bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal Placement of PMU for Fast Robust Power System Dynamic State Estimation Using UKF–GBDT Technique
Authors: Mishra Biswaranjan , Thakur Siddhartha Sankar , Mallick Sourav , Panigrahi Chinmoy Kumar
Published: December 2021

This paper proposes a fast and robust dynamic state estimation technique based on model transformation method using the proposed hybrid technique. The proposed hybrid method is the combination of Unscented Kalman Filter (UKF) and Gradient Boosting Decision Tree (GBDT), hence commonly referred to as the UKF–GBDT technique. The proposed model transformation approach is accomplished by taking the active power generator measured as input variable and derived frequency as rate of change of frequency measurements of phasor measurement units (PMU) as dynamic generator output variable model. The proposed hybrid technique is also formulated to deal with data quality issues, and the rate of change of frequency and frequency measurements may be skewed in the presence of rigorous disruption or communication problems. This permits to obtain discrete-time linear dynamic equations in state space based on the linear Kalman filter (LKF). With this proper control, this model alleviates filter divergence problems, which can be a severe issue if the nonlinear model is utilized in greatly strained operating system conditions, and gives quick estimate of rotor speeds together with angles through transient modes if only the transient stability with control is concerned. In the case of long-term dynamics, the outcome of governor’s response in long-term system dynamics is offset together with mechanical power at rotor speed and the state vector angles for joint evaluation. At last, the performance of the proposed method is simulated in MATLAB/Simulink and the performance is compared to the existing methods like UKF, GBDT and ANN. The proposed technique is simulated under three case studies like IEEE 14-, 30- and 118-bus systems.
Reliability Evaluation of Augmented Cubes on Degree
Authors: Zhang Mingzu , Yang Xiaoli , He Xiaomin , Qin Zhuangyan , Ma Yongling
Published: December 2021

The [Formula: see text]-dimensional augmented cube [Formula: see text], proposed by Choudum and Sunitha in 2002, is one of the most famous interconnection networks of the distributed parallel system. Reliability evaluation of underlying topological structures is vital for fault tolerance analysis of this system. As one of the most extensively studied parameters, the [Formula: see text]-conditional edge-connectivity of a connected graph [Formula: see text], [Formula: see text], is defined as the minimum number of the cardinality of the edge-cut of [Formula: see text], if exists, whose removal disconnects this graph and keeps each component of [Formula: see text] having minimum degree at least [Formula: see text]. Let [Formula: see text], [Formula: see text] and [Formula: see text] be three integers, where [Formula: see text], if [Formula: see text] and [Formula: see text], if [Formula: see text]. In this paper, we determine the exact value of the [Formula: see text]-conditional edge-connectivity of [Formula: see text], [Formula: see text] for each positive integer [Formula: see text] and [Formula: see text], and give an affirmative answer to Shinde and Borse’s corresponding conjecture on this topic in [On edge-fault tolerance in augmented cubes, J. Interconnection Netw. 20(4) (2020), DOI:10.1142/S0219265920500139 ].
An Integrated Double Hybrid Fusion Approach for Image Smoothing
Authors: Kumawat Anchal , Panda Sucheta
Published: December 2021

Often in practice, during the process of image acquisition, the acquired image gets degraded due to various factors like noise, motion blur, mis-focus of a camera, atmospheric turbulence, etc. resulting in the image unsuitable for further analysis or processing. To improve the quality of these degraded images, a double hybrid restoration filter is proposed on the two same sets of input images and the output images are fused to get a unified filter in combination with the concept of image fusion. First image set is processed by applying deconvolution using Wiener Filter (DWF) twice and decomposing the output image using Discrete Wavelet Transform (DWT). Similarly, second image set is also processed simultaneously by applying Deconvolution using Lucy–Richardson Filter (DLR) twice followed by the above procedure. The proposed filter gives a better performance as compared to DWF and DLR filters in case of both blurry as well as noisy images. The proposed filter is compared with some standard deconvolution algorithms and also some state-of-the-art restoration filters with the help of seven image quality assessment parameters. Simulation results prove the success of the proposed algorithm and at the same time, visual and quantitative results are very impressive.
THREE-DIMENSIONAL COMPUTATIONAL MODEL OF EARLY UPPER LIMB DEVELOPMENT
Authors: MILLAN CLARO LUIS FELIPE , MÁRQUEZ FLÓREZ KALENIA , DUQUE-DAZA CARLOS A. , GARZÓN-ALVARADO DIEGO A.
Published: December 2021

Limb development begins during embryogenesis when a series of biochemical interactions are triggered between a particular region of the mesoderm and the ectoderm. These processes affect the morphogenesis and growth of bones, joints, and all the other constituent elements of limbs; nevertheless, how the biochemical regulation affects mesenchymal condensation is not entirely clear. In this study, a three-dimensional computational model is designed to predict the appearance and location of the mesenchymal condensation in the stylopod and zeugopod; the biochemical events were described with reaction–diffusion equations that were solved using the finite elements method. The result of the gene expression in our model was consistent with the one reported in literature; the obtained patterns of Fgf8, Fgf10, and Wnt3a can predict the shape of the mesenchymal condensation of early upper limb development; the simple diffusive patterns of molecules were suitable to explain the areas where sox9 is expressed. Furthermore, our results suggest that the expression of Tgf-[Formula: see text] in the upper limb could be due to the inhibition of retinoic acid. These results suggest the importance of building computational scenarios where pathologies may be comprehensively examined.
Fractionally charged BPS particles in M-string on 3D orbifolds
Authors: Boukaddid S. , Ahl Laamara R. , Drissi L. B. , Saidi E. H. , Zerouaoui J.
Published: December 2021

