Miracle-dz/UniFAR-FTUs huggingface dataset:
The cohesin loader NIPBL interacts with pre-ribosomal RNA and treacle to regulate ribosomal RNA synthesis

NIPBL is an essential loader of cohesin to mediate sister chromatid cohesion and chromatin loop organization. NIPBL mutations cause Cornelia de Lange Syndrome. How NIPBL’s genomic localization is specified is not fully understood. We found that NIPBL localizes to the nucleolus in an RNA-dependent manner and binds directly to ribosomal RNA (rRNA). We identified two RNA binding domains in NIPBL in vitro, both of which are required for efficient rRNA binding in vivo. NIPBL binds to ribosomal DNA (rDNA) in an RNA-stimulated manner, recruits PAF1 and promotes pre-rRNA transcription. Stress that inhibits rRNA synthesis displaces NIPBL from the nucleolus and rDNA. Interestingly, treacle, mutated in Treacher Collins syndrome, tightly binds to and recruits NIPBL to the nucleolus, nucleolar organizer regions, and the stress-induced nucleolar cap. The results reveal that a subpopulation of NIPBL is recruited to the nucleolus through its interaction with RNA and treacle and regulates pre-rRNA transcription.
From clinical narratives to ICD codes: automatic text categorization for medico-economic encoding

Summary We report on the design and preliminary evaluation of a system to help assignment ICD (International Classification of Disease) codes to clinical narratives. The objective of the project is to deliver an operational system to assist professional encoders of the University Hospital of Geneva in their coding task. We combine a set of machine learning and data-poor methods to generate a single automatic text categorizer, which returns a ranked list of ICD codes for any given output. In its current settings, the system is accepting three different textual fields as input: anamnesis, diagnosis and prescription fields. The combined ranking system currently obtains a precision of 74% at high ranks and a recall of about 63% for the top twenty returned codes. Although fairly promising, the impact of the tool on the institution coding efforts as well as on the billing figures (DRG: Diagnosis Related Groups) must now be evaluated.
Mosel: An Overview

This paper introduces the basics of the Mosel language that are required to use the software as a modeling and solution reporting interface to standard matrix-based solvers. Taking this a step further, it also shows how Mosel can be used to implement more complex solution algorithms. Using the Mosel libraries, a model written in the Mosel language can be integrated with and accessed from application programs implemented in programming languages such as C, C++, Java, C#, Visual Basic. The open, modular architecture of the Mosel environment for modeling and solving has been designed to be easily extensible, not being restricted to a particular type of problem or solver. The paper explains how the user can extend the existing Mosel language to provide new functionality that may be required, for instance, to access other solvers.
Design and Evaluation of an Underactuated Robotic Gripper for Manipulation Associated with Disaster Response

The following study focuses on the design and validation of an underactuated robotic gripper built for the Tactical Hazardous Operations Robot (THOR). THOR is a humanoid robot designed for use in the DARPA Robotics Challenge (DRC) and the Shipboard Autonomous Fire Fighting Robot (SAFFiR) project, both of which pertain to completing tasks associated with disaster response. The gripper was designed to accomplish a list of specific tasks outlined by the DRC and SAFFiR project. Underactuation was utilized in the design of the gripper to keep its complexity low while acquiring the level of dexterity needed to complete the required tasks. The final gripper contains two actuators, two underactuated fingers and a fixed finger resulting in four total degrees of freedom (DOF). The gripper weighs 0.68 kg and is capable of producing up to 38 N and 62 N on its proximal and distal phalanges, respectively. The gripper was put through a series of tests to validate its performance pertaining to the specific list of tasks it was designed to complete. The results of these tests show the gripper is in fact capable of completing all the necessary actions but does so within some limitations. This work is supported by DARPA through grant N65236-12-1-1002 and by ONR through grant N00014-11-1-0074.
Power Efficient Dynamic Source Routing Protocol

