Miracle-dz/UniFAR-FTUs huggingface dataset:
A Strategy for Parametrization Refinement in the Solution of a Geometric Inverse Problem

This paper treats the problem of identifying a single inclusion in a conductor domain based on the knowledge of measured electrical potentials on the external boundary of the conductor body due to known injected electrical currents. The inclusion boundary is approximated by an Extended X-Spline, that allows identify inclusions with smooth or sharp boundary. In this work, the forward problem is solved by an implementation of the direct formulation of the Boundary Element Method (BEM) and the inverse one is solved by Levenberg-Marquardt method, which requires the evaluation of the objective function derivatives, here approximated by finite differences. This work presents a methodology to increase the number of optimization variables during the solution of the inverse problem in order to improve the quality of the results.
Context-aware pedestrian detection using LIDAR

LIDAR-based object detection usually relies on geometric feature extraction, followed by a generative or discriminative classification approach. Instead, we propose to change the way of detecting objects using LIDAR by means of not only a featureless approach, but also inferring context-aware relations of object parts. For the first feature, a coarse-to-fine segmentation based on β-skeleton random graph is proposed; after segmentation, each segment is labeled, and scored by a Procrustes analysis. For the second feature, after defining the sub-segments of each object, a contextual analysis is in charge of assessing levels of intra-object or inter-object relationship, ultimately integrated into a Markov logic network. This way, we contribute with a system which deals with partial segmentation, also embodying contextual information. The system proof-of-concept is in pedestrian detection, but the rationale of the approach can be applied to any other object after the definition of its physical structure. The effectiveness of the proposed method was assessed over a data set gathered in challenging scenarios, with a significant gain in accuracy over a full segmentation version of the system.
Resource allocation with different MCSs for mobile IPTV services in wireless cellular networks

The required bandwidth for mobile IPTV services is usually much higher than that of voice and data services. Thus, how to enhance the spectrum efficiency of the mobile network supporting IPTV services becomes an important issue. In this paper, the performance of mobile IPTV services which use the adaptive Modulation and Coding Scheme (MCS) according to channel conditions or SNRs of group users, will be investigated. For the adaptive MCS scheme, if the multicast IPTV group consists of only cell-center users, the MCS at a higher data rate may be employed; otherwise, the MCS at a lower data rate must be used. According to simulation results, the adaptive MCS can achieve a better blocking rate performance and consume less spectrum, compared with the fixed MCS scheme that always employs the MCS at the worst data rate for all multicast IPTV groups.
VS-501: a novel, nonabsorbed, calcium- and aluminum-free, highly effective phosphate binder derived from natural plant polymer

Inadequate control of serum phosphate in chronic kidney disease can lead to pathologies of clinical importance. Effectiveness of on‐market phosphate binders is limited by safety concerns and low compliance due to high pill size/burden and gastrointestinal (GI) discomfort. VS‐501 is a nonabsorbed, calcium‐ and aluminum‐free, chemically modified, plant‐derived polymer. In vitro studies show that VS‐501 has a high density and a low swell volume when exposed to simulated gastric fluid (vs. sevelamer). When male Sprague–Dawley (SD) rats on normal diet were treated with VS‐501 or sevelamer, serum phosphate was not significantly altered, but urinary phosphate levels decreased by >90%. VS‐501 had no effect on serum calcium (Ca) or urinary Ca, while 3% sevelamer significantly increased serum and urine Ca. In 5/6 nephrectomized (NX) uremic SD rats on high‐phosphate diet, increasing dietary phosphate led to an increase in serum and urine phosphate, which was prevented in rats treated with VS‐501 or sevelamer (0.2–5% in food). High‐phosphate diet also increased serum fibroblast growth factor‐23 and parathyroid hormone in 5/6 NX rats that was prevented by VS‐501 or sevelamer. VS‐501 or sevelamer increased fecal phosphate in a dose‐dependent manner. More aortic calcification was observed in 5/6 NX rats treated with 5% sevelamer, while VS‐501 and sevelamer did not show significant effects on cardiac parameters, fibrosis, intestine histology, and intestinal sodium‐dependent phosphate cotransporter gene expression. These results suggest that VS‐501 is effective in binding phosphate with no effects on calcium homeostasis, and may have improved pill burden and GI side effects.
Computing Termination Conditions of While Loops ∗

