Miracle-dz/UniFAR-FTUs huggingface dataset:
Smoking as a Permissive Factor of Periodontal Disease in Psoriasis

Background Population-based studies have identified smoking as a pathogenetic factor in chronic periodontitis. At the same time, chronic periodontal disease has also been found to occur more often in persons suffering from psoriasis than in controls with no psoriasis. It is known that smoking aggravates both periodontal disease and psoriasis, but so far it has not been investigated how smoking influences the occurrence and severity of periodontal disease in psoriasis. Methods A hospital-based study was conducted to investigate this question. The study population consisted of 82 psoriasis patients and 89 controls. All patients received a full-mouth periodontal examination, and a published classification based on bleeding on probing, clinical attachment level and probing depth was utilized for staging. Both patients and controls were divided into smoker and non-smoker groups, and the resulting groups were compared in terms of periodontal status. Beyond the descriptive statistics, odds ratios were computed. Results Psoriasis in itself increased the likelihood of severe periodontal disease to 4.373 (OR, as compared to non-smoker controls, p<0.05), while smoking increased it to 24.278 (OR, as compared to non-smoker controls, p<0.001) in the studied population. In other words, the risk of severe periodontal disease in psoriasis turned out to be six times higher in smokers than in non-smokers. Conclusions The results of this study corroborate those of other studies regarding the link between psoriasis and periodontal disease, but they also seem to reveal a powerful detrimental effect of smoking on the periodontal health of psoriasis patients, whereby the authors propose that smoking may have a permissive effect on the development of severe periodontal disease in psoriasis.
Nonlinear optical properties of organic materials

The second-order hyperpolarizabilities of two groups of organic materials, retinal derivatives and mesoionic compounds, are obtained through measurements of nonlinear optical susceptibilities. The Z-scan technique was employed to characterize the sign and magnitude of the third-order nonlinear optical coefficient, whilst the Kerr Gate method was employed to infer the response time of the nonlinearity with 60 fs resolution. From these measurements, supported by quantum chemical theoretical calculations, the origin of the nonlinearity was determined for both materials.
When can we trust progress estimators for SQL queries?

The problem of estimating progress for long-running queries has recently been introduced. We analyze the characteristics of the progress estimation problem, from the perspective of providing robust, worst-case guarantees. Our first result is that in the worst case, no progress estimation algorithm can yield anything even moderately better than the trivial guarantee that identifies the progress as lying between 0% and 100%. In such cases, we introduce an estimator that can optimally bound the error. However, we show that in many "good" scenarios, it is possible to design effective progress estimators with small error bounds. We then demonstrate empirically that these "good" scenarios are common in practice and discuss possible ways of combining the estimators.
Does Size Matter? Text and Grammar Revision for Parsing Social Media Data

We explore improving parsing social media and other web data by altering the input data, namely by normalizing web text, and by revising output parses. We find that text normalization improves performance, though spell checking has more of a mixed impact. We also find that a very simple tree reviser based on grammar comparisons performs slightly but significantly better than the baseline and well outperforms a machine learning model. The results also demonstrate that, more than the size of the training data, the goodness of fit of the data has a great impact on the parser.
Synergism between cytosine-guanine oligodeoxynucleotides and monoclonal antibody in the treatment of lymphoma.

Synthetic oligodeoxynucleotides containing unmethylated cytosine-guanine dinucleotides (CpG ODN) are potent immunostimulatory agents that can activate various immune cell subsets. We have found that CpG ODN show a variety of effects that could be useful in enhancing the efficacy of antibody therapy of lymphoma. In a mouse model, CpG ODN alone had no effect on survival of animals inoculated with lymphoma. In contrast, CpG ODN plus monoclonal antibody (MAb) was more effective at inhibiting tumor growth than MAb alone or MAb plus control ODN. Cytosine-guanine ODN plus MAb cured mice with a large tumor burden that could not be cured with MAb therapy alone. We also evaluated the effects of CpG ODN on the phenotype of human malignant B cells. Cytosine-guanine ODN upregulated the expression of a number of antigens, including CD20. The upregulation of CD20 was most extensive in cells that had low baseline expression of this antigen. We conclude that CpG ODN enhances the efficacy of MAb in a murine lymphoma model, most likely by activating effector cells, and upregulates expression of CD20 on primary human malignant B cells. Given the effects of CpG ODN on both target antigen expression and effector-cell function, further evaluation of the combination of CpG ODN plus rituximab (Rituxan; Genentech, Inc, South San Francisco, CA, and IDEC Pharmaceuticals, San Diego, CA) and CpG ODN plus other MAbs is warranted.
A Novel Biobased Resin-Epoxidized Soybean Oil Modified Cyanate Ester

