Disturbance Factors Research Articles

Automatic Fault Detection Method of Rotating Machinery Bearing Based on Complexity Analysis

In order to improve the working condition stability of rotating machinery bearings, an automatic fault detection method of rotating machinery bearings based on complexity analysis is proposed. The parameters of rotating machinery bearings are detected by using discrete sensor detection method, and the fault characteristics of rotating machinery bearings are extracted by fault type parameter extraction method. The complexity of rotating machinery bearings is detected by wavelet transform and fuzzy logic analysis. Considering the load mutation, noise disturbance, control strategy and other factors of rotating machinery bearings, the fault diagnosis and feature analysis model of rotating machinery bearings is established. The clustering and feature detection of rotating machinery bearings’ fault types are realized by the method of discrete complexity fusion clustering. Based on adaptive feedback compensation and parameter estimation, the output diagnostic error is taken as the fault detection index parameter, and the feature estimation in normal state and fault state is realized by harmonic level detection, so as to realize automatic fault detection of rotating machinery bearings. The simulation results show that this method has high accuracy and small deviation in fault detection of rotating machinery bearings, which improves the ability of automatic fault diagnosis.

Effects of dredging wastewater input history and aquaculture type on greenhouse gas fluxes from mangrove sediments along the shorelines of the Jiulong River Estuary, China

Dredging wastewater (DW) from aquaculture ponds is a major disturbance factor in mangrove management, and its effects on the greenhouse gas (GHG) fluxes from mangrove sediment remain controversial. In this study, we investigated GHG (N2O, CH4, and CO2) fluxes from mangrove sediment at typical aquaculture pond–mangrove sites that were stimulated by DW discharged for different input histories and from different farm types. The GHG fluxes exhibited differing cumulative effects with increasing periods of DW input. The N2O and CH4 fluxes from mangrove sediment that received DW inputs for 17 y increased by ∼10 and ∼1.5 times, respectively, whereas the CO2 flux from mangrove sediment that received DW inputs for 11 y increased by ∼1 time. The effect of DW from shrimp ponds on the N2O flux was significantly larger than those of DW from fish/crab ponds and razor clam ponds. Moreover, the total global warming potentials (GWPs) at the field sites with DW inputs increased by 29–129% of which the CO2 flux was the main contributor to the GWP (85–96%). N2O as a proportion of CO2-equivalent flux increased from 2% to 12%, indicating that N2O was an important contributor to the increase in GWP. Overall, DW increased the GHG fluxes from mangrove sediments, indicating that the contribution of mangroves to climate warming was enhanced under DW input. It also implies that the carbon sequestration potential of mangrove sediments may be threatened to some extent. Therefore, future assessments of the carbon sequestration capacity of mangroves at regional or global scales should consider this phenomenon.

Responses of multimetric indices to disturbance are affected by index construction features

Multimetric indices (MMIs) are used worldwide to assess the ecological conditions of aquatic and terrestrial ecosystems. Different criteria and approaches are used to construct MMIs, resulting in widely different indices. Therefore, scientists, managers, and policymakers sometimes question whether such MMIs are useful for biomonitoring and bioassessment programs. Crucial design issues for biomonitoring programs include MMI responsiveness, the bioindicator group used, survey design, field sampling methods, level of taxonomic resolution, metric selection and scoring, and reference condition identification. We performed a meta-analysis on MMI development and applications worldwide to analyze the response of MMIs to different disturbance factors and to determine the degree to which MMI construction features influence their responsiveness to anthropogenic disturbances. We used the Web of Science database to find articles that applied an MMI and related MMI values to an environmental stressor, and we extracted data from 157 articles. We performed random-effects modeling to estimate the overall effect of MMI responses to disturbance and used subgroup analysis to analyze the extent to which the effect sizes varied as a function of different MMI construction features. We found that reference condition criteria had the major effect on MMI responses to disturbance. The environmental disturbance type, the number of metrics, and the ecosystem type to which MMIs were applied contributed more weakly to the effect size variance. The general response of MMIs to disturbance was little affected by the bioindicator group, taxonomic resolution, metric selection criteria, or scoring method. These findings have important implications for designing biomonitoring programs, including developing and improving cost-effective biological indices, because they could enhance MMI development and application protocols.

