Disturbance Factors Research Articles

Robust Resilient Base Containment Control of Fractional Order Multiagent Systems With Disturbance and Time Delays

ABSTRACTThis article examines the resilient base containment control (CC) for fractional order multiple agent system with disturbance term in the dynamical system. In order to deal with resilient base CC in Riemann–Liouville sense with time delays, a simple and effective method is proposed where followers have weighted digraph topology among them. A disturbance factor is present into both linear and nonlinear delayed RL‐fractional‐order multiple agent systems (FMASs) with distributed time delays. This disturbance term effect the agents by introducing the uncertainty into the behavior of agents. In this article, Lyapunov technique, fractional calculus properties, and analytical methods are used to approach resilient base CC. The major benefit of this approach is that the first‐order derivative of Lyapunov function may be used to keep away from complex calculations, which effectively reduce troubles and difficulties resulting from time delays and fractional derivatives. At the end of our study, three illustration are provided to show the effectiveness and validity of our approach.

Obesity as a Risk Factor for Hyperglycemia, Electrolyte Disturbances, and Acute Kidney Injury in the Emergency Department

Background/Objectives: Obesity is a global health challenge linked to a higher risk of metabolic and cardiovascular complications. This study investigates the role of cardiovascular markers in predicting metabolic crises in obese patients, focusing on the prevalence and clinical implications of these markers. Methods: This retrospective cohort study included 433 patients presenting with metabolic crises at the Emergency Department of Timișoara Municipal Emergency Hospital between 2019 and 2024. Patients were classified into obese (n = 161) and non-obese (n = 272) groups, with obesity further stratified into four grades based on body mass index (BMI). Cardiovascular markers, including NT-proBNP, troponin I, CRP, CK-MB, and D-dimer, alongside metabolic parameters, were analyzed. Results: Metabolic crises were significantly more prevalent in obese patients in all metabolic emergencies: hyperglycemia (27.9% vs. 11.0%, p < 0.001), electrolyte imbalance (23.6% vs. 9.2%, p < 0.001), and acute kidney injury (AKI) (12.4% vs. 5.5%, p = 0.01). NT-proBNP levels independently predicted AKI in obese patients (adjusted OR: 1.14 per 1000 pg/mL, 95% CI: 1.10–1.19, p < 0.001), with excellent discriminatory power (AUC: 0.88). Troponin I and D-dimer were higher in hyperglycemia and electrolyte imbalance, respectively, emphasizing the role of cardiac stress and pro-thrombotic states. Inflammatory markers such as CRP were significantly associated with metabolic disturbances, supporting the contribution of systemic inflammation. Comorbidities, particularly heart failure and atrial fibrillation, further increased the risk of metabolic crises. Conclusions: Cardiovascular markers suggest potential utility for early risk stratification of metabolic crises in obese patients. However, further studies are needed to validate their clinical applicability and to establish standardized approaches for integrating these biomarkers into routine practice, especially in patients with advanced obesity grades.

Recognizing pain phenotypes: biopsychosocial sources of variability in the transition to chronic postsurgical pain.

Chronic postsurgical pain (CPSP) is a cause of new chronic pain, with a wide range of reported incidence. Previous longitudinal studies suggest that development of CPSP may depend more on the constellation of risk factors around a patient (pre-existing pain phenotype) rather than on the extent of surgical injury itself. The biopsychosocial model of pain outlines a broad array of factors that modulate the severity, longevity, and impact of pain. Biological variables associated with CPSP include age, sex, baseline pain sensitivity, and opioid tolerance. Psychological factors, including anxiety, depression, somatization, sleep disturbance, catastrophizing, and resilience, and social factors, like education and social support, may also importantly modulate CPSP. Prevention efforts have targeted acute pain reduction using multimodal analgesia (regional anesthesia and intraoperative analgesic adjuvant medications). However, studies that do not measure or take phenotypic risk factors into account (either using them for enrichment or statistically as effect modifiers) likely suffer from underpowering, and thus, fail to discern subgroups of patients that preventive measures may be most helpful to. Early preoperative identification of a patient's pain phenotype allows estimation of their constellation of risk factors and may greatly enhance successful, personalized prevention of postoperative pain. Effective preoperative employment of behavioral interventions like cognitive-behavioral therapy, stress reduction, and physical and mental prehabilitation may particularly require knowledge of a patient's pain phenotype. Preoperative assessment of patients' pain phenotypes will not only inform high-quality personalized perioperative care clinically, but it will enable enriched testing of novel therapies in future scientific studies.

