Miracle-dz/UniFAR-FTUs huggingface dataset:
Community evolution detection in dynamic heterogeneous information networks

As the rapid development of all kinds of online databases, huge heterogeneous information networks thus derived are ubiquitous. Detecting evolutionary communities in these networks can help people better understand the structural evolution of the networks. However, most of the current community evolution analysis is based on the homogeneous networks, while a real community usually involves different types of objects in a heterogeneous network. For example, when referring to a research community, it contains a set of authors, a set of conferences or journals and a set of terms. In this paper, we study the problem of detecting evolutionary multi-typed communities defined as net-clusters in dynamic heterogeneous networks. A Dirichlet Process Mixture Model-based generative model is proposed to model the community generations. At each time stamp, a clustering of communities with the best cluster number that can best explain the current and historical networks are automatically detected. A Gibbs sampling-based inference algorithm is provided to inference the model. Also, the evolution structure can be read from the model, which can help users better understand the birth, split and death of communities. Experiments on two real datasets, namely DBLP and Delicious.com, have shown the effectiveness of the algorithm.
Mechanoafferent neurons innervating tail of Aplysia. I. Response properties and synaptic connections.

Mechanical, chemical, or electrical stimulation of the tail elicits a short-latency (less than 1 s) tail-withdrawal reflex that is graded with the intensity of the stimulus. The tail-withdrawal reflex is not elicited by stimulation of parts of the body outside of the tail region. Mechanoafferent neurons innervating the tail are located in a small subcluster within a large, homogeneous group of medium-size (40-80 micron) cells on the ventrocaudal (VC) surface of each pleural ganglion. The tail sensory neurons within this large VC cluster are activated by tactile pressure or by electrical stimulation of discrete regions of the tail. They adapt slowly to maintained stimulation and sometimes respond to stimulus offset as well. Both mechanical and electrical stimuli produce responses that are graded with the intensity of the stimulus. Cells in the VC cluster appear to be primary mechanoreceptors because they have axons in peripheral nerves (including nerves innervating the tail), they exhibit action potentials lacking prepotentials in response to tactile stimulation, and these action potentials are still produced by cutaneous stimulation when peripheral and central chemical synaptic transmission is blocked. Stimulation of fields all over the body surface evokes synaptically mediated hyperpolarizing responses in individual mechanoafferent neurons that may represent afferent inhibition. Hyperpolarizing responses lasting many seconds can be produced by brief cutaneous stimuli. The mechanoafferent neurons innervating the tail region make strong monosynaptic connections to tail motor neurons in the ipsilateral pedal ganglion, and through these connections this subpopulation of the VC neurons appears to make a substantial contribution to the short-latency tail-withdrawal reflex. In addition, the combined excitatory receptive fields of these mechanoafferents match the excitatory receptive field of the tail-withdrawal reflex. Mechanoafferent neurons in the VC cluster that have receptive fields on other parts of the body (outside the excitatory receptive field of the tail-withdrawal reflex) have not been observed to make monosynaptic connections to the tail motor neurons. The neurons innervating the tail are reliably found in a discrete region within the larger VC cluster. In addition to this gross somatotopic organization, there is evidence of a finer level of somatotopic organization between the position of the excitatory receptive field on the tail and the position of the cell soma in the tail subcluster. (ABSTRACT TRUNCATED AT 400 WORDS)
Structure recovery by part assembly

This paper presents a technique that allows quick conversion of acquired low-quality data from consumer-level scanning devices to high-quality 3D models with labeled semantic parts and meanwhile their assembly reasonably close to the underlying geometry. This is achieved by a novel structure recovery approach that is essentially local to global and bottom up, enabling the creation of new structures by assembling existing labeled parts with respect to the acquired data. We demonstrate that using only a small-scale shape repository, our part assembly approach is able to faithfully recover a variety of high-level structures from only a single-view scan of man-made objects acquired by the Kinect system, containing a highly noisy, incomplete 3D point cloud and a corresponding RGB image.
Evolution, neural networks, games, and intelligence

Mathematical games provide a framework for studying intelligent behavior in models of real-world settings or restricted domains. The obstacle comes in choosing the appropriate representation and learning algorithm. Neural networks and evolutionary algorithms provide useful means for addressing these issues. This paper describes efforts to hybridize neural and evolutionary computation to learn appropriate strategies in zero- and nonzero-sum games, including the iterated prisoner's dilemma, tic-tac-toe, and checkers. With respect to checkers, the evolutionary algorithm was able to discover a neural network that can be used to play at a near-expert level without injecting expert knowledge about how to play the game. The implications of evolutionary learning with respect to machine intelligence are also discussed. It is argued that evolution provides the framework for explaining naturally occurring intelligent entities and can be used to design machines that are also capable of intelligent behavior.
Trophic amplification of climate warming

