基于Count Sketch的预处理贪婪Kaczmarz方法

在贪婪Kaczmarz方法中,通过对系数矩阵进行正交三角分解引入右预处理子能够提高贪婪Kaczmarz方法的收敛速率。但在系数矩阵的行数远大于列数的情况下,正交三角分解的成本过高。为降低预处理的成本,通过引入Count Sketch变换,提出了基于Count Sketch的预处理贪婪Kaczmarz方法,并对新方法进行了收敛性分析。理论分析说明了新方法在系数矩阵条件数较大时比已有方法具有更好的收敛速率。数值实验验证了新方法的有效性。

基于LIWC文本情感分析的高校大学生二语写作研究

研究采用LIWC文本情感分析词典,对不同性别及不同外语写作水平的高校非英语专业大二学生的英语同题作文进行了情感分析。结果显示,在认知过程维度上,男性学习者认知参与度高于女性学习者,意愿、要求表达强烈,且逻辑性更强;不同性别的学生在第一人称代词使用上并未表现出显著差异;第一人称代词的使用与作文水平成正相关;不同性别及不同水平组的学生在积极和消极情绪表达上没有显著差异。

Lightweight Res-Connection Multi-Branch Network for Highly Accurate Crowd Counting and Localization

Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep learning.However,there have been stillmany challenges including crowd multi-scale variations and high network complexity,etc.To tackle these issues,a lightweight Resconnection multi-branch network(LRMBNet)for highly accurate crowd counting and localization is proposed.Specifically,using improved ShuffleNet V2 as the backbone,a lightweight shallow extractor has been designed by employing the channel compression mechanism to reduce enormously the number of network parameters.A light multi-branch structure with different expansion rate convolutions is demonstrated to extract multi-scale features and enlarged receptive fields,where the information transmission and fusion of diverse scale features is enhanced via residual concatenation.In addition,a compound loss function is introduced for training themethod to improve global context information correlation.The proposed method is evaluated on the SHHA,SHHB,UCF-QNRF and UCF_CC_50 public datasets.The accuracy is better than those of many advanced approaches,while the number of parameters is smaller.The experimental results show that the proposed method achieves a good tradeoff between the complexity and accuracy of crowd counting,indicating a lightweight and high-precision method for crowd counting.

Sensitivity of diagnosis of spontaneous bacterial peritonitis is higher with the automated cell count method

BACKGROUND Spontaneous bacterial peritonitis(SBP)is one of the most important complications of patients with liver cirrhosis entailing high morbidity and mortality.Making an accurate early diagnosis of this infection is key in the outcome of these patients.The current definition of SBP is based on studies performed more than 40 years ago using a manual technique to count the number of polymorphs in ascitic fluid(AF).There is a lack of data comparing the traditional cell count method with a current automated cell counter.Moreover,current international guidelines do not mention the type of cell count method to be employed and around half of the centers still rely on the traditional manual method.AIM To compare the accuracy of polymorph count on AF to diagnose SBP between the traditional manual cell count method and a modern automated cell counter against SBP cases fulfilling gold standard criteria:Positive AF culture and signs/symptoms of peritonitis.METHODS Retrospective analysis including two cohorts:Cross-sectional(cohort 1)and case-control(cohort 2),of patients with decompensated cirrhosis and ascites.Both cell count methods were conducted simultaneously.Positive SBP cases had a pathogenic bacteria isolated on AF and signs/symptoms of peritonitis.RESULTS A total of 137 cases with 5 positive-SBP,and 85 cases with 33 positive-SBP were included in cohort 1 and 2,respectively.Positive-SBP cases had worse liver function in both cohorts.The automated method showed higher sensitivity than the manual cell count:80%vs 52%,P=0.02,in cohort 2.Both methods showed very good specificity(>95%).The best cutoff using the automated cell counter was polymorph≥0.2 cells×10^(9)/L(equivalent to 200 cells/mm^(3))in AF as it has the higher sensitivity keeping a good specificity.CONCLUSION The automated cell count method should be preferred over the manual method to diagnose SBP because of its higher sensitivity.SBP definition,using the automated method,as polymorph cell count≥0.2 cells×10^(9)/L in AF would need to be considered in patients admitted with decompensated cirrhosis.

