nils-herrmann/clean_scirepeval huggingface dataset:
Determination of critical quality attributes for monoclonal antibodies using quality by design principles.
Venue: Biologicals journal of the International Association of Biological Standardization

Quality by design (QbD) is a global regulatory initiative with the goal of enhancing pharmaceutical development through the proactive design of pharmaceutical manufacturing process and controls to consistently deliver the intended performance of the product. The principles of pharmaceutical development relevant to QbD are described in the ICH guidance documents (ICHQ8 11) An integrated set of risk assessments and their related elements developed at Roche/Genentech were designed to provide an overview of product and process knowledge for the production of a recombinant monoclonal antibody. This chapter describes the identification of critical quality attributes (CQAs) as an important first step for QbD development of biopharmaceuticals. A systematic scientific based risk ranking and filtering approach allows a thorough understanding of quality attributes and an assignment of criticality for their impact on drug safety and efficacy. To illustrate the application of the approach and tools, a few examples from monoclonal antibodies are shown. The identification of CQAs is a continuous process and will further drive the structure and function characterization of therapeutic proteins.
Neural Network Control Based Adaptive Learning Design for Nonlinear Systems With Full State Constraints
Venue: IEEE Transactions on Neural Networks and Learning Systems

In order to stabilize a class of uncertain nonlinear strict feedback systems with full state constraints, an adaptive neural network control method is investigated in this paper. The state constraints are frequently emerged in the real life plants and how to avoid the violation of state constraints is an important task. By introducing a barrier Lyapunov function (BLF) to every step in a backstepping procedure, a novel adaptive backstepping design is well developed to ensure that the full state constraints are not violated. At the same time, one remarkable feature is that the minimal learning parameters are employed in BLF backstepping design. By making use of Lyapunov analysis, we can prove that all the signals in the closed loop system are semiglobal uniformly ultimately bounded and the output is well driven to follow the desired output. Finally, a simulation is given to verify the effectiveness of the method.
Neural Network Based Model Design for Short Term Load Forecast in Distribution Systems
Venue: IEEE Transactions on Power Systems

Accurate forecasts of electrical substations are mandatory for the efficiency of the Advanced Distribution Automation functions in distribution systems. The paper describes the design of a class of machine learning models, namely neural networks, for the load forecasts of medium voltage/low voltage substations. We focus on the methodology of neural network model design in order to obtain a model that has the best achievable predictive ability given the available data. Variable selection and model selection are applied to electrical load forecasts to ensure an optimal generalization capacity of the neural network model. Real measurements collected in French distribution systems are used to validate our study. The results show that the neural network based models outperform the time series models and that the design methodology guarantees the best generalization ability of the neural network model for the load forecasting purpose based on the same data.
Gestion Integree du Changement des Modeles de Processus Metier
Venue: INFORSID

For the past few years, the Business Process Models or BPMs, have been largely used to specify the different processes of an organisation. The existing frameworks, may also generate executable information systems, deployed on distributed platforms, from the instantiation of business process models. This has been facilitated by the generalization of the so called Service Oriented Architecture (SOA) We propose a graph based approach, along with the graph re writing system, for the modeling and simulation of the change impact propagation among the different constituents of the instantiated business process models. We use ontologies for the semantic representation of the relations linking the different constituents of such applications. This semantic knowledge is then used by an algorithm that may generate the graph re writing rules to incorporate the change impact propagation in such applications. MOTS CLES Modeles de Processus Metier (BPM) Propagation de l'impact du changement, Systemes de reecriture de graphe, Ontologies.
Gas Flaring: When Will Nigeria Decarbonise Its Oil and Gas Industry

