Miracle-dz/UniFAR-FTUs huggingface dataset:
Mixotrophy in the nematocyst – taeniocyst complex-bearing

Polykrikos hartmannii is a phototrophic dinoflagellate with chloroplasts, and it swims as a single zooid or forms a two-zooid pseudo-colony. To investigate the feeding ability of P. hartmannii, its feeding occurrence, prey species, and feeding mechanism were explored. Furthermore, the growth and ingestion rates of P. hartmannii on the mixotrophic dinoflagellate Cochlodinium polykrikoides, the optimal prey, as a function of prey concentration were measured. This study reported for the first time that P. hartmannii is a mixotrophic dinoflagellate. When diverse algal species were provided as potential prey, P. hartmannii could feed only on chain-forming toxic mixotrophic dinoflagellates C. polykrikoides and Gymnodinium catenatum. P. hartmannii ingested cells of these prey by engulfment after anchoring a prey cell using a nematocyst–taeniocyst complex. With increasing mean prey concentration, the ingestion rate of P. hartmannii on C. polykrikoides increased, but reached saturation at a prey concentration of 945 ng C ml 1 (1350 cells ml ). The maximum ingestion rate of P. hartmannii on C. polykrikoides was 1.9 ng C predator 1 d 1 (2.7 cells predator 1 d ). However, the maximum mixotrophic growth rate of P. hartmannii with added C. polykrikoides cells (0.030 d ), at 20 8C under a 14:10 h light-dark cycle of 100 mE m 2 s , was slightly greater than of those without added prey (0.023 d ). The low maximum ingestion rate of P. hartmannii may be responsible for this small difference between the maximum mixotrophic and autotrophic growth rates. The calculated grazing coefficients for P. hartmannii on cooccurring C. polykrikoides were up to 0.324 d 1 (28% of the population of C. polykrikoides was removed by P. hartmannii populations in 1 d). The results of the present study suggest that P. hartmannii can have a considerable grazing impact on C. polykrikoides populations. 2015 Elsevier B.V. All rights reserved.
Long Coding RNA XIST Contributes to Neuronal Apoptosis through the Downregulation of AKT Phosphorylation and Is Negatively Regulated by miR-494 in Rat Spinal Cord Injury

Recent evidence has suggested that long non-coding RNAs (lncRNAs) may play a significant role in the pathogenesis of several neurological diseases, including spinal cord injury (SCI). However, little is known about the role of lncRNAs in SCI. The aim of the present study was to evaluate the potential functions of lncRNAs in SCI and to identify the underlying mechanisms of action. We firstly analyzed Gene Expression Omnibus (GEO) datasets to investigate aberrantly-expressed lncRNAs which might be involved in the pathogenesis of SCI. The long non-coding RNA X-inactive specific transcript (XIST) was found to be one of the most significantly upregulated lncRNAs in the GEO dataset analysis, and is associated with apoptosis. We, therefore, selected this as a candidate lncRNA and investigated its function. We found that knockdown of lncRNA-XIST by Lv-shRNA had a prominent protective effect on SCI recovery by suppressing apoptosis through reactivation of the PI3K/AKT signaling pathway in rat spinal cord tissue. In particular, our results suggested that lncRNA-XIST may act as a competitive endogenous RNA, effectively becoming a sink for miR-494, leading to derepression of its target gene, phosphatase and tensin homolog deleted on chromosome ten (PTEN). In addition, an inverse relationship between lncRNA-XIST and miR-494 was observed in spinal cord tissues of SCI rats. Further study demonstrated that antagomiR-494 could reverse the protective effects of lncRNA-XIST knockdown on SCI rats through blocking the PTEN/PI3K/AKT signaling pathway. These results suggested that lncRNA-XIST knockdown may play an important role in limiting neuronal apoptosis in rats following SCI, and that the observed protective effects of lncRNA-XIST knockdown might have been mediated by its regulation on the phosphorylation of AKT by competitively binding miR-494. These findings have revealed, for the first time, the importance of the XIST/miR-494/PTEN/AKT signaling axis in the pathogenesis of SCI and suggest that lncRNA-XIST may be a promising molecular target for SCI therapy.
The Statechart Workbench: Enabling scalable software event log analysis using process mining

