Miracle-dz/UniFAR-FTUs huggingface dataset:
A balanced energy consumption clustering algorithm for heterogeneous energy wireless sensor networks

In this paper, a balanced energy consumption clustering algorithm (BECC) is proposed. This new scheme is a cluster-based algorithm designed for heterogeneous energy wireless sensor networks. A polarized energy factor is introduced to adjust the probability with which each node may become a cluster head in the election of the new clustering scheme. Under the condition that the expected number of cluster heads in the network preserves the theoretical optimal number, BECC makes sure that nodes with higher residual energy will become cluster heads with higher probabilities while nodes with lower residual energy will not become cluster heads. Simulation results show that this new scheme provides longer lifetime than the classical clustering algorithms including LEACH and other improved algorithms in heterogeneous networks, and BECC also reaches larger amount of messages received at the sink.
The Hand1 and Hand2 transcription factors regulate expansion of the embryonic cardiac ventricles in a gene dosage-dependent manner

The basic helix-loop-helix transcription factors Hand1 and Hand2 display dynamic and spatially restricted expression patterns in the developing heart. Mice that lack Hand2 die at embryonic day 10.5 from right ventricular hypoplasia and vascular defects, whereas mice that lack Hand1 die at embryonic day 8.5 from placental and extra-embryonic abnormalities that preclude analysis of its potential role in later stages of heart development. To determine the cardiac functions of Hand1, we generated mice harboring a conditional Hand1-null allele and excised the gene by cardiac-specific expression of Cre recombinase. Embryos homozygous for the cardiac Hand1 gene deletion displayed defects in the left ventricle and endocardial cushions, and exhibited dysregulated ventricular gene expression. However, these embryos survived until the perinatal period when they died from a spectrum of cardiac abnormalities. Creation of Hand1/2 double mutant mice revealed gene dose-sensitive functions of Hand transcription factors in the control of cardiac morphogenesis and ventricular gene expression. These findings demonstrate that Hand factors play pivotal and partially redundant roles in cardiac morphogenesis, cardiomyocyte differentiation and cardiac-specific transcription.
Meaningful Activity and Adaptation to Spinal Cord Injury: An Empirical Investigation of a Cognitive-Existential Measure

Objective: To examine a measure of meaningful activity and purpose attributions for predicting disability outcome in adults with spinal cord injury (SCI). Study Design: Cross-sectional survey correlational design using multiple regression to examine the relationship between the meaningful activity scale and other disability outcome measures. Participants: Adults with spinal cord injury living independently in a community setting (n = 73). Main Outcome Measures: Sense of Coherence, the Centers for Epidemiological Studies of Depression Scale, the Hope Scale, the Health Promoting Lifestyle Inventory and the Life Satisfaction Scale. Results: Significant and substantial variation in each of the outcome measures was attributable to the purpose attribution subscale of the meaningful activity scale. Concurrent validity with both the Sense of Coherence Meaningfulness subscale and the Health Promoting Lifestyle Inventory Personal Growth Orientation subscale was good. Conclusions: The Meaningful Activity Scale provides an alternative approach to assessing disability outcome and quality of life. The cognitive existential conceptual model for the measurement instrument may be useful for developing interventions to help adults with SCI improve their long-term adaptation and outcome following injury.
Advances in noise‐based testing of concurrent software

Testing of concurrent software written in programming languages like Java and C/C++ is a highly challenging task owing to the many possible interactions among threads. A simple, cheap, and effective approach that addresses this challenge is testing with noise injection, which influences the scheduling so that different interleavings of concurrent actions are witnessed. In this paper, multiple results achieved recently in the area of noise‐injection‐based testing by the authors are presented in a unified and extended way. In particular, various concurrency coverage metrics are presented first. Then, multiple heuristics for solving the noise placement problem (i.e. where and when to generate noise) as well as the noise seeding problem (i.e. how to generate the noise) are introduced and experimentally evaluated. In addition, several new heuristics are proposed and included into the evaluation too. Recommendations on how to set up noise‐based testing for particular scenarios are then given. Finally, a novel use of the genetic algorithm for finding suitable combinations of the many parameters of tests and noise techniques is presented. Copyright © 2014 John Wiley & Sons, Ltd.
On the Feasibility of Moderating a Peer-to-Peer CDN System: A Proof-of-Concept Implementation

Content Delivery Network (CDN) Systems share many similarities with On-line Markets (OM), since they both provide a way to acquire something (be it information or a physical good) whose quality needs to be certified in order to provide consumer protection. In most common implementations the quality is guaranteed by a central node that provides moderation but also constitutes a bottleneck, a single point of failure and requires a significant amount of dedicated resources (both in hardware and in staffing). In this paper, we study the feasibility of a fully distributed, peer-to-peer based CDN system capable at the same time to provide quality guarantees about the content through well-defined, authenticated and enforced roles. We describe how to build such a structure leveraging bit-coin block-chains, cryptographic accumulators and the bit-torrent network, we describe a use case of such a structure to prove its usefulness, and finally we provide a proof-of-concept implementation.
Inclusionary policy and marginalised groups in Aoteaora/New Zealand process, impacts and politics

