Miracle-dz/UniFAR-FTUs huggingface dataset:
Re-evaluating the Paleogeography of the River-dominated and Wave-influenced Ferron Notom Delta, Southern Central Utah: an Integration of Detailed Facies-architecture and Paleocurrent Analysis

Abstract This study re-evaluates the paleogeography of a river-dominated and wave-influenced deltaic system in a single parasequence (6a) of the Cretaceous Ferron Sandstone, south-central Utah, which was previously interpreted as a typical asymmetric delta. The conceptual asymmetric-delta model of Bhattacharya and Giosan (2003) has been widely applied to interpret ancient deltaic systems. However, reconstructed paleogeographies relying on this conceptual model are commonly not scaled to the architectural elements, which could possibly lead to inaccurate interpretations, especially when data are relatively sparse. The extensively exposed Ferron Sandstone outcrops provide an opportunity to demonstrate how detailed facies-architecture work can be integrated with regional facies relationships to elucidate a properly scaled paleogeography. Seven facies associations (FA) are identified in parasequence 6a and are arranged into two distinctively different successions. The river-dominated succession consists of prodelta, distal delta-front, proximal delta-front, and terminal-distributary-channel FA, while the wave- and storm-dominated succession comprises offshore-shelf, lower-shoreface, and upper-shoreface FA. The river-dominated succession is muddier and less bioturbated than the wave- and storm-dominated succession. Facies-architecture analysis shows that the river-dominated proximal delta-front facies consists of mouth-bar and terminal distributary-channel elements that are not seen in the wave- and storm-dominated facies. The scales of mouth bars and terminal distributary channels suggest that they are rather small features compared with the river-dominated delta lobe, which is incompatible with the simple bar-elongation asymmetric-delta model presented by Li et al. (2011). Instead, parasequence 6a is interpreted to be a valley-fed, river-dominated symmetric delta protected from waves by an updrift barrier system, which is analogous to the modern Mongky river delta on the west coast of Madagascar. The progressive change in orientation of west-directed mouth bars, to north-directed and east-directed lobes around the periphery of the river-dominated delta, indicates a highly radial Lafourche-type delta. Moving away from the protection of the barrier system, there is a gradual change from highly river-dominated facies to increasingly wave- and storm-influenced facies toward the southeast. Due to the entrenched nature of the feeder river associated with an incised-valley system, the parasequence 6a delta was bifurcation-dominated rather than avulsion-dominated. This study shows that it is critical to integrate detailed facies-architecture analysis in order to reconstruct properly scaled paleogeographies and hypothesizes that stable bifurcation-dominated deltas should be more common than avulsion-dominated deltas in a lowstand delta system due to the entrenched nature of the feeding trunk river, which inhibits avulsion.
QoS-Based Design for Security Enhancement in TDMA-Based Wireless Networks

This paper investigates a cross-layer design to secure a set of buffered legitimate source nodes wishing to communicate with a common destination node. We assume a slotted-system and time-division multiple-access spectrum sharing where only one legitimate source node is allowed to transmit in a given time slot. The users' assignment probabilities to the time slots are optimized to satisfy a certain quality-of-service (QoS) requirement for all the legitimate source nodes. These probabilities are shown to be functions of the system parameters, secrecy rate outage probabilities, and arrival rates to the users' queues. To further improve the system's security and maximize the network performance measured by QoS metrics, i.e., secure stable-throughput region, we propose and compare beamforming-based cooperative jamming schemes that depend on the availability of the eavesdropper's instantaneous channel state information at the legitimate nodes. Each of the jamming schemes results in a different set of secrecy outage probabilities for the legitimate users which vary the time-assignment probabilities. We derive the secrecy stable- throughput region of the investigated wireless network. Our proposed jamming schemes achieve significant increase in the secure throughput over the fixed-jamming and no-jamming schemes.
A tabletop groupware system for computer-based music composition

Tabletop can be used in groupware systems in order to both provide a rich interface shared workspaces and support work with co-located and remote users. Tabletop-based groupware systems can allow users to work together over a shared horizontal display. Music composition is an application that can exploit the features of tabletops. However, there is no current tabletop groupware approach that allows remote users to collaborate in music composition. This paper presents a discussion on how to promote collaborative music composition with tabletop groupware in a distributed context. In order to support the discussion, we have built a prototype to simulate instruments and to record the notes played into a modified music editing application. The prototype allows remote users to cooperate by playing music and recording the result of the composition. Potential applications of our prototype include music playing and training, computer aided composition, education, and recreational usage.
"MS-Patch-Clamp" or the Possibility of Mass Spectrometry Hybridization with Patch-Clamp Setups for Single Cell Metabolomics and Channelomics

