Miracle-dz/UniFAR-FTUs huggingface dataset:
GAM/ZFp/ZNF512B is central to a gene sensor circuitry involving cell-cycle regulators, TGFβ effectors, Drosha and microRNAs with opposite oncogenic potentials

MicroRNAs (miRNAs) are small regulatory RNAs targeting multiple effectors of cell homeostasis and development, whose malfunctions are associated with major pathologies such as cancer. Herein we show that GAM/ZFp/ZNF512B works within an intricate gene regulatory network involving cell-cycle regulators, TGFβ effectors and oncogenic miRNAs of the miR-17-92 cluster. Thus, GAM impairs the transcriptional activation of the miR-17-92 promoter by c-Myc, downregulates miR-17-92 miRNAs differentially, and limits the activation of genes responsive to TGFβ canonical pathway. In contrast, TGFβ decreases GAM transcripts levels while differentially upregulating miR-17-92 miRNAs. In turn, miR-17, miR-20a and miR-92a-1 target GAM transcripts, thus establishing a feedback autoregulatory loop. GAM transcripts are also targeted by miRNAs of the let-7 family. GAM downregulates Drosha, the main effector of miRNA maturation in the nucleus, and interacts with it in a RNA-dependent manner. Finally, GAM modulates the levels of E2F1 and Ras, and increases apoptosis while reducing cell proliferation. We propose that GAM represents a new kind of vertebrate regulator aimed at balancing the opposite effects of regulators of cell homeostasis by increasing the robustness of gene circuitries controlling cell proliferation, differentiation and development.
Essential Roles of Cyclin Y-Like 1 and Cyclin Y in Dividing Wnt-Responsive Mammary Stem/Progenitor Cells

Cyclin Y family can enhance Wnt/β-catenin signaling in mitosis. Their physiological roles in mammalian development are yet unknown. Here we show that Cyclin Y-like 1 (Ccnyl1) and Cyclin Y (Ccny) have overlapping function and are crucial for mouse embryonic development and mammary stem/progenitor cell functions. Double knockout of Ccnys results in embryonic lethality at E16.5. In pubertal development, mammary terminal end buds robustly express Ccnyl1. Depletion of Ccnys leads to reduction of Lrp6 phosphorylation, hampering β-catenin activities and abolishing mammary stem/progenitor cell expansion in vitro. In lineage tracing experiments, Ccnys-deficient mammary cells lose their competitiveness and cease to contribute to mammary development. In transplantation assays, Ccnys-deficient mammary cells fail to reconstitute, whereas constitutively active β-catenin restores their regeneration abilities. Together, our results demonstrate the physiological significance of Ccnys-mediated mitotic Wnt signaling in embryonic development and mammary stem/progenitor cells, and reveal insights in the molecular mechanisms orchestrating cell cycle progression and maintenance of stem cell properties.
Anticonvulsant effect of Satureja hortensis aerial parts extracts in mice

Objective: Regarding the anticonvulsant effects of Satureja hortensis (S. hortensis) in Avicenna’s book: canon of medicine; the present study was undertaken to evaluate the anti- eplileptic effects of S. hortensis aqueous and ethanolic aerial part extracts. Furthermore, the mechanisms of their anticonvulsant activities were also evaluated. Materials and Methods: Seizure was induced by Pentylentetrazol (PTZ) and MES (maximal electroshock) models. Mice were randomly divided into 8 groups; negative control (normal saline, 10ml/Kg), positive control (diazepam, 2 mg/kg), S. hortensis aqueous and ethanolic extracts (200, 400 and 600 mg/kg). In PTZ test, latency to the first minimal clonic seizure (MCS), latency to the first generalized tonic–clonic seizures (GTCS), the total duration of seizures and protection against mortality were evaluated. In MES test, the stretching length of extremities and protection against mortality were recorded. Results: Aqueous and ethanolic extracts (400 and 600 mg/kg) significantly increased MCS and GTCS latencies in PTZ model. Three doses of the extracts decreased the total duration of seizure. These extracts did not show any protective effects on seizure induced by MES model. In PTZ model, flumazenil, an antagonist of benzodiazepine (BZD) site in the GABAA-BZD receptor complex and 7- nitroindazole (7- NI), a selective nNOS (neuronal nitric oxide synthase) inhibitor, reduced the prolongation of seizure latency. Conclusion: S. hortensis showed anticonvulsant activity in PTZ model and this effect may be mediated, at least partly, through interacting with nitric oxide and GABAA-BZD receptor complex.
How do emerging adults respond to exercise advice from parents? A test of advice response theory

