Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient, Consistent and Secure Global-Scale Data Management

Processing and analyzing data is becoming increasingly ubiquitous and is the driving force behind the sustained growth of Internet applications and the emergence of Big Data Analytics. These applications typically adopt the cloud model where they are hosted in a single datacenter. This introduces a fundamental limitation: communication to a centralized datacenter incurs significant latencies. The utilization of edge nodes is inevitable for the future success and growth of many emerging low latency and mobile applications. In this talk, we will explore various technologies that aim to facilitate building global-scale and edge-aware data management systems. These approaches are based on Geo-replication, where data is replicated across geographic locations to be closer to users, and Edge-awareness, where applications are deployed on edge locations to bypass the last-mile infrastructure. We propose novel consensus approaches that manage access to partitioned data across globally-distributed datacenters and edge nodes. The main objective is to reduce the latency of serving user requests, while ensuring fault-tolerance and adapting gracefully to mobility. In addition to failures, data centers are constantly exposed to an increasing number of nontrivial adversarial threats. Traditional cryptographic methods either limit the functionality of the data, or significantly increase retrieval costs. We will highlight some novel approaches that ensure efficient privacy preserving access to data in the Cloud.
Crystalline morphology and isothermal crystallization kinetics of poly(ethylene terephthalate)/clay nanocomposites

A poly(ethylene terephthalate) (PET)/montmorillonite clay nanocomposite was synthesized via in situ polymerization. Microscopic studies revealed that in an isothermal crystallization process, some crystallites in the nanocomposite initially were rod-shaped and later exhibited three-dimensional growth. The crystallites in the nanocomposite were irregularly shaped, rather than spherulitic, being interlocked together without clear boundaries, and they were much smaller than those of neat PET. With Avrami analysis, the isothermal crystallization kinetic parameters (the Avrami exponent and constant) were obtained. The rate constants for the nanocomposite demonstrated that clay could greatly increase the crystallization rate of PET. The results for the Avrami exponent were consistent with the observation of the rodlike crystallites in the PET/clay nanocomposite during the initial stage. Wide-angle X-ray scattering and Fourier transform infrared studies showed that, in comparison with neat PET, the crystal lattice parameters and crystallinity of the nanocomposite did not change significantly, whereas more defects may have been present in the crystalline regions of the nanocomposite because of the presence of the clay.
Gestational Weight Gain and Exposure of Newborns to Persistent Organic Pollutants

Background: Exposure to persistent organic pollutants (POPs) during fetal development can increase the risk of adverse health effects during childhood. Maternal characteristics and physiological changes during gestation, such as gestational weight gain (GWG), may have an influence in the overall burden of POPs in neonates. However, the associations between GWG and POP concentrations are still not well established. Objective: We examined the association of GWG with cord serum POPs concentrations after adjusting for prepregnancy maternal body mass index (BMI) and other potential determinants of the transfer of POPs into newborns. The GWG values were evaluated after grouping by the reference guidelines of the Institute of Medicine (IOM). Methods: We measured levels of 14 organochlorine pesticides, 7 polychlorobiphenyls (PCBs), and 14 polybrominated diphenyl ethers (PBDEs) in 325 cord serum samples from a Spanish birth cohort. Multivariable models were used to estimate associations of GWG, prepregnancy BMI, and other maternal determinants on cord serum concentrations of POPs. Results: Neonatal concentrations of POPs were inversely associated with GWG after adjustment for age, prepregnancy BMI, educational level, and fish consumption. On average, neonates of women with IOM-recommended GWG have lower POP concentrations than do neonates of mothers with inadequate GWG. Conclusions: The present findings suggest an association between neonatal exposure to POPs and inadequate GWG during pregnancy. Encouraging pregnant women to meet the recommended IOM guidelines for GWG may reduce the accumulation of POPs in newborns. Citation: Vizcaino E, Grimalt JO, Glomstad B, Fernández-Somoano A, Tardón A. 2014. Gestational weight gain and exposure of newborns to persistent organic pollutants. Environ Health Perspect 122:873–879; http://dx.doi. org/10.1289/ehp.1306758
Plerixafor for stem cell mobilization: the current status

