bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and simulation of system to prevent runway overrun during landing of civil aircraft
Authors: Zhang Tao , Wang Xiaorui
Published: July 2024

The airborne runway overrun prevention system predicts landing distance by utilizing real-time aircraft status parameters obtained through onboard sensors. This system offers early warnings to pilots, thereby enhancing flight safety. This paper introduces a design scheme for a runway overrun prevention system considering aircraft dynamic performance. Initially, the study analyzes the basic components and functional requirements of the system based on the Minimum Operational Performance Standard For A Runway Overrun Awareness And Alerting System by the European Aviation Safety Agency. Subsequently, the approach and landing phases are segmented into four stages, providing a methodology for calculating landing distance using a dynamic model. Finally, concluded with a simulation verification conducted on the X-Plane flight simulation platform, we test the visual alarm system of the proposed runway overrun prevention system. Simulation results demonstrate that, during the landing phase, the system dynamically calculates and updates stopping points for each braking mode based on the current braking method. In situations where there is a risk of runway overrun, the system issues timely and well-founded alarms.
Optimization of the deformation transfer mechanism: analysis of spring hanging point and structural parameters
Authors: Lin Zhuoyu , Luo Kai , Zhang Meng , Yang Minghao
Published: July 2024

This paper thoroughly investigates the impact of the spring hanging point’s positioning and structural parameters on the multi-mode robot’s performance within the deformable transfer domain mechanism. The spring hanging point is a pivotal design element, significantly influencing the robot’s extensive deformation, efficiency, and adaptability. Operating as a cross-domain entity between land and air, the robot effectuates the transition between ground and aerial domains via the deformation trans-domain mechanism, executing a spectrum of intricate tasks. The precise placement of the spring hanging point and variations in structural parameters directly shape the robot’s performance metrics, encompassing deformation speed, stability, and energy utilization. Through elucidating fundamental principles, deliberating spring hanging point location choices, suggesting optimization methodologies, scrutinizing structural parameter impact on performance, and validating via dynamic modeling, this paper offers theoretical underpinnings for deforming domain mechanism design and enhancement, thereby elevating the robot’s overall efficacy.
Analysis of structural dynamic response of vertical sound barriers under natural wind and vehicle induced pulsating wind effects
Authors: Wen Duo , Zhang Xiao’an , Yang Li
Published: July 2024

Aiming at the influence of natural wind and vehicle-induced pulsating wind on vertical sound barriers, a finite element plug-in panel sound barrier is established based on the finite element method for dynamic response analysis. This paper establishes a sound barrier finite element analysis model based on finite element analysis software. It takes the 8-span vertical sound barrier as the basic working condition to analyze the dynamic response analysis of the sound barrier structure under the action of natural wind of different grades, i.e., the influence of pressure and displacement; the dynamic response of the sound barrier structure with a natural wind speed of 7 grades or more. In addition, it analyzes the dynamic properties of the sound barrier structure caused by train-induced pulsating wind pressure at speeds of more than 200 km/h, i.e., the influence of pressure and displacement, and investigates the dynamic characteristics of different vehicles with different wind speeds, pressure, and displacement. Furthermore, the response of the vertical sound barrier at different vehicle speeds is also explored, and the results are compared to examine its dynamic response. The research findings show that the sound barrier structure does not resonate during the self-resonance analysis, but the vibration of adjacent sound barrier panels affects each other. As natural wind speeds increase, the displacement of the steel column endpoints of the vertical sound barrier gradually increases; along the length of the sound barrier, the change of the peak pressure at the top of the steel columns and the top of the unit plate shows a symmetrical trend, and the displacements of the steel columns and the top of the unit plate show a trend of gradual increase in the travelling direction, and they both increase at the end of the column. The displacement of the top of the steel column and the top of the unit plate both show a trend of gradual increase along the direction of the vehicle, and both reach the maximum value at the end of the steel column and the unit plate. With the increase in vehicle speed, the overall peak displacement value also increases synchronously.
Design and analysis of sensor structure based on ultrasonic temperature measurement
Authors: Ye Shiqing , Cui Rongxu , Liu Dongjing , Zhang Yangyang , Li Jiahua , Huang Hui
Published: July 2024

Based on the principle of ultrasonic temperature measurement, this paper designs the structure of a waveguide rod sensor with a reflective groove. Using multi-physics field simulation software to conduct acoustic thermal coupling parametric simulation analysis on six different high melting point materials, we obtain the curve functions of the relationship between sound velocity and temperature for the six materials and verify the feasibility of ultrasonic temperature measurement using waveguide rods. Analysis shows that the sensitivity of six alloys to temperature changes is as follows: Ti6Al4V titanium alloy > α-Al2O3 > Inconel693 nickel-based alloy > ThO2 > Tungsten-rhenium alloy > Ta8W2Hf. At the same time, three different shapes of waveguide rods were designed: single groove waveguide rod, multi-zone waveguide rod, and spiral waveguide rod to analyze the impact of temperature measurement accuracy. The research results have important theoretical guidance significance for solving the problem of temperature measurement in high-temperature environments.
Structural design and simulation of herringbone groove bearing lubricated with liquid metal
Authors: Fu Zhenlei , Wang Wen
Published: July 2024

