nils-herrmann/clean_scirepeval huggingface dataset:
Hearing Impairment and Cognitive Energy: The Framework for Understanding Effortful Listening (FUEL)
Venue: Ear and hearing

The Fifth Eriksholm Workshop on "Hearing Impairment and Cognitive Energy" was convened to develop a consensus among interdisciplinary experts about what is known on the topic, gaps in knowledge, the use of terminology, priorities for future research, and implications for practice. The general term cognitive energy was chosen to facilitate the broadest possible discussion of the topic. It goes back to Titchener (1908) who described the effects of attention on perception; he used the term psychic energy for the notion that limited mental resources can be flexibly allocated among perceptual and mental activities. The workshop focused on three main areas: (1) theories, models, concepts, definitions, and frameworks; (2) methods and measures; and (3) knowledge translation. We defined effort as the deliberate allocation of mental resources to overcome obstacles in goal pursuit when carrying out a task, with listening effort applying more specifically when tasks involve listening. We adapted Kahneman's seminal (1973) Capacity Model of Attention to listening and proposed a heuristically useful Framework for Understanding Effortful Listening (FUEL) Our FUEL incorporates the well known relationship between cognitive demand and the supply of cognitive capacity that is the foundation of cognitive theories of attention. Our FUEL also incorporates a motivation dimension based on complementary theories of motivational intensity, adaptive gain control, and optimal performance, fatigue, and pleasure. Using a three dimensional illustration, we highlight how listening effort depends not only on hearing difficulties and task demands but also on the listener's motivation to expend mental effort in the challenging situations of everyday life.
Strategies for optimizing polymer lipid hybrid nanoparticle mediated drug delivery
Venue: Expert opinion on drug delivery

Polymer lipid hybrid nanoparticles (PLN) are an emerging nanoparticle drug delivery system made of polymers and lipids taking advantages of both materials. PLN are solid at body temperature, which is similar to solid lipid nanoparticles (SLN)[1,2] but different from the traditionally referred lipidbased nanoparticles liposomes that consist of an aqueous core enclosed in a lipid bilayer. The coexistence of polymer and lipid possessing different material properties, such as hydrophobicity and water solubility, imparts PLN versatile capability of loading varying types of payloads, which is different from SLN and nanostructured lipid carriers that are mainly for loading hydrophobic compounds. Compared to other types of nanoparticle drug carriers, PLN exhibit a number of unique advantages including (1) wide selections of biocompatible polymers and lipids and numerous polymer lipid combinations, (2) easy fabrication by a single step method, and (3) superior capability of co encapsulating therapeutic and imaging agents of different properties. PLN formulations have been demonstrated to increase drug loading efficiency, enable controlled drug release, improve drug uptake and intracellular drug transport, and circumvent membrane efflux transportermediated multidrug resistance (MDR) in cancer cells. Like other types of nanocarriers, PLN can also be conjugated with targeting moieties for targeted drug delivery to tumor vasculature and tumor cells. Because of these advantages, PLN system is of tremendous potential for delivery of a broad range of therapeutic agents. However, it is challenging to design optimal formulations with all desirable characteristics for specific applications such as cancer chemotherapy. This editorial article provides an overview of PLN formulations with a focus on injectables for cancer therapy, representative examples, and discusses the key factors, strategies, and future in the development of PLN for effective delivery of individual or combinatorial therapeutic agents.
PEG/heparin decorated lipid polymer hybrid nanoparticles for long circulating drug delivery

