Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Internal Ribosome Entry Site (IRES) and Furin-2A (F2A) for Monoclonal Antibody Expression Level and Quality in CHO Cells

Four versions of tricistronic vectors expressing IgG1 light chain (LC), IgG1 heavy chain (HC), and dihydrofolate reductase (DHFR) in one transcript were designed to compare internal ribosome entry site (IRES) and furin-2A (F2A) for their influence on monoclonal antibody (mAb) expression level and quality in CHO DG44 cells. LC and HC genes are arranged as either the first or the second cistron. When using mAb quantification methods based on the detection antibodies against HC Fc region, F2A-mediated tricistronic vectors appeared to express mAb at higher levels than the IRES-mediated tricistronic vectors in both transient and stable transfections. Further analysis revealed that more than 40% of products detected in stably transfected pools generated using the two F2A-mediated tricistronic vectors were aggregates. LC and HC from the F2A stably transfected pools were not properly processed, giving rise to LC+F2A+HC or HC+F2A+LC fusion proteins, LC and HC polypeptides with F2A remnants, and incorrectly cleaved signal peptides. Both IRES-mediated tricistronic vectors express mAb with correct sizes and signal peptide cleavage. Arrangement of LC as the first cistron in the IRES-mediated tricistronic vectors exhibits increased mAb expression level, better growth, and minimized product aggregation, while arrangement of HC as first cistron results in low expression, slower growth, and high aggregation. The results obtained will be beneficial for designing vectors that enhance mAb expression level and quality in mammalian cells.
Extracting Knowledge from Twitter and The Web

Extracting Knowledge from Twitter and The Web Alan Ritter Co-Chairs of the Supervisory Committee: Professor Oren Etzioni Computer Science & Engineering Professor Mausam Computer Science & Engineering The internet has revolutionized the way we communicate, leading to a constant flood of text in electronic format, including the Web, email, SMS and the short informal texts found in microblogs such as Twitter. This presents a big opportunity for Natural Language Processing (NLP) and Information Extraction (IE) technology to enable new large scale data-analysis applications by extracting machine-processable information from unstructured text at scale. This thesis discusses the challenges and opportunities which arise when applying NLP and IE to large open-domain and heterogeneous text corpora such as Twitter and the Web, and presents solutions to a number of issues which arise in this setting. In cases where the number of output labels is small, for example syntactic annotations such as parts of speech (POS), good performance is achieved using a mostly supervised rvnapproach. We build a set of low-level syntactic annotation tools for noisy informal Twitter text including a POS tagger, shallow parser, named entity segmenter and event recognizer using supervised learning techniques trained on an annotated corpus of tweets. Supervised learning becomes impractical however, for semantic processing tasks such as: named entity categorization, event categorization, inferring selectional preferences and relation extraction, where the number of output labels is large and/or unknown a-priori. A key hypothesis which is evaluated throughout this thesis is that semantic processing of massive, diverse text corpora such as Twitter and the Web requires unsupervised and weakly supervised methods which can leverage large unlabeled datasets for learning, rather than relying on the relatively small corpora which are feasible to annotate. We present a set of techniques for unsupervised and weakly-supervised information extraction based on probabilistic latent variable models, which are applied to infer the semantics of large numbers of words and phrases and extract knowledge from large open-domain text corpora.
AUXIN RESPONSE FACTOR8 Is a Negative Regulator of Fruit Initiation in Arabidopsis[W]

