Miracle-dz/UniFAR-FTUs huggingface dataset:
Extending the Sonic Flashlight to Real Time Tomographic Holography

Real Time Tomographic Reflection (RTTR) permits in situ visualization of tomographic images, enabling natural hand-eye coordination to guide invasive procedures. The method as originally developed uses a halfsilvered mirror to merge the visual outer surface of the patient with a simultaneous scan of the patient’s interior. A viewpoint-independent virtual image is reflected precisely into the correct location within the patient. When applied to ultrasound, we call the resulting device the sonic flashlight. In this paper we present the first published description of a derivative method that replaces the half-silvered mirror with a Holographic Optical Element (HOE). The new technique, called Real Time Tomographic Holography (RTTH), has the advantage over the mirror-based system that the virtual image is no longer required to match the size and shape of the actual display. We are currently in the first year of an NSF grant from the Robotics and Human Augmentation Program (CISE/IIS) to develop prototype RTTH systems. Although at the time of this writing our systems are not yet functional, we consider the concept itself of potential importance, and wish to report it, along with our current progress towards implementation, to the Augmented Reality community.
Human decidual macrophages and NK cells differentially express Toll-like receptors and display distinct cytokine profiles upon TLR stimulation

Maternofetal pathogen transmission is partially controlled at the level of the maternal uterine mucosa at the fetal implantation site (the decidua basalis), where maternal and fetal cells are in close contact. Toll-like receptors (TLRs) may play an important role in initiating rapid immune responses against pathogens in the decidua basalis, however the tolerant microenvironment should be preserved in order to allow fetal development. Here we investigated the expression and functionality of TLRs expressed by decidual macrophages (dMs) and NK cells (dNKs), the major decidual immune cell populations. We report for the first time that both human dMs and dNK cells express mRNAs encoding TLRs 1-9, albeit with a higher expression level in dMs. TLR2, TLR3, and TLR4 protein expression checked by flow cytometry was positive for both dMs and dNK cells. In vitro treatment of primary dMs and dNK cells with specific TLR2, TLR3, TLR4, TLR7/8, and TLR9 agonists enhanced their secretion of pro- and anti-inflammatory cytokines, as well as cytokines and chemokines involved in immune cell crosstalk. Only dNK cells released IFN-γ, whereas only dMs released IL-1β, IL-10, and IL-12. TLR9 activation of dMs resulted in a distinct pattern of cytokine expression compared to the other TLRs. The cytokine profiles expressed by dMs and dNK cells upon TLR activation are compatible with maintenance of the fetotolerant immune environment during initiation of immune responses to pathogens at the maternofetal interface.
Gender Differences in Plasma Biomarker Levels in a Cohort of COPD Patients: A Pilot Study

Rationale Little is known about gender differences in plasma biomarker levels in patients with chronic obstructive pulmonary disease (COPD). Hypothesis There are differences in serum biomarker levels between women and men with COPD. Objective Explore gender differences in plasma biomarker levels in patients with COPD and smokers without COPD. Methods We measured plasma levels of IL-6, IL-8, IL-16, MCP-1, MMP-9, PARC and VEGF in 80 smokers without COPD (40 males, 40 females) and 152 stable COPD patients (76 males, 76 females) with similar airflow obstruction. We determined anthropometrics, smoking history, lung function, exercise tolerance, body composition, BODE index, co-morbidities and quality of life. We then explored associations between plasma biomarkers levels and the clinical characteristics of the patients and also with the clinical and physiological variables known to predict outcome in COPD. Results The plasma biomarkers level explored were similar in men and women without COPD. In contrast, in patients with COPD the median value in pg/mL of IL-6 (6.26 vs 8.0, p = 0.03), IL-16 (390 vs 321, p = 0.009) and VEGF (50 vs 87, p = 0.02) differed between women and men. Adjusted for smoking history, gender was independently associated with IL-16, PARC and VEGF levels. There were also gender differences in the associations between IL-6, IL-16 and VEGF and physiologic variables that predict outcomes. Conclusions In stable COPD patients with similar airflow obstruction, there are gender differences in plasma biomarker levels and in the association between biomarker levels and important clinical or physiological variables. Further studies should confirm our findings.
A simple, fast and scalable non-blocking concurrent FIFO queue for shared memory multiprocessor systems

