bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of threats during the bodywork and paint repair process
Authors: Kuliś Ewa
Published: February 2024

Body repairs are often based not so much on procedures as on the experience of the people who perform these repairs. The problem is that heat repairs change the internal structure of the vehicle's skin. When obtaining homologation, manufacturers must prove the specific strength of the materials during crash tests. During a bodywork repair, these parameters may change, and after the repair, there is no obligation to check the strength parameters of a specific element or system. By interfering with the structure, we cannot be sure that we still maintain an appropriate level of security. Therefore, during further tests, together with a team from the Bydgoszcz University of Technology, we plan to check the strength parameters of the vehicle's skin after repair. And what impact on the structure of the material is the duration of individual stages of sheet metal work, the intensity of the current and the temperature to which the material is heated in order to optimize the parameters and increase the level of safety of users.
Reassembling digital archives—strategies for counter-archiving
Authors: Blanke Tobias
Published: February 2024

Archives have long been a key concern of academic debates about truth, memory, recording and power and are important sites for social sciences and humanities research. This has been the case for traditional archives, but these debates have accelerated with the digital transformation of archives. The proliferation of digital tools and the fast-growing increase in digital materials have created very large digitised and born-digital archives. This article investigates how new digital archives continue existing archival practices while at the same time discontinuing them. We present novel methodologies and tools for changing memory and power relations in digital archives through new ways of reassembling marginalised, non-canonical entities in digital archives. Reassembling digital archives can take advantage of the materiality and the algorithmic processuality of digital collections and reshape them to inscribe lost voices and previously ignored differences. Digital archives are not fixed and are changed with new research and political questions and are only identified through new questions. The article presents six distinct techniques and strategies to reassemble digital archives and renders these according to three different types of new digital archives. We consider both the extension of archives towards evidence that is otherwise thrown away as well as the provision of new intensive, non-discriminatory viewpoints on existing collections.
Understanding the self-perceived customer experience and repurchase intention in live streaming shopping: evidence from China
Authors: Yi Minqin , Chen Ming , Yang Jilang
Published: February 2024

As an increasingly mature way of shopping in China, live streaming shopping still faces the problems of high return rates and low repurchase rates. Based on the expectation confirmation theory, this study uses structural equation modeling (SEM) to explore the repurchase intention of live streaming shopping(LSS)users. The results show that perceived interactivity, perceived quality and perceived value have a direct and significant effect on confirmation and customer satisfaction. Perceived discounts do not directly improve user satisfaction; they must pass through a complete intermediary variable of confirmation. In addition, we also verified that the degree of confirmation affects satisfaction, and satisfaction has an impact on repurchase intention. Finally, our model tested gender factors as a control variable and found that gender differences significantly impact consumers’ repurchase intentions. Considering these findings, we provide practical suggestions for retaining users and hopefully promoting the long-term development of live streaming shopping.
A scoping review of the literature on content and language integrated learning assessment
Authors: Liang Weijun , Wu Yanjun
Published: February 2024

Despite being an essential element of Content and Language Integrated Learning (CLIL), CLIL assessment has received scarce
research attention and remains a relatively underexplored area. Since few review studies have been conducted in the field of CLIL
assessment, this article constitutes the first attempt to synthesise both theoretical and empirical studies on CLIL assessment around the
globe with a view to yielding implications for the understanding, design, and improvement of assessment in CLIL and providing suggestions
for future research agendas. Based on a thematic analysis of 77 pertinent publications selected among 763 search results, this scoping
review first identified three prominent research themes in CLIL assessment including assessment issues, assessment practices, and assessment
frameworks. Subsequently, the review elaborated each theme and discussed some interesting patterns of the literature in great depth. The
review concluded with suggestions on future research directions with a view to advancing the uncharted area of CLIL assessment.
The scattering map on collapsing charged spherically symmetric spacetimes
Authors: Alford Fred
Published: February 2024

In this paper we generalise our previous results (Alford 2020 Ann. Inst. Henri Poincare
21 2031–92) concerning scattering on the exterior of collapsing dust clouds to the charged case, including in particular the extremal case. We analyse the energy boundedness of solutions φ to the wave equation on the exterior of collapsing spherically symmetric charged matter clouds. We then proceed to define the scattering map on this spacetime, and look at the implications of our boundedness results on this map. More specifically, we first construct a class of spherically symmetric charged collapsing matter cloud exteriors, and then consider solutions to the wave equation with Dirichlet (reflective) boundary conditions on the surface of these clouds. We then show that the energy of φ remains uniformly bounded going forwards or backwards in time, and that the scattering map is bounded going forwards but not backwards. Therefore, the scattering map is not surjective onto the space of finite energy on

I

+

∪

H

+

. Thus there does not exist a backwards scattering map from finite energy radiation fields on

I

+

∪

H

+

to finite energy radiation fields on

I

−

for these models. These results will be used to give a treatment of Hawking radiation in a companion paper (Alford 2023 arXiv:2309.03022).
Atomic-scale insight into arc plasma radiation-induced gassing materials ablation: photothermal decomposition behavior
Authors: Cao Weidong , Li Xingwen , Zhang Yanfeng , Wang Qian , Yu Renjie , Chen Zhenyi , Zhuang Tao
Published: February 2024

