Miracle-dz/UniFAR-FTUs huggingface dataset:
Silver Nanoparticles Induced Changes in DNA Methylation and Histone H3 Methylation in a Mouse Model of Breast Cancer

The importance of epigenetic changes as a measurable endpoint in nanotoxicological studies is getting more and more appreciated. In the present work, we analyzed the epigenetic effects induced by citrate- and PEG-coated 20 nm silver nanoparticles (AgNPs) in a model consisting of 4T1 breast cancer tumors in mice. Animals were administered with AgNPs intragastrically (1 mg/kg b.w. daily—total dose 14 mg/kg b.w.) or intravenously (administration twice with 1 mg/kg b.w.—total dose 2 mg/kg b.w.). We observed a significant decrease in 5-methylcytosine (5-mC) level in tumors from mice treated with citrate-coated AgNPs regardless of the route of administration. For PEG-coated AgNPs, a significant decrease in DNA methylation was observed only after intravenous administration. Moreover, treatment of 4T1 tumor-bearing mice with AgNPs decreased histone H3 methylation in tumor tissue. This effect was the most pronounced for PEG-coated AgNPs administered intravenously. No changes in histone H3 Lys9 acetylation were observed. The decrease in methylation of DNA and histone H3 was accompanied by changes in expression of genes encoding chromatin-modifying enzymes (Setd4, Setdb1, Smyd3, Suv39h1, Suv420h1, Whsc1, Kdm1a, Kdm5b, Esco2, Hat1, Myst3, Hdac5, Dnmt1, Ube2b, and Usp22) and genes related to carcinogenesis (Akt1, Brca1, Brca2, Mlh1, Myb, Ccnd1, and Src). The significance of the observed changes and the mechanisms responsible for their development are unclear, and more research in this area is warranted. Nevertheless, the present work points to the epigenetic effects as an important level of interaction between nanomaterials and biological systems, which should always be taken into consideration during analysis of the biological activity of nanomaterials and development of nanopharmaceuticals.
Utilization of electromyographic biofeedback in speech therapy to attenuate the signs of facial aging: a case report

ABSTRACT Myotherapy intervention in facial aesthetics aims to attenuate wrinkles and signs of facial aging. The relationship between accentuated muscle contraction during chewing, swallowing and speaking and the appearance of facial wrinkles has been suggested by speech-language pathology literature. This study aimed to report the effect of electromyographic biofeedback associated with training of chewing, swallowing, and smiling patterns, during speech therapy intervention aimed at reducing the signs of facial wrinkles and furrows, in a 55-year-old woman. The therapy also included isotonic and isometric exercises and clinical procedures to decrease the contraction of facial mimicry muscles, which were not associated with training using electromyographic biofeedback. Signal collection and training were performed using the Biotrainer software on the New Miotool Face by Miotec, over nine weekly sessions. Two assessments were performed (before and after the nine sessions), using the MBGR Protocol (assessment of chewing, swallowing, and smiling) and validated scales described in the literature (assessment of signs of facial aging). In the reported case, the usefulness of electromyographic biofeedback was verified for learning trained orofacial myofunctional patterns, as well as to improve chewing and swallowing functions and decrease signs of facial aging. However, further research is needed to demonstrate the positive effects of electromyographic biofeedback associated with myofunctional therapy aimed at attenuating the signs of facial aging.
Plant Life Extension programs - useful resources for preservation and amplification of Nuclear Power Plants efficiency

"Plant Life Management (PLIM) is now usually taken to mean those many activities which are to do with the normal operational management of a nuclear power plant to maintain its 'good condition' and to enable operators or Owner(s) to meet the plant's intended amortisation period, operational life or design operational life. That is, it is to do with existing planned Plant Operational or Service Life assurance and not necessarily to do ith meeting an additional period or extended operation time in excess of that intended at the design or evaluation stage, which is usually known as Plant Life Extension (PLEX). The paper presents considerations regarding the ageing management of the NPP’s key components, Plant Life Management (PLIM), refurbishment as activity strictly necessary for Plant Life Extension, and the Romanian refurbishment program as part of PLIM from Cernavoda CANDU NPP. "
Boundary Integral Formulation Of General Source- Based Method For Convective-diffusive Solid-liquid Phase Change Problems

