Accuracy of biometric formulae for intraocular lens power calculation in a teaching hospital

AIM: To evaluate the accuracy of three commonly used biometric formulae across different axial lengths(ALs) at one United States Veterans Affairs teaching hospital.METHODS: A retrospective chart review was conducted from November 2013 to May 2018. One eye of each patient who underwent cataract surgery with a monofocal intraocular lens(IOL) was included. The range of postoperative follow-up period was from 3 wk to 4 mo. The Holladay 2, Barrett Universal II, and Hill-Radial Basis Function(Hill-RBF) formulae were used to predict the postoperative refraction for all cataract surgeries. For each formula, we calculated the prediction errors [including mean absolute prediction error(MAE)] and the percentage of eyes within ±0.25 diopter(D) and ±0.5 D of predicted refraction. We performed subgroup analyses for short(AL<22.0 mm), medium(AL 22.0-25.0 mm), and long eyes(AL>25.0 mm).RESULTS: A total of 1131 patients were screened, and 909 met the inclusion criteria. Resident ophthalmologists were the primary surgeons in 710(78.1%) cases. We found no statistically significant difference in predictive accuracy among the three formulae over the entire AL range or in the short, medium, and long eye subgroups. Across the entire AL range, the Hill-RBF formula resulted in the lowest MAE(0.384 D) and the highest percentage of eyes with postoperative refraction within ±0.25 D(42.7%) and ±0.5 D(75.5%) of predicted. All three formulae had the highest MAEs(>0.5 D) and lowest percentage within ±0.5 D of predicted refraction(<55%) in short eyes.CONCLUSION: In cataract surgery patients at our teaching hospital, three commonly used biometric formulae demonstrate similar refractive accuracy across all ALs. Short eyes pose the greatest challenge to predicting postoperative refractive error.

Application of total keratometry in ten intraocular lens power calculation formulas in highly myopic eyes

Background:The accuracy of using total keratometry(TK)value in recent IOL power calculation formulas in highly myopic eyes remained unknown.Methods:Highly myopic patients who underwent uneventful cataract surgery were prospectively enrolled in this prospective comparative study.At one month postoperatively,standard deviation(SD)of the prediction errors(PEs),mean and median absolute error(MedAE)of 103 highly myopic eyes were back-calculated and compared among ten formulas,including XGboost,RBF 3.0,Kane,Barrett Universal II,Emmetropia Verifying Optical 2.0,Cooke K6,Haigis,SRK/T,and Wang-Koch modifications of Haigis and SRK/T formulas,using either TK or standard keratometry(K)value.Results:In highly myopic eyes,despite good agreement between TK and K(P>0.05),larger differences between the two were associated with smaller central corneal thickness(P<0.05).As to the refractive errors,TK method showed no differences compared to K method.The XGBoost,RBF 3.0 and Kane ranked top three when considering SDs of PEs.Using TK value,the XGboost calculator was comparable with the RBF 3.0 formula(P>0.05),which both presented smaller MedAEs than others(all P<0.05).As for the percentage of eyes within±0.50 D or±0.75 D of PE,the XGBoost TK showed comparable percentages with the RBF 3.0 TK formula(74.76%vs.66.99%,or 90.29%vs.87.38%,P>0.05),and statistically larger percentages than the other eight formulas(P<0.05).Conclusions:Highly myopic eyes with thinner corneas tend to have larger differences between TK and K.The XGboost enhancement calculator and RBF 3.0 formula using TK showed the most promising outcomes in highly myopic eyes.

Ground moving target signal model and power calculation in forward scattering micro radar

Forward scattering micro radar is used for situation awareness; its operational range is relatively short because of the battery power and local horizon, the free space propagation model is not appropriate. The ground moving targets, such as humans, cars and tanks, have only comparable size with the transmitted signal wavelength; the point target model and the linear change of observation angle are not applicable. In this paper, the signal model of ground moving target is developed based on the case of forward scattering micro radar, considering the two-ray propagation model and area target model, and nonlinear change of observation angle as well as high order phase error. Furthermore, the analytical form of the received power from moving target has been obtained. Using the simulated forward scattering radar cross section, the received power of theoretical calculation is near to that of measured data. In addition, the simulated signal model of ground moving target is perfectly matched with the experimented data. All these results show the correctness of analytical calculation completely.

