Miracle-dz/UniFAR-FTUs huggingface dataset:
What Is Happening in the Video? —Annotate Video by Sentence

Due to the popularity of online video sharing Web sites such as YouTube, millions of users have treated online video as a source of information and entertainment. Therefore, video annotation has evoked great interest in the past few years. In this paper, we propose a four-step approach to automatically annotate video shots with sentences. The first step is video preprocessing, converting video shot into a sequence of frame images. The second step is to find related candidate elements of the sentence about the video contents. The main elements in the sentence are objects, events, scenes, and modifiers. These candidate elements are gained by searching for similar images with the video frames in our collected image data sets instead of video data sets. The third step is to select the best elements among these candidate ones by a weighted scoring algorithm. The final step is to construct a sentence with the help of a correlation graph algorithm to analyze the relationships among the best elements. The experimental results indicate that our method is effective to annotate videos with sentences. What is more, the weighted scoring algorithm and the correlation graph algorithm that we propose are efficient in developing the experimental performance.
Nuclear Localization of Dengue Virus Nonstructural Protein 5 Does Not Strictly Correlate with Efficient Viral RNA Replication and Inhibition of Type I Interferon Signaling

ABSTRACT Dengue virus (DENV) is an important human pathogen, especially in the tropical and subtropical parts of the world, causing considerable morbidity and mortality. DENV replication occurs in the cytoplasm; however, a high proportion of nonstructural protein 5 (NS5), containing methyltransferase (MTase) and RNA-dependent RNA polymerase (RdRp) activities, accumulates in the nuclei of infected cells. The present study investigates the impact of nuclear localization of NS5 on its known functions, including viral RNA replication and subversion of the type I interferon response. By using a mutation analysis approach, we identified the most critical residues within the αβ nuclear localization signal (αβNLS), which are essential for the nuclear accumulation of this protein. Although we observed an overall correlation between reduced nuclear accumulation of NS5 and impaired RNA replication, we identified one mutant with drastically reduced amounts of nuclear NS5 and virtually unaffected RNA replication, arguing that nuclear localization of NS5 does not correlate strictly with DENV replication, at least in cell culture. Because NS5 plays an important role in blocking interferon signaling via STAT-2 (signal transducer and activator of transcription 2) degradation, the abilities of the NLS mutants to block this pathway were investigated. All mutants were able to degrade STAT-2, with accordingly similar type I interferon resistance phenotypes. Since the NLS is contained within the RdRp domain, the MTase and RdRp activities of the mutants were determined by using recombinant full-length NS5. We found that the C-terminal region of the αβNLS is a critical functional element of the RdRp domain required for polymerase activity. These results indicate that efficient DENV RNA replication requires only minimal, if any, nuclear NS5, and they identify the αβNLS as a structural element required for proper RdRp activity.
CODOMs: Protecting software with Code-centric memory Domains

Today's complex software systems are neither secure nor reliable. The rudimentary software protection primitives provided by current hardware forces systems to run many distrusting software components (e.g., procedures, libraries, plugins, modules) in the same protection domain, or otherwise suffer degraded performance from address space switches. We present CODOMs (COde-centric memory DOMains), a novel architecture that can provide finer-grained isolation between software components with effectively zero run-time overhead, all at a fraction of the complexity of other approaches. An implementation of CODOMs in a cycle-accurate full-system x86 simulator demonstrates that with the right hardware support, finer-grained protection and run-time performance can peacefully coexist.
Electroimmunodiffusion (EID): a simple, rapid method for quantitation of immunoglobulins in dilute biological fluids.

