bluuebunny/crossref_metadata_2025_split huggingface dataset:
Numerical analysis of projectile penetration and perforation of plain and fiber reinforced concrete slabs
Authors: Smith Jovanca , Cusatis Gianluca 
Published: July 2016

SummaryThe research presented in this paper deals with the numerical analysis of projectile impact on regular strength concrete (RSC), high‐strength concrete (HSC), and engineered cementitious composites (ECC) using the Lattice Discrete Particle Model (LDPM). The LDPM is chosen in this study as it naturally captures the failure mechanisms at the length scale of coarse aggregate of concrete, and its capabilities include the accurate depiction of both intrinsic and apparent rate effects in concrete, as well as fiber reinforcement effects. The model is used to predict the experimental impact response performed by four independent testing laboratories, and for each data set the model parameters are calibrated and validated using a combination of uniaxial compression, triaxial compression, uniaxial strain compression, and dogbone tests. In the first study, perforation experiments on RSC and HSC for varied impact velocities are carried out, and the exit velocity is compared with the available experimental data. The second study focuses on ECC, where multiple impact of steel and plastic fiber reinforced concrete panels are explored. A third investigation is performed on four RSC panels with varied thicknesses and subjected to the same impact velocity. In this instance, the model is used to predict the penetration depths for the different cases. Finally, in the last study, the response of large‐thickness infinite panels of sizes ranging from 300 mm to 700 mm under projectile impact is considered. Copyright © 2016 John Wiley & Sons, Ltd.
Fiscal Decentralization, Flat Administrative Structure, and Local Government Size: Evidence and Lessons from China
Authors: Zhang Ping , Zhu Chunkui , Hou Yilin 
Published: July 2016

SummaryThis paper examines the effects of fiscal decentralization and flat administrative structure on local budget size and program outlays. We test three related theoretical hypotheses in China's adoption of province‐over‐county scheme of financial administration. We provide evidence that both decentralization of expenditure and decentralization of revenue increase the size of local budgets; that the impact of the former far outweighs that of the latter with local budgets on a rising trajectory; and that discretion grants localities more means to increase their budget. These results show that as China's reform deepens the proportion of local outlay on administration declines because of more local discretion from eliminating the prefecture bypass between the province and counties. But neither decentralization nor increased local discretion has allocated more local resources for education, and both contribute to increasing outlay on economic development. The paper formulates tentative policy recommendations that carry potential application for other countries. Copyright © 2016 John Wiley & Sons, Ltd.
Improving protein–protein interactions prediction accuracy using protein evolutionary information and relevance vector machine model
Authors: An Ji‐Yong , Meng Fan‐Rong , You Zhu‐Hong , Chen Xing , Yan Gui‐Ying , Hu Ji‐Pu 
Published: July 2016

AbstractPredicting protein–protein interactions (PPIs) is a challenging task and essential to construct the protein interaction networks, which is important for facilitating our understanding of the mechanisms of biological systems. Although a number of high‐throughput technologies have been proposed to predict PPIs, there are unavoidable shortcomings, including high cost, time intensity, and inherently high false positive rates. For these reasons, many computational methods have been proposed for predicting PPIs. However, the problem is still far from being solved. In this article, we propose a novel computational method called RVM‐BiGP that combines the relevance vector machine (RVM) model and Bi‐gram Probabilities (BiGP) for PPIs detection from protein sequences. The major improvement includes (1) Protein sequences are represented using the Bi‐gram probabilities (BiGP) feature representation on a Position Specific Scoring Matrix (PSSM), in which the protein evolutionary information is contained; (2) For reducing the influence of noise, the Principal Component Analysis (PCA) method is used to reduce the dimension of BiGP vector; (3) The powerful and robust Relevance Vector Machine (RVM) algorithm is used for classification. Five‐fold cross‐validation experiments executed on yeast and Helicobacter pylori datasets, which achieved very high accuracies of 94.57 and 90.57%, respectively. Experimental results are significantly better than previous methods. To further evaluate the proposed method, we compare it with the state‐of‐the‐art support vector machine (SVM) classifier on the yeast dataset. The experimental results demonstrate that our RVM‐BiGP method is significantly better than the SVM‐based method. In addition, we achieved 97.15% accuracy on imbalance yeast dataset, which is higher than that of balance yeast dataset. The promising experimental results show the efficiency and robust of the proposed method, which can be an automatic decision support tool for future proteomics research. For facilitating extensive studies for future proteomics research, we developed a freely available web server called RVM‐BiGP‐PPIs in Hypertext Preprocessor (PHP) for predicting PPIs. The web server including source code and the datasets are available at http://219.219.62.123:8888/BiGP/.
Data‐driven multivariable ILC: enhanced performance by eliminatingLandQfilters
Authors: Bolder Joost , Kleinendorst Stephan , Oomen Tom 
Published: July 2016

