Static Process Research Articles

Novel coumarin-thiazolidine-2,4‑dione hybrids as potential α-glucosidase inhibitors: Synthesis and bioactivity evaluation

To discover novel α-glucosidase inhibitors, a series of coumarin- thiazolidine-2,4‑dione hybrids (BJX1∼20) were synthesized and assessed their inhibitory activities against α-glucosidase. Compared to acarbose (IC50 = 655.01 ± 52.54 μM), coumarin-thiazolidinedione hybrids (BJX1∼20) displayed stronger α-glucosidase inhibitory activity, with IC50 values ranging from 5.12 ± 0.48 to 24.07 ± 1.96 μM. BJX3, BJX9, and BJX15 exhibited strongest inhibitory activities against α-glucosidase and acted as non-competitive inhibitors. The fluorescence quenching experiment revealed that the interaction between BJX3, BJX9, BJX15, and α-glucosidase followed a static binding process. CD spectra and 3D fluorescence spectra analysis revealed that the binding of BJX3, BJX9, and BJX15 to α-glucosidase induced a conformation change of α-glucosidase, thereby inhibiting its activity. Molecular docking simulation revealed the binding mechanism of BJX3, BJX9, and BJX15 with α-glucosidase. In vitro cytotoxicity assay indicated BJX15 (0∼64 μM) showed no obvious cytotoxicity against HEK 293 cells. In vivo experiments in mice demonstrated the ameliorative effect of orally administered BJX15 (50 mg kg-1) on postprandial hyperglycemia.

Searching of optimal conditions and development of analysis of isocyanate groups in prepolymers

The purpose of the work was to study the options for volumetric analysis of isocyanate groups in prepolymers and to search for factors affecting the accuracy of the analysis in order to identify differences between the values specified by the manufacturer and those obtained in the laboratory.Metods. Intermediate polymerization products based on isocyanates from two or more monomeric units used for the production of polyurethanes, the quality of which is determined by the optimal ratio of isocyanate and hydroxyl groups, were selected as the object of research. The NCO index was determined by the volumetric method based on the interaction of isocyanate groups with diethylamine, with confirmation of the results by methods of mathematical statistics.Results. the work analyzes currently known methods for determining the content of isocyanate groups in prepolymers and identifies differences in the technique of execution. A volumetric method for determining the NCO index based on the interaction of isocyanate groups with diethylamine was used. The solubility of industrial prepolymer samples was evaluated and the dissolution rate was calculated, on the basis of which the optimal volume of the solution and prepolymer samples were determined, providing an accurate determination of the isocyanate number. The adjusted conditions allowed us to reach the required value of the NCO index of the SKU prepolymer, calculated on the basis of static processing of the results and the construction of the Gauss distribution curve. Changes in the methodology make it possible to reach a certified value of the indicator, which allows its use for further calculations in the synthesis of polyurethane.Conclusion. Recommendations for determining the isocyanate index for the analysis of prepolymer by the volumetric method will help to monitor incoming raw materials for compliance with certificates to perform an accurate calculation of raw materials in the synthesis of polyurethane.Key words: prepolymer, polyurethane, isocyanate index, volumetric analysis, diethylamine, solubility.

Neural Encoding of Bodies for Primate Social Perception.

Primates, as social beings, have evolved complex brain mechanisms to navigate intricate social environments. This review explores the neural bases of body perception in both human and nonhuman primates, emphasizing the processing of social signals conveyed by body postures, movements, and interactions. Early studies identified selective neural responses to body stimuli in macaques, particularly within and ventral to the superior temporal sulcus (STS). These regions, known as body patches, represent visual features that are present in bodies but do not appear to be semantic body detectors. They provide information about posture and viewpoint of the body. Recent research using dynamic stimuli has expanded the understanding of the body-selective network, highlighting its complexity and the interplay between static and dynamic processing. In humans, body-selective areas such as the extrastriate body area (EBA) and fusiform body area (FBA) have been implicated in the perception of bodies and their interactions. Moreover, studies on social interactions reveal that regions in the human STS are also tuned to the perception of dyadic interactions, suggesting a specialized social lateral pathway. Computational work developed models of body recognition and social interaction, providing insights into the underlying neural mechanisms. Despite advances, significant gaps remain in understanding the neural mechanisms of body perception and social interaction. Overall, this review underscores the importance of integrating findings across species to comprehensively understand the neural foundations of body perception and the interaction between computational modeling and neural recording.

