bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence mechanisms of linoleic acid and oleic acid on the gel properties of egg yolk protein
Authors: Huang Xinyuan , Li Xin , Zhang Yufeng , Li Xiefei , Zhang Pei , Song Hongbo , Huang Qun , Fu Guiming
Published: April 2024

BACKGROUND

Gel property is among the crucial functional properties of egg yolk (EY), which determines the texture and flavor of EY products. In the present study, the effects of two unsaturated fatty acids [monounsaturated fatty acid oleic acid (OA) and diunsaturated fatty acid linoleic acid (LA)] on the gel properties of EY protein were investigated.

RESULTS

Compared with the blank group, the addition of LA and OA (10–50 g kg−1) improved the gel hardness (from 270.54 g to 385.85 g and 414.38 g, respectively) and viscosity coefficient (from 0.015 Pa.sn to 11.892 Pa.sn and 1.812 Pa.sn, respectively). The surface hydrophobicity of EY protein increased to a maximum value of 40 g kg−1 with the addition of both fatty acids (39.06 μg and 41.58 μg, respectively). However, excess unsaturated fatty acids (≥ 50 g kg−1) disrupted the completeness of the gel matrix and weakened the structural properties of the EY gel.

CONCLUSION

Both fatty acids improved the gel properties of EY protein. At the same addition level, OA was superior to LA in improving gel properties. The present study provides a theoretical underpinning for the sensible application of unsaturated fatty acids in improving EY gel properties. © 2024 Society of Chemical Industry.
The boundedness of operators on weighted multi‐parameter mixed Hardy spaces
Authors: Ding Wei , Gu Min , Zhu YuePing
Published: April 2024

In this paper, we discuss the boundedness of mixed Journé's class operators on weighted multi‐parameter mixed Hardy spaces via atoms decomposition. Moreover, we give a specific singular integral operator in mixed Journé's class which has better properties.
Preparation, processing, and application of ultrathin lithium metal
Authors: Huang Shaozhen , Li Wenhao , Zhang Yu , Li Tianbao , Chen Yuejiao , Kuang Guichao , Liu Wen , He Zhiyuan , Wu Zhibin , Chen Libao
Published: April 2024

Lithium metal is a promising electrode material for next‐generation high‐energy‐density rechargeable batteries with its high theoretical capacity (3860 mAh g−1) and low standard electrode potential (−3.04 V vs. SHE). However, the special physicochemical properties of lithium metal, including low tensile strength, viscoplastic creep, and high reactivity hinder the processing and preparation of lithium strips toward ultrathin thickness (≤20 μm). Developing new matrixes, interfaces, and processing methods can be promising for overcoming these problems. This review summarizes the physicochemical properties of lithium metal and the design principles for preparing the ultrathin Li metal, and concludes the recent development in this field from the perspective of processing design, and proposes to provide in‐depth understanding of reliable fabrication of ultrathin lithium metal strips, and prospects the challenges and opportunities of ultrathin‐scale preparation and processing of lithium metal.
Multiplicative generalized tube surfaces with multiplicative quaternions algebra
Authors: Ceyhan Hazal , Özdemir Zehra , Gök Ismail
Published: April 2024

Along with other types of calculus, multiplicative calculus brings an entirely new perspective. Geometry now has a new field as a result of this new understanding. In this study, multiplicative differential geometry was used to explore peculiar surfaces. Multiplicative quaternions are also used to depict surfaces. Additionally, multiplicative differential geometry was used to generate the accretive surface subject, which is a developing subject. The derived surfaces' perspective silhouette curve equation is provided. The Bishop multiplicative frame was also established and applied when expressing surfaces along with these. Finally, the surfaces and perspective silhouette curves were visualized using Maple, and the equations were obtained.
A medical image segmentation method for rectal tumors based on multi‐scale feature retention and multiple attention mechanisms
Authors: Zhao Jumin , Liu Linjun , Yang Xiaotang , Cui Yanfen , Li Dengao , Zhang Huiting , Zhang Kenan
Published: April 2024

Background

With the continuous development of deep learning algorithms in the field of medical images, models for medical image processing based on convolutional neural networks have made great progress. Since medical images of rectal tumors are characterized by specific morphological features and complex edges that differ from natural images, achieving good segmentation results often requires a higher level of enrichment through the utilization of semantic features.

Purpose

The efficiency of feature extraction and utilization has been improved to some extent through enhanced hardware arithmetic and deeper networks in most models. However, problems still exist with detail loss and difficulty in feature extraction, arising from the extraction of high‐level semantic features in deep networks.

Methods

In this work, a novel medical image segmentation model has been proposed for Magnetic Resonance Imaging (MRI) image segmentation of rectal tumors. The model constructs a backbone architecture based on the idea of jump‐connected feature fusion and solves the problems of detail feature loss and low segmentation accuracy using three novel modules: Multi‐scale Feature Retention (MFR), Multi‐branch Cross‐channel Attention (MCA), and Coordinate Attention (CA).