Accuracy of intraocular lens power calculation formulae after laser refractive surgery in myopic eyes:a meta-analysis

Background:To compare the accuracy of intraocular lens power calculation formulae after laser refractive surgery in myopic eyes.Methods:We searched the databases on PubMed,EMBASE,Web of Science and the Cochrane library to select relevant studies published between Jan 1st,2009 and Aug 11th,2019.Primary outcomes were the percentages of refractive prediction error within±0.5 D and±1.0 D.Results:The final meta-analysis included 16 studies using seven common methods(ASCRS average,Barrett True-K no history,Double-K SRK/T,Haigis-L,OCT formula,Shammas-PL,and Wang-Koch-Maloney).ASCRS average yielded significantly higher percentage of refractive prediction error within±0.5 D than Haigis-L,Shammas-PL and WangKoch-Maloney(P=0.009,0.01,0.008,respectively).Barrett True-K no history also yielded significantly higher percentage of refractive prediction error within±0.5 D than Shammas-PL and Wang-Koch-Maloney(P=0.01,P<0.0001,respectively),and a similar result was found when comparing OCT formula with Haigis-L and Shammas-PL(P=0.03,P=0.01,respectively).Conclusion:The ASCRS average or Barrett True-K no history should be used to calculate the intraocular lens power in eyes after myopic laser refractive surgery.The OCT formula if available,can also be a good alternative choice.

Instantaneous power calculation based on intrinsic frequency of single-phase virtual synchronous generator

In order to enhance the stability of single-phase microgrid,virtual synchronous generator(VSG)control method is investigated in this paper.Its electromagnetic model and electromechanical model are established to illustrate the performance of VSG.Considering the 2 nd fluctuation of fundamental-frequency in the output power,an instantaneous power calculation strategy is proposed based on the intrinsic frequency of single-phase VSG.Besides,a virtual power calculation method is presented to achieve islanded/grid-connected seamless transition.Stability analysis and comparison simulation results demonstrate the correctness of the presented power calculation method.At last,the effectiveness of the proposed approach is verified by comparison experiments of islanded/gridconnected operations in a 500 VA single-phase inverter.

Accuracy of intraocular lens power calculation formulae after laser refractive surgery in myopic eyes:a meta-analysis

Background:To compare the accuracy of intraocular lens power calculation formulae after laser refractive surgery in myopic eyes.Methods:We searched the databases on PubMed,EMBASE,Web of Science and the Cochrane library to select relevant studies published between Jan 1st,2009 and Aug 11th,2019.Primary outcomes were the percentages of refractive prediction error within±0.5 D and±1.0 D.Results:The final meta-analysis included 16 studies using seven common methods(ASCRS average,Barrett True-K no history,Double-K SRK/T,Haigis-L,OCT formula,Shammas-PL,and Wang-Koch-Maloney).ASCRS average yielded significantly higher percentage of refractive prediction error within±0.5 D than Haigis-L,Shammas-PL and Wang,Koch-Maloney(P=0.009,0.01,0.008,respectively).Barrett True-K no history also yielded significantly higher percentage of refractive prediction error within±0.5 D than Shammas-PL and Wang-Koch-Maloney(P=0.01,P<0.0001,respectively),and a similar result was found when comparing OCT formula with Haigis-L and Shammas-PL(P=0.03,P=0.01,respectively).Conclusion:The ASCRS average or Barrett True-K no history should be used to calculate the intraocular lens power in eyes after myopic laser refractive surgery.The OCT formula if available,can also be a good alternative choice.