To understand and maintain the behavior of a (legacy) software system, one can observe and study the system's behavior by analyzing event data. For model-driven reverse engineering and analysis of system behavior, operation and usage based on software event data, we need a combination of advanced algorithms and techniques. In this paper, we present the Statechart Workbench: a novel software behavior exploration tool. Our tool provides a rich and mature integration of advanced (academic) techniques for the analysis of behavior, performance (timings), frequency (usage), conformance and reliability in the context of various formal models. The accompanied Eclipse plugin allows the user to interactively link all the results from the Statechart Workbench back to the source code of the system and enables users to get started right away with their own software. The work can be positioned in-between reverse engineering and process mining. Implementations, documentation, and a screen-cast (https://youtu.be/xR4XfU3E5mk) of the proposed approach are available, and a user study demonstrates the novelty and usefulness of the tool.
Image-Guided Rendering with an Evolutionary Algorithm Based on Cloud Model

The process of creating nonphotorealistic rendering images and animations can be enjoyable if a useful method is involved. We use an evolutionary algorithm to generate painterly styles of images. Given an input image as the reference target, a cloud model-based evolutionary algorithm that will rerender the target image with nonphotorealistic effects is evolved. The resulting animations have an interesting characteristic in which the target slowly emerges from a set of strokes. A number of experiments are performed, as well as visual comparisons, quantitative comparisons, and user studies. The average scores in normalized feature similarity of standard pixel-wise peak signal-to-noise ratio, mean structural similarity, feature similarity, and gradient similarity based metric are 0.486, 0.628, 0.579, and 0.640, respectively. The average scores in normalized aesthetic measures of Benford's law, fractal dimension, global contrast factor, and Shannon's entropy are 0.630, 0.397, 0.418, and 0.708, respectively. Compared with those of similar method, the average score of the proposed method, except peak signal-to-noise ratio, is higher by approximately 10%. The results suggest that the proposed method can generate appealing images and animations with different styles by choosing different strokes, and it would inspire graphic designers who may be interested in computer-based evolutionary art.
Information seeking on the Web by women in IT professions

The paper develops a behavioral model of Web information seeking that identifies four complementary modes of information seeking: undirected viewing, conditioned viewing, informal search, and formal search. In each mode of viewing or searching, users would adopt distinctive patterns of browser moves: starting, chaining, browsing, differentiating, monitoring, and extracting. The model is applied empirically to analyze the Web information seeking behavior of 24 women in IT professions over a two‐week period. Our results show that participants engaged in all four modes of information seeking on the Web, and that each mode may be characterized by certain browser actions. Overall, the study suggests that a behavioral approach that links information seeking modes (goals and reasons for browsing and searching) to moves (actions used to find and view information) may be helpful in understanding Web‐based information seeking.
Subtraction with Dirichlet Process Mixture Models

Video analysis often begins with background subtraction. This problem is often approached in two steps a background model followed by a regularisation scheme. A model of the background allows it to be distinguished on a per-pixel basis from the foreground, whilst the regularisation combines information from adjacent pixels. We present a new method based on Dirichlet process Gaussian mixture models, which are used to estimate per-pixel background distributions. It is followed by probabilistic regularisation. Using a non-parametric Bayesian method allows per-pixel mode counts to be automatically inferred, avoiding over-/underfitting. We also develop novel model learning algorithms for continuous update of the model in a principled fashion as the scene changes. These key advantages enable us to outperform the state-of-the-art alternatives on four benchmarks.
Effects of an Attachment-based Intervention on CPS-Referred Mothers ’ Event-related Potentials to Children ’ s Emotions

