nils-herrmann/clean_scirepeval huggingface dataset:
Infrared spectroscopy as a tool to characterise starch ordered structure a joint FTIR ATR, NMR, XRD and DSC study.
Venue: Carbohydrate polymers

Starch has a heterogeneous, semi crystalline granular structure and the degree of ordered structure can affect its behaviour in foods and bioplastics. A range of methodologies are employed to study starch structure; differential scanning calorimetry, (13)C nuclear magnetic resonance, X ray diffraction and Fourier transform infrared spectroscopy (FTIR) Despite the appeal of FTIR as a rapid, non destructive methodology, there is currently no systematically defined quantitative relationship between FTIR spectral features and other starch structural measures. Here, we subject 61 starch samples to structural analysis, and systematically correlate FTIR spectra with other measures of starch structure. A hydration dependent peak position shift in the FTIR spectra of starch is observed, resulting from increased molecular order, but with complex, non linear behaviour. We demonstrate that FTIR is a tool that can quantitatively probe short range interactions in starch structure. However, the assumptions of linear relationships between starch ordered structure and peak ratios are overly simplistic.
Investigating LSTMs for Joint Extraction of Opinion Entities and Relations
Venue: ACL

We investigate the use of deep bidirectional LSTMs for joint extraction of opinion entities and the IS FROM and ISABOUT relations that connect them the first such attempt using a deep learning approach. Perhaps surprisingly, we find that standard LSTMs are not competitive with a state of the art CRF+ILP joint inference approach (Yang and Cardie, 2013) to opinion entities extraction, performing below even the standalone sequencetagging CRF. Incorporating sentence level and a novel relation level optimization, however, allows the LSTM to identify opinion relations and to perform within 1 3% of the state of the art joint model for opinion entities and the IS FROM relation; and to perform as well as the state of theart for the IS ABOUT relation all without access to opinion lexicons, parsers and other preprocessing components required for the feature rich CRF+ILP approach.
Convergence Culture in European Newsrooms

For two decades, convergence culture has been an important motivator for change in journalism worldwide. Journalism research has followed these developments, investigating the dimensions of change that define convergence as a cultural shift in the newsroom. Research in the European context has mostly been comprised of national case studies of flagship media outlets whereas comparative, let alone quantitative, studies are scarce. In response to these shortcomings, we present a comparative survey among newspaper journalists in managerial positions on convergence strategies in newsrooms from Germany, the Netherlands, Switzerland, Austria, Spain, and Portugal. Results show that there is still a dominant print culture present in newsrooms across Europe; however, a shift toward convergence journalism is evident in the strategic implementation of editorial routines and practices as well as in the encouragement of journalists to join convergence developments. Furthermore, newsrooms in Mediterranean countries are more advanced than those in North/Central Europe when it comes to embracing convergence culture because of a stronger audio visual than print news tradition and a higher motivation among journalists. Our study reveals that after two decades of European convergence journalism, cultural change moves slowly but steadily toward a news production that makes use of the possibilities emerging from convergence.
Moving convergence culture towards cultural intermediation: social media and cultural inclusion

Raymond Williams noted culture is specific to each society, where 'the making of a society is the finding of common meanings and direction' Cultural studies provide a foundation for an array of emerging research areas that seek to explore those meanings and directions, such as convergence culture. Recent humanities scholarship has called for researchers to move beyond the marvel of convergence culture, with its potential for increased social inclusion and cultural diversity, to a more nuanced understanding of networked participation. This paper uses empirical research data gathered from the Australian Broadcasting Corporation to argue that embedded cultural industries research can contribute, through the cultural intermediation framework, to cultural studies and the political, economic, and practice based strengths of the creative industries. It also argues that in a contemporary institutional social media environment, cultural intermediation is a useful framework to understand convergent media practices.
La ensenanza de conceptos basicos de Fisica Cuantica para un aprendizaje significativo del Modelo Atomico Actual

En este trabajo de investigacion se realiza una exploracion acerca de las acciones que realizan estudiantes de escuela media para intentar comprender los rasgos mas generales del 'Modelo Atomico Actual' La busqueda se hace empleando como fuentes de indicios los trabajos escritos desarrollados en diferentes instancias del proceso de ensenanza y aprendizaje y los registros obtenidos a partir de las clases, donde las interacciones orales dan cuenta, aunque en forma parcial, del tipo de pensamiento conceptual que circula en el aula. Ademas se toman en cuenta para el estudio todas aquellas acciones que acompanan al texto oral: los dialogos entre pares, las respuestas extemporaneas, los gestos, los silencios, es decir, lo que forma parte del acto comunicativo. Desde lo investigativo es factible construir balizas en el campo del aprendizaje y de la ensenanza, siempre que el marco teorico sea pertinente, y continuar contribuyendo con los fundamentos de la investigacion en educacion en ciencias, area en expansion intrinsecamente interdisciplinaria. Desde la didactica parece posible abordar con bastante fidelidad los conceptos de foton, de probabilidad y de estado, en el marco de uno de los modelos mas productivos de las ciencias tal como es el modelo atomico actual.
Impact of grain shape on seismic attenuation and phase velocity in cubic polycrystalline materials

