Nonlinear mirror instability

Slow dynamical changes in magnetic-field strength and invariance of the particles' magnetic moments generate ubiquitous pressure anisotropies in weakly collisional, magnetized astrophysical plasmas. This renders them unstable to fast, small-scale mirror and firehose instabilities, which are capable of exerting feedback on the macroscale dynamics of the system. By way of a new asymptotic theory of the early nonlinear evolution of the mirror instability in a plasma subject to slow shearing or compression, we show that the instability does not saturate quasilinearly at a steady, low-amplitude level. Instead, the trapping of particles in small-scale mirrors leads to nonlinear secular growth of magnetic perturbations, $\delta B/B \propto t^{2/3}$. Our theory explains recent collisionless simulation results, provides a prediction of the mirror evolution in weakly collisional plasmas and establishes a foundation for a theory of nonlinear mirror dynamics with trapping, valid up to $\delta B/B =O(1)$.Comment: 5 pages, submitte

Subproton-scale cascades in solar wind turbulence: driven hybrid-kinetic simulations

A long-lasting debate in space plasma physics concerns the nature of subproton-scale fluctuations in solar wind (SW) turbulence. Over the past decade, a series of theoretical and observational studies were presented in favor of either kinetic Alfv\'en wave (KAW) or whistler turbulence. Here, we investigate numerically the nature of the subproton-scale turbulent cascade for typical SW parameters by means of unprecedented high-resolution simulations of forced hybrid-kinetic turbulence in two real-space and three velocity-space dimensions. Our analysis suggests that small-scale turbulence in this model is dominated by KAWs at $\beta\gtrsim1$ and by magnetosonic/whistler fluctuations at lower $\beta$. The spectral properties of the turbulence appear to be in good agreement with theoretical predictions. A tentative interpretation of this result in terms of relative changes in the damping rates of the different waves is also presented. Overall, the results raise interesting new questions about the properties and variability of subproton-scale turbulence in the SW, including its possible dependence on the plasma $\beta$, and call for detailed and extensive parametric explorations of driven kinetic turbulence in three dimensions.Comment: 6 pages, 4 figures, accepted for publication in The Astrophysical Journal Letter

Differentiability of the value function without interiority assumptions

This paper studies first-order differentiability properties of the value function in concave dynamic programs. Motivated by economic considerations, we dispense with commonly imposed interiority assumptions. We suppose that the correspondence of feasible choices varies with the vector of state variables, and we allow the optimal solution to belong to the boundary of this correspondence. Under minimal assumptions we show that the value function is continuously differentiable. We then discuss this result in the context of several economic models.Constrained optimization, Value and policy functions, Differentiability, Envelope theorem, Shadow price

Metodología para Detección de Características Faciales con Fines de Reconocimiento de Emociones

Se cree que la detección de emociones podrá llevar a determinar el estado de _animo de una persona e incluso un posible fraude. La detección de rasgos faciales claves para la detección de una emoción son de fácil reconocimiento para los humanos, pero la dificultad crece cuando se realiza por medio de software. Por este motivo, la presente investigación aborda el problema de detección mediante varias técnicas, identificando una en especial basada en las proporciones _áureas la cual robustece la detección de rasgos faciales y por consiguiente la detección de la emoción; guardando siempre unas medidas de incertidumbre racionales.It is believed that the detection of emotions could lead to determine the mood of a person or even a possible fraud. The detection of key facial features to detect emotions are of easy recognition for humans, but the diffculty increases when is done by software. For this reason, this investigation addresses the problem of detection of emotions through several techniques, identifying one in particular based on the golden proportions, which strengthens the detection of facial features and therefore the detection of emotion, keeping rational measures of uncertainty

Towards a Classifier to Recognize Emotions Using Voice to Improve Recommendations

