Miracle-dz/UniFAR-FTUs huggingface dataset:
Magnetically Assisted Immobilization-Free Detection of microRNAs Based on the Signal Amplification of Duplex-Specific Nuclease

The double specific nuclease (DSN)-based methods for microRNAs (miRNAs) detection usually require the immobilization of DNA probes on a solid surface. However, such strategies have the drawbacks of low hybridization and cleavage efficiency caused by steric hindrance effect and high salt concentration on the solid surface. Herein, we proposed an immobilization-free method for miRNA detection on the basic of DSN-assisted signal amplification. The biotin- and fluorophore-labeled probes were captured by streptavidin-modified magnetic beads through streptavidin–biotin interactions, thus producing a poor fluorescence signal. Once the DNA probes were hybridized with target miRNA in solution to form DNA-miRNA duplexes, DNA stands in the duplexes would be selectively digested by DSN. The released target miRNA could initiate the next hybridization/cleavage recycling in the homogeneous solution, finally resulting in the release of numerous fluorophore-labeled fragments. The released fluorophores remained in solution and emitted strong fluorescence after treatment by the streptavidin-modified magnetic beads. The immobilization-free method achieved the assays of miRNA-21 with a detection limit down to 0.01 pM. It was employed to evaluate the expression levels of miRNA-21 in different cancer cells with satisfactory results.
Comparison of Sieve Sampling with Random and Cell Sampling of Monetary Units

Sieve sampling has been proposed as a method of selecting a sample of monetary units in auditing. The primary purpose of this paper is to compare sieve sampling with random and cell sampling of monetary units in terms of the behavior of the Stringer and cell bounds for two methods of assigning errors to the constituent monetary units of a line item. A simulation study based on two actual accounting populations was conducted
Magnetic Beads inside Droplets for Agitation and Splitting Manipulation by Utilizing a Magnetically Actuated Platform

We successfully developed a platform for the magnetic manipulation of droplets containing magnetic beads and examined the washing behaviors of the droplets, including droplet transportation, magnetic bead agitation inside droplets, and separation from parent droplets. Magnetic field gradients were produced with two layers of 6 × 1 planar coils fabricated by using printed circuit board technology. We performed theoretical analyses to understand the characteristics of the coils and successfully predicted the magnetic field and thermal temperature of a single coil. We then investigated experimentally the agitation and splitting kinetics of the magnetic beads inside droplets and experimentally observed the washing performance in different neck-shaped gaps. The performance of the washing process was evaluated by measuring both the particle loss ratio and the optical density. The findings of this work will be used to design a magnetic-actuated droplet platform, which will separate magnetic beads from their parent droplets and enhance washing performance. We hope that this study will provide digital microfluidics for application in point-of-care testing. The developed microchip will be of great benefit for genetic analysis and infectious disease detection in the future.
Effectiveness of four home oral care products
for primary enamel re-mineralization with early
carious lesion: an in-vitro study

Introduction: Management of dental caries during early stages is considered a clinical problem in young children. Objectives: The current in-vitro study assessed the influence of four home oral care products on re-mineraliza-tion of early caries lesions using enamel micro-hardness (EMH) test and morphological changes with scanning electron microscopy (SEM). Material and methods: Sixty primary canine teeth were selected and randomly divided into 5 groups ( n = 12 in each group). Samples were de-mineralized, and toothpaste slurries were prepared to treat de-mineralized enamel with a pH-cycling model. The groups were divided as follows: Group 1. Control (no intervention); Group 2. Fluo ridated toothpaste; Group 3. Tooth mousse containing casein phosphopeptide-amorphous calcium phosphate (CPP-ACP); Group 4. Toothpaste containing bio-active glass and fluoride; Group 5. Tooth cream containing nano-hydroxyapatite, fluoride, and xylitol. EMH was evaluated in fifty specimens (each group, n = 10) at three times: before and after de-mineralization, and after 28 days of pH-cycling and treatment. Two samples from each group were observed with SEM. Data were analyzed with multiple-sample repeated measures ANOVA and Tukey’s HSD post-hoc tests ( p < 0.05). Results: There was a significant difference in EMH between mean baseline values and de-mineralized enamel ( p < 0.001). Re-mineralization significantly increased EMH in all treatment groups ( p < 0.001). In group 5, the percent of EMH recovery was significantly greater than in other groups ( p < 0.001). There were significant differences among the other three treatment groups (all p < 0.001). SEM images showed minerals deposited on the dissolved prismatic enamel in all groups. Conclusions: The nano-hydroxyapatite-based tooth cream was the most effective home oral care product for re-mineralization of primary tooth enamel.
Modeling Urban Precipitation Modification by Spatially Heterogeneous Aerosols

