Miracle-dz/UniFAR-FTUs huggingface dataset:
Recommendations for mass spectrometry data quality metrics for open access data (corollary to the Amsterdam Principles).

Policies supporting the rapid and open sharing of proteomic data are being implemented by the leading journals in the field. The proteomics community is taking steps to ensure that data are made publicly accessible and are of high quality, a challenging task that requires the development and deployment of methods for measuring and documenting data quality metrics. On September 18, 2010, the U.S. National Cancer Institute (NCI) convened the "International Workshop on Proteomic Data Quality Metrics" in Sydney, Australia, to identify and address issues facing the development and use of such methods for open access proteomics data. The stakeholders at the workshop enumerated the key principles underlying a framework for data quality assessment in mass spectrometry data that will meet the needs of the research community, journals, funding agencies, and data repositories. Attendees discussed and agreed up on two primary needs for the wide use of quality metrics: (1) an evolving list of comprehensive quality metrics and (2) standards accompanied by software analytics. Attendees stressed the importance of increased education and training programs to promote reliable protocols in proteomics. This workshop report explores the historic precedents, key discussions, and necessary next steps to enhance the quality of open access data. By agreement, this article is published simultaneously in the Journal of Proteome Research, Molecular and Cellular Proteomics, Proteomics, and Proteomics Clinical Applications as a public service to the research community. The peer review process was a coordinated effort conducted by a panel of referees selected by the journals.
Bacteriophage φYeO3-12, Specific forYersinia enterocolitica Serotype O:3, Is Related to Coliphages T3 and T7

ABSTRACT Bacteriophage φYeO3-12 is a lytic phage of Yersinia enterocolitica serotype O:3. The phage receptor is the lipopolysaccharide O chain of this serotype that consists of the rare sugar 6-deoxy-l-altropyranose. A one-step growth curve of φYeO3-12 revealed eclipse and latent periods of 15 and 25 min, respectively, with a burst size of about 120 PFU per infected cell. In electron microscopy φYeO3-12 virions showed pentagonal outlines, indicating their icosahedral nature. The phage capsid was shown to be composed of at least 10 structural proteins, of which a protein of 43 kDa was predominant. N-terminal sequences of three structural proteins were determined, two of them showing strong homology to structural proteins of coliphages T3 and T7. The phage genome was found to consist of a double-stranded DNA molecule of 40 kb without cohesive ends. A physical map of the phage DNA was constructed using five restriction enzymes. The phage infection could be effectively neutralized using serum from a rabbit immunized with whole φYeO3-12 particles. The antiserum also neutralized T3 infection, although not as efficiently as that of φYeO3-12. φYeO3-12 was found to share, in addition to the N-terminal sequence homology, several common features with T3, including morphology and nonsubjectibility to F exclusion. The evidence conclusively indicated that φYeO3-12 is the first close relative of phage T3 to be described.
Obstacle Avoidance On Roadways Using Range Data

This report describes range data based obstacle avoidance techniques developed for use on an autonomous road-following robot vehicle. The purpose of these techniques is to detect and locate obstacles present in a road environment for navigation of a robot vehicle equipped with an active laser-based range sensor. Techniques are presented for obstacle detection, obstacle location, and coordinate transformations needed in the construction of Scene Models (symbolic structures representing the 3-D obstacle boundaries used by the vehicle's Navigator for path planning). These techniques have been successfully tested on an outdoor robotic vehicle, the Autonomous Land Vehicle (ALV), at speeds up to 3.5 km/hour.
Discriminative Orthogonal Neighborhood-Preserving Projections for Classification

