Miracle-dz/UniFAR-FTUs huggingface dataset:
What ’ s love got to do with it ? Ontogenetic changes in drivers of dispersal in a marine ectoparasite

Sex-biased dispersal is common in nature and can influence the way in which organisms are distributed throughout the environment with consequences at the individual, population, community, and species level. Much of our understanding of what drives sex-biased dispersal stems from work on birds and mammals where dispersal tends to be female and male biased, respectively. Here, we draw on this large body of empirical and theoretical work on vertebrates to investigate what drives breeding dispersal in an ectoparasite, the salmon louse, Lepeophtheirus salmonis. We manipulated the density, sex, and developmental stage of lice on pairs of juvenile pink salmon (Oncorhynchus gorbuscha) hosts and show that the probability of leaving a host is density dependent at the preadult I stage and dependent on the presence of the opposite sex at preadult II and adult stages. Experiments in which louse movement was observed in groups of 25 individually infected hosts supported findings from individual experiments. Lice appeared to account for predation risk as they were 3 times more likely to disperse in the dark, when susceptibility to predation was low, than in the light. Our results support the hypothesis that asymmetry in reproductive investment shapes patterns of sex-biased dispersal and highlight the potential for drivers of dispersal to change with ontogeny. These findings are the first to establish what drives dispersal in the ecologically and economically important salmon louse and highlight the generality of the role mate competition plays in driving sex-biased dispersal across the animal kingdom.
Artificial neural network based radial bending characteristics of mixed-flow pump impeller

Impeller radial bending characteristic has applied to many type turbine machines except of pump. Specially, there is no news about application on the mixed-flow pump. In this study, an artificial neural network (ANN) was used for modeling the performance of mixed-flow pump impeller. Thirty seven results were used to train and test. Many patterns have been randomly selected and used as the test date. The main parameters for the experiments are the Gamma, Betal and Beta2. Gamma, Betal and Beta2 have been used as the input layer, and η has been used as the output layer. The best training algorithm and number of neurons were obtained. At last, a new type, high efficiency mixed-flow pump impeller can be designed.
Mutation at a Single Position in the V2 Domain of the HIV-1 Envelope Protein Confers Neutralization Sensitivity to a Highly Neutralization-Resistant Virus

ABSTRACT Understanding the determinants of neutralization sensitivity and resistance is important for the development of an effective human immunodeficiency virus type 1 (HIV-1) vaccine. In these studies, we have made use of the swarm of closely related envelope protein variants (quasispecies) from an extremely neutralization-resistant clinical isolate in order to identify mutations that conferred neutralization sensitivity to antibodies in sera from HIV-1-infected individuals. Here, we describe a virus with a rare mutation at position 179 in the V2 domain of gp120, where replacement of aspartic acid (D) by asparagine (N) converts a virus that is highly resistant to neutralization by multiple polyclonal and monoclonal antibodies, as well as antiviral entry inhibitors, to one that is sensitive to neutralization. Although the V2 domain sequence is highly variable, D at position 179 is highly conserved in HIV-1 and simian immunodeficiency virus (SIV) and is located within the LDI/V recognition motif of the recently described α4β7 receptor binding site. Our results suggest that the D179N mutation induces a conformational change that exposes epitopes in both the gp120 and the gp41 portions of the envelope protein, such as the CD4 binding site and the MPER, that are normally concealed by conformational masking. Our results suggest that D179 plays a central role in maintaining the conformation and infectivity of HIV-1 as well as mediating binding to α4β7.
WATER MANAGEMENT AND BIODIVERSITY : The opportunity cost of protecting biodiversity in a Mediterranean delta . DRAFT

In wetlands, hydrology is a driving factor in all ecological economic interactions. Any attempt at water management for human activities will alter the balance of these interactions, and may threaten sustainable use of wetland resources. The Camargue is an extensive area of wetland (80 000 ha) in the Rhône delta in the South of France, where hydrology has long been influenced by man. The interaction of freshwater introduced for human activities, as early as the XVIIth century, and salt water, has produced over the years a rich mosaic of habitats and high biological diversity. Over recent decades, however, water has been more intensively
Socialising Data with Google Fusion Tables