УЛОГА ДИМЕНЗИЈА КВАЛИТЕТА ПОРОДИЧНИХ ИНТЕРАКЦИЈА И ШКОЛСКОГ ЖИВОТА У ПРЕДИКЦИЈИ ШКОЛСКЕ ДИСЦИПЛИНЕ

The problem of school discipline has a long history, however, it still represents an important disturbing factor in the course of teaching. As the teaching staff faces difficulties in eliminating unwanted behavior of students and maintaining discipline, it is essential to have a good knowledge of the etiology of school discipline in order to effectively work on its prevention. The subject of this research is the examination of the predictive power of dimensions of the quality of family interactions and school life in predicting school discipline. The sample consisted of 200 respondents, fourth-grade students of high schools from the territory of the city of Leskovac. School discipline is operationalized by the School Indiscipline Scalе, dimensions of the quality of family interactions with the Scale of the quality of family interactions, while the Quality of School Life Questionnaire was used to examine the dimensions of the quality of school life. The expected correlations of certain dimensions of the quality of school life and family interactions with the dimensions of school indiscipline were determined. Through the procedure of hierarchical regression analysis, it was determined that the dimensions of the quality of family interactions are not single statistically significant predictors of the dimensions of school indiscipline

Research on the expansion and optimization control strategy of cascaded rectifier H-bridge

Extensive research on the multi-bridge extension of cascaded rectifier stages is deemed important to meet the requirements of high-voltage and high-power applications. Two control structures for capacitor voltage balancing in cascaded rectifier stages are analyzed in this paper. On this basis, the balance strategy for the multi-bridge extension of single-phase cascaded rectifiers is explored. The balance method of ultra-fast balance modulation trajectories is introduced into single-phase multi-bridge cascaded rectification, and the optimal control strategy is selected through simulation verification and comparative analysis. During the actual experiments, some disturbance factors were introduced into the system, causing an instantaneous unbalanced state. However, through the control strategy proposed in this paper, the system can quickly regain balance. Through simulation validation and analysis of the experimental results, the reliability and innovation of this control strategy have been demonstrated.

Postfire Forest Regrowth Algorithm Using Tasseled-Cap-Retrieved Indices

Wildfires are a common disturbance factor worldwide, especially over the last decade due to global climate change. Monitoring postfire forest regrowth provides fundamental information needed to enhance the management and support of ecosystem recovery after fires. The purpose of this study is to propose an algorithm for postfire forest regrowth monitoring using tasseled-cap-derived indices. A complex approach is used for its implementation, for which a model is developed based on three components—Disturbance Index (DI), Vector of Instantaneous Condition (VIC), and Direction Angle (DA). The final product—postfire regrowth (PFIR)—allows for a quantitative assessment of the intensity of regrowth. The proposed methodology is based on the linear orthogonal transformation of multispectral satellite images—tasseled cap transformation (TCT)—that increases the degree of identification of the three main components that change during a fire—soil, vegetation, and water/moisture—and implies a higher accuracy of the assessments. The results provide a thematic raster representing the intensity of the regrowth classes, which are defined after the PFIR threshold values are determined (HRI—high regrowth intensity; MRI—moderate regrowth intensity; and LRI—low regrowth intensity). The accuracy assessment procedure is conducted using very-high-resolution (VHR) aerial and satellite data from World View (WV) sensors, as well as multispectral Sentinel 2A images. Three different forest test sites affected by fire in Bulgaria are examined. The results show that the classified thematic raster maps are distinguished by a good performance in monitoring the regrowth dynamics, with an average overall accuracy of 62.1% for all three test sites, ranging from 73.9% to 48.4% for the individual forests.

