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BACKGROUND: Cranial autonomic symptoms (CASs) include lacrimation, conjunctival injection, rhinorrhea, nasal congestion, facial flushing or sweating, ptosis, and myosis. These symptoms may be associated with trigeminal autonomic cephalalgias (TACs) and migraine. OBJECTIVES: The aim of the study was to assess whether CASs are also reported by patients with frequent episodic tension-type headache (eTTH). MATERIAL AND METHODS: A cross-sectional online survey of a large Polish population was conducted between August 2021 and June 2022...

The Connectorship Scale was designed to assess how leaders connect with their followers and is described to measure eight dimensions: social interactivity, dependability, positive communication, presenting oneself, storytelling ability, belief in networking, tangible introduction, and belief in the importance of online networking. This study explores the scale properties and confirmatory factor analyses (CFA) of the Connectorship Scale and examines how the scale scores correlate with self-efficacy and extraversion based on responses from 454 (52% women) adult business students...

Utilising Machine Learning (ML) models to predict dosimetric parameters in pencil beam scanning proton therapy presents a promising and practical approach. The study developed Artificial Neural Network (ANN) models to predict proton beam spot size and relative positional errors using 9000 proton spot data. The irradiation log files as input variables and corresponding scintillation detector measurements as the label values. The ANN models were developed to predict six variables: spot size in the x -axis, y -axis, major axis, minor axis, and relative positional errors in the x -axis and y -axis...

Majority voting is a simple mathematical function that returns the most frequently occurring value within a given set. As a popular decision fusion technique (DFT), the majority voting function (MVF) finds applications in resolving conflicts, where several independent voters report their opinions on a classification problem. Despite its importance and its various applications in ensemble learning, data crowdsourcing, remote sensing, and data oracles for blockchains, the accuracy of the MVF for the general multiclass classification problem has remained unknown...

As an emerging decentralized machine learning technique, federated learning organizes collaborative training and preserves the privacy and security of participants. However, untrustworthy devices, typically Byzantine attackers, pose a significant challenge to federated learning since they can upload malicious parameters to corrupt the global model. To defend against such attacks, we propose a novel robust aggregation method-maximum correntropy aggregation (MCA), which applies the maximum correntropy criterion (MCC) to derive a central value from parameters...

Graph neural networks (GNN) suffer from severe inefficiency due to the exponential growth of node dependency with the increase of layers. It extremely limits the application of stochastic optimization algorithms so that the training of GNN is usually time-consuming. To address this problem, we propose to decouple a multi-layer GNN as multiple simple modules for more efficient training, which is comprised of classical forward training (FT) and designed backward training (BT). Under the proposed framework, each module can be trained efficiently in FT by stochastic algorithms without distortion of graph information owing to its simplicity...

Negative flips are errors introduced in a classification system when a legacy model is updated. Existing methods to reduce the negative flip rate (NFR) either do so at the expense of overall accuracy by forcing a new model to imitate the old models, or use ensembles, which multiply inference cost prohibitively. We analyze the role of ensembles in reducing NFR and observe that they remove negative flips that are typically not close to the decision boundary, but often exhibit large deviations in the distance among their logits...

Knife-edge imaging is a successful method for determining the wavefront distortion of focusing optics such as Kirkpatrick-Baez mirrors or compound refractive lenses. In this study, the wavefront error of an imperfect elliptical mirror is predicted by developing a knife-edge program using the SHADOW/OASYS platform. It is shown that the focusing optics can be aligned perfectly by minimizing the parabolic and cubic coefficients of the wavefront error. The residual wavefront error provides precise information about the figure/height errors of the focusing optics suggesting it as an accurate method for in situ optical metrology...

ConspectusIn the ever-increasing renewable-energy demand scenario, developing new photovoltaic technologies is important, even in the presence of established terawatt-scale silicon technology. Emerging photovoltaic technologies play a crucial role in diversifying material flows while expanding the photovoltaic product portfolio, thus enhancing security and competitiveness within the solar industry. They also serve as a valuable backup for silicon photovoltaic, providing resilience to the overall energy infrastructure...

STUDY OBJECTIVES: To evaluate the accuracy and precision of continuous overnight oxygen saturation (SpO2 ) measurement by a commercial wrist device (WD) incorporating high-grade sensors, and investigate WD estimation of sleep-disordered breathing by quantifying overnight oxygen desaturation index (ODI) compared to polysomnography (PSG) ODI and apnea-hypopnea index (AHI) with and without sleep questionnaire data, to assess WD ability to detect obstructive sleep apnea (OSA) and determine its severity...