This study examined the neurobiology of maternal sensitivity to children’s emotions among mothers involved with Child Protective Services (CPS) and low-risk comparison mothers (Mean age = 31.6 years). CPS-referred mothers participated in the Attachment and Biobehavioral Catchup (ABC) intervention or a control intervention. Mothers’ event-related potentials (ERP) were measured while they categorized images of children with crying, laughing, and neutral expressions. CPS-referred ABC mothers (n = 19) and low-risk comparison mothers (n = 30) showed a larger enhancement of ERP responses for emotional faces relative to neutral faces than CPS-referred control mothers (n = 21). Additionally, the magnitude of ERP responses to emotional faces was associated with observed maternal sensitivity. Findings add to our understanding of the neurobiology of deficits in parenting and suggest that these deficits are changeable through a parenting intervention. Neglecting mothers often struggle to respond sensitively and synchronously to their children’s cues. Although these deficits have been most often measured through behavioral observation, there is increasing attention being directed toward understanding the neurobiology of optimal and atypical maternal care (Barrett & Fleming, 2011; Swain, Lorberbaum, Kose, & Strathearn, 2007). The Attachment and Biobehavioral Catch-up intervention (ABC; Dozier & the Infant Caregiver Project Lab, 2006) for mothers identified as at risk for neglecting their infants aims to enhance mothers’ sensitivity to children’s distress and increase mothers’ synchronous responding to children’s signals. For the present study, we used event-related potential (ERP) methodology to examine the degree to which the ABC intervention enhanced mothers’ neurobiological processing of children’s emotional signals. Corresponding author: Kristin Bernard, Department of Psychology, Stony Brook University, Stony Brook, NY 11794, kristin.bernard@stonybrook.edu. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Mental Health or the National Institutes of Health. HHS Public Access Author manuscript Child Dev. Author manuscript; available in PMC 2016 November 01. Published in final edited form as: Child Dev. 2015 November ; 86(6): 1673–1684. doi:10.1111/cdev.12418. A uhor M anscript
Reliable Navigation Planning Implementation on a Two-Wheeled Mobile Robot

Autonomous mobile robots must be equipped with appropriate planification and control navigation systems in order to obtain robust behaviours. This study aims at dealing with this kind of problems when implementing on a two wheeled mobile robot. The planning navigation system uses our previously proposed reliable and safe navigation planning algorithm based on the incremental sampling-based planning algorithm, e.g., the widely-used Rapidly-exploring Random Tree (RRT), while the control navigation level consists in a go to goal controller strategy. Through experiments, we demonstrate the usefulness of robust navigation planner in an autonomous navigation schemes, where uncertain localization has to be taken into account.
Field-Scale Apparent Soil Electrical Conductivity

Soils are notoriously spatially heterogeneous and many soil properties are temporally variable. Spatial variability of soil properties has a profound infl uence on agricultural and environmental processes, such as plant–water–soil interactions, water fl ow, and solute transport, resulting in within-fi eld plant yield variation and degradation of soil quality, to mention only a few. Field-scale mapping of spatial variability and monitoring of temporally dynamic soil properties is necessary for a variety of edaphic activities, such as soil surveys, reclamation, crop selection, sitespecifi c management, and soil quality assessment. There are various approaches for characterizing soil spatial variability, but none of these has been as extensively investigated and is as reliable and cost effective as apparent soil electrical conductivity (ECa) directed soil sampling. Geospatial measurements of ECa are well suited for characterizing the spatial distribution of soil properties because they are reliable, quick, and easy to take with GPS-based mobilized ECa measurement equipment. Directed soil sampling based on geo-referenced measurements of ECa is a proven and robust means of characterizing the spatial variability of any soil property that infl uences ECa, including sol salinity, water content, texture, bulk density, organic matter, and cation exchange capacity. It is the goal of this methodology paper to provide an overview of the characterization of soil spatial variability across multiple scales using ECa–directed soil sampling with a focus on the fi eld scale. Mobile ECa equipment, protocols, guidelines, special considerations, data reliability tests, and strengths and limitations are presented for characterizing spatial and temporal variation in soil properties using ECa–directed soil sampling.
Play recognition using spatio-temporal relationship of football tracking data

In professional football, every play data is recorded such as "Pass", "Dribble", etc. The play data is manually recorded, which requires huge effort. To reduce the human effort, we propose a method to recognize the labels of plays in football games from tracking data. By using features extracted from tracking data, we generate a play classifier model by Conditional Random Field (CRF). We evaluated the proposed method and the results indicate that our play recognition is effective for a part of play classes while it is still challenging for the others.
Association of cadmium but not arsenic levels in lung cancer tumor tissue with smoking, histopathological type and stage.