Slope stability analysis applied to the 5th section of the Northern Marmara Motorway, İzmit, Türkiye

The Northern Marmara Motorway is a project that aims to alleviate the heavy traffic congestion in the provinces of İstanbul, Tekirdağ, Kocaeli and Adapazarı. Within the 5th section bounded by “the Motorway Port Connection Road” and “İzmit Intersection”, mass movements of slide (Y1, Y2) and flow (Y3) types were observed along the route. This study investigated the causes of mass movements in the Korucu Formation, which consists of sandstone and shale alternation. It also evaluated the support systems to prevent these movements. The analysis considered project criteria, both static and dynamic conditions, types of mass movements and triggering factors. The study identified a combination of factors, including the water table and surface waters, which lead to progressive weathering and mass movement. Stability analyses were conducted for specific right-cut slope sections. These analyses included assessments of soil structure, soil–rock mechanics, engineering geology and geotechnics, as well as examination of field and laboratory test results. These analyses aimed to comprehensively investigate and understand the factors influencing the occurrence of mass movements, particularly for km: 170 + 300–170 + 400, km: 170 + 640 and km: 175 + 297–175 + 463. At Y1, pile retaining walls are proposed using Slide2 software to reduce the slope angle from 22° to 17°. At Y2, a translational landslide occurred with recommendations for the adjustment of the slope angle and protective measures considering the disturbance factors (D = 0.3 and D = 0.5). Y3 was a flow-type movement that required protection of the slope with riprap due to the different geological conditions and disturbance factors. This study underlines the need for a comprehensive geological analysis and structural measures to ensure safety in these areas.

Flicker Emission Analysis of a Wind Farm

In this paper is presented the criteria used by UTE, with respect to the Flicker emission of power plants; considering that this is one of the quality parameters monitored at the connection node. This work is focused in the flicker emission phenomenon. It sets out the criteria used to determine the emission limits for individual users connected to the distribution network. Additionally it presents a theoretical method, based on international standards, to estimate the total emission of flicker that will produce a wind farm in the connection node. The aim of this paper is to compare the theoretical emission flicker, with the field measurements in the connection node of a power generator. Here are calculated individual emission limits and the theoretical estimation of the flicker emission from a wind farm of 10MW connected to a network of 31.5kV. Finally, these values are compared with Pst and Plt parameters, short-term flicker disturbance factor and long-term flicker disturbance factor of the installation of wind turbines, which arise from a registry conducted in the field, with real data measured in the connection node of the wind farm.

Therapeutic Strategies in Children with Epilepsy: A Quality-of-Life-Related Perspective.

Back ground: Children with epilepsy are affected by several factors, including clinical and social variables. Among these variables, cognitive decline and behavioral disturbances, perceptions of stigma, and fatigue can lead to reductions in quality of life (QOL). Epileptic activities, including seizure severity, frequent seizures, and status epilepticus (SE), have been identified as important predictors of QOL. In addition, the frequency of interictal epileptiform discharges (IEDs) on electroencephalogram (EEG) may also be an important predictor of QOL, because IEDs can lead to cognitive decline and behavioral disturbances. Moreover, frequent seizures and/or IEDs may play a role in emotional mediators, such as stigma and fatigue, in childhood epilepsy. Seizure severity and/or IEDs are, therefore, important QOL-related factors in childhood epilepsy. Seizure severity as a QOL-related factor: Frontal lobe dysfunctions, such as cognitive decline and behavioral disturbances, can result in reduced QOL for both the child and their family. Frontal and prefrontal lobe growth disturbances can be present during active-phase epilepsy in some children with neuropsychological impairments. Recovery from prefrontal lobe growth disturbances may depend on the active seizure period. Children with a shorter active seizure period can recover from disturbances in prefrontal lobe growth more rapidly. In contrast, recovery may be delayed in children with a longer active seizure period. Moreover, frequent seizures can lead to seizure-associated headaches, perceptions of self-stigma and parental stigma, and fatigue. Accordingly, severe seizures can lead to neuropsychological impairments in association with prefrontal lobe growth disturbances in children with epilepsy. EEG abnormalities as QOL-related factors: IEDs on EEG, representing persistent pathological neuronal discharges, may be associated with several pathological aspects. Frontal IEDs can be a risk factor for recurrent seizures, cognitive decline, and behavioral disturbances, and they may also play a role as emotional mediators similar to stigma. In addition, behavioral disturbances may result in the presence of secondary bilateral synchrony (SBS) on EEG. Behavioral disturbances can be improved in association with a reduction in IEDs in children with frontal IEDs and SBS. Therefore, EEG abnormalities, such as frontal IEDs and SBS, can also lead to neuropsychological impairments in children with epilepsy. Therapeutic strategies in children with epilepsy: Seizure severity and IEDs on EEG may be associated with neuropsychological impairments, leading to QOL reduction. Therapeutic management may be desirable to reduce seizures and EEG abnormalities, such as frontal IEDs and SBS, as early as possible to improve QOL in children with epilepsy. During antiseizure medication (ASM) selection and adjustment, physicians should strategize the therapeutic approach to controlling seizures and suppressing EEG abnormalities in children with epilepsy. Among various ASMs, novel ASMs, such as levetiracetam and perampanel, may suppress both clinical seizures and IEDs on EEG; thus, these novel ASMs may represent an important addition to the treatments available for epileptic children presenting with frontal IEDs and SBS.

