Miracle-dz/UniFAR-FTUs huggingface dataset:
Conditioning of native substrates by chondroitin sulfate proteoglycans during cardiac mesenchymal cell migration

It is generally proposed that embryonic mesenchymal cells use sulfated macromolecules during in situ migration. Attempts to resolve the molecular mechanisms for this hypothesis using planar substrates have been met with limited success. In the present study, we provide evidence that the functional significance of certain sulfated macromolecules during mesenchyme migration required the presence of the endogenous migratory template; i.e., native collagen fibrils. Using three-dimensional collagen gel lattices and whole embryo culture procedures to produce metabolically labeled sulfated macromolecules in embryonic chick cardiac tissue, we show that these molecules were primarily proteoglycan (PG) in nature and that their distribution was class specific; i.e., heparan sulfate PG, the minor labeled component (15%), remained pericellular while chondroitin sulfate (CS) PG, the predominately labeled PG (85%), was associated with collagen fibrils as "trails" of 50-60-nm particles when viewed by scanning electron microscopy. Progressive "conditioning" of collagen with CS-PG inhibited the capacity of the template to support subsequent cell migration. Lastly, metabolically labeled, PG-derived CS chains were compared with respect to degree of sulfation in either the C-6 or C-4 position by chromatographic separation of chondroitinase AC digestion products. Results from temporal and regional comparisons of in situ-labeled PGs indicated a positive correlation between the presence of mesenchyme and an enrichment of disaccharide-4S relative to that from regions lacking mesenchyme (i.e., principally myocardial tissue). The suggestion of a mesenchyme-specific CS-PG was substantiated by similarly examining the PGs synthesized solely by cardiac mesenchymal cells migrating within hydrated collagen lattice in culture. These data were incorporated into a model of "substratum conditioning" which provides a molecular mechanism by which secretion of mesenchyme-specific CS-PGs not only provides for directed and sustained cell movement, but ultimately inhibits migration of the cell population as a whole.
Communicating by Cosets and Applications to Broadcast

We describe a constructive coset-based coding framework for the general broadcast problem. Our construction is inspired by the information-theoretic framework of Marton [16], who used the concept of random binning to provide the best-known achievable broadcast region to date. Our approach leverages our recent coset-based construction for the Slepian-Wolf coding problem. The key enabling idea is to use cosets of codes to communicate. For the special case of degraded broadcast, our approach has the practical advantage of not compromising the privacy of the message sets of the individual users, with no user being able to decode any other user’s message. A recent work [6] demonstrated that it is possible to apply the framework of Costa [7] into more general cases beyond the strictly Gaussian case. We describe a Trellis-based coset coding framework based on our previous work on the dual problem [15] which illustrates signal design for broadcast inspired by our previous work in source coding with side information, and provide encouraging preliminary simulation results that validate the efficacy of our approach.
Bounding Performance Loss in Approximate MDP Homomorphisms

We define a metric for measuring behavior similarity between states in a Markov decision process (MDP), which takes action similarity into account. We show that the kernel of our metric corresponds exactly to the classes of states defined by MDP homomorphisms (Ravindran & Barto, 2003). We prove that the difference in the optimal value function of different states can be upper-bounded by the value of this metric, and that the bound is tighter than previous bounds provided by bisimulation metrics (Ferns et al. 2004, 2005). Our results hold both for discrete and for continuous actions. We provide an algorithm for constructing approximate homomorphisms, by using this metric to identify states that can be grouped together, as well as actions that can be matched. Previous research on this topic is based mainly on heuristics.
Multiple Color and Depth Video Coding Using a Hierarchical Representation

This paper presents coding schemes for multiple color and depth video using a hierarchical representation. We use the concept of layered depth image (LDI) to represent and process multiview video with depth. After converting those data to the proposed representation, we encode color, depth, and auxiliary data representing the hierarchical structure, respectively. Two kinds of preprocessing approaches are proposed for multiple color and depth components. In order to compress auxiliary data, we have employed a near lossless coding method. Finally, we have reconstructed the original viewpoints successfully from the decoded LDI frames. From our experiments, we realize that the proposed approach is useful for dealing with multiple color and depth data simultaneously.
Secreted Frizzled-related Protein 2 (sFRP2) Redirects Non-canonical Wnt Signaling from Fz7 to Ror2 during Vertebrate Gastrulation*

