Miracle-dz/UniFAR-FTUs huggingface dataset:
A slip-link model for rheology of entangled polymer melts with crystallization

Many industrial polymer melts are entangled and undergo crystallization during processing. Several recent studies have reported experimental data for the rheology of crystallizing entangled polymers. Meanwhile, over the past few years, slip-link models have been demonstrated to describe the rheology of entangled melts under a variety of nonlinear deformation conditions. In this work, we present a modification of the slip-link model to describe the rheology of an entangled melt undergoing crystallization. The partially crystallized melt is represented by a blend of linear chains with free ends and cross-linked, bridgelike chains with fixed ends that resemble the tie molecules between developing crystallites. Two new parameters are introduced: the fraction of cross-linked chains and a modulus shift factor, both of which are functions of the degree of crystallinity. The model captures the evolution of viscosity and elasticity simultaneously over the whole range of available frequencies in the linear regime. The model is validated using experimental datasets for isotactic polypropylene.Many industrial polymer melts are entangled and undergo crystallization during processing. Several recent studies have reported experimental data for the rheology of crystallizing entangled polymers. Meanwhile, over the past few years, slip-link models have been demonstrated to describe the rheology of entangled melts under a variety of nonlinear deformation conditions. In this work, we present a modification of the slip-link model to describe the rheology of an entangled melt undergoing crystallization. The partially crystallized melt is represented by a blend of linear chains with free ends and cross-linked, bridgelike chains with fixed ends that resemble the tie molecules between developing crystallites. Two new parameters are introduced: the fraction of cross-linked chains and a modulus shift factor, both of which are functions of the degree of crystallinity. The model captures the evolution of viscosity and elasticity simultaneously over the whole range of available frequencies in the linear regime.
Tensor FISTA-Net for Real-Time Snapshot Compressive Imaging

Snapshot compressive imaging (SCI) cameras capture high-speed videos by compressing multiple video frames into a measurement frame. However, reconstructing video frames from the compressed measurement frame is challenging. The existing state-of-the-art reconstruction algorithms suffer from low reconstruction quality or heavy time consumption, making them not suitable for real-time applications. In this paper, exploiting the powerful learning ability of deep neural networks (DNN), we propose a novel Tensor Fast Iterative Shrinkage-Thresholding Algorithm Net (Tensor FISTA-Net) as a decoder for SCI video cameras. Tensor FISTA-Net not only learns the sparsest representation of the video frames through convolution layers, but also reduces the reconstruction time significantly through tensor calculations. Experimental results on synthetic datasets show that the proposed Tensor FISTA-Net achieves average PSNR improvement of 1.63∼3.89dB over the state-of-the-art algorithms. Moreover, Tensor FISTA-Net takes less than 2 seconds running time and 12MB memory footprint, making it practical for real-time IoT applications.
Supplementary Information for Temporal and state abstractions for eﬃcient learning, transfer and composition in humans Potential asymmetry in Block 7 of Experiment 1

We checked whether the performance of circle and square in Block 7 was asymmetrically affected due to the interleaving of odd and even blocks (Fig. 2B). Specifically, participants might start Block 7 by using HO1 in odd blocks; thus the negative transfer in the first stage of Block 7 would be primarily due to more key presses from the square, not the circle. To test this possibility, we calculated average number of key presses in the first 5 trials for circle and square respectively in Block 7. However, we found no significant difference between the performance of circle and square in the first stage (paired t-test, t(24) = 1.38, p = 0.18); we also found no significant difference between the performance in the second stage following circle and square (paired t-test, t(24) = 0.44, p = 0.66).
Instability analysis of carbon nanotubes conveying viscoelastic fluid

The influence of internal moving viscoelastic fluid on single-walled carbon nanotubes (SWCNTs) with two fixed ends is first investigated. The constitutive relation of viscoelastic fluid is presented by a Maxwell non-Newtonian fluid model. A new governing equation of motion of a SWCNT conveying viscoelastic fluid with third-order derivative with respect to time is derived. Differential quadrature method is used to discretize the governing equation, and the complex vibration frequencies of the SWCNT are obtained by solving a cubic eigenvalue problem. It is interesting to observe from computational results that natural frequency of the SWCNT is obviously larger, and decaying rate of the amplitude is smaller, for the larger viscoelastic parameter of the Maxwell fluid.
A cohesive model of dissection in arterial layers

