Miracle-dz/UniFAR-FTUs huggingface dataset:
Chromophoric Dissolved Organic Matter and Dissolved Organic Carbon from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS) and MERIS Sensors: Case Study for the Northern Gulf of Mexico

Empirical band ratio algorithms for the estimation of colored dissolved organic matter (CDOM) and dissolved organic carbon (DOC) for Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS) and MERIS ocean color sensors were assessed and developed for the northern Gulf of Mexico. Match-ups between in situ measurements of CDOM absorption coefficients at 412 nm (aCDOM(412)) with that derived from SeaWiFS were examined using two previously reported reflectance band ratio algorithms. Results indicate better performance using the Rrs(510)/Rrs(555) (Bias = −0.045; RMSE = 0.23; SI = 0.49, and R2 = 0.66) than the Rrs(490)/Rrs(555) reflectance band ratio algorithm. Further, a comparison of aCDOM(412) retrievals using the Rrs(488)/Rrs(555) for MODIS and Rrs(510)/Rrs(560) for MERIS reflectance band ratios revealed better CDOM retrievals with MERIS data. Since DOC cannot be measured directly by remote sensors, CDOM as the colored component of DOC is utilized as a proxy to estimate DOC remotely. A seasonal relationship between CDOM and DOC was established for the summer and spring-winter with high correlation for both periods (R2~0.9). Seasonal band ratio empirical algorithms to estimate DOC were thus developed using the relationships between CDOM-Rrs and seasonal CDOM-DOC for SeaWiFS, MODIS and MERIS. Results of match-up comparisons revealed DOC estimates by both MODIS and MERIS to be relatively more accurate during summer time, while both of them underestimated DOC during spring-winter time. A better DOC estimate from MERIS in comparison to MODIS in spring-winter could be attributed to its similarity with the SeaWiFS band ratio CDOM algorithm.
Code of conduct in open source projects

Open source projects rely on collaboration of members from all around the world using web technologies like GitHub and Gerrit. This mixture of people with a wide range of backgrounds including minorities like women, ethnic minorities, and people with disabilities may increase the risk of offensive and destroying behaviours in the community, potentially leading affected project members to leave towards a more welcoming and friendly environment. To counter these effects, open source projects increasingly are turning to codes of conduct, in an attempt to promote their expectations and standards of ethical behaviour. In this first of its kind empirical study of codes of conduct in open source software projects, we investigated the role, scope and influence of codes of conduct through a mixture of quantitative and qualitative analysis, supported by interviews with practitioners. We found that the top codes of conduct are adopted by hundreds to thousands of projects, while all of them share 5 common dimensions.
The PITA System for Logical-Probabilistic Inference

Probabilistic Inductive Logic Programming (PILP) is gaining interest due to its ability to model domains with complex and uncertain relations among entities. Since PILP systems generally must solve a large number of inference problems in order to perform learning, they rely critically on the support of efficient inference systems. PITA [7] is a system for reasoning under uncertainty on logic programs. While PITA includes frameworks for reasoning with possibilistic logic programming, and for reasoning on probabilistic logic programs with special exclusion and independence assumptions, we focus here on PITA’s framework for reasoning on general probabilistic logic programs following the distribution semantics, one of the most prominent approaches to combining logic programming and probability. Syntactically, PITA targets Logic Programs with Annotated Disjunctions (LPADs) [9] but can be used for other languages that follow the distribution semantics, such as ProbLog [3], PRISM [8] and ICL [5], as there are linear transformation from one language to the others [1]. PITA is distributed as a package of XSB Prolog and uses tabling along with an XSB feature called answer subsumption that allows the combination of different explanations for the same atom in a fast and simple way. PITA works by transforming an LPAD into a normal program and then querying the program. In this paper we provide an overview of PITA and an experimental comparison of it with ProbLog, a state of the art system for probabilistic logic programming. The experiments show that PITA has very good performances, often being faster than ProbLog.
Chandra Study of Young Stellar Objects in the NGC 1333 Star-forming Cloud