The study of the termination condition of a loop is an important part of the analysis of loops. In this paper, we use the concept of invariant relations to compute termination conditions of loops. Our definition of termination encompasses not only the condition that the number of iterations is finite, but also the condition that each iteration of the loop executes without raising an exception, such an array reference out of bounds, a division by zero, an overflow/ underflow, an illegal pointer reference, etc.
Risk-driven effort-estimation of tasks within the software performance engineering

The current methods of estimating costs frequently only indirectly take performance engineering (PE) tasks into account. Moreover, there are major differences in the propositions put forward by such methods. To create transparency and acceptance of these tasks, which are of great importance as part of the life cycles of IT systems, an approach is pursued which derives the costs from an appropriate risk analysis and, in the course of doing so, investigates the business process to be supported, the software development as well as active operations. The initial results of empirical analyses are presented by way of 6 industrial projects.
Interval colorings of complete balanced multipartite graphs

A graph $G$ is called a complete $k$-partite ($k\geq 2$) graph if its vertices can be partitioned into $k$ independent sets $V_{1},. ,V_{k}$ such that each vertex in $V_{i}$ is adjacent to all the other vertices in $V_{j}$ for $1\leq i<j\leq k$. A complete $k$-partite graph $G$ is a complete balanced $k$-partite graph if $|V_{1}| = |V_{2}| =. = |V_{k}|$. An edge-coloring of a graph $G$ with colors $1,. ,t$ is an interval $t$-coloring if all colors are used, and the colors of edges incident to each vertex of $G$ are distinct and form an interval of integers. A graph $G$ is interval colorable if $G$ has an interval $t$-coloring for some positive integer $t$. In this paper we show that a complete balanced $k$-partite graph $G$ with $n$ vertices in each part is interval colorable if and only if $nk$ is even. We also prove that if $nk$ is even and $(k-1)n\leq t\leq ((3/2)k-1)n-1$, then a complete balanced $k$-partite graph $G$ admits an interval $t$-coloring. Moreover, if $k=p2^{q}$, where $p$ is odd and $q\in \mathbb{N}$, then a complete balanced $k$-partite graph $G$ has an interval $t$-coloring for each positive integer $t$ satisfying $(k-1)n\leq t\leq (2k-p-q)n-1$.
Transcriptome Sequencing Identifies SPL7-Regulated Copper Acquisition Genes FRO4/FRO5 and the Copper Dependence of Iron Homeostasis in Arabidopsis[C][W]

In a genome-wide analysis of the transcriptional changes in Arabidopsis thaliana in response to Cu deficiency, about 13% are found to depend on the transcription factor SPL7. These include the genes encoding Cu(II) reductases FRO4 and FRO5, which are shown to act in high-affinity root Cu uptake. Severe physiological Cu deficiency results in a disruption of Fe homeostasis. The transition metal copper (Cu) is essential for all living organisms but is toxic when present in excess. To identify Cu deficiency responses comprehensively, we conducted genome-wide sequencing-based transcript profiling of Arabidopsis thaliana wild-type plants and of a mutant defective in the gene encoding SQUAMOSA PROMOTER BINDING PROTEIN-LIKE7 (SPL7), which acts as a transcriptional regulator of Cu deficiency responses. In response to Cu deficiency, FERRIC REDUCTASE OXIDASE5 (FRO5) and FRO4 transcript levels increased strongly, in an SPL7-dependent manner. Biochemical assays and confocal imaging of a Cu-specific fluorophore showed that high-affinity root Cu uptake requires prior FRO5/FRO4-dependent Cu(II)-specific reduction to Cu(I) and SPL7 function. Plant iron (Fe) deficiency markers were activated in Cu-deficient media, in which reduced growth of the spl7 mutant was partially rescued by Fe supplementation. Cultivation in Cu-deficient media caused a defect in root-to-shoot Fe translocation, which was exacerbated in spl7 and associated with a lack of ferroxidase activity. This is consistent with a possible role for a multicopper oxidase in Arabidopsis Fe homeostasis, as previously described in yeast, humans, and green algae. These insights into root Cu uptake and the interaction between Cu and Fe homeostasis will advance plant nutrition, crop breeding, and biogeochemical research.
Investigation of Invariants of a Chemical Reaction System with Algorithms of Computer Algebra

