Miracle-dz/UniFAR-FTUs huggingface dataset:
Glycogen Synthase Kinase 3 Phosphorylates RBL2/p130 during Quiescence

ABSTRACT Phosphorylation of the retinoblastoma-related or pocket proteins RB1/pRb, RBL1/p107, and RBL2/p130 regulates cell cycle progression and exit. While all pocket proteins are phosphorylated by cyclin-dependent kinases (CDKs) during the G1/S-phase transition, p130 is also specifically phosphorylated in G0-arrested cells. We have previously identified several phosphorylated residues that match the consensus site for glycogen synthase kinase 3 (GSK3) in the G0 form of p130. Using small-molecule inhibitors of GSK3, site-specific mutants of p130, and phospho-specific antibodies, we demonstrate here that GSK3 phosphorylates p130 during G0. Phosphorylation of p130 by GSK3 contributes to the stability of p130 but does not affect its ability to interact with E2F4 or cyclins. Regulation of p130 by GSK3 provides a novel link between growth factor signaling and regulation of the cell cycle progression and exit.
A proposed index of usability: A method for comparing the relative usability of different software systems

Abstract Usability is becoming a more and more important software criterion, but the present usability measurement methods are either difficult to apply, or overly dependent upon evaluators' expertise. Based on human information processing theory, this study identified eight human factors considerations which are relevant to software usability. These considerations as well as the three stages of human information processing theory formed the framework from which our Purdue Usability Testing Questionnaire (PUTQ) is derived. An experiment was conducted to test the validity of PUTQ. The experiment result showed high correlation between PUTQ and the Questionnaire for User Interaction Satisfaction (QUIS version 5.5). In addition, PUTQ detected the differences in user performance between two experimental interface systems, but QUIS failed to do so.
Interleukin 3- receptor targeted exosomes inhibit in vitro and in vivo Chronic Myelogenous Leukemia cell growth

Despite Imatinib (IM), a selective inhibitor of Bcr-Abl, having led to improved prognosis in Chronic Myeloid Leukemia (CML) patients, acquired resistance and long-term adverse effects is still being encountered. There is, therefore, urgent need to develop alternative strategies to overcome drug resistance. According to the molecules expressed on their surface, exosomes can target specific cells. Exosomes can also be loaded with a variety of molecules, thereby acting as a vehicle for the delivery of therapeutic agents. In this study, we engineered HEK293T cells to express the exosomal protein Lamp2b, fused to a fragment of Interleukin 3 (IL3). The IL3 receptor (IL3-R) is overexpressed in CML blasts compared to normal hematopoietic cells and thus is able to act as a receptor target in a cancer drug delivery system. Here we show that IL3L exosomes, loaded with Imatinib or with BCR-ABL siRNA, are able to target CML cells and inhibit in vitro and in vivo cancer cell growth.
DeepArchitect: Automatically Designing and Training Deep Architectures

In deep learning, performance is strongly affected by the choice of architecture and hyperparameters. While there has been extensive work on automatic hyperpa- rameter optimization for simple spaces, complex spaces such as the space of deep architectures remain largely unexplored. As a result, the choice of architecture is done manually by the human expert through a slow trial and error process guided mainly by intuition. In this paper we describe a framework for automatically designing and training deep models. We propose an extensible and modular lan- guage that allows the human expert to compactly represent complex search spaces over architectures and their hyperparameters. The resulting search spaces are tree- structured and therefore easy to traverse. Models can be automatically compiled to computational graphs once values for all hyperparameters have been chosen. We can leverage the structure of the search space to introduce different model search algorithms, such as random search, Monte Carlo tree search (MCTS), and sequen- tial model-based optimization (SMBO). We present experiments comparing the different algorithms on CIFAR-10 and show that MCTS and SMBO outperform random search. We also present experiments on MNIST, showing that the same search space achieves near state-of-the-art performance with a few samples. These experiments show that our framework can be used effectively for model discov- ery, as it is possible to describe expressive search spaces and discover competitive models without much effort from the human expert. Code for our framework and experiments has been made publicly available
Da Vinci research kit : PSM and MTM dynamic modelling

The DVRK is currently used by 26 research groups around the world [1]. The platform consists of two patient side manipulators (PSMs), one endoscopic manipulator and two master tool manipulators (MTMs). The Johns Hopkins University [2] provides a full ROS-based open controller of all the DVRK robotic arms. The controller allows position, velocity and current control and thus opens the way for developing and testing advanced control techniques. However, some control techniques, e.g. impedance-force control, realistic dynamic simulations and sensor-less strategies for collision detection or contact force estimation, requires an accurate knowledge of the robots dynamic models. The aim of this work is to derive a complete dynamic model of both the MTMs and the PSMs arms of the DVRK system and use state of the art methods to obtain accurate identification of the dynamic parameters. In the case of the DVRK robot the presence of a 1-DOF double parallelogram and a counterweight in the PSM, and of a 2DOF parallelogram in the MTM make the model complex and require a detailed discussion. A constrained optimization approach based on LMIs has been adopted to guarantee physical consistency of the dynamic parameters. The results of the experimental validation of the identified models are satisfactory, especially for the PSM, although they could be further improved.
Integrating expanding annotations with a 3D explosion probe

