Miracle-dz/UniFAR-FTUs huggingface dataset:
Promises Kept, Promises Broken: An Axiomatic and Quantitative Treatment of Fulfillment

In this paper, we propose a theoretical framework within which to evaluate the reliability of promises that an agent makes, based on past performance of the agent. Our framework does not just propose one such measure, but defines axioms that govern the choice of measure. The framework is able to account for partial fulfillment of promises, late fulfillment of promises, fulfillment of variants of promises, and the like. Within this framework, we propose some specific measures to evaluate promises made by agents and develop algorithms to compute these efficiently. We tested our methods on a real world data set of airline flight information and show that our methods are both accurate and quickly computable, even on large data sets.
Determination of DPD Model Aiming Biomedical Application

The application of the Metropolis Monte Carlo method to the optimization of the repulsion parameter in Dissipative Particle Dynamics (DPD) simulation of nano-particle coated with dextran particle which is a contrast agent for MR and will be applied as a carrier in Drug Delivery System was discussed. In the method where several molecules are included in one DPD bead, conventional procedure doesn’t give adequate interaction parameters. By using the alternative parameters based on proposed modified sampling method, corresponding simulation gave more proper results reproducing available experimental data.
Thermodynamic studies of a series of homologous HIV-1 TAR RNA ligands reveal that loose binders are stronger Tat competitors than tight ones

RNA is a major drug target, but the design of small molecules that modulate RNA function remains a great challenge. In this context, a series of structurally homologous ‘polyamide amino acids’ (PAA) was studied as HIV-1 trans-activating response (TAR) RNA ligands. An extensive thermodynamic study revealed the occurence of an enthalpy–entropy compensation phenomenon resulting in very close TAR affinities for all PAA. However, their binding modes and their ability to compete with the Tat fragment strongly differ according to their structure. Surprisingly, PAA that form loose complexes with TAR were shown to be stronger Tat competitors than those forming tight ones, and thermal denaturation studies demonstrated that loose complexes are more stable than tight ones. This could be correlated to the fact that loose and tight ligands induce distinct RNA conformational changes as revealed by circular dichroism experiments, although nuclear magnetic resonance (NMR) experiments showed that the TAR binding site is the same in all cases. Finally, some loose PAA also display promising inhibitory activities on HIV-infected cells. Altogether, these results lead to a better understanding of RNA interaction modes that could be very useful for devising new ligands of relevant RNA targets.
Effects of instability training devices on dynamic balance in preschoolers born with biological risk factors

ABSTRACT The aim was to investigate the effects of a six-month balance intervention based on Ayres therapy on dynamic balance in 5–6-year-old preschoolers born with biological risk factors. Sixty-four preschoolers participated in this study, and were assigned to an experimental group (VR, born with risk factors), a control group 1 (KR, born with risk factors) and a control group 2 (KI, born with no risk factors). VR group attended a 30-min balance training two times a week for six months. KR and KI groups followed the regular Physical Education schedule. A beam-walking task was used to measure dynamic balance. Significant distance differences were found for VR group. Balance values of VR group approached to those who did not attend the intervention. Neither results of pre- and post-tests show significant gender differences. Training with instability training devices can be an effective way to improve balance performance for preschoolers with developmental delay.
3D Line Voxelization and Connectivity Control

Voxelization algorithms that convert a 3D continuous line representation into a discrete line representation have a dual role in graphics. First, these algorithms synthesize voxel-based objects in volume graphics. The 3D line itself is a fundamental primitive, also used as a building block for voxelizing more complex objects. For example, sweeping a 3D voxelized line along a 3D voxelized circle generates a voxelized cylinder. The second application of 3D line voxelization algorithms is for ray traversal in voxel space. Rendering techniques that cast rays through a volume of voxels are based on algorithms that generate the set of voxels visited (or pierced) by the continuous ray. Discrete ray algorithms have been developed for traversing a 3D space partition or a 3D array of sampled or computed data. These algorithms produce one discrete point per step, in contrast to ray casting algorithms for volume rendering, which track a continuous ray at constant intervals, and to voxelization algorithms that generate nonbinary voxel values (for example, partial occupancies). Before considering algorithms for generating discrete lines, we introduce the topology and geometry of discrete lines.
Voltage-Dependent Rhythmogenic Property of Respiratory Pre-Bötzinger Complex Glutamatergic, Dbx1-Derived, and Somatostatin-Expressing Neuron Populations Revealed by Graded Optogenetic Inhibition123

