Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hybrid Evolutionary Algorithm Based on HSA and CLS for Multi-objective Community Detection in Complex Networks

Detecting community structure is crucial for uncovering the links between structures and functions in complex networks. Most of contemporary community detection algorithms employ single optimization criteria (e.g., modularity), which may have fundamental disadvantages. This paper considers the community detection process as a Multi-Objective optimization Problem (MOP). To solve the community detection problem this study used modified harmony search algorithm (HAS), the original HAS often converges to local optima which is a disadvantage with this method. To avoid this shortcoming the HAS was combined with a Chaotic Local Search (CLS). In the proposed algorithm an external repository considered to save non-dominated solutions found during the search process and a fuzzy clustering technique was used to control the size of the repository. The experiments in synthetic and real networks show that the proposed multi-objective community detection algorithm is able to discover more accurate community structures.
Optimal cloud resource allocation by means of the analytic hierarchy process

Improve resource provisioning for applications hosted in the cloud is a major research challenge. This is because is necessary to address two conflicting objectives: meet customer requirements; and save money. As there is a delay, which can take minutes, between the request for a new resource and it be ready for use, it is necessary to predict the future demand for each time interval. However, there is not a prediction model that is appropriate in all cases. To resolve this problem, it is proposed in this paper, the combination of different forecasting models by the analytic hierarchy process. In this way, we intend to create a generic solution, able to optimize the allocation of resources to several applications types, with different demand types. The results obtained by simulation show that our proposal achieves this goal.
Evaluation of a single radio rural mesh network in South Africa

This paper evaluates the ability of a low cost wireless mesh network to provide Internet access to a rural area in South Africa with limited broadband connectivity. The network was installed in a mountainous area with a wide range of distances between nodes ranging from long range 5.5 km links to short hops between buildings of only 30 to 50 m. Due to this combination of distances, a mix of unplanned node placement with omni-directional antennas and planned nodes using directional antennas was used. The current network consists of 9 nodes spread over an area of about 15 square kilometers. There is electricity at all the sites but power outages are common, occurring at average intervals of one outage in 7 days, lasting between 3 and 24 hours. The network provides a good service to the satellite based Internet with throughput rates ranging between 300 kbps for 4 hops and 11000 kbps for 1 hop and an average throughput rate of 2324 kbps. The paper evaluates the throughput and delay performance of the OLSR routing protocol being used in the mesh network as well as giving an overview of usage patterns and social behavioural patterns of the users. The users range from first time users in poorer areas of the network to fairly accustomed Internet users in wealthier farming areas.
Molecular Characterization of a Novel Big Defensin from Clam Venerupis philippinarum

Antimicrobial peptides (AMPs) are important mediators of the primary defense mechanism against microbial invasion. In the present study, a big defensin was identified from Venerupis philippinarum haemocytes (denoted as VpBD) by RACE and EST approaches. The VpBD cDNA contained an open reading frame (ORF) of 285 bp encoding a polypeptide of 94 amino acids. The deduce amino acid sequence of VpBD shared the common features of big defensin including disulfide array organization and helix structure, indicating that VpBD should be a new member of the big defensin family. The mRNA transcript of VpBD was up-regulated significantly during the first 24 hr after Vibrio anguillarum challenge, which was 7.4-fold increase compared to that of the control group. Then the expression decreased gradually from 24 hr to 96 hr, and the lowest expression level was detected at 96 hr post-infection, which was still 3.9-fold higher than that of control. The mature peptide of VpBD was recombined in Escherichia coli and purified for minimum inhibitory concentration (MIC) determination. The rVpBD displayed broad-spectrum inhibitory activity towards all tested bacteria with the highest activity against Staphyloccocus aureus and Pseudomonas putida. These results indicated that VpBD was involved in the host immune response against bacterial infection and might contribute to the clearance of invading bacteria.
An efficient admission control for IEEE 802.11 networks based on throughput analyses of (Un)saturated channel