Deep Learning Based Efficient Crowd Counting System

Estimation of crowd count is becoming crucial nowadays,as it can help in security surveillance,crowd monitoring,and management for different events.It is challenging to determine the approximate crowd size from an image of the crowd’s density.Therefore in this research study,we proposed a multi-headed convolutional neural network architecture-based model for crowd counting,where we divided our proposed model into two main components:(i)the convolutional neural network,which extracts the feature across the whole image that is given to it as an input,and(ii)the multi-headed layers,which make it easier to evaluate density maps to estimate the number of people in the input image and determine their number in the crowd.We employed the available public benchmark crowd-counting datasets UCF CC 50 and ShanghaiTech parts A and B for model training and testing to validate the model’s performance.To analyze the results,we used two metrics Mean Absolute Error(MAE)and Mean Square Error(MSE),and compared the results of the proposed systems with the state-of-art models of crowd counting.The results show the superiority of the proposed system.

Rapid Detection of Somatic Cell Count Based on Hybrid Variable Selection Method

Somatic cell count detection is the daily work of dairy farms to monitor the health of cows.The feasibility of applying near-infrared spectroscopy to somatic cell count detection was researched in this paper.Milk samples with different somatic cell counts were collected and preprocessing methods were studied.Variable selection algorithm based on hybrid strategy and modelling method based on ensemble learning were explored for somatic cell count detection.Detection model was used to diagnose subclinical mastitis and the results showed that near-infrared spectroscopy could be a tool to realize rapid detection of somatic cell count in milk.

A multi-source information fusion layer counting method for penetration fuze based on TCN-LSTM

When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ferromagnetic materials,thereby posing challenges in accurately determining the number of layers.To address this issue,this research proposes a layer counting method for penetration fuze that incorporates multi-source information fusion,utilizing both the temporal convolutional network(TCN)and the long short-term memory(LSTM)recurrent network.By leveraging the strengths of these two network structures,the method extracts temporal and high-dimensional features from the multi-source physical field during the penetration process,establishing a relationship between the multi-source physical field and the distance between the fuze and the target plate.A simulation model is developed to simulate the overload and magnetic field of a projectile penetrating multiple layers of target plates,capturing the multi-source physical field signals and their patterns during the penetration process.The analysis reveals that the proposed multi-source fusion layer counting method reduces errors by 60% and 50% compared to single overload layer counting and single magnetic anomaly signal layer counting,respectively.The model's predictive performance is evaluated under various operating conditions,including different ratios of added noise to random sample positions,penetration speeds,and spacing between target plates.The maximum errors in fuze penetration time predicted by the three modes are 0.08 ms,0.12 ms,and 0.16 ms,respectively,confirming the robustness of the proposed model.Moreover,the model's predictions indicate that the fitting degree for large interlayer spacings is superior to that for small interlayer spacings due to the influence of stress waves.

Platelet counts to spleen diameter ratio:A promising noninvasive tool for predicting esophageal varices in cirrhosis patients

