Miracle-dz/UniFAR-FTUs huggingface dataset:
Delivery of steric block morpholino oligomers by (R-X-R)4 peptides: structure–activity studies

Redirecting the splicing machinery through the hybridization of high affinity, RNase H- incompetent oligonucleotide analogs such as phosphoramidate morpholino oligonucleotides (PMO) might lead to important clinical applications. Chemical conjugation of PMO to arginine-rich cell penetrating peptides (CPP) such as (R-Ahx-R)4 (with Ahx standing for 6-aminohexanoic acid) leads to sequence-specific splicing correction in the absence of endosomolytic agents in cell culture at variance with most conventional CPPs. Importantly, (R-Ahx-R)4–PMO conjugates are effective in mouse models of various viral infections and Duchenne muscular dystrophy. Unfortunately, active doses in some applications might be close to cytotoxic ones thus presenting challenge for systemic administration of the conjugates in those clinical settings. Structure–activity relationship studies have thus been undertaken to unravel CPP structural features important for the efficient nuclear delivery of the conjugated PMO and limiting steps in their internalization pathway. Affinity for heparin (taken as a model heparan sulfate), hydrophobicity, cellular uptake, intracellular distribution and splicing correction have been monitored. Spacing between the charges, hydrophobicity of the linker between the Arg-groups and Arg-stereochemistry influence splicing correction efficiency. A significant correlation between splicing correction efficiency, affinity for heparin and ability to destabilize model synthetic vesicles has been observed but no correlation with cellular uptake has been found. Efforts will have to focus on endosomal escape since it appears to remain the limiting factor for the delivery of these splice-redirecting ON analogs.
A subject-specific musculoskeletal modeling framework to predict in vivo mechanics of total knee arthroplasty.

Musculoskeletal (MS) models should be able to integrate patient-specific MS architecture and undergo thorough validation prior to their introduction into clinical practice. We present a methodology to develop subject-specific models able to simultaneously predict muscle, ligament, and knee joint contact forces along with secondary knee kinematics. The MS architecture of a generic cadaver-based model was scaled using an advanced morphing technique to the subject-specific morphology of a patient implanted with an instrumented total knee arthroplasty (TKA) available in the fifth "grand challenge competition to predict in vivo knee loads" dataset. We implemented two separate knee models, one employing traditional hinge constraints, which was solved using an inverse dynamics technique, and another one using an 11-degree-of-freedom (DOF) representation of the tibiofemoral (TF) and patellofemoral (PF) joints, which was solved using a combined inverse dynamic and quasi-static analysis, called force-dependent kinematics (FDK). TF joint forces for one gait and one right-turn trial and secondary knee kinematics for one unloaded leg-swing trial were predicted and evaluated using experimental data available in the grand challenge dataset. Total compressive TF contact forces were predicted by both hinge and FDK knee models with a root-mean-square error (RMSE) and a coefficient of determination (R2) smaller than 0.3 body weight (BW) and equal to 0.9 in the gait trial simulation and smaller than 0.4 BW and larger than 0.8 in the right-turn trial simulation, respectively. Total, medial, and lateral TF joint contact force predictions were highly similar, regardless of the type of knee model used. Medial (respectively lateral) TF forces were over- (respectively, under-) predicted with a magnitude error of M < 0.2 (respectively > -0.4) in the gait trial, and under- (respectively, over-) predicted with a magnitude error of M > -0.4 (respectively < 0.3) in the right-turn trial. Secondary knee kinematics from the unloaded leg-swing trial were overall better approximated using the FDK model (average Sprague and Geers' combined error C = 0.06) than when using a hinged knee model (C = 0.34). The proposed modeling approach allows detailed subject-specific scaling and personalization and does not contain any nonphysiological parameters. This modeling framework has potential applications in aiding the clinical decision-making in orthopedics procedures and as a tool for virtual implant design.
Improved Bounded Matrix Completion for Large-Scale Recommender Systems

