Miracle-dz/UniFAR-FTUs huggingface dataset:
Global Down-regulation of Gene Expression Induced by Mouse Mammary Tumor Virus (MMTV) in Normal Mammary Epithelial Cells

Mouse mammary tumor virus (MMTV) is a betaretrovirus that causes breast cancer in mice. The mouse mammary epithelial cells are the most permissive cells for MMTV, expressing the highest levels of virus upon infection and being the ones later transformed by the virus due to repeated rounds of infection/superinfection and integration, leading eventually to mammary tumors. The aim of this study was to identify genes and molecular pathways dysregulated by MMTV expression in mammary epithelial cells. Towards this end, mRNAseq was performed on normal mouse mammary epithelial cells stably expressing MMTV, and expression of host genes was analyzed compared with cells in its absence. The identified differentially expressed genes (DEGs) were grouped on the basis of gene ontology and relevant molecular pathways. Bioinformatics analysis identified 12 hub genes, of which 4 were up-regulated (Angp2, Ccl2, Icam, and Myc) and 8 were down-regulated (Acta2, Cd34, Col1a1, Col1a2, Cxcl12, Eln, Igf1, and Itgam) upon MMTV expression. Further screening of these DEGs showed their involvement in many diseases, especially in breast cancer progression when compared with available data. Gene Set Enrichment Analysis (GSEA) identified 31 molecular pathways dysregulated upon MMTV expression, amongst which the PI3-AKT-mTOR was observed to be the central pathway down-regulated by MMTV. Many of the DEGs and 6 of the 12 hub genes identified in this study showed expression profile similar to that observed in the PyMT mouse model of breast cancer, especially during tumor progression. Interestingly, a global down-regulation of gene expression was observed, where nearly 74% of the DEGs in HC11 cells were repressed by MMTV expression, an observation similar to what was observed in the PyMT mouse model during tumor progression, from hyperplasia to adenoma to early and late carcinomas. Comparison of our results with the Wnt1 mouse model revealed further insights into how MMTV expression could lead to activation of the Wnt1 pathway independent of insertional mutagenesis. Thus, the key pathways, DEGs, and hub genes identified in this study can provide important clues to elucidate the molecular mechanisms involved in MMTV replication, escape from cellular anti-viral response, and potential to cause cell transformation. These data also validate the use of the MMTV-infected HC11 cells as an important model to study early transcriptional changes that could lead to mammary cell transformation.
Thermal stresses in a coating–substrate assembly caused by internal heat source

ABSTRACT We determine two-dimensional temperature and thermal stresses distributions in a semiconductor coating-substrate assembly caused by the heat source at the contact surface. The analysis is based on the Laplace and Hankel integral transforms of equations of thermal elasticity, and the obtained analytical solutions can be used without any limitations on the duration of heating, the thickness of a coating, mechanical and thermal characteristics of materials. We consider the effect of the thickness of a coating, thermal mismatch between the substrate and the coating on the magnitude of thermal stresses. Using the obtained thermal stress distribution we analyze the delamination failure at the substrate-coating interface.
A Tale of Two Bankruptcies: Geographic Differences in Bankruptcy Chapter Choice

IZA DP No. 16105 MAY 2023 A Tale of Two Bankruptcies: Geographic Differences in Bankruptcy Chapter Choice* The importance of place of birth or residence on a host of economic outcomes cannot be overstated. The treatment of households in consumer bankruptcy appears to be no different. Despite the U.S. Bankruptcy Code being federal law, there is extreme geographic variation in the relative use of the two types of consumer bankruptcy – Chapter 7 and Chapter 13 – and these differences lead to disparities in bankruptcy’s balance between debt relief and creditor repayment. Guided by the legal literature, we develop a framework to decompose the geographic variation into three potential sources: (i) differences in filer characteristics, (ii) differences in how courts steer filers based on those characteristics, and (iii) differences in how frequently filers deviate from court steering. The results reveal that heterogeneity surrounding a single characteristic, disposable income, explains most of the geographic variation in chapter choice. Moreover, we show that disposable income plays an important and overlooked role in screening within the bankruptcy system, and we discuss the legal mechanisms behind this screening. Finally, we explore the consequences of improving uniformity in the bankruptcy system. JEL Classification: D31, G28, G51, R59
The Influence of Gender on Hip Range of Motion, Hip Muscle Strength, Gluteus Medius Thickness and M-Mode Ultrasound Examination in Asymptomatic University Athletes: A Cross-Sectional Study

