1,234 research outputs found

    Conversion of Legal Agreements into Smart Legal Contracts using NLP

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    A Smart Legal Contract (SLC) is a specialized digital agreement comprising natural language and computable components. The Accord Project provides an open-source SLC framework containing three main modules: Cicero, Concerto, and Ergo. Currently, we need lawyers, programmers, and clients to work together with great effort to create a usable SLC using the Accord Project. This paper proposes a pipeline to automate the SLC creation process with several Natural Language Processing (NLP) models to convert law contracts to the Accord Project's Concerto model. After evaluating the proposed pipeline, we discovered that our NER pipeline accurately detects CiceroMark from Accord Project template text with an accuracy of 0.8. Additionally, our Question Answering method can extract one-third of the Concerto variables from the template text. We also delve into some limitations and possible future research for the proposed pipeline. Finally, we describe a web interface enabling users to build SLCs. This interface leverages the proposed pipeline to convert text documents to Smart Legal Contracts by using NLP models

    Coupled ocean-atmosphere modeling and predictions

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    Key aspects of the current state of the ability of global and regional climate models to represent dynamical processes and precipitation variations are summarized. Interannual, decadal, and globalwarming timescales, wherein the influence of the oceans is relevant and the potential for predictability is highest, are emphasized. Oceanic influences on climate occur throughout the ocean and extend over land to affect many types of climate variations, including monsoons, the El Niño Southern Oscillation, decadal oscillations, and the response to greenhouse gas emissions. The fundamental ideas of coupling between the ocean-atmosphere-land system are explained for these modes in both global and regional contexts. Global coupled climate models are needed to represent and understand the complicated processes involved and allow us to make predictions over land and sea. Regional coupled climate models are needed to enhance our interpretation of the fine-scale response. The mechanisms by which large-scale, low-frequency variations can influence shorter timescale variations and drive regionalscale effects are also discussed. In this light of these processes, the prospects for practical climate predictability are also presented.AJMwas supported by theNSFEarth System Modeling Program (OCE1419306) and the NOAA Climate Variability and Prediction Program (NA14OAR4310276). HS thanks the Office of Naval Research for support under N00014-15-1-2588. LPP was supported by “Advanced Studies in Medium and High Latitudes Oceanography” (CAPES 23038.004304/2014-28) and “National Institute of Science andTechnology of the Cryosphere” (CNPq/PROANTAR704222/2009). VM was supported by NOAA grant NA12OAR4310078. TGJ was supported by the U. S. Naval Research Laboratory 6.2 project “Fresh Water Balance in the Coupled Ocean-Atmosphere System” (BE-435-040-62435N-6777) YHT was supported by the MOST grant 106-2111-M-002-001, Taiwan

    Thermal stress induces glycolytic beige fat formation via a myogenic state.

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    Environmental cues profoundly affect cellular plasticity in multicellular organisms. For instance, exercise promotes a glycolytic-to-oxidative fibre-type switch in skeletal muscle, and cold acclimation induces beige adipocyte biogenesis in adipose tissue. However, the molecular mechanisms by which physiological or pathological cues evoke developmental plasticity remain incompletely understood. Here we report a type of beige adipocyte that has a critical role in chronic cold adaptation in the absence of ÎČ-adrenergic receptor signalling. This beige fat is distinct from conventional beige fat with respect to developmental origin and regulation, and displays enhanced glucose oxidation. We therefore refer to it as glycolytic beige fat. Mechanistically, we identify GA-binding protein α as a regulator of glycolytic beige adipocyte differentiation through a myogenic intermediate. Our study reveals a non-canonical adaptive mechanism by which thermal stress induces progenitor cell plasticity and recruits a distinct form of thermogenic cell that is required for energy homeostasis and survival

