Search Results (563)

Mesenchymal stromal cells (MSCs) are intensively investigated in oncology owing to their intrinsic tumor-homing ability and capacity to deliver therapeutic agents directly into the tumor microenvironment (TME). Recent advances in genetic engineering have enabled precise modification of MSCs, allowing controlled expression of therapeutic genes and other cargo delivery, thus improving targeting efficiency. As cellular carriers, MSCs have been engineered to transport oncolytic viruses, suicide genes in gene-directed enzyme prodrug therapy (GDEPT), multifunctional nanoparticles, and therapeutic factors such as IFN-β or TRAIL, while engineered MSC-derived extracellular vesicles (MSC-EVs) offer a promising cell-free alternative. These strategies increase intratumoral drug concentration, amplify bystander effects, and synergize with standard therapies while reducing systemic toxicity. Conversely, accumulating evidence highlights the tumor-promoting properties of MSCs: once recruited by inflammatory and hypoxic cues, they remodel the tumor microenvironment by stimulating angiogenesis, suppressing immune responses, differentiating into cancer-associated fibroblasts, and promoting epithelial-to-mesenchymal transition (EMT), ultimately enhancing invasion, metastasis, and therapy resistance. This duality has sparked both enthusiasm and concern in the oncology field. The present review outlines the paradoxical role of MSCs in oncology—ranging from their potential to promote tumor growth to their emerging utility as vehicles for targeted drug delivery. By highlighting both therapeutic opportunities and biological risks, we aim to provide a balanced perspective on how MSC-based strategies might be refined, optimized, and safely integrated into future cancer therapies. Full article

Worldwide the adoption of electric vehicles (EVs) is recognized as a key strategy for reducing transport-related greenhouse gas (GHG) emissions, a major contributor to global warming and climate change. The objective of this pilot study is to examine the key variables that might have influenced electric vehicle (EV) purchase decisions among current EV owners and how they are aligned or different for the prospective EV owners in North Carolina (NC). By adopting a web-based survey for data collection, the study specifically aims to identify economic, demographic, environmental, and commuting behaviors, along with existing government policies and incentives that might motivate consumer choices regarding EV adoption. Most existing EV owners who participated in the survey identified themselves as college-educated White men with USD 100 K or higher income, have more than two cars, commute more than 30 min, and live in single-family homes with EV charging. In contrast, among non-EV owners who plan to adopt an EV within the next three years, a significant proportion are non-White, women, and earn USD 50,000 or less annually. While home charging is important to both current EV owners and non-EV owners, EV incentive policies and proximity to public changing stations are found to be more important to non-EV owners’ decision to adopt EVs. A reasonable conclusion from this research is that expanding EV-friendly policies, incentives, and infrastructure will encourage first-time EV ownership in NC while providing deeper insights into the dynamics of sociodemographic among both EV owners and non-EV owners. Full article

This paper presents a comprehensive methodology to forecast the daily energy demand associated with recharging private electric vehicles in urban areas. The approach is based on plausible scenarios regarding the penetration of battery-powered vehicles and the availability of charging infrastructure. Accurate space and time forecasting of charging activities and power requirements is a critical issue in supporting the transition from conventional to battery-powered vehicles for urban mobility. This technological shift represents a key milestone toward achieving the zero-emissions target set by the European Green Deal for 2050. The methodology leverages Floating Car Data (FCD) samples. The widespread use of On-Board Units (OBUs) in private vehicles for insurance purposes ensures the methodology’s applicability across diverse geographical contexts. In addition to FCD samples, the estimation of charging demand for private electric vehicles is informed by a large-scale, detailed survey conducted by ENEA in Italy in 2023. Funded by the Ministry of Environment and Energy Security as part of the National Research on the Electric System, the survey explored individual charging behaviors during daily urban trips and was designed to calibrate a discrete choice model. To date, the methodology has been applied to the Metropolitan Area of Rome, demonstrating robustness and reliability in its results on two different scenarios of analysis. Each demand/supply scenario has been evaluated in terms of the hourly distribution of peak charging power demand, at the level of individual urban zones or across broader areas. Results highlight the role of the different components of power demand (at home or at other destinations) in both scenarios. Charging at intermediate destinations exhibits a dual peak pattern—one in the early morning hours and another in the afternoon—whereas home-based charging shows a pronounced peak during evening return hours and a secondary peak in the early afternoon, corresponding to a decline in charging activity at other destinations. Power distributions, as expected, sensibly differ from one scenario to the other, conditional to different assumptions of private and public recharge availability and characteristics. Full article

