Search Results (437)

Alzheimer’s disease (AD) is increasingly recognized as a multifactorial disorder driven by a combination of disruptions in proteostasis and organelle communication. The 2020 Lancet commission reported that approximately 10 million people worldwide were affected by AD in the mid-20th century. AD is the most prevalent cause of dementia. By early 2030, the global cost of dementia is projected to rise by USD 2 trillion per year, with up to 85% of that cost attributed to daily patient care. Several factors have been implicated in the progression of neurodegeneration, including increased oxidative stress, the accumulation of misfolded proteins, the formation of amyloid plaques and aggregates, the unfolded protein response (UPR), and mitochondrial–endoplasmic reticulum (ER) calcium homeostasis. However, the exact triggers that initiate these pathological processes remain unclear, in part because clinical symptoms often emerge gradually and subtly, complicating early diagnosis. Among the early hallmarks of neurodegeneration, elevated levels of reactive oxygen species (ROS) and the buildup of misfolded proteins are believed to play pivotal roles in disrupting proteostasis, leading to cognitive deficits and neuronal cell death. The accumulation of amyloid-β (Aβ) plaques and tau neurofibrillary tangles is a characteristic feature of AD. These features contribute to chronic neuroinflammation, which is marked by the release of pro-inflammatory cytokines and chemokines that exacerbate oxidative stress. Given these interconnected mechanisms, targeting stress-related signaling pathways, such as oxidative stress (ROS) generated in the mitochondria and ER, ER stress, UPR, and cytosolic chaperones, represents a promising strategy for therapeutic intervention. This review focuses on the relationship between stress chaperone responses and organelle function, particularly the interaction between mitochondria and the ER, in the development of new therapies for AD and related neurodegenerative disorders. Full article

This paper presents a behavior tree-based control architecture for end-to-end mission planning of an autonomous underwater vehicle (AUV) collaborating with a moving mothership in dynamic marine environments. The framework is organized into three phases—prepare and launch, execute the mission, and retrieval and docking—each encapsulated in an independent sub-tree to enable modular error handling and seamless phase transitions. The AUV and mothership operate entirely underwater, with real-time docking to a moving platform. An extended Kalman filter (EKF) fuses data from inertial, pressure, and acoustic sensors for accurate navigation and state estimation. At the same time, obstacle avoidance leverages forward-looking sonar (FLS)-based potential field methods to react to unpredictable underwater hazards. The system is implemented on the robot operating system (ROS) and validated in the Stonefish physics engine simulator. Simulation results demonstrate reliable mission execution, successful dynamic docking under communication delays and sensor noise, and robust retrieval from injected faults, confirming the validity and stability of the proposed architecture. Full article

Millimeter-wave frequencies are crucial for meeting the high-capacity, low-latency demands of 5G communication systems, thereby driving the need for compact, high-gain antenna arrays capable of efficient beamforming. This paper presents the design, simulation, fabrication, and experimental validation of a compact, high-efficiency 1 × 6 linear series-fed microstrip patch antenna array for 5G millimeter-wave communication operating at 28 GHz. The proposed antenna is fabricated on a low-loss Rogers RO3003 substrate and incorporates an integrated symmetric two-way microstrip power divider to ensure balanced feeding and phase uniformity across elements. The antenna achieves a simulated peak gain of 11.5 dBi and a broad simulated impedance bandwidth of 30.21%, with measured results confirming strong impedance matching and a return loss better than −20 dB. The far-field radiation patterns demonstrate a narrow, highly directive beam in the E-plane, and the H-plane results reveal beam tilting behavior, validating the antenna’s capability for passive beam steering through feedline geometry and element spacing (~0.5λ). Surface current distribution analysis confirms uniform excitation and efficient radiation, further validating the design’s stability. The fabricated prototype shows excellent agreement with the simulation, with minor discrepancies attributed to fabrication tolerances. These results establish the proposed antenna as a promising candidate for applications requiring compact, high-gain, and beam-steerable solutions, such as 5G mm-wave wireless communication systems, point-to-point wireless backhaul, and automotive radar sensing. Full article

