Miracle-dz/UniFAR-FTUs huggingface dataset:
Fabrication and research of 3D complex scaffolds for bone tissue engineering based on extrusion–deposition technique

Fabrication of scaffold is the key for bone tissue engineering, which is commonly regarded as the most potential route for repairing bone defects. Previously, porous ceramic scaffolds were fabricated through a variety of traditional methods, like moulding and casting, but most of them cannot produce customised tissue-engineered scaffolds. Therefore, 3D printing methods are gaining more attention and are currently being explored and developed to make scaffolds with acceptable biocompatibility. With the considerable development of bone tissue engineering, the bioactivity of scaffolds is becoming increasingly demanded, which leads to new methods and techniques to produce highly biomimetic bone scaffolds. In this study, a new fabrication process to optimise the structures of scaffolds was developed, and intensive researches were performed on the porous scaffolds to confirm their advantages in biological performance. Specifically, by combination of motor assisted extrusion deposition and gas-foaming (graphite as the porogen) technique, hierarchically porous scaffolds with improved microstructures, i.e. multi-scaled pores from nanometre to millimetre (nm-μm-mm), was successfully developed. In this thesis, the optimal content of porogen for scaffolds was studied in terms of compressive strength and in-rod porosities. The most concerned physicochemical properties of scaffolds were carefully examined and the results revealed that such scaffolds exhibit excellent physicochemical properties owing to hierarchically porous structures. Due to additional in-rod micropores and increased specific surface area, along with better hydrophilicity, hierarchically porous scaffolds exerted complete superiority in biological activity, including promoting cellular proliferation of osteoblasts, adhesion and spreading status, as well as the ability to induce cellular differentiation.
Synchronous Distributed Load Balancing on Totally Dynamic Networks

In this paper, first order diffusion load balancing algorithms for totally dynamic networks are investigated. Totally dynamic networks are networks in which the topology may change dynamically. Some edges or nodes can appear, disappear or move during the time. In our previous works on dynamic networks, the dynamism was limited to the edges. The main result of this study consists in proving that the load balancing algorithms reduce the unbalance on arbitrary dynamic networks. Notice that the hypotheses of our result are realistic and that for example the network does not have to be maintained connected. To study the behavior of these algorithms, we compare the load evolution by several simulations.
Positron-trapping mechanism at dislocations in Zn.

The evolution of the positron-lifetime parameters with the measuring temperature has been studied in deformed Zn in the temperature range 12\char21{}210 K. For two samples with different degrees of deformation the presence of a component with a lifetime close to that in a monovacancy is observed. Both the average lifetime and the intensity of the long component decrease with increasing temperature. The experimental results are very well described in terms of a generalized trapping model where it is assumed that positrons become trapped in deep traps (jogs) via shallow traps (dislocation lines). The temperature dependence of the positron-lifetime spectra below 120 K is attributed to the temperature dependence of the trapping rate to the dislocation line. The experimental results have demonstrated that detrapping processes from the dislocation line take place above 120 K. The positron binding energy to the dislocation line has been shown to be 40\ifmmode\pm\else\textpm\fi{}20 meV.
Multimodal Assessment of Conversational Engagement in Persons with Parkinson ’ s Disease

Our capacity to engage in meaningful conversations depends on a multitude of communication cues: verbal delivery of articulate and intelligible speech, tone and modulation of voice, exhibition of a range of facial expressions, and display of body gestures, among others.Parkinson’s disease diminishes verbal and non-verbal communication facilities in affected persons. Occupational therapists measure the expressive behavior of persons with Parkinson’s through observation and interaction. In this paper, we propose a computational model of measuring expressiveness and engagement. We record persons engaged in conversation and compute descriptors from multiple modalities (face, body, voice). We train a regression model from these multimodal features to scores obtained from domain experts and seek to answer the following questions. First, can a machine learning model be trained to accurately score expressive behavior? Second, what multimodal features are important in order to assess the level of conversational engagement? Third, what is the minimum length of observation required by the model to make an accurate prediction?
How Science Takes Stock: the Story of Meta-analysis