We describe the social features of Google Fusion Tables, a cloud-based data management service whose goal is to facilitate collaboration around data sets. The social features include the ability to specify attribution of data sets, a mechanism for conducting discussions on data (at ﬁne granularity, such as row, column or cell), the ability to merge tables that belong to different owners, and the ability to share speciﬁc queries and visualizations and embed them in other properties on the Web. We describe the rationale for designing these features and our experiences after our ﬁrst year of interacting with users
On the Effectiveness of Diffusive Content Caching in Content-Centric Networking

Recently, data-centric networking is getting increased attention. A representative example of data-centric networking is Content-Centric Networking (CCN), which routes packets within a network based on their content identifiers. In CCN, each CCN router on a network reuses data by caching relayed contents. Specifically, the CCN router caches a copy of the content in its buffer memory. However, in CCN, routers on the path from a user to the source cache contents. A CCN router cannot use contents cached by neighboring CCN routers unless the neighboring CCN routers are on the path to the source. In this paper, we propose Diffusive Content Caching (DCC), which improves the efficiency of buffer memory usage by advertising information of contents cached by a CCN router to neighboring CCN routers. Hence, with DCC, the CCN router can forward a request packet to any of neighboring CCN routers, which cache the corresponding contents using the standard CCN routing mechanism. We also evaluate the effectiveness of DCC by simulations. Our simulation results show that DCC reduces the average contents delivery time by approximately 8 % on average.
Testing Of Analog Systems Using Behavioral Models And Optimal Experimental Design Techniques

This paper describes a new CAD algorithm which performs automatic test pattern generation (ATPG) for a general class of analog systems, namely those circuits which can be efficiently modeled as an additive combination of user-defined basis functions. The algorithm is based on the statistical technique of I-optimal experimental design, in which test vectors are chosen to be maximally independent so that circuit performance will be characterized as accurately as possible in the presence of measurement noise and model inaccuracies. This technique allows analog systems to be characterized more accurately and more efficiently, thereby significantly reducing system test time and hence total manufacturing cost.
BTA, a novel reagent for DNA attachment on glass and efficient generation of solid-phase amplified DNA colonies

The tricarboxylate reagent benzene-1,3,5-triacetic acid (BTA) was used to attach 5′-aminated DNA primers and templates on an aminosilanized glass surface for subsequent generation of DNA colonies by in situ solid-phase amplification. We have characterized the derivatized surfaces for the chemical attachment of oligonucleotides and evaluate the properties relevant for the amplification process: surface density, thermal stability towards thermocycling, functionalization reproducibility and storage stability. The derivatization process, first developed for glass slides, was then adapted to microfabricated glass channels containing integrated fluidic connections. This implementation resulted in an important reduction of reaction times, consumption of reagents and process automation. Innovative analytical methods for the characterization of attached DNA were developed for assessing the surface immobilized DNA content after amplification. The results obtained showed that the BTA chemistry is compatible and suitable for forming highly dense arrays of DNA colonies with optimal surface coverage of about 10 million colonies/cm2 from the amplification of initial single-template DNA molecules immobilized. We also demonstrate that the dsDNA colonies generated can be quantitatively processed in situ by restriction enzymes digestion. DNA colonies generated using the BTA reagent can be used for further sequence analysis in an unprecedented parallel fashion for low-cost genomic studies.
Lactobacillus gasseri: effects on mouse intestinal flora enzyme activity and isoflavonoids in the caecum and plasma

