Miracle-dz/UniFAR-FTUs huggingface dataset:
Resource Provisioning with Budget Constraints for Adaptive Applications in Cloud Environments

The recent emergence of clouds is making the vision of utility computing realizable, i.e., computing resources and services can be delivered, utilized, and paid for as utilities such as water or electricity. This, however, creates new resource provisioning problems. Because of the pay-as-you-go model, resource provisioning should be performed in a way to keep resource costs to a minimum, while meeting an application's needs. In this work, we focus on the use of cloud resources for a class of adaptive applications, where there could be application-specific flexibility in the computation that may be desired. Furthermore, there may be a fixed time-limit as well as a resource budget. Within these constraints, such adaptive applications need to maximize their Quality of Service (QoS), more precisely, the value of an application-specific benefit function, by dynamically changing adaptive parameters. We present the design, implementation, and evaluation of a framework that can support such dynamic adaptation for applications in a cloud computing environment. The key component of our framework is a multi-input-multi-output feedback control model-based dynamic resource provisioning algorithm which adopts reinforcement learning to adjust adaptive parameters to guarantee the optimal application benefit within the time constraint. Then a trained resource model changes resource allocation accordingly to satisfy the budget. We have evaluated our framework with two real-world adaptive applications, and have demonstrated that our approach is effective and causes a very low overhead.
The 11S Proteasomal Activator REGγ Impacts Polyglutamine-Expanded Androgen Receptor Aggregation and Motor Neuron Viability through Distinct Mechanisms

Spinal and bulbar muscular atrophy (SBMA) is caused by expression of a polyglutamine (polyQ)-expanded androgen receptor (AR). The inefficient nuclear proteasomal degradation of the mutant AR results in the formation of nuclear inclusions containing amino-terminal fragments of the mutant AR. PA28γ (also referred to as REGγ) is a nuclear 11S-proteasomal activator with limited proteasome activation capabilities compared to its cytoplasmic 11S (PA28α, PA28β) counterparts. To clarify the role of REGγ in polyQ-expanded AR metabolism, we carried out genetic and biochemical studies in cell models of SBMA. Overexpression of REGγ in a PC12 cell model of SBMA increased polyQ-expanded AR aggregation and contributed to polyQ-expanded AR toxicity in the presence of dihydrotestosterone (DHT). These effects of REGγ were independent of its association with the proteasome and may be due, in part, to the decreased binding of polyQ-expanded AR by the E3 ubiquitin-ligase MDM2. Unlike its effects in PC12 cells, REGγ overexpression rescued transgenic SBMA motor neurons from DHT-induced toxicity in a proteasome binding-dependent manner, suggesting that the degradation of a specific 11S proteasome substrate or substrates promotes motor neuron viability. One potential substrate that we found to play a role in mutant AR toxicity is the splicing factor SC35. These studies reveal that, depending on the cellular context, two biological roles for REGγ impact cell viability in the face of polyQ-expanded AR; a proteasome binding-independent mechanism directly promotes mutant AR aggregation while a proteasome binding-dependent mechanism promotes cell viability. The balance between these functions likely determines REGγ effects on polyQ-expanded AR-expressing cells.
An Intuitive Interface for Interactive High Quality Image‐Based Modeling

We present the design of an interactive image‐based modeling tool that enables a user to quickly generate detailed 3D models with texture from a set of calibrated input images. Our main contribution is an intuitive user interface that is entirely based on simple 2D painting operations and does not require any technical expertise by the user or difficult pre‐processing of the input images. One central component of our tool is a GPU‐based multi‐view stereo reconstruction scheme, which is implemented by an incremental algorithm, that runs in the background during user interaction so that the user does not notice any significant response delay.
Changing potency by spontaneous fusion

