Energy Response Research Articles

Performance of the CMS High Granularity Calorimeter prototype to charged pion beams of 20–300 GeV/c

The upgrade of the CMS experiment for the high luminosity operation of the LHC comprises the replacement of the current endcap calorimeter by a high granularity sampling calorimeter (HGCAL). The electromagnetic section of the HGCAL is based on silicon sensors interspersed between lead and copper (or copper tungsten) absorbers. The hadronic section uses layers of stainless steel as an absorbing medium and silicon sensors as an active medium in the regions of high radiation exposure, and scintillator tiles directly read out by silicon photomultipliers in the remaining regions. As part of the development of the detector and its readout electronic components, a section of a silicon-based HGCAL prototype detector along with a section of the CALICE AHCAL prototype was exposed to muons, electrons and charged pions in beam test experiments at the H2 beamline at the CERN SPS in October 2018. The AHCAL uses the same technology as foreseen for the HGCAL but with much finer longitudinal segmentation. The performance of the calorimeters in terms of energy response and resolution, longitudinal and transverse shower profiles is studied using negatively charged pions, and is compared to GEANT4 predictions. This is the first report summarizing results of hadronic showers measured by the HGCAL prototype using beam test data.

Molecular Docking and Pharmacokinetic Prediction of Potential Compounds from Luffa acutangula as Antidiabetic Candidates

Luffa acutangula is commonly used, but its considerable potential as an alternative treatment for diabetics with a molecular target action is not yet known. Preliminary study of bioinformatics to decipher the compounds of L. acutangulaable to interact with the protein targets of antidiabetic therapy. This study aims to identify the potential compounds of L. acutangula that are thought to interact with the insulin receptor, aldose reductase, and PTP-1B, as well as provide predictions of pharmacokinetics and toxicity. Molecular docking was conducted in AutoDock 4.2.6 with the stages initiated by the preparation of macromolecules (PDB ID: 1IR3; 2PEV; 4Y14) and ligands, molecular docking, and visualization. The pharmacokinetic profiles are predictable by using the Swiss ADME and toxicity estimates by Toxtree. The results showed that cucurbitacin B, cucurbitacin E, oleanolic acid, catechin, ferulic acid and apigenin are the most potential compounds to interact with the macromolecular with a binding energy response similar to the native ligand. Pharmacokinetic predictions show that cucurbitacin B and cucurbitacin E deviate from one Lipinski rule (BM> 500), do not diffuse into the blood brain barrier, are not CYP450 inhibitors, as well as classified as Pgp substrates. The prediction of toxicity indicates that all potential compounds are classified as high toxicity compounds with a risk of narcosis, except oleanolic acid and ferulic acid. These compounds are not genotoxic or non-genotoxic carcinogens.

Comparative study on seismic performance of structure with TMD and particle TMD considering SSI effects

Tuned mass dampers (TMDs) are widely adopted to suppress structural response under dynamic loads. Some novel nonlinear TMDs have been developed to improve control performance, such as particle TMD (PTMD). The damping mechanism of TMD and PTMD are linear and nonlinear, respectively. Ignoring soil-structure interaction (SSI) effects may lead to inaccurate evaluation for the structural seismic responses and effectiveness of TMDs. In this study, the seismic control performance of the linear TMD and the nonlinear PTMD considering SSI effects are explored. Based on the shaking table test results, the mitigation effects of TMD and PTMD on floor acceleration and displacement responses are compared, in terms of average decreasing amplitude ratios and root-mean-square decreased ratios. Furthermore, to provide insights into the mitigation mechanism of TMD and PTMD including SSI effects, the recorded signals are decomposed and the energy response analysis is conducted using wavelet packet transform. The results show that when SSI effects are included, the performance of the linear TMD and the nonlinear PTMD on acceleration response is close, but the effectiveness of the linear TMD on displacement response and energy response is superior to that of PTMD. This study improves the understanding of TMDs’ effectiveness in SSI system subjected to seismic excitations.