Abstract An immunoprecipitation method called electroimmunodiffusion (EID) is described in which antigen diffuses, under the influence of an electric field, into a layer of agar containing specific antiserum. The antigen-antibody precipitate length is proportional to the concentration of antigen in the well, and to the duration of electrophoresis. The method is rapid, accurate, and reproducible, and requires 4 μL of sample. EID is more sensitive than simple radial diffusion. The lower limits of accurate quantitation are γG, 0.2 mg. per cent; γA, 0.5 mg. per cent; γM, 0.8 mg. per cent. The method is suitable for the measurement of immunoglobulins in small samples of dilute and unconcentrated biological fluids. Conditions for the measurement of γG-globulin in cerebrospinal fluid (CSF) are described. Normal CSF contained 1.0 to 3.1 mg. per 100 ml. γG.
Small-animal PET registration method with intrinsic validation designed for large datasets

We present a procedure to validate the results of small animal Positron Emission Tomography (PET) image registration by means of consistency measures. Small animal 2- Deoxy-2-[F-18]fluoro-D-glucose (FDG) PET studies do not show the same intensity distribution even for images acquired in similar conditions, as the resulting image is influenced by several variables which are not always completely under control. Because of these difficulties, the results from automatic registration methods have to be visually inspected to detect failures. We propose a method to automate this validation process. Two reference images from the dataset are selected by an expert user avoiding images with poor contrast, animal movement or low quality, and both are co-registered using anatomical landmarks. All the remaining images in the dataset are then registered to every reference with an automatic two-step algorithm based on Mutual Information. The known transformation relating both references allows measuring the registration consistency, which is a good estimator of the accuracy of the alignment process, for every image in the dataset. This value can be used to assess the quality of the registration and therefore detect the incorrect results. We have applied this validation process on a large dataset of 120 FDG-PET rat brain images obtained with a rotating PET scanner. The registration consistency was calculated for every image in the dataset and values below 1.65 mm (PET image resolution) were considered as successful registrations. 116 images were correctly registered with an average error of 0.839 mm, while in four images the proposed method detected a registration failure. Two of these failures were due to very low image quality and these studies were discarded from the study, while the other two were correctly aligned after applying a manual pre-alignment step. Our approach requires minimal user interaction and provides automatic assessment of the registration error, making it unnecessary to visually inspect and check every registration result.
Uterine Dysfunction in Biglycan and Decorin Deficient Mice Leads to Dystocia during Parturition

Cesarean birth rates are rising. Uterine dysfunction, the exact mechanism of which is unknown, is a common indication for Cesarean delivery. Biglycan and decorin are two small leucine-rich proteoglycans expressed in the extracellular matrix of reproductive tissues and muscle. Mice deficient in biglycan display a mild muscular dystrophy, and, along with mice deficient in decorin, are models of Ehlers-Danlos Syndrome, a connective tissue anomaly associated with uterine rupture. As a variant of Ehlers-Danlos Syndrome is caused by a genetic mutation resulting in abnormal biglycan and decorin secretion, we hypothesized that biglycan and decorin play a role in uterine function. Thus, we assessed wild-type, biglycan, decorin and double knockout pregnancies for timing of birth and uterine function. Uteri were harvested at embryonic days 12, 15 and 18. Nonpregnant uterine samples of the same genotypes were assessed for tissue failure rate and spontaneous and oxytocin-induced contractility. We discovered that biglycan/decorin mixed double-knockout dams displayed dystocia, were at increased risk of delayed labor onset, and showed increased tissue failure in a predominantly decorin-dependent manner. In vitro spontaneous uterine contractile amplitude and oxytocin-induced contractile force were decreased in all biglycan and decorin knockout genotypes compared to wild-type. Notably, we found no significant compensation between biglycan and decorin using quantitative real time PCR or immunohistochemistry. We conclude that the biglycan/decorin mixed double knockout mouse is a model of dystocia and delayed labor onset. Moreover, decorin is necessary for uterine function in a dose-dependent manner, while biglycan exhibits partial compensatory mechanisms in vivo. Thus, this model is poised for use as a model for testing novel targets for preventive or therapeutic manipulation of uterine dysfunction.
Learning to Infer Graphics Programs from Hand-Drawn Images

