Miracle-dz/UniFAR-FTUs huggingface dataset:
eBUSINESS SCHEME FOR ENGINEERING CONSULTING SERVICES

Despite the availability of ICT tools and infrastructures, civil engineers and design consultants still don't take full advantage in their daily activities of the eBusiness scheme which may open the door of the global market to providers of specialized consulting services. This perspective may allow even small consulting offices to get in contact with potential clients located in any part of the world widening enormously their commercial possibilities. Legal and contractual problems at present still hinder such perspective. The outcome of the combined effort of eLEGAL and ISTforCE projects (both funded by the European Commission under the IST programme), contributed to solve the problems due to lack of infrastructures for remote consulting and legally sound remote business relationships. The concepts and developments resulting from these two projects, which are going to be applied by Geodeco for its specialized consulting services to be offered on-line, are discussed in this paper.
Pattern recognition using interval-valued intuitionistic fuzzy set and its similarity degree

Pattern recognition under fuzzy environments is an interesting and important research topic which has been receiving more and more attention in recent years. Aiming at this kind of pattern recognition problems, fuzzy theories have been applied to the field widely and effectively. Especially interval-valued intuitionistic fuzzy sets (IVIFSs) can give not only a membership degree, but also a non-membership degree, which is more or less independent. Meanwhile the membership degree and non-membership degree are denoted by an interval which makes the IVIFSs can represent the dynamic character of features. Therefore in this paper, depending on IVIFSs and corresponding similarity degree (or distance measure) we construct a kind of novel pattern recognition approach. This approach chooses different weight for each feature according to its dissimilarity with other features. Thus the approach can show the corresponding influence and importance of different features. Finally, we utilize concrete examples to validate the proposed approach.
Phenobarbital Increases Spontaneous Transmitter Release at the Frog Neuromuscular Junction

Phenobarbital (1-2 × 10-4M) markedly increases the frequency of miniature end-plate potentials at the neuromuscular synapse of the frog. This effect was seen in calcium free media containing EGTA. The drug probably acts presynaptically at an intracellular locus to increase the presynaptic free calcium concentration.
Consumption and Social Change in a Post-Soviet Middle Class

What happens when your once-dignified profession no longer supports a dignified lifestyle? In 1990s St. Petersburg, teachers had to find out the hard way. Although the institutions and ideologies of Soviet life situated them as "cultured" consumers, contemporary processes of marketization and privatization left them unable to attain what they now considered to be respectable material standards of living. In this fascinating new ethnographic study, Patico examines the various ways in which teachers have adjusted their activities and interactions as consumers, demonstrating how this has led to dramatic shifts in their assessments of their own lives and of the society around them. Consumption and Social Change in a Post-Soviet Middle Class presents a much-needed look at the lives of ordinary people in Russia today, in the process contributing both to postsocialist studies of social change and to broader anthropological theorizations of consumption and value.
Enabling fast prediction for ensemble models on data streams

Ensemble learning has become a common tool for data stream classification, being able to handle large volumes of stream data and concept drifting. Previous studies focus on building accurate prediction models from stream data. However, a linear scan of a large number of base classifiers in the ensemble during prediction incurs significant costs in response time, preventing ensemble learning from being practical for many real world time-critical data stream applications, such as Web traffic stream monitoring, spam detection, and intrusion detection. In these applications, data streams usually arrive at a speed of GB/second, and it is necessary to classify each stream record in a timely manner. To address this problem, we propose a novel Ensemble-tree (E-tree for short) indexing structure to organize all base classifiers in an ensemble for fast prediction. On one hand, E-trees treat ensembles as spatial databases and employ an R-tree like height-balanced structure to reduce the expected prediction time from linear to sub-linear complexity. On the other hand, E-trees can automatically update themselves by continuously integrating new classifiers and discarding outdated ones, well adapting to new trends and patterns underneath data streams. Experiments on both synthetic and real-world data streams demonstrate the performance of our approach.
Tetrahydrobiopterin improves endothelium-dependent vasodilation in chronic smokers : evidence for a dysfunctional nitric oxide synthase.

