Miracle-dz/UniFAR-FTUs huggingface dataset:
Associations of Content and Context of Communication with Prostate-Specific Antigen Testing

There is limited research about the content and context of communication on prostate-specific antigen (PSA) testing among men in the state of Florida. The purpose of this study is to understand how the content communication (discussion of advantages and disadvantages of PSA testing between provider and patient; provider recommendations of PSA testing) and the context of communication (continuity of care denoted by the presence of a personal doctor) influence PSA testing. Data were drawn from the Florida Behavioral Risk Factor Surveillance System. Receipt of PSA testing was the primary outcome. Multiple logistic regression analyses were used to adjust for sociodemographic, clinical, healthcare access, and lifestyle characteristics when associating the content and context of communication with PSA testing. Discussions were classified into four mutually exclusive categories: discussions of advantages and disadvantages, only advantages, only disadvantages, and no discussion. The most significant predictors for PSA testing included physician recommendation, discussions including advantages, older age, non-smoking, and having a personal doctor. Individualized PSA screening may be a pathway to reducing racial disparities in screening for prostate cancer (PCa) and, by extension, lower incidence and mortality rates. Developing a bill to create an Office of Men’s Health at Health & Human Services is recommended.
Glioma Grade Classification Using CNNs and Segmentation With an Adaptive Approach Using Histogram Features in Brain MRIs

Artificial intelligence (AI) applications have become popular due to their advantages in solving health problems with high accuracy and confidence. One such application is the diagnosis of brain tumors or anomalies. This paper presents two new approaches for brain tumor grade classification and segmentation. Convolutional neural network (CNN) models were used as the first approach to classify High-Grade Glioma (HGG) and Low-Grade Glioma (LGG) tumors and achieved with 99.85% accuracy, 99.85% F1 and 99.92% AUC scores. A new pipeline consisting of normalization, modality fusion and CNN model for HGG-LGG classification tasks was also proposed and developed. A novel algorithm based on histograms, thresholding and morphological filtering with feature fusion was also proposed and developed for the segmentation task. 70.58% Dice Similarity (DS) on average was achieved with the complete tumor segmentation. Experimental results have shown that the proposed algorithm has improved to measure the complete tumor region 15% more compared to the fixed thresholding. Segmentation results also encourage that the algorithm can be used as a feature extraction process on different sized brain MR images. It is expected that the extracted center of gravity features can be further used in AI algorithms for better segmentation, including T1 and T1CE modalities.
A dual algorithm for a class of augmented convex signal recovery models

Convex optimization models find interesting applications, especially in signal/image processing and compressive sensing. We study some augmented convex models, which are perturbed by strongly convex functions, and propose a dual gradient algorithm. The proposed algorithm includes the linearized Bregman algorithm and the singular value thresholding algorithm as special cases. Based on fundamental properties of proximal operators, we present a concise approach to establish the convergence of both primal and dual sequences, improving the results in the existing literature. Extensions to models with gauge functions are provided.
Clinical Characteristics of Acute Appendicitis in Pregnancy: 10-Year Experience at a Single Institution in South Korea

Background: Acute appendicitis is the most common cause of non-obstetric surgical disease in pregnant women. The diagnosis and treatment of appendicitis during pregnancy are very important because it can cause life-threatening morbidity to the fetus and mother. We evaluated the clinical characteristics of acute appendicitis in pregnant women. Methods: We retrospectively reviewed a medical database that included patients who underwent surgery for acute appendicitis at our hospital from January 2013 through December 2022. We compared non-pregnant women of reproductive age with pregnant women. We classified the pregnant women according to gestational age. Result: A total of 828 patients were reproductive-aged women between 15 and 44 years old. There were 759 non-pregnant patients and 69 pregnant patients. ASA (American Society of Anesthesiologists) physical status classes were significantly higher and hospital stays were significantly longer in the pregnant group. There was no significant intergroup difference in terms of the proportions of complicated appendicitis, extended surgery, or complications. When the enrolled pregnant women were divided into three subgroups according to gestational age, the mean operation time was longest in the third-trimester subgroup. There were no differences among the subgroups in terms of the proportions of complicated appendicitis, extended surgery, or complications, nor were there differences among the subgroups in terms of laboratory findings. Preterm labor and stillbirth occurred in two pregnant women with complicated appendicitis in the second trimester. Conclusion: Immediate surgical treatment should be strongly considered in pregnant women with appendicitis. Efforts for more accurate diagnosis are needed for pregnant women with appendicitis.
Extracellular Vesicle-Packaged miR-195-5p Sensitizes Melanoma to Targeted Therapy with Kinase Inhibitors

