nils-herrmann/clean_scirepeval huggingface dataset:
How clinical registries can make a difference in hip fracture care
Venue: Anaesthesia

ment initiation, follow up and perioperative management. Cardiovascular and Hematological Disorders Drug Targets 2015; 15: 120 6. 11. Van Veen JJ, Makris M. Management of peri operative anti thrombotic therapy. Anaesthesia 2015; 70 (Suppl 1) 58 e23. 12. McLintic AJ, Irwin MG. Is the jury out on consensus opinion? Anaesthesia 2016; 71: 256 60. 13. Clinical practice guidelines for vascular access. American Journal of Kidney Disease 2006; 48: S248 73. 14. O'Grady NP, Alexander M, Burns LA, et al. Centre for Disease Control: Guidelines for the prevention of intravascular catheter related infections, 2011. http:/www.cdc.govhicpac/pdf/ guidelines/bsi guidelines 2011.pdf (accessed 20/01/2016) 15. O'Grady NP, Alexander M, Burns LA, et al. Guidelines for the prevention of intravascular catheter related infections.  S1 34. 16. Brass P, Hellmich M, Kolodziej L, et al. Ultrasound guidance versus anatomical landmarks for internal jugular vein catheterization. Cochrane Database of Systematic Reviews 2015; 1: CD006962. 17. Choi SW, Lam DMH. Funnels for publication bias have we lost the plot? Anaesthesia 2016; 71: 338 41. 18. Fragou M, Gravvanis A, Dimitriou V, et al. Real time ultrasound guided subclavian vein cannulation versus the landmark method in critical care patients: a prospective randomized study. Critical Care Medicine 2011; 39: 1607 12. 19. Grebenik CR, Boyce A, Sinclair ME, et al. NICE guidelines for central venous catheterization in children. Is the evidence base sufficient? British Journal of Anaesthesia 2004; 92: 827 30. 20. Choi SW, Lam DMH. Trials and tribulations of a meta analyst. Anaesthesia 2016; 71: 228 31. 21. Tovey G, Stokes M. A survey of the use of 2D ultrasound guidance for insertion of central venous catheters by UK consultant paediatric anaesthetists.  71 5. 22. Johnston AJ, Holder A, Bishop SM, See TC, Streater CT. Evaluation of the Sherlock 3CG Tip Confirmation System on peripherally inserted central catheter malposition rates. Anaesthesia 2014;
A study on the enhancement plan to develop an MRO business complex at Cheongju International Airport based on low cost carriers

The objective of this exploratory study is to examine the enhancement plan to develop an MRO(Maintenance, Repair, and Overhaul) business complex at Cheongju International Airport based on LCCs(Low cost carriers) In order to achieve that purpose, the author specifically analyzed related literature, government and business reports, domestic and international case studies, and also conducted expert group interviews. Because most of MRO activities on LCCs have been outsourced by overseas organizations due to maintenance cost reductions and lack of technical skills related to engine overhaul, the highly significant improvement plans for the development of an MRO industry in Cheongju are as follows. As the result of analysis, first of all it is essential not only to reinforce strategic networks with domestic business partners, but also to attract foreign MRO companies and their investment to have technical cooperation, and to organize competitive MRO services. Second, Cheongju Airport should be a specialized MRO station of LCCs to offer low cost and high maintenance quality. To do so, it has to reach an agreement for price competitiveness to adjust to current high labor charges for aircraft mechanics. Third, the MRO business, which is a rapidly growing industry, strongly requires certified high level technical skills performed by well trained, skilled employees; and it needs to offer effective TAT(turn around time) and implement international marketing strategies to secure overseas customers. Furthermore, it should also consider military aircraft MRO activities to expand market demand.
The Truth and Nothing But the Truth: Multimodal Analysis for Deception Detection
Venue: 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW)