Physical activity is a proposed factor int the development of hip pathologies in male and female. The main objectives of this study were to investigate the influence of gender on isometric hip muscle strength, hip range of motion and gluteus medius thickness at rest, during contraction and onset activation.A cross-sectional study was carried out. Hip range of motion, hip muscle strength and gluteus medius thickness at rest, (B-Mode) and onset activation (M-Mode) were measured in thirty asymptomatic university athletes without history hip pain.A total of fifteen males (30 hips) and fifteen females (30 hips) with a mean age of 22 ± 6.5 and 20 ± 2.75 years old were recruited. Females demonstrated greater hip range of motion in flexion, abduction and internal rotation in dominant and non-dominant legs (p < .05) but no differences were found extension, adduction and external rotation (p > .05). Furthermore, females showed less isometric hip muscle strength in hip flexion, extension, abduction, adduction, internal and external rotation (p < .05) but not in strength ratios (p > .05). In addition, female exhibited less gluteus medius thickness at muscle contraction, less differences in rest-contaction thickness, but no differences were observed for rest thickness or contraction velocity.This study found that asymptomatic female athletes demonstrated greater hip flexion, abduction and internal rotation ROM, less isometric hip muscle strength and different gluteus medius thickness and onset activation compared with asymptomatic male athletes.
Central Limit Theorems for Martingales with Discrete or Continuous Time

This survey paper consists of two parts. In the first part (up to and including setion 3) we review the central limit theorems for discrete time martingales, and show that many different sets of conditions for convergence may be reduced to one basic set, where conditions are given in terms of conditional moments of truncated variables, given the past. In the second part (sections 4 and 5) we first recall some basic facts from the modern "French" theory of stochastic processes, then show that Rebolledo's recent functional limit theorems for martingales with continuous time can be deduced from the limit theorems for discrete time martingales. Again, several related sets of conditions for convergence are formulated.
Multimodal region-consistent saliency based on foreground and background priors for indoor scene

Visual saliency is a very important feature for object detection in a complex scene. However, image-based saliency is influenced by clutter background and similar objects in indoor scenes, and pixel-based saliency cannot provide consistent saliency to a whole object. Therefore, in this paper, we propose a novel method that computes visual saliency maps from multimodal data obtained from indoor scenes, whilst keeping region consistency. Multimodal data from a scene are first obtained by an RGB+D camera. This scene is then segmented into over-segments by a self-adapting approach to combine its colour image and depth map. Based on these over-segments, we develop two cues as domain knowledge to improve the final saliency map, including focus regions obtained from colour images, and planar background structures obtained from point cloud data. Thus, our saliency map is generated by compounding the information of the colour data, the depth data and the point cloud data in a scene. In the experiments, we extensively compare the proposed method with state-of-the-art methods, and we also apply the proposed method to a real robot system to detect objects of interest. The experimental results show that the proposed method outperforms other methods in terms of precisions and recall rates.
Centrality for nodes in social networks

In social networks, investigating node influence and influence maximization is an important issue and attracts great interest in the research community. In order to analyze its personal influence and potential influence, it proposes a Personal-Potential Influence(PPI)algorithm, which evaluates the weight of its k-shell, closeness centrality and betweenness centrality by considering the strength of relationship between nodes. The experimental results show that PPI has the higher accuracy in node influence and outperforms other algorithms.
Research on Model Construction of Electric Energy Metering System Based on Intelligent Sensor Data

