Search Results (1,519)

The optimal control of cooling water systems is of great significance for energy saving inchiller plants. Previously optimal control methods optimize the flow rate, temperature or temperature difference setpoints but cannot control pumps and cooling tower fans directly. This study proposes a direct optimal control method for pumps and fans based on derivativecontrol strategyby decoupling water flow rate optimization and airflow rate optimization, which can make the total power of chillers, pumps and fans approach a minimum. Simulations for different conditions were performed for the validation and performance analysis of the optimal control strategy. The optimization algorithms and implementation methods of direct optimal control were developed and validated by experiment. The simulation results indicate that total power approaches a minimum when the derivative of total power with respect to water/air flow rate approaches zero. The power-saving rate of the studied chiller plant is 13.2% at a plant part-load ratio of 20% compared to the constant-speed pump/fan mode. The experimental results show that the direct control method, taking power frequency as a controlled variable, can make variable frequency drives regulate their output frequencies to be equal to the optimized power frequencies of pumps and fansin a timely manner. Full article

Frame Replication and Elimination for Reliability (FRER) in Time-Sensitive Networking (TSN) enhances fault tolerance by duplicating critical traffic across disjoint paths. However, always-on FRER configurations introduce persistent redundancy overhead, even under nominal network conditions. This paper proposes a predictive FRER activation framework that anticipates faults using a Key Performance Indicator (KPI)-driven bidirectional Long Short-Term Memory (BiLSTM) model. By continuously analyzing multivariate KPIs—such as latency, jitter, and retransmission rates—the model forecasts potential faults and proactively activates FRER. Redundancy is deactivated upon KPI recovery or after a defined minimum protection window, thereby reducing bandwidth usage without compromising reliability. The framework includes a Python-based simulation environment, a real-time visualization dashboard built with Streamlit, and a fully integrated runtime controller. The experimental results demonstrate substantial improvements in link utilization while preserving fault protection, highlighting the effectiveness of anticipatory redundancy strategies in industrial TSN environments. Full article

Essential oils play important roles in the modern food industry as additives and spices. At the same time, most essential oils have broad-spectrum bacteriostatic properties and can be used as natural antimicrobial materials. However, the application of essential oils is limited due to their strong volatility and insolubility in aqueous substrates. In this study, we used ultrasonic emulsification, carboxymethyl chitosan, and Tween 80 to formulate tea tree essential oil (TTO) nanoemulsions with high stability. With a minimum diameter of about 51 nm (PDI = 0.236 ± 0.021) post-emulsification, the TTO nanoemulsions disperse effectively in the drainage system and exhibit good stability after 14 days of storage. In addition, the bioactivity (antibacterial and antioxidant) of TTO nanoemulsions was significantly enhanced following emulsification, as evidenced by MIC and DPPH assays, indicating that nano-emulsification is beneficial to the development of various essential oils. TTO nanoemulsions can be used as a new food preservative to control the growth of bacteria and prevent the deterioration of food via oxidation. Full article

Acid mine drainage (AMD) is an environmental concern that needs to be addressed by some mining industries because of its high concentrations of metals and acidity that destroy affected ecosystems. Its formation typically persists beyond the operating life of a mine site. Its management is even more challenging for sites that are abandoned without rehabilitation. In this study, a legacy copper–gold mine located in Sto. Niño, Tublay, Benguet, Philippines, generating a copper- and manganese-rich AMD (Cu, maximum 17.2 mg/L; Mn, maximum 2.90 mg/L) at pH 4.59 (minimum) was investigated. With its remote location inhabited by the indigenous people local community (IPLC), a novel limestone-based hybrid passive treatment system that combines a limestone leach bed (LLB) and a controlled modular packed bed reactor (CMPB) has been developed from the laboratory and successfully deployed in the field while investigating the effective hydraulic retention time (HRT), particle size, and redox conditions (oxic and anoxic) in removing Cu and Mn and increasing pH. Laboratory-scale and pilot-scale systems using simulated and actual AMD, respectively, revealed that a 15 h HRT and both oxic and anoxic conditions were effective in treating the AMD. Considering these results and unsteady conditions of the stream in the legacy mine, a hybrid multi-stage limestone leach bed and packed bed were deployed having variable particle size (5 mm to 100 mm) and HRT. Regular monitoring of the system showed the effective removal of Cu (88.5%) and Mn (66.83%) as well as the increase of pH (6.26), addressing the threat of AMD in the area. Improvement of the lifespan of the system needs to be addressed, as issues of Cu-armoring were observed, resulting in reduced performance over time. Nonetheless, the study presents a novel technique in implementing passive treatment systems beyond the typical treatment trains reported in the literature. Full article