We designed a novel herringbone groove sliding bearing suitable for gallium-based liquid metal lubrication, taking advantage of the excellent fluidity, high thermal conductivity, and strong stability of gallium-based liquid metal at room temperature. We used the finite element method to analyze how eccentricity affected the bearing pressure variation and chose the best structural parameters by comparing how different groove parameters affected the peak pressure and carrying capacity. The results show that the herringbone groove reduces bearing friction resistance and causes the bearing pressure variation to exhibit a herringbone pattern. The herringbone groove structural parameters have a significant impact on the peak pressure and carrying capacity of the bearing. The gallium-based liquid metal bearing works well when the herringbone angle is 50°, the groove depth is between 15 μm and 25 μm, and the groove ratio is between 0.7 and 0.9.
Simulation and analysis of short circuit fault in ship power system based on simulink
Authors: Li Zhaoqiang , Yang Haijun , Wang Lingling , Ji Wendong
Published: July 2024

In this paper, a short-circuit fault simulation of a ship’s electrical power system is carried out based on Simulink. According to the power system sketch of the ship, a simulation model is built, initial conditions are set, two-phase short-circuit faults and three-phase short-circuit faults are simulated, and the simulation results are analyzed. The results show that the short-circuit fault has a large impact on both the generator side and the load side, in which the impact on the load side is more serious. At the generator side, the voltage of the corresponding phase drops by about 1/3-1/2, and the current increases by about 1.5 times. At the load side, when a two-phase short circuit occurs, the voltage drops to half of the original one, and when a three-phase short circuit occurs, the voltage drops to 0. The short-circuit current has the largest value at the beginning of the short circuit, then oscillates and decays, and finally stabilizes at about 15 times the normal working current.
An aging simulation method based on the change of input vector inside the critical path
Authors: Sang Qianqian , Yang Xinhuan , Wang Liang , Wang Shuo , Wang Chuanzheng , Yu Mingyan , Zhao Yuanfu
Published: July 2024

With the large-scale expansion and process shrinking of modern integrated circuits, aging has become one of the main factors threatening circuit reliability. To evaluate the impact of aging on circuit life, it is important to investigate aging simulation methods. Aiming at the problem of slow speed and insufficient accuracy of large-scale digital circuit aging simulation methods, a circuit aging simulation method based on the change of input vector inside the critical path (CICP) is proposed in this paper. First, the critical path (CP) with the tightest timing is extracted by static timing analysis (STA), and SPICE simulation is carried out to accurately predict the aging of the CP of the circuit. Second, the aging simulation is carried out considering the change of the internal input vector of the CP. The simulation results show that after changing the internal input signal, the aging path delay increases up to 3.5%.
Clustering statistical method of high dimensional sparse data based on fuzzy data
Authors: Wang Hu
Published: July 2024

Developing effective clustering and statistical methods for high-dimensional sparse data presents unique challenges compared to traditional low-dimensional data. To address this, a novel approach is proposed, leveraging fuzzy data principles to enhance the clustering and statistical performance of high-dimensional sparse datasets. The method builds upon the fuzzy C-means clustering algorithm, introducing key modifications for better suitability to high-dimensional sparse data. One crucial enhancement involves tackling the local optimization problem by optimizing the initial clustering center, significantly reducing clustering statistical time. Replacing the original Euclidean distance with cosine distance improves the clustering and statistical performance of high-dimensional sparse data. Experimental results have shown that this method has superior clustering statistical performance when the data dimensions are different. When the data dimension is low, and the blocking ratio is 10%, the clustering statistical effect is optimal. When the data dimension is high, and the blocking ratio is 40%, the clustering statistical effect is optimal. This method has higher hit rates and clustering statistical efficiency at different sparsity levels.
Research on topology optimization of carbon fiber reinforced composite electric vehicle helmet based on deep learning
Authors: Zhang Xiangkui , Wei Wei , Hu Ping , Han Chengxiang
Published: July 2024

To study the topology optimization of carbon fiber composite helmets, a method of optimizing the three-dimensional (hereinafter referred to as 3D) model based on a deep learning network after dimensionality reduction is proposed. In this method, the 3D shell model is expanded and tiled into two-dimensional (hereinafter referred to as 2D) grids based on the one-step inverse forming method. The variable density method (Isotropic Material Penalty Density method) is used to collect the data set required for deep learning training, and the U-Net neural network is built to complete the training. To obtain the input tensor of the neural network, the mechanical analysis of the 3D model is carried out, and the physical properties are imported into the network for learning. In this way, the 2D optimization results of the helmet model are obtained and then reflected in the 3D model according to the unit topology relationship to obtain the final optimization results. Then, the ordinary helmet and the optimized helmet are simulated and compared under the same quality to test their mechanical properties. The results show that the stiffness performance and energy absorption effect of the optimized helmet are stronger when the quality of the two helmets is the same.
Evaluation method of software reliability index
Authors: Wang Jia , Liu Fusheng , Shen Ying , Xu Dan
Published: July 2024

