Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of composition and temperature on the properties of High-Level Waste (HLW) glasses melting above 1200{degrees}C (Draft)

Increasing the melting temperature of HLW glass allows an increase of waste loading (thus reducing product volume) and the production of more durable glasses at a faster melting rate. However, HLW glasses that melt at high temperatures differ in composition from glasses formulated for low temperature ({approximately}1150{degree}C). Consequently, the composition of high-temperature glasses falls in a region previously not well tested or understood. This report represents a preliminary study of property/composition relationships of high-temperature Hanford HLW glasses using a one-component-at-a-time change approach. A test matrix has been designed to explore a composition region expected for high-temperature high-waste loading HLW glasses to be produced at Hanford. This matrix was designed by varying several key components (SiO{sub 2}, B{sub 2}O{sub 3}, Na{sub 2}O, Li{sub 2}O, Fe{sub 2}O{sub 3}, Al{sub 2}O{sub 3}, ZrO{sub 2}, Bi{sub 2}O{sub 3}, P{sub 2}O{sub 5}, UO{sub 2}, TiO{sub 2}, Cr{sub 2}O{sub 3}, and others) starting from a glass based on a Hanford HLW all-blend waste. Glasses were fabricated and tested for viscosity, glass transition temperature, electrical conductivity, crystallinity, liquidus temperature, and PCT release. The effect of individual components on glass properties was assessed using first- and second- order empirical models. The first-order component effects were compared with those from low-temperature HLW glasses.
ZF-CxxC domain-containing proteins, CpG islands and the chromatin connection

Vertebrate DNA can be chemically modified by methylation of the 5 position of the cytosine base in the context of CpG dinucleotides. This modification creates a binding site for MBD (methyl-CpG-binding domain) proteins which target chromatin-modifying activities that are thought to contribute to transcriptional repression and maintain heterochromatic regions of the genome. In contrast with DNA methylation, which is found broadly across vertebrate genomes, non-methylated DNA is concentrated in regions known as CGIs (CpG islands). Recently, a family of proteins which encode a ZF-CxxC (zinc finger-CxxC) domain have been shown to specifically recognize non-methylated DNA and recruit chromatin-modifying activities to CGI elements. For example, CFP1 (CxxC finger protein 1), MLL (mixed lineage leukaemia protein), KDM (lysine demethylase) 2A and KDM2B regulate lysine methylation on histone tails, whereas TET (ten-eleven translocation) 1 and TET3 hydroxylate methylated cytosine bases. In the present review, we discuss the most recent advances in our understanding of how ZF-CxxC domain-containing proteins recognize non-methylated DNA and describe their role in chromatin modification at CGIs.
Optical fiber‐based in vivo quantification of growth factor receptors

Growth factor receptors such as epidermal growth factor receptor 1 and human epidermal growth receptor 2 (HER2) are overexpressed in certain cancer cells. Antibodies against these receptors (eg. cetuximab and transtuzumab [Herceptin]) have shown therapeutic value in cancer treatment. The existing methods for the quantification of these receptors in tumors involve immunohistochemistry or DNA quantification, both in extracted tissue samples. The goal of the study was to evaluate whether an optical fiber‐based technique can be used to quantify the expression of multiple growth factor receptors simultaneously.
Gamma-Secretase-Dependent and -Independent Effects of Presenilin1 on β-Catenin·Tcf-4 Transcriptional Activity

Presenilin1 (PS1) is a component of the γ-secretase complex mutated in cases of Familial Alzheimer's disease (FAD). PS1 is synthesized as a 50 kDa peptide subsequently processed to two 29 and 20 kDa subunits that remain associated. Processing of PS1 is inhibited by several mutations detected in FAD patients. PS1 acts as negative modulator of β-catenin·Tcf-4 transcriptional activity. In this article we show that in murine embryonic fibroblasts (MEFs) the mechanisms of action of the processed and non-processed forms of PS1 on β-catenin·Tcf-4 transcription are different. Whereas non-processed PS1 inhibits β-catenin·Tcf-4 activity through a mechanism independent of γ-secretase and associated with the interaction of this protein with plakoglobin and Tcf-4, the effect of processed PS1 is prevented by γ-secretase inhibitors, and requires its interaction with E- or N-cadherin and the generation of cytosolic terminal fragments of these two cadherins, which in turn destabilize the β-catenin transcriptional cofactor CBP. Accordingly, the two forms of PS1 interact differently with E-cadherin or β-catenin and plakoglobin: whereas processed PS1 binds E-cadherin with high affinity and β-catenin or plakoglobin weakly, the non-processed form behaves inversely. Moreover, contrarily to processed PS1, that decreases the levels of c-fos RNA, non-processed PS1 inhibits the expression c-myc, a known target of β-catenin·Tcf-4, and does not block the activity of other transcriptional factors requiring CBP. These results indicate that prevention of PS1 processing in FAD affects the mechanism of repression of the transcriptional activity dependent on β-catenin.
Whole-brain ex-vivo quantitative MRI of the cuprizone mouse model

