bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Comparison of Esthetic Preferences on Female Skeletal Class II Alterations among Laypeople of Different Facial Profiles
Authors: Tipyanggul Wiwan , Changsiripun Chidsanu , Chamnannidiadha Niramol 
Published: July 2024

Abstract
Objectives This study aimed to investigate the influences of assessors' different personal profiles on the esthetic perception of Class II facial profile corrections and the agreement between profile and silhouette images.
Materials and Methods A profile photo of a female with skeletal Class II was digitally altered into three profile and three silhouette images (most pronounced Class II division 1 characteristic, more retruded upper lip position, and more protruded mandibular position). Ninety-six laypeople from three facial profile groups (straight, convex, and concave profiles) chose these images for facial attractiveness. Data were analyzed using an SPSS program. Cohen's kappa coefficient and intraclass correlation coefficients were applied to determine intraparticipant and intra-examiner reliabilities. Chi-square tests were used to test between-group preferences and the relationship of profile preference with other factors. Cohen's kappa coefficient was used to test the agreement in selecting profile and silhouette images (p = 0.05).
Results All groups favored profiles with a protruded mandibular position (11-degree facial contour angle [FCA] and 91-degree nasolabial angle [NLA]). Despite facial profile differences, preference remained consistent (p = 0.649). The convex group showed a stronger inclination toward an untreated-simulating profile (17-degree FCA and 91-degree NLA). Preferences were consistent regardless of sex (p = 0.198) and education (p = 0.105). The percentage of agreement between profile and silhouette images in the total sample was 67.71% (kappa = 0.386). All groups of participants chose the more retruded upper lip position (17-degree FCA and 107-degree NLA) profile in silhouette more than in photograph.
Conclusion All groups preferred a mandibular advancement-simulating profile. Using the photographs or silhouettes to assess the esthetic preference resulted in a similar trend. However, the flatter profile was more preferred in silhouette than in photograph.
Role of Endoscopy in Managing Complications Associated with Pancreaticoduodenectomy: Concise Review of Literature
Authors: Puri Rahul , Mahajan Akhil , Sundaram Sridhar 
Published: July 2024

AbstractPancreaticoduodenectomy (PD) is a complex surgery for the management of periampullary tumors. It is associated with significant morbidity and mortality of 20% and 3 to 5% respectively. While early complications like delayed gastric emptying, hemorrhage, and collections are common, late complications like biliary and pancreatic anastomotic stenosis are also known to occur. With the increase in cases of pancreatic and periampullary cancers, there is an upward trend seen even in the rates of surgery. Endoscopy has emerged over the years as a tool for both evaluation and management of various complications. In this narrative review, we aim to provide a primer for gastroenterologists who are likely to be called upon for endoscopic management of post-PD complications.
The “bridge character”: Carl Schurz and West German–American rapprochement
Authors: Kinney Brandon 
Published: July 2024

AbstractIn 1952, West Germans and Americans held a joint, year-long observation celebrating the centennial of the arrival of German-born Carl Schurz in the USA. The collaborative, transatlantic celebration served to publicize a historical and cultural relationship between the German and American peoples through the memory of Carl Schurz. State and non-state participants publicly remembered Schurz as the quintessential German–American and a “bridge character” that transcended national borders, occupied an important ideological space, legitimized the Cold War relationship between erstwhile enemies, and perpetuated an on-going process to construct a transnational, cultural identity rooted in Western liberal-democratic political culture. For the US government, the historical character of Carl Schurz also became a means of promoting a liberal heritage in the face of on-going Soviet accusations of American imperialism, warmongering, and poor race relations.
First-principles study of non-linear thermal expansion in cadmium titanate by molecular dynamics incorporating nuclear quantum effects
Authors: Kanayama Kansei , Toyoura Kazuaki 
Published: July 2024

