bluuebunny/crossref_metadata_2025_split huggingface dataset:
Face-centered cubic carbon as a fourth basic carbon allotrope with properties of intrinsic semiconductors and ultra-wide bandgap
Authors: Konyashin Igor , Muydinov Ruslan , Cammarata Antonio , Bondarev Andrey , Rusu Marin , Koliogiorgos Athanasios , Polcar Tomáš , Twitchen Daniel , Colard Pierre-Olivier , Szyszka Bernd , Palmer Nicola 
Published: July 2024

AbstractCarbon is considered to exist in three basic forms: diamond, graphite/graphene/fullerenes, and carbyne, which differ in a type of atomic orbitals hybridization. Since several decades the existence of the fourth basic carbon allotropic form with the face-centered cubic (fcc) crystal lattice has been a matter of discussion despite clear evidence for its laboratory synthesis and presence in nature. Here, we obtain this carbon allotrope in form of epitaxial films on diamond in a quantity sufficient to perform their comprehensive studies. The carbon material has an fcc crystal structure, shows a negative electron affinity, and is characterized by a peculiar hybridization of the valence atomic orbitals. Its bandgap (~6 eV) is typical for insulators, whereas the noticeable electrical conductivity (~0.1 S m−1) increases with temperature, which is typical for semiconductors. Ab initio calculations explain this apparent contradiction by noncovalent sharing p-electrons present in the uncommon valence band structure comprising an intraband gap. This carbon allotrope can create a new pathway to ‘carbon electronics’ as the first intrinsic semiconductor with an ultra-wide bandgap.
High-dimensional mapping of human CEACAM1 expression on immune cells and association with melanoma drug resistance
Authors: Huang Yu-Hwa , Yoon Charles H. , Gandhi Amit , Hanley Thomas , Castrillon Carlos , Kondo Yasuyuki , Lin Xi , Kim Walter , Yang Chao , Driouchi Amine , Carroll Michael , Gray-Owen Scott D. , Wesemann Duane R. , Drake Charles G. , Bertagnolli Monica M. , Beauchemin Nicole , Blumberg Richard S. 
Published: July 2024

Abstract
Background
Human carcinoembryonic antigen cell adhesion molecule 1 (CEACAM1) is an inhibitory cell surface protein that functions through homophilic and heterophilic ligand binding. Its expression on immune cells in human tumors is poorly understood.

Methods
An antibody that distinguishes human CEACAM1 from other highly related CEACAM family members was labeled with 159Tb and inserted into a panel of antibodies that included specificity for programmed cell death protein 1 (PD1) and PD-L1, which are targets of immunotherapy, to gain a data-driven immune cell atlas using cytometry by time-of-flight (CyTOF). A detailed inventory of CEACAM1, PD1, and PD-L1 expression on immune cells in metastatic lesions to lymph node or soft tissues and peripheral blood samples from patients with treatment-naive and -resistant melanoma as well as peripheral blood samples from healthy controls was performed.

Results
CEACAM1 is absent or at low levels on healthy circulating immune cells but is increased on immune cells in peripheral blood and tumors of melanoma patients. The majority of circulating PD1-positive NK cells, innate T cells, B cells, monocytic cells, dendritic cells, and CD4+ T cells in the peripheral circulation of treatment-resistant disease co-express CEACAM1 and are demonstrable as discrete populations. CEACAM1 is present on distinct types of cells that are unique to the tumor microenvironment and exhibit expression levels that are highest in treatment resistance; this includes tumor-infiltrating CD8+ T cells.

Conclusions
To the best of our knowledge, this work represents the first comprehensive atlas of CEACAM1 expression on immune cells in a human tumor and reveals an important correlation with treatment-resistant disease. These studies suggest that agents targeting CEACAM1 may represent appropriate partners for PD1-related pathway therapies.
Analysis of anthropometric outcomes in Indian children during the COVID-19 pandemic using National Family Health Survey data
Authors: Summan Amit , Nandi Arindam , Laxminarayan Ramanan 
Published: July 2024

Abstract
Background
Disruptions in food, health, and economic systems during the COVID-19 pandemic may have adversely affected child health. There is currently limited research on the potential effects of the COVID-19 pandemic on stunting, wasting, and underweight status of young children.

