bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection and quantification of breast arterial calcifications on mammograms: a deep learning approach
Authors: Mobini Nazanin , Codari Marina , Riva Francesca , Ienco Maria Giovanna , Capra Davide , Cozzi Andrea , Carriero Serena , Spinelli Diana , Trimboli Rubina Manuela , Baselli Giuseppe , Sardanelli Francesco
Published: May 2023

Objective

Breast arterial calcifications (BAC) are a sex-specific cardiovascular disease biomarker that might improve cardiovascular risk stratification in women. We implemented a deep convolutional neural network for automatic BAC detection and quantification.

Methods

In this retrospective study, four readers labelled four-view mammograms as BAC positive (BAC+) or BAC negative (BAC−) at image level. Starting from a pretrained VGG16 model, we trained a convolutional neural network to discriminate BAC+ and BAC− mammograms. Accuracy, F1 score, and area under the receiver operating characteristic curve (AUC-ROC) were used to assess the diagnostic performance. Predictions of calcified areas were generated using the generalized gradient-weighted class activation mapping (Grad-CAM++) method, and their correlation with manual measurement of BAC length in a subset of cases was assessed using Spearman ρ.

Results

A total 1493 women (198 BAC+) with a median age of 59 years (interquartile range 52–68) were included and partitioned in a training set of 410 cases (1640 views, 398 BAC+), validation set of 222 cases (888 views, 89 BAC+), and test set of 229 cases (916 views, 94 BAC+). The accuracy, F1 score, and AUC-ROC were 0.94, 0.86, and 0.98 in the training set; 0.96, 0.74, and 0.96 in the validation set; and 0.97, 0.80, and 0.95 in the test set, respectively. In 112 analyzed views, the Grad-CAM++ predictions displayed a strong correlation with BAC measured length (ρ = 0.88, p < 0.001).

Conclusion

Our model showed promising performances in BAC detection and in quantification of BAC burden, showing a strong correlation with manual measurements.

Clinical relevance statement

Integrating our model to clinical practice could improve BAC reporting without increasing clinical workload, facilitating large-scale studies on the impact of BAC as a biomarker of cardiovascular risk, raising awareness on women’s cardiovascular health, and leveraging mammographic screening.

Key Points

• We implemented a deep convolutional neural network (CNN) for BAC detection and quantification.

• Our CNN had an area under the receiving operator curve of 0.95 for BAC detection in the test set composed of 916 views, 94 of which were BAC+ .

• Furthermore, our CNN showed a strong correlation with manual BAC measurements (ρ = 0.88) in a set of 112 views.
Introduction of a breast apparent diffusion coefficient category system (ADC-B) derived from a large multicenter MRI database
Authors: Bickel Hubert , Clauser Paola , Pinker Katja , Helbich Thomas , Biondic Iva , Brkljacic Boris , Dietzel Matthias , Ivanac Gordana , Krug Barbara , Moschetta Marco , Neuhaus Victor , Preidler Klaus , Baltzer Pascal
Published: May 2023

Objectives

To develop an intuitive and generally applicable system for the reporting, assessment, and documentation of ADC to complement standard BI-RADS criteria.

Methods

This was a multicentric, retrospective analysis of 11 independently conducted institutional review board–approved studies from seven institutions performed between 2007 and 2019. Breast Apparent Diffusion coefficient (ADC-B) categories comprised ADC-B0 (ADC non-diagnostic), ADC-B1 (no enhancing lesion), and ADC-B2-5. The latter was defined by plotting ADC versus cumulative malignancy rates. Statistics comprised ANOVA with post hoc testing and ROC analysis. p values ≤ 0.05 were considered statistically significant.

Results

A total of 1625 patients (age: 55.9 years (± 13.8)) with 1736 pathologically verified breast lesions were included. The mean ADC (× 10−3 mm2/s) differed significantly between benign (1.45, SD .40) and malignant lesions (.95, SD .39), and between invasive (.92, SD .22) and in situ carcinomas (1.18, SD .30) (p < .001). The following ADC-B categories were identified: ADC-B0—ADC cannot be assessed; ADC-B1—no contrast-enhancing lesion; ADC-B2—ADC ≥ 1.9 (cumulative malignancy rate < 0.1%); ADC-B3—ADC 1.5 to < 1.9 (0.1–1.7%); ADC-B4—ADC 1.0 to < 1.5 (10–24.5%); and ADC-B5—ADC < 1.0 (> 24.5%). At the latter threshold, a positive predictive value of 95.8% (95% CI 0.94–0.97) for invasive versus non-invasive breast carcinomas was reached.

Conclusions

The breast apparent diffusion coefficient system (ADC-B) provides a simple and widely applicable categorization scheme for assessment, documentation, and reporting of apparent diffusion coefficient values in contrast-enhancing breast lesions on MRI.

Clinical relevance statement

The ADC-B system, based on diverse MRI examinations, is clinically relevant for stratifying breast cancer risk via apparent diffusion coefficient measurements, and complements BI-RADS for improved clinical decision-making and patient outcomes.

Key Points

• The breast apparent diffusion coefficient category system (ADC-B) is a simple tool for the assessment, documentation, and reporting of ADC values in contrast-enhancing breast lesions on MRI.

• The categories comprise ADC-B0 for non-diagnostic examinations, ADC-B1 for examinations without an enhancing lesion, and ADC-B2-5 for enhancing lesions with an increasing malignancy rate.

