bluuebunny/crossref_metadata_2025 huggingface dataset:
Heat transfer characteristics of rectangular/triangular/convex-shaped fins filled with hybrid nanoparticles under dry and wet conditions
Authors: Raju C. S. K. , Sajjan Kiran , Yook Se-Jin
Published: November 2023

Numerous researchers have been interested in nanofluids because of their improved thermal characteristics and heat transmission capabilities. Recently, it has been possible to create a novel nanofluid with exceptional thermal properties by combining ternary nanoparticles of various shapes. In this respect, it is believed that the thickness of the fin will change with the length of the fin and that the impacts of thermal radiation, convection on a heat transfer mechanism, and internal heat production in a fin wetted with ternary hybrid nanofluid will depend on the length of the fin. As a result, several fin profiles, including triangular, convex, and rectangular, have been taken into consideration. This study also investigates the comparison of heat and thermal energy fluctuations in both wet and dry conditions. In order to examine the porous nature, Darcy's model is required. With the aid of the Maple computer program, the resultant nonlinear partial differential equation and boundary conditions are non-dimensionalized and numerically resolved using the implicit finite difference approach, the graphic explanation of fin efficiency, and transient thermal response for different values of the essential parameters. The investigation yielded the novel discovery that the effectiveness of the fins is enhanced by the presence of a ternary hybrid nanofluid. Three fins with varied shapes have been compared in both wet and dry circumstances. The study has discovered that triangular fins have a quicker rate of temperature decline, whereas rectangular fins have a greater efficiency. The investigation's results have a significant impact on improving heat transmission in industrial operations.
Quasi-bound states in the continuum induced by C4v structure
Authors: Zhou Bin , Meng Haiyu , Li Hongju , Xue Xiongxiong
Published: November 2023

We propose a method to achieve symmetry-protected bound states in the continuum (BICs) while maintaining the C4v structural symmetry, utilizing a periodically arranged array of topological Dirac semimetals (TDS) squares. By numerically controlling the metamaterial using four identical square films of TDS, we can manipulate both the resonance position and number. This phenomenon arises due to the inherent permittivity asymmetry of the metamaterial, causing the creation of quasi-BICs. When all four squares have the same Fermi energy, a BIC is formed. Different Fermi energies are assigned to the four squares, resulting in quasi-BICs with narrow resonances. The electric analysis in the x-y plane identified the dominant contributors as the electric quadrupole and octupole. Our findings provide a direct route to achieve high-quality (high-Q) quasi-BICs without any introduction of symmetry-breaking elements, such as transverse, in-plane, and out-of-plane components in the structure, or the use of oblique incidences within a non-breaking system.
A cross-sectional study exploring equity of access to telehealth in culturally and linguistically diverse communities in a major health service
Authors: Gallegos-Rejas Victor M. , Kelly Jaimon T. , Lucas Karen , Snoswell Centaine L. , Haydon Helen M. , Pager Sue , Smith Anthony C. , Thomas Emma E.
Published: November 2023

Objectives The utilisation of telehealth among culturally and linguistically diverse communities in Australia remains unexplored. We aimed to describe telehealth (telephone and videoconference) utilisation within a major health service and identify sociodemographic factors that may contribute to limited telehealth access. Methods A cross-sectional study was performed using service activity data from four metropolitan hospitals in Queensland, Australia. Outpatient department data (January to December 2021) were examined. These data included patients (N = 153 427) of all ages who had an outpatient appointment within 10 speciality services (i.e. Hepatology, Gastroenterology, Immunology and Psychology) that were the most frequent videoconference users. This study measured telehealth utilisation across the four tertiary hospitals and its association with sociodemographic factors. Descriptive statistics and regression analysis were used. Multivariate regression models were adjusted by sex, socioeconomic level and language use. Results Overall, 39% of appointments were delivered through telehealth, with 65% of all reported telehealth services involving a telephone consultation. People who required interpreter services were 66% less likely to use telehealth services (OR adjusted 0.33, 95% CI 0.31–0.36, P < 0.05) than English-speaking people. Among those using telehealth, people requiring interpreter services were 13% less likely to use videoconference than phone (OR adjusted 0.87, 95% CI 0.77–0.98, P < 0.005). Conclusion There is a gap in Australian telehealth service use for people with culturally diverse backgrounds and limited English proficiency. This study highlights a critical need to determine how people from culturally diverse backgrounds would like to engage with digital care options such as telehealth and the necessary support to enable this.
Influence of hydroperiod on aquatic food-web structure and energy production in a floodplain wetland: implications for environmental flow management
Authors: Frost Lindsey K. , Mika Sarah J. , Thompson Ross M. , Growns Ivor
Published: November 2023