A non-blocking FIFO queue algorithm for multiprocessor shared memory systems is presented in this paper. The algorithm is very simple, fast and scales very well in both symmetric and non-symmetric multiprocessor shared memory systems. Experiments on a 64-node SUN Enterprise 10000 — a symmetric multiprocessorsystem — and on a 64-node SGI Origin 2000 — a cache coherent non uniform memory access multiprocessorsystem — indicate that our algorithm considerably outperforms the best of the known alternatives in both multiprocessors in any level of multiprogramming. This work introduces two new, simple algorithmic mechanisms. The first lowers the contention to key variables used by the concurrent enqueue and/or dequeue operations which consequently results in the good performance of the algorithm, the second deals with the pointer recycling problem, an inconsistency problem that all non-blocking algorithms based on the compare-and-swap synchronisation primitive have to address. In our construction we selected to use compare-and-swap since compare-and-swap is an atomic primitive that scales well under contention and either is supported by modern multiprocessors or can be implemented efficiently on them.
Learning Dictionaries for Information Extraction by Multi-Level Bootstrapping

Information extraction systems usually require two dictionaries: a semantic lexicon and a dictionary of extraction patterns for the domain. We present a multilevel bootstrapping algorithm that generates both the semantic lexicon and extraction patterns simultaneously. As input, our technique requires only unannotated training texts and a handful of seed words for a category. We use a mutual bootstrapping technique to alternately select the best extraction pattern for the category and bootstrap its extractions into the semantic lexicon, which is the basis for selecting the next extraction pattern. To make this approach more robust, we add a second level of bootstrapping (metabootstrapping) that retains only the most reliable lexicon entries produced by mutual bootstrapping and then restarts the process. We evaluated this multilevel bootstrapping technique on a collection of corporate web pages and a corpus of terrorism news articles. The algorithm produced high-quality dictionaries for several semantic categories.
Spring phenology and phenology-climate links inferred from two remotely sensed vegetation indices across regions and biomes

Abstract. The timing of spring greenup (SG) as inferred by remotely sensed vegetation indices have showed contrasting dynamics across the same region and periods. Assessing the uncertainty in SG associated with different Normalized Difference Vegetation Index (NDVI) products is essential for robustly interpreting the links between climate and phenological dynamics. We compare SG inferred from two NDVI products over the period 2001–2013: (1) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and (2) National Oceanic and Atmospheric Administration's (NOAA's) Advanced Very High Resolution Radiometer (AVHRR) instruments processed by the Global Inventory Monitoring and Modeling Studies (GIMMS) to explore confidence and uncertainty in the NDVI-inferred SG trend and its links to climate variability. Both MODIS and GIMMS agreed in showing an advancement of SG in northern Canada, the eastern United States, and Russia, as well as a delay in SG in western North America, parts of Baltic Europe and East Asia. In the regions with advanced SG, GIMMS inferred much weaker advancement whereas in the regions with delayed SG, GIMMS inferred much stronger delay than MODIS. This resulted in a GIMMS SG delay in both North America and Eurasia. MODIS data show no significant SG shift in North American for spatial heterogeneity in SG shift, but dominant SG advancement in Eurasia. The SG advancement inferred from MODIS is associated with a stronger coupling between SG and temperature and a stronger sensitivity across biomes as compared to GIMMS. The main uncertainty in the SG trend and SG-temperature sensitivity are in northern high latitudes (>50° N) where GIMMS and MODIS show different magnitude and sign of the annual SG anomalies. Compared to 1988–2000, inter-biome GIMMS SG-temperature sensitivity is stable and the SG-temperature sensitivity increased in the boreal and Arctic biomes despite a slight reduction in the SG-temperature coupling over the period 2001–2013. The explanation for the increased SG-temperature sensitivity remains unclear and requires further investigation. We suggest broader evaluation of the NDVI products against field measurements and inter-validation for robust assessment of vegetation dynamics.
Improving Second-order Surface Estimation

The paper proposes a reliable method for estimating second-order surfaces from 3D range data in the framework of object recognition and localization or object modelling. Instead of estimating such surface individually the approach ts all the surfaces captured in the scene together, taking into account the geometric relationships between them and their speci c characteristics. The technique is compared with other methods through experiments performed on real objects and demonstrates that the use of constrained relationships improves shape estimates.
Localization for robotic capsule looped by axially magnetized permanent-magnet ring based on hybrid strategy

To actively maneuver a robotic capsule for interactive diagnosis in the gastrointestinal tract, visualizing accurate position and orientation of the capsule when it moves in the gastrointestinal tract is essential. A possible method that encloses the circuits, batteries, imaging device, etc into the capsule looped by an axially magnetized permanent-magnet ring is proposed. Based on expression of the axially magnetized permanent-magnet ring’s magnetic fields, a localization and orientation model was established. An improved hybrid strategy that combines the advantages of particle-swarm optimization, clone algorithm, and the Levenberg–Marquardt algorithm was found to solve the model. Experiments showed that the hybrid strategy has good accuracy, convergence, and real time performance.
Tolerance to beta,beta'-iminodipropionitrile (IDPN)-induced neurobehavioural and vestibular toxicity in diabetic rats.

