Miracle-dz/UniFAR-FTUs huggingface dataset:
Interpolatory Mercer kernel construction for kernel direct LDA on face recognition

This paper proposes a novel methodology on Mercer kernel construction using interpolatory strategy. Based on a given symmetric and positive semi-definite matrix (Gram matrix) and Cholesky decomposition, it first constructs a nonlinear mapping Φ, which is well-defined on the training data. This mapping is then extended to the whole input feature space by utilizing Lagrange interpolatory basis functions. The kernel function constructed by inner product is proven to be a Mercer kernel function. The self-constructed interpolatory Mercer (IM) kernel keeps the Gram matrix unchanged on the training samples. To evaluate the performance of the proposed IM kernel, a popular kernel direct linear discriminant analysis (KDDA) method for face recognition is selected. Comparing with RBF kernel based KDDA method on two face databases, namely FERET and CMU PIE databases, the IM kernel based KDDA approach could increase the performance by around 20% on CMU PIE database.
Thai Phoneme Soft Segmentation and Recognition Using Hidden Markov Models

In this paper, we propose a Thai phoneme recognition system with a soft phoneme segmentation. The soft phoneme segmentation technique is based on the characteristics of Thai language in that the vowel is the core of a syllable. The recognition system utilizes the discrete hidden Markov model to recognize the Thai phonemes, i.e., 21-class initial consonants, 18-class vowels, and 9-class final consonants. We use the Mel frequency with perceptual linear prediction as the features of a phoneme. We experiment the recognition system on both speaker-dependent and speaker-independent data sets recorded from 30 speakers. The experimental results show promising recognition performances in both cases.
Automatic Formalisation of UML to Z

The software development practices currently used in industry are not rigorous or precise, often leading to systems being incorrectly specified. Graphically modelling a system allows its design to be visualised intuitively, however the semantics of modelling languages are not well defined. Formal methods offers the ability to specify and verify systems using mathematical logic. Formal languages have precise semantics, allowing for less ambiguous models of systems to be designed. However their use has not been widely adopted due to the mathematical nature of the languages. This project automates the process developed by Amálio for transforming graphical models into formal specifications, thus gaining the ability to formally validate a diagram. Automating this process and concealing the formal rigour from the user improves the reliability of mainstream software practices without altering the process significantly.
Optimal selection of cane usage with humanoid robot

Humanoid robots are required to improve its walking ability (stability and efficiency) in order to adapt to various environments. Extension of the embodiment by a cane is effective as well as human like elderly. In this paper, we propose a scheme that enables the robot to perform cane-supported walking and select the optimal cane usage based on its condition so as to maximize the performance of cane support. For cane-supported walking, we propose cyclic and leg-like usages, which correspond to two-point and three-point gaits. Our strategy for selecting the optimal cane usages, which have respective utilities, utilizes falling factors in Selection Algorithm for Locomotion (Us-SAL). We express affinities between the cane usages and the falling factors as Q-values, which are learned by Q-learning, and select the optimal usage based on the Q-values. Us-SAL was validated by an experiment; the robot selected the optimal usage for its condition, and walked efficiently without falling.
Whole-Brain Atrophy Differences between Progressive Supranuclear Palsy and Idiopathic Parkinson’s Disease

