Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic networks controlled by the bacterial replication initiator and transcription factor DnaA in Bacillus subtilis

DnaA is the widely conserved bacterial AAA+ ATPase that functions as both the replication initiator and a transcription factor. In many organisms, DnaA controls expression of its own gene and likely several others during growth and in response to replication stress. To evaluate the effects of DnaA on gene expression, separate from its role in replication initiation, we analyzed changes in mRNA levels in Bacillus subtilis cells with and without dnaA, using engineered strains in which dnaA is not essential. We found that dnaA was required for many of the changes in gene expression in response to replication stress. We also found that dnaA indirectly affected expression of several regulons during growth, including those controlled by the transcription factors Spo0A, AbrB, PhoP, SinR, RemA, Rok and YvrH. These effects were largely mediated by the effects of DnaA on expression of sda. DnaA activates transcription of sda, and Sda inhibits histidine protein kinases required for activation of the transcription factor Spo0A. We also found that loss of dnaA caused a decrease in the development of genetic competence. Together, our results indicate that DnaA plays an important role in modulating cell physiology, separate from its role in replication initiation.
High-resolution Clinoform Characterization By 2-D Model-driven Seismic Bayesian Inversion

Summary Many important details of potential subsurface reservoirs that we wish to characterize are only indirectly present in the reflected wavefields measured at the Earth’s surface. Therefore, the analysis of seismic data always presents an inversion problem. Instead of analyzing the data trace by trace, we propose an automated procedure that adjusts the parameters of a two-dimensional geological model by minimizing the mismatch between the simulated and measured seismic. This approach differs from standard inversion problems in that the size of the required details of the 2D geological reservoir model is far below the limits of the seismic resolution.
The Intracellular Localization of ID2 Expression Has a Predictive Value in Non Small Cell Lung Cancer

Background ID2 is a member of a subclass of transcription regulators belonging to the general bHLH (basic-helix-loop-helix) family of transcription factors. In normal cells, ID2 is responsible for regulating the balance between proliferation and differentiation. More recent studies have demonstrated that ID2 is involved in tumor progression in several cancer types such as prostate or breast. Methodology/Principal Findings In this work, we investigated, for the first time, the relationship between the expression of ID2 in non-small cell lung cancer (NSCLC) patients and the clinicopathological features and prognosis of these patients. Immunohistochemistry was performed on tissue microarrays, which included 62 NSCLC tumors. In malignant tissues, ID2 expression has been detected in both the nuclear and cytoplasmic compartments, but we have demonstrated that only nuclear expression of ID2 is inversely correlated with the differentiation grade of the tumor (p = 0.007). Interestingly, among patients with poorly differentiated tumors, high nuclear expression of ID2 was an independent and unfavorable prognostic factor for survival (p = 0.036). Conclusions These results suggest that ID2 could be involved in tumor dedifferentiation processes of NSCLC, and could be used as prognostic marker for patients with poorly differentiated tumors.
Learning from the environment based on percepts and actions