In this projecting work we propose a mass spectrometric patch-clamp equipment with the capillary performing both a local potential registration at the cell membrane and the analyte suction simultaneously. This paper provides a current literature analysis comparing the possibilities of the novel approach proposed with the known methods, such as scanning patch-clamp, scanning ion conductance microscopy, patch clamp based on scanning probe microscopy technology, quantitative subcellular secondary ion mass spectrometry or "ion microscopy", live single-cell mass spectrometry, in situ cell-by-cell imaging, single-cell video-mass spectrometry, etc. We also consider the ways to improve the informativeness of these methods and particularly emphasize the trend at the increasing of the analysis complexity. We propose here the way to improve the efficiency of the cell trapping to the capillary during MS-path-clamp, as well as to provide laser surface ionization using laser trapping and tweezing of cells with the laser beam transmitted through the capillary as a waveguide. It is also possible to combine the above system with the microcolumn separation system or capillary electrophoresis as an optional direction of further development of the complex of analytical techniques emerging from the MS variation of patch-clamp.
Deliveries in an Inventory/Routing Problem Using Stochastic Dynamic Programming

An industrial gases tanker vehicle visitsn customers on a tour, with a possible ( n + 1)st customer added at the end. The amount of needed product at each customer is a known random process, typically a Wiener process. The objective is to adjust dynamically the amount of product provided on scene to each customer so as to minimize total expected costs, comprising costs of earliness, lateness, product shortfall, and returning to the depot nonempty. Earliness costs are computed by invocation of an annualized incremental cost argument. Amounts of product delivered to each customer are not known until the driver is on scene at the customer location, at which point the customer is either restocked to capacity or left with some residual empty capacity, the policy determined by stochastic dynamic programming. The methodology has applications beyond industrial gases.
LTCC Oversized Rectangular Waveguide Slot Array Antenna With Air-Layer in the Radiating Part in the Millimeter-Wave Band

This paper presents an LTCC oversized rectangular waveguide slot array antenna with an air layer in the radiating part. The antenna is fed by an LTCC fully-filled waveguide. The air-layer addition reduces the transmission loss to enhance the gain. It also reduces the effective dielectric constant to enhance the bandwidth of the series-fed slot array. The measured near-field distribution shows the hard-surface sidewalls to enhance the field uniformity on the aperture by ensuring quasi-TEM mode propagation. The transmission loss in the radiating part with the addition of the air layer of half the height was reduced compared with conventional fully-filled LTCC antenna.
Discriminative Unsupervised Dimensionality Reduction

As an important machine learning topic, dimensionality reduction has been widely studied and utilized in various kinds of areas. A multitude of dimensionality reduction methods have been developed, among which unsupervised dimensionality reduction is more desirable when obtaining label information requires onerous work. However, most previous unsupervised dimensionality reduction methods call for an affinity graph constructed beforehand, with which the following dimensionality reduction steps can be then performed. Separation of graph construction and dimensionality reduction leads the dimensionality reduction process highly dependent on quality of the input graph. In this paper, we propose a novel graph embedding method for unsupervised dimensionality reduction. We simultaneously conduct dimensionality reduction along with graph construction by assigning adaptive and optimal neighbors according to the projected local distances. Our method doesn't need an affinity graph constructed in advance, but instead learns the graph concurrently with dimensionality reduction. Thus, the learned graph is optimal for dimensionality reduction. Meanwhile, our learned graph has an explicit block diagonal structure, from which the clustering results could be directly revealed without any postprocessing steps. Extensive empirical results on dimensionality reduction as well as clustering are presented to corroborate the performance of our method.
Joint Modeling of Trigger Identification and Event Type Determination in Chinese Event Extraction

Currently, Chinese event extraction systems suffer much from the low quality of annotated event corpora and the high ratio of pseudo trigger mentions to true ones. To resolve these two issues, this paper proposes a joint model of trigger identification and event type determination. Besides, several trigger filtering schemas are introduced to filter out those pseudo trigger mentions as many as possible. Evaluation on the ACE 2005 Chinese corpus justifies the effectiveness of our approach over a strong baseline.
Unsupervised feature selection for sparse data

Feature selection is a well-known problem in machine learning and pattern recognition. Many high-dimensional datasets are sparse, that is, many features have zero value. In some cases, we do not known the class label for some (or even all) patterns in the dataset, leading us to semi-supervised or unsupervised learning problems. For instance, in text classification with the bag-of-words (BoW) represen- tations, there is usually a large number of features, many of which may be irrelevant (or even detrimental) for categorization tasks. In this paper, we propose one efficient unsupervised feature selection technique for sparse data, suitable for both standard floating point and binary features. The experimental results on standard datasets show that the proposed method yields efficient feature selection, reducing the number of features while simultaneously improving the classification accuracy.
Covariance descriptors on moving regions for human detection in very complex outdoor scenes

