Miracle-dz/UniFAR-FTUs huggingface dataset:
A Complex Network Analysis Approach for Risk Increase Factor Prediction in Nuclear Power Plants

We explore applying network based metrics to predict safety metrics of components in Nuclear Power Plants (NPP). We first show how to model accident sequences as complex networks, then we conduct a statistical study over the main network metrics to show that these are highly correlated with the RIF (Risk Increase Factor) which is a very popular metric in nuclear safety studies.
Tunable Phosphorescent NIR Oxygen Indicators Based on Mixed Benzo- and Naphthoporphyrin Complexes

A series of π-extended phosphorescent palladium(II) and platinum(II) porphyrin complexes were synthesized, in which additional benzene rings are fused radially onto at least one of the four peripheral benzo groups. The photophysical properties of the metalloporphyrins palladium(II)-meso-tetra-(4-fluorophenyl)mononaphthotribenzoporphyrin (Pd1NF), cis-palladium(II)-meso-tetra-(4-fluorophenyl)dibenzodinaphthoporphyrin (Pd2NF), and palladium(II)-meso-tetra-(4-fluorophenyl)monobenzotrinaphthoporphyrin (Pd3NF) and the corresponding platinum(II) compounds (Pt1NF, cis-Pt2NF, Pt3NF) were investigated. The compounds under investigation absorb intensively in the near-infrared region (628−691 nm) and emit at room temperature at 815−882 nm. Phosphorescence quantum yields of the platinum(II) porphyrins range from 25 to 53% with luminescence decay times of 21 to 44 μs in deoxygenated toluene solutions at room temperature. The corresponding palladium(II) complexes exhibit quantum yields in the range of 7 to 18% with lifetimes of 106 to 206 μs. Density functional theory (DFT) calculations revealed nonplanar geometries for all complexes and corroborate the absorption characteristics. The subsequent π extension of the porphyrin system leads to near-infrared absorbing oxygen indicators with tailor-made luminescence properties as well as tunable oxygen sensitivity.
Distributing SystemC structures in parallel simulations

This paper deals with the most popular attempts of distributing SystemC simulations. SystemC is becoming a popular framework for System-On-Chip (SoC) design and verification. Innovation in processor design does not come easily. Smaller features, faster speeds, and intricate digital logic require more simulation resources to accurately gauge the worth of a new design. In order to provide these resources, distributed simulation conforms to a scalable solution to test and verification of complex system models. In this paper, we review the main approaches to distribute SystemC framework. We analyze the efficiency of the main approaches to distribute the simulation of SystemC models and we present our own approach, which is based on the analyzed ones. We test the scalability of our distributed approach by increasing the number of elements in a self-developed system model. After this, we evaluate its usability in a real SystemC design where complex C++ structures are used and must be distributed across several processes. We show the effectiveness of our approach using a model with n RISC processors and a single n-port RAM.
Evaluating fitts' law performance with a non-ISO task

We used a target-selection task to evaluate head-tracking as an input method on a mobile device. The procedure used a non-ISO Fitts' law task since targets were randomly positioned from trial to trial. Due to a non-constant amplitude within each sequence of trials, throughput was calculated using two methods of data aggregation: by sequence of trials using the mean amplitude and by common A-W conditions. For each data set, we used four methods for calculating throughput. The grand mean for throughput calculated using the division of means and the adjustment for accuracy was 0.74 bps, which is 45% lower than the value obtained using an ISO task. We recommend calculating throughput using the division of means (and not the slope reciprocal from the regression model) and with the adjustment for accuracy. We present design recommendation for non-ISO tasks: Keep amplitude and target width constant within each sequence of trials and use strategies to avoid or remove reaction time.
Legionella taurinensis sp . nov . , a new species antigen ica I I y si m i la r to Legionella spiritensis