Advice response theory (ART) proposes advisor characteristics, advice politeness, and advice content impact recipient perceptions of advice quality, their intention to implement the advice, and their coping. However, ART has primarily been examined in friend-to-friend advising on academic, romantic, or social issues. To test ART in an understudied relational and topical context, emerging adults (N = 196, aged 18–28 years) were surveyed about physical activity or exercise advice they received from a parent. Current findings supported propositions about advisor characteristics and politeness, and parent–child relational elements were particularly salient. Emerging adults satisfied with their parent–child relationship rated all advice features and outcomes more favorably, and participants who reported their parents conveyed that the participant was approved of, competent, and likeable rated all outcomes more favorably. Counter to ART predictions, emerging adults displayed psychological reactance to certain message content features, responding favorably to advice they perceived to propose an efficacious solution but reacting negatively to advice perceived to emphasize their capability of performing the action and the lack of drawbacks in doing so (especially when feelings of obligation were high). ART propositions about advisor characteristics and politeness may hold across advice situations, but the parent–child dynamic during emerging adulthood and inherent face threat for health influence attempts may explain why certain formulations of advice messages elicited responses inconsistent with ART.
DISSIPATION EFFICIENCY IN TURBULENT CONVECTIVE ZONES IN LOW-MASS STARS

We extend the analysis of Penev et al. to calculate effective viscosities for the surface convective zones of three main-sequence stars of 0.775 M☉, 0.85 M☉, and the present day Sun. In addition, we also pay careful attention to all normalization factors and assumptions in order to derive actual numerical prescriptions for the effective viscosity as a function of the period and direction of the external shear. Our results are applicable for periods that are too long to correspond to eddies that fall within the inertial subrange of Kolmogorov scaling, but no larger than the convective turnover time, when the assumptions of the calculation break down. We find moderately anisotropic viscosity, scaling linearly with the period of the external perturbation, with its components having magnitudes between three and ten times smaller than the Zahn's prescription.
Neural Agent Car-Following Models

This paper presents a car-following model that was developed using a neural network approach for mapping perceptions to actions. The model has a similar formulation to the desired spacing models that do not consider reaction time or attempt to explain the behavioral aspects of car following. The model's performance was evaluated based on field data and compared to a number of existing car-following models. The results showed that neural network models outperformed the Gipps and psychophysical family of car-following models. A qualitative drift behavior analysis also confirmed the findings. The model was validated at the microscopic and macroscopic levels, and the results showed very close agreement between field data and model outputs. Local and asymptotic stability analysis results also demonstrated the robustness of the model under mild and severe traffic disturbances
Automatic Recognition of Clauses

This paper describes an attempt to solve the problem of recognizing clauses and their mutual relationship in complex Czech sentences on the basis of limited information, namely the information obtained by morphological analysis only. The method described in this paper may be used in the future for splitting the parsing process into two phases, namely (1) Recognizing clauses and their mutual relationships; and (2) Parsing the individual clauses. This approach should be able to improve the result of parsing long complex sentences.
Reduction of Switching Noise in Digital CMOS Circuits by Pin Swapping of Library Cells 1