In medical terms and referring to aortic arterial damage, dissection is the separation of intra-medial tissue induced by a radial tear cutting the intima and a portion of the underling media. Pressurized blood pervading the tear usually progresses the intramural process of dissection and may later induces formation of clots. The purpose of this study is to setup a mechanical model of arterial dissection, based on cohesive theories of fracture, able to detect the critical mechanical conditions leading to the tissue damage.
Some physicochemical characteristics of black and white mulberry genotypes from Bosnia and Herzegovina

Some physicochemical characteristics of black and white mulberry genotypes from and Herzegovina. -Genetika, Vol 51, No.3, Recently, Therefore, the focus of this research is to determine some physicochemical properties of mulberry fruits from the area of northwest Bosnia, where significant amount genetic resources of mulberries are available. In total, six genotypes of black and eight genotypes of white mulberries were analyzed. From physical properties, the fruit mass, fruit height, fruit width and length were determined. Black mulberries are found richer than white mulberries for most of the searched parameters. The average water, soluble solids, total acidity, total sugar, ash, vitamin C, total phenol and total anthocyanin of black mulberry genotypes were 86.46%, 14.88%, 0.08%, 7.30%, 0.68%, 45.84 mg/100 g FW (fresh weight), 50.67 mg GAE/100 g FW and 562.42 cyanidin-3-glucoside mg/g. These values were 82.49%, 17.51%, 0.09%, 7.34%, 0.78%, 43.79 mg/100 g FW and 29.49 mg GAE/100 g FW for white mulberries. The obtained results can serve for future steps in the breeding of these species, and because of the high quality fruit characteristics, they can affect the conservation of these species due to the increasing genetic erosion of this species. PC3 PC4
Student Participation in Supplemental Instruction in STEM Courses at a Large Urban Community College in California

ABSTRACT A realist evaluation framework asks what works best for whom under what circumstances. This study utilized a realist evaluation framework to determine which students benefited under what circumstances from supplemental instruction, an academic support program using peer-assisted problem-solving techniques. The study setting was a large urban community college that was also a Hispanic-Serving Institution (HSI), with 80% Hispanic students and over 50% of all students qualifying for financial aid. Two sources of existing administrative data were analyzed using a quasi-experimental design. All science, technology, engineering, and math (STEM) courses in one semester with supplemental instruction (SI) (n = 18 courses in spring 2015) were matched to STEM courses that did not have SI (n = 35). Student-level comparisons based on the number of SI sessions attended were also made (N = 1,851). Three research questions were analyzed: (a) what was the pattern of SI participation? ; (b) Did course pass rates increase with SI participation? ; and (c) Were grade outcomes different based on SI participation? Results indicated that as expected, SI participation was higher among students in SI STEM courses (33.4%) compared to those in non-SI supported STEM courses (5.3%). In addition, increasing numbers of students passed their courses with increasing SI session attendance. Mean grade differences of just under half a grade were found, favoring students who attended one or more SI sessions. Across all students and in math courses, more students who attended SI earned higher grades (A’s, B’s, C’s) and fewer withdrew or received an F compared to students who did not attend SI.
Video reflection: An emerging tool for training client‐centred communication skills in staff supporting adults with learning disabilities in an education setting

Speech and Language Therapists (SLTs) contribute to communication with adults with learning disabilities by providing training to the networks that support them. The requirements for successful communication with this population are frequently complex and necessitate an effective training medium to transfer the target knowledge and skills. Video has increasingly been used as a tool to facilitate self-reflection and behaviour change. Currently there is limited research into the effectiveness of video-based training in education settings for adults with learning disabilities. Therefore, this study investigated the effectiveness of Video-Reflection Training (VRT) for support staff in a college for adults with learning disabilities.
GAAS: An Efficient Group Associated Architecture and Scheduler Module for Sparse CNN Accelerators

