bluuebunny/crossref_metadata_2025_split huggingface dataset:
Time-reversal invariance violation effect in dd scattering*
Authors: Platonova M. N. , Uzikov Yu. N. 
Published: December 2024

Abstract
A formalism is developed for calculating the signal of the violation of time-reversal invariance, provided that space-reflection (parity) invariance is conserved during the scattering of tensor-polarized deuterons on vector-polarized deuterons. The formalism is based on Glauber theory and fully considers the spin dependence of

elastic scattering amplitudes and the spin structure of colliding deuterons. Numerical calculations are performed in the laboratory proton energy range

–1.2 GeV using the SAID database for spin amplitudes and in the energy region of the SPD NICA experiment corresponding to the invariant mass of the interacting nucleon pairs

–25 GeV, using two phenomenological models of

elastic scattering. It is found that only one type of the time-reversal non-invariant parity conserving

interaction gives a non-zero contribution to the signal in question, which is important for isolating an unknown constant of this interaction from the corresponding data.
Constraining Schwarzschild Models with Orbit Classifications
Authors: Long Richard J. 
Published: December 2024

Abstract
A simple orbit classification constraint extension to stellar dynamical modeling using Schwarzschild’s method is demonstrated. The classification scheme used is the existing ‘orbit circularity’ scheme (λ_z) where orbits are split into four groups - hot, warm, cold and counter rotating orbits. Other schemes which can be related to the orbit weights are expected to be viable as well. The results show that the classification constraint works well in modeling. However, given that orbits in external galaxies are not observable, it is not clear how the orbit classification for any particular galaxy may be determined. Perhaps range constraints for different types of galaxies determined from cosmological simulations may offer a way forward.
Study on Soil Vibration Propagation Characteristics Caused by Subway near Foundation Pit
Authors: Xia Zhifan , Huang Peng , Huang Yanwu , Zhang Jingjing 
Published: December 2024

Abstract
Based on the Shanghai Metro Line 12, a three-dimensional finite element calculation model is established to study the influence of adjacent foundation pits on subway train vibration propagation. A comparative analysis is conducted on the vibration response and propagation characteristics of the subway during single and bidirectional metro operation under free field and adjacent foundation pit conditions. The effects of subway train speed and tunnel depth on vibration propagation are discussed in detail. It is indicated that as the train speed increases, the ground vibration increases, and the increasing trend of vertical acceleration gradually slows down. The deeper the tunnel is buried, the smaller the ground vibration response. The variation of tunnel burial depth has no effect on the attenuation law of vertical vibration.
Darboux integrability of hyperbolic partial differential equations: is it a property of integrals rather than equations?
Authors: Startsev S Ya 
Published: December 2024

Abstract
We consider functions that depend on x, y,

u
(
x
,
y
)

and its derivatives with respect to x. Among them, we are interested in functions g for which there exists an ordinary differential operator such that its composition with the Fréchet derivative of g is expressed in terms of x, g and the total derivatives of g with respect to x. Integrals of the smallest orders for Darboux integrable partial differential equations (PDEs) possess the above property (which is completely independent of any PDE). We prove an almost converse statement: if a function g has the above property and there exists an equation for which g is an integral, then this equation admits integrals in the other characteristic and is therefore Darboux integrable. In particular, if g is an integral of the smallest order for a Darboux integrable equation, then any equation admitting the same integral g is Darboux integrable too. These facts can be used to check the already known lists of Darboux integrable equations for completeness and to find new Darboux integrable equations. As an illustration of this approach, we obtain a family of the Darboux integrable equations, which is probably new. We also briefly discuss whether the Darboux integrability can be defined via properties of the integrals only (without employing the PDEs). If this is possible, then the classification of the Darboux integrable equations may be reduced to the classification of the functions with these properties.
Results of the study of operating conditions in the cylinder and changes in the characteristics of diesel and gas diesel motor oils
Authors: Utaev Sobir , Temurkhanov Anver 
Published: December 2024

Abstract
This article discusses the results of a study of changes in the characteristics of M10G2 oils during the operation of diesel engines and gas engines based on diesel engines. During engine operation, the oil in the lubrication system circulates under conditions of temperature difference. The thermal load of the engine depends on the engine boost. Thermal stress and temperature of hot gases intensively influence the oxidation of oil; this process occurs in the annular zone of the pistons. The operating conditions are harsh in the working surface of the cylinder in the piston stroke area, in this area the oil is subject to thermal decomposition and high oxidation intensity. When operating a diesel engine, compared to a gas-diesel engine, the main oil indicators such as viscosity, density, mechanical impurities, high- and low-temperature characteristics, chemical characteristics such as base number have lower limit values, and the oil service life can be considered 1.5 times higher when operating at gaseous fuel. The alkaline number in samples of used oils varies from 2.24 to 1.4, which indicates the emergency condition of the used oil. The results of analyzes of the alkaline number of the studied motor oils show that when the engine is running on gaseous fuel it decreased on average from 6.0 to 2.2 mg KOH/g, and when running on diesel fuel from 6.0 to 1.4 mg KOH/g. i.e. below the permissible level.
Method to improve the classification accuracy by in situ laser cleaning of painted metal scraps during laser-induced breakdown spectroscopy based sorting
Authors: LEE Jaepil , SHIN Sungho , JANG Inseok , BAE Seongguk , JEONG Sungho 
Published: December 2024