Context Environmental water is often used to manage floodplain wetlands that support many taxa, both terrestrial and aquatic. It is important to optimise the managed hydroperiod to maximise the provision of aquatically derived resources from wetlands. Aims To test the hypothesis that increasing hydroperiod affects food-web structure and energy production in floodplain wetlands. Methods Fatty acids and stable isotopes of δ13C and δ15N were used to define food-web structure, and estimate total energy production throughout a managed inundation event in a wetland in the northern Murray–Darling Basin. Key results Food-web complexity increased with an increasing hydroperiod in line with predictable patterns of community assemblage development, before reducing sharply immediately prior to drying. Energy availability increased with an increasing hydroperiod and there was a strong correlation (ρ = 0.669, P = 0.0001) between energy availability and fatty acid concentration, which was in turn related to patterns of taxon occurrence. Conclusions and implications Hydroperiod exerts a strong influence on aquatic invertebrate community trophic dynamics and energy provision. Planned flows should support maturation and stabilisation of the invertebrate community to optimise energy provision to consumers.
High-throughput quantification of red blood cell deformability and oxygen saturation to probe mechanisms of sickle cell disease
Authors: Williams Dillon C. , Wood David K.
Published: November 2023

The complex, systemic pathology of sickle cell disease is driven by multiple mechanisms including red blood cells (RBCs) stiffened by polymerized fibers of deoxygenated sickle hemoglobin. A critical step toward understanding the pathologic role of polymer-containing RBCs is quantifying the biophysical changes in these cells in physiologically relevant oxygen environments. We have developed a microfluidic platform capable of simultaneously measuring single RBC deformability and oxygen saturation under controlled oxygen and shear stress. We found that RBCs with detectable amounts of polymer have decreased oxygen affinity and decreased deformability. Surprisingly, the deformability of the polymer-containing cells is oxygen-independent, while the fraction of these cells increases as oxygen decreases. We also find that some fraction of these cells is present at most physiologic oxygen tensions, suggesting a role for these cells in the systemic pathologies. Additionally, the ability to measure these pathological cells should provide clearer targets for evaluating therapies.
Barriers for why pregnant women do not visit a dentist on a regular basis: using group concept mapping methodology
Authors: Winckler Karoline , Rasmussen Marianne Uggen , Laugenborg Jeannet , Bukkehave Kathrine Hansen , Fischer Heidi , Heitmann Berit Lilienthal , Wæhrens Eva Ejlersen
Published: November 2023

Objectives: Periodontitis in pregnancy represents a significant, but often overlooked challenge due to its association to adverse pregnancy (preeclampsia and gestational diabetes) and birth related outcomes (preterm birth and low birth weight). The overall study aim was to identify, organize, and prioritize barriers influencing dental visits among Danish pregnant women not seeing a dentist on a regularly basis.
Materials and methods: Participants were pregnant women screened at weeks 11–13 of gestation, and were recruited if they were not seeing a dentist regularly. The study was conducted at Holbæk and Nykøbing Falster Hospital in Region Zealand, Denmark. The Group Concept Mapping (GCM) approach was applied. The pregnant women participated in brainstorming (n = 18), sorting (n = 20), and rating (n = 17) the seating question ‘Thinking as broadly as you can, please list all barriers of importance to you for not seeing a dentist on a regular basis’.
Results: A total of 38 unique barriers were identified, organized, and prioritized online. The multidimensional scaling analysis involved 10 iterations and revealed a low stress value of 0.21. A cluster solution with five clusters including ‘economic reasons’, ‘lack of priority’, ‘lack of time and energy’, ‘no problems with teeth’, and ‘dental fear’, was discussed and interpreted at a validation meeting.
Conclusions: Five overall clusters explaining barriers for not seeing a dentist regularly were revealed. Of the five clusters, ‘economic reasons’ and ‘lack of priority’ were rated as the most important clusters. Accordingly, such barriers should be considered in the planning of future strategies of dental care during pregnancy.
Detection of scatterers using an XFEM-BEM level set solver based on the topological derivative
Authors: Canelas Alfredo , Abreu Ana I , Roche Jean R
Published: November 2023

A numerical method is proposed for the solution of the inverse scattering problem. This problem consists of determining the location and shape of an unknown number of inclusions composed by a homogeneous material with known mechanical properties different that those of the surrounding medium. The information available to solve the inverse problem are measurements of the fundamental mechanical magnitude of the wave propagation problem. At the boundary of the scatterers, transmission conditions depending on the material properties are considered. For the solution of the forward problem, a coupled extended finite element method (XFEM)-boundary element method (BEM) is proposed, where the XFEM is used for the bounded region where the scatterers are supposed to be located, and the BEM is used for the exterior domain. The inverse problem is formulated as a topology optimization problem, and solved by means of a heuristic algorithm based on the topological derivative and a level set representation of the scatterers.
Generation of higher-order topological insulators using periodic driving
Authors: Ghosh Arnob Kumar , Nag Tanay , Saha Arijit
Published: November 2023

Topological insulators (TIs) are a new class of materials that resemble ordinary band insulators in terms of a bulk band gap but exhibit protected metallic states on their boundaries. In this modern direction, higher-order TIs (HOTIs) are a new class of TIs in dimensions d > 1. These HOTIs possess

(
d
−
1
)

