Method For Quantitative Characterization Research Articles

Drought propagation and its driving forces in central Asia under climate change

Drought propagation time (PT) and threshold (TR) play crucial roles in real-time monitoring of drought progression and severity under climate change, for which there is currently no unified method or standard for quantitative characterization. Central Asia (CA), a prototypical arid region, is frequently plagued by droughts that profoundly impact its ecology and socioeconomic framework, leaving a lack of comprehension about the transition from meteorological to soil moisture drought as for the complex impact of ground-atmosphere interaction. Therefore, this study revealed high-resolution PT and TR across CA based on precipitation and soil moisture datasets by employing a Bayesian causal framework for drought propagation modeling, in which the sliding window with the random forest method was integrated to investigate the dynamic changes and driving factors of drought propagation over recent decades. The conclusions drawn are as follows: (1) in the southeastern hilly and eastern plateau, a prolonged PT (i.e., longer than 100 days) was experienced during the extremities of the growing season, while most areas had a shorter mid-season PT (i.e., less than 40 days), in which the soil moisture drought intensity was positively correlated with longer PTs; (2) from 1948 to 2022, the central and western regions in CA generally displayed lower TR values than those in the northeast, seldom exceeding 30 mm, reflecting the regional precipitation gradient and the positive relationship between TR and severe soil moisture droughts; and (3) the increase in vapor pressure deficit (VPD), the decrease in aridity index (AI) for the reduced precipitation, and the considerable impact of vegetation transpiration on soil moisture consumption contributed to accelerated drought propagation. Overall, this study reveals the complex dynamics and mechanisms of drought propagation amid environmental changes, laying the foundation for innovative drought early warning systems and emergency management approaches in CA.

Asymmetric optical properties and bandgap shift of pre-strained flexible ZnO films

Strain engineering has been extensively explored to modulate the various intrinsic properties of flexible inorganic semiconductor films. However, experimental characterization of tensile and compressive strain-induced modulation of optoelectronic properties and their differences has not been easily implemented in flexible inorganic semiconductor films. Herein, the strain-dependent structural, optical, and optoelectronic properties of flexible ZnO films under pre-tensile and pre-compressive strains are systemically investigated by a Mueller matrix ellipsometry-based quantitative characterization method combined with x-ray diffraction and first-principle calculation. With extended prestress-driven deposition processing under bi-direction bending modes, pre-tensile and pre-compressive strains with symmetric magnitudes can be achieved in flexible ZnO films, which allows precise observation of the strain-driven asymmetric modulation of optoelectronic properties. When the applied prestrain varies approximately equally from 0% (baseline) to −0.99% (compression) and 1.07% (tensility), respectively, the relative changes for the c-axis lattice constant are 0.0133 and 0.0104 Å, respectively. Meanwhile, the dependence factors of the bandgap energy on the pre-compression and pre-tensile strains were determined as −0.0099 and −0.0156 eV/%, respectively, and the complex refractive index also presents an asymmetric varying trend. With the help of the strain–stress analysis and the first-principle calculation, the intriguing asymmetric strain-optical modulation effect could be attributed to the biaxial strain mechanism and the difference in the deformation potential between the two prestrain modes. These systematic investigation consequences are thus promising as a basis for the booming applications of the flexible inorganic semiconductor ensemble.

Development of a GC-FID method for quantitative characterisation of polyglycerols in polyglycerol polyricinoleate (PGPR) present in a lipid matrix

PGPR is an emulsifier (E476) widely used in the food industry. In this study, a gas chromatography–flame ionisation detection (GC-FID) method was developed for the quantitative characterisation of the polyglycerol composition of PGPR. The method was validated to analyse quantitatively the polyglycerol species in neat PGPR products and in PGPR samples present in a lipid matrix. This method consists of saponification, acidification and petroleum ether extraction to remove interfering fatty acids, neutralisation, silylation and finally GC-FID analysis. Phenyl β-D-glucopyranoside was used as internal standard as sorbitol proved unsuitable due to its susceptibility to interference from Na/K chloride during silylation. The response factors of glycerol and diglycerol towards phenyl β-D-glucopyranoside were determined using pure standards, while response factors of polyglycerols with a degree of polymerisation of at least 3 could be reliably estimated according to an effective carbon number (ECN) approach. The validity of the method applied to PGPR samples was further supported on the basis of a mass balance considering the experimentally determined polyglycerol and fatty acid content. Moreover, recoveries of di-, tri-, tetra- and pentaglycerol were more than 95% for various PGPR samples added to two different lipid matrices at 2 wt% and 5 wt% concentrations. Furthermore, the method proved to be very repeatable (with relative standard deviation values below 2.2%). On the other hand, the inevitable presence of glycerol in the lipid samples caused fouling of the detector and column overloading, requiring frequent cleaning of the detector and trimming off part of the column.

