Rate Of Energy Delivery Research Articles

Treatment of Spontaneous Tumors With Algorithmically Controlled Electroporation.

To study the safety and efficacy of algorithmically controlled electroporation (ACE) against spontaneous equine melanoma. A custom temperature sensing coaxial electrode was paired with a high voltage pulse generation system with integrated temperature feedback controls. Computational modeling and ex vivo studies were conducted to evaluate the system's ability to achieve and maintain target temperatures. Twenty-five equine melanoma tumors were treated with a 2000 V protocol consisting of a 2-5-2 waveform, 45 °C temperature set point, and integrated energized times of 0.005 s, 0.01 s, or 0.02 s (2500x, 5000x, and 10000x 2 μs pulses, respectively). Patients returned 20-50 days post treatment to determine the efficacy of the treatment. ACE temperature control algorithms successfully achieved and maintained target temperatures in a diverse population of spontaneous tumors with significant variation in tissue impedance. All treatments were completed successfully without and without adverse events. Complete response rates greater than 93% were achieved in all treatment groups. ACE is a safe and effective treatment for spontaneous equine melanoma. The temperature control algorithm enabled rapid delivery of electroporation treatments without prior knowledge of tissue electrical or thermal properties and could adjust to real time changes in tissue properties. Real time temperature control in electroporation procedures enables treatments near critical structures where thermal damage is contraindicated. Unlike standard approaches, ACE protocols do not require extensive pretreatment planning or knowledge of tissue properties to determine an optimal energy delivery rate and they can account for changes in tissue state (e.g., perfusion) in real time to simultaneously minimize treatment time and potential for thermal damage.

Enhanced energy delivery of direct-write fabricated reactive materials with energetic graphene oxide

Aluminum (Al) based reactive materials are of interest as their addition can significantly increase the energy density of energetic composites such as solid propellants. In this study, we employed graphene oxide (GO) as an energetic gas generator to increase the ignitability of Al and promote the flame propagation of Al/CuO thermite composites. Compared to the pristine Al/CuO composite, 2.5 wt % addition of GO releases gas and heat upon disproportionation, resulting in a 2X higher burn rate and heat flux. Though both GO and reduced graphene oxide (rGO) addition can reduce the agglomeration size of Al NPs by 2X, GO is more energetic with heat and gas release at low temperature, granting it the ability to increase the ignitability of Al NPs and promote the energy delivery of Al/CuO composite. This study provides a simple way to increase the energy delivery rate of reactive materials by adding a small percentage of functionalized carbon nanomaterials.

The effects of saline water preheating and heat recovery in a vapour-based multistage solar still

The current study complements a broader body of research on solar distillation, including research on heat recycling capabilities and other related factors in multistage solar distillation systems. Solar stills can be used in various applications to provide safe and clean water from natural sources. This study is based on field data collected, analysed, and interpreted over ten (10) months. The solar still operated at atmospheric pressure and produced a distillate by evaporating saline water (SW) at ~ 100 °C. The maximum SW preheating was 75.5 °C with 30,821.04 kJ/m2 day collected by the solar collectors. The corresponding overall thermal efficiency of the test rig was 33.83%. The overall thermal efficiency decreased with increasing wind speed, averaging at 3.12 m/s to 28.31% due to increased heat loss to the environment when 30,780 kJ/m2day was collected. It further declined to 5.89% with low meteorological conditions of 209.81 W/m2, 15.66 °C and 2.66 m/s, respectively, on average. However, the benefits of increased wind speed were enhanced condensation and productivity. The study also found that the ideal thermal energy delivery rate was sim 600 W/m2 or an impulsive mode at higher solar insolation. A balanced condensation rate, SW preheating, heat recovery and overall thermal efficiency can be achieved at this delivery rate. A significant correlation was observed, indicating that the simultaneous increase in the average heat input rate and wind velocities positively impacted distillate output. Conversely, low average wind velocity improved overall thermal efficiency, resulting in a distillate output of 6730 ml for the five stacked stages, despite a slight discrepancy of 3.2 W/m2 in the heat input rate.