Conditions associated with impaired nitric oxide (NO) activity and accelerated atherosclerosis have been shown to be associated with a reduced bioavailability of tetrahydrobiopterin (BH4). We therefore hypothesized that BH4 supplementation may improve endothelial dysfunction of chronic smokers. Forearm blood flow (FBF) responses to the endothelium-dependent vasodilators acetylcholine (ACh; 0.75, 1.5, and 3.0 microg/100 mL tissue/min) or serotonin (5-HT; 0.7, 2.1, and 6.3 ng/100 mL tissue/min), to the inhibitor of endothelial nitric oxide synthase (NOS) N(G)-monomethyl-L-arginine (L-NMMA; 2, 4, and 8 micromol/min), and to the endothelium-independent vasodilator sodium nitroprusside (SNP; 0.1, 0.3, and 1.0 microg/100 mL tissue/min) were measured by venous occlusion plethysmography in controls and chronic smokers. Drugs were infused into the brachial artery, and FBF was measured before and during concomitant intra-arterial infusion of BH4, tetrahydroneopterin (NH4; another reduced pteridine), or the antioxidant vitamin C (6 and 18 mg/min). In control subjects, BH4 had no effect on FBF in response to ACh, 5-HT, and SNP. In contrast, in chronic smokers, the attenuated FBF responses to ACh and 5-HT were markedly improved by concomitant administration of BH4, whereas the vasodilator responses to SNP were not affected. L-NMMA-induced vasoconstriction was significantly reduced in smokers compared with controls, suggesting impaired basal NO bioactivity. BH4 improved L-NMMA responses in smokers while having no effect on L-NMMA responses in controls. Pretreatment with vitamin C abolished BH4 effects on ACh-dependent vasodilation. In vitro, NH4 scavenged superoxide created by the xanthine/xanthine oxidase reaction equipotent like BH4 but failed to modify ACh-induced changes in FBF in chronic smokers in vivo. These data support the concept that in addition to the free radical burden of cigarette smoke, a dysfunctional NOS III due to BH4 depletion may contribute at least in part to endothelial dysfunction in chronic smokers.
A Generalized Model with Spatial Resources Labels

This paper proposes a generalized model by extending Markov chain with spatial resources labels, which can describe the functional and performance properties and some basic characteristics such as nondeterminacy and randomicity. The syntax and semantics of the new model are shown based on the existing temporal logics such as CSRL and pathCSRL. The model checking procedure is discussed and thus the practicability of the new model is intuitive. Based on the existing models, the proposed model includes spatial resources labels only by adding the spatial information to the existing labels of states, so the treatment of the state explosion problem is similar to that in the existing models.
A Point Mutation in the Gene for Asparagine-Linked Glycosylation 10B (Alg10b) Causes Nonsyndromic Hearing Impairment in Mice (Mus musculus)

The study of mouse hearing impairment mutants has led to the identification of a number of human hearing impairment genes and has greatly furthered our understanding of the physiology of hearing. The novel mouse mutant neurological/sensory 5 (nse5) demonstrates a significantly reduced or absent startle response to sound and is therefore a potential murine model of human hearing impairment. Genetic analysis of 500 intercross progeny localized the mutant locus to a 524 kilobase (kb) interval on mouse chromosome 15. A missense mutation in a highly-conserved amino acid was found in the asparagine-linked glycosylation 10B gene (Alg10b), which is within the critical interval for the nse5 mutation. A 20.4 kb transgene containing a wildtype copy of the Alg10b gene rescued the mutant phenotype in nse5/nse5 homozygous animals, confirming that the mutation in Alg10b is responsible for the nse5/nse5 mutant phenotype. Homozygous nse5/nse5 mutants had abnormal auditory brainstem responses (ABRs), distortion product otoacoustic emissions (DPOAEs), and cochlear microphonics (CMs). Endocochlear potentials (EPs), on the other hand, were normal. ABRs and DPOAEs also confirmed the rescue of the mutant nse5/nse5 phenotype by the wildtype Alg10b transgene. These results suggested a defect in the outer hair cells of mutant animals, which was confirmed by histologic analysis. This is the first report of mutation in a gene involved in the asparagine (N)-linked glycosylation pathway causing nonsyndromic hearing impairment, and it suggests that the hearing apparatus, and the outer hair cells in particular, are exquisitely sensitive to perturbations of the N-linked glycosylation pathway.
Bayesian Decision Fusion for Dynamic Multi-Cue Object Detection

Visual object detection using single cue information has been successfully applied in various tasks, in particular for near range recognition. While robust classification and probabilistic representation enhance 2D pattern recognition performance, they are ’per se’ restricted due to the limited information content of single cues. The contribution of this work is to demonstrate performance improvement using multi-cue information integrated within a probabilistic framework. 2D and 3D visual information naturally complement one another, each information source providing evidence for the occurrence of the object of interest. We demonstrate preliminary work describing Bayesian decision fusion for object detection and illustrate the method by robust detection of traffic infrastructure, and add an extension to integrate belief dynamically from image sequences.
Knowledge-Intensive Business Services (KIBS) as drivers of multilevel knowledge dynamics