The INFN proton computed tomography system for relative stopping power measurements: calibration and verification

Objective. This paper describes the procedure to calibrate the three-dimensional (3D) proton stopping power relative to water (SPR) maps measured by the proton computed tomography (pCT) apparatus of the Istituto Nazionale di Fisica Nucleare (INFN, Italy). Measurements performed on water phantoms are used to validate the method. The calibration allowed for achieving measurement accuracy and reproducibility to levels below 1%. Approach. The INFN pCT system is made of a silicon tracker for proton trajectory determination followed by a YAG:Ce calorimeter for energy measurement. To perform the calibration, the apparatus has been exposed to protons of energies ranging from 83 to 210 MeV. Using the tracker, a position-dependent calibration has been implemented to keep the energy response uniform across the calorimeter. Moreover, correction algorithms have been developed to reconstruct the proton energy when this is shared in more than one crystal and to consider the energy loss in the non-uniform apparatus material. To verify the calibration and its reproducibility, water phantoms have been imaged with the pCT system during two data-taking sessions. Main results. The energy resolution of the pCT calorimeter resulted to be at 196.5 MeV. The average values of the water SPR in fiducial volumes of the control phantoms have been calculated to be 0.995±0.002. The image non-uniformities were below 1%. No appreciable variation of the SPR and uniformity values between the two data-taking sessions could be identified. Significance. This work demonstrates the accuracy and reproducibility of the calibration of the INFN pCT system at a level below 1%. Moreover, the uniformity of the energy response keeps the image artifacts at a low level even in the presence of calorimeter segmentation and tracker material non-uniformities. The implemented calibration technique allows the INFN-pCT system to face applications where the precision of the SPR 3D maps is of paramount importance.

Deformation behaviour, crack initiation and crack damage of weathered composite sandstone-shale by using the ultrasonic wave and the acoustic emission under uniaxial compressive stress

Anticipating the progressive damage and strength of an anisotropic and interbedded rock mass is challenging due to the overwhelming variables which need to be considered. Therefore, the strength and progressive damage of each rock material is not a realistic model which can be used to define the deformation of the interbedded anisotropic rock mass. In this research, weathered (sandstone-shale-sandstone) composite samples under unconfined compressive stresses were concurrently assessed using acoustic emission (AE) and ultrasonic pulses. Shale interlayer significantly impacts the composite's behaviour, according to the mechanical properties and stress-strain relationships of weathered sandstone, shale, and composite. The deformation behaviour was derived following (velocity, amplitude and energy) responses of both the ultrasonic and AE waves. The intensity of AE energy reflects the best interaction with the progressive deformation of the rocks under uniaxial stress. Although the ultrasonic velocity was only sensitive toward the macro-deformation or specimen failure, the ultrasonic parameters (i.e., amplitude and energy) reflected a substantial alteration, specifically during the plastic deformation. The cumulative AE energy tangent (CSEET) method exhibited clear uncertainties in defining the CI and CD of composite specimens compared to sandstone and shale. The impact of AE energy attenuation due to the joint between shale and sandstone in the composite specimen was highlighted. For instance, the AE energy induced by CI and CD was about 6.0 E+09 mV and 2.4 E+11 mV for sandstone, 2.0 E+08 mV and 2.5 E+8 mV for shale, 1.6 E+08 mV and 2.2 E+8 mV for composite. The crack initiation (CI) (i.e., represents the plastic threshold of rock where the micro-cracks took place), and the crack damage (CD) (i.e., represents the stage where unstable macro-cracks begin to grow), which was indicated by the ultrasonic parameters, were addressed as alternative novel approaches for determining the plastic deformation of composite specimens. The CI commenced at 43%–80%, 53%–78%, and 35%–55% of the peak stress, whereas the CD occurred at 84%–97%, 78%–95%, and 75%–94% of the peak stress for the weathered sandstone, weathered shale, and composite, respectively. This research may help evaluate the deformation behaviour of the interbedded rock masses using the ultrasonic approach, presuming a sufficient material strength differential between the interbedded rocks.

