The Conventional Gait Model’s Sensitivity to Lower-limb Marker Placement

Clinical gait analysis supports treatment decisions for patients with motor disorders. Measurement reproducibility is affected by extrinsic errors such as marker misplacement—considered the main factor in gait analysis variability. However, how marker placement affects output kinematics is not completely understood. The present study aimed to evaluate the Conventional Gait Model’s sensitivity to marker placement. Using a dataset of kinematics for 20 children, eight lower-limb markers were virtually displaced by 10 mm in all four planes, and all the displacement combinations were recalculated. Root-mean-square deviation angles were calculated for each simulation with respect to the original kinematics. The marker movements with the greatest impact were for the femoral and tibial wands together with the lateral femoral epicondyle marker when displaced in the anterior–posterior axis. When displaced alone, the femoral wand was responsible for a deviation of 7.3° (± 1.8°) in hip rotation. Transversal plane measurements were affected most, with around 40% of simulations resulting in an effect greater than the acceptable limit of 5°. This study also provided insight into which markers need to be placed very carefully to obtain more reliable gait data.

Implications of AlphaFold2 for crystallographic phasing by molecular replacement

The AlphaFold2 results in the 14th edition of Critical Assessment of Structure Prediction (CASP14) showed that accurate (low root-mean-square deviation) in silico models of protein structure domains are on the horizon, whether or not the protein is related to known structures through high-coverage sequence similarity. As highly accurate models become available, generated by harnessing the power of correlated mutations and deep learning, one of the aspects of structural biology to be impacted will be methods of phasing in crystallography. Here, the data from CASP14 are used to explore the prospects for changes in phasing methods, and in particular to explore the prospects for molecular-replacement phasing using in silico models.

Investigating errors when forecasting processes with uncertain dynamics and observation noise by the self-adjusting brown's zero-order model

This paper reports a study into the errors of process forecasting under the conditions of uncertainty in the dynamics and observation noise using a self-adjusting Brown's zero-order model. The dynamics test models have been built for predicted processes and observation noises, which make it possible to investigate forecasting errors for the self-adjusting and adaptive models. The test process dynamics were determined in the form of a rectangular video pulse with a fixed unit amplitude, a radio pulse of the harmonic process with an amplitude attenuated exponentially, as well as a video pulse with amplitude increasing exponentially. As a model of observation noise, an additive discrete Gaussian process with zero mean and variable value of the mean square deviation was considered. It was established that for small values of the mean square deviation of observation noise, a self-adjusting model under the conditions of dynamics uncertainty produces a smaller error in the process forecast. For the test jump-like dynamics of the process, the variance of the forecast error was less than 1 %. At the same time, for the adaptive model, with an adaptation parameter from the classical and beyond-the-limit sets, the variance of the error was about 20 % and 5 %, respectively. With significant observation noises, the variance of the error in the forecast of the test process dynamics for the self-adjusting and adaptive models with a parameter from the classical set was in the range from 1 % to 20 %. However, for the adaptive model, with a parameter from the beyond-the-limit set, the variance of the prediction error was close to 100 % for all test models. It was established that with an increase in the mean square deviation of observation noise, there is greater masking of the predicted test process dynamics, leading to an increase in the variance of the forecast error when using a self-adjusting model. This is the price for predicting processes with uncertain dynamics and observation noises.

GNSS-IR Measurements of Inter Annual Sea Level Variations in Thule, Greenland from 2008–2019

Studies of global sea level often exclude Tide Gauges (TGs) in glaciated regions due to vertical land movement. Recent studies show that geodetic GNSS stations can be used to estimate sea level by taking advantage of the reflections from the ocean surface using GNSS Interferometric Reflectometry (GNSS-IR). This method has the immediate benefit that one can directly correct for bedrock movements as measured by the GNSS station. Here we test whether GNSS-IR can be used for measurements of inter annual sea level variations in Thule, Greenland, which is affected by sea ice and icebergs during much of the year. We do this by comparing annual average sea level variations using the two methods from 2008–2019. Comparing the individual sea level measurements over short timescales we find a root mean square deviation (RMSD) of 13 cm, which is similar to other studies using spectral methods. The RMSD for the annual average sea level variations between TG and GNSS-IR is large (18 mm) compared to the estimated uncertainties concerning the measurements. We expect that this is in part due to the TG not being datum controlled. We find sea level trends from GNSS-IR and TG of −4 and −7 mm/year, respectively. The negative trend can be partly explained by a gravimetric decrease in sea level as a result of ice mass changes. We model the gravimetric sea level from 2008–2017 and find a trend of −3 mm/year.

