Diagnostic Accuracy of Computerized Bowel Sound Analysis with Non-Invasive Devices for Irritable Bowel Syndrome:A Systematic Review and Meta-Analysis

Objective To assess the diagnostic accuracy of bowel sound analysis for irritable bowel syndrome(IBS)with a systematic review and meta-analysis.Methods We searched MEDLINE,Embase,the Cochrane Library,Web of Science,and IEEE Xplore databases until September 2023.Cross-sectional and case-control studies on diagnostic accuracy of bowel sound analysis for IBS were identified.We estimated the pooled sensitivity,specificity,positive likelihood ratio,negative likeli-hood ratio,and diagnostic odds ratio with a 95% confidence interval(CI),and plotted a summary receiver operat-ing characteristic curve and evaluated the area under the curve.Results Four studies were included.The pooled diagnostic sensitivity,specificity,positive likelihood ratio,nega-tive likelihood ratio,and diagnostic odds ratio were 0.94(95%CI,0.87‒0.97),0.89(95%CI,0.81‒0.94),8.43(95%CI,4.81‒14.78),0.07(95%CI,0.03‒0.15),and 118.86(95%CI,44.18‒319.75),respectively,with an area under the curve of 0.97(95%CI,0.95‒0.98).Conclusions Computerized bowel sound analysis is a promising tool for IBS.However,limited high-quality data make the results'validity and applicability questionable.There is a need for more diagnostic test accuracy studies and better wearable devices for monitoring and analysis of IBS.

Urea breath test for Helicobacter pylori infection in adult dyspeptic patients: A meta-analysis of diagnostic test accuracy

BACKGROUND Helicobacter pylori(H.pylori)infection has been well-established as a significant risk factor for several gastrointestinal disorders.The urea breath test(UBT)has emerged as a leading non-invasive method for detecting H.pylori.Despite numerous studies confirming its substantial accuracy,the reliability of UBT results is often compromised by inherent limitations.These findings underscore the need for a rigorous statistical synthesis to clarify and reconcile the diagnostic accuracy of the UBT for the diagnosis of H.pylori infection.AIM To determine and compare the diagnostic accuracy of 13C-UBT and 14C-UBT for H.pylori infection in adult patients with dyspepsia.METHODS We conducted an independent search of the PubMed/MEDLINE,EMBASE,and Cochrane Central databases until April 2022.Our search included diagnostic accuracy studies that evaluated at least one of the index tests(^(13)C-UBT or ^(14)C-UBT)against a reference standard.We used the QUADAS-2 tool to assess the methodo-logical quality of the studies.We utilized the bivariate random-effects model to calculate sensitivity,specificity,positive and negative test likelihood ratios(LR+and LR-),as well as the diagnostic odds ratio(DOR),and their 95%confidence intervals.We conducted subgroup analyses based on urea dosing,time after urea administration,and assessment technique.To investigate a possible threshold effect,we conducted Spearman correlation analysis,and we generated summary receiver operating characteristic(SROC)curves to assess heterogeneity.Finally,we visually inspected a funnel plot and used Egger’s test to evaluate publication bias.endorsing both as reliable diagnostic tools in clinical practice.CONCLUSION In summary,our study has demonstrated that ^(13)C-UBT has been found to outperform the ^(14)C-UBT,making it the preferred diagnostic approach.Additionally,our results emphasize the significance of carefully considering urea dosage,assessment timing,and measurement techniques for both tests to enhance diagnostic precision.Nevertheless,it is crucial for researchers and clinicians to evaluate the strengths and limitations of our findings before implementing them in practice.

Further Analysis of Machine Tool Dimensional Accuracy and Thermal Stability under Varying Floor Temperature

Machining is as old as humanity, and changes in temperature in both the machine’s internal and external environments can be of great concern as they affect the machine’s thermal stability and, thus, the machine’s dimensional accuracy. This paper is a continuation of our earlier work, which aimed to analyze the effect of the internal temperature of a machine tool as the machine is put into operation and vary the external temperature, the machine floor temperature. Some experiments are carried out under controlled conditions to study how machine tool components get heated up and how this heating up affects the machine’s accuracy due to thermally induced deviations. Additionally, another angle is added by varying the machine floor temperature. The parameters mentioned above are explored in line with the overall thermal stability of the machine tool and its dimensional accuracy. A Robodrill CNC machine tool is used. The CNC was first soaked with thermal energy by gradually raising the machine floor temperature to a certain level before putting the machine in operation. The machine was monitored, and analytical methods were deplored to evaluate thermal stability. Secondly, the machine was run idle for some time under raised floor temperature before it was put into operation. Data was also collected and analyzed. It is observed that machine thermal stability can be achieved in several ways depending on how the above parameters are joggled. This paper, in conclusion, reinforces the idea of machine tool warm-up process in conjunction with a carefully analyzed and established machine floor temperature variation for the approximation of the machine tool’s thermally stability to map the long-time behavior of the machine tool.