The informatization construction of the power grid is becoming increasingly popular, business application systems are constantly emerging, and power-related data is rapidly expanding. These discrete power data are scattered in various application systems, and it is not easy to directly provide advanced enterprise applications. The establishment of intelligent power statistical model is an urgent need for constructing power grid informatization. This paper proposes a model of an electric energy metering system based on intelligent sensor data and introduces the existing digital metering system. This model is the integration and promotion of business integration based on the digital metering system. It is the first time to apply new metering equipment, such as measurement and control devices with integrated metering functions, and new metering technologies, such as IEC 61850 electricity meter reading applications. It is hoped that this paper can lay a foundation for further research.
“This is for us, not them”: Troubling adultism through a pedagogy of solidarity in youth organizing and activism

ABSTRACT Social studies education research lauds the importance of schools as spaces to practice democratic values while also largely ignoring the agency youth exercise to shape their lives in the present. This article explores how young people organize and enact democratic practices within youth-mediated contexts in schools by examining the pedagogy of solidarity that adults must enact to support youths’ visions of democratic life. This qualitative study examines youth organizers’ response to the murder of a Black man in their community and how adults acted in solidarity or against their civic action. The findings elucidate how youth organizing and action can be re-framed as democratic actions and what it takes for adults to make this epistemic and ontological maneuver. The article concludes with a discussion about implications for social studies research when centering youth agency, as well as an analysis of social education beyond the classroom and adult-centered understandings of democratic education.
Entrainment and Migration Control of Permanent-Magnet Synchronous Motor System

The entrainment and migration control of the PMSM is studied. It is shown that when the system orbits lie in the convergent basin, the entrainment and migration control can be achieved to make the system orbits from a stable state to chaos, from a stable fixed point to another one and from a strange attractor to a stable fixed point.
Analisis Karakteristik Antivirus Berdasarkan Aktivitas Malware menggunakan Analisis Dinamis

Malware, short for “Malicious Software”, is a program specifically designed to perform an activity that can harm software on a victim's device. Examples of commonly found malware include trojans, ransomware and downloaders. It is important for computer users to recognize and avoid malware when using computer devices. Therefore, computer users can overcome malware attacks by using protection software specifically for computer devices using Antivirus software designed to prevent, find, detect, and remove the types of malware that have been mentioned previously. In this study, the dynamic analysis method is used to determine malware activity by running it and monitoring the activity that occurs. This method is usually used to identify the actions that malware performs when it runs. The results showed that the higher the number of malware activities, the higher the metrics tested on the antivirus, such as CPU, memory, disk, and scan time. Regarding the removable drive protection feature, Avast antivirus is relatively more efficient compared to other antiviruses because it has an average CPU usage, low memory, a fairly high detection rate, and fast scan times. Kaspersky Antivirus is relatively the most effective in detecting malware samples with the highest detection rate of 100%. Meanwhile, the Windows Defender antivirus is relatively the weakest in terms of detection rate because it has the lowest detection rate.
Improved Method for End Effects of EMD Based on Mirror Extension and Neural Network

Empirical Mode Decomposition (EMD) has been employed extensively in mechanical fault diagnosis,but the serious problem existed in the application is end effects. Mirror Extension is an effective method to overcome it. When the mirror extension is used to treat with end effects,it needs to put the mirror at local extreme point. Aiming at this problem,a method combining the mirror extension with the Neural Network is proposed to extend the data. The Neural Network is adopted to forecast an extreme point forward and backward,and then the mirror extension is used to restrain end effects. Through analyzing a simulated vibration signal,the results show that the proposed method restrains the end effects effectively.
Variable Selection for Mediators under a Bayesian Mediation Model

Abstract This study proposes a Bayesian variable selection approach to select mediators and quantify their respective posterior probabilities in exploratory mediation analysis. Monte Carlo simulation studies demonstrate that the proposed method has high statistical power in selecting mediating effects and low Type I error rate in excluding null effects. By estimating the probability of a given mediating effect via the posterior distribution, the proposed method quantifies the variable’s influence on a continuum scale. This is an attractive and unique gain that neither conventional p-value-based mediation methods nor the regularization-based LASSO method for exploratory mediation possess. We offer four decision rules to assist in selecting mediators and excluding null effects to minimize a common problem (i.e., elevated type I errors) in the exploratory context, as well as provide an empirical example to illustrate the proposed method’s application and interpretation. We end with a discussion of the work and directions for future work.
Will Absolute Risk Estimation for Time to Next Screen Work for an Asian Mammography Screening Population?