Results

Compared with existing methods, our proposed model is able to segment the tumor region more effectively, achieving 97.4% and 94.9% in Dice and mIoU metrics, respectively, exhibiting excellent segmentation performance and computational speed.

Conclusions

Our proposed model has improved the accuracy of both lesion region and tumor edge segmentation. In particular, the determination of the lesion region can help doctors identify the tumor location in clinical diagnosis, and the accurate segmentation of the tumor edge can assist doctors in judging the necessity and feasibility of surgery.
Estimate and compensate head motion in non‐contrast head CT scans using partial angle reconstruction and deep learning
Authors: Chen Zhennong , Li Quanzheng , Wu Dufan
Published: April 2024

Background

Patient head motion is a common source of image artifacts in computed tomography (CT) of the head, leading to degraded image quality and potentially incorrect diagnoses. The partial angle reconstruction (PAR) means dividing the CT projection into several consecutive angular segments and reconstructing each segment individually. Although motion estimation and compensation using PAR has been developed and investigated in cardiac CT scans, its potential for reducing motion artifacts in head CT scans remains unexplored.

Purpose

To develop a deep learning (DL) model capable of directly estimating head motion from PAR images of head CT scans and to integrate the estimated motion into an iterative reconstruction process to compensate for the motion.

Methods

Head motion is considered as a rigid transformation described by six time‐variant variables, including the three variables for translation and three variables for rotation. Each motion variable is modeled using a B‐spline defined by five control points (CP) along time. We split the full projections from 360° into 25 consecutive PARs and subsequently input them into a convolutional neural network (CNN) that outputs the estimated CPs for each motion variable. The estimated CPs are used to calculate the object motion in each projection, which are incorporated into the forward and backprojection of an iterative reconstruction algorithm to reconstruct the motion‐compensated image. The performance of our DL model is evaluated through both simulation and phantom studies.

Results

The DL model achieved high accuracy in estimating head motion, as demonstrated in both the simulation study (mean absolute error (MAE) ranging from 0.28 to 0.45 mm or degree across different motion variables) and the phantom study (MAE ranging from 0.40 to 0.48 mm or degree). The resulting motion‐corrected image, , exhibited a significant reduction in motion artifacts when compared to the traditional filtered back‐projection reconstructions, which is evidenced both in the simulation study (image MAE drops from 178 33HU to 37 9HU, structural similarity index (SSIM) increases from 0.60 0.06 to 0.98 0.01) and the phantom study (image MAE drops from 117 17HU to 42 19HU, SSIM increases from 0.83 0.04 to 0.98 0.02).

Conclusions

We demonstrate that using PAR and our proposed deep learning model enables accurate estimation of patient head motion and effectively reduces motion artifacts in the resulting head CT images.
Effect of digital technology interventions for cognitive function improvement in mild cognitive impairment and dementia: A systematic review and meta‐analysis
Authors: Park Hyojin , Ha Juyoung
Published: April 2024

The development and commercialization of digital therapeutics are increasing. The aim of this study was to determine the effects of digital technology interventions on cognitive function, thereby providing evidence for the development and practical application of interventions to manage cognitive function in patients with mild cognitive impairment and dementia. We conducted a systematic review and meta‐analysis of randomized controlled trials according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta‐Analysis) guidelines. Randomized controlled trials on digital technology interventions published until April 2023 were searched in PubMed, Embase, Cochrane Library, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases without a period limit. Articles that identified the effects of digital technology interventions on cognitive function improvement in dementia and mild cognitive impairment were integrated and analyzed. RevMan software 5.4 was used for quality assessment and meta‐analysis. Twelve out of 708 studies were included in the review and meta‐analysis. Digital technology interventions had significant effects on global cognitive function (standardized mean difference [SMD] = 0.31; 95% confidence interval [CI] = 0.04–0.57; p = 0.02; I² = 60%). In addition, these interventions had significant effects on neuropsychological characteristics, including attention (SMD = 1.17; 95% CI = 0.36–1.97; p = 0.004; I² = 84%), visuospatial perception (SMD = 0.68; 95% CI = 0.19–1.17; p = 0.006; I² = 57%), and memory (SMD = 0.45; 95% CI = 0.19–0.71; p = 0.0007; I² = 22%). The results suggest that digital technology interventions help improve cognitive function in patients with dementia and mild cognitive impairment.
Relationship Between National Residency Matching Program (NRMP) Rank Order and Otolaryngology Residency Performance
Authors: Ezeh Uche C. , Svirsky Mario A. , April Max M.
Published: April 2024

Objective

The process of resident recruitment is costly, and our surgical residency program expends significant time on the resident selection process while balancing general duties and responsibilities. The aim of our study was to explore the relationship between otolaryngology–head and surgery (OHNS) residents' National Residency Matching Program (NRMP) rank‐list position at our institution and their subsequent residency performance.