Cyanate ester (CE) resin was modified with renewable resource, i.e. epoxidized soybean oil (ESO), and the effects of ESO content on the curing co-reaction, morphologies, water absorption behaviors, thermal and mechanical properties of CE/ESO blends were studied. Differential scanning calorimeter (DSC), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and dynamic mechanical analysis (DMA) were employed to characterize the ESO-modified CE polymer networks. Homogeneous structures were observed for low-content of ESO modified CE systems by SEM, while ESO-rich particles were observed in the modified systems with ESO above 15 wt %. The blend of the CE and ESO resulted in an excellent combination as a new biobased thermoset material having relatively high mechanical properties with 15 and 20 wt % ESO as replacement of CE. Enhanced elongations at break were observed for the modified systems while the tensile strengths kept about the same level at the same time. The storage moduli and glass transition temperatures of the modified systems in the glassy state and rubber plateau were observed to be lower than those of neat CE with the increase of ESO weight percent. POLYM. ENG. SCI., 2008. © 2008 Society of Plastics Engineers
Variation between Hospitals with Regard to Diagnostic Practice, Coding Accuracy, and Case-Mix. A Retrospective Validation Study of Administrative Data versus Medical Records for Estimating 30-Day Mortality after Hip Fracture

Background The purpose of this study was to assess the validity of patient administrative data (PAS) for calculating 30-day mortality after hip fracture as a quality indicator, by a retrospective study of medical records. Methods We used PAS data from all Norwegian hospitals (2005–2009), merged with vital status from the National Registry, to calculate 30-day case-mix adjusted mortality for each hospital (n = 51). We used stratified sampling to establish a representative sample of both hospitals and cases. The hospitals were stratified according to high, low and medium mortality of which 4, 3, and 5 hospitals were sampled, respectively. Within hospitals, cases were sampled stratified according to year of admission, age, length of stay, and vital 30-day status (alive/dead). The final study sample included 1043 cases from 11 hospitals. Clinical information was abstracted from the medical records. Diagnostic and clinical information from the medical records and PAS were used to define definite and probable hip fracture. We used logistic regression analysis in order to estimate systematic between-hospital variation in unmeasured confounding. Finally, to study the consequences of unmeasured confounding for identifying mortality outlier hospitals, a sensitivity analysis was performed. Results The estimated overall positive predictive value was 95.9% for definite and 99.7% for definite or probable hip fracture, with no statistically significant differences between hospitals. The standard deviation of the additional, systematic hospital bias in mortality estimates was 0.044 on the logistic scale. The effect of unmeasured confounding on outlier detection was small to moderate, noticeable only for large hospital volumes. Conclusions This study showed that PAS data are adequate for identifying cases of hip fracture, and the effect of unmeasured case mix variation was small. In conclusion, PAS data are adequate for calculating 30-day mortality after hip-fracture as a quality indicator in Norway.
Smart Multicrossbar Router Design in NOC

This paper gives the innovative idea of designing a router using multicrossbar switch in Network on Chip(NoC) . In Network-on-Chip architectures the input buffer can consume a large portion of the total power. Eliminating all input buffer would result in increased power consumption at high load, while reducing the size of input buffer degrades the performance. In this paper we have proposed a muticrossbar router design using elastic buffer by combining the advantage of both buffered and buffer less network. In the proposed design Power Delay Product is reduced by around 37 . 91% as compared to baseline router.
A multivariate approach to utilizing mid-sequence process control data