Accuracy and Utility of Vessel Analysis Using Non-Contrast CT for Planning Endovascular Aortic Repair

Objectives: This study aimed to determine whether errors in vascular measurements would affect device selection in endovascular aortic repair (EVAR) by comparing measurements obtained using non-contrast computed tomography (NCT) with those obtained using contrast-enhanced CT (CECT). Materials and Methods: This single-center, retrospective study included 25 patients who underwent EVAR for abdominal aortic aneurysm at our institution. A 1-mm horizontal cross-sectional slice of NCT and CECT from each patient was retrospectively reviewed. The area from the abdominal aorta to the common iliac artery was divided into four zones. A centerline was created using the NCT by manually plotting the center points. Subsequently, the centerlines were automatically extracted and manually corrected during the arterial phase of CECT. The diameter and length of each zone were measured for each modality. The mean diameters and lengths of the target vessels were compared between NCT and CECT. Results: The measurements obtained using both methods were reproducible and demonstrated good agreement. The mean differences in vessel length and diameter measurements for each segment between NCT and CECT were not statistically significant, indicating good consistency. Conclusion: NCT may be useful for preoperative EVAR evaluation in patients with renal dysfunction or allergies to contrast agents.

Accuracy and Precision of Energy Dispersive X-Ray Fluorescence (EDXRF) Analysis of Trace and Major Elements in Rock Standard Reference Materials Using Fine Powder

In this work the performance of a screening analytical method for Energy Dispersive X-Ray Fluorescence (EDXRF) analysis in terms of accuracy and precision was evaluated through analysis of rock standard reference materials. The method allowed the division of elements into four groups taking into account the excitation energies and measurement conditions of the sample. Two standard reference materials were used and 15 sample replicates were prepared and analyzed, then statistics were applied to assess the precision and accuracy of analytical results. The obtained results show that major compounds or elements (SiO2, P2O5, K2O, CaO, Fe2O3, Ti) can be determined in fine powder sample with a deviation lower than 15%, and a relative standard deviation in the range (1 - 10)%. The deviation was found to be lower than 5% for major compounds such as K2O, and CaO, which suggest that the EDXRF is accurate in evaluating major elemental concentrations in rock samples. It was also found that the method seems to be more accurate and precise for major elements than for trace element investigation. This screening analytical method can be used for routine analysis with acceptable results, even though the method should be optimized to increase its precision and accuracy.

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning

Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).

Social-ecological perspective on the suicidal behaviour factors of early adolescents in China:a network analysis

Background In early adolescence,youth are highly prone to suicidal behaviours.Identifying modifiable risk factors during this critical phase is a priority to inform effective suicide prevention strategies.Aims To explore the risk and protective factors of suicidal behaviours(ie,suicidal ideation,plans and attempts)in early adolescence in China using a social-ecological perspective.Methods Using data from the cross-sectional project‘Healthy and Risky Behaviours Among Middle School Students in Anhui Province,China',stratified random cluster sampling was used to select 5724 middle school students who had completed self-report questionnaires in November 2020.Network analysis was employed to examine the correlates of suicidal ideation,plans and attempts at four levels,namely individual(sex,academic performance,serious physical llness/disability,history of self-harm,depression,impulsivity,sleep problems,resilience),family(family economic status,relationship with mother,relationship with father,family violence,childhood abuse,parental mental illness),school(relationship with teachers,relationship with classmates,school-bullying victimisation and perpetration)and social(social support,satisfaction with society).Results In total,37.9%,19.0%and 5.5%of the students reported suicidal ideation,plans and attempts in the past 6 months,respectively.The estimated network revealed that suicidal ideation,plans and attempts were collectively associated with a history of self-harm,sleep problems,childhood abuse,school bullying and victimisation.Centrality analysis indicated that the most influential nodes in the network were history of self-harm and childhood abuse.Notably,the network also showed unique correlates of suicidal ideation(sex,weight=0.60;impulsivity,weight=0.24;family violence,weight=0.17;relationship with teachers,weight=-0.03;school-bullying perpetration,weight=0.22),suicidal plans(social support,weight=-0.15)and suicidal attempts(relationship with mother,weight=-0.10;parental mental llness,weight=0.61).Conclusions This study identified the correlates of suicidal ideation,plans and attempts,and provided practical implications for suicide prevention for young adolescents in China.Firstly,this study highlighted the importance of joint interventions across multiple departments.Secondly,the common risk factors of suicidal ideation,plans and attempts were elucidated.Thirdly,this study proposed target interventions to address the unique influencing factors of suicidal ideation,plans and attempts.

