bluuebunny/crossref_metadata_2025_split huggingface dataset:
SARS‐CoV‐2 infection as cause of in‐utero fetal death: regional multicenter cohort study
Authors: Nkobetchou M. , Leruez‐Ville M. , Guilleminot T. , Roux N. , Petrilli G. , Guimiot F. , Saint‐Frison M.‐H. , Deryabin I. , Ville Y. , Faure‐Bardon V. 
Published: July 2023

ABSTRACTObjectivePlacental infection with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) can lead to placental insufficiency and in‐utero fetal death (IUFD). The objective of this study was to confirm and quantify the extent to which fetoplacental infection with SARS‐CoV‐2 is a cause of fetal death.MethodsThis was a multicenter retrospective cohort study of fetal deaths that underwent postmortem examination between January 2020 and January 2022 in three fetal pathology units in Paris, France. All cases of IUFD and termination of pregnancy (TOP) occurring in 31 maternity hospitals in the Paris region undergo detailed placental pathological examination in these units. Databases were searched for cases of IUFD and TOP. Cases with fetal malformation or cytogenetic abnormality were excluded to avoid bias. We included cases of IUFD with a placental or undetermined cause and cases of TOP in the context of severe intrauterine growth restriction (IUGR). Placentas were sent to a single virology unit for reverse‐transcription polymerase chain reaction (RT‐PCR) testing by a single laboratory technician blinded to the initial postmortem examination report. Our primary endpoint was the proportion of positive placental SARS‐CoV‐2 RT‐PCR tests in the cohort.ResultsAmong 147 722 deliveries occurring over 2 years, 788 postmortem examinations for IUFD and TOP for severe IUGR were recorded, of which 462 (58.6%) were included. A total of 13/462 (2.8%) placentas tested positive for SARS‐CoV‐2 by RT‐PCR. Wild‐type virus and alpha and delta variants were identified. All positive cases had histological lesions consistent with placental dysfunction. There was a strong correlation between SARS‐CoV‐2 placentitis and the presence of chronic intervillositis and/or massive fibrin deposits in the placenta. When both lesion types were present, the specificity and negative predictive value for the diagnosis of placental SARS‐CoV‐2 infection were 0.99 (95% CI, 0.98–1.00) and 0.96 (95% CI, 0.94–0.98), respectively.ConclusionsAt the height of the SARS‐CoV‐2 pandemic, the cause of more than half of fetal deaths in the Paris area was determined by postmortem analysis to be of placental or undetermined origin. Of these cases, 2.8% were due to placental SARS‐CoV‐2 infection with a specific pattern of histological involvement. This study highlights the need for SARS‐CoV‐2 screening in stillbirth assessment. The impact of vaccination coverage remains to be established. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
Nuclear medicine radiomics in digestive system tumors: Concept, applications, challenges, and future perspectives
Authors: Huang Wenpeng , Tao Zihao , Younis Muhsin H. , Cai Weibo , Kang Lei 
Published: July 2023

AbstractRadiomics aims to develop novel biomarkers and provide relevant deeper subvisual information about pathology, immunophenotype, and tumor microenvironment. It uses automated or semiautomated quantitative analysis of high‐dimensional images to improve characterization, diagnosis, and prognosis. Recent years have seen a rapid increase in radiomics applications in nuclear medicine, leading to some promising research results in digestive system oncology, which have been driven by big data analysis and the development of artificial intelligence. Although radiomics advances one step further toward the non‐invasive precision medical analysis, it is still a step away from clinical application and faces many challenges. This review article summarizes the available literature on digestive system tumors regarding radiomics in nuclear medicine. First, we describe the workflow and steps involved in radiomics analysis. Subsequently, we discuss the progress in clinical application regarding the utilization of radiomics for distinguishing between various diseases and evaluating their prognosis, and demonstrate how radiomics advances this field. Finally, we offer our viewpoint on how the field can progress by addressing the challenges facing clinical implementation.
Real‐time rotor effective wind speed estimation based on actuator disc theory: Design and full‐scale experimental validation
Authors: Lio Alan W.H. , Meng Fanzhong , Larsen Gunner Chr. 
Published: July 2023

