Search Results (13,211)

The accurate estimation of outflow discharge from Piano Key Weirs (PKWs) under unsteady flow conditions is critical for effective flood management and the safety of dams. While extensive research exists on PKWs under steady flow, their hydraulic behavior during unsteady flow remains poorly understood. This study addresses this gap by investigating a Type-A PKW using combined physical and numerical modeling. A total of eight steady-flow and fifty-three unsteady-flow experiments were conducted. The steady flow experiments covered a range of Q = 5.13–40.76 L/s (H = 1.29–10.45 cm), while the unsteady experiments employed hydrographs with peak discharges up to ~68 L/s. Outflow was estimated via the Modified Puls method (hydrological routing) and a validated 3D numerical model (hydraulic routing). The results revealed significant discrepancies between steady and unsteady stage-discharge relationships, with a mean relative error of up to 41.37% and instantaneous errors exceeding 150% during the rising limbs of hydrographs with high rates of change in discharge, associated with intensified unsteady flow effects. A validated looped stage-discharge curve was observed under unsteady conditions, showing lower discharge on the rising limb for the same head. The Modified Puls method exhibited high accuracy, with relative errors below 5% when compared to hydraulic routing results. Additionally, three comparative indices were proposed and used to evaluate the performance of outflow estimation methods. The findings underscore the importance of incorporating unsteady flow conditions in the design and analysis of PKWs, particularly in the context of climate change and increasing flood uncertainties. Full article

In the 21st century, Saudi cities have witnessed a high rate of private car ownership, averaging 1.38 vehicles per family. This has significantly increased demand for parking in residential areas, leading to unregulated parking behaviors that negatively affect street and sidewalk infrastructure. Although some research has been conducted in Saudi Arabia on illegal parking in commercial streets, research on unregulated parking in residential streets remains underexplored. This study investigates the impact of unregulated parking behavior on street and sidewalk infrastructure in residential districts with apartment zones in Jeddah, Saudi Arabia, determining the extent to which current sidewalk strips have been modified to extend on-street parking, create front setbacks for parking, and provide access to ground-floor private parking and residential building entrances. We selected six typical apartment building zones and mapped parking behavior through direct observations, processing collected data through ArcGIS. Our findings reveal negative impacts, resulting in significant parts of sidewalks, front setbacks, and streets being used for parking, thereby creating unhealthy and unsafe residential areas for walking and other physical activities. This study offers a comprehensive understanding of the unregulated parking problem and its subsequent impact on residents’ quality of life, particularly in terms of walking accessibility and safety. Full article

Objectives: To develop and validate a transthoracic lung ultrasound (TLUS)-integrated clinical nomogram for predicting pulmonary arterial hypertension (PAH) in patients with connective tissue disease-associated interstitial lung disease (CTD-ILD). Methods: This multicenter retrospective study included 550 patients with CTD-ILD from the Second Affiliated Hospital of Fujian Medical University and 169 external cases from the Xijing Hospital, Fourth Military Medical University. Patients were randomly divided into a training cohort (n = 385) and an internal validation cohort (n = 165); the external dataset served as a testing cohort. Demographic, physiological, laboratory, pulmonary function, and TLUS data were collected. Univariate and multivariate logistic regression analyses identified independent predictors of PAH, which were used to construct a nomogram model. Discrimination was assessed using receiver operating characteristic (ROC) curves and area under the curve (AUC) values. Calibration, decision curve analysis (DCA), and clinical impact curves (CIC) were performed to evaluate model accuracy and clinical utility. Results: Five independent predictors were identified: respiratory rate, diffusing capacity of the lung for carbon monoxide (DLCO% predicted), TLUS score, red blood cell (RBC) count, and brain natriuretic peptide (BNP). The model achieved excellent discrimination with AUCs of 0.952 (95% confidence interval [CI]: 0.927–0.977) in the training cohort, 0.935 (95% CI: 0.885–0.985) in the validation cohort, and 0.874 (95% CI: 0.806–0.942) in the testing cohort, outperforming individual predictors. Calibration plots showed close agreement between predicted and observed probabilities, while DCA and CIC confirmed strong clinical benefit and applicability across all thresholds. Conclusions: This TLUS-integrated nomogram provides a noninvasive and reliable tool for individualized PAH risk assessment in CTD-ILD patients. By combining ultrasound findings with physiological and laboratory markers, the model enables accurate detection of high-risk cases and may assist clinicians in optimizing surveillance and management strategies. Full article