The objective of this paper is to explore the applicability of a very specific design technique at a gate-level to achieve a reduction of switching noise in conventional CMOS digital circuits. The proposed technique optimizes switching noise maintaining operation speed, power consumption and transistor count. Basically, we will show how the selection of the suited pin in a gate for implementing a logic function, can bring important advantages in terms of switching noise reduction. The characterization of some CMOS 0. 35μm library cell shows different behavior regarding switching noise depending on what transitions in which input pin takes place. This has been used as the basis for a noise optimization methodology, verified through some design examples showing the noise reduction produced by the use of the proposed technique.
Stochastic control over finite capacity channels: Causality and feedback

Optimal communication/control analysis and design of dynamical controlled systems, when there are finite capacity communication constraints often involve information and control theoretic analysis. This paper, employees information theoretic concepts, which are subject to causality, and thus applicable to control/communication system analysis and design in which encoders, decoders and controllers are causal. The basic mathematical concepts are constructive; they are based on a modified version of Shannon's self-mutual information, known as directed information, which describes how much information a random process conveys to another random process, to account for the causality of the probabilistic channel connecting these random processes, when feedback is used. Following this construction data processing inequalities are derived while the solution to the casual information rate distortion is obtained in which the optimal reconstruction kernel is causally dependent on the source and control. Further, in view of the complexity of the causal rate distortion function, a tight lower bound on the casual rate distortion function is derived which is easy to apply in many control/communication systems. Finally, using the information transmission theorem, the connection between stabilizabilty and observability of the control system is related to the causal rate distortion function and its lower bound.
The Sectorized Mobility Prediction Algorithm for Wireless Networks

One of the requirements for seamless mobility is efficient resource reservation and context transfer procedures during handoff. If context transfer and resource reservation can occur prior to handoff continuation of the same level of service as at the previous connection point is possible. Resource reservation is required to be non-aggressive for optimal use of limited bandwidth and a low call blocking probability. In this work we present a method of mobility prediction that can aid in achieving seamless mobility. In order to optimize the efficiency of a resource reservation algorithm we believe accurate prediction of the future movements of the user is required. The aims and contributions of this paper can be summarized as: - (a) Achieve accuracy in prediction with a considerable decrease in the total tracking area of the network and (b) a prediction algorithm that is efficient for both regular and random movements of users.
Observability Properties and Optimal Trajectories for On-line Odometry Self-Calibration

In this paper we derive theoretical results for the problem of on-line odometry self-calibration for a mobile robot. A first series of results regards the problem of understanding if a given system (consisting of a robot with several sensors) contains the necessary information to perform the on-line self calibration of the odometry. We consider several cases corresponding to different odometry systems and different types of robot sensors. Finally, we also consider the problem of maximizing the calibration accuracy and we formulate this problem as an optimal control problem. For the special case of a holonomic vehicle, we derive second order differential equations characterizing the solution, i.e. defining the best trajectory which maximizes the calibration accuracy
GHOSTX: An Improved Sequence Homology Search Algorithm Using a Query Suffix Array and a Database Suffix Array

DNA sequences are translated into protein coding sequences and then further assigned to protein families in metagenomic analyses, because of the need for sensitivity. However, huge amounts of sequence data create the problem that even general homology search analyses using BLASTX become difficult in terms of computational cost. We designed a new homology search algorithm that finds seed sequences based on the suffix arrays of a query and a database, and have implemented it as GHOSTX. GHOSTX achieved approximately 131–165 times acceleration over a BLASTX search at similar levels of sensitivity. GHOSTX is distributed under the BSD 2-clause license and is available for download at http://www.bi. cs.titech. ac.jp/ghostx/. Currently, sequencing technology continues to improve, and sequencers are increasingly producing larger and larger quantities of data. This explosion of sequence data makes computational analysis with contemporary tools more difficult. We offer this tool as a potential solution to this problem.
Cognition and Vascular Risk Factors: An Epidemiological Study

