Miracle-dz/UniFAR-FTUs huggingface dataset:
FPGA implementation for real-time Chroma-key effect using Coarse and Fine Filter

Chroma-key is a robust and important technique for processing image or video that is widely used in cinema films, magazine covers, video game industries as well as television programs such as weather forecast, live talk show, ect. This paper presents study of Chroma-key method and proposes a hardware architecture for Chroma-key effect in real-time. Based on K-means algorithm, we propose an improved method namely Coarse and Fine Filter, which is more robust on segmentation and more appropriate for hardware design thanks to usage of small buffer. A VLSI architecture for the proposed method is implemented on the Altera DE2 FPGA board. Experimental results show that the proposed design can perform Chroma-key effect with pleasing quality in real-time.
Self-Explanation and Reading Strategy Training (SERT) Improves Low-Knowledge Students’ Science Course Performance

ABSTRACT This study demonstrates the generalization of previous laboratory results showing the benefits of Self-Explanation Reading Training (SERT) to college students’ course exam performance. The participants were 265 students enrolled in an Introductory Biology course, 59 of whom were provided with SERT. The results showed that SERT benefited students who began the course with less knowledge about science but did not benefit students with greater prior science knowledge. Moreover, across the three exams in the course, low-knowledge students who received SERT performed as well as high-knowledge students, whereas low-knowledge students without SERT performed more poorly than high-knowledge students. Hence, instruction on how to self-explain and use comprehension strategies allowed low-knowledge students to overcome their knowledge deficits. These results provide further evidence that self-explanation in combination with instruction and practice using comprehension strategies helps students to more effectively process and understand science.
Slipstream Memory Hierarchies

A slipstream processor harnesses an otherwise unused processing element in a chip multipro-cessor (CMP) to speed up a single program. It does this by running two redundant copies of the program. Predicted-non-essential computation is speculatively removed from one of the programs , speeding it up. The second program checks the forward progress of the first and is also sped up in the process. Both program copies finish sooner than either can alone. The redundant programs are architecturally independent and this leads to a simple execution model. Physical memory pages are duplicated by the operating system, sparing the processor from explicitly managing a fixed amount of transparent rename storage. Unfortunately, doubling memory usage partially negates performance gains. We observe that 1) the already-replicated L1 caches in a CMP provide enough implicit rename storage and 2) this storage does not need to be explicitly managed because the slipstream paradigm is tolerant of slightly inaccurate memory renaming. Leveraging unmodified cache actions within a typical private-L1/shared-L2 memory hierarchy, we develop an efficient hardware-based memory duplication approach that significantly outperforms software-based duplication, yet does not require any explicit hardware management. Furthermore, the new duplication approach enables much simpler state recovery when the speculative program diverges. Simple cache flushing eliminates a previously-required slipstream recovery component. And the performance impact of flush-induced compulsory misses is reduced by exploiting preserved data within flushed cache lines as highly-accurate value predictions.
Cholinergic innervation of the smooth muscle cells in the choroid coat of the chick eye and its development

The mechanical and pharmacological characteristics of the cholinergic activation of the smooth muscle in the choroidal coat of the chick eye have been assessed in tissues isolated from birds 1 d posthatching using histological, electrophysiological, and immunological techniques. The choroidal coat is innervated by a dense network of cholinergic nerves that make en passant synapses with smooth muscle. Thirty-hertz stimulation of these nerves initiates red blood cell (RBC) movement in the vessels of the choroidal coat, and this activation is blocked by muscarinic ACh receptor (AChR) antagonists. Force-transducer recordings of nerve-induced contractions of this tissue have a slow onset and relaxation time course similar to those of smooth muscle contractions. Furthermore, since nearly half the cholinergic neurons innervating the choroid die within a defined period during development, the onset and pharmacology of this innervation were studied during embryogenesis. With a neural cytoskeletal-like immunostain, we demonstrated that choroid axons are present in peripheral tissue by stage (St) 29. Extracellular electrical recordings made after choroid nerve stimulation allowed us to distinguish axon from muscle responses. These procedures permitted us to examine the time course of the innervation of the smooth muscle. However, to visualize the postsynaptic smooth muscle response, it was necessary to treat the isolated preparation with tetraethylammonium chloride (TEA). Accordingly, TEA-enhanced electrical smooth muscle responses to single-nerve stimuli could be recorded only after St 39. Treatment of the nerve-muscle preparation with prostigmine allowed the recording of TEA-enhanced electrical activity as early as St 36 (1 d after the beginning of the normal choroid neuron death period). This synaptic activation was completely blocked by atropine or quinuclidinyl benzylate (QNB), and was not affected by alpha bungarotoxin (alpha BTX), indicating that, as in the posthatching tissue, neuromuscular transmission is mediated by muscarinic receptors. These results show that cholinergic muscarinic activation of the choroidal coat can occur as early as St 36, but that it is not as efficient as transmission later in embryogenesis.
Cardiac Excitation and Contraction Reduced density and altered regulation of rat atrial L-type Ca 2 current in heart failure

