Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatially-constrained growth enhances conversional meltdown

Cells that mutate or commit to a specialized function (differentiate) often undergo conversions that are effectively irreversible. Slowed growth of converted cells can act as a form of selection, balancing unidirectional conversion to maintain both cell types at a steady-state ratio. However, when one-way conversion is insuffciently counterbalanced by selection, the original cell type will ultimately be lost, often with negative impacts on the population’s overall ftness. The critical balance between selection and conversion needed for preservation of unconverted cells and the steady-state ratio between cell types depends on the spatial circumstances under which cells proliferate. We present experimental data on a yeast strain engineered to undergo irreversible conversion: this synthetic system permits cell type-specifc fuorescent labeling and exogenous variation of the relative growth and conversion rates. We fnd that populations confned to grow on a fat agar surface are more susceptible than their well-mixed counterparts to ftness loss via a conversion-induced “meltdown. ” We then present analytical predictions for growth in several biologically-relevant geometries – well-mixed liquid media, radially-expanding two-dimensional colonies, and linear fronts in two dimensions – by employing analogies to the directed percolation transition from non-equilibrium statistical physics. These simplifed theories are consistent with the experimental results.
Measuring differences between faces

This paper presents a novel approach for extracting characteristic parts of a face. Rather than finding a priori specified features such as nose, eyes, mouth or others, the proposed approach is aimed at extracting from a face the most distinguishing or dissimilar parts with respect to another given face, i.e. at “finding differences” between faces. This is accomplished by feeding a binary classifier by a set of image patches, randomly sampled from the two face images, and scoring the patches (or features) by their mutual distances. In order to deal with the multi-scale nature of natural facial features, a local space-variant sampling has been adopted.
Comparison of endoscopic ultrasound-guided fine-needle aspiration by capillary action, suction, and no suction methods: a randomized blinded study

Abstract Background and study aim Different types of endoscopic ultrasound (EUS)-guided fine-needle aspiration (FNA) techniques are used in clinical practice; the best method in terms of outcome has not been determined. The aim of the study was to compare the diagnostic adequacy of aspirated material, and the cytopathological and EUS morphological features between capillary action, suction, and no-suction FNA methods. Patients and methods This was a prospective, single-blinded, randomized study conducted at a tertiary care hospital. Patients were randomized to the three groups: capillary action, suction, and no suction. A total of 300 patients were included, with 100 patients in each arm. Results A total of 300 patients (195 males) underwent EUS-FNA of 235 lymph nodes and 65 pancreatic masses (distribution not statistically different between the groups). The mean age was 52 ± 14 years. A 22 gauge needle was used in the majority (93 %) of procedures. There was no statistical difference between the three groups regarding lymph node size at the largest axis and ratio, type of needle, echo features, echogenicity, calcification, necrosis, shape, borders (lymph nodes), number of passes, and cellularity. Diagnostic adequacy of the specimen was 91 %, 91 %, and 94 % in the capillary, suction, and no suction groups, respectively (P = 0.67). Significantly more slides and blood clots were generated by the suction method compared with the other methods. Conclusion The capillary action, suction, and no suction methods of EUS-FNA are similar in terms of diagnostic adequacy of the specimen. The suction method has the disadvantages of causing more bleeding and generating more slides.
A Novel Network Coding Multi-User Coordinated Multipoint Downlink Transmission Scheme

A novel network coding based coordinated multi- point (NC-CoMP) process, which allows one of the cooperative base stations (BSs) to serve one more non-cell-edge UE simultaneously in its own cell, is proposed in this paper. To implement the NC-CoMP transmission, an alignment combined precoding(ACP) algorithm is designed to eliminate the inter-user interference and simultaneously to extract useful signal from the network coded signals. Two algorithms are presented to optimize the precoding vectors with the aim at maximizing the receive signal-to-noise rate(SNR) of the cell-edge users. Compared with the conventional two UE multi-user coherent joint processing CoMP (CJP-CoMP) scheme, the proposed NC-CoMP scheme can increase the date throughput significantly without requiring any extra resources. Simulations also illustrate that the bit error rate (BER) performance of the cell-edge users can be improved significantly when the NC-CoMP scheme is employed.
Variational problems in machine learning and their solution with finite elements

