nils-herrmann/clean_scirepeval huggingface dataset:
Direct fabrication of compound eye microlens array on curved surfaces by a facile femtosecond laser enhanced wet etching process

We report a direct fabrication of an omnidirectional negative microlens array on a curved substrate by a femtosecond laser enhanced chemical etching process, which is utilized as a molding template for duplicating bioinspired compound eyes. The femtosecond laser treatment of the curved glass substrate employs a common x y z stage without rotating the sample surface perpendicular to the laser beam, and uniform, omnidirectional aligned negative microlenses are generated after a hydrofluoric acid etching. Using the negative microlens array on the concave glass substrate as a molding template, we fabricate an artificial compound eye with 3000 positive microlenses of 95 mm diameter close packed on a 5 mm polymer hemisphere. Compared to the transferring process, the negative microlenses directly fabricated on the curved mold by our method are distortion free, and the duplicated artificial eye presents clear and uniform imaging capabilities. This work provides a facile and efficient route to the fabrication of microlenses on any curved substrates without complicated alignment and motion control processes, which has the potential for the development of new microlens based devices and systems.
Suicide and suicidal behaviour
Venue: The Lancet

Suicide is a complex public health problem of global importance. Suicidal behaviour differs between sexes, age groups, geographic regions, and sociopolitical settings, and variably associates with different risk factors, suggesting aetiological heterogeneity. Although there is no effective algorithm to predict suicide in clinical practice, improved recognition and understanding of clinical, psychological, sociological, and biological factors might help the detection of high risk individuals and assist in treatment selection. Psychotherapeutic, pharmacological, or neuromodulatory treatments of mental disorders can often prevent suicidal behaviour; additionally, regular follow up of people who attempt suicide by mental health services is key to prevent future suicidal behaviour.
Suicide prevention strategies revisited: 10 year systematic review.
Venue: The lancet. Psychiatry

Many countries are developing suicide prevention strategies for which up to date, high quality evidence is required. We present updated evidence for the effectiveness of suicide prevention interventions since 2005.  We searched PubMed and the Cochrane Library using multiple terms related to suicide prevention for studies published between Jan 1, 2005, and Dec 31, 2014. We assessed seven interventions: public and physician education, media strategies, screening, restricting access to suicide means, treatments, and internet or hotline support. Data were extracted on primary outcomes of interest, namely suicidal behaviour (suicide, attempt, or ideation) and intermediate or secondary outcomes (treatment seeking, identification of at risk individuals, antidepressant prescription or use rates, or referrals) 18 suicide prevention experts from 13 European countries reviewed all articles and rated the strength of evidence using the Oxford criteria. Because the heterogeneity of populations and methodology did not permit formal meta analysis, we present a narrative analysis.  We identified 1797 studies, including 23 systematic reviews, 12 meta analyses, 40 randomised controlled trials (RCTs) 67 cohort trials, and 22 ecological or population based investigations. Evidence for restricting access to lethal means in prevention of suicide has strengthened since 2005, especially with regard to control of analgesics (overall decrease of 43% since 2005) and hot spots for suicide by jumping (reduction of 86% since 2005, 79% to 91% School based awareness programmes have been shown to reduce suicide attempts (odds ratio [OR] 0*45, 95% CI 0*24 0*85; p=0*014) and suicidal ideation (0*5, 0*27 0*92; p=0*025) The anti suicidal effects of clozapine and lithium have been substantiated, but might be less specific than previously thought. Effective pharmacological and psychological treatments of depression are important in prevention. Insufficient evidence exists to assess the possible benefits for suicide prevention of screening in primary care, in general public education and media guidelines. Other approaches that need further investigation include gatekeeper training, education of physicians, and internet and helpline support. The paucity of RCTs is a major limitation in the evaluation of preventive interventions.  In the quest for effective suicide prevention initiatives, no single strategy clearly stands above the others. Combinations of evidence based strategies at the individual level and the population level should be assessed with robust research designs.  The Expert Platform on Mental Health, Focus on Depression, and the European College of Neuropsychopharmacology.
Increase in Suicide in the United States, 1999 2014.
Venue: NCHS data brief