Structural insights into redox signal transduction mechanisms in the control of nitrogen fixation by the NifLA system

NifL is a conformationally dynamic flavoprotein responsible for regulating the activity of the σ54-dependent activator NifA to control the transcription of nitrogen fixation (nif) genes in response to intracellular oxygen, cellular energy, or nitrogen availability. The NifL-NifA two-component system is the master regulatory system for nitrogen fixation. NifL serves as a sensory protein, undergoing signal-dependent conformational changes that modulate its interaction with NifA, forming the NifL-NifA complex, which inhibits NifA activity in conditions unsuitable for nitrogen fixation. While NifL-NifA regulation is well understood, these conformationally flexible proteins have eluded previous attempts at structure determination. In work described here, we advance a structural model of the NifL dimer supported by a combination of scattering techniques and mass spectrometry (MS)-coupled structural analyses that report on the average structure in solution. Using a combination of small angle X-ray scattering-derived electron density maps and MS-coupled surface labeling, we investigate the conformational dynamics responsible for NifL oxygen and energy responses. Our results reveal conformational differences in the structure of NifL under reduced and oxidized conditions that provide the basis for a model for modulating NifLA complex formation in the regulation of nitrogen fixation in response to oxygen in the model diazotroph, Azotobacter vinelandii.

Optical Properties of MoSe2 Monolayer Implanted with Ultra-Low-Energy Cr Ions.

This paper explores the optical properties of an exfoliated MoSe2 monolayer implanted with Cr+ ions, accelerated to 25 eV. Photoluminescence of the implanted MoSe2 reveals an emission line from Cr-related defects that is present only under weak electron doping. Unlike band-to-band transition, the Cr-introduced emission is characterized by nonzero activation energy, long lifetimes, and weak response to the magnetic field. To rationalize the experimental results and get insights into the atomic structure of the defects, we modeled the Cr-ion irradiation process using ab initio molecular dynamics simulations followed by the electronic structure calculations of the system with defects. The experimental and theoretical results suggest that the recombination of electrons on the acceptors, which could be introduced by the Cr implantation-induced defects, with the valence band holes is the most likely origin of the low-energy emission. Our results demonstrate the potential of low-energy ion implantation as a tool to tailor the properties of two-dimensional (2D) materials by doping.

BGO quenching effect on spectral measurements of cosmic-ray nuclei in DAMPE experiment

The Dark Matter Particle Explorer (DAMPE) is a satellite-borne detector designed to measure high energy cosmic-rays and γ-rays. As a key sub-detector of DAMPE, the Bismuth Germanium Oxide (BGO) imaging calorimeter is utilized to measure the particle energy with a high resolution. The nonlinear fluorescence response of BGO for large ionization energy deposition, known as the quenching effect, results in an under-estimate of the energy measurement for cosmic-ray nuclei. In this paper, various models are employed to characterize the BGO quenching factors obtained from the experimental data of DAMPE. Applying the proper quenching model in the detector simulation process, we investigate the tuned energy responses for various nuclei and compare the results based on two different simulation softwares, i.e. GEANT4 and FLUKA. The BGO quenching effect results in a decrease of the measured energy by approximately 2.5% (5.7%) for carbon (iron) at ∼10 GeV/n and <1% above 1 TeV/n, respectively. Accordingly, the correction of the BGO quenching effect leads to an increase of the low-energy flux measurement of cosmic-ray nuclei.

