Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuroactive peptides as markers of retinal ganglion cell populations that differ in anatomical organization and function

Abstract Recent immunocytochemical studies indicate the existence of several classes of peptide- (PRGC) and catecholamine-containing retinal ganglion cells in anurans, birds, and mammals. Different classes of PRGC project to discrete and seemingly unique layers in the retino-recipient portion of the anuran and avian optic tectum. Peptide-containing retinofugal projections to the frog tectum originate early in development, and are reestablished by some classes of PRGC during regeneration of the optic nerve. These findings indicate that chemically specific, parallel retinofugal pathways presumably subserve different functional aspects of vision in vertebrates. Exciting prospects for research include the correlation of physiologically with immunocytochemically defined classes of retinal ganglion cells, the analysis of the possible role of neuroactive peptides in retinofugal transmission, and the pharmacological manipulation of putative peptidergic retinofugal pathways to analyze their role in visual function.
FPGA based implementation of robust spatial domain image watermarking algorithm

The proliferation of the digitized media introduces an exigent problem of security in multimedia data transmission in the network surroundings. Consequently, digital watermark technique needs to be incorporated in a digital rights management framework to address different aspects of the content supervision. The objective is to develop low power, real time, reliable and secure data hiding system that can be achieved all the way through hardware implementation. As an attempt towards the power efficient system, here we present an oblivious, spatial domain watermarking based authentication algorithm and its FPGA implementation. It is shown that the low cost data embedding algorithm can conceal watermark into original cover image coming from a sensor much faster than software implementation and the embedded image is easily transmitted to PC by using proper interface. The quality of the transmitted image is also comparable to that obtained by software algorithm.
Transthoracic three-dimensional echocardiography is as good as magnetic resonance imaging in measuring dynamic changes in left ventricular volume during the heart cycle in children.

AIMS The purpose of the study was to assess the dynamic changes in left ventricular (LV) volume by transthoracic three-dimensional echocardiography (3DE) and to compare the results with those obtained by magnetic resonance imaging (MRI). METHODS AND RESULTS Thirty healthy children were studied by digitized 3DE and Doppler, and by MRI. Three-dimensional echocardiography of LV was performed by using rotational acquisition from the transthoracic apical view with ECG gating and without respiratory gating. The acquisition of 3DE data took 10-15s. Three-dimensional echocardiography gave similar values to MRI for EDV, ESV and LVM measurements, and the results correlated well. Peak emptying rates by 3DE and MRI were -236.6 and -169.6ml/s and peak filling rates were 215.0 and 215.9ml/s, respectively. Dynamic changes of LV volumes during the heart cycle were detectable with both methods. CONCLUSION Digitized 3DE performed in the outpatient clinic and MRI were both useful methods for studying the physiological volume changes in left ventricle in children. These methods may be used for further study of the systolic and diastolic function of the left ventricle in various clinical conditions.
Challenges of Simultaneously Defining and Measuring Knowledge for Teaching

Schilling et al. (this issue) have done a commendable job in illustrating a comprehensiveprocessofvalidatingassessmentsof teacherknowledge(and,morebroadly, other types of tests as well). On one hand, the concrete illustration of a process that often remains murky and incomplete is profoundly heartening, as it provides a rigorous model for others addressing similar measurement challenges. On the other hand, some of the results are profoundly discouraging. The work described in this set of papers builds upon over a decade of effort—starting with Ball and Bass’ original work (Ball, 1999; Ball & Bass, 2000) in the area of teacher knowledge— on the part of a highly talented and well-funded research team. Yet, at its core, strong validity claims about measures of mathematical knowledge for teaching (MKT)seem limited to the measurement of common content knowledge (CCK), not necessarily the mathematical knowledge specific to teaching (specialized content knowledge—SCK—and knowledge of content and students—KCS). In this commentary, I focus on an inherent challenge in the type of work Schilling and his colleagues have undertaken: attempting to measure a construct which is still being defined and explored. Because the construct of knowledge for teaching is itself not well understood, important assumptions about the behavior of its measures may or may not be warranted. At this stage in the development of the construct, it is important to consider validity evidence from teachers with
Herpes Simplex Virus Type 1 ICP4 Promotes Transcription Preinitiation Complex Formation by Enhancing the Binding of TFIID to DNA