Purpose of reviewNowadays, plerixafor is approved for patients who fail to mobilize sufficient CD34+ cells for an autologous stem cell transplantation. Plerixafor is effective in the majority of these patients, who otherwise could not be treated adequately. We discussed in this review the current status of the optimal use of plerixafor in different clinical diagnoses and settings. Recent findingsPlerixafor seems to be more effective in patients with multiple myeloma than in lymphoma. Even patients who had very low circulating CD34+ cells before administration of plerixafor have an important benefit. Several strategies in different clinical settings showed an effective response after administration of plerixafor, without the superiority of one strategy. Plerixafor is well tolerated with acceptable toxicity; however, it is an expensive drug. SummaryPlerixafor is an effective drug in patients who fail to mobilize with conventional strategy. No strategy seems superior for the optimal use of plerixafor. More studies focusing on the kinetics and cost-effectiveness are needed.
Phase II study of weekly docetaxel and capecitabine in patients with metastatic breast cancer.

PURPOSE This phase II study evaluated the safety and efficacy of weekly docetaxel and capecitabine in patients with metastatic breast cancer. PATIENTS AND METHODS Thirty-nine patients with metastatic breast cancer received 30 mg/m2 of docetaxel on days 1, 8, and 15 in combination with capecitabine 800 mg/m2 twice daily on days 1-21, repeated every 28 days. RESULTS The median number of treatment cycles was 4 (range, 1-20 cycles). Grade 3 toxicities per patient were asthenia (n = 7; 18%), diarrhea (n = 7; 18%), nausea/vomiting (n = 5; 13%), stomatitis (n = 5; 13%), neutropenia (n = 5; 13%), and hand-foot syndrome (n = 4; 10%). There were only 2 grade 4 toxicities, febrile neutropenia and pulmonary embolism. The overall response rate was 44% (95% confidence interval (CI), 28%-60%), median duration of response was 9.1 months (95% CI, 6.2-12 months), and median time to progression was 5.5 months (95% CI, 3.7-7.3 months). CONCLUSION Weekly docetaxel with capecitabine was active with acceptable toxicities. Additional trials to define the optimal schedule of docetaxel and capecitabine are justified.
Composite theoretical performance

Export controls require that computer systems, specifically Digital Central Processing units, be characterized as to performance. Absolute performance measurement is not required, rather a very wide range of CPUs, from micros to supercomputers, must be rank ordered. Ranking is based on a synthetic characterization and is influenced by the design details of the particular processor that make it useful for one or more strategic applications. This paper describes the strategic export control concerns, the rationale involved in the choice of a metric, the technical considerations, and the elements included in the CTP metric.
Nanoporous Microneedle Arrays Effectively Induce Antibody Responses against Diphtheria and Tetanus Toxoid

The skin is immunologically very potent because of the high number of antigen-presenting cells in the dermis and epidermis, and is therefore considered to be very suitable for vaccination. However, the skin’s physical barrier, the stratum corneum, prevents foreign substances, including vaccines, from entering the skin. Microneedles, which are needle-like structures with dimensions in the micrometer range, form a relatively new approach to circumvent the stratum corneum, allowing for minimally invasive and pain-free vaccination. In this study, we tested ceramic nanoporous microneedle arrays (npMNAs), representing a novel microneedle-based drug delivery technology, for their ability to deliver the subunit vaccines diphtheria toxoid (DT) and tetanus toxoid (TT) intradermally. First, the piercing ability of the ceramic (alumina) npMNAs, which contained over 100 microneedles per array, a length of 475 µm, and an average pore size of 80 nm, was evaluated in mouse skin. Then, the hydrodynamic diameters of DT and TT and the loading of DT, TT, and imiquimod into, and subsequent release from the npMNAs were assessed in vitro. It was shown that DT and TT were successfully loaded into the tips of the ceramic nanoporous microneedles, and by using near-infrared fluorescently labeled antigens, we found that DT and TT were released following piercing of the antigen-loaded npMNAs into ex vivo murine skin. Finally, the application of DT- and TT-loaded npMNAs onto mouse skin in vivo led to the induction of antigen-specific antibodies, with titers similar to those obtained upon subcutaneous immunization with a similar dose. In conclusion, we show for the first time, the potential of npMNAs for intradermal (ID) immunization with subunit vaccines, which opens possibilities for future ID vaccination designs.
Improving Activity Discovery with Automatic Neighborhood Estimation

