Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcriptional Analysis of p30 Major Outer Membrane Multigene Family of Ehrlichiacanis in Dogs, Ticks, and Cell Culture at Different Temperatures

ABSTRACT Ehrlichia canis, an obligatory intracellular bacterium of monocytes and macrophages, causes canine monocytic ehrlichiosis. E. canisimmunodominant 30-kDa major outer membrane proteins are encoded by a polymorphic multigene family consisting of more than 20 paralogs. In the present study, we analyzed the mRNA expression of 14 paralogs in experimentally infected dogs andRhipicephalussanguineus ticks by reverse transcription-PCR using gene-specific primers followed by Southern blotting. Eleven out of 14 paralogs in E.canis were transcribed in increasing numbers and transcription levels, while the mRNA expression of the 3 remaining paralogs was not detected in blood monocytes of infected dogs during the 56-day postinoculation period. Three different groups ofR. sanguineus ticks (adult males and females and nymphs) were separately infected with E.canis by feeding on the infected dogs. In these pools of acquisition-fed ticks as well as in the transmission-fed adult ticks, the transcript from only one paralog was detected, suggesting the predominant transcription of that paralog or the suppression of the remaining paralogs in ticks. Expression of the same paralog was higher whereas expression of the remaining paralogs was lower inE. canis cultivated in dog monocyte cell line DH82 at 25°C than in E. caniscultivated at 37°C. Analysis of differential expression ofp30 multigenes in dogs, ticks, or monocyte cell cultures would help in understanding the role of these gene products in pathogenesis and E. canis transmission as well as in designing a rational vaccine candidate immunogenic against canine ehrlichiosis.
On p-adic propreties of the Witten-Reshetikhin-Turaev invariant

We use the properties of the Melvin-Morton expansion of the colored Jones polynomial in order to prove that the trivial connection contribution converges p-adicly to the SO(3) Witten-Reshetikhin-Turaev invariant of rational homology spheres, as it was conjectured by R. Lawrence.
Understanding Interactions among Genetic Algorithm Parameters

Genetic algorithms (GAs) are multi-dimensional and stochastic search methods, involving complex interactions among their parameters. For last two decades, researchers have been trying to understand the mechanics of GA parameter interactions by using various techniques. The methods include careful 'functional' decomposition of parameter interactions, empirical studies, and Markov chain analysis. Although the complex knot of these interactions are getting loose with such analyses, it still remains an open question in the mind of a new-comer to the field or to a GA-practitioner as to what values of GA parameters (such as population size, choice of GA operators, operator probabilities, and others) to use in an arbitrary problem. In this paper, we investigate the performance of simple tripartite GAs on a number of simple to complex test problems from a practical standpoint. Since function evaluations are most time-consuming in a real-world problem, we compare different GAs for a fixed number of function evaluations. Based on probability calculations and simulation results, it is observed that for solving simple problems (unimodal or small modality problems) mutation operator plays an important role, although crossover operator can also solve these problems. However, two operators (when applied alone) have two different working zones for population size. For complex problems involving massive multimodality and misleadingness (deception), crossover operator is the key search operator and performs reliably with an adequate population size. Based on these studies, it is recommended that when in doubt, the use of the crossover operator with an adequate population size is a reliable approach.
Existential Closures for Knowledge Compilation

We study the existential closures of several propositional languages L considered recently as target languages for knowledge compilation (KC), namely the incomplete fragments KROM-C, HORN-C, K/H-C, renH-C, AFF, and the corresponding disjunction closures KROM-C[V], HORN-C[V], K/H-C[V], renH-C[V], and AFF[V]. We analyze the queries, transformations, expressiveness and succinctness of the resulting languages L[∃] in order to locate them in the KC map. As a by-product, we also address several issues concerning disjunction closures that were left open so far. From our investigation, the language HORN - C[V, ∃] (where disjunctions and existential quantifications can be applied to Horn CNF formulae) appears as an interesting target language for the KC purpose, challenging the influential DNNF languages.
A Model of Extended, Semisystematic Visual Search

