Miracle-dz/UniFAR-FTUs huggingface dataset:
A Wide Tuning Range Dual-Core Quad-Mode Orthogonal-Coupled VCO With Concurrently Dual-Output Using Parallel 8-Shaped Resonator

This article presents a dual-core quad-mode orthogonal-coupled wide frequency tuning range voltage-controlled oscillator (VCO) using mode control switches to realize the even/odd mode selection. Each core of the VCO adopts a parallel 8-shaped coil structure to avoid the influence of the other orthogonal-coupled one. Together with capacitor banks and varactors, the combination of orthogonal-coupled VCO cores demonstrates an extremely wide frequency tuning range on the basis of the existing range expanding from the dual-mode. The proposed VCO can be classified into two cases with different applications. One is that only one oscillation frequency is required; thus, four modes together show a wide frequency range. The other is that two different oscillation signals can be provided at the same time. The VCO has a measured tuning range of 8.3–21.7 GHz for the combination of low- and high-band cores. It consumes 4–6 mW with a measured phase noise of −127 dBc/Hz at a 10-MHz offset from a carrier of 9.6 GHz, and the FoM and FoMT are −179 and −199 dBc/Hz, respectively. The VCO is designed and implemented in the 65-nm complementary metal-oxide-semiconductor (CMOS) technology with a die area of 0.4 mm2.
Non-intrusive measurement of internal pressure and flow in pipelines using fiber Bragg grating

In this paper we propose and demonstrate a non-intrusive measurement method for internal pressure and water flow in hydraulic pipeline systems. Fiber Bragg Gratings are used to measure deformations in the external side of pipes under different working conditions for two different experiments. In the first experiment a PVC sewerage pipeline with a diameter of 90 mm was subjected to a variable air pressures up to 4 bars; in the second a PVC sewerage pipeline with a diameter of 32 mm was subjected to a water flow between 10 and 35 liters per minute.
GOLM1 and FAM49B: Potential Biomarkers in HNSCC Based on Bioinformatics and Immunohistochemical Analysis

Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers worldwide. We aimed to identify potential genetic markers that could predict the prognosis of HNSCC. A total of 44 samples of GSE83519 from Gene Expression Omnibus (GEO) datasets and 546 samples of HNSCC from The Cancer Genome Atlas (TCGA) were adopted. The differently expressed genes (DEGs) of the samples were screened by GEO2R. We integrated the expression information of DEGs with clinical data from GES42743 using the weighted gene co-expression network analysis (WGCNA). A total of 17 hub genes were selected by the module membership (|MM| > 0.8), and the gene significance (|GS| > 0.3) was selected from the turquoise module. GOLM1 and FAM49B genes were chosen based on single-gene analysis results. Survival analysis showed that the higher expression of GOLM1 and FAM49B genes was correlated with a worse prognosis of HNSCC patients. Immunohistochemistry and multiplex immunofluorescence techniques verified that GOLM1 and FAM49B genes were highly expressed in HNSCC cells, and high expressions of GOLM1 were associated with the pathological grades of HNSCC. In conclusion, our study illustrated a new insight that GOLM1 and FAM49B genes might be used as potential biomarkers to determine the development of HNSCC, while GOLM1 and FAM49B have the possibility to be prognostic indicators for HNSCC.
Telecom Churn Prediction using Machine Learning

In every industry, customers are crucial. Customer churn can have a variety of effects and have a negative influence on sales. Analysis and forecasting of customer turnover must be a key component of any business. We will analyze and forecast customer turnover in the telecom industry in our study. The study of consumer behavior is crucial for the telecommunications sector in order to identify those customers who are most likely to cancel their subscriptions. Because there is so much data available and the market is becoming more competitive, businesses are spending more time trying to keep their present consumers than they are trying to win over new ones. The mobile telecommunications market recently transitioned from being one that was expanding quickly to one that was saturated. The goal of telecom companies is to refocus their attention away from attracting new, huge customers and toward retaining existing ones. Knowing which clients are likely to switch to a competitor in the future is important for this reason. Using machine learning techniques such as Decision Tree, Logistic Regression, Random Forest, Gradient Boosted Machine Tree, and Extreme Gradient Boosting, the model is proposed for churn analysis and prediction for telecommunication firms. The performance of various models is also compared. On the basis of the supplied dataset, comparisons are made on the algorithm’s effectiveness.
Th2 high and mast cell gene signatures are associated with corticosteroid sensitivity in COPD