• The breast apparent diffusion coefficient category system may be used to complement BI-RADS in clinical decision-making.
Mach and Reynolds number effects on transonic buffet on the XRF-1 transport aircraft wing at flight Reynolds number
Authors: Waldmann Andreas , Ehrle Maximilian C. , Kleinert Johannes , Yorita Daisuke , Lutz Thorsten
Published: May 2023

This work provides an overview of aerodynamic data acquired in the European Transonic Windtunnel using an XRF-1 transport aircraft configuration both at cruise conditions and at the edges of the flight envelope. The goals and design of the wind tunnel test were described, highlighting the use of the cryogenic wind tunnel’s capability to isolate the effects of $$M_{\infty }$$

M
∞

, $${\text{Re}}_{\infty }$$

Re
∞

and the dynamic pressure q/E. The resulting dataset includes an aerodynamic baseline characterization of the full span model with vertical and horizontal tailplanes and without engine nacelles. The effects of different inflow conditions were studied using data from continuous polars, evaluating the changes in aeroelastic deformation which are proportional to q/E and the influence of $$M_{\infty }$$

M
∞

and $${\text{Re}}_{\infty }$$

Re
∞

on the shock position. Off-design data was analyzed at the lowest and highest measured Mach numbers of 0.84 and 0.90, respectively. Wing lower surface flow and underside shock motion was analyzed at negative angles of attack using $${{c}_{\text{p}}}$$

c
p

distribution and unsteady pressure transducer fluctuation data, identifying significant upstream displacement of the shock close to the leading edge. Wing upper-side flow and the shock motion near buffet onset and beyond was analyzed using unsteady pressure data from point transducers and unsteady pressure-sensitive paint (PSP) measurements. Buffet occurs at lower angles of attack at high Mach number, and without clearly defined lift break. Spectral contents at the acquired data points in the buffet range suggest broadband fluctuations at Strouhal numbers between 0.2 and 0.6, which is consistent with recent literature. The spanwise shock propagation velocities were determined independently via analysis of unsteady PSP and pressure transducers to be in the range between $$u_{\text{s}} / u_{\infty } = 0.24$$

u
s

/

u
∞

=
0.24

and 0.32, which is similarly in line with published datasets using other swept wing aircraft models.
Manipulation of moves in sequential contests
Authors: Protopappas Konstantinos
Published: May 2023

In two-player Tullock contests with endogenous timing of moves, the weak player moves early and the strong player follows. This order of moves is the third-best outcome for a contest organiser as it leads to a contest with lower aggregate effort compared to a contest where the players move in reverse order (first best) or simultaneously (second best). We propose that if the contest organiser—who does not knowex antewhich player is the strong and which is the weak one—offers a lower price (effort cost) to the player(s) who choose(s) to exert effort early, she can achieve a greater payoff by affecting the contestants’ sequence of moves. We show that there exists no price that generates the first-best outcome. However, there is a price (or a range of prices) that induces both players to move early and receive it, leading to the second-best outcome. We also discuss the case where both players move early but only one receives the low price, e.g., lobbying or Instagram “giveaway” contests.
E-ReMI: Extended Maximal Interaction Two-mode Clustering
Authors: Ahmed Zaheer , Cassese Alberto , van Breukelen Gerard , Schepers Jan
Published: May 2023

In this paper, we present E-ReMI, a new method for studying two-way interaction in row by column (i.e., two-mode) data. E-ReMI is based on a probabilistic two-mode clustering model that yields a two-mode partition of the data with maximal interaction between row and column clusters. The proposed model extends REMAXINT by allowing for unequal cluster sizes for the row clusters, thus introducing more flexibility in the model. In the manuscript, we use a conditional classification likelihood approach to derive the maximum likelihood estimates of the model parameters. We further introduce a test statistic for testing the null hypothesis of no interaction, discuss its properties and propose an algorithm to obtain its distribution under this null hypothesis. Free software to apply the methods described in this paper is developed in the R language. We assess the performance of the new method and compare it with competing methodologies through a simulation study. Finally, we present an application of the methodology using data from a study of person by situation interaction.
Paediatric subarachnoid haemorrhage and severe vasospasm secondary to traumatic pseudoaneurysm of a fenestrated vertebral artery: a case report and review of the literature
Authors: Kameda-Smith Michelle , James Greg , Seunarine Kiran , Rennie Adam , Robertson Fergus , Silva Adikarige Haritha Dulanka
Published: May 2023

Paediatric intracranial aneurysms are rare entities accounting for less than 5% of all age intracranial aneurysms. Traumatic aneurysms are more common in children and have an association with anatomical variations such as arterial fenestrations. Here, we present a case of a child initially presenting with traumatic subarachnoid haemorrhage who returned to baseline and was discharged home only to return within 2 weeks with diffuse subarachnoid and intraventricular re-haemorrhage. A dissecting aneurysm of a duplicated (fenestrated) V4 vertebral artery segment was identified as a rare cause of rebleeding. We describe a course complicated by severe vasospasm delaying aneurysm detection and treatment. Dissecting aneurysms in children should be considered in all cases of delayed post-traumatic cranial rebleeding, particularly where there is anomalous arterial anatomy.
Large diameter hemicraniectomy does not improve long-term outcome in malignant infarction
Authors: Lehrieder Dominik , Müller Hans-Peter , Kassubek Jan , Hecht Nils , Thomalla Götz , Michalski Dominik , Gattringer Thomas , Wartenberg Katja E. , Schultze-Amberger Jörg , Huttner Hagen , Kuramatsu Joji B. , Wunderlich Silke , Steiner Hans-Herbert , Weissenborn Karin , Heck Suzette , Günther Albrecht , Schneider Hauke , Poli Sven , Dohmen Christian , Woitzik Johannes , Jüttler Eric , Neugebauer Hermann ,   on behalf of the DESTINY-R (DEcompressive Surgery for the Treatment of malignant INfarction of the middle cerebral arterY - Registry) Study Group and IGNITE (Initiative of German NeuroIntensive Trial Engagement) Study Group
Published: May 2023