DNA contents per cell were determined by staining cells with propidium iodide and subsequent FACS analysis. Genomic DNA were extracted from embryonic stem cells, bone marrow cells, and BMESL cells. DNA was amplified using microsatellite primers (D9MIT48, Research Genetics) detecting polymorphisms between the bone marrow genome (mostly C57BL/6) and the embryonic stem cell genome (129/Sv), separated on 5% agarose gel and visualized by ethidium bromide staining. Turning blood into brain: cells bearing neuronal antigens generated in vivo from bone marrow. Multi-organ, multi-lineage engraftment by a single bone marrow-derived stem cell. A. Generating green fluorescent mice by germline transmission of green fluorescent ES cells. Targeted disruption of p70 s6k defines its role in protein synthesis and rapamycin sensitivity. et al. MEKK1 suppresses oxidative stress-induced apoptosis of embryonic stem cell-derived cardiac myocytes. The gene for the embryonic stem cell coactivator UTF1 carries a regulatory element which selectively interacts with a complex composed of Oct-3/4 and Sox-2. Induction of midbrain dopaminergic neurons from ES cells by stromal cell-derived inducing activity. reprogramming of somatic nucleus in hybrid cells. Induction of multinucleated giant cell formation from in vitro culture of human monocytes with interleukin-3 and interferon-b: comparison with other stimulating factors. Am.
A MAP-Based Image Interpolation Method via Viterbi Decoding of Markov Chains of Interpolation Functions

A new method of image resolution up-conversion (image interpolation) based on maximum a posteriori sequence estimation is proposed. Instead of making a hard decision about the value of each missing pixel, we estimate the missing pixels in groups. At each missing pixel of the high resolution (HR) image, we consider an ensemble of candidate interpolation methods (interpolation functions). The interpolation functions are interpreted as states of a Markov model. In other words, the proposed method undergoes state transitions from one missing pixel position to the next. Accordingly, the interpolation problem is translated to the problem of estimating the optimal sequence of interpolation functions corresponding to the sequence of missing HR pixel positions. We derive a parameter-free probabilistic model for this to-be-estimated sequence of interpolation functions. Then, we solve the estimation problem using a trellis representation and the Viterbi algorithm. Using directional interpolation functions and sequence estimation techniques, we classify the new algorithm as an adaptive directional interpolation using soft-decision estimation techniques. Experimental results show that the proposed algorithm yields images with higher or comparable peak signal-to-noise ratios compared with some benchmark interpolation methods in the literature while being efficient in terms of implementation and complexity considerations.
Why Is Spatial Stereoresolution So Low?

Spatial stereoresolution (the finest detectable modulation of binocular disparity) is much poorer than luminance resolution (finest detectable luminance variation). In a series of psychophysical experiments, we examined four factors that could cause low stereoresolution: (1) the sampling properties of the stimulus, (2) the disparity gradient limit, (3) low-pass spatial filtering by mechanisms early in the visual process, and (4) the method by which binocular matches are computed. Our experimental results reveal the contributions of the first three factors. A theoretical analysis of binocular matching by interocular correlation reveals the contribution of the fourth: the highest attainable stereoresolution may be limited by (1) the smallest useful correlation window in the visual system, and (2) a matching process that estimates the disparity of image patches and assumes that disparity is constant across the patch. Both properties are observed in disparity-selective neurons in area V1 of the primate (Nienborg et al., 2004).
Word Alignment for Languages with Scarce Resources Using Bilingual Corpora of Other Language Pairs

This paper proposes an approach to improve word alignment for languages with scarce resources using bilingual corpora of other language pairs. To perform word alignment between languages L1 and L2, we introduce a third language L3. Although only small amounts of bilingual data are available for the desired language pair L1-L2, large-scale bilingual corpora in L1-L3 and L2-L3 are available. Based on these two additional corpora and with L3 as the pivot language, we build a word alignment model for L1 and L2. This approach can build a word alignment model for two languages even if no bilingual corpus is available in this language pair. In addition, we build another word alignment model for L1 and L2 using the small L1-L2 bilingual corpus. Then we interpolate the above two models to further improve word alignment between L1 and L2. Experimental results indicate a relative error rate reduction of 21.30% as compared with the method only using the small bilingual corpus in L1 and L2.
Incorporating trust relationships in collaborative filtering recommender system

