Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of Biosynthetic Controls as Performance Standards for Next-Generation Sequencing Assays of Somatic Tumors: A Multilaboratory Study.

BACKGROUND Next-generation sequencing (NGS) assays are highly complex tests that can vary substantially in both their design and intended application. Despite their innumerous advantages, NGS assays present some unique challenges associated with the preanalytical process, library preparation, data analysis, and reporting. According to a number of professional laboratory organization, control materials should be included both during the analytical validation phase and in routine clinical use to guarantee highly accurate results. The SeraseqTM Solid Tumor Mutation Mix AF10 and AF20 control materials consist of 26 biosynthetic DNA constructs in a genomic DNA background, each containing a specific variant or mutation of interest and an internal quality marker at 2 distinct allelic frequencies of 10% and 20%, respectively. The goal of this interlaboratory study was to evaluate the Seraseq AF10 and AF20 control materials by verifying their performance as control materials and by evaluating their ability to measure quality metrics essential to a clinical test. METHODS Performance characteristics were assessed within and between 6 CLIA-accredited laboratories and 1 research laboratory. RESULTS Most laboratories detected all 26 mutations of interest; however, some discrepancies involving the internal quality markers were observed. CONCLUSION This interlaboratory study showed that the Seraseq AF10 and AF20 control materials have high quality, stability, and genomic complexity in variant types that are well suited for assisting in NGS assay analytical validation and monitoring routine clinical applications.
Temperature Compensation of Solidly Mounted Bulk Acoustic Wave Resonators

This thesis introduces a novel way of temperature compensation of Bulk Acoustic Wave (BAW) resonators. By adding very thin (30-70nm) SiO2 layers at high stress regions within the resonator, temperature coefficients ranging from -10 ppm/˚C to +12ppm/˚C have been successfully demonstrated. With this method, it was possible to reach full temperature compensation of less than 1ppm/˚C with the use of only 32nm placed within 1180 nm of AlN. Thanks to this significant reduction in SiO2 thickness, more than 200% improvement in the coupling coefficient has been achieved over the current state of the art. The thermal properties of thin SiO2 layers have also been investigated and experimentally found to be different from their bulk corresponding values used in BAW literature. Experimental data suggests that temperature coefficient of elasticity of SiO2 decreases with thinner SiO2 layers.
Building Emotional Awareness and Mental Health (BEAM): A Pilot Randomized Controlled Trial of an App-Based Program for Mothers of Toddlers

Background Families have faced unprecedented challenges during the COVID-19 pandemic, leading to increased maternal mental health problems and barriers to accessing care. Innovative programs are needed to support both maternal mental health and parenting, and to buffer the long-term impacts of stress on young children. Using a patient-oriented approach, our research team aimed to co-develop and pilot test an App-based psychoeducation and social-connection platform: Building Emotional Awareness and Mental Health (BEAM). Methods The co-development process involved a parent advisory board from conceptualization and design, through to direct participation in the program delivery. The BEAM program includes weekly videos and activities based on Unified Protocol therapy modules and emotion-focused parenting strategies, a weekly telehealth group review session, and access to a private online forum for support from other mothers and clinical coaches. A parallel randomized control trial was conducted across two provinces in Canada. Mothers of preschool children (aged 18–36 months old), with moderate-to-severe depression (Patient Health Questionaire-9 ≥ 10), were recruited online and randomized to either the 10-week BEAM intervention or treatment as usual (TAU) control group. Online surveys (ensuring researcher blinding) included questions about feasibility and acceptability of the program and pre/post self-report measures of mental health, parenting, positive coping and child behavior outcomes. The primary outcome measures were symptoms of depression and parenting stress. Data were analyzed using mixed models and an intention-to-treat approach. Results 65 participants were randomized, by an online allocation tool, to the BEAM (n = 33) and TAU (n = 32) groups. Engagement was relatively high at the beginning of the program, with 78.8% starting the BEAM App and 70.6% attending ≥1 telehealth session. Most respondents felt socially supported, satisfied with the App, and found it easy to use. Pre-post results indicated interaction effects with greater reductions in overall mental health problems, and specifically anxiety and sleep symptoms, among BEAM vs. control participants. There were also time effects with reductions in depression symptoms across both groups. No significant treatment effects emerged for the other mental health symptoms, parenting problems, positive coping, or child behavior outcomes. Descriptive data are included to highlight possible areas of promise for future large efficacy trials. Technological difficulties and other challenges that may have led to attrition and impacted outcomes are discussed. There were no adverse events related to study participation. Conclusions The BEAM program has promise as a novel, feasible and acceptable intervention for improving mental health among mothers of young children. Clinical Trial Registration [www.ClinicalTrials. gov], identifier [NCT04772677].
An adaptive harmonic abatement in three-phase multilevel inverter topology with reduced switches using metaheuristic approaches for renewable energy applications

