bluuebunny/crossref_metadata_2025_split huggingface dataset:
Do unions care about low‐paid workers? Evidence from Norway
Authors: Svarstad Elin 
Published: November 2023

AbstractOne of the core objectives of unions is to raise the wages of the lowest paid. Utilizing a panel of individual‐matched employee–employer data covering the Norwegian private sector in the period 2000–2014, I investigate how workplace union density is related to individual low‐pay risk. By exploiting changes in tax deductions for union members in Norway as a source of exogenous variation, a negative effect of increased union density on low‐pay risk is identified within jobs. The results further suggest that the effect of local bargaining power on individual low‐pay probability is larger among immigrants than among natives.
An ILP approach for tactical flight rescheduling during airport access mode disruptions
Authors: Scozzaro Geoffrey , Mancel Catherine , Delahaye Daniel , Feron Eric 
Published: November 2023

AbstractAirport access mode disruptions, such as a subway shutdown, threaten the whole passenger door‐to‐door journey. When such a disruptive event occurs, knowledge of passengers' delays would help the airport operation centre to decide if a departure flight should be delayed. This paper proposes a tactical flight rescheduling at an airport to minimise the number of stranded passengers while considering operational constraints. An integer linear programming formulation of the problem is presented. Constraints such as terminal capacities, maximal runway throughput, minimum turnaround time or minimum transfer time for connecting passengers are considered. An exact and heuristic resolution is proposed and compared to a study case around Paris‐Charles de Gaulle airport. The new schedule satisfies the operational constraints and reduces up to 60% of the number of stranded passengers with moderate deviation from the initial planning.
Machine learning‐based crystal structure prediction for high‐entropy oxide ceramics
Authors: Liu Jicheng , Wang Anzhe , Gao Pan , Bai Rui , Liu Junjie , Du Bin , Fang Cheng 
Published: November 2023

AbstractPredicting the crystal structure is essential to address the reliance on serendipity for facilitating the discovery and design of high‐performance high‐entropy oxides (HEOs). Here, three classic algorithms‐based machine learning models to predict the crystal structure of HEOs are successfully established and analyzed by combining five metrics, and the XGBoost classifier shows excellent accuracy and robustness with ACC and F1 scores up to 0.977 and 0.975, respectively. SHAP summary plot indicates that the anion‐to‐cation radius ratio (rA/rC) has the greatest impact on crystal structure, followed by difference in Pauling and Mulliken electronegativities (ΔχPauling and ΔχMulliken). It is noteworthy that the rA/rC, ΔχPauling, and ΔχMulliken lower than 0.35, 0.1, and 0.2, respectively, tend to lead to a fluorite crystal structure, whereas rock‐salt and spinel crystal structures are always formed. This work is expected to facilitate the discovery and design of HEOs with tailorable crystal structures and properties.
Executive compensation, internal control quality, and corporate social responsibility in China
Authors: Hu Junnan , Lin Xuan , Xie Feixue 
Published: November 2023

AbstractWe explore the relations among executive compensation, internal control quality (ICQ), and corporate social responsibility (CSR), focusing on improving the CSR outcomes of listed firms in China. Our findings are fourfold. First, we document that executive compensation and ICQ have a significant positive impact on CSR. Second, we find that executive compensation positively affects ICQ; hence, we identify ICQ as a channel that can further improve the impact of executive compensation on CSR. Third, we discover that the documented effects are stronger in state‐owned firms than in non‐state‐owned firms. Fourth, we observe that regulatory changes have both positive and negative impacts on CSR. Our findings are less vulnerable to endogeneity and have key implications for policy makers.
The ratio of M1 to M2 microglia in the striatum determines the severity of L‐Dopa‐induced dyskinesias
Authors: Rentsch Peggy , Egan Timothy , Kuriakose Andrea , Stayte Sandy , Vissel Bryce 
Published: November 2023

