Miracle-dz/UniFAR-FTUs huggingface dataset:
On models of fractal networks

A couple of iterative models for the theoretical study of fractal networks whose topologies are generated via iterated function systems is presented: a lumped‐parameter impedor‐oriented one and a two‐port‐network‐oriented one. With the former, the voltage and current patterns give a detailed understanding of the electromagnetic fields' self‐similar distribution throughout the network; on the other hand, model complexity exponentially increases with the prefractal iteration order. The latter ‘black‐box’ model only controls port‐oriented global parameters that are the ones commonly used in the integration of different electronic systems, and its complexity is independent of prefractal order. Sierpinski gasket and carpet topologies are reported as examples. Copyright © 2008 John Wiley & Sons, Ltd.
Revisiting Francisella tularensis subsp. holarctica, Causative Agent of Tularemia in Germany With Bioinformatics: New Insights in Genome Structure, DNA Methylation and Comparative Phylogenetic Analysis

Francisella (F.) tularensis is a highly virulent, Gram-negative bacterial pathogen and the causative agent of the zoonotic disease tularemia. Here, we generated, analyzed and characterized a high quality circular genome sequence of the F. tularensis subsp. holarctica strain 12T0050 that caused fatal tularemia in a hare. Besides the genomic structure, we focused on the analysis of oriC, unique to the Francisella genus and regulating replication in and outside hosts and the first report on genomic DNA methylation of a Francisella strain. The high quality genome was used to establish and evaluate a diagnostic whole genome sequencing pipeline. A genotyping strategy for F. tularensis was developed using various bioinformatics tools for genotyping. Additionally, whole genome sequences of F. tularensis subsp. holarctica isolates isolated in the years 2008–2015 in Germany were generated. A phylogenetic analysis allowed to determine the genetic relatedness of these isolates and confirmed the highly conserved nature of F. tularensis subsp. holarctica.
The role of olive oil in disease prevention: a focus on the recent epidemiological evidence from cohort studies and dietary intervention trials

Consumption of olive oil within the Mediterranean diet has been long known to have many health benefits. However, only over the last decade has epidemiological research confirmed its protective role against developing several chronic diseases. The objective of this review was to give an overview of the state of art epidemiological evidence concerning the relationship between olive oil and key public health outcomes including mortality, CVD, diabetes, metabolic syndrome (MetS), obesity and cancer, with a particular focus on recent results from cohort studies and dietary intervention trials. Recent epidemiological research has shown that regular consumption of olive oil is associated with increased longevity. This benefit is partly due to the olive oil's unequivocal cardio-protective role. There is converging evidence on the benefits of olive oil for preventing several CVD risk factors, including diabetes, MetS and obesity. Olive oil is also implicated in preventing certain cancers, with the most promising findings for breast and digestive tract cancers, although the data are still not entirely consistent and mainly from case–control studies. These health benefits are supported by strong mechanistic evidence from experimental studies, demonstrating that specific components of olive oil have antihypertensive, antithrombotic, antioxidant, antiinflammatory and anticarcinogenic action. Despite the accumulating epidemiological research, there is still a lack of consistent results from high-quality studies for many health outcomes (i.e. certain cancers and metabolism-related disorders). Further research is mandatory, above all from prospective studies and randomised dietary intervention trials when feasible, to confirm some of the still potential health benefits.
Mild Mitochondrial Uncoupling and Calorie Restriction Increase Fasting eNOS, Akt and Mitochondrial Biogenesis

Enhanced mitochondrial biogenesis promoted by eNOS activation is believed to play a central role in the beneficial effects of calorie restriction (CR). Since treatment of mice with dinitrophenol (DNP) promotes health and lifespan benefits similar to those observed in CR, we hypothesized that it could also impact biogenesis. We found that DNP and CR increase citrate synthase activity, PGC-1α, cytochrome c oxidase and mitofusin-2 expression, as well as fasting plasma levels of NO• products. In addition, eNOS and Akt phosphorylation in skeletal muscle and visceral adipose tissue was activated in fasting CR and DNP animals. Overall, our results indicate that systemic mild uncoupling activates eNOS and Akt-dependent pathways leading to mitochondrial biogenesis.
Functional Interaction between Type III-Secreted Protein IncA of Chlamydophila psittaci and Human G3BP1