Management of advanced melanoma remains challenging, with most BRAF (B-Raf proto-oncogene, serine/threonine kinase)-mutated metastatic patients relapsing within a few months upon MAPK inhibitors treatment. Modulation of tumor-derived extracellular vesicle (EVs) cargo with enrichment of antitumoral molecules is a promising strategy to impair tumor progression and increase treatment response. Herein, we report that restored expression of miR-195-5p, down-regulated in melanoma favoring drug resistance, increases the release of EVs enriched in the tumor suppressor miRNAs, miR-195-5p, miR-152-3p, and miR-202-3p. Incorporating these EVs by bystander tumor cells resulted in decreased proliferation and viability, accompanied by a reduction in CCND1 and YAP1 mRNA levels. Upon treatment with MAPK inhibitors, miR-195 EVs significantly decreased BCL2-L1 protein levels and increased cell death ratio and treatment efficacy. Additionally, EVs exogenously loaded with miR-195-5p by electroporation reduced tumor volume in vivo and impaired engraftment and growth of xenografts implanted with melanoma cells exposed to MAPK inhibitors. Our study shows that miR-195-5p antitumoral activity can be spread to bystander cells through EVs, improving melanoma response to targeted therapy and revealing a promising EV-based strategy to increase clinical response in patients harboring BRAF mutations.
ICCRN: Inplace Cepstral Convolutional Recurrent Neural Network for Monaural Speech Enhancement

According to the mechanism of speech production, speech can be decomposed into excitation and vocal tract which are sparsely represented in cepstral domain. In this study, we propose a neural network for monaural speech enhancement on time-frequency cepstral space that is implemented by inserting a cepstral frequency block into our inplace convolutional recurrent network. The proposed method has a good ability of restoring the speech masked by noise. Experimental results show that the proposed ICCRN model significantly outperforms the baseline system, particularly under low SNR conditions.
Non-Linear Scale Interactions in a Forced Turbulent Boundary Layer

This thesis explores the dynamics of scale interactions in a turbulent boundary layer through a forcing-response type experimental study. An emphasis is placed on the analysis of triadic wavenumber interactions since the governing Navier-Stokes equations for the flow necessitate a direct coupling between triadically consist scales. Two sets of experiments were performed in which deterministic disturbances were introduced into the flow using a spatially-impulsive dynamic wall perturbation. Hotwire anemometry was employed to measure the downstream turbulent velocity and study the flow response to the external forcing. In the first set of experiments, which were based on a recent investigation of dynamic forcing effects in a turbulent boundary layer, a 2D (spanwise constant) spatio-temporal normal mode was excited in the flow; the streamwise length and time scales of the synthetic mode roughly correspond to the very-large-scale-motions (VLSM) found naturally in canonical flows. Correlation studies between the large- and small-scale velocity signals reveal an alteration of the natural phase relations between scales by the synthetic mode. In particular, a strong phase-locking or organizing effect is seen on directly coupled small-scales through triadic interactions. Having characterized the bulk influence of a single energetic mode on the flow dynamics, a second set of experiments aimed at isolating specific triadic interactions was performed. Two distinct 2D large-scale normal modes were excited in the flow, and the response at the corresponding sum and difference wavenumbers was isolated from the turbulent signals. Results from this experiment serve as an unique demonstration of direct non-linear interactions in a fully turbulent wall-bounded flow, and allow for examination of phase relationships involving specific interacting scales. A direct connection is also made to the Navier-Stokes resolvent operator framework developed in recent literature. Results and analysis from the present work offer insights into the dynamical structure of wall turbulence, and have interesting implications for design of practical turbulence manipulation or control strategies.
DOES "IS" INNOVATION DIFFUSION CONTRIBUTE TO THE NON-FINANCIAL PERFORMANCE OF THE VILLAGE GOVERNMENT?