Myelin is a critical component of the nervous system and a major contributor to contrast in Magnetic Resonance (MR) images. However, the precise contribution of myelination to multiple MR modalities is still under debate. The cuprizone mouse is a well-established model of demyelination that has been used in several MR studies, but these have often imaged only a single slice and analysed a small region of interest in the corpus callosum. We imaged and analyzed the whole brain of the cuprizone mouse ex-vivo using high-resolution quantitative MR methods (multi-component relaxometry, Diffusion Tensor Imaging (DTI) and morphometry) and found changes in multiple regions, including the corpus callosum, cerebellum, thalamus and hippocampus. The presence of inflammation, confirmed with histology, presents difficulties in isolating the sensitivity and specificity of these MR methods to demyelination using this model.
Target imaging based on ℓ1ℓ0 norms homotopy sparse signal recovery and distributed MIMO antennas

Conventional inverse synthetic aperture radar observes the target from one viewing direction and only obtains partial information. By using a distributed multiple-input multiple-output (MIMO) array, the target can be observed from multiple views and a better image can be obtained. The distributed MIMO radar imaging signal model is derived in this paper. Because the strong scatterers (scattering centers) of a target are usually sparsely distributed, a sparse signal recovery algorithm using homotopy between the ℓ<sub>1</sub> norm and ℓ<sub>0</sub> norm applicable to complex signals is proposed to recover the strong scatterers. This ℓ<sub>1</sub> norm and ℓ<sub>0</sub> norm homotopy method is then extended to the block sparse signal case. The equivalence between complex ℓ<sub>1</sub> ℓ<sub>0</sub> norms homotopy method and block size of two real ℓ<sub>1</sub> ℓ<sub>0</sub> norms homotopy method is demonstrated. This proves that a complex signal-based algorithm is better than a real signal-based algorithm, which only separates the complex signal into its real part and imagery part and does not use their block property. This method is compared with other methods, i.e., block orthogonal matching pursuit (BOMP), block CoSaMp, block smoothed ℓ<sub>0</sub> norm based method (BSL0), spectral projected gradient (SPG L1), and block sparse Bayesian learning (BSBL). The signal recovery performance of ℓ<sub>1</sub> ℓ<sub>0</sub> norms homotopy method is better than the other methods except for BSBL. However, BSBL costs more computationally. Imaging using distributed MIMO antennas is simulated. The simulation results show that the image quality using distributed MIMO radar is better than that using monostatic (or bistatic) MIMO radar.
Codomain scale space and regularization for high angular resolution diffusion imaging

Regularization is an important aspect in high angular resolution diffusion imaging (HARDI), since, unlike with classical diffusion tensor imaging (DTI), there is no a priori regularity of raw data in the co-domain, i.e. considered as a multispectral signal for fixed spatial position. HARDI preprocessing is therefore a crucial step prior to any subsequent analysis, and some insight in regularization paradigms and their interrelations is compulsory. In this paper we posit a codomain scale space regularization paradigm that has hitherto not been applied in the context of HARDI. Unlike previous (first and second order) schemes it is based on infinite order regularization, yet can be fully operationalized. We furthermore establish a closed-form relation with first order Tikhonov regularization via the Laplace transform.
Contacting electronics to fabric circuits with nonconductive adhesive bonding