Power consumption in wireless ad hoc networks is an important design concern in the modern network research scenario. It is a concern because wireless nodes run with the help of battery and it has a limited life time period If the power failure of mobile node occurs it affects not only its ability to forward packets to destination but also its ability to forward packets on behalf of others and hence overall network lifetime. Moreover, it is very difficult to replace or recharge a mobile node powered by batteries so in order to maximize the life time of nodes routing of traffic should be in such a way that power consumption is minimized. Hence, every effort is to be channeled towards reducing power. More precisely, network lifetime is a key design metric in MANETs. Our main contribution in this thesis is Power Efficient Dynamic Source Routing (PEDSR) protocol, satisfying less power consumption from the viewpoints of nodes and network. To achieve our goal, first, we studied DSR protocol using performance and power aware metrics. Modifications are done on the Dynamic Source Routing (DSR) protocol by taking into consideration the outcomes of the pre-simulation, the existing feature of DSR for implementation of the design, and the previous research works done on DSR routing protocol by many researchers. Subsequently, we studied the performance evaluation of our proposition. The simulation results show that the power aware routing protocol, PEDSR outperforms the original DSR protocol in majority of the scenarios and evaluation metrics.
Applications of cross-sectional methodologies in developmental psychology

Book synopsis: Fully revised and updated, the second edition of the International Encyclopedia of the Social and Behavioral Sciences, first published in 2001, offers a source of social and behavioral sciences reference material that is broader and deeper than any other. Available in both print and online editions, it comprises over 3,900 articles, commissioned by 71 Section Editors, and includes 90,000 bibliographic references as well as comprehensive name and subject indexes.
Indwelling urinary catheter use and associated outcomes among adult patients undergoing surgery

Background : Indwelling Urinary catheters (IUCs) are the most utilized devices. They are complicated into postoperative catheter-associated urinary tract infections, urethral trauma, pain that culminate into prolonged immobility and hospital stay with associated financial implications. The aim of this review was to give an overview of the use of indwelling catheters among adult patients undergoing surgery. Methods : A systematic review approach was employed. A literature search was done using of search engines that include HINARI, PubMed, Google Scholar and Cochrane, using search words related to the title and aim of the review. Results : Eleven out of 236 articles involving 218,000,790 patients studied met the inclusion criteria. 86% to 87.3% of patients undergoing major operations were exposed to routine catheterization depending on the type of surgical procedure. Only 7.7% to 8% of patients needed postoperative IUCs. Unduly prolonged retention of IUCs was the most reason for inappropriate IUCs use with 18% without a documented removal order. IUCs contributed 80% to 87.8% of postoperative UTIs as the third most common postoperative infections. Conclusion : Use of IUCs is necessary for certain surgeries as per existing guidelines. The lack of IUC removal instructions is one of the factors contributing to CAUTIs. _________________________________________________________________________ Keywords : indwelling urinary catheter, CAUTI, surgery, perioperative
Spectrally and Spatially Informed Noise Suppression Using Beamforming and Convolutive NMF

Speech enhancement in low SNR conditions or in presence of large amount of reverberation is a challenging task. However, in some applications, prior information about the interfering noise source is available and can be exploited to tackle this issue. We propose to combine a beamformer with convolutive NMF in order to estimate the PSDs of the target speech signal and of the noise to be suppressed by exploiting knowledge of the noise source location and about its spectral content. We apply the proposed system to ego-noise suppression for a robotic platform. Simulations show that the spectral information exploited using convolutive NMF is beneficial to the noise reduction performance when compared to methods based on blind estimation but that estimating the noise PSD from the output of the beamformer is beneficial mostly when no prior knowledge of the noise spectral content is available.
Measured scattered signals at 4 GHz confirm strong specular reflections off buildings

The authors report measures of building reflections in the Fresnel region which clearly show the existence of large specular reflections which would severely interfere with radio links. Measurements of microwave terrestrial radio signals in the 4-GHz common carrier band were made using the Division 21320 van. Measurements were taken at several sites of specular and diffusely scattered signal levels. The measured specular reflection is 20 to 30 dB higher than the diffusely scattered energy and is caused by reflection from a building illuminated by a sidelobe 17 dB below the boresight beam of the transmitter, indicating that a reflection in the main beam would cause interference which may be 37 to 47 dB higher than that predicted by terrain scatter models. <<ETX>>
BROKERAGE QUALIFICATIONS IN RINGING OPERATIONS

