Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression profiling of transforming growth factor beta superfamily genes in developing orofacial tissue.

BACKGROUND Numerous signaling molecules have been shown to participate in the dynamic process of orofacial development. Among these signal mediators, members of the transforming growth factor beta (TGFbeta) superfamily have been shown to play critical roles. Developing orofacial tissue expresses TGFbeta and bone morphogenetic protein (BMP) mRNAs, their protein isoforms and TGFbeta- and BMP-specific receptors. All these molecules display unique temporospatial patterns of expression in embryonic orofacial tissue, suggesting functional roles in orofacial development. For example, the TGFbetas and BMPs regulate maxillary mesenchymal cell proliferation and extracellular matrix synthesis. This is particularly noteworthy in that perturbation of either process results in orofacial clefting. Although the cellular and phenotypic effects of the TGFbeta superfamily of growth factors on embryonic orofacial tissue have been extensively studied, the specific genes that function as effectors of these cytokines in orofacial development have not been well defined. METHODS In the present study, oligonucleotide-based microarray technology was utilized to provide a comprehensive analysis of the expression of the panoply of genes related to the TGFbeta superfamily, as well as those encoding diverse groups of proteins functionally associated with this superfamily, during orofacial ontogenesis. RESULTS Of the 7000 genes whose expression was detected in the developing orofacial region, 249 have been identified that encode proteins related to the TGFbeta superfamily. Expression of some (27) of these genes was temporally regulated. In addition, several candidate genes, whose precise role in orofacial development is still unknown, were also identified. Examples of genes constituting this cluster include: TGFbeta1-induced antiapoptotic factor-1 and -2, TGFbeta-induced factor 2, TGFbeta1 induced transcript-1 and -4, TGFbeta-inducible early growth response 1, follistatin-like 1, follistatin-like 3, transmembrane protein with EGF-like and two follistatin-like domains (Tmeff)-1 and -2, nodal modulator 1, various isoforms of signal transducers and activators of transcription (Stat), notch, and growth and differentiation factors. CONCLUSIONS Elucidation of the precise physiological roles of these proteins in orofacial ontogenesis should provide unique insights into the intricacies of the TGFbeta superfamily signal transduction pathways utilized during orofacial development.
Assessment of Scaffolding Properties for Chondrogenic Differentiation of Adipose-Derived Mesenchymal Stem Cells in Nasal Reconstruction

Importance Nasal reconstruction in patients who are missing a significant amount of structural nasal support remains a difficult challenge. One challenge is the deficiency of cartilage left within the nose as a consequence of rhinectomy or a midline destructive disease. Historically, the standard donor source for large quantities of native cartilage has been costal cartilage. Objective To enable the development of protocols for new mesenchymal stem cell technologies as alternative procedures with reduced donor site morbidity, risk of infection and extrusion. Design, Setting, and Materials We examined 6 popular scaffold materials in current practice in terms of their biodegradability in tissue culture, effect on adipose-derived mesenchymal stem cell growth, and chondrogenic fate commitment. Various biomaterials of matching size, porosity, and fiber alignment were synthesized by electrospinning and overlaid with rabbit adipose-derived mesenchymal cells in media supplemented or not with chondrogenic factors. Experiments were performed in vitro using as end points biomarkers for cell growth and chondrogenic differentiation. Polydioxanone (PDO), poly-3-hydroxybutyrate-co-3-hydroxyvalerate (PHBV), PHBV-polycaprolactone, poly(L-lactide-co-caprolactone), poly(lactic-co-glycolic acid), and polystyrene scaffolds of 60% to 70% porosity and random fiber alignment were coated with poly(L)-lysine/laminin to promote cell adhesion and incubated for 28 days with 2.5 to 3.5 × 105 rabbit adipose mesenchymal cells. Main Outcomes and Measures Cell growth was measured by fluorometric DNA quantitation and chondrogenic differentiation of stem cells by spectrophotometric sulfated glycosaminoglycan (sGAG) assay. Microscopic visualization of cell growth and matrix deposition on formalin-fixed, paraffin-embedded tissue sections was performed, respectively, with nuclear fast red and Alcian blue. Results Of 6 scaffold materials tested using rabbit apidose mesenchymal cells, uncoated scaffolds promoted limited cell adhesion but coating with poly(L)-lysine/laminin enabled efficient cell saturation of scaffold surfaces, albeit with limited involvement of scaffold interiors. Similar growth rates were observed under these conditions, based on DNA content analysis. However, PDO and PHBV/PCL scaffolds supported chondrogenic fate commitment better than other materials, based on soluble sGAG analysis and microscopic observation of chondrogenic matrix deposition. The mean (SD) sGAG scaffold values expressed as fold increase over control were PDO, 2.26 (0.88), PHBV/PCL, 2.09 (0.83), PLCL, 1.36 (0.39), PLGA, 1.34 (0.77), PHBV, 1.07 (0.31), and PS, 0.38 (0.14). Conclusions and Relevance These results establish materials, reagents, and protocols for tissue engineering for nasal reconstruction using single-layer, chondrogenically differentiated, adipose-derived mesenchymal stem cells. Stackable, scaffold-supported, multisheet bioengineered tissue may be generated using these protocols. Level of Evidence NA.
Lung Shunting: An Indicator of Survival, But Not Necessarily a Tool for Selecting Patients for Radioembolization.