For over two decades, different types of fabric circuits have been developed. These are fabrics with integrated electric conductors. However, a technology for contacting electronics to these circuits in a simple and reliable manner was missing. This inhibited any greater commercial success of fabric circuits as a potential means to create electronics-in-textiles applications. This paper presents a novel contacting approach based on nonconductive adhesive bonding that is both simple and very versatile concerning the choice of fabric circuit and type of electronics to be contacted. Test vehicles with two different kinds of fabric circuits were developed and exposed to different kinds of textile-typical stress. The results show that this contacting approach is very reliable. Finally, two demonstrators were developed, to show the potential of this novel process.
Magnetic Properties of Nanowires guided by Carbon Nanotubes

The physical properties of one-dimension al (1 D) nanostructure s of magnetic materials are presently the subject of intensive research, taking into account the considerable attention they have recently received and the few cases reported. [1-4] Much of the early work was concerned with exploratory issues, such as establishing an easy axis for typical preparation conditions and the essential involvement of shape anisotropy, as opposed to magnetocrystalline anisotropy. More recently, attention has shifted towards the understanding of magnetization processes and related applications. Particularly interesting problems are the magnetic hysteresis of the wires and the time dependence of the magnetic reversal. Thus, magnetic nanowires have provided a highly successful test ground for understanding the microscopic mechanisms that determine macroscopically important parameters in the different applications where they can be used. [5] On the other hand, these building blocks, as in the case of spherical nanoparticles, are at the border between the solid and molecular state displaying the novel effects that can now be exploited. Therefore, it becomes imperative to take into account the fact that the properties of materials composed of magnetic nanostructures are a result of both the intrinsic properties of the small building blocks and the interactions in between. [6] This chapter is not meant as a survey of th e present state and future developments of magnetic nanowires and since only two examples are considered, is far from being complete. The purpose of this chapter is three fold: a) an introductory level overview about magnetic colloids, the basic physics in the magnetism at the nanoscale; in terms of superparamagnetism, the concept of magnet ic anisotropy and the dynamics of these systems. We have emphasized the dominant role of the surface effects on the intrinsic properties at the nanoscale and the competition with the interactions in the case of assemblies, leading to a characteristic magnetic behavior termed as spin-glass. Additionally, a brief introduction referred to carbon nanotubes (CNTs) is included. b) Characteristi c examples of magnetic nanowires whose morphology was achieved by taking advantage of CNTs and exploiting wet-chemistry methods, and c) a complete analysis of the magnetic behavior displayed in both examples.
Comparative analysis of tandem T7-like promoter containing regions in enterobacterial genomes reveals a novel group of genetic islands

Based on molecular information theory, 10 T7-like promoter models were built for the T7 group of phages and used to scan their host genomes and closely related genomes. 38 genomes were scanned and 12 clusters of tandem promoters were identified in nine enteropathogens. Comparative analysis of these tandem promoter-bearing regions reveals that they are similar to each other, forming prophage-like islands of 4–13 kb. Each island appears to contain two or three tandem T7-like promoters within a stretch of 150–620 bases, but there are no corresponding RNA polymerase (RNAP) genes. The promoters would transcribe two to five putative phage-related proteins, but none of these resemble known phage structural proteins. An integrase belonging to the Int family of site-specific recombinases is encoded upstream of the tandem promoters. A direct repeat of 17–24 bases was found on the ends of all 12 islands. Comparative analysis of the islands shows that these islands appear to have recombined with each other. These results suggest that the islands could encode a group of satellite phages. Activation and function of the islands may depend on transcription by a T7-like RNAP after infection by a T7-like phage or foreign DNA that encodes a T7-like RNAP.
Regulation of Craniofacial Bone Healing Using Noggin

