Thermal Constraints Research Articles

SURG-31. HYBRID THERAPY FOR NEWLY DIAGNOSED AND RECURRENT GLIOBLASTOMA: STAGED PROCEDURE INTEGRATING OPEN SURGICAL RESECTION WITH LASER INTERSTITIAL THERMAL THERAPY

Abstract BACKGROUND Glioblastoma (GBM) is the most common and aggressive primary malignant brain tumor in adults with a median overall survival (OS) of 15.6 months. Despite advancements, 5-year survival rates have not significantly improved. Laser interstitial thermal therapy (LITT) has been employed to treat both newly diagnosed (nGBM) and recurrent GBM (rGBM) with demonstrable safety and efficacy. Traditionally, LITT has been limited to smaller lesions given physical and thermal constraints. OBJECTIVE We present two case examples of a novel, hybrid treatment approach to GBM, utilizing both surgery and laser ablation as part of a single-staged procedure. METHODS Two geriatric (>65 years) patients with nGBM or rGBM were treated with surgical resection followed by LITT the subsequent day. Both patients underwent preoperative magnetic resonance imaging (MRI) showing multifocal disease with a dominant component, causing mass effect in the second case, and an unresectable component. RESULTS The first case underwent surgical resection of a large, multicentric rGBM in the parieto-occipital region, followed by LITT of an unresectable lesion in the inferior temporal gyrus. The second patient underwent surgical resection of the dominant temporal lobe component, and LITT of the insular component. Neither patient had intraoperative or ablation complications. Both patients had stable postoperative neurological exams and were discharged on the day after ablation, with no new deficits at follow-up. CONCLUSION The prognosis for GBM remains dismal despite significant research and attempts at advancements in patient management. Surgical resection is a critical component of the GBM treatment paradigm. However, surgery alone is not sufficient in many patients. LITT has shown promise for improving GBM outcomes, mainly due to its minimal invasiveness, enhanced immune responses, BBB disruption, and cytoreductive potential. We demonstrate a novel, hybrid approach to GBM using hybrid surgical resection and LITT in a single-staged procedure to overcome traditional constraints of LITT.

Soil microbial carbon use efficiency and the constraints

Abstract Background Microbial contributions to soil organic carbon formation have received increasing attention, and microbial carbon use efficiency is positively correlated with soil organic carbon storage. Mainbody This work reviews the impact on microbial carbon use efficiency from six constraints, including plant community composition and diversity, soil pH, substrate quality, nutrient availability and stoichiometric ratios, soil texture and aggregates, water and thermal constraints, and external nutrient inputs. In general, the response of microbial carbon use efficiency showed large uncertainty to above constraints, including positive-, negative-, or non-correlation. However, some factors are biased, more likely to promote or inhibit carbon use efficiency. For example, external nutrient input (N, P, K, Ca) tended to promote carbon use efficiency, while climate warming showed more negative influence. Conclusion Further, overwhelming works focused on single constraint, we suggest the importance to consider the synergistic influence of multiple environmental variables on microbial carbon use efficiency, special for the regulation mechanism of biological-environmental interactions.

A multidisciplinary framework from reactors to repositories for evaluating spent nuclear fuel from advanced reactors

This study presents a multidisciplinary reactor-to-repository framework to compare different advanced reactors with respect to their spent nuclear fuel (SNF) disposal. The framework consists of (1) OpenMC for simulating neutronics, fuel depletion, and radioactive decays; (2) NWPY for computing the repository footprint given the thermal constraints; and (3) PFLOTRAN for simulating radionuclide transport in the geosphere to quantify the repository performance and environmental impact. We first perform the meta-analysis of past comparative analyses to identify the factors that led previously to their inconsistent conclusions. We then demonstrate the new framework by comparing five reactor types. Our analysis highlights the granularity and the specificities of each reactor and fuel type so that we should avoid making sweeping conclusions about advanced reactor SNF. Significant findings are that (1) the repository footprint is neither linearly related to SNF volume nor to decay heat, due to the repository’s thermal constraint (2), fast reactors have significantly higher I-129 inventory, which is often the primary dose contributor, and (3) the repository performance primarily depends on the waste forms. The TRISO-based reactors, in particular, have significantly higher SNF volumes compared to the others but result in smaller repository footprints and lower peak dose rates. The open-source framework ensures proper multidisciplinary connections between reactor simulations and environmental assessments, as well as the transparency/traceability required for such comparative analyses. It aims to support reactor designers, repository developers, and policymakers in evaluating the impact of different reactor designs, with the ultimate goal of improving the sustainability of nuclear energy systems.