Ecosystems can alternate suddenly between contrasting persistent states due to internal processes or external drivers. It is important to understand the mechanisms by which these shifts occur, especially in exploited ecosystems. There have been several abrupt marine ecosystem shifts attributed either to fishing, recent climate change or a combination of these two drivers. We show that temperature has been an important driver of the trophodynamics of the North Sea, a heavily fished marine ecosystem, for nearly 50 years and that a recent pronounced change in temperature established a new ecosystem dynamic regime through a series of internal mechanisms. Using an end-to-end ecosystem approach that included primary producers, primary, secondary and tertiary consumers, and detritivores, we found that temperature modified the relationships among species through nonlinearities in the ecosystem involving ecological thresholds and trophic amplifications. Trophic amplification provides an alternative mechanism to positive feedback to drive an ecosystem towards a new dynamic regime, which in this case favours jellyfish in the plankton and decapods and detritivores in the benthos. Although overfishing is often held responsible for marine ecosystem degeneration, temperature can clearly bring about similar effects. Our results are relevant to ecosystem-based fisheries management (EBFM), seen as the way forward to manage exploited marine ecosystems.
Objective Evaluation of Differences in Protein Subcellular Distribution

Research on the cell and molecular biology of proteins involved in membrane traffic often requires determination of the effects of various experimental conditions on the subcellular distributions of those proteins. This is most often accomplished by acquiring fluorescence microscope images and visually comparing these images. While this approach is quite suitable for detecting major changes in distributions, it is not sensitive to small changes and does not permit a quantitative and objective analysis. We therefore describe the application of pattern analysis methods to the comparison of sets of fluorescence microscope images. This approach provides a high throughput and reproducible technique to determine whether image distributions differ within a specified statistical confidence, and is shown to resolve image sets indistinguishable by visual inspection.
A check-valved silicone diaphragm pump

Two generations of check-valved silicone rubber diaphragm pumps are presented. Significant improvements have been made from pump to pump including the design and fabrication of a double-sided check valve, a bossed silicone membrane, and silicone gaskets. Water flow rates of up to 13 ml/min and a maximum back pressure of 5.9 kPa were achieved through pneumatic operation with an external compressed air source. Using a custom designed solenoid actuator, flow rates of up to 4.5 ml/min and a maximum back pressure of 2.1 kPa have been demonstrated.
Automatic Extraction of Efficient Axiom Sets from Large Knowledge Bases

Efficient reasoning in large knowledge bases is an important problem for AI systems. Hand-optimization of reasoning becomes impractical as KBs grow, and impossible as knowledge is automatically added via knowledge capture or machine learning. This paper describes a method for automatic extraction of axioms for efficient inference over large knowledge bases, given a set of query types and information about the types of facts in the KB currently as well as what might be learned. We use the highly right skewed distribution of predicate connectivity in large knowledge bases to prune intractable regions of the search space. We show the efficacy of these techniques via experiments using queries from a learning by reading system. Results show that these methods lead to an order of magnitude improvement in time with minimal loss in coverage.
Ten years of axial capacitively coupled contactless conductivity detection for CZE – a review

Contactless conductivity detection is universal for CE in that all charged species can be quantified, and it is particularly attractive for those inorganic and organic ions that are not directly accessible by optical means. It is not necessary to make precise alignments or to create an optical window into the capillary. Commercial detectors that can be retrofitted to existing instruments are available at a cost that is lower than that of any other electrophoresis detector. The approach is also suited for lab‐on‐chip devices. It is attempted in this review to summarize some of the expertise accumulated since the introduction of the axial contactless conductivity detector to CE 10 years ago.
Functional analysis of a reproductive organ predominant expressing promoter in cotton plants

Transgenic Bt insect-resistant cotton plants have high insect resistance in the early stage of development, but relatively low resistance in the late stage. Substituting a reproductive organ-specific promoter for the CaMV35S promoter presently being used could be an ideal solution. For the first time, the promoter sequence of ADP-ribosylation factor 1 (arf1) gene was isolated from Gossypium hirsutumY18 by means of inverse PCR. The sequencing result discovered the unique structure of the arf1 promoter, including four promoter-specific elements, the initiator, TATA box, CAAT box and GC box, and also an intron in 5′-untranslation region. Four plant expression vectors were constructed for functional analysis of the promoter. Based on the pBI121 plant expression vector, four truncated arf1 promoters took the place of the CaMV35S promoter. These vectors were different only in their promoter regions. They were introduced into cotton plants via pollen tube pathway. Histochemical GUS staining and fluorescence quantitative analyses were performed to examine the expression patterns of the GUS gene driven by the 4 arf1 truncated promoters in transgenic cotton plants respectively. The results showed that the arf1 promoter was a typical reproductive organ-specific promoter. Hopefully, the arf1 promoter can be a regulatory element for designing cotton reproductive organs with desired characteristics.
Limitations of Simple Flow Models for the Simulation of Nanoimprint