Background: The absence of markers for ante-mortem diagnosis of progressive supranuclear palsy (PSP), results in this disorder being commonly mistaken for other conditions, such as idiopathic Parkinson’s disease (IPD). Such mistakes occur particularly in the initial stages, when “plus syndrome” has not yet clinically emerged. Objective: To investigate the global brain volume and tissue loss in patients with PSP relative to patients with IPD and healthy controls and correlations between clinical parameters and magnetic resonance imaging (MRI)-derived brain volume estimates. Methods: T1-weighted images were obtained from three groups of Chilean Latin American adults: 21 patients with IPD, 18 patients with PSP and 14 healthy controls. We used Structural Imaging Evaluation with Normalization of Atrophy (SIENAX) to assess white matter, gray matter and whole-brain volumes (normalized to cranial volume). Imaging data were used to analyze putative correlations with the clinical status of PSP and IPD patients using the Unified Parkinson’s Disease Rating Scale Part III (UPDRS III), Hoehn and Yahr (H&Y), the Clinical Global Impression for Disease Severity Scale (CGI-S) and the Frontal Assessment Battery (FAB). Results: PSP patients had significantly lower whole brain volume than both IPD patients and controls. Whole brain volume reduction in PSP patients was primarily attributable to gray matter volume reduction. We found a significant correlation between brain volume reduction and clinical status in the PSP group. Conclusions: At the group level, the whole brain and gray matter volumes differentiated patients with PSP from patients with IPD. There was also significant clinical-imaging correlations with motor disturbances in PSP.
A Context-aware Natural Language Generator for Dialogue Systems

We present a novel natural language generation system for spoken dialogue systems capable of entraining (adapting) to users' way of speaking, providing contextually appropriate responses. The generator is based on recurrent neural networks and the sequence-to-sequence approach. It is fully trainable from data which include preceding context along with responses to be generated. We show that the context-aware generator yields significant improvements over the baseline in both automatic metrics and a human pairwise preference test.
Two Distinct Dynamic Modes Subtend the Detection of Unexpected Sounds

The brain response to auditory novelty comprises two main EEG components: an early mismatch negativity and a late P300. Whereas the former has been proposed to reflect a prediction error, the latter is often associated with working memory updating. Interestingly, these two proposals predict fundamentally different dynamics: prediction errors are thought to propagate serially through several distinct brain areas, while working memory supposes that activity is sustained over time within a stable set of brain areas. Here we test this temporal dissociation by showing how the generalization of brain activity patterns across time can characterize the dynamics of the underlying neural processes. This method is applied to magnetoencephalography (MEG) recordings acquired from healthy participants who were presented with two types of auditory novelty. Following our predictions, the results show that the mismatch evoked by a local novelty leads to the sequential recruitment of distinct and short-lived patterns of brain activity. In sharp contrast, the global novelty evoked by an unexpected sequence of five sounds elicits a sustained state of brain activity that lasts for several hundreds of milliseconds. The present results highlight how MEG combined with multivariate pattern analyses can characterize the dynamics of human cortical processes.
Nerve fiber growth in culture on tissue substrata from central and peripheral nervous systems

In adult mammals, injured neurons regenerate extensively within the PNS but poorly, if at all, within the CNS. We have studied the effect of substrata consisting of tissue sections from various nervous systems on nerve fiber growth in culture and correlated our results with the growth potential of these tissues in vivo. Ganglionic explants from embryonic chicks (9–12 d) fail to extend nerve fibers onto sections of adult rat optic nerve or spinal cord (CNS) but do so on sciatic nerve (PNS). Dissociated DRG neurons behave similarly whether in serum- containing or defined medium. Tissue substrata from nervous systems that support regeneration in vivo--i.e., goldfish optic nerve, embryonic rat spinal cord, degenerating sciatic nerve--also support fiber growth in culture. Within the same culture, neurons will grow onto sciatic nerve rather than neighboring optic nerve sections, suggesting that the responsible agent(s) is not soluble. In addition, neurons adhere more extensively to sciatic nerve substrata than to optic nerve. The occurrence of 3 molecules known to be involved in neuron-substratum adhesion and nerve fiber growth in vitro has been documented immunocytochemically in the tissue sections. One of these, laminin, is demonstrable in all tissues tested that supported nerve fiber growth. Immunoreactivities for fibronectin and heparan sulfate proteoglycan are found in only some of these tissues. None of these 3 molecules can be demonstrated in neural cells of normal adult rat CNS tissue. Our data suggest that these molecules may be important effectors of nerve regeneration in neural tissues.
Prognostic relevance of sunitinib toxicities and comparison of continuous vs. intermittent sunitinib dosing schedule in metastatic renal cell cancer patients