ABSTRACT This paper presents the consolidated findings of a four-year research project that evaluated policy inclusion between the New Zealand government and communities of difference – specifically, ethnic/migrant/refugee groups, women/gender and Māori. Policy inclusion builds on foundational principles of deliberative democracy that dialogue and relationship not only improve policy but also foster democratic transitions towards pluralism and diversity. Although associated with the social democratic agenda of the Fifth Labour government, collaborative policymaking with marginalised groups continued in the subsequent National government. Drawing on interviews with policy communities, this paper analyses (a) the processes of inclusionary policymaking, (b) policy impacts and (c) implications for politics of difference. The findings suggest that, overall, the greatest efforts in inclusive policy have been at the level of design, primarily by maximising the presence of members and promoting visibility for communities of difference. These processes have had less impact on sustained, deep political transformations or opportunities for advancing diversity. The findings suggest that inclusionary policymaking had benefits for recognition politics, but against the backdrop of recent neo-conservatism, the prospects for pluralistic politics have been compromised, paving instead a politics of regulation.
A novel vector space model for tree based concept similarity measurement

The attribute based vector space model generalizes standard representations of similarity concept in terms of tree architecture. In the model, every concept in the hierarchical tree has its collections of attributes including common and distinctive parts, and the probability of the attributes attached to the concept. A concept is represent as an attribute based vector space, and the similarity is described as feature matching process with cosine similarity measure. The model contains node depth information, node density information of the tree architecture inherent and hidden in it, we show that this measure compares favorably to other measures. This measure is flexible in that it can make comparisons between any two concepts in a hierarchical tree without regard to corpus and dictionary information.
Different Approaches to Groups and Key Person Identification in Blogosphere

Two approaches for identifying key persons in the blogosphere-based social network are analysed in the paper: discovery of the most important individuals either in persistent or in global social communities existing on web blogs. A new method for the separation of stable groups fulfilling given conditions is presented. Additionally, a new concept for extraction of user roles and key persons in such groups is proposed. It has been compared to the general clustering method and structural node position measure applied to rank users in the time-aggregated data. Experimental, comparative studies have been conducted on real blogosphere data gathered over one year.
A design automation tool for low-power signal filters for use in sensor interfaces

This paper presents a design automation tool for the generation of signal filters for low-power applications. The tool requires a set of functional filter specifications and generates an optimized circuit for filters in a wide range of frequencies. Auxiliary circuits (biasing circuits, common-mode feedback) are also sized and integrated with the main circuit. The tool allows the addition of new types of components and the modification of existing ones. It works with different technologies. Two filters are designed using the tool. Simulation results indicate that the filter tool has the desired functionality.
Novel Nano-Sized MR Contrast Agent Mediates Strong Tumor Contrast Enhancement in an Oncogene-Driven Breast Cancer Model

The current study was carried out to test the potential of a new nanomaterial (Spago Pix) as a macromolecular magnetic MR contrast agent for tumor detection and to verify the presence of nanomaterial in tumor tissue. Spago Pix, synthesized by Spago Nanomedical AB, is a nanomaterial with a globular shape, an average hydrodynamic diameter of 5 nm, and a relaxivity (r1) of approximately 30 (mM Mn)−1 s−1 (60 MHz). The material consists of an organophosphosilane hydrogel with strongly chelated manganese (II) ions and a covalently attached PEG surface layer. In vivo MRI of the MMTV-PyMT breast cancer model was performed on a 3 T clinical scanner. Tissues were thereafter analyzed for manganese and silicon content using inductively coupled plasma-atomic emission spectroscopy (ICP-AES). The presence of nanomaterial in tumor and muscle tissue was assessed using an anti-PEG monoclonal antibody. MR imaging of tumor-bearing mice (n = 7) showed a contrast enhancement factor of 1.8 (tumor versus muscle) at 30 minutes post-administration. Contrast was retained and further increased 2–4 hours after administration. ICP-AES and immunohistochemistry confirmed selective accumulation of nanomaterial in tumor tissue. A blood pharmacokinetics analysis showed that the concentration of Spago Pix gradually decreased over the first hour, which was in good agreement with the time frame in which the accumulation in tumor occurred. In summary, we demonstrate that Spago Pix selectively enhances MR tumor contrast in a clinically relevant animal model. Based on the generally higher vascular leakiness in malignant compared to benign tissue lesions, Spago Pix has the potential to significantly improve cancer diagnosis and characterization by MRI.
A uniform framework for approximating weighted connectivity problems