Abstract
Scrap metals are typically covered with surface contaminants, such as paint, dust, and rust, which can significantly affect the emission spectrum during laser-induced breakdown spectroscopy (LIBS) based sorting. In this study, the effects of paint layers on metal surfaces during LIBS classification were investigated. LIBS spectra were collected from metal surfaces painted with black and white paints by ablation with a nanosecond pulsed laser (wavelength = 1064 nm, pulse width = 7 ns). For the black-painted samples, the LIBS spectra showed a broad background emission, emission lines unrelated to the target metals, large shot-to-shot variation, and a relatively low signal intensity of the target metal, causing poor classification accuracy even at high shot numbers. Cleaning the black paint layer by ablating over a wide area prior to LIBS analysis resulted in high classification accuracy with fewer shot numbers. A method to determine the number of cleaning shots necessary to obtain high classification accuracy and high throughput is proposed on the basis of the change in LIBS signal intensity during cleaning shots. For the white-painted samples, the paint peeled off the metal surface after the first shot, and strong LIBS signals were measured after the following shot, which were attributed to the nanoparticles generated by the ablation of the paint, allowing an accurate classification after only two shots. The results demonstrate that different approaches must be employed depending on the paint color to achieve high classification accuracy with fewer shot numbers.
Equivariant Variational Quantum Eigensolver to detect phase transitions through energy level crossings
Authors: Crognaletti Giulio , Di Bartolomeo Giovanni , Vischi Michele , Loris Viteritti Luciano 
Published: December 2024

Abstract
Level spectroscopy stands as a powerful method for identifying the transition point that delineates distinct quantum phases. Since each quantum phase exhibits a characteristic sequence of excited states, the crossing of energy levels between low-lying excited states offers a reliable mean to estimate the phase transition point. While approaches like the Variational Quantum Eigensolver are useful for approximating ground states of interacting systems using quantum computing, capturing low-energy excitations remains challenging. In our study, we introduce an equivariant quantum circuit that preserves the total spin and the translational symmetry to accurately describe singlet and triplet excited states in the J
1–J
2 Heisenberg model on a chain, which are crucial for characterizing its transition point. Additionally, we assess the impact of noise on the variational state, showing that conventional mitigation techniques like Zero Noise Extrapolation reliably restore its physical properties.
Framing flooding in African cities: a corpus-assisted discourse analysis of the phenomenon in the Ghanaian press
Authors: Terkper Paulina , Baddianaah Issah 
Published: December 2024

Abstract
Increasing climate change and urban planning deficiencies have exacerbated flood disasters in African cities, attracting widespread media discussion and public concern. This study examines the discursive construction of perennial flooding in Accra, in the Ghanaian press, to bring to light how the phenomenon is represented with regards to whether or not it contributes to a proper appreciation of the situation in attempting to address the problem. It uses as dataset an 86,602-word specialised corpus built from news reports on flooding and a 422,436-word reference corpus (written component of International Corpus of English, Ghana). The study employs a Corpus-Assisted Discourse Studies (CADS) approach to explore the discourse using Keyword analysis, Concordance lines and Collocate analysis. Findings revealed framing of perennial flooding in the city as an unwelcome threat, as it is found to colligate with: ‘problems, damage, death and loss’, giving it a negative discourse prosody. In addition, there is unclear (de)construction of the major cause of the floods in the news, as experts assert that siltation of the drains is the major challenge, but what is often projected by the media as the cause is choked gutters. The findings inform policymakers that robust proactive measures, public education and sensitisation, as well as a firm commitment on the part of the government, in particular, are needed to tackle the perennial floods in Accra.
Dynamic hybrid visual-thermal multimodal perception neuromorphic devices based on defect modulation of electrospun nanofibers
Authors: Wen Shengkai , Liu Yanan , Li Yi , Xie Liang , Li Jun , Zhang Jianhua 
Published: December 2024