The present investigation was undertaken to study the neurotoxic effects of beta,beta'-iminodipropionitrile (IDPN) in normal, diabetic and insulin-treated diabetic rats. Sprague-Dawley male rats were divided into five groups: control, IDPN, diabetes, diabetes plus IDPN and diabetes plus insulin plus IDPN. The diabetes was induced with a single i.p. injection of streptozotocin (50 mg kg(-1)). One month after the induction of diabetes, the rats were treated with IDPN (100 mg kg(-1), i.p.) daily for 11 days. One of the diabetic groups treated with IDPN also received daily injection of insulin (25 U kg(-1), s.c. ), 1 h before IDPN. The rats were observed daily for abnormal head movements and circling. The grip strength of the forelimbs was also measured. In the IDPN group the dyskinetic symptoms appeared on the 8th day, whereas the onset of dyskinesia was on the 12th day in IDPN-treated diabetic rats. The incidence and severity of dyskinesia were significantly higher in IDPN-treated normal (non-diabetic) rats as compared to IDPN-treated diabetic rats. The treatment of diabetic rats with insulin normalized striatal dopamine (DA) turnover but partially reversed diabetes-induced protection against IDPN dyskinesia. There was severe degeneration of sensory hair cells in crista ampullaris of IDPN-treated normal rats, whereas the diabetic rats showed significant protection against IDPN-induced vestibular hair cell degeneration. In conclusion, our study clearly demonstrates that diabetic rats are resistant to IDPN-induced neurobehavioural and vestibular toxicity. The results also show that diabetes-induced protection against IDPN-induced dyskinesia can be partially reversed by insulin. The mechanism behind the decreased vulnerability of diabetic animals to IDPN remains to be resolved. Further studies are warranted to investigate this paradoxical phenomenon.
Predicting future locations with hidden Markov models

The analysis of human location histories is currently getting an increasing attention, due to the widespread usage of geopositioning technologies such as the GPS, and also of online location-based services that allow users to share this information. Tasks such as the prediction of human movement can be addressed through the usage of these data, in turn offering support for more advanced applications, such as adaptive mobile services with proactive context-based functions. This paper presents an hybrid method for predicting human mobility on the basis of Hidden Markov Models (HMMs). The proposed approach clusters location histories according to their characteristics, and latter trains an HMM for each cluster. The usage of HMMs allows us to account with location characteristics as unobservable parameters, and also to account with the effects of each individual's previous actions. We report on a series of experiments with a real-world location history dataset from the GeoLife project, showing that a prediction accuracy of 13.85% can be achieved when considering regions of roughly 1280 squared meters.
THE ECOLOGY OF A NEW HAMPSHIRE ESTUARINE TIDAL RAPID

THE ECOLOGY OF A NEW HAMPSHIRE ESTUARINE TIDAL RAPID by NORMAN B. REYNOLDS A detailed synecological study was made of the organisms in the Dover Point, New Hampshire, tidal rapid. The site is located in the middle of the Great Bay Estuary System. Currents of at least 5 1/2 knots occur at the location. Values for surface water salinity and temperature varied from 8 0/00 to 31 0/00 and -2°C. to +19°C. respectively during the 3 year study. Annual and seasonal changes in growth, zonation, occurrence, biomass, grazing and predation of all macroscopic marine organisms were studied in relation to a variety of ecological factors (tidal currents, water temperature, air temperature dissolved oxygen and salinity). Eighty-three taxa of benthonic algae were recorded at Dover Point, including 39 Rhodophyceae, 24 Chlorophyceae, and 20 Phaeophy­ ceae. The largest number of taxa occurred in July, while the smallest number occurred in September and January. Seasonal changes in the vertical distribution of Petalonia fascia, Dumontia incrassata, Chaetomorpha linum, Cladophora sericea, Urospora penicilliformis, Balanus balanoides, Littorina littorea, Scytosiphonia lomentaria, Porphyra umbilicalis and Entermorpha intestinalis were recorded. In addition, comparison was made of the zonation and seasonal occurrence of marine algae at Dover Point and Jaffrey Point, New Hampshire (a semi-exposed open coastal station) showing that the sublittoral zone at the Dover Point tidal rapid has an "open coastal" flora, while the littoral zone has a more estuarine flora. The response of selected
Image clustering based on a shared nearest neighbors approach for tagged collections

Browsing and finding pictures in large-scale and heterogeneous collections is an important issue, most particularly for online photo sharing applications. Since such services are experiencing rapid growth of their databases, the tag-based indexing strategy and the results displayed in a traditional matrix representation may not be optimal for browsing and querying image collections. Naturally, unsupervised data clustering appeared as a good solution by presenting a summarized view of an image set instead of an exhaustive but useless list of its element. We present a new method for extracting meaningful and representative clusters based on a shared nearest neighbors (SNN) approach that treats both content-based features and textual descriptions (tags). We describe, discuss and evaluate the SNN method for image clustering and present some experimental results using the Flickr collections showing that our approach extracts representative information of an image set.
Isolation and Characterization of Type I Signal Peptidase of Different Malaria Parasites

