Miracle-dz/UniFAR-FTUs huggingface dataset:
Exacerbated Airway Toxicity of Environmental Oxidant Ozone in Mice Deficient in Nrf2

Ozone (O3) is a strong oxidant in air pollution that has harmful effects on airways and exacerbates respiratory disorders. The transcription factor Nrf2 protects airways from oxidative stress through antioxidant response element-bearing defense gene induction. The present study was designed to determine the role of Nrf2 in airway toxicity caused by inhaled O3 in mice. For this purpose, Nrf2-deficient (Nrf2−/−) and wild-type (Nrf2+/+) mice received acute and subacute exposures to O3. Lung injury was determined by bronchoalveolar lavage and histopathologic analyses. Oxidation markers and mucus hypersecretion were determined by ELISA, and Nrf2 and its downstream effectors were determined by RT-PCR and/or Western blotting. Acute and sub-acute O3 exposures heightened pulmonary inflammation, edema, and cell death more severely in Nrf2−/− mice than in Nrf2+/+ mice. O3 caused bronchiolar and terminal bronchiolar proliferation in both genotypes of mice, while the intensity of compensatory epithelial proliferation, bronchial mucous cell hyperplasia, and mucus hypersecretion was greater in Nrf2−/− mice than in Nrf2+/+ mice. Relative to Nrf2+/+, O3 augmented lung protein and lipid oxidation more highly in Nrf2−/− mice. Results suggest that Nrf2 deficiency exacerbates oxidative stress and airway injury caused by the environmental pollutant O3.
Virtual Cluster Scheduling Through the Scheduling Graph

This paper presents an instruction scheduling and cluster assignment approach for clustered processors. The proposed technique makes use of a novel representation named the scheduling graph which describes all possible schedules. A powerful deduction process is applied to this graph, reducing at each step the set of possible schedules. In contrast to traditional list scheduling techniques, the proposed scheme tries to establish relations among instructions rather than assigning each instruction to a particular cycle. The main advantage is that wrong or poor schedules can be anticipated and discarded earlier. In addition, cluster assignment of instructions is performed using another novel concept called virtual clusters, which define sets of instructions that must execute in the same cluster. These clusters are managed during the deduction process to identify incompatibilities among instructions. The mapping of virtual to physical clusters is postponed until the scheduling of the instructions has finalized. The advantages this novel approach features include: (1) accurate scheduling information when assigning, and, (2) accurate information of the cluster assignment constraints imposed by scheduling decisions. We have implemented and evaluated the proposed scheme with superblocks extracted from Speclnt95 and MediaBench. The results show that this approach produces better schedules than the previous state-of-the-art. Speed-ups are up to 15%, with average speed-ups ranging from 2.5% (2-Clusters) to 9.5% (4-Clusters)
Executive functions and parenting behaviors in association with medical adherence and autonomy among youth with spina bifida.

OBJECTIVE This study was designed to examine whether executive functions and parenting behaviors (acceptance, behavioral control, and psychological control) are associated with medical adherence and autonomy among preadolescents and adolescents with spina bifida (SB). METHODS Questionnaire and observational data were collected from a sample of 8-15 year olds with SB (N = 140) and their mothers, fathers, and teachers. Youth also completed neuropsychological testing. RESULTS Youth with SB demonstrated impairment on measures of executive functions, based on questionnaire and test data. Executive functions (questionnaire data only) and parenting behaviors were associated with medical adherence, but only executive functions (test data only) were associated with medical autonomy. Analyses also suggest that maternal and paternal behavioral control and paternal psychological control moderate relations between executive functions and adherence. CONCLUSIONS Interventions that target executive functions and parenting behaviors may facilitate positive health care behavior outcomes among youth with SB.
Enabling Dark Energy Science with Deep Generative Models of Galaxy Images