Software reliability refers to the ability of software not to cause system failure under specified conditions and within the specified time. With the increasing demand for equipment systems for software systems, the software system has become an important part of determining the success or failure of combat force system missions. The reliability assessment of the software system is becoming more and more important. Aiming at the problem of software reliability evaluation, this paper discusses the choice of reliability evaluation model. The model parameters are determined. On this basis, according to the selected reliability evaluation model, the model parameters are estimated through the collected data. Finally, the reliability evaluation analysis is carried out.
Prediction model for very high frequency communication interruption based on random forest regression algorithm
Authors: Han Chunyong , Li Yawei , Su Zhongzhi
Published: July 2024

The onboard Very High Frequency (VHF) communication is susceptible to interruption due to antenna radiation signal blockage caused by the aircraft body at certain angles resulting from changes in the aircraft’s attitude. To establish a prediction model for communication interruptions, data on the radiation power level, attitude angle 1, and attitude angle 2 of the antenna were initially collected. Subsequently, a machine learning model was constructed to predict the radiation power at two specific frequency points of a VHF communication antenna for helicopters. The model was built by using the random forest (RF) regression algorithm. For the prediction model of frequency point 1, the Goodness of Fit (R2) and Mean Squared Error (MSE) were 0.997 and 0.023, respectively, with feature importance scores of 0.98 for attitude angle 1 and 0.02 for attitude angle 2. For the prediction model of frequency point 2, the R2 and MSE were 0.999 and 0.008, respectively, with feature importance scores of 0.91 for attitude angle 1 and 0.09 for attitude angle 2. The study results indicate that the variation in attitude angle 1 significantly impacts the antenna’s radiation power. The RF regression model can effectively predict the onboard VHF communication capability, thereby providing technical support for reducing the potential risk of communication interruption.
Performance research of edge computing nodes based on heterogeneous environment
Authors: Cheng Wei , Lin Bing , Cheng Liming
Published: July 2024

Edge computing realizes real-time parallel storage and computing in a distributed way, which can reduce the data transmission cost. The edge nodes, which are composed of different heterogeneous physical devices and hardware resources, assume the computing and storage capacity of the edge network. At present, the resource characteristics and performance of heterogeneous edge nodes are difficult to characterize. Therefore, a resource-aware performance feature detection model for heterogeneous edge compute nodes is proposed in this study. This model is based on a resource utilization matrix and resource relative performance quantization algorithm to extract the performance characteristics of the same type of resources of the edge nodes, to realize multi-dimensional and systematic feature detection and description of heterogeneous edge nodes. On this basis, a weight-based edge node task scheduling algorithm is designed. The final verification results show that the CPU relative performance ratios of Node 1-Node 2, Node 1-Node 3, and Node 2-Node 3 are 6.23, 3.81, and 0.81 respectively. The performance relationship among the three nodes is Node 1> Node 3> Node 2. The test group and the verification group tend to be consistent overall. This method has a good application prospect.
Dynamic iterative imputation algorithm based on rough fuzzy C-Means clustering
Authors: Gong Zheng , Yan Chun , Liu Wei
Published: July 2024

Missing data is a very common phenomenon in daily life. To mitigate its adverse impact on data analysis, this paper proposes a dynamic iterative imputation algorithm based on the rough fuzzy C-means algorithm. The algorithm incorporates dynamic approximations to partition and iterate the cluster assignment of missing sample points, utilizing information from complete sample points within the same cluster for iterative imputation. The imputation results are evaluated by using MAE and RMSE metrics, and the optimal number of iterations and imputation values are determined by minimizing these metrics. To verify the effectiveness of the proposed algorithm, 6 UCI public datasets are selected for imputation tests, and the change curves of metric value with iterations are generated under different missing proportions in each dataset. The optimal imputation result is obtained based on the lowest point of the curve. Subsequently, the performance of the proposed algorithm is compared with three cluster-based and five machine learning-based imputation algorithms. The results demonstrate the significant superiority of the proposed algorithm over the other methods, achieving a more approximate imputation of missing values in the dataset.
Shock waves in Interstellar Cloud-Cloud and Wind-Cloud Collisions
Authors: Navarrete S. , Pinargote B. J. , Banda-Barragán W. E.
Published: July 2024

The interstellar medium (ISM) is a key ingredient of galaxies and their evolution, consisting of multiphase, turbulent dust and gas. Some of the star-forming regions in our Galaxy originate from cloud-cloud and wind-cloud collisions, which generate shock waves that change the physical and chemical properties of the gas. We utilise our own python-based shock-finding algorithm to study the properties and distribution of shocks in interstellar collisions. Such interactions are studied via 3D numerical simulations with different initial conditions: Cloud-cloud collisions (CCc): We identify four stages of evolution: pre-collision, compression, pass-through, and dissipation. We also vary the size of one of the colliding clouds. Larger clouds facilitate cloud erosion and the formation of more and stronger shocks at early stages. Shock distributions are also time-dependent, as strong shocks are only produced during the early stages. As the collisions evolve, turbulent kinetic energy is rapidly dissipated, so most perturbations become subsonic waves at late times. Wind-cloud collisions (WCc): we identify four stages: compression, stripping, expansion, and break-up. We study the evolution of several diagnostics in these clouds: energies (thermal and kinetic), temperature, displacement of the centre of mass, and mass-weighted averages of the cloud density and acceleration. We show, that the geometry of the cloud impact the diagnostic parameters, for example, smoothing the edges of the cloud leads to enhanced mass losses and dispersion, but has little impact on the shock distribution.
Lane-Emden equations for Relativistic Anisotropic Polytropes
Authors: Fernando Bustos Oscar
Published: July 2024