Bond RC, Bryant SM, Watson JJ, Hancox JC, Orchard CH, James AF. Reduced density and altered regulation of rat atrial L-type Ca current in heart failure. Am J Physiol Heart Circ Physiol 312: H384–H391, 2017. First published December 6, 2016; doi:10.1152/ ajpheart.00528. 2016. —Constitutive regulation by PKA has recently been shown to contribute to L-type Ca current (ICaL) at the ventricular t-tubule in heart failure. Conversely, reduction in constitutive regulation by PKA has been proposed to underlie the downregulation of atrial ICaL in heart failure. The hypothesis that downregulation of atrial ICaL in heart failure involves reduced channel phosphorylation was examined. Anesthetized adult male Wistar rats underwent surgical coronary artery ligation (CAL, N 10) or equivalent sham-operation (Sham, N 12). Left atrial myocytes were isolated ~18 wk postsurgery and whole cell currents recorded (holding potential -80 mV). ICaL activated by depolarizing pulses to voltages from -40 to 50 mV were normalized to cell capacitance and current density-voltage relations plotted. CAL cell capacitances were ~1.67fold greater than Sham (P 0.0001). Maximal ICaL conductance (Gmax) was downregulated more than 2-fold in CAL vs. Sham myocytes (P 0.0001). Norepinephrine (1 mol/l) increased Gmax 50% more effectively in CAL than in Sham so that differences in ICaL density were abolished. Differences between CAL and Sham Gmax were not abolished by calyculin A (100 nmol/l), suggesting that increased protein dephosphorylation did not account for ICaL downregulation. Treatment with either H-89 (10 mol/l) or AIP (5 mol/l) had no effect on basal currents in Sham or CAL myocytes, indicating that, in contrast to ventricular myocytes, neither PKA nor CaMKII regulated basal ICaL. Expression of the L-type 1C-subunit, protein phosphatases 1 and 2A, and inhibitor-1 proteins was unchanged. In conclusion, reduction in PKA-dependent regulation did not contribute to downregulation of atrial ICaL in heart failure. NEW & NOTEWORTHY Whole cell recording of L-type Ca currents in atrial myocytes from rat hearts subjected to coronary artery ligation compared with those from sham-operated controls reveals marked reduction in current density in heart failure without change in channel subunit expression and associated with altered phosphorylation independent of protein kinase A.
Proteiomic patterns for endometrial cancer using SELDI-TOF-MS

Serum samples from endometrial cancer (EC) patients and healthy females were analyzed using surface-enhanced laser desorption-ionization time-of-flight mass spectrometry (SELDI-TOF-MS) to discover the potential diagnostic biomarker for detection of EC. A preliminary training set of spectra derived from 40 EC patients and 30 healthy women were used to develop a proteomic model that effectively discriminated cancer patients from healthy women. The training set had a specificity of 100% and sensitivity of 92.5% in the EC detection. A blind test set, including 20 new cancer cases and 10 healthy women, was used to validate the sensitivity and specificity of this multivariate model, which had a corresponding results of 60% in specificity and 75% in sensitivity, respectively. The combination of SELDI-TOF-MS with bioinformatics tools could help find new biomarkers and establish the detection of EC with high sensitivity and specificity.
Learning integer lattices

