Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Benchmark Brown Dwarf

We present optical spectroscopy of three brown dwarf candidates identified in the first 1% of the DENIS sky survey. Low resolution spectra from 6430–9150 Å show these objects to have similar spectra to the uncertain brown dwarf candidate GD 165B. High resolution spectroscopy shows that one of the objects – DBD 1228-1547 – has a strong 2.3±0.05 Å equivalent width absorption line of Li I 6708 Å, and is therefore a brown dwarf with mass below 0.065M⊙, and age < ∼ 1.5Gyr. DBD 1228-1547 can now be the considered proto-type for brown dwarfs close to the hydrogen burning limit. Subject headings: stars: low-mass, brown dwarfs
Three‐dimensional passive seismic waveform imaging around the SAFOD site, California, using the generalized Radon transform

We apply a three‐dimensional (3D) generalized Radon transform (GRT) to scattered P‐waves from 575 local earthquakes recorded at 68 temporary network stations for passive‐source imaging of (near‐vertical) structures close to the San Andreas Fault Observatory at Depth (SAFOD) site. The GRT image profiles through or close by the SAFOD site reveal near‐vertical reflectors close to the fault zone as well as in the granite to the southwest and the Franciscan mélange to the northeast of the main fault. Although slightly lower in resolution, these structures are generally similar to features in 2D images produced with steep‐dip prestack seismic migration of data from active source seismic reflection and refraction surveys. Our GRT images, however, also reveal several vertical reflectors to the northeast of the SAF that do not appear in the migration images but which are consistent with local geology. These results suggest that in a seismically active area, inverse scattering of earthquake data (for instance with the GRT) can be a viable and, in 3D, economic alternative to an active source survey.
Leveraging Online Virtual Agents to Crowdsource Human-Robot Interaction

Robots require a broad range of interaction skills in order to work effectively alongside humans. They must have the ability to detect and recognize the actions and intentions of a person, produce functionally valid and situationally appropriate actions, and engage in social interactions through physical cues and dialog. However, social interactions with one of today’s robots will quickly become one-sided and repetitive, even after just a few minutes due to its shallow depth of knowledge and experience. This problem exposes weaknesses in the underlying traditional approaches that aim to pre-code responses to a limited number of inputs. We propose the use of crowdsourcing as a tool for the development of social robots that allow for rich, diverse and natural human-robot interaction. To enable crowdsourcing at a massive scale, we describe a newly implemented system that uses online virtual agents to collect data and then leverages the resulting corpus to train our robot behavior system for use on a real world task.
Rewriting-based optimization for XQuery transformational queries

The modern XML query language called XQuery includes advanced facilities both to query and to transform XML data. An XQuery query optimizer should be able to optimize any query. For "querying" queries almost all techniques inherited from SQL-oriented DBMS may be applied. The XQuery transformation facilities are XML-specific and have no counterparts in other query languages. That is why XQuery transformational queries need to be optimized with novel techniques. In this paper two kinds of such techniques (namely push predicates down XML element constructors and projection of transformation) are considered. A subset of XQuery for which these techniques can be fully implemented is identified. This subset seems to be the most interesting from the practical viewpoint. Rewriting rules for this subset are proposed and the correctness of these rules is formally justified. For the rest of the language we propose solutions that work for the most of common cases or consider the problems we have encountered.
Discovering novelty in spatio/temporal data using one-class support vector machines

Novelty or anomaly detection in spatio/temporal data refers to the automatic identification of novel or abnormal events embedded in data that occur at a specific location/time. Traditional techniques used in process control to identify novelties are not robust for noise in the data set. We present an algorithm based on the support vector machine approach for domain description. This technique is intrinsicly robust for outliers in the data set but to make it work, several extensions are needed which form the contribution of this work: an extended representation of the spatio/temporal data, a tensor product kernel to separately deal with the distinct features of time and measurements, and a voting function which identifies novelties based on different representations of the time series in a robust way. Experimental results on both artificial and real data demonstrate that our algorithm performs significantly better than other standard techniques used in process control.
Polymorphism in the Spotlight: Studying Its Prevalence in Java and Smalltalk

