Miracle-dz/UniFAR-FTUs huggingface dataset:
Diamond microdisk cavity optomechanics

Optomechanical coupling between GHz frequency mechanical modes and λ ~ 1. 5μm optical modes in single-crystal diamond microdisks is demonstrated. The mechanical modes have a Q frequency product of 2 × 1013 Hz in ambient conditions, and are excited into ~ 31 pm self-oscillations by radiation pressure.
Optimal Wavelets Vanishing Moments for Singular Signal Detection

The wavelet transform modular maximum corresponds to the singularity of signal. Based on the fact that wavelet transform modular maximum of signal is different from that of noise at different scales, the noise can be removed from signal. The relationship between wavelet with different vanishing moments and Lipschitz exponent is discussed. And the influence of vanishing moments on singular signal detection is analyzed. The experimental results show that it is necessary to choose appropriate wavelets with different vanishing moments to detect signals with different singularities.
Observation of Fermi Pressure in a Gas of Trapped Atoms

We report the attainment of simultaneous quantum degeneracy in a mixed gas of bosons (lithium-7) and fermions (lithium-6). The Fermi gas has been cooled to a temperature of 0.25 times the Fermi temperature by thermal collisions with the evaporatively cooled bosons. At this temperature, the spatial size of the gas is strongly affected by the Fermi pressure resulting from the Pauli exclusion principle and gives clear experimental evidence for quantum degeneracy.
A novel approach to the assessment of response to chemotherapy in sarcoma imaged with PET-FDG

Human sarcoma is a class of malignant tumors affecting soft tissue, cartilage and bone. Standard therapy typically involves resection with neo-adjuvant chemotherapy being employed to shrink the tumor mass prior to surgery. The effectiveness of chemotherapy is variable and there is on-going interest in being able to rapidly determining this so that alternative therapies might be considered, when indicated. We are exploring ways in which PET imaging with FDG can be used for the assessment of chemotherapy response with sarcoma. Quantitative assessment requires an alignment or co-registration of pre- and post-therapy scans data. Obviously PET attenuation information is key but this can be augmented to ensure that the uptake weighted spatial mean and covariance of the tumor pre- and post-therapy are also aligned. This is achieved by means of a Procrustes rotation procedure applied to the pre- and post-covariance matrices. Once the pre- and post-therapy scans are aligned, a statistical summary of voxel-by-voxel changes in uptake can be used to assess the chemotherapy response. An advantage of this assessment is that it is necessarily sensitive to the changes in the spatial pattern of uptake within the tumor. A regression analysis is proposed in which the average change from the post- to the pre-therapy values is evaluated in terms of a standardized coefficient that has the form of a z-test statistic. The statistic provides a more meaningful scale in which to evaluate chemotherapy effects. We illustrate the use of these procedures is a series of data from a set of 48 sarcoma patients. The relation between the proposed chemotherapy response assessment and patient outcome shows promise.
Latency-Associated Nuclear Antigen E3 Ubiquitin Ligase Activity Impacts Gammaherpesvirus-Driven Germinal Center B Cell Proliferation

ABSTRACT Viruses have evolved mechanisms to hijack components of cellular E3 ubiquitin ligases, thus modulating the ubiquitination pathway. However, the biological relevance of such mechanisms for viral pathogenesis in vivo remains largely unknown. Here, we utilized murid herpesvirus 4 (MuHV-4) infection of mice as a model system to address the role of MuHV-4 latency-associated nuclear antigen (mLANA) E3 ligase activity in gammaherpesvirus latent infection. We show that specific mutations in the mLANA SOCS box (V199A, V199A/L202A, or P203A/P206A) disrupted mLANA's ability to recruit Elongin C and Cullin 5, thereby impairing the formation of the Elongin BC/Cullin 5/SOCS (EC5SmLANA) complex and mLANA's E3 ligase activity on host NF-κB and Myc. Although these mutations resulted in considerably reduced mLANA binding to viral terminal repeat DNA as assessed by electrophoretic mobility shift assay (EMSA), the mutations did not disrupt mLANA's ability to mediate episome persistence. In vivo, MuHV-4 recombinant viruses bearing these mLANA SOCS box mutations exhibited a deficit in latency amplification in germinal center (GC) B cells. These findings demonstrate that the E3 ligase activity of mLANA contributes to gammaherpesvirus-driven GC B cell proliferation. Hence, pharmacological inhibition of viral E3 ligase activity through targeting SOCS box motifs is a putative strategy to control gammaherpesvirus-driven lymphoproliferation and associated disease. IMPORTANCE The gammaherpesviruses Epstein-Barr virus (EBV) and Kaposi's sarcoma-associated herpesvirus (KSHV) cause lifelong persistent infection and play causative roles in several human malignancies. Colonization of B cells is crucial for virus persistence, and access to the B cell compartment is gained by virus-driven proliferation in germinal center (GC) B cells. Infection of B cells is predominantly latent, with the viral genome persisting as a multicopy episome and expressing only a small subset of viral genes. Here, we focused on latency-associated nuclear antigen (mLANA) encoded by murid herpesvirus-4 (MuHV-4), which exhibits homology in sequence, structure, and function to KSHV LANA (kLANA), thereby allowing the study of LANA-mediated pathogenesis in mice. Our experiments show that mLANA's E3 ubiquitin ligase activity is necessary for efficient expansion of latency in GC B cells, suggesting that the development of pharmacological inhibitors of LANA E3 ubiquitin ligase activity may allow strategies to interfere with gammaherpesvirus-driven lymphoproliferation and associated disease.
Investigations of a magnetorheological fluid damper