-dimensional boundaries that, unlike those of conventional TIs, do not conduct via gapless states but are themselves TIs. Precisely, an nth order d-dimensional higher-order TI is characterized by the presence of boundary modes that reside on its

d
c

=
(
d
−
n
)

-dimensional boundary. For instance, a three-dimensional second (third) order TI hosts gapless (localized) modes on the hinges (corners), characterized by

d
c

=
1
(
0
)

. Similarly, a second-order TI (SOTI) in two dimensions only has localized corner states (

d
c

=
0

). These higher-order phases are protected by various crystalline as well as discrete symmetries. The non-equilibrium tunability of the topological phase has been a major academic challenge where periodic Floquet drive provides us golden opportunity to overcome that barrier. Here, we discuss different periodic driving protocols to generate Floquet HOTIs while starting from a non-topological or first-order topological phase. Furthermore, we emphasize that one can generate the dynamical anomalous π-modes along with the concomitant 0-modes. The former can be realized only in a dynamical setup. We exemplify the Floquet higher-order topological modes in two and three dimensions in a systematic way. Especially, in two dimensions, we demonstrate a Floquet SOTI (FSOTI) hosting 0- and π corner modes. Whereas a three-dimensional FSOTI and Floquet third-order TI manifest one- and zero-dimensional hinge and corner modes, respectively.
Characterizing the fault performance of real-time precise satellite orbit and clock correction products
Authors: Huang Weiquan , Li Menghao , Li Liang , Wang Renlong , Wang Liuqi , Wang Ningbo
Published: November 2023

The a priori fault probability of the real-time precise satellite orbit and clock correction products is the critical parameter for integrity monitoring of precise point positioning (PPP). The traditional fault probability evaluation methods use the worst-case instantaneous user ranging error (IURE) as the conservative test statistic. However, the systematic biases of IURE contained in the worst-case IURE barely affect the PPP accuracy, which will undermine the statistical distribution of test statistic and reduce the sensitivity of fault detection. The fault probability will be estimated over-conservatively for the traditional methods. By clarifying the sources of the systematic biases, a new test statistic is constructed by deliberately removing the systematic biases of IURE originated from satellite orbit and clock errors. One-year Global Positioning System correction products evaluation results have demonstrated that the constructed test statistic follows the Gaussian distribution with the decreased uncertainty and the improved fault detection sensitivity. The real-world data experiments have shown that the a priori probabilities of the satellite fault and the constellation fault are at the order of 10−4 and 10−5 levels, respectively.
Model for predicting the angles of upper limb joints in combination with sEMG and posture capture
Authors: Wang Zhen-Yu , Xiang Ze-Rui , Zhi Jin-Yi , Ding Tie-Cheng , Zou Rui , Lan Yong-Xia
Published: November 2023

Since poor man–machine interaction and insufficient coupling occur in the processes of angle prediction and rehabilitation training based purely on the surface electromyography (sEMG) signal, a model for predicting the angles of upper limb joints was presented and validated by experiments. The sEMG and posture capture features were combined to build a hybrid vector, and the intentions of upper limb movements were characterized. The original signals were pre-treated with debiasing, filtering, and noise reduction, and then they were integrated to obtain signal characteristics. Then, feature values in the time domain, frequency domain, time-frequency domain, and entropy were extracted from the treated signals. The snake optimizer least squares support vector machine (SO-LSSVM) was modeled to predict the angles of upper limb joints to improve the poor precision and slow velocity of existing models in the movement control field. Experimental results showed that the prediction model performed well in predicting the motion trails of human upper limb joints from the sEMG signal and attitude information. It effectively reduced both skewing and error in prediction. Hence, it holds great promise for improving the man–machine coupling precision and velocity. Compared to the conventional LSSVM model, the proposed SO-LSSVM model reduced the training time, execution time, and root mean square error of evaluation parameters by 65%, 11%, and 76%, respectively. In summary, the proposed SO-LSSVM model satisfied the real-time requirement for rehabilitation robots and showed high accuracy and robustness.
A whale optimization detection (WOD) method for bladder volume estimation with bioelectrical impedance spectroscopy (BIS)
Authors: Hong Zhiyang , Zhu Jin , Wu Yang , Fang Junyang , Ye Ming , Liu Kai , Yao Jiafeng
Published: November 2023

A whale optimization detection (WOD) method is presented for rapid bladder volume estimation with bioelectrical impedance spectroscopy (BIS). Firstly, the WOD method for bladder volume estimation is established, which includes a bladder volume estimation electrical equivalent circuit (EEC) model and a rapid fitting strategy. Secondly, an abdominal phantom is constructed, which consists of an abdominal cavity shell and four bladders with volumes of V
b = 30 ml, 100 ml, 200 ml, and 300 ml. Next, BIS experiments are conducted using the phantom with the WOD method fitted to the obtained data. The results demonstrated a high linear correlation coefficient R
2 > 0.987 between the experimental and WOD results. Finally, in vivo testing is performed using both the Caresono HD-5 ultrasonic bladder scanner and the proposed WOD method. The EEC parameters obtained by the WOD method form a mathematical formula that accurately describes the subject’s bladder volume, with a detection correlation coefficient r = 98.71%, and the maximum relative error δ = 5.88% between WOD and ultrasound testing results. In conclusion, the proposed method is expected to be applied for rapid monitoring of patients’ bladder volume.
RLC series circuit made simple and portable with smartphones
Authors: Torriente-García Ives , Martí Arturo C , Monteiro Martín , Stari Cecilia , Castro-Palacio Juan C , Monsoriu Juan A
Published: November 2023

