Miracle-dz/UniFAR-FTUs huggingface dataset:
Underwater acoustic slant range measurements related to weather and sea state

Underwater range measurements are key factor in underwater acoustic positioning, used in Long Base-Line (LBL) or Ultra Short Base-Line (USBL) computing techniques. These measurements are commonly carried out through acoustic communications between modems and their accuracy can be affected by different factors, such as sea state, weather conditions, and obstacles in the line of sight propagation. This is especially important in shallow waters areas, where others phenomena such as multi-path have to be considered. Therefore, range accuracy and the associated position estimation errors are an important area of research. Here, we addressed the relation between range measurements variability and sea state (i.e. currents or waves height) as proxy of real-world conditions, affecting acoustic positioning performances. For that purpose, a long-term deployment have been carried out in the underwater cabled observatory OBSEA, which provide different measurements of the sea and weather state.
A Real Options Model of Stepwise Entry Into Self-Employment

This paper tests a real options model of stepwise entrepreneurial entry. We distinguish between part time and full time entry among the self employed in Swedish knowledge intensive industries. Two multinomial logit models tests the entry from employment to part- or full time entry in 1998, and to subsequent full time entry in 1999. The empirical evidence indicates the need to distinguish between part time and full time entry, something overlooked in earlier research. We find strong support for our notion that entrepreneurs used part time entry as a strategy to test the value of their conceived business opportunity without risking their full income. However, our hypothesis that entrepreneurs use a real options heuristic shaped by the uncertainty and the irreversibility of entry received only mixed support.
Beam Codebook Based Beamforming Protocol for Multi-Gbps Millimeter-Wave WPAN Systems

In this paper, we propose a feasible beamforming (BF) scheme realized in media access control (MAC) layer following the guidelines of the IEEE 802.15. 3c criteria for millimeter-wave 60GHz wireless personal area networks (60GHz WPANs). The proposed BF targets to minimize the BF set-up time and mitigates the high path loss of 60GHz WPAN systems. It is based on designed multi-resolution codebooks, which generate three kinds of patterns of different half power beam widths (HPBWs): quasi-omni pattern, sector and beam. These three kinds of patterns are employed in the three stages of the BF protocol, namely device-to-device (DEV-to-DEV) linking, sector-level searching and beam-level searching. All the three stages can be completed within one superframe, which minimizes the potential interference to other systems during BF set-up period. In this paper, we show some example codebooks and provide the details of BF procedure. Simulation results show that the setup time of the proposed BF protocol is as small as 2% when compared to the exhaustive searching protocol. The proposed BF is a complete design, it re-uses commands specified in IEEE 802.15. 3c, completely compliant to the standard; It has thus been adopted by IEEE 802.15. 3c as an optional functionality to realize Giga-bit-per-second (Gbps) communication in WPAN Systems.
Crystal structure of 5-(4-benzyloxyphenyl)-3-(4-methoxyphenyl)-6-methylcyclohex-2-en-1-one

5-(4-Benzyloxyphenyl)-3-(4-methoxyphenyl)-6-methylcyclohex-2-en-1-one crystallized with two independent molecules in the asymmetric unit. The cyclohexene ring adopts an envelope conformation in both molecules, with the C atom to which is attached the central benzene ring as the flap. The crystal packing, is stabilized by C—H⋯π interactions.
Joint-Feature Guided Depth Map Super-Resolution With Face Priors

In this paper, we present a novel method to super-resolve and recover the facial depth map nicely. The key idea is to exploit the exemplar-based method to obtain the reliable face priors from high-quality facial depth map to improve the depth image. Specifically, a new neighbor embedding (NE) framework is designed for face prior learning and depth map reconstruction. First, face components are decomposed to form specialized dictionaries and then reconstructed, respectively. Joint features, i.e., low-level depth, intensity cues and high-level position cues, are put forward for robust patch similarity measurement. The NE results are used to obtain the face priors of facial structures and smooth maps, which are then combined in an uniform optimization framework to recover high-quality facial depth maps. Finally, an edge enhancement process is implemented to estimate the final high resolution depth map. Experimental results demonstrate the superiority of our method compared to state-of-the-art depth map super-resolution techniques on both synthetic data and real-world data from Kinect.
NF-κB p50 Regulates C/EBPα Expression and Inflammatory Cytokine-Induced Neutrophil Production1