SummaryIterative learning control (ILC) algorithms enable high‐performance control design using only approximate models of the system. To deal with severe modeling errors, a robustness filterQis typically employed. Irrespective of the large performance enhancement, these approaches thus require a modeling effort and are subject to a performance/robustness tradeoff. The aim of this paper is to develop a fully data‐driven ILC approach that does not require a modeling effort and mitigates the performance/robustness tradeoff. The main idea is to replace the use of a model by dedicated experiments on the system. Convergence conditions are developed in a finite‐time framework, and insight in the convergence aspects is presented using a frequency‐domain analysis. Extensions to increase the convergence speed are proposed. The developed framework is validated through experiments on a multivariable industrial flatbed printer. Both increased performance and robustness are demonstrated in a comparison with closely related model‐based ILC algorithms. Copyright © 2016 John Wiley & Sons, Ltd.
From Amino Acids to High‐Energy Dense Oxidizers: Polynitro Materials Derived from β‐Alanine andL‐Aspartic Acid
Authors: Klapötke Thomas M. , Krumm Burkhard , Scharf Regina 
Published: July 2016

AbstractNew oxygen‐rich compounds starting from the amino acids β‐alanine andL‐aspartic acid were synthesized and comprehensively analyzed including multinuclear NMR spectroscopy and vibrational spectroscopy. Thermal stabilities were measured and the behavior towards external stimuli like friction or impact were determined. Detonation and combustion parameters were predicted by using the EXPLO5 V6.02 code and were compared with common explosives. In addition, crystal structures were obtained for two compounds.
Natural History of Pneumoperitoneum After Laparotomy: Findings on Multidetector‐Row Computed Tomography
Authors: Malgras Brice , Placé Vinciane , Dohan Anthony , Lo Dico Réa , Duron Sandrine , Soyer Philippe , Pocard Marc 
Published: July 2016

AbstractBackgroundPostoperative pneumoperitoneum after abdominal surgery represents a diagnostic challenge. This study was designed to analyze the appearance of pneumoperitoneum on computed tomography after uncomplicated abdominal surgery through laparotomy.MethodsThe database of the department of digestive surgery was retrospectively queried to identify all patients who underwent abdominal surgery through laparotomy during a 13‐month period. This initial search retrieved a total of 384 consecutive patients. Criteria for inclusion in this study were: (a) the operation was performed in our institution, (b) the patient had computed tomography examination postoperatively, and (c) the patient had no postoperative grade ≥3 complication.ResultsPostoperative pneumoperitoneum was visible in 38/80 patients (47.5 %), with a mean volume of 15 ± 22.8 (SD) cm3 and multiple locations in 32/38 patients (84 %). Postoperative pneumoperitoneum was observed in 22/26 patients (85 %) until day 5 postoperative, 14/34 patients (41 %) between day 6 and day 15 postoperative, and in 2/21 patients (9.5 %) after day 15 postoperative. Its volume decreased when the time interval between surgery and computed tomography increased. Results of multivariate analysis showed that the time interval between surgery and computed tomography was the single independent variable that was associated with the presence of postoperative pneumoperitoneum.ConclusionsPostoperative pneumoperitoneum is a frequent finding on computed tomography in the early period following abdominal surgery and commonly with multiple locations. Although commonly observed before day 5 postoperative, its presence must be considered as an alarming finding after day 7 postoperative, if present in a single location with a volume >20 cm3.
Risk Factors for Predicting Occult Lymph Node Metastasis in Patients with Clinical Stage I Non‐small Cell Lung Cancer Staged by Integrated Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography
Authors: Kaseda Kaoru , Asakura Keisuke , Kazama Akio , Ozawa Yukihiko 
Published: July 2016