Nowadays with the readily accessibility of online social networks (OSNs), people are facilitated to share interesting information with friends through OSNs. Undoubtedly these sharing activities make our life more fantastic. However, meanwhile one challenge we have to face is information overload that we do not have enough time to review all of the content broadcasted through OSNs. So we need to have a mechanism to help users recognize interesting items from a large pool of content. In this project, we aim at filtering unwanted content based on the strength of trust relationships between users. We have proposed two kinds of trust models-basic trust model and source-level trust model. The trust values are estimated based on historical user interactions and profile similarity. We estimate dynamic trusts and analyze the evolution of trust relationships over dates. We also incorporate the auxiliary causes of interactions to moderate the noisy effect of user's intrinsic tendency to perform a certain type of interaction. In addition, since the trustworthiness of diverse information sources are rather distinct, we further estimate trust values at source-level. Our recommender systems utilize several types of Collaborative Filtering (CF) approaches, including conventional CF (namely user-based, item-based, singular value decomposition (SVD)based), and also trust-combined user-based CF. We evaluate our trust models and recommender systems on Friendfeed datasets. By comparing the evaluation results, we found that the recommendations based on estimated trust relationships were better than conventional CF recommendations.
Explicit symmetric pseudo-random matrices

We consider the problem of generating symmetric pseudo-random sign (±1) matrices based on the similarity of their spectra to Wigner's semicircular law. Using binary m-sequences (Golomb sequences) of lengths n = 2m − 1, we give a simple explicit construction of circulant n × n sign matrices and show that their spectra converge to the semicircular law when n grows. The Kolmogorov complexity of the proposed matrices equals to that of Golomb sequences and is at most 2log2(n) bits.
Use Cases for Triple Stores and Graph Databases in Scalable Data Infrastructures

Various types of NoSQL databases may present a sound alternative to relational databases in eInfrastructures that require managing and analysing data supplied from disparate sources. This work considers a few use cases where particular types of NoSQL databases – triple stores and graph databases – may be a natural choice for scalable data services. The purpose of this work is to brief on the experiments performed and to provide a roadmap for further technology evaluation. Cases suggested are mapped to EUDAT common services [11] yet should be of interest to other eInfrastructures.
Inhibition of Complex Glycosylation Increases the Formation of PrPsc

N‐linked glycans with complex structure have a major role in the biological activity of a wide variety of cell surface and secreted glycoproteins. Here, we show that geldanamycin, an inhibitor of Hsp90, interferes with the formation of complex glycosylated mammalian prion protein (PrPC). Similarly to inhibitors of α‐mannosidases, geldanamycin stabilized a high mannose PrPC glycoform and prevented the subsequent processing into complex structures. Moreover, a PrP/Grp94 complex could be isolated from geldanamycin‐treated cells, suggesting that Grp94 might play a role in the processing of PrPC in the endoplasmic reticulum. Inhibition of complex glycosylation did not interfere with the glycosylphosphatidylinositol (GPI) anchor attachment and cellular trafficking of high mannose PrPC to the outer leaflet of the plasma membrane. In scrapie‐infected neuroblastoma cells, however, high mannose PrPC glycoforms were preferred substrates for the formation of PrP‐scrapie (PrPSc). Our study reveals that complex glycosylation is dispensable for the cellular trafficking of PrPC, but modulates the formation of PrPSc.
Efficient parallelization of the Discrete Wavelet Transform algorithm using memory-oblivious optimizations