AbstractL‐Dopa, while treating motor symptoms of Parkinson's disease, can lead to debilitating L‐Dopa‐induced dyskinesias, limiting its use. To investigate the causative relationship between neuro‐inflammation and dyskinesias, we assessed if striatal M1 and M2 microglia numbers correlated with dyskinesia severity and whether the anti‐inflammatories, minocycline and indomethacin, reverse these numbers and mitigate against dyskinesia. In 6‐OHDA lesioned mice, we used stereology to assess numbers of striatal M1 and M2 microglia populations in non‐lesioned (naïve) and lesioned mice that either received no L‐Dopa (PD), remained non‐dyskinetic even after L‐Dopa (non‐LID) or became dyskinetic after L‐Dopa treatment (LID). We also assessed the effect of minocycline/indomethacin treatment on striatal M1 and M2 microglia and its anti‐dyskinetic potential via AIMs scoring. We report that L‐Dopa treatment leading to LIDs exacerbates activated microglia numbers beyond that associated with the PD state; the severity of LIDs is strongly correlated to the ratio of the striatal M1 to M2 microglial numbers; in non‐dyskinetic mice, there is no M1/M2 microglia ratio increase above that seen in PD mice; and reducing M1/M2 microglia ratio using anti‐inflammatories is anti‐dyskinetic. Parkinson's disease is associated with increased inflammation, but this is insufficient to underpin dyskinesia. Given that L‐Dopa‐treated non‐LID mice show the same ratio of M1/M2 microglia as PD mice that received no L‐Dopa, and, given minocycline/indomethacin reduces both the ratio of M1/M2 microglia and dyskinesia severity, our data suggest the increased microglial M1/M2 ratio that occurs following L‐Dopa treatment is a contributing cause of dyskinesias.
Human lower leg muscles grow asynchronously
Authors: Chow Brian V. Y. , Morgan Catherine , Rae Caroline , Warton David I. , Novak Iona , Davies Suzanne , Lancaster Ann , Popovic Gordana C. , Rizzo Rodrigo R. N. , Rizzo Claudia Y. , Kyriagis Maria , Herbert Robert D. , Bolsterlee Bart 
Published: November 2023

AbstractMuscle volume must increase substantially during childhood growth to generate the power required to propel the growing body. One unresolved but fundamental question about childhood muscle growth is whether muscles grow at equal rates; that is, if muscles grow in synchrony with each other. In this study, we used magnetic resonance imaging (MRI) and advances in artificial intelligence methods (deep learning) for medical image segmentation to investigate whether human lower leg muscles grow in synchrony. Muscle volumes were measured in 10 lower leg muscles in 208 typically developing children (eight infants aged less than 3 months and 200 children aged 5 to 15 years). We tested the hypothesis that human lower leg muscles grow synchronously by investigating whether the volume of individual lower leg muscles, expressed as a proportion of total lower leg muscle volume, remains constant with age. There were substantial age‐related changes in the relative volume of most muscles in both boys and girls (p < 0.001). This was most evident between birth and five years of age but was still evident after five years. The medial gastrocnemius and soleus muscles, the largest muscles in infancy, grew faster than other muscles in the first five years. The findings demonstrate that muscles in the human lower leg grow asynchronously. This finding may assist early detection of atypical growth and allow targeted muscle‐specific interventions to improve the quality of life, particularly for children with neuromotor conditions such as cerebral palsy.
The Global Impact of Brexit Uncertainty
Authors: HASSAN TAREK A. , HOLLANDER STEPHAN , LENT LAURENCE VAN , TAHOUN AHMED 
Published: November 2023

ABSTRACTWe propose a text‐based method for measuring the cross‐border propagation of large shocks at the firm level. We apply this method to estimate the expected costs, benefits, and risks of Brexit and find widespread reverberations in listed firms in 81 countries. International (i.e., non‐U.K.) firms most exposed to Brexit uncertainty (the second moment) lost significant market value and reduced hiring and investment. International firms also overwhelmingly expected negative first‐moment impacts from the U.K.'s decision to leave the European Union (EU), particularly related to regulation, asset prices, and labor market impacts of Brexit.
The Finite Element Method in Time for Multibody Dynamics
Authors: Bauchau Olivier A. 
Published: November 2023