Particulate matter (PM), mainly PM_0.5, represents a significant concern for human health, particularly relating to lung homeostasis, and more research is required to ascertain its tissue tropism and the molecular pathways involved. In this study, we first focus on classical in vitro toxicological endpoints (cytotoxicity and cell growth) in human bronchial and alveolar epithelial cell lines mimicking the two pulmonary target tissues. Air samples were collected in five Italian cities (Brescia, Lecce, Perugia, Pisa, Turin) during winter and spring. To better decipher the PM_0.5 effects on pulmonary cells, a further winter sampling was performed in Brescia, and studies were extended to assess tumour promotion, oxidative stress, and the activity of Matrix metalloproteases (MMP). The results confirmed that the effect of air pollution is linked to the seasons (winter is usually more cytotoxic than spring) and is correlated with the peculiar characteristics of the cities studied (meteoclimatic conditions, economic/anthropogenic activities). Alveolar cells were often less sensitive than bronchial cells. All PM samples from Brescia inhibited intercellular communication mediated by gap junctions (GJIC), increased the total content in glutathione, and decreased the reduced form of glutathione, whereas the Reactive Oxygen Species (ROS) content was almost constant. Long-term treatments at higher doses of PM decreased MMP2 and MMP9 activity. Taken together, the results confirmed that PM is cytotoxic and can potentially act as tumour promoters, but the mechanisms involved in oxidative stress and lung homeostasis are dose- and time-dependent and quite complex. Full article

In social networks like community Question-Answering (cQA) services, members interact with each other by asking and answering each other’s questions. This way they find counsel and solutions to very specific real-life situations. Thus, it is safe to say that community fellows log into this kind of social network with the goal of satisfying information needs that cannot be readily resolved via traditional web searches. And in order to expedite this process, these platforms also allow registered, and many times unregistered, internauts to browse their archives. As a means of encouraging fruitful interactions, these websites need to be efficient when displaying contextualized/personalized material and when connecting unresolved questions to people willing to help. Here, demographic factors (i.e., gender) together with frontier deep neural networks have proved to be instrumental in adequately overcoming these challenges. In fact, current approaches have demonstrated that it is perfectly plausible to achieve high gender classification rates by inspecting profile images or textual interactions. This work advances this body of knowledge by leveraging lexicalized dependency paths to control the level of abstraction across texts. Our qualitative results suggest that cost-efficient approaches exploit distilled frontier deep architectures (i.e., DistillRoBERTa) and coarse-grained semantic information embodied in the first three levels of the respective dependency tree. Our outcomes also indicate that relative/prepositional clauses conveying geographical locations, relationships, and finance yield a marginal contribution when they show up deep in dependency trees. Full article

Smart farming is an agricultural technology integrating advanced technology such as cloud computing, Artificial Intelligence (AI), the Internet of Things (IoT), and robots into traditional farming. Smart farming can help farmers by increasing agricultural production and managing resources efficiently. However, malicious attackers can attempt security attacks because communication in smart farming is conducted via public channels. Therefore, an authentication scheme is necessary to ensure security in smart farming. In 2024, Rahaman et al. proposed a privacy-centric authentication scheme for smart farm monitoring. However, we demonstrated that their scheme is vulnerable to stolen mobile device, impersonation, and ephemeral secret leakage attacks. This paper suggests a secure and privacy-preserving scheme to resolve the security defects of the scheme proposed by Rahaman et al. We also verified the security of our scheme through “the Burrows-Abadi-Needham (BAN) logic”, “Real-or-Random (RoR) model”, and “Automated Validation of Internet Security Protocols and Application (AVISPA) tool”. Furthermore, a performance analysis of the proposed scheme compared with related studies was conducted. The comparison result proves that our scheme was more efficient and secure than related studies in the smart farming environment. Full article