Morton Hunt Russell Sage Foundation, 24$, pp 256 ISBN 0 87154 389 3 Rating: ! [Graphic][1] ! [Graphic][2] ! [Graphic][3] Morton Hunt has mastered the seemingly impossible task of conveying to a broad range of readers, in a language that can be understood by all, the genesis and development of meta-analysis. Althugh only recently “discovered” in medicine, meta-analysis has a longer tradition in the social sciences, particularly psychology, and this is where Hunt begins his story. Many of the personalities who helped develop meta-analysis are interviewed, including Gene Glass, Joseph Lau, Graham Colditz, and both Iain and Tom Chalmers. Several important developments are reviewed, … [1]: /embed/inline-graphic-1.gif [2]: /embed/inline-graphic-2.gif [3]: /embed/inline-graphic-3.gif
Structural Attention Neural Networks for improved sentiment analysis

We introduce a tree-structured attention neural network for sentences and small phrases and apply it to the problem of sentiment classification. Our model expands the current recursive models by incorporating structural information around a node of a syntactic tree using both bottom-up and top-down information propagation. Also, the model utilizes structural attention to identify the most salient representations during the construction of the syntactic tree.
A Methodology for Power Aware High-Level Synthesis of Co-processors from Software Algorithms

Hardware co-processors are used for accelerating specific compute-intensive tasks dedicated to video/audio codec, encryption/decryption, etc. Since many of these data-processing tasks already have efficient software algorithms, one could reuse those to synthesize the co-processor IPs. However, such software algorithms are usually sequential and written in C/C++. High-level Synthesis (HLS) helps in converting software implementation to register transfer level (RTL) hardware design. Such co-processor based systems show enhanced performance but often have greater power/energy consumption. Therefore, the automated synthesis of such accelerator IPs must be power-aware. Downstream power savings features such as clock-gating are unknown during HLS. Designer is forced to take such power-aware decisions only after logic synthesis stage, causing an increase in design time and effort. In this paper, we present a design automation solution to facilitate various granularities of clock-gating at high-level C description of the design.
The modified sleeper stretch and modified cross-body stretch to increase shoulder internal rotation range of motion in the overhead throwing athlete.

SYNOPSIS Stretching techniques that focus on increasing posterior shoulder soft tissue flexibility are commonly incorporated into prevention and treatment programs for the overhead athlete. The cross-body and sleeper stretch exercises have been described as stretching techniques to improve posterior shoulder soft tissue flexibility and to increase glenohumeral joint internal rotation and horizontal adduction range of motion in the overhead athlete. But, based on the inability to stabilize the scapula and control glenohumeral joint rotation with the cross-body stretch and the potential for subacromial impingement with the sleeper stretch, the authors recommend modifications to both of these commonly performed stretches. This clinical commentary reviews the literature on posterior shoulder stretches, describes modifications to both of these commonly performed stretches, and outlines a strategy to maintain or improve posterior shoulder soft tissue flexibility and glenohumeral joint internal rotation range of motion in the overhead athlete. LEVEL OF EVIDENCE Therapy, level 5.
Miniaturized watt-level laser modules emitting in the yellow-green spectral range for biophotonic applications

Many biophotonic applications used in ophthalmology, dermatology, or flow cytometry rely on laser sources emitting in the yellow-green spectral range. To enable miniaturized laser sources one has to rely on diode lasers. As no direct emitting diode lasers with excellent beam qualities are readily available in this wavelength range, second harmonic generation (SHG) of novel diode lasers emitting wavelengths of 1120 nm and 1152 nm is one feasible approach. For high SHG conversion efficiencies a high beam quality as well as a high optical output power of the fundamental laser light is needed. Our approach is a hybrid integrated master oscillator power amplifier (MOPA) setup which incorporates an optical micro-isolator to protect the MO against back reflections and thereby keep high mode stability. Using individually designed and machined parts based on the results of optical simulations, a platform to integrate different laser system setups has been realized. Using this platform, we were able to compare different approaches of SHG (using planar waveguide or volume LiNbO3 crystals) and beam output possibilities (free space or fiber-coupled) to satisfy a wide range of applications. In this work we show novel miniaturized diode laser modules emitting more than 2 W and 1.6 W at wavelengths of 560 nm and 576 nm, respectively, which can be used in a wide range of biophotonic applications.
Blood–spinal cord barrier permeability in experimental spinal cord injury: dynamic contrast‐enhanced MRI