Objective: A model of semisystematic search was sought that could account for both memory retrieval and other performance-shaping factors. Background: Visual search is an important aspect of many examination and monitoring tasks. As a result, visual search performance has been the topic of many empirical investigations. These investigations have reported that individual search performance depends on participant factors such as search behavior, which has motivated the development of models of visual search that incorporate this behavior. Search behavior ranges from random to strictly systematic; variation in behavior is commonly assumed to be caused by differences in memory retrieval and search strategy. Methods: This model ultimately took the form of a discrete-time nonstationary Markov process. Results: It yields both performance and process measures that include accuracy, time to perception, task time, and coverage while avoiding the statistical difficulties inherent to simulations. In particular, it was seen that as the search behavior becomes more systematic, expected coverage and accuracy increase while expected task time decreases. Conclusion: In addition to explaining these outcomes and their interrelationships from a theoretical standpoint, the model can predict these outcomes in practice to a certain extent as it can create an envelope defined by best- and worst-case search performance. Application: The model also has the capability of supporting assessment. That is, it can be used to assess the effectiveness of an individual's search performance, and to provide possible explanations for this performance, through the use of one or more of the output measures.
Alternative to the soft-agar assay that permits high-throughput drug and genetic screens for cellular transformation

Significance The paper describes an assay for cellular transformation that involves growth in low attachment (GILA). This assay is comparable to the gold-standard soft-agar assay, but it is much easier to perform and is suitable for high-throughput drug and genetic screens. We describe such screens for drugs and genes that selectively inhibit or increase transformation, but not proliferation. Such molecules are unlikely to be found through conventional drug screening. Lastly, we demonstrate the ability of Food and Drug Administration-approved noncancer drugs to selectively kill ovarian cancer cells derived from patients with chemotherapy-resistant disease, suggesting this approach may provide useful information for personalized cancer treatment. Colony formation in soft agar is the gold-standard assay for cellular transformation in vitro, but it is unsuited for high-throughput screening. Here, we describe an assay for cellular transformation that involves growth in low attachment (GILA) conditions and is strongly correlated with the soft-agar assay. Using GILA, we describe high-throughput screens for drugs and genes that selectively inhibit or increase transformation, but not proliferation. Such molecules are unlikely to be found through conventional drug screening, and they include kinase inhibitors and drugs for noncancer diseases. In addition to known oncogenes, the genetic screen identifies genes that contribute to cellular transformation. Lastly, we demonstrate the ability of Food and Drug Administration-approved noncancer drugs to selectively kill ovarian cancer cells derived from patients with chemotherapy-resistant disease, suggesting this approach may provide useful information for personalized cancer treatment.
Nup192p Is a Conserved Nucleoporin with a Preferential Location at the Inner Site of the Nuclear Membrane*

Human Nup93, the homologue of yeast Nic96p, is associated with a 205-kDa protein whose intracellular location and function is unknown. We show here that the yeast open reading frame YJL039c, which is homologous to this human p205, encodes the so far largest yeast nucleoporin. Accordingly, green fluorescent protein (GFP)-tagged YJL039c was localized to the nuclear pores and therefore named Nup192p. Affinity purification of ProtA-Nic96p from glutaraldehyde-fixed spheroplasts reveals association with Nup192p.NUP192 is essential for cell growth. A temperature-sensitive mutant nup192–15 is neither impaired in nuclear import of a SV40 nuclear localization sequence-containing reporter protein nor in mRNA export, but association of Nup49-GFP with nuclear pores is inhibited at the non-permissive temperature. By immunoelectron microscopy, Nup192p-ProtA is seen at the inner site of the nuclear pores, at a distance of 60 ± 15 nm from the central plane of the pore. This suggests that Nup192p is an evolutionarily conserved structural component of the nuclear pore complex with a preferential location at the inner site of the nuclear membrane.
Surface Pollen Distribution from Akhnoor of Jammu District (Jammu and Kashmir), India: Implications for the Interpretation of Fossil Pollen Records