This study investigates the accelerating adoption of electric vehicles (EVs) integrated with residential rooftop solar and battery storage in Australia, employing Actor–Network Theory (ANT) to elucidate socio-technical dynamics. Through purposive sampling, semi-structured interviews with 15 EV industry stakeholders were conducted and analysed using NVivo 14. Findings revealed EV–solar–storage adoption as a negotiated process shaped by alignments among human and non-human actors, structured by three interdependent obligatory passage points. First, technological integration hinges on interoperability among inverters, smart chargers, EV supply equipment, batteries, and home energy management systems. These are constrained by factors like off-street parking availability. Second, policy and market frameworks require clear interconnection standards, bidirectional charging protocols, streamlined approvals, and targeted incentives. Third, consumer engagement depends on energy literacy, equitable access for renters, and daytime charging infrastructure. Smart and bidirectional charging positions EVs as flexible energy assets, yet gaps in standards and awareness destabilise networks. This ANT-framed study offers a practice-oriented model for clean mobility integration, proposing targeted interventions such as device compatibility standards, equitable policies, and education to maximise environmental and economic benefits at household and system levels. Full article

Mixed-use development (MXD) is crucial for urban planning and travel. The COVID-19 outbreak had a significant impact on travel behaviour and MXD projects worldwide, particularly in high-income countries. However, limited studies have explored the predictors of MXD usage and travel patterns in low- and middle-income countries, including Malaysia, and how these events were affected by COVID-19. Using the Rowley and extended Hopenbrouwer and Louw models, this study investigates the travel patterns within MXD premises, their associated factors, and residents’ perspectives of internal and external trips before and during COVID-19 in Klang Valley, Malaysia. A mixed-method study was conducted by using a validated survey and performing a structured interview with MXD residents. A total of 134 and 52 respondents participated in the survey and qualitative interviews, respectively. Data were analysed using descriptive statistics, logistic regression models, and thematic analysis. A significantly higher proportion of MXD respondents engaged in external travel compared to internal travel before and during COVID-19. Before COVID-19, external travel was significantly higher among younger residents, government servants, higher-income earners, and those who owned a car and had recently moved to MXD areas. The odds of internal travel were significantly higher among private-sector employees, students, and low-income earners. During the pandemic, external travel frequency was significantly higher among male residents, older residents, government servants, high-income earners, and those with multiple vehicles. Residents with more parking lots tended to travel less internally compared to those with fewer parking lots allocated. Qualitative analyses revealed that cost-saving, convenience and comfort, social lifestyle, health and well-being, and green environment were the factors that shaped MXD residents’ perceived benefits of trip internalisation. Meanwhile, the barriers to internal trips included the lack of infrastructure, poor management, lifestyle activities/individual factors, and environmental factors. The recommended strategies to reduce external trips were to ensure diversified services and accessibility, inclusiveness in planning activities, promoting social interaction, and work-from-home policies. These findings reflect the strategies that can be incorporated to reduce external trips generated by MXD and enhance effective traffic management. Full article

The Internet of Things (IoT) has become deeply embedded in modern society, enabling applications across smart homes, healthcare, industrial automation, and environmental monitoring. However, as billions of interconnected devices continuously collect and exchange sensitive data, privacy and security concerns have escalated. This survey systematically reviews the state-of-the-art privacy-preserving techniques in IoT systems, emphasizing approaches that protect user data during collection, transmission, and storage. Peer-reviewed studies from 2016 to 2025 and technical reports were analyzed to examine applied mechanisms, datasets, and analytical models. Our analysis shows that blockchain and federated learning are the most prevalent decentralized privacy-preserving methods, while homomorphic encryption and differential privacy have recently gained traction for lightweight and edge-based IoT implementations. Despite these advancements, challenges persist, including computational overhead, limited scalability, and real-time performance constraints in resource-constrained devices. Furthermore, gaps remain in cross-domain interoperability, energy-efficient cryptographic designs, and privacy solutions for Unmanned Aerial Vehicle (UAV) and vehicular IoT systems. This survey offers a comprehensive overview of current research trends, identifies critical limitations, and outlines promising future directions to guide the design of secure and privacy-aware IoT architectures. Full article

