Quantum Dissipation in a Neutrino System Propagating in Vacuum and in Matter

Considering the neutrino state like an open quantum system, we analyze its propagation in vacuum or in matter. After defining what can be called decoherence and relaxation effects, we show that in general the probabilities in vacuum and in constant matter can be written in a similar way, which is not an obvious result in this approach. From this result, we analyze the situation where neutrinos evolution satisfies the adiabatic limit and use this formalim to study solar neutrinos. We show that the decoherence effect may not be bounded by the solar neutrino data and review some results in the literature. We discuss the current results where solar neutrinos were used to put bounds on decoherence effects through a model-dependent approach. We conclude explaining how and why this models are not general and we reinterpret these constraints.Comment: new version: title was changend and was added a table. To appear at Nucl. Physic.

On the Effects of Quantum Decoherence in a Future Supernova Neutrino Detection

Quantum decoherence effects in neutrinos, described by the open quantum systems formalism, serve as a gateway to explore potential new physics, including quantum gravity. Previous research extensively investigated these effects across various neutrino sources, imposing stringent constraints on the spontaneous loss of coherence. In this study, we demonstrate that even within the Supernovae environment, where neutrinos are released as incoherent states, quantum decoherence could influence the flavor equipartition of $3\nu$ mixing. Additionally, we examine the potential energy dependence of quantum decoherence parameters ($\Gamma = \Gamma_0 (E/E_0)^n$) with different power laws ($n = 0, 2, 5/2$). Our findings indicate that future-generation detectors (DUNE, Hyper-K, and JUNO) can significantly constrain quantum decoherence effects under different scenarios. For a Supernova located 10 kpc away from Earth, DUNE could potentially establish $3\sigma$ bounds of $\Gamma \leq 6.2 \times 10^{-14}$ eV in the normal mass hierarchy (NH) scenario, while Hyper-K could impose a $2\sigma$ limit of $\Gamma \leq 3.6 \times 10^{-14}$ eV for the inverted mass hierarchy (IH) scenario with $n=0$ - assuming no energy exchange between the neutrino subsystem and non-standard environment ($[H,V_p] = 0$). These limits become even more restrictive for a closer Supernova. When we relax the assumption of energy exchange ($[H,V_p] \neq 0$), for a 10 kpc SN, DUNE can establish a $3\sigma$ limit of $\Gamma_8 \leq 4.2 \times 10^{-28}$ eV for NH, while Hyper-K could constrain $\Gamma_8 \leq 1.3 \times 10^{-27}$ eV for IH ($n=0$) with $2\sigma$, representing the most stringent bounds reported to date. Furthermore, we examine the impact of neutrino loss during propagation for future Supernova detection

An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus

Hybrid models to detect dementia based on Machine Learning can provide accurate diagnoses in individuals with neurological disorders and cognitive complications caused by Human Immunodeficiency Virus (HIV) infection. This study proposes a hybrid approach, using Machine Learning algorithms associated with the multicriteria method of Verbal Decision Analysis (VDA). Dementia, which affects many HIV-infected individuals, refers to neurodevelopmental and mental disorders. Some manuals standardize the information used in the correct detection of neurological disorders with cognitive complications. Among the most common manuals used are the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, 5th edition) of the American Psychiatric Association and the International Classification of Diseases, 10th edition (ICD-10)—both published byWorld Health Organization (WHO). The model is designed to explore the predictive of specific data. Furthermore, a well-defined database data set improves and optimizes the diagnostic models sought in the research.info:eu-repo/semantics/publishedVersio

Hybrid model for early identification post-Covid-19 sequelae

Artificial Intelligence techniques based on Machine Learning algorithms, Neural Networks and Naïve Bayes can optimise the diagnostic process of the SARS-CoV-2 or Covid-19. The most significant help of these techniques is analysing data recorded by health professionals when treating patients with this disease. Health professionals' more specific focus is due to the reduction in the number of observable signs and symptoms, ranging from an acute respiratory condition to severe pneumonia, showing an efficient form of attribute engineering. It is important to note that the clinical diagnosis can vary from asymptomatic to extremely harsh conditions. About 80% of patients with Covid-19 may be asymptomatic or have few symptoms. Approximately 20% of the detected cases require hospital care because they have difficulty breathing, of which about 5% may require ventilatory support in the Intensive Care Unit. Also, the present study proposes a hybrid approach model, structured in the composition of Artificial Intelligence techniques, using Machine Learning algorithms, associated with multicriteria methods of decision support based on the Verbal Decision Analysis methodology, aiming at the discovery of knowledge, as well as exploring the predictive power of specific data in this study, to optimise the diagnostic models of Covid-19. Thus, the model will provide greater accuracy to the diagnosis sought through clinical observation.info:eu-repo/semantics/publishedVersio

Host-defense peptides AC12, DK16 and RC11 with immunomodulatory activity isolated from Hypsiboas raniceps skin secretion