We propose a data driven method for automatic deception detection in real life trial data using visual and verbal cues. Using OpenFace with facial action unit recognition, we analyze the movement of facial features of the witness when posed with questions and the acoustic patterns using OpenSmile. We then perform a lexical analysis on the spoken words, emphasizing the use of pauses and utterance breaks, feeding that to a Support Vector Machine to test deceit or truth prediction. We then try out a method to incorporate utterance based fusion of visual and lexical analysis, using string based matching.
Influence of Animal Health, Breed, and Diet on Non cow Milk Composition

Non cow milk is the predominant source of nourishing food in many parts of the world. In this review, the importance of the milk and its characteristics and animal udder health, the major factor that affects milk quality, are considered in major non cow milk producing species: buffaloes, yaks, camels, donkeys, sheep, and goats. Each of these species has a unique milk composition that provides exceptional opportunities to exploit for human benefits. Buffaloes, camels, and yaks produce milk in extreme environments. Buffalo milk is used to produce dairy products with unique characteristics, camel milk for producing medicinal food, and donkey milk for producing hypo allergic milk for infants. Qualitatively, the same factors that affect milk composition are common to all species. The effects of subclinical mastitis on milk composition are considered in detail since it is a major factor affecting milk quality. However, because the immune system is species specific, we stress the need to increase knowledge of the factors affecting milk quality in non cow species.
Resistive switching memories based on metal oxides: mechanisms, reliability and scaling

With the explosive growth of digital data in the era of the Internet of Things (IoT) fast and scalable memory technologies are being researched for data storage and data driven computation. Among the emerging memories, resistive switching memory (RRAM) raises strong interest due to its high speed, high density as a result of its simple two terminal structure, and low cost of fabrication. The scaling projection of RRAM, however, requires a detailed understanding of switching mechanisms and there are potential reliability concerns regarding small device sizes. This work provides an overview of the current understanding of bipolar switching RRAM operation, reliability and scaling. After reviewing the phenomenological and microscopic descriptions of the switching processes, the stability of the low and high resistance states will be discussed in terms of conductance fluctuations and evolution in 1D filaments containing only a few atoms. The scaling potential of RRAM will finally be addressed by reviewing the recent breakthroughs in multilevel operation and 3D architecture, making RRAM a strong competitor among future high density memory solutions.
Non linear electro thermal AlGaN/GaN model including large signal dynamic thermal trapping effects
Venue: 2016 IEEE MTT S International Microwave Symposium (IMS)

This paper presents a non linear electro thermal AlGaN/GaN model for CAD application with a new additive thermal trap model to take into account the dynamic behavior of trap states and their associated temperature variation. The thermal trap model is extracted through low frequency small signal CW S parameter measurements and large signal pulsed RF measurements at different temperatures. This thermal trap model allows accurately predicting the physical temperature activation of traps and also the thermal signature of traps. It is also demonstrated that extrapolation of trap model parameters by stretched multi exponential function of drain current transient measurements during pulsed RF excitations allows deeply improving the envelope simulations.
Ursgal, Universal Python Module Combining Common Bottom Up Proteomics Tools for Large Scale Analysis.
Venue: Journal of proteome research

Proteomics data integration has become a broad field with a variety of programs offering innovative algorithms to analyze increasing amounts of data. Unfortunately, this software diversity leads to many problems as soon as the data is analyzed using more than one algorithm for the same task. Although it was shown that the combination of multiple peptide identification algorithms yields more robust results, it is only recently that unified approaches are emerging; however, workflows that, for example, aim to optimize search parameters or that employ cascaded style searches can only be made accessible if data analysis becomes not only unified but also and most importantly scriptable. Here we introduce Ursgal, a Python interface to many commonly used bottom up proteomics tools and to additional auxiliary programs. Complex workflows can thus be composed using the Python scripting language using a few lines of code. Ursgal is easily extensible, and we have made several database search engines (X!Tandem, OMSSA, MS GF+ Myrimatch, MS Amanda) statistical postprocessing algorithms (qvality, Percolator) and one algorithm that combines statistically postprocessed outputs from multiple search engines "combined FDR" accessible as an interface in Python. Furthermore, we have implemented a new algorithm "combined PEP" that combines multiple search engines employing elements of "combined FDR" PeptideShaker, and Bayes' theorem.
KGEN: A Python Tool for Automated Fortran Kernel Generation and Verification
Venue: ICCS