3 Unite des EnterobactCries, A group of 42 Legionella-like organisms reacting specifically with Legionella spiritensis serogroup 1 antisera were collected throughout Europe by the Centre National de RBfBrence (French National Reference Centre) for Legionella. This group of isolates differed somewhat from L. spiritensis in terms of biochemical reactions, ubiquinone content and protein profile. The latter two analyses revealed that one of these L. spiritensis-like isolates, Tur in I no. lT, was highly related, but not identical t o any of the red autofluorescent species of Legionella. In fact, this strain was the first of these particular isolates recognized to emit a red autofluorescence when exposed t o UV light. Profile analysis of randomly amplified polymorphic DNA established that the red autof luorescent L. spiritensis-like isolates constituted a homogeneous group distinct from Legionella rubrilucens and Legionella erythra. DNA-DNA hybridization studies involving the use of 51 nuclease confirmed that the indicated group of isolates are a new species of Legionella, for which the name Legionella taurinensis is proposed with strain Turin I no. IT (deposited as ATCC 700508”) as the type strain.
In Vitro Bioactivity Study of RGD-Coated Titanium Alloy Prothesis for Revision Total Hip Arthroplasty

Total hip arthroplasty (THA) is a common procedure for the treatment of end-stage hip joint disease, and the demand for revision THA will double by 2026. Ti6Al4V (Titanium, 6% Aluminum, and 4% Vanadium) is a kind of alloy commonly used to make hip prothesis. To promote the osseointegration between the prothesis and host bone is very important for the revision THA. The peptide Arg-Gly-Asp (RGD) could increase cell attachment and has been used in the vascular tissue engineering. In this study, we combined the RGD with Ti6Al4V alloy using the covalent cross-linking method to fabricate the functional Ti6Al4V alloy (FTA). The distribution of RGD oligopeptide on the FTA was even and homogeneous. The FTA scaffolds could promote mouse osteoblasts adhesion and spreading. Furthermore, the result of RT-qPCR indicated that the FTA scaffolds were more beneficial to osteogenesis, which may be due to the improvement of osteoblast adhesion by the RGD oligopeptide coated on FTA. Overall, the FTA scaffolds developed herein pave the road for designing and building more efficient prothesis for osseointegration between the host bone and prothesis in revision THA.
RTL delay macro-modeling with Vt and Vdd variability

Recent low-power design utilizes a variety of approaches for Vdd and Vt control to reduce dynamic and leakage power. It is important to be able to explore various low-power design options at a high-level early in the design process. Furthermore, process variation is becoming large and greatly affects the power and delay results. In particular, the delay analysis becomes very complicated and time-consuming with existing tools. This paper proposes a new efficient RTL delay macro-model to address these recent problems. The goal is to provide transistor-level accuracy at the RTL level with Vt and Vdd variability. It also includes the ability to handle PVT variations. The validation of the model is demonstrated by comparison with a circuit simulator and a timing verification tool. The experiments show this macro-model predicts the delay for variable Vdd and Vt with an accuracy of ±5% against HSPICE™ and ±10% against PrimeTime™ for a number of ITC'99 benchmark circuits.
Effects of the Mitochondria-Targeted Antioxidant Mitoquinone in Murine Acute Pancreatitis

Although oxidative stress has been strongly implicated in the development of acute pancreatitis (AP), antioxidant therapy in patients has so far been discouraging. The aim of this study was to assess potential protective effects of a mitochondria-targeted antioxidant, MitoQ, in experimental AP using in vitro and in vivo approaches. MitoQ blocked H2O2-induced intracellular ROS responses in murine pancreatic acinar cells, an action not shared by the control analogue dTPP. MitoQ did not reduce mitochondrial depolarisation induced by either cholecystokinin (CCK) or bile acid TLCS, and at 10 µM caused depolarisation per se. Both MitoQ and dTPP increased basal and CCK-induced cell death in a plate-reader assay. In a TLCS-induced AP model MitoQ treatment was not protective. In AP induced by caerulein hyperstimulation (CER-AP), MitoQ exerted mixed effects. Thus, partial amelioration of histopathology scores was observed, actions shared by dTPP, but without reduction of the biochemical markers pancreatic trypsin or serum amylase. Interestingly, lung myeloperoxidase and interleukin-6 were concurrently increased by MitoQ in CER-AP. MitoQ caused biphasic effects on ROS production in isolated polymorphonuclear leukocytes, inhibiting an acute increase but elevating later levels. Our results suggest that MitoQ would be inappropriate for AP therapy, consistent with prior antioxidant evaluations in this disease.
Paint with Me: Stimulating Creativity and Empathy While Painting with a Painter in Virtual Reality