As the rate of single-thread CPU performance improvement per generation has diminished due to lower transistor-speed scaling and energy related issues, researchers and industry have shifted their interest towards multi-core and many-core architectures for improving performance. Comparisons between optimized applications for parallel architectures have been quantified many times in the literature, but contradictory results have been reported mainly due to biased methods of evaluating and comparing these architectures. In this paper, we present memory-oblivious optimizations of the widely used Discrete Wavelet Transform (DWT), and provide detailed comparisons of the algorithm on Intel and AMD multi-core CPUs, Nvidia many-core GPUs, as well as the Intel's Xeon Phi many-core coprocessor. Our results indicate that, compared to their respective non-optimized single thread implementations, memory-oblivious optimization delivers up to 17.9×-197.2× performance improvement for the various architectures examined. Furthermore, compared to the state-of-the-art, the presented CPU and GPU memory-oblivious implementations are 2.6× and 1.3× faster respectively than the fastest implementations of DWT currently available in the literature. No comparison to the state-of-the-art can be made for the Xeon Phi, as, to the best of our knowledge, this is the first study that optimizes the DWT for this newfangled architecture.
Functional Genomic Analysis of Remyelination Reveals Importance of Inflammation in Oligodendrocyte Regeneration

Tumor necrosis factor α (TNFα), a proinflammatory cytokine, was shown previously to promote remyelination and oligodendrocyte precursor proliferation in a murine model for demyelination and remyelination. We used Affymetrix microarrays in this study to identify (1) changes in gene expression that accompany demyelination versus remyelination and (2) changes in gene expression during the successful remyelination of wild-type mice versus the unsuccessful attempts in mice lacking TNFα. Alterations in inflammatory genes represented the most prominent changes, with major histocompatibility complex (MHC) genes dramatically enhanced in microglia and astrocytes during demyelination, remyelination, and as a consequence of TNFα stimulation. Studies to examine the roles of these genes in remyelination were then performed using mice lacking specific genes identified by the microarray. Analysis of MHC-II-null mice showed delayed remyelination and regeneration of oligodendrocytes, whereas removal of MHC-I had little effect. These data point to the induction of MHC-II by TNFα as an important regulatory event in remyelination and emphasize the active inflammatory response in regeneration after pathology in the brain.
A multi-staining chip using hydrophobic valves for exfoliative cytology in cancer

Exfoliative cytology is a highly established technique for the diagnosis of tumors. Various microfluidic devices have been developed to minimize the sample numbers by conjugating multiple antibodies in a single sample. However, the previous multi-staining devices require complex control lines and valves operated by external power sources, to deliver multiple antibodies separately for a single sample. In addition, most of these devices are composed of hydrophobic materials, causing unreliable results due to the non-specific binding of antibodies. Here, we present a multi-staining chip using hydrophobic valves, which is formed by the partial treatment of 2-hydroxyethyl methacrylate (HEMA). Our chip consists of a circular chamber, divided into six equal fan-shaped regions. Switchable injection ports are located at the center of the chamber and at the middle of the arc of each fan-shaped zone. Thus, our device is beneficial for minimizing the control lines, since pre-treatment solutions flow from the center to outer ports, while six different antibodies are introduced oppositely from the outer ports. Furthermore, hydrophobic narrow channels, connecting the central region and each of the six fan-shaped zones, are closed by capillary effect, thus preventing the fluidic mixing without external power sources. Meanwhile, HEMA treatment on the exterior region results in hydrophobic-to-hydrophilic transition and prevents the non-specific binding of antibodies. For the application, we measured the expression of six different antibodies in a single sample using our device. The expression levels of each antibody highly matched the conventional immunocytochemistry results. Our device enables cancer screening with a small number of antibodies for a single sample.
The potency of chicken egg yolk immunoglobulin (IgY) specific as immunotherapy to Mycobacterium tuberculosis infection