Convergent extension movements during vertebrate gastrulation require a balanced activity of non-canonical Wnt signaling pathways, but the factors regulating this interplay on the molecular level are poorly characterized. Here we show that sFRP2, a member of the secreted frizzled-related protein (sFRP) family, is required for morphogenesis and papc expression during Xenopus gastrulation. We further provide evidence that sFRP2 redirects non-canonical Wnt signaling from Frizzled 7 (Fz7) to the receptor tyrosine kinase-like orphan receptor 2 (Ror2). During this process, sFRP2 promotes Ror2 signal transduction by stabilizing Wnt5a-Ror2 complexes at the membrane, whereas it inhibits Fz7 signaling, probably by blocking Fz7 receptor endocytosis. The cysteine-rich domain of sFRP2 is sufficient for Ror2 activation, and related sFRPs can substitute for this function. Notably, direct interaction of the two receptors via their cysteine-rich domains also promotes Ror2-mediated papc expression but inhibits Fz7 signaling. We propose that sFRPs can act as a molecular switch, channeling the signal input for different non-canonical Wnt pathways during vertebrate gastrulation.
Spread : A Remote Collaboration Architecture for Domain Specific Modeling

Domain-Specific Modeling Languages (DSMLs) are graphical modeling languages designed to mirror the notations and terminology of a particular target domain. This paper presents an approach, called Spread, to create a generalized remote collaboration framework for DSML modeling. Spread allows metaprogrammable modeling environments to use a common remoting framework across a diverse set of DSML languages, despite differences in the terminology, structure, and semantics of each language.
Effect van het leerklimaat en werktevredenheid op de organisatiebetrokkenheid en OCB van medewerkers.

Het hebben en behouden van betrokken medewerkers is voor een organisatie erg belangrijk omdat het de prestaties van medewerkers positief beinvloed. Daarnaast zorgt een hoge mate van betrokkenheid voor organizational citizenship behavior (OCB), gedrag van medewerkers wat een positief effect heeft op het functioneren van een organisatie. Organisatiebetrokkenheid en OCB kunnen o.a. worden beinvloed door de mate van werktevredenheid en het leerklimaat binnen de organisatie. Onbekend is welke aspecten van het leerklimaat belangrijk zijn voor het verhogen van organisatiebetrokkenheid en of werktevredenheid hier een medierende rol in speelt. Om dit te onderzoeken werd er onder medewerkers van tien Nederlands organisaties (N=204) een vragenlijst uitgezet. Uit de resultaten blijkt dat affectieve betrokkenheid een zeer belangrijke, verbindende rol speelt in het onderzoek. Het is namelijk de belangrijkste voorspeller van OCB, het wordt direct beinvloed door werktevredenheid en indirect door leerklimaat, via werktevredenheid. Met deze medierende rol van werktevredenheid wordt het belang van medewerkerstevredenheidsonderzoeken onderstreept. Voor vervolgonderzoek is het daarom interessant om naast een onderscheid in de dimensies van leerklimaat, zoals is gedaan in dit onderzoek, ook te focussen op de specifieke facetten van werktevredenheid en welke belangrijke voorspellers zijn voor betrokkenheid dan wel OCB.
Fast Identification n-Widths and Quasianalytic Inputs for Continuous LTI Systems

The problem of fast identification is investigated for continuous-time systems in both the H¿ and L1 norms. It is shown that although in the noise free case it is possible to identify a stable (possibly infinite dimensional) LTI system accurately on any interval using quasianalytic inputs, the identification speed is limited when the measurements are corrupted by noise.
Mapping Auto-context Decision Forests to Deep ConvNets for Semantic Segmentation

