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Using force myography (FMG) to monitor volumetric changes in limb muscles is a promising and effective alternative for controlling bio-robotic prosthetic devices. In recent years, there has been a focus on developing new methods to improve the performance of FMG technology in the control of bio-robotic devices. This study aimed to design and evaluate a novel low-density FMG (LD-FMG) armband for controlling upper limb prostheses. The study investigated the number of sensors and sampling rate for the newly developed LD-FMG band. The performance of the band was evaluated by detecting nine gestures of the hand, wrist, and forearm at varying elbow and shoulder positions. Six subjects, including both fit and amputated individuals, participated in this study and completed two experimental protocols: static and dynamic. The static protocol measured volumetric changes in forearm muscles at the fixed elbow and shoulder positions. In contrast, the dynamic protocol included continuous motion of the elbow and shoulder joints. The results showed that the number of sensors significantly impacts gesture prediction accuracy, with the best accuracy achieved on the 7-sensor FMG band arrangement. Compared to the number of sensors, the sampling rate had a lower influence on prediction accuracy. Additionally, variations in limb position greatly affect the classification accuracy of gestures. The static protocol shows an accuracy above 90% when considering nine gestures. Among dynamic results, shoulder movement shows the least classification error compared to elbow and elbow–shoulder (ES) movements.

IoT (Internet of Things)-based remote monitoring and controlling applications are increasing in dimensions and domains day by day. Sensor-based remote monitoring using a Wireless Sensor Network (WSN) becomes challenging for applications when both temporal and spatial data from widely spread sources are acquired in real time. In applications such as environmental, agricultural, and water quality monitoring, the data sources are geographically distributed, and have little or no cellular connectivity. These applications require long-distance wireless or satellite connections for IoT connectivity. Present WSNs are better suited for densely populated applications and require a large number of sensor nodes and base stations for wider coverage but at the cost of added complexity in routing and network organization. As a result, real time data acquisition using an IoT connected WSN is a challenge in terms of coverage, network lifetime, and wireless connectivity. This paper proposes a lightweight, dynamic, and auto-reconfigurable communication protocol (LDAP) for Wide-Area Remote Monitoring (WARM) applications. It has a mobile data sink for wider WSN coverage, and auto-reconfiguration capability to cope with the dynamic network topology required for device mobility. The WSN coverage and lifetime are further improved by using a Long-Range (LoRa) wireless interface. We evaluated the performance of the proposed LDAP in the field in terms of the data delivery rate, Received Signal Strength (RSS), and Signal to Noise Ratio (SNR). All experiments were conducted in a field trial for a water quality monitoring application as a case study. We have used both static and mobile data sinks with static sensor nodes in an IoT-connected environment. The experimental results show a significant reduction (up to 80%) of the number of data sinks while using the proposed LDAP. We also evaluated the energy consumption to determine the lifetime of the WSN using the LDAP algorithm.

The Mobile Ad Hoc Networks (MANETs) are dynamic and infrastructure-less wireless networks where the devices are resource constrained and the topology changes rapidly. In the development of routing protocols in MANETs, it is very important to optimize parameters such as bandwidth, hop count and reduce energy usage. This paper introduces a new multi-objective routing protocol (NMORP) that will improve the performance and efficiency of MANET. The proposed protocol employs a composite cost scheme that considers a variety of metrics (energy, bandwidth, hop count) to guide routing choices in heterogeneous networks. We deploy NMORP in OMNeT++/INET and make comparisons to the conventional Destination-Sequenced Distance Vector (DSDV) protocol. The simulation outcome demonstrates that NMORP is superior to DSDV: network lifetime increases by a factor of up to 41%, throughput increases by approximately 32%, the end-to-end delay is minimized by up to 90%, and Packet Delivery Ratio (PDR) becomes more than 98% in certain situations. These advances indicate that NMORP can efficiently use its resources and provide credible data transfer across different conditions, which outlines the significance of multi-metric routing plans in the next-generation MANET design.

