Miracle-dz/UniFAR-FTUs huggingface dataset:
Qualitative System Identification from Imperfect Data

Experience in the physical sciences suggests that the only realistic means of understanding complex systems is through the use of mathematical models. Typically, this has come to mean the identification of quantitative models expressed as differential equations. Quantitative modelling works best when the structure of the model (i.e., the form of the equations) is known; and the primary concern is one of estimating the values of the parameters in the model. For complex biological systems, the model-structure is rarely known and the modeler has to deal with both model-identification and parameter-estimation. In this paper we are concerned with providing automated assistance to the first of these problems. Specifically, we examine the identification by machine of the structural relationships between experimentally observed variables. These relationship will be expressed in the form of qualitative abstractions of a quantitative model. Such qualitative models may not only provide clues to the precise quantitative model, but also assist in understanding the essence of that model. Our position in this paper is that background knowledge incorporating system modelling principles can be used to constrain effectively the set of good qualitative models. Utilising the model-identification framework provided by Inductive Logic Programming (ILP) we present empirical support for this position using a series of increasingly complex artificial datasets. The results are obtained with qualitative and quantitative data subject to varying amounts of noise and different degrees of sparsity. The results also point to the presence of a set of qualitative states, which we term kernel subsets, that may be necessary for a qualitative model-learner to learn correct models. We demonstrate scalability of the method to biological system modelling by identification of the glycolysis metabolic pathway from data.
Capital Structure in Iran E-business

Structural capital has been described as more hidden part of intellectual capital and organizational knowledge. In spite of more clarity regarding the indicators of human capital,the first dimension of intellectual capital, structural capital sub-dimensions and indicators have been a challenging subject in intellectual capital literature. Clarifying structural capital indicators in e-business as more knowledge-based arena is also a missing topic of research in the literature. Despite the highly importance of intellectual capital in e-business success, few applicable research has been conducted in recent years. This research ontributes to the literature and practices in using a two-step survey in order to discover the most influencing indicators in the success of e-business. The application of the analytic hierarchy process. (AHP) is utilized to extract weights for setting the priority among criteria.
A Phone Mapping Technique for Acoustic Modeling of Under-Resourced Languages

This paper presents a novel method for acoustic modeling of a new language with a limited amount of training data. In this approach, we use well-trained acoustic models of a foreign language to generate acoustic scores for each feature vector of the target language. These scores are then used as the input for mapping to context dependent triphones of the target language using a limited amount of training data. With this approach, we do not need to modify or have a special requirement for the foreign acoustic models. In this paper, English is used as the foreign language while Malay is used as the target language. Experiments on a Malay large vocabulary continuous speech recognition (LVCSR) task show that with using only few minutes of training data we can achieve a low word error rate which outperforms the best monolingual baseline acoustic model significantly.
2016 Ieee International Conference on Big Data (big Data) Materialized View Selection in Feed following Systems

—Recently emerging feed-following applications generate personalized event streams from various feeds and deliver them to a large number of users. To provide a low-latency service, a feed-following system has to buffer the events in a number of tables, called materialized views, and choosing views to materialize is critical to the system performance. State-of-the-art solutions only consider view selections for each individual user. Due to the existence of very popular feeds and social communities, users often share a lot of feeds that they follow and hence performing a global optimization by considering all the users can significantly enhance the system performance. However, performing such a global optimization needs to choose views for materialization from an exponential number of possible ones. To solve the issue, we propose an effective method to generate candidate views that are potentially beneficial. We then propose several cost-based algorithms to solve the global view selection problem, which adopt a cost model that captures the cost of both user query processing and view maintenance and make use of the containment relationships among the sets of feeds followed by the individual users. We implement the complete approach in a prototype system and perform experiments on a computing cluster using both real and synthetic data. The results indicate that our approach outperforms the state-of-the-art approaches significantly.
An Orbifold of Type 0 B Strings and Non-supersymmetric Gauge Theories

We study a ZZ2 orbifold of Type 0B string theory by reflection of six of the coordinates (this theory may also be thought of as a ZZ4 orbifold of Type IIB string theory by a rotation by π in three independent planes). We show that the only massless mode localized on the fixed fourplane IR is a U(1) gauge field. After introducing D3-branes parallel to the fixed fourplane we find non-supersymmetric non-abelian gauge theories on their worldvolume. One of our results is that the theory on equal numbers of electric and magnetic D3-branes placed at the fourplane is the ZZ4 orbifold of N = 4 supersymmetric Yang-Mills theory by the center of its R-symmetry group.
Cross-modal attribute based facial image retrieval