NGC 1333, a highly active star formation region within the Perseus molecular cloud complex, has been observed with the ACIS-I detector on board the Chandra X-Ray Observatory. In our image with a sensitivity limit of ~1028 ergs s-1, we detect 127 X-ray sources, most with subarcsecond positional accuracy. While 32 of these sources appear to be foreground stars and extragalactic background, 95 X-ray sources are identified with known cluster members. The X-ray luminosity function of the discovered young stellar object (YSO) population spans a range of log LX ≃ 28.0-31.5 ergs s-1 in the 0.5-8 keV band, and absorption ranges from log NH ≃ 20 to 23 cm-2. Most of the sources have plasma energies between 0.6 and 3 keV, but a few sources show higher energies up to ~7 keV. Comparison with K-band source counts indicates that we detect all of the known cluster members with K < 12 and about half of the members with K > 12. K ≃ 11, the peak of the K-band luminosity function, corresponds to 0.2-0.4 M☉ stars for a cluster age of ~1 Myr. We detect seven of the 20 known YSOs in NGC 1333 producing jets or molecular outflows as well as one deeply embedded object without outflows. No evident difference in X-ray emission of young stars with and without outflows is found. Based on the complete subsample of T Tauri stars, we also find no difference in X-ray properties and X-ray production mechanism of stars with and without K-band excess disks. Several other results are obtained. We suggest that the X-ray emission from two late B stars that illuminate the reflection nebula originates from unresolved late-type companions. Two T Tauri stars are discovered in the ACIS images as previously unknown components of visual binaries. A good correlation LX ∝ J is seen, which confirms the well-known relation LX ∝ Lbol found in many star-forming regions. Based on spectral analysis for the X-ray counterpart of SVS 16, we establish that the column density NH is much lower than that expected from near-IR photometry so that its X-ray luminosity, log LX ≃ 30.6 ergs s-1, is not unusually high.
Performance Analysis and Comparison of Adaptive Filters for Wireless Channel Equalization

: In this paper we have applied radial basis function neural networks for equalization of wireless channel in the presence of additive noise. We have been tested the adaptive filter algorithms of simple Kalman filter, extended Kalman filter, rbfn Kalman filter, rbfn extended Kalman filter, fuzzy Kalman filter and fuzzy extended Kalman filter which might be considered applicable for wireless channel equalization in presence of noise. The Kalman filter is one of the most widely used due to its simplicity, optimality, tractability and robustness. However, the application of the KF to nonlinear systems can be difficult. The most common approach is to use the extended Kalman filter. We have shown that performance of the fuzzy extended Kalman filter is superior. More specifically, this paper highlights the error rate performance of the adaptive filters for channel equalization. Simulation results demonstrate that the adaptive fuzzy Kalman filter and fuzzy extended Kalman filter works successfully, efficiently.
Discourses of Teacher Professionalism: “From Within” and “From Without” or Two Sides of the Same Coin?

Drawing on data from a larger doctoral study, this paper specifically explores influences on the discourses of professionalism amongst a sample of highly engaged members of the Elementary Teachers’ Federation of Ontario (ETFO). Based on the assumption that discourse takes shape within a highly politicized system of socialization where language plays a significant role in the maintenance of particular power structures and the cultures that support them (Hilferty, 2004), the case suggests that the professionalism discourses of teachers and their unions and those of government are not necessarily as mutually exclusive as they are often presented in the literature.
Voice control of a robotic forceps using hierarchical instructions