ABSTRACT The present study aims to document modern pollen assemblages and compare them with the extant vegetation, through palynological analysis of 40 modern moss cushions, from the Akhnoor sector of Jammu District (Jammu and Kashmir), India. The study revealed that the pollen of Pinus sp. (average 62%) dominates the pollen assemblages. The over-representation of Pinus pollen could be attributed to its high pollen productivity and excellent pollen dispersal capacity. However, other conifers (needle-leaved taxa) as well as broad-leaved taxa, with a few exceptions, are either sporadically recorded or remain palynologically silent (present in the extant vegetation but absent in the recovered pollen assemblages). This discrepancy could be owing to their long-distance transport by wind and/or water from the upland areas/the higher reaches of the Himalaya. Tubuliflorae, Cerealia and other cultural pollen taxa, and Poaceae, are well to poorly represented in the pollen assemblages. The associates of sub-tropical deciduous forests are poorly represented in the pollen spectra because they are not wind pollinated nor are they high pollen producers. The extant vegetation of the sampling location in Akhnoor of Jammu province plays a pivotal role in the present study, which has important implications for the interpretation of vegetation dynamics and associated climate change during the Holocene on the Indian subcontinent.
Ischemic Preconditioning Potentiates the Protective Effect of Stem Cells through Secretion of Exosomes by Targeting Mecp2 via miR-22

Mesenchymal stem cells (MSCs) have potential application for the treatment of ischemic heart diseases. Besides differentiation properties, MSCs protect ischemic cardiomyocytes by secretion of paracrine factors. In this study, we found exosomes enriched with miR-22 were secreted by MSCs following ischemic preconditioning (ExoIPC) and mobilized to cardiomyocytes where they reduced their apoptosis due to ischemia. Interestingly, by time-lapse imaging, we for the first time captured the dynamic shedding of miR-22 loaded exosomes from cytosol to extracellular space. Furthermore, the anti-apoptotic effect of miR-22 was mediated by direct targeting of methyl CpG binding protein 2 (Mecp2). In vivo data showed that delivery of ExoIPC significantly reduced cardiac fibrosis. Our data identified a significant benefit of ExoIPC for the treatment of cardiac diseases by targeting Mecp2 via miR-22.
Muscle-based skeletal bipedal locomotion using neural evolution

The developmental of bipedal walkers has long been a very important problem in the fields of robotics and computer simulation. In this work we propose using evolutionary methods and muscle based control to evolve bipedal walkers. We present an efficient method for evolving walking controller, which are used by a robot to walk large distances. Our approach mimics both the human limb control mechanism and the human learning process to create natural walking patterns and provides valuable insight into the learning process.
The New Issues Puzzle: Testing the Investment-Based Explanation

An investment factor, long in low-investment stocks and short in high-investment stocks, helps explain the new issues puzzle. Adding the investment factor into standard factor regressions reduces the SEO underperformance by about 75%, the IPO underperformance by 80%, the underperformance following convertible debt offerings by 50%, and Daniel and Titman's (2006) composite issuance effect by 40%. The reason is that issuers invest more than nonissuers, and the investment factor earns a significantly positive average return of 0.57% per month. The Author 2007. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org. , Oxford University Press.
Computing Cut-Based Hierarchical Decompositions in Almost Linear Time

We present a fast construction algorithm for the hierarchical tree decompositions that lie at the heart of oblivious routing strategies and that form the basis for approximation and online algorithms for various cut problems in graphs. Given an undirected graph G = (V, E, c) with edge capacities, we compute a single tree T = (VT, ET, cT), where the leaf nodes of T correspond to nodes in G, such that the tree approximates the cut-structure of G up to a factor of O(log4 n). The best existing construction by Harrelson, Hildrum, and Rao [12] just guarantees a polynomial running time but offers a better approximation guarantee of O(log2 n log log n). Phrasing our results in terms of vertex sparsifiers, we obtain the following: For a graph G = (V, E) with a subset S of terminals, we compute a tree T with at most 2|S| vertices (and the leafs of T correspond to nodes in S) such that T is a flow-sparsifier for S in G with quality O(log2 n log2 k), where |V| = n and |S| = k. The running time is O(polylog n · T(m, 1/log3n)) where T(m, e) is the time for computing an approximate maxflow in a graph with m edges. The latter is almost linear due to the recent results of Sherman [23] and Kelner et al. [13].
Laparoscopic surgery for endometriosis: How often do we need to re-operate?

