Miracle-dz/UniFAR-FTUs huggingface dataset:
MR image coding using content-based mesh and context

Existing schemes for 3-D magnetic resonance (MR) images, such as block matching method and uniform mesh-based scheme, are inadequate to model the motion field of MR sequence because deformation within a mesh element may not all be similar. We propose a scheme consisting of (a) content-based mesh generation using optic flow between two consecutive images (b) forward motion tracking (c) motion compensation using affine transformation and (d) context-based modeling. We also propose a simple scheme to overcome aperture problem at edges where an accurate estimation of motion vectors is not possible. By using context-based modeling, motion compensation yields a better estimate of the next frame and hence a lower entropy of the residue. The obtained average compression ratio of 4.3 is better than the values of 4, achieved by CALIC, and 3, by the existing uniform mesh-based interframe coding scheme.
Bactericidal action of high‐power Nd:YAG laser light on Escherichia coli in saline suspension

Infra‐red light (1064 nm) from a high‐power Nd:YAG laser caused more than 90% loss of viability of Escherichia coli during exposures that raised the temperature of PBS suspensions of the bacteria to 50 °C in a thermocouple‐equipped cuvette. In contrast, there was minimal loss of viability after heating the same suspensions to 50 °C in a water‐bath, or in a PCR thermal cycler. The mechanism of laser killing at 50 °C was explored by differential scanning calorimetry, by laser treatment of transparent and turbid bacterial suspensions, and by optical absorbancy studies of E. coli suspensions at 1064 nm. Taken together, the data suggested that the bactericidal action of Nd:YAG laser light at 50 °C was due partly to thermal heating and partly to an additional, as yet undefined, mechanism. Scanning electron microscopy revealed localized areas of surface damage on laser‐exposed E. coli cells.
SEM/EDX and FTIR Characterization of a Dental Resin Cement with Antibacterial Agents Incorporated

The demand from patients for aesthetic in posterior teeth restoration has been increasing in recent years. As an alternative to metal alloy restorations used in posterior tooth, aesthetical materials such as ceramics have been more often utilized. Resin cement, a derivative from dental composite, based on the combination of bis-GMA and inorganic filler is used to fixate these ceramic restorations to posterior teeth. Similar to resin composite, incorporated antibacterial agents to resin cement can be an effective way to increase the aesthetic restoration durability. Resin cements C&B® (Bisco) and Fill Magic Dual Cement® (Vigodent) were used in the present study. For experimental resin cement, Triclosan was incorporated to the base cement paste. Samples were investigated by Scanning Electron Microscopy coupled to EDX microprobe (SEM/EDX) and FTIR spectroscopy. The results have demonstrated that the incorporation of antibacterial agents to resin cement is possible through the developed procedure.
Search by Detection: Object-Level Feature for Image Retrieval

In content-based image retrieval (CBIR), images are usually represented by local invariant features or global features. Although great success has been witnessed, there still exists some non-trivial problems with those features. In this paper, we propose a novel image representation for image retrieval. We identify some regions of interest with an advanced general object detector, and the regions are described by features extracted with convolutional neural network (CNN). We evaluate the performance of the proposed representation on two public datasets. The experimental results demonstrate the effectiveness of the proposed method.
Towards Detecting Patterns in Failure Logs of Large-Scale Distributed Systems

The ability to automatically detect faults or fault patterns to enhance system reliability is important for system administrators in reducing system failures. To achieve this objective, the message logs from cluster system are augmented with failure information, i.e., The raw log data is labelled. However, tagging or labelling of raw log data is very costly. In this paper, our objective is to detect failure patterns in the message logs using unlabelled data. To achieve our aim, we propose a methodology whereby a pre-processing step is first performed where redundant data is removed. A clustering algorithm is then executed on the resulting logs, and we further developed an unsupervised algorithm to detect failure patterns in the clustered log by harnessing the characteristics of these sequences. We evaluated our methodology on large production data, and results shows that, on average, an f-measure of 78% can be obtained without having data labels. The implication of our methodology is that a system administrator with little knowledge of the system can detect failure runs with reasonably high accuracy.
Information Literacy Education in Asian Developing Countries: cultural factors affecting curriculum development and programme delivery

The prevailing models of information literacy education (ILE) are contextually grounded in Western social and intellectual structures. For the most part these models follow the taxonomy developed in the 1950s by Bloom, which has been adopted as appropriate for developing societies without considering the contexts from which they are derived, and in which they are being applied. For ILE to be meaningfully embedded in the educational fabric of a developing country, it is important to take account of a range of contextual variables that affect how and why individuals learn. Focusing on ILE through the lens of cultural contextuality, this paper addresses three questions in relation to ILE in developing countries: How do we define information literacy in a developing country context? How do we best determine the educational objectives of information literacy education in a developing country context? How can cultural awareness improve information literacy education?
Cognitive radio decision engine using hybrid binary particle swarm optimization