The detection of humans in very complex scenes can be very challenging, due to the performance degradation of classical motion detection and tracking approaches. An alternative approach is the detection of human-like patterns over the whole image. The present paper follows this line by extending Tuzel et al.'s technique [1] based on covariance descriptors and LogitBoost algorithm applied over Riemannian manifolds. Our proposal represents a significant extension of it by: (a) exploiting motion information to focus the attention over areas where motion is present or was present in the recent past; (b) enriching the human classifier by additional, dedicated cascades trained on positive and negative samples taken from the specific scene; (c) using a rough estimation of the scene perspective, to reduce false detections and improve system performance. This approach is suitable in multi-camera scenarios, since the monolithic block for human-detection remains the same for the whole system, whereas the parameter tuning and set-up of the three proposed extensions (the only camera-dependent parts of the system), are automatically computed for each camera. The approach has been tested on a construction working site where complexity and dynamics are very high, making human detection a real challenge. The experimental results demonstrate the improvements achieved by the proposed approach.
An experimental study of large-scale mobile social network

Mobile social network is a typical social network where one or more individuals of similar interests or commonalities, conversing and connecting with one another using the mobile phone. Our works in this paper focus on the experimental study for this kind of social network with the support of large-scale real mobile call data. The main contributions can be summarized as three-fold: firstly, a large-scale real mobile phone call log of one city has been extracted from a mobile phone carrier in China to construct mobile social network; secondly, common features of traditional social networks, such as power law distribution and small diameter etc, have been experimented, with which we confirm that the mobile social network is a typical scale-free network and has small-world phenomenon; lastly, different from traditional analytical methods, important properties of the actors, such as gender and age, have been introduced into our experiments with some interesting findings about human behavior, for example, the middle-age people are more active than the young and old people, and the female is unusual more active than the male while in the old age.
Estrogen induction of hepatocellular carcinomas in Armenian hamsters

Liver tumors were found in most Armenian hamsters (Cricetulus migratorius) injected with on 15‐mg pellet of diethylstilbestrol. The tumors were detectable as early as 1.5 mo after diethylstilbestrol administration and were usually present as multiple nodules that progressively increased in size. Histologically, the multicentric neoplasms were all hepatocellular carcinomas of varied degrees of differentiation and frequently (42.8%) contained Mallory bodies; preneoplastic lesions were not observed. This hepatocellular carcinoma hamster model is unique because estrogen alone without any other known mutagen is responsible for induction of hepatocellular carcinoma. (HEPATOLOGY 1990; 11:570:577.)
Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors

An accurate model of patient survival time can help in the treatment and care of cancer patients. The common practice of providing survival time estimates based only on population averages for the site and stage of cancer ignores many important individual differences among patients. In this paper, we propose a local regression method for learning patient-specific survival time distribution based on patient attributes such as blood tests and clinical assessments. When tested on a cohort of more than 2000 cancer patients, our method gives survival time predictions that are much more accurate than popular survival analysis models such as the Cox and Aalen regression models. Our results also show that using patient-specific attributes can reduce the prediction error on survival time by as much as 20% when compared to using cancer site and stage only.
A 10-bit 500-MS/s Partial-Interleaving Pipelined SAR ADC With Offset and Reference Mismatch Calibrations

A 10-bit 500-MS/s partial-interleaving pipelined successive approximation register (SAR) analog-to-digital converter (ADC) architecture is presented that implements a full-speed 2-bit/cycle SAR at the front end with interleaved residue MDACs and SAR ADCs at the back end. This architecture achieves high speed, while preventing the interleaving spurs. In addition, the design considerations and calibration techniques for gain and offset are also introduced. A histogram stage gain error (HSGE) calibration is implemented to correct the conversion nonlinearities in the digital domain. Measurement results on a 65-nm CMOS prototype show an signal-to-noise distortion ratio (SNDR) of 55.9 dB at dc input and a figure of merit (FoM) of 32 fJ/conversion step at 1.2 V supply.
Attenuation of TORC1 signaling delays replicative and oncogenic RAS-induced senescence

Numerous stimuli, including oncogenic signaling, DNA damage or eroded telomeres trigger proliferative arrest, termed cellular senescence. Accumulating evidence suggests that cellular senescence is a potent barrier to tumorigenesis in vivo, however oncogene induced senescence can also promote cellular transformation.1,2 Several oncogenes, whose overexpression results in cellular senescence, converge on the TOR (target of rapamycin) pathway. We therefore examined whether attenuation of TOR results in delay or reversal of cellular senescence. By using primary human fibroblasts undergoing either replicative or oncogenic RAS-induced senescence, we demonstrated that senescence can be delayed, and some aspects of senescence can be reversed by inhibition of TOR, using either the TOR inhibitor rapamycin or by depletion of TORC1 (TOR Complex 1). Depletion of TORC2 fails to affect the course of replicative or RAS-induced senescence. Overexpression of REDD1 (Regulated in DNA Damage Response and Development), a negative regulator of TORC1, delays the onset of replicative senescence. These results indicate that TORC1 is an integral component of the signaling pathway that mediates cellular senescence.
Noninvasive Assessment of Tissue Heating During Cardiac Radiofrequency Ablation Using MRI Thermography