We introduce a new algorithmic technique that applies to several graph connectivity problems. Its power is demonstrated by experimental studies of the minimum-weight strongly-connected spanning subgraph problem and the minimum-weight augmentation problem. Even though we are unable to improve the approximation ratios for these problems, OUT studies indicate that the new method generates significantly better solutions than the current known approximation algorithms, and yields solutions very close to optimal. We believe that our technique will eventually lead to algorithms that improve the performance ratios as well.
Assessing anosognosia: a critical review

Anosognosia is a multi-factorial syndrome whose clinical manifestations can vary considerably from patient to patient. Considering the complexity of this syndrome, its assessment represents a major challenge for the diagnostic process, and presents various methodological complications. Lack of agreement about diagnostic criteria, high exclusion rates of specific patient categories, assessment limited to certain aspects of unawareness, and the lack of normative data and methodologically robust tools may have led to contrasting, or apparently contrasting, interpretations of this syndrome. Despite the apparently greater sensitivity of the last generation of anosognosia studies to many of these issues, many aspects are still overlooked. In this manuscript, we critically review the literature on the assessment of anosognosia, mainly focusing on motor and language deficits, with a note on the issue of awareness for memory deficits.
Deconvolution of Poisson Images in Bayesian Domain Using Fuzzy Median Filter S

The inverse problem associated with reconstruction of Poisson blurred images arising from many fields ranging from engineering to medicine has attracted much attention in the recent years. Digital images captured at medium to low light levels are often corrupted by sensor noise which is dominated by Poisson statistics. The zoom optics, sensor PSF and atmospheric turbulence cause blurring in acquired images. In this paper, we propose to address the problem of reconstruction of Poisson blurred images captured by surveillance imaging / digital photography in Bayesian domain using fuzzy median filter as a Gibbs prior. The addition of prior information makes the problem well-posed and aids to distinguish between an edge and noisy pixels thereby effects noise filtering. The performance of the proposed algorithm at several intensity levels have been studied qualitatively and quantitatively using mean absolute error (MAE) and Universal Quality Index (UQI) as metrics. The results are compared with other state-of-the-art approaches.
Genetic Adaptive and Supervisory Control

A genetic algorithm (GA) uses the principles of evolution, natural selection, and genetics to offer a method for parallel search of complex spaces. Motivated by past work using the GA as a tool for off-line computer-aided-design of control systems, we introduce several ways to use the GA for on-line identification and controller tuning. In particular, we introduce two new, but closely related approaches to genetic adaptive control which we call “genetic model based control” (GMBC) and “genetic model reference adaptive control” (GMRAC). In these techniques a GA manipulates a set (population) of parameterized controllers in order to evolve the controller most capable of providing good performance for the current plant operating conditions. Next, we introduce a hierarchical GA-based supervisory controller (GASC) that seeks to evolve the GMRAC’s fitness evaluation procedure so that the controllers chosen by GMRAC guide the system towards reduced error and decreased use of control energy. The use of GASC removes the need for the designer to specify GMRAC parameters. In addition, we show how GA-based estimation (GAE) can be used to evolve a model of the plant that is used in the model based controllers GMBC and GMRAC. A cargo ship steering problem is used throughout this paper as a theme example to illustrate each of the genetic adaptive control concepts and techniques.
Symmetry Based Chinese Ancient Architecture Reconstruction from Incomplete Point Cloud

In this paper, we propose a novel method to reconstruct Chinese ancient architecture from incomplete point cloud obtained from multi-view reconstruction approach. The proposed method utilizes both global symmetry and partial symmetry to complete the missing part in the original point cloud. First global symmetry is extracted automatically and a matching cost function based on the images associated with each point is introduced to accelerate the extraction. Then we propose a tool which allows the user to interactively fill the holes by exploring the partial symmetries in the original point set. Our experiments demonstrate the effectiveness of our algorithm.
Waiting for (African) Cinema: Jean-Pierre Bekolo’s Quest

Abstract: Throughout his career, Cameroonian director Jean-Pierre Bekolo has been searching for cinema; not African cinema, just Cinema. In order to explain properly this claim, the essay will first consider Bekolo’s work within the context of the ever-ongoing conversation regarding the framing and aesthetics of African and Third Cinemas. Second, for a closer perspective on what will be termed “neurotic cinema,” the essay will key on Bekolo’s latest effort, Naked Reality (2016), a purposely unfinished work that echoes absurdist theater, mimics frantic contemporary thought, and proposes that cinema should not yield finalized products because that may go against its very nature. Résumé: Tout au long de sa carrière, le réalisateur camerounais Jean-Pierre Bekolo recherche le cinéma ; pas le cinéma africain, seulement le cinéma. Afin d’expliquer correctement cette affirmation, l’essai va d’abord examiner le travail de Bekolo dans le contexte d’une conversation toujours en cours concernant le cadrage et l’esthétique de L ’Afrique et du Troisième Cinémas. Deuxièmement, pour une perspective plus proche de ce qu’on appellera « cinéma névrotique », l’essai portera sur le dernier effort de Bekolo, Réalité Nue (2016), une œuvre volontairement inachevée qui reprend le théâtre de l’absurde, imite la pensée contemporaine frénétique et propose que le cinéma ne doit pas donner un produit finis parce que cela peut aller à l’encontre de sa nature.
Floor sensing system using laser range finder and mirror for localizing daily life commodities