Rationale Severe asthma and chronic obstructive pulmonary disease (COPD) share common pathophysiological traits such as relative corticosteroid insensitivity. We recently published three transcriptome-associated clusters (TACs) using hierarchical analysis of the sputum transcriptome in asthmatics from the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) cohort comprising one Th2-high inflammatory signature (TAC1) and two Th2-low signatures (TAC2 and TAC3). Objective We examined whether gene expression signatures obtained in asthma can be used to identify the subgroup of patients with COPD with steroid sensitivity. Methods Using gene set variation analysis, we examined the distribution and enrichment scores (ES) of the 3 TACs in the transcriptome of bronchial biopsies from 46 patients who participated in the Groningen Leiden Universities Corticosteroids in Obstructive Lung Disease COPD study that received 30 months of treatment with inhaled corticosteroids (ICS) with and without an added long-acting β-agonist (LABA). The identified signatures were then associated with longitudinal clinical variables after treatment. Differential gene expression and cellular convolution were used to define key regulated genes and cell types. Measurements and main results Bronchial biopsies in patients with COPD at baseline showed a wide range of expression of the 3 TAC signatures. After ICS±LABA treatment, the ES of TAC1 was significantly reduced at 30 months, but those of TAC2 and TAC3 were unaffected. A corticosteroid-sensitive TAC1 signature was developed from the TAC1 ICS-responsive genes. This signature consisted of mast cell-specific genes identified by single-cell RNA-sequencing and positively correlated with bronchial biopsy mast cell numbers following ICS±LABA. Baseline levels of gene transcription correlated with the change in RV/TLC %predicted following 30-month ICS±LABA. Conclusion Sputum-derived transcriptomic signatures from an asthma cohort can be recapitulated in bronchial biopsies of patients with COPD and identified a signature of airway mast cells as a predictor of corticosteroid responsiveness.
Photothermal detection of local thermal effects during selective nanophotothermolysis

Photothermal (PT) technique was applied to the detection of laser-induced local thermal effects around absorbing nanoparticles into cells. The experiments demonstrated the capability of this technique for studying the threshold and the dynamic of thermal events around even a single particle in a broad temperature range, including monitoring of microbubble dynamic. PT technique shows promise for optimizing cancer-cell killing by incorporation of gold nanoparticles into the cells (selective “nanophotothermolysis”), as verified by electron microscopy and conventional viability tests.
Goodness‐of‐fit test for a parametric mixture cure model with partly interval‐censored data

Partly interval‐censored event time data arise naturally in medical, biological, sociological and demographic studies. In practice, some patients may be immune from the event of interest, invoking a cure model for survival analysis. Choosing an appropriate parametric distribution for the failure time of susceptible patients is an important step to fully structure the mixture cure model. In the literature, goodness‐of‐fit tests for survival models are usually restricted to uncensored or right‐censored data. We fill in this gap by proposing a new goodness‐of‐fit test dealing with partly interval‐censored data under mixture cure models. Specifically, we investigate whether a parametric distribution can fit the susceptible part by using a Cramér‐von Mises type of test, and establish the asymptotic distribution of the test . Empirically, the critical value is determined from the bootstrap resamples. The proposed test, compared to the traditional leveraged bootstrap approach, yields superior practical results under various settings in extensive simulation studies. Two clinical data sets are analyzed to illustrate our method.
Evaluation of data-driven respiratory gating for subcentimeter lesions using digital PET/CT system and three-axis motion phantom