KIBS research to date has been conducted mainly by taking an innovation perspective where an explicit focus on knowledge processes is not very well pronounced. The paper intends to make a conceptual contribution to a deeper understanding of the role of KIBS as an industry that produces, uses and transforms knowledge. It focuses on the knowledge dimension and uses evolutionary and organisation-based knowledge approaches to show that KIBS can be identified as drivers of knowledge dynamics in multilevel contexts. Both the specific characteristics of their composite knowledge products and the way these are produced are considered to be responsible for the unique way they foster knowledge dynamics in firm, sector and territorial contexts. By the application of different knowledge dimensions such as types of knowledge bases and domains mainly used to examine knowledge processes and innovation in industrial sectors, the specificities of KIBS to multilevel knowledge dynamics are analysed and discussed.
Solving uncertainty during robot navigation by integrating grid cell and place cell firing based on rat spatial cognition studies

The efficient resolution of spatial localization is a key challenge in autonomous mobile robots. We describe in this paper our latest work in understanding spatial localization based on rat behavioral and neural studies. We develop a grid cell neural model based on studies in the Medial Entorhinal Cortex that integrates to a place cell neural model in the Hippocampus to generate “neural odometry” and spatial localization in the rat. We evaluate the model through simulated and physical robot experiments using a Khepera III autonomous robot in a laboratory environment.
A time-delay digital tanlock loop

A digital tanlock loop (DTL) that utilises a constant time-delay unit instead of the constant 90/spl deg/ phase-shifter is proposed to reduce the complexity of implementation and rid the circuit of the practical problems, approximations and limitations caused by the 90/spl deg/ phase-shifter. The time-delay digital tanlock loop (TDTL) preserves the most important features of the conventional DTL (CDTL) and introduces improvement over the first-order CDTL under suitable choice of the circuit parameters.
VorSLAM: A new solution to simultaneous localization and mapping

This paper presents a new solution to the problem of simultaneous localization and mapping (SLAM). Traditional extended Kalman filter (EKF) based SLAM (EKF-SLAM) algorithms describe unknown environments with simple geometric elements, such as points for landmarks. This limits the EKF-SLAM to environments suited to such models and tends to discard much potentially useful data. The solution proposed in this paper makes use of all the collected data and gives a more detailed description to the environment, which is a combination of EKF-SLAM and scan match. Landmarks are extracted from raw observations and their locations are estimated by using feature based EKF-SLAM. Around each landmark a local dense map of the environment is built. The landmarks and local maps together give a detailed and compact description of the environment. Voronoi division has been used to build local maps. It guarantees the local maps have none overlaps and have a proper metric scale. Experimental result demonstrates the efficiency of the algorithm.
Dietary Polyphenols Promote Growth of the Gut Bacterium Akkermansia muciniphila and Attenuate High-Fat Diet–Induced Metabolic Syndrome

Dietary polyphenols protect against metabolic syndrome, despite limited absorption and digestion, raising questions about their mechanism of action. We hypothesized that one mechanism may involve the gut microbiota. To test this hypothesis, C57BL/6J mice were fed a high-fat diet (HFD) containing 1% Concord grape polyphenols (GP). Relative to vehicle controls, GP attenuated several effects of HFD feeding, including weight gain, adiposity, serum inflammatory markers (tumor necrosis factor [TNF]α, interleukin [IL]-6, and lipopolysaccharide), and glucose intolerance. GP lowered intestinal expression of inflammatory markers (TNFα, IL-6, inducible nitric oxide synthase) and a gene for glucose absorption (Glut2). GP increased intestinal expression of genes involved in barrier function (occludin) and limiting triglyceride storage (fasting-induced adipocyte factor). GP also increased intestinal gene expression of proglucagon, a precursor of proteins that promote insulin production and gut barrier integrity. 16S rRNA gene sequencing and quantitative PCR of cecal and fecal samples demonstrated that GP dramatically increased the growth of Akkermansia muciniphila and decreased the proportion of Firmicutes to Bacteroidetes, consistent with prior reports that similar changes in microbial community structure can protect from diet-induced obesity and metabolic disease. These data suggest that GP act in the intestine to modify gut microbial community structure, resulting in lower intestinal and systemic inflammation and improved metabolic outcomes. The gut microbiota may thus provide the missing link in the mechanism of action of poorly absorbed dietary polyphenols.
Designing Incremental Sigma-Delta ADCs for low Thermal Noise in Image Sensors

Incremental Sigma-Delta (ISD) ADCs are becoming popular in the imaging field mainly due to 2 characteristics: the intrinsic oversampling of the converter which decreases the thermal noise of the pixel source follower and the reduced accuracy required by the analog building blocks. In this paper we present some design guidelines for choosing the appropriate ISD architecture according to the imager design specifications in terms of conversion speed, power consumption and noise. Furthermore, we propose some novel solutions to common ISD design issues, such as modulator reference buffering, which hinder the implementation of this converter type in high speed, high resolution image sensors. Keywords—Incremental Sigma Delta, ADC, low noise, low power, shared opamp, reference buffering, calibration
Toward a Psychology of Person-Environment (PE) Correlation: The Role of Spouse Selection