Quantifying the agreement and accuracy characteristics of four satellite-based LULC products for cropland classification in China

Various land use and land cover(LULC)products have been produced over the past decade with the development of remote sensing technology.Despite the differences in LULC classification schemes,there is a lack of research on assessing the accuracy of their application to croplands in a unified framework.Thus,this study evaluated the spatial and area accuracies of cropland classification for four commonly used global LULC products(i.e.,MCD12Q1V6,GlobCover2009,FROM-GLC and GlobeLand30)based on the harmonised FAO criterion,and quantified the relationships between four factors(i.e.,slope,elevation,field size and crop system)and cropland classification agreement.The validation results indicated that MCD12Q1 and GlobeLand30 performed well in cropland classification regarding spatial consistency,with overall accuracies of 94.90 and 93.52%,respectively.The FROMGLC showed the worst performance,with an overall accuracy of 83.17%.Overlaying the cropland generated by the four global LULC products,we found the proportions of complete agreement and disagreement were 15.51 and 44.72% for the cropland classification,respectively.High consistency was mainly observed in the Northeast China Plain,the Huang-Huai-Hai Plain and the northern part of the Middle-lower Yangtze Plain,China.In contrast,low consistency was detected primarily on the eastern edge of the northern and semiarid region,the Yunnan-Guizhou Plateau and southern China.Field size was the most important factor for mapping cropland.For area accuracy,compared with China Statistical Yearbook data at the provincial scale,the accuracies of different products in descending order were:GlobeLand30,FROM-GLC,MCD12Q1,and GlobCover2009.The cropland classification schemes mainly caused large area deviations among the four products,and they also resulted in the different ranks of spatial accuracy and area accuracy among the four products.Our results can provide valuable suggestions for selecting cropland products at the national or provincial scale and help cropland mapping and reconstruction,which is essential for food security and crop management,so they can also contribute to achieving the Sustainable Development Goals issued by the United Nations.

A Review on Sources,Extractions and Analysis Methods of a Sustainable Biomaterial:Tannins

Condensed and hydrolysable tannins are non-toxic natural polyphenols that are a commercial commodity industrialized for tanning hides to obtain leather and for a growing number of other industrial applications mainly to substitute petroleum-based products.They are a definite class of sustainable materials of the forestry industry.They have been in operation for hundreds of years to manufacture leather and now for a growing number of applications in a variety of other industries,such as wood adhesives,metal coating,pharmaceutical/medical applications and several others.This review presents the main sources,either already or potentially commercial of this forestry by-materials,their industrial and laboratory extraction systems,their systems of analysis with their advantages and drawbacks,be these methods so simple to even appear primitive but nonetheless of proven effectiveness,or very modern and instrumental.It constitutes a basic but essential summary of what is necessary to know of these sustainable materials.In doing so,the review highlights some of the main challenges that remain to be addressed to deliver the quality and economics of tannin supply necessary to fulfill the industrial production requirements for some materials-based uses.