In this study, we present a novel computational atomistic study of the photothermal decomposition behavior of arc plasma on radiation-induced gassing materials ablation, studying a polyamide 66 (PA66) system using reactive force field (ReaxFF) molecular dynamics (MD). We determine the infrared (IR) vibrational frequency of the PA66 permanent molecular dipole using MD and then computationally impose an electric field at the same frequency to simulate photothermal decomposition by IR, verifying our observations with gas chromatography-mass spectrometry (GCMS) of experimental decomposition. MD indicates that photothermal decomposition reaction is dominated by either cleavage at low temperature or cyclization at high temperature. At low temperature, initial chain scission takes place at the two amide C–N, and the remaining chains break down into a variety of molecular fragments and free radicals. Further increasing the temperature stabilizes a variety of branched chain structures via cyclization, debranching and polymerization, with further cleavage forming hydrocarbons and volatile small molecule gases. Overall, H2, CO, H2O, alkanes and alkenes are the main gaseous products and cyclic structures (especially nitrogen-containing three-membered ring) are the main solid products during the photothermal decomposition of PA66, and their formation results from a variety of complex chemical reactions. The results of MD cover the experimental observations of GCMS, demonstrating that this computational methodology helps us understand the molecular breakdown mechanisms of arc plasma radiation-induced gassing materials. We also discuss the physical mechanism by which the main gas can accelerate arc quenching, and the importance and necessity of using electric fields to simulate IR photothermal decomposition of arc-induced ablation.
Thermal evolution of low-temperature magnetic texture modulation in fept thin films by direct visualization
Authors: Quinteros Cynthia P , Goijman Dafne , Damerio Silvia , Milano Julián
Published: February 2024

Patterns of ferroic domains and domain walls are being intensively studied to implement new logic schemes. Any technological application of such objects depends on a detailed understanding of them. Using low-temperature magnetic force measurements (10–300 K), the evolution of ferromagnetic stripes on equiatomic FePt thin films is thoroughly analyzed. Since FePt is known to develop a transition from in-plane homogeneous magnetization to stripe domains upon varying its thickness, multiple samples are studied demonstrating the well-established reduction upon thickness decrease and a non-trivial dependence on temperature. Moreover, the room-temperature uniform distribution of the pattern evolves into a distorted one upon temperature cycling. Finally, dissimilar stripe patterns are obtained upon reducing and increasing temperature indicating the states are dependent on the history of applied stimuli rather than the parametric conditions.
An effective approach for aerosol dynamics modeling in dusty plasma
Authors: Tetard G , Michau A , Prasanna S , Hassouni K
Published: February 2024

In this paper, we demonstrate the application of the Dirac-lognormal bimodal moment approach to investigate aerosol dynamics in dusty plasmas. This approach was evaluated by comparison with the detailed and computationally expensive sectional approach for two dusty plasma systems. The first one is a sputtering Argon DC discharge and the second is a capacitively coupled Ar/C2H2 radio-frequency (CCRF) discharge. The results obtained by the bimodal and the sectional approaches are in good agreement for the sputtering DC discharge where the aerosol dynamics is dominated by nucleation and surface deposition growth processes. This agreement is obtained not only on the averaged characteristics of the particle cloud, but also on the detailed particle size distributions. In the case of the CCRF discharge a satisfactory agreement between the two approaches is obtained on the averaged characteristics and on the core distributions of the particle cloud even if a significant difference is observed at low and intermediate particle size. Nevertheless, the bimodal moment approach is accurate enough for the simulation of the dusty plasmas of interest. Its low-computational cost makes it a very effective method as far as dusty plasma simulation is concerned.
Predicting materials properties with generative models: applying generative adversarial networks for heat flux generation
Authors: Kong Qi , Shibuta Yasushi
Published: February 2024

In the realm of materials science, the integration of machine learning techniques has ushered in a transformative era. This study delves into the innovative application of generative adversarial networks (GANs) for generating heat flux data, a pivotal step in predicting lattice thermal conductivity within metallic materials. Leveraging GANs, this research explores the generation of meaningful heat flux data, which has a high degree of similarity with that calculated by molecular dynamics simulations. This study demonstrates the potential of artificial intelligence (AI) in understanding the complex physical meaning of data in materials science. By harnessing the power of such AI to generate data that is previously attainable only through experiments or simulations, new opportunities arise for exploring and predicting properties of materials.
Study on the detection technology for inner-wall outer surface defects of the automotive ABS brake master cylinder based on BM-YOLOv8
Authors: Liu Guixiong , Yan Yipu , Meng Joe
Published: February 2024