A New Back-End-Of-Line Ferroelectric Field-Effect Transistor Platform via Laser Processing.

The discovery of ferroelectricity in hafnia-based materials has revitalized interest in realizing ferroelectric field-effect transistors (FeFETs) due to its compatibility with modern microelectronics. Furthermore, low-temperature processing by atomic layer deposition offers promise for realizing monolithic three-dimensional (M3D) integration toward energy- and area-efficient computing paradigms. However, integrating ferroelectrics with channel materials in FeFETs for M3D integration remains challenging due to the dual requirement of a high-quality ferroelectric-channel interface and low-power operation, all while maintaining back-end-of-line (BEOL)-compatible fabrication temperatures. Recent studies on 2D semiconductors and metal oxide channels highlight these challenges. Polycrystalline silicon (poly-Si), a channel material long integrated into the semiconductor industry, presents a promising alternative; however, its high fabrication temperature has hindered its applications to M3D integration. To overcome this challenge, wedemonstrates a BEOL-compatible FeFET platform using poly-Si channels fabricated via locally-confined laser thermal processing and hafnia-based ferroelectrics by low-temperature atomic layer deposition with wafer-scale uniformity. The local nature of the laser processing mitigates the trade-off between the high-temperature crystallization for the quality of the interface and BEOL thermal budget constraints. The laser-processed FeFETs boast the largest effective memory widow for all BEOL-compatible FeFETs. Moreover, the fabricated FeFETs are integrated into wafer-scale synaptic arrays for neuromorphic computing, achieving record-high energy efficiency. Therefore, this work establishes a promising BEOL-compatible FeFET materials platform toward M3D integration.

The characterization of ancient Methanococcales malate dehydrogenases reveals that strong thermal stability prevents unfolding under intense γ-irradiation.

Malate dehydrogenases (MalDH) (EC.1.1.1.37), which are involved in the conversion of oxaloacetate to pyruvate in the tricarboxylic acid cycle, are a relevant model for the study of enzyme evolution and adaptation. Likewise, a recent study showed that Methanococcales, a major lineage of Archaea, is a good model to study the molecular processes of proteome thermoadaptation in prokaryotes. Here, we use ancestral sequence reconstruction and paleoenzymology to characterize both ancient and extant MalDHs. We observe a good correlation between inferred optimal growth temperatures (OGTs) and experimental optimal temperatures for activity (A-Topt). In particular, we show that the MalDH present in the ancestor of Methanococcales was hyperthermostable and had an A-Topt of 80°C, consistent with a hyperthermophilic lifestyle. This ancestor gave rise to two lineages with different thermal constraints, one remaining hyperthermophilic while the other underwent several independent adaptations to colder environments. Surprisingly, the enzymes of the first lineage have retained a thermoresistant behavior (i.e., strong thermostability and high A-Topt), whereas the ancestor of the second lineage shows a strong thermostability, but a reduced A-Topt. Using mutants, we mimic the adaptation trajectory towards mesophily and show that it is possible to significantly reduce the A-Topt without altering the thermostability of the enzyme by introducing a few mutations. Finally, we reveal an unexpected link between thermostability and the ability to resist γ-irradiation-induced unfolding.