Gas flaring and venting are a safe methods of disposing unwanted gas during emergencies and equipment failures, or where the gas cannot be captured, stored or used economically. In whichever circumstance the flaring and venting occur, they both present an environmental and a resource management challenge. In Nigeria, gas flaring and venting began ever since the start of oil production in 1956. Gas flaring and venting have a number of negative consequences on the environment, human health, and the economy of the Nigerian state. Studies have put the revenue lost to flaring by Nigeria at around US$2.5billion annually. This study reviews the various measures put in place by the government and the oil companies in form of laws, policies, regulations, programmes, and penalties with a view to discouraging flaring and encouraging gas utilisation. However, these measures have not been able to phase out flaring in the country. Gas flaring elimination deadlines have repeatedly been shifted with the most recent one being December 2012. It was found that economic and fiscal considerations on the part of the oil companies and lack of strict enforcement of gas flaring reduction regulations on the part of the government, couple with ageing infrastructure to develop and utilise the gas resource, poor access to local and international energy markets, and lack of political will to see to the end of gas flaring are the main reasons for continued flaring in Nigeria. Policy makers in the country need to strategise and come up with effective gas utilisation programs. They need to reform and develop the gas industry to effectively support gas gathering; marketing and distribution, and on the part of the government, strengthen its legal and regulatory frameworks related to gas flaring and venting. Incentives should be granted for gas flaring reduction projects and penalties should realistically reflect the prevailing economic value of flaring. If these are not done analysts would continue to question when Nigeria is actually ready to decarbonise its oil and gas industry by eliminating the flaring and venting of associated gas into the atmosphere.
Gas Flaring Effects and Revenue Made from Crude Oil in Nigeria

The study examines gas flaring and crude oil revenue in Nigeria. The study used secondary data for 14 years from 2000 to 2014 inclusive to analyze the issue using multiple regression analysis. The study employed time series data hence, a unit root test is conducted and found that they are stationary at level. Using three variables, gas flaring as the aggregate amount of gas flared by oil producing companies in Nigeria as an independent variable and crude oil revenue as an aggregate of revenue generated from all oil companies crude oil as dependent variable and tax as penalty on flaring is used as a control variable, the findings of the study show that gas flaring has a negative impact on Nigerian crude oil revenue and is statistically significant. From the research there are strong indications that the implementation of regulations and incentives to abate gas glaring in Nigeria has to be improving in other to increase revenue generated from crude oil. The author suggests that government should embark seriously on gas utilization policy and increase the penalty for companies who still engage in gas flaring. In addition, the government should utilize the gas flaring for electricity generation or implore another means of either utilizing it or curtail it.
The Potential Reduction of Carbon Dioxide (CO2) Emissions from Gas Flaring in Nigeria's Oil and Gas Industry through Alternative Productive Use

Globally, climate change and its adverse effects on the human population and the environment has necessitated significant research on the sustainable use of natural resources. Gas flaring in Nigeria's oil and gas industry causes environmental and health hazards and to a large extent, culminates in yearly loss of the Nation's revenue. The aim of the study is to highlight the potentials of converting flared gas from the Nigerian oil and gas industry to compressed natural gas (CNG) which could be an alternative fuel for the 220 Lagos Bus Rapid Transit (BRT Lite) while reducing CO2 emissions. In addition, the study provided an overview of gas flaring in the oil and gas industry and energy utilisation in some selected sectors in the country. The Long range Energy Alternative Planning System (LEAP) software was employed to model the energy demand and carbon dioxide emissions from the BRT Lite by creating a current scenario and projections to the year 2030. The use of CNG as an alternative fuel for Lagos BRT Lite will significantly reduce CO2 emissions in Nigeria's oil and gas industry. Other utilization options for flared gas from this industry includes: Liquefied Natural Gas (LNG) Liquefied Petroleum Gas (LPG) and power generation.
An empirical study of socialbot infiltration strategies in the Twitter social network
Venue: Social Network Analysis and Mining