AbstractThe use of state estimation techniques offers a means of inferring rotor effective wind speed from standard measurements of wind turbines. Typical wind speed estimators rely upon a pre‐computed quasi‐steady aerodynamic mapping, which describes the relationship between pitch angle and tip‐speed ratio and the power coefficient. In practice, the static mapping does not capture the influence of turbine structural dynamics and atmospheric turbulence, inevitably resulting in poor performance of the wind speed estimation. In addition, the turbine aerodynamic properties might not be easily accessible. Thus, this paper presents a rotor effective wind speed estimation method that obviates the requirement for prior knowledge of turbine power coefficients. Specifically, the proposed method exploits a simple actuator disc model, where the aerodynamic power and thrust coefficients can be characterized in terms of axial induction factors. Based on this insight and standard turbine measurements, real‐time estimation of rotor effective wind speed and axial induction factors can then be achieved using a simplified turbine drive‐train model and an extended Kalman filter. In addition, the actuator disc model can be updated easily over time by calibrating solely two correction factors. Thus, the proposed algorithm presents an alternative for estimating the rotor effective wind speed, which is valuable for numerous applications, for example, LiDAR‐assisted control and coherence studies.
Periorbital rejuvenation in the clinic: A state‐of‐the‐art review
Authors: Russel Sarah M. , Clark J. Madison 
Published: July 2023

AbstractObjectiveTo provide an overview of the various treatment options available in the clinic to achieve periorbital rejuvenation.Data SourcesLiterature review and expert opinion.ConclusionsPeriorbital rejuvenation in the clinic can be accomplished through a variety of treatment modalities, including topical therapies, skin resurfacing, and fillers and injectables. Furthermore, some surgical approaches, such as upper blepharoplasties, ptosis, and brow lifts, can be performed in the clinic under local anesthesia with only mild oral sedation. However, the successful execution of such procedures depends on proper patient selection and maximizing patient comfort.
A new thin layer model for viscous flow between two nearby non‐static surfaces
Authors: Rodríguez José M. , Taboada‐Vázquez Raquel 
Published: July 2023

AbstractWe propose a two‐dimensional flow model of a viscous fluid between two close moving surfaces. We show, using a formal asymptotic expansion of the solution, that its asymptotic behavior, when the distance between the two surfaces tends to zero, is the same as that of the the Navier‐Stokes equations.The leading term of the formal asymptotic expansions of the solutions to the new model and Navier‐Stokes equations are solution of the same limit problem, and the type of the limit problem depends on the boundary conditions. If slip velocity boundary conditions are imposed on the upper and lower bound surfaces, the limit is a solution of a lubrication model, but if the tractions and friction forces are known on both bound surfaces, the limit is a solution of a thin fluid layer model.The model proposed has been obtained to be a valuable tool for computing viscous fluid flow between two nearby moving surfaces, without the need to decide a priori whether the flow is typical of a lubrication or a thin fluid layer problem, and without the enormous computational effort that would be required to solve the Navier‐Stokes equations in such a thin domain.
Energy based methods applied in mechanics by using the extended Noether's formalism
Authors: Abali Bilen Emek 
Published: July 2023

AbstractPhysical systems are modeled by field equations; these are coupled, partial differential equations in space and time. Field equations are often given by balance equations and constitutive equations, where the former are axiomatically given and the latter are thermodynamically derived. This approach is useful in thermomechanics and electromagnetism, yet challenges arise once we apply it in damage mechanics for generalized continua. For deriving governing equations, an alternative method is based on a variational framework known as the extended Noether's formalism. Its formal introduction relies on mathematical concepts limiting its use in applied mechanics as a field theory. In this work, we demonstrate the power of extended Noether's formalism by using tensor algebra and usual continuum mechanics nomenclature. We demonstrate derivation of field equations in damage mechanics for generalized continua, specifically in the case of strain gradient elasticity.
Gig Work, Algorithmic Technologies, and the Uncertain Future of Work
Authors: Duggan James , Jooss Stefan 
Published: July 2023