Introduction

In malignant cerebral infarction decompressive hemicraniectomy has demonstrated beneficial effects, but the optimum size of hemicraniectomy is still a matter of debate. Some surgeons prefer a large-sized hemicraniectomy with a diameter of more than 14 cm (HC > 14). We investigated whether this approach is associated with reduced mortality and an improved long-term functional outcome compared to a standard hemicraniectomy with a diameter of less than 14 cm (HC ≤ 14).

Methods

Patients from the DESTINY (DEcompressive Surgery for the Treatment of malignant INfarction of the middle cerebral arterY) registry who received hemicraniectomy were dichotomized according to the hemicraniectomy diameter (HC ≤ 14 cm vs. HC > 14 cm). The primary outcome was modified Rankin scale (mRS) score ≤ 4 after 12 months. Secondary outcomes were in-hospital mortality, mRS ≤ 3 and mortality after 12 months, and the rate of hemicraniectomy-related complications. The diameter of the hemicraniectomy was examined as an independent predictor of functional outcome in multivariable analyses.

Results

Among 130 patients (32.3% female, mean (SD) age 55 (11) years), the mean hemicraniectomy diameter was 13.6 cm. 42 patients (32.3%) had HC > 14. There were no significant differences in the primary outcome and mortality by size of hemicraniectomy. Rate of complications did not differ (HC ≤ 14 27.6% vs. HC > 14 36.6%, p = 0.302). Age and infarct volume but not hemicraniectomy diameter were associated with outcome in multivariable analyses.

Conclusion

In this post-hoc analysis, large hemicraniectomy was not associated with an improved outcome or lower mortality in unselected patients with malignant middle cerebral artery infarction. Randomized trials should further examine whether individual patients could benefit from a large-sized hemicraniectomy.

Clinical trial registration information

German Clinical Trials Register (URL: https://www.drks.de; Unique Identifier: DRKS00000624).
Artificial intelligence in retinal disease: clinical application, challenges, and future directions
Authors: Daich Varela Malena , Sen Sagnik , De Guimaraes Thales Antonio Cabral , Kabiri Nathaniel , Pontikos Nikolas , Balaskas Konstantinos , Michaelides Michel
Published: May 2023

Retinal diseases are a leading cause of blindness in developed countries, accounting for the largest share of visually impaired children, working-age adults (inherited retinal disease), and elderly individuals (age-related macular degeneration). These conditions need specialised clinicians to interpret multimodal retinal imaging, with diagnosis and intervention potentially delayed. With an increasing and ageing population, this is becoming a global health priority. One solution is the development of artificial intelligence (AI) software to facilitate rapid data processing. Herein, we review research offering decision support for the diagnosis, classification, monitoring, and treatment of retinal disease using AI. We have prioritised diabetic retinopathy, age-related macular degeneration, inherited retinal disease, and retinopathy of prematurity. There is cautious optimism that these algorithms will be integrated into routine clinical practice to facilitate access to vision-saving treatments, improve efficiency of healthcare systems, and assist clinicians in processing the ever-increasing volume of multimodal data, thereby also liberating time for doctor-patient interaction and co-development of personalised management plans.
Association of autoantibody levels with different stages of age-related macular degeneration (AMD): Results from the population-based Gutenberg Health Study (GHS)
Authors: Korb Christina A. , Lackner Karl J. , Wolters Dominik , Schuster Alexander K. , Nickels Stefan , Beutgen Vanessa M. , Münzel Thomas , Wild Philipp S. , Beutel Manfred E. , Schmidtmann Irene , Pfeiffer Norbert , Grus Franz H.
Published: May 2023

Purpose

Anti-retinal autoantibodies are assumed to be associated with age-related macular degeneration (AMD). To our knowledge, this is the first evaluation of autoantibodies in human sera of participants with different stages of AMD in a large population-based, observational cohort study in Germany.

Methods

The Gutenberg Health Study (GHS) is a population-based, observational cohort study in Germany, including 15,010 participants aged between 35 and 74. Amongst others, non-mydriatic fundus photography (Visucam PRO NM™, Carl Zeiss Meditec AG, Jena, Germany) was performed. Fundus images of the first 5000 participants were graded based on the Rotterdam Eye Study classification. Sera of participants with AMD (n=541) and sera of age-matched participants without AMD (n=490) were analyzed by antigen-microarrays. Besides descriptive statistics, autoantibody-levels were compared by Mann-Whitney-U test and the associations of level of autoantibodies with AMD were calculated by logistic regression analysis. Likewise, possible associations of the autoantibodies and both clinical and laboratory parameters on AMD subjects were analyzed.