Study Design

Retrospective cohort study.

Setting

Single site institution.

Methods

We retrospectively reviewed 7 consecutive resident classes (2011‐2017) at a single tertiary OHNS residency program. We reviewed each resident's absolute rank order in the NRMP matches. Measures of residency performance included overall faculty evaluation during postgraduate year 5 (PGY5), annual in‐service examination scores (scaled score), and the number of manuscripts published in peer‐reviewed journals. Correlations between NRMP rank order and subsequent residency performance were assessed using Spearman's rho correlation coefficients (ρ).

Results

Twenty‐eight residents entered residency training between 2011 and 2017. The average rank position of the trainees during this study was 9.7 (range: 1‐22). We found no significant correlation between rank order and faculty evaluation during PGY5 (ρ = 0.097, P = .625) or number of publications (ρ = −0.256, P = .189). Additionally, when assessing the association between rank order and annual Otolaryngology Training Examination‐scaled scores, no statistically significant relationship was found between the 2 (P > .05).

Conclusion

Our results showed that there were no significant correlations between OHNS rank order and various measures of success in residency training, which aligns with existing literature. Further investigation of this relationship should be conducted to ensure the applicability of our findings.
The interplay of bank competition and institutional quality: Implications for shadow economy
Authors: Khattak Mudeer Ahmed , Azmi Wajahat , Ali Mohsin , Khan Noureen A.
Published: April 2024

This study investigates the impact of institutional quality and banking competition on shadow economy for 127 economies for the period of 2005–2017. It further explores if institutional quality/competition shapes the relationship differently between banking competition/institutional quality and shadow economy. This paper uses the system GMM estimator to tackle potential omitted variable bias, endogeneity, and simultaneity issues. The findings suggest that overall, greater competition among banks and stricter institutions in the country reduce the size of shadow economy. Furthermore, impact of competition on shadow economy is even stronger in countries with weak institutions and the impact of institutional quality is greater in lower competitive environment. Only severe competition matters for shadow economy in case of developed countries. To sum up the novel findings of this research, competition and institutions complement each other in reducing the size of shadow economy. These findings are robust to different econometric estimators. The findings carry vital policy implications for the governments and regulators to play their part in reducing the shadow economy.
Synthesis and characterization of cellulose nanofibers from waste paper and their utilization in wood adhesion
Authors: Joshi Garima , Chauhan Shakti Singh
Published: April 2024

Nanocellulose extraction from lignocellulosic materials is a highly chemical and energy‐intensive process as it requires the removal of lignin and hemicellulose. Writing paper is one of the processed materials that could be used as a raw material for the extraction of nanocellulose. In this work, cellulose nanofibers (CNFs) were synthesized from paper waste using TEMPO‐oxidation followed by high‐shear microfluidization. Scanning electron microscopy and atomic force microscopy confirmed the diameter of fibers in the nano‐range and a consistent zeta potential confirmed the stability of CNF suspension in water over a long time frame. Characterization of the CNFs using Fourier transform infrared spectroscopy indicated the presence of a carbonyl group due to the oxidation process. Thermogravimetric analysis and x‐ray diffraction revealed lower thermal stability and reduction in the crystallinity index of CNFs, as compared to pulp fibers. The obtained CNFs were used successfully as the sole binding agent in the preparation of fiberboards and also utilized as a reinforcing agent for polyvinyl acetate (PVAc) adhesive in the preparation of laminated veneer lumber (LVLs). The addition of CNFs in PVAc improved the glue shear strength indicating superior bonding characteristics and also increased the water resistance of the LVLs.

Highlights

This work focused on cellulose nanofibers (CNFs) extraction from waste paper

Obtained CNFs form stable water suspension and have a diameter of less than 15 nm

Thermal stability and crystallinity index reduced after conversion to nanofibers

CNFs form a complex network and act as a sole binder to make fiberboards

CNFs were utilized as a reinforcing agent for PVAc in preparation of LVLs
Density Functional Theory‐Based Adsorption Studies of ClO2 and Its Decomposition Products on Defective and Metal‐Doped Graphene
Authors: Zhu Pengcheng , Yu Weiyao , Zhao Jiaming , Zhu Yongliang
Published: April 2024

When ClO2 is exposed to heat, light, organic matter, or other environments that promote oxidation, it can rapidly decompose and can even cause an explosion; therefore, its physical and chemical decomposition has a wide range of implications. Herein, density functional theory is used to examine the adsorption of ClO2, HCl, HClO, and Cl2 on single‐vacancy‐, double‐vacancy‐, and Stone–Wales‐defected graphene and metal (Fe or Au)‐doped graphene to verify their effects on the adsorption of the target gases. Specifically, the adsorption energy, charge transfer, density of states, and charge density differences in the adsorption systems are investigated. The results indicate that the target gases are strongly adsorbed on metal‐doped graphene, particularly when doped with Fe. In contrast, the interactions between defective graphene and the adsorbed gases are weaker. However, single‐vacancy‐defected graphene also has better performance for the adsorption of target gases. This study provides a theoretical basis for the development of sensitive gas sensors for ClO2 and its decomposition products and is expected to guide further research on modified graphene‐based gas sensors.
Dynamical study of three African Easterly Waves in September 2021
Authors: Jonville Tanguy , Flamant Cyrille , Lavaysse Christophe
Published: April 2024