Aphid control often relies on synthetic pesticides, but their overuse has raised concerns about resistance development and negative impact on wildlife and human health. Consequently, the search for new biopesticide agents has gained significant attention. Nemertide alpha-1, a peptide toxin from the marine nemertean worm Lineus longissimus (Gunnerus, 1770), is known for its pesticide activity but has less documented biological safety. This study investigates the aphid feeding deterrence and biological safety of the experimental biopesticide nemertide alpha-1. Nemertide alpha-1 demonstrated a clear dose-dependent repellent effect on the penetration behaviour of the green peach aphid (Myzus persicae, Sulzer). It also demonstrates bacteriostatic and bactericidal effects in an MIC (Minimum Inhibitory Concentration) assay, respectively, on E. coli (MIC: 112.5 µM) and S. aureus (MIC: 28.4 µM). In a bacterial liposome leakage assay, nemertide alpha-1 exhibits a less pronounced effect than the melittin control (20% maximum leakage at 100 µM), strengthening the hypothesis on the specificity of its neurotoxic mode of action. It is not toxic to mammalian cell U-937 GTB with only a slight decline in the percentage of survival at the highest concentration tested (80 µM). Finally, nemertide alpha-1 displays thermal stability over time for four weeks in three different conditions: cold (6 °C), room temperature (20–24 °C), and physiological temperature (37 °C). Nemertide alpha-1 deters green peach aphid feeding in the low micromolar range and exhibits low antimicrobial properties and very low toxicity to human cells. Its potential utility is further underscored by thermal stability over time. Full article

In producing docosahexaenoic acid (DHA) with Schizochytrium sp., the production yield of DHA can be effectively increased through using hydrogen peroxide (H₂O₂) and controlling its concentration at the desired level, since H₂O₂ is a common regulatory mediator for lipid accumulation in oleaginous microorganisms. However, when exposed to the environment of oxidative stress induced by the long-term exogenous addition of H₂O₂ over an extended time span, cells’ metabolic activity would be gradually decreased or even stopped, which ultimately results in a limited duration for producing DHA efficiently. In fact, the severe accumulation of ROS cannot be avoided when implementing the normal DHA fermentation batch without the use of exogenous H₂O₂ because of the necessity of supplying a mass of oxygen for cell respiration. Aiming to overcome these issues, a novel periodic feeding strategy for H₂O₂ and p-aminobenzoate was proposed, and the underlying principle of this strategy is that the substantial harm inflicted on cells due to their continuous exposure to the oxidative stress environment can be effectively alleviated through the implementation of a recovery treatment (p-aminobenzoate, reducing agent) subsequent to the environmental stimulus. When using this strategy, it was achieved that, concurrently, activities of the vital enzymes participating in lipid biosynthesis were maintained at their maximum levels and the maintenance coefficient of glucose reduced to its minimum level (0.0034 1/h vs. 0.0027 1/h) by controlling ROS concentration at lower and desired levels, and thus DHA concentration reached the maximum value of 1.49 ± 0.20 g/L, with a 49% increase compared to the control group. Full article

Background: Multimodal analgesia, combining adductor canal block (ACB) and local infiltration analgesia (LIA), is commonly used for pain control after total knee arthroplasty (TKA). However, ACB alone may not fully cover the anteromedial knee, a region extensively disrupted by TKA. Recent studies suggest that blocking branches of the anterior femoral cutaneous nerve (AFCN) could enhance analgesia, but targeted AFCN blocks are technically challenging. We evaluated supra-sartorial subcutaneous infiltration (SSSI) at the femoral triangle apex as a simpler alternative to AFCN blocks. Methods: We retrospectively reviewed 19 patients undergoing TKA with a standardized multimodal analgesic protocol, including intraoperative LIA limited to posterior capsule (PC-LIA), postoperative SSSI, and delayed intermittent ACB via catheter. SSSI involved infiltrating 20 mL of 0.3% ropivacaine into the subcutaneous plane above the sartorius muscle at the level of femoral triangle apex. Pain was assessed using Numerical Rating Scale (NRS) scores at rest and during movement at 9:00 PM on postoperative day 0 (POD 0) and 9:00 AM on POD 1, with scheduled ACB doses administered at the time of NRS pain score assessments. Rescue ACB boluses were given for intolerable pain before the first scheduled dose. Results: Eleven patients (58%) required no rescue analgesia before the first scheduled ACB, maintaining NRS scores ≤ 4 at rest and with movement for a minimum of 575–785 min post-spinal anesthesia. Eight patients needed rescue ACB, with variable pain relief. Conclusions: SSSI, when combined with PC-LIA, provided clinically meaningful analgesia in 58% of our patient cohort following TKA, though the variability observed suggests limited consistency. As a practical alternative to targeted AFCN blocks, SSSI could potentially complement ACB in multimodal pain management, but its efficacy remains uncertain due to the retrospective, non-controlled study design without a comparator group. Further investigation through prospective randomized controlled trials is warranted to validate these preliminary findings. Full article