Introduction. The application of data-driven respiratory gating (DDG) for subcentimeter lesions with respiratory movement remains poorly understood. Hence, this study aimed to clarify DDG application for subcentimeter lesions and the ability of digital Positron emission tomography/computed tomography (PET/CT) system combined with DDG to detect these lesions under three-axis respiration. Methods. Discovery MI PET/CT system and National Electrical Manufacturers Association (NEMA) body phantom with Micro Hollow Sphere (4, 5, 6, 8, 10, and 13 mm) were used. The NEMA phantom was filled with 18F-FDG solutions of 42.4 and 5.3 kBq/ml for each hot sphere and background region. The 3.6 s cycles of three-axis respiratory motion were reproduced using the motion platform UniTraQ. The PET data acquisition was performed in stationary and respiratory-moving states. The data were reconstructed in three PET groups: stationary (NM-PET), no gating with respiratory movement (NG-PET), and DDG gating with respiratory movement (DDG-PET) groups. For image quality, percent contrast (QH); maximum, peak, and mean standardized uptake value (SUV); background region; and detectability index (DI) were evaluated in each PET group. Visual assessment was also conducted. Results. The groups with respiratory movement had deteriorated QH and SUVs compared with NM-PET. Compared with NG-PET, DDG-PET has significantly improved QH and SUVs in spheres above 6 mm. The background region showed no significant difference between groups. The SUVmax, SUVpeak, and QH values of 8 mm sphere were highest in NM-PET, followed by DDG-PET and NG-PET. In visual assessment, the spheres above 6 mm were detected in all PET groups. DDG application did not detect new lesions, but it increased DI and visual score. Conclusions. The application of principal component analysis (PCA)-based DDG algorithm improves both image quality and quantitative SUVs in subcentimeter lesions measuring above 6 mm. Although DDG application cannot detect new subcentimeter lesions, it increases the visual indices.
Jointly Learning Multiple Perceptual Similarities

Perceptual similarity between objects is multi-faceted and it is easier to judge similarity when the focus is on a specific aspect. We consider the problem of mapping objects into view specific embeddings where the distance between them is consistent with the similarity comparisons of the form "from the t-th perspective, object A is more similar to B than to C". Our framework jointly learns view specific embeddings and can exploit correlations between views if they exist. Experiments on a number of datasets, including a large dataset of multi-view crowdsourced comparison on bird images, show the proposed method achieves lower triplet generalization error and better grouping of classes in most cases, when compared to learning embeddings independently for each view. The improvements are especially large in the realistic setting when there is limited triplet data for each view.
The role of next‐generation sequencing in the examination of signaling genes in Brca1/2‐negative breast cancer cases

Breast cancer is the most prevalent malignancy in women worldwide. Although pathogenic variants in the BRCA1/2 genes are responsible for the majority of hereditary breast cancer cases, a substantial proportion of patients are negative for pathogenic variations in these genes. In cancers, the signal transduction pathways of the cell are usually affected first. Therefore, this study aimed to detect and classified genetic variations in non‐BRCA signaling genes and investigate the underlying genetic causes of susceptibility to breast cancer.
Roles of Drizzle in a One-Dimensional Third-Order Turbulence Closure Model of the Nocturnal Stratus-Topped Marine Boundary Layer.

Abstract This study focuses on the effects of drizzle in a one-dimensional third-order turbulence closure model of the nocturnal stratus-topped marine boundary layer. When the simulated drizzle rate is relatively small (maximum ∼0.6 mm day−1), steady-state solutions are obtained. The boundary layer stabilizes essentially because drizzle causes evaporative cooling of the subcloud layer. This stabilization considerably reduces the buoyancy flux and turbulence kinetic energy below the stratus cloud. Thus, drizzle tends to decouple the cloud from the subcloud layer in the model, as suggested by many observational studies. In addition, the evaporation of drizzle in the subcloud layer creates small scattered clouds, which are likely to represent cumulus clouds, below the solid stratus cloud in the model. The sensitivity experiments show that these scattered clouds help maintain a coupled boundary layer. When the drizzle rate is relatively large (maximum ∼0.9 mm day−1), the response of the model becomes transien.
Noise removal methods for high resolution MRI

It is well-known that the noise in magnetic resonance images obeys a Rician distribution. Unlike additive Gaussian noise, Rician noise is signal-dependent and consequently separating signal from noise is a difficult task. Rician noise is especially problematic in high resolution low signal-to-noise ration regimes where it not only causes random fluctuations, but also introduces a signal-dependent bias to the data that reduces image contrast. This paper reports on a novel wavelet-domain filter that removes Rician noise contamination in MR images. The new method is especially well-suited for high-resolution, low SNR imaging.
Increasing Consumption of Korean Dramas during the COVID-19 Pandemic

