Miracle-dz/UniFAR-FTUs huggingface dataset:
Scalable Pattern Matching over Compressed Graphs via Dedensification

One of the most common operations on graph databases is graph pattern matching (e.g., graph isomorphism and more general types of "subgraph pattern matching"). In fact, in some graph query languages every single query is expressed as a graph matching operation. Consequently, there has been a significant amount of research effort in optimizing graph matching operations in graph database systems. As graph databases have scaled in recent years, so too has recent work on scaling graph matching operations. However, the performance of recent proposals for scaling graph pattern matching is limited by the presence of high-degree nodes. These high-degree nodes result in an explosion of intermediate result sizes during query execution, and therefore significant performance bottlenecks. In this paper we present a dedensification technique that losslessly compresses the neighborhood around high-degree nodes. Furthermore, we introduce a query processing technique that enables direct operation of graph query processing operations over the compressed data, without ever having to decompress the data. For pattern matching operations, we show how this technique can be implemented as a layer above existing graph database systems, so that the end-user can benefit from this technique without requiring modifications to the core graph database engine code. Our technique reduces the size of the intermediate result sets during query processing, and thereby improves query performance.
Axonal Dysfunction Precedes Motor Neuronal Death in Amyotrophic Lateral Sclerosis

Wide-spread fasciculations are a characteristic feature in amyotrophic lateral sclerosis (ALS), suggesting motor axonal hyperexcitability. Previous excitability studies have shown increased nodal persistent sodium conductances and decreased potassium currents in motor axons of ALS patients, both of the changes inducing hyperexcitability. Altered axonal excitability potentially contributes to motor neuron death in ALS, but the relationship of the extent of motor neuronal death and abnormal excitability has not been fully elucidated. We performed multiple nerve excitability measurements in the median nerve at the wrist of 140 ALS patients and analyzed the relationship of compound muscle action potential (CMAP) amplitude (index of motor neuronal loss) and excitability indices, such as strength-duration time constant, threshold electrotonus, recovery cycle and current-threshold relationships. Compared to age-matched normal controls (n = 44), ALS patients (n = 140) had longer strength-duration time constant (SDTC: a measure of nodal persistent sodium current; p < 0.05), greater threshold changes in depolarizing threshold electrotonus (p < 0.05) and depolarizing current threshold relationship (i.e. less accommodation; (p < 0.05), greater superexcitability (a measure of fast potassium current; p < 0.05) and reduced late subexcitability (a measure of slow potassium current; p < 0.05), suggesting increased persistent sodium currents and decreased potassium currents. The reduced potassium currents were found even in the patient subgroups with normal CMAP (> 5mV). Regression analyses showed that SDTC (R = -0.22) and depolarizing threshold electrotonus (R = -0.22) increased with CMAP decline. These findings suggest that motor nerve hyperexcitability occurs in the early stage of the disease, and precedes motor neuronal loss in ALS. Modulation of altered ion channel function could be a treatment option for ALS.
Social Discovery and Composition of Web Services

In this paper, we propose a new approach for services recommendation to assist services composition in a Mashup environment capturing and analyzing social interactions. This approach uses an implicit social graph inferred from the common composition interests of users. We describe in detail the transformation of users-services interactions into a social graph and a possible means to leverage that graph to derive service recommendation. This proposal was implemented within a platform called SoCo and the experiments show interesting results.
A Novel Image Representation via Local Frequency Analysis for Illumination Invariant Stereo Matching

In this paper, we propose a novel image representation approach to tackle illumination variations in stereo matching problems. Images are mapped using their Fourier transforms which are convolved with a set of monogenic filters. Frequency analysis is carried out at different scales to account for most image content. The phase congruency and the local weighted mean phase angle are then computed over all the scales. The original image is transformed into a new representation using these two mappings. This representation is invariant to illumination and contrast variations. More importantly, it is generic and can be used with most sparse as well as dense stereo matching algorithms. In addition, sequential feature matching or tracking can also benefit from our approach in varying radiometric conditions. We demonstrate the improvements introduced with our image mappings on well-established data sets in the literature as well as on our own experimental scenarios that include high dynamic range imagery. The experiments include both dense and sparse stereo and sequential matching algorithms where the latter is considered in the very challenging visual odometry framework.
Partial Eigenvalue Assignment for Large Linear Control Systems

The eigenvalue assignment problem is a classical problem in Control Theory. This paper presents new algorithms for the stabilization of large single-input time-invariant control systems by partial eigenvalue assignment. Our algorithms are based on the implicitly restarted Arnoldi method, and are well suited for control systems that require the reassignment of a few eigenvalues.
RETIRED A STARS: THE EFFECT OF STELLAR EVOLUTION ON THE MASS ESTIMATES OF SUBGIANTS

