Previous studies have explored the relationships between dengue fever (DF) and its impact factors, using various models. However, few have considered the spatial heterogeneity of these relationships in simulating DF variations. This study analyzed monthly DF incidence and rate data across 34 provincial-level administrative divisions (PLADs) in China from 2004 to 2019, along with climatic and socioeconomic variables. Nine impact factors were included: six climatic variables - minimum temperature (Tmin), mean temperature (Tmean), maximum temperature (Tmax), relative humidity (RH), precipitation (PRCP), and the El Niño-Southern Oscillation (ENSO) - and three socioeconomic variables - population density (PD), per capita regional gross domestic product (pcGDP) and number of foreign visitor arrivals (NFVAs). We introduced a modeling system that incorporates the spatial heterogeneity of these factors and integrates four artificial intelligence (AI) algorithms: support vector machine (SVM), artificial neural network (ANN), random forest (RF), and gradient boosting machine (GBM). This system was implemented under a novel framework - grid-by-grid, multi-algorithms, optimal combination (GGMAOC) - to explore the spatial heterogeneity of both algorithms and impact factors. From 2004 to 2019, DF in China showed a significant upward trend, an average annual increase of 1,618 cases. Among the impact factors, socioeconomic variables exhibited stronger associations, with correlation coefficients exceeding 0.77. In Yunnan, the ANN model performed best (DISO=0.18), with PDLag3 contributing over 31%. In Guangdong, the RF model was optimal (DISO=0.26), with TmaxLag2 contributing over 67%. Performance varied across PLADs, which highlights the spatial heterogeneity of both impact factors and algorithmic responses. Importantly, the proposed GGMAOC framework substantially outperformed the traditional stepwise regression approach. Our findings reveal that impact factor patterns vary across PLADs, emphasizing spatial heterogeneity and the need for PLAD-specific modeling. The GGMAOC framework identifies key impact factors and optimal models for DF dynamics, offering high predictive confidence and broad applicability to other diseases with spatially heterogeneous impact factors. Furthermore, the successful model construction in GD and YN and the identification of challenges in TW modeling further support the necessity and innovation of adopting a spatially heterogeneous modeling framework in infectious disease modeling as proposed in this study.
The classification of functional brain networks plays an important role in the diagnosis of neurodegenerative diseases, brain decoding and other fields. Functional brain networks can effectively reflect the functional connection relationships between brain regions or neurons and accurately represent brain activities. Therefore, a large number of problems related to the classification of functional brain networks have been studied. However, the traditional functional brain network merely measures the static correlation between brain regions or neurons in a simple way, and does not reflect the causal transmission effect between brain regions. This directionality is crucial for the regulatory relationship between brain regions. Furthermore, since the brain is constantly in a state of dynamic change, the dynamics of functional connectivity also plays a very important role in the classification of functional brain networks. Therefore, we propose a classification framework named Dynamic Directed Propagation Networks (DDPN) for functional brain networks considering the dynamic directed propagation mechanism. This method effectively captures the dynamics and directionality of the dynamic directed brain network and further improves the classification accuracy of the functional brain network. To verify the effectiveness of the proposed method, we conduct experiments on real datasets. The experiments show that the proposed method improved by 3.1-4.1% compared with state-of-the art methods in two datasets.
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Digital mental health tools-including telehealth, mobile applications, wearable devices, machine learning, and artificial intelligence-are changing the way patients and providers manage mental health care. This review summarizes the current research findings of digital interventions on patient access to care, the factors impacting personalized care, and overall patient engagement. Gaps of knowledge and future considerations are discussed, including careful observation of existing barriers to care. Clinical recommendations are discussed for clinicians who are considering implementing digital mental health tools into practice.