In this research article, a fast and efficient hybrid Maximum Power Point Tracking (MPPT) control technique is proposed for photovoltaic (PV) systems. The method combines two phases—offline and online—to estimate the appropriate duty cycle for operating the converter at the maximum power point (MPP). In the offline phase, temperature and irradiance inputs are used to compute the real-time reference peak power voltage through an Adaptive Neuro-Fuzzy Inference System (ANFIS). This estimated reference is then utilized in the online phase, where the Robust Backstepping Super-Twisting (RBST) controller treats it as a set-point to generate the control signal and continuously adjust the converter’s duty cycle, driving the PV system to operate near the MPP. The proposed RBST control scheme offers a fast transient response, reduced rise and settling times, low tracking error, enhanced voltage stability, and quick adaptation to changing environmental conditions. The technique is tested in MATLAB/Simulink under three different scenarios: continuous variation in meteorological parameters, sudden step changes, and partial shading. To demonstrate the superiority of the RBST method, its performance is compared with classical backstepping and integral backstepping controllers. The results show that the RBST-based MPPT controller achieves the minimum rise time of $0.018$$\mathrm{s}$, the lowest squared error of $0.3015$$\mathrm{V}$, the minimum steady-state error of $0.29$%, and the highest efficiency of $99.16$%. Full article

Background: Human immunodeficiency virus and hypertension increasingly co-occur in South Africa. Despite publicly funded care, patients with multimorbidity face high out-of-pocket costs, yet limited evidence exists from the patient perspective. Purpose: To quantify the economic burden of comorbid HIV and hypertension, assess predictors of monthly out-of-pocket costs, and explore coping mechanisms. Methods: We conducted a cross-sectional analysis using patient-level data from the Mobile Phone Text Messages to Improve Hypertension Medication Adherence in Adults with HIV (MOPHADHIV trial) [Trial number: PACTR201811878799717], a randomized controlled trial evaluating short messages services adherence support for hypertension care in people with HIV. We calculated the monthly direct non-medical, indirect, and coping costs from a patient perspective, valuing indirect costs using both actual income and minimum wage assumptions. Generalized linear models with a gamma distribution and log link were used to identify cost determinants. Catastrophic expenditure thresholds (10–40% of monthly income) were assessed. Results: Among 683 participants, mean monthly total costs were ZAR 105.81 (USD 5.72) using actual income and ZAR 182.3 (USD 9.9) when valuing indirect costs by minimum wage. These time-related productivity losses constituted the largest share of overall expenses. Regression models revealed a strong income gradient: participants in the richest quintile incurred ZAR 131.9 (95% CI: 63.6–200.1) more per month than the poorest. However, this gradient diminished or reversed under standardized wage assumptions, suggesting a heavier proportional burden on middle-income groups. Other socio-demographic factors (gender, employment, education) not significantly associated with total costs, likely reflecting the broad reach of South Africa’s primary health system. Nearly half of the participants also reported resorting to coping mechanisms such as borrowing or asset sales. Conclusions: Comorbid HIV and hypertension impose substantial patient costs, predominantly indirect. Income disparities drive variation, raising equity concerns. Strengthening integrated human immunodeficiency virus—non-communicable diseases care and targeting financial support are key to advancing South Africa’s Universal Health Coverage reforms. Full article

