Miracle-dz/UniFAR-FTUs huggingface dataset:
The small world yields the most effective information spreading

The spreading dynamics of information and diseases are usually analyzed by using a unified framework and analogous models. In this paper, we propose a model to emphasize the essential difference between information spreading and epidemic spreading, where the memory effects, the social reinforcement and the non-redundancy of contacts are taken into account. Under certain conditions, the information spreads faster and broader in regular networks than in random networks, which to some extent supports the recent experimental observation of spreading in online society (Centola D 2010 Science 329 1194). At the same time, the simulation result indicates that the random networks tend to be favorable for effective spreading when the network size increases. This challenges the validity of the above-mentioned experiment for large-scale systems. More importantly, we show that the spreading effectiveness can be sharply enhanced by introducing a little randomness into the regular structure, namely the small-world networks yield the most effective information spreading. This work provides insights into the role of local clustering in information spreading.
Sialylated Core 1 O-Glycans Influence the Sorting of Pmel17/gp100 and Determine Its Capacity to Form Fibrils*

Pmel17 is a melanocyte/melanoma-specific protein that is essential for the maturation of melanosomes to form mature, fibrillar, and pigmented organelles. Recently, we reported that the less glycosylated form of Pmel17 (termed iPmel17) is sorted via the plasma membrane in a manner distinct from mature Pmel17 (termed mPmel17), which is sorted directly to melanosomes. To clarify the mechanism(s) underlying the distinct processing and sorting of Pmel17, we generated a highly specific antibody (termed αPEP25h) against an epitope within the repeat domain of Pmel17 that is sensitive to changes in O-glycosylation. αPEP25h recognizes only iPmel17 and allows analysis of the processing and sorting of iPmel17 when compared with αPEP13h, an antibody that recognizes both iPmel17 and mPmel17. Our novel findings using αPEP25h demonstrate that iPmel17 differs from mPmel17 not only in its sensitivity to endoglycosidase H, but also in the content of core 1 O-glycans modified with sialic acid. This evidence reveals that iPmel17 is glycosylated differently in the Golgi and that it is sorted through the secretory pathway. Analysis of Pmel17 processing in glycosylation-deficient mutant cells reveals that Pmel17 lacking the correct addition of sialic acid and galactose loses the ability to form fibrils. Furthermore, we show that addition of sialic acid affects the stability and sorting of Pmel17 and reduces pigmentation. Alterations in sialyltransferase activity and substrates differ between normal and transformed melanocytes and may represent a critical change during malignant transformation.
Insolvency Prediction Model Using Multivariate Discriminant Analysis and Artificial Neural Network for the Finance Industry in New Zealand

Models of insolvency are important for managers who may not appreciate how serious the financial health of their company is becoming until it is too late to take effective action. Multivariate discriminant analysis and artificial neural network are utilized in this study to create an insolvency predictive model that could effectively predict any future failure of a finance company and validated in New Zealand. Financial ratios obtained from corporate balance sheets are used as independent variables while failed/non-failed company is the dependent variable. The results indicate the financial ratios of failed companies differ significantly from non-failed companies. Failed companies were also less profitable and less liquid and had higher leverage ratios and lower quality assets.
Exploring constructive algorithms with stopping criteria to produce accurate and diverse individual neural networks in an ensemble

Explores the use of constructive algorithms with stopping criteria to design accurate and diverse individual neural networks (NNs) in an ensemble. Based on constructive algorithms and stopping criteria, a constructive neural network ensemble (CNNE) method to design accurate and diverse individual NNs in an ensemble is proposed. The CNNE is applied to three benchmarked problems in NNs. They are cancer, diabetes and heart disease problems. The experimental results demonstrate the effectiveness of CNNE.
Synthesis, characterization and in vitro/in vivo evaluation of novel reduction-sensitive hybrid nano-echinus-like nanomedicine