Lagrangian coherent structure analysis on transport of Acetes chinensis along coast of Lianyungang,China

Spatial heterogeneity or“patchiness”of plankton distributions in the ocean has always been an attractive and challenging scientific issue to oceanographers.We focused on the accumulation and dynamic mechanism of the Acetes chinensis in the Lianyungang nearshore licensed fishing area.The Lagrangian frame approaches including the Lagrangian coherent structures theory,Lagrangian residual current,and Lagrangian particle-tracking model were applied to find the transport pathways and aggregation characteristics of Acetes chinensis.There exist some material transport pathways for Acetes chinensis passing through the licensed fishing area,and Acetes chinensis is easy to accumulate in the licensed fishing area.The main mechanism forming this distribution pattern is the local circulation induced by the nonlinear interaction of topography and tidal flow.Both the Lagrangian coherent structure analysis and the particle trajectory tracking indicate that Acetes chinensis in the licensed fishing area come from the nearshore estuary.This work contributed to the adjustment of licensed fishing area and the efficient utilization of fishery resources.

Iron and ferritin effects on intensive care unit mortality:A metaanalysis

BACKGROUND The effect of serum iron or ferritin parameters on mortality among critically ill patients is not well characterized.AIM To determine the association between serum iron or ferritin parameters and mortality among critically ill patients.METHODS Web of Science,Embase,PubMed,and Cochrane Library databases were searched for studies on serum iron or ferritin parameters and mortality among critically ill patients.Two reviewers independently assessed,selected,and abstracted data from studies reporting on serum iron or ferritin parameters and mortality among critically ill patients.Data on serum iron or ferritin levels,mortality,and demographics were extracted.RESULTS Nineteen studies comprising 125490 patients were eligible for inclusion.We observed a slight negative effect of serum ferritin on mortality in the United States population[relative risk(RR)1.002;95%CI:1.002-1.004].In patients with sepsis,serum iron had a significant negative effect on mortality(RR=1.567;95%CI:1.208-1.925).CONCLUSION This systematic review presents evidence of a negative correlation between serum iron levels and mortality among patients with sepsis.Furthermore,it reveals a minor yet adverse impact of serum ferritin on mortality among the United States population.

Influence of initial check, information exchange, final accuracy check, reaction information nursing on the psychology of elderly with lung cancer

BACKGROUND As one of the fatal diseases with high incidence,lung cancer has seriously endangered public health and safety.Elderly patients usually have poor self-care and are more likely to show a series of psychological problems.AIM To investigate the effectiveness of the initial check,information exchange,final accuracy check,reaction(IIFAR)information care model on the mental health status of elderly patients with lung cancer.METHODS This study is a single-centre study.We randomly recruited 60 elderly patients with lung cancer who attended our hospital from January 2021 to January 2022.These elderly patients with lung cancer were randomly divided into two groups,with the control group taking the conventional propaganda and education and the observation group taking the IIFAR information care model based on the conventional care protocol.The differences in psychological distress,anxiety and depression,life quality,fatigue,and the locus of control in psychology were compared between these two groups,and the causes of psychological distress were analyzed.RESULTS After the intervention,Distress Thermometer,Hospital Anxiety and Depression Scale(HADS)for anxiety and the HADS for depression,Revised Piper’s Fatigue Scale,and Chance Health Locus of Control scores were lower in the observation group compared to the pre-intervention period in the same group and were significantly lower in the observation group compared to those of the control group(P<0.05).After the intervention,Quality of Life Questionnaire Core 30(QLQ-C30),Internal Health Locus of Control,and Powerful Others Health Locus of Control scores were significantly higher in the observation and the control groups compared to the pre-intervention period in their same group,and QLQ-C30 scores were significantly higher in the observation group compared to those of the control group(P<0.05).CONCLUSION The IIFAR information care model can help elderly patients with lung cancer by reducing their anxiety and depression,psychological distress,and fatigue,improving their tendencies on the locus of control in psychology,and enhancing their life qualities.

Semi-analytical solution for drained expansion analysis of a hollow cylinder of critical state soils

The expansion of a thick-walled hollow cylinder in soil is of non-self-similar nature that the stress/deformation paths are not the same for different soil material points.As a result,this problem cannot be solved by the common self-similar-based similarity techniques.This paper proposes a novel,exact solution for rigorous drained expansion analysis of a hollow cylinder of critical state soils.Considering stress-dependent elastic moduli of soils,new analytical stress and displacement solutions for the nonself-similar problem are developed taking the small strain assumption in the elastic zone.In the plastic zone,the cavity expansion response is formulated into a set of first-order partial differential equations(PDEs)with the combination use of Eulerian and Lagrangian descriptions,and a novel solution algorithm is developed to efficiently solve this complex boundary value problem.The solution is presented in a general form and thus can be useful for a wide range of soils.With the new solution,the non-self-similar nature induced by the finite outer boundary is clearly demonstrated and highlighted,which is found to be greatly different to the behaviour of cavity expansion in infinite soil mass.The present solution may serve as a benchmark for verifying the performance of advanced numerical techniques with critical state soil models and be used to capture the finite boundary effect for pressuremeter tests in small-sized calibration chambers.