Subtype polymorphism is a cornerstone of object-oriented programming. By hiding variability in behavior behind a uniform interface, polymorphism decouples clients from providers and thus enables genericity, modularity and extensibility. At the same time, however, it scatters the implementation of the behavior over multiple classes thus potentially hampering program comprehension. The extent to which polymorphism is used in real programs and the impact of polymorphism on program comprehension are not very well understood. We report on a preliminary study of the prevalence of polymorphism in several hundred open source software systems written in Smalltalk, one of the oldest object-oriented programming languages, and in Java, one of the most widespread ones. Although a large portion of the call sites in these systems are polymorphic, a majority have a small number of potential candidates. Smalltalk uses polymorphism to a much greater extent than Java. We discuss how these findings can be used as input for more detailed studies in program comprehension and for better developer support in the IDE.
Study on a joint synchronization algorithm in timedomain for OFDM-UWB based indoor precision positioning system receiver

According to the basic principle of Orthogonal Frequency Division Multiplexing Ultra Wide Band (OFDM-UWB) based indoor precision positioning system, a Symbol Timing Synchronization (STS) algorithm with the high synchronization precision of only a few (1~3) sampling intervals is required to achieve indoor centimeter-level precision positioning. The performance of existing synchronization algorithms of OFDM-UWB system is so far to fit the rigorous needs of this indoor precision system. In this study, a new type of information frame format is designed, and based on which, a joint synchronization algorithm in time-domain for OFDM-UWB based indoor precision positioning system receiver is presented during the studying on STS. STS is the key technique of the joint synchronization algorithm, and at the same time, the joint algorithm comes into being by associating STS with Carrier Decimal Frequency Offset (CDFO), with Carrier Integer Frequency Offset (CIFO), and with Frame Timing Synchronization (FTS). The function verification and the performance analysis of the joint synchronization algorithm are made using MATLAB software in this study. The simulation results show that STS precision is only one sampling interval (1.89394ns) with a lower Signal Noise Ratio (SNR) of -15dB and carrier frequency offset disturb existing, which proves that the shortcomings of those existing STS algorithms that are easy to be disturbed by noise and frequency offset are overcame by the new joint synchronization algorithm, and proves that the joint synchronization algorithm meets the function requirements of the indoor positioning system fully. And at the same time, because these four synchronization technologies are integrated by the joint synchronization algorithm, the hardware resources can be saved effectively, the system costs can be reduced largely, and the anti-jamming performance and the stability of the receiver system can be enhanced hugely.
Type-dependent parameter inference

An algorithm is presented to infer the type and operation parameters of polymorphic functions. Operation parameters are named and typed at the function definition, but are selected from the set of overloaded definitions available wherever the function is used. These parameters are always implicit, implying that the complexity of using a function does not increase with the generality of its type.
Antisense Activity across the Nesp Promoter is Required for Nespas-Mediated Silencing in the Imprinted Gnas Cluster

Macro long non-coding RNAs (lncRNAs) play major roles in gene silencing in inprinted gene clusters. Within the imprinted Gnas cluster, the paternally expressed Nespas lncRNA downregulates its sense counterpart Nesp. To explore the mechanism of action of Nespas, we generated two new knock-in alleles to truncate Nespas upstream and downstream of the Nesp promoter. We show that Nespas is essential for methylation of the Nesp differentially methylated region (DMR), but higher levels of Nespas are required for methylation than are needed for downregulation of Nesp. Although Nespas is transcribed for over 27 kb, only Nespas transcript/transcription across a 2.6 kb region that includes the Nesp promoter is necessary for methylation of the Nesp DMR. In both mutants, the levels of Nespas were extraordinarily high, due at least in part to increased stability, an effect not seen with other imprinted lncRNAs. However, even when levels were greatly raised, Nespas remained exclusively cis-acting. We propose Nespas regulates Nesp methylation and expression to ensure appropriate levels of expression of the protein coding transcripts Gnasxl and Gnas on the paternal chromosome. Thus, Nespas mediates paternal gene expression over the entire Gnas cluster via a single gene, Nesp.
A uniformly consistent estimator of causal effects under the k-Triangle-Faithfulness assumption