Methods
We examine the short-term associations between the pandemic and anthropometric outcomes of under-5 children (n = 232,920) in India, using data from the National Family Health Survey (2019–2021). Children surveyed after March 2020 are considered as the post-COVID group, while those surveyed earlier are considered as pre-COVID. Potential biases arising from differences in socioeconomic characteristics of the two groups are mitigated using propensity score matching methods.

Results
Post-COVID children surveyed in 2020 and 2021 have 1.2% higher underweight rates, 1.2% lower wasting rates, 0.1 lower height-for-age z-scores (HAZ), and 0.04 lower weight-for-height z-scores as compared with matched pre-COVID children. Post-COVID children surveyed in 2020 have 1.6%, 4.6%, and 2.4% higher stunting, underweight, and wasting rates, respectively, and 0.07 lower HAZ, as compared with matched pre-COVID children. Reductions in nutritional status are largest among children from households in the poorest wealth quintiles.

Conclusions
These findings indicate a trend towards a recovery in child anthropometric outcomes in 2021 after the initial post-pandemic reductions. The resilience of health and food systems to shocks such as COVID-19 should be strengthened while immediate investments are required to decrease child malnutrition and improve broader child health outcomes.
Kinematics of Hitting in Youth Baseball: Implications for Skill
Development
Authors: Bordelon Nicole , Fava Anthony , Friesen Kenzie B. , Crotin Ryan L , Oliver Gretchen D 
Published: July 2024

AbstractThis study compared lower extremity, trunk, and upper extremity kinematics
between tee and front toss hitting in youth baseball athletes. Twenty youth
baseball athletes (14.3±2.9 yrs) performed three maximal effort swings off front
toss and tee. Kinematic data were collected during the preparatory and
acceleration phases. Lower extremity, trunk, and upper extremity kinematics were
compared between tee and front toss hitting using 1-dimensional statistical
parametric mapping (SPM). There was a significant difference in trunk kinematics
between tee and front toss during the preparatory phase (p=.001); the trunk
rotated more toward the back side when hitting off a tee compared to front toss
(p<0.001). There was also a significant difference in trunk kinematics
between tee and front toss for 67% of the acceleration phase; the trunk rotated
more towards the back side from 0 to 67% when hitting off the tee (p<0.001).
Significant differences were found in trunk kinematics between tee and front
toss hitting in youth baseball players, where the trunk is less rotated toward
the pitcher in the tee than in the front toss. Coaches utilize various training
modalities to enhance hitting performance; however, differences in trunk
kinematics should be considered between modalities when developing fundamental
hitting techiques in youth baseball athletes.
Particle and light motion in Lyra–Schwarzschild spacetime
Authors: Cuzinatto R R , de Morais E M , Pimentel B M 
Published: July 2024

Abstract
In this paper we recall the static and spherically symmetric solution derived within LyST gravity. LyST stands for ‘Lyra Scalar-Tensor’ and is a scalar-tensor proposal for the gravitational interaction modifying general relativity by adopting Lyra manifold as the spacetime substrate. Lyra manifold is characterized both by the metric tensor

g

μ
ν

(
x
)

and the scale

ϕ

(
x
)

; the latter being an integral part of the definition of reference frame. In a previous work, we have launched the formal geometrical basis of LyST, we have proposed an associated action integral for the gravitational interaction, we have derived the field equations generalizing Einstein field equation, and we have solved these equation to obtain the generalized version of Schwarzschild line element in Lyra manifold. This lead us to Lyra–Schwarzschild spacetime, which is further explored in the present paper. Herein, the trajectories of test particles is thoroughly studied. This is done for both massive particles and massless particles. The geodesic equations are built and solved. The effective potential associated to the motion of these particles around the source is determined and characterized. The possible trajectories include gravitational capture, scattering, bounded orbits, stable and unstable circular orbits, near-horizon motion. The innermost circular orbit allowed for massive particles is determined and compared to the one predicted by GR. The last photon orbit is also calculated for Lyra–Schwarzschild metric. The equation for the periastron shift in the context of Lyra–Schwarzschild solution is constructed; its application to observational data could be useful to constrain the parameters typical of LyST, telling it apart from GR.
Manipulating chiral Majorana mode with additional potential in superconductor-Chern insulator heterostructures
Authors: Lao Junming , Zhou Tao 
Published: July 2024