In this research work, spherically symmetric compact objects with anisotropic matter are studied within the framework of general relativity. For this purpose, the equation of state of the master polytrope P = Kργ
+ αρ − β is employed, which prevents the divergence of the tangential velocity at the object’s surface and generalizes the treatment of the equation of state. The corresponding Lane-Emden equation is derived and integrated using an anisotropy function that encompasses conformally flat polytropes and vanishing compactness factor. Furthermore, the physical acceptability conditions of the solutions are analyzed.
Stellar models with like-Wyman IIa complexity factor
Authors: Andrade J. , Andrade D.
Published: July 2024

The goal of this work is to build a new family of stellar interior solutions in the anisotropic regime of pressure using the framework of gravitational decoupling via minimal geometric deformation. For such purpose, we use a generalization of the complexity factor of the well-known Wyman IIa (n = 1) interior solution in order to close the Einstein’s Field Equations, as well we use the Wyman IIa, Tolman IV, and Heintzmann IIa and Durgapal IV models as seeds solutions. These models fulfill the fundamental physical acceptability conditions for the compactness factor of the system 4U 1820-30. Stability against convection and against collapse are also studied.
Virtual Acoustic Characterization of a Multipurpose Sports Facility: A Case Study of the Coliseum at “Unidad Educativa Municipal Sebastián de Benalcázar”, Quito, Ecuador
Authors: Jácome L S , Simbaña P , Cadena G
Published: July 2024

This study presents a virtual acoustic characterization of a multipurpose sports facility, focusing on a case study of the coliseum at “Unidad Educativa Municipal Sebastián de Benalcázar” in Quito, Ecuador. Utilizing a non-intrusive, simulation-based approach, an initial detailed survey of the coliseum’s interior was conducted. AutoCAD and SketchUp software were utilized to generate a three-dimensional (3D) model based on the acquired data. This model was then exported to ODEON software for acoustic simulation. Important acoustic parameters, including reverberation duration, clarity, STI (Speech Transmission Index), and RASTI (Rapid Speech Transmission Index), were obtained from the simulation. These parameters were instrumental in characterizing the sports facility’s acoustic quality and comparing it with established reference values. Special emphasis was given to the initial parameters of reverberation time and STI, crucial for assessing the acoustic quality of the space. This virtual characterization provides significant insights into the acoustical properties of the coliseum, highlighting its potential and limitations as a multifunctional sports venue. The present study makes a significant contribution to the field of virtual acoustic assessments by providing a comprehensive framework for future improvements in the acoustic design and sound quality of similar environments. The study specifically addresses the distinct geographical and architectural context of Quito, Ecuador.
First model of industrial noise propagation in the vicinity of the Yasuní National Park
Authors: Velasco Geoconda M. , Vásconez C. L. , Xulvi-Brunet R. , Dueñas-Vidal A. , Vizcarra S. , de la Cruz I. , Rivera-Parra P. , Rivera-Parra J. L.
Published: July 2024

This work addresses aspects of industrial noise produced by the facilities of oil extraction near Yasuní National Park, located in the Ecuadorian Amazon region. The acoustic sources within this kind of facilities could influence in the wildlife behavior, which could impact negatively on the species. The acoustic wave radial propagation model in an open field is proposed through a geometric divergence attenuation, atmospheric absorption effect, dispersion effects due to obstacles, and soil effects. The initial model without obstacles makes predictions based on an algorithm considering that the data are associated to a GPS position, the first propagation model without obstacles determines the level of sound pressure for each quasi-horizontal measurement (x, y). Then, dispersion factors are incorporated through the NORD2000 model to consider the local flora that introduces reflection and dispersion phenomena which are in the environment considering geometric measurements estimated in situ. The pressure level of the model without obstacles decreases as the frequency increases, but with less intensity compared to the pressure level of the model with obstacles. As the frequency increases, there are important fluctuations since the attenuating factors influence more than the correction factors.
Martin-Puplett interferometer for studying THz and subTHz radiation
Authors: Nazhmudinov R M , Kishin I A , Yu Kidanova E , Karataev P V
Published: July 2024