BACKGROUND Liver cirrhosis is the end stage of progressive liver fibrosis as a consequence of chronic liver inflammation,wherein the standard hepatic architecture is replaced by regenerative hepatic nodules,which eventually lead to liver failure.Cirrhosis without any symptoms is referred to as compensated cirrhosis.Complications such as ascites,variceal bleeding,and hepatic encephalopathy indicate the onset of decompensated cirrhosis.Gastroesophageal varices are the hallmark of clini-cally significant portal hypertension.AIM To determine the accuracy of the platelet count-to-spleen diameter(PC/SD)ratio to evaluate esophageal varices(EV)in patients with cirrhosis.METHODS This retrospective observational study was conducted at Tikur Anbessa Specia-lized Hospital and Adera Medical Center from January 1,2019,to December 30,2023.Data were collected via chart review and direct patient interviews using structured questionnaires.The data were exported to the SPSS software version 26 for analysis and clearance.A receiver operating characteristic curve was plotted for splenic diameter,platelet count,and PC/SD ratio to obtain sensitivity,speci-ficity,positive predictive value,negative predictive value,positive likelihood ratio,and negative likelihood ratio.RESULTS Of the 140 participants,67%were men.Hepatitis B(38%)was the most common cause of cirrhosis,followed by cryptogenic cirrhosis(28%)and hepatitis C(16%).Approximately 83.6%of the participants had endoscopic evidence of EV,whereas 51.1%had gastric varices.Decompensated cirrhosis and PC were associated with the presence of EV with adjusted odds ratios of 12.63(95%CI:3.16-67.58,P=0.001)and 0.14(95%CI:0.037-0.52,P=0.004),respectively.A PC/SD ratio<1119 had a sensitivity of 86.32%and specificity of 70%with area under the curve of 0.835(95%CI:0.736-0.934,P<0.001).CONCLUSION A PC/SD ratio<1119 predicts EV in patients with cirrhosis.It is a valuable,noninvasive tool for EV risk assess-ment in resource-limited settings.

Diagnostic significance of complete blood cell count and hemogramderived markers for neonatal sepsis at Southwest Public Hospitals,Ethiopia

BACKGROUND Neonatal sepsis is defined as an infection-related condition characterized by signs and symptoms of bacteremia within the first month of life.It is the leading cause of mortality and morbidity among newborns.While several studies have been conducted in other parts of world to assess the usefulness of complete blood count parameters and hemogram-derived markers as early screening tools for neonatal sepsis,the associations between sepsis and its complications with these blood parameters are still being investigated in our setting and are not yet part of routine practice.AIM To evaluate the diagnostic significance of complete blood cell count hemogramderived novel markers for neonatal sepsis among neonates attending public hospitals in the southwest region of Oromia,Ethiopia,through a case control study.METHODS A case control study was conducted from October 2021 to October 2023 Sociodemographic,clinical history,and laboratory test results data were collected using structured questionnaires.The collected data were entered into Epi-data 3.1 version and exported to SPSS-25 for analysis.Chi-square,independent sample ttest,and receiver operator characteristics curve of curve were used for analysis.A P-value of less than 0.05 was considered statistically significant.RESULTS In this study,significant increases were observed in the following values in the case group compared to the control group:In white blood cell(WBC)count,neutrophils,monocyte,mean platelet volume(MPV),neutrophils to lymphocyte ratio,monocyte to lymphocyte ratio(MLR),red blood cell width to platelet count ratio(RPR),red blood width coefficient variation,MPV to RPR,and platelet to lymphocyte ratio.Regarding MLR,a cut-off value of≥0.26 was found,with a sensitivity of 68%,a specificity of 95%,a positive predictive value(PPV)of 93.2%,and a negative predictive value(NPV)of 74.8%.The area under the curve(AUC)was 0.828(P<0.001).For WBC,a cutoff value of≥11.42 was identified,with a sensitivity of 55%,a specificity of 89%,a PPV of 83.3%,and a NPV of 66.4%.The AUC was 0.81(P<0.001).Neutrophils had a sensitivity of 67%,a specificity of 81%,a PPV of 77.9%,and a NPV of 71.1%.The AUC was 0.801,with a cut-off value of≥6.76(P=0.001).These results indicate that they were excellent predictors of neonatal sepsis diagnosis.CONCLUSION The findings of our study suggest that certain hematological parameters and hemogram-derived markers may have a potential role in the diagnosis of neonatal sepsis.

