In India, where the transport sector contributes significantly to CO2 emissions, there has been a growing shift towards electric vehicles (EVs), particularly in the three-wheeler segment. Traditional auto-rickshaws, a staple in urban transportation, are often powered by internal combustion engines, leading to pollution and high fuel consumption. Electric three-wheelers, or e-rickshaws, have emerged as a cleaner, more efficient alternative, with zero tailpipe emissions. However, the successful adoption of electric three-wheelers depends on understanding the preferences and challenges faced by auto-rickshaw drivers, who are key to the Intermediate Public Transport (IPT) system. Based on this motivation, the study contributed to the literature by analyzing stated preference survey data from 2,403 respondents who purchased electric tricycles in 2023. We provide insights into the relationship between consumer demographics (such as age, income, gender, education), Vehicle operations, Vehicle financing and Electrification perspective and their preferences for specific electric and fuel tricycle segments. Finally, we estimate consumers' preference for electric tricycles and fuel tricycles. To do this, we use a discrete choice model and estimate the impact factor of Indian consumers in purchasing electric tricycles to obtain market penetration strategies for future electric tricycles.

In the face of the burgeoning electricity demands and the imperative for sustainable development amidst rapid industrialization, this study introduces a dynamic and adaptable framework suitable for policy-makers and renewable energy experts working on integrating and optimizing renewable energy solutions. While using a case study representative model for Sub-Saharan Africa (SSA) to demonstrate the challenges and opportunities present in introducing optimization methods to bridge power supply deficits and the scalability of the model to other regions, this study presents an agile multi-criteria decision tool that pivots on four key development phases, advancing upon established methodologies and pioneering refined computational techniques, to select optimal configurations from a set of Policy Decision Making Metrics (PDM-DPS). Central to this investigation lies a rigorous comparative analysis of variants of three advanced algorithmic approaches: Swarm-Based Multi-objective Particle Swarm Optimization (MOPSO), Decomposition-Based Multi-objective Evolutionary Algorithm (MOEA/D), and Evolutionary-Based Strength Pareto Evolutionary Algorithm (SPEA2). These are applied to a grid-connected hybrid system, evaluated through a comprehensive 8760-hour simulation over a 20-year planning horizon. The evaluation is further enhanced by a set of refined Algorithm Performance Evaluation Metrics (AL-PEM) tailored to the specific constraints. The findings not only underscore the robustness and consistency of the SPEA2 variant over 15 runs of 200 generations each, which ranks first on the AL-PEM scale but also validate the strategic merit of combining multiple technologies and empowering policymakers with a versatile toolkit for informed decision-making.

The potential of metallic lithium to become the anode material for next-generation batteries is hampered by significant challenges, chief among which is dendrite growth during battery charging. These dendritic structures not only impair battery performance but also pose safety risks. Among the non-destructive analytical techniques in battery research, Magnetic Resonance Imaging (MRI) stands out as a promising tool. However, the direct imaging of lithium by 7Li MRI is hindered by its low sensitivity and spatial resolution, making its use for of dendritic growth imaging very difficult. Instead, a recently introduced indirect imaging approach based on 1H MRI of the electrolyte was used in this study. This method was used for sequential 3D imaging to monitor the charging process of lithium metal symmetric cells in three different electrical circuits: single cell, four cells in parallel, four cells in series. The measured sequential images allowed measurement of dendrite growth in each cell using volumetric analysis. The growth results confirmed the theoretical expectation that growth across cells is uneven in a parallel circuit and even in a series circuit. The methods presented in this study can be applied also to many other dendrite-related issues in batteries.

The working environment of mining electric locomotives is wet and muddy coal mine 1 roadway. There may be idling or slipping between the wheels and rails of mining electric locomotives 2 due to low friction between the wheel and rail and insufficient utilization of creep rate. Therefore, it 3 is necessary to control the creep rate within a reasonable range. In this paper, the autonomous control 4 algorithm for mining electric locomotives based on improved ε-greedy is theoretically proven to be 5 convergent and effective firstly. Secondly, after analyzing the contact state between the wheel and rail 6 under wet and slippery road conditions, it was concluded that the value of creep rate is an important 7 factor affecting the autonomous driving of mining electric locomotives. Therefore, the autonomous 8 control method for mining electric locomotives based on creep control is proposed in this paper. 9 Finally, the effectiveness of the proposed method was verified through simulation. The problem of 10 wheel slipping and idling caused by insufficient friction of mining electric locomotives in coal mining 11 environments is effectively suppressed. Autonomous operation of vehicles with optimal driving 12 efficiency can be achieved through quantitative control and utilization of the creep rate between 13 wheels and rails

A hypothesis that the generally accepted value of the LiPON conductivity should be attributed to the absorption and displacement currents is substantiated. The reason is a small contribution of the drift current due to field screening by the electric double layer. The basis for this assumption is the measurement of the LiPON absorption capacitance, according to which its dielectric constant is about 106. An alternative equivalent circuit containing a non-ideal absorption element is proposed and its impedance is calculated. It is shown that the Bode diagrams of the alternative circuit well approximate the experimental curves. Parameters and the magnitude of electric field screening are calculated basing on proposed model of a double electric layer. Considering the screening effect, the drift conductivity of LiPON is obtained, which value is in good agreement with the data on lithium concentration and mobility.

This article explores the cutting-edge advancement of gypsum and cement building boards infused with shape-stabilized n-octadecane, an organic phase change material (PCM). The primary focus is on improving energy efficiency and providing electromagnetic interference (EMI) shielding capabilities for contemporary buildings. The research investigates the integration of these materials into construction materials, using red-mud Carbon Foam as a stabilizer for n-octadecane (OD@CCF). Various analyses, including microstructural examination, porosity assessment, and additive dispersion, were conducted using X-ray microtomography and density measurements. Thermal conductivity measurements demonstrated the enhancement of composite boards as the OD@CCF content increased, while mechanical tests indicated an optimal additive content of up to 20%. The thermal-regulated capabilities of these advanced panels were evaluated in a custom-designed room model equipped with a homemade environmental chamber, illustrating a consistent temperature environment during heating and cooling cycles. The incorporation of OD@CCF into cement boards exhibited improved thermal energy storage properties. Moreover, the examined composite boards displayed efficient electromagnetic shielding performance within the frequency range of 3.2–7.0 GHz, achieving EMI values of approximately 18 and 19.5 dB for gypsum and cement boards, respectively, meeting the entry-level value required for commercial applications.

The article studies and analyzes a hybrid power source system, lithium battery, and fuel cell assisted by flexible photovoltaic panels for hybrid electric vehicles (HEVs). The new configuration operates based on optimizing the performance of the dual power source to maximize the available energy and operating time. The operational mode simulates specific driving conditions in urban, peripheral, and intercity routes under variable driving patterns and traffic conditions. The simulation results show that the new configuration increases the hybrid electric vehicle performance, providing higher reliability despite the more complex design. The proposed system reduces the external power supply dependence and avoids unexpected sudden stops due to energy exhaustion. The new configuration also extends the vehicle driving range depending on driving mode and route conditions. The vehicle driving range extension may reach up to 276.3 km. The hybridization of fuel cells with lithium battery and PV panel assistance enhances battery management, reducing battery servicing and increasing lifespan. The proposed topology is cheaper than a single fuel cell power system by 17.2%, reducing the total cost related to the single battery power system if we consider the battery recharge for its entire lifespan. The cost saving is 2.6% for the American market and 14.8% for the European one.

The results shown in this paper extend our research group's previous work, which presents the theoretically achievable hydrogen engine-out NOx (H2-NOx) Pareto front of a hydrogen hybrid electric vehicle (H2-HEV). While the Pareto front is calculated offline, which requires significant computing power and time, this work presents an online-capable algorithm to tackle the energy management of a H2-HEV with explicit consideration of the H2-NOx trade-off. Through the inclusion of realistic predictive data on the upcoming driving mission, a model predictive control algorithm (MPC) is utilized to effectively tackle the conflicting goal of achieving low hydrogen consumption while simultaneously minimizing the NOx. In a case study it is shown that the MPC is able to satisfy user-defined NOx limits over the course of various driving missions. Moreover, a comparison to the optimal Pareto front highlights the MPC's ability to achieve close-to-optimal fuel-performance for any desired cumulated NOx target on four realistic routes for passenger cars.

The work aims to improve the battery performance in hybrid electric vehicles (HEVs) by reducing the vehicle speed. We develop a specific protocol for managing battery use and optimizing the energy consumption rate to achieve this goal. The protocol automatically controls the driving operation, avoiding incompatible driving patterns with energy-saving mode and performance improvement. The protocol is submitted to a simulation process to predict the energy rate lowering and battery performance enhancement. The proposed protocol applies to any hybrid electric vehicle type and route conditions since it uses vehicle mass, drag and rolling coefficients, and road slope as variable parameters to determine the minimum energy consumption rate. We run experimental tests to validate the simulation data and the proposed protocol. Furthermore, the protocol applies to variable starting vehicle speeds, from 10 to 50 km/h, corresponding to the current driving patterns, sport, normal, and eco, set up by car manufacturers. A reduction of 10% in vehicle speed in urban and peripheral routes achieves a minimum energy rate, enhancing battery management. Current vehicle speed shows a deviation from optimum management of 18% while applying the vehicle speed reduction limits the deviation to 0.2%. Experimental results show a good agreement with simulation data with 94% accuracy. We tested the protocol for urban and peripheral routes with maximum vehicle speed limits of 60 and 90 km/h.

Non-Small Cell Lung Cancer (NSCLC) is the most common pulmonary malignancy, most frequently diagnosed at an advanced stage (III/IV). Patients in the Locally-Advanced Stage Subgroup (IIIA) are relatively few, yet compose of heterogenic phenotypes posing a diagnostic and treating challenge, leading to lack of clinical guidelines regarding the optimal standard of care. Several approaches exist, with a general agreement that a combined oncological and surgical modality approach is required. In this current retrospective descriptive study, operable Stage IIIA NSCLC patients who underwent surgery between 2013-2020 were evaluated on several aspects, including initial diagnosis, neoadjuvant regimens, outcomes of surgical intervention, overall survival at 2-years and 5-years following treatment. A total of 35 patients had neoadjuvant oncological treatment (mostly chemoradiation therapy) prior to surgery, out of which 28 patients were diagnosed with Stage IIIA NSCLC. In post-operative assessment of pathological staging, downstaging was reported in 20 patients, of which 7 (25%) cases were defined as complete pathological response. The 2-years overall survival rate was 65% and the 5-years overall survival rate was 60%. The main pattern of disease recurrence was distant metastasis.

The development of accurate dynamic battery pack models for electric vehicles (EVs) is critical for the ongoing electrification of the global automotive vehicle fleet, since these serve as a key element in the energy performance of an EV powertrain system. The Equivalent Circuit Model (ECM) technique at the cell level is commonly employed for this purpose, combining accuracy and efficiency in the representation of battery operation within the broader powertrain system. In this study, a second-order ECM model of a battery cell is being developed using Modelica, an equation-based modeling language. Parameter lookup tables at multiple levels of state of charge (SoC), extracted from Li-ion battery cells with 4 different commonly used cathode materials, have been utilized. This approach allows for a representation of the battery systems that are used in a wide range of commercial EV applications. To verify the model, an integrated EV model is developed and simulation results of the FTP75 driving cycle have been compared against an equivalent application in MATLAB Simulink. The findings demonstrate a close match between the results obtained from both software across different system points. Specifically, the maximum deviation of SoC is limited to 0.08% and the maximum value of relative voltage deviation is 1.4%. The verified model enables the exploration of multiple possible architecture configurations of EV powertrains with Modelica.

Today, there are commercially available high-performance electric wheelchairs, capa-ble of responding to strong limitations. However, despite these advancements, there is a significant portion of the population with severe disabilities who cannot access this mobility solution due to safety reasons. Indeed, either due to motor issues preventing reliable control of the wheelchair's commands, or associated visual or cognitive pathologies, the use of an electric wheelchair by these individuals would put them at risk and could also constitute a danger to those around them. This is why our research team is working on the development of augmented wheelchairs that allow a greater autonomy. We are mainly developing a system compatible with all electric wheel-chairs on the market, capable of making them anti-collision and anti-fall on uneven ground (sidewalks, stairs, etc.). In this article, we present our solution regarding the anti-collision function, in particular the sensors used to do this, as well as the strategy. We will focus on the shortcomings and weaknesses of various types of sensors and demonstrate how, by combining them in a certain way, we can develop a collision avoidance device capable of managing the diversity of everyday life situations. The two types of sensors that will be combined here are an in-house developed special near infrared sensor from the laboratory and a commercially available ultrasonic sensor. We will present the internal operation of the sensors, their limitations, experimental tests involving integration with the wheelchair, and the structure of the complete device.

The methods of Artificial Intelligence (AI) have been used in the planning and operation of power systems for more than 40 years. In recent years, due to the development of microprocessor and data storage technologies, the effectiveness of this use has greatly increased. This paper provides a systematic overview of the application of AI including the use of Machine Learning (ML) to the power system. The potential application areas are divided into four blocks and the classification matrix has been used for clustering the AI application tasks. Furthermore, the data acquisition methods for setting the parameters of AI and ML algorithms are presented and discussed in a systematic way considering the supervised and unsupervised learning methods. Based on this, three complex application examples: wind power generation forecasting, smart grid security as-sessment (using two methods), and automatic system fault detection are presented and discussed in detail. Summary and outlook conclude the paper.