Attribute-based facial image retrieval has wide range of applications, such as in law enforcement, online social networks, etc. The problem becomes more challenging if the images are from different modalities. For example, the input is a sketch or a composite image, and the task is to retrieve photo images which have the same facial attributes as the input data. In this work, we propose a learning-based approach, in which two transformations are learnt to transform the training images from the two modalities with associated attribute annotations such that images which have similar attributes move closer to each other, and images with very different attributes move farther from each other in the transformed space. Given a query image, it is first transformed to the learnt space in which the images with similar attributes are retrieved. The same framework works seamlessly if the images to be retrieved are of same or different modality as compared to the query data. The attributes of the query image are also automatically obtained as a byproduct of the algorithm. Extensive experimental evaluation on three datasets shows the effectiveness of the proposed approach.
A Method for the Construction of a Probabilistic Hierarchical Structure Based on a Statistical Analysis of a Large-scale Corpus

The purpose of this study is to develop a method of constructing a probabilistic hierarchical structure based on a statistical analysis of a Japanese corpus using a combination of Kameya and Sato's statistical language analysis and Rose's model. First, the co-occurrence frequencies of adjectives and nouns are calculated from a Japanese corpus based on modification relations. Second, latent classes are extracted from a statistical language analysis of the cooccurrence data. Third, the centroid vectors of the latent classes are calculated from the analysis results and a probabilistic hierarchical structure of the latent classes is constructed by utilizing Rose's model. Finally, the conditional probabilities of the categories given the latent classes are computed as the association probabilities of the concepts to the categories and the conditional probabilities of the categories given the concepts are computed as the association probabilities of the concepts to the categories.
Prospective study of bone mineral density changes in aging men with or at risk for HIV infection

Objective:To investigate rates and predictors of change in bone mineral density (BMD) in a cohort of aging men with or at risk for HIV infection. Design:A prospective cohort study among 230 HIV-infected and 159 HIV-uninfected men aged at least 49 years. Methods:Longitudinal analyses of annual change in BMD at the femoral neck, total hip, and lumbar spine. Results:At baseline, 46% of men had normal BMD, 42% had osteopenia, and 12% had osteoporosis. Of those men with normal BMD, 14% progressed to osteopenia and 86% continued to have normal BMD. Of the men initially with osteopenia, 12% progressed to osteoporosis and 83% continued to have osteopenia. Osteopenia incidence per 100 person-years at risk was 2.6 for HIV-uninfected men and 7.2 for HIV-infected men; osteoporosis incidence was 2.2 per 100 person-years at risk among men with osteopenia, regardless of HIV status. In multivariable analysis of annual change in BMD at the femoral neck, we found a significant interaction between heroin use and AIDS diagnosis, such that the greatest bone loss occurred with both AIDS and heroin use (adjusted predicted mean annual bone loss 0.0196 g/cm2). Hepatitis C virus seropositivity was also associated with femoral neck bone loss (P = 0.04). The interaction between AIDS and heroin use also was associated with bone loss at the total hip, as was current methadone use (P < 0.01). Conclusion:We found an association of heroin use and AIDS with BMD change, suggesting that heroin users with AIDS may be at particular risk for bone loss.
An implemented planner for manipulating a polygonal object in the plane with three disc-shaped mobile robots

Presents an implementation of a planner that uses three disc-shaped robots to manipulate a polygonal object in the plane in the presence of obstacles. The approach is based on the computation of the maximal discs (maximal independent capture discs or MICaDs) where the robots can move independently while preventing the object from escaping their grasp. It has been shown that, in the absence of obstacles, it is always possible to bring a polygonal object from any configuration to any other one with robot motions constrained to lie in a set of overlapping MICaDs. This approach is generalized to the case where obstacles are present by decomposing the motion planning task into (1) the construction of a collision-free path for a modified form of the object, and (2) the execution of this path by a sequence of simultaneous and independent robot motions within overlapping MICaDs. The approach is guaranteed to work provided a collision free path exists for the modified form of the object. Experiments with Nomadic Scouts and a visual localization system are presented.
Rearrangement of multiple objects by a robot group having a multi-task function