Three convectively active African easterly waves (AEWs) that propagated south of the African easterly jet were observed over the northeast Atlantic Ocean in September 2021. Their evolution is studied using a suite of theoretical frameworks, as well as the European Centre for Medium‐range Weather Forecast reanalyses and satellite‐derived brightness temperature observations. The environment of these AEWs was sampled during the Cloud–Atmospheric Dynamics–Dust Interactions in West Africa campaign near Cape Verde with the goal to assess their potential for developing into tropical cyclones. We highlight the processes that inhibited the development of the first AEW (which evolved into tropical disturbance Pierre‐Henri) and that played a role in the development of the later two into tropical storms Rose and Peter on September 19, 2021. The three AEWs developed a so‐called “marsupial protective” pouch. For Peter and Rose, the pouch was associated with a vertically aligned vortex at low levels and efficiently protected the convective systems inside from dry and dusty air intrusion. The development of this low‐level vortex is associated with an interaction with the monsoon trough for Rose and with a vorticity center associated with a wave propagating north of the African easterly jet (AEJ) in the case of Peter. The presence of a dust flux toward the convective core near the surface is highlighted for Rose and Peter in spite of the presence of the protective marsupial pouch. On the other hand, Pierre‐Henri interacted positively with both the monsoon trough and an AEW north of the AEJ but failed to develop into a tropical cyclone. The wave north of the AEJ brought Saharan air layer air masses inside the pouch that led to a drying of the circulation that may explain the decrease in convective activity.
Iterative distributed model predictive control for nonlinear systems with coupled non‐convex constraints and costs
Authors: Wu Jinxian , Dai Li , Xia Yuanqing
Published: April 2024

This paper proposes a distributed model predictive control (DMPC) algorithm for dynamic decoupled discrete‐time nonlinear systems subject to nonlinear (maybe non‐convex) coupled constraints and costs. Solving the resulting nonlinear optimal control problem (OCP) using a DMPC algorithm that is fully distributed, termination‐flexible, and recursively feasible for nonlinear systems with coupled constraints and costs remains an open problem. To address this, we propose a fully distributed and globally convergence‐guaranteed framework called inexact distributed sequential quadratic programming (IDSQP) for solving the OCP at each time step. Specifically, the proposed IDSQP framework has the following advantages: (i) it uses a distributed dual fast gradient approach for solving inner quadratic programming problems, enabling fully distributed execution; (ii) it can handle the adverse effects of inexact (insufficient) calculation of each internal quadratic programming problem caused by early termination of iterations, thereby saving computational time; and (iii) it employs distributed globalization techniques to eliminate the need for an initial guess of the solution. Under reasonable assumptions, the proposed DMPC algorithm ensures the recursive feasibility and stability of the entire closed‐loop system. We conduct simulation experiments on multi‐agent formation control with non‐convex collision avoidance constraints and compare the results against several benchmarks to verify the performance of the proposed DMPC method.
Not the only novice in the room: Partnerships and belongingness in a research immersion program
Authors: Ayers Katherine Ann , Pennella Robyn Ann , Mohorn‐Mintah Olayinka , Jasper Summer Jane , Nordstrom Susan Naomi
Published: April 2024

Lack of access to STEMM mentors has been identified as a critical barrier to biomedical research careers, leading to a lack of diversity in this field. To address such a barrier, the National Institutes of Health invested funds to support institutions in developing research immersion programs to provide “underrepresented” students with mentored research experiences. While providing access and opportunity for research experiences is an important equity endeavor, a focus solely on broadening participation neglects the role of institutions in perpetuating hegemonic views of science. Institutions often fail to recognize how entanglements of affect and emotion shape youth experiences in these programs and work to (de)legitimize their sense of belonging in science and perpetuate the notion of science as for an exclusive few. In this paper, we describe findings from a project aimed at understanding the entanglement of emotion and affect in a research immersion program and how these entanglements shaped participants' sense of belongingness in the program and research more broadly. Drawing on a poststructural feminist framework, we come to understand how individual histories and emotional experiences with racial and gender stereotypes work at the meta‐affective level to contract feelings of belongingness in science for students.
Self‐Powered Water Splitting of Ni3FeN@Fe24N10 Bifunctional Catalyst Improved Catalytic Activity and Durability by Forming Fe24N10 on Catalyst Surface via the Kirkendall Effect
Authors: Jeong Dong In , Kang Donghyeon , Kang Bong Kyun , Lee Ui Young , Suh In‐Yong , Kim Yeseul , Weon Byung Mook , Kim Sang‐Woo , Yoon Dae Ho
Published: April 2024

