Improving PID Controller Performance in Nonlinear Oscillatory Automatic Generation Control Systems Using a Multi-objective Marine Predator Algorithm with Enhanced Diversity

Power systems are pivotal in providing sustainable energy across various sectors. However, optimizing their performance to meet modern demands remains a significant challenge. This paper introduces an innovative strategy to improve the optimization of PID controllers within nonlinear oscillatory Automatic Generation Control (AGC) systems, essential for the stability of power systems. Our approach aims to reduce the integrated time squared error, the integrated time absolute error, and the rate of change in deviation, facilitating faster convergence, diminished overshoot, and decreased oscillations. By incorporating the spiral model from the Whale Optimization Algorithm (WOA) into the Multi-Objective Marine Predator Algorithm (MOMPA), our method effectively broadens the diversity of solution sets and finely tunes the balance between exploration and exploitation strategies. Furthermore, the QQSMOMPA framework integrates quasi-oppositional learning and Q-learning to overcome local optima, thereby generating optimal Pareto solutions. When applied to nonlinear AGC systems featuring governor dead zones, the PID controllers optimized by QQSMOMPA not only achieve 14 reduction in the frequency settling time but also exhibit robustness against uncertainties in load disturbance inputs

Protective effect of grifolin against brain injury in an acute cerebral ischemia rat model

Purpose: To evaluate the protective effects of grifolin against brain injury in an acute cerebral ischemia rat model.Methods: Rats were assigned to five groups: control, negative control, and grifolin (50, 100, and 200 mg/kg, p.o.) treated groups, which received the drug for 2 weeks. All the animals were sacrificed at the end of the protocol, and tissue homogenates were prepared from isolated brain tissue. Glutathione peroxidase (GPX), superoxide dismutase (SOD), malondialdehyde (MDA), and nitric oxide (NO), as oxidative stress indicators, were determined for the tissue homogenates of the ischemic rats. Inflammatory mediators (cytokines and nuclear factor kappa B p65, NF κB), DNA damage, and ATP and caspase 3 levels in the tissue homogenates were also assessed.Results: Treatment with grifolin increased SOD and GPX significantly and decreased MDA and NO levels in tissue homogenates of the cerebral ischemic rats compared with those in the negative control group (p < 0.05). Treatment with grifolin also attenuated the altered levels of inflammatory mediators (cytokines and NF-κB), caspase 3, and ATP levels in the tissue homogenate of cerebral ischemic rats (p < 0.05). The results of comet assay on the tissue homogenate suggest that treatment with grifolin reduced or prevented damage.Conclusions: The results show that treatment with grifolin protects against neuronal damage in acute cerebral ischemic rats via its anti-inflammatory and anti-oxidant properties.Keywords: Neuroprotection, Cerebral ischemia, Brain injury, DNA, Grifolin, Anti oxidan

Cell separation using tilted-angle standing surface acoustic waves

Separation of cells is a critical process for studying cell properties, disease diagnostics, and therapeutics. Cell sorting by acoustic waves offers a means to separate cells on the basis of their size and physical properties in a label-free, contactless, and biocompatible manner. The separation sensitivity and efficiency of currently available acoustic-based approaches, however, are limited, thereby restricting their widespread application in research and health diagnostics. In this work, we introduce a unique configuration of tilted-angle standing surface acoustic waves (taSSAW), which are oriented at an optimally designed inclination to the flow direction in the microfluidic channel. We demonstrate that this design significantly improves the efficiency and sensitivity of acoustic separation techniques. To optimize our device design, we carried out systematic simulations of cell trajectories, matching closely with experimental results. Using numerically optimized design of taSSAW, we successfully separated 2- and 10-µm-diameter polystyrene beads with a separation efficiency of ~99%, and separated 7.3- and 9.9-µm-polystyrene beads with an efficiency of ~97%. We illustrate that taSSAW is capable of effectively separating particles–cells of approximately the same size and density but different compressibility. Finally, we demonstrate the effectiveness of the present technique for biological–biomedical applications by sorting MCF-7 human breast cancer cells from nonmalignant leukocytes, while preserving the integrity of the separated cells. The method introduced here thus offers a unique route for separating circulating tumor cells, and for label-free cell separation with potential applications in biological research, disease diagnostics, and clinical practice.National Institutes of Health (U.S.) (Grant U01HL114476)National Institutes of Health (U.S.) (New Innovator Award 1DP2OD007209-01)National Science Foundation (U.S.). Materials Research Science and Engineering Centers (Program) (Grant DMR-0820404

Single-Cell Phosphoproteomics Resolves Adaptive Signaling Dynamics and Informs Targeted Combination Therapy in Glioblastoma

Intratumoral heterogeneity of signaling networks may contribute to targeted cancer therapy resistance, including in the highly lethal brain cancer glioblastoma (GBM). We performed single-cell phosphoproteomics on a patient-derived in vivo GBM model of mTOR kinase inhibitor resistance and coupled it to an analytical approach for detecting changes in signaling coordination. Alterations in the protein signaling coordination were resolved as early as 2.5 days after treatment, anticipating drug resistance long before it was clinically manifest. Combination therapies were identified that resulted in complete and sustained tumor suppression in vivo. This approach may identify actionable alterations in signal coordination that underlie adaptive resistance, which can be suppressed through combination drug therapy, including non-obvious drug combinations