Brokers are fundamental for maintaining flexibility in the networks that embed criminal activities. Our study aims at offering more precision on this key issue by examining the impact that brokers may have on crime-commission processes. To do so, we analyze two stolen-vehicle exportation (or ringing) operations within a framework that merges crime-script analysis and social-network analysis. We assess how diverse degrees of brokerage are distributed across the ringing operations and how the removal of key brokers would have had a disruptive impact by reducing the scope of alternatives for crime-script permutation and flexibility. Crime often proceeds in chain-like transactional settings that incorporate the action of a wide range of participants. Although a common premise regarding the structure of such collective action is one of rigid organization and authoritarian coordination, a crucial asset in these crimecommission processes is the extent to which they remain adaptable and flexible. Whether in contexts of organized crime, criminal enterprise, or more general criminal networks, past research repeatedly has come to the conclusion that loosely structured processes are more advantageous and, therefore, more likely to exist than rigid structures of order. In this article, we examine the coordination of such loosely structured processes by merging crime-script and social-network analyses. This merge allows us to reconfigure criminal ventures (the resale of stolen vehicles or ringing networks, in this study) in a framework that represents both the * We thank Robert Morselli, Marcus Felson, Pierre Tremblay, and the anonymous reviewers for their suggestions throughout the preparation of this article. Direct correspondence to Carlo Morselli, School of Criminology, Universit ´ e de
A Hierarchical Approach in Tamil Phoneme Classification using Support Vector Machine

Most of the speech recognition systems are designed based on the sub-word unit phoneme which is the basic sound unit of a language. In the proposed work, a novel hierarchical approach based phoneme classification task has been carried out to reduce time complexity and search space. Hierarchical classification of set of Tamil phonemes has been done in three levels. Phoneme boundaries of the given speech utterance are identified using Spectral Transition Measure (STM) and phonemes are separated. Mel-Frequency Cepstral Coefficients (MFCC) are extracted for each phoneme represented by 9 frames including the contextual frames of corresponding phoneme. In each hierarchical level, different number of models is built using Support Vector Machine (SVM) for classifying each phoneme group/phoneme. It is observed from the results that in hierarchical approach phoneme group recognition rate at level 1 and 2 has greatly improved compared to flat classification model. Complexity of search space is significantly reduced at level 2 and level 3 contrasts to flat phoneme classification model. Hierarchical phoneme classifier can be very well employed in phoneme recognition task which is useful in applications such as spoken term detection, out-ofvocabulary detection, named entity recognition, spoken document retrieval.
A Study on Firewall Policy Anomaly Representation Techniques

2 ABSTRACT: A firewall is a system that acts as an interface between private network and a public network. It implements the security policy based on the rules defined by the network administrator; which decides the packets can be allowed or blocked to the organization's private network. Manual definition of rules often results in anomalies in the policy. Existing research on this problem have been focused on analysis and detection of firewall policy anomalies. This paper discusses about two major firewall policy anomaly representations that is policy tree representation and a rule-based segmentation mechanism which uses grid-based representation. This grid-based segmentation mechanism overcomes some limitations of policy tree representation.
Optimal genetic and adaptive fuzzy washout filter design in the motion‐cueing simulator

This paper has improved the simulation fidelity of a motion‐cueing simulator within a limited working space by using the optimal genetic algorithm and an adaptive fuzzy algorithm in the washout filter design, especially, in solving the real‐time parameter auto‐tuning problem. The optimal parameters of the washout filter have been searched out globally by the genetic algorithm. The fuzzy inference methodology is adopted to solve the real‐time auto‐tuning problem of the motion‐cueing parameters in the coordinate adaptive washout filter design according to the varying frequency of the dynamic input signal and the attitude of the upper platform within a limited working space.
Session Initiation Protocol (SIP) Call Control - Conferencing for User Agents

