Search Results (9)

This work presents a novel time-to-digital converter based on the analog sampling of dual-phase periodic signals generated from a free-running oscillator. A proof-of-concept ASIC, implemented in 130 nm CMOS technology, achieves an average single-shot precision of 0.9 ps-rms for time intervals up to 3 ns, with a best performance of 0.79 ps-rms. It maintains a precision below 3.7 ps-rms for intervals up to 25 ns. The design demonstrates excellent linearity, with a peak-to-peak differential nonlinearity of 0.56 LSB and a peak-to-peak integral nonlinearity of 1.43 LSB. The free-running oscillator is shareable across multiple channels, enabling power consumption of approximately 4.1 mW per channel and efficient area utilization. These features make the design highly suitable for detection systems requiring picosecond-level precision and high channel density, such as silicon pixel sensors, SPADs, LiDARs, and time-correlated single-photon counting systems. Furthermore, the architecture shows strong potential for use in high-count-rate applications, reaching up to 22 Mcps. Full article

The global adoption of battery electric vehicles (EVs) and hybrid electric vehicles (HEVs) as a substitute for internal combustion engine cars (ICEs) in various nations offers a substantial opportunity to reduce carbon dioxide (CO₂) emissions from land transportation. EVs are fitted with an energy conversion system that efficiently converts stored energy into propulsion, referred to as “tank-to-wheel (TTW) conversion”. Battery-electric vehicles have a significant advantage in that their exhaust system does not produce any pollutants. This hypothesis is equally relevant to public transport. Despite their higher upfront cost, electric buses contribute significantly to environmental sustainability during their operation. This study aimed to evaluate the environmental sustainability of electric buses during their operational phase by utilizing the life cycle assessment (LCA) technique. This paper used the MATLAB R2021b code to ascertain the mean load of the buses during their operation. The energy consumption of battery electric and hybrid electric buses was evaluated using the WLTP Class 2 standard, which refers to vehicles with a power-to-mass ratio between 22 and 34 W/kg, overing four speed phases (low, medium, high, extra high) with speeds up to 131.3 km/h. The code was used to calculate the energy consumption levels for the complete test cycle. The code adopts an idealized rectangular blind box model, disregarding the intricate design of contemporary buses to streamline the computational procedure. Simulating realistic test periods of 1800 s resulted in an average consumption of 1.451 kWh per km for electric buses and an average of 25.3 L per 100 km for hybrid buses. Finally, through an examination of the structure of the Hungarian power system utilization, it was demonstrated that electrification is a more appropriate method for achieving the emission reduction goals during the utilization phase. Full article

The emergence of the Coronavirus Disease 2019 (COVID-19) pandemic has brought forth various clinical manifestations and long-term complications, including a condition known as long COVID. Long COVID refers to a persistent set of symptoms that continue beyond the acute phase of the disease. This study investigated the risk factors and the utility of spiroergometry parameters for diagnosing patients with long COVID symptoms. The 146 patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with normal left ventricular ejection fraction and without respiratory diseases were included and divided into two groups: the group demonstrating long COVID symptoms [n = 44] and the group without long COVID symptoms [n = 102]. The clinical examinations, laboratory test results, echocardiography, non-invasive body mass analysis, and spiroergometry were evaluated. ClinicalTrials.gov Identifier: NCT04828629. Patients with long COVID symptoms had significantly higher age [58 (vs.) 44 years; p < 0.0001], metabolic age [53 vs. 45 years; p = 0.02)], left atrial diameter (LA) [37 vs. 35 mm; p = 0.04], left ventricular mass index (LVMI) [83 vs. 74 g/m², p = 0.04], left diastolic filling velocity (A) [69 vs. 64 cm/s, p = 0.01], the ratio of peak velocity of early diastolic transmitral flow to peak velocity of early diastolic mitral annular motion (E/E’) [7.35 vs. 6.05; p = 0.01], and a lower ratio of early to late diastolic transmitral flow velocity (E/A) [1.05 vs. 1.31; p = 0.01] compared to the control group. In cardiopulmonary exercise testing (CPET), long COVID patients presented lower forced vital capacity (FVC) [3.6 vs. 4.3 L; p < 0.0001], maximal oxygen consumption measured during incremental exercise indexed per kilogram (VO_2max) [21 vs. 23 mL/min/kg; p = 0.04], respiratory exchange ratio (RER) [1.0 vs. 1.1; p = 0.04], forced expiratory volume in one second (FEV1) [2.90 vs. 3.25 L; p = 0.04], and a higher ratio of forced expiratory volume in one second to forced vital capacity (FEV1/FVC%) [106 vs. 100%; p = 0.0002]. The laboratory results pointed out that patients with long COVID symptoms also had a lower rate of red blood cells (RBC) [4.4 vs. 4.6 × 10⁶/uL; p = 0.01]; a higher level of glucose [92 vs. 90 mg/dL; p = 0.03]; a lower glomerular filtration rate (GFR) estimate by Modification of Diet in Renal Disease (MDRD) [88 vs. 95; p = 0.03]; and a higher level of hypersensitive cardiac Troponin T (hs-cTnT) [6.1 vs. 3.9 pg/mL; p = 0.04]. On the multivariate model, only FEV1/FVC% (OR 6.27, 95% CI: 2.64–14.86; p < 0.001) independently predicted the long COVID symptoms. Using the ROC analysis, the FEV1/FVC% ≥ 103 was the most powerful predictor of spiroergometry parameters (0.67 sensitive, 0.71 specific, AUC of 0.73; p < 0.001) in predicting the symptoms of long COVID. Spiroergometry parameters are useful in diagnosing long COVID and differentiating it from cardiovascular disease. Full article