    Necdin Controls Proliferation of White Adipocyte Progenitor Cells

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    White adipose tissues are composed mainly of white fat cells (adipocytes), which play a key role in energy storage and metabolism. White adipocytes are terminally differentiated postmitotic cells and arise from their progenitor cells (preadipocytes) or mesenchymal stem cells residing in white adipose tissues. Thus, white adipocyte number is most likely controlled by the rate of preadipocyte proliferation, which may contribute to the etiology of obesity. However, little is known about the molecular mechanisms that regulate preadipocyte proliferation during adipose tissue development. Necdin, which is expressed predominantly in postmitotic neurons, is a pleiotropic protein that possesses anti-mitotic and pro-survival activities. Here we show that necdin functions as an intrinsic regulator of white preadipocyte proliferation in developing adipose tissues. Necdin is expressed in early preadipocytes or mesenchymal stem cells residing in the stromal compartment of white adipose tissues in juvenile mice. Lentivirus-mediated knockdown of endogenous necdin expression in vivo in adipose tissues markedly increases fat mass in juvenile mice fed a high-fat diet until adulthood. Furthermore, necdin-null mutant mice exhibit a greater expansion of adipose tissues due to adipocyte hyperplasia than wild-type mice when fed the high-fat diet during the juvenile and adult periods. Adipose stromal-vascular cells prepared from necdin-null mice differentiate in vitro into a significantly larger number of adipocytes in response to adipogenic inducers than those from wild-type mice. These results suggest that necdin prevents excessive preadipocyte proliferation induced by adipogenic stimulation to control white adipocyte number during adipose tissue development

    Sensitive and low-potential electrochemical detection of hydroquinone using a nanodiamond modified glassy carbon electrode

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    © 2017 The Authors. The present work describes the sensitive and low-potential detection of hydroquinone (HQ) using a glassy carbon electrode (GCE) modified with nanodiamond (ND). The presence of ND was confirmed by high-resolution scanning electron microscopy, FTIR and Raman spectroscopy. The cyclic voltammetry results reveal that ND modified GCE has high electrocatalytic activity towards oxidation of HQ than unmodified GCE. In addition, the ND modified GCE shows a significantly lower oxidation potential towards CC than unmodified GCE, which is due to the presence of -OH functional groups in ND. The CV studies confirm that the redox electrochemical behavior of CC is a diffusion controlled electrochemical process on ND modified electrode. The ND modified electrode was able to detect the HQ across a linear response range from 1.0 to 78.0 ΌM. The limit of detection of the sensor was 0.19 ΌM. The sensor shows an appropriate selectivity in the presence of 20-fold concentrations of benzenediols and neurotransmitters. The practicality of the sensor is appropriate and shows excellent recovery of HQ in lab water samples

    Gadolinium oxide nanocrystal nonvolatile memory with HfO2/Al2O3 nanostructure tunneling layers

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    In this study, Gd2O3 nanocrystal (Gd2O3-NC) memories with nanostructure tunneling layers are fabricated to examine their performance. A higher programming speed for Gd2O3-NC memories with nanostructure tunneling layers is obtained when compared with that of memories using a single tunneling layer. A longer data retention (< 15% charge loss after 104 s) is also observed. This is due to the increased physical thickness of the nanostructure tunneling layer. The activation energy of charge loss at different temperatures is estimated. The higher activation energy value (0.13 to 0.17 eV) observed at the initial charge loss stage is attributed to the thermionic emission mechanism, while the lower one (0.07 to 0.08 eV) observed at the later charge loss stage is attributed to the direct tunneling mechanism. Gd2O3-NC memories with nanostructure tunneling layers can be operated without degradation over several operation cycles. Such NC structures could potentially be used in future nonvolatile memory applications

    Nonmonotone Barzilai-Borwein Gradient Algorithm for ℓ1\ell_1-Regularized Nonsmooth Minimization in Compressive Sensing