CLPr_in_ML: Cleft Lip and Palate Reconstructed Features with Machine Learning

Background: Cleft lip and palate are two of the most common craniofacial congenital malformations in humans. It influences tens of millions of patients worldwide. The hazards of this disease are multifaceted, extending beyond the obvious facial malformation to encompass physiological functions, oral health, psychological well-being, and social aspects. Objective: The primary objective of our study is to demonstrate the importance of imaging in detecting cleft lip and palate. By observing the morphological and structural abnormalities involving the lip and palate through imaging methods, this study aims to establish imaging as the primary diagnostic approach for this disease. Methods: In this work, we proposed a novel model to analyze unilateral complete cleft lip and palate after velopharyngeal closure and non-left lip and palate patients from the Department of Stomatology of Xuzhou First People's Hospital, Conical Beam CT (CBCT) images in silicon. In order to demonstrate the generalization, the simulated dataset was constructed using the random disturbance factor, which is from the actual dataset. We extracted several raw features from CBCT images in detail. Then, we proposed a novel feature reconstruction method, including six types of reconstructed factors, to reconstruct the existing features. Then, the reconstructed features weretrained with machine learning algorithms. Finally, the testing and independent data model was utilized to analyze the performance of this work. Results: By comparing different operator features, the min operator, max operator, average operator, and all operators can achieve good performances in both the testing set and the independent set. Conclusion: With the different operator features, the majority of classification models, including Gradient Boosting, Hist Gradient Boosting, Multilayer Perceptron, lightGBM, and broadened learning, classification algorithms can get the well-performances in the selected reconstructed feature operators.

Study on the effectiveness and influencing factors of vegetation protection in national nature reserves on the Qinghai‐Tibet Plateau

AbstractProtected areas are the cornerstone of national and global efforts to mitigate biodiversity loss. This study focused on the national nature reserves (NNRs) of the Qinghai‐Tibet Plateau (QTP), using a long‐term series of NDVI data from 2010 to 2020 to assess the effectiveness of vegetation protection across the entire region. By employing a multiple regression model, we accounted for 71% of the variation in the NDVI change rate, indicating a goodness of fit (R‐squared) that indicated an interplay between factors such as the natural environment, management capabilities, human‐mediated disturbance, and population density in shaping vegetation protection effectiveness within the NNRs of the QTP. The managerial capacity, natural environment, population, and human‐mediated disturbance factors contributed 46.0%, 37.5%, 11.4%, and 5.1%, respectively, of the total. The regression analysis findings highlight the crucial role that environmental elements play in the success of conservation by showing that latitude, longitude, elevation, and average annual precipitation all have a major impact on the effectiveness of NNRs. The effectiveness of conservation is significantly positively impacted by province and per capita patrol area, and negatively by per capita management area. Practical conservation and management solutions appropriate for the NNRs of the QTP are also offered to meet current challenges and management restrictions. These suggestions are meant to help the QTP function as an ecological security barrier more successfully.