Data from the National Vital Statistics System, Mortality *From 1999 through 2014, the age adjusted suicide rate in the United States increased 24% from 10.5 to 13.0 per 100,000 population, with the pace of increase greater after 2006. Suicide rates increased from 1999 through 2014 for both males and females and for all ages 10 74. The percent increase in suicide rates for females was greatest for those aged 10 14, and for males, those aged 45 64. The most frequent suicide method in 2014 for males involved the use of firearms (55.4% while poisoning was the most frequent method for females (34.1% *Percentages of suicides attributable to suffocation increased for both sexes between 1999 and 2014.
Ship Pipe Routing Design Using NSGA II and Coevolutionary Algorithm

Pipe route design plays a prominent role in ship design. Due to the complex configuration in layout space with numerous pipelines, diverse design constraints, and obstacles, it is a complicated and time consuming process to obtain the optimal route of ship pipes. In this article, an optimized design method for branch pipe routing is proposed to improve design efficiency and to reduce human errors. By simplifying equipment and ship hull models and dividing workspace into three dimensional grid cells, the mathematic model of layout space is constructed. Based on the proposed concept of pipe grading method, the optimization model of pipe routing is established. Then an optimization procedure is presented to deal with pipe route planning problem by combining maze algorithm (MA) nondominated sorting genetic algorithm II (NSGA II) and cooperative coevolutionary nondominated sorting genetic algorithm II (CCNSGA II) To improve the performance in genetic algorithm procedure, a fixed length encoding method is presented based on improved maze algorithm and adaptive region strategy. Fuzzy set theory is employed to extract the best compromise pipeline from Pareto optimal solutions. Simulation test of branch pipe and design optimization of a fuel piping system were carried out to illustrate the design optimization procedure in detail and to verify the feasibility and effectiveness of the proposed methodology.
Accelerating BFS shortest paths calculations using CUDA for Internet topology measurements
Venue: 2016 International Conference on High Performance Computing Simulation (HPCS)

Within the last decade, the number of devices connected to the Internet has seen immense growth and it has grown to be a large and complex network. To analyze this network, Internet topology analysis has become a popular research area and the analysis can be computationally expensive for such a large scale network. In this paper, we have implemented algorithms to find the shortest paths on large scale Internet topology graphs based on real topology data using breadth first search. The algorithms have been implemented on graphical processing units (GPUs) using the CUDA platform. We performed our performance measurements on graph sizes ranging from 1,100 to 6.8 million nodes and achieved a maximum speed up of 47x on a single GPU and 124x speed up using 8 GPUs for 100 different starting points.
Customer Opinion Summarization Based on Twitter Conversations
Venue: WIMS

As Twitter gains popularity, millions of messages are generated every day via this platform allowing people to communicate with each other through daily chatter and public conversations. This social content is usually considered more subjective than professional articles involving a lot of opinions and thoughts. This has stimulated many companies to use tweets to keep track and have general overview on their customer opinions about the brand. The conversational element of Twitter is of particular interest to the marketing community. However, most studies on summarizing customer opinions through Twitter, have so far employed single tweets rather than considering the whole conversations. As tweets are limited to 140 characters and usually written in an informal way, it is frequently hard to detect the exact meaning of the tweet when taken separately. In this paper, we propose a new approach for customer opinion summarization based on Twitter conversations named COSTwiC. We employ a new conversation based method that employs conversation interactions to effectively extract the different product features as well as the polarity of the conversation messages. Experimentations show promising results. In particular, we have proved that incorporating conversation structure in the opinion summarization task contributes to improving system performance.
node2vec: Scalable Feature Learning for Networks
Venue: KDD

Prediction tasks over nodes and edges in networks require careful effort in engineering features used by learning algorithms. Recent research in the broader field of representation learning has led to significant progress in automating prediction by learning the features themselves. However, present feature learning approaches are not expressive enough to capture the diversity of connectivity patterns observed in networks. Here we propose node2vec, an algorithmic framework for learning continuous feature representations for nodes in networks. In node2vec, we learn a mapping of nodes to a low dimensional space of features that maximizes the likelihood of preserving network neighborhoods of nodes. We define a flexible notion of a node's network neighborhood and design a biased random walk procedure, which efficiently explores diverse neighborhoods. Our algorithm generalizes prior work which is based on rigid notions of network neighborhoods, and we argue that the added flexibility in exploring neighborhoods is the key to learning richer representations. We demonstrate the efficacy of node2vec over existing state of the art techniques on multi label classification and link prediction in several real world networks from diverse domains. Taken together, our work represents a new way for efficiently learning state of the art task independent representations in complex networks.
Serious games: An overview of the game designing factors and their application in surgical skills training
Venue: 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom)

