Hybrid Gene Selection Methods for High-Dimensional Lung Cancer Data Using Improved Arithmetic Optimization Algorithm

Lung cancer is among the most frequent cancers in the world,with over one million deaths per year.Classification is required for lung cancer diagnosis and therapy to be effective,accurate,and reliable.Gene expression microarrays have made it possible to find genetic biomarkers for cancer diagnosis and prediction in a high-throughput manner.Machine Learning(ML)has been widely used to diagnose and classify lung cancer where the performance of ML methods is evaluated to identify the appropriate technique.Identifying and selecting the gene expression patterns can help in lung cancer diagnoses and classification.Normally,microarrays include several genes and may cause confusion or false prediction.Therefore,the Arithmetic Optimization Algorithm(AOA)is used to identify the optimal gene subset to reduce the number of selected genes.Which can allow the classifiers to yield the best performance for lung cancer classification.In addition,we proposed a modified version of AOA which can work effectively on the high dimensional dataset.In the modified AOA,the features are ranked by their weights and are used to initialize the AOA population.The exploitation process of AOA is then enhanced by developing a local search algorithm based on two neighborhood strategies.Finally,the efficiency of the proposed methods was evaluated on gene expression datasets related to Lung cancer using stratified 4-fold cross-validation.The method’s efficacy in selecting the optimal gene subset is underscored by its ability to maintain feature proportions between 10%to 25%.Moreover,the approach significantly enhances lung cancer prediction accuracy.For instance,Lung_Harvard1 achieved an accuracy of 97.5%,Lung_Harvard2 and Lung_Michigan datasets both achieved 100%,Lung_Adenocarcinoma obtained an accuracy of 88.2%,and Lung_Ontario achieved an accuracy of 87.5%.In conclusion,the results indicate the potential promise of the proposed modified AOA approach in classifying microarray cancer data.

State-selective charge exchange cross sections in collisions of highly-charged sulfur ions with helium and molecular hydrogen

The state-selective cross section data are useful for understanding and modeling the x-ray emission in celestial observations.In the present work,using the cold target recoil ion momentum spectroscopy,for the first time we investigated the state-selective single electron capture processes for S^(q+)–He and H_(2)(q=11–15)collision systems at an impact energy of q×20 keV and obtained the relative state-selective cross sections.The results indicate that only a few principal quantum states of the projectile energy level are populated in a single electron capture process.In particular,the increase of the projectile charge state leads to the population of the states with higher principal quantum numbers.It is also shown that the experimental averaged n-shell populations are reproduced well by the over-barrier model.The database is openly available in Science Data Bank at 10.57760/sciencedb.j00113.00091.

An Algorithm for Short-Circuit Current Interval in Distribution Networks with Inverter Type Distributed Generation Based on Affine Arithmetic

During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in uncertainties in the calculation of the short-circuit current at the time of a fault.Additionally,the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources.Thus,it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network.In this study,an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented.The proposed algorithm includes two stages.In the first stage,normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources.Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence,the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources.The second stage is implemented after a malfunction occurs.In this stage,an affine optimization model is first established.This model is developed to characterizes the short-circuit current interval of a transmission line,and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations.Finally,the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted.The algorithm proposed in this article obtains an interval range containing accurate results through interval operation.Compared with traditional point value calculation methods,interval calculation methods can provide more reliable analysis and calculation results.The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Therefore,the proposed algorithm has good suitability and does not require iterative calculations,resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Furthermore,the proposed algorithm can provide more reliable analysis and calculation results,improving the safety and stability of power systems.

Absolute partial and total ionization cross sections of carbon monoxide with electron collision from 350 eV to 8000 eV

The absolute partial and total cross sections for electron impact ionization of carbon monoxide are reported for electron energies from 350 eV to 8000 eV.The product ions(CO^(+),C^(+),O^(+),CO^(2+),C^(2+),and O^(2+))are measured by employing an ion imaging mass spectrometer and two ion-pair dissociation channels(C^(+)+O^(+)and C^(2+)+O^(+))are identified.The absolute cross sections for producing individual ions and their total,as well as for the ion-pair dissociation channels are obtained by normalizing the data of CO^(+)to that of Ar^(+)from CO-Ar mixture target with a fixed 1:1 ratio.The overall errors are evaluated by considering various kinds of uncertainties.A comprehensive comparison is made with the available data,which shows a good agreement with each other over the energy ranges that are overlapped.This work presents new cross-section data with electron energies above 1000 eV.