Collision Mitigation by Dolphin Ant Lion Optimizer Pre-Packet Scheduling Approach

A wireless sensor network (WSN) consists of distributed autonomous sensors deployed over a large geographical area. Wireless Sensor Networks (WSNs) are composed of large-scale sensors that are specifically assigned to do particular tasks, with a significant portion of these tasks involving reporting and monitoring activities. Nevertheless, because to the potential expansion of the network to several sensor nodes, the likelihood of collision is significantly increased. This research presents an innovative approach for conducting collision detection and mitigation in wireless sensor networks (WSN). The first step involves conducting a simulation of Wireless Sensor Networks (WSN), followed by the utilization of the Fractional Artificial Bee Colony (FABC) algorithm for the selection of cluster heads. In this context, the network-based parameter is derived by considering factors such as the Received Signal Strength Index (RSSI), priority level, delivery rate, and energy consumption. The Deep Recurrent Neural Network (DRNN) has been modified to suit the task of collision detection. The training of the deep recurrent neural network (DRNN) is conducted via the Lion Crow Search optimizer (LCSO). Following the completion of collision detection, the subsequent step involves the implementation of a collision mitigation process utilizing a pre-scheduling technique known as Dolphin Ant Lion Optimizer (Dolphin ALO). In this context, the evaluation of fitness encompasses many factors related to collision mitigation, including energy consumption, Sleep Index (SI), delivery rate, priority level, E-waste management, and E-save measures. The approach presented in this study demonstrated superior performance in terms of energy consumption, throughput, Packet Delivery Ratio (PDR), and collision detection rate. Specifically, it achieved the least energy consumption of 0.185, the greatest throughput of 0.815, the highest PDR of 0.815, and the highest collision detection rate of 0.930.

Elucidating the role of pulse shaping on defects formation in aluminum alloys fabricated by powder bed fusion

The Powder Bed Fusion (PBF) additive manufacturing technique, although widely studied and implemented in the industry, still presents issues of porosity and lack of fusion even when optimal processing parameters are used. The benefits and drawbacks of PBF utilizing pulsed lasers are both consequences of the transient temperature field induced by laser-matter interaction. During laser processing with nanosecond pulse durations, intense heating and cooling rates are induced, setting the melt pool dimensions, which are directly related to the occurrence of lack of fusion, and ablation of the processed material, leading to recoil pressure that induces the keyhole effect, increasing the occurrence of porosity. Consequently, controlling the transient temperature field is a major challenge in incorporating pulsed wave laser technology into PBF to minimize porosity and lack of fusion defects. In this study, to reduce porosity and lack of fusion, a smooth heating rate able to sinter powder grains is designed to facilitate heat flow through the heat affected zone, followed by a sharper heating rate that generates a fully molten region while reducing ablation at the same time. This work represents the first attempt to control the transient temperature field, by shaping a nanosecond laser pulse in the time domain, thereby affecting the formation of defects. The effects of the pulse shape on build quality quantified by lack of fusion and high-energy spherical pores were investigated using X-ray microtomography, molecular dynamics (MD), X-ray diffraction (XRD), Electron Backscatter Diffraction (EBSD), and finite element simulations. The variation of porosity and lack of fusion within manufactured samples were revealed by the high-resolution 3D X-ray micro computed tomography. The differences in the transient temperature field, resulting residual stresses, and microstructure are attributed to the differences in the energy delivery rates within the time domain shaped laser pulses. Laser pulse shaping is an additional parameter that plays an important role in optimizing the PBF as-processed part's production opening a new research niche.