Many machine learning problems deal with the estimation of conditional probabilities $p(y \mid x)$ from data $(x_1,y_i),\ldots,(x_n,y_n)$. This includes classification, regression and density estimation. Given a prior for $p(y \mid x)$ the maximum a-posteriori method estimates $p(y \mid x)$ as the most likely probability given the data. This principle can be formulated rigorously using the Cameron-Martin theory of stochastic processes and allows a variational characterisation of the estimator. The resulting nonlinear Galerkin equations are solved numerically. Convexity and total positivity lead to existence, uniqueness and error bounds. For machine learning problems dealing with large numbers of features we suggest to use sparse grid approximations.
Efficient and Effective Classroom Phonological Awareness Practices to Improve Reading Achievement

International studies of reading achievement demonstrate that significant inequalities in reading outcomes continue to exist among some of the world’s wealthiest countries, despite strong investment in initiatives directed towards raising literacy achievement for all children (United Nations Educational, Scientific and Cultural Organisation—UNESCO, 2009; United Nations Children’s Fund—UNICEF, 2010). One approach towards the elevation of reading achievement is to investigate how key predictors of reading success are incorporated into everyday classroom literacy practices. Phonological awareness (PA) is widely recognised as a powerful predictor and underlying precursor to early reading success for both typically developing and at-risk readers (Al Otaiba, Kosanovich, & Torgesen, 2012; Blachman, Ball, Black, & Tangel, 2000; Goswami, 2001; Pressley, 2006). A majority of research demonstrating the benefits of PA to literacy growth has been conducted under controlled research settings outside of the classroom environment (Ehri, Nunes, Willows, Schuster, Yaghoub-Zadeh, & Shanahan, 2001; Gillon, 2000a, 2005; Gillon & McNeill, 2009), and thus less is known about whether such benefits hold true when integrated into the heterogeneous classroom setting. For this reason, four experiments reported in this thesis investigated whether PA can be efficiently and effectively integrated into the classroom literacy programme with the overarching aim of raising reading achievement and equalising reading outcomes for the majority of children in the first year of formal education. In the first experiment (reported in Chapter 3), time-efficiency and congruency of scores between a computer-based PA screening and monitoring tool (described in Chapter 2) and a paper-based equivalent were examined. Thirty-three children aged between four years 10 months and five years zero months participated in the study, 12 of
Assessment of a multi-sensor approach for noise removal on Landsat-8 OLI time series using CBERS-4 MUX data to improve crop classification based on phenological features

In this work we investigated a method for noise removal on Landsat-8 OLI time series using CBERS-4 MUX data to improve crop classiï¬ cation. An algorithm was built to look to the nearest MUX image for each Landsat image, based on an user deï¬ ned time span. The algorithm checks for cloud contaminated pixels on the Landsat time series using Fmask and replaces the contaminated pixels to build the integrated time series (Landsat-8 OLI + CBERS-4 MUX). Phenological features were extracted from the time series samples for each method (EVI and NDVI original time series and multi sensor time series, with and without ï¬ ltering) and subjected to data mining using Random Forest classiï¬ cation. In general, we observed a slight increase in the classiï¬ cation accuracy when using the proposed method. The best result was observed with the EVI integrated ï¬ ltered time series (78%), followed by the ï¬ ltered Landsat EVI time series (76%).
Choosing landmarks for risky planning

This work examines the effect of landmark placement on the efficiency and accuracy of risk-bounded searches over probabilistic costmaps for mobile robot path planning. In previous work, risk-bounded searches were shown to offer in excess of 70% efficiency increases over normal heuristic search methods. The technique relies on precomputing distance estimates to landmarks which are then used to produce probability distributions over exact heuristics for use in heuristic searches such as A* and D*. The location and number of these landmarks therefore influence greatly the efficiency of the search and the quality of the risk bounds. Here four new methods of selecting landmarks for risk based search are evaluated. Results are shown which demonstrate that landmark selection needs to take into account the centrality of the landmark, and that diminishing rewards are obtained from using large numbers of landmarks.
Chondroitin Sulfate as a Molecular Portal That Preferentially Mediates the Apoptotic Killing of Tumor Cells by Penetratin-directed Mitochondria-disrupting Peptides*

