Uniform Parameters Research Articles

Enhancing Daily Crash Count Prediction using Deep Learning with Window Size Selection and Seasonality Predictor Integration

The escalating need for proactive safety measures, coupled with advancements in data collection and analytical techniques, has significantly refined the accuracy of crash count predictions, shifting from annual scales to finer daily or hourly estimates. This research places emphasis on recurrent neural networks (RNNs), specifically the long short-term memory (LSTM) model, acknowledged for effectively managing sequential data in time series predictions. Paramount considerations encompass the treatment of input data, including the decision to incorporate temporal features alongside endogenous historical target values, and the establishment of an optimal window size for data input. Despite the critical nature of these facets, exhaustive studies concurrently investigating both under controlled conditions are scarce. This research addresses this gap, assessing diverse scenarios featuring distinct temporal treatments and window sizes, and employing an LSTM model with uniform fine-tuned parameters to ensure a fair comparison. Findings indicate a significant variation in performance among models employing different window sizes and month predictor integration, under identical RNN structures and LSTM configurations. The best model outperformed the least effective by roughly 30% concerning root mean square error (RMSE) and ranking correlation between predicted and actual target crash counts in the test datasets. Unlike seasonality predictor treatment, diverse window size selections did not lead to statistically significant differences in model performance. Generally, a window size of 3 performed worst under most conditions, followed by a size of 14. Sizes of 7 and 28 performed best in nearly an equal numbers of cases.

Importance of aerosol composition and aerosol vertical profiles in global spatial variation in the relationship between PM2.5 and aerosol optical depth

Abstract. Ambient fine particulate matter (PM2.5) is the leading global environmental determinant of mortality. However, large gaps exist in ground-based PM2.5 monitoring. Satellite remote sensing of aerosol optical depth (AOD) offers information to help fill these gaps worldwide when augmented with a modeled PM2.5–AOD relationship. This study aims to understand the spatial pattern and driving factors of this relationship by examining η (PM2.5AOD) using both observations and modeling. A global observational estimate of η for the year 2019 is inferred from 6870 ground-based PM2.5 measurement sites and satellite-retrieved AOD. The global chemical transport model GEOS-Chem, in its high-performance configuration (GCHP), is used to interpret the observed spatial pattern of annual mean η. Measurements and the GCHP simulation consistently identify a global population-weighted mean η value of 96–98 µg m−3, with regional values ranging from 59.8 µg m−3 in North America to more than 190 µg m−3 in Africa. The highest η value is found in arid regions, where aerosols are less hygroscopic due to mineral dust, followed by regions strongly influenced by surface aerosol sources. Relatively low η values are found over regions distant from strong aerosol sources. The spatial correlation of observed η values with meteorological fields, aerosol vertical profiles, and aerosol chemical composition reveals that spatial variation in η is strongly influenced by aerosol composition and aerosol vertical profiles. Sensitivity tests with globally uniform parameters quantify the effects of aerosol composition and aerosol vertical profiles on spatial variability in η, exhibiting a population-weighted mean difference in aerosol composition of 12.3 µg m−3, which reflects the determinant effects of composition on aerosol hygroscopicity and aerosol optical properties, and a population-weighted mean difference in the aerosol vertical profile of 8.4 µg m−3, which reflects spatial variation in the column–surface relationship.

Optimization of Connection Parameters of Self-Adaptive Modular Floating Wind Farms

Connection parameters are the key factors influencing the responses of modular floating structures; due to the complexity of structural response properties, the assessment and optimization of connection parameters are still vital issues in designing modular floating structures. In the present work, for a novel structural configuration of self-adaptive modular floating wind farms based on existing works from the case of a mobile offshore base, a quantified approach for the assessment of connection parameters is established based on frequency domain numerical analysis taking into account both the economic effects and generalized performance. Based on the quantified assessment, an optimization process is carried out, to obtain a connection parameter combination. From the optimized connection parameters, it can be found that the most appropriate tri-axial stiffness according to present studies is in the magnitude from 1 × 106 to 7 × 107 N/m, and the damping ratio is close to 1.0 for most connection structures. By contrast with feasible uniform connection parameters, the optimization methodology is confirmed to be able to reduce both connection parameters and responses. Then, a time domain approach for the calculation of motions of interconnected modular floating structures taking into account geometry nonlinearity is proposed and obtained in good accordance with the frequency domain results, and the effectiveness of both the frequency domain and time domain is validated.