Study on the factors influencing ecological environment and zoning control: a study case of the Dongting Lake area

IntroductionProtecting the ecosystem of the Dongting Lake area is of utmost importance for maintaining ecological balance and achieving human well-being.MethodsThis study identifies the key factors influencing the remote sensing based ecological index (RESI) in the Dongting Lake area based on the spatial and temporal evolution characteristics of the RESI and environmental changes and anthropogenic disturbance factors. The priority zoning for ecological restoration was delineated in combination with the anthropogenic composite index (ACI). By exploring the influence of anthropogenic disturbances on RESI, the zoning locations were determined using spatial statistics and linear regression methods.ResultsThe overall RESI of the Dongting Lake area showed a decline from 2001 to 2020, with the mean value decreasing from 0.52 to 0.48. High-quality zones were mainly located in mountainous and forested areas, while low-quality zones were mainly distributed in more developed cities in the east urban area. Anthropogenic factors were the main reasons for the decline in the ecological environment, while natural factors showed a positive correlation with RESI. Based on the RESI and ACI, four ecological control zones (H-H, H-L, L-H, and L-L) were delineated, which accounted for a total of 45.66% of the Dongting Lake area. Among them, 3.91% required immediate control and management, while 17.80% required artificial maintenance. This study explores the influencing factors and mechanisms of the ecological environment quality in the Dongting Lake area, and explores the effective spatial paths for the implementation of ecological restoration zoning control and differentiated restoration strategies in the Dongting Lake area.DiscussionThis study provides a scientific basis for mitigating ecological and environmental problems in the Dongting Lake area, and provides a reference for ecological restoration and regulation and the realization of sustainable development goals in China and global regions with complex environmental problems.

Prevalence and risk factors for abnormal glucose metabolism in first-episode and drug-naïve major depressive disorder outpatients with comorbid anxiety: A cross-sectional study from a large sample of the Chinese Han population

BackgroundBoth abnormal glucose metabolism and anxiety have been reported to be common in major depressive disorder (MDD). However, few studies have explored glucose disturbances in first-episode and drug-naive (FEDN) MDD patients with anxiety. The purpose of this study was to examine the prevalence and risk factors of glucose disturbance in FEND MDD patients comorbid with anxiety. Methods1718 FEDN MDD patients were included in this study. The positive subscale of the Positive and Negative Syndrome Scale (PANSS), Hamilton Anxiety Rating Scale (HAMA), and Hamilton Depression Rating Scale (HAMD) were used to measure psychotic, anxiety and depressive symptoms respectively. Sociodemographic and biochemical indicators were also collected. ResultsThe prevalence of glucose disorders in MDD patients combined with anxiety was 15.7 %, significantly higher than in MDD patients without anxiety symptoms (7.1 %). Glucose disturbances were associated with HAMD score, HAMA score, thyroid-stimulating hormone (TSH), thyroid peroxidase antibody (TPOAb), anti-thyroglobulin (TGAb), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein (LDL-C), fasting blood glucose (FBG), systolic blood pressure (SBP), diastolic blood pressure (DBP), suicide attempts, and psychotic symptoms. Further logistic regression showed that illness duration, TSH, TGAb, and TPOAb levels were correlates of glucose disturbances in MDD patients with anxiety. LimitationsNo causal relationship could be drawn due to the cross-sectional design. ConclusionsOur findings suggest that TSH, TGAb and TPOAb may be promising biomarkers of glucose disturbances in MDD comorbid with anxiety, suggesting the importance of regular assessment of thyroid function parameters for abnormal glucose metabolism prevention.