9. Yeom KW, Mitchell LA, Lober RM, et al. Arterial spin-labeled perfusion of pediatric brain tumors. AJNR Am J Neuroradiol 2014;35(2):395–401. analysis because tumor absorbed doses are known to correlate with outcome (3,4). Second, imaging of 99mTc-MAA more than 1 hour after injection can lead to an increased LSF (the study by Narsinh and colleagues used a 2-hour limit) (5). Most importantly, however, LSF was calculated with planar imaging only, which is known to overestimate LSF. Factors causing overestimation may include spillover of liver counts in the lungs due to organ overlap, scatter, and respiratory motion (2). It would be interesting to study whether LSF is still an independent prognostic factor, or perhaps an even stronger prognostic factor, in case LSF is more accurately calculated by using attenuationand scatter-corrected SPECT/computed tomography (CT). LSF as a prognostic factor could reflect a more aggressive tumor with immature vessels that allow arteriovenous shunting. Although these patients have a worse prognosis, it does not imply that they benefit less from radioembolization than do patients with an LSF of 10% or less. Therefore, there is at this moment no reason to withhold therapy from patients with an LSF greater than 10%.
On benchmark properties for adaptive operator selection

Adaptive Operator Selection (AOS) algorithms are on-line adaptive techniques that adjust the probability of applying search operators to the current solution(s). Recent work has proposed new adaptation mechanisms and have tested them empirically on either artificial reward environments or on simple benchmark functions [4], [1], [2], [3]. In this short note we would like to reflect on the properties we should expect of AOS algorithms. In addition we also discuss which of these properties are being tested by simple benchmark functions like the omnipresent OneMax problem. As noted in [3], AOS algorithms basically consist of two components. First, one needs to define the credit assignment mechanism that specifies how operators are rewarded for their contribution to the search process. Secondly, one needs to define the operator selection rule that adapts the probabilities with which operators are selected during the search. The first component’s task is to continuously measure the performance of the search operators. The second component’s task is to select the appropriate operator based on their performance estimate. Here we focus on the second component. Successfull AOS algorithms should have at least the following properties:
Finite-element modeling predicts possibility of thermoelectrically cooled lead-salt diode lasers

Finite-element thermal modeling shows that thermoelectric cooled operation of IV-VI semiconductor diode lasers is possible by replacing the thermally resistive lead-salt substrate with copper. Contrasting thermal models reveal a 63 K decrease in active region temperature under normal operating conditions when PbTe is replaced with copper. This improved device structure can be obtained by using epitaxial-lift-off techniques similar to those developed for III-V semiconductor devices.
Privacy-Preserving Ridge Regression on Distributed Data

