Miracle-dz/UniFAR-FTUs huggingface dataset:
Short-Term Changes in Two Tropical Coastal Lagoons: Effects of Sandbar Openings on Fish Assemblages

ABSTRACT Camara, E.M. ; Caramaschi, É. P.; Di Dario, F. , and Petry, A.C. , 2018. Short-term changes in two tropical coastal lagoons: Effects of sandbar openings on fish assemblages. Sandbar openings (SBOs) are among the largest possible disturbances in coastal lagoons. This study investigated the mechanisms of the responses of fish assemblages to short-term environmental changes resulting from several SBOs during 1 year in two coastal lagoons in southeastern Brazil. Lagoons were sampled monthly in sites closer to, and more distant from, the sandbars. A principal component analysis summarized limnological differences between periods of contact and isolation from the sea, and site- and lagoon-based variation partitioning and independent redundancy analyses (RDAs) quantified the unique and shared effects of limnology, space, and period on species and groups of species (marine, estuarine, and freshwater). Limnological differences between periods were associated with a higher marine influence during SBOs and an increasingly eutrophic state influenced by the lagoon and days of isolation. Limnology explained most of the variance in composition and abundance of species, and large fractions were shared with, or explained exclusively by, lagoons and distance of sites from the sandbar. The responses of groups of species were less evident in lagoon-based analyses and more associated with trophic state, most likely because of the short intervals between SBOs, which reduced temporal differences in the marine influence. Responses at the group level were more relevant in site-based analyses, given the predominance of species based on their tolerances or affinities in sites with different salinities. Therefore, the responses of groups of species to limnological changes associated with the features of lagoons and sites (e.g., morphometry, human impacts, and freshwater inflow) determined the effects of SBOs on the fish assemblages.
Spectrum estimation with Gaussian mixture particle filter

Based on the idea of using the finite Gaussian mixture model to approach a complex probability distribution, a spectrum estimation algorithm using Gaussian mixture particle filter is proposed in this paper for non-stationary signals. In order to balance the accuracy and the dynamic performance, a revised time-varying autoregressive model is presented combining with Gaussian mixture particle filter, which can estimate the frequency directly and quite reduce the computation cost. Experimental result from the recordings of underwater voice shows that, the proposed method has great performance for non-stationary signals with frequency steps.
Dependence Potential of Propofol: Behavioral Pharmacology in Rodents

Propofol is an anesthetic commonly used to provide sedation or to induce and maintain an anesthetic stated. However, there are reports which indicate propofol may cause psychological dependence or be abused. In the present study, we used various behavioral tests including climbing test, jumping test, conditioned place preference, and self-administration test to assess the dependence potential and abuse liability of propofol compared to a positive control (methamphetamine) or a negative control (saline or intralipid). Among the tests, the conditioned place preference test was conducted with a biased method, and the selfadministration test was performed under a fixed ratio (FR) 1 schedule, 1 h per session. No difference was found in the climbing test and jumping test, but propofol (30 mg/kg, i.p.) increased the rewarding effect in the conditioned place preference test, and it showed a positive reinforcing effect compared to the vehicle. These results indicate that propofol tends to show psychological dependence rather than physical dependence, and it seems not to be related with dopaminergic system.
Operads and knot spaces

Let Em denote the space of embeddings of the interval I = [? 1,1] in the cube Im with endpoints and tangent vectors at those endpoints fixed on opposite faces of the cube, equipped with a homotopy through immersions to the unknot; see Definition 5.1. By Proposition 5.17, Em is homotopy equivalent to Emb(I,Im) x i? lmm(l, Im). In [28], McClure and Smith define a cosimplicial object O* associated to an operad with multiplication 0, whose homotopy invariant totalization we denote Tot(? #); see Definition 2.17 and Definition 2.5 below. Let /Cm denote the rath Kontsevich operad, introduced in [22], whose entries are compactified configuration spaces and which is weakly equivalent to the little ra-disks operad [37]; see Definition 4.1 and Theorem 4.5.
Effect of data quality on estimates of farm infectiousness trends in the UK 2001 foot-and-mouth disease epidemic

Most of the mathematical models that were developed to study the UK 2001 foot-and-mouth disease epidemic assumed that the infectiousness of infected premises was constant over their infectious periods. However, there is some controversy over whether this assumption is appropriate. Uncertainty about which farm infected which in 2001 means that the only method to determine if there were trends in farm infectiousness is the fitting of mechanistic mathematical models to the epidemic data. The parameter values that are estimated using this technique, however, may be influenced by missing and inaccurate data. In particular to the UK 2001 epidemic, this includes unreported infectives, inaccurate farm infection dates and unknown farm latent periods. Here, we show that such data degradation prevents successful determination of trends in farm infectiousness.
GPFinder: Tracking the invisible in Android malware