Bioconvection flow of Carreau nanomaterial invoking Soret and Dufour impacts

Background and objectiveThermal transport enhancement through nanomaterial flow has gained much attention of the investigators recently. Such attention is for applications in engineering, petroleum industries, geothermal engineering and pharmaceutical developments such as X-ray imaging, welding process, semiconductor material production, thermal storage system, electric cooling devices, drug delivery, magma solidification etc. In view of such interest here we analyze the bioconvective stretched flow of Carreau nanoliquid. Thermal, microorganism and mass convective constraints are considered. Gyrotactic microorganisms within presence of chemical reaction is considered. Variable thermal conductivity is considered. Dufour and Soret features are under consideration. Thermophoresis diffusion and random movement features are considered. Energy relation comprises heat generation and radiation. MethodologyNonlinear dimensionless expressions are developed by employing suitable transformations. Numerical computations are obtained by implementation of Newton built in-shooting technique. ResultsPerformance of liquid flow, concentration, microorganism field, and thermal field is studied. Numerical values of quantities of engineering performance via influential parameters are explored. Larger Weissenberg number yield velocity increase. Reduction in velocity through bioconvection Rayleigh number is witnessed. Concentration and thermal field through solutal thermal Biot numbers have similar effect. An increment in thermal distribution and Nusselt number for Dufour number is detected. Increasing values of Soret number and chemical reaction correspond to decay in concentration. An augmentation in thermal transfer rate and temperature through radiation is noticed. An increment in density number against Peclet and bioconvection Lewis numbers is noticed.

Lithospheric Structure and Strength Variations in Antarctica From Joint Modeling of Elevation, Geoid and Seismic Data

AbstractAntarctica is renowned for its ancient cratons, difficult‐to‐observe sutures and active continental rifts. Detailed lithospheric structure and strength estimates are crucial for understanding the potential distribution, long‐term geological evolution, and deformation patterns of this continent. The lithospheric structure of the Antarctic continent is investigated based on joint modeling of elevation and geoid data with the incorporation of seismic data and thermal constraints. Moreover, these results are used to infer the yield strength envelopes across Antarctica. The laterally variable lithospheric strength is finally generated by vertically integrating the above envelopes. Our results show that the variations in the depth of the lithosphere‐asthenosphere boundary (LAB) are analogous to the variations in the integrated lithospheric strength; these parameters vary from 60 to 220 km and from 0.5 × 1013 Pa m to 4.5 × 1013 Pa m, respectively. Several regions of East Antarctica exhibit thick and strong lithospheric mantle, suggesting the presence of scattered cratonic blocks. In contrast, a thin and weak lithosphere is observed in the tectonically active West Antarctica and East Antarctic orogenic belts. Generally, our new LAB model correlates well with previous estimates, but there is a significant inconsistency beneath the Gamburtsev Subglacial Mountains, where a shallow LAB (∼120 km), high Moho temperature, and low strength (<1.0 × 1013 Pa m) are estimated. We speculate that this anomaly may be similar to the thinned lithosphere in Dronning Maud Land and reflects the removal of the mantle lithosphere during or after the orogenesis associated with the assembly of the Gondwana supercontinent.

Strain and Deformation Analysis Using 3D Geological Finite Element Modeling with Comparison to Extensometer and Tiltmeter Observations

This study verifies the practicality of using finite element analysis for strain and deformation analysis in regions with sparse GNSS stations. A digital 3D terrain model is constructed using DEM data, and regional rock mass properties are integrated to simulate geological structures, resulting in the development of a 3D geological finite element model (FEM) using the ANSYS Workbench module. Gravity load and thermal constraints are applied to derive directional strain and deformation solutions, and the model results are compared to actual strain and tilt measurements from the Jiujiang Seismic Station (JSS). The results show that temperature variations significantly affect strain and deformation, particularly due to the elevation difference between the mountain base and summit. Higher temperatures increase thermal strain, causing tensile effects, while lower temperatures reduce thermal strain, leading to compressive effects. Strain and deformation patterns are strongly influenced by geological structures, gravity, and topography, with valleys experiencing tensile strain and ridges undergoing compression. The deformation trend indicates a southwestward movement across the study area. A comparison of FEM results with ten years of strain and tiltmeter data from JSS reveals a strong correlation between the model predictions and actual measurements, with correlation coefficients of 0.6 and 0.75 for strain in the NS and EW directions, and 0.8 and 0.9 for deformation in the NS and EW directions, respectively. These findings confirm that the 3D geological FEM is applicable for regional strain and deformation analysis, providing a feasible alternative in areas with limited GNSS monitoring. This method provides valuable insights into crustal deformation in regions with sparse strain and deformation measurement data.

