Miracle-dz/UniFAR-FTUs huggingface dataset:
Predation and anthropogenic impact on community structure of boulder beaches

Predator impacts on intertidal community structure have been studied for rocky platforms, but intertidal boulder fields, a habitat with a greater extension and heterogeneity, have not yet been considered. Keeping in mind that disturbances are considered an important force in determining intertidal habitat diversity, the aims of this work were to describe and quantify boulder field community structure and to assess boulder field community dynamics by proposing possible food webs, taking into consideration predatory and anthropogenic impacts. These aims were achieved by installing predator-exclusion cages outfitted with rocks that were monitored monthly over one year in two study zones, a Management and Exploitation Area for Benthic Resources (MEABR, Playa Chica) and open-access area (OAA, Playa Grande). For both study zones, juveniles were the dominant observed ontogenetic state and invertebrate richness and density were higher inside exclusion cages. Furthermore, the MEABR had a differentiated impact on community structure and dynamics in comparison with the OAA. In conclusion, the roles played by boulder fields in intertidal diversity, especially in recruitment and as a nursery zone, are important to consider in management plans.
1,5-Diketone Synthesis Promoted by Barium Hydride or Barium Alkoxides

A tandem cross-coupling reaction of ketones with aldehydes has been achieved using barium hydride or isopropoxide as a promoter, in which barium enolates are generated in situ and then three successive reactions (aldol reaction-β-elimination-Michael addition) follow; this one-pot process is effective for obtaining symmetrical 1,5-diketones in good yields.
SPILLOVER EFFECTS IN FORECASTING VOLATILITY AND VALUE-AT-RISK

Accurate modelling of volatility (or risk) is important in finance, particularly as it relates to the modelling and forecasting of Value-at-Risk (VaR) thresholds. As financial applications typically deal with a portfolio of assets and risks, there are several multivariate GARCH models which specify the risk of one asset as depending dynamically on its own past, as well as the past of other assets. In this paper we analyse the importance of considering spillover effects when forecasting financial volatility. The forecasting performance of the VARMA-GARCH model of Ling and McAleer (2003), which includes spillover effects from all assets, the CCC model of Bollerslev (1990), which includes no such spillovers, and the new PSGARCH model, which accommodates aggregate spillovers parsimoniously, are compared using a VaR example. The empirical results suggest that the inclusion of spillover effects is not necessarily important in forecasting VaR thresholds, even when these volatility spillovers are statistically significant.
Towards a polarity standard for multicomponent seafloor seismic data

This paper deals with the question of a polarity standard for multicomponent seismic data. The primary goal is to provide a standard according to which the designations normal polarity and reverse(d) polarity may be used in association with the seismic sections from any or all of the four components normally acquired in a multicomponent seafloor survey. Since this includes a hydrophone component and three geophone components, land 3C and streamer seismic should then also be comprised as special cases. Recommendations or guidelines are given on how to proceed, both in acquisition and preprocessing, in order to arrive at a given polarity for any particular data component. The basis of this standard is the SEG polarity standard, which was first enunciated as a field-recording standard for single-component seismic data. In effect, the present recommendations are for a field-recording and preprocessing standard, rather than a final-display polarity standard. A primary objective has been an internally consistent system of polarity specifications, encompassing all of the recorded components, in order to enable consistent horizon correlation among these datasets.
Using Engel Curves to Estimate Bias in the Canadian CPI as a Cost of Living Index

Semiparametric Engel curves are used to infer bias in the Canadian CPI as a Cost of Living Index. The budget share of food has long been used as an indicator of welfare. We compare households with the same levels of CPI deflated total expenditure over the period 1978-2000. Differences in the expenditure share of food are attributed to the CPI failing to capture changes in costs of living. We employ a novel econometric approach using a single index penalized linear spline model. Over the period, we find that the CPI overstated changes in the cost of living between 1.33 and 1.86% for the four household types considered.
A Multilayer Na \ ve Bayes Model for Analyzing User ’ s Retweeting Sentiment

