Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Analyses of Gene Expression during Mouse Endochondral Ossification

Background Endochondral ossification is a complex process involving a series of events that are initiated by the establishment of a chondrogenic template and culminate in its replacement through the coordinated activity of osteoblasts, osteoclasts and endothelial cells. Comprehensive analyses of in vivo gene expression profiles during these processes are essential to obtain a complete understanding of the regulatory mechanisms involved. Methodology/Principal Findings To address these issues, we completed a microarray screen of three zones derived from manually segmented embryonic mouse tibiae. Classification of genes differentially expressed between each respective zone, functional categorization as well as characterization of gene expression patterns, cytogenetic loci, signaling pathways and functional motifs both confirmed reported data and provided novel insights into endochondral ossification. Parallel comparisons of the microdissected tibiae data set with our previously completed micromass culture screen further corroborated the suitability of micromass cultures for modeling gene expression in chondrocyte development. The micromass culture system demonstrated striking similarities to the in vivo microdissected tibiae screen; however, the micromass system was unable to accurately distinguish gene expression differences in the hypertrophic and mineralized zones of the tibia. Conclusions/Significance These studies allow us to better understand gene expression patterns in the growth plate and endochondral bones and provide an important technical resource for comparison of gene expression in diseased or experimentally-manipulated cartilages. Ultimately, this work will help to define the genomic context in which genes are expressed in long bones and to understand physiological and pathological ossification.
Navigation and Mapping in Large Unstructured Environments

In this paper we address the problem of autonomous navigation in very large unstructured environments. A new hybrid metric map (HYMM) structure is presented that combines feature maps with other metric representations in a consistent manner. The global feature map is partitioned into a set of connected local triangular regions (LTRs), which provide a reference for a detailed multidimensional description of the environment. The HYMM framework permits the combination of efficient feature-based simultaneous localization and mapping (SLAM) algorithms for localization with, for example, occupancy grid maps for tasks such as obstacle avoidance, path planning or data association. This fusion of feature and grid maps has several complementary properties; for example, grid maps can assist data association and can facilitate the extraction and incorporation of new landmarks as they become identified from multiple vantage points. In this paper we also present a path-planning technique that efficiently maintains the estimated cost of traversing each LTR. The consistency of the SLAM algorithm is investigated with the introduction of exploration techniques to guarantee a certain measure of performance for the estimation process. Experimental results in outdoor environments are presented to demonstrate the performance of the algorithms proposed.
Genome-wide transcription factor activities are explained by intrinsic conformational dynamics of binding-sites and distal flanking-regions

Transcription factors (TFs) recognize small DNA sequence motifs directly or through their sequence-dependent structure. While sequence composition and degeneracy are verified to be the defining factors of TF binding specificity, the role of conformational dynamics of the DNA remains poorly understood. With growing evidence from next generation sequencing (NGS) data suggesting the inadequacy of sequence-only models, alternative models for describing the TF binding preferences are required, wherein the conformational dynamics presents an attractive option. Here, we report a novel method (DynaSeq) which accurately predicts DNA-conformational ensembles for genomic targets of TFs. Using DynaSeq we demonstrate how the dynamics of binding sites and their distal flanking regions can be used to elucidate TF-binding patterns for two model systems: cell type-specific binding of STAT3 and chromatin structural specificity of 3 functional TF classes viz. pioneers, settlers and migrants. We find that TF preferences in both these systems can be accurately explained by the conformational dynamics of their binding sites and their distal flanking DNA regions. Conformational dynamics not only distinguishes binding sites from genomic backgrounds in STAT3; it also points to a modular organization of their surrounding regions. Further, the differential binding modes of STAT3-DNA reveal a potential mechanism of cellular specificity. Our model identifies clear signatures to accurately classify pioneer, migrant and settler TF targets from the dynamics of distal flanking regions. This suggests that the chromatin preferences of TFs are significantly influenced by the intrinsic conformational dynamics of the DNA surrounding the TF binding sites.
The HIV-1 Nef protein as a target for antiretroviral therapy