Background—Failure to achieve properly localized, permanent tissue destruction is a common cause of arrhythmia recurrence after cardiac ablation. Current methods of assessing lesion size and location during cardiac radiofrequency ablation are unreliable or not suited for repeated assessment during the procedure. MRI thermography could be used to delineate permanent ablation lesions because tissue heating above 50°C is the cause of permanent tissue destruction during radiofrequency ablation. However, image artifacts caused by cardiac motion, the ablation electrode, and radiofrequency ablation currently pose a challenge to MRI thermography in the heart. In the current study, we sought to demonstrate the feasibility of MRI thermography during cardiac ablation. Methods and Results—An MRI-compatible electrophysiology catheter and filtered radiofrequency ablation system was used to perform ablation in the left ventricle of 6 mongrel dogs in a 1.5-T MRI system. Fast gradient-echo imaging was performed before and during radiofrequency ablation, and thermography images were derived from the preheating and postheating images. Lesion extent by thermography was within 20% of the gross pathology lesion. Conclusions—MR thermography appears to be a promising technique for monitoring lesion formation and may allow for more accurate placement and titration of ablation, possibly reducing arrhythmia recurrences.
De Novo Sequencing and Characterization of the Floral Transcriptome of Dendrocalamus latiflorus (Poaceae: Bambusoideae)

Background Transcriptome sequencing can be used to determine gene sequences and transcript abundance in non-model species, and the advent of next-generation sequencing (NGS) technologies has greatly decreased the cost and time required for this process. Transcriptome data are especially desirable in bamboo species, as certain members constitute an economically and culturally important group of mostly semelparous plants with remarkable flowering features, yet little bamboo genomic research has been performed. Here we present, for the first time, extensive sequence and transcript abundance data for the floral transcriptome of a key bamboo species, Dendrocalamus latiflorus, obtained using the Illumina GAII sequencing platform. Our further goal was to identify patterns of gene expression during bamboo flower development. Results Approximately 96 million sequencing reads were generated and assembled de novo, yielding 146,395 high quality unigenes with an average length of 461 bp. Of these, 80,418 were identified as putative homologs of annotated sequences in the public protein databases, of which 290 were associated with the floral transition and 47 were related to flower development. Digital abundance analysis identified 26,529 transcripts differentially enriched between two developmental stages, young flower buds and older developing flowers. Unigenes found at each stage were categorized according to their putative functional categories. These sequence and putative function data comprise a resource for future investigation of the floral transition and flower development in bamboo species. Conclusions Our results present the first broad survey of a bamboo floral transcriptome. Although it will be necessary to validate the functions carried out by these genes, these results represent a starting point for future functional research on D. latiflorus and related species.
Obtaining Trustworthy Test Results in Multi-threaded Systems

Testing multi-threaded systems is quite a challenge. The non-determinism of these systems makes their implementation and their test implementation far more susceptible to error. It is common to have tests of these systems that may not pass sometimes and whose failures are not caused by application faults (bugs). For instance, this can happen when test verifications (assertions) are performed at inappropriate times. Unreliable tests make developers waste their time trying to find non-existing bugs, or else make them search for bugs in the wrong place. Another problem is that developers may cease to believe that certain test failures are caused by software bugs even when this is the case. In this paper, we propose an approach to avoid test failures that are caused, not by application bugs, but by test assertions performed either too early or too late. Our basic idea is to use thread monitoring to support test development. Moreover, we put forward a testing framework that follows the proposed approach, and we also evaluate the effectiveness of this framework for testing a multi-threaded system.
Hybrid real-coded genetic algorithms with female and male differentiation

Parent-centric real-parameter crossover operators create the offspring in the neighborhood of one of the parents, the female parent, using a probability distribution. The other parent, the male one, defines the range of this probability distribution. The female and male differentiation process determines the individuals in the population that may become female or/and male parents. An important property of this process is that it makes possible the design of two kinds of real-coded genetic algorithms: ones that promote global search and ones that are effective local searchers. In this paper, we study the performance of a hybridization of these real-coded genetic algorithms when tackling the test problems proposed for the Special Session on Real-Parameter Optimization of the IEEE Congress on Evolutionary Computation 2005