Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and analysis of a micro pressure sensor with optical fiber

We described an optical micro-electro-mechanical-system (MEMS) pressure sensor based on light intensity modulation that can be used in petrochemical and oil well area. The idea is to use light for transmission to replace electrical signals. Utilizing bulk micromachining technology of silicon, a membrane is obtained for sensing pressure and reflecting the light. The intensity of reflected light shifts when the membrane deforms caused by the loaded pressure. The intensity shift of reflected light can be measured by the photoelectric detection circuit that converts light intensity to voltage, so the loaded pressure can be gauged. The micro machining technology minimizes sensor size. Optical fiber is used to conduct light which makes the sensor be isolated from electricity. The sensor has been fabricated and encapsulated and the photoelectric detection circuit has been completed. The measurement range is 0~20MPa and the experimental sensitivity is 7.2mV/MPa.
Use of PALSAR polarimetric data for tropical forest stratification and comparison of simulated dual and compact polarimetric modes

This paper presents a case study addressing the comparison between different SAR polarimetric mode for tropical forest stratification: Full polarimetry (FP), Dual Polarimetry (DP) and Compact Polarimetry (CP). These 2 latter modes are simulated using FP data acquired by the L band PALSAR sensor over 2 study sites. Cayenne in French Guyana and the Fazenda São Nicolau in Brazil. The classification approach used to evaluate each mode based on Support Vector Machine (SVM) algorithm shows the good capabilities of the FP mode to discriminate different kinds of vegetation. The choice of one DP mode that gives twice bigger swath than FP mode depends on the study classes. In this tropical environment the hh/hv existing mode seems to be a good choice and CP mode show a good alternative to all the actual DP modes.
In vitro enzymatic activity of human immunodeficiency virus type 1 reverse transcriptase mutants in the highly conserved YMDD amino acid motif correlates with the infectious potential of the proviral genome

Reverse transcriptases contain a highly conserved YXDD amino acid motif believed to be important in enzyme function. The second amino acid is not strictly conserved, with a methionine, valine or alanine occupying the second position in reverse transcriptases from various retroviruses and retroelements. Recently, a 3.5-A (0.35-nm) resolution electron density map of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase positioned the YMDD motif within an antiparallel beta-hairpin structure which forms a portion of its catalytic site. To further explore the role of methionine of the conserved YMDD motif in HIV-1 reverse transcriptase function, we have substituted methionine with a valine, alanine, serine, glycine, or proline, reflecting in some cases sequence motifs of other related reverse transcriptases. Wild-type and mutant enzymes were expressed in Escherichia coli, partially purified by phosphocellulose chromatography, and assayed for the capacity to polymerize TTP by using a homopolymeric template [poly(rA)] with either a DNA [oligo(dT)] or an RNA [oligo(U)] primer. With a poly(rA). oligo(dT) template-primer, reverse transcriptases with the methionine replaced by valine (YVDD), serine (YSDD), or alanine (YADD) were 70 to 100% as active as the wild type, while those with the glycine substitution (YGDD) were approximately 5 to 10% as active. A proline substitution (YPDD) completely inactivated the enzyme. With a poly(rA). oligo(U) template-primer, only the activity of mutants with YVDD was similar to that of the wild type, while mutants with YADD and YSDD were approximately 5 to 10% as active as the wild-type enzyme. The reverse transcriptases with the YGDD and YPDD mutations demonstrated no activity above background. Proviruses containing the reverse transcriptase with the valine mutation (YVDD) produced viruses with infectivities similar to that of the wild type, as determined by measurement of p24 antigen in culture supernatants and visual inspection of syncytium formation. In contrast, proviruses with reverse transcriptases containing the YADD and YSDD mutations were less infectious than wild-type virus. These results point to the critical role of methionine of the YMDD motif in the activity of HIV-1 reverse transcriptase and subsequent replication potential of the virus.
Network anomography

Anomaly detection is a first and important step needed to respond to unexpected problems and to assure high performance and security in IP networks. We introduce a framework and a powerful class of algorithms for network anomography, the problem of inferring network-level anomalies from widely available data aggregates. The framework contains novel algorithms, as well as a recently published approach based on Principal Component Analysis (PCA). Moreover, owing to its clear separation of inference and anomaly detection, the framework opens the door to the creation of whole families of new algorithms. We introduce several such algorithms here, based on ARIMA modeling, the Fourier transform, Wavelets, and Principal Component Analysis. We introduce a new dynamic anomography algorithm, which effectively tracks routing and traffic change, so as to alert with high fidelity on intrinsic changes in network-level traffic, yet not on internal routing changes. An additional benefit of dynamic anomography is that it is robust to missing data, an important operational reality. To the best of our knowledge, this is the first anomography algorithm that can handle routing changes and missing data. To evaluate these algorithms, we used several months of traffic data collected from the Abilene network and from a large Tier-1 ISP network. To compare performance, we use the methodology put forward earlier for the Abilene data set. The findings are encouraging. Among the new algorithms introduced here, we see: high accuracy in detection (few false negatives and few false positives), and high robustness (little performance degradation in the presence of measurement noise, missing data and routing changes).
Heterogeneity within the native range: population genetic analyses of sympatric invasive and noninvasive clades of the freshwater invading copepod Eurytemora affinis