This paper presents a novel analytical model and an efficient admission control algorithm for IEEE 802.11 DCF access mechanism. In contrast to the previous approaches that only analyzed the saturated status of IEEE 802.11 networks, both saturated and unsaturated states of network are analyzed and the impacts of error-frame rate and retransmission limit are also taken into account based on an improved Markov chain model. Taking the throughput difference between saturated and unsaturated states as the residual bandwidth, an efficient admission control algorithm is designed to utilize the network resources effectively. Extensive simulation data demonstrate that the admission control algorithm is efficient and can make the effective utilization of network resources
Gravitational waves from self-ordering scalar fields

Gravitational waves were copiously produced in the early Universe whenever the processes taking place were sufficiently violent. The spectra of several of these gravitational wave backgrounds on subhorizon scales have been extensively studied in the literature. In this paper we analyze the shape and amplitude of the gravitational wave spectrum on scales which are superhorizon at the time of production. Such gravitational waves are expected from the self ordering of randomly oriented scalar fields which can be present during a thermal phase transition or during preheating after hybrid inflation. We find that, if the gravitational wave source acts only during a small fraction of the Hubble time, the gravitational wave spectrum at frequencies lower than the expansion rate at the time of production behaves as $\Omega_{\rm GW}(f) \propto f^3$ with an amplitude much too small to be observable by gravitational wave observatories like LIGO, LISA or BBO. On the other hand, if the source is active for a much longer time, until a given mode which is initially superhorizon ($k\eta_* \ll 1$), enters the horizon, for $k\eta \gtrsim 1$, we find that the gravitational wave energy density is frequency independent, i.e. scale invariant. Moreover, its amplitude for a GUT scale scenario turns out to be within the range and sensitivity of BBO and marginally detectable by LIGO and LISA. This new gravitational wave background can compete with the one generated during inflation, and distinguishing both may require extra information.
Semantically Rich API for In-database Data Manipulation in Main-memory ERP Systems

: Assuming the feasibility of main-memory database management systems, the current research aims at de-signing a new type of data manipulation API, called Business Object Query Language (BOQL), speciﬁcally tailored for in-database data manipulation in main-memory ERP systems. The paper contributes the concept of business object virtualization and describes a query processor that takes advantage of this concept. The ﬁrst serves as a means of grouping raw memory-resident data into high-level data structures, while the second exposes a ﬂexible query-like API to manipulate the high-level data structures. Special effort has been dedicated to integrating the API into C++ programming language.
A square-root sampling approach to fast histogram-based search

We present an efficient pixel-sampling technique for histogram-based search. Given a template image as a query, a typical histogram-based algorithm aims to find the location of the target in another large test image, by evaluating a similarity measure for comparing the feature histogram of the template with that of each possible subwindow in the test image. The computational cost would be high if each subwindow needs to compute its histogram and evaluate the similarity measure. In this paper, we adopt the probability-product kernels as the similarity measures, and show that the computation of histograms and the evaluation of the kernel-based similarities can be integrated through a sampling approach. Specifically, we present a square-root sampling method to avoid the computation of histograms, and meanwhile, reduce the number of pixels required for evaluating the similarity measure. The proposed approximation algorithm is time- and memory-efficient. The time complexity of computing the similarity for each subwindow is O(1). The memory requirement of our algorithm is not in proportion to the size of the template or the number of histogram bins, which allows the use of more distinctive image representations for better search accuracy.
A fast growth distance algorithm for incremental motions

A fast algorithm is presented for computing the growth distance between a pair of convex objects in three-dimensional space. The growth distance is a measure of both separation and penetration between objects. When the objects are polytopes represented by their faces, the growth distance is determined by the solution of a linear program (LP). The article presents an approach to the solution of the LP. Under appropriate conditions, the computational time is very small and does not depend on the total number of faces of the objects. Compared to the existing algorithm for growth distance, there is a time reduction of several orders of magnitude. This increase in speed is achieved by exploiting two resources: adjacency of the object faces and the computational coherence induced by incremental motions of the objects, Computational experiments show that the performance of the algorithm is in the same range as the fastest codes for the computation of the Euclidean separation distance.
Model driven development of secure XML databases