A new one-domain dual reciprocity boundary integral method technique for solving one-phase continuum formulation of the convective-diffusive energy equation as appears when treating energy transport in solid-liquid phase change systems is described. Laplace equation fundamental solution weighting, straight line geometry and constant field shape functions on the boundary, Crank-Nicolson time discretization and thin plate splines for transforming the domain integrals into a finite series of boundary integrals are employed. Iterations over the timestep are based on the Voller-Swaminathan scheme, upgraded to cope with the convective term. The technique could be applied to a wide range of solid-liquid phase change problems where finite volume or finite element solvers have been almost exclusively used in the past.
A review on machine learning

Machine learning is a particular branch of artificial intelligence that teaches a machine how to learn, whereas artificial intelligence (AI) is the general science that aims to emulate human abilities. An AI method called machine learning teaches computers to learn from their past experiences. Machine learning algorithms don't rely on a predetermined equation as a model, but instead "learn" information directly from data using computational techniques. As the quantity of learning examples increases, the algorithms adaptively get better at what they do. This paper provides an overview of the field as well as a variety of machine learning approaches, including supervised, unsupervised, and reinforcement learning and various languages used for machine learning.
Metatronic analogues of the Wheatstone bridge

The Wheatstone bridge is a classical electrical circuit developed by Sir Charles Wheatstone in the middle of the 19th century. The operating principle of the Wheatstone bridge is based on the concept of a difference measurement, and it is one of the most popular circuits in the characterization of resistors. Here, we utilize the optical metatronic paradigm—metamaterial-inspired optical nanocircuitry—to extend the use of the Wheatstone bridge to different platforms and frequency regimes. Specifically, using numerical simulations we present three different designs in which the analogue of the Wheatstone bridge concept is implemented on all-optical metamaterial boards, microwave waveguides, and planar silicon photonic systems, operating in frequency bands ranging from microwaves to the visible. The proposed devices enrich the collection of available nanocircuitry, and it is shown that high accuracy and simplicity of the Wheatstone bridge can be transplanted and exploited in multiple nanophotonic applications including, e.g., the characterization of nanoparticles.
Zero-Shot Single-View Point Cloud Reconstruction via Cross-Category Knowledge Transferring

Single-view point cloud reconstruction aims to generate a 3D point cloud of an object given one 2D image taken from an arbitrary viewpoint. Most previous works assume that all the test categories have been present to the model during training. However, it is impossible to know all the test categories that the model will meet in advance. And we discover these methods can not deal with novel categories well. Therefore, in this article, we investigate a more realistic and challenging setting of single-view point cloud reconstruction, zero-shot, where the model's performance on novel categories is pursued. Towards this task, we propose the Cross-Category Knowledge Transferring Network (CCKTN), which maintains a knowledge bank to mine transferable knowledge from known categories to help reconstruct novel categories. Additionally, we conduct auxiliary learning for the point cloud reconstruction model with the point cloud autoencoder via sharing the same knowledge bank. This design enables the knowledge bank to collect more fruitful 3D knowledge of point clouds. Moreover, we devise a diversity loss regularization for the knowledge vectors to guarantee their diversities, further enhancing CCKTN's performance. Comprehensive experiments conducted on ShapeNet and ModelNet datasets show CCKTN's superiority towards existing methods and demonstrate CCKTN's effectiveness for reconstructing novel category objects.
An Efficient Numerical Solution to the Stochastic Collection Equation