Invasive species are often composed of highly differentiated populations or sibling species distributed across their native ranges. This study analysed patterns of distribution and the evolutionary and demographic histories of populations within the native range of the copepod species complex Eurytemora affinis. Genetic structure was analysed for samples from 17 locations from both the invaded and native ranges in the St Lawrence River drainage basin, using 652 base pairs of the mitochondrial cytochrome oxidase subunit I gene. This study revealed a high degree of heterogeneity in genetic structure and habitat type in the native range, as well as a bias in the sources of invasive populations. Two genetically distinct clades showed a pattern of niche partitioning within the St Lawrence basin. The noninvasive North Atlantic clade primarily occupied the central portion of the St Lawrence Middle Estuary, whereas the invasive Atlantic clade was more prevalent along the margins, in the upstream reaches of the estuary and downstream salt marshes. Habitat partitioning and genetic subdivision was also present within the Atlantic clade. The freshwater populations were genetically more proximate to the Atlantic clade populations in the estuary than to those in the salt marsh, suggesting the estuary as the source of the invasive populations. The freshwater invading populations showed evidence of a modest population bottleneck. Populations from both clades showed genetic signatures of demographic population expansions that preceded the timing of the last glacial maximum, supporting the St Lawrence as a secondary contact zone between the two clades. Additional analyses on physiological and evolutionary properties of populations in the native range, along with analysis of the selection regime within native habitats, might yield insights into the evolutionary potential to invade.
Study of macro-segregations in a continuously cast billet

Ta clanek obravnava studij makro-izcej na vzdolžnem prerezu kontinuirno ulite gredice O 160 mm namenjene za proizvodnjo brezsivnih cevi. Ocena je sestavljena iz vizuelnega pregleda po makrojedkanju, iz ocene in kvantitativne rentgenske mikroanalize s pomocjo energijsko disperzijske rentgenske analize (EDX) izbranih podrocij. Izracunani so bili tudi parametri izcejanja s pomocjo podatkov zgorevne analize. Rezultati, prikazani v tem clanku, predstavljajo osnovno informacijo o notranji strukturi v kontinuirno uliti gredici. Rezultati bodo uporabljeni, poleg drugega, tudi za preverjanje rezultatov numericnega modeliranja kontinuirno ulitih gredic.
Bionic camouflage underwater acoustic communication based on sea lion sounds

In military confrontation, traditional underwater acoustic communication techniques with fixed frequency and modulation fashion are likely to result in the exposure of the submarine's position. It is helpful for enhance the submarine's concealment to use the sea background noise as carrier to perform communication. In this paper, a novel covert underwater communication method based on sea lion sounds is proposed. Properties of sea lion sounds are investigated firstly. According to the analysis result, sea lion click sound is used as information carrier and whistles are used as synchronization. Information is modulated on the compressed click based on the dual-orthogonal modulation method. For improving the receiving SNR, the channel equalization is performed by passive time reversal mirror technique, whereas channel estimation is done through matching pursuit method under the theory of compressed sensing. The efficiency and feasibility of the proposed method are verified by the simulation.
Sequencing of the Pseudomonas aeruginosa and Burkholderia cepacia genomes and their applications in relation to cystic fibrosis.

Determination of the complete DNA sequence of an organism (genome sequencing) is one of the greatest recent revolutions to have taken place in biology. Understanding the genes and complete genetic information present within an organism provides scientists with a blue-print for all its functions and capabilities. Hence for pathogenic bacteria, genome sequencing greatly enhances our understanding of how they cause disease and also enables the design of rationale strategies to prevent and treat infection. The Gram-negative bacteria, Pseudomonas aeruginosa and the Burkholderia cepacia complex, cause devastating respiratory infections in patients with cystic ﬁbrosis (CF). The complete genome sequence of P. aeruginosa was determined during the late 1990s, published in 2000 and has already led to signiﬁcant advances in how we study its role in CF lung disease. B. cepacia complex bacteria form a group of closely related species and a representative of the most prevalent group to infect patients with CF, B. cepacia genomovar III, was chosen in 2000 for complete genome analysis. The B. cepacia genomovar III genome project is due to be completed in 2003 with most of the raw sequence data already available to the research community. The genome sequencing strategy adopted for both CF pathogens was the same. However, the historical perspective behind the choice of strains sequenced was different. Genome sequence data enables researchers to rapidly identify bacterial genes that play a role in infection, clone them and mutate them to better understand their functions. The sequence data also enables genome arrays or chips to be constructed which contain every bacterial gene that can be used to determine when and how bacteria switch genes on or off during infection. Overall, the determination of genome sequence data for P. aeruginosa and B. cepacia genomovar III has not only provided a vital experimental resource, but also a major focus for the CF research community upon which to better understand respiratory
Joint scheduling and power control in multi-cell networks for inter-cell interference coordination