Simple Summary Personalized breast cancer screening has the potential to improve the accuracy and effectiveness of breast cancer screening by tailoring the screening protocol to an individual’s risk factors. Currently, most women undergo mammograms at regular intervals based on age and family history, regardless of their risk factors. We examined the applicability of the Gail model, a well-known breast cancer prediction tool including several risk factors, in an Asian population. While the tool predicts the risks of developing breast cancer in the next 2, 5, 10, and 15 years to some extent, the age at which the disease occurs cannot be estimated. In addition, the tool performs better for longer prediction horizons (10 or 15 years), limiting its utility for risk prediction for two-year screening intervals. Abstract Personalized breast cancer risk profiling has the potential to promote shared decision-making and improve compliance with routine screening. We assessed the Gail model’s performance in predicting the short-term (2- and 5-year) and the long-term (10- and 15-year) absolute risks in 28,234 asymptomatic Asian women. Absolute risks were calculated using different relative risk estimates and Breast cancer incidence and mortality rates (White, Asian-American, or the Singapore Asian population). Using linear models, we tested the association of absolute risk and age at breast cancer occurrence. Model discrimination was moderate (AUC range: 0.580–0.628). Calibration was better for longer-term prediction horizons (E/Olong-term ranges: 0.86–1.71; E/Oshort-term ranges:1.24–3.36). Subgroup analyses show that the model underestimates risk in women with breast cancer family history, positive recall status, and prior breast biopsy, and overestimates risk in underweight women. The Gail model absolute risk does not predict the age of breast cancer occurrence. Breast cancer risk prediction tools performed better with population-specific parameters. Two-year absolute risk estimation is attractive for breast cancer screening programs, but the models tested are not suitable for identifying Asian women at increased risk within this short interval.
Semantic data mining‐based decision support for quality assessment in steel industry

This study evaluates quality management practices in Industry 4.0 in a specific case of steel manufacturing. We formulate a novel proposal based on Semantic Data Mining techniques a step towards knowledge‐driven decision support based on the industrial Six Sigma approach. In our research we combine machine learning classifiers, and explanation generation algorithms with the Six Sigma practice to automate the evaluation of quality of steel products and determine origins of their defects. We describe our original method, and provide evaluation of the results with real–life data from our industrial partner.
Chemical Synthesis of Innovative Silver Nanohybrids with Synergistically Improved Antimicrobial Properties

Background The wide use of antibiotics has created challenges related to antibiotic-resistant bacteria, which have been increasingly found in recent decades. Antibiotic resistance has led to limited choices of antibiotics. Multiple old antimicrobial agents have high antimicrobial properties toward bacteria, but they unfortunately also possess high toxicity toward humans. For instance, silver (Ag) compounds were frequently used to treat tetanus and rheumatism in the 19th century and to treat colds and gonorrhea in the early 20th century. However, the high toxicity of Ag has limited its clinical use. Purpose We aimed to reformulate Ag to reduce its toxicity toward human cells like osteoblasts and to optimize its antimicrobial properties. Results Ag, an old antimicrobial agent, was reformulated by hybriding nanomaterials of different dimensions, and silver nanoparticles (AgNPs) of controllable sizes (95–200 nm) and varying shapes (cube, snowflake, and sphere) were synthesized on carbon nanotubes (CNTs). The obtained AgNP-CNT nanohybrids presented significantly higher killing efficacy against Staphylococcus aureus (S. aureus) compared to AgNPs at the same molar concentration and showed synergism in killing S. aureus at 0.2 and 0.4 mM. AgNPs presented significant osteoblast toxicity; in contrast, AgNP-CNT nanohybrids demonstrated significantly enhanced osteoblast viability at 0.04–0.8 mM. The killing of S. aureus by AgNP-CNT nanohybrids was fast, occurring within 15 min. Conclusion Ag was successfully reformulated and Ag nanohybrids with various AgNP shapes on CNTs were synthesized. The nanohybrids presented significantly enhanced antimicrobial properties and significantly higher osteoblast cell viability compared to AgNPs, showing promise as an innovative antimicrobial nanomaterial for a broad range of biomedical applications.
Development of a new oscillometric blood pressure measurement system