This study aimed to characterize practices and decision-making for extracorporeal membrane oxygenation (ECMO) for congenital anomalies of the kidney and urinary tract (CAKUT). General practices (GP) section inquired about institutional practices and barriers, ECMO criteria, and dialysis. The hypothetical cases (HC) illustrated four clinical scenarios with varying degrees of renal severity for ECMO candidacy. Then, 99 (42 centers) and 91 (38 centers) physicians completed the GP and HC components, respectively. The majority considered ECMO on a case-by-case basis (66%). Bilateral renal agenesis was the most common diagnosis for exclusion (52%). Prenatal markers used for ECMO exclusion included anhydramnios (43%) and lung volumes (43%). The majority of centers had nephrology involved in ECMO decision-making. Challenges for implementing ECMO included disease heterogeneity (79%) and poor evidence on outcomes (66%). HC responses demonstrated variability in considering ECMO for CAKUT. Variability among providers and institutes underscores the need for consensus-based guidelines to optimize decision-making and outcomes.
Gob-side entry driving is widely applied in deep coal mines, where rapid unloading of surrounding rock on the gob side induces stress redistribution, and the coal pillar is consequently regarded as a key load-bearing structure. The stability of the roadway is governed by the competition between elastic elastic strain energy and dissipated energy within the coal pillar. To address the difficulty of identifying stability state transition points in coal pillar width design under deep burial and weak rock conditions, this study analyzes the surrounding rock response from an energy perspective and establishes an energy analysis framework based on the coupling of elastic elastic strain energy and dissipated energy, with the dissipated energy ratio introduced as an evaluation index. Based on FLAC3D numerical simulations, the spatial distribution and evolution of elastic strain energy, dissipated energy, and dissipated energy ratio under different coal pillar widths are investigated. The results indicate that when the coal pillar width increases from 4 to 6 m, the bearing mechanism gradually shifts from plastic dissipation-dominated behavior to an elastoplastic coordinated state dominated by elastic elastic strain energy, with the dissipated energy ratio decreasing from 1 to approximately 0.67. When the width further increases to 8 ~ 14 m, elastic strain energy rapidly accumulates in the central region of the coal pillar, resulting in the formation of a pronounced energy concentration zone. Compared with traditional indicators based on stress, displacement, and plastic zone distribution, the dissipated energy ratio is more effective in characterizing. Considering energy evolution characteristics, bearing capacity, and engineering economy, a 6 m coal pillar is considered to achieve the most favorable balance under the conditions of the studied mine. Field monitoring results further verify the engineering applicability of the proposed energy-based criterion and coal pillar width optimization scheme.
To compare the effectiveness of injected low- and high-molecular-weight hyaluronic acid (HA-LMW, HA-HMW) vs corticosteroids (CCS), placebo- or physical therapy (PT), on pain at rest (Prest), at night (Pnight), and during activity (Pact), range of motion (ROM), functional status (FS), and quality of life (QoL) in patients with chronic Sp, at 3 (3mo) and 6 months (6mo) follow-up. A systematic literature search was conducted through October 2024 across MEDLINE, Embase, and Cochrane CENTRAL. Fourteen studies were included: 12 randomized controlled trials and 2 prospective cohort studies that compared at least two of the treatments of interest in adults with chronic shoulder pain (Sp). Two reviewers independently extracted data related to the outcomes. A frequentist network meta-analysis with mean differences (MD) and standardized mean differences (SMD) was performed; p<0.05 was statistically significant. PT reduced Prest compared to HA-HMW (MD = -3.02, p<0.01 at 3mo; MD = -2.08, p<0.01 at 6mo) and HA-LMW (MD = -1.95, p<0.01 at 6mo) in tendinopathy. PT showed greater reduction than both HA formulations in Pnight and Pact at 6mo in tendinopathy. No differences were observed between HA-HMW and HA-LMW for pain outcomes considering shoulder different diseases. HA improved adduction and internal rotation at 3mo considering shoulder different disease; PT was superior for flexion and external rotation at 6mo in tendinopathy. Stratified by pathology, HA-HMW showed moderate efficacy in adhesive capsulitis. HA-HMW improved FS compared to HA-LMW at 3mo. CCS improved abduction in shoulder disease due to different causes. PT provides greater pain control for Sptendinopathy, particularly for Prest, Pnight, and Pact at both 3mo and 6mo. HA may contribute to improved QoL and specific ROM parameters. Further high-quality studies are required to consolidate these findings.