Computational kernels, which are small pieces of software that selectively capture the characteristics of larger applications, have been used successfully for decades. Kernels allow for the testing of a compiler's ability to optimize code, performance of future hardware and reproducing compiler bugs. Unfortunately they can be rather time consuming to create and do not always accurately represent the full complexity of large scientific applications. Furthermore, expert knowledge is often required to create such kernels. In this paper, we present a Python based tool that greatly simplifies the generation of computational kernels from Fortran based applications. Our tool automatically extracts partial source code of a larger Fortran application into a stand alone executable kernel. Additionally, our tool also generates state data necessary for proper execution and verification of the extracted kernel. We have utilized our tool to extract more than thirty computational kernels from a million line climate simulation model. Our extracted kernels have been used for a variety of purposes including: code modernization, identification of limitations in compiler optimizations, numerical algorithm debugging, compiler bug reporting, and for procurement benchmarking.
Culinary travel as new approach for cultural tourism

Gastronomy is emerging as one of the key elements for the development and promotion of tourist destinations, also having a positive influence both on increasing overnight stays as in the enhancement of primary sector of a certain geographic area. The methodology used to carry out this research study was based on the realization of a fieldwork with the objective of getting to know the tourist profile visiting the city of Caceres, Spain and its feedback and motivations regarding gastronomy. The results of this research show the important relationship between culture and gastronomy and point out how cultural destinations can enhance visitor satisfaction through the promotion of its cuisine. The findings of this research point to the importance of gastronomy in the satisfaction of tourists visiting the city of Caceres. Thus an enhancement of the same would, consequently, determine higher tourist satisfaction. This paper can contribute to the analysis of gastronomic tourism in Europe, contributing as a key element, in addition to the high level of response from tourists, the fact that surveys have been conducted at the restaurants themselves when the traveler was having lunch or dinner.
Exploring Potentials for Culinary Tourism through a Food Festival: The Case of Thessaloniki Food Festival

This paper seeks to conceptualize the way Thessaloniki is promoting culinary tourism, whilst supporting and building upon local networks; engaging and co creating an urban experience with its citizens and visitors. The aim of the paper is to suggest a potential framework that can be used as a strategic planning tool for the promotion of culinary tourism in Thessaloniki. In this direction, a food festival is being investigated. The last, is conceived by the organizers as the foundation of the idea of culinary tourism in the city. However, the findings indicate that there is a lack of active participation by the locals and not enough communication among various assets that are associated with the culinary identity of the city. In general, Thessaloniki seems to embody the ongoing struggle of a new destination, which is dealing with the complex process of branding and marketing without having the proper tools and the vital required collaboration between its structural networks. Accordingly, the research provides a lens through which the culinary culture of Thessaloniki can be used as a strategic pillar for stimulating a sustainable way of "consuming" and promoting the city's identity; enhancing Thessaloniki's appeal as a culinary destination.
Action Recognition with Joints Pooled 3D Deep Convolutional Descriptors
Venue: IJCAI

Torso joints can be considered as the landmarks of human body. An action consists of a series of body poses which are determined by the positions of the joints. With the rapid development of RGB D camera technique and pose estimation research, the acquisition of the body joints has become much easier than before. Thus, we propose to incorporate joint positions with currently popular deep learned features for action recognition. In this paper, we present a simple, yet effective method to aggregate convolutional activations of a 3D deep convolutional neural network (3D CNN) into discriminative descriptors based on joint positions. Two pooling schemes for mapping body joints into convolutional feature maps are discussed. The joints pooled 3D deep convolutional descriptors (JDDs) are more effective and robust than the original 3D CNN features and other competing features. We evaluate the proposed descriptors on recognizing both short actions and complex activities. Experimental results on real world datasets show that our method generates promising results, outperforming state of the art results significantly.
Inkjet Printing of a Highly Loaded Palladium Ink for Integrated, Low Cost pH Sensors