Doppler surveys have shown that the occurrence rate of Jupiter-mass planets appears to increase as a function of stellar mass. However, this result depends on the ability to accurately measure the masses of evolved stars. Recently, Lloyd called into question the masses of subgiant stars targeted by Doppler surveys. Lloyd argues that very few observable subgiants have masses greater than 1.5 M☉, and that most of them have masses in the range 1.0–1.2 M☉. To investigate this claim, we use Galactic stellar population models to generate an all-sky distribution of stars. We incorporate the effects that make massive subgiants less numerous, such as the initial mass function and differences in stellar evolution timescales. We find that these effects lead to negligibly small systematic errors in stellar mass estimates, in contrast to the ≈50% errors predicted by Lloyd. Additionally, our simulated target sample does in fact include a significant fraction of stars with masses greater than 1.5 M☉, primarily because the inclusion of an apparent magnitude limit results in a Malmquist-like bias toward more massive stars, in contrast to the volume-limited simulations of Lloyd. The magnitude limit shifts the mean of our simulated distribution toward higher masses and results in a relatively smaller number of evolved stars with masses in the range 1.0–1.2 M☉. We conclude that, within the context of our present-day understanding of stellar structure and evolution, many of the subgiants observed in Doppler surveys are indeed as massive as main-sequence A stars.
The File System Interface is an Anachronism

Contemporary file systems implement a set of abstractions and semantics that are suboptimal for many (if not most) purposes. The philosophy of using the simple mechanisms of the file system as the basis for a vast array of higher-level mechanisms leads to inefficient and incorrect implementations. We propose several extensions to the canonical file system model, including explicit support for lock files, indexed files, and resource forks, and the benefit of session semantics for write updates. We also discuss the desirability of application-level file system transactions and file system support for versioning.
Brutality Under Cover of Ambiguity

Five studies tested four hypotheses on the drivers of punitive judgments. Study 1 showed that people imposed covertly retributivist physical punishments on extreme norm violators when they could plausibly deny that is what they were doing (attributional ambiguity). Studies 2 and 3 showed that covert retributivism could be suppressed by subtle accountability manipulations that cue people to the possibility that they might be under scrutiny. Studies 4 and 5 showed how covert retributivism can become self-sustaining by biasing the lessons people learn from experience. Covert retributivists did not scale back punitiveness in response to feedback that the justice system makes false-conviction errors but they did ramp up punitiveness in response to feedback that the system makes false-acquittal errors. Taken together, the results underscore the paradoxical nature of covert retributivism: It is easily activated by plausible deniability and persistent in the face of false-conviction feedback but also easily deactivated by minimalist forms of accountability.
Leveraging Human Computations to Improve Schematization of Spatial Relations from Imagery

The process of generating schematic maps of salient objects from a set of pictures of an indoor environment is challenging. It has been an active area of research as it is crucial to a wide range of context- and location-aware services, as well as for general scene understanding. Although many automated systems have been developed to solve the problem, most of them either require predefining labels or expensive equipment, such as RGBD sensors or lasers, to scan the environment. In this article, we introduce a prototype system to show how human computations can be utilized to generate schematic maps from a set of pictures, without making strong assumptions or demanding extra devices. The system requires humans (crowd workers from Amazon Mechanical Turks) to do simple spatial mapping tasks in various conditions, and their data are aggregated by filtering and clustering techniques that allow salient cues to be identified in the pictures and their spatial relations to be inferred and projected on a two-dimensional map. In particular, we tested and demonstrated the effectiveness of two methods that improved the quality of the generated schematic map: (1) We encouraged humans to adopt an allocentric representations of salient objects by guiding them to perform mental rotations of these objects and (2) we sensitized human perception by guided arrows superimposed on the imagery to improve the accuracy of depth and width estimation. We demonstrated the feasibility of our system by evaluating the results of schematic maps generated from indoor pictures taken from an office building. By calculating Riemannian shape distances between the generated maps to the ground truth, we found that the generated schematic maps captured the spatial relations well. Our results showed that the combination of human computations and machine clustering could lead to more-accurate schematized maps from imagery. We also discuss how our approach may have important insights on methods that leverage human computations in other areas.
Alterations of Excitation–Contraction Coupling and Excitation Coupled Ca2+ Entry in Human Myotubes Carrying CAV3 Mutations Linked to Rippling Muscle Disease