The increasing penetration of renewable energy and electric vehicles (EVs) has intensified the need for grid-forming (GFM) inverters capable of supporting frequency and voltage stability. Virtual Oscillator Control (VOC) has recently emerged as a promising time-domain GFM strategy due to its fast dynamics and autonomous synchronisation capability. This paper presents a comprehensive analysis of recent VOC developments, focusing on the Andronov–Hopf Oscillator (AHO) and its variants. A comparative overview of different VOC structures highlights their capabilities in providing essential services such as dispatchability, fault ride-through (FRT), virtual inertia, and damping. A generalised small-signal state-space model is developed to assess the influence of virtual inertia, grid impedance, and control parameters on transient performance, which is essential for optimal parameter design and controller tuning in various applications. Experimental validation using a 2.5 kVA single-phase inverter shows excellent agreement with theoretical predictions. The results confirm that while increased virtual inertia enhances frequency stability, it also introduces oscillations that can be effectively mitigated through damping enhancement. Furthermore, the experiments demonstrate that advanced AHO-based strategies successfully deliver vehicle-to-grid (V2G) and vehicle-to-home (V2H) services, confirming their practical applicability in future EV-integrated and renewable-rich power systems. Full article

Operation of vehicle–trailer combinations is currently popular throughout many countries. Connecting a trailer to a passenger car increases the car’s utility value because it is possible to transport more goods over shorter or longer distances. Trailers are also popular as caravans, which provide a home on wheels during holiday periods. As a trailer is connected to a towing vehicle by means of a spherical joint from the mechanics’ point of view, a vehicle–trailer combination has significantly different driving properties in comparison with a sole vehicle. These differences are manifested mainly while driving in a curve as lower stability of the vehicle. In this case, the lower stability is considered an uncontrolled sway motion. This study is focused on researching the driving stability of a vehicle–trailer combination regarding the sway motion problem. The research is fully performed by means of simulation computations in a commercial multibody simulation software. The investigated vehicle–trailer combination consists of an SUV passenger car and a single-axle goods trailer. Two model driving maneuvers are investigated, namely bypassing an obstacle in a lane and changing lanes on a road. Simulation computations are performed for chosen loads of the trailer and for a different position of the center of gravity of the load in the single-axle trailer. The performed research has proven that the applied simulation computations represent a robust tool to investigate real tasks related to vehicle safety without performing expensive and dangerous tests. Very important findings include identifying the proper position of the center of gravity of the load on the trailer to ensure safe driving properties for driving maneuvers that could pose potential danger during real operation. Full article

Germany’s energy transition to a higher share of renewable energy sources (RESs) is characterized by decentralization, with citizens, cooperatives, SMEs, and municipalities playing a central role. As of early 2025, private individuals own a significant share of renewable energy installations, particularly PV panels, which corresponds to approximately half of the total installed PV power. This trend is driven by physical, technological, and societal factors. Technological advances in battery storage and sector coupling are expected to further decentralize the energy system. Thereby, the electrification of mobility, particularly through electric vehicles (EVs), offers significant storage potential and grid-balancing capabilities via bidirectional charging, although it also introduces challenges, especially for distribution grids during peak loads. Within this work we present a detailed digital twin of the entire distribution grid of the rural German municipality of Wüstenrot. Using grid operator data and transformer measurements, we evaluate strategic expansion scenarios for electromobility, PV and heat pumps based on existing infrastructure and predicted growth in both public and private sectors. A core focus is the intelligent integration of EV charging infrastructure to avoid local overloads and to optimise grid utilisation. Thereby municipally planned and privately driven expansion scenarios are compared, and grid bottlenecks are identified, proposing solutions through charge load management and targeted infrastructure upgrades. This study of Wüstenrot’s low-voltage grid reveals substantial capacity reserves for future integration of heat pumps, electric vehicles (EVs), and photovoltaic systems, supporting the shift to a sustainable energy system. While full-scale expansion would require significant infrastructure investment, mainly due to widespread EV adoption, simple measures like temporary charge load reduction could cut grid stress by up to 51%. Additionally, it is shown that bidirectional charging offers further relief and potential income for EV owners. Full article

