Explore the vast range of titles available.

Accurate position and altitude control of quadrotor Unmanned Aerial Vehicles (UAVs) is essential for mission-critical applications such as surveillance, defense, and autonomous delivery. This study introduces an innovative control framework that integrates a Linear Quadratic Regulator (LQR) with a hybrid Grey Wolf Optimizer–Cuckoo Search (GWO–CS) algorithm for optimal gain tuning. The innovation lies in combining GWO’s global exploration with CS’s local exploitation, ensuring faster convergence and higher-quality tuning of LQR weighting matrices. A comprehensive nonlinear dynamic model of the quadrotor was developed using the Newton–Euler formalism, and the LQR–GWO–CS controller was implemented in a simulated environment. Comparative analysis reveals that the proposed controller achieves significant improvements. For the X-axis, the settling time is reduced from 4.08 s (LQR) and 7.36 s (LQR–GWO) to 1.70 s with zero overshoot, while the Integral Absolute Error (IAE) improves by approximately 39% compared to the conventional LQR. For the Y-axis, the proposed method reduced the IAE from 1.16 (LQR) to 0.70 with a settling time of 1.64 s and zero overshoot, outperforming LQR-WOA, which exhibited 4.2% overshoot. In altitude (Z-axis) control, the proposed controller limited overshoot to 2.0% while reducing settling time from 4.27 s (LQR) to 1.96 s, with lower IAE than both LQR and LQR-WOA. Robustness was further demonstrated under external disturbances and validated through real-time Hardware-in-the-Loop testing on OPAL-RT (Operational and Automation Platform for Real-Time applications), confirming feasibility for practical UAV missions. Overall, the LQR–GWO–CS framework outperforms state-of-the-art controllers, offering a quantitatively validated, robust, and efficient solution for UAV operation in dynamic and uncertain environments.

This manuscript presents the analysis and design of a fixed normalized least mean fourth (XE-NLMF) based algorithm for a single-stage, three-phase grid-integrated solar photovoltaic (SPV) system. The SPV system comprises a solar PV array, a voltage source converter (VSC), a three-phase utility, and a combination of linear and nonlinear loads. The conventional least mean fourth (LMF) algorithm is known for its lower steady-state error and enhanced stability in noisy environments. However, the proposed XE-NLMF algorithm demonstrates superior steady-state performance compared to the conventional LMF technique. In this study, an SPV array coupled with the perturb and observe (P&O) method for maximum power point tracking (MPPT) is integrated with a VSC-based converter controlled using the XE-NLMF algorithm, interfacing with a three-phase utility. The performance of the proposed VSC-based controller is evaluated in a MATLAB simulation environment under various operating conditions, including changes in solar insolation levels, load unbalancing, grid weakness, and different load combinations (linear and nonlinear). Finally, the novelty lies in the stability of the proposed controller, which is assessed by using (i) Time Domain State Space System Generation, (ii) novel pole-zero analysis technique, (iii) Stability using Impulse response from Inverse Transform , (iv) in the Z-domain by using Lypaunouv Stability analysis and by normal Zdomain analysis to realise the real time analysis by stability analysis. Moreover, the proposed controller ensures compliance with IEEE-519 standards by maintaining power quality and limiting harmonic distortions.

Necrotizing enterocolitis (NEC) is the most devastating intestinal disease affecting preterm infants. In addition to being associated with short term mortality and morbidity, survivors are left with significant long term sequelae. The cost of caring for these infants is high. Epidemiologic evidence suggests that use of antibiotics and type of feeding may cause an intestinal dysbiosis important in the pathogenesis of NEC, but the contribution of specific infectious agents is poorly understood. Fecal samples from preterm infants ≤ 32 weeks gestation were analyzed using 16S rRNA based methods at 2, 1, and 0 weeks, prior to diagnosis of NEC in 18 NEC cases and 35 controls. Environmental factors such as antibiotic usage, feeding type (human milk versus formula) and location of neonatal intensive care unit (NICU) were also evaluated. Microbiota composition differed between the three neonatal units where we observed differences in antibiotic usage. In NEC cases we observed a higher proportion of Proteobacteria (61%) two weeks and of Actinobacteria (3%) 1 week before diagnosis of NEC compared to controls (19% and 0.4%, respectively) and lower numbers of Bifidobacteria counts and Bacteroidetes proportions in the weeks before NEC diagnosis. In the first fecal samples obtained during week one of life we detected a novel signature sequence, distinct from but matching closest to Klebsiella pneumoniae, that was strongly associated with NEC development later in life. Infants who develop NEC exhibit a different pattern of microbial colonization compared to controls. Antibiotic usage correlated with these differences and combined with type of feeding likely plays a critical role in the development of NEC.