Today microblogging has increasingly become a means of information diffusion via user’s retweeting behavior. Since retweeting content, as context information of microblogging, is an understanding of microblogging, hence, user’s retweeting sentiment tendency analysis has gradually become a hot research topic. Targeted at online microblogging, a dynamic social network, we investigate how to exploit dynamic retweeting sentiment features in retweeting sentiment tendency analysis. On the basis of time series of user’s network structure information and published text information, we first model dynamic retweeting sentiment features. Then we build Näıve Bayes models from profile-, relationship-, and emotion-based dimensions, respectively. Finally, we build a multilayer Näıve Bayes model based on multidimensional Näıve Bayes models to analyze user’s retweeting sentiment tendency towards a microblog. Experiments on real-world dataset demonstrate the effectiveness of the proposed framework. Further experiments are conducted to understand the importance of dynamic retweeting sentiment features and temporal information in retweeting sentiment tendency analysis. What is more, we provide a new train of thought for retweeting sentiment tendency analysis in dynamic social networks.
An Assistive Handwashing System with Emotional Intelligence Using Emotional Intelligence in Cognitive Intelligent Assistant Systems

Whether emotional intelligence (or, affective reasoning) is included can influence the effectiveness of a cognitive assistive system. This thesis presents a novel emotionally intelligent hand-washing assistant that aims to help older adults with Alzheimer’s disease complete hand-washing tasks more independently. The thesis reviews previous works in the development of cognitive assistants and in the study of emotional intelligence, and then designs a hand-washing system prototype that combines the two research streams. The difficulties in designing such a system, including probabilistic and decision-theoretic reasoning of the user’s functional and emotional states, computer-vision based activity monitoring and affective recognition, and embodied prompting are discussed. Designing the hand-washing system as an integration of independent components, the thesis also discusses coordination between the components. The thesis implements the system in the end, and shows by preliminary tests in laboratory settings that the system implemented (1) runs in real-time from the perspective of the user group, (2) is able to provide a level of functional assistance, (3) produces system prompts that have encoded to some extent the emotional state of its user. The preliminary tests also indicated that a user with emotions with high potency levels (and high activity levels) is more likely to receive system prompts with low potency levels (and high activity levels). This thesis is one of the exploratory works in the area of integrating emotional intelligence with cognitive intelligent assistive systems. It provides a solution to fitting emotional intelligence in a functional system, as well as points out directions for future improvements. The framework designed in this thesis is portable and extensible, and can be generalized to be used in other applications.
Denoising Near Infrared Spectroscopy Signals with Principal Component Analysis Improves the Detection of Metabolic Foci

In this work Principal Component Analysis (PCA) was applied, in order to denoise NearInfraRed Spectroscopy data recorded from 10 subjects performing visual tasks at different flickering frequencies. Due to the poor signal quality, indeed, the sole application of General Linear Model had not been able to extract any metabolic focus of activation, at the group level. Nevertheless, after preprocessing with PCA, the same dataset could provide stable, bilateral occipital pattern of activation at group level, by means of the same General Linear Model used before. Overall, the employment of Principal Component Analysis during the preprocessing stage provided improved detection of the metabolic foci.
Record of Tetrastichus howardi (Hymenoptera: Eulophidae) parasitizing Diatraea sp. (Lepidoptera: Crambidae) in sugarcane crop in Brazil

The biological control has been considered a viable alternative and new research are carried out to improving efficiency or addition of new natural enemies. We present the record of Tetrastichus howardi (Olliff, 1893) (Hymenoptera: Eulophidae) parasitizing Diatraea sp. (Lepidoptera: Crambidae) larvae and pupae. Diatraea sp. pupae parasitized by T. howardi were collected in the sugarcane crop in Dourados, Mato Grosso do Sul State, Brazil and has been maintained on D. saccharalis pupae in laboratory. Beyond recording this natural enemy in the field, data on parasitism of D. saccharalis larvae in laboratory by T. howardi are presented. These results indicate that T. howardi parasitize and develops into Diatraea sp. larvae and pupae and its potential biocontrol agent of this pest in the sugarcane crop should be investigated.
The effect of spatio-temporal knowledge flows on regional innovation performance: the case of ICT patenting in Europe

