The effects of verbal information on children's fear beliefs about social situations

Two experiments explored the role of verbal information in changing children’s fearrelated beliefs about social situations. In Experiment 1, 118 6- to 8- and 12- to 13-year-olds heard positive, negative, or no information about individuals’ experiences of three social situations. Fear beliefs regarding each situation were assessed before and after this manipulation. Verbal information had no significant influence on children’s fear beliefs. In Experiment 2, the same paradigm was used with 80 12- to 13-year-olds, but the information took the form of multiple attitude statements about the situations expressed by groups of peers, older children, or adults. An affective priming task of implicit attitudes was used to complement the explicit questions about fear beliefs. Negative information influenced both explicit and implicit fear beliefs. The source of information and the child’s own social anxiety did not moderate these effects. Implications for our understanding of the socialisation of childhood fears are discussed

Algorithm-assisted discovery of an intrinsic order among mathematical constants

In recent decades, a growing number of discoveries in fields of mathematics have been assisted by computer algorithms, primarily for exploring large parameter spaces that humans would take too long to investigate. As computers and algorithms become more powerful, an intriguing possibility arises - the interplay between human intuition and computer algorithms can lead to discoveries of novel mathematical concepts that would otherwise remain elusive. To realize this perspective, we have developed a massively parallel computer algorithm that discovers an unprecedented number of continued fraction formulas for fundamental mathematical constants. The sheer number of formulas discovered by the algorithm unveils a novel mathematical structure that we call the conservative matrix field. Such matrix fields (1) unify thousands of existing formulas, (2) generate infinitely many new formulas, and most importantly, (3) lead to unexpected relations between different mathematical constants, including multiple integer values of the Riemann zeta function. Conservative matrix fields also enable new mathematical proofs of irrationality. In particular, we can use them to generalize the celebrated proof by Ap\'ery for the irrationality of $\zeta(3)$. Utilizing thousands of personal computers worldwide, our computer-supported research strategy demonstrates the power of experimental mathematics, highlighting the prospects of large-scale computational approaches to tackle longstanding open problems and discover unexpected connections across diverse fields of science.Comment: 21 pages, 6 figures, and 1 table; with 9 appendix sections totaling 12 pages, 1 figure, and 4 table

Odderon and Pomeron from the Vacuum Correlator Method

Glueball masses with J<=7 are computed both for C=+1 and C=-1 using the string Hamiltonian derived in the framework of the Vacuum Correlator Method. No fitting parameters are used, and masses are expressed in terms of string tension $\sigma$ and effective value of $\alpha_s$. We extend the calculations done for J<=3 using the same Hamiltonian, which provided glueball masses in good agreement with existing lattice data, to higher mass states. It is shown that 3^{--}, 5^{--} and 7^{--} states lie on the odderon trajectories with the intercept around or below 0.14. Another odderon trajectory with 3g glueballs of Y-shape, corresponds to 11% higher masses and low intercept. These findings are in agreement with recent experimental data, setting limits on the odderon contribution to the exclusive $\gamma p$ reactions.Comment: 16 pages. Journal version. To be published in Phys.Lett.

Production technology estimates and balanced growth

Capital-labor substitution and TFP estimates are essential features of many economic models. Such models typically embody a balanced growth path. This often leads researchers to estimate models imposing stringent prior choices on technical change. We demonstrate that estimation of the substitution elasticity and TFP growth can be substantially biased if technical progress is thereby mis-specified. We obtain analytical and simulation results in the context of a model consistent with balanced and near-balanced growth (i.e., departures from balanced growth but broadly stable factor shares). Given this evidence, a Constant Elasticity of Substitution production function system is then estimated for the US economy. Results show that the estimated substitution elasticity tends to be significantly lower using a factor-augmenting specification (well below one). We are also able to reject conventional neutrality forms in favor of general factor augmentation with a non-negligible capital-augmenting component. Our work thus provides insights into production and supply-side estimation in balanced-growth frameworks

Optogenetics and deep brain stimulation neurotechnologies

Brain neural network is composed of densely packed, intricately wired neurons whose activity patterns ultimately give rise to every behavior, thought, or emotion that we experience. Over the past decade, a novel neurotechnique, optogenetics that combines light and genetic methods to control or monitor neural activity patterns, has proven to be revolutionary in understanding the functional role of specific neural circuits. We here briefly describe recent advance in optogenetics and compare optogenetics with deep brain stimulation technology that holds the promise for treating many neurological and psychiatric disorders

Percepciones de la comunicación no verbal y el liderazgo transformacional en docentes y estudiantes de un instituto superior privado de diseño gráfico de Lima en el periodo 2020-II