AbstractBackgroundLymph nodes in patients with non‐small cell lung cancer (NSCLC) are often staged using integrated 18F‐fluorodeoxyglucose positron emission tomography/computed tomography (FDG‐PET/CT). However, this modality has limited ability to detect micrometastases. We aimed to define risk factors for occult lymph node metastasis in patients with clinical stage I NSCLC diagnosed by preoperative integrated FDG‐PET/CT.MethodsWe retrospectively reviewed the records of 246 patients diagnosed with clinical stage I NSCLC based on integrated FDG‐PET/CT between April 2007 and May 2015. All patients were treated by complete surgical resection. The prevalence of occult lymph node metastasis in patients with clinical stage I NSCLC was analysed according to clinicopathological factors. Risk factors for occult lymph node metastasis were defined using univariate and multivariate analyses.ResultsOccult lymph node metastasis was detected in 31 patients (12.6 %). Univariate analysis revealed CEA (P = 0.04), SUVmax of the primary tumour (P = 0.031), adenocarcinoma (P = 0.023), tumour size (P = 0.002) and pleural invasion (P = 0.046) as significant predictors of occult lymph node metastasis. Multivariate analysis selected SUVmax of the primary tumour (P = 0.049), adenocarcinoma (P = 0.003) and tumour size (P = 0.019) as independent predictors of occult lymph node metastasis.ConclusionsThe SUVmax of the primary tumour, adenocarcinoma and tumour size were risk factors for occult lymph node metastasis in patients with NSCLC diagnosed as clinical stage I by preoperative integrated FDG‐PET/CT. These findings would be helpful in selecting candidates for mediastinoscopy or endobronchial ultrasound‐guided transbronchial needle aspiration.
Missed Opportunities for Loco‐Regional Treatment of Elderly Women with Breast Cancer
Authors: Bhoo‐Pathy Nirmala , Balakrishnan Nanthini , See Mee‐Hoong , Taib Nur Aishah , Yip Cheng‐Har 
Published: July 2016

AbstractBackgroundFactors associated with surgery, adjuvant radiotherapy, and chemotherapy and whether there were missed opportunities for treatment in elderly patients were determined in an Asian setting.MethodsAll 5616 patients, diagnosed with breast cancer in University Malaya Medical Centre from 1999 to 2013 were included. In 945 elderly patients (aged 65 years and above), multivariable logistic regression was performed to identify factors associated with treatment, following adjustment for age, ethnicity, tumor, and other treatment characteristics. The impact of lack of treatment on survival of the elderly was assessed while accounting for comorbidities.ResultsOne in five elderly patients had comorbidities. Compared to younger patients, the elderly had more favorable tumor characteristics, and received less loco‐regional treatment and chemotherapy. Within stage I–IIIa elderly breast cancer patients, 10 % did not receive any surgery. These patients were older, more likely to be Malays, have comorbidities, and bigger tumors. In elderlies with indications for adjuvant radiotherapy, no irradiation (30 %) was associated with increasing age, comorbidity, and the absence of systemic therapy. Hormone therapy was optimal, but only 35 % of elderly women with ER negative tumors received chemotherapy. Compared to elderly women who received adequate treatment, those not receiving surgery (adjusted hazard ratio: 2.30, 95 %CI: 1.10–4.79), or radiotherapy (adjusted hazard ratio: 1.56, 95 %CI: 1.10–2.19), were associated with higher mortality. Less than 25 % of the survival discrepancy between elderly women receiving loco‐regional treatment and no treatment were attributed to excess comorbidities in untreated patients.ConclusionWhile the presence of comorbidities significantly influenced loco‐regional treatment decisions in the elderly, it was only able to explain the lower survival rates in untreated patients up to a certain extent, suggesting missed opportunities for treatment.
Biosurfactant from Lysinibacillus chungkukjangi from Rice Bran Oil Sludge and Potential Applications
Authors: Bhardwaj Garima , Cameotra Swaranjit Singh , Chopra Harish Kumar 
Published: July 2016