Linear regression is an important statistical tool that models the relationship between some explanatory values and an outcome value using a linear function. In many current applications (e.g. predictive modelling in personalized healthcare), these values represent sensitive data owned by several different parties that are unwilling to share them. In this setting, training a linear regression model becomes challenging and needs specific cryptographic solutions. In this work, we propose a new system that can train a linear regression model with 2-norm regularization (i.e. ridge regression) on a dataset obtained by merging a finite number of private datasets. Our system is composed of two phases: The first one is based on a simple homomorphic encryption scheme and takes care of securely merging the private datasets. The second phase is a new ad-hoc twoparty protocol that computes a ridge regression model solving a linear system where all coefficients are encrypted. The efficiency of our system is evaluated both on synthetically generated and real-world datasets.
An Infrastructure to Support Secure Internet Routing

This document describes an architecture for an infrastructure to support secure Internet routing. The foundation of this architecture is a public key infrastructure (PKI) that represents the allocation hierarchy of IP address space and Autonomous System Numbers; certificates from this PKI are used to verify signed objects that authorize autonomous systems to originate routes for specified IP address prefixes. The data objects that comprise the PKI, as well as other signed objects necessary for secure routing, are stored and disseminated through a distributed repository system. This document also describes at a high level how this architecture can be used to add security features to common operations such as IP address space allocation and route filter construction.
Reconstruction of Continuous and Focalized Brain Functional Source Images From Electroencephalography

In this paper, a new hybrid approach to reconstruct more accurate brain functional source images from electroencephalography is proposed. The proposed approach combines extended source model and focal underdetermined system solution algorithm. Feasibility studies with realistic simulation data and the epilepsy patient's data demonstrate that continuous, as well as focalized, brain electrical source images can be reconstructed utilizing the proposed approach
A low-power 2nd-order CT ΔΣ modulator with a single operational amplifier

This paper presents a multi-bit continuous-time ΔΣ modulator intended for ultra low power radios. The modulator features a 2nd order loop filter implemented with a single operational amplifier to reduce the power consumption. Furthermore, a 4-bit quantizer is used to achieve high resolution at a low oversampling ratio of 16. The ΔΣ modulator has been implemented in a 65nm CMOS process. Simulation results show a peak SNDR of 65 dB over a 500 kHz signal bandwidth, while consuming 76 μW from a 800 mV power supply.
Motion of metallic particles in gas insulated systems

The presence of metallic contamination can seriously reduce the insulation performance of a gas insulated system (GIS). This presentation is focused on the motion of elongated particles, since these particles are considered the ones most frequently found in GIS. The aim of the work has been to learn more about the motion and thereby to suggest improvements to the models that traditionally have been used. With a good model, a more accurate calculation of the motion of a particle and, in turn, a better estimation about its severity in a system can be made.
L1/2 regularization method for multiple-target reconstruction in fluorescent molecular tomography

We present a method to accurately localize multiple small fluorescent objects within the tissue using fluorescence molecular tomography (FMT). The proposed method exploits the localized or sparse nature of the fluorophores in the tissue as a priori information to considerably improve the accuracy of the reconstruction of fluorophore distribution. This is accomplished by minimizing a cost function that includes the L1/2 norm of the fluorophore distribution vector. To deal with the nonconvex penalty, the L1/2 regularizer is transformed into a reweighted L1-norm minimization problem and then it is efficiently solved by a homotopy-based algorithm. Simulation experiments on a 3D digital mouse atlas are performed to verify the feasibility of the proposed method, and the results demonstrate L1/2 regularization is a promising approach for image reconstruction problem of FMT.
The Parsing Algorithm of Translation Corresponding Tree ( TCT ) Grammar