NF-κB is a key transcriptional inducer of the inflammatory response in mature myeloid cells, and also stimulates cell survival, but its role in immature myeloid cell development has not been well characterized. C/EBPα is required for the development of monocytic and granulocytic myeloid cells from early progenitors, and NF-κB and C/EBPβ cooperatively induce several inflammatory mediators. Having found that C/EBPα binds NF-κB p50 preferentially compared with NF-κB p65, we have now investigated myelopoiesis in nfkb1(−/−) mice lacking NF-κB p50. Absence of p50 leads to a significant reduction in the number of granulocytic progenitors, CFU-granulocyte, obtained with G-CSF or GM-CSF in vitro and reduces neutrophil production in vivo in response to G-CSF, with preservation of monopoiesis in vitro in response to cytokines or LPS. To gain insight into the mechanism underlying reduced granulopoiesis in the absence of NF-κB p50, we assessed the expression of several myeloid regulatory proteins in lineage-negative, immature myeloid cells. Although PU.1, C/EBPβ, and STAT3 levels were unchanged, C/EBPα protein and RNA levels were reduced ∼3-fold in the absence of NF-κB p50. In addition, NF-κB p50 and C/EBPα bound the endogenous C/EBPα promoter in a chromatin immunoprecipitation assay, and NF-κB p50 trans activated the C/EBPα promoter, alone or in cooperation with C/EBPα. Despite reduction of C/EBPα, G-CSFR and M-CSFR levels were maintained in total marrow and in lineage-negative cells. Together, these data indicate that acute inflammation not only activates mature myeloid cells, but also stimulates neutrophil production via NF-κB p50 induction of C/EBPα transcription.
Overview of IP Multicast in a Multi-Protocol Label Switching (MPLS) Environment

This document offers a framework for IP multicast deployment in an MPLS environment. Issues arising when MPLS techniques are applied to IP multicast are overviewed. The pros and cons of existing IP multicast routing protocols in the context of MPLS are described and the relation to the different trigger methods and label distribution modes are discussed. The consequences of various layer 2 (L2) technologies are listed. Both point-to-point and multi-access networks are considered.
Recognizing emphysema - a neural network approach

An accurate and fully automatic method for detecting and quantifying emphysema in CT-images is presented. The method is based on an image preprocessing step followed by a neural network classifier trained to separate true emphysema from artifacts. The proposed approach is shown to be superior to an established method when applied on real patient data.
Stephan Dempe , Alain Bertrand Zemkoho A Bilevel Approach for Traffic Management in Capacitated Networks

We consider a bilevel programming (or leader’s) problem with linear lower-level (or follower’s) problem. Under a regularity condition based on the stability regions for the follower’s problem, some simple optimality conditions are derived for the leader’s problem. Furthermore, we apply this model to the formulation of a traffic control problem designed to solve problems including accidents and/or pollution alleviation on some parts of a road networks.
Endotoxemia: methods of detection and clinical correlates

As an assay for endotoxin, the Limulus amebocyte lysate assay has several desirable properties: sensitivity, specificity, and potential for adaptation to a quantitative format. Several modifications have been developed to enhance its potential for clinical application. The modifications that allow quantitative measurement of endotoxin and also improve its application to blood samples are described in this review. In fluids other than blood, the detection of endotoxin with the Limulus amebocyte lysate assay can be used as an aid to identify the presence of gram-negative bacteria, and the assay has established utility. With blood, however, there are a range of factors that interfere with the detection of endotoxemia and there are disparate views with respect to the diagnostic and prognostic significance of the test results. In general, the clinical significance of the finding of endotoxemia broadly parallels the frequency and importance of gram-negative sepsis in the patient groups studied and a decline in endotoxin levels accompanies clinical improvement. However, with therapies designed to reduce levels of endotoxin, or to antagonize its effects, it is unclear whether clinical improvement occurs as a consequence of changes in the levels of endotoxemia.
Empirical evaluation of price-based technical patterns using probabilistic neural networks