The distal-to-proximal pressure ratio (dpPR) has emerged as a superior indicator compared to the diameter stenosis rate (DSR) for assessing the functional severity of carotid artery stenosis (CAS). However, unlike DSR, dpPR cannot be directly determined by vascular imaging. In this study, we developed a hemodynamic modeling method to predict dpPR based on medical images available in clinical settings. A multiscale modeling method was employed to integrate a three-dimensional (3D) hemodynamic model of CAS into a lumped-parameter model of systemic hemodynamics, while incorporating patient-specific geometric information of large cerebral arteries derived from computed tomography angiography (CTA) images. The 3D modeling method was validated through in vitro fluid dynamics experiments, while the accuracy of the resulting multiscale model in predicting dpPR was evaluated by comparing model predictions with invasive pressure wire measurements. The model-predicted dpPR values for 27 carotid artery stenoses demonstrated strong agreement with invasive measurements, with a mean relative error of - 0.8% and a standard deviation of 2.5%. dpPR was only moderately correlated with DSR (r = - 0.55, p = 0.003). Further analysis revealed that the anatomical structure of the circle of Willis (CoW) is a major factor influencing the relationship between dpPR and DSR. Constructing a multiscale model based on CTA images provides a practical approach for assessing the hemodynamic impact of CAS. The significant influence of CoW's anatomical structure on the relationship between dpPR and DSR underscores the importance of considering systemic cerebral hemodynamics when evaluating the functional severity of CAS.
Cancer-associated cachexia (CAC) is a multifactorial wasting syndrome characterized by progressive loss of fat and lean mass, systemic inflammation, and poor therapeutic responsiveness. While brown adipose tissue (BAT) is traditionally considered a protective, energy-dissipating organ, its qualitative remodeling in CAC remains poorly characterized.Here, we demonstrate that CAC induces a senescent conversion of BAT, marked by thermogenic failure, fibrosis, inflammation, and acquisition of a senescence-associated secretory phenotype (SASP). Through integrative transcriptomic, proteomic, and secretomic analyses in a murine model of lung cancer-induced cachexia, we identify S100A9 as a key factor selectively upregulated and secreted by brown adipocytes. Functional assays reveal that the BAT secretome exerts deleterious paracrine effects on white adipocytes and skeletal myotubes, promoting lipolysis and atrophy, while also impairing brown adipocyte identity in an autocrine manner. Co-culture and gain-of-function experiments with S100A9 recapitulate these phenotypes in vitro in mouse and human brown adipocytes, whereas pharmacological blockade of S100A9 signaling partially restores thermogenic and metabolic features. Collectively, our findings reveal that BAT undergoes functional reprogramming into a senescent and secretory tissue in cancer cachexia, with adipocyte-derived S100A9 acting as a novel pro-cachectic mediator. This work redefines the role of BAT in CAC and identifies S100A9 as a potential therapeutic target within the adipose-muscle crosstalk.