While nothing can be more vivid, immediate and real than our own sensorial experiences, emerging virtual reality technologies are playing with the possibility of being able to share someone else's sensory reality. The Painter Project is a virtual environment where users see a video from a painter's point of view in tandem with a tracked rendering of their own hand while they paint on a physical canvas. The end result is an experiment in superimposition of one experiential reality on top of another, hopefully opening a new window into an artist's creative process. This explorative study tested this virtual environment on stimulating empathy and creativity. The findings indicate potential for this technology as a new expert-novice mentorship simulation.
Performance of Rateless Codes under Spatial Coupling

Spatial coupling of individual LDPC codes improves the BP threshold of the coupled ensemble to the MAP threshold of the underlying ensemble. In this report, we investigate t he performance of spatial coupling on LDGM codes which might lead to constructing a new class of rateless codes. In what follows, we study Raptor codes as a class of rateless codes and investigate spatial coupling on LDPC ensembles by reviewing LDPC convolutional codes. We also verify the threshold increase in spatially coupled LDGM ensembles by our simulat ion results.
Improved and Scalable Bradley-Terry Model for Collaborative Ranking

In collaborative ranking, the Bradley-Terry (BT) model is widely used for modeling pairwise user preferences. However, when this model is combined with matrix factorization on sparsely observed ratings, a challenging identifiability issue arises since the optimization will involve non-convex constraints. Besides, in some situations, fitting the Bradley-Terry model yields a numerical challenge as it may include an objective function that is unbounded from below. In this paper, we will discuss and develop a simple strategy to resolve these issues. Specifically, we propose an Improved-BT model by adding a penalty term, and we develop two parallel algorithms to make Improved-BT model scalable. Through extensive experiments on benchmark datasets, we show that our proposed method outperforms many considered state-of-the-art collaborative ranking approaches in terms of both ranking performance and time efficiency.
Multiplicative Watermark Detection Using Locally Optimum Nonlinearity

This paper concentrates on watermark detection problem, which judges the existence of watermark. A multiplicative watermark detector using locally optimum nonlinearity is derived, based on the condition that DWT coefficients obey to a generalized Gaussian distribution. Experimental results show that the suggested detector has good performances under various situations. Finally, a method for improving its responses is suggested.
Expected complexity of sphere decoding for sparse integer least-square problems

Sparse integer least-squares problems come up in a wide range of applications including wireless communications and genomics. The sphere decoding algorithm can find near-optimal solution to these problems with reduced average complexity if the knowledge of sparsity of the unknown vector is used in decoding. In this paper, we formulate a sphere decoding approach that relies on the ℓ0-norm constraint on the unknown vector to solve sparse integer least-squares problems. The expected complexity of this algorithm is derived analytically for sparse alphabets associated with common applications such as sparse channel estimation and validated via simulations. The results indicate superior performance and speed compared to the classical sphere decoding algorithm.
Estimation of Missing Values Using Decision Tree Approach

: Data mining has made a great progress in recent year but the problem of missing data or value has remained great challenge for data mining. Missing data or value in a datasets can affect the performance of classifier which leads to difficulty of extracting useful information from datasets Dataset taken for this study is student records of university system that contains some missing values. The missing value are present in tm_10and tm_12. To estimate missing values classification algorithm (C4.5/J48) is used and then accuracy is measured through confusion matrix. Weka data mining tool is used for this analysis.
Experiments of passivity-based bilateral aerial teleoperation of a group of UAVs with decentralized velocity synchronization

