Do Balance Demands Induce Shifts in Visual Proprioception in Crawling Infants?

The onset of hands-and-knees crawling during the latter half of the first year of life heralds pervasive changes in a range of psychological functions. Chief among these changes is a clear shift in visual proprioception, evident in the way infants use patterns of optic flow in the peripheral field of view to regulate their postural sway. This shift is thought to result from consistent exposure in the newly crawling infant to different patterns of optic flow in the central field of view and the periphery and the need to concurrently process information about self-movement, particularly postural sway, and the environmental layout during crawling. Researchers have hypothesized that the demands on the infant's visual system to concurrently process information about self-movement and the environment press the infant to differentiate and functionalize peripheral optic flow for the control of balance during locomotion so that the central field of view is freed to engage in steering and monitoring the surface and potentially other tasks. In the current experiment, we tested whether belly crawling, a mode of locomotion that places negligible demands on the control of balance, leads to the same changes in the functional utilization of peripheral optic flow for the control of postural sway as hands-and-knees crawling. We hypothesized that hands-and-knees crawlers (n = 15) would show significantly higher postural responsiveness to movements of the side walls and ceiling of a moving room than same-aged pre-crawlers (n = 19) and belly crawlers (n = 15) with an equivalent amount of crawling experience. Planned comparisons confirmed the hypothesis. Visual-postural coupling in the hands-and-knees crawlers was significantly higher than in the belly crawlers and pre-crawlers. These findings suggest that the balance demands associated with hands-and-knees crawling may be an important contributor to the changes in visual proprioception that have been demonstrated in several experiments to follow hands-and-knees crawling experience. However, we also consider that belly crawling may have less potent effects on visual proprioception because it is an effortful and attention-demanding mode of locomotion, thus leaving less attentional capacity available to notice changing relations between the self and the environment

Design, synthesis, and evaluation of curcumin-derived arylheptanoids for glioblastoma and neuroblastoma cytotoxicity

Using an innovative approach toward multiple carbon-carbon bond-formations that relies on the multifaceted catalytic properties of titanocene complexes we constructed a series of C1-C7 analogs of curcumin for evaluation as brain and peripheral nervous system anti-cancer agents. C2-Arylated analogs proved efficacious against neuroblastoma (SK-N-SH & SK-N-FI) and glioblastoma multiforme (U87MG) cell lines. Similar inhibitory activity was also evident in p53 knockdown U87MG GBM cells. Furthermore, lead compounds showed limited growth inhibition in vitro against normal primary human CD34+hematopoietic progenitor cells. Taken together, the present findings indicate that these curcumin analogs are viable lead compounds for the development of new central and peripheral nervous system cancer chemotherapeutics with the potential for little effects on normal hematopoietic progenitor cells

Assessment of online water-soluble brown carbon measuring systems for aircraft sampling

Brown carbon (BrC) consists of particulate organic species that preferentially absorb light at visible and ultraviolet wavelengths. Ambient studies show that as a component of aerosol particles, BrC affects photochemical reaction rates and regional to global climate. Some organic chromophores are especially toxic, linking BrC to adverse health effects. The lack of direct measurements of BrC has limited our understanding of its prevalence, sources, evolution, and impacts. We describe the first direct, online measurements of water-soluble BrC on research aircraft by three separate instruments. Each instrument measured light absorption over a broad wavelength range using a liquid waveguide capillary cell (LWCC) and grating spectrometer, with particles collected into water by a particle-into-liquid sampler (CSU PILS-LWCC and NOAA PILS-LWCC) or a mist chamber (MC-LWCC). The instruments were deployed on the NSF C-130 aircraft during WE-CAN 2018 as well as the NASA DC-8 and the NOAA Twin Otter aircraft during FIREX-AQ 2019, where they sampled fresh and moderately aged wildfire plumes. Here, we describe the instruments, calibrations, data analysis and corrections for baseline drift and hysteresis. Detection limits (3σ) at 365 nm were 1.53 Mm−1 (MC-LWCC; 2.5 min sampling time), 0.89 Mm−1 (CSU PILS-LWCC; 30 s sampling time), and 0.03 Mm−1 (NOAA PILS-LWCC; 30 s sampling time). Measurement uncertainties were 28 % (MC-LWCC), 12 % (CSU PILS-LWCC), and 11 % (NOAA PILS-LWCC). The MC-LWCC system agreed well with offline measurements from filter samples, with a slope of 0.91 and R2=0.89. Overall, these instruments provide soluble BrC measurements with specificity and geographical coverage that is unavailable by other methods, but their sensitivity and time resolution can be challenging for aircraft studies where large and rapid changes in BrC concentrations may be encountered