We consider the task of pixel-wise semantic segmentation given a small set of labeled training images. Among two of the most popular techniques to address this task are Decision Forests (DF) and Neural Networks (NN). In this work, we explore the relationship between two special forms of these techniques: stacked DFs (namely Auto-context) and deep Convolutional Neural Networks (ConvNet). Our main contribution is to show that Auto-context can be mapped to a deep ConvNet with novel architecture, and thereby trained end-to-end. This mapping can be used as an initialization of a deep ConvNet, enabling training even in the face of very limited amounts of training data. We also demonstrate an approximate mapping back from the refined ConvNet to a second stacked DF, with improved performance over the original. We experimentally verify that these mappings outperform stacked DFs for two different applications in computer vision and biology: Kinect-based body part labeling from depth images, and somite segmentation in microscopy images of developing zebrafish. Finally, we revisit the core mapping from a Decision Tree (DT) to a NN, and show that it is also possible to map a fuzzy DT, with sigmoidal split decisions, to a NN. This addresses multiple limitations of the previous mapping, and yields new insights into the popular Rectified Linear Unit (ReLU), and more recently proposed concatenated ReLU (CReLU), activation functions.
An Infrared Network for Mobile Computers

The infrared network provides a flexible infrastructure for research into wireless mobile computing. The network consists of a collection of room-sized cells each wired with a base station transceiver. Mobile computers communicate with transceivers through a carrier sense multiple access (CSMA) protocol and act as terminals for applications executing on remote hosts. Each mobile computer is represented by a proxy, or agent, accessible to applications at a fixed network address. In the system it is the agent that is responsible for delivering requests to its corresponding mobile computer, and tracking the mobile as it moves from cell to cell.
Author identification using Sequential Minimal Optimization

Author identification is a substantial factor in the global economic loss due to computer-related crimes. According to the Center for Strategic and International Studies (CSIS), computer crimes or cyber-crimes cost the global economy an estimated 375 to 575 billion dollars each year [1]. Recently, various techniques have been used to improve the accuracy of author identification. In this paper, we propose combining unigram features and a variety of stylometric features that include n-grams and part-of-speech. Using a Reuters Corpus dataset of 2,500 unique articles (50 authors with 50 news articles each), we were able to effectively capture a non-topic sensitive sample. Results with the Weka machine learning software produced classification accuracies ranging from 76.08 to 84.88 percent using classification techniques such as Random Forest and Sequential Minimal Optimization (SMO). Weka also ranked and weighted the most influential feature attributes.
Improving LVCSR System Combination Using Neural Network Language Model Cross Adaptation

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple subsystems developed at different sites. Cross system adaptation can be used as an alternative to direct hypothesis level combination schemes such as ROVER. The standard approach involves only cross adapting acoustic models. To fully exploit the complimentary features among sub-systems, language model (LM) cross adaptation techniques can be used. Previous research on multi-level n-gram LM cross adaptation is extended to further include the cross adaptation of neural network LMs in this paper. Using this improved LM cross adaptation framework, significant error rate gains of 4.0%-7.1% relative were obtained over acoustic model only cross adaptation when combining a range of Chinese LVCSR sub-systems used in the 2010 and 2011 DARPA GALE evaluations. Copyright © 2011 ISCA.
Itraconazole solid dispersion prepared by a supercritical fluid technique: preparation, in vitro characterization, and bioavailability in beagle dogs