Towards sharper excess risk bounds for differentially private pairwise learning

Pairwise learning is a vital part of machine learning. It depends on pairs of training instances, and is naturally fit for modeling relationships between samples. However, as a data driven paradigm, it faces huge privacy issues. Differential privacy (DP) is a useful tool to protect the privacy of machine learning, but corresponding excess population risk bounds are loose in existing DP pairwise learning analysis. In this paper, we propose a gradient perturbation algorithm for pairwise learning to get better risk bounds under Polyak–Łojasiewicz condition, including both convex and non-convex cases. Specifically, for the theoretical risk bound in expectation, previous best results are of rates O(pn2ϵ2+1n) and O(pnϵ+1n) under strongly convex condition and convex conditions, respectively. In this paper, we use the on-average stability and achieve an O(min{pn1.5ϵ+p1.5n2.5ϵ3,pn2ϵ2+1n}) bound, significantly improving previous bounds. For the high probability risk bound, previous best results are analyzed by the uniform stability, and O(βnU+pnϵ) excess population risk bounds are achieved under strongly convex or convex conditions, where βnU is the traditional pairwise uniform stability parameter, it is large since it considers the worst case of the loss sensitivity. In this paper, we propose the pairwise locally elastic stability and improve the high probability bound to O(βEn+pnϵ), in which the pairwise locally elastic stability parameter βE≪βnU because it considers the average sensitivity of the pairwise loss function.

3-D geometric design of microwaveable food products for optimal heating uniformity based on machine learning-supervised multiphysics models

Multiphysics models can assist in geometric design of frozen microwaveable foods, but the conventional 'parametric-sweeping' strategy is computationally intensive. This study develops an online machine learning (ML)-supervised multiphysics modeling strategy to simultaneously optimize multiple geometrical parameters (e.g., top surface width, top surface length, and the ratio of top-to-bottom dimensions) for optimal microwave heating uniformity. First, one or more paired geometric dimensional parameters and heating uniformity results obtained from multiphysics modeling are used as initial training data for the ML optimization process that integrates Gaussian Process Regression (GPR) and Bayesian optimization. Then, the multiphysics modeling procedure is supervised by an ML process to generate new paired geometry-heating uniformity results to expand the training dataset. The loop of multiphysics modeling and ML optimization is conducted to effectively identify geometry designs with good heating uniformity. Results indicate that the ML-supervised optimization strategy can efficiently identify good geometric designs with low heating uniformity by using much fewer multiphysics models than the parametric sweep approach. The ML-supervised approach also exhibits great robustness, delivering good performance even with small (as little as one model) and randomly selected initial training data. This ML-supervised approach is flexible and can be modified to meet specific needs for broad industrial implementation in the development of microwaveable food.

DEVELOPMENT OF AN ALGORITHM FOR CALCULATING COMPONENT COMPOSITION TO IMPROVE THE DEVELOPMENT OF OFFSHORE OIL FIELDS IN THE NORTH CASPIAN BASIN

The paper presents an algorithm to reconstruct the component composition of the mixture based on the results of production modeling in the black oil format and a fixed set of tables with the results of phase equilibrium calculations in a given pressure range. The approach is based on analyzing the ratio of flow rates for each phase and the ratio between average reservoir pressure and saturation pressure. The algorithm takes into account the possibility of oil degassing when saturation pressure decreases, as well as gas breakthrough of gas caps to the bottoms of producing wells.Implementation of the method is based on a unified thermodynamic model of multilayer reservoir, built on the principles of a single set of HC mixture components and uniform parameters of the equation of state on a set of fluid samples for all modeling stages: reservoir model, model of the gathering system and site facilities. In addition to steady-state flow calculations performed together with reservoir modeling, the unified model is planned to be used for dynamic flow calculations in the corresponding simulator (well start/stop), which will allow solving production problems in the process of operation of wells with complex completions.The conversion algorithm is automated using modern high-level tools: Python and data automation components from MS Excel, which eliminates the need for manual data input at all stages and makes it possible to obtain the estimated component composition of produced fluid for any set of wells and for any time step within the forecasting horizon.The obtained compositions are used to verify the reproduction of the main controlled parameters (oil density and gas oil ratio) and can be used for subsequent calculations of fluid transportation and treatment systems.The implemented algorithm has been tested for stability at different ratios of gas and oil flow rates by wells and meets the practical requirements of engineering calculations — the error of oil density is not higher than 2 % and gas factor is not higher than 10 %.