ABSTRACT Renewable energy sources like solar, wind, and fuel cell are the medium sources of energy to produce high output power. The power electronics conversion in the renewable energy system is the significant drawback of poor-quality output due to its harmonic content and switching losses due to its increasing number of switching components. This article proposes a novel three-phase Multilevel Inverter (MLI) topology based on a series-parallel switched multilevel dc-link inverter configuration with a reduced number of switches that minimize the lower-order harmonics 3rd, 5th, and 7th using Selective Harmonic Elimination (SHE) based on the Particle Swarm Optimization (PSO) algorithm. The configuration also engages the Artificial Neural Network (ANN) to provide optimum switching angles for varying input voltages over a period, as in the case of renewable energy applications. The output of the MLI and its harmonic profile are examined in the MATLAB/Simulink platform. The hardware results are proven with the Xilinx-based FPGA Nexys-4 board that generates discrete pulses to the switches.
Laser-Induced Forward Transfer of Silver Nanoparticles for a Black Metal Absorber

Plasmonic nanostructures emerged as an appealing approach for black metal absorbers (BMAs) to provide significant light absorption. We present the simple and rapid fabrication of BMAs using laser-induced forward transfer of silver nanoparticles (AgNPs). Randomly distributed plasmon silver nanostructures at a multiscale were produced simultaneously during laser transfer, providing significant light absorption and antireflection features. The laser-transferred BMAs exhibit excellent absorption capacity of a value over 96% and a minimum reflection of 0.38%. A high scanning speed of 10 m/s was used that can complete the laser-induced forward transfer (LIFT) process within 2 s for a 1 cm2 area. The nearfield light confinement is discussed in terms of the morphology of the obtained nanostructures. Photothermal conversion with macroscale temperature rising was demonstrated for the LIFT process is an effective method for the industrial production of BMAs with excellent absorption capacity.
Multi-Scale Attention-Based Mechanism in Gradient Boosting Convolutional Neural Network for Diabetic Retinopathy Grade Classification

: Diabetic Retinopathy (DR) is a common complication of Diabetes Mellitus (DM) that produces retinal abnormalities and can lead to blindness if not diagnosed and treated on time. To address this concern, an adaptive Convolutional Neural Network (CNN) model with Gradient Boosting (GB) called ResNetGB has been used from the literature where a Principal Component Analysis (PCA) based Fully Connected (FC) layer is used to capture the discriminative characteristics from the Retinal Fundus (RF) samples. It is essential to extract more effective features to categorize the DR grades. Hence, in this article, the Multi-Scale Attention (MSA) strategy is incorporated into the ResNetGB model for effective DR grade classification. First, the encoder network is used to embed the RF image in a high-level interpretational space in which the mixture of mid and high-level characteristics is considered to enhance the representation. Then, a Multi-Scale Feature Pyramid (MSFP) is added to define the retinal pattern in various localities and the MSA strategy is applied to the high-level interpretation. Moreover, the entire MSA-ResNetGB framework is trained by the cross-entropy loss to categorize the patients with respective DR grades. Finally, the experimental analysis exhibit that the MSA-ResNetGB model achieves the 94.40% and 94.17% accuracy on two benchmark datasets: Kaggle-APTOS and IDRiD, respectively compared to the cutting-edge models.
Airspace Dimension Assessment with Nanoparticles (AiDA) in Comparison to Established Pulmonary Function Tests