Quantitative Characterization of Respiratory Patterns on Dynamic Higher Temporal Resolution MRI to Stratify Postacute Covid-19 Patients by Cardiopulmonary Symptom Burden.

Postacute Covid-19 patients commonly present with respiratory symptoms; however, a noninvasive imaging method for quantitative characterization of respiratory patterns is lacking. To evaluate if quantitative characterization of respiratory pattern on free-breathing higher temporal resolution MRI stratifies patients by cardiopulmonary symptom burden. Prospective analysis of retrospectively acquired data. A total of 37 postacute Covid-19 patients (25 male; median [interquartile range (IQR)] age: 58 [42-64] years; median [IQR] days from acute infection: 335 [186-449]). 0.55 T/two-dimensional coronal true fast imaging with steady-state free precession (trueFISP) at higher temporal resolution. Patients were stratified into three groups based on presence of no (N = 11), 1 (N = 14), or ≥2 (N = 14) cardiopulmonary symptoms, assessed using a standardized symptom inventory within 1 month of MRI. An automated lung postprocessing workflow segmented each lung in each trueFISP image (temporal resolution 0.2 seconds) and respiratory curves were generated. Quantitative parameters were derived including tidal lung area, rates of inspiration and expiration, lung area coefficient of variability (CV), and respiratory incoherence (departure from sinusoidal pattern) were. Pulmonary function tests were recorded if within 1 month of MRI. Qualitative assessment of respiratory pattern and lung opacity was performed by three independent readers with 6, 9, and 23 years of experience. Analysis of variance to assess differences in demographic, clinical, and quantitative MRI parameters among groups; univariable analysis and multinomial logistic regression modeling to determine features predictive of patient symptom status; Akaike information criterion to compare the quality of regression models; Cohen and Fleiss kappa (κ) to quantify inter-reader reliability. Two-sided 5% significance level was used. Tidal area and lung area CV were significantly higher in patients with two or more symptoms than in those with one or no symptoms (area: 15.4 cm2 vs. 12.9 cm2 vs. 12.8 cm2 ; CV: 0.072, 0.067, and 0.058). Respiratory incoherence was significantly higher in patients with two or more symptoms than in those with one or no symptoms (0.05 vs. 0.043 vs. 0.033). There were no significant differences in patient age (P = 0.19), sex (P = 0.88), lung opacity severity (P = 0.48), or pulmonary function tests (P = 0.35-0.97) among groups. Qualitative reader assessment did not distinguish between groups and showed slight inter-reader agreement (κ = 0.05-0.11). Quantitative respiratory pattern measures derived from dynamic higher-temporal resolution MRI have potential to stratify patients by symptom burden in a postacute Covid-19 cohort. 3 TECHNICAL EFFICACY: Stage 3.

Study on working mechanism and performance of deep groove seal at high temperature and high speed in mixed lubrication

The deep groove seal is a kind of mechanical seal with millimeter depth grooves on the end face of the sealing ring, widely used in aviation and nuclear fields. However, its working mechanism and sealing performance are still unclear. In this research, a fluid-solid-thermal coupling numerical analysis model at high temperature and high speed in mixed lubrication is established to solve these problems. Mechanism analysis indicates that deep grooves cause circumferential waviness of micron level on the end face, strongly affecting the sealing performance. A quantitative characterization method is proposed, solving the characteristic parameters and analytical expression of deep groove seal waviness, so that the deep groove seal can be approximately equivalent to the waviness seal and be explained by the law of the waviness seal. The sealing performance can be controlled through the design of groove parameters. The results have been verified by the experiment. The fluid-solid-thermal coupling model and characterization method of equivalent waviness parameters for the deep groove seal proposed in this article provide a theoretical basis for further study of the mechanism and performance of the deep groove seal.

Largely Enhanced Service Life and Energy Harvesting Stability of Dielectric Elastomer Generator by Designing and Optimizing Compliance of Electrodes.