Abstract The rhythm of breathing in mammals, originating within the brainstem pre-Bötzinger complex (pre-BötC), is presumed to be generated by glutamatergic neurons, but this has not been directly demonstrated. Additionally, developmental expression of the transcription factor Dbx1 or expression of the neuropeptide somatostatin (Sst), has been proposed as a marker for the rhythmogenic pre-BötC glutamatergic neurons, but it is unknown whether these other two phenotypically defined neuronal populations are functionally equivalent to glutamatergic neurons with regard to rhythm generation. To address these problems, we comparatively investigated, by optogenetic approaches, the roles of pre-BötC glutamatergic, Dbx1-derived, and Sst-expressing neurons in respiratory rhythm generation in neonatal transgenic mouse medullary slices in vitro and also more intact adult perfused brainstem-spinal cord preparations in situ. We established three different triple-transgenic mouse lines with Cre-driven Archaerhodopsin-3 (Arch) expression selectively in glutamatergic, Dbx1-derived, or Sst-expressing neurons for targeted photoinhibition. In each line, we identified subpopulations of rhythmically active, Arch-expressing pre-BötC inspiratory neurons by whole-cell recordings in medullary slice preparations in vitro, and established that Arch-mediated hyperpolarization of these inspiratory neurons was laser power dependent with equal efficacy. By site- and population-specific graded photoinhibition, we then demonstrated that inspiratory frequency was reduced by each population with the same neuronal voltage-dependent frequency control mechanism in each state of the respiratory network examined. We infer that enough of the rhythmogenic pre-BötC glutamatergic neurons also have the Dbx1 and Sst expression phenotypes, and thus all three phenotypes share the same voltage-dependent frequency control property.
An XML Schema-based data integration

the purpose for integration system is to provide a unified, global view to the user over various heterogeneous sources. To answer user queries, a data integration system employs a set of semantic mapping between and mediated schema(global schema) and schemas of data sources(local schema). Such data integration raises main challenging issue:(1)Scheme creations and(2) Schema mappings. In order to address these two fundamental metadata ingredients that are the core of such integration system, we propose a novel approach to integration systems which uses XML schemas based mappings. In this approach, XML Schema allows entertaining manager to manage data models intuitively. XML Schema-based mapping represents the relations between the local schema and global schema. We present the design and implementation of a prototype system based on XML schema.
Reduced Gamma Oscillations in a Mouse Model of Intellectual Disability: A Role for Impaired Repetitive Neurotransmission?

Intellectual disability affects 2–3% of the population; mutations of the X-chromosome are a major cause of moderate to severe cases. The link between the molecular consequences of the mutation and impaired cognitive function remains unclear. Loss of function mutations of oligophrenin-1 (OPHN1) disrupt Rho-GTPase signalling. Here we demonstrate abnormal neurotransmission at CA3 synapses in hippocampal slices from Ophn1 -/y mice, resulting from a substantial decrease in the readily releasable pool of vesicles. As a result, synaptic transmission fails at high frequencies required for oscillations associated with cognitive functions. Both spontaneous and KA-induced gamma oscillations were reduced in Ophn1 -/y hippocampal slices. Spontaneous oscillations were rapidly rescued by inhibition of the downstream signalling pathway of oligophrenin-1. These findings suggest that the intellectual disability due to mutations of oligophrenin-1 results from a synaptopathy and consequent network malfunction, providing a plausible mechanism for the learning disabilities. Furthermore, they raise the prospect of drug treatments for affected individuals.
Semi-supervised Learning of Joint Density Models for Human Pose Estimation

Learning regression models (for example for body pose estimation, or BPE) currently requires large numbers of training examples—pairs of the form (image, pose parameters). These examples are difficult to obtain for many problems, demanding considerable effort in manual labelling. However it is easy to obtain unlabelled examples—in BPE, simply by collecting many images, and by sampling many poses using motion capture. We show how the use of unlabelled examples can improve the performance of such estimators, making better use of the difficult-to-obtain training examples. Because the distribution of parameters conditioned on a given image is often multimodal, conventional regression models must be extended to allow for multiple modes. Such extensions have to date had a pre-set number of modes, independent of the contents of the input image, and amount to fitting several regressors simultaneously. Our framework models instead the joint distribution of images and poses, so the conditional estimates are inherently multimodal, and the number of modes is a function of the joint-space complexity, rather than of the maximum number of output modes. We demonstrate the improvements obtainable by using unlabelled samples on synthetic examples and on a real pose estimation problem, and demonstrate in both cases the additional accuracy provided by the use of unlabelled data.
Chapter 23 Industrial Procurement Auctions