Serious game is a promising tool for interactive teaching and training. The serious games are applicable to a wide variety of scenarios ranging from school education to training of professionals. The serious game design is different from normal game designing as there is a learning objective involved. The perfect blend of learning and entertainment along with promising results is a challenging task. In the case of specific applications like skills training in surgery, assessment methods and validity measures are the additional inevitable requirements. The main focus of our paper is to provide an overview of design factors for skills training applications in surgery.
An Overview of Serious Games in Cognitive Rehabilitation

Serious Games (SG) are an emergent field of research focused on the use of games with other purposes than mere entertainment with applications in many diverse areas. Although the term SG is becoming more and more popular, there is no current definition of the concept. Zyda (2005) was the first author to give a definition of SGs as "a mental contest, played with a computer in accordance with specific rules, that uses entertainment to further government or corporate training, education, health, public policy, and strategic communication objectives" (p. 26) Michael Chen (2006) define SGs as "games that do not have entertainment, enjoyment or fun as their primary purpose" (p. 21) The authors classify SGs into a number of markets: military games, government games, educational games, corporate games, healthcare games, and political, religious and art games. Susi et al. gave an overview of SGs (Susi, 2005) Despite such classifications, many games could belong to more than one category and nowadays this concept is largely used in respect to computer games. The use of SG in rehabilitation has increased substantially over the past decade. By taking advantage of game technology in order to create more attractive user experiences and increasing playability, the environments and tasks simulated in the SG can be used to teach or train users in various situations (Rego, 2012) In particular, games applied in the field of neurorehabilitation are helping to improve the process of motor learning and recovery from incidents of stroke, traumatic brain injury, and other neuromuscular impairment by increasing user motivation during training (Perry, 2011) In this chapter we present a review of the state of the art and evolution of SG in cognitive rehabilitation, revealing how they can help in the process of rehabilitation, pointing several advantages of their use, presenting some relevant SG available, as well as technologies and platforms used to their development. Furthermore, it will be also addressed new ways of human interactions and several cases of success applied to cognitive rehabilitation in patients. Lastly, some research opportunities and open problems will be identified.
Crowdsourcing system on measuring quality of experience for Internet video streaming
Venue: 2016 IEEE International Conference on Consumer Electronics Taiwan (ICCE TW)

This paper proposes a crowdsourcing system that can provide Internet streaming media companies with the ability to assess users' Quality of Experience (QoE) when they are watching the company's online video streaming at their residences. To validate the effectiveness of the system, a resident measuring device and crowdsourcing applications on users' end device are implemented with several scenario experiments to measure objective metrics and subjective metrics. Experiment results show approximately 81 100% accuracy of participant assessments when comparing with the standard assessment values.
Data Structures And Algorithms In Java

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Artificial neural networks in the calibration of nonlinear mechanical models
Venue: Adv. Eng. Softw.

Paper reviews applications of artificial neural networks in model calibration.Neural network based calibration strategies are classified into three groups.Identification strategies are compared on calibration of affinity hydration model.The most precise strategy uses an ANN based surrogate of each response component.Principal component based inverse mapping is the best for a repeated use on new data. Rapid development in numerical modelling of materials and the complexity of new models increase quickly together with their computational demands. Despite the growing performance of modern computers and clusters, calibration of such models from noisy experimental data remains a nontrivial and often computationally intensive task. Layered neural networks provide a robust and efficient technique for overcoming the time consuming simulations of calibrated models. The potential advantages of neural networks include simple implementation and high versatility in approximating nonlinear relationships. Therefore, there were several approaches proposed in literature for accelerating the calibration of nonlinear models by neural networks. This contribution reviews and compares three possible strategies based on approximating (i) the model response, (ii) the inverse relationship between the model response and its parameters and (iii) an error function quantifying how well the model fits the data. The advantages and drawbacks of particular strategies are demonstrated with the calibration of four parameters of an affinity hydration model from simulated data as well as from experimental measurements. The affinity hydration model is highly nonlinear but computationally cheap, thus allowing its calibration without any approximation and better quantification of results obtained by the examined calibration strategies. This paper can be viewed as a guide for engineers to help them develop an appropriate strategy for their particular calibration problems.
Tools for Assessment of Innovation Potential of the Business Environment Development in the Region

