POPULATION ASSESSMENT OF THE EFFICIENCY OF PROVIDING CONDITIONS FOR WELL-BEING AND SAFE INTERACTION OF MIGRANTS AND THE RECEPTION POPULATION

Migration processes are complex, multifaceted and have both positive and negative impact on various spheres of society and the state. From the experience of many countries, it can be noted that high migration dynamics can provoke and exacerbate tensions and hostility between migrants and the host population. This aspect makes it relevant to study the conditions for safe and reliable interaction between migrants and the host population. The article presents an analysis of sociological research in six border regions of Russia (n = 2452). The analysis of the effectiveness of providing conditions in the region for the safe and secure interaction of migrants and visitors, representatives of various nationalities and religions was based on six value judgments presented to the population. A general assessment of the effectiveness of the conditions of interaction is given and statistical differences are revealed in the context of socio-demographic characteristics (gender, age, territory).

Gaze-Head Input: Examining Potential Interaction with Immediate Experience Sampling in an Autonomous Vehicle

Autonomous vehicles (AV) increasingly allow drivers to engage in secondary tasks such as eating or working on a laptop and thus require easy and reliable interaction inputs to facilitate communication between the driver and the vehicle. However, drivers report feeling less in control when driving is no longer the primary task, which suggests that novel approaches for assessing satisfaction regarding AV decision-making are needed. Therefore, we propose an immediate experience sampling method (IESM) that learns driver preferences for AV actions. We also suggest gaze-head input (G-HI) as a novel input in an AV. G-HI provides a hands-free, remote, and intuitive input modality that allows drivers to interact with the AV while continuing to engage in non-driving related tasks. We compare G-HI with voice and touch inputs via IESM for two simulated driving scenarios. Our results report the differences among the three inputs in terms of system usability, reaction time, and perceived workload. It also reveals that G-HI is a promising candidate for AV input interaction, which could replace voice or touch inputs where those inputs could not be utilized. Variation in driver satisfaction and expectations for AV actions confirms the effectiveness of using IESM to increase drivers’ sense of control.

Anti- SARS-CoV-2 main protease complex (Mpro) activity of Palmatine

The Pandemic situation caused due to SARS-CoV-2 causing Coronavirus Disease (CoVID-19) around globe. Recent, COVID-19 main protease complex (Mpro), highly modulating enzyme in SARS-CoV-2 was reported for viral replication and transcription. This multifunctionality of Mpro attracts for identification of potential drug target. Considering impact, In silico analysis was performed for Palmatine alkaloid against Mpro. Naturally, present in Tinospora cordifolia, found effective against Cancer, HIV, viral infections, diabetics. In methods, physico-chemical analysis by ProtParam tool and Structure of Mpro was predicted by SWISS-MODEL Workspace homology modeling server. Superimposition Structure and significant equal QMQE, QSQE values were found for eight highly similar templates. Structural assessment validation by Ramachandran plot (97.67% favoured), Local Quality estimate ratio (>0.6) and higher QMEAN score (y-axis). Further, docking was performed with validated Mpro model by SwissDock server. Interaction with -8.281919 ΔG indicates reliable Interaction. Also, comparative docking reveals, most favoured Palmatine interaction. Thus, an attempt was made to find potent inhibitor for SARS-CoV-2, as there is no promising and specific anti-viral drug or vaccine available for prevention and treatment of infections. However, In Vitro studies are required. Toxicity studies reported against Palmatine for acute effect (135 mg/kg body weight) on mouse model LD 50.

Importance of Model Size in Quantum Mechanical Studies of DNA Intercalation

There is currently a dearth of effective computational tools to design nucleobase-targeting small molecules and molecular mechanics force-fields for nucleobases lag behind their protein-focused counterparts. While quantum chemical methods can provide reliable interaction energies for small molecule-nucleobase interactions, these come at a steep computational cost. As a first step toward refining available tools for predicting small molecule-nucleobase interactions, we assessed the convergence of DFT-computed interaction energies with increasing binding site model size. We find that while accurate intercalator interaction energies can be derived from binding site models featuring only the flanking nucleotides for uncharged intercalators that bind parallel to the DNA base pairs, errors remain significant even when including distant nucleotides for intercalators that are charged, exhibit groove-binding tails that engage in non-covalent interactions with distant nucleotides, or that bind perpendicular to the DNA base pairs. Consequently, binding site models that include at least three adjacent nucleotides are required to consistently predict converged binding energies. The computationally inexpensive HF-3c method is shown to provide reliable interaction energies and can be routinely applied to such large models.<br>