Aim of the study Sunitinib-related side effects may develop as a result of the pharmacokinetic pathway affects the of the drug. Material and methods Data on mRCC patients were obtained from the hospital archives. Outcomes of patients were evaluated in terms of related prognostic factors, sunitinib adverse events during the treatment, and two different sunitinib dosing schedules. Results Seventy patients diagnosed with mRCC and treated with sunitinib were analyzed for prognostic factors and survival rates. During the mean follow-up of 33.5 months, 38 (54%) patients were alive and 32 (46%) patients died. The median time of overall survival (OS) and progression-free survival (PFS) was 27 months (12–61) and 19 months (5–45), respectively. In univariate analysis, good prognostic risk group according to the Memorial Sloan-Kettering Cancer Center (MSKCC), hypothyroidism as sunitinib toxicity and patients on sunitinib treatment more than 1 year were favorable prognostic factors for OS. Leukopenia and fatigue as sunitinib toxicity were poor prognostic factors for OS. PFS and OS of the patients were not significantly different when we compared intermittent (4/2) vs. continuous treatment dosing schedules. Conclusions As a result of this trial, having hypothyroidism as an adverse effect of sunitinib was a favorable prognostic factor for OS and PFS in mRCC patients. It was also found that 4/2 and continuous dosing schedules of sunitinib did not give rise to different outcomes in mRCC patients.
Printed Circuit Board Materials Handbook

Continuous Glass Fiber Reinforcement for Printed Wiring Board Application.Glass Reinforcement.Films, Polymide.Polyethylene Teraphthalate (PET) and Polyethylene Naphthalate (PEN) for Printed Circuit Application.Punching Grades of Copper Clad Laminates.Resins. Copper Foils.Anodes for Printed Wiring Plating.Prepreg and Laminates.Non-Woven Aramid Reinforcement.Drill Bits and Routers.Fabrication of Rigid Printed Wiring Boards.Fabrication of Flexible and Rigid Flexible Printed Wiring Boards.Photoresist. Etching Inner Layers.Oxide Coatings.Lamination of Rigid Multilayer Boards.Lamination of Flex and Rigid Flex Printed Wiring Boards.Entry and Back-Up Material.Drilling Rigid and Flexible Printed Wiring Boards.Desmear/Etchback Process.Plasma Etchback.Electroless Copper Process.Direct Metalization Process.Electroplating. Additive Copper.Etching Outer Layers.Photoimageable Soldermask.Screenable Solder Mask Coatings.Hot Air Leveling.Microsection Anaysis.Electrical Test.
Collaborative Protege: Enabling Community-based Authoring of Ontologies

Ontologies are becoming so large in their coverage that no single person or a small group of people can develop them effectively and ontology development becomes a community-based enterprise. We present Collaborative Protege--an extension of the Protege ontology editor that we have designed specifically to support the collaboration process for a community of users. During the ontology-development process, Collaborative Protege allows users to hold discussions about the ontology components and changes using typed annotations; it tracks the change history of the ontology entities; it provides a chat and search functionality. Users edit simultaneously an ontology stored in a common repository. All changes made by a user are seen immediately by other users. Collaborative Protege is open source and distributed with the full installation of Protege.
On equitable approaches to resource allocation problems: the conditional minimax solutions

Resource allocation problems are concerned with the allocation of limited resources among competing activities so as to achieve the best overall performances. In this paper, we focus on approaches that attempt to allocate resources equitably among the competing activities. The problems of efficient and equitable resource allocation arise in various systems which serve many users, like in telecommunication systems. Telecommunication networks are expected to satisfy the increasing demand for traditional services as well as to accommodate multimedia services. Hence, it becomes critical to allocate network resources, such as available bandwidth, so as to provide high level performance of all services at numerous destination nodes. The performance can be measured in terms of expected delays to be equitably minimized for all service demands. In this paper we introduce and analyze a solution concept of the conditional minimax as a generalization of the minimax solution concept extended to take into account the number of services (the portion of demand) related to the worst performances. Namely, for a specified portion of demand we take into account the corresponding portion of the maximum results and we consider their average as the worst conditional mean to be minimized. We show that, similar to the standard minimax approach, the minimization of the worst conditional mean can be defined by a linear objective and a number of auxiliary linear inequalities. We report some results of initial computational experience with the new solution concept.
Study on the Sliding Friction of Endothelial Cells Cultured on Hydrogel and the Role of Glycocalyx on Friction Reduction