Abstract
The generalized-α scheme has become the approach of choice for the time integration of the equations of motion of multibody systems. Despite its simplicity, this scheme presents drawbacks: the time-step size cannot be changed easily, making it difficult to implement time adaptivity, and the solution of periodic problems cannot be found easily. This paper explores an alternative approach based on the finite element method in time. The basic principles underpinning the approach are presented and both time-continuous and time-discontinuous approaches are investigated. Two types of Galerkin schemes will be presented here: the time-continuous and the time-discontinuous schemes. In the former, the displacement field is continuous across interelement boundaries, whereas discontinuities or “jumps” are allowed across interelement boundaries for the latter. Simple problems are treated to identify the best schemes. Families of schemes of various accuracies are presented. The first family, based on time-continuous elements, features schemes that do not present numerical dissipation. Asymptotic annihilation is achieved by the time-discontinuous elements that form the second family. The problem of kinematic constraints is treated within the framework of the finite element method in time. Special emphasis is devoted to the satisfaction of the kinematic constraints and their time derivative within a time element.
An Improved Fixture to Quantify Corrosion in Bolted Flanged Gasketed Joints
Authors: Hakimian Soroosh , Bouzid Abdel-Hakim , Hof Lucas A. 
Published: November 2023

Abstract
This study discusses the corrosion behavior of bolted flanged gasketed joint systems. A novel fixture is proposed to quantify the corrosion at the gasket–flange interface under service conditions. Due to the presence of crevices and potential differences between gaskets and flanges, corrosion widely occurs in such joints. Crevice corrosion and galvanic corrosion can create paths to leakage of the pressurized fluid and may cause catastrophic failure. Corrosion in bolted gasketed joints was investigated previously; however, the effects of the operating conditions were not reported. Operating conditions include fluid flow, pressure, pH, conductivity, temperature, and average gasket contact stress. This study starts by introducing a new experimental setup to examine the corrosion behavior of bolted flanged gasketed joints. The developed fixture consists of a pressurized bolted gasketed joint that enables real-time monitoring and recording of the corrosion parameters under the influence of service conditions. Second, potentiodynamic polarization testing is conducted to measure the corrosion rate and obtain data on the corrosion behavior of a pair of flange and gasket materials. These tests are performed using the novel setup that reproduces the behavior of industrial bolted flanged gasketed joint systems. It consists of a working electrode (flange material), a reference electrode (Ag/AgCl), and an auxiliary electrode (a stainless steel rod). Three types of graphite gaskets compressed in the fixture are subject to electrochemical corrosion tests with a 0.6 M NaCl solution. The morphology of the specimen's corroded surfaces is examined via confocal laser microscopy.
Design of a Novel Large-Stroke Compliant Constant-Torque Mechanism Based on Chained Beam-Constraint Model
Authors: Phan Thanh-Vu , Truong Van Men , Pham Huy-Tuan , Nguyen Van-Khien 
Published: November 2023

Abstract
This study addressed the development of a novel compliant constant-torque mechanism (CCTM) that utilizes Bezier curved beams to provide a large stroke in the constant-torque operating range. Previous CCTMs are limited by their working stroke, which reduces their applicability. The proposed mechanism is based on an analytical model using the chained beam-constraint model (CBCM), which captures the kinetostatic behavior of flexible segments. A genetic algorithm based on the CBCM was used to obtain the optimal structure, which was then verified through finite element analysis and experimental results. The results show that the proposed CCTM provides good flatness with a deviation of 3.7% and a large stroke of 80 deg in the constant-torque working range, while maintaining compactness. This novel CCTM has the potential to provide a simple and effective solution for torque regulators in various applications.
Seasonal trends in antidepressant prescribing, depression, anxiety and self-harm in adolescents and young adults: an open cohort study using English primary care data
Authors: Jack Ruth H , Joseph Rebecca M , Hollis Chris , Hippisley-Cox Julia , Butler Debbie , Waldram Dave , Coupland Carol 
Published: November 2023

