bluuebunny/crossref_metadata_2025_split huggingface dataset:
Topological edge state assisted dynamically tunable microwave propagations in photonic crystals
Authors: Jana Sambhu , Devi Koijam Monika , Kulkarni Gopal , Mallick Soumyajyoti , Roy Chowdhury Dibakar 
Published: August 2023

Abstract
Topological photonics has emerged as a cutting-edge and intriguing field that permits electromagnetic waves to transmit with minimal losses even when they come in contact with sharp turns or imperfections or defects. In this study, we validate a strategy to realize dynamically amplitude tunable light propagation in a topological waveguide based on a three-dimensional printed valley Hall photonic crystal structure operating in the microwave frequency region. Here, tunable light propagation is facilitated by inserting an active defect in the form of a semiconductor (silicon) material slab across the domain boundary of the topological waveguide. In this configuration, dynamic variation of transmission amplitude is realized via photoexcitation of the semiconductor defect using an external laser of wavelength,

λ
∼
510

nm. This results in active amplitude tunability of

∼
−
10

dB in topological wave propagation under a photoexcitation of 100 mW. Our demonstrated route can lead to the design of dynamically controlled topological photonic devices such as optical modulators, switches, optical buffers, etc which are important for the development of 6G communication systems.
Higher-order co-mutation interactions in mitochondrial genomes
Authors: Verma Rahul K , Shinde Pramod , Mishra Ankit , Jalan Sarika 
Published: August 2023

Abstract
Pair-wise co-mutation networks of the mitochondrial genome have already provided ample evidences about the roles of genetic interactions in the manifestation of phenotype under altered environmental conditions. Here, we present a method to construct and analyze higher-order interactions, namely, three-uniform hypergraphs of the mitochondrial genome for different altitude populations to decipher the role of co-mutating variable sites beyond pair-wise interactions. We considered the human mitochondrial DNA residing at different altitudes with respect to Tibet in Asia as a case study. We found that in 50% of the gene triangles, two positions were occupied by coding genes, which suggested that coding genes are dominantly involved in forming the hyperedges. Based on weights of the gene triangles, we identified altitude-specific genes such as, in low-altitude ATP6 and ND genes, in mid-altitude CO1 and ND genes, and in high-altitude ATP6, CO1, CYB and ND genes. This framework of three-uniform hypergraph serves an avenue for future investigation of nuclear genomes in context of phenotypic association and genetic disorders beyond the pair-wise interactions.
Effects of pulse energy and contact foil thickness on the surface integrity of LY2 aluminum alloy subjected to laser shock wave planishing technology
Authors: Wu Lei , Dai Fengze , Huang Shu , Chen Xizhang 
Published: August 2023

Abstract
Reducing the surface roughness is an effective way to improve the fatigue performance of aero-engine blades. In this paper, the milled surface of LY2 aluminum alloy was processed by a laser shock wave planishing (LSWP) technology, and the influence of the laser pulse energy and the contact foil thickness on the surface integrity were studied. The results showed that the thinner the contact foil and the higher the pulse energy were, the higher the removal rate of tool marks (the degree to which the milled topography of LY2 aluminum alloy surface is flattened) was. On the contrary, the thicker the contact foil and the lower the pulse energy were, the lower the removal rate of tool marks was. It will cause ‘center depression’ under LSWP with a thin contact foil and a high laser pulse energy, resulting in an increase of surface roughness, a large difference in residual stress and micro-hardness between the center and the laser spot edge. In the overlapping LSWP experiment, when the contact foil thickness matched the appropriate laser pulse energy, the milled surface was flattened without boundary effect, and in 67% overlapping experiment, a thicker contact foil can be used to achieve the same high-quality surface as in 50% overlapping experiment.
Preparation and characterization of Ni-Co-TiN/CeO2 composite coating by jet electrodeposition for improved mechanical and anti-corrosion properties
Authors: Chen Yuanlong , Li Huigui , Fang Cheng , Deng Weiping , Zhu Fankai , He Gaoqing , Tian Zongjun , Jiang Wei 
Published: August 2023

