Miracle-dz/UniFAR-FTUs huggingface dataset:
Translation of Polioviral mRNA Is Inhibited by Cleavage of Polypyrimidine Tract-Binding Proteins Executed by Polioviral 3Cpro

ABSTRACT The translation of polioviral mRNA occurs through an internal ribosomal entry site (IRES). Several RNA-binding proteins, such as polypyrimidine tract-binding protein (PTB) and poly(rC)-binding protein (PCBP), are required for the poliovirus IRES-dependent translation. Here we report that a poliovirus protein, 3Cpro (and/or 3CDpro), cleaves PTB isoforms (PTB1, PTB2, and PTB4). Three 3Cpro target sites (one major target site and two minor target sites) exist in PTBs. PTB fragments generated by poliovirus infection are redistributed to the cytoplasm from the nucleus, where most of the intact PTBs are localized. Moreover, these PTB fragments inhibit polioviral IRES-dependent translation in a cell-based assay system. We speculate that the proteolytic cleavage of PTBs may contribute to the molecular switching from translation to replication of polioviral RNA.
Ability of Pit and Fissure Sealant-containing Amorphous Calcium Phosphate to inhibit Enamel Demineralization

ABSTRACT Aim: To evaluate the effect of amorphous calcium phosphate (ACP)-containing pit and fissure sealant on inhibition of enamel demineralization in vitro. Materials and methods: Enamel specimens (n = 75) were prepared using freshly extracted noncarious human third molars. Box-shaped cavities (8 × 2 × 2 mm) on the buccal or lingual surfaces were prepared and restored with resin-based sealant (Concise™), ACP-containing sealant (Aegis®) or fluoride-containing sealant (Conseal-F™). The samples were acid challenged in a demineralizing solution of 50 mmol/l lactic acid at pH 5.0 for 4 days. The change in enamel microhardness (ASuH) was calculated. Data were analyzed using one-way analysis of variance (ANOVA) and Tukey’s post hoc test. Results: The mean SuH0 (±SD) (in Vicker’s unit) prior to the acid challenge was: Concise™ (318.83 ± 33.86), Aegis® (331.03 ± 21.52), Conseal-F™ (310.12 ± 34.31). Following the acid challenge, the values dropped in all groups and ASuH (±SD) values were 269.17 ± 47.49, 151.39 ± 23.96 and 175.79 ± 32.39 respectively. Conclusion: The ACP-containing pit and fissure sealant has the potential to inhibit enamel demineralization. How to cite this article: Zawaideh FI, Owais AI, Kawaja W. Ability of pit and fissure sealant-containing amorphous calcium phosphate to inhibit enamel demineralization. Int J Clin Pediatr Dent 2016;9(1):10-14.
Testing for Weak-Form Efficiency in South African Futures Markets for White and Yellow Maize

Agricultural marketing policy in South Africa has moved from a fully regulated marketing environment to a more open and transparent system. The demise of the Maize Board in 1996 created a need for South African maize producers to give more attention to price risk management. Commodity futures markets should be efficient to play the most effective role in price risk management. This study tests for weak-form efficiency in the South African Futures markets for white and yellow maize by examining the predictability of daily futures price changes. The results suggest that futures price changes for both white and yellow maize are partially predictable from past price information. The implication is that past price information does contain additional information that could be used to forecast the future price once the current futures price is known. But when taking into account brokerage costs and the time value of money, out of sample predictive performance of the model indicates that trading decisions based on the direction of predicted futures price changes do not lead to profitable trades for either crop. Hence, the evidence suggests there is no strong support for weak-form inefficiency in South African futures markets for white and yellow maize. The results further suggest that there is no trend in market efficiency over time for white and yellow maize futures markets in South Africa.
FEAST - A Multistep, Feedback Centric, Freshness Oriented Search Engine

This work aims at a multi-step feedback centric web search engine ensuring the retrieval of relevant fresh live results instead of those existing in the indexes. The methodology is based on the new concept called "Micro Search" which in turn creates the "Micro Indexes". These micro-indexes are the key factors utilized in re-ranking the selected documents. A prototype of the system called FEAST (Freshness Enriched Active Searching Technology) has been implemented. The results of experiments conducted on FEAST are encouraging and they confirm the improved quality of information retrieved.
Journal of Computational and Applied Mathematics Manuscript Draft Title: an Optimization Based Empirical Mode Decomposition Scheme Title: an Optimization Based Empirical Mode Decomposition Scheme an Optimization Based Empirical Mode Decomposition Scheme