Matrix completion is a widely used technique for personalized recommender systems. In this paper, we focus on the idea of Bounded Matrix Completion (BMC) which imposes bounded constraints into the standard matrix completion problem. It has been shown that BMC works well for several real world datasets, and an efficient coordinate descent solver called BMA has been proposed in [R. Kannan and Park. , 2012]. However, we observe that BMA can sometimes converge to nonstationary points, resulting in a relatively poor accuracy in those cases. To overcome this issue, we propose our new approach for solving BMC under the ADMM framework. The proposed algorithm is guaranteed to converge to stationary points. Experimental results on real world datasets show that our algorithm can reach a lower objective function value, obtain a higher prediction accuracy and have better scalability compared with existing bounded matrix completion approaches. Moreover, our method outperforms the state-of-art standard matrix factorization in terms of prediction error in many real datasets.
Distributed partition-based optimization via dual decomposition

In this paper we consider a novel partition-based framework for distributed optimization in peer-to-peer networks. In several important applications the agents of a network system have to solve an optimization problem with two important features: (i) the dimension of the decision variable is a function of the network size, and (ii) the cost function and the constraints have a sparsity structure that is related to the sparsity of the graph. For this class of problems a straightforward application of existing methods would result in all the nodes reaching consensus on the minimizer. This approach has two inefficiencies: poor scalability and redundancy of shared information. Indeed, the dimension of the vector stored by each node and the size of the local problem to be solved depend on the network size. Furthermore, all the nodes compute the entire solution. In this paper we provide a preliminary contribution in developing and analyzing novel partition based algorithms. We propose a partition-based algorithm based on dual decomposition. We show that, exploiting the problem structure, the solution can be partitioned among the nodes so that each node stores a local copy of just a portion of the decision variable (rather than a copy of the entire decision vector) and solves a small scale local problem.
Graph expansion and the unique games conjecture

The edge expansion of a subset of vertices S ⊆ V in a graph G measures the fraction of edges that leave S. In a d-regular graph, the edge expansion/conductance Φ(S) of a subset S ⊆ V is defined as Φ(S) = (|E(S, V\S)|)/(d|S|). Approximating the conductance of small linear sized sets (size δ n) is a natural optimization question that is a variant of the well-studied Sparsest Cut problem. However, there are no known algorithms to even distinguish between almost complete edge expansion (Φ(S) = 1-ε), and close to 0 expansion. In this work, we investigate the connection between Graph Expansion and the Unique Games Conjecture. Specifically, we show the following: We show that a simple decision version of the problem of approximating small set expansion reduces to Unique Games. Thus if approximating edge expansion of small sets is hard, then Unique Games is hard. Alternatively, a refutation of the UGC will yield better algorithms to approximate edge expansion in graphs. This is the first non-trivial "reverse" reduction from a natural optimization problem to Unique Games. Under a slightly stronger UGC that assumes mild expansion of small sets, we show that it is UG-hard to approximate small set expansion. On instances with sufficiently good expansion of small sets, we show that Unique Games is easy by extending the techniques of [4].
Human recognition of a partner robot based on relevance theory and neuro-fuzzy computing

This paper proposes a human recognition method of a partner robot for natural communication with human. Basically, human recognition is performed by using various types of information. In this paper, we use the color image of human face and pattern of conversation with the human. The proposed method is composed of k-means algorithm, spiking neural network, self-organizing map, and steady-state genetic algorithm. Furthermore, we show experimental results of the partner robot based on the proposed method.
Connections between layer 4B of area 17 and the thick cytochrome oxidase stripes of area 18 in the squirrel monkey