The state-of-the-art smart city has been calling for an economic but efficient energy management over large-scale network, especially for the electric power system. It is a critical issue to monitor, analyze and control electric loads of all users in system. In this paper, we employ the popular computer vision techniques of AI to design a non-intrusive load monitoring method for smart electric energy management. First of all, we utilize both signal transforms (including wavelet transform and discrete Fourier transform) and Gramian Angular Field (GAF) methods to map one-dimensional current signals onto two-dimensional color feature images. Second, we propose to recognize all electric loads from color feature images using a deep neural network with multi-scale feature extraction and attention mechanism. Third, we design our method as a cloud-based, non-intrusive monitoring of all users, thereby saving energy cost during electric power system control. Experimental results on both public and our private datasets have demonstrated our method achieves superior performances than its peers, and thus supports efficient energy management over large-scale Internet of Things.

Unmanned vehicles (UVs) have become increasingly important in various scenarios of civil and military operations. The present work aims at the conceptual design of a modular Amphibious Unmanned Ground Vehicle (A-UGV), that can be easily adapted for different types of land and/or water missions, with low monetary cost (<5k€, without sensors). Basing the design on the needs highlighted in the 2021 review of the Strategic Directive of the Portuguese Navy, the necessary specifications and requirements are established for two mission scenarios. Then a market research analysis focused on vehicles currently available, and their technological advances, is conducted to identify existing UVs solutions and respective characteristics/capabilities of interest to the current work. To study and define the geometry of the hull and the configuration of the A-UGV itself, preliminary computational structural and fluid analyses are carried out to ensure it complies with the specifications initially established. As a result, one obtains a fully electric vehicle, with approximate dimensions of 1050×670×450mm (length-width-height), enabled with 6×6 traction capable of reaching 20km/h in land, possesses amphibious capabilities of independent propulsion in water up to 8kts, and with an estimated autonomy of over 60 minutes.

This paper introduces an innovative energy circuit that challenges conventional understandings of energy conservation, marking a significant departure from traditional frameworks. Seeking to enhance energy generation within existing paradigms, this innovation holds promise for addressing pressing global issues such as the energy crisis and environmental sustainability, while also stimulating scientific inquiry. In contrast to prevalent misconceptions rooted in philosophical and scientific constraints, this study refutes the notion of generating energy from nothing and questions the viability of perpetual motion machines as conceptual models. Instead, it proposes a novel circuit design derived from an unconventional electrical short circuit, which is shown to disrupt the established principles of energy conservation. This circuit offers a transformative approach with diverse applications, including self-recharging capabilities for electric vehicles, bolstering microgrid infrastructure, and facilitating the integration of renewable energy sources. Transcending conventional scientific boundaries, this paper prompts philosophical reflections on the evolving nature of scientific exploration. Ultimately, the energy circuit represents a pivotal step towards mitigating the global energy crisis by reducing reliance on finite resources and fostering sustainability. The paper concludes by illustrating the circuit's potential to revolutionize energy systems and contribute to a more resilient and sustainable future.

Introduction: Identifying the complexity of palliative care needs is a key aspect of referral to specialised multidisciplinary early palliative care (EPC) teams. The PALCOM scale is an instrument consisting of five multidimensional assessment domains, developed in 2018 and validated in 2023, to identify the level of complexity in patients with advanced cancer. Objectives: The main objective of this study was to determine the degree of instability (likelihood of level change or death), health resource consumption and survival of patients according to the level of palliative complexity assigned at the baseline visit during a 6-month follow-up. Method: An observational, prospective, multicentre study was conducted using pooled data from the development and validation cohort of the PALCOM scale. The main outcome variables were: a) instability ratio (IR), defined as the probability of level change or death; b) emergency department visits; c) days of hospitalisation; d) hospital death; e) survival. All variables were analysed monthly according to the level of complexity assigned at the baseline visit. Results: A total of 607 patients with advanced cancer were enrolled. According to the PALCOM scale, 20% of patients were classified as low complexity, 50% as medium and 30% as high complexity. The overall IR was 45% in the low complexity group, 68% in the medium complexity group and 78% in the high complexity group (p

Cardiomyopathies (CMPs) are a group of myocardial disorders that are characterized by structural and functional abnormalities of the heart muscle. These abnormalities occur in the absence of coronary artery disease (CAD), hypertension, valvular disease, and congenital heart disease. CMPs are an increasingly important topic in the field of cardiovascular diseases due to the complexity of their diagnosis and management. In 2023, the ESC guidelines on cardiomyopathies were first published, marking significant progress in the field. The growth of techniques such as cardiac magnetic resonance imaging (CMR) and genetics has been fueled by the development of multimodal imaging approaches. For the diagnosis of CMPs, a multimodal imaging approach, including CMR, is recommended. CMR has become the standard for non-invasive analysis of cardiac morphology and myocardial function. This document provides an overview of the role of CMR in CMPs, with a focus on tissue mapping. CMR enables the characterization of myocardial tissues and the assessment of cardiac functions. CMR sequences and techniques, such as late gadolinium enhancement (LGE) and parametric mapping, provide detailed information on tissue composition, fibrosis, edema, and myocardial perfusion. These techniques offer valuable insights for early diagnosis, prognostic evaluation, and therapeutic guidance of CMPs. The use of quantitative CMR markers enables personalized treatment plans, improving overall patient outcomes. This review aims to serve as a guide for the use of these new tools in clinical practice.

Background: Locally advanced rectal cancers (10-20%) can present with infiltration into adjacent viscera. R0 resections remain the key factor for better survival. Traditionally these cases have been managed with open surgery. There are some limitations of laparoscopic surgery in these case, which can potentially be overcome by robotic surgery. Objectives: To determine the feasibility and outcome results of robotic multi-visceral resection of stage T4 rectal carcinoma. Methods: Consecutive patients having locally advanced carcinoma of rectum, who undergone robotic multi-visceral resection as the primary treatment between 2015 -2018 were included, through our database which was maintained prospectively. All perioperative and intraoperative parameters were analyzed. Patient demographics, co-morbidities, preoperative imaging, endoscopic findings, operative data, histopathology results, postoperative hospital course and procedure related postoperative adverse events were noted and analyzed. Results: Twenty-one patients with the diagnosis of nonmetastatic locally advanced rectal cancers were operated with Robotic Si/X platform. The median body mass index was 28.5 kg/m2 (range 21-42). The mean blood loss during operation was 20 ml (range 5-200), and the mean duration of surgery was 280 min (range 240-430). The median hospital stay after operation was 6 days (range 4-25 days). On postoperative histopathology, R0 resection rate was 90.5% (19/21). Conclusions: The robotic multi-visceral en-bloc resection of stage T4 rectal carcinoma is technically feasible and oncologically safe. Advanced technical skills, accurate radiological staging and careful patient selection can allow the extension of minimal access surgery to this challenging group of patients.

: Considering that Einstein's relation between the diffusion coefficient and the drift mobility of the free randomly moving charge carriers in homogeneous materials including metals is always valid, it is shown that the effective electric force acting on free electrons in metal depends on the ratio between the kinetic free electron energy at the Fermi surface to the classical particle energy 3kT/2. The electrical resistivity of elemental metals dependence on very low temperatures has the quadratic term, which has been explained by electron-electron scattering. In this paper, it is shown that the quadratic term of the electrical resistivity at low temperatures is caused by scattering of the free RM electrons by electronic defects due to linear effective free electron scattering cross-section dependence on temperature, but not by electron-electron scattering.

In this case series, we examine the impact of the Titan-iR Pro® deep spectrum biotherapeutic device on brain function in healthy individuals. Here we present 15 participants, aged 26-68 years, who enrolled in this open-label study, designed to assess the effect of a single 15-minute course of deep spectrum biotherapy on brain function. Although symptom-free upon enrollment, participants had diverse medical histories with some displaying early signs of cognitive decline. As part of the evaluation, all participants engaged in electroencephalogram (EEG) recording sessions that focused on assessing event-related potential (ERP) evaluations, including audio P300 amplitudes and latencies (speeds), neurocognitive testing, and physical reaction times. Following the Titan-iR Pro intervention an improvement in EEG-based cognitive markers was observed. These results underscore the importance of further investigation into the potential of advanced and deep spectrum photobiomodulation in the prevention and treatment of cognitive decline and other neurological disorders.

A self-propelled electric tea seed-planter is designed to address the lack of tea seed seeding equipment, low seeding efficiency, and poor seeding uniformity. Based on the physical characteristics of the tea seeds and the agronomic requirements of tea planting, the key structure of the planter is designed, and the structural parameters are determined. The motor and battery configurations are determined by calculating the power consumption of the entire machine. In a field experiment, the driving gear (A), ditching depth (B), and planting gear position (C) are used as test factors, and the acceptance index (AI), replay index (RI) and leakage index (LI) are used as test indexes. The test results showed that the driving speed and planting gear position significantly affect the acceptance index, replay, and leakage index, whereas the ditching depth has little effect on the performance indexes. When the driving speed was medium, ditching depth was 30 mm, and planting gear position was in the third gear, the corresponding acceptance index was 87.22%, the replay index was 8.89%, and the leakage index was 3.89%. The test prototype has a good working quality and can provide theoretical guidance for production practices.

Vision impairment may delay responses to hazards when driving. In a proof-of-concept driving simulator study, we evaluated a hazard warning device designed for vision impaired drivers. Three groups participated: 11 persons with central vision loss (CVL; median age 60 years), 12 with homonymous field loss (HFL; 52 years) and 11 with normal vision (NV; 60 years). CVL is characterised by impaired visual acuity and contrast sensitivity while HFL is a loss of vision in the same half of the visual field (blind side) in both eyes. Participants completed drives with and without the device which gave a directional vibro-tactile warning for an approaching pedestrian hazard when collision risk exceeded a pre-defined threshold. Warnings significantly (p< 0.001) reduced brake response times for CVL (∆= 0.54s) and HFL (∆= 0.30s), but not NV participants. For HFL participants, the reduction was greater (p = 0.02) for hazards on the blind (∆= 0.57s) than seeing side (∆= 0.10s). The warnings significantly reduced collision rates for CVL participants from 11 to 0% (all hazards) and for HFL participants from 30 to 1.7% (blind side hazards). Thus, hazard warnings may be beneficial in improving safety of vision impaired drivers; further research is warranted.

To satisfy the interests of multiple agents and those of comprehensive indicators such as peak-to-valley differences and load fluctuations occurring on the network side, this paper presents a flexible load demand-side response optimization method that considers the benefits of peak-to-valley smoothing. First, load aggregation modelling of air conditioning and electric vehicles was conducted, and the complementarity of the power consumption behaviour of different types of flexible loads was used to improve the responsiveness of the load aggregator. Second, considering demand-side responses and taking into account the interests of both supply and demand, the load fluctuation and peak-to-valley difference on the network side are reduced, and a flexible load double-layer optimization model incorporating the peak-to-valley smoothing benefit is established. Finally, the effectiveness of the proposed optimization model is verified by using the KKT condition and the big M method to evaluate this two-layer optimization problem as a single-layer optimization problem. Comparative examples demonstrate that the proposed two-layer optimization method can improve the revenue of the distribution network operators and the load aggregators by using the complementary nature of the load response characteristics of electric vehicles and air conditioners. Moreover, the proposed method can effectively reduce the load peak-to-valley difference and load fluctuation of the distribution network by introducing the peak-to-valley smoothing benefit model.

This comprehensive review traces the transformative journey of genomic mapping, ushering in the era of "Genomic Atlas 2.0," characterized by advanced strategies and cutting-edge technologies. Beginning with a historical overview, it highlights the evolution from early linkage analysis to the current landscape shaped by high-throughput sequencing. Key breakthroughs are emphasized, showcasing the pivotal role of platforms such as Illumina and Oxford Nanopore in accelerating the identification of genetic variations. Long-read sequencing technologies, including PacBio and Oxford Nanopore, are explored as transformative elements overcoming limitations associated with short-read sequencing. The review delves into spatial genomics and chromatin conformation capture techniques, revealing the three-dimensional intricacies of the genome, with a particular focus on the revolutionary impact of Hi-C in understanding chromatin interactions. CRISPR technologies emerge as indispensable tools in Genomic Atlas 2.0, enabling targeted genome editing and the generation of precise genetic models. Functional genomics screens, utilizing RNA interference and CRISPR-based techniques, are discussed for their scalable precision in deciphering genome functions. Navigating challenges, the review addresses complexities in data integration and ethical considerations, offering strategies to ensure the robustness and ethical conduct of genetic mapping. Looking optimistically towards the future, it explores opportunities such as improved sequencing accuracy and novel applications of CRISPR technologies. Envisioning the expansion of genomics into personalized medicine, agriculture, and conservation biology, the review serves as a guiding resource for researchers, scientists, and students navigating the intricate terrain of Genomic Atlas 2.0.

