nils-herrmann/clean_scirepeval huggingface dataset:
Compensation for PKMz in long term potentiation and spatial long term memory in mutant mice
Venue: eLife

PKMz is a persistently active PKC isoform proposed to maintain late LTP and long term memory. But late LTP and memory are maintained without PKMz in PKMz null mice. Two hypotheses can account for these findings. First, PKMz is unimportant for LTP or memory. Second, PKMz is essential for late LTP and long term memory in wild type mice, and PKMz null mice recruit compensatory mechanisms. We find that whereas PKMz persistently increases in LTP maintenance in wild type mice, PKCi/l, a gene product closely related to PKMz, persistently increases in LTP maintenance in PKMz null mice. Using a pharmacogenetic approach, we find PKMz antisense in hippocampus blocks late LTP and spatial long term memory in wild type mice, but not in PKMz null mice without the target mRNA. Conversely, a PKCi/l antagonist disrupts late LTP and spatial memory in PKMz null mice but not in wild type mice. Thus, whereas PKMz is essential for wild type LTP and long term memory, persistent PKCi/l activation compensates for PKMz loss in PKMz null mice.
Mass Spectrometric Investigation of Silicon Extremely Enriched in (28)Si: From (28)SiF4 (Gas Phase IRMS) to (28)Si Crystals (MC ICP MS)
Venue: Analytical chemistry

A new generation of silicon crystals even further enriched in (28)Si (x((28)Si) 0.999 98 mol/mol) recently produced by companies and institutes in Russia within the framework of a project initiated by PTB, were investigated with respect to their isotopic composition and molar mass M(Si) A modified isotope dilution mass spectrometric (IDMS) method treating the silicon as the matrix containing a so called virtual element (VE) existing of the isotopes (29)Si and (30)Si solely and high resolution multicollector inductively coupled plasma mass spectrometry (MC ICP MS) were applied in combination. This method succeeds also when examining the new materials holding merely trace amounts of (29)Si (x((29)Si) 5 x 10( 6) mol/mol) and (30)Si (x((30)Si) 7 x 10( 7) mol/mol) extremely difficult to detect with lowest uncertainty. However, there is a need for validating the enrichment in (28)Si already in the precursor material of the final crystals, silicon tetrafluoride (SiF4) gas prior to crystal production. For that purpose, the isotopic composition of selected SiF4 samples was determined using a multicollector magnetic sector field gas phase isotope ratio mass spectrometer. Contaminations of SiF4 by natural silicon due to storing and during the isotope ratio mass spectrometry (IRMS) measurements were observed and quantified. The respective MC ICP MS measurements of the corresponding crystal samples show in contrast several advantages compared to gas phase IRMS. M(Si) of the new crystals were determined to some extent with uncertainties urel(M) 1 x 10( 9) This study presents a clear dependence of the uncertainty urel(M(Si) on the degree of enrichment in (28)Si. This leads to a reduction of urel(M(Si) during the past decade by almost 3 orders of magnitude and thus further reduces the uncertainty of the Avogadro constant NA which is one of the preconditions for the redefinition of the SI unit kilogram.
Terrain Based GPS Independent Lane Level Vehicle Localization Using Particle Filter and Dead Reckoning
Venue: 2016 IEEE 84th Vehicular Technology Conference (VTC Fall)

The need of accurate and reliable positioning in various location aware safety critical transportation applications is increasing day by day. The Global Positioning System (GPS) is not able to provide lane level vehicle localization without the aid of differential corrections. It also suffers from signal outages in urban areas resulting in a complete loss of location information. Therefore, GPS independent localization methods are now being developed. In this domain, inertial sensors along with a terrain map have been successfully deployed to achieve sub meter level accuracy in the longitudinal direction of the vehicle in an urban environment. However, lateral localization of the vehicle with good accuracy and computational efficiency remains a challenging topic. Existing algorithms are computationally intensive, and do not provide location information during the process of lane change by the vehicle. This information is very crucial as the risk of potential conflict with nearby vehicles is higher during lane changes. In this paper, we present a computationally efficient method for achieving lane level localization in a multi lane scenario by combining the particle filter with dead reckoning. The particle filter provides the location information about a single lane while location information during the lane change maneuvers is provided by dead reckoning. Lane change maneuvers are detected by constantly observing the yaw rate of the vehicle. Developing a computationally efficient algorithm enables the GPS independent localization algorithm to be run on low cost micro controllers making its deployment feasible for packaged devices. Experiments performed on an instrumented vehicle show the superiority of the proposed algorithm on the existing ones.
Should compulsive sexual behavior be considered an addiction?
Venue: Addiction