The use of cell-penetrating peptides (CPPs) as drug carriers for targeted therapy is limited by the unrestricted cellular translocation of CPPs. The preferential induction of tumor cell death by penetratin (Antp)-directed peptides (PNC27 and PNC28), however, suggests that the CPP Antp may contribute to the preferential cytotoxicity of these peptides. Using PNC27 as a molecular model, we constructed three novel peptides (PT, PR9, and PD3) by replacing the leader peptide Antp with one of three distinct CPPs (TAT, R9, or DPV3), respectively. The IC50 values of PNC27 in tumor cells were 2–3 times lower than in normal cells. However, all three engineered peptides demonstrated similar cytotoxic effects in tumor and normal cells. Another three chimeric peptides containing the leader peptide Antp with different mitochondria-disrupting peptides (KLA-Antp (KGA), B27-Antp (BA27), and B28-Antp (BA28)), preferentially induced apoptosis in tumor cells. The IC50 values of these peptides (3–10 μm) were 3–6 times lower in tumor cells than in normal cells. In contrast, TAT-directed peptides (TAT-KLA (TK), TAT-B27 (TB27), and TAT-B28 (TB28)), were cytotoxic to both tumor and normal cells. These data demonstrate that the leader peptide Antp contributes to the preferential cytotoxicity of Antp-directed peptides. Furthermore, Antp-directed peptides bind chondroitin sulfate (CS), and the removal of endogenous CS reduces the cytotoxic effects of Antp-directed peptides in tumor cells. The overexpression of CS in tumor cells is positively correlated to the cell entry and cytotoxicity of Antp- directed peptides. These results suggest that CS overexpression in tumor cells is an important molecular portal that mediates the preferential cytotoxicity of Antp-directed peptides.
Cloning of the Alcaligenes eutrophus genes for synthesis of poly-beta-hydroxybutyric acid (PHB) and synthesis of PHB in Escherichia coli

Eight mutants of Alcaligenes eutrophus defective in the intracellular accumulation of poly-beta-hydroxybutyric acid (PHB) were isolated after transposon Tn5 mutagenesis with the suicide vector pSUP5011. EcoRI fragments which harbor Tn5-mob were isolated from pHC79 cosmid gene banks. One of them, PPT1, was used as a probe to detect the intact 12.5-kilobase-pair EcoRI fragment PP1 in a lambda L47 gene bank of A. eutrophus genomic DNA. In six of these mutants (PSI, API, GPI, GPIV, GPV, and GPVI) the insertion of Tn5-mob was physically mapped within a region of approximately 1.2 kilobase pairs in PP1; in mutant API, cointegration of vector DNA has occurred. In two other mutants (GPII and GPIII), most probably only the insertion element had inserted into PP1. All PHB-negative mutants were completely impaired in the formation of active PHB synthase, which was measured by a radiometric assay. In addition, activities of beta-ketothiolase and of NADPH-dependent acetoacetyl coenzyme A (acetoacetyl-CoA) reductase were diminished, whereas the activity of NADPH-dependent acetoacetyl-CoA reductase was unaffected. In all PHB-negative mutants the ability to accumulate PHB was restored upon complementation in trans with PP1. The PHB-synthetic pathway of A. eutrophus was heterologously expressed in Escherichia coli. Recombinant strains of E. coli JM83 and K-12, which harbor pUC9-1::PP1, pSUP202::PP1, or pVK101::PP1, accumulated PHB up to 30% of the cellular dry weight. Crude extracts of these cells had significant activities of the enzymes PHB synthase, beta-ketothiolase, and NADPH-dependent acetoacetyl-CoA reductase. Therefore, PP1 most probably encodes all three genes of the PHB-synthetic pathway in A. eutrophus. In addition to PHB-negative mutants, we isolated mutants which accumulate PHB at a much lower rate than the wild type does. These PHB-leaky mutants exhibited activities of all three PHB-synthetic enzymes; Tn5-mob had not inserted into PP1, and the phenotype of the wild type could not be restored with fragment PP1. The rationale for this mutant type remains unknown.
Wildlife disease elimination and density dependence