Understanding complex 3D virtual models can be difficult, especially when the model has interior components not initially visible and ancillary text. We describe new techniques for the interactive exploration of 3D models. Specifically, in addition to traditional viewing operations, we present new text extrusion techniques combined with techniques that create an interactive explosion diagram. In our approach, scrollable text annotations that are associated with the various parts of the model can be revealed dynamically, either in part or in full, by moving the mouse cursor within annotation trigger areas. Strong visual connections between model parts and the associated text are included in order to aid comprehension. Furthermore, the model parts can be separated, creating interactive explosion diagrams. Using a 3D probe, occluding objects can be interactively moved apart and then returned to their initial locations. Displayed annotations are kept readable despite model manipulations. Hence, our techniques provide textual context within the spatial context of the 3D model.
Differential response of embryonic and fetal myoblasts to TGF beta: a possible regulatory mechanism of skeletal muscle histogenesis.

Embryonic and fetal skeletal myoblasts were grown in culture in the presence of TGF beta. Under the conditions employed, TGF beta inhibited differentiation of fetal but not of embryonic myoblasts. To investigate the possible relevance of these data to skeletal muscle histogenesis in vivo, we studied the proliferation/differentiation state of mesodermal cells in the proximal region of the limb bud at the time of primary fiber formation. BrdU labeling and immunostaining for myosin heavy chains revealed that very few mesodermal cells enter the S phase of the cycle when differentiated primary fibers first appear. However, a few hours later, many cells in S phase surround newly formed muscle fibers, suggesting that the latter may be a source of mitogens for undifferentiated myoblasts. Co-culture experiments supported this hypothesis, showing that medium conditioned by fiber-containing explants can stimulate myoblast proliferation. Taken together these data suggested a possible mechanism for the regulation of muscle fiber formation. The model assumes that fibers form in the proximal region of the limb bud, where TGF beta is known to be present, and BrdU labeling experiments did not reveal cells in S phase. It is conceivable that non-dividing embryonic myoblasts (which do not respond to TGF beta) can undergo differentiation, while fetal myoblasts are inhibited by TGF beta. Once formed, primary fibers may stimulate a new wave of proliferation in fetal myoblasts, in order to expand the pool of cells needed to form secondary fibers. (ABSTRACT TRUNCATED AT 250 WORDS)
TRANSLATIONS AS SHAPED BY INSTALLED BASE AND ACTORS' INTERESTS

A flat top carrier deck includes a base plate, and at least one elevating gate. The base plate is preferably fabricated from a perforated sheet of material. Each elevating gate engages the base plate. Each elevating gate is either disposed in a retracted position or an extended position. Preferably, a handle clearance impression is formed in a first end of the base plate and a lift clearance impression is formed in a second end thereof. The clearance impressions provide an outline for snapping out a clearance slot. However, handle and lift clearance slots may also be formed in the base plate during manufacture. The clearance slots allow the flat top carrier deck to be retained by a horizontal hand truck.
The Aphasia Communication Outcome Measure: Item Reduction, Scaling, and Concurrent Validity of Self-Reported Communicative Functioning in Aphasia

While there have been many advances over the past 40 years, barriers to effective measurement of functional communication skills in adults with aphasia remain. First, the ability range targeted by current assessments frequently falls below the ability level of many community-dwelling stroke survivors (Frattali, 1992). Second, the burden of assessment associated with most functional communication assessments is high, limiting their use in the current healthcare environment (Worrall, 2001).
Interaural Time Difference Discrimination Thresholds for Single Neurons in the Inferior Colliculus of Guinea Pigs

Sensitivity to changes in the interaural time difference (ITD) of 50 msec tones was measured in single units in the inferior colliculus of urethane-anesthetized guinea pigs. ITD functions were measured with 100 repeats and fine spacing (100 points per cycle). The just noticeable difference (jnd) for ITD was determined using receiver operating characteristic (ROC) analysis of the spike-count distribution at each ITD. The jnd became progressively smaller as the signal frequency increased from 50 to 800 Hz but became unmeasurable above 1 kHz. The lowest jnds (30 μsec) were comparable with human jnds, indicating that there is sufficient information in the firings of individual neurons to permit discrimination without obligatory pooling. ROC analysis requires the choice of a reference ITD from which the jnd may be found by stepping the target ITD through the ITD function. For each neuron the reference was chosen to minimize the jnd. The lowest jnd was usually for ipsilateral leading references, near the minimum of the ITD function where the variance was also low, but where the slope was nearing its steepest. This was despite the peak of the ITD function occurring for contralateral leading stimuli. When the reference ITD was on midline, a jnd could be obtained by looking for firing rates either greater or smaller than the firing rate at midline. The lower jnd was usually obtained by looking for a decrease in firing rate. As duration increased, jnds either decreased or increased, depending on unit type, whereas when level increased, jnds generally increased.
On the unification problem for Cartesian closed categories

