Miracle-dz/UniFAR-FTUs huggingface dataset:
Organic carbon distribution and water column respiration in the NW Africa-Canaries Coastal Transition Zone

The Canary Current (CC) is characterised by strong disruption of its flow by the Canaries Archipelago, which extends across the prevailing flow. In the Coastal Transition Zone (CTZ) downstream of the islands, a region of high mesoscale activity connects the eutrophic waters of the NW Africa coastal upwelling (UW) system with the oligotrophic open ocean waters of the eastern subtropical North Atlantic gyre (ESNA). We studied the distribution of particulate (POC) and dissolved organic carbon (DOC) and carbon remineralization rates in the 0 to 1000 m water column of this transitional region to assess its role in horizontal and vertical export of organic matter. The epipelagic waters (0 to 200 m) of the CTZ are characterised by higher mean surface integrated concentrations of POC (0.8 ± 0.4 mol C m -2 ) and DOC (17 ± 7 mol C m -2 ), and by higher community respiration (R >100 mmol C m -2 d -1 ) than the ESNA or UW waters. Integrated R was much lower (7 ± 3 mmol C m -2 d -1 ) in the mesopelagic zone (200 to 1000 m), indicating that most of the organic mat- ter was respired in the upper 200 m, with little being transported downwards. Nevertheless, peaks in DOC and R were observed at 300 to 600 m depth, coinciding with the depth of the deep scattering layer. These relative maxima were particularly important in the case of DOC, reaching concentra- tions comparable to surface waters (> 80 µM). In spite of this, DOC contributed only 26.5% to the apparent oxygen utilisation (AOU) in the mesopelagic zone. Correlations between R and particulate- and dissolved organic matter suggest that respiration was mainly supported by particulate material at surface and deep waters. We compared plankton metabolic balances along the UW, CTZ and ESNA. Our analyses show that during summer time, and probably during most of the year, the ESNA and CTZ behave as net heterotrophic regions. In spite of a relatively high primary production (P) favoured by mesoscale activity in the CTZ, plankton R clearly exceeds P as result of the excess carbon advected from the coastal UW. However, a significant amount of non-respired carbon must be trans- ported from the CTZ to the open ocean to account for part of the surface metabolic imbalance between P and R reported for the ESNA.
Large-Area Quantitative Phase Mapping in the Scanning Electron Microscope

Silicon-drift-based energy-dispersive X-ray spectrometers and spectral imaging data storage have expanded the possibilities for collecting high information-content X-ray data in a modern scanning electron microscope. The implementation of principal component analysis for phase determination combined with an automated stage and the capability to stitch together a series of sequentially collected images enables the collection and analysis of large-area quantitative phase maps for detailed materials characterization on practical time scales. The new approach provides significant improvements, particularly in speed and completeness of analysis. Examples show detailed quantitative analyses of a mineralogical sample and a complex
The development of microwave power amplifiers and nonlinear measurement systems - is the measurement systems manufacturer still lead by the PA designer?

Developments within modern nonlinear measurement systems offer an increasing degree of flexibility to the microwave power amplifier (PA) designer. The PA designer has historically been a driving factor in setting the development directions of new measurement systems, fueling the paradigm, that PA innovations largely push new measurement requirements. It would appear that measurement system manufacturers are now the ones pushing the technology envelope. This paper discusses current trends within modern nonlinear measurement systems to determine who is leading whom and whether the aforementioned paradigm is shifting.
Performance of a Hopping Rotochute

A hybrid micro air/ground vehicle has been developed and is specifically tailored to explore interior spaces with complex terrain. The vehicle, called the hopping rotochute, maneuvers through intricate environments by hopping over or through impeding obstacles. A small coaxial rotor system provides the necessary lift while a moveable internal mass allows directional control. In addition, the low mass center and egg-like exterior shape of the body creates a means to passively reorient the vehicle to an upright attitude when in contact with the ground while protecting the rotating components. This paper examines basic flight performance of the device obtained through a validated simulation. Key parameters such as system weight, rotor speed, internal mass weight and location, as well as battery capacity are varied to explore air vehicle performance characteristics such as single hop height and range, number of hops, and total achievable range. In general, the total achievable range is increased as the internal mass weight, internal mass offset, and battery capacity are increased. For a given system, an optimum rotor speed and pulse width results in the maximum achievable total range for a single battery charge. The sensitivity of the hopping rotochute to atmospheric winds is also investigated and the ability of the device to perform trajectory shaping is shown.
Detecting Human Actions in Surveillance Videos