Attenuation and phase velocity of seismic waves propagating in cubic polycrystalline aggregates with elongated grains are computed from the Rayleigh (low frequency) to the geometrical optics (high frequency) regime using a spectral function approach. In this study, we consider the case of perfectly aligned ellipsoidal grains with randomly oriented crystallographic axes. Such anisometric medium exhibits transverse isotropy. The frequency dependence of both phase velocity and scattering attenuation for quasi compressional (q P quasi shear vertical (q S V and quasi shear horizontal (q S H waves are examined in detail. The attenuation depends on the effective volume of the grain in the Rayleigh regime, on the grain dimension in the direction of propagation in the stochastic regime, and is inversely proportional to the grain size in the direction of propagation in the geometrical optics regime. The phase velocity exhibits a much more complex pattern depending on the grain shape and frequency. In particular, the fast/slow direction of propagation is not systematically aligned with the direction of low/high attenuation. The anisotropy in velocity typically varies from 1% in the Rayleigh regime to a few percents at the transition from the stochastic to the geometrical optics regime. Even for a highly anisotropic cubic iron crystals, q S V and q S H attenuations differ by at most 12% in the Rayleigh to stochastic transition regime but are equal in other frequency ranges. The q S V and q S H phase velocities, from the Rayleigh to the stochastic regime, differ by at most 1% Anisotropy induced by geometrical effects should therefore be detectable in laboratory or seismological data.
Fixation of strategies driven by switching probabilities in evolutionary games

We study the evolutionary dynamics of strategies in finite populations which are homogeneous and well mixed by means of the pairwise comparison process, the core of which is the proposed switching probability. Previous studies about this subject are usually based on the known payoff comparison of the related players, which is an ideal assumption. In real social systems, acquiring the accurate payoffs of partners at each round of interaction may be not easy. So we bypass the need of explicit knowledge of payoffs, and encode the payoffs into the willingness of any individual shift from her current strategy to the competing one, and the switching probabilities are wholly independent of payoffs. Along this way, the strategy updating can be performed when game models are fixed and payoffs are unclear, expected to extend ideal assumptions to be more realistic one. We explore the impact of the switching probability on the fixation probability and derive a simple formula which determines the fixation probability. Moreover we find that cooperation dominates defection if the probability of cooperation replacing defection is always larger than the probability of defection replacing cooperation in finite populations. Last, we investigate the influences of model parameters on the fixation of strategies in the framework of three concrete game models: prisoner's dilemma, snowdrift game and stag hunt game, which effectively portray the characteristics of cooperative dilemmas in real social systems.
Petri net based simulation analysis for emergency response to multiple simultaneous large scale fires

In the field of hazardous chemicals, there are many flammable materials located in different places within an industrial area. It is possible that major fires occur at the same time due to terrorism or vandalism (i.e. a security point of view) These fires might lead to domino effects at different locations around. Whether the fire emergency response preparedness, which is organized to fight against one of the fires, can handle the multiple fires, is studied in this article and a Petri net based simulation approach is proposed. Through Petri net based simulation, the process of fire fighting can be revealed. A model of fighting against three fires is established, and the strategies of fire fighters staffing arrangements are analyzed. The results show that in most cases the distribution according to fire severity is better than the average distribution, but in some conditions the average distribution strategy prevails. Different backup staffing strategies are also compared, and the results indicate that the improvement by increasing staffing backups also depends on the fire conditions.
Reduced reward driven eating accounts for the impact of a mindfulness based diet and exercise intervention on weight loss: Data from the SHINE randomized controlled trial
Venue: Appetite

