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Recently, dotted-art MPPs have been proposed in which a designed pattern is made with the holes. In such a case, the MPP becomes heterogeneous in general. However, existing theories used for the prediction of the absorption characteristics of MPPs assume homogeneity. Therefore, the elaboration of a method for heterogeneous MPPs needs to be performed. In previous work, the authors proposed a method to predict the absorption characteristics of a heterogeneous MPP by using synthesized impedances of each part with different parameters; this is called the synthetic impedance method (SIM) in the present paper. The SIM can potentially be used for various heterogeneous MPPs; however, its scope of applicability needs to be clarified. Furthermore, in proposing a design concept of dotted-art heterogeneous MPPs, the condition that would make the designed MPPs fall within the scope of the SIM needs to be determined. Therefore, in this study, in order to clarify the scope of the applicability of the SIM, twelve samples are first prepared, and then measured sound absorption characteristics and predicted ones are compared and examined in terms of prediction errors. The results show that there are two conditions that should be met to produce predictable heterogeneous MPPs: (1) holes are distributed over the entire surface of the specimen, and (2) the hole spacing is constant. Considering these conditions, a design concept for a dotted-art heterogeneous MPP is proposed: two types of holes, larger holes for the pattern and smaller holes for the background, should be used to meet the above two conditions. Case studies with nine prototypes show that the SIM can make predictions for dotted-art heterogeneous MPPs fabricated according to the concept described above.

This study examines the characteristic parameters required for non-circular-hole microperforated panels (MPPs) to achieve sound absorption performance comparable to that of conventional circular-hole MPPs. Through numerical analysis, the flow resistivity and perforation ratio were found to be key parameters influencing the absorption characteristics of MPPs with square and equilateral triangular holes. The results indicate that for square-hole MPPs, matching either the flow resistivity alone or both the flow resistivity and perforation ratio to those of circular-hole MPPs leads to similar sound absorption characteristics. In contrast, for equilateral triangular-hole MPPs, both the above parameters must be matched to ensure comparable performance. Furthermore, this study explores MPPs incorporating a combination of circular and non-circular holes. It was confirmed that by appropriately matching the flow resistivity and perforation ratio, such mixed-hole MPPs can achieve sound absorption characteristics similar to those of MPPs composed solely of circular holes. These findings contribute to the broader design possibilities of MPPs, providing a foundation for optimising hole geometries in practical applications where manufacturing constraints or aesthetic considerations may necessitate non-circular hole patterns.

Partial shading conditions (PSC) in photovoltaic (PV) systems degrade energy harvest by generating multi-peak power-voltage (P–V) curves, trapping conventional maximum power point tracking (MPPT) algorithms at local maxima. This paper presents a Multi-Peak to Single-Peak Conversion (MSMPPT) framework that enables conventional algorithms like Perturb & Observe (P&O) and Incremental Conductance (INC) to reliably track the global maximum power point (GMPP) under PSC without structural modifications. The framework operates via two stages: dynamic estimation of optimal voltage boundaries to shrink the GMPP search space to under 10% of the original P–V range, and active voltage regulation to enforce operation within this zone, effectively transforming the multi-peak curve into a single-peak profile. The proposed MSMPP-P&O and MSMPP-INC algorithms achieve 50% faster tracking (64 ms vs. 122 ms for P&O) and near-perfect steady-state efficiency under static shading, reducing power losses below 2%. In dynamic shading scenarios with abrupt irradiance shifts, MSMPPT maintains robustness with less than 1.5 W net loss, outperforming conventional methods that incur over 30 W of power losses. By eliminating oscillations and hotspot risks through voltage regulation, the framework retains algorithmic simplicity while enhancing performance under complex shading scenarios. Validated across benchmark shading profiles, MSMPPT demonstrates fidelity without requiring additional hardware or complex optimizers. This innovation bridges the gap between conventional MPPT simplicity and partial shading resilience, offering a cost-effective, scalable solution to boost PV system reliability in shading environments.