Highly efficient water splitting electrocatalyst for producing hydrogen as a renewable energy source offers potential to achieve net‐zero. However, it has significant challenges in using transition metal electrocatalysts as alternatives to noble metals due to their low efficiency and durability, furthermore, the reliance on electricity generation for electrocatalysts from fossil fuels leads to unavoidable carbon emissions. Here, a highly efficient self‐powered water splitting system integrated is designed with triboelectric nanogenerator (TENG) and Ni3FeN@Fe24N10 catalyst with improved catalytic activity and durability. First, the durability of the Ni3FeN catalyst is improved by forming N, P carbon shell using melamine, polyetherimide, and phytic acid. The catalyst activity is improved by generating Fe24N10 in the carbon shell through the Kirkendall effect. The synthesized Ni3FeN@Fe24N10 catalyst exhibited excellent bifunctional catalytic activity (ηOER = 261.8 mV and ηHER = 151.8 mV) and remarkable stability (91.7% in OER and 90.5% in HER) in 1 m KOH. Furthermore, to achieve ecofriendly electricity generation, a rotation‐mode TENG that sustainably generate high‐performance is realized using butylated melamine formaldehyde. As a result, H2 is successfully generated using the integrated system composed of the designed TENG and catalyst. The finding provides a promising approach for energy generation to achieve net‐zero.
Pushing the Limits of Heat Conduction in Covalent Organic Frameworks Through High‐Throughput Screening of Their Thermal Conductivity
Authors: Thakur Sandip , Giri Ashutosh
Published: April 2024

Tailor‐made materials featuring large tunability in their thermal transport properties are highly sought‐after for diverse applications. However, achieving `user‐defined’ thermal transport in a single class of material system with tunability across a wide range of thermal conductivity values requires a thorough understanding of the structure‐property relationships, which has proven to be challenging. Herein, large‐scale computational screening of covalent organic frameworks (COFs) for thermal conductivity is performed, providing a comprehensive understanding of their structure‐property relationships by leveraging systematic atomistic simulations of 10,750 COFs with 651 distinct organic linkers. Through the data‐driven approach, it is shown that by strategic modulation of their chemical and structural features, the thermal conductivity can be tuned from ultralow (≈0.02 W m−1 K−1) to exceptionally high (≈50 W m−1 K−1) values. It is revealed that achieving high thermal conductivity in COFs requires their assembly through carbon–carbon linkages with densities greater than 500 kg m−3, nominal void fractions (in the range of ≈0.6–0.9) and highly aligned polymeric chains along the heat flow direction. Following these criteria, it is shown that these flexible polymeric materials can possess exceptionally high thermal conductivities, on par with several fully dense inorganic materials. As such, the work reveals that COFs mark a new regime of materials design that combines high thermal conductivities with low densities.
Product and service quality risks: A survey about evolution and application in different business domains to facilitate quality engineering
Authors: Poth Alexander
Published: April 2024

Products and services are developed to realize chances on the market. Often, development teams are focusing primarily on the potential chances rather than on the corresponding risks of new products and services. However, it is possible to integrate the product and service quality risks early into the development procedures for a balanced and holistic view. The integration enables systematic mitigation and quality assurance actions to handle the risks. The article analyzes the literature related to quality risk approaches, identifies mature and generally applicable product and service risk approaches, and gives selected approach examples about its methodical evolution and how it can be integrated into the development procedures including soft‐skills development such as employee awareness and systematical training within organizations. A case study in the Group IT of the Volkswagen AG is discussed.
Assessing the viability of virtual structured democratic dialogue
Authors: Laouris Yiannis , Metcalf Gary
Published: April 2024

The paper examines the impact of virtual rendering of the Structured Democratic Dialogue (SDD) process. The authors discuss the implications of implementing each process stage virtually and suggest necessary adaptations to the relevant practices. They provide recommendations for improving the overall quality of online sessions and propose qualitative and quantitative indicators that can be used to compare and evaluate face‐to‐face and hybrid or virtual implementations. Pertinent indicators include financial cost, completion time, cost of required resources, number of factors generated, Spreadthink, extent, depth and quality of discussions during clustering and mapping stages, number of dimensions identified, number of factors included in the influence map, number of connections in the influence tree, situational complexity indices and degree of agreement on how to move forward. The authors propose that further research and additional case studies can help systems scientists and practitioners converge on reliable and validated criteria and metrics to allow solid assessment of possible quality loss associated with rendering each stage of the SDD process virtual.
Answering Temporal Conjunctive Queries over Description Logic Ontologies for Situation Recognition in Complex Operational Domains
Authors: Westhofen Lukas , Neurohr Christian , Jung Jean Christoph , Neider Daniel
Published: April 2024