In this paper, we study the M-string realization of chiral [Formula: see text]-super-conformal field theory in 6 dimensions and its orbifold compactification down to three-dimensional (3D). We analyze its fractionally charged BPS particle spectrum in connection with effective 3D Chern–Simons gauge theory and the supersymmetric fractional quantum Hall effect in [Formula: see text] dimensions. We construct the set of underlying fractionally charged BPS particles in the ground state of the compactified M string and find that it contains 144 BPS states that are generated by four basic quasi-particles (two bosonic-like and two fermionic like) and their CPT conjugate. Two representations of the gauge bosons and the gauginos as condensates of the basic quasiparticles are found and explicit realizations are also given. Other features concerning generalizations are also discussed.
Improved Maxwell Model Describing the Whole Creep Process of Salt Rock and its Programming
Authors: Wang Junbao , Wang Tong , Song Zhanping , Zhang Yuwei , Zhang Qiang
Published: December 2021

Based on the creep test results of salt rock, three stages of changes in the viscosity coefficient with time during the creep process of salt rock were delimited from the perspective of creep rate, namely, gradually increased stage, basically unchanged stage and gradually decreased stage. According to this variation, a nonlinear dashpot was proposed, and its viscosity coefficient was assumed as a function of creep time. Then, the dashpot in the Maxwell model was replaced by this nonlinear dashpot to establish an improved Maxwell model that can describe the whole creep process of rock. The rationality of the improved Maxwell model was verified based on the uniaxial compression creep test results of salt rock and the triaxial compression creep test results of coal. Comparisons of the theoretical curves of the model and test results show good agreement between them, and the model can describe the three stages of the whole creep process of rock with a unified expression, thereby overcoming the shortcomings of the traditional mechanical model that requires segmentation processing. Based on the secondary development platform of the FLAC[Formula: see text] software, the secondary development of the improved Maxwell model was achieved by using VC++ 6.0 development environment, and the computer application program of the model was obtained. Then, the secondary development program of the model was used to simulate the uniaxial compression creep test of salt rock and the triaxial compression creep test of coal. In general, the numerical simulation results are in good agreement with the test results, proving the correctness of the secondary development calculation program of the model.
Nano-Sized Effect on Liquid Phase and Their Energy
Authors: Lee Yu-Hyung , Park Suyoung , Jin Changhyun
Published: December 2021

Regardless of the state of matter, such as solids, liquids, and gases, the smaller the matter size from bulk to nano-scale, especially in the quantum region, the more rapid is the energy increase. To this end, this study introduces the concept of a group system, in which atoms behave as one, and this system is reinterpreted as that comprising temperature–entropy (TS) energy in thermodynamic data. Based on this concept, water was passed through various mesh-like dissolved tubes, where the size and energy of the water group system were observed to change. Thereafter, as the scale and number of the meshes increased, the ozone, chlorine, and oxygen constituents, which are closely related to sterilization and washing, are generated, changing the basic water composition. Thus, this nano-size impact is not limited to solids and could facilitate in revolutionizing the future applications in fluids.
Optimal structure control for earthquake resistance
Authors: Yang Xianyang , Lee James D.
Published: December 2021

This work developed the optimal and active control algorithms applicable to structural control for earthquake resistance. [Lewis, F. L., Vrabie, D. and Syrmos, V. L. [2012] Optimal Control (John Wiley & Sons)] developed a rigorous and comprehensive procedure for the derivation of an optimal control strategy based on the calculus of variation. This work is an application of Lewis’ formulation to the control of a structure for earthquake resistance. We developed a computer software which can be used to generate a dynamic model to simulate a planar structure and to construct the control law. This model also includes the tendon driven actuators, sensors and true history of earthquake excitation. The control law has two parts: (I) the feedback control which depends on the estimate state variables (Kalman filter) and (II) the record of the realistic earthquake excitation. The optimal control problem eventually leads to a two-point boundary value problem whose solution hinges on the knowledge of the entire history of the earthquake excitation. We employ true records of earthquake excitation as input. This approach enables one to solve the Riccati equations rigorously. Then, from the simulation results, one may study the relations between the control algorithm design and the characteristics (frequency, amplitude and duration) of earthquake excitation.
Langevin Equations, Fokker–Planck Equations and Entropic Analysis of a Model-Independent Classical Plasma
Authors: Jacques Kendra Jean , Sharma Preet
Published: December 2021

