Miracle-dz/UniFAR-FTUs huggingface dataset:
Proton NMR observation of glycogen in vivo

Our previous solution studies of the proton relaxation properties of glycogen H1 have shown significant dipolar cross–relaxation with intra‐ring H2 and inter‐ring H4′ protons characterized by a correlation time τc= 2.7 × 10−9 s. This leads to a significant negative Nuclear Overhauser Enhancement (NOE) of glycogen H1 following either transient or steady state perturbations of the longitudinal magnetization of dipolar coupled protons, especially H2 and H4′. Here we use the NOE to edit selectively the H1 resonance of glycogen in the rat liver in vivo using a surface coil probe. The approach shows the possibility of measuring glycogen in vivo with high sensitivity using 1H NMR.
Aura Digital Toolkit

This paper discusses an experimental solution that provides the development medium for augmented reality, through a vision based sensory approach. The development medium is a digital toolkit which consists of six modularized components. They are the capture engine (which acquires digital video streams from hardware or media files), the analysis engine (performing various search algorithms), the database repository (which retrieves data), the augmentation engine (that displays relevant context aware information), the delivery agent (that enables the broadcast of digital media streams across a network) and the presentation engine (providing a graphical user interface). In order to discuss the digital toolkit as a viable solution for augmented reality, this paper presents two concept solutions which are the customized visual tag and a real world tag, based on optical character recognition.
Sedation Agents Differentially Modulate Cortical and Subcortical Blood Oxygenation: Evidence from Ultra-High Field MRI at 17.2 T

Background Sedation agents affect brain hemodynamic and metabolism leading to specific modifications of the cerebral blood oxygenation level. We previously demonstrated that ultra-high field (UHF) MRI detects changes in cortical blood oxygenation following the administration of sedation drugs commonly used in animal research. Here we applied the UHF-MRI method to study clinically relevant sedation drugs for their effects on cortical and subcortical (thalamus, striatum) oxygenation levels. Methods We acquired T2*-weighted images of Sprague-Dawley rat brains at 17.2T in vivo. During each MRI session, rats were first anesthetized with isoflurane, then with a second sedative agent (sevoflurane, propofol, midazolam, medetomidine or ketamine-xylazine) after stopping isoflurane. We computed a T2*-oxygenation-ratio that aimed at estimating cerebral blood oxygenation level for each sedative agent in each region of interest: cortex, hippocampus, thalamus and striatum. Results The T2*-oxygenation-ratio was consistent across scan sessions. This ratio was higher with inhalational agents than with intravenous agents. Under sevoflurane and medetomidine, T2*-oxygenation-ratio was homogenous across the brain regions. Intravenous agents (except medetomidine) induced a T2*-oxygenation-ratio imbalance between cortex and subcortical regions: T2*-oxygenation-ratio was higher in the cortex than the subcortical areas under ketamine-xylazine; T2*-oxygenation-ratio was higher in subcortical regions than in the cortex under propofol or midazolam. Conclusion Preclinical UHF MRI is a powerful method to monitor the changes in cerebral blood oxygenation level induced by sedative agents across brain structures. This approach also allows for a classification of sedative agents based on their differential effects on cerebral blood oxygenation level.
Preparation and Characterization of Al(OH)3 Coated CaF2 Composite Powder

Al (OH)3 coated CaF2 composite powder was prepared by coating Al (OH)3 on surface of micro-sized CaF2 particles using heterogeneous nucleation method. Influence of Al3+ concentration, PH value and reaction temperature was studied. The result reveals that CaF2 particle was uniformly coated with a layer of Al (OH)3 and Al3+ concentration, pH value and reaction temperature are the main factors that affect coating result. Optimum technological conditions are Al3+ concentration of solution before reaction at 0.15 mol/L, pH value at 7.5 and temperature at 75 oC.
A Framework for Collaborative Multi Class Heterogeneous Wireless Sensor Networks

For many applications, simultaneous sensing of a number of parameters is crucial that leads to the deployment of multiple classes of sensors having different initial energy, data generation rate and deployment density within the vicinity of a cluster as opposed to identical sensors assumed in the existing heterogeneous sensor networks. For data transmission to cluster head, such networks use single hop, multi hop and their hybrid as intra-cluster transmission policy which suffer highly from non-uniform energy usage among sensors, thereby reducing the lifetime drastically leaving considerable amount of energy in many nodes. In this paper, we propose a framework for multi-class heterogeneous sensor networks where incoming traffic is relayed towards cluster head in collaboration among multiple classes of sensors considering their heterogeneity. We also propose two transmission policies for this framework considering generic polygonal cluster and limited transmission range for individual sensors. Performance analysis shows substantial improvement of overall lifetime by the collaborative framework of multi-class sensors. Our proposed transmission policies further improve the lifetime over existing multi hop and hybrid communications through better distribution of energy usage among sensors.
Experimental Investigation of Constraint Effects on Creep Crack Growth