Spirtes, Glymour and Scheines [Causation, Prediction, and Search (1993) Springer] described a pointwise consistent estimator of the Markov equivalence class of any causal structure that can be represented by a directed acyclic graph for any parametric family with a uniformly consistent test of conditional independence, under the Causal Markov and Causal Faithfulness assumptions. Robins et al. [Biometrika 90 (2003) 491�515], however, proved that there are no uniformly consistent estimators of Markov equivalence classes of causal structures under those assumptions. Subsequently, Kalisch and Buhlmann [J. Mach. Learn. Res. 8 (2007) 613�636] described a uniformly consistent estimator of the Markov equivalence class of a linear Gaussian causal structure under the Causal Markov and Strong Causal Faithfulness assumptions. However, the Strong Faithfulness assumption may be false with high probability in many domains. We describe a uniformly consistent estimator of both the Markov equivalence class of a linear Gaussian causal structure and the identifiable structural coefficients in the Markov equivalence class under the Causal Markov assumption and the considerably weaker k-Triangle-Faithfulness assumption.
Cell Matrix Remodeling Ability Shown by Image Spatial Correlation

Extracellular matrix (ECM) remodeling is a critical step of many biological and pathological processes. However, most of the studies to date lack a quantitative method to measure ECM remodeling at a scale comparable to cell size. Here, we applied image spatial correlation to collagen second harmonic generation (SHG) images to quantitatively evaluate the degree of collagen remodeling by cells. We propose a simple statistical method based on spatial correlation functions to determine the size of high collagen density area around cells. We applied our method to measure collagen remodeling by two breast cancer cell lines (MDA-MB-231 and MCF-7), which display different degrees of invasiveness, and a fibroblast cell line (NIH/3T3). We found distinct collagen compaction levels of these three cell lines by applying the spatial correlation method, indicating different collagen remodeling ability. Furthermore, we quantitatively measured the effect of Latrunculin B and Marimastat on MDA-MB-231 cell line collagen remodeling ability and showed that significant collagen compaction level decreases with these treatments.
On irreducible four--manifolds

We show that minimal symplectic 4--manifolds with $b_2^+ >1$ and with residually finite fundamental groups are irreducible. We also give examples of irreducible orientable four--manifolds with indefinite intersection forms which are not almost complex with respect to either orientation.
Performance Improvement of MX-CIF Quadtree by Reducing the Query Results

An MX-CIF quadtree is a variant of quadtreewhich is for efficient spatial querysuch as whether objects are included by a spatial area. When query objects are indexed, a primary result withcandidates which may intersect the query rectanglewill be reported to have asuccessional precise inspection.We saved time from inspecting each of the objectsintensively.The fewer the candidates are reported to the exact query; the less the timeis used to accomplish a query.In this paper, we propose an improved MX-CIF quadtree, compared with the original MX-CIF quadtree.A filter with our structure will decrease the failure rate of result, that is, a query will get fewer uncertain objects, the mechanism of which accelerates the secondary query. Compare to original MX-CIF quadtree, with polygon data given by JTS Topology Suite (JTS)(1), 42.1%~67.5% incorrect resultswere filtered outby our improved MX-CIF quadtree,and its cost of tree-building timeis only slightly higher than the original MX-CIF quadtree.
Lipid MALDI MS Profiles of Gastric Cancer