<p class="JurnalASSETSABSTRAK"><strong>ABSTRACT</strong></p><p>This research paper analyzes the Influence of IS innovation diffusion on the performance/ outcome of the village government. Besides this paper also determines the role of organizational support and technological advantage in determining performance. Finally, this study researched these variables as moderating between IS innovation diffusion and implementation. The primary data was collected through a survey and analyzed using the smart-pls. The result shows that the technological advantage is significantly associated with the performance of the village government. This finding contributes to the technology organization environment. </p><p class="JurnalASSETSABSTRAK"><strong><em>ABSTRAK</em></strong><em></em></p><p><em>Penelitian ini menganalisis pengaruh difusi inovasi SI terhadap kinerja pemerintah desa. Selain itu, penelitian ini juga menentukan peran dukungan organisasi dan keunggulan teknologi dalam menentukan kinerja. Terakhir, penelitian ini juga meneliti variabel-variabel tersebut sebagai variabel pemoderasi antara difusi inovasi SI dan kinerja. Data primer dikumpulkan melalui survei dan dianalisis menggunakan smart-pls. Hasil penelitian menunjukkan bahwa keunggulan teknologi berpengaruh secara signifikan dengan kinerja pemerintah desa. Temuan ini secara teoritis berkontribusi pada technology organization environment. </em></p>
A Model of Inertial Oscillations with Deformation Frontogenesis

Abstract A model of inertial oscillations that may occur with, and be modulated by, deformation frontogenesis is formulated. The deformation parameter is α ∼ 10−5 s−1 and the Coriolis parameter is f ∼ 10−4 s−1. This timescale separation, distinguished by the ratio α/f ∼ 10−1, provides the basis for application of a two-timescale analysis that separates the frontal evolution from the inertial frequency oscillations. To lowest order, the inertial oscillations do not influence frontogenesis, described by the classical Hoskins and Bretherton model. The frontal evolution, characterized by the alongfront geostrophic wind, does, however, provide an amplitude modulation of the inertial wind oscillation and of the temperature that also undergoes an oscillation at the inertial frequency. Parameter values are chosen to illustrate frontal contraction and translation characteristics that can distort the wind hodograph from circular motion. Ground-level temperature traces also exhibit unusual attributes, such as an ini.
On a representation of fractional order systems: interests for the Initial Condition Problem

This paper proposes a representation of fractional order system that involves a classical linear integer system and a system described by a parabolic equation. It thus demonstrates that fractional order systems are halfway between these two classes of systems, and are particularly suited for diffusion phenomena modeling. This representation is used here to derive a coherent initialization function for the considered systems.
Estimation of High-Dimensional Differential Graphs from Multi-Attribute Data

We consider the problem of estimating differences in two Gaussian graphical models (GGMs) which are known to have similar structure. The GGM structure is encoded in its precision (inverse covariance) matrix. In many applications one is interested in estimating the difference in two precision matrices to characterize underlying changes in conditional dependencies of two sets of data. Existing methods for differential graph estimation are based on single-attribute models where one associates a scalar random variable with each node. In multi-attribute graphical models, each node represents a random vector. In this paper, we analyze a group lasso penalized D-trace loss function approach for differential graph learning from multi-attribute data. An alternating direction method of multipliers (ADMM) algorithm is presented to optimize the objective function. Theoretical analysis establishing consistency in support recovery and estimation in high-dimensional settings is provided. We illustrate our approach using a numerical example where the multi-attribute approach is shown to outperform a single-attribute approach.
Evaluating night-time light sources and correlation with socio-economic development using high-resolution multi-spectral Jilin-1 satellite imagery of Quito, Ecuador

