Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective

Modifications to the Machine Optics of BESSY II Necessitated by the EMIL Project

The Helmholtz Zentrum Berlin and the Max Planck Society are going to build a new dedicated X ray beam line at the synchrotron light source BESSY II which will be used for analyzing materials for renewable energy generation. The new large scale project has been dubbed EMIL. In this document we present the modifications to the machine optics and to what extent these changes affect the performance of BESSY I

Understanding Test Takers' Choices in a Self-Adapted Test: A Hidden Markov Modeling of Process Data

With the rise of more interactive assessments, such as simulation- and game-based assessment, process data are available to learn about students' cognitive processes as well as motivational aspects. Since process data can be complicated due to interdependencies in time, our traditional psychometric models may not necessarily fit, and we need to look for additional ways to analyze such data. In this study, we draw process data from a study on self-adapted test under different goal conditions (Arieli-Attali, 2016) and use hidden Markov models to learn about test takers' choice making behavior. Self-adapted test is designed to allow test takers to choose the level of difficulty of the items they receive. The data includes test results from two conditions of goal orientation (performance goal and learning goal), as well as confidence ratings on each question. We show that using HMM we can learn about transition probabilities from one state to another as dependent on the goal orientation, the accumulated score and accumulated confidence, and the interactions therein. The implications of such insights are discussed

Moving from information and collaboration to action: report from the 3rd International Dog Health Workshop, Paris in April 2017

Abstract Background Breed-related health problems in dogs have received increased focus over the last decade. Responsibility for causing and/or solving these problems has been variously directed towards dog breeders and kennel clubs, the veterinary profession, welfare scientists, owners, regulators, insurance companies and the media. In reality, all these stakeholders are likely to share some responsibility and optimal progress on resolving these challenges requires all key stakeholders to work together. The International Partnership for Dogs (IPFD), together with an alternating host organization, holds biennial meetings called the International Dog Health Workshops (IDHW). The Société Centrale Canine (French Kennel Club) hosted the 3rd IDHW, in Paris, in April, 2017. These meetings bring together a wide range of stakeholders in dog health, science and welfare to improve international sharing of information and resources, to provide a forum for ongoing collaboration, and to identify specific needs and actions to improve health, well-being and welfare in dogs. Results The workshop included 140 participants from 23 countries and was structured around six important issues facing those who work to improve dog health. These included individualized breed-specific strategies for health and breeding, extreme conformations, education and communication in relation to antimicrobial resistance, behavior and welfare, genetic testing and population-based evidence. A number of exciting actions were agreed during the meeting. These included setting up working groups to create tools to help breed clubs accelerate the implementation of breed-health strategies, review aspects of extreme conformation and share useful information on behavior. The meeting also heralded the development of an online resource of relevant information describing quality measures for DNA testing. A demand for more and better data and evidence was a recurring message stressed across all themes. Conclusions The meeting confirmed the benefits from inclusion of a diverse range of stakeholders who all play relevant and collaborative parts to improve future canine health. Firm actions were set for progress towards improving breed-related welfare. The next international workshop will be in the UK in 2019 and will be organized by the UK Kennel Club

UV spectrophotometry method for the monitoring of galacto-oligosaccharides production

Monitoring the industrial production of galacto-oligosaccharides (GOS) requires a fast and accurate methodology able to quantify, in real time, the substrate level and the product yield. In this work, a simple, fast and inexpensive UV spectrophotometric method, together with partial least squares regression (PLS) and artificial neural networks (ANN), was applied to simultaneously estimate the products (GOS) and the substrate (lactose) concentrations in fermentation samples. The selected multiple models were trained and their prediction abilities evaluated by cross-validation and external validation being the results obtained compared with HPLC measurements. ANN models, generated from absorbance spectra data of the fermentation samples, gave, in general, the best performance being able to accurately and precisely predict lactose and total GOS levels, with standard error of prediction lower than 13 g kg 1 and coefficient of determination for the external validation set of 0.93–0.94, showing residual predictive deviations higher than five, whereas lower precision was obtained with the multiple model generated with PLS. The results obtained show that UV spectrophotometry allowed an accurate and non-destructive determination of sugars in fermentation samples and could be used as a fast alternative method for monitoring GOS production.Fundação para a Ciência e a Tecnologia (FCT) - Bolsa de doutouramento SFRH/BDE/15510/2004Agência da Inovação – Programa IDEIA (Potugal

