Quantifying scaling in the velocity field of the anisotropic turbulent solar wind

Solar wind turbulence is dominated by Alfvénic fluctuations with power spectral exponents that somewhat surprisingly evolve toward the Kolmogorov value of −5/3, that of hydrodynamic turbulence. We analyze in situ satellite observations at 1AU and show that the turbulence decomposes linearly into two coexistent components perpendicular and parallel to the local average magnetic field and determine their distinct intermittency independent scaling exponents. The first of these is consistent with recent predictions for anisotropic MHD turbulence and the second is closer to Kolmogorov-like scaling

Solar cycle dependence of scaling in solar wind fluctuations

In this review we collate recent results for the statistical scaling properties of fluctuations in the solar wind with a view to synthesizing two descriptions: that of evolving MHD turbulence and that of a scaling signature of coronal origin that passively propagates with the solar wind. The scenario that emerges is that of coexistent signatures which map onto the well known "two component" picture of solar wind magnetic fluctuations. This highlights the need to consider quantities which track Alfvénic fluctuations, and energy and momentum flux densities to obtain a complete description of solar wind fluctuations

Scaling collapse and structure functions: identifying self-affinity in finite length time series

Empirical determination of the scaling properties and exponents of time series presents a formidable challenge in testing, and developing, a theoretical understanding of turbulence and other out-of-equilibrium phenomena. We discuss the special case of self affine time series in the context of a stochastic process. We highlight two complementary approaches to the differenced variable of the data: i) attempting a scaling collapse of the Probability Density Functions which should then be well described by the solution of the corresponding Fokker-Planck equation and ii) using structure functions to determine the scaling properties of the higher order moments. We consider a method of conditioning that recovers the underlying self affine scaling in a finite length time series, and illustrate it using a Lévy flight

Testing the Resolving Power of 2-D K^+ K^+ Interferometry

Adopting a procedure previously proposed to quantitatively study two-dimensional pion interferometry, an equivalent 2-D chi^2 analysis was performed to test the resolving power of that method when applied to less favorable conditions, i.e., if no significant contribution from long lived resonances is expected, as in kaon interferometry. For that purpose, use is made of the preliminary E859 K^+ K^+ interferometry data from Si+Au collisions at 14.6 AGeV/c. As expected, less sensitivity is achieved in the present case, although it still is possible to distinguish two distinct decoupling geometries. The present analysis seems to favor scenarios with no resonance formation at the AGS energy range, if the preliminary K^+ K^+ data are confirmed. The possible compatibility of data with zero decoupling proper time interval, conjectured by the 3-D experimental analysis, is also investigated and is ruled out when considering more realistic dynamical models with expanding sources. These results, however, clearly evidence the important influence of the time emission interval on the source effective transverse dimensions. Furthermore, they strongly emphasize that the static Gaussian parameterization, commonly used to fit data, cannot be trusted under more realistic conditions, leading to distorted or even wrong interpretation of the source parameters!Comment: 11 pages, RevTeX, 4 Postscript figures include

Effects of Higher-Order Cognitive Strategy Training on Gist-Reasoning and Fact-Learning in Adolescents

Improving the reasoning skills of adolescents across the United States has become a major concern for educators and scientists who are dedicated to identifying evidence-based protocols to improve student outcome. This small sample randomized, control pilot study sought to determine the efficacy of higher-order cognitive training on gist-reasoning and fact-learning in an inner-city public middle school. The study compared gist-reasoning and fact-learning performances after training in a smaller sample when tested in Spanish, many of the students’ native language, versus English. The 54 eighth grade students who participated in this pilot study were enroled in an urban middle school, predominantly from lower socio-economic status families, and were primarily of minority descent. The students were randomized into one of three groups, one that learned cognitive strategies promoting abstraction of meaning, a group that learned rote memory strategies, or a control group to ascertain the impact of each program on gist-reasoning and fact-learning from text-based information. We found that the students who had cognitive strategy instruction that entailed abstraction of meaning significantly improved their gist-reasoning and fact-learning ability. The students who learned rote memory strategies significantly improved their fact-learning scores from a text but not gist-reasoning ability. The control group showed no significant change in either gist-reasoning or fact-learning ability. A trend toward significant improvement in overall reading scores for the group that learned to abstract meaning as well as a significant correlation between gist-reasoning ability and the critical thinking on a state-mandated standardized reading test was also found. There were no significant differences between English and Spanish performance of gist-reasoning and fact-learning. Our findings suggest that teaching higher-order cognitive strategies facilitates gist-reasoning ability and student learning

Protected Areas in Tropical Africa: Assessing Threats and Conservation Activities