Ensuring precise electric locomotive stopping is pivotal for achieving intelligent and unmanned auxiliary transportation systems. Currently, human drivers' expertise plays a central role in the stopping process, posing challenges for automation and cargo location accuracy, particularly in coal mining. This paper focuses on achieving accurate electric locomotive stopping under diverse conditions by utilizing permanent magnet synchronous motor-driven locomotives. This technique introduces a novel stopping control method that combines a fuzzy Proportional-Integral-Derivative (F-PID) controller and a vector control model for permanent magnet synchronous motors (PMSM). After this, we design the F-PID using the PMSM technique based on the new fuzzy rules for each sub-system. In the end, extensive simulations and real-world experiments are conducted on an electric locomotive stopping test bed, which demonstrate the effectiveness of the proposed control method. From the simulation results, it confirming that the ability to achieve precise stopping under various working conditions.

Cellular Technology came into existence in Japan in 1979. From that time, we have seen many advances in technology. Currently, most of the person uses either 4G or 5G, among which 5G is a newer technology. 4G network was the first network to use LTE. LTE stands for Long Term Evaluation. Most people get confused between 4G and LTE, they assume both to be the same. In reality, LTE has evolved on the 4G technology. It was first introduced in 2008 to provide higher efficiency and data rates to the cellular network. It was designed to evolve the performance of the networks which includes the evolution of hardware components, optimization of software, power and cost efficiency. This work presents a study on LTE, LTE-A and VoLTE technology. We also discussed about the several packet scheduling algorithms that are being used for transmission of packets. It brings out new opportunities for the researchers to work on increasing the efficiency of those algorithms by modifications.

Predictions of mean values of statistical variables of large scale turbulent flow by the widely used basic k-ϵ model and a new fundamentally based model are verified against published results of Direct Numerical Simulations DNS of the Navier-Stokes equations. The verification concerns turbulent channel flow at shear Reynolds numbers of 950, 2000 and 104. The basic k-ϵ model is largely based on empirical formulations accompanied by calibration constants. This contrasts with the new model where descriptions of leading statistical quantities are based on the general principles of statistical turbulence at large Reynolds number. Predicted values of major output variables such as turbulent viscosity, diffusivity of passive admixture, temperature, and fluid velocities compare well with DNS in case of the new model. Significant differences are seen in case of the basic k-ϵ model.

Advanced glycation end products (AGEs) play a significant role in the aging processes, further regarding as a hallmark of aging. Despite the importance, a lack of monitoring tools has hampered the study of relationship between AGEs and aging. Here, we firstly report a novel AGEs-selective probe, AGO. AGO presented its ability to detect AGEs more sensitively than a conventional approach of measuring autofluorescence from AGEs. In addition, we confirmed that AGO can detect AGEs depending on kinetics, reflecting by a preference to ribose-derived AGEs. Finally, AGO revealed its competence to visualize glycation products in glycation mimicking model, made by collagen framework. We believe that this study will enrich molecular toolboxes to understand physiological processes of AGEs during aging processes.

Electric torque wrenches play a crucial role in the assembly of high-strength bolts. This study focuses on three assembly processes for high-strength bolts and introduces a statistical analysis method to assess the quality of the bolt assembly. To enhance the performance, a novel, fully digital, Internet of Things (IoT) electric torque wrench is designed, incorporating a smart meter chip. This wrench achieves integration between the current sensor control method and the torque sensor control method using a simplified hardware circuit, ensuring high precision and stability. Additionally, this study employs the AC voltage self-stabilization method and Savitzky–Golay filtering method to enhance the accuracy and robustness of the wrench. Simulation experiments using Simulink and Matlab validate the effectiveness of these two methods. Furthermore, a cloud platform is utilized to enable rapid IoT access for the wrench, facilitating seamless connectivity and data transmission.

Background and Objectives: In recent years Electronic scooters (E-Scooters) have gained popularity, whether for private use or as a publicly available transportation method. With introduction of these vehicles, reports of E-Scooter related accidents have surged, sparking a public debate and concern. Aim of this study was to analyse epidemiological data, characteristics and severity of traumatic brain injury (TBI) related to E-Scooter accidents. Materials and Methods: This retrospective case series evaluated 28 patients who were admitted to three largest neurosurgery clinics in Riga, Latvia between time period from April to October in two separate years – 2022 and 2023 after an E-Scooter related accident. Data were collected on patient demographics, time of the accident, alcohol consumption, helmet use, type of TBI, other related injuries, treatment and assessment at discharge. Results: A total of 28 patients were admitted with TBI related to E-Scooter use, with median age 30 years (Q1-Q3, 20.25-37.25), four individuals under age of 18, majority (64%) were male. In 23 cases the injury mechanism was fall, in 5 cases collision. None were wearing a helmet at time of injury. Alcohol intoxication was evident in over half of the patients (51.5%), with severe intoxication (&gt;1.2ppm) in 75% cases among them. Neurological symptoms upon admission were noted in 50% of cases. All patients had intracranial trauma - 50% brain contusions, 43% traumatic subdural hematoma, almost 30% - epidural hematoma. Craniofacial fractures were evident in 71% of cases, fractures in other parts of body in 3 patients. 6 patients required emergency neurosurgical intervention. Neurological complications were noted in 2 patients, 1 patient died. Conclusions: E-Scooter related accidents result in a significant number of brain and other associated injuries, with notable frequency linked to alcohol influence and lack of helmet use. Prevention campaigns to raise awareness of potential risks and implementation of more strict regulations should be done.

Among natural disasters, earthquakes have a considerable impact and are among the ten deadliest, with an extreme impact on the healthcare sector. This study aimed to analyze best practices in nursing care for earthquake victims. An in-depth analysis was carried out by using a scoping review, a method used in accordance with the PRISMA-ScR recommendations to identify best nursing practice in these circumstances based on searches of eight databases: MEDLINE via PubMed; Cochrane Library; Embase; VHL; PDQ-Evidence; Scopus; ProQuest; Google Scholar. Twenty-one studies were selected. The nursing practices identified were grouped into two distinct dimensions, each subdivided into four subcategories: (i) care practices: a) immediate care, b) intermediate care, psychosocial care and d) ethical care; (ii) care management and coordination practices, which cover (a) care coordination, (b) victim care network organization, (c) teamwork and (d) training. By analyzing these nursing practices during care and relief operations for earthquake victims, this study identified the various actions carried out, the nursing skills to be developed and the reinforcement of these advanced practices through the systematization of nurses’ skills, in order to promote victims’ rehabilitation, minimize their suffering and improving their quality of life during and after an earthquake.

We explore 3D printing modules for self-assembling spacecraft and robots – structure, actuators, electrics. Self-assembly has long been viewed as a highly desirable capability for autonomous construction of large space structures. We review self-assembly in space which focusses on the self-assembly of modules that demonstrate the range of applications. However, self-assembly may be synergised with 3D printing to offer an automated capability from raw material to modules for assembling new spacecraft or habitats. One application of 3D printing is using space debris on-orbit as an in-situ resource - defunct spacecraft may be salvaged as raw material for in-situ construction on demand. The common features of all self-assembling modules are that the modules constitute a structure housing a computer-controlled actuator internally and a reversible latching mechanism externally. We have demonstrated a 3D printed DC electric motor in which the only components that were not 3D printed are the wire coils. We have married our 3D printed motor prototype as an actuated joint between two 3D printed trigon-type panels developed as part of a trigon self-assembling system concept. The trigon concept underlies a modular approach to self-assembling and self-deploying structures. The 3D printed motorised panel system demonstrates that the motor aspect and structural aspects of robotic self-assembling machines are amenable to 3D printing. This has implications for self-assembling systems into modular satellites as a solution to space debris.

The goal of the study presented in this article is to investigate interconnection issues of the Intelligent Electrical Networks (IENs) with the existing ones, as well as the deployment of the appropriate load forecasting demand techniques. The concept of IENs has recently emerged as a potential solution to the global energy problem, due to the more flexible dispersed production units that are involved. In the same context, additional issues, such as the reduction of production-transfer-distribution costs as well as power losses are analyzed as well, via the penetration of Renewable Energy Sources (RESs). To this end, it is necessary to use appropriate advanced infrastructure, where in combination with modern telecommunication networks will make possible the full exploitation of IENs. Moreover, to make the electricity system more efficient, to avoid voltage and frequency imbalance issues and to implement optimal production and consumption planning, the Electric Load Forecast (ELF) is a vital process and plays a key role in the planning as well as in the management of electricity systems. Therefore, recent state of the art approaches in ELF methods are discussed as well.

Synchronous electrical cardioversion is a relatively common procedure in the emergency department (ED), often performed for unstable supraventricular tachycardia (SVT) or unstable ventricular tachycardia (VT). However, it is also used for stable cases resistant to drug therapy, which carry a risk of deterioration. In addition to the inherent risks linked with procedural sedation, there is a possibility of malignant arrhythmias or bradycardia, which could potentially result in cardiac arrest following this procedure. Here, we present a case of complete heart block unresponsive to transcutaneous pacing and positive inotropic and chronotropic drugs for 90 minutes, resulting in multiple cardiac arrests. The repositioning of the transcutaneous cardio-stimulation electrodes, one of them placed in the left latero-sternal position and the other at the level of the apex, led to immediate stabilization of the patient. Extubation of the patient was performed the following day, while full recovery and discharge within 7 days, after insertion of a permanent pacemaker.

This article presents a novel approach to understanding the influence of electric Energy on space-time curvature. EFE actual calculations refer solely to gravitational charges. In this article, I expand them to include the electric charge with calculations carried specifically for electric charges, with exciting results. The article leverages the universal consistency of physical laws, applying the known effects of gravitational charges on space-time curvature to electric charges. The research focuses on calculating the specific impact of electric charges on space-time curvature, rooted in the principle that space-time curvature is omnipresent. The findings reveal that space-time curvature's alteration due to an electric charge is influenced by various factors, including the charge's location, magnitude, mass, density, associated electric field, and its motion through space-time. Notably, the conversion factor for electric charges differs from the conversion factor for gravitational charges. These insights significantly enhance our understanding of electromagnetism and general relativity, paving the way for a more profound comprehension of electric charges.

Efficient processing of end-of-life lithium-ion batteries of electric vehicles is important and a pressing challenge for a circular economy. Regardless of whether the processing strategy is recycling, repurposing or remanufacturing, the first processing step would usually involve disassembly. As battery disassembly is a dangerous task, efforts have been made to robotise it. In this paper, a robotic disassembly platform using four industrial robots is proposed to automate the non-destructive disassembly of a plug-in hybrid electric vehicle battery pack into modules. The work was conducted as a case study to demonstrate the concept of autonomous disassembly of an electric vehicle battery pack. A two-step object localisation method based on visual information is used to overcome positional uncertainties from different sources and is validated by experiments. Also, the unscrewing system is highlighted, and its functions, such as handling untightened fasteners, loosening jammed screws, and changing the nutrunner adapters with square drives, are detailed. Furthermore, the time required for each operation is compared with that taken by human operators. Finally, the limitations of the platform are reported and future research directions are suggested.

Addressing the pressing challenge of global warming, reducing greenhouse gas emissions in the transportation sector is a critical imperative. Battery and fuel-cell electric vehicles have emerged as promising solutions for curbing emissions in this sector. In this study, we conducted a comprehensive life cycle assessment (LCA) for typical passenger vehicles, heavy duty trucks and city buses using either proton-exchange membrane fuel cells or Li-ion batteries with different cell chemistries. To ensure accuracy, we supplemented existing studies with data from the literature, particularly for the recycling phase, as database limitations were encountered. Our results highlight that fuel cell and battery systems exhibit large emissions in the production phase. Recycling can significantly offset some of these emissions, but a comparison of the technologies examined revealed considerable differences. Overall, battery electric vehicles consistently outperform fuel cell electric vehicles regarding absolute greenhouse gas emissions. Hence, we recommend prioritizing battery electric over fuel cell vehicles. However, deploying fuel cell electric vehicles could become attractive in a hydrogen economy scenario where other factors, e. g. the conversion and storage of surplus renewable electricity via electrolysis, become important.

Decarbonization of air mobility requires the decarbonization of its energy. While biofuels will play an important role, other low carbon energy carriers based on electricity are considered: battery electrification, liquid hydrogen (LH₂) or eFuel, a hydrogen-based energy carrier. Each energy carrier has its own conversion steps and losses and its own integration effects with the aircraft. These combinations lead to different energy requirements and must be understood to compare their cost and CO₂ emissions. Since they are all electricity-based, this study compares these energy carriers using the well to rotor methodology when applied to a standard Vertical Take-Off and Landing (VTOL) air mobility mission. This novel approach allows one to understand that the choice of the energy carrier dictates the propulsive system architecture, leading to integration effects with the aircraft which can significantly change the energy required, from 400 to 2665 kWh for the same mission. These deviations lead significant differences in CO₂ emissions and costs. Battery electrification is impacted by the battery manufacturing but has the lowest electricity consumption. It is an optimum solution but only until the battery weight can be lifted. In all scenarios eFuel is more efficient than LH₂. We conclude that carrying the most efficient molecule in an aircraft pays the extra energy cost spent on the ground. Finally, we found that for each of these energy carriers, it is the electricity carbon intensity and price which will dictate the cost and CO₂ emissions of an air mobility mission.