MultiWD: Multi-label wellness dimensions in social media posts

Background:Halbert L. Dunn’s concept of wellness is a multi-dimensional aspect encompassing social and mental well-being. Neglecting these dimensions over time can have a negative impact on an individual’s mental health. The manual efforts employed in in-person therapy sessions reveal that underlying factors of mental disturbance if triggered, may lead to severe mental health disorders. Objective:In our research, we introduce a fine-grained approach focused on identifying indicators of wellness dimensions and mark their presence in self-narrated human-writings on Reddit social media platform. Design and Method:We present the MultiWD dataset, a curated collection comprising 3281 instances, as a specifically designed and annotated dataset that facilitates the identification of multiple wellness dimensions in Reddit posts. In our study, we introduce the task of identifying wellness dimensions and utilize state-of-the-art classifiers to solve this multi-label classification task. Results:Our findings highlights the best and comparative performance of fine-tuned large language models with fine-tuned BERT model. As such, we set BERT as a baseline model to tag wellness dimensions in a user-penned text with F1 score of 76.69. Conclusion:Our findings underscore the need of trustworthy and domain-specific knowledge infusion to develop more comprehensive and contextually-aware AI models for tagging and extracting wellness dimensions.

Research on military-civilian collaborative innovation of science and technology based on a stochastic differential game model.

The construction of an integrated national strategic system and capability is an essential goal of implementing the strategy of military-civilian integration in the contemporary era. And the collaborative innovation of military-civilian S&T is an inevitable choice to achieve this goal. Due to the dynamic, complex, and stochastic characteristics of military-civilian S&T collaborative innovation, the level of S&T innovation is highly volatile. This paper takes the internal and external stochastic disturbance factors of military-civilian S&T collaborative innovation as the perspective, studies the strategy selection problem of military-civilian S&T collaborative innovation under military domination, constructs a differential game model to explore the innovation strategies under the non-cooperative model without military subsidies, the non-cooperative model with military subsidies, and the collaborative model. Finally, we use numerical experiments to verify the validity of the conclusions. The study shows that: (1) Within a reasonable range of values of the benefit distribution coefficient, the system can achieve the Pareto optimum, and the collaborative model is conducive to improving the S&T innovation level and the optimum benefit level of the system. (2) Military subsidies can increase the benefits of the system and the parties involved to achieve Pareto improvement. (3) The level of S&T innovation under the collaborative model has dynamic evolutionary characteristics of maximum expectation and variance. As the intensity of disturbance increases, the stability of the system may be destroyed. Risk-averse civil enterprises prefer the cooperative mode, whereas risk-averse civil enterprises prefer the non-cooperative model.

The correlation between serum total bile acid and alanine aminotransferase of pregnant women and the disorders of neonatal hyperbilirubinemia-related amino acid metabolism