Identification of cell surface markers for acute myeloid leukemia prognosis based on multi-model analysis

Given the extremely high inter-patient heterogeneity of acute myeloid leukemia(AML),the identification of biomarkers for prognostic assessment and therapeutic guidance is critical.Cell surface markers(CSMs)have been shown to play an important role in AML leukemogenesis and progression.In the current study,we evaluated the prognostic potential of all human CSMs in 130 AML patients from The Cancer Genome Atlas(TCGA)based on differential gene expression analysis and univariable Cox proportional hazards regression analysis.By using multi-model analysis,including Adaptive LASSO regression,LASSO regression,and Elastic Net,we constructed a 9-CSMs prognostic model for risk stratification of the AML patients.The predictive value of the 9-CSMs risk score was further validated at the transcriptome and proteome levels.Multivariable Cox regression analysis showed that the risk score was an independent prognostic factor for the AML patients.The AML patients with high 9-CSMs risk scores had a shorter overall and event-free survival time than those with low scores.Notably,single-cell RNA-sequencing analysis indicated that patients with high 9-CSMs risk scores exhibited chemotherapy resistance.Furthermore,PI3K inhibitors were identified as potential treatments for these high-risk patients.In conclusion,we constructed a 9-CSMs prognostic model that served as an independent prognostic factor for the survival of AML patients and held the potential for guiding drug therapy.

Model reduction of fractional impedance spectra for time–frequency analysis of batteries, fuel cells, and supercapacitors

Joint time–frequency analysis is an emerging method for interpreting the underlying physics in fuel cells,batteries,and supercapacitors.To increase the reliability of time–frequency analysis,a theoretical correlation between frequency-domain stationary analysis and time-domain transient analysis is urgently required.The present work formularizes a thorough model reduction of fractional impedance spectra for electrochemical energy devices involving not only the model reduction from fractional-order models to integer-order models and from high-to low-order RC circuits but also insight into the evolution of the characteristic time constants during the whole reduction process.The following work has been carried out:(i)the model-reduction theory is addressed for typical Warburg elements and RC circuits based on the continued fraction expansion theory and the response error minimization technique,respectively;(ii)the order effect on the model reduction of typical Warburg elements is quantitatively evaluated by time–frequency analysis;(iii)the results of time–frequency analysis are confirmed to be useful to determine the reduction order in terms of the kinetic information needed to be captured;and(iv)the results of time–frequency analysis are validated for the model reduction of fractional impedance spectra for lithium-ion batteries,supercapacitors,and solid oxide fuel cells.In turn,the numerical validation has demonstrated the powerful function of the joint time–frequency analysis.The thorough model reduction of fractional impedance spectra addressed in the present work not only clarifies the relationship between time-domain transient analysis and frequency-domain stationary analysis but also enhances the reliability of the joint time–frequency analysis for electrochemical energy devices.

Application of Isogeometric Analysis Method in Three-Dimensional Gear Contact Analysis

Gears are pivotal in mechanical drives,and gear contact analysis is a typically difficult problem to solve.Emerging isogeometric analysis(IGA)methods have developed new ideas to solve this problem.In this paper,a threedimensional body parametric gear model of IGA is established,and a theoretical formula is derived to realize single-tooth contact analysis.Results were benchmarked against those obtained from commercial software utilizing the finite element analysis(FEA)method to validate the accuracy of our approach.Our findings indicate that the IGA-based contact algorithmsuccessfullymet theHertz contact test.When juxtaposed with the FEA approach,the IGAmethod demonstrated fewer node degrees of freedomand reduced computational units,all whilemaintaining comparable accuracy.Notably,the IGA method appeared to exhibit consistency in analysis accuracy irrespective of computational unit density,and also significantlymitigated non-physical oscillations in contact stress across the tooth width.This underscores the prowess of IGA in contact analysis.In conclusion,IGA emerges as a potent tool for addressing contact analysis challenges and holds significant promise for 3D gear modeling,simulation,and optimization of various mechanical components.

