Miracle-dz/UniFAR-FTUs huggingface dataset:
Transcriptional activation upon pheromone stimulation mediated by a small domain of Saccharomyces cerevisiae Ste12p

In the yeast Saccharomyces cerevisiae, Ste12p induces transcription of pheromone-responsive genes by binding to a DNA sequence designated the pheromone response element. We generated a series of hybrid proteins of Ste12p with the DNA-binding and activation domains of the transcriptional activator Gal4p to define a pheromone induction domain of Ste12p sufficient to mediate pheromone-induced transcription by these hybrid proteins. A minimal pheromone induction domain, delineated as residues 301 to 335 of Ste12p, is dependent on the pheromone mitogen-activated protein (MAP) kinase pathway for induction activity. Mutation of the three serine and threonine residues within the minimal pheromone induction domain did not affect transcriptional induction, indicating that the activity of this domain is not directly regulated by MAP kinase phosphorylation. By contrast, mutation of the two tyrosines or their preceding acidic residues led to a high level of transcriptional activity in the absence of pheromone and consequently to the loss of pheromone induction. This constitutively high activity was not affected by mutations in the MAP kinase cascade, suggesting that the function of the pheromone induction domain is normally repressed in the absence of pheromone. By two-hybrid analysis, this minimal domain interacts with two negative regulators, Dig1p and Dig2p (also designated Rst1p and Rst2p), and the interaction is abolished by mutation of the tyrosines. The pheromone induction domain itself has weak and inducible transcriptional activity, and its ability to potentiate transcription depends on the activity of an adjacent activation domain. These results suggest that the pheromone induction domain of Ste12p mediates transcriptional induction via a two-step process: the relief of repression and synergistic transcriptional activation with another activation domain.
The Papain-Like Protease of Severe Acute Respiratory Syndrome Coronavirus Has Deubiquitinating Activity

ABSTRACT Replication of the genomic RNA of severe acute respiratory syndrome coronavirus (SARS-CoV) is mediated by replicase polyproteins that are processed by two viral proteases, papain-like protease (PLpro) and 3C-like protease (3CLpro). Previously, we showed that SARS-CoV PLpro processes the replicase polyprotein at three conserved cleavage sites. Here, we report the identification and characterization of a 316-amino-acid catalytic core domain of PLpro that can efficiently cleave replicase substrates in trans-cleavage assays and peptide substrates in fluorescent resonance energy transfer-based protease assays. We performed bioinformatics analysis on 16 papain-like protease domains from nine different coronaviruses and identified a putative catalytic triad (Cys1651-His1812-Asp1826) and zinc-binding site. Mutagenesis studies revealed that Asp1826 and the four cysteine residues involved in zinc binding are essential for SARS-CoV PLpro activity. Molecular modeling of SARS-CoV PLpro suggested that this catalytic core may also have deubiquitinating activity. We tested this hypothesis by measuring the deubiquitinating activity of PLpro by two independent assays. SARS CoV-PLpro hydrolyzed both diubiquitin and ubiquitin-7-amino-4-methylcoumarin (AMC) substrates, and hydrolysis of ubiquitin-AMC is approximately 180-fold more efficient than hydrolysis of a peptide substrate that mimics the PLpro replicase recognition sequence. To investigate the critical determinants recognized by PLpro, we performed site-directed mutagenesis on the P6 to P2′ residues at each of the three PLpro cleavage sites. We found that PLpro recognizes the consensus cleavage sequence LXGG, which is also the consensus sequence recognized by cellular deubiquitinating enzymes. This similarity in the substrate recognition sites should be considered during the development of SARS-CoV PLpro inhibitors.
Comparison of measurements of cardiac output by bioimpedance and thermodilution in severely ill surgical patients