Insights into inhibitory action and interaction of bisdemethoxycurcumin on tyrosinase: Spectroscopic and docking analysis

Bisdemethoxycurcumin (BDMC), a demethoxy derivative of curcumin, has garnered interest for its potential anti-tyrosinase properties, which are crucial for applications in food preservation and cosmetic industries. Despite its recognized bioactive effects, the detailed inhibitory action and interaction of BDMC on tyrosinase and its application in anti-browning processes remain unclear. This study aims to dissect the molecular interactions of BDMC with tyrosinase, elucidate its inhibition mechanism, and assess its efficacy in preventing browning, thereby underpinning its potential as a natural anti-browning agent. Employing a battery of spectroscopic techniques, we characterized the interaction of BDMC with tyrosinase. The anti-browning properties of BDMC were evaluated on fresh-cut apples, and its effect on enzymatic activities related to browning was also investigated. The results indicate that BDMC interacts with tyrosinase in a reversible mixed-type inhibition manner with an IC50 value of 12.5 ± 0.2 μM. Surface Plasmon Resonance (SPR) results indicated that BDMC presented good binding affinity toward tyrosinase. Fluorescence quenching results showed that BDMC could quench the fluorescence of tyrosinase in a static process. Synchronous fluorescence, circular dichroism spectra, and three-dimensional fluorescence results indicated that interaction of BDMC against tyrosinase resulted in changes of tyrosinase on microenvironment and conformation, thus causing decrease of tyrosinase activity. Copper-chelating results presented that BDMC could chelate to copper with stoichiometric ratio of 1: 2. Molecular docking provided intricate details of how BDMC interacted with tyrosinase. Moreover, BDMC exhibited anti-browning capability on fresh cut apples, and could regulate PPO, POD, and APX activities. The comprehensive analysis proposed in this study consolidated the theoretical basis of BDMC as a tyrosinase inhibitor and supported its potential anti-browning application.

Experimental study on residual compressive bearing capacity of cracked reinforced concrete columns by SCDA

Abstract The static demolition of structures via soundless chemical demolition agent (SCDA) is attracting increasing attention because of its environmental friendliness and safety, especially in the dense urban areas. However, the research on the application of SCDA in demolishing the reinforced concrete is still scarce, seriously limiting the development of static demolition. In this work, with the combined efforts of experiments and theoretical analysis, we investigate the critical role of borehole layouts in the static demolition of reinforced concrete (RC) by determining the occurrence and expansion of cracks during static demolition, and the resulting residual mechanical properties of RC. The results show that the growth of cracks is significantly dependent on the reaction of SCDA. Additionally, the initiation time of cracking exhibits minimal sensitivity to variations in the layouts pattern of boreholes, while the progression of cracking is predominantly governed by the layouts of boreholes. We demonstrate that cracks formed in static demolition process can significantly reduce the strength of RC with about the remaining bearing capacity is only 10% to 33% of the original and change its failure mode. Further, it is point out that the key factor controlling the failure of RC under axial compression (i.e., the integrity of structures), and the RC with larger crack size and less structural integrity is more prone to fail. The results and findings in this work further clarify the role of borehole layouts and are of great significance in improving the efficiency of static demolition.