While the measurement of cell efficiency is still considered one of the primary assessments of a cell's quality, a modern photovoltaic manufacturing facility will also include a range of metrology to assess the performance at various steps during the manufacturing sequence. These measurements can be used to control individual processes and ensure reliable process interactions, but they are at their most powerful where they can be correlated to the final performance of the cell. Such a relationship is not always easy to establish, particularly when the data collected during the process cannot be parametrized entirely with a single variable. This paper shows how two multivariate approaches can be used to form a relationship between cell lifetime data collected early in a fabrication sequence, and the final cell Voc. While building a model with a high level of predictive accuracy is rarely feasible, it is possible to identify a higher proportion of under-performing product and provide insight into how material type interacts with the manufacturing sequence.
Lanczos-Einstein-Petiau: From Dirac ' $s$ equation to nonlinear wave mechanics

In 1929 Lanczos showed how to derive Dirac's equation from a more fundamental system that predicted that spin 1/2 particles should come in pairs. Today, these pairs can unambiguously be interpreted as isospin doublets. From the same fundamental equation, Lanczos derived also the correct form of the wave equation of massive spin 1 particles that would be rediscovered in 1936 by Proca. Lanczos's fundamental system was put in Lagrangian form and generalized in 1933 by Einstein and Mayer, who used the semivector instead of the quaternion formalism. Although they not did study all possible solutions, Einstein and Mayer showed that the doublets consisted of particles with different mass and charge. In fact, there are two main classes of doublets: proton/neutron and electron/neutrino pairs.
Race/Ethnicity-specific Disparities in Hepatocellular Carcinoma Stage at Diagnosis and its Impact on Receipt of Curative Therapies

Goals:To evaluate race/ethnicity-specific disparities in hepatocellular carcinoma (HCC) stage at diagnosis and how this impacts receiving curative therapies. Background:HCC is a leading cause of morbidity and mortality worldwide. The highest incidence of HCC is seen among ethnic minorities in the United States. Study:Using the 2003-2011 Surveillance, Epidemiology, and End Results database and United Network of Organ Sharing, population-based registries for cancer and liver transplantation (LT) in the United States, race/ethnicity-specific cancer stage at diagnosis and treatment received among adults with HCC were evaluated. Results:Compared with non-Hispanic whites, blacks had significantly more advanced HCC at diagnosis [odds ratio (OR), 1.20; 95% confidence interval (CI), 1.10-1.30; P<0.001], whereas Asians were less likely to have advanced disease (OR, 0.87; CI, 0.80-0.94; P<0.001). Among patients with HCC meeting Milan criteria, Hispanics (OR, 0.64; 95% CI, 0.57-0.71; P<0.001) and blacks (OR, 0.67; 95% CI, 0.59-0.76; P<0.001) were significantly less likely to receive curative therapy (resection or LT), whereas Asians were more likely to receive curative therapy (OR, 1.22; 95% CI, 1.10-1.35; P<0.001) compared with non-Hispanic whites. However, Asians (OR, 0.49; 95% CI, 0.42-0.58; P<0.001) and Hispanics (OR, 0.51; 95% CI, 0.44-0.60; P<0.001) were less likely to receive LT. Conclusions:Among US adults with HCC, blacks consistently had more advanced stage at diagnosis and lower rates of receiving treatment. After correcting for cancer stage and evaluating the subset of patients eligible for curative therapies, blacks and Hispanics had significantly lower rates of curative HCC treatment.
Preoperative quantitative dynamic contrast-enhanced MRI and diffusion-weighted imaging predict aggressive disease in endometrial cancer

Background Quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) may yield preoperative tumor biomarkers relevant for prognosis and therapy in cancer. Purpose To explore the value of preoperative DCE-MRI and DWI for the prediction of aggressive disease in endometrial cancer patients. Material and Methods Preoperative MRI (1.5-T) from 177 patients were analyzed and imaging parameters reflecting tumor microvasculature (from DCE-MRI) and tumor microstructure (from DWI) were estimated. The derived imaging parameters were explored in relation to clinico-pathological stage, histological subtype and grade, molecular markers, and patient outcome. Results Low tumor blood flow (Fb) and low rate constant for contrast agent intravasation (kep) were associated with high-risk histological subtype (P ≤ 0.04 for both) and tended to be associated with poor prognosis (P ≤ 0.09). Low tumor apparent diffusion coefficient (ADC) value and large tumor volume were both significantly associated with deep myometrial invasion (P < 0.001 for both) and were also unfavorable prognostic factors (P = 0.05 and P < 0.001, respectively). Conclusion DCE-MRI and DWI represent valuable supplements to conventional MRI by providing preoperative imaging biomarkers that predict aggressive disease in endometrial cancer patients.
Human T-Cell Responses to Vaccinia Virus Envelope Proteins