AbstractThroughout the last decade, the so-called gig economy has emerged as a disruptive and widely debated trend in the world of work. In this chapter, we trace the emergence of the gig economy from its inception during the global economic crisis to the present day where gig work arrangements span several sectors and face continuing scrutiny from critics. Specifically, we focus on the important role of algorithmic technologies in controlling the activities of gig workers and the subsequent challenges and controversies arising from the use of these new digital mechanisms. Finally, we identify the key implications arising from this new form of labour for workers, organisations, and regulatory bodies. In doing so, we explore a range of ongoing efforts to develop effective solutions for the various stakeholders involved.
Smart Technology in the Workplace: Threats and Opportunities for Trusting Employers
Authors: Zheng Xuchang , Schafheitle Simon Daniel , van der Werff Lisa 
Published: July 2023

AbstractIn this chapter, we discuss the implications of how smart technology is experienced in the workplace for employee trust. Focusing on the defining features of smart technology and how these influence social interaction, we explore how trends in the permeation of technology in workplaces can influence employee trust in their employers creating both threats and opportunities for trust in this relationship. Realising the benefits of technological development requires employees to trust the intentions and capability of their employers to manage smart technology in ways that protect employee interests. We highlight the features of smart technology that may hamper this trust and discuss how addressing concerns related to data privacy, situational normality, structural assurance, and employees’ participation in the process is crucial for protecting and building trust in the workplace.
Diversity and Inclusion
Authors: McCarthy Jean , Bosak Janine , Cleveland Jeanette N. , Parry Emma 
Published: July 2023

AbstractThe composition of the workforce, the pool of potential job applicants, and the diversity of the workplace are changing. In this chapter, we focus on the future of workplace diversity and inclusion of human workers, as well as how diversity and inclusion are likely to be affected by developments in technology (e.g., artificial intelligence and non-human presence at work). We argue that these technological developments are likely to have an impact on how organisations react to the increasing diversity of the workforce, and that they have the potential to either enhance or impede diversity and inclusion. We consider the implications of increasing diversity for organisations, such as changes to legal and economic structures, reimagining work-family balance and working time, the use of technology in reducing bias and, importantly, a focus on organisational cultures and individual attitudes that might promote a more diverse, inclusive and, indeed, sustainable workplace in the years ahead.
Building Information Modelling
Authors: Doukari Omar , Kassem Mohamad , Greenwood David 
Published: July 2023

AbstractFrom its origins as a computer-aided three-dimensional modelling tool, Building Information Modelling (BIM) has evolved to incorporate time scheduling, cost management, and ultimately an information management framework that has the potential to enhance decision-making throughout the whole life-cycle of built assets. This chapter summarises state-of-the-art BIM and its benefits. It then considers the particular characteristics of deep renovation projects, the challenges confronting their delivery, and the potential for using BIM to meet the challenges. This includes the application of Artificial Intelligence (AI) and Machine Learning (ML) to BIM models to optimise deep renovation project delivery. The prospects for this are encouraging, but further development work, including the creation of ontologies that are appropriate for renovation work, is still needed.
Big Data and Analytics in the Deep Renovation Life Cycle
Authors: Koukaras Paraskevas , Krinidis Stelios , Ioannidis Dimosthenis , Tjortjis Christos , Tzovaras Dimitrios 
Published: July 2023

AbstractThe rising volume of heterogeneous data accessible at various phases of the construction process has had a significant impact on the construction industry. The availability of data is especially advantageous in the context of deep renovation, where it may significantly accelerate the decision-making process for building stock retrofit. This chapter covers Big Data and analytics in the context of deep renovation and shows how Machine Learning and Artificial Intelligence have affected the various phases of the deep renovation life cycle. It presents a review of the literature on Big Data and deep renovation and discusses a series of use cases, applications, advantages, and benefits as well as challenges and barriers. Finally, Big Data and deep renovation prospects are discussed, including future potential developments and guidelines.
Higher Chern-Simons based on (2-)crossed modules
Authors: Song Danhua , Wu Mengyao , Wu Ke , Yang Jie 
Published: July 2023