Orthogonal neighborhood-preserving projection (ONPP) is a recently developed orthogonal linear algorithm for overcoming the out-of-sample problem existing in the well-known manifold learning algorithm, i.e., locally linear embedding. It has been shown that ONPP is a strong analyzer of high-dimensional data. However, when applied to classification problems in a supervised setting, ONPP only focuses on the intraclass geometrical information while ignores the interaction of samples from different classes. To enhance the performance of ONPP in classification, a new algorithm termed discriminative ONPP (DONPP) is proposed in this paper. DONPP 1) takes into account both intraclass and interclass geometries; 2) considers the neighborhood information of interclass relationships; and 3) follows the orthogonality property of ONPP. Furthermore, DONPP is extended to the semisupervised case, i.e., semisupervised DONPP (SDONPP). This uses unlabeled samples to improve the classification accuracy of the original DONPP. Empirical studies demonstrate the effectiveness of both DONPP and SDONPP.
Design pattern density defined

Design pattern density is a metric that measures how much of an object-oriented design can be understood and represented as instances of design patterns. Expert developers have long believed that a high design pattern density implies a high maturity of the design under inspection. This paper presents a quantifiable and observable definition of this metric. The metric is illustrated and qualitatively validated using four real-world case studies. We present several hypotheses of the metric's meaning and their implications, including the one about design maturity. We propose that the design pattern density of a maturing framework has a fixed point and we show that if software design patterns make learning frameworks easier, a framework's design pattern density is a measure of how much easier it will become.
Five‐minute, 1/2°, and 1° data sets of continental watersheds and river networks for use in regional and global hydrologic and climate system modeling studies

A major shortcoming of the land surface component in climate models is the absence of a river transport algorithm. This issue becomes particularly important in fully coupled climate system models (CSMs), where river transport is required to close and realistically represent the global water cycle. The development of a river transport algorithm requires knowledge of watersheds and river networks at a scale that is appropriate for use in CSMs. These data must be derived largely from global digital topographic information. The purpose of this paper is to describe a new data set of watersheds and river networks, which is derived primarily from the TerrainBase 5′ Global DTM (digital terrain model) and the CIA World Data Bank II. These data serve as a base map for routing continental runoff to the appropriate coast and therefore into the appropriate ocean or inland sea. Using this data set, the runoff produced in any grid cell, when coupled with a routing algorithm, can easily be transported to the appropriate water body and distributed across that water body as desired. The data set includes watershed and flow direction information, as well as supporting hydrologic data at 5′, 1/2°, and 1° resolutions globally. It will be useful in fully coupled land‐ocean‐atmosphere models, in terrestrial ecosystem models, or in stand‐alone macroscale hydrologic‐modeling studies.
Proof-irrelevant model of CC with predicative induction and judgmental equality

We present a set-theoretic, proof-irrelevant model for Calculus of Constructions (CC) with predicative induction and judgmental equality in Zermelo-Fraenkel set theory with an axiom for countably many inaccessible cardinals. We use Aczel's trace encoding which is universally defined for any function type, regardless of being impredicative. Direct and concrete interpretations of simultaneous induction and mutually recursive functions are also provided by extending Dybjer's interpretations on the basis of Aczel's rule sets. Our model can be regarded as a higher-order generalization of the truth-table methods. We provide a relatively simple consistency proof of type theory, which can be used as the basis for a theorem prover.
Mass and energy flux estimates at different spatial resolutions in a heterogeneous area through a distributed energy–water balance model and remote-sensing data