ABSTRACT One approach for a safer smallpox vaccine is to utilize recombinant subunits rather than live vaccinia virus (VACV). The products of the VACV envelope genes A27L, L1R, B5R, and A33R induce protective antibodies in animal models. We propose that proteins that elicit T-cell responses, as well as neutralizing antibodies, will be important to include in a molecular vaccine. To evaluate VACV-specific memory T-cell responses, peripheral blood mononuclear cells (PBMC) from four VACV vaccinees were tested against whole VACV and the individual envelope proteins A27, B5, L1, and A33, using gamma interferon enzyme-linked immunospot and cytokine flow cytometry assays. PBMC were stimulated with autologous dendritic cells infected with VACV or electroporated with individual VACV protein mRNAs. T-cell lines from all donors, vaccinated from 1 month to over 20 years ago, recognized all four VACV envelope proteins. Both CD4+ and CD8+ T-cell responses to each protein were detected. Further analysis focused on representative proteins B5 and A27. PBMC from a recent vaccinee exhibited high frequencies of CD4+ and CD8+ T-cell precursors to both B5 (19.8 and 20%, respectively) and A27 (6.8 and 3.7%). In comparison, B5- and A27-specific T-cell frequencies ranged from 0.4 to 1.3% in a donor vaccinated 3 years ago. Multiple CD4+ and CD8+ T-cell epitopes were identified from both A27 and B5, using overlapping 15-mer peptides. These data suggest that all four VACV envelope proteins may contribute to protective immunity, not only by inducing antibody responses, but also by eliciting T-cell responses.
Predicting Response to Bevacizumab in Ovarian Cancer: A Panel of Potential Biomarkers Informing Treatment Selection

Purpose: The aim of this study was to identify and validate novel predictive and/or prognostic serum proteomic biomarkers in patients with epithelial ovarian cancer (EOC) treated as part of the phase III international ICON7 clinical trial. Experimental Design: ICON7 was a phase III international trial in EOC which showed a modest but statistically significant benefit in progression-free survival (PFS) with the addition of bevacizumab to standard chemotherapy. Serum samples from 10 patients who received bevacizumab (five responders and five nonresponders) were analyzed by mass spectrometry to identify candidate biomarkers. Initial validation and exploration by immunoassay was undertaken in an independent cohort of 92 patients, followed by a second independent cohort of 115 patients (taken from across both arms of the trial). Results: Three candidate biomarkers were identified: mesothelin, fms-like tyrosine kinase-4 (FLT4), and α1-acid glycoprotein (AGP). Each showed evidence of independent prognostic potential when adjusting for high-risk status in initial (P < 0.02) and combined (P < 0.01) validation cohorts. In cohort I, individual biomarkers were not predictive of bevacizumab benefit; however, when combined with CA-125, a signature was developed that was predictive of bevacizumab response and discriminated benefit attributable to bevacizumab better than clinical characteristics. The signature showed weaker evidence of predictive ability in validation cohort II, but was still strongly predictive considering all samples (P = 0.001), with an improvement in median PFS of 5.5 months in signature-positive patients in the experimental arm compared with standard arm. Conclusions: This study shows a discriminatory signature comprising mesothelin, FLT4, AGP, and CA-125 as potentially identifying those patients with EOC more likely to benefit from bevacizumab. These results require validation in further patient cohorts. Clin Cancer Res; 19(18); 5227–39. ©2013 AACR.
Bioinspired Effective Prevention of Restacking in Multilayered Graphene Films: Towards the Next Generation of High‐Performance Supercapacitors