Context: Optimizing nitrogen application and planting density is critical for achieving high yields and increasing lodging resistance in crops. However, the agronomic mechanisms underlying these benefits remain unclear. Objectives: This study aimed to elucidate the relationships among light distribution within the canopy, photosynthetic capacity, root architecture, yield, and lodging resistance in sweet corn. Methods: A two-year field experiment (2024–2025) was conducted using a split-plot design with two factors: nitrogen application levels as main plots (namely, N150 and N200; 150 kg/ha and 200 kg/ha, respectively) and three planting densities as sub-plots (D20, D25, and D30, representing plant spacing of 20 cm, 25 cm, and 30 cm, respectively, with a fixed row spacing of 80 cm). Results: At a given planting density, N150-treated plants exhibited significantly enhanced basal stem node strength and root architecture compared to those treated with N200. These improvements were closely associated with the increase in light interception rate (IR) into the lower canopy under N150. Consequently, root-lodging resistance increased, reducing the root lodging rate by 80.82% (7.32% vs. 13.21% under N200). Due to these advantages, the average yield of N150-treated plants was higher than that of N200-treated plants (+3.16%). Notably, increasing planting density emerged as the primary factor driving ear yield improvement, with the highest yield observed under the N150D20 group plants, which can reach ~29 t/ha. Conclusion: Coordinating nitrogen input with appropriate planting density improves vertical light distribution, particularly in the middle and lower canopy, thereby strengthening the basal stem and root systems and enhancing root lodging resistance and yield. Implication: These findings offer practical guidance for achieving high sweet corn yields by integrating canopy light management with optimized nitrogen application and planting density, and provide scientific guidance on “smart canopy” selection for sweet corn breeding. Full article

The cotton boll opening rate (BOR) is an important indicator for evaluating the physiological maturation process of cotton and the critical stage of yield formation, and it provides essential guidance for subsequent defoliant application and mechanical harvesting. The investigation of cotton BOR usually relies on manual field surveys, which are time-consuming and destructive, making it difficult to achieve large-scale and efficient monitoring. UAV remote sensing technology has been widely used in crop growth monitoring due to its operational flexibility and high image resolution. However, because of the dense growth of the cotton canopy in UAV remote sensing imagery, the boll opening condition in the lower parts of the canopy cannot be completely observed. In contrast, UAV imagery can effectively monitor cotton leaf chlorophyll content (SPAD) and leaf area index (LAI), both of which undergo continuous changes during the boll opening process. Therefore, this study proposes using SPAD and LAI retrieved from UAV multispectral imagery as physiological intermediary variables to construct an empirical statistical equation and compare it with end-to-end machine learning baselines. Multispectral and ground synchronous data (n = 360) were collected in Baibi Town, Anyang, Henan Province, across four dates (8/28, 9/6, 9/13, 9/24). Twenty-eight commonly used vegetation indices were calculated from multispectral imagery, and Pearson’s correlation analysis was conducted to select indices sensitive to cotton SPAD, LAI, and BOR. Prediction models were constructed using the Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Support Vector Machine (SVM), and Partial Least Squares (PLS) models. The results showed that GBDT achieved the best prediction performance for SPAD (R² = 0.86, RMSE = 1.19), while SVM performed best for LAI (R² = 0.77, RMSE = 0.38). The quadratic polynomial equation constructed using SPAD and LAI achieved R² = 0.807 and RMSE = 0.109 in BOR testing, which was significantly better than the baseline model using vegetation indices to directly regress BOR. The method demonstrated stable performance in spatial mapping of BOR during the boll opening period and showed promising potential for guiding defoliant application and harvest timing. Full article