The Flowback Proppant Scaling Mechanism in the Horizontal Shale Oil Wells of Qingcheng Oilfield

Abstract Proppant scaling in the horizontal shale oil wells is a common problem in the Qingcheng Oilfield, one of the largest shale oil producers in China. However, few studies have focused on the mechanism of the proppant scaling during the flowback stage of hydraulic fracturing. To elucidate the scaling mechanism, in this study we collected the samples of produced water and solid scales and analyzed their compositions. The experimental simulations of the static and dynamic scaling processes using fracturing fluids, formation water, and reservoir rocks were also performed. In these experiments, the scale was found to be mainly SiO2 combined with FeCO3 and/or CaCO3. FeCO3 was dominant at the initial stage of the flowback, and CaCO3 became dominant at later stages of the flowback and during the stable production stage. It is believed that the high percentage of ferrous minerals (e.g., 46.4% of ferrocalcite) in multiple formation rocks is an essential reason that the proppant scaling happened during the flowback stage. The Fe2+ and Ca2+ ions were believed to be released via reservoir rock reacting with the fracturing fluid under the reservoir temperature and pressure (e.g. 60 °C, 20MPa). In addition, the FeCO3 formed in the initial flowback stage of the fracturing has the greatest impact on production.

Dynamic uncertainty evaluation of cylindricity error based on Bayesian deep neural network propagation method

Most of the existing methods for measuring and evaluating product geometric tolerances are for static processes, which use lower dimensions, are more complex to calculate, and have poor traceability and dynamic manageability and control of the measurement process. In this paper, a dynamic evaluation model of cylindricity error uncertainty based on the Bayesian deep neural network propagation method is proposed. Firstly, the input random variable sampling sample containing error uncertainty is generated by proposing the improved Monte Carlo sampling method (IMCS), which has the characteristics of homogeneity and validity; then the principle and construction process of a Bayesian neural network model are introduced to generate the propagation model of multidimensional random error variables; further, the Gaussian mixture model is trained by the Monte Carlo method, and the probability density function of the target response is generated by using the Gaussian mixture model. Through numerical experiments, test analysis of bearing outer rings, and comparison with ISO standard methods, the results show that the model based on the dynamic Bayesian deep neural network propagation method can correctly and effectively assess the uncertainty dynamically, and the whole estimation process is stable.

Consistency-based semi-supervised learning for oriented object detection

Semi-Supervised Object Detection (SSOD) has emerged as a potent framework that leverages unlabeled data to reduce annotation costs while enhancing model performance. Nevertheless, existing SSOD methods primarily concentrate on the conventional localization of horizontal objects, overlooking the common arbitrary-oriented objects in aerial scenes. Extending semi-supervised learning to oriented object detection still encounters two major challenges: (1) There is an inconsistency between classification and localization in oriented object detectors, which means that pseudo-labels selected solely based on classification scores cannot properly represent the localization quality. (2) The static and monotonic pseudo-label selection process fails to dynamically filter pseudo-labels for different tasks and categories throughout the iteration process, inevitably introducing accumulated noise and bias into the supervisory signals for the student model. To mitigate this problems, we proposed a novel consistency-based semi-supervised oriented object detection framework, named CSLO-Det. Specifically, Task Alignment Learning (TAL) is proposed to improve the consistency in terms of both features and learning objectives, thereby facilitating a more robust selection of pseudo-labels. Noise-Resistant Pseudo-label Mining (NR-PM) is introduced to separately and dynamically exploits positives for the classification and localization task. Moreover, diverging from the conventional semi-supervised learning frameworks that utilize pseudo-boxes, our method applies pixel-level dense supervision during unsupervised training, which improves detection performance. Comprehensive experiment results reveal that the proposed CSLO-Det attains state-of-the-art performance under multiple semi-supervised datasets.