Abstract
We present higher Chern-Simons theories based on (2-)crossed modules. We start from the generalized differential forms in Generalized Differential Calculus and define the corresponding generalized connections which consist of higher connections. Then we establish the generalized Chern-Simons forms to get the higher Chern-Simons actions. Finally, we develop the higher second Chern forms and Chern-Weil theorems.
The ABC of RPV: classification of R-parity violating signatures at the LHC for small couplings
Authors: Dreiner Herbi K. , Koay Yong Sheng , Köhler Dominik , Lozano Víctor Martín , Berlingen Javier Montejo , Nangia Saurabh , Strobbe Nadja 
Published: July 2023

Abstract
We perform a classification of all potential supersymmetric R-parity violating signatures at the LHC to address the question: are existing bounds on supersymmetric models robust, or are there still signatures not covered by existing searches, allowing LHC-scale supersymmetry to be hiding? We analyze all possible scenarios with one dominant RPV trilinear coupling at a time, allowing for arbitrary LSPs and mass spectra. We consider direct production of the LSP, as well as production via gauge-cascades, and find 6 different experimental signatures for the $$ LL\overline{E} $$
LL

E
¯

-case, 6 for the $$ LQ\overline{D} $$
LQ

D
¯

-case, and 5 for the $$ \overline{U} $$

U
¯

$$ \overline{D} $$

D
¯

$$ \overline{D} $$

D
¯

-case; together these provide complete coverage of the RPV-MSSM landscape. This set of signatures is confronted with the existing searches by ATLAS and CMS. We find all signatures have been covered at the LHC, although not at the sensitivity level needed to probe the direct production of all LSP types. For the case of a dominant $$ LL\overline{E} $$
LL

E
¯

-operator, we use CheckMATE to quantify the current lower bounds on the supersymmetric masses and find the limits to be comparable to or better than the R-parity conserving case. Our treatment can be easily extended to scenarios with more than one non-zero RPV coupling.
Probabilistic multi-modal depth estimation based on camera–LiDAR sensor fusion
Authors: Obando-Ceron Johan S. , Romero-Cano Victor , Monteiro Sildomar 
Published: July 2023

AbstractMulti-modal depth estimation is one of the key challenges for endowing autonomous machines with robust robotic perception capabilities. There have been outstanding advances in the development of uni-modal depth estimation techniques based on either monocular cameras, because of their rich resolution, or LiDAR sensors, due to the precise geometric data they provide. However, each of these suffers from some inherent drawbacks, such as high sensitivity to changes in illumination conditions in the case of cameras and limited resolution for the LiDARs. Sensor fusion can be used to combine the merits and compensate for the downsides of these two kinds of sensors. Nevertheless, current fusion methods work at a high level. They process the sensor data streams independently and combine the high-level estimates obtained for each sensor. In this paper, we tackle the problem at a low level, fusing the raw sensor streams, thus obtaining depth estimates which are both dense and precise, and can be used as a unified multi-modal data source for higher-level estimation problems. This work proposes a conditional random field model with multiple geometry and appearance potentials. It seamlessly represents the problem of estimating dense depth maps from camera and LiDAR data. The model can be optimized efficiently using the conjugate gradient squared algorithm. The proposed method was evaluated and compared with the state of the art using the commonly used KITTI benchmark dataset.
System engineering design approach and virtual assessment of a new charging arm concept for LHC robotic TIM
Authors: Zoppoli Andrea , Armentani Enrico , Buonocore Luca , Buonocore Sara , Di Giovannantonio Sergio , Di Castro Mario , Di Gironimo Giuseppe 
Published: July 2023

