Miracle-dz/UniFAR-FTUs huggingface dataset:
The rheology of suspensions of solid particles

We present data for the rheology of suspensions of monodisperse particles of varying aspect ratio, from oblate to prolate, and covering particle volume fractions φ from dilute to highly concentrated. Rheology is characterized by fitting the experimental data to the model of Herschel & Bulkley (Herschel & Bulkley 1926 Kolloid Z. 39, 291–300 (doi:10.1007/BF01432034)) yielding three rheometric parameters: consistency K (cognate with viscosity); flow index n (a measure of shear-thinning); yield stress τ0. The consistency K of suspensions of particles of arbitrary aspect ratio can be accurately predicted by the model of Maron & Pierce (Maron & Pierce 1956 J. Colloid Sci. 11, 80–95 (doi:10.1016/0095-8522(56)90023-X)) with the maximum packing fraction φm as the only fitted parameter. We derive empirical relationships for φm and n as a function of average particle aspect ratio rp and for τ0 as a function of φm and a fitting parameter τ*. These relationships can be used to predict the rheology of suspensions of prolate particles from measured φ and rp. By recasting our data in terms of the Einstein coefficient, we relate our rheological observations to the underlying particle motions via Jeffery’s (Jeffery 1922 Proc. R. Soc. Lond. A 102, 161–179 (doi:10.1098/rspa.1922.0078)) theory. We extend Jeffery’s work to calculate, numerically, the Einstein coefficient for a suspension of many, initially randomly oriented particles. This provides a physical, microstructural explanation of our observations, including transient oscillations seen during run start-up and changes of rheological regime as φ increases.
Semi-supervised learning of speech sounds

Recently, there has been much interest in both semi-supervised and manifold learning algorithms, though their applicability has not been explored for all domains. This paper has two goals: (i) to demonstrate semi-supervised approaches based solely on clustering are insufficient for phoneme classification and (ii) to present a new manifold-based semi-supervised algorithm to remedy this shortcoming. The improved performance of our approach over cluster-based methods substantiates the practical relevance of a geometric perspective on speech sounds.
MIREX 2013 QBSH TASK : NETEASE ’ S SOLUTION

This document describes our submission to QBSH task of MIREX 2013. Our algorithm adopts a two-stage cascaded solution based on Locality Sensitive Hashing (LSH) and accurate matching of frame-level pitch sequence. Firstly, LSH is employed to quickly filter out songs with low matching possibilities, resulting in a list of candidate songs for further processing. In the second stage, Dynamic Time Warping (DTW) is applied to find the N (set to 10) most matching songs from the candidate list. This approach allows for fast pruning of irrelevant songs whilst preserving the most matching ones.
Proteomic analyses of recombinant human follicle-stimulating hormone and urinary-derived gonadotropin preparations.

OBJECTIVE To understand the properties of each available gonadotropin preparation, especially in terms of the differences between urinary-derived and recombinant preparations. STUDY DESIGN Human menopausal gonadotropin (hMG), highly purified urinary-derived follicle-stimulating hormone (uFSH-HP) and recombinant FSH (rFSH) were subjected to 2-dimensional gel electrophoresis (2-DE), and protein spots were visualized by silver-staining procedures. Major spots were analyzed by mass spectrometry. Fluorescent-labeled preparations were also subjected to 2-DE to evaluate the quantities of FSH isohormones contained in each preparation. RESULTS 2-DE and mass spectrometry analyses of hMG identified many extracellular proteins as major impurities and several plasma membrane proteins including prion proteins. Both uFSH-HP and rFSH demonstrated slight impurities and showed several alpha and beta subunit isohormones. rFSH contained higher amounts of the basic isohormones of the alpha subunit than uFSH-HP, whereas the predominance of the basic isohormones was less significant in the beta subunit. CONCLUSION Proteomic analyses demonstrated the detailed protein profiles of each preparation. Differences in the quantities of alpha subunit isohormones may contribute to the variations in FSH activity observed between recombinant and urinary-derived FSH preparations.
Gated Recurrent Neural Tensor Network