The problem of learning an integer lattice of ${\bf Z}^k $ in an on-line fashion is considered. That is, the learning algorithm is given a sequence of k-tuples of integers and predicts for each tuple in the sequence whether it lies in a hidden target lattice of ${\bf Z}^k $. The goal of the algorithm is to minimize the number of prediction mistakes. An efficient learning algorithm with an absolute mistake bound of $k + \lfloor k\log (n\sqrt k ) \rfloor $ is given, where n is the maximum component of any tuple seen. It is shown that this bound is approximately a $\log \log n$ factor larger than the lower bound on the worst case number of mistakes given by the VC dimension of lattices that are restricted to $\{ - n, \cdots ,0, \cdots ,n \}^k $. This algorithm is used to learn rational lattices, cosets of lattices, an on-line word problem for abelian groups, and a subclass of the commutative regular languages. Furthermore, by adapting the results of [D. Helmbold, R. Sloan, and M. K. Warmuth, Machine Learning.
CellSort: High Performance Sorting on the Cell Processor

In this paper we describe the design and implementation of CellSort - a high performance distributed sort algorithm for the Cell processor. We design CellSort as a distributed bitonic merge with a data-parallel bitonic sorting kernel. In order to best exploit the architecture of the Cell processor and make use of all available forms of parallelism to achieve good scalability, we structure CellSort as a three-tiered sort. The first tier is a SIMD (single-instruction multiple data) optimized bitonic sort, which sorts up to 128KB of items that cat fit into one SPE's (a co-processor on Cell) local store. We design a comprehensive SIMDization scheme that employs data parallelism even for the most fine-grained steps of the bitonic sorting kernel. Our results show that, SIMDized bitonic sorting kernel is vastly superior to other alternatives on the SPE and performs up to 1.7 times faster compared to quick sort on 3.2GHz Intel Xeon. The second tier is an in-core bitonic merge optimized for cross-SPE data transfers via asynchronous DMAs, and sorts enough number of items that can fit into the cumulative space available on the local stores of the participating SPEs. We design data transfer and synchronization patters that minimize serial sections of the code by taking advantage of the high aggregate cross-SPE bandwidth available on Cell. Results show that, in-core bitonic sort scales well on the Cell processor with increasing number of SPEs, and performs up to 10 times faster with 16 SPEs compared to parallel quick sort on dual-3.2 GHz Intel Xeon. The third tier is an out-of-core bitonic merge which sorts large number of items stored in the main memory. Results show that, when properly implemented, distributed out-of-core bitonic sort on Cell can significantly outperform the asymptotically (average case) superior quick sort for large number of memory resident items (up to 4 times faster when sorting 0.5GB of data with 16 SPEs, compared to dual-3.2GHz Intel Xeon).
Determining Song Similarity via Machine Learning Techniques and Tagging Information

The task of determining item similarity is a crucial one in a recommender system. This constitutes the base upon which the recommender system will work to determine which items are more likely to be enjoyed by a user, resulting in more user engagement. In this paper we tackle the problem of determining song similarity based solely on song metadata (such as the performer, and song title) and on tags contributed by users. We evaluate our approach under a series of different machine learning algorithms. We conclude that tf-idf achieves better results than Word2Vec to model the dataset to feature vectors. We also conclude that k-NN models have better performance than SVMs and Linear Regression for this problem.
A Role for Groucho Tetramerization in Transcriptional Repression

ABSTRACT The Drosophila Groucho (Gro) protein is a corepressor required by a number of DNA-binding transcriptional repressors. Comparison of Gro with its homologues in other eukaryotic organisms reveals that Gro contains, in addition to a conserved C-terminal WD repeat domain, a conserved N-terminal domain, which has previously been implicated in transcriptional repression. We determined, via a variety of hydrodynamic measurements as well as protein cross-linking, that native Gro is a tetramer in solution and that tetramerization is mediated by two putative amphipathic α-helices (termed leucine zipper-like motifs) found in the N-terminal region. Point mutations in the leucine zipper-like motifs that block tetramerization also block repression by Gro, as assayed in cultured Drosophila cells with Gal4-Gro fusion proteins. Furthermore, the heterologous tetramerization domain from p53 fully substitutes for the Gro tetramerization domain in transcriptional repression. These findings suggest that oligomerization is essential for Gro-mediated repression and that the primary function of the conserved N-terminal domain is to mediate this oligomerization.
A Systematic Analysis on DNA Methylation and the Expression of Both mRNA and microRNA in Bladder Cancer