AbstractSystem engineering (SE) methods and principles are nowadays widely adopted in the product development processes, especially in the industrial sector, where saving production time and costs are primary goals. This work describes an application of a particular SE methodology, the V-model-based design, in which the system development lifecycle is divided on the basis of a graphical V-shaped scheme, called V-model. Following this approach, a new concept of charging arm for Robotic Train Inspection Monorail (TIM) of Large Hadron Collider (LHC) at CERN (Conseil Européen pour la Recherche Nucléaire) has been developed. The current charging arm version is affected by several issues and limits that have led to the necessity of a new solution. Starting from the first stages of functional requirements (FRs) definition and decomposition (left side of the “V”), a new concept has been implemented, in order to be tested for its verification and validation (right side of the “V”). As part of the principles of SE, the process has been based on virtual models of the product and on virtual simulations of its operation, rather than on the realization of time-consuming and expensive physical models and tests, even if a final physical prototype has also been built and some physical operative tests have also been carried out on it. These tests have showed that the new product appears to fulfill each one of its FRs and overcome the limits imposed by the previous version. The future commissioning and operative tests in the real operating condition and location shall definitely validate the new product.
Sex differences in acute delta-9-tetrahydrocannabinol (Δ9-THC) response and tolerance as a function of mouse strain
Authors: Lulek Courtney F. , Maulik Malabika , Mitra Swarup , Guindon Josée , Morgan Daniel J. , Henderson-Redmond Angela N. 
Published: July 2023

AbstractCannabinoids are increasingly used to alleviate pain; however, tolerance to their antinociceptive effects, including those of delta-9-tetrahydrocannabinol (Δ9-THC), may limit their therapeutic utility. With more women than men using medical cannabis for pain relief, it is crucial to understand how sex influences cannabinoid-mediated antinociception and tolerance. Though studies in rats consistently find females are more sensitive to the acute antinociceptive effects of cannabinoids, our work with mice consistently finds the converse. The present study examined whether our observed sex differences in Δ9-THC-induced antinociception and tolerance are consistent across multiple mouse strains or are strain-dependent. Male and female C57BL/6J (B6), DBA/2, AKR, and CBA/J mice were assessed for differences in acute Δ9-THC-induced antinociception and hypothermia prior to and following seven days of once-daily Δ9-THC administration. Consistent with our previous findings, male B6 mice were more sensitive to the acute antinociceptive effects of Δ9-THC than female littermates, an effect which dissipated with age. B6 males had decreased cannabinoid expression in the PAG compared to females. While DBA and CBA female mice showed increased Δ9-THC-antinociception compared to male littermates at 30 and 10 mg/kg Δ9-THC, respectively, these differences were less pronounced at higher doses, revealing that dose of Δ9-THC may also be important. Overall, CBA mice were more sensitive to Δ9-THC-induced antinociception while AKR mice were less responsive. These studies highlight the therapeutic potential of Δ9-THC in pain management and underscore the importance of considering not only Δ9-THC dose as a function of sex, but potentially genetic differences when evaluating their clinical utility.
Liquid chromatography–high-resolution tandem mass spectrometry of anatoxins, including new conjugates and reduction products
Authors: Beach Daniel G. , Zamlynny Lydia , MacArthur Melanie , Miles Christopher O. 
Published: July 2023

AbstractAnatoxins (ATXs) are a potent class of cyanobacterial neurotoxins for which only a handful of structural analogues have been well characterized. Here, we report the development of an LC–HRMS/MS method for the comprehensive detection of ATXs. Application of this method to samples of benthic cyanobacterial mats and laboratory cultures showed detection of several new ATXs. Many of these result from nucleophilic addition to the olefinic bond of the α,β-unsaturated ketone functional group of anatoxin-a (ATX) and homoanatoxin-a (hATX), analogous to the conjugation chemistry of microcystins, which contain similar α,β-unsaturated amide functionality. Conjugates with glutathione, γ-glutamylcysteine, methanethiol, ammonia, methanol and water were detected, as well as putative C-10 alcohol derivatives. Structural confirmation was obtained by simple and selective analytical-scale semisynthetic reactions starting from available ATX standards. Methanol, water and ammonia conjugates were found to result primarily from sample preparation. Reduction products were found to result from enzymatic reactions occurring primarily after cell lysis in laboratory cultures ofKamptonema formosumandCuspidothrix issatschenkoi. The relative contributions of the identified analogues to the anatoxin profiles in a set of 22 benthic-cyanobacterial-mat field samples were estimated, showing conjugates to account for up to 15% of total ATX peak area and 10-hydroxyanatoxins up to 38%. The developed methodology, new analogues and insight into the chemical and enzymatic reactivity of ATXs will enable a more comprehensive study of the class than possible previously.