Machine learning adaptation of intraocular lens power calculation for a patient group

Background:To examine the effectiveness of the use of machine learning for adapting an intraocular lens(IOL)power calculation for a patient group.Methods:In this retrospective study,the clinical records of 1,611 eyes of 1,169 Japanese patients who received a single model of monofocal IOL(SN60WF,Alcon)at Miyata Eye Hospital were reviewed and analyzed.Using biometric metrics and postoperative refractions of 1211 eyes of 769 patients,constants of the SRK/T and Haigis formulas were optimized.The SRK/T formula was adapted using a support vector regressor.Prediction errors in the use of adapted formulas as well as the SRK/T,Haigis,Hill-RBF and Barrett Universal II formulas were evaluated with data from 395 eyes of 395 distinct patients.Mean prediction errors,median absolute errors,and percentages of eyes within±0.25 D,±0.50 D,and±1.00 D,and over+0.50 D of errors were compared among formulas.Results:The mean prediction errors in the use of the SRT/K and adapted formulas were smaller than the use of other formulas(P<0.001).In the absolute errors,the Hill-RBF and adapted methods were better than others.The performance of the Barrett Universal II was not better than the others for the patient group.There were the least eyes with hyperopic refractive errors(16.5%)in the use of the adapted formula.Conclusions:Adapting IOL power calculations using machine learning technology with data from a particular patient group was effective and promising.

Machine learning adaptation of intraocular lens power calculation for a patient group

Background:To examine the effectiveness of the use of machine learning for adapting an intraocular lens(IOL)power calculation for a patient group.Methods:In this retrospective study,the clinical records of 1,611 eyes of 1,169 Japanese patients who received a single model of monofocal IOL(SN60WF,Alcon)at Miyata Eye Hospital were reviewed and analyzed.Using biometric metrics and postoperative refractions of 1211 eyes of 769 patients,constants of the SRK/T and Haigis formulas were optimized.The SRK/T formula was adapted using a support vector regressor.Prediction errors in the use of adapted formulas as well as the SRK/T,Haigis,Hill-RBF and Barrett Universal II formulas were evaluated with data from 395 eyes of 395 distinct patients.Mean prediction errors,median absolute errors,and percentages of eyes within±0.25 D,±0.50 D,and±1.00 D,and over+0.50 D of errors were compared among formulas.Results:The mean prediction errors in the use of the SRT/K and adapted formulas were smaller than the use of other formulas(P<0.001).In the absolute errors,the Hill-RBF and adapted methods were better than others.The performance of the Barrett Universal II was not better than the others for the patient group.There were the least eyes with hyperopic refractive errors(16.5%)in the use of the adapted formula.Conclusions:Adapting IOL power calculations using machine learning technology with data from a particular patient group was effective and promising.

A New Parallel Algorithm in Power Flow Calculation:Dynamic Asynchronous Parallel Algorithm

Based on the general methods in power flow calculation of power system and on conceptions and classifications of parallel algorithm, a new approach named Dynamic Asynchronous Parallel Algorithm that applies to the online analysis and real-time dispatching and controlling of large-scale power network was put forward in this paper. Its performances of high speed and dynamic following have been verified on IEEE-14 bus system.

Calculation of Skin Depths and Eddy-Current Power Losses for Magnetic Position Sensors

We present a theoretic model to calculate skin depths and eddy-current power losses for a magnetic position sensor. Eddy-current, arised from the operation of an alternating-current excitation, induces secondary currents and fields between magnetic material and magnetic position sensor. In this paper, a magnetic position sensor system is simplified to be an outer-winding coil along the axial direction of a low carbon steel bar. The analytical model is derived from basic field and circuit theory considering a linear approximation for a nonlinear permeability. Thus the skin depths and eddy-current power losses from the model in eddy-current modeling techniques at various frequencies of an excited current source can be calculated. The proposed configuration is capable of predicting the skin depths and eddy-current power losses for a magnetic position sensor and has a consistence with experiments.

