bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the role of interaction in older-adult service innovation: insights from the testing stage
Authors: Chin Ya-Lan , Wu Feng-Shang , Liu Jian-Bing , Li Yan , Wang Jin 
Published: July 2024

AbstractIn the context of global aging trends, service innovation targeting older adults is becoming increasingly crucial. Because the traditional focus areas of service innovation have predominantly been design and implementation, a significant gap in the existing literature overlooks the criticality of the testing phase. This oversight is particularly notable in relation to the unique attributes of the older adult population and their interaction dynamics with technology teams in service innovation. To bridge this lacuna, this study introduces a comprehensive framework, meticulously crafted for the testing stage of service innovation tailored to older adults. To validate this framework, a rigorous, four-year empirical research project was undertaken with one of the foremost service providers for older adults in Beijing. The findings robustly support the efficacy of the proposed framework, revealing the indispensable role of the testing phase in ensuring service innovations are aptly aligned with the needs and preferences of the aging demographic. This research enriches the discourse in service innovation, thus underscoring the imperative to integrate the testing phase as a fundamental component in the holistic approach aimed at catering effectively to an aging population.
Analytic solutions for drag and Magnus forces
Authors: Kajiyama Yuji 
Published: July 2024

Abstract
When a spinning object moves in air, it is affected by three forces: the gravitational force, the drag force, and the Magnus force. The equations of motion for such an object are nonlinear, making it difficult to find analytic solutions. Hence, numerical solutions using computers are often preferred. This paper provides two examples of analytic solutions of the equations of motion with the drag and Magnus forces: nearly vertical motion and motion of a light object. In these two cases, we find analytic solutions for the velocity and the position of the object, avoiding mathematical difficulties. It is suitable for university students studying physics.
2D-Bio-FETs for sensitive detection of cardiovascular diseases
Authors: Choudhary Piyush , Singh Vijay K , Dixit Ambesh 
Published: July 2024

Abstract
The biosensing industry has seen exponential growth in the past decade. Impact of biosensors in the current scenario cannot be overlooked. Cardiovascular diseases (CvDs) have been recognized as one of the major causes for millions of deaths globally. This mortality can be minimized by early and accurate detection/diagnosis of CvDs with the help of biosensing devices. This also presents a global market opportunity for the development of biosensors for CvDs. A vast variety of biosensing methods and devices have been developed for this problem. Most of commercially available platforms for CvD detection rely on optical (fluorometric and colorimetric analysis) techniques using serum biomarkers since optical testing is the gold standard in medical diagnosis. Field effect transistors-based biosensors, termed as Bio-FETs, are the upcoming devices for blood or serum analyte detection due to excellent sensitivity, low operational voltage, handheld device structure and simple chip-based operation. Further, the discovery of two dimensional (2D) materials and their integration with conventional FETs has improved the overvoltage problem, sensitivity and strict operating conditions as compared to conventional FETs. Graphene-FETs based biosensing devices have been proven as promising candidates due to their attractive properties. Despite the severe threat of CvDs which has further increased in post-covid era, the Bio-FET sensor studies in literature are still rare. In this review, we aim to provide a comprehensive view of all the multidisciplinary concepts related to 2D-BioFETs for CvDs. A critical review of the different platforms has been covered with detailed discussions of related studies to provide a clear concept and present status of 2D-BioFETs based CvD biosensors.
AFM interlaboratory comparison for nanodimensional metrology on silicon nanowires
Authors: Ribotta Luigi , Delvallée Alexandra , Cara Eleonora , Bellotti Roberto , Giura Andrea , Carlo Ivan De , Fretto Matteo , Knulst Walter , Koops Richard , Torre Bruno , Saghi Zineb , Boarino Luca 
Published: July 2024

Abstract
Silicon nanowires (NWs) with a cylindrical form are fabricated by means of nanosphere lithography and metal-assisted chemical etching to obtain high aspect ratio nanostructures (diameter of about 100 nm and length of more than 15 µm) on an approximately 1 cm2 area. The nanodimensional characterization of individual NWs is performed by using several techniques, because dimensions at the nanoscale strictly relate to functional performance. In this study, we report the results of an interlaboratory comparison between measurements from a metrological atomic force microscope (AFM) and research AFMs located in different national metrology institutes (NMIs) across Europe and in a university. The purpose of this study is to characterize two measurands: (i) sidewall roughness (