A defect detection approach based on the BiFormer + MPDIoU’s YOLOv8 (BM-YOLOv8) model is proposed which addresses the challenges of low accuracy and low efficiency in detecting tiny defects on the inner-wall outer surface of automotive Anti-lock Brake Systems (ABS) brake master cylinder. This method constructs an imaging model based on process parameters such as speed and inspection accuracy required during the production of automotive ABS brake master cylinder. On this basis, it employs the dynamic sparse self-attention mechanism of the BiFormer to build a network for self-attention feature extraction and fusion. It also utilizes the Minimum Point Distance Intersection over Union (MPDIoU) to optimize the bounding box regression loss function, allowing for precise detection of defects on the inner-wall outer surface of automotive ABS brake master cylinder. Both qualitative and quantitative studies demonstrated that the BM-YOLOv8 method achieves a defect identification rate of 98.8% for the inner-wall outer surface defects of automotive ABS brake master cylinder. More than 25 images per second can be detected in this process. The performance of this method meets the accuracy and real-time requirements for defect detection on the inner-wall outer surface of automotive ABS brake master cylinder.
Control of the robotic arm system with an SSVEP-based BCI
Authors: Fu Rongrong , Feng Xiaolei , Wang Shiwei , Shi Ye , Jia Chengcheng , Zhao Jing
Published: February 2024

Recent studies on brain–computer interfaces (BCIs) implemented in robotic systems have shown that the system’s effectiveness in assisting individuals with movement disorders to enhance their human–computer interaction skills. However, achieving precise and rapid online completion of tasks remains a challenge for manipulators with multiple degrees of freedom (DOFs). In this paper, we explore a time-sharing control strategy for studying motion control of a robotic arm based on steady-state visual evoked potentials. The signals are generated by the joint frequency-phase modulation method, analyzed with the filter-bank canonical correlation analysis algorithm, and identified to control the six-DOF robotic arm for task execution. The shared control strategy not only reduces user’s cognitive fatigue but also enhances system in practical environments. The use of high-frequency stimuli significantly improves user comfort, and hybrid coding increases the universality of the BCI system. Additionally, by setting multiple locations and actions randomly, the robotic arm can adaptively program the optimal path. The online results showed that BCI instructions of the proposed system could be accurately chosen from six options within 6.45 s. Subjects used an average of 12 commands for the robotic arm to achieve the proposed task with an average accuracy of 98.21%. These findings validate the feasibility and effectiveness of applying the system to robotic control. The control strategy proposed in this study exhibits versatility in controlling robots to perform various complex tasks across different domains.
Material decomposition with a prototype photon-counting detector CT system: expanding a stoichiometric dual-energy CT method via energy bin optimization and K-edge imaging
Authors: Richtsmeier Devon , Rodesch Pierre-Antoine , Iniewski Kris , Bazalova-Carter Magdalena
Published: February 2024

Objective. Computed tomography (CT) has advanced since its inception, with breakthroughs such as dual-energy CT (DECT), which extracts additional information by acquiring two sets of data at different energies. As high-flux photon-counting detectors (PCDs) become available, PCD-CT is also becoming a reality. PCD-CT can acquire multi-energy data sets in a single scan by spectrally binning the incident x-ray beam. With this, K-edge imaging becomes possible, allowing high atomic number (high-Z) contrast materials to be distinguished and quantified. In this study, we demonstrated that DECT methods can be converted to PCD-CT systems by extending the method of Bourque et al (2014). We optimized the energy bins of the PCD for this purpose and expanded the capabilities by employing K-edge subtraction imaging to separate a high-atomic number contrast material. Approach. The method decomposes materials into their effective atomic number (Z
eff) and electron density relative to water (ρ

e
). The model was calibrated and evaluated using tissue-equivalent materials from the RMI Gammex electron density phantom with known ρ

e
values and elemental compositions. Theoretical Z
eff values were found for the appropriate energy ranges using the elemental composition of the materials. Z
eff varied slightly with energy but was considered a systematic error. An ex vivo bovine tissue sample was decomposed to evaluate the model further and was injected with gold chloride to demonstrate the separation of a K-edge contrast agent. Main results. The mean root mean squared percent errors on the extracted Z
eff and ρ

e
for PCD-CT were 0.76% and 0.72%, respectively and 1.77% and 1.98% for DECT. The tissue types in the ex vivo bovine tissue sample were also correctly identified after decomposition. Additionally, gold chloride was separated from the ex vivo tissue sample with K-edge imaging. Significance. PCD-CT offers the ability to employ DECT material decomposition methods, along with providing additional capabilities such as K-edge imaging.
Analysis of electrode arrangements for brain stroke diagnosis via electrical impedance tomography through numerical computational models
Authors: Lee Hannah , Culpepper Jared , Porter Emily
Published: February 2024