The empirical mode decomposition (EMD) has been developed by N.E. Huang et al. in 1998 as an iterative method to decompose a nonlinear and nonstationary univariate function additively into multiscale components. These components called intrinsic mode functions (IMFs) are constructed such that they are approximately orthogonal to each other with respect to the L2 inner product. Moreover, the components allow for a definition of instantaneous frequencies through complexifying each component by means of the application of the Hilbert transform. This approach via analytic signals, however, does not guarantee that the resulting frequencies of the components are always non-negative and, thus, physically meaningful, and that the amplitudes can be interpreted as envelopes. In this paper, we formulate an optimization problem which takes into account important features desired of the resulting EMD. Specifically, we propose a data-adapted iterative method which minimizes in each iteration step a smoothness functional subject to inequality constraints involving the extrema. In this way, our method constructs a sparse data-adapted basis for the input function as well as a mathematically stringent envelope for the function. Moreover, we present an optimization-based normalization to extract instantaneous frequencies from the analytic function approach. We present corresponding algorithms together with several examples.
Distal Pancreatectomy and Splenectomy: A Robotic or LESS Approach

Introduction: The role and application of robotic surgery are debated, particularly given the expansion of laparoscopy, especially laparoendoscopic single-site (LESS) surgery. This cohort study was undertaken to delineate differences in outcomes between LESS and robotic distal pancreatectomy and splenectomy. Methods: With Institutional Review Board approval, patients undergoing LESS or robotic distal pancreatectomy and splenectomy from September 1, 2012, through December 31, 2014, were prospectively observed, and data were collected. The results are expressed as the median, with the mean ± SD. Results: Thirty-four patients underwent a minimally invasive distal pancreatectomy and splenectomy: 18 with robotic and 16 with LESS surgery. The patients were similar in sex, age, and body mass index. Conversions to open surgery and estimated blood loss were similar. There were two intraoperative complications in the group that underwent the robotic approach. Time spent in the operating room was significantly longer with the robot (297 vs 254 minutes, P = .03), although operative duration (i.e., incision to closure) was not longer (225 vs 190 minutes; P = .15). Of the operations studied, 79% were undertaken for neoplastic processes. Tumor size was 3.5 cm for both approaches; R0 resections were achieved in all patients. Length of stay was similar in the two study groups (5 vs 4 days). There was one 30-day readmission after robotic surgery. Conclusions: Patient outcomes are similar with LESS or robotic distal pancreatectomy and splenectomy. Robotic operations require more time in the operating room. Both are safe and efficacious minimally invasive operations that follow similar oncologic principles for similar tumors, and both should be in the surgeon's armamentarium for distal pancreatectomy and splenectomy.
Geometric Data Transformation For Privacy Preserving Clustering

Despite its benefit in a wide range of applications, data mining techniques also have raised a number of ethical issues. Some such issues include those of privacy, data security, intellectual property rights, and many others. In this paper, we address the privacy problem against unauthorized secondary use of information. To do so, we introduce a family of geometric data transformation methods (GDTMs) which ensure that the mining process will not violate privacy up to a certain degree of security. We focus primarily on privacy preserving data clustering, notably on partition-based and hierarchical methods. Our proposed methods distort only confidential numerical attributes to meet privacy requirements, while preserving general features for clustering analysis. Our experiments demonstrate that our methods are effective and provide acceptable values in practice for balancing privacy and accuracy. We report the main results of our performance evaluation and discuss some open research issues.
Expression of the jun-B gene during induction of monocytic differentiation.

The AP-1 protein complex binds to specific DNA sequences that regulate transcription of genes responsive to certain growth factors and phorbol esters. This complex is composed of products of the jun and fos gene families. The present studies have examined the effects of 12-O-tetradecanoylphorbol-13-acetate (TPA) on the regulation of jun-B gene expression during induction of monocytic differentiation. Low levels of jun-B transcripts were present in uninduced HL-60 promyelocytic leukemia cells. In contrast, treatment with TPA was associated with rapid increases in jun-B mRNA levels that were maximal at 3 h and remained elevated at 48 h. The induction of jun-B expression by TPA in these cells preceded that of the c-jun and c-fos genes. Similar increases in jun-B transcripts were detectable in TPA-treated THP-1 and U-937 myeloid leukemia cells, although expression of this gene was transient in the more differentiated THP-1 cells. Run-on assays demonstrated low levels of jun-B gene activation in untreated HL-60 cells, whereas TPA treatment was associated with a 6-fold increase in the transcription rate of this gene. This induction of jun-B expression occurred in the absence of de novo protein synthesis. In contrast, inhibition of protein synthesis was associated with superinduction of TPA-induced jun-B mRNA levels and an increase in stability of this transcript. These findings suggest that jun-B gene expression is regulated at both the transcriptional and posttranscriptional levels during induction of monocytic differentiation. (ABSTRACT TRUNCATED AT 250 WORDS)
The Inefficient Use of Macroeconomic Information in Analysts' Earnings Forecasts in Emerging Markets