R
a

,

R
q

,

R
z

,

R

sk

,

R

ku

parameters) extracted from the top profile measured along the nanowire length, and (ii) diameter of the nanowires measured as top-height. To this goal, the nanowires are spread horizontally on a silicon substrate, which has several areas labelled with a pattern of crosses and letters facilitating the measurement of the same NW, in order to study the reproducibility due to different instruments. Measurements show a good agreement between the different NMIs, with a combined standard uncertainty of top-height diameter less than 3%, and with a combined standard uncertainty of roughness parameters well within 5% for

R
a

and

R
q

values.
Lightweight bearing fault diagnosis method based on cross-scale learning transformer under imbalanced data*
Authors: Zhao Huimin , Li Peixi , Guo Aibin , Deng Wu 
Published: July 2024

Abstract
Due to the limited amount of failure data in rolling bearing faults, traditional fault diagnosis models encounter challenges such as low diagnostic accuracy and efficiency when dealing with imbalanced data. Additionally, many fault diagnosis models are overly complex and demand high computational resources. To address these issues, a lightweight bearing fault diagnosis method based on cross-scale learnable transformer (CSLT) is proposed for imbalanced data. For difficult-to-classify samples, a learnable generalized focal loss function is defined. The learnable parameters are employed to increase its flexibility, it better addresses the issue of bearing fault diagnosis under imbalanced data conditions. Then, a multi-head broadcasted self-attention mechanism is designed by capturing critical local features of the signal through one-dimensional convolution operations, which not only improves feature extraction capability but also reduces computational complexity. Finally, a dynamic label prediction pruning module is developed to trim redundant labels, which helps in lightening the model and enhancing both feature extraction and diagnostic efficiency. The experimental results demonstrate that the proposed diagnosis method exhibits superior diagnostic precision and efficiency by comparing with other methods.
Two-stage re-parameterization and sample disentanglement network for surveillance vehicle detection
Authors: Xie Wei , Liu Weiming , Dai Yuan 
Published: July 2024

Abstract
Detecting vehicles from a surveillance viewpoint is essential, as it has wide applications in community security and traffic control. However, existing methods completely overlook the high memory access costs (MAC) and low degree of parallelism inherent in multi-branch topologies, resulting in significant latency during inference. Additionally, existing methods share the same positive/negative sample set between the classification and localization branches, leading to sample misalignment, and rely solely on intersection-over-union for sample assignment, thereby causing a decrease in detection performance. To tackle these issues, this paper introduces a two-stage re-parameterization and sample disentanglement network (TRSD-Net). It is based on two-stage depthwise to pointwise re-parameterization (RepTDP) and task-aligned sample disentanglement (TSD). RepTDP employs structural re-parameterization to decouple the multi-branch topology during training and the plain architecture during inference, thus achieving low latency. By employing different sample assignment strategies, TSD can adaptively select the most suitable positive/negative sample sets for classification and localization tasks, thereby enhancing detection performance. Additionally, TSD considers three important factors influencing sample assignment. TRSD-Net is evaluated on both the UA-DETRAC and COCO datasets. On the UA-DETRAC dataset, compared to state-of-the-art methods, TRSD-Net improves the detection accuracy from 58.8% to 59.7%. Additionally, it reduces the parameter count by 87%, the computational complexity by 85%, and the latency by 39%, while increasing the detection speed by 65%. Similar performance improvement trends are observed on the COCO dataset.
Valence-state mixing and reduced magnetic moment in

Fe

3
−
δ

GeTe
2

single crystals with varying Fe content probed by x-ray spectroscopy
Authors: Backes D , Fujita R , Veiga L S I , Mayoh D A , Wood G D A , Dhesi S S , Balakrishnan G , van der Laan G , Hesjedal T 
Published: July 2024