Abstract
First-principles molecular dynamics (FPMD) simulations were applied for analyzing structural evolutions around the paraelectric-ferroelectric phase transition temperature in the perovskite-type cadmium titanate, CdTiO3. Since the phase transition is reported to occur at the low temperature around 80 K, the quantum thermal bath (QTB) method was utilized in this study, which incorporates the nuclear quantum effects (NQEs). The structural evolutions in the QTB-FPMD simulations are in reasonable agreement with the experimental results, by contrast in the conventional FPMD simulations using the classical thermal bath (CTB-FPMD). Especially, the non-linear thermal expansion of lattice constants around the phase transition temperature was well reproduced in the QTB-FPMD with the NQEs. Thus, the NQEs are of importance in phase transitions at low temperatures, particularly below the room temperature, and the QTB is useful in that it incorporates the NQEs in MD simulations with low computational costs comparable to the conventional CTB.
A new perspective on ductile high-Tc superconductors under ambient pressure: few-hydrogen metal-bonded hydrides
Authors: Shi Jun-jie , Tian Chong , He Yong , Liu Shi-ming , Zhu Yao-hui , Du Juan , Zhong Hong-xia , Wang Xinqiang 
Published: July 2024

Abstract
Superconducting materials have garnered widespread attention due to their zero-resistance characteristic and complete diamagnetism. After more than 100 years of exploration, various high-temperature superconducting materials including cuprates, nickelates, iron-based compounds, and ultra-high pressure multi-hydrides have been discovered. However, the practical application of these materials is severely hindered by their poor ductility and/or the need for high-pressure conditions to maintain structural stability. To address these challenges, we first provide a new thought to build high-temperature superconducting materials based on few-hydrogen metal-bonded hydrides under ambient pressure. We then review the related research efforts in this article. Moreover, based on the bonding type of atoms, we classify the existing important superconducting materials and propose the new concepts of pseudo-metal and quasi-metal superconductivity, which are expected to be helpful for the design of new high-temperature superconducting materials in the future.
Comprehensive quality evaluation method of ultrasound tomography algorithms based on entropy method
Authors: Xiong Zichen , Hu Jingyi , Li Nan 
Published: July 2024

Abstract
Multiphase flow systems, crucial in fields like chemical, petroleum, and biology, often involve challenging gas–liquid flows with variable interfaces. Ultrasonic Tomography (UT) helps visualize these flows by using array sensors to create two-dimensional images. However, issues arise in assessing the cross-section gas-holding ratio with UT, as original images usually need filter processing and multi-dimensional evaluations can be contradictory. This study introduces a comprehensive evaluation method for UT image quality, leveraging the entropy evaluation method (EEM). It uses ultrasonic data and algorithms like Sector-diffusion-matrix-based Local Binary Pattern, Landweber, and Tikhonov for image reconstruction. Evaluation focuses on three aspects: Pearson correlation coefficient, image position error, and reconstruction area error, offering a thorough assessment of image accuracy. The EEM balances contradictory indicators and aligns with most indicator distribution laws, proving effective in assessing UT image reconstruction quality.
FR-YOLOv7: feature enhanced YOLOv7 for rotated small object detection in aerial images
Authors: Tang Xue , Deng Hao , Liu Guihua , Li Guilin , Li Qiuheng , Zhao Junqin , Zhou Yuan 
Published: July 2024

AbstractFor the problems of weak object feature expression and variable object orientation in aerial image object detection, this paper proposed a feature enhanced YOLOv7 for rotated small object detection in aerial images. Firstly, for the problem of feature loss in the feature extraction stage, the feature enhanced spatial pyramid pooling and cross stage partial connections module was proposed, which effectively boost the feature expression of small object. Secondly, an attention guided max-pooling module was constructed to address the problem of feature loss. Then, the rotated object detection head was introduced to solve the problem of false negatives caused by variable object angles and dense object distribution. Finally, a multi-scale loss function was proposed for improving the detection effects of rotated small objects detection in aerial images. Extensive experiments were conduct on the public datasets of DOTA and University of the Chinese Academy of Sciences-AOD, with the help of the proposed method, we can achieve the detection accuracy that the mean average precision are 79.7% and 98.9%, respectively. Experimental results demonstrate that the proposed method has a significant improvement on the detection of small targets in aerial images.
Seismic noise effect suppression for the performance testing of high-precision space electrostatic accelerometers using a torsion pendulum with differential configuration
Authors: Li J , Liu Z F , Ma Y , Yu J B , Liu L , Zhou Z B 
Published: July 2024