AbstractA newly discovered bacterium, Lysinibacillus chungkukjangi, was isolated from the sludge of rice bran oil processing. When the bacterium was grown on rice bran, it produced biosurfactant which reduced the surface tension of the media to 27.9 from 72 mN/m. The biosurfactant was recovered by a solvent extraction method and characterized with the help of various structure elucidation techniques viz. FTIR, 1H‐ and 13C‐NMR spectroscopy and LC–MS analysis. The combined results of FTIR and NMR revealed the presence of carbonyl, olefinic and aliphatic groups, with the typical spectra of lipids. Moreover, LC–MS analysis also supported the same information. The biosurfactant was also studied for its anti‐oxidant and microbial enhanced oil recovery (MEOR) potential. The anti‐oxidant activity was observed by the DPPH free radical scavenging method using ascorbic acid as the standard. The IC50 (the half maximal inhibitory concentration) was calculated and for standard, it was 0.056 mg/mL and for the biosurfactant it turned out to be 1.3 mg/mL which shows its good anti‐oxidant potential. The sandpack test was performed to check its MEOR potential and kerosene was recovered up to 90 %, which shows its excellent applicability in the MEOR processes.
Effect of Roasting on Physicochemical Properties of Wild Almonds (Amygdalus scoparia)
Authors: Hojjati Mohammad , Lipan Leontina , Carbonell‐Barrachina Ángel A. 
Published: July 2016

AbstractRoasting enhances sensory quality of wild almonds (Amygdalus scoparia). The aim of the study was to evaluate the use of microwaves (480 W for 3 or 4 min) in roasting of wild almonds in comparison with traditional Spanish (165 °C for 20 min) and Iranian (soaking in 20 % NaCl in water for 30 min, drying at 60 °C for 2 h and roasting at 135 °C for 20 min) hot‐air processes. The influence of roasting wild almonds on moisture and oil contents, crispness, fatty acid profile, volatile compounds, and odour intensity was investigated. Roasting causes changes in appearance, texture and flavour, due to dehydration, browning, lipid oxidation, and diverse structural changes. The moisture content and hardness of the samples significantly decreased with all roasting methods. Roasting resulted in higher amounts of characteristics aroma compounds and only microwave roasting increased the oil content. The final recommendation is that microwave roasting at 480 W for 4 min led to roasted almonds of high physicochemical [dark and intense colour (L*44.9, a*8.4, and b*19.6), the highest content of total volatile compounds (132 mg kg−1), 85.2 % of unsaturated fatty acids], and sensory (high intensity of “roasted almond” aroma) quality. Microwaves can be used for roasting wild almond as a quick, safe, and economical method.
Coupling the Kolmogorov diffusion: maximality and efficiency considerations
Authors: Banerjee Sayan , Kendall Wilfrid S. 
Published: July 2016

AbstractThis is a case study concerning the rate at which probabilistic coupling occurs for nilpotent diffusions. We focus on the simplest case of Kolmogorov diffusion (Brownian motion together with its time integral or, more generally, together with a finite number of iterated time integrals). We show that in this case there can be no Markovian maximal coupling. Indeed, there can be no efficient Markovian coupling strategy (efficient for all pairs of distinct starting values), where the notion of efficiency extends the terminology of Burdzy and Kendall (2000). Finally, at least in the classical case of a single time integral, it is not possible to choose a Markovian coupling that is optimal in the sense of simultaneously minimizing the probability of failing to couple by time t for all positive t. In recompense for all these negative results, we exhibit a simple efficient non-Markovian coupling strategy.
Probabilistic aspects of critical growth-fragmentation equations
Authors: Bertoin Jean , Watson Alexander R. 
Published: July 2016

AbstractThe self-similar growth-fragmentation equation describes the evolution of a medium in which particles grow and divide as time proceeds, with the growth and splitting of each particle depending only upon its size. The critical case of the equation, in which the growth and division rates balance one another, was considered in Doumic and Escobedo (2015) for the homogeneous case where the rates do not depend on the particle size. Here, we study the general self-similar case, using a probabilistic approach based on Lévy processes and positive self-similar Markov processes which also permits us to analyse quite general splitting rates. Whereas existence and uniqueness of the solution are rather easy to establish in the homogeneous case, the equation in the nonhomogeneous case has some surprising features. In particular, using the fact that certain self-similar Markov processes can enter (0,∞) continuously from either 0 or ∞, we exhibit unexpected spontaneous generation of mass in the solutions.
The sound of silence: equilibrium filtering and optimal censoring in financial markets
Authors: Gietzmann Miles B. , Ostaszewski Adam J. 
Published: July 2016