Abstract
We present a spectroscopic study of the magnetic properties of

Fe

3
−
δ

GeTe
2

single crystals with varying Fe content, achieved by tuning the stoichiometry of the crystals. We carried out x-ray absorption spectroscopy and analyzed the x-ray circular magnetic dichroism spectra using the sum rules, to determine the orbital and spin magnetic moments of the materials. We find a clear reduction of the spin and orbital magnetic moment with increasing Fe deficiency. Magnetic susceptibility measurements show that the reduction in magnetization is accompanied by a reduced Curie temperature. Multiplet calculations reveal that the Fe2+ state increasingly mixes with a higher valence state when the Fe deficiency is increased. This effect is correlated with the weakening of the magnetic moment. As single crystals are the base material for exfoliation processes, our results are relevant for the assembly of 2D magnetic heterostructures.
Magnetic properties of ferromagnetic nanoparticles of Fe
x
GeTe2 (x = 3, 5) directly exfoliated and dispersed in pure water
Authors: Lim Hyunjong , Ahn Hyo-Bin , Lee Changgu 
Published: July 2024

Abstract
Fe
x
GeTe2 (x = 3, 5) are two-dimensional ferromagnetic (FM) materials that have gained significant attention from researchers due to their relatively high Curie temperature and tunability. However, the methods for preparing FM nanoparticles (FNPs) and large-area Fe
x
GeTe2 films are still in the early stages. Here, we studied the magnetic properties of Fe
x
GeTe2 FNPs exfoliated via wet exfoliation in pure water. The coercive field of Fe3GeTe2 FNPs increases significantly, up to 60 times, while that of Fe5GeTe2 only slightly increases from that of bulk crystals. Further investigation related to the dimension of nanoparticles and the Henkel plot analysis reveals that the variation in their coercive field stems from the material’s thickness-dependent coercive field and the type of term that governs the interaction between single-domain nanoparticles. Our work demonstrates a facile method for preparing FNPs using van der Waals FM materials and tuning their magnetic properties.
Customizing pyridinic nitrogen coordination in Ni–N–C for electrocatalytic CO2 reduction towards CO
Authors: Ai Ying , Zhang Kai , Li Jingde , Du Xiaohang , Wang Yanji , Wu Lanlan , Zhang Zisheng 
Published: July 2024

Abstract
Nickel anchored N-doped carbon electrocatalysts (Ni–N–C) are rapidly developed for the electrochemical reduction reaction of carbon dioxide (CO2RR). However, the high-performanced Ni–N–C analogues design for CO2RR remains bewilderment, for the reason lacking of definite guidance for its structure-activity relationship. Herein, the correlation between the proportion of nitrogen species derived from various nitrogen sources and the CO2RR activity of Ni–N–C is investigated. The x-ray photoelectron spectroscopy (XPS) spectrum combined with the CO2RR performance results show that pyridinic-N content has a positive correlation with CO2RR activity. Moreover, density functional theory (DFT) demonstrates that pyridinic-N coordinated Ni–N4 sites offers optimized free energy and favorable selectivity towards CO2RR compared with pyrrolic-N. Accordingly, Ni–Na–C with highest pyridinic-N content (ammonia as nitrogen source) performs superior CO2RR activity, with the maximum carbon monoxide faradaic efficiency (FECO) of 99.8% at −0.88 V vs. RHE and the FECO surpassing 95% within potential ranging of −0.88 to −1.38 V vs. RHE. The building of this parameter for CO2RR activity of Ni–N–C give instructive forecast for low-cost and highly active CO2RR electrocatalysts.
FreqSNet: a multiaxial integration of frequency and spatial domains for medical image segmentation
Authors: Liu Shangwang , Lin Yinghai , Liu Danyang 
Published: July 2024