ABSTRACT Infected-cell polypeptide 4 (ICP4) of herpes simplex virus type 1 (HSV-1) activates the expression of many HSV genes during infection. It functions along with the cellular general transcription factors to increase the transcription rates of genes. In this study, an HSV late promoter consisting of only a TATA box and an INR element was immobilized on a magnetic resin and incubated with nuclear extracts or purified TFIID in the presence and absence of ICP4. Analysis of the complexes formed on these promoters revealed that ICP4 increased the formation of transcription preinitiation complexes (PICs) in a TATA box-dependent manner, as determined by the presence of ICP4, TFIID, TFIIB, and polymerase II on the promoter. With both nuclear extract and purified TFIID, it was determined that ICP4 helped TFIID bind to the promoter and the TATA box. These observations differed from those for the activator Gal4-VP16. As previously observed by others, Gal4-VP16 also increased the formation of PICs without helping TFIID bind to the promoter, suggesting that ICP4 and VP16 differ in their mechanism of activation and that ICP4 functions to facilitate PIC formation at an earlier step in the formation of PICs. We also observed that the DNA binding activity of ICP4 was not sufficient to help TFIID bind to the promoter and that the region of ICP4 that was responsible for this activity is located between residues 30 and 274. Taken together these results demonstrate that a specific region of ICP4 helps TFIID bind to the TATA box and that this in turn facilitates the formation of transcription PICs.
Corticothalamic phase synchrony and cross-frequency coupling predict human memory formation

The anterior thalamic nucleus (ATN) is thought to play an important role in a brain network involving the hippocampus and neocortex, which enables human memories to be formed. However, its small size and location deep within the brain have impeded direct investigation in humans with non-invasive techniques. Here we provide direct evidence for a functional role for the ATN in memory formation from rare simultaneous human intrathalamic and scalp electroencephalogram (EEG) recordings from eight volunteering patients receiving intrathalamic electrodes implanted for the treatment of epilepsy, demonstrating real-time communication between neocortex and ATN during successful memory encoding. Neocortical-ATN theta oscillatory phase synchrony of local field potentials and neocortical-theta-to-ATN-gamma cross-frequency coupling during presentation of complex photographic scenes predicted later memory for the scenes, demonstrating a key role for the ATN in human memory encoding. DOI:http://dx.doi. org/10.7554/eLife.05352. 001
Phylogenetically enhanced statistical tools for RNA structure prediction

MOTIVATION Methods that predict the structure of molecules by looking for statistical correlation have been quite effective. Unfortunately, these methods often disregard phylogenetic information in the sequences they analyze. Here, we present a number of statistics for RNA molecular-structure prediction. Besides common pair-wise comparisons, we consider a few reasonable statistics for base-triple predictions, and present an elaborate analysis of these methods. All these statistics incorporate phylogenetic relationships of the sequences in the analysis to varying degrees, and the different nature of these tests gives a wide choice of statistical tools for RNA structure prediction. RESULTS Starting from statistics that incorporate phylogenetic information only as independent sequence evolution models for each position of a multiple alignment, and extending this idea to a joint evolution model of two positions, we enhance the usual purely statistical methods (e.g. methods based on the Mutual Information statistic) with the use of phylogenetic information available in the sequences. In particular, we present a joint model based on the HKY evolution model, and consequently a X(2) test of independence for two positions. A significant part of this work is devoted to some mathematical analysis of these methods. We tested these statistics on regions of 16S and 23S rRNA, and tRNA.
DExD/H-Box Helicase 36 Signaling via Myeloid Differentiation Primary Response Gene 88 Contributes to NF-κB Activation to Type 2 Porcine Reproductive and Respiratory Syndrome Virus Infection