To determine whether substantial differences in coronal plane alignment of the knee phenotype distribution, as well as systematic angular measurement discrepancies, exist between CT and long-leg radiography. From February 2021 to April 2025, we searched PubMed, Embase, and the Cochrane Central Register of Controlled Trials for studies comparing CT- and long-leg radiography-derived coronal plane alignment classifications of the knee in patients with osteoarthritis. The primary outcome was distribution of coronal plane alignment phenotypes. Secondary outcomes included differences in medial proximal tibial angle, lateral distal femoral angle, arithmetic hip-knee-ankle angle, and joint line obliquity. Four studies (1,134 knees) were included. Compared with long-leg radiography-derived classification, CT-derived classification increased type I phenotypes (risk difference: 0.10; 95% confidence interval: 0.01-0.20; P = 0.040) and decreased type III (risk difference: -0.04; 95% confidence interval: -0.07 to -0.01; P = 0.020) and type V phenotypes (risk difference: -0.04; 95% confidence interval: -0.07 to -0.01; P = 0.004). CT yielded significantly lower medial proximal tibial angle (weighted mean difference: - 1.18°; P < 0.001), arithmetic hip-knee-ankle angle (weighted mean difference: - 0.95°; P < 0.001), and joint line obliquity (weighted mean difference: - 1.40°; P < 0.001) than long-leg radiography. Heterogeneity was high for type I phenotype (I2 = 81%), lateral distal femoral angle (I2 = 70%), and joint line obliquity (I2 = 69%). Discrepancies between CT-based software-generated and long-leg radiography-derived measurements substantially affect coronal plane alignment classification and angular parameters. Surgeons should consider these modality-specific variations and employ compensatory verification strategies to ensure optimal alignment.
Itch is a complex noxious sensation associated with many skin and systemic conditions, which varies in intensity and quality across different body regions. Despite its prevalence, the molecular and cellular mechanisms underlying regional itch differences remain poorly understood. Investigating the neural basis of regional itch differences, we identified a functional divergence in neuropeptide signaling and central circuit engagement between the trigeminal and spinal systems, which was independent of peripheral innervation density. Utilizing a combination of behavioral, pharmacological, genetic, and molecular assays, we identified a unique population of trigeminal (TG) neurons that facilitate specialized itch-pain coding. Our results indicate that while histamine receptors HRH1 and HRH3 are both involved in mediating mixed itch-and-pain sensations, the specific activity of Substance P (SP)- and Somatostatin (SST)-expressing neurons orchestrates this transition in the cheek. This behavioral shift is mediated by a central mechanism wherein sensory neurons activation recruits distinct nociceptive circuits within the brainstem. In brief, these findings provide insights into the molecular and cellular mechanisms underlying regional itch differences, highlighting the importance of considering anatomical location when developing targeted treatments.
Self-rated health (SRH) is a widely used indicator of overall health and a robust predictor of morbidity and mortality. Although metabolic health and obesity are well-established determinants of SRH, most previous studies have examined these factors at the individual level. This study investigated how spousal metabolic phenotypes, defined by metabolic and weight status, are jointly associated with SRH among Korean adults. We analyzed nationally representative data from 1817 heterosexual couples. Participants were classified into four phenotypes: metabolically healthy normal weight (MHNW), metabolically healthy obesity (MHO), metabolically unhealthy normal weight (MUNW), and metabolically unhealthy obesity (MUO). We applied actor-partner interdependence models (APIM) and couple-level analyses to assess associations with worse SRH, adjusting for sociodemographic factors, health behaviors, perceived stress, and comorbidities. Among husbands, the MUNW phenotype was significantly associated with worse SRH, with marginal partner effects were observed when wives were MUNW. Among wives, both MUNW and MUO were significant predictors of worse SRH, whereas partner effects were not significant. At the couple level, husbands had higher odds of worse SRH across all non-MHNW couple combinations, whereas wives had higher odds only in discordant couples in which the wife was non-MHNW and the husband was MHNW. Sensitivity analyses among older couples confirmed these findings. These findings highlight gender-specific actor and partner effects and suggest that couple-level metabolic profiles may shape SRH, underscoring the importance of considering spousal metabolic status in its assessment.