In this paper, we propose a methodological approach for the model driven development of secure XML databases (DB). This proposal is within the framework of MIDAS, a model driven methodology for the development of Web Information Systems based on the Model Driven Architecture (MDA) proposed by the Object Management Group (OMG) [20]. The XML DB development process in MIDAS proposes using the data conceptual model as a Platform Independent Model (PIM) and the XML Schema model as a Platform Specific Model (PSM), with both of these represented in UML. In this work, such models will be modified, so as to be able to add security aspects if the stored information is considered as critical. On the one hand, the use of a UML extension to incorporate security aspects at the conceptual level of secure DB development (PIM) is proposed; on the other, the previously-defined XML schema profile will be modified, the purpose being to incorporate security aspects at the logical level of the secure XML DB development (PSM). In addition to all this, the semi-automatic mappings from PIM to PSM for secure XML DB will be defined.
Epidural Brain Metastases in a Patient with Early Onset Pancreatic Cancer: A Case Report and Literature Review

We present a case of early onset pancreatic cancer related extra-axial brain metastases. A 46-year-old Caucasian non-Jewish nonobese male with a history of PC diagnosed 3 months ago with metastases to the liver, omentum, malignant ascites, and a history of a pulmonary embolism was admitted to the hospital because of a new onset headache, nausea, and vomiting which started 2 days prior to the encounter. Brain MRI was ordered, which showed acute bihemispheric subdural hematomas and left hemispheric extra-axial heterogeneously enhancing lesions consisting with metastatic disease. The patient was started on ondansentron, metoclopramide, and dexamethasone. The cranial irradiation was started, and the patient's headache and nausea significantly improved. There are only 9 published reports of extra-axial brain metastases related to the pancreatic cancer, whereas our paper is the first such case reported on a patient with epidural metastases and early onset pancreatic cancer.
Eurodéputés et représentation des territoires

Les eurodeputes se positionnent a la jonction de plusieurs territoires (europeen, national, et local). Pour consolider les positions qu'ils occupent dans l'espace politique et reduire les incertitudes quant a leur reelection, ils investissent le role d'intermediaire entre divers espaces. D'un cote, l'action des eurodeputes consiste a defendre des enjeux specifiques du territoire au sein de l'assemblee. D'un autre cote, des biens politiques europeens sont egalement echanges entre les eurodeputes et les citoyens ou les elus locaux. Amenes a creer des liens ascendants et descendants entre l'espace europeen et les espaces locaux, les deputes europeens participent ainsi a l'emboitement des territoires et a la constitution progressive d'un espace de transactions politiques.
Los espectadores y espectadoras de la ciberviolencia de género

La finalidad del estudio fue analizar el papel que tienen las y los jovenes cuando son observadores de ciberviolencias de genero, identificando que caracteristicas de ellos/as pueden aumentar la probabilidad de actuar con complicidad con el ciberagresor, y cuales de actuar con ayuda a la victima. Se aplico una encuesta mediante cuestionario on-line a una muestra de 4536 adolescentes de 3o y 4o de Ensenanza Secundaria Obligatoria procedentes de las comunidades de Cataluna, Aragon, Galicia, Andalucia, Islas Baleares y Canarias. El analisis, mediante la tecnica de los arboles de decision, revelo que las variables que tienen una mayor probabilidad de influir en las actuaciones de los observadores/as de ciberviolencia son el sexo, tener caracteristicas de vulnerabilidad, la edad, haber sufrido acoso y la percepcion de los riesgos de las redes sociales en internet. Las chicas tienen mayor probabilidad de actuar como defensoras de la victima, probabilidad que aumenta cuando sienten que tienen alguna caracteristica que las hace vulnerables ante las ciberviolencias. A mas edad, mayor probabilidad de tener el perfil de complicidad con el agresor, probabilidad que aumenta siendo chicos que se sienten vulnerables, que han sufrido ciberacoso en alguna ocasion, y que perciben los riesgos que tienen las redes sociales en internet. Consecuentemente, son los que tienen menor probabilidad de actuar defendiendo a la victima. Los resultados obtenidos alientan la necesidad de emprender acciones educativas que ayuden a paliar el fenomeno de la ciberviolencia de genero, enfatizandose la idea de que no deben estar centradas en los dos polos del fenomeno, agresor y victima, sino incluir tambien a las personas observadoras. Las acciones tambien deberian orientarse a la formacion del profesorado, pues los docentes son un elemento principal para llevar a cabo cambios en el entorno educativo, entorno en el que comienza y se expande la ciberviolencia de genero.
Extending the Linear Mixed Effects Model Worked Examples