We conducted an epidemiological approach to identify the negative impact of the vascular risk factors (such as hypertension, diabetes and hypercholesterolemia) over cognition. The interesting aspect of this study was that the survey was conducted in all age groups through a voluntary call (n = 1365; ≥18 years old, both sexes; age 49 ± 15 y, female 75.7%). Thus, we demonstrated that the use of a Minimum Cognitive Examination (MCE), a brief, simple, and easy managed neuropsychological evaluation, detected a greater number of people with cognitive decline surpassing to the Minimal Mental Statement Examination alone (14.5% of the participants showed MMSE ≤24, 34,6% showed dys-executive function, and 45,8% memory impairment. Out of the 4 studied RF, the only one that was not related to cognitive impairment was dyslipemia. Finally, we noted the importance of cognitive state early detection in all age groups, even in the youngest group. Acting in the middle of the life stages, we can prevent or delay the onset of a disease in adults, nowadays incurable: dementia.
A Converse Lyapunov Theorem and Input-to-State Stability Properties for Discrete-Time Nonlinear Systems

In this work we study the input-to-state stability (iss) property for discrete-time nonlinear systems. We rst establish a converse Lyapunov theorem for robust global asymptotic stability in discrete-time. Then, it is shown that most iss results for continuous-time nonlinear systems in the current literature can be extended to the discrete-time case. Several equivalent characterizations of iss are introduced and two iss small-gain theorems are proved for nonlinear and interconnected discrete-time systems. ISS stabilizability is discussed and comparisons with the continuous-time case are made. As in the continuous time framework, where the notion iss found wide applications, we expect that this notion will provide a useful tool in areas related to stability and stabilization for nonlinear discrete time systems as well.
VCD: A network visualization tool based on community detection

In a complex network, communities are groups of nodes that are densely connected inside while sparsely connected to the outside. The study of such communities is crucial in exploring the structure of a network, especially when small communities form larger ones that in turn group together to build even larger ones, resulting in a hierarchy. Besides, fence-sitting nodes, nodes shared among different communities, are common in real networks. Although a large amount of network visualization tools are available, few could visualize the hierarchical community structure and fence-sitting nodes. Thus, we proposed visualization methods and accordingly developed a network visualization tool to dynamically uncover the hierarchical community structure and reveal fence-sitting nodes. Tests on a yeast network yielded satisfying results.
Prediction of user ’ s intention based on the eye-hand coordination

The action to grasp an object by a human hand comprises not only an eye-hand coordination, but also a motion process that controls and plans the movement for grasping objects. To understand this behavior, it is necessary to study eye and hand movements simultaneously. A novel approach to understand the user’s intentions with computer vision technics is proposed in this paper. Our solution performs a fusion between the user’s gaze and a hand motion estimation using wearable systems and multiples cameras. To realize such system, we employ multiples cameras on the user’s head, beneath the wrist, and a eye-tracker device. To predict the user’s movement, we use information from multiples point-of-view and we characterize a handmovement trough a Hidden-Markov Model framework. As main result, our system can predict the movement before the hand can reach an
A general method for isolation of high molecular weight DNA from eukaryotes.

A new method for isolation of high molecular weight DNA from eukaryotes is presented. This procedure allows preparation of DNA from a variety of tissues such as calf thymus or human placenta and from cells which were more difficult to lyse until now (e.g. Crypthecodinium cuhnii, a dinoflagellate). The DNA obtained in such a way has an average molecular weight of about 200 X 10(6) d and contains very few, if any, single strand breaks.
Exploring animacy as a mnemonic dimension