Convolutional neural networks (CNNs) have become powerful algorithms in various tasks. Application-specific integrated circuit (ASIC) has been widely used to accelerate CNN on mobile platforms because of its tremendous energy efficiency and performance. Meanwhile, CNNs have become much sparser with the development of network pruning algorithms. Recent works have employed different methods to improve the energy efficiency and performance of ASIC accelerators by utilizing the sparsity character of CNN. However, some of these methods suffer from tremendous output memory overhead and performance degradation induced by hash collisions. To overcome the aforementioned problem, we propose GAAS: an efficient group associated architecture and scheduler module for sparse CNN accelerators. It achieves smaller output memory overhead and higher performance compared with the state-of-the-art accelerator. Our proposed method GAAS mainly consists of two parts: 1) an <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>-way group associated architecture to reduce the output memory overhead and 2) a scheduler module to improve the performance. Besides, a load-balancing algorithm is proposed and implemented in the scheduler module to improve the performance by reducing the hash collision rate. To demonstrate the efficiency of GAAS, we implement a 4-way image-principal associated architecture with a <inline-formula> <tex-math notation="LaTeX">$16\times 16$ </tex-math></inline-formula> PE array and the scheduler module on our proposed method. The experimental results on AlexNet, VGG16, ResNet18, and MobileNet show that GAAS can reduce the output memory overhead by 50%, and it can surely improve the performance of them by <inline-formula> <tex-math notation="LaTeX">$1.53\times $ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$1.62\times $ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$1.46\times $ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$1.55\times $ </tex-math></inline-formula>, respectively.
The prediction of quality characteristics of cotton/elastane core yarn using artificial neural networks and support vector machines

Core yarn is a type of yarn that has a filament fiber in the center with a different fiber wrapped around it. This type of yarn is of growing importance in the textile industry. It is important to predict the quality characteristics of a core yarn before production to prevent the faulty production of fabrics. Therefore, the development of predictive models is a necessity in the textile industry. In this study, artificial neural network (ANN) and support vector machine (SVM) models are proposed to predict the quality characteristics of cotton/elastane core yarn, using fiber quality and spinning parameters. Principal component analysis and analysis of variance techniques are also used to reduce input dimensions, since high dimensional data may reduce a model’s potential for success in prediction. The prediction models are trained and tested using the data obtained from a textile production plant. The results of all the models are compared with each other on test data. Mean absolute percentage error (MAPE), mean absolute error (MAE) and correlation coefficient (R) are used to assess the prediction power of the models. Although on most of the tests SVM models fared slightly better than ANN models, both models provide accurate predictions for most of the yarn quality characteristics. The results show that the best models have over 90% success rate in MAPE and R. In particular, the Coefficient of Variance of mass (CVm) along the yarn, hairiness and Reisskilometer quality characteristics of the cotton/elastane core yarn are predicted with 91%, 93% and 95% accuracy, respectively.
Electron beam irradiated maize starch: Changes in structural, physicochemical properties, and digestibility

Electron beam (EB) irradiation was applied on maize starch at doses from 0 to 7 kGy. Electron beam irradiation resulted in (a) depolymerization of starch molecules, (b) formation of cross-linkages leading to the increasing of crystalline regions, and (c) degradation of the large crystalline region to smaller one. The increasing of irradiation dose resulted in the reduction of pH, reduced viscosity, molecular weight, and the increase of free acid content. During treatment, the color of the sample became darker. FITR spectra, A-type X-ray diffraction pattern and the ratio of amorphous/alpha-helix region of starches were not significantly changed during treatment. These mechanisms above caused not only the changes in amylose content but also the reduction of swelling factor and the increase of solubility. Furthermore, the interaction of these mechanisms could be explained to the conversion between slowly digestible starch and resistant starch fractions.
Graft-versus-host disease following living donor liver transplantation: high risk when the donor is HLA-homozygous