Fruit and seed formation in plants is normally initiated after pollination and fertilization, and, in the absence of fertilization, flowers senesce. In the Arabidopsis thaliana mutant fruit without fertilization, a mutation in AUXIN RESPONSE FACTOR8 (ARF8) results in the uncoupling of fruit development from pollination and fertilization and gives rise to seedless (parthenocarpic) fruit. Parthenocarpy was confirmed in two additional recessive alleles and was caused by mutations within the coding region of ARF8. Genetic experiments indicate that ARF8 acts as an inhibitor to stop further carpel development in the absence of fertilization and the generation of signals required to initiate fruit and seed development. Expression of ARF8 was found to be regulated at multiple levels, and transcriptional autoregulation of ARF8 was observed. Analysis of plants transformed with a transcriptional PARF8:β-glucuronidase (GUS) construct or a translational ARF8:GUS fusion construct displayed distinct developmental regulation of the reporter in floral tissues involved in pollination and fertilization and in the carpel wall. After fertilization, the level of GUS activity declined in the developing seed, while in unfertilized ovules that are destined to senesce, ARF8:GUS expression spread throughout the ovule. This is consistent with a proposed role for ARF8 in restricting signal transduction processes in ovules and growth in pistils until the fruit initiation cue.
Intratumoral NAMI-A Treatment Triggers Metastasis Reduction, Which Correlates to CD44 Regulation and Tumor Infiltrating Lymphocyte Recruitment

Intratumor (i.t.) injection of 35 mg/kg/day NAMI-A for six consecutive days to CBA mice bearing i.m. implants of MCa mammary carcinoma reduces primary tumor growth and particularly lung metastasis formation, causing 60% of animals to be free of macroscopically detectable metastases. The i.t. treatment allows study of the effects of NAMI-A on in vivo tumor cells exposed to millimolar concentrations for a relatively prolonged time. Under these conditions, NAMI-A reduces the number of CD44+ tumor cells and changes tumor cell phenotype to a lower aggressive behavior, as shown by scanning electron microscopy analysis. On primary tumor site, NAMI-A causes unbalance between 2n and aneuploid cells in favor of lymphocytes. Furthermore, in tumor tissue, nitric oxide production is increased and active matrix metalloproteinase 9 is decreased, and these effects are accompanied by a reduced hemoglobin concentration. These data are in agreement with the reduction of tumor invasion and metastasis and suggest the therapeutic usefulness of NAMI-A in neoadjuvant or tumor reduction treatments for preventing metastasis formation. These data further stress the usefulness of intratumor treatments as experimental preclinical model for studying in vivo the mechanism of tumor cell interactions after prolonged exposure to ruthenium-based compounds to be developed for metastasis inhibition.
Frequency dynamics of gain-switched injection-locked semiconductor lasers

The frequency dynamics of gain-switched single-mode semiconductor lasers subject to optical injection is investigated. The requirements for low time jitter and reduced frequency chirp operation are studied as a function of the frequency mismatch between the master and slave lasers. Suppression of the power overshoot, typical during gain-switched operation, can be achieved for selected frequency detunings.
Automatic Reconstruction of Colored 3D Models

A basic issue of mobile robotics is the automatic generation of environment maps. This paper presents novel results for the reconstruction of textured 3D maps with an autonomous mobile robot, a 3D laser range finder and two pan-tilt color cameras. Building 3D maps involves a number of fundamental scientific issues. This paper adresses the issue of how to fuse the geometry data of the 3D laser range finder with camera images. The proposed algorithm allows to texturize geometrical 3D scenes-models.
Heuristic Real-Time Dynamic Programming ( Preliminary Results ) Blai Bonet and Hdctor Geffner

Building on the work of Korf on real-time search, and of Barto, Bradtke and Singh on real-time dynamic programming, we discuss three features that we have found crucial for the solution of large MDP’s; namely, selective updates, selective lookahead, and good heuristic functions. We also present an RTDP algorithm that exhibits these features and assess its performance over three types of problems.
Stability and Dispersion Analysis of a TLM Unified Approach for Dispersive Anisotropic Media

With the advancement of technology, modern equipment involves new functionalities that require complex media (e.g., anisotropic dispersive media such as ferrite, lossy dielectrics, or graphene) for a variety of applications. This imposes the necessity to extend simulation techniques capable of solving Maxwell’s equations in such media. However, as far as discrete time-domain models are concerned, their performance in terms of dispersion and stability criterion has not been thoroughly investigated in the presence of complex media. More particularly, a question arises about which maximum mesh size can be used and the resulting time step to ensure stability. Starting from a transmission-line matrix method algorithm for the general linear media, procedures for dispersion and stability analysis are given and special cases are presented. It is found that the proposed approach allows, in certain cases, some significant reduction in the computer cost compared to the approximate rules generally used. The same procedures can be easily extended to other time-domain schemes such as FDTD.
What is the perceived contribution of coaching to leaders transitioning to more senior roles in the NHS