The purpose of this study is to assess the innovation potential of the economy and prospects for the innovative development of business environment in a particular economic region. Assessment of the innovation potential was performed using fuzzy set analysis and hierarchy analysis. Innovation level of the business environment and its development priorities were determined by the means of complex numbers. During the study, the authors disclosed the contents of the innovation potential of the regional economy, the allocated groups of the business environment, represented the situational modeling of the dynamics of the development of the innovative activity in the territory (development options and their economic interpretation) In the context of the West Siberian and East Siberian economic regions of Russia, the development of innovation potential of the business environment in the territories was assessed under the author's system of indicators that reveal the content of components of the business activity potential. Modeling the innovation potential of the region and business environment demonstrates the viability and validity of their application for the analysis of real economic processes. The presented authoring tools to study the extent of development of innovative economy of the regions will help shape the effective areas of state regulation and support of the business environment at the macro and micro level. Prospects for research in this area are to build multivariate models using computer calculations.
Selected Characteristics of Business Environment in Visegrad Region

Business environment is considered to be an important factor that affects the competitiveness of the country or region. The assessment of business environment is subject to analysis realized by many national as well as internationally accepted institutions, whose outputs have usually form of composite indices reflecting the quality of the business environment. The aim of the article is to investigate the relationship between different indices of the quality of business environment on one side and selected macroeconomic indicators and country's credit rating on the other side. The analysis concentrates on the countries of Visegrad four region (V4) Slovakia, Czech Republic, Hungary and Poland. The following indices are analyzed: Ease of Doing Business created by the World Bank Group Global Competitiveness Index, Index of Economic Freedom, rating from The World Competitiveness Yearbook and Fragile State Index. We use the real gross domestic product, unemployment rate and inflation rate as the macroeconomic indicators and the results of the country's credit rating evaluated by Moody's, Standard Poor's and Fitch Ratings. The analysis is based on the country level data for the 2005 2014 period derived from the official statistical reports of World Bank, World Economic Forum, Institute for Management Development, The Heritage Foundation, Fund for Peace and Eurostat. The analysis is performed through correlation analysis using Pearson as well as Spearman correlation coefficients. The results of our analysis indicate that relationship between different indices of the quality of business environment and selected macroeconomic indicators or country's credit rating is country specific.
Community detection in visibility networks: an approach to categorize percussive influence on audio musical signals
Venue: COMPLEX NETWORKS

The feature extraction is a very important step in the music audio classification. This task has been performed by renowned descriptors using, in most cases, the time frequency approach. In this article we propose a descriptor that performs the feature extraction in a set of music audio files labeled in symphonic and percussive music, using parameters calculated within the Euclidean domain. First we calculate the variance fluctuation series of music signal, after we map this series into visibility graphs  At the end each audio track will correspond to a network, where the links are defined by the visibility of variance fluctuations of their respective audio signal. Then, we measure the strength of the partitions of each network in clusters, using calculation of modularity. The results of computation of this parameter in sixty networks showed that percussive and symphonic music can be distinguished and hierarchized on a growing rang, following a direct correlation with modularity.
Mutations in CAPN1 Cause Autosomal Recessive Hereditary Spastic Paraplegia.
Venue: American journal of human genetics

Hereditary spastic paraplegia (HSP) is a genetically and clinically heterogeneous disease characterized by spasticity and weakness of the lower limbs with or without additional neurological symptoms. Although more than 70 genes and genetic loci have been implicated in HSP, many families remain genetically undiagnosed, suggesting that other genetic causes of HSP are still to be identified. HSP can be inherited in an autosomal dominant, autosomal recessive, or X linked manner. In the current study, we performed whole exome sequencing to analyze a total of nine affected individuals in three families with autosomal recessive HSP. Rare homozygous and compound heterozygous nonsense, missense, frameshift, and splice site mutations in CAPN1 were identified in all affected individuals, and sequencing in additional family members confirmed the segregation of these mutations with the disease (spastic paraplegia 76  CAPN1 encodes calpain 1, a protease that is widely present in the CNS. Calpain 1 is involved in synaptic plasticity, synaptic restructuring, and axon maturation and maintenance. Three models of calpain 1 deficiency were further studied. In Caenorhabditis elegans, loss of calpain 1 function resulted in neuronal and axonal dysfunction and degeneration. Similarly, loss of function of the Drosophila melanogaster ortholog calpain B caused locomotor defects and axonal anomalies. Knockdown of calpain 1a, a CAPN1 ortholog in Danio rerio, resulted in abnormal branchiomotor neuron migration and disorganized acetylated tubulin axonal networks in the brain. The identification of mutations in CAPN1 in HSP expands our understanding of the disease causes and potential mechanisms.