bluuebunny/crossref_metadata_2025_split huggingface dataset:
Elucidating distinct clinico-radiologic signatures in the borderland between neuromyelitis optica and multiple sclerosis
Authors: Juryńczyk Maciej , Klimiec-Moskal Elżbieta , Kong Yazhuo , Hurley Samuel , Messina Silvia , Yeo Tianrong , Jenkinson Mark , Leite Maria Isabel , Palace Jacqueline 
Published: May 2021

AbstractBackgroundSeparating antibody-negative neuromyelitis optica spectrum disorders (NMOSD) from multiple sclerosis (MS) in borderline cases is extremely challenging due to lack of biomarkers. Elucidating different pathologies within the likely heterogenous antibody-negative NMOSD/MS overlap syndrome is, therefore, a major unmet need which would help avoid disability from inappropriate treatment.ObjectiveIn this study we aimed to identify distinct subgroups within the antibody-negative NMOSD/MS overlap syndrome.MethodsTwenty-five relapsing antibody-negative patients with NMOSD features underwent a prospective brain and spinal cord MRI. Subgroups were identified by an unsupervised algorithm based on pre-selected NMOSD/MS discriminators.ResultsFour subgroups were identified. Patients from Group 1 termed “MS-like” (n = 6) often had central vein sign and cortical lesions (83% and 67%, respectively). All patients from Group 2 (“spinal MS-like”, 8) had short-segment myelitis and no MS-like brain lesions. Group 3 (“classic NMO-like”, 6) had high percentage of bilateral optic neuritis and longitudinally extensive transverse myelitis (LETM, 80% and 60%, respectively) and normal brain appearance (100%). Group 4 (“NMO-like with brain involvement”, 5) typically had a history of NMOSD-like brain lesions and LETM. When compared with other groups, Group 4 had significantly decreased fractional anisotropy in non-lesioned tracts (0.46 vs. 0.49,p = 0.003) and decreased thalamus volume (0.84 vs. 0.98,p = 0.04).ConclusionsNMOSD/MS cohort contains distinct subgroups likely corresponding to different pathologies and requiring tailored treatment. We propose that non-conventional MRI might help optimise diagnosis in these challenging patients.
Establishing the twig method for investigations on pollen characteristics of allergenic tree species
Authors: Jung Stephan , Zhao Feng , Menzel Annette 
Published: May 2021

AbstractThe twig method in climate chambers has been shown to successfully work as a proxy for outdoor manipulations in various experimental setups. This study was conducted to further establish this method for the investigation of allergenic pollen from tree species (hazel, alder, and birch). Direct comparison under outdoor conditions revealed that the cut twigs compared to donor trees were similar in the timing of flowering and the amount of pollen produced. Cut twigs were able to flower in climate chambers and produced a sufficient amount of pollen for subsequent laboratory analysis. The addition of different plant or tissue fertilizers in the irrigation of the twigs did not have any influence; rather, the regular exchange of water and the usage of fungicide were sufficient for reaching the stage of flowering. In the experimental setup, the twigs were cut in different intervals before the actual flowering and were put under warming conditions in the climate chamber. An impact of warming on the timing of flowering/pollen characteristics could be seen for the investigated species. Therefore, the twig method is well applicable for experimental settings in pollen research simulating, e.g., accelerated warming under climate change.
Deep learning for cephalometric landmark detection: systematic review and meta-analysis
Authors: Schwendicke Falk , Chaurasia Akhilanand , Arsiwala Lubaina , Lee Jae-Hong , Elhennawy Karim , Jost-Brinkmann Paul-Georg , Demarco Flavio , Krois Joachim 
Published: May 2021

Abstract
Objectives
Deep learning (DL) has been increasingly employed for automated landmark detection, e.g., for cephalometric purposes. We performed a systematic review and meta-analysis to assess the accuracy and underlying evidence for DL for cephalometric landmark detection on 2-D and 3-D radiographs.

Methods
Diagnostic accuracy studies published in 2015-2020 in Medline/Embase/IEEE/arXiv and employing DL for cephalometric landmark detection were identified and extracted by two independent reviewers. Random-effects meta-analysis, subgroup, and meta-regression were performed, and study quality was assessed using QUADAS-2. The review was registered (PROSPERO no. 227498).