The adaptation of the radio parameters is one of the basic capabilities of cognitive radio decision engine. Many researches focus on using genetic algorithm (GA) to select the optimal parameters. However, the convergence speed of GA is low. Recently, particle swarm optimization (PSO) has been used a lot in the cognitive radio system. In this paper, we proposed a hill-climbing binary particle swarm optimization (BPSO) which optimize optimal individual after one iterative operation by hill-climbing algorithm. The proposed method would enhance the local search capability at the later stage of each generation of BPSO. We designed a multi-carrier system for performance analysis. Through different weighting scenarios multiple objective fitness functions, the simulation results illustrate the trade-off between the fitness function and the transmission parameters configuration. And the results show that the hill-climbing BPSO is better than pure BPSO in stability and average fitness value.
A model of the lateral line of fish for vortex sensing

In this paper, the lateral line trunk canal (LLTC) of a fish is modeled to investigate how it is affected by an external flow field. Potential flow theory is adopted to model the flow field around a fish's body in the presence of a Karman vortex street. Karman and reverse Karman streets represent the flow patterns behind a bluff body and a traveling fish, respectively. An analytical solution is obtained for a flat body, while a fish-like body is modeled using a Joukowski transformation and the corresponding equations are solved numerically. The pressure distribution on the body surface is then computed employing Bernoulli's equation. For a known external flow, the flow inside the LLTC is driven by the pressure gradient between a pair of consecutive pores, which can be solved analytically. Governing dimensionless parameters are obtained from this analytical solution, and the effects of these numbers on the amplitude or features of the velocity distribution inside the canal are studied. The results show that the main characteristics of a vortex street including the magnitude of vortices, their translational speed, their spacing, their distance from the fish's body and the angle of the vortex street axis can all be recovered by measuring the velocity distribution along the canal and its changes with time. To this end, the proposed LLTC model could explain how a fish identifies the characteristics of a Karman vortex street shed by a nearby object or a traveling fish. It is also demonstrated that while this model captures the ac (alternating current) component of the external velocity signal, the dc (direct current) component of the signal is filtered out. Based on the results of our model, the role of the LLTC in a fish's schooling and its evolutionary impact on fish sensing are discussed.
A Case Study of Open Source Software Development in Proteomic Area: The LIMS ePims

The objective of this paper is to provide an illustrative feedback on development of Open Source software among several partners. We describe the first stage of the design of a specific software package, namely a customized Laboratory Information Management System (LIMS) for biology applications. This software package is structured in several modules which are reusable and can be customized for other applications. In this paper, we address the problem of multi-licensing for the same software tools due to the participation of several partners, the reuse of code source, and the subsequent distribution of this produced software.
A Survey on Kernel Speci cation and Veri cation

Formal methods have been traditionally used to model and verify operating systems Dif ferent methods verify di erent operating systems properties such as process management mutual exclusion and inter process communication Moreover various methods may capture di erent design errors such as deadlocks or unspeci ed receptions The system kernel supports higher level system services Hence kernel veri cation is es sential for the proper operation of the system In addition providing clear kernel speci cation improves the interoperability between its various implementations In this paper we describe commonly used methods for kernel speci cation and veri cation Some methods provide a mathematical model and use logic to prove properties of interest These include PVS and Boyer Moore logic Others use a programming language to simulate the system then apply veri cation tools to capture system errors These include the SPIN tool Distributed operating systems are susceptible to unexpected failure events complicating the issue of system robustness This issue is not addressed explicitly by traditional veri cation methods We present a new STRESS method that can be used to analyze system robustness STRESS is based on a simulation framework and facilitates fault simulation for distributed operating systems and kernels Finally our comparison shows that some of the methods discussed are complementary Thus several methods may be used to obtain better fault coverage of the target system
The impact of a hospitalist on role boundaries in an orthopedic environment

Purpose Hospitalists specialize in the management of hospitalized patients. They work with several health care professionals to provide patient care. There has been little research examining the perceived impact of the hospitalist’s role on staff working in an orthopedic environment. This study examined the experiences of staff across several professional backgrounds in working with a hospitalist in an orthopedic environment. Participants and methods A qualitative descriptive approach was taken to investigate the experience of staff working with a hospitalist at a specialized orthopedic hospital. Purposive sampling was used to recruit interview participants including nurses, internists, pharmacists, physiotherapists, anesthetists, senior administration, and orthopedic surgeons to the point of theoretical saturation, which occurred after 12 interviews. Interviews were coded, and these codes were combined into categories and predominant themes were identified. Findings Overall, staff believed that the hospitalist role was a positive addition to the facility. The role benefitted patients and supported the clinical well-being and education of staff. Many staff felt the hospitalist had no impact on their workload, but others reported that their work had decreased or increased. Several described the potential for role overlap between the hospitalist and other physicians. Conclusion The importance of interprofessional collaboration in the implementation of the hospitalist role was a recurring theme in our analysis. This study demonstrates the importance of educating staff about the hospitalist role boundaries prior to implementing hospitalist care.
Project Acronym : Optique Project Title : Scalable End-user Access to Big Data Instrument : Integrated Project Scheme : Information & Communication Technologies Deliverable D 5 . 1 A Semantics for Temporal and Stream-Based Query Answering in an OBDA Context