The effects of Lactobacillus gasseri JCM 1131T on isoflavonoid levels within the caecum and plasma were assessed in adult mice. Male 5-week-old mice were fed an AIN 93M diet for 30 d. Two groups of mice were administered either L. gasseri JCM 1131T (the LGI group) or physiological saline solution (the control (CI) group) daily for 5 d before dissection. The plasma daidzein concentration was significantly higher in the LGI group, however, their plasma equol concentration was significantly less than in the CI group. The total amount of equol present as aglycone in the caecum was significantly greater in the CI group, but there was no significant difference in the total daidzein present as caecal aglycone. In an in vitro incubation of daidzin with the faecal flora of mice, the equol concentration was significantly higher in the CI group. The numbers of lactobacilli present were significantly higher in the LGI group. The present data suggest that the administration of L. gasseri is likely to influence the effect of isoflavonoids on the host via changes in the gastrointestinal environment.
An Operating Condition-Based Scheme to Alternate Between Control Strategies for Improved Steady-State and Transient Behavior

The control strategies that use modulation techniques have great acceptance in the current control of static power converters. Indeed, they offer a wide variety of alternatives to address the steady-state characteristics required by the system. Nevertheless, its computation and modulation delay negatively affects its dynamic performance. In order to improve the time response of the system, the modulator is avoided and the strategies of direct choice of the switching state have been presented. They can provide a very fast dynamic response; however, the absence of switching state sequences makes more complex the task of establishing specific switching features for improved steady-state performance. In this work, a control scheme that selects a specific control strategy according to the operating condition of the system is proposed. This allows using modulators to satisfy the switching characteristics required in steady-state and avoids its use when a rapid dynamic response is required. In addition, a soft transition method between the control strategies is presented to prevent unwanted behaviors when these are alternated. The proposed control scheme allows simplifying the design and keeps the main advantages of each selected strategy. To validate the scheme, experimental results are obtained for a control structure that alternates between a finite set model predictive control (direct type for rapid dynamic response) and a proportional integral (PI) control with sinusoidal pulse width modulation (SPWM) (modulated type for high steady-state performance).
The Mediating Relation between Symbolic and Nonsymbolic Foundations of Math Competence

This study investigated the relation between symbolic and nonsymbolic magnitude processing abilities with 2 standardized measures of math competence (WRAT Arithmetic and KeyMath Numeration) in 150 3rd- grade children (mean age 9.01 years). Participants compared sets of dots and pairs of Arabic digits with numerosities 1–9 for relative numerical magnitude. In line with previous studies, performance on both symbolic and nonsymbolic magnitude processing was related to math ability. Performance metrics combining reaction and accuracy, as well as weber fractions, were entered into mediation models with standardized math test scores. Results showed that symbolic magnitude processing ability fully mediates the relation between nonsymbolic magnitude processing and math ability, regardless of the performance metric or standardized test.
Association of type 3 protein kinase C with focal contacts in rat embryo fibroblasts

We have used immunocytofluorescence techniques to determine the subcellular distribution of the Ca2+, phospholipid-dependent protein kinase, protein kinase C (PKC). Using monoclonal antibodies that are specific for Type 3 (alpha) PKC, we have determined that there are least two pools of PKC in normal rat embryo fibroblasts (REF52 cells): diffuse cytoplasmic and fiber-associated. Extraction with chelators and detergent before fixing and staining removes the cytoplasmic PKC. The fiber-associated staining remains in these cytoskeleton preparations. The cytoskeleton Type 3 PKC staining closely resembles that of the focal contact protein vinculin and colocalizes with another focal contact protein, talin. Cytochalasin, but not colchicine, coordinately disrupts the staining pattern of vinculin and PKC. Activation of PKC by treatment with phorbol esters causes depolymerization of microfilaments and reorganization of vinculin staining. We propose that Type 3 PKC is a modulatory component of the focal contact and has a primary role in regulation of the association of microfilament bundles with the plasma membrane.
Hidden Markov Model based Recognition of Musical Pattern in South Indian Classical Music

