Search Results (922)

Under California’s Clean Miles Standard (or SB 1014), transportation network companies (TNCs) must transition to zero-emission vehicles by 2030. One significant hurdle for TNC drivers is the electric vehicle (EV) acquisition and operating costs versus an internal combustion engine (ICE) vehicle. This study therefore evaluates net TNC driving earnings through EV acquisition pathways—financing, leasing, and renting—along with EV-favoring policy options. Key metrics assessed include (1) total TNC income when considering service fees, fuel costs, monthly vehicle payments, etc., and (2) the time EVs take to reach parity with their ICE counterparts. Monthly comparisons illustrate the earning differentials between new/used EVs and gas-powered vehicles. Our analyses employing TNC data from 2019 to 2020 suggest that EV leasing is optimal for short-term low-mileage drivers; EV financing is more feasible for those planning to drive for TNCs for over two years; EV rentals are only optimal for higher mileages, and they are not an economical pathway for longer-term driving. Sensitivity analyses further indicate that EV charging price discounts are effective in shortening the time for EVs to reach cost parity over ICEs. Drivers may experience a total asset gain when reselling their TNC vehicle after two to three years. Full article

The growing adoption of electric vehicles (EVs) presents new challenges for managing parking infrastructure, particularly concerning charging station utilization and user behavior patterns. This review examines the current state-of-the-art in intelligent monitoring systems for EV charging stations in parking facilities. We specifically focus on two key inefficiencies: vehicles occupying charging spots beyond the optimal fast-charging range (80% state-of-charge) and remaining connected even after reaching full capacity (100%). We analyze the theoretical and practical foundations of these systems, summarizing existing research on intelligent monitoring architectures and commercial implementations. Building on this analysis, we also propose a novel monitoring framework that integrates Internet of things (IoT) sensors, edge computing, and cloud services to enable real-time monitoring, predictive maintenance, and adaptive control. This framework addresses both the technical aspects of monitoring systems and the behavioral factors influencing charging station management. Based on a comparative analysis and simulation studies, we propose performance benchmarks and outline critical research directions requiring further experimental validation. The proposed architecture aims to offer a scalable, adaptable, and secure solution for optimizing EV charging infrastructure utilization while addressing key research gaps in the field. Full article

The management of laicity in Mexico, legally and politically, is a federal issue that involves regulating the activities of Churches and religious communities in the public space, in their practices, rituals, and relations with the organs of the state. However, in recent years, the growing presence and activity of Churches at the local level has called into question the need to observe how laicity is managed by subnational governments, both state and municipal. Are there mechanisms at the local level to regulate the presence of religion in the public space? How are religious traditions presented as culturally managed? What are the demands of Churches on local authorities and what is their political relationship with them? How is the demand for religious freedom resolved locally without violating citizens’ other freedoms, such as the freedom of conscience in issues such as education, health, traffic, and freedom of expression? All this has put into perspective whether laicity and the secular state should continue to be a national dimension or whether it is necessary to rethink legal and political forms at the local level, building new frameworks of governance and governability. This text reviews the public management of laicity in eight entities of the country, which in turn is representative of the rest of the entities with their local variations. However, they generally move in the constant dimensions of religious diversity, interreligious councils, offices, or those in charge of religious affairs, and levels of municipal participation. The construction of a new laicity is then proposed, which does not exclude religion from the public agenda but rather a new secular perspective on the participation of religious communities in public affairs. From a Latin American perspective, Mexico is seen as an effective government regime that separates religion from politics, restricting the participation of religious organizations in the public agenda. However, at the local level, this regime is changing with the inclusion of faith-based organizations in politics. This will undoubtedly lead to a change in the historical concept, a reference point in the region. The term management of laicity refers to the regulation and administration of governments (services, legal support, spaces, and dialogues) with religious communities. Management (control, regulation, permits, sanctions, and recognition) is defined by law and in public policy towards religion from the federal government, but not in local governments that lack clear regulatory frameworks, intervention guidelines, and support, hence the emphasis on the term. Full article