Background DNA methylation aberration and microRNA (miRNA) deregulation have been observed in many types of cancers. A systematic study of methylome and transcriptome in bladder urothelial carcinoma has never been reported. Methodology/Principal Findings The DNA methylation was profiled by modified methylation-specific digital karyotyping (MMSDK) and the expression of mRNAs and miRNAs was analyzed by digital gene expression (DGE) sequencing in tumors and matched normal adjacent tissues obtained from 9 bladder urothelial carcinoma patients. We found that a set of significantly enriched pathways disrupted in bladder urothelial carcinoma primarily related to “neurogenesis” and “cell differentiation” by integrated analysis of -omics data. Furthermore, we identified an intriguing collection of cancer-related genes that were deregulated at the levels of DNA methylation and mRNA expression, and we validated several of these genes (HIC1, SLIT2, RASAL1, and KRT17) by Bisulfite Sequencing PCR and Reverse Transcription qPCR in a panel of 33 bladder cancer samples. Conclusions/Significance We characterized the profiles between methylome and transcriptome in bladder urothelial carcinoma, identified a set of significantly enriched key pathways, and screened four aberrantly methylated and expressed genes. Conclusively, our findings shed light on a new avenue for basic bladder cancer research.
“Talking Fire out of Burns”: Biomedical Transgressions and the Logic of Care

The descriptions of fire charmers’ practice, its context, and physicians’ stances toward these healing practices demonstrate the resistance of French biomedical institutions toward the full acceptance of the logic of care. I draw on data from observations conducted in a rural area of the Auvergne, France (1996–1999), semistructured interviews with general practitioners, healers, and oncologists collected between 1993 and 2011, and online investigations of fire charming, to provide new insights into the relationships between French physicians and fire charmers. In doing so, I explore the distinction between clinical/empirical practice and scientific knowledge.
Activation of stress signaling molecules in bat brain during arousal from hibernation

Induction of glucose‐regulated proteins (GRPs) is a ubiquitous intracellular response to stresses such as hypoxia, glucose starvation and acidosis. The induction of GRPs offers some protection against these stresses in vitro, but the specific role of GRPs in vivo remains unclear. Hibernating bats present a good in vivo model to address this question. The bats must overcome local high oxygen demand in tissue by severe metabolic stress during arousal thermogenesis. We used brain tissue of a temperate bat Rhinolopus ferrumequinum to investigate GRP induction by high metabolic oxygen demand and to identify associated signaling molecules. We found that during 30 min of arousal, oxygen consumption increased from nearly zero to 11.9/kg/h, which was about 8.7‐fold higher than its active resting metabolic rate. During this time, body temperature rose from 7°C to 35°C, and levels of TNF‐α and lactate in brain tissue increased 2–2.5‐fold, indicating a high risk of oxygen shortage. Concomitantly, levels of GRP75, GRP78 and GRP94 increased 1.5–1.7‐fold. At the same time, c‐Jun N‐terminal protein kinase (JNK) activity increased 6.4‐fold, and extracellular signal‐regulated protein kinase (ERK) activity decreased to a similar degree (6.1‐fold). p38 MAPK activity was very low and remained unchanged during arousal. In addition, survival signaling molecules protein kinase B (Akt) and protein kinase C (PKC) were activated 3‐ and 5‐fold, respectively, during arousal. Taken together, our results showed that bat brain undergoes high oxygen demand during arousal from hibernation. Up‐regulation of GRP proteins and activation of JNK, PKCγ and Akt may be critical for neuroprotection and the survival of bats during the repeated process.
GALAXIES IN X-RAY SELECTED CLUSTERS AND GROUPS IN DARK ENERGY SURVEY DATA. I. STELLAR MASS GROWTH OF BRIGHT CENTRAL GALAXIES SINCE z ∼ 1.2