Automatic recognition of musical patterns plays a crucial part in Musicological and Ethno musicological research and can become an indispensable tool for the search and comparison of music extracts within a large multimedia database. This paper finds an efficient method for recognizing isolated musical patterns in a monophonic environment, using Hidden Markov Model. Each pattern, to be recognized, is converted into a sequence of frequency jumps by means of a fundamental frequency tracking algorithm, followed by a quantizer. The resulting sequence of frequency jumps is presented to the input of the recognizer which use Hidden Markov Model. The main characteristic of Hidden Markov Model is that it utilizes the stochastic information from the musical frame to recognize the pattern. The methodology is tested in the context of South Indian Classical Music, which exhibits certain characteristics that make the classification task harder, when compared with Western musical tradition. Recognition of 100% has been obtained for the six typical music pattern used in practise. South Indian classical instrument, flute is used for the whole experiment.
Multi-agent reinfocement learning for stochastic power management in cognitive radio network

Frequency spectra are nowadays getting overcrowded because of increasing cell phone users. Cognitive radio network offers an alternative modality to utilize unused spectra efficiently among unlicensed users. This paper attempts to allocate transmission power among cognitive users in an efficient way without creating interference to the licensed users. We here adopt multi-agent reinforcement learning for cooperative power allocation in cognitive radio network. Multi-agent learning is here used to handle stochastic behavior of the environment. We use three mixed strategies (Correlated equilibrium) to control transmission power in multi-agent learning. After the learning algorithm converges, we obtain the optimum power level under different situations for subsequent use in power utilization during communication. Experimental results indicate that the proposed algorithm outperforms its classical counterparts by a significant margin.
Application-specific workload shaping in multimedia-enabled personal mobile devices

Today, most personal mobile devices (e.g., cell phones and PDAs) are multimedia-enabled and support a variety of concurrently running applications, such as audio/video players, word processors, and web browsers. Media-processing applications are often computationally expensive and most of these devices typically have 100--400-MHz processors. As a result, the user-perceived application response times are often poor when multiple applications are concurrently fired. In this paper, we show that by using application-specific dynamic buffering techniques, the workload of these applications can be suitably “shaped” to fit the available processor bandwidth. Our techniques are analogous to traffic shaping, which is widely used in communication networks to optimally utilize network bandwidth. Such shaping techniques have recently attracted a lot of attention in the context of embedded systems design (e.g., for dynamic voltage scaling). However, they have not been exploited for enhanced schedulability of multiple applications, as we do in this paper.
Using Random Forests for Network-based Anomaly detection at Active routers

Network intrusion detection systems (NIDSs) is one of the primary components in any network security infrastructure. Currently, many NIDSs that are developed are rule-based systems and their performances mainly depend on the rule sets. But rules formation becomes a tedious and rime consuming task due to the enormous amount of network traffic. This is overcome by using data mining techniques. These techniques build intrusion detection models adaptively. Random forests is an efficient data mining algorithm which can be used for network intrusion detection This can be used for real time intrusion detection. In this paper, we discuss the approaches for feature selection, and optimization of parameters of random forests, compare different models, and also discuss the other method for detecting the anomalies across active networks.
Apical and basolateral coated pits of MDCK cells differ in their rates of maturation into coated vesicles, but not in the ability to distinguish between mutant hemagglutinin proteins with different internalization signals

