Miracle-dz/UniFAR-FTUs huggingface dataset:
Three-dimensional shape reconstruction by active rangefinder

A new type of rangefinder is proposed, and a method for 3-D object shape reconstruction is described. The proposed rangefinder is compact and light and consists of a charge-coupled device camera, a galvano mirror, and a semiconductor laser. A slit-ray from the laser is scanned by the mirror and patterns of light are made by temporal switching of the laser. Range maps are obtained by the space encoded technique. A 512/spl times/256 range map is captured within 0.3 s. The rangefinder is installed at a tip of a robot manipulator, and takes range maps from various directions. Experimental results are described for range map integration and 3-D shape reconstruction. <<ETX>>
Maximizing Network Capacity of Cognitive Radio Networks by Capacity-Aware Spectrum Allocation

In this paper, we present a novel capacity-aware spectrum allocation model for cognitive radio networks. First, we model interference constraints based on the interference temperature model, and let the secondary users (SUs) increase their transmission power until the interference temperature on one of their neighbors exceeds its interference temperature threshold. Then, knowing the SINR and bandwidth of potential links, we calculate the link capacity based on the Shannon formula, and model the co-channel interference between potential links on each channel by using an interference graph. Next, we formulate the spectrum assignment problem in the form of a binary integer linear programming (BILP) to find the optimal feasible set of simultaneously active links among all the potential links in the sense of maximizing the overall network capacity. We also propose a new radix tree based algorithm that, by removing the sparse areas in the search space, leads to a considerable decrease in time complexity of solving the spectrum allocation problem as compared to the BILP algorithm. The simulation results have shown that this proposed model leads to a considerable improvement in overall network capacity as compared to genetic algorithm, and leads to a considerable decrease in time duration needed to find the optimal solution as compared to the BILP algorithm.
Adaptive active contour model based automatic tongue image segmentation

For about 1800 years, tongue inspection has been one of the four major diagnostic methods in Traditional Chinese Medicine (TCM). The tongue is believed to be able to reflect the health status of the human body. However, making an accurate diagnose with the tongue is not a trivial task. It usually requires enormous training on the TCM doctor before he can make a reasonable diagnosis. Recently, image processing methods have been proposed to automatically process the tongue images and make diagnosis. This study proposes a k-means clustering and adaptive active contour model based automatic tongue region segmentation algorithm. This study is the first step towards the automatic tongue diagnosis. The method was applied on a set of real tongue images. To quantitatively evaluate the segmentation results, the automatically extracted boundaries were compared to the tongue boundaries drawn by experts. An average coverage ratio of 92% was found, indicating the accuracy of the proposed algorithm.
Gedankenexperiment for Initial Expansion of the Universe and Effects of a Nearly Zero Inflaton in Pre Planckian Physics Space-Time Satisfying Traditional Slow Roll Formulas Which Happens in Pre Planckian Regimes Even if

We first of all consider what if the initial inflaton was nearly zero instead of proportional to a Planck mass, in a SUSY type potential. Using the construction of Padmanabhan about general inflaton physics and the conditions of what are usual constituent slow roll requirements for inflation, and also of Kolb, Pi and Raby about a SUSY potential, we come up with the counter intuitive formulation of how usual tests for slow roll give the standard answers even if the inflaton in the SUSY potential as given by Kolb, Pi, and Raby is initially zero. The result gives support to a formulation of VEV conditions used right after a Planck instant of time. As it is, we will from first principles examine what adding acceleration does as to the HUP previously derived. In doing so we will be tying it in our discussion with the earlier work done on the HUP. The HUP results, so modified are appropriate for the Pre-Planckian results and may explain why the slow roll formulation as given by Padmanabhan holds where there is the phenomenon of 2 SUSY V φ for Pre-Planckian space-time. This leads to a very paradoxical result that in Pre-Planckian physics the traditional slow roll formulas are satisfied even if 2 SUSY V φ . But it also puts in extremely tight restrictions upon the formulation of the degree of freedom problem, as given in Equation (26) in this document.
Graphical Tools for Linear Structural Equation Modeling

Abstract : This paper surveys graphical tools developed in the past three decades that are applicable to linear structural equation models (SEMs). These tools permit researchers to answer key research questions by simple path-tracing rules, even for highly complex models. They include parameter identification, causal effect identification, regressor selection, selecting instrumental variables, finding testable implications of a given model, identifying equivalent models and estimating counterfactual relationships.
Alveolar Haemorrhage in the Immunocompetent Host: A Scale for Early Diagnosis of an Immune Cause