In cases of craniosynostosis, defined as the premature fusion of the cranial sutures, there is a need to inhibit bone formation in small calvarial defects to avoid the occurrence of postoperative resynostosis. Similarly, reconstruction of bone in the craniofacial skeleton following injury or tumor resection necessitates controlled bone regeneration to avoid bone overgrowth. Bone morphogenetic proteins (BMPs) are potent bone inducing growth factors that are expressed during normal bone healing. Noggin is an extracellular antagonist to BMPs. This work studied the use of Noggin to prevent postoperative resynostosis in a rabbit model of human nonsyndromic craniosynostosis via protein therapy. A mouse model of a healing suturectomy was also developed. This model was used to study the effects of Noggin ex vivo gene therapy on the inhibition of postoperative resynostosis. Finally, the ability of Noggin to inhibit bone overgrowth and improve BMP4-induced bone formation was tested. The work presented here demonstrates that a single dose of Noggin protein is capable of inhibiting resynostosis and improving craniofacial growth after surgery to correct craniosynostosis in rabbits. Noggin delivered through ex vivo gene therapy was able to inhibit bone formation in a novel mouse model. Also, the implantation of Noggin expressing cells along with BMP4 expressing cells reduced ectopic bone formation and improved bone density. These results suggest that Noggin therapy may be useful for the inhibition of postoperative resynostosis in children with craniosynostosis. Furthermore, by recreating naturally occurring expression patterns (for example, both Noggin and BMP4), we may be able to control the size, shape and quality of bone formed by biologically-driven therapies.
Heterodimerization of apelin receptor and neurotensin receptor 1 induces phosphorylation of ERK1/2 and cell proliferation via Gαq-mediated mechanism

Dimerization of G protein‐coupled receptors (GPCRs) is crucial for receptor function including agonist affinity, efficacy, trafficking and specificity of signal transduction, including G protein coupling. Emerging data suggest that the cardiovascular system is the main target of apelin, which exerts an overall neuroprotective role, and is a positive regulator of angiotensin‐converting enzyme 2 (ACE2) in heart failure. Moreover, ACE2 cleaves off C‐terminal residues of vasoactive peptides including apelin‐13, and neurotensin that activate the apelin receptor (APJ) and neurotensin receptor 1 (NTSR1) respectively, that belong to the A class of GPCRs. Therefore, based on the similar mode of modification by ACE2 at peptide level, the homology at amino acid level and the capability of forming dimers with other GPCRs, we have been suggested that APJ and NTSR1 can form a functional heterodimer. Using co‐immunoprecipitation, BRET and FRET, we provided conclusive evidence of heterodimerization between APJ and NTSR1 in a constitutive and induced form. Upon agonist stimulation, hetrodimerization enhanced ERK1/2 activation and increased proliferation via activation of Gq α‐subunits. These novel data provide evidence for a physiological role of APJ/NTSR1 heterodimers in terms of ERK1/2 activation and increased intracellular calcium and induced cell proliferation and provide potential new pharmaceutical targets for cardiovascular disease.
AutoEncoder by Forest

Auto-encoding is an important task which is typically realized by deep neural networks (DNNs) such as convolutional neural networks (CNN). In this paper, we propose EncoderForest (abbrv. eForest), the first tree ensemble based auto-encoder. We present a procedure for enabling forests to do backward reconstruction by utilizing the Maximal-Compatible Rule (MCR) defined by the decision paths of the trees, and demonstrate its usage in both supervised and unsupervised setting. Experiments show that, compared with DNN based auto-encoders, eForest is able to obtain lower reconstruction error with fast training speed, while the model itself is reusable and damage-tolerable.
Careful neuropsychological testing reveals a novel genetic marker, GSTO1*C, linked to the pre-stage of Alzheimer's disease

Approximately 30 million people currently suffer from late-onset Alzheimer's disease (LOAD) worldwide. Twin studies demonstrated that 60 to 80% of LOAD is genetically determined, 20% of which remaining unassigned. This case-control study included 118 cognitively healthy controls, 52 patients with mild cognitive impairment (MCI; the pre-stage of LOAD) and 71 LOAD patients. The participants were genotyped for the genetic LOAD marker apolipoprotein E4 (APOE4) and the single-nucleotide polymorphism rs4925 in glutathione S-transferase omega-1 (GSTO1). Additive logistic regression showed a novel, statistically significant association of the major allele GSTO1*C with MCI (OR1.9; p = 0.032). However, identification of significant SNP-disease relations required well-defined study groups. When classifying participants solely by the short Mini Mental State examination (MMSE), the associations of GSTO1*C and the reference marker APOE4 with MCI were cancelled. Moreover, even identifying only the control group by MMSE nullified a statistically significant association (OR1.8; p = 0.045) between GSTO1*C and LOAD. In contrast, these statistical relations were retained when the detailed Consortium to Establish a Registry for Alzheimer's Disease (CERAD-Plus) test battery was used. Hence, besides proposing rs4925 as a genetic marker for cognitive impairment, this work also emphasized the importance of carefully characterized controls in addition to well-diagnosed patients in case-control studies.
An efficient multi-relational Naïve Bayesian classifier based on semantic relationship graph