Background/Objectives: Bacterial resistance to antimicrobials is a major global health challenge, limiting the effectiveness of conventional therapies and complicating infection control. The aim of this study was to investigate the antibacterial potential of biologically synthesized silver nanoparticles (Bio-AgNP), alone and in combination with ampicillin (AMP) and enrofloxacin (ENRO), against multidrug-resistant (MDR) bacterial isolates of clinical and veterinary relevance. Methods: The antibacterial activity of Bio-AgNP, AMP, and ENRO, alone or in combination, was assessed against reference strains and MDR isolates of Escherichia coli, Salmonella enterica serovar Typhimurium and Enteritidis, and Staphylococcus aureus. Minimum inhibitory concentration (MIC) values were determined, and bacterial tolerance to prolonged antimicrobial exposure was evaluated. Additionally, assays were conducted to explore potential mechanisms of action, including cell membrane permeability and oxidative stress induction. Results: All bacterial strains developed increased MIC values after prolonged exposure to conventional antibiotics, confirming resistance. Only E. coli developed resistance to Bio-AgNP. Notably, the Bio-AgNP + AMP combination effectively restored susceptibility in E. coli, while only S. Enteritidis developed resistance to this combination upon prolonged exposure. The synergistic effect of Bio-AgNP with conventional antibiotics significantly reduced bacterial growth within two hours, compared with longer times observed in monotherapy. Mechanistic analysis suggested that the combinations increased membrane permeability, facilitating antibiotic entry. Conclusions: Bio-AgNPs combined with AMP or ENRO enhanced antibacterial activity and overcame resistance in MDR isolates, representing a promising therapeutic alternative. The biological synthesis of Bio-AgNPs, capped with organic biomolecules, supports their potential as safe adjuvants to conventional antibiotics in combating MDR bacterial infections. Full article

With the increasing penetration of renewable energy, power system frequency stability faces multiple challenges. In addition to the decline of system inertia traditionally provided by synchronous machines, uncertainties such as wind power forecast errors, converter control characteristics, and stochastic load fluctuations further exacerbate the system’s sensitivity to power disturbances, increasing the risks of frequency deviation and instability. Among these factors, insufficient inertia is widely recognized as one of the most direct and critical drivers of the initial frequency response. This study focuses on this issue and explores the use of battery energy storage system (BESS) parameter optimization to enhance system stability. To this end, a simulation platform was developed in PSS^®E V34 based on the IEEE New England 39-bus system, incorporating three wind turbines and two BESS units. The WECC generic models were adopted, and three wind disturbance scenarios were designed, including (i) disconnection of a single wind turbine, (ii) derating of two turbines to 50% output, and (iii) derating of three turbines to 50% output. In this study, a one-at-a-time (OAT) sensitivity analysis was first performed to identify the key parameters affecting frequency response, followed by optimization using an improved particle swarm optimization (IPSO) algorithm. The simulation results show that the minimum system frequency was 59.888 Hz without BESS control, increased to 59.969 Hz with non-optimized BESS control, and further improved to 59.976 Hz after IPSO. Compared with the case without BESS, the overall improvement was 0.088 Hz, of which IPSO contributed an additional 0.007 Hz. These results clearly demonstrate that IPSO can significantly strengthen the frequency support capability of BESS and effectively improve system stability under different wind disturbance scenarios. Full article

We explored the mass concentrations of water-soluble ions in PM_2.5 and their variations across different time scales and concentration levels. Using the Positive Matrix Factorization (PMF) model and backward trajectory analysis, we focused on identifying the sources of PM_2.5 and its water-soluble ion fractions, with particular emphasis on regional transport. The findings reveal that the average mass concentration of total water-soluble ions in Hainan between 1 August 2021 and 31 July 2022 was 7.0 ± 4.4 µg m⁻³, constituting 73.5% ± 24.4% of PM_2.5. Secondary ions (SO₄²⁻, NO₃⁻, NH₄⁺) were dominant, accounting for 84.0% ± 12.4% of the total water-soluble ions, followed by sea-salt particles. Seasonal variations were pronounced, with the highest concentrations observed in winter and the lowest in summer. The results of the PMF analysis showed that secondary sources, combustion sources, dust sources, and oceanic sources are the main sources of PM_2.5 at the monitoring site. The potential sources and transport pathways of water-soluble ions exhibit distinct seasonal characteristics, with the land-based outflows from the YRD–PRD–Fujian corridor controlling Hainan’s PM_2.5 maxima, while southerly marine air delivers the annual minimum; seasonal alternation between dust/secondary aerosols (winter–spring), combustion (autumn), and oceanic dilution (summer) dictates the island’s air-quality rhythm. Full article