Background: Diffuse alveolar haemorrhage (DAH) is a life-threatening condition due to immune and non-immune causes. Early identification of an underlying immune disorder is essential in order to initiate appropriate treatment. Objective: The purpose of this study was to identify early predictive factors of an immune cause of DAH. Methods: We conducted a retrospective study of 76 immunocompetent patients with DAH to identify early predictive factors of immune-related DAH using clinical, radiological and routine biological data available in the first 24 h after hospital admission. Results: Multivariate analysis identified 4 parameters which were independently associated with immune-related DAH: (1) onset of first respiratory symptoms ≧11 days, (2) fatigue and/or weight loss during the month prior to presentation, (3) arthralgias or arthritis and (4) proteinuria ≧1 g/l. A simplified scale was constructed using these variables, with an area under the receiver operating characteristic curve of 0.913, for the diagnosis of immune-related DAH. Conclusions: A simple diagnostic scale can be used to identify an immune-related cause of DAH in immunocompetent patients and may help guide treatment decisions such as initiation of steroid therapy on the day of admission.
Synthesis of unsymmetric diphospho-inositol polyphosphates.

The phosphate esters of myo-inositol (1) have long been recognized as molecules of tremendous biological relevance in cellular signaling events. Given the already high complexity of the inositol signaling cascade, a striking discovery was that inositol hexakisphosphate InsP6 can be further phosphorylated by inositolhexakisphosphate kinases (IP6K) to pyrophosphorylated representatives such as 5-diphosphoinositol-1,2,3,4,6-pentakisphosphate 5-PP-InsP5. [2] Different positional isomers of diphospho-inositol polyphosphates (XPP-InsP5, for example, 2–5) have been discovered and were found to occur in all domains of biology ranging from archaea to mammals. Highly conserved enzymes tightly regulate their production and destruction.
α-Costic anhydride

The title compound [systematic name: 2-(4a,8-dimethyl-1,2,3,4,4a,5,6,8a-octahydronaphthalen-2-yl)acrylic acid anhydride], C30H42O3, is a new isocostic anhydride which was synthesized from the aerial part of Inula Viscosa (L) Aiton [or Dittrichia Viscosa (L) Greuter]. The molecule adopts an essentially linear shape with two terminal fused-rings bridged by the anhydride group. The external rings have the same conformation (half-chair) while each of the two inner rings has an almost ideal chair conformation. In the crystal, intermolecular C—H⋯O interactions link the molecules into a two-dimensional array in the bc plane.
A stakeholder-centric software architecture analysis approach

At Nortel’s Software Engineering Analysis Lab, a modelling technique was developed, when applied with SAAM ensures the rigor required for ensuring that stakeholder objectives are explicitly addressed and traced. Our model is practical in representing and validating software architectures across multiple stakeholders. The model serves as our engine for analysis and provides continuity for the assets generated and evolved throughout the software lifecycle .
How to Train a Cell–Cutting-Edge Molecular Tools

In biological systems, the formation of molecular complexes is the currency for all cellular processes. Traditionally, functional experimentation was targeted to single molecular players in order to understand its effects in a cell or animal phenotype. In the last few years, we have been experiencing rapid progress in the development of ground-breaking molecular biology tools that affect the metabolic, structural, morphological, and (epi)genetic instructions of cells by chemical, optical (optogenetic) and mechanical inputs. Such precise dissection of cellular processes is not only essential for a better understanding of biological systems, but will also allow us to better diagnose and fix common dysfunctions. Here, we present several of these emerging and innovative techniques by providing the reader with elegant examples on how these tools have been implemented in cells, and, in some cases, organisms, to unravel molecular processes in minute detail. We also discuss their advantages and disadvantages with particular focus on their translation to multicellular organisms for in vivo spatiotemporal regulation. We envision that further developments of these tools will not only help solve the processes of life, but will give rise to novel clinical and industrial applications.
AffectiView: mobile video camera application using physiological data

In recent years, devices such as smartphones have made it increasingly easier for people to capture videos and then share those videos on Social Networking Services. Shared videos are able of representing almost all emotional experiences, such as interest, astonishment and excitement. However, it is difficult for people who have little knowledge concerning professional video shooting to express these experiences using only video. To address this issue, we developed AffectiView -- a mobile video camera application that captures users' affective responses while they are capturing videos, and also provides a way for sharing that data with other users. In this System, affective responses are measured using physiological proxies. We have organized into three styles the representation of physiological signals between users found in prior works. This system provides video shooters' emotional experiences to viewers by applying each of these three styles to the captured video. A preliminary user study has revealed the positive effects of capturing and sharing physiological signals together with video.
A Reinforcement Learning Approach for Adaptive Query Processing

