Miracle-dz/UniFAR-FTUs huggingface dataset:
Models of retinal diseases and their applicability in drug discovery

ABSTRACT Introduction: The impact of vision debilitating diseases is a global public health concern, which will continue until effective preventative and management protocols are developed. Two retinal diseases responsible for the majority of vision loss in the working age adults and elderly populations are diabetic retinopathy (DR) and age-related macular degeneration (AMD), respectively. Model systems, which recapitulate aspects of human pathology, are valid experimental modalities that have contributed to the identification of signaling pathways involved in disease development and consequently potential therapies. Areas covered: The pathology of DR and AMD, which serve as the basis for designing appropriate models of disease, is discussed. The authors also review in vitro and in vivo models of DR and AMD and evaluate the utility of these models in exploratory and pre-clinical studies. Expert opinion: The complex nature of non-Mendelian diseases such as DR and AMD has made identification of effective therapeutic treatments challenging. However, the authors believe that while in vivo models are often criticized for not being a ‘perfect’ recapitulation of disease, they have been valuable experimentally when used with consideration of the strengths and limitations of the experimental model selected and have a place in the drug discovery process.
On quantized compressed sensing with saturated measurements via convex optimization

In this paper, we address the problem of sparse signal recovery, from multi-bit scalar quantized compressed sensing measurements, where the saturation issue is taken into account. We propose a convex optimization approach, where saturation errors are jointly estimated with the sparse signal to be recovered. In the proposed approach, saturated measurements, even though over-identified, are considered as outliers and the associated errors are handled as non-negative sparse corruptions with partial support information. We highlight the theoretical recovery guarantee of the proposed approach and we demonstrate, via simulation results, its reliability in cancelling out the effect of the outlying saturated measurements.
Photoluminescence properties of InAs nanowires grown on GaAs and Si substrates

We report the first photoluminescence (PL) characterization of InAs nanowires (NWs). The InAs NWs were grown on GaAs(111) B and Si(111) substrates using the Au-assisted molecular beam epitaxy (MBE) growth technique or metal-organic chemical vapor deposition (MOCVD). We compared the PL response of four samples grown under different conditions using MBE or MOCVD. High-resolution transmission electron microscopy (HRTEM) and selected area electron diffraction (SAED) patterns were utilized to determine the crystal structure and growth directions of the NWs to relate PL features to NW structural parameters. We observed mainly three PL peaks which were below, near and above InAs bandgaps, respectively. Temperature and excitation intensity dependence PL measurements were also performed to help elucidate the origins of the PL peaks of NWs. Of particular interest was a band-edge emission peak that was blue-shifted due to quantization effects of the InAs NWs, as confirmed by our calculation.
The Brain on Low Power Architectures - Efficient Simulation of Cortical Slow Waves and Asynchronous States

Efficient brain simulation is a scientific grand challenge, a parallel/distributed coding challenge and a source of requirements and suggestions for future computing architectures. Indeed, the human brain includes about 10^15 synapses and 10^11 neurons activated at a mean rate of several Hz. Full brain simulation poses Exascale challenges even if simulated at the highest abstraction level. The WaveScalES experiment in the Human Brain Project (HBP) has the goal of matching experimental measures and simulations of slow waves during deep-sleep and anesthesia and the transition to other brain states. The focus is the development of dedicated large-scale parallel/distributed simulation technologies. The ExaNeSt project designs an ARM-based, low-power HPC architecture scalable to million of cores, developing a dedicated scalable interconnect system, and SWA/AW simulations are included among the driving benchmarks. At the joint between both projects is the INFN proprietary Distributed and Plastic Spiking Neural Networks (DPSNN) simulation engine. DPSNN can be configured to stress either the networking or the computation features available on the execution platforms. The simulation stresses the networking component when the neural net - composed by a relatively low number of neurons, each one projecting thousands of synapses - is distributed over a large number of hardware cores. When growing the number of neurons per core, the computation starts to be the dominating component for short range connections. This paper reports about preliminary performance results obtained on an ARM-based HPC prototype developed in the framework of the ExaNeSt project. Furthermore, a comparison is given of instantaneous power, total energy consumption, execution time and energetic cost per synaptic event of SWA/AW DPSNN simulations when executed on either ARM- or Intel-based server platforms.
Sizes distribution characteristics of cutting fluid roplets for electrostatic atomization minimum quantity lubrication