Dielectric elastomer generator (DEG), which consists of a dielectric elastomer (DE) film sandwiched between two flexible electrodes (FEs), has the advantages of lightweight, high energy density, and high energy conversion efficiency, providing a simple and feasible solution for harvesting energy from human motion or nature. As crucial constituents of DEG, FEs are expected to possess excellent conductivity and compliance. Nevertheless, there is currently no quantitative characterization method for FE compliance. In addition, the impact mechanism of FE compliance on the energy harvesting performance and fatigue life of the DEG remains unclear. In this study, the dynamic mechanical property (DMP) was used to assess the compliance of FEs, and the quantitative characterization method of FE compliance was proposed. A series of silicone rubber electrodes (SREs) with different DMPs and compliance were designed and prepared, and the impact mechanism of FE compliance on the energy harvesting stability and fatigue life of the DEG was investigated. The results indicate that the key to achieving excellent FE compliance lies in reducing the difference in the magnitude of the complex modulus and phase angle between the FEs and DE, which can significantly reduce interfacial friction and extend the fatigue life of DEG. Benefiting from the enhanced FE compliance, the fatigue life and full-life energy density of the DEG device increase by 20.3 times and 26.4 times, respectively, compared with those of the commonly used carbon-based electrodes.

Characterization and reconstruction of rough fractures based on vector statistics

The characteristics of fracture networks are of great significance for unconventional geo-energy exploitation such as shale oil, shale gas and geo-thermal extraction. Natural fractures and induced fractures after reservoir stimulation control the mechanical properties and fluid flow of the reservoirs. The quantitative characterization and reconstruction of rough fractures are essential for studying the fluid flow and mechanical properties of the reservoirs with complicated fracture networks. Based on vector statistics, a vector statistical method (VSM) for quantitative characterization of rough fractures is proposed and tested using 10 standard joint profiles. Furthermore, the growth vector counting method (counting method) and growth vector probability method (probability method) for single rough fractures in two-dimensional (2D) and three-dimensional (3D) models are proposed. Afterward, a morphology comparison and quantitative evaluation of single rough fractures before and after reconstruction are conducted. When the counting and probability methods are used to reconstruct single rough fractures, the difference in the tortuosity and fractal dimensions of the original and reconstructed fractures are less than 5% and 2.5%, respectively. It implies the counting and probability methods proposed herein can reconstruct rough fractures with approximate statistical characteristics and quantitative characterization parameters. Subsequently, the counting and probability methods for single rough fractures are further developed for 2D and 3D modeling of conventional and rough discrete fracture networks. The results indicate that the growth vector counting and probability methods proposed in this study have significant potential for rough discrete fracture network modeling. In addition, the merits and limitations of the proposed algorithms in modeling discrete fracture network models are discussed.

Photoacoustic elastography based on laser-excited shear wave

Elastography can be used as a diagnostic method for quantitative characterization of tissue hardness information and thus, differential changes in pathophysiological states of tissues. In this study, we propose a new method for shear wave elastography (SWE) based on laser-excited shear wave, called photoacoustic shear wave elastography (PASWE), which combines photoacoustic (PA) technology with ultrafast ultrasound imaging. By using a focused laser to excite shear waves and ultrafast ultrasonic imaging for detection, high-frequency excitation of shear waves and noncontact elastic imaging can be realized. The laser can stimulate the tissue with the light absorption characteristic to produce the thermal expansion, thus producing the shear wave. The frequency of shear wave induced by laser is higher and the frequency band is wider. By tracking the propagation of shear wave, Young’s modulus of tissue is reconstructed in the whole shear wave propagation region to further evaluate the elastic information of tissue. The feasibility of the method is verified by experiments. Compared with the experimental results of supersonic shear imaging (SSI), it is proved that the method can be used for quantitative elastic imaging of the phantoms. In addition, compared with the SSI method, this method can realize the noncontact excitation of the shear wave, and the frequency of the shear wave excited by the laser is higher than that of the acoustic radiation force (ARF), so the spatial resolution is higher. Compared to the traditional PA elastic imaging method, this method can obtain a larger imaging depth under the premise of ensuring the imaging resolution, and it has potential application value in the clinical diagnosis of diseases requiring noncontact quantitative elasticity.

