Miracle-dz/UniFAR-FTUs huggingface dataset:
Particulate Matter-Induced Lung Inflammation Increases Systemic Levels of PAI-1 and Activates Coagulation Through Distinct Mechanisms

Background Exposure of human populations to ambient particulate matter (PM) air pollution significantly contributes to the mortality attributable to ischemic cardiovascular events. We reported that mice treated with intratracheally instilled PM develop a prothrombotic state that requires the release of IL-6 by alveolar macrophages. We sought to determine whether exposure of mice to PM increases the levels of PAI-1, a major regulator of thrombolysis, via a similar or distinct mechanism. Methods and Principal Findings Adult, male C57BL/6 and IL-6 knock out (IL-6−/−) mice were exposed to either concentrated ambient PM less than 2.5 µm (CAPs) or filtered air 8 hours daily for 3 days or were exposed to either urban particulate matter or PBS via intratracheal instillation and examined 24 hours later. Exposure to CAPs or urban PM resulted in the IL-6 dependent activation of coagulation in the lung and systemically. PAI-1 mRNA and protein levels were higher in the lung and adipose tissue of mice treated with CAPs or PM compared with filtered air or PBS controls. The increase in PAI-1 was similar in wild-type and IL-6−/− mice but was absent in mice treated with etanercept, a TNF-α inhibitor. Treatment with etanercept did not prevent the PM-induced tendency toward thrombus formation. Conclusions Mice exposed to inhaled PM exhibited a TNF-α-dependent increase in PAI-1 and an IL-6-dependent activation of coagulation. These results suggest that multiple mechanisms link PM-induced lung inflammation with the development of a prothrombotic state.
A lattice algorithm for optimal phase unwrapping in noise

Use of the phase of a signal to measure distance carries an inherent ambiguity. The problem is typically addressed by the use of several different frequencies and the Chinese Remainder Theorem or lattice methods, but these methods result in computational complexity issues. The difficulties are increased by the presence of noise. This paper presents a lattice-based algorithm to resolve phase ambiguity more efficiently and under more relaxed constraints than existing approaches. Simulations are presented to illustrate the performance of the proposed algorithm and compared with existing methods.
Filopodial Adhesion Does Not Predict Growth Cone Steering Events In Vivo

Migration of growth cones is in part mediated by adhesive interactions between filopodia and the extracellular environment, transmitting forces and signals necessary for pathfinding. To elucidate the role of substrate adhesivity in growth cone pathfinding, we developed an in vivo assay for measuring filopodial–substrate adhesivity using the well-characterized Ti pioneer neuron pathway of the embryonic grasshopper limb. Using time-lapse imaging and a combination of rhodamine-phalloidin injections and DiI labeling, we demonstrate that the filopodial retraction rate after treatment with cytochalasin D or elastase reflects the degree of filopodial–substrate adhesivity. Measurements of filopodial retraction rates along regions of known differing substrate adhesivities confirmed the use of this assay to examine filopodial–substrate adhesion duringin vivo pathfinding events. We analyzed 359 filopodia from 22 Ti growth cones and found that there is no difference between the retraction rates of filopodia extending toward the correct target (on-axis) and filopodia extending away from the correct target (off-axis). These results indicate on-axis and off-axis filopodia have similar substrate adherence. Interestingly, we observed a 300% increase in the extension rates of on-axis filopodia during Ti growth cone turning events. Therefore, in addition to providing filopodia with important guidance information, regional cues are capable of modulating the filopodial extension rate. The homogeneity in filopodial retraction rates, even among these turning growth cones in which differential adhesivity might be expected to be greatest, strongly establishes that differential adhesion does not govern Ti pioneer neuron migration rate or pathfinding. We propose that the presence of local differences in receptor-mediated second messenger cascades and the resulting assembly of force-generating machinery may underlie the ability of filopodial contacts to regulate growth cone steering in vivo.
MODEN : Multi-Robot , Obstacle-Driven Elastic Network Path Planning