Chlamydophila (Cp.) psittaci, the causative agent of psittacosis in birds and humans, is the most important zoonotic pathogen of the family Chlamydiaceae. These obligate intracellular bacteria are distinguished by a unique biphasic developmental cycle, which includes proliferation in a membrane-bound compartment termed inclusion. All Chlamydiaceae spp. possess a coding capacity for core components of a Type III secretion apparatus, which mediates specific delivery of anti-host effector proteins either into the chlamydial inclusion membrane or into the cytoplasm of target eukaryotic cells. Here we describe the interaction between Type III-secreted protein IncA of Cp. psittaci and host protein G3BP1 in a yeast two-hybrid system. In GST-pull down and co-immunoprecipitation experiments both in vitro and in vivo interaction between full-length IncA and G3BP1 were shown. Using fluorescence microscopy, the localization of G3BP1 near the inclusion membrane of Cp. psittaci-infected Hep-2 cells was demonstrated. Notably, infection of Hep-2 cells with Cp. psittaci and overexpression of IncA in HEK293 cells led to a decrease in c-Myc protein concentration. This effect could be ascribed to the interaction between IncA and G3BP1 since overexpression of an IncA mutant construct disabled to interact with G3BP1 failed to reduce c-Myc concentration. We hypothesize that lowering the host cell c-Myc protein concentration may be part of a strategy employed by Cp. psittaci to avoid apoptosis and scale down host cell proliferation.
A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network

In this paper, we propose a novel embedding model, named ConvKB, for knowledge base completion. Our model ConvKB advances state-of-the-art models by employing a convolutional neural network, so that it can capture global relationships and transitional characteristics between entities and relations in knowledge bases. In ConvKB, each triple (head entity, relation, tail entity) is represented as a 3-column matrix where each column vector represents a triple element. This 3-column matrix is then fed to a convolution layer where multiple filters are operated on the matrix to generate different feature maps. These feature maps are then concatenated into a single feature vector representing the input triple. The feature vector is multiplied with a weight vector via a dot product to return a score. This score is then used to predict whether the triple is valid or not. Experiments show that ConvKB achieves better link prediction performance than previous state-of-the-art embedding models on two benchmark datasets WN18RR and FB15k-237.
The Effect of Walnut Shell Powder on the Properties of Polypropylene Filled Composite

The effect of particle size and filler content on the mechanical and end -use properties of walnut shell powder filled polypropylene have been investigated at filler contents of 0 to 2 0 wt % and particle sizes of 0.100, 0.200, and 0.300m m. The polypropylene composites were melt-blended and homogenized in an injection moulding machine. Experimental results showed that for all the particle size of walnut shell powdered filler considered the tensile strength, elongation at break, and flexural strength of the polypropylene composites decreased with increase in walnut shell filler contents. However, the hardness and specific gravity of the composites were found to increase with increase in filler loadings and particle sizes. The water absorption properties of the composites as a function of filler content increased with increase in walnut shell filler content and also decreased with reduction in the particle sizes. The incorporation of walnut shell powder into the polypropylene was inefficient in reducing th e flame propagation rate of polypropylene.
Design and Realization of an Optical Rotary Sensor

The traditional optical rotary sensors measured the absolute angular position of a rotating object by sensing the current position of a coded disk using the optical trans-receiver. Due to the small air gap in between the optical trans-receiver and the disk, the sensor cannot withstand the effect of vibration. Also, its fabrication cost is correlated with the disk coding pattern. Thus, in order to overcome such issues a simple, coding free optical rotary sensor is presented in this paper. Instead of binary patterns, here an opaque shaft coupled disk having a single window is used as a positional pointer over a light sensitive circular track. The track has four equal spaces of hollow channels and each one consists of a single photo detector (PD). The PD is placed at the end of the channel wall. Thus, in the presence of a light source, the position of the disk window is determined by measuring the diffused light intensity variation of each channel surface. In order to prove this concept, an experimental prototype has been designed, developed, and tested, where satisfactory performance is achieved in the measured range of 0–360°.
A transfer function for the prediction of gas hydrate inventories in marine sediments

Abstract. A simple prognostic tool for gas hydrate (GH) quantification in marine sediments is presented based on a diagenetic transport-reaction model approach. One of the most crucial factors for the application of diagenetic models is the accurate formulation of microbial degradation rates of particulate organic carbon (POC) and the coupled formation of biogenic methane. Wallmann et al. (2006) suggested a kinetic formulation considering the ageing effects of POC and accumulation of reaction products (CH4, CO2) in the pore water. This model is applied to data sets of several ODP sites in order to test its general validity. Based on a thorough parameter analysis considering a wide range of environmental conditions, the POC accumulation rate (POCar in g/m2/yr) and the thickness of the gas hydrate stability zone (GHSZ in m) were identified as the most important and independent controls for biogenic GH formation. Hence, depth-integrated GH inventories in marine sediments (GHI in g of CH4 per cm2 seafloor area) can be estimated as: GHI = a · POCar · GHSZb · exp (– GHSZc/POCar/d) + e with a = 0.00214, b = 1.234, c = –3.339, d = 0.3148, e = –10.265. The transfer function gives a realistic first order approximation of the minimum GH inventory in low gas flux (LGF) systems. The overall advantage of the presented function is its simplicity compared to the application of complex numerical models, because only two easily accessible parameters need to be determined.
Heat transport in Rayleigh–Bénard convection and angular momentum transport in Taylor–Couette flow: a comparative study