This notebook paper summarizes Team NEC-UIUC’s approaches for TRECVid 2009 Evaluation of Surveillance Event Detection. Our submissions include two types of systems. One system employs the brute force search method to test each space-time location in the video by a binary classifier on whether a specific event occurs. The other system takes advantage of human detection and tracking to avoid the costly brute force search and evaluates the candidate space-time cubes by combining 3D convolutional neural networks (CNN) and SVM classifiers based on bag-ofwords local features to detect the presence of events of inte rests. Via thorough cross-validation on the development set , we select proper combining weights and thresholds to minimize the detection cost rates (DCR). Our systems achieve good performance on event categories which involve actions of a single person, e.g. CellToEar , ObjectPut , and Pointing.
Users' response to affective film content: A narrative perspective

In this paper, we take a human-centred view to the definition of the affective content of films. We investigate the relationship between users physiological response and multimedia features extracted from the movies, from the perspective of narrative evolution rather than by measuring average values. We found a certain dynamic correlation between arousal, derived from measures of Galvanic Skin Resistance during film viewing, and specific multimedia features in both sound and video domains. Dynamic physiological measurements were also consistent with post-experiment self-assessment by the subjects. These findings suggest that narrative aspects (including staging) are central to the understanding of video affective content, and that direct mapping of video features to emotional models taken from psychology may not capture these phenomena in a straightforward manner.
Assimilation of T-TREC-Retrieved Winds from Single-Doppler Radar with an Ensemble Kalman Filter for the Forecast of Typhoon Jangmi (2008)

AbstractA tropical cyclone (TC) circulation Tracking Radar Echo by Correlation technique (T-TREC) developed recently is applied to derive horizontal winds from single Doppler radar reflectivity Z data (combined with radial velocity Vr data when available). The typically much longer maximum range of Z observations compared to Vr data allows for much larger spatial coverage of the T-TREC-retrieved winds (VTREC) when a TC first enters the maximum range of a coastal radar. Retrieved using data from more than one scan volume, the T-TREC winds also contain valuable cross-beam wind information. The VTREC or Vr data at 30-min intervals are assimilated into the Advanced Regional Prediction System (ARPS) model at 3-km grid spacing using an ensemble Kalman filter, over a 2-h window shortly after Typhoon Jangmi (2008) entered the Vr coverage area of an operational weather radar of Taiwan. The assimilation of VTREC data produces analyses of the typhoon structure and intensity that more closely match observations than .
fMRI of alcohol craving after individual cues: A follow-up case report

Alcohol addiction is typically associated with intense alcohol craving triggered by internal or environmental cues linked with past alcohol use. We used functional magnetic resonance imaging (fMRI) to record cerebral correlates of craving in an alcoholic patient. Craving was evoked by highly individual cues associated with past alcohol use and was assessed before (T1) and after an 8-month period of psychotherapy (T2). To control for effects of life event memories related to non alcoholic cravings, the patient provided two events from periods of his life when he experienced caffeine craving. We detected activation of the superior temporal lobe during recall of a highly alcohol craving situation (T1 minus T2), whereas we did not observe any activation during coffee craving recall when pre und post activations were compared. These results indicate that the superior temporal lobe may be involved when alcohol craving is initiated by individual verbal cues. Further studies using individual cues are needed to explore the neural correlates of alcohol craving.
Risk factors for carpal tunnel syndrome in a general population.