OBJECTIVE: To evaluate the effects of rigid corneal lenses (RCL) in patients with keratoconus, based on eccentricity. METHODS: Eighty-four eyes from 84 patients were included in this retrospective comparative study. Based on the median value of eccentricity difference between the cornea and back surface of the RCL, the patients were divided into groups 1 (<0.08) and 2 (≥0.08). Visual acuity, refractive index, and corneal topography indices were compared before and three months after lens use...

In the article cited above, Fig. 7G mistakenly featured the same images as Fig. 7E due to an error during manuscript preparation. The corresponding graphs and associated data interpretation were not affected, and the conclusions remain unchanged. The correct image for Fig. 7G appears below. The authors apologize for the error. The online version of the article (https://doi.org/10.2337/db22-0745) has been updated with the correct image.

No abstract text is available yet for this article.

OBJECTIVES: This study aimed to determine the in vitro efficacy of cefiderocol in carbapenem-resistant Acinetobacter baumannii (CRAB) isolates and evaluate the disk-diffusion (DD) method as an alternative method to broth-microdilution (BMD). METHODS: Totally 89 CRAB isolates were included. Cluster analysis was determined by Pulsed-Field Gel Electrophoresis (PFGE). Resistance genes; blaOXA-51 , blaOXA-23 , blaOXA-24 , blaOXA-58, blaPER-1 , blaNDM , blaIMP and mcr-1 were screened...

OBJECTIVE: To describe overall survival (OS) and disease-free survival (DFS) in a cohort of tongue cancer patients, together with the corresponding demographic, tumor and surgical characteristics. METHODS: A retrospective study was made of 205 consecutive patients with primary tongue cancer subjected to surgery and adjuvant therapy according to the stage of the disease, in Hospital Clínico Universitario Virgen de la Arrixaca (HUVA) (Murcia, Spain) during the period 2000-2020...

Innovatively, we consider stomatal detection as rotated object detection and provide an end-to-end, batch, rotated, real-time stomatal density and aperture size intelligent detection and identification system, RotatedeStomataNet. Stomata acts as a pathway for air and water vapor in the course of respiration, transpiration, and other gas metabolism, so the stomata phenotype is important for plant growth and development. Intelligent detection of high-throughput stoma is a key issue. Nevertheless, currently available methods usually suffer from detection errors or cumbersome operations when facing densely and unevenly arranged stomata...

PURPOSE: To review all studies reporting the onset of white dot syndromes following COVID-19 vaccines. METHODS: Our protocol was registered prospectively on PROSPERO [registration number: CRD42023426012]. We searched five different databases including PubMed, Scopus, Web of Science, Google Scholar, and Science Direct up to May 2023. All the studies that reported the occurrence of white dot syndrome following COVID-19 vaccines were included. All statistical tests were conducted with a 95% confidence interval and a 5% error margin...

A charge detector has been constructed and mounted inside the vacuum housing of a commercial mass spectrometer (Micromass-Waters Quattro I, Waters Corp., Manchester, UK). The in-house built single-pass charge detector is composed of a designed, complete electronics system that includes a low-noise charge amplifier. Communication to the data acquisition system was enabled, and analog and digital filters were devised, followed by their tuning and programming. Data treatment scripts for data analysis and plotting were automated, and the assembled system was calibrated and tested...

In this work, a measurement setup to study the Seebeck and Nernst effect at high temperatures and high magnetic fields is introduced and discussed. The measurement system allows for simultaneous measurements of both thermoelectric effects up to 700 K and magnetic fields up to 12 T. Based on theoretical concepts, measurement equations are derived that counteract constant spurious offset voltages and, therefore, inhibit systematic errors in the measurement setup. The functionality is demonstrated on polycrystalline samples of elemental bismuth as well as various full-Heusler materials, exhibiting an anomalous Nernst effect...

The progress of research focused on cholangiocytes and the biliary tree during development and following injury is hindered by limited available quantitative methodologies. Current techniques include two-dimensional standard histological cell-counting approaches, which are rapidly performed error-prone and lack architectural context; or three-dimensional analysis of the biliary tree in opacified livers, which introduce technical issues along with minimal quantitation. The present study aims to fill these quantitative gaps with a supervised machine learning model (BiliQML) able to quantify biliary forms in the liver of anti-Keratin 19 antibody-stained whole slide images...