Plasma dynamics have been studied extensively and there is a fair amount of understanding where the scientific community has reached at. However, there is still a very big gap in completely explaining plasma physics at the classical as well as the quantum level. The dynamics of plasma from an entropic approach are not very well understood or explained. There is too much chaos to account for and even a small deviation in terms of perturbations of any kind makes a sizeable difference. This study is based on the entropic approach where we take a model independent classical plasma. Then we apply Langevin equations and Fokker–Planck equations to explain the entropy generated and entropy produced. Then we study various conditions in which we apply an electric field and a magnetic field and understand the various trends in entropy changes. When we apply the electric field and the magnetic fields independently of each other and together in the plasma model, we see that there is a very important change in the increase in entropy. There are also changes in the plasma flow, but the overall flow does not drastically change since we have considered a model independent plasma. Finally, we show that there are indeed changes to the entropy in a model-independent classical plasma in the various cases as mentioned in this study.
Understanding and Supporting Self-Tracking App Selection
Authors: Lee Jong Ho , Schroeder Jessica , Epstein Daniel A.
Published: December 2021

People often face barriers to selecting self-tracking tools that support their goals and needs, resulting in tools not meeting their expectations and ultimately abandonment. We therefore examine how people approach selecting self-tracking apps and investigate how technology can better support the process. Drawing on past literature on how people select and perceive the features of commercial and research tracking tools, we surface seven attributes people consider during selection, and design a low-fidelity prototype of an app store that highlights these attributes. We then conduct semi-structured interviews with 18 participants to further investigate what people consider during selection, how people select self-tracking apps, and how surfacing tracking-related attributes could better support selection. We find that people often prioritize features related to self-tracking during selection, such as approaches to collecting and reflecting on data, and trial apps to determine whether they would suit their needs. Our results also show potential for technology surfacing how apps support tracking to reduce barriers to selection. We discuss future opportunities for improving self-tracking app selection, such as ways to enhance existing self-tracking app distribution platforms to enable people to filter and search apps by desirable features.
My(o) Armband Leaks Passwords
Authors: Gazzari Matthias , Mattmann Annemarie , Maass Max , Hollick Matthias
Published: December 2021

Wearables that constantly collect various sensor data of their users increase the chances for inferences of unintentional and sensitive information such as passwords typed on a physical keyboard. We take a thorough look at the potential of using electromyographic (EMG) data, a sensor modality which is new to the market but has lately gained attention in the context of wearables for augmented reality (AR), for a keylogging side-channel attack. Our approach is based on neural networks for a between-subject attack in a realistic scenario using the Myo Armband to collect the sensor data. In our approach, the EMG data has proven to be the most prominent source of information compared to the accelerometer and gyroscope, increasing the keystroke detection performance. For our end-to-end approach on raw data, we report a mean balanced accuracy of about 76 % for the keystroke detection and a mean top-3 key accuracy of about 32 % on 52 classes for the key identification on passwords of varying strengths. We have created an extensive dataset including more than 310 000 keystrokes recorded from 37 volunteers, which is available as open access along with the source code used to create the given results.
A CNN-based Human Activity Recognition System Combining a Laser Feedback Interferometry Eye Movement Sensor and an IMU for Context-aware Smart Glasses
Authors: Meyer Johannes , Frank Adrian , Schlebusch Thomas , Kasneci Enkeljeda
Published: December 2021

Smart glasses are considered the next breakthrough in wearables. As the successor of smart watches and smart ear wear, they promise to extend reality by immersive embedding of content in the user's field of view. While advancements in display technology seems to fulfill this promises, interaction concepts are derived from established wearable concepts like touch interaction or voice interaction, preventing full immersion as they require the user to frequently interact with the glasses. To minimize interactions, we propose to add context-awareness to smart glasses through human activity recognition (HAR) by combining head- and eye movement features to recognize a wide range of activities. To measure eye movements in unobtrusive way, we propose laser feedback interferometry (LFI) sensors. These tiny low power sensors are highly robust to ambient light. We combine LFI sensors and an IMU to collect eye and head movement features from 15 participants performing 7 cognitive and physical activities, leading to a unique data set. To recognize activities we propose a 1D-CNN model and apply transfer learning to personalize the classification, leading to an outstanding macro-F1 score of 88.15 % which outperforms state of the art methods. Finally, we discuss the applicability of the proposed system in a smart glasses setup.
ModElec
Authors: He Liang , Wittkopf Jarrid A. , Jun Ji Won , Erickson Kris , Ballagas Rafael Tico
Published: December 2021

Integrating electronics with highly custom 3D designs for the physical fabrication of interactive prototypes is traditionally cumbersome and requires numerous iterations of manual assembly and debugging. With the new capabilities of 3D printers, combining electronic design and 3D modeling workflows can lower the barrier for achieving interactive functionality or iterating on the overall design. We present ModElec---an interactive design tool that enables the coordinated expression of electronic and physical design intent by allowing designers to integrate 3D-printable circuits with 3D forms. With ModElec, the user can arrange electronic parts in a 3D body, modify the model design with embedded circuits updated, and preview the auto-generated 3D traces that can be directly printed with a multi-material-based 3D printer. We demonstrate the potential of ModElec with four example applications, from a set of game controls to reconfigurable devices. Further, the tool was reported as easy to use through a preliminary evaluation with eight designers.
VREED
Authors: Tabbaa Luma , Searle Ryan , Bafti Saber Mirzaee , Hossain Md Moinul , Intarasisrisawat Jittrapol , Glancy Maxine , Ang Chee Siang
Published: December 2021