This thesis is a study of "learning from the environment. " As machine learning moves from toy environments towards the real world, the problem of learning autonomously from environments whose structure is not completely defined a priori becomes ever more critical. Three of the major challenges are: (1) how to integrate various high level AI techniques such as exploration, problem solving, learning, and experimentation with low level perceptions and actions so that learning can be accomplished through interactions with the environment; (2) how to acquire new knowledge of the environment and to learn from mistakes autonomously, permitting incorrect information to be identified and corrected; (3) how to create features in such a way that knowledge acquisition is not limited by the initial concept description language provided by the designers of a system. The thesis defines learning from the environment as inferring the laws of the environment that enable the learner to solve problems. The inputs to the learning are goals to be achieved, percepts and actions sensed and effected by the learner, and constructors for organizing the percepts and the actions. The output is a set of prediction rules that correlate actions and percepts for achieving the given goals. The thesis develops a framework called scLIVE that unifies problem solving with rule induction. It creates rules by noticing the changes in the environment when actions are taken during exploration. It uses a new learning method called complementary discrimination to learn both disjunctive and conjunctive rules incrementally and unbiasedly from feedback and experiments. Furthermore, it constructs "new terms" to describe newly discovered hidden features in the environment that are beyond the scope of the initial perception description language. Theoretically, if the environment is a $n$ state finite deterministic automaton and each of the learner's $m$ actions has a known inverse, then the learning method can learn with accuracy 1 $-$ $\epsilon$ and confidence 1 $-$ $\xi$ the correct model of the environment within $O(n\sp2m{1\over\epsilon}$log${1\over\xi}$) steps. Empirically, in comparison with existing learning systems, this approach has shown the advantages of creating problem spaces by interacting with environments, eliminating the bias posed by the initial concept hierarchy, and constructing new vocabulary through actions. The generality of this approach is illustrated by experiments conducted in various domains, including child learning, puzzle solving, robot simulation and scientific discovery.
The Effect of Selective Transcranial Magnetic Stimulation with Functional Near-Infrared Spectroscopy and Intensive Speech Therapy on Individuals with Post-Stroke Aphasia

Purpose: To examine the efficacy of selective repetitive transcranial magnetic stimulation (rTMS) therapy guided by functional near-infrared spectroscopy (fNIRS) combined with intensive speech therapy (iST) on post-stroke patients with aphasia. Material and Methods: Eight right-handed patients with aphasia in the chronic stage after stroke were grouped into left and right hemisphere-activated for a language task based on pre-intervention fNIRS. Those with left hemisphere activation received 1-Hz TMS to the right inferior frontal gyrus (RtIFG; low-frequency rTMS [LFS] group), and those with right hemisphere activation received 10-Hz TMS to the RtIFG (high-frequency rTMS [HFS] group). The patients underwent an 11-day program of rTMS and iST. Results: Both groups showed a significant improvement in language function as measured by Standard Language Test of Aphasia (SLTA) total score at post-intervention relative to pre-intervention. Furthermore, the pre-to-post SLTA change scores were not statistically different between the groups. Comparison of pre- and post-intervention fNIRS revealed a resolution of the imbalance of interhemispheric inhibition in the LFS group and activation of the target hemisphere in the HFS group. Conclusions: The administration of fNIRS-guided selective rTMS therapy and iST to post-stroke patients with aphasia induced a significant improvement in language function, with both groups demonstrating a similar degree of improvement.
Rapid purification and characterization of protein kinase C from bovine retinal rod outer segments.

A rapid FPLC procedure for the purification of protein kinase C from bovine rod outer segments is described. The enzyme is essentially homogeneous after purification and exhibits a molecular mass of approximately 85 kDa, as determined by SDS/PAGE. From its chromatographic behaviour on hydroxyapatite, and from Western-blotting experiments using isoenzyme-specific antibodies, we were able to identify the bovine rod outer segment protein kinase C as being of the alpha or type-III form. The purified protein kinase C has a specific activity of 1066 nmol 32P.min-1.mg protein-1, and shows a 30-fold activation upon the addition of the effectors Ca2+, PtdSer and 1,2-diacylglycerol. Arachidonic acid and linoleic acid were also found to enhance significantly the activity of the purified enzyme.
A 200 MSPS 10-bit pipelined ADC using digital calibration