A macroscopic constitutive relation for isotropic-genesis, polydomain liquid crystal elastomers

Liquid crystal elastomers (LCEs) are rubber-like solids that incorporate nematic mesogens (stiff rod-like molecules) as a part of their polymer chains. In recent years, isotropic-genesis, polydomain liquid crystal elastomers (I-PLCEs) has been a topic of both scientific and technological interest due to their intriguing properties such as soft behavior, ability to dissipate energy and stimuli response, as well as the ease with which they can be synthesized. We present a macroscopic or engineering scale constitutive model of the behavior of I-PLCEs. The model implicitly accounts for the complex evolution of the domain patterns and is able to faithfully capture the experimentally observed complex response to multi-axial loading. We describe a multiscale framework that motivates the model, explore various aspects of the model, validate it against experiments, and finally verify and demonstrate a numerical implementation.

Empirical optimization of energy bin weights for compressing measurements with realistic photon counting x-ray detectors.

Photon counting detectors (PCDs) provide higher spatial resolution, improved contrast-to-noise ratio (CNR), and energy discriminating capabilities. However, the greatly increased amount of projection data in photon counting computed tomography (PCCT) systems becomes challenging to transmit through the slip ring, process, and store. This study proposes and evaluates an empirical optimization algorithm to obtain optimal energy weights for energy bin data compression. This algorithm is universally applicable to spectral imaging tasks including 2 and 3 material decomposition (MD) tasks and virtual monoenergetic images (VMIs). This method is simple to implement while preserving spectral information for the full range of object thicknesses and is applicable to different PCDs, for example, silicon detectors and CdTe detectors. We used realistic detector energy response models to simulate the spectral response of different PCDs and an empirical calibration method to fit a semi-empirical forward model for each PCD. We numerically optimized the optimal energy weights by minimizing the average relative Cramér-Rao lower bound (CRLB) due to the energy-weighted bin compression, for MD and VMI tasks over a range of material area density (0-40g/cm2 water, 0-2.16g/cm2 calcium). We used Monte Carlo simulation of a step wedge phantom and an anthropomorphic head phantom to evaluate the performance of this energy bin compression method in the projection domain and image domain, respectively. The results show that for 2 MD, the energy bin compression method can reduce PCCT data size by 75% and 60%, with an average variance penalty of less than 17% and 3% for silicon and CdTe detectors, respectively. For 3 MD tasks with a K-edge material (iodine), this method can reduce the data size by 62.5% and 40% with an average variance penalty of less than 12% and 13% for silicon and CdTe detectors, respectively. We proposed an energy bin compression method that is broadly applicable to different PCCT systems and object sizes, with high data compression ratio and little loss of spectral information.

Dose distributions of the INTRABEAM electronic brachytherapy system measured with traceable detectors

In this work, a methodology to determine the absorbed dose rate to water distribution from electronic brachytherapy (eBT) units is suggested. It involves measuring directly in a full scatter water tank with small active detectors whose energy response at low X-ray photon energies have been previously characterized. Dose distributions of an INTRABEAM PRS 500 system in two configurations — bare needle and with the spherical applicator of 40 mm diameter — were measured in water using the Exradin A26 ionization chamber and the PTW 60019 microDiamond detector. The continuous energy response of these two detectors in terms of air kerma from 5 keV to 70 keV (eBT energy range) was available from a previous calibration at several X-ray radiation qualities. Here, it is converted to the response in absorbed dose to water using correction factors obtained with Monte Carlo (MC) particle transport simulations. The detectors were modelled using the MCNP code. The air kerma calibration factors were simulated and compared with measurements to refine and validate the models. A series of simulations of the experimental arrangement of the INTRABEAM and the detector were carried out for determining the system specific detector correction factors. These values are distance-dependent due to the steep dose gradient and the remarkable spectral changes around the eBT source in water. The dose rate with distance from the source, the radial and the polar distributions of the INTRABEAM are reported and compared with the manufacturers supplied data. This work is an effort to provide traceability for detectors and measurement procedures for the determination of 3D dose distributions as part of the European joint research project “Primary standards and traceable measurement methods for X-ray emitting electronic brachytherapy devices” (18NRM02 PRISM-eBT).