Data
From 321 identified records, 19 studies (published 2017–2020), all employing convolutional neural networks, mainly on 2-D lateral radiographs (n=15), using data from publicly available datasets (n=12) and testing the detection of a mean of 30 (SD: 25; range.: 7–93) landmarks, were included. The reference test was established by two experts (n=11), 1 expert (n=4), 3 experts (n=3), and a set of annotators (n=1). Risk of bias was high, and applicability concerns were detected for most studies, mainly regarding the data selection and reference test conduct. Landmark prediction error centered around a 2-mm error threshold (mean; 95% confidence interval: (–0.581; 95 CI: –1.264 to 0.102 mm)). The proportion of landmarks detected within this 2-mm threshold was 0.799 (0.770 to 0.824).

Conclusions
DL shows relatively high accuracy for detecting landmarks on cephalometric imagery. The overall body of evidence is consistent but suffers from high risk of bias. Demonstrating robustness and generalizability of DL for landmark detection is needed.

Clinical significance
Existing DL models show consistent and largely high accuracy for automated detection of cephalometric landmarks. The majority of studies so far focused on 2-D imagery; data on 3-D imagery are sparse, but promising. Future studies should focus on demonstrating generalizability, robustness, and clinical usefulness of DL for this objective.
A note on super Koszul complex and the Berezinian
Authors: Noja Simone , Re Riccardo 
Published: May 2021

AbstractWe construct the super Koszul complex of a free supercommutative A-module V of rank p|q and prove that its homology is concentrated in a single degree and it yields an exact resolution of A. We then study the dual of the super Koszul complex and show that its homology is concentrated in a single degree as well and isomorphic to $$\Pi ^{p+q} A$$

Π

p
+
q

A

, with $$\Pi $$
Π
the parity changing functor. Finally, we show that, given an automorphism of V, the induced transformation on the only non-trivial homology class of the dual of the super Koszul complex is given by the multiplication by the Berezinian of the automorphism, thus relating this homology group with the Berezinian module of V.
Fatigue Crack Growth in Austenitic and Martensitic NiTi: Modeling and Experiments
Authors: Sgambitterra E. , Magarò P. , Niccoli F. , Furgiuele F. , Maletta C. 
Published: May 2021

AbstractFatigue crack growth of austenitic and martensitic NiTi shape memory alloys was analyzed, with the purpose of capturing the effects of distinct stress-induced transformation mechanics in the two crystal structures. Mode I crack growth experiments were carried out, and near-crack-tip displacements were captured by in-situ digital image correlation (DIC). A special fitting procedure, based on the William’s solution, was used to estimate the effective stress intensity factor (SIF). The SIF was also computed by linear elastic fracture mechanics (LEFM) as well as by a special analytical model that takes into account the unique thermomechanical response of SMAs. A significant difference in the crack growth rate for the two alloys was observed, and it has been attributed to dissimilar dissipative phenomena and different crack-tip stress–strain fields, as also directly observed by DIC. Finally, it was shown that the predictions of the analytical method are in good agreement with effective results obtained by DIC, whereas a very large mismatch was observed with LEFM. Therefore, the proposed analytical model can be actually used to analyze fatigue crack propagation in both martensitic and austenitic NiTi.
Effect of sex hormones on human voice physiology: from childhood to senescence
Authors: Zamponi Virginia , Mazzilli Rossella , Mazzilli Fernando , Fantini Marco 
Published: May 2021

AbstractThe aim of the present literature review is to describe the influence of sex hormones on the human voice in physiological conditions. As a secondary sexual organ, the larynx is affected by sex hormones and may change considerably over the lifespan. In the current review, sex hormone-related voice modifications occurring during childhood, puberty, the menstrual cycle, pregnancy and senescence are described. The roles of sex hormones (including gonadotropins, testosterone, estrogen, androstenedione, dehydroepiandrosterone, and dehydroepiandrosterone-sulfate) underlying physiological voice changes are discussed, the main differences between males and females are explained and clinical implications are taken into account.
A trade-off methodology for micro-launchers
Authors: Governale G. , Rimani J. , Viola N. , Villace V. Fernandez 
Published: May 2021