In area 18 of the primate visual cortex, staining for the mitochondrial enzyme cytochrome oxidase reveals 3 types of stripelike subdivisions running perpendicular to the 17/18 border: thick, thin, and pale stripes. In a previous paper (Livingstone and Hubel, 1984), we described the anatomical connections with area 17 of 2 of these 3 subdivisions, but we did not have any conclusive information on the third subdivision, the thick stripes. Here we report that, in the squirrel monkey, the main input to the thick stripes from area 17 arises from layer 4B. Layer 4B receives its input from the magnocellular division of the lateral geniculate body by way of layer 4C alpha; the thick stripes therefore probably belong to the magnocellular subdivision of the visual pathway.
Multiscale 3D edge representation of volume data by a DOG wavelet

This paper proposes a method to expand volume data into the 3D DOG (D#wence of Gaz~~s&ns) functions by using the frame theory of non-orthogonal wavclcts. The spherically symmetric fcaturc of the 3D DOG fnnction is suitable for the visualization methods based on the volume density projection. Since the DOG function approximates a V”G (Laplacian of Gaussian) fnnction, the rcprcscntation can bc consiclcrcd as a hierarchy of the 3D cclgcs on diffcrcnt scales. Thcrcforc WC can cnhancc the cdgc information at will by blending the projection images on cliffcrcnt scales. Since the wavclct cocfficicnts have significant value whcrc the volume dcnsity changes, WC may nsc this rcprcscntation method for the cnhanccmcnt of the biomedical fcaturcs and also can WC it as a data compression method by ncglccting the insignificant coctficicnts. WC will apply onr rcprcscntation method to medical CT volume data and show the cfficicncy in &scribing the spatial structnrc of the volume.
Alitheia Core: An extensible software quality monitoring platform

Research in the fields of software quality and maintainability requires the analysis of large quantities of data, which often originate from open source software projects. Pre-processing data, calculating metrics, and synthesizing composite results from a large corpus of project artefacts is a tedious and error prone task lacking direct scientific value. The Alitheia Core tool is an extensible platform for software quality analysis that is designed specifically to facilitate software engineering research on large and diverse data sources, by integrating data collection and preprocessing phases with an array of analysis services, and presenting the researcher with an easy to use extension mechanism. The system has been used to process several projects successfully, forming the basis of an emerging ecosystem of quality analysis tools.
A Rolling Shutter Compliant Method for Localisation and Reconstruction

Nowadays Rolling shutter CMOS cameras are embedded on a lot of devices. This type of cameras does not have its retina exposed simultaneously but line by line. The resulting distortions affect structure from motion methods developed for global shutter, like CCD cameras. The bundle adjustment method presented in this paper deals with rolling shutter cameras. We use a projection model which considers pose and velocity and need 6 more parameters for one view in comparison to the global shutter model. We propose a simplified model which only considers distortions due to rotational speed. We compare it to the global shutter model and the full rolling shutter one. The model does not need any condition on the inter-frame motion so it can be applied to fully independent views, even with global shutter images equivalent to a null velocity. Results with both synthetic and real images shows that the simplified model can be considered as a good compromise between a correct geometrical modelling of rolling shutter effects and the reduction of the number of extra parameters. Keywords
Specimens from Biopsies of Colorectal Polyps Often Harbor Additional Diagnoses

Objectives. The utility of examining specimens from colorectal biopsies of polyps for nonneoplastic diseases is currently unknown. Our objectives were to characterize such additional diagnoses that could be rendered. Methods. We retrospectively and prospectively reviewed specimens from endoscopic biopsies of colorectal polyps obtained during routine screening or surveillance. Results. 17 of 168 specimens (10.1%) contained additional diagnoses, including schistosomiasis, eosinophilic colitis, intestinal spirochetosis, melanosis coli, and other entities. These findings were easily overlooked because they often affected mucosa that was spared by the polyps or were often evident only at high magnification. Schistosomiasis, eosinophilic colitis, and intestinal spirochetosis were clinically occult. Conclusions. Specimens from biopsies of colorectal polyps often harbor other diagnoses, in addition to polyps, and can be simultaneously screened for polyps and examined for nonneoplastic diseases. Detection of other diagnoses in addition to polyps requires awareness, examination at high magnification, and examination of areas spared by the polyps.
Cooperative Secure Beamforming for AF Relay Networks With Multiple Eavesdroppers