HIV-1 Nef is a peripheral membrane protein that affects both signal transduction and membrane trafficking in infected cells. Alterations in these cellular processes enhance the efficiency of viral replication and the pathogenesis of AIDS in vivo. The precise mechanisms by which Nef functions are not fully elucidated. Nef is not an enzyme but appears to act as a linker molecule, mediating a variety of protein-protein interactions. Structural, biochemical and mutational data have allowed tentative identification of the key interactive surfaces on Nef, their cellular partners and their roles in Nef activity. Nef contains an SH3-binding surface through which it can interact with cellular Src-family tyrosine kinases and/or activator molecules for small GTPases involved in signal transduction. This SH3-binding surface is important for the ability of Nef to facilitate the activation of host T-lymphocytes, a process which renders the cells more permissive for viral replication. Nef also contains two relatively unstructured, solvent-exposed loops, through which it interacts with the cellular proteins that coat vesicles involved in membrane trafficking. These surfaces are important for Nef-mediated alterations in the subcellular distribution of transmembrane proteins, a process which causes diverse effects, including the assembly of maximally infectious viral particles and viral evasion of the host immune system. These data provide precise molecular targets within the Nef protein. Molecules that bind these interactive surfaces are predicted to inhibit Nef activity and provide the basis for novel chemotherapeutic agents for the treatment of HIV-infection.
Modified reward function on abstract features in inverse reinforcement learning

We improve inverse reinforcement learning (IRL) by applying dimension reduction methods to automatically extract abstract features from human-demonstrated policies, to deal with the cases where features are either unknown or numerous. The importance rating of each abstract feature is incorporated into the reward function. Simulation is performed on a task of driving in a five-lane highway, where the controlled car has the largest fixed speed among all the cars. Performance is almost 10.6% better on average with than without importance ratings.
Retrieving audio recordings using musical themes

In 1948, Barlow and Morgenstern released a collection of about 10,000 themes of well-known instrumental pieces from the corpus of Western Classical music [1]. These monophonic themes (usually four bars long) are often the most memorable parts of a piece of music. In this paper, we report on a systematic study considering a cross-modal retrieval scenario. Using a musical theme as a query, the objective is to identify all related music recordings from a given audio collection. By adapting well-known retrieval techniques, our main goal is to get a better understanding of the various challenges including tempo deviations, musical tunings, key transpositions, and differences in the degree of polyphony between the symbolic query and the audio recordings to be retrieved. In particular, we present an oracle fusion approach that indicates upper performance limits achievable by a combination of current retrieval techniques.
Numerical Simulations of Fractionated Electrograms and Pathological Cardiac Action Potential

The aim of this work is twofold. First we focus on the complex phenomenon of electrogram fractionation, due to the presence of discontinuities in the conduction properties of the cardiac tissue in a bidomain model. Numerical simulations of paced activation may help to understand the role of the membrane ionic currents and of the changes in cellular coupling in the formation of conduction blocks and fractionation of the electrogram waveform. In particular, we show that fractionation is independent of INa alterations and that it can be described by the bidomain model of cardiac tissue. Moreover, some deflections in fractionated electrograms may give nonlocal information about the shape of damaged areas, also revealing the presence of inhomogeneities in the intracellular conductivity of the medium at a distance. The second point of interest is the analysis of the effects of space ‐ time discretization on numerical results, especially during slow conduction in damaged cardiac tissue. Indeed, large discretization steps can induce numerical artifacts such as slowing down of conduction velocity, alteration in extracellular and transmembrane potential waveforms or conduction blocks, which are not predicted by the continuous bidomain model. Several possible numerical and physiological explanations of these effects are given. Essentially, the discrete system obtained at the end of the approximation process may be interpreted as a discrete model of the cardiac tissue made up of isopotential cells where the effective intracellular conductivity tensor depends on the space discretization steps; the increase of these steps results in an increase of the effective intracellular resistance and can induce conduction blocks if a certain critical value is exceeded.
Short-term traffic flow forecasting of urban network based on dynamic STARIMA model

This paper puts forward a hybrid spatio-temporal method of short-term traffic forecasting, i.e., Dynamic Space-Time Autoregressive Integrated Moving Average Model (Dynamic STARIMA). This method combines STARIMA model and Dynamic Turn Ratio Prediction model (DTRP) to enhance the forecasting performance and efficiency on urban intersections. To verify the Dynamic-STARIMA modeling method in real situation, an experimental model is constructed to produce forecasting traffic flow for part of urban network in Beijing, China based on actual data. The prediction accuracy of Dynamic STARIMA model is generally satisfying compared to other forecasting methods, which testifies the advantage and practicability of the proposed model.
A multi-pulse front-end rectifier system with electronic phase-shifting for harmonic mitigation in motor drive applications