In order to understand the sizes distribution characteristics of the cutting fluid droplets for electrostatic atomization lubrication,image recognition and detection technology was applied to the sizes measures of the charged cutting fluid droplets. After the feature extraction and recognition analysis of droplets areas in collecting images,the transformation of two-dimensional plane diameter and threedimensional space diameter was established. A practical method was presented to detect the distribution characteristics of droplets sizes in gas-fog flow. On the basis of setting droplets collecting device,the droplets in gas-fog flow were collected and detected on the different sections. The experiment results indicate that the Sauter mean diameter(SMD)of droplets become smaller with the electrostatic voltage increasing. The distribution of the droplets diameters become more uniform and the atomization quality is improved dramatically. On the three sections from 60 mm~140 mm,the average SMD of droplets are increased with the spray distance increasing and the distribution of the droplets diameters become more nonuniform.
Analysis Of Mechanical Properties Of Chopped Strand Mat E- Glass Fiber Epoxy Resin Nanoclay Composites

---------------------------------------------------Abstract---------------------------------------------------------Composite materials play a vital role in many industrial applications. Researchers are working on fabrication of new composite materials worldwide to enhance the applicability of these materials. In view of this, the objective of the present work is to analyse the effect of nanoclay content on the mechanical behaviour of chopped strand mat E-glass fiber, reinforced in epoxy matrix with nanoclay filler. Three different types of composites are fabricated using 1wt% nanoclay, 5wt% nanoclay and 7wt% nanoclay with 30% wt fiber, epoxy resin and hardener. The epoxy resin and hardener are mixed in 10:1 weight ratio. The results of the study show that the incorporation of nanoclay has a significant effect on the mechanical behaviour of composites.
Facial landmark localization based on hierarchical pose regression with cascaded random ferns

The main challenge of facial landmark localization in real-world application is that the large changes of head pose and facial expressions cause substantial image appearance variations. To avoid high dimensional regression in the 3D and 2D facial pose spaces simultaneously, we propose a hierarchical pose regression approach, estimating the head rotation, facial components and landmarks hierarchically. The regression process works in a unified cascaded fern framework. We present generalized gradient boosted ferns (GBFs) for the regression framework, which give better performance than traditional ferns. The framework also achieves real time performance. We verify our method on the latest benchmark datasets. The results show that it outperforms state-of-the-art methods in both accuracy and speed.
Effects of different dietary ratio of physically effective neutral detergent fiber and metabolizable glucose on rumen fermentation, blood metabolites and growth performance of 8 to 10-month-old heifers

Objective The present study was undertaken to determine an optimal balance between the amount of physically effective neutral detergent fiber (peNDF) to metabolizable glucose (MG) on rumen fermentation, blood metabolites and growth performance of 8 to 10-month-old heifers. Methods A total of 15 healthy Holstein heifers weighing an average of 256 kg (8 month of age) were randomly assigned to three groups of five. Treatment diets consisted of the following three peNDF8.0/MG levels: 1.46 (Treatment A), 1.74 (Treatment B), and 2.08 (Treatment C). Results The results showed that the ratio of peNDF8.0/MG affected rumen fermentation, blood metabolites and growth performance of heifers. The average daily gain of heifers tended to decrease as the ratio of peNDF8.0/MG increased (p = 0.07). The concentrations of blood urea nitrogen, triglyceride, and cholesterol increased significantly (p<0.05), while the high-density lipoprotein concentration decreased (p<0.05). After feeding 2 h and 4 h, insulin concentration in Treatment A was greater than Treatment C (p<0.05). Propionate concentration had decreasing trend (p = 0.07); acetate to propionate ratio and non-glucogenic to glucogenic volatile fatty acid (NGR) increased significantly (p<0.05). In addition, the digestibility of dry matter, crude protein, neutral detergent fiber, and acid detergent fiber decreased significantly (p<0.05). Conclusion The present investigation indicated that dietary peNDF8.0/MG ratio can affect the growth and development, blood metabolites, rumen fermentation and apparent digestibility of heifers, and the optimal dietary peNDF8.0/MG ratio for 8 to 10-month-old heifers in the present study was 1.46.
Verification of the FAIR Control System Using Deterministic Network Calculus

