS in networks. NER was compared with the random edge rectification (RER) strategy and the unconstrained rewiring (UCR) strategy on synthetic networks and real-world networks by simulation. The simulation results show that NER can better improve the robustness of network’s controllability, and NER can also quickly improve the initial network controllability for networks with more than one driver node. In addition, as NER is executed, NRS gains more edges in the network, so the network has better controllability robustness. NER will be helpful for network model design or network optimization in future.
Effect of Deformation on Safety and Capacity of Li-Ion Batteries
Authors: Wang Genwei , Wu Juanjuan , Zheng Zijun , Niu Lingeng , Pan Lei , Wang Bin
Published: November 2022

Deformations in lithium-ion batteries, which may lead to thermal runaway, can occur during storage and transportation handling, as well as in road use. In this study, both radial and axial compression deformation were produced experimentally to analyze their influence on the performance and safety of lithium-ion batteries. In the radial plate compression experiment, the battery was loaded to different displacements and then charge–discharge cycles were performed. It was found that the greater the deformation of the battery, the smaller the initial capacity and the faster the capacity decay. Under axial loading, the voltage of low state of charge (SOCs) batteries showed a clear step-drop phenomenon. The battery was compressed until the first voltage drop, loading was stopped, and the voltage gradually dropped to 0 V. For high-SOC lithium-ion batteries, there was almost no voltage step-down, and a small deformation could cause thermal runaway in the battery. The results showed that the small deformation in the radial direction only reduced the capacity of the battery, but had little impact on its safety, whereas a small deformation in the axial direction was more likely to cause an internal short circuit (ISC).
Electrospun Interconnected Bead-Like P2-NaxCoyMn1−yO2 (x = 0.66, y = 0.1) Cathode Material for Stable Sodium-Ion Storage
Authors: Haridas Anupriya K. , Sadan Milan K. , Kim Joo-Hyung , Lee Younki , Ahn Jou-Hyeon
Published: November 2022

The development of high-rate and long-cycle-life Na-based cathode materials, on par with the performance of commercialized lithium-based cathodes, is crucial to satisfy the recurring surge in energy demand. Here, we report an interconnected bead-like P2-type manganese-based oxide NaxCoyMn1−yO2 (x = 0.66, y = 0.1) synthesized by electrospinning and subsequent heat treatment as a high-rate cathode material for sodium-ion batteries (SIBs). The employed strategy of one-dimensional morphological design with interconnected bead-like particles profusely enhances Na+ diffusion pathways. This layered cathode material exhibits a stable and superior discharge capacity of 180.0 mAh g−1 at 50 mA g−1 compared to a bare cathode material synthesized via the sol–gel process. Further, a high capacity of 78.3 mAh g−1 was achieved, maintaining excellent capacity retention of 85.0% even after 500 insertion/desertion cycles implying robust Na+ storage properties. High-rate tests also revealed promising electrochemical performances at C-rates as high as 5000 mA g−1, affirming the potential of this layered cathode material for high-rate Na+ storage. Additionally, full SIBs assembled with a NaxCoyMn1−yO2 (x = 0.66, y = 0.1) cathode and a carbon nanofiber (CNF) anode exhibited a high cycle performance, retaining 96.3 mAh g−1 after 100 cycles at 300 mA g−1.
PSO-Driven Feature Selection and Hybrid Ensemble for Network Anomaly Detection
Authors: Louk Maya Hilda Lestari , Tama Bayu Adhi
Published: November 2022

As a system capable of monitoring and evaluating illegitimate network access, an intrusion detection system (IDS) profoundly impacts information security research. Since machine learning techniques constitute the backbone of IDS, it has been challenging to develop an accurate detection mechanism. This study aims to enhance the detection performance of IDS by using a particle swarm optimization (PSO)-driven feature selection approach and hybrid ensemble. Specifically, the final feature subsets derived from different IDS datasets, i.e., NSL-KDD, UNSW-NB15, and CICIDS-2017, are trained using a hybrid ensemble, comprising two well-known ensemble learners, i.e., gradient boosting machine (GBM) and bootstrap aggregation (bagging). Instead of training GBM with individual ensemble learning, we train GBM on a subsample of each intrusion dataset and combine the final class prediction using majority voting. Our proposed scheme led to pivotal refinements over existing baselines, such as TSE-IDS, voting ensembles, weighted majority voting, and other individual ensemble-based IDS such as LightGBM.
Comparison of Osseointegration of Dental Implants Placed in Rabbit Tibia Using Two Dental Laser and Implant Handpiece Systems
Authors: Park Jin-Han , Son Keunbada , Son Young-Tak , Kim Yong-Gun , Suh Jo-Young , Lee Kyu-Bok , Lee Jae-Mok
Published: November 2022