The focus of this paper is targeted towards multi-cell dense LTE and LTE-Advanced networks, which are composed of multiple evolved Node B (eNodeB) co-existing in the same operating area and sharing the available radio resources. In such scenarios, momentous emphasis is given towards the techniques that take Inter-Cell Interference (ICI) into account while allocating the scarce radio resources. In this context, we propose solutions for the problem of joint power control and scheduling in the framework of Inter-Cell Interference Coordination (ICIC) in the downlink of LTE OFDMA-based multi-cell systems. Two approaches are adopted to allocate system resources in order to achieve high performance: a centralized approach based on convex optimization and a semi-distributed approach based on non-cooperative game theory. The centralized approach needs a central controller to optimally allocate resources like in LTE CoMP (Coordinated Multipoint). In the semi-distributed approach, eNodeBs coordinate among each other for efficient resource allocation based on local knowledge conveyed by the X2 interface. It turns out that despite the lower complexity of the semi-distributed approach and its inherent adaptability, there is only a slight discrepancy of results among both approaches, which makes the distributed approach much more promising, in particular as a procedure of SON (Self Organized Network).
Distributed under Creative Commons Cc-by 4.0 the Role of Multiple Negative Social Relationships in Inflammatory Cytokine Responses to a Laboratory Stressor Negative Mood Blood Handling Results Preliminary Analyses Cluster Analysis for Negative Relationship Profiles

The present study examined the unique impact of perceived negativity in multiple social relationships on endocrine and inflammatory responses to a laboratory stressor. Via hierarchical cluster analysis, those who reported negative social exchanges across relationships with a romantic partner, family, and their closest friend had higher mean IL-6 across time and a greater increase in TNF-α from 15 min to 75 min post stress. Those who reported negative social exchanges across relationships with roommates, family, and their closest friend showed greater IL-6 responses to stress. Differences in mean IL-6 were accounted for by either depressed mood or hostility, whereas differences in the cytokine stress responses remained significant after controlling for those factors. Overall, this research provides preliminary evidence to suggest that having multiple negative relationships may exacerbate acute inflammatory responses to a laboratory stressor independent of hostility and depressed mood. Stress is a routine part of daily life and interpersonal stress is often the most common and arguably the strongest type of stressor most people experience (Kiecolt-Glaser, Gouin & Hantsoo, 2010). Poorer overall health and dysregulated immune function are strongly linked with interpersonal stress both from negative social exchanges (Chiang et al. Interpersonal stress appears to have a long lasting impact on health in part by contributing to chronically elevated inflammation, which can confer risk of diverse age-related diseases (Ershler & Keller, 2000; How to cite this article Song et al. (2015), The role of multiple negative social relationships in inflammatory cytokine responses to a laboratory stressor. However, the majority of studies on immune responses to social conflict have focused on a particular type of relationship (e.g., marital relationships), while the effect of having conflict across multiple relationships is largely unknown. Further, the degree to which multiple social conflicts affect inflammatory responses to stress and whether the association is independent of related psychosocial characteristics are important issues that are not well understood. The present research is expected to advance the literature by examining interpersonal relationships in multiple areas and how negativity across multiple interpersonal relationships affects inflammatory responses to a laboratory stressor. Studies most relevant to the current research have examined the effects of acute social conflict on health related outcomes. For example, the frequency of negative social exchanges with close others has been negatively associated with physical and mental health among college students (Edwards et al., 2001) and is predictive of depressed mood in a sample of married adults …
inContexto: A fusion architecture to obtain mobile context

Thanks to the embedded sensors providing in mobile devices will revolutionize the way to carry out with. Mobile devices provide a set of embedded sensors, such as accelerometer, digital compass, gyroscope, GPS, microphone, and camera. Another point to consider, is that mobile devices are easily programmable since an API was included by the OS companies. This paper aims to describe a distributed architecture, called inContexto, to recognize physical actions perfomed by users such as walking, running, being stand, sitting and also retrieve context information from the user. Sensory data is collected by HTC magic application made in Android OS.
Challenges and Opportunities in Internet Data Mining