DExD/H-box helicase 36 (DHX36) is known to be an ATP-dependent RNA helicase that unwinds the guanine-quadruplexes DNA or RNA, but emerging data suggest that it also functions as pattern recognition receptor in innate immunity. Porcine reproductive and respiratory syndrome virus (PRRSV) is an Arterivirus that has been devastating the swine industry worldwide. Interstitial pneumonia is considered to be one of the most obvious clinical signs of PRRSV infection, suggesting that the inflammatory response plays an important role in PRRSV pathogenesis. However, whether DHX36 is involved in PRRSV-induced inflammatory cytokine expression remains unclear. In this study, we found that PRRSV infection increased the expression of DHX36. Knockdown of DHX36 and its adaptor myeloid differentiation primary response gene 88 (MyD88) by small-interfering RNA in MARC-145 cells significantly reduced NF-κB activation and pro-inflammatory cytokine expression after PRRSV infection. Further investigation revealed that PRRSV nucleocapsid protein interacted with the N-terminal quadruplex binding domain of DHX36, which in turn augmented nucleocapsid protein-induced NF-κB activation. Taken together, our results suggest that DHX36–MyD88 has a relevant role in the recognition of PRRSV nucleocapsid protein and in the subsequent activation of pro-inflammatory NF-κB pathway.
Iterated Posterior Linearization Smoother

This note considers the problem of Bayesian smoothing in nonlinear state-space models with additive noise using Gaussian approximations. Sigma-point approximations to the general Gaussian Rauch-Tung-Striebel smoother are widely used methods to tackle this problem. These algorithms perform statistical linear regression (SLR) of the nonlinear functions considering only the previous measurements. We argue that SLR should be done taking all measurements into account. We propose the iterated posterior linearization smoother (IPLS), which is an iterated algorithm that performs SLR of the nonlinear functions with respect to the current posterior approximation. The algorithm is demonstrated to outperform conventional Gaussian nonlinear smoothers in two numerical examples.
Subsets of Visceral Adipose Tissue Nuclei with Distinct Levels of 5-Hydroxymethylcytosine

The reprogramming of cellular memory in specific cell types, and in visceral adipocytes in particular, appears to be a fundamental aspect of obesity and its related negative health outcomes. We explored the hypothesis that adipose tissue contains epigenetically distinct subpopulations of adipocytes that are differentially potentiated to record cellular memories of their environment. Adipocytes are large, fragile, and technically difficult to efficiently isolate and fractionate. We developed fluorescence nuclear cytometry (FNC) and fluorescence activated nuclear sorting (FANS) of cellular nuclei from visceral adipose tissue (VAT) using the levels of the pan-adipocyte protein, peroxisome proliferator-activated receptor gamma-2 (PPARg2), to distinguish classes of PPARg2-Positive (PPARg2-Pos) adipocyte nuclei from PPARg2-Negative (PPARg2-Neg) leukocyte and endothelial cell nuclei. PPARg2-Pos nuclei were 10-fold enriched for most adipocyte marker transcripts relative to PPARg2-Neg nuclei. PPARg2-Pos nuclei showed 2- to 50-fold higher levels of transcripts encoding most of the chromatin-remodeling factors assayed, which regulate the methylation of histones and DNA cytosine (e.g., DNMT1, TET1, TET2, KDM4A, KMT2C, SETDB1, PAXIP1, ARID1A, JMJD6, CARM1, and PRMT5). PPARg2-Pos nuclei were large with decondensed chromatin. TAB-seq demonstrated 5-hydroxymethylcytosine (5hmC) levels were remarkably dynamic in gene bodies of various classes of VAT nuclei, dropping 3.8-fold from the highest quintile of expressed genes to the lowest. In short, VAT-derived adipocytes appear to be more actively remodeling their chromatin than non-adipocytes.
New method for ellipse detection by means of symmetry