Disease control by managers is a crucial response to emerging wildlife epidemics, yet the means of control may be limited by the method of disease transmission. In particular, it is widely held that population reduction, while effective for controlling diseases that are subject to density-dependent (DD) transmission, is ineffective for controlling diseases that are subject to frequency-dependent (FD) transmission. We investigate control for horizontally transmitted diseases with FD transmission where the control is via culling or harvest that is non-selective with respect to infection and the population can compensate through DD recruitment or survival. Using a mathematical model, we show that culling or harvesting can eradicate the disease, even when transmission dynamics are FD. Eradication can be achieved under FD transmission when DD birth or recruitment induces compensatory growth of new, healthy individuals, which has the net effect of reducing disease prevalence by dilution. We also show that if harvest is used simultaneously with vaccination, and there is high enough transmission coefficient, application of both controls may be less efficient than vaccination alone. We illustrate the effects of these control approaches on disease prevalence for chronic wasting disease in deer where the disease is transmitted directly among deer and through the environment.
Shunt active power filter using Hysteresis and PI control for improving the power quality using MATLAB

The paper explains Hysteresis controller and Proportional Integral control of three phase Shunt Active Power Filter to improve the Power Quality of non-linear loads. The Hysteresis used to control Current. Proportional and Integral Control for reducing voltage harmonics. Gating pulses for the Shunt Active Filter is generated using Hysteresis current controller based Pulse width modulation technique. The Total Harmonic Distortion of Nonlinear load has decreased from 21.32% to 5.95%. The proposed model is simulated in MATLAB / SIMULINK.
Graphene-based charge sensors

We discuss graphene nanoribbon-based charge sensors and focus on their functionality in the presence of external magnetic fields and high frequency pulses applied to a nearby gate electrode. The charge detectors work well with in-plane magnetic fields of up to 7 T and pulse frequencies of up to 20 MHz. By analyzing the step height in the charge detector’s current at individual charging events in a nearby quantum dot, we determine the ideal operation conditions with respect to the applied charge detector bias. Average charge sensitivities of 1.3 × 10−3e Hz−1/2 can be achieved. Additionally, we investigate the back action of the charge detector current on the quantum transport through a nearby quantum dot. By varying the charge detector bias from 0 to 4.5 mV, we can increase the Coulomb peak currents measured at the quantum dot by a factor of around 400. Furthermore, we can completely lift the Coulomb blockade in the quantum dot.
Selective Enhancement of Synaptic Inhibition by Hypocretin (Orexin) in Rat Vagal Motor Neurons: Implications for Autonomic Regulation

The hypocretins (orexins) are hypothalamic neuropeptides implicated in feeding, arousal, and autonomic regulation. These studies were designed to determine the actions of hypocretin peptides on synaptic transmission in the dorsal motor nucleus of the vagus nerve (DMV). Whole-cell patch-clamp recordings were made from DMV neurons in transverse slices of rat brainstem. Some of the neurons were identified as gastric-related by retrograde labeling after inoculation of the stomach wall with pseudorabies virus 152, a viral label that reports enhanced green fluorescent protein. Consistent with previous findings, hypocretins caused an inward current (6–68 pA) in most neurons at holding potentials near rest. In addition, the frequency of spontaneous IPSCs was increased in a concentration-related manner (up to 477%), with little change in EPSCs. This effect was preserved in the presence of tetrodotoxin, suggesting a presynaptic site of action. Hypocretins increased the amplitude of IPSCs evoked by electrical stimulation of the nucleus tractus solitarius (NTS) but not evoked EPSCs. Hypocretin-induced increases in the frequency of IPSCs evoked by photoactivation of caged glutamate within the NTS were also observed. Identical effects of the peptides were observed in identified gastric-related and unlabeled DMV neurons. In contrast to some previous studies, which have reported primarily excitatory actions of the hypocretins in many regions of the CNS, these data support a role for hypocretin in preferentially enhancing synaptic inhibition, including inhibitory inputs arising from neurons in the NTS. These findings indicate that the hypocretins can modulate and coordinate visceral autonomic output by acting directly on central vagal circuits.
PREFRONTAL CONTROL OF PREPARATORY ATTENTION AND COORDINATION WITH THE VENTRAL TEGMENTAL AREA