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    This paper is devoted to minimizing the sum of a smooth function and a nonsmooth ℓ1\ell_1-regularized term. This problem as a special cases includes the ℓ1\ell_1-regularized convex minimization problem in signal processing, compressive sensing, machine learning, data mining, etc. However, the non-differentiability of the ℓ1\ell_1-norm causes more challenging especially in large problems encountered in many practical applications. This paper proposes, analyzes, and tests a Barzilai-Borwein gradient algorithm. At each iteration, the generated search direction enjoys descent property and can be easily derived by minimizing a local approximal quadratic model and simultaneously taking the favorable structure of the ℓ1\ell_1-norm. Moreover, a nonmonotone line search technique is incorporated to find a suitable stepsize along this direction. The algorithm is easily performed, where the values of the objective function and the gradient of the smooth term are required at per-iteration. Under some conditions, the proposed algorithm is shown to be globally convergent. The limited experiments by using some nonconvex unconstrained problems from CUTEr library with additive ℓ1\ell_1-regularization illustrate that the proposed algorithm performs quite well. Extensive experiments for ℓ1\ell_1-regularized least squares problems in compressive sensing verify that our algorithm compares favorably with several state-of-the-art algorithms which are specifically designed in recent years.Comment: 20 page

    Prognostic factors and monomicrobial necrotizing fasciitis: gram-positive versus gram-negative pathogens

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    <p>Abstract</p> <p>Background</p> <p>Monomicrobial necrotizing fasciitis is rapidly progressive and life-threatening. This study was undertaken to ascertain whether the clinical presentation and outcome for patients with this disease differ for those infected with a gram-positive as compared to gram-negative pathogen.</p> <p>Methods</p> <p>Forty-six patients with monomicrobial necrotizing fasciitis were examined retrospectively from November 2002 to January 2008. All patients received adequate broad-spectrum antibiotic therapy, aggressive resuscitation, prompt radical debridement and adjuvant hyperbaric oxygen therapy. Eleven patients were infected with a gram-positive pathogen (Group 1) and 35 patients with a gram-negative pathogen (Group 2).</p> <p>Results</p> <p>Group 2 was characterized by a higher incidence of hemorrhagic bullae and septic shock, higher APACHE II scores at 24 h post-admission, a higher rate of thrombocytopenia, and a higher prevalence of chronic liver dysfunction. Gouty arthritis was more prevalent in Group 1. For non-survivors, the incidences of chronic liver dysfunction, chronic renal failure and thrombocytopenia were higher in comparison with those for survivors. Lower level of serum albumin was also demonstrated in the non-survivors as compared to those in survivors.</p> <p>Conclusions</p> <p>Pre-existing chronic liver dysfunction, chronic renal failure, thrombocytopenia and hypoalbuminemia, and post-operative dependence on mechanical ventilation represent poor prognostic factors in monomicrobial necrotizing fasciitis. Patients with gram-negative monobacterial necrotizing fasciitis present with more fulminant sepsis.</p

    Regulation of Brown Fat Adipogenesis by Protein Tyrosine Phosphatase 1B

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    Protein-tyrosine phosphatase 1B (PTP1B) is a physiological regulator of insulin signaling and energy balance, but its role in brown fat adipogenesis requires additional investigation.To precisely determine the role of PTP1B in adipogenesis, we established preadipocyte cell lines from wild type and PTP1B knockout (KO) mice. In addition, we reconstituted KO cells with wild type, substrate-trapping (D/A) and sumoylation-resistant (K/R) PTP1B mutants, then characterized differentiation and signaling in these cells. KO, D/A- and WT-reconstituted cells fully differentiated into mature adipocytes with KO and D/A cells exhibiting a trend for enhanced differentiation. In contrast, K/R cells exhibited marked attenuation in differentiation and lipid accumulation compared with WT cells. Expression of adipogenic markers PPARγ, C/EBPα, C/EBPΎ, and PGC1α mirrored the differentiation pattern. In addition, the differentiation deficit in K/R cells could be reversed completely by the PPARγ activator troglitazone. PTP1B deficiency enhanced insulin receptor (IR) and insulin receptor substrate 1 (IRS1) tyrosyl phosphorylation, while K/R cells exhibited attenuated insulin-induced IR and IRS1 phosphorylation and glucose uptake compared with WT cells. In addition, substrate-trapping studies revealed that IRS1 is a substrate for PTP1B in brown adipocytes. Moreover, KO, D/A and K/R cells exhibited elevated AMPK and ACC phosphorylation compared with WT cells.These data indicate that PTP1B is a modulator of brown fat adipogenesis and suggest that adipocyte differentiation requires regulated expression of PTP1B
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