We propose a new approach for detecting ellipses. The approach is based on the geometrical property that five points on an ellipse can determine the parameters of the ellipse, and the symmetry of ellipses is used to obtain these points. Using symmetry, we classify the edge points in an input image into several subimages. Ellipses with different symmetric axes will lie in different subimages. In each subimage, symmetry is applied again to obtain those sets of five points that possibly lie on the same ellipse. Finally, using geometrical properties and the Hough transform, we extract all ellipses in an input image successfully. The proposed method can detect partially occluded ellipses. Experimental results show that the proposed method is fast and robust.
Researching learning outcomes: building confidence in our conclusions

The ESRC Teaching and Learning Research Programme is expected to produce knowledge of high social scientific quality and practical pedagogic value. It faces, in a particularly acute form, the issue of how confidence in its conclusions can be built. This article begins with some conceptual clarification of the notion of a ‘warrant’ for research findings and distinguishes between warrants in social research and warrants for educational policy and practice. It then, in the specific context of research on learning outcomes, proposes an integrated model that recognizes the importance of, and relationships among, criteria associated with research design and empirical work, theoretical coherence, relationship with other research, and user affirmation. It concludes by emphasizing the need for continuing debate about, and development of, the roles and relationships of ‘researchers’ and ‘users’.
Research and Design for Intrusion Detection System with Hybrid Detector and Apriori Algorithm

Network and host Intrusion Detection Systems (IDS) have become a standard component in security infrastructures. As the action of intrusion represents variable, complicated, and uncertainty characteristic, they face so many problems to resolve for intrusion detection. Each approach has its strengths and weaknesses. We propose a hybrid IDS, which combines network and host IDS, with anomaly and misuse detection mode, utilizes auditing programs to extract an extensive set of features that describe each network connection or host session, and applies data mining programs to learn rules that accurately capture the behavior of intrusions and normal activities. We use an association rule to track all relevant data dependency rule sets for different access roles using a hierarchical structure. We identify malicious transactions from the transaction logs in the database using the data dependency rule sets. These rule sets are continuously updated and stored in a repository. The optimized algorithm actually improves the performance of IDS. Our approach is shown to reduce data access bottlenecks, and ensures minimal manual intervention for maintaining a secure database.
Liquid: A Scalable Deduplication File System for Virtual Machine Images

A virtual machine (VM) has been serving as a crucial component in cloud computing with its rich set of convenient features. The high overhead of a VM has been well addressed by hardware support such as Intel virtualization technology (VT), and by improvement in recent hypervisor implementation such as Xen, KVM, etc. However, the high demand on VM image storage remains a challenging problem. Existing systems have made efforts to reduce VM image storage consumption by means of deduplication within a storage area network (SAN) cluster. Nevertheless, an SAN cannot satisfy the increasing demand of large-scale VM hosting for cloud computing because of its cost limitation. In this paper, we propose Liquid, a scalable deduplication file system that has been particularly designed for large-scale VM deployment. Its design provides fast VM deployment with peer-to-peer (P2P) data transfer and low storage consumption by means of deduplication on VM images. It also provides a comprehensive set of storage features including instant cloning for VM images, on-demand fetching through a network, and caching with local disks by copy-on-read techniques. Experiments show that Liquid's features perform well and introduce minor performance overhead.
"The Leicester City Fairytale?": Utilizing New Soccer Analytics Tools to Compare Performance in the 15/16 & 16/17 EPL Seasons

The last two years have been somewhat of a rollercoaster for English Premier League (EPL) team Leicester City. In the 2015/16 season, against all odds and logic, they won the league to much fan-fare. Fast-forward nine months later, and they are battling relegation. What could describe this fluctuating form? As soccer is a very complex and strategic game, common statistics (e.g., passes, shots, possession) do not really tell the full story on how a team succeeds and fails. However, using machine learning tools and a plethora of data, it is now possible to obtain some insights into how a team performs. To showcase the utility of these new tools (i.e., expected goal value, expected save value, strategy-plots and passing quality measures), we first analyze the EPL 2015/16 season which a specific emphasis on the champions Leicester City, and then compare it to the current one. Finally, we show how these features can be used to predict future performance.
Overcomplete image coding using iterative projection-based noise shaping