Measurement of the neutron-induced total cross sections of ^(nat)Pb from 0.3 eV to 20 MeV on the Back-n at CSNS

The neutron-induced total cross sections of natural lead have been measured in a wide energy range(0.3 eV-20 MeV)on the back-streaming white neutron beamline(Back-n)at the China Spallation Neutron Source.Neutron energy was determined by the neutron total cross-section spectrometer using the time-of-flight technique.A fast multi-cell fission chamber was used as the neutron detector,and a 10-mm-thick high-purity natural lead sample was employed for the neutron transmission measurements.The on-beam background was determined using Co,In,Ag,and Cd filters.The excitation function of ^(nat)Pb(n,tot)reaction below 20 MeV was calculated using the TALYS-1.96 nuclear-reaction modeling program.The present results were compared with previous results,the evaluated data available in the five major evaluated nuclear data libraries(i.e.,ENDF/B-VIII.0,JEFF-3.3,JENDL-5,CENDL-3.2,and BROND-3.1),and the theoretical calculation curve.Good agreement was found between the new results and those of previous experiments and with the theoretical curves in the corresponding region.This measurement obtained the neutron total cross section of natural lead with good accuracy over a wide energy range and added experimental data in the resonance energy range.This provides more reliable experimental data for nuclear engineering design and nuclear data evaluation of lead.

Enhanced Arithmetic Optimization Algorithm Guided by a Local Search for the Feature Selection Problem

High-dimensional datasets present significant challenges for classification tasks.Dimensionality reduction,a crucial aspect of data preprocessing,has gained substantial attention due to its ability to improve classification per-formance.However,identifying the optimal features within high-dimensional datasets remains a computationally demanding task,necessitating the use of efficient algorithms.This paper introduces the Arithmetic Optimization Algorithm(AOA),a novel approach for finding the optimal feature subset.AOA is specifically modified to address feature selection problems based on a transfer function.Additionally,two enhancements are incorporated into the AOA algorithm to overcome limitations such as limited precision,slow convergence,and susceptibility to local optima.The first enhancement proposes a new method for selecting solutions to be improved during the search process.This method effectively improves the original algorithm’s accuracy and convergence speed.The second enhancement introduces a local search with neighborhood strategies(AOA_NBH)during the AOA exploitation phase.AOA_NBH explores the vast search space,aiding the algorithm in escaping local optima.Our results demonstrate that incorporating neighborhood methods enhances the output and achieves significant improvement over state-of-the-art methods.

Improved Arithmetic Optimization Algorithm with Multi-Strategy Fusion Mechanism and Its Application in Engineering Design

This article addresses the issues of falling into local optima and insufficient exploration capability in the Arithmetic Optimization Algorithm (AOA), proposing an improved Arithmetic Optimization Algorithm with a multi-strategy mechanism (BSFAOA). This algorithm introduces three strategies within the standard AOA framework: an adaptive balance factor SMOA based on sine functions, a search strategy combining Spiral Search and Brownian Motion, and a hybrid perturbation strategy based on Whale Fall Mechanism and Polynomial Differential Learning. The BSFAOA algorithm is analyzed in depth on the well-known 23 benchmark functions, CEC2019 test functions, and four real optimization problems. The experimental results demonstrate that the BSFAOA algorithm can better balance the exploration and exploitation capabilities, significantly enhancing the stability, convergence mode, and search efficiency of the AOA algorithm.