A simple, bioinspired approach to effectively prevent the restacking of chemically converted graphene sheets in multilayered films is presented. The method enables the creation of a new generation of supercapacitors that combine high energy density, high power density, and high operation rates. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A methodology for deriving probabilistic correctness measures from recognizers

This paper describes the derivation of probability of correctness from scores assigned by most recognizers. Motivation for this research is three-fold: (i) probability values can be used to rerank the output of any recognizer by using a new set of training data; if the training data is sufficiently large and representative of the test data, the recognition rates are seen to improve significantly, (ii) derivation of probability values puts the output of different recognizers on the same scale; this makes comparison across recognizers trivial, and (iii) word recognition can be readily extended to phrase and sentence recognition because the integration of language models becomes straightforward. We have conducted an extensive set of experiments. The results show a reranking of recognition choices based on the derived probability values leading to an enhancement in performance.
High Diversity of Extended-Spectrum Beta-Lactamase-Producing Bacteria in an Urban River Sediment Habitat

ABSTRACT Antibiotic-resistant bacteria (ARB) have been surveyed widely in water bodies, but few studies have determined the diversity of ARB in sediment, which is the most taxon-abundant habitat in aquatic environments. We isolated 56 extended-spectrum β-lactamase (ESBL)-producing bacteria from a single sediment sample taken from an urban river in China. All strains were confirmed for ESBL-producing capability by both the clavulanic acid combination disc method and MIC determination. Of the isolated strains, 39 were classified as Enterobacteriaceae (consisting of the genera Escherichia, Klebsiella, Serratia, and Aeromonas) by 16S rRNA gene sequencing and biochemical analysis. The present study identifies, for the first time, ESBL-producing strains from the families Brucellaceae and Moraxellaceae. The blaCTX-M gene was the most dominant of the ESBL genes (45 strains), while the blaTEM gene was the second-most dominant (22 strains). A total of five types of blaCTX-M fragments were identified, with both known and novel sequences. A library of blaCTX-M cloned from the sediment DNA showed an even higher diversity of blaCTX-M sequences. The discovery of highly diverse ESBL-producing bacteria and ESBL genes, particularly blaCTX, in urban river sediment raises alarms for potential dissemination of ARB in communities through river environments.
Modeling Psychomotor Activity: Current Approaches and Open Issues

This paper presents current approaches and open issues regarding the modeling of users' physical activity when learning motor skills, such as those required to dance, play a musical instrument, practice sports or train in martial arts. On the one hand, it reveals the lack of personalized psychomotor learning systems and how the modeling of users' physical activity is just now becoming part of UMAP (User Modeling, Adaptation and Personalization) community research agenda. On the other hand, it proposes the Labanotation as a way for describing the movements performed during the users' physical activity, and comments on related works which show that it seems to be feasible to perform this labeling automatically with machine learning techniques. To touch down the proposal, the applicability of Labanotation for modeling the psychomotor activity when learning defensive martial arts movements such as those performed jointly in pairs in Aikido is analyzed.
Proof of a fundamental result in self-similar traffic modeling

We state and prove the following key mathematical result in self-similar traffic modeling: the superposition of many ON/OFF sources (also known as packet trains) with strictly alternating ON- and OFF-periods and whose ON-periods or OFF-periods exhibit the Noah Effect (i.e., have high variability or infinite variance) can produce aggregate network traffic that exhibits the Joseph Effect (i.e., is self-similar or long-range dependent). There is, moreover, a simple relation between the parameters describing the intensities of the Noah Effect (high variability) and the Joseph Effect (self-similarity). This provides a simple physical explanation for the presence of self-similar traffic patterns in modern high-speed network traffic that is consistent with traffic measurements at the source level. We illustrate how this mathematical result can be combined with modern high-performance computing capabilities to yield a simple and efficient linear-time algorithm for generating self-similar traffic traces.We also show how to obtain in the limit a L&eacute;vy stable motion, that is, a process with stationary and independent increments but with infinite variance marginals. While we have presently no empirical evidence that such a limit is consistent with measured network traffic, the result might prove relevant for some future networking scenarios.