In this paper, we present an experimental validation of a novel decentralized passivity-based control strategy for teleoperating a group of Unmanned Aerial Vehicles (UAVs): the slave side, consisting of the UAVs, is endowed with large group autonomy by allowing time-varying topology and interrobot/obstacle collision avoidance. The master side, represented by a human operator, controls the group motion and receives suitable force feedback cues informing her/him about the remote slave motion status. Passivity theory is exploited for guaranteeing stability of the slave side and of the overall teleoperation channel. Results of experiments involving the use of 4 quadcopters are reported and discussed, confirming the soundness of the paper theoretical claims.
Predicting Math Performance from Raw Large-Scale Educational Assessments Data : A Machine Learning Approach

Large-scale educational assessment studies (LSAs) regularly collect massive amounts of very rich cognitive and contextual data of whole student populations. Currently, LSAs are limited to reporting student proficiencies in the form of plausible values (PVs). PVs are random draws from the posterior distribution of a student’s ability, which is based on the Bayesian approach with the prior distribution modeling the student background within the population and the likelihood test item response using the Rasch model. While PVs have shown to be a reliable estimate for proficiencies of populations, a more comprehensive study of these rich data sets by deploying machine learning algorithms may provide a better understanding of the underlying factors affecting student performance and thus yield to better and more interpretable predictive models. This paper presents such a novel approach to learn directly from LSA data by deploying a combination of both unsupervised and supervised learning feature selection algorithms to predict student performance on math scores. Our technique learns the difficulty level of different math questions and predicts weather or not a student with a particular background profile will be successful in answering correctly.
The 3‐hydroxy‐3‐methylglutaryl coenzyme A reductase inhibitor pravastatin enhances neurite outgrowth in hippocampal neurons

Epidemiological studies demonstrate a relationship between statin [3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitor] usage and reduced risk of developing Alzheimer's disease. To determine whether statins affect neuronal development, we treated cultured rat hippocampal neurons with pravastatin. After 4-48 h of treatment, pravastatin significantly increased the number of neurites produced by each cell and caused a corresponding increase in levels of the membrane phospholipid phosphatidylcholine. Pravastatin treatment also significantly increased neurite length and branching but did not affect cellular cholesterol levels. Co-incubation with mevalonate, but not cholesterol, abolished the stimulatory effect of pravastatin on neurite outgrowth. Treatment of neurons with isoprenoids also abolished the effect of pravastatin on neurite growth, suggesting that pravastatin may stimulate neuritogenesis by preventing isoprenylation of signaling molecules such as the Rho family of small GTPases. A specific inhibitor of geranylgeranylation, but not farnesylation, mimicked the stimulatory effect of pravastatin on neuritogenesis. Pravastatin treatment significantly decreased levels of membrane-associated RhoA. These data suggest that pravastatin treatment increases neurite outgrowth and may do so via inhibiting the activity of geranylgeranylated proteins such as RhoA.
Simulation of Hydrokinetic Turbines in Turbulent Flow Using Vortex Particle Methods

This work presents the development of computational models that capture vorticity generation and turbulent diffusion within wind and hydrokinetic turbine farms. The use of vortex methods is examined as an alternative for modeling turbulent wakes and rotor-wake interaction. The vorticity-velocity formulation of the Navier-Stokes equations are simulated by a hybrid Lagrangian-Eulerian method involving both fluid particles that carry vorticity and mesh discretizations which enable an efficient solution to N-body vorticity dynamics. A “mesh free” particle-strength-exchange (PSE) algorithm and a “particle-mesh” vortex-in-cell (VIC) algorithm are implemented for a series of benchmarks to verify the simulation method for low Reynolds number flows, including: vortex ring dynamics, flow over bluff bodies, and a 3D wing. These examples are presented on a variety of computer architectures, with support for distributed-memory parallelism, multi-core, and GPGPU computing. The scalability and stability of these proposed vortex methods shows potential for modeling the large range of scales present between rotor-scale and farm-scale hydrodynamics. The desired feature of this methodology is faithful prediction of unsteady phenomenon, capture of vortex shedding, and tracking the evolution of vortical structures as they evolve and interact with immersed structures and ambient turbulent flow.
Effective Blocking for Combining Multiple Entity Resolution Systems