BackgroundTo explore the association between liver metabolism-related indicators in maternal serum and neonatal hyperbilirubinemia (NHB), and further investigate the predictive value of these indicators in NHB-related amino acid metabolism disorders.Methods51 NHB and 182 No-NHB newborns and their mothers who treated in the Fourth Hospital of Shijiazhuang from 2018 to 2022 were participated in the study. The differences in clinical data were compared by the Mann-Whitney U test and Chi-square test. Multivariate logistic regression was used to analyze the relationship between maternal serum indicators and the occurrence of NHB. The correlation analysis and risk factor assessment of maternal serum indicators with NHB-related amino acid metabolic disorders were performed using Spearman correlation analysis and multivariate logistic regression.ResultsCompared to the non NHB group, the NHB group had higher maternal serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), ALT/AST, and total bile acid (TBA), while lower levels of serum albumin (ALB), total cholesterol (TC) and high-density lipoprotein (HDL). The levels of alanine (ALA), valine (VAL), ornithine (ORN), and proline (PRO) in the newborns were reduced in NHB group, while arginine (ARG) showed a tendency to be elevated. Multiple logistic regression analysis showed that maternal ALT, AST, ALT/AST, and TBA levels were all at higher risk with the development of NHB, whereas ALB, TC, and HDL levels were negatively associated with NHB development. Increasing maternal TBA level was associated with lower ALA (r=-0.167, p = 0.011), VAL (r=-0.214, p = 0.001), ORN (r=-0.196, p = 0.003), and PRO in the newborns (r=-0.131, p = 0.045). Maternal ALT level was negatively associated with ALA (r=-0.135, p = 0.039), VAL (r=-0.177, p = 0.007), ORN (r=-0.257, p < 0.001), while ALT/AST was positively correlated with ARG (r = 0.133, p = 0.013). After adjustment for confounding factors, maternal serum TBA and ALT were the independent risk factor for neonatal ORN metabolic disorders [(adjusted odds ratio (AOR) = 0.379, 95%CI = 0.188–0.762, p = 0.006), (AOR = 0.441, 95%CI = 0.211–0.922, p = 0.030)]. Maternal ALT level was an independent risk factor for neonatal VAL metabolic disorders (AOR = 0.454, 95%CI = 0.218–0.949, p = 0.036).ConclusionsThe levels of high TBA, ALT, AST, and low HDL, TC of maternal were associated with the risk of NHB. Maternal TBA and ALT levels were independent risk factors for NHB-related amino acid disturbances which have value as predictive makers.

Adaptive optimal ℓ∞‐induced robust stabilization of minimum phase SISO plant under bounded disturbance and coprime factor perturbations

AbstractThis paper addresses the problem of optimal robust stabilization of a discrete‐time minimum‐phase plant in the framework of robust control theory in the setup and under poor a priori information. Coefficients of the transfer function of the plant nominal model with stable zeros are unknown and belong to a known bounded polyhedron in the space of coefficients. The gains of coprime factor perturbations of the plant and the upper bound of external disturbance are also unknown. The problem under consideration is to design adaptive controller that minimizes, with the prescribed accuracy, the worst‐case asymptotic upper bound of the output. Solution of the problem is based on set‐membership estimation of unknown parameters and treating the control criterion as the identification criterion. A hard nonconvex problem of on‐line computation of optimal estimates is reduced, under additional nonrestrictive assumption, to a linear‐fractional programming via a nonlinear transformation of estimated parameters. Despite the non‐identifiability of the unknown parameters, the proposed adaptive controller guarantees, with the prescribed accuracy, the same optimal asymptotic upper bound of the output of adaptive system as the optimal controller for the plant with known parameters. In addition to the optimality of adaptive control, the proposed solution provides on‐line verification/validation of current estimates and a priori assumptions.

Analysis and assessment of the reliability of rail elements

The article conducts a study and calculation of reliability indicators of rail elements of various types, taking into account structural diagrams that include series and parallel connection of elements. Taking into account the climatic characteristics of the Republic of Uzbekistan and taking into account the impact on various areas of the region, the article conducted a study of fastenings for various disturbing factors and ensuring trouble-free operation of system components. The goal of the work was to develop an algorithm for determining optimal parameters. As a result, an assessment of the distribution parameters was proposed taking into account the durability of the elements of the fastening unit. Analytical expressions were developed and a graph was presented.