The clinical success of lipid polymer hybrid nanoparticles (LPHNPs) for effective targeted drug delivery is still hindered by their rapid clearance from the bloodstream. In this work, a novel strategy for surface modification of LPHNPs with combined polyethylene glycol (PEG) and heparin (HEP) was developed to achieve a significant prolongation in blood circulation. All the LPHNPs formulated with a diameter of 100 200 nm were prepared by a modified w/o/w solvent diffusion/evaporation method and physicochemically characterized. The synergistic action of PEG and HEP was observed, as combinatorial modification significantly improved the surface hydrophilicity as well as the suspension stability of nanoparticles and tailored the surface charge close to neutrality, in comparison to LPHNPs surface treated with PEG or HEP alone. In vitro and in vivo studies showed that the PEG/HEP coating significantly prohibited the macrophage uptake and extended the blood circulation of LPHNPs with concomitant reduced liver sequestration. The in vitro phagocytosis results using murine peritoneal macrophages showed 8.2 fold reduction compared to the control LPHNP group. The in vivo study in ICR mice showed PEG/HEP coating increased the blood circulation half life of LPHNPs from 0.3 h to 72.6 h. Moreover, PEG/HEP LPHNPs exhibited dramatically reduced liver accumulation when compared to LPHNPs. These results demonstrated that PEG/HEP LPHNPs with optimized particle size, surface hydrophilicity and surface charge, have a promising potential as long circulating drug delivery systems.
iRGD decorated lipid polymer hybrid nanoparticles for targeted co delivery of doxorubicin and sorafenib to enhance anti hepatocellular carcinoma efficacy.
Venue: Nanomedicine nanotechnology, biology, and medicine

The combination of doxorubicin (DOX) with sorafenib (SOR) has proven an effective strategy to enhance anti hepatocellular carcinoma (HCC) efficacy. However, respective in vivo pharmacokinetic profiles and different endocytosis capacities of these two drugs greatly hinder their current application. Herein, the tumor targeting peptide iRGD decorated lipid polymer hybrid nanoparticles (NPs) with a shell core structure were developed for co delivery of DOX and SOR (DOX+SOR/iRGD NPs) After the drug ratio was optimized, the stabilized DOX+SOR/iRGD NPs were prepared. Through the iRGD integrin recognition, DOX+SOR/iRGD NPs showed synergistic cytotoxicity, pro apoptotic ability and enhanced internalization rate in human liver cancer HepG2 cells. In vivo pharmacokinetic result demonstrated that an extended circulation and bioavailability of DOX+SOR/iRGD NPs than free drugs. More importantly, DOX+SOR/iRGD NPs significantly enhanced antitumor efficiency in HCC xenograft mouse models. Overall, this study describes a promising nanoparticulate drug co delivery strategy to combine clinical anticancer drugs and enhance anti HCC efficacy.
From Life Cycle Costing to Economic Life Cycle Assessment Introducing an Economic Impact Pathway

Economic activities play a key role in human societies by providing goods and services through production, distribution, and exchange. At the same time, economic activities through common focus on short term profitability may cause global crisis at all levels. The inclusion of three dimensions environment, economy, and society when measuring progress towards sustainable development has accordingly reached consensus. In this context, the Life cycle sustainability assessment (LCSA) framework has been developed for assessing the sustainability performance of products through Life cycle assessment (LCA) Life cycle costing (LCC) and Social life cycle assessment (SLCA) Yet, the focus of common economic assessments, by means of LCC, is still on financial costs. However, as economic activities may have a wide range of positive and negative consequences, it seems particularly important to extend the scope of economic assessments. Foremost, as the limitation to monetary values triggers inconsistent implementation practice. Further aspects like missing assessment targets, uncertainty, common goods, or even missing ownership remain unconsidered. Therefore, we propose economic life cycle assessment (EcLCA) for representing the economic pillar within the LCSA framework, following the requirements of ISO 14044, and introducing an economic impact pathway including midpoint and endpoint categories towards defined areas of protection (AoPs) We identify important target ratios by means of economic AoPs, which drive economic activities on the macro and microeconomic level. Furthermore, we provide suggestions for midpoint and endpoint indicators representing the defined categories. With the presented EcLCA framework, a first step towards the inclusion of economic impacts within LCSA has been made. Relations between economic activities and resulting consequences are displayed, going beyond the cost driven view of classical LCC. Further research and fine tuning of the identified midpoint and endpoint categories and related indicators is, however, needed to enable a valid and consistent assessment basis for fostering the practical implementation of EcLCA and LCSA.
xBreeze/ADL: A language for software architecture specification and analysis
Venue: Int. J. Autom. Comput.