Intestinal luminal microbiota likely contribute to the etiology of necrotizing enterocolitis (NEC), a common disease in preterm infants. Microbiota development, a cascade of initial colonization events leading to the establishment of a diverse commensal microbiota, can now be studied in preterm infants using powerful molecular tools. Starting with the first stool and continuing until discharge, weekly stool specimens were collected prospectively from infants with gestational ages ≤32 completed weeks or birth weights≤1250 g. High throughput 16S rRNA sequencing was used to compare the diversity of microbiota and the prevalence of specific bacterial signatures in nine NEC infants and in nine matched controls. After removal of short and low quality reads we retained a total of 110,021 sequences. Microbiota composition differed in the matched samples collected 1 week but not <72 hours prior to NEC diagnosis. We detected a bloom (34% increase) of Proteobacteria and a decrease (32%) in Firmicutes in NEC cases between the 1 week and <72 hour samples. No significant change was identified in the controls. At both time points, molecular signatures were identified that were increased in NEC cases. One of the bacterial signatures detected more frequently in NEC cases (p<0.01) matched closest to γ-Proteobacteria. Although this sequence grouped to the well-studied Enterobacteriaceae family, it did not match any sequence in Genbank by more than 97%. Our observations suggest that abnormal patterns of microbiota and potentially a novel pathogen contribute to the etiology of NEC.

Preterm birth is the second leading cause of death in children under the age of five years worldwide, but the etiology of many cases remains enigmatic. The dogma that the fetus resides in a sterile environment is being challenged by recent findings and the question has arisen whether microbes that colonize the fetus may be related to preterm birth. It has been posited that meconium reflects the in-utero microbial environment. In this study, correlations between fetal intestinal bacteria from meconium and gestational age were examined in order to suggest underlying mechanisms that may contribute to preterm birth. Meconium from 52 infants ranging in gestational age from 23 to 41 weeks was collected, the DNA extracted, and 16S rRNA analysis performed. Resulting taxa of microbes were correlated to clinical variables and also compared to previous studies of amniotic fluid and other human microbiome niches. Increased detection of bacterial 16S rRNA in meconium of infants of <33 weeks gestational age was observed. Approximately 61·1% of reads sequenced were classified to genera that have been reported in amniotic fluid. Gestational age had the largest influence on microbial community structure (R = 0·161; p = 0·029), while mode of delivery (C-section versus vaginal delivery) had an effect as well (R = 0·100; p = 0·044). Enterobacter, Enterococcus, Lactobacillus, Photorhabdus, and Tannerella, were negatively correlated with gestational age and have been reported to incite inflammatory responses, suggesting a causative role in premature birth. This provides the first evidence to support the hypothesis that the fetal intestinal microbiome derived from swallowed amniotic fluid may be involved in the inflammatory response that leads to premature birth.

The daunting task required of the gut-barrier to prevent luminal pathogens and harmful substances from entering into the internal milieu and yet promoting digestion and absorption of nutrients requires an exquisite degree of coordination between the different architectural units of this barrier. The complex integration and execution of these functions are superbly carried out by the intestinal mucosal (IM) surface. Exposed to trillions of luminal microbes, the IM averts threats by signaling to the innate immune system, through pattern recognition receptors (PRR), to respond to the commensal bacteria by developing tolerance (hyporesponsiveness) towards them. This system also acts by protecting against pathogens by elaborating and releasing protective peptides, cytokines, chemokines, and phagocytic cells. The IM is constantly sampling luminal contents and making molecular adjustments at its frontier. This article describes the topography of the IM and the mechanisms of molecular adjustments that protect the internal milieu, and also describes the role of the microbiota in achieving this goal.