Abstract A quick evaluation of the forces involved in nanoimprint would be very helpful in the prevention of mold deflection. Unfortunately, it is shown here that assuming simplified flows may lead to quite incorrect evaluations of these forces, even for simple periodic patterns and a Newtonian behavior. The mere use of the classical result of the lubrication theory does not account for the range of thickness-to-width ratios that may be involved, especially at the beginning of the process. An improved squeeze model includes this effect, but still underestimates the imprint force. Moreover, finite element simulations demonstrate limitations of two more elaborate models that are found in the literature. These simulations also show that two flow modes can be defined, according to whether or not the polymer touches the mold sidewalls. A deeper analysis of these two modes may help the definition of a more appropriate simplified model in the future.
Testing the rolling tack of pressure-sensitive adhesive materials. Part II: Effect of adherend surface roughness

A novel method and custom-made apparatus for testing the rolling tack of pressure-sensitive adhesives (PSAs) and related materials were developed to measure bonding and debonding processes. The combined effects of adherend (probe) surface roughness, longitudinal load, and dwell time on bond-formation performance of five different tacky materials chosen from various application areas were studied. These materials included synthetic PSAs (acrylic tape and the hydrocolloid dressing, Granuflex®), water-remoistenable adhesive (CENTRAL®), edible wheat flour dough, and a static cling vinyl (PENSTIC®). Tack-rolling velocity curves were analyzed to study bonding and debondong processes. Each of the tested materials showed different tack behavior in response to varying probe roughness, external load, and velocity (dwell time). Surface wetting and mechanical interlocking were proposed as the mechanisms governing tack in most tested PSAs. Acrylic PSA tested on a smooth probe over a velocity range of 0.12-2.12 m/s showed higher tack values than on a rough one. A significant reduction in tack was due to restricted bond formation. Similarly, tack of Granuflex® to a smooth model skin surface showed higher values than to a rough skin surface. CENTRAL® showed typical cohesive failure when tested on silicone-coated paper. Interfacial failure and short-term bonding accounted for good tack performance on porous paper. Dough tested with aluminum probes showed cohesive failure similar to that of CENTRAL® at velocities higher than 0.2 m/s where the tack was independent of probe surface roughness. PENSTIC® adhered only to smooth glass where the tack values tended to decrease with increased velocity. Bonding and debonding processes of the various tacky materials were clearly affected by adherend surface roughness, longitudinal load, and dwell time, and could be successfully analyzed using our novel proposed method and apparatus.
Convex Multiview Semi-Supervised Classification

In many practical applications, there are a great number of unlabeled samples available, while labeling them is a costly and tedious process. Therefore, how to utilize unlabeled samples to assist digging out potential information about the problem is very important. In this paper, we study a multiclass semi-supervised classification task in the context of multiview data. First, an optimization method named Parametric multiview semi-supervised classification (PMSSC) is proposed, where the built classifier for each individual view is explicitly combined with a weight factor. By analyzing the weakness of it, a new adapted weight learning strategy is further formulated, and we come to the convex multiview semi-supervised classification (CMSSC) method. Comparing with the PMSSC, this method has two significant properties. First, without too much loss in performance, the newly used weight learning technique achieves eliminating a hyperparameter, and thus it becomes more compact in form and practical to use. Second, as its name implies, the CMSSC models a convex problem, which avoids the local-minimum problem. Experimental results on several multiview data sets demonstrate that the proposed methods achieve better performances than recent representative methods and the CMSSC is preferred due to its good traits.
Comparing Implementations of Near-Data Computing with In-Memory MapReduce Workloads

The emergence of 3D stacking and the imminent release of Micron's Hybrid Memory Cube (HMC) device have made it more practical to move computation near memory. This work presents a detailed analysis of in-memory MapReduce in the context of near-data computing (NDC). MapReduce is a good fit for NDC because it is embarrassingly parallel and has highly localized memory accesses. This article considers two NDC architectures: one that exploits HMC devices and one that does not. It thus provides insight on the benefits of different NDC approaches and quantifies the potential for improvement for an important emerging big-data workload.
Compressive Sensing Based Time Domain Synchronous OFDM Transmission for Vehicular Communications

