nils-herrmann/clean_scirepeval huggingface dataset:
Uncertainty quantification of the effects of biotic interactions on community dynamics from nonlinear time series data
Venue: Journal of The Royal Society Interface
Year: 2018

Biotic interactions are expected to play a major role in shaping the dynamics of ecological systems. Yet, quantifying the effects of biotic interactions has been challenging due to a lack of appropriate methods to extract accurate measurements of interaction parameters from experimental data. One of the main limitations of existing methods is that the parameters inferred from noisy, sparsely sampled, nonlinear data are seldom uniquely identifiable. That is, many different parameters can be compatible with the same dataset and can generalize to independent data equally well. Hence, it is difficult to justify conclusive assertions about the effect of biotic interactions without information about their associated uncertainty. Here, we develop an ensemble method based on model averaging to quantify the uncertainty associated with the effect of biotic interactions on community dynamics from non equilibrium ecological time series data. Our method is able to detect the most informative time intervals for each biotic interaction within a multivariate time series and can be easily adapted to different regression schemes. Overall, this novel approach can be used to associate a time dependent uncertainty with the effect of biotic interactions. Moreover, because we quantify uncertainty with minimal assumptions about the data generating process, our approach can be applied to any data for which interactions among variables strongly affect the overall dynamics of the system.
Human Development Research Paper 2009/46 The Moving Middle: Migration, Place Premiums and Human Development in Bolivia
Year: 2009

Over half of Bolivian heads of household are lifetime migrants. This paper looks at the long term impact of internal migration over human development in Bolivia. Three issues frame these effects. First, twenty five years of rural to urban migration have transformed the demographic profile of Bolivian society. The new middle third is younger, more bilingual and better educated, with more access to social services than in the past. The poorest of the poor, however, did not migrate to the extent of the non poor. Second, urban workers make approximately four times as much wages as identical workers in rural areas, controlling for age, ethnicity, and years of schooling. Two caveats dampen this place premium effect: schooling quality and informal insurance mechanisms that make migration more costly. Third, increases in human development can be associated to an "urbanization dividend" that made social services more accessible to first and second generation migrants over a twenty five year period. Future increases in human development, however, are likely to depend on providing quality services and expanding socials services to the rural poor, rather on gains from urbanization. The key policy challenges of the future include both an expansion of services to the poorest of the poor in rural areas and breaking down discrimination barriers against women and indigenous people in urban labor markets.  Migration, human development, poverty, employment, schooling.  The findings, interpretations and conclusions are strictly those of the authors and do not necessarily represent the views of UNDP or United Nations Member States. Moreover, the data may not be consistent with that presented in Human Development Reports.
Ontology Population and Alignment for the Legal Domain: YAGO, Wikipedia and LKIF
Venue: SEMWEB
Year: 2017

We present a methodology and framework to align ontologies through annotation of texts, and we show how this methodology applies successfully to the legal domain. This method reduces the difficulty of aligning ontologies, because annotators are asked to associate two labels from different inventories to a concrete example, which requires a simple judgment. In a second phase, those correspondences are consolidated into a proper alignment. The resulting alignment is a partial connection between diverse ontologies. By annotating judgments of the European Court of Human Rights, we have aligned an ontology of the legal domain, LKIF, to YAGO, we have thus populated LKIF in order to train a legal Named Entity Recognizer and Classifier with examples from the Wikipedia that are trivially mapped to LKIF classes. The resulting resources and the best practices we defined supported a step towards automation in legal informatics.
Postharvest application of thiol compounds affects surface browning and antioxidant activity of fresh cut potatoes.
Venue: Journal of food biochemistry
Year: 2020

The aim of this study was to compare the effects of sodium metabisulphite and the thiol compounds, glutathione (GSH) L cysteine (CYS) and N acetylcysteine (NAC) on the enzymatic browning, antioxidant activities, total phenolic, and ascorbic acid content of potatoes after 1, 24, and 48 hr. Three different concentrations (0.5% 1.0% and 2.0% of each thiol compound were tested. While sulphite solution inhibited polyphenol oxidase as expected, NAC and CYS also decreased its activity. CYS treated samples exhibited the highest residual thiol content, while the amount of residual thiol in GSH treated samples was the lowest. The 2.0% NAC and 2.0% CYS solutions were the most effective at increasing antioxidant activity and ascorbic acid content; however, the results of total phenolic content assays were complicated. In summary, solutions containing 2.0% NAC, 1.0% CYS, and 2.0% CYS prevented enzymatic browning and increased the residual thiol content, ascorbic acid, and antioxidant activities of fresh cut potatoes significantly, but GSH did not significantly inhibit browning.  Fresh cut potatoes are susceptible to enzymatic browning, which significantly reduces their commercial value. In literature, there have been several methods to protect the enzymatic browning of fruits and vegetables. Among these methods, thiols are good inhibitors of enzymatic browning. So, GSH, CYS, and NAC were used in this study. The outcomes of current work may help to inhibit polyphenol oxidase activity and increase the ascorbic acid content, residual thiol content, and antioxidant activity of fresh cut potatoes. Both CYS and NAC may be useful alternatives to sulphite anti browning agents, which may have adverse health effects.
World Bank Partnerships and the Promise of Democratic Governance
Year: 2016