Late onset sepsis (LOS) is a major contributor to neonatal morbidity and mortality, especially in premature infants. Distortions in the establishment of normal gut microbiota, commensal microbes that colonize the digestive tract, might increase the risk of LOS via disruption of the mucosal barrier with resultant translocation of luminal contents. Correlation of distortions of the intestinal microbiota with LOS is a necessary first step to design novel microbiota-based screening approaches that might lead to early interventions to prevent LOS in high risk infants. Using a case/control design nested in a cohort study of preterm infants, we analyzed stool samples that had been prospectively collected from ten preterm infants with LOS and from 18 matched controls. A 16S rRNA based approach was utilized to compare microbiota diversity and identify specific bacterial signatures that differed in their prevalence between cases and controls. Overall α-diversity (Chao1) was lower in cases two weeks before (p<0.05) but not one week before or at the time of diagnosis of LOS. Overall microbiota structure (Unifrac) appeared distinct in cases 2 weeks and 1 week before but not at diagnosis (p<0.05). Although we detected few operational taxonomic units (OTUs) unique or enriched in cases, we found many OTUs common in controls that were lacking in cases (p<0.01). Bifidobacteria counts were lower in cases at all time points. Our results support the hypothesis that a distortion in normal microbiota composition, and not an enrichment of potential pathogens, is associated with LOS in preterm infants.

In this paper, we report a novel Fe₃O₄@MCM-41-Cystine-ZnCl₂ nanocatalyst as a highly active, recyclable, and sustainable platform for the synthesis of triarylpyridines. This catalyst integrates the benefits of a mesoporous MCM-41 support, magnetic Fe₃O₄ core, and ZnCl₂ Lewis acid centers stabilized by cystine linkers, resulting in high surface area, strong catalytic activity, and excellent stability. Under optimized conditions (100 °C, 2 h, 7 mol% catalyst) in a deep eutectic solvent (choline chloride–glycerol), twenty triarylpyridines were obtained in excellent yields (84–98%). The system exhibited broad substrate tolerance, efficiently converting electron-donating, electron-withdrawing, sterically hindered, and heteroaryl substrates with consistent turnover numbers (TON = 12.0–14.0) and turnover frequencies (TOF = 6.0–7.0 h⁻ 1 ). Compared to conventional catalysts, this method offers significantly shorter reaction times, higher yields, operation under air without oxidants, and facile magnetic recovery with reusability up to eight cycles. Thus, this approach provides a practical, eco-friendly, and scalable alternative for the synthesis of triarylpyridines, aligning efficiency with sustainability.

Metallic nanoparticles have been used to harvest energy from a light source and transfer it to adsorbed gas molecules, which results in a reduced chemical reaction temperature. However, most reported reactions, such as ethylene epoxidation, ammonia decomposition and H–D bond formation are exothermic, and only H–D bond formation has been achieved at room temperature. These reactions require low activation energies (<2 eV), which are readily attained using visible-frequency localized surface plasmons (from ~1.75 eV to ~3.1 eV). Here, we show that endothermic reactions that require higher activation energy (>3.1 eV) can be initiated at room temperature by using localized surface plasmons in the deep-UV range. As an example, by leveraging simultaneous excitation of multiple localized surface plasmon modes of Al nanoparticles by using high-energy electrons, we initiate the reduction of CO 2 to CO by carbon at room temperature. We employ an environmental transmission electron microscope to excite and characterize Al localized surface plasmon resonances, and simultaneously measure the spatial distribution of carbon gasification near the nanoparticles in a CO 2 environment. This approach opens a path towards exploring other industrially relevant chemical processes that are initiated by plasmonic fields at room temperature. Metallic nanoparticles used to harvest energy from a light source typically result in reduced chemical reaction temperature. Endothermic reactions requiring higher activation energy can now be initiated at room temperature using localized surface plasmons in the deep-UV range.

Surface and subsurface are commonly considered as separate entities because of the difference in the bonding environment and are often investigated separately due to the experimental challenges in differentiating the surface and subsurface effects. Using in-situ atomic-scale transmission electron microscopy to resolve the surface and subsurface at the same time, we show that the hydrogen–CuO surface reaction results in structural oscillations in deeper atomic layers via the cycles of ordering and disordering of oxygen vacancies in the subsurface. Together with atomistic calculations, we show that the structural oscillations in the subsurface are induced by the hydrogen oxidation-induced cyclic loss of oxygen from the oxide surface. These results demonstrate the propagation of the surface reaction dynamics into the deeper layers in inducing nonstoichiometry in the subsurface and have significant implications in modulating various chemical processes involving surface–subsurface mass transport such as heterogeneous catalysis, oxidation, corrosion and carburization. Atomically differentiating surface and subsurface is experimentally challenging. Here, the authors use in-situ electron microscopy to simultaneously monitor the surface and subsurface and show that H 2 oxidation on CuO surfaces induces cycles of ordering and disordering of oxygen vacancies in the subsurface.