This paper presents the results of a study of a magnetorheological fluid (MRF) damper. The principle could be used for such applications as seismic protectors for civil structure (where the dimensions are chosen to handle the greatest forces) or shock absorbers for the automotive industry (where the dimensions are chosen to accommodate heating effects). We describe the preparation method and some characteristics of the MRF, the experimental method (we used a hydraulic linear motor and pressure measurements), and the main experimental results. The external force required to move the damper increases several times when the magnetic field is applied.
From Descriptors to Predicted Properties: Experimental Design by Using Applicability Domain Estimation

The importance of reliable methods for representative sub-sampling in terms of experimental design and risk assessment within the European Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) system is crucial. We developed experimental design approaches, by utilising predicted properties and the ‘distance to model’ parameter, to estimate the benefits of certain compounds to the quality of a resulting model. A statistical evaluation of four regression data sets and one classification data set showed that the adaptive concept of iteratively refining the representation of the chemical space contributes to a more efficient and more reliable selection in comparison to traditional approaches. The evaluation of compounds with regard to the uncertainty and the correlation of prediction is beneficial, and in particular, for regression data sets of sufficient size, whereas the use of predicted properties to define the chemical space is beneficial for classification models.
Frame duplication/mirroring detection method with binary features

Multimedia devices have become increasingly popular due to high quality and low cost products using advanced technology. These devices can capture multimedia files, which can be modified easily by video editing tools. One of the most frequently encountered forgery types in video forensics is the frame duplication (FD) forgery. Many methods have been proposed in the literature to deal with this type of forgery. These methods do not consider frame-mirroring (FM) attack which copy a sequence of frames and paste its mirrored versions somewhere else on the same video. A new FD/FM detection method is proposed in this work. The method extracts binary features from frames and determines the similarity among features. Peak-signal-to-noise ratio of the candidate frames is used to eliminate some of the large number of candidates to improve the detection of the forged frames. Experimental results show that the proposed method successfully detects FM/FD attacks and also yields better execution time and detection results compared to similar works reported in the literature.
Phosphorylation of presynaptic and postsynaptic calcium channels by cAMP‐dependent protein kinase in hippocampal neurons.

Phosphorylation by cAMP‐dependent protein kinase (PKA) and other second messenger‐activated protein kinases modulates the activity of a variety of effector proteins including ion channels. Anti‐peptide antibodies specific for the alpha 1 subunits of the class B, C or E calcium channels from rat brain specifically recognize a pair of polypeptides of 220 and 240 kDa, 200 and 220 kDa, and 240 and 250 kDa, respectively, in hippocampal slices in vitro. These calcium channels are localized predominantly on presynaptic and dendritic, somatic and dendritic, and somatic sites, respectively, in hippocampal neurons. Both size forms of alpha 1B and alpha 1E and the full‐length form of alpha 1C are phosphorylated by PKA after solubilization and immunoprecipitation. Stimulation of PKA in intact hippocampal slices also induced phosphorylation of 25‐50% of the PKA sites on class B N‐type calcium channels, class C L‐type calcium channels and class E calcium channels, as assessed by a back‐phosphorylation method. Tetraethylammonium ion (TEA), which causes neuronal depolarization and promotes repetitive action potentials and neurotransmitter release by blocking potassium channels, also stimulated phosphorylation of class B, C and E alpha 1 subunits, suggesting that these three classes of channels are phosphorylated by PKA in response to endogenous electrical activity in the hippocampus. Regulation of calcium influx through these calcium channels by PKA may influence calcium‐dependent processes within hippocampal neurons, including neurotransmitter release, calcium‐activated enzymes and gene expression.
Ship detection in SAR medium resolution imagery for maritime surveillance: Algorithm validation using AIS data

In this paper paper we address performances of ship detection algorithms in medium resolution SAR imagery. An automatic validation approach based on coastal AIS data allows to evaluate detectors efficiency. Detection capabilities remain sensitive to dataset features such as SAR imaging characteristics, meteorological conditions or vessel size. The influence of this different key parameters is fully assessed in this study. This analysis is valuable for operational services, allowing to select the most appropriate type of data for different applications in maritime surveillance.
A Tutorial Review of Electrical Neuroimaging From Group-Average to Single-Trial Event-Related Potentials