Numerous protected areas (PAs) have been created in Africa to safeguard wildlife and other natural resources. However, significant threats from anthropogenic activities and decline of wildlife populations persist, while conservation efforts in most PAs are still minimal. We assessed the impact level of the most common threats to wildlife within PAs in tropical Africa and the relationship of conservation activities with threat impact level. We collated data on 98 PAs with tropical forest cover from 15 countries across West, Central and East Africa. For this, we assembled information about local threats as well as conservation activities from published and unpublished literature, and questionnaires sent to long-term field workers. We constructed general linear models to test the significance of specific conservation activities in relation to the threat impact level. Subsistence and commercial hunting were identified as the most common direct threats to wildlife and found to be most prevalent in West and Central Africa. Agriculture and logging represented the most common indirect threats, and were most prevalent in West Africa. We found that the long-term presence of conservation activities (such as law enforcement, research and tourism) was associated with lower threat impact levels. Our results highlight deficiencies in the management effectiveness of several PAs across tropical Africa, and conclude that PA management should invest more into conservation activities with long-term duration.Additional co-authors: Jef Dupain, Atanga Ekobo, Manasseh Eno-Nku, Gilles Etoga, Takeshi Furuichi, Sylvain Gatti, Andrea Ghiurghi, Chie Hashimoto, John A. Hart, Josephine Head, Martin Hega, Ilka Herbinger, Thurston C. Hicks, Lars H. Holbech, Bas Huijbregts, Hjalmar S. Kühl, Inaoyom Imong, Stephane Le-Duc Yeno, Joshua Linder, Phil Marshall, Peter Minasoma Lero, David Morgan, Leonard Mubalama, Paul K. N'Goran, Aaron Nicholas, Stuart Nixon, Emmanuelle Normand, Leonidas Nziguyimpa, Zacharie Nzooh-Dongmo, Richard Ofori-Amanfo, Babafemi G. Ogunjemite, Charles-Albert Petre, Hugo J. Rainey, Sebastien Regnaut, Orume Robinson, Aaron Rundus, Crickette M. Sanz, David Tiku Okon, Angelique Todd, Ymke Warren, Volker Somme

Novel Psychiatric Disorder 6 Months After Traumatic Brain Injury in Children and Adolescents

OBJECTIVE: To investigate the factors predictive of novel psychiatric disorders in the interval 0-6 months following traumatic brain injury (TBI). METHODS: Children ages 5-14 years consecutively hospitalized for mild to severe TBI at five hospitals were recruited. Participants were evaluated at baseline (soon after injury) for pre-injury characteristics including psychiatric disorders, socioeconomic status (SES), psychosocial adversity, family function, family psychiatric history, and adaptive function. In addition to the psychosocial variables, injury severity and lesion location detected with acquisition of a research MRI were measured to develop a biopsychosocial predictive model for development of novel psychiatric disorders. Psychiatric outcome, including occurrence of a novel psychiatric disorder, was assessed 6 months after the injury. RESULTS: The recruited sample numbered 177 children, and 141 children (80%) returned for the six-month assessment. Of the 141 children, 58 (41%) developed a novel psychiatric disorder. In univariable analyses, novel psychiatric disorder was significantly associated with lower SES, higher psychosocial adversity, and lesions in frontal lobe locations, such as frontal white matter, superior frontal gyrus, inferior frontal gyrus, and orbital gyrus. Multivariable analyses found that novel psychiatric disorder was independently and significantly associated with frontal-lobe white matter, superior frontal gyrus, and orbital gyrus lesions. CONCLUSION: The results demonstrate that occurrence of novel psychiatric disorders following pediatric TBI requiring hospitalization is common and has identifiable psychosocial and specific biological predictors. However, only the lesion predictors were independently related to this adverse psychiatric outcome

Expanding NEON biodiversity surveys with new instrumentation and machine learning approaches

A core goal of the National Ecological Observatory Network (NEON) is to measure changes in biodiversity across the 30-yr horizon of the network. In contrast to NEON’s extensive use of automated instruments to collect environmental data, NEON’s biodiversity surveys are almost entirely conducted using traditional human-centric field methods. We believe that the combination of instrumentation for remote data collection and machine learning models to process such data represents an important opportunity for NEON to expand the scope, scale, and usability of its biodiversity data collection while potentially reducing long-term costs. In this manuscript, we first review the current status of instrument-based biodiversity surveys within the NEON project and previous research at the intersection of biodiversity, instrumentation, and machine learning at NEON sites. We then survey methods that have been developed at other locations but could potentially be employed at NEON sites in future. Finally, we expand on these ideas in five case studies that we believe suggest particularly fruitful future paths for automated biodiversity measurement at NEON sites: acoustic recorders for sound-producing taxa, camera traps for medium and large mammals, hydroacoustic and remote imagery for aquatic diversity, expanded remote and ground-based measurements for plant biodiversity, and laboratory-based imaging for physical specimens and samples in the NEON biorepository. Through its data science-literate staff and user community, NEON has a unique role to play in supporting the growth of such automated biodiversity survey methods, as well as demonstrating their ability to help answer key ecological questions that cannot be answered at the more limited spatiotemporal scales of human-driven surveys

Novel Oppositional Defiant Disorder 6 Months After Traumatic Brain Injury in Children and Adolescents

OBJECTIVE: The investigators aimed to assess predictive factors of novel oppositional defiant disorder (ODD) among children and adolescents in the first 6 months following traumatic brain injury (TBI). METHODS: Children ages 5-14 years who experienced a TBI were recruited from consecutive admissions to five hospitals. Testing of a biopsychosocial model that may elucidate the development of novel ODD included assessment soon after injury (baseline) of preinjury characteristics, including psychiatric disorders, adaptive function, family function, psychosocial adversity, family psychiatric history, socioeconomic status, injury severity, and postinjury processing speed (which may be a proxy for brain injury). MRI analyses were also conducted to examine potential brain lesions. Psychiatric outcome, including that of novel ODD, was assessed 6 months after the injury. RESULTS: A total of 177 children and adolescents were recruited for the study, and 134 who were without preinjury ODD, conduct disorder, or disruptive behavior disorder not otherwise specified (DBD NOS) returned for the 6-month assessment. Of those who returned 6 months postinjury, 11 (8.2%) developed novel ODD, and none developed novel conduct disorder or DBD NOS. Novel ODD was significantly associated with socioeconomic status, preinjury family functioning, psychosocial adversity, and processing speed. CONCLUSIONS: These findings show that an important minority of children with TBI developed ODD. Psychosocial and injury-related variables, including socioeconomic status, lower family function, psychosocial adversity, and processing speed, significantly increase risk for this outcome