Quantitative Evaluation of Paleocene Reservoir Diagenetic Facies by Logging in Lishui West Sag, East China Sea Basin

Exploration in the Lishui West Sag of the East China Sea Basin is limited by the scarcity of offshore drilling sites, and the prediction of deep, high-quality reservoirs is challenging using only geophysical methods. This study introduces a quantitative approach to diagenetic facies division in individual wells based on logging data, providing a new method and perspective for the prediction of deep, high-quality reservoirs. We employed comprehensive data from core, logging, thin-section casting, cathodoluminescence, scanning electron microscopy, and X-ray diffraction analyses from five wells to study the petrology, physical properties, diagenetic types and strength, and diagenetic minerals of the Paleocene sandstone reservoirs in the Lishui West Sag. Apparent compaction rate, apparent cementation rate, and other quantitative characterization parameters were used to calculate the comprehensive diagenetic coefficient (Cg), and the diagenetic facies were divided into compaction, cementation, and dissolution facies. A logging calculation model for the comprehensive diagenetic coefficient (Cg) and a quantitative identification method for diagenetic facies in individual well reservoirs were established through a fitting analysis between Cg and logging curve parameters. Continuous quantitative identification of vertical diagenetic facies in the five wells in the study area showed that the high-quality reservoirs in wells L1, L2, and L3 within the L1 gas field are characterized by extensive development of dissolution facies, while wells L4 and L5 are dominated by compaction and cementation facies, with poor reservoir properties and no industrial gas flow output. The results demonstrate the reliability of the model method. The establishment of this quantitative characterization method for diagenetic facies using logging data provides guidance for the prediction of favorable reservoirs.

Evaluation and quantitative characterization for the ecological environment impact of open pit mining on vegetation destruction from landsat time series: A case study of Wulishan limestone mine

Quantitatively evaluating the ecological environment impacts of vegetation destruction due to open-pit mining activities is vital for enhancing the green mining standard and cost management capabilities of mining enterprises. Based on the Landsat time series, this study proposes an ecological environment impact assessment and quantitative characterization method for vegetation destruction in mining areas resulting from open-pit mining activities. First, the modified normalized difference water index and the normalized difference vegetation index time series data were calculated. The water body thresholds and the fraction of vegetation coverage were ascertained using the K-means clustering algorithm and the dimidiate pixel model, respectively, to determine the area of direct vegetation destruction in mining areas. Second, utilizing the Theil-Sen Median trend analysis and the Mann-Kendall test, the indirect impact area of vegetation in the mining region was identified. Lastly, by integrating vegetation's net primary productivity with the Chinese Emission Allowance price index, the total carbon emission cost of vegetation destruction due to mining activities over 20 years was calculated to be about 2.122 million yuan. The findings indicated that the ecological environmental impact of open-pit mining activities on vegetation destruction cannot be ignored. From 2000 to 2020, open-pit mining at the Wulishan limestone mine in Anhui Province, China, increased the area of direct vegetation destruction by 9.072 × 105 m2, and the indirect impact area on vegetation was 7.371 × 105 m2. The carbon emission cost of vegetation destruction in the direct destruction area was about 104,000 yuan per year, and the carbon emission cost of vegetation damage in the indirect impact area was approximately 2,082.53 yuan per year. This research provides a scientific foundation for ecological environmental protection, regulations, green mining, and cost management for mining enterprises, promoting the harmonious progress of both the economy and environmental protection.

Study on Dynamic Crack Expansion and Size Effect of Back–Filling Concrete under Uniaxial Compression

With the continuous expansion of the application range of gob–side entry retaining technology, the depth, height, and advancing speed of coal seams also increase, which brings great problems to the stability control of surrounding rock structures of gob–side entry retaining. As one of the main bearing structures of the surrounding rock, the stability of the roadway–side support body is a key factor for the success of gob–side entry retaining. In order to study the deformation characteristics and instability mechanism of roadway-side support body, based on the roadway–side support materials of gob-side entry retaining, the dynamic expansion test of back–filling concrete cracks under uniaxial compression was carried out. The YOLOv5 algorithm was applied to establish the fine identification and quantitative characterization method of macroscopic cracks of the samples, and the dynamic expansion rule of roadway-side support body cracks and its dimensional effect were revealed by combining the fractal theory. The results show that the F1 value and average precision mean of the intelligent dynamic crack identification model reached 75% and 71%, respectively, the GIoU loss value tends to fit around 0.038, and the model reached the overall optimal solution. During the uniaxial compression process, micro cracks on the surface of the back–filling concrete first initiated at the end, and after reaching the yield stress, the macroscopic cracks developed significantly. Moreover, several secondary cracks expanded, pooled, and connected from the middle of the specimen to the two ends, inducing the overall instability of the specimen. The surface crack expansion rate, density, and fractal dimension all show stage change characteristics with the increase in stress, and the main crack expansion rate has obvious precursor characteristics. With the increase in the size, the decrease in crack density after back–filling concrete failures gradually decreases from 93.19% to 4.08%, the surface crack network develops from complex to simple, and the failure mode transits from tensile failure to shear failure. The above research results provide a basic experimental basis for design optimization and instability prediction of a roadway–side support body for engineering-scale applications.