This paper presents empirical evidence that security analysts do not efficiently use publicly available macroeconomic information in their earnings forecasts for emerging market stocks. Analysts completely ignore forecasts on political stability, while these provide valuable information for firm-level earnings growth. Analysts do incorporate output growth forecasts, but these actually bear no relevant information for firm-level earnings growth. Inflation forecasts are taken into account correctly. In addition, the information environment appears to be crucially important in emerging markets, as we find evidence that analysts handle macroeconomic information in a better way for more transparent firms.
Accurate detection for process-hotspots with vias and incomplete specification

This paper introduces the concept of via range patterns and incompletely specified range patterns to represent new types of process-hotspots. Via range patterns can represent process-hotspots containing vias that are a major source of lithography issues. An incompletely specified range pattern can accurately and succinctly represent a process-hotspot where any configuration of objects (that is unknown to the user apriori) can exist in some of its peripheral regions. These new types of range patterns cannot be accurately represented and/or detected using the concept of range patterns introduced in [7]. A new detection algorithm that can accurately detect these new types of patterns is also proposed. This is necessitated since the range pattern matching algorithm proposed earlier causes mismatches: it either misses true matches or reports false matches for these new kinds of patterns. Theoretical results show that the proposed algorithm prevents the incorrect mis-match issues, while experimental results on fab provided process-hotspots show the algorithm is computationally efficient and practical for use on real industrial designs.
A hybrid feature extraction method-based object recognition by neural network

This paper presents a neural based approach for rotated object recognition in still black and white images. The system comprises two phases: extraction of information from edge of the objects known as feature extraction and classification of objects by artificial neural network (ANN) trained with back propagation algorithm. The two different methods of features extraction are adopted from rotated edge images of the objects. First the magnitude of 2D discrete Fourier transform (DFT) of the rotated edge image of the object are computed and stored in a matrix form. The features are calculated from these coefficients and stored in a vector form. The above feature extraction method is repeated to all rotated images of the objects. The second is an efficient hybrid features extraction method which combines the features from first method and the features from 3 - level decomposition of rotated edge image by 2D discrete wavelet transform (DWT). The same method is followed to extract the features from all the rotated images. The neural classifiers are trained with 75% of data sets obtained by two different feature data sets. The performance of the neural systems is evaluated on 25% of test data sets. The results are compared in both cases which predict that ANN presents higher accuracy of object recognition rate when trained with method 2 data sets than method 1.
Increased Grey Matter Associated with Long-Term Sahaja Yoga Meditation: A Voxel-Based Morphometry Study

Objectives To investigate regional differences in grey matter volume associated with the practice of Sahaja Yoga Meditation. Design Twenty three experienced practitioners of Sahaja Yoga Meditation and twenty three non-meditators matched on age, gender and education level, were scanned using structural Magnetic Resonance Imaging and their grey matter volume were compared using Voxel-Based Morphometry. Results Grey matter volume was larger in meditators relative to non-meditators across the whole brain. In addition, grey matter volume was larger in several predominantly right hemispheric regions: in insula, ventromedial orbitofrontal cortex, inferior temporal and parietal cortices as well as in left ventrolateral prefrontal cortex and left insula. No areas with larger grey matter volume were found in non-meditators relative to meditators. Conclusions The study shows that long-term practice of Sahaja Yoga Meditation is associated with larger grey matter volume overall, and with regional enlargement in several right hemispheric cortical and subcortical brain regions that are associated with sustained attention, self-control, compassion and interoceptive perception. The increased grey matter volume in these attention and self-control mediating regions suggests use-dependent enlargement with regular practice of this meditation.
A View at Desktop Clouds

Cloud has emerged as a new computing paradigm that promises to move into computing-as-utility era. Desktop Cloud is a new type of Cloud computing. It merges two computing models: Cloud computing and volunteer computing. The aim of Desktop Cloud is to provide Cloud services out of infrastructure that is not made for this purpose in order to reduce running and maintenance costs. This paper discusses this new type of Cloud by comparing it with current Cloud and Desktop Grid models. It, also, presents several research challenges in Desktop Cloud that require further attention.
Recurrent evolution of life history ecotypes in sockeye salmon: implications for conservation and future evolution