This research aimed to develop a supercritical fluid (SCF) technique for preparing a particulate form of itraconazole (ITZ) with good dissolution and bioavailability characteristics. The ITZ particulate solid dispersion was formulated with hydroxypropyl methylcellulose, Pluronic F-127, and L-ascorbic acid. Aggregated particles showed porous structure when examined by scanning electron microscopy. Powder X-ray diffraction and Fourier transform infrared spectra indicated an interaction between ITZ and excipients and showed that ITZ existed in an amorphous state in the composite solid dispersion particles. The solid dispersion obtained by the SCF process improved the dissolution of ITZ in media of pH 1.0, pH 4.5, and pH 6.8, compared with a commercial product (Sporanox®), which could be ascribed to the porous aggregated particle shape and amorphous solid state of ITZ. While the solid dispersion did not show a statistical improvement (P=0.50) in terms of oral bioavailability of ITZ compared with Sporanox®, the Cmax (the maximum plasma concentration of ITZ in a pharmacokinetic curve) of ITZ was raised significantly (P=0.03) after oral administration. Thus, the SCF process has been shown to be an efficient, single step process to form ITZ-containing solid dispersion particles with good dissolution and oral bioavailability characteristics.
Multi-Task Learning Using Mismatched Transcription for Under-Resourced Speech Recognition

It is challenging to obtain large amounts of native (matched) labels for audio in under-resourced languages. This could be due to a lack of literate speakers of the language or a lack of universally acknowledged orthography. One solution is to increase the amount of labeled data by using mismatched transcription, which employs transcribers who do not speak the language (in place of native speakers), to transcribe what they hear as nonsense speech in their own language (e.g., Mandarin). This paper presents a multi-task learning framework where the DNN acoustic model is simultaneously trained using both a limited amount of native (matched) transcription and a larger set of mismatched transcription. We find that by using a multi-task learning framework, we achieve improvements over monolingual baselines and previously proposed mismatched transcription adaptation techniques. In addition, we show that using alignments provided by a GMM adapted by mismatched transcription further improves acoustic modeling performance. Our experiments on Georgian data from the IARPA Babel program show the effectiveness of the proposed method.
Use of a Peritoneal Dialysis Remote Monitoring System in India

Peritoneal dialysis (PD) as treatment for patients with end-stage renal disease (ESRD) was adopted in India only in the mid 1990s. That timing was a result of initial misgivings about the viability of a home dialysis therapy in a predominantly rural, geographically vast country, with poor connectivity and access to health care, difficult sanitary conditions, and a tropical climate; however, the PD modality has shown impressive growth since then (1–3). By conservative estimate, about 250 of approximately 1000 nephrologists now prescribe PD to more than 6500 patients (4). This growth contrasts with the prevailing declining trend seen in most Western countries, including the United States, which has experienced a drop in the PD utilization rate to 7% in 2010 from 14% in 1995. Today, a major challenge affecting the acceptance and outcomes of PD is the perceived “inaccessibility” on the part of the patient to the nephrologist and to the “mother unit” (MU)—more so in geographically large countries with remote and inaccessible habitations, as typified by India, the United States, and Canada, among others. Our PD unit has worked to innovate with practical and costeffective solutions to overcome this barrier (5). Rapid strides in communications connectivity have been made across the world: Internet and mobile phone technology now truly penetrate almost every geographic and socio-economic boundary extant, especially in India. We are using the mobile phone Short Messaging Service, inexpensive digital cameras, and the World Wide Web to address specific patient accessibility needs. Those technologies—coupled with a dedicated PD team (comprising medical and paramedical staff) and a regular home visit protocol (6)—have enabled us to develop a unique PD remote monitoring system. Patients are constantly in touch with their MU and nephrologist, communicating in real time, around the clock, with improved PD outcomes, especially in rural patients (7).
Development of laser range finder-implemented JAUS-compliant local pose component

Accurate and stable localization is one of most important autonomous mobile robot functions. To achieve accurate and stable localization, we employed an additional laser range finder to accurately estimate local position using a simultaneous location and mapping (SLAM) technique. In this paper, we describe the implementation of a Joint Architecture for Unmanned Systems (JAUS)-compliant local pose component in order to validate the proposed localization algorithm. In both simulation and actual experiments, the local pose component was validated.
Resource-Definition Policies for Autonomic Computing

The paper introduces a framework for the formal specification of autonomic computing policies, and uses it to define a new type of autonomic computing policy termed a resource-definition policy. We describe the semantics of resource-definition policies, explain how they can be used as a basis for the development of autonomic system of systems, and present a sample data-centre application built using the new policy type.
Design and simulation of a quaternary memory cell based on a physical memristor