Architecture description languages play an important role in modelling software architectures. However, many architecture description languages (ADLs) are either unable to deal with the verification and dynamic changes directly or too formal to be understood and manipulated. This paper presents xBreeze/ADL, a novel extensible markup language (XML) based verification and evolution supported architecture description language, which is specifically designed for modelling the software architecture of large, complex systems. Five principle design goals are 1) to separate template from instance to define a loose coupling structure, 2) to present virtual and concrete link to identify service execution flow, 3) to clearly represent component behaviour to specify architecture semantics, 4) to introduce multi dimension restrictions to define the architecture constraints, and 5) to use the graph transformation theory to implement the architecture configuration management (i.e. reconfiguration and verification) Various advanced features of xBreeze/ADL are illustrated by using an example on online movie ticket booking system.
Catalytic effects of nano additives on decomposition and combustion of RDX HMX and AP based energetic compositions

The RDX, HMX, and AP are currently the most widely used energetic ingredients in composite solid propellants, since the newly developed energetic compounds are still unable to replace them due to various bottleneck technical problems. In order to improve their combustion efficiency and performance, a common alternative way is to utilize novel nano sized energetic additives. There are a great many nanomaterials that have been developed in the past decades, which include nanometal particles, metal oxides, metal salts, metallic composites, organometallic compounds, energetic nanocatalysts, and carbon nanomaterials. These additives could increase both the decomposition and the burning rate as well as enhance the combustion efficiency of the corresponding solid propellants by changing the thermal conductivity, energy barrier of thermolysis, heat of reaction, and gas phase reaction mechanisms of the main ingredients such as RDX, HMX, and AP. This review paper discusses and summarizes the effects of abovementioned nano additives on decomposition kinetics, reaction models, decomposition mechanisms and burning rates, pressure exponents, combustion wave structures, and flame propagation of RDX HMX and AP based energetic compositions. The catalytic mechanisms associated with different types of nanomaterials are explained and clarified. Owing to their extremely large specific surface areas, nano sized energetic additives have significant catalytic effects in both condensed and gas phases during decomposition and subsequent combustion via activation of the reactants and acceleration of their transition state formations. The flame structures of AP based composite propellants under the effect of some nanoadditives are presented showing the enhanced burning characteristics and stabilized combustion process.
Thermal Behavior and Decomposition Kinetics of RDX and RDX/HTPB Composition Using Various Techniques and Methods

In this paper, the thermal behavior and decomposition kinetics of trinitrohexahydrotriazine (RDX) and its polymer bonded explosive (PBX) containing a hydroxyl terminated polybutadiene (HTPB) based polyurethane binder in the ratio 80% RDX/ 20% HTPB were investigated using various experimental techniques and analytical methods. The HTPB polyurethane matrix contains other additives and was cured using hexamethylene diisocyanate (HMDI) Thermogravimetric analysis (TGA) Differential Scanning Calorimetry (DSC) Vacuum Stability Test (VST) and Ignition Delay Techniques were applied both isothermally and non isothermally. The kinetic parameters were determined using both the isoconversional (model free) and the model fitting methods. For comparison, Advanced Kinetics and Technology Solution (AKTS) software was also used. It was found that the addition of an HTPB based polyurethane matrix to pure RDX decreased its decomposition temperature. It was also found that RDX/ HTPB has a lower activation energy than pure RDX. The polyurethane matrix had a significant effect on the decomposition mechanism of RDX resulting in different reaction models. It was concluded that the activation energies obtained using the Ozawa, Flynn, and Wall (OFW) and Kissinger Akahira Sunose (KAS) methods were very close to the results obtained via the AKTS software lying in the range 218.3 220.2 kJ*mol 1. The VST technique yielded kinetic parameters close to those obtained using TG/DTG. On the other hand, the Ignition Delay Technique yielded different and inconsistent kinetic parameters.
Matrix and Tensor Factorization Techniques for Recommender Systems
Venue: SpringerBriefs in Computer Science