We examine the evolutionary history and speculate about the evolutionary future of three basic life history ecotypes that contribute to the biocomplexity of sockeye salmon (Oncorhynchus nerka). The ‘recurrent evolution’ (RE) hypothesis claims that the sea/river ecotype is ancestral, a ‘straying’ form with poorly differentiated (meta)population structure, and that highly structured populations of lake‐type sockeye and kokanee have evolved repeatedly in parallel adaptive radiations between recurrent glaciations of the Pleistocene Epoch. Basic premises of this hypothesis are consistent with new, independent evidence from recent surveys of genetic variation in mitochondrial and microsatellite DNA: (1) sockeye salmon are most closely related to pink (O. gorbuscha) and chum (O. keta) salmon with sea‐type life histories; (2) the sockeye life history ecotypes exist as polyphyletic lineages within large drainages and geographic regions; (3) the sea/river ecotype exhibits less genetic differentiation among populations than the lake or kokanee ecotypes both within and among drainages; and (4) genetic diversity is typically higher in the sea/river ecotype than in the lake and kokanee ecotypes. Anthropogenic modification of estuarine habitat and intensive coastal fisheries have likely reduced and fragmented historic metapopulations of the sea/river ecotype, particularly in southern areas. In contrast, the kokanee ecotype appears to be favoured by marine fisheries and predicted changes in climate.
Big IoT and Social Networking Data for Smart Cities - Algorithmic Improvements on Big Data Analysis in the Context of RADICAL City Applications

In this paper we present a SOA (Service Oriented Architecture)-based platform, enabling the retrieval and analysis of big datasets stemming from social networking (SN) sites and Internet of Things (IoT) devices, collected by smart city applications and socially-aware data aggregation services. A large set of city applications in the areas of Participating Urbanism, Augmented Reality and Sound-Mapping throughout participating cities is being applied, resulting into produced sets of millions of user-generated events and online SN reports fed into the RADICAL platform. Moreover, we study the application of data analytics such as sentiment analysis to the combined IoT and SN data saved into an SQL database, further investigating algorithmic and configurations to minimize delays in dataset processing and results retrieval.
ICARUS and DARIUS approaches towards interoperability Two complementary projects that cover the full spectrum of interoperability issues for the integration of unmanned platforms in Search and Rescue operations

The two FP7 projects ICARUS and DARIUS share a common objective which is to integrate the unmanned platforms in Search and Rescue operations and assess their added value through the development of an integrated system that will be tested in realistic conditions on the field. This paper describes the concept of both projects towards an optimized interoperability level in the three dimensions: organizational, procedural and technical interoperability, describing the system components and illustrating the results of the trials already performed. Keywords— Search and Rescue; Unmanned Systems, Interoperability
Recollection of children following intensive care

BACKGROUND AND AIMS The recollections of critically ill children following discharge from the paediatric intensive care unit (PICU) have not previously been described. We have interviewed such children to establish the nature of their recollections. METHODS Children aged 4 years and above were interviewed following discharge from the PICU at the Queens Medical Centre, Nottingham, either in hospital or at home, using a semistructured interview. Their recollections were recorded and interpreted by content analysis. RESULTS A total of 38 interviews were carried out; 44 specific recollections were reported, the majority being neutral (60%) or positive (25%). Only 15% of recollections were negative. Negative recollections related to aspects of medical care and environmental factors. No child treated with neuromuscular blocking agents remembered any period of therapeutic paralysis. CONCLUSIONS Children's recollections of PICU are mainly neutral or positive. Mechanically ventilated children sedated with midazolam and morphine remember little of endotracheal intubation.
Timer Embedded Finite State Machine Modeling And Its Application

In this paper, we propose an extension of classical finite state machine as it called a timer embedded finite state machine (TEFSM) with its formal modeling methods. In the proposed state-based approach, a discrete event system is modeled as a coupled TEFSM. Also presented is a systematic procedure and architecture of developing a simulation executor with a synchronization manager for the coupled TEFSM model. A TEFSM toolkit for modeling and simulation of the proposed TEFSM model has been implemented and a ping pong system was developed as an illustrative example.
A short daytime test using correlation dimension for respiratory movement in OSAHS

In order to examine the pathology in patients with obstructive sleep apnoea/hypopnoea syndrome (OSAHS), the nonlinear properties of respiratory movement and breath-to-breath variations during resting wakefulness with eyes closed was investigated. Recording of the respiratory movement using inductive plethysmography was performed on 14 patients with OSAHS and 13 control subjects for 2 h in the supine position during daytime. To calculate the correlation dimension (D2) for respiratory movement, an algorithm proposed by Grassberger and Procaccia was applied. The indices of breath-to-breath variations were estimated. To calculate D2 and breath-to-breath variations, two different segments were selected (200 s each). The value of D2 for respiratory movement in patients with OSAHS was significantly greater than that in control subjects. In the case of ≥2.0 of D2 for respiratory movement, the sensitivity and specificity of detecting the presence of OSAHS was 85.7% and 76.9%, respectively. On the basis of breath-to-breath variations, only the coefficient of variation of expiratory time for respiratory movement in patients with OSAHS was significantly greater than that in the control subjects. In conclusion, the measurements of correlation dimensions for respiratory movement with a brief period during wakefulness may be a useful index for identifying patients with obstructive sleep apnoea/hypopnoea syndrome.