Open habitats in forests perform several important functions. In addition to enriching biodiversity, they have an impact on the diversification of the forest landscape, and through complex processes and trophic relationships, they provide greater sustainability in forest communities. It turns out that they are also important not only for the functioning of nature, but also due to their regenerative properties, through which people can improve their well-being and recover their mental balance. The purpose of this study was to determine whether and to what extent mid-forest open dunes and wetlands are able to provide people with feelings of relaxation and mental renewal. The study was conducted in June 2024 in one of the forest complexes located in the suburban zone of Warsaw. The experiment was conducted with the participation of 52 young adult volunteers. The experiment used a pre–posttest method. The subjects’ mood and well-being were determined using four psychological questionnaires: the Positive and Negative Affect Schedule (PANAS), Restorative Outcome Scale (ROS), Subjective Vitality Scale (SVS), and Profile of Mood States (POMSs). The key findings from the research conducted are as follows: compared to the control sample (before entering the forest), exposure to all three variants of greenery had a restorative effect on the experimental participants; the water environment had the most favorable effect compared to the control sample (before entering the forest); and exposure to this environment provided the greatest increase in positive feelings and the greatest decrease in negative feelings. Research has shown that areas important for preserving forest biodiversity are also important for humans because of their high restorative properties. Preserving non-forest enclaves in forests and promoting their regenerative values for humans can be one nature-based solution to improve people’s health and well-being, especially for people living in urban areas. Full article

Integrated photonics is a transformative technology for enhancing communication and computation in Cloud and Fog computing networks. Photonic integrated circuits (PICs) enable significant improvements in data-processing speed, energy-efficiency, scalability, and latency. In Cloud infrastructures, PICs support high-speed optical interconnects, energy-efficient switching, and compact wavelength division multiplexing (WDM), addressing growing data demands. Fog computing, with its edge-focused processing and analytics, benefits from the compactness and low latency of integrated photonics for real-time signal processing, sensing, and secure data transmission near IoT devices. PICs also facilitate the low-loss, high-speed modulation, transmission, and detection of RF signals in scalable Radio-over-Fiber (RoF) links, enabling seamless IoT integration with Cloud and Fog networks. This results in centralized processing, reduced latency, and efficient bandwidth use across distributed infrastructures. Overall, integrating photonic technologies into RoF, Fog and Cloud computing networks paves the way for ultra-efficient, flexible, and scalable next-generation network architectures capable of supporting diverse real-time and high-bandwidth applications. This paper provides a comprehensive review of the current state and emerging trends in integrated photonics for IoT sensors, RoF, Fog and Cloud computing systems. It also outlines open research opportunities in photonic devices and system-level integration, aimed at advancing performance, energy-efficiency, and scalability in next-generation distributed computing networks. Full article

Knowledge of ionospheric plasma altitudinal distribution is crucial for the effective operation of radio wave propagation, communication, and navigation systems. High-frequency sounding radars—ionosondes—provide unbiased benchmark measurements of ionospheric plasma density due to a direct relationship between the frequency of sound waves and ionospheric electron density. But ground-based ionosonde observations are limited by the F2 layer peak height and cannot probe the topside ionosphere. GNSS Radio Occultation (RO) onboard Low-Earth-Orbiting satellites can provide measurements of plasma distribution from the lower ionosphere up to satellite orbit altitudes (~500–600 km). The main goal of this study is to investigate opportunities to obtain full observation-based ionospheric electron density profiles (EDPs) by combining advantages of ground-based ionosondes and GNSS RO. We utilized the high-rate Ebre and El Arenosillo ionosonde observations and COSMIC-2 RO EDPs colocated over the ionosonde’s area of operation. Using two types of ionospheric remote sensing techniques, we demonstrated how to create the combined ionospheric EDPs based solely on real high-quality observations from both the bottomside and topside parts of the ionosphere. Such combined EDPs can serve as an analogy for incoherent scatter radar-derived “full profiles”, providing a reference for the altitudinal distribution of ionospheric plasma density. Using the combined reference EDPs, we analyzed the performance of the International Reference Ionosphere model to evaluate model–data discrepancies. Hence, these new profiles can play a significant role in validating empirical models of the ionosphere towards their further improvements. Full article