Neuroanatomical Basis of Postoperative Pain and Assessment of Its Management in a Series of Patients Undergoing Caesarean Sections

Introduction: In recent decades, the cost of postoperative pain has been the subject of many studies based on protocols developed by scientific societies for its assessment and optimization. At the Regional Hospital of Saint-Louis (Senegal), several protocols have been developed for pain management, but no study has focused on the assessment of postoperative pain management specifically. We therefore initiated this work, the objectives of which were to remind the neuroanatomical and neurophysiological bases of postoperative pain, and to analyze the assessment and management of this pain in patients who have undergone a caesarean section. Materials and methods: This was a prospective and descriptive study, which took place in the gynecology-obstetrics department, over a period from January 2019 to July 2020. All patients who gave birth by cesarean section were included. The data was collected from a survey sheet written for this purpose. For each of the patients, the information was taken every day throughout the duration of postoperative hospitalization. Results: It appears from our work that after a cesarean section, the pain felt evolves on the first postoperative days with a peak during the second day. As in the data reported in the literature, there does not seem to be a difference in terms of pain intensity and analgesia dosage between scheduled and emergency caesarean sections. However, young age and female gender—for other types of surgeries—are risk factors associated with high postoperative pain scores. This trend is probably related to the low pain experience of tested patients. Our initial hypothesis was that acute post-operative pain after caesarean sections could be linked to defects in the perception and processing of pain by caregivers. Indeed, we have shown that awareness-raising, information, and training actions have made it possible to significantly improve the management of pain after a cesarean section. Conclusion: After a cesarean section the pain is intense, especially when the effects of the morphine wear off. However, in our context where morphine and its derivatives are only slightly used, the post-operative pain is maximal rapidly. This pain therefore needs to be researched and treated appropriately. After a campaign to raise awareness among healthcare personnel, it is possible to significantly improve the systematic administration of analgesics.

Probability Distribution of Arithmetic Average of China Aviation Network Edge Vertices Nearest Neighbor Average Degree Value and Its Evolutionary Trace Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network,the probability distribution and evolution trace of arithmetic average of edge vertices nearest neighbor average degree values of China aviation network were studied based on the statistics data of China civil aviation network in 1988,1994,2001,2008 and 2015.According to the theory and method of complex network,the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network.Based on the statistical data,the arithmetic averages of edge vertices nearest neighbor average degree values of China aviation network in 1988,1994,2001,2008 and 2015 were calculated.Using the probability statistical analysis method,it was found that the arithmetic average of edge vertices nearest neighbor average degree values had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.

On the Equality of Weighted BajratarevićMeans to Quasi-Arithmetic Means

In this paper, we considered the equality problem of weighted Bajraktarević means with weighted quasi-arithmetic means. Using the method of substituting for functions, we first transform the equality problem into solving an equivalent functional equation. We obtain the necessary and sufficient conditions for the equality equation.

Progress of photonuclear cross sections for medical radioisotope production at the SLEGS energy domain

Photonuclear reactions using a laser Compton scattering(LCS)gamma source provide a new method for producing radioisotopes for medical applications.Compared with the conventional method,this method has the advantages of a high specific activity and less heat.Initiated by the Shanghai Laser Electron Gamma Source(SLEGS),we conducted a survey of potential photonuclear reactions,(γ,n),(γ,p),and(γ,γ')whose cross sections can be measured at SLEGS by summarising the experimental progress.In general,the data are rare and occasionally inconsistent.Therefore,theoretical calculations are often used to evaluate the production of medical radioisotopes.Subsequently,we verified the model uncertainties of the widely used reaction code TALYS-1.96,using the experimental data of the^(100)Mo(γ,n)^(99)Mo,^(65)Cu(γ,n)^(64)Cu,and^(68)Zn(γ,p)^(67)Cu reactions.