The World Bank promotes public private partnerships as vehicles for democratizing environmental governance. This article presents an overview of their constitution in the World Bank, including what the Bank as an organization identified as their promise, and investigates what its partnerships for biodiversity conservation achieved. The article focuses on the institutional design of partnerships' governance structures, and assesses their democratic quality based on their potential to enable inclusion and empowerment of stakeholders. It examines nine global biodiversity partnerships between the World Bank and non state actors from 1992 to 2008 and analyses the extent to which they have fulfilled the principled expectations expressed by the Bank. I find that partnerships have been organized through institutional arrangements that fail to promote inclusiveness and empowerment, which are minimum normative inputs for democratic decision making in natural resource management. This suggests that World Bank partnerships are not sufficiently well poised to fulfil the democratic promise.
The economics of quality in the specialty coffee industry: insights from the Cup of Excellence auction programs
Year: 2013

This study estimates price determinants for specialty green coffee auctions using records from the 2004 2010 Cup of Excellence programs hosted by the Alliance for Coffee Excellence. While some literature on coffee has focused on certifications and sustainability labels, the discussion of price determinants has been limited. This article replicates one of the first publications on price determinants and formulates a new model to more accurately describe the market. We include the necessary additional variables and estimate the model using a truncated maximum likelihood estimation technique. While sensory quality has a strong effect on price, the highest premiums stem from obtaining a top rank compared to other coffees from the same country, and North American buyers are more responsive to sensory quality than buyers in Asian and European markets.
Analysis of Metadata Schemas for Children's Libraries
Year: 2011

The purpose of this study is to evaluate two metadata schemas, AACR2+ and the International Children's Digital Library's metadata schema, in light of children's information seeking behavior for book selection. While previous studies focus on the development of child friendly interfaces, few of these studies discuss a metadata schema for children's libraries. Given that effective information retrieval is based on well constructed information organization, this study's significance is its greater emphasis on information organization as a relevant factor than in previous studies. The methodology for this study consists of three parts: a meta analysis of relevant research on children's information seeking behaviors for book choices, a crosswalk of the metadata schemas, and a comparison of two data sets from the previous stages. The study finds that ICDL's metadata schema tends to better reflect children's unique information seeking behaviors for book choices as independent metadata elements than standard library cataloging does. Standard library cataloging tends to describe information reflecting children's unique information seeking behaviors in a note area rather than describing in independent metadata elements. Therefore, by having independent and relevant metadata elements regarding the unique characteristics of children's book choices, ICDL's metadata schema provides more access points in a browse search system.
A state of the art review of smart tourism research
Year: 2020

Using a mixed method approach combining qualitative and quantitative review techniques, this study analyzed 86 articles to identify state of the art thematic research trends and articulate knowledge domains in the smart tourism research. In particular, the thematic analysis identified 11 themes from the current smart tourism research. Results of the co citation analysis identified and visualized four knowledge domains as the theoretical underpinning of existing smart tourism literature, thereby supplementing, and complementing the findings of the thematic analysis. The constituents of each theme and knowledge domain were discussed to reveal critical gaps and suggest future research directions.
Reason Based Choice Correspondences
Venue: Math. Soc. Sci.
Year: 2009

A reason based choice correspondence rationalizes choice behaviour in terms of a two stage choice procedure. Given a feasible set S the individual eliminates from it all of the dominated alternatives according to her fixed (not necessarily complete) strict preference relation, in the first step. In the second step, first she constructs for each maximal alternative identified in the first step its lower contour set (i.e. the set of alternatives which are dominated by it in S and then she eliminates from the maximal set all of those alternatives so that the following justification holds: there exists another maximal alternative whose lower contour set strictly contains that of another maximal alternative. This procedural model captures the basic idea behind the experimental finding known as "attraction effect" We study the rationalizability of reason based choice correspondences axiomatically. We relate our choice consistency conditions to standard consistency proprieties. Our characterization result offers testable restrictions on this `choice anomaly' for large (but finite) set of alternatives.
GIS based landslide susceptibility modelling: a comparative assessment of kernel logistic regression, Naive Bayes tree, and alternating decision tree models
Year: 2017