The per capita availability of freshwater resources on a global scale is gradually decreasing due to population growth, rapid urbanization, industrialization, and modern lifestyles. In this situation, wastewater management becomes a major concern. Conventional treatment processes used to treat wastewater discharges are not adequate for the advanced removal of pollutants, especially refractory organic pollutants, which are mainly organic compounds that are not easily biodegradable in the environment. The use of photocatalytic membrane reactors (PMRs) for tertiary wastewater treatment has attracted much interest in recent periods, and various configurations have been investigated. The performance of a PMR using an iron doped titanium photo catalyst and Polysulfone-based polymeric membrane for municipal wastewater treatment was evaluated under natural and simulated solar light. Obtained results proved that solar driven PMRs can remove organic loading (COD) with high efficiencies and may represent a suitable alternative for the tertiary treatment step of municipal wastewater.

This paper proposes an electric vehicle routing problem with considering states of charging stations and suggests solution strategies. Charging of electric vehicles is a main issue in the field of electric vehicle routing problem. There are many studies to find locations of charging stations, recharging functions for batteries of vehicles, and so on. However, states of charging stations significantly affect the routes of electric vehicles, which is not much explored. The states may include open or close of charging stations, occupied or empty of charging slots, and so on. This paper investigates how the states of charging stations are estimated and routing strategies are determined. We formulate a mixed integer programming model and suggest how to solve the problem with exact method. Numerical examples provide the optimal routing strategies of electric vehicles in the changing environments of the states of charging stations.

Background: A challenge in locally advanced, unresectable pancreatic cancer treatment is to achieve both survival benefits and a safe margin-negative resection. There is no robust evidence regarding the treatment of patients with unresectable pancreatic cancer. Methods: We conducted a prospective, single-arm, phase II trial in patients with unresectable pancreatic cancer using the FOLFIRINOX regimen. After completing 4–8 cycles, patients underwent surgical resection when feasible. The primary endpoint was the R0 resection rate. Results: Fifteen patients were enrolled in this study. This study was terminated without reaching the prespecified accrual target due to low accrual rate. A median of six courses of FOLFIRINOX chemotherapy was administered, and a partial response or R0 resection was achieved in 26.7% or 33% of the patients, respectively. Se-vere adverse events due to chemotherapy and major surgical complications were observed in 33.3% and 6.7% of patients, respectively. The median overall survival rate of patients who un-derwent R0 resection or with R1 or unresectable disease was 47.8 months (95% CI, 22.5–73.1) or 14.5 months (95% CI, 11.8–17.2), respectively (P=0.031). Conclusions: Well-selected patients with URLA-PC treated with FOLFIRINOX achieved a relatively high rate of R0 resection and had pro-longed survival. Therefore, induction FOLFIRINOX is feasible and well-tolerated for locally ad-vanced, initially unresectable pancreatic cancer, and may be effective in facilitating R0 resection and prolonging survival. This should be further assessed in future randomized multicenter trials.

This study conducts a comprehensive review of the integration of Hybrid Electric Turbochargers in mass-produced road vehicles. The primary objective is to inform the readers about the potential advantages and innovative applications of HETs. Employing a SWOT analysis, the research compares the performance of HETs on thermal engines versus traditional turbochargers and HETs on thermal engines versus HETs on hybrid engines based on a synthesis of multiple research findings. The study elucidates the fundamental mechanics of turbochargers, emphasizing their inherent benefits. Additionally, it introduces a novel approach with the integration of the hy-brid-electric turbocharger, demonstrating its capacity, supported by practical examples. The in-corporation of turbochargers with energy recovery mechanisms, including HETs, is shown to significantly contribute to emissions reduction. Moreover, the electric drive facilitates the utili-zation of hybrid turbines, particularly on low-displacement engines, resulting in enhanced effi-ciency, torque, and liter power. In conclusion, the research underscores the potential of HETs to substantially mitigate the environmental impact of the transportation sector by reducing emis-sions and conserving energy. Their ability to optimize the fuel efficiency and power output of internal combustion engines, coupled with the feasibility of downsized engines, positions HETs as an attractive option for both manufacturers and consumers. However, it is acknowledged that the implementation of HETs is in its early stages, necessitating further research to comprehensively understand their environmental impact. Despite this, the promising positive impact on the en-vironment designates HETs as a technology deserving close attention in the forthcoming years.

Data obtained by Direct Numerical Simulations (DNS) of pressure-driven turbulent channel flow are studied in the range 180 ≤ Reτ≤ 10,000. Reynolds number effects on the Mean Velocity Profile (MVP) and second order statistics are analyzed with a view of finding logarithmic behavior in the overlap region or even further from the wall, well in the boundary layer’s outer region. Values of Kármán constant for the MVPs and the Townsend-Perry constants for the streamwise and spanwise fluctuation variances are determined for the Reynolds numbers considered. A data-driven model of the MVP, proposed and validated for zero pressure gradient flow over a flat plate, is employed for pressure-driven channel flow by appropriately adjusting Coles’ strength of the wake function parameter, Π. There is excellent agreement between the analytic model predictions of MVP and the DNS-computed MVP as well as of the Reynolds shear stress profile. The skin friction coefficient Cf is calculated analytically. The agreement between the analytical model predictions and the DNS-based computed discrete values of Cf is excellent.

The aim of this study is to investigate transient dynamic flow characteristics of the fluid flow through 5-way electric coolant valve (PCCV : Penta-Control Coolant Valve). To achieve this goal, the present paper attempts the three-dimensional dynamic simulation of the fluid flow through the valve using a commercial CFD solver with moving mesh technique to consider flow inertia and dynamic flow in the opening and closing stages of the ball valve rotating motion. Firstly, dynamic flow characteristics and the thermal mixing inside the PCCV ball valve during the opening and closing stage was analyzed. It is found that the discrepancies between dynamic and steady state simulation is remarkable when fluxes with different levels of enthalpy and momentum flow into the PCCV leads to strong flow interference and flow inertia, while the discrepancies are relatively small at low rotation speed and weak flow interference. Then, the effect of dynamic flow characteristics of the valve on dynamic thermal mixing characteristics at two different ball valve rotational speeds and rotational directions were investigated. It was found that the dynamic flow and thermal mixing characteristics inside the PCCV are greatly affected by the rotation speed, rotation direction, and degree of flow interference between fluxes. It is helpful for the design of the better coolant control strategies and the improvement of the FCEV thermal management system.

The thick functionally graded material (FGM) circular cylindrical shells with advanced varied shear correction coefficient and third-order shear deformation theory (TSDT) under advanced thermal vibration are studied by the method of generalized differential quadrature (GDQ). The coefficient of displacement model of TSDT is applied to derive the equations of motion for the thick FGM circular cylindrical shells. The stiffness in simpler forms of thick FGM circular cylindrical shells and temperature rise in linear expression of the heat conduction equation are used. The differential equations in dynamic equilibrium state of thick FGM circular cylindrical shells can be obtained and rewritten into displacements and shear rotations in partial derivative expressions under dynamic thermal loads in partial derivative expressions. Parametric effect studies including advanced nonlinear varied shear correction coefficient, nonlinear coefficient c1 value, power law index and thermal temperature difference of external heating loads on the displacements and stresses of thick FGM cylindrical shells under thermal dynamic vibration are investigated.

In the last decade, with the increased concerns about the global environmental situation, attempts have been made to promote the replacement of fossil fuels with sustainable sources. For transport, which accounts for around a quarter of total greenhouse gas emissions, meeting climate neutrality goals will require replacing existing fleets with electric or hydrogen propelled vehicles. This research addresses the problem of transport fleet renewal by proposing a multi-criteria decision-making approach, taking into account the multiple propulsion technologies currently available and the objectives of the EU Green Deal, as well as the uncertainty related to the technological scenario, in a generalized Life Cycle framework. The proposed approach, based on the TOPSIS model, demonstrates how the optimality of the choice is related to the different technological scenarios and to the risky attitude of the decision maker. The proposed methodology is finally validated against a practical case referred the strategic fleet renewal decision process, and the results obtained demonstrate how the decision maker’s perception about the technological evolution of the propulsion technologies influences the decision process, thus leading to different optimal choices.

Introduction: Advanced glycation end-products (AGEs) may play a relevant role as inducers in the chronic inflammatory pathway present in immune-mediated diseases, such as systemic lupus erythematosus (SLE). AGEs concentrations have been associated, with discrepant results to date, with some parameters such as disease activity or accrual damage, suggesting their potential usefulness as biomarkers of the disease. Objectives: To confirm differences in AGEs levels measured by cutaneous autofluorescence between SLE patients and healthy controls (HC) and study their correlation with various disease parameters. Methods: Cross-sectional study, where AGEs levels were measured by skin autofluorescence, and SLE patients’ data were compared with those of sex- and age-matched HC in a 1:3 proportion through a multiple linear regression model. Correlations of AGEs levels with demographic and clinical data were analyzed through ANOVA tests. Both analyses were adjusted for confounders. Results: AGEs levels in SLE patients were significantly higher than in HC (p<0.001). We found statistically significant positive correlation with SLE disease activity index (SLEDAI) and damage index (SDI), physician and patient global assessment, C-reactive protein, leukocyturia, complement C4, IL6 and oral ulcers. We also found a negative statistically significant correlation with current positivity of anti-nuclear and anti-Ro60 antibodies. Conclusions: AGEs seem to have a role in LES pathophysiology, becoming a new management and prognosis biomarker in this disease. The association with specific antibodies and disease manifestations may indicate a specific clinical phenotype related to higher AGEs levels.

The paper proposes a methodological way to compensate the imbalance between energy generation and consumption using the battery block of electric vehicles as energy reservoir through the well-known Vehicle to Grid system (V2G). The method is based on a simulation process developed by the authors that take into consideration the daily fluctuations of energy consumption as well as the power level generated by an energy source, either conventional, renewable or hybrid. The study shows that for very large electric vehicle fleet the system renders non-viable, since the remaining energy in the battery block to let the electric vehicle usable for running during daytime avoids to compensating for the energy grid imbalance, only allowing to cover a percentage of the energy imbalance, which the proposed methodology may optimize. The analysis of the proposed methodology also shows the viability of the system when being applied to a small fleet of electric vehicles, not only compensating for the energy imbalance but also preserving the required energy in the battery of the electric vehicle to make it run. The method allows predicting the optimum size of electric vehicle battery, which depends on the energy generation level, coverage factor of the energy imbalance and size of the electric vehicle fleet.

End-of-life electric vehicle (EV) batteries can be reused to reduce their environmental impact and economic costs. However, the growth of a second-life market is limited by the lack of information on the characteristics and performance of these batteries. As the volume of end-of-life EVs may exceed the amount of batteries needed for stationary applications, investigating the possibility of repurposing them in mobile applications is also necessary. This article presents an experimental test that can be used to collect the data necessary to fill a battery passport. The proposed procedure can facilitate the decision making process regarding the suitability of a battery for reuse at the end of its first life. Once the battery passport has been completed, the performance and characteristics of the battery are compared with the requirements of several mobile applications. Mobile charging stations and forklift trucks were identified as relevant applications for the reuse of high capacity prismatic cells. Finally, a definition of a state of health (SoH) is proposed to track the suitability of the battery during use in the second life application considering not only energy but also power and efficiency of the battery. This SoH shows that even taking into account accelerated ageing data, a repurposed battery can have an extended life of 11 years at 25~°C. It has also been shown that energy fade is the most limiting performance for lifetime and that cell-to-cell variation should be tracked as it has been shown to have a significant impact on battery life.

In steel recycling, the optimization of electric arc furnaces (EAFs) is of central importance in order to increase efficiency and reduce costs. This study focuses on the optimization of electric arcs, which make a significant contribution to the energy consumption of EAFs. A three-phase equivalent circuit integrated with the Cassie-Mayr arc model is used to capture the nonlinear and dynamic characteristics of arcs, including arc breakage and ignition process. A particle swarm optimization technique is applied to real EAF data containing current and voltage measurements to estimate the parameters of the Cassie-Mayr model. A novel Arc Quality Index (AQI) is introduced in the study, which can be used to evaluate arc quality based on deviations from optimal conditions. The AQI provides a qualitative assessment of arc quality, analogous to indices such as arc coverage and arc stability. The study concludes that the AQI serves as an effective operational tool for EAF operators to optimize production and increase the efficiency and sustainability of steel production. The results underline the importance of understanding electric arc dynamics for the development of EAF technology.

Background: Neuromuscular electrical stimulation (NMES) has beneficial effects on physical functions in Multiple Sclerosis (MS) patients. However, the neurophysiological mechanisms underlying these functional improvements are still unclear. This study aims at comparing acute responses in spinal excitability, as measured by soleus Hoffmann reflex (H-reflex), between MS patients and healthy individuals, following three experimental conditions involving the ankle planta flexor muscles: 1) passive NMES (pNMES); 2) NMES superimposed to isometric voluntary contraction (NMES+); and 3) isometric voluntary contraction (ISO). Methods: 20 MS patients (MSp) and 20 healthy individuals as control group (CG) took part in a single experimental session. During each condition, participants performed 15 repetitions of 6 seconds at 20% of maximal voluntary isometric contraction, with 6 seconds of recovery between repetitions. Before and after each condition, H-reflex amplitudes were recorded. Results: In MSp, H-reflex amplitude did not change following any experimental condition (ISO: p = 0.506; pNMES: p = 0.068; NMES+: p = 0.126). In CG, H-reflex amplitude significantly increased following NMES+ (p = 0.01), decreased after pNMES (p = 0.000) and was unaltered following ISO (p = 0.829). Conclusion: the different H-reflex responses between MS and CG might reflect a reduced ability of MS patients in modulating spinal excitability.