Abstract
The Ni-Co alloy was coated with Ni-Co-TiN/CeO2 by Jet electrodeposition to enhance the properties of Nickel-Cobalt (Ni-Co) alloy. The morphologies, texture orientation, microhardness, coating adhesion, wear resistance, and corrosion resistance of Ni-Co-TiN/CeO2 composite coatings were characterized. The influences of concentration of mixed particles (micron-TiN and nano- CeO2) on microstructural, surface properties, mechanical properties and anti-corrosion performance of the composite coatings were studied. The addition of nano-mixed particles changed the morphology of Ni-Co-TiN/CeO2 composite coating from large cellular protrusion structures to fine granular structures, the mechanical properties and anti-corrosion performance of Ni-Co-TiN/CeO2 composite coatings were improved. The composite coating exhibited superior microhardness, bonding force, wear resistance and anti-corrosion performance, when the concentration of mixed particles was 4 g l−1. This work contributed to the development of a variety of micro- and nanoparticle phase-enhanced metal-based composite coatings.
Using a fast hybrid pixel detector for dose-efficient diffraction imaging beam-sensitive organic molecular thin films
Authors: Wu Mingjian , Stroppa Daniel G , Pelz Philipp , Spiecker Erdmann 
Published: August 2023

Abstract
We discuss the benefits and showcase the applications of using a fast, hybrid-pixel detector (HPD) for 4D-STEM experiments and emphasize that in diffraction imaging the structure of molecular nano-crystallites in organic solar cell thin films with a dose-efficient modality 4D-scanning confocal electron diffraction (4D-SCED). With 4D-SCED, spot diffraction patterns form from an interaction area of a few nm while the electron beam rasters over the sample, resulting in high dose effectiveness yet highly demanding on the detector in frame speed, sensitivity, and single-pixel count rate. We compare the datasets acquired with 4D-SCED using a fast HPD with those using state-of-the-art complementary metal-oxide-semiconductor (CMOS) cameras to map the in-plane orientation of π-stacking nano-crystallites of small molecule DRCN5T in a blend of DRCN5T: PC71BM after solvent vapor annealing. The high-speed CMOS camera, using a scintillator optimized for low doses, showed impressive results for electron sensitivity and low noise. However, the limited speed restricted practical experimental conditions and caused unintended damage to small and weak nano-crystallites. The fast HPD, with a speed three orders of magnitude higher, allows a much higher probe current yet a lower total dose on the sample, and more scan points cover a large field of view in less time. A lot more faint diffraction signals that correspond to just a few electron events are detected. The improved performance of direct electron detectors opens more possibilities to enhance the characterization of beam-sensitive materials using 4D-STEM techniques.
Investigating the aerodynamic effect of rooftop cargo compartment – a case of modified intercity bus
Authors: Tefera Addis , Bekele Addisu , Pandey Vivek 
Published: August 2023

Abstract
Buses are one mode of mass transportation but they are inefficient in terms of fuel consumption and ergonomically poor when loaded. Thus to decrease the fuel consumption, an improvement on the aerodynamic shape of the bus is required. This paper mainly focused on locally modified ISUZU buses which are serving as an intercity bus in Ethiopia. These buses are inefficient in terms of fuel consumption because of their body design and other add-on devices. One of the add-on devices which spoil the aerodynamic profile of this bus is the luggage loaded on the roof rack. Therefore, in this paper aerodynamically efficient rooftop luggage compartment is designed for these buses. The performance test is carried out for a scaled-down ISUZU bus model numerically using ANSYS Fluent CFD software and experimentally using wind tunnel testing. The numerical results are validated by an experimental test which is carried out using HM 170 open wind tunnel set-up. According to the numerical result, the modified bus reduced the drag coefficient by 34%, 34.5% and 34%, when compared to the clean roof baseline bus, the baseline bus with roof rack and the loaded baseline bus respectively. Similarly, the drag force is reduced by 12%, 14% and 32% respectively. In addition, the fuel consumption is reduced by 2.15 l h
−1, 4.17 l h
−1 and 7.24 l h
−1 respectively. It is also found that the numerical results are in good agreement with the experimental results. Overall, the modified bus is found to be more fuel saving and ergonomically better design.
Enhancement of corrosion resistance of CrMoV low alloy steels using cryogenic treatment
Authors: Sarveswara Reddy S , Durga Rajesh K V , Francis Luther King M 
Published: August 2023