Abstract
Neuromorphic devices, inspired by the intricate architecture of the human brain, have garnered recognition for their prodigious computational speed and sophisticated parallel computing capabilities. Vision, the primary mode of external information acquisition in living organisms, has garnered substantial scholarly interest. Notwithstanding numerous studies simulating the retina through optical synapses, their applications remain circumscribed to single-mode perception. Moreover, the pivotal role of temperature, a fundamental regulator of biological activities, has regrettably been relegated to the periphery. To address these limitations, we proffer a neuromorphic device endowed with multimodal perception, grounded in the principles of light-modulated semiconductors. This device seamlessly accomplishes dynamic hybrid visual and thermal multimodal perception, featuring temperature-dependent paired pulse facilitation properties and adaptive storage. Crucially, our meticulous examination of transfer curves, capacitance–voltage (C–V) tests, and noise measurements provides insights into interface and bulk defects, elucidating the physical mechanisms underlying adaptive storage and other functionalities. Additionally, the device demonstrates a variety of synaptic functionalities, including filtering properties, Ebbinghaus curves, and memory applications in image recognition. Surprisingly, the digital recognition rate achieves a remarkable value of 98.8%. These discernments furnish crucial insights for the prospective evolution of intricate neuromorphic systems.
Real-time rainfall projection in hilly areas using ARLSTM model: a case of Dharamshala, India
Authors: Mahajan Deepika , Sharma Sandeep , Saini Komal 
Published: December 2024

Abstract
Rainfall forecasting is essential in many industries, including agriculture, hydrology, urban planning, disaster management, and renewable energy. However, typical forecasting approaches frequently fail to reflect the complex spatiotemporal dynamics inherent in rainfall patterns, particularly in hilly areas. Since, the mountainous terrain influences wind patterns, moisture flow, and temperature inversions which affect precipitation patterns, adding challenge to meteorologists. So, designing a predictive forecasting model is essential for people and governments to make preventive measures in time. In recent years, the introduction of Internet of Things (IoT) technology and advances in machine learning (ML) techniques have provided a promising route for improving rainfall prediction accuracy. Real-time data on environmental elements such as temperature, wind speed, air pressure, and humidity can be collected using IoT sensor networks. This research paper investigates the efficacy of the Auto-Regressive Integrated Moving Average - Long Short-Term Memory (ARIMA-LSTM) model for real-time rainfall prediction in hilly towns like Dharamshala. Utilizing real-time data collected from sensors and using edge to preprocess it before sending it to the cloud, this study explores the integration of traditional time series analysis techniques with deep learning architectures to enhance predictive accuracy. The propounded model is paralleled against alternative forecasting approaches and shows a significant reduction in Root Mean Square Error (RMSE), Relative Root Mean Square Error (RRMSE), and Mean Square Error (MSE). Furthermore, it had a 0% Absolute Percentage Bias (APB), a high Nash-Sutcliffe Efficiency (NSE) of 0.99, and a low Theil’s coefficient (U2) of 0.01. These results demonstrate that the ARLSTM model outperforms other forecasting models of rainfall prediction.
Process tomography of structured optical gates with convolutional neural networks
Authors: Jaouni Tareq , Di Colandrea Francesco , Amato Lorenzo , Cardano Filippo , Karimi Ebrahim 
Published: December 2024

Abstract
Efficient and accurate characterization of an experimental setup is a critical requirement in any physical setting. In the quantum realm, the characterization of an unknown operator is experimentally accomplished via Quantum Process Tomography (QPT). This technique combines the outcomes of different projective measurements to reconstruct the underlying process matrix, typically extracted from maximum-likelihood estimation. Here, we exploit the logical correspondence between optical polarization and two-level quantum systems to retrieve the complex action of structured metasurfaces within a QPT-inspired context. In particular, we investigate a deep-learning approach that allows for fast and accurate reconstructions of space-dependent SU(2) operators by only processing a minimal set of measurements. We train a convolutional neural network based on a scalable U-Net architecture to process entire experimental images in parallel. Synthetic processes are reconstructed with average fidelity above 90%. The performance of our routine is experimentally validated in the case of space-dependent polarization transformations acting on a classical laser beam. Our approach further expands the toolbox of data-driven approaches to QPT and shows promise in the real-time characterization of complex optical gates.
Changes in upper airway airflow after rapid maxillary expansion considering normal craniofacial development as a factor: a retrospective study using computer fluid dynamics
Authors: Lo Giudice Antonino , Polizzi Alessandro , Lagravere Manuel , Flores-Mir Carlos , Isola Gaetano , Ronsivalle Vincenzo , Leonardi Rosalia 
Published: December 2024

Abstract

Background/Objectives
Evidence suggests nasal airflow resistance reduces after rapid maxillary expansion (RME). However, the medium-term effects of RME on upper airway (UA) airflow characteristics when normal craniofacial development is considered are still unclear. This retrospective cohort study used computer fluid dynamics (CFD) to evaluate the medium-term changes in the UA airflow (pressure and velocity) after RME in two distinct age-based cohorts.