AbstractThe trend of cost-effective access to space and satellite technologies’ evolution is increasing the small satellite market. However, small payloads usually ride as piggyback, being a secondary passenger of a space vector, with very low flexibility in target orbit and launch schedule. The micro-launchers are designed to answer the needs of the small satellite missions, with a payload capacity up to 350 kg to Low Earth Orbit, aiming to low turn-over time and competitive prices. This paper explains the work performed by Politecnico di Torino in support of the ESA–ESTEC activities on micro-launchers. The aim is to provide preliminary guidelines for choosing and evaluating new innovative micro-launcher flight vehicle engineering processes. A trade-off methodology is proposed and defined based on the Analytically Hierarchical Process (AHP). This methodology considers, among other features, the flight profile, maximum payload, and physical characteristics. To support the trade-off analysis, a software tool is built for the automatic generation of the aerodynamics and propulsion parameters needed for the completion of the preliminary designs, enabling the performance estimation. The launcher’s performance models, with an analysis of the take-off sites and target orbits, are also produced. This allows the definition of performance maps where the maximum payload is graphed as a function of the orbit altitude and inclination. A set of innovative micro-launchers exploiting different technologies is also assessed as a case study.
A Survey on Variational Autoencoders from a Green AI Perspective
Authors: Asperti Andrea , Evangelista Davide , Loli Piccolomini Elena 
Published: May 2021

AbstractVariational Autoencoders (VAEs) are powerful generative models that merge elements from statistics and information theory with the flexibility offered by deep neural networks to efficiently solve the generation problem for high-dimensional data. The key insight of VAEs is to learn the latent distribution of data in such a way that new meaningful samples can be generated from it. This approach led to tremendous research and variations in the architectural design of VAEs, nourishing the recent field of research known as unsupervised representation learning. In this article, we provide a comparative evaluation of some of the most successful, recent variations of VAEs. We particularly focus the analysis on the energetic efficiency of the different models, in the spirit of the so-called Green AI, aiming both to reduce the carbon footprint and the financial cost of generative techniques. For each architecture, we provide its mathematical formulation, the ideas underlying its design, a detailed model description, a running implementation and quantitative results.
Solid-state welding of ultrafine grained copper rods
Authors: Morawiński Łukasz , Jasiński Cezary , Ciemiorek Marta , Chmielewski Tomasz , Olejnik Lech , Lewandowska Małgorzata 
Published: May 2021

Abstract
The article focuses on the Direct Drive Rotary Friction Welding of ultrafine-grained copper rods, which feature increased mechanical properties and good electrical properties, yet are limited in size. The use of UFG metals is often limited by the too small dimensions of semi-finished elements produced by SPD methods. Therefore, the production of finished machine parts from UFG metals is currently economically unjustified. Dismissal of dimensional limitations can be done by introducing joining to technological processes. The proposed joining method does not lead to a melting of the material in the joining zone or excessive degradation of the UFG microstructure. To obtain the best results, the research used the method of low-energy welding of two kinds of specimens: with a flat or a conical contact surface. In the article, the authors present, by means of metallographic microsections and microhardness measurements, the influence of rotational speed, welding pressure and conical shape contact surface on the quality of the obtained joints. The conducted research made it possible to obtain good quality joints whose microhardness is reduced only by about 10% in comparison with the base material and the tensile strength dropped from only 397–358 MPa.
Urinary sodium excretion and the risk of CVD: a community-based cohort study in Taiwan
Authors: Wang Yi-Jie , Chien Kuo-Liong , Hsu Hsiu-Ching , Lin Hung-Ju , Su Ta-Chen , Chen Ming-Fong , Lee Yuan-Teh 
Published: May 2021

AbstractUrinary Na excretion is a potential risk factor for CVD. However, the underlying biological mechanisms and effects of salt sensitivity are unclear. The purpose of this study was to characterise the relative contribution of biological factors to the Na–CVD association. A total of 2112 participants were enrolled in this study. Structured questionnaires and blood and urine samples were obtained. Twenty-four-hour Na excretion was estimated using a single overnight urine sample. Hypertension, the metabolic syndrome and overweight status were considered to indicate salt sensitivity. Cox proportional hazard models were used to investigate the effects of salt sensitivity on urinary Na excretion and CVD risk. The traditional mediation approach was used to calculate the proportion of mediation. The mean age (sd) of the 2112 participants was 54·5 (sd12·2) years, and they were followed up for a mean of 14·1 (sd8·1) years. Compared with those in the lowest quartile, the highest baseline urinary Na excretion (>4·2 g/24 h) was associated with a 43 % higher CVD risk (hazard ratio, 1·43; 95 % CI 1·02, 1·99). Participants with high urinary Na excretion, hypertension or the metabolic syndrome had a significantly high risk of CVD. The carotid intima-media thickness had the largest mediating effect (accounting for 35 % of the Na–CVD association), followed by systolic blood pressure (BP) (33 %), left ventricular mass (28 %) and diastolic BP (14 %). Higher urinary Na excretion increased the risk of CVD, which was explained largely by carotid media-thickness and systolic BP.
Cassius Dio's figures for the demographic consequences of the Bar Kokhba War: Exaggeration or reliable account?
Authors: Raviv Dvir , Ben David Chaim 
Published: May 2021