This specification defines conferencing call control features for the Session Initiation Protocol (SIP). This document builds on the Conferencing Requirements and Framework documents to define how a tightly coupled SIP conference works. The approach is explored from the perspective of different user agent (UA) types: conference- unaware, conference-aware, and focus UAs. The use of Uniform Resource Identifiers (URIs) in conferencing, OPTIONS for capabilities discovery, and call control using REFER are covered in detail with example call flow diagrams. The usage of the isfocus feature tag is defined. This document specifies an Internet Best Current Practices for the Internet Community, and requests discussion and suggestions for improvements.
Accurate Prostate Volume Determination from T2-w MRI using Statistical Shape Models

Introduction: Prostate volume is highly indicative of treatment outcome for patients with prostate cancer, and is used in determining PSA density [1-3]. The currently clinical standard is for a clinician to manually determine the anterior-posterior, transverse, and cranio-caudal lengths of the prostate, and to use these measurements to model the prostate as an ellipsoid [4]. However, this can be time consuming and subject to interand intraobserver variability. We aim to automatically segment that prostate on each slice of a 3D MR stack using an advanced Active Shape Model (ASM) [5] system, donned a multi-feature ASM (MFA), and to use these segmentations to determine the volume of the prostate.
Discovery of noun semantic relations based on sentential context analysis

The last years saw a surge in the statistical processing of natural language and in particular in corpus based methods oriented to language acquisition. Polysemy is pointed at as the main obstacle to many tasks in the area and to thesaurus construction in particular. This dissertation summarizes the current results of a work on automatic synonymy discovery. The accent is focused on the difficulties that spring from polysemy and on linguistically and empirically motivated means to deal with it. In particular, we propose an unsupervised method to identify word usage profiles pertinent to specific word meanings. Further, we show that the routine to verify every possibility in search of semantic relations is not only computationally expensive but is rather counterproductive. As a consequence, we propose an application of a recently developed system for paraphrases extraction and alignment so that the exhaustive search is avoided in an unsupervised manner. This led to a method, that creates short lists of pairs of words that are highly probable to be in synonymy relation. The results show that the negative impact of polysemy is significantly reduced for part of the polysemy specter that covers about two thirds of the vocabulary. Besides the increased probability to discover frequently manifested synonymy relations, paraphrase alignment proved to highlight infrequent word meanings, and to reliably identify a set of very specific semantic relations.
An optimality theoretic approach to variable consonantal alternations in Qatari Arabic

v Acknowledgement.vi List of abbreviations.vii List of Tables.viii 0. INTRODUCTION.1 0.1 Qatari Arabic.2 0.2 Outline.4 1. QATARI ARABIC: THE SEGMENTAL INVENTORY 1.1 The surface inventory of Qatari Arabic.7 1.2 Previous approaches to the consonants under study.8 1.2.1 The traditional approach.8 1.2.2 Alternative approaches.10 1.2.3 Summary.12 1.3 The phonological status of []. 12 1.3. 1 Historical background.13 1.3. 2 Problems for considering /q/ the UR of [] . 15 1.3. 2.1 The case of affrication in Bahraini Arabic.15 1.3. 2.2 Local lexical items containing []. 16 1.3. 2.3 Minimal pairs.19 1.3. 3 The alternation between [q]/[] and []/[d]. 19 1.4 The phonological status of [t]. 20 1.4. 1 Historical background.21 1.4. 2 Problems for denying the phonemic status of /t/. 23 1.4. 2.1 Lexical items that surface invariably with [t]. 23 1.4. 2.2 Minimal pairs.25 1.5 The current position.26 1.6 Feature specifications for the relevant segments.28 1.7 Conclusion.31 2. AFFRICATION IN ARABIC: A SURVEY 2.0 Introduction.32 2.1 Tafxi.m and emphasis.33 2.2 Cantineau (1936, 1937). 35 2.3 Johnstone (1967). 38 2.4 Johnstone (1978). 47 2.5 Altoma (1969). 51 2.6 Mat>ar (1969). 52 2.7 Mat>ar (1985). 56 2.8 Al-amadidhi (1985). 56 2.9 Summary.57
Feature Selection Techniques using for High Dimensional Data in Machine Learning