Corporate bankruptcy prediction is essential for assessing companies' capacity to maintain sustainable customer relationships and service quality. This study proposes a novel CNN-based hybrid approach that transforms correlation-filtered financial features into 64 × 64 grayscale images, enabling reliable identification of firms at financial risk whose deteriorating conditions could compromise their ability to maintain quality customer service and sustain long-term business relationships. The research explicitly examines the linkage between financial health indicators and customer relationship sustainability by categorizing financial features based on their operational impact on service delivery, relationship management capabilities, and long-term customer commitment fulfillment. The methodology was evaluated on a comprehensive dataset of 43,405 Polish companies (2,091 bankrupt, 41,314 healthy) using two resampling strategies: random downsampling and Synthetic Minority Oversampling Technique (SMOTE). Following correlation-based feature selection that reduced multicollinearity by eliminating features with absolute correlation coefficients exceeding 0.8, retained financial features were normalized and transformed into spatial image representations. Six classification models were implemented: Deep Neural Network (DNN), Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Gradient Boosting (GB), and Logistic Regression (LR), alongside five CNN-hybrid variants, evaluated using 5-fold cross-validation. SMOTE-balanced datasets demonstrated superior performance across all models. Ensemble methods achieved exceptional accuracy, with Random Forest reaching 99.99% and Gradient Boosting 99.97%. The innovative CNN-SVM hybrid model attained 99.77% accuracy with perfect ROC-AUC (1.000), providing reliable indicators for assessing firms' financial stability and their ability to invest in customer experience initiatives. Statistical analysis identified company size and working capital as the most discriminative financial indicators directly impacting customer service delivery capabilities. Customer-related metrics such as receivables turnover and collection period indicators emerged as critical predictors of relationship management effectiveness. The study contributes a novel spatial feature representation methodology enabling precise identification of companies whose financial deterioration could compromise customer service quality and relationship sustainability. These findings provide significant implications for stakeholders seeking enhanced risk assessment capabilities that consider both internal financial health and external customer relationship dynamics in bankruptcy prediction.
Although endovascular techniques dominate the treatment of abdominal aortic aneurysms (AAAs), open aortic repair (OAR) remains essential for selected patients. As previous research has focused primarily on procedure specific hospital volume for infrarenal AAA repair, this study evaluated whether hospital volume of cumulated non-cardiac open aortic procedures is associated with in hospital mortality and peri-operative outcomes after infrarenal OAR for intact AAA (iAAA). This study was a retrospective nationwide secondary data analysis based on German hospital episode statistics (diagnosis related group [DRG] data) covering the years 2010 to 2023. All hospitals performing non-cardiac open aortic procedures were included and were stratified into quartiles according to their annual volume of all non-cardiac open aortic procedures. A predefined subcohort of cases undergoing open infrarenal repair for iAAA was analysed. The primary outcome was in hospital mortality; secondary outcomes included acute myocardial infarction, acute kidney injury, acute peripheral ischaemia, and mesenteric thrombosis or embolism. Associations were assessed using multivariable multilevel logistic regression analysis adjusted for age, sex, Elixhauser comorbidity score, and treatment in vascular surgery departments with random intercepts for hospital and year. Among 100 137 non-cardiac open aortic procedures, 34 100 cases involved infrarenal OAR for iAAA. Overall, in hospital mortality was 5.9%, ranging from 11.3% in Q1 to 5.2% in Q4. In multivariable analysis, treatment in lower volume hospitals was associated with higher mortality (Q1 vs. Q4: odds ratio [OR] 1.79, 95% confidence interval [CI] 1.30 - 2.47; p < .001). Treatment in vascular surgery departments was associated with reduced mortality (OR 0.83, 95% CI 0.72 - 0.94; p = .005). Higher hospital volume of all non-cardiac open aortic procedures was associated with lower in hospital mortality after infrarenal OAR for iAAA. These findings support centralisation efforts and suggest that minimum case volume requirements should consider the overall non-cardiac open aortic caseload rather than infrarenal procedures alone.