Cranial endothermy in mobulid rays: Evolutionary and ecological implications of a thermogenic brain.

The large, metabolically expensive brains of manta and devil rays (Mobula spp.) may act as a thermogenic organ representing a unique mechanistic basis for cranial endothermy among fishes that improves central nervous system function in cold waters. Whereas early hominids in hot terrestrial environments may have experienced a thermal constraint to evolving larger brain size, cetaceans and mobulids in cold marine waters may have experienced a thermal driver for enlargement of a thermogenic brain. The potential for brain enlargement to yield the dual outcomes of cranial endothermy and enhanced cognition in mobulids suggests one may be an evolutionary by-product of selection for the mechanisms underlying the other, and highlights the need to account for non-cognitive functions when translating brain size into cognitive capacity. Computational scientific imaging offers promising avenues for addressing the pressing mechanistic and phylogenetic questions needed to assess the theory that cranial endothermy in mobulids is the result of temperature-driven selection for a brain with augmented thermogenic potential.

Turbulent transport mechanisms and their impact on the pedestal top of JET plasmas with small-ELMs

Abstract Understanding the transport mechanisms that regulate the H-mode pedestal structure is crucial for developing regimes with edge dynamics that are compatible with the thermal and particle load constraints of plasma facing components. In this regard, at the JET tokamak, H-mode plasma regimes featuring small-ELM (BSE) dynamics have been developed, expelling less plasma energy per ELM compared to the standard type-I ELM. The pedestal of these new regimes remains stable against peeling-ballooning modes, leaving its structure unexplained.
In this study, three baseline H-mode JET discharges, a reference with type-I ELM and two BSE regimes, are selected to investigate the turbulent transport mechanisms occurring in pedestals with different structures. The turbulence analysis is conducted using local gyrokinetic simulations around the pedestal top position. The results show that at ion-scales, while hybrid ITG-KBM and KBM are destabilized in the type-I ELM discharge, the BSE regimes are dominated by hybrid ITG-TEM, suggesting a different role of turbulent transport in the two cases. At electron-scales, both regimes are dominated by toroidal and slab ETG, the latter extending up to very small scales. Simulations of turbulence driven by hybrid ITG-TEM focuses on the impact and competition of electromagnetic (EM) effects and equilibrium $\vb*{E}\times\vb*{B}$ shearing. A strong EM stabilization mechanism is found, resulting in a saturated turbulence regime with spectra different from those in the electrostatic limit (ES$_l$). Additionally, while increasing $\vb*{E}\times\vb*{B}$ shearing reduces transport in ES$_l$ simulations, it is observed to have the opposite effect in the EM regime. Finally, stiff ETG transport is also shown to produce transport levels compatible with experimental observations.
The findings of this study suggest the EM stabilization and its competition with $\vb*{E}\times\vb*{B}$ shearing as new key elements determining the nature of the turbulent transport mechanisms around the pedestal top, which need to be considered in reduced models for pedestal limits.

Coupled tidal tomography and thermal constraints for probing Mars viscosity profile