BackgroundThere is an increasing demand for mental health services for young people, which may vary across the year.ObjectiveTo determine whether there are seasonal patterns in primary care antidepressant prescribing and mental health issues in adolescents and young adults.MethodsThis cohort study used anonymised electronic health records from general practices in England contributing to QResearch. It included 5 081 263 males and females aged 14–18 (adolescents), 19–23 and 24–28 years between 2006 and 2019. The incidence rates per 1000 person-years and the incidence rate ratios (IRRs) were calculated for the first records of a selective serotonin reuptake inhibitor (SSRI) prescription, depression, anxiety and self-harm. The IRRs were adjusted for year, region, deprivation, ethnic group and number of working days.FindingsThere was an increase in SSRI prescribing, depression and anxiety incidence in male and female adolescents in the autumn months (September–November) that was not seen in older age groups. The IRRs for SSRI prescribing for adolescents peaked in November (females: 1.75, 95% CI 1.67 to 1.83, p<0.001; males: 1.72, 95% CI 1.61 to 1.84, p<0.001, vs in January) and for depression (females: 1.29, 95% CI 1.25 to 1.33, p<0.001; males: 1.29, 95% CI 1.23 to 1.35, p<0.001). Anxiety peaked in November for females aged 14–18 years (1.17, 95% CI 1.13 to 1.22, p<0.001) and in September for males (1.19, 95% CI 1.12 to 1.27, p<0.001).ConclusionsThere were higher rates of antidepressant prescribing and consultations for depression and anxiety at the start of the school year among adolescents.Clinical implicationsSupport around mental health issues from general practitioners and others should be focused during autumn.
Assessment of ChatGPT’s performance on neurology written board examination questions
Authors: Chen Tse Chiang , Multala Evan , Kearns Patrick , Delashaw Johnny , Dumont Aaron , Maraganore Demetrius , Wang Arthur 
Published: November 2023

Background and objectivesChatGPT has shown promise in healthcare. To assess the utility of this novel tool in healthcare education, we evaluated ChatGPT’s performance in answering neurology board exam questions.MethodsNeurology board-style examination questions were accessed from BoardVitals, a commercial neurology question bank. ChatGPT was provided a full question prompt and multiple answer choices. First attempts and additional attempts up to three tries were given to ChatGPT to select the correct answer. A total of 560 questions (14 blocks of 40 questions) were used, although any image-based questions were disregarded due to ChatGPT’s inability to process visual input. The artificial intelligence (AI) answers were then compared with human user data provided by the question bank to gauge its performance.ResultsOut of 509 eligible questions over 14 question blocks, ChatGPT correctly answered 335 questions (65.8%) on the first attempt/iteration and 383 (75.3%) over three attempts/iterations, scoring at approximately the 26th and 50th percentiles, respectively. The highest performing subjects were pain (100%), epilepsy & seizures (85%) and genetic (82%) while the lowest performing subjects were imaging/diagnostic studies (27%), critical care (41%) and cranial nerves (48%).DiscussionThis study found that ChatGPT performed similarly to its human counterparts. The accuracy of the AI increased with multiple attempts and performance fell within the expected range of neurology resident learners. This study demonstrates ChatGPT’s potential in processing specialised medical information. Future studies would better define the scope to which AI would be able to integrate into medical decision making.
Tailoring follow-up endoscopy in patients with severe oesophagitis
Authors: Grant Rebecca K , Brindle William M , Taylor Caitlyn L , Rycroft Edward J , Oyewole Oluwadara , Morgan Sarah C , Watson Eleanor F , Anand Atul , McAvoy Norma C , Penman Ian D , Church Nicholas I , Trimble Kenneth C , Noble Colin L , Plevris John N , Masterton Gail S M , Kalla Rahul 
Published: November 2023

ObjectiveWe aimed to investigate the clinical utility of follow-up oesophagogastroduodenoscopy (OGD2) in patients with severe oesophagitis (Los Angeles grades C or D) through evaluating the yield of Barrett’s oesophagus (BO), cancer, dysplasia and strictures. Second, we aimed to determine if the Clinical Frailty Scale (CFS) may be used to identify patients to undergo OGD2s.Design/methodPatients in NHS Lothian with an index OGD (OGD1) diagnosis of severe oesophagitis between 1 January 2014 and 31 December 2015 were identified. Univariate analysis identified factors associated with grade. Patients were stratified by frailty and a diagnosis of stricture, cancer, dysplasia and BO.ResultsIn total 964 patients were diagnosed with severe oesophagitis, 61.7% grade C and 38.3% grade D. The diagnostic yield of new pathology at OGD2 was 13.2% (n=51), new strictures (2.3%), dysplasia (0.5%), cancer (0.3%) and BO (10.1%). A total of 140 patients had clinical frailty (CFS score ≥5), 88.6% of which were deceased at review (median of 76 months). In total 16.4% of frail patients underwent OGD2s and five new pathologies were diagnosed, none of which were significantly associated with grade. Among non-frail patients at OGD2, BO was the only pathology more common (p=0.010) in patients with grade D. Rates of cancer, dysplasia and strictures did not vary significantly between grades.ConclusionOur data demonstrate that OGD2s in patients with severe oesophagitis may be tailored according to clinical frailty and only be offered to non-frail patients. In non-frail patients OGD2s have similar pick-up rates of sinister pathology in both grades of severe oesophagitis.
Direct comparison of digital subtraction myelography versus CT myelography in lateral decubitus position: evaluation of diagnostic yield for cerebrospinal fluid-venous fistulas
Authors: Lützen Niklas , Demerath Theo , Würtemberger Urs , Belachew Nebiyat Filate , Barvulsky Aleman Enrique , Wolf Katharina , El Rahal Amir , Volz Florian , Fung Christian , Beck Jürgen , Urbach Horst 
Published: November 2023