Abstract To remedy the problems resulting from the usage of anti-cancer drugs in cancer chemotherapy, such as deficient drug concentration in tumour cells, low water-solubility and non-specific distribution of antitumour drugs, a kind of reduction-sensitive polymer prodrug of curcumin (Cur) containing in the nano-echinus was synthesized and designed. The nano-echinus-like nanomedicine presented synergistic effect with glycyrrhetic acid (GA) and oligomeric hyaluronic (HA) for targeting and combating HepG2 human liver cancer cell. Firstly, a kind of small molecular prodrug of Cur, dithiodipropionic acid-Cur (-SS-Cur), was chemically conjugated onto the side chain of the conjugated glycyrrhetic acid- oligomeric hyaluronic (GA-HA) to generate an amphiphilic polymeric prodrug of Cur, GA-HA-SS-Cur. The obtained GA-HA-SS-Cur prodrug and subsidiary material mPEG-DSPE could self-assemble into a sea urchin-like micelles in aqueous media and release Cur rapidly in response to glutathion (GSH). Then, Cur was loaded into the nano-echinus with a particle size of (118.1 ± 0.2 nm) and drug-loading efficiency of (8.03 ± 2.1%). The structure of GA-HA-SS-Cur was characterized by 1H-NMR in this report. The morphology of micelles was observed with a transmission electron microscope (TEM). Subsequently, the reduction-sensitivity of the nano-echinus was confirmed by the changes in in-vitro drug release after different concentrations of GSH treatment. Besides, the cellular uptake behaviour and MTT assays of the nano-echinus were investigated, suggesting that the nano-echinus was of desirable safety and could be taken into HepG2 cells in a time-dependent manner. Later, anti-tumour efficacy in vivo revealed the effective inhibition of tumour growth.
On the utility of causal diagrams in modeling attrition: a practical example.

In a recent communication [1], Breskin, Cole and Hudgens aimed to demonstrate “how single-world intervention graphs can supplement traditional causal diagrams”. The example used in their demonstration involved selection bias due to attrition, namely, subjects drop-ping out from a randomized trial before the outcome is observed. Here we use the same example to demonstrate the opposite conclusion; the derivation presented by Breskin et al. is in fact longer and more complicated than the standard, three-step derivation facilitated by traditional causal diagrams. We further show that more natural solutions to attrition problems are obtained when viewed as missing-data problems encoded in causal diagrams. The trial example of Breskin et al. is shown in the causal diagram of Figure 1a. The task is to estimate the average causal eﬀect E [ Y | do ( A = a )] in the general population, given complete data on A (vaccine assignment) and W (injection site pain), while data on Y (disease outcome) is available only for those subjects who did not drop out of the study ( S = 0). U stands for unmeasured health status, and participants with poor health ( U = 1) are assumed to be both more likely to experience pain and get the disease. The standard strategy of causal diagrams is to convert the query expression, E [ Y | do ( A = a )], into an equivalent expression that can be estimated from the available data 3]. The derivation goes as follows:
Assessing musical ability quickly and objectively: development and validation of the Short‐PROMS and the Mini‐PROMS

The study of musical ability has gained considerable traction across disciplines in recent years. In comparison, less effort has been invested in the development of sound measures of musical ability. To redress this gap, we conducted four studies to empirically validate two brief measures derived from the Profile of Music Perception Skills (PROMS)—an exceptionally inclusive battery of musical abilities that takes about 1 h to complete. In the Short‐PROMS, test duration was reduced to less than half an hour by substantially reducing the number of trials per subtest. In the Mini‐PROMS, the number of subtests was reduced to four, resulting in a battery that takes 15 min to complete. Both measures exhibited good internal consistency and retest reliability. Support for convergent, discriminant, and criterion validity was found across the studies. Additional strengths of the new instruments include their suitability for online administration and a feature called Modular PROMS, which offers researchers the possibility to request customized batteries that may include any combination of the subtests. The role of refining objective assessment instruments in research on music and the mind is discussed.
Genomics Nursing Faculty Champion Initiative