OBJECTIVE: To determine the individual, physical, and psychosocial risk factors for carpal tunnel syndrome in a general population. METHODS: Population based case-control study in Marshfield epidemiological study area in Wisconsin, USA. Cases were men and women aged 18-69 with newly diagnosed carpal tunnel syndrome (n = 206 (83.1%) of 248 eligible). Controls were a random sample of residents of the study area who had no history of diagnosed carpal tunnel syndrome (n = 211 (81.5%) of 259 eligible). Cases and controls were matched by age. Telephone interviews and reviews of medical records obtained height and weight, medical history, average daily hours of exposure to selected physical and organisational work factors, and self ratings on psychosocial work scales. RESULTS: In the final logistic regression model, five work and three non-work variables were associated with risk of carpal tunnel syndrome, after adjusting for age. For each one unit of increase in body mass index (kg/m2), risk increased 8% (odds ratio (OR) 1.08; 95% confidence interval (95% CI) 1.03 to 1.14). Having a previous musculoskeletal condition was positively associated with carpal tunnel syndrome (OR 2.54; 95% CI 1.03 to 6.23). People reporting the least influence at work had 2.86 times the risk (95% CI, 1.10 to 7.14) than those with the most influence at work. CONCLUSIONS: Carpal tunnel syndrome is a work related disease, although some important measures of occupational exposure, including keyboard use, were not risk factors in this general population study. The mechanism whereby a weight gain of about six pounds increases the risk of disease 8% requires explanation.
Multiplexed Detection of O-GlcNAcome, Phosphoproteome, and Whole Proteome within the Same Gel

The cellular diversity of proteins results in part from their post-translational modifications. Among all of them, the O-GlcNAcylation is an atypical glycosylation, more similar to phosphorylation than classical glycosylations. Highly dynamic, reversible, and exclusively localized on cytosolic, nuclear, and mitochondrial proteins, O-GlcNAcylation is known to regulate almost all if not all cellular processes. Fundamental for the cell life, O-GlcNAcylation abnormalities are involved in the etiology of several inherited diseases. Assessing to O-GlcNAcylation pattern will permit to get relevant data about the role of O-GlcNAcylation in cell physiology. To get understanding about the role of O-GlcNAcylation, as also considering its interplay with phosphorylation, the O-GlcNAc profiling remains a real challenge for the community of proteomists/glycoproteomists. The development of multiplexed proteomics based on fluorescent detection of proteins permits to go further in the understanding of the proteome complexity. We propose herein a multiplexed proteomic strategy to detect O-GlcNAcylated proteins, phosphoproteins, and the whole proteome within the same bidimensional gel. In particular, we investigated the phosphoproteome through the ProQ Diamond staining, while the whole proteome was visualized through Sypro Ruby staining, or after the labeling of proteins with a T-Dye fluorophore. The O-GlcNAcome was revealed by the way of the Click chemistry and the azide–alkyne cycloaddition of a fluorophore on GlcNAc moieties. This method permits, after sequential image acquisition, the direct in-gel detection of O-GlcNAcome, phosphoproteome, and whole proteome.
Economics of smoking cessation

Smoking imposes a huge economic burden on society—currently up to 15% of total healthcare costs in developed countries. Smoking cessation can save years of life, at a very low cost compared with alternative interventions. This chapter reviews some of the economic aspects of smoking cessation. Self rated health status (100 = best imaginable health state), by age and smoking status. Data from Kind et al. UK population norms for EQ-5D. York: Centre for Health Economics (Discussion paper 172) The most obvious benefits of smoking cessation are improvements in life expectancy and prevention of disease. However, cessation also improves individuals' quality of life as smokers tend to have a lower self reported health status than non-smokers, and this improves after stopping smoking. View this table: Benefits of smoking cessation There are also wider economic benefits to individuals and society, arising from reductions in the effects of passive smoking in non-smokers and savings to the health service and the employer. These wider benefits are often omitted from economic evaluations of cessation interventions, which consequently tend to underestimate the true value for money afforded by such programmes. Many estimates have been made of the economic cost of smoking in terms of health resources. For the United States they typically range from about 0.6% to 0.85% of gross domestic product. In absolute terms, the US public health service estimates a total cost of $50bn (£29bn;€42bn) a year for the treatment of smoking related diseases, in addition to an annual $47bn in lost earnings and productivity. Estimated total costs in Australia and Canada, as a proportion of their gross domestic product, are 0.4% and 0.56% respectively. In the United Kingdom, the treatment of smoking related disease has been estimated to cost the NHS £1.4bn-£1.5bn a year (about 0.16% of the gross domestic product)—including £127m to treat lung cancer …
Network security and anomaly detection with Big-DAMA, a big data analytics framework