[EN] The recognition of emotions in tone voice is currently a tool with a high potential when it comes to making recommendations, since it allows to personalize recommendations using the mood of the users as information. However, recognizing emotions using tone of voice is a complex task since it is necessary to pre-process the signal and subsequently recognize the emotion. Most of the current proposals use recurrent networks based on sequences with a temporal relationship. The disadvantage of these networks is that they have a high runtime, which makes it difficult to use in real-time applications. On the other hand, when defining this type of classifier, culture and language must be taken into account, since the tone of voice for the same emotion can vary depending on these cultural factors. In this work we propose a culturally adapted model for recognizing emotions from the voice tone using convolutional neural networks. This type of network has a relatively short execution time allowing its use in real time applications. The results we have obtained improve the current state of the art, reaching 93.6% success over the validation set.This work is partially supported by the Spanish Government project TIN2017-89156-R, GVA-CEICE project PROMETEO/2018/002, Generalitat Valenciana and European Social Fund FPI grant ACIF/2017/085, Universitat Politecnica de Valencia research grant (PAID-10-19), and by the Spanish Government (RTI2018-095390-B-C31).Fuentes-López, JM.; Taverner-Aparicio, JJ.; Rincón Arango, JA.; Botti Navarro, VJ. (2020). Towards a Classifier to Recognize Emotions Using Voice to Improve Recommendations. Springer. 218-225. https://doi.org/10.1007/978-3-030-51999-5_18S218225Balakrishnan, A., Rege, A.: Reading emotions from speech using deep neural networks. Technical report, Stanford University, Computer Science Department (2017)Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9, 1735–1780 (1997)Kerkeni, L., Serrestou, Y., Mbarki, M., Raoof, K., Mahjoub, M.: Speech emotion recognition: methods and cases study, pp. 175–182 (2018)McCluskey, K.W., Albas, D.C., Niemi, R.R., Cuevas, C., Ferrer, C.: Cross-cultural differences in the perception of the emotional content of speech: a study of the development of sensitivity in Canadian and Mexican children. Dev. Psychol. 11(5), 551 (1975)Paliwal, K.K.: Spectral subband centroid features for speech recognition. In: Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing. ICASSP 1998 (Cat. No. 98CH36181), vol. 2, pp. 617–620. IEEE (1998)Paulmann, S., Uskul, A.K.: Cross-cultural emotional prosody recognition: evidence from Chinese and British listeners. Cogn. Emot. 28(2), 230–244 (2014)Pépiot, E.: Voice, speech and gender: male-female acoustic differences and cross-language variation in English and French speakers. Corela Cogn. Représent. Lang. (HS-16) (2015)Picard, R.W., et al.: Affective computing. Perceptual Computing Section, Media Laboratory, Massachusetts Institute of Technology (1995)Rincon, J., de la Prieta, F., Zanardini, D., Julian, V., Carrascosa, C.: Influencing over people with a social emotional model. Neurocomputing 231, 47–54 (2017)Russell, J.A., Lewicka, M., Niit, T.: A cross-cultural study of a circumplex model of affect. J. Pers. Soc. Psychol. 57(5), 848 (1989)Schuller, B., Rigoll, G., Lang, M.: Hidden Markov model-based speech emotion recognition, vol. 2, pp. 401–404 (2003)Schuller, B., Villar, R., Rigoll, G., Lang, M.: Meta-classifiers in acoustic and linguistic feature fusion-based affect recognition, vol. 1, pp. 325–328 (2005)Thompson, W., Balkwill, L.-L.: Decoding speech prosody in five languages. Semiotica 2006, 407–424 (2006)Tyagi, V., Wellekens, C.: On desensitizing the Mel-cepstrum to spurious spectral components for robust speech recognition. In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP 2005, vol. 1, pp. I–529. IEEE (2005)Ueda, M., Morishita, Y., Nakamura, T., Takata, N., Nakajima, S.: A recipe recommendation system that considers user’s mood. In: Proceedings of the 18th International Conference on Information Integration and Web-based Applications and Services, pp. 472–476. ACM (2016)Zhang, B., Quan, C., Ren, F.: Study on CNN in the recognition of emotion in audio and images. In: 2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS), pp. 1–5, June 201

Angiotensin II and growth factors in the pathogenesis of diabetic nephropathy

Angiotensin II and growth factors in the pathogenesis of diabetic nephropathy. The renin-angiotensin system (RAS) and growth factors mediate structural and functional changes during the course of diabetic nephropathy (DN). Studies in humans and experimental models with DN suggest their involvement in the development and progression of DN. Activation of renal tissue RAS and increased expression of growth factors have been demonstrated at early stages of the disease. Angiotensin II and growth factors alter renal hemodynamics and exert trophic changes in renal cells that eventually result in fibrosis through direct mechanisms or through the release of other mediators. Their effects are likely modulated by metabolic changes including high glucose and free fatty acids. While blockade of the RAS ameliorates DN in humans, such evidence for blockade of growth factors is still lacking. It is likely that susceptibility to the development of DN and therapeutic efficacy are modulated by genetic polymorphisms in components of the RAS and growth factors including their receptors and other target molecules. Approaches to understand the intricate relationship between these systems and the mechanism(s) by which they alter capillary permeability and result in structural changes are areas of fruitful investigation