Novel quantitative method for characterization of hippocampal sclerosis and its association with other neuropathologies and cognitive deficits

AbstractBackgroundHippocampal sclerosis of aging (HS) is characterized by neuronal loss and astrogliosis in subiculum and/or CA1 subfield of hippocampus. Using a novel quantitative approach, we studied the prevalence and localization of HS pathology in a well‐characterized oldest‐old cohort and examined its association with other neuropathologic changes and cognitive impairment.MethodsWe studied 409 consecutive autopsied participants of The 90+ Study with longitudinal assessments. In those with HS by traditional method (presence/absence), we used digitized hematoxylin and eosin and luxol fast blue hippocampal slides for further quantitative analysis. Using QuPath, we measured the length of each hippocampal subfield partitioned into three subregions (Figure1). We then calculated the proportion affected by HS for each subregion. Both traditional (presence/absence) and quantitative (subfield‐specific proportions) measures were used to study the relationship between HS and other neuropathologic changes and cognitive outcomes using regression models adjusted for sex, age at death, and education with all neuropathologic changes as covariates.ResultsHS was present in 11% of participants and was always focal, mostly affecting CA1 (89%), followed by subiculum (27%). Overlapping CA1/subiculum pathology was seen in 16% (Figure2). Left‐sided HS was more frequent (75%) than right‐sided (18%). Bilateral cases were the least frequent (7%). HS presence (traditional measure) was only associated with Limbic‐predominant age‐related TDP‐43 encephalopathy (LATE) (OR = 3.45, p<0.001). Quantitative measures revealed that HS proportion in subiculum and CA1 was associated with arteriolosclerosis (t36 = 4.11, p = 0.001) and LATE (t35 = 2.98, p = 0.005). HS proportion in subiculum alone was inversely associated with microvascular lesions (t41 = ‐3.16, p = 0.003) (Table1). HS proportion in subiculum and CA1 was associated with dementia at death and impairment of memory, language, calculation, and orientation. HS proportion in subiculum was additionally associated with impaired executive function. HS traditional measure was only associated with impaired orientation (Table1).ConclusionBased on our novel quantitative analysis, HS pathology was always focal, mostly unilateral, and associated with dementia and impairment in major cognitive domains. We found associations between HS and vascular pathologies that were not detected using traditional measure. The associations of HS with dementia and impaired memory, language, and calculation, identified with our quantitative method, were not detected using traditional measure.

Inverse Determination Of Interfacial Properties of a Bonded Structure Using Lamb Waves Generated By Laser Lateral Excitation

Nondestructive testing of the adhesive bond properties of a bonded structure is essential in aviation, automotive, and other industries. In this study, a Lamb wave–based quantitative characterization method is proposed to determine the interfacial stiffness of bonded structures. A theoretical model is established, with which the dispersion relationship of Lamb waves in a bonded structure is investigated. Different interfacial states ranging from a perfect bond to a weak bond are simulated, and the numerical results show the sensitivity of Lamb waves to interfacial stiffness. A lateral excitation method is proposed to enhance the excitation of the interfacial sensitive Lamb wave modes, and laser ultrasonic experiments show the enhancement of the Lamb wave signals on aluminum-epoxy-aluminum samples generated by the lateral excitation method. Then, a rapid construction method of inversion objective function is presented to reconstruct the interfacial stiffness coefficient of a bonded structure, and its functionality is validated via finite element simulations. Finally, the interfacial properties of the samples are reconstructed using the inversion scheme.