In order to evaluate a new thoracic electrical bioimpedance (TEB) system for measurement of stroke volume based on the Sramek-Bernstein equation, 391 paired values of cardiac output were measured simultaneously with the standard thermodilution method. These values were obtained from 16 patients selected for having the most severe illness during a 6-month period; the intent was to evaluate the bioimpedance method in the worst possible situations. The correlation coefficient (r) was 0.83, slope was 0.87, intercept was 1.53, and the mean difference between the two methods was 16.2 ± 11.8 (SD)% in the total series. In 285 paired samples where satisfactory conditions were met, r was 0.90, slope was 0.98, intercept was 0.34, and the mean difference was 11.8 ± 8.9%. The data indicate satisfactory correlations between these two methods. When the TEB waveform is satisfactory, the agreement between TEB and thermodilution is as good as the agreement between serial thermodilution methods. Difficulties may arise with dysrhythmias, tachycardia (heart rate greater than 150 beat/min), metal in the chest or chest wall, sepsis, hypertension, and extremely oily skin. Mechanical ventilation did not appear to be a problem.
Host Cell Signaling and Trypanosoma cruzi Invasion: Do All Roads Lead to Lysosomes?

Trypanosoma cruzi, the protozoan parasite that causes Chagas’ disease in humans, is capable of invading and replicating within a wide variety of nucleated mammalian cell types. Host cell invasion by infective T. cruzi trypomastigotes is governed by parasite-triggered activation of host cell signaling pathways. Recent studies highlighting a role for host cell phosphatidylinositol 3-kinases (PI3Ks) in the T. cruzi invasion process have revealed surprising new insights into the mechanism of host cell invasion by this pathogen. In this Perspective, we discuss these findings and propose alternative models of T. cruzi invasion that incorporate this new information.
Xprobe2++: Low volume remote network information gathering tool

Active operating system fingerprinting is the process of actively determining a target network system's underlying operating system type and characteristics by probing the target system network stack with specifically crafted packets and analyzing received response. Identifying the underlying operating system of a network host is an important characteristic that can be used to complement network inventory processes, intrusion detection system discovery mechanisms, security network scanners, vulnerability analysis systems and other security tools that need to evaluate vulnerabilities on remote network systems.
Tangible Widgets for a Multiplayer Tablet Game in Comparison to Finger Touch

Tangible widgets are graspable physical objects that can be detected by a capacitive touch screen. These are used as an interaction method in the tablet game "Hover Wars", a 2-player competitive combat game. Hover Wars was designed to work mainly with tangible widgets and the affordances thereof in mind. A version using finger touch was also implemented and the controls were changed to work optimally with this interaction method. The two versions were compared to each other in a user study, revealing that players tend to prefer the usage of tangible widgets over finger touch. The study also uncovers some advantages and disadvantages of using tangible widgets as an interaction method.
Burn Rehabilitation and Research: Proceedings of a Consensus Summit

Burn rehabilitation is an essential component of successful patient care. In May 2008, a group of burn rehabilitation clinicians met to discuss the status and future needs of burn rehabilitation. Fifteen topic areas pertinent to clinical burn rehabilitation were addressed. Consensus positions and suggested future research directions regarding the physical aspects of burn rehabilitation are shared.
Influence of cAMP and Calcium on [3H]Inositol Efflux, Inositol Phosphate Accumulation, and Insulin Release From Isolated Rat Islets

The influence of cyclic AMP (cAMP) and extracellular calcium on phosphoinositide (PI) hydrolysis in isolated islets was assessed and related to insulin output. Three stimulants were chosen to activate the β-cell: sulfated cholecystokinin (CCK-8S, 200 nM), high-level glucose (20 mM), and the sulfonylurea tolbutamide (200 μM). The insulin secretory response to all three agonists was amplified by forskolin (which increases cAMP levels) and reduced by nitrendipine (which decreases calcium influx). All three stimulants increased the hydrolysis of inositol-containing phospholipids, an event monitored by an increase in [3H]inositol efflux from [3H]inositol-prelabeled islets and by the accumulation of labeled inositol phosphates. Forskolin, despite its positive impact on insulin secretion, reduced [3H]inositol efflux and inositol phosphate accumulation in response to all agonists. A similar inhibitory effect on these parameters was noted with nitrendipine; however, nitrendipine abolished secretion in response to all agonists. These findings support the following conclusions: 1) an increase in cellular cAMP levels reduces the quantitative impact of various agonists on these indices of PI hydrolysis; 2) despite this inhibitory effect, cAMP amplifies the insulin secretory response to these agonists; and 3) extracellular calcium is a crucial determinant of both PI hydrolysis and the ensuing insulin secretory response.
Ocean changes – warming, stratification, circulation, acidification, and deoxygenation