Malicious Android applications use clever techniques to hide their real intents from the user and avoid detection by security tools. They resort to code obfuscation and dynamic loading, or wait for special events on the system like reboot or WiFi activation. Therefore, promising approaches aim to locate, study and execute specific parts of Android applications in order to monitor for suspicious behavior. They rely on Control Flow Graphs (CFGs) to obtain execution paths towards sensitive codes. We claim here that these CFGs are incomplete because they do not take into consideration implicit control flow calls, i.e., those that occur when the Android framework calls a method implemented in the application space. This article proposes a practical tool, GPFinder, exposing execution paths towards any piece of code considered as suspicious. GPFinder takes the Android framework into account and considers explicit and implicit control flow calls to build CFGs. Using GPFinder, we give global characteristics of application CFGs by studying a dataset of 14,224 malware and 2,311 goodware samples. We evaluate that 72.69% of the analyzed malicious samples have at least one suspicious method reachable only through implicit calls.
Functions of Arginase Isoforms in Macrophage Inflammatory Responses: Impact on Cardiovascular Diseases and Metabolic Disorders

Macrophages play a paramount role in immunity and inflammation-associated diseases, including infections, cardiovascular diseases, obesity-associated metabolic imbalances, and cancer. Compelling evidence from studies of recent years demonstrates that macrophages are heterogeneous and undergo heterogeneous phenotypic changes in response to microenvironmental stimuli. The M1 killer type response and the M2 repair type response are best known, and are two extreme examples. Among other markers, inducible nitric oxide synthase and type-I arginase (Arg-I), the enzymes that are involved in l-arginine/nitric oxide (NO) metabolism, are associated with the M1 and M2 phenotype, respectively, and therefore widely used as the markers for characterization of the two macrophage phenotypes. There is also a type-II arginase (Arg-II), which is expressed in macrophages and prevalently viewed as having the same function as Arg-I in the cells. In contrast to Arg-I, little information on the role of Arg-II in macrophage inflammatory responses is available. Emerging evidence, however, suggests that differential roles of Arg-I and Arg-II in regulating macrophage functions. In this article, we will review recent developments on the functional roles of the two arginase isoforms in regulation of macrophage inflammatory responses by focusing on their impact on the pathogenesis of cardiovascular diseases and metabolic disorders.
General deletion lemmas via the Harris inequality

We present a new approach to the deletion method that is based on the Harris inequality. We obtain deletion lemmas that are similar in spirit to those of Rodl and Rucinski, but hold for arbitrary decreasing properties. That is, we show that under appropriate conditions, with very high (‘Janson-like’) probability it suffices to delete a small fraction of the edges of a random graph Gn,p to ensure that a given decreasing property holds. We also obtain stronger results for decreasing properties that only depend on edges involved in copies of some given graph H. As an application of our methods, we present a new deletion lemma that concerns local subgraph counts, i.e., the number of copies of H each edge or vertex of Gn,p is contained in.
On Low-Space Differentially Private Low-rank Factorization in the Spectral Norm

Low-rank factorization is used in many areas of computer science where one performs spectral analysis on large sensitive data stored in the form of matrices. In this paper, we study differentially private low-rank factorization of a matrix with respect to the spectral norm in the turnstile update model. In this problem, given an input matrix $\mathbf{A} \in \mathbb{R}^{m \times n}$ updated in the turnstile manner and a target rank $k$, the goal is to find two rank-$k$ orthogonal matrices $\mathbf{U}_k \in \mathbb{R}^{m \times k}$ and $\mathbf{V}_k \in \mathbb{R}^{n \times k}$, and one positive semidefinite diagonal matrix $\textbf{\Sigma}_k \in \mathbb{R}^{k \times k}$ such that $\mathbf{A} \approx \mathbf{U}_k \textbf{\Sigma}_k \mathbf{V}_k^\mathsf{T}$ with respect to the spectral norm. Our main contributions are two computationally efficient and sub-linear space algorithms for computing a differentially private low-rank factorization. We consider two levels of privacy. In the first level of privacy, we consider two matrices neighboring if their difference has a Frobenius norm at most $1$. In the second level of privacy, we consider two matrices as neighboring if their difference can be represented as an outer product of two unit vectors. Both these privacy levels are stronger than those studied in the earlier papers such as Dwork {\it et al.} (STOC 2014), Hardt and Roth (STOC 2013), and Hardt and Price (NIPS 2014). As a corollary to our results, we get non-private algorithms that compute low-rank factorization in the turnstile update model with respect to the spectral norm. We note that, prior to this work, no algorithm that outputs low-rank factorization with respect to the spectral norm in the turnstile update model was known; i.e., our algorithm gives the first non-private low-rank factorization with respect to the spectral norm in the turnstile update mode.
Case-Based Collective Classification