In-situ study of texture-breakage coupling in a copper ore using X-ray micro-CT

As the mining industry continues to seek greater energy efficiency, it needs more effective characterization of ore material as it progresses from mine to mill. The energy cost of ore mineral liberation, for example, is critically dependent on management of rock breakage from blasting to comminution. The study reported here presents a quantitative method for 3D characterization of ore texture and breakage based on X-ray micro-CT and in-situ micromechanical test. A porphyry copper ore is studied from its initial mechanical failure to the onset of fragmentation. This work integrates a quantitative ore textural analysis with 3D mapping of both the dominant minerals and micro-porosity in the ore sample. It enables us to show, as the fractured ore is still under loading, that internal breakage of feldspar grains dominates grain boundary fracturing. We discuss how the microporous regions, mostly found in hydrothermally altered plagioclase, may act as a weakening factor leading to the dominant breakage of plagioclase. We measure quantitatively and discuss how size reduction, ore texture and breakage characteristics control the degree of liberation of Cu minerals. Combining characterisation of ore texture with breakage in 3D could provide much needed insights for achieving more energy-efficient comminution and optimal liberation of critical minerals.

ZAFG Method for Quantitative Characterization of Spherical Particles: Deriving a Universal Equation for Geometrical Correction.

This study introduces a universal equation to calculate the geometrical correction factor (G) as the fourth factor in the conventional ZAF method for quantifying spherical particles (specifically, NIST-K411 glass microspheres mounted on bulk carbon substrate). Note that the fluorescence correction factor (F) is not considered in this study. Our findings demonstrate that the G factor, as a function of the particle diameter (D) and the range of emitted X-rays in a bulk sample (Xe), provides the best model. Xe depends on the chemical composition and accelerating voltage. We observed excellent agreement between the G factor predicted by our model and experimental data obtained from NIST-K411 standard particles. Our results show that when Xe is greater than D, the G factor decays exponentially, independent of the incident electron energy, X-ray lines, and chemical composition of the particles. We also found that when DXe > 1, the particle behaves as a bulk sample, and G = 1. Notably, our data indicate that the G factor depends only on DXe, not on the chemical composition or beam energy.

Visualization and quantitative evaluation of delamination defects in GFRPs via sparse millimeter-wave imaging and image processing

Multilayer glass fiber reinforced polymer (GFRP) has broad applications, playing a pivotal role in various fields including aerospace and wind energy production. These structures may develop internal delamination defects during their manufacture or service, which can significantly impair the integrity and safety of the equipment. Thus, the inspection of such delamination defects during the service life of the equipment is crucial for assessing its operational performance and lifespan. Millimeter-wave (MMW) nondestructive testing (NDT) presents a promising method for detecting these defects in GFRPs, due to its high resolution and powerful penetration characteristics. This paper proposes a visual NDT and quantitative characterization method based on sparse imaging and image processing. This method encompasses the following three key points. (i) To facilitate rapid detection and visualization in monostatic mode, we proposed a detection approach utilizing sparse scanning and imaging. Initially, we developed a sparse sampling control matrix grounded to guide the probe for spatial automatic sparse sampling, thereby enhancing data acquisition efficiency and reducing data volume. Subsequently, we introduced a rapid sparse imaging method, integrating wave spectrum reconstruction and compressed sensing (CS). Beginning from the original data domain, we designed a fast imaging operator employing forward and inverse transformations of spectrum reconstruction imaging. (ii) In order to further refine the quality of the detection images, we proposed an adaptive singular value decomposition (SVD) approach to suppress the coupling signal and enhance the specimen signal. By adaptively adjusting the singular values, we generated a signal with the optimal target-to-background ratio (TBR). (iii) We ascertained the position and area parameters of the delamination defects using the proposed defect quantification method, combining image segmentation and image statistics. Experimental validation affirmed the effectiveness of the proposed method, revealing the following results: 1) The proposed method, despite utilizing a small amount of observational data, generates better visual images while maintaining efficient detection; 2) It can effectively identify all 0.5 mm-thick internal delamination defects in GFRPs, simultaneously retaining high quantitative characterization precision; 3) The positional quantification error remains less than 0.5 mm, and the relative area quantification error is constrained within 8%.