The paper introduces a multimodal affective dataset named VREED (VR Eyes: Emotions Dataset) in which emotions were triggered using immersive 360° Video-Based Virtual Environments (360-VEs) delivered via Virtual Reality (VR) headset. Behavioural (eye tracking) and physiological signals (Electrocardiogram (ECG) and Galvanic Skin Response (GSR)) were captured, together with self-reported responses, from healthy participants (n=34) experiencing 360-VEs (n=12, 1--3 min each) selected through focus groups and a pilot trial. Statistical analysis confirmed the validity of the selected 360-VEs in eliciting the desired emotions. Preliminary machine learning analysis was carried out, demonstrating state-of-the-art performance reported in affective computing literature using non-immersive modalities. VREED is among the first multimodal VR datasets in emotion recognition using behavioural and physiological signals. VREED is made publicly available on Kaggle1. We hope that this contribution encourages other researchers to utilise VREED further to understand emotional responses in VR and ultimately enhance VR experiences design in applications where emotional elicitation plays a key role, i.e. healthcare, gaming, education, etc.
Evaluation of Subchronic Toxicity and Genotoxicity of Ethanolic Extract of Aster glehni Leaves and Stems
Authors: Lim Mi Kyung , Kim Ju Yeon , Jeong Jeongho , Han Eun Hye , Lee Sang Ho , Lee Soyeon , Kim Sun-Don , Lee Jinu
Published: December 2021

Aster glehni, a traditional plant on Ulleung Island in the Republic of Korea, has been recognized for its multiple medicinal properties. However, potential toxicity and safety analyses of A. glehni have not been previously investigated. Therefore, this study aimed to evaluate the safety profile of ethanolic extract of A. glehni leaves and stems (EAG) in terms of genotoxicity and subchronic oral animal toxicity under OECD guidelines and GLP conditions. Toxicological assessments were performed at doses of 1,250, 2,500, and 5,000 mg/kg/day in a 13-week oral repeated-dose toxicity study of EAG in male and female SD rats. In addition, an Ames test, an in vitro mammalian chromosomal aberration test, and a micronucleus test were performed. No toxicological changes in clinical signs, body weights, water and food consumption, urinalysis, hematology, clinical biochemistry, gross findings, and histopathological examinations were observed in subchronic oral animal toxicity. In addition, EAG gave negative results when evaluated using in vitro and in vivo genotoxicity tests. In conclusion, the no-observed-adverse-effect level (NOAEL) of EAG was considered to be 5,000 mg/kg/day, and no target organs were identified in both sexes of rats. EAG was also classified as nonmutagenic and nonclastogenic in genotoxicity testing. Collectively, these results show a lack of general toxicity and genotoxicity for EAG that supports clinical work for development as a herbal medicine.
A New Decision Support Framework with Picture Fuzzy Information: Comparison of Video Conferencing Platforms for Higher Education in India
Authors: Biswas Sanjib , Pamucar Dragan , Chowdhury Paramita , Kar Samarjit
Published: December 2021

The purpose of this paper is to present a novel extension of a very recently developed multicriteria decision making (MCDM) algorithm known as the preference ranking on the basis of ideal-average distance (PROBID) method in a picture fuzzy (PF) environment. We use the full consistency method (FUCOM) with picture fuzzy numbers (PFNs) for deriving the criteria weights. We attempt to apply our proposed model for addressing a real-life complex decision making problem in social science research that gets influenced by the dynamics of discrete human behaviors. We compare eight popular video conferencing (VC) tools used for teaching-learning and meeting purposes in India using our novel integrated multicriteria decision making (MCDM) framework of FUCOM-PROBID with PF information. The criteria have been derived using the theoretical foundation of usability and user experience (UX). Based on the opinion of the decision makers (DM) or users who took part in the study, we find that ease of operations, compatibility with multiple systems and devices, quality of the voice, and video transmission and features are given more emphasis while Zoom, Microsoft Teams, and Google Meet are found to be preferable options to the users. The result of the proposed model shows stability and robustness as evident from the validation test and sensitivity analysis.
The Impact of Green Finance Development on China’s Energy Structure Optimization
Authors: Wang Hui , Jiang Lili , Duan Hongjun , Wang Yifeng , Jiang Yichen , Lin Xiaoken
Published: December 2021