Background Airspace Dimensions Assessment with nanoparticles (AiDA) is a new method for non-invasive measurement of pulmonary distal airspaces. The aim of this study was to compare AiDA measurements with other pulmonary function variables to better understand the potential of AiDA in a clinical context. Methods AiDA measurements and pulmonary function tests were performed in 695 subjects as part of the Swedish CArdioPulmonary bioImage Study. The measurement protocol included spirometry, measurement of diffusing capacity of carbon monoxide, oscillometry and pulmonary computed tomography. AiDA indices were compared to all other pulmonary examination measurements using multivariate statistical analysis. Results Our results show that AiDA measurements were significantly correlated with other pulmonary function examination indices, although covariance was low. We found that AiDA variables explained variance in the data that other lung function variables only influenced to a minor extent. Conclusion We conclude that the AiDA method provides information about the lung that is inaccessible with more conventional lung function techniques.
Identification of Up-Regulated ANXA3 Resulting in Fracture Non-Union in Patients With T2DM

Diabetes mellitus is a metabolic disorder that increases fracture risk and interferes with bone formation and impairs fracture healing. Genomic studies on diabetes and fracture healing are lacking. We used a weighted co-expression network analysis (WGCNA) method to identify susceptibility modules and hub genes associated with T2DM and fracture healing. First, we downloaded the GSE95849, GSE93213, GSE93215, and GSE142786 data from the Gene Expression Omnibus (GEO) website, analyzed differential expression genes and constructed a WGCNA network. Second, we screened out 30 hub genes, which were found to be enriched in neutrophil activation, translational initiation, RAGE receptor binding, propanoate metabolism, and other pathways through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) analyses. Third, we searched for genes related to bone metabolism and fracture healing in the published genome-wide single nucleotide polymorphism (SNP) data, built a protein-protein interaction (PPI) network with hub genes, and found that they were associated with metabolic process, blood vessel development, and extracellular matrix organization. ANXA3 was identified as the biomarker based on gene expression and correlation analysis. And the AUC value of it was 0.947. Fourth, we explored that ANXA3 was associated with neutrophils in fracture healing process by single-cell RNA sequencing analysis. Finally, we collected clinical patient samples and verified the expression of ANXA3 by qRT-PCR in patents with T2DM and fracture non-union. In conclusion, this is the first genomics study on the effect of T2DM on fracture healing. Our study identified some characteristic modules and hub genes in the etiology of T2DM-associated fracture non-union, which may help to further investigate the molecular mechanisms. Up-regulated ANXA3 potentially contributed to fracture non-union in T2DM by mediating neutrophils. It can be a prognostic biomarker and potential therapeutic target.
Non-Lipid Effects of PCSK9 Monoclonal Antibodies on Vessel Wall

Elevated low density lipoprotein (LDL) cholesterol and lipoprotein(a) (Lp(a)) levels have an important role in the development and progression of atherosclerosis, followed by cardiovascular events. Besides statins and other lipid-modifying drugs, PCSK9 monoclonal antibodies are known to reduce hyperlipidemia. PCSK9 monoclonal antibodies decrease LDL cholesterol levels through inducing the upregulation of the LDL receptors and moderately decrease Lp(a) levels. In addition, PCSK9 monoclonal antibodies have shown non-lipid effects. PCSK9 monoclonal antibodies reduce platelet aggregation and activation, and increase platelet responsiveness to acetylsalicylic acid. Evolocumab as well as alirocumab decrease an incidence of venous thromboembolism, which is associated with the decrease of Lp(a) values. Besides interweaving in haemostasis, PCSK9 monoclonal antibodies play an important role in reducing the inflammation and improving the endothelial function. The aim of this review is to present the mechanisms of PCSK9 monoclonal antibodies on the aforementioned risk factors.
Boundary Outlier Centroid Based Reduced Overlapping Image Segmentation