The hydrogen embrittlement of a typical Oil Country Tubular Good (OCTG) steel, API 5CT T95, was investigated through electrochemical hydrogen pre-charging followed by mechanical testing. J-integral and tensile tests were performed on electrochemically pre-charged samples, with varying charging conditions to simulate different hydrogen environmental exposure. Hydrogen concentration profiles during the electrochemical hydrogen charging process and subsequent mechanical testing in air were calculated with the support of hydrogen permeation tests and Finite Elements Method (FEM) mass diffusion analysis. This approach enabled a deeper understanding of the actual impact of hydrogen on the assessed mechanical properties. The results were compared with tests performed in air and with data available in the literature and were critically analyzed and discussed. A toughness reduction of up to 60% was observed under the most severe charging conditions; however, the alloy retained good ductility with a critical stress intensity factor of 124 MPa√m, well above the minimum values required for pipelines in high-pressure hydrogen gas and sour service applications, 55 MPa√m and 30 MPa√m, respectively, as specified by current ASME Standard and EFC Guidelines. Tensile tests on pre-charged specimens exhibited certain limitations due to the rapid hydrogen desorption rate with respect to the time required to conduct proper slow strain-rate tests. Full article

To reduce airport operational costs and minimize environmental pollution, an increasing number of airports are transitioning from fuel-powered to electric ground-handling vehicles. However, the limited battery capacity of electric vehicles and the need for charging make the scheduling of these vehicles more complex. To address this scheduling problem, this paper proposes an electric ground-handling vehicle scheduling algorithm that combines the MAMBA model with an attention-based neural network. The MAMBA model is designed to process multi-dimensional features such as flight information, vehicle locations, service demands, and time window constraints. Subsequently, an attention mechanism-based neural network is developed to dynamically integrate vehicle states, service records, and operational and charging constraints, in order to select the most suitable flights for electric ground-handling vehicles to service. The experiments use flight data from Xiamen Gaoqi International Airport and compare the proposed method with CPLEX solvers, existing heuristic algorithms, and custom heuristic algorithms. The results demonstrate that the proposed method not only effectively solves the electric ground-handling vehicle scheduling problem and provides high-quality solutions, but also exhibits good scalability in different parameter settings and real-time scheduling scenarios. Full article

A micro electric vehicle (micro-EV) is a small electric car with one or two seats designed for short-to-medium-distance trips. Micro-EVs produce relatively less pollution during operation and, due to their compact size, offer greater mobility in narrow areas compared to conventional transportation. These advantages have led to a continuous increase in the number of micro-EVs. However, their small battery capacity results in a limited driving range per charge, and restrictions on power and speed lead to lower driving performance. Due to these drawbacks, micro-EVs still hold a small share of the overall vehicle market. Therefore, it is necessary to evaluate the strengths of micro-EVs and analyze how they should be utilized to promote their widespread adoption. Therefore, this study analyzed the strengths of micro-EVs and identified the types of services where they can be effectively utilized to promote the use of micro-EVs as a smart mobility option. This study focused on micro-EVs used as a shared transport service, delivery service, and in public service, as part of an R&D project on micro-EVs conducted by the Ministry of Trade, Industry, and Energy. A total of 106 micro-EVs were deployed for each service type: 57 for shared transport, 13 for delivery, and 36 for public service. Each micro-EV was equipped with a GPS device, and the analysis was conducted using GPS data collected from January 2021 to October 2021. Micro-EVs with missing data due to GPS device malfunctions were excluded from the analysis. As a result, two micro-EVs from the shared transport service and one from the public service were excluded. The study compared the travel characteristics of micro-EVs across the three different service types. Additionally, a comparative analysis of the driving characteristics of micro-EVs and conventional vehicles was conducted to assess the advantages of micro-EVs over traditional vehicles. The results of the analyses showed that micro-EVs were more utilized for the delivery service type than other service types in terms of daily usage time and travel distance (3.5 h/day and 38.5 km/day, respectively), trip amounts (24.1 trips/day), and number of trips per trip chain (9.4 trips/trip chain). Moreover, micro-EVs have their strengths compared to other modes of transportation when traveling narrow roads. Analysis of the roads around the areas where micro-EVs were located showed that the micro-EVs were exposed to narrow roads with a width of under 5 m (among the total road link extensions, 57% consisted of road links with a width of less than 5 m), especially the micro-EVs used for delivery service. It is expected that the findings of this study will serve as a foundational resource for developing strategies to promote the adoption of micro electric vehicles. Full article