A robotic forceps is controlled by voice instructions in the framework of a fuzzy coach-player system. In the proposed system, we can deal with some fuzziness included in voice instructions and the system is composed of two instruction levels in order to increase the efficiency of voice instructions. One is a local instruction level that uses any action commands directly. The other is a global instruction level that uses a task command. Such a fuzzy coach-player system is applied for the manipulation of a robotic forceps and the effectiveness of the present system is verified through some actual experiments.
Towards an Infrastructure for Distributed e-Business Projects

avoid that e-Business projects run out of time, exceed budget, and deliver poor quality applications. However, the variety of technologies and the high pace of technological change make it difficult to find the knowledge and skills required for developing a large e-Business application. This problem can be solved by geographical distribution of development teams, analogously to Open Source Software (OSS) projects that have much contributed to the spreading of the Internet. We present process and product-oriented methods that supply an infrastructure for managing cooperative work in distributed development of e-Business applications. I. INTRODUCTION The goal of software engineering is to produce software that works reliably, it is easy to use and maintain, and arrives within budget and on time. To achieve this goal, the software engineering field has proposed process and product-oriented technologies that have much contributed to satisfy the increasing demand for big and complex software systems. Among the many application domains covered by software engineering, the development of e-Business software faces extreme challenges by heterogeneous and fast changing technologies. Today, a common e-Business application might employ most of the following technologies:-HTML and CSS for web page rendering,-DOM and JavaScript for enabling dynamic clients,-ASP, JSP, or PHP for enabling dynamic generation of web pages,-Java servlets, JavaBeans or ActiveX components for reusing functional building blocks,-IDLs for exposing the services of wrapped legacy systems,-SQL-based APIs for interfacing corporate relational databases,-XML for data interchange, and XSLT for data transformation.
Aplicação de aprendizagem de máquina no diagnóstico de declínio cognitivo e demência de Alzheimer baseado em testes cognitivos e marcadores genéticos

Um grande numero de solucoes baseadas em sistemas computacionais tem sido desenvolvido recentemente para a classificacao de anormalidades cognitivas em idosos, de modo que individuos com alto risco de desenvolver doencas neurodegenerativas, como Declinio Cognitivo (DC) e Demencia de Alzheimer (DA), podem ser identificados antes da manifestacao das doencas. Varios fatores estao relacionados a essas patologias, tornando o processo de diagnostico de alta complexidade para ser resolvido. Este trabalho propoe utilizacao de modelo computacional baseado em aprendizagem de maquina para realizar processos de regressao de dados e classificacao de padroes, em uma base de dados reais de individuos idosos. A proposta leva em conta dados sobre o genero, a idade, o nivel de instrucao dos individuos e os escores resultantes dos testes cognitivos (Mini-Exame do Estado Mental, Teste de Fluencia Verbal e Semântica, Taxa de Demencia Clinica - Clinical Dementia Rating - e Teste de Determinacao de Demencia - Ascertaining Dementia). Usando modelos de regressao nao-linear, que permitem projetar classificadores para distinguir quando o envelhecimento esta sendo saudavel e/ou patologico. O objetivo primario desta pesquisa e utilizar um modelo de regressao para analisar o conjunto de dados para verificar quais parâmetros sao mais relevantes para alcancar alta precisao no diagnostico de disturbios neurodegenerativos. Uma das conclusoes indica que o processo de diagnostico baseado apenas nos resultados dos testes cognitivos, podem obter uma alta taxa de desempenho, em comparacao a utilizacao de todos os fatores, incluindo dados socio-culturais. Nesta analise, demonstra-se que o uso de testes cognitivos produz melhores valores medios. Outras analises foram realizadas incluindo marcadores geneticos (CYP46A1 e ApoE4), sem influenciar os resultados com relacao a acuracia das analises, comparando com a performance dos testes cognitivos. Analises estatisticas mostram que o melhor desempenho em termos de sensibilidade e acima de 97% quando as configuracoes tem apenas testes cognitivos. A abordagem apresentada pode ser encapsulada como uma ferramenta de suporte ao processo de diagnostico clinico, para identificar pacientes com demencia ou declinio cognitivo.
Depth-Fighting Aware Methods for Multifragment Rendering