Preparatory attention selects upcoming stimuli that will be used to guide behavior. This cognitive faculty is controlled by the prefrontal cortex (PFC), which primes sensory cortex neurons that represent the stimulus. Lesion studies have implicated multiple PFC regions in the control of attention, including the rat prelimbic cortex (PL) and anterior cingulate cortex (ACC). The first aim of this dissertation was to characterize and compare neural activity in these regions during a preparatory attention task. The second aim was to assess interactions between these regions during preparatory attention. Coordinated activity between the PL and ACC was studied by measuring spike synchrony with local field potential (LFP) oscillations. The third aim was to study neural activity in the ventral tegmental area (VTA), which provides dopamine projections to the PFC that are known to modulate PFC control of attention. The nature of VTA neural activity during attention and its coordination with the PFC has not been characterized. In order to study PFC and VTA neural activity during preparatory attention, we recorded single unit spiking and LFP and primarily focused analysis on the pre-stimulus period, when a preparatory attention control signal is generated by PFC neurons. The rat was trained to orient to a wall of three stimulus ports, expect a brief illumination at one of the ports, and make a response into the illuminated port. While the timing of stimulus onset was predictable, the location varied randomly. These task characteristics resulted in error trials in which the rat responded to an incorrect port. The analyses of pre-stimulus neural activity compared correct and error trials. We observed a sustained change in PFC single unit firing rate during the pre-stimulus period. The sustained firing patterns were predictive of attentional accuracy, in that the sustained activity was reduced during error trials. Furthermore, we demonstrated that the PL and ACC interacted during preparatory attention. We also observed sustained activity in the VTA, which may stabilize sustained PFC activity during preparatory attention. VTA spiking correlated with ACC gamma (40 Hz) oscillations, which may be used to communicate the attention control signal from the PFC to sensory cortex.
Mining Evolving Web Clickstreams with Explicit Retrieval Similarity Measures

Data on the Web is noisy, huge, and dynamic. This poses enormous challenges to most data mining techniques that try to extract patterns from this data. While scalable data mining methods are expected to cope with the size challenge, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary stoppages and reconfigurations is still an open challenge. This dynamic and single pass setting can be cast within the framework of mining evolving data streams. The harsh restrictions imposed by the “you only get to see it once” constraint on stream data calls for different computational models that may bring some interesting surprises when it comes to the behavior of some well known similarity measures during clustering. In this paper, we explore the task of mining evolving clusters in a single pass with a new scalable immune based clustering approach (TECNO-STREAMS), and study the effect of the choice of different similarity measures on the mining process and on the interpretation of the mined patterns. We propose a simple similarity measure that has the advantage of explicitely coupling the precision and coverage criteria to the early learning stages, and furthermore requiring that the affinity of the data to the learned profiles or summaries be defined by the minimum of their coverage or precision, hence requiring that the learned profiles are simultaneously precise and complete, with no compromises. In our simulations, we study the task of mining evolving user profiles from Web clickstream data (web usage mining) in a single pass, and under different trend sequencing scenarios.
Implementing Layered Designs with Mixin Layers 1

Mixin layers are a technique for implementing layered object-oriented designs (e.g., collaboration-based designs). Mixin layers are similar to abstract subclasses (mixin classes) but scaled to a multiple-class granularity. We describe mixin layers from a programming language viewpoint, discuss checking the consistency of a mixin layer composition, and analyze the language support issues involved.