A robot having a multi-task function can carry more than two objects simultaneously; however, a robot without that function can carry only one at any given time. A multi-task function robot has the potential to shorten the transfer path, which reduces the process time; however, a single-function robot does not have that capability. In this paper, a planning algorithm that consists of Simulated Annealing and Scheduling with prioritization rules for a robot group having a multi-task function is proposed. Experiments are conducted in a real environment to validate the proposed algorithms.
Evaluation of Object Detection Proposals Under Condition Variations

Object detection is a fundamental task in many computer vision applications, therefore the importance of evaluating the quality of object detection is well acknowledged in this domain. This process gives insight into the capabilities of methods in handling environmental changes. In this paper, a new method for object detection is introduced that combines the Selective Search and EdgeBoxes. We tested these three methods under environmental variations. Our experiments demonstrate the outperformance of the combination method under illumination and view point variations.
A robust method for determining the magnitude of the fully asymmetric alignment tensor of oriented macromolecules in the absence of structural information.

It has recently been shown that the degree of alignment of macromolecules in an aqueous dilute liquid crystalline medium of bicelles is sufficient to permit accurate values of residual 15N-1H, 13C-1H, and 13Calpha-C' dipolar couplings to be obtained on a routine basis, thereby providing potentially unique long-range structural information. To make use of this information in macromolecular structure determination, the magnitude of the axial and rhombic components of the molecular alignment tensor must be determined. This can be achieved by taking advantage of the fact that different, fixed-distance internuclear vector types are differently distributed relative to the alignment tensor. A histogram of the ensemble of normalized residual dipolar couplings for several such vector types approximates a powder pattern from which the magnitude of the axial and rhombic components are readily extracted in the absence of any prior structural information. The applicability of this method is demonstrated using synthetic data derived from four proteins representative of different sizes, topologies, and secondary structures, and experimental data measured on the small protein ubiquitin.
A new lower bound for one-machine earliness-tardiness scheduling

In one-machine scheduling, MIP time-indexed formulations are often used to provide very good lower bounds through Lagrangian relaxations. In order to get an improved lower bound, we add valid cuts to a time-indexed formulation and show we still have a Lagrangian relaxation that can be solved as a shortest path in a graph. Two branch-and-bound algorithms are then presented for the earliness-tardiness scheduling problem with either common or general due dates. In both cases, our algorithms outperform the previously published approaches.
Fixed point ratios in actions of finite exceptional groups of lie type.

Let G be a finite exceptional group of Lie type acting transitively on a set O. For x in G, the fixed point ratio of x is the proportion of elements of O which are fixed by x. We obtain new bounds for such fixed point ratios. When a point-stabilizer is parabolic we use character theory; and in other cases, we use results on an analogous problem for algebraic groups in Lawther, Liebeck & Seitz, 2002. These give dimension bounds on fixed point spaces of elements of exceptional algebraic groups, which we apply by passing to finite groups via a Frobenius morphism.
Stochastic Neural Field Theory and the System-Size Expansion

We analyze a master equation formulation of stochastic neurodynamics for a network of synaptically coupled homogeneous neuronal populations each consisting of N identical neurons. The state of the network is specified by the fraction of active or spiking neurons in each population, and transition rates are chosen so that in the thermodynamic or deterministic limit ($N\rightarrow\infty$) we recover standard activity-based or voltage-based rate models. We derive the lowest order corrections to these rate equations for large but finite N using two different approximation schemes, one based on the Van Kampen system-size expansion and the other based on path integral methods. Both methods yield the same series expansion of the moment equations, which at $\mathcal{O}(1/N)$ can be truncated to form a closed system of equations for the first- and second-order moments. Taking a continuum limit of the moment equations while keeping the system size N fixed generates a system of integrodifferential equations for the .
A Data Dissemination Protocol Based on Multiple Virtual Grids in Wireless Sensor Network

Sensor networks are composed of a great number of sensor nodes. Since all sensor nodes are energy-restricted and hard to recharge, it is very important. However, the energy consumption may significantly increase if mobile sources or sinks exist in sensor networks. The reason is that the routing information for mobile sources and sinks needs to be update frequently for efficient data delivery. The routing algorithm supporting mobile sinks should consider not only continuous data delivery but also the energy consumption of sensor nodes. However, most of the existing research e.g. Fan Ye, et al. (Set. 2002), Zehua Zhou, et al., (Jun 2006) focuses on even energy consumption while the mobility of sinks and sources is rarely consider. In this paper, we propose an efficient routing protocol with multiple virtual grids to reduce energy consumption and improve packets delivery efficiency. Simulation results show that our algorithm can guarantee high data delivery ratio and lower average delivery delay, while consuming lower energy than existing routing protocols in sensor networks.
Toward a Narrative Ethics