The FAIR control system (CS) is an alarm-based design and employs White Rabbit time synchronization over a GbE network to issue commands executed accurate to 1 ns. In such a network based CS, graphs of possible machine command sequences are specified in advance by physics frameworks. The actual traffic pattern, however, is determined at runtime, depending on interlocks and beam requests from experiments and accelerators. In ’unlucky’ combinations, large packet bursts can delay commands beyond their deadline, potentially causing emergency shutdowns. Thus, prior verification if any possible combination of given command sequences can be delivered on time is vital to guarantee deterministic behavior of the CS. Deterministic network calculus (DNC) can derive upper bounds on message delivery latencies. This paper presents an approach for calculating worst-case descriptors of runtime traffic patterns. These so-called arrival curves are deduced from specified partial traffic sequences and are used to calculate end-to-end traffic properties. With the arrival curves and a DNC model of the FAIR CS network, a worst-case latency for specific packet flows or the whole CS can be obtained.
A Two-Center Randomized Trial of an Additional Early Dose of Measles Vaccine: Effects on Mortality and Measles Antibody Levels

Background In addition to protecting against measles, measles vaccine (MV) may have beneficial nonspecific effects. We tested the effect of an additional early MV on mortality and measles antibody levels. Methods Children aged 4-7 months at rural health and demographic surveillance sites in Burkina Faso and Guinea-Bissau were randomized 1:1 to an extra early standard dose of MV (Edmonston-Zagreb strain) or no extra MV 4 weeks after the third diphtheria-tetanus-pertussis-hepatitis B-Haemophilus influenzae type b vaccine. All children received routine MV at 9 months. We assessed mortality through home visits and compared mortality from enrollment to age 3 years using Cox proportional hazards models, censoring for subsequent nontrial MV. Subgroups of participants had blood sampled to assess measles antibody levels. Results Among 8309 children enrolled from 18 July 2012 to 3 December 2015, we registered 145 deaths (mortality rate: 16/1000 person-years). The mortality was lower than anticipated and did not differ by randomization group (hazard ratio, 1.05; 95% confidence interval, 0.75-1.46). At enrollment, 4% (16/447) of children in Burkina Faso and 21% (90/422) in Guinea-Bissau had protective measles antibody levels. By age 9 months, no measles-unvaccinated/-unexposed child had protective levels, while 92% (306/333) of early MV recipients had protective levels. At final follow-up, 98% (186/189) in the early MV group and 97% (196/202) in the control group had protective levels. Conclusions Early MV did not reduce all-cause mortality. Most children were susceptible to measles infection at age 4-7 months and responded with high antibody levels to early MV. Clinical Trials Registration NCT01644721.
Progression of calcium density in the ascending thoracic aorta is inversely associated with incident cardiovascular disease events