Numerical investigation of the reflection of unsteady decelerating incident shock waves

The incident shock attenuation phenomenon in shock tube has received widespread interest because of its inevitable influence on experimental gas properties. However, few studies have investigated the cascading effects of the resulting nonuniformity on shock reflection in shock tunnels before the nozzle. This paper describes a numerical study on the unsteady reflection of a decelerating incident shock driven by a decelerating piston, as a simplification of the complex nonideal factors. The initial decay and uniform parameter distributions are generated based on the non-inertial frame. The results indicate that the existence of the nonuniform area forces the reflected shock wave region to undergo a transition process of attenuation and then stability. The final values of the gas parameters in zone 5 will, therefore, deviate from those given by the traditional relation for an ideal shock tube, which are only dependent on the terminal shock Mach number. This affects the determination of the total temperature T5, which is difficult to measure directly. We discuss the reconstruction of the nonuniform region with the attenuation trajectory of the incident shock wave and find that there is no one-to-one correspondence between this trajectory and the resulting nonuniformity, which introduces additional uncertainties to the predictions. Thus, an analogy method is developed through the multilevel block building algorithm, allowing the total temperature T5 to be determined using the total pressure p5 considering the effect of nonuniformity. Further assessments verify the applicability of this method in cases with multidimensional and viscous interactions.

Stellar spectral template library construction based on generative adversarial networks

Stellar spectral template libraries play an important role in the automated analysis of stellar spectra. Synthetic template libraries cover a very large parameter space but suffer from poor matching with observed spectra. In this study, we propose a synthetic-to-observed spectral translation (SOST) method based on generative adversarial networks. The SOST method is able to calibrate synthetic spectra by converting them to the corresponding observed spectra. We applied this method to Kurucz synthetic spectra and observed spectra data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). After that, we constructed a stellar spectral library with uniform and broad parameter distributions using the SOST-corrected Kurucz synthetic spectra. Our stellar spectral template library contains 2431 spectra spanning a parameter space of 3500–8000 K for effective temperature (Teff), 0.0–5.0 dex for surface gravity (log g), and −2.0–0.5 dex for metallicity ([Fe/H]). The spectra in the library have a resolution of R ∼ 1800 and cover the wavelength range 3900–8700 Å. In order to verify the accuracy of this template library, we used the template library and the template-matching algorithm to derive the parameters of the PASTEL database. Compared to measurements using the original synthetic template library, the accuracies of the three parameters, Teff, log g, and [Fe/H], are improved, from 140 K, 0.31 dex, and 0.21 dex to 121 K, 0.26 dex, and 0.13 dex, respectively. In addition, we re-parameterised more than six million stellar spectra released by LAMOST DR8.

3D numerical study of NH3/H2 MILD combustion in a reversed flow MILD combustion furnace

Combustion of fuels to generate energy is essential for numerous residential and industrial human endeavors. In contrast to fossil fuels, the demand for carbon-free fuels such as ammonia and hydrogen to meet climate commitments is rapidly growing. This study conducts a numerical investigation of NH3/H2 MILD combustion. A three-dimensional CFD simulation model of a 90-degree sector of a reversed flow MILD combustion furnace is presented. The SAGE detailed chemical kinetics solver featuring the CEU-NH3 mechanism is employed with dynamic mechanism reduction for computational efficiency. The effects of varying the hydrogen mole fraction in the inlet fuel mixture from 0 to 50 % on the thermal characteristics, reaction zone, and emissions are investigated. The findings show that temperature homogeneity, assessed through temperature uniformity parameters and standard deviation, reveals a diminishing trend in temperature homogeneity with increased hydrogen concentration. The boundaries of the reaction zone are determined according to the NNH and N mole fractions, and both criteria are approximately identical. All the investigated cases match the MILD combustion definition; however, the cases with H2 concentrations ranging from 10 to 40 % fall under the MILD-like combustion regime. Emissions analysis shows that for all investigated cases, the ammonia slip emissions and the exhaust N2O emissions are below 1 and 0.5 ppm, respectively. The NOx emissions are found to increase abruptly with increasing hydrogen concentration from 0 to 35 % and subsequently undergo minor fluctuations.