A physically based, distributed energy–water balance model, Flash-Flood Event-Based Spatially Distributed Rainfall–Runoff Transformation-Energy Water Balance (FEST-EWB) model, and remote-sensing data were analysed to study the representativeness of mass and energy fluxes at different spatial resolutions. The analyses were performed in an agricultural area of Barrax (Spain) in the framework of the Sentinel-2 and Fluorescence Experiment (SEN2FLEX). In particular, there were two main objectives: (1) to evaluate the ability of the distributed hydrological model to compute energy and mass fluxes for a heterogeneous area compared to remote-sensing and ground data and (2) to define the length scales of different processes (evapotranspiration (ET) and land surface temperature (LST)) above which the variance of the different variables becomes insignificant for the process, so that bare soil and vegetation behaviours are no longer distinguishable. Mass and energy fluxes were collected from ground data and from an Airborne Hyperspectral Scanner (AHS), with a spatial resolution between 2 and 4 m, and from the Moderate Resolution Imaging Spectroradiometer (MODIS), with a spatial resolution of 1000 m, and then compared with hydrological model outputs. ET and LST spatial variability was analysed at different spatial resolutions using histograms, statistical parameters, and spatial autocorrelation functions. Computed ET with the FEST-EWB model at high spatial resolution (10 m) showed for the three days of analysis a mean relative error of 9.4% compared to AHS data, whereas for land surface temperature comparison a relative error of 1.6% was found. Then, LSTs from AHS and FEST-EWB were aggregated at decreasing spatial resolutions (50, 150, 300, 400, 500, 600, 750, and 1000 m), showing that the thermodynamic variability tends to disappear with a lower number of classes in the histograms and with a decrease of the coefficient of variation (CV) and of standard deviation values. At each scale, a similar behaviour was reported between each pair of images, with the values of standard deviation starting, respectively, from 8.9°C and 9.6°C at 10 m of spatial resolution to 7.7°C and 7.9°C at 1000 m of spatial resolution. Similar results were obtained from the spatial aggregation of ET images. The decrease in standard deviation values of LST and ET with a decrease in the scale became substantial around pixel dimensions equal to 400 m.
Origin and development of marginal basins in the western Pacific

The semi-isolated basins and series of basins of intermediate to normal oceanic depths that lie behind island arc systems are termed marginal basins, and are believed to be of extensional origin. Marginal basins, although differing in size and amount of sediment fill, are all underlain by oceanic crust, and can be divided into actively spreading inter-arc basins and older inactive basins. The inactive basins are grouped on the basis of age as reflected by crustal heat flow; inactive basins with above-normal heat flow are apparently younger than those with normal heat flow. Volcano-tectonic rift zones with associated silicic tuffs are found in the tectonic position of inter-arc basins in some continental trench-arc systems and are thought to have been formed by similar extensional process. Large scale crustal extension and demonstratable trench migration imply displacement of the Benioff zone. However, the portion of the Benioff zone shallower than 150 km, and lying between the volcanic chain and the trench, remains relatively undeformed along the trend of arc systems in which the dip of the deeper segment of the Benioff zone changes markedly. Geometric relationships suggest that, as the inter-arc basin opens, the trench is forced to migrate and the Benioff zone is flattened, except in areas where crust can be consumed in a second trench behind the extensional zone. Active extension is restricted to arc systems with earthquakes deeper than about 350 km. The available data can be explained by a thermal diapir of shear-heated mantle material, bouyantly rising beneath the inter-arc basin from the upper surface of the under-thrust lithosphere. Hydrostatic forces associated with such a diapir are felt capable of over-coming the compressional forces in the mantle produced by shearing along the upper surface of the lithosphere and by the bending of the lithosphere. The existence of low density, high temperature upper mantle is indicated by the lack of a large gravity anomaly over the shallow oceanic crust of the inter-arc basin, by high heat flow there, and by anomalously high attenuation of shear waves passing through the upper mantle beneath the extensional zone.
A Comparison of Methods for Measuring Spinal Motion in Female Patients With Adolescent Idiopathic Scoliosis

Noninvasive surface measures of spine motion are validated in adult patients but are infrequently used in adolescent scoliosis patients. The agreement between surface and radiographic measurements of spinal motion is not known. We performed a comparative prospective analysis of 3 methods to measure spinal motion in female patients with adolescent idiopathic scoliosis (AIS) to establish normative data of spinal motion in AIS patients and evaluate the relationship between surface and radiographic measurements of spine motion. Measurements were obtained using a cloth tape measure, dual inclinometers, and a 3-dimensional electrogoniometer in 37 female patients with AIS. Radiographic parameters of the deformity were correlated with the spine motion. Differences between methods were evaluated by paired t tests. The Bland-Altman method was applied to evaluate agreement in measuring flexion. The average spinal flexion was 5.7 ± 2.2 cm by the modified Schober method, 49 ± 11 degrees by the dual inclinometers method, and 64 ± 10 degrees by the 3-dimensional electrogoniometer. Spinal motion did not vary with magnitude of the scoliosis. In addition, surface measurements of spinal motion did not correlate with radiographic measurements of scoliosis flexibility. In this study, the amount of spinal motion varied, depending on the method of measurement. Surface measurements of motion cannot predict the magnitude or flexibility of the scoliosis.
Parallel community detection on large networks with propinquity dynamics

