Dempseybengtsson5077

Shapelets are discriminative segments used to classify time-series instances. Shapelet methods that jointly learn both classifiers and shapelets have been studied in recent years because such methods provide both interpretable results and superior accuracy. The partial area under the receiver operating characteristic curve (pAUC) for a low range of false-positive rates (FPR) is an important performance measure for practical cases in industries such as medicine, manufacturing, and maintenance. In this article, we propose a method that jointly learns both shapelets and a classifier for pAUC optimization in any FPR range, including the full AUC. In addition, we propose the following two extensions for shapelet methods (1) reducing algorithmic complexity in time-series length to linear time and (2) explicitly determining the classes that shapelets tend to match. Comparing with state-of-the-art learning-based shapelet methods, we demonstrated the superiority of pAUC on UCR time-series data sets and its effectiveness in industrial case studies from medicine, manufacturing, and maintenance.Physics-based simulations are often used to model and understand complex physical systems in domains such as fluid dynamics. Such simulations, although used frequently, often suffer from inaccurate or incomplete representations either due to their high computational costs or due to lack of complete physical knowledge of the system. In such situations, it is useful to employ machine learning (ML) to fill the gap by learning a model of the complex physical process directly from simulation data. However, as data generation through simulations is costly, we need to develop models being cognizant of data paucity issues. In such scenarios, it is helpful if the rich physical knowledge of the application domain is incorporated in the architectural design of ML models. We can also use information from physics-based simulations to guide the learning process using aggregate supervision to favorably constrain the learning process. In this article, we propose PhyNet, a deep learning model using physics-guided structural priors and physics-guided aggregate supervision for modeling the drag forces acting on each particle in a computational fluid dynamics-discrete element method. We conduct extensive experiments in the context of drag force prediction and showcase the usefulness of including physics knowledge in our deep learning formulation. PhyNet has been compared with several state-of-the-art models and achieves a significant performance improvement of 7.09% on average. The source code has been made available*.Early diagnosis of autism spectrum disorder (ASD) is of paramount importance as it opens the road to early intervention, which is associated with better prognosis. However, early diagnosis is often delayed until preschool or school age. The purpose of the current retrospective study was to explore the age of recognition of first alarming symptoms in boys and girls as well as the age at diagnosis of different subtypes of ASD in a small sample. A total of 128 parents' of children with ASDs were participated in the survey by completing a self-report questionnaire about early signs and symptoms that raised their concern. Parents of children with autism voiced concerns earlier and obtained diagnosis significantly earlier compared to parents of children with Asperger syndrome (p value less then 0.000). No significant difference (p value less then 0.05) has been detected between males and females in early manifestation of first signs and symptoms of ASD. The mean age at diagnosis was 3.8 years for autistic disorder, 6.2 years for children with Asperger syndrome and 6.4 years for other, e.g., PDD-NOS. The most commonly reported symptoms were speech and language problems (p value = 0.001) for children who were later diagnosed with autism, while behavior problems (p value = 0.046) as well as difficulties in education at school (p value = 0.013) for children with Asperger syndrome. The gap between early identification and diagnosis pinpoints the urgent need for national systematic early screening, the development of reliable and sensitive diagnostic instruments for infants and toddlers and heightened awareness of early signs of ASD among parents, teachers, and healthcare professionals and providers as well.Aim To explore the circular RNA (circRNA) profile in cumulus cells from endometriosis-associated infertility patients. Methods The expression of circRNAs was profiled by high-throughput sequencing. Sanger sequencing was performed to identify the backsplicing site. Six candidate circRNAs and their parental genes were measured in 30 samples by quantitative reverse transcription-polymerase chainreaction (qRT-PCR). Bioinformatics analysis was performed to predict the functions. Results A total of 55 upregulated and 41 downregulated differentially expressed circRNAs were detected. Kyoto Encyclopedia of Genes and Genomes data indicated that these target genes were mainly involved in cumulus cell growth- and differentiation-related pathways. Hsa_circ_0072391, hsa_circ_0007299 and hsa_circ_0057799 were significantly increased, and hsa_circ_001533 was significantly decreased in endometriosis-associated infertility patients. Conclusion The differentially expressed circRNAs might be potentially involved in pathophysiology of endometriosis-associated infertility.

Traditional Kirschner wire (K-wire) stabilization of first metatarsal distal chevron osteotomy involves 1 cortex of fixation; however, unicortical fixation is associated with a high complication rate, including pin migration. A method of K-wire fixation utilizing 3 cortices may be biomechanically superior and potentially equivalent to single-screw fixation.

Cadaveric specimens fixed with tricortical K-wires were tested in both the physiologic and cantilever conditions against specimens fixed with unicortical K-wires (N = 8) and single screws (N = 9) utilizing matched-pair comparison groups. Differences in physiologic and cantilever fixed/intact stiffness ratio and cantilever failure load were determined.