Aims Little is known regarding the risk of atherosclerotic cardiovascular disease (ASCVD) conferred by changes in the volume and density of ascending thoracic aorta calcium (ATAC) over time. We evaluated changes in ATAC volume and density scores and incident ASCVD events. Methods and results The Multi-Ethnic Study of Atherosclerosis is a prospective cohort study of individuals without baseline clinical ASCVD. Ascending thoracic aorta calcium was measured from baseline and follow-up (mean interval 2.4 years) cardiac computed tomography (CT). Cox proportional hazard regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) per standard deviation for events after the follow-up exam adjusted for ASCVD risk factors, baseline ATAC and coronary artery calcium (CAC) volume and density, and changes in CAC volume and density. Among 5887 participants, 296 (5.0%) had detectable ATAC at baseline, follow-up, or both exams. A total of 403 events occurred over 9.5 years. An increase in ATAC volume was associated with coronary heart disease (CHD) (HR 1.90, 95% CI 1.14-3.16), ASCVD (HR 1.93, 95% CI 1.26-2.94), and ischaemic stroke (HR 2.14, CI 1.21-3.78). An increase in ATAC density was inversely associated with CHD (HR 0.29, 95% CI 0.14-0.60) and ASCVD (HR 0.42, 95% CI 0.23-0.76), but not stroke (HR 0.61, CI 0.23-1.61). Conclusion Ascending thoracic aorta calcium is uncommon on serial cardiac CT. However, changes in ATAC volume and density are both associated with incident ASCVD events, but in opposite directions. Serial assessments in those with baseline ATAC may provide insight into an individual's trajectory of ASCVD risk.
DRAW : Deep networks for Recognizing styles of Artists Who illustrate children ’ s books

is paper is motivated from a young boy’s capability to recognize an illustrator’s style in a totally dierent context. In the book ”We are All Born Free” [1], composed of selected rights from the Universal Declaration of Human Rights interpreted by dierent illustrators, the boywas surprised to see a picture similar to the ones in the ”Winnie the Witch” series drawn by Korky Paul (Figure 1). e style was noticeable in other characters of the same illustrator in dierent books as well. e capability of a child to easily spot the style was shown to be valid for other illustrators such as Axel Scheer and Debi Gliori. e boy’s enthusiasm let us to start the journey to explore the capabilities of machines to recognize the style of illustrators. We collected pages from children’s books to construct a new illustrations dataset consisting of about 6500 pages from 24 artists. We exploited deep networks for categorizing illustrators and with around 94% classication performance our method over-performed Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for prot or commercial advantage and that copies bear this notice and the full citation on the rst page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permied. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specic permission and/or a fee. Request permissions from permissions@acm.org. ICMR ’17, June 6–9, 2017, Bucharest, Romania © 2017 ACM. ACM ISBN 978-1-4503-4701-3/17/06. $15.00 DOI: hp://dx.doi. org/10.1145/3078971.3078982 the traditional methods bymore than 10%. Going beyond categorization we explored transferring style. e classication performance on the transferred images has shown the ability of our system to capture the style. Furthermore, we discovered representative illustrations and discriminative stylistic elements.
On the effective permittivity of silver-insulator nanocomposites

The Bruggeman formalism provides an estimate of the effective permittivity of a composite material comprising two constituent materials, with each constituent material being composed of electrically small particles. When one of the constituent materials is silver and the other is an insulating material, the Bruggeman estimate of the effective permittivity of the composite exhibits resonances with respect to volume fraction that are not physically plausible.
Nature as a Source for Inspiring New Optimization Algorithms

The different fields of nature inspired computing (NIC; also called natural computing) have proven their success in tackling many optimization problems. Many real-world problems were long known as unsolved ones. Meanwhile, many phenomena in nature and more particular the group behavior fascinated computer scientists to use them as sources of inspiration for developing new problem solving techniques. For that, this paper explores NIC and more particularly biology-based algorithms (as they are one of its most successful branches) emphasizing the natural sources of inspiration, basic design principles, and the scope of their applications. Also, It emphasizes how different nature inspired algorithms can be applied.
Genome Sequencing of Listeria monocytogenes “Quargel” Listeriosis Outbreak Strains Reveals Two Different Strains with Distinct In Vitro Virulence Potential

