Miracle-dz/UniFAR-FTUs huggingface dataset:
Repurposing the FDA-Approved Pinworm Drug Pyrvinium as a Novel Chemotherapeutic Agent for Intestinal Polyposis

Mutations in the WNT-pathway regulator ADENOMATOUS POLYPOSIS COLI (APC) promote aberrant activation of the WNT pathway that is responsible for APC-associated diseases such as Familial Adenomatous Polyposis (FAP) and 85% of spontaneous colorectal cancers (CRC). FAP is characterized by multiple intestinal adenomas, which inexorably result in CRC. Surprisingly, given their common occurrence, there are few effective chemotherapeutic drugs for FAP. Here we show that the FDA-approved, anti-helminthic drug Pyrvinium attenuates the growth of WNT-dependent CRC cells and does so via activation of CK1α. Furthermore, we show that Pyrvinium can function as an in vivo inhibitor of WNT-signaling and polyposis in a mouse model of FAP: APCmin mice. Oral administration of Pyrvinium, a CK1α agonist, attenuated the levels of WNT-driven biomarkers and inhibited adenoma formation in APCmin mice. Considering its well-documented safe use for treating enterobiasis in humans, our findings suggest that Pyrvinium could be repurposed for the clinical treatment of APC-associated polyposes.
EC-MMR: Revised exemplar-based clustering with automatic parameter estimation techniques

In this study, we discuss recent advances in the theory and practice of exemplar-based clustering. In the context of clustering, exemplars are those representative objects in the data sets. A recently proposed approach called convex clustering with exemplar-based models, referred as (CCE), adopts a convex objective function with a global solution. Although the existing frame work of CCE is attractive, the parameter sensitivity problem may make the original CCE infeasible to be used for some real applications. In this paper, we propose an improved version called exemplar-based clustering with minimal marginal redundancy (EC-MMR). In EC-MMR, the shape parameter is estimated automatically based on the data. Further more, the finally exemplars are selected in an improved way in which both the representativeness of each individual object and the whole exemplar set are considered. Our experiment results show that with these procedures incorporated, the new approach improves the CCE approach greatly with respect to producing higher quality of clusters in a fully automatical manner.
Robust feature description and matching using local graph

Feature detection and matching are essential parts in most computer vision applications. Many researchers have developed various algorithms to achieve good performance, such as SIFT (Scale-Invariant Feature Transform) and SURF (Speeded Up Robust Features). However, they usually fail when the scene has considerable out-of-plane rotation because they only focus on in-plane rotation and scale invariance. In this paper, we propose a novel feature description algorithm based on local graph representation and graph matching based, which is more robust to out-of-plane rotation. The proposed local graph encodes the geometric correlation between the neighboring features. In addition, we propose an efficient score function to compute the matching score between the local graphs. Experimental result shows that the proposed algorithm is more robust to out-of-plane rotation than conventional algorithms.
In: Neural Codes and Distributed Representations Foundations of Neural Computation Edited

Research into how neurons represent the world is proceeding rapidly. Most of the pioneering studies of sensory and motors systems were based on single unit recordings. Although our current understanding of the response properties of neurons in the brain is largely based on this approach, there is likely to be additional information that can only be accessed by examining the firing patterns of large populations of neurons. New experimental techniques, such as simultaneous recordings of more than 100 neurons (Gray et al., 1995; Meister, 1996), provide a glimpse of large-scale population codes and distributed representations in different parts of the brain. The papers in this volume are a selection of those that have appeared in Neural Computation and represent a sample of diverse approaches to the problem of neuronal coding. This introduction gives some background for these papers as well as additional references for further reading.
The NAIST-NTT TED talk treebank

Syntactic parsing is a fundamental natural language processing technology that has proven useful in machine translation, language modeling, sentence segmentation, and a number of other applications related to speech translation. However, there is a paucity of manually annotated syntactic parsing resources for speech, and particularly for the lecture speech that is the current target of the IWSLT translation campaign. In this work, we present a new manually annotated treebank of TED talks that we hope will prove useful for investigation into the interaction between syntax and these speechrelated applications. The first version of the corpus includes 1,217 sentences and 23,158 words manually annotated with parse trees, and aligned with translations in 26-43 different languages. In this paper we describe the collection of the corpus, and an analysis of its various characteristics.
A behaviour based decisional model using vote

The coordination mechanism is an important aspect of the behaviour based approach. Many strategies are developed to select an action among the proposals of each behaviour. Distributed preference voting present many advantages compared to the other strategies. However, several disadvantages persist. Thus we propose an improvement of this method. The modifications aim particularly at reducing the development problems (choice of votes weights). We propose to select the decisions in a continuous action space. We also increase the number of behaviours that is often used. And finally we try to specify the voting mechanism
A Cache Oblivious Approach for the Problem of Computing Single Source Shortest Paths on Undirected Graphs