This book presents the algorithms used to provide recommendations by exploiting matrix factorization and tensor decomposition techniques. It highlights well known decomposition methods for recommender systems, such as Singular Value Decomposition (SVD) UV decomposition, Non negative Matrix Factorization (NMF) etc. and describes in detail the pros and cons of each method for matrices and tensors. This book provides a detailed theoretical mathematical background of matrix/tensor factorization techniques and a step by step analysis of each method on the basis of an integrated toy example that runs throughout all its chapters and helps the reader to understand the key differences among methods. It also contains two chapters, where different matrix and tensor methods are compared experimentally on real data sets, such as Epinions, GeoSocialRec, Last.fm, BibSonomy, etc. and provides further insights into the advantages and disadvantages of each method. The book offers a rich blend of theory and practice, making it suitable for students, researchers and practitioners interested in both recommenders and factorization methods. Lecturers can also use it for classes on data mining, recommender systems and dimensionality reduction methods.
Motivation to Learn and Distance Learning Programs: What Brazilian Workers Think about?

Distance education encompasses all forms of learning and teaching in which those who learn and who teach are in different locations. It involves the separation of teachers and learners which distinguishes it from face to face education. Online education is characterized by the influence of an educational organization which distinguishes it from self study and private tutoring. Organizations are both consumers and suppliers of distance education because of its benefits such as productivity improvements and cost savings in training. This paper aims to identify the motivational profile to learning by distance education students who work in a national Brazilian Organization. We consider that the participation in distance learning programs is motivator of stay work. We applied a Brazilian questionnaire (17 item) to 127 employees (majority were male 97.60% in the range 26 33 years and 6 to 10 years of time of service in the Organization) who were enrolled or who had taken any course in distance modality in the last 2 years. The results indicate that there is a relatively negative participants' perception about how distance learning programs can add to their performance in terms of skills and competences acquisition. The support of colleagues is very important for learning and its impact at work organizational routines.
Measurement of the Double Beta Decay Half Life and Search for the Neutrinoless Double Beta Decay of {48}\rm Ca} with the NEMO 3 Detector

The NEMO 3 experiment at the Modane Underground Laboratory has investigated the double \beta$ decay of {48}\rm Ca} Using $5.25$ yr of data recorded with a $6.99\\rm g} sample of {48}\rm Ca} approximately $150$ double \beta$ decay candidate events have been selected with a signal to background ratio greater than $3$ The half life for the two neutrino double \beta$ decay of {48}\rm Ca} has been measured to be $T^{2\nu}_{1/2}[6.4\ +0.7}_{ 0.6}\rm (stat. +1.2}_{ 0.9}\rm (syst.  A search for neutrinoless double \beta$ decay of {48}\rm Ca} yields a null result and a corresponding lower limit on the half life is found to be $T^{0\nu}_{1/2} 2.0 \times 10^{22}\rm yr} at $90\ confidence level, translating into an upper limit on the effective Majorana neutrino mass of 6.0 26$ \rm eV} with the range reflecting different nuclear matrix element calculations. Limits are also set on models involving Majoron emission and right handed currents.
Dynamics of Correlations in the Presences of Intrinsic Decoherence

The dynamics of a mixed spin system governed by XXZ model in additional to an intrinsic decoherence is investigated. The behavior of quantum correlation and the degree of entanglement between the two subsystems is quantified by using measurement induced disturbance and the negativity, respectively. It is shown that, the phenomena of long lived entanglement appears for larger values of intrinsic decoherence parameters. The degree of entanglement and quantum correlation depend on the dimensions of subsystems which are pass through the external field and the initial states setting. We show that the negativity for some initial classes is more robust than the measurement induced disturbance, while for some other initial classes the quantum correlations are more robust than entanglement.
Judith Butler: Gender Trouble. Feminism and the Subversion of Identity, Routledge: New York 1990, 172 S. (dt. Das Unbehagen der Geschlechter, Frankfurt: Suhrkamp 1991, 236 S.