Abstract : This is the first paper on textual case-based reasoning to employ collective classification, a methodology for simultaneously classifying related cases that has consistently attained higher accuracies than standard classification approaches when cases are related. Thus far, case-based classifiers have not been examined for their use in collective classification. We introduce Case-Based Collective Classification "CBCC" and report that it outperforms a traditional case-based classifier on three tasks. We also address issues of case representation and feature weight learning for CBCC. In particular, we describe a cross-validation approach for tuning feature weights and show that it increases CBCC accuracy on these tasks.
Probing the Binding Entropy of Ligand–Protein Interactions by NMR

The draft human genome sequence has revealed about 30 000–40 000 protein-coding genes in the human genome— roughly twice as many as in a fly. Thus, it follows that the complexity of higher organisms lies in part in the interactions between gene products. Despite their fundamental importance, it is perhaps therefore surprising that our knowledge of the driving forces that govern biomolecular interactions is very rudimentary. For example, our ability to predict protein folds from sequence (an intramolecular-recognition problem) is currently a distant dream, as is our ability to design novel leaddrug candidates from high-resolution structures of target biomolecules.
TCP symbiosis: congestion control mechanisms of TCP based on Lotka-Volterra competition model

In this paper, we propose TCP Symbiosis, which has a robust, self-adaptive and scalable congestion control mechanism for TCP. Our method is quite different from existing approaches. We change the window size of a TCP connection in response to information of the physical and available bandwidths of the end-to-end network path. The bandwidth information is obtained by an inline network measurement technique we have previously developed. Using the bandwidth information we can resolve the inherent problems in existing AIMD/MIMD-based algorithms such as periodic packet loss and unfairness caused by the difference in RTT. We borrow algorithms from biophysics to update the window size: the logistic growth model and the Lotka-Volterra competition model. This is because these models describe changes in the population size of a species that depends on the living environment. The population of a species can be viewed as the window size of a TCP connection and the living environment as the bandwidth of the bottleneck link. The greatest advantage of using these models is that we can refer to previous discussions and results for various characteristics of the mathematical models, including scalability, convergence, fairness and stability in these models. Through mathematical analysis and extensive simulation experiments, we compare the proposed mechanism with traditional TCP Reno, HighSpeed TCP, Scalable TCP and FAST TCP, and exhibit its effectiveness in terms of scalability to the network bandwidth and delay, convergence time, fairness among competing connections, and stability.
Methods of Qualitative Analysis in the Problem of Rigid Body Motion in Medium

The present paper describes the application of methods of qualitative analysis in the classical problem of rigid body motion in medium. Three particular problems are used as examples: bolides flight, galloping of aeroelastic constructions, and behavior of horizontal axis wind turbine. It is shown that this approach reveals the general properties of the behavior of objects studied, such as impossibility of translational deceleration of bolides and the presence of hysteretic phenomena in the operation of wind turbines.
Consistency of Nearest Neighbor Methods

In this lecture we return to the study of consistency properties of learning algorithms, where we will be interested in the question of whether the generalization error of the function learned by an algorithm approaches the Bayes error in the limit of infinite data. In particular, we will consider consistency properties of the simple k-nearest neighbor (k-NN) classification algorithm (in the next lecture, we will investigate consistency properties of algorithms such as SVMs and AdaBoost that effectively minimize a convex upper bound on the zero-one loss). We start with a brief review of statistical consistency and related results.
Upgrading Pacemaker Patients with Right Ventricular Apical Pacing to Right Ventricular Septal Pacing Improves Left Ventricular Performance and Functional Capacity

Background: Right ventricular (RV) apical pacing results in abnormal left ventricular (LV) electrical and mechanical activation and is associated with an increased risk of developing heart failure. Chronic RV septal pacing has been shown to be superior to RV apical pacing in newly implanted patients. However, whether RV septal pacing can reverse deleterious effects of RV apical pacing remain unclear.
Classification and Learning-to-rank Approaches for Cross-Device Matching at CIKM Cup 2016

In this paper, we propose two methods for tackling the problem of cross-device matching for online advertising at CIKM Cup 2016. The first method considers the matching problem as a binary classification task and solve it by utilizing ensemble learning techniques. The second method defines the matching problem as a ranking task and effectively solve it with using learning-to-rank algorithms. The results show that the proposed methods obtain promising results, in which the ranking-based method outperforms the classification-based method for the task.
Advances in acid anhydride induced occupational asthma

The acid anhydrides have been signal occupational agents for study because of their inherent and complex biological activity and the wide range of associated occupational airway disease that is manifest in exposed workers in a variety of occupational settings. This year in review has shed light on many of the complexities of anhydride exposure, biologic reactivity and airway disease.
Maternal height and child mortality in 42 developing countries