In this work the effects of specimen size and type on creep crack growth rates in stainless steel are examined. Experiments have been carried out on high constraint compact tension specimens (CT) and low constraint centre cracked panels (CCP) of ex-service 316H stainless steel. All testing was carried out at 550°C. Constraint effects have been observed in the data, with the large CT specimens having the fastest crack growth rate and the small CCP specimens the slowest. These trends are consistent with those that would be predicted from two parameter (C*–Q) theories. However, it is found that a constraint dependent creep crack growth model based on ductility exhaustion overpredicts the constraint dependence of the crack growth data.Copyright © 2002 by ASME
A multi-criteria model for electronic auctions

In this paper we present a multi-criteria model for electronic auctions, which is based on reference points. According to the model, the buyer must specify an aspiration point that expresses his desired values on the attributes of the item to be purchased and a reservation point that represents the minimal values required. Negotiation takes place between software agents that negotiate on behalf of their human owners. The multi-criteria model allows the buyer agent to control the negotiation process on each attribute of the deal. We illustrate the use of this model by providing an auction mechanism based on an English reverse auction protocol.
Data-dependent evaluator modeling and its application to emotional valence classification from speech

Practical supervised learning scenarios involving subjectively evaluated data have multiple evaluators, each giving their noisy version of the hidden ground truth. Majority logic combination of labels assumes equally skilled evaluators, and is generally suboptimal. Previously proposed models have assumed data independent evaluator behavior. This paper presents a data dependent evaluator model, and an algorithm to jointly learn evaluator behavior and a classifier. This model is based on the intuition that real world evaluators have varying performance depending on the data. Experiments on an emotional valence classification task show modest performance improvements of the proposed algorithm as compared to the majority logic baseline and a data independent evaluator model. But more critically, the algorithm also provides accurate estimates of individual evaluator performance, thus paving the way for incorporating active learning, evaluator feedback and unreliable data detection.
On enhancing on-line collaboration using fuzzy logic modeling

Web-based collaboration calls for professional skills and competences to the benefit of the quality of the collaboration and its output. Within this framework, educational virtual environments may provide a means for training upon these skills and in particular the collaborative ones. On the basis of the existing technological means such training may be enhanced even more. Designing considerations towards this direction include the close follow-up of the collaborative activity and provision of support grounded upon a pedagogical background. To this vein, a fuzzy logic-based expert system, namely Collaboration/ReflectionFuzzy Inference System (C/R-FIS,) is presented in this paper. By means of interconnected FISs, the C/RFIS expert system automatically evaluates the collaborative activity of two peers, during their asynchronous, written, web-based collaboration. This information is used for the provision of adaptive support to peers during their collaboration, towards equilibrium of their collaborative activity. In particular, this enhanced formative feedback aims at diminishing the possible dissonance between the individual collaborative skills by challenging self-adjustment procedures. The proposed model extents the evaluation system of a web-based collaborative tool namely Lin2k, which has served as a test-bed for the C/R-FIS experimental use. Results from its experimental use have proved the potentiality of the proposed model to significantly contribute to the enhancement of the collaborative activity and its transferability to other collaborative learning contexts, such as medicine, environmental engineering, law, and music education.
Please Scroll down for Article Optimization Methods and Software Concave Programming for Finding Sparse Solutions to Problems with Convex Constraints Concave Programming for Finding Sparse Solutions to Problems with Convex Constraints

This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. In this work, we consider a class of nonlinear optimization problems with convex constraints with the aim of computing sparse solutions. This is an important task arising in various fields such as machine learning, signal processing, and data analysis. We adopt a concave optimization-based approach, we define an effective version of the Frank–Wolfe algorithm, and we prove the global convergence of the method. Finally, we report numerical results on test problems showing both the effectiveness of the concave approach and the efficiency of the implemented algorithm.
Preceding Vehicle Trajectory Prediction by Multi-Cue Integration

In this paper we describe an approach to detect and predict the driving trajectory of a preceding vehicle on highway. In particular, we focus on detecting and predicting the changing lane intention and action of the preceding vehicle. Our algorithm employs SVM for driving pattern recognition by integrating two different cues: motion cue and appearance cue, which is trained on two class feature sets extracted from examples of lane changing and lane keeping video sequences. The method is evaluated on the real-world data collected in an intelligent vehicle test-bed. The method is applied to a vision-based safety driving system, which tracks the lane, the preceding vehicle, and uses the vehicle lane-change warning to serve for other intelligent vehicle controls.
A Harmonized Perspective on Transportation Management in Smart Cities: The Novel IoT-Driven Environment for Road Traffic Modeling