Abstract
We employed the self-consistent Bogoliubov–de Gennes equations to explore the states of chiral Majorana mode in quantum anomalous Hall insulators in proximity to a superconductor, leading to the development of an extensive topological phase diagram. Our investigation focused on how an additional potential affects the separation of chiral Majorana modes across different phase conditions. We substantiated our findings by examining the zero-energy Local Density of States spectrum and the probability distribution of the chiral Majorana modes. We established the universality of chiral Majorana mode separation by applying an additional potential. This finding serves as a vital resource for future endeavors aimed at controlling and detecting these particles, thereby contributing to the advancement of quantum computing and condensed matter physics.
Accuracy analysis of UAV aerial photogrammetry based on RTK mode, flight altitude, and number of GCPs
Authors: Tan Chenyan , Chen Zijun , Chen Zijun , Liao Ailin , Zeng Xintian , Cao Jinchao 
Published: July 2024

Abstract
The optimization of an unmanned aerial vehicle (UAV) aerial photogrammetry scheme is crucial for achieving higher precision mapping results. Three representative factors, namely the real-time kinematic (RTK) mode, flight altitude, and the number of ground control points (GCPs) were selected to analyze their impact on UAV aerial photogrammetry accuracy. Four flight altitude tests were conducted separately in two RTK modes, and five GCP layout schemes were designed. Based on this, the root mean square error (RMSE) values of 40 aerial photogrammetric results were analyzed. The results showed a significant correlation between flight altitude and resolution of the UAV aerial photogrammetric results. Further, conversion formulas between actual image resolution and flight altitude for different GCP values were also derived in RTK and non-RTK modes. In the case of precise positioning, the horizontal and vertical accuracy of the aerial photogrammetric image decreased with increasing flight altitude. Under the same flight altitude, the addition or no addition of GCPs, including changes in GCP numbers, had no significant effect on improving the accuracy of aerial photogrammetry in RTK mode. However, in non-RTK mode, the number of GCPs significantly affected accuracy. The horizontal and vertical RMSE values decreased rapidly with the increase in GCP numbers and then stabilized. However, regardless of whether RTK was activated, an excessive number of GCPs was not conducive to improving the accuracy of aerial photogrammetric results. The mapping accuracy of UAVs in RTK mode without GCPs was equivalent to that in non-RTK mode with GCPs. Therefore, when using RTK-UAVs, deploying GCPs is unnecessary under suitable circumstances. Finally, practical suggestions for optimizing the UAV aerial photogrammetry scheme are provided as a reference for related applications.
Multi-lane vehicle load measurement using bending and shear strains
Authors: Zhang Qingqing , Gong Lingling , Tian Kang , Jian Zhenao 
Published: July 2024

Abstract
Many load identification methods have been proposed, but most are affected by the basic axle parameters and lateral distribution of vehicles. To effectively measure traffic flow with lateral distribution information, this article presents an innovative method that employs a strain decoupling model (SDM) and a vehicle information identification model (VIDM) to measure multi-lane vehicle load depending on the bending strain and shear strain from long-gauge fiber Bragg grating sensors. The SDM decouples the measured coupling strain into the strain for a single lane load, thereby simplifying the complex structural response resulting from lateral distributed vehicles. By exploiting the distinct characteristics of different strain types that reflect various aspects of the structure, the VIDM establishes a sophisticated mapping relationship between bending, shear strain and axle parameters, which enables the accurate determination of axle parameters including axle speed and spacing. The real-time estimation of the multi-lane vehicle load is achieved by combining the obtained axle information with the decoupled bending strain. This method effectively solves the problem of large load estimation error caused by inaccurate identification of axle parameters, and enables accurate acquisition of vehicle load in lateral distribution using bending and shear strains near the bridge entrance. Both numerical studies and laboratory tests are carried out on a simply supported beam for conceptual verification. The results demonstrate that the proposed method successfully improves the measurement of multi-lane vehicle load.
High-precision long distance measurement based on broad spectrum interferometry using a femtosecond laser
Authors: Gao Haoran , Huang Lei , Xu Xin , Wang Dagui , Ge Pengxiang , Zhao Huining 
Published: July 2024