Summary This study aimed to examine the rate of re-operation in women with endometriosis over a 10-year period. This was a retrospective study set in a university hospital in the UK. Notes of all women diagnosed with endometriosis were reviewed and data entered on a standard proforma. A total of 486 out of 988 procedures were for treatment of endometriosis. Some 240 (49%) had pelvic pain and 246 (51%) had subfertility. The mean age of those women who had a re-operation was lower than those who did not have any further operations. Using logistic regression, three factors were found to be the most important factors influencing the likelihood of women having re-operation – in decreasing order of importance, these factors were: (1) age, (2) pregnancy achievement and (3) improvement of symptoms. Re-operation occurred in 51% of our study population, the information may be useful for guidance of our patients.
Risk of having BRCA1 mutation in high‐risk women with triple‐negative breast cancer: a meta‐analysis

Testing for BRCA1 mutation has important clinical implications such as identifying risk of second primary cancers and risk of cancer in the family. This study seeks to quantify the risk of having BRCA1 mutation in female breast cancer patients with triple‐negative phenotype compared with those with other phenotypes. We undertook a search of MEDLINE and EMBASE databases for relevant studies through 10 May 2013. Outcomes were calculated and reported as risk ratio and risk difference. 12 studies comprising 2533 breast cancer patients were included in the analysis. It was found that almost all eligible studies were performed on high‐risk population with breast cancer. By analyzing the incidence rates of BRCA1 mutation in patients with triple‐negative breast cancer (TNBC) and non‐TNBC, our meta‐analysis provides a relative risk of 5.65 [95% confidence interval (CI), 4.15–7.69] and risk difference of 0.22 (95% CI, 0.15–0.29). This implies that, in selected population with high‐risk features, women with TNBC are approximately five and a half times more likely to have BRCA1 mutation compared with non‐TNBC phenotype, and approximately two in nine women with TNBC harbor BRCA1 mutation. Triple‐negative phenotype significantly increases the risk of having BRCA1 mutation in high‐risk breast cancer patients compared with non‐TNBC.
A DC Programming Approach for Sparse Eigenvalue Problem

We investigate the sparse eigenvalue problem which arises in various fields such as machine learning and statistics. Unlike standard approaches relying on approximation of the l0-norm, we work with an equivalent reformulation of the problem at hand as a DC program. Our starting point is the eigenvalue problem to which a constraint for sparsity requirement is added. The obtained problem is first formulated as a mixed integer program, and exact penalty techniques are used to equivalently transform the resulting problem into a DC program, whose solution is assumed by a customized DCA. Computational results for sparse principal component analysis are reported, which show the usefulness of our approach that compares favourably with some related standard methods using approximation of the l0-norm.
Analysis of postoperative morbidity and mortality following surgery for gastric cancer. Surgeon volume as the most significant prognostic factor