This paper studies the impact of the development of green finance on China’s energy consumption structure. 17 basic indexes and the improved entropy weight method are used to construct the green finance index (GFI). Multiple regression, panel regression, and spatial regression are used to study the impact of green finance on China’s traditional energy and renewable energy consumption. The results show that there is a positive spatial spillover effect in the development of green finance among provinces in China. The development of green finance contributes to the conversion of traditional to renewable energy consumption. The effect of green finance on the transformation of energy consumption structure is mainly reflected in the direct effect. The green finance in each province not only helps the local development of green energy but also plays a good role in the production and utilization of clean energy consumption in surrounding provinces. Therefore, the government should support the green finance, reduce traditional energy consumption, and increase renewable energy consumption.
Effect of Discectomy on Dynesys Dynamic Fixation in the Treatment of Lumbar Degenerative Diseases
Authors: Zhao Chen , Liu Liehua , Luo Lei , Li Pei , Wang Yiyang , Liang Lichuan , Wen Xueping , Jiang Dianming , Zhou Qiang
Published: December 2021

Objective. To compare the effect of decompression of the spinal canal with or without discectomy on the clinical efficacy of Dynesys dynamic fixation treatment in lumbar degenerative diseases. Methods. A total of 62 patients treated for single-segment lumbar degenerative disease from October 2010 to November 2017 were retrospectively analyzed. All patients underwent decompression of the spinal canal with Dynesys dynamic fixation and were divided into two groups. Twenty-seven patients in group A did not undergo discectomy, and 35 patients in group B underwent discectomy. The intervertebral height, range of motion, Pfirrmann grade of the surgical segment and the upper adjacent segment, function scores, and operation information were compared. Results. All patients were followed up for an average of 30.7 ± 11.5 months. At the final follow-up, the intervertebral height and range of motion of the surgical segment decreased significantly in both group A and B (

p
<
0.05

), the range of motion of the upper adjacent segment increased significantly (

p
<
0.05

), and the intervertebral height did not change significantly (

p
<
0.05

). The retained percentages of surgical segment intervertebral height and ROM in group A were significantly better than those in group B (

p
<
0.05

). The intervertebral height (

p
>
0.05

) and range of motion (

p
<
0.05

) of the surgical segment in group A were higher than those in group B. The surgical segment Pfirrmann grading of group A was better than that of group B (

p
<
0.05

). Conclusion. Dynesys in the treatment of lumbar degenerative diseases may lead to a good clinical effect. In selected cases without discectomy, the range of motion and intervertebral height may be better preserved, and disc degeneration may be reduced.
First-Principles Study on Adsorption and Decomposition of NOx on Mo (110) Surface
Authors: Huang Yunmi , Luo Haijun , Dong Changkun
Published: December 2021

Based on the density functional theory, the adsorption and decomposition of NOx (x = 1, 2) on Mo (110) surface are studied with first-principles calculations. Results show that the stable structures of NO2/Mo (110) are MoNO2 (T, μ1-N), MoNO2 (H, μ3-N, O, O′), MoNO2 (S, η2-O, O′), and MoNO2 (L, η2-O, O′). The corresponding adsorption energies for the structures are −3.83 eV, −3.40 eV, −2.81 eV, and −2.60 eV, respectively. Besides, the stable structures of NO/Mo (110) are MoNO (H, μ1-N), MoNO (H, μ2-N, O), and MoNO (H, η1-N) with the corresponding adsorption energies of −3.75 eV, −3.57 eV, and −3.01 eV, respectively. N and O atoms are easily adsorbed at the hollow sites on Mo (110) surfaces, and their adsorption energies reach −7.02 eV and −7.70 eV, respectively. The preferable decomposition process of MoNO2 (H, μ3-N, O, O′) shows that the first and second deoxidation processes need to overcome energy barriers of 0.11 eV and 0.64 eV, respectively. All these findings indicate that NO2 is relatively easy to dissociate on Mo (110) surface.
Thermal Performance Improvement of Solar Parabolic Dish System Using Modified Spiral Coil Tubular Receiver
Authors: Malviya Rajkumar , Baredar Prashant V. , Kumar Anil
Published: December 2021

The present research intends to design an efficient receiver for solar thermal applications with a solar dish concentrator system. Thermal and dynamic analysis is carried out for different convolutions of a spiral coil, and experiments are performed for testing the modified absorber. Experimental results are validated for the spiral absorber with numerical results. Three receivers of different numbers of convolutions are analyzed, and simulation steps are performed for these receivers to make improvements in the system efficiency. Finally, 5 convolutions of a spiral coil tubular absorber are taken for the modified design of the system. Absorber position for every spiral convolution is kept at the focus of the concentrated solar dish collector to achieve maximum efficiency. Material used for the reflective surface is anodized aluminum and copper for the absorber. The diameter of the aperture for the parabolic dish collector is 1.4 m. The maximum absorber temperature for May month comes out to be 296°C, and the maximum working fluid outlet temperature is found to be 294.2°C which is near to simulating temperature of 289.59°C and 288.15°C, respectively. This innovative design of the absorber consists of a feature of a 5 mm extension to the spiral tube at the exit and entry; hence, the turbulence effect could be overcome. Experimental thermal efficiency was found the highest (i.e.,

η

th

max

=
75.98
%

) for May. This work emphasizes on improving thermal performance by obtaining optimum absorber size using convolution strategy. Investigation of 5 convolutions of spiral coil tubular absorber with extended ends for obtaining optimum performance than existing work is the superiority of this work.
Analysis of Lens Thickness Distribution Based on Swept-Source Optical Coherence Tomography (SS-OCT)
Authors: Feng Xi , Wang Yong , Liang Jianheng , Xu Yali , Ortega-Usobiaga Julio , Cao Danmin
Published: December 2021