This article presents a novel method for studying RLC series circuits using two smartphones, one used as a signal generator and the other as an oscilloscope. We measure the voltage at the external resistor as a function of frequency when subjected to a sinusoidal electromotive force. The experimental results demonstrate a remarkable agreement with the theoretical curve for the voltage at the resistor and the resonance frequency, validating the accuracy of the smartphone-based setup. The experiment fills the gap in educational materials related to electrical circuits and provides a portable alternative to traditional, expensive laboratory equipment.
Effect of problem-based learning on students’ problem-solving ability to learn physics
Authors: Gumisirizah Nicholus , Muwonge Charles M , Nzabahimana Joseph
Published: November 2023

A learner’s success is supported by the ability to understand real-world problems. This study aimed to examine the effect of problem-based learning on problem-solving ability in the teaching and learning of physics. The study was guided by socio-constructivism theory. A quasi-experiment was conducted with 829 Senior-2 Physics students (age 13–15) from eight (8) selected lower secondary schools in Sheema District, Uganda. Schools were assigned to treatment and control groups using a purposive random sampling technique. Students’ problem-solving ability was measured by conducting a problem-solving ability test in each group before and after studying a chapter on simple machines in physics. Repeated measures analysis of variances was applied for data analysis. The study’s findings showed a significant improvement in students’ problem-solving ability with simple machines in the treatment group compared to the control group (p < .001). Therefore, educators are encouraged to embrace learner-centred methods that enhance students’ problem-solving abilities to help them compete in the world of work.
Hybrid optimization of laser-driven fusion targets and laser profiles
Authors: Li Z , Zhao Z Q , Yang X H , Zhang G B , Ma Y Y , Xu H , Wu F Y , Shao F Q , Zhang J
Published: November 2023

Quasi-isentropic compression is an effective method to achieve high-density and high-temperature implosion in laser-driven inertial confinement fusion (ICF). However, it requires precise matching between the laser profile and the target structure. Designing the optimal laser profile and the corresponding target for ICF is a challenge due to the large number of parameters involved. In this paper, we present a novel method that combines random walk and Bayesian optimization. The basic sampling data for Bayesian optimization are a series of laser pulse profiles and target structures that can produce relatively high areal densities obtained by the random walk method. This approach reduces the number of samples required for Bayesian optimization and mitigates low efficiency in the latter stages of the random walk method. The method also reduces the randomness in the optimization process and enhances the optimization efficiency. It should have important applications in ICF research.
The ternary phase diagram of nitrogen doped lutetium hydrides can not explain its claimed high Tc superconductivity
Authors: Gubler Moritz , Krummenacher Marco , Finkler Jonas A , Flores-Livas José A , Goedecker Stefan
Published: November 2023

This paper presents the results of an extensive structural search of ternary solids containing lutetium, nitrogen and hydrogen. Based on thousands of thermodynamically stable structures the convex hull of the formation enthalpies is constructed. To obtain the correct energetic ordering, the highly accurate RSCAN DFT functional is used in high quality all-electron calculations, eliminating possible pseudopotential errors. In this way, a novel lutetium hydride structure (HLu2) is found that is on the convex hull. An electron phonon analysis however shows that it is not a candidate structure for near ambient superconductivity. Besides this structure, which appears to have been missed in previous searches, possibly due to different DFT methodologies, our results agree closely with the results of previously published structure search efforts. This shows, that the field of crystal structure prediction has matured to a state where independent methodologies produce consistent and reproducible results, underlining the trustworthiness of modern crystal structure predictions. Hence it is quite unlikely that a structure, that would give rise within standard BCS theory to the superconducting properties, claimed to have been observed by Dasenbrock-Gammon et al (2023 Nature
615 244), exists. This solidifies the evidence that structures with high Tc conventional superconductivity, that could give rise to the experimental claims, do not exist in this material.
A Bayesian quantum state tomography along with adaptive frameworks based on linear minimum mean square error criterion
Authors: Mondal Subhadeep , Dutta Amit Kumar
Published: November 2023