The design of a portable terahertz and subterahertz interferometer, manufactured according to the Martin-Puplett scheme, is presented. The possibility of using film polypropylene polarizers in interferometers of this type has been demonstrated. The provided possibility of using various types of radiation detectors makes it possible to perform measurements in high-performance or high-sensitivity modes. The presented interferometer is proposed to be used to measure the spectra of terahertz and subterahertz radiation produced during the interaction of bunched and continuous beams of charged particles with solid targets.
Effect of ultrasound exposure time in the size distribution of lecithin liposomes in the nanoscale
Authors: Barros J L , Rodríguez V A , Bayas M V
Published: July 2024

The characteristics of liposome suspensions subjected to ultrasound were studied using the Nanoparticle Trajectory Analysis (NTA) technique. These were prepared with either DPPC or soy lecithin using the thin layer method. For each preparation protocol, the size and ζ potential probability densities were determined by averaging the densities obtained in several measurements. Ultrasound exposure changed the characteristics of the size and ζ potential distributions. For the size distribution, the exposure resulted in an increment of the number of liposomes with diameters in the range of ∼ 100 nm, the corresponding size distributions became slimmer, with mean diameters smaller than the ones without exposure. This is reflected in the reduction of the polydispersity index experienced by the liposome suspensions after sonication. For DPPC liposomes, it changed from ≈ 0.26 without exposure to ≈ 0.19 after 10 min sonication whereas for soy lecithin liposomes it changed from ≈ 0.30 without exposure to ≈ 0.21 after 10 min sonication. For the ζ potential, after 10 min exposure, the distributions became wider, with mean values more negative than the ones without exposure. The mean ζ potential, for DPPC liposomes, changed from ≈ −35 mV without exposure to ≈ −39 mV after 10 min sonication whereas for soy lecithin liposomes it changed from ≈ −38 mV without exposure to ≈ −42 mV after 10 min sonication. Therefore, our results show that exposure to ultrasound reduced the polydispersity and increased the stability of the liposome suspensions.
Enhanced fluorescence emission of a single quantum dot in a porous silicon photonic crystal—plasmonic hybrid resonator
Authors: Granizo Evelyn , Kriukova Irina , Escudero-Villa Pedro , Samokhvalov Pavel , Nabiev Igor
Published: July 2024

Currently, much interest is attracted to investigating the potential of hybrid systems that exhibit plasmon-induced photoluminescence (PL) enhancement of quantum emitters in terms of optoelectronics and biosensing applications. The implementation of these systems based on photonic microcavities offers benefits due to a stronger localization of the field within the resonant cavity. Porous silicon is one of interesting materials for engineering such microcavities thanks to the simplicity of its fabrication and the possibility to embed emitters from the solution into a ready-made resonator. In this theoretical study, the fluorescence enhancement of a quantum dot (QD) in a hybrid system based on a porous silicon microcavity (pSiMC) and silver nanoplatelets (AgNPs) was investigated using finite element method (FEM) numerical simulations. For this purpose, infinite arrays were simulated by using a periodic unit cell. The pSiMC was designed as two λ/4 distributed Bragg reflectors with alternating refractive indices and a cavity layer of a double thickness between them. For comparison, simulations were also performed for an AgNP and a QD in a reference monolayer with a constant refractive index without a microcavity structure. The results show QD fluorescence enhancement in the AgNP/pSiMC hybrid system, mainly due to the higher excitation rate.
Quantum fluctuation dynamics of open quantum systems with collective operator-valued rates, and applications to Hopfield-like networks
Authors: Fiorelli Eliana
Published: July 2024

We consider a class of open quantum many-body systems that evolves in a Markovian fashion, the dynamical generator being in GKS-Lindblad form. Here, the Hamiltonian contribution is characterized by an all-to-all coupling, and the dissipation features local transitions that depend on collective, operator-valued rates, encoding average properties of the system. These types of generators can be formally obtained by generalizing, to the quantum realm, classical (mean-field) stochastic Markov dynamics, with state-dependent transitions. Focusing on the dynamics emerging in the limit of infinitely large systems, we build on the exactness of the mean-field equations for the dynamics of average operators. In this framework, we derive the dynamics of quantum fluctuation operators, that can be used in turn to understand the fate of quantum correlations in the system. We then apply our results to quantum generalized Hopfield associative memories. Here we show that, asymptotically and at the description level of quantum fluctuations, only a very weak amount of quantum correlations, in the form of quantum discord, emerges beyond classical correlations.
Direct 3D printing of freeform anisotropic bioactive structure based on shear-oriented ink system
Authors: Yuan Chenhui , Jiang Jinhong , Zhang Xinyu , Gu Lin , Wang Xueping , Shao Lei
Published: July 2024

Various anisotropic tissue structures exist in organisms, including muscle tissue, skin tissue, and nerve tissue. Replicating anisotropic tissue structures in vitro has posed a significant challenge. Three-dimensional (3D) printing technology is often used to fabricate biomimetic structures due to its advantages in manufacturing principle. However, direct 3D printing of freeform anisotropic bioactive structures has not been reported. To tackle this challenge, we developed a ternary F/G/P ink system that integrates the printability of Pluronic F127 (F), the robust bioactivity and photocrosslinking properties of gelatin methacryloyl (G), and the shear-induced alignment functionality of high-molecular-weight polyethylene glycol (P). And through this strategic ternary system combination, freeform anisotropic tissue structures can be 3D printed directly. Moreover, these anisotropic structures exhibit excellent bioactivity, and promote orientational growth of different cells. This advancement holds promise for the repair and replacement of anisotropic tissues within the human body.
Facile printing of liquid–metal-based stretchable conductor using EGaIn/Ga2O3 composite
Authors: Wang Yi-Fei , Kaneko Takeru , Yoshida Ayako , Takeda Yasunori , Yoshida Junya , Sekine Tomohito , Kumaki Daisuke , Tokito Shizuo
Published: July 2024