In-situ rapid nondestructive characterization of multiple irregular three-dimensional grain boundary structures and electrical properties by nanorobot with SEM in ZnO

To address the problem of spatial quantification of irregular grain boundaries, a unique approach for the nondestructive characterization of multiple irregular three-dimensional grain boundaries is proposed using nanorobots with scanning electron microscopy (SEM) to accomplish in-situ rapid synchronized quantification of structures and electrical properties. By constructing a three-dimensional trigonometric geometric mapping relationship, multiple irregular three-dimensional grain boundary structures and electrical properties can be rapidly quantified. Experimental results demonstrate that it is feasible to accomplish in-situ rapid nondestructive characterizations. The two-dimensional profile shapes of the targeted grain boundaries at each layer exhibit irregular and non-uniform features in the Y-Z plane. The hypotenuse length between the virtual space tilting lines presents a three-dimensional characteristic in the X-Z plane. The spatial tilt angle of the virtual space tilting line can be calculated using the right-triangle relation. The unequal numbers of grains along the same tilted hypotenuse direction with equal lengths directly illustrate the existence of irregular and nonlinear grain boundaries in bulk ZnO ceramics. The relatively uniform spatial sizes of the grain boundary illustrate the coupled spatial characteristics existing in the irregular micro-structures. The relatively uniform equivalent circuit fitting parameters confirm the existence of relatively uniform doping components in bulk ZnO ceramics. Furthermore, this method provides a unique approach for the rapid nondestructive quantitative analysis of multiple three-dimensional irregular grain boundaries in bulk polycrystalline materials.

Lab on a bead with oscillatory centrifugal microfluidics for fast and complete mixing enables fast and accurate biomedical assays

Rapid mixing and precise timing are key for accurate biomedical assay measurement, particularly when the result is determined as the rate of a reaction: for example rapid immunoassay in which the amount of captured target is kinetically determined; determination of the concentration of an enzyme or enzyme substrate; or as the final stage in any procedure that involves a capture reagent when an enzyme reaction is used as the indicator. Rapid mixing and precise timing are however difficult to achieve in point-of-care devices designed for small sample volumes and fast time to result. By using centrifugal microfluidics and transposing the reaction surface from a chamber to a single mm-scale bead we demonstrate an elegant and easily manufacturable solution. Reagents (which may be, for example, an enzyme, enzyme substrate, antibody or antigen) are immobilised on the surface of a single small bead (typically 1–2 mm in diameter) contained in a cylindrical reaction chamber subjected to periodically changing rotational accelerations which promote both mixing and uniform mass-transfer to the bead surface. The gradient of Euler force across the chamber resulting from rotational acceleration of the disc, dΩdisc/dt, drives circulation of fluid in the chamber. Oscillation of Euler force by oscillation of rotational acceleration with period, T, less than that of the hydrodynamic relaxation time of the fluid, folds the fluid streamlines. Movement of the bead in response to the fluid and the changing rotational acceleration provides a dynamically changing chamber shape, further folding and expanding the fluid. Bead rotation and translation driven by fluid flow and disc motion give uniformity of reaction over the surface. Critical parameters for mixing and reaction uniformity are the ratio of chamber radius to bead radius, rchamber/rbead, and the product Trchamber(dΩdisc/dt), of oscillation period and Euler force gradient across the fluid. We illustrate application of the concept using the reaction of horse radish peroxidase (HRP) immobilised on the bead surface with its substrate tetramethylbenzidine (TMB) in solution. Acceleration from rest to break a hydrophobic valve provided precise timing for TMB contact with the bead. Solution uniformity from reaction on the surface of the bead in volumes 20–50 uL was obtained in times of 2.5 s or less. Accurate measurement of the amount of surface-bound HRP by model fitting to the measured kinetics of colour development at 10 s intervals is demonstrated.