We propose an efficient and elegant heuristic algorithm for path planning that makes use of an elastic network. The network initializes as a simple straight path between the initial and goal positions. It then randomly samples the space around the areas of this initial path that lie inside obstacles, “pushing” the network away from the obstacles and thus determining an obstacle-free path. The fundamental algorithm, dubbed as ODEN (Obstacle-Driven Elastic Network), is an improved extension of the path-planning algorithm proposed in [1]. We also propose a multi-robot variation of ODEN, that we have named MODEN (Multi-robot ODEN). We illustrate the application of both algorithms in numerous test environments and discuss its applicability to general path-planning problems.
Transition from drift to interchange instabilities in an open magnetic field line configuration

The transition from a regime dominated by drift instabilities to a regime dominated by pure interchange instabilities is investigated and characterized in the simple magnetized toroidal device TORPEX [TORoidal Plasma EXperiment, A. Fasoli et al., Phys. of Plasmas 13, 055906 (2006)]. The magnetic field lines are helical, with a dominant toroidal component and a smaller vertical component. Instabilities with a drift character are observed in the favorable curvature region, on the high field side with respect to the maximum of the background density profile. For a limited range of values of the vertical field they coexist with interchange instabilities in the unfavorable curvature region, on the plasma low field side. With increasing vertical magnetic field magnitude, a gradual transition between the two regimes is observed on the low field side, controlled by the value of the field line connection length. The observed transition follows the predictions of a two-fluid linear model.
A bi-criteria approach for Steiner's tree problems in communication networks

In this paper, an improved version of a previously proposed heuristic that finds 'good' compromise solutions for a bi-criteria Steiner trees problem is presented. This bi-criteria formulation of the Steiner's tree problem is well suited for application in telecommunication networks whenever it is important to find the minimum amount of resources to connect a given subset of network nodes. In fact there are some (additive) metrics that may not lead to a tree with the minimum number of Steiner nodes when used in the single criterion Steiner's tree problem. In this case it can be advantageous to consider also the minimisation of the hop count as a second criteria in the problem formulation. The performance of the new heuristic is evaluated and compared with the previous version by recurring to reference networks from a library of Steiner's tree problems.
Development and Validation of the Bicultural Youth Acculturation Questionnaire

Objectives Acculturation is a multidimensional process involving changes in behaviour and beliefs. Questionnaires developed to measure acculturation are typically designed for specific ethnic populations and adult experiences. This study developed a questionnaire that measures acculturation among ethnically diverse populations of youth that can be included as a module in population surveys. Methods Questionnaires measuring acculturation in youth were identified in the literature. The importance of items from the existing questionnaires was determined using a Delphi process and this informed the development of our questionnaire. The questionnaire was then pilot tested using a sample of 248 Canadians aged 18–25 via an online system. Participants identified as East and South East Asian (27.8%), South Asian (17.7%) and Black (13.7%). The majority were 1st (33.5%) or 2nd generation immigrants (52.0%). After redundant items were eliminated, exploratory factor analysis grouped items into domains, and, for each domain, internal consistency, and convergent validity with immigrant generation then age at immigration estimated. A subset of participants re-completed the questionnaire for reliability estimation. Results The literature review yielded 117 articles that used 13 questionnaires with a total of 440 questions. The Delphi process reduced these to 32 questions. Pilot testing occurred in 248 Canadians aged 18–25. Following item reduction, 16 questions in three domains remained: dominant culture, heritage language, and heritage culture. All had good internal consistency (Cronbach’s alphas > .75). The mean dominant domain score increased with immigrant generation (1st generation: 3.69 (95% CI: 3.49–3.89), 2nd: 4.13 (4.00–4.26), 3rd: 4.40 (4.19–4.61)), and mean heritage language score was higher among those who immigrated after age 12 than before (p = .0001), indicative of convergent validity. Conclusions This Bicultural Youth Acculturation Questionnaire has demonstrated validity. It can be incorporated into population health surveys to elucidate the impact of acculturation on health outcomes among bicultural youth.
Dynamic Assortment Planning