Recurrent Neural Networks (RNNs), which are a powerful scheme for modeling temporal and sequential data need to capture long-term dependencies on datasets and represent them in hidden layers with a powerful model to capture more information from inputs. For modeling long-term dependencies in a dataset, the gating mechanism concept can help RNNs remember and forget previous information. Representing the hidden layers of an RNN with more expressive operations (i.e., tensor products) helps it learn a more complex relationship between the current input and the previous hidden layer information. These ideas can generally improve RNN performances. In this paper, we proposed a novel RNN architecture that combine the concepts of gating mechanism and the tensor product into a single model. By combining these two concepts into a single RNN, our proposed models learn long-term dependencies by modeling with gating units and obtain more expressive and direct interaction between input and hidden layers using a tensor product on 3-dimensional array (tensor) weight parameters. We use Long Short Term Memory (LSTM) RNN and Gated Recurrent Unit (GRU) RNN and combine them with a tensor product inside their formulations. Our proposed RNNs, which are called a Long-Short Term Memory Recurrent Neural Tensor Network (LSTMRNTN) and Gated Recurrent Unit Recurrent Neural Tensor Network (GRURNTN), are made by combining the LSTM and GRU RNN models with the tensor product. We conducted experiments with our proposed models on word-level and character-level language modeling tasks and revealed that our proposed models significantly improved their performance compared to our baseline models.
A Viscometer Based on Velocity Attenuation of Rotary Cylinder

A viscometer based on velocity attenuation of rotating cylinder is presented in the paper. A solid rotor motor drives the cylinder immersed in liquid in a cup to a scheduled velocity. The electricity supply of the motor is cut, the velocity of the cylinder with rotor of the motor attenuates with time because of viscous torque and other resistance torque. The velocity is measured by optical encoder. Viscosity of the fluid was calculated by a computer. Experiments are carried out and results show that deviation of viscosity beyond 1000 mPa•s are below 3%. The viscometer can be used in measurement of viscosity beyond 1000 mPa•s in industry.
Improved Translation with Source Syntax Labels

We present a new translation model that include undecorated hierarchical-style phrase rules, decorated source-syntax rules, and partially decorated rules. Results show an increase in translation performance of up to 0.8% BLEU for German--English translation when trained on the news-commentary corpus, using syntactic annotation from a source language parser. We also experimented with annotation from shallow taggers and found this increased performance by 0.5% BLEU.
Sub-Pixel Edge Detection for Precision Measurement Based on Canny Criteria

A new nonlinear intensity interpolation algorithm is presented to realize sub-pixel edge detection. The interpolation algorithm based on the Canny criteria makes full use of grads information attained by Canny edge detection to perform special interpolation in the grads direction. When the resolution is enhanced, the interpolated image by the new interpolation scheme can efficiently preserve high frequency component in the original image. The edge detection of interpolated image permits high precision localization. The new interpolation algorithm is more effective in reserving the grads information of the step edge of the initial image than the usual linear interpolations. It requires simpler computation than the present non-linear interpolations.
Silkworm Gut Fiber of Bombyx mori as an Implantable and Biocompatible Light-Diffusing Fiber

This work describes a new approach to the delivery of light in deeper tissues, through a silk filament that is implantable, biocompatible, and biodegradable. In the present work, silkworm gut fibers (SGFs) of Bombyx mori L. , are made by stretching the silk glands. Morphological, structural, and optical properties of the fibers have been characterized and the stimulatory effect of red laser light diffused from the fiber was assayed in fibroblast cultures. SGFs are formed by silk fibroin (SF) mainly in a β-sheet conformation, a stable and non-soluble state in water or biological fluids. The fibers showed a high degree of transparency to visible and infrared radiation. Using a red laser (λ = 650 nm) as source, the light was efficiently diffused along the fiber wall, promoting a significant increment in the cell metabolism 5 h after the irradiation. SGFs have shown their excellent properties as light-diffusing optical fibers with a stimulatory effect on cells.
An energy and distance based clustering protocol for wireless sensor networks

This paper proposes an energy-efficient clustering protocol for wireless sensor networks (WSNs). Unlike LEACH and other existing clustering protocols, the proposed clustering protocol considers both the residual energy of a sensor node and the distance between the sensor node and the sink in electing a cluster head and a sensor node with more residual energy and closer to the sink has a higher probability to become a cluster head. Simulation results show that compared with LEACH the proposed clustering protocol can better balance the energy consumption among sensor nodes, and can thus effectively reduce the energy consumption and prolong the lifetime of a WSN.
Power-Law Distributions for Paraphrases Extracted from Bilingual Corpora