Blood cell counts and nonalcoholic fatty liver disease: Evidence from Mendelian randomization analysis

BACKGROUND Previous research has highlighted correlations between blood cell counts and chronic liver disease.Nonetheless,the causal relationships remain unknown.AIM To evaluate the causal effect of blood cell traits on liver enzymes and nonalcoholic fatty liver disease(NAFLD)risk.METHODS Independent genetic variants strongly associated with blood cell traits were extracted from a genome-wide association study(GWAS)conducted by the Blood Cell Consortium.Summary-level data for liver enzymes were obtained from the United Kingdom Biobank.NAFLD data were obtained from a GWAS meta-analysis(8434 cases and 770180 controls,discovery dataset)and the Fingen GWAS(2275 cases and 372727 controls,replication dataset).This analysis was conducted using the inverse-variance weighted method,followed by various sensitivity analyses.RESULTS One SD increase in the genetically predicted haemoglobin concentration(HGB)was associated with aβof 0.0078(95%CI:0.0059-0.0096),0.0108(95%CI:0.0080-0.0136),0.0361(95%CI:0.0156-0.0567),and 0.0083(95%CI:00046-0.0121)for alkaline phosphatase(ALP),alanine aminotransferase(ALT),aspartate aminotransferase,and gammaglutamyl transferase,respectively.Genetically predicted haematocrit was associated with ALP(β=0.0078,95%CI:0.0052-0.0104)and ALT(β=0.0057,95%CI:0.0039-0.0075).Genetically determined HGB and the reticulocyte fraction of red blood cells increased the risk of NAFLD[odds ratio(OR)=1.199,95%CI:1.087-1.322]and(OR=1.157,95%CI:1.071-1.250).The results of the sensitivity analyses remained significant.CONCLUSION Novel causal blood cell traits related to liver enzymes and NAFLD development were revealed through Mendelian randomization analysis,which may facilitate the diagnosis and prevention of NAFLD.

A Study on the Correlation Between LIWC Word Categories and Chinese Composition Writing Performance of Fourth,Fifth,and Sixth Grade Students

This study focuses on the analysis of the Chinese composition writing performance of fourth,fifth,and sixth grade students in 16 selected schools in Longhua District,Shenzhen during the spring semester of 2023.Using LIWC(Linguistic Inquiry and Word Count)as a text analysis tool,the study explores the impact of LIWC categories on writing performance which is scaled by score.The results show that the simple LIWC word categories have a significant positive influence on the composition scores of lower-grade students;while complex LIWC word categories have a significant negative influence on the composition scores of lower-grade students but a significant positive influence on the composition scores of higher-grade students.Process word categories have a positive influence on the composition scores of all three grades,but the impact of complex process word categories increases as the grade level rises.

COUNT评分对于特发性肺纤维化病人肺移植早期预后的预测价值

目的:研究控制营养状态(COUNT)评分对于特发性肺纤维化(IPF)病人肺移植早期预后的预测价值。方法:回顾性收集在无锡市人民医院行肺移植术的154名IPF病人,收集术前资料包括人口统计学资料、术前合并症以及最后一次的实验室检查结果,术中以及术后并发症情况。使用ROC曲线评估COUNT评分及其他营养评估工具预测30 d生存情况的能力,使用Kaplan-Meier法绘制低COUNT组和高COUNT组生存曲线,Log-rank比较两组生存率差异。并使用COX回归分析IPF病人术后30d预后不良的独立危险因素。结果:根据COUNT评分划分,IPF病人术前合并营养不良的有101例(65.6%)。COUNT评分对于IPF肺移植病人早期30d预后不佳的预测能力要高于BMI、Alb、PNI指数。使用ROC确定的cutoff值为2.5划分高低COUNT组,高COUNT组30d、90d生存率低于低COUNT组(P<0.05)。并且高COUNT组入ICU前24hAPACHEⅡ评分更高,术后AKI发生率更高,术后机械通气时间延长、ECMO转流时间延长(P<0.05)。多因素COX回归分析提示高COUNT评分及肥胖是IPF病人肺移植术后30d预后不佳的独立危险因素。结论:COUNT评分是肺移植早期预后不佳的预测因素,在IPF病人肺移植术前进行营养评估至关重要。