AbstractThis study introduces a methodology to simulate how spatially heterogeneous urban aerosols modify a precipitating thunderstorm in a numerical weather model. An air quality model (simple photochemical model) was coupled with a high-resolution mesoscale weather model (the Regional Atmospheric Modeling System) and generated variable urban cloud condensation nuclei values consistent with those measured in previous field studies. The coupled emission model was used to simulate the passage of a synoptic low pressure system with embedded thunderstorms over an idealized city using the real-atmosphere idealized land surface (RAIL) method. Experiments were conducted to calibrate the surface formation of cloud-nucleating aerosols in an urban environment and then to assess the specific response of different aerosol loads on simulated precipitation. The model response to aerosol heterogeneity reduced the total precipitation but significantly increased simulated rain rates. High-aerosol-loading scenarios produc.
Expectancy-Value Motivation and Physical Activity- and Health-Related Outcomes among At-Risk Children and Adolescents

Despite a large amount of research having been done to examine and promote physical activity and health among adolescents and children, relatively little attention has been paid attention to underrepresented populations. In this study, we investigated the relationships between expectancy-value motivation and physical activity- and health-related outcomes among a group of at-risk boys at a summer sports camp. The total participants included 107 boys (Mage = 11.78 years, SD = 1.20). The boys’ perceived expectancy beliefs (EXP), importance (IMP), interest (INT), usefulness (USE), effort (EFT), and intention for future participation (IFP) were assessed using established questions on a five-point Likert scale, and a PACER test was performed to estimate their cardiovascular fitness (CVF). Through a path analysis, we found that EXP positively predicted CVF (β = 0.19, p < 0.01), IMP positively predicted EFT (β = 0.26, p < 0.01), and INT positively predicted both EFT (β = 0.34, p < 0.01) and IFP (β = 0.28, p < 0.01), while USE had no statistically significant effect on either EFT, IFP, or CVF. We discussed the limitations and implications of the present study. We recommend including a diverse sample and employing the expectancy-value model in future research, and advocating expectancy beliefs and task values, especially importance and interest, among participants during physical activity promotion.
Axonal spike initiation can be maintained with low axonal Na channel density, but temporal precision of spiking is lost

In central neurons, action potentials (APs) originate in the axon initial segment (AIS) presumably due to its high concentration of voltage-dependent sodium (NaV) channels. In the AIS, NaV and their cytoskeletal anchoring proteins display a highly periodical nanoscale arrangement with unknown functional relevance. In mouse hippocampal neurons, we examined a mutation of the AIS-specific protein $\beta$IV-spectrin and assessed AP initiation locus, AIS molecular organization, and the precision of in vivo-like AP encoding. In mutants, NaV concentration was strongly reduced in AIS but not soma, while AIS nanoscale organization was preserved. Surprisingly, APs still originated in the axon, even if the axonal channel density was as low as in the somatic membrane. However, the timing of those APs was less precise, therefore the neuron's encoding bandwidth was substantially decreased. Therefore, the high NaV density in the AIS is not required for axonal AP initiation, it is crucial for AP timing precision.
Semiparametric Estimation of Distribution Algorithms for Continuous Optimization