Temporary characteristics of heart rate variability in medical workers of obstetric institutions

Hygienic working conditions and the labor process affect the functional state of the body of workers and reflect in the performance indicators of the cardiovascular system. The study aims to learn the temporal characteristics of heart rate variability in doctors and nursing staff of second-and third-level obstetric institutions. Scientists examined 228 people of higher and secondary medical personnel with the help of the Varikard 2.51 hardware and software complex. In the dynamics of the working shift, we studied the mean square deviation of the cardiac intervals R-R; the square root of the sum of the differences of a sequential series of NN intervals; the voltage index of regulatory systems. We researched the basis of maternity institutions of the second and third levels in some cities of the Central Federal District: Ryazan, Kolomna, Lipetsk, Smolensk. The data obtained during the study of the features of the regulatory potential of medical workers of various professional groups allowed us to understand the influence of factors of the labor process on adaptive resources, estimated by the indicators of the time analysis of heart rate variability (HRV). The researchers obtained statistically significant differences in time indicators of heart rate variability (the mean square deviation of cardiac intervals R-R; the square root of the sum of the differences of a consecutive series of NN intervals; stress index of regulatory systems) in professional groups of obstetricians, gynecologists, neonatologists, midwives, anesthesiologists, as well as ward nurses of perinatal centers and maternity hospitals in the dynamics of the work shift. It is possible to use the results of the conducted research to develop scientifically based recommendations for the prevention of professionally caused overstrain of adaptive systems of the body.

Evaluating the thickness of thin-bed seams using seismic data on the example of the Tula-Bobrikovian sediments in the Republic of Tatarstan

Background. Determining the productive deposit thickness is of fundamental importance for assessing the reserves of oil and gas fields. 3D seismic data is used to assess the thickness of seams in the interwell space. However, owing to the limited vertical resolution of seismic data, estimating thicknesses of thin deposits (less than 20 m) is challenging.Aim. To evaluate different approaches to calculating the thickness of the productive deposits based on seismic data with the purpose of selecting the most optimal approach.Materials and methods. We compared the results obtained using different approaches to assessing the productive deposit thickness of the Tula-Bobrikovian age in the interwell space, including the convergence method (calculating the thickness for oilwells with no seismic data used), the use of seismic attributes to calculate the “seismic attribute — reservoir thickness” dependency (for attributes, dominant frequency and mono-frequency component at 60 Hz), estimation of the thickness from the seismic signal shape. Cokriging was used to calculate inferred power maps from seismic attribute data and to classify them by waveform. For each of the techniques, the crossvalidation method and calculating the root-mean-square deviation were used as quality criteria.Results. When assessing the accuracy of thickness map development, the root-mean-square deviation was 12.3 m according to convergence method, 10.2 m — to the dominant frequency attribute, 7.2 m — to the attribute of the monofrequency component at 60 Hz and 6.3 m — to the signal shape classification. The latter method yielded the best results, and the developed thickness map allowed paleo-cut to be traced.Conclusions. Applying the thickness estimation method based on the seismic signal shape allows the value of the root-mean-square deviation to be reduced by a factor of 2 compared to that of the widely adopted convergence method. This approach permits productive deposits thickness to be more accurately estimated and hydrocarbon reserves to be determined.

Brownian Motion and its Mathematical Applications in Medicine

Brownian motion is small particles suspended in a liquid tend to move in pseudorandom or stochastic paths through the liquid, even if the liquid in question is inert. By Einstein's theories for Brownian motion referring to the 1905 works, equilibrium relations and viscous friction, osmotic pressure reaching the diffusion coefficient of Brownian particles. In the fluid medium, we will address the deviation (diffusion equation and basically the relationship between the mean square deviation of the particle position and the fluid temperature, the higher the temperature, the greater the mean square deviation, that is, directly proportional to the constant of the diffusion). The importance of this study is the movement of particles and molecules in the fluid medium, whether these molecules are lipids, proteins, we know that viruses and bacteria are having a certain movement in the organism and its systems, we will tend to study their movement within vessels and between fluids body, with two densities and particular conditions, knowing the likely displacement, we will know therapeutic interventions that are probably more effective. The aim of this work is to demonstrate through mathematical applications the Brownian motion.