Many individuals with obesity report over eating despite intentions to maintain or lose weight. Two barriers to long term weight loss are reward driven eating, which is characterized by a lack of control over eating, a preoccupation with food, and a lack of satiety; and psychological stress. Mindfulness training may address these barriers by promoting awareness of hunger and satiety cues, self regulatory control, and stress reduction. We examined these two barriers as potential mediators of weight loss in the Supporting Health by Integrating Nutrition and Exercise (SHINE) randomized controlled trial, which compared the effects of a 5.5 month diet and exercise intervention with or without mindfulness training on weight loss among adults with obesity. Intention to treat multiple mediation models tested whether post intervention reward driven eating and psychological stress mediated the impact of intervention arm on weight loss at 12 and 18 months post baseline among 194 adults with obesity (BMI: 30 45) Mindfulness (relative to control) participants had significant reductions in reward driven eating at 6 months (post intervention) which, in turn, predicted weight loss at 12 months. Post intervention reward driven eating mediated 47.1% of the total intervention arm effect on weight loss at 12 months [b 0.06, SE(b) 0.03, p .030, 95% CI 0.12, 0.01) This mediated effect was reduced when predicting weight loss at 18 months (p .396) accounting for 23.0% of the total intervention effect, despite similar weight loss at 12 months. Psychological stress did not mediate the effect of intervention arm on weight loss at 12 or 18 months. In conclusion, reducing reward driven eating, which can be achieved using a diet and exercise intervention that includes mindfulness training, may promote weight loss (
Review on the role of Nanotechnology in Dentistry and Medicine

To study the role and advancements of Nanomedicine in Dentistry and its Benefits  This is to study the changes and improvements in the field of Dentistry due to the incorporation of Nanomedicine and nano technological methods for treatment.  Every field involved in Health Care services must be dynamic and open to the introduction of newer methods and technology. The incorporation of Nanomedicine in Dentistry has opened new doors to increase the scope of dentistry and has made path breaking changes in oral surgery among other procedures.  There is an increasing need for awareness about the futuristic and advanced forms of treatment provided today. Nanomedicine provides an opportunity for dentists to incorporate more biomimetic substances in dental treatment so that there is greater coordination between the nanostructures replacing the parts of the teeth with our body's regenerative processes.
Personalized medicine: the enabling role of nanotechnology.
Venue: Nanomedicine

2016 Personalized medicine has recently taken center stage in cancer research and has led to a number of therapeutic success stories in oncological practice. Cancer is an immensely complex, heterogeneous disease that is caused by the interplay of multiple intrinsic (genetic predisposition) and extrinsic (lifestyle) factors. As cancer progresses, genetic drifts in the cell population typically result in heterogeneity with regard to cell antigenicity, differentiation state, proliferation rate, invasiveness, metastatic potential and response to chemotherapeutics. It has been increasingly recognized that cancer is a heterogeneous, evolving and adaptive malady that requires personalization of the treatment, as to the extent where the right drug is administered to the right patient with the right dose at the right time. Given the system complexity and the vastly limited understanding of the underlying pathophysiology, however, this poses a constitutive challenge to modern medicine (multiparameter optimization problem with many unknowns) In recent years, analysis of somatic mutations in cancer genomes has led to the identification of a compendium of aberrations that confer cancer development and has in turn enabled development of drugs that specifically target hallmarks of neoplasia  A range of small molecule inhibitors and therapeutic antibodies have been developed to target overexpressed proteins, driving the exceedingly rapid translation of genomic discoveries into clinical end points. Selection of patient subsets (so called responders) out of bigger patient cohorts based on genomic data has proven to be highly beneficial with regard to drug efficacy and patient outcome and has ushered in a new era, the era of precision medicine. Although perceived with much excitement by the scientific community, personalized therapy heavily relies on initial genomic profiling and the constitutive monitoring of biomarkers which require costefficient analysis of massive amounts of data, and hence few personalized medicines have entered clinical routine  While a few years back the challenges in this field were scientific in nature, with the maturation of the omics' sciences, it now seems that the major barriers are increasingly related to effective clinical implementation and socioeconomics [3,4] Personalized medicine requires a re thinking and transition away from the 'one drug to fit all' idea. Every day, millions of people take medications that will not only not help but in the worst case even harm them, hence causing a significant burden to the healthcare system. Still, these very same medications are the drugs that reach blockbuster status and bring the revenue that is so vital for a filled drug development pipeline and thus are critiPersonalized medicine: the enabling role of nanotechnology
Keystroke Dynamics for User Authentication and Identification by using Typing Rhythm

In this era computer security is an important issue now a days because these are used everywhere to store process the sensitive data. Specially those used in e banking, e commerce, virtual offices, e learning, distributed, computing various services over the internet. Using Keystroke dynamics authentication technology can be secured by password from various attacks. This technique is based on human behavior to type their password. Here analysis is done using human behavior with their typing pattern. As keystroke dynamics does not require any hardware, no extra hardware is used. Only software based technology is required for password protection. The result provides emphasis with pleasure security that growing in demand in web based application.
Gravitational wave emission by the high braking index pulsar PSR J1640 4631