BACKGROUND To evaluate association of lung cancer with arsenic and cadmium levels measured in tumor tissue. MATERIALS AND METHODS Ninety-five patients with lung cancer tumor tissue obtained surgically were included in this study. Arsenic and cadmium levels were measured and levels of metals were compared among types of lung cancer and with reference to patient data. RESULTS The histopathologic diagnoses of the 95 cases were SCC, 49, adenocarcinoma, 28, large cell, 11 and SCLC, 1. Mean tumor arsenic and cadmium levels were 149.3±129. 1μg/kg and 276.3±219. 3μg/kg, respectively. Cadmium levels were significantly associated with smoking (p=0.02), histopathologic type (p=0.005), and TNM staging (r=0.325; p=0.001), although arsenic was not related to any parameter (p>0.05). There was no relation between metal levels and mortality (p>0.05). CONCLUSIONS We found a significant association between tumor cadmium levels of patients with lung cancer and smoking, histopathologic type and staging, although there was no relation with arsenic levels.
Seven Helix Chemoattractant Receptors Transiently Stimulate Mitogen-activated Protein Kinase in Dictyostelium

Mitogen-activated protein (MAP) kinases are involved in controlling a cell's responses to a variety of stimuli and can be activated by both protein tyrosine kinase and G protein-coupled receptors. It was shown previously that Dictyostelium MAP kinase ERK2 is required for normal activation of adenylyl cyclase and erk2 null cells are aggregation-deficient. In this manuscript, we show that the Dictyostelium MAP kinase ERK2 is rapidly and transiently activated in response to the chemoattractant cAMP. This response requires cAMP receptors, but is independent of the coupled Gα2 subunit and the only known Gβ subunit. These data indicate that ligand-mediated receptor activation of adenylyl cyclase requires two receptor-dependent pathways, one of which requires heterotrimeric G proteins, including Gα2 and the only known Gβ subunit, and the second of which requires ERK2. Our results suggest that ERK2 may be activated by a novel receptor-mediated pathway.
Distinguishing the Indistinguishable: Exploring Structural Ambiguities via Geodesic Context

A perennial problem in structure from motion (SfM) is visual ambiguity posed by repetitive structures. Recent disambiguating algorithms infer ambiguities mainly via explicit background context, thus face limitations in highly ambiguous scenes which are visually indistinguishable. Instead of analyzing local visual information, we propose a novel algorithm for SfM disambiguation that explores the global topology as encoded in photo collections. An important adaptation of this work is to approximate the available imagery using a manifold of viewpoints. We note that, while ambiguous images appear deceptively similar in appearance, they are actually located far apart on geodesics. We establish the manifold by adaptively identifying cameras with adjacent viewpoint, and detect ambiguities via a new measure, geodesic consistency. We demonstrate the accuracy and efficiency of the proposed approach on a range of complex ambiguity datasets, even including the challenging scenes without background conflicts.
Preparation of Size-Controlled TiO 2 Nanoparticles and Derivation of Optically Transparent Photocatalytic

TiO2 nanoparticles were prepared by hydrothermal reaction of titanium alkoxide stabilized in acidic ethanol/water solution. The sizes of particles have been controlled to the range of 7-25 nm by adjusting the concentration of Ti precursor and the composition of the solvent system. The TiO2 samples synthesized under this acidic ethanol/water environment were mainly primary particles in anatase phase without secondary structure. The suspension of as-prepared 7-nm-sized TiO2 nanoparticles demonstrates long-term stability, and has been applied successfully for the fabrication of ultra-transparent particulate TiO2 films. The photocatalytic efficiency of TiO2 films prepared from the 7-nm-sized nanoparticles was 1.6 times of that of films derived from Degussa P25 in decomposing gaseous 2-propanol.
Seed Sets and Search Structures for Accelerated Isocontouring