For developing safe automated systems, recognizing safety-critical situations in data from their complex operational domain is imperative. This capability is, for example, essential when evaluating the system’s conformance to specified requirements in test run data. The requirements involve a temporal dimension, as the system operates over time. Moreover, the generated data are usually relational and require additional background knowledge about the domain for correctly recognizing the situation. This fact makes propositional temporal logics, an established tool, unsuitable for the task. We address this issue by developing a tailored temporal logic to query for situations in relational data over complex domains. Our language combines mission-time linear temporal logic with conjunctive queries to access time-stamped data with background knowledge formulated in an expressive description logic. Currently, however, no tools exist for answering queries in such settings. We hence also contribute an implementation in the logic reasoner Openllet, leveraging the efficacy of well-established conjunctive query answering. Moreover, we present a benchmark generator in the setting of automated driving and demonstrate that our tool performs well when tasked with recognizing safety-critical situations in road traffic.
SootUp: A Redesign of the Soot Static Analysis Framework
Authors: Karakaya Kadiray , Schott Stefan , Klauke Jonas , Bodden Eric , Schmidt Markus , Luo Linghui , He Dongjie
Published: April 2024

Since its inception two decades ago, Soot has become one of the most widely used open-source static analysis frameworks. Over time it has been extended with the contributions of countless researchers. Yet, at the same time, the requirements for Soot have changed over the years and become increasingly at odds with some of the major design decisions that underlie it. In this work, we thus present SootUp, a complete reimplementation of Soot that seeks to fulfill these requirements with a novel design, while at the same time keeping elements that Soot users have grown accustomed to.
Explainable Online Monitoring of Metric First-Order Temporal Logic
Authors: Lima Leonardo , Huerta y Munive Jonathan Julián , Traytel Dmitriy
Published: April 2024

Metric first-order temporal logic (MFOTL) is an expressive formalism for specifying temporal and data-dependent constraints on streams of time-stamped, data-carrying events. It serves as the specification language of several runtime monitors. These monitors input an MFOTL formula and an event stream prefix and output satisfying assignments to the formula’s free variables. For complex formulas, it may be unclear why a certain assignment is output. We propose an approach that accompanies assignments with detailed explanations, in the form of proof trees. We develop a new monitor that outputs such explanations. Our tool incorporates a formally verified checker that certifies the explanations and a visualization that allows users to interactively explore and understand the outputs.
Automate where Automation Fails: Proof Strategies for Frama-C/WP
Authors: Correnson Loïc , Blanchard Allan , Djoudi Adel , Kosmatov Nikolai
Published: April 2024

Modern deductive verification tools succeed in automatically proving the great majority of program annotations thanks in particular to constantly evolving SMT solvers they rely on. The remaining proof goals still require interactively created proof scripts. This tool demo paper presents a new solution for an automatic creation of proof scripts in /, a popular deductive verifier for C programs. The verification engineer defines a proof strategy describing several initial proof steps, from which proof scripts are automatically generated and applied. Our experiments on a large real-life industrial project confirm that the new proof strategy engine strongly facilitates the verification process by automating the creation of proof scripts, thus increasing the potential of industrial applications of deductive verification on large code bases.
Search for hidden neutrinos at the European Spallation Source: the SHiNESS experiment
Authors:   The SHiNESS experiment, Soleti Stefano Roberto , Coloma Pilar , Gómez Cadenas Juan José , Cabrera Anatael
Published: April 2024

Abstract

The upcoming European Spallation Source (ESS) will soon provide the most intense neutrino source in the world. We propose the Search for Hidden Neutrinos at the ESS (SHiNESS) experiment, highlighting its unique opportunities to search for the existence of sterile neutrinos across a wide range of scales: anomalous oscillations at short baselines; non-unitarity mixing in the active neutrino sector; or an excess of events with multiple leptons in the final state, produced in the decay of heavy neutrinos. The baseline design of the detector comprises an active volume filled with 42 ton of liquid scintillator, located 25 m far from the ESS beam target. We show that SHiNESS will be able to considerably improve current global limits for the three cases outlined above. Although in this work we focus on new physics in the neutrino sector, the proposed setup may also be used to search for signals from weakly interacting particles in a broader context.
Polarised cross sections for vector boson production with Sherpa
Authors: Hoppe Mareen , Schönherr Marek , Siegert Frank
Published: April 2024