A Cluster-Tree-Based Secure Routing Protocol Using Dragonfly Algorithm (DA) in the Internet of Things (IoT) for Smart Agriculture

The Internet of Things defines a global and comprehensive network whose task is to monitor and control the physical world by collecting, processing, and analyzing data sensed by IoT devices. This network has succeeded in various areas, and one of its most important applications is in smart agriculture because there are many demands for producing high-quality foodstuff in the world. These demands need new production schemes in the agriculture area. In IoT, communication security is essential due to the extensive heterogeneity of IoT devices. In this paper, a cluster-tree-based secure routing approach using the dragonfly algorithm (CTSRD) is proposed for IoT. The proposed scheme presents a distributed and lightweight trust mechanism called weighted trust (W-Trust). W-Trust reduces the trust value corresponding to malicious nodes based on a penalty coefficient to isolate this node in the network. Furthermore, it improves the trust value of honest IoT devices based on a reward coefficient. Additionally, CTSRD introduces a trust-based clustering process called T-Clustering. In this clustering process, cluster head nodes (CHs) are selected among honest IoT nodes. Finally, CTSRD establishes a routing tree based on the dragonfly algorithm (DA) between CHs. This tree is called DA-Tree. To evaluate the quality of the routing tree, a new fitness function is provided in CTSRD. DA-Tree finds a secure, stable, and optimal routing tree to balance the consumed energy and boost the network lifetime. CTSRD is compared with EEMSR and E-BEENISH with regard to the network lifetime, consumed energy, and packet delivery rate. This comparison shows that our scheme can uniformly distribute the consumed energy in IoT and improves the energy consumption and network lifetime. However, it has a slightly lower packet delivery rate than EEMSR.

Unzipping polymers significantly enhance energy flux of aluminized composites

This paper describes a new approach to enhancing the energy delivery rate of pyrotechnics by employing an unzipping polymer. The basic strategy is to localize the heat feedback to just near the reaction front by driving the endothermic chemistry of unzipping. This should then liberate gas near the flame front and propel particles away from the burning surface, to minimize agglomeration and sintering. In this study, polypropylene carbonate (PPC) is employed to load 90 wt% Al and CuO nanoparticles (NPs) via direct ink-writing. The results show a >1500% faster energy release rate from the aluminothermic reaction compared to a conventional polymer binder. Through in-operando microscopy, we observed a 6X thinner flame front and smaller combustion products, revealing significantly lower agglomeration of Al NPs with the unzipping polymer. Fast-heating Time-of-Flight Mass Spectrometry confirms that the unzipping polymer decomposes to low-molecular-weight gasses at a relatively low temperature, which significantly reduces the sintering of Al NPs. The thinner flame implies that heat feedback to the unreacted materials is more localized and drives the endothermic unzipping reaction for gas generation. This study provides a new approach to substantially increasing the energy release rate of nanoscale metallic fuels.

Intracycle power distribution in a heterogeneous multi-compartmental mathematical model: possible links to strain and VILI

BackgroundRepeated expenditure of energy and its generation of damaging strain are required to injure the lung by ventilation (VILI). Mathematical modeling of passively inflated, single-compartment lungs with uniform parameters for resistance and compliance indicates that standard clinical modes (flow patterns) differ impressively with respect to the timing and intensity of energy delivery—the intracycle power (ICP) that determines parenchymal stress and strain. Although measures of elastic ICP may accurately characterize instantaneous rates of global energy delivery, how the ICP component delivered to a compartment affects the VILI-linked variable of strain is determined by compartmental mechanics, compartmental size and mode of gas delivery. We extended our one-compartment model of ICP to a multi-compartment setting that varied those characteristics.Main findingsThe primary findings of this model/simulation indicate that: (1) the strain and strain rate experienced within a modeled compartment are nonlinear functions of delivered energy and power, respectively; (2) for a given combination of flow profile and tidal volume, resting compartmental volumes influence their resulting maximal strains in response to breath delivery; (3) flow profile is a key determinant of the maximal strain as well as maximal strain rate experienced within a multi-compartment lung. By implication, different clinician-selected flow profiles not only influence the timing of power delivery, but also spatially distribute the attendant strains of expansion among compartments with diverse mechanical properties. Importantly, the contours and magnitudes of the compartmental ICP, strain, and strain rate curves are not congruent; strain and strain rate do not necessarily follow the compartmental ICP, and the hierarchy of amplitudes among compartments for these variables may not coincide.ConclusionsDifferent flow patterns impact how strain and strain rate develop as compartmental volume crests to its final value. Notably, as inflation proceeds, strain rate may rise or fall even as total strain, a monotonic function of volume, steadily (and predictably) rises. Which flow pattern serves best to minimize the maximal strain rate and VILI risk experienced within any sector, therefore, may strongly depend on the nature and heterogeneity of the mechanical properties of the injured lung.