In machine translation (MT), parsing acts as a kernel step to analyze and acquire the syntactic information of an input sentence for the purpose to reproduce the corresponding translation in target language according to the syntactic relationships between the source and target sentences. The parsing process is guided by a set of language formalism, and the design of such algorithm is highly depending on how the language information it represents, especially in the development of example-based machine translation (EBMT) system, where the foundmental language information are the set of translation examples. In this paper, a parsing algorithm is designed to parse the Translation Corresponding Tree (TCT) structure based on the augmented GLR algorithm. The TCT, as the examples representation schema, has been used to the annotation of bilingual text in EBMT system. In order to achieve in parsing the tree language based on GLR parsing algorithm, a TCT equivalent synchronous formalism based on the notation of context free grammar (CFG) is proposed. Where the feature properties of a TCT structure can be fully expressed in term of the proposed formalism, and which, as a result, can be parsed by any CFG parsers. In this paper, GLR algorithm is extended and adapted to this parsing task in the development of an EBMT system for Portuguese to Chinese machine translation.
Irony detection on microposts with limited set of features

Detecting irony in texts attracts computer scientists' attention as a recent research problem. Automatic detection of irony on microblog texts, i.e., microposts, poses additional challenges. Microposts have limited number of characters, and generally include typing errors, therefore traditional methods of text mining cannot be applied easily. This study aims to automatically detect irony in microposts. The proposed solution is based on supervised learning through a limited set of features extracted from the text. Experimental results show the effectiveness of the approach for Turkish and English informal texts.
Non-Medical Prescription Sedative Use Among Adult Latina Mothers and Daughters

Abstract This study examines correlates of non-medical prescription sedative, tranquilizer, and hypnotics use (hereafter NPSU) among a non-clinical, community-based sample of adult Latina mother-daughter dyads. Participants were 316 Latina mothers and daughters enrolled in a study of intergenerational transmission of drug abuse and HIV/AIDS risk behaviors in South Florida. Interviewers administered a questionnaire containing study variables such as age, education, time in the U.S., Spanish language proficiency, health insurance status, wellness behaviors, perceived health condition, alcohol use, NPSU, and other drug use. Correlates of NPSU across mothers and daughters were determined using a dyadic model analysis. Daughters’ health status, age, wellness, and illicit drug use were associated with mothers’ NPSU. Mothers who reported being uninsured, having higher levels of education, and indicating poorer health statuses reported more NPSU. Daughters’ wellness behaviors, age, illicit drug use, and insurance status were associated with their NPSU. Insured mothers and mothers who engaged in illicit drug use had daughters who reported more NPSU. The study's findings provide a modest understanding of family dynamics surrounding NPSU, and it suggests that as women age and their perceived health status worsens, their NPSU may increase.
A Framework for Certification of Large-scale Component-based Parallel Computing Systems in a Cloud Computing Platform for HPC Services

This paper addresses the verification of software components in the context of their orchestration to build cloud-based scientific applications with high performance computing requirements. In such a scenario, components are often supplied by different sources and their cooperation rely on assumptions of conformity with their published behavioral interfaces. Therefore, a faulty or ill-designed component, failing to obey to the envisaged behavioral requirements, may have dramatic consequences in practice. Certifier components, introduced in this paper, implement a verification as a service framework and are able to access the implementation of other components and verify their consistency with respect to a number of functional, safety and liveness requirements relevant to a specific application or a class of them. It is shown how certifier components can be smoothly integrated in HPC Shelf, a cloud-based platform for high performance computing in which different sorts of users can design, deploy and execute scientific applications.
Self-renewal and cell lineage differentiation strategies in human embryonic stem cells and induced pluripotent stem cells