This tutorial review details some of the recent advances in signal analyses applied to event-related potential (ERP) data. These “electrical neuroimaging” analyses provide reference-independent measurements of response strength and response topography that circumvent statistical and interpretational caveats of canonical ERP analysis methods while also taking advantage of the greater information provided by high-density electrode montages. Electrical neuroimaging can be applied across scales ranging from group-averaged ERPs to single-subject and single-trial datasets. We illustrate these methods with a tutorial dataset and place particular emphasis on their suitability for studies of clinical and/or developmental populations.
Experimental and Computational Atomic Spectroscopy for Astrophysics : Oscillator strengths and lifetimes for Mg I, Si I, Si II, Sc I, and Sc II

Atomic data such as oscillator strengths and wavelengths are important for astrophysical applications as they have a crucial role in determining abundances of specific elements in a star, a galaxy, or any object emitting radiation in the space. Stars in the Galaxy mostly keep the composition of the interstellar gas from which they were formed, therefore studying stellar abundances helps us understand how the Milky Way was formed and how it evolved. However, atomic data of most chemical elements are incomplete and/or have low quality, particularly for the infrared wavelength region and for the highly excited levels. This PhD project focuses on completing missing atomic data for the infrared region in addition to the optical and UV regions, and improving the existing data. In order to achieve this, I have performed both laboratory measurements and large scale atomic structure calculations.Experimental oscillator strengths have been derived by combining measured branching fractions with radiative lifetimes. A hollow cathode discharge lamp has been used as a light source to produce free atoms in a plasma and a Fourier transform spectrometer has recorded the intensity-calibrated high-resolution spectra. In addition, atomic structure calculations have been performed using the multiconfiguration Hartree-Fock programmes ATSP2K and GRASP2K to determine oscillator strengths and lifetimes. Combining the experimental work with the computational approach allows determining a large set of accurate and validated atomic data.In this thesis, an evaluated set of atomic data for Mg I, Si I, Si II, Sc I, and Sc II has been provided for astrophysical applications. The experimental oscillator strengths in the infrared region have been measured for the first time. The uncertainties in the experimental oscillator strengths are as low as 5% for strong transitions. The theoretical oscillator strengths are validated with the experimental values and with internal investigations of the length and velocity forms. The small uncertainties in the values allow accurate astrophysical abundance determinations within the 0.1dex uncertainty. (Less)
Cardiopulmonary exercise testing and prognosis in heart failure due to systolic left ventricular dysfunction: a validation study of the European Society of Cardiology Guidelines and Recommendations (2008) and further developments

Aims: The study aims were to validate the cardiopulmonary exercise testing (CPET) parameters recommended by the European Society of Cardiology 2008 Guidelines for risk assessment in heart failure (HF) (ESC-predictors) and to verify the predictive role of 11 supplementary CPET (S-predictors) parameters. Methods and results: We followed 749 HF patients for cardiovascular death and urgent heart transplantation for 3 years: 139 (19%) patients had cardiac events. ESC-predictors – peak oxygen consumption (VO2), slope of minute ventilation vs carbon dioxide production (VE/VCO2) and exertional oscillatory ventilation – were all related to outcome at univariate and multivariable analysis. The ESC/2008 prototype based on ESC-predictors presented a Harrell's C concordance index of 0.725, with a likely χ2 of 98.31. S-predictors – predicted peak VO2, peak oxygen pulse, peak respiratory exchange ratio, peak circulatory power, peak VE/VCO2, VE/VCO2 slope normalized by peak VO2, VO2 efficiency slope, ventilatory anaerobic threshold detection, peak end-tidal CO2 partial pressure, peak heart rate, and peak systolic arterial blood pressure (SBP) – were all linked to outcome at univariate analysis. When individually added to the ESC/2008 prototype, only peak SBP and peak O2 pulse significantly improved the model discrimination ability: the ESC + peak SBP prototype had a Harrell's C index 0.750 and reached the highest likely χ2 (127.16, p < 0.0001). Conclusions: We evaluated the longest list of CPET prognostic parameters yet studied in HF: ESC-predictors were independent predictors of cardiovascular events, and the ESC prototype showed a convincing predictive capacity, whereas none of 11 S-predictors enhanced the prognostic performance, except peak SBP.
Support Vector Machines and MLP for automatic classification of seismic signals at Stromboli volcano