Nurse faculty are challenged to keep up with the emerging and fast-paced field of genomics and the mandate to prepare the nursing workforce to be able to translate genomic research advances into routine clinical care. Using Faculty Champions and other options, the initiative stimulated curriculum development and promoted genomics curriculum integration. The authors summarize this yearlong initiative for undergraduate and graduate nursing faculty.
AlN-on-Si MEMS resonator bounded by wide acoustic bandgap two-dimensional phononic crystal anchors

We report an AlN-on-Si Lamb wave resonator with a unique wide acoustic bandgap (ABG) phononic crystal (PnC) structure at its anchors that provides an almost 4-fold increase in quality factor (Q). We show that the wider ABG provides for greater suppression of anchor loss and thus higher Q relative to a narrower ABG. Compared to more common circular void PnC structures, the unique PnC structures presented herein based on solid disks offer a 9-fold increase in the ABG size (82MHz vs. 9MHz) at a similar center frequency around 142MHz. The measured improvements in Q over multiple devices are consistent with finite element simulations on tuning the ABG size.
MAAP Annotate: When archaeology meets augmented reality for annotation of megalithic art

Megalithic art is a spectacular form of symbolic representation found on prehistoric monuments. Carved by Europe's first farmers, this art allows an insight into the creativity and vision of prehistoric communities. As examples of this art continue to fade, it is increasingly important to document and study these symbols. This paper presents MAAP Annotate, a Mixed Reality annotation tool from the Megalithic Art Analysis Project (MAAP). It provides an innovative method of interacting with megalithic art, combining cross-disciplinary research in digital heritage, 3D scanning and imaging, and augmented reality. The development of the tool is described, alongside the results of an evaluation carried out on a group of archaeologists from University College Dublin, Ireland. It is hoped that such tools will enable archaeologists to collaborate worldwide, and non-specialists to experience and learn about megalithic art.
A novel mixed values k-prototypes algorithm with application to health care databases mining

The current availability of large datasets composed of heterogeneous objects stresses the importance of large-scale clustering of mixed complex items. Several algorithms have been developed for mixed datasets composed of numerical and categorical variables, a well-known algorithm being the k-prototypes. This algorithm is efficient for clustering large datasets given its linear complexity. However, many fields are handling more complex data, for example variable-size sets of categorical values mixed with numerical and categorical values, which cannot be processed as is by the k-prototypes algorithm. We are proposing a variation of the k-prototypes clustering algorithm that can handle these complex entities, by using a bag-of-words representation for the multivalued categorical variables. We evaluate our approach on a real-world application to the clustering of administrative health care databases in Quebec, with results illustrating the good performances of our method.
Dysregulation of Amyloid-β Protein Precursor, β-Secretase, Presenilin 1 and 2 Genes in the Rat Selectively Vulnerable CA1 Subfield of Hippocampus Following Transient Global Brain Ischemia

Abstract The interaction between brain ischemia and Alzheimer’s disease (AD) has been intensively investigated recently. Nevertheless, we have not yet understood the nature and mechanisms of the ischemic episodes triggering the onset of AD and how they influence its slow progression. The assumed connection between brain ischemia and the accumulation of amyloid-β (Aβ) peptide awaits to be clearly explained. In our research, we employed a rat cardiac arrest model to study the changes in gene expression of amyloid-β protein precursor (AβPP) and its cleaving enzymes, β- and γ-secretases (including presenilins) in hippocampal CA1 sector, following transient 10-min global brain ischemia. The quantitative reverse-transcriptase PCR assay demonstrated that the expression of all above genes that contribute to Aβ peptide generation was dysregulated during 30 days in postischemic hippocampal CA1 area. It suggests that studied Aβ peptide generation-related genes can be involved in AβPP metabolism, following global brain ischemia and will be useful to identify the molecular mechanisms underpinning that cerebral ischemia might be an etiological cause of AD via dysregulation of AβPP and its cleaving enzymes, β- and γ-secretases genes, and subsequently, it may increase Aβ peptide production and promote the gradual and slow development of AD neuropathology. Our data demonstrate that brain ischemia activates delayed neuronal death in hippocampus in an AβPP-dependent manner, thus defining a new and important mode of ischemic cell death.
Residence time distributions for turbulent, critical, and laminar pipe flow