ABSTRACT Artificial light at night (ALAN) has positive and negative effects on social, economic, environmental, and ecological systems, and will increase with urban expansion. In this study, we used a multi-spectral 1.5 m resolution night-time acquisition from a Jilin-1 satellite over the city of Quito, Ecuador, to evaluate spatial lighting patterns in an expanding and topography complex-built environment. We demonstrated a requirement for robust georeferencing and orthorectification due to the complex topography, with errors on the order of 4–6 pixels (5.8–8.4 m CE95). We also quantified differences in observed brightness due to the image acquisition and local geometry. Street light type was distinguishable between high-pressure sodium (HPS) and light emitting diode (LED) sources (F1-score = 0.72–0.83) using a shark random forest decision tree approach. Additionally, street lights could be located within 10 m (F1-score = 0.71) with balanced omissions and commissions. Spatial trends revealed that the road network was the dominant source of illumination, accounting for 45% of illuminated pixels, whereas built-up areas accounted for 23%. Overall, 68% of all illuminated pixels were on or within 10 m of the road. Higher socio-economic development was associated with higher proportions of LED lighting, greater road network lighting and density of street lights, higher overall radiance for built-up areas and the road network, and greater coverage and illumination of designated green spaces. The broad impacts of ALAN mean that addressing the causes and consequences of lighting inequalities is a complex issue. Nonetheless, Jilin-1 night-time imagery offers a low-cost way to map and monitor light sources at high-resolution that will be beneficial to city-planners and progressing Sustainable Development Goals. Key policy highlights Image acquisition geometry affects the observed radiance and would require consideration when evaluating spatial and temporal trends. Jilin-1 night-time satellite imagery offers a low-cost mechanism to map and monitor light sources at high-resolution that is sufficient to identify individual sources such as street lights, buildings, and recreational spaces. Radiance intensity was correlated with the degree of socio-economic development. In the higher socio-economic classes, we observed higher proportions of LED lighting, greater road network lighting and density of street lights, higher overall radiance for built-up areas and the road network, and greater coverage and illumination of designated green spaces.
Prompt Makes mask Language Models Better Adversarial Attackers

Generating high-quality synonymous perturbations is a core challenge for textual adversarial tasks. However, candidates generated from the masked language model often contain many words that are antonyms or irrelevant to the original words, which limit the perturbation space and affect the attack’s effectiveness. We present ProAttacker1 which uses Prompt to make the mask language models better adversarial Attackers. ProAttacker inverts the prompt paradigm by leveraging the prompt with the class label to guide the language model to generate more semantically-consistent perturbations. We present a systematic evaluation to analyze the attack performance on 6 NLP datasets, covering text classification and inference. Our experiments demonstrate that ProAttacker outperforms state-of-the-art attack strategies in both success rate and perturb rate.
Bacteriostatic Effects of Yujin Powder and Its Components on Clinical Isolation of Multidrug-Resistant Avian Pathogenic Escherichia coli