The conventional supply chain management has undergone major advancements following IoT-enabled revolution. The IoT-enabled drones in particular have ignited much recent attention for package delivery in logistics. The service delivery paradigm in logistics has seen a surge in drone-assisted package deliveries and tracking. There have been a lot of recent research proposals on various aspects of last-mile delivery systems for drones in particular. Although drones have largely changed the logistics landscape, there are many concerns regarding security and privacy posed to drones due to their open and vulnerable nature. The security and privacy of involved stakeholders needs to be preserved across the whole chain of Supply Chain Management (SCM) till delivery. Many earlier studies addressed this concern, however with efficiency limitations. We propose a Physical Uncloneable Function (PUF)-based secure authentication protocol (PSL-IoD) using symmetric key operations for reliable last-mile drone delivery in SCM. PSL-IoD ensures mutual authenticity, forward secrecy, and privacy for the stakeholders. Moreover, it is protected from machine learning attacks and drone-related physical capture threats due to embedded PUF installations along with secure design of the protocol. The PSL-IoD is formally analyzed through rigorous security assessments based on the Real-or-Random (RoR) model. The PSL-IoD supports 26.71% of enhanced security traits compared to other comparative studies. The performance evaluation metrics exhibit convincing findings in terms of efficient computation and communication along with enhanced security features, making it viable for practical implementations. Full article

Traditional cryptographic systems face critical vulnerabilities posed by the rapid advancement of quantum computing, particularly concerning key exchange mechanisms and the quality of entropy sources for random number generation. To address these challenges, this paper proposes a multi-layered, quantum-resistant hybrid cryptographic architecture. First, to ensure robust data confidentiality and secure key establishment, the architecture employs AES-256 (Advanced Encryption Standard-256) for data encryption and utilizes the Kyber Key Encapsulation Mechanism (KEM), which is based on the Learning With Errors (LWE) problem, for secure key exchange. Second, to further bolster overall security by establishing a high-quality cryptographic foundation, we design a TRNG (true random number generator) system based on a multi-level Ring Oscillator (RO) architecture (employing 5, 7, 9, and 11 inverter stages), which provides a reliable and high-quality entropy source. Third, to enable intelligent and adaptive security management, we introduce FA-Kyber (Flow-Adaptive Kyber), a dual-trigger key exchange framework facilitating dynamic key management strategies. Experimental evaluations demonstrate that our implementation exhibits robust performance, achieving an encrypted data transmission throughput of over 550 Mbps with an average end-to-end latency of only 3.14 ms and a key exchange success rate of 99.99% under various network conditions. The system exhibits excellent stability under network congestion, maintaining 86% of baseline throughput under moderate stress, while adaptively increasing the key rotation frequency to enhance security. This comprehensive approach strikes an optimal balance between performance and post-quantum resilience for sensitive communications. Full article

This article presents the design, implementation, and validation of a Remotely Piloted Safety Cone (RPSC), an autonomous robotic system developed to enhance safety and operational efficiency in road maintenance. The RPSC addresses challenges associated with road works, including workers’ exposure to traffic hazards and inefficiencies of traditional traffic cones, such as manual placement and retrieval, limited visibility in low-light conditions, and inability to adapt to dynamic changes in work zones. In contrast, the RPSC offers autonomous mobility, advanced visual signalling, and real-time communication capabilities, significantly improving safety and operational flexibility during maintenance tasks. The RPSC integrates sensor fusion, combining Global Navigation Satellite System (GNSS) with Real-Time Kinematic (RTK) for precise positioning, Inertial Measurement Unit (IMU) and encoders for accurate odometry, and obstacle detection sensors within an optimised navigation framework using Robot Operating System (ROS2) and Micro Air Vehicle Link (MAVLink) protocols. Complying with European regulations, the RPSC ensures structural integrity, visibility, stability, and regulatory compliance. Safety features include emergency stop capabilities, visual alarms, autonomous safety routines, and edge computing for rapid responsiveness. Field tests validated positioning accuracy below 30 cm, route deviations under 15 cm, and obstacle detection up to 4 m, significantly improved by Kalman filtering, aligning with digitalisation, sustainability, and occupational risk prevention objectives. Full article