Purpose: This study assessed the adaptations resulting from implementing an experimental, integrated training program tailored to sex-specific traits. The aim was to enhance motor abilities, aerobic capacity, and metabolic variables in female and male rugby sevens athletes. Methods: Employing a combined observational and experimental design, initial and post-intervention assessments were conducted over three months (March–June 2023) with 24 elite professional players, divided equally by sex (12 females, 12 males). The protocol consisted of 12 micro-cycles, each lasting 7 days and comprising 12 training sessions. The evaluations included sprint and jumping tests, as well as functional assessments such as resting metabolic rate and cardiopulmonary exercise testing. Results: Using one-way repeated measures ANOVA, significant improvements were noted across all performance parameters (p < 0.001), with effect sizes ranging from small to very large. Sex-specific differences were evident, with females demonstrating consistent improvements in aerobic capacity and jumping ability, while males excelled in explosive power and longer sprints. Despite initial performance disparities, both sexes improved in short-distance sprints (10 m and 40 m). Cardiovascular efficiency improved as indicated by reduced maximum heart rates and lower respiratory quotients. Conclusions: Males showed superior progress in strength and explosive power tests, reflecting distinct physiological traits. These findings underscore the need for individualized and sex-specific training programs to optimize performance in high-intensity sports, such as rugby sevens. Full article

Background: Solid organ transplant recipients (SOTRs) are highly vulnerable to severe COVID-19 infection, yet initial vaccine trials provided limited data on efficacy and safety in this immunocompromised population. Heterogeneous seroconversion rates and conflicting safety reports complicate the formulation of clear clinical guidelines. This systematic review and meta-analysis aim to aggregate existing evidence to determine the precise seroconversion and safety profiles of COVID-19 vaccines and identify key factors influencing immune response in SOTRs. Methods: A comprehensive literature search was conducted identifying 125 studies evaluating WHO/FDA-authorized vaccines in SOTRs. Outcomes were the pooled seroconversion proportion and safety profile. Subgroup analyses were performed based on vaccine type, transplanted organ, number of doses, and prior SARS-CoV-2 infection status, confirmed by leave-one-out sensitivity analysis and bootstrap methods. Results: Most studies assessed mRNA-based vaccines (123/125, 98.4%). The overall pooled seroconversion proportion across all SOTRs was significantly blunted at 0.49 (95% CI, 0.43 to 0.55), demonstrating high heterogeneity (I² = 94.2%). Seroconversion showed a clear positive dose–response relationship, increasing from 27% after one dose to 84% after four doses. Prior COVID-19 infection was the strongest predictor of a response, resulting in a pooled seroconversion of 0.90 (95% CI, 0.82 to 0.94; I² = 0%). Organ-specific analyses revealed the highest response in Liver recipients (0.80) and the lowest in Lung recipients (0.29). Vaccine platform analysis showed that the highest response was with mRNA-1273 (0.55) and the lowest with CoronaVac (0.29). The safety profile was limited. Conclusions: SOTRs exhibit profound hypo responsiveness to COVID-19 vaccines; however, the extreme heterogeneity observed across studies necessitates a cautious interpretation of pooled seroconversion estimates. While the data indicates a significant dose–response relationship favoring an aggressive, multi-dose strategy, the apparent safety profile may reflect under-reporting and limited follow-up rather than confirmed safety equivalence. Rare but clinically critical outcomes, such as acute allograft rejection, remain inadequately characterized in the current literature. Consequently, while the prioritization of multi-dose regimens and hybrid immunity is supported to maximize protection, clinicians must recognize that individual responses remain highly variable, and the long-term immunological impact of repeated stimulation requires further standardized investigation. Full article

Salt stress is one of the most harmful abiotic stresses that strongly affects plant growth and crop yield, limiting agricultural production across the Mediterranean area. Consequently, there is a growing need to identify resilient crops capable of adapting to saline conditions and enhancing desirable qualitative traits through a wide spectrum of physiological, biochemical, and molecular mechanisms. Therefore, this study aimed to investigate the effects of four different NaCl concentrations (0, 12.5, 25, and 50 mM) on the growth rates, biometric and productive characteristics, leaf gas exchange, and biochemical traits of Stevia rebaudiana Bertoni plants grown hydroponically (in a floating raft system) in a glasshouse. The results showed that NaCl-treated plants exhibited reduced growth parameters and productivity and a lower content of photosynthetic pigment content compared to the control. On the other hand, an increase in antioxidant capacity was observed due to the significant accumulation of total phenols and flavonoids, especially when stevia plants were treated with 50 mM NaCl. Similarly, the leaf concentration of ascorbic acid and glutathione remarkably increased. This provides new insight into the antioxidant defense strategy of S. rebaudiana under salt stress, demonstrating that stevia plants rely mainly on non-enzymatic mechanisms to counter oxidative stress. Although the highest salinity level (50 mM NaCl) resulted in the lowest content of steviol glycosides (stevioside + rebaudioside A), plants treated with 25 mM NaCl showed both the highest rebaudioside A content and Reb A/Stev ratio, which are desirable properties for the production of high-quality natural sweeteners. Overall, these findings underline that stevia can be considered a moderately salt-tolerant species, and mild stress conditions are able to promote the biosynthesis of interesting secondary metabolites, such as polyphenols and rebaudioside A. Full article