Abstract
The current investigation explores the effect of cryogenic treatment on the microstructural and corrosion behavior of CrMoV low-alloy steels. The casted samples in the required dimensions were treated by annealing followed by deep cryogenic treatment (DCT). Initially, the microstructural modification brought by combined treatments was studied using an optical microscope (OM), scanning electron microscope (SEM), and x-ray diffraction (XRD) technique. After DCT, a refined and uniform grain structure was identified. The DCT resulted in the development of a fine-grained structure and reduced the mean grain size of the alloy, and this refinement of the grain structure is due to the reduction of lattice defects during the cooling process. The corrosion behavior was studied using the weight loss and Tafel polarization tests. The corrosion findings indicated a significant enhancement in the corrosion resistance of the specimens after DCT. The DCT specimens exhibited higher corrosion potentials compared to the base material. The DCT can promote the development of a more protective passive layer on the sample’s surface. This passive layer serves as an obstacle, preventing the diffusion of corrosive products and increasing corrosion resistance. Finally, it suggests that DCT positively impacts the CrMoV steels’ resistance to corrosion.
Deep learning neural network for approaching Schrödinger problems with arbitrary two-dimensional confinement
Authors: Radu A , Duque C A 
Published: August 2023

Abstract
This article presents an approach to the two-dimensional Schrödinger equation based on automatic learning methods with neural networks. It is intended to determine the ground state of a particle confined in any two-dimensional potential, starting from the knowledge of the solutions to a large number of arbitrary sample problems. A network architecture with two hidden layers is proposed to predict the wave function and energy of the ground state. Several accuracy indicators are proposed for validating the estimates provided by the neural network. The testing of the trained network is done by applying it to a large set of confinement potentials different from those used in the learning process. Some particular cases with symmetrical potentials are solved as concrete examples, and a good network prediction accuracy is found.
Comorbid Conditions and Complications in Body Contouring Surgery: A Retrospective Review
Authors: Garoosi Kassra , Mundra Leela , Jabbari Kayvon , Winocour Julian , Iorio Matthew L , Mathes David W , Kaoutzanis Christodoulos 
Published: August 2023

Abstract

Background
Body contouring procedures have significantly increased in popularity in the United States.

Objectives
The authors sought to understand, categorize, and classify patients’ experiences with postoperative complications following common body contouring procedures.

Methods
PearlDiver (PearlDiver Technologies, Colorado Springs, CO), a database with over 90 million patients, was queried to identify patients who had undergone body contouring procedures between 2010 and 2021 using current procedural terminology (CPT) codes. The authors identified patients who underwent panniculectomy, abdominoplasty, brachioplasty, thighplasty, mastopexy, breast augmentation, augmentation mastopexy, breast reduction, and liposuction for analysis. They reviewed combined procedures and analyzed risk factors associated with the most common complications.

Results
There were 243,886 patients included in the study. The majority of patients were female, between 50 and 59 years old, and had their procedures performed in the southern United States. There were an average of 25,352 procedures per year. The majority of cases involved breast surgeries. The most common preoperative comorbid conditions diagnosed 1 year before surgery were hypertension, obesity, and diabetes. The most common postoperative complications within 90 days were wound dehiscence, hematoma, and urinary tract infection. A logistic regression evaluating the association of the preoperative comorbid conditions with postoperative complications found that patients with obesity, tobacco use, diabetes, and hypertension had an increased risk of developing wound dehiscence, hematoma, and surgical-site infection.

Conclusions
The data suggest that patients with obesity, tobacco use, diabetes, and hypertension undergoing body contouring surgery are at greater risk of developing wound dehiscence, hematomas, and surgical-site infections. Understanding this data is imperative for providers to adequately identify associated risk factors, stratify patients, and provide adequate perioperative counseling.