A fundamental problem for artificial intelligence is identifying perceptual primitives from raw sensory signals that are useful for higher-level reasoning. We equate these primitives with initially unknown recurring patterns called motifs. Autonomously learning the motifs is difficult because their number, location, length, and shape are all unknown. Furthermore, nonlinear temporal warping may be required to ensure the similarity of motif occurrences. In this paper, we extend a leading motif discovery algorithm by allowing it to operate on multidimensional sensor data, incorporating automatic parameter estimation, and providing for motif-specific similarity adaptation. We evaluate our algorithm on several data sets and show how our approach leads to faster real world discovery and more accurate motifs compared to other leading methods.
High-power single-mode 915-nm, InAlGaAs quantum-well lasers grown by MOCVD

We report results on single-mode, InAlGaAs/AlGaAs/GaAs, 915 nm, lser-diodes operating reliably at 300 mW. The graded-index, separate-confinement, strained, single quantum-well structure was grown by metal-organic chemical-vapor deposition. Carbon, rather than zinc, was used as the p-doping srouce to reduce internal loss and potential reliability issues due to the thermal diffusion of zinc. A threshold current density of 133 A/cm2, internal loss of 2.0 cm-1 and internal quatnum efficiency of 93% were achieved. FOr 1500 μm long ridge waveguide lasers, a record single-mode output-power of 500mW was obtained for devices mounted epitaxial-side up onto AlN submounts using eutectic Au80Sn20 solder. Ten burned-in devices have now been aged at a constant current of 450 mA at 85°C for more than 1500 hours wihtout measurable degradation.
DSCMC: Distributed Stateless Code Model Checker

Stateless code model checking is an effective verification technique, which is more applicable than stateful model checking to the software world. Existing stateless model checkers support the verification of neither LTL formulae nor the information flow security properties. This paper proposes a distributed stateless code model checker (DSCMC) designed based on the Actor model, and has the capability of verifying code written in different programming languages. This tool is implemented using Erlang, which is an actor-based programming language. DSCMC is able to detect deadlocks, livelocks, and data races automatically. In addition, the tool can verify information flow security and the properties specified in LTL. Thanks to its actor-based architecture, DSCMC provides a wide range of capabilities. The parallel architecture of the tool exploiting the rich concurrency model of Erlang is suited to the time-intensive process of stateless code model checking.
New Method for Performance Evaluation of Grayscale Image Denoising Filters

Combining noise removal and detail preservation is a challenging issue in the design of image denoising filters. In this letter a new full-reference method for objective evaluation of such features in grayscale pictures is presented. The proposed approach is based on the classification of the filtering errors in two classes that respectively take into account the amount of noise still present after processing and the actual distortion produced by the filter. Results of computer simulations show the advantages of the proposed method with respect to other measures of filtering performance that are available in the literature.
Epithelial Cells Derived from Swine Bone Marrow Express Stem Cell Markers and Support Influenza Virus Replication In Vitro

The bone marrow contains heterogeneous population of cells that are involved in the regeneration and repair of diseased organs, including the lungs. In this study, we isolated and characterized progenitor epithelial cells from the bone marrow of 4- to 5-week old germ-free pigs. Microscopically, the cultured cells showed epithelial-like morphology. Phenotypically, these cells expressed the stem cell markers octamer-binding transcription factor (Oct4) and stage-specific embryonic antigen-1 (SSEA-1), the alveolar stem cell marker Clara cell secretory protein (Ccsp), and the epithelial cell markers pan-cytokeratin (Pan-K), cytokeratin-18 (K-18), and occludin. When cultured in epithelial cell growth medium, the progenitor epithelial cells expressed type I and type II pneumocyte markers. Next, we examined the susceptibility of these cells to influenza virus. Progenitor epithelial cells expressed sialic acid receptors utilized by avian and mammalian influenza viruses and were targets for influenza virus replication. Additionally, differentiated type II but not type I pneumocytes supported the replication of influenza virus. Our data indicate that we have identified a unique population of progenitor epithelial cells in the bone marrow that might have airway reconstitution potential and may be a useful model for cell-based therapies for infectious and non-infectious lung diseases.
Building Community Wikipedias: A Machine-Human Partnership Approach