1. The world’s oceans have absorbed about 93% of the excess heat caused by greenhouse gas warming since the mid-20th century, making them warmer and altering global and regional climate feedbacks. Ocean heat content has increased at all depths since the 1960s and surface waters have warmed by about 1.3° ± 0.1°F (0.7° ± 0.08°C) per century globally since 1900 to 2016. Under a high emissions scenario, a global increase in average sea surface temperature of 4.9° ± 1.3°F (2.7° ± 0.7°C) by 2100 is projected, with even higher changes in some U.S. coastal regions. (Very high confidence) 2. The potential slowing of the Atlantic Meridional Overturning Circulation (AMOC) (of which the Gulf Stream is one component)—as a result of increasing ocean heat content and freshwater driven buoyancy changes—could have dramatic climate feedbacks as the ocean absorbs less heat and CO2 from the atmosphere. This slowing would also affect the climates of North America and Europe. Any slowing documented to date cannot be directly tied to anthropogenic forcing primarily due to lack of adequate observational data and to challenges in modeling ocean circulation changes. Under a high emissions scenario (RCP8.5) in CMIP5 simulations, it is likely that the AMOC will weaken over the 21st century by 12% to 54%. (Low confidence) 3. The world’s oceans are currently absorbing more than a quarter of the CO2 emitted to the atmosphere annually from human activities, making them more acidic (very high confidence), with potential detrimental impacts to marine ecosystems. In particular, higher-latitude systems typically have a lower buffering capacity against pH change, exhibiting seasonally corrosive conditions sooner than low-latitude systems. Acidification is regionally increasing along U.S. coastal systems as a result of upwelling (for example, in the Pacific Northwest) (high confidence), changes in freshwater inputs (for example, in the Gulf of Maine) (medium confidence), and nutrient input (for example, in urbanized estuaries) (high confidence). The rate of acidification is unparalleled in at least the past 66 million years (medium confidence). Under RCP8.5, the global average surface ocean acidity is projected to increase by 100% to 150% (high confidence). 4. Increasing sea surface temperatures, rising sea levels, and changing patterns of precipitation, winds, nutrients, and ocean circulation are contributing to overall declining oxygen concentrations at intermediate depths in various ocean locations and in many coastal areas. Over the last half century, major oxygen losses have occurred in inland seas, estuaries, and in the coastal and open ocean (high confidence). Ocean oxygen levels are projected to decrease by as much as 3.5% under the RCP8.5 scenario by 2100 relative to preindustrial values (high confidence). CSSR 5OD: FINAL CLEARANCE Chapter 13 Subject to Final Copyedit 28 June 2017 540 13. Ocean Acidification and Other Ocean Changes 1
Fine‐scale genetic structure and inferences on population biology in the threatened Mediterranean red coral, Corallium rubrum

Identifying microevolutionary processes acting in populations of marine species with larval dispersal is a challenging but crucial task because of its conservation implications. In this context, recent improvements in the study of spatial genetic structure (SGS) are particularly promising because they allow accurate insights into the demographic and evolutionary processes at stake. Using an exhaustive sampling and a combination of image processing and population genetics, we highlighted significant SGS between colonies of Corallium rubrum over an area of half a square metre, which sheds light on a number of aspects of its population biology. Based on this SGS, we found the mean dispersal range within sites to be between 22.6 and 32.1 cm, suggesting that the surveyed area approximately corresponded to a breeding unit. We then conducted a kinship analysis, which revealed a complex half‐sib family structure and allowed us to quantify the level of self‐recruitment and to characterize aspects of the mating system of this species. Furthermore, significant temporal variations in allele frequencies were observed, suggesting low genetic drift. These results have important conservation implications for the red coral and further our understanding of the microevolutionary processes acting within populations of sessile marine species with a larval phase.
DSS: Text Similarity Using Lexical Alignments of Form, Distributional Semantics and Grammatical Relations