This work targets the development of a mobility control system for high-speed series hybrid electric tracked vehicles, which operate with independent traction motors for each track. The scope of the research encompasses the modeling of the series hybrid powertrain specific to military tracked vehicles, as well as an in-depth analysis of their dynamic behavior. Subsequently, the study conducts a critical review of the mobility control approaches sourced from literature, identifying key techniques relevant to high-inertia vehicular applications. Building on the foundational models, the study puts forward a robust closed-loop mobility control system aimed at ensuring precise and stable off-road vehicle operations. The system's resilience and adaptability to a variety of driving conditions are emphasized, with a particular focus on handling maneuvers such as steering and pivoting, which are challenging operations for tracked vehicle agility. The performance of the proposed mobility control system is tested through a series of simulations, covering a spectrum of operational scenarios. These tests are carried out in both offline simulation settings, which permit meticulous fine-tuning of system parameters, and real-time environments that replicate actual field conditions. The simulation results demonstrate the system's capacity to improve vehicular response and highlight its potential impact on the future designs of mobility control systems for the heavy-duty vehicle sector, particularly in defense applications.

This article provides a comprehensive exploration of the electric vehicle (EV) business, investigating its current state, market dynamics, and pivotal role in sustainable transportation. It delves into factors driving EV adoption, challenges faced by the industry, and the landscape of key players. The discussion extends to investments, infrastructure development, consumer trends, and the technological innovations shaping the future. The article concludes with insights into the anticipated growth and transformative impact of EVs, emphasizing their significance in fostering a cleaner, more sustainable future for global transportation.

The exceptional performance of graphene has driven the advancement of its preparation technique and application. Laser-induced graphene (LIG), as a novel graphene preparation technique, has been applied in various fields. Graphene periodic structures created by LIG technique exhibit superhydrophobic characteristics and can be used for deicing and anti-icing applications, which are significantly influenced by the laser parameters. The laser surface treatment process was simulated by a finite element software analysis (COMSOL Multiphysics) to optimize the scanning parameter range, and the linear array surface structure were subsequently fabricated by the LIG technique. The generation of graphene was confirmed by Raman spectroscopy, and energy-dispersive X-ray spectroscopy. The periodic linear array structure were observed by Scanning electron microscopy (SEM) and confocal laser imaging (CLSM). In addition, CLSM testings, contact angle measurements, and delayed icing experiments were systematically performed to investigate the effect of scanning speed on surface hydrophobicity. The results show that the high quality and uniform graphene can be achieved using the laser scanning speed of 125 mm/s. The periodic linear array structures can obviously increase the contact angle and suppress delayed icing. Furthermore, these structures have the enhanced ability of the electric heating deicing, which can reach 100°C and 240°C within 15 s and within 60 s under the DC voltage power supply ranging from 3 to 7 V, respectively. These results indicate that the LIG technique can be developed to provide an efficient, economical, and convenient approach for preparing graphene and the hydrophobic surface array structure based on LIG has considerable potential for deicing and anti-icing applications.

This review is a first attempt at bringing together various concepts from research on wall- and magnetically-bounded turbulent flows. Brief reviews of both fields are provided: The main similarities identified are coherent (turbulent) structures, flow generation and transport barriers. Examples are provided and discussed.

The electrical energy supply relies on the satisfactory operation of insulators. The ultrasound recorded from insulators in different conditions has a time series output, which can be used to classify faulty insulators. The random convolutional kernel transform (Rocket) algorithms use convolutional filters to extract various features from time series data. This paper proposes the combination of Rocket algorithms, machine learning classifiers, and empirical mode decomposition (EMD) methods, such as complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), empirical wavelet transform (EWT), and variational mode decomposition (VMD). The results show that the EMD methods combined with MiniRocket, significantly improve the accuracy of logistic regression in insulator fault diagnosis. The proposed strategy achieves respectively an accuracy of 0.992 using CEEMDAN, 0.995 with EWT, and 0.980 with VMD. These results highlight the potential of incorporating EMD methods in insulator failure detection models to enhance the safety and dependability of power systems.

Abstract: Cervical cancer, which is the fourth most common malignancy and the fourth greatest cause of cancer-related deaths in women globally, continues to be a serious issue for global health. Despite advancements in treatment techniques, particularly the implementation of concomitant chemoradiation therapy, predicting the prognosis of locally advanced cervical cancer, especially for stage III, remains challenging. In recent years, neoadjuvant chemotherapy (NACT) has gained interest as a viable treatment strategy. The objective of this review paper is to scrutinize the clinical data and outcomes associated with NACT in the management of stage 3 cervical cancer. Electronic databases were used to perform a comprehensive literature search, and research up to 2023 were included. The findings suggest that NACT followed by irradiation may have advantages such as lowering tumor size, pelvic architectural distortion, and subclinical distant metastases, therefore enhancing radiation delivery. However, several studies have produced conflicting findings, raising questions regarding toxicity and finding no appreciable survival benefit over radiation alone. NACT followed by radical surgery has demonstrated more promising outcomes compared to surgery alone in terms of increasing rates of overall survival (OS) and progression-free survival (PFS). Additionally, NACT has been associated with decreased tumor growth, parametrial infiltration, nodal, metastases, and vascular space invasion. These findings suggest adjuvant radiation treatment. Although the overall survival rate has been markedly increased by concomitant chemoradiation treatment, metastatic disease continues to be a major factor in the death rate from cervical cancer. Therefore, improving outcomes in locally advanced cervical cancer requires investigating novel systemic treatments, such as NACT. The study also emphasizes how crucial it is to research factors like cisplatin dose-intensity and cycle lengths in order to maximize NACT's efficacy. To prevent the need for subsequent treatments and cumulative toxicity, more study should concentrate on patient selection for NACT followed by surgery.

Abstract: Recent years demonstrate the increased attention to radon from two scientific directions. After neglecting radon as earthquake precursors in 1990-th it becomes again the subject of earthquake-forecast papers discussions due to growing networks of the radon monitoring in different countries, especially, the technologies of real-time radon measurements where the gamma-spectrometers become the leader of interest as the sources of 222Rn identification. The second fast developing direction is including the radon in the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) models as a source of the boundary layer ionization. And here we encounter with second direction which is not connected with the earthquake forecast problems. It is the role of air ionization by radon as a source of the Global Electric Circuit (GEC) modification. In this publication we try to unite all these problems to present more complex view on radon as important element of our environment.

This study proposes a methodology for identifying time intervals in which time-of-use (ToU) energy tariffs can be set. This is achieved by analyzing the variability in electric power demand and esti-mating the potential for demand flexibility. The proposed methodology is as follows: first, data preprocessing is performed, focusing on the organization and cleaning of individual consumption records. Subsequently, the data are processed and classified by using consumption variability analysis and clustering techniques. Then, representative clusters are selected and time intervals are analyzed to identify periods of high electric power consumption variability. This methodology was tested with real data from smart meters in the Colombian electrical system, in which time intervals with potential for settinh ToU tariffs were ultimately identified. This work promotes the implementation of demand response strategies that enhance sustainability and facilitate the transition to a more resilient energy landscape both nationally and internationally. The findings are expected to contribute to the formulation of tariff schemes that encourage con-scious changes in electric energy consumption patterns.

Background: biophysical stimulation therapy, and in particular Pulsed Electromagnetic Fields (PEMFs) and capacitively coupled electric fields (CCEFs) has significantly increased in the last twenty years. For this, it is necessary to have clear information regarding the efficacy, the therapeutic indication and the expected objectives. Methods: we conducted a narrative review taking into consideration different types of studies with different areas of application. The objective was to take into consideration and analyze the different fields of use and the relevant information present in the literature. Results: There is unanimous opinion regarding the usefulness of applying biophysical therapy on the bone compartment both in terms of the tissue healing process and the symptoms associated with this situation. Differently, but no less importantly, in the joint compartment positive opinions were observed mainly on the inflammatory and catabolic process, however, at present,we did not report evidence regarding cartilaginous tissue regeneration. Conclusion: the effectiveness of PEMFs and CCEFs on the bone healing process in the Orthopedic and Traumatology fields is consolidated evidence in the literature. We have also found positive results on symptoms and patient compliance with rehabilitation therapies. Therefore, notable application can be envisaged in the fields of Prosthetic Surgery and Sports Medicine.

Electric vehicles can effectively make use of the time-of-use electricity price to reduce the charging cost, meanwhile using the grid power to preheat the battery before departure is particularly important for improving the vehicle mileage and reducing the use cost.In this paper, a dynamic programming algorithm is used to optimize the battery AC charging-preheating strategy to minimize the total cost of battery charging and preheating, with the charging current and battery preheating power consumption as the control variables. The cost difference between the optimized control strategy and the conventional preheating strategy was analyzed under different ambient temperatures (-20℃~ 0℃) and different target travel time (7:00 ~ 12:00). The simulation results show that the optimized control strategy makes the battery SOC and temperature reach the set value at the user's target departure time, and the total cost of the grid is the lowest. Compared with the conventional preheating strategy, the optimized control strategy can utilize the power grid energy in the valley price area, reduce the opening time of water heating PTC in the flat and the peak price zones, and the cost utilization rate can reach 18.41% ~ 73.96%, and the cost-saving effect is significant.

Abstract: This review addresses the complexities of type 1 diabetes (T1D)and its associated complications, with a par-ticular focus on diabetic retinopathy (DR). This review outlines the progression from non-proliferative to proliferative diabetic retinopathy and diabetic macular edema, highlighting the role of dysglycemia in the pathogenesis of these conditions. A significant portion of the review is devoted to technological advances in diabetes management, particu-larly the use of Hybrid Closed Loop systems (HCLS) and to the potential of open-source HCLS systems, which could be easily adapted to different patiens’needs using big data analytics and machine learning. Personalized HCLS algorithms that integrate factors such as patient lifestyle, dietary habits, and hormonal variations are highlighted as critical to reducing the incidence of diabetes-related complications and improving patient outcomes.

This work aims to study and analyze a hybrid power system for electric vehicles consisting of a dual low and high-rate lithium battery block and a fuel cell. In this configuration, the high-rate lithium battery powers the electric vehicle in high power demand processes like acceleration mode or on an uphill road; the low-rate battery operates at a low output power range, servicing the auxiliary systems and low power loads and the fuel cell supplies energy at intermediate power demand conditions, normal driving mode, constant velocity, or flat and downhill terrain. The dual power system improves global efficiency since every power unit operates optimally depending on driving conditions. Power sharing optimizes the lithium battery performance and fuel cell capacity, minimizing the size and weight of each energy system and enlarging the driving range. A comparative study between different lithium battery configurations and fuel cell shows an efficiency improvement of 31.4% for the hybrid dual battery block and fuel cell operating in low, high, and intermediate output power ranges, respectively. The study bases on a simulation process recreating current driving conditions for electric cars in urban, peripheral, and intercity routes. An alternative solution consisting of a hybrid system, fuel cell and a high rate lithium battery produces a 29 % power gain.

This paper focuses on the impact that urban traffic has on the environment. The study characterizes the global effect of GHG emissions, including the ecologic evaluation and the characterization, normalization, and evaluation factor. The work makes a detailed survey of the different modes of driving and their influence on engine performance as one of the principal causes of gas emissions during the combustion process. The article analyzes six types of vehicles equipped with different engine configurations: diesel and gasoline, GLP and GNC, hybrid electric, and plug-in hybrid electric. Simulation of the driving mode under various operational conditions for every type of engine results in energy consumption, thus, in GHG emissions, carbon dioxide and monoxide, nitrogen oxides, and Sulphur dioxide. The study concludes that a reduction in vehicle speed, thus in the engine revolutions, has positive effects on engine combustion and gasses emissions, which is reduced by 27.5%. The study also concludes that the limitation in driving mode, avoiding sharp and sudden acceleration, may reduce up to 45% of GHG emissions. The changes applied in the driving mode improve the air quality in the urban environment, reducing the content of GHG from 39% to 61%.

This study conducted experiments to optimize the electro-dewatering of sludge using a dynamic model calculation method and the Wild Horse optimizer. Specifically, we explored two factors that might influence dewatering: the composition of the electrode materials and the strength of the electrical field. Compared to other electrodes commonly used in electro-dewatering—such as RuO2/Ir2O3-Ti, graphite, Ir2O3/Ta2O5-Ti, and Ti—the Electro-kinetic Geosynthetics (EKG) electrode exhibited superior performance. This was determined by considering both energy consumption and model establishment. Our findings also identified electric-field strength as a crucial factor determining the final moisture content. As the electrical intensity increased, the dewatering effect improved, aligning with our model calculations. However, we observed a steep increase in energy consumption per kilogram of filtrate when the electric-field strength exceeded a certain threshold. To optimize the energy consumption of the dehydration process, we constructed a multi-factor model. The simulation results from this model confirmed that electric-field intensity is the primary factor affecting dehydration. It was established that 10 V/cm is a critical threshold for the process.