We introduce a model that learns to convert simple hand drawings into graphics programs written in a subset of \LaTeX. The model combines techniques from deep learning and program synthesis. We learn a convolutional neural network that proposes plausible drawing primitives that explain an image. These drawing primitives are like a trace of the set of primitive commands issued by a graphics program. We learn a model that uses program synthesis techniques to recover a graphics program from that trace. These programs have constructs like variable bindings, iterative loops, or simple kinds of conditionals. With a graphics program in hand, we can correct errors made by the deep network, measure similarity between drawings by use of similar high-level geometric structures, and extrapolate drawings. Taken together these results are a step towards agents that induce useful, human-readable programs from perceptual input.
The Prostaglandin E2 Receptor EP4 Regulates Obesity-Related Inflammation and Insulin Sensitivity

With increasing body weight, macrophages accumulate in adipose tissue. There, activated macrophages secrete numerous proinflammatory cytokines and chemokines, giving rise to chronic inflammation and insulin resistance. Prostaglandin E2 suppresses macrophage activation via EP4; however, the role of EP4 signaling in insulin resistance and type 2 diabetes mellitus remains unknown. In this study, we treated db/db mice with an EP4-selective agonist, ONO-AE1-329, for 4 weeks to explore the role of EP4 signaling in obesity-related inflammation in vivo. Administration of the EP4 agonist did not affect body weight gain or food intake; however, in the EP4 agonist–treated group, glucose tolerance and insulin resistance were significantly improved over that of the vehicle–treated group. Additionally, administration of the EP4 agonist inhibited the accumulation of F4/80-positive macrophages and the formation of crown-like structures in white adipose tissue, and the adipocytes were significantly smaller. The treatment of the EP4 agonist increased the number of anti-inflammatory M2 macrophages, and in the stromal vascular fraction of white adipose tissue, which includes macrophages, it markedly decreased the levels of proinflammatory cytokines and chemokines. Further, EP4 activation increased the expression of adiponectin and peroxidase proliferator–activated receptors in white adipose tissue. Next, we examined in vitro M1/M2 polarization assay to investigate the impact of EP4 signaling on determining the functional phenotypes of macrophages. Treatment with EP4 agonist enhanced M2 polarization in wild-type peritoneal macrophages, whereas EP4-deficient macrophages were less susceptible to M2 polarization. Notably, antagonizing peroxidase proliferator–activated receptor δ activity suppressed EP4 signaling-mediated shift toward M2 macrophage polarization. Thus, our results demonstrate that EP4 signaling plays a critical role in obesity-related adipose tissue inflammation and insulin resistance by regulating macrophage recruitment and polarization. The activation of EP4 signaling holds promise for treating obesity and type 2 diabetes mellitus.
Glucose up‐regulates HIF‐1α expression in primary cortical neurons in response to hypoxia through maintaining cellular redox status

It has been suggested that hypoxia‐inducible factor 1 (HIF‐1), a key regulator in cell’s adaptation to hypoxia, plays an important role in the fate of neurons during ischemia. However, the mechanism of HIF‐1 regulation is still not fully understood in neurons subjected to ischemia. In this study, we demonstrated that glucose up‐regulated the expression of HIF‐1α, the oxygen‐dependent subunit of HIF‐1, in rat primary cortical neurons exposed to hypoxia. To understand the mechanism of glucose‐regulated HIF‐1α expression, we investigated the relationships between HIF‐1α expression, reactive oxygen species (ROS), and redox status. Low levels of HIF‐1α protein expression were observed in the neurons exposed to in vitro ischemic conditions that had high levels of ROS (oxidizing environments), and vice versa. The glutathione (GSH) precursor, N‐acetyl cysteine, induced HIF‐1α protein expression in hypoxic neurons while the GSH synthesis inhibitor, l‐buthionine sulfoximine, inhibited the expression. Moreover, (−)‐epicatechin gallate, a ROS scavenger, elevated HIF‐1α expression in the neurons subjected to in vitro ischemia. Furthermore, results from a systemic hypoxia model showed that a reducing environment increased HIF‐1α expression in rat brains. Taken together, these data presented the first evidence that glucose promoted HIF‐1α stabilization through regulating redox status in primary neurons exposed to hypoxia. The results imply that hypoxia only may not be sufficient to stabilize HIF‐1α and that a reducing environment is required to stabilize HIF‐1α in neurons exposed to hypoxia.
Rapid‐on‐chip determination of dielectric properties of biological cells using imaging techniques in a dielectrophoresis dot microsystem