To review the evidence base for classifying compulsive sexual behavior (CSB) as a non substance or 'behavioral' addiction.  Data from multiple domains (e.g. epidemiological, phenomenological, clinical, biological) are reviewed and considered with respect to data from substance and gambling addictions.  Overlapping features exist between CSB and substance use disorders. Common neurotransmitter systems may contribute to CSB and substance use disorders, and recent neuroimaging studies highlight similarities relating to craving and attentional biases. Similar pharmacological and psychotherapeutic treatments may be applicable to CSB and substance addictions, although considerable gaps in knowledge currently exist.  Despite the growing body of research linking compulsive sexual behavior (CSB) to substance addictions, significant gaps in understanding continue to complicate classification of CSB as an addiction.
Less is more: prolonged intermittent access cocaine self administration produces incentive sensitization and addiction like behavior
Venue: Psychopharmacology

RationaleContemporary animal models of cocaine addiction focus on increasing the amount of drug consumption to produce addiction like behavior. However, another critical factor is the temporal pattern of consumption, which in humans is characterized by intermittency, both within and between bouts of use.ObjectiveTo model this, we combined prolonged access to cocaine ~70 days in total) with an intermittent access (IntA) self administration procedure and used behavioral economic indicators to quantify changes in motivation for cocaine.ResultsIntA produced escalation of intake, a progressive increase in cocaine demand (incentive sensitization) and robust drug and cue induced reinstatement of drug seeking behavior. We also asked whether rats that vary in their propensity to attribute incentive salience to reward cues (sign trackers [STs] vs. goal trackers [GTs] vary in the development of addiction like behavior. Although STs were more motivated to take cocaine after limited drug experience, after IntA, STs and GTs no longer differed on any measure of addiction like behavior.ConclusionsExposure to large quantities of cocaine is not necessary for escalation of intake, incentive sensitization, or other addiction like behaviors (IntA results in far less total cocaine consumption than 'long access' procedures) Also, the ST phenotype may increase susceptibility to addiction, not because STs are inherently susceptible to incentive sensitization (perhaps all individuals are at risk) but because this phenotype promotes continued drug use, subjecting them to incentive sensitization. Thus, the pharmacokinetics associated with the IntA procedure are especially effective in producing a number of addiction like behaviors and may be valuable for studying associated neuroadaptations and for assessing individual variation in vulnerability.
Carrots and sticks fail to change behavior in cocaine addiction
Venue: Science

Punishment doesn't work in cocaine addicts Addiction is extremely difficult to treat, particularly cocaine use disorder. Animal experiments have led to the concept of drug addiction as abnormal goal directed learning and habit formation. Ersche et al. found that overtraining with positive reinforcement such as rewards made cocaine addicted patients less sensitive to the outcome of their actions. In contrast, overtraining on a punishment paradigm had no effect. Thus, habits may determine the behavior of cocaine users. Science, this issue p. 1468 Habits determine behavior in cocaine use disorder, even in the face of aversive consequences. Cocaine addiction is a major public health problem that is particularly difficult to treat. Without medically proven pharmacological treatments, interventions to change the maladaptive behavior of addicted individuals mainly rely on psychosocial approaches. Here we report on impairments in cocaine addicted patients to act purposefully toward a given goal and on the influence of extended training on their behavior. When patients were rewarded for their behavior, prolonged training improved their response rate toward the goal but simultaneously rendered them insensitive to the consequences of their actions. By contrast, overtraining of avoidance behavior had no effect on patient performance. Our findings illustrate the ineffectiveness of punitive approaches and highlight the potential for interventions that focus on improving goal directed behavior and implementing more desirable habits to replace habitual drug taking.
A meta analysis of the relationship between brain dopamine receptors and obesity: a matter of changes in behavior rather than food addiction?
Venue: International Journal of Obesity