AbstractScholars have long doubted the historical accuracy of Cassius Dio's account of the consequences of the Bar Kokhba War (Roman History69.14). According to this text, considered the most reliable literary source for the Second Jewish Revolt, the war encompassed all of Judea: the Romans destroyed 985 villages and 50 fortresses, and killed 580,000 rebels. This article reassesses Cassius Dio's figures by drawing on new evidence from excavations and surveys in Judea, Transjordan, and the Galilee. Three research methods are combined: an ethno-archaeological comparison with the settlement picture in the Ottoman Period, comparison with similar settlement studies in the Galilee, and an evaluation of settled sites from the Middle Roman Period (70–136 CE). The study demonstrates the potential contribution of the archaeological record to this issue and supports the view of Cassius Dio's demographic data as a reliable account, which he based on contemporaneous documentation.
A pathway phenotype linking metabolic, immune, oxidative, and opioid pathways with comorbid depression, atherosclerosis, and unstable angina
Authors: Mousa Rana Fadhil , Smesam Hasan Najah , Qazmooz Hasan Abbas , Al-Hakeim Hussein Kadhem , Maes Michael 
Published: May 2021

AbstractBackgroundThere is strong comorbidity between atherosclerosis (ATS) and depression which is attributed to increased atherogenicity, insulin resistance (IR), and immune and oxidative stress.Aim of the studyTo examine the role of the above pathways and mu-opioid receptor (MOR), β-endorphin levels, zinc, copper, vitamin D3, calcium, and magnesium in depression due to ATS/unstable angina (UA).MethodsBiomarkers were assayed in 58 controls and 120 ATS patients divided into those with moderate and severe depression according to the Beck Depression Inventory-II (BDI-II) scores >19 and >29, respectively.ResultsNeural network and logistic regression models showed that severe depression due to ATS/UA was best predicted by interleukin-6 (IL-6), UA, MOR, zinc, β-endorphin, calcium and magnesium, and that moderate depression was associated with IL-6, zinc, MOR, β-endorphin, UA, atherogenicity, IR, and calcium. Neural networks yielded a significant discrimination of severe and moderate depression with an area under the receiver operating curves of 0.831 and 0.931, respectively. Using Partial Least Squares path analysis, we found that 66.2% of the variance in a latent vector extracted from ATS/UA clinical features, and the BDI-II scores, atherogenicity, and IR could be explained by the regression on IL-6, IL-10, zinc, copper, calcium, MOR, and age. The BDI-II scores increased from controls to ATS to UA class III to UA class IV.ConclusionsImmune activation, the endogenous opioid system, antioxidants, trace elements, and macrominerals modulate a common core shared by increased depressive symptoms, ATS, UA, atherogenicity, and IR.
Acquisition of the Significant Wave Height From CFOSAT SWIM Spectra Through a Deep Neural Network and Its Impact on Wave Model Assimilation
Authors: Wang J. K. , Aouf L. , Dalphinet A. , Li B.X. , Xu Y. , Liu J. Q. 
Published: May 2021