As illustrated in the previous chapters, combinatorial auctions have successfully been applied to various application domains, such as the allocation of airspace system resources (Chapter 20), truckload transportation (Chapter 21) and bus routes (Chapter 22). Industrial procurement is potentially a huge application domain for combinatorial auctions, and it has turned into a topic of interest for software vendors and procurement managers in the B2B domain. A number of applications have been reported, but unfortunately, possibly because of efforts to protect proprietary information and competitive advantages, there is little documentation and public information on details of the design of combinatorial auctions in industrial procurement. The focus of this chapter is on describing current practice in this domain. We will also provide a case study of procurement auctions at Mars, Incorporated in order to illustrate the particularities in this field.
Privacy-Preserving and Regular Language Search Over Encrypted Cloud Data

Using cloud-based storage service, users can remotely store their data to clouds but also enjoy the high quality data retrieval services, without the tedious and cumbersome local data storage and maintenance. However, the sole storage service cannot satisfy all desirable requirements of users. Over the last decade, privacy-preserving search over encrypted cloud data has been a meaningful and practical research topic for outsourced data security. The fact of remote cloud storage service that users cannot have full physical possession of their data makes the privacy data search a formidable mission. A naive solution is to delegate a trusted party to access the stored data and fulfill a search task. This, nevertheless, does not scale well in practice as the fully data access may easily yield harm for user privacy. To securely introduce an effective solution, we should guarantee the privacy of search contents, i.e., what a user wants to search, and return results, i.e., what a server returns to the user. Furthermore, we also need to guarantee privacy for the outsourced data, and bring no additional local search burden to user. In this paper, we design a novel privacy-preserving functional encryption-based search mechanism over encrypted cloud data. A major advantage of our new primitive compared with the existing public key based search systems is that it supports an extreme expressive search mode, regular language search. Our security and performance analysis show that the proposed system is provably secure and more efficient than some searchable systems with high expressiveness.
CSCW, Or What's In A Name? *

The topic of Computer-Supported Cooperative Work (CSCW) has attracted much attention in the last few years. While the field is obviously still in the process of development, there is a marked ambiguity about exactly what is or is not included under its rubric. The lack of a commonly accepted view on the nature of the field may hinder its further development and lead to fractionation. In this paper we set out an approach to CSCW which would provide a more coherent conceptual framework for this area. This paper develops a framework for CSCW suggesting that it should be concerned with the support requirements of cooperative work forms. Other conceptualizations of the field are briefly contrasted in the context of how they view cooperative work. The paper then presents and enlarges on some important issues that we see as vital to the development of usable CSCW systems including support for articulation work and support for cooperation via the construction of a common information space.
Kajian keperluan kerangka pengajaran praktikal subjek elektronik di kolej vokasional

Kertas kerja ini menerangkan berkenaan keperluan pembentukan satu kerangka panduan pengajaran praktikal subjek elektronik di Kolej Vokasional Malaysia yang dipersetujui oleh guru-guru pakar elektronik. Kajian keperluan ini dijalankan adalah berbentuk kajian kuantitatif dan menggunakan soal selidik sebagai medium kajian. Min digunakan sebagai perwakilan data yang diperoleh dan ditunjukkan dalam jadual. Dapatan kajian mendapati bahawa terdapat keperluan merangka satu panduan pengajaran praktikal yang memfokuskan kepada subjek elektronik di Kolej Vokasional.
Mg2+ Extrusion from Intestinal Epithelia by CNNM Proteins Is Essential for Gonadogenesis via AMPK-TORC1 Signaling in Caenorhabditis elegans

Mg2+ serves as an essential cofactor for numerous enzymes and its levels are tightly regulated by various Mg2+ transporters. Here, we analyzed Caenorhabditis elegans strains carrying mutations in genes encoding cyclin M (CNNM) Mg2+ transporters. We isolated inactivating mutants for each of the five Caenorhabditis elegans cnnm family genes, cnnm-1 through cnnm-5. cnnm-1; cnnm-3 double mutant worms showed various phenotypes, among which the sterile phenotype was rescued by supplementing the media with Mg2+. This sterility was caused by a gonadogenesis defect with severely attenuated proliferation of germ cells. Using this gonadogenesis defect as an indicator, we performed genome-wide RNAi screening, to search for genes associated with this phenotype. The results revealed that RNAi-mediated inactivation of several genes restores gonad elongation, including aak-2, which encodes the catalytic subunit of AMP-activated protein kinase (AMPK). We then generated triple mutant worms for cnnm-1; cnnm-3; aak-2 and confirmed that the aak-2 mutation also suppressed the defective gonadal elongation in cnnm-1; cnnm-3 mutant worms. AMPK is activated under low-energy conditions and plays a central role in regulating cellular metabolism to adapt to the energy status of cells. Thus, we provide genetic evidence linking Mg2+ homeostasis to energy metabolism via AMPK.
Violência homicida no nordeste brasileiro: uma refutação às explicações baseadas na desigualdade e na pobreza