The complexity of the Internet and the volume of network traffic have dramatically increased in the last few years, making it more challenging to design scalable Network Traffic Monitoring and Analysis (NTMA) systems. Critical NTMA applications such as the detection of network attacks and anomalies require fast mechanisms for on-line analysis of thousands of events per second, as well as efficient techniques for off-line analysis of massive historical data. The high-dimensionality of network data provided by current network monitoring systems opens the door to the massive application of machine learning approaches to improve the detection and classification of network attacks and anomalies, but this higher dimensionality comes with an extra data processing overhead. In this paper we present Big-DAMA, a big data analytics framework (BDAF) for NTMA applications. Big-DAMA is a flexible BDAF, capable to analyze and store big amounts of both structured and unstructured heterogeneous data sources, with both stream and batch processing capabilities. Big-DAMA uses off-the-shelf big data storage and processing engines to offer both stream data processing and batch processing capabilities, decomposing separate engines for stream, batch and query, following a Data Stream Warehouse (DSW) paradigm. Big-DAMA implements several algorithms for anomaly detection and network security using supervised and unsupervised machine learning (ML) models, using off-the-shelf ML libraries. We apply Big-DAMA to the detection of different types of network attacks and anomalies, benchmarking multiple supervised ML models. Evaluations are conducted on top of real network measurements collected at the WIDE backbone network, using the well-known MAWILab dataset for attacks labeling. Big-DAMA can speed up computations by a factor of 10 when compared to a standard Apache Spark cluster, and can be easily deployed in cloud environments, using hardware virtualization technology.
Elastic strain effects on the catalytic response of Pt and Pd thin films deposited on Pd–Zr metallic glass

In this study, the influence of an externally applied elastic strain on the electrochemical activity of metal film catalysts during the oxygen reduction reaction (ORR) was examined. A novel three-layer specimen, composed of a 10 nm-thick Pt or Pd surface film on a 20 nm-thick Pd_70Zr_30 metallic glass film that was first deposited on a polymer substrate was used. The intermediate metallic glass layer is instrumental in allowing the top-layer catalytic film to be elastically deformed to a large elastic strain, (up to 2%), enabling a strain effect to be clearly observed. The results consistently show that an applied compressive strain improves the ORR catalytic activity of the Pd and Pt surface layer, while a tensile strain degrades it. These experimental findings are consistent with the prediction of the d-band model, and provide an opportunity to improve the catalytic response during ORR.
Exploration of sonification design process through an interdisciplinary workshop

In sonification of scientific data, designers know very little about the domain science and domain scientists are not familiar with the sonification methodology. The knowledge about the domain science is not given, but evolved during the problem-solving process. We discuss design challenges in auditory display design regarding user-centered approaches and suggest a method to involve domain scientists throughout sonification designs. We explore this within a workshop in which sonification experts, domain experts, and programmers worked together to better understand and solve problems collaboratively. The sonification framework that is used during the workshops is briefly described and the workshop process and how each group worked together during the workshop sessions are examined. Participants worked on pre-defined and exploratory tasks to sonify climate data. Furthermore, they grasped each other's domains; climate scientists especially became more open to use auditory display and sonification as a tool in their data mining tasks. Resulting sonification prototypes and workshop sessions are documented on a wiki to be used by the sonification community. To get started, we used some of the sonification designs created during the workshop for an online study where participants from science, engineering, and humanities were asked questions about the data behavior by listening to sonifcations of bivariate time series. Results indicate that sonic representation of data from resulting sonification allows most users (even with little or no knowledge of sound and music) to successfully complete some common data exploration tasks.
Semi-Supervised Classifier Ensembles for Classifying Remote Sensing Data