The pacing pulse produced by implantable stimulators can be described as a truncated exponential decay from the starting peak amplitude, corresponding to the discharge of the output stage capacitance (reservoir and isolation capacitors, in series) along the application time. Pulse decay and charge balancing have relevant implications on the ideal setting of a pacing device, as demonstrated by mathematical predictions based on well-acknowledged theoretical statements. Successful stimulation is achieved with minimum energy expense at a pulse duration shorter than the chronaxie time, which represents the upper border of the advisable duration interval. With any start amplitude, the stimulation safety margin can be improved by a duration increase beyond the chronaxie only up to an absolute limit (longest useful duration), which depends on the chronaxie and the pulse time-constant. At the longest useful duration, the threshold start amplitude is at the minimum and cannot decrease any further, though it and the corresponding pulse mean amplitude largely exceed the rheobase. The overall pacing performance is affected, in addition, by the load resistance and the electrode capacitance. Pulse amplitude decay limits the effectiveness of extended duration in implantable stimulators, making short pulses preferable whenever possible. Proper pulse settings based on actual waveform properties can prevent energy waste and reduce pacing consumption, thus prolonging the service life of the stimulator. Full article

Increasing adoption of electric vehicles (EVs) and the expansion of EV charging infrastructure present opportunities for enhancing sustainable transportation within smart cities. However, the interconnected nature of EV charging stations (EVCSs) exposes this infrastructure to various cyber threats, including false data injection, man-in-the-middle attacks, malware intrusions, and denial of service attacks. Financial attacks, such as false billing and theft of credit card information, also pose significant risks to EV users. In this work, we propose a Hyperledger Fabric-based blockchain network for EVCSs to mitigate these risks. The proposed blockchain network utilizes smart contracts to manage key processes such as authentication, charging session management, and payment verification in a secure and decentralized manner. By detecting and mitigating malicious data tampering or unauthorized access, the blockchain system enhances the resilience of EVCS networks. A comparative analysis of pre- and post-implementation of the proposed blockchain network demonstrates how it thwarts current cyberattacks in the EVCS infrastructure. Our analyses include performance metrics using the benchmark Hyperledger Caliper test, which shows the proposed solution’s low latency for real-time operations and scalability to accommodate the growth of EV infrastructure. Deployment of this blockchain-enhanced security mechanism will increase user trust and reliability in EVCS systems. Full article

Due to the large-scale use of renewable energy generation and its lack of inertia, the frequency of the grid is extremely unstable. At the same time, with the vigorous development of new energy vehicles, large-scale power batteries have huge potential for renewable energy consumption. In this context, the Vehicle-to-Grid (V2G) method is proposed. Electric vehicles are used as energy storage systems to provide frequency regulation services as flexible power grid resources. However, when electric vehicles are invested in large-scale frequency regulation, their own power battery durability will also be affected. Based on this problem, the pseudo-two-dimensions (P2D) model of the battery was established in this paper, and the effects of temperature, state of charge (SOC), reported power, and frequency regulation conditions on battery capacity attenuation and negative potential distribution were explored through experiments and simulations. Full article