Understanding the nature of dark energy, the mysterious force driving the accelerated expansion of the Universe, is a major challenge of modern cosmology. The next generation of cosmological surveys, specifically designed to address this issue, rely on accurate measurements of the apparent shapes of distant galaxies. However, shape measurement methods suffer from various unavoidable biases and therefore will rely on a precise calibration to meet the accuracy requirements of the science analysis. This calibration process remains an open challenge as it requires large sets of high quality galaxy images. To this end, we study the application of deep conditional generative models in generating realistic galaxy images. In particular we consider variations on conditional variational autoencoder and introduce a new adversarial objective for training of conditional generative networks. Our results suggest a reliable alternative to the acquisition of expensive high quality observations for generating the calibration data needed by the next generation of cosmological surveys.
Singer Identification in Rembetiko Music

In this paper, the problem of the automatic identification of a singer is investigated using methods known from speaker identification. Ways for using world models are presented and the usage of Cepstral Mean Subtraction (CMS) is evaluated. In order to minimize the difference due to musical style we use a novel data set, consisting of samples from greek Rembetiko music, being very similar in style. The data set also explores for the first time the influence of the recording quality, by including many historical gramophone recordings. Experimental evaluations show the benefits of world models for frame selection and CMS, resulting in an average classification accuracy of about 81% among 21 different singers.
How Many Different "John Smiths", and Who Are They?

In this work we propose three unsupervised measures to automatically identify the number of distinct entities a given ambiguous name refers to in a corpus. We experiment with 22 artificially created name conflations and observe that the measure (PK2) formulated as the ratio of two successive clustering criterion function values outperforms the other two measures. We also describe a method to assign a unique label to each discovered cluster so as to identify the underlying entity that it refers to.
Rest-based sensor networks with OData

RESTful services gained a lot of attention recently, even in the enterprise world, which is traditionally more web-service centric. Data centric RESfFul services, as previously mainly known in web environments, established themselves as a second paradigm complementing functional WSDL-based SOA. In the Internet of Things, and in particular when talking about sensor motes, the Constraint Application Protocol (CoAP) is currently in the focus of both research and industry. In the enterprise world a protocol called OData (Open Data Proto-col) is becoming the future RESTful data access standard. To integrate sensor motes seamlessly into enterprise networks, an embedded OData implementation on top of CoAP is desirable, not requiring an intermediary gateway device. In this paper we introduce and evaluate an embedded OData implementation. We evaluate the OData protocol in terms of performance and energy consumption, considering different data encodings, and compare it to a pure CoAP implementation. We were able to demonstrate that the additional resources needed for an OData/JSON implementation are reasonable when aiming for enterprise interoperability, where OData is suggested to solve both the semantic and technical interoperability problems we have today when connecting systems.
Chemical composition of free tropospheric aerosol for PM1 and coarse mode at the high alpine site Jungfraujoch

The chemical composition of submicron (fine mode) and supermicron (coarse mode) aerosol particles has been investigated at the Jungfraujoch high alpine research station (3580 m a.s.l., Switzerland) as part of the GAW aerosol monitoring program since 1999. A clear seasonality was observed for all major components throughout the pe- riod with low concentrations in winter (predominantly free tropospheric aerosol) and higher concentrations in summer (enhanced vertical transport of boundary layer pollutants). In addition, mass closure was attempted during intensive cam- paigns in March 2004, February-March 2005 and August 2005. Ionic, carbonaceous and non-refractory components of the aerosol were quantified as well as the PM1 and coarse mode total aerosol mass concentrations. A relatively low conversion factor of 1.8 for organic carbon (OC) to partic- ulate organic matter (OM) was found in winter (February- March 2005). Organics, sulfate, ammonium, and nitrate were the major components of the fine aerosol fraction that were identified, while calcium and nitrate were the only two measured components contributing to the coarse mode. The aerosol mass concentrations for fine and coarse mode aerosol measured during the intensive campaigns were not typical of the long-term seasonality due largely to dynam- ical differences. Average fine and coarse mode concentra- tions during the intensive field campaigns were 1.7 µg m 3 and 2. 4µg m 3 in winter and 2. 5µg m 3 and 2. 0µg m 3 in summer, respectively. The mass balance of aerosols showed higher contributions of calcium and nitrate in the coarse mode during Saharan dust events (SDE) than without SDE.
Real-time Stereo Visual SLAM