—Traditional estimation of distribution algorithms (EDAs) often use Gaussian densities to optimize continuous functions, such as the estimation of Gaussian network algorithms (EGNAs) which use Gaussian Bayesian networks (GBNs). However, this assumes a parametric density function, and, in GBNs, linear dependencies between variables. Furthermore, the EGNA baseline learns a GBN at each iteration based on the best individuals in the last iteration, which may lead to local optimum convergence or large variance between solutions across multiple independent runs of the algorithm. In this work we propose a semiparametric EDA in which the restriction of assuming Gaussianity in the variables is relaxed using semiparametric Bayesian networks, in which nodes estimated by kernels coexist with nodes that assume Gaussianity, and the algorithm itself is able to determine where to use each type of node. Additionally, our approach takes into account information from several past iterations to learn the semiparametric Bayesian network from which the new solutions are sampled in each iteration. The empirical results show that semiparametric EDAs are a useful tool for continuous scenarios compared to different kinds of EDAs and other optimization techniques in continuous environments.
SOCS1 as a Biomarker Candidate for HPV Infection and Prognosis of Head and Neck Squamous Cell Carcinomas

The pathogenesis of head and neck squamous cell carcinoma (HNSCC) is associated with human papillomavirus (HPV) infection. However, the molecular mechanisms underlying the interactions between HNSCC and HPV remain unclear. Bioinformatics was used to analyze the gene expression dataset of HPV-associated HNSCC based on the Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) in HPV-positive and HPV-negative HNSCC were screened. Gene function enrichment, protein–protein interactions (PPI), survival analysis, and immune cell infiltration of DEGs were performed. Furthermore, the clinical data of HNSCC tissue samples were analyzed using immunohistochemistry. In total, 194 DEGs were identified. A PPI network was constructed and 10 hub genes (EREG, PLCG1, ERBB4, HBEGF, ZFP42, CBX6, NFKBIA, SOCS1, ATP2B2, and CEND1) were identified. Survival analysis indicated that low expression of SOCS1 was associated with worse overall survival. Immunohistochemistry demonstrated that SOCS1 expression was higher in HPV-negative HNSCC than in HPV-positive HNSCC, and there was a positive correlation between SOCS1 expression and patient survival. This study provides new information on biological targets that may be relevant to the molecular mechanisms underpinning the occurrence and development of HNSCC. SOCS1 may play an important role in the interaction between HPV and HNSCC and serve as a potential biomarker for future therapeutic targets.
Driving Style Classification and the Effectiveness of Advanced Driving Assistance Systems: Differences between Teen and Adult Drivers

Advanced driving assistance systems (ADAS) are designed to reduce potential crash risks and enhance driving safety. However, drivers’ interactions with ADAS may vary depending on their individual driving styles and characteristics. This study proposes a novel approach to classifying driving styles and explores how age and gender affect interactions with ADAS. The study utilized two naturalistic driving data sets comprising 148 drivers from four age groups: teens; younger adults; middle-aged adults; and older adults. Data were collected during two periods: baseline (without ADAS); and treatment (with ADAS). First, the K-means clustering algorithm was employed to divide trips into one conservative and two aggressive groups based on three driving behavior metrics: tailgating; speeding; and lane-changing. The aggressive-trip ratios were then calculated for each driver during each of the two periods. The Bayesian Gaussian mixture model was applied to determine the threshold values of the aggressive-trip ratios to classify drivers as conservative, moderate, or aggressive during each period. This allowed for identifying changes in driving style upon the activation of ADAS. The subsequent multinomial logistic regression model results showed that driving styles vary across age groups, with teens being the most aggressive drivers. Certain changes in driving style were observed, with some conservative drivers becoming aggressive or moderate and some aggressive drivers becoming conservative or moderate, but these differences were statistically non-significant. The findings of this study indicate that warning-based ADAS may not elicit significant changes in driving style, particularly among teenage drivers who are consistently the most aggressive drivers.
Tutorial – applying extreme value theory to characterize food‐processing systems