We investigate optimal assortment planning strategies for a retailer with limited shelf space. The retailer can choose among basic and fashion items with low and high risk (and return) respectively. Our motivation is in the apparel industry, and we explicitly model the vogue as a stochastic process that the retailer tries to follow. The objective is to maximize the long‐term value of the retail business by dynamically adjusting the menu of products on display.
What else is the evolution of PSO telling us

Evolutionary algorithms (EAs) can be used in order to design particle swarm optimization (PSO) algorithms that work, in some cases, considerably better than the human-designed ones. By analyzing the evolutionary process of designing PSO algorithms, we can identify different swarm phenomena (such as patterns or rules) that can give us deep insights about the swarm behavior. The rules that have been observed can help us design better PSO algorithms for optimization. We investigate and analyze swarm phenomena by looking into the process of evolving PSO algorithms. Several test problems have been analyzed in the experiments and interesting facts can be inferred from the strategy evolution process (the particle quality could influence the update order, some particles are updated more frequently than others, the initial swarm size is not always optimal).
Efficient gateway synthesis from formal specifications

We present an efficient procedure converters from formal specifications. David M. Kristol David Lee Arun N. Netravali Krishan K. Sabnani AT&T Bell Laboratories Murray Hill, NJ 07974 that computes protocol This urocedure has a polynomial number of computation steps; on the other hand, all other procedures reported in the literature require an exponential number of computation steps. A major step in our procedure is the computation of the largest common subset of services. This largest common subset is used to compute the converter. Conditions under which the converter can be stateless are also described. As an example, we compute a converter for interconnecting a half-duplex protocol with a full-duplex protocol from their formal specifications.
Memory Expansion Technology (MXT): Software support and performance

A novel memory subsystem called Memory Expansion Technology (MXT) has been built for fast hardware compression of main-memory content. This allows a memory expansion to present a "real" memory larger than the physically available memory. This paper provides an overview of the memory-compression architecture, its OS support under Linux and Windows®, and an analysis of the performance impact of memory compression. Results show that the hardware compression of main memory has a negligible penalty compared to an uncompressed main memory, and for memory-starved applications it increases performance significantly. We also show that the memory content of an application can usually be compressed by a factor of 2.
A novel strategy for speaker verification based on SVM classification of pairs of speech sequences

We introduce a novel strategy for speaker verification based on the conception of a classifier which is independent of the target speaker, as opposed to traditional systems where the classifier is always target dependent. The basic principle is to build a system that decides whether two sequences were pronounced by the same speaker. In our view, this system is aimed to complement traditional ones. We borrow techniques from the speaker segmentation area, namely the Bayesian Information Criterion (BIC), to conceive a kernel between pairs of sequences. We then use this kernel to implement our new system in an SVM scheme. We present experiments on NIST SRE data using the Biosecure project protocol. The individual performance of the new system is poor as compared to the baseline UBM-GMM and the GLDS-SVM. However, as expected, the fusion leads to better performances.
InVis: An Interactive Visualization Tool for Exploring Interaction Networks

We introduce InVis, a novel visualization technique and tool for exploring, navigating, and understanding user interaction data. InVis creates a interaction network from student-interaction data extracted from large numbers of students using educational systems, and enables instructors to make new insights and discoveries about student learning. Here we present our novel interaction network model and InVis tool. We also demonstrate that InVis is an effective tool for providing instructors with useful and meaningful insights to how students solve problems.
A Scenario Planning Framework for Australian Landscapes