This report presents the current state of my research activity in the framework of my Doctorate program. The main problem I am studying is how to obtain an I/O efficient cache oblivious Single Source Shortest Paths (SSSP) algorithm for undirected graphs. The background of my work is described in Section 1, where we explain why it is important to develop algorithms making an efficient usage of memory hierarchies, and we describe two important models for studying the efficiency of such algorithms. Section 2 deals with existing I/O efficient algorithms for the SSSP and for a closely related problem, Breadth First Search (BFS). Section 3 is focused on my ongoing research, and describes how some of the techniques presented in the previous section may be reused to obtain the desired algorithm. In Section 4 we draw conclusions, and point out how I intend to organize my work for the forthcoming year.
Ultra low power pulse generator based on a ring oscillator with direct path current avoidance

This paper presents a wide frequency range, ultra low power pulse generator based on a ring oscillator. The proposed architecture avoids the direct path current, reaching pulse frequencies down to the kHz range while maintaining the power consumption proportional to frequency. Furthermore, the used topology for the current starved inverter circuit improves the symmetry between rising and falling edges of the output signals of the ring oscillator with respect to the traditional implementation. A frequency range from 1.75kHz to 10MHz consuming 1nW and 3. 6μW respectively was achieved in a 130nm CMOS process. The modular design can be used to generate any non-overlapping pulse sequence with variable width.
Multi-kernel PCA based high-dimensional images feature reduction

Parameter selection in the intelligent technology model refers to a lot computation of shape image, and there will be much computation of image feature computing. The traditional parameter selection model can not make the shape that will be straight classified in time. Aiming at the bottleneck of the traditional method in high dimensions, based on analysis each kernel function's advantage this paper raises multi-kernel PCA method. This method mixes Multinomial kernel function, Sigmoid kernel function and Gauss radial basis kernel function, make full use of each kernel function's advantage in high dimension shape parameter reduction; Also, Genetic Algorithm is used to determine the key parameters of multi-kernel model. Last, the multi-kernel PCA method is used in shape image Dimension reduction, effectiveness and excellence are tested and verified.
A mobility model for pedestrian content distribution

Mobile communication devices may be used for spreading multimedia data without support of an infrastructure. Such a scheme, where the data is carried by people walking around and relayed from device to device by means of short range radio, could potentially form a public content distribution system that spans vast urban areas. The transport mechanism is the flow of people and it can be studied but not engineered. The question addressed in this paper is how well pedestrian content distribution may work. We answer this question by modeling the mobility of people moving around in a city, constrained by a given topology. Our contributions are both the queuing analytic model that captures the flow of people and the results on the feasibility of pedestrian content distribution. Furthermore, we discuss possible extensions to the mobility model to capture speed-distance relations that emerge in dense crowds.
The Effects of Season of Birth on the Inflammatory Response to Psychological Stress in Hainan Island, China

Season of birth (SOB) has been investigated as one of the environmental factors that might epigenetically determine the physiology of individuals. This study investigated the role of SOB in the association between Quality of Life (QOL), a proxy of psychological stress status, and C-reactive protein (CRP) concentration (i.e., inflammatory status) among 1,085 adults (aged 20–57 years old) in Hainan Island, China. High sensitivity CRP concentration was measured in dried blood spot samples, while the abbreviated version of the World Health Organization’s QOL questionnaire was used to gather information on six QOL domains. Analysis stratified by three historically distinct age groups revealed a significant association between CRP concentration, SOB, QOL and an interaction between SOB and QOL among the youngest and oldest groups. In the oldest group, those born in the dry season had a higher CRP concentration with worse QOL whereas in the youngest group, there was a higher CRP concentration with better QOL. Annual per capita rice production, a proxy of population nutritional status in the year of birth, was found to predict CRP concentration only among the second oldest group. These findings suggest that the early environment might affect the immune response to psychological stress in adulthood and that its effect may differ by the time period in which people were born.
Seven Scales to Measure the Seven Beatitudes in Leaders

This study presents the development of seven five-item scales to measure leadership traits in the seven Beatitudes found in Matthew 5: 3-10. The Cronbach’s alpha reliability coefficients for these scales are . 86, . 95, . 89, . 92, . 93, . 93, and . 92. Convergence validity was demonstrated by significant positive correlations for all seven scales with the Essential Servant Leadership Behavior scale and significant negative correlation with the Despotic Leadership scale. The value of the seven scales lies in their ability to assist researchers to compare leadership effectiveness with the seven representative virtues and, in time after normative data are developed, to offer a leadership tool for leadership selection and development.
How to Securely Prolong the Computational Bindingness of Pedersen Commitments