Abstract A new, accurate, efficient method for solving the stochastic collection equation (SCE) is proposed. The SCE is converted to a set of moment equations in categories using a new analytical form of Bleck&'s approach. The equations are written in a form amenable to solution and to a category-by-category analysis of drop formation and removal. This method is unique in that closure of the equations is achieved using an expression relating high-order moments to any two lower order moments, thereby restricting the need for approximation of the category distribution function only to integrals over incomplete categories. Moments in categories are then expressed in terms of complete moments with the aid of linear or cubic polynomials. The method is checked for the case of the constant kernel and a linear polynomial kernel. Results show that excellent approximation to the analytical solutions for these kernels are obtained. This is achieved without the use of weighting functions and with modest computing tim.
Efficacy and Feasibility of Remote Cognitive Remediation Therapy in Parkinson's Disease: A Randomized Controlled Trial

Background Non-motor symptoms of Parkinson's disease (PD) such as cognitive impairment are common and decrease patient quality of life and daily functioning. While no pharmacological treatments have effectively alleviated these symptoms to date, non-pharmacological approaches such as cognitive remediation therapy (CRT) and physical exercise have both been shown to improve cognitive function and quality of life in people with PD. Objective This study aims to determine the feasibility and impact of remote CRT on cognitive function and quality of life in patients with PD participating in an organized group exercise program. Methods Twenty-four subjects with PD recruited from Rock Steady Boxing (RSB), a non-contact group exercise program, were evaluated using standard neuropsychological and quality of life measures and randomized to the control or intervention group. The intervention group attended online CRT sessions for one hour, twice a week for 10 weeks, engaging in multi-domain cognitive exercises and group discussion. Results Twenty-one subjects completed the study and were reevaluated. Comparing groups over time, the control group (n = 10) saw a decline in overall cognitive performance that trended towards significance (p = 0.05) and a statistically significant decrease in delayed memory (p = 0.010) and self-reported cognition (p = 0.011). Neither of these findings were seen in the intervention group (n = 11), which overwhelmingly enjoyed the CRT sessions and attested to subjective improvements in their daily lives. Conclusions This randomized controlled pilot study suggests that remote CRT for PD patients is feasible, enjoyable, and may help slow the progression of cognitive decline. Further trials are warranted to determine the longitudinal effects of such a program.
Robust aircraft segmentation from very high-resolution images based on bottom-up and top-down cue integration

Abstract. Existing segmentation methods require manual interventions to optimally extract objects from cluttered background, so that they can hardly work well in automated surveillance systems. In order to automatically extract aircrafts from very high-resolution images, we proposed a segmentation method that combines bottom-up and top-down cues. Three essential principles from local contrast, global contrast, and center bias are involved to compute bottom-up cue. In addition, top-down cue is computed by incorporating aircraft shape priors, and it is achieved by training a classifier from a rich set of visual features. Iterative operations and adaptive fitting are designed to get refined results. Experimental results demonstrated that the proposed method can provide significant improvements on the segmentation accuracy.
A Study of The Use of Writing Strategies from The Social Cognitive View

Writing is a daunting task for second language learners as it involves a complex process. From the pre-writing activities until the drafting and revising stage, learners are required to actively engage with the writing process. As writing skill is crucial for university students to master, there is a need to further develop an understanding of how writing strategies can assist students in their writing. Thus, this study explores the perception of learners on their use of learning strategies based from the social cognitive view. Data was procured from a total of 102 undergraduate university students using a 5-likert scale survey questionnaire which consists of four sections that tends to explore the motivation factors for learning among undergraduates. Descriptive statistics using mean score and Pearson Correlation Analysis was employed in the data analysis procedures. The findings revealed that the respondents reported to have a high level of metacognitive strategy used in writing and there is a high significant correlation between personal factor (metacognitive strategy) and behaviour factor (effect regulation and cognitive strategies) as compared to personal and environment (low significant correlation) and behaviour and environment (medium significant correlation). The findings suggest that language instructors embed writing strategies in writing class to help ESL writers become better writers and they should guide ESL writers to self-evaluate their writings so that they are aware of the problems and consequently think of the appropriate strategies to be used
TORSIONAL ANALYSIS OF PIEZOELECTRIC HOLLOW BARS