Crystal phase control and ignition properties of HNS/CL-20 composite microspheres prepared by microfluidics combined with emulsification techniques

Improved controllability and energy density of ignition agents are of great significance for the development of energetic composite materials. In this study, droplet microfluidics and emulsification techniques were combined to prepare HNS/CL-20 composite microspheres with polyglycidyl azide polymer (GAP) as the binder. The influence of binder content on the morphology of microspheres was investigated, and the microspheres were characterized and tested for particle size, crystal structure, thermal decomposition, dispersibility, mechanical sensitivity, combustion behavior and detonation performance. The results showed that microspheres prepared with a binder content of 3% had higher sphericity and particle size uniformity. The microspheres retained the crystal structure of both HNS and CL-20 (ε-type). Compared with raw HNS, the microspheres had higher apparent activation energy, better safety performance, and good dispersibility. The ignition experiments and detonation performance tests show that HNS/CL-20 composite microspheres have excellent ignition performance, obvious combustion flame, and significant energy release effects, which are expected to achieve high energy and high-speed response of the igniter, thus improving the ignition reliability in special environments or systems.

Enhanced interlaminar mechanical behavior of advanced fiber metal laminates via nano Al2O3‐IPN formation and surface pre‐treatments

AbstractThe inferior delamination resistance and out‐of‐plane performance of fiber metal laminates (FMLs) are of serious concerns. This work employs two modification methods, namely metal surface's chemical pre‐treatment and nano Al2O3 embedded interpenetrating polymer network (IPN) formation for improving the delamination resistance of aluminum and glass fiber‐reinforced polymer (GFRP) composite‐based FMLs. The synergetic effect of the two modification techniques resulted in high degrees of improvement in delamination resistance that were ~28% for critical strain energy release rate during mode‐I interlaminar fracture toughness (ILFT), that is (GIC) and ~37% for GIIC. Simultaneously, the flexural strength, tensile strength, and interlaminar shear strength improved by ~23%, ~17%, and ~24%, respectively. Scanning electron microscopy, atomic force microscopy, and surface energy measurement studies showed that the chemical pre‐treatment significantly influenced the surface morphology, surface roughness, and surface energy responses of aluminum, respectively. Fractographic study validated the effect of modification methods on the failure behavior under various testing modes.

The energy response of LiF:Mg,Ti radioluminescent detector: A Monte Carlo simulation and experimental tests

It has been reported that LiF as commonly used thermoluminescent dosimeter (TLD) has a flat energy response, yet the energy dependence as radioluminescent (RL) detector has not been reported up to now. LiF is a near-tissue-equivalent material with a low effective atomic number, leading to its intrinsic virtue of flat energy response, theoretically. In this paper, Super-MC software was employed to simulate the energy deposition of LiF, the energy response of which was compared with NaI, and then the influence of the size of the detector on energy response was also investigated. Finally, the experimental verification of RL energy response was performed based on an in-house developed detector coupled LiF:Mg,Ti crystal with SiPM. The experimental energy responses (with respect to 137Cs) of three volume detector show good agreement (within ±30% in the range of 33 keV–1.25 MeV) with MC simulation results, which proved that LiF:Mg,Ti has a flat energy response, and it is feasible to obtain real-time dose-rate from count-rate collection without traditional method of hardware compensation or energy spectrum acquisition. In conclusion, this scheme can be a promising candidate for the rapid and accurate real-time dosimetry in the future, simplifying detector structure and measurement algorithm.