Many applications require operations on multiple fragments that result from ray casting at the same pixel location. To this end, several approaches have been introduced that process for each pixel one or more fragments per rendering pass, so as to produce a multifragment effect. However, multifragment rasterization is susceptible to flickering artifacts when two or more visible fragments of the scene have identical depth values. This phenomenon is called coplanarity or Z-fighting and incurs various unpleasant and unintuitive results when rendering complex multilayer scenes. In this work, we develop depth-fighting aware algorithms for reducing, eliminating and/or detecting related flaws in scenes suffering from duplicate geometry. We adapt previously presented single and multipass rendering methods, providing alternatives for both commodity and modern graphics hardware. We report on the efficiency and robustness of all these alternatives and provide comprehensive comparison results. Finally, visual results are offered illustrating the effectiveness of our variants for a number of applications where depth accuracy and order are of critical importance.
Proteins : Structure , Function , and Genetics

After printing the PDF file, please read the page proofs carefully and: 1) indicate changes or corrections in the margin of the page proofs; 2) answer all queries (footnotes A,B,C, etc.) on the last page of the PDF proof; 3) proofread any tables and equations carefully; 4) check that any Greek, especially "mu", has translated correctly. Within 48 hours, please return the following to the address given below: 1) original PDF set of page proofs, 2) Reprint Order form, 3) Return fax form Return to: Your article will be published online via our EarlyView service within a few days of correction receipt. Your prompt attention to and return of page proofs is crucial to faster publication of your work. If you experience technical problems, please contact Doug Frank (
Applying learning achievement and thinking styles to cooperative learning grouping

Grouping strategy plays a pivotal role in cooperative learning. It affects the learning performance of the groups involved. As widely discussed in previous literature, heterogeneous groups are an effective means of cooperative learning. This study presents a grouping strategy based on the evaluating-conceptual graph and thinking styles. The evaluating-conceptual graph represents the students' knowledge structures. The present grouping objective is for cooperative learning groups to consist of members whose evaluating-conceptual graphs and thinking styles are not only heterogeneous but also nearly complementary. The present grouping strategies have been adopted in a cooperative learning course, "design of the compiler". The evaluation conducted in this study has yielded positive experimental results.
Efecto de la orientación al mercado, la capacidad de redes y la orientación emprendedora en el desempeño internacional de las PYMEs

This study contributes to the literature on the internationalization of SMEs by analyzing the influence of International Market Orientation, Networking Capability and International Entrepreneurial Orientation on the International Performance of this type of companies. In particular, we analyze both the direct effects of the explanatory variables on International Performance and the interdependence relations existing between them. The results obtained from an example of 161 Mexican SMEs through SEM-PLS analysis show that the International Performance of this type of companies is positively influenced by Network Capability and International Entrepreneurial Orientation, but not by International Market Orientation. Likewise, there is an interdependence between the explanatory variables of SMEs International Performance, and more specifically a positive impact of International Entrepreneurial Orientation on Network Capacity and International Market Orientation of SMEs.
12 Simulation in Plastic Surgery Training : Past , Present and Future

The face of medicine is characterized by rapid and constant evolution. New procedures, new technology, and new solutions to clinical challenges are forever changing the field. However, medical education has been historically stagnant. From the advent of medicine until Abraham Flexner’s landmark report on the state of medical education in 1910, the apprenticeship model reigned. Training was highly variable and largely dependent on one’s supervisor. As a result, by the turn of the 20th century the quality of health care in the United States (US) was cause for concern. Flexner’s report proposed several radical changes to medical education and in doing so, redefined the fundamental contract between physicians and society (Flexner, 1910).
LOW-FREQUENCY SPECTRA OF GAMMA-RAY BURSTS

Particles with energies below the mean energy E(sub 0) in relativistic shocked plasmas should assume an equilibrium energy distribution. This leads to a synchrotron spectrum F(sub nu) proportional to nu(exp 1/3) up to approximately the critical frequency nu(sub 0) of an electron with the energy E(sub 0). Application to gamma-ray bursts (GRBs) implies that a burst with 10(exp -5) ergs/sq cm/s of soft gamma rays and h nu(sub 0) = 300 keV should simultaneously be about 18th magnitude in visible light and a few micro-J at 1 GHz (less if self-absorbed); the low-freqency intensities peak later at higher values.
Flower image classification with basket of features and multi layered artificial neural networks