In this paper the qualitative study of a reversible chemical reaction model represented by a three-dimensional system of ordinary differential equations with nine parameters is performed. Algebraic invariant surfaces of the system are obtained by using methods of computational algebra. Then we look for singular points on the invariant surfaces and study their stability and bifurcations. Finally numerical simulations which confirm our theoretical results are presented. The study is carried out with help of computer algebra systems Singular and Mathematica.
A Benchmark Data Set for Data Association

In this technical report we present a data set which can be used by researchers to test and compare their algorithms related to feature-based SLAM and in particular data association tasks. The data set covers a large path mostly through an indoor office environment with artificial and natural landmarks. It provides odometry and geometrical results from computer vision-based landmark detection, as well as raw images and camera calibration data. The artificial landmarks are white discs on the floor where the position relative to the robot is provided as measurement. The natural landmarks are vertical lines where only the bearing relative to the robot is provided and data association is remarkably difficult. This technical report provides full information about experimental setup, model and measurement functions. The focus of this data set is on data association and for comparison of different approaches we provide full ground truth by annotating all features.
Bioinformatics resources for cancer research with an emphasis on gene function and structure prediction tools

The immensely popular fields of cancer research and bioinformatics overlap in many different areas, e.g. large data repositories that allow for users to analyze data from many experiments (data handling, databases), pattern mining, microarray data analysis, and interpretation of proteomics data. There are many newly available resources in these areas that may be unfamiliar to most cancer researchers wanting to incorporate bioinformatics tools and analyses into their work, and also to bioinformaticians looking for real data to develop and test algorithms. This review reveals the interdependence of cancer research and bioinformatics, and highlight the most appropriate and useful resources available to cancer researchers. These include not only public databases, but general and specific bioinformatics tools which can be useful to the cancer researcher. The primary foci are function and structure prediction tools of protein genes. The result is a useful reference to cancer researchers and bioinformaticians studying cancer alike.
A benchmark proposal for design pattern detection

FactoryDef : DPDef name = "Abstract Factory" L1 : LevelDef AF : RoleDef name = "Abstract Factory" L2 : LevelDef L3 : LevelDef CF : RoleDef name = "Concrete Factory" AP : RoleDef name = "Abstract Product" L4 : LevelDef CP : RoleDef name = "Concrete Product" root
Mobile Commerce Acceptance Model: An Integrated Theory Model

Based on TAM and TTF theory, we construct an adoption model to analyze factors that influence users adoption m-commerce. The theoretical model indicates that perceived fit have positive effect on perceived usefulness and perceived security, perceived value was positively related to intention to adopt m-commerce; moreover, perceived value mediates the effect of perceived usefulness and perceived security on users' intention to use m-commerce. Implications for theory and practice as well as limitations and future directions are also discussed.
Leukoaraiosis severity predicts rate of decline in primary progressive aphasia