In this study, we focus on the effects of external knowledge on regional innovation performance by considering that the neighborhood that supply a region with external knowledge might be relational as well as geographical, and it may evolve in time. Following Autant Bernard and LeSage (2011), and Lee and Yu (2012) we worked on a Spatial Durbin model, which includes time varying weight matrices, and space and time lagged variables. Our empirical application bases on European data in the field of ICT and aims at quantifying the effect of spatial, temporal and spatio-temporal flows on the inventive activity of 226 regions during 2003-2009. The results suggest that external knowledge emanating from geographical and relational neighbors play an equally important role on the regional inventive activity. The magnitude of contemporaneous flows from neighbors is small but they are in play in time because past inventive activity affects current inventive activity.
Numerical modelling of POC yearly dynamics in the southern Baltic under variable scenarios of nutrients, light and temperature

Abstract. This paper presents various scenarios of the particulate organic carbon (POC) in the southern Baltic Sea. The study is based on a one-dimensional Particulate Organic Carbon model (1-D POC). Mathematically, the pelagic variables of 1-D POC model are described by a second-order partial differential equations of the diffusion type with biogeochemical sources and sinks. The POC concentration is determined as the sum of phytoplankton, zooplankton and dead organic matter (detritus) concentrations. The temporal changes in the phytoplankton biomass are caused by primary production, mortality, grazing by zooplankton and sinking. The zooplankton biomass is affected by ingestion, excretion, faecal production, mortality, and carnivorous grazing. The changes in the pelagic detritus concentration are determined by input of: dead phytoplankton and zooplankton, natural mortality of predators, faecal pellets, and sinks: sedimentation, zooplankton grazing and biochemical decomposition. The 1-D POC model was used to simulate temporal dynamics of POC in the southern Baltic Sea (Gdansk Deep, Bornholm Deep and Gotland Deep) under scenarios characterized by different temperature, nutrients and light. Daily, monthly, seasonal and annual variabilities of POC in the upper water layer are presented for the different scenarios. The starting-point of the numerical simulations was assumed as average values of the investigated pelagic variables for 1965–1998 period. Two- to three-fold increases of POC concentrations in late spring were revealed as well as the shift towards postponed maximum POC concentration. It is speculated that, due to POC increase, oxygenation of under-halocline water layer will decrease, while supply of food to organisms from higher trophic level should increase.
Impact Of Reversible Invert Emulsion Drilling Fluid Rheology On Productivity

Drilling muds are multi-component fluid systems designed to perform several functions during drilling operation and as a drill-in fluid under varying conditions of temperature and pressure. the use of conventional oil-base mud for drilling can bring with it an associated trade-off in formation damage. for a drilling engineer, oil-base muds control reactive shales, improve penetration rates and enhance overall drilling efficiency. for reservoir engineer, the oil-wet state of the wellbore and filtercake may present a skin challenge.
Sperm depletion: a cost for single mated females of Podisus nigrispinus (Dallas, 1851) (Heteroptera: Pentatomidae)

Entre os heteropteros, o declinio da concentracao de esperma pode ser um fator limitante para o sucesso reprodutivo desses insetos. Acasalamentos multiplos conferem um reabastecimento de esperma e podem permitir um aumento do valor adaptativo das femeas. Neste estudo foi testada a hipotese de que a poliandria aumenta a viabilidade dos ovos. A longevidade de femeas de Podisus nigrispinus, bem como seus parâmetros reprodutivos em resposta a diferentes numeros de acasalamentos (0, 1, 2, 3 ou em coabitacao com o mesmo macho) foi avaliada. Esse percevejo vem sendo usado em programas de controle biologico de pragas em reflorestamentos de Eucalipto no Brasil. Apesar da diminuicao no tempo de sobrevivencia das femeas, acasalamentos multiplos mantiveram a viabilidade dos ovos e o periodo reprodutivo das femeas, permitindo um maior numero de descendentes produzidos. Tais resultados indicam que um numero minimo de tres acasalamentos antes da primeira postura permite uma maximizacao do sucesso reprodutivo dessa especie.
Stray loss evaluation in power transformers-a review

