nils-herrmann/clean_scirepeval huggingface dataset:
Exploiting correlation and budget constraints in Bayesian multi armed bandit optimization
Year: 2013

We address the problem of finding the maximizer of a nonlinear smooth function, that can only be evaluated point wise, subject to constraints on the number of permitted function evaluations. This problem is also known as fixed budget best arm identification in the multi armed bandit literature. We introduce a Bayesian approach for this problem and show that it empirically outperforms both the existing frequentist counterpart and other Bayesian optimization methods. The Bayesian approach places emphasis on detailed modelling, including the modelling of correlations among the arms. As a result, it can perform well in situations where the number of arms is much larger than the number of allowed function evaluation, whereas the frequentist counterpart is inapplicable. This feature enables us to develop and deploy practical applications, such as automatic machine learning toolboxes. The paper presents comprehensive comparisons of the proposed approach, Thompson sampling, classical Bayesian optimization techniques, more recent Bayesian bandit approaches, and state of the art best arm identification methods. This is the first comparison of many of these methods in the literature and allows us to examine the relative merits of their different features.
Cholangiocarcinoma 2020: the next horizon in mechanisms and management
Venue: Nature Reviews Gastroenterology Hepatology
Year: 2020

Cholangiocarcinoma (CCA) includes a cluster of highly heterogeneous biliary malignant tumours that can arise at any point of the biliary tree. Their incidence is increasing globally, currently accounting for ~15% of all primary liver cancers and ~3% of gastrointestinal malignancies. The silent presentation of these tumours combined with their highly aggressive nature and refractoriness to chemotherapy contribute to their alarming mortality, representing ~2% of all cancer related deaths worldwide yearly. The current diagnosis of CCA by non invasive approaches is not accurate enough, and histological confirmation is necessary. Furthermore, the high heterogeneity of CCAs at the genomic, epigenetic and molecular levels severely compromises the efficacy of the available therapies. In the past decade, increasing efforts have been made to understand the complexity of these tumours and to develop new diagnostic tools and therapies that might help to improve patient outcomes. In this expert Consensus Statement, which is endorsed by the European Network for the Study of Cholangiocarcinoma, we aim to summarize and critically discuss the latest advances in CCA, mostly focusing on classification, cells of origin, genetic and epigenetic abnormalities, molecular alterations, biomarker discovery and treatments. Furthermore, the horizon of CCA for the next decade from 2020 onwards is highlighted. Cholangiocarcinoma (CCA) comprises heterogeneous biliary malignant tumours, and their incidence is increasing worldwide. This expert Consensus Statement, endorsed by the ENS CCA, summarizes the latest advances in CCA, including classification, genetics and treatment, and provides recommendations for CCA management and priorities across basic, translational and clinical research.
Estereotipos: Constitucion de la imagen de la sociedad china a traves de los medios de masas.
Year: 2013

espanolPresento con este articulo una problematica que surge ante mi reflexion sobre como me ven los espanoles. Asi he realizado una investigacion para llegar a algunas conlcusiones. He utilizado la autoetnografia para partir de mis propias vivencias y recuerdos y conclusiones; y he realizado una encuesta orientativa que me sirva de evidencia para contrastar mi vision con algunos datos que puedo constatar extraidos de la encuesta. En definitiva, con este estudio se ha pretendido indagar si los ciudadanos espanoles y con acceso a internet acceden al conocimiento de la cultura China a traves de diferentes canales comunicativos, aparte de los medios tradicionales de comunicacion de masas. Y si este conocimiento de los mismos les ha permitido una mayor comprension y entendimiento, en la era de las redes sociales; les ha permitido una inclusion mas profunda en la vision de otras formas de entender el mundo fomentando el respeto y la valoracion del otro. Estamos en un momento historico de la Humanidad donde el acceso universal a la informacion y al conocimiento puede permitir una construccion de un concepto nuevo de ciudadania global donde los cambios sociales, politicos y culturales tengan lugar en un mismo espacio y en un mismo momento a nivel mundial. EnglishThe article presents a problematic that appears after my reflection on how the Spaniards look at a Chinese woman that I am So I have done some research to come to some conclusions From my own experiences I have used autoethnography as a method I have also made an indicative survey in order to take this into evidence. In short, this study has sought to investigate whether Spanish citizens with internet access can know Chinese culture through different mass media new and traditional And if the knowledge of them has allowed a greater comprehension of other ways of understanding the world y fostering respect and appreciation for others We are at a historic moment of humanity where universal access to information and knowledge may allow construction of a new concept of global citizenship where social, political and cultural changes taking place in the same space and at the same time at world.
Evaluation of antimicrobial effects of novel implant materials by testing the prevention of biofilm formation using a simple small scale medium throughput growth inhibition assay
Venue: Biofouling
Year: 2012