AbstractFollowing the approach of standard filtering theory, we analyse investor valuation of firms, when these are modelled as geometric-Brownian state processes that are privately and partially observed, at random (Poisson) times, by agents. Tasked with disclosing forecast values, agents are able purposefully to withhold their observations; explicit filtering formulae are derived for downgrading the valuations in the absence of disclosures. The analysis is conducted for both a solitary firm andmco-dependent firms.
Time-varying copula models for financial time series
Authors: Kiesel Rüdiger , Mroz Magda , Stadtmüller Ulrich 
Published: July 2016

AbstractWe perform an analysis of the potential time inhomogeneity in the dependence between multiple financial time series. To this end, we use the framework of copula theory and tackle the question of whether dependencies in such a case can be assumed constant throughout time or rather have to be modeled in a time-inhomogeneous way. We focus on parametric copula models and suitable inference techniques in the context of a special copula-based multivariate time series model. A recent result due to Chanet al.(2009) is used to derive the joint limiting distribution of local maximum-likelihood estimators on overlapping samples. By restricting the overlap to be fixed, we establish the limiting law of the maximum of the estimator series. Based on the limiting distributions, we develop statistical homogeneity tests, and investigate their local power properties. A Monte Carlo simulation study demonstrates that bootstrapped variance estimates are needed in finite samples. Empirical analyses on real-world financial data finally confirm that time-varying parameters are an exception rather than the rule.
Existence of moments of a counting process and convergence in multidimensional time
Authors: Klesov Oleg , Stadtmüller Ulrich 
Published: July 2016

AbstractStarting with independent, identically distributed random variables X1,X2... and their partial sums (Sn), together with a nondecreasing sequence (b(n)), we consider the counting variable N=∑n1(Sn>b(n)) and aim for necessary and sufficient conditions on X1 in order to obtain the existence of certain moments for N, as well as for generalized counting variables with weights, and multi-index random variables. The existence of the first moment of N when b(n)=εn, i.e. ∑n=1∞ℙ(|Sn|>εn)<∞, corresponds to the notion of complete convergence as introduced by Hsu and Robbins in 1947 as a complement to Kolmogorov's strong law.
Approximating the Laplace transform of the sum of dependent lognormals
Authors: Laub Patrick J. , Asmussen Søren , Jensen Jens L. , Rojas-Nandayapa Leonardo 
Published: July 2016

AbstractLet (X1,...,Xn) be multivariate normal, with mean vector 𝛍 and covariance matrix 𝚺, and letSn=eX1+⋯+eXn. The Laplace transform ℒ(θ)=𝔼e-θSn∝∫exp{-hθ(𝒙)}d𝒙 is represented as ℒ̃(θ)I(θ), where ℒ̃(θ) is given in closed form andI(θ) is the error factor (≈1). We obtain ℒ̃(θ) by replacinghθ(𝒙) with a second-order Taylor expansion around its minimiser 𝒙*. An algorithm for calculating the asymptotic expansion of 𝒙*is presented, and it is shown thatI(θ)→ 1 as θ→∞. A variety of numerical methods for evaluatingI(θ) is discussed, including Monte Carlo with importance sampling and quasi-Monte Carlo. Numerical examples (including Laplace-transform inversion for the density ofSn) are also given.
Asymptotic normality of degree counts in a preferential attachment model
Authors: Resnick Sidney I. , Samorodnitsky Gennady 
Published: July 2016

AbstractPreferential attachment is a widely adopted paradigm for understanding the dynamics of social networks. Formal statistical inference, for instance GLM techniques, and model-verification methods will require knowing test statistics are asymptotically normal even though node- or count-based network data are nothing like classical data from independently replicated experiments. We therefore study asymptotic normality of degree counts for a sequence of growing simple undirected preferential attachment graphs. The methods of proof rely on identifying martingales and then exploiting the martingale central limit theorems.