Tissue matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS)may identify lipids differentially expressed between cancer and adjacent normal tissue. To identify lipidomic profiles for gastric cancer, 24 gastric cancerswere profiled for lipid by the histology-directed, tissue MALDI MS technology. Lipid profiles differed between gastric cancer and adjacent normal tissue samples. At P<0.05, median class prediction accuracy in 100 random training-to-test partitions was 83.3% (5/6) for all classifiers tested. A peak at m/z 741.6 (sphingomyelin 34:1 K) was overexpressed, and a peak at m/z 782.6 (phosphatidylcholine 34:1 Na) was underexpressed in gastric cancers compared with normal tissue. Thus, lipid MALDI MS analysis may capture a global alteration in lipid profile of gastric cancer tissue, distinguishing cancerous epithelium from normal epithelium.
Current status of tropical fruit breeding and genetics for three tropical fruit species cultivated in Japan: pineapple, mango, and papaya

Tropical fruit crops are predominantly produced in tropical and subtropical developing countries, but some are now grown in southern Japan. Pineapple (Ananas comosus), mango (Mangifera indica) and papaya (Carica papaya) are major tropical fruits cultivated in Japan. Modern, well-organized breeding systems have not yet been developed for most tropical fruit species. Most parts of Japan are in the temperate climate zone, but some southern areas such as the Ryukyu Islands, which stretch from Kyushu to Taiwan, are at the northern limits for tropical fruit production without artificial heating. In this review, we describe the current status of tropical fruit breeding, genetics, genomics, and biotechnology of three main tropical fruits (pineapple, mango, and papaya) that are cultivated and consumed in Japan. More than ten new elite cultivars of pineapple have been released with improved fruit quality and suitability for consumption as fresh fruit. New challenges and perspectives for obtaining high fruit quality are discussed in the context of breeding programs for pineapple.
Medicine Box: Doctor’s Prescription Recognition Using Deep Machine Learning

A Doctor’s prescription is a handwritten document written by doctors in the form of instructions that describes list of drugs for patients in time sickness, injuries and other disability problems. While we receiving a new prescription from doctor, it is unable to understand what drug name is prescribed on it. In most cases, however, we wouldn't be able to read it anyway because doctors use Latin abbreviations and medical terminologies on prescriptions that are not understandable by the general persons which make reading it very difficult. According to the National Academy of Sciences estimates that at least 1.5 million peoples are sickened, injured or killed each year by errors while reading prescription. This paper resolves the problems in doctor’s prescriptions through Medicine Box, and Smart phone application that uses Conventional Neural Network (CNN) to recognize handwritten medicine names and return readable digital text. This mobile application uses TensorFlow as the machine learning library, and Custom Repository to match the partial string with the drug name. With Medicine Box, cases of misinterpretation of medicine names can be decreased. This makes the ordinary persons to understand what doctor is prescribed in the prescription and also help for pharmacists.
Implementing family-centred care: an exploration of the beliefs and practices of paediatric nurses.

OBJECTIVE This study explored paediatric nurses' perceptions of how they include and involve parents in the care of hospitalised children. DESIGN This qualitative study used individual unstructured interviews to gather data, the data was analysed using thematic coding. SETTING Paediatric wards within two regional area health services of New South Wales, Australia. SUBJECTS Fourteen paediatric nurses were asked to describe their beliefs and practices regarding the clinical application of family-centred care. MAIN OUTCOME MEASURE Paediatric nurses' beliefs and practices about family-centred care were explored in an effort to explain how the concept was implemented. RESULTS The findings are presented as four interconnected themes. The first describes how participants either allocated tasks to parents or retained them, the second relates to the nurses' professional identity, the third theme identifies barriers and constraints to the implementation of family-centred care, while the fourth describes the nurses' beliefs about their responsibilities when delivering family-centred care. CONCLUSIONS Together these findings suggest that while nurses endorse the concept of family-centred care, the implementation into practice is more problematic. While it is not possible to generalise these findings to other paediatric nurses, the authors believe the insight gained will resonate with paediatric nurses internationally. The findings from this study are being used as the basis for the development of clinical practice guidelines to assist paediatric nurses to more consistently apply the concepts of family-centred care to their practice.
Demonstrations in Visual Frames: Syntagmatic Analysis of Online Photo Albums of Two Egyptian Revolutions