Online social networks (OSNs) such as Twitter and Facebook have become a significant testing ground for Artificial Intelligence developers who build programs, known as socialbots, that imitate human users by automating their social network activities such as forming social links and posting content. Particularly, Twitter users have shown difficulties in distinguishing these socialbots from the human users in their social graphs. Frequently, socialbots are effective in acquiring human users as followers and exercising influence within them. While the success of socialbots is certainly a remarkable achievement for AI practitioners, their proliferation in the Twitter sphere opens many possibilities for cybercrime. The proliferation of socialbots in Twitter motivates us to assess the characteristics or strategies that make socialbots most likely to succeed. In this direction, we created 120 socialbot accounts in Twitter, which have a profile, follow other users, and generate tweets either by reposting others' tweets or by generating their own synthetic tweets. Then, we employ a $2^k$$2k factorial design experiment to quantify the infiltration performance of different socialbot strategies, and examine the effectiveness of individual profile and activity related attributes of the socialbots. Our analysis is the first of a kind, and reveals what strategies make socialbots successful in the Twitter sphere.
Use of Liposomal Gentamicin for Treatment of 5 Foals with Experimentally Induced Rhodococcus equi Pneumonia
Venue: Journal of veterinary internal medicine

Adverse effects of, and bacterial resistance to, macrolides used to treat Rhodococcus equi infections have prompted search for clinically effective alternative antimicrobials. Liposomal gentamicin (LG) is effective against R. equi in vitro and decreases tissue concentrations of R. equi in experimentally infected mice. Effectiveness of LG treatment of foals with R. equi pneumonia, however, has not been described.  Liposomal gentamicin is safe and effective for treating foals with R. equi pneumonia.  Ten foals with experimentally induced R. equi pneumonia.  Pilot treatment trial. Foals with pneumonia induced by intrabronchial instillation of R. equi were randomly allocated to receive either clarithromycin combined with rifampin (CLR RIF) PO or LG IV, and followed by daily physical examinations and weekly thoracic ultrasonography and serum creatinine concentration determinations until the resolution of clinical signs. Treatment success was defined as the resolution of clinical signs and ultrasonographically identified pulmonary abscesses.  foals were successfully treated. Two of 5 foals treated with LG developed azotemia within 1 week; LG was discontinued and treatment switched to CLR RIF for these foals. None of the CLR RIF treated foals developed azotemia.  Liposomal gentamicin IV can be effective for treatment of R. equi pneumonia, but nephrotoxicity indicates that an alternative dosing interval or route (such as nebulization) will be needed before LG is adequately safe for clinical use. Larger comparative trials will be needed to evaluate the relative efficacy of a safer LG dosage regimen.
Two centuries temperature variations over subtropical southeast China inferred from Pinus taiwanensis Hayata tree ring width
Venue: Climate Dynamics

High resolution long term temperature reconstructions in subtropical southeast China (SSC) are very scarce, yet indispensable for the comprehensive understanding of climate change in China, even in East Asia. We reconstructed the first previous growth season temperature in the Sanqingshan Mountains (SQS) southeast China since 1806 based on tree ring width data. The reconstruction accounts for 56.4 of the total variance in the instrumental record over 1954 2009. Unlike the Northern Hemispheric warming during recent two centuries, the reconstruction captured a slowly cooling trend from 1806 to 1980, followed by a rapid warming afterward. 2003 2009 was the warmest period in the reconstruction. 1970 2000 was colder than the last stage of the Little Ice Age (LIA) Most of the warm and cold periods in this reconstruction could be found in the tree ring based temperature reconstructions of vicinity area, indicating that the temperature variations in SSC were almost synchronous at least at decadal scale. This regional coherence of temperature variation was further confirmed by the spatial correlation patterns with the CRU TS3.22 grid dataset. A strong positive relationship between the temperature over SQS region and sea surface temperature (SST) over the North Pacific Ocean (NP) has been noted, suggesting that SST variations over NP and the related Pacific Decadal Oscillation significantly influenced the temperature variability over SSC. To better understand the climate variability during the LIA and the regional differences in temperature variations over SQS and northern Hemisphere, long data sets from more diverse areas of southern China are needed.
Biomarker records of palaeoenvironmental variations in subtropical Southern Africa since the late Pleistocene: Evidences from a coastal peatland