BackgroundCerebrospinal fluid (CSF)-venous fistulas (CVFs) are increasingly identified as a cause of spontaneous intracranial hypotension (SIH). Lateral decubitus digital subtraction myelography (LD-DSM) and CT myelography (LD-CTM) are mainly used for detection, but the most sensitive method is yet unknown.ObjectiveTo compare LD-DSM with LD-CTM for diagnostic yield of CVFs.MethodsPatients with SIH diagnosed with a CVF between January 2021 and December 2022 in which the area of CVF(s) was covered by both diagnostic modalities were included. LD-CTM immediately followed LD-DSM without repositioning the spinal needle, and the second half of the contrast agent was injected at the CT scanner. Patients were awake or mildly sedated. Retrospectively, two neuroradiologists evaluated data independently and blinded for the presence of CVF.ResultsTwenty patients underwent a total of 27 combined LD-DSM/LD-CTM examinations (4/20 with follow-up and 3/20 with bilateral examinations). Both raters identified significantly more CVFs with LD-CTM than with LD-DSM (rater 1: 39 vs 9, P<0.001; rater 2: 42 vs 12, P<0.001). Inter-rater agreement was substantial for LD-DSM (κ=0.732) and LD-CTM (κ=0.655). The results remained significant after considering the senior rating for cases of disagreement (39 vs 10; P<0.001), and no CVF detected on LD-DSM was missed on LD-CTM.ConclusionIn this study, LD-CTM has a higher diagnostic yield for the detection of CVFs than LD-DSM and should supplement LD-DSM, but further studies are needed. LD-CTM can be easily acquired in awake or mildly sedated patients with the second half of contrast injected just before CT scanning, or it may be considered as a stand-alone investigation.
3DEmo: For Portrait Emotion Recognition with New Dataset
Authors: Liu Shao , Agaian Sos S. 
Published: November 2023

Emotional Expression Recognition (EER) and Facial Expression Recognition (FER) are active research areas in the affective computing field, which involves studying human emotion, recognition, and sentiment analysis. The main objective of this research is to develop algorithms that can accurately interpret and estimate human emotions from portrait images. The emotions depicted in a portrait can reflect various factors such as psychological and physiological states, the artist’s emotional responses, social and environmental aspects, and the period in which the painting was created. This task is challenging because (i) the portraits are often depicted in an artistic or stylized manner rather than realistically or naturally, (ii) the texture and color features obtained from natural faces and paintings differ, affecting the success rate of emotion recognition algorithms, and (iii) it is a new research area, where practically we do not have visual arts portrait facial emotion estimation models or datasets.
To address these challenges, we need a new class of tools and a database specifically tailored to analyze portrait images. This study aims to develop art portrait emotion recognition methods and create a new digital portrait dataset containing 927 images. The proposed model is based on (i) a 3-dimensional estimation of emotions learned by a deep neural network and (ii) a novel deep learning module (3DEmo) that could be easily integrated into existing FER models. To evaluate the effectiveness of the developed models, we also tested their robustness on a facial emotion recognition dataset. The extensive simulation results show that the presented approach outperforms established methods. We expect that this dataset and the developed new tools will encourage further research in recognizing emotions in portrait paintings and predicting artists’ emotions in the painting period based on their artwork.