Graft-versus-host disease (GVHD) is the most common and well-known cause of morbidity and mortality following allogeneic bone marrow transplantation. Sporadic cases have been reported after cadaveric donor liver transplantation with usually fatal outcomes, however, the actual incidence and the characteristics of GVHD after living donor liver transplantation (LDLT) remain unknown. We herein report a person who developed fatal GVHD following LDLT and discuss the applicability of an HLA-homozygous donor to an HLA-haploidentical recipient. A 48-year-old male underwent LDLT for unresectable hepatocellular carcinoma with alcoholic liver cirrhosis. The donor was his 20-year-old son whose pretransplant HLA typing was homozygous at all loci. GVHD occurred 35 days after LDLT and was characterized by fever, diarrhea, maculopapular rash, and leukopenia, which led to the development of fatal pneumonia. We identified 4 cases of GVHD after LDLT in Japan and 1 in the United States, all associated with the use of an HLAhomozygous donor. The use of an HLA homozygous donor which results in a complete 1-way donor-recipient HLA match carries an extremely high risk of developing GVHD after LDLT. Therefore, it is possible that LDLT should be ruled out for such donors. A pretransplant work-up of the HLA type in both the donors and recipients is therefore imperative before determining the indications for LDLT. [Abstract reproduced by permission of Liver Transpl 2004; 10: 460–4]
Semi-automated setup of CFD simulations of rectangular cylinders and streamlined box decks

A piece of software that acts as a Graphical User Interface (GUI) for the setup of computational fluid dynamics (CFD) models that are solved by means of the open source code OpenFOAM, is presented. The software is extensively described, with emphasis in the generation of block structured meshes using hexahedral elements. This computer program has been developed aiming at being applied in wind engineering problems of interest in civil engineering, such as the computation of force coefficients, flutter derivatives and vortex-induced vibrations. It has been devised to deal efficiently with rectangular cylinders and streamlined box decks. This software demands limited intervention from the user, and its core routines can be embedded in automated design processes such as parametric or optimal design problems in wind engineering. Two application examples have been considered: static and forced oscillation simulations of both, a side ratio 2:1 rectangular cylinder and a streamlined box deck. It has been found that this software is an efficient tool for the setup of URANS simulations in OpenFOAM, while the numerical results obtained for the studied aerodynamic and aeroelastic phenomena show good agreement with wind tunnel data, and their level of accuracy is equivalent to other CFD-based simulations.
Monitoring of noncommunicable diseases

Abstract Noncommunicable diseases (NCDs) represent a major fraction of the global health burden in terms of morbidity and mortality, and its prevalence is on the rise across the world. As more and more people are living with various NCD, primary and secondary prevention becomes an important tool to contain this impending epidemic. The spectrum of major NCD includes cardiovascular disorders (CVD), diabetes mellitus (DM), chronic obstructive pulmonary disorder (COPD), and cancer, with CVD contributing to the majority of deaths attributed to NCD. Control of hypertension is important intervention which can significantly decrease the risk of CVD, which can be achieved by three-pronged approaches such as encompassing dietary, physical exercise, and pharmacological interventions. Monitoring is an integral part of this approach, wherein recording of blood pressure and various investigations are required to be done at variable intervals. DM is an important NCD where primary and secondary preventions are of paramount importance. Similarly, other NCDs such as COPD and cancer also require various monitoring protocols. In this article, we review the current concepts in monitoring and prevention of major NCDs along with the recommendations from the scientific societies.
Automatic Wheeze Detection System as Symptoms of Asthma Using Spectral Power Analysis