The thermal degradation of brakes has a significant impact on the stability of pure electric commercial vehicles during long downhill braking. Based on road slope and using fuzzy control method, design strategies for motor regenerative braking force and friction braking force distribution, with the aim of reducing friction braking force, improving braking stability, and recovering braking energy. By establishing driving conditions on roads with different slopes and using numerical analysis methods to verify the proposed control strategy. the results show that under the 6% constant slope driving condition, the vehicle maintains a constant speed of 30km/h downhill driving, and the braking energy recovery rate reaches 50.93%; Under the condition of 3% -6% gradient driving, the vehicle speed fluctuates slightly, but it can still be maintained at a constant speed of 30km/h for downhill driving through the adjustment of the motor's reverse drag characteristic, with a braking energy recovery rate of 49.97%; During the process of driving downhill at a constant speed, the frictional braking force does not participate in braking; The braking energy recovery rate is determined by the slope and braking deceleration.

The meticulously engineered powertrain mounting system of hybrid-electric vehicles plays a critical role in minimizing vehicle vibrations and noise, thereby enhancing the longevity of vital powertrain components. However, developing and designing such a system demands substantial time and financial investments due to intricate analysis and modeling requirements. To tackle this challenge, this study integrates data-mining technology into the design and optimization processes of the powertrain mount system. The research focuses on the powertrain mounting system of a transverse four-cylinder hybrid-electric vehicle, employing the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology to establish a data-mining prediction model for mounting stiffness. This model utilizes three data mining algorithms—Multi-SVR, MRTs, and MLPR—assessing their predictive accuracy concerning mounting system stiffness estimation. A comparative analysis reveals that the MRTs algorithm outperforms others as the most effective prediction model. The proposed predictive model elucidates the quantifiable correlation between vibration isolation performance and installation stiffness, overcoming complexities associated with traditional modeling approaches. Applying this model in powertrain mounting system design showcases the efficacy of the CRISP-DM-based approach, significantly enhancing design efficiency without compromising prediction accuracy.

Among the sensors necessary to equip vehicles with an autonomous driving system, there is a tacit agreement that cameras and some type of radar would be essential. The ability of radar to spatially locate objects (pedestrians, other vehicles, street furniture and traffic signs) makes it the most economical complement to the cameras in the visible spectrum, in order to give the correct depth to scenes. From the echoes obtained by the radar, some data fusion algorithm will try to locate each object in its correct place within the space surrounding the vehicle. In any case, the usefulness of the radar will be determined by several performance parameters, such as its aver-age error in distance, the maximum errors and the number of echoes per second it can provide. In this work we have tested experimentally the AWR1843 MIMO radar from Texas Instruments to measure those parameters.

Human Platelet lysate, a hemoderivative product rich in growth factors, holds significant promise in tissue engineering and regenerative medicine. However, its practical utility in liquid or gel form is hampered by challenges such as limited stability and handling difficulties. This study aimed to engineer dry and porous aerogels from platelet lysate hydrogel using an environmen-tally friendly supercritical CO2-based shaping process customized for tissue engineering appli-cations. The resulting aerogels demonstrated remarkable mechanical robustness and improved manageability. Notably, they exhibited a high-water absorption capacity. Moreover, these aer-ogels exhibited a sustained and favourable biological response in-vitro. They demonstrated the ability to release functional growth factors, sustaining cellular metabolic activity similar to that of conventional culture conditions, even after prolonged storage. Furthermore, they supported the adhesion and proliferation of murine fibroblasts (BALB-3T3) and the migration of Human Um-bilical Vein Endothelial Cells (HUVEC). In addition to serving as excellent matrices for cell culture, these proposed aerogels also function as efficient growth factor delivery systems. This multi-functional capability positions them as promising candidates for various tissue regeneration strategies. Importantly, the elaborated aerogels can be conveniently stored and considered as ready-to-use products, enhancing their practicality and applicability in regenerative medicine

New composite with core-shell structure based on magnesium hydride and finely dispersed aluminum powder with aluminum oxide shell was mechanically synthesized. We used magnesium chips to produce magnesium hydride and aluminum wire after exploitation to produce nano-sized aluminum powder. The beginning of the hydrogen release from composite occurred at the temperature of 117°C. The maximum desorption temperature from the MgH₂-EEWAl composite (10 wt.%) is 336°C compared to pure magnesium hydride – 417°C. The mass content of hydrogen in the composite is 5.5 wt.%. The positive effect of aluminum powder produced by the electric explosion of wires method on reducing the activation energy of desorption was demonstrated. Calculations showed that the activation energy of desorption for the composite is 106±1 kJ/mol, compared with pure magnesium hydride, whose activation energy was 155±2 kJ/mol. The results obtained make it possible to expand the possibility of using magnesium and aluminum waste for hydrogen energy.

The advancement of technology has led to a shift in the automotive industry from gasoline vehicles to electric vehicles. One of the key factors in modern vehicles is the communication between control devices and commands. This thesis presents a prototype of communication in the form of CAN BUS Protocol with CAN STANDARD SAE.J1939 for All-Terrain Vehicle (ATV) using MRS Developers Studio software to control the CAN Bus system. This thesis discusses the operation of communication from the assembly of the ATV, the packing of a 72 V 25Ah battery as a power source for the vehicle, the layout of the wiring system for receiving/sending communication signals for the 3 CAN Bus control boxes, and programming with MRS Developers Studio software used in communication. The communication of the vehicle in the ATV consists of receiving/sending signals of switches, headlights, left turn signal, right turn signal, brake light, emergency light, horn, forward-reverse gear, and accelerator. The results of the operation of the CAN Bus Protocol found that the CAN Bus control box has only 6 input and output pins, making the communication that has both receiving and sending signals insufficient. Therefore, starting from the CAN Bus1 control box acts as a receiver of signals from the forward-reverse gear switch sent to the output of the CAN Bus3 control box, the CAN Bus1 control box acts as a receiver of all light signals sent to the output of the CAN Bus2 control box. The signal transmission between devices will send signals through the CAN HUB line to ensure stability and minimal interference. In addition, the communication between devices from testing the operation of various switches on and off up to 1000 times found that this communication does not cause errors, making this communication reliable and stable.

The urgency for a shift towards cleaner and more efficient energy alternatives for power generation is underscored by the escalating demand for energy and the detrimental environmental impacts of conventional fossil fuels. In the case of automotive power, electric vehicles are being adopted in many applications, however, challenges remain such as extended charging periods and limited ranges between charges. Therefore, this research study conducts a techno-economic analysis of renewable energy technologies (including solar modules, wind turbines and piezoelectric materials) to augment the efficiency and sustainability of electric buses. The study examines the scope for these technologies to be adopted on double-decker electric buses in London in the United Kingdom. The solar modules are placed on the rooftop and sides of the bus generating 15.9 kWh/day and the wind turbine in the front bumper of the bus generates 8.3 kWh/day. However, the piezoelectric material generated only 22.6 Wh/day, rendering it an impractical inclusion in further analysis. Therefore, both the solar modules and wind turbines combined generate 24.2 kWh/day, which can increase the driving range by 16.3 km per day and this results in savings of 19.36 minutes for charging at the stations. Investing in such projects would have a positive return as the internal rate of return (IRR) and net present value (NPV) are 2.8% and £11,175 respectively. The annual revenue would be £6,712, and the greenhouse gas (GHG) reduction would be two metric tons annually. Electricity exported to the grid, the electricity export rate, and the initial investment are identified as key factors influencing power outage in a sensitivity analysis. In conclusion, this numerical modelling study paves the way for experimental validation towards implementation of renewable energy technologies on electric bus fleets.

This article explores the crucial task of estimating State of Charge (SOC) in Hybrid Electric Vehicles (HEVs) and examines the applicability of various regression models for this purpose. We delve into the strengths and limitations of Linear Regression, Support Vector Regression (SVR), and Neural Network Regression (NNR) in the context of SOC estimation. Linear regression provides a simple and interpretable baseline, SVR extends this to nonlinear relationships, while NNR emerges as a powerful tool with adaptive capabilities. The choice of model depends on factors such as data characteristics, interpretability, and computational resources. As the field evolves, the article advocates for a nuanced approach, possibly incorporating hybrid models, to achieve robust and accurate SOC estimation, contributing to the ongoing enhancement of HEV efficiency and sustainability.

In a recent paper, we extended previous studies on solar-terrestrial relationships by investigating the origin of the March 2012 heatwave in northeast USA. In the present study we check the possible relationship of solar activity with the early March 2012 bad weather in northeast Thrace, Greece. To this end, we examined data from various remote sensing instrumentation monitoring the Sun (SDO satellite), the Interplanetary Space (ACE satellite), the Earth’s magnetosphere (Earth based measurements, NOAA-19 satellite), the top of the clouds (TERRA and AQUA satellites) and the near ground atmosphere. Our comparative data analysis suggests that: (i) the winter-like weather (rainfall, fast winds, decreased temperature) in Thrace started on 6 March 2012, on the same day as the heatwave starting in USA, (ii) during the March 2012 winter-like event in Thrace (6-15 March), the ACE satellite recorded enhanced fluxes of solar energetic particles (SEPs), while SOHO and PAMELA recorded solar protons at very high energies (> 500 MeV), (iii) Thrace experienced particularly intense cyclonic circulation, during periods of magnetic storms on 8 - 10 and 12-13 March, which occurred after the arrival at ACE of two interplanetary shock waves, on March 8 and March 11, respectively, (iv) at the beginning of the two above mentioned periods large atmospheric electric fields were recorded, with values ranging between ~-2000V/m - ~1800V/m on 8 March, (v) the winter-like 8-10 March 2012 weather occurred after the detection of the main SEP event related with a coronal mass ejection released in the interplanetary space as a result of intense solar flare activity observed by SDO on 7 March 2012, (vi) the 8-10 March weather was related with a deep drop of ~630C in the cloud top temperature measured by MODIS/TERRA, which favors strong precipitation. Finally, we analyzed data from the electric power network in Thrace (~410N) and we found, for the first time sudden voltage changes of ~3.5kV in the electric grid in Greece, during the decay phase of the March 2012 superstorm. We discuss the winter-like March 2012 event in Thrace in terms of solar cosmic ray influence on the low troposphere mediated by positive NAO. Finally, we infer that the novel finding of the geomagnetic effects on the electric power grid in Thrace may open a new window into space weather applications research.

In Thailand, there are several bus fleets—predominantly diesel buses—which is an internal combustion engine (ICEs) in circulation. These fleets are consumed a lot of energy and cause pollution, especially by emitting GHGs and PM2.5. Battery electric buses (BEBs) have been proposed to address these issues. BEB fleets still have a high initial cost, which is why most fleet governance agencies, such as the Bangkok Mass Transit Authority (BMTA), are facing investment decisions. This study aims to develop an energy model for the BMTA BEB fleet by using their real operating data. The methodology for the development of the investment model with two steps is described; there is a BMTA bus route analysis step and a fleet management and charging design step. The output is illustrated in terms of the maximum number of BEBs that can be operated on a sample route with the minimum number of chargers. Interesting results were obtained with the first step: Two of the five BMTA bus routes can be changed into BEBs in phases with a limit of 200 kWh for the energy requirements for every two rounds. The results from the second step demonstrated that the maximum number of BEBs for the two routes was 13, with four charger plugs of charger, thus requiring 150 kW per plug. The charging profile peaked at 600 kW from 4:00 to 8:00 p.m. These results show the potential of the model for fleet design and investment decisions. The sample results from the models illustrate energy savings and cost evaluations for fleet management and design. Compared with diesel buses, THB 10.44 million per year can be saved in terms of energy costs by using a BEB fleet. An optimization model was used to assess the savings incurred due to the investment cost. More than 37% of the costs were saved. A full economic investigation should be carried out in the future. These results show only the energy used when the fleet has already been transformed into a BEB fleet in phases. The emphasis of battery size investigation and energy used were illustrated. They only depict an economic validation of the model, but do not refer to such projects’ feasibility, and the model has not yet been fully validated.

The extreme environmental issues and the resulting needs to save energy have turned the attention to electrification of energy applications. One of the key components involved in energy efficiency improvements is the appropriate conception and manufacturing of electric machines. This paper overviews the electromagnetic analysis governing the behavior of permanent magnets that enabled substantial efficiency gains in recent electric machine developments. Particular emphasis is given to model the properties and losses developed in permanent magnets in the emerging high speed applications. In addition, the investigation of properties and harmonic losses related to ferromagnetic materials constituting the machine magnetic circuits are equally analyzed and discussed. The experimental validation of the implemented methodologies and developed models with respect to the obtained precision is reported. The introduction of mixed numerical techniques based on the finite element method intended to appropriately represent the different physical phenomena encountered is outlined and discussed. Finally, fast and accurate simulation techniques including aggregated lumped parameter models considering harmonic losses associated with inverter supplies are commented.