An inkjet printing process for depositing palladium (Pd) thin films from a highly loaded ink >14 wt% is reported. The viscosity and surface tension of a Pd organic precursor solution is adjusted using toluene to form a printable and stable ink. A two step thermolysis process is developed to convert the printed ink to continuous and uniform Pd films with good adhesion to different substrates. Using only one printing pass, a low electrical resistivity of 2.6 mO m of the Pd film is obtained. To demonstrate the electrochemical pH sensing application, the surfaces of the printed Pd films are oxidized for ion to electron transduction and the underlying layer is left for electron conduction. Then, solid state reference electrodes are integrated beside the bifunctional Pd electrodes by inkjet printing. These potentiometric sensors have sensitivities of 60.6 0.1 and 57 0.6 mV pH 1 on glass and polyimide substrates, and short response times of 11 and 6 s, respectively. Also, accurate pH values of real water samples are obtained by using the printed sensors with a low cost multimeter. These results indicate that the facile and cost effective inkjet printing and integration techniques may be applied in fabricating future electrochemical monitoring systems for environmental parameters and human health conditions.
Active Learning Environment for Achieving Higher Order Thinking Skills in Engineering Education
Venue: 2016 IEEE 4th International Conference on MOOCs, Innovation and Technology in Education (MITE)

Higher order thinking, known as higher order thinking skills (HOTS) is a conception of education reorganization based on learning taxonomy. Skills involving analysis, evaluation and synthesis are considered to be of higher order, requiring diverse learning and teaching methods than the customary learning of facts and concepts. HOTS involves the learning of complex judgmental skills such as critical thinking and problem solving. They are activated when individuals encounter unfamiliar problems, uncertainties, questions, or dilemmas. Successful application of the skills results in justifications, decisions, performances, and products that are valid within the context of existing knowledge that encourages continued growth in other intellectual skills. The major difficulty in attaining HOTS among engineering students is that we still pursue the traditional approach of teacher centered classroom where the teacher is an active transmitter and the students are passive recipients. To achieve HOTS among engineering students we establish an Active Learning Environment (ALE) with the effective usage of Information and communication technologies (ICT) Active learning is embodied in a learning environment where the teachers and students are actively engaged with the content through discussions, problem solving, critical thinking, or a multitude of activities that encourage interaction among learners, instructors and the material. Supporting to active learning, the ICT usage lends itself to more student centered learning. This paper demonstrates the strategies to achieve HOTS through various ALE strategies like Role Play, Jigsaw, Brainstorming, debate, Mind map etc for Concept Understanding and Group assignments, combined mini projects, Discussion on Topics, Quiz, and Puzzles for Concept Applying. We have applied various learning strategies and assessed the student outcomes. HOTS is achieved by developing applications or products, with improved inter personal skills and lifelong learning skills. The evidence for the effectiveness of ALE among engineering students is showed by great improvement in their academic result, placement record and research interests
Single Atom Catalyst of Platinum Supported on Titanium Nitride for Selective Electrochemical Reactions.
Venue: Angewandte Chemie

As a catalyst, single atom platinum may provide an ideal structure for platinum minimization. Herein, a single atom catalyst of platinum supported on titanium nitride nanoparticles were successfully prepared with the aid of chlorine ligands. Unlike platinum nanoparticles, the single atom active sites predominantly produced hydrogen peroxide in the electrochemical oxygen reduction with the highest mass activity reported so far. The electrocatalytic oxidation of small organic molecules, such as formic acid and methanol, also exhibited unique selectivity on the single atom platinum catalyst. A lack of platinum ensemble sites changed the reaction pathway for the oxygen reduction reaction toward a two electron pathway and formic acid oxidation toward direct dehydrogenation, and also induced no activity for the methanol oxidation. This work demonstrates that single atom platinum can be an efficient electrocatalyst with high mass activity and unique selectivity.
Beyond Energy Efficiency: Evaluating Green Datacenter Applications for Energy Agility
Venue: ICPE