Abstract

Measurements of vector boson polarisation in vector boson production processes offer a powerful probe of the electroweak symmetry breaking mechanism, scrutinising the Standard Model and new physics scenarios alike. Since massive vector bosons can only be observed as intermediate particles, polarised cross section templates from simulation are necessary to extract their polarisation from measurable unpolarised distributions. In this work we present an extension of the Sherpa Monte-Carlo event generator allowing the simulation of polarised cross sections for vector boson production processes. Based on the narrow-width approximation, polarised cross sections of all possible polarisation combinations for an arbitrary number of intermediate vector bosons can be simulated in a single simulation run. In addition, it is possible to directly predict the interference between different intermediate polarisation states, and various differing polarisation definitions can be studied simultaneously. Besides the simulation of polarised cross sections at fixed LO and LO+PS accuracy as well as in multijet-merged calculations, we also present parton-shower-matched polarised cross sections with approximate NLO QCD corrections in the vector boson production processes. We demonstrate that the differences of this approximation to full NLO QCD predictions are small and it thus opens up the possibility for fully-simulated calculations at the hadron level including polarisation information and higher-order QCD effects for the first time.
On the IR divergences in de Sitter space: loops, resummation and the semi-classical wavefunction
Authors: Céspedes Sebastián , Davis Anne-Christine , Wang Dong-Gang
Published: April 2024

Abstract

In this paper, we revisit the infrared (IR) divergences in de Sitter (dS) space using the wavefunction method, and explicitly explore how the resummation of higher-order loops leads to the stochastic formalism. In light of recent developments of the cosmological bootstrap, we track the behaviour of these nontrivial IR effects from perturbation theory to the non-perturbative regime. Specifically, we first examine the perturbative computation of wavefunction coefficients, and show that there is a clear distinction between classical components from tree-level diagrams and quantum ones from loop processes. Cosmological correlators at loop level receive contributions from tree-level wavefunction coefficients, which we dub classical loops. This distinction significantly simplifies the analysis of loop-level IR divergences, as we find the leading contributions always come from these classical loops. Then we compare with correlators from the perturbative stochastic computation, and find the results there are essentially the ones from classical loops, while quantum loops are only present as subleading corrections. This demonstrates that the leading IR effects are contained in the semi-classical wavefunction which is a resummation of all the tree-level diagrams. With this insight, we go beyond perturbation theory and present a new derivation of the stochastic formalism using the saddle-point approximation. We show that the Fokker-Planck equation follows as a consequence of two effects: the drift from the Schrödinger equation that describes the bulk time evolution, and the diffusion from the Polchinski’s equation which corresponds to the exact renormalization group flow of the coarse-grained theory on the boundary. Our analysis highlights the precise and simple link between the stochastic formalism and the semi-classical wavefunction.
Zero-bin subtraction and the qT spectrum beyond leading power
Authors: Ferrera Giancarlo , Ju Wan-Li , Schönherr Marek
Published: April 2024

Abstract

In this paper, we present an algorithm to construct the qT distribution at NLO accuracy to arbitrary power precision, including the assembly of suitable zero-bin subtrahends, in a mathematically well-defined way for a generic choice of rapidity-divergence regularisation prescription. In its derivation, we divide the phase space into two sectors, the interior of the integration domain as well as the integration boundary, which we include here for the first time. To demonstrate the applicability and usefulness of our algorithm, we calculate the N2LP corrections for Higgs hadroproduction for the first time. We observe that our approximate N2LP-accurate qT spectra replicate the asymptotic behaviour of the full QCD calculation to a much better degree than the previously available results, both within the qT → 0 limit and in the large-qT domain for all the involved partonic processes. While playing a minor role at larger transverse momenta, we show that the newly incorporated boundary contribution plays a vital role in the qT → 0 limit, where any subleading power accuracy would be lost without them. In particular, our N2LP-accurate qT expansion can approximate the exact qT distribution up to qT ≈ 30 GeV at the percent level for rapidities |YH| ≲ 3.
Covariant action for self-dual p-form gauge fields in general spacetimes
Authors: Hull C.M.
Published: April 2024

Abstract

Sen’s action for a p-form gauge field with self-dual field strength coupled to a spacetime metric g involves an explicit Minkowski metric and the presence of this raises questions as to whether the action is coordinate independent and whether it can be used on a general spacetime manifold. A natural generalisation of Sen’s action is presented in which the Minkowski metric is replaced by a second metric $$\overline{g }$$ on spacetime. The theory is covariant and can be formulated on any spacetime. The theory describes a physical sector, consisting of the chiral p-form gauge field coupled to the dynamical metric g, plus a shadow sector consisting of a second chiral p-form and the second metric $$\overline{g }$$. The fields in this shadow sector only couple to each other and have no interactions with the physical sector, so that they decouple from the physical sector. The resulting theory is covariant and can be formulated on any spacetime. Explicit expressions are found for the interactions and extensions to include interactions with other physical fields or higher-derivative field equations are given. A spacetime with two metrics has some interesting geometry and some of this is explored here and used in the construction of the interactions. The action has two diffeomorphism-like symmetries, one acting only on the physical sector and one acting only on the shadow sector, with the spacetime diffeomorphism symmetry arising as the diagonal subgroup. This allows a further generalisation in which $$\overline{g }$$ is not a tensor field but is instead a gauge field whose transition functions involve the usual coordinate transformation together with a shadow sector gauge transformation.
Evidence for cemented TKA and THA based on a comparison of international register data
Authors: Humez Martina , Kötter Katharina , Skripitz Ralf , Kühn Klaus-Dieter
Published: April 2024

Background

Hip and knee implants can either be fixed without cement, press-fit, or with bone cement. Real-world data from arthroplasty registers, as well as studies provide a broad database for the discussion of cemented versus uncemented arthroplasty procedures.