Objective. This study aimed to analyze the distribution of lens thickness (LT) and its associations in age-related cataract patients based on swept-source optical coherence tomography (SS-OCT). Methods. This cross-sectional study included 59,726 Chinese age-related cataract patients. Only right-eye data were included in the study. Repeated measures of ocular parameters were performed using an IOL Master 700 device. The distributions of ocular biometric data including anterior chamber depth (ACD), LT, axial length (AL), central corneal thickness (CCT), white-to-white (WTW), and mean keratometry (MK) and their associations with age were assessed. The anterior segment (AS) was measured as the sum of CCT, ACD, and LT, while the vitreous chamber depth (VCD) was calculated as the difference between AL and AS. The values of LT : AL, AS : AL, and VCD : AL in different AL groups and their changes are the main outcome measures used to observe the proportion of the anterior and posterior segments of the eye. Results. Biometric data were available for 59,726 individuals. The mean age was 68.81 years (range = 40–100); 40.62% were male and 59.38% were female. Mean anterior chamber depth (ACD) was 3.02 ± 0.44 mm, mean LT was 4.51 ± 0.44 mm, mean axial length (AL) was 23.89 ± 1.92 mm, mean central corneal thickness (CCT) was 0.53 ± 0.03 mm, mean white-to-white (WTW) was 11.64 ± 0.44 mm, and mean keratometry (MK) was 44.27 ± 1.65 diopter. Female patients had shorter AL, shallower ACD, smaller CCT and WTW, decreased LT, and steeper corneas (

p

 < 0.005). ACD revealed the strongest negative correlation (

p

 ≤ 0.001, r = –0.682) with LT. Age (

p

 ≤ 0.001, r = 0.348) showed a moderate positive correlation, whereas MK (

p

 ＜ 0.05, r = 0.011), CCT (

p

 ≤ 0.001, r = 0.041) had a weak positive correlation and WTW (

p

 ≤ 0.001, r = –0.034) had a weak negative correlation with LT. A nonlinear correlation was found between LT and AL. LT increased with age in both males and females. LT changed variably in eyes with AL less than 27 mm, LT decreased as AL increased, then LT gradually increased as AL increased in extremely long and extra-long eyes (

p

 ≤ 0.001). LT : AL and AS : AL decreased as AL increased, VCD : AL gradually increased as AL increased in highly myopic eyes, and VCD : AL increased by about 0.01 for every 1 mm increase in AL. Conclusions. Among Chinese age-related cataract patients, we found LT to have the strongest relation with ACD. The lens was thicker in elderly patients and women. The correlation between LT and AL is not a simple negative correlation; with the increase of age, LT decreases first and then increases. The proportion of VCD is constantly rising with the elongation of AL.
Text Complexity Classification Data Mining Model Based on Dynamic Quantitative Relationship between Modality and English Context
Authors: Zhang Dan
Published: December 2021

With the rapid development of mobile internet technology, there are a large number of unstructured data in dynamic data, such as text data, multimedia data, etc., so it is essential to analyze and process these unstructured data to obtain potentially valuable information. This article first starts with the theoretical research of text complexity analysis and analyzes the source of text complexity and its five characteristics of dynamic, complexity, concealment, sentiment, and ambiguity, combined with the expression of user needs in the network environment. Secondly, based on the specific process of text mining, namely, data collection, data processing, and data visualization, it is proposed to subdivide the user demand analysis into three stages of text complexity acquisition, recognition, and expression, to obtain a text complexity analysis based on text mining technology. After that, based on computational linguistics and mathematical-statistical analysis, combined with machine learning and information retrieval technology, the text in any format is converted into a content format that can be used for machine learning, and patterns or knowledge are derived from this content format. Then, through the comparison and research of text mining technology, combined with the text complexity analysis hierarchical structure model, a quantitative relationship complexity analysis framework based on text mining technology is proposed, which is embodied in the use of web crawler technology. Experimental results show that the collected quantitative relationship information is identified and expressed in order to realize the conversion of quantitative relationship information into product features. The market data and text data can be integrated to help improve the model performance and the use of text data can further improve predictions for accuracy.
A Deep Transfer NOx Emission Inversion Model of Diesel Vehicles with Multisource External Influence
Authors: Xu Zhenyi , Wang Ruibin , Kang Yu , Zhang Yujun , Xia Xiushan , Wang Renjun
Published: December 2021