The present study aimed to confirm the usefulness of a multi-laser handpiece system currently under development. Implants were placed in the tibia of rabbits using a conventional separate laser-implant handpiece system (control group; SurgicPro+; NSK, Kanuma, Japan and Epic 10; Biolase, Irvine, CA, USA) and a multi-laser handpiece system (experimental group; BLP 10; Saeshin, Daegu, Korea). Implants were placed in left and right tibias of five rabbits using a conventional laser-implant handpiece system and a multi-laser handpiece system (N = 5 per group). Subsequently, micro-computed tomography (micro-CT; bone-to-implant contact evaluation), implant stability quotient (ISQ) measurement, and histological evaluations were performed to confirm the implant placement results. The independent t-test and the paired t-test were used to compare the ISQ values and the results of the two implant-laser handpiece groups (α = 0.05), respectively. No statistically significant difference in micro-CT, ISQ, and histological evaluations was observed between implant placement by the two systems (p > 0.05) except implant initial stability. The use of the multi-laser handpiece system is expected to produce the same results as a conventional separate laser-implant handpiece system with the higher implant initial stability. Additionally, it will potentially make the clinical environment more pleasant and will provide convenience for the clinicians.
Ocruranus–Eohalobia Sclerites from the Cambrian Stage 2 Yanjiahe Formation in South China: Scleritome Reconstruction and Zoological Affinity
Authors: Song Zuchen , Guo Junfeng , Pan Bing , Qiang Yaqin , Li Guoxiang , Peng Jiaxin , Sun Jie , Han Jian
Published: November 2022

The isolated sclerites of the Ocruranus and Eohalobia group are abundant among the early Cambrian small shelly fossil assemblages, which were recently assigned to the same scleritome as an early member of the polyplacophoran (chiton) stem lineage. However, the scleritome reconstruction and zoological affinities of these sclerites are still controversial due to the lack of exceptionally preserved articulated specimens with in-situ sclerites. Herein, we report new specimens of Ocruranus and Eohalobia sclerites from Member 5 of the Yanjiahe Formation, which provide new insights into the reconstruction of the original scleritome. The Eohalobia sclerites from the Yanjiahe Formation have an extended and upfolded proximal field with dense wrinkles, which seems to be a weakly mineralized structure and acted as a joint with another sclerite, Ocruranus. Comparing the butterfly-shaped proximal field on a unique sclerite of Eohalobia with the sub-apical field on Ocruranus sclerites suggests that the original scleritome of this group may consist of only two types of sclerites: the Ocruranus-type and the Eohalobia-type. The polygonal structure on the internal mold of Eohalobia sclerites is interpreted herein as the muscle attachment zone; their distribution corresponds well with that of the modern chitons, which provides strong evidence to support the close relationship between the Ocruranus–Eohalobia group and the Polyplacophora.
Acute Effects of Neuromuscular Electrical Stimulation on Contralateral Plantar Flexor Neuromuscular Function
Authors: Donnelly Chris , Popesco Timothée , Rossé Julie , Kayser Bengt , Maffiuletti Nicola A. , Place Nicolas
Published: November 2022

Contralateral facilitation, i.e., the increase in contralateral maximal voluntary strength that is observed when neuromuscular electrical stimulation (NMES) is applied to the ipsilateral homonymous muscle, has previously been reported for the knee extensors but the neurophysiological mechanisms remain to be investigated. The aim of this study was to compare plantar flexor contralateral facilitation between a submaximal voluntary contraction (~10% MVC torque) and two evoked contractions (conventional and wide-pulse high-frequency NMES) of the ipsilateral plantar flexors, with respect to a resting condition. Contralateral MVC torque and voluntary activation level were measured in 22 healthy participants while the ipsilateral plantar flexors were at rest, voluntarily contracted or stimulated for 15 s. Additional neurophysiological parameters (soleus H-reflex and V-wave amplitude and tibialis anterior coactivation level) were quantified in a subgroup of 12 participants. Conventional and wide-pulse high-frequency NMES of the ipsilateral plantar flexors did not induce any contralateral facilitation of maximal voluntary strength and activation with respect to the resting condition. Similarly, no alteration of neurophysiological parameters was observed in the different conditions. This absence of contralateral facilitation contrasts with some results previously obtained on the knee extensors but is consistent with the absence of neurophysiological changes on the contralateral soleus.
Distributional Response of the Rare and Endangered Tree Species Abies chensiensis to Climate Change in East Asia
Authors: Dong Peng-Bin , Wang Li-Yang , Wang Ling-Juan , Jia Yun , Li Zhong-Hu , Bai Gang , Zhao Rui-Ming , Liang Wei , Wang Hong-Yan , Guo Feng-Xia , Chen Yuan
Published: November 2022

Globally, increasing temperatures due to climate change have severely affected natural ecosystems in several regions of the world; however, the impact on the alpine plant may be particularly profound, further raising the risk of extinction for rare and endangered alpine plants. To identify how alpine species have responded to past climate change and to predict the potential geographic distribution of species under future climate change, we investigated the distribution records of A. chensiensis, an endangered alpine plant in the Qinling Mountains listed in the Red List. In this study, the optimized MaxEnt model was used to analyse the key environmental variables related to the distribution of A. chensiensis based on 93 wild distribution records and six environmental variables. The potential distribution areas of A. chensiensis in the last interglacial (LIG), the last glacial maximum (LGM), the current period, and the 2050s and 2070s were simulated. Our results showed that temperature is critical to the distribution of A. chensiensis, with the mean temperature of the coldest quarter being the most important climatic factor affecting the distribution of this species. In addition, ecological niche modeling analysis showed that the A. chensiensis distribution area in the last interglacial experiencing population expansion and, during the last glacial maximum occurring, a population contraction. Under the emission scenarios in the 2050s and 2070s, the suitable distribution area would contract significantly, and the migration routes of the centroids tended to migrate toward the southern high-altitude mountains, suggesting a strong response from the A. chensiensis distribution to climate change. Collectively, the results of this study provide a comprehensive and multidimensional perspective on the geographic distribution pattern and history of population dynamics for the endemic, rare, and endangered species, A. chensiensis, and it underscores the significant impact of geological and climatic changes on the geographic pattern of alpine species populations.