VanArsdall, Joshua Edward. Ph.D., Purdue University, August 2016. Exploring Animacy as a Mnemonic Dimension. Major Professor: James S. Nairne. There is a great deal of evidence across cognitive science that animacy, or more generally, the features that make up what it means to be a living thing, is a foundational dimension of human cognition. In perception, animates both capture attention (Pratt, Radulescu, Guo, & Abrams, 2010) and are relatively immune to change blindness (New, Cosmides, & Tooby, 2007). Developmental work places the animate-inanimate distinction as one of the first categories children learn (Opfer & Gelman, 2011). Work in neuroscience points toward a fundamental role for animacy in semantic memory (Caramazza & Mahon, 2003), and linguists have identified animacy as a “linguistic universal” (Comrie, 1989). Despite seemingly overwhelming evidence for the fundamental role animacy plays in human cognition, little effort has been made to understand the role of animacy in episodic memory. In three studies, the role of animacy as a dimension of word meaning was investigated. The collection of normative data for 1200 words on six scales believed to relate to the animacy construct in Study 1 set the stage for Studies 2 and 3, which explored the makeup of the animacy dimension and how it relates to other word dimensions (Study 2), and then how both animacy and other word dimensions predict
Gamma-Ray Constraints on Neutralino Dark Matter Clumps in the Galactic Halo

According to high-resolution cold dark matter (CDM) simulations, large virialized halos are formed through the constant merging of smaller halos formed at earlier times. In particular, the halo of our Galaxy may have hundreds of dark matter clumps. The annihilation of dark matter particles such as the neutralino in these clumps generates gamma-ray fluxes that can potentially be detected by future experiments such as GLAST. We find that, depending on the parameters of the clump density profile and on the distribution of clumps in the Galactic halo, the contribution to the diffuse gamma-ray background from clumps can constrain the properties of neutralinos such as the mass and annihilation cross section. We model the density profile of clumps by three representative dark matter profiles, singular isothermal spheres (SISs), Moore profiles, and Navarro, Frenk, and White (NFW) density profiles, and calculate the spectrum and angular distribution in the sky of the gamma-ray flux due to neutralino annihilation in the clumpy halo of the Galaxy. The calculations are carried out in the context of two different scenarios for the distribution of clumps in the Galaxy and their concentrations, which result in very different conclusions.
A novel heterogeneous nuclear RNP protein with a unique distribution on nascent transcripts

Immediately after the initiation of transcription in eukaryotes, nascent RNA polymerase II transcripts are bound by nuclear proteins resulting in the formation of heterogeneous nuclear ribonucleoprotein (hnRNP) complexes. hnRNP complexes from HeLa cell nuclei contain greater than 20 major proteins in the molecular mass range of 34,000- 120,000 D. Among these are the previously described A, B, and C groups of proteins (34,000-43,000 D) and several larger, and as yet uncharacterized, proteins. Here we describe the isolation and characterization of a novel hnRNP protein termed the L protein (64-68 kD by mobility in SDS-polyacrylamide gels). Although L is a bona fide component of hnRNP complexes, it also appears to be a different type of hnRNP protein from those previously characterized. A considerable amount of L is found outside hnRNP complexes, and monoclonal antibodies to the L protein also strongly stain unidentified discrete nonnucleolar structures, in addition to nucleoplasm, in HeLa cell nuclei. Interestingly, the same antibodies stain the majority of nonnucleolar nascent transcripts from the loops of lampbrush chromosomes in the newt, but the most intense staining is localized to the landmark giant loops. The L protein is the first protein of giant loops identified so far, and antibodies to it thus provide a useful tool with which to study these unique RNAs. In addition, isolation and sequencing of cDNA clones for the L protein from human cells predicts a glycine- and proline-rich protein of 60,187 D, which contains two 80 amino acid segments only distantly related to the RNP consensus sequence-type RNA- binding domain. The L protein, therefore, is a new type of hnRNP protein.
Joint Detection and Decoding in the Presence of Prior Information With Uncertainty

An optimal decision framework is proposed for joint detection and decoding when the prior information is available with some uncertainty. The proposed framework provides tradeoffs between the average inclusive error probability (computed using estimated prior probabilities) and the worst case inclusive error probability according to the amount of uncertainty while satisfying constraints on the probability of false alarm and the maximum probability of miss-detection. Theoretical results that characterize the structure of the optimal decision rule according to the proposed criterion are obtained. The proposed decision rule reduces to some well-known detectors in the case of perfect prior information or when the constraints on the probabilities of miss-detection and false alarm are relaxed. Numerical examples are provided to illustrate the theoretical results.