Rippling muscle disease is caused by mutations in the gene encoding caveolin‐3 (CAV3), the muscle‐specific isoform of the scaffolding protein caveolin, a protein involved in the formation of caveolae. In healthy muscle, caveolin‐3 is responsible for the formation of caveolae, which are highly organized sarcolemmal clusters influencing early muscle differentiation, signalling and Ca2+ homeostasis. In the present study we examined Ca2+ homeostasis and excitation–contraction (E‐C) coupling in cultured myotubes derived from two patients with Rippling muscle disease with severe reduction in caveolin‐3 expression; one patient harboured the heterozygous c.84C>A mutation while the other patient harbored a homozygous splice‐site mutation (c.102+ 2T>C) affecting the splice donor site of intron 1 of the CAV3 gene. Our results show that cells from control and rippling muscle disease patients had similar resting [Ca2+]i and 4‐chloro‐m‐cresol‐induced Ca2+ release but reduced KCl‐induced Ca2+ influx. Detailed analysis of the voltage‐dependence of Ca2+ transients revealed a significant shift of Ca2+ release activation to higher depolarization levels in CAV3 mutated cells. High resolution immunofluorescence analysis by Total Internal Fluorescence microscopy supports the hypothesis that loss of caveolin‐3 leads to microscopic disarrays in the colocalization of the voltage‐sensing dihydropyridine receptor and the ryanodine receptor, thereby reducing the efficiency of excitation–contraction coupling. Hum Mutat 32:309–317, 2011. © 2011 Wiley‐Liss, Inc.
A structure-from-motion method for 3-D reconstruction of moving objects from multiple-view image sequences

Solving the correspondence problem is the most essential task for multiview reconstruction techniques, yet finding unique correspondences between views is impossible at some points, due to such problems as occlusions and ambiguities. We have developed a closed-form solution through constructive geometry for a special case of the structure-from-motion (SI-M) problem with four rigidly moving points. This solution allows the 3-D position of a point on a moving object to be computed without having to find the correspondence between its projections on the image planes of multiple views, given its projected 2-D motion vector on an image plane and 3-D information of three other points. With this method we do not have to depend entirely on multiview feature correspondences in reconstructing 3-D objects, hence easing those problems caused by occlusions and ambiguities.
Activation of Mammalian Target of Rapamycin (mTOR) by Insulin Is Associated with Stimulation of 4EBP1 Binding to Dimeric mTOR Complex 1*

Insulin stimulates protein synthesis by promoting phosphorylation of the eIF4E-binding protein, 4EBP1. This effect is rapamycin-sensitive and mediated by mammalian target of rapamycin (mTOR) complex 1 (mTORC1), a signaling complex containing mTOR, raptor, and mLST8. Here we demonstrate that insulin produces a stable increase in the kinase activity of mTORC1 in 3T3-L1 adipocytes. The response was associated with a marked increase in 4EBP1 binding to raptor in mTORC1, and it was abolished by disrupting the TOR signaling motif in 4EBP1. The stimulatory effects of insulin on both 4EBP1 kinase activity and binding occurred rapidly and at physiological concentrations of insulin, and both effects required an intact mTORC1. Results of experiments involving size exclusion chromatography and coimmunoprecipitation of epitope-tagged subunits provide evidence that the major insulin-responsive form is dimeric mTORC1, a structure containing two heterotrimers of mTOR, raptor, and mLST8.
A researcher's journey through complexity, reflexivity and transformation: a case study from Rwanda

Rwanda is a land-locked Central African country faced with two major challenges ensuring recovery, rehabilitation and reconciliation after the genocide of 1994, and the massive need for sustainable development. Within this context education and health reform are playing an important role in reconciliation, reconstruction and development. The first author spent two years in Rwanda and established a primary and a lower secondary school. For the two years that the first author lived in Rwanda, she worked with teachers and students and was struck by their resilience, simplicity, hope and determination. This paper highlights the voices of teachers as they struggled to achieve against great odds. The first author’s personal journey has been examined over the course of the research study and her voice has been used to speak from socio-cultural and practical perspectives. Through personal reflections and use of narratives, the present study involved interactions with teachers which enabled the first author to embark on a transformative process and understand the complexity of school reform in a transitional society.
KEGG for representation and analysis of molecular networks involving diseases and drugs