Results

Autoantibodies against transferrin (p<0.001) were significantly downregulated in participants with early AMD and soft, distinct drusen (≥63 μm) or pigmentary abnormalities only compared to Controls. Mitogen-activated protein kinase 3 (p=0.041), glutathione peroxidase 4 (p=0.048), clusterin (p=0.045), lysozyme (p=0.19), protein kinase C substrate 80K-H (p=0.02), heat shock 70 kDa protein 1A (p=0.04) and insulin (p=0.018) show a trend between Control and participants with early AMD and soft, distinct drusen (≥63 μm) or pigmentary abnormalities only.

Conclusions

This study contributes to a growing knowledge of autoantibodies in association with different AMD stages compared to controls in the context of a large population-based study in Germany. Especially autoantibodies against inflammatory proteins were downregulated in participants with early AMD and soft, distinct drusen (≥63 μm) or pigmentary abnormalities only.
Incidence of shoulder disorders in a cohort of healthcare workers from 2009 to 2020
Authors: Iavernig Thomas , Zanette Marta , Miani Andrea , Ronchese Federico , Larese Filon Francesca
Published: May 2023

Purpose

To estimate the incidence of shoulder disorders in a cohort of Health Care Workers (HCWs).

Methods

4406 workers employed from 2009 to 2020, were included in the study. Occupational risk factors and jobs were assessed according to working history. Incident cases were defined in case of shoulder pain associated with functional limitations during the medical examination. The Cox regression model was used to calculate the Hazard Ratio (HR) for different work activities, adjusted for age, sex, body mass index, and previous musculoskeletal injuries, using clerks as the reference category.

Results

The incidence rates of shoulder musculoskeletal disorder for men and women were 13.1 for 1000 person-years (CI 95% 10.6–16.3) and 20.1 for 1000 person-years (CI 95% 17.8–22.6) respectively. The adjusted HR was significantly increased with age (1.06, CI 95% 1.05–1.07), outpatient health activities (2.82, CI 95% 1.89–4.219), and wards health activity (2.37, CI 95% 1.68–3.33).

Conclusion

HCWs with high biomechanical risk such as nurses and healthcare assistants had a higher incidence of shoulder disorders. Actions are needed for better prevention in health care assistance.
Effects of COVID-19 pandemic on pediatric tuberculosis: decrease in notification rates and increase in clinical severity
Authors: Lo Vecchio Andrea , Scarano Sara Maria , Amato Chiara , Spagnuolo Maria Immacolata , Bruzzese Eugenia , Guarino Alfredo
Published: May 2023

The outbreak of COVID-19 resulted in a decrease in tuberculosis notification rates globally. We compared tuberculosis incidence rates and disease severity in children seen in our centre prior and during COVID-19 pandemic.We performed a cohort study enrolling children aged under 18 years who received a diagnosis of tuberculosis (January 1st, 2010-December 31st, 2021) at our Pediatric Infectious Diseases Unit. Disease severity was evaluated based on: the classification proposed by Wiseman et al., smear positivity, presence of symptoms at presentation, lung cavitation, extrapulmonary disease, respiratory failure and need for intensive care support. Overall, 168 children (50.6% female, median age 69 months, IQR 95.4) received a diagnosis of tuberculosis, 156 (92.8%) between 2010–2019, before COVID-19 outbreak, and 12 (7.2%) between 2020–2021, during the pandemic. The annual tuberculosis notification rate dropped by 73% in 2021 (0.38/100000, 95%CI 0.1–0.96) compared with 2019 (1.46/100000, 95%CI 0.84–2.37). Compared to the pre-pandemic period, the proportion of children classified as severe was higher in 2020–2021 (5, 41.6% vs 23, 15.7%, p = 0.006) with a higher rate of respiratory failure (2, 16.7%, vs 4, 2.6%, p = 0.01) and an increased need for intensive care support (1, 8.3% vs 1, 0.6%, p = 0.01).

   Conclusion: During COVID-19 pandemic we observed a reduction in tuberculosis notification rate in pediatric population and a significant increase in disease severity. This scenario may be the consequence of a delay in diagnosis and an underreporting of cases, rather than the effect of a reduced transmission of tuberculosis. Children reached health-care services only in the need of urgent medical attention.

What is Known:• COVID-19 pandemic had a huge impact on national health care systems, resulting in a reduction of access to medical care.

What is New:• In Campania Region, Italy, a low tuberculosis incidence country, we witnessed a 75% reduction in tuberculosis notification rate during pandemic. In parallel we demonstrated a significant increase in disease severity, suggesting that the reduction in notification rate may be attributed to an underreporting of cases and consequential diagnostic delay, rather than a reduced transmission of infection.
Psychosocial distress in cancer patients undergoing radiotherapy: a prospective national cohort of 1042 patients in Germany
Authors: Fabian Alexander , Rühle Alexander , Domschikowski Justus , Trommer Maike , Wegen Simone , Becker Jan-Niklas , Wurschi Georg , Boeke Simon , Sonnhoff Mathias , Fink Christoph A. , Käsmann Lukas , Schneider Melanie , Bockelmann Elodie , Treppner Martin , Mehnert-Theuerkauf Anja , Krug David , Nicolay Nils H. ,   Young DEGRO Group
Published: May 2023

Purpose

Psychosocial distress is common among cancer patients in general, but those undergoing radiotherapy may face specific challenges. Therefore, we investigated the prevalence and risk factors for distress in a large national cohort.

Methods

We performed a secondary analysis of a multicenter prospective cross-sectional study which surveyed cancer patients at the end of a course of radiotherapy using a patient-reported questionnaire. Distress was measured with the distress thermometer (DT), using a cut-off of ≥ 5 points for clinically significant distress. Univariate analyses and multivariate multiple regression were used to assess associations of distress with patient characteristics. A two-sided p-value < 0.05 was considered statistically significant.

