nils-herrmann/clean_scirepeval huggingface dataset:
Multi probe cosmological analysis with the dark energy survey
Year: 2019

Ongoing and future photometric surveys will enable detailed measurements of the late time Universe and powerful tests of the nature of dark energy and General Relativity. These surveys will be able to obtain cosmological constraints from multiple probes, and the combination of these probes can improve their robustness and constraining power. This thesis is focused on the combination of multiple tracers of large scale structure (LSS) to obtain tighter cosmological constraints. First, we combine the galaxy clustering from the Dark Energy Survey (DES) Year 1 (Y1) data with CMB lensing from the optimal combination of South Pole Telescope (SPT) and Planck, obtaining constraints on the galaxy bias, the growth function and the cosmological parameters. Our results are consistent with LCDM and other measurements of DES Y1. However, their constraining power is limited due to conservative scale cuts. We expect an improved signal to noise in future analyses. We then combine the galaxy clustering of two different galaxy samples (the so called multi tracer approach) to explore the constraints on redshift space distortions (RSD) and primordial non Gaussianities (PNG) For this purpose, we consider a pair of optimistic samples (with large bias differences and number densities) and the DES Year 3 (Y3) lens samples. We find that the constraints on RSD can be improved a factor of five at low redshift with respect to a single tracer, and the constraints on PNG can be improved more than a factor three. We also test the impact of including CMB lensing cross correlations in our analysis, in which we keep the cosmology fixed, finding it mainly improves the galaxy bias constraints. Last, we define and optimize a magnitude limited galaxy sample to be used for the galaxy clustering measurements in the DES Y3 analysis, in combination with galaxy galaxy lensing. We rely on Fisher forecasts, and we test how these change given the variations obtained for the number density and estimated redshift uncertainty for a set of magnitude cuts. We also characterize the impact of redshift binning choices in our cosmological constraints for this sample and the other DES Y3 lens sample: redmagic. Finally, our forecasts show that we can potentially obtain 15\ tighter constraints with this magnitude limited sample, compared to redmagic.
A Longitudinal Study of Cognition, Proton MR Spectroscopy and Synaptic and Neuronal Pathology in Aging Wild type and AbPPswe PS1dE9 Mice
Venue: PloS one
Year: 2013

Proton magnetic resonance spectroscopy (1H MRS) is a valuable tool in Alzheimer's disease research, investigating the functional integrity of the brain. The present longitudinal study set out to characterize the neurochemical profile of the hippocampus, measured by single voxel 1H MRS at 7 Tesla, in the brains of AbPPSswe PS1dE9 and wild type mice at 8 and 12 months of age. Furthermore, we wanted to determine whether alterations in hippocampal metabolite levels coincided with behavioral changes, cognitive decline and neuropathological features, to gain a better understanding of the underlying neurodegenerative processes. Moreover, correlation analyses were performed in the 12 month old AbPP PS1 animals with the hippocampal amyloid b deposition, TBS T soluble Ab levels and high molecular weight Ab aggregate levels to gain a better understanding of the possible involvement of Ab in neurochemical and behavioral changes, cognitive decline and neuropathological features in AbPP PS1 transgenic mice. Our results show that at 8 months of age AbPPswe PS1dE9 mice display behavioral and cognitive changes compared to age matched wild type mice, as determined in the open field and the (reverse) Morris water maze. However, there were no variations in hippocampal metabolite levels at this age. AbPP PS1 mice at 12 months of age display more severe behavioral and cognitive impairment, which coincided with alterations in hippocampal metabolite levels that suggest reduced neuronal integrity. Furthermore, correlation analyses suggest a possible role of Ab in inflammatory processes, synaptic dysfunction and impaired neurogenesis.
Building University Industry Co Innovation Networks in Transnational Innovation Ecosystems: Towards a Transdisciplinary Approach of Integrating Social Sciences and Artificial Intelligence
Venue: Sustainability
Year: 2019

This paper presents a potential solution to fill a gap in both research and practice that there are few interactions between transnational industry cooperation (TIC) and transnational university cooperation (TUC) in transnational innovation ecosystems. To strengthen the synergies between TIC and TUC for innovation, the first step is to match suitable industrial firms from two countries for collaboration through their common connections to transnational university/academic partnerships. Our proposed matching solution is based on the integration of social science theories and specific artificial intelligence (AI) techniques. While the insights of social sciences, e.g. innovation studies and social network theory, have potential to answer the question of why TIC and TUC should be looked at as synergetic entities with elaborated conceptualization, the method of machine learning, as one specific technic off AI, can help answer the question of how to realize that synergy. On the way towards a transdisciplinary approach to TIC and TUC synergy building, or creating transnational university industry co innovation networks, the paper takes an initial step by examining what the supports and gaps of existing studies on the topic are, and using the context of EU China science, technology and innovation cooperation as a testbed. This is followed by the introduction of our proposed approach and our suggestions for future research.
Pragmatics in acquisition*
Venue: Journal of Child Language
Year: 2014