A Novel Energy-Aware Routing in Wireless Sensor Network Using Clustering Based on Combination of Multiobjective Genetic and Cuckoo Search Algorithm

The development of various applications of wireless sensor networks has aroused great interest in using these types of networks in various fields. These networks, without infrastructure and self-organization, are easily deployed in most environments and collect information about environmental phenomena for analysis and proper response to accidents and send them to the basic centers. They do. Wireless sensor networks are made up of some sensor nodes that both act as sensors and act as relay nodes concerning to each other. On the other hand, the lack of infrastructure in these networks has limited resources so that the nodes of the battery are fed with limited energy. Due to the location of networks in difficult and impassable areas, it is not possible to recharge or replace the node battery. Therefore, saving energy consumption in this type of network is one of the most important challenges. Since the rate of energy consumption when sensing information and receiving data packets from another node is a fixed value, so sensor nodes have the highest energy consumption when sending data. Therefore, routing methods try to reduce energy consumption based on systematic approaches. One of the most promising solutions to reduce energy consumption in wireless sensor networks is to cluster the nodes and select the threaded node based on the data transfer parameters so that the average energy consumption in the nodes is reduced and the network lifetime is increased. Therefore, in this research, a new optimization approach using multiobjective genetic algorithm and cuckoo algorithm for clustering wireless sensor networks is presented. In this study, in order to select clustered nodes from a multiobjective genetic algorithms based on reducing intracluster distances and reducing energy consumption in cluster member nodes and near-optimal routing based on cuckoo optimization algorithm to transfer information between nodes have been used in the direction of the cavity. The implementation results show that considering the evolutionary capabilities of the multiobjective genetic algorithm and the cuckoo optimization algorithm, the proposed method in terms of energy consumption, efficiency, delivery rate, and packet transmission latency, compared to previous methods, has improved.

Ultrathin Polypyrrole Layers Boosting MoO3 as Both Cathode and Anode Materials for a 2.0 V High-Voltage Aqueous Supercapacitor.

An aqueous supercapacitor is an emerging energy storage unit on account of its low cost, fast energy delivery rate, and long service life. The energy density of an aqueous supercapacitor can be enlarged via extending the voltage window of electrode materials, while the aqueous electrolyte remains thermodynamically constant at 1.23 V. Herein, an aqueous supercapacitor with a 2.0 V high-voltage window is realized by core-shell MoO3-x/polypyrrole (MP) nanocomposites as both cathode and anode materials. The ultrathin PPy layer on the MoO3 core not only improves the conductivity and cycle stability of the nanocomposites but also acts as a reductant, leading to the formation of oxygen vacancies in the MoO3 core. When used as a cathode material, the potential range of the as-obtained MP nanocomposite is up to 1.0 V. As an anode material, the stable potential range could reach -1.0 V. Due to the large potential range of the cathode and anode, the as-obtained 2.0 V aqueous supercapacitor shows a remarkably high delivery energy of 58.5 Wh kg-1. The synthesis of MP nanocomposites is simple and the electrode performance is significantly enhanced; thus, it is a suitable candidate for high-energy-density aqueous supercapacitors.