Classification is one of the most popular data mining tasks with a wide range of applications, and lots of algorithms have been proposed to build accurate and scalable classifiers. Most of these algorithms only take a single table as input, whereas in the real world most data are stored in multiple tables and managed by relational database systems. As transferring data from multiple tables into a single one usually causes many problems, development of multi-relational classification algorithms becomes important and attracts many researchers' interests. Existing works about extending Naïve Bayes to deal with multi-relational data either have to transform data stored in tables to main-memory Prolog facts, or limit the search space to only a small subset of real world applications. In this work, we aim at solving these problems and building an efficient, accurate Naïve Bayesian classifier to deal with data in multiple tables directly. We propose an algorithm named Graph-NB, which upgrades Naïve Bayesian classifier to deal with multiple tables directly. In order to take advantage of linkage relationships among tables, and treat different tables linked to the target table differently, a semantic relationship graph is developed to describe the relationship and to avoid unnecessary joins. Furthermore, to improve accuracy, a pruning strategy is given to simplify the graph to avoid examining too many weakly linked tables. Experimental study on both real-world and synthetic databases shows its high efficiency and good accuracy.
Hypoadiponectinemia in Extremely Low Gestational Age Newborns with Severe Hyperglycemia – A Matched-Paired Analysis

Background Hyperglycemia is commonly observed in extremely low gestational age newborns (ELGANs) and is associated with both increased morbidity and mortality. The objective of this study was to examine the relationship between neonatal hyperglycemia and adiponectin levels in ELGANs. Methodology/Principal Findings Ten preterm infants between 22+6/7 and 27+3/7 weeks’ gestation with neonatal hyperglycemia (defined as pre-feeding blood glucose levels above 200mg/dl on two consecutive measurements with a maximum parenteral glucose infusion of 4mg/kg*min−1) formed the case cohort of this study. To every single patient of this case cohort a patient with normal fasting ( = pre-feeding) blood glucose levels was matched in terms of gestational age and gender. Adiponectin ELISAs were performed both at onset of hyperglycemia and at term-equivalent age. In the case cohort 9/10 patients had to be treated with insulin for 1–26 days (range 0.01–0.4 IU/kg*h−1). Compared to matched-paired controls, significant hypoadiponectinemia was observed at onset of hyperglycemia in these affected patients (6.9µg/ml versus 15.1µg/ml, p = 0.009). At term equivalent age, normoglycemia without any insulin treatment was found in both groups. Moreover, adiponectin levels at that time were no longer significantly different (12.3µg/ml versus 20.0µg/ml; p = 0.051) possibly indicating a mechanistic relevance of this adipokine in regulating insulin sensitivity in ELGANs. Conclusions/Significance Decreased circulating adiponectin levels are correlated with hyperglycemia in ELGANs and may contribute to the pathogenesis of impaired glucose homeostasis in these infants. These findings suggest that adiponectin might be a potential future drug target for the potentially save treatment of hyperglycemia in pre-term infants.
Brain–Computer Interfaces for Multimodal Interaction: A Survey and Principles

For decades, brain–computer interfaces (BCIs) have been used for restoring the communication and mobility of disabled people through applications such as spellers, web browsers, and wheelchair controls. In parallel to advances in computational intelligence and the production of consumer BCI products, BCIs have recently started to be considered as alternative modalities in human–computer interaction (HCI). One of the popular topics in HCI is multimodal interaction (MMI), which deals with combining multiple modalities in order to provide powerful, flexible, adaptable, and natural interfaces. This article discusses the situation of BCI as a modality within MMI research. State-of-the-art, real-time multimodal BCI applications are surveyed in order to demonstrate how BCI can be helpful as a modality in MMI. It is shown that multimodal use of BCIs can improve error handling, task performance, and user experience and that they can broaden the user spectrum. The techniques for employing BCI in MMI are described, and the experimental and technical challenges with some guidelines to overcome these are shown. Issues in input fusion, output fission, integration architectures, and data collection are covered.