Quantum state tomography (QST) is essential for characterizing unknown quantum states. Several methods of estimating quantum states already exist and can be classified mainly into three broad classes. They are based on the criteria like maximum likelihood, linear inversion, and Bayesian framework. The Bayesian framework for QST gives a better reconstruction performance. However, the existing methods of the Bayesian frameworks are computationally extensive and, most of the time require knowledge about the prior distribution of the quantum state. In this paper, we propose a Bayesian method of QST based on the linear minimum mean square error criterion, where the prior statistics are estimated and the computational complexity is comparable to that of the linear inversion based QST method. We also propose an adaptive version based on the block estimation of parameters. Extensive numerical simulations are conducted to demonstrate its efficacy over the linear inversion-based QST regarding trace distance error metric.
Effect of annealing temperature on the formation of oxygen vacancies on the surface of flower-like SnSe/SnO2 heterostructure and visible light catalytic performance
Authors: Liao Lei , Li Siyuan , Jin Yingrong , Cai Fanggong , Zhang Qinyong
Published: November 2023

The morphology, structure, and oxygen vacancies in principle determine the light absorption, charge transfer, and separation of photocatalysts, thereby determining their photocatalytic performance. In this study, flower-like SnSe obtained from hydrothermal reactions was oxidized to obtain heterojunctions with SnSe/SnO2. Flower-like SnSe/SnO2 heterojunctions with different concentrations of oxygen vacancies were prepared by annealing them in an argon atmosphere at different temperatures. The flower-like SnSe/SnO2 series with different oxygen vacancies were systematically characterized by TEM, XRD, XPS, PL, and EPR. The research results demonstrate the presence of oxygen vacancies in the flower-like SnSe/SnO2. As the annealing temperature increases, the surface oxygen vacancy concentration shows a trend of first increasing and then decreasing. When the annealing temperature reaches 600 °C, the oxygen vacancy concentration of flower-like SnSe/SnO2 is the highest. Meanwhile, research has shown that surface oxygen vacancies help expand the light absorption range, and the increased valence bandwidth leads to effective charge transfer and separation, thereby promoting visible light photoactivity. SnSe/SnO2-600 °C exhibited excellent visible light photocatalytic activity. The photodegradation of methylene blue (MB) at ≥ 400 nm can reach ∼70% within 120 min. This study verified the route for the introduction of oxygen vacancies via facile calcination and constructed SnSe/SnO2 with surface oxygen vacancies, providing a reference with deep insights for improving photocatalytic activity.
Particle dynamics, black hole shadow and weak gravitational lensing in the f (Q) theory of gravity
Authors: Ditta Allah , Tiecheng Xia , Atamurotov Farruh , Hussain Ibrar , Mustafa G
Published: November 2023

We study the particle dynamics around a black hole (BH) in f(Q) gravity. First, we investigate the influence of the parameters of f(Q) gravity on the horizon structure of the BH, photon orbits and the radius of the innermost stable circular orbit (ISCO) of massive particles. We further study the effects of the parameters of  f(Q) gravity on the shadow cast by the BH. Moreover, we consider weak gravitational lensing using the general method, where we also explore the deflection angle of light rays around the BH in  f(Q) gravity in uniform and nonuniform plasma mediums.
Computing character tables of symmetric groups using higher order permutation representations
Authors: Lei Zikang
Published: November 2023

In this paper, we will introduce the topic of representation theory by focusing on the techniques of computing character tables of finite groups, in particular, the symmetric group Sn
. First, we will introduce some basic concepts of representation theory of finite groups over ℂ. Then we will compute the character tables for S
3 and S
4 using the classical methods introduced in Section 2. Also, we will construct a series of representations for Sn
and compute their characters. Finally, we will compute the character tables for S
5 and S
6 using our method introduced in Section 3.
Convex optimization and the smallest ball problem
Authors: Yang Junchi
Published: November 2023

The Smallest Ball Problem is a famous problem in mathematics that was proposed by James Joseph Sylvester. In the past, many algorithms to solve this problem were founded but there was only a limited number of researches that focused on the rigorous mathematical proof of this problem. Thus, the goal of this essay is to provide a rigorous proof of the claim that the smallest enclosing ball must exist and it is unique. In this essay, the Smallest Ball Problem will be converted into a convex optimization problem and the result that the smallest enclosing ball exists and is unique can be proved by proving the optimal solution of this programming problem exists. The meaning of this research is to give a theoretically mathematical proof of the Smallest Ball Problem so that it can tell the algorithms to solve this problem can always work. Thus, it can also ensure the effectiveness of all the related algorithms.
A study on aerodynamics of Ultra-efficient cars
Authors: Zhang Boxiang
Published: November 2023

Ultra-efficient cars (i.e. Formula One racing cars) are loaded with many different aerodynamic components. They interact to produce highly nonlinear flows, which have a very complex effect on the airflow around the racing car. Clearing up fluid phenomena makes it possible to optimize aerodynamic components effectively. This paper reviews the aerodynamic performance of currently used shapes, as well as the definition of the design constraints for the vehicle. The designs are inspired by formula one cars, especially by Honda F1 Team, but they are adjusted according to the limit conditions of CFD simulation software Ansys CFX, and parameters are scaled accordingly based on the space requirements of this test. A level of velocity at 40 km/h is tested, giving ideas of the full model performance. Results are then compared and discussed to obtain a comprehensive and valid conclusion about the potential improvement in the aerodynamics of road cars, which can be extracted from those ultra-efficient ones.
Research of the problems of heat conduction in fluids
Authors: Wang Haojun
Published: November 2023