Simultaneous localisation and mapping (SLAM) has been the focus of intensive research in the last decade due to the potential benefits it offers to the field of autonomous mobile robotics. SLAM is concerned with the ability of an autonomous vehicle to navigate through an unexplored environment and incrementally construct a map of the environment and localise itself within this map. This thesis describes an entirely vision-based, large-area, 6DoF SLAM system that was developed specifically for real-time deployment on an autonomous underwater vehicle (AUV) equipped with a calibrated stereo system. This SLAM system is based on the extended Kalman filter (EKF) and incorporates a novel approach to landmark description and data association in which landmarks are essentially local submaps that consist of a cloud of 3D points and their associated SIFT or SURF descriptors. Furthermore, landmarks are sparsely distributed in the constructed map which greatly simplifies and accelerates data association and map updates. In addition to performing localisation based on landmark observations the system also performs visual odometry and predicts vehicle motion using a constant-velocity model. For a simulated 87m long 3D loop trajectory the mean squared localisation error of the system was 3.16 and the maximum absolute error in roll, pitch and yaw angles was 11.6, 24.3 and 24.4 respectively when the stereo and landmark correspondences contained Gaussian noise with a standard deviation of 0.1 pixels and 10% of correspondences were outliers. This thesis represents an important contribution to entirely vision-based 6DoF SLAM as very few implementations currently exist, and the approach utilised in this thesis achieves comparable results and has the potential to operate in real-time. I have yet to see any problem, however complicated, which, when you looked at it the right way, did not become still more complicated.
A system for flexible parallel execution

Exponential growth in transistor density combined with diminishing returns from uniprocessor improvements has compelled the industry to transition to multicore architectures. To realize the performance potential of multicore architectures, programs must be parallelized effectively. The efficiency of parallel program execution depends on the execution environment comprised of workload, platform, and performance goal. In writing parallel programs, most programmers and compilers expose parallelism and optimize it to meet a particular performance goal on a single platform under an assumed set of workload characteristics. In the field, changing workload characteristics, new parallel platforms, and deployments with different performance goals make the programmer's or compiler's development-time or compile-time choices suboptimal. This dissertation presents Parcae1, a generally applicable holistic system for platform-wide dynamic parallelism tuning. Parcae includes: (1) the Nona compiler, which applies a variety of auto-parallelization techniques to create flexible parallel programs whose tasks can be efficiently paused, reconfigured, and resumed during execution; (2) the Decima monitor, which measures resource availability and system performance to detect change in the environment; and (3) the Morta executor, which cuts short the life of executing tasks, replacing them with other functionally equivalent tasks better suited to the current environment. Parallel programs made flexible by Parcae outperform original parallel implementations in a variety of interesting scenarios. 1According to Roman mythology, the Parcae are the Three Fates that control the metaphorical thread of life of each mortal. They are Nona, who creates the thread of life; Decima, who measures the thread of life; and Morta, who cuts the thread of life.
Proposal Title : Developing Cyber-Physical Systems : Autonomous Vehicles in Regular Traffic

“Cyber-physical systems (CPS) are engineered systems that are built from and depend upon the synergy of computational and physical components. Emerging CPS will be coordinated, distributed, and connected, and must be robust and responsive. ” (From NSF – USA). In this tutorial we will cover aspects of the analysis and synthesis of CPS, concentrating on the design of Autonomous Vehicles. We shall specifically consider autonomous and semiautonomous cars in a street network, interacting with human-driven cars. Topics that will be covered are:  Modeling of interconnected dynamic systems  Information and coordination hierarchies  Hybrid system modeling  Autonomous vehicles  Examples from o The Urban Challenge o An intersection approach o 4 communicating cars
Supplementary Data Figure 1 : Expression of Flag-trf1