Example Description 1 Tracer lot stability data { classical linear mixed eeects model 2 Pill dissolution data { classical linear mixed eeects model 3 Rat pup weight data { classical linear mixed eeects model 4 CD4 trajectories { linear mixed model with nonconstant intra-subject variance 5 Soybean growth study { nonlinear mixed model with nonconstant within-plot variance 6 Population PK study of phenobarbital { nonlinear mixed model with sparse data 7 Tracer lot stability data { Bayesian analysis 8 Pill dissolution data { Bayesian analysis
Towards An Algorithms Ontology Cluster: for Modular Code Reuse and Polyglot Programming

Code reuse is rarely practiced and polyglot programming an informal discipline. This paper proposes the use of ontologies in tackling these issues, seeing as ontologies inherently encourage reuse and are often used as bridges between languages. This paper also reviews existing research and literature in the fields of ontologies in software engineering, code reuse and polyglot programming.
Rationality in Algebras with a Series Operation

We consider the notion of rationality in algebras with a designated binary associative operation called the series operation, or the sequential product. We define automata operating in these algebras and rational expressions matching their expressive power, and we show that this expressive power equals that of algebraic recognizability. The framework which we consider encompasses both the free semigroup and the term algebras and the restriction of our results to these special cases coincides exactly with the classical results on recognizability (Kleene, Myhill, and Nerode for word languages, and Thatcher and Wright for term languages). Next we consider the behavior of the automata and the rational expression which we introduce when conditions such as associativity and commutativity are imposed on the term operations. We also characterize algebraically, syntactically and automata-theoretically the languages which have a bound on the number of nested occurrences of certain designated term operations. Finally, we consider the applications of our results to the languages of series-parallel labelled posets. 2001 Elsevier Science
Two extensions for fitting discrete time term structure models with normally distributed factors

This paper provides extensions to procedures for the implementation of two well‐known term structure models. In the first part, a misleading implication given in two textbooks concerning the ability to fit a Ho–Lee type term structure tree through trial and error is corrected, and it is shown that the tree can be fitted precisely with a simple and easily programmable formula. In the second part, a previously published result that obtains the drift for a single‐factor discrete time Heath–Jarrow–Morton model is extended to a multi‐factor world. In both cases numerical examples are provided.
Correcting Preposition Errors in Learner English Using Error Case Frames and Feedback Messages

This paper presents a novel framework called error case frames for correcting preposition errors. They are case frames specially designed for describing and correcting preposition errors. Their most distinct advantage is that they can correct errors with feedback messages explaining why the preposition is erroneous. This paper proposes a method for automatically generating them by comparing learner and native corpora. Experiments show (i) automatically generated error case frames achieve a performance comparable to conventional methods; (ii) error case frames are intuitively interpretable and manually modifiable to improve them; (iii) feedback messages provided by error case frames are effective in language learning assistance. Considering these advantages and the fact that it has been difficult to provide feedback messages by automatically generated rules, error case frames will likely be one of the major approaches for preposition error correction.
A restrained-parameter thermal-factor refinement procedure