In large companies such as Siemens and Statoil monitoring tasks are of great importance, e.g., Siemens does monitoring of turbines and Statoil of oil behaviour in wells. This tasks bring up importance of both streaming and historical (temporal) data in the Big Data challenge for industries. We present the Optique project that addresses this problem by developing an Ontology Based Data Access (OBDA) system that incorporates novel tools and methodologies for processing and analyses of temporal and streaming data. In particular, we advocate for modelling time time aware data by temporal RDF and reduce monitoring tasks to knowledge discovery and data mining.
A Comprehensive Standardized Model for Ultrawideband Propagation Channels

A comprehensive statistical model is described for ultrawideband (UWB) propagation channels that is valid for a frequency range from 3-10 GHz. It is based on measurements and simulations in the following environments: residential indoor, office indoor, builtup outdoor, industrial indoor, farm environments, and body area networks. The model is independent of the used antennas. It includes the frequency dependence of the path gain as well as several generalizations of the Saleh-Valenzuela model, like mixed Poisson times of arrival and delay-dependent cluster decay constants. A separate model is specified for the frequency range below 1 GHz. The model can thus be used for realistic performance assessment of UWB systems. It was accepted by the IEEE 802.15. 4a Task Group as standard model for evaluation of UWB system proposals. This paper also presents a critical assessment of the applicability of the model and possible generalizations and improvements
PDF-optimized LSF vector quantization based on beta mixture models

The line spectral frequencies (LSF) are known to be the mostefficient representation of the linear predictive coding (LPC) parametersfrom both the distortion and perceptual point of view.By considering the bounded property of the LSF parameters,we apply beta mixture models (BMM) to model the distributionof the LSF parameters. Meanwhile, by following the principlesof probability density function (PDF) optimized vector quantization(VQ), we derive the bit allocation strategy for the BMM.The LSF parameters are obtained from the TIMIT database anda practical VQ is designed. By taking the Bayesian informationcriterion (BIC), the square error (SE) and the spectral distortion(SD) as the criteria, the BMM based VQ outperforms theGaussian mixture model based VQ with uncorrelated Gaussiancomponent (UGMVQ) by about 1-2 bits/vector.
CAST: A Context-Aware Story-Teller for Streaming Social Content

Online social streams such as Twitter timelines, forum discussions and email threads have emerged as important channels for information propagation. Mining transient stories and their correlations implicit in social streams is a challenging task, since these streams are noisy and surge quickly. In this paper, we propose CAST, which is a context-aware story-teller that discovers new stories from social streams and tracks their structural context on the fly to build a vein of stories. More precisely, we model the social stream as a capillary network, and define stories by a new cohesive subgraph type called (k,d)-Core in the capillary network. We propose deterministic and randomized context search to support the iceberg query, which builds the story vein as social streams flow. We perform detailed experimental study on real Twitter streams and the results demonstrate the creativity and value of our approach.
Photoacoustic microscopy imaging – From a single erythrocyte to a vascular network/Bildgebung mittels photoakustischer Mikroskopie – Vom einzelnen Erythrozyt zum Gefäßnetz

Abstract A label-free angiography photoacoustic microscopy system is proposed which was produced by the integration of a two-dimensional scanning galvanometer, an objective lens, a focused ultrasound transducer, a water container and a sample supporter. Using this system, in vivo blood vessels and capillaries in the back of a mouse and in the mouse ear were clearly imaged. Moreover it was possible to reconstruct a three-dimensional image of the mouse back vascular network. Ex vivo erythrocytes were used to prove the imaging capability of the system, and a single erythrocyte was mapped with high contrast. The experimental results demonstrate that the galvanometer-based photoacoustic microscopy system can accomplish label-free photoacoustic imaging and that it has clinical potential for use in the detection of erythrocytes and blood vessels. Zusammenfassung Ein markierungsfreies photoakustisches Mikroskopiesystem für die Angiographie wird vorgestellt, bestehend aus einem zweidimensionalen Galvanometerscanner, einer Objektivlinse, einem fokussierten Ultraschallwandler, einem Wasserbehälter und einem Probenhalter. Mit diesem System konnten in vivo Blutgefäße und Kapillaren am Rücken und am Ohr einer Maus eindeutig dargestellt werden. Außerdem war es möglich, ein dreidimensionales Bild des Gefäßnetzes am Rücken der Maus zu rekonstruieren. Ex-vivo-Erythrozyten wurden verwendet, um die Leistungsfähigkeit des Systems nachzuweisen, und ein einzelner Erythrozyt konnte mit hohem Kontrast abgebildet werden. Die experimentellen Ergebnisse zeigen, dass es möglich ist mit einem Galvanometer-basierten photoakustischen Mikroskopiesystem eine markierungsfreie photoakustische Bildgebung durchzuführen und dass dieses System klinisches Potenzial zur Detektion von Erythrozyten und Blutgefäßen hat.
Hemodynamic–Morphologic Discriminants for Intracranial Aneurysm Rupture