Key environmental predictors as drivers of avifauna assemblages in Ghana’s coastal ecosystems

Avian assemblages are not only influenced by spatial factors but also by temporal variations in environmental conditions, creating dynamic patterns of bird presence in a given area. This study examined environmental elements affecting bird assemblages in Ghana's coastal ecosystems. We conducted point transect sampling along a 15-km coastal stretch, analyzing bird abundance, richness, and diversity in relation to microclimate and urbanization. Humidity and wind speed had a significant negative relationship with bird abundance as well as time of day (morning) having a negative relationship. Mean bird richness, diversity, were significantly higher in natural shoreline areas compared to urbanized ones. Bird abundance and seasonality were positive related where wet season was characterized by higher bird numbers which can be attributed to the favorability of the wet season in terms of food availability and habitat suitability. Indicator Species Analysis identified nineteen species significantly associated specific habitat characterization, with eleven species linked to lagoon adjacent shorelines. These results show the relationship between environmental factors and avian assemblages in coastal ecosystems, highlighting impacts of human disturbance and climate-related factors and the importance of pristine ecosystems in biodiversity conservation.

Integrated Evaluation of the Ecological Security Pattern in Central Beijing Using InVEST, MSPA, and Multifactor Indices

Scientific identification of ecological sources and corridors is crucial in constructing an ecological security pattern (ESP). To develop an ESP tailored to the scale of central urban areas in megacities, this study takes Central Beijing as the research object. It innovatively integrates the integrated valuation of ecosystem services and tradeoffs (InVEST), the morphological spatial pattern analysis (MSPA), and the Conefor software to identify ecological sources. Seven indicators related to topographic, natural conditions, and human disturbance factors are selected to build the ecological resistance surface, which is then combined with circuit theory to construct the ESP. The results show the following: (1) Central Beijing contains 157 ecological sources, primarily distributed in the western, northern, and eastern regions, with woodland as the dominant land type. (2) A total of 439 ecological corridors were extracted, including 317 key ecological corridors and 122 inactive ecological corridors. (3) The identified ecological pinch points are mainly the Jingmi Diversion Canal and the West Moat. (4) The identified ecological barriers are spread throughout the entire study area. The results of this study are highly significant for improving the quality of ecological security and protecting biodiversity in the study area and other urban centers.

Robust topological rainbow trapping in shamrock-leaf phononic crystal plates

Abstract The topological properties of elastic waves underpin the visions of widespread novel phonon devices such as topological rainbow trapping. In this work, a shamrock-leaf perforated phononic crystal with a graded interface is designed to achieve both the topological edge states (TES) and rainbow effect together. The topological rainbow mechanism activated by varying TES along the gradient interface is uncovered, and spatial trapped waves of different frequencies are presented. Meanwhile, based on the topological rainbow effect, the wave packet behaviors encountering various types of defects at interfaces are observed. Furthermore, deviations from the original trapping position under different disturbance factors are investigated. This work provides a useful handle for piloting applications of topological phononic transports.

Reeve's Muntjac (Muntiacus reevesi) Habitat Suitability Under Climate Change Scenarios in Hupingshan National Nature Reserve, China.

Climate change and human disturbance are critical factors affecting the habitat distribution of wild animals, with implications for management strategies such as protecting migration corridors, habitat restoration, and species conservation. In the Hupingshan National Nature Reserve (NNR), Reeve's muntjac (Muntiacus reevesi) is a key prey species for the South China tiger (Panthera tigris amoyensis), which is extinct in the wild and targeted for reintroduction by the Chinese government. Thus, understanding the habitat distribution and abundance of Reeve's muntjac is essential to ensure the survival and sustainability of reintroduced tiger populations. Despite significant conservation efforts, the impacts of climate change and human disturbance on Reeve's muntjac habitat distribution in Hupingshan NNR remain unclear, though these factors could necessitate adaptive tiger management strategies due to shifts in prey abundance. In this study, we employed an optimized MaxEnt model to assess current habitat distribution and identify key environmental variables influencing the habitat distribution of Reeve's muntjac. Assuming non-climatic environmental factors will remain constant over the next century, we projected future habitat distribution under two shared socioeconomic pathways (SSP126 and SSP585) for the mid-century (2050s) and the late-century (2090s). Comparative analyses of current and projected habitat areas revealed potential impacts of climate change on this species. MaxEnt outputs classified habitat suitability into high, medium, and low levels. Results showed that climatic and human disturbance factors contributed 35.2% and 49.4% to habitat suitability, respectively. Under the SSP126 scenario, habitats with decreased suitability covered 0 km2 in the 2050s, expanding slightly to 4.2 km2 in the 2090s, while those with increased suitability spanned 491.1 km2 (2050s) and 463.2 km2 (2090s). Under the SSP585 scenario, habitats with decreased suitability covered 10.2 km2 in the 2050s and 431.8 km2 in the 2090s. Habitats with increased suitability were comparatively smaller under SSP585, covering 162.0 km2 (2050s) and 1.1 km2 (2090s). These findings suggest that while mid-century climate projections (SSP126 and SSP585) may support Reeve's muntjac's survival, habitat loss is projected by 2090s (SSP126). Thus, future climate change may lead to decreased habitat suitability and increased fragmentation, raising extinction risks for Reeves's muntjac. Mitigating these effects could involve establishing migration corridors, minimizing human disturbances, and potentially supplementing prey populations with captive-bred prey. Such measures are essential to support the South China tiger reintroduction plan and help ensure that prey availability remains sufficient for sustaining reintroduced tiger populations.