Overcomplete transforms, like the dual-tree complex wavelet transform, offer more flexible signal representations than critically-sampled transforms. Large numbers of transform coefficients can be discarded without much reconstruction quality loss by forcing compensatory changes in the remaining coefficients. We develop and demonstrate a new and unique system for achieving these transform coding aims of coefficient elimination and compensation. The system is based on iterative projection of signals between the image domain and transform domain.
Online Figure-ground Segmentation with Edge Pixel Classification

The need for figure-ground segmentation in video arises in many vision problems like tracker initialization, accurate object shape representation and drift-free appearance model adaptation. This paper uses a 3D spatio-temporal Conditional Random Field (CRF) to combine different segmentation cues while enforcing temporal coherence. Without supervised parameter training, the weighting factors for different data potential functions in the CRF model are adapted online to reflect changes in object appearance and environment. To get an accurate boundary based on the 3D CRF segmentation result, edge pixels are classified into three classes: foreground, background and boundary. The final foreground region bitmask is constructed from the foreground and boundary edge pixels. The effectiveness of our approach is demonstrated on several airborne videos with large appearance change and heavy occlusion.
Off‐fault damage patterns due to supershear ruptures with application to the 2001 Mw 8.1 Kokoxili (Kunlun) Tibet earthquake

[1] We extend a model of a two-dimensional self-healing slip pulse, propagating dynamically in steady state with slip-weakening failure criterion, to the supershear regime in order to study the off-fault stressing induced by such a slip pulse and investigate features unique to the supershear range. Specifically, we show that there exists a nonattenuating stress field behind the Mach front that radiates high stresses arbitrarily far from the fault (practically this would be limited to distances comparable to the depth of the seismogenic zone), thus being capable of creating fresh damage or inducing Coulomb failure in known structures at large distances away from the main fault. We allow for both strike-slip and dip-slip failure induced by such a slip pulse. We show that off-fault damage is controlled by the speed of the slip-pulse, scaled stress drop, and principal stress orientation of the prestress field. We apply this model to study damage features induced during the 2001 Kokoxili (Kunlun) event in Tibet, for which it has been suggested that much of the rupture was supershear. We argue that an interval of simultaneous induced normal faulting is more likely due to a slip partitioning mechanism suggested previously than to the special features of supershear rupture. However, those features do provide an explanation for otherwise anomalous ground cracking at several kilometers from the main fault. We also make some estimates of fracture energy which, for a given net slip and dynamic stress drop, is lower than for a sub-Rayleigh slip pulse because part of the energy fed by the far-field stress is radiated back along the Mach fronts.
A V139M Mutation Also Causes the Reversible CNS Phenotype in CMTX

X-linked Charcot Marie Tooth disease (CMTX; OMIM # 320800) is the second most common cause of inherited demyelinating neuropathy and is caused by mutations in the GJB1 ( also referred to as connexin 32) gene coding for the gap junction protein connexin 32 (Cx32). Cx32 is expressed in the myelinating Schwann cells in the peripheral nervous system (PNS) and in oligodendrocytes in the central nervous system (CNS). Gap junctions help rapid transport of ions and small molecules across cell membranes.1 Various central nervous system manifestations (clinical and subclinical) in CMTX have been reported.2-9 In the last ten years a distinct, reversible clinical syndrome associated with pyramidal and or bulbar weakness and concomitant transient magnetic resonance imaging (MRI) findings of diffuse, confluent white matter abnormalities has been increasingly reported.10-13 All 11 patients reported in the published English literature since 1998, when the above syndrome was first described, have various mutations in the GJB1 gene causing dysfunctional gap junctions. We report two brothers who presented with pyramidal weakness, dysarthria, ataxia and bulbar weakness a year apart predating their genomic CMTX diagnosis. Both boys and their mother were later confirmed to have a V139M mutation in the GJB1 gene. Computed tomography (CT), magnetic resonance imaging and magnetic resonance spectroscopy (MRS) features of one of the brothers are described.