We applied and compared two supervised pattern recognition techniques, namely the Multilayer Perceptron (MLP) and Support Vector Machine (SVM), to classify seismic signals recorded on Stromboli volcano. The available data are firstly preprocessed in order to obtain a compact representation of the raw seismic signals. We extract from data spectral and temporal information so that each input vector is made up of 71 components, containing both spectral and temporal information extracted from the early signal. We implemented two classification strategies to discriminate three different seismic events: landslide, explosion-quake, and volcanic microtremor signals. The first method is a two-layer MLP network, with a Cross-Entropy error function and logistic activation function for the output units. The second method is a Support Vector Machine, whose multi-class setting is accomplished through a 1vsAll architecture with gaussian kernel. The experiments show that although the MLP produces very good results, the SVM accuracy is always higher, both in term of best performance, 99.5%, and average performance, 98.8%, obtained with different sampling permutations of training and test sets.
Therapy for Child Sexual Abuse: Women Talk About Helpful and Unhelpful Therapy Experiences

ABSTRACT Women with histories of childhood sexual abuse (CSA) were asked to describe what was helpful and unhelpful to them in therapy. From 191 completed postal questionnaires, a subsample of 20 participants was interviewed. This paper focuses on three specific areas of therapy raised by interviewees: (1) Establishing a therapeutic relationship; (2) talking about experiences and effects of CSA; and (3) dealing with errors in therapy. Findings suggest that to avoid making serious therapy errors, therapists (1) need special skills to be aware of the dynamics and effects of CSA and of abuse-focused therapy and to deal with abuse-related material, and (2) need to develop an equal and open therapy relationship that includes ongoing consultation with clients about their experiences of therapy.
Selfish behavior of restriction-modification systems

Plasmids carrying gene pairs encoding type II DNA restriction endonucleases and their cognate modification enzymes were shown to have increased stability in Escherichia coli. The descendants of cells that had lost these genes appeared unable to modify a sufficient number of recognition sites in their chromosomes to protect them from lethal attack by the remaining restriction enzyme molecules. The capacity of these genes to act as a selfish symbiont is likely to have contributed to the evolution of restriction-modification gene pairs.
Data Mining Classification Methods Applied in Drug Design

Data mining incorporates a group of statistical methods used to analyze a set of information, or a data set. It operates with models and algorithms, which are powerful tools with the great potential. They can help people to understand the patterns in certain chunk of information so it is obvious that the data mining tools have a wide area of applications. For example in the theoretical chemistry data mining tools can be used to predict moleculeproperties or improve computer-assisted drug design. Classification analysis is one of the major data mining methodologies. The aim of thecontribution is to create a classification model, which would be able to deal with a huge data set with high accuracy. For this purpose logistic regression, Bayesian logistic regression and random forest models were built using R software. TheBayesian logistic regression in Latent GOLD software was created as well. These classification methods belong to supervised learning methods. It was necessary to reduce data matrix dimension before construct models and thus the factor analysis (FA) was used. Those models were applied to predict the biological activity of molecules, potential new drug candidates. Keywords—data mining, classification, drug design, QSAR
Improved cancelable fingerprint templates using minutiae-based functional transform

Since Ratha et al. introduced the functional transform for cancelable fingerprint templates, a few simulation attacks to this method have been proposed. The attacks are based on the fact that the transform depends only on the predefined parameters. That is, the attacker may fully simulate the transform and partially invert it if the parameters are available. Although an original template is transformed using different parameters for different systems, even the compromise of only one of these systems may reveal the original template, which may be a serious potential threat from a practical viewpoint. In this paper, we propose an improved functional transform, whose parameters are decided by the original template, as well as predefined user-specific keys. Because the information on the original template will not be available to the attacker even when a system is compromised, the proposed method significantly improves the security of the original template by preventing the attacker from reconstructing the transform. Copyright © 2013 John Wiley & Sons, Ltd.
A universal electrode approach for automated electrochemical detection of bacterial 16S rRNA

Transforming microfluidics based biosensing systems from laboratory research into clinical reality remains an elusive goal despite decades of intensive research. A fundamental obstacle towards the development of fully automated microfluidic diagnostic systems is the lack of an effective strategy for combining multiple pumping. , sample preparation, and detection modules into an integrated platform. Herein. , we report a universal electrode approach, which incorporates DC electrolytic pumping, AC electrokinetic sample preparation, and self-assembled monolayer based electrochemical sensing on a single micro fluidic platform, to automate complicated molecular analysis procedures in non-traditional healthcare settings. Using the universal electrode approach, major microfluidic operations required in molecular diagnostics, such as pumping. , mixing. , washing, and sensing can be performed in a single platform. We demonstrate the universal electrode platform for detecting bacterial 16S rRNA, a phylogenetic marker. , toward rapid diagnostics of urinary tract infection. Since only electronic interfaces are required to operate the platform, the universal electrode approach represents an effective system integration strategy to realize the potential of micro fluidics in molecular diagnostics at the point of care.
Development of Human Blood‐CSF‐Brain Barrier

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