Results

Out of 2341 potentially eligible patients, 1075 participated in the study, of which 1042 completed the DT. The median age was 65 years and 49% (511/1042) of patients were female. The mean DT score was 5.2 (SD = 2.6). Clinically significant distress was reported by 63% (766/1042) of patients. Of the patient characteristics that were significantly associated with distress in the univariate analysis, a lower level of education, a higher degree of income loss, lower global quality of life, and a longer duration of radiotherapy in days remained significantly associated with higher distress in the multivariate analysis. Yet effect sizes of these associations were small.

Conclusion

Nearly two in three cancer patients undergoing radiotherapy reported clinically significant distress in a large multicenter cohort. While screening and interventions to reduce distress should be maintained and promoted, the identified risk factors may help to raise awareness in clinical practice.

Trial Registry identifier

DRKS: German Clinical Trial Registry identifier: DRKS00028784.
An image-based meso-scale model for the hygro-mechanical time-dependent analysis of concrete
Authors: Zhang Sen , Hamed Ehab , Song Chongmin
Published: May 2023

A new computational framework is developed in this paper for investigating the time-dependent behaviour of concrete including creep, shrinkage and cracking. The developed model aims to explain certain aspects of the time-dependent cracking and creep of concrete that cannot be captured using homogeneous models. The model is based on the scaled boundary finite element method, and it is coupled with a quadtree decomposition algorithm which converts digital images of concrete meso-structures into meshes. Concrete is treated as a two-phase composite which consists of elastic aggregates and mortar that is subjected to time-dependent deformation. The basic creep behaviour is treated as viscoelastic, which is modelled based on a rate-type rheological model corresponding to a Kelvin chain. Drying creep is modelled using a viscous unit which depends on the stress level, and drying shrinkage is stress independent. Both drying creep and drying shrinkage are related to the internal humidity. The humidity distribution within concrete is determined using a diffusion analysis. The moisture movement within mortar is governed by a nonlinear diffusion equation, whereas the aggregates are assumed impermeable. The cracking of concrete is explicitly modelled on the meso-scale through coupling of the continuum damage model for cracking within the mortar phase, and the cohesive zone model for debonding between aggregates and mortar. The proposed model is verified by simulating well-documented experimental studies in the literature. The capability of the proposed model in simulating the time-dependent behaviour of concrete and capturing the crack patterns has also been demonstrated.
Circulating retinol and 25(OH)D contents and their association with symptoms in children with chronic tic disorders
Authors: Wang Cheng-Xin , Wang Bing , Sun Jian-Jian , Xiao Chun-Ying , Ma Huan , Jia Fei-Yong , Li Hong-Hua
Published: May 2023

The present study measured serum levels of vitamin A (VA) and vitamin D (VD) in children with chronic tic disorders (CTD) and investigated their potential association with CTD and comorbidity of attention deficit hyperactivity disorder (ADHD) and the association of their co-insufficiencies or deficiencies with CTD symptoms. A total of 176 children (131 boys and 45 girls, median age of 9 years) with CTD were recruited as the CTD group. During the same period, 154 healthy children were selected as the healthy control (HC) cohort. Circulating retinol and 25-hydroxyvitamin D (25[OH]D) levels were measured for all participants using high-performance liquid chromatography (HPLC) and tandem mass spectrometry. The Yale Global Tic Severity Scale (YGTSS) was employed for the assessment of tic status and CTD impairment. The Swanson, Nolan, and Pelham Rating Scale (SNAP-IV) and the Children’s Yale-Brown Obsessive–Compulsive Scale (CY-BOCS) were used to evaluate comorbidity symptoms. CTD pediatric participants exhibited markedly diminished circulating retinol and 25(OH)D levels compared to HCs. Moreover, VA and VD deficiencies and their co-insufficiencies/deficiencies were more prevalent in CTD participants than HCs. Circulating 25(OH)D levels were inversely proportional to the YGTSS motor tic scores. YGTSS scores in CTD children with only VA or VD insufficiency or deficiency or with VA and VD co-insufficiency/deficiency did not differ from those in CTD children with normal VA and VD. CTD children with comorbid ADHD displayed reduced circulating retinol and 25(OH)D concentrations and elevated prevalence of VD deficiency compared to CTD participants without comorbid ADHD. Lower serum retinol content was intricately linked to the presence of elevated CTD and comorbid ADHD. VA and VD deficiencies and their co-insufficiencies/deficiencies were markedly enhanced in CTD pediatric participants compared to HCs. Lower VA concentration was linked to the presence of enhanced CTD and comorbid ADHD. Therefore, children with CTD, especially with comorbid ADHD, may be at a higher risk of VA or VD deficiency, which may prompt the clinicians to consider whether blood tests for VA and VD in CTD children would be helpful for clinical care.
MPF6D: masked pyramid fusion 6D pose estimation
Authors: Pereira Nuno , Alexandre Luís A.
Published: May 2023

