Miracle-dz/UniFAR-FTUs huggingface dataset:
Incorporate Hashing with Multi-view Learning

Multi-view learning concentrates on multiple distinct feature sets mainly following either the consensus principle or the complementary principle. SVM-2K, as a typical SVM-based multi-view learning model, extends SVM for multi-view learning by combining Kernel Canonical Correlation Analysis (KCCA). However, SVM-2K cannot fully unleash the power of the complementary information among different feature views. Recently, a framework of Predictable Dual-View Hashing (PDH) has been proposed to process two-view data sharing the complementary information. Motivated by PDH, we propose a novel strategy: Incorporate Hashing with Multi-view Learning (IHMVL). The specific implementation of IHMVL is to incorporate the PDH algorithm with SVM-2K for two-view classification, which suffices to both the consensus and complementary principles. This is the first work that extends hashing to multi-view learning. Experimental results on the synthetic data sets confirm the effectiveness of the proposed method.
Lymphomatosis cerebri: a rare form of primary central nervous system lymphoma. Analysis of 7 cases and systematic review of the literature.

BACKGROUND Primary central nervous system lymphomas may present as diffuse, nonenhancing infiltrative lesions. This rare variant is termed lymphomatosis cerebri (LC). We did a systematic review and analysis of the literature, adding our own cases, to better characterize LC in order to improve early diagnosis and treatment. METHODS PubMed, ISI Web of Knowledge, and hospital databases were reviewed. Information was extracted regarding demographic, clinical, histological, cerebrospinal fluid (CSF), neuroimaging, and treatment variables. The impact of single parameters on overall survival (OS) was determined by applying univariate and multivariate analyses. RESULTS Forty-two patients were included (median age: 58 y; range: 28-80 y). At consultation, 52% of patients had a poor KPS. The most common presenting symptom was cognitive decline (59.5%). Imaging studies showed supratentorial and infratentorial infiltration in 55% of patients and bilateral hemispheric involvement in 95%. CSF pleocytosis was present in 51.5% of the patients. Median time to diagnosis was 4.5 (range: 1-30) months, and the diagnosis was not established until autopsy for 33% of patients. The median OS was 2.95 (range: 0.33-56) months; however, those patients who received methotrexate had a median OS of 13.8 (range: 0.7-56) months. Analysis identified KPS ≥ 70 (HR: 0.32; 95% CI: 0.114-0.894; P = .03) and treatment with methotrexate (HR: 0.19; 95% CI: 0.041-0.886; P = .034) as independent favorable prognostic factors, whereas T-cell lymphoma was independently related with a worse outcome (HR: 6.62; 95% CI: 1.317-33.316; P = .022). CONCLUSIONS LC is a misdiagnosed entity associated with considerable diagnostic delay. MRI evidence of bilateral hemispheric involvement and CSF pleocytosis should be alerts for this diagnosis. Treatment with methotrexate-based chemotherapy must be considered, especially for patients with good KPS.
Public Disagreement

Members of different social groups often hold widely divergent public beliefs regarding the nature of the world in which they live. We develop a model that can accommodate such public disagreement, and use it to explore questions concerning the aggregation of distributed information and the consequences of social integration. The model involves heterogeneous priors, private information, and repeated communication until beliefs become public information. We show that when priors are correlated, all private information is eventually aggregated and public beliefs are identical to those arising under observable priors. When priors are independently distributed, however, some private information is never revealed and the expected value of public disagreement is greater when priors are unobservable than when they are observable. If the number of individuals is large, communication breaks down entirely in the sense that disagreement in public beliefs is approximately equal to disagreement in prior beliefs. Interpreting integration in terms of the observability of priors, we show how increases in social integration can give rise to less divergent public beliefs on average. Communication in segregated societies can cause initial biases to be amplified, and new biases to emerge where none previously existed. Even though all announcements are public and all signals equally precise, minority groups members face a disadvantage in the interpretation of public information that results in medium run beliefs that are less closely aligned with the true state.
FPGA implementation of Spiking Neural Networks supported by a Software Design Environment

Abstract This paper is focused on the creation of Spiking Neural Networks (SNN) in hardware due to their advantages for certain problem solving and their similarity to biological neural system. One of the main uses of this neural structure is pattern classification. The chosen model for the spiking neuron is the Spike Response Model (SRM). For SNN design and implementation, a software application has been developed to provide easy creation, simulation and automatic generation of the hardware model. VHDL was used for the hardware model. This paper describes the functionality of SNN and the design procedure followed to obtain a working neural system in both software and hardware. Designed VHDL code is fully synthesizable; it has been tested with Xilinx ISE implementation software. Final results show some applications showing the ability of SNN for pattern recognition as well as their performance and occupation in FPGA.
Buckling of Plates Types T