Staphylococcal colonization of implants is a serious complication of orthopaedic surgery. Anti infectious modification of implant surfaces may serve to prevent bacterial colonization. The authors set out to develop an in vitro test system for the analysis of prevention of biofilm formation by Staphylococcus epidermidis and Staphylococcus aureus on implant materials. Biofilm growth was monitored over 10 days on titanium disks in order to develop appropriate test parameters. Bacterial cell counts following ultrasonic treatment of the colonized samples were compared with scanning electron microscope images of the specimens. Copper ion containing surfaces (ie copper [Cu] and inter metallic Ti Cu films) were used for growth inhibition assays: Copper ion releasing specimens led to reduced bacterial numbers in biofilms and decreased bacterial persistence in the model used. The assay used represents an inexpensive and quick in vitro screen for the antibacterial effects of novel implant surface materials.
A sequential thin film deposition equipment for in situ fabricating all solid state thin film lithium batteries
Year: 2007

To improve the interfacial quality and electrochemical performance of all solid state thin film lithium batteries (TFLBs) a sequential thin film deposition equipment has been developed. This equipment consists of a dry glove box for packing TFLB and four vacuum chambers, one chamber of them for deposition lithium film anode by flash thermal evaporation, and the other three vacuum chambers for deposition of current collectors, cathode and solid electrolyte by magnetron sputtering, respectively. This equipment has been used to sequentially deposited Au current collector, TiO2 cathode, LiPON (lithium phosphorus oxynitride) solid electrolyte and metallic Li anode thin films, and to prepare a TFLB with a structural configuration of Li/LiPON/TiO2/Au via an in situ process without breaking vacuum. The results showed that the TFLB exhibited lower interface resistance and better electrochemical performance than that fabricated via an ex situ process.
Hierarchical Bayesian nonparametric models for knowledge discovery from electronic medical records
Venue: Knowl. Based Syst.
Year: 2016

Electronic Medical Record (EMR) has established itself as a valuable resource for large scale analysis of health data. A hospital EMR dataset typically consists of medical records of hospitalized patients. A medical record contains diagnostic information (diagnosis codes) procedures performed (procedure codes) and admission details. Traditional topic models, such as latent Dirichlet allocation (LDA) and hierarchical Dirichlet process (HDP) can be employed to discover disease topics from EMR data by treating patients as documents and diagnosis codes as words. This topic modeling helps to understand the constitution of patient diseases and offers a tool for better planning of treatment. In this paper, we propose a novel and flexible hierarchical Bayesian nonparametric model, the word distance dependent Chinese restaurant franchise (wddCRF) which incorporates word to word distances to discover semantically coherent disease topics. We are motivated by the fact that diagnosis codes are connected in the form of ICD 10 tree structure which presents semantic relationships between codes. We exploit a decay function to incorporate distances between words at the bottom level of wddCRF. Efficient inference is derived for the wddCRF by using MCMC technique. Furthermore, since procedure codes are often correlated with diagnosis codes, we develop the correspondence wddCRF (Corr wddCRF) to explore conditional relationships of procedure codes for a given disease pattern. Efficient collapsed Gibbs sampling is derived for the Corr wddCRF. We evaluate the proposed models on two real world medical datasets PolyVascular disease and Acute Myocardial Infarction disease. We demonstrate that the Corr wddCRF model discovers more coherent topics than the Corr HDP. We also use disease topic proportions as new features and show that using features from the Corr wddCRF outperforms the baselines on 14 days readmission prediction. Beside these, the prediction for procedure codes based on the Corr wddCRF also shows considerable accuracy.
Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning
Venue: Frontiers in Molecular Biosciences
Year: 2020

Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the "second secret of life." The fundamental biological importance and complexity of these processes require a multi faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation based multiscale approaches, experiment informed Markovian models, and network modeling of allostery and information theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well suited platform for development of data driven research strategies. Data centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.
Thirteen years secular trends reveal a dramatic drop in recommended daily physical activity in Swedish youth a smartphone effect?
Year: 2015