Renewable energy resources are more useful when associated with the thermal power generation network because of their high accessibility in the environment, good system response, easy manufacturing, plus high scalable. So, the present research is going on solar power to reduce consumer grid dependency. The running of the PV network is quite easier, plus less human sources are involved. However, the solar modules’ power generation is nonlinear fashion. So, the collection of peak power from the sunlight-dependent systems is a highly challenging task. In this article, a Modified Differential Step Grey Wolf Optimization with Adaptive Fuzzy Logic Controller (MDSGWO with FLC) is developed for collecting the maximum power from renewable energy resources under diverse Partial Shading Conditions (PSCs). The introduced method comprehensive analysis has been done along with the other recently existing MPPT methods in terms of convergence speed, MPP tracking accuracy, operating efficiency of the introduced method, functioning duty value of the DC–DC boost power converter, dependence of MPPT on sunlight system, total number of sensing devices are needed, plus peak power extraction from the proposed system. Here, the sunlight power generation cost is more to limit this issue, a power converter is selected in the second objective to develop the voltage source capability of the PV network. The overall PV-interfaced power converter network is examined by utilizing the MATLAB environment.

In neurons, Ca2+ is essential for a variety of physiological processes that regulate gene transcription to neuronal growth and their survival. 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and 1-methyl-4-phenylpyridinium ions (MPP+) are potent neurotoxins that selectively destroys the dopaminergic (DA) neurons and mimics Parkinson’s disease (PD) like symptoms, but the mechanism as how MPP+/MPTP effects DA neuron survival is not well-understood. In the present study, we found that MPP+ treatment increased the level of reactive oxygen species (ROS) that activates and upregulates the expression and function of melastatin-like transient receptor potential (TRPM) subfamily member, melastatin-like transient receptor potential channel 2 (TRPM2). Correspondingly, TRPM2 expression was also increased in substantia nigra of MPTP-induced PD mouse model and PD patients. ROS-mediated activation of TRPM2 resulted in an increased intracellular Ca2+, which in turn promoted cell death in SH-SY5Y cells. Intracellular Ca2+ overload caused by MPP+-induced ROS also affected calpain activity, followed by increased caspase 3 activities and activation of downstream apoptotic pathway. On the other hand, quenching of H2O2 by antioxidants, resveratrol (RSV), or N-acetylcysteine (NAC) effectively blocked TRPM2-mediated Ca2+ influx, decreased intracellular Ca2+ overload, and increased cell survival. Importantly, pharmacological inhibition of TRPM2 or knockdown of TRPM2 using siRNA, but not control siRNA, showed an increased protection by preventing MPP+-induced Ca2+ increase and inhibited apoptosis. Taken together, we show here a novel role for TRPM2 expression and function in MPP+-induced dopaminergic neuronal cell death.

Mycoplasma pneumoniae (MP) is an important human pathogen that mainly affects children causing general and severe Mycoplasma pneumoniae pneumonia (G/SMPP). In the present study, a comprehensive immune response data (33 cytokines) was obtained in school-age children (3–9 years old) during MPP, aiming to analyze the immune response patterns during MPP. At acute phase, changes of cytokines were both detected in GMPP (24/33) and SMPP (23/33) groups compared to the healthy group (p < 0.05), with 20 identical cytokines. Between MPP groups, the levels of 13 cytokines (IL-2, IL-10, IL-11, IL-12, IL-20, IL-28A, IL-32, IL-35, IFN-α2, IFN-γ, IFN-β, BAFF, and TSLP) were higher and three cytokines (LIGHT, OPN and CHI3L1) were lower in the SMPP group than in the GMPP group (p < 0.05). Function analysis reveals that macrophage function (sCD163, CHI3L1) are not activated in both MPP groups; difference in regulatory patterns of T cells (IL26, IL27, OPN, LIGHT) and defective activation of B cells (BAFF) were detected in the SMPP group compared to the GMPP group. Besides, the level of osteocalcin; sIL-6Rβ and MMP-2 are both decreased in MPP groups at acute and convalescent phases compared to the healthy group, among which the levels of sIL-6Rβ and MMP-2 showed negative correlations (p < 0.1) to the application of bronchial lavage in SMPP group, indicating their roles in the development of MPP. At the convalescent phase, more cytokines recovered in GMPP (18) than SMPP (11), revealing better controlled immune response during GMPP. These results reveal different immune response patterns during GMPP and SMPP. In addition, the differentiated cytokines may serve as potential indicators of SMPP; early intervention on immune response regulations may be helpful in reducing the severity of SMPP.