The aim of this study was to characterize of chicken egg yolk immunoglobulins (IgYs) specific as immunotherapy to Mycobacterium tuberculosis complex (MTBC) infection. Lohmann laying hens were immunized intramuscularly with antigenic of MTBC. Egg yolk was separated from egg white, and IgY antibody was then purified by multiple polyethylene glycols 6000 extraction and ammonium sulfate purification steps. The IgY anti-MTBC concentration in egg yolk increased at 2 weeks and it reached a maximum at 4 weeks after immunization. After 6 weeks, the levels of IgY anti-MTBC decreased gradually. The antibody of MTBC was detected and produces a specific line of precipitation in agar gel precipitation test beginning the week 2 after the first immunization. Analysis of results obtained with ELISA showed a significant increase in the MTBC specific antibodies after 2 weeks and reached a plateau at 4 weeks from the booster immunization. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis revealed the IgY preparation to be pure and dissociated into protein bands with molecular weights of 112, 78, 69, 49, and 28 kDa and Western blot analysis shown the presence of anti-MTBC IgY in egg yolks, with molecular weights of approximately 78 kDa. These results suggested that egg yolk could be a practical strategy in large-scale production of specific anti-MTBC IgY for immunotherapy of TBC.
The lumigraph

This paper discusses a new method for capturing the complete appearance of both synthetic and real world objects and scenes, representing this information, and then using this representation to render images of the object from new camera positions. Unlike the shape capture process traditionally used in computer vision and the rendering process traditionally used in computer graphics, our approach does not rely on geometric representations. Instead we sample and reconstruct a 4D function, which we call a Lumigraph. The Lumigraph is a subsetof the complete plenoptic function that describes the flow of light at all positions in all directions. With the Lumigraph, new images of the object can be generated very quickly, independent of the geometric or illumination complexity of the scene or object. The paper discusses a complete working system including the capture of samples, the construction of the Lumigraph, and the subsequent rendering of images from this new representation.
The light chain composition of chicken brain myosin-Va: calmodulin, myosin-II essential light chains, and 8-kDa dynein light chain/PIN.

Class V myosins are a ubiquitously expressed family of actin-based molecular motors. Biochemical studies on myosin-Va from chick brain indicate that this myosin is a two-headed motor with multiple calmodulin light chains associated with the regulatory or neck domain of each heavy chain, a feature consistent with the regulatory effects of Ca(2+) on this myosin. In this study, the identity of three additional low molecular weight proteins of 23-,17-, and 10 kDa associated with myosin-Va is established. The 23- and 17-kDa subunits are both members of the myosin-II essential light chain gene family, encoded by the chicken L23 and L17 light chain genes, respectively. The 10-kDa subunit is a protein originally identified as a light chain (DLC8) of flagellar and axonemal dynein. The 10-kDa subunit is associated with the tail domain of myosin-Va.
Transcriptional Analysis of the Pre-Erythrocytic Stages of the Rodent Malaria Parasite, Plasmodium yoelii

The molecular biology of the clinically silent pre-erythrocytic stages of mammalian Plasmodium spp, composed of both the sporozoite and liver stages, has remained largely uncharacterized. Improved understanding of the biological processes required for progression through the pre-erythrocytic stages could lead to the identification of novel drug and vaccine targets. To gain insights into the molecular events that occur during the pre-erythrocytic stages of Plasmodium, comparative transcriptional analysis was performed on radiation attenuated sporozoites (RAS), wild type sporozoites (wtSPZ) and liver stage parasites collected either 24 hours (24hrLS) or 48 hours (48hrLS) after mice were infected with Plasmodium yoelii. Our results revealed 1100 Plasmodium genes that were differentially expressed in one or more constituents of the pre-erythrocytic stages relative to the mixed blood stages. Overall, the transcriptional profile of P. yoelii gradually became more similar to the mixed blood stages as pre-erythrocytic stage development progressed into the mature liver stage schizont. The transcriptional profiles of RAS and wtSPZ were found to be nearly identical. Likewise, the transcriptional profile of 24hrLS was very similar to that of the 48hrLS parasites. The largest differences in gene expression were observed when comparing wtSPZ or RAS to either of the liver stage samples. Further characterization of the differentially expressed genes identified in this study could help elucidate the biological mechanisms employed by Plasmodium during the pre-erythrocytic stages.