Technical analysis is the art of identifying patterns in historical data with the belief that certain patterns foretell future price movements. An empirical evaluation of the effectiveness of technical analysis is confounded by the subjectivity involved in identifying patterns. This work presents a robust framework for pattern identification using probabilistic neural networks (PNN). The thirty components of the Dow Jones Industrial Average and a set of ten indices are considered. Fourteen patterns are analyzed. In order to test the possibility that technical patterns are more predictable in certain market environments, the period under study (1990–2015) is partitioned into bull and bear markets and the statistical significance of profits earned by identified patterns observed in each environment is analyzed. A range of holding periods from 10 to 50 trading days is considered and a simple model of transaction costs is added. The study reveals that no pattern produces statistically and economically significant profits for a cross-section of stocks and indices analyzed, though a few patterns are more successful predictors. Bullish (bearish) patterns are more reliable predictors in bullish (bearish) market environments. These observations can be explained by the Adaptive Market Hypothesis with certain patterns becoming more accurate predictors in specific market environments.
Error correction of microchip synthesized genes using Surveyor nuclease

The development of economical and high-throughput gene synthesis technology has been hampered by the high occurrence of errors in the synthesized products, which requires expensive labor and time to correct. Here, we describe an error correction reaction (ECR), which employs Surveyor, a mismatch-specific DNA endonuclease, to remove errors from synthetic genes. In ECR reactions, errors are revealed as mismatches by re-annealing of the synthetic gene products. Mismatches are recognized and excised by a combination of mismatch-specific endonuclease and 3′→5′ exonuclease activities in the reaction mixture. Finally, overlap extension polymerase chain reaction (OE-PCR) re-assembles the resulting fragments into intact genes. The process can be iterated for increased fidelity. With two iterations, we were able to reduce errors in synthetic genes by >16-fold, yielding a final error rate of ∼1 in 8700 bp.
Resolving automated perception system failures in bin-picking tasks using assistance from remote human operators

We present an approach to resolve automated perception failures during bin-picking operations in hybrid assembly cells. Our model exploits complementary strengths of humans and robots. Whereas the robot performs bin-picking and proceeds to the subsequent operation like kitting or assembly, a remotely located human assists the robot in critical situations by resolving any automated perception problems encountered during bin-picking. We present the design details of our overall system comprising an automated part recognition system and a remote user interface that allows effective information exchange between the human and the robot that is geared toward solutions that minimize human operator time in resolving the detected perception failures. We use illustrative real robot experiments to show that human-robot information exchange leads to improved bin-picking performance.
Analysis of vegetation recovery surrounding a restored wetland using the normalized difference infrared index (NDII) and normalized difference vegetation index (NDVI)

ABSTRACT Watershed restoration efforts seek to rejuvenate vegetation, biological diversity, and land productivity at Cienega San Bernardino, an important wetland in southeastern Arizona and northern Sonora, Mexico. Rock detention and earthen berm structures were built on the Cienega San Bernardino over the course of four decades, beginning in 1984 and continuing to the present. Previous research findings show that restoration supports and even increases vegetation health despite ongoing drought conditions in this arid watershed. However, the extent of restoration impacts is still unknown despite qualitative observations of improvement in surrounding vegetation amount and vigor. We analyzed spatial and temporal trends in vegetation greenness and soil moisture by applying the normalized difference vegetation index (NDVI) and normalized difference infrared index (NDII) to one dry summer season Landsat path/row from 1984 to 2016. The study area was divided into zones and spectral data for each zone was analyzed and compared with precipitation record using statistical measures including linear regression, Mann–Kendall test, and linear correlation. NDVI and NDII performed differently due to the presence of continued grazing and the effects of grazing on canopy cover; NDVI was better able to track changes in vegetation in areas without grazing while NDII was better at tracking changes in areas with continued grazing. Restoration impacts display higher greenness and vegetation water content levels, greater increases in greenness and water content through time, and a decoupling of vegetation greenness and water content from spring precipitation when compared to control sites in nearby tributary and upland areas. Our results confirm the potential of erosion control structures to affect areas up to 5 km downstream of restoration sites over time and to affect 1 km upstream of the sites.
Trajectory representation by nonlinear scaling of dynamic movement primitives