Abstract
The method based on broad spectrum interference using femtosecond pulses is an important ranging method. In this paper, we experimentally evaluate the effect of interferometric spectral bandwidth used for calculation on the ranging results, and precision can be improved by choosing the optimal spectral bandwidth. In addition, in order to eliminate the influence of interferometric spectral fluctuations on the measurement results, we introduce the detrend algorithm into the processing algorithm and compare the measurement results before and after the algorithm improvement. Then, four kinds of nominal distance were measured and the contribution of the relevant factors to the measurement uncertainty is evaluated. Finally, the synthetic standard uncertainty of measurement results was 0.02, 0.10, 1.05 and 2.78 μm for nominal distance of ∼0, ∼1.5 ∼16.5 and ∼43.5 m respectively.
A novel adaptive blind deconvolution algorithm: application to feature extraction of weak faults in RV reducer gears
Authors: Tang Yin , Lv Zhongliang , Jia Xiangyu , Peng Linhao , Li Lingfeng , Zhou Jie , Luo Jiasen , Xu Youwei 
Published: July 2024

Abstract
Aiming at the problem that the non-stationary and nonlinear weak fault signal of RV (rotate vector) reducers is hard to extract fault features due to the influence of noise and transmission paths, as well as the selection of parameters for maximum correlation kurtosis deconvolution (MCKD) relies heavily on manual experience, this article proposes a fault feature extraction method based on parameter adaptive MCKD for the gear faults of RV reducers. Firstly, the sparrow search algorithm combining sine-cosine and Cauchy mutation (SCSSA) is used to adaptively search for the input parameters of MCKD and obtain the signal after deconvolution with the optimal parameters. Secondly, the deconvoluted signal is subjected to ensemble empirical mode decomposition to obtain modal components on different frequency bands. Finally, calculate the multi-scale fuzzy entropy (MFE) of each component, constructing a MFE feature set vector, and input the feature vector into the support vector machine for fault classification and recognition. The experimental analysis and verification results both indicate that the proposed method can adaptively enhance the weak impact components in the gear signals of the RV reducer, effectively extracting weak fault features disturbed by noise. Compared with minimum entropy deconvolution, multipoint optimal minimum entropy deconvolution adjusted and MCKD, the proposed method has improved identification rate by 17.50%, 10.63% and 15.63%, respectively. In addition, in comparison to multiverse optimization and particle swarm optimizatio algorithms, the SCSSA exhibits superior performance when optimizing MCKD parameters, offering faster convergence speed, higher accuracy, and greater robustness.
Development and comprehensive investigation of a lightweight FBG accelerometer for small structure acceleration measurements
Authors: Rahim Muhammad Rais , Hossain MD Mofazzal , Hassan Mohd Firdaus 
Published: July 2024

Abstract
Despite their sensitivity potential, diaphragm-type fiber Bragg grating accelerometers with inertia mass are often too complex and large, limiting their suitability for measuring small structures. Designing a suitable accelerometer for small structures, where its weight must be less than one-tenth of the measured structure, is challenging. This paper introduces a compact, simplified, and fabricable non-inertia mass FBG accelerometer (FBGA-SD), featuring a longer FBG tunnel and a through-hole for monitoring. The proposed FBGA-SD is 16 × 16 × 10 mm, weighing 4 grams. Numerical and experimental results show good agreement, though amplitude sensitivity differs by 50%. The experimental sensitivity is 9.64 × 10−2 pm g−1, while transient response analysis gives 4.79 × 10−2 pm g−1, valid for 10–100 Hz excitation frequencies and up to 10.5 m s−2 base acceleration.
A GNSS/SINS fault detection and robust adaptive algorithm based on sliding average smooth bounded layer width
Authors: Zhao Guiling , Wang Jinbao , Gao Shuai , Jiang Zihao 
Published: July 2024