This paper proposes a novel approach to image segmentation that integrates the improved K-means algorithm with Otsu Segmentation and Watershed algorithm. The conventional K-means algorithm is widely used for image segmentation because of its ease of use and small computation time, but has certain drawbacks such as strongly affected by outliers and may settle at the local minima, thereby leading to poor scaling. Similarly, the traditional watershed algorithm is widely used but has certain drawbacks such as over segmentation and high sensitivity. So the shortcomings of the conventional K-means algorithm and the hide-bound Watershed algorithm are addressed by integrating them such that better segmenting results are obtained. The proposed BOCRO algorithm utilises the combination of clustering algorithm with initial centroids by Centroid Calculation and Overlapping Reduction with Boundary Outliers and is efficient in terms of complexity and produces accurate results. It can be incorporated with a device to detect and segment images to obtain meaningful information.
The Existence Value of Brand Ambassadors: A Perspective study on Chinese Consumers

Aim/Purpose: This study aims to verify the existence of a significant perception difference between two consumer groups in China towards the use of celebrity endorsement. Background: Through an online questionnaire survey investigating 212 consumers across the Chinese market, this study found that there is no significant difference between these two groups’ perceptions towards celebrity endorsement, indicating an advanced way of understanding media coverage and public opinions in the Chinese market. Methodology: To better find out the perceptions of the newly targeted young consumers and the already existing middle-class customer base, it was necessary to collect quantitative data expressed in numbers. This was appropriate to cover a large number of samples across different areas in the Chinese market, and generalized knowledge could be achieved based on this. Primary data were collected by the author of this study through a self-administered online survey, in which every participant answered the questions without any intervention from the researcher from the beginning to the end. Findings: The non-existence of significant difference of the perceptions between premium brands’ newly targeted consumers, the young consumer group, and their already existing consumers, the middle-class consumer group, towards young entertainment star’s endorsement clearly answered the first research question, and, meanwhile, filled the research gap found and explained in the literature review. Impact on Society: This research demonstrated that the BMW China’s way of hiring a young entertainment star was actually wining on both sides. This celebrity endorsement successfully helped to attract young consumers’ attention and increased the brand exposure.
Potentiometric Performance of Ion-Selective Electrodes Based on Polyaniline and Chelating Agents: Detection of Fe2+ or Fe3+ Ions

We constructed a sensor for the determination of Fe2+ and/or Fe3+ ions that consists of a polyaniline layer as an ion-to-electron transducer; on top of it, chelating molecules are deposited (which can selectively chelate specific ions) and protected with a non-biofouling poly(2-methyl-2-oxazoline)s layer. We have shown that our potentiometric sensing layers show a rapid response to the presence of Fe2+ or Fe3+ ions, do not experience interference with other ions (such as Cu2+), and work in a biological environment in the presence of bovine serum albumin (as a model serum protein). The sensing layers detect iron ions in the concentration range from 5 nM to 50 µM.
The Research of Loop Closure Detection Algorithm Based on DeepLabv3+

Loop closure detection is the key step of simultaneous localization and mapping (SLAM), which is essential for building a consistent map. Traditional loop closure detection algorithms construct visual bag-of-words by extracting image features to detect whether loops occur. Aiming at the problem that traditional features are easily affected by the external environment and have no ability to understand the environment, a loop closure detection algorithm based on semantic segmentation is proposed. Firstly, perform semantic segmentation on the pre-trained DeepLabv3+ network of the query frame and the candidate frame image, cluster the segmentation results into semantic nodes to construct a semantic topology map, and calculate the similarity of the semantic topology map to measure the spatial similarity of the image. Then, the similarity of the appearance of the image is measured by calculating the similarity of the Hu matrix of each species of static object in the semantic segmentation results. Finally, the species, space and appearance similarity of static objects contained in the integrated image determine the overall similarity of the image for loop closure detection. Experiments show that compared with the traditional bag-of-words model method, the algorithm has more satisfactory performance.
Engineering Functional Vascularized Beige Adipose Tissue from Microvascular Fragments of Models of Healthy and Type II Diabetes Conditions