This case study explores the contribution of coaching in addressing the adaptive challenges of senior leadership transitions from the perspective of leaders who have recently transitioned to more senior roles in the NHS. The findings reveal a clear perception from participants that coaching helped them through the critical phases of their transition journey, enabling them to develop the confidence, resilience and capacities to take hold of their new role. The opportunity of a supportive and reflective space where they could step away from the intensity of their job demands and engage in thoughtful reflection on their experience was significantly valued.
Maximum Entropy based Rule Selection Model for Syntax-based Statistical Machine Translation

This paper proposes a novel maximum entropy based rule selection (MERS) model for syntax-based statistical machine translation (SMT). The MERS model combines local contextual information around rules and information of sub-trees covered by variables in rules. Therefore, our model allows the decoder to perform context-dependent rule selection during decoding. We incorporate the MERS model into a state-of-the-art linguistically syntax-based SMT model, the tree-to-string alignment template model. Experiments show that our approach achieves significant improvements over the baseline system.
A Discontinuous Galerkin Method to Solve the EEG Forward Problem Using the Subtraction Approach

In order to perform electroencephalography (EEG) source reconstruction, i.e., to localize the sources underlying a measured EEG, the electric potential distribution at the electrodes generated by a dipolar current source in the brain has to be simulated, which is the so-called EEG forward problem. To solve it accurately, it is necessary to apply numerical methods that are able to take the individual geometry and conductivity distribution of the subject's head into account. In this context, the finite element (FE) method (FEM) has shown high numerical accuracy with the possibility to model complex geometries and conductive features, e.g., white matter conductivity anisotropy. In this article, we introduce and analyze the application of a discontinuous Galerkin (DG) method, an FEM that includes features of the finite volume framework, to the EEG forward problem. The DG-FEM approach fulfills the conservation property of electric charge also in the discrete case, making it attractive for a variety of applicat.
Working Paper Series 3 / 2009 The endogeneity bias in the relationship between employee commitment and job satisfaction

The effect of job satisfaction on organisational commitment has attracted a great deal of interest in the human resource management and organizational psychology literatures. However, much of the empirical work is based on relatively small sample sizes and neglects the possibility of endogeneity of job satisfaction, potentially leading to biased estimates of the effect of job satisfaction on organizational commitment. Using a large matched employee-employer dataset this paper re-examines the relationship between the two work-related attitudes by employing micro-econometric techniques to correct for potential endogeneity arising from omitted variables and simultaneity. We show both theoretically and empirically that ignoring the endogeneity leads to overestimate of the effects.
Distributed Consensus Strategy for Platooning of Vehicles in the Presence of Time-Varying Heterogeneous Communication Delays

We analyze and solve the platooning problem by treating it as the problem of achieving consensus in a network of dynamical systems affected by time-varying heterogeneous delays due to wireless communication among vehicles. Specifically, a platoon is modeled as a dynamical network where: 1) each vehicle, with its own dynamics, is a node; 2) the presence of communication links between neighboring vehicles is represented by edges; and 3) the structure of the intervehicle communication is encoded in the network topology. A distributed control protocol, which acts on every vehicle in the platoon, is derived. It is composed of two terms: a local action depending on the state variables of the vehicle itself (measured onboard) and an action depending on the information received from neighboring vehicles through the communication network. The stability of the platoon is proven by using Lyapunov-Razumikhin theorem. Numerical results are included to confirm and illustrate the theoretical derivation.
Être passionné un peu, beaucoup, énormément? Le concept de la passion chez les joueurs de poker, une étude qualitative.