During mission design, the concept of operations (ConOps) describes how the system operates during various life cycle phases to meet stakeholder expectations. ConOps is sometimes declined in a simple evaluation of the power consumption or data generation per mode. Different operational timelines are typically developed based on expert knowledge. This approach is robust when designing an automated system or a system with a low level of autonomy. However, when studying highly autonomous systems, designers may be interested in understanding how the system would react in an operational scenario when provided with knowledge about its actions and operational environment. These considerations can help verify and validate the proposed ConOps architecture, highlight shortcomings in both physical and functional design, and help better formulate detailed requirements. Hence, this study aims to provide a framework for the simulation and validation of operational scenarios for autonomous robotic space exploration systems during the preliminary design phases. This study extends current efforts in autonomy technology for planetary systems by focusing on testing their operability and assessing their performances in different scenarios early in the design process. The framework uses Model-Based Systems Engineering (MBSE) as the knowledge base for the studied system and its operations. It then leverages a Markov Decision Process (MDP) to simulate a set of system operations in a relevant scenario. It then outputs a feasible plan with the associated variation of a set of considered resources as step functions. This method was applied to simulate the operations of a small rover exploring an unknown environment to observe and sample a set of targets. Full article

The design of a refractometric sensing system for liquids analysis with a sensor and the scheme for its intensity interrogation combined on a single photonic integrated circuit (PIC) is proposed. A racetrack microring resonator with a channel for the analyzed liquid formed on the top is used as a sensor, and another microring resonator with a lower Q-factor is utilized to detect the change in the resonant wavelength of the sensor. As a measurement result, the optical power at its drop port is detected in comparison with the sum of the powers at the through and drop ports. Simulations showed the possibility of registering a change in the analyte refractive index with a sensitivity of 110 nm per refractive index unit. The proposed scheme was analyzed with a broadband source, as well as a source based on an optoelectronic oscillator using an optical phase modulator. The second case showed the fundamental possibility of implementing an intensity interrogator on a PIC using an external typical single-mode laser as a source. Meanwhile, additional simulations demonstrated an increased system sensitivity compared to the conventional interrogation scheme with a broadband or tunable light source. The proposed approach provides the opportunity to increase the integration level of a sensing device, significantly reducing its cost, power consumption, and dimensions. Full article

This article addresses the problem of optimal phase-swapping in asymmetric distribution grids through the application of hurricane-based optimization algorithm (HOA). The exact mixed-integer nonlinear programming (MINLP) model is solved by using a master–slave optimization procedure. The master stage is entrusted with the definition of load connection at each stage by using an integer codification that ensures that, per node, only one from the possible six-load connections is assigned. In the slave stage, the load connection set provided by the master stage is applied with the backward/forward power flow method in its matricial form to determine the amount of grid power losses. The computational performance of the HOA was tested in three literature test feeders composed of 8, 25, and 37 nodes. Numerical results show the effectiveness of the proposed master–slave optimization approach when compared with the classical Chu and Beasley genetic algorithm (CBGA) and the discrete vortex search algorithm (DVSA). The reductions reached with HOA were $24.34\%$, $4.16\%$, and $19.25\%$ for the 8-, 28-, and 37-bus systems; this confirms the literature reports in the first two test feeders and improves the best current solution of the IEEE 37-bus grid. All simulations are carried out in the MATLAB programming environment. Full article