Objective. Rapid stroke-type classification is crucial for improved prognosis. However, current methods for classification are time-consuming, require expensive equipment, and can only be used in the hospital. One method that has demonstrated promise in a rapid, low-cost, non-invasive approach to stroke diagnosis is electrical impedance tomography (EIT). While EIT for stroke diagnosis has been the topic of several studies in recent years, to date, the impact of electrode placements and arrangements has rarely been analyzed or tested and only in limited scenarios. Optimizing the location and choice of electrodes can have the potential to improve performance and reduce hardware cost and complexity and, most importantly, diagnosis time. Approach. In this study, we analyzed the impact of electrodes in realistic numerical models by (1) investigating the effect of individual electrodes on the resulting simulated EIT boundary measurements and (2) testing the performance of different electrode arrangements using a machine learning classification model. Main results. We found that, as expected, the electrodes deemed most significant in detecting stroke depend on the location of the electrode relative to the stroke lesion, as well as the role of the electrode. Despite this dependence, there are notable electrodes used in the models that are consistently considered to be the most significant across the various stroke lesion locations and various head models. Moreover, we demonstrate that a reduction in the number of electrodes used for the EIT measurements is possible, given that the electrodes are approximately evenly distributed. Significance. In this way, electrode arrangement and location are important variables to consider when improving stroke diagnosis methods using EIT.
Sampling rate requirement for accurate calculation of heart rate and its variability based on the electrocardiogram
Authors: Zhou Yuanyuan , Lindsey Bryndan , Snyder Samantha , Bell Elizabeth , Reider Lucy , Vignos Michael , Bar-Kochba Eyal , Mousavi Azin , Parreira Jesse , Hanley Casey , Shim Jae Kun , Hahn Jin-Oh
Published: February 2024

Objective. To develop analytical formulas which can serve as quantitative guidelines for the selection of the sampling rate for the electrocardiogram (ECG) required to calculate heart rate (HR) and heart rate variability (HRV) with a desired level of accuracy. Approach. We developed analytical formulas which relate the ECG sampling rate to conservative bounds on HR and HRV errors: (i) one relating HR and sampling rate to a HR error bound and (ii) the others relating sampling rate to HRV error bounds (in terms of root-mean-square of successive differences (RMSSD) and standard deviation of normal sinus beats (SDNN)). We validated the formulas using experimental data collected from 58 young healthy volunteers which encompass a wide HR and HRV ranges through strenuous exercise. Main results. The results strongly supported the validity of the analytical formulas as well as their tightness. The formulas can be used to (i) predict an upper bound of inaccuracy in HR and HRV for a given sampling rate in conjunction with HR and HRV as well as to (ii) determine a sampling rate to achieve a desired accuracy requirement at a given HR or HRV (or its range). Significance. HR and its variability (HRV) derived from the ECG have been widely utilized in a wide range of research in physiology and psychophysiology. However, there is no established guideline for the selection of the sampling rate for the ECG required to calculate HR and HRV with a desired level of accuracy. Hence, the analytical formulas may guide in selecting sampling rates for the ECG tailored to various applications of HR and HRV.
Nonlinear dynamic morphing of conical bistable dielectric elastomer actuator
Authors: Zhang Jian , Zhao Jian , Wang Xuefeng , Wang Hongyu , Liu Pengbo , Huang Yu
Published: February 2024

The bistable dielectric elastomer actuator (BDEA) possesses two stable positions which offers notable advantages of stable-state self-maintenance, fast response, and threshold snap-through characteristic in comparison with conventional dielectric elastomers. However, the strong nonlinearity induced by the coupling among materials, structure, and electrostatic fields greatly affect the dynamic response and gives rise to stability issues. Hence, a novel BDEA is proposed by introducing DEA film centrally connected with one mass block and linear spring, and the bistability can be adjusted by applying external voltage. A nonlinear dynamical model considering the electro-mechanical coupling effects is established using the Euler-Lagrange method, with which the snap-through procedure is theoretically analyzed and validated through the analytic method and finite element method. The influences of the electric actuation and structural parameters on the number of stable states and natural frequency are analyzed. Additionally, the supercritical pitchfork bifurcation and saddle-node bifurcation are investigated through dynamic analysis under forced vibration. Furthermore, the ranges of electrical actuation parameters can be determined for preventing the bifurcation phenomena under parametric excitations. Moreover, an active morphing strategy for achieving nonlinear dynamic morphing between steady states of BDEA using drive voltage is obtained, thereby enhancing the versatility of conical BDEA.
Multimode auxetic piezoelectric energy harvester for low-frequency vibration
Authors: He Longfei , Kurita Hiroki , Narita Fumio
Published: February 2024

Herein, we propose a piezoelectric energy harvester (PEH) capable of vibrating in multi-degrees-of-freedom. The resonant frequency, working bandwidth, and output power of the PEH were improved by introducing an auxetic structure (AS). The proposed PEH exhibited a symmetric serpentine structure with a doubly clamped configuration comprising several proof masses at the junctions. Finite element method (FEM) simulation was conducted to investigate the characteristics of an AS PEH and a plain-structure PEH. Prototypes of the PEHs were manufactured by three-dimensional (3D) printing technology, and their performance was evaluated through vibrational energy-harvesting experimental tests. The results showed that introducing the AS reduced the first and second resonant frequencies by 49% and 44%, respectively, considerably improved the output power in the first mode (up to 2548%) and narrowed the frequency bandgap between the first two resonance modes by 29%. The proposed multimode AS PEH can operate in a low-frequency environment of less than 20 Hz. Finally, we discussed several ways of optimizing the AS. It has been found that the PEH performance could be further improved by selecting a reasonable thickness for the AS, increasing the number of periodic unit cells, and using an AS with a variable cross-section unit cell.
The effect of multiple cooling channels on the formation of dark compact objects
Authors: Bramante Joseph , Diamond Melissa , Kim J. Leo
Published: February 2024