La passion est étudiée depuis une quinzaine d’années chez les joueurs de jeu de hasard et d’argent. Elle comprend deux formes, soit la passion obsessive (PO) qui est contrôlante et la passion harmonieuse (PH) qui laisse de la place à d’autres activités du joueur. Les études transversales associent la PO aux problèmes de jeu, ce qui n’est pas le cas de la PH. Toutefois, la pertinence de l’utilisation du concept de passion et son influence sur les comportements de jeu, selon le discours des joueurs, sont totalement méconnues. Les objectifs de cette étude étaient d’examiner la pertinence du concept de passion chez des joueurs poker (JdP) et de comprendre les liens entre les deux formes de passion et les problèmes de jeu. Cette étude qualitative descriptive est la deuxième composante d’une étude mixte séquentielle auprès de JdP du Québec (n=12). L’analyse de contenu thématique a été réalisée en privilégiant la thématisation en continu. Parmi les participants, la majorité a été ou est actuellement passionnée de poker et les deux formes de passion sont des concepts pertinents selon les joueurs. Le fait d’être passionné serait l’un des facteurs influençant les comportements de jeu. Toutefois, un JdP peut continuer à jouer sans être passionné alors que l’on peut également être passionné sans nécessairement jouer fréquemment. Il ne semble donc pas y avoir de lien direct entre la passion et la fréquence de jeu. La pertinence du concept de passion pour les joueurs permet de penser qu’il pourrait être utilisé en prévention ou encore dans le traitement des JdP. Passion among gamblers has been studied for the last decade and a half. There are two forms of passion: obsessive passion (OP), which is controlling, and harmonious passion (HP), which leaves room for the gambler’s other activities. Cross-sectional studies associate OP with gambling problems, which is not the case for HP. The relevance of the concept of passion and passion’s influence on gambling behaviour are, however, uncertain, according to gamblers themselves. The objectives of this study were to examine the relevance of the concept of passion for poker players (PP) and understand the connections between the two forms of passion and gambling problems. This qualitative descriptive study is the second part of a sequential mixed study with PPs in Québec (n=12). The thematic content analysis was conducted using continuous thematization. The majority of the participants were or are currently passionate about poker, and both forms of passion are relevant concepts for these players. According to them, being passionate is one of the behaviours that influences gambling behaviour. A PP may, however, continue to play without being passionate, but also be passionate without necessarily playing frequently. There does not, therefore, seem to be any direct connection between passion and frequency of play. The relevance of the concept of passion for poker players suggests that it may be used preventively or in the treatment of PPs.
Systemic administration of 6-OHDA to rhesus monkeys upregulates HLA-DR expression in brain microvasculature

Background We recently developed a nonhuman primate model of cardiac dysautonomia by systemic dosing of the catecholaminergic neurotoxin 6-hydroxydopamine (6-OHDA). The aim of this study was to assess whether systemic 6-OHDA affects the central nervous system of nonhuman primates, in particular the dopaminergic nigrostriatal system. Methods Brain sections from adult rhesus monkeys that received systemic 6-OHDA (50 mg/kg intravenously; n=5) and were necropsied 3 months later, as well as normal controls (n=5) were used in this study. Tissue was cut frozen at 40 μm on a sliding microtome, processed for immunohistochemistry, and blindly evaluated. Results Neither the optical density of tyrosine hydroxylase immunoreactivity (TH-ir; a dopaminergic neuronal marker) in the caudate and putamen nucleus nor the TH-ir cell number and volume in the substantia nigra showed significant differences between groups. Yet within groups, statistical analysis revealed significant individual differences in the 6-OHDA-treated group, with two animals showing a lower cell count and volume. Optical density quantification of α-synuclein-ir in the substantia nigra did not show differences between groups. As α-synuclein intracellular distribution was noted to vary between animals, it was further evaluated with a semiquantitative scale. A greater intensity and presence of α-synuclein-positive nigral cell bodies was associated with larger TH-positive nigral cell volumes. Increased human leukocyte antigen (HLA-DR; a microglial marker) expression was observed in 6-OHDA-treated animals compared with controls. HLA-DR-ir was primarily localized in endothelial cells and perivascular spaces throughout cortical and subcortical structures. Semiquantitative evaluation using a rating scale revealed higher HLA-DR-ir in blood vessels of 6-OHDA-treated animals than controls, specifically in animals with the lowest number of dopaminergic nigral neurons. Conclusion Our results demonstrate that systemic 6-OHDA administration to rhesus monkeys can affect the dopaminergic nigrostriatal system and upregulate inflammatory markers in the cerebrovasculature that persist 3 months post neurotoxin challenge. The variability of the subject response suggests differences in individual sensitivity to 6-OHDA.
Constraints on Cosmological Parameters from MAXIMA-1