Magnetic resonance imaging (MRI) is the preferred staging modality in the evaluation of rectal cancer. We aimed to evaluate the accuracy of MRI among large rectal polyps referred for endoscopic resection. We analyzed consecutive patients who underwent MRI prior to endoscopic resection for rectal neoplasia. 44 patients with large rectal polyps (mean size 5.8 cm) underwent MRI prior to endoscopic resection. MRI categorized 24 (54.5%) lesions as T0/T1, 16 (36.4%) T2, and 4 (9.1%) T3. Final pathology demonstrated 5 (11.4%) adenomas, 21 (47.7%) high grade dysplasia, 5 (11.4%) intramucosal adenocarcinoma, 9 (20.5%) pT1 adenocarcinoma, and 4 (9.1%) pT2 adenocarcinoma. Findings were discordant in 21 (47.7%) patients (p < 0.01), where MRI over-staged 18 (40.9%) and under-staged 3 (6.8%) patients. We demonstrate that MRI over-stages over 40% (18/44) of large rectal polyps. MRI staging should be interpreted cautiously when considering endoscopic resection for large rectal polyps.
A history of prior cardiac surgery (PCS) determines treatment decision and long-term outcomes in patients requiring aortic valve replacement. This study examined patient profiles, treatment-decisions and long-term outcomes of patients under 75 years with PCS undergoing transcatheter and surgical aortic valve implantation/replacement (TAVI, SAVR) in the Netherlands. Data from 1,284 patients (ages 50-75 years) with PCS undergoing TAVI or SAVR between 2015 and 2020 were analyzed using data from the Netherlands Heart Registration. Logistic and cox regression identified determinants of treatment selection and long-term mortality. Determinants were considered impactful if they had an odds ratio (OR) or hazard ratio (HR) of ≥ 1.5 or ≤ 0.7 and a prevalence of ≥ 5%. Of 1,284 patients, 690 underwent TAVI (54%) and 594 SAVR (46%). Prior index surgery most frequently involved coronary artery bypass grafting (CABG) (57% in the TAVI group vs 40% in the SAVR group; p < 0.001) and previous aortic valve surgery (25% vs 51%; p < 0.001). TAVI patients were significantly older (median 71 vs. 67 years, p < 0.001) and had a higher EuroSCORE II (median 5.7 vs. 4.4, p = 0.003) than SAVR patients. SAVR was the preferred strategy for intermediate-risk patients (62%), while TAVI was favored in high- and prohibitive-risk patients (62% and 94%, respectively). In descending order of odds ratio, the strongest independent determinants of TAVI selection were left ventricular ejection fraction ≤ 30% ((OR: 4.8; 95% CI: 2.6-8.8), poor mobility ((OR: 3.4; 95% CI: 1.6-7.0) and obesity/cachexia (OR 2.7; 95% CI: 1.6-4.4); the key determinants of SAVR selection were pure native aortic regurgitation (OR: 0.1; 95% CI: 0.1-0.3) and failing surgical bioprosthesis (OR: 0.7; 95% CI: 0.5-1.0. Thirty-day, 1- and 5 year survival after TAVI and SAVR was 97% and 96%, 83% and 91%, and 56% and 83%, respectively (p-value < 0.001). Left ventricular ejection fraction ≤ 30% and chronic lung disease were important mortality determinants for both procedures, with higher odds ratios for mortality in SAVR as compared to in TAVI patients. In the Netherlands, TAVI and SAVR rates were comparable among patients < 75 years with PCS. Higher-risk patients were directed toward TAVI except for those presenting with pure native aortic regurgitation and bioprosthesis failure who mainly received SAVR. Severe left ventricular dysfunction and chronic lung disease were key mortality predictors for both procedures.
Catastrophic hemorrhage from uterine rupture is a rare but life threatening obstetric emergency. Patients often present in extremis with concurrent hemodynamic instability. The case study describes the retrieval of a critically ill patient and the challenges encountered during patient transfer and resuscitation. The patient was profoundly hypovolemic and hypoxemic and required intensive therapies such as massive transfusion and adjustments to mechanical ventilation. The case review highlights therapies relevant to the practice of critical care transport medicine including damage control resuscitation. Novel hemorrhage control techniques such as resuscitative endovascular balloon occlusion of the aorta were also considered. Finally, the case report describes complications linked to ongoing resuscitation including transfusion associated circulatory overload. The case emphasizes the utility of multidisciplinary collaboration for complex patient retrievals.