ABSTRACT Background: The rate of decline in language in primary progressive aphasia (PPA) is highly variable and difficult to predict at baseline. The severity of diffuse white matter disease (leukoaraiosis), a marker of overall brain health, may substantially influence the rate of decline. Aims: To test the hypothesis that leukoaraiosis is associated with a steeper decline in naming in PPA. Methods and procedures: In this longitudinal, observational study, 29 individuals with PPA (all variants) were administered the Boston Naming Test (BNT) at baseline and 1 year later. Two raters evaluated leukoaraiosis on baseline MRI, using the Cardiovascular Health Study scale. We evaluated the effects of leukoaraiosis severity, age, education, and baseline BNT on decline measured by change in BNT accuracy with multivariable linear regression. We also evaluated the effects of these variables on the dichotomized outcome of faster decline in BNT (worst 50%) versus slower decline (best 50%) using logistic regression. Outcomes and results: Taken together, leukoaraiosis, age, education, and baseline BNT score predicted change in BNT score (F(3, 25) = 8.12; p = 0.0006). Change in BNT score was predicted by severity of leukoaraiosis (t = −3.81; p = 0.001) and education (t = −2.45; p = 0.022), independently of the other variables. When we dichotomized outcome into upper 50th percentile versus lower 50th percentile (faster decline), faster decline was predicted by all variables together (chi-squared = 13.91; p = 0.008). However, only leukoaraiosis independently predicted outcome (OR = 2.80; 95%CI: 1.11 to 7.03). For every 1 point increase on the CHS rating scale, there was 2.8 times higher chance of showing faster decline in naming. Conclusion: Severity of leukoaraiosis is associated with steeper decline in naming in PPA. This imaging marker can aide in prognosis and planning by caregivers and stratification of participants in clinical trials.
Ultrastructural Mapping of the Zebrafish Gastrointestinal System as a Basis for Experimental Drug Studies

Research in the field of gastroenterology is increasingly focused on the use of alternative nonrodent model organisms to provide new experimental tools to study chronic diseases. The zebrafish is a particularly valuable experimental platform to explore organ and cell structure-function relationships under relevant biological and pathobiological settings. This is due to its optical transparency and its close-to-human genetic makeup. To-date, the structure-function properties of the GIS of the zebrafish are relatively unexplored and limited to histology and fluorescent microscopy. Occasionally those studies include EM of a given subcellular process but lack the required full histological picture. In this work, we employed a novel combined biomolecular imaging approach in order to cross-correlate 3D ultrastructure over different length scales (optical-, X-ray micro-CT, and high-resolution EM). Our correlated imaging studies and subsequent data modelling provide to our knowledge the first detailed 3D picture of the zebrafish larvae GIS. Our results provide unequivocally a limit of confidence for studying various digestive disorders and drug delivery pathways in the zebrafish.
UFO: A United Framework for Target Localization in Wireless Sensor Networks

Recently, various range-free based target localization applications and systems are developed in Wireless Sensor Networks. Nevertheless, few of them can be reused or grafted by others, which has led to serious waste. In this paper, a Unified Framework for target lOcalization (UFO) is proposed and an adaptive grids dividing algorithm is addressed within the framework. Based on the common ground of current typical range-free localization methods, UFO is constructed by four major modules to achieve candidate area acquisition and target location determination: sensor deployment and signal process module, candidate area acquisition module, target localization module and parameter setting module. Not only can UFO construct a localization framework quickly, the computing complexity of loaded localization methods is expected to be decreased by bringing in adaptive grids dividing. In our simulations, the UFO assembled with schemes from node sequences based localization method is tested, and the results from our framework are compared with the original method's. Performance evaluation shows us both UFO and original schemes perform well at localizing accuracy, while the former has a big advantage at real-time capacity.
An Approach for Virtualization and Integration of Heterogeneous Cloud Databases

Virtualization is the key technology behind cloud computing that allows the creation of an abstraction layer of the underlying cloud Infrastructure. Using virtualization, resources (hardware and software) can be shared and utilized while hiding the complexity from the cloud users. A lot of cloud database are available that managed by different organization such asAmazon Storage for the Cloud, Google Storage for the Cloud, Hadoop Storage for the Cloud, Yahoo! ’s PNUTS, Cassandra, CouchDB etc. This paper is presented to propose a virtual Database framework that enables the centralized global object oriented database. A virtually integrated huge database that will hide the heterogeneity of various cloud databases. Once they are integrated a consistent access is provide
Latest advances in gallium nitride HEMT modeling