We present in this paper the design and implementation of a 10-bit, 200 Mega samples per second (MSPS) pipelined and digitally calibrated analog-to-digital converter (ADC). The proposed ADC is based on simple topologies of analog building blocks to reach the high sampling rate. On the other hand, the achieved combination of resolution and performances are due to digital calibration, which allows compensating the nonlinearity introduced by the simplified architectures of analog circuits. This ADC was designed and implemented using CMOS 0.18/spl mu/m technology.
Modèle utilisateur et modélisation utilisateur dans les systèmes de gestion des connaissances : une approche fondée sur les ontologies

by Liana Razmerita La nouvelle economie est dominee par les echanges de savoir et par la production de connaissances; on parle d'economie de l’immateriel (Zackland et Grundstein, 2001). La connaissance est un enjeu economique majeur de nos jours; c’est le raison pour laquelle les organisations essayent de gerer au mieux leurs ressources. Les systemes de gestion des connaissances (SGC) sont destines a capitaliser et a gerer le patrimoine des connaissances dans les organisations. Au debut, les SGC etaient destines a la gestion des connaissances explicites dans les organisations. Elles etaient similaires aux systemes de gestion de bases de donnees. Les connaissances explicites sont les documents, les donnees, la bibliotheque de logiciels, etc. Mais a part ce type de connaissances explicites, il y a les connaissances tacites, le savoir faire, les connaissances qui ne sont pas transcrites. Les SGC essaient de donner un caractere tangible aux connaissances. La diffusion des connaissances, le partage des connaissances tacites est aussi l’enjeu des SGC modernes. Un systeme permettant de gerer un capital de connaissances est un probleme complexe, aux multiples facettes, qui peut impliquer un changement organisationnel important. Le role des SGC s’articule autour de trois actions cles: capitaliser, partager et creer des connaissances. L’objectif du travail de cette these a ete d’etudier le role du modele d’utilisateur et d’integrer ce modele utilisateur et la modelisation utilisateurs dans un SGC a base d’ontologies. Les avancees technologiques de l'informatique (technologie Web) et les recherches dans le domaine de l’intelligence artificielle (agents, ontologies, modele utilisateur) permettent de developper une nouvelle generation de SGC. Une nouvelle generation de SGC doit integrer beaucoup plus de fonctions que la simple gestion des connaissances mais cette generation doit aussi depasser les limitations des SGC actuels. L’objectif de
Evidence of a hyperkinetic state in children with elevated blood pressure

Abstract Background: Left ventricular hypertrophy (LVH) and elevated left ventricular mass index (LVMI) are important predictors of cardiovascular morbidity and mortality in adults. Children with hypertension and pre-hypertension demonstrate LVH and greater LVMI compared to normotensive children. The impact of blood pressure (BP) on early changes in left ventricular properties provides an opportunity to understand and identify cardiovascular risk early in childhood. Aim: The aim of this study was to assess left ventricular structural and functional properties in a sample of children across a wide range of BP values. Subjects and methods: Children aged 11–14-years were divided into BP groups: hypertensives (HTN; ≥95th percentile; n = 21) and normotensives (NTN; <90th percentile; n = 85) based on BP measures taken at two time points. Resting supine heart rate (HR), cardiac output (CO) and total peripheral resistance (TPR) were collected along with left ventricular structural and functional properties using ultrasound sonography. Results: LVMI and TPR were not different between groups. CO, HR and left ventricular end-diastolic and end-systolic volumes were elevated in the HTN group. Furthermore, HR and body mass index were found to be independent predictors of BP group status in children. Conclusion: These findings show that children with elevated BP are characterized by high HR and CO and normal TPR. Also, the results identify HR as a predictor of BP group status in early childhood.
Creating Images for Perception Research

Partially deleted line drawings are often used in object recognition studies. In this tutorial, software is demonstrated that allows researchers to manually delete pixels of a line drawing (percent deletion is calculated as the image is fragmented) or to select a random deletion process based on percent deletion. An online database is also described that allows researchers to catalog images for use in other studies.
PERSIVAL, a system for personalized search and summarization over multimedia healthcare information

In healthcare settings, patients need access to online information tha t can help them understand their medical situation. Physicians need information that is clinically relevant to an individual patient. In this paper, we present our progress on developing a system, PERSIVAL, that is designed to provide personalized access to a distributed patient care digital library. Using the secure, online patient records at New York Presbyterian Hospital as a user model, PERSIVAL's components tailor search, presentation and summarization of online multimedia information to both patients and healthcare providers.
Neural - Adaptive Control Based on Feedback Linearization for Electro Hydraulic Servo System