Scheme of long distance power supply for electrified railway traction network based on traction cable

Purpose–The traction cable is paralleled with the existing traction network of electrified railway through transverse connecting line to form the scheme of long distance power supply for the traction network.This paper aims to study the scheme composition and power supply distance(PSD)of the scheme.Design/methodology/approach–Based on the structure of parallel traction network(referred to as“cable traction network(CTN)”),the power supply modes(PSMs)are divided into cableþdirect PSM and cableþautotransformer(AT)PSM(including Japanese mode,French mode and new mode).Taking cableþJapanese AT PSM as an example,the scheme of long distance power supply for CTN under the PSMs of co-phase and out-of-phase power supply are designed.On the basis of establishing the equivalent circuit model and the chain circuit model of CTN,taking the train working voltage as the constraint condition,and based on the power flow calculation of multiple train loads,the calculation formula and process for determining the PSD of CTN are given.The impedance and PSD of CTN under the cableþAT PSM are simulated and analyzed,and a certain line is taken as an example to compare the scheme design.Findings–Results show that the equivalent impedance of CTN under the cableþAT PSM is smaller,and the PSD is about 2.5 times of that under the AT PSM,which can effectively increase the PSD and the flexibility of external power supply location.Originality/value–The research content can effectively improve the PSD of traction power supply system and has important reference value for the engineering application of the scheme.

Reactive Power Flow Convergence Adjustment Based on Deep Reinforcement Learning

Power flow calculation is the basis of power grid planning and many system analysis tasks require convergent power flow conditions.To address the unsolvable power flow problem caused by the reactive power imbalance,a method for adjusting reactive power flow convergence based on deep reinforcement learning is proposed.The deep reinforcement learning method takes switching parallel reactive compensation as the action space and sets the reward value based on the power flow convergence and reactive power adjustment.For the non-convergence power flow,the 500 kV nodes with reactive power compensation devices on the low-voltage side are converted into PV nodes by node type switching.And the quantified reactive power non-convergence index is acquired.Then,the action space and reward value of deep reinforcement learning are reasonably designed and the adjustment strategy is obtained by taking the reactive power non-convergence index as the algorithm state space.Finally,the effectiveness of the power flow convergence adjustment algorithm is verified by an actual power grid system in a province.

Modeling load distribution for rural photovoltaic grid areas using image recognition

Expanding photovoltaic(PV)resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape,aligning with the“carbon peaking and carbon neutrality”objectives.However,rural power grids often lack digitalization;thus,the load distribution within these areas is not fully known.This hinders the calculation of the available PV capacity and deduction of node voltages.This study proposes a load-distribution modeling approach based on remote-sensing image recognition in pursuit of a scientific framework for developing distributed PV resources in rural grid areas.First,houses in remote-sensing images are accurately recognized using deep-learning techniques based on the YOLOv5 model.The distribution of the houses is then used to estimate the load distribution in the grid area.Next,equally spaced and clustered distribution models are used to adaptively determine the location of the nodes and load power in the distribution lines.Finally,by calculating the connectivity matrix of the nodes,a minimum spanning tree is extracted,the topology of the network is constructed,and the node parameters of the load-distribution model are calculated.The proposed scheme is implemented in a software package and its efficacy is demonstrated by analyzing typical remote-sensing images of rural grid areas.The results underscore the ability of the proposed approach to effectively discern the distribution-line structure and compute the node parameters,thereby offering vital support for determining PV access capability.

TESTING FOR VARYING DISPERSION OF LONGITUDINAL BINOMIAL DATA IN NONLINEAR LOGISTIC MODELS WITH RANDOM EFFECTS

In this paper, it is discussed that two tests for varying dispersion of binomial data in the framework of nonlinear logistic models with random effects, which are widely used in analyzing longitudinal binomial data. One is the individual test and power calculation for varying dispersion through testing the randomness of cluster effects, which is extensions of Dean(1992) and Commenges et al (1994). The second test is the composite test for varying dispersion through simultaneously testing the randomness of cluster effects and the equality of random-effect means. The score test statistics are constructed and expressed in simple, easy to use, matrix formulas. The authors illustrate their test methods using the insecticide data (Giltinan, Capizzi & Malani (1988)).