Drawing on experience of community-based health research with a First Nation population, I present a case for the incorporation of an ethics grounded in narrative, particularly within Indigenous community-based research (CBR). Viewing conventional bioethics’ emphasis on individual autonomy as increasingly insufficient in grappling with the complexities of research with Indigenous communities, with their often historically, socially, and culturally specific notions of kinship, intersubjectivity, and relationality, I suggest that an ethics of narrative has the potential to respond to a conventional bioethics of autonomy in ways that would be more commensurable with the ethical and lived experiences of Indigenous persons. Drawing on poststructuralist and Indigenous thought, I ultimately argue for the narrative competency to engage with and respond to the stories of sickness and health that may arise from cultural contexts other than those sedimented within Western Euro-American frameworks. Key to this endeavor is attention to and understanding of conceptions of self and community formation as multiple and diverse, marked by porosity and even the potential for ethical failure.
Composition and dynamics of the Caenorhabditis elegans early embryonic transcriptome

Temporal profiles of transcript abundance during embryonic development were obtained by whole-genome expression analysis from precisely staged C. elegans embryos. The result is a highly resolved time course that commences with the zygote and extends into mid-gastrulation, spanning the transition from maternal to embryonic control of development and including the presumptive specification of most major cell fates. Transcripts for nearly half (8890) of the predicted open reading frames are detected and expression levels for the majority of them (>70%) change over time. The transcriptome is stable up to the four-cell stage where it begins rapidly changing until the rate of change plateaus before gastrulation. At gastrulation temporal patterns of maternal degradation and embryonic expression intersect indicating a mid-blastula transition from maternal to embryonic control of development. In addition, we find that embryonic genes tend to be expressed transiently on a time scale consistent with developmental decisions being made with each cell cycle. Furthermore, overall rates of synthesis and degradation are matched such that the transcriptome maintains a steady-state frequency distribution. Finally, a versatile analytical platform based on cluster analysis and developmental classification of genes is provided.
The in vitro Effect of Irrigants with Low Surface Tension on Enterococcus faecalis

Introduction: Due to the complex anatomy of the root canal system and high surface tension of common root canal irrigants (RCI), conducting an investigation on RCIs containing surfactants is a priority. The aim of this in vitro study was to verify the antibacterial potential of RCI with low surface tension in root canals infected with Enterococcus faecalis (E. faecalis). Methods and Materials: Thirty-five extracted human maxillary anterior teeth were prepared and inoculated with E. faecalis for 60 days. After root canal preparation, the teeth were randomly divided to one positive and one negative control groups and 5 experimental groups: Hypoclean/Tetraclean NA, Hypoclean, Tetraclean, NaOCl/Tetraclean and NaOCl. Bacterial growth was observed by turbidity of culture medium and then measured using a UV spectrophotometer. Data were analyzed in three time intervals (pre-instrumentation and, 20 min and 72 h after canal preparation) using the ANOVA and post hoc Tukey’s tests. The level of significance was set at 0.05. Results: The results indicated the presence of E. faecalis in all post-irrigation samples irrespective of the RCI. However, the optical densities in both post-irrigation periods showed bacterial reduction and significant differences between groups. Conclusion: RCI with low surface tension showed antibacterial potential in E. faecalis infected roots.
Tool support for checking railway interlocking designs

The development of railway interlocking systems is currently very labour-intensive. Specialists develop the interlocking design for a particular area and manually check for completeness and consistency. The interlocking is implemented in either software or using electrical relays. The interlocking has to be tested against the safety requirements for signalling systems, i.e., the signalling principles.The whole process can be supported by various tools, ranging from editors to animators. In this paper we focus on exploiting model checking to automatically check the design with respect to safety. The main concerns of this technique are the problem size and the efficiency of available tools. We have investigated both of these problems: seeking to work with a minimal model of the interlocking design and to improve efficiency of the model-checking process by exploiting domain knowledge of our particular application.
Computation of Average Distance, Radius and Centre of a Circular-Arc Graph in Parallel

The determination of centre of a graph is very important task in facility location problem. Computation of centre depends on the computation of radius of the graph. In this paper, we have design some parallel algorithms to find the average distance, radius, diameter and centre of a circular-arc graph. The proposed parallel algorithms run in O(n 2 /p + log n) time on a EREW PRAM, where p and n represent respectively the number of processors and the number of vertices of the circular-arc graph.