DBDAA: A real-time approach to Dynamic Banker’s Deadlock Avoidance Algorithm with optimized time complexity

Effective resource allocation is crucial in operating systems to prevent deadlocks, especially when resources are limited and non-shareable. Traditional methods like the Banker’s algorithm provide solutions but suffer from limitations such as static process handling, high time complexity, and a lack of real-time adaptability. To address these challenges, we propose the Dynamic Banker’s Deadlock Avoidance Algorithm (DBDAA). The DBDAA introduces real-time processing for safety checks, significantly improving system efficiency and reducing the risk of deadlocks. Unlike conventional methods, the DBDAA dynamically includes processes in safety checks, considerably decreasing the number of comparisons required to determine safe states. This optimization reduces the time complexity to O(n) in the best-case and O(nd) in the average and worst-case scenarios, compared to the O(n2d) complexity of the original Banker’s algorithm. The integration of real-time processing ensures that all processes can immediately engage in safety checks, improving system responsiveness and making the DBDAA suitable for dynamic and time-sensitive applications. Additionally, the DBDAA introduces a primary unsafe sequence mechanism that enhances the acceptability and efficiency of the algorithm by allowing processes to participate in safety checks repeatedly after a predetermined amount of system-defined time. Experimental comparisons with existing algorithms demonstrate the superiority of the DBDAA in terms of reduced safe state prediction time and increased efficiency, making it a robust solution for deadlock avoidance in real-time systems.

The Digital Twin Immersive Design Process and Its Potential Disruption to Healthcare Design through a User-Centered Approach

This applied research proposes a solution to the static government design process for Thai healthcare architecture to better serve the needs of its elderly society. In its place, a novel real-time design process, termed the Digital Twin Immersive Design Process (DT-IDP), repurposes aspects of digital twin and virtual reality technologies into a ‘unitary’ immersive design system. This system accesses ‘experiential’ user-centered data, helping enhance the design of Thai healthcare space beyond a standardized government response. This text builds a rationale for departing from the current design process by describing the formation and advantages of the DT-IDP process. To test its credibility, the DT-IDP process is used to build and compare two digital versions of an existing healthcare space. In these spaces, participants are immersed (elderly patients n = 30; nursing staff n = 5; government healthcare architects n = 5) to assess visitor experiences based on daylighting, artificial lighting, and views of nature. Following immersion, government healthcare architects are interviewed in-depth to evaluate the process’s efficacy and their willingness to adopt it. Results confirm the potential for this process to capture ‘user-centered’ insights, otherwise unobtainable without immersion. Consequently, healthcare architects express a unanimous preference for DT-IDP, acknowledging its unique capacity to bridge a market gap through an experiential component that could better assist them in creating a superior final product. Ultimately, they assert that demand for these features could have a disruptive impact to the current healthcare design process, helping to re-envisage the design of future Thai healthcare space.

Enhancing virus inhibition in track-etched membranes through surface modification with silver nanoparticles and curcumin

The present work reports on the use of silver nanoparticles (AgNPs) and curcumin immobilized on the surface of microfiltration track-etched membranes (mTMs) as antiviral filtration materials. AgNPs were synthesized through the direct reduction of silver nitrate by sodium borohydride in the presence of a stabilizing agent. The synthesized nanoparticles and curcumin were immobilized on polyethyleneimine (PEI)-modified mTMs through a static sorption process. TEM, SEM, UV–vis. spectroscopy and luminescence measurements revealed a uniform distribution of AgNPs and confirmed the presence of curcumin on the membrane surface. The resulting TM-PEI-AgNPs-PVP and TM-PEI-Curcumin hybrid membranes were employed for the filtration of HSV-1, VSV, IAV, and EMCV viruses. While both membrane types exhibited insignificant inhibition for the latter two, they achieved 95 and 99 % inhibition for HSV-1 and VSV, respectively. These findings suggest that hybrid membranes with immobilized AgNPs and curcumin can have potential as antiviral filtration materials.