Validation of a new global irrigation scheme in the land surface model ORCHIDEE v2.2

Abstract. Irrigation activities are important for sustaining food production and account for 70 % of total global water withdrawals. In addition, due to increased evapotranspiration (ET) and changes in the leaf area index (LAI), these activities have an impact on hydrology and climate. In this paper, we present a new irrigation scheme within the land surface model ORCHIDEE (ORganising Carbon and Hydrology in Dynamic EcosystEms)). It restrains actual irrigation according to available freshwater by including a simple environmental limit and using allocation rules that depend on local infrastructure. We perform a simple sensitivity analysis and parameter tuning to set the parameter values and match the observed irrigation amounts against reported values, assuming uniform parameter values over land. Our scheme matches irrigation withdrawals amounts at global scale, but we identify some areas in India, China, and the USA (some of the most intensively irrigated regions worldwide), where irrigation is underestimated. In all irrigated areas, the scheme reduces the negative bias of ET. It also exacerbates the positive bias of the leaf area index (LAI), except for the very intensively irrigated areas, where irrigation reduces a negative LAI bias. The increase in the ET decreases river discharge values, in some cases significantly, although this does not necessarily lead to a better representation of discharge dynamics. Irrigation, however, does not have a large impact on the simulated total water storage anomalies (TWSAs) and its trends. This may be partly explained by the absence of nonrenewable groundwater use, and its inclusion could increase irrigation estimates in arid and semiarid regions by increasing the supply. Correlation of irrigation biases with landscape descriptors suggests that the inclusion of irrigated rice and dam management could improve the irrigation estimates as well. Regardless of this complexity, our results show that the new irrigation scheme helps simulate acceptable land surface conditions and fluxes in irrigated areas, which is important to explore the joint evolution of climate, water resources, and irrigation activities.

Nonlinear vibrations of porous-hyperelastic cylindrical shell under harmonic force using harmonic balance and pseudo-arc length continuation methods

The resonant responses are investigated for the porous-hyperelastic Mooney–Rivlin cylindrical shell subjected to a radial harmonic excitation. Considering the higher-order shear deformation theory (HSDT), fourth-order strain-displacement relations are derived, which include the radial geometric imperfections varying along the thickness direction. Using the porous-hyperelastic Mooney–Rivlin constitution relation and Lagrange equation, the differential governing equations of motion are obtained for the porous-hyperelastic cylindrical shells. The resonant conditions are presented and the accuracy of the mathematical models is verified. The harmonic balance and pseudo-arc length continuation methods are used to obtain the amplitude-frequency and forced-amplitude curves. The stability of the solutions is analyzed by Floquet theory. The effects of the external excitation amplitudes, structure parameters and porosity infill parameters on the linear frequencies, amplitude-frequency responses and force-amplitude responses are discussed for the imperfect porous-hyperelastic cylindrical shells. The results show that the linear frequencies of the porous-hyperelastic cylindrical shells increase obviously as the uniform and sigmoid function porosity parameters reach the certain values. The increase of the structure parameters enhances the response amplitudes of the first-order mode and minified response amplitudes of the second-order mode. The decreasing porosity ratios weaken the softening nonlinear behaviors of the porous-hyperelastic cylindrical shells. With the changes of the external excitation amplitudes and structure parameters, the motion of the porous-hyperelastic cylindrical shell indicates that the synchronous vibrations occur with the period and chaotic vibrations alternately.

Optimizing Atomic Layer Deposition Processes with Nanowire‐Assisted TEM Analysis

AbstractAtomic layer deposition (ALD) is one of the premier methods to synthesize ultra‐thin materials on complex surfaces. The technique allows for precise control of the thickness down to single atomic layers, while at the same time providing uniform coverage even for structures with extreme aspect ratios such as deep trenches or wires. While many materials can be readily deposited using ALD there is still a lot of research going on to make other materials more accessible. When establishing a new process or adapting an existing process to a new reactor, precise optimization of the deposition parameters is necessary. However, characterizing the parameters of deposition rate, uniformity, composition, and structure is a challenging and time‐consuming task. Here a method is presented to optimize these process parameters during ALD deposition using high‐aspect ratio nanowires and transmission electron microscopy (TEM). Nanowire samples are prepared directly on TEM grids that are put into the ALD reactor during deposition. Within min of the process the coated nanowires can be analyzed by TEM to obtain the thickness of the layers, chemical composition, crystallinity, and conformality of the coating. This allows for a high testing throughput and subsequently a rapid optimization of deposition parameters.