With the rapid development of Internet of Things (IoT) technology, the demand for distributed data sharing has surged. Privacy breaches, a single point of failure, and high communication overhead have become core challenges. Existing privacy protection based on single federated learning lacks reliable collaboration mechanisms and fault tolerance capabilities. The traditional PBFT algorithm also faces communication complexity and is incompatible with high concurrency scenarios. To address the limitations of these single technologies, a multi-layer data sharing framework is proposed. It integrates federated learning and blockchain technology is proposed to deal with the security and efficiency issues of privacy data transmission in the IoT environment. The framework uses differential privacy to ensure data privacy and solves server single-point failures using the Proof of Quality (PoQ) consensus algorithm. A reputation mechanism supervises node behavior. Meanwhile, an improved PBFT consensus algorithm based on dynamic region partitioning is designed to handle fast data transmission and improve consensus efficiency in the IoT. By integrating these two solutions, an overall architecture is constructed to achieve efficient IoT data transmission. Experimental verification showed that the differential privacy mechanism only reduced data transmission accuracy by 3.5% after introducing Gaussian noise. In terms of fault tolerance, the PoQ algorithm had a fault rate of 14.3% for fault-tolerant nodes. Dynamic partitioning PBFT optimization, reduced communication frequency by 44% compared to single-layer PBFT, and transaction latency by 63%. These results indicate that the designed solution has significant advantages in high-concurrency IoT scenarios and can effectively meet real-time security demands.

Classical homogenization theory treats critical exponents as universal quantities depending only on spatial dimension, but recent evidence shows that this assumption fails for continuum composites once the mechanism of randomness generation is taken into account. We synthesize three complementary frameworks—structural approximation, structural sums, and self-similar renormalization—to develop a unified geometric theory of criticality in random composites. Dilute-regime expansions for the effective conductivity and shear modulus are expressed in terms of structural sums whose ensemble statistics depend sensitively on the randomness protocol. To bridge the dilute and critical regimes, we employ self-similar factor approximants, iterated-root approximants, additive approximants, and renormalization schemes based on minimal-difference and minimal-sensitivity conditions, combined with Borel summation. For maximally disordered protocols P(τ), the conductivity index s and the elasticity index S fall within comparable numerical ranges, indicating a shared geometric origin and spectral response to the continuous breaking of translational symmetry. A regular periodic arrangement of inclusions (τ=0) possesses full discrete translational symmetry; as a stochastic protocol P(τ) is applied (τ increases), this symmetry is gradually degraded until statistical chaos is reached. For instance, the parameter τ can be considered as a time of stirring. During this evolution, the system traverses a continuous spectrum of critical indices, s=s[P(τ)], which encodes the geometric and topological memory of the initial ordered state. It is established that the classical “universality” of percolation corresponds to a fixed point τ within a broader manifold of protocol-dependent critical behaviors. The framework developed here provides a coherent basis for inverse design, diagnostics, and classification of random composites by their disorder history, offering a geometric alternative to the universality paradigm.

Preserving energy of sensor node in wireless sensor network is an effort to prolong the lifetime of network. Energy of sensor node is very crucial because battery powered and irreplaceable. Energy conservation of sensor node is an effort to reduce energy consumption in order to preserve resource for network lifetime. It can be achieved through efficient energy usage by reducing consumption of energy or decrease energy usage while achieving a similar outcome. In this paper, the authors propose power layer energy efficient routing protocol in wireless sensor network, named PLRP, which use power control and multi-hop routing protocol to control overhead of sensor node and create clustering to distribute energy dissipation and increase energy efficiency of all sensor node. The main idea of PLRP is the use of power control, which divide sensor node into group by base station uses layer of energy and maximize the computation energy in base station to reduce computational energy in sensor node for conservation of network lifetime. The performance of PLRP compared to BCDCP and BIDRP based of hierarchical routing protocol. The simulation results show that PLRP achieve 25% and 30% of improvement on network lifetime.

In multi-user cognitive-radio internet of things (CR-IoT) network, accurate estimations of data arrival are critical for secondary users to allocate channels. In the context of the data arrival model with long-term variations of rate, improving the accuracy of the performance evaluation of channel allocation protocols is an open issue. Thus, to evaluate the performance of various channel allocation protocols with predefined models of data arrival, a queuing analysis framework is developed using a probability allocation vector (PrA). The time-varying feature of data arrival is described by a Markov process including various data arrival states in the proposed framework. A dynamic probability allocation vector (DPrA) protocol capable of adjusting allocation strategy according to the arrival states by constructing the PrA is proposed. For comparative analysis, a maximum throughput allocation (MTA) protocol for conventional data arrival model is also evaluated under the proposed framework. Numerical results show that the DPrA protocol outperforms the MTA protocol in various performance metrics. Furthermore, the proposed modeling method for data traffic can provide convenience and effectiveness when designing channel allocation protocols in a CR-IoT network.