The unprecedented growth of today’s cities together with increased population mobility are fueling the avalanche in the numbers of vehicles on the roads. This development led to the new challenges for the traffic management, including the mitigation of road congestion, accidents, and air pollution. Over the last decade, researchers have been focusing their efforts on leveraging the recent advances in sensing, communications, and dynamic adaptive technologies to prepare the deployed road traffic management systems (TMS) for resolving these important challenges in future smart cities. However, the existing solutions may still be insufficient to construct a reliable and secure TMS that is capable of handling the anticipated influx of the population and vehicles in urban areas. Along these lines, this work systematically outlines a perspective on a novel modular environment for traffic modeling, which allows to recreate the examined road networks in their full resemblance. Our developed solution is targeted to incorporate the progress in the Internet of Things (IoT) technologies, where low-power, embedded devices integrate as part of a next-generation TMS. To mimic the real traffic conditions, we recreated and evaluated a practical traffic scenario built after a complex road intersection within a large European city.
Visualizing Software Structures through Enhanced Interactive Sunburst Layout

Visualizing large software system structure in compact representations would help software architects and analysts in understanding the overall software structure accurately and efficiently. Space-filling techniques (e.g., Sunburst or Tree-map) are nowadays used for producing compact representations of large hierarchical data. In this paper, we use the Sunburst layout with some enhancements to show the overall software system structure and the inside details in a compact visual form, in order to make it more readable for software architects and analysts. We also report some initial findings of the preliminary conducted evaluation study.
Nber Working Paper Series Supermodality and Tipping Supermodality and Tipping

are especially grateful to Larry Samuelson for assistance with this paper, and also grateful to Doug Bernheim, Vince Crawford and two referees for constructive comments. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research. ABSTRACT We model tipping as a game-theoretic phenomenon and investigate the connection between supermodular games, tipping of equilibria and cascading, and apply the results to issues that arise in the context of homeland security and computer security. We show that tipping and cascading can occur in supermodular games and that "increasing differences"is a sufficient condition for tipping. Supermodularity and tipping of equilibria are closely related. We relate our results to Schelling's early work on tipping.
Learning Relationships between Data Obtained Independently

The aim of this paper is to provide a new method for learning the relationships between data that have been obtained independently. Unlike existing methods like matching, the proposed technique does not require any contextual information, provided that the dependency between the variables of interest is monotone. It can therefore be easily combined with matching in order to exploit the advantages of both methods. This technique can be described as a mix between quantile matching, and deconvolution. We provide for it a theoretical and an empirical validation.
Species conservation profile of the cave spider Turinyphia cavernicola (Araneae, Linyphiidae) from Terceira Island, Azores, Portugal

Turinyphia cavernicola Wunderlich, 2008 is one of the two endemic cavernicolous spiders known from the Azorean archipelago (Portugal). In spite of relatively intensive searches, this species is known from only three caves, but with a single sustainable subpopulation restricted to the Algar do Carvão show cave. With an observed extent of occurrence (EOO) of 2 km2 and an area of occupancy (AOO) around 0,75 km2, it presents a restricted range, severe fragmentation, and continuing decline in EOO, AOO, habitat quality, number of locations and subpopulations caused by the ongoing threat from pasture intensification and tourist activities in the cave systems.
Radiating Amyloid Fibril Formation on the Surface of Lipid Membranes through Unit-Assembly of Oligomeric Species of α-Synuclein

Background Lewy body in the substantia nigra is a cardinal pathological feature of Parkinson's disease. Despite enormous efforts, the cause-and-effect relationship between Lewy body formation and the disorder is yet to be explicitly unveiled. Methodology/Principal Findings Here, we showed that radiating amyloid fibrils (RAFs) were instantly developed on the surface of synthetic lipid membranes from the β-sheet free oligomeric species of α-synuclein through a unit-assembly process. The burgeoning RAFs were successfully matured by feeding them with additional oligomers, which led to concomitant dramatic shrinkage and disintegration of the membranes by pulling off lipid molecules to the extending fibrils. Mitochondria and lysosomes were demonstrated to be disrupted by the oligomeric α-synuclein via membrane-dependent fibril formation. Conclusion The physical structure formation of amyloid fibrils, therefore, could be considered as detrimental to the cells by affecting membrane integrity of the intracellular organelles, which might be a molecular cause for the neuronal degeneration observed in Parkinson's disease.
DULO: an effective buffer cache management scheme to exploit both temporal and spatial locality