Abstract

Objective. In recent years, convolutional neural networks, which typically focus on extracting spatial domain features, have shown limitations in learning global contextual information. However, frequency domain can offer a global perspective that spatial domain methods often struggle to capture. To address this limitation, we propose FreqSNet, which leverages both frequency and spatial features for medical image segmentation. Approach. To begin, we propose a frequency-space representation aggregation block (FSRAB) to replace conventional convolutions. FSRAB contains three frequency domain branches to capture global frequency information along different axial combinations, while a convolutional branch is designed to interact information across channels in local spatial features. Secondly, the multiplex expansion attention block extracts long-range dependency information using dilated convolutional blocks, while suppressing irrelevant information via attention mechanisms. Finally, the introduced Feature Integration Block enhances feature representation by integrating semantic features that fuse spatial and channel positional information. Main results. We validated our method on 5 public datasets, including BUSI, CVC-ClinicDB, CVC-ColonDB, ISIC-2018, and Luna16. On these datasets, our method achieved Intersection over Union (IoU) scores of 75.46%, 87.81%, 79.08%, 84.04%, and 96.99%, and Hausdorff distance values of 22.22 mm, 13.20 mm, 13.08 mm, 13.51 mm, and 5.22 mm, respectively. Compared to other state-of-the-art methods, our FreqSNet achieves better segmentation results. Significance. Our method can effectively combine frequency domain information with spatial domain features, enhancing the segmentation performance and generalization capability in medical image segmentation tasks.
Sex differences in chest electrical impedance tomography findings
Authors: Frerichs I , Händel C , Becher T , Schädler D 
Published: July 2024

Abstract

Objective. Electrical impedance tomography (EIT) has been used to determine regional lung ventilation distribution in humans for decades, however, the effect of biological sex on the findings has hardly ever been examined. The aim of our study was to determine if the spatial distribution of ventilation assessed by EIT during quiet breathing was influenced by biological sex. Approach. 219 adults with no known acute or chronic lung disease were examined in sitting position with the EIT electrodes placed around the lower chest (6th intercostal space). EIT data were recorded at 33 images/s during quiet breathing for 60 s. Regional tidal impedance variation was calculated in all EIT image pixels and the spatial distribution of the values was determined using the established EIT measures of centre of ventilation in ventrodorsal (CoVvd) and right-to-left direction (CoVrl), the dorsal and right fraction of ventilation, and ventilation defect score. Main results. After exclusion of one subject due to insufficient electrode contact, 218 data sets were analysed (120 men, 98 women) (age: 53 ± 18 vs 50 ± 16 yr (p = 0.2607), body mass index: 26.4 ± 4.0 vs 26.4 ± 6.6 kg m−2 (p = 0.9158), mean ± SD). Highly significant differences in ventilation distribution were identified between men and women between the right and left chest sides (CoVrl: 47.0 ± 2.9 vs 48.8 ± 3.3% of chest diameter (p < 0.0001), right fraction of ventilation: 0.573 ± 0.067 vs 0.539 ± 0.071 (p = 0.0004)) and less significant in the ventrodorsal direction (CoVvd: 55.6 ± 4.2 vs 54.5 ± 3.6% of chest diameter (p = 0.0364), dorsal fraction of ventilation: 0.650 ± 0.121 vs 0.625 ± 0.104 (p = 0.1155)). Ventilation defect score higher than one was found in 42.5% of men but only in 16.6% of women. Significance. Biological sex needs to be considered when EIT findings acquired in upright subjects in a rather caudal examination plane are interpreted. Sex differences in chest anatomy and thoracoabdominal mechanics may explain the results.
Studying species distribution in laser-induced plasma by molecular and atomic fluorescence
Authors: Beglaryan Babken G , Zakuskin Aleksandr S , Zaytsev Sergey M , Labutin Timur A 
Published: July 2024

Abstract
The spatial distribution profiles of particles in plasma sources push forward our understanding of plasma evolution and physicochemical processes occuring inside. Optical probe methods, such as laser-induced fluorescence, are advanced tools for spatially resolved plasma studies. In our work, we focused on investigation of distribution of neutral Ca and Fe atoms and CaO and FeO molecules in laser-induced plasma by means of laser-induced fluorescence. The development of excitation-emission schemes for Fe and FeO and the practical implementation of schemes for Ca and CaO allowed us to construct distribution maps of these species in laser plasma at 10 and 100 Torr pressures. Both atomic and molecular fluorescence were observed much further from the plasma formation point than the region of bright spontaneous atomic emission. Additionally, by comparing fluorescence intensity distributions with plasma imaging data, we explain the origin of some pecularities in observable plasma inhomogeneity. Distributions of Ca and CaO fluorescence intensity, as well the distribution of CaO/Ca intensity ratio, demostrate that the monoxide is distributed within the plume by the shock wave, but its concentration in the outer layers of plasma is influenced by recombination with atmospheric oxygen.
Individual quantification of ozone and reactive nitrogen species in mixtures by broadband UV–visible absorption spectra deconvolution
Authors: Huh Seong-Cheol , Bae Jin Hee , Lee Hyungyu , Kim Jinwoo , Choe Wonho , Park Sanghoo 
Published: July 2024