Materials/Methods
The study included 48 subjects who underwent RME divided into two cohorts: a 6−9-year-old group (EEG group: early expansion group − 25 subjects) and an 11−14-year-old group (LEG group: late expansion group − 23 subjects). The nasal cavity and pharyngeal anatomy were segmented from Cone-beam computed tomography reconstructions taken before RME (T0) and 12 after RME (T1). The two UA airflow variables (pressure and velocity) were simulated using CFD. The maxillary expansion (PW) amount, two cross-sectional area measurements (CS1 = anterior cross-section and CS2 = posterior cross-section), and four UAs’ subregions (NC = nasal cavity, PAtotal = pharyngeal airway, NP = nasopharynx, VP = velopharynx, and OP = Oropharynx) were also considered. All data were statistically analyzed.

Results
At the baseline, the airflow pressure, velocity, and noted obstructions were significantly higher in the EEG compared to LEG. At T1, there was a significant improvement in the median airway parameters in both groups, which was remarkably greater in the EEG. A significant negative correlation was found between pressure/velocity and both CS2 and NP. According to the CFD plots, the airflow pressure and velocity changes could be attributed to the reduction of the adenotonsillar tissues’ sizes, which were remarkably more marked in the EEG.

Limitations
The results of this study cannot be generalized since they referred to a retrospective orthodontic sample without obstructive adenotonsillar hypertrophy.

Conclusions/Implications
Twelve months after RME, normal craniofacial developmental changes and spontaneous adenotonsillar tissues volume regression could represent the most significant factors influencing UA airflow changes.
The effect of education debt on PAs' specialty choice or preference
Authors: Kozikowski Andrzej , Bruza-Augatis Mirela , Morton-Rias Dawn , Puckett Kasey , Jeffery Colette , Quella Alicia , Mauldin Sheila , Goodman Joshua 
Published: December 2024

ABSTRACT

Objective:
This study investigated educational debt, repayment strategies, and other factors potentially related to recently certified physician associates/assistants' (PAs') choice or preference for primary care versus all other specialties.

Methods:
A national dataset from 2023 of recently certified PAs was used to conduct quantitative and qualitative analyses. Analyses were conducted separately for PAs who had accepted a clinical position and those who had not accepted a clinical position.

Results:
Overall, 88% of respondents reported having educational debt, with 13.5% owing $200,000 or more. PAs from backgrounds underrepresented in medicine had accrued higher educational debt than their counterparts. Educational debt was significantly associated with specialty choices/preferences: PAs with higher debt were more likely to opt for nonprimary care specialties. Qualitative analyses revealed that PAs rely on different strategies for repaying their loans, depending on whether they choose or prefer primary care or nonprimary care specialties.

Conclusions:
These results suggest that educational debt plays a role in specialty selection, but other factors also are significant.
Aromatherapy with tanxiang prescription for mild to moderate anxiety: a randomized controlled pilot trial
Authors: Fang Yan , Fung Kandace , Xia Ying , Wei Wei , Liu Jiali , Wu Xiaqiu , Zhang Weijun 
Published: December 2024

Objective:
To investigate the feasibility and preliminary effectiveness of Tanxiang Prescription (TXP) ointment for alleviating mild to moderate anxiety.

Methods:
A single-center pilot trial was conducted. Participants were randomly assigned to the experimental group or the control group. The experimental group received TXP treatment and health education, while the control group only received health education. The study evaluated the feasibility based on recruitment, retention, adherence, and adverse events. The primary outcome was assessed using the Self-Rating Anxiety Scale (SAS), while the secondary outcomes were evaluated using the Self-Rating Depression Scale (SDS) and Pittsburgh Sleep Quality Index (PSQI). Assessments were conducted at baseline, week 2, and week 4.

Results:
58 participants were successfully enrolled, with 56 in all have finished whole research, which illustrating a recruitment rate of 33.7%, a randomization rate of 100%, and a loss rate of 3.57% in this study. No adverse events were observed. Both the experimental (n=29) and control (n=29) groups showed a significant decrease in SAS, SDS, and PSQI scores in comparison to their baseline scores at week 4 (P<0.05). Additionally, the experimental group showed significantly greater reductions in SAS, SDS, and PSQI scores than those in the control group at week 4 (P<0.05).

Conclusions:
TXP may be a promising treatment option for mild to moderate anxiety, offering a duel benefit of alleviating depression and promoting better sleep without any adverse effects. This study also references the effectiveness of Traditional Chinese Medicine aromatherapy for anxiety management. Further pharmacological and clinical studies are needed to observe the impact of TXP on emotional regulation in patients with anxiety.