nils-herrmann/clean_scirepeval huggingface dataset:
It's a matter of time: Reframing the development of cognitive control as a modification of the brain's temporal dynamics
Venue: Developmental Cognitive Neuroscience

Cognitive control is a process that unfolds over time and regulates thought and action in the service of achieving goals and managing unanticipated challenges. Prevailing accounts attribute the protracted development of this mental process to incremental changes in the functional organization of a cognitive control network. Here, we challenge the notion that cognitive control is linked to a topologically static network, and argue that the capacity to manage unanticipated challenges and its development should instead be characterized in terms of inter regional functional coupling dynamics. Ongoing changes in temporal coupling have long represented a fundamental pillar in both empirical and theoretical based accounts of brain function, but have been largely ignored by traditional neuroimaging methods that assume a fixed functional architecture. There is, however, a growing recognition of the importance of temporal coupling dynamics for brain function, and this has led to rapid innovations in analytic methods. Results in this new frontier of neuroimaging suggest that time varying changes in connectivity strength and direction exist at the large scale and further, that network patterns, like cognitive control process themselves, are transient and dynamic.
Changes in cortico subcortical and subcortico subcortical connectivity impact cognitive control to emotional cues across development.
Venue: Social cognitive and affective neuroscience

The capacity to suppress inappropriate thoughts, emotions and actions in favor of appropriate ones shows marked changes throughout childhood and adolescence. Most research has focused on pre frontal circuit development to explain these changes. Yet, subcortical circuitry involving the amygdala and ventral striatum (VS) has been shown to modulate cue triggered motivated behaviors in rodents. The nature of the interaction between these two subcortical regions in humans is less well understood, especially during development when there appears to be heightened sensitivity to emotional cues. In the current study, we tested how task based cortico subcortical and subcortico subcortical functional connectivity in 155 participants ages from 5 to 32 impacted cognitive control performance on an emotional go/nogo task. Functional connectivity between the amygdala and VS was inversely correlated with age and predicted cognitive control to emotional cues, when controlling for performance to neutral cues. In contrast, increased medial pre frontal amygdala connectivity was associated with better cognitive control to emotional cues and this cortical subcortical connectivity mediated the association between amygdala VS connectivity and emotional cognitive control. These findings suggest a dissociation in how subcortical subcortical and cortical subcortical connectivity impact cognitive control across development.
The Impact of Emotional States on Cognitive Control Circuitry and Function
Venue: Journal of Cognitive Neuroscience

Typically in the laboratory, cognitive and emotional processes are studied separately or as a stream of fleeting emotional stimuli embedded within a cognitive task. Yet in life, thoughts and actions often occur in more lasting emotional states of arousal. The current study examines the impact of emotions on actions using a novel behavioral paradigm and functional neuroimaging to assess cognitive control under sustained states of threat (anticipation of an aversive noise) and excitement (anticipation of winning money) Thirty eight healthy adult participants were scanned while performing an emotional go/no go task with positive (happy faces) negative (fearful faces) and neutral (calm faces) emotional cues, under threat or excitement. Cognitive control performance was enhanced during the excited state relative to a nonarousing control condition. This enhanced performance was paralleled by heightened activity of frontoparietal and frontostriatal circuitry. In contrast, under persistent threat, cognitive control was diminished when the valence of the emotional cue conflicted with the emotional state. Successful task performance in this conflicting emotional condition was associated with increased activity in the posterior cingulate cortex, a default mode network region implicated in complex processes such as processing emotions in the context of self and monitoring performance. This region showed positive coupling with frontoparietal circuitry implicated in cognitive control, providing support for a role of the posterior cingulate cortex in mobilizing cognitive resources to improve performance. These findings suggest that emotional states of arousal differentially modulate cognitive control and point to the potential utility of this paradigm for understanding effects of situational and pathological states of arousal on behavior.
Primate cognition: attention, episodic memory, prospective memory, self control, and metacognition as examples of cognitive control in nonhuman primates.
Venue: Wiley interdisciplinary reviews. Cognitive science