Oral health assessment in institutionalized elderly: a scoping review

When elderly become frail and in need for complex care, they can no longer live independently at home and may be admitted to nursing homes. Various studies have shown that oral health in this population is remarkably poor, which may lead to distressing situations and impacts quality of life. A variety of definitions or descriptions for oral health is used. Without a uniform parameter, it is impossible to determine whether oral health in institutionalized elderly is actually improving or deteriorating over time, as well as the effect of (preventive) interventions. In search for an adequate and clinically applicable parameter to determine oral health in this specific patient group, this scoping review aims to give an overview of the currently used parameters for determining oral health in institutionalized elderly. Ninety different parameters were identified, and 50 parameters were solely used by one study. Only 4 parameters were frequently used (in > 20 studies). The relevance of these parameters for this specific patient group is discussed. To aid the planning and commissioning of future research and patient care, there is an urgent need for an adequate and uniform parameter for oral health determination in institutionalized elderly.

An Investigation into the Effect of Near-Fault Ground Motion Duration Parameters on the Nonlinear Seismic Response of Intake Towers

Intake towers, essential for hydraulic hub projects, are integral to maintaining safety and efficiency, especially under seismic conditions that are prevalent near fault zones. These structures are vital for the integrity of hydraulic hubs, effective hydropower generation, and downstream safety. The duration of seismic events notably influences the towers’ structural response. In light of China’s initiative to build numerous high dams and large reservoirs, understanding the interplay between seismic duration and the intake tower response is crucial. This study, utilizing a duration-dependent composite parameter method based on seismic intensity, investigates the impact of near-fault ground motion duration effects on the response characteristics of intake towers. It analyzes the correlation between three types of six duration parameters and six duration-related composite parameters with the nonlinear seismic response of the physical model of the intake tower structure, as well as the rapid seismic response of the simplified model. This study investigates the impact of near-fault ground motion duration on intake towers, which is crucial for hydraulic hub projects, particularly in seismic-prone areas like those targeted by China’s dam construction initiative. Utilizing a duration-dependent composite parameter method, the study establishes a strong correlation between seismic duration parameters and the nonlinear response of intake towers, emphasizing the significance of uniform duration-related composite intensity parameters for characterizing near-fault seismic motion features. The findings reveal a pronounced correlation between the elasto-plastic response of intake towers and consistent duration-related composite strength parameters, offering crucial insights for optimizing structural design and enhancing seismic response assessment, particularly in the realm of large-scale dam projects.

Influence of convective heat transfer coefficients on thermal behaviour of a lithium-ion cell: a numerical study.

In the current study, the impact of C-ratio, convective heat transfer coefficient, and free stream temperature on the maximal cell temperature and temperature uniformity was computationally and statistically examined. Results revealed that the free stream temperature was the main influential factor for the maximal cell temperature for both natural and forced convection conditions while the C-ratio was the most effective parameter for the temperature uniformity for both natural and forced convections. On the other hand, the contribution of the free stream temperature to the maximum battery temperature increased from 63% to 94% when the conditions were changed from natural convection to forced convection. Moreover, the contribution of the C-rate to the temperature uniformity decreased from 89% to 79% when the conditions were changed from natural convection to forced convection. The results obtained from this study are significant in terms of determining which factor should be given more importance under natural and forced convection conditions.

Цифровое неравенство в системе местного самоуправления: понятие, критерии, пути преодоления