Rayleigh–Bénard convection and Taylor–Couette flow are two canonical flows that have many properties in common. We here compare the two flows in detail for parameter values where the Nusselt numbers, i.e. the thermal transport and the angular momentum transport normalized by the corresponding laminar values, coincide. We study turbulent Rayleigh–Bénard convection in air at Rayleigh number Ra=107 and Taylor–Couette flow at shear Reynolds number ReS=2×104 for two different mean rotation rates but the same Nusselt numbers. For individual pairwise related fields and convective currents, we compare the probability density functions normalized by the corresponding root mean square values and taken at different distances from the wall. We find one rotation number for which there is very good agreement between the mean profiles of the two corresponding quantities temperature and angular momentum. Similarly, there is good agreement between the fluctuations in temperature and velocity components. For the heat and angular momentum currents, there are differences in the fluctuations outside the boundary layers that increase with overall rotation and can be related to differences in the flow structures in the boundary layer and in the bulk. The study extends the similarities between the two flows from global quantities to local quantities and reveals the effects of rotation on the transport. This article is part of the themed issue ‘Toward the development of high-fidelity models of wall turbulence at large Reynolds number’.
The Short-term Effects of a Cyberbullying Prevention Intervention for Parents of Middle School Students

This study experimentally evaluated the short-term effects of the Arizona Attorney General’s cybersafety promotion presentation, a key component of which is cyberbullying prevention. Fifty-one parents of children attending a middle school in the southwestern United States participated in the study. Results reveal parents who viewed the presentation believed their children to be more susceptible to cyberbullying, and indicated that they were more likely to talk to their children about saving evidence, not retaliating, and telling an adult compared to parents who had not viewed the presentation. The theoretical and practical implications of these results are discussed.
Multimodal Recurrent Neural Networks With Information Transfer Layers for Indoor Scene Labeling

This paper proposes a new method called multimodal recurrent neural networks (RNNs) for RGB-D scene semantic segmentation. It is optimized to classify image pixels given two input sources: RGB color channels and depth maps. It simultaneously performs training of two RNNs that are crossly connected through information transfer layers, which are learnt to adaptively extract relevant cross-modality features. Each RNN model learns its representations from its own previous hidden states and transferred patterns from the other RNNs previous hidden states; thus, both model-specific and cross-modality features are retained. We exploit the structure of quad-directional 2D-RNNs to model the short- and long-range contextual information in the 2D input image. We carefully designed various baselines to efficiently examine our proposed model structure. We test our multimodal RNNs method on popular RGB-D benchmarks and show how it outperforms previous methods significantly and achieves competitive results with other state-of-the-art works.
Sabin Vaccine Reversion in the Field: a Comprehensive Analysis of Sabin-Like Poliovirus Isolates in Nigeria

ABSTRACT To assess the dynamics of genetic reversion of live poliovirus vaccine in humans, we studied molecular evolution in Sabin-like poliovirus isolates from Nigerian acute flaccid paralysis cases obtained from routine surveillance. We employed a novel modeling approach to infer substitution and recombination rates from whole-genome sequences and information about poliovirus infection dynamics and the individual vaccination history. We confirmed observations from a recent vaccine trial that VP1 substitution rates are increased for Sabin-like isolates relative to the rate for the wild type due to increased nonsynonymous substitution rates. We also inferred substitution rates for attenuating nucleotides and confirmed that reversion can occur in days to weeks after vaccination. We combine our observations for Sabin-like virus evolution with the molecular clock for VP1 of circulating wild-type strains to infer that the mean time from the initiating vaccine dose to the earliest detection of circulating vaccine-derived poliovirus (cVDPV) is 300 days for Sabin-like virus type 1, 210 days for Sabin-like virus type 2, and 390 days for Sabin-like virus type 3. Phylogenetic relationships indicated transient local transmission of Sabin-like virus type 3 and, possibly, Sabin-like virus type 1 during periods of low wild polio incidence. Comparison of Sabin-like virus recombinants with known Nigerian vaccine-derived poliovirus recombinants shows that while recombination with non-Sabin enteroviruses is associated with cVDPV, the recombination rates are similar for Sabin isolate-Sabin isolate and Sabin isolate–non-Sabin enterovirus recombination after accounting for the time from dosing to the time of detection. Our study provides a comprehensive picture of the evolutionary dynamics of the oral polio vaccine in the field. IMPORTANCE The global polio eradication effort has completed its 26th year. Despite success in eliminating wild poliovirus from most of the world, polio persists in populations where logistical, social, and political factors have not allowed vaccination programs of sustained high quality. One issue of critical importance is eliminating circulating vaccine-derived polioviruses (cVDPVs) that have properties indistinguishable from those of wild poliovirus and can cause paralytic disease. cVDPV emerges due to the genetic instability of the Sabin viruses used in the oral polio vaccine (OPV) in populations that have low levels of immunity to poliovirus. However, the dynamics responsible are incompletely understood because it has historically been difficult to gather and interpret data about evolution of the Sabin viruses used in OPV in regions where cVDPV has occurred. This study is the first to combine whole-genome sequencing of poliovirus isolates collected during routine surveillance with knowledge about the intrahost dynamics of poliovirus to provide quantitative insight into polio vaccine evolution in the field.
MicroRNA Profiling Reveals Marker of Motor Neuron Disease in ALS Models