Level of Evidence: 2
diseaseGPS: auxiliary diagnostic system for genetic disorders based on genotype and phenotype
Authors: Huang Daoyi , Jiang Jianping , Zhao Tingting , Wu Shengnan , Li Pin , Lyu Yongfen , Feng Jincai , Wei Mingyue , Zhu Zhixing , Gu Jianlei , Ren Yongyong , Yu Guangjun , Lu Hui 
Published: August 2023

Abstract

Summary
The next-generation sequencing brought opportunities for the diagnosis of genetic disorders due to its high-throughput capabilities. However, the majority of existing methods were limited to only sequencing candidate variants, and the process of linking these variants to a diagnosis of genetic disorders still required medical professionals to consult databases. Therefore, we introduce diseaseGPS, an integrated platform for the diagnosis of genetic disorders that combines both phenotype and genotype data for analysis. It offers not only a user-friendly GUI web application for those without a programming background but also scripts that can be executed in batch mode for bioinformatics professionals. The genetic and phenotypic data are integrated using the ACMG-Bayes method and a novel phenotypic similarity method, to prioritize the results of genetic disorders. diseaseGPS was evaluated on 6085 cases from Deciphering Developmental Disorders project and 187 cases from Shanghai Children’s hospital. The results demonstrated that diseaseGPS performed better than other commonly used methods.

Availability and implementation
diseaseGPS is available to freely accessed at https://diseasegps.sjtu.edu.cn with source code at https://github.com/BioHuangDY/diseaseGPS.
RNA 3D structure modeling by fragment assembly with small-angle X-ray scattering restraints
Authors: Chojnowski Grzegorz , Zaborowski Rafał , Magnus Marcin , Mukherjee Sunandan , Bujnicki Janusz M 
Published: August 2023

Abstract

Summary
Structure determination is a key step in the functional characterization of many non-coding RNA molecules. High-resolution RNA 3D structure determination efforts, however, are not keeping up with the pace of discovery of new non-coding RNA sequences. This increases the importance of computational approaches and low-resolution experimental data, such as from the small-angle X-ray scattering experiments. We present RNA Masonry, a computer program and a web service for a fully automated modeling of RNA 3D structures. It assemblies RNA fragments into geometrically plausible models that meet user-provided secondary structure constraints, restraints on tertiary contacts, and small-angle X-ray scattering data. We illustrate the method description with detailed benchmarks and its application to structural studies of viral RNAs with SAXS restraints.

Availability and implementation
The program web server is available at http://iimcb.genesilico.pl/rnamasonry. The source code is available at https://gitlab.com/gchojnowski/rnamasonry.
IsoFrog: a reversible jump Markov Chain Monte Carlo feature selection-based method for predicting isoform functions
Authors: Liu Yiwei , Yang Changhuo , Li Hong-Dong , Wang Jianxin 
Published: August 2023

AbstractMotivationA single gene may yield several isoforms with different functions through alternative splicing. Continuous efforts are devoted to developing machine-learning methods to predict isoform functions. However, existing methods do not consider the relevance of each feature to specific functions and ignore the noise caused by the irrelevant features. In this case, we hypothesize that constructing a feature selection framework to extract the function-relevant features might help improve the model accuracy in isoform function prediction.ResultsIn this article, we present a feature selection-based approach named IsoFrog to predict isoform functions. First, IsoFrog adopts a reversible jump Markov Chain Monte Carlo (RJMCMC)-based feature selection framework to assess the feature importance to gene functions. Second, a sequential feature selection procedure is applied to select a subset of function-relevant features. This strategy screens the relevant features for the specific function while eliminating irrelevant ones, improving the effectiveness of the input features. Then, the selected features are input into our proposed method modified domain-invariant partial least squares, which prioritizes the most likely positive isoform for each positive MIG and utilizes diPLS for isoform function prediction. Tested on three datasets, our method achieves superior performance over six state-of-the-art methods, and the RJMCMC-based feature selection framework outperforms three classic feature selection methods. We expect this proposed methodology will promote the identification of isoform functions and further inspire the development of new methods.Availability and implementationIsoFrog is freely available at https://github.com/genemine/IsoFrog.
Accessibility of covariance information creates vulnerability in Federated Learning frameworks
Authors: Huth Manuel , Arruda Jonas , Gusinow Roy , Contento Lorenzo , Tacconelli Evelina , Hasenauer Jan 
Published: August 2023

Abstract

Motivation
Federated Learning (FL) is gaining traction in various fields as it enables integrative data analysis without sharing sensitive data, such as in healthcare. However, the risk of data leakage caused by malicious attacks must be considered. In this study, we introduce a novel attack algorithm that relies on being able to compute sample means, sample covariances, and construct known linearly independent vectors on the data owner side.