Internet measurement data provides the foundation for the operation and planning of the networks that comprise the Internet, and is a necessary component in research for analysis, simulation, and emulation. Despite its critical role, however, the management of this data—from collection and transmission to storage and its use within applications—remains primarily ad hoc, using techniques created and re-created by each corporation or researcher that uses the data. This paper examines several of the challenges faced when attempting to collect and archive large volumes of network measurement data, and outlines an architecture for an Internet data repository—thedatapository —designed to create a framework for collaboratively addressing these challenges.
Robust audio-codebooks for large-scale event detection in consumer videos

In this paper we present our audio based system for detecting “events” within consumer videos (e.g. You Tube) and report our experiments on the TRECVID Multimedia Event Detection (MED) task and development data. Codebook or bag-of-words models have been widely used in text, visual and audio domains and form the state-of-the-art in MED tasks. The overall effectiveness of these models on such datasets depends critically on the choice of low-level features, clustering approach, sampling method, codebook size, weighting schemes and choice of classifier. In this work we empirically evaluate several approaches to model expressive and robust audio codebooks for the task of MED while ensuring compactness. First, we introduce the Large Scale Pooling Features (LSPF) and Stacked Cepstral Features for encoding local temporal information in audio codebooks. Second, we discuss several design decisions for generating and representing expressive audio codebooks and show how they scale to large datasets. Third, we apply text based techniques like Latent Dirichlet Allocation (LDA) to learn acoustictopics as a means of providing compact representation while maintaining performance. By aggregating these decisions into our model, we obtained 11% relative improvement over our baseline audio systems.
The geometry of parallelism: classical, probabilistic, and quantum effects

We introduce a Geometry of Interaction model for higher-order quantum computation, and prove its adequacy for a fully fledged quantum programming language in which entanglement, duplication, and recursion are all available. This model is an instance of a new framework which captures not only quantum but also classical and probabilistic computation. Its main feature is the ability to model commutative effects in a parallel setting. Our model comes with a multi-token machine, a proof net system, and a -style language. Being based on a multi-token machine equipped with a memory, it has a concrete nature which makes it well suited for building low-level operational descriptions of higher-order languages.
Popular Concepts beyond Organizations: Exploring New Dimensions of Information Technology Innovations

The abundance of innovation concepts in the world of information technology and their differentiated influence on the design, production, and use of IT in organizations make it important that we understand what shapes these concepts themselves. Taking the perspective that an IT innovation concept emerges and evolves beyond organizational boundaries in a community, I argue that the prevalence or popularity of the concept in IT discourse positively influences the adoption of the underlying innovation. Then with the aim to explore what makes an IT innovation concept popular, my empirical analysis of the once highly popular concept ERP (enterprise resource planning) suggests that (1) the popularity of ERP was influenced positively by the prevalence of highlighted business problems that ERP was claimed to solve; (2) ERP’s popularity was influenced negatively by the prevalence of related innovation concepts; and (3) these influences largely disappeared after ERP passed its peak popularity. These results imply that the popularity of an IT innovation concept responds to the broader climate of business and relies on the right type of attention drawn and released by other concepts in a network of concepts. Going beyond the dominant paradigm, this paper helps broaden IT innovation research along two new dimensions: toward the innovation concept, as a complement to material innovation, and toward community-level analysis, as an extension of the traditional organizational analysis. The paper also suggests that practitioners evaluate an innovation concept’s fit with the broader environment and relationship with other popular concepts, as a way to make sense of the innovation and anticipate its impact on IT practice.
Electric turbulence in a plasma subject to a strong magnetic field

We consider in this paper a plasma subject to a strong deterministic magnetic field and we investigate the effect on this plasma of a stochastic electric field. We show that the limit behaviour, which corresponds to the transfer of energy from the electric wave to the particles (Landau phenomena), is described by a Spherical Harmonics Expansion (SHE) model.
ZFTL: A Zone-based Flash Translation Layer with a two-tier selective caching mechanism

In this paper, we propose a Zone-based Flash Translation Layer (ZFTL) for NAND flash-based storage systems. ZFTL is a novel page-level flash translation layer to divide a whole flash into several Zones so that it can reduce the size of SRAM by caching address mapping information of on-demand Zone. Moreover, we propose a two-tier selective caching mechanism to jointly exploit temporal locality and spatial locality of workloads. By selectively caching request mapping entry with the two-tier architecture, ZFTL utilizes the limited SRAM more efficiently so as to improve cache hit ratio and reduce system respond time. Our experimental evaluation with various realistic workloads shows that ZFTL outperforms state-of-the-art FTL schemes. In particular, ZFTL reduces address translation overhead by up to 85% and improves system response time by up to 60% compared to DFTL, though it uses only 5% of SRAM.