Miracle-dz/UniFAR-FTUs huggingface dataset:
Epitope-Tagged P0Glycoprotein Causes Charcot-Marie-Tooth–Like Neuropathy in Transgenic Mice

In peripheral nerve myelin, the intraperiod line results from compaction of the extracellular space due to homophilic adhesion between extracellular domains (ECD) of the protein zero (P0) glycoprotein. Point mutations in this region of P0 cause human hereditary demyelinating neuropathies such as Charcot-Marie-Tooth. We describe transgenic mice expressing a full-length P0 modified in the ECD with a myc epitope tag. The presence of the myc sequence caused a dysmyelinating peripheral neuropathy similar to two distinct subtypes of Charcot-Marie-Tooth, with hypomyelination, altered intraperiod lines, and tomacula (thickened myelin). The tagged protein was incorporated into myelin and was associated with the morphological abnormalities. In vivo and in vitro experiments showed that P0myc retained partial adhesive function, and suggested that the transgene inhibits P0-mediated adhesion in a dominant-negative fashion. These mice suggest new mechanisms underlying both the pathogenesis of P0 ECD mutants and the normal interactions of P0 in the myelin sheath.
Relationship between Destination Image and Loyalty: Developing Cooperative Branding for Rural Destinations

Destination image has been extensively studied, yet literature on the cooperative branding is limited. A cooperative branding model that represents the important determinants of destination loyalty was developed based on previous studies in a number of fields. Seven distinct image constructs were identified, three of which are affective based and four cognitive based. This study noted that idyllic (among affective image) and entertaining and quality service (among cognitive image) had a direct impact on overall destination image and indirect impact on destination loyalty through overall image. The results of this investigation provide important implications for strategic image management and can aid in designing and implementing marketing programs for creating and enhancing tourism destination images.
Under Review as a Conference Paper at Iclr 2016 Learning Metrics by Learning Constrained Em- Beddings of Objects to R N

Similarity metrics are a core component of many information retrieval and machine learning systems. In this work we propose a method capable of learning a similarity metric from data equipped with a binary relation. By modelling the adjacency matrix of the relation we are able to learn target vectors for each instance. A regression model can then be constructed that maps instances to these learned targets, resulting in a feature extractor that computes vectors for which Euclidean distance is a meaningful measure of relatedness. We present results on several image recognition datasets.
A Cloud Controller for Performance-Based Pricing

New dynamic cloud pricing options are emerging with cloud providers offering resources as a wide range of CPU frequencies and matching prices that can be switched at runtime. On the other hand, cloud providers are facing the problem of growing operational energy costs. This raises a trade-off problem between energy savings and revenue loss when performing actions such as CPU frequency scaling. Although existing cloud controllers for managing cloud resources deploy frequency scaling, they only consider fixed virtual machine (VM) pricing. In this paper we propose a performance-based pricing model adapted for VMs with different CPU-bounded ness properties. We present a cloud controller that scales CPU frequencies to achieve energy cost savings that exceed service revenue losses. We evaluate the approach in a simulation based on real VM workload, electricity price and temperature traces, estimating energy cost savings up to 32% in certain scenarios.
A Self-Organization Strategy for Unmanned Autonomous Systems

Complex systems are constructed from multiple subsystemsand components with each serving incremental tasks, wherethe “emergent” system behavior cannot be deduced from thebehaviors of the individual parts. The key requirement ofcomplex systems is the ability to compensate for unforeseenand extreme disturbances, so it is important to design acontrol method that ensures acceptable level of systemresilience throughout its operation. Therefore, detailed andaccurate knowledge of system behaviors is paramount for thedesign of complex system control strategies. This paperpresents a self-organizing control strategy that incorporatesboth situational awareness and failure impact compensationfor a resilient unmanned autonomous system.
2 Computing Exact Ground Statesof Hard Ising Spin Glass Problemsby Branch-and-Cut

Whenstudyinggroundstatepropertiesof Isingspinglasses, thecomputationof exactground states,i.e., spincon gurations with exact ratherthanapproximateminimumenergy, is often desirable. The Ising model is oneof the mostcommonlyused,both for its simplicity and its accuracy in describingmany realworld systems.Whenwe refer to a spinglass in this chapter , wealwayshavetheIsingmodelin mind. The con gurations that are mostly consideredin the literatureare the twoand threedimensional Isingspinglassesonagrid with nearest neighborinteractionsandfreeor periodic boundaryinteractions,with or without an exterior magnetic eld.The periodic boundary conditionsare a standardway of approximatingan in nitespin glasswith a structurethat containsonly a nitenumberof spins. Unfortunately, therearenofunctionsin closedform that,givenall interactionsbetweenthe spinsandtheexterior eld, yield agroundstate.Therefore,theonly wayto computeaground
Fast Noise Reduction in CDNA Microarray Images