In adaptive query processing, query plans are improved at ru ntime by means of feedback. In the very flexible approach based on so-called eddies, query executio n is treated as a process of routing tuples to the query operators that combine to compute a query. This mak es it possible to alter query plans at the granularity of tuples. Further, the complex task of searchi ng the query plan space for a suitable plan now resides in the routing policies used. These policies must ad apt to the changing execution environment and must converge at a near-optimal plan when the environmen t stabilizes. This paper advances adaptive query processing in two respec ts. First, it proposes a general framework for the routing problem that may serve the same role for a daptive query processing as does the framework of search in query plan space for conventional que ry processing. It thus offers an improved foundation for research in adaptive query processing. The f ramework leverages reinforcement learning theory and formalizes a tuple routing policy as a mapping fro m a state space to an action space, capturing query semantics as well as routing constraints. In effect, t he framework transforms query optimization from a search problem in query plan space to an unsupervised l earning problem with quantitative rewards that is tightly coupled with the query execution. The f ramework covers selection queries as well as joins that use all proposed join execution mechanisms (SH Js, SteMs, STAIRs). Second, in addition to showing how existing routing policies can fit into the fram ework, the paper demonstrates new routing policies that build on advances in reinforcement learning. By means of empirical studies, it is shown that the proposed policies embody the desired adaptivity an d co vergence characteristics, and that they are capable of clearly outperforming existing policies.
Interfacial aspects of carbon composites

Abstract Carbon-based composites bring great promise for various practical applications ranging from aviation industry to advanced biomedical sensors. The interface chemistry and the ultimate conductivity of these composites are responsible for their functional applicability. The interfaces can be modified by various chemical and physical techniques. This article reviews the synthesis methods of carbon composites and discusses how the interface properties dictate their applicability.
A Comparative Evaluation of Five Obturation Techniques in the Management of Simulated Internal Resorptive Cavities: An Ex Vivo Study

Background: Root resorption is the loss of dental hard tissues as a result of clastic activities. It might be broadly classified into external or internal resorption by the location of the resorption in relation to the root surface. the various techniques used these days for filling internal resorption include warm condensation, vertical condensation, core techniques, thermoplasticized gutta-percha, warm vertical compaction, and cold lateral condensation. Objectives: The aims and objectives of this study were to compare the quality of root fillings in artificially created internal resorption cavities filled with warm vertical compaction, lateral condensation, Obtura II along with System B, E and Q plus along with System B, and Thermafil, and to calculate the percentage of gutta-percha, sealer, and voids using an ImageJ software. Results: Results between the warm vertical compaction (group I), lateral condensation (group II), Obtura II with System B (group III), E and Q plus with System B (group IV), and Thermafil (group V), group III showed the highest percentage of gutta-percha plus sealer and gutta-percha, and least number of voids, which was statistically significant (P < 0.000). Conclusion: It can be concluded that Obtura II along with System B was found to be the most suitable obturation technique for the management of teeth exhibiting internal resorption. Thermafil was found to give the poorest obturation quality when used to fill the teeth with internal resorption. Similarly, lateral condensation technique was observed to show maximum sealer and hence was not ideal for the management of internal resorptive cavities.
Introducing bioactivity into electrospun scaffolds for in situ cardiovascular tissue engineering

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Parenteral Nutrition–Associated Hyperglycemia in Non–Critically Ill Inpatients Increases the Risk of In-Hospital Mortality (Multicenter Study)

OBJECTIVE Hyperglycemia may increase mortality in patients who receive total parenteral nutrition (TPN). However, this has not been well studied in noncritically ill patients (i.e., patients in the nonintensive care unit setting). The aim of this study was to determine whether mean blood glucose level during TPN infusion is associated with increased mortality in noncritically ill hospitalized patients. RESEARCH DESIGN AND METHODS This prospective multicenter study involved 19 Spanish hospitals. Noncritically ill patients who were prescribed TPN were included prospectively, and data were collected on demographic, clinical, and laboratory variables as well as on in-hospital mortality. RESULTS The study included 605 patients (mean age 63.2 ± 15.7 years). The daily mean TPN values were 1.630 ± 323 kcal, 3.2 ± 0.7 g carbohydrates/kg, 1.26 ± 0.3 g amino acids/kg, and 0.9 ± 0.2 g lipids/kg. Multiple logistic regression analysis showed that the patients who had mean blood glucose levels >180 mg/dL during the TPN infusion had a risk of mortality that was 5.6 times greater than those with mean blood glucose levels <140 mg/dL (95% CI 1.47–21.4 mg/dL) after adjusting for age, sex, nutritional state, presence of diabetes or hyperglycemia before starting TPN, diagnosis, prior comorbidity, carbohydrates infused, use of steroid therapy, SD of blood glucose level, insulin units supplied, infectious complications, albumin, C-reactive protein, and HbA1c levels. CONCLUSIONS Hyperglycemia (mean blood glucose level >180 mg/dL) in noncritically ill patients who receive TPN is associated with a higher risk of in-hospital mortality.
Evolutionary multiobjective optimization and multiobjective fuzzy system design