Sequentiality of requested blocks on disks, or their spatial locality, is critical to the performance of disks, where the throughput of accesses to sequentially placed disk blocks can be an order of magnitude higher than that of accesses to randomly placed blocks. Unfortunately, spatial locality of cached blocks is largely ignored and only temporal locality is considered in system buffer cache management. Thus, disk performance for workloads without dominant sequential accesses can be seriously degraded. To address this problem, we propose a scheme called DULO (DUal LOcality), which exploits both temporal and spatial locality in buffer cache management. Leveraging the filtering effect of the buffer cache, DULO can influence the I/O request stream by making the requests passed to disk more sequential, significantly increasing the effectiveness of I/O scheduling and prefetching for disk performance improvements. DULO has been extensively evaluated by both trace-driven simulations and a prototype implementation in Linux 2.6. 11. In the simulations and system measurements, various application workloads have been tested, including Web Server, TPC benchmarks, and scientific programs. Our experiments show that DULO can significantly increase system throughput and reduce program execution times.
Papillary thyroid carcinoma tall cell variant.

BACKGROUND The most common of the aggressive variant of papillary thyroid carcinoma (PTC) is the tall cell variant (TCV). Because there are serious prognostic and management implications to a diagnosis of TCV, we review the entity to inform clinicians about the many facets of TCV. SUMMARY The TCV of PTC is characterized by cells having the nuclear features of PTC and whose height is at least twice or thrice their width. There is disagreement regarding the proportion of tall cells and the cell height required to diagnose TCV. In view of its blurred definition and rarity, studies have shown that TCV is still underdiagnosed. We propose that PTC be diagnosed as TCV if it is composed of > or =50% tall cells. The latter should have a height that is at least twice their width, an eosinophilic cytoplasm, and the nuclear features of PTC. Whatever its definition, there is a consensus that TCV has a higher recurrence and death rate than classical PTC. Most authorities believe that TCV's worse prognosis is related to its older age at presentation, larger tumor size, and high frequency of extrathyroid extension (ETE). However, in a recent article, TCV without ETE was shown to have a more aggressive behavior than classical PTC without ETE independent of age, gender, and tumor size. The aggressive behavior of TCV could be related to the high expression of Muc1 and matrix metalloproteinase and to the higher prevalence of B-RAF mutations when compared to classical PTC. The importance of TCV is accentuated by the fact that it is overrepresented in those fluorodeoxyglucose positron-emission tomogram (FDG-PET)-positive thyroid carcinomas that are refractory to radioactive iodine (RAI) therapy constituting 20% of these incurable tumors. CONCLUSION TCV is a biologically and clinically aggressive form of PTC that is still underdiagnosed. TCV is overrepresented in patients with RAI refractory disease. It has a high prevalence of B-RAF mutations making the latter an attractive target in RAI refractory cases. Imaging modalities that can detect RAI refractory disease such as FDG-PET scanning are needed in many patients and a requirement in those with extensive ETE. More studies are needed to identify those TCV that become RAI refractory and develop effective target therapies against these incurable carcinomas.
Optical properties and photoconductivity of amorphous silicon carbon nitride thin film and its application for UV detection

Optical properties of amorphous silicon carbon nitride thin films as a function of carbon content have been studied by the spectral microreflectometry. The compositions of a-SiCN thin films deposited with different CH4 flow rates were analyzed by X-ray photoemission spectroscopy (XPS). It was found that the transmittance of a-SiCN thin films decreases with the increasing carbon content; the index of refraction n varies from ~2.0 to ~2.2 and the optical gap (Tauc gap) Eopt value progressively decreases from 4.1 to 3.3 eV while the carbon content changes from 0 to 25% in the films. In addition, a MSM (metal-semiconductor-metal) photodetector device based on the a-SiCN thin film demonstrates excellent selective sensing features with a large photo-to-dark current ratio about 1800 under illumination of the 250 nm UV light source, providing potential applications for low-cost UV detection. D 2004 Elsevier B.V. All rights reserved.
COMB-FILTER FREE AUDIO MIXING USING STFT MAGNITUDE SPECTRA AND PHASE ESTIMATION

This paper presents a new audio mixing algorithm which avoids comb-filter distortions when mixing an input signal with timedelayed versions of itself. Instead of a simple signal addition in the time domain, the proposed method calculates the short-time Fourier magnitude spectra of the input signals and adds them. The sum determines the output magnitude on the time-frequency plane, whereas a modified RTISI algorithm estimates the missing phase information. An evaluation using PEAQ shows that the proposed method yields much better results than temporal mixing for nonzero delays up to 10 ms.