For the motion control of ships in confined and curved waterways, from broad coastal channels to narrow river bends, conventional methods often struggle to ensure both tracking accuracy and navigational safety. A key deficiency is the inability of standard algorithms to incorporate the nuanced principles of good seamanship. To address this, a novel, hierarchical adaptive control framework is proposed. The core novelty of this framework lies in its versatile and adaptive guidance rules, which embed maritime practice into the control loop for different navigating scenarios. In general maritime channels with wind and current, these rules function to ensure robust, high-fidelity route tracking. For the most challenging inland river curved channels, it is further enhanced to generate a strategic, non-centerline trajectory that replicates the crucial inland navigational practice of “holding high and taking low”. This is complemented by a reinforcement learning-based strategy at the control layer, which performs real-time tuning of PID gains to adapt to the vessel’s dynamics. The framework’s dual capabilities were systematically validated. The core adaptive algorithms proved effective for robust control in curved channels under wind and current disturbances. Furthermore, the full framework, including the seamanship-informed strategy, demonstrated superior performance in the most complex inland river scenarios. Compared to a conventional controller, the proposed method reduced the peak cross-track error by over 40% and increased the minimum safety margin from the bank by more than 49% under a strong 3 m/s cross-current. An effective solution for motion control is thus provided, bridging the gap between modern control theory and the context-dependent expertise of practical pilotage. Full article

Addressing the problems of wind power’s anti-peak regulation characteristics, increasing system peak regulation difficulty, and wind power uncertainty causing frequency deviation leading to power imbalance, this paper considers the peak shaving and valley filling function and frequency regulation characteristics of energy storage, establishing a day-ahead and intraday coordinated two-stage optimization scheduling model for research. Stage 1 establishes a deterministic wind power prediction model based on time series Autoregressive Integrated Moving Average (ARIMA), adopts dynamic peak-valley identification method to divide energy storage operation periods, designs energy storage peak regulation working interval and reserves frequency regulation capacity, and establishes a day-ahead 24 h optimization model with minimum cost as the objective to determine the basic output of each power source and the charging and discharging plan of energy storage participating in peak regulation. Stage 2 still takes the minimum cost as the objective, based on the output of each power source determined in Stage 1, adopts Monte Carlo scenario generation and improved scenario reduction technology to model wind power uncertainty. On one hand, it considers how energy storage improves wind power system inertia support to ensure the initial rate of change of frequency meets requirements. On the other hand, considering energy storage reserve capacity responding to frequency deviation, it introduces dynamic power flow theory, where wind, thermal, load, and storage resources share unbalanced power proportionally based on their frequency characteristic coefficients, establishing an intraday real-time scheduling scheme that satisfies the initial rate of change of frequency and steady-state frequency deviation constraints. The study employs improved chaotic mapping and an adaptive weight Particle Swarm Optimization (PSO) algorithm to solve the two-stage optimization model and finally takes the improved IEEE 14-node system as an example to verify the proposed scheme through simulation. Results demonstrate that the proposed method improves the system net load peak-valley difference by 35.9%, controls frequency deviation within ±0.2 Hz range, and reduces generation cost by 7.2%. The proposed optimization scheduling model has high engineering application value. Full article

This paper proposes a nonlinear model predictive control (MPC) framework initialized using an initial-guess particle swarm optimization (IG-PSO) algorithm for mobile robots navigating in environments with nonconvex obstacles. The proposed method is designed to address the local minimum problem inherent in conventional optimization-based MPC by incorporating a PSO-based global search method to generate effective initial guesses. In addition, a grid-based representation of the nonconvex obstacles is implemented to systematically define the collision avoidance constraints within the MPC formulation. The proposed method was validated in real-time simulations using the Robot Operating System (ROS) and the Gazebo physics simulator. The results demonstrate that the proposed MPC initialized by IG-PSO generates collision-free trajectories that avoid local minima and track the desired reference trajectory in environments with nonconvex obstacles. Compared with conventional IPOPT-based MPC, the proposed method exhibited improved performance in the tested scenario. The proposed method also maintains real-time control capabilities by selectively activating the IG-PSO algorithm only as required. The findings of this study demonstrate the potential of the proposed framework for robust and efficient trajectory planning in complex, nonconvex obstacle environments. Full article