We investigate the sliding friction of HUVEC monolayers cultured on PNaSS gel, intending to elucidate the role of glycocalyx on the surface of ECs in friction reduction. Three sets of HUVEC monolayers are investigated: an as‐cultured HUVEC monolayer; a HUVEC monolayer treated with TGF‐β1, which increases the glycocalyx by 148%; and a HUVEC monolayer treated with heparinase I, which reduces the glycocalyx by 57%. When being slid on a flat, glass surface, the frictional stress of the HUVEC monolayer decreases in the order: heparinase‐I‐treated > as‐cultured > TGF‐β1‐treated samples. The results suggest that glycocalyx may play a role in reducing the friction of endothelial cell monolayer.
The Converging Inflow Spectrum Is an Intrinsic Signature for a Black Hole: Monte Carlo Simulations of Comptonization on Free-falling Electrons

An accreting black hole is, by definition, characterized by the drain. Namely, matter falls into a black hole much the same way as water disappears down a drain: matter goes in and nothing comes out. As this can only happen in a black hole, it provides a way to see "a black hole," a unique observational signature of black holes. The accretion proceeds almost in a free-fall manner close to the black hole horizon, where the strong gravitational field dominates the pressure forces. In this paper we calculate (by using Monte Carlo simulations) the specific features of X-ray spectra formed as a result of upscattering of the soft (disk) photons in the converging inflow (CI) within about 3 Schwarzschild radii of the black hole. The full relativistic treatment has been implemented to reproduce these spectra. We show that spectra in the soft state of black hole systems (BHS) can be described as the sum of a thermal (disk) component and the convolution of some fraction of this component with the CI upscattering spread (Green's) function. The latter boosted photon component is seen as an extended power law at energies much higher than the characteristic energy of the soft photons. We demonstrate the stability of the power spectral index (α=1.8±0.1) over a wide range of the plasma temperature, 0-10 keV, and mass accretion rates (higher than 2 in Eddington units). We also demonstrate that the sharp high-energy cutoff occurs at energies of 200-400 keV, which are related to the average energy of electrons mec2 impinging on the event horizon. The spectrum is practically identical to the standard thermal Comptonization spectrum (Hua & Titarchuk) when the CI plasma temperature is getting of order of 50 keV (the typical ones for the hard state of BHS). In this case one can see the effect of the bulk motion only at high energies, where there is an excess in the CI spectrum with respect to the pure thermal one. Furthermore, we demonstrate that the change of spectral shapes from the soft X-ray state to the hard X-ray state is clearly to be related to the temperature of the bulk flow. We derive a generic formula for the temperature of the emitting region (CI) that depends on the ratio of the energy release in this very region and in the disk. Using this formula, we demonstrate that the temperature of the emission region in the hard state of the BHS is approximately 2 times higher than the ones of neutron star systems (NSS) in the hard state, which is confirmed by recent RXTE and Beppo-SAX observations of the hard state of NSS. The effect of the bulk Comptonization compared with the thermal one is getting stronger when the plasma temperature drops below 10 keV. These Monte Carlo simulated CI spectra are an inevitable stamp of the BHS where the strong gravitational field dominates the pressure forces.
Development, Characterization, and Reversal of Acquired Resistance to the MEK1 Inhibitor Selumetinib (AZD6244) in an In Vivo Model of Childhood Astrocytoma