After a primary traumatic injury, spinal cord tissue undergoes a series of pathobiological changes, including compromised blood–spinal cord barrier (BSCB) integrity. These vascular changes occur over both time and space. In an experimental model of spinal cord injury (SCI), longitudinal dynamic contrast‐enhanced MRI (DCE‐MRI) studies were performed up to 56 days after SCI to quantify spatial and temporal changes in the BSCB permeability in tissue that did not show any visible enhancement on the post‐contrast MRI (non‐enhancing tissue). DCE‐MRI data were analyzed using a two‐compartment pharmacokinetic model. These studies demonstrate gradual restoration of BSCB with post‐SCI time. However, on the basis of DCE‐MRI, and confirmed by immunohistochemistry, the BSCB remained compromised even at 56 days after SCI. In addition, open‐field locomotion was evaluated using the 21‐point Basso–Beattie–Bresnahan scale. A significant correlation between decreased BSCB permeability and improved locomotor recovery was observed. Copyright © 2008 John Wiley & Sons, Ltd.
Reversal of SIN‐1‐induced eNOS dysfunction by the spin trap, DMPO, in bovine aortic endothelial cells via eNOS phosphorylation

Nitric oxide (NO) derived from eNOS is mostly responsible for the maintenance of vascular homeostasis and its decreased bioavailability is characteristic of reactive oxygen species (ROS)‐induced endothelial dysfunction (ED). Because 5,5‐dimethyl‐1‐pyrroline‐N‐oxide (DMPO), a commonly used spin trap, can control intracellular nitroso‐redox balance by scavenging ROS and donating NO, it was employed as a cardioprotective agent against ED but the mechanism of its protection is still not clear. This study elucidated the mechanism of protection by DMPO against SIN‐1‐induced oxidative injury to bovine aortic endothelial cells (BAEC).
Progesterone and 17β‐estradiol increase differentiation of mouse embryonic stem cells to motor neurons

Embryonic stem (ES) cells have the capacity to differentiate into endodermal, mesodermal, and ectodermal lineages. Motor neuron (MN) differentiation of mouse ES cells involves embryoid bodies formation with addition of Sonic hedgehog and retinoic acid. In this work, using immunocytochemistry, flow cytometry, and quantitative RT‐PCR, we investigated whether progesterone or 17β‐estradiol have inductive effects on ES cell‐derived MN, as it has been demonstrated that these hormones modify proliferation and neural differentiation of pluripotent cells. When 100 nM progesterone was added during differentiation, we found higher proportions of MN, compared to the control condition; coincubation of progesterone with the progesterone receptor (PR) antagonist RU‐486 caused a decrease in the number of MN to a percentage even lower than controls. The addition of nanomolar concentrations of 17β‐estradiol also significantly induced MN differentiation. This effect of estradiol was completely antagonized by addition of the general estrogen receptor (ER) antagonist ICI 182,780. To identify the ER subtype mediating the increase on MN differentiation, we incubated estradiol with the ER‐α antagonist MPP or with the ER‐β blocker PHTPP. When we coincubated 17β‐estradiol with MPP, we found a significant decrease in the percentage of MN. In contrast, the coincubation of 17β‐estradiol with PHTPP had no effect on the induction of MN differentiation. All these effects on cell number were confirmed by significant changes in the expression of the MN markers Islet‐1 and Choline acetyl transferase, assessed by real‐time RT‐PCR. Cell proliferation in embryoid bodies was significantly enhanced by progesterone treatment. No changes in apoptotic cell death were found in differentiating cells after progesterone or 17β‐estradiol addition. Our findings indicate that progesterone and 17β‐estradiol induce a higher proportion of MN derived from mouse ES cells through intracellular PR and ER, respectively. Furthermore, the effect of estradiol was mediated by specific activation of ER‐α. © 2011 IUBMB IUBMB Life, 2011
How Can We Define Recovery after Acute Kidney Injury? Considerations from Epidemiology and Clinical Trial Design

The recent recognition that acute kidney injury (AKI) may lead to the development of chronic kidney disease and end-stage renal disease, with the attendant increase in mortality, has led to interest in the clinical epidemiology and the mechanistic understanding of renal recovery after an episode of AKI. At present, no uniform definition for recovery after AKI exists and various considerations should be taken into account in the development of a definition. Renal recovery after an AKI episode may affect clinical decision making around the initiation of renal replacement therapy, and has significant implication for biomarker assessment and identification of mechanistic targets to guide potential future clinical trials.
A critical comment