Addiction to a wide range of substances of abuse has been suggested to reflect a 'Reward Deficiency Syndrome' That is, drugs are said to stimulate the reward mechanisms so intensely that, to compensate, the population of dopamine D2 receptors (DD2R) declines. The result is that an increased intake is necessary to experience the same degree of reward. Without an additional intake, cravings and withdrawal symptoms result. A suggestion is that food addiction, in a similar manner to drugs of abuse, decrease DD2R. The role of DD2R in obesity was therefore examined by examining the association between body mass index (BMI) and the Taq1A polymorphism, as the A1 allele is associated with a 30 40% lower number of DD2R, and is a risk factor for drug addiction. If a lower density of DD2R is indicative of physical addiction, it was argued that if food addiction occurs, those with the A1 allele should have a higher BMI. A systematic review found 33 studies that compared the BMI of those who did and did not have the A1 allele. A meta analysis of the studies compared those with (A1/A1 and A1/A2) or without (A2/A2) the A1 allele; no difference in BMI was found (standardized mean difference 0.004 (s.e. 0.021) variance 0.000, Z=0.196, P<0.845) It was concluded that there was no support for a reward deficiency theory of food addiction. In contrast, there are several reports that those with the A1 allele are less able to benefit from an intervention that aimed to reduce weight, possibly a reflection of increased impulsivity.
Modeling behavior of Computer Generated Forces with Machine Learning Techniques, the NATO Task Group approach
Venue: 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Commercial/Military Off The Shelf (COTS/MOTS) Computer Generated Forces (CGF) packages are widely used in modeling and simulation for training purposes. Conventional CGF packages often include artificial intelligence (AI) interfaces, but lack behavior generation and other adaptive capabilities. We believe Machine Learning (ML) techniques can be beneficial to the behavior modeling process, yet such techniques seem to be underused and perhaps under appreciated. This paper aims at bridging the gap between users in academia and the military/industry at a high level when it comes to ML and AI. We address specific requirements and desired capabilities for applying machine learning to CGF behavior modeling applications. The paper is based on the work of the NATO Research Task Group IST 121 RTG 060 Machine Learning Techniques for Autonomous Computer Generated Entities.
Assisted content based labelling and classification of documents
Venue: 2016 International Conference on Military Communications and Information Systems (ICMCIS)

The correct labelling of all information at its point of origin is a critical enabler for effective information access control in modern military systems. If information is not properly labeled it cannot be shared between different communities of interest and coalition partners, which affects the responsibility to share and potentially impedes ongoing military operations. This paper describes two experiments performed at the NATO Communications and Information Agency related to supporting correct labelling of both pre existing and newly created information objects. Two different techniques are used, one based on semantic analysis and the other on machine learning. Both approaches offer promising results in their respective use case scenarios, but require further development prior to operational deployment.
Anthropogenic land use stress alters community concordance at the river riparian interface

Organisms often respond in similar ways to environmental or spatial gradients, particularly at large spatial scales. Yet, while understanding these relationships is important for both basic and applied purposes, such as identifying surrogate taxa for conservation and monitoring purposes, patterns at finer scales and across ecotones are less certain. Our central aim was to explore patterns in community concordance at the river riparian interface and examine whether concordance was decoupled by increasing anthropogenic stress (a gradient of local land use intensity) We explored this at 15 sites over three years within the LTER site, Rhine Main Observatory, a low mountain river system in central Germany, assessing concordance between four organism groups: riparian spiders and carabid beetles, benthic macroinvertebrates, and combined aquatic macrophytes and riparian plants. This represented three different linkages: (1) predator prey, (2) direct competition, and (3) habitat associations. While there were no correlations in richness patterns, multivariate community structure was highly concordant between all groups. Anthropogenic stress strongly reduced links between riparian spiders and carabid beetles, likely resulting from their shared resource requirements. However, increasing concordance generally occurred between plants and other groups, although inconsistently between the three groups. We posit that patterns may be resulting from two processes: (1) linkages between directly competing species decouple with increasing anthropogenic stress, and (2) stronger coupling may occur between habitat providers and dependent species when overall habitat complexity is reduced. Our results highlight the complex manner in which anthropogenic stress can influence ecosystem structure, particularly at small scales. Based on these complexities, we recommend considering the full suite of community data to adequately explore biodiversity patterns or when searching for surrogate taxa.
Habitat Characterization for Submerged and Floating Leaved Aquatic Vegetation in Coastal River Deltas of Mississippi and Alabama