Biofilm development of Candida boidinii and the effect of tyrosol on biofilm formation

ObjectivesThe applicability of a simple and high-throughput method for quantitative characterization of biofilm formation by Candida boidinii was tested in order to evaluate the effects of exogenous tyrosol on yeast growth and biofilm formation capacity.ResultsSignificant concentration-, temperature and time-dependent effect of tyrosol (2-(4-hydroxyphenyl)ethanol) was demonstrated, but it differentially affected the growth and biofilm formation (characterized by crystal violet staining and XTT-reduction assay) of Candida boidinii. Testing biofilm based on metabolic activity displayed sensitively the differences in the intensity of biofilm in terms of temperature, tyrosol concentration, and exposure time. At 22 °C after 24 h none of the tyrosol concentrations had significant effect, while at 30 °C tyrosol-mediated inhibition was observed at 50 mM and 100 mM concentration. After 48 h and 72 h at 22 °C, biofilm formation was stimulated at 6.25–25 mM concentrations, meanwhile at 30 °C tyrosol decreased the biofilm metabolic activity proportionally with the concentration.ConclusionsThe research concludes that exogenous tyrosol exerts unusual effects on Candida boidinii growth and biofilm formation ability and predicts its potential application as a regulating factor of various fermentations by Candida boidinii.

STATISTICAL ASPECTS OF THE STUDY OF THE DYNAMICS OF INDUSTRIAL ENTERPRISES DEVELOPMENT

The article presents practical aspects of statistical research of the dynamics of development of industrial enterprises. It is determined that the main task of a statistical study of industrial enterprises is to determine the volume of industrial production, its structure; analysis of plan implementation by volume and assortment, grade, completeness, rhythm; identification of additional reserves. It is proved that in order to raise the level of industrial production statistics in Ukraine, it is necessary to make certain changes in the proportions of individual industries, and they should be consistent and interrelated. The study found that the main factors of industrial recovery will be: a gradual improvement in the situation on world markets, the resumption of production in certain sectors of the economy, improvement of the financial condition of enterprises, as well as an increase in investment and consumer demand. The following mathematical and statistical methods are used depending on the purpose of the statistical study and the nature of the source data: 
 1) mathematical methods of quantitative characterization of relationships: correlation and regression analysis; operations research and queuing theory; economic cybernetics; classical methods of elementary mathematics; simulation modeling; functionally hierarchical (forecast scenarios); methods of structural analogy; method of expert estimates; 
 2) statistical methods of quantitative characterization of relationships: analysis of variance; correlation analysis; method of analytical groupings; rank correlation; complex statistical coefficients; statistical equations of dependencies; statistical indices; indicators of dynamics analysis.
 When choosing statistical methods for studying socio-economic phenomena, it is necessary to take into account their interconnectedness and interdependence. Any phenomenon is the result of a certain set of causes and is the cause of other phenomena and processes. Therefore, the statistical study of the interrelationships of economic phenomena and processes should be approached comprehensively, trying to classify a wide range of methods that allow them to be quantified.

Quantitative characterization method of 3D roughness of rock mass structural surface considering size effect

The surface morphology of the structural surface of the rock mass plays a crucial role in determining its macroscopic physical and mechanical properties, including shear strength and seepage characteristics. The morphological characteristics of the rock mass structure exhibit significant anisotropy and size effects. The distribution characteristics of the two key indicators that affect the morphological characteristics of the structure were analyzed, revealing that the undulation degree and undulation angle conform to the normal distribution and Weibull distribution, respectively. The present study defines a method for quantifying the 3D roughness of structural surface based on the features of undulation degree and undulation angle. Through quantitative analysis, it was observed that the roughness parameters exhibit anisotropic characteristics at different sampling intervals and shear directions.

Exploration on the characteristics of 3D crack network expansion induced by hydraulic fracturing: A hybrid approach combining experiments and algorithms

To efficiently develop and utilize unconventional energy, it is essential to investigate the characteristics of 3D crack network expansion during sandstone hydraulic fracturing (HF). This paper presents the results of physical simulation experiments of sandstone HF under varying shear stress levels, where CT image data acquisition was used to enable 3D reconstruction and establishment of identification algorithms for 3D crack network. The graph theory representation method of crack network was improved using the intersection and extension of crack branch elements as precursors for two vertex sets U and V of a bipartite graph G=(U,V,E), extending the topological structure representation method to 3D crack network. Using topology and fractal theory, a quantitative characterization method of crack network was developed, which comprehensively considered topological structure parameters and fractal dimension. The findings showed that the fractal dimension of the crack increases linearly with the increase of the shear stress level, and the parameters of the crack topological structure increased first and then decreased. While the parameters of the crack topological structure first increased and then decreased.