Southern Africa's unique global position has given rise to a dynamic climate influenced by large sea surface temperature gradients and seasonal fluctuations in the Inter Tropical Convergence Zone. Due to the semi arid climate of the region, terrestrial palaeorecords are rare and our understanding of the long term sensitivity of Southern African terrestrial ecosystems to climatic drivers is ambiguous. A 810 cm continuous peat core was extracted from the Mfabeni peatland with a 14 C basal age of c. 47 thousand years calibrated before present (kcal yr BP) positioning it as one of the oldest known sub tropical coastal peatlands in Southern Africa. This peat core provides an opportunity to investigate palaeoenvironmental changes in subtropical Southern Africa since the late Pleistocene. Biomarker n alkane, n alkanoic acid and n alkanol) analysis, in conjunction with previously published bulk geochemical data, was employed to reconstruct organic matter (OM) sources, rates of OM remineralisation and peatland hydrology. Our results showed that the principal OM source into the peatland was emergent and terrestrial plants with exception of shallow lake conditions when submerged macrophytes dominated (c. 44.5 42.6, 29.7, 26.1 23.1, 16.7 7.1 and 2.2 kcal yr BP) n Alkane proxies suggest that local plant assemblages were predominantly influenced by peatland hydrology. By incorporating temperature sensitive n alkanoic acid and n alkanol proxies, it was possible to disentangle the local temperature and precipitation changes. We report large variations in precipitation intensities, but subdued temperature fluctuations during the late Pleistocene. The Holocene period was characterised by overall elevated temperatures and precipitation compared to the preceding glacial period, interspersed with a millennial scale cooling event. A close link between the Mfabeni archive and adjacent Indian Ocean marine core records was observed, suggesting the regional ocean surface temperatures to be the dominant climate driver in this region since the late Pleistocene.
Density based Denoising of Point Cloud
Venue: ArXiv

Point cloud source data for surface reconstruction is usually contaminated with noise and outliers. To overcome this deficiency, a density based point cloud denoising method is presented to remove outliers and noisy points. First, particle swam optimization technique is employed for automatically approximating optimal bandwidth of multivariate kernel density estimation to ensure the robust performance of density estimation. Then, mean shift based clustering technique is used to remove outliers through a thresholding scheme. After removing outliers from the point cloud, bilateral mesh filtering is applied to smooth the remaining points. The experimental results show that this approach, comparably, is robust and efficient.
Advantages and Limitations of Open Source Software for Library Management System Functions: The Experience of Libraries in India

The explosion of availability of information on the Internet requires that libraries evolve into value added information providers, rather than mere curators of collections. Modern libraries need to stay relevant to a diverse, technologically savvy patron base and to facilitate and add value to the research community, while facing significant resource constraints. To face these challenges, libraries need to embrace digital technologies and library management systems (LMS) in order to work smart and achieve more with less. While LMS systems have been around for decades, libraries can explore the new frontier by embracing open source solutions, like open source software (OSS) library systems, which are free to acquire. They need to collaborate with computer experts and become technologically savvy to harness the full power of OSS solutions to meet the specific needs of the library and patron base. This article provides an overview of the availability, benefits, and drawbacks of various LMS systems and OSS variants, drawing from experiences in the present Indian context.
The Tao Of Physics An Exploration Of The Parallels Between Modern Physics And Eastern Mysticism

Thank you very much for downloading the tao of physics an exploration of the parallels between modern physics and eastern mysticism. As you may know, people have look hundreds times for their chosen novels like this the tao of physics an exploration of the parallels between modern physics and eastern mysticism, but end up in malicious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they cope with some infectious virus inside their desktop computer.
Mysticism and schizophrenia: A phenomenological exploration of the structure of consciousness in the schizophrenia spectrum disorders
Venue: Consciousness and Cognition

