Best-fit Distribution Research Articles

Cost-Effectiveness of brentuximab vedotin with chemotherapy in frontline treatment of CD30-expressing peripheral T-cell lymphoma.

e19060 Background: The most common frontline treatment for peripheral T-cell lymphoma (PTCL) is cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) or a CHOP-like regimen. In the recently reported phase 3 ECHELON-2 trial, brentuximab vedotin (BV) in combination with CHP (A+CHP) demonstrated significant improvement in progression-free survival (PFS) and overall survival (OS) compared to CHOP, with a manageable safety profile. The objective of this analysis was to evaluate the cost-effectiveness of A+CHP in the frontline setting for CD30-expressing PTCL. Methods: A partitioned survival model consisting of 3 health states (PFS, post progression survival, and death), was constructed using clinical and quality of life data from ECHELON-2 from a US payer perspective over a lifetime time horizon. PFS and OS observed from ECHELON-2 were extrapolated using standard parametric distributions. The best-fitting distributions (log-normal for both arms) were selected based on statistical goodness of fit and clinical plausibility of the long-term projections. Health utilities were derived from the European Quality of Life 5-Dimensions (EQ-5D) data collected in ECHELON-2. The average utility scores for the pre- and post-progression periods were estimated via a repeated-measures mixed-effects model. Medical resource use and costs were from literature. Results: The model predicted A+CHP extended undiscounted PFS by 2.92 and OS by 3.38 years over CHOP. These survival gains drive the value in the model. After adjusting for quality of life and discounting, A+CHP was associated with 1.79 quality-adjusted life years (QALYs) gained at an incremental cost of $176,842, yielding an incremental cost-effectiveness ratio (ICER) of $98,987. Sensitivity analyses of alternative model assumptions provided ICERs from $64,000 to $154,000. The estimated probability that A+CHP is cost-effective compared with CHOP was 75% at a willingness-to-pay threshold of $150,000. Conclusions: Based on the ECHELON-2 trial data, this analysis showed for patients with previously untreated CD30-expressing PTCL, treatment with BV in combination with CHP is likely to be cost-effective in comparison to CHOP.

Association between time to first subsequent therapy (TFST) and overall survival (OS) in previously untreated patients with ovarian cancer (OC): A SEER Medicare database analysis.

e17095 Background: TFST may be a patient-relevant indicator of efficacy beyond progression in OC, however, the association between TFST and OS is unknown. We analyzed the SEER Medicare database to determine whether OS varied by TFST in previously untreated patients with OC. Methods: From the SEER-Medicare linked database, we identified newly diagnosed OC patients (≥66 years) who initiated first-line chemotherapy between 2009 and 2015. Patients were followed through the end of 2016. TFST was defined as the time from initiation of first-line chemotherapy until the start of subsequent therapy or death. Cox models summarized the overall association between TFST and OS through hazard ratios (HRs), and by TFST strata for patients who had a TFST event. In case hazards were non-proportional, we examined the fit of independent parametric survival curves. Results: In the cohort of 1407 patients, 1005 patients had a TFST event. Median age was 74 years and 34.9% were alive at the time of this analysis. For population with a TFST, the median TFST was 13.1 months and median OS was 30.88 months (HR = 0.29, 95% CI: 0.26, 0.32). Among patients < 75 years, the median TFST was 13.65 months and the median OS was 37.07 months (HR = 0.24, 95% CI: 0.21, 0.28). In the full cohort of 1407 patients, the best-fitting distributions accelerated failure time models under which the (unrestricted) mean TFST and OS were 44.9 and 73.8 months respectively. This indicated that on average TFST was an acceleration of OS by a factor of 39%. Conclusions: In this elderly population of previously untreated OC, longer TFST was associated with longer OS. Limitations of this analysis include censoring of OS and immortal time bias. [Table: see text]

PCN60 FITTING DISTRIBUTIONS OF PARAMETRIC MODELS INTO NON-PARAMETRIC KAPLAN-MEIER CURVE: APPLICATION IN EXCEL AND COMPARISON OF DIFFERENT DATA RECREATION METHODS

To use Excel spreadsheet software to fit parametric survival distributions onto non-parametric Kaplan-Meier curve. The difference between Individual Patient Data (IPD) and survival data reconstructed in Excel and SAS was reviewed and the impact of those differences on economic evaluation results was assessed. Three sets of patient data on Overall Survival (OS) were compared using different elicitation methods: “Original” IPD, “Reconstructed SAS” and “Reconstructed Excel”. Best-fit distribution was selected using visual observation, supported by graphical tests of linear plots of predicted probabilities, goodness-of-fit coefficients(R-squared)and the sum of squared errors of prediction (SSE). Outcomes in Incremental Cost-Effectiveness Ratio (ICER), Incremental Net Benefit (INB), incremental cost and life-years gained over short- and life-time horizons were compared for different data sets. Log-Normal, Log-Logistic and Weibull distributions showed best-fit when visual test, R-squared and SSE were applied in Excel. Weibull and Exponential distributions showed significant differences with IPD data. Data on short-term (5 years) visual comparison and graphical test of parametric distributions generated by different data re-creation methods showed a close resemblance with data reconstructed from SAS to the Original IPD. Results of ICER and INB were dependent on the time horizon and selected parametric distribution from the model. Different approaches used in fitting parametric survival distribution yielded predicted probabilities that substantially differed to those using original IPD. Guidelines to economic evaluations would benefit from the inclusion of parametric survival analysis techniques with guidance in selecting the best fitting parametric survival distribution.