Using the science verification data of the Dark Energy Survey for a new sample of 106 X-ray selected clusters and groups, we study the stellar mass growth of bright central galaxies (BCGs) since redshift z ~ 1.2. Compared with the expectation in a semi-analytical model applied to the Millennium Simulation, the observed BCGs become under-massive/under-luminous with decreasing redshift. We incorporate the uncertainties associated with cluster mass, redshift, and BCG stellar mass measurements into an analysis of a redshift-dependent BCG-cluster mass relation, m * ∝ M 200 1.5 × 10 14 M ⊙ 0.24 ± 0.08 ( 1 + z ) − 0.19 ± 0.34 ? > , and compare the observed relation to the model prediction. We estimate the average growth rate since z = 1.0 for BCGs hosted by clusters of M200,z = 1013.8 M⊙; at z = 1.0: m*,BCG appears to have grown by 0.13 ± 0.11 dex, in tension at the ∼2. 5σ significance level with the 0.40 dex growth rate expected from the semi-analytic model. We show that the build-up of extended intracluster light after z = 1.0 may alleviate this tension in BCG growth rates.
Adaptive congestion estimation and control in active queue management

Active Queue Management (AQM) policies provide an early indication of incipient congestion to the source. In this paper, we propose a new AQM policy that predicts the instantaneous queue length at next time instant using adaptive filtering technique. To use the algorithm in fast routers, we reduce its computational complexity using a direct method to compute the manipulating signals. We show that adaptive congestion estimation is able to control the oscillations in the instantaneous queue length. We compare the performance of our method with respect to other well-known AQM methods such as RED and PI which are also simulated by MATLAB. We also compare the computational complexity of these algorithms with each other.
Cocoa flavanol metabolites activate HNF-3β, Sp1, and NFY-mediated transcription of apolipoprotein AI in human cells.

SCOPE To identify the mechanisms by which cocoa induces HDL levels and since apolipoprotein AI (ApoAI) is the major protein in HDLs, we analyzed, upon incubation with cocoa metabolites, ApoAI mRNA levels, its transcriptional regulation, and the levels of the transcription factors involved in this process. METHODS AND RESULTS Epicatechin and cocoa metabolites caused an increase in ApoAI expression in HepG2 cells. Electrophoretic mobility shift assays revealed the involvement of Sites A and B of the ApoAI promoter in the induction of ApoAI mRNA upon incubation with cocoa metabolites. Using supershift assays, we demonstrated the binding of HNF-3β, HNF-4, ER-α, and RXR-α to Site A and the binding of HNF-3β, NFY, and Sp1 to Site B. Luciferase assays performed with a construct containing Site B confirmed its role in the upregulation of ApoAI by cocoa metabolites. Incubation with 3-methyl-epicatechin led to an increase in HNF-3β mRNA, HNF-3β, ER-α, Sp1, and NFY protein levels and the activation of ApoAI transcription mediated by NFY, Sp1, and ER-α. CONCLUSION The activation of ApoAI transcription through Site B by cocoa flavanol metabolites is mainly mediated by an increase in HNF-3β, with a significant contribution of Sp1 and NFY, as a mechanism for the protective role of these compounds in cardiovascular diseases.
Compression and stylometry for author identification

In this paper we compare two different paradigms for author identification. The first one is based on compression algorithms where the entire process of defining and extracting features and training a classifier is avoided. The second paradigm, on the other hand, takes into account the classical pattern recognition framework, where linguistic features proposed by forensic experts are used to train a Support Vector Machine classifier. Comprehensive experiments performed on a database composed of 20 writers show that both strategies achieve similar performance but with an interesting degree of complementarity demonstrated through the confusion matrices. Advantages and drawback of both paradigms are also discussed.
Bounce Management using Text Mining

Direct marketers assign the communication channel e-mail an increasing importance, evolving a marketer’s collection of customer e-mail addresses to an asset of important business value in order to provide customers the right offer at the right point in time. Besides the design and content of an e-mail campaign the e-mail-transportation process is of critical importance to really reach your potential customer. Possible errors in the transportation can be of either permanent – hardbounces – or temporary nature – softbounces. With the transportation error communication by internet-service-providers lacking of compliance to existing standards, companies face the problem of having inaccurate information regarding deliverability. And quite often this results in the blocking of actually intact potential customer addresses. Therefore a model processing bounce messages and predicting the possibility of deliverability using semantic information obtained through text mining and the embedded Singular Value Decomposition is presented. We discuss the application of text mining tools regarding error messages and apply a multistaged decision model that minimizes the falsenegative-rate to discard addresses with permanent non-deliverability from the database while identifying addresses that maintain business value although being bounced.