A violencia homicida e crescente no Nordeste. De 1996 a 2008 o impacto percentual foi na ordem de 106% nos numeros absolutos, num crescimento linear na serie historica. O Nordeste e conhecido pela desigualdade e pela pobreza. O objetivo central deste trabalho e avaliar o grau de relacao da desigualdade e da pobreza com a violencia homicida. Os dados utilizados foram resgatados do Sistema de Informacao de Mortalidade (SIM/SUS) e do IBGE/IPEADATA.No confronto dos dados de homicidios com as macrovariatas socioeconomicas utilizadas como proxy para desigualdade e pobreza, concluimos que nao ha relacao entre as variaveis, ou seja, refutamos que, no Nordeste em geral, e em Pernambuco em particular, a violencia homicida seja explicada (ou causada) pela desigualdade/pobreza.
Gene Expression Profiling and Secretome Analysis Differentiate Adult-Derived Human Liver Stem/Progenitor Cells and Human Hepatic Stellate Cells

Adult-derived human liver stem/progenitor cells (ADHLSC) are obtained after primary culture of the liver parenchymal fraction. The cells are of fibroblastic morphology and exhibit a hepato-mesenchymal phenotype. Hepatic stellate cells (HSC) derived from the liver non-parenchymal fraction, present a comparable morphology as ADHLSC. Because both ADHLSC and HSC are described as liver stem/progenitor cells, we strived to extensively compare both cell populations at different levels and to propose tools demonstrating their singularity. ADHLSC and HSC were isolated from the liver of four different donors, expanded in vitro and followed from passage 5 until passage 11. Cell characterization was performed using immunocytochemistry, western blotting, flow cytometry, and gene microarray analyses. The secretion profile of the cells was evaluated using Elisa and multiplex Luminex assays. Both cell types expressed α-smooth muscle actin, vimentin, fibronectin, CD73 and CD90 in accordance with their mesenchymal origin. Microarray analysis revealed significant differences in gene expression profiles. HSC present high expression levels of neuronal markers as well as cytokeratins. Such differences were confirmed using immunocytochemistry and western blotting assays. Furthermore, both cell types displayed distinct secretion profiles as ADHLSC highly secreted cytokines of therapeutic and immuno-modulatory importance, like HGF, interferon-γ and IL-10. Our study demonstrates that ADHLSC and HSC are distinct liver fibroblastic cell populations exhibiting significant different expression and secretion profiles.
Channel and noise adaptation via HMM mixture mean transform and stochastic matching

We present a non-linear model transformation for adapting Gaussian mixture HMMs using both static and dynamic MFCC observation vectors to additive noise and constant system tilt. This transformation depends upon a few compensation coefficients which can be estimated from channel distorted speech via maximum-likelihood stochastic matching. Experimental results validate the effectiveness of the adaptation. We also provide an adaptation strategy which can result in improved performance at reduced computational cost compared with a straightforward implementation of stochastic matching.
Accurate Semi-supervised Classification for Graph Data

Most machine learning algorithms require labeled instances as training data; however, not all instances are equally easy to obtain labels for. For example, the best-known papers and/or websites would be easier for a domain expert to label. We propose a new PageRank-style method for performing semi-supervised learning by propagating labels from labeled seed instances to unlabeled instances in a graph using only the link structure. We show that on four real-world datasets, the proposed method, using only a small number of seed instances, gives highly accurate classification results and both outperforms simple content-only baselines and is competitive with state-of-the-art fully supervised algorithms that uses both the content and the link structure. In addition, the method is efficient for large datasets and works well given high-PageRank seeds.
Metadata for Electronic Learning Resources Metapodatki pri elektronskih unih virih

Over the last decades, extensive catalogues and large repositories of educational content have been made available to schools, teachers and students. As the number of resources in these repositories continues to grow, the demand for better identification of resources is increasing: more precise and detailed tagging of resources is needed in order to enable teachers and learners quickly and easily search, find and access the needed learning materials. The problem of identification of resources and consequently more accurate search can be solved by using better and richer metadata. Since creation of needed metadata is long-lasting and complex procedure, approaches how to deal with this issue are presented in this article. Social tagging and automated metadata generation are examples of such approaches. The number of repositories that offer these resources is increasing as well, so extra attention is given to metadata exchange that provides a way to perform federated search. Since exchange between different systems can be made only by using standard formats, an insight of common standards is given as well.