We set new constraints on a seven-dimensional space of cosmological parameters within the class of inflationary adiabatic models. We use the angular power spectrum of the cosmic microwave background measured over a wide range of l in the first flight of the MAXIMA balloon-borne experiment (MAXIMA-1) and the low-l results from the COBE Differential Microwave Radiometer experiment. We find constraints on the total energy density of the universe, Ω = 1.0, the physical density of baryons, Ωbh2 = 0.03 ± 0.01, the physical density of cold dark matter, Ωcdmh2 = 0.2, and the spectral index of primordial scalar fluctuations, ns = 1.08 ± 0.1, all at the 95% confidence level. By combining our results with measurements of high-redshift supernovae we constrain the value of the cosmological constant and the fractional amount of pressureless matter in the universe to 0.45 < ΩΛ < 0.75 and 0.25 < Ωm < 0.50, at the 95% confidence level. Our results are consistent with a flat universe and the shape parameter deduced from large-scale structure, and in marginal agreement with the baryon density from big bang nucleosynthesis.
User Interfaces for Portable Proofs

Portable proofs are a new and interesting way of integrating theorem provers into distributed environments like the web. This article reports on user interface’s challenges and opportunities for theorem provers in such environments. In particular, this article reports on the design of user interfaces used for searching, browsing and inspecting TSTP problems when published as portable proofs.
ESTIMATING THE APPROXIMATION ERROR IN LEARNING THEORY

Let B be a Banach space and (ℋ,‖·‖ℋ) be a dense, imbedded subspace. For a ∈ B, its distance to the ball of ℋ with radius R (denoted as I(a, R)) tends to zero when R tends to infinity. We are interested in the rate of this convergence. This approximation problem arose from the study of learning theory, where B is the L2 space and ℋ is a reproducing kernel Hilbert space. The class of elements having I(a, R) = O(R-r) with r > 0 is an interpolation space of the couple (B, ℋ). The rate of convergence can often be realized by linear operators. In particular, this is the case when ℋ is the range of a compact, symmetric, and strictly positive definite linear operator on a separable Hilbert space B. For the kernel approximation studied in Learning Theory, the rate depends on the regularity of the kernel function. This yields error estimates for the approximation by reproducing kernel Hilbert spaces. When the kernel is smooth, the convergence is slow and a logarithmic convergence rate is presented for analytic kern.
Planning agile motions for quadrotors in constrained environments

Planning physically realistic and easily controllable motions of flying robots requires considering dynamics. This paper presents a local trajectory planner, based on a simplified dynamic model of quadrotors, which fits the requirements to be integrated into a global motion planning approach. It relies on a closed-form solution to compute curves in the kinodynamic state space that tend to minimize the flying time. These curves have suitable continuity properties and guarantee respect of physical limits of the system (i.e. bounds for the time-derivatives of the pose coordinates). The paper explains how this local planner can be used within different motion planning approaches that enable the treatment of difficult problems in constrained environments.
The Application of Fuzzy-Neural Network Based on HGA in the Washing Machine Control System

This paper has combined neural network with fuzzy control and achieved the self-learning and adaptive of fuzzy-controller, has realized the control of washing machines by a fuzzy-neural network optimization algorithms based on Hierarchical Genetic Algorithm(HGA). In addition, fuzzy-neural network structure and weight parameters have been optimized and the optimal control of the washing machine with characteristics of non-linear? time-varying? interference and pure –delay has been achieved.