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder marked by the loss of motor neurons (MNs) in the brain and spinal cord, leading to fatally debilitating weakness. Because this disease predominantly affects MNs, we aimed to characterize the distinct expression profile of that cell type to elucidate underlying disease mechanisms and to identify novel targets that inform on MN health during ALS disease time course. microRNAs (miRNAs) are short, noncoding RNAs that can shape the expression profile of a cell and thus often exhibit cell-type-enriched expression. To determine MN-enriched miRNA expression, we used Cre recombinase-dependent miRNA tagging and affinity purification in mice. By defining the in vivo miRNA expression of MNs, all neurons, astrocytes, and microglia, we then focused on MN-enriched miRNAs via a comparative analysis and found that they may functionally distinguish MNs postnatally from other spinal neurons. Characterizing the levels of the MN-enriched miRNAs in CSF harvested from ALS models of MN disease demonstrated that one miRNA (miR-218) tracked with MN loss and was responsive to an ALS therapy in rodent models. Therefore, we have used cellular expression profiling tools to define the distinct miRNA expression of MNs, which is likely to enrich future studies of MN disease. This approach enabled the development of a novel, drug-responsive marker of MN disease in ALS rodents. SIGNIFICANCE STATEMENT Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease in which motor neurons (MNs) in the brain and spinal cord are selectively lost. To develop tools to aid in our understanding of the distinct expression profiles of MNs and, ultimately, to monitor MN disease progression, we identified small regulatory microRNAs (miRNAs) that were highly enriched or exclusive in MNs. The signal for one of these MN-enriched miRNAs is detectable in spinal tap biofluid from an ALS rat model, where its levels change as disease progresses, suggesting that it may be a clinically useful marker of disease status. Furthermore, rats treated with ALS therapy have restored expression of this MN RNA marker, making it an MN-specific and drug-responsive marker for ALS rodents.
Experience with Extra Hepatic Intra Abdominal Hydatid Cyst.

INTRODUCTION Hydatid disease is a significant health problem with their location at Extrahepatic Intra abdominal sites is a very rare disease. Disease in these sites usually found concurrently with liver hydatid disease. Diagnosis is based blood tests & imaging studies. Surgery is the mainstay of treatment. This study will help us in determining the frequency of Extra Hepatic Intra Abdominal Hydatid Disease. Also different methods to diagnose & treat the disease will be evaluated. METHODS It includes patients of extra hepatic intra abdominal Hydatid cyst above 13 years and underwent surgery from 2009 to 2014. Variables include age, sex, clinical findings, diagnostic investigations, operative findings, operative procedure, post operative complications. RESULTS Eleven patients; 07 male & 04 female; mean age 37.54 years. Most common symptoms were mass in abdomen in 11 patients & dull pain abdomen in 09 (81.8%) patients. Examination revealed non tender mass in epigastric & umbilical region in 04 (36.3%) patients. Ultrasound Abdomen showed hydatid cyst spleen in 02 (18.1%) patients, epigastrium in 04 (36.3%) patients, beneath left crus of diaphragm in 02 (18.1%) patients & right iliac fossa & pelvis in 1 (9.09%) patient. In 02 (18.1%) patients multiple Hydatid cysts were noted. Hydatid cysts liver found in 07 (63.6%) patients. C.T scan Abdomen was performed in 09 (81.8%) patients. Surgical procedures performed include Saucerization & omental packing in liver Hydatid cysts; Splenectomy for Splenic disease & complete excision of remaining intra-abdominal Hydatid cysts. Postoperative complications noted in 05 (45.4%) patients. CONCLUSION Extra hepatic intra abdominal is an infrequent disease presents significant diagnostic & therapeutic challenge for surgeons.
Interpretability via Model Extraction

The ability to interpret machine learning models has become increasingly important now that machine learning is used to inform consequential decisions. We propose an approach called model extraction for interpreting complex, blackbox models. Our approach approximates the complex model using a much more interpretable model; as long as the approximation quality is good, then statistical properties of the complex model are reflected in the interpretable model. We show how model extraction can be used to understand and debug random forests and neural nets trained on several datasets from the UCI Machine Learning Repository, as well as control policies learned for several classical reinforcement learning problems.