Background/Objectives: Adults with intellectual disability (ID) experience high rates of psychiatric comorbidity but often face diagnostic challenges and treatment barriers, leading to inappropriate psychotropic medication use. This study examined the extent to which specialized psychiatric assessment and improved diagnostic accuracy had an impact on medication management and clinical outcomes in adults with ID and co-occurring psychiatric disorders. Methods: This observational retrospective study analyzed medical records from 25 adults with ID who underwent specialized psychiatric assessment at a community-based service in Italy between January 2023 and January 2024. Psychopathological diagnoses were established according to Diagnostic Manual—Intellectual Disability, Second Edition (DM-ID2) criteria, based on clinical observation and a comprehensive assessment using validated instruments. Clinical outcomes were assessed using a psychometric tool encompassing multiple psychopathological and behavioral dimensions. Data on psychotropic prescriptions and side effects were also collected. Non-parametric analyses were performed, with significance set at α = 0.05. Results: The proportion of patients with a psychiatric diagnosis increased from 32% to 96% after specialized assessment (p < 0.001), with notable rises in depressive (0% to 32%), bipolar (8% to 36%), anxiety (4% to 24%), and impulse control (0% to 16%) disorders. First-generation antipsychotic prescriptions decreased (from 36% to 8%, p = 0.023), while antidepressant use increased (from 12% to 52%, p = 0.004). The mean number of side effects per patient declined from 1.6 to 0.5 (p < 0.001), particularly the elevated prolactin level and psychomotor retardation. Significant improvements were observed in symptom intensity and frequency across multiple domains, including aggression, mood disturbances, and compulsions (p < 0.001). Conclusions: In this single-center retrospective study, specialized psychiatric assessment was associated with improved diagnostic accuracy, medication management, and clinical outcomes in adults with ID. The increase in psychiatric diagnoses likely reflects improved identification, addressing key challenges in precision diagnosis for people with neurodevelopmental disorders. Although the overall number of prescribed medications remained stable, optimization of treatment regimens reduced first-generation antipsychotic use and related adverse effects. These findings indicates that access to specialized assessment and precision diagnosis could improve psychopharmacological interventions and outcomes for this vulnerable population, but larger, multi-center and longer-term studies are needed to confirm these results. Full article

Following the normalization of the COVID-19 pandemic, the focus of wastewater-based epidemiology (WBE) must be broadened from SARS-CoV-2 to encompass surveillance of other major infectious diseases, particularly for pathogens where conventional clinical monitoring systems exhibit inherent surveillance gaps. In this study, we conducted a continuous two-year WBE study (January 2023 to December 2024) across three high-population-density cities in Guangdong, China to establish epidemiological baselines for enteric diarrheal viruses. We analyzed monthly raw wastewater samples from major treatment plants using advanced molecular methods, including digital PCR (ddPCR) for viral load quantification and targeted high-throughput sequencing (tNGS) for genotypic analysis. Our findings revealed diverse circulation patterns among the monitored enteric viruses. Astrovirus (AstV) had the highest detection rate (100%), reflecting its broad endemic distribution, while Norovirus genogroup II (NoV GII) exhibited relatively high viral loads (median 4 × 10⁴ copies/mL) and presented explosive seasonal peaks (significant upward trend in spring.), highlighting its epidemic potential. Furthermore, distinct spatiotemporal patterns were observed, with Sapovirus showing a significant summer peak in Foshan city, contrasting with the winter/spring peaks in the other cities. The tNGS results demonstrated similar sensitivity to RT-PCR in virus detection, and sequencing analyses uncovered the co-circulation and periodic shifts in dominant viral genotypes, such as the emergence of multiple NoV and AstV lineages. This longitudinal WBE surveillance successfully established critical baseline data and demonstrated significant regional heterogeneity in viral circulation, providing essential, complementary data to inform public health strategies for preventing diarrheal outbreaks in urban settings. Full article