Future landscapes are the result of many different processes, some controllable and some not, some predictable and others less so. This lack of predictability and controllability are real challenges to landscape planners and modellers alike who are interested in medium to long-term futures. Scenarios are a standard tool for dealing with and describing variation in the future, however it is important for a scenario planning system to be able to explicitly deal with different types of drivers and uncertainty. Models used to visualise alternative futures are frequently detailed and complicated – while necessary this can present a considerable barrier to policy makers and stakeholders who own the issues under investigation. This paper describes a framework for developing alternative landscape scenarios with the aim of helping policy makers design evidence-based, long-term policy in the face of different sources of uncertainty. The framework combines the scenario planning approach of Schwartz and others and analytically simulation modelling. This framework gives control and ownership of the driver identification and scenario crafting process to the owners of the issues, without them having to be fully conversant with detailed analytical models. Using this framework alternative scenarios are the product of uncertain drivers, processes that will affect the future but that we can not predict; and policy responses, the different management choices that are made in response to the changing world. The process can be used to help choose between alternative polices, or to design policy that is robust under alternative future operating environments.
A Method for Bayesian Meta-Reasoning Applied to Real-Time Systems Using Multiple Characterization

As Bayesian networks are applied to more complex and realistic real-world applications, the development of more efficient inference algorithms working under real-time constraints is increasingly important. In this paper, we present a method for meta-reasoning in Bayesian networks, which may be applied by real-time probabilistic systems that adopt anytime algorithms for approximate propagation of evidence and combine multiple simulation schemes. The proposed method is based on multiple characterizations of Bayesian networks to predict the algorithm that will provide the lower approximate error in future inferences, considering time restrictions. This method applies multiple regression analysis to create the conditional performance profiles of approximate inference algorithms. The analysis is based on experimental results to estimates of propositions that were used to create the utility curves of Gibbs Sampling and Stratified Simulation algorithms. These algorithms belong to stochastic and deterministic sampling methods, respectively. Some experimental analyses compare multiple and simple characterization of Bayesian networks for meta-reasoning and show better results in simulation errors when multiple characterizations are used.
Approximate coverage in wireless sensor networks

Recent advances in microelectronic technology have made it possible to construct compact and inexpensive wireless sensors. Sensor networks have received significant attention due to their potential applications from civil to military domains. Since sensors in sensor networks are equipped with energy-limited batteries, energy conservation in such networks is of paramount importance in order to prolong the network lifetime. Sensing coverage and sensor connectivity in sensor networks are two fundamental issues, which have been extensively addressed in the literature, and most existing work on sensing coverage has focused on the (connected) full coverage problem that aims to cover the entire monitored region using the minimum number of sensors. However, in some application scenarios, full coverage is either impossible or unnecessary and a partial coverage with a certain degree guarantee is acceptable. In this paper, we study the connected coverage problem with a given coverage guarantee. We first introduce the partial coverage concept and analyze its properties for the first time in order to prolong the network lifetime. Due to NP-hardness of the concerned problem, we then present a heuristic algorithm which takes into account the partial coverage and sensor connectivity simultaneously. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithm
Molecular signature induced by RNASET2, a tumor antagonizing gene, in ovarian cancer cells

Using the Hey3Met2 human ovarian cancer cell line, we previously found the RNASET2 gene to possess a remarkable in vivo tumor suppressor activity, although no in vitro features such as inhibition of cell proliferation, clonogenic potential, impaired growth in soft agar and increase in apoptotic rate could be detected. This is reminiscent of the behavior of genes belonging to the class of tumor antagonizing genes (TAG) which act mainly within the context of the microenvironment. Here we present transcriptional profiles analysis which indicates that investigations of the mechanisms of TAG biological functions require a comparison between the in vitro and in vivo expression patterns. Indeed several genes displaying a biological function potentially related to tumor suppression could not be validated by subsequent in vivo expression analysis. On the other hand the fact that we could find congruency for three genes both in vivo and in vitro adds a warning to a too much stringent categorization of this class of genes which relies on the sensitivity of the methodological approaches.
Reproductive endocrinology GnRH-agonist versus GnRH-antagonist IVF cycles : is the reproductive outcome affected by the incidence of progesterone elevation on the day of HCG triggering ? A randomized prospective study †