Habitat attributes of submerged aquatic vegetation and floating leaved aquatic vegetation were analyzed from survey data collected in estuaries and coastal river systems of Mississippi and Mobile Bay, Alabama. The objectives were to: locate aquatic plant beds along tidally influenced areas and characterize landscape parameters of the sites; group the plant species into a manageable number of logical clusters; and characterize the landscape attributes indicative of the plant communities through Classification and Regression Tree (CART) analysis. Based on the cluster analyses, aquatic vegetation was categorized into three groups: (1) downstream estuarine/saline group, (2) brackish tolerant freshwater species group, and (3) upstream freshwater only group. Landscape features used for habitat characterization and plant classification were defined by long term environmental conditions which would shape plant communities, rather than water quality parameters, such as water transparency and salinity, that exhibit higher variability and reflect the discrete conditions at time of sampling. The CART results suggest that salinity and "energy" (relative exposure to waves/currents) are the two most important abiotic factors that structure plant communities in the river deltas studied. Atributos del habitat de vegetacion acuatica sumergida y vegetacion acuatica con hojas flotantes fueron analizados a partir de los datos de encuestas recogidas en los estuarios y sistemas fluviales costeras de Mississippi y la bahia de Mobile, Alabama. Los objetivos fueron: localizar camas de plantas acuaticas a lo largo de las zonas influidas por las mareas y caracterizar los parametros del paisaje de los sitios; Agrupar las especies de plantas en un numero manejable de agrupaciones logicos; y caracterizar los atributos paisajisticos indicativos de las comunidades de plantas a traves del analisis de arboles de clasificacion y regresion (CART) Con base en los analisis de agrupaciones, la vegetacion acuatica se clasifico en tres grupos: (1) Grupo de aguas abajo del estuario solucion salina, (2) Grupo de especies de agua dulce tolerantes salobres, y (3) grupo de aguas arriba solamente agua dulce. Las caracteristicas del paisaje utilizadas para la caracterizacion del habitat y la clasificacion de plantas fueron definidas por las condiciones ambientales a largo plazo, que darian forma a las comunidades de plantas, en lugar de parametros de calidad del agua, tales como la transparencia del agua y la salinidad, que presentan una mayor variabilidad y reflejan las condiciones discretas en el momento del muestreo. Los resultados del CART analisis sugieren que la salinidad y "energia" (exposicion relativa a las ondas/corrientes) son los dos factores abioticos mas importantes que estructuran comunidades vegetales en los deltas de los rios estudiados.
Financial Development and International Trade

This paper studies the industry level and aggregate implications of financial development on international trade. I set up a multi industry general equilibrium model of international trade with heterogeneous firms subject to export entry costs and financial frictions, in which industries differ in their dependence on external finance. The model is parametrized to match key features of plant level data. I find that financial frictions have a large effect on the extent of international trade across industries, but a negligible impact at the aggregate level. I show that these findings are consistent with estimates from cross country industry and aggregate level data.
Introducing a New Broad Based Index of Financial Development

There is a vast body of literature estimating the impact of financial development on economic growth, inequality, and economic stability. A typical empirical study approximates financial development with either one of two measures of financial depth the ratio of private credit to GDP or stock market capitalization to GDP. However, these indicators do not take into account the complex multidimensional nature of financial development. The contribution of this paper is to create nine indices that summarize how developed financial institutions and financial markets are in terms of their depth, access, and efficiency. These indices are then aggregated into an overall index of financial development. With the coverage of 183 countries on annual frequency between 1980 and 2013, the database should offer a useful analytical tool for researchers and policy makers.
Identifying consumer buying preferences of beef

This study investigated the drivers which influence consumers' beef buying behavior. A validated questionnaire was used to collect the data and to evaluate consumer beef purchasing behavior. Exploratory factor analysis was employed to analyze the data while Cronbach alpha coefficient was used to calculate the reliability of the drivers. Satisfactory levels of reliability were recorded. The analysis identified eight drivers that influence the buying behavior of consumers when they purchase beef products. These drivers were: quality of the meat, buying preference, farming practices, intention to buy, health, convenience, packaging presentation and future purchase. In addition, correlational analysis indicates that additional important attributes to buying behavior are supplier characteristics and packaging presentation. The study culminates in a frame of reference for beef (and possibly other meat products) buying behavior analysis whilst it also provides a frame of reference for marketers to better understand their customers' behavior when they are selling beef. As a result it is recommended that retailers focus their actions on the more important beef purchasing drivers and that the study be repeated on a larger scale so that the results of the present study can either be confirmed or further refined.
Air Toxics Under the Big Sky: examining the effectiveness of authentic scientific research on high school students' science skills and interest
Venue: International journal of science education

Toxics Under the Big Sky is an environmental science outreach/education program that incorporates the Next Generation Science Standards (NGSS) 8 Practices with the goal of promoting knowledge and understanding of authentic scientific research in high school classrooms through air quality research. This research explored: (1) how the program affects student understanding of scientific inquiry and research and (2) how the open inquiry learning opportunities provided by the program increase student interest in science as a career path. Treatment students received instruction related to air pollution (airborne particulate matter) associated health concerns, and training on how to operate air quality testing equipment. They then participated in a yearlong scientific research project in which they developed and tested hypotheses through research of their own design regarding the sources and concentrations of air pollution in their homes and communities. Results from an external evaluation revealed that treatment students developed a deeper understanding of scientific research than did comparison students, as measured by their ability to generate good hypotheses and research designs, and equally expressed an increased interest in pursuing a career in science. These results emphasize the value of and need for authentic science learning opportunities in the modern science classroom.