Background/Objectives: Long-term obesity management consistently fails due to two major barriers: poor adherence, exacerbated by ultra-processed foods with addictive potential, and post-weight loss metabolic adaptation that reduces energy expenditure by approximately 500 kcal/day. Current paradigms—static diets and GLP-1 receptor agonists—address these barriers only partially. The objectives of this thesis-driven review are: (1) to conduct a focused evidence-mapping of Ketogenic–Mediterranean Diet (KMD) protocols; (2) to analyze why existing protocols have not explicitly countered metabolic adaptation; and (3) to present the Adaptive Ketogenic–Mediterranean Protocol (AKMP). Methods: Hybrid methodology—an argumentative narrative review anchored by a structured evidence-mapping search (PRISMA-style flow for transparency). Results: We identified 29 studies implementing KMD protocols with significant weight loss and superior adherence. However, none of the published protocols explicitly implement anti-adaptive strategies, despite an estimated ketogenic metabolic advantage (≈100–300 kcal/day), context-dependent and more consistently observed in longer trials and during weight-maintenance settings. Conclusions: Unlike GLP-1 receptor agonists—which primarily suppress appetite, require ongoing pharmacotherapy, and do not directly mitigate the decline in energy expenditure—the AKMP couples a Mediterranean foundation for adherence with a ketogenic metabolic advantage and a biomarker-guided adjustment system explicitly designed to counter metabolic adaptation, aiming to improve the durability of weight loss and patient self-management. As a theoretical construct, the AKMP requires confirmation in prospective, controlled studies; accordingly, we outline a pragmatic 24-week pilot design in “Pragmatic Pilot Trial to Validate the AKMP–Incretin Sequencing”.

In this study, a field survey was conducted on the fixed anchorages of the operation and power generation facilities installed in domestic power plants. A static/dynamic performance evaluation was conducted to present safety evaluation guidelines that meet the domestic seismic performance requirements. Seismic performance tests were performed on the post-installed set anchors M10 and M12, which are mainly used for anchorages in accordance with the US and European seismic performance standards. The dynamic shear test results showed that the M12 anchor met the seismic performance verification criterion, whereas the M10 anchor did not because its dynamic performance was reduced, owing to the cyclic loading. In the results of the dynamic pull-out test, M12 also met the seismic performance verification criterion, whereas M10 was safe only in a non-cracked state. In summary, the seismic performance of M12 in both cracks and non-cracks was satisfied, but, in the case of M10, the results were not satisfied in cracks. This was an experimental study; it will be necessary to conduct additional analytical research in the future to verify the reliability and parameters of the experiment.

In the paper the adaptability of Dynamic Source Routing (DSR) Protocol to the changes in network topography, its ability to establish new routes and the viability in modern sensing devices is simulated and analyzed. For a dynamic network the distance between source and destination changes along with their position in respect to their neighboring nodes. In our experiments, three scenarios considering real world deployment techniques like fixed position, clustering and random mobility are designed and the behavior of the protocol has been studied in two networks consisting of 100 and 150 nodes respectively. Comparative analysis is performed considering characteristics such as Instantaneous throughput, Bandwidth consumption, Average throughput, Packet delivery ratios and Residual energy of the individual nodes and of the network. The experimental data provides valuable insight for real-world applications. Path selection in DSR protocol is based on control messages which are flooded throughout the network. As seen from our experiments, the protocol can be greatly enhanced by reducing the overhead (number of packets required for network communication) to conserve bandwidth. Before making changes to the header or the routing mechanism we need to make sure that the protocol can still accommodate the various types of payloads, options and adopt to fragmented or dynamic networks. Due to the severe limitations on the resources available, the selected protocol should provide high energy efficiency, reliability and robustness to attacks. Hence the analysis of networking/routing protocols should be considered and variations of the selected protocol can be developed to accommodate the challenges faced in such networks.