Inflammation is a natural defense mechanism of the immune system; however, when unregulated, it can lead to chronic illness. Glucocorticoids are the most commonly used agents to effectively treat inflammatory conditions, including autoimmune diseases, however these substances can trigger a number of side effects. Thus, viable alternatives to the use of these drugs would be advantageous. In this study, we have analyzed the anti-inflammatory profile of three synthetic peptides first identified in skin secretion of the tree frog Hypsiboas raniceps. Structural characterization was performed using NMR spectroscopy and Mass Spectrometry, and the peptides were tested in vitro in RAW 264.7 cells and in vivo in Balb/c mice for their functional properties. The samples did not show a significant antimicrobial profile. NMR spectroscopy indicated that AC12 (ACFLTRLGTYVC) has a disulfide bond between C2 and C11 and a β-sheet-turn-β-sheet conformation in aqueous solution. This peptide showed no cytotoxic effect in mammalian cells and it was the most effective in reducing anti-inflammatory markers, such as NO, TNF-α and IL-12. Peptide DK16 (DKERPICSNTFRGRKC) demonstrated anti-inflammatory properties in vitro, while RC11 (RCFRRRGKLTC) significantly altered the cell viability in RAW 264.7 but was shown to be safe in Balb/c erythrocytes. Our results indicate that, of the three peptides studied, AC12 is the most efficient in reducing anti-inflammatory markers, and it could be a potential agent for the treatment of inflammatory diseases.publishe

Effect of essential oil of Alpinia zerumbet on cardiovascular and autonomic function in rats with isoproterenol induced acute myocardial infarction

Abstract Alpinia zerumbet is a plant popularly used to treat hypertension and anxiety. Studies with Alpinia zerumbet demonstrate antihypertensive and vasodilator effects, among others. The objective of this study was to analyze the effect of essential oil of Alpinia zerumbet (EOAz) on cardiovascular and autonomic function in rats with isoproterenol-induced myocardial infarction. Male Wistar rats (n=32) were equally allocated into four groups: Control, ISO (150mg/kg, subcutaneous), EOAz (100mg/kg by gavage), ISO+EOAz. The rats were evaluated for cardiovascular and, autonomic parameters, electrocardiogram, and infarct size. EOAz was not able to reduce the electrocardiographic variations induced by ISO. Heart rate variability showed a decrease in sympathetic modulation on the heart in the groups treated with EOAz. The cardiopulmonary reflex induced by serotonin invoked a superior blood pressure variation at the 2 µg/kg dose in the EOAz treated groups, while the heart rate variation was significantly higher at the 16 µg/kg dose, when compared to other doses, in all groups, except EOAz+ISO. The sympathetic vagal index was higher in ISO group than in control. EOAz did not reduce the infarct size. We conclude that pretreatment with EOAz does not reverse the hemodynamic and electrocardiographic damage caused by isoproterenol but does reduce sympathetic modulation

Solar neutrinos: global analysis with day and night spectra from SNO

We perform global analysis of the solar neutrino data including the day and night spectra of events at SNO. In the context of two active neutrino mixing, the best fit of the data is provided by the LMA MSW solution with Delta m^2 = 6.15 10^{-5} eV^2, tan^2\theta = 0.41, f_B = 1.05, where f_B is the boron neutrino flux in units of the corresponding flux in the Standard Solar Model (SSM). At 3 sigma level we find the following upper bounds: tan^2\theta < 0.84 and Delta m^2 < 3.6 10^{-4} eV^2. From 1 sigma-interval we expect the day-night asymmetries of the charged current and electron scattering events to be: A_{DN}^{CC} = 3.9 +3.6-2.9 and A_{DN}^{ES} = 2.1 +2.1-1.4. The only other solution which appears at 3 sigma-level is the VAC solution with Delta m^2 = 4.5 10^{-10} eV^2, tan^2\theta = 2.1 and f_B=0.75. The best fit point in the LOW region, with Delta m^2 = 0.93 10^{-7} eV^2 and tan^2\theta = 0.64, is accepted at 99.95% (3.5 sigma) C.L. . The least chi^2 point from the SMA solution region, with Delta m^2 = 4.6 10^{-6} eV^2 and tan^2\theta = 5 10^{-4}, could be accepted at 5.5 sigma-level only. In the three neutrino context the influence of theta_{13} is studied. We find that with increase of theta_{13} the LMA best fit point shifts to larger Delta m^2, mixing angle is practically unchanged, and the quality of the fit becomes worse. The fits of LOW and SMA slightly improve. Predictions for KamLAND experiment (total rates, spectrum distortion) have been calculated.Comment: Typos corrected, reference adde

Dilatação dos confins: caminhos, vilas e cidades na formação da Capitania de São Paulo (1532-1822)

Este ensaio analisa a formação da rede urbana das capitanias de São Vicente e Santo Amaro, depois unidas na Capitania de São Paulo. Discute o processo de apropriação do sertão, a pulsação e dilatação dos confins ao sabor dos deslocamentos humanos e de interesses políticos. Interpreta o papel de capelas, freguesias, vilas e cidades no controle e produção de territórios metropolitanos em solos ultramarinos.This essay analyzes the development of urban networks in the Captaincies of São Vicente and Santo Amaro, later merged into the Captaincy of São Paulo. It discusses the process of appropriation of the sertão (backcountry), the commotion and expansion beyond the confines to the tune of population movements and political interests. The paper also interprets the role of chapels, parishes, villages and towns in initiatives to create and control metropolitan areas on overseas soil