Recent research has highlighted several areas where pragmatics plays a central role in the process of acquiring a first language. In talking with their children, adults display their uses of language in each context, and offer extensive feedback on form, meaning, and usage, within their conversational exchanges. These interactions depend critically on joint attention, physical co presence, and conversational co presence essential factors that help children assign meanings, establish reference, and add to common ground. For young children, getting their meaning across also depends on realizing language is conventional, that words contrast in meaning, and that they need to observe Grice's cooperative principle in conversation. Adults make use of the same pragmatic principles as they solicit repairs to what children say, and thereby offer feedback on both what the language is and how to use it.
Tingkat Pengetahuan Berhubungan dengan Sikap Cuci Tangan Bersih Pakai Sabun Sebelum dan Setelah Makan pada Siswa SDN Ngebel Tamantirta, Kasihan, Bantul, Yogyakarta
Year: 2016

Hands are the principal means of germs transmitting that causing diseases. Due to less of hand washing habits, children become the highest sufferers of diarrhea and respiratory diseases, and its can end in death. Soaps have been reached to almost all of houses in Indonesia, but only about 3% that used soap every year. Approximatley the causes of died in 100,000 children in Indonesia were diarrhea, mostly in aged 5 14 years. Indonesia's infant mortality rate was 32 per 1,000 live births. The mortality rate of nearly 19% due to diarrhea. Indonesian people's behavior against five important time of handwashing with soap can be influenced by the level of knowledge, such a condition is evident in students SDN Ngebel Tamantirta, Kasihan, Bantul, Yogyakarta. The purpose of study was to determine the relationship between knowledge level of hand washing with soap attitudes before and after meals on student at SD N Ngebel Tamantirta, Kasihan, Bantul, Yogyakarta. This study was inferential with cross sectional design. The respondents were all students in grade 4, 5, and 6 SDN Ngebel Tamantirta Poor Bantul Yogyakarta. Samples included 96 people. Data were taken using a questionnaire. In conclusion, there was a correlation between knowledge level of hand washing with soap attitudes before and after meals on student at SD N Ngebel Tamantirta, Kasihan, Bantul, Yogyakarta.
Dependency Parsing for Spoken Dialog Systems
Venue: EMNLP
Year: 2019

Dependency parsing of conversational input can play an important role in language understanding for dialog systems by identifying the relationships between entities extracted from user utterances. Additionally, effective dependency parsing can elucidate differences in language structure and usage for discourse analysis of human human versus human machine dialogs. However, models trained on datasets based on news articles and web data do not perform well on spoken human machine dialog, and currently available annotation schemes do not adapt well to dialog data. Therefore, we propose the Spoken Conversation Universal Dependencies (SCUD) annotation scheme that extends the Universal Dependencies (UD) (Nivre et al. 2016) guidelines to spoken human machine dialogs. We also provide ConvBank, a conversation dataset between humans and an open domain conversational dialog system with SCUD annotation. Finally, to demonstrate the utility of the dataset, we train a dependency parser on the ConvBank dataset. We demonstrate that by pre training a dependency parser on a set of larger public datasets and fine tuning on ConvBank data, we achieved the best result, 85.05% unlabeled and 77.82% labeled attachment accuracy.
The Influence of the Microstructure and Morphology of CeO2 Buffer Layer on the Properties of YBCO Films PLD Grown on Ni Tape
Year: 2014

YBa2Cu3O7 d films were deposited on CeO2 buffered nickel substrates, with different buffer thickness. Full width at half maximum of rocking curve, Do, of CeO2 and yttrium barium copper oxide (YBCO) as well as the critical temperature, Tc, of YBCO were shown to be strongly dependent on buffer thickness. They behave similarly but not proportional to the buffer thickness increase. This and the fact that Do vs. buffer thickness and Tc vs. buffer thickness for YBCO behave similar with RMS roughness vs. thickness of CeO2 indicates that the surface peculiarity of buffers is responsible for YBCO properties. More precisely, the surface of CeO2 films prepared by the chemical solution route based on propionic acid is prone to agglomerate (de wet) and the degree of agglomeration depends in an intricate way on buffer thickness. We showed that nor RMS roughness neither (00 l) texture degree can define alone the surface suitable for c axis YBCO nucleation. The {111} faceted grains (even in the case of high (00 l) texture) and other defects generated by agglomeration supply a low fraction of (00 l) flat terminations of buffer that affect the nucleation of c axis oriented YBCO phase. Moreover, the thermal instability of the surface morphology of CeO2 buffers (further development of de wetting process, {111} faceted grains, etc. during superconducting layer deposition) influence the quality of YBCO films.
Writing the doctoral thesis differently
Year: 2019