Graphs or networks can be used to model complex systems. Detecting community structures from large network data is a classic and challenging task. In this paper, we propose a novel community detection algorithm, which utilizes a dynamic process by contradicting the network topology and the topology-based propinquity, where the propinquity is a measure of the probability for a pair of nodes involved in a coherent community structure. Through several rounds of mutual reinforcement between topology and propinquity, the community structures are expected to naturally emerge. The overlapping vertices shared between communities can also be easily identified by an additional simple postprocessing. To achieve better efficiency, the propinquity is incrementally calculated. We implement the algorithm on a vertex-oriented bulk synchronous parallel(BSP) model so that the mining load can be distributed on thousands of machines. We obtained interesting experimental results on several real network data.
Control of a Robot Dancer for Enhancing Haptic Human-Robot Interaction in Waltz

Haptic interaction between a human leader and a robot follower in waltz is studied in this paper. An inverted pendulum model is used to approximate the human's body dynamics. With the feedbacks from the force sensor and laser range finders, the robot is able to estimate the human leader's state by using an extended Kalman filter (EKF). To reduce interaction force, two robot controllers, namely, admittance with virtual force controller, and inverted pendulum controller, are proposed and evaluated in experiments. The former controller failed the experiment; reasons for the failure are explained. At the same time, the use of the latter controller is validated by experiment results.
An e $ cient fuzzy algorithm for aligning shapes under a $ ne transformations

A fuzzy algorithm for aligning object shapes under a$ne transformations is proposed in this paper. The algorithm, with the name of fuzzy alignment algorithm (FAA), extends Marques' algorithm to a$ne transformations. It can e$ciently estimate the point correspondence and the relevant a$ne transformational parameters between the feature points of the object shape and the reference shape. In this algorithm, the fuzzy point-correspondence degrees are used to describe an uncertainty point assignment, then both the parameters of the a$ne transformation and the fuzzy correspondence degrees are iteratively calculated by minimizing a constrained fuzzy objective function. To prevent FAA from sinking into local minimum when the shapes are greatly deformed, an initialization method based on a$ne invariants is designed. Comparing to the eigenvector method, the e! ectiveness and robustness of the proposed algorithm is investigated with a sensitivity study based on randomly generated points. At last, good performance of FAA is illustrated with several experiments on aligning digits and object shapes. 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Toward the Integration of Monitoring in the Orchestration of Across-spaces Learning Situations

Technologies such as augmented Reality (AR), 3D Virtual Worlds (3DVWs) and mobile phones are extending education to other spaces beyond the classroom or the Virtual Learning Environments (VLEs). However, the richness of across-spaces learning situations that could be conducted in all these spaces is hampered by the difficulties (encompassed under the “orchestration” metaphor) that teachers face to carry them out. Monitoring can help in such orchestration, and it has been highly explored in face-to-face and blended learning. Nevertheless, in ubiquitous environments it is usually limited to activities taking place in a specific type of space (e.g., outdoors). In this paper we propose an orchestration system which supports the monitoring of learning situations that may involve web, AR-enabled physical and 3DVW spaces. The proposal was evaluated in three authentic studies, in which a prototype of the system provided monitoring through a web dashboard, an AR app, and a Virtual Globe.
Integrated nutrient management in winter maize (Zea mays L.) sown at different dates