Pedersen commitments are important cryptographic primitives. They allow a prover to commit to a certain value without revealing any information about it and without the prover being able to change its mind later on. Since the first property holds unconditionally this is an essential primitive for many schemes providing long-term confidentiality. However, the second property only holds computationally. Hence, in the long run bindingness is lost, making the primitive improper for long-lived systems. Thus in this paper, we describe a protocol that, in a sense, prolongs the bindingness of a given Pedersen commitment. More precisely, we demonstrate how to prove in perfect zero-knowledge that a new Pedersen commitment - generated with a larger security parameter - and a corresponding old commitment both commit to the same value. We stress that this is a non-trivial procedure. Up until now the only known perfect zero-knowledge proof techniques for proving message equivalence of two commitments work when both commitments use isomorphic message spaces. However, as we will show in this work, to prolong the security of Pedersen commitments we cannot tolerate this restriction. Our prolonging technique works for non-isomorphic message spaces, is efficient, can be repeated an arbitrary number of times, maintains unconditional confidentiality, and allows to preserve the format of the Pedersen commitments. This makes the construction presented here an important contribution to long-lived systems. Finally, we illustrate this by discussing how commitments with prolongable bindingness can be used to allow for archiving solutions that provide not only integrity but also confidentiality in the long-term.
The Role of Northern Sea Ice Cover for the Weakening of the Thermohaline Circulation under Global Warming

Abstract An increase in atmospheric CO2 concentration and the resulting global warming are typically associated with a weakening of the thermohaline circulation (THC) in model scenarios. For the models participating in the Coupled Model Intercomparison Project (CMIP), this weakening shows a significant (r = 0.62) dependence on the initial THC strength; it is stronger for initially strong overturning. The authors propose a physical mechanism for this phenomenon based on an analysis of additional simulations with the coupled climate models CLIMBER-2 and CLIMBER-3α. The mechanism is based on the fact that sea ice cover greatly reduces heat loss from the ocean. The extent of sea ice is strongly influenced by the near-surface atmospheric temperature (SAT) in the North Atlantic but also by the strength of the THC itself, which transports heat to the convection sites. Consequently, sea ice tends to extend farther south for weaker THC. Initially larger sea ice cover responds more strongly to atmospheric warming; .
Nonverbal immediacy behaviors and online student engagement: bringing past instructional research into the present virtual classroom

ABSTRACT Nonverbal immediacy behaviors are underresearched in the online teaching environment. Using social presence theory as a guiding framework, this study explores several online nonverbal immediacy behaviors: emoticons/figurative language, color, cohesion, visual imagery, and audio in course design; response latency, length, time of day, and message frequency in forums; and type and promptness of feedback via grading and email. Coding of 51 online courses found that more consistent use of nonverbal immediacy behaviors was related to students’ reports of higher course engagement. However, the nonverbal behaviors most associated with engagement were the ones not used as often. Findings indicate instructors can improve the effectiveness of online learning environments via nonverbal immediacy behaviors.
Possibilities or paradoxes? How aspiring turnaround principals conceptualise turnaround and their place within it

ABSTRACT This study focuses on how a cohort of participants in a programme aimed at producing ‘turnaround leaders’ came to understand this policy and their role within it. Using a theory of action framework, I find that, over time, participants’ espoused theories of turnaround shifted in three key areas: (1) the cause of poor school performance, (2) the principal’s approach to leading change, and (3) the district’s role in turnaround. While these shifts created more complex views of organisational change, they also produced disillusionment and highlighted tensions in current conceptualisations of turnaround including their potential role in enacting it.
MPCA+MDA: A novel approach for face recognition based on tensor objects

This paper presents a novel approach to solve the supervised dimensionality reduction problem and feature extraction by encoding an image object as a general tensor of 2-D/3-D order. In this paper a multilinear principal component analysis (MPCA) for tensor object feature extraction and then a multilinear discriminant analysis (MDA), to find the best subspaces have been proposed. It should be noted that both of the algorithms work with tensor objects so the structure of the objects has been never broken. Therefore we achieve a better result than the result of the traditional methods. The focus of these algorithms is avoiding the curse of dimensionality. Finally, a comprehensive experiments on ORL and FERET databases has been provided by encoding face images as 2-D or 3-D tensors to demonstrate that MPCA+MDA algorithm based on higher order tensors has the potential to outperform the traditional vector-based subspace learning algorithms such as Eigenface and Fisherface, especially in the cases with small sample sizes and curse of dimensionality dilemma.
An Ontology-based Knowledge Repository Model on the Grid

Knowledge plays a key role in the Grid environment,while no adequate attention has been paid on how to construct knowledge repository on the grid by means of the existing resource.On the basis of OGSA,The paper proposes an ontology-based grid knowledge repository storage model,puts forward the ontologies which are necessary for building KR,studies the general architecture of knowledge repository model as well as the storage model based on the adapter.Finally discusses the access mechanism of grid knowledge repository.
LANDSCAPE COLOGY : What Is the State of the Science ?