Mysticism and schizophrenia are different categories of human existence and experience. Nonetheless, they exhibit important phenomenological affinities, which, however, remain largely unaddressed. In this study, we explore structural analogies between key features of mysticism and major clinical phenomenological aspects of the schizophrenia spectrum disorders i.e. attitudes, the nature of experience, and the 'other' mystical or psychotic reality. Not only do these features gravitate around the issue of the basic dimensions of consciousness, they crucially seem to implicate and presuppose a specific alteration of the very structure of consciousness. This finding has bearings for the understanding of consciousness and its psychopathological distortions.
Hierarchical Models for Uncertainty Quantification: An Overview

Analyses of complex processes should account for the uncertainty in the data, the processes that generated the data, and the models that are used to represent the processes and data. Accounting for these uncertainties can be daunting in traditional statistical analyses. In recent years, hierarchical statistical models have provided a coherent probabilistic framework that can accommodate these multiple sources of quantifiable uncertainty. This overview describes C.K. Wikle Department of Statistics, University of Missouri, Columbia, MO, USA e mail: wiklec@missouri.edu (c) Springer International Publishing Switzerland 2015 R. Ghanem et al. (eds. Handbook of Uncertainty Quantification, DOI 10.1007/978 3 319 11259 6_4 1 1
Scaling limits in computational Bayesian inversion

Computational Bayesian inversion of operator equations with distributed uncertain input parameters is based on an infinite dimensional version of Bayes' formula established in M. Dashti and A.M. Stuart [Handbook of Uncertainty Quantification edited by R. Ghanem, D. Higdon and H. Owhadi. Springer (2015) and its numerical realization in C. Schillings and Ch. Schwab [Inverse Problems 29 (2013) 065011; Inverse Problems 30 (2014) 065007. Based on the sparsity of the posterior density shown in C. Schillings and Ch. Schwab [Inverse Problems 29 (2013) 065011; Inverse Problems 30 (2014) 065007. C. Schwab and A.M. Stuart [Inverse Problems 28 (2012) 045003. dimension adaptive Smolyak quadratures can afford higher convergence rates than MCMC in terms of the number M of solutions of the forward (parametric operator) equation in C. Schillings and Ch. Schwab [Inverse Problems 29 (2013) 065011; Inverse Problems 30 (2014) 065007. The error bounds and convergence rates obtained in C. Schillings and Ch. Schwab [Inverse Problems 29 (2013) 065011; Inverse Problems 30 (2014) 065007. are independent of the parameter dimension (in particular free from the curse of dimensionality) but depend on the (co)variance G 0 of the additive, Gaussian observation noise as exp(b G 1 for some constant b 0. It is proved that the Bayesian estimates admit asymptotic expansions as G 0. Sufficient (nondegeneracy) conditions for the existence of finite limits as G 0 are presented. For Gaussian priors, these limits are shown to be related to MAP estimators obtained from Tikhonov regularized least squares functionals. Quasi Newton (QN) methods with symmetric rank 1 updates are shown to identify the concentration points in a non intrusive way, and to obtain second order information of the posterior density at these points. Based on the theory, two novel computational Bayesian estimation algorithms for Bayesian estimation at small observation noise covariance G 0 with performance independent of G 0 are proposed: first, dimension adaptive Smolyak quadrature from C. Schillings and Ch. Schwab [Inverse Problems 29 (2013) 065011; Inverse Problems 30 (2014) 065007. combined with a reparametrization of the parametric Bayesian posterior density near the MAP point (assumed unique) and, second, generalized Richardson extrapolation to the limit of vanishing observation noise variance. Numerical experiments are presented which confirm G independent convergence of the curvature rescaled, adaptive Smolyak algorithm. Dimension truncation of the posterior density is justified by a general compactness result for the posterior's Hessian at the MAP point.