This tutorial presents extreme value theory (EVT) as an analytical tool in process characterization and shows its potential to describe production performance, eg, across different factories, via reliable estimates of the frequency and scale of extreme events. Two alternative EVT methods are discussed: point over threshold and block maxima. We illustrate the theoretical framework for EVT by process data from two different examples from the food‐processing industry. Finally, we discuss limitations, decisions, and possibilities when applying EVT for process data.
Nonsmooth Stabilization of a Class of Markovian Jump Stochastic Nonlinear Systems with Parametric and Dynamic Uncertainties

In this paper, we investigate the finite‐time stabilization of Markovian jump stochastic nonlinear (SNL) systems with dynamic uncertainties. Firstly, a proper criterion on finite‐time globally asymptotically stability in probability (FGSP) and some useful lemmas are introduced. Then, overcoming the influence of coupled item which determined by Markovian switching, by adding a power integrator technique and induction method, a state‐feedback finite‐time controller is explicitly constructed. It is proven that, the system state of the closed‐loop systems is FGSP. Simulation examples illustrate the effectiveness of our method.
Multiple Positive Solutions to a Kirchhoff Type Problem Involving a Critical Nonlinearity in ℝ3

Abstract In this paper, we investigate a class of Kirchhoff type problems in ℝ3{\mathbb{R}^{3}} involving a critical nonlinearity, namely, - ( 1 + b ∫ ℝ 3 | ∇ u | 2 d x ) △ u = λ f ( x ) u + | u | 4 u , u ∈ D 1 , 2 ( ℝ 3 ) , -\biggl{(}1+b\int_{\mathbb{R}^{3}}\lvert\nabla u|^{2}\,dx\biggr{)}\triangle u=% \lambda f(x)u+|u|^{4}u,\quad u\in D^{1,2}(\mathbb{R}^{3}), where b>0{b>0}, λ>λ1{\lambda>\lambda_{1}} and λ1{\lambda_{1}} is the principal eigenvalue of -△⁢u=λ⁢f⁢(x)⁢u{-\triangle u=\lambda f(x)u}, u∈D1,2⁢(ℝ3){u\in D^{1,2}(\mathbb{R}^{3})}. We prove that there exists δ>0{\delta>0} such that the above problem has at least two positive solutions for λ1<λ<λ1+δ{\lambda_{1}<\lambda<\lambda_{1}+\delta}. Furthermore, we obtain the existence of ground state solutions. Our tools are the Nehari manifold and the concentration compactness principle. This paper can be regarded as an extension of Naimen’s work [21].
Economic Evaluation of Anesthesiology-Led Cardiac Implantable Electronic Device Service

Background: Implementation of an anesthesiology-led cardiac implantable electronic device (CIED) service can be viewed to have economic and efficiency challenges. This study evaluates the cost savings of an anesthesiology-led CIED service. Methods: A total of 830 patients presented in the pre-implementation period from 1 March 2016 to 31 December 2017, and 1981 patients presented in the post-implementation period from 1 January 2018 to 31 October 2021. Interrupted time-series analysis for single-group comparisons was used to evaluate the cost savings resulting from reduction in operating room (OR) start delays for patients with CIEDs. Results: OR start-time delay was reduced by 10.6 min (95%CI: −20.5 to −0.83), comparing pre- to post-implementation. For an OR cost of USD 45/min, we estimated the direct cost to the department to be USD 1.68/min. The intervention translated into a total cost reduction during the intervention period of USD 250,000 (USD 18,000 to USD 470,000) per year for the institution and USD 9800 (USD 730 to USD 17,000) per year for the department. The yearly cost of employing a full-time team of CIED specialists would have been USD 135,456. The service triggered electrophysiology consultation on 13 device malfunctions. Conclusions: An anesthesiology-led CIED service resulted in substantial cost savings, increased OR efficiency and patient safety.
The Productivity Benefits of Overeducation

Overeducation is an issue of concern in the public discourse that has implications for aggregate labor productivity. Extending a literature focused on individual outcomes, we find productivity-enhancing effects in Canadian data by province and industry spanning 1997–2015. Dynamic panel models with external instruments show that productivity increases by about 3% for each 1% increase in the overeducation shares. Effects are largest among industries with more intangible capital investment or with more jobs that require university education and among small-firm employees that are not unionized. Our results provide yet another argument for the benefits of postsecondary education.
Diverse Sphingolipid Profiles in Rectal and Colon Cancer