Preparation of diatomite-based porous ceramics and their adsorption properties for Cu2+

Diatomite-based porous ceramics were prepared by wet grinding and high temperature calcination with diatomite as the main raw material. The structure and properties of the ceramics were characterized by SEM, XRD, and FI-TR detection techniques. The results show that the diatomite-based porous ceramics are mainly quartz crystal phase and contain a large amount of Si-OH. Their pore size distribution is 500∼3500 nm, the specific surface area is 6.14 m2/g, and the porosity is 47.8%. The static adsorption process of Cu2+ in water by ceramic particles conforms to the quasi-second-order kinetic model, and the adsorption equilibrium is reached after 6 h with the maximum adsorption capacity of 4.5 mg/g. The Thomas model can be applied to represent the dynamic adsorption of Cu2+ in water. In the adsorption of Cu2+, pH exerts a strong influence. In solution, Cu2+ forms a ligand with hydroxyl surface functional groups on the surface of ceramics and pores through electrostatic interaction, and the hydrogen on the hydroxyl group exchanges with Cu2+, so that Cu2+ can be removed.

Fabrication of sulfur-based functionalized activated carbon as solid phase extraction adsorbent for selective analysis of selenite in water

Based on the important feature of sulfur with excellent selectivity toward selenite in the presence of selenate, a simple and low-cost adsorbent of solid phase extraction known as sulfur loading activated carbon (SAC-6) was successfully prepared and applied for selenite (Se(IV)) analysis in water. Microstructure and morphological characteristics of SAC-6 had been identified by XRD, TEM, BET and FT-IR. In the static adsorption experiments, Se(IV) could be separated in a wide range of pH values (pH=3–11). The retention process of Se(IV) onto SAC-6 was characterized as spontaneous exothermic reaction. An obvious change of adsorption mechanism occurred in static and dynamic adsorption processes shown that the behaviors followed monolayer and hybrid adsorption. The theoretical maximum adsorption capacity of SAC-6 calculated by Langmuir-Freundlich was 13.48 mg/g. The microcolumn filled with SAC-6 was applied to extract Se(IV) in water solution. The detection limit of Se(IV) analytical procedure was confirmed as 0.27 μg/L within a linear range of 10–1000 μg/L. A good precision with relative standard deviation of 1.34 % (100 μg/L, n = 6) was achieved. The high adaptability and accuracy of SAC-6 microcolumn was validated by analyzing natural water samples and certified reference materials. Our work successfully excavated the application value of the sulfur selectivity, and also provided a new adsorbent for Se(IV) extraction and analysis.

Development, characterization and validation of a novel physics-informed equivalent circuit model for silicon–graphite battery cells

The widespread deployment of electric vehicles (EVs), as well as the growing requirements both from manufacturers and consumers, necessitate an increase in energy density with regard to current lithium-ion batteries (LIBs). In this regard, one of the most promising alternatives is the addition of silicon to conventional graphite anodes, thus giving rise to energy-dense LIBs. However, this entails a significant increment in modeling, parameterization and computational complexities due to the interactions between both negative electrode materials. In this article, we present a novel physics-informed equivalent circuit model for cells with blended electrodes, which is able to provide accurate results with respect to a state-of-the-art electrochemical model, not only for the output voltage (≤25 mV RMS), but also internal states, namely active material particle surface concentrations (≤1.2 %) and current distribution (≤2.6 %) at a much lower computational cost. Furthermore, this formulation also allows for a notable simplification of model parameterization. Hence, we describe thorough static and dynamic parameterization processes from half-cell experimental data and impedance measurements. Finally, we validate the proposed model in constant-current as well as dynamic operation, highlighting the influence that the choice of hysteresis model has on the latter. We understand that the presented model is an interesting alternative for the modeling of cells with blended electrodes, and is also suitable for its implementation in Battery Management Systems (BMSs) in EVs.