AbstractLongitudinal dispersion processes are often described by the advection dispersion equation (ADE), which is analogous to Fick’s law of diffusion, where the impulse response function of the spatial concentration distribution is assumed to be Gaussian. This paper assesses the validity of the assumption of a Gaussian impulse response function, using residence time distributions (RTDs) obtained from new laboratory data. Measured up- and downstream temporal concentration proﬁles have been deconvolved to numerically infer RTDs for a range of turbulent, critical, and laminar pipe ﬂows. It is shown that the Gaussian impulse response function provides a good estimate of the system’s mixing characteristics for turbulent and critical ﬂows, and an empirical equation to estimate the dispersion coefficient for the Reynolds number, R, between 3,000 and 20,000 is presented. For laminar ﬂow, here identified as R<3,000, the RTDs do not conform to the Gaussian assumption because of insufficient available time for the.
Example Use of Low-Cost System for Capturing the Kinetic Parameters of Sperm Cells in Atlantic Salmon (Salmo salar)

A spermiogramme is an analysis performed to assess the quality of semen. Motility parameters are primarily obtained by subjectively observing samples or by using complex systems, such as computer-assisted sperm analysis (CASA). Here, we describe an easy and low-cost analysis system for obtaining quantifiable kinetic observations using Salmo salar semen model. In this work, we observed and captured video images of both fresh and stored Atlantic salmon semen to describe the possibility of analysis using the ImageJ CASA plug-in application for the kinetic parameters obtained from the videos. The semen is exposed to “powermilt”, a commercial activating solution, and the curvilinear velocity (VCL), straight line velocity (VSL), average path velocity (VAP) values are described. When the samples were activated after having been stored, differences were detected in sperm quality, using the low-cost plug-in application. However, this system was not able to detect small variations in the same recorded sample, suggesting limits in sample observation. The results indicate that it is possible to quantify the kinetic parameters of semen samples using a low-cost video system and free software.
Performance analysis of content-centric networks with mobility support

Content-centric networking (CCN) is being considered as a paradigm for the Future Internet. CCN is focused on the content itself rather than the host. CCN can be used to enhance the performance of delivery latency, robustness, and security. One of the immediate needs that CCN has to address is mobility support because the number of users who are using mobile devices is increasing rapidly. Users demand seamless handover when mobile devices move from one point of attachment to another point of attachment. In this paper, we first analyze existing approaches with respect to mobility, evaluate the performance of content-centric mobile networks in terms of handover delay and content delivery time, and show that content-centric networks work well in the mobile environment.
An efficient topology adaptation system for parametric active contour segmentation of 3D images

Active contour models have already been used succesfully for segmentation of organs from medical images in 3D. In implicit models, the contour is given as the isosurface of a scalar function, and therefore topology adaptations are handled naturally during a contour evolution. Nevertheless, explicit or parametric models are often preferred since user interaction and special geometric constraints are usually easier to incorporate. Although many researchers have studied topology adaptation algorithms in explicit mesh evolutions, no stable algorithm is known for interactive applications. In this paper, we present a topology adaptation system, which consists of two novel ingredients: A spatial hashing technique is used to detect self-colliding triangles of the mesh whose expected running time is linear with respect to the number of mesh vertices. For the topology change procedure, we have developed formulas by homology theory. During a contour evolution, we just have to choose between a few possible mesh retriangulations by local triangle-triangle intersection tests. Our algorithm has several advantages compared to existing ones: Since the new algorithm does not require any global mesh reparametrizations, it is very efficient. Since the topology adaptation system does not require constant sampling density of the mesh vertices nor especially smooth meshes, mesh evolution steps can be performed in a stable way with a rather coarse mesh. We apply our algorithm to 3D ultrasonic data, showing that accurate segmentation is obtained in some seconds.
A Novel Fingerprint Indexing Technique based on Level-1 and Level-2 Features