Retention of known geometry, with regard to mean atomic positions, has proved useful in the refinement of macromolecules. In structures with a paucity of diffraction data and large displacements of the atoms from their mean positions, it is also of value to restrain the thermal factors to be consistent with known stereochemistry. This paper presents a technique for accomplishing this by restraining the variances of the interatomic distributions (which are functions of the mean atomic positions and the thermal parameters) to suitably small values. This procedure allows meaningful anisotropic refinement of macromolecules to be carried out with low-resolution diffraction data. Anisotropic thermal parameters obtained in this way should prove useful in understanding the dynamics of the biological functions of macromolecules.
A 3 D Keypoint Detector based on Biologically Motivated Bottom-Up Saliency Map

We present a new method for the detection of 3D keypoints on point clouds and we perform benchmarking between each pair of 3D keypoint detector and 3D descriptor to evaluate their performance on object and category recognition. Our keypoint detector is inspired by the behavior and neural architecture of the primate visual system. The 3D keypoints are extracted based on a bottom-up 3D saliency map, that is, a map that encodes the saliency of objects in the visual environment. The saliency map is determined by computing conspicuity maps of the orientation, intensity and color information in a bottom-up and in a purely stimulusdriven manner. Finally, the focus of attention (or “keypoint location") is sequentially directed to the most salient points in this map. The main conclusions are: with a similar average number of keypoints, our 3D keypoint detector outperforms the other 3D keypoint detectors evaluated in the category and object recognition experiments.
Multiple evidence fusion based information diffusion model for social network

Study on diffusion behaviors, such as contagion of virus, adoption of production, and information propagation, is one of the hottest topics of social network research. The conventional models usually focus on a particular factor that influences the contagion process. A novel model of diffusion based on multiple behavior evidence fusion is proposed on the analysis of prevalent social network data set, which can simulate the information propagation process with the fitting goodness of 0.79. In this model, impact factors, i.e. the influence between neighborhood, and the activity of user, are taken into account together and fused into combined evidence mass function, which can be used to infer users' forwarding behavior by D-S theory reasoning. Series of experiments tested on the published Enron email data set show that the multiple evidence fusion based diffusion model (MEFDM) is reasonable and feasible in demonstrating the cascading of information in the social network.
Deficiency of filamin A in endothelial cells impairs left ventricular remodelling after myocardial infarction.

AIMS Actin-binding protein filamin A (FLNA) regulates signal transduction important for cell locomotion, but the role of FLNA after myocardial infarction (MI) has not been explored. The main purpose of this study was to determine the impact of endothelial deletion of FLNA on post-MI remodelling of the left ventricle (LV). METHODS AND RESULTS We found that FLNA is expressed in human and mouse endothelial cells (ECs) during MI. To determine the biological significance of endothelial expression of FLNA, we used mice that are deficient for endothelial FLNA by cross-breeding adult mice expressing floxed Flna (Flna(o/fl)) with mice expressing Cre under the vascular endothelial-specific cadherin promoter (VECadCre+). Male Flna(o/fl) and Flna(o/fl)/VECadCre+ mice were subjected to permanent coronary artery ligation to induce MI. Flna(o/fl)/VECadCre+ mice that were deficient for endothelial FLNA exhibited larger and thinner LV with impaired cardiac function as well as elevated plasma levels of NT-proBNP and decreased secretion of VEGF-A. The number of capillary structures within the infarcted areas was reduced in Flna(o/fl)/VECadCre+ hearts. ECs silenced for Flna mRNA expression exhibited impaired tubular formation and migration, secreted less VEGF-A, and produced lower levels of phosphorylated AKT and ERK1/2 as well as active RAC1. CONCLUSION Deletion of FLNA in ECs aggravated MI-induced LV dysfunction and cardiac failure as a result of defective endothelial response and increased scar formation by impaired endothelial function and signalling.