AbstractThe wave numerical simulation accuracy can be improved by assimilating remotely sensed wave observations. In addition to the nadir, significant wave height (SWH), the Surface Waves Investigation and Monitoring (SWIM) onboard Chinese‐French Oceanic SATellite (CFOSAT) provides two additional columns of wave spectra observations within wavelengths from 70 to 500 m. A model based on a deep neural network (DNN) is developed to retrieve the total SWH from the partially wave spectra observed by SWIM. The DNN model uses the parameters from both the SWIM spectra and the nearest nadir as the inputs, and the DNN is trained on the SWH from cross‐matched altimeter observations. The DNN‐based acquisition of the SWH is verified to achieve a high accuracy. A set of assimilation experiments are performed based on MFWAM and show promising results. Compared to the assimilation of SWIM nadir SWHs only, the addition of the newly obtained SWIM SWH notably enhances the positive impacts of assimilation, not only proving the effectiveness and accuracy of the DNN model but also demonstrating the unique potential of SWIM in wave assimilation.
Estimating the Acute Health Impacts of Fire‐Originated PM2.5 Exposure During the 2017 California Wildfires: Sensitivity to Choices of Inputs
Authors: Cleland Stephanie E. , Serre Marc L. , Rappold Ana G. , West J. Jason 
Published: May 2021

AbstractExposure to wildfire smoke increases the risk of respiratory and cardiovascular hospital admissions. Health impact assessments, used to inform decision‐making processes, characterize the health impacts of environmental exposures by combining preexisting epidemiological concentration–response functions (CRFs) with estimates of exposure. These two key inputs influence the magnitude and uncertainty of the health impacts estimated, but for wildfire‐related impact assessments the extent of their impact is largely unknown. We first estimated the number of respiratory, cardiovascular, and asthma hospital admissions attributable to fire‐originated PM2.5 exposure in central California during the October 2017 wildfires, using Monte Carlo simulations to quantify uncertainty with respect to the exposure and epidemiological inputs. We next conducted sensitivity analyses, comparing four estimates of fire‐originated PM2.5 and two CRFs, wildfire and nonwildfire specific, to understand their impact on the estimation of excess admissions and sources of uncertainty. We estimate the fires accounted for an excess 240 (95% CI: 114, 404) respiratory, 68 (95% CI: −10, 159) cardiovascular, and 45 (95% CI: 18, 81) asthma hospital admissions, with 56% of admissions occurring in the Bay Area. Although differences between impact assessment methods are not statistically significant, the admissions estimates' magnitude is particularly sensitive to the CRF specified while the uncertainty is most sensitive to estimates of fire‐originated PM2.5. Not accounting for the exposure surface's uncertainty leads to an underestimation of the uncertainty of the health impacts estimated. Employing context‐specific CRFs and using accurate exposure estimates that combine multiple data sets generates more certain estimates of the acute health impacts of wildfires.
Transcranial magnetic stimulation as a translational biomarker for AMPA receptor modulation
Authors: O’Donnell Patricio , Dijkstra Francis M. , Damar Ugur , Quanhong Lei , de Goede Annika A. , Xu Lin , Pascual-Leone Andres , Buhl Derek L. , Zuiker Rob , Ruijs Titia Q. , Heuberger Jules A. A. C. , MacMullin Paul , Lubell Martin , Asgharnejad Mahnaz , Murthy Venkatesha , Rotenberg Alexander , Jacobs Gabriel E. , Rosen Laura 
Published: May 2021

AbstractTAK-653 is a novel α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-positive allosteric modulator being developed as a potential therapeutic for major depressive disorder (MDD). Currently, there are no translational biomarkers that evaluate physiological responses to the activation of glutamatergic brain circuits available. Here, we tested whether noninvasive neurostimulation, specifically single-pulse or paired-pulse motor cortex transcranial magnetic stimulation (spTMS and ppTMS, respectively), coupled with measures of evoked motor response captures the pharmacodynamic effects of TAK-653 in rats and healthy humans. In the rat study, five escalating TAK-653 doses (0.1–50 mg/kg) or vehicle were administered to 31 adult male rats, while measures of cortical excitability were obtained by spTMS coupled with mechanomyography. Twenty additional rats were used to measure brain and plasma TAK-653 concentrations. The human study was conducted in 24 healthy volunteers (23 males, 1 female) to assess the impact on cortical excitability of 0.5 and 6 mg TAK-653 compared with placebo, measured by spTMS and ppTMS coupled with electromyography in a double-blind crossover design. Plasma TAK-653 levels were also measured. TAK-653 increased both the mechanomyographic response to spTMS in rats and the amplitude of motor-evoked potentials in humans at doses yielding similar plasma concentrations. TAK-653 did not affect resting motor threshold or paired-pulse responses in humans. This is the first report of a translational functional biomarker for AMPA receptor potentiation and indicates that TMS may be a useful translational platform to assess the pharmacodynamic profile of glutamate receptor modulators.