Abstract
To test the performance of high-precision electrostatic accelerometers for next generation satellite gravity measurement missions, a torsion pendulum integrated with two electrostatic accelerometers is proposed. In this differential configuration scheme, the seismic noise effect can be further suppressed due to common-mode rejection. Theoretical analysis shows that the seismic noise effect rejection ratio is determined by the inconsistency factors of two accelerometers, and after the compensation for inconsistency, the seismic noise effect can be suppressed by at least 85 dB below 0.1 Hz. Preliminary experimental results are agreed with the theoretical analysis, and its detection sensitivity comes to

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at 10 mHz, which is limited by the intrinsic noises of accelerometers used here.
Enhanced measurement and optimization of railway profile parameters for large tamping machine operations
Authors: Li Shu , Liu Zhihui , Han Lei , Jing Guoqing 
Published: July 2024

Abstract
In the realm of modern railway maintenance, the employment of large tamping machine for the enhancement of track geometry and elasticity, and the minimization of disturbance to the roadbed, has become a key operational approach. However, factors such as repeated load applications, changes in topography and geology, and ongoing maintenance activities have been known to cause significant deviations of the actual track location from its original design. These deviations present challenges, such as increased construction difficulty and workload, during tamping operations predicated on the original design. Moreover, methods based on manual intervention have rendered large machine maintenance operations inefficient. In this paper, an optimisation method for railway profile parameters suitable for large tamping machine operations is proposed. The method integrates the total least squares method and the direct search method, enabling the accurate fitting of slope segments preceding and following the slope change points and the alignment of circular curve segments to determine the optimal curve radius. Consequently, optimised profile parameters for the continuous track section are obtained. Focusing on the Beijing–Guangzhou line, the operational efficacy of the proposed optimisation method is compared with that of the artificial slope method. The results showed that the proposed optimisation method is not only more accurate and efficient but also adheres to the principle of ‘prefer lifting rather than descending’ of the railways. The method further provides a theoretical basis and practical guidance for the optimisation of railway profile, underscoring the potential for improved maintenance efficiency and enhanced safety in train operations.
Fault diagnosis of complex industrial equipment based on chunked statistical global-local feature fusion
Authors: Yang Fang , Lian Zisheng , Li Runze , Liao Yaoyao , Nie Zhengqi 
Published: July 2024

Abstract
Industrial process equipment is bulky and complex in structure, which is easy to produce faults during operation and affect production efficiency, cause huge economic losses, and even threaten the safety of workers. To achieve sustainable operation of large-scale industrial processes, timely and accurate monitoring and handling of abnormal situations are essential. However, fault monitoring of large equipment requires the collection of abundant data, which includes many complex related variables, resulting in excessive redundant data generated during the fault monitoring process. Moreover, the existing principal component analysis (PCA) method can only retain the global characteristic of variance information, and cannot obtain the local characteristic that can characterize the topological relationship between the data points, which affects its monitoring reliability and intelligence level. In response to these issues, a fault diagnosis model for complex industrial processes based on chunked statistical global-local feature fusion (CSGLFF) is proposed in this paper. First, considering the correlation characteristics between industrial process variables, a correlation variable chunking method mutual information-based is designed to merge the variables with small correlation to obtain the optimal chunking of variables. Second, PCA and locality preserving projections (LPP) are combined to construct a global-local feature fusion (GLFF) model that can extract global and local features simultaneously. The chunked data are imported into the GLFF for the extraction of its features respectively, and the corresponding CSGLFF is established. In addition, Bayesian inference is used to fuse the statistics of each sub-chunk to establish an overall fault monitoring statistical indicators, and the reason for failure is found through the variable contribution graph. Finally, two cases of Tennessee Eastman process (TEP) and laboratory emulsion pump were used to conduct experimental research on the performance of CSGLFF. The results show that compared with the chunked statistical PCA, chunked statistical LPP, and GLFF algorithms, The accuracy of fault monitoring for TEP mean, flow pulsation impact, and pressure anomaly of this method reached 92.91%, 97%, and 90.30%, respectively. It has good monitoring effect in processing data with large variables, reducing the generation of redundant data, improving the accuracy of industrial monitoring, and accurately identifying the relevant variables of fault occurrence. This provides a theoretical basis for determining the fault location and points out the direction for maintenance by staff.
Zero-shot fault diagnosis of high-voltage circuit breakers: fusion of phase space reconstruction and attribute embedding methods
Authors: Yang Qiuyu , Liu Yawen , Lin Yuyi , Li Jianxing , Ruan Jiangjun 
Published: July 2024