In this paper the problem of buckling of plates on foundation of finite length and with different side support is studied. The Finite Strip Method is used as tool for the analysis. method uses finite strip elastic, foundation, and geometric matrices build the assembly matrices for the whole structure, then after introducing boundary conditions at supports, the resulting reduced matrices is transformed into a standard Eigenvalue problem. The solution of this problem will enable the determination of the buckling load, the associated buckling modes and the buckling wave length. To carry out the buckling analysis starting from foundation, and geometric stiffness matrices for each strip a computer program FORTRAN list is developed. Since stiffness matrices are function of wave length of buckling, the computer program used an iteration procedure to find the critical buckling stress for each value of foundation modulus and for each boundary condition. The results showed the use of elastic medium to support plates subject to axial load increase a great deal the buckling load, the results found are very close with those obtained by other analytical methods and experimental work. The results also showed that foundation compensates the effect of the weakness of some types of constraint of side support and maximum benefit found for plate with one side simply supported the other free. Keywords—Buckling, Finite Strip, Different Plates on Foundation.
Pollen Limitation of Plant Reproduction: Pattern and Process

▪ Abstract Quantifying the extent to which seed production is limited by the availability of pollen has been an area of intensive empirical study over the past few decades. Whereas theory predicts that pollen augmentation should not increase seed production, numerous empirical studies report significant and strong pollen limitation. Here, we use a variety of approaches to examine the correlates of pollen limitation in an effort to understand its occurrence and importance in plant evolutionary ecology. In particular, we examine the role of recent ecological perturbations in influencing pollen limitation and discuss the relation between pollen limitation and plant traits. We find that the magnitude of pollen limitation observed in natural populations depends on both historical constraints and contemporary ecological factors.
Prevalence of Subclinical Mastitis and Distribution of Pathogens in Dairy Farms of Rubavu and Nyabihu Districts, Rwanda

A cross-sectional study was conducted from May 2016 to January 2017 in Rubavu and Nyabihu districts, Western Rwanda, aiming at estimating the prevalence of subclinical mastitis (SCM) and identifying its causative bacteria. Management practices and milking procedures were recorded through a questionnaire. 123 crossbreed milking cows from 13 dairy farms were randomly selected and screened for SCM using California Mastitis Test (CMT). Composite CMT positive milk samples were processed for bacterial isolation and identification. The overall SCM prevalence at cow level was 50.4%. 68 bacterial isolates were identified by morphological and biochemical characteristics. They included, Coagulase Negative Staphylococci (51.5%), Staphylococcus aureus (20.6%), Streptococcus species (10.3%), Bacillus species (10.3%), Streptococcus agalactiae (5.8%), and Escherichia coli (1.5%). About 67.1% of the farmers checked for mastitis; of these, 58.9% relied on clinical signs and only 6.8% screened with CMT. Only 5.5% and 2.7% of the farmers tried to control mastitis using dry cow therapy and teat dips, respectively. Thus, to reduce the prevalence of SCM, farmers in the study area need to be trained on good milking practices, including regular use of teat dips, application of dry cow therapy, and SCM screening. This will improve their sales and their financial status.
Adaptive Replication in Distributed Content Delivery Networks

We address the problem of content replication in large distributed content delivery networks, composed of a data center assisted by many small servers with limited capabilities and located at the edge of the network. The objective is to optimize the placement of contents on the servers to offload as much as possible the data center. We model the system constituted by the small servers as a loss network, each loss corresponding to a request to the data center. Based on large system / storage behavior, we obtain an asymptotic formula for the optimal replication of contents and propose adaptive schemes related to those encountered in cache networks but reacting here to loss events, and faster algorithms generating virtual events at higher rate while keeping the same target replication. We show through simulations that our adaptive schemes outperform significantly standard replication strategies both in terms of loss rates and adaptation speed.
Cross-cutting Messages and Voter Turnout: Evidence from a Same-Sex Marriage Amendment

Does disagreement stimulate political participation, or discourage it? Some researchers find that exposure to cross-cutting views demobilizes voters. Selection bias in the way individuals expose themselves to disagreement and other sources of endogeneity pose challenges to causal inference. I address these concerns by using an experimental design that exogenously assigns cross-cutting or reinforcing messages. A random sample of North Carolina Democrats and Republicans received postcards summarizing either liberal or conservative opinions on a statewide same-sex marriage amendment. I find that individuals exposed to disagreement demobilize by 1.0 to 1.6 percentage points, with the majority of the combined effect attributable to a 2.0-percentage point decrease in turnout among Republicans receiving a Democratic message. I observe a similar level of demobilization when defining disagreement on the basis of predicted issue position on same-sex marriage in place of partisan affiliation. The effects are strongest among moderate supporters of traditional marriage that receive a cross-cutting treatment. The experimental design thus enables causal evidence on the nuanced interactions between political or issue position and exposure to campaign information from the opposing side.
Self-organised music