A field experiment was conducted during rabi season of 2006 to 2007 and 2007 to 2008 to study the effect of sowing dates and integrated nutrient management on growth, yield and quality of winter maize. The trial was laid out in split plot design with three replications, assigning total 27 treatment combinations i.e. three sowing dates (15 October, 25 October and 5 November) in main plots and three levels of nitrogen from inorganic fertilizer urea (50, 100 and 150 N20 kg ha-1) and two organic fertilizer (FYM, Azospirillum) and control in sub plots. The crop sown on 25 October significantly enhanced the growth and grain yield than early sowing 15 October and late sowing 5 November while, 150 kg of N2O ha-1 application significantly increased over 100 and 50 kg N2O ha-1. However, N2O application through FYM was found statistically at par with N2O application through the Azospirillum in growth and grain yield during both years. But, application of 100 kg ha-1 with 7.50 t ha-1 FYM at the sowing of 25 Oct significantly influenced the growth, yield and quality of maize and was recorded 9.35 and 23.07% more grain yield over the other treatment combinations. Key words: Rabi maize, sowing dates, integrated nutrient management (INM), sustainable, growth, yield.
The Kakeya set and maximal conjectures for algebraic varieties over finite fields

Using the polynomial method of Dvir \cite{dvir}, we establish optimal estimates for Kakeya sets and Kakeya maximal functions associated to algebraic varieties $W$ over finite fields $F$. For instance, given an $n-1$-dimensional projective variety $W \subset \P^n(F)$, we establish the Kakeya maximal estimate $$ \| \sup_{\gamma \ni w} \sum_{v \in \gamma(F)} |f(v)| \|_{\ell^n(W)} \leq C_{n,W,d} |F|^{(n-1)/n} \|f\|_{\ell^n(F^n)}$$ for all functions $f: F^n \to \R$ and $d \geq 1$, where for each $w \in W$, the supremum is over all irreducible algebraic curves in $F^n$ of degree at most $d$ that pass through $w$ but do not lie in $W$, and with $C_{n,W,d}$ depending only on $n, d$ and the degree of $W$; the special case when $W$ is the hyperplane at infinity in particular establishes the Kakeya maximal function conjecture in finite fields, which in turn strengthens the results of Dvir.
Structure and Seasonal Dynamics of Larval Fish in the Caeté River Estuary in North Brazil

The larval fish assemblage was examined along a salinity gradient of the Caete River Estuary situated in northern Brazil. A total of 35 555 larvae, representing 28 families and 63 taxa were collected in samples taken monthly between July 1996 and September 1997, with a mean concentration of 9 individuals per 100 m3. Sciaenidae was the most abundant family comprising 46·5% (11 species) of all teleosts sampled in the Caete River Estuary, followed by Engraulidae (41·9%, seven species). The most abundant larval taxa were the engraulid Anchovia clupeoides and the sciaenid Stellifer microps accounting together for 70·4% of the total catch. The most abundant developmental stages of A. clupeoides was preflexion larva, confirming that this species is resident. Apart from estuarine species, the upper estuary additionally has taxa associated with freshwater conditions, whereas species with marine affinities were captured in the lower estuary. The densities of most species were influenced to a greater degree by site than by season, showing maximum densities in the upper estuary. Larval density peaked in the upper estuary during the dry season and was lowest when freshwater discharge was at its maximum, which was attributed to an increased seaward drift of larvae. Species number was greatest in the upper estuary between the rainy and dry season.
Separating sparse and low-dimensional signal sequences from time-varying undersampled projections of their sums

The goal of this work is to recover a sequence of sparse vectors, st; and a sequence of dense vectors, ℓt, that lie in a “slowly changing” low dimensional subspace, from time-varying undersampled linear projections of their sum. This type of problem typically occurs when the quantity being imaged can be split into a sum of two layers, one of which is sparse and the other is low-dimensional. A key application where this problem occurs is in undersampled functional magnetic resonance imaging (fMRI) to detect brain activation patterns in response to a stimulus. The brain image at time t can be modeled as being a sum of the active region image, st, (equal to the activation in the active region and zero everywhere else) and the background brain image, ℓt, which can be accurately modeled as lying in a slowly changing low dimensional subspace. We introduce a novel solution approach called matrix completion projected compressive sensing or MatComProCS. Significantly improved performance of MatComProCS over existing work is shown for the undersampled fMRI based brain active region detection problem.