Biometric feature is used for human identification and verification in access management of physical, virtual work space and many other real time applications. The current state-of-art biometric identification algorithm focuses on accuracy and hence works well in terms of response time on small scale database.In real life scenario biometric database are huge and without any intelligent scheme the response time should be high, but the existing algorithms requires an exhaustive search on the database which increases proportionally when the size of the database grows. A good indexing technique is essential to narrow down the search space. This work addresses the problem of biometric indexing in the context of fingerprint. Indexing is a technique to reduce the number of candidate identities to be considered by the identification algorithm. The fingerprint indexing methodology projected in this work is based on a combination of Level-1 and Level-2 features. The result obtained portraits the combination of level-1 and level-2 features capitulates better performance than with any one feature.
Comparative Branching-Time Semantics for Markov Chains 3 and Continuous Stochastic

This paper presents various semantics in the branching-time spectrum of discrete-time and continuous-time Markov chains (DTMCs and CTMCs). Strong and weak bisimulation equivalence and simulation pre-orders are covered and are logically characterised in terms of the temporal logics PCTL (Probabilistic Computation Tree Logic) and CSL (Continuous Stochastic Logic). Apart from presenting various existing branching-time relations in a uniform manner, this paper presents the following new results: (i) strong simulation for CTMCs, (ii) weak simulation for CTMCs and DTMCs, (iii) logical characterizations thereof (including weak bisimulation for DTMCs), (iv) a relation between weak bisimulation and weak simulation equivalence, and (v) various connections between equivalences and pre-orders in the continuousand discrete-time setting. The results are summarized in a branching-time spectrum for DTMCs and CTMCs elucidating their semantics as well as their relationship.
Clover - Measuring the Cosmic Microwave Background B-mode Polarization

Clover is a UK-led experiment to measure the Bmode polarization of the cosmic microwave background. The instruments are currently under construction and deployment to the Pampa La Bola site in the Atacama Desert is planned for 2010. It consists of two 2-m class telescopes feeding background limited imaging arrays of ~100 dual polarization pixels at each of 97, 150 and 225 GHz. The waveguide and antenna fed TES bolometers are limited by unavoidable photon noise from the atmosphere, and read-out using NIST’s time domain multiplexing scheme. The entire instrument has been designed for exceptionally low systematic errors in polarization measurements, which has necessitated novel designs for the instrument optics, horn arrays, OMTs and detector feeds, as well as careful development of the scan strategy, field location and data analysis methods. The experiment aims to measure the polarization of the CMB with an angular resolution of 5.5′ − 8′ across 1000 deg2 of sky(angular multipole range 20 < l < 1000) to a sensitivity of 8 μK-arcmin after foreground cleaning. If all systematics are adequately controlled this will allow the detection of the primordial B-mode CMB anisotropies down to tensor to scalar ratios of 0.03, as well as providing extremely accurate measurements of the CMB temperature, E-mode polarization, and B-mode lensing polarization. Detecting or constraining the level of the primordial B-mode signal will allow constraints to be placed on the energy scale of inflation, providing an unprecedented insight into the physics of the early Universe. We describe the current status of the Clover project, including the current instrument design and construction status, and the development of the novel technology involved.
A Novel Rapidly Growing Mycobacterium Species Causing an Abdominal Cerebrospinal Fluid Pseudocyst Infection

Nontuberculous mycobacteria (NTM) are a rare cause of ventriculoperitoneal shunt infections. We describe the isolation and identification of a novel, rapidly growing, nonpigmented NTM from an abdominal cerebrospinal fluid pseudocyst. The patient presented with fevers, nausea, and abdominal pain and clinically improved after shunt removal. NTM identification was performed by amplicon and whole-genome sequencing.