Primate Cognition is the study of cognitive processes, which represent internal mental processes involved in discriminations, decisions, and behaviors of humans and other primate species. Cognitive control involves executive and regulatory processes that allocate attention, manipulate and evaluate available information (and, when necessary, seek additional information) remember past experiences to plan future behaviors, and deal with distraction and impulsivity when they are threats to goal achievement. Areas of research that relate to cognitive control as it is assessed across species include executive attention, episodic memory, prospective memory, metacognition, and self control. Executive attention refers to the ability to control what sensory stimuli one attends to and how one regulates responses to those stimuli, especially in cases of conflict. Episodic memory refers to memory for personally experienced, autobiographical events. Prospective memory refers to the formation and implementation of future intended actions, such as remembering what needs to be done later. Metacognition consists of control and monitoring processes that allow individuals to assess what information they have and what information they still need, and then if necessary to seek information. Self control is a regulatory process whereby individuals forego more immediate or easier to obtain rewards for more delayed or harder to obtain rewards that are objectively more valuable. The behavioral complexity shown by nonhuman primates when given tests to assess these capacities indicates psychological continuities with human cognitive control capacities. However, more research is needed to clarify the proper interpretation of these behaviors with regard to possible cognitive constructs that may underlie such behaviors.  resources related to this article, please visit the WIREs website.
Cognitive Control and Anxious Arousal in Worry and Generalized Anxiety: An Initial Test of an Integrative Model
Venue: Cognitive Therapy and Research

Pathological worry is thought to persist, in part, because it fosters avoidance of unpleasant internal experience. However, current models disagree as to whether worry serves that function because: (1) it suppresses high levels of autonomic arousal (AA) symptoms or (2) it leads to persistent heightened AA symptoms. In fact, pathological worry and generalized anxiety disorder (GAD) are linked to both high and low levels of AA symptoms. To account for this heterogeneity, we propose an integrative model, which predicts that AA symptoms vary as a function of the worrier's capacity to perform the subtle cognitive maneuver necessary to avoid such arousal. We review evidence supporting this model and report an initial test in a large college sample. Our results provide clear support for the major premise of our model: AA symptoms in worry and GAD vary as a function of individual differences in cognitive control capacity.
Measurement of software size: Contributions of cosmic to estimation improvements

This paper presents 1) an outline of the design of COSMIC, the 2 nd generation of functional size measurement methods; 2) industry evidence that COSMIC has met its primary design goal to be of practical value in software project performance measurement and estimating; 3) industry evidence of the method's automation, including full automation with very high accuracy for real time embedded software specified in a Matlab Simulink environment and developed through a global network of software contractors.
The evolution of energy law and energy jurisprudence: Insights for energy analysts and researchers

Energy law is gaining prominence among legal subjects. In the three spheres of academic, professional and public life, there is an increasing realization of the potential importance of energy law. The underlying objective of this paper is to contribute to the creation of a theory of energy law through advancing what this should encompass. Energy law has addressed particular issues in the energy sector but it has not had a holistic view of the sector, in particular, concerning the issue of energy waste management, which remains a serious problem. The conditions for a more holistic approach to manage energy resources are emerging and in the future it may be expected that energy law will have a core theoretical framework. This framework is important as it will in essence provide energy law with a 'spirit' or a raison d'etre The theory proposed here is on the Evolution of Energy Law and the centre point of this theoretical perspective is that to date there have been Five Stages in the Evolution of Energy Law In understanding what have been the key stages (or drivers) in the development of energy law it will give the energy law scholar an understanding of the motivation(s) behind the formulation of energy law.
Intuitive Jurisprudence: Early Reasoning About the Functions of Punishment

Traditional research on lay beliefs about punishment is often hampered by the complex nature of the question and its implications. We present a new intuitive jurisprudence approach that utilizes the insights of developmental psychology to shed light on the origins of punishment intuitions, along with the first empirical study to test the approach. Data from 80 child participants are presented, providing evidence that children expect punishment to serve as a specific deterrent, but finding no evidence that children expect punishment to have a general deterrent or rehabilitative effect. We also find that children understand punishment in a way that is consistent with the expressive theory of law and with expressive retributivism, and we present evidence that an understanding of the value of punishment to the social contract develops throughout childhood. Finally, we discuss the application of the intuitive jurisprudence approach to other important legal questions.
A Novel Cluster Arrangement Energy Efficient Routing Protocol for Wireless Sensor Networks