Type I signal peptidases are important membrane-bound serine proteases responsible for the cleavage of the signal peptide of the proteins. These enzymes are unique serine proteases that carry out catalysis using a serine/lysine catalytic dyad. In the present study, we report the isolation of type I signal peptidase from the malaria parasites Plasmodium falciparum, Plasmodium knowlesi, and Plasmodium yoelii and some characterization of type I signal peptidase of Plasmodium falciparum. We show that these enzymes are homologous to signal peptidases from various sources and also contain the conserved boxes present in other type I signal peptidases. The type I signal peptidase from P falciparum is an intron-less and a single-copy gene. The results also show that the enzyme from Plasmodium falciparum is subject to self-cleavage and it has been demonstrated to possess type I signal peptidase activity in E coli preprotein processing in vivo by complementation assay. This study will be helpful in understanding one of the important metabolic pathways “the secretory pathway” in the parasite and should make an important contribution in understanding the complex process of protein targeting in the parasite.
A novel scalable and reconfigurable emulation platform for embedded systems verification

Modern embedded systems are characterized by a heterogeneous architecture including several modules (e.g., DSPs, memories and mixed-signal IPs) often integrated with one or more microprocessor cores controlling the system functionalities by means of embedded software programs. The verification of such a kind of systems has become a challenge due to their increasing complexity that makes traditional simulation and emulation techniques unaffordable methods for current quality and time-to-market constraints. This paper presents a new platform for the hardware and software verification of modern embedded systems based on a reconfigurable device. The main novelty consists in an infrastructure architecture containing a signal processing IP and a microprocessor core flexibly interfaced with the device under validation, aimed at the overall reduction of the design verification time. It also provides a dynamic interface supporting the software verification of the embedded system microprocessors. The proposed environment is fully scalable and adaptable to the requirements of a general purpose embedded system, enabling advanced verification flows at different phases of design and integration without time expensive interface modification. Experimental and performance analysis on a real industrial case study are reported proving the effectiveness of the proposed solution.
Multi-level inverter with H-bridge clamp circuit for single-phase three-wire grid connection suitable for Super-junction/SiC MOSFET

A multilevel inverter with H-bridge clamp circuit is proposed for single-phase three-wire (1P3W) utility connected applications such as PV system. The proposed inverter consists of two n-level inverters and a H-bridge clamp circuit. The proposed inverter features high compatibility with next generation semiconductors because the uses of a high voltage H-bridge clamp circuit at grid frequency switching. The proposed inverter requires only 12 controllable switches to obtain a 5-level output voltage. In conventional multi-level converters with grounded neutral point of the DC-bus, 16 switches are required. The control strategy is discussed in this paper. Moreover, a numerical parameter design method is considered and then verified by simulation. Finally, conduction loss of the clamp circuit is shown lower than that comparing with the conventional active neutral point clamped (ANPC) inverter using Super-junction MOSFET or SiC MOSFET.
Rotations of Normal Fault Blocks Quantify Extension in the Central Tauride Intramontane Basins, SW Turkey

Quantifying the amount of stretching in extensional basin systems is often challenging in the absence of seismic profiles or boreholes. However, when fault spacing and orientation as well as vertical axis rotation patterns are known, map‐view restoration may provide a good estimate of total extension. This integrated structural and paleomagnetic approach provides a relatively straightforward tool in extensional basin restoration and fault zone kinematic analysis. Here we provide results of an extensive paleomagnetic survey of the Neogene Central Tauride intramontane basins (SW Turkey), where previous work revealed a complex array of basin‐bounding normal faults and relay ramps. In total, 437 oriented cores were sampled at 43 sites distributed within Miocene‐Pliocene continental sedimentary rocks from the Ilgın, Altınapa, Yalvaç, and Beyşehir basins. Despite the more or less coherent overall strike of the mountain belt and basins, rotations vary from ~42° clockwise (Yalvaç) to ~10° (Beyşehir), ~21° (Ilgın), and ~30° (Altınapa) counterclockwise. We show that the rotation pattern is related to normal faults and lateral variations in fault displacement superimposed on regional rotation patterns. We restore these to estimate a minimum NE‐SW horizontal extension of ~30–35 km across the basin system. As a consequence of our reconstruction, it appears that the Sultandağları range that exposes low‐grade metamorphic Paleozoic and Mesozoic rocks of the Geyikdağı and Bolkardağ nappes of the Taurides represents a Miocene extensional core complex.