A large listeriosis outbreak occurred in Austria, Germany and the Czech Republic in 2009 and 2010. The outbreak was traced back to a traditional Austrian curd cheese called “Quargel” which was contaminated with two distinct serovar 1/2a Listeria monocytogenes strains (QOC1 and QOC2). In this study we sequenced and analysed the genomes of both outbreak strains in order to investigate the extent of genetic diversity between the two strains belonging to MLST sequence types 398 (QOC2) and 403 (QOC1). Both genomes are highly similar, but also display distinct properties: The QOC1 genome is approximately 74 kbp larger than the QOC2 genome. In addition, the strains harbour 93 (QOC1) and 45 (QOC2) genes encoding strain-specific proteins. A 21 kbp region showing highest similarity to plasmid pLMIV encoding three putative internalins is integrated in the QOC1 genome. In contrast to QOC1, strain QOC2 harbours a vip homologue, which encodes a LPXTG surface protein involved in cell invasion. In accordance, in vitro virulence assays revealed distinct differences in invasion efficiency and intracellular proliferation within different cell types. The higher virulence potential of QOC1 in non-phagocytic cells may be explained by the presence of additional internalins in the pLMIV-like region, whereas the higher invasion capability of QOC2 into phagocytic cells may be due to the presence of a vip homologue. In addition, both strains show differences in stress-related gene content. Strain QOC1 encodes a so-called stress survival islet 1, whereas strain QOC2 harbours a homologue of the uncharacterized LMOf2365_0481 gene. Consistently, QOC1 shows higher resistance to acidic, alkaline and gastric stress. In conclusion, our results show that strain QOC1 and QOC2 are distinct and did not recently evolve from a common ancestor.
Opportunities and Challenges of Ad-based Measurements from the Edge of the Network

For many years, the research community, practitioners, and regulators have used myriad methods and tools to understand the complex structure and behavior of ISPs from the edge of the network. Unfortunately, the nature of these techniques forces the researcher to find a balance between ISP-coverage, user scale, and accuracy. In this paper we present AdTag, a network measurement paradigm that leverages the opportunistic nature of online targeted advertising to measure the Internet from the edge of the network. We discuss and formalize AdTag's design space---including technical, ethical, deployability and economic factors---and its potential to analyze a wide spectrum of Internet connectivity aspects from the browser. We run several experiments to demonstrate that AdTag can be tailored towards geographic and device-based user groups, finding also several challenges to be faced in order to maximize the number of samples. In a 7-day campaign, AdTag could access more than 20K ISPs at a global scale (185 countries) using millions of edge nodes.
Evaluating surrogate marker information using censored data

Given the long follow‐up periods that are often required for treatment or intervention studies, the potential to use surrogate markers to decrease the required follow‐up time is a very attractive goal. However, previous studies have shown that using inadequate markers or making inappropriate assumptions about the relationship between the primary outcome and surrogate marker can lead to inaccurate conclusions regarding the treatment effect. Currently available methods for identifying and validating surrogate markers tend to rely on restrictive model assumptions and/or focus on uncensored outcomes. The ability to use such methods in practice when the primary outcome of interest is a time‐to‐event outcome is difficult because of censoring and missing surrogate information among those who experience the primary outcome before surrogate marker measurement. In this paper, we propose a novel definition of the proportion of treatment effect explained by surrogate information collected up to a specified time in the setting of a time‐to‐event primary outcome. Our proposed approach accommodates a setting where individuals may experience the primary outcome before the surrogate marker is measured. We propose a robust non‐parametric procedure to estimate the defined quantity using censored data and use a perturbation‐resampling procedure for variance estimation. Simulation studies demonstrate that the proposed procedures perform well in finite samples. We illustrate the proposed procedures by investigating two potential surrogate markers for diabetes using data from the Diabetes Prevention Program. Copyright © 2017 John Wiley & Sons, Ltd.