Abstract
The Global Navigation Satellite System/Strapdown Inertial Navigation System (GNSS/SINS) integrated navigation system is an important technology for UAV measurement and vehicle movement measurement. But in the operational process of the GNSS/SINS integrated navigation system, the GNSS signal is vulnerable to external interference, resulting in abnormal system measurement data, and system faults. These faults will reduce the navigation and positioning performance of the system and reduce the measurement accuracy of the system. Aiming at this problem, a GNSS/SINS fault detection and robust adaptive algorithm based on sliding average smooth bounded layer width is proposed. The algorithm evaluates the system measurement data based on the innovation residual and incorporates the sliding average filter to design the fault detection function based on the smooth bounded width layer. Accurate detection of system faults using fault detection function. The fault detection function value is used to construct the robust cofactor matrix to correct the measurement error in real-time, to improve the accuracy and robustness of the state estimation. The experimental results show that: The proposed algorithm in the paper compares with two traditional robust adaptive algorithms based on smooth bounded layer fault detection and residual chi-square fault detection. The fault detection rates for small step faults show an increase of more than 44.26% and 9.54%, respectively. Similarly, for slowly varying faults, the fault detection rates exhibit an increase of more than 29.32% and 13.56%, respectively. Throughout the fault, the filtering accuracy demonstrates an increase of more than 16.52% and 15.47%, respectively. The algorithm effectively improves the measurement accuracy of the GNSS/SINS integrated navigation system.
Molecular Oxygen Abundance in Galactic Massive Star Formation Regions Based on SWAS Observations
Authors: Wang Bing-Ru , Li Di , Goldsmith Paul F. , Wu Jingwen , Tsai Chao-Wei , Quan Donghui , Zhang Xia , Wang Junzhi , Melnick Gary J. , Li Jin-Zeng , Fuller Gary A. , Xie Jinjin 
Published: July 2024

Abstract
Molecular oxygen abundance is a key parameter in understanding the chemical network of the interstellar medium. We estimate the molecular oxygen column density and abundance for a sample of Galactic massive star formation regions based on observations from the Submillimiter Wave Astronomy Satellite (SWAS) survey. We obtained an averaged O2 spectrum based on this sample using the (SWAS) survey data (O2, 487.249 GHz, N = 3–1, J = 3–2). No emission or absorption feature is seen around the supposed central velocity with a total integration time of t
total = 8.67 × 103 hr and an rms noise per channel of 1.45 mK. Assuming a kinetic temperature T
kin = 30 K, we derive the 3σ upper limit of the O2 column density to be 3.3 × 1015 cm−2, close to the lowest values reported in Galactic massive star formation regions in previous studies. The corresponding O2 abundance upper limit is 6.7 × 10−8, lower than all previous results based on SWAS observations and is close to the lowest reported value in massive star formation regions. On a galactic scale, our statistical results confirm a generally low O2 abundance for Galactic massive star formation regions. This abundance is also lower than results reported in extragalactic sources.
Action formalism for geometric phases from self-closing quantum trajectories
Authors: Shea Dominic , Romito Alessandro 
Published: July 2024

Abstract
When subject to measurements, quantum systems evolve along stochastic quantum trajectories that can be naturally equipped with a geometric phase observable via a post-selection in a final projective measurement. When post-selecting the trajectories to form a close loop, the geometric phase undergoes a topological transition driven by the measurement strength. Here, we study the geometric phase of a subset of self-closing trajectories induced by a continuous Gaussian measurement of a single qubit system. We utilize a stochastic path integral that enables the analysis of rare self-closing events using action methods and develop the formalism to incorporate the measurement-induced geometric phase therein. We show that the geometric phase of the most likely trajectories undergoes a topological transition for self-closing trajectories as a function of the measurement strength parameter. Moreover, the inclusion of Gaussian corrections in the vicinity of the most probable self-closing trajectory quantitatively changes the transition point in agreement with results from numerical simulations of the full set of quantum trajectories.