In recent years, W-Cu composite systems have become very interesting subjects due to good electrical and thermal conductivity, high-temperature strength, certain plasticity, and excellent radiation resistance. W-Cu composites are a very important class of materials in applications like PFM (plasma facing materials), functional graded materials (FGM), electronic packaging materials, high-voltage electrical contacts, sweating materials, shaped charge liners, electromagnetic gun-rail materials, kinetic energy penetrators, and radiation shielding/protection. There is no possibility of forming a crystalline structure between these two materials. However, due to the unique properties these materials possess, they can be used by preparing them as a composite. Generally, W-Cu composites are prepared via the conventional powder metallurgy routes, i.e., sintering, hot pressing, hot isostatic pressing, isostatic cold pressing, sintering and infiltration, and microwave sintering. However, these processes have certain limitations, like the inability to produce bulk material, they are expensive, and their adoptability is limited. Here, in this review, we will discuss in detail the fabrication routes of additive manufacturing, and its current progress, challenges, trends, and associated properties obtained. We will also explain the challenges for the additive manufacturing of the composite. We will also compare W-Cu composites to other materials that can challenge them in terms of specific applications or service conditions. The solidification mechanism will be explained for W-Cu composites in additive manufacturing. Finally, we will conclude the progress of additive manufacturing of W-Cu composites to date and suggest future recommendations based on the current challenges in additive manufacturing. Full article

The transport sector is responsible for about 60% of emissions in the atmosphere due to the exhaust-polluting gases of internal combustion engine (ICE) vehicles. An effective solution to this issue is the electrification of the transport means, which can significantly reduce pollution, especially in urban areas. Apart from the necessary technological advancements that must improve the battery performances, the diffusion of electric vehicles (EVs) must be further supported and facilitated by new dedicated services and tools for electric vehicle users and operators aiming at improving the travel and charging experience. To this goal, this paper proposes new models based on Timed Colored Petri Nets (TCPN) to simulate and manage the charge demand of the EV fleet. At first, the proposed tool must take into account the charging requests from different EV drivers with different charging need located in different geographical areas. This is possible by knowing input data such as EV current location, battery data, charge points (CPs) availability, and compatibility. In particular, EV drivers are simulated when finding and booking the preferred charge option according to the available infrastructure in the area of interest and the CPs tariff and power rate. The proposed TCPN is designed to model the multi-user charging demand in specific geographic areas, and it is evaluated in several scenarios of a case study to measure its performance in serving multiple EV users. Full article

Background: Treatment dropout in substance use disorder (SUD) programs poses a significant challenge to achieving successful outcomes and leads to legal and financial issues. Socioeconomic factors have been identified as key contributors to treatment attrition; yet, the specific impact of patients’ socioeconomic conditions remains underexplored. The purpose of this study is to examine the relationship between socioeconomic factors and SUD treatment dropout. Methods: We conducted a retrospective analysis of socioeconomic factors associated with treatment dropout among individuals with alcohol, marijuana, and heroin substance abuse. Logistic regression was used to examine the association between patients’ socioeconomic factors and treatment dropout. Adjusted odds ratios were calculated to quantify the strength of these associations. Results: Our findings demonstrate that demographic factors and financial status, including age (12–19 years), Black or African American race, and reliance on public assistance, correlate with an increased likelihood of treatment dropout. Black or African American patients receiving public assistance exhibit elevated dropout rates in ambulatory services, while patients of other single races without private insurance show higher dropout rates in detox services. Individuals aged 18–49 who are not part of the labor force have increased dropout rates in rehab services. Interestingly, patients in dependent living situations, who pay for services through private insurance or receive them at no charge, experience lower dropout rates as the number of arrests increases. Conversely, independently living patients with prior SUD treatments have higher dropout rates compared to those undergoing treatment for the first time. Conclusions: This study underscores the critical importance of addressing financial barriers to treatment access and retention in order to improve outcomes for individuals with substance use disorders (SUDs). Targeted interventions that support economically disadvantaged populations are essential for reducing treatment dropout rates and enhancing the effectiveness of SUD treatment programs. Full article