The rapid growth of Web communities has motivated many solutions for building community data portals. These solutions follow roughly two approaches. The first approach (e.g., Libra, Citeseer, Cimple) employs semi-automatic methods to extract and integrate data from a multitude of data sources. The second approach (e.g., Wikipedia, Intellipedia) deploys an initial portal in wiki format, then invites community members to revise and add material. In this paper we consider combining the above two approaches to building community portals. The new hybrid machine-human approach brings significant benefits. It can achieve broader and deeper coverage, provide more incentives for users to contribute, and keep the portal more up-to-date with less user effort. In a sense, it enables building "community wikipedias", backed by an underlying structured database that is continuously updated using automatic techniques. We outline our ideas for the new approach, describe its challenges and opportunities, and provide initial solutions. Finally, we describe a real-world implementation and preliminary experiments that demonstrate the utility of the new approach.
Boron Deficiency in Soils and Crops: A Review

Waqar Ahmad1, Munir H. Zia2, Sukhdev S. Malhi3, Abid Niaz4 and Saifullah5,6 1Faculty of Agriculture, Food, and Natural Resources, The University of Sydney, 2Research & Development Section, Fauji Fertilizer Company Ltd, Rawalpindi, 3Agriculture and Agri-Food Canada, Melfort, Saskatchewan, 4Soil Chemistry Section, Institute of Soil Chemistry & Environmental Sciences, Ayub Agricultural Research Institute, Faisalabad, 5Institute of Soil and Environmental Sciences, University of Agriculture Faisalabad, 6School of Earth and Environment, Faculty of Natural and Agricultural Sciences, The University of Western Australia, Crawley, Perth, 1,6Australia 2,4,5Pakistan 3Canada
Map estimation for Bayesian mixture models with submodular priors

We propose a Bayesian approach where the signal structure can be represented by a mixture model with a submodular prior. We consider an observation model that leads to Lipschitz functions. Due to its combinatorial nature, computing the maximum a posteriori estimate for this model is NP-Hard, nonetheless our converging majorization-minimization scheme yields approximate estimates that, in practice, outperform state-of-the-art methods.
Meaningful term extraction and discriminative term selection in text categorization via unknown-word methodology

In this article, an approach based on unknown words is proposed for meaningful term extraction and discriminative term selection in text categorization. For meaningful term extraction, a phrase-like unit (PLU)-based likelihood ratio is proposed to estimate the likelihood that a word sequence is an unknown word. On the other hand, a discriminative measure is proposed for term selection and is combined with the PLU-based likelihood ratio to determine the text category. We conducted several experiments on a news corpus, called MSDN. The MSDN corpus is collected from an online news Website maintained by the Min-Sheng Daily News, Taiwan. The corpus contains 44,675 articles with over 35 million words. The experimental results show that the system using a simple classifier achieved 95.31% accuracy. When using a state-of-the-art classifier, kNN, the average accuracy is 96.40%, outperforming all the other systems evaluated on the same collection, including the traditional term-word by kNN (88.52%); sleeping-experts (82.22%); sparse phrase by four-word sleeping-experts (86.34%); and Boolean combinations of words by RIPPER (87.54%). A proposed purification process can effectively reduce the dimensionality of the feature space from 50,576 terms in the word-based approach to 19,865 terms in the unknown word-based approach. In addition, more than 80% of automatically extracted terms are meaningful. Experiments also show that the proportion of meaningful terms extracted from training data is relative to the classification accuracy in outside testing.
Separating Figure from Ground with a Parallel Network