Printing gallium-based liquid metals (LMs) poses a significant challenge due to their high surface tension. In this work, we introduce a printable LM-based conductor using an EGaIn/Ga2O3 composite. This composite is achieved through a simple mixing process and is suitable for scalable stencil printing. The blend ratio of EGaIn/Ga2O3 is optimized to create LM pastes with an excellent balance of printability and electromechanical performance. Using these developed LM pastes, we successfully demonstrate a stretchable strain sensor with a gauge factor of 2 for monitoring human hand gestures. Additionally, we showcase a stretchable LED array deformable for up to 100% strain.
Stochastic eigenvalue computation for cantilever beam dynamics using eigenvector-based polynomial chaos expansion
Authors: Kumar Rakesh
Published: July 2024

This paper presents an innovative technique for ascertaining the eigenfrequencies of beams characterized by a random elastic modulus. Our method leverages Polynomial Chaos Expansion (PCE), uniquely focusing on the expansion of eigen vectors rather than the conventional approach of expanding both eigenvalues and eigenvectors. An exceptional aspect of our proposed methodology lies in its seamless integration with the widely-utilized MATLAB ‘eig’ tool, offering a more accessible and efficient solution. To validate the accuracy of our proposed method, we performed comparisons against Monte Carlo simulations, showcasing excellent agreement with both benchmarks. Notably, the mean of our method demonstrates consistent alignment with Monte Carlo simulations, further affirming its precision. We further investigated the computational cost of our method and contrasted it with Monte Carlo simulations, demonstrating its efficiency and computational advantages.
Central lines, aseptic batching services, and infection rates: A pharmacy-led initiative of intravenous tube priming within a NICU
Authors: Zackeroff Sydney , Nash David , McDermott Kathleen , Miller Rachel R , Pasquini Grace
Published: July 2024

Purpose

Central line–associated bloodstream infections (CLABSIs) are hospital-acquired, serious complications that greatly affect many vulnerable neonates throughout their hospital stay. This article describes the implementation of a unique practice in which pharmacy primes continuous infusions through medication tubing for neonatal central lines in a cleanroom at Children’s Hospital Colorado – Colorado Springs (CHCO-CSH).

This institution is a freestanding children’s hospital with a level III neonatal intensive care unit (NICU) that opened in April 2019. Since then, the pharmacy department has been priming central line tubing for continuous infusions for all patients in the NICU. Neonates are at increased risk for developing CLABSIs due to their immature immune systems and frequent need for central line placement. With that in mind, the pharmacy department decided to focus efforts on this population. Pharmacists and pharmacy technicians received training on how to properly prime tubing, document when a patient received a new central line, document if a central line was removed, and record when new tubing was due based on a department policy.

Conclusion

This novel, pharmacy-led priming procedure resulted in a low CLABSI incidence, offering a promising strategy to reduce CLABSIs in a NICU.
A possible case of adaptive radiation in cycads. A commentary on ‘Transcriptome sequencing data provide a solid base to understand the phylogenetic relationships, biogeography and reticulated evolution of the genus Zamia L. (Cycadales: Zamiaceae)’
Authors: Gutiérrez-Ortega José Said , Villarreal A. Juan Carlos
Published: July 2024

This article comments on:

Anders Lindstrom, Sadaf Habib, Shanshan Dong, Yiqing Gong, Jian Liu, Michael Calonje, Dennis Stevenson and Shouzhou Zhang, Transcriptome sequencing data provide a solid base to understand the phylogenetic relationships, biogeography and reticulated evolution of the genus Zamia L. (Cycadales: Zamiaceae), Annals of Botany, Volume 134, Issue 5, 1 November 2024, Pages 747–768 https://doi.org/10.1093/aob/mcae065
Normative Data for the Famous People Fluency Test in the Adult French-Quebec Population and Validation Study in Mild Cognitive Impairment and Alzheimer’s Disease
Authors: Macoir Joël , Landry Mariane , Hudon Carol
Published: July 2024

Objective

The production of words in verbal fluency tests relies heavily on executive functions and linguistic abilities. New tests such as the famous people fluency test can also be useful in clinical practice and research. This test, in which participants are asked to name so many famous people, has the potential to distinguish healthy individuals from participants with neurological disorders such as mild cognitive impairment or Alzheimer’s disease.

Method

The aim of this study was to determine the psychometric validity of the test (Study 1) and to provide normative data in the adult population of French Quebec for the famous people fluency test (Study 2).