Photos of demonstrations in Egypt have been overwhelmingly used in online news since the revolution of January 25, 2011. This article explores the visual aspects of demonstration photo albums during the political conflicts in Egypt that led to two Egyptian revolutions.1 It scrutinizes the different types of photo albums, considers the differences and similarities between photo album frames and still photograph frames, and implements syntagmatic analysis of demonstration albums. The article concludes that visual framing occurs through nonchronological and sequential syntagmas.
Limits on Stellar and Planetary Companions in Microlensing Event OGLE-1998-BUL-14

We present the PLANET photometric data set for OGLE-1998-BUL-14, a high-magnification (Amax ~ 16) event alerted by the OGLE collaboration toward the Galactic bulge in 1998. The PLANET data set consists a total of 461 I-band and 139 V-band points, the majority of which was taken over a 3 month period. The median sampling interval during this period is about 1 hr, and the 1 σ scatter over the peak of the event is 1.5%. The excellent data quality and high maximum magnification of this event make it a prime candidate to search for the short-duration, low-amplitude perturbations that are signatures of a planetary companion orbiting the primary lens. The observed light curve for OGLE-1998-BUL-14 is consistent with a single lens (no companion) within photometric uncertainties. We calculate the detection efficiency of the light curve to lensing companions as a function of the mass ratio and angular separation of the two components. We find that companions of mass ratio ≥ 0.01 are ruled out at the 95% significance level for projected separations between 0.4 and 2.4rE, where rE is the Einstein ring radius of the primary lens. Assuming that the primary is a G dwarf with rE ~ 3 AU, our detection efficiency for this event is ~60% for a companion with the mass and separation of Jupiter and ~5% for a companion with the mass and separation of Saturn. Our efficiencies for planets like those around υ And and 14 Her are > 75%.
iWarp: an integrated solution to high-speed parallel computing

A description is given of the iWarp architecture and how it supports various communication models and system configurations. The heart of an iWarp system is the iWarp component: a single-chip processor that requires only the addition of memory chips to form a complete system building block, called the iWarp cell. Each iWarp component contains both a powerful computation engine that runs at 20 MFLOPS (million floating-point operations per second) and a high-throughput (320 Mb/s), low-latency (100-150-ns) communication engine for interfacing with other iWarp cells. Because of their strong computation and communication capabilities, the iWarp components provide a versatile building block for high-performance parallel systems ranging from special-purpose systolic arrays to general-purpose distributed memory computers. They can support both fine-grain parallel and coarse-grain distributed computation models simultaneously in the same system. The initial iWarp demonstration system consists of an 8*8 torus of iWarp cells, delivering more than 1.2 GFLOP (billions of FLOPS). It can be expanded to include up to 1024 cells. <<ETX>>
Naïve Random Neighbor Selection for memory based Collaborative Filtering

Collaborative Filtering (CF) is one challenging problem in information retrieval, with memory based become popular among other applicable methods. Memory based CF measure distance/similarity between users by calculating their rating to several items. In the next step system will predict user rating with specific algorithm e.g. Weight Sum. One similarity measurement that often used is Pearson correlation. Since CF used many (almost all) users and items, Pearson correlation suffer on time and space complexity. To overcome this problem, CF that used Pearson correlation often selects some user to be used as neighbor. The mechanism itself, never mention clearly. In this paper, we introduce Naïve Random Neighbor Selection mechanism. Our research show that best performance achieve at parameter combination of Pearson Correlation Threshold = 0.1 and Number of Neighbor = 21 that shows MAE = 0.791 that placed on the third position among other algorithm.