Abstract
Ozone (O3), nitrogen oxides (NO
x
), and reactive nitrogen species (RNS) play critical roles in atmospheric-pressure plasma applications. Although it is crucial to individually quantify these species to understand atmospheric-pressure plasmas and increase their effectiveness, the lack of reliable and cost-effective diagnostics makes this difficult for many researchers. To address this problem, we introduce a new deconvolution method of broadband ultraviolet–visible absorption spectra for the simultaneous measurement of eight species—O3, NO, NO2, NO3, N2O4, N2O5, HONO, and HNO3. Processing of broadband spectra enables deconvolution of similar cross-section profiles and measurement of high densities exceeding the instrumental limit. Novel correction processes enable accurate analysis despite incomplete cross-section data and utilize a priori chemical knowledge to ensure theoretically reasonable results. Two case studies test the efficacy of the method: NO2 and N2O4 equilibria, and reactive species produced by a surface dielectric barrier discharge. With an analysis time of 15–20 ms per spectrum, the measured densities agree well with other theoretical and experimental results, and detection limits on the order of ppmv were achieved with a short path length of 15 cm. This spectral analysis method will facilitate the real-time monitoring of O3, NO
x
, and RNS in many scientific research and industrial applications of atmospheric pressure plasmas.
Quantitative regulation of electron–phonon coupling
Authors: Pei Shenghai , Zhang Zejuan , Jiao Chenyin , Wang Zhenyu , Lv Jian , Zhang Yujun , Huang Mingyuan , Wang Yanchao , Wang Zenghui , Xia Juan 
Published: July 2024

Abstract
Electron–phonon (e–p) coupling plays a crucial role in various physical phenomena, and regulation of e–p coupling is vital for the exploration and design of high-performance materials. However, the current research on this topic lacks accurate quantification, hindering further understanding of the underlying physical processes and its applications. In this work, we demonstrate quantitative regulation of e–p coupling, by pressure engineering and in-situ spectroscopy. We successfully observe both a distinct vibrational mode and a strong Stokes shift in layered CrBr3, which are clear signatures of e–p coupling. This allows us to achieve precise quantification of the Huang–Rhys factor S at the actual sample temperature, thus accurately determining the e–p coupling strength. We further reveal that pressure efficiently regulates the e–p coupling in CrBr3, evidenced by a remarkable 40% increase in S value. Our results offer an approach for quantifying and modulating e–p coupling, which can be leveraged for exploring and designing functional materials with targeted e–p coupling strengths.
Efficient entanglement enhancement of partially entangled pairs
Authors: Harraz Sajede , Cong Shuang 
Published: July 2024

Abstract
We present a comprehensive approach to transform a partially entangled pure state into a maximally entangled state, utilizing only local operations and a single copy of the entangled state. Our approach eliminates the need for multiple copies of entangled states, bilateral operations, and the time-consuming partial-collapse weak measurements. Integrating ancilla qubits, rotation gates, and CNOT gates, we simplify the process of enhancing entanglement, achieving significant efficiency using only a single partially entangled state. Assuming perfect local operations, we showcase the efficacy of our method through both mathematical analysis and the practical implementation of the corresponding circuit in Qiskit. Furthermore, we explore the impact of imperfect local operations, specifically focusing on the CNOT gate and measurement, for a comprehensive analysis. Additionally, we address the case of unknown parameters in the partially entangled pure state and introduce a robust method to effectively handle this uncertainty, ensuring reliable entanglement fidelity optimization in practical situations. We extend our investigation to the application of our method to mixed initial entangled states. Our results demonstrate the reliability of our method in increasing entanglement even in the presence of phase damping and amplitude damping. Additionally, we illustrate its effectiveness in transforming specific mixed initial states in the presence of depolarization into states with enhanced entanglement.