Results
We show that these basic functionalities, which are available in several established FL frameworks, are sufficient to reconstruct privacy-protected data. Additionally, the attack algorithm is robust to defense strategies that involve adding random noise. We demonstrate the limitations of existing frameworks and propose potential defense strategies analyzing the implications of using differential privacy. The novel insights presented in this study will aid in the improvement of FL frameworks.

Availability and implementation
The code examples are provided at GitHub (https://github.com/manuhuth/Data-Leakage-From-Covariances.git). The CNSIM1 dataset, which we used in the manuscript, is available within the DSData R package (https://github.com/datashield/DSData/tree/main/data).
A neighborhood-regularization method leveraging multiview data for predicting the frequency of drug–side effects
Authors: Wang Lin , Sun Chenhao , Xu Xianyu , Li Jia , Zhang Wenjuan 
Published: August 2023

Abstract

Motivation
A critical issue in drug benefit-risk assessment is to determine the frequency of side effects, which is performed by randomized controlled trails. Computationally predicted frequencies of drug side effects can be used to effectively guide the randomized controlled trails. However, it is more challenging to predict drug side effect frequencies, and thus only a few studies cope with this problem.

Results
In this work, we propose a neighborhood-regularization method (NRFSE) that leverages multiview data on drugs and side effects to predict the frequency of side effects. First, we adopt a class-weighted non-negative matrix factorization to decompose the drug–side effect frequency matrix, in which Gaussian likelihood is used to model unknown drug–side effect pairs. Second, we design a multiview neighborhood regularization to integrate three drug attributes and two side effect attributes, respectively, which makes most similar drugs and most similar side effects have similar latent signatures. The regularization can adaptively determine the weights of different attributes. We conduct extensive experiments on one benchmark dataset, and NRFSE improves the prediction performance compared with five state-of-the-art approaches. Independent test set of post-marketing side effects further validate the effectiveness of NRFSE.

Availability and implementation
Source code and datasets are available at https://github.com/linwang1982/NRFSE or https://codeocean.com/capsule/4741497/tree/v1.
771 Heart Rate Variability as a Marker of Surgeon’s Stress and Cognitive Load Within Vascular Surgery
Authors: De Louche C D , Mandal M , Fernandes L , Lawson J , Pouncey A L , Bicknell C D 
Published: August 2023

Abstract

Aim
Surgeons experience significant stress levels in theatre. Acute stress can cause cognitive overload, worsening surgical performance. Chronic stress poses a substantial risk to surgeons’ health. Effectively identifying intraoperative stress may allow for preventative strategies that reduce surgeons’ stress and improve patient outcomes. Here, the feasibility of using heart rate variability (HRV) as a marker of stress during vascular surgery was assessed.

Method
11 senior surgeons were evaluated performing 3 distinct vascular surgery procedures. HRV metrics (low-frequency/high-frequency ratio and standard deviation of the normal-normal interval) were determined from single-lead ECG traces at pre-determined procedural performance points. Surgeon-reported stress was assessed using the State-Trait Anxiety Inventory-6 (STAI-6), a validated clinical stress tool. Subjective reports of procedural difficulty were also collected. One-way ANOVA compared HRV at key performance points to baseline. Pearson’s coefficient assessed correlation between HRV and subjective stress.

Results
Data was collected for 6 carotid endarterectomies, 6 open abdominal aortic aneurysm repairs, and 5 lower limb bypasses. HRV metrics indicating significantly greater stress were observed at key performance points in all procedures. Peaks in stress were consistent across different surgeons performing the same procedure. A significant correlation was observed between HRV metrics and subjective STAI-6 stress reports (r = 0.7680, p = 0.0003). HRV metrics displaying the greatest stress corresponded with the most difficult procedural steps reported.

Conclusions
HRV may present a feasible method to assess intraoperative stress and cognitive load in vascular surgery and could be used to evaluate whether a theatre intervention (e.g., timeout) could reduce stress in areas of surgical difficulty.