In the fluid of the pipeline, the phenomena of heat convection, heat conduction, and radiation heat transfer occur between the pipeline and the outside world as well as between the pipeline and the inside. In the calculation of the relevant temperature and heat, we need to know the heat transfer coefficient, pipeline characteristic length, flow velocity, and other data to get the results. Based on previous research results, this paper will use Ansys software to explore the change law of heat transfer effect with various parameters. We can find that in the simulation, as the flow rate increases, the heating effect will become worse and worse.
Design and analysis of root locus based controllers
Authors: Yang Wenbo
Published: November 2023

The root locus method is the classical method for analyzing the variation of the position of the poles of a closed-loop control system transfer function in the complex plane. It is also the basis for guiding the design of various controllers. Starting from the nature of the root locus, this paper takes a standard form of closed-loop feedback control system as an example, and analyzes in detail the internal logic of designing a controller and compensator by the root locus method. At the same time, software such as MATLAB/Simulink, and Octave are used. The working principles and properties of the PD controller; the lead and lag compensator, their interconnections, advantages, and characteristics, as well as the adjustment of parameters to better suit practical needs, are sorted out. The PD controller improves the system response, the lead compensator eliminates the PD controller’s defects, and the lag compensator reduces the steady-state error of the system. It provides help for understanding the essence of controller design and provides design ideas for control problems in actual engineering.
Effect of slab dimensions on the maximum stress and ultimate vertical load of a 15-story flat slab building
Authors: Wang Tingyu
Published: November 2023

The research of flat slab structures requires more investigation into the full-scale analysis of steel flat slab structures under vertical loads. The impact of slab dimensions on the maximum stress of slabs and columns, as well as the ultimate vertical load at the linear elastic stage, has been examined using full-scale finite element models. The particular structures selected for the analysis are 15-story steel flat slab structures with various slab dimensions under the static vertical load and standard earth gravity. This research also involves: (1) the verification of stress singularity at the corner of cubic columns in the finite element model; (2) the discussion about the variation of maximum stress of slabs and columns as the floor changes, and the interaction of columns and slabs; (3) the validation of the vulnerability of slab-column connection.
Improved deep semantic dictionary learning for multi-label image classification
Authors: Zhang Shihan
Published: November 2023

Multi-label image classification is a practical and challenging task in the field of machine learning. It is a fundamental but essential task used in auto driving, internet image classification, and other fields. Many researchers have done various researches on relevant aspects. Deep Semantic Dictionary Learning (DSDL) is a multi-label image classification method brought out by previous researchers which combines the semantic meaning information into the classification task. However, it only uses one kind of feature extraction network as the feature map generator without considering other alternatives. In this paper, six types of pretrained networks are applied as alternative choices to validate the performance of DSDL on different neural networks. Experiments are conducted on the VOC2007 dataset and the result shows the inner relation of different series of neural networks and demonstrates that different feature extraction networks perform variously on different tasks. The ResNet-152 achieves the mean average precision (mAP) of 94.5% and outperforms the original DSDL method of 0.3% mAP.
Research on electronic stethoscope system and signal processing algorithm
Authors: Li Xiao , Shang Yujing , Wei Jiaqi , Zhou Yiheng
Published: November 2023

Stethoscopes have an important role in non-invasive diagnosis of cardiovascular and respiratory diseases, digestive diseases, and other kinds of diseases. The emergence of high-end diagnostic devices and new diagnostic methods have caused the status of the stethoscope to decline. However, stethoscope has the advantages of simple operation, mature auscultation theory and low cost, and thus is still widely used in medical diagnosis. This paper first introduces the design and application of electronic stethoscope solutions based on contact sensors and air coupling sensors, and then introduces advanced algorithms for digital signal processing for the diagnosis and treatment of different diseases, including heart sound noise reduction algorithm, heart sound segmentation algorithm and heart sound feature extraction and recognition algorithm. Finally, this paper summarizes the application of the electronic stethoscope system in medical testing, and its future development direction. In summary, the electronic stethoscope system is a reliable medical testing tool, which can convert sound signals into digital signals through complex signal processing algorithms for more accurate detection of human physiological parameters. The research of this paper will be of great value to the research and application of electronic stethoscopes.
CNN combined with data augmentation for face recognition on small dataset
Authors: Chen Siru
Published: November 2023