In this paper we present our systems for the STS task. Our systems are all based on a simple process of identifying the components that correspond between two sentences. Currently we use words (that is word forms), lemmas, distributional similar words and grammatical relations identified with a dependency parser. We submitted three systems. All systems only use open class words. Our first system (alignheuristic) tries to obtain a mapping between every open class token using all the above sources of information. Our second system (wordsim) uses a different algorithm and unlike alignheuristic, it does not use the dependency information. The third system (average) simply takes the average of the scores for each item from the other two systems to take advantage of the merits of both systems. For this reason we only provide a brief description of that. The results are promising, with Pearson's coefficients on each individual dataset ranging from . 3765 to . 7761 for our relatively simple heuristics based systems that do not require training on different datasets. We provide some analysis of the results and also provide results for our data using Spearman's, which as a nonparametric measure which we argue is better able to reflect the merits of the different systems (average is ranked between the others).
Facial Expression Recognition using Image Processing and Neural Network

Face recognition is an important technique and has drawn the attention of many researchers due to its varying applications such as security systems, medical systems, entertainment. A face recognition system is one of the biometric information processing systems. The developed algorithm for the facial expression recognition system, which uses the two-dimensional discrete cosine transform(2D- DCT) for image compression and the self organizing map(SOM) neural network for recognition purpose, simulated in MATLAB. By using 2D-DCT we extract image vectors and these vectors become the input to neural network classifier, which uses self organizing map algorithm to recognize familiar faces (trained) and faces with variations in expression. In this paper we have developed and illustrated a recognition system for human faces using a novel self organizing map based retrieval system. SOM has good feature extracting property due to its topological ordering. The facial analytics result for the 25 images of AT &T database reflects that the face recognition rate using one the neural network algorithm SOM is 95.05% for 5 persons.
Scale-dependent reproduction of pen-and-ink illustrations

This paper describes a representation for pen-and-ink illustrations that allows the creation of high-ﬁdelity illustrations at any scale or resolution. We represent a pen-and-ink illustration as a low-resolution grey-scale image, augmented by a set of discontinuity segments, along with a stroke texture. To render an illustration at a particular scale, we ﬁrst rescale the grey-scale image to the desired size and then hatch the resulting image with pen-and-ink strokes. The main technical contribution of the paper is a new reconstruction al-gorithm that magniﬁes the low-resolution image while keeping the resulting image sharp along discontinuities. CR
Living on the edge of chaos: minimally nonlinear models of genetic regulatory dynamics

Linearized catalytic reaction equations (modelling, for example, the dynamics of genetic regulatory networks), under the constraint that expression levels, i.e. molecular concentrations of nucleic material, are positive, exhibit non-trivial dynamical properties, which depend on the average connectivity of the reaction network. In these systems, an inflation of the edge of chaos and multi-stability have been demonstrated to exist. The positivity constraint introduces a nonlinearity, which makes chaotic dynamics possible. Despite the simplicity of such minimally nonlinear systems, their basic properties allow us to understand the fundamental dynamical properties of complex biological reaction networks. We analyse the Lyapunov spectrum, determine the probability of finding stationary oscillating solutions, demonstrate the effect of the nonlinearity on the effective in- and out-degree of the active interaction network, and study how the frequency distributions of oscillatory modes of such a system depend on the average connectivity.
A method of detecting bearing's quality based on image edge morphologic analysis

In this paper, a method of detecting industrial bearing's quality based on image edge morphologic analysis and recognition technology was proposed. The image filter, enhancement and segmentation were adopted to pre-process the image and a novel image coding method based on relative direction coding was presented as well. Furthermore, an improved method based on image edge morphologic analysis was proposed, which can analyze the image edge with large quantities. Finally, a customized neural network classifier was utilized to sort images. The experimental results show that the approach to detecting bearing's quality is effective and practical.
Multiscale Data Assimilation and Prediction using Clustered 1 Particle Filters 2