Intracycle power and ventilation mode as potential contributors to ventilator-induced lung injury

BackgroundHigh rates of inflation energy delivery coupled with transpulmonary tidal pressures of sufficient magnitude may augment the risk of damage to vulnerable, stress-focused units within a mechanically heterogeneous lung. Apart from flow amplitude, the clinician-selected flow waveform, a relatively neglected dimension of inflation power, may distribute inflation energy of each inflation cycle non-uniformly among alveoli with different mechanical properties over the domains of time and space. In this initial step in modeling intracycle power distribution, our primary objective was to develop a mathematical model of global intracycle inflation power that uses clinician-measurable inputs to allow comparisons of instantaneous ICP profiles among the flow modes commonly encountered in clinical practice: constant, linearly decelerating, exponentially decelerating (pressure control), and spontaneous (sinusoidal).MethodsWe first tested the predictions of our mathematical model of passive inflation with the actual physical performance of a mechanical ventilator–lung system that simulated ventilation to three types of patients: normal, severe ARDS, and severe airflow obstruction. After verification, model predictions were then generated for 5000 ‘virtual ARDS patients’. Holding constant the tidal volume and inflation time between modes, the validated model then varied the flow profile and quantitated the resulting intensity and timing of potentially damaging ‘elastic’ energy and intracycle power (pressure–flow product) developed in response to random combinations of machine settings and severity levels for ARDS.ResultsOur modeling indicates that while the varied flow patterns ultimately deliver similar total amounts of alveolar energy during each breath, they differ profoundly regarding the potentially damaging pattern with which that energy distributes over time during inflation. Pressure control imposed relatively high maximal intracycle power.ConclusionsFlow amplitude and waveform may be relatively neglected and modifiable determinants of VILI risk when ventilating ARDS.

The Influence of Heavy Cosmic Rays in Energy Deposition in Molecular Clouds Employing the GEANT4 Code and Voyager I Data

Abstract Galactic and extragalactic cosmic rays fully illuminate and trigger several physical and physicochemical changes in molecular clouds (MCs), including gas and grain heating, molecular destruction and formation, and molecular and atomic desorption (sputtering) from dust/ices to gas phase. Besides the major component in cosmic ray inventory (in flux) being electrons, protons, and alphas, particles with larger atomic numbers have a higher rate of energy delivery (due to richer cosmic ray showers) than the lighter particles, and this may add extra energy input into MCs. To understand this issue, we perform complementary calculations to the previous work on MCs, now adding the heavy ions (12 ≤ Z ≤ 29) in the cosmic ray incoming inventory. Once more, the calculations were performed employing the Monte Carlo toolkit GEANT4 code (considering nuclear and hadron physics). We observe that most projectiles in the heavy ion group have lower deposited energies (roughly 10 times less) than iron with the exception of magnesium (Z = 12) and silicon (Z = 14) which are about double. Cobalt presents the lowest deposited energies with respect to iron (only 0.5%). The total energy deposition in the current model was only roughly 10% higher (outer layers) and virtually the same at the center of the cloud when compared with the previous model (with only protons + alphas + electrons sources). The results show that energy deposition by heavy ions is small compared with the values from light particles, and also suggest a very low temperature enhancement due to heavy ions within the MC, being the protons the dominant agent in the energy delivery and also in the cloud’s heating.

Nutrition therapy in the intensive care unit during the COVID-19 pandemic: Findings from the ISIIC point prevalence study