Introduction. Since the end of the 20th and beginning of the 21st centuries, all areas of social management, including public management, have been seriously influenced by modern digital technologies, which, on the one hand, create new opportunities to increase the efficiency of management activities; on the other hand, they pose certain risks, potentially provoking digital inequality. The article presents an analysis of the prerequisites and causes of digital inequality in municipalities. The criteria for such inequality are identified and generalized. An attempt was made to find out the attitude of local governments and citizens, living under digital lockdown, towards the digital transformation of public administration and local economy. Proposals have been made to level the digital divide in municipalities. Theoretical analysis. The problem of digital inequality has been the focus of attention of researchers for over 20 years. However, the scientific discourse on digital inequality is still fragmented: there is no universal interpretation of this phenomenon in the theoretical aspect; there are no uniform parameters for measuring it, and no algorithm for overcoming it has been developed. It is noted that approaches to understanding digital inequality and its consequences have undergone major changes: from unhindered access to the Internet to a person’s request to use digital resources, including those in the field of local government. Empirical analysis. The analysis of the legal regulation of digital transformation was carried out. As a result, it was concluded that flexible or “soft” legal regulation of the digitalization of public administration currently prevails. It is indicated that a special federal law regulating the process of digital transformation in the public administration system and in the local government system, respectively, has not been adopted in the Russian Federation. The criteria for assessing the digital inequality of Russian subjects, the possibility and feasibility of scaling them to the level of local government were analyzed. Results. Based on the results of the study, it is shown that at the local government level, digital inequality is an urgent problem that has a complex technological, socio-economic, socio-cultural and legal nature. It has been proven that there has been a transformation in the essence and understanding of digital inequality: from the problem of access to digital technologies to ensuring equal conditions for citizens to exercise their constitutional rights through such technologies, including the right to local self-government. A proposal for a special program approach has been made to overcome the digital divide in municipalities.

Feasibility of Tear Meniscus Height Measurements Obtained with a Smartphone-Attachable Portable Device and Agreement of the Results with Standard Slit Lamp Examination

Purpose: We aimed to evaluate the feasibility of using a novel device, the Smart Eye Camera (SEC), for assessing tear meniscus height (TMH) after fluorescein staining and the agreement of the results with measurements obtained using standard slit lamp examination. Methods: TMH was assessed using both SEC and conventional slit lamp examination. The images were analyzed using the software ImageJ 1.53t (National Institutes of Health, Bethesda, MD, USA). A common measurement unit scale was established based on a paper strip, which was used as a calibration marker to convert pixels into metric scale. A color threshold was applied using uniform parameters for brightness, saturation, and hue. The images were then binarized to black and white to enhance the representation of the tear menisci. A 2 mm area around the upper and lower meniscus in the central eye lid zone was selected and magnified 3200 times to facilitate manual measurement. The values obtained using SEC were compared with those obtained with a slit lamp. Results: The upper and lower TMH values measured using the SEC were not statistically different from those obtained with a slit lamp (0.209 ± 0.073 mm vs. 0.235 ± 0.085, p = 0.073, and 0.297 ± 0.168 vs. 0.260 ± 0.173, p = 0.275, respectively). The results of Bland–Altman analysis demonstrated strong agreement between the two instruments, with a mean bias of −0.016 mm (agreement limits: −0.117 to 0.145 mm) for upper TMH and 0.031 mm (agreement limits: −0.306 to 0.368 mm) for lower TMH. Conclusions: The SEC demonstrated sufficient validity and reliability for assessing TMH in healthy eyes in a clinical setting, demonstrating concordance with the conventional slit lamp examination.

Invigorasi Larutan Bawang Merah Terhadap Viabilitas dan Vigor Tiga Benih Padi Varietas Lokal

Rice production in South Kalimantan during January to September 2020 decreased compared to 2019. The use of rice seeds per hectare is generally still not in accordance with the recommendations. The local varieties of rice seeds that cultivated are from last year's cropping season, where storage was not good which could lead to a decrease in seed quality. Shallots contain hormones auxin and gibberellins, can be used as a natural growth regulator. This study used a solution of shallots on three local varieties of rice seeds. The purpose of this study was to provide information on the use of natural growth regulators in shallot solution as an alternative to increase seed viability to become a provider of quality seeds. This research carried out from October to November 2021 at the Production Laboratory of the Department of Agroecotechnology, Faculty of Agriculture, Lambung Mangkurat University. The implementation of the research is making shallot stock solution, seed preparation, seed soaking, seed germination, and maintenance. The method used was qualitative using single factor Completely Randomized Design with three levels of treatment and each treatment consisted of five replications. The results showed that treatment using onion solution invigoration had a significant effects on the parameters of growth uniformity and maximum growth potential of expired local rice seeds of Siam Banjar variety. The highest growth speed and seed germination were found in Siam Saba variety. The highest growth uniformity was found in Siam Unus variety. The highest maximum growth potential is found in Siam Mutiara variety.