In this paper a novel approach to the impulsive noise removal in color images is presented. The proposed technique employs the switching scheme based on the impulse detection mechanism using the so called peer group concept. Compared to the vector median filter, the proposed technique consistently yields better results in suppressing the random-valued impulsive noise. The main advantage of the proposed noise detection framework is its high computational speed, which enables efficient filtering of large images in real-time applications. The proposed filtering scheme has been successfully applied to the denoising of the cDNA microarray images. Experimental results proved that the new filter is capable of removing efficiently the impulses present in multichannel images, while preserving their textural features
Robust tracking control for switched linear systems with time-varying delays

Robust tracking control for switched linear systems with time-varying delays is investigated in this paper. Sufficient conditions for the solvability of robust tracking control problem are developed. Average dwell time approach and piecewise Lyapunov functional methods are utilized to the stability analysis and controller design, and with free weighting matrix scheme, switching control laws are obtained such that the weighted Hinfin model reference robust tracking performance is satisfied. By using linear matrix inequalities, the controller design problem can be solved efficiently. A simulation example shows the effectiveness of the proposed switching control laws.
Sound Energy Harvester with Frequency Tunable Acoustic Metamaterial Cavity

We demonstrate a new type of acoustic harvester by utilizing an acoustic metamaterial cavity designed by double coiledup space like structures. In the case of double coiled-up metamaterials, high refractive index (n) miniaturizes the device at the subwavelength scale and high impedance (z) leads to efficient sound amplification rate inside the cavity, respectively. These miniaturized cavities enable to enhance the energy-convergence rate of acoustic harvester. When the resonant frequency of acoustic cavity coincides with the 1st natural frequency of the piezoelectric harvester, the amplification of sound pressure with 16dB sound pressure level gain leads to efficient acoustic mechanical-electrical conversion rate. Compared to acoustic harvesting method with only piezoelectric devices, experimental results illustrate that the proposed techniques exhibit six-time higher voltage output.
Quantification of Integrity

Two kinds of integrity measures—contamination and suppression—are introduced. Contamination measures how much untrusted information reaches trusted outputs; it is the dual of information-flow confidentiality. Suppression measures how much information is lost from outputs; it does not have a confidentiality dual. Two forms of suppression are considered: programs and channels. Program suppression measures how much information about the correct output of a program is lost because of attacker influence and implementation errors. Channel suppression measures how much information about inputs to a noisy channel is missing from channel outputs. The relationship between quantitative integrity, confidentiality, and database privacy is examined.
A string pattern regression algorithm and its application to pattern discovery in long introns.

We present a new approach to pattern discovery called string pattern regression, where we are given a data set that consists of a string attribute and an objective numerical attribute. The problem is to find the best string pattern that divides the data set in such a way that the distribution of the numerical attribute values of the set for which the pattern matches the string attribute, is most distinct, with respect to some appropriate measure, from the distribution of the numerical attribute values of the set for which the pattern does not match the string attribute. By solving this problem, we are able to discover, at the same time, a subset of the data whose objective numerical attributes are significantly different from rest of the data, as well as the splitting rule in the form of a string pattern that is conserved in the subset. Although the problem can be solved in linear time for the substring pattern class, the problem is NP-hard in the general case (i.e. more complex patterns), and we present an exact but efficient branch-and-bound algorithm which is applicable to various pattern classes. We apply our algorithm to intron sequences of human, mouse, fly, and zebrafish, and show the practicality of our approach and algorithm. We also discuss possible extensions of our algorithm, as well as promising applications, such as microarray gene expression data.
Lyrics Recognition from a Singing Voice Based on Finite State Automaton for Music Information Retrieval

Recently, several music information retrieval (MIR) systems have been developed which retrieve musical pieces by the user’s singing voice. All of these systems use only the melody information for retrieval. Although the lyrics information is useful for retrieval, there have been few attempts to exploit lyrics in the user’s input. In order to develop a MIR system that uses lyrics and melody information, lyrics recognition is needed. Lyrics recognition from a singing voice is achieved by similar technology to that of speech recognition. The difference between lyrics recognition and general speech recognition is that the input lyrics are a part of the lyrics of songs in a database. To exploit linguistic constraints maximally, we described the recognition grammar using a finite state automaton (FSA) that accepts only lyrics in the database. In addition, we carried out a “singing voice adaptation” using a speaker adaptation technique. In our experimental results, about 86% retrieval accuracy was obtained.
A multicentre phase II study of vorinostat in patients with relapsed or refractory indolent B-cell non-Hodgkin lymphoma and mantle cell lymphoma