Regular physical activity (PA) provides a substantial health benefit for children. Monitoring physical activity would help in developing policies and guidelines to increase activity levels. Evaluation and comparison of physical activity across time have several underlying assumptions. Thus, it is fundamental to compare matching populations, and to use the same measurement technique, instrument and test protocol during similar test conditions. In a study of secular trends of pedometer determined physical activity in 7 9 year old Swedish children, physical activity increased during 2000 2006 and in another study of children aged 13 14 years reported no significant decrease in PA during 2000 2008. Could this positive finding hold true even over a longer time span in Sweden? To our knowledge, longer time spans of pedometer determined PA trends have never been published.  To explore secular trends of pedometerdetermined physical activity (PA) body mass index (BMI) the percentage to meet recommendations of daily PA and the percentage of overweight/obese from 2000 to 2006 and 2013 in second graders from the very same two schools and from 2000 to 2013 in fifth graders.  Trends between three cross sectional cohorts from five schools in 2000, and from two schools in 2006 and 2013 were analysed. Participating 2nd graders were n 2000 126 (57 girls) in 2006 84 (42 girls) and in 2013 (44 (23 girls) and 5th graders in 2000 105 (53 girls) and in 2013 38 (18 girls) During four consecutive weekdays, physical activity data were collected, height and weight measured, and BMI computed. Identical instruments and procedures were used on all three occasions. One way ANOVA Post hoc Scheffe was applied for analysis.  In 2nd grade girls a significant increase of PA from 2000 to 2006 was observed (p< 0.01) and followed by a stable level between 2006 and 2013. No significant differences between the boy's cohorts were seen. In 5th grade boys a significant decrease was observed between 2000 and 2013 with a drop in average daily PA from 16670 to 12704 (p< 0.01) In girls level of PAwas stable between 2000 and 2013. The percentage fulfilling upper endpoint for both boys (15,000 steps) and girls (12000 steps) to achieve the 60minutes of MVPA recommendation was higher in 2013 compared to 2000 for both genders in second grade, for fifth graders it dropped from 71% to 61% and from 76% to 20% between 2000 and 2013 in girls and boys respectively. Conclusion(s) Secular trends of PA differ between boys and girls. 2nd graders and 5th grade girls were largely stable whereas PA in 5th grade boys dropped by 24% between 2000 and 2013. Changing recess and leisure time habits such as smartphone use could be one of the causes.  This study, point out the possible magnitude of unlimited smartphone use during recess or leisure time on children's physical activity and the need to further study this phenomena.
Metastatic Colorectal Cancer: Review of Diagnosis and Treatment Options
Year: 2014

Colorectal cancer (CRC) is currently considered the third most common neoplasm in the world according to the World Cancer Research Fund International with 1.4 million cases diagnosed in 2012, and the second malignity as cause of death. Approximately 1/5 of patients present directly with metastatic disease (mCRC) and 30 to 50% develop metastasis after surgical treatment for initially localized disease. The aims of the current study are to review the diagnostic particularities, treatment options and clinical evolution of mCRC. Metastatic process in CRC is long and complex, involving several mechanisms, molecular pathways and cellular types. Advances in medical imaging now allow an early and accurate diagnosis of metastatic lesions no matter their location. The progress of fundamental research in CRC led to understanding the molecular basis of the metastatic process that was further translated into novel chemotherapic and biological agents, thus increasing overall survival and and progression free survival rates. Resection of liver, lung and brain metastases is crucial for survival when achievable and is more effective when completed by an oncological treatment and rigorous follow up. All patients with mCRC should be discussed by a multidisciplinary team (surgeon, oncologist, radiologist, and gastroenterologist) in order to identify the most appropriate therapeutic management.
Analysis on the Luminous Efficiency of Phosphor Conversion White Light Emitting Diode
Year: 2013

The author analyzes the luminous efficiency of the phosphor conversion white light emitting diode (LED) that consists of a blue LED chip and a yellow phosphor. A theoretical model is derived to find the relation between luminous efficiency (LE) of a white LED, wall plug efficiency (WPE) of a blue LED chip, and the phosphor absorption ratio of blue light. The presented model enables to obtain the theoretical limit of LE and the lower bound of WPE. When the efficiency model is applied to the measured results of a phosphor conversion white LED, the limit theoretical value of LE is obtained to be 261 lm/W. In addition, for LE of 88 lm/W at 350 mA, the lower bound of WPE in the blue LED chip is found to be ~34% The phosphor absorption ratio of blue light was found to have an important role in optimizing the luminous efficiency and colorimetric properties of phosphor conversion white LEDs.
The FvCYP714C2 gene plays an important role in gibberellin synthesis in the woodland strawberry
Venue: Genes genomics
Year: 2020