The tricortical fixation specimens had a significantly higher stiffness ratio in cantilever loading than the unicortical fixation specimens (60.50% tricortical, 34.17% unicortical,

= .02) but not in physiologic load (15.34% tricortical, 25.75% unicortical,

= .23). In cantilever failure loading, the tricortical fixation specimens had a significantly higher load to failure than the unicortical fixation specimens (132.81 N tricortical, 58.58 N unicortical,

< .01). Stiffness ratio under physiologic load, cantilever load, and ultimate load to failure were not significantly different between tricortical K-wire and screw-fixation groups.

Tricortical K-wire fixation for distal chevron osteotomies is biomechanically superior to traditional unicortical K-wire fixation, and equivalent to single-screw fixation.

Level V Cadaver study.

Level V Cadaver study.Aim An advanced proteomics platform for protein biomarker discovery in diabetic chronic kidney disease (DKD) was developed, validated and implemented. Materials & methods Three Type 2 diabetes mellitus patients and three control subjects were enrolled. Urinary peptides were extracted, samples were analyzed on a hybrid LTQ-Orbitrap Velos Pro instrument. Raw data were searched using the SEQUEST algorithm and integrated into Proteome Discoverer platform. Results & discussion Unique peptide sequences, resulted sequence coverage, scoring of peptide spectrum matches were reported to albuminuria and databases. Five proteins that can be associated with early DKD were found apolipoprotein AI, neutrophil gelatinase-associated lipocalin, cytidine deaminase, S100-A8 and hemoglobin subunit delta. Conclusion Urinary proteome analysis could be used to evaluate mechanisms of pathogenesis of DKD.This is a single-center randomized open label active-controlled crossover trial comparing efficacy and safety of fast acting insulin aspart (FA) (FIASP®) versus insulin aspart (IAsp) (NovoLog®) when used in the Medtronic 670G system in auto mode in patients with type 1 diabetes. Forty patients were randomized to either IAsp or FA. Each treatment period was 7 weeks and a standardized meal test was administered 6 weeks after the start of each treatment period. The primary endpoint was postprandial glucose (PPG) increment after the meal test at 1 h. Treatment with FA using the MiniMed 670G hybrid closed loop (HCL) led to a greater reduction in 1-h postprandial glucose increase compared with treatment with IAsp during the standardized mixed meal test. Change in glucose [estimated treatment difference (ETD ± standard deviation [SD]); 95% confidence interval] 70.27 (±17.36) mg/dL (3.9 ± 1.0 mmol/L) with FA versus 98.42 (±17.36) mg/dL (5.5 ± 1.0 mmol/L) with IAsp (P = 0.008). Patients spent 1.81% (P = 0.016) more time (equivalent to 26 min per day) in the 70-180 mg/dL (3.89-9.99 mmol/L) range with FA than with IAsp. The entire sample spent only 0.5% of time less then 54 mg/dL ( less then 3.0 mmol/L) range. The increment in the 1 h postmeal test glucose was significantly lower with FA versus IAsp. FA in a HCL setting is safe and effective with patients spending more time in the 70-180 mg/dL (3.89-9.99 mmol/L) target range than with IAsp. Trial registration Clinicaltrials.gov identifier NCT03977727.

To determine the impact coronavirus disease of 2019 (COVID-19) will have on the 2020-2021 otolaryngology (OTO-HNS) resident application cycle.

A cross-sectional survey targeting OTO-HNS program directors (PD) was created and disseminated via email to PDs on May 28th 2020. Descriptive analyses of the 19-question survey was performed, and free text responses for certain suitable questions were thematically categorized into groups determined to be relevant during analysis.

Twenty-nine of 123 solicited PDs (23.6%) completed the survey. Nineteen (65.5%) respondents indicated they would not host away rotations (AR) in 2020, and 9 (31.0%) reported that they would consider away rotators without home programs. Regarding the historical importance of AR, 21 (72.4%) PDs stated they were either "extremely" or "very" important in evaluating candidates. Sixteen (55.2%) PDs stated that virtual interviews would impact their ability to properly gauge candidates and 12 (41.4%) were unsure. Eight PDs (27.6%) stated their e is expected to change.Interleukin-22 (IL-22), secreted by tumor infiltrated lymphocytes, is identified as a tumor-promoting factor in certain cancers, which was secreted by tumor infiltrated lymphocytes. However, the role of IL-22 in breast cancer remains conflicting. In this study, we assessed the expression of IL-22, IL-22 receptor 1 (IL-22R1), CD4, CD8, FOXP3, and CD68 in breast cancer by immunohistochemistry. IL-22 expression was exhibited in 105 (69.1%) cases in tumor cells (tIL-22), whereas only 24 (15.8%) samples displayed IL-22 expression in stromal cells. Multivariate analysis showed that tIL-22 expression was a poor prognostic factor for overall survival (OS) (p = 0.04). Meanwhile, IL-22R1 was predominantly presented in tumor cells (84.9%), which was associated with tIL-22 expression. Seladelpar The CD68-positive tumor-associated macrophages (TAMs) displayed the highest infiltration rate (50.7%) compared with CD4-, CD8-, and FOXP3-positive cells. Kaplan-Meier analysis confirmed patients with high TAM infiltration displayed significantly worse relapse-free survival (RFS) compared with low TAMs group (p = 0.