Although initial rituximab‐containing chemotherapies achieve high response rates, indolent B‐cell non‐Hodgkin lymphoma (B‐NHL), such as follicular lymphoma (FL), is still incurable. Therefore, new effective agents with novel mechanisms are anticipated. In this multicentre phase II study, patients with relapsed/refractory indolent B‐NHL and mantle cell lymphoma (MCL) received vorinostat 200 mg twice daily for 14 consecutive days in a 21‐d cycle until disease progression or unacceptable toxicity occurred. The primary endpoint was overall response rate (ORR) in FL patients and safety and tolerability in all patients. Secondary endpoints included progression‐free survival (PFS). Fifty‐six eligible patients were enrolled; 50 patients (39 with FL, seven with other B‐NHL, and four with MCL) were evaluable for ORR, and 40 patients had received rituximab‐containing prior chemotherapeutic regimens. For the 39 patients with FL, the ORR was 49% [95% confidence interval (CI): 32·4, 65·2] and the median PFS was 20 months (95% CI: 11·2, 29·7). Major toxicities were manageable grade 3/4 thrombocytopenia and neutropenia. Vorinostat offers sustained antitumour activity in patients with relapsed or refractory FL with an acceptable safety profile. Further investigation of vorinostat for clinical efficacy is warranted.
Sodium channel gating currents. Origin of the rising phase

There has been some uncertainty in the past as to the origin of the rising phase of the gating current. We present evidence here that proves that the gating current does not have a rising phase and that the observed rising phase is due to an uncompensated series resistance in the Frankenhaeuser-Hodgkin (F-H) space. When a squid giant axon is bathed in a solution that is 10-20% hyperosmotic with respect to the internal solution, the rising phase of the gating current is eliminated. In parallel with this, a component of the capacity transient (time constant, 20 microseconds) is reduced so that the capacity transient now appears to be closer to a single fast (5-10 microseconds) component. These changes in the capacity transient and gating current occur without altering the amount of charge moved in either. This indicates that the charge is simply redistributed in time. The gating current without a rising phase can still be immobilized by inactivation. Supporting evidence is provided by measuring the accumulation and washout of K+ from the F-H space. It was found that K+ washes out 35% faster when the axon is bathed in hyperosmotic solution. It was estimated that the F-H space thickness (theta) increased 2.5 +/- 0.4-fold (mean +/- SEM) in hyperosmotic solution. Similarly, K+ accumulation in the F-H space was decreased, leading to an estimate of a 5 +/- 1.4-fold increase in theta in hyperosmotic solution. These results are consistent with the simple structural model presented.
Two‐Timescale Carbon Cycle Response to an AMOC Collapse

Atmospheric CO2 concentrations (pCO2) varied on millennial timescales in phase with Antarctic temperature during the last glacial period. A prevailing view has been that carbon release and uptake by the Southern Ocean dominated this millennial‐scale variability in pCO2. Here, using Earth System Model experiments with an improved parameterization of ocean vertical mixing, we find a major role for terrestrial and oceanic carbon releases in driving the pCO2 trend. In our simulations, a change in Northern Hemisphere insolation weakens the Atlantic Meridional Overturning Circulation (AMOC) leading to increasing pCO2 and Antarctic temperatures. The simulated rise in pCO2 is caused in equal parts by increased CO2 outgassing from the global ocean due to a reduced biological activity and changed ventilation rates, and terrestrial carbon release as a response to southward migration of the Intertropical Convergence Zone. The simulated terrestrial release of carbon could explain stadial declines in organic carbon reservoirs observed in recent ice core δ13C measurements. Our results show that parallel variations in Antarctic temperature and pCO2 do not necessitate that the Southern Ocean dominates carbon exchange; instead, changes in carbon flux from the global ocean and land carbon reservoirs can explain the observed pCO2 (and δ13C) changes.
Entropic Measure of Epistemic Uncertainties in Multibody System Models by Axiomatic Design

In this paper, the use of the MaxInf Principle in real optimization problems is investigated for engineering applications, where the current design solution is actually an engineering approximation. In industrial manufacturing, multibody system simulations can be used to develop new machines and mechanisms by using virtual prototyping, where an axiomatic design can be employed to analyze the independence of elements and the complexity of connections forming a general mechanical system. In the classic theories of Fisher and Wiener-Shannon, the idea of information is a measure of only probabilistic and repetitive events. However, this idea is broader than the probability alone field. Thus, the Wiener-Shannon’s axioms can be extended to non-probabilistic events and it is possible to introduce a theory of information for non-repetitive events as a measure of the reliability of data for complex mechanical systems. To this end, one can devise engineering solutions consistent with the values of the design constraints analyzing the complexity of the relation matrix and using the idea of information in the metric space. The final solution gives the entropic measure of epistemic uncertainties which can be used in multibody system models, analyzed with an axiomatic design.
A flexible, scalable finite-state transducer architecture for corpus-based concatenative speech synthesis