The main purpose of this paper is to explore some potential applications of sophisticated machine learning techniques such as the kernel logistic regression, Naive Bayes tree and alternating decision tree models for landslide susceptibility analysis at Taibai county (China) Initially, a landslide inventory map containing the information of 212 historical landslide locations was prepared. Seventy percentage (148) of landslides were randomly selected for training models and the remaining were used for validation. Additionally, 12 landslide conditioning factors were considered and the thematic layers were prepared in GIS. Subsequently, these three models were applied to build landslide susceptibility maps. The performances of the models were compared using the receive operating characteristic curves, kappa index, and statistical evaluation measures. The results show that the KLR model has the highest AUC values of 0.910 and 0.936 for training and validation datasets, respectively. The KLR model also has the highest degree of goodness of fits (84.5% for the training dataset. The NBTree model has the highest goodness of fits (91.4% for the validation dataset. However, the KLR model has the preferable balance performance for both the training and validation process. The results of this study demonstrate the benefit of selecting the optimal machine learning techniques in landslide susceptibility mapping.
A case of gliosarcoma in a child with neurofibromatosis type 1
Year: 2020

Gliosarcoma (GS) is a rarely seen form of glioblastoma. These tumors are mostly seen in males older than 60 years of age. It is extremely rare in pediatric central nervous system (CNS) tumors. In this case report, we present a 3 year old boy with a giant gliosarcoma. Magnetic resonance (MR) imaging and histopathologic findings are discussed. A 3 year old boy with a clinically diagnosed NF 1 was admitted to the emergency department with a complaint of intractable vomiting. Magnetic resonance imaging (MRI) of the brain was suggestive of a large lobulated mass lesion in the left parietal lobe extending to the vertex and slightly compressing the left lateral ventricle. The final histopathologic diagnosis of the tumor was considered as gliosarcoma. To our knowledge, this case constitutes the first youngest case with neurofibromatosis type 1 reported in the literature in all pediatric cases of GS.
Prenatal exposure to maternal depression and cortisol influences infant temperament.
Venue: Journal of the American Academy of Child and Adolescent Psychiatry
Year: 2007

Accumulating evidence indicates that prenatal maternal and fetal processes can have a lasting influence on infant and child development. Results from animal models indicate that prenatal exposure to maternal stress and stress hormones has lasting consequences for development of the offspring. Few prospective studies of human pregnancy have examined the consequences of prenatal exposure to stress and stress hormones.  In this study the effects of prenatal maternal psychosocial (anxiety, depression, and perceived stress) and endocrine (cortisol) indicators of stress on infant temperament were examined in a sample of 247 full term infants. Maternal salivary cortisol and psychological state were evaluated at 18 20, 24 26, and 30 32 weeks of gestation and at 2 months postpartum. Infant temperament was assessed with a measure of negative reactivity (the fear subscale of the Infant Temperament Questionnaire) at 2 months of age.  Elevated maternal cortisol at 30 32 weeks of gestation, but not earlier in pregnancy, was significantly associated with greater maternal report of infant negative reactivity. Prenatal maternal anxiety and depression additionally predicted infant temperament. The associations between maternal cortisol and maternal depression remained after controlling for postnatal maternal psychological state.  These data suggest that prenatal exposure to maternal stress has consequences for the development of infant temperament.
An adaptive global local approach for phase field modeling of anisotropic brittle fracture
Year: 2020

This work addresses an efficient Global Local approach supplemented with predictor corrector adaptivity applied to anisotropic phase field brittle fracture. The phase field formulation is used to resolve the sharp crack surface topology on the anisotropic/non uniform local state in the regularized concept. To resolve the crack phase field by a given single preferred direction, second order structural tensors are imposed to both the bulk and crack surface density functions Accordingly, a split in tension and compression modes in anisotropic materials is considered. A Global Local formulation is proposed, in which the full displacement/phase field problem is solved on a lower (local) scale, while dealing with a purely linear elastic problem on an upper (global) scale. Robin type boundary conditions are introduced to relax the stiff local response at the global scale and enhancing its stabilization. Another important aspect of this contribution is the development of an adaptive Global Local approach, where a predictor corrector scheme is designed in which the local domains are dynamically updated during the computation. To cope with different finite element discretizations at the interface between the two nested scales, a non matching dual mortar method is formulated. Hence, more regularity is achieved on the interface. Several numerical results substantiate our developments.
Kajian faktor risiko belia terlibat dengan penyalahgunaan bahan di kawasan bandar di Negeri Johor
Year: 2013