Importance of Model Size in Quantum Mechanical Studies of DNA Intercalation

There is currently a dearth of effective computational tools to design nucleobase-targeting small molecules and molecular mechanics force-fields for nucleobases lag behind their protein-focused counterparts. While quantum chemical methods can provide reliable interaction energies for small molecule-nucleobase interactions, these come at a steep computational cost. As a first step toward refining available tools for predicting small molecule-nucleobase interactions, we assessed the convergence of DFT-computed interaction energies with increasing binding site model size. We find that while accurate intercalator interaction energies can be derived from binding site models featuring only the flanking nucleotides for uncharged intercalators that bind parallel to the DNA base pairs, errors remain significant even when including distant nucleotides for intercalators that are charged, exhibit groove-binding tails that engage in non-covalent interactions with distant nucleotides, or that bind perpendicular to the DNA base pairs. Consequently, binding site models that include at least three adjacent nucleotides are required to consistently predict converged binding energies. The computationally inexpensive HF-3c method is shown to provide reliable interaction energies and can be routinely applied to such large models.<br>

Ecological stability and plasticity of maize hybrids in different groups of ripeness

Ecological stability and plasticity of maize hybrids in different groups of ripeness – Knezha 307, Knezha 435, Knezha 509 and Knezha M625 by the traits grain yield and length of the ear was evaluated. The ecological parameters were determined by using the method of Eberhart and Russell (1966) and of Pakudin and Lopatina (1984). In the period of study (2014-2017) the hybrids demonstrate different plasticity and stability by the examined traits. The results of the analysis of the variances demonstrate reliable differences of the hybrids and the conditions for the two traits and primarily reliable interaction genotype – environment. The variances of the regression Si2 of all hybrids for the trait grain yield reliably differ from their theoretical value which determines them as plastic, i.e. responsive to more favourable conditions of growth. According to the values of bi the hybrid Knezha 435 (bi<1) is stable by the trait grain yield, the hybrids Knezha 307 and Knezha M625 are with values of bi close to one and have relatively medium stability and Knezha 509 with bi>1 is unstable. With reliable values of Si2 for the trait length of the ear is only the hybrid Knezha M625. The ecological stability of the other hybrids was evaluated by the value of the coefficient of regression (bi). Increased stability by this trait is demonstrated by Knezha 435, followed by Knezha 509. Knezha 307 is with medium stability (bi=1.1) by the respective trait.

A Moment-Based Maximum Entropy Model for Fitting Higher-Order Interactions in Neural Data

Correlations in neural activity have been demonstrated to have profound consequences for sensory encoding. To understand how neural populations represent stimulus information, it is therefore necessary to model how pairwise and higher-order spiking correlations between neurons contribute to the collective structure of population-wide spiking patterns. Maximum entropy models are an increasingly popular method for capturing collective neural activity by including successively higher-order interaction terms. However, incorporating higher-order interactions in these models is difficult in practice due to two factors. First, the number of parameters exponentially increases as higher orders are added. Second, because triplet (and higher) spiking events occur infrequently, estimates of higher-order statistics may be contaminated by sampling noise. To address this, we extend previous work on the Reliable Interaction class of models [1] to develop a normalized variant that adaptively identifies the specific pairwise and higher-order moments that can be estimated from a given dataset for a specified confidence level. The resulting “Reliable Moment” model is able to capture cortical-like distributions of population spiking patterns. Finally, we show that, compared with the Reliable Interaction model, the Reliable Moment model infers fewer strong spurious higher-order interactions and is better able to predict the frequencies of previously unobserved spiking patterns.

Feasibility of interactive gesture control of a robotic microscope

Robotic devices become increasingly available in the clinics. One example are motorized surgical microscopes. While there are different scenarios on how to use the devices for autonomous tasks, simple and reliable interaction with the device is a key for acceptance by surgeons. We study, how gesture tracking can be integrated within the setup of a robotic microscope. In our setup, a Leap Motion Controller is used to track hand motion and adjust the field of view accordingly. We demonstrate with a survey that moving the field of view over a specified course is possible even for untrained subjects. Our results indicate that touch-less interaction with robots carrying small, near field gesture sensors is feasible and can be of use in clinical scenarios, where robotic devices are used in direct proximity of patient and physicians.