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Management of Cardiac Pacemakers in a Pregnant Patient

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Open Journal of Obstetrics and Gynecology 2015年第1期5卷 60-69页

作者： sonal grover Puja Sheth David E. Haines Mazhar Khan Bernard Gonik Department of Obstetrics and Gynecology Wayne State University School of Medicine Detroit USA Department of Cardiovascular Medicine Oakland University William Beaumont School of Medicine Royal Oak USA Department of Cardiology Wayne State University School of Medicine Detroit USA

Introduction: Despite the increasing use of permanent cardiac pacemakers in a younger patient population, there are little data related to pregnancy. We present our experience in managing a pregnant patient with a pre-existing pacemaker and review the existing literature to establish management guidelines. Case: A 27-year-old G1 P0 presented for prenatal care in the first trimester of pregnancy. She had a past medical history of bradycardia, hypotension and syncope that required dual chamber cardiac pacemaker placement 6 years earlier, and one episode of left upper extremity venous thrombosis related to replacement of the pacemaker wire 4 years earlier. In the early second trimester, the patient began experiencing light-headedness and breathlessness with exertion. The rate settings of the pacemaker were increased with resolution of the patient’s symptoms. The patient underwent primary cesarean section at 39 weeks gestation with delivery of a healthy term infant. Preoperative anesthesia consultation was obtained. The postoperative course was uneventful. Pre-pregnancy pacemaker settings were re-established after the postpartum period. Discussion: The current literature on managing pregnant patients with pre-existing pacemakers is quite limited. Such patients require a multidisciplinary approach to care. Normal physiologic changes in pregnancy may necessitate rate adjustments. Other than routine thromboprophylaxis, no other anticoagulation is needed. Route of delivery is generally based on obstetric indications. During surgery consider using bipolar electrocautery in place of unipolar electrocautery, to reduce electromagnetic interference. Also, the placement of the grounding pad should be as far away from the pacemaker as possible. It should be anticipated that the patient will return to her baseline cardiac status postpartum and therefore pacemaker settings can be adjusted accordingly.

关键词： Pacemaker Pregnancy Anticoagulants Fetal Monitoring Electrocardiography Anesthesia Antepartum

Prediction of bearing capacity of pile foundation using deep learning approaches

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Frontiers of Structural and Civil Engineering 2024年第6期18卷 870-886页

作者： Manish KUMAR Divesh Ranjan KUMAR Jitendra KHATTI Pijush SAMUI Kamaldeep Singh grover Department of Civil Engineering SRM Institute of Science and Technology Tiruchirappalli CampusTrichy 621105India Department of Civil Engineering National Institute of Technology PatnaBihar 800005India Department of Civil Engineering Faculty of EngineeringThammasat School of EngineeringThammasat UniversityBangkok10200Thailand Department of Civil Engineering Rajasthan Technical UniversityKota 324010India

The accurate prediction of bearing capacity is crucial in ensuring the structural integrity and safety of pile *** research compares the Deep Neural Networks(DNN),Convolutional Neural Networks(CNN),Recurrent Neural Networks(RNN),Long Short-Term Memory(LSTM),and Bidirectional LSTM(BiLSTM)algorithms utilizing a data set of 257 dynamic pile load tests for the first ***,this research illustrates the multicollinearity effect on DNN,CNN,RNN,LSTM,and BiLSTM models’performance and accuracy for the first time.A comprehensive comparative analysis is conducted,employing various statistical performance parameters,rank analysis,and error matrix to evaluate the performance of these *** performance is further validated using external validation,and visual interpretation is provided using the regression error characteristics(REC)curve and Taylor *** from the comparative analysis reveal that the DNN(Coefficient of determination(R^(2))_(training(TR))=0.97,root mean squared error(RMSE)_(TR)=0.0413;R^(2)_(testing(TS))=0.9,RMSE_(TS)=0.08)followed by BiLSTM(R^(2)_(TR)=0.91,RMSE_(TR)=0.782;R^(2)_(TS)=0.89,RMSE_(TS)=0.0862)model demonstrates the highest performance *** is noted that the BiLSTM model is better than LSTM because the BiLSTM model,which increases the amount of information for the network,is a sequence processing model made up of two LSTMs,one of which takes the input in a forward manner,and the other in a backward *** prediction of pile-bearing capacity is strongly influenced by ram weight(having a considerable multicollinearity level),and the effect of the considerable multicollinearity level has been determined for the model based on the recurrent neural network *** this study,the recurrent neural network model has the least performance and accuracy in predicting the pile-bearing capacity.