Neural Adaptive based on feedback linearization is used in this study to control the velocity and recognition of an electro hydraulic servo system (EHSS) in the presence of flow nonlinearities as well as internal friction and noise. This controller consists of four parts: PID controller, feedback linearization controller, neural network controller and the neural network identifier. The feedback linearization controller is used to prevent the system state in a region where the neural network can be accurately trained to achieve optimal control. The combination of controllers produces a stable system which adapts to optimize performance. This technique, as shown, can be prosperously used to stabilize any selected operating point of the system with noise and without interference. All consequences achieved are validated by computer simulation of a nonlinear mathematical model of the system. The fore mentioned controllers have a vast range to control the system. We compare Neural Adaptive based on feedback linearization controller results with feedback linearization, back stepping and PID controller.
PriA and phage T4 gp59: factors that promote DNA replication on forked DNA substrates

The initiation of DNA synthesis on forked DNA templates is a vital process in the replication and maintenance of cellular chromosomes. Two proteins that promote replisome assembly on DNA forks have so far been identified. In phage T4 development the gene 59 protein (gp59) assembles replisomes at D‐loops, the sites of homologous strand exchange. Bacterial PriA protein plays an analogous function, most probably restarting replication after replication fork arrest with the aid of homologous recombination proteins, and PriA is also required for phage Mu replication by transposition. Gp59 and PriA exhibit similar DNA fork binding activities, but PriA also has a 3′ to 5′ helicase activity that can promote duplex opening for replisome assembly. The helicase activity allows PriA’s repertoire of templates to be more diverse than that of gp59. It may give PriA the versatility to restart DNA replication without recombination on arrested replication forks that lack appropriate duplex openings.
Credibility in Search Systems via Information Retrieval theory

Information Retrieval methods, and search systems in general, are now a significant part of our interaction with the world outside of our direct reach. As such, they influence the way we perceive the reality we cannot directly experience. From here, the issue of credibility of IA systems is raised, and in this poster we look at the work which has already been done, observe its limits and propose some directions for future work in this area.
Emergent Use of Anticoagulation for Treatment of Patients With Ischemic Stroke

Background— Several clinical trials have tested the potential utility of emergent anticoagulation for acute ischemic stroke. Summary of Review— Rather than performing a meta-analysis that combines the data from several trials, this review focuses on individual studies. Although these trials do have inherent limitations, they demonstrate that emergent use of an anticoagulant is associated with a modest but significantly increased risk of hemorrhagic transformation of the ischemic stroke or serious nonneurological bleeding. The trials do not demonstrate a benefit from emergent anticoagulation in improving outcome, reducing mortality, and preventing early recurrent stroke. Conclusions— These results suggest that most patients with acute stroke should not be treated with unfractionated heparin or other rapidly acting anticoagulants after stroke. Prevention of deep vein thrombosis and pulmonary embolism among bedridden patients is the only established indication for early anticoagulation after acute ischemic stroke.
Estimating the number of segments for improving dialogue act labelling†

Abstract In dialogue systems it is important to label the dialogue turns with dialogue-related meaning. Each turn is usually divided into segments and these segments are labelled with dialogue acts (DAs). A DA is a representation of the functional role of the segment. Each segment is labelled with one DA, representing its role in the ongoing discourse. The sequence of DAs given a dialogue turn is used by the dialogue manager to understand the turn. Probabilistic models that perform DA labelling can be used on segmented or unsegmented turns. The last option is more likely for a practical dialogue system, but it provides poorer results. In that case, a hypothesis for the number of segments can be provided to improve the results. We propose some methods to estimate the probability of the number of segments based on the transcription of the turn. The new labelling model includes the estimation of the probability of the number of segments in the turn. We tested this new approach with two different dialogue corpora: SwitchBoard and Dihana. The results show that this inclusion significantly improves the labelling accuracy.
Adoption of Software Testing in Open Source Projects--A Preliminary Study on 50,000 Projects