Analytical formulations are presented for Saint-Venant's torsion of orthotropic piezoelectric hollow members. It is assumed that the cross-section consists of straight and curved segments with the same thickness. Governing equations are based on Prandtl's stress and electric displacement potential functions. Some examples are solved using the presented formulations and verified by the finite element method solutions. The results show the accuracy of the present method for torsional analysis of thin- to moderately thick-walled hollow bars.
Aperiodic Sampled-Data-Based Control for T-S Fuzzy Systems: An Improved Fuzzy-Dependent Adaptive Event-Triggered Mechanism

This article is devoted to designing a novel aperiodic sampled-data-based event-triggered control strategy for Takagi–Sugeno fuzzy systems. First, via taking the structural features of fuzzy subsystems and the available information of fuzzy membership functions into consideration, an improved fuzzy-dependent adaptive event-triggered mechanism, which designs different adaptive event-triggered mechanisms for corresponding fuzzy subsystems, is proposed to provide extra design flexibility and further optimize communication efficiency. Then, the two-side looped-functional method and dynamic partitioning approach are introduced in the construction of the novel Lyapunov–Krasovskii functional (LKF). These two methods contribute to deriving preferable stability criterion and stabilization approach via relaxing the positive definite constraint on LKF and fully utilizing the inner system state during the whole aperiodic sampling interval. Eventually, two simulation examples are introduced to verify the effectiveness of the proposed control strategy and its advantages in lightening communication frequency.
The Power of Symmetries in Nuclear Structure and Some of Its Problems

A review of several classical, algebraic models in nuclear structure physics, which use symmetries as an important tool, are presented. After a conceptual introduction to group theory, a selection of models is chosen to illustrate the methods and the power of the usage of symmetries. This enables us to describe very involved systems in a greatly simplified manner. Some problems are also discussed, when ignoring basic principles of nature, such as the Pauli exclusion principle. We also show that occasionally one can rescue these omissions. In a couple of representative models, applications of symmetries are explicitly applied in order to illustrate how extremely complicated systems can be treated. This contribution is meant as a review of the use of algebraic models in nuclear physics, leading to a better understanding of the articles in the same special volume.
Development of BioPolyurethane Coatings from Biomass-Derived Alkylphenol Polyols—A Green Alternative

Bio-based polyols were obtained from the thermochemical liquefaction of two biomass feedstocks, pinewood and Stipa tenacissima, with conversion rates varying between 71.9 and 79.3 wt. %, and comprehensively characterized. They exhibit phenolic and aliphatic moieties displaying hydroxyl (OH) functional groups, as confirmed by attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) and nuclear magnetic resonance spectroscopy (NMR) analysis. The biopolyols obtained were successfully employed as a green raw material to produce bio-based polyurethane (BioPU) coatings on carbon steel substrates, using, as an isocyanate source, a commercial bio-based polyisocyanate—Desmodur® Eco N7300. The BioPU coatings were analyzed in terms of chemical structure, the extent of the reaction of the isocyanate species, thermal stability, hydrophobicity, and adhesion strength. They show moderate thermal stability at temperatures up to 100 °C, and a mild hydrophobicity, displaying contact angles between 68° and 86°. The adhesion tests reveal similar pull-off strength values (ca. 2.2 MPa) for the BioPU either prepared with pinewood and Stipa-derived biopolyols (BPUI and BPUII). Electrochemical impedance spectroscopy (EIS) measurements were carried out on the coated substrates for 60 days in 0.05 M NaCl solution. Good corrosion protection properties were achieved for the coatings, with particular emphasis on the coating prepared with the pinewood-derived polyol, which exhibited a low-frequency impedance modulus normalized for the coating thickness of 6.1 × 1010 Ω cm at the end of the 60 days test, three times higher than for coatings prepared with Stipa-derived biopolyols. The produced BioPU formulations show great potential for application as coatings, and for further modification with bio-based fillers and corrosion inhibitors.
VAT: The effectivity of electronic tax compliance in the face of the determinants of the tax gap