Hepatocellular carcinoma (HCC) ranks as the second most lethal malignancy worldwide, presenting formidable therapeutic challenges including tumor heterogeneity, complex microenvironment, and inefficient drug delivery. Conventional therapies such as surgery, chemotherapy, and immunotherapy are limited by systemic toxicity, drug resistance, and poor targeting specificity. Mesenchymal stem cells (MSCs) have emerged as promising drug delivery vehicles, leveraging their innate tumor-homing capacity, immunomodulatory properties, and exosome-mediated cargo transport. Preclinical studies demonstrate that MSC-based systems triple drug accumulation in tumors and synergize with immunotherapy, extending survival in HCC models. This review systematically examines recent advances in MSC-based delivery systems for HCC, focusing on engineering strategies to enhance targeting precision and controlled drug release, including genetic modification, exosome engineering, and stimuli-response systems. Despite progress, challenges such as MSC heterogeneity and scalable production persist. Emerging solutions like single-cell RNA sequencing for subpopulation selection and 3D bioprinting for standardized culture are highlighted. This work provides a roadmap for developing MSC-based precision therapies, bridging translational gaps in HCC treatment. Full article

This paper presents an intelligent hybrid framework for short-term energy consumption forecasting and real-time energy management in photovoltaic (PV)-integrated smart homes with Vehicle-to-Home (V2H) systems, tailored to the Tunisian context. The forecasting module employs an Attention-based Long Short-Term Memory (LSTM) neural network, whose hyperparameters (learning rate, hidden units, temporal window size) are optimized using the Harris Hawks Optimization (HHO) algorithm. Simulation results show that the proposed LSTM-HHO model achieves a Root Mean Square Error (RMSE) of 269 Wh, a Mean Absolute Error (MAE) of 187 Wh, and a Mean Absolute Percentage Error (MAPE) of 9.43%, with R² = 0.97, substantially outperforming conventional LSTM (RMSE: 945 Wh, MAPE: 51.05%) and LSTM-PSO (RMSE: 586 Wh, MAPE: 28.72%). These accurate forecasts are exploited by the Energy Management System (EMS) to optimize energy flows through dynamic appliance scheduling, HVAC load shifting, and coordinated operation of home and EV batteries. Compared with baseline operation, PV self-consumption increased by 18.6%, grid reliance decreased by 25%, and household energy costs were reduced by 17.3%. Cost savings are achieved via predictive and adaptive control that prioritizes PV utilization, shifts flexible loads to surplus periods, and hierarchically manages distributed storage (home battery for short-term balancing, EV battery for extended deficits). Overall, the proposed LSTM-HHO-based EMS provides a practical and effective pathway toward smart, sustainable, and cost-efficient residential energy systems, contributing directly to Tunisia’s energy transition goals. Full article

Tamibarotene (AM80) is an agonist of retinoic acid receptor alpha. It is licensed in Japan for the treatment of acute promyelocytic leukemia. Results from preclinical models suggest that tamibarotene might also be effective in the treatment of diverse autoimmune diseases. The effect of tamibarotene on autoimmune diseases of the skin, however, has not been explored. We therefore examined the effect of tamibarotene on disease in the antibody-transfer mouse model of bullous pemphigoid (BP)-like epidermolysis bullosa acquisita (EBA), a prototypical example for pemphigoid diseases. Pemphigoid diseases are a group of autoimmune blistering skin diseases driven by autoantibodies and the recruitment and activity of granulocytes in the dermis. In sharp contrast to its effect in models of other autoimmune diseases, tamibarotene aggravated EBA pronouncedly. At the peak of disease, skin inflammation in tamibarotene-treated mice involved, on average, 1.6-fold more of the total body surface compared to vehicle-treated mice. Tamibarotene markedly reduced the recruitment of regulatory T cells (T_regs) into the dermis. This blunted the counterregulatory mechanisms that normally curb skin inflammation in this model. The effect aligns with previous reports describing tamibarotene-mediated downregulation of skin-homing receptors on T_regs. In addition, tamibarotene prolonged the responsiveness of aging neutrophils to immune complexes in vitro, providing another mechanism that may exacerbate EBA. Collectively, our results suggest that tamibarotene may elicit detrimental effects in patients with EBA by abolishing the recruitment of T_regs into skin. This warrants great caution when using tamibarotene in patients with EBA and possibly other pemphigoid diseases. Full article