Background & aims:Nutrition therapy for Intensive Care Unit (ICU) patients involves complex decision-making, especially during the COVID-19 pandemic. We investigated the use of nutrition therapy in ICU patients with and without COVID-19 infections.MethodsNutrition therapy was evaluated during a world-wide one-day prevalence study focused on implementation of the ABCDEF bundle (A: regular pain assessment, B: both spontaneous awakening and breathing trials, C: regular sedation assessment, D: regular delirium assessment, E: early mobility and exercise, and F: family engagement and empowerment) during the COVID-19 pandemic. Basic ICU and patient demographics including nutrition therapy delivery were collected on the survey day. Physical activity for patients with and without COVID infections was categorized using the ICU mobility scale (IMS). Multivariable regression analysis of nutrition was conducted using ICU parameters.ResultsThe survey included 627 non-COVID and 602 COVID patients. A higher proportion of COVID-19 patients received energy ≥20 kcal/kg/day (55% vs. 45%; p = 0.0007) and protein ≥1.2 g/kg/day (45% vs. 35%; p = 0.0011) compared to non-COVID patients. Enteral nutrition was provided to most COVID patients even with prone positioning (91%). Despite nutrition therapy, IMS was extremely low in both groups; median IMS was 1 in non-COVID patients and 0 in COVID patients. The rate of energy delivery ≥20 kcal/kg/day was significantly higher in patients with COVID-19 infections in the subgroup of ICU days ≤5 days and IMS ≤2. Having a dedicated ICU nutritionist/dietitian was significantly associated with appropriate energy delivery in patients both with and without COVID-19 infections, but not with protein delivery.ConclusionDuring the COVID-19 pandemic, patients with COVID-19 infections received higher energy and protein delivery. Generally low mobility levels highlight the need to optimize early mobilization with nutrition therapy in all ICU patients.

Preliminary observations of a system for determination of phototherapy exposure over a neonate body shape

While it is possible to determine the irradiance and spectral content for a given neonatal phototherapy device at various locations over a neonate's surface, this does not allow estimation of the total rate of energy delivery within a specific spectral range over the neonate's exposed body surface. A series of 192 blue wavelength enhanced silicon photodiodes was distributed over the surface of a commercially available newborn body shape and connected to a specially designed interface circuit. Placement of photosensors over the surface of the baby shape was determined with consideration of the surface area of twelve specific anatomical areas where each was allocated 16 individual photodiodes. Calibration of detection channels for specific wavelength intervals was undertaken using a Bentham dmc150 spectroradiometer system and also a separate hand held spectroradiometer. This made it possible to estimate the effective integrated dose rate in Watts for specific wavelength intervals such as 460 nm to 490 nm as identified by the American Academy of Pediatrics for phototherapy lamp devices. This allowed identification of dose rate contributions from specific anatomical areas. Initial observations are reported for a range of phototherapy lamp systems and the findings are discussed in terms of their predicted relative clinical effectiveness. Options are also discussed in relation to the future development of the reported measurement system.

DTEC-MAC: Diverse Traffic with Guarantee Energy Consumption for MAC in Wireless Body Area Networks

Wireless body area networks (WBAN) are innovative technologies that have been the anticipation greatly promote healthcare monitoring systems. All WBAN included biomedical sensors that can be worn on or implanted in the body. Sensors are monitoring vital signs and then processing the data and transmitting to the central server. Biomedical sensors are limited in energy resources and need an improved design for managing energy consumption. Therefore, DTEC-MAC (Diverse Traffic with Energy Consumption-MAC) is proposed based on the priority of data classification in the cluster nodes and provides medical data based on energy management. The proposed method uses fuzzy logic based on the distance to sink and the remaining energy and length of data to select the cluster head. MATLAB software was used to simulate the method. This method compared with similar methods called iM-SIMPLE and M-ATTEMPT, ERP. Results of the simulations indicate that it works better to extend the lifetime and guarantee minimum energy and packet delivery rates, maximizing the throughput.

Influence of Mechanical Milling and Heat Treatment on the Properties of Bronze Powder

We have studied the influence of high-energy treatments on changes in the morphology, structure, phase composition, and (as a consequence) hardness of BrA 10 (DIN CuAl10Fe3Mn2) bronze powder particles. It has been shown for the first time that, independent of energy delivery rate during mechanical treatment of the powder, after the delivery of a given amount of energy the particles are similar in size, phase composition, and internal structure. Mechanical milling of the material leads to changes in particle shape, cleaning and activation of the particle surface, changes in the internal structure of the particles, and an increase in their hardness from 248 to 322 HV0.025. Unlike mechanical milling, heat treatment of the material leads to stress relieve, accompanied by a decrease in its hardness from 248 to 104 HV0.025.

Electrical Power Diversification: An Approach Based on the Method of Maximum Entropy in the Mean.