Dielectrophoresis is a technique whereby polarisable particles are manipulated by non‐uniform alternating electric fields. A specific application of this technique is deducing the dielectric properties of cells from analysis of the dielectrophoretic spectrum of that particular cell population. We have developed a new microelectrode geometry consisting of two parallel electrode planes, one of which is patterned with arrays of circular apertures or ‘dots’. The radial symmetry of the dots means that the polarisability of the particles within the dot can be directly related to change shifts in light transmission through the dot, and quantified from analysis of digital images. We have validated our system using well‐characterised cell types and found a high degree of agreement to published data. Furthermore, we have observed that at high particle concentrations, electrostatic inter‐particle repulsion causes spontaneous, rapid particle re‐dispersion over the dot volume upon removal of an applied electric field. This allows the automated acquisition of a spectrum of 26 data points in approximately 15 min.
Expression Profiling in the Muscular Dystrophies

We used expression profiling to define the pathophysiological cascades involved in the progression of two muscular dystrophies with known primary biochemical defects, dystrophin deficiency (Duchenne muscular dystrophy) and α-sarcoglycan deficiency (a dystrophin-associated protein). We employed a novel protocol for expression profiling in human tissues using mixed samples of multiple patients and iterative comparisons of duplicate datasets. We found evidence for both incomplete differentiation of patient muscle, and for dedifferentiation of myofibers to alternative lineages with advancing age. One developmentally regulated gene characterized in detail, α-cardiac actin, showed abnormal persistent expression after birth in 60% of Duchenne dystrophy myofibers. The majority of myofibers (∼80%) remained strongly positive for this protein throughout the course of the disease. Other developmentally regulated genes that showed widespread overexpression in these muscular dystrophies included embryonic myosin heavy chain, versican, acetylcholine receptor α-1, secreted protein, acidic and rich in cysteine/osteonectin, and thrombospondin 4. We hypothesize that the abnormal Ca2+ influx in dystrophin- and α-sarcoglycan–deficient myofibers leads to altered developmental programming of developing and regenerating myofibers. The finding of upregulation of HLA-DR and factor XIIIa led to the novel identification of activated dendritic cell infiltration in dystrophic muscle; these cells mediate immune responses and likely induce microenvironmental changes in muscle. We also document a general metabolic crisis in dystrophic muscle, with large scale downregulation of nuclear-encoded mitochondrial gene expression. Finally, our expression profiling results show that primary genetic defects can be identified by a reduction in the corresponding RNA.
Profiling of promoter occupancy by PPARα in human hepatoma cells via ChIP-chip analysis

The transcription factor peroxisome proliferator-activated receptor α (PPARα) is an important regulator of hepatic lipid metabolism. While PPARα is known to activate transcription of numerous genes, no comprehensive picture of PPARα binding to endogenous genes has yet been reported. To fill this gap, we performed Chromatin immunoprecipitation (ChIP)-chip in combination with transcriptional profiling on HepG2 human hepatoma cells treated with the PPARα agonist GW7647. We found that GW7647 increased PPARα binding to 4220 binding regions. GW7647-induced binding regions showed a bias around the transcription start site and most contained a predicted PPAR binding motif. Several genes known to be regulated by PPARα, such as ACOX1, SULT2A1, ACADL, CD36, IGFBP1 and G0S2, showed GW7647-induced PPARα binding to their promoter. A GW7647-induced PPARα-binding region was also assigned to SREBP-targets HMGCS1, HMGCR, FDFT1, SC4MOL, and LPIN1, expression of which was induced by GW7647, suggesting cross-talk between PPARα and SREBP signaling. Our data furthermore demonstrate interaction between PPARα and STAT transcription factors in PPARα-mediated transcriptional repression, and suggest interaction between PPARα and TBP, and PPARα and C/EBPα in PPARα-mediated transcriptional activation. Overall, our analysis leads to important new insights into the mechanisms and impact of transcriptional regulation by PPARα in human liver and highlight the importance of cross-talk with other transcription factors.
Effects of Language Experience on Organization of Vowel Sounds