Interleukin-12 is not essential for silicosis in mice

BACKGROUND: Silicosis features foci of inflammation where macrophages and lymphocytes precede and accompany fibroblast proliferation, alveolar epithelial hyperplasia, and increased deposition of connective tissue matrix material. In the mouse following silica inhalation there is recruitment of natural killer-, B-, and CD4(+ )and CD8(+ )lymphocytes to the alveolar spaces, enlargement of bronchial-associated lymphoid tissues (BALT), and aggregation of lymphocytes surrounding small airways and blood vessels. A substantial fraction of the recruited lung lymphocytes produce interferon-γ (IFN-γ), and IFN-γ gene-deleted mice develop less silicosis than wild-type mice. Interleukin-12 (IL-12) is an important pathway for driving the adaptive immune response towards a TH1-like phenotype. We hypothesized that IL-12 might stimulate lymphocyte activation and the up-regulation of IFN-γ, and consequently be an essential mediator for silicosis. RESULTS: C57Bl/6 wild-type (WT) and IL-12 deficient (IL-12 KO) mice were exposed to sham-air or crystobalite silica (61 mg/m(3)) by inhalation for 5 hours/day for 12 days and then studied from 1 to 112 days after exposure. Mice exposed to sham-air had normal lung histology at all time points. WT mice exposed to titanium dioxide (72 mg/m(3)) showed pulmonary macrophage recruitment but no increase in lung collagen. Both WT and IL-12 KO mice exposed to silica showed similar progressive lung pathology, increased wet lung weight and increased total lung collagen (hydroxyproline). IL-12 p35 mRNA was not increased in either strain after silica exposure; IL-12 p40 mRNA was up-regulated after silica in WT mice and constitutively absent in the IL-12 KO mice. IL-18 mRNA was not increased after silica exposure. The expression of IL-15 (an important driver for innate immunity, Natural Killer cell activation, and IFN-γ production) was abundant in air-exposed mice and was increased slightly in the lungs of mice with silicosis. CONCLUSION: The axis of IL-12 driving IFN-γ production is not essential for the full manifestations of silicosis in mice exposed to a crystobalite silica aerosol

MHD simulations of the magnetorotational instability in a shearing box with zero net flux: the case Pm=4

This letter investigates the transport properties of MHD turbulence induced by the magnetorotational instability at large Reynolds numbers Re when the magnetic Prandtl number Pm is larger than unity. Three MHD simulations of the magnetorotational instability (MRI) in the unstratified shearing box with zero net flux are presented. These simulations are performed with the code Zeus and consider the evolution of the rate of angular momentum transport as Re is gradually increased from 3125 to 12500 while simultaneously keeping Pm=4. To ensure that the small scale features of the flow are well resolved, the resolution varies from 128 cells per disk scaleheight to 512 cells per scaleheight. The latter constitutes the highest resolution of an MRI turbulence simulation to date. The rate of angular momentum transport, measured using the alpha parameter, depends only very weakly on the Reynolds number: alpha is found to be about 0.007 with variations around this mean value bounded by 15% in all simulations. There is no systematic evolution with Re. For the best resolved model, the kinetic energy power spectrum tentatively displays a power-law range with an exponent -3/2, while the magnetic energy is found to shift to smaller and smaller scales as the magnetic Reynolds number increases. A couple of different diagnostics both suggest a well-defined injection length of a fraction of a scaleheight. The results presented in this letter are consistent with the MRI being able to transport angular momentum efficiently at large Reynolds numbers when Pm=4 in unstratified zero net flux shearing boxes.Comment: 5 pages, 4 figures, accepted in Astronomy and Astrophysic

ME3CA - Monitoring environment exercise and emotion by a cognitive assistant

The elderly population has increased dramatically in today’s society. This fact implies the need to propose new policies of attention to this group but without increasing social spending. Currently, there is a need to promote the care of elderly people in their own homes, avoiding being transferred to saturated residences. Bearing this in mind, in recent years numerous approaches have tried to offer solutions in this sense using the continuous advances in new information and communication technologies. In this way, this article proposes the employment of a personal assistant to help the elderly in the development of their daily life activities. The proposed system, called ME3CA, is a cognitive assistant that involves users in rehabilitating exercise, consisting of a sensorization platform and different integrated decision-making mechanisms. The system tries to plan and recommend activities to older people trying to improve their physical activity. In addition, in the decision making process the assistant takes into account the emotions of the user. In this way, the system is more personalized and emotionally intelligent.- (undefined

Digital literacy linked to engagement and psychological benefits among breast cancer survivors in Internet-based peer support groups

© 2019 John Wiley & Sons Ltd Objective: Internet-based peer support groups (ISGs) represent an innovative, scalable approach to addressing information and support needs of cancer survivors. However, this innovation may not benefit survivors equally due to population variance in digital literacy. This study examined how digital literacy influences level of engagement in and psychological benefits from participating in ISGs for breast cancer (N = 183). Methods: Secondary analysis of data from a randomised trial of ISGs that included behavioural measures of engagement, subjective ratings and psychological distress symptoms. Results: Digital literacy was positively related to education level (p =.005). Relative to women with high digital literacy, those with lower digital literacy were more likely to report difficulties using the ISG and to value the user's guide and facilitator assistance (all p's <.05). Digital literacy was negatively correlated with computer anxiety pre-intervention, distress before and after online chat during the intervention and post-intervention depressive symptoms (all p's <.05). Conclusion: Low digital literacy is associated with computer anxiety and barriers to ISG use, as well as distress during and after ISG use. Digital literacy must be taken into account when designing or delivering innovative digital interventions for cancer survivors