A dissipative dark sector can result in the formation of compact objects with masses comparable to stars and planets. In this work, we investigate the formation of such compact objects from a subdominant inelastic dark matter model, and study the resulting distributions of these objects. In particular, we consider cooling from dark Bremsstrahlung and a rapid decay process that occurs after inelastic upscattering. Inelastic transitions introduce an additional radiative processes which can impact the formation of compact objects via multiple cooling channels. We find that having multiple cooling processes changes the mass and abundance of compact objects formed, as compared to a scenario with only one cooling channel. The resulting distribution of these astrophysical compact objects and their properties can be used to further constrain and differentiate between dark sectors.
Development and implementation of an automated four-terminal-pair Josephson impedance bridge
Authors: Pimsut Yaowaret , Bauer Stephan , Kraus Marco , Behr Ralf , Kruskopf Mattias , Kieler Oliver , Palafox Luis
Published: February 2024

The four-terminal-pair impedance bridge using pulse-driven Josephson voltage standards at PTB has been fully automated. The same bridge configuration was employed to determine R:R and C:C ratios over the frequency range between 53 Hz to 50 kHz. Only minor changes are needed to cover this large frequency range: amplifiers to increase the sensitivity of the current detections for low frequencies and signal generators with higher resolution at high frequencies to reach 50 kHz. Furthermore, the bridge can be operated for quadrature R:(1/ωC) measurements. The combined standard uncertainties (k = 1) for the new bridge were evaluated for all operating frequencies. They reach 2 nF F−1 and 4 nΩ Ω−1 at 1233.15 Hz. At this frequency, the 10 nF:10 nF ratio matched the ratio of PTB’s bridge employing inductive voltage dividers within 1 nF F−1 ± 3 nF F−1 (k = 1). Over 45 days, the 10 nF:10 nF ratio deviated less than −2 nF F−1 ± 3 nF F−1 (k = 1). The 12.9 kΩ:10 kΩ ratio at 53 Hz differed −2 nΩ Ω−1 ± 5 nΩ Ω−1 (k = 1) from the DC ratio measured by the PTB’s cryogenic current comparator bridge. Using a 12.9 kΩ resistance standard and a graphene AC quantum Hall resistance, the 10 nF:10 nF ratios derived from quadrature measurements agreed with the PTB’s inductive voltage divider bridge better than 9 nF F−1 ± 13 nF F−1 (k = 1).
Finite-element modeling of neuromodulation via controlled delivery of potassium ions using conductive polymer-coated microelectrodes
Authors: Verardo Claudio , Mele Leandro Julian , Selmi Luca , Palestri Pierpaolo
Published: February 2024

Objective. The controlled delivery of potassium is an interesting neuromodulation modality, being potassium ions involved in shaping neuron excitability, synaptic transmission, network synchronization, and playing a key role in pathological conditions like epilepsy and spreading depression. Despite many successful examples of pre-clinical devices able to influence the extracellular potassium concentration, computational frameworks capturing the corresponding impact on neuronal activity are still missing. Approach. We present a finite-element model describing a PEDOT:PSS-coated microelectrode (herein, simply ionic actuator) able to release potassium and thus modulate the activity of a cortical neuron in an in-vitro-like setting. The dynamics of ions in the ionic actuator, the neural membrane, and the cellular fluids are solved self-consistently. Main results. We showcase the capability of the model to describe on a physical basis the modulation of the intrinsic excitability of the cell and of the synaptic transmission following the electro-ionic stimulation produced by the actuator. We consider three case studies for the ionic actuator with different levels of selectivity to potassium: ideal selectivity, no selectivity, and selectivity achieved by embedding ionophores in the polymer. Significance. This work is the first step toward a comprehensive computational framework aimed to investigate novel neuromodulation devices targeting specific ionic species, as well as to optimize their design and performance, in terms of the induced modulation of neural activity.
Study of cosmogenic activation above ground of Ar for DarkSide-20k
Authors: Cebrián S. ,   the DarkSide-20k collaboration
Published: February 2024

The production of long-lived radioactive isotopes due to the exposure to cosmic rays on the Earth's surface is an hazard for experiments searching for rare events like the direct detection of galactic dark matter particles. The use of large amounts of liquid argon is foreseen in different projects, like the DarkSide-20k experiment, intended to look for Weakly Interacting Massive Particles at the Laboratori Nazionali del Gran Sasso. Here, results from the study of the cosmogenic activation of argon carried out in the context of DarkSide-20k are presented. The induced activity of several isotopes, including 39Ar, and the expected counting rates in the detector have been deduced, considering exposure conditions as realistic as possible.
Model and analysis of the data readout architecture for the ITS3 ALICE Inner Tracker System
Authors: Viqueira Rodriguez M. ,   the ALICE collaboration
Published: February 2024