There is a long tradition in laboratory phonetics of describing the interaction of phonetic inventories and constraints of auditory perception and articulatory production. For example, Liljencrants & Lindblom (1972) attempted to predict the inventories of typical vowel systems by appealing to the notion of maximal perceptual distinctiveness. Stevens (1989) explained the makeup of these inventories with reference to stable articulatory-acoustic mappings. This tradition is based on the notion that speech is a system which developed to provide robust, reliable and efficient communication. It is presumed that these desiderata have led to linguistic systems that take advantage of the operating principles of the perceptual and articulatory systems and that the structure of phonetic inventories (both supra-and sub-phonemic) will reflect, in some manner, these operating principles (see e. this approach). This is certainly a compelling story as far as it goes. However, it is also important that linguistic systems are learnable. Infants and second-language learners must be able to induce the phonetic inventory (and, of course, other aspects of language) to be competent participants in communication. The operating principles of whatever learning is responsible for the induction of phonetic inventories may also leave a fingerprint on the membership and structure of these inventories. Recent experimental work has been concerned with the description of processes underlying acquisition of phonetic categories. This paper will discuss
Process groups and group communications: classifications and requirements

Different distributed applications are examined and their requirements for group communication support are outlined. The concept of a process group is defined. On the basis of internal structures and external behavior, groups are classified into different categories and their properties are discussed. Group communication is an OS-level abstraction that offers convenience and clarity to the programmer. <<ETX>>
The Effectiveness of Emotional Intelligence Training on the Mental Health of Male Deaf Students

Abstract Background Deafness is a common neural-sensory impairment which leads to lower life quality, withdrawal, social activities reduction, and rejection feeling. So, it is important to plan suitable training programs for mental health promotion of deaf children. Emotional intelligence training is one of these programs. The present study was aimed to determine the effectiveness of emotional intelligence training on the mental health of deaf students. Methods In this semi-experimental study with pretest and posttest design, General Health Questionnaire (GHQ) was completed in 40 randomly selected boy deaf students with mean age of (12.48) years old before and after the intervention. The aim of the questionnaire was obtaining information of somatic symptoms, anxiety, social dysfunction, and depression as well as general health. The students were assigned in experimental and control group randomly and in equal. Experimental group participated in 12 sessions (each session lasts for 50 minutes; twice a week) and were trained by emotional intelligence program, but control group did not. Multivariate analysis of covariance (MANCOVA) was used for analyzing the data. Results There was a significant difference (P<0.001) between experimental and control group according to somatic symptoms, anxiety, social dysfunction, depression and general health as a whole after participation in intervention sessions. Conclusion There was a significant decrease in somatic symptoms, anxiety, social dysfunction, depression and increase in general health of experimental group. Our findings showed that emotional intelligence training program led to promote of general health of boy deaf students.
Efficient and Self-Balanced ROLLUP Aggregates for Large-Scale Data Summarization

Data summarization queries that compute aggregates by grouping datasets across several dimensions are essential to help users make sense of very large datasets. In this work, we focus on ROLLUP, an important operator that has been recently added to the Hadoop MapReduce ecosystem. However, its current implementation suffers from very large communication costs, leading to inefficient executions. We thus proceed with the design of a new ROLLUP operator for high-level languages. Our operator is self-optimizing, which means that it automatically performs load-balancing and determines a suitable operating point to achieve the highest performance. We have implemented our ROLLUP operator for Apache Pig, a popular high-level language in the Hadoop ecosystem. Our experimental results, obtained on both synthetic and real datasets, indicate that our new operator outperforms the current ROLLUP implementation in Pig by at least 50%.