Results

The results of the normative study, derived from a sample of 378 healthy individuals between the ages of 50 and 92, showed that age and educational level significantly influence performance on the test. Therefore, percentile ranks were calculated for performance on the famous people fluency test, stratified for these two variables. The results of Study 2 showed that the test differentiated the performance of healthy participants from the performance of participants with mild cognitive impairment or Alzheimer’s disease. The results also showed that the famous people fluency test has adequate convergent validity, established with a semantic fluency test, and that the results showed good stability over time (test–retest validity).

Conclusion

Norms and psychometric data for the famous people fluency test will improve the ability of clinicians and researchers to better recognize executive and language impairments associated with pathological conditions.
Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework
Authors: Zhang Guoqing , Wang Hui , Zhang Zhiguo , Zhang Lu , Guo Guibing , Yang Jian , Yuan Fajie , Ju Feng
Published: July 2024

High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding gene sequences. However, accurately assigning protein functions to novel gene sequences remain a challenge. To this end, we developed FunGeneTyper, an extensible framework with two new deep learning models (i.e., FunTrans and FunRep), structured databases, and supporting resources for achieving highly accurate (Accuracy > 0.99, F1-score > 0.97) and fine-grained classification of antibiotic resistance genes (ARGs) and virulence factor genes. Using an experimentally confirmed dataset of ARGs comprising remote homologous sequences as the test set, our framework achieves by-far-the-best performance in the discovery of new ARGs from human gut (F1-score: 0.6948), wastewater (0.6072), and soil (0.5445) microbiomes, beating the state-of-the-art bioinformatics tools and sequence alignment-based (F1-score: 0.0556–0.5065) and domain-based (F1-score: 0.2630–0.5224) annotation approaches. Furthermore, our framework is implemented as a lightweight, privacy-preserving, and plug-and-play neural network module, facilitating its versatility and accessibility to developers and users worldwide. We anticipate widespread utilization of FunGeneTyper (https://github.com/emblab-westlake/FunGeneTyper) for precise classification of protein-coding gene functions and the discovery of numerous valuable enzymes. This advancement will have a significant impact on various fields, including microbiome research, biotechnology, metagenomics, and bioinformatics.
Flow inefficiencies in non-obstructive HCM revealed by kinetic energy and hemodynamic forces on 4D-flow CMR
Authors: Pola K , Ashkir Z , Myerson S , Arheden H , Watkins H , Neubauer S , Arvidsson P M , Raman B
Published: July 2024

Aims

Patients with non-obstructive hypertrophic cardiomyopathy (HCM) exhibit myocardial changes which may cause flow inefficiencies not detectable on echocardiogram. We investigated whether left ventricular (LV) kinetic energy (KE) and hemodynamic forces (HDF) on 4D-flow cardiovascular magnetic resonance (CMR) can provide more sensitive measures of flow in non-obstructive HCM.

Methods and results

Ninety participants (70 with non-obstructive HCM and 20 healthy controls) underwent 4D-flow CMR. Patients were categorized as phenotype positive (P+) based on maximum wall thickness (MWT) ≥ 15 mm or ≥13 mm for familial HCM, or pre-hypertrophic sarcomeric variant carriers (P−). LV KE and HDF were computed from 4D-flow CMR. Stroke work was computed using a previously validated non-invasive method. P+ and P− patients and controls had comparable diastolic velocities and LV outflow gradients on echocardiography, LV ejection fraction, and stroke volume on CMR. P+ patients had greater stroke work than P− patients, higher systolic KE compared with controls (5.8 vs. 4.1 mJ, P = 0.0009), and higher late diastolic KE relative to P− patients and controls (2.6 vs. 1.4 vs. 1.9 mJ, P < 0.0001, respectively). MWT was associated with systolic KE (r = 0.5, P < 0.0001) and diastolic KE (r = 0.4, P = 0.005), which also correlated with stroke work. Systolic HDF ratio was increased in P+ patients compared with controls (1.0 vs. 0.8, P = 0.03) and correlated with MWT (r = 0.3, P = 0.004). Diastolic HDF was similar between groups. Sarcomeric variant status was not associated with KE or HDF.

Conclusion

Despite normal flow velocities on echocardiography, patients with non-obstructive HCM exhibited greater stroke work, systolic KE and HDF ratio, and late diastolic KE relative to controls. 4D-flow CMR provides more sensitive measures of haemodynamic inefficiencies in HCM, holding promise for clinical trials of novel therapies and clinical surveillance of non-obstructive HCM.
Joint and Individual Mitochondrial DNA Variation and Cognitive Outcomes in Black and White Older Adults
Authors: Odden Michelle C , Li Yongmei , Jotwani Vasantha , Dobrota Sylvie , Tan Annabel X , Cummings Steven R , Shlipak Michael G , Scherzer Rebecca , Ix Joachim H , Buckwalter Marion S , Tranah Gregory J
Published: July 2024

Background

Mitochondrial dysfunction manifests in neurodegenerative diseases and other age-associated disorders. In this study, we examined variation in inherited mitochondrial DNA (mtDNA) sequences in Black and White participants from 2 large aging studies to identify variants related to cognitive function.