Object pose estimation has multiple important applications, such as robotic grasping and augmented reality. We present a new method to estimate the 6D pose of objects that improves upon the accuracy of current proposals and can still be used in real-time. Our method uses RGB-D data as input to segment objects and estimate their pose. It uses a neural network with multiple heads to identify the objects in the scene, generate the appropriate masks and estimate the values of the translation vectors and the quaternion that represents the objects’ rotation. These heads leverage a pyramid architecture used during feature extraction and feature fusion. We conduct an empirical evaluation using the two most common datasets in the area, and compare against state-of-the-art approaches, illustrating the capabilities of MPF6D. Our method can be used in real-time with its low inference time and high accuracy.
Globally $\pmb{+}$-regular varieties and the minimal model program for threefolds in mixed characteristic
Authors: Bhatt Bhargav , Ma Linquan , Patakfalvi Zsolt , Schwede Karl , Tucker Kevin , Waldron Joe , Witaszek Jakub
Published: May 2023

We establish the Minimal Model Program for arithmetic threefolds whose residue characteristics are greater than five. In doing this, we generalize the theory of global$F$F-regularity to mixed characteristic and identify certain stable sections of adjoint line bundles. Finally, by passing to graded rings, we generalize a special case of Fujita’s conjecture to mixed characteristic.
Deep learning implementations in mining applications: a compact critical review
Authors: Azhari Faris , Sennersten Charlotte C. , Lindley Craig A. , Sellers Ewan
Published: May 2023

Deep learning is a sub-field of artificial intelligence that combines feature engineering and classification in one method. It is a data-driven technique that optimises a predictive model via learning from a large dataset. Digitisation in industry has included acquisition and storage of a variety of large datasets for interpretation and decision making. This has led to the adoption of deep learning in different industries, such as transportation, manufacturing, medicine and agriculture. However, in the mining industry, the adoption and development of new technologies, including deep learning methods, has not progressed at the same rate as in other industries. Nevertheless, in the past 5 years, applications of deep learning have been increasing in the mining research space. Deep learning has been implemented to solve a variety of problems related to mine exploration, ore and metal extraction and reclamation processes. The increased automation adoption in mining provides an avenue for wider application of deep learning as an element within a mine automation framework. This work provides a compact, comprehensive review of deep learning implementations in mining-related applications. The trends of these implementations in terms of years, venues, deep learning network types, tasks and general implementation, categorised by the value chain operations of exploration, extraction and reclamation are outlined. The review enables shortcomings regarding progress within the research context to be highlighted such as the proprietary nature of data, small datasets (tens to thousands of data points) limited to single operations with unique geology, mine design and equipment, lack of large scale publicly available mining related datasets and limited sensor types leading to the majority of applications being image-based analysis. Gaps identified for future research and application includes the usage of a wider range of sensor data, improved understanding of the outputs by mining practitioners, adversarial testing of the deep learning models, development of public datasets covering the extensive range of conditions experienced in mines.
BOUNCE: memory-efficient SIMD approach for lightweight integer compression
Authors: Hildebrandt Juliana , Habich Dirk , Lehner Wolfgang
Published: May 2023

Integer compression plays an important role in columnar database systems to reduce the main memory footprint as well as to speedup query processing. To keep the additional computational effort of (de)compression as low as possible, the powerful Single Instruction Multiple Data (SIMD) extensions of modern CPUs are heavily applied. While a scalar compression algorithm usually compresses a block of N consecutive integers, the state-of-the-art SIMDified implementation scales the block size to $$k \cdot N$$

k
·
N

with k as the number of elements which could be simultaneously processed in an SIMD register. On the one hand, this scaling SIMD approach improves the performance of (de)compression. But on the other hand, it can lead to a degradation of the memory footprint of the compressed data. Within this article, we analyze this degradation effect for various integer compression algorithms and present a novel SIMD concept to overcome that effect. The core idea of our novel SIMD concept called BOUNCE is to concurrently compress k different blocks of size N within SIMD registers, guaranteeing the same compression ratio as scalar variant. As we are going to show, our proposed SIMD idea works well on various Intel CPUs and may offer a new generalized SIMD concept to optimize further algorithms.
Tailoring LPSO phases in Mg–Y–Zn alloys to govern hydrogenation kinetics
Authors: Nicholson Kyle S. , Skripnyuk Vladimir , Xu Chunjie , Gao Xiang , Rabkin Eugen , Hodgson Peter D. , Lapovok Rimma
Published: May 2023

A series of Mg–Y–Zn alloys with varying long-period stacking ordered (LPSO) phase fractions were prepared through control of alloy content, heat-treatment, and single-pass extrusion. The effect of LPSO phase volume fraction and microstructure refinement on the hydrogen absorption/desorption properties of ball-milled powders prepared from the extruded alloys was experimentally assessed. The hydrogen absorption and desorption kinetics scaled with the LPSO phase volume fraction, though the results of this study suggest that the scaling is not linear. Variations in the LPSO phase fraction and alloy content did not alter the (de)hydrogenation equilibrium pressure, indicating there is no significant change in thermodynamics of hydrogenation. Hydrogen absorption experiments on thin foils made from the extruded Mg–Y–Zn alloy with a high LPSO phase fraction demonstrated that the LPSO structures decompose into Mg phase, lamellar Mg/Mg–Zn structures and YH2 particles at hydrogen partial pressures sufficient to form YH2. This study shows that the hydrogen absorption/desorption kinetics in the Mg–Y–Zn alloys can be controlled by tailoring the LPSO phases using conventional metallurgical techniques.