This letter studies cooperative secure beamforming for amplify-and-forward (AF) relay networks in the presence of multiple eavesdroppers. Under both total and individual relay power constraints, we propose two schemes, namely secrecy rate maximization (SRM) beamforming and null-space beamforming. In the first scheme, our design problem is based on SRM. Using a suboptimal, but convex, technique-semidefinite relaxation (SDR), we show that this problem can be handled by performing a one-dimensional search which involves solving a sequence of semidefinite programs (SDPs). To reduce the complexity, in the second scheme, we instead maximize the information rate at the destination while completely eliminating the information leakage to all eavesdroppers. We prove that this problem can be exactly solved by SDR with one SDP only. Simulation results demonstrate the performance gains of the two proposed designs.
Does Your Cohort Matter? Measuring Peer Effects in College Achievement

To estimate peer effects in college achievement we exploit a unique dataset in which individuals have been exogenously assigned to peer groups of about 30 students with whom they are required to spend the majority of their time interacting. This feature enables us to estimate peer effects that are more comparable to changing the entire cohort of peers. Using this broad peer group, we find academic peer effects of much larger magnitude than found in previous studies that have measured peer effects among roommates alone. We find the peer effects persist at a diminishing rate into the sophomore, junior, and senior years, indicating social network peer effects may have long lasting effects on academic achievement. Our findings also suggest that peer effects may be working through study partnerships versus operating through establishment of a social norm of effort.
Service Oriented Architecture (SOA) Adoption Phases: A Case Study

The paper argues that attitudes to SOA follow a typical hype cycle from Technological Trigger, Peak of Inflated Expectations, and a Trough of Disillusionment to the more recent realisation that SOA is a concept that may offer certain benefits but has several limitations. The main research question studies how the attitude to SOA changes in various phases of the hype cycle, how the SOA implementation cycle and an increase in business process maturity (BPMa) are interconnected and which factors influence the transition between the hype cycle phases. The paper shows that an organization’s success with implementing SOA depends on its ability to match the SOA implementation with an increase in BPMa. The dual purpose of implementing SOA is shown in the first framework: to assure the coherence of IT assets and to assure business/IT alignment. In the second framework, the interconnection of SOA and BPMa and its role in transiting through the hype cycle phases is outlined. The findings are analysed using a longitudinal case study of a large Slovenian company.
Estimation of the light source distribution and its use in integrated shape recovery from stereo and shading

The authors deal with estimation of the light source distribution and its use in surface shape estimation by the methods of stereo and shading. There are many advantages to integrating stereo and shading information. However, shape from shading algorithms are limited in their applicability by the assumption of overly simplistic models of the light source distribution. A more complete representation is described in which the lighting model makes use of multiple fixed point sources located at infinity. Methods of estimating the model parameters are developed, and a method of estimating the surface shape given the albedo and source distribution is presented. The shading algorithm is combined with a stereo algorithm in an integrated approach that is designed to handle albedo variations through the use of color images. <<ETX>>
The Combination of RAD001 and MK-2206 Exerts Synergistic Cytotoxic Effects against PTEN Mutant Gastric Cancer Cells: Involvement of MAPK-Dependent Autophagic, but Not Apoptotic Cell Death Pathway