Alternative Formulations of Job Strain and Sleep Disturbances: A Longitudinal Study in the United States.

Sleep disturbances are a major public health concern in the United States, leading to adverse health outcomes. In the working population, job strain has been identified as an important risk factor for sleep disturbances, but evidence from the United States remained limited. This study aimed to examine longitudinal associations between job strain and sleep disturbances in the United States, with a focus on the alternative formulations of job strain. A total of 1721 participants were drawn from two waves of the Midlife in the United States (MIDUS) study, with an average 9-year follow-up period. Job strain was measured using Karasek's Job-Demand-Control model and operationalized in six formulations: standard quadrant, simplified quadrant, linear, quotient, logarithm quotient, and quartile based on quotient. Generalized Estimating Equations were used to estimate longitudinal associations of alternative formulations of job strain at baseline with sleep disturbances across follow-up. Corrected Quasi-likelihood Information Criterion (QICu) was used to assess the goodness of fit. All approaches showed that higher job strain at baseline was significantly associated with an increase in sleep disturbances across follow-up. QICu scores indicated that continuous Demand-Control formulations (linear, quotient, logarithm quotient) had better model performance of 4602.66, 4604.28, and 4601.99, respectively. The logarithm quotient showed the best fit. Our findings imply the importance of early workplace interventions in reducing job strain to improve sleep hygiene. They further show that the continuous formulations quantifying job strain were more consistent and robust, which provides suggestions for future workplace health research in the United States.

Relationship between deadwood structural diversity and carbon stock along environmental and disturbance gradients in Tropical dry forests

Abstract Deadwood is a substantial component of forest ecosystems playing a vital role in maintaining ecosystem health and functioning. However, there is limited information on deadwood stand structure which encompasses attributes such as type, quantities and distribution of deadwood pieces and how it is related to its biomass. This study examined the relationship between deadwood species structural diversity and carbon stock along different environmental and disturbance factors in forest and woodland ecosystems. An agglomerative hierarchical clustering analysis was used to identify species communities, followed by indicator species analysis which was done to determine the species significantly associated with each community. Species richness, evenness and Shannon-Wiener diversity index were calculated to determine deadwood species diversity in both ecosystems. Multimodel inference approach was used to analyse the relationship between deadwood carbon stock and diversity indices, soil properties, climate and proximity to roads and settlements. Three communities were identified from forest ecosystems while four communities were from woodland. Multimodel analysis found a positive significant relationship between deadwood carbon stock and species abundance, Shannon-Wiener diversity, soil moisture and proximity to roads in both ecosystems. These findings provide insights into conservation strategies that prioritize protection and restoration of ecosystems as carbon reservois.