In machine learning the classification task is normally known as supervised learning. In supervised learning present a specified set of classes and objects are labeled with the correct class. The goal is to generalize from the training objects that will make possible novel objects to be identified as belonging to one of the classes. Evaluating the performance of learning algorithms is a fundamental aspect of machine learning. The main objective of this paper is to study the classification accuracy using feature selection with machine learning algorithms. The dimensionality of the data is reduced by implementing Feature selection and accuracy of a learning algorithm improved. The filtered feature space that is, the condensed feature space provided by a filter. The advantage of feature selection for learning can include a reduction in the amount of data required to achieve learning, improved predictive accuracy, learned knowledge that is more compact and easily comprehend, and reduced execution time.
Detection of Synergistes jonesii and genetic variants in ruminants from different geographical locations

Keynote paper presented at the International Leucaena Conference, 1‒3 November 2018, Brisbane, Queensland, Australia.Leucaena leucocephala is a nutritionally rich forage tree legume that contains a toxic non-protein amino acid, mimosine, from which other toxic compounds 3,4-dihydroxypyridone (3,4-DHP) and 2,3-DHP are formed in the rumen. The rumen bacterium Synergistes jonesii is able to degrade these DHP isomers into non-toxic end products. In this study we developed new PCR-based assays to improve the specificity and sensitivity of detection of S. jonesii in the rumen. Using these new assays in a survey of ruminants from different countries showed S. jonesii appeared to be ubiquitous rather than isolated geographically. The bacterium was present as a minor population (<106 cells/mL) in the rumen and was usually comprised of several genetic variants of the species. Although the indigenous nature of S. jonesii could imply animals are protected from toxicity, the relative abundance of the bacterium, potential variation in DHP degrading ability of genetic variants of the species, and amount of leucaena in the diet may determine the ability of the resident population in the rumen to protect the animal from toxicity.
Rapid, Accurate, Precise and Reproducible Binding Affinity Calculations using Ensembles of Molecular Dynamics Simulations

The accurate prediction of the binding affinities of ligands to proteins is a major goal in drug discovery and personalised medicine. The use of in silico methods to predict binding affinities has been largely confined to academic research until recently, primarily due to the lack of their reproducibility, as well as unaffordably longer time to solution. In this thesis, I mainly describe the ensemble based molecular dynamics approaches, ESMACS and TIES, that provide a route to reliable predictions of free energies meeting the requirements of speed, accuracy, precision and reliability. The performance of both these methods when applied to a diverse set of protein targets and ligands is reported. The results are in very good agreement with experimental data while the methods are repeatable by construction. Statistical uncertainties of the order of 0.5 kcal/mol or less are achieved. These methods have been further extended to incorporate enhanced sampling techniques based on replica exchange (also known as parallel tempering) to handle situations where conformational sampling is difficult using standard molecular dynamics. A critical assessment of free energy estimators like MBAR has been made for their application in binding affinity prediction. The methodologies described are shown to have a positive impact in the drug design process in the pharmaceutical domain as well as in personalised medicine, with concomitant potential major industrial and societal impact. Finally, our automated workflow, comprising the Binding Affinity Calculator (BAC) together with the FabSim are described. These tools and services help us complete the entire execution in 8 hours or less, depending on the high performance architecture and hardware available.
Supplemental Tables : 3 Title : Multimodal parameters of brain structure and function related to sex differences in cognitive performance

Title: Multimodal parameters of brain structure and function related to sex differences in cognitive performance. Authors: Ruben C. Gur, Tyler M. Moore, Adon F.G. Rosen, Kosha Ruparel, Theodore D. Satterthwaite, David R. Roalf, Efstathios D. Gennatas, Warren B. Bilker, Russell T. Shinohara, Allison Port, Mark A. Elliott, Ragini Verma, Christos Davatzikos, Daniel H. Wolf, John A. Detre, Raquel E. Gur