The ALICE collaboration is developing the Inner Tracker System 3 (ITS3), a novel detector that exploits the stitching technique to construct single-die monolithic pixel sensors of up-to 266 mm × 93 mm. ITS3 requires all hits from a particle flux of 5.75 MHz/cm2 to be transmitted on-chip to one of the sensor edges. This on-chip readout must balance the resources of power consumption, dead area, and readout performance by tuning different design parameters such as on-chip memories or on-chip links bandwidth. For doing so, a model of the ITS3 on-chip readout architecture will be presented. This model combines an accurate simulation of the particle flux fluctuations expected in ALICE with a clock-accurate digital readout simulator, combining high accuracy with fast code in terms of simulation speed.
Measurement of radon emanation and impurity adsorption from argon gas using ultralow radioactive zeolite
Authors: Ogawa Hiroshi , Iyoki Kenta , Matsukura Minoru , Wakihara Toru , Abe Ko , Miuchi Kentaro , Umehara Saori
Published: February 2024

The amount of radioactive impurities contaminated in the detector gases is required to be
kept at a very low level for rare event particle physics such as dark matter and neutrino
observation experiments. Zeolite is a well-known class of materials and is one of the possible
candidates for removing impurities from gases. At the same time, the amount of radioactive
impurities released from the adsorbent material needs to be sufficiently small. In this paper, a
development of a new ultralow radioactive zeolite as a product of the selection of ultralow
radioactive materials is reported. Results on the radon emanation and impurity adsorption from
argon gas measurements are also described.
The development of segmented electrode thin-film parallel plate avalanche counter (PPAC)
Authors: Li Zhijie , Wei Xianglun , Yang Yuansheng , He Zhoubo , He Zhixuan , Wen Xiangjie , Deng Yubin , Yang Herun , Lu Chengui , Ma Peng , He Zhiyong , Xiao Zhigang , Hu Rongjiang , Duan Limin , Qiu Tianli
Published: February 2024

In order to improve the counting rate and position
resolution of the Parallel Plate Avalanche Counter (PPAC) within the
Compact Spectrometer for Heavy Ion Experiment, a new strip
film-structured PPAC has been developed. The developped PPAC
detector consists of three layers of film electrodes. The upper and
lower layers which serve as the anodes are comprised of
self-developed strip film electrodes, oriented perpendicularly to
each other. The middle layer utilizes double-sided aluminized Mylar
film as the cathode. There is a 3 mm gap between each layer, and
the detector has an effective area of 76 mm×
76 mm. Operating in a low-pressure environment with isobutane gas
as the working medium, the performance of the PPAC has been measured
using a 5.486 MeV α radiation source. The measurement
results indicate that the overall position resolution of the PPAC
attains approximately 380 μm, and the position resolution
improves to 300 μm when using slit width correction. Finally,
the Monte Carlo simulation has been performed to simulate the
distribution of electrons generated by the detector's ionization
under the same conditions on the anode readout strip. The simulation
results closely matches the observed multiplicity of hit anode
readout strips in measurement.
Silica silanization graft-strengthening bone cement poly(methyl methacrylate): process and dynamic mechanical properties
Authors: Shi Shih-Chen , Zeng Xin-Xing
Published: February 2024

Poly(methyl methacrylate) (PMMA) has garnered widespread interest as a potential polymer-based bone cement (BC). However, many challenges in its mechanical properties, especially elongation behavior, need to be overcome. This study focused on PMMA reinforcement with SiO2 particles from two different perspectives, i.e., particle size (nano, submicro, and micro) and surface silanization of the SiO2 particles. Silanization improves the bonding between the additive and polymer matrix, which should improve the dynamic mechanical properties of the composite. The presence of silane bonding was confirmed through Fourier transform infrared spectroscopy, chemical titration, and x-ray photoelectron spectroscopy, and it was determined that 6000 μmol g−1 of silane was successfully coated onto the SiO2 particles. Reinforcement with silanized SiO2 nanoparticles increased elongation at break by 136%. The mechanism by which the size and silanization of the SiO2 additive affected elongation behavior was also discussed in detail.
Carbide precipitation during tempering of hybrid steel 60
Authors: Zheng Zhuo , Lei Min , Huang Chaowen , Wan Mingpan
Published: February 2024

The effects of carbide precipitation on mechanical performance of Hybrid Steel 60, known as a novel bearing steel, have not been investigated. In this study, the austenite transformation temperatures of Hybrid Steel 60 during heating were revealed by the thermal expansion curve. The temperature and effective activation energy of the second phase precipitation were determined by the differential scanning calorimetry (DSC) curve. Different solid solution structures after austenitization were detected using various cooling rates. The solubility temperature was determined based on hardness and residual austenite content. The carbides precipitated at the peak temperature were qualitatively identified using XRD. It was discovered that the temperature points Ac1 and Ac3 of the steel were 786 °C and 864 °C, respectively. In addition, the effect of solid solution temperature on quenching hardness is minimal, while the cooling rate has a greater impact on hardness, reaching a peak at 5 °C s−1. The primary carbide phase in Hybrid Steel 60 is the M7C3 and VC. When the temperature ranges from 500 °C to 550 °C, M23C6 begins to precipitate. As a result, after tempering at 525 °C, the hardness peak value reached 566 HV.
Growth of telecom C-band In(Ga)As quantum dots for silicon quantum photonics
Authors: Vijayan Ponraj , Joos Raphael , Werner Marco , Hirlinger-Alexander Jakob , Seibold Matthias , Vollmer Sergej , Sittig Robert , Bauer Stephanie , Braun Fiona , Portalupi Simone Luca , Jetter Michael , Michler Peter
Published: February 2024