Abstract
Traditional mechanical fault diagnosis methods for high-voltage circuit breakers (CBs) largely rely on data-driven learning from a substantial amount of labeled fault samples. However, the scarcity of target fault samples in practical engineering applications often limits diagnostic performance, leading to high misdiagnosis rates and poor generalization capabilities. To address these challenges, this study proposes an attribute embedding zero-shot diagnosis (AEZSD) method, designed to overcome the limitations of sample insufficiency. Initially, this paper utilizes phase space reconstruction techniques to thoroughly explore the intrinsic dynamic features of vibrational signals within CBs. Subsequently, by integrating the electromechanical signal characteristics of the CBs, the concept of fault attributes is introduced, and an attribute embedding learning network is constructed. Through this network and statistical rules, the proposed method can effectively identify previously unseen fault types. Experimental results confirm that the AEZSD method can leverage historical fault data to pre-learn fault attribute knowledge and accurately diagnose faults without target fault samples, providing a novel solution for CB fault diagnosis.
Multifractal magnitude and sign correlations in multiphase flows
Authors: Ren Weikai , Jin Ningde 
Published: July 2024

Abstract
It is important to reveal the complex phenomenon of bubble coalescence or breakup in gas–liquid two-phase flow to understand the dynamic mechanism of flow pattern transition. Magnitude and sign decomposition paves a way to study the linear and nonlinear fractal characteristic separately. In this work, we extended this method to multifractal analysis, namely the multifractal magnitude and sign correlations. Test was conducted and an eight-electrode rotating conductivity sensor is utilized to collect the signals of different flow patterns in the gas–liquid two phase flow. The signal is initially decomposed into magnitude time series and sign time series. The width and difference of multifractal spectrum are introduced to characterize the nonlinear dynamics in the flow pattern evolution that gas–liquid two-phase slug flow breaks into the bubble flow or loses stability transforms into churn flow. And then these parameters of multifractal magnitude and sign decomposition are fed into k-Nearest Neighbor (KNN) for flow pattern identification. The results suggest that multifractal magnitude and sign decomposition has higher prediction accuracy (93%) than traditional multifractal analysis. The findings show that multifractal magnitude and sign correlations analysis is a powerful technique for investigating the flow dynamic of gas–liquid two phase flow.
Validation of dual-energy CT-based composition analysis using fresh animal tissues and composition-optimized tissue equivalent samples
Authors: Niepel Katharina , Tattenberg Sebastian , Marants Raanan , Hu Guyue , Bortfeld Thomas , Verburg Joost , Sudhyadhom Atchar , Landry Guillaume , Parodi Katia 
Published: July 2024