Landscape ecology focuses on the reciprocal interactions between spatial pattern and ecological processes, and it is well integrated with ecology. The field has grown rapidly over the past 15 years. The persistent influence of land-use history and natural disturbance on contemporary ecosystems has become apparent Development of pattern metrics has largely stabilized, and they are widely used to relate landscape pattern to ecological responses. Analyses conducted at multiple scales have demonstrated the importance of landscape pattern for many taxa, and spatially mediated interspecific interactions are receiving increased attention. Disturbance remains prominent in landscape studies, and current research is addressing disturbance interactions. Integration of ecosystem and landscape ecology remains challenging but should enhance understanding of landscape function. Landscape ecology should continue to refine knowledge of when spatial heterogeneity is fundamentally important, rigorously test the generality of its concepts, and develop a more mechanistic understanding of the relationships between pattern and process.
Continuous area sweeping: a task definition and initial approach

As mobile robots become increasingly autonomous over extended periods of time, opportunities arise for their use on repetitive tasks. We define and implement behaviors for a class of such tasks that we call continuous area sweeping tasks. A continuous area sweeping task is one in which a robot (or group of robots) must repeatedly visit all points in a fixed area, possibly with non-uniform frequency, as specified by a task-dependent cost function. Examples of problems that need continuous area sweeping are trash removal in a large building and routine surveillance. We present a formulation for this problem and an initial algorithm to address it. The approach is analyzed analytically and is fully implemented and tested, both in simulation and on a physical robot
Market-based coordination of thermostatically controlled loads-Part I: A mechanism design formulation

This paper focuses on the coordination of a population of thermostatically controlled loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the device bidding and market clearing strategies to motivate self-interested users to realize efficient energy allocation subject to a peak energy constraint. This coordination problem is formulated as a mechanism design problem, and we propose a mechanism to implement the social choice function in dominant strategy equilibrium. The proposed mechanism consists of a novel bidding and clearing strategy that incorporates the internal dynamics of TCLs in the market mechanism design, and we show it can realize the team optimal solution. This paper is divided into two parts. Part I presents a mathematical formulation of the problem and develops a coordination framework using the mechanism design approach. Part II presents a learning scheme to account for the unknown load model parameters, and evaluates the proposed framework through realistic simulations.
Reflections on the “Orientalized Orientals”

What we really need is a critical language and a full-scale critical culture, not name calling or the rhetorical equivalent of political murder. Our purpose is to assess and critique power in the Arab world. Not according to grandiose schemas imported from Hegel and Stalin and so on: many of the miseries of the Arab left are ascribable to the importation of methodological instruments or Orientalist models from abroad having no relation to our life. We must ingeniously and imaginatively develop composite or hybrid models of the sort, for example, of Abdallah Laroui in North Africa, or Anwar Abdel Malek. Like-minded individuals have to give such a critique of power greater currency in their discussion. -Edward Said, Intellectuals and the War, 1991.
Investigation of the spray characteristics for a secondary fuel injection nozzle using a digital image processing method

There are many ways to reduce diesel engine exhaust emissions. However, NOx emission is difficult to reduce because the hydrocarbon (HC) concentration in a diesel engine is not sufficient for NOx conversion. Therefore, in order to create stoichiometric conditions in the De-NOx catalyst, a secondary injection system is designed to inject liquid HC into the exhaust pipe. The atomization and distribution characteristics of the HC injected from a secondary injector are key technologies to obtain a high NOx conversion because inhomogeneous droplets of injected HC cause not only high fuel consumption but also deterioration of NOx emission. This paper describes the spray characteristics of a secondary injector including the spray angle, penetration length and breakup behaviour of the spray to optimize the reduction rate of the NOx catalyst. In this study, various optical diagnostics were applied to investigate these spray characteristics, the atomization mechanism and spray developing process. The visualization and image processing method for the spray pulsation were developed by high speed photography. The influence of the fuel supply pressure on the spray behaviour and a more detailed spray developing process have been analysed experimentally using image processing. Finally, the experimental results were used to correlate the spray structure to the injection system performance and to provide a design guide for a secondary injector nozzle.