This paper proposes a new method of measuring position of daily commodities placed on a floor. Picking up an object on a floor will be a typical task for a robot working in our daily life environment. However, it is difficult for a robotic vision to find a small daily life object left on a large floor. The floor surface may have various texture and shadow, while other furniture may obstruct the vision. Various objects may also exist on the floor. Moreover, the surface of the object has various optical characteristics: color, metallic reflection, transparent, black etc. Our method uses a laser range finder (LRF) together with a mirror installed on the wall very close to floor. The LRF scans the laser beam horizontally just above the floor and measure the distance to the object. Some beams are reflected by the mirror and measure the distance of the object from virtually different origin. Even if the LRF fails two measurements, the method calculates the position of the object by utilizing information that the two measurements are unavailable. Thus, the method achieves two major advantages: 1) robust against occlusion and 2) applicable to variety of daily life commodities. In the experiment, success rate of observation of our method achieves 100% for any daily commodity, while that of the existing method for a cell-phone is 69.4%.
How Much Overtesting Is Needed to Safely Exclude a Diagnosis? A Different Perspective on Triage Testing Using Bayes' Theorem

Ruling out disease often requires expensive or potentially harmful confirmation testing. For such testing, a less invasive triage test is often used. Intuitively, few negative confirmatory tests suggest success of this approach. However, if negative confirmation tests become too rare, too many disease cases could have been missed. It is therefore important to know how many negative tests are needed to safely exclude a diagnosis. We quantified this relationship using Bayes’ theorem, and applied this to the example of pulmonary embolism (PE), for which triage is done with a Clinical Decision Rule (CDR) and D-dimer testing, and CT-angiography (CTA) is the confirmation test. For a maximum proportion of missed PEs of 1% in triage-negative patients, we calculate a 67% 'mandatory minimum' proportion of negative CTA scans. To achieve this, the proportion of patients with PE undergoing triage testing should be appropriately low, in this case no higher than 24%. Pre-test probability, triage test characteristics, the proportion of negative confirmation tests, and the number of missed diagnoses are mathematically entangled. The proportion of negative confirmation tests—not too high, but definitely not too low either—could be a quality benchmark for diagnostic processes.
Flexible Soft Frequency Reuse Schemes for Heterogeneous Networks (Macrocell and Femtocell)

A mass deployment of femtocells is anticipated to affect a number of areas more adversely, especially in the cell-edge of the macrocell network. In this paper, we propose a flexible frequency-partitioning scheme for OFDMA network based on cyclic difference sets. The cyclic property of these sets allows a quick construction of orthogonal patterns for the macrocell network with an emphasis on tri-sector sites. The impact and the co-deployment of femtocells is also investigated. Unlike, with existing works in the literature, the novel scheme can adaptively control the level of coverage in the cell-edges areas and additionally enables coexistence of femtocells in the network. Simulation results confirm the effectiveness of the proposed scheme in both macrocell and femtocell networks compared to the legacy soft frequency reuse and universal frequency reuse.
An improved sink particle algorithm for SPH simulations

Numerical simulations of star formation frequently rely on the implementation of sink particles, (a) to avoid expending computational resource on the detailed internal physics of individual collapsing protostars, (b) to derive mass functions, binary statistics and clustering kinematics (and hence to make comparisons with observation), and (c) to model radiative and mechanical feedback; sink particles are also used in other contexts, for example to represent accreting black holes in galactic nuclei. We present a new algorithm for creating and evolving sink particles in SPH simulations, which appears to represent a significant improvement over existing algorithms – particularly in situations where sinks are introduced after the gas has become optically thick to its own cooling radiation and started to heat up by adiabatic compression. (i) It avoids spurious creation of sinks. (ii) It regulates the accretion of matter onto a sink so as to mitigate non-physical perturbations in the vicinity of the sink. (iii) Sinks accrete matter, but the associated angular momentum is transferred back to the surrounding medium. With the new algorithm – and modulo the need to invoke sufficient resolution to capture the physics preceding sink formation – the properties of sinks formed in simulations are essentially independent of the user-defined parameters of sink creation, or the number of SPH particles used.