Optimal Scheduling Strategy for Multi-Energy Microgrid Considering Integrated Demand Response

Research on energy storage plants has gained significant interest due to the coupled dispatch of new energy generation, energy storage plants, and demand-side response. While virtual power plant research is prevalent, there is comparatively less focus on integrated energy virtual plant station research. This study aims to contribute to the integrated energy virtual plant station research by exploring the relationship between the integrated energy electro-thermal coupling capacity, various forms of electro-thermal integrated energy response, and electro-thermal integrated energy storage. Analyzing the attributes of an integrated energy microgrid, including energy storage characteristics, time-of-use tariffs, and electric and thermal loads, is crucial. A grid-connected microgrid with cogeneration systems, electric boilers, fuel cells, and energy storage systems is used as an illustrative example. The dispatching method prioritizes multiple complementary energy sources while considering the integrated energy demand response. The study presents different models for the electricity demand and thermal energy demand response and introduces the design of a wholesale power trader involved in building energy storage facilities and participating in the demand response. To verify the feasibility and rationality of the integrated energy demand response scenario, three different schemes are compared, and an economic analysis is conducted.

Performance Evaluation of Hybrid Meta-Heuristics-Based Task Scheduling Algorithm for Energy Efficiency in Fog Computing

Task scheduling in fog computing is one of the areas where researchers are having challenges as the demand grows for the use of internet of things (IoT) to access cloud computing resources. Many resource scheduling and optimization algorithms were used by many researchers in fog computing; some used single techniques while others used combined schemes to achieve dynamic scheduling in fog computing, many optimization techniques were assessed based on deterministic and meta-heuristic to find out solution to task scheduling problem in fog computing but could not achieve excellent results as required. This article proposes hybrid meta-heuristic optimization algorithm (HMOA) for energy efficient task scheduling in fog computing, the study combined modified particle swarm optimization (MPSO) meta-heuristic and deterministic spanning tree (SPT) to achieve task scheduling with the intention of eliminating the drawbacks of the two algorithms when used separately, the MPSO was used to schedule user task requests among fog devices, while hybrid MPSO-SPT was used to perform resource allocation and resource management in the fog computing environment. The study implemented the proposed algorithm using iFogSim; the performance of the algorithm was evaluated, assessed, and compared with other state-of-the-art task scheduling and resource management algorithms, the proposed method performs better in terms of energy consumption, resource utilization and response time, and the study proposed future research on evaluating the execution time using the hybrid algorithm.

Spatiotemporal parameters for energy efficient kilohertz-frequency nerve block with low onset response

BackgroundElectrical nerve conduction block has great potential for treatment of disease through reversible and local inactivation of somatic and autonomic nerves. However, the relatively high energy requirements and the presence of undesired excitation at the onset of the kilohertz-frequency (KHF) signals used for block pose obstacles to effective translation. Frequency, electrode geometry, and waveform shape are known to influence block threshold and onset response, but available data provide a limited understanding of how to select these parameters to optimize nerve block.MethodsWe evaluated KHF nerve block in rat tibial nerve across frequencies (5–60 kHz), electrode geometries (monopolar, bipolar, and tripolar), and waveform shapes. We present a novel Fourier-based method for constructing composite signals that systematically sample the KHF waveform design space.ResultsThe lowest frequencies capable of blocking (5–16 kHz) were not the most energy-efficient among the tested frequencies. Further, bipolar cuffs required the largest current and power to block, monopolar cuffs required the lowest current, and both tripolar and monopolar cuffs required the lowest power. Tripolar cuffs produced the smallest onset response across frequencies. Composite signals comprised of a first harmonic sinusoid at fundamental frequency (f0) superposed on a second harmonic sinusoid at 2f0 could block at lower threshold and lower onset response compared to the constituent sinusoids alone. This effect was strongly dependent on the phase of the second harmonic and on the relative amplitudes of the first and second harmonics. This effect was also dependent on electrode geometry: monopolar and tripolar cuffs showed clear composite signal effects in most experiments; bipolar cuffs showed no clear effects in most experiments.ConclusionsOur data provide novel information about block threshold and onset response at the boundary of frequencies that can block. Our results also show an interaction between spatial (cuff geometry) and temporal (frequency and waveform shape) parameters. Finally, while previous studies suggested that temporal parameters could reduce onset response only in exchange for increased block threshold (or vice versa), our results show that waveform shape influences KHF response in ways that can be exploited to reduce both energy and onset responses.