Risk factors for moderate disturbance of consciousness in patients with unilateral chronic subdural hematoma

Risk factors for moderate disturbance of consciousness in patients with unilateral chronic subdural hematoma

Особливості поширення й екології ведмедя бурого (Ursus arctos) у Карпатському національному природному парку

The distribution and some ecological features of the brown bear (Ursus arctos) in the Carpathian National Nature Park (CNNP) during 2019–2023 are considered. The study is based on field observations and analysis of camera traps. The data was collected by the inspectors of the park's departments and employees of the scientific department. In particular, 157 cases of bear activity and presence were recorded, of which three cases were captured by camera traps. The results show that the brown bear prefers middle-aged spruce and fir plantations (38.7%). Bear tracks are also frequently found in middle-aged stands with dense crown closure (26.5 %), which may indicate the importance of dense forests for bears. Brown bears prefer old-growth spruce and fir stands, which account for 38.7 % of the total number of cases. This may be due to the fact that such forests provide sufficient food and shelter for bears. A smaller number of cases are occurrences in young and maturing stands. This may be due to the fact that such stands have not yet reached the optimal structure to meet the needs of bears. The lowest number of cases was found in pastures and hayfields. The maximum altitude at which a bear was recorded was 1696 m, and the minimum was 745 m. The highest number of observation was recorded at altitudes of 900–1000 m (31.2%), and the lowest at altitudes of 700-800 m (3.18%). According to the authors, this is due to the fact that there are no settlements at higher altitudes and the disturbance factor of animals is lower. The distribution and places of occurrence of this species in the Park over the past five years are analysed. The number of bears has increased in recent years. This is obviously due to a decrease in human impact (coronavirus restrictions, martial law and the absence of poaching). Currently, there are up to 20 individuals in the Park. The exact number of bears is difficult to determine due to double counting and lack of coordination between neighbouring forestry enterprises and protected areas. The data presented here are important for the development of conservation strategies for the brown bear, as they allow to identify the most favourable environments and plan measures for the protection and management of the Park's territory.

Risk Factors and Prevalence of Sleep Disturbance in Degenerative Cervical Myelopathy.

Sleep disturbances, especially those lasting more than one hour, are under-researched in patients with degenerative cervical myelopathy (DCM). This study aims to investigate the prevalence and risk factors for such disturbances in DCM patients undergoing decompression surgery and to identify factors contributing to poor postoperative improvement. A multicenter retrospective observational study was conducted on consecutive patients diagnosed with DCM who underwent cervical decompression surgery between April 2018 and August 2022. The neck disability index (NDI) sleep component was assessed at baseline and 12 months post-surgery. Univariate and multivariable logistic regression analyses were used to identify risk factors for persistent sleep disturbances and poor improvement. Of the 1912 patients included, 54.8% reported sleep disturbances, with 33.0% experiencing disturbances of more than one hour at baseline. Multivariable analysis identified male sex, high BMI, high numerical rating scale (NRS) for arm pain, high NDI, and high Core Outcome Measures Index (COMI) Neck as significant risk factors for sleep disturbances. At 12 months, 35.2% of these patients continued to experience significant sleep issues. The presence of ossification of the posterior longitudinal ligament (OPLL) and high baseline NRS for neck pain were significant predictors of poor improvement. The study highlights that OPLL and high baseline neck pain are significant risk factors for persistent sleep disturbances post-surgery in DCM patients. Early identification and targeted interventions may be necessary to improve outcomes.

A System Dynamics Stability Model for Discrete Production Ramp-Up

Manufacturing companies are increasingly challenged to deliver customizable products with shorter time to market and higher quality while adhering to sustainability requirements. To meet these challenges, the frequency and importance of production ramp-ups will increase in the future. However, most ramp-ups still fail to meet targets due to unpredictable equipment failures, operator errors, and system complexity. We propose a system dynamics model that captures the unique dynamics of ramp-up phases by integrating stability and disturbance factors that influence the key performance indicators overall equipment effectiveness, process capability, and production output. A systematic literature review informed the identification of stability factors, which were validated through expert interviews in the automotive industry. Our system dynamic simulation results indicate that control factors realistically influence production system behaviour during different ramp-up phases. Despite some limitations regarding the effects of maintenance personnel and engineering changes on key performance indicators, our model effectively simulates realistic ramp-up behaviour. The findings highlight the need for tailored models that consider specific ramp-up contexts and emphasize the importance of data acquisition for enhanced performance prognosis in future research.