Faces have universal structures yet contain distinct features among individuals. Recognizing individuals based on their faces has always been a popular topic in pattern recognition, and computer vision and many traditional approaches have yielded satisfying results. In recent years, rapid growth in deep learning has encouraged researchers to use deep learning methods to solve authentication problems. Convolutional neural networks are one of the most popular deep neural networks with multiple layers and the ability to reduce parameters by using kernels to capture features from input. It has outstanding performance in pattern recognition due to its ability to extract features and take images as inputs. In machine learning, data augmentation is a technique to seemingly enlarge a dataset to avoid underfitting or overfitting problems caused by insufficient data. This paper uses convolutional neural networks to solve face recognition problems on a small dataset. It compares performance with traditional face recognition methods such as Principal Component Analysis and examines the impact on performance using data augmentation. Overall, data augmentation boosts the accuracy of the network but also results in an unsteady learning curve. The convolutional neural network performs well on pattern recognition and obtains an accuracy of 94% in an augmented dataset with only two convolutional layers.
Face image generation and feature visualization using deep convolutional generative adversarial networks
Authors: Wu Han
Published: November 2023

Generative Neural Networks (GAN) aims to generate realistic and recognizable images, including portraits, cartoons and other modalities. Image generation has broad application prospects and important research value in the fields of public security and digital entertainment, and has become one of the current research hotspots. This article will introduce and apply an important image generation model called GAN, which stands for Generative Adversarial Network. Unlike recent image processing models such as Variational Autoencoders (VAE), The discriminative network evaluates potential candidates while the GAN generates candidates. As a result, the discriminative network distinguishes created and real candidates, while the generative network learns to map from a latent space to an interest data distribution. In this article, the GAN model and some of its extensions will be thoroughly applied and implemented based on the dataset of CelebA, and details will be discussed through the images and graphs generated by the model. Specific training methods for various models and optimization algorithms can be produced by the GAN framework. The experiment’s findings in this article will show how the framework’s potential may be quantified and qualitatively assessed using the samples that were produced.
Review of ansatz designing techniques for variational quantum algorithms
Authors: Qin Junhan
Published: November 2023

For a large number of tasks, quantum computing demonstrates the potential for exponential acceleration over classical computing. In the NISQ era, variable-component subcircuits enable applications of quantum computing. To reduce the inherent noise and qubit size limitations of quantum computers, existing research has improved the accuracy and efficiency of Variational Quantum Algorithm (VQA). In this paper, we explore the various ansatz improvement methods for VQAs at the gate level and pulse level, and classify, evaluate and summarize them.
Theoretical framework and advanced applications of spiking neural networks
Authors: Zhu Shurui
Published: November 2023

Developed from traditional Artificial neural networks (ANN), the Spiking neural network (SNN) faithfully mimics the biological behaviours of natural neurons. SNNs transmit information through firing of spiking neurons only when the membrane potential reaches a certain threshold. Because of this property, SNNs are referred to as the most biologically plausible neural model. They are also evaluated as time-efficient and low power-consuming when dealing with complex computational tasks. In this paper, the differences between SNNs and ANNs are first identified. The theoretical framework of the SNN, including the biomedical background, classical spiking neuron models, neural coding mechanisms as well as the learning algorithm are then thoroughly introduced. From the theories, the SNN’s biological plausibility, working principles, strengths and limitations are discussed. Additionally, two applications in the medical & robotics field using the SNN’s pattern recognition and classification are described in detail, indicating its potential in more innovative studies. More imaginative uses of SNNs are in demand for its dominant role in future computational fields.
Convergence analysis of a positivity-preserving numerical scheme for the Cahn-Hilliard-Stokes system with Flory-Huggins energy potential
Authors: Guo Yunzhuo , Wang Cheng , Wise Steven , Zhang Zhengru
Published: November 2023

A finite difference numerical scheme is proposed and analyzed for the Cahn-Hilliard-Stokes system with Flory-Huggins energy functional. A convex splitting is applied to the chemical potential, which in turns leads to the implicit treatment for the singular logarithmic terms and the surface diffusion term, and an explicit update for the expansive concave term. The convective term for the phase variable, as well as the coupled term in the Stokes equation, is approximated in a semi-implicit manner. In the spatial discretization, the marker and cell difference method is applied, which evaluates the velocity components, the pressure and the phase variable at different cell locations. Such an approach ensures the divergence-free feature of the discrete velocity, and this property plays an important role in the analysis. The positivity-preserving property and the unique solvability of the proposed numerical scheme are theoretically justified, utilizing the singular nature of the logarithmic term as the phase variable approaches the singular limit values. An unconditional energy stability analysis is standard, as an outcome of the convex-concave decomposition technique. A convergence analysis with accompanying error estimate is provided for the proposed numerical scheme. In particular, a higher order consistency analysis, accomplished by supplementary functions, is performed to ensure the separation properties of numerical solution. In turn, using the approach of rough and refined error estimates, we are able to derive an optimal rate convergence. To conclude, several numerical experiments are presented to validate the theoretical analysis.
Social Ecological Influences on Nicotine/Tobacco Use Among Gender-Varying and Gender-Stable Adolescents and Adults in the USA
Authors: Kcomt Luisa , Evans-Polce Rebecca J , Engstrom Curtiss W , Takahashi Jodene , Matthews Phoenix A , Veliz Phil T , West Brady T , McCabe Sean Esteban
Published: November 2023

Background and Purpose

Our study examined individual-, interpersonal-, community-, and policy-level associations with nicotine/tobacco use among gender-varying and gender-stable U.S. individuals.