The pI-TRF1 or the pIRES plasmid DNAs were transfected in the 3B10 and 2A3 pCMV clones and the 4C4 and 4C11 pCMVTelo clones. Four days post-transfection, a neomycin selection was applied (t0) and cells were cultured under selection during more than 30 MPDs. Images (A-C) : Immunofluorescence of a group of 4C11 cells transfected with pITRF1 at 20 MPDs post-selection. Cells were grown on slides and fixed for 20 min. in methanol at –20°C and air dried. Slides were then blocked for 1h in blocking solution (0.8xPBS/50mM NaCl/0.5% Triton X100/1% Blocking Reagent (ROCHE BIOCHEMICALS, Germany)), incubated 1h at 37°C in blocking solution with anti-FLAG antibodies, washed 3 times 10 min. in 0.8xPBS/50mM NaCl/0.5% Blocking Reagent, incubated 1h at 37°C with an ALEXA488-conjugated anti-mouse secondary antibody (MOLECULAR PROBES) in blocking solution (1:500), washed 3 times 10 min. in 0.8xPBS/50mM NaCl/0.1% Triton X100, and finally stained in propidium iodide (0.2µg/ml) and mounted in VECTA S HIELD (VECTOR LABORATORIES). (A) propidium iodide counterstaining; (B) anti-FLAG antibodies coupled
Shared Control between Human and Machine: Using a Haptic Steering Wheel to Aid in Land Vehicle Guidance

When humans interface with machines, the control interface is usually passive and its response contains little information pertinent to the state of the environment. Usually, information flows through the interface from human to machine but not so often in the reverse direction. This work proposes a control architecture in which bi-directional information transfer occurs across the control interface, allowing the human to use the interface to simultaneously exert control and extract information. In this alternative control architecture, which we call shared control, the human utilizes the haptic sensory modality to share control of the machine interface with an automatic controller. We present a fixed-base driving simulator experiment in which subjects take advantage of a haptic steering wheel, which aids them in a path following task. Results indicate that the haptic steering wheel allows a significant reduction in visual demand while improving path following performance.
Abordagens evolucionárias para problemas relacionados a integração de dados

Data integration aims to combine data from di erent sources (data repositories such as databases, digital libraries, etc.) by adopting a global data model and by detecting and resolving schema and data con icts so that a homogeneous, uni ed view can be provided. Two speci c problems related to data integration schema matching and replica identi cation present a large solution space. This space is computationally expensive and technically prohibitive to be intensively and exhaustively explored by traditional approaches. Moreover, the solutions for these problems usually require that multiple, sometimes con icting, objectives must be simultaneously attended. This thesis aims to show that evolutionary-based techniques can be successfully applied to such problems, leading to novel approaches and methods that address all aforementioned requirements and, at the same time, provide e cient and high accuracy solutions. In this thesis, we rst propose a genetic programming approach to record deduplication. This approach combines several di erent pieces of evidence extracted from the actual data present in the repositories to suggest a deduplication function that is able to identify whenever two entries in a repository are replicas or not. As shown by our experiments, our approach outperforms existing state-of-the-art methods found in the literature. Moreover, the suggested function is computationally less demanding since it uses fewer evidence. Finally, it is also important to notice that our approach is capable of automatically adapting to a given xed replica identi cation boundary, freeing the user from the burden of having to choose and tune this parameter Based on the previous approach, we also devised a novel evolutionary approach xv that is able to automatically nd complex schema matches. Our aim was to develop a method to nd semantic relationships between schema elements, in a restricted scenario in which only the data instances are available. To the best of our knowledge, this is the rst approach that is capable of discovering complex schema matches using only the data instances, which is performed by exploiting record deduplication and information retrieval techniques to nd schema matches during the evolutionary process. To demonstrate the e ectiveness of our approach, we conducted an experimental evaluation using real-world and synthetic datasets. Our results show that our approach is able to nd complex matches with high accuracy, despite using only the data instances.
Correlation of LNCR rasiRNAs Expression with Heterochromatin Formation during Development of the Holocentric Insect Spodoptera frugiperda