In this paper we describe our work involving the conversion of our phonologically-based synthesizer into a ﬁnite-state transducer (FST) representation which can be used for real-time natural-sounding synthesis. We have designed a transducer structure to efﬁciently perform the common task of unit selection in concatenative speech synthesis. By encapsulating domain-independent concatenative synthesis costs into a constraint kernel, we have obtained a topology that scales linearly with the size of the synthesis corpus. The FST representation provides a ﬂex-ible, uniﬁed framework in which we can leverage our previous work in speech recognition in areas such as pronunciation modelling and search. The FST synthesizer has been incorporated into two servers which operate within our conversational system architecture to convert meaning representations into waveforms. We have had preliminary success with the new FST-based synthesis in several constrained spoken dialogue applications.
Learning to segment on tiny datasets: A new shape model

Current object segmentation algorithms are based on the hypothesis that one has access to a very large amount of data. In this paper, we aim to segment objects using only tiny datasets. To this extent, we propose a new automatic part-based object segmentation algorithm for non-deformable and semi-deformable objects in natural backgrounds. We have developed a novel shape descriptor which models the local boundaries of an object's part. This shape descriptor is used in a bag-of-words approach for object detection. Once the detection process is performed, we use the background and foreground likelihood given by our trained shape model, and the information from the image content, to define a dense CRF model. We use a mean field approximation to solve it and thus segment the object of interest. Performance evaluated on different datasets shows that our approach can sometimes achieve results near state-of-the-art techniques based on big data while requiring only a tiny training set.
Slender Tactile Sensor for Contour and Roughness Measurements Within Deep and Narrow Holes

A tactile cantilever sensor is described which was designed for quality assurance of high-aspect ratio microcomponents, e.g., spray holes of diesel injector nozzles. It was constructed as an extremely slender silicon cantilever of 1.5-5 mm in length, 30-200 mum in width, and 25-50 mum in height comprising a silicon probing tip at its free end. Close to its clamping, a piezoresistive strain gauge was integrated for signal read-out. The novel sensor was designed to be operated at high scanning speeds offering a millimeter scanning range at a micrometer lateral resolution and a ten nanometers vertical resolution. Cross sensitivity versus temperature and ambient light referred to vertical tip deflection was below 10 nm during a tactile measurement, which was performed under typical tactile probing conditions, i.e., temperature and light intensity variations of 1 K and 0.1 mW/cm 2, respectively. In form and roughness measurements with calibrated standard artifacts as well as with narrow spray holes of advanced diesel injector nozzles, we demonstrated the potential of slender cantilever sensors for high-aspect-ratio micrometrology.
Structural Alterations in the Translational Attenuator of Constitutively Expressed ermC Genes

ABSTRACT Sequence deletions of 16, 59, and 111 bp as well as a tandem duplication of 272 bp with respect to the corresponding sequence of pT48 were identified in the regulatory regions of constitutively expressed ermC genes. Constitutive ermC gene expression as a consequence of these structural alterations is based on either the prevention of the formation of mRNA secondary structures in the translational attenuator or the preferential formation of those mRNA secondary structures which do not interfere with the translation of the ermC transcripts. A model for the development of sequence deletions in the ermC translational attenuator by homologous recombination is presented and experimentally tested by in vitro selection of constitutively expressed mutants in staphylococcal strains deficient and proficient in homologous recombination.
Biological monitoring of kidney function among workers occupationally exposed to trichloroethylene

Aims: To investigate the nephrotoxic potential of trichloroethylene in a currently exposed population using sensitive urinary markers of kidney toxicity. Methods: Renal dysfunction was monitored in a cross-sectional study of 70 workers currently exposed to trichloroethylene. An age and sex matched control population of 54 individuals was drawn from hospital and administrative staff. Results: The mean exposure to trichloroethylene, estimated from urinary trichloroacetic acid concentrations, was 32 ppm (range 0.5–252 ppm) with an average duration of exposure of 4.1 years (range 1–20 years). Significant differences between the exposed and control populations were found for nephrotoxicity markers N-acetylglucosaminidase (NAG) and albumin, and for the mode of action marker, formic acid. However, neither NAG nor albumin showed a significant correlation with either the magnitude or duration of exposure to trichloroethylene. There was a significant correlation between urinary formic acid and trichloroacetic acid concentrations. Within the exposed population there were dose dependent increases in urinary methylmalonic acid concentrations and urinary glutathione S-transferase α activity. Although still within the control range, these changes were clearly dose dependent and consistent with one of the proposed mechanisms of trichloroethylene induced kidney toxicity. Conclusion: Although there was no evidence of kidney toxicity within the population studied, the results suggest that kidney damage could occur at exposure concentrations higher (>250 ppm) than those encountered in this study.