An axiomatization of the isomorphisms that hold in all Cartesian closed categories (CCCs), discovered independently by S.V. Soloviev (1983) and by K.B. Bruce and G. Longo (1985), leads to seven equalities. It is shown that the unification problem for this theory is undecidable, thus setting an open question. It is also shown that an important subcase, namely unification modulo the linear isomorphisms, is NP-complete. Furthermore, the problem of matching in CCCs is NP-complete when the subject term is irreducible. CCC-matching and unification form the basis for an elegant and practical solution to the problem of retrieving functions from a library indexed by types investigated by M. Rittri (1990, 1991). It also has potential applications to the problem of polymorphic higher-order unification, which in turn is relevant to theorem proving, logic programming, and type reconstruction in higher-order languages. <<ETX>>
Signature Identification Using Dynamic and HMM Features and KNN Classifier

Dynamic feature-based signature recognition systems obtain more identification accuracy rate than static feature-based signature recognition systems. On the other hand, because of point to point comparing of captured signals, local features produce less error than general features. In this paper, a novel signature identification algorithm based on dynamic and Hidden Markov Models (HMM) features and K-Nearest Neighbor (KNN) classifier is proposed. In this algorithm, special point dynamic features of handwritten signatures are selected and normalized and then used as signature features. In the used HMM, different number of states in transition matrix for each signature are calculated and used as feature vector. This strategy not only reduces complexity computational but also is extracted features based on general characteristics of signature. The proposed algorithm is evaluated on the standard SVC2004 database. The obtained results are reported based on various values of parameters of the proposed algorithm and compared with presented approaches in the literature.
Identification of Key Residues That Confer Rhodobacter sphaeroides LPS Activity at Horse TLR4/MD-2

The molecular determinants underpinning how hexaacylated lipid A and tetraacylated precursor lipid IVa activate Toll-like receptor 4 (TLR4) are well understood, but how activation is induced by other lipid A species is less clear. Species specificity studies have clarified how TLR4/MD-2 recognises different lipid A structures, for example tetraacylated lipid IVa requires direct electrostatic interactions for agonism. In this study, we examine how pentaacylated lipopolysaccharide from Rhodobacter sphaeroides (RSLPS) antagonises human TLR4/MD-2 and activates the horse receptor complex using a computational approach and cross-species mutagenesis. At a functional level, we show that RSLPS is a partial agonist at horse TLR4/MD-2 with greater efficacy than lipid IVa. These data suggest the importance of the additional acyl chain in RSLPS signalling. Based on docking analysis, we propose a model for positioning of the RSLPS lipid A moiety (RSLA) within the MD-2 cavity at the TLR4 dimer interface, which allows activity at the horse receptor complex. As for lipid IVa, RSLPS agonism requires species-specific contacts with MD-2 and TLR4, but the R2 chain of RSLA protrudes from the MD-2 pocket to contact the TLR4 dimer in the vicinity of proline 442. Our model explains why RSLPS is only partially dependent on horse TLR4 residue R385, unlike lipid IVa. Mutagenesis of proline 442 into a serine residue, as found in human TLR4, uncovers the importance of this site in RSLPS signalling; horse TLR4 R385G/P442S double mutation completely abolishes RSLPS activity without its counterpart, human TLR4 G384R/S441P, being able to restore it. Our data highlight the importance of subtle changes in ligand positioning, and suggest that TLR4 and MD-2 residues that may not participate directly in ligand binding can determine the signalling outcome of a given ligand. This indicates a cooperative binding mechanism within the receptor complex, which is becoming increasingly important in TLR signalling.
Transformed Residual Quantization for Approximate Nearest Neighbor Search

The success of product quantization (PQ) for fast nearest neighbor search depends on the exponentially reduced complexities of both storage and computation with respect to the codebook size. Recent efforts have been focused on employing sophisticated optimization strategies, or seeking more effective models. Residual quantization (RQ) is such an alternative that holds the same property as PQ in terms of the aforementioned complexities. In addition to being a direct replacement of PQ, hybrids of PQ and RQ can yield more gains for approximate nearest neighbor search. This motivated us to propose a novel approach to optimizing RQ and the related hybrid models. With an observation of the general randomness increase in a residual space, we propose a new strategy that jointly learns a local transformation per residual cluster with an ultimate goal to reduce overall quantization errors. We have shown that our approach can achieve significantly better accuracy on nearest neighbor search than both the original and the optimized PQ on several very large scale benchmarks.
Using Invariant Detection Mechanism in Black Box Inference