Photonic integrated circuits (PICs) based on the silicon-on-insulator platform currently allow high-density integration of optical and electro-optical components on the same chip. This high complexity is also transferred to quantum PICs, where non-linear processes are used for the generation of quantum light on the silicon chip. However, these intrinsically probabilistic light emission processes pose challenges to the ultimately achievable scalability. Here, an interesting solution would be employing on-demand sources of quantum light based on III–V platforms, which are nonetheless very complex to grow directly on silicon. In this paper, we show the integration of InAs quantum dots (QDs) on silicon via the growth on a wafer-bonded GaAs/Si template. To ensure emission in the telecom C-band (∼1550 nm), a metamorphic buffer layer approach is utilized. We show that the deposited single QDs show similar performance to their counterparts directly grown on the well-established GaAs platform. Our results demonstrate that on-demand telecom emitters can be directly and effectively integrated on silicon, without compromises on the performances of either the platforms.
On hyperbolic dimension gap for entire functions
Authors: Mayer Volker , Urbański Mariusz
Published: February 2024

Polynomials and entire functions whose hyperbolic dimension is strictly smaller than the Hausdorff dimension of their Julia set are known to exist but in all these examples the latter dimension is maximal, i.e. equal to two. In this paper we show that there exist hyperbolic entire functions

f
f

having Hausdorff dimension of the Julia set

HD
⁡
(

J

f

)
>
2

\operatorname {HD} (\mathcal {J}_f)>2

and hyperbolic dimension

H
y
p
D
i
m

(
f
)
>

H
D

(

J

f

)

\mathrm {HypDim}(f)>\mathrm {HD}(\mathcal {J}_f)

.
Deep centroid: a general deep cascade classifier for biomedical omics data classification
Authors: Xie Kuan , Hou Yuying , Zhou Xionghui
Published: February 2024

Motivation

Classification of samples using biomedical omics data is a widely used method in biomedical research. However, these datasets often possess challenging characteristics, including high dimensionality, limited sample sizes, and inherent biases across diverse sources. These factors limit the performance of traditional machine learning models, particularly when applied to independent datasets.

Results

To address these challenges, we propose a novel classifier, Deep Centroid, which combines the stability of the nearest centroid classifier and the strong fitting ability of the deep cascade strategy. Deep Centroid is an ensemble learning method with a multi-layer cascade structure, consisting of feature scanning and cascade learning stages that can dynamically adjust the training scale. We apply Deep Centroid to three precision medicine applications—cancer early diagnosis, cancer prognosis, and drug sensitivity prediction—using cell-free DNA fragmentations, gene expression profiles, and DNA methylation data. Experimental results demonstrate that Deep Centroid outperforms six traditional machine learning models in all three applications, showcasing its potential in biological omics data classification. Furthermore, functional annotations reveal that the features scanned by the model exhibit biological significance, indicating its interpretability from a biological perspective. Our findings underscore the promising application of Deep Centroid in the classification of biomedical omics data, particularly in the field of precision medicine.

Availability and implementation

Deep Centroid is available at both github (github.com/xiexiexiekuan/DeepCentroid) and Figshare (https://figshare.com/articles/software/Deep_Centroid_A_General_Deep_Cascade_Classifier_for_Biomedical_Omics_Data_Classification/24993516).
StructuralDPPIV: a novel deep learning model based on atom structure for predicting dipeptidyl peptidase-IV inhibitory peptides
Authors: Wang Ding , Jin Junru , Li Zhongshen , Wang Yu , Fan Mushuang , Liang Sirui , Su Ran , Wei Leyi
Published: February 2024

Motivation

Diabetes is a chronic metabolic disorder that has been a major cause of blindness, kidney failure, heart attacks, stroke, and lower limb amputation across the world. To alleviate the impact of diabetes, researchers have developed the next generation of anti-diabetic drugs, known as dipeptidyl peptidase IV inhibitory peptides (DPP-IV-IPs). However, the discovery of these promising drugs has been restricted due to the lack of effective peptide-mining tools.

Results

Here, we presented StructuralDPPIV, a deep learning model designed for DPP-IV-IP identification, which takes advantage of both molecular graph features in amino acid and sequence information. Experimental results on the independent test dataset and two wet experiment datasets show that our model outperforms the other state-of-art methods. Moreover, to better study what StructuralDPPIV learns, we used CAM technology and perturbation experiment to analyze our model, which yielded interpretable insights into the reasoning behind prediction results.