Recursive identification of kernel-based hammerstein model for online energy efficiency estimation of large-scale chemical plants

Accurate energy efficiency prediction is crucial for decision-making in large-scale chemical production, especially considering energy management and environmental concerns. The complexity of chemical processes, characterized by strong nonlinearities, dynamics, and uncertainties, challenges traditional prediction methods. This paper introduces KHSM (Kernel-based Hammerstein Subspace Model), which models nonlinear static and linear dynamic processes in series by embedding kernel function-based nonlinear mapping into subspace modeling for energy efficiency estimation. KHSM identifies nonlinear process models without explicit nonlinear mapping functions, constructing dynamic models that encompass both energy input and product output variables. An adaptive KHSM variant dynamically updates the energy efficiency model, improving accuracy by iteratively selecting and excluding samples. Comparative analysis shows KHSM outperforms existing methods, achieving a coefficient of determination (R2) closest to 1 and reducing the root-mean-square error (RMSE) by up to an order of magnitude, with the smallest mean and standard deviation. Additionally, modeling efficiency increases by an order of magnitude. The developed model enables ongoing energy efficiency estimation and proactive identification of efficiency trends. Validation through mathematical and real-world ethylene process cases demonstrates KHSM's efficacy and applicability. These estimates facilitate informed adjustments to energy management strategies and optimization of production approaches in energy-intensive chemical processes.

Flow Effects and Propulsion Performance on Various Single Expansion Ramp Nozzle Configurations of Scramjet Engine

This study serves as a research endeavor aiming to explore the behavior of the coupling flow effects of the single expansion ramp nozzle (SERN) in over-expansion conditions during the static start-up process. The open-source program OpenFOAM and its solver “rhoCentralFoam” are employed in the 2D simulation and the two critical geometric variations, the shape of the ramp and the length of the flap beyond the throat, are considered in the geometric variation. The result shows the preferable propulsion performance in the FSS (Free Shockwave Separation) state compared to RSS (Restricted Shockwave Separation). FSS also plays the role of the initial, albeit transient, separation, which originates from the shockwave from the throat and will eventually transform into a stabler RSS state. For the 100% flap length configuration in this study, the axial thrust can achieve a high value of 500 N/m in the FSS state and decrease to around 450 N/m, on average, in the RSS state. The trust angle also shows a preferable performance of around −13° in FSS compared to −30° in RSS. Regarding geometric modifications, both modifications, shorting the flap and bell-shaped ramp adjustments, manifest similar effects. Both conical and bell-shaped short flap configurations demonstrate an axial thrust from around 1750 to 1900 N/m and a thrust angle of around −45°. However, the flap shortening, which may demonstrate an attitude compensation effect, exhibits a more pronounced effect compared to the bell-shaped modification.

Robot-based dynamic optics scanning infrared thermography for debonding defect detection of big-sized CFRP specimen

ABSTRACT The use of infrared thermography (IRT) for non-destructive testing (NDT) of large aerospace composites, such as carbon fibre reinforced polymer (CFRP), is often limited by the narrow field of view infrared cameras. This paper experimentally investigates the big-sized CFRP specimens with simulated debonding defects using a robot-based dynamic optics scanning infrared thermography (RDOS-IRT) method to meet these issues. Then, static pulse IRT and RDOS-IRT were performed, and the processing performance of different algorithms (pulsed phase thermography, PPT; total harmonic distortion, THD; matched filtering, MF; and supervised dimensionality reduction, SDR) on pulsed IRT was discussed. A combination of pseudo-static matrix reconstruction (FSMR) algorithm and static image sequence processing algorithm is innovatively adopted to improve the defect detection performance of RDOS-IRT results. The experiments show that the RDOS-IRT method with FSMR and static image sequence processing algorithm is effective; moreover, it has almost a similar detection ability compared to the traditional static pulse IRT method in practical applications and saves more time. Results show that the signal-to-noise ratio (SNR) of the repeated defects is not differentiated, and the detection effect is similar. Therefore, the RDOS-IRT method is a reliable tool for NDT tasks on big-sized CFRP specimens and can be practically applied in an industrial setting for high detection efficiency.