Domestic showers are critical points of human exposure to microbial biofilms, which may harbor opportunistic pathogens such as Legionella spp. and nontuberculous Mycobacterium. However, biofilm development in reverse osmosis (RO)-treated drinking water systems remains poorly understood. We tested whether shower plumbing material (flexible polymer hose versus showerhead with inline polyethersulfone filter) and seasonal water variations influence biofilm community assembly. In a controlled field study, commercial shower systems were deployed in households supplied with RO-treated tap water from the KAUST Seawater Desalination Plant; biofilm samples were collected from hoses and filters over 3–17 months. Flow cytometry and 16S rRNA gene amplicon sequencing characterized microbial abundance, diversity, and taxonomic composition. We found that alpha diversity, measured by observed OTUs, was uniformly low, reflecting ultra-low biomass in RO-treated tap water. Beta diversity analyses revealed clear clustering by material type, with hoses exhibiting greater richness and evenness than filters. Core taxa—Pelomonas, Blastomonas, and Porphyrobacter—dominated both biofilm types, suggesting adaptation to low-nutrient, chlorinated conditions. Overall, our results demonstrate that ultra-low-nutrient RO tap water still supports the formation of material-driven, low-diversity biofilms dominated by oligotrophic taxa, underscoring plumbing-material choice as a critical factor for safeguarding shower water quality. These findings advance our understanding of biofilm ecology in RO-treated systems, informing strategies to mitigate potential health risks in shower water. Full article

With the rapid advancement of information and communication technology, the number of items users encounter increased exponentially. Consequently, the importance of recommendation systems emerged to reduce the time and effort required for users to make item selections. Recently, among various studies on recommendation systems, there has been significant interest in leveraging review text as auxiliary information. This study proposes a novel model to enhance recommendation performance by effectively analyzing review texts through the fusion of local and global features. By combining convolutional neural networks (CNN), which excel in extracting local features, and the RoBERTa model, renowned for capturing global contextual features, the proposed approach effectively uncovers users’ latent preferences embedded within review texts. The proposed model comprises three key components: the user–item interaction module, which learns complex interactions between users and items; the feature extraction module, which extracts both local and global features using CNN and RoBERTa; and the preference prediction module, which combines the output vectors from the previous modules to predict user preferences for specific items. Extensive experiments conducted on three datasets collected from Amazon platform demonstrate that the proposed model significantly outperforms baseline models. These findings highlight the effectiveness of the proposed approach in considering both local and global features for extracting user preferences from review texts. Full article

With the increasing demand for drones in diverse tasks, the Internet of Drones (IoD) has recently emerged as a significant technology in academia and industry. The IoD environment enables various services, such as traffic and environmental monitoring, disaster situation management, and military operations. However, IoD communication is vulnerable to security threats due to the exchange of sensitive information over insecure public channels. Moreover, public key-based cryptographic schemes are impractical for communication with resource-constrained drones due to their limited computational capability and resource capacity. Therefore, a secure and lightweight key agreement scheme must be developed while considering the characteristics of the IoD environment. In 2024, Alzahrani proposed a secure key agreement protocol for securing the IoD environment. However, Alzahrani’s protocol suffers from high computational overhead due to its reliance on elliptic curve cryptography and is vulnerable to drone and mobile user impersonation attacks and session key disclosure attacks by eavesdropping on public-channel messages. Therefore, this work proposes a lightweight and security-enhanced key agreement scheme for the IoD environment to address the limitations of Alzahrani’s protocol. The proposed protocol employs a physical unclonable function and simple cryptographic operations (XOR and hash functions) to achieve high security and efficiency. This work demonstrates the security of the proposed protocol using informal security analysis. This work also conducted formal security analysis using the Real-or-Random (RoR) model, Burrows–Abadi–Needham (BAN) logic, and Automated Verification of Internet Security Protocols and Applications (AVISPA) simulation to verify the proposed protocol’s session key security, mutual authentication ability, and resistance to replay and MITM attacks, respectively. Furthermore, this work demonstrates that the proposed protocol offers better performance and security by comparing the computational and communication costs and security features with those of relevant protocols. Full article