We describe a novel method that extracts paraphrases from a bitext, for both the source and target languages. In order to reduce the search space, we decompose the phrase-table into sub-phrase-tables and construct separate clusters for source and target phrases. We convert the clusters into graphs, add smoothing/syntactic-information-carrier vertices, and compute the similarity between phrases with a random walk-based measure, the commute time. The resulting phrase-paraphrase probabilities are built upon the conversion of the commute times into artificial co-occurrence counts with a novel technique. The co-occurrence count distribution belongs to the power-law family.
Nanopatterning of gold colloids for label-free biosensing

We present an approach for the controlled positioning of single gold colloids onto dot and line nanoarrays which have the potential to serve as label-free biosensor platforms. The separation between the high-resolution nanolithography step, extreme ultraviolet interference lithography, and the subsequent functionalization has many advantages, among them the independence of the linkage chemistry. The activation of the pre-patterned substrates is performed by transforming them into a surface of biotinylated nanopatches in a protein-resistant background. Complexes of streptavidin and single-stranded DNAs can then be selectively immobilized onto the biotinylated patches, which are embedded in an inert background. This approach enables the creation of single gold colloid dot and line arrays by directed self-assembly using the specificity of DNA hybridization.
Generating Content for Scenario-Based Serious-Games Using CrowdSourcing

Scenario-based serious-games have become an important tool for teaching new skills and capabilities. An important factor in the development of such systems is reducing the time and cost overheads in manually creating content for these scenarios. To address this challenge, we present ScenarioGen, an automatic method for generating content about everyday activities through combining computer science techniques with the crowd. ScenarioGen uses the crowd in three different ways: to capture a database of scenarios of everyday activities, to generate a database of likely replacements for specific events within that scenario, and to evaluate the resulting scenarios. We evaluated ScenarioGen in 6 different content domains and found that it was consistently rated as coherent and consistent as the originally captured content. We also compared ScenarioGen's content to that created by traditional planning techniques. We found that both methods were equally effective in generating coherent and consistent scenarios, yet ScenarioGen's content was found to be more varied and easier to create.
Investigating habits: strategies, technologies and models

Understanding habits at a biological level requires a combination of behavioral observations and measures of ongoing neural activity. Theoretical frameworks as well as definitions of habitual behaviors emerging from classic behavioral research have been enriched by new approaches taking account of the identification of brain regions and circuits related to habitual behavior. Together, this combination of experimental and theoretical work has provided key insights into how brain circuits underlying action-learning and action-selection are organized, and how a balance between behavioral flexibility and fixity is achieved. New methods to monitor and manipulate neural activity in real time are allowing us to have a first look “under the hood” of a habit as it is formed and expressed. Here we discuss ideas emerging from such approaches. We pay special attention to the unexpected findings that have arisen from our own experiments suggesting that habitual behaviors likely require the simultaneous activity of multiple distinct components, or operators, seen as responsible for the contrasting dynamics of neural activity in both cortico-limbic and sensorimotor circuits recorded concurrently during different stages of habit learning. The neural dynamics identified thus far do not fully meet expectations derived from traditional models of the structure of habits, and the behavioral measures of habits that we have made also are not fully aligned with these models. We explore these new clues as opportunities to refine an understanding of habits.
Development of slow release silver-containing biomaterial for wound care applications

Silver-containing wound dressings are now commonly available with much publicised claims of antimicrobial activities against all kinds of pathogens including methicillin-resistant Staphylococcus aureus (MRSA). However, there are little or no credible reports on the control release agents for the minimum potent quantities of silver needed in dressings for antimicrobial purposes over time. This paper introduces a new biomaterial fibre made from natural polymers with an inbuilt ability to gel and absorb large quantities of pseudo exudates. Furthermore, the new fibre carries up to six times less silver than it is conventionally used in silver dressings and displays a very slow rate of release whilst maintaining full potency over time against known microorganisms including methicillin-resistant S. aureus. The paper concludes that the developed fibre has long-lasting antimicrobial and gelling properties comparable, if not better, than Acticoat AA and Aquacel Ag, two commercially available silver dressings.
Global Asymptotic Stabilization of Nonlinear Deterministic Systems Using Wiener Processes

The objective of this study is to present a noise-assisted stabilization method and a constructive method for designing a stabilizing controller. We investigate the stabilization of a deterministic nonlinear affine system by using a controller with a Wiener process. Our approach focuses on the global asymptotic stabilization of nonholonomic systems. The proposed method for designing a stabilizing controller is based on the notion of a stochastic control Lyapunov function. We show that if there exists a stochastic control Lyapunov function with small control property, the designed controller globally asymptotically stabilizes a given system with probability one.
Structural purity of magnetite nanoparticles in magnetotactic bacteria