Wireless sensor networks are application based networks designed by large number of sensor nodes. Utilizing the energy in efficient way is the one of the main design issue in Wireless Sensor Network (WSN) Limited battery capacity of sensor nodes makes energy efficiency a major and challenging problem in wireless sensor networks.  In order to improve Network lifetime, Energy efficiency and Load balance in Wireless Sensor Network, a Cluster Arrangement Energy Efficient Routing Protocol CAERP is proposed. It mainly includes efficient way of node clustering and distributed multi hop routing. In the clustering part of CAERP we introduce an un even clustering mechanism. Cluster head which are closer to the Base Station (BS) have smaller cluster size than those farther from BS, so in here they can preserve some energy in the time of inter cluster data communication. Our protocol consists of cluster head selection algorithm, a cluster formation scheme and a routing algorithm for the data transmission between cluster heads and the base station.  Each sensor node should effectively handle its energy in order to keep the WSN at its operation state. In each time duration Q leach is consume more energy than the CAERP. CAERP eliminate the initial dead node problem. During the initial stage the message overhead between the Q Leach and CAERP have somewhat similar, but after the uneven clustering formation the CAERP message overhead is reduced comparing with the Q LEACH. In CAERP protocol it mainly focuses for utilizing the energy in efficient way. This improvement is accomplished because the nodes remain alive due to the efficient way of cluster arrangement. CAERP has mainly five cluster Head so each cycle the Cluster Head varying based on the CAERP CH selection algorithm. Due to efficient CH selection algorithm the CAERP have high network life time compared to Q LEACH. The simulation result shows that CAERP significantly increasing the network lifetime and minimizes energy consumption of nodes compared with Q leach protocol.  The performance of the proposed protocol is compared with that of Q LEACH using different parameters with the help network simulators. Our protocol CAERP has significantly improved in average energy consumption, survival rate and the extended the network life cycle which means the energy efficiency of the CAERP network is improved.
Aromatic hydrocarbon production by catalytic pyrolysis of palm kernel shell waste using a bifunctional Fe/HBeta catalyst: effect of lignin derived phenolics on zeolite deactivation

Conversion of lignin to aromatic hydrocarbons over zeolites is a challenging issue due to low reactivity of lignin derived phenolic compounds over zeolites as well as their high potential for strong adsorption on zeolite acid sites. Hence, pure zeolites are not appropriate catalysts for upgrading of the lignocellulosic biomass with high content of lignin. In this research, a bifunctional Fe/HBeta catalyst showed to be efficient for production of aromatic hydrocarbons in catalytic pyrolysis of palm kernel shell waste with a high lignin content of about 50 wt% Lignin derived phenolics were deoxygenated through a hydrogenolysis reaction promoted by Fe active sites. A comparison between catalytic behaviour of HBeta and HZSM 5 in conversion of palm kernel shells showed that catalyst deactivation via occupation of zeolite acid sites by lignin derived phenolics is affected by catalyst pore size and strength of zeolite acid sites. Meanwhile, cellulose and lignin were compared in terms of reactivity over zeolite acid sites and influence on zeolite deactivation. It was also shown that the yield of aromatic hydrocarbons obtained from conversion of lignin was remarkably enhanced by incorporation of iron into the HBeta structure. However, both HBeta and Fe/HBeta resulted in approximately similar aromatic yield from conversion of cellulose.
Insights into the Major Reaction Pathways of Vapor Phase Hydrodeoxygenation of m Cresol on a Pt/HBeta Catalyst

Conversion of m cresol was studied on a Pt/HBeta catalyst at 225 350 degC and ambient hydrogen pressure. At 250 degC, the reaction proceeds through two major reaction pathways: (1) direct deoxygenation to toluene (DDO path) (2) hydrogenation of m cresol to methylcyclohexanone and methylcyclohexanol on Pt, followed by fast dehydration on Bronsted acid sites (BAS) to methylcyclohexene, which is either hydrogenated to methylcyclohexane on Pt or ring contracted to dimethylcyclopentanes and ethylcyclopentane on BAS (HYD path) The initial hydrogenation is the rate determining step of the HYD path as its rate is significantly lower than those of subsequent steps. The apparent activation energy of the DDO path is 49.7 kJ mol 1 but the activation energy is negative for the HYD path. Therefore, higher temperatures lead to the DDO path becoming the dominant path to toluene, whereas the HYD path, followed by fast equilibration to toluene, is less dominant, owing to the inhibition of the initial hydrogenation of m cresol.
Comparative Effects of Two Metacognitive Instructional Strategies on Gender and Students' Problem Solving Ability in Selected Chemistry Concepts

Successful chemistry learning in secondary schools involves students' ability to solve chemistry problems irrespective of their sex. Metacognitive instructional strategies have been found to be effective in this direction. However, the comparative effects of analogies and concept mapping strategies on male and female students' problem solving ability in tasks involving mole, electrolysis and stoichiometry have not been documented. The study aimed at finding out if male and female students differ in their problem solving ability when taught the three concepts using analogies, concept maps and lecture method. 96 students were randomly selected, pre tested and assigned into control, and two experimental groups. The control group was taught using lecture method, while the experimental groups were taught using analogy and concept mapping respectively. Three instruments, Chemistry Achievement Test (CAT) Mathematical Skill Test (MST) and Chemistry Problem Solving Test (CPST) were developed and use. Students' posttest mean scores in the CPST were analyzed using t test and ANOVA (at 0.05 level) Results showed that there were no significant differences between the posttest mean scores of male and female students taught using concept mapping. However, there was a significant difference between the posttest mean scores of the male and female students taught using analogies. In each of male and female groups, there was a significant difference between the students taught with concept maps and those taught with analogies. The study recommended the use of concept mapping strategy for teaching both male and female students problem solving tasks in electrolysis, mole and stoichiometry
Working Memory Capacity and Self Explanation Strategy Use Provide Additive Problem Solving Benefits