Self-organisation, as manifest, for example, by swarms, flocks, herds and other collectives, is a powerful natural force, capable of generating large and sustained structures. Yet the individuals who participate in these social groups may not even be aware of the structures that they are creating. Almost certainly, these structures emerge through the application of simple, local interactions. Improvised music is an uncertain activity, characterised by a lack of top-down organisation and busy, local activity between improvisers. Emerging structures may only be perceivable at a (temporal) distance. The development of higher-level musical structure arises from interactions at lower levels, and we propose here that the self-organisation of social animals provides a very suggestive analogy. This paper builds a model of interactivity based on stigmergy, the process by which social insects communicate indirectly by environment modification. The improvisational element of our model arises from the dynamics of a particle swarm. A process called interpretation extracts musical parameters from the aural environment, and uses these parameters to place attractors in the environment of the swarm, after which stigmergy can take place. The particle positions are reinterpreted as parameterised audio events. This paper describes this model and two applications, Swarm Music and Swarm Granulator.
Joint Topic-Opinion Model for Implicit Feature Extracting

Topic model has been used to extract implicit features yet little concerns have been given to general opinion words, e.g., "Okey" (good). In this paper we present a modified topic model joint topic-opinion model (JTO) for extracting implicit features of opinion words including special and general ones. Our model is based on an extension to standard LDA model by adding an opinion level. This model considers both topics and context of opinion words. Experiments show that JTO provides higher accuracy in implicit features extraction.
Replication control in promiscuous plasmid RK2: kil and kor functions affect expression of the essential replication gene trfA

We previously reported that broad-host-range plasmid RK2 encodes multiple host-lethal kil determinants (kilA, kilB1, kilB2, and kilC) which are controlled by RK2-specified kor functions (korA, korB, and korC). Here we show that kil and kor determinants have significant effects on RK2 replication control. First, korA and korB inhibit the replication of certain RK2 derivatives, unless plasmid replication is made independent of the essential RK2 gene trfA. Second, kilB1 exerts a strong effect on this interaction. If the target plasmid is defective in kilB1, sensitivity to korA and korB is enhanced at least 100-fold. Thus, korA and korB act negatively on RK2 replication, whereas kilB1 acts in a positive manner to counteract this effect. A mutant RK2 derivative, resistant to korA and korB, was found to have fused a new promoter to trfA, indicating that the targets for korA and korB are at the 5' end of the trfA gene. We constructed a trfA-lacZ fusion and found that synthesis of beta-galactosidase is inhibited by korA and korB. Thus korA, korB, and kilB1 influence RK2 replication by regulating trfA expression. We conclude that the network of kil and kor determinants is part of a replication control system for RK2.
Retail Globalization and Household Welfare: Evidence from Mexico

The arrival of global retail chains in developing countries is causing a radical transformation in the way households source their consumption. This paper draws on a rich collection of Mexican microdata to estimate the effect of foreign supermarket entry on household welfare and decomposes this effect into six channels. We find that foreign entry causes large welfare gains for the average household predominantly driven by a reduction in the cost of living—both through price reductions at domestic stores and through the direct consumer gains from foreign stores. These gains are, on average, positive for all income groups but are regressive.
An improved SAM algorithm for red blood cells and white blood cells segmentation

The segmentation of red blood cells and white blood cells has important research value in the field of rheological properties of blood and the pathogenesis of some diseases. And it is the reflection of bone hematopoietic state, blood diseases and other diseases. Especially for the diagnosis of blood diseases, the detection and prevention of treatment process, there is high value of clinical research. The separation of red blood cells and white blood cells using hyperspectral remote sensing image processing is a new field that it is essentially different from traditional multi spectral classification. Because of the different chemical composition and molecular space structure of red blood cells and white blood cells, it results in different spectrum. Each pixel of hyperspectral image can obtain a unique continuous spectral curve, and it can be compared with the spectral curves which are known to obtain target object. So the author designs a new analytical method which is based on the various processing methods of hyperspectral image. First of all, using the BandMax wizard to lock target image and band based on target detection; secondly, conducting differential search algorithm based on the blind signal; thirdly, using an improved algorithm—based on SAM combined with SID algorithm; finally, using advanced filtering method to get clearer image information. In this paper, it focuses on the effective extraction and improves the classification accuracy of white blood cells.
Functional dissection of Arabidopsis COP1 reveals specific roles of its three structural modules in light control of seedling development