Evolutionary multiobjective optimization (EMO) is one of the most active research areas in evolutionary computation. EMO algorithms have been successfully used in various application areas. Among them are multiobjective design of neural networks and fuzzy systems. Especially, fuzzy system design has often been discussed as multiobjective problems. This is because we have two conflicting objectives in the design of fuzzy systems: accuracy maximization and complexity minimization. In this paper, we first explain some basic concepts in multiobjective optimization, a basic framework of EMO algorithms and some hot research issues in the EMO community. Next we explain EMO-based approaches to the design of fuzzy systems. We demonstrate through computational experiments that a large number of non-dominated fuzzy systems with different accuracy-complexity tradeoffs can be obtained by a single run of an EMO algorithm. Then we describe the use of EMO algorithms in other areas such as neural networks, genetic programming, clustering, feature selection, and data mining.
Cell selection for range expansion with almost blank subframe in heterogeneous networks

To encourage data offloading in heterogeneous networks, range expansion techniques have been introduced in LTE-Advanced system. By adding a positive bias in cell selection process, more users can select picocells as their serving cells even the picocell is not of the strongest signal. Also, to protect offloaded users from severe macrocell interference, a specific subframe called almost blank subframe (ABS) is introduced. Since macrocell is kept silent during ABSs, the offloaded users can be allocated without strong macrocell interference within ABSs. It is noted that the offloaded user's average data rate highly depends on the amount of ABSs rather than the bias value because the scheduling opportunities of offloaded users are limited within ABSs. And from the user's point of view, the cell which is expected to give high data rate should be selected as a serving cell. In this paper, we propose a cell selection scheme based on expected user data rate which is a function of the ABS ratio. Simulation results show that the performance of our proposed cell selection scheme can improve average user rate and increase the number of offloaded users as the ABS ratio increases.
FACTS &#8211; A Rule-based Middleware Architecture for Wireless Sensor Networks

Introducing a middleware layer into wireless sensor networks is a widely accepted solution to facilitate application programming and to allow network organization. In this paper we introduce FACTS, a highly flexible middleware architecture able to provide support for a wide range of different applications. Instead of developing middleware and application apart from one another, we seek to combine them at programming level. Our rule-based language, tailored to this concept and the domain of networked sensors, enables high-level software development. The objective is to combine advantages of event-centric processing and rule-based execution while preserving low resource usage
Real-time representation of inter-reflection for cubic marker

This paper proposes a method for rendering an inter-reflection between a marker and a glossy floor in Augmented Reality (AR). At first, a reflectance ratio of the floor is estimated from the reflection on the floor and from the marker box directly. Then the roughness of the floor is estimated based on the sharpness of the reflected marker box image on the floor. Lastly, the marker box reflection is eliminated based on the surrounding colors of the marker box reflection. Rendered images show that natural inter-reflection can be achieved by using the proposed method.
Weight change among people randomized to minimal intervention control groups in weight loss trials

Evidence on the effectiveness of behavioral weight management programs often comes from uncontrolled program evaluations. These frequently make the assumption that, without intervention, people will gain weight. The aim of this study was to use data from minimal intervention control groups in randomized controlled trials to examine the evidence for this assumption and the effect of frequency of weighing on weight change.
Microblog-genre noise and impact on semantic annotation accuracy

Using semantic technologies for mining and intelligent information access to microblogs is a challenging, emerging research area. Unlike carefully authored news text and other longer content, tweets pose a number of new challenges, due to their short, noisy, context-dependent, and dynamic nature. Semantic annotation of tweets is typically performed in a pipeline, comprising successive stages of language identification, tokenisation, part-of-speech tagging, named entity recognition and entity disambiguation (e.g. with respect to DBpedia). Consequently, errors are cumulative, and earlier-stage problems can severely reduce the performance of final stages. This paper presents a characterisation of genre-specific problems at each semantic annotation stage and the impact on subsequent stages. Critically, we evaluate impact on two high-level semantic annotation tasks: named entity detection and disambiguation. Our results demonstrate the importance of making approaches specific to the genre, and indicate a diminishing returns effect that reduces the effectiveness of complex text normalisation.