Computing the tidal deformations of Mars, we explored various Mars spherically symmetric internal structures with different types of interface between the mantle and the liquid core. By assessing their compatibility with a diverse set of geophysical observations we show that despite the very short periods of excitation, tidal deformation is very efficient to constrain Mars interior. We calculated densities and thicknesses for Martian lithosphere, mantle, core–mantle boundary layers and core and found them consistent with preexisting results from other methods. We also estimated new viscosities for these layers. We demonstrated that the geodetic records associated with thermal constraints are very sensitive to the presence of a 2-layered interface on the top of the liquid core in deep Martian mantle. This interface is composed by 2 layers of similar densities but very different viscosity and rheology: the layer on the top of the core is liquid (Newtonian, NBL) and the one at the base of the mantle, overlaying the liquid one, is an Andrade layer (ABL) with a viscosity in average 10 orders of magnitude greater than the Newtonian layer. Our results also indicate that the existence of this 2-layered interface significantly impacts the viscosity profiles of the mantle and the lithosphere. More precisely, models including the 2-layered interface do not display significant viscosity contrast between the mantle and the lithosphere, preventing mechanical decoupling between a lithosphere and the mantle immediately below. Such models are in favor of a stagnant lid regime that can be supported by the current absence of an Earth-like plate tectonics on Mars. Finally, in our results, the presence of liquid Newtonian layer at the top of the liquid core is incompatible with the existence of a solid inner core.

Thermal constraints and gender-related differences in the activity patterns of the monomorphic rodent Clyomys laticeps

Abstract The daily activity pattern of animals can be classified as diurnal, nocturnal, crepuscular, and cathemeral reflecting strategic decisions to maximize mating and foraging while reducing predation risks and thermal constraints. Among monomorphic mammals, competition for resources and gender-related differences in physiology and reproductive strategies may translate into different activity patterns of males and females. Therefore, to understand the daily activity pattern both aboveground and belowground of the semifossorial rodent Clyomys laticeps, we tested the following hypotheses: (1) males and females differ in their diel activity patterns; (2) males are active for longer periods than females due to a promiscuous mating system and female site fidelity; and (3) higher maximum temperatures restrain C. laticeps activity. The study was carried out in the Serra de Caldas Novas State Park (Goiás, Brazil) in the Cerrado biome. The activity of C. laticeps was recorded using the telemetry technique over 5 days and nights (twice in each season, rainy and dry, between 2019 and 2021). Clyomys laticeps activity was bimodal, with 2 peaks around dawn and dusk, resembling a crepuscular pattern. Temporal segregation in male and female activity patterns was restricted to the dry season, when female activity was more diurnal than males who were mainly nocturnal. Intersexual competition for resources or male-avoidance behavior by females during the dry food scarcity season could contribute to this pattern, although it may also be explained by gender-related differences in thermal tolerances. Overall, males were active for longer periods than females, probably as a strategy to increase mating opportunities among the former and site fidelity in the latter. Finally, temperature imposed major constraints on C. laticeps activities who preferred milder temperatures and avoided being active in temperatures above their thermoneutral zone.

Thermodynamic and electrochemical performance coupling analysis of single ammonia-fueled tubular solid oxide fuel cell toward low operating temperatures

The primary development strategy for ammonia-fueled solid oxide fuel cell (SOFC) focuses on enhancing the cell lifetime by reducing the operating temperature, albeit inevitably affecting the cell output performance. This study has established a multi-physics model of the single ammonia-fueled tubular SOFC and conducted a thorough analysis and weighing of the improvements in cell stress and the losses in output performance at low temperature operating conditions. As the operating temperature is reduced from 800 °C to 700 °C, the inhomogeneity in its internal temperature distribution and stress distribution is significantly reduced, albeit with a concomitant increase in ohmic impedance by 1.75 Ω cm2 and a reduction in maximum power density by 42.16 %. The study employs the reduction of electrolyte thickness to compensate for the ohmic losses incurred by low temperature, while simultaneously incorporating a material thermal deformation constraint mechanism. As the electrolyte thickness is reduced from 200 μm to 20 μm, the overall thermal deformation variance ranges from 0.0977 to 0.1214. When the electrolyte thickness falls below 80 μm, there is a significant increase in thermal deformation variance. However, adjusting the electrolyte thickness within the range of 80–200 μm results in a relatively small change in overall thermal deformation variance, while also achieving a power density improvement of 0–30.57 %.