This qualitative study focuses on Indonesian transnational fans’ consumption of Korean dramas (hereafter K-dramas) during the COVID-19 pandemic. This study highlights the fans’ lived experiences, thoughts, and interpretation of Korean culture in watching K-dramas as well as how they construct identities through their consumption and articulation in their everyday lives. This study used qualitative questionnaire as the instrument to collect the data for the study. Using thematic analysis, the study reveals that there were four emerging motivating factors to watch K-Dramas among Indonesian viewers: fresh substitutive choice, easy access, interesting stories and visuals, and cultural factors. Additionally, the study also showed four outcomes of their consumptive behavior: language acquisition and motivation to learn Korean, cultural understanding and new perceptions of Korea, pursuit of education, and pure entertainment and stress-reliever. Hence, this study contributes to the body of literature on K-Dramas consumption, especially in the era of COVID-19 pandemic.
Sex, Age, and Regional Differences in CHRM1 and CHRM3 Genes Expression Levels in the Human Brain Biopsies: Potential Targets for Alzheimer's Disease-related Sleep Disturbances

Background Cholinergic hypofunction and sleep disturbance are hallmarks of Alzheimer’s disease (AD), a progressive disorder leading to neuronal deterioration. Muscarinic acetylcholine receptors (M1-5 or mAChRs), expressed in hippocampus and cerebral cortex, play a pivotal role in the aberrant alterations of cognitive processing, memory, and learning, observed in AD. Recent evidence shows that two mAChRs, M1 and M3, encoded by CHRM1 and CHRM3 genes, respectively, are involved in sleep functions and, peculiarly, in rapid eye movement (REM) sleep. Methods We used twenty microarray datasets extrapolated from post-mortem brain tissue of non-demented healthy controls (NDHC) and AD patients to examine the expression profile of CHRM1 and CHRM3 genes. Samples were from eight brain regions and stratified according to age and sex. Results CHRM1 and CHRM3 expression levels were significantly reduced in AD compared with age- and sex-matched NDHC brains. A negative correlation with age emerged for both CHRM1 and CHRM3 in NDHC but not in AD brains. Notably, a marked positive correlation was also revealed between the neurogranin (NRGN) and both CHRM1 and CHRM3 genes. These associations were modulated by sex. Accordingly, in the temporal and occipital regions of NDHC subjects, males expressed higher levels of CHRM1 and CHRM3, respectively, than females. In AD patients, males expressed higher levels of CHRM1 and CHRM3 in the temporal and frontal regions, respectively, than females. Conclusion Thus, substantial differences, all strictly linked to the brain region analyzed, age, and sex, exist in CHRM1 and CHRM3 brain levels both in NDHC subjects and in AD patients.
Exploring the Potential Mechanism of Danshen in the Treatment of Concurrent Ischemic Heart Disease and Depression Using Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation

Objective: This study aimed to explore the potential targets and mechanism of action of Danshen in treating concurrent ischemic heart disease (IHD) and depression using network pharmacology, molecular docking, and molecular dynamics simulation (MDS). Methods: The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was used to obtain active ingredients and targets of Danshen. Candidate targets for IHD and depression were obtained from the Genecards and DisGeNet databases. The protein–protein interaction (PPI) network was constructed using the STRING database and the Cytoscape 3.8. 2 software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the Metascape database and the GlueGO package of the Cytoscape 3.8. 2 software. Molecular docking was performed using Autodock 1.5. 6 and Vina, and the MDS was completed using GROMACS 5.1. 2. Results: We obtained 65 active ingredients of Danshen with 131 candidate targets and 39 intersection targets of the active ingredients and diseases. Luteolin, tanshinone IIA, and salviolone were the core active ingredients, and AKT1, TNF, IL-6, MMP9, CASP3, IL-10, PTGS2, STAT3, PPARG, IL-4, EGFR, MAPK14, NOS3, and EDN1 were the core targets. The GO and KEGG pathway enrichment analyses revealed that the intersection targets were mainly enriched in positive regulation of protein phosphorylation, blood circulation, IL-17 signaling pathway, VEGF signaling pathway, and JAK/STAT signaling pathway. The molecular docking revealed that the core active ingredients had a good affinity for the core targets. The results of MDS revealed that the protein-ligand complexes were stable. Conclusions: This study used network pharmacology to analyze the potential mechanism of action of Danshen in the treatment of concurrent IHD and depression. Additionally, the study provided a theoretical basis for further studying the pharmacological mechanisms and targets of Danshen.
Moving-Target Defense in Depth: Pervasive Self- and Situation-Aware VM Mobilization across Federated Clouds in Presence of Active Attacks