Graphical Abstract
Exome sequence analysis of rare frequency variants in Late-Onset Alzheimer Disease
Authors: Sundarrajan Sudharsana , Venkatesan Arthi , Kumar S Udhaya , Gopikrishnan Mohanraj , Tayubi Iftikhar Aslam , Aditya M , Siddaiah Gowrishankar Bychapur , George Priya Doss C. , Zayed Hatem
Published: May 2023

Alzheimer disease (AD) is a leading cause of dementia in elderly patients who continue to live between 3 and 11 years of diagnosis. A steep rise in AD incidents is observed in the elderly population in East-Asian countries. The disease progresses through several changes, including memory loss, behavioural issues, and cognitive impairment. The etiology of AD is hard to determine because of its complex nature. The whole exome sequences of late-onset AD (LOAD) patients of Korean origin are investigated to identify rare genetic variants that may influence the complex disorder. Computational annotation was performed to assess the function of candidate variants in LOAD. The in silico pathogenicity prediction tools such as SIFT, Polyphen-2, Mutation Taster, CADD, LRT, PROVEAN, DANN, VEST3, fathmm-MKL, GERP +  + , SiPhy, phastCons, and phyloP identified around 17 genes harbouring deleterious variants. The variants in the ALDH3A2 and RAD54B genes were pathogenic, while in 15 other genes were predicted to be variants of unknown significance. These variants can be potential risk candidates contributing to AD. In silico computational techniques such as molecular docking, molecular dynamic simulation and steered molecular dynamics were carried out to understand the structural insights of RAD54B with ATP. The simulation of mutant (T459N) RAD54B with ATP revealed reduced binding strength of ATP at its binding site. In addition, lower binding free energy was observed when compared to the wild-type RAD54B. Our study shows that the identified uncommon variants are linked to AD and could be probable predisposing genetic factors of LOAD.
NoC-based hardware software co-design framework for dataflow thread management
Authors: Mazumdar Somnath , Scionti Alberto , Zuckerman Stéphane , Portero Antoni
Published: May 2023

Applications running in a large and complex manycore system can significantly benefit from adopting the dataflow model of computation. In a dataflow execution environment, a thread can run only if all its required inputs are available. While the potential benefits are large, it is not trivial to improve resource utilization and energy efficiency by focusing on dataflow thread execution models (i.e., the ways specifying how the threads adhering to a dataflow model of computation execute on a given compute/communication architecture). This paper proposes and implements a hardware-software co-design-based dataflow threads management framework. It works at the Network-on-Chip (NoC) level and consists of three stages. The first stage focuses on a fast and effective thread distribution policy. The next stage proposes an approach that adds reconfigurability to a 2D mesh NoC via customized instructions to manage the dataflow thread distribution. Finally, a 2D mesh and ring-based hybrid NoC is proposed for better scalability and higher performance. This work can be considered a primary reference framework from which extensions can be carried out.
Measures of frequency and effect in clinical research
Authors: D’Arrigo Graziella , Gori Mercedes , Pitino Annalisa , Tsalikakis Dimitrios G. , Liakopoulos Vassilios , Roumeliotis Stefanos , Tripepi Giovanni
Published: May 2023

The assessment of risk and effect size of a specific endpoint associated to the presence/absence of a certain exposure is a hallmark in clinical and epidemiological research. In fact, before recommending any treatment, it is mandatory to investigate the magnitude of the benefits and harms between the exposure under investigation (e.g. a given treatment) and a specific disease or event. To do this, clinicians and statisticians use absolute (risk differences, number needed to treat, likelihood to be helped or harmed) and relative (risk ratio, incidence rate ratio, hazard ratio and odds ratio) measures of effect. Herein, using a series of clinical examples, we aim to present a step by step methodologic approach of measures of effect in the area of nephrology and urology.
The Expanded Exercise Addiction Inventory (EAI-3): Towards Reliable and International Screening of Exercise-Related Dysfunction
Authors: Granziol Umberto , Griffiths Mark D. , Zou Liye , Yang Peiying , Herschel Hannah K. , Junker Annika , Akimoto Takayuki , Stoll Oliver , Alpay Merve , Aydın Zeynep , Zandonai Thomas , Di Lodovico Laura , Lichtenstein Mia Beck , Trott Mike , Portman Robert M. , Schipfer Melanie , Cook Brian , Cerea Silvia , Egorov Aleksei Y. , Cantù-Berrueto Abril , de la Vega Marcos Ricardo , Fernandes Paula Texeira , Landolfi Emilio , Demetrovics Zsolt , Tóth Eliza E. , Solmi Marco , Szabo Attila
Published: May 2023

Exercise addiction (EA) refers to excessive exercise, lack of control, and health risks. The Exercise Addiction Inventory (EAI) is one of the most widely used tools in its assessment. However, the cross-cultural psychometric properties of the EAI could be improved because it misses three pathological patterns, including guilt, exercise despite injury, and experienced harm. Therefore, the present study tested the psychometric properties of the expanded EAI (EAI-3) in a large international sample. The EAI-3 was administered to 1931 physically active adult exercisers speaking five languages (Chinese, German, Italian, Japanese, and Turkish) and other measures for obsessive–compulsive behavior, eating disorders, and personality traits. The assessment structure and reliability of the EAI-3 were tested with factorial analyses and through measurement invariance across languages and sex. Finally, a cutoff point for dysfunction-proneness was calculated. The EAI-3 comprised two factors, reflecting the positive and pathological sides of exercise. The structure had excellent reliability and goodness-of-fit indices and configural and metric invariances of the scale were supported. However, three items caused violations in scalar invariance. The results of partial measurement invariance testing suggested an adequate fit for the data. Following sensitivity and specificity analysis, the EAI-3’s cutoff score was 34 out of a maximum score of 48. This preliminary study suggests that the EAI-3 is a promising tool for screening EA in an international sample, with a robust and reliable structure comparable across languages and sex. In addition, the proposed cutoff could pave the way toward a consensus on a threshold to screen for EA.
An Improved Cellular Automata Solidification Model Considering Kinetic Undercooling
Authors: Liang Xiaohui , Bos Cornelis , Hermans Marcel , Richardson Ian
Published: May 2023