Introduction Surgical resection is the only potentially curative modality for gastric cancer and it is associated with substantial morbidity and mortality. Aim To determine risk factors for postoperative morbidity and mortality following major surgery for gastric cancer. Material and methods Between 1.08. 2006 and 30.11. 2014 in the Department of Oncological Surgery of Gdynia Oncology Centre 162 patients underwent gastric resection for adenocarcinoma. All procedures were performed by 13 surgeons. Five of them performed at least two gastrectomies per year (n = 106). The remaining 56 resections were done by eight surgeons with annual volume lower than two. Perioperative mortality was defined as every in-hospital death and death within 30 days after surgery. Causes of perioperative deaths were the matter of in-depth analysis. Results Overall morbidity was 23.5%, including 4.3% rate of proximal anastomosis leak. Mortality rate was 4.3%. Morbidity and mortality were not dependent on: age, gender, body mass index, tumour location, extent of surgery, splenectomy performance, or pTNM stage. The rates of morbidity (50% vs. 21.3%) and mortality (16.7% vs. 3.3%) were significantly higher in cases of tumour infiltration to adjacent organs (pT4b). Perioperative morbidity and mortality were 37.5% and 8.9% for surgeons performing less than two gastrectomies per year and 16% and 0.9% for surgeons performing more than two resections annually. The differences were statistically significant (p = 0.002, p = 0.003). Conclusions Annual surgeon case load and adjacent organ infiltration (pT4b) were significant risk factors for morbidity and mortality following major surgery for gastric cancer. The most common complications leading to perioperative death were cardiac failure and proximal anastomosis leak.
On-Bottom Stability Analysis of Cylinders under Tsunami-Like Solitary Waves

A two-dimensional (2D) laboratory investigation on the horizontal and vertical hydrodynamic forces induced by tsunami-like solitary waves on horizontal circular cylinders placed on a rigid sea bed is presented. A series of 30 physical model tests was conducted in the wave channel of the University of Calabria in which a rigid circular cylinder was equipped with 12 pressure transducers placed along its external surface to determine the wave loads, with three wave gauges to record the surface elevation. The observed experimental range was characterized by the prevalence of the inertia component for the horizontal forces and of the lift component for the vertical ones. On the basis of the performance of several time-domain methods, the wave loads and the undisturbed velocity and acceleration derived from the surface elevation of the cylinder section were used to calculate the drag, lift, and horizontal and vertical inertia coefficients in the practical Morison and transverse semi-empirical equations.
Outer-membrane PapC molecular usher discriminately recognizes periplasmic chaperone-pilus subunit complexes.

P pili are highly ordered composite structures consisting of thin fibrillar tips joined end-to-end to rigid helical rods. The production of these virulence-associated structures requires a periplasmic chaperone (PapD) and an outer membrane protein (PapC) that is the prototype member of a newly recognized class of proteins that we have named "molecular ushers. " Two in vitro assays showed that the preassembly complexes that PapD forms with the three most distal tip fibrillar proteins (PapG, PapF, and PapE) bound to PapC. The relative affinity of each complex for PapC was found to correlate with the final position of the subunit type in the tip fibrillum. In contrast, the complexes PapD forms with the major component of the pilus rod, PapA, or the pilus rod initiating protein, PapK, did not recognize PapC. The in vitro data argue that differential targeting of chaperone-subunit complexes to PapC may be part of a mechanism to ensure the correctly ordered assembly of adhesive composite pili.
Detection for binary transmission in a mixture of Gaussian noise and impulsive noise modeled as an alpha-stable process

The impact of nonGaussian impulsive noise combined with Gaussian noise on the performance of the binary transmission is analyzed. The impulsive noise is modeled as an alpha-stable process. The probability of error for optimum, linear and nonlinear receivers is derived. The proposed nonlinear detectors show substantial improvements in performance compared to linear ones. The obtained results will be useful in performance evaluation of digital communication links subject to Gaussian and impulsive noises. <<ETX>>
RATM: Recurrent Attentive Tracking Model

We present an attention-based modular neural framework for computer vision. The framework uses a soft attention mechanism allowing models to be trained with gradient descent. It consists of three modules: a recurrent attention module controlling where to look in an image or video frame, a feature-extraction module providing a representation of what is seen, and an objective module formalizing why the model learns its attentive behavior. The attention module allows the model to focus computation on task-related information in the input. We apply the framework to several object tracking tasks and explore various design choices. We experiment with three data sets, bouncing ball, moving digits and the real-world KTH data set. The proposed RATM performs well on all three tasks and can generalize to related but previously unseen sequences from a challenging tracking data set.