Magnetosome biomineralization and chain formation in magnetotactic bacteria are two processes that are highly controlled at the cellular level in order to form cellular magnetic dipoles. However, even if the magnetosome chains are well characterized, controversial results about the microstructure of magnetosomes were obtained and its possible influence in the formation of the magnetic dipole is to be specified. For the first time, the microstructure of intracellular magnetosomes was investigated using high-resolution synchrotron X-ray diffraction. Significant differences in the lattice parameter were found between intracellular magnetosomes from cultured magnetotactic bacteria and isolated ones. Through comparison with abiotic control materials of similar size, we show that this difference can be associated with different oxidation states and that the biogenic nanomagnetite is stoichiometric, i.e. structurally pure whereas isolated magnetosomes are slightly oxidized. The hierarchical structuring of the magnetosome chain thus starts with the formation of structurally pure magnetite nanoparticles that in turn might influence the magnetic property of the magnetosome chains.
User Centric Privacy in Mobile Communication Scenarios

One common assumption when defining location privacy metrics is that one is dealing with attackers whose objective is to re-identify an individual out of an anonymized data set. However, today's communication scenarios are more diverse. For instance, there are several entities involved in mobile location sharing between individuals. Hence, in a communication relation with a service provider (e.g. SNS or network infrastructure) or with social contacts, an anonymity approach seems inadequate. Between each user and every single entity involved there is some level of trust and the identities are already known, at least to some extent. Hence, taking an anonymity approach for communication relations to peers or service providers (e.g. SNS or network infrastructure) seems to be inadequate. Therefore, we present an attacker model and propose a user-centric privacy metric to allow a user to uncover the extent of information disclosure and to evaluate autonomously his privacy level in a communication relation with semi-trusted listener groups. The goal of such a metric is to enable an individual to estimate the privacy loss caused by disclosing location information in a specific communication scenario and thus enabling the user to make informed choices, e.g. choose the right protection mechanism.
Improving the understanding and treatment of complex grief: an important issue for psychotraumatology

In the Netherlands, every year 500,000 people are confronted with the death of a close relative. Many of these people experience little emotional distress. In some, bereavement precipitates severe grief, distress, and dysphoria. A small yet significant minority of bereaved individuals develops persistent and debilitating symptoms of persistent complex bereavement disorder (PCBD) (also termed prolonged grief disorder), posttraumatic stress disorder, and depression. Knowledge about early identification of, and preventive care for complex grief has increased. Moreover, in recent years there has been an increase in treatment options for people for whom loss leads to persistent psychological problems. That said, preventive and curative treatments are effective for some, but not all bereaved individuals experiencing distress and dysfunction following loss. This necessitates further research on the development, course, and treatment of various stages of complex grief, including PCBD. Highlights of the article “Complex grief” is an informal term referring to debilitating, non-normative grief. It will likely be named Prolonged Grief Disorder in the forthcoming ICD-11. It is named Persistent Complex Bereavement Disorder in DSM-5. Research on the development, course, and treatment of complex grief is needed. This research should address different stages and manifestations of complex grief.
A probabilistic numerical algorithm based on Terracini's lemma for proving nondefectivity of Segre varieties

The CANDECOMP/PARAFAC (CP) tensor decomposition is a crucial data analysis and processing technique in applications and sciences. Tensors admitting a CP decomposition of rank at most s can be considered points of the sth order secant variety of a Segre variety, yet the most basic invariant of this variety—its dimension— is not yet fully understood. A conjecture was nevertheless proposed in [H. Abo, G. Ottaviani, and C. Peterson, Induction for secant varieties of Segre varieties. Trans. Amer. Math. Soc. , 361:767–792, 2009], proved to be correct for s ≤ 6. We propose a memory efficient probabilistic numerical algorithm based on Terracini’s Lemma to verify with high probability whether this conjecture is true. The proposed method can geometrically decrease the probability of incorrectly classifying a defective Segre variety as nondefective by performing more statistically independent checks. While increasing the precision of the calculations is not required to decrease the probability of an incorrect classification, a meticulous numerical analysis illustrates that the computations must, nevertheless, be performed with sufficiently high precision. The numerical experiments in this paper establish that the Segre varieties PC1 × PC2 × · · · × PCd embedded in PCn1×···×nd with generic rank s ≤ 55 obey the conjecture; the probability that the obtained results are due to chance is less than 10−55.