In this paper, an electronic phase-shifting strategy has been optimized for a multi-parallel configuration of line-commutated rectifiers with a common dc-bus voltage used in motor drive application. This feature makes the performance of the system independent of the load profile and maximizes its harmonic reduction ability. To further reduce the generated low order harmonics, a dc-link current modulation scheme and its phase shift values of multi-drive systems have been optimized. Analysis and simulations have been carried out to verify the proposed method.
Structural insights into the molecular mechanism of H‐NOX activation

Nitric oxide (NO) signaling in mammals controls important processes such as smooth muscle relaxation and neurotransmission by the activation of soluble guanylate cyclase (sGC). NO binding to the heme domain of sGC leads to dissociation of the iron–histidine (Fe–His) bond, which is required for enzyme activity. The heme domain of sGC belongs to a larger class of proteins called H‐NOX (Heme‐Nitric oxide/OXygen) binding domains. Previous crystallographic studies on H‐NOX domains demonstrate a correlation between heme bending and protein conformation. It was unclear, however, whether these structural changes were important for signal transduction. Subsequent NMR solution structures of H‐NOX proteins show a conformational change upon disconnection of the heme and proximal helix, similar to those observed in the crystallographic studies. The atomic details of these conformational changes, however, are lacking in the NMR structures especially at the heme pocket. Here, a high‐resolution crystal structure of an H‐NOX mutant mimicking a broken Fe–His bond is reported. This mutant exhibits specific changes in heme conformation and major N‐terminal displacements relative to the wild‐type H‐NOX protein. Fe–His ligation is ubiquitous in all H‐NOX domains, and therefore, the heme and protein conformational changes observed in this study are likely to occur throughout the H‐NOX family when NO binding leads to rupture of the Fe–His bond.
ReTrace : Collecting Execution Trace with Virtual Machine Deterministic Replay

Execution trace is an important tool in computer architecture research. Unfortunately, existing trace collection techniques are often slow (due to software tracing overheads) or expensive (due to special tracing hardware requirements). Regardless of the method of collection, detailed trace files are generally large and inconvenient to store and share. We present ReTrace, a trace collection tool based on the deterministic replay technology of the VMware hypervisor. ReTrace operates in two stages: capturing and expansion. ReTrace capturing accumulates the minimal amount of information necessary to later recreate a more detailed execution trace. It captures (records) only non-deterministic events resulting in low time and space overheads (as low as 5% run-time overhead, as low as 0.5 byte per thousand instructions log growth rate) on supported platforms. ReTrace expansion uses the information collected by the capturing stage to generate a complete and accurate execution trace without any data loss or distortion. ReTrace is an experimental feature of VMware Workstation 6.0 currently available in Windows and Linux flavors for commodity IA32 platforms. No special tracing hardware is required. We have three key results. First, we find that trace collection can be done both efficiently and inexpensively. Second, deterministic replay is an effective technique for compressing large trace files. Third, performing the trace collection at the hypervisor layer is minimally invasive to the collected trace while enabling tracing of the entire system (user/supervisor level, CPU, peripheral devices). ReTrace is a rapidly evolving technology. We would like to use this paper to solicit feedback on the applicability of ReTrace in computer architecture research to help us refine our future development plans.
Whither Music IR Evaluation Infrastructure : Lessons to be Learned from TREC

Benchmark tasks are a powerful method for advancing the state of the art in a field. The music information retrieval community recently acknowledged the utility of such tasks by resolving to create an evaluation framework for music information retrieval (MIR) tasks and music digital libraries (MDL). This paper describes the processes used in the Text REtrieval Conference (TREC) evaluations to create information retrieval evaluation infrastructure, reviews assessments of how appropriate the evaluation methodology is for TREC tasks, and makes suggestions regarding the development of an MIR/MDL evaluation framework based on TREC experience.
Expression of Mutant Huntingtin in Leptin Receptor-Expressing Neurons Does Not Control the Metabolic and Psychiatric Phenotype of the BACHD Mouse