The present study examined the impact of working memory capacity (WMC) on college students' ability to solve probability problems while using a self explanation strategy. Participants learned to solve probability problems in one of three conditions: a backward faded self explanation condition, an example problem pairs self explanation condition, or a control (no self explanation) condition. Even when accounting for the impact of WMC, learning to problem solve using self explanation led to superior problem solving performance. Conditions that prompted self explanation during problem solving resulted in significantly better problem solving performance than the control condition. These findings provide insight into the influence of individual differences on problem solving when strategies are provided, as well as information about the effectiveness of the self explanation strategy during mathematical problem solving.
In vitro germination and shoot proliferation of the threatened species Cinchona officinalis L (Rubiaceae)
Venue: Journal of Forestry Research

Cinchona officinalis (Rubiaceae) is an endemic species of the Loja Valley in southern Ecuador with medicinal uses. Because of over exploitation in the nineteenth century and more recent disturbances to its ecosystem, C. officinalis populations are threatened. Currently, natural regeneration of the populations is low, despite its high plant regeneration and seed formation capacity. In the present study, an efficient protocol for germination, shoot proliferation and plantlets regeneration was developed for this species. Phenolic content and germination rate of C. officinalis seeds were compared with a control species, C. pubescens. Nodal segments from seedlings of C. officinalis were cultured on Gamborg medium supplemented with different combinations of plant growth regulators. Because the phenol content is high in C. officinalis, the phenolic should be removed with hydrogen peroxide or water washes to stimulate germination. Shoots and callus developed from nodal segments within 45 days using most of the tested combinations of plant growth regulators. The best rates of shoot proliferation, callus formation and adventitious buds were obtained in medium supplemented with 5.0 mg L 1 6 benzyl aminopurine and 3.0 mg L 1 indole 3 butyric acid.
In Vitro Callus Induction of Duroia Macrophylla Huber, Chemical Prospection and Biotechnological Potentialities of Its Extracts

The Amazonian wild tree species Duroia Macrophylla (Rubiaceae) produces triterpenes and alkaloids, some of them showed antituberculosis and antitumoral activities. This paper describes the in vitro establishment and callus induction of Duroia Macrophylla leaf explants, preparation of callus extracts and the chemical analysis to verify the presence of alkaloids and terpenes in it. Young leaf explants were established in vitro with 50% of asepsis, being the best disinfestation method with immersion of 5 h at biocide solution (fungicidal and bactericidal) 3 min in 70% ethanol and 15 min in sodium hypochlorite 2% Once established, the explants in vitro were induced to callus formation process by adding the growth regulators kinetin and 2,4 dichlorophenoxyacetic acid, on Murashige and Skoog medium. In vitro callus were extracted with hexane and methanol and the presence of secondary metabolites was assessed by thin layer chromatography and 1H NMR analysis. Preliminary chemical analysis suggests that both callus extract of D. macrophylla did not contain alkaloids, but terpenes. Thus, more studies are needed to induce the production of alkaloids in D. macrophylla callus, where the use of elicitors, or other methods, may induce the production of these metabolites in callus, as alkaloids and terpenes showed antituberculosis and antitumoral activities, what are potential of (social and economics) uses with bioprospection activities. This is the first report of D. macrophylla callus induction and the chemical prospection of its extracts.
Artificial Neural Network and Its Application in Steel Industry

The recent developments in computational intelligence has enhances the applicability of empirical modelling in different areas particularly in the area of machine learning. These new approaches are based on analysing the data about a system, in particular finding connections between the system state variables (input, internal and output variables) without having precise knowledge about the physical behaviour of the system. These data driven methods explain advances on conventional empirical modelling and include contributions from many overlapping fields like Artificial Intelligence (AI) Computational Intelligence (CI) Soft Computing (SC) Machine Learning (ML) Intelligent Data Analysis (IDA) and Data Mining (DM) The most popular computational intelligence techniques used in process modelling of steel industry includes neural networks, fuzzy rule based systems, genetic algorithms as well as approaches to model integration. This chapter describes mainly the application of Artificial Neural Network (ANN) in steel industry. ANN has extensively used in improving and controlling different processes of steel industry like steel making, casting and rolling which lead to indirect energy savings through reduced product rejects, improved productivity and reduced down time. The efficiency of artificial neural network tool in handling steel plant processes has been discussed in detail. ANN based models are found to be very potential to handle very complex, dynamic and non linear problems.