The analysis of data sets, which were acquired within different time periods over the same geographical region is interesting for updating land cover maps and operational monitoring systems. In this context an adequate and temporally stable classification approach is worthwhile. In the presented study a classifier ensemble (i.e., random forests) is trained on a multispectral image from an agricultural region from and is successively modified and adapted, to classify a data set from another year. A detailed accuracy assessment clearly demonstrates that the proposed modification of the classifier significantly improves the overall accuracy, whereas a simple transfer of a classifier to a data set from another year is limited and results in a decreased accuracy. Thus the proposed approach can be recommended for classifying multiannual data sets and updating land cover maps.
Keddah: Capturing Hadoop Network Behaviour

As a distributed system, Hadoop heavily relies on the network to complete data processing jobs. While Hadoop traffic is perceived to be critical for job execution performance, the actual behaviour of Hadoop network traffic is still poorly understood. This lack of understanding greatly complicates research relying on Hadoop workloads. In this paper, we explore Hadoop traffic through experimentation. We analyse the generated traffic of multiple types of MapReduce jobs, with varying input sizes, and cluster configuration parameters. As a result, we present Keddah, a toolchain for capturing, modelling and reproducing Hadoop traffic, for use with network simulators. Keddah can be used to create empirical Hadoop traffic models, enabling reproducible Hadoop research in more realistic scenarios.
Nearly tight bounds for testing function isomorphism

We study the problem of testing isomorphism (equivalence up to relabelling of the variables) of two Boolean functions <i>f,g</i>: {0, 1}<sup><i>n</i></sup> → {0, 1}. Our main focus is on the most studied case, where one of the functions is given (explicitly) and the other function may be queried. We prove that for every <i>k</i> ≤ <i>n</i>, the worst-case query complexity of testing isomorphism to a given <i>k</i>-junta is Ω(<i>k</i>) and <i>O</i>(<i>k</i> log <i>k</i>). Consequently, the query complexity of testing function isomorphism is θ(<i>n</i>). Prior to this work, only lower bounds of Ω(log <i>k</i>) queries were known, for limited ranges of <i>k</i>, proved by Fischer et al. (FOCS 2002), Blais and O'Donnell (CCC 2010), and recently by Alon and Blais (RANDOM 2010). The nearly tight <i>O</i>(<i>k</i> log <i>k</i>) upper bound improves on the <i>Õ</i>(<i>k</i><sup>4</sup>) upper bound from Fischer et al. (FOCS 2002). Extending the lower bound proof, we also show polynomial query-complexity lower bounds for the problems of testing whether a function can be computed by a circuit of size ≤ <i>s</i>, and testing whether the Fourier degree of a function is ≤ <i>d</i>. This answers questions posed by Diakonikolas et al. (FOCS 2007). We also address two closely related problems -- 1. Testing isomorphism to a <i>k</i>-junta with one-sided error: we prove that for any 1 < <i>k</i> < <i>n</i> − 1, the query complexity is Ω(log (<sup><i>n</i></sup><sub><i>k</i></sub>)), which is almost optimal. This lower bound is a consequence of a proof that the query complexity of testing, with one-sided error, whether a function is a <i>k</i>-parity is Θ(log (<sup><i>n</i></sup><sub><i>k</i></sub>). 2. Testing isomorphism between two unknown functions that can be queried: we prove that the query complexity in this setting is Ω(√2<sup><i>n</i></sup>) and <i>O</i>(√2<sup><i>n</i></sup><i>n</i> log <i>n</i>).
EXPONENTIAL STABILITY OF LINEAR STOCHASTIC DIFFERENTIAL EQUATIONS WITH BOUNDED DELAY AND THE W-TRANSFORM

We demonstrate how the method of auxiliary ('reference') equations, also known as N. V. Azbelev's W-transform method, can be used to derive efficientconditions for the exponential Lyapunov stability of linear delay equations driven by a vector-valued Wiener process. For the sake of convenience the W-method is briefly outlined in the paper, its justification is however omitted. The paper contains a general stability result, which is specified in the last section in the form of seven corollaries providing sufficient stability conditions for some important classes of Ito equations with delay.