关键词： deep learning algorithms high-strain dynamic pile test bearing capacity of the pile

Prediction of compaction parameters for fine-grained soil: Critical comparison of the deep learning and standalone models

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Journal of Rock Mechanics and Geotechnical Engineering 2023年第11期15卷 3010-3038页

作者： Jitendra Khatti Kamaldeep Singh grover Department of Civil Engineering Rajasthan Technical UniversityKota324010RajasthanIndia

A comparison between deep learning and standalone models in predicting the compaction parameters of soil is presented in this *** hundred and ninety and fifty-three soil samples were randomly picked up from two hundred and forty-three soil samples to create training and validation datasets,*** performance and accuracy of the models were measured by root mean square error(RMSE),coefficient of determination(R2),Pearson product-moment correlation coefficient(r),mean absolute error(MAE),variance accounted for(VAF),mean absolute percentage error(MAPE),weighted mean absolute percentage error(WMAPE),a20-index,index of scatter(IOS),and index of agreement(IOA).Comparisons between standalone models demonstrate that the model MD 29 in Gaussian process regression(GPR)and model MD 101 in support vector machine(SVM)can achieve over 96%of accuracy in predicting the optimum moisture content(OMC)and maximum dry density(MDD)of soil,and outperformed other standalone *** comparison between deep learning models shows that the models MD 46 and MD 146 in long short-term memory(LSTM)predict OMC and MDD with higher accuracy than ANN ***,the LSTM models outperformed the GPR models in predicting the compaction *** sensitivity analysis illustrates that fine content(FC),specific gravity(SG),and liquid limit(LL)highly influence the prediction of compaction parameters.

关键词： Artificial intelligence(AI) Anderson-darling(AD)test Compaction parameters Fine-grained soil Soft computing Score analysis

Allium cepa root tip assay in assessment of toxicity of magnesium oxide nanoparticles and microparticles

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Journal of Environmental Sciences 2018年第4期30卷 125-137页

作者： Bhanuramya Mangalampalli Naresh Dumala Paramjit grover Toxicology Unit Pharmacology and Toxicology Division CSIR-Indian Institute of Chemical Technology Academy of Scientific and Innovative Research CSIR-Indian Institute of Chemical Technology

Allium cepa bioassay had been used from decades for the assessment of toxicants and their harmful effects on environment as well as human health. Magnesium oxide（MgO） particles are being utilized in different fields. However, reports on the adverse effects of MgO nanoparticles on the environment and mankind are scarce. Hence, the toxicity of MgO particles is of concern because of their increased utilization. In the current study, A. cepa was used as an indicator to assess the toxicological efficiency of MgO nano-and microparticles（NPs and MPs） at a range of exposure concentrations（12.5, 25, 50, and100 μg/m L）. The toxicity was evaluated by using various bioassays on A. cepa root tip cells such as comet assay, oxidative stress and their uptake/internalization profile. Results indicated a dose dependent increase in chromosomal aberrations and decrease in mitotic index（MI） when compared to control cells and the effect was more significant for NPs than MPs（at p 〈 0.05）. Comet analysis revealed that the Deoxyribonucleic acid（DNA） damage in terms of percent tail DNA ranged from 6.8–30.1 over 12.5–100 μg/m L concentrations of MgO NPs and was found to be significant at the exposed concentrations. A significant increase in generation of hydrogen peroxide and superoxide radicals was observed in accordance with the lipid peroxidation profile in both MgO NPs and MPs treated plants when compared with control. In conclusion, this investigation revealed that MgO NPs exposure exhibited greater toxicity on A. cepa than MPs.

关键词： Magnesium oxide nanoparticles Allium cepa root tip assay Histochemical staining Oxidative stress Internalization of nanoparticles