By installing on-board diagnostics (OBD) on tested vehicles, the after-treatment exhaust emissions can be monitored in real time to construct driving cycle-based emission models, which can provide data support for the construction of dynamic emission inventories of mobile source emission. However, in actual vehicle emission detection systems, due to the equipment installation costs and differences in vehicle driving conditions, engine operating conditions, and driving behavior patterns, it is impossible to ensure that the emission monitoring data of different vehicles always follow the same distribution. The traditional machine learning emission model usually assumes that the training set and test set of emission test data are derived from the same data distribution, and a unified emission model is used for estimation of different types of vehicles, ignoring the difference in monitoring data distribution. In this study, we attempt to build a diesel vehicle NOx emission prediction model based on the deep transfer learning framework with a few emission monitoring data. The proposed model firstly uses Spearman correlation analysis and Lasso feature selection to accomplish the selection of factors with high correlation with NOx emission from multiple sources of external factors. Then, the stacked sparse AutoEncoder is used to map different vehicle working condition emission data into the same feature space, and then, the distribution alignment of different vehicle working condition emission data features is achieved by minimizing maximum mean discrepancy (MMD) in the feature space. Finally, we validated the proposed method with the diesel vehicle OBD data that were collected by the Hefei Environmental Protection Bureau. The comprehensive experiment results show that our method can achieve the feature distribution alignment of emission data under different vehicle working conditions and improve the prediction performance of the NOx inversion model given a little amount of NOx emission monitoring data.
Effects of Different Green Tea Extracts on Chronic Alcohol Induced‐Fatty Liver Disease by Ameliorating Oxidative Stress and Inflammation in Mice
Authors: Li Bang-Yan , Li Hang-Yu , Zhou Dan-Dan , Huang Si-Yu , Luo Min , Gan Ren-You , Mao Qian-Qian , Saimaiti Adila , Shang Ao , Li Hua-Bin
Published: December 2021

Alcoholic fatty liver disease (AFLD) is a common chronic liver disease and has become a critical global public health problem. Green tea is a popular drink worldwide and contains several bioactive compounds. Different green teas could contain diverse compounds and possess distinct bioactivities. In the present study, the effects of 10 green teas on chronic alcohol induced‐fatty liver disease in mice were explored and compared. The results showed that several green teas significantly reduced triacylglycerol levels in serum and liver as well as the aminotransferase activities in mice at a dose of 200 mg/kg, suggesting that they possess hepatoprotective effects. Moreover, several green teas remarkably decreased the expression of cytochrome P450 2E1, the levels of malondialdehyde and 4‐hydroxynonenoic acid, and the contents of proinflammatory cytokines, indicating that they could alleviate oxidation damage and inflammation induced by chronic alcohol exposure. In addition, Seven Star Matcha Tea and Selenium‐Enriched Matcha Tea could increase glutathione level. Furthermore, the main phytochemical components in green teas were determined and quantified by high‐performance liquid chromatography, and the correlation analysis showed that gallic acid, gallocatechin, catechin, chlorogenic acid, and epigallocatechin gallate might at least partially contribute to protective effects on AFLD. In conclusion, Selenium‐Enriched Chaoqing Green Tea, Xihu Longjing Tea, Taiping Houkui Tea, and Selenium‐Enriched Matcha Tea showed the strongest preventive effects on AFLD. This research also provides the public with new insights about the effects of different green teas on AFLD.
Analysis of Artistic Modeling of Opera Stage Clothing Based on Big Data Clustering Algorithm
Authors: Luo Weiwei
Published: December 2021

In order to deal with the problem that the traditional stage costume artistry analysis method cannot correct the results of big data clustering, which leads to deviations in the extraction of costume artistry features, this paper proposes a clothing artistic modeling method based on big data clustering algorithm. The proposed method provides a database for big data clustering by constructing the attribute set of the big data feature sequence training set and, at the same time, constructing a second-order cone programming model to correct the big data. Aiming at the problem that traditional stage costume art analysis methods cannot correct the clustering results of big data. On this basis, the costume elements of the opera stage are segmented, initialized, and transformed into a binary function. Finally, using the convolutional neural network, combining the element segmentation results and the large data clustering space state vector, a feature extraction model of stage costume art is constructed. Experimental results show that the model has good convergence, short time-consuming, high accuracy, and ideal feature recognition capabilities.
Assessment of Availability and Quality of Emergency Obstetric and Newborn Care Service in Southwestern Oromia, Ethiopia, 2017
Authors: Edosa Dejene
Published: December 2021

Background. Emergency obstetrics and newborn care (EmONC) is an important lifesaving function which can avert the death of women facing obstetrics-related complications. It is a cost-effective, significant intervention to decrease maternal and neonatal morbidity and mortality in poor resource settings, including Ethiopia. Objective. The aim of this study was to assess the availability and quality of the EmONC services in southwestern Oromia, Ethiopia, in 2017. Methods. An institutional-based cross-sectional study was implemented from April to May 2017. Data were collected using checklists and questionnaires developed from different studies. Data were analyzed using EPI-info and exported to SPSS version 20 for further analysis. Each descriptive statistic was summarized using frequency, percentage, and tables for categorical variables. Results. Despite the fact that the overall coverage of fully functioning basic emergency obstetric and newborn care (BEmONC) facilities was greater than 5 per 500,000 people, nearly one-fourth (25.64%) provided less than expected signal functions, indicating that these facilities were nonfunctional. There were only 0.24 comprehensive emergency obstetric and newborn care (CEmONC) facilities per 500,000 people. The result of this study also revealed that the quality of EmONC facilities in all health-care settings was poor. Conclusion and Recommendation. There were gaps in performance signal functions as well as the availability and quality of EmONC in the study area. Availability and quality of EmONC necessitate improvements through enhancing health-care providers’ skills by training and mentoring as well as enabling facilities accessible for utilization of EmONC. Further research is needed to identify factors that could be barriers to the performance quality and coverage of EmONC services.
On Certain Bounds for Edge Metric Dimension of Zero-Divisor Graphs Associated with Rings
Authors: Siddiqui Hafiz Muahmmad Afzal , Mujahid Ammar , Binyamin Muhammad Ahsan , Nadeem Muhammad Faisal
Published: December 2021