A new blood pressure measurement system was developed, based on the oscillometric method using a controlled linear deflation technique. The system was structured in order to make several tasks independent and specialized, thus allowing for future punctual developments. An oscillometric signal data base was formed according to the standard ANSI/AAMI/SP10-1992, using the manual auscultatory method as a reference to determine measurement techniques to be used. The correlation among several quantities such as reference blood pressure measurements, characteristic ratios, age, weight, height and arm circumference size, was studied. A new strategy to obtain systolic mean and diastolic pressures was an oscillometric pulse envelope, depending on parameters such as actual cuff pressure, mean pressure, pulse amplitude and arm circumference size. Mean differences of about -1,49 and 0,61 and standard deviations of 5,11 and 5,89 mmHg were obtained for systolic and diastolic pressure measurements, respectively. Moreover, a comparative study with commercial equipment was performed, with a simulator.
A 2.5-5 μm spectroscopic study of hard X-ray selected AGNs with AKARI

Abstract We explore the relationships between the 3.3 μm polycyclic aromatic hydrocarbon (PAH) feature and active galactic nucleus (AGN) properties of a sample of 54 hard X-ray selected bright AGNs, including both Seyfert 1 and Seyfert 2 type objects, using the InfraRed Camera (IRC) on board the infrared astronomical satellite AKARI. The sample is selected from the 9-month Swift/BAT survey in the 14-195 keV band and all of them have measured X-ray spectra at E ≲ 10 keV. These X-ray spectra provide measurements of the neutral hydrogen column density (NH) towards the AGNs. We use the 3.3 μm PAH luminosity (L3.3μm) as a proxy for star formation activity and hard X-ray luminosity (L14-195keV) as an indicator of the AGN activity. We searched for possible difference of star-formation activity between type 1 (un-absorbed) and type 2 (absorbed) AGNs. Our regression analysis of log L14-195keV versus log L3.3μm shows a positive correlation and the slope seems steeper for type 1/unobscured AGNs than that of type 2/obscured AGNs. The same trend has been found for the log (L14-195keV/MBH) versus log (L3.3μm/MBH) correlation. Our analysis show that the circum-nuclear star-formation is more enhanced in type 2/absorbed AGNs than type 1/un-absorbed AGNs for low X-ray luminosity/low Eddington ratio AGNs.
Learning Spatio-Temporal Semantics and Cluster Relation for Zero-Shot Action Recognition

Zero-shot Action Recognition (ZSAR) aims at bridging the video $\rightarrow $ class relation with only labeled training data of seen classes while generalizing the model to alleviate the heterogeneity of unseen actions. Most existing methods have comprehensively represented videos and action classes, however, the semantic gap and the hubness problem between them remain crucial challenges that are under-explored. In this paper, we propose an effective method to tackle the above issues. Specifically, to narrow the semantic gap, we end-to-end generate a spatio-temporal semantics for each video, which provides essential textual information to refine the video representation. Furthermore, we propose a compactness-separability loss that optimizes the intra- and inter-class relations in a unified formula and quantitatively constrains cluster distribution, thus effectively diminishing the impact of the hubness problem. Extensive experiments on UCF101, HMDB51, and Olympic Sports datasets prove the effectiveness of the proposed approach and demonstrate our approach outperforms the state-of-the-art methods.