Time domain synchronous OFDM (TDS-OFDM) has higher spectral efficiency and faster synchronization than standard cyclic prefix OFDM (CP-OFDM), but suffers from the difficulty of supporting 256QAM in low-speed vehicular channels with long delay spread and the performance loss over fast time-varying vehicular channels. This paper addresses how to efficiently use the compressive sensing (CS) theory to solve those problems. First, we break through the conventional concept of cancelling the interferences if present, and propose the idea of using the inter-block-interference (IBI)-free region of small size to reconstruct the high-dimensional sparse multipath channel, whereby no interference cancellation is required any more. In this way, without changing the current signal structure of TDS-OFDM at the transmitter, the mutually conditional time-domain channel estimation and frequency-domain data detection in conventional TDS-OFDM receivers can be decoupled. Second, we propose the parameterized channel estimation method based on priori aided compressive sampling matching pursuit (PA-CoSaMP) algorithm to achieve reliable performance over vehicular channels, whereby partial channel priori available in TDS-OFDM is used to improve the performance and reduce the complexity of the classical CoSaMP signal recovery algorithm. Simulation results demonstrate that the proposed scheme can support the 256QAM and gain improved performance over fast fading channels.
Modal Logics for Metric Spaces: Open Problems

Modal logics and their models have been used to speak about and represent topological spaces since the 1940s [22, 23, 16, 17]. Examples include Tarski’s programme of algebraisation of topology (“of creating an algebraic apparatus for the treatment of portions of point-set topology,” to be more precise) which involved modal logic S4 [17], and the use of the extension of S4 with the universal modality (and its fragments) for spatial representation and reasoning; see, e.g., [5, 18, 7, 8, 1, 9] and references therein. Metric spaces are even more important mathematical structures that are fundamental for many areas of mathematics and computer science (recent examples include classification in bioinformatics, linguistics, botany, etc. using various similarity measures). A natural research programme is then to find out to which extent modal-like formalisms can be useful for speaking about metric spaces. Such a programme was launched in 2000 [21, 13, 14]. The aim of this note is to attract attention to the most important open problems and new directions of research in this exciting and promising area.
Entangled Monte Carlo

We propose a novel method for scalable parallelization of SMC algorithms, Entangled Monte Carlo simulation (EMC). EMC avoids the transmission of particles between nodes, and instead reconstructs them from the particle genealogy. In particular, we show that we can reduce the communication to the particle weights for each machine while efficiently maintaining implicit global coherence of the parallel simulation. We explain methods to efficiently maintain a genealogy of particles from which any particle can be reconstructed. We demonstrate using examples from Bayesian phylogenetic that the computational gain from parallelization using EMC significantly outweighs the cost of particle reconstruction. The timing experiments show that reconstruction of particles is indeed much more efficient as compared to transmission of particles.
Hypersusceptibility to Substrate Analogs Conferred by Mutations in Human Immunodeficiency Virus Type 1 Reverse Transcriptase

ABSTRACT Human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) contains four structural motifs (A, B, C, and D) that are conserved in polymerases from diverse organisms. Motif B interacts with the incoming nucleotide, the template strand, and key active-site residues from other motifs, suggesting that motif B is an important determinant of substrate specificity. To examine the functional role of this region, we performed “random scanning mutagenesis” of 11 motif B residues and screened replication-competent mutants for altered substrate analog sensitivity in culture. Single amino acid replacements throughout the targeted region conferred resistance to lamivudine and/or hypersusceptibility to zidovudine (AZT). Substitutions at residue Q151 increased the sensitivity of HIV-1 to multiple nucleoside analogs, and a subset of these Q151 variants was also hypersusceptible to the pyrophosphate analog phosphonoformic acid (PFA). Other AZT-hypersusceptible mutants were resistant to PFA and are therefore phenotypically similar to PFA-resistant variants selected in vitro and in infected patients. Collectively, these data show that specific amino acid replacements in motif B confer broad-spectrum hypersusceptibility to substrate analog inhibitors. Our results suggest that motif B influences RT-deoxynucleoside triphosphate interactions at multiple steps in the catalytic cycle of polymerization.
Visual map matching and localization using a global feature map

This paper presents a novel method to support environmental perception of mobile robots by the use of a global feature map. While typical approaches to simultaneous localization and mapping (SLAM) mainly rely on an on-board camera for mapping, our approach uses geographically referenced aerial or satellite images to build a map in advance. The current position on the map is determined by matching features from the on-board camera to the global feature map. The problem of feature matching is posed as a standard point pattern matching problem and a solution using the iterative closest point method is given. The proposed algorithm is designed for use in a street vehicle and uses lane markings as features, but can be adapted to almost any other type of feature that is visible in aerial images. Our approach allows for estimating the robot position at a higher precision than by a purely GPS-based localization, while at the same time providing information about the environment far beyond the current field of view.