Analysis of Image Features and TCM Syndrome Types of Lobar Pneumonia in Children Based on Mean Square Deviation Lung CT Image Registration Algorithm

The aim was to analyze the application of computed tomography (CT) images in the diagnosis of lesions, and the composition of traditional Chinese medicine (TCM) syndromes in children with lobar pneumonia. Lung CT image registration algorithm was constructed based on optimized mean square deviation (OMSD) algorithm, which was applied to CT images of 188 children patients with lobar pneumonia before and after treatment. Besides, free-form deformation (FFD) algorithm and mean square deviation (MSD) algorithm were introduced for comparison with OMSD. Results showed that sum of squared differences (SSD) of OMSD was significantly lower than that of MSD and FFD ( P < 0.05 ). The mutual information (MI), relative overlap rate (ROR), and rcc of OMSD were markedly higher than those of MSD and FFD ( P < 0.05 ). After treatment, the number of pulmonary interstitial thickening, lobular interstitial thickening, ground-glass shadow, patchy shadow, consolidation shadow, pleural thickening, pleural effusion, lymphadenopathy, pneumothorax, and mediastinal emphysema decreased sharply in contrast to before treatment ( P < 0.05 ). Among the selected children, there were 184 children patients with empirical TCM syndrome, accounting for 97.85%, and its dominant syndrome was wind-heat closed lung syndrome (52.75%) and phlegm-heat closed lung syndrome (46.11%). The main symptoms of wind-heat closed and phlegm-heat closed lung syndrome were fever, cough, and pulmonary rales. In conclusion, OMSD was superior to MSD and FFD in lung CT image registration. CT registration image based on OMSD could clearly display the intrapulmonary and extrapulmonary manifestations of children patients, so as to enhance the clinical diagnosis effect. Besides, wind-heat closed lung syndrome and phlegm-heat closed lung syndrome were the common types of TCM syndrome of children pneumonia with the common symptoms of fever and cough.

The Treatment of Alzheimer’s Disease through Molecular Docking Studies using Phyltetralin against Kallikrein_6: A Bioinformatic Approach

Alzheimer's disease (AD) is a neurodegenerative disease that generally begins leisurely and gets worse with time. Alzheimer’s disease (AD) dementia is the specific beginning of age-related declination of cognitive abilities and function, which eventually leads to death. Alzheimer’s disease (AD) is one of the neurodeteriorating disorders which is one of the mostcritical complications that our current health care system faces. The phenomenon of molecular docking has progressively become a strong tool in the field of pharmaceutical research including drug discovery. The aim of the presentin silico study was to inhibit the expression of KLK-6 (kallikrein-6) which is a target or receptor protein by its interaction with three distinct secondary metabolites for treating Alzheimer's disease (AD) through molecular docking. Methods: The in-silico study was based on molecular docking. Docking was executed amidst ligands- Quercetin (CID: 5280343), Ricinoleic Acid (CID: 643684), Phyltetralin (CID: 11223782), and the target or receptor protein Kallikrein-6 (PDB ID: 1LO6). The protein and the ligands were downloaded in the required format. Through PyRx, the ligands were virtually screened after importing them in the PyRx window. The results of PyRx and SwissADME were analyzed and the best ligand was finalized. Among the three, Phyltetralin was the best ligand contrary to KLK-6 having minimum binding energy and it was following Lipinski’s five rules along with 0 violations. Results: The final docking was carried out between Phyltetralin and KLK-6 through AutoDock Vina. The outcome showed 9 poses with distinct binding energy, RSMD LB (root mean square deviation lower bound) and RSMD UB (root mean square deviation upper bound). With the help of PyMOL which is an open-access tool for molecular visualization, the interaction amidst Phyltetralin and KLK-6 can be visualized. Conclusion: Based on this in silico study it can be concluded that KLK-6 (kallikrein-6) which is responsible for causing AD can be inhibited by ligand Phyltetralin and for the treatment of AD, phyltetralin might act as a potential drug. Thus, in future studies, Phyltetralin from natural sources can prevent Alzheimer's disease and can be proved as a promising and efficient drug for treating Alzheimer's disease.