The aim of this study was to evaluate the effects of a protein-rich oat by-product obtained during β-glucan extraction, used as a partial substitute for soybean meal (SBM) in broiler chicken diets, on growth performance, carcass traits, and selected gastrointestinal parameters. The experiment involved 320 one-day-old male Ross 308 broilers divided into four groups (10 replicates of eight birds each). Diets contained 0%, 10%, 15%, or 20% oat by-product. Growth performance parameters were monitored throughout the experiment, and on day 42, carcass traits, gastrointestinal function, the pH of cecal digesta, the concentrations of short-chain fatty acids (SCFA), and intestinal histomorphology were evaluated. No significant differences were found in final growth performance or dressing percentage among treatments. The birds that received the oat by-product had a lower proportion of abdominal fat (P < 0.001). Diets containing 10% or 15% oat by-product reduced cecal pH and the concentrations of isobutyric and isovaleric acids (P < 0.001). Histomorphological analysis revealed optimal villus and crypt parameters at 10-15% inclusion levels of the tested product and less favorable values at 20% (P < 0.001). These results indicate that the tested oat by-product may be considered a promising partial substitute for SBM in broiler diets, although its efficacy depends on the inclusion level. The 10%-15% range yielded the most favorable overall response, while the 20% level was associated with suboptimal histomorphological characteristics of the small intestine.
Trigeminal ganglion percutaneous balloon compression (PBC) for treating trigeminal neuralgia (TN) is favored for its high success rate and minimal complications. During PBC, significant hemodynamic changes can occur, leading to sudden bradycardia, asystole, or rapid blood pressure increase, collectively known as the trigeminocardiac reflex (TCR). Isolated bradycardia during PBC is common. Despite this, mortality risk is very low, with bradycardia becoming critical in few patients. This unknown mechanism might indicate effective compression on Gasser's ganglion, crucial for clinical response in treating TN. An observational study of TN patients who underwent PBC was performed at a neurosurgical unit. The outcome was to assess prognostic impact of bradycardia during PBC and investigate clinical factors for its occurrence. A total of 123 patients were included, divided into two groups: the bradycardia group (n = 35) and the normal frequency group (n = 88). An excellent outcome (BNI I-II) was achieved in 45% of patients in Group 1 and in 34% of patients in Group 2 (p = 0.05). The mean pain-free survival (PFS) duration was significantly longer in the bradycardia group (26 vs. 13 months, p = 0.017). Stable efficacy of pain relief was found in the bradycardia group throughout the follow-up period. Patients who manifested bradycardia demonstrated greater clinical efficacy with a superior Pain outcome and PFS compared with the normal-frequency group with an independent clinical outcome with respect to obtaining pear-shape and time of compression. This finding could be considered as an important prognostic factor.
This paper proposes an integral sliding mode based adaptive robust backstepping control scheme to improve the trajectory tracking and hovering performance of a quadrotor unmanned aerial vehicle (UAV) under large-scale time-varying disturbances. It also considers the impact of variations in the payload mass of the UAV, such as in tasks such as power line maintenance or rescue operations. The proposed scheme effectively mitigates the influence of disturbances on the flight process when the upper bound of the time-varying disturbance is unknown, and estimates the potentially uncertain parameters of the system in real time. Using Lyapunov stability theory, it was proven that the designed controller ensured the asymptotic convergence of the tracking error to zero. Furthermore, this paper integrates adaptive control with the concept of integral sliding mode, combining their respective technical characteristics in a complementary manner. The proposed adaptive law, incorporating a σ-modification term, effectively suppresses the chattering inherent in sliding mode control, ensuring system stability. The integration of the sliding mode surface further accelerates the error convergence to zero. The simulation results validate the performance of the proposed control scheme in various scenarios, including continuous weak disturbances, changes in payload mass, and sudden large-scale time-varying disturbances. The results demonstrate that the proposed control scheme has strong robust stabilization and wide applicability, outperforming the traditional adaptive robust control methods and classical PID methods.