Measurement of^(134)Xe(n,2n)^(133m),gXe reaction cross sections in 14‑MeV region with detailed uncertainty quantification

A lead-shielded HPGe detector and offlineγ-ray spectra of the residual product were used to measure the cross section(CS)and ratios of isomeric CS(σm/σg)in^(134)Xe(n,2n)^(133m),gXe reactions at different energies(13.5 MeV,13.8 MeV,14.1 MeV,14.4 MeV,14.8 MeV)relative to the^(93)Nb(n,2n)^(92)mNb reaction CS.The target was high-purity natural Xe gas under high pressure.The T(d,n)4He reaction produces neutrons.TALYS code(version 1.95)for nuclear reactions was used for calculations,with default parameters and nuclear level density models.The uncertainties in the measured CS data were thoroughly analyzed using the covariance analysis method.The results were compared with theoretical values,evaluation data,and previous experimental findings.CS data of the 134Xe(n,2n)133mXe and 134Xe(n,2n)133gXe reactions and the corresponding isomeric CS ratios at 13.5 MeV,13.8 MeV,and 14.1 MeV neutron energies are reported for the first time.This research advances our knowledge of pre-equilibrium emission in the(n,2n)reaction channel by resolving inconsistencies in the Xe data.

Fine-grained gravity flow sedimentation and its influence on development of shale oil sweet sections in lacustrine basins in China

The geological conditions and processes of fine-grained gravity flow sedimentation in continental lacustrine basins in China are analyzed to construct the model of fine-grained gravity flow sedimentation in lacustrine basin,reveal the development laws of fine-grained deposits and source-reservoir,and identify the sweet sections of shale oil.The results show that fine-grained gravity flow is one of the important sedimentary processes in deep lake environment,and it can transport fine-grained clasts and organic matter in shallow water to deep lake,forming sweet sections and high-quality source rocks of shale oil.Fine-grained gravity flow deposits in deep waters of lacustrine basins in China are mainly fine-grained high-density flow,fine-grained turbidity flow(including surge-like turbidity flow and fine-grained hyperpycnal flow),fine-grained viscous flow(including fine-grained debris flow and mud flow),and fine-grained transitional flow deposits.The distribution of fine-grained gravity flow deposits in the warm and humid unbalanced lacustrine basins are controlled by lake-level fluctuation,flooding events,and lakebed paleogeomorphology.During the lake-level rise,fine-grained hyperpycnal flow caused by flooding formed fine-grained channel–levee–lobe system in the flat area of the deep lake.During the lake-level fall,the sublacustrine fan system represented by unconfined channel was developed in the flexural slope breaks and sedimentary slopes of depressed lacustrine basins,and in the steep slopes of faulted lacustrine basins;the sublacustrine fan system with confined or unconfined channel was developed on the gentle slopes and in axial direction of faulted lacustrine basins,with fine-grained gravity flow deposits possibly existing in the lower fan.Within the fourth-order sequences,transgression might lead to organic-rich shale and fine-grained hyperpycnal flow deposits,while regression might cause fine-grained high-density flow,surge-like turbidity flow,fine-grained debris flow,mud flow,and fine-grained transitional flow deposits.Since the Permian,in the shale strata of lacustrine basins in China,multiple transgression-regression cycles of fourth-order sequences have formed multiple source-reservoir assemblages.Diverse fine-grained gravity flow sedimentation processes have created sweet sections of thin siltstone consisting of fine-grained high-density flow,fine-grained hyperpycnal flow and surge-like turbidity flow deposits,sweet sections with interbeds of mudstone and siltstone formed by fine-grained transitional flows,and sweet sections of shale containing silty and muddy clasts and with horizontal bedding formed by fine-grained debris flow and mud flow.The model of fine-grained gravity flow sedimentation in lacustrine basin is significant for the scientific evaluation of sweet shale oil reservoir and organic-rich source rock.

Measurement of Br(n,γ)cross sections up to stellar s-process temperatures at the CSNS Back‑n

The neutron capture cross sections(n,γ)of bromine were obtained using the time-of-flight technique at the Back-n facility of the China Spallation Neutron Source.Promptγ-rays originating from neutron-induced capture events were detected using four C_(6)D_(6) detectors.The pulse-height weighting technique and double-bunch unfolding method based on Bayesian theory were used in the data analysis.Background deductions,normalization,and corrections were carefully considered to obtain reliable measurement results.The multilevel R-matrix Bayesian code SAMMY was used to extract the resonance parameters in the resolved resonance region(RRR).The average cross sections in the unresolved resonance region(URR)were obtained from 10 to 400 keV.The experimental results were compared with data from several evaluated libraries and previous experi-ments in the RRR and URR.The TALYS code was used to describe the average cross sections in the URR.The astrophysical Maxwell average cross sections(MACSs)of ^(79,81)Br from kT=5 to 100 keV were calculated over a sufficiently wide range of neutron energies.At a thermal energy of kT=30 keV,the MACS value for ^(79)Br 682±68 mb was in good agreement with the KADoNiS v1.0 recommended value.By contrast,the value of 293±29 mb for ^(81)Br was substantially higher than that of the evaluated database and the KADoNiS v1.0 recommended value.