This paper proposes a household energy management system for all-electric households, focusing on the interplay between cost savings and occupant comfort through an implicit demand response programme. A sequential multi-objective optimisation model is developed based on the lexicographic approach, allowing for the effective prioritisation of objectives. The model optimally schedules a diverse range of electricity demands using real-world data from a Norwegian pilot household to evaluate its unique flexibility potential, while remaining adaptable for other regions. This includes integrating thermal and non-thermal demands with electric mobility via vehicle-to-home enabled electric vehicle charger. This approach achieves significant cost savings on energy bills and enhances user comfort across aggregated comfort indicators. Multiple scenarios are designed to evaluate the performance of the proposed demand response under diverse pricing mechanisms. Results indicate that transitioning from variable pricing to fixed pricing can lead to lower average electricity costs and higher average user comfort. The analysis reveals that prioritising occupant comfort can substantially increase electricity demand, resulting in a nearly fourfold rise in average annual expenses, while also leading to a decrease in self-consumption and self-sufficiency. Additionally, the study illustrates how grid tariff adjustments can benefit households and support the development of local renewable energy. Full article

A multi-port conversion system that connects photovoltaic (PV) arrays, battery energy storage (BES), and an electric vehicle (EV) to a single-phase grid offers a flexible solution for smart homes. By integrating Vehicle-to-Grid (V2G) and Vehicle-to-Home (V2H) technologies, the system supports bidirectional energy flow, optimizing usage, improving grid stability, and supplying backup power. The proposed four-port converter consists of an interleaved bidirectional DC-DC converter for high-voltage BES, a bidirectional buck–boost DC-DC converter for EV charging and discharging, a DC-DC boost converter with MPPT for PV, and a grid-tied inverter. Its non-isolated structure ensures high efficiency, compact design, and fewer switches, making it suitable for residential applications. A state-of-charge (SoC)-based power management strategy coordinates operation among PV, BES, and EV in both on-grid and off-grid modes. It reduces reliance on EV energy when supporting V2G and V2H, while SoC balancing between BES and EV extends lifetime and lowers current stress. A 7.5 kVA system was simulated in MATLAB/Simulink to validate feasibility. Two scenarios were studied: PV, BES, and EV with V2G supporting the grid and PV, BES, and EV with V2H providing backup power in off-grid mode. Tests under PV fluctuations and load variations confirmed the effectiveness of the proposed design. The system exhibited a fast transient response of 0.05 s during grid-support operation and maintained stable voltage and frequency in off-grid mode despite PV and load fluctuations. Its protection scheme disconnected overloads within 0.01 s, while harmonic distortions in both cases remained modest and complied with EN50610 standards. Full article

The rapid development and spread of electric vehicles is fundamentally revolutionizing transportation in the European Union and around the world. With the diffusion of electric vehicles, issues related to the batteries that power them have also become more prominent. Given that the production of these components is one of the most environmentally burdensome processes, the need for their secondary use has quickly become evident. Based on the Eurostat database, this article analyzes the indicators that may influence the prospects for the secondary use of batteries. It examines the relationship between the GDP (Gross Domestic Product) of European Union member states and the number of electric vehicles, the share of renewable energy, and household electricity consumption. The results show that electric vehicle penetration and the use of renewable energy vary greatly among EU member states. The second part of the article examines battery data from an electric vehicle, the solar panel production of a family home, and electricity consumption using a linear programming model on a monthly basis. The objective function of the model makes it possible to minimize the amount of energy purchased from the grid. The resulting savings can be quantified. The article focuses on providing a foundation for the opportunities offered by the secondary-use battery market. Full article