Arabidopsis COP1 acts as a repressor of photomorphogenesis in darkness, and light stimuli abrogate the repressive ability and nuclear abundance of COP1. COP1 has three known structural modules: an N‐terminal RING‐finger, followed by a predicted coiled‐coil and C‐terminal WD‐40 repeats. A systematic study was undertaken to dissect the functional roles of these three COP1 domains in light control of Arabidopsis seedling development. Our data suggest that COP1 acts primarily as a homodimer, and probably dimerizes through the coiled‐coil domain. The RING‐finger and the coiled‐coil domains can function independently as light‐responsive modules mediating the light‐controlled nucleocytoplasmic partitioning of COP1. The C‐terminal WD‐40 domain functions as an autonomous repressor module since the overexpression of COP1 mutant proteins with intact WD‐40 repeats are able to suppress photomorphogenic development. This WD‐40 domain‐mediated repression can be at least in part accounted for by COP1's direct interaction with and negative regulation of HY5, a bZIP transcription factor that positively regulates photomorphogenesis. However, COP1 self‐association is a prerequisite for the observed interaction of the COP1 WD‐40 repeats with HY5. This work thus provides a structural basis of COP1 as a molecular switch.
Lamotrigine-induced obsessional symptoms in a patient with bipolar II disorder: a case report

Lamotrigine is an anticonvulsant that appears to have a mainly antidepressant effect and is indicated for the maintenance treatment of bipolar depression. Literature associated with obsessional symptoms related to lamotrigine treatment is limited. We report the emergence of obsessive symptoms during treatment with lamotrigine in a patient who subsequently experienced significant improvement after dose reduction and stopping of this medication. The obsessive symptoms associated with lamotrigine treatment were observed after the lamotrigine dose was increased to 100 mg/day. The possible mechanisms, including inhibition on the presynaptic release of glutamate and alteration of striatal dopamine uptake, are discussed. It is unclear why lamotrigine induces obsessions in some patients. Controlled studies are necessary to identify the population at risk for obsessionality in bipolar illness following treatment with lamotrigine and to investigate a possible dose—response relationship between obsessive symptoms and lamotrigine.
Caregivers’ Attitudes Toward Milk Fat Type and Milk Consumption Among WIC Participants: An Exploratory Study

Caregivers’ Attitudes Toward Milk Fat Type and Milk Consumption Among WIC Participants: An Exploratory Study. (May 2010) Katrina Jane Serrano, B.S., University of Illinois at Chicago Chair of Advisory Committee: Dr. E. Lisako J. McKyer Factors such as parental/caregiver influences and socioeconomic status have been shown to impact food-related attitudes and behaviors. Consequently, these attitudes and behaviors affect health outcomes. The purpose of this study was to assess, using the Social Cognitive Theory (SCT), attitudes toward milk fat type and milk consumption among Texas WIC participants. Few studies, using this theoretical framework, have examined milk intake specifically among this population. Four hypotheses were proposed according to the theoretical model. The inclusionary criteria used for this study yielded a subset sample of 2,115; all cases included were Texas WIC participants. The results of this study show that caregivers’ attitudes toward drinking and offering milk fat type are related. Caregivers’ attitudes toward drinking milk fat type and the type of milk they drank were proven to be statistically significant. Similarly, caregivers’ attitudes toward offering milk fat type and the milk fat type their children drank were proven to be significant. Caregivers’ milk intakes were positively associated with children’s milk intakes.
Fast and automatic 3D full head synthesis using iPhone

3D full head synthesis (3DFHS) is of interest in many applications, including gaming and social networks. One well known related work is [Blanz and Vetter 1999] but it is only restricted to the synthesis of the face area (and not the head area). FaceGen [FaceGen 2011] uses a similar statistical approach and it provided a solution by coloring the head area with a single matching color. However, both of these approaches are not automatic, and user interactions are needed to manually assign the locations of the feature points. In addition, computation time to perform 3D face synthesis is in the order of several minutes on relatively fast PCs.
An efficient parameterization of dynamic neural networks for nonlinear system identification

Dynamic neural networks (DNNs), which are also known as recurrent neural networks, are often used for nonlinear system identification. The main contribution of this letter is the introduction of an efficient parameterization of a class of DNNs. Having to adjust less parameters simplifies the training problem and leads to more parsimonious models. The parameterization is based on approximation theory dealing with the ability of a class of DNNs to approximate finite trajectories of nonautonomous systems. The use of the proposed parameterization is illustrated through a numerical example, using data from a nonlinear model of a magnetic levitation system.