Memristors were theorized more than fifty years ago, but only recently physical devices with memristor's behavior have been fabricated and shipped. In this work, we experiment on one of these physical memristors by designing a memristor-based memory cell, implementing the cell, and testing it. Our experiments demonstrate that the memristor technology is not yet mature for practical applications, but, nevertheless, when production will provide reliable and dependable devices, memristor-based memory systems may replace CMOS memories with some advantages.
The cannabinoid CB1 receptor is involved in the anxiolytic, sedative and amnesic actions of benzodiazepines

Previous studies in our laboratory showed that cannabinoid CB1 receptor knockout mice (CB1-/-) presented increased anxiety-like behaviours that did not respond to the anxiolytic actions of benzodiazepines. These results suggest that the pharmacological effects of benzodiazepines may involve the participation of cannabinoid CB1 receptors. Therefore, the purpose of this study was to examine the effects of alprazolam and the cannabinoid CB1 receptor antagonist AM251 on behavioural assays (light—dark box test, neurological severity score and step-down inhibitory avoidance test) and on the functional activity of the CB1 receptor (WIN-55,212-stimulated [35S] guanosine triphosphate (GTP) γ binding autoradiography). The administration of alprazolam (40 μg/kg, intraperitoneal (i.p.)) decreased anxiety-like behaviours in the light—dark box test and significantly reduced WIN-55,212-stimulated [35S]GTPγ binding autoradiography in the amygdala and in the CA1 field of the hippocampus, but was without effects on CA2, CA3 and the dentate gyrus (DG) of the hippocampus. The administration of AM251 (3 mg/kg, i.p.) blocked the anxiolytic action of alprazolam (40 μg/kg, i.p.), significantly reduced the sedative (ataxia, neurological severity score in the 0.5 cm bar) and the amnesic actions (short time term memory (1 h after electric shock)) of alprazolam (0.5 mg/kg, i.p.). Taken together, these findings revealed that cannabinoid CB1 receptor plays a pivotal role in the pharmacological actions of benzodiazepines. Furthermore, these results suggest that blockade of cannabinoid CB1 receptors may be useful in the treatment of patients with problems related to the consumption of benzodiazepines. Further clinical trials are needed to test this hypothesis.
Using Classification in the Preprocessing Step on Wi-Fi Data as an Enabler of Physical Analytics

In this research we present a remote localization technique as an essential preprocessing step to enable Physical Analytics in the retail and hospitality sector. We studied two crowdsourced Wi-Fi data sources as potential inputs for fingerprinting-based positioning systems. These sources are non intrusively crowdsourced and can be easily acquired at almost any retail store. We evaluated our hypothesis on large, real-world datasets using statistical and machine learning techniques. With the use of these sources, we built a fingerprinting-based positioning system that achieved reliable and accurate physical positioning results. Our method is capable of estimating positions without any prior knowledge about the store plan or the antennas' location with, only one off-the-shelf access point. Unlike other positioning techniques, instead of estimating a relative position of a device from an antenna, we provide an absolute position for a device as inside or outside of a venue without making any assumption about the site nor the positioned devices. To investigate its practicality, we evaluated our method with datasets of five different stores.
FlowFixer: Using BFECC for Fluid Simulation

Back and Forth Error Compensation and Correction (BFECC) was recently developed for interface computation by using the level set method. We show that it can be applied to reduce dissipation and diffusion encountered in various advection steps in uid simulation such as velocity, smoke density and image advections. BFECC can be implemented easily on top of the r st order upwinding or semi-Lagrangian integration of advection equations, while providing second order accuracy both in space and time. When applied to level set evolution, BFECC reduces volume loss signi cantly . We combine these techniques with variable density projection and show that they yield a realistic animations of two-phase ows. We demonstrate the bene ts of this approach on the image advection and on the simulation of smoke, of bubbles in water, and of a highly dynamic interaction between water, a solid, and air.