In software engineering, testing is a crucial activity that is designed to ensure the quality of program code. For this activity, development teams spend substantial resources constructing test cases to thoroughly assess the correctness of software functionality. What is however the proportion of open source projects that include test cases? What kind of projects are more likely to include test cases? In this study, we explore 50,000 projects and investigate the correlation between the presence of test cases and various project development characteristics, including the lines of code and the size of development teams.
Mechanisms of Cigarette Smoke Effects on Human Airway Smooth Muscle

Cigarette smoke contributes to or exacerbates airway diseases such as asthma and COPD, where airway hyperresponsiveness and airway smooth muscle (ASM) proliferation are key features. While factors such as inflammation contribute to asthma in part by enhancing agonist-induced intracellular Ca2+ ([Ca2+]i) responses of ASM, the mechanisms by which cigarette smoke affect ASM are still under investigation. In the present study, we tested the hypothesis that cigarette smoke enhances the expression and function of Ca2+ regulatory proteins leading to increased store operated Ca2+ entry (SOCE) and cell proliferation. Using isolated human ASM (hASM) cells, incubated in the presence and absence cigarette smoke extract (CSE) we determined ([Ca2+]i) responses and expression of relevant proteins as well as ASM proliferation, reactive oxidant species (ROS) and cytokine generation. CSE enhanced [Ca2+]i responses to agonist and SOCE: effects mediated by increased expression of TRPC3, CD38, STIM1, and/or Orai1, evident by attenuation of CSE effects when siRNAs against these proteins were used, particularly Orai1. CSE also increased hASM ROS generation and cytokine secretion. In addition, we found in the airways of patients with long-term smoking history, TRPC3 and CD38 expression were significantly increased compared to life-long never-smokers, supporting the role of these proteins in smoking effects. Finally, CSE enhanced hASM proliferation, an effect confirmed by upregulation of PCNA and Cyclin E. These results support a critical role for Ca2+ regulatory proteins and enhanced SOCE to alter airway structure and function in smoking-related airway disease.
Pun and Non-Pun Humor in Second-Language Learning

We believe that the use of humor by conversational software agents would significantly improve secondlanguage learning. Puns help students to learn about homophony, and to distinguish between words with similar sounds or spellings; idiom-based jokes provide memorable contexts for idioms, which are notoriously difficult to memorize; and scalar humor introduces the student to common comparisons in the target language, and helps them build networks of vocabulary, particularly between nouns and adjectives. In general, humor is likely to motivate the student to study more often, and humanizes the interface, so that the conversational agent is perceived as a worthwhile dialogue partner. Moreover, because humor frequently rests on cultural concepts such as social station, rudeness, stereotypes and so on, studying humor can lead to the kind of deeper understanding that is necessary for true fluency. Finally, practice in the humorous forms of the target culture might allow a student to actively use humor in the same way a native speaker would, increasing the chances of genuine communication taking place. Here, we describe scalar humor in some depth, and discuss how computer-generated scalar humor could improve second language learning.
A New Quadtree-based Image Compression Technique using Pattern Matching Algorithm

A New Quadtree-based Image Compression Technique using Pattern Matching Algorithm F. Keissarian1 Summary In this paper, a new image compression technique is proposed in which variable block size technique is adopted, using quadtree decomposition, for coding images at low bit rates. The proposed algorithm decomposes the host image into blocks of variable sizes according to histogram analysis of the block residuals. Variable block sizes are then encoded at different rates based on their visual activity levels. To preserve edge integrity, a high-detail block is coded by a set of parameters associated with the pattern appearing inside the block. The use of these parameters at the receiver together with the quadtree code reduces the cost of reconstruction significantly and exploits the efficiency of the proposed technique. keywords: Image compression, Quadtree decomposition, Pattern classification.