People all over the world live and die from, respiratory disorders. It doesn’t matter who suffer may be young or old. This respiratory problem they have from birth or develop in certain environmental condition over the years. Wheezes are more musical respiratory sounds as compared to normal respiratory sound, which usually due to pathological condition of the respiratory system especially irregularities in pulmonary obstruction, such as asthma and chronic obstructive pulmonary disease (COPD). Identification of the Wheeze sound is the first step in controlling the asthma. Using that easy to understand the disease progress, and how close research to developing new test and treatments and what still needs to be done. Although many studies have addressed the problem of wheeze detection, a limited number of scientific works has focused on real time detection of wheeze sound. As day to day increasing number of asthmatic patient there is a need of automatic monitoring of the wheeze sound to assist the physicians in diagnosing and monitoring the patient. The purpose of this study was to develop automatic wheeze detection systems with spectral power estimation in real time to assist the physicians in diagnosing and monitoring the patient.
VALIDITY OF THE PHYSICAL ACTIVITY BEHAVIOR QUESTIONNAIRE (QCAF) AMONG HEALTHY AND UNHEALTHY INDIVIDUALS

Aim: The aim of this study was to test the convergent and divergent validity of the Physical Activity Behavior Questionnaire (QCAF, acronym in Portuguese for Questionario do Comportamento de Atividade Fisica), an instrument developed based on the Theory of Planned Behavior.Methods: An exploratory study was conducted in an outpatient clinic among 236 individuals referred for cardiopulmonary exercise testing with oxygen uptake. Coronary heart disease, hypertensive and healthy individuals were enrolled. PA was measured by the QCAF and the Baecke Habitual PA Questionnaire (Baecke-HPA). Cardiorespiratory fitness was estimated by the Veterans Specific Activity Questionnaire (VSAQ), the peak (VO2peak) and the maximum oxygen uptake (VO2max). Results: The convergent validity was verified by the confirmed relation between the QCAF and the measures of physical activity – Baecke-HPA (radj=0.32; p<0.0001) and cardiorespiratory fitness – VO2peak (radj=0.15; p=0.02), VO2max (radj=0.13; p=0.05) and VSAQ (radj=0.13; p=0.05). The divergent validity was confirmed by the absence of significant correlations between the QCAF and the Occupational Physical Activity domain of the Baecke-HPA (r=0.04; p=0.49), as expected.Conclusion: The QCAF presented acceptable levels of convergent and divergent validity, demonstrating to be a useful tool in order to measure walking among a diverse adult population.
Division of labor between YAP and TAZ in non-small cell lung cancer

Lung cancer is the leading cause of cancer-related deaths worldwide. The paralogous transcriptional cofactors Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ, also called WWTR1), the main downstream effectors of the Hippo signal transduction pathway, are emerging as pivotal determinants of malignancy in lung cancer. Traditionally, studies have tended to consider YAP and TAZ as functionally redundant transcriptional cofactors, with similar biological impact. However, there is growing evidence that each of them also possesses distinct attributes. Here, we sought to systematically characterize the division of labor between YAP and TAZ in non-small cell lung cancer (NSCLC), the most common histological subtype of lung cancer. Employing representative NSCLC cell lines, as well as patient-derived data, we show that the two paralogs orchestrate non-overlapping transcription programs in this cancer type: whereas YAP preferentially regulates gene sets associated with cell division and cell cycle progression, TAZ preferentially regulates genes associated with extracellular matrix organization. Concordantly, depletion of YAP, but not TAZ, leads to growth arrest, while YAP overexpression promotes cell proliferation. Likewise, depletion of TAZ, but not YAP, compromises cell migration, whereas TAZ overexpression enhances migration. Importantly, the differential effects of YAP vs TAZ on key cellular processes are also associated with differential response to anti-cancer therapies. Uncovering the different activities and downstream effects of YAP and TAZ may thus facilitate better stratification of lung cancer patients for anti-cancer therapies.
NEURONAL CULTURE AT SINGLE CELL LEVEL FOR CREATION OF BIOLOGICAL NEURONAL NETWORK

To understand the electrophysiological dynamics of neurons, the use of micro-electrode array (MEA) is common because it is non-invasive and it allows long-term monitoring. However, as the culture are randomly arranged on fixated electrodes, it is not capable of recording electrophysiology at single cell level. Here, we present a fully transparent neuronal culture device capable of monitoring cells growth or activity at single scale level. To trap cells singularly, dielectrophoresis is used on a ITO glass coated with fluoropolymer component called CYTOP® to manipulate cells.