Evaluating Body Image Disturbance and Its Influencing Factors in Breast Cancer Patients Following Unilateral Mastectomy.

Patients with unilateral breast loss after single mastectomy for breast cancer may have body image disorders such as surgical lymphedema, flap ischemia, and spinal deformity, resulting in negative emotions such as depression, inferiority, and social dysfunction. This study mainly investigated and analyzed the status quo and influencing factors of body image disorder in breast cancer patients after single mastectomy. This study is a cross-sectional study. Breast cancer patients admitted from May 2023 to April 2024 were selected as the research subjects. Data were collected with a general information questionnaire, the Body Image Scale (BIS), the Self-Image Scale, the Self-Acceptance Questionnaire, and the Perceived Social Support Scale. Based on the scores, the research subjects were divided into a body image disturbance group and a non-disturbance group. Univariate and multiple logistic regression analyses were conducted to analyze the influencing factors of body image disturbances in breast cancer patients. One hundred fifty questionnaires were distributed in this study, and 146 valid questionnaires were collected. Among the 146 patients, 51 (34.93%) experienced body image disturbances after surgery, while 95 (65.07%) did not. The results of univariate and multiple logistic regression analyses showed that educational level, lymphedema in the affected limb, intimate relationships, self-image, self-acceptance, and perceived social support scores were independent risk factors for body image disturbances in breast cancer patients after surgery (P < .05). Body image disturbances in breast cancer patients who undergo unilateral mastectomy need further improvement. Educational level, lymphedema in the affected limb, intimate relationships, self-image, self-acceptance, and perceived social support are the main influencing factors.

Using Minimum Travel Time to Determine Factors Influencing Travel Time Discrepancy and Variability in Tram Transit

Quality of service in urban surface transit has a great impact on sustainable urban mobility, with travel time being one of the most important indicators of service reliability. But urban surface transit is prone to many disturbance factors causing travel time discrepancy and variability, making transit less reliable for passengers. We conducted research in the City of Zagreb on a single tram line by splitting it into constant-frequency segments. The first phase was modeling minimum segment travel times to base the indicators and predictors upon, and the second phase was establishing correlation matrices between the predictors and travel time using Pearson correlation coefficients and significance. Variance inflation factors were used to check for collinearities. While predictors belonging to the transport supply irregularity group did not have an impact, the ones belonging to the disturbance factors group showed correlation, with six of them being significant. This research in rarely represented tram transit determined the most significant disturbance factors rich in traffic context that can be used to develop travel time prediction models.

Cost-effectiveness of remote sensing technology for spruce budworm monitoring in Maine, USA

Forest pests are a major disturbance factor in forest ecosystems, which can result in tree mortality and loss of ecosystem services, leading to further negative impacts on the forest economy. Spruce budworm (Choristoneura fumiferana (Clem.); SBW) is a native forest pest in the northeastern USA and Canada, including the state of Maine, which defoliates balsam fir (Abies balsamea (L.) Mill.) and spruce (Picea spp.) trees with cyclical outbreaks every 30-60 years. SBW is typically monitored via ground sampling techniques such as pheromone traps and overwintering second instar larvae (L2) branch sampling. Remote sensing data can also provide information about defoliation patterns across the landscape and forest susceptibility to outbreaks. This study presents a cost-effectiveness analysis comparing remote sensing data, ground sampling techniques, and an integrated monitoring approach, combining remote sensing change detection with field sampling. Over a 10-year project period, Sentinel-2 imagery emerged as the most cost-effective option, ranging from US$33 to US$63/square kilometer (sq km), offering wide spatial coverage and moderate resolution suitable for the identification of defoliation patterns. PlanetScope imagery ranged from US$77 to US$241/sq km, and unmanned aerial vehicle (UAV) imagery had the greatest variation, from US$9,220 to US$58,481/sq km. Labor costs are the most influential in our study, ranging from 30% of total costs for remote sensing approaches to 80% for field sampling. The integrated monitoring approach proposed in this study presents a synergistic strategy for effective and timely SBW monitoring, ranging from US$144 to US$213/sq km. Utilizing this integrated approach leverages both remote sensing and L2 branch surveys to enhance the accuracy and timeliness of monitoring efforts, leading to more effective management strategies for mitigating pest outbreaks for landowners. Our research highlights the importance of adaptive monitoring strategies and integrating remote sensing for forest pest detection.