Background: Although the main target of SARS-CoV-2 is the respiratory system, in some patients, it may affect multiple organ systems, leading to multi-organ failure. Acute kidney injury (AKI) remains one of the most frequent and clinically significant complications of severe COVID-19, with clinical importance extending beyond the acute phase due to its association with long-term renal outcomes and persistent morbidity. The incidence of AKI is particularly high among patients admitted to the intensive care unit (ICU), where its development has been consistently associated with prolonged hospitalization and increased mortality. The primary aim of this study was to determine the incidence of COVID-19-associated AKI, identify factors related to its development and severity, and evaluate mortality as a clinical outcome. Methods: Data from 238 COVID-19 patients monitored in the Intensive Care Unit of Ankara University Ibni Sina Hospital (ISH-ICU) between 1 January 2021 and 1 January 2022 were retrospectively reviewed. Patients were divided into two groups according to the presence of AKI. Those with AKI were staged according to KDIGO criteria (stages 1–2–3). Demographic characteristics, comorbidities, disease severity scores, laboratory parameters, and mortality outcomes were analyzed and compared between groups. Results: AKI was identified in 54.6% of patients. Of the patients with AKI, 32 (13.4%) had stage 1, 25 (10.5%) had stage 2, and 73 (30.7%) had stage 3 AKI. Thirteen patients (5.5%) had already developed AKI at ICU admission. AKI developed at a median of 11 days after symptom onset and 3 days after ICU admission. Advanced age, hypertension, cardiovascular disease, and chronic kidney disease were more frequent in patients with AKI (p < 0.001). Higher Charlson Comorbidity Index (CCI) and Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) scores were observed in patients with stage 3 AKI. Lymphopenia and elevated levels of D-dimer, ferritin, IL-6, CRP, and procalcitonin were significantly higher in patients with stage 3 AKI than in patients with other AKI stages and the non-AKI group. Mortality rates were higher in patients with AKI and increased with advancing AKI stage (p < 0.001). ICU length of stay was significantly longer in the AKI group (p < 0.001). Conclusions: AKI is a common complication among critically ill patients with COVID-19 and is associated with prolonged ICU stay and higher mortality rates, particularly in advanced stages. Early identification of clinical and laboratory factors associated with AKI may support timely risk stratification and targeted management in this high-risk population. Full article

The presented study aims to experimentally investigate the potential of flash sanitation (short time exposure to hot air stream) for wheat seeds to control surface contamination and protect against fungal diseases. Experiments were conducted at the laboratory scale using very short residence times (2–4 s) and higher temperature range (150–350 °C) of dry air stream at two different flow rates (280 L/min and 557 L/min). The goal was to identify thermal conditions that provide high sanitation efficiency while maintaining seed viability. A design of the experiment approach, employing central-composite design and face-centred response surface methodology, was used to evaluate the effects of the thermal treatment on seed surface temperature, sanitation efficiency, and germination capabilities. Higher air flow rate (557 L/min) significantly increased post-treatment seed surface temperatures (42.1–122.7 °C) compared to the flow rate of 280 L/min (36.7–80.5 °C). Pronounced germination drops were observed with air temperatures above 175 °C. Satisfactory sanitation efficiency >90% was achieved only with high-temperature air >250 °C, which, however, caused unacceptable germination loss. Extending residence time beyond the experimental plan is unlikely to yield significant benefits, as the factor was identified as weak and insignificant compared to temperature. Higher flow rates improve heat transfer but require strict control to prevent variability affecting seed quality. The heating media flow rate should be considered an essential factor in thermal treatment studies. Dry air has not proven to be appropriate for seeds’ flash sanitation within the selected experimental condition framework. Full article