Identifying the important ways in which attributes of persons correlate with features of the interpersonal environment is perhaps one of the most intriguing issues facing the development of an interactional psychology. Little empirical progress has yet been made, however, in documenting the domains within which person-environment (PE) correspondence occurs, in identifying the mechanisms by which such correspondence is brought about, and in exploring the consequences of obtained correspondence. One hypothesis of this article is that nonrandom spouse selection (assortative marriage) is one mechanism by which correspondences between persons and their interpersonal environments are created. An empirical study of 93 married couples examined spouse correlations within eight interpersonal categories (e.g., dominance, submissivness, extraversion) by using self and observer reports of the performance frequencies of 800 acts. Substantial spouse correspondence was found, particularly for the domains of extraversion, dominance, quarrelsomeness, and ingenuousness. In addition, changes in degree of spouse correspondence were associated with length of marital relationship. Discussion focuses on different types of PE correspondence, implications for the study of adult personality development, and the emergence of a psychology of PE correlation.
Towards a structured unified process for software security

Security is often an afterthought when developing software, and is often bolted on late in development or even during deployment or maintenance, through activities such as penetration testing, add-on security software and penetrate-and patch maintenance. We believe that security needs to be built in to the software from the beginning, and that security activities need to take place throughout the software lifecycle. Accomplishing this effectively and efficiently requires structured approach combining a detailed understanding on what causes vulnerabilities, and how specific activities combine to prevent them.In this paper we introduce key elements of the approach we are taking: vulnerability cause graphs, which encode information about vulnerability causes, and security activity graphs, which encode information about security activities. We discuss how these can be applied to design software development processes (or changes to processes) that eliminate software vulnerabilities.
Proposal : Self-reconfigurable Robot Systems

Self-reconfigurable robots are robots composed of many physically connected modules which can change their structural configuration to support multiple functionalities. The modules may be complete robots in themselves capable of performing some tasks without cooperation, or they may be units which are functional only when some minimum number of modules are present. Modules create structures by attaching themselves to static objects or to each other. We claim that self-reconfigurable robots are more versatile, extensible, and reliable than conventional fixed-architecture robots. In this thesis proposal we describe two different self-reconfigurable robot systems. One system is based on the Inchworm robot, a small mobile robot which can perform independent navigation and manipulation tasks and can also cooperate to create structures with expanded functionality. The second system is based on our recently developed Molecule robot. Molecules are simple robots which cannot act as independent units but can cooperate to form three-dimensional structures which can move using selfreconfiguration. We discuss the scientific challenges of these systems, present a proposal for future thesis work, and describe the current status of our research.
Distributed System Security via Logical Frameworks

We describe a project to advance security in distributed systems via the application of logical frameworks. At the heart of the effort lies an authorization logic which plays a triple role: (1) to specify an access-control policy as a logical theory, (2) to enforce the policy by mechanically verifying proofs in the logic, and (3) to reason about the policy by characterizing the space of all possible proofs. We are deploying a security infrastructure based on these ideas using mobile phones as a universal access-control device at Carnegie Mellon University. ACM subject classifiers: C.2. 0 General—Security and protection; D.4. 6 Security and Protection—Access controls; F.4. 1 Mathematical Logic—Computational Logic; K.6. 5 Security and Protection—Authentication
Discovering Temporal Relations with

Temporal information plays an important role in many NLP applications. The identification of temporal relations between temporal entities (events and temporal expressions) is indispensable in obtaining the temporal interpretation of a given text. This paper presents our approach for discovering temporal relations using the temporal annotation system we have developed. This system is called TICTAC (Syntactico-Semantic Temporal Annotation Cluster) and it comprises both knowledge based and statistical techniques. It has achieved the best performance among all systems participating at the TempEval competition organised as part of SemEval-2007, competition that evaluated temporal relation identification capabilities.
Video Completion as Noise Removal

(cid:151)Video completion algorithms have concentrated on obtaining visually consistent solutions to (cid:2)ll-in the missing portions, without any emphasis on the physical correctness of the video. Resulting solutions thus use texture or image structure based cues and are limited in the situations they can handle. In this paper we take a model based signal processing approach to video completion [1]. Completion of the video is then de(cid:2)ned as satisfying the given model by detecting and removing the error (selected parts of the video to be replaced). Given a probabilistic model, video completion then becomes an unsupervised learning algorithm with the input video giving a (cid:147)noisy(cid:148) version. Dense completion is the automatic inferencing of the (cid:147)noise-less(cid:148) or (cid:147)true(cid:148) video from the input. This approach (cid:2)nds a solution that satis(cid:2)es visual coherence and is applicable to a wide variety of scenarios. We demonstrate the ef(cid:2)cacy of our approach and its wide applicability using two scenarios.