三维加速度counts估算不同步速能量消耗应用初探

以间接热测定法为标准,探索counts与能量消耗之间的关系,建立基于三维加速度counts能耗推算方程,寻求不同强度身体运动的counts切点。实验选取115名受试者,佩戴Cortex-3B便携式气体代谢分析仪与ActiGraph GT3X三轴加速度计,分别采用4.8km/h、5.6km/h、6.4km/h、7.2km/h、8.0km/h、8.8km/h步速。结果认为:不同步速下合矢量counts性别间差异不显著;不同步速下体重组别合矢量counts差异无统计学意义;身高、去脂体重与VO2、MET相关性较低,而性别、BMI都在0.2左右水平上显著相关;将BMI与性别引入推算方程,有效提高了counts预测能耗的准确性。

肌松药神经肌肉阻滞期间TOF的T_1与TOF count对比

目的探讨应用定性方法评估TOF T1水平的可行性。方法择期手术成年患者108例,静脉输注丙泊酚及瑞芬太尼维持麻醉。用TOF WATCH SX监测仪以TOF模式透皮刺激腕部尺神经,同时在同侧手应用目测法观测单次静注2×ED95罗库溴铵或顺阿曲库铵后肌松监测仪诱发拇内收肌颤搐反应的恢复过程。按给予的不同肌松药将患者分成男性罗库溴铵组(Rm组)、女性罗库溴铵组(Rf组)、男性顺阿曲库铵组(Cm组)及女性顺阿曲库铵组(Cf组)。记录TOF WATCH SX监测TOF反应依次出现时的T1值、T4出现时的TOFr值;Tmax到T1出现时间(T0～T1)、T1到T2再现时间(T1～T2)、T1到T3再现时间(T1～T3)及T1到T4再现时间(T1～T4)。目测法观测当TOF count=1、2、3、4时,肌松监测仪实测的T1值,记为C1、C2、C3、C4;记录Tmax到TOF count 1出现时间(T0～C1)、TOF count 1到TOF count 2再现时间(C1～C2)、TOF count 1到TOF count 3再现时间(C1～C3)及TOF count 1到TOF count 4再现时间(C1～C4)。结果四组分别比较T0～C1、T0～T1,Cm组较Rm组时间长(P<0.05),Cf组较Rf组时间长(P<0.05)。分别比较C1～C2、C1～C3、C1～C4、T1～T2、T1～T3、T1～T4,四组间无显著性差异(P>0.05)。四组总体C1～C2与T1～T2比较、C1～C3与T1～T3比较、C1～C4与T1～T4比较均无明显差异(P>0.05)。四组患者应用TOF WATCH SX所测得的TOF反应依次出现时的实测T1值为4.0(3.0,4.0)%、12.0(10.0,16.0)%、22.0(18.0,27.0)%、27.0(21.3,33.0)%。当TOF count=1时,四组患者实测T1值为0。当TOF count=2、3、4时,所对应的实测T1值为0.0(0.0,3.8)%、6.0(5.0,9.0)%、9.0(6.0,13.0)%。结论肌松药从深度阻滞到早期恢复阶段罗库溴铵较顺阿曲库铵恢复快。目测法观测TOF count 1出现较加速度换能器肌松监测仪测到的T1显现早。根据TOF count 1出现的时间可预估神经肌肉阻滞程度恢复到TOF count=2、3、4的时间。