6 Multiscale data assimilation uses a coarse-resolution forecast model to increase the number of samples in the estimation of large-scale and long time behavior of highdimensional complex systems along with noisy incomplete observations. A new class of multiscale particle filters, the multiscale clustered particle filter, is developed here as an effective multiscale data assimilation method for capturing non-Gaussian distributions and extreme events of high-dimensional turbulent systems using relatively few particles. The multiscale clustered particle combines the single-scale clustered particle filter with a general multiscale data assimilation framework that can handle mixed observations of both the resolved and unresolved scale components. To test the multiscale data assimilation method, we use a two-layer Lorenz system having 440 modes with important features of turbulent systems such as non-Gaussian statistics including fat-tails and intermittent extreme events. The effect of the observation model error is investigated and it is shown that the multiscale clustered particle filter captures non-Gaussian distributions using a small number of samples while an ensemble-based method fails to capture the correct distribution.
An implementation of complete, asynchronous, distributed garbage collection

Most existing reference-based distributed object systems include some kind of acyclic garbage collection, but fail to provide acceptable collection of cyclic garbage. Those that do provide such GC currently suffer from one or more problems: synchronous operation, the need for expensive global consensus or termination algorithms, susceptibility to communication problems, or an algorithm that does not scale. We present a simple, complete, fault-tolerant, asynchronous extension to the (acyclic) cleanup protocol of the SSP Chains system. This extension is scalable, consumes few resources, and could easily be adapted to work in other reference-based distributed object systems---rendering them usable for very large-scale applications.
Common-Description Learning: A Framework for Learning Algorithms and Generating Subproblems from Few Examples

Current learning algorithms face many difficulties in learning simple patterns and using them to learn more complex ones. They also require more examples than humans do to learn the same pattern, assuming no prior knowledge. In this paper, a new learning framework is introduced that is called common-description learning (CDL). This framework has been tested on 32 small multi-task datasets, and the results show that it was able to learn complex algorithms from a few number of examples. The final model is perfectly interpretable and its depth depends on the question. What is meant by depth here is that whenever needed, the model learns to break down the problem into simpler subproblems and solves them using previously learned models. Finally, we explain the capabilities of our framework in discovering complex relations in data and how it can help in improving language understanding in machines.
Differences in Dopamine Clearance and Diffusion in Rat Striatum and Nucleus Accumbens Following Systemic Cocaine Administration

Acute cocaine administration preferentially increases extracellular dopamine levels in nucleus accumbens as compared with striatum. To investigate whether a differential effect of cocaine on dopamine uptake could explain this observation, we used in vivo electrochemical recordings in anesthetized rats in conjunction with a paradigm that measures dopamine clearance and diffusion without the confounding effects of release. When a finite amount of dopamine was pressure‐ejected at 5‐min intervals from a micropipette adjacent to the electrode, transient and reproducible increases in dopamine levels were detected. In response to 15 mg/kg of cocaine‐HCl (i.p.), these signals increased in nucleus accumbens, indicating significant inhibition of the dopamine transporter. The time course of the dopamine signal increase paralleled that of behavioral changes in unanesthetized rats receiving the same dose of cocaine. In contrast, no change in the dopamine signal was detected in dorsal striatum; however, when the dose of cocaine was increased to 20 mg/kg, enhancement of the dopamine signal occurred in both brain areas. Quantitative auto‐radiography with [3H]mazindol revealed that the affinity of the dopamine transporter for cocaine was similar in both brain areas but that the density of [3H]mazindol binding sites in nucleus accumbens was 60% lower than in dorsal striatum. Tissue dopamine levels in nucleus accumbens were 44% lower. Our results suggest that a difference in dopamine uptake may explain the greater sensitivity of nucleus accumbens to cocaine as compared with dorsal striatum. Furthermore, this difference may be due to fewer dopamine transporter molecules in nucleus accumbens for cocaine to inhibit, rather than to a higher affinity of the transporter for cocaine.