E.G. Papanikolaou1,2,3,*, G. Pados1,3, G. Grimbizis1,3, E. Bili1,3, L. Kyriazi3, N.P. Polyzos4, P. Humaidan5, H. Tournaye4, and B. Tarlatzis1,3 Assisted Reproduction Unit, Biogenesis, Thessaloniki, Greece Human Reproduction & Genetics Foundation, Andrianoupoloeos 6, Kalamaria, 55133 Thessaloniki, Greece Unit of Assisted Reproduction, 1st Obstetrics and Gynecology Department, Aristotle University, Thessaloniki, Greece Center for Reproductive Medicine, UZ VUB, Brussels, Belgium Assisted Reproduction Unit, Odense University, Odense, Denmark
Antiviral Activity of Nucleoside Analogues against Norovirus

Background Norovirus (NoV) is the leading cause of epidemic gastroenteritis worldwide. The lack of a cell culture has significantly hampered the development of effective therapies against human NoV. Clinically approved nucleoside and non-nucleoside analogues have been used successfully against RNA viruses. Methods In this study, we evaluated the efficacy of four nucleoside analogues (2′-C-MeC, 2′-F-2′-C-MeC, β-D-N(4)-hydroxycytidine [NHC] and lamivudine) on Norwalk virus (NV) RNA levels and protein expression in NV replicon-harbouring cells (HG23 cells), and their efficacy in blocking murine norovirus (MNV) replication in RAW 264.7 cells. Results 2′-C-MeC and 2′-F-2′-C-MeC reduced MNV RNA levels and infectivity in RAW 264.7 cells in a concentration- and time-dependent manner. The median effective concentrations (EC50) of 2′-C-MeC and 2′-F-2′-C-MeC were 6.9 μM and 12.7 μM, respectively. 2′-C-MeC, 2′-F-2′-C-MeC and NHC reduced NV RNA levels and protein expression in HG23 cells. For the NV replicon, the EC50 of 2′-C-MeC (1.3 μM) was comparable to the antiviral activity of NHC (1.5 μM) and twofold more potent than 2′-F-2′-C-MeC (3.2 μM). The combination of 2′-C-MeC/ ribavirin resulted in modest synergistic activity, whereas NHC/ribavirin was antagonistic for NV replication in HG23 cells. Conclusions The antiviral activity of 2′-C-MeC against strains of two different NoV genogroups and the low EC50 suggest that this nucleoside analogue may be effective against the more prevalent GII NoVs. In the absence of a vaccine, antiviral agents could be an effective intervention to control the spread of human NoV in populations at a high risk for NoV disease.
Design analysis and testing of Wilkinson Power Divider with harmonics suppression using Defected Ground Structures

Wilkinson Power Divider is a passive component used in wireless communication as a key device, for dividing RF / microwave power. Defected Ground Structures (DGS) have been developed to improve characteristics of microwave devices & circuits, due to its band-stop property. In this paper, a new effective technique of suppression of second & third harmonic in Wilkinson Power Divider is proposed by using two square headed dumb-bell shaped DGS. The electromagnetic simulation results obtained by using IE3D software shows fairly good agreement with the results gained by applying basic transmission line theory & with the testing results found after implementation of the proposed device. As per the testing results, the error in shift in the frequency where it has maximum return loss is 6.8%. This is due to fabrication tolerances & high-frequency parasitic effect.
Multimodal diff-hash

Many applications require comparing multimodal data with different structure and dimensionality that cannot be compared directly. Recently, there has been increasing interest in methods for learning and efficiently representing such multimodal similarity. In this paper, we present a simple algorithm for multimodal similarity-preserving hashing, trying to map multimodal data into the Hamming space while preserving the intra- and inter-modal similarities. We show that our method significantly outperforms the state-of-the-art method in the field.