Application of the Mathematical Simulation Methods for the Assessment of the Wastewater Treatment Plant Operation Work Reliability

The aim of the present work was the modeling of the wastewater treatment plant operation work using Monte Carlo method and different random variables probability distributions modeling. The analysis includes the following pollutants indicators; BOD5 (Biochemical Oxygen Demand), CODCr (Chemical Oxygen Demand), Total Suspended Solids (SSt), Total Nitrogen (TN), and Total Phosphorus (TP). The Anderson–Darling (A–D) test was used for the assessment of theoretical and empirical distributions compatibility. The selection of the best-fitting statistical distributions was performed using peak-weighted root mean square (PWRMSE) parameter. Based on the performed calculations, it was stated that pollutants indicators in treated sewage were characterized by a significant variability. Obtained results indicate that the best-fitting pollutants indicators statistical distribution is Gauss Mixed Model (GMM) function. The results of the Monte Carlo simulation method confirmed that some problems related to the organic and biogenic pollutants reduction may be observed in the Wastewater Treatment Plant, in Jaworzno.

Optimizing the Lightning Warning Radii at Spaceport Florida

Abstract Air Force Manual 91–203 (AFMAN 91–203) directs that a lightning warning be issued when lightning is occurring within a 5 nautical mile (n mi; 1 n mi = 1.852 km) radius of a predetermined location. The 45th Weather Squadron (45 WS), located on the central eastern coast of Florida, provides weather support to Cape Canaveral Air Force Station, NASA Kennedy Space Center, and Patrick Air Force Base. The primary objective of this study is to optimize the lightning warning safety buffer; in particular, to determine if the 5 n mi safety radius can be reduced while maintaining a desired level of safety. The research uses processed Lightning Detection and Ranging II (LDAR-II) data from 2013 to 2016 to map the movement of preexisting lightning storms using ellipses. These ellipses are updated with every lightning flash. The distance from the ellipse boundary of each flash occurring outside the ellipse is recorded. Those exterior flash distances are then used to find the best-fit distribution from which the stand-off distance for the desired level of safety can be calculated. The distances from the edge of the ellipse are fit to a Weibull distribution and a reduction in the radius by 1 to 4 or 5 n mi is selected as the optimized balance between safety and operational impact. The 4 or 5 n mi radii are tested with a resulting failure rate of 3.58%, with an average savings of 130.75 false alarms and 15.7 8-h man days a year for the months of May–September.

Development of marine water quality criteria for inorganic mercury in China based on the retrievable toxicity data and a comparison with relevant criteria or guidelines.

The development of marine water quality criteria (WQC) in China has been insufficient because data on the toxicity of pollutants for marine organisms based on the species sensitivity distribution (SSD) method are lacking. The Chinese aquatic environmental quality standards, including those for seawater, were derived from the developed countries. Therefore, establishing Chinese marine WQC is crucial for identifying the sensitivity of marine species in China and will improve their protection from threats. Mercury (Hg) is one of the primary pollutants commonly exceeding Chinese seawater quality standards. Several countries have developed their marine WQC for inorganic Hg in the past decades, but no study has been conducted in China. In this study, 45 acute toxicity and 14 chronic toxicity data of inorganic Hg on the marine species which inhabit in China were obtained mainly from the ECOTOX database, the CNKI, and the Google Scholar. The acute and chronic hazardous concentrations for 5% of the species (HC5) were calculated based on the best-fit distribution model Sweibull. The criteria for maximum and continuous concentrations of 1.30 and 0.66 μg/L, respectively, for inorganic Hg to protect marine organisms in China were derived by halving the HC5 values. The criteria were comparable to those of the United States, Australia, and the European Union countries, indicating the general applicability of WQCs developed based on the classical SSD method using different species groups. This study may provide valuable information for assessing marine ecological risk in China.