Optimal Fast-charging Strategy for Cylindrical Li-ion Cells

This paper presents an innovative approach to optimize the fast-charging strategy for cylindrical Li-ion NMC 3Ah cells, with a focus on enhancing both charging efficiency and thermal safety. Leveraging the power of Model Predictive Control (MPC), we introduce a cost function that approximates the thermal safety boundary of Li-ion batteries, revealing a relationship between temperature gradient and state of charge. Our proposed approach formulates the fast and safe charging problem as an optimal output regulator problem, incorporating thermal safety margin constraints. To solve the optimization problem, we develop an MPC algorithm. Our charge control structure incorporates an equivalent circuit model coupled with a thermal equation for battery state of charge and temperature estimation. Through numerical validation with real experimental data obtained from testing an NMC 3Ah cylindrical cell, we demonstrate that our approach respects the battery’s electrical and thermal constraints throughout the charging process.

Solving a bilevel strategic offering model for a generation company in a hydrothermal energy market: A new convexification approach

This paper proposes a bilevel strategic offering (SO) model suitable for a strategic company (SC) that operates in a hydro-dominated day-ahead energy market. The upper-level model of the proposed SO model maximizes the SC’s profits, while the lower-level model embodies a hydrothermal market clearing (MC). This MC incorporates detailed hydro and thermal constraints for units of both the SC and non-strategic companies (NSC), in addition to the network constraints. The proposed solution approach entails replacing the lower-level model with its corresponding primal and dual constraints, along with a strong duality equality constraint. This leads to a non-convex mathematical programming with equilibrium constraints (MPEC) model, which is then reformulated to feature only a single bilinear term in its structure. Finally, the recast MPEC model is convexified around an initial point and solved iteratively until a convergence criteria is achieved. The model and solution approach proposed are evaluated on an adapted version of the IEEE 24-bus system, exploring scenarios where the SC acts strategically or non-strategically (perfect competition).

NeuroTAP: Thermal and Memory Access Pattern-aware Data Mapping on 3D DRAM for Maximizing DNN Performance

Deep neural networks (DNNs) have been widely adopted, owing to break-through performance and high accuracy. DNNs exhibit varying memory behavior involving specific and recognizable memory access patterns and access intensity, depending on the selected data reuse in different layers. Such applications have high memory bandwidth demands due to aggressive computations, performing several billion-floating-point-operations-per-second (BFLOPs). 3D DRAMs, providing very high memory access bandwidth, are extensively employed to break the memory wall , bridging the gap between compute and memory while running DNNs. However, the vertical integration in 3D DRAM introduces serious thermal issues, resulting from high power density and close proximity of memory cells, and requires dynamic thermal management (DTM). To unleash the true potential of 3D DRAM and exploit the enormous bandwidth under thermal constraints, there is a need to intelligently map the DNN application’s data across memory channels, pseudo-channels, and banks, minimizing the effective memory latency and reducing the thermal-induced application slowdown. The specific memory access patterns exhibited by a DNN layer execution are crucial to determine a favourable data mapping method for 3D DRAM dies that potentially causes minimal thermal impact, and also maximize DRAM bandwidth utilization. In this work, we propose an application-aware and thermal-sensitive data mapping that intelligently assigns portions of the 3D DRAM to DNN layers, leveraging the knowledge about layer’s memory access patterns and minimizing DTM-induced performance overheads. Additionally, we also deploy a DRAM low-power states based DTM mechanism to keep the 3D DRAM within safe thermal limits. Using our proposal, we observe a performance improvement of 1% to 61%, and memory energy savings of 1% to 55% for popular deep neural networks over state-of-the-art DTM strategies while running DNN inference.

Nanofluids' thermal assessment: Active and passive control approach

The nanofluids are decomposition of nano-sized metallic particles with base materials maintaining peak thermal properties. Owing to enhanced thermal features, various applications of nanofluids are observed in enhancing energy resources and cooling processes. The objective of current work is exploring the thermal impact of nanofluid associated to the oblique stagnation point flow. The thermal interpretation of nanofluid is subject to active and passive control approach. The heat trnasfer analysis is identified by using convective thermal flow constraints. The Buongiorno nanofluid model is adopted, endorsing the Brownian and thermophoresis consequences. The flow problem is first simplfied intodimensionless form. The numerical computations are performed by using famous shooting scheme with justifiable accuracy. A comparative change in the thermal phenomenon given the passive and active frameworks is presented. It is exmained that heat transfer reduces for stretching ratio parameter. The concentration profile reduces for angle of incidence for both active and passive control approach.