A cellular automata (CA) model has been developed for solidification simulation considering the kinetic undercooling at the interface. The state-of-the-art model incorporates a decentered growth algorithm to suppress the grid anisotropy and a generalized height function method to calculate the curvature accurately. To develop a CA model which is independent of the mesh size, a new diffusion term is proposed to handle the diffusion between the interface cells and liquid cells. The developed CA model is employed to simulate the single-dendritic solidification of an Al–3Cu (wt pct) alloy. The simulated tip velocities agree with the prediction of the Kurz–Giovanola–Trivedi (KGT) model. Further studies show that the developed CA model converges to an equilibrium model with increasing kinetic mobility values. Moreover, it is found that the virtual liquid cell assumption which is commonly used in existing CA models may lead to a deviation in the mass balance. The mass balance error has been resolved by redistributing solutes from neighboring liquid cells in each time step. The developed CA model could be potentially used in solidification simulations with a high undercooling, which is common in welding and additive manufacturing.
Geochemical Survey and Estimation of Baseline Concentrations of Major and Trace Elements in Stream Water, Uttar Pradesh, India: Implication for Environmental Studies
Authors: Kumar Harish , Naim Nikhat , Ali Danish
Published: May 2023

Stream water plays an important role in the development of habitats. It is one of the important sources of water used for drinking and irrigation in the region. Before using, it is necessary to test the quality of all types of surface water available for various use. A geochemical study of stream water has been conducted in parts of Pratapgarh, Raebareli, and Allahabad districts of Uttar Pradesh to assess its suitability for domestic purposes and establish the baseline concentration of major ions, trace and REEs. 20 samples of stream water from different locations of 1st or 2nd order streams were collected during post-monsoon period, from 18th to 31st October 2021. Different hydrochemical parameters such as pH, electrical conductivity (EC), temperature, dissolved oxygen (DO), salinity, total dissolved solids (TDS), major cations and anions were analysed. In order to obtain maximum quality and purity of water, the stream water samples were analyzed by ICP-MS analytical method in the chemical lab for 47 trace elements including REEs contents. The obtained values of each parameter have been compared with the standard values recommended by BIS and WHO. The value of each element except uranium has been found to be within the desirable and permissible limits prescribed by BIS (2012) and WHO (2006). Selenium and arsenic have been found to be marginally exceed the permissible limits. The pH values of all stream waters in the study area range from 7.14 to 8.86 with an average value of 7.86 indicating an alkaline nature of stream water. The concentration of uranium in stream water varied from 1.5 ppb to 48.67 ppb with a mean value of 7.9 ppb. It is observed that wherever concentration of uranium in the samples increased, the pH as well as the bicarbonate level increased accordingly. Correlation coefficient revealed that uranium is strongly correlated with bicarbonate (r=0.67), moderately with sodium (r=6.1), and low positively correlated with the concentration of pH (r=0.34), EC (r=0.52), and salinity (r=0.52), indicates the same origin. Water quality index (WQI) of water was determined for suitability of drinking purpose, revealed that 65% water samples fall in excellent category and 30% water samples fall in good category while only 5% water sample are in poor category. Trilinear plot of sample shows that most of the stream water samples are Ca-Mg-HCO3 type.
Non-hydrostatic layer-averaged approximation of Euler system with enhanced dispersion properties
Authors: Escalante C. , Fernández-Nieto E. D. , Garres-Díaz J. , Morales de Luna T. , Penel Y.
Published: May 2023

A new family of non-hydrostatic layer-averaged models for the non-stationary Euler equations is presented in this work, with improved dispersion relations. They are a generalisation of the layer-averaged models introduced in Fernández-Nieto et al. (Commun Math Sci 16(05):1169–1202, 2018), named LDNH models, where the vertical profile of the horizontal velocity is layerwise constant. This assumption implies that solutions of LDNH can be seen as a first order Galerkin approximation of Euler system. Nevertheless, it is not a fully (x, z) Galerkin discretisation of Euler system, but just in the vertical direction (z). Thus, the resulting model only depends on the horizontal space variable (x), and therefore specific and efficient numerical methods can be applied (see Escalante-Sanchez et al. in J Sci Comput 89(55):1–35, 2021). This work focuses on particular weak solutions where the horizontal velocity is layerwise linear on z and possibly discontinuous across layer interfaces. This approach allows the system to be a second-order approximation in the vertical direction of Euler system. Several closure relations of the layer-averaged system with non-hydrostatic pressure are presented. The resulting models are named LIN-NH$$_k$$

k

models, with $$k=0,1,2$$

k
=
0
,
1
,
2

. Parameter k indicates the degree of the vertical velocity profile considered in the approximation of the vertical momentum equation. All the introduced models satisfy a dissipative energy balance. Finally, an analysis and a comparison of the dispersive properties of each model are carried out. We show that Models LIN-NH$$_1$$

1

and LIN-NH$$_2$$

2

provide a better dispersion relation, group velocity and shoaling than LDNH models.