Artificial intelligence is penetrating most of the classification and recognition tasks performed by a computer. This work proposes to classify flower images based on features extracted during segmentation and after segmentation using multiple layered neural networks. The segmentation models used are watershed, wavelet, wavelet fusion model, supervised active contours based on shape, color and Local binary pattern textures and color, fused textures based active contours. Multi-dimension feature vectors are constructed from these segmented results for each indexed flower image labelled with their name. Each feature becomes input to a neuron in various feature layers and error back propagation algorithm with convex optimization structure trains these multiple feature layers. Testing with different flower images sets from multiple sources resulted in average classification accuracy of 92% for shape, color and texture supervised active contour segmented flower images.
Incidents Investigation and Dynamic Analysis of Large Alarm Databases in Chemical Plants: A Fluidized-Catalytic-Cracking Unit Case Study†

A novel framework to model the chronology of incidents is presented—depicting the relationship of initiating events with the various regulating and protection systems of the process—eventually leading to consequences, varying from zero to high severities. The key premise is that the departures and subsequent returns of process and product quality variables, from and to their normal operating ranges, are recognized as near-misses, which could have propagated to incidents. This leads to the availability of vast near-miss information recorded in distributed control and emergency shutdown systems databases that monitor the dynamics of the process. New performance indices, which utilize this abundant information, are introduced to conduct quantitative and qualitative (absolute and relative) assessment of the real-time safety and operability performances of an industrial fluidized-catalytic-cracking unit (FCCU) at a petroleum refinery. Also, new techniques for abnormal event tracking and recovery-time analysis .
A Cognitive-Based Approach to Learning Integrated Language Components

The learning component of a cognitive-based language model (LEAP) designed to easily integrate into agent systems is presented. Building on the Interlaced Micro-Patterns (IMP) theory and the Alchemy/Goal Mind environment, the LEAP research improves agent-to-human and agent-to-agent communication by incorporating aspects of human language development within the framework of general cognition. Using a corpus of child through youth fiction, we provide evidence that micro-patterns can be used to simultaneously learn a lexicon, syntax, thematic roles and concepts.
Quintessence as a runaway dilaton

We consider a late-time cosmological model based on a recent proposal that the infinite-bare-coupling limit of superstring/M-theory exists and has good phenomenological properties, including a vanishing cosmological constant, and a massless, decoupled dilaton. As it runs away to $+ \infty$, the dilaton can play the role of the quintessence field recently advocated to drive the late-time accelerated expansion of the Universe. If, as suggested by some string theory examples, appreciable deviations from General Relativity persist even today in the dark matter sector, the Universe may smoothly evolve from an initial "focusing" stage, lasting untill radiation--matter equality, to a "dragging" regime, which eventually gives rise to an accelerated expansion with frozen $\Omega(\rm{dark energy})/\Omega(\rm{dark matter})$.
Knowledge-Based Extraction of Measurement-Entity Relations from German Radiology Reports

A large percentage of relevant radiologic patient information is currently only available in unstructured formats such as free text reports. In particular measurements are important since they are comparable and thus provide insight into the change of the health status over time, for example in response to some treatment. In radiology most of the measurements in reports describe the size of anatomical entities. Even though it is possible to extract measurements and anatomical entities from text using standard information extraction techniques, it is difficult to extract the relation between the measurement and the corresponding anatomical entity. Here we present a knowledge-based approach to extract this relation for size measurements using a model about typical size descriptions of anatomical entities in combination with hierarchical knowledge of existing medical ontologies. We evaluate our approach on two data sets of German radiology reports reaching an F1-measure of 0.85 and 0.79 respectively.