The quest to reduce the informational asymmetry between tax authorities and taxpayers, increasing tax compliance, was one of the main intentions with the implementation of SPED in Brazil. Thus, the need arose to understand its efficiency, as well as its impact on revenue. In this context, this study focused on assessing whether the implementation of SPED had an impact on the ICMS tax gap, from the perspective of tax auditors, using the PLS-SEM structural equation modeling technique. As a result, the significant influence of the tax gap determinants presented in the literature and SPED on the ICMS tax gap was observed, with emphasis on more agile and comprehensive inspections, greater access to taxpayer information, influence on the taxpayer's decision to reduce the portion of amounts to be withheld and the identification of those who declare amounts lower than those due, contributing with legislators and tax authorities in the development of policies to optimize collection.
MEASUREMENTS AND COMPUTATIONS OF FUEL DROPLET TRANSPORT IN TURBULENT FLOWS

The objective of this project is to study the dynamics of fuel droplets in turbulent water flows. The results are essential for development of models capable of predicting the dispersion of slightly light/heavy droplets in isotropic turbulence. Since we presently do not have any experimental data on turbulent diffusion of droplets, existing mixing models have no physical foundations. Such fundamental knowledge is essential for understanding/modeling the environmental problems associated with water-fuel mixing, and/or industrial processes involving mixing of immiscible fluids. The project has had experimental and numerical components: 1. The experimental part of the project has had two components. The first involves measurements of the lift and drag forces acting on a droplet being entrained by a vortex. The experiments and data analysis associated with this phase are still in progress, and the facility, constructed specifically for this project is described in Section 3. In the second and main part, measurements of fuel droplet dispersion rates have been performed in a special facility with controlled isotropic turbulence. As discussed in detail in Section 2, quantifying and modeling the of droplet dispersion rate requires measurements of their three dimensional trajectories in turbulent flows. To obtain the required data, we have introducedmore » a new technique - high-speed, digital Holographic Particle Image Velocimetry (HPIV). The technique, experimental setup and results are presented in Section 2. Further information is available in Gopalan et al. (2005, 2006). 2. The objectives of the numerical part are: (1) to develop a computational code that combines DNS of isotropic turbulence with Lagrangian tracking of particles based on integration of a dynamical equation of motion that accounts for pressure, added mass, lift and drag forces, (2) to perform extensive computations of both buoyant (bubbles) and slightly buoyant (droplets) particles in turbulence conditions relevant to the experiments, and (3) to explore whether the corresponding predictions can explain the experimentally-observed behavior of the rise and dispersion of oil droplets in isotropic turbulence. A brief summary of results is presented in Section 4. « less
Pressure and temperature dependence of the Ce valence and c -f hybridization gap in Ce T In 5 (T =Co ,Rh ,Ir ) heavy-fermion superconductors

Pressure- and temperature-induced changes in the Ce valence and c-f hybridization of the Ce115 superconductors have been studied systematically. Resonant x-ray-emission spectroscopy indicated that the increase of the Ce valence with pressure was significant for CeCoIn5, and moderate for CeIr(In0.925Cd0.075)5. We found no abrupt change of the Ce valence in the Kondo regime for CeIr(In0.925Cd0.075)5, which suggests that valence fluctuations are unlikely to mediate the superconductivity in this material. X-ray-diffraction results were consistent with the pressure-induced change in the Ce valence. High-resolution photoelectron spectroscopy revealed a temperature-dependent reduction of the spectral intensity at the Fermi level, indicating enhanced c-f hybridization on cooling.