GaN-based high electron mobility transistor (HEMT) has been considered as the next-generation technology for high-frequency/high-power and high-speed/high-voltage applications. This paper discusses the needs and challenges for advanced GaN HEMT models, and reviews latest advances by focusing on Compact Model Coalition's (CMC) newly launched effort on GaN HEMT model standardization and DynaFET, a unique characterization and modeling methodology that uses large-signal waveform measurement as a central input. Distinct technical approaches in DynaFET and CMC's candidate models (the Angelov-GaN model, the COMON model, the HSP model, and the MVSG-HV model) are highlighted.
An Investigation of the Lead-Lag Relationship between the VIX Index and the VIX Futures on the S&P500

This study investigates the lead-lag relationship between the price movements of VIX futures and VIX index levels. As a proxy for the futures, the front month VIX futures contract is used. A Johansen cointegration approach with a vector error correction model and Granger causality analysis are applied. The results suggest that VIX futures lead spot VIX index, which implies that VIX futures market seems to play a more important role in price discovery.
The role of social interactions in value creation in agile software development processes

This position paper presents an emerging research based on a set of expressed statements and impressions from conducted empirical research during the past few years. Agile software development emphasizes on social aspects through its methods and principles. In order to improve the processes within the organization and amongst various stakeholders, there is a need for social processes and various types of interactions to be studied in the context of agile development. The objective of this paper is to present the need to conduct more empirical studies to investigate the socialness of software engineering processes and in particular the role of various type of social interactions in improving development processes and therefore creating more value in organizations.
Cytotoxic T cells specific for glutamic acid decarboxylase in autoimmune diabetes

Insulin-dependent diabetes mellitus (IDDM) is an autoimmune disease that results in the destruction of the pancreatic islet beta cells. Glutamic acid decarboxylase (GAD) has been recently indicated as a key autoantigen in the induction of IDDM in nonobese diabetic mice. In human diabetes, the mechanism by which the beta cells are destroyed is still unknown. Here we report the first evidence for the presence of GAD-specific cytotoxic T cells in asymptomatic and recent diabetic patients. GAD65 peptides displaying the human histocompatibility leukocyte antigen (HLA)-A*0201 binding motif have been synthesized. One of these peptides, GAD114-123, binds to HLA-A*0201 molecules in an HLA assembly assay. Peripheral blood mononuclear cells from individuals with preclinical IDDM, recent-onset IDDM, and from healthy controls were stimulated in vitro with the selected peptide in the presence of autologous antigen-presenting cells. In three cases (one preclinical IDDM and two recent-onset IDDM), we detected specific killing of autologous antigen-presenting cells when incubated with GAD114-123 peptide or when infected with a recombinant vaccinia virus expressing GAD65. These patients were the only three carrying the HLA-A*0201 allele among the subjects studied. Our finding suggests that GAD- specific cytotoxic T lymphocytes may play a critical role in the initial events of IDDM.
Efficient Picking through Atomic Operations

Picking is the process through which a single entity or a list of entities is selected from a scene. The subject of picking is both a rendering and a collision detection problem, with the majority of research being on optimizing the ray-scene intersection problem. Several algorithms that solve the picking problem exist in the context of rasterization, but all of them lack several of the features of our proposed solution while, with one exception, all being much more expensive in terms of computational time. We propose a novel single frame method which is able to correctly select not only primitives but also any type of objects that may appear on the screen at a fragment level including hardware instanced, alpha culled, hardware tessellated, hardware animated and particle systems. The proposed technique has optimal memory requirements and offers the opportunity to pick at micro polygon level and is not limited to the first contact, offering the full intersection list per ray if required to do so. The proposed technique offers further unique opportunities such as flexible fuzzy object selection and is the only technique that selects without disregarding opacity accumulation from transparent objects.