Purpose: The BT-40 low-grade childhood astrocytoma xenograft model expresses mutated BRAFV600E and is highly sensitive to the MEK inhibitor selumetinib (AZD6244). In this study, we developed and characterized selumetinib resistance and explored approaches to circumventing the mechanisms of acquired resistance. Experimental Design: BT-40 xenografts were selected in vivo for selumetinib resistance. Resistant tumors were obtained and characterized, as were tumors that reverted to sensitivity. Characterization included expression profiling, assessment of MEK signature and compensatory pathways, MEK inhibition, BRAF expression, and cytokine levels. Combination treatment of BT-40/AZD–resistant tumors with the MEK inhibitor and a STAT3 inhibitor (LLL12) was assessed. Results: Resistance was unstable, tumors reverting to selumetinib sensitivity when passaged in untreated mice, and MEK was equally inhibited in sensitive and resistant tumors by selumetinib. Drug resistance was associated with an enhanced MEK signature and increased interleukin (IL)-6 and IL-8 expression. Selumetinib treatment induced phosphorylation of STAT3 (Y705) only in resistant xenografts, and similar results were observed in BRAFV600E astrocytic cell lines intrinsically resistant to selumetinib. Treatment of BT-40–resistant tumors with selumetinib or LLL12 had no significant effect, whereas combined treatment induced complete regressions of BT-40/AZD–resistant xenografts. Conclusions: Resistance to selumetinib selected in vivo in BT-40 tumor xenografts was unstable. In resistant tumors, selumetinib activated STAT3, and combined treatment with selumetinib and LLL12 induced complete responses in resistant BT-40 tumors. These results suggest dual targeting BRAF (V600E) signaling and STAT3 signaling may be effective in selumetinib-resistant tumors or may retard or prevent onset of resistance. Clin Cancer Res; 19(24); 6716–29. ©2013 AACR.
Downlink Precoding With Mixed Statistical and Imperfect Instantaneous CSI for Massive MIMO Systems

In this paper, the feasibility of a new downlink transmission mode in massive multi-input multi-output (MIMO) systems is investigated with two types of users, i.e., the users with only statistical channel state information (CSI) and the users with imperfect instantaneous CSI. The problem of downlink precoding design with mixed utilization of statistical and imperfect instantaneous CSI is addressed. We first theoretically analyze the impact of the mutual interference between the two types of users on their achievable rate. Then, considering the mutual interference suppression, we propose an extended zero forcing and an extended maximum ratio transmission precoding methods to minimize the total transmit power of base station and to maximize the received signal power of users, respectively. Thanks to the exploitation of statistical CSI, pilot-based channel estimation is avoided enabling more active users, higher system sum rate, and shorter transmission delay. Finally, simulations are performed to validate the accuracy of the theoretical analysis and the advantages of the proposed precoding methods.
Indexing multi-dimensional data in a cloud system

Providing scalable database services is an essential requirement for extending many existing applications of the Cloud platform. Due to the diversity of applications, database services on the Cloud must support large-scale data analytical jobs and high concurrent OLTP queries. Most existing work focuses on some specific type of applications. To provide an integrated framework, we are designing a new system, epiC, as our solution to next-generation database systems. In epiC, indexes play an important role in improving overall performance. Different types of indexes are built to provide efficient query processing for different applications. In this paper, we propose RT-CAN, a multi-dimensional indexing scheme in epiC. RT-CAN integrates CAN [23] based routing protocol and the R-tree based indexing scheme to support efficient multi-dimensional query processing in a Cloud system. RT-CAN organizes storage and compute nodes into an overlay structure based on an extended CAN protocol. In our proposal, we make a simple assumption that each compute node uses an R-tree like indexing structure to index the data that are locally stored. We propose a query-conscious cost model that selects beneficial local R-tree nodes for publishing. By keeping the number of persistently connected nodes small and maintaining a global multi-dimensional search index, we can locate the compute nodes that may contain the answer with a few hops, making the scheme scalable in terms of data volume and number of compute nodes. Experiments on Amazon's EC2 show that our proposed routing protocol and indexing scheme are robust, efficient and scalable.