Most human diseases are complex multi-factorial diseases resulting from the combination of various genetic and environmental factors. In the KEGG database resource (http://www.genome.jp/kegg/), diseases are viewed as perturbed states of the molecular system, and drugs as perturbants to the molecular system. Disease information is computerized in two forms: pathway maps and gene/molecule lists. The KEGG PATHWAY database contains pathway maps for the molecular systems in both normal and perturbed states. In the KEGG DISEASE database, each disease is represented by a list of known disease genes, any known environmental factors at the molecular level, diagnostic markers and therapeutic drugs, which may reflect the underlying molecular system. The KEGG DRUG database contains chemical structures and/or chemical components of all drugs in Japan, including crude drugs and TCM (Traditional Chinese Medicine) formulas, and drugs in the USA and Europe. This database also captures knowledge about two types of molecular networks: the interaction network with target molecules, metabolizing enzymes, other drugs, etc. and the chemical structure transformation network in the history of drug development. The new disease/drug information resource named KEGG MEDICUS can be used as a reference knowledge base for computational analysis of molecular networks, especially, by integrating large-scale experimental datasets.
Kleinian Theory: A Contemporary Perspective

1 Melanie Klein, Beginnings, Catalina Bronstein. 2 Freud and Klein on the Concept of Phantasy, Elizabeth Bott Spillius. 3 The Paranoid--schizoid position, Priscilla Roth. 4 Depressive Position, Jane Temperley. 5 Beyond The depressive Position, Ronald Britton. 6 The Oedipus Complex, Jill Boswell. 7 Envy and Gratitude, Marco Chiesa. 8 What are Internal Objects? Catalina Bronstein. 9 Projective Identification, David Bell. 10 Symbolisation, Hanna Segal. 11 Changing models of The Mind, Hanna Segal. 12 Biona s Theory of Containment, Ruth riesenberg--malcolm. 13 Transference, Betty Joseph. References.
Preliminary Field Trial for Teleoperated Communication Robots

This paper introduces a "teleoperated communication robot" whose unique point is that its language component is performed by an operator to avoid the automatic recognition difficulty of spoken language. On the other hand, conceptually, its nonverbal behavior will be autonomously controlled. One important point is to identify whether ordinary people will accept this type of communication robot. Therefore, we conducted a preliminary field trial at a shopping center, which revealed positive perspectives as well as technical problems to be solved
Opponent modelling in automated multi-issue negotiation using Bayesian learning

In this paper, we show that it is nonetheless possible to construct an opponent model, i.e. a model of the opponent’s preferences that can be effectively used to improve negotiation outcomes. We provide a generic framework for learning both the preferences associated with issue values as well as the weights that rank the importance of issues to an agent. The main idea is to exploit certain structural features and rationality principles to guide the learning process and focuses the algorithm on the most likely preference profiles of an opponent. We present a learning algorithm based on Bayesian learning techniques that computes the probability that an opponent has a particular preference profile. Our approach can be integrated into various negotiating agents using different strategies.
Parallel Algorithms for Computation of the Manipulator Inertia Matrix

This article presents the development of an O(log 2 N) parallel algorithm for the manipulator inertia matrix. It is based on an efficient serial algorithm that uses the composite rigid- body method. Recursive doubling is used to reformulate the linear recurrence equations that are required to compute the diagonal elements of the matrix. It results in O(log 2 N) levels of computation. Computation of the off-diagonal ele ments involves N linear recurrences of varying size, and a new method, which avoids redundant computation of position and orientation transforms for the manipulator, is developed. The O(log 2 N) algorithm is presented in both equation and graphic forms that clearly show the parallelism inherent in the algorithm. The relationship between the number of pro cessors required and the order of the computation is also given for several versions of parallel algorithms for the inertia matrix.
Distributed Parallel Computing in Mermera: Mixing Noncoherent Shared Memories

Abstract Programmers of parallel processes that communicate through shared globally distributed data structures (DDS) face a difficult choice. Either they must explicitly program DDS management, by partitioning or replicating it over multiple distributed memory modules, or be content with a high latency coherent (sequentially consistent) memory abstraction that hides the DDS'' distribution. We present Mermera, a formalism and system that enables a smooth spectrum of noncoherent shared memory behaviors to coexist between the above two extremes. Our approach allows us to define known noncoherent memories in a new simple way, to identify new memory behaviors, and to characterize generic mixed-behavior computations. The latter are useful for programming using multiple behaviors that complement each others'' advantages, and for programming by step-wise refinement. On the practical side, we show that the large class of programs that use asynchronous iterative methods (AIM) can run correctly on slow memory, one of the weakest, and hence most efficient and fault-tolerant, noncoherence conditions. An example AIM program to solve linear equations, is developed to illustrate the need for concurrently mixing memory behaviors, and the performance gains attainable via noncoherence. Other program classes tolerate weak memory consistency by synchronizing in such a way as to yield executions indistinguishable from coherent ones. AIM computations on noncoherent memory yield noncoherent, yet correct, computations. We present performance data that illustrate the benefits of noncoherence, in terms of raw memory performance, as well as application speed.