Metabolic and psychiatric disturbances occur early on in the clinical manifestation of Huntington’s disease (HD), a neurodegenerative disorder caused by an expanded CAG repeat in the huntingtin (HTT) gene. Hypothalamus has emerged as an important site of pathology and alterations in this area and its neuroendocrine circuits may play a role in causing early non-motor symptoms and signs in HD. Leptin is a hormone that controls energy homeostasis by signaling through leptin receptors in the hypothalamus. Disturbed leptin action is implicated in both obesity and depression and altered circulating levels of leptin have been reported in both clinical HD and rodent models of the disease. Pathological leptin signaling may therefore be involved in causing the metabolic and psychiatric disturbances of HD. Here we tested the hypothesis that expression of mutant HTT in leptin receptor carrying neurons plays a role in the development of the non-motor phenotype in the BACHD mouse model. Our results show that inactivation of mutant HTT in leptin receptor-expressing neurons in the BACHD mouse using cross-breeding based on a cre-loxP system did not have an effect on the metabolic phenotype or anxiety-like behavior. The data suggest that mutant HTT disrupts critical hypothalamic pathways by other mechanisms than interfering with intracellular leptin signaling.
How the credit assignment problems in motor control could be solved after the cerebellum predicts increases in error

We present a cerebellar architecture with two main characteristics. The first one is that complex spikes respond to increases in sensory errors. The second one is that cerebellar modules associate particular contexts where errors have increased in the past with corrective commands that stop the increase in error. We analyze our architecture formally and computationally for the case of reaching in a 3D environment. In the case of motor control, we show that there are synergies of this architecture with the Equilibrium-Point hypothesis, leading to novel ways to solve the motor error and distal learning problems. In particular, the presence of desired equilibrium lengths for muscles provides a way to know when the error is increasing, and which corrections to apply. In the context of Threshold Control Theory and Perceptual Control Theory we show how to extend our model so it implements anticipative corrections in cascade control systems that span from muscle contractions to cognitive operations.
COMPARISON OF OPERATIONAL CLOUD PROPERTIES DERIVED FROM GOME/ERS-2 AND MSG/SEVIRI DATA

We focus on the retrieval of cloud properties appropriate for trace gas retrieval from sun-normalized UV/VIS backscatter spectra obtained from the Global Ozone Monitoring Experiment (GOME) on-board ERS-2. A data fusion technique is applied to calculate the fractional cloud cover of GOME footprints from GOME’s Polarization Measurement Devices (PMDs). Furthermore, cloudtop albedo and cloud-top height are retrieved simultaneously from GOME measurements around the oxygen Aband by a neural network approach. We compare the operationally derived GOME results with corresponding results from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer on-board the first EUMETSAT METEOSAT Second Generation (MSG-1) geostationary spacecraft. Finally we present the latest development of the GOME cloud retrieval algorithms, including the initial results obtained with GOME-2/MetOp in the framework of EUMETSAT’s Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M-SAF).
Autologous hematopoietic cell transplantation for multiple sclerosis: a systematic review

Background and objectives: The purpose of this systematic review was to evaluate the safety and efficacy of autologous hematopoietic cell transplantation in patients with progressive multiple sclerosis (MS) refractory to conventional medical treatment. Methods: Eight case series met our a priori inclusion criteria for the primary outcome of progression-free survival. Individual study quality was rated using an 11-item scale for case series. The strength of the overall body of evidence for each outcome was rated using a system developed by the ECRI Institute. Data from different studies were statistically combined using meta-analysis. An additional six studies were included for a summary of mortality and morbidity. Results: For secondary progressive MS, immunoablative therapy with autologous bone marrow/peripheral blood stem cell transplantation was associated with higher progression-free survival (up to 3 years following treatment) when using intermediate-intensity conditioning regimens compared with high-intensity conditioning regimens. The evidence was insufficient to determine whether the treatment was effective in patients with other types of MS. Treatment-related mortality was about 2.7%. Conclusions: Patients with secondary progressive MS refractory to conventional medical treatment have longer progression-free survival following autologous stem cell transplantation with intermediate-intensity conditioning regimens than with high-intensity conditioning regimens.
EmojiNet: An Open Service and API for Emoji Sense Discovery

This paper presents the release of EmojiNet, the largest machine-readable emoji sense inventory that links Unicode emoji representations to their English meanings extracted from the Web. EmojiNet is a dataset consisting of: (i) 12,904 sense labels over 2,389 emoji, which were extracted from the web and linked to machine-readable sense definitions seen in BabelNet; (ii) context words associated with each emoji sense, which are inferred through word embedding models trained over Google News corpus and a Twitter message corpus for each emoji sense definition; and (iii) recognizing discrepancies in the presentation of emoji on different platforms, specification of the most likely platform-based emoji sense for a selected set of emoji. The dataset is hosted as an open service with a REST API and is available at http://emojinet.knoesis. org/. The development of this dataset, evaluation of its quality, and its applications including emoji sense disambiguation and emoji sense similarity are discussed.