Electrical energy is generated in different ways, each located at some specific geographical area, and with different impact on the environment. Different sectors require heterogeneous rates of energy delivery, due to economic requirements. An important problem to solve is to determine how much energy must be sent from each supplier to satisfy each demand. Besides, the energy distribution process may have to satisfy ecological, technological, or economic cost constraints.

Routing Protocols in Delay Tolerant Networks: Comparative and Empirical Analysis

A Delay Tolerant Network (DTN) is a network capable of handling long delays and data loss efficiently in various challenged scenarios and environments. Owing to the mentioned challenges, it becomes crucial to study how the routing protocols are designed to adapt in such networks. Currently, the research in this domain is focused on the improving the data delivery ratio and minimizing delays in the routing protocols. This paper reviews state-of-the-art routing protocols for Delay Tolerant Networks (DTNs) as well as performs their comparative analysis. DTN routing protocols are grouped into four categories viz encounter based, time based, infrastructure based and hybrid & others. This categorization depends on the information they use for relay selection routing. We have also discussed some of the inherent drawbacks such as energy consumption, delivery rates and buffer constraints of the existing routing algorithms. We have also conducted an empirical analysis and observed the performance of the most popular existing algorithms of encounter and time based category. This paper offers a widespread study of the routing protocols with their pros and cons.

Electro-thermal therapy: Microsecond duration pulsed electric field tissue ablation with dynamic temperature control algorithms

Electro-thermal therapy (ETT) is a new cancer treatment modality which combines the use of high voltage pulsed electric fields, dynamic energy delivery rates, and closed loop thermal control algorithms to rapidly and reproducibly create focal ablations. This study examines the ablative potential and profile of pulsed electric field treatments delivered in conjunction with precise temperature control algorithms. An ex vivo perfused liver model was utilized to demonstrate the capability of 5000 V 2 μs duration bipolar electrical pulses and dynamic temperature control algorithms to produce ablations. Using a three applicator array, 4 cm ablation zones were created in under 27 min. In this configuration, the algorithms were able to rapidly achieve and maintain temperatures of 80 °C at the tissue-electrode interface. A simplified single applicator and grounding pad approach was used to correlate the measured ablation zones to electric field isocontours in order to determine lethal electric field thresholds of 708 V/cm and 867 V/cm for 45 °C and 60 °C treatments, respectively. These results establish ETT as a viable method for hepatic tumor treatment with ablation profiles equivalent to other energy based techniques. The single applicator and multi-applicator approaches demonstrated may enable the treatment of complex tumor geometries. The flexibility of ETT temperature control yields a malleable intervention which gives clinicians robust control over the ablation modality, treatment time, and safety profile.

A lifetime-enhancing cooperative data gathering and relaying algorithm for cluster-based wireless sensor networks

Despite unique energy-saving dispositions of cluster-based routing protocols, clustered wireless sensor networks with static sinks typically have problems of unbalanced energy consumptions, as the cluster head nodes around the sink are typically loaded with traffic from upper levels of clusters. This results in reduced lifetimes of the nodes and deterioration of other crucial performances. Meanwhile, it has been inferred from current literature that dedicated relay cooperation in cluster-based wireless sensor networks guarantees longer lifetime of the nodes and more improved performance. Therefore, to attain further enhanced performance among the current schemes, a lifetime-enhancing cooperative data gathering and relaying algorithm for cluster-based wireless sensor networks is proposed in this article. The proposed lifetime-enhancing cooperative data gathering and relaying algorithm shares the nodes into clusters using a hybrid K-means clustering algorithm that combines K-means clustering and Huffman coding algorithms. It makes full use of dedicated relay cooperative multi-hop communication with network coding mechanisms to achieve reduced data propagation cost from the various cluster sections to the central base station. The relay node selection is framed as a NP-hard problem, with regard to communication distances and residual energy metrics. Furthermore, to resolve the problem, a gradient descent algorithm is proposed. Simulation results endorse the proposed scheme to outperform related schemes in terms of latency, lifetime, and energy consumption and delivery rates.