The incidence and mortality of cervical cancer are high in Romania compared to other European countries, particularly for locally advanced cervical cancer cases, which are predominant at the time of diagnosis. Widely accepted therapeutic guidelines indicate that the treatment for locally advanced cervical cancer consists of concurrent chemoradiotherapy (total dose 85-90Gy at point A), with surgery not being necessary as it does not lead to improved survival and results in significant additional morbidity. In Romania, the treatment for locally advanced cervical cancer differs, involving lower-dose chemotherapy (total dose 60-65Gy at point A), followed by surgery which, under these circumstances, ensures better local control. In this regard, we attempted to evaluate the role and necessity of surgery in Romania, considering that in our study, residual lesions were found in 55.84% of cases on resected specimens, especially in cases with unfavorable histology (adenocarcinoma and adenosquamous carcinoma). This type of surgery was associated with significant morbidity (28.22%) in our study. The recurrence rate was 24.21% for operated patients compared to 62% for non-operated patients receiving suboptimal concurrent chemotherapy alone. In conclusion, In Romania, surgery will continue to play a predominant role until radiotherapy achieves the desired effectiveness for local control.

Locally Advanced Breast Cancer (LABC) is a complex disease that requires a multidisciplinary approach. Neoadjuvant Chemotherapy (NAC) is usually performed in order to achieve loco-regional radical resection; although its importance in the multidisciplinary approach to LABC is well recognised, a small number of patients show Progressive Disease (PD). No standard Salvage Treatment (ST) has been defined and different strategies can be adopted, such as second line systemic therapies, radiation therapy, and surgery. Herein a case of LABC in PD during NAC is reported with a literature review, with the aim of highlighting the importance of a tailored multidisciplinary treatment in each patient.

The maritime sector, grapples with environmental challenges, but the adoption of "cold ironing" emerges as a promising solution, signifying a shift toward sustainability by providing energy to ships at port, reducing reliance on fossil fuels, and significantly lowering emissions, contributing to global climate change efforts. This transition towards renewable energy is especially crucial for islands like Lesvos, addressing challenges of high energy costs and environmental degradation resulting from reliance on imported fossil fuels, highlighting the potential for positive economic and environmental impacts. The existing literature highlights a research gap in the development of Renewable Energy Sources (RES) to support cold ironing operations, specifically due to the absence of specific data for the power demand needed in such operations and the lack of monitoring data for accurate calculations. This study's primary objective is to utilize real monitoring data from the port of Lesvos to evaluate the power demand for a potential cold ironing application. Additionally, the study aims to analyze the implementation of a wind power park to meet the energy needs of an electric port and evaluate the potential reduction in CO2 emissions. The database of Marine Traffic S.A. was utilized, while the determination of the energy used in-port per ship depended on factors such as the number of arrivals, the duration of hoteling, and the type of engine used by the ships. In addition, the software RETSCREEN was used for the energy analysis of a simulated 20 MW wind park that can support the in-port operations. The combined monthly energy demand for both main and auxiliary engines of shipping vessels at Mytilini port was assessed to be 6118 MWh and averaging a power demand equaled to 8.2 MW. The simulation analysis indicates that the annual electricity delivered to the port can be72080 MWh, with a significant portion remaining unused and exported to the grid, amounting to 14956 MWh annually. Due to demand fluctuations, in-port activities require an additional 924 MWh from the main electrical grid, which highlights the importance of additional measures like energy storage and demand-response practices for the gradual transition to 100% Renewable Energy Sources (RES) operations.

The integration of renewable energy and hybrid energy storage system (HESS) into electrified railways to build electric railway smart microgrid system (ERSMS) is beneficial for reducing fossil fuel consumption and minimizing energy waste. However, the fluctuations of renewable energy generation and traction load challenge the energy management effectiveness for such a complex system. In this work, an energy management strategy is proposed which firstly decomposes the renewable energy into low-frequency and high-frequency components by an integrated empirical mode decomposition (IEMD). Then, a two-stage energy distribution approach is utilized to appropriately distribute the energy flow among the ERSMS. Finally, the feasibility and effectiveness of the proposed solution are validated through case study.

BACKGROUND: Functional constipation can lead to painful defecations, fecal incontinence, and abdominal pain, significantly affecting a child's quality of life. Treatment options include non-pharmacological and pharmacological approaches, but some cases are intractable and require alternative interventions like neuromodulation. A subtype of neuromodulation, called Transcutaneous Posterior Tibial Nerve Stimulation (TPTNS), comprises electrical stimulation at the ankle level, by means of electrodes fixed to the skin. TPTNS is a minimally invasive, easy-to-apply technique that can potentially improve constipation symptoms in the pediatric population by stimulating the sacral nerves. AIM: To evaluate the clinical results and applicability of TPTNS as an adjuvant treatment for children and adolescents with functional constipation. METHODS: Between April 2019 and October 2021, 38 patients diagnosed with functional constipation according to the Rome IV Criteria were invited to participate in the study. The study followed a single-center, uncontrolled, prospective cohort design. Patients received TPTNS for 4 or 8 weeks, with assessments conducted immediately after the periods of TPTNS and 4 weeks after the end of the intervention period. The data normality distribution was determined by the Shapiro-Wilk test. Wilcoxon test and Student's t-test for paired samples were used to compare quantitative variables, and the McNemar test was used to compare categorical variables. RESULTS: Of the 38 enrolled patients, 28 children and adolescents with intractable function constipation completed the study, receiving TPTNS for 4 weeks. Sixteen patients (57.1%) extended the intervention period for 4 extra weeks, receiving 8 weeks of intervention. TPTNS led to significant improvements in stool consistency, frequency of defecation, and bowel function scores, with a reduction in abdominal pain. Quality of life across physical and psychosocial domains showed substantial enhancements. The quality of life-related to bowel habits also improved significantly, particularly in lifestyle, behavior, and embarrassment domains. The positive effects of this intervention are seen relatively early, detected after 4 weeks of intervention, and even 4 weeks after the end of the intervention. TPTNS was well-tolerated, with an adherence rate of approximately 78%, and no adverse effects were reported. CONCLUSION: TPTNS is an adjuvant treatment for intractable functional constipation, improving bowel function and quality of life. The effects of TPTNS were observed relatively early and sustained even after treatment cessation.

This paper provides a proof of concept for a linear electric generator that can be used to harvest energy from various sources of linear motion, such as vibrations, free-piston engines and wave energy. The generator can be used to power small electronic devices, such as sensors, or charge household batteries. Literature was reviewed to develop an understanding about the applications, control methods, excitation methods and mechanics of rotating and linear electric machines. A bidirectional, two-sided linear machine was designed with two stator cores and a single mover core. The stator windings and mover winding can be independently excited, allowing for three modes: no mover excitation, DC excited mover, and AC excited mover. Simulations results showed that the magnetic flux generated by DC excited stator cores were concentrated in the centre of the mover core. The use of two stator cores eliminates lateral flux in the mover core when it is not excited, minimising attraction and repulsion forces. Parametric analysis showed that flux cutting occurred in all operation modes, verifying that the generator will produce power when operating. Hardware tests produced an output current when the machine is electrically and mechanically excited, verifying the proposed design.

Water pollution, intensified by the release of hard-to-degrade pollutants, poses severe threats to ecosystems, human health, and economic development. The existing advanced oxidation processes often involve high operational costs and may result in secondary pollution, highlighting the necessity for innovative and more sustainable solutions. To address these challenges, our study introduces a cost-effective and eco-friendly corona discharge barrier plasma discharger for wastewater treatment. Through the central composite design/response surface methodology, a high decolorization rate of 98% of methylene blue (MB) within 10 minutes was achieved by optimizing parameters such as pH and voltage. Furthermore, the mechanisms of the generation of reactive oxygen species via this device was discussed in detail and the degradation pathways of MB were described. Moreover, this device is also very energy-efficient, with a low energy density and electrical energy per order of 0.15 watt/mL and 5.79 kWh/m³/order, respectively. In conclusion, the plasma discharger developed in this study provides a cost-effective and environmentally sustainable solution for dye wastewater treatment. This research contributes significantly to the advancement of sustainable dye wastewater management practices, offering an innovative method that meets both environmental and economic objectives.

Background and Objectives: In recent years, electric scooters have gained widespread popularity as an easy and affordable mode of transport in urban areas worldwide. Simultaneously, trauma centres have observed an increasing number of associated injuries to users. While injury patterns associated with other vehicles are now well-researched, electric scooter-related injuries are a new topic in the literature. Our study aims to investigate the disparities in injury patterns and other critical accident characteristics among bicycle, electric scooter, and scooter riders. Materials and Methods: In this one-year prospective observational study, we examined patients who sustained injuries while riding bicycles, electric scooters, or scooters between April 2021 and March 2022 at Hungary's largest trauma centre in Budapest. During this one-year period, we identified 1938 patients, 1378 cyclists, 370 electric scooters and 190 scooter users. We collected basic demographic information, recorded injury type and severity, time of day the injury occurred, and alcohol intoxication. Results: While 4.6% of cyclists and 5.8% of scooter riders had consumed alcohol, 26.8% of electric scooter riders were intoxicated at the time of their accident. 45.8% of electric scooter-related injuries occurred at night, compared to only 9.2% and 14.1% of bike and scooter-related injuries, respectively. Sober patients were more likely to suffer mild and severe limb injuries (Odds Ratio (OR): 3.85, P = .0001 and OR: 3.26, P = .0001), but less likely to experience mild and severe head injuries (OR: 0.1, P = .0001 and OR: 0.25, P = .0001) than intoxicated patients. Cyclists had significantly fewer cases of severe head trauma than those injured while using electric scooters (OR: 0.34, P = .0166). Conclusions: Severe craniofacial injuries are more common in intoxicated patients and in patients injured using electric scooters.

Abstract: This study investigates the effect of Electric Vehicle Charging Stations (EVCS) on light-duty Electric Vehicle sales and the Total California rebates. Electric Vehicle Charging Stations (EVCS) are infrastructure facilities that allow for the charging of electric vehicles (EVs). I applied the before and after model with California state county using its community-level attributes and used the difference-in-difference design to identify a strategy for estimating the causal effects of these attributes. These attributes include EVCS installations by time, EV sales by time, rebate applications by time, the number of multi-unit housing units, and the median income levels. The empirical ev-idence of this study shows the estimated relationship between public EV charging installation and EV sales overall by community income level, housing density, and other relevant factors, the result shows that EVCSs is highly correlated with light duty Electric Vehicle adoption. For the investors, policymakers, and other stakeholders, this study provides evidence of a threshold of EVCS on Light Duty Electric Vehicle adoption and rebate in California.

In this study, we focused on the eco-driving of electric vehicles (EVs). The target vehicle is an electric bus developed by our research team. Using the parameters of the bus and speed pattern optimization algorithm, we derived the EV eco-driving speed pattern. Compared to eco-driving of internal combustion engine vehicles (ICVs), we found several different characteristics. We verified these characteristics with actual vehicle driving test data of the target bus, and the results confirmed its rationality. The EV eco-driving method can improve electricity consumption by about 10% - 20% under the same average speed.

The inherited ‘EIA’ process at Brexit is based on a ‘Project’ period from Inception tothe start of construction works. The ‘Incompleteness’ of the process covers andidentifies stages that will impact on the environmental cycle: construction period,operational life, de-commissioning and a return to acceptable environmental footprint.A master environment structure-plan framework is required to commence with theupgrading of the complete ‘EIA’ process, embracing separate limbs for the UK’spriority environmental targets for climate change, and other major adverse effectswhich result in serious ‘harm’ to the UK environment. The identification of the processfor ‘incompleteness’ requires effective sustainability, and inclusion of effectivemanagement tools, for the essential ‘monitoring/control/recording’ proceduresthroughout the project life and the natural environmental cycle. This will allow theopportunity for a new approach to a structured ‘Suite of EIAR Directives’, to enable a‘EIAR’ regime that ‘will remain fit and proper for UK purpose’.

In this research, the concept of the instability of tension in Microgrid still becomes the focus of study and purpose. Scrutinously, First-Swing Instability occurs in the system in noted changes with properties of making the system unstable or restore to a state of stability. The latter calls itself as a phenomenon of re-synchronization. Allied to aspects of system instability, it is evident that by connecting fast electric chargers for battery-electric vehicles to the distribution system from microgrids, they increase the necessary basic electrical charges and reduce the stability of the electrical energy system. Transient electrical currents have the characteristic of severely impacting microgrids not prepared in connected states or island of the main system. The occurrences of the electromagnetic incompatibility of the inrush current, due to their unpredictability and intermittent characteristic, have complex identification studies. With the elevation of electricity demand by battery-electric vehicle chargers, concerns about the effects of the integration of the electricity grid increase proportionally. The research described in this article emphasizes the influence of fast chargers’ initialization on the power variation related to the re-synchronization phenomenon and its mitigation of the stability of electricity microgrid. An optimization algorithm based on particle swarm optimization (PSO) implements the development of virtual impedances. The PSO optimization algorithm analyzes all possible operating points and aims to maximize the stability index of microgrid, maintaining reactive energy incompatibilities at the minimum level supported. The fractional objective function facilitates the service to these goals simultaneously. The optimization algorithm is implemented in a case study and the corresponding virtual impedance is incorporated into the microgrid. Voltage levels are verified as a condition in the optimization process, comparing system effectiveness.