La presente investigación tiene como objetivo describir cuáles son las percepciones de la comunicación no verbal y el liderazgo transformacional en docentes y estudiantes de un Instituto Superior Privado de Diseño Gráfico de Lima, en el periodo 2020-II. La investigación tiene un enfoque de tipo cualitativo, alcance descriptivo y diseño fenomenológico. La población estuvo conformada por 35 estudiantes y 5 docentes de la carrera de Diseño Gráfico. El tipo de muestra fue no probabilística por conveniencia, por lo que se determinó trabajar con 13 estudiantes y 3 docentes, a quienes se les aplicó una entrevista. Los docentes y estudiantes perciben que emplean la comunicación no verbal. Sin embargo, los movimientos corporales empleados por los docentes no se alinean en su totalidad a la teoría y práctica de las categorías, dificultando la retroalimentación y comprensión de la clase. Al mejorar esto, ayudará a que el mensaje sea claro y preciso. Por otro lado, los docentes y estudiantes en su mayoría perciben el empleo del liderazgo transformacional que motiva a su desenvolvimiento a través de una comunicación abierta de manera individual y grupal. Sin embargo, otros, han percibido que aún hay vacíos de información, respuestas inconclusas que quiebran la confianza entre ambos para seguir con el vínculo en la clase. Se concluye que los docentes y estudiantes de un instituto superior de la carrera de diseño gráfico de Lima, perciben ambas variables con desconocimiento de lo que implica el uso de cada una de las categorías que lo componen mostrando ausencia de lo teórico y práctico.This research aims to describe the perceptions of non-verbal communication and transformational leadership in teachers of a Private Higher Institute of Graphic Design in Lima, in the period 2020-II. The research has a qualitative approach, descriptive scope and phenomenological design. The population consisted of 35 students and 5 teachers from the Graphic Design career. The type of sample was non-probabilistic for convenience; therefore, it was determined to work with 13 students and 3 teachers, who were interviewed. Teachers and students perceive that they use non-verbal communication. However, the body movements used by teachers do not fully align with the theory and practice of the categories, making feedback and understanding difficult in the class. By improving this, you will help make the message clear and accurate. Likewise, students perceive that their teachers use transformational leadership that motivates their development and confidence through open communication individually. The creative stimulation that teachers use to motivate their students with various tools is also perceived. On the other hand, teachers and students mostly perceive the use of transformational leadership that motivates their development through open communication individually and in groups. However, others have perceived that there are still information gaps, inconclusive answers that break the trust between both to continue with the bond in the class. It is concluded that teachers and students of a higher institute of the graphic design career in Lima, perceive both variables with ignorance of what the use of each of the categories that compose it implies, showing absence of the theoretical and practical.Escuela de Postgrad

ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset

Magnetic resonance imaging (MRI) is an important imaging modality in stroke. Computer based automated medical image processing is increasingly finding its way into clinical routine. The Ischemic Stroke Lesion Segmentation (ISLES) challenge is a continuous effort to develop and identify benchmark methods for acute and sub-acute ischemic stroke lesion segmentation. Here we introduce an expert-annotated, multicenter MRI dataset for segmentation of acute to subacute stroke lesions (https://doi.org/10.5281/zenodo.7153326). This dataset comprises 400 multi-vendor MRI cases with high variability in stroke lesion size, quantity and location. It is split into a training dataset of n = 250 and a test dataset of n = 150. All training data is publicly available. The test dataset will be used for model validation only and will not be released to the public. This dataset serves as the foundation of the ISLES 2022 challenge (https://www.isles-challenge.org/) with the goal of finding algorithmic methods to enable the development and benchmarking of automatic, robust and accurate segmentation methods for ischemic stroke

ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset.

Magnetic resonance imaging (MRI) is an important imaging modality in stroke. Computer based automated medical image processing is increasingly finding its way into clinical routine. The Ischemic Stroke Lesion Segmentation (ISLES) challenge is a continuous effort to develop and identify benchmark methods for acute and sub-acute ischemic stroke lesion segmentation. Here we introduce an expert-annotated, multicenter MRI dataset for segmentation of acute to subacute stroke lesions ( https://doi.org/10.5281/zenodo.7153326 ). This dataset comprises 400 multi-vendor MRI cases with high variability in stroke lesion size, quantity and location. It is split into a training dataset of n = 250 and a test dataset of n = 150. All training data is publicly available. The test dataset will be used for model validation only and will not be released to the public. This dataset serves as the foundation of the ISLES 2022 challenge ( https://www.isles-challenge.org/ ) with the goal of finding algorithmic methods to enable the development and benchmarking of automatic, robust and accurate segmentation methods for ischemic stroke

An adaptive version of k-medoids to deal with the uncertainty in clustering heterogeneous data using an intermediary fusion approach

This paper introduces Hk-medoids, a modified version of the standard k-medoids algorithm. The modification extends the algorithm for the problem of clustering complex heterogeneous objects that are described by a diversity of data types, e.g. text, images, structured data and time series. We first proposed an intermediary fusion approach to calculate fused similarities between objects, SMF, taking into account the similarities between the component elements of the objects using appropriate similarity measures. The fused approach entails uncertainty for incomplete objects or for objects which have diverging distances according to the different component. Our implementation of Hk-medoids proposed here works with the fused distances and deals with the uncertainty in the fusion process. We experimentally evaluate the potential of our proposed algorithm using five datasets with different combinations of data types that define the objects. Our results show the feasibility of the our algorithm, and also they show a performance enhancement when comparing to the application of the original SMF approach in combination with a standard k-medoids that does not take uncertainty into account. In addition, from a theoretical point of view, our proposed algorithm has lower computation complexity than the popular PAM implementation

Seasonal variation in the relative dominance of herbivore guilds in an African savanna

African savannas are highly seasonal with a diverse array of both mammalian and invertebrate herbivores, yet herbivory studies have focused almost exclusively on mammals. We conducted a 2-yr exclosure experiment in South Africa's Kruger National Park to measure the relative impact of these two groups of herbivores on grass removal at both highly productive patches (termite mounds) and in the less productive savanna matrix. Invertebrate and mammalian herbivory was greater on termite mounds, but the relative importance of each group changed over time. Mammalian offtake was higher than invertebrates in the dry season, but can be eclipsed by invertebrates during the wet season when this group is more active. Our results demonstrate that invertebrates play a substantial role in savanna herbivory and should not be disregarded in attempts to understand the impacts of herbivory on ecosystems