Power Flow Model for Medium-voltage Distribution Systems Considering Measurement and Structure Characteristics

Medium-voltage distribution systems(MVDSs)mainly consist of a feeder head,lines,distribution transformers,and the equivalent load or power supply interfaced with the distribution transformers.The information of such load or power supply can be measured via the three-wattmeter method(THM)and the two-wattmeter method(TWM).The measurements can be used to perform the control of the power supply and simulate the characteristics of the load,so the models of the load and the power supply need to consider the measurement characteristics.Existing research works on three-phase power flow(PF)just consider the measurement characteristics of THM.Hence,the PF equation of the bus measured via TWM is firstly built.Based on conventional measurements,an accurate and general model of the grounded and ungrounded slack bus is proposed.Furthermore,the influence arising from the connection type and angle shift of distribution transformers on the admittance matrix is considered,and thus a general three-phase transformer model is summarized,which is applicable for all the transformers mentioned herein.Finally,Newton's method is adopted to solve the PF calculation,and the performance of the proposed PF model is demonstrated through designed tests.

Comparison of a new optical biometer and a standard biometer in cataract patients

Background:Cataract surgery is the most common surgical procedure in ophthalmology.Biometry data and accurate intraocular lens(IOL)calculations are very important in achieving the desired refractive outcomes.The aim of this study was to compare measurements using a new optical low coherence reflectometry(OLCR)biometer(OA-2000)and the gold standard partial coherence interferometry(PCI)optical biometer(IOLMaster 500).Methods:Ocular biometry of cataract patients were measured by the OA-2000 and IOLMaster 500 to compare keratometry(K),axial length(AL),anterior chamber depth(ACD),white-to-white(WTW)diameter,and IOL power using the SRK/T formula.Results:One hundred and two eyes of 68 cataract patients were evaluated with the two optical biometers.The mean values of the AL,K,ACD,and WTW differed very little(OCLR biometer,23.12 mm,44.50 diopters(D),3.06,and 11.64 mm,respectively;PCI biometer,23.18 mm,44.6 D,3.15,and 11.86 mm,respectively),but the differences were significant(all,p≤0.05).The AL,K,and ACD showed excellent correlations(r=0.999,0.980,and 0.824,respectively;all p<0.001);however,there was a weak correlation of the WTW diameter between the two devices(r=0.256).The IOL powers using the SRK-T formula derived from both instruments were very similar,with an excellent correlation(r=0.989).The mean difference between the two instruments was 0.32 D.Conclusions:The OLCR biometer showed very a strong agreement with the standard PCI optical biometer for almost all ocular biometry measurements,except for the WTW diameter.Trial registration:TCTR20160614003;date 06/09/2016;‘retrospectively registered’.

Approximation by random weighting method for M-test in linear models

The M-test has been in common use and widely studied in testing the linear hypotheses in linear models. However, the critical value for the test is usually related to the quantities of the unknown error distribution and the estimate of the nuisance parameters may be rather involved, not only for the M-test method but also for the existing bootstrap methods. In this paper we suggest a random weighting resampling method for approximating the null distribution of the M-test statistic. It is shown that, under both the null and the local alternatives, the random weighting statistic has the same asymptotic distribution as the null distribution of the M-test. The critical values of the M-test can therefore be obtained by the random weighting method without estimating the nuisance parameters. A distinguished feature of the proposed method is that the approximation is valid even the null hypothesis is not true and the power evaluation is possible under the local alternatives.

Operational Risk Assessment for Integrated Transmission and Distribution Networks

To satisfy the requirements of accurate operationalrisk assessment of integrated transmission and distribution networks (I-T&D), an integrated operational risk assessment (IORA) algorithm is proposed. Specific cases demonstrate thatan I-ORA is necessary because it provides accurate handlingof the coupling between transmission and distribution networks,accurate analysis of power supply mode (PSM) changes ofimportant users and helps to improve security and stability ofpower grid operations. Two key technical requirements in theI-ORA algorithm are realized, i.e., integrated topology analysisand integrated power flow calculation. Under a certain contingency, integrated topology analysis is used to assess the risksof substation power cuts, network split and PSM changes ofimportant users, while the integrated power flow calculation,based on the self-adaptive Levenburg-Marquard method andNewton method, can be implemented to assess risks of heavyload/overload and voltage deviation. In addition, the graphicsprocessing unit is used to parallelly process some computationintensive steps. Numerical experiments show that the proposedI-ORA algorithm can realize accurate assessment for the entireI-T&D. In addition, the efficiency and convergence are satisfying,indicating the proposed I-ORA algorithm can significantly benefitreal practice in the coordination operation of I-T&D in the future.