The estimation of dynamic thermal line rating (DTLR) requires a reliable weather monitoring system to accurately capture parameters such as temperature, wind velocity, and solar radiation. This paper introduces an approach for obtaining an additional measurement, derived from the weather monitoring parameters used in DTLR estimation, to enhance the measurement redundancy of power system state estimation. This additional measurement plays a critical role in maintaining system observability, particularly in scenarios involving meter failures or missing conventional measurements. Furthermore, real-time weather data are employed to estimate the operating resistance of transmission lines, thereby improving the accuracy of the state estimation process. The proposed approach is validated in accordance with IEEE Standard 738–2012 and evaluated on the IEEE 14-bus and IEEE 118-bus test systems.
Abstract High-quality drinking water is essential for modern settlements, and accurate modeling of solute mixing at pipe junctions is crucial in water distribution networks (WDNs). While complete mixing is often assumed, recent studies emphasize the need to account for incomplete mixing. This paper advances the understanding of incomplete mixing effects on water quality dynamics in WDNs. Computational fluid dynamics (CFD) simulations are employed to examine how pipe connection angles in cross junctions influence solute mixing. The results highlight the significance of the junction angle and the relative distribution of inflow and outflow rates, whereas the diffusion coefficient and the turbulent Schmidt number have a limited influence. A generic regression model is developed to capture the nonlinear relationships between the dominant factors, providing accurate predictions of mixing at pipe junctions with minimal computational cost. The model is validated against experimental data from the literature and can be integrated into traditional WDN solvers such as EPANET. The findings improve the simulation reliability of contaminant concentration profiles, supporting more robust water quality analysis and advancing the state of the art in WDN modeling.
Widespread customer participation in modern-day Active Distribution Networks (ADNs), and co-ordinated dispatch of controllable loads based on time-of-use energy pricing leads to significant intermittencies during Demand Response (DR) events. The accuracy of conventional Distribution System State Estimation (DSSE) methodologies suffers during DR or sudden switching events of these controllable loads. Tuning the noise covariances helps in achieving better estimates considering these aforementioned events. Towards this objective, this work proposes Sage-Husa Adaptive Cubature Kalman Filter (SH-ACKF) for DSSE in the ADNs. To further reduce the computational burden in real-time, Sage-Husa adaptation is conditionally enforced over CKF on violation of Event-Trigger (ET) threshold. These events are detected using Entropy Weighted Independent Component Analysis (EW-ICA), and the results obtained in the IEEE benchmark test feeders validate the superiority of ET-SH-ACKF over SH-ACKF and CKF in terms of computational effort and estimation accuracy.
Methanol is a potential alternative fuel that reduces particulate emissions in the engine exhaust. This experimental study compared particulate matter (PM) emissions from a dual-fuelled genset engine and a baseline diesel-fuelled genset engine. In this experimental investigation, different fractions of methanol were used to displace mineral diesel on an energy basis in the dual-fuel combustion mode. The experiments were conducted using the Genset engine at a fixed speed of 1500 rpm and varying engine loads. Results showed that PM emissions were lower for dual-fuel combustion than for baseline diesel combustion. The particulate number-size distribution was higher in baseline diesel combustion. One key observation of this study was lower emissions of nanoparticles, nucleation-mode particles, and accumulation-mode particles from the dual-fuel engine compared to the baseline diesel engine. PM morphology investigations revealed that the baseline diesel engine emitted more agglomerated soot. The concentrations of trace metals in the PM were nearly similar for dual-fuel and baseline diesel combustion, which was another important observation of this study. The parametric characterisation of engine exhaust emissions showed the elimination of PM-NOx trade-off in dual-fuel mode. The maximum reductions in NOx, particulate mass, and particulate number were ∼79%, ∼62%, and ∼84%, respectively, for the methanol-diesel-fueled engine compared to baseline diesel. Soot reduction was ∼89% for the methanol-diesel-fueled engine. Soot, particulate mass, particulate number, and NOx emissions were lower from the dual-fuel engine, and methanol emerged as a superior alternative fuel for compression-ignition engines.
Genomic instability may result from a shift in the double-strand break (DSB) repair pathway from homologous recombination (HR) to error-prone non-homologous end joining (NHEJ). Normal BRCA1 expression is essential for high-fidelity HR, and its deficiency may promote error-prone NHEJ. Similarly, a low NADH/NAD+ ratio promotes low-fidelity HR, whereas a high NADH/NAD+ ratio promotes NHEJ. Further, although p53 inhibits HR, it is required for the high fidelity of this process. Furthermore, estrogen promotes NHEJ and nuclear export of p53, leading to low-fidelity HR or error-prone NHEJ. Thus, a shift in BRCA1 expression, NADH/NAD+ ratio, or a higher level of estrogen may cause genomic instability, which may initiate breast cancer. Furthermore, hypoxia may shift DSB repair from HR to NHEJ by repressing BRCA1 through dimeric CtBP, which forms under an elevated NADH/NAD+ ratio caused by hypoxia. Genomic instability caused by this shift in the DSB repair mechanism under hypoxia promotes EMT-induced breast cancer metastasis. This review discusses the roles of CtBP, BRCA1, estrogen, and metabolic shift linked to an altered NADH/NAD+ ratio in the initiation of breast cancer and EMT-mediated metastasis.