The problem of the optimal load redistribution in electrical three-phase medium-voltage grids is addressed in this research from the point of view of mixed-integer convex optimization. The mathematical formulation of the load redistribution problem is developed in terminals of the distribution node by accumulating all active and reactive power loads per phase. These loads are used to propose an objective function in terms of minimization of the average unbalanced (asymmetry) grade of the network with respect to the ideal mean consumption per-phase. The objective function is defined as the $l_1$-norm which is a convex function. As the constraints consider the binary nature of the decision variable, each node is conformed by a $3\times 3$ matrix where each row and column have to sum 1, and two equations associated with the load redistribution at each phase for each of the network nodes. Numerical results demonstrate the efficiency of the proposed mixed-integer convex model to equilibrate the power consumption per phase in regards with the ideal value in three different test feeders, which are composed of 4, 15, and 37 buses, respectively. Full article

An increase in the neutral current results in a malfunction of the low energy over current (LCO) protective relay and raises the neutral-to-ground voltage in three-phase, four-wire radial distribution feeders. Thus, the key point for mitigating its effect is to keep the current under a specific level. The most common approach for reducing the neutral current caused by the inherent imbalance of distribution feeders is to rearrange the phase connection between the distribution transformers and the load tapped-off points by using the metaheuristics algorithms. However, the primary task is to obtain the effective load data for phase rearrangement; otherwise, the outcomes would not be worthy of practical application. In this paper, the effective load data can be received from the feeder terminal unit (FTU) installed along the feeder of Taipower. The net load data consisting of customers’ power consumption and the power generation of distributed energy resources (DERs) were measured and transmitted to the feeder dispatch control center (FDCC). This paper proposes a method of establishing the equivalent full-scale net load model based on FTU data format, and the long short-term memory (LSTM) was adopted for monthly load forecasting. Furthermore, the full-scale net load model was built by the monthly per hour load data. Next, the particle swarm optimization (PSO) algorithm was applied to rearrange the phase connection of the distribution transformers with the aim of minimizing the neutral current. The outcomes of this paper are helpful for the optimal setting of the limit current of the LCO relay and to avoid its malfunction. Furthermore, the proposed method can also improve the three-phase imbalance of distribution feeders, thus reducing extra power loss and increasing the operating efficiency of three-phase induction motors. Full article

Sustainable transportation and mobility are key components and central to sustainable development. This research aims to reveal the macro-level social, economic, and environmental impacts of alternative vehicle technologies in the U.S. The studied vehicle technologies are conventional gasoline, hybrid, plug-in hybrid with four different all-electric ranges, and full battery electric vehicles (BEV). In total, 19 macro level sustainability indicators are quantified for a scenario in which electric vehicles are charged through the existing U.S. power grid with no additional infrastructure, and an extreme scenario in which electric vehicles are fully charged with solar charging stations. The analysis covers all life cycle phases from the material extraction, processing, manufacturing, and operation phases to the end-of-life phases of vehicles and batteries. Results of this analysis revealed that the manufacturing phase is the most influential phase in terms of socio-economic impacts compared to other life cycle phases, whereas operation phase is the most dominant phase in the terms of environmental impacts and some of the socio-economic impacts such as human health and economic cost of emissions. Electric vehicles have less air pollution cost and human health impacts compared to conventional gasoline vehicles. The economic cost of emissions and human health impact reduction potential can be up to 45% and 35%, respectively, if electric vehicles are charged through solar charging stations. Electric vehicles have potential to generate income for low and medium skilled workers in the U.S. In addition to quantified sustainability indicators, some sustainability metrics were developed to compare relative sustainability performance alternative passenger vehicles. BEV has the lowest greenhouse gas emissions and ecological land footprint per $ of its contribution to the U.S. GDP, and has the lowest ecological footprint per unit of its energy consumption. The only sustainability metrics that does not favor the BEV is the water-energy ratio, where the conventional gasoline vehicle performed best. Full article