As of now, all over the world is focusing on the Electric Vehicle (EV) technology because its features are low environmental pollution, less maitainence cost required, high robustness, and good dynamic response. Also, the EVs work continuously until the input fuel is provided to the fuel stack. Here, a Proton Exchange Membrane Fuel Cell (PEMFC) is used as an input source to the electric vehicle system because of its merits fast startup, and quick response. However, the PEMFC gives nonlinear voltage versus current characteristics. As a result, the extraction of maximum power from the fuel stack is very difficult. The main aim of this work is to study different Maximum Power Point Tracking Techniques (MPPT) for the DC-DC converter-fed PEMFC system. The studied MPPT controllers are Adjusted Step Value of Perturb & Observe (ASV with P&O), Adaptive Step Size with Incremental Conductance (ASS with IC), Radial Basis Functional Network (RBFN), Incremental Step-Fuzzy Logic Controller (IS with FLC), Continuous Step Variation based Particle Swarm Optimization (CSV with PSO), and Adaptive Step Value-Cuckoo Search Algorithm (ASV with CSA). The selected MPPT controllers’ comprehensive study has been in terms of maximum power extraction, tracking speed of the MPP, settling time of the fuel stack output voltage, oscillations across the MPP, and design complexity. From the comprehensive performance results of the hybrid MPPT controllers, the ASV with CSA technique gives superior performance when equated to the other MPPT controllers.

Soybean is the world’s leading source of vegetable protein and demand for its seed continues to grow. Breeders have successfully increased soybean yield, but the genetic architecture of yield and key agronomic traits is poorly understood. We developed a 40-mating soybean nested association mapping (NAM) population of 5,600 inbred lines that were characterized by single nucleotide polymorphism (SNP) markers and six agronomic traits in field trials in 22 environments. Analysis of the yield, agronomic, and SNP data revealed 23 significant marker-trait associations for yield, 19 for maturity, 15 for plant height, 17 for plant lodging, and 29 for seed mass. A higher frequency of estimated positive yield alleles was evident from elite founder parents than from exotic founders, although unique desirable alleles from the exotic group were identified, demonstrating the value of expanding the genetic base of US soybean breeding.

At present, power transmission systems are moving to renewable sources because their features are more reliable, easy to install, increase public health, and lower development costs when associated with conventional energy systems. Here, solar technology is considered because of its advantages when equated with other renewable sources are free energy production, good energy density, low air pollutants, and less maintenance requirement. In this article, a triple diode cell technology is considered for achieving the accurate voltage of the PV, and its power production is increased by proposing the Adjustable Cuckoo Search Methodology (ACSM). Here, the ACSM is studied by comparing it with the other swarm and conventional Maximum Power Point Tracking (MPPT) methodologies. The proposed MPPT controller tracks the MPP with 0.025 s time duration at 355 K. Finally, the one-switch non-isolated voltage improvement DC-DC circuit is used in the proposed system for giving the wide voltage gain to the consumer loads. The proposed ACSM-fed DC-DC converter system is investigated by utilizing the MATLAB/Simulink tool and the converter is investigated experimentally by applying the programmable power source.

R/qtl2 is an interactive software environment for mapping quantitative trait loci (QTL) in experimental populations. The R/qtl2 software expands the scope of the widely-used R/qtl software package to include multiparental populations, better handles modern high-dimensional data... R/qtl2 is an interactive software environment for mapping quantitative trait loci (QTL) in experimental populations. The R/qtl2 software expands the scope of the widely used R/qtl software package to include multiparent populations derived from more than two founder strains, such as the Collaborative Cross and Diversity Outbred mice, heterogeneous stocks, and MAGIC plant populations. R/qtl2 is designed to handle modern high-density genotyping data and high-dimensional molecular phenotypes, including gene expression and proteomics. R/qtl2 includes the ability to perform genome scans using a linear mixed model to account for population structure, and also includes features to impute SNPs based on founder strain genomes and to carry out association mapping. The R/qtl2 software provides all of the basic features needed for QTL mapping, including graphical displays and summary reports, and it can be extended through the creation of add-on packages. R/qtl2, which is free and open source software written in the R and C++ programming languages, comes with a test framework.