Availability and implementation

The project code is available at https://github.com/WeiLab-BioChem/Structural-DPP-IV.
Prognostic nomogram model for selecting between transarterial chemoembolization plus lenvatinib, with and without PD-1 inhibitor in unresectable hepatocellular carcinoma
Authors: Sheng Ye , Wang Qing , Liu HaiFeng , Wang Qi , Chen WenHua , Xing Wei
Published: February 2024

Objectives

To establish and verify a prognostic nomogram model for selecting in unresectable hepatocellular carcinoma (uHCC) treated by transarterial chemoembolization plus lenvatinib (TACE-L) with or without PD-1 inhibitor.

Methods

Data of 241 uHCC patients who underwent TACE-L (n = 128) and TACE-L plus PD-1 inhibitor (TACE-L-P, n = 113) were retrospectively reviewed. The differences in tumour responses, progression-free survival (PFS), overall survival (OS), and adverse events (AEs) between two groups were compared, and a prognostic nomogram model was established based on independent clinical-radiologic factors and confirmed by Cox regression analysis for predicting PFS and OS. The treatment selection for uHCC patients was stratified by the nomogram score.

Results

Compared to TACE-L, TACE-L-P presented prolonged PFS (14.0 vs. 9.0 months, P < .001), longer OS (24.0 vs. 15.0 months, P < .001), and a better overall objective response rate (54.0% vs. 32.8%, P = .001). There was no significant difference between the rate of AEs in the TACE-L-P and the TACE-L (56.64% vs. 46.09%, P = .102) and the rate of grade ≥ 3 AEs (11.50% vs. 9.38%, P = .588), respectively. The nomogram model presented good discrimination, with a C-index of 0.790 for predicting PFS and 0.749 for predicting OS. Patients who underwent TACE-L and obtained a nomogram score >9 demonstrated improved 2-year PFS when transferred to TACE-L-P, and those with a nomogram ≤25 had better 2-year OS when transferred to TACE-L-P.

Conclusions

TACE-L-P showed significant improvements in efficiency and safety for uHCC patients compared with TACE-L. The nomogram was useful for stratifying treatment decisions and selecting a suitable population for uHCC patients.

Advances in knowledge

Prognostic nomogram model is of great value in predicting individualized survival benefits for uHCC patients after TACE-L or/and TACE-L-P. And the nomogram was helpful for selection between TACE-L-P and TACE-L among uHCC patients.
Impaired value-based decision-making in Parkinson’s disease apathy
Authors: Gilmour William , Mackenzie Graeme , Feile Mathias , Tayler-Grint Louise , Suveges Szabolcs , Macfarlane Jennifer A , Macleod Angus D , Marshall Vicky , Grunwald Iris Q , Steele J Douglas , Gilbertson Tom
Published: February 2024

Apathy is a common and disabling complication of Parkinson’s disease characterized by reduced goal-directed behaviour. Several studies have reported dysfunction within prefrontal cortical regions and projections from brainstem nuclei whose neuromodulators include dopamine, serotonin and noradrenaline. Work in animal and human neuroscience have confirmed contributions of these neuromodulators on aspects of motivated decision-making. Specifically, these neuromodulators have overlapping contributions to encoding the value of decisions, and influence whether to explore alternative courses of action or persist in an existing strategy to achieve a rewarding goal.

Building upon this work, we hypothesized that apathy in Parkinson’s disease should be associated with an impairment in value-based learning. Using a four-armed restless bandit reinforcement learning task, we studied decision-making in 75 volunteers; 53 patients with Parkinson’s disease, with and without clinical apathy, and 22 age-matched healthy control subjects. Patients with apathy exhibited impaired ability to choose the highest value bandit. Task performance predicted an individual patient’s apathy severity measured using the Lille Apathy Rating Scale (R = −0.46, P < 0.001). Computational modelling of the patient’s choices confirmed the apathy group made decisions that were indifferent to the learnt value of the options, consistent with previous reports of reward insensitivity. Further analysis demonstrated a shift away from exploiting the highest value option and a reduction in perseveration, which also correlated with apathy scores (R = −0.5, P < 0.001).

We went on to acquire functional MRI in 59 volunteers; a group of 19 patients with and 20 without apathy and 20 age-matched controls performing the Restless Bandit Task. Analysis of the functional MRI signal at the point of reward feedback confirmed diminished signal within ventromedial prefrontal cortex in Parkinson’s disease, which was more marked in apathy, but not predictive of their individual apathy severity. Using a model-based categorization of choice type, decisions to explore lower value bandits in the apathy group activated prefrontal cortex to a similar degree to the age-matched controls. In contrast, Parkinson’s patients without apathy demonstrated significantly increased activation across a distributed thalamo-cortical network. Enhanced activity in the thalamus predicted individual apathy severity across both patient groups and exhibited functional connectivity with dorsal anterior cingulate cortex and anterior insula.

Given that task performance in patients without apathy was no different to the age-matched control subjects, we interpret the recruitment of this network as a possible compensatory mechanism, which compensates against symptomatic manifestation of apathy in Parkinson’s disease.