With the advancement of intelligent power generation and consumption technologies, an increasing number of renewable energy sources (RESs), smart loads, and electric vehicles (EVs) are being integrated into smart grids. This paper proposes a coordinated frequency control strategy for hybrid power systems with RESs, smart loads, EVs, and a thermal power unit (TPU), in which EVs and the TPU participate in short-term frequency regulation (FR) jointly. All EVs provide FR auxiliary services as controllable loads; specifically, the EV aggregations operate in charging mode when participating in FR. The proposed coordinated frequency control strategy is implemented by an improved recurrent neural network (IRNN), which combines a recurrent neural network with a functional-link layer. The weights and biases of the IRNN are trained by an improved backpropagation through time (BPTT) algorithm, in which a chaotic competitive swarm optimizer (CCSO) is proposed to optimize the learning rates. Finally, the simulation results verify the superiority of the coordinated frequency control strategy. Full article

Durability is crucial for reinforced concrete, directly influencing the service life of structures. The presence of aggressive agents, especially chloride ions, significantly impacts durability. This study investigates the differences between ASTM C1202 and IBRACON/NT Build 492 standards in concrete containing various types of cement designed for a characteristic compressive strength of 40 MPa. Forty-eight cylindrical samples were prepared using eight types of Portland cement, including those with blast furnace slag, filler, and pozzolanic materials. Chloride migration tests were performed according to the ASTM C1202/2022 and IBRACON/NT Build 492/1999 methodologies. At a 95% confidence level, the results indicated that concrete made with filler-containing cement (PCII F-SR and PC II F) showed the poorest chloride resistance, with charge passing values exceeding 4000 coulombs (ASTM C1202) and diffusion coefficients above 10 × 10⁻¹² m²/s (IBRACON/NT Build 492). In contrast, concrete containing high slag cement (PC III-SR) and pozzolan cement (PC IV) demonstrated superior resistance to chloride penetration, with charge passing values below 1500 coulombs and diffusion coefficients under 5 × 10⁻¹² m²/s. Notably, discrepancies in classification were observed, as PC II Z (fly-ash based) and PC II E-SR (slag-based) received different ratings under the two methods. ASTM C1202 was found to be more stringent than NT Build 492, highlighting significant variations in the classification criteria between these standards. Based on the findings, new interval values are proposed for classifying concrete regarding the risk of chloride ion penetration, particularly for the ASTM C1202 standard, in order to better align with performance-based durability criteria and improve classification accuracy. Full article

In the current mobile edge computing (MEC) system, the user dynamics, diversity of applications, and heterogeneity of services have made cooperative service caching and task offloading decision increasingly important. Service caching and task offloading have a naturally hierarchical structure, and thus, hierarchical reinforcement learning (HRL) can be used to effectively alleviate the dimensionality curse in it. However, traditional HRL algorithms are designed for short-term missions with sparse rewards, while existing HRL algorithms proposed for MEC lack delicate a coupling structure and perform poorly. This article introduces a novel HRL-based algorithm, named hierarchical service caching and task offloading (HSCTO), to solve the problem of the cooperative optimization of service caching and task offloading in MEC. The upper layer of HSCTO makes decisions on service caching while the lower layer is in charge of task offloading strategies. The upper-layer module learns policies by directly utilizing the rewards of the lower-layer agent, and the tightly coupled design guarantees algorithm performance. Furthermore, we adopt a fixed multiple time step method in the upper layer, which eliminates the dependence on the semi-Markov decision processes (SMDPs) theory and reduces the cost of frequent service replacement. We conducted numerical evaluations and the experimental results show that HSCTO improves the overall performance by 20%, and reduces the average energy consumption by 13% compared with competitive baselines. Full article