A Psychological Study of the Impact of Social Media Addiction on Sleep Patterns

This study presents findings from a comprehensive psychological investigation aimed at exploring the impact of social media addiction on sleep patterns among young adults. The research utilized a mixed-methods approach, incorporating quantitative surveys, objective sleep assessments, and qualitative interviews to provide a holistic understanding of the complex relationship between social media use and sleep disturbances. Eightyparticipants aged 18-35 were recruited from diverse demographic backgrounds and assessed for social media addiction using validated scales such as the Bergen Social Media Addiction Scale (BSMAS). Sleep patterns were evaluated using self-report measures (e.g., Pittsburgh Sleep Quality Index) and objective measures such as actigraphy. Psychological factors including anxiety, depression, stress, and self-esteem were also assessed. Results revealed a significant association between social media addiction and disrupted sleep patterns, with higher levels of social media addiction correlating with poorer sleep quality and decreased sleep duration. Qualitative analysis of interviews provided insights into the psychological mechanisms underlying this relationship, highlighting factors such as fear of missing out (FOMO), heightened cognitive arousal, and maladaptive coping strategies. The findings underscore the importance of addressing social media addiction as a potential risk factor for sleep disturbances and suggest the need for targeted interventions to promote healthier digital habits and improve sleep hygiene among young adults.

Effect of Rock Mass Disturbance on Stability of 3D Hoek–Brown Slope and Charts

The present study performs a stability analysis of a three-dimensional (3D) rock slope in disturbed rock masses following the Generalized Hoek–Brown (GHB) failure criterion. The factor of safety (FoS) of the slope is derived and the optimal solution is captured combining the limit analysis method and the strength reduction technique. It is indicated by the parametric analysis that the 3D geometric characteristics have a significant impact on slope stability such that FoS decreases sharply with the increase in the width-to-height ratio B/H within 0&lt;B/H≤2.0 and thereafter reaches a constant value asymptotically. The FoS decreases more than 60% linearly when the disturbance factor D increases from 0 to 1.0. Stability charts and slope angle weight factor fβ_3D for 3D slopes are proposed to provide a convenient and straightforward approach to obtain the FoS solutions of 3D slopes. A case study was carried out to apply the stability charts on practical engineering cases, which showed that slope stability under two-dimensional (2D) plane strain will lead to conservative results, and a 3D stability analysis of slope is more appropriate, especially for a slope with a limited width.

Іван Літус — фахівець у галузі акліматизації мисливських тварин, організатор «царських полювань»

An essay about a specialist who developed the ideas of isolated, powerful hunting grounds with the introduction of alien species, excessively high abundance of wild game and measures to maintain it artificially. His focus was primarily on game animals and everything that contributed to the ‘enrichment’ of hunting grounds, excluding factors of disturbance to the local people and ordinary hunters, creating a system of fenced areas for the release of imported animals and preventing their escape. He is the author of four publications on mammals (and about 10 on hunting grounds and their fauna), including the monograph ‘Acclimatisation of Wild Animals’ (1986).

How Do Driving Factors Affect Vegetation Coverage Change in the Shaanxi Region of the Qinling Mountains?

Understanding the effects of natural and human disturbance factors on fractional vegetation coverage (FVC) is significant in the promotion of ecological and environmental protection. However, most of the relevant studies neglect to consider differences in the effect of driving factors on areas with different vegetation change characteristics. In this paper, we have combined Theil-Sen median trend analysis and Mann-Kendall testing to identify degraded and restored areas. Differences in the impact of various factors on FVC in terms of degradation, restoration, and the whole region were distinguished quantitatively using the geodetector model. Additionally, the constraint line approach was used to detect the influence thresholds of factors on FVC. The results are shown as below: (1) FVC showed an overall improving trend, and vegetation restoration and degradation areas accounted for 69.2% and 22.0%, respectively. (2) The two dominant factors affecting FVC were Digital Elevation Model (DEM) and temperature for both degraded and restored regions. However, the explanatory power of precipitation was noticeably different between regions. (3) Most natural factors had a “convex” constraint effect on FVC, which gradually weakened with an increase in the variable below the threshold and vice versa. Human disturbance factors negatively constrained FVC, and the constraint effect increased with increased human activity. This study can help decision-makers optimize specific implementation policies relating to ecological restoration and sustainable development.