Regional Frequency Analysis of Precipitation Extremes and Its Spatio-Temporal Patterns in the Hanjiang River Basin, China

Extreme events such as rainstorms and floods are likely to increase in frequency due to the influence of global warming, which is expected to put considerable pressure on water resources. This paper presents a regional frequency analysis of precipitation extremes and its spatio-temporal pattern characteristics based on well-known index-flood L-moments methods and the application of advanced statistical tests and spatial analysis techniques. The results indicate the following conclusions. First, during the period between 1969 and 2015, the annual precipitation extremes at Fengjie station show a decreasing trend, but the Wuhan station shows an increasing trend, and the other 24 stations have no significant trend at a 5% confidence level. Secondly, the Hanjiang River Basin can be categorized into three homogenous regions by hierarchical clustering analysis with the consideration of topography and mean precipitation in these areas. The GEV, GNO, GPA and P III distributions fit better for most of the basin and MARE values range from 3.19% to 6.41% demonstrating that the best-fit distributions for each homogenous region is adequate in predicting the quantiles estimates. Thirdly, quantile estimates are reliable enough when the return period is less than 100 years, however estimates for a higher return period (e.g., 1000 years) become unreliable. Further, the uncertainty of quantiles estimations is growing with the growing return periods and the estimates based on R95P series have a smaller uncertainty to describe the extreme precipitation in the Hanjiang river basin (HJRB). Furthermore, In the HJRB, most of the extreme precipitation events (more than 90%) occur during the rainy season between May and October, and more than 30% of these extreme events concentrate in July, which is mainly impacted by the sub-tropical monsoon climate. Finally, precipitation extremes are mainly concentrated in the areas of Du River, South River and Daba Mountain in region I and Tianmen, Wuhan and Zhongxiang stations in region III, located in the upstream of Danjiangkou Reservoir and Jianghan Plain respectively. There areas provide sufficient climate conditions (e.g., humidity and precipitation) responsible for the occurring floods and will increase the risk of natural hazards to these areas.

Reliability, availability and maintainability analysis of a cement plant: a case study

Purpose The demand of cement in India is expected to increase rapidly as the government has been giving immense boost to various housing facilities, infrastructure projects, road networks and railway corridors. One of the ways to meet this rise in the demand of cement is to increase the capacity utilization of the existing cement plants by improving their availability. The availability of a cement plant can be improved by avoiding failures and reducing maintenance time through reliability, availability and maintainability (RAM) analysis of its subsystems. The paper aims to discuss this issue. Design/methodology/approach The data related to time between failure (TBF) and time to repair (TTR) of all the critical subsystems of a cement plant were collected over a period of two years for carrying out RAM analysis. Trend test and serial correlation test were performed on TBF and TTR data to verify whether these data are independent and identically distributed or not. Afterwards, the authors use EasyFit 5.6 professional software to find best-fit distribution of TBF and TTR data and their parameters. The effectiveness of a preventive maintenance policy was evaluated by simulating the real and proposed systems. Findings The results of the analysis show that the raw mill and the coal mill are critical subsystems of a cement plant from a reliability point of view, whereas the kiln is a critical subsystem from an availability point of view. The analysis shows that the repair time of the cement mill should be reduced for improving the availability of the cement plant. The RAM analysis showed that the capacity of the case study company is 17 percent underutilized due to maintenance-related problems and 15 percent underutilized because of management-related problems. Practical implications The study exhibits the usage of RAM analysis in deciding preventive maintenance programs of several cement plant subsystems. Thus, it would serve as a reference for reliability and maintenance managers in deciding maintenance strategies of cement plants as well as in improving their capacity utilization. Originality/value The study exhibits the usage of RAM analysis in deciding preventive maintenance programs of several cement plant subsystems. Even more, using a simulation study, the authors show that preventive maintenance of the cement plant beyond a certain level can be disadvantageous as it leads to an increase in downtime and decrease in availability.

Examining two-wheelers' overtaking behavior and lateral distance choices at a shared roadway facility

This article investigates the lateral distance that overtaking two-wheelers (bicycles, e-bikes, and e-scooters) keep from automobiles at shared traffic streets. A video-based computer vision technique is used to track road users, collect their trajectories, and measure the lateral distance. A full Bayesian logit model is developed to examine the factors that affect the likelihood of two-wheelers accepting the critical lateral distance that is defined as the 10th percentile lateral distance. The results show that (a) the average lateral distance between overtaking two-wheelers and automobiles is 1.54 m, (b) the lateral distance for bicycles is significantly larger than that for e-bikes and e-scooters, (c) the lateral distance follows a best-fitted Gamma distribution. Further results from the full Bayesian logit model show that (a) two-wheelers type, evasive action manner, occurrence of a platoon of moving two-wheelers, and two-wheelers' yaw rate ratio are significantly positively related to the probability of two-wheelers accepting the critical lateral distance and (b) the presence of heavy vehicles and the speed difference between two-wheelers and interacting automobiles are negatively associated with the above probability.

Future Changes in Monthly Extreme Precipitation in Japan Using Large-Ensemble Regional Climate Simulations

AbstractThis study investigated future changes in monthly extreme precipitation in Japan during summer (June–August). The uncertainties in estimating extreme monthly precipitation were analyzed using large-ensemble regional climate simulations for both present and 4-K warmer climates. The main diagnostics were based on the 100-yr return values of monthly total precipitation PT100 estimated from a best-fit probability distribution. Under the warmer climate, PT100 was projected to increase in approximately 87%, 88%, and 78