An important aspect of maintaining information quality in data repositories is determining which sets of records refer to the same real world entity. This so called entity resolution problem comes up frequently for data cleaning and integration. Entity Resolution (ER) is a problem that arises in many information integration applications. ER process identifies duplicated records that refer to the same real-world entity, and derives composite information about the entity. The cost of the ER process is high. In this propose paper, input data is split according to the blocking variables. As no comparisons are conducted between different blocks, each block can be processed independently form all others. Blocks can contain different numbers of records which results in varying processing times. We propose an effective blocking for combining multiple entity resolution systems. Keywordsentity resolution, data integration, data reduction, indexing, pre-processing
ULISSE: an Unsupervised Algorithm for Detecting Reliable Dependency Parses

In this paper we present ULISSE, an unsupervised linguistically--driven algorithm to select reliable parses from the output of a dependency parser. Different experiments were devised to show that the algorithm is robust enough to deal with the output of different parsers and with different languages, as well as to be used across different domains. In all cases, ULISSE appears to outperform the baseline algorithms.
Legacy software evaluation model for outsourced maintainer

Outsourcing has become common practice in the software industry. Organizations routinely subcontract the maintenance of their software assets to specialized companies. A great challenge for these companies, is to rapidly evaluate the quality of the systems they will have to maintain so as to accurately estimate the amount of work they will require. To answer these concerns, we developed a framework of metrics to evaluate the complexity of a legacy software system and help an outsourcing maintainer define its contracts. This framework was defined using a well known approach in software quality, called "goal-question-metric". We present the goal-question-metric approach, its results, and the initial experimentation of the metrics on five real life systems in Cobol.
Genome-Wide Pathway Analysis Reveals Different Signaling Pathways between Secreted Lactoferrin and Intracellular Delta-Lactoferrin

Human lactoferrin (LF) is a multifunctional protein involved in immunomodulation, cellular growth, and differentiation. In addition to its secreted form (sLF), an alternative form (ΔLF) lacking the signal sequence has been found to be downregulated in cancer. Although the signaling pathways mediated by LF have been studied in a few cell models, there have been no relevant systemic approaches. Therefore, this study was carried out to identify and compare signaling networks provoked by the two LF isoforms. For this, the two forms were overexpressed in HEK293 cells using the Flp-In T-Rex system, after which genome-wide expression analysis of 18,367 genes was conducted. Pathway analysis of the genes showing altered expression identified pathways which are responsible for cell survival and apoptosis. In addition, the pathways mediated by the two LF forms were within distantly related networks. GPCR, PI3K complex, and POU5F1, which are involved in receptor-mediated pathways, were centered in the sLF network, whereas RIF1, NOS3, and RNPS1, which are involved in intracellular signaling, were centered in the ΔLF network. These results suggest that structural differences between the LF isoforms, mainly glycosylation, determine the fate of LF signaling. Furthermore, these findings provide information relating to the role of ΔLF which is downregulated during carcinogenesis.
Evidence for a large fraction of Compton-thick quasars at high redshift

Using mid-infrared and radio selection criteria, we pre-select a sample of candidate high-redshift type-2 quasars in the Subaru XMM-Newton Deep Field (SXDF). To filter out starburst contaminants, we use a bayesian method to fit the spectral energy distributions (SEDs) between 24-� m and B-band, obtain photometric redshifts, and identify the best candidates for high-z type-2 quasars. This leaves us with 12 zphot > 1.7 type-2 quasar candidates in an area � 0.8 deg 2 , of which only two have secure X-ray detections. Given the large bolometric luminosities and redshifts of the objects, the lack of X-ray detections suggests extreme absorbing columns NH > 10 28 m 2 are typical. We conclude that we have found a population of “Compton-thick” highredshift type-2 quasars, at least comparable to, and probably larger than the type-1 quasar population.