In polarized epithelial MDCK cells, all known endogenous endocytic receptors are found on the basolateral domain. The influenza virus hemagglutinin (HA) which is normally sorted to the apical plasma membrane, can be converted to a basolateral protein by specific mutations in its short cytoplasmic domain that also create internalization signals. For some of these mutations, sorting to the basolateral surface is incomplete, allowing internalization of two proteins that differ by a single amino acid of the internalization signal to be compared at both the apical and basolateral surfaces of MDCK cells. The rates of internalization of HA-Y543 and HA-Y543,R546 from the basolateral surface of polarized MDCK cells resembled those in nonpolarized cells, whereas their rates of internalization from the apical cell surface were fivefold slower. However, HA-Y543,R546 was internalized approximately threefold faster than HA-Y543 at both membrane domains, indicating that apical endocytic pits in polarized MDCK cells retained the ability to discriminate between different internalization signals. Slower internalization from the apical surface could not be explained by a limiting number of coated pits: apical membrane contained 0.7 as many coated pits per cell cross-section as did basolateral membranes. 10-14% of HA-Y543 at the apical surface of polarized MDCK cells was found in coated pits, a percentage not significantly different from that observed in apical coated pits of nonpolarized MDCK cells, where internalization was fivefold faster. Thus, there was no lack of binding sites for HA-Y543 in apical coated pits of polarized cells. However, at the apical surface many more shallow pits, and fewer deep, mature pits, were observed than were seen at the basolateral. These results suggest that the slower internalization at the apical surface is due to slower maturation of coated pits, and not to a difference in recognition of internalization signals.
Tsallis differential entropy and divergences derived from the generalized Shannon-Khinchin axioms

In discrete systems, Shannon entropy is well known to be characterized by the Shannon-Khinchin axioms. Recently, this set of axioms was generalized for Tsallis entropy, one-parameter generalization of Shannon entropy. In continuos systems, Shannon differential entropy has been introduced as a natural extension of the above Shannon entropy without using an axiomatic approach. We derive the generalized entropy function as a solution of the functional equation determined by the generalized Shannon additivity, one of the most important axiom of the generalized Shannon-Khinchin axioms for Tsallis entropy. This generalized entropy function naturally introduces Tsallis differential entropy and two Tsallis divergences. In particular, one (Csiszár type) of the divergences has almost the same form as the α-divergence in information geometry and the other the Bregman type divergence. Our results reveal that the generalized Shannon additivity representing a branch structure of a rooted tree plays an essential role in the determination of these entropies.
Side Channel Analysis of Hardware Trojan Based on Smooth Filtering Algorithm

Aimed at the problem of the noise in the side channel analysis (SCA) of hardware Trojan, a novel idea to develop an optimal algorithm model based on smooth filtering is discussed in this paper. To reduce the influence of the abnormal points on the curve, the idea uses the least square method to fit the original data curve. The approach is validated using power simulation with a 128-bit Advanced Encryption Standard (AES) cipher circuit and hardware Trojan circuit whose Trojan's area is 0.16%. The experiment shows that the impact of the noise on power is reduced effectively by using the proposed smooth filtering algorithm, especially for the small-area Trojan circuit.
Outage performance of two-way DF relaying systems with a new relay selection metric

This paper investigates a new constrained relay selection scheme for two-way relaying systems where two end terminals communicate simultaneously via a relay. The introduced technique is based on the maximization of the weighted sum rate of both users. To evaluate the performance of the proposed system, the outage probability is derived in a general case (where an arbitrary channel is considered), and then over independently but not necessarily identically distributed (i.n.i.d.) Rayleigh fading channels. The analytical results are verified through simulations.
Coherent photons and pomerons in heavy ion collisions

Ultrarelativistic heavy ion beams carry large electromagnetic and strong absorptive fields, allowing exploration of a variety of physics. γγ, γP, and PP interactions can probe a huge variety of couplings and final states. RHIC will be the first heavy ion accelerator energetic enough to produce hadronic final states via coherent couplings. Virtual photons from the nuclear EM fields can interact in γγ interactions, which can be exploited to study many particle spectroscopy and QCD topics. Because the photon flux scales as Z2, γγ luminosities are large up to an energy of about γℏc/R≈3 GeV/c. Photon-Pomeron interactions are sensitive to how different vector mesons, including the J/ψ, interact with nuclear matter. PP collisions rates are sensitive to the range of the Pomeron. Signals can be separated from backgrounds by using cuts on final state isolation (rapidity gaps) and p⊥. We present Monte Carlo studies of different backgrounds, showing that representative signals can be extracted with good rates and sig.