Survey of current research papers reveals the continued interest in application of advanced techniques for accurate estimation and control of stray losses in transformers. This paper gives an overview of research, development and application of various computational tools for stray loss analysis, based on over 50 published papers. All landmark papers are systematically classified. Practicality of application of methods by transformer designers is discussed. The report concludes with critical comments on efficacy of all approaches and directions for pursuing further research.
Fuzzy-Based Optimal Adaptive Line-of-Sight Path Following for Underactuated Unmanned Surface Vehicle with Uncertainties and Time-Varying Disturbances

This paper investigates the path following control problem for an underactuated unmanned surface vehicle (USV) in the presence of dynamical uncertainties and time-varying external disturbances. Based on fuzzy optimization algorithm, an improved adaptive line-of-sight (ALOS) guidance law is proposed, which is suitable for straight-line and curve paths. On the basis of guidance information provided by LOS, a three-degree-of-freedom (DOF) dynamic model of an underactuated USV has been used to design a practical path following controller. The controller is designed by combining backstepping method, neural shunting model, neural network minimum parameter learning method, and Nussbaum function. Neural shunting model is used to solve the problem of “explosion of complexity,” which is an inherent illness of backstepping algorithm. Meanwhile, a simpler neural network minimum parameter learning method than multilayer neural network is employed to identify the uncertainties and time-varying external disturbances. In particular, Nussbaum function is introduced into the controller design to solve the problem of unknown control gain coefficient. And much effort is made to obtain the stability for the closed-loop control system, using the Lyapunov stability theory. Simulation experiments demonstrate the effectiveness and reliability of the improved LOS guidance algorithm and the path following controller.
Comparing growth rates of natural phytoplankton communities to laboratory culturing experiments

In a world facing ever-increasing atmospheric carbon dioxide, understanding the various facets of the carbon cycle is critical. In temperate coastal systems, diatoms play a key role in the carbon cycle by contributing to the biological pump that sequesters carbon into deep ocean sediments. Many scientists use culturing experiments to make predictions about the responses of phytoplankton to environmental
Soothing spaces and healing places: is there an ideal counselling room design?

This qualitative study explores the difference a counselling room can make to the work between counsellor and client. Early and recent research relevant to the influence of the workspace on health practitioners, counsellors and their clients is reviewed. A focus group was used to formulate a questionnaire on counsellor perceptions of the contribution of their designated counselling space to the work with clients. Questionnaires were distributed to professional counsellors around Australia. Thirty-four responses were received and analysed for major and minor themes. Emerging themes from the data were compared with the literature. A range of ideal attributes were indicated, including preferences for larger work spaces, natural light, use of aesthetically pleasing decor, and provision for clients to have choice in seating.
ScienceDirect Product Services Systems and Value Creation . Proceedings of the 6 th CIRP Conference on Industrial Product-Service Systems Service knowledge capture and reuse

The keynote will start with the need for service knowledge capture and reuse for industrial product-service systems. A novel approach to capture the service damage knowledge about individual component will be presented with experimental results. The technique uses active thermography and image processing approaches for the assessment. The paper will also give an overview of other non-destructive inspection techniques for service damage assessment. A robotic system will be described to automate the damage image capture. The keynote will then propose ways to reuse the knowledge to predict remaining life of the component and feedback to design and manufacturing. © 2014 The Authors. Published by Elsevier B.V. Selection and peer-review under responsibility of the International Scientific Committee of “The 6th CIRP Conference on Industrial ProductService Systems” in the person of the Conference Chair Professor Hoda ElMaraghy.
Computational Study of Enthalpies of Formation of OXO (X = Cl, Br, and I) and Their Anions