We present three algorithms for the construction of seed sets, a subset of a cell complex which contains at least one cell for each connected component of each isocontour, for all possible isovalues. Seed sets reduce the storage requirements of high performance search structures for isocontouring, such as the segment tree or the interval tree. The three algorithms determine seed sets with varying properties. The first computes seed sets within a constant factor of the optimal size, requiring O(nlogn) time, where n is the size of the mesh. A more conservative approach computes seed sets of slightly larger size with O(n) processing time, and is very amenable to parallel processing. The seeds produced follow a particular pattern which can be leveraged for performing out-of-core isocontouring, dynamically loading only the data which is necessary from secondary storage or a remote server. A specialized form of the second algorithm for regular grids computes seed sets of intermediate size, with only slightly additional effort and the same computational complexity. We examine the use of three search structures and compare their application to the seed sets and full sets of cells from a variety of computational grids.
Use of thermography for quantitative studies of spatial and temporal variation of stomatal conductance over leaf surfaces

This paper describes a new approach to the calibration of thermal infrared measurements of leaf temperature for the estimation of stomatal conductance and illustrates its application to thermal imaging of plant leaves. The approach is based on a simple reformulation of the leaf energy balance equation that makes use of temperature measurements on reference surfaces of known conductance to water vapour. The use of reference surfaces is an alternative to the accurate measurement of all components of the leaf energy balance and is of potentially wide application in studies of stomatal behaviour. The resolution of the technique when applied to thermal images is evaluated and some results of using the approach in the laboratory for the study of stomatal behaviour in leaves of Phaseolus vulgaris L. are presented. Conductances calculated from infrared measurements were well correlated with estimates obtained using a diffusion porometer.
Low-dropout regulators: Hybrid-cascode compensation to improve stability in nano-scale CMOS technologies

A modified circuit-level strategy to improve the speed/stability trade-off of low-dropout regulators is presented. The technique, called hybrid-cascode compensation, is applied to stabilize the regulation loop. When designed carefully, results prove the efficacy of this method in minimizing output settling time under various transient conditions. Equivalently, power consumption and/or die area can be minimized for the same settling time. Employing this technique, a 0.7V–10mA voltage regulator with a minimum line voltage of 1V has been designed in 90nm CMOS technology. With improved settling time, stability is guaranteed for load capacitors as low as 50pF. Power supply rejection is always better than −30dB for all frequencies.
Saddle connectors - an approach to visualizing the topological skeleton of complex 3D vector fields

One of the reasons that topological methods have a limited popularity for the visualization of complex 3D flow fields is the fact that such topological structures contain a number of separating stream surfaces. Since these stream surfaces tend to hide each other as well as other topological features, for complex 3D topologies the visualizations become cluttered and hardly interpretable. This paper proposes to use particular stream lines called saddle connectors instead of separating stream surfaces and to depict single surfaces only on user demand. We discuss properties and computational issues of saddle connectors and apply these methods to complex flow data. We show that the use of saddle connectors makes topological skeletons available as a valuable visualization tool even for topologically complex 3D flow data.
This is a repository copy of Evaluation of a Silent Speech Interface based on Magnetic Sensing and Deep Learning for a Phonetically Rich Vocabulary

To help people who have lost their voice following total laryngectomy, we present a speech restoration system that produces audible speech from articulator movement. The speech articulators are monitored by sensing changes in magnetic field caused by movements of small magnets attached to the lips and tongue. Then, articulator movement is mapped to a sequence of speech parameter vectors using a transformation learned from simultaneous recordings of speech and articulatory data. In this work, this transformation is performed using a type of recurrent neural network (RNN) with fixed latency, which is suitable for realtime processing. The system is evaluated on a phoneticallyrich database with simultaneous recordings of speech and articulatory data made by non-impaired subjects. Experimental results show that our RNN-based mapping obtains more accurate speech reconstructions (evaluated using objective quality metrics and a listening test) than articulatory-to-acoustic mappings using Gaussian mixture models (GMMs) or deep neural networks (DNNs). Moreover, our fixed-latency RNN architecture provides comparable performance to an utterance-level batch mapping using bidirectional RNNs (BiRNNs).