Inhibitory Effects, Fluorescence Studies, and Molecular Docking Analysis of Some Novel Pyridine-Based Compounds on Mushroom Tyrosinase.

Melanin biosynthesis in different organisms is performed by a tyrosinase action. Excessive enzyme activity and pigment accumulation result in different diseases and disorders including skin cancers, blemishes, and darkening. In fruits and vegetables, it causes unwanted browning of these products and reduces their appearance quality and economic value. Inhibiting enzyme activity and finding novel powerful and safe inhibitors are highly important in agriculture, food, medical, and pharmaceutical industries. In this regard, in the present study, some novel synthetic pyridine-based compounds including 2,6-bis (tosyloxymethyl) pyridine (compound 3), 2,6-bis (butylthiomethyl) pyridine (compound 4), and 2,6-bis (phenylthiomethyl) pyridine (compound 5) were synthesized for the first time, and their inhibitory potencies were assessed on mushroom tyrosinase diphenolase activity. The results showed that while all tested compounds significantly decreased the enzyme activity, compounds 4 and 5 had the highest inhibitory effects (respectively, 80 and 89% inhibition with the IC50 values of 17.0 and 9.0 μmol L-1), and the inhibition mechanism was mixed-type for both compounds. Ligand-binding studies were carried out by fluorescence quenching and molecular docking methods to investigate the enzyme-compound interactions. Fluorescence quenching results revealed that the compounds can form nonfluorescent complexes with the enzyme and result in quenching of its intrinsic emission by the static process. Molecular docking analyses predicted the binding positions and the amino acid residues involved in the interactions. These compounds appear to be suitable candidates for more studies on tyrosinase inhibition.

Related technological density and regional industrial upgrading from perspective of product space theory: evidence from China

ABSTRACT When the product space theory is applied to study regional technology and industry evolution, both the theory exploitation and practical application are not comprehensive and detailed enough. This article traces the connotation of ‘density’ in the product space theory, explains the micro-foundation of regional industrial upgrading from a firm’s perspective, and abstracts industrial upgrading into four processes at two stages. Empirical research shows that an increase in related technological density (i.e. the average proximity of related technologies in a certain region) is beneficial for all processes of industrial upgrading. Marketization has a positive moderating effect on the static stage but a certain ‘counterproductive’ effect on the dynamic stage. Regional heterogeneity analysis shows that, on the whole, the industrial upgrading effect of the related technological density increase is relatively stronger on static processes but relatively weaker on dynamic processes in eastern China, and such results may be attributed to differences in regional resource dependence.

Features of body balance in 12-year-old schoolchildren with visual deprivation compared to their relatively healthy peers

Purpose. The purpose of the presented scientific research was to carry out a comparative analysis of the state of functional balance of the body of 12-year-old schoolchildren with visual deprivation in accordance with their relatively healthy peers. Material & Methods. The scientific study involved 23 schoolchildren aged 12 years, of which 13 were with visual deprivation and 10 were relatively healthy. The pedagogical research took place at the Educational and Rehabilitation Center “Zorozvit” in Odessa and at the Basic Educational Institution “Vypasnyansky Institution of General Secondary Education” of the Mologovo Village Council of the Bilhorod-Dnistrovsky District, Odessa Region. The follo wing methods were used in the study: theoretical (analysis and synthesis of scientific and methodological literature); pedagogical research (experiment and testing of the development of body balance using the Flamingo test), mathematical static data processing. Results. A scientific study found that among schoolchildren without visual deprivation, only 10% had a low ability to maintain body balance. In turn, 90% of schoolchildren with visual deprivation had a sufficient, satisfactory and high level of development of body balance. It should be noted that schoolchildren with visual deprivation demonstrate a low level of ability to maintain balance, which distinguishes them from their peers without visual deprivation.