Solving Arithmetic Word Problems of Entailing Deep Implicit Relations by Qualia Syntax-Semantic Model

Solving arithmetic word problems that entail deep implicit relations is still a challenging problem.However,significant progress has been made in solving Arithmetic Word Problems(AWP)over the past six decades.This paper proposes to discover deep implicit relations by qualia inference to solve Arithmetic Word Problems entailing Deep Implicit Relations(DIR-AWP),such as entailing commonsense or subject-domain knowledge involved in the problem-solving process.This paper proposes to take three steps to solve DIR-AWPs,in which the first three steps are used to conduct the qualia inference process.The first step uses the prepared set of qualia-quantity models to identify qualia scenes from the explicit relations extracted by the Syntax-Semantic(S2)method from the given problem.The second step adds missing entities and deep implicit relations in order using the identified qualia scenes and the qualia-quantity models,respectively.The third step distills the relations for solving the given problem by pruning the spare branches of the qualia dependency graph of all the acquired relations.The research contributes to the field by presenting a comprehensive approach combining explicit and implicit knowledge to enhance reasoning abilities.The experimental results on Math23K demonstrate hat the proposed algorithm is superior to the baseline algorithms in solving AWPs requiring deep implicit relations.

Differential Evolution with Arithmetic Optimization Algorithm Enabled Multi-Hop Routing Protocol

Wireless Sensor Networks(WSN)has evolved into a key technology for ubiquitous living and the domain of interest has remained active in research owing to its extensive range of applications.In spite of this,it is challenging to design energy-efficient WSN.The routing approaches are leveraged to reduce the utilization of energy and prolonging the lifespan of network.In order to solve the restricted energy problem,it is essential to reduce the energy utilization of data,transmitted from the routing protocol and improve network development.In this background,the current study proposes a novel Differential Evolution with Arithmetic Optimization Algorithm Enabled Multi-hop Routing Protocol(DEAOA-MHRP)for WSN.The aim of the proposed DEAOA-MHRP model is select the optimal routes to reach the destination in WSN.To accomplish this,DEAOA-MHRP model initially integrates the concepts of Different Evolution(DE)and Arithmetic Optimization Algorithms(AOA)to improve convergence rate and solution quality.Besides,the inclusion of DE in traditional AOA helps in overcoming local optima problems.In addition,the proposed DEAOA-MRP technique derives a fitness function comprising two input variables such as residual energy and distance.In order to ensure the energy efficient performance of DEAOA-MHRP model,a detailed comparative study was conducted and the results established its superior performance over recent approaches.

Measurements of absolute electron capture cross sections in He^(2+)–He and Ne^(8+)–O_(2'), N_(2'), CH_4 collisions

The total absolute cross sections of single-and double-electron capture (SEC and DEC) in the collisions of He^(2+)with He and Ne^(8+)with O_(2),N_(2),and CH_(4) were studied in the energy ranges 3.5–50 keV/u and 2.8–40 keV/u,respectively.Through a deep analysis of the experimental systematic uncertainties in the measurement procedure and data evaluation,the error in the experimental results of the SEC cross sections is less than 9%.Within the uncertainties,the present results of the He^(2+)–He collision show good consistency with previous measurements,validating the experimental system and paving the way for precise measurements of EC cross sections for a variety of ions and neutral gases.The present measurements allow for a test of EC theory and provide crucial EC cross section data for the establishment of plasma models in fusion research and astrophysical X-ray studies.