Background: Elastography is a non-invasive technique used to assess tissue stiffness. There are two main types of elastography: shear-wave elastography and strain imaging. Both are useful for evaluating the degree of liver fibrosis (LF). Shear-wave imaging is influenced by fibrosis and hepatic congestion, whereas strain imaging primarily reflects fibrosis progression and is less affected by congestion. We previously reported the clinical usefulness of combinational elastography in patients with heart failure (HF). However, its prognostic significance in this population remains unclear. Accordingly, in this prospective study, we aimed to evaluate the prognostic impact of combinational elastography in patients with HF. Methods: We included 77 patients with HF (median age: 79 years). Shear-wave imaging was used to obtain shear-wave velocity (Vs), whereas the liver fibrosis index (LF index) was derived from strain imaging. The Vs/LF index (V/L) was used as a prognostic indicator based on combinational elastography. Cardiac events were defined as cardiac death or hospitalization due to HF. Results: During a median follow-up of 716 days, 17 cardiac deaths or hospitalizations for HF were observed. The V/L demonstrated a cut-off value of 1.2 for predicting cardiac death or hospitalization for HF, with an area under the curve of 0.80, sensitivity of 0.82, and specificity of 0.68. Kaplan–Meier analysis demonstrated that patients with a high V/L (≥1.2) had significantly higher rates of hospitalization for HF than those with a low V/L (<1.2; log-rank test, p < 0.001). Conclusions: Combinational elastography demonstrated prognostic utility in patients with HF and may serve as a novel, non-invasive tool for assessing hepatic congestion. Full article

Background: Minimally invasive pancreatoduodenectomy (MIPD) has evolved from an experimental technique to a feasible surgical option for pancreatic cancer in selected settings. However, its oncologic adequacy, safety, and generalizability remain debated, particularly given the biological aggressiveness of pancreatic ductal adenocarcinoma (PDAC) and the technical complexity of the procedure. Methods: This narrative review critically summarizes contemporary evidence regarding MIPD for pancreatic cancer, with particular attention to randomized controlled trials (RCTs), meta-analyses, and large observational studies. We distinguish findings derived from mixed periampullary tumor cohorts from those specific to PDAC and evaluate methodological limitations, learning-curve effects, and sources of heterogeneity across studies. Results: Recent RCTs and meta-analyses demonstrate that, when performed by experienced surgeons in high-volume centers, MIPD achieves perioperative outcomes comparable to open pancreatoduodenectomy, with advantages including reduced blood loss, shorter hospital stay, and faster functional recovery. Importantly, oncologic parameters such as R0 resection rates and lymph node yield appear equivalent between approaches, although robust long-term survival data from PDAC-specific RCTs remain lacking. Emerging evidence supports the feasibility of MIPD in complex clinical scenarios, including after neoadjuvant therapy, in frail or elderly patients, and in selected cases requiring vascular resection. Nonetheless, outcomes are strongly influenced by surgeon experience, institutional volume, and patient selection. Cost-effectiveness analyses and data from lower-volume centers remain limited. Conclusions: Current evidence supports MIPD as a viable alternative to open surgery for pancreatic cancer in carefully selected patients treated at specialized centers. However, claims of oncologic superiority are premature. Future research should focus on PDAC-specific randomized trials, standardized quality metrics, and strategies to mitigate learning-curve and resource-related barriers to broader implementation. Full article

Deep reinforcement learning (DRL) plays a pivotal role in decision-making within financial markets. However, DRL models are highly reliant on raw market data and often overlook the impact of future trends on model performance. To address these challenges, we propose a novel framework named Cluster Embedding-Proximal Policy Optimization (CE-PPO) for trading decision-making in financial markets. Specifically, the framework groups feature channels with intrinsic similarities and enhances the original model by leveraging clustering information instead of features from individual channels. Meanwhile, zero-shot prediction for unseen samples is achieved by assigning them to appropriate clusters. Future Open, High, Low, Close, and Volume (OHLCV) data predicted from observed values are integrated with actually observed OHLCV data, forming the state space inherent to reinforcement learning. Experiments conducted on five real-world financial datasets demonstrate that the time series model integrated with Cluster Embedding (CE) achieves significant improvements in predictive performance: in short-term prediction, the Mean Absolute Error (MAE) is reduced by an average of 20.09% and the Mean Squared Error (MSE) by 30.12%; for zero-shot prediction, the MAE and MSE decrease by an average of 21.56% and 31.71%, respectively. Through data augmentation using real and predicted data, the framework substantially enhances trading performance, achieving a cumulative return rate of 137.94% on the S&P 500 Index. Beyond its empirical contributions, this study also highlights the conceptual relevance of symmetry in the domain of algorithmic trading. The constructed deep reinforcement learning framework is capable of capturing the inherent balanced relationships and nonlinear interaction characteristics embedded in financial market behaviors. Full article