A happiness degree predictor using the conceptual data structure for deep learning architectures

[EN] Background and Objective: Happiness is a universal fundamental human goal. Since the emergence of Positive Psychology, a major focus in psychological research has been to study the role of certain factors in the prediction of happiness. The conventional methodologies are based on linear relationships, such as the commonly used Multivariate Linear Regression (MLR), which may suffer from the lack of representative capacity to the varied psychological features. Using Deep Neural Networks (DNN), we define a Happiness Degree Predictor (H-DP) based on the answers to five psychometric standardized questionnaires. Methods: A Data-Structure driven architecture for DNNs (D-SDNN) is proposed for defining an HDP in which the network architecture enables the conceptual interpretation of psychological factors associated with happiness. Four different neural network configurations have been tested, varying the number of neurons and the presence or absence of bias in the hidden layers. Two metrics for evaluating the influence of conceptual dimensions have been defined and computed: one quantifies the influence weight of the conceptual dimension in absolute terms and the other one pinpoints the direction (positive or negative) of the influence. Materials: A cross-sectional survey targeting the non-institutionalized adult population residing in Spain was completed by 823 cases. The total of 111 elements of the survey are grouped by socio-demographic data and by five psychometric scales (Brief COPE Inventory, EPQR-A, GHQ-28, MOS-SSS, and SDHS) measuring several psychological factors acting one as the outcome (SDHS) and the four others as predictors. Results: Our D-SDNN approach provided a better outcome (MSE: 1.46 · 10^-2 ) than MLR (MSE: 2.30 · 10^-2 ), hence improving by 37% the predictive accuracy, and allowing to simulate the conceptual structure. Conclusions: We observe a better performance of Deep Neural Networks (DNN) with respect to traditional methodologies. This demonstrates its capability to capture the conceptual structure for predicting happiness degrees through psychological variables assessed by standardized questionnaires. It also permits to estimate the influence of each factor on the outcome without assuming a linear relationship.Perez-Benito, FJ.; Villacampa-Fernandez, P.; Conejero, JA.; Garcia-Gomez, JM.; Navarro-Pardo, E. (2019). A happiness degree predictor using the conceptual data structure for deep learning architectures. Computer Methods and Programs in Biomedicine. 168:59-68. https://doi.org/10.1016/j.cmpb.2017.11.004S596816

The Journalists of the Future meet Entrepreneurial Journalism

Journalism is undergoing a strong restructuring of its labour market due to the consequences of the economic crisis and the technological innovations. Discussions on the search for new formulas for job creation are centred on the emergence of entrepreneurial journalism. Spain is a paradigmatic example of this phenomenon because between 2008 and 2014, 454 news media outlets were created. The rise of entrepreneurial journalism raises many questions and challenges that affect all areas of journalism. One is their introduction in journalism education and the views of journalism students. The aim of this article is to analyse the perceptions regarding entrepreneurship held by those who will be future journalists and who are now receiving their education in the classroom. Our goal is to find out what knowledge journalism students have about entrepreneurship and the skills that are deemed essential. We evaluate the willingness of journalism students to develop their own business project and the major barriers and obstacles. The methodology uses a quantitative approach based on surveys in Spain (N=184). The results suggest an increase of the willingness in students to engage in entrepreneurship. However, students also have a negative and disenchanted view of journalism as they progress in their studies.This research was supported by the Universitat Jaume I de Castelló [grant number PI11A2013– 12]

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Environmental Exposure and Leptospirosis, Peru

Human infection by leptospires has highly variable clinical manifestations, which range from subclinical infection to fulminant disease. We conducted a population-based, cross-sectional seroepidemiologic study in Peru to determine potential relationships of environmental context to human exposure to Leptospira and disease associated with seroconversion. Three areas were studied: a flooded, urban slum in the Peruvian Amazon city of Iquitos; rural, peri-Iquitos villages; and a desert shantytown near Lima. Seroprevalence in Belen was 28% (182/650); in rural areas, 17% (52/316); and in a desert shantytown, 0.7% (1/150). Leptospira-infected peridomestic rats were found in all locales. In Belen, 20 (12.4%) of 161 patients seroconverted between dry and wet seasons (an incidence rate of 288/1,000). Seroconversion was associated with history of febrile illness; severe leptospirosis was not seen. Human exposure to Leptospira in the Iquitos region is high, likely related both to the ubiquity of leptospires in the environment and human behavior conducive to transmission from infected zoonotic sources