Spatiotemporal Evolution and Spatial Convergence Analysis of Total Factor Productivity of Citrus in China

In this study, the DEA–Malmquist index method was used to measure the total factor productivity of citrus in seven major mandarin-producing provinces and seven major tangerine-producing provinces in China from 2006 to 2020. Moran’s I index was used to test the spatial correlation of total factor productivity of mandarin and tangerine, and its σ convergence and β convergence characteristics were explored using coefficient of variation and spatial panel models. The results show that from the perspective of time series evolution, the growth rate of total factor productivity of mandarin and tangerine in China slowed down year by year after reaching the maximum value in 2008. Technological progress was the main factor affecting the total factor productivity of citrus. The total factor productivity growth of tangerine was more stable than that of mandarin, and the pure technical efficiency index and scale efficiency change index of mandarin and tangerine were not stable. From the perspective of regional differences, the total factor productivity of China’s main citrus-producing provinces all indicated positive growth, showing an increasing trend from east to west. The drivers of growth were mainly technological progress and scale efficiency. The regional differences in total factor productivity growth for mandarin were more obvious than for tangerine. The total factor productivity of mandarin and tangerine showed obvious spatial correlation characteristics; the positive spatial spillover effect was significant; and there were σ convergence, absolute β convergence, and conditional β convergence. Regional disparities in citrus industry development can be more objectively reflected by convergence analysis that takes spatial factors, economic and social factors, and other factors into account

An effective dimensionality reduction approach for short-term load forecasting

Accurate power load forecasting has a significant effect on a smart grid by ensuring effective supply and dispatching of power. However, electric load data generally possesses the characteristics of nonlinearity, periodicity, and seasonality. For complex electric load systems, the presence of redundant information potentially reduces the real pattern extraction for load forecasting. Bearing in mind these issues, we propose an effective forecasting model in which a feature extraction module is introduced that is combined with the variational mode decomposition (VMD) with the variational autoencoder (VAE). In this combination, VMD is utilized for decomposing complex load series and VAE is used to filter the redundant information (noises) from each decomposed series. With two real data sets from China, we demonstrate that the proposed model can achieve highly accurate predictions, as we find the mean absolute percentage error (MAPE) values for one-step-ahead prediction to be 1% (Nanjing) and 0.8% (Taixing), respectively

Data on megakaryocytes in the bone marrow of mice exposed to formaldehyde.

Previously, we reported that occupational exposure to formaldehyde (FA) exposure in factory workers reduced platelet counts, http://dx.doi.org/10.1158/1055-9965.EPI-09-0762[1], while exposure in mice increased platelet counts http://dx.doi.org/10.1371/journal.pone.0074974[2]. Bone marrow megakaryocyte (MK) numbers were also increased in exposed mice, as determined qualitatively. The data presented here are from a quantitative evaluation of MK numbers in the bone marrow histopathological slides from the previous FA exposure experiments in mice. Bone marrow slides were prepared using a single 5 μm section of femur from 2 mice randomly selected from each exposure group (n=9) treated with 0, 0.5 and 3.0 mg/m(3) FA by nose-only inhalation. MKs were systemically counted and average MK frequency was calculated as the total MK per slide divided by the number of fields evaluated. Data are presented visually as microscopy views and graphically as MK frequency

Data on megakaryocytes in the bone marrow of mice exposed to formaldehyde

Previously, we reported that occupational exposure to formaldehyde (FA) exposure in factory workers reduced platelet counts, http://dx.doi.org/10.1158/1055-9965.EPI-09-0762 [1], while exposure in mice increased platelet counts http://dx.doi.org/10.1371/journal.pone.0074974 [2]. Bone marrow megakaryocyte (MK) numbers were also increased in exposed mice, as determined qualitatively. The data presented here are from a quantitative evaluation of MK numbers in the bone marrow histopathological slides from the previous FA exposure experiments in mice. Bone marrow slides were prepared using a single 5 μm section of femur from 2 mice randomly selected from each exposure group (n=9) treated with 0, 0.5 and 3.0 mg/m3 FA by nose-only inhalation. MKs were systemically counted and average MK frequency was calculated as the total MK per slide divided by the number of fields evaluated. Data are presented visually as microscopy views and graphically as MK frequency

A hybrid robust system considering outliers for electric load series forecasting

Electric load forecasting has become crucial to the safe operation of power grids and cost reduction in the production of power. Although numerous electric load forecasting models have been proposed, most of them are still limited by poor effectiveness in the model training and a sensitivity to outliers. The limitations of current methods may lead to extra operational costs of a power system or even disrupt its power distribution and network safety. To this end, we propose a new hybrid load-forecasting model, which is based on a robust extreme-learning machine and an improved whale optimization algorithm. Specifically, Huber loss, which is insensitive to outliers, is proposed as the objective function in extreme learning machine (ELM) training. In addition, an improved whale optimization algorithm is designed for the robust ELM training, in which a cellular automaton mechanism is used to enhance the local search. To verify our improved whale optimization algorithm, some experiments were then conducted based on seven benchmark test functions. Due to the enhancement of the local search, the improved optimizer was around 7% superior to the basic. Finally, our proposed hybrid forecasting model was validated by two real electric load datasets (Nanjing and New South Wales), and the experimental results confirmed that the proposed hybrid load-forecasting model could achieve satisfying improvements in both datasets