Colorectal cancer is a heterogenous group of neoplasms showing a variety of clinical and pathological features depending on their anatomical location. Sphingolipids are involved in the formation and progression of cancers, and their changes are an important part of the abnormalities observed during carcinogenesis. Because the course of rectal and colonic cancer differs, the aim of the study was to assess whether the sphingolipid profile is also different in tumors of these two regions. Using a combination of ultra-high-performance liquid chromatography combined with triple quadrupole mass spectrometry, differences in the amounts of cellular sphingolipids were found in colorectal cancer. Sphingosine content was higher in rectal cancer than in adjacent healthy tissue, while the content of two ceramides (C18:0-Cer and C20:0-Cer) was lower. In colon cancer, a higher content of sphingosine, sphinganine, sphingosine-1-phosphate, and two ceramides (C14:0-Cer and C24:0-Cer) was found compared to healthy tissue, but there was no decrease in the amount of any of the assessed sphingolipids. In rectal cancer, the content of sphinganine and three ceramides (C16:0-Cer, C22:0-Cer, C24:0-Cer), as well as the entire pool of ceramides, was significantly lower compared to colon cancer. The S1P/Cer ratio in rectal cancer (S1P/C18:1-Cer, S1P/C20:0-Cer, S1P/C22:0-Cer, S1P/C24:1-Cer) and in colon cancer (S1P/C18:0-Cer, S1P/C18:1-Cer, S1P/C20:0-Cer) was higher than in adjacent healthy tissue and did not differ between the two sites (rectal cancer vs. colonic cancer). It seems that the development of colorectal cancer is accompanied by complex changes in the metabolism of sphingolipids, causing not only qualitative shifts in the ceramide pool of cancer tissue but also quantitative disturbances, depending on the location of the primary tumor.
Direct Oxidation of Hibiscus cannabinus Stalks to Vanillin Using CeO2 Nanostructure Catalysts

Biomass lignin can be used to produce vanillin through an oxidation process. Although its purity is high, the processing time and separation efficiency are not ideal. This research aims to produce vanillin directly from Kenaf stalks without separating the lignin first from the lignocellulosic biomass. This method is greener because it does not require the separation of cellulose and hemicellulose from the biomass, thus minimizing the use of acid and alkaline solutions and saving time. A high oxygen storage capacity and release capacity of ceria as an oxidation catalyst contribute to the reversable redox properties between Ce4+ and Ce3+ in ceria lattice. Cerium oxide nanostructures were synthesized using a hydrothermal method treated under alkaline NaOH, followed by drying at 120 °C for 16 h and calcining at different temperatures between 400 and 600 °C for the direct oxidation of Kenaf stalks to vanillin under microwave irradiation. The catalysts were characterized for their physicochemical properties using XRD, N2 adsorption–desorption isotherms and TEM. All synthesized CeO2 nanostructures showed the presence of diffraction peaks assigned to the presence of cubic fluorite. The N2 adsorption–desorption isotherms showed that all catalysts possess a Type IV isotherm, indicating a mesoporous structure. The TEM image shows the uniform shape of the CeO2 nanostructures, while HRTEM images show that the CeO2 nanostructures are single-crystalline in nature. All catalysts were tested for the direct oxidation of Kenaf stalks using H2O2 as the oxidizing agent in temperatures ranging from 160 to 180 °C for 10–30 min with 0.1–0.3 g catalyst loading under 100–500 W of microwave irradiation. The CeO2-Nps-400 catalyst produced the highest vanillin yields of 3.84% and 4.32% for the direct oxidation of Kenaf stalks and extraction of lignin from Kenaf stalks, respectively. Compared to our earlier study, the highest vanillin yields of 2.90% and 3.70% for direct biomass and extracted lignin were achieved using a Ce/MgO catalyst.