MultiPsi: A python‐driven MCSCF program for photochemistry and spectroscopy simulations on modern HPC environments

AbstractWe present MultiPsi, an open‐source MCSCF program for the calculation of ground and excited states properties of strongly correlated systems. The program currently implements a general MCSCF code with excited states available using either state‐averaging or linear response. It is written in a highly modular fashion using Python/C++ which makes it well suited as a development platform, enabling easy prototyping of novel methods, and as a teaching tool using interactive notebooks. The code is also very efficient and designed for modern high‐performance computing environments using hybrid OpenMP/MPI parallelization. This efficiency is demonstrated with the calculation of the CASSCF energy and linear response of a molecule with more than 700 atoms as well as a fully optimized conventional CI calculation on more than 400 billion determinants.This article is categorized under: Software &gt; Quantum Chemistry Electronic Structure Theory &gt; Ab Initio Electronic Structure Methods Theoretical and Physical Chemistry &gt; Spectroscopy

Brain responses to energy intake and its association with cognition in Alzheimer’s Disease

AbstractBackgroundTo evaluate the brain response to energy intake using cerebral blood flow(CBF) in Alzheimer’s disease (AD), mild cognitive impairment (MCI) and healthy controls (HC) and its relationship with cognition.MethodA self‐comparison design was used to test the effects of energy intake on brain activity in participants with AD (n = 30), MCI participants (n = 32), and HC (n = 30) and its relationship with cognitive function. Brain perfusion was measured using arterial spin labeling (ASL) functional brain imaging. Participants arrived at the site in the morning and underwent the ASL‐MRI with at least 10 hours fasting overnight. Then the second ASL‐MRI at 30 minutes after eating a standard breakfast was performed. Energy response ΔCBF was computed by subtracting the fasting CBF from the postprandial CBF obtained from ASL‐MRI. Whole brain grey matter voxel‐wise paired T test and linear regression analyses were used for statistical analysis.ResultAD and MCI group had different energy response ΔCBF pattern with HC group. In AD group, energy intake induced a significantly decreased CBF in temporal lobe including lateral inferior and superior temporal gyrus, right superior temporal gyrus, parietal lobe including bilateral superior and inferior parietal lobe, postcentral gyrus and precuneus, most of occipital lobe and frontal lobe including right rolandic operculum, right precentral gyrus and left middle frontal gyrus. (q &lt; 0.05, false discovery rate corrected). MCI had similar energy intake response pattern with AD. HC group had no significantly changed CBF response to energy intake. Energy response ΔCBF in the vicinity of the superior temporal gyrus showed significant negative correlation with Minimum Mental State Examination (MMSE) in all AD, MCI and HC groups.ConclusionThe different energy response ΔCBF pattern may help to characterize the energy disorder in AD and may indicate the different brain energy rescue effect in the three groups. Energy response ΔCBF in the superior temporal gyrus is an indicator of cognitive function in AD.

A Light Weight Optimal Resource Scheduling Algorithm for Energy Efficient and Real Time Cloud Services

Abstract: Cloud computing has become an essential technology for providing various services to customers. Energy consumption and response time are critical factors in cloud computing systems. Therefore, scheduling algorithms play a vital role in optimizing resource usage and improving energy efficiency. In this paper, we propose a lightweight optimal scheduling algorithm for energy-efficient and real-time cloud services. Our algorithm considers the trade-off between energy consumption and response time and provides a solution that optimizes both factors. We evaluate our algorithm on a cloud computing testbed using the Cloud Sim simulation toolkit and compare it with load balancing round robin, ant colony, genetic algorithm, and analytical algorithm. The results show that our proposed algorithm outperforms these algorithms in terms of energy efficiency and response time.