An effective robot trajectory representation should encode all relevant aspects of the desired motion. For kinematic representations, this means that both the spatial course of the trajectory and its speed profile must be specified. The concept of dynamic movement primitives (DMP) provides a kinematic representation that fully specifies these two aspects of motion. They are, however, not separated from each other within the DMP representation. This can be problematic when movements with significant speed variations are compared within movement recognition and skill learning algorithms. In such comparisons it is often important to distinguish between the spatial and temporal aspects of motion. In this paper we propose a new representation based on dynamic movement primitives, where spatial and temporal aspects are well separated. We demonstrate the effectiveness of the proposed representation for statistical learning of robot skills and movement recognition and compare the performance with standard DMPs, where temporal and spatial aspects of motion are intertwined.
The links between axin and carcinogenesis

The products of the two mammalian Axin genes (Axin1 and its homologue Axin2) are essential for the degradation of β catenin, a component of Wnt signalling that is frequently dysregulated in cancer cells. Axin is a multidomain scaffold protein that has many functions in biological signalling pathways. Overexpression of axin results in axis duplication in mouse embryos. Wnt signalling activity determines dorsal–ventral axis formation in vertebrates, implicating axin as a negative regulator of this signalling pathway. In addition, Wnts modulate pattern formation and the morphogenesis of most organs by influencing and controlling cell proliferation, motility, and fate. Defects in different components of the Wnt signalling pathway promote tumorigenesis and tumour progression. Recent biochemical studies of axins indicate that these molecules are the primary limiting components of this pathway. This review explores the intriguing connections between defects in axin function and human diseases.
Featured CME Topic: Spirituality Methodologic Issues in Research on Religion and Health

This study examines several methodologic issues in research on religion and health, including the measurement of the concept of religion, research designs, sampling, and statistical controls for assessing the “net” effects of religion on health outcomes. It briefly discusses differences in analytical perspectives that have contributed to the debate about the effects of religion on health. The authors review some of the methodologic problems of past research in this area of study and address what needs to be done to enhance the quality of the research. The authors conclude that the research methodology used in studies of religion and health has improved over time and that it continues to do so.
Computer-Assisted Culture Learning in an Online Augmented Reality Environment Based on Free-Hand Gesture Interaction

The physical-virtual immersion and real-time interaction play an essential role in cultural and language learning. Augmented reality (AR) technology can be used to seamlessly merge virtual objects with real-world images to realize immersions. Additionally, computer vision (CV) technology can recognize free-hand gestures from live images to enable intuitive interactions. Therefore, we incorporate the latest AR and CV algorithms into a Virtual English Classroom, called VECAR, to promote immersive and interactive language learning. By wearing a pair of mobile computing glasses, users can interact with virtual contents in a three-dimensional space by using intuitive free-hand gestures. We design three cultural learning activities that introduce students to authentic cultural products and new cultural practices, and allow them to examine various cultural perspectives. The objectives of the VECAR are to make cultural and language learning appealing, improve cultural learning effectiveness, and enhance interpersonal communication between teachers and students.
Final Report – CS 6604 Spring 2017 Global Events Team CS 6604 : TS : Digital Libraries