Stability Analysis and Performance Evaluation of Additive Mixed-Precision Runge-Kutta Methods

Additive Runge-Kutta methods designed for preserving highly accurate solutions in mixed-precision computation were previously proposed and analyzed.These specially designed methods use reduced precision for the implicit computations and full precision for the explicit computations.In this work,we analyze the stability properties of these methods and their sensitivity to the low-precision rounding errors,and demonstrate their performance in terms of accuracy and efficiency.We develop codes in FORTRAN and Julia to solve nonlinear systems of ODEs and PDEs using the mixed-precision additive Runge-Kutta(MP-ARK)methods.The convergence,accuracy,and runtime of these methods are explored.We show that for a given level of accuracy,suitably chosen MP-ARK methods may provide significant reductions in runtime.

Preliminary electromagnetic analysis of the COOL blanket for CFETR

The supercritical CO_(2)cOoled Lithium-Lead(COOL)blanket has been designed as one advanced blanket candidate for the Chinese Fusion Engineering Test Reactor(CFETR).This work focuses on the electromagnetic(EM)loads(Maxwell force and Lorentz force)acting on the COOL blanket,which are important mechanical loads in further structural analysis of the COOL blanket.A 3D electromagnetic analysis is performed using the ANSYS finite element method to obtain EM loads on the COOL blanket in this study.At first,the magnetic scalar potential(MSP)method is used to obtain the magnetic field and the Maxwell force on the COOL blanket.Then,the magnetic vector potential(MVP)method is performed during a plasma disruption event to get the eddy current distribution.At last,a multi-step method is adopted for the calculation of the Lorentz force and the torque.The maximum Lorentz forces of inboard and outboard blanket structural components are 5624 kN and 2360 kN respectively.

SFGA-CPA: A Novel Screening Correlation Power Analysis Framework Based on Genetic Algorithm

Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key degeneration and slow evolution within populations.These challenges significantly hinder key recovery efforts.This paper proposes a screening correlation power analysis framework combined with a genetic algorithm,named SFGA-CPA,to address these issues.SFGA-CPA introduces three operations designed to exploit CPA characteris-tics:propagative operation,constrained crossover,and constrained mutation.Firstly,the propagative operation accelerates population evolution by maximizing the number of correct bytes in each individual.Secondly,the constrained crossover and mutation operations effectively address key degeneration by preventing the compromise of correct bytes.Finally,an intelligent search method is proposed to identify optimal parameters,further improving attack efficiency.Experiments were conducted on both simulated environments and real power traces collected from the SAKURA-G platform.In the case of simulation,SFGA-CPA reduces the number of traces by 27.3%and 60%compared to CPA based on multiple screening methods(MS-CPA)and CPA based on simple GA method(SGA-CPA)when the success rate reaches 90%.Moreover,real experimental results on the SAKURA-G platform demonstrate that our approach outperforms other methods.

Geometric prior guided hybrid deep neural network for facial beauty analysis

Facial beauty analysis is an important topic in human society.It may be used as a guidance for face beautification applications such as cosmetic surgery.Deep neural networks(DNNs)have recently been adopted for facial beauty analysis and have achieved remarkable performance.However,most existing DNN-based models regard facial beauty analysis as a normal classification task.They ignore important prior knowledge in traditional machine learning models which illustrate the significant contribution of the geometric features in facial beauty analysis.To be specific,landmarks of the whole face and facial organs are introduced to extract geometric features to make the decision.Inspired by this,we introduce a novel dual-branch network for facial beauty analysis:one branch takes the Swin Transformer as the backbone to model the full face and global patterns,and another branch focuses on the masked facial organs with the residual network to model the local patterns of certain facial parts.Additionally,the designed multi-scale feature fusion module can further facilitate our network to learn complementary semantic information between the two branches.In model optimisation,we propose a hybrid loss function,where especially geometric regulation is introduced by regressing the facial landmarks and it can force the extracted features to convey facial geometric features.Experiments performed on the SCUT-FBP5500 dataset and the SCUT-FBP dataset demonstrate that our model outperforms the state-of-the-art convolutional neural networks models,which proves the effectiveness of the proposed geometric regularisation and dual-branch structure with the hybrid network.To the best of our knowledge,this is the first study to introduce a Vision Transformer into the facial beauty analysis task.