Previous research reports mixed results about the association between maternal height and child mortality. Some studies suggest that the negative association might be stronger in contexts with fewer resources. This hypothesis has yet not been tested in a cross‐nationally comparative design. We use data on 307,223 children born to 194,835 women in 444 districts of 42 developing countries to estimate the association between maternal height and child mortality and test whether this association is modified by indicators at the level of the household (like sex, age and twin status of the child and socio‐economic characteristics of the mother and her partner), district (regional level of development, public health facilities and female occupational attainment) and country (GDP per capita). We find a robust negative effect of logged maternal height on child mortality. The effect of maternal health is strongest for women with least education and is more important in the first year after birth and for twin births. The indicators of development at the district and country level do not modify the effect of maternal height. Am. J. Hum. Biol. 2009. © 2008 Wiley‐Liss, Inc.
GPE Promotes the Proliferation and Migration of Mouse Embryonic Neural Stem Cells and Their Progeny In Vitro

This study was designed to investigate a possible role of the N-terminal tripeptide of insulin-like growth factor-1 (IGF-I), Gly-Pro-Glu (GPE), physiologically generated in neurons following IGF-I-specific cleavage, in promoting neural regeneration after an injury. Primary cultures of mouse neural stem cells (NSCs), obtained from 13.5 Days post-conception (dpc) mouse embryos, were challenged with either GPE, growth hormone (GH), or GPE + GH and the effects on cell proliferation, migration, and survival were evaluated both under basal conditions and in response to a wound healing assay. The cellular pathways activated by GPE were also investigated by using specific chemical inhibitors. The results of the study indicate that GPE treatment promotes the proliferation and the migration of neural stem cells in vitro through a mechanism that involves the activation of extracellular signal-regulated kinase (ERK) and phosphoinositide 3-kinase PI3K-Akt pathways. Intriguingly, both GPE effects and the signaling pathways activated were similar to those observed after GH treatment. Based upon the results obtained from this study, GPE, as well as GH, may be useful in promoting neural protection and/or regeneration after an injury.
Optimal design of simultaneous source encoding

A broad range of parameter estimation problems involve the collection of an excessively large number of observations N. Typically, each such observation involves excitation of the domain through injection of energy at some predefined sites and recording of the response of the domain at another set of locations. It has been observed that similar results can often be obtained by considering a far smaller number K of multiple linear superpositions of experiments with . This allows the construction of the solution to the inverse problem in time instead of . Given these considerations it should not be necessary to perform all the N experiments but only a much smaller number of K experiments with simultaneous sources in superpositions with certain weights. Devising such procedure would results in a drastic reduction in acquisition time. The question we attempt to rigorously investigate in this work is: what are the optimal weights? We formulate the problem as an optimal experimental design problem and show that by leveraging techniques from this field an answer is readily available. Designing optimal experiments requires some statistical framework and therefore the statistical framework that one chooses to work with plays a major role in the selection of the weights.
Assessment of Heavy Metal Fluxes and Radiation Exposure due to NORM in the Extraction and Processing of Coltan Ores in Selected Areas of Rwanda

The present study quantifies heavy metal fluxes and radiation exposure due to Naturally Occurring Radioactive Materials (NORM) in the extraction and processing o f the ColumbiteTantalite (Coltan) mineral in Muhanga, Ruli and Ngoma areas o f Rwanda. Heavy metal in samples of Coltan ore, mine sediments and soil from the three areas were analyzed using the Energy Dispersive X-Ray Fluorescence (EDXRF) spectrometry. Activity concentrations o f primordial radionuclides 40K, 238U and 232Th in samples of Coltan, sediments and soil were determined by Hyper Pure Germanium (HPGe)-based gamma-ray spectrometry. Multivariate chemometrics techniques, Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were used to explore the salient relationships among measured data (heavy metals, radionuclides). The heavy metals were categorized into three classes which may be interpreted as, elements normally associated with coltan; radioactive minerals; and heavy metal toxic elements. Multivariate chemometrics techniques enabled to classify the samples into three coltan types namely; processed coltan, extracted (or unprocessed) coltan, mine sediments and control soil samples. Processed coltan is purified coltan which is obtained after separating soil and coltan by using water. Extracted coltan is the raw ore taken immediately from soil; it is a mixture of coltan and soil. Sediments are the wastes produced after removing coltan. Control soil sample is the soil which was taken from an area within the vicinity but outside the mining site. Coltan ore were also classified according to their origin using principal component analysis (PCA). The result o f elemental analysis showed that the most abundant elements were I antalum (1 a), Niobium (Nb) and Tin (Sn). These elements are normally associated with Coltan. The highest