I TABLE OF TABLES . III TABLE OF FIGURES . IV 1 OVERVIEW . 5 1.1 MANAGEMENT . 5 1.2 CHALLENGES . 5 1.3 SOLUTION DEVELOPED . 6 2 LITERATURE REVIEW . 7 3 REQUIREMENTS . 8 4 DESIGN . 10 4.1 EVENTS CRAWLING DESIGN . 11 4.2 HBASE SCHEMA DESIGN . 14 5 IMPLEMENTATION . 15 5.1 OVERVIEW . 15 5.2 TIMELINE . 15 5.3 TOOLS . 17 5.3. 1 ArchiveSpark . 17 5.3. 2 D3.js . 17 6 USER MANUAL . 19 7 DEVELOPER MANUAL . 22 7.1 INTERNET ARCHIVE TOOL . 22 7.2 TUTORIALS FOR DEPLOYING EFC . 23 7.2.1 Install Dependencies . 23 7.2. 2 Run EFC . 23 7.3 TUTORIALS FOR DEPLOYING ARCHIVESPARK IN JUPYTER . 24 7.3. 1 Install JDK 8 . 24 7.3. 2 Install Python 3.5 and Pip . 24 7.3. 3 Install Jupyter . 25 7.3. 4 Install Spark 2.1. 0 . 25 7.3.5 Install ArchiveSpark . 26 7.3. 6 Replace the Original Scala . 26 7.4 TUTORIALS FOR DEPLOYING ARCHIVESPARK IN INTELLIJ . 27 7.4.1 Install Spark and Scala . 27 7.4.2 Deploy ArchiveSpark . 27
Abnormalities in the pattern of platelet amyloid precursor protein forms in patients with mild cognitive impairment and Alzheimer disease.

CONTEXT Patients affected by sporadic Alzheimer disease (AD) show a significant alteration of amyloid precursor protein (APP) forms in platelets when compared with patients with dementia but without AD and age-matched controls. OBJECTIVE To evaluate the ratio of platelet APP forms (APPr) in early-stage AD and mild cognitive impairment (MCI) and its potential as a biomarker for the early identification of AD. SETTING Community population-based sample of patients admitted to 4 AD centers for investigation of cognitive disturbances. DESIGN AND METHODS Thirty-five patients with mild AD (mAD), 21 patients with very mild AD (vmAD), 30 subjects with MCI, and 25 age-matched controls were included. The APPr was evaluated by Western blot analysis in platelet homogenate. RESULTS Compared with controls (mean +/- SD, 0.93 +/- 0.3), the mean APPr was decreased in patients with mAD (0.44 +/- 0.24; P<.001) and patients with vmAD (0.49 +/- 0.3; P<.001). Regarding the MCI group, a significant decrease in APPr was found compared with controls (0.62 +/- 0.33; P<.001). Fixing a cutoff score of 0.6, sensitivity was 88.6% (31/35) for patients with mAD and 85.7% (18/21) for patients with vmAD, whereas specificity was 88% (22/25) for controls. Among patients with MCI, 18 (60%) of 30 individuals displayed APPr values below the cutoff. CONCLUSIONS Alteration of platelet APP forms is an early event in AD, and the measurement of APPr may be useful for the identification of preclinical AD in patients with MCI.
PerfView : A Performance Monitoring and Visualization Tool for Intel ® Itanium ® Architecture

Application performance analysis in modern microprocessors has become extremely complex due to substantial instruction level parallelism, complex processor pipelines and deep memory hierarchies. Performance analysts need to have a thorough understanding of the dynamic behavior of programs in order to identify and fix performance bottlenecks. In order to help in the performance analysis process, modern day processors provide hardware support in the form of performance registers that capture micro-architectural events at program runtime. However, the data provided by these hardware registers is at a very low level and an extensive effort has to be made by performance analysts to make sense of the data. Therefore, it is extremely beneficial to make use of performance analysis tools that can assemble various types of performance related information available from the performance registers to provide a high level summary of the data. In this paper, we discuss PerfView, which is (1) a source-code based visualization tool (2) a tool that identifies and allows users to view performance-critical events based on execution paths and (3) an interactive performance monitoring and debugging tool.