Federated clouds are interconnected cooperative cloud infrastructures offering vast hosting capabilities, smooth workload migration and enhanced reliability. However, recent devastating attacks on such clouds have shown that such features come with serious security challenges. The oblivious heterogeneous construction, management, and policies employed in federated clouds open the door for attackers to induce conflicts to facilitate pervasive coordinated attacks. In this paper, we present a novel proactive defense that aims to increase attacker uncertainty and complicate target tracking, a critical step for successful coordinated attacks. The presented systemic approach acts as a VM management platform with an intrinsic multidimensional hierarchical attack representation model (HARM) guiding a dynamic, self and situation-aware VM live-migration for moving-target defense (MtD). The proposed system managed to achieve the proposed goals in a resource-, energy-, and cost-efficient manner.
A simple method for the preparation of CeO2 with high antioxidant activity and wide application range

Cerium oxide (CeO2) is a well-known antioxidant with the ability to scavenge reactive oxygen species due to its unique electronic structure and chemical properties. Although many methods to enhance the antioxidant activity of CeO2 have been reported, its antioxidant activity is still not high enough, and some enhancement effects are limited by the material concentration. There are also some CeO2 obtained with high antioxidant activity at high concentrations, which is not conducive to the application of biomedicine. Therefore, it is urgent to obtain CeO2 material with low cell cytotoxicity, high antioxidant activity and wide application range. In this work, rod-like metal organic framework derived CeO2 (CeO2-MOF) was prepared by a simple method. Compared with the CeO2 nanorods prepared by hydrothermal method, it shows better antioxidant activity compared with the CeO2 nanorods prepared by hydrothermal method. Moreover, the advantage of CeO2-MOF’s antioxidant activity is not affected by the hydroxyl radical and material concentrations The reason why CeO2-MOF has higher antioxidant activity should be attributed to its higher Ce3+ content and larger specific surface area. In addition, CeO2-MOF also exhibits low cytotoxicity to HeLa cells and PC12 cells in vitro. The strategy of using MOF as a structural and compositional material to create CeO2 provides a new method to explore highly efficient and biocompatible CeO2 for practical applications.
The Growing Dictionary of the Slovenian Language (2014-) and Slovenian Neologisms: Study on Types of Data and Their Use

The article aims at presenting the methods of detection of Slovenian neologisms, used in the making of the Growing Dictionary of the Slovenian Language, accessible at the Fran portal , which integrates various dictionaries into a single whole, form 2014 onwards. In the first year of compiling and for the following few years, the main source of the candidates was corpus Gigafida 1.0, built in 2013. Due to the corpus not being updated regularly (and unavailability of other appropriate sources), users’ suggestions have taken over the main role. Users submit suggestions directly on the Fran portal. The corpus Gigafida and other (Janes, SlWaC) are still used for checking users’ suggestions. Due to a high number of such suggestions and a growing demand for new lexical descriptions, their importance cannot be overlooked. The neologisms collected in the dictionary exhibit a number of characteristics, a brief overview of which is provided at the end of the study.
Saliency map based active contour method for automatic image segmentation

In this paper, we present a novel automatic image segmentation method, which combines the active contour method and the saliency map method. The saliency map which is obtained by inversing the spectral residual of the image brings a priori knowledge to bear on the image segmentation. The initial level set function is constructed from saliency map. In this way, an automatic initialization of the level set evolution can be obtained. This method can minimize the iterations of the level set evolution. The efficiency and accuracy of the method are demonstrated by the experiments on the synthetic and real images.