The testing and formal verification of black box software components is a challenging domain. The problem is even harder when specifications of these components are not available. An approach to cope with this problem is to combine testing with learning techniques, such that the learned models of the components can be used to explore unknown implementation and thus facilitate testing efforts. In recent years, we have contributed to this approach by proposing techniques for learning parameterized state machine models and then use them in the integration testing of black box components. The major problem in this technique left unaddressed was the selection of parameter values during the learning process. In this paper, we propose to use an invariant detection mechanism to select values in the learning process, thus refining model inference and testing approach. Initial experiments with small examples yielded positive results.
Recognition of Smart Objects by a Mobile Robot using SIFT-based Image Recognition and Wireless Communication

In this work, we focus on the problem of object location and recognition by an autonomous mobile robot. In our approach, the robot does not have any prior knowledge about the form and multiplicity of the objects. The robot, however, is equipped with an onboard camera and both objects and robot are capable of exchanging data by using a common low-cost, low-rate wireless technology, namely a TmoteSky mote. The small storage memory of the mote is used to store a simple communication protocol and a description of the physical appearance of the object, encoded by means of a set of Scale Invariant Feature Transform (SIFT) descriptors. The mobile robot queries the surrounding smart objects by sending a broadcast query packet through the wireless interface. The smart objects that receive such a query reply by sending their ID and a selection of the SIFTS that describe their appearance. When a subset of the SIFT descriptors extracted by the current image of the robot’s camera matches the SIFT descriptors received from a smart objects, the robot can locate the object in its current view and autonomously navigate towards the object, interacting with it.
Development of Sendai Virus Vectors and their Potential Applications in Gene Therapy and Regenerative Medicine

Gene delivery/expression vectors have been used as fundamental technologies in gene therapy since the 1980s. These technologies are also being applied in regenerative medicine as tools to reprogram cell genomes to a pluripotent state and to other cell lineages. Rapid progress in these new research areas and expectations for their translation into clinical applications have facilitated the development of more sophisticated gene delivery/expression technologies. Since its isolation in 1953 in Japan, Sendai virus (SeV) has been widely used as a research tool in cell biology and in industry, but the application of SeV as a recombinant viral vector has been investigated only recently. Recombinant SeV vectors have various unique characteristics, such as low pathogenicity, powerful capacity for gene expression and a wide host range. In addition, the cytoplasmic gene expression mediated by this vector is advantageous for applications, in that chromosomal integration of exogenous genes can be undesirable. In this review, we introduce a brief historical background on the development of recombinant SeV vectors and describe their current applications in gene therapy. We also describe the application of SeV vectors in advanced nuclear reprogramming and introduce a defective and persistent SeV vector (SeVdp) optimized for such reprogramming.
Communicative Pointing Ameliorates Grasping Deficits after an Inactivation and Lesions of the Ventral Premotor Cortex in Japanese Monkeys ( Macaca fuscata )

Pointing is the most convenient communication in social interaction: its gesture is highly visible and is found in all cultures with the identical form. However, the brain mechanisms of communicative pointing are still unknown. The pointing is, from a psychological point of view, considered to develop from grasping attempt with help from others. Thus, we hypothesized that pointing deficits would appear after lesions of the ventral premotor cortex (PMv) that was fundamental to grasping, and examined whether the pointing would be influenced by the PMv lesions in monkeys. The PMv-lesioned subjects showed deficits in reaching and grasping, and those deficits were, contrary to our expectation, ameliorated through the pointing. A subject with muscimol injection to PMv required 4. 02 sec to obtain food but the time was reduced to 1. 19 sec after communicative pointing. Another subject rarely used one limb after bilateral PMv ablations, but became to grasp food with the hand after the training of communicative pointing. These results suggest that communicative pointing is useful to recover the grasping and reaching deficits induced by PMv lesions.
Using unmanned ground vehicle performance measurements as a unique method of terrain classification

Unmanned vehicles are used to serve as an extension of our ability in environments and situations that we will not or cannot operate in, therefore they must be highly capable and be able to cope with obstacles within their environment. For the Unmanned Ground Vehicle (UGV) one of its biggest obstacles is terrain which can be unpredictable, unstructured and untraversable; which could cause a vehicle to become stuck and render it useless. It is proposed that a system with more knowledge about terrain and its properties will have greater success when operating in unforgiving conditions. This paper discusses the work done towards creating a system capable of sensing and measuring terrain using vehicle performance measurements; which will ultimately help to create a more terrain capable vehicle.