Introduction: Since the initial discoveries of human embryonic and induced pluripotent stem cells, many strategies have been developed to utilize the potential of these cells for translational research and disease modeling. The success of these aims and the development of future applications in this area will depend on the ability to generate high-quality and large numbers of differentiated cell types that genetically, epigenetically, and functionally mimic the cells found in the body. Areas covered: In this review, we highlight the current strategies used to maintain stem cell pluripotency (a measure of stem cell quality), as well as provide an overview of the various differentiation strategies being used to generate cells from all three germ lineages. We also discuss the particular considerations that must be addressed when utilizing these cells for translational therapy, and provide an example of a cell type currently used in clinical trials. Expert opinion: The major challenge in regenerative medicine and disease modeling will be in generating functional cells of sufficient quality that are physiologically and epigenetically similar to the diverse cells that they are modeled after. By meeting these criteria, these differentiated products can be successfully used in disease modeling, drug/toxicology screens, and cellular replacement therapy.
Ophthalmic Anthropometry for Ghanaian Adults

In a prospective ophthalmic anthropometric study of Ghanaian adults of either sex, four hundred ethnic Ghanaians, whose ages ranged between 18 and 63 years (mean 25.40+ 8.5), was undertaken investigating interpupillary distance at far and near, length to bend, temple with bridge height, inter-inner and inter-outer central distances. The primary objective of the study was to establish data for optical industries for the design and manufacture of spectacle frames and lens blank. Results showed that normative mean values interpupillary distance at far for early and late adults were 68.1 + 3.3mm and 68.3+ 3.0 mm respectively, and 69.6 + 3.0mm, 66.3 + 2.8mm for the males and females respectively. Results further showed that only the length to bend, bridge height and inter-outer canthal distance differed in the early and late adult Ghanaian’s. However, with the exception of the bridge height the difference in anthropometric parameters were significant for both sexes (p Key Words: Ophthalmic anthropometry ethnic Ghanaians.
Neural network based model for radiated emissions prediction from high speed PCB traces

Printed Circuit Board (PCB) traces are one of most important PCB Radiated Emissions (RE) sources. These traces is becoming electrically long as the trace length is comparable with the wavelength resulting in higher RE. Therefore, it is essential to predict the RE to avoid out of compliance test issues. In this paper, a neural network Multi-Layer Percetron (MLP) model is developed to predict the radiated emissions of PCB traces. The MLP model is then trained and tested using data set generated based recently developed closed-form equations. Results had shown that a good estimate of the radiated emissions can be obtained using this developed model avoiding both the time-consuming simulations and expensive prototype testing in the compliance chambers. Double-layer PCB is fabricated to validate the proposed neural network model by measurement in a Semi Anechoic Chamber (SAC). Moreover, reasonable agreements are obtained between the measurement and proposed model results.
Robust Locality Preserving Projections With Cosine-Based Dissimilarity for Linear Dimensionality Reduction

Locality preserving projection (LPP) is a classical tool for dimensionality reduction problems. However, it is sensitive to outliers because of utilizing the <inline-formula> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math></inline-formula>-norm-based distance criterion. In this paper, we propose a new approach, termed Euler-LPP, by preserving the local structures of data under the distance criterion of the cosine-based dissimilarity. Euler-LPP is robust to outliers in that the cosine-based dissimilarity suppresses the influence of outliers more efficiently than the <inline-formula> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math></inline-formula>-norm. An explicit mapping, defined by a complex kernel (euler kernel) is adopted to map the data from the input space to complex reproducing kernel Hilbert spaces (CRKHSs), in which the distance of the data pairs under the <inline-formula> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math></inline-formula>-norm is equal to that in the input space under the cosine-based dissimilarity. Thus, the robust dimensionality problem can be directly solved in CRKHS, where the solution is guaranteed to converge to a global minimum. In addition, Euler-LPP is easy to implement without significantly increasing computational complexity. Experiment results on several benchmark databases confirm the effectiveness of the proposed method.
Input Nyquist sampling suffices to identify and compensate nonlinear systems

Nonlinear systems usually cause spectral spreading resulting in an output signal bandwidth greater than that of the input signal. When identifying and compensating nonlinear systems by digital methods, it has been common practice to set the sampling frequency at the Nyquist rate of the output signal. This correspondence presents experimental evidence for the author's proposal that nonlinear systems can be identified and compensated at the lowest possible sampling rate: the Nyquist rate of the input signal.