Objective

What does current evidence from international arthroplasty registries and meta-analyses recommend regarding cemented or cementless fixation of hip and knee implants?

Methods

A recommendation is generated by means of direct data comparison from the arthroplasty registries of eight countries (USA, Germany, Australia, UK, Sweden, Norway, New Zealand, Netherlands), the comparison of 22 review studies and meta-analyses based on registry data, as well as an evaluation of recommendations of healthcare systems from different nations. For this purpose, reviews and meta-analyses were selected where the results were statistically significant, as were the annual reports of the arthroplasty registries that were current at the time of writing.

Results

For knee arthroplasties, long survival time as well as lower risk of revision can be achieved with the support of cemented fixation with antibiotic-loaded bone cement. In patients aged 70 years and older, cemented fixation of hip stem implants significantly reduces risk of intraoperative or postoperative periprosthetic fracture (quadruple). This applies both to elective total hip arthroplasties and to hemiarthroplasty after femoral neck fractures. Antibiotic-loaded bone cement significantly (p = 0.041) reduces the risk of periprosthetic infection, especially in patients with femoral neck fractures.

Conclusion

Total knee replacement with antibiotic-loaded bone cement is well established internationally and is evidence-based. Registry data and meta-analyses recommend cemented fixation of the hip stem in older patients. In Germany, USA and Australia these evidence-based recommendations still must be transferred to daily practice.

Graphic abstract
Experimental and numerical optimization of deep drawing process parameters for square medical container design with the Taguchi method
Authors: Taşkın Aleyna , Dengiz Cengiz Görkem
Published: April 2024

Medical containers that sterilize surgical instruments are constantly needed in the healthcare industry. In line with this need, improvements in the fabrication of medical containers are important. Determining the design factors of medical containers fabricated by deep drawing saves time and cost. This study determined, the design factors of square medical containers and experimentally verified the deep drawing process modeled in Abaqus/Explicit finite element (FE) software. Taguchi statistical method was used to reduce the number of experiments. Blank holder force (BHF), punch radius (RP), die radius (RD), coefficient of friction between die and blank (µDB), coefficient of friction between punch and blank (µPB), coefficient of friction between holder and blank (µHB) as variable factors while selecting thickness reduction (TR) and maximum punch force (PF) were selected as output parameters. The effect of variable factors on the output parameters was determined by ANOVA analysis. As a result of the examinations, it was deter-mined that TR and PF increased as BHF, µDB and µHB values increased, whereas they decreased as RP and RD increased. On the other hand, it was determined that TR decreased and PF increased as µPB increased. In addition, the corners of the sheets were chamfered in different sizes to prevent the formation of ears in the containers. Finally, the appropriate chamfer size was determined by examining the sheet thicknesses.
Deep Learning for Automated Measurement of Total Cardiac Volume for Heart Transplantation Size Matching
Authors: Szugye Nicholas A. , Mahalingam Neeraja , Somasundaram Elanchezhian , Villa Chet , Segala Jim , Segala Michael , Zafar Farhan , Morales David L. S. , Moore Ryan A.
Published: April 2024

Total Cardiac Volume (TCV)-based size matching using Computed Tomography (CT) is a novel technique to compare donor and recipient heart size in pediatric heart transplant that may increase overall utilization of available grafts. TCV requires manual segmentation, which limits its widespread use due to time and specialized software and training needed for segmentation. This study aims to determine the accuracy of a Deep Learning (DL) approach using 3-dimensional Convolutional Neural Networks (3D-CNN) to calculate TCV, with the clinical aim of enabling fast and accurate TCV use at all transplant centers. Ground truth TCV was segmented on CT scans of subjects aged 0–30 years, identified retrospectively. Ground truth segmentation masks were used to train and test a custom 3D-CNN model consisting of a DenseNet architecture in combination with residual blocks of ResNet architecture. The model was trained on a cohort of 270 subjects and a validation cohort of 44 subjects (36 normal, 8 heart disease retained for model testing). The average Dice similarity coefficient of the validation cohort was 0.94 ± 0.03 (range 0.84–0.97). The mean absolute percent error of TCV estimation was 5.5%. There is no significant association between model accuracy and subject age, weight, or height. DL-TCV was on average more accurate for normal hearts than those listed for transplant (mean absolute percent error 4.5 ± 3.9 vs. 10.5 ± 8.5, p = 0.08). A deep learning-based 3D-CNN model can provide accurate automatic measurement of TCV from CT images. This initial study is limited as a single-center study, though future multicenter studies may enable generalizable and more accurate TCV measurement by inclusion of more diverse cardiac pathology and increasing the training data.