Recently, a braking index for the pulsar PSR J1640 4631 has been measured. With a braking index of $n 3.15 \pm 0.03$ this pulsar has the highest braking index ever measured. As it is well known, a pure magnetic dipole brake yields $n 3$ whereas a pure gravitational wave brake yields $n 5$ Therefore, each of these mechanisms alone can not account for the braking index found for PSR J1640 4631. Here we show that such a braking index can be accounted for if the spindown model combines magnetic dipole and gravitational wave brakes. Then, we briefly discuss the detectability of this pulsar by aLIGO and the planned Einstein Telescope. In particular, we show that the amplitude of the gravitational wave that comes from our model is around a factor four lower than the amplitude modeled exclusively by gravitational wave energy loss. Another interesting outcome of our modeling is that we are able to obtain the ellipticity from the braking index and other pulsar parameters.
GRAVITATIONAL WAVES FROM PULSARS AND THEIR BRAKING INDICES: THE ROLE OF A TIME DEPENDENT MAGNETIC ELLIPTICITY

We study the role of time dependent magnetic ellipticities on the calculation of the braking index of pulsars. Moreover, we study the consequences of such a on the amplitude of gravitational waves (GWs) generated by pulsars with measured braking indices. We show that, since the ellipticity generated by the magnetic dipole is extremely small, the corresponding amplitude of GWs is much smaller than the amplitude obtained via the spindown limit.
Gravitational waves from pulsars with measured braking index

We study the putative emission of gravitational waves (GWs) in particular for pulsars with measured braking index. We show that the appropriate combination of both GW emission and magnetic dipole brakes can naturally explain the measured braking index, when the surface magnetic field and the angle between the magnetic dipole and rotation axes are time dependent. Then we discuss the detectability of these very pulsars by aLIGO and the Einstein Telescope. We call attention to the realistic possibility that aLIGO can detect the GWs generated by at least some of these pulsars, such as Vela, for example.
BPMTimeline: JavaScript Tempo Functions and Time Mappings using an Analytical Solution

Time mapping is a common feature in many (commercial and/or open source) Digital Audio Workstations, allowing the musician to automate tempo changes of a musical performance or work, as well as to visualize the relation between score time (beats) and real/performance time (seconds) Unfortunately, available music production, performance and remixing tools implemented with web technologies like JavaScript and Web Audio API do not offer any mechanism for flexible, and seamless, tempo manipulation and automation. In this paper, we present BPMTimeline, a time mapping library, providing a seamless mapping between score and performance time. To achieve this, we model tempo changes as tempo functions (a well documented subject in literature) and realize the mappings through integral and inverse of integral of tempo functions.
Plant cell culture strategies for the production of natural products
Venue: BMB reports

Plants have evolved a vast chemical cornucopia to support their sessile lifestyles. Man has exploited this natural resource since Neolithic times and currently plant derived chemicals are exploited for a myriad of applications. However, plant sources of most high value natural products (NPs) are not domesticated and therefore their production cannot be undertaken on an agricultural scale. Further, these plant species are often slow growing, their populations limiting, the concentration of the target molecule highly variable and routinely present at extremely low concentrations. Plant cell and organ culture constitutes a sustainable, controllable and environmentally friendly tool for the industrial production of plant NPs. Further, advances in cell line selection, biotransformation, product secretion, cell permeabilisation, extraction and scale up, among others, are driving increases in plant NP yields. However, there remain significant obstacles to the commercial synthesis of high value chemicals from these sources. The relatively recent isolation, culturing and characterisation of cambial meristematic cells (CMCs) provides an emerging platform to circumvent many of these potential difficulties.
Detection and classification of diseases of Grape plant using opposite colour Local Binary Pattern feature and machine learning for automated Decision Support System
Venue: 2016 3rd International Conference on Signal Processing and Integrated Networks (SPIN)

Plant diseases cause major economic and production losses as well as curtailment in both quantity and quality of agricultural production. Now a day's, for supervising large field of crops there is been increased demand for plant leaf disease detection system. The critical issue here is to monitor the health of the plants and detection of the respective diseases. Studies show that most of the plant disease can be diagnosed from the properties of the leaf. Thus leaf based disease analysis for plants is an exciting new domain. The technique proposed for identification of plant disease through the leaf texture analysis and pattern recognition. In this work we focus on Grapes plant leaf disease detection system. The system takes a single leaf of a plant as an input and segmentation is performed after background removal. The segmented leaf image is then analyzed through high pass filter to detect the diseased part of the leaf. The segmented leaf texture is retrieved using unique fractal based texture feature. Fractal based features are locally invariant in nature and therefore provides a good texture model. The texture of every independent disease will be different. The extracted texture pattern is then classified using multiclass SVM. The work classifies focus on major diseases commonly observed in Grapes plant which are downy mildew black rot. The proposed approach avails advice of agricultural experts easily to farmers with the accuracy of 96.6%