Die US amerikanische Philosophin Judith Butler (1956) die als eine der wichtigsten Vertreter/innen des poststrukturalistischen Feminismus und der Queer Theory gilt, erlangte mit der Publikation von Gender Trouble eine uberraschende Popularitat. Butlers Kritik an identitatspolitischen Strategien, ihre radikale Infragestellung biologischer Begrundungen der Geschlechterdifferenz und ihr Vorschlag, die heteronormative Ordnung parodistisch zu unterlaufen, trafen auf begeisterte Zustimmung, provozierten aber auch heftige Kritik. Gerade deshalb erreichte das Buch bald den Status eines Grundlagentexts der sozialwissenschaftlichen Geschlechterforschung. Butler selbst greift zentrale Fragen aus Gender Trouble in spateren Arbeiten wieder auf. Wesentliche Zuge des Buches konnen so als grundlegend fur ihr bisheriges Werk gelten: eine dezidiert politische Haltung, ein Interesse fur die produktive Macht von Sprache und ein kritischer Blick auf die Ausschlusse, die den Status als Subjekt begrunden.
Turbulent Flow A Computational Model of World Literature

This article uses computational modeling and large scale pattern detection to develop a theory of global textual transmission as a process of turbulent flow. Specifically, it models stream of consciousness narration as a discrete set of linguistic features and rhetorical elements and uses this model to track the movement of this modernist technique across generic boundaries (from anglophone modernism to more popular genres) and linguistic ones (from English to Japanese) Oscillating between statistical models and moments of close reading, the article shows how a quantitatively scaled up approach, rather than reinforcing an image of global textual flows as singular and monolithic, illuminates world literature as a system constituted by patterns of divergence in structure and of difference in sameness.
The Mixture of Textrank and Lexrank Techniques of Single Document Automatic Summarization Research in Tibetan
Venue: 2016 8th International Conference on Intelligent Human Machine Systems and Cybernetics (IHMSC)

Today is an era of knowledge economy and information dominated. Automatic summarization is an important research in the field of natural language processing, its purpose to explore human obtain valuable information from natural language texts. As the Tibetan information processing technology is backward, and the achievements of automatic summarization have not been publicly reported in Tibetan. This paper references the existed Chinese and English automatic summarization technology in domestic and foreign, and proposes a method of Tibetan automatic summarization. Combination with the advantage of keyword processing based on TextRank and processing of the relationship between sentences based on LexRank algorithm. Take full account of the frequency, part of speech, word position, word length, content and position of a sentence. In particular, the generated summarization considering the similarity of candidate sentences. Experiments analysis three summarization methods based on TextRank, based on LexRank and based on LexRank+TextRank respectively, and using the ROUGE value to evaluate the effect of summarization. Experimental results show that, the effect of the mixture of TextRank and LexRank techniques of single document automatic summarization in Tibetan is better and accuracy reached 80%
Modified LexRank for Tweet Summarization
Venue: Int. J. Rough Sets Data Anal.

Summary generation is an important process in those conditions where the user needs to obtain the key features of the document without having to go through the whole document itself. The summarization process is of basically two types: 1 Single document Summarization and, 2 Multiple Document Summarization. But here the microblogging environment is taken into account which have a restriction on the number of characters contained within a post. Therefore, single document summarizers are not applicable to this condition. There are many features along which the summarization of the microblog post can be done for example, post's topic, it's posting time, happening of the event, etc. This paper proposes a method that includes the temporal features of the microblog posts to develop an extractive summary of the event from each and every post, which will further increase the quality of the summary created as it includes all the key features in the summary.