Fundamental energy scale of the thick brane in mimetic gravity

In this paper, thick branes generated by the mimetic scalar field with Lagrange multiplier formulation are investigated. We give three typical thick brane background solutions with different asymptotic behaviors and show that all the solutions are stable under tensor perturbations. The effective potentials of the tensor perturbations exhibit as volcano potential, Poöschl–Teller potential, and harmonic oscillator potential for the three background solutions, respectively. All the tensor zero modes (massless gravitons) of the three cases can be localized on the brane. We also calculate the corrections to the four-dimensional Newtonian potential. On a large scale, the corrections to the four-dimensional Newtonian potential can be ignored. While on a small scale, the correction from the volcano-like potential is more pronounced than the other two cases. Combining the specific corrections to the four-dimensional Newtonian potential of these three cases and the latest results of short-range gravity experiments, we get the constraint on the scale parameter as $$k > rsim 10^{-4}$$ k ≳ 10 - 4 eV, and constraint on the corresponding five-dimensional fundamental scale as $$M_* > rsim 10^5$$ M ∗ ≳ 10 5 TeV.

Fundamental Scale of Evaluation of Productivity of Irrigated Gray-Meadow Soils which are Appointed for Growing Melon Crops

In the following article, the basic scale for assessing the fertility of irrigated gray-meadow soils planted with melons is based on the mechanical composition of the soil. The mechanical composition of the soil correlation coefficient between the yields of melons and gourds was 0.88 for watermelon, 0.89 for melon and 0.88 for pumpkin. Accordingly, light sandy soils for ground watermelon and squash were rated as productive with a score of 100 points, heavy sandy soils with a score of 85 points for watermelon and 75 points for pumpkin. For the melon crop, medium sandy soil was rated at 100 points, heavy sandy soil at 90 points, and light sandy soil at 75 points.

A Numerical Comparison of the Sensitivity of the Geometric Mean Method, Eigenvalue Method, and Best–Worst Method

In this paper, we compare three methods for deriving a priority vector in the theoretical framework of pairwise comparisons—the Geometric Mean Method (GMM), Eigenvalue Method (EVM) and Best–Worst Method (BWM)—with respect to two features: sensitivity and order violation. As the research method, we apply One-Factor-At-a-Time (OFAT) sensitivity analysis via Monte Carlo simulations; the number of compared objects ranges from 3 to 8, and the comparison scale coincides with Saaty’s fundamental scale from 1 to 9 with reciprocals. Our findings suggest that the BWM is, on average, significantly more sensitive statistically (and thus less robust) and more susceptible to order violation than the GMM and EVM for every examined matrix (vector) size, even after adjustment for the different numbers of pairwise comparisons required by each method. On the other hand, differences in sensitivity and order violation between the GMM and EMM were found to be mostly statistically insignificant.

Modern system approach to the diagnosis, therapy and rehabilitation of mental disorders

Introduction The current stage of research on mental disorders is associated with the use of system approaches to the development of the scientific foundations of psychiatric care. Objectives Approach to solving problems that arise in the diagnosis of psychopathological conditions, assessing their severity, as well as evaluating the effectiveness of psychosocial treatment and rehabilitation. Methods Clinical, psychometric, system analysis methods and algorithms of the Analytical Hierarchy Process (AHP) [1] were used. Results When assessing a patient's condition and behavior, it is necessary to make decisions (diagnosis, development of treatment and rehabilitation plans) based on heterogeneous information (genetic, neuronal and environmental, involving individual characteristics, as well as family and social context). This information is hierarchically organized and includes quantitative and qualitative data. Exposure at each of these different levels can affect the onset and course of the disease, and therefore should be considered in primary prevention and subsequent psychosocial therapy and rehabilitation of patients. Analysis of the problems of assessing psychopathological states and related psychosocial problems shows that these problems can be presented in the form of appropriate hierarchies, the structure of which must be taken into account when processing the initial information. The main advantages of the AHP include the use of the relationship scale (fundamental scale) for processing heterogeneous data based on expert, clinical information. Conclusions The approach provides correct integration of heterogeneous characteristics when considering diagnostic procedures, psychosocial therapy and rehabilitation.1. Mitikhin V.G., Solokhina T.A. S.S. Korsakov Journal of Neurology and Psychiatry, 2019, 2: 49-54. doi:10.17116/jnevro201911902149

Questioning the Meaning of a Change on the Alzheimer’s Disease Assessment Scale–Cognitive Subscale (ADAS-Cog): Noncomparable Scores and Item-Specific Effects Over Time

Longitudinal invariance indicates that a construct is measured over time in the same way, and this fundamental scale property is a sine qua non to track change over time using ordinary mean comparisons. The Alzheimer’s Disease Assessment Scale–cognitive (ADAS-Cog) and its subscale scores are often used to monitor the progression of Alzheimer’s disease, but longitudinal invariance has not been formally evaluated. A configural invariance model was used to evaluate ADAS-Cog data as a three correlated factors structure for two visits over 6 months, and four visits over 2 years (baseline, 6, 12, and 24 months) among 341 participants with Alzheimer’s disease. We also attempted to model ADAS-Cog subscales individually, and furthermore added item-specific latent variables. Neither the three-correlated factors ADAS-Cog model, nor its subscales viewed unidimensionally, achieved longitudinal configural invariance under a traditional modeling approach. No subscale achieved scalar invariance when considered unidimensional across 6 months or 2 years of assessment. In models accounting for item-specific effects, configural and metric invariance were achieved for language and memory subscales. Although some of the ADAS-Cog individual items were reliable, comparisons of summed ADAS-Cog scores and subscale scores over time may not be meaningful due to a lack of longitudinal invariance.

Cancer: Division by Zero

We propose a hypothesis for the cause at the quantum informational level for the insane multiplication of cancer cells at its most fundamental scale.

Probing an Extended Uncertainty Principle black hole with gravitational lensings

We study signals of the weak and strong deflection gravitational lensings by an Extended Uncertainty Principle (EUP) black hole, which is based on a modified Heisenberg relation with an additional correction of position-uncertainty. Gravitational lensing observables, including positions, magnifications and differential time delays between lensed images, are obtained in both scenarios and analyzed for the supermassive black holes (SMBHs) in the Galactic Center (Sgr A*) and M87. We find that, for Sgr A*, measurements on the separation between the primary and secondary images in the weak deflection lensing and the apparent size of the photon sphere in the strong deflection lensing are two feasible ways to constrain EUP, imposing comparable lower bounds on the fundamental scale of EUP as [Formula: see text][Formula: see text]1010 m. For the SMBH in M87, measurements on strong deflection lensing observables are only available and they can give a much bigger lower bound as [Formula: see text][Formula: see text]1013 m. These results might provide hints for probing EUP black holes by gravitational lensings.