Writing a doctoral thesis is a testament to years of anxiety, excitement, confusion, terror and passion. A thesis is, however, much more than just an output of learning. It is a formative process through which a doctoral student learns what it means to be a researcher. The doctoral thesis as a form of academic writing has, however, received scant attention in organisational studies. My decision to write my thesis differently inspired me to think deeply about the conventions and procedures of doctoral writing. How is it that doctoral students write? What conventions govern them? And how could doctoral writing be done differently to expand the boundaries of thought in management? In this article, I give an autoethnographic account of how I wrote my thesis differently to provide the groundwork for doctoral students to reconsider the conventional approach to doctoral writing. Ultimately, I offer guidance and points of reflection for how doctoral students and their supervisors might break with writing conventions and contribute to their learning as emerging management researchers through writing the doctoral thesis differently.
A spectral spatial SVM based multi layer learning algorithm for hyperspectral image classification
Year: 2018

Conventional Markov random field (MRF) or Graph cut (GC) based support vector machine (SVM) methods for hyperspectral image (HSI) classification use MRF or GC to adjust spectral based SVM results to increase the spatial consistency in an unsupervised way, thus, the pixels on the border and small sized regions may be misclassified. In this letter, we propose a new framework of spectral spatial SVM based multi layer learning algorithm (SSMLL) for HSI classification. In the first layer of SSMLL, the spectral based SVM is adopted to process the original HSI datasets; the nonlinear mapping is used to scale the first layer output and enhance the nonlinear structure in the second layer; in the last layer, the spatial information is incorporated into the SVM to obtain the final classification results in a supervised way. Experimental results show that the proposed SSMLL framework provides superior classification accuracy when compared to several state of the art spectral spatial SVM based algorithms.
Corrigendum to "The effective chiral Lagrangian for a light dynamical "Higgs Particle" " [Phys. Lett. B 722 (2013) 330 335]
Year: 2013

can be reduced to a combination of P6(h) P18(h) and P21(h) P23(h) respectively, plus a term that can be absorbed in the redefinition of the couplings of the gauge bosons and h, plus a term containing a dependence on the Yukawa couplings. When fermion masses are considered, these operators are redundant; otherwise they are independent and must be taken into consideration. We profit from this erratum to point out another fact, although it has no impact on the basis. The equations of motion for the gauge fields and the Dirac equation in the section Massive fermions: DmV 0 must be substituted by DWmn j i g 4 v2 Tr[Vns j]FC (h) g 2 Q Lgns j Q L, Bmn i g 4 v2 Tr[TVn ]FC (h) g' i=L,R Q ignhi Q i,
Person recognition across multi session and multi exemplar images using ensemble of classifiers
Venue: International Conference on Digital Image Processing
Year: 2021

Person recognition over time is a bit challenging task as compared to re identification in multi camera environment. Usually, people appear after certain time period at public places like airports, carrying accessories and changing of clothes etc. In this paper, we proposed a newer recognition framework using two types of images i.e. whole and upper body silhouette. A customized version of DeepLabv3 is used for human body semantic segmentation. The Generic Fourier Descriptor (GFD) based feature set is fed to One Vs Rest schema in ensemble of K Nearest Neighbor (KNN) and Random Forest (RF) classifiers. The experiments are carried out on Front View Gait (FVG) dataset recorded in year 2017 and 2018 respectively. An overall recognition accuracy of more than 93% is noted using both classifiers on whole body human silhouette images. On the other hand, upper half human silhouette obtained recognition accuracy of more than 91% and 88% using RF and KNN respectively. Code is available at https:/git.io/JtfMY
Total Variation Regularized Low Rank Matrix Factorization for Hyperspectral Image Restoration
Venue: IEEE Transactions on Geoscience and Remote Sensing
Year: 2016