Operating systems are designed to serve user needs and maximize system performance and efficiency. There exists, however, a basic problem in formulating operating system goals. The computer world has been groping in the dark in the most fundamental matters of basic user information. Who are computer users? What occupational categories do they come from? what problems do they work on? With what kinds of computers, computer configurations, and computer languages? What experience do they have with computer facilities? To my knowledge, we have never undertaken a definitive census on computer users, their characteristics and their applications. As a result, everyon e is second-guesslng everyone else as to what computer users are doing and where they are going-even the biggest firms are no exception to this rule. Intelligent growth of the computer industry and intelligent public response to the use and extension of computers requires emplricalp up-to-date frequency counts of user populations and their computer applications. One way to work toward a definitive computer census is to collect pilot data on a small scale, refine attributes on the basis of initial Inputs~ obtain feedback from representative user groups on the value of such pooled statistics, iteratej and converge toward a field-tested plan for a more ambitious computer user census, perhaps on a national scale under top-level sponsorship. In working toward this eventual posslbilltyj the chairman of SIGOPS has suggested that members (or other interested individuals) who have access to such data from their own organizations, together with any useful suggestions or ideas in this area, send them to Hal Sackman [address above]. Perhaps the pooling of such data might provide a critical mass to work toward respectable and worthwhile statistics on the growing legions of computer users for the mutual benefit of all. It is generally agreed that computer manufacturers and computer users should work together In developing new systems. But who should take the lead In the design process? Presently the manufacturers appear to take the long term lead while users take the short term lead. The manufacturers attempt to serve user trends while user innovations are restricted to employing current machines better. There are many shortcomings to these techniques.
A New Framework for Cloud based Application Testing

Cloud computing has gained considerable interest in recent years as a new paradigm for developing and delivering computing applications and services via existing affordable infrastructures. Software development process has changed under the impact of cloud computing, software testing is also part of this process. Cloud testing is a rapidly developing area of research in software engineering. It's ironic that the compressed development cycle for SaaS practically increases the overall testing effort. In this paper we introduce a new framework for cloud testing that is based on the ISTQB standard framework and according to the requirements and cloud testing steps. The framework include developing test scenarios, test cases design, select cloud service provider, setup infrastructure, leverage cloud servers, start testing, monitor test progress, test report and finally test closure. Each of these steps are included some activities.
Optical gas sensing properties of gold-nanoparticle incorporated LSTO films at high temperature

In-situ sensing in high temperature and chemically reactive environments – i.e., within solid oxide fuel cells or power plant boiler systems – is inherently challenging due to the rapid degradation of most traditional sensor materials within this regime. Although optical fiber based sensors provide clear advantages in this context, progress in this area of application has hinged on the development of (a) optical fiber materials and (b) thin film materials with strong optical response to gas environment, both of which must resist degradation under such conditions. Conducting metal oxide thin films have been examined in the literature as a candidate to solve the latter problem, due to a free-carrier governed optical response in the NIR (1-2 μm), that can be strongly dependent upon gas environment. In this work, we present the impact of incorporating gold nanoparticles in one such metal oxide, lanthanum-doped strontium titanite (LSTO), on the gas sensing response, both in the NIR and UV-VIS range. Via optical transmission measurements performed at high temperature (up to 800 C), the intertwined free-carrier response of the film and the localized surface plasmon response of the nanoparticles are examined in the presence of hydrogen of varying concentration. Measurements are presented for films coated both on planar substrates and on optical fibers.
Combining Review Text Content and Reviewer-Item Rating Matrix to Predict Review Rating

E-commerce develops rapidly. Learning and taking good advantage of the myriad reviews from online customers has become crucial to the success in this game, which calls for increasingly more accuracy in sentiment classification of these reviews. Therefore the finer-grained review rating prediction is preferred over the rough binary sentiment classification. There are mainly two types of method in current review rating prediction. One includes methods based on review text content which focus almost exclusively on textual content and seldom relate to those reviewers and items remarked in other relevant reviews. The other one contains methods based on collaborative filtering which extract information from previous records in the reviewer-item rating matrix, however, ignoring review textual content. Here we proposed a framework for review rating prediction which shows the effective combination of the two. Then we further proposed three specific methods under this framework. Experiments on two movie review datasets demonstrate that our review rating prediction framework has better performance than those previous methods.
Functional Linear Models for Association Analysis of Quantitative Traits

Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F‐distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT‐O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT‐O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study.