The enthalpies of formation of OXO (X = Cl, Br, and I) and their anions were calculated using the Hartree−Fock, the second-order Moller−Plesset perturbation theory, the density functional theory with the B3LYP hybrid functional, and the coupled cluster theory using single and double excitation with a perturbational treatment of triplet excitation methods with two basis sets of triple-ζ plus polarization quality by employing several isodesmic (or congeneric) reactions. The weighted averages and their associated uncertainties for the enthalpies of formation were derived for these molecules using Irikura's procedure. The calculated standard enthalpies of formation at 0 K are 102.2 ± 6.5, 163.9 ± 7.1, 113.9 ± 10.3, −104.8 ± 6.5, −76.0 ± 7.0, and −135.0 ± 10.3 kJ/mol for OClO, OBrO, OIO, OClO-, OBrO-, and OIO-, respectively. The derived values are in excellent agreement with the available experimental values.
How to Solve the Smart Paradox

Abstract The mobile instant messengers could change the lives of average citizens as much as did the telephone in the early part of the 20th century and television in the 1950s and 1960s. Researchers are debating whether the mobile instant messengers are improving or harming participation in community life and social relationships. For this study, 155 participants in two universities completed questionnaires pertaining to their own mobile instant messengers use and feelings of loneliness. We used survey data to examine the effects of the mobile instant messengers on social involvement and psychological well-being. In this sample, the mobile instant messengers were used extensively for communication. Results suggest that greater use of the mobile instant messengers were associated with declines in participants' communication with the people around which in turn creases their loneliness. These findings have implications for research and for the design of technology. Key Words : loneliness, smart paradox, mobile instant messenger
Segmentation of Image Sequence into Scene-Coherent Parts

The Narrative Clip is a small wearable camera that takes an image every 30 seconds. By wearing the clip a whole day a user captures a long image sequence of the day's events. In this thesis we will segment such a sequence into the individual events automatically. Multiple sequences are segmented by humans in order to nd a groundtruth for each sequence. The groundtruth will be used to determine the performance of the algorithm and also how well individual humans are able to segment a sequence. The method presented here takes a sequence of images and tries to nd the location where the mean of the descriptors changes. The images are described using various image descriptors that capture colors, lines, textures and similar low level features. We also introduce an indoor/outdoor classication method that combines a SVM and a HMM. The classication method is combined with the segmentation for each descriptor in order to create a combined segmentation. The indoor classication method achieves an accuracy of 97% which is to be considered very good results. The best human segmentation has an F1-score of 0.82 while the best automatic segmentation method's F1-score is 0.43. The conclusion is that the current system is not suitable for any practical usage.
Combination of Biorthogonal Wavelet Hybrid Kernel OCSVM with Feature Weighted Approach Based on EVA and GRA in Financial Distress Prediction

Financial distress prediction plays an important role in the survival of companies. In this paper, a novel biorthogonal wavelet hybrid kernel function is constructed by combining linear kernel function with biorthogonal wavelet kernel function. Besides, a new feature weighted approach is presented based on economic value added (EVA) and grey relational analysis (GRA). Considering the imbalance between financially distressed companies and normal ones, the feature weighted one-class support vector machine based on biorthogonal wavelet hybrid kernel (BWH-FWOCSVM) is further put forward for financial distress prediction. The empirical study with real data from the listed companies on Growth Enterprise Market (GEM) in China shows that the proposed approach has good performance.
Merced Proceedings of the Annual Meeting of the Cognitive Science Society Title

This study investigates the strategies used by expert scientists to evaluate hypotheses when they analyze data. We used an in vivo methodology to observe experts' on-line thinking. In contrast to the results of laboratory studies of scientific reasoning, we found that the scientists rarely used experimentation but relied on a variety of other strategies, including conceptual simulation. This strategy was most prevalent in evaluating a hypothesis about a phenomenon that violated the scientists' expectations.