In this paper, we present a spatial spectral hyperspectral image (HSI) mixed noise removal method named total variation (TV) regularized low rank matrix factorization (LRTV) In general, HSIs are not only assumed to lie in a low rank subspace from the spectral perspective but also assumed to be piecewise smooth in the spatial dimension. The proposed method integrates the nuclear norm, TV regularization, and L1 norm together in a unified framework. The nuclear norm is used to exploit the spectral low rank property, and the TV regularization is adopted to explore the spatial piecewise smooth structure of the HSI. At the same time, the sparse noise, which includes stripes, impulse noise, and dead pixels, is detected by the L1 norm regularization. To tradeoff the nuclear norm and TV regularization and to further remove the Gaussian noise of the HSI, we also restrict the rank of the clean image to be no larger than the number of endmembers. A number of experiments were conducted in both simulated and real data conditions to illustrate the performance of the proposed LRTV method for HSI restoration.
Network Energy Efficient Mobile Edge Computing with Reliability Guarantees
Venue: 2019 IEEE Global Communications Conference (GLOBECOM)
Year: 2019

This paper proposes a novel algorithmic solution for dynamic computation offloading, aimed at reducing the energy consumption of a mobile network endowed with multi access edge computing. The dynamic evolution of the system is modeled through three queues: a local queue at the user side, a computation queue at the edge server, and a queue of results at the network access point. The optimization problem is cast as the minimization of the long term average energy consumption of the whole system, comprising user devices, servers, and access points. Quality of service constraints for end users are imposed in terms of probability that the \textit{sum of the queues} exceeds a given threshold. A suitable weighting parameter can be tuned to drive the system toward a user centric, a network centric, or a hybrid solution. Exploiting stochastic optimization tools, the problem is solved thanks to a dynamic optimization algorithm, based on the solution of deterministic convex problems in each time slot. The algorithm does not assume any knowledge on the task input and output random sizes and the radio channel statistics. Several numerical results illustrate the advantages of the proposed method.
Development of a Predictive Limited Sampling Strategy for Estimation of Mycophenolic Acid Area Under the Concentration Time Curve in Patients Receiving Concomitant Sirolimus or Cyclosporine
Venue: Therapeutic drug monitoring
Year: 2008

Limited sampling strategies for estimation of the area under the concentration time curve (AUC) for mycophenolic acid (MPA) co administered with sirolimus (SRL) have not been previously evaluated. The authors developed and validated 68 regression models for estimation of MPA AUC for two groups of patients, one with concomitant SRL (n 24) and the second with concomitant cyclosporine (n=14) using various combinations of time points between 0 and 4 hours after drug administration. To provide as robust a model as possible, a dataset splitting method similar to a bootstrap was used. In this method, the dataset was randomly split in half 100 times. Each time, one half of the data was used to estimate the equation coefficients, and the other half was used to test and validate the models. Final models were obtained by calculating the median values of the coefficients. Substantial differences were found in the pharmacokinetics of MPA between these groups. The mean MPA AUC as well as the standard deviation was much greater in the SRL group, 56.4 23.5 mg*h/L, compared with 30.4 11.0 mg*h/L in the cyclosporine group (P 0.001) Mean maximum concentration was also greater in the SRL group: 16.4 7.7 mg/L versus 11.7 7.1mg/L (P 0.005) The second absorption peak in the pharmacokinetic profile, presumed to result from enterohepatic recycling of glucuronide MPA, was observed in 70% of the profiles in the SRL group and in 35% of profiles from the cyclosporine group. Substantial differences in the predictive performance of the regression models, based on the same time points, were observed between the two groups. The best model for the SRL group was based on 0 (trough) and 40 minutes and 4 hour time points with R2, root mean squared error, and predictive performance values of 0.82, 10.0, and 78% respectively. In the cyclosporine group, the best model was 0 and 40 minutes and 2 hours, with R2, RMSE, and predictive performance values of 0.86, 4.1, and 83% respectively. The model with 2 hours as the last time point is also recommended for the SRL group for practical reasons, with the above parameters of 0.77, 11.3, and 69% respectively.
AN ANALYSIS ON THE FORMATION REASON AND COUNTERMEASURE OF THE FEMALE COLLEGE STUDENTS'DIFFICULT EMPLOYMENT POSITION UNDER UNDER NEW CIRCUMSTANCES
Year: 2012

Nowadays,under in the gradually austere situation of the colleges students' employment circumstances,the discrimination and the troublesome problem in employment that the female college students' encounters became disharmonious phenomenon in structuring harmonious society,obtained society's universal attention.Solve female college students' difficult employment position need to mobilize stratification plane strengths and so on society,law,university,establish safeguard employment of long effect mechanism.We also hope that the female college students unearth their superiority,promote employment strength,square point of view,face competition.