Clinical nursing value of predictive nursing in reducing complications of pregnant women undergoing short-term massive blood transfusion during cesarean section

BACKGROUND Cesarean hemorrhage is one of the serious complications,and short-term massive blood transfusion can easily cause postoperative infection and physical stress response.However,predictive nursing intervention has important clinical significance for it.AIM To explore the effect of predictive nursing intervention on the stress response and complications of women undergoing short-term mass blood transfusion during cesarean section(CS).METHODS A clinical medical record of 100 pregnant women undergoing rapid mass blood transfusion during sections from June 2019 to June 2021.According to the different nursing methods,patients divided into control group(n=50)and observation group(n=50).Among them,the control group implemented routine nursing,and the observation group implemented predictive nursing intervention based on the control group.Moreover,compared the differences in stress res-ponse,complications,and pain scores before and after the nursing of pregnant women undergoing rapid mass blood transfusion during CS.RESULTS The anxiety and depression scores of pregnant women in the two groups were significantly improved after nursing,and the psychological stress response of the observation group was significantly lower than that of the control group(P<0.05).The heart rate and mean arterial pressure(MAP)of the observation group during delivery were lower than those of the control group,and the MAP at the end of delivery was lower than that of the control group(P<0.05).Moreover,different pain scores improved significantly in both groups,with the observation group considerably less than the control group(P<0.05).After nursing,complications such as skin rash,urinary retention,chills,diarrhea,and anaphylactic shock in the observation group were 18%,which significantly higher than in the control group(4%)(P<0.05).CONCLUSION Predictive nursing intervention can effectively relieve the pain,reduce the incidence of complications,improve mood and stress response,and serve as a reference value for the nursing of women undergoing rapid mass transfusion during CS.

Prevalence, Indications and Morbidity of Caesarean Sections in a Referral Hospital of the Health Voucher Program: The Case of Garoua Regional Hospital in the Northern Region of Cameroon

Caesarean section (CS) is a surgical procedure performed to remove a fetus from the mother’s uterus through an incision on the abdominal wall, then on the uterine wall. The indications of CS vary not only between countries, but also from one hospital to another and from one team to another within the same hospital. Despite advances in asepsis and anesthesia/resuscitation technics, there are still complications of varying severity inherent to the gravid-puerperal state on one hand and the technics used on the other, irrespective of the operative indication. Thus, the present study was carried out with the objectives of determining the prevalence, identifying the indications, and evaluating the morbidity linked to caesarean sections in our environment. Cameroon has also set up a health voucher program in its northern region, aimed at reducing maternal and fetus morbidity and mortality. The program aims to improve financial access in antenatal care and deliveries, including caesarean sections, in this low-income region of the country. We conducted a descriptive cross-sectional study with retrospective data collection, from February 1, 2022, to May 31, 2022. We included all women who gave birth by caesarean section. In our study series, out of 905 parturient admissions into the Department of Obstetrics and Gynecology, 226 were caesarian cases. The overall frequency of CS during our study period was 25%. Fetal indications were dominated by cephalopelvic disproportion and non-reassuring fetal heart in 17.3% and 13.7% of cases respectively. Intraoperative complications were dominated by hemorrhage (15.5%). In our study, we noted an 11.1% of prevalence perinatal mortality. Cameroon is a low-income country with limited financial resources, especially in the Northern region. The health voucher program has improved financial access to caesarean sections for parturient in northern Cameroon, and consequently to emergency obstetric and neonatal care.

Proper interpretation of sectional analysis results

Displacement control algorithms commonly used to evaluate axial force-bending moment(PM)diagrams may lead to incorrect interpretations of the strength envelopes for asymmetric sections.This paper aims to offer valuable insights by comparing existing displacement control algorithms with a newly proposed force control algorithm.The main focus is on the PM diagrams of three example sections that exhibit varying degrees of asymmetry.The comparative study indicates that conventional displacement control algorithms inevitably introduce non-zero out-of-plane bending moments.The reported PM diagram in such cases erroneously neglects the out-of-plane moment and fails to represent the strength envelope accurately.This oversight results in significant and unconservative errors when verifying the strength of asymmetric sections.