Computing researchers have long focused on improving energy efficiency under the implicit assumption that all energy is created equal. Yet, this assumption is actually incorrect: energy's cost and carbon footprint vary substantially over time. As a result, consuming energy inefficiently when it is cheap and clean may sometimes be preferable to consuming it efficiently when it is expensive and dirty. Green datacenters adapt their energy usage to optimize for such variations, as reflected in changing electricity prices or renewable energy output. Thus, we introduce energy agility as a new metric to evaluate green datacenter applications. To illustrate fundamental tradeoffs in energy agile design, we develop GreenSort, a distributed sorting system optimized for energy agility. GreenSort is representative of the long running, massively parallel, data intensive tasks that are common in datacenters and amenable to delays from power variations. Our results demonstrate the importance of energy agile design when considering the benefits of using variable power. For example, we show that GreenSort requires 31% more time and energy to complete when power varies based on real time electricity prices versus when it is constant. Thus, in this case, real time prices should be at least 31% lower than fixed prices to warrant using them.
The IKZF1 IRF4 axis regulates macrophage polarization and macrophage mediated anti tumor immunity

In addition to antimicrobial activity, macrophages regulate tissue development, remodeling, and repair. In terms of neoplastic growth, tumor associated macrophages (TAMs) are even considered pro tumorigenic based on their angiogenic and T cell suppressive properties. In multiple myeloma (MM) macrophages represent an abundant component of the stromal cell compartment and are believed to support proliferation, survival, and drug resistance of MM cells. Those pro tumorigenic functions are partly instructed by T helper (TH) 2 cytokines such as interleukin 4 (IL 4) and IL 10, which skew TAM differentiation towards an alternatively activated, or so called M2 like, phenotype. In contrast, M1 macrophages generally considered as potent effectors in response to microbial products or interferon g (IFN g) are characterized by superior antigen presentation, abundant production of pro inflammatory cytokines such as interleukin 12 (IL 12) and consequently, promote a polarized type I immune response against infections as well as malignant cells. Transcriptional regulation is a key determinant for macrophage polarization. The Ikaros (IKZF1) transcription factor is critical for lymphoid development and is found in all hematopoietic progenitors as well as in T B NK cells and macrophages. Interestingly, IKZF1 is overexpressed in MM and selectively degraded by lenalidomide, which is approved in MM therapy. The potential role of IKZF1 in modulating macrophage polarization has not been elucidated yet. Here, we show that IKZF1expression is found highly elevated in M2 like macrophages and in MM TAMs. IKZF1 deletion in human macrophages by small interfering RNA (siRNA) or by lenalidomide yields an upregulation of M1 specific cytokines (IL 12 and IL 1b) chemokines (CXCL10 and CCL5) and costimulatory molecules (CD86 and CD40) and leads to a potent TH1 TH17 response. In fact, lenalidomide pretreated macrophages display strong tumoricidal effects when co cultured with MM cell lines as opposed to their untreated counterparts promoting MM proliferation and viability. Utilizing immunoprecipitation sequencing (ChIP Seq) we reveal that IKZF1 governs IRF4 and IRF5 expression in human macrophages. Recent studies demonstrate that IRF4 controls M2 macrophage polarization, while IRF5 regulates the M1 phenotype respectively. We could show that a lenalidomid mediated M1 phenotype induction is efficiently abrogated by IRF4 overexpression or IRF5 silencing. Overall, these findings unravel a novel role for IKZF1 in orchestrating macrophage polarization via the IRF4/IRF5 pathway. Disclosures No relevant conflicts of interest to declare.