Currently, many researchers have an interest in the investigation of the electric field in the fair-weather electric environment, along with its diurnal and seasonal variations across all regions of the world. However, a similar study in the southern part of Siberia has not yet been carried out. In this regard, the study aims to estimate the mean values of the electric field and their variations in the mountain and steppe landscapes using measurement data from the Khakass-Tyva expedition in 2022. The maximum values of positive ion density were noted at the site in the Iyussko-Shirinsky steppe between Belyo and Tus salt lakes in the Khakass-Minusinsk ba-sin. The maximum values of negative ion density were observed at site in the Shol tract in the center part of the Tyva depression. The potential gradient tends to increase with altitude and reaches a maximum in the highlands. The maximum values of the potential gradient were noted in the highlands plateau near the Mongun-Taiga mountain massif and Khindiktig-Khol lake. The diurnal cycles of potential gradient at different observation sites were divided into two groups: 1) a diurnal cycle in the form of a double wave; 2) a daily cycle with a more complex course due to the strong influence of local factors.

Objectives: Evaluate hand-held echocardiography (HHE) performed and interpreted by trained Advanced Practice Providers (APPs) on hospitalized CHF patients for image quality and interpretation, by comparing against expert echocardiographer and SE findings. Background: Congestive heart failure (CHF) is associated with increased hospital admissions and mortality. While standard echocardiogram (SE) is the gold standard for cardiac assessment, it is not readily available. Hospitalized CHF patients require rapid assessment for expedited treatment. Methods: Over 6 months, five trained APPs performed HHE on hospitalized CHF patients and interpreted: a) Left ventricular (LV) size, b) LV ejection fraction (LVEF), and c) right atrial pressure (RAP). The study echocardiographer reviewed and blindly interpreted HHE images and compared with APPs and SE findings. Kappa-statistics determined the degree of agreement between APPs and study echocardiographer interpretation of HHE images and SE. Results: 80 CHF patients [age 73±14 years, 58% males; LVEF (by SE) 45±19%; 36.3% body mass indexes ≥30 kg/m2] were enrolled. HHE interpretation by APPs had good agreement for LVEF (kappa 0.79) with study echocardiographer and SE (kappa 0.74), and good agreement for RAP (kappa 0.67) with study echocardiographer. Correlation between absolute LVEF interpretation by study echocardiographer on HHE and SE was r=0.88 (p<0.0001). Conclusions: Trained APPs obtained diagnostic-quality HHE images and interpreted LV function and RAP in CHF patients, with good agreement with the study echocardiographer. LVEF by HHE correlated with LVEF by SE. Our study suggests trained APPs can use HHE to evaluate LVEF and RAP in CHF patients leading to expedited and optimized treatment.

Electric mobility is one of the ways to contain greenhouse gas and local pollutants emissions in urban areas. Nevertheless, the massive introduction of battery-powered electric vehicles (EVs) brings some concerns related to their energy demand. Modelling vehicle usage and charging behavior is essential for charge demand forecasting and energy consumption estimation. Therefore, it is crucial to understand how the charging decisions of EV owners are influenced by different factors, ranging from the charging infrastructure characteristics to the users’ profiles. This review intends to investigate the approaches used to investigate on charging behavior and highlight trends and differences between the results, remarking on any gaps worthy of further investigation.

In view of the problem of charging and hydrogen filling facilities construction in the transition from fuel vehicles to electric vehicles and hydrogen fuel cell vehicles, in order to meet the electric energy demand of electric vehicles and hydrogen energy demand of hydrogen fuel cell vehicles at the same time, this paper puts forward a method of siting and capacity determination of electric-hydrogen refueling integrated station (EHRIS) based on Voronoi diagram and particle swarm algorithm based on calculating the demand of charging and filling of hydrogen in vehicles. Firstly, OD pair(Origin-Destination) is used to represent the starting point and end point of the car to portray the travel demand of the car, and on the basis of the traffic network model, the shortest driving path of the new energy car is determined by Dijkstra algorithm, and Monte Carlo simulation is used to get the electric-hydrogen energy demand of the car; secondly, the Voronoi diagram is introduced to classify the service scope of the electric-hydrogen charging station to determine the equipment capacity of the electric-hydrogen charging station, while taking into account the electric-hydrogen charging and refueling capacity. Secondly, a Voronoi diagram is introduced to divide the service scope of the EHRIS, determine the capacity of the equipment in the EHRIS, and consider the distance constraints between the sites of EHRIS, so as to make the division of the site and service scope more reasonable. Finally, a dynamic optimal current model framework for distribution networks based on second-order cone relaxation is established, and each element of the active distribution network is planned, so that the distribution network can operate safely and stably after being connected to the EHRIS. With the objective of minimizing the total social cost of EHRIS and considering the constraints of the charging equipment and hydrogen production and injection equipment of the EHRIS, a siting and capacity model to meet the electric-hydrogen energy demand of electric and hydrogen fuel cell vehicles is developed, and solved by a particle swarm algorithm. Finally, the simulation planning is carried out with Sioux Falls city and IEEE33 network, which ensures the stable operation of the power grid while meeting the energy demand of automobiles, and the results verify the effectiveness and feasibility of the proposed method.

The goal of this study was to evaluate the feasibility of methods based on the Worldwide Harmonized Light-Duty Vehicles Test Procedure Brake Cycle to measure brake wear particle emissions for currently used electrified vehicles. Our results indicated that reducing brake friction work reduced brake wear particle emissions. Commercially available, plug-in hybrid electric vehicles reduced emissions by 85% for PM₁₀, 78% for PM_2.5, and 87% for particle numbers (PNs) compared to vehicles with internal combustion engines. Brake friction work showed a linear relationship with PM₁₀ and PM_2.5. Nanoparticle PM emissions tended to increase slightly with regenerative braking, but did not contribute significantly to the overall PM percentage. the emission events of high number concentrations of nuclei mode particles (<20 nm in diameter) in electric vehicle brake assemblies designed for regenerative braking use under high-temperature, high-load braking conditions with full-friction brakes. The nuclei mode particles amplified the PN emissions and led to a high variability. In strict regulatory certification tests, where measurement reproducibility and stability are required, it is appropriate to measure PNs under brake conditions appropriate for the actual use of electric vehicles rather than under full-friction brake conditions or to remove particle measurements smaller than 20 nm.

This article investigates the source of booming noise emanating from the tailgates of electric vehicles, along with proposed strategies to mitigate it. This study involved the measurement of booming noises during on-road vehicle tests to pinpoint their origins. Additionally, operational deflection shapes (ODS) were extracted from the tailgate vibration signals to gain insight into its dynamic behavior. Modal tests were conducted on the tailgate to determine its dynamic characteristics and compared with driving test results to reveal the mechanism responsible for tailgate-induced booming noise. It was established that such noise is primarily due to the tailgate modes resulting from a combination of rigid body motion in the fore-aft direction and deformation in the central section of the panel. An analytical model of the tailgate was developed using commercial finite element analysis software to propose measures for reducing booming noise. Experimental findings validated the model accuracy. Structural enhancements were implemented to enhance the panel stiffness and improve the connection between the vehicle and tailgate via bushings to dampen the booming noise resulting from tailgate motion. Under random force inputs, analytical results demonstrated a 13.8% reduction in maximum deformation in the tailgate model in the improved structural configuration with increased panel stiffness.

Lithium-ion batteries with improved energy densities have made understanding the Solid Electrolyte Interphase (SEI) generation mechanisms that cause mechanical, thermal, and chemical failures more complicated. SEI processes reduce battery capacity and power. Thus, a review of this area's understanding is important. It is essential to know how batteries degrade in EVs to estimate battery lifespan as it goes, predict, and minimize losses, and determine the ideal time for a replacement. Lithium-ion batteries used in EVs mainly suffer two types of degradation: calendar degradation and cycling degradation. Despite the existence of several existing works in the literature, several aspects of battery degradation remain unclear or have not been analyzed in detail. This work presents a systematic review of existing works in the literature. The results of the present investigation provide insight into the complex relationships among various factors affecting battery degradation mechanisms. Specifically, this systematic review examined the effects of time, side reactions, temperature fluctuations, high charge/discharge rates, depth of discharge, mechanical stress, thermal stress, and the voltage relationship on battery performance and longevity. The results revealed that these factors interact in complex ways to influence the degradation mechanisms of batteries. For example, high charge currents and deep discharges were found to accelerate degradation, while low temperatures and moderate discharge depths were shown to be beneficial for battery longevity. Additionally, the results showed that the relationship between cell voltage and State-of-Charge (SOC) plays a critical role in determining the rate of degradation. Overall, these findings have important implications for the design and operation of battery systems, as they highlight the need to carefully manage a range of factors to maximize battery performance and longevity. The result is an analysis of the main articles published in this field in recent years. This work aims to present new knowledge about fault detection, diagnosis, and management of lithium-ion batteries based on battery degradation concepts. The new knowledge is presented and discussed in a structured and comprehensive way.

This study aimed to investigate the effects of jet-milling on lutein extraction contents of spinach powder (SP) and pulsed electric fields as a non-thermal pasteurization technology on spinach juice (SJ) to preserve lutein contents. SP particles were divided into SP-coarse (Dv50 = 315.2 μm), SP-fine (Dv50 = 125.20 μm), and SP-superfine (Dv50 = 5.59 μm) fractions and SP-superfine was added to SJ due to the highest contents of lutein extract. The PEF and thermal treatment were applied to evaluate the effects of preserving the lutein content of PEF during storage (25 days). The juice after being designated to untreated (no pasteurization), PEF1,2 (SJ treated with PEF 20 kV/cm 110 kJ/L, 150 kJ/L), Thermal1,2 (SJ treated with 90 ℃, 10 min and 121 ℃, 15 min). The sizes and surface shapes of superfine SP particles were more homogeneous and smoother than the other samples. SJ made with SP-superfine and treated by PEF had the highest lutein content and antioxidant activities among the group. Complex of jet-milling and PEF pasteurization could be great potential technologies to improve the lutein contents of lutein-enriched juice in the food industry.

Hybrid electric vehicles are certainly one of the key solutions for improving fuel efficiency and reducing emissions, especially in special vehicle application and with the use of CO2 neutral fuels. Determining the energy management strategy and finding the optimal solution with regard to the aforementioned goals re-mains the one of the main challenges in the design of HEV. This paper presents a new vehicle modeling method, with an emphasis on HEVs, which is based on the frequency analysis of emissions and consumption according to the current specific traction power of the vehicle. The evaluation of the newly introduced model in the RDE, NEDC and WLTP cycle was performed and the results were compared with the standard verified vehicle model that was created in AVL's CruiseM software package. Positive traction energies have positive deviations of between 0.35% and 2.85%. The largest deviation in CO2 emissions was recorded for the HEV model in the RDE cycle and in the non-hybrid model in the WLTP cycle of 3.79% and 4.4% respectively, all other combinations of cycle and vehicles had deviations of up to about 1%. As expected, the largest relative deviations were recorded for NOx emissions from 0.13% to 9.62% for HEV in the WLTP cycle.

This study delves into the atmospheric corrosion behavior of chromium-free complex-phase steel (CP), specifically investigating the influence of wet/dry frequency and ratio in cyclic corrosion tests (CCT). The study employs a modified ISO 14993 standard CCT method, which involves salt spray, dry, and wet stages. After 15 and 30 CCT cycles, mass loss, maximum corrosion depth, and corrosion products were analyzed to gain insights into corrosion mechanisms. In general, increasing the frequency and wet/dry stage ratio in CCT extends the time for autocatalytic reactions to occur, leading to accelerated localized CP corrosion and increased pitting factors. However, as the rust layer thickens, uniform corrosion may also intensify, so careful considerations are necessary. This study underscores the importance of controlling the frequency and ratio of wet/dry stages in CCT for effectively analyzing localized corrosion behavior in specimens.

In its prefusion state, the SARS-CoV-2 Spike protein (similarly to other class I viral fusion proteins) is metastable, which is considered to be an important feature for optimizing or regulating their functions. After the binding process of its S1 subunit (S1) with the ACE2, the Spike protein (S) suffers a dramatic conformational change where S1 splits from the S2 subunit, which then penetrates the membrane of the host cell, promoting the fusion of the viral and cell membranes. This results in the infection of the host cell. In a previous work, we showed -using large scale molecular dynamics simulations- that the application of external electric fields (EF) induces drastic changes and damage in the receptor-binding domain (RBD) of the wild type Spike protein, as well of the Alpha, Beta and Gamma variants, leaving a structure which cannot be recognized any more by ACE2. In this work, we first extend the study to the Delta and Omicron variants and confirm the high sensitivity and extreme vulnerability of S to moderate EF (as weak as 104 V m-1), but, more importantly, we also show that, in contrast, the postfusion state of the spike protein does not suffer structural damage even if electric field intensities four orders of magnitude higher are applied. These results provide a solid scientific basis to confirm the prefusion state metastability roots of the SARS-CoV-2 Spike protein susceptibility to be damaged by EF. After the virus docks to the ACE2 receptor, the stable and robust postfusion conformation develops, which exhibits a similar resistance to EF (damage threshold higher than 108 V m-1) like most globular proteins.