In the current study, we showed that the combination of mammalian target of rapamycin (mTOR) inhibitor RAD001 (everolimus) and Akt inhibitor MK-2206 exerted synergistic cytotoxic effects against low-phosphatase and tensin homolog (PTEN) gastric cancer cells (HGC-27 and SNU-601 lines). In HGC-27 cells, RAD001 and MK-2206 synergistically induced G1/S cell cycle arrest, growth inhibition, cell death but not apoptosis. RAD001 and MK-2206 synergistically induced light chain 3B (LC3B) and beclin-1 expression, two important autophagy indicators. Meanwhile, the autophagy inhibitor 3-methyladenine (3-MA) and chloroquine inhibited the cytotoxic effects by RAD001 and MK-2206, suggesting that autophagic, but not apoptotic cell death was important for the cytotoxic effects by the co-administration. We observed that the combination of RAD001 and MK-2206 exerted enhanced effects on Akt/mTOR inhibition, cyclin D1 down-regulation and ERK/MAPK(extracellular signal-regulated kinase/mitogen-activated protein kinases) activation. Intriguingly, MEK/ERK inhibitors PD98059 and U0126 suppressed RAD001 plus MK-2206-induced beclin-1 expression, autophagy induction and cytotoxicity in HGC-27 cells. In conclusion, these results suggested that the synergistic anti-gastric cancer cells ability by RAD001 and MK-2206 involves ERK-dependent autophagic cell death pathway.
Impulse: Memory system support for scientific applications

Impulse is a new memory system architecture that adds two important features to a traditional memory controller. First, Impulse supports application-specific optimizations through configurable physical address remapping. By remapping physical addresses, applications control how their data is accessed and cached, improving their cache and bus utilization. Second, Impulse supports prefetching at the memory controller, which can hide much of the latency of DRAM accesses. Because it requires no modification to processor, cache, or bus designs, Impulse can be adopted in conventional systems. In this paper we describe the design of the Impulse architecture, and show how an Impulse memory system can improve the performance of memory-bound scientific applications. For instance, Impulse decreases the running time of the NAS conjugate gradient benchmark by 67%. We expect that Impulse will also benefit regularly strided, memory-bound applications of commercial importance, such as database and multimedia programs.
Blind separation of binaural sound mixtures using SIMO-ICA with self-generator for initial filter

In this paper, we address the blind separation problem of binaural mixed signals, and propose a novel blind separation method using Single-Input-Multiple-Output-model-based independent component analysis (SIMO-ICA) with a self-generator (SG) for the initial filter. SIMO-ICA which has been proposed by the authors can separate mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources as they are at the microphones. Although this attractive feature of SIMO-ICA is beneficial to the binaural sound separation, SIMO-ICA has a serious drawback in its high sensitivity to the initial settings of the separation filter. In the proposed method, the SG functions as the preprocessor of SIMO-ICA, and it can provide a valid initial filter for SIMO-ICA. To evaluate its effectiveness, binaural sound separation experiments are carried out under a reverberant condition. The experimental results reveal that the separation performance of the proposed method is superior to those of conventional methods.
QRP06-1: Estimating Flow Rate from Sampled Packet Streams for Detection of Performance Degradation at TCP Flow Level

A method of estimating TCP flow-rates of sampled flows through packet sampling is described in this paper. We use sequence numbers of sampled packets, which make it possible to improve markedly the accuracy of estimating the flow rates. Using an analytical model, we investigate how to set parameters such as packet sampling probability used in this method of estimation. As a remarkable result, we show that the estimation accuracy improves as the sampling probability decreases. Using measured data, we also show that this method gives accurate estimations. We also show that this estimation method enables us to detect performance degradation at the TCP flow level.
An analysis framework for search sequences

In this paper we present a general framework to study sequences of search activities performed by a user. Our framework provides (i) a vocabulary to discuss types of features, models, and tasks, (ii) straightforward feature re-use across problems, (iii) realistic baselines for many sequence analysis tasks we study, and (iv) a simple mechanism to develop baselines for sequence analysis tasks beyond those studied in this paper. Using this framework we study a set of fourteen sequence analysis tasks with a range of features and models. While we show that most tasks benefit from features based on recent history, we also identify two categories of "sequence-resistant" tasks for which simple classes of local features perform as well as richer features and models.