Simple Summary Yujin powder is a polyherbal formulation that has been used to treat the large intestine dampness-heat syndrome for a long time. Escherichia coli is one of the most common pathogenic bacteria to cause this syndrome in diarrheal chickens, leading to serious economic losses in the poultry industry. The limited effect of antibiotics on antibiotic-resistant E. coli makes this bacterium a potential threat to human health. The present study is designed to explore the treatment effects and mechanisms of the Yujin powder and its potential bioactive components on lethal diarrhea caused by clinical isolated multidrug-resistant avian pathogenic E. coli and demonstrate the potential bioactive component of YJP. A multidrug-resistant E. coli was isolated and identified from a clinical diarrheal chick. Yujin powder and its components could directly inhibit the growth of this strain at high concentrations in vitro, and presents obvious anti-bacterial effects by reducing the bacterial loads, the release of endotoxin, and inflammation in vivo, which was much more effective than the resistant antibiotic ciprofloxacin. Based on our results, Yujin powder and its components, Scutellariae Radix and Baicalin, could be used as novel treatment against the diarrhea caused by this isolated multidrug-resistant E. coli. Abstract Escherichia coli is one of the most common pathogenic bacteria in diarrheal chickens, leading to serious economic losses in the poultry industry. The limited effect of antibiotics on antibiotic-resistant E. coli makes this bacterium a potential threat to human health. Yujin powder (YJP) has been reported as an agent that releases the symptoms caused by E. coli for a long time. The objective of this study is to investigate the effect of Yujin powder (YJP) and its components, Scutellariae Radix (SR) and Baicalin (Bac), anti-against multi-drug-resistant E. coli in vitro and in vivo. A multi-drug-resistant bacteria was isolated and identified from a clinical diarrheal chick. Then, the anti-bacterial effects of drugs were assessed in vitro and in vivo by analyzing the bacteria loads of organs, the levels of endotoxin, TNF-α, IL-1β, and IL-6 of the serum. Results found that the pathogenic E. coli was resistant to 19 tested antibiotics. YJP, SR, and Bac could directly inhibit the growth of this strain at high concentrations in vitro, and presents obvious anti-bacterial effects by reducing the bacterial loads, the release of endotoxin, and inflammation in vivo, which was much more effective than the resistant antibiotic ciprofloxacin. This study demonstrates that those natural medicines have the potential to be used as novel treatments to treat the disease caused by this isolated MDREC strain.
Fungal Spore Diversity and Abundance in Five Areas in Ibadan, South West, Nigeria

Background: Airborne fungal spores may pose as a potential high risk of fungal-related health problems in humans, animals, and plants which necessitated the need to constantly monitor the presence and diversity of fungi spores in the atmosphere regularly. This study aims to investigate diversity and abundance of airborne fungal spores across multiple locations for two years in Ibadan, South West, Nigeria. Subjects dan Method: Study descriptive cross-sectional are used to investigate diversity and abundance of airborne fungal spores across multiple locations. The variable in this study were Air-borne fungi spores diversity sampled monthly from five different locations in Ibadan, Oyo State, South-West Nigeria for two years using the open plate sedimentation method with the petri dishes of Dichloran-glycerol 18 (DG-18) and Potato Dextrose Agar (PDA) media. Monthly Meteorological parameters were equally taken during the duration of sampling. The data were collected and graphical presented using histograms. Results: A total of 39 fungal species were identified throughout duration of study. Aspergillus and Penicillium were the most abundant fungi genera isolated while few Zygomycetes, Ascomycetes, and Basidiomycetes were found. Rainy season period favours high number of fungi in the atmosphere. The highest abundance of fungal spores was recorded in June and July while lower fungi concentration was recorded between December and February. Conclusion: the study revealed the most dominant and abundant spores belong to the genera Aspergillus, Penicillium, and Fusarium. The results show the need for people suffering from fungi sensitivity and allergies to be well informed.
Consistent viscous-spring artificial boundaries and viscous-spring boundary elements

The concept of the consistent viscous-spring artificial boundaries and viscous-spring boundary elements was proposed.The stiffness matrix and damp matrix of the 2D consistent artificial boundaries were deduced.The equivalent viscous-spring artificial boundary elements were developed by comparing the matrix of the general finite element and the consistent viscous-spring artificial boundaries.This method was applied to the uniform and layered half space problems.It was shown that the precision of viscous-spring boundary elements was the same as that of lumped viscous-spring artificial boundaries.The viscous-spring boundary elements were efficient and could be applied simply.