Robin and zero‐mass diffusion analysis for radiated unsteady flow of Maxwell nanofluid due to porous stretched regime: Analytical simulations

AbstractOwing to the multidisciplinary applications of nanomaterials, a wide range of research has been conducted on this topic recently. The aim of current research is to analyze the enhancement of heat transfer due to the unsteady flow of Maxwell nanofluid associated with the zero mass thermal constraints. The applications of the radiated phenomenon and magnetic force are contributed to the current flow problem. The analysis is subject to the implementation of Robin and zero‐mass diffusion constraints. A bidirectional moving porous surface endorsed the flow. The appropriate variables are taken for simplifying the system. The homotopy analysis method (HAM) is used to compute the solution procedure. The obtained results are confirmed with already performed studies. It has been observed that the temperature and nanoparticle concentration distributions decrease for higher unsteady parameter values.

Energy-aware virtual machine placement based on a holistic thermal model for cloud data centers

As energy-intensive infrastructures, data centers (DCs) have become a pressing challenge for managers due to their significant energy consumption and carbon emissions. Information technology (IT) and cooling systems contribute the most to energy consumption. Energy-aware virtual machine (VM) scheduling methods have been widely demonstrated to reduce energy consumption and operating costs in DCs. However, as realistic DCs exhibit complex power and thermodynamic behaviors, existing works cannot provide efficient measures to optimize computing and cooling power consumption simultaneously. To overcome this challenge, we construct a holistic thermal model (including CPU and server inlet thermal models) to accurately represent the non-uniform, dynamic thermal environment. Subsequently, this work proposes a thermal model-based energy-aware VM placement method (TEVP) to minimize the holistic energy consumption of the DCs, considering resource and thermal constraints. We develop a novel hybrid swarm intelligence algorithm (DE-ERPSO) combining differential evolution (DE) and particle swarm optimization with an elite re-selection mechanism (ERPSO) to explore more energy-efficient VM placement schemes. Extensive experiments are conducted on an extended CloudSim to validate the performance of the proposed TEVP using real-world workload traces (PlanetLab and Azure). Results show that TEVP saves over 5.6% of the total energy consumption over the advanced baselines while maintaining low thermal violations.

A new model of electrosurgical tissue damage for neurosurgery simulation

BackgroundBipolar hemostasis electrocoagulation is a fundamental procedure in neurosurgery. A precise electrocoagulation model is essential to enable realistic visual feedback in virtual neurosurgical simulation. However, existing models lack an accurate description of the heat damage and irreversible tissue deformation caused by electrocoagulation, thus diminishing the visual realism. This work focuses on the electrocoagulation model for neurosurgery simulation. MethodIn this paper, a position-based dynamics (PBD) model with a bioheat transfer and damage prediction (BHTDP) method is developed for simulating the deformation of brain tissue caused by electrocoagulation. The presented BTHDP method uses the Arrhenius equation to predict thermal damage of brain tissue. A deformation model with energy and thermal damage constraints is developed to characterize soft tissue deformation during heat absorption before and after thermal injury. Visual effect of damaged brain tissue is re-rendered. ResultTo evaluate the accuracy of the proposed method, numerical simulations were conducted and compared with commercial finite element software. The maximum normalized error of the proposed model for predicting midpoint temperature is 10.3 % and the maximum error for predicting the thermal damage is 5.4 %. The contraction effects of heat-exposed anisotropic tissues are also simulated. The results indicate that the presented electrocoagulation model provides stable and realistic visual effects, making it applicable for simulating the electrocoagulation process in virtual neurosurgery.