Grounding Word Learning in Space

Humans and objects, and thus social interactions about objects, exist within space. Words direct listeners' attention to specific regions of space. Thus, a strong correspondence exists between where one looks, one's bodily orientation, and what one sees. This leads to further correspondence with what one remembers. Here, we present data suggesting that children use associations between space and objects and space and words to link words and objects—space binds labels to their referents. We tested this claim in four experiments, showing that the spatial consistency of where objects are presented affects children's word learning. Next, we demonstrate that a process model that grounds word learning in the known neural dynamics of spatial attention, spatial memory, and associative learning can capture the suite of results reported here. This model also predicts that space is special, a prediction supported in a fifth experiment that shows children do not use color as a cue to bind words and objects. In a final experiment, we ask whether spatial consistency affects word learning in naturalistic word learning contexts. Children of parents who spontaneously keep objects in a consistent spatial location during naming interactions learn words more effectively. Together, the model and data show that space is a powerful tool that can effectively ground word learning in social contexts

MRSA in Conventional and Alternative Retail Pork Products

In order to examine the prevalence of Staphylococcus aureus on retail pork, three hundred ninety-five pork samples were collected from a total of 36 stores in Iowa, Minnesota, and New Jersey. S. aureus was isolated from 256 samples (64.8%, 95% confidence interval [CI] 59.9%–69.5%). S. aureus was isolated from 67.3% (202/300) of conventional pork samples and from 56.8% (54/95) of alternative pork samples (labeled “raised without antibiotics” or “raised without antibiotic growth promotants”). Two hundred and thirty samples (58.2%, 95% CI 53.2%–63.1%) were found to carry methicillin-sensitive S. aureus (MSSA). MSSA was isolated from 61.0% (183/300) of conventional samples and from 49.5% (47/95) of alternative samples. Twenty-six pork samples (6.6%, 95% CI 4.3%–9.5%) carried methicillin-resistant S. aureus (MRSA). No statistically significant differences were observed for the prevalence of S. aureus in general, or MSSA or MRSA specifically, when comparing pork products from conventionally raised swine and swine raised without antibiotics, a finding that contrasts with a prior study from the Netherlands examining both conventional and “biologic” meat products. In our study spa types associated with “livestock-associated” ST398 (t034, t011) were found in 26.9% of the MRSA isolates, while 46.2% were spa types t002 and t008—common human types of MRSA that also have been found in live swine. The study represents the largest sampling of raw meat products for MRSA contamination to date in the U.S. MRSA prevalence on pork products was higher than in previous U.S.-conducted studies, although similar to that in Canadian studies

An overview of the recent developments on fructooligosaccharide production and applications

Over the past years, many researchers have suggested that deficiencies in the diet can lead to disease states and that some diseases can be avoided through an adequate intake of relevant dietary components. Recently, a great interest in dietary modulation of the human gut has been registered. Prebiotics, such as fructooligosaccharides (FOS), play a key role in the improvement of gut microbiota balance and in individual health. FOS are generally used as components of functional foods, are generally regarded as safe (generally recognized as safe status—from the Food and Drug Administration, USA), and worth about 150€ per kilogram. Due to their nutrition- and health-relevant properties, such as moderate sweetness, low carcinogenicity, low calorimetric value, and low glycemic index, FOS have been increasingly used by the food industry. Conventionally, FOS are produced through a two-stage process that requires an enzyme production and purification step in order to proceed with the chemical reaction itself. Several studies have been conducted on the production of FOS, aiming its optimization toward the development of more efficient production processes and their potential as food ingredients. The improvement of FOS yield and productivity can be achieved by the use of different fermentative methods and different microbial sources of FOS producing enzymes and the optimization of nutritional and culture parameter; therefore, this review focuses on the latest progresses in FOS research such as its production, functional properties, and market data.Agencia de Inovacao (AdI)-Project BIOLIFE reference PRIME 03/347. Ana Dominguez acknowledges Fundacao para a Ciencia e a Tecnologia, Portugal, for her PhD grant reference SFRH/BD/23083/2005

Narcissism: a factor behind the selective sharing of news online

The current study examined the extent to which narcissism influences the social network users’ intention to share positive and negative life events with (close or unknown) online contacts. Using an online survey, small vignettes and a cross-sectional convenience sample of 119 participants, the results showed that narcissism positively predicted sharing intention of positive and negative life events with strangers. However, individuals rating higher in narcissism were less likely to share negative news with family. The research findings suggest that personality traits such as narcissism, the type of contacts online, and the nature of the news may shape what information is shared by online users. The type of news presented may therefore be a function of who is posting the content, their personality, and the kind of social network contacts they have online