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Background. Regional anesthesia has become widely used in routine anesthesiology practice, it is considered a safer method of anesthesia in older patients and those with concomitant pathology. Nevertheless, both general and regional anesthesia have side effects on the cardiovascular system. The cardiotoxic effect of anesthesia in one way or another is present with any variant of anesthesia. One of the most transparent signs is rhythm alterations on the ECG. These changes can occur not only intraoperatively, but also in the early postoperative period, have an asymptomatic clinical course. But the presence of these signs can have a negative impact on the patient’s prognosis. That is why we performed daily Holter monitoring for patients undergoing trauma surgery. The purpose of the study was to compare regional and general anesthesia as a risk factor for perioperative rhythm disturbances. Materials and methods. It was a 2-group observational study that included 120 trauma patients undergoing surgery using general (group GA) or regional anesthesia (group RA). Postoperative Holter monitoring lasted 24 hours. Further analysis of the recording included the assessment of the presence of ischemic changes or extrasystoles. Results. The incidence of ST-depression episodes within 24 perioperative hours was 10 % in the GA group compared to 3 % in the RA group. In the GA group, the percentage of extrasystole was significantly higher compared to the RA group: 1.5 ± 2.1 % versus 0.7 ± 1.3 % (p = 0.0145). An increase in Qtd was significantly higher in the GA group 15 minutes after the start of anesthesia (51.31 ± 23.09) compared to the RA group (40.70 ± 19.97; p = 0.008). At the same time, QT dispersion was statistically significantly higher in the RA group 1 hour after the start of anesthesia compared to the GA group — 38.22 ± 12.30 versus 50.1 ± 19.5 (p = 0.04). The QT interval was significantly longer in the GA group 15 minutes after the start of anesthesia: 440.00 ± 33.09 versus 400.70 ± 23.18 in the RA group (p = 0.04). One hour after the start of anesthesia, QTt was longer in the RA group: 390.22 ± 23.60 versus 410.1 ± 30.1 in the GA group (p = 0.05). Conclusions. Regional anesthesia has less hemodynamic effects and is the method of choice in patients with cardiovascular comorbidity. However, given the risk of cardiotoxicity due to the resorptive effect of the local anesthetic, in older patients and with existing risk factors, it is crucial to account for the arrhythmogenic effects of local anesthetics and adjust the dosage accordingly.

Research progress and prospect of key technologies of fruit target recognition for robotic fruit picking.

It is crucial for robotic picking fruit to recognize fruit accurately in orchards, this paper reviews the applications and research results of target recognition in orchard fruit picking by using machine vision and emphasizes two methods of fruit recognition: the traditional digital image processing method and the target recognition method based on deep learning. Here, we outline the research achievements and progress of traditional digital image processing methods by the researchers aiming at different disturbance factors in orchards and summarize the shortcomings of traditional digital image processing methods. Then, we focus on the relevant contents of fruit target recognition methods based on deep learning, including the target recognition process, the preparation and classification of the dataset, and the research results of target recognition algorithms in classification, detection, segmentation, and compression acceleration of target recognition network models. Additionally, we summarize the shortcomings of current orchard fruit target recognition tasks from the perspectives of datasets, model applicability, universality of application scenarios, difficulty of recognition tasks, and stability of various algorithms, and look forward to the future development of orchard fruit target recognition.