Given a finite commutative unital ring

S

having some non-zero elements

x
,
 
y

such that

x
.
y
=
0

, the elements of

S

that possess such property are called the zero divisors, denoted by

Z

S

. We can associate a graph to

S

with the help of zero-divisor set

Z

S

, denoted by

ζ

S

(called the zero-divisor graph), to study the algebraic properties of the ring

S

. In this research work, we aim to produce some general bounds for the edge version of metric dimension regarding zero-divisor graphs of

S

. To do so, we will discuss the zero-divisor graphs for the ring of integers

ℤ

m

modulo

m

, some quotient polynomial rings, and the ring of Gaussian integers

ℤ

m

i

modulo

m

. Then, we prove the general result for the bounds of edge metric dimension of zero-divisor graphs in terms of maximum degree and diameter of

ζ

S

. In the end, we provide the commutative rings with the same metric dimension, edge metric dimension, and upper dimension.
ACAMA: Deep Learning-Based Detection and Classification of Android Malware Using API-Based Features
Authors: Ko Eunbyeol , Kim Jinsung , Ban Younghoon , Cho Haehyun , Yi Jeong Hyun
Published: December 2021

As a great number of IoT and mobile devices are used in our daily lives, the security of mobile devices is being important than ever. If mobile devices which play a key role in connecting devices are exploited by malware to perform malicious behaviors, this can cause serious damage to other devices as well. Hence, a huge research effort has been put forward to prevent such situation. Among them, many studies attempted to detect malware based on APIs used in malware. In general, they showed the high accuracy in detecting malware, but they could not classify malware into detailed categories because their detection mechanisms do not consider the characteristics of each malware category. In this paper, we propose a malware detection and classification approach, named ACAMA, that can detect malware and categorize them with high accuracy. To show the effectiveness of ACAMA, we implement and evaluate it with previously proposed approaches. Our evaluation results demonstrate that ACAMA detects malware with 26% higher accuracy than a previous work. In addition, we show that ACAMA can successfully classify applications that another previous work, AVClass, cannot classify.
Wave Mode Control of Cantilever Slab Structure of T‐Beam Bridge with Large Aspect Ratio
Authors: Liu Tingting , Zhou Chuanping , Yan Zhigang , Chen Guojin
Published: December 2021

The cantilever plate structure in a T‐beam bridge with a large aspect ratio will cause vibration under the influence of environmental disturbance and self‐stress, resulting in fatigue damage of the plate structure. Wave control based on elastic wave theory is an effective method to suppress the vibration of the cantilever plate structure in a beam bridge. Based on the classical thin plate theory and the wave control method, the active vibration control of the T‐shaped cantilever plate with a large aspect ratio in the beam bridge is studied in this paper. The wave mode control strategy of structural vibration is analyzed and studied, the controller is designed, the vibration mode function of the cantilever plate is established, and the control force/sensor feedback wave control is implemented for the structure. The dynamic response of the cantilever plate before and after applying wave control force is analyzed through numerical examples. The results show that the response of the structure is intense before control, but after wave control, the structure increases damping, absorbs the energy carried by the elastic wave in the structure, weakens the sharp response, and changes the natural frequency of the structure to a certain extent.
Experimental Research on Key Factors Influencing the Expansion Performance of New Type Sealing Materials
Authors: Li Yaobin , Guo Xin , Xue Sheng , Zheng Chun-Shan , Shen Maoliang , Xu Yang
Published: December 2021

To improve the borehole sealing effect, especially that of coal seam with low permeability and micro fissures, this paper takes the expansion rate of the sealing material as the response value and establishes the quadratic model embracing the expansion rate and various experimental factors by designing orthogonal experiments. The response surface is used to further determine the significance order of each key factor according to the expansion rate and adjust the admixture content to obtain the optimal ratio of the sealing material. For the research investigating a sealing material, the optimal ratio of the sealing material is obtained: the content of water reducing agent of 0.5%, the content of retarder of 0.04%, water‐cement ratio of 0.8, and the content of expansion agent of 10%. At this time, the expansion rate reaches 3.136%. Besides, a scanning electron microscope is used to observe the microscopic morphology of the material. According to the scanning electron microscopy analysis of new borehole sealing materials, the surface of the new borehole sealing material shows no holes and possesses compactness; and a large amount of ettringite is formed on the surface of the hydration product of hardened cement slurry. The ettringite improves the expansibility of the material. The new sealing material provides a new idea for gas sealing, which is of great significance to improve the efficiency of borehole extraction, improve the utilization rate of resources, and prevent gas accidents.