Fragaria vesca the woodland strawberry, is a diploid relative of the cultivated strawberry. A GA deficient mutant was found in ethyl methanesulfonate (EMS) mutagenized lines of the Fragaria vesca accession 'Yellow Wonder' Objective CYP714C2 was found to be differentially expressed using RNA seq analysis. It is necessary to identify the function of this gene.  In order to identify the function of this gene, it was cloned and transformed into Arabidopsis thaliana  The DNA sequence of CYP714C2 was found to be 1940 bp in length, with an open reading frame (ORF) of 1539 bp that is predicted to encode a protein of 512 amino acids. The hydrophilicity of this protein is low and it is unstable. The highest relative expression of FvCYP714C2 was found in the leaves, followed by the pedicels, and low expression levels were found in the other tissues examined. Constitutive expression of FvCYP714C2 significantly promoted the growth of transgenic A. thaliana plants; transgenic Arabidopsis plants grew faster and grew well than wild type Col 0 plants. GA 1+3 contents of the genetically modified Arabidopsis lines were significantly higher than that in the wild type.  We conclude that FvCYP714C2 is a gene that functions in the gibberellin biosynthesis pathway in strawberry.
As tecnologias da informacao no Brasil: um ensaio sobre processos tecnologicos no periodo de 1995 2010
Year: 2020

In this paper we will seek to reconstruct the beginning of the Brazilian internet market. For this we will start from articles published on sites of different natures, in the period of the initial 15 years of the internet market in Brazil. This news is important because it brings time honored questions about Brazilians' use of the internet, as well as the state's effort to create and control the internet market. Still, we will bring dilemmas that concerned the subjects in this period, either from the point of view of the impacts of the internet and technology on the lives of its users, or the legal devices needed to protect the subjects in their daily relationship with the internet. These data will be mobilized in the operationalization of different network theories that are in dispute in the field of sociological knowledge production, cujo os representantes sao Castells, Elias, Granovetter e Latour. Thus, through these theories, we will denature the concerns related to the use of the internet in Brazil, as well as remember that the issues that afflict us today, in fact, are old.
Non Cooperative Power Control Game in D2D Underlying Networks with Variant System Conditions
Venue: Electronics
Year: 2019

In this paper, the problem of power control using a game theoretic approach based on sigmoid cost function is studied for device to device (D2D) communications underlying cellular networks. A non cooperative game, where each D2D transmitter and a cellular user select their own transmit power level independently, is analyzed to minimize their user serving cost function and achieve a target signal to interference plus noise ratio (SINR) requirement. It is proved analytically that the Nash equilibrium point of the game exists and it is unique under certain constraints. Numerical results verify the analysis and demonstrate the effectiveness of the proposed game with variant system conditions, such as path loss exponents, target SINR, interference caused by the cellular user, pricing coefficients, and sigmoid control parameter.
Carbon storage estimation of tropical urban trees by an improved allometric model for aboveground biomass based on terrestrial laser scanning
Venue: Urban Forestry Urban Greening
Year: 2019

Current estimations of the carbon stored by urban trees are usually based on allometric models developed for natural forests. However, urban trees grow in different conditions, and their architecture might differ, thus models developed specially for urban trees are needed. With the aim of improving estimations of carbon storage and sequestration in tropical cities, we developed a model for Singapore's urban trees based on three dimensional data acquired on standing trees using a terrestrial LiDAR. This model relates the aboveground biomass (AGB) with the trunk diameter, wood specific density and total height of the tree. Its performance was compared to the performance of selected models for tropical forests and urban trees. As expected, being locally derived, our model reduced the bias of both individual and plot level estimates. The AGB estimates compared to those retrieved from the LiDAR showed a deviation of
A Machine Learning Based Approach for Opinion Mining on Social Network Data
Year: 2017

Micro blogging has been widely used for voicing out opinions in the public domain. One such website, Twitter is a point of attraction for researchers in the areas such as prediction of electoral events, movie box office, stock market, consumer brands etc. In our paper, we focus on using Twitter, for the task of opinion mining. We explore how combining the different parameters affect the accuracy of the machine learning algorithms with respect to the consumer products. In this paper, we have combined the methods of feature extraction with a parameter known as negation handling. Negation words can awfully change the meaning of a sentence and hence the sentiment expressed in them. We experimented with supervised learning methods like Naive Bayes (NB) Classifier and Maximum Entropy (MaxEnt) Classifier along with optimization iteration algorithms i.e. Generalized Iterative Scaling (GIS) and Improved Iterative Scaling (IIS) Experimental evaluations show that our proposed technique is better. We have obtained a 99.29% of specificity measure using the MaxEnt IIS Classifier.