Time-to-Count技术测量辐射强度的原理

GM管广泛应用于辐射测量,由于传统的测量方法受到GM管死时间的影响,其测量精度不高。介绍了没有死时间影响,可以提高测量精度的T im e-to-Coun t技术的测量方法,并从理论上论证了采用该方法的数学原理,在此基础上,提出对辐射强度的新估计式,并证明该估计是无偏的渐近最优的,是形式中最优的。并通过计算机仿真证明了该方法的正确性。

一种新的GM计数管Time-To-Count测量方法

主要介绍了目前最新的 GM计数管 Time- To- Count测量方法的基本原理及其工作模型 ,对测量方法的基本特点进行了探讨 ,通过方案设计加以实现并给出了试验结果。

Time-to-Count测量方法的应用研究

Time-to-Count方法是一种通过计算时间差来测量辐射强度的方法。通过控制加到探测元件上的高压,首先测量加上高压后到产生第一个脉冲计数之间的计数时间差,再根据计数时间差进一步计算出辐射强度。这种方法可以消除死时间、饱和电流和高端脉冲重叠等因素的影响,提高探测效率。利用蒙特卡罗方法对Time-to-Count测量方法进行计算机模拟,进一步证明Time-to-Count测量方法的可行性。

Conditional autoregressive negative binomial model for analysis of crash count using Bayesian methods

In order to improve crash occurrence models to account for the influence of various contributing factors, a conditional autoregressive negative binomial （CAR-NB） model is employed to allow for overdispersion （tackled by the NB component）, unobserved heterogeneity and spatial autocorrelation （captured by the CAR process）, using Markov chain Monte Carlo methods and the Gibbs sampler. Statistical tests suggest that the CAR-NB model is preferred over the CAR-Poisson, NB, zero-inflated Poisson, zero-inflated NB models, due to its lower prediction errors and more robust parameter inference. The study results show that crash frequency and fatalities are positively associated with the number of lanes, curve length, annual average daily traffic （AADT） per lane, as well as rainfall. Speed limit and the distances to the nearest hospitals have negative associations with segment-based crash counts but positive associations with fatality counts, presumably as a result of worsened collision impacts at higher speed and time loss during transporting crash victims.

单平台TruCount和PLG-CD_4测定CD_4T细胞绝对计数的比较

目的了解单平台TruCount和PLG-CD4两种不同流式设门方法,对同一样品测定CD4T细胞绝对计数的影响。方法采集408份样品,包括同批次114份,不同时间15批次294份,比较两种不同设门方法检测同一样品CD4T细胞的绝对计数。结果对TruCount和PLG-CD4两种流式设门方法所获取的408份样品的CD4T细胞绝对计数进行分层后显示:只有4例在分层时落入不同范围,判定差异率<1%;在≤200个细胞/μl的范围内,PLG-CD4判定90例,比TruCount少判1例。两种不同方法所得CD4T细胞绝对计数差异均<10%,相关系数r=0.99。结论单平台TruCount和PLG-CD4两种不同流式设门方法测定的CD4T细胞绝对计数是一致的,实际应用中所采用的方法将决定于不同试剂的价格与操作的简易性。

科学评价视角下文献使用比较研究——基于Usage Count的实证分析

[目的/意义]对比分析相同主题的不同类型科学文献的使用行为,利用用户学术行为数据全面测评学术论文影响力。[方法/过程]基于Web of Science数据库中学术论文使用次数,分析比较不同学科文献的使用差异。从文献使用入手,收集2013-2017年3D打印领域的论文数据,以化学、工程文献为对比分析对象,从论文的学科视角分析使用次数与被引频次之间的相关性,分析高使用与高引用(Top 10%)论文的重合文献,探测文献使用差异,并进行独立样本T检验。[结果/结论]U1与被引次数成微弱正相关,U2与被引次数显著性相关;两学科的科学论文在使用上存在统计学意义上的显著差异,可能原因是不同学科学者的文献使用行为不同。此外,文献类型对使用次数有影响,综述类文献信息量较为丰富,从而可以获得更多的使用、引用。