Engineered beige adipose tissues could be used for screening therapeutic strategies or as a direct treatment for obesity and metabolic disease. Microvascular fragments are vessel structures that can be directly isolated from adipose tissue and may contain cells capable of differentiation into thermogenic, or beige, adipocytes. In this study, culture conditions were investigated to engineer three-dimensional, vascularized functional beige adipose tissue using microvascular fragments isolated from both healthy animals and a model of type II diabetes (T2D). Vascularized beige adipose tissues were engineered and exhibited increased expression of beige adipose markers, enhanced function, and improved cellular respiration. While microvascular fragments isolated from both lean and diabetic models were able to generate functional tissues, differences were observed in regard to vessel assembly and tissue function. This study introduces an approach that could be employed to engineer vascularized beige adipose tissues from a single, potentially autologous source of cells.
Synergistic Effect of Nano-Silica and Micro-Silica Fillers on the Rheological and Thermal Properties of Epoxy Resins

This article aims to improve nanofiller dispersion in epoxy resins by using an electrostatic disperser (ED), as well as reduce costs by using a combination of microfillers and nanofillers. The ED method aids in homogenized mixing of nanofillers in epoxy resin, due to its jet elongation and shearing effect on a polymer mix. In this article, two concentrations (7.5 wt% and 5 wt%) of nanosilica are used with resin, and the rheological properties of hybrid composites are tested before and after the addition of 50 wt% microsilica. It is observed that the electrostatic dispersion method aids in the network formation of nanosilica, unlike the high shear (HS) method, wherein clusters of nanosilica are formed. Hence, the ED method aids in reducing the viscosity values with the addition of microsilica, which is helpful in the product molding process. A plausible mechanism of filler dispersion is explained for ED and HS methods. The morphological analysis showed that the composites are brittle due to the high silica content, and that the silica fillers are dispersed well within the epoxy matrix. The flexural strength lies in the same range for both composites prepared using ED and HS methods. Thermal conductivity depends both on nanosilica and epoxy matrix dispersion, while heat deflection temperature, thermal diffusivity and specific heat depend on the dispersion method.
The diurnal cycle of the lightning potential index over the Mexican tropical continental region during tropical cyclone Bud

Atmospheric processes over the Mexican continental territory can be influenced by the occurrence of tropical cyclones (TCs) over the adjacent oceans. Furthermore, the Mexican territory is characterized by the presence of diurnal cycles of lightning. The Lightning Potential Index (LPI), that is a measure of the potential for charge generation and separation that leads to lightning production in convective storms, was assessed for the diurnal variability of lightning that exhibited a strong diurnal cycle over the Mexican continental territory when TC Bud was over the adjacent eastern Pacific Ocean. The assessment, from 0000 UTC 10 June to 2000 UTC 15 June 2018, used the Weather Research and Forecasting (WRF) model with a new hybrid terrain‐following sigma‐pressure vertical coordinate. Two ensembles with various cumulus and microphysical parameterizations were performed with a grid spacing of 2 km. In one ensemble, sea surface temperature (SST) was prescribed from the Real‐time global (RTG) SST analysis product and allowed to evolve interactively with the modeled atmosphere. Then, all the ensemble members were compared against available observations from the World Wide Lightning Location Network (WWLLN) to evaluate which model configurations perform best. It is not known if the LPI is capable of reproducing diurnal cycles of lightning over tropical regions; and the results allow gaining an understanding of the LPI when it reproduces the observed diurnal variability of lightning over land. The ensemble members that had better performances were those that included the prescribed SST.