Abstract

Objective. Proton therapy allows for highly conformal dose deposition, but is sensitive to range uncertainties. Several approaches currently under development measure composition-dependent secondary radiation to monitor the delivered proton range in-vivo. To fully utilize these methods, an estimate of the elemental composition of the patient’s tissue is often needed. Approach. A published dual-energy computed tomography (DECT)-based composition-extraction algorithm was validated against reference compositions obtained with two independent methods. For this purpose, a set of phantoms containing either fresh porcine tissue or tissue-mimicking samples with known, realistic compositions were imaged with a CT scanner at two different energies. Then, the prompt gamma-ray (PG) signal during proton irradiation was measured with a PG detector prototype. The PG workflow used pre-calculated Monte Carlo simulations to obtain an optimized estimate of the sample’s carbon and oxygen contents. The compositions were also assessed with chemical combustion analysis (CCA), and the stopping-power ratio (SPR) was measured with a multi-layer ionization chamber. The DECT images were used to calculate SPR-, density- and elemental composition maps, and to assign voxel-wise compositions from a selection of human tissues. For a more comprehensive set of reference compositions, the original selection was extended by 135 additional tissues, corresponding to spongiosa, high-density bones and low-density tissues. Results. The root-mean-square error for the soft tissue carbon and oxygen content was 8.5 wt% and 9.5 wt% relative to the CCA result and 2.1 wt% and 10.3 wt% relative to the PG result. The phosphorous and calcium content were predicted within 0.4 wt% and 1.1 wt% of the CCA results, respectively. The largest discrepancies were encountered in samples whose composition deviated the most from tabulated compositions or that were more inhomogeneous. Significance. Overall, DECT-based composition estimations of relevant elements were in equal or better agreement with the ground truth than the established SECT-approach and could contribute to in-vivo dose verification measurements.
Efficient radiation treatment planning based on voxel importance
Authors: Mair Sebastian , Fu Anqi , Sjölund Jens 
Published: July 2024

Abstract

Objective. Radiation treatment planning (RTP) involves optimization over a large number of voxels, many of which carry limited information about the clinical problem. We propose an approach to reduce the large optimization problem by only using a representative subset of informative voxels. This way, we drastically improve planning efficiency while maintaining the plan quality. Approach. Within an initial probing step, we pre-solve an easier optimization problem involving a simplified objective from which we derive an importance score per voxel. This importance score is then turned into a sampling distribution, which allows us to subsample a small set of informative voxels using importance sampling. By solving a—now reduced—version of the original optimization problem using this subset, we effectively reduce the problem’s size and computational demands while accounting for regions where satisfactory dose deliveries are challenging. Main results. In contrast to other stochastic (sub-)sampling methods, our technique only requires a single probing and sampling step to define a reduced optimization problem. This problem can be efficiently solved using established solvers without the need of modifying or adapting them. Empirical experiments on open benchmark data highlight substantially reduced optimization times, up to 50 times faster than the original ones, for intensity-modulated radiation therapy, all while upholding plan quality comparable to traditional methods. Significance. Our novel approach has the potential to significantly accelerate RTP by addressing its inherent computational challenges. We reduce the treatment planning time by reducing the size of the optimization problem rather than modifying and improving the optimization method. Our efforts are thus complementary to many previous developments.
Study on the regulation factors and mechanism of self-heating effects in non-rectangular 14 nm bulk FinFET*
Authors: Qin Zhaohui , Chen Lan , Lu Renjie , Wang Yali , Hao Xiaoran , Chen Rong , Sun Yan , Du Qin 
Published: July 2024

Abstract
This work investigates the innovative design of a 14 nm bulk 3D non-rectangular structure fin field-effect transistor (FinFET). By incorporating a cylindrical trapezoidal structure into the upper portion of the FinFET, it transcend the limitations posed by the self-heating (SH) effect observed in traditional rectangular fins.Through the density gradient model and thermal conduction model, the changes in the electron carrier temperature and lattice temperature of the channel are studied, and the relationship between electrical properties and thermal resistance was further analyzed, revealing the effect of SH on the threshold voltage and switching speed of the device. In addition, the SH effect of the doping of source and drain extension regions was also explored, and the effects of electron mobility changes at different ambient temperatures were also studied to clarify their impact on the electrical properties. Ultimately, this work offers novel insights into the design, optimization, and reliability studies of device structures affected by SH effects.