Tujuan kajian ini adalah untuk mengkaji perbandingan faktor risiko demografi, internal dan eksternal dalam kalangan belia yang terlibat dengan penyalahgunaan bahan di kawasan bandar di Negeri Johor. Kajian ini amat penting untuk dilakukan kerana akan memberi manfaat yang besar terhadap pihak pihak yang berkepentingan seperti Agensi Anti Dadah Kebangsaan, masyarakat setempat dan negara. Kajian ini telah menggunakan software Winstep dan Rasch Model dalam membuat perbandingan faktor faktor risiko penyalahgunaan bahan. Data yang diperolehi dianalisis dengan menggunakan SPSS. Dari segi reka bentuk kajian, penyelidikan ini menggunakan kaedah tinjauan yang dilakukan melalui soal selidik yang diedarkan kepada 295 orang pelatih di Rumah Komuniti Penyayang di negeri Johor.Lokasi kajian pula hanya melibatkan di Daerah Pontian, Batu Pahat, Kota Tinggi, Mersing, Johor Bahru, Segamat dan Kluang dan keatas respondan yang berasal dari bandar di Rumah Komuniti Penyayang. Kesahan dan keboleh percayaan instrument telah diuji dan dianalisi melalui kajian rintis yang telah dilakukan di Rumah Komuniti Penyayang Daerah Muar, Johor.Hasil kajian telah menunjukkan faktor jantina lelaki berumur diantara 19 39 tahun yang bekerja sebagai buruh am, berpendidikan sehingga SPM dan bujang adalah faktor risiko demografi yang paling mempengaruhi belia dikawasan bandar diseluruh negeri Johor terhadap penyalahgunaan bahan.Manakala faktor risiko internal dan eksternal menunjukkan faktor rakan sebaya meupakan faktor risiko yang utama terhadap penyalahgunaan bahan dikawasan bandar. Data yang diperolehi dari jawapan soal selidik akan dianalisis dan dibuat laporan untuk menghasilkan dapatan yang berguna untuk semua pihak.Pengkaji mencadangkan agar kajian lanjutan diperluaskan kepada responden bukan sahaja di Rumah Komuniti Penyayang, bahkan kepada pelatih pelatih di Pusat Serenti, penjara dan sebagainya.Kajian lanjutan juga boleh diperluaskan bukan sahaja di negeri Johor, bahkan di seluruh Malaysia.
Neural Prescribed Performance Control for Uncertain Marine Surface Vessels without Accurate Initial Errors
Year: 2017

This paper deals with the problems concerned with the trajectory tracking control with prescribed performance for marine surface vessels without velocity measurements in uncertain dynamical environments, in the presence of parametric uncertainties, unknown disturbances, and unknown dead zone. First, only the ship position and heading measurements are available and a high gain observer is used to estimate the unmeasurable velocities. Second, by utilizing the prescribed performance control, the prescribed tracking control performance can be ensured, while the requirement for the initial error is removed via the preprocessing. At last, based on neural network approximation in combination with backstepping and Lyapunov synthesis, a robust adaptive neural control scheme is developed to handle the uncertainties and input dead zone characteristics. Under the designed adaptive controller for marine surface vessels, all the signals in the closed loop system are semiglobally uniformly ultimately bounded (SGUUB) and the prescribed transient and steady tracking control performance is guaranteed. Simulation studies are performed to demonstrate the effectiveness of the proposed method.
Robust vehicle detection in low resolution aerial imagery
Venue: Defense Commercial Sensing
Year: 2010

We propose a feature based approach for vehicle detection in aerial imagery with 11.2 cm/pixel resolution. The approach is free of all constraints related to the vehicles appearance. The scale invariant feature transform (SIFT) is used to extract keypoints in the image. The local structure in the neighbouring of the SIFT keypoints is described by 128 gradient orientation based features. A Support Vector Machine is used to create a model which is able to predict if the SIFT keypoints belong to or not to car structures in the image. The collection of SIFT keypoints with car label are clustered in the geometric space into subsets and each subset is associated to one car. This clustering is based on the Affinity Propagation algorithm modified to take into account specific spatial constraint related to geometry of cars at the given resolution.
Big data science: A literature review of nursing research exemplars.
Venue: Nursing outlook
Year: 2017

Big data and cutting edge analytic methods in nursing research challenge nurse scientists to extend the data sources and analytic methods used for discovering and translating knowledge.  The purpose of this study was to identify, analyze, and synthesize exemplars of big data nursing research applied to practice and disseminated in key nursing informatics, general biomedical informatics, and nursing research journals.  A literature review of studies published between 2009 and 2015. There were 650 journal articles identified in 17 key nursing informatics, general biomedical informatics, and nursing research journals in the Web of Science database. After screening for inclusion and exclusion criteria, 17 studies published in 18 articles were identified as big data nursing research applied to practice.  Nurses clearly are beginning to conduct big data research applied to practice. These studies represent multiple data sources and settings. Although numerous analytic methods were used, the fundamental issue remains to define the types of analyses consistent with big data analytic methods.  There are needs to increase the visibility of big data and data science research conducted by nurse scientists, further examine the use of state of the science in data analytics, and continue to expand the availability and use of a variety of scientific, governmental, and industry data resources. A major implication of this literature review is whether nursing faculty and preparation of future scientists (PhD programs) are prepared for big data and data science.