Repeat-associated small interfering RNAs (rasiRNAs) are derived from various genomic repetitive elements and ensure genomic stability by silencing endogenous transposable elements. Here we describe a novel subset of 46 rasiRNAs named LNCR rasiRNAs due to their homology with one long non-coding RNA (LNCR) of Spodoptera frugiperda. LNCR operates as the intermediate of an unclassified transposable element (TE-LNCR). TE-LNCR is a very invasive transposable element, present in high copy numbers in the S. frugiperda genome. LNCR rasiRNAs are single-stranded RNAs without a prominent nucleotide motif, which are organized in two distinct, strand-specific clusters. The expression of LNCR and LNCR rasiRNAs is developmentally regulated. Formation of heterochromatin in the genomic region where three copies of the TE-LNCR are embedded was followed by chromatin immunoprecipitation (ChIP) and we observed this chromatin undergo dynamic changes during development. In summary, increased LNCR expression in certain developmental stages is followed by the appearance of a variety of LNCR rasiRNAs which appears to correlate with subsequent accumulation of a heterochromatic histone mark and silencing of the genomic region with TE-LNCR. These results support the notion that a repeat-associated small interfering RNA pathway is linked to heterochromatin formation and/or maintenance during development to establish repression of the TE-LNCR transposable element. This study provides insights into the rasiRNA silencing pathway and its role in the formation of fluctuating heterochromatin during the development of one holocentric organism.
Enhancing software module reusability using port plug-ins: An experiment with the iCub robot

Systematically developing high-quality reusable software components is a difficult task and requires careful design to find a proper balance between potential reuse, functionalities and ease of implementation. Extendibility is an important property for software which helps to reduce cost of development and significantly boosts its reusability. This work introduces an approach to enhance components reusability by extending their functionalities using plug-ins at the level of the connection points (ports). Application-dependent functionalities such as data monitoring and arbitration can be implemented using a conventional scripting language and plugged into the ports of components. The main advantage of our approach is that it avoids to introduce application-dependent modifications to existing components, thus reducing development time and fostering the development of simpler and therefore more reusable components. Another advantage of our approach is that it reduces communication and deployment overheads as extra functionalities can be added without introducing additional modules. The details of the plug-in system is described in the paper and its advantages for the development of robotics applications are demonstrated by developing a step-by-step example on the iCub humanoid robot.
Fetal ECG extraction based on adaptive filters and Wavelet Transform: Validation and application in fetal heart rate variability analysis

The analysis of cardiac electrical activity in the fetus (fECG) has become a crucial tool for monitoring the physiological condition of the fetus during pregnancy. In this paper we present a new method for extraction of fetal ECG based on wavelet decomposition and an adaptive filter noise canceller with the least mean square algorithm (LMS). Firstly, the interfering signals are removed, with a FIR filter and Wavelet analysis. The detail coefficients corresponding to the reference signal (thoracic signal) and the input signal (abdominal signal) with greater similarity in shape are processed with the algorithm LMS, and is applied Stationary Wavelet Transform (SWT) as a filter and finally the coefficients were reconstructed by inverse SWT to obtain fECG. The algorithm has been tested on 10 non-invasive records from Database for the Identification of Systems (DaISy) and MIT/PhysioNet database; the signals were recorded from different women with gestational age between 35 and 40 weeks of gestation. The evaluation of the proposed method, showing a 96% accuracy by identifying the R wave of fECG are considered promising for future work. The algorithm has been applied in the analysis of fetal heart rate (fHR) and fetal heart rate variability (fHRV) that are indicators of fetal suffering and hypoxia.