Methods

Participants included self-reported Black and White adults aged ≥70 years in the Lifestyle Interventions and Independence for Elders (LIFE; N = 1 319) and Health Aging and Body Composition (Health ABC; N = 788) studies. Cognitive function was measured by the Digit-Symbol Substitution Test (DSST), and the Modified Mini-Mental State Examination (3MSE) at baseline and over follow-up in LIFE (3.6 years) and Health ABC (10 years). We examined the joint effects of multiple variants across 16 functional mitochondrial regions with cognitive function using a sequence kernel association test. Based on these results, we prioritized meta-analysis of common variants in Black and White participants using mixed effects models. A Bonferroni-adjusted p value of <.05 was considered statistically significant.

Results

Joint variation in subunits ND1, ND2, and ND5 of Complex I, 12S RNA, and hypervariable region (HVR) were significantly associated with DSST and 3MSE at baseline. In meta-analyses among Black participants, variant m.4216T>C, ND1 was associated with a faster decline in 3MSE, and variant m.462C>T in the HVR was associated with a slower decline in DSST. Variant m.5460G>C, ND2 was associated with slower and m.182C>T in the HVR was associated with faster decline in 3MSE in White participants.

Conclusions

Among Black and White adults, oxidative phosphorylation Complex I variants were associated with cognitive function.
Sketch-and-solve approaches to k-means clustering by semidefinite programming
Authors: Clum Charles , Mixon Dustin G , O’Hare Kaiying , Villar Soledad
Published: July 2024

We study a sketch-and-solve approach to speed up the Peng–Wei semidefinite relaxation of $k$-means clustering. When the data are appropriately separated we identify the $k$-means optimal clustering. Otherwise, our approach provides a high-confidence lower bound on the optimal $k$-means value. This lower bound is data-driven; it does not make any assumption on the data nor how they are generated. We provide code and an extensive set of numerical experiments where we use this approach to certify approximate optimality of clustering solutions obtained by k-means++.
Identity in the Presence of Adjunction
Authors: Stroiński Mateusz
Published: July 2024

We develop a theory of adjunctions in semigroup categories, that is, monoidal categories without a unit object. We show that a rigid semigroup category is promonoidal, and thus one can naturally adjoin a unit object to it. This extends the previous results of Houston in the symmetric case, and addresses a question of his. It also extends the results in the non-symmetric case with additional finiteness assumptions, obtained by Benson–Etingof–Ostrik, Coulembier, and Ko–Mazorchuk–Zhang. We give an interpretation of these results using comonad cohomology, and, in the absence of finiteness conditions, using enriched traces of monoidal categories. As an application of our results, we give a characterization of finite tensor categories in terms of the finitary $2$-representation theory of Mazorchuk–Miemietz.
“For the first time…I am seriously fighting burnout”: clinician experiences with a challenging electronic health record transition
Authors: Ball Sherry L , Rucci Justin M , Molloy-Paolillo Brianne K , Cutrona Sarah L , Brunner Julian , Mohr David C , Kim Bo , Moldestad Megan , Zepeda E David , Orlander Jay D , Anderson Ekaterina , Cohen-Bearak Adena , Helfrich Christian D , Sayre George , Rinne Seppo T
Published: July 2024

Objectives

The Department of Veterans Affairs (VA) is transitioning from its legacy electronic health record (EHR) to a new commercial EHR in a nationwide, rolling-wave transition. We evaluated clinician and staff experiences to identify strategies to improve future EHR rollouts.

Materials and Methods

We completed a convergent mixed-methods formative evaluation collecting survey and interview data to measure and describe clinician and staff experiences. Survey responses were analyzed using descriptive statistics; interview transcripts were coded using a combination of a priori and emergent codes followed by qualitative content analysis. Qualitative and quantitative findings were compared to provide a more comprehensive understanding of participant experience. Employees of specialty and primary care teams at the first nationwide EHR transition site agreed to participate in our study. We distributed surveys at 1-month pre-transition, 2 months post-transition, and 10 months post-transition to each of the 68 identified team members and completed longitudinal interviews with 30 of these individuals totaling 122 semi-structured interviews.

Results

Interview participants reported profoundly disruptive experiences during the EHR transition that persisted at 1-year post implementation. Survey responses indicated training difficulties throughout the transition, and sharp declines (P ≤ .05) between pre- and post-go-live measures of EHR usability and increase in EHR burden that were perceived to be due in part to system inefficiencies, discordant positive messaging that initially ignored user challenges, and inadequate support for and attention to ongoing EHR issues. Participants described persistent high levels of stress associated with these disruptions.

Discussion

Our findings highlight strategies to improve employee experiences during EHR transitions: (1) working with Oracle Cerner to resolve known issues and improve usability; (2) role-based training with opportunities for self-directed learning; (3) peer-led support systems and timely feedback on issues; (4) messaging that responds to challenges and successes; and (5) continuous efforts to support staff with issues and address clinician and staff stress and burnout.

Conclusion

Our findings provide relevant strategies to navigate future EHR transitions while supporting clinical teams.