Background and Purpose— The purpose of this study was to identify significant morphological and hemodynamic parameters that discriminate intracranial aneurysm rupture status using 3-dimensional angiography and computational fluid dynamics. Methods— One hundred nineteen intracranial aneurysms (38 ruptured, 81 unruptured) were analyzed from 3-dimensional angiographic images and computational fluid dynamics. Six morphological and 7 hemodynamic parameters were evaluated for significance with respect to rupture. Receiver operating characteristic analysis identified area under the curve (AUC) and optimal thresholds separating ruptured from unruptured aneurysms for each parameter. Significant parameters were examined by multivariate logistic regression analysis in 3 predictive models—morphology only, hemodynamics only, and combined—to identify independent discriminants, and the AUC receiver operating characteristic of the predicted probability of rupture status was compared among these models. Results— Morphological parameters (size ratio, undulation index, ellipticity index, and nonsphericity index) and hemodynamic parameters (average wall shear stress [WSS], maximum intra-aneurysmal WSS, low WSS area, average oscillatory shear index, number of vortices, and relative resident time) achieved statistical significance (P<0.01). Multivariate logistic regression analysis demonstrated size ratio to be the only independently significant factor in the morphology model (AUC, 0.83; 95% CI, 0.75 to 0.91), whereas WSS and oscillatory shear index were the only independently significant variables in the hemodynamics model (AUC, 0.85; 95% CI, 0.78 to 0.93). The combined model retained all 3 variables, size ratio, WSS, and oscillatory shear index (AUC, 0.89; 95% CI, 0.82 to 0.96). Conclusion— All 3 models—morphological (based on size ratio), hemodynamic (based on WSS and oscillatory shear index), and combined—discriminate intracranial aneurysm rupture status with high AUC values. Hemodynamics is as important as morphology in discriminating aneurysm rupture status.
Pig latin: a not-so-foreign language for data processing

There is a growing need for ad-hoc analysis of extremely large data sets, especially at internet companies where innovation critically depends on being able to analyze terabytes of data collected every day. Parallel database products, e.g., Teradata, offer a solution, but are usually prohibitively expensive at this scale. Besides, many of the people who analyze this data are entrenched procedural programmers, who find the declarative, SQL style to be unnatural. The success of the more procedural map-reduce programming model, and its associated scalable implementations on commodity hardware, is evidence of the above. However, the map-reduce paradigm is too low-level and rigid, and leads to a great deal of custom user code that is hard to maintain, and reuse. We describe a new language called Pig Latin that we have designed to fit in a sweet spot between the declarative style of SQL, and the low-level, procedural style of map-reduce. The accompanying system, Pig, is fully implemented, and compiles Pig Latin into physical plans that are executed over Hadoop, an open-source, map-reduce implementation. We give a few examples of how engineers at Yahoo! are using Pig to dramatically reduce the time required for the development and execution of their data analysis tasks, compared to using Hadoop directly. We also report on a novel debugging environment that comes integrated with Pig, that can lead to even higher productivity gains. Pig is an open-source, Apache-incubator project, and available for general use.
MPICH-V2: a Fault Tolerant MPI for Volatile Nodes based on Pessimistic Sender Based Message Logging

Execution of MPI applications on clusters and Grid deployments suffering from node and network failures motivates the use of fault tolerant MPI implementations. We present MPICH-V2 (the second protocol of MPICH-V project), an automatic fault tolerant MPI implementation using an innovative protocol that removes the most limiting factor of the pessimistic message logging approach: reliable logging of in transit messages. MPICH-V2 relies on uncoordinated checkpointing, sender based message logging and remote reliable logging of message logical clocks. This paper presents the architecture of MPICH-V2, its theoretical foundation and the performance of the implementation. We compare MPICH-V2 to MPICH-V1 and MPICH-P4 evaluating a) its point-to-point performance, b) the performance for the NAS benchmarks, c) the application performance when many faults occur during the execution. Experimental results demonstrate that MPICH-V2 provides performance close to MPICH-P4 for applications using large messages while reducing dramatically the number of reliable nodes compared to MPICH-V1.