The differentiation of figure from ground plays an important role in the perceptual organization of visual stimuli. The rapidity with which we can discriminate the inside from the outside of a figure suggests that at least this step in the process may be performed in visual cortex by a large number of neurons in several different areas working together in parallel. We have attempted to simulate this collective computation by designing a network of simple processing units that receives two types of information: bottom-up input from the image containing the outlines of a figure, which may be incomplete, and a top-down attentional input that biases one part of the image to be the inside of the figure. No presegmentation of the image was assumed. Two methods for performing the computation were explored: gradient descent, which seeks locally optimal states, and simulated annealing, which attempts to find globally optimal states by introducing noise into the computation. For complete outlines, gradient descent was faster, but the range of input parameters leading to successful performance was very narrow. In contrast, simulated annealing was more robust: it worked over a wider range of attention parameters and a wider range of outlines, including incomplete ones. Our network model is too simplified to serve as a model of human performance, but it does demonstrate that one global property of outlines can be computed through local interactions in a parallel network. Some features of the model, such as the role of noise in escaping from nonglobal optima, may generalize to more realistic models.
Common Genetic Determinants of Lung Function, Subclinical Atherosclerosis and Risk of Coronary Artery Disease

Chronic obstructive pulmonary disease (COPD) independently associates with an increased risk of coronary artery disease (CAD), but it has not been fully investigated whether this co-morbidity involves shared pathophysiological mechanisms. To identify potential common pathways across the two diseases, we tested all recently published single nucleotide polymorphisms (SNPs) associated with human lung function (spirometry) for association with carotid intima-media thickness (cIMT) in 3,378 subjects with multiple CAD risk factors, and for association with CAD in a case-control study of 5,775 CAD cases and 7,265 controls. SNPs rs2865531, located in the CFDP1 gene, and rs9978142, located in the KCNE2 gene, were significantly associated with CAD. In addition, SNP rs9978142 and SNP rs3995090 located in the HTR4 gene, were associated with average and maximal cIMT measures. Genetic risk scores combining the most robustly spirometry–associated SNPs from the literature were modestly associated with CAD, (odds ratio (OR) (95% confidence interval (CI95) = 1.06 (1.03, 1.09); P-value = 1.5×10−4, per allele). In conclusion, our study suggests that some genetic loci implicated in determining human lung function also influence cIMT and susceptibility to CAD. The present results should help elucidate the molecular underpinnings of the co-morbidity observed across COPD and CAD.
Optimal heavy tail estimation, Part I: Order selection

Abstract. The tail probability, P, of the distribution of a variable is important for risk analysis of extremes. Many variables in complex geophysical systems show heavy tails, where P decreases with the value, x, of a variable as a power law with a characteristic exponent, α. Accurate estimation of α on the basis of data is currently hindered by the problem of the selection of the order, that is, the number of largest x values to utilize for the estimation. This paper presents a new, widely applicable, data-adaptive order selector, which is based on computer simulations and brute force search. It is the first in a set of papers on optimal heavy tail estimation. The new selector outperforms competitors in a Monte Carlo experiment, where simulated data are generated from stable distributions and AR(1) serial dependence. We calculate error bars for the estimated α by means of simulations. We illustrate the method on an artificial time series. We apply it to an observed, hydrological time series from the River Elbe and find an estimated characteristic exponent of 1.48 ± 0.13. This result indicates finite mean but infinite variance of the statistical distribution of river runoff.
Estimating Fish Densities from Single Fish Echo Traces

Estimating mean fish density per unit area has been done by counting single fish echo traces with a split beam echo sounder system in the open sea. A data program has been written that scans the acoustic signals for echo peaks and classify these into echo traces. The program counts the number of echo traces from fish that cross the beam within given distances from the acoustic axis over a known sailing distance, and gives an absolute estimate of fish density. This is ob- tained by using the off acoustic axis angles of fish that generate resolved echoes to compute the athwartship distance from the vertical acoustic axis to the fish. The program is described and demonstrated on selected files of raw data recorded by the SIMRAD EK 60 split beam system. Estimated fish densities for these files are also obtained by the echo integration method, and the echo trace method gives estimates that agree well with these estimates under sufficiently "good condi- tions".