Methods

Data from Waves 2–4 (2014/15–2016/18) of the Population Assessment of Tobacco and Health (n = 33,197 U.S. adolescents and adults aged ≥14 years) and state-level gender minority policy data were used. Using multivariable logistic regression, the odds of past-30-day nicotine/tobacco use at W4 were estimated as a function of gender stability/variability, psychological distress, number of tobacco products used by family/friends, anti-tobacco marketing exposure, and change in gender minority-related policies from 2015 to 2017.

Results

Gender-varying individuals had higher odds of nicotine/tobacco use compared with gender-stable individuals (AOR range = 1.7–2.3, p < .01). In the overall sample, positive change in gender minority policy protections (tallied from medium to high) was associated with lower odds of any nicotine/tobacco, other tobacco, and poly-tobacco use (AOR = 0.8, p < .05) compared to states with no change in their negative policies. Anti-tobacco marketing exposure was associated with lower odds of any tobacco, cigarette, e-cigarette, and poly-tobacco use compared with those who had no anti-tobacco marketing exposure (AOR = 0.9, p < .05). Higher psychological distress (AOR range = 1.7–2.4, p < .001) and an increasing number of tobacco products used by family/friends (AOR range = 1.1–1.3, p < .001) were associated with increased odds of nicotine/tobacco use.

Conclusions

Multilevel prevention and intervention strategies are needed to reduce the risk of nicotine/tobacco use among gender-varying and gender-stable individuals.
Postacute symptoms 4 months after SARS-CoV-2 infection during the Omicron period: a nationwide Danish questionnaire study
Authors: Spiliopoulos Lampros , Sørensen Anna Irene Vedel , Bager Peter , Nielsen Nete Munk , Hansen Jørgen Vinsløv , Koch Anders , Meder Inger Kristine , Videbech Poul , Ethelberg Steen , Hviid Anders
Published: November 2023

Postacute symptoms are not uncommon after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with pre-Omicron variants. How the Omicron variant and coronavirus disease 2019 (COVID-19) booster vaccination influence the risk of postacute symptoms is less clear. We analyzed data from a nationwide Danish questionnaire study, EFTER-COVID, comprising 36 109 individuals aged ≥15 years who were tested between July 2021 and January 2022, to evaluate the associations of the Omicron variant and COVID-19 booster vaccination with postacute symptoms and new-onset general health problems 4 months after infection with SARS-CoV-2. Risk differences (RDs) were estimated by comparing Omicron cases with controls, comparing Omicron cases with Delta cases, and comparing Omicron cases vaccinated with 3 doses with those vaccinated with 2 doses, adjusting for age, sex, body mass index, self-reported chronic diseases, Charlson comorbidity index, health-care occupation, and vaccination status. Four months after testing for SARS-CoV-2 during the Omicron period, cases experienced substantial postacute symptoms and new-onset health problems in comparison with controls; the largest RD was observed for memory issues (RD = 7.4%; 95% CI, 6.4-8.3). However, risks were generally lower than those in the Delta period, particularly for dysosmia (RD = –15.0%; 95% CI, −17.0 to −13.2) and dysgeusia (RD = –11.2%; 95% CI, −13.2 to −9.5). Booster vaccination was associated with fewer postacute symptoms and new-onset health problems 4 months after Omicron infection as compared with 2 doses of COVID-19 vaccine.
Inconsistency in UK Biobank Event Definitions From Different Data Sources and Its Impact on Bias and Generalizability: A Case Study of Venous Thromboembolism
Authors: Bassett Emily , Broadbent James , Gill Dipender , Burgess Stephen , Mason Amy M
Published: November 2023

The UK Biobank study contains several sources of diagnostic data, including hospital inpatient data and data on self-reported conditions for approximately 500,000 participants and primary-care data for approximately 177,000 participants (35%). Epidemiologic investigations require a primary disease definition, but whether to combine data sources to maximize statistical power or focus on only 1 source to ensure a consistent outcome is not clear. The consistency of disease definitions was investigated for venous thromboembolism (VTE) by evaluating overlap when defining cases from 3 sources: hospital inpatient data, primary-care reports, and self-reported questionnaires. VTE cases showed little overlap between data sources, with only 6% of reported events for persons with primary-care data being identified by all 3 sources (hospital, primary-care, and self-reports), while 71% appeared in only 1 source. Deep vein thrombosis–only events represented 68% of self-reported VTE cases and 36% of hospital-reported VTE cases, while pulmonary embolism–only events represented 20% of self-reported VTE cases and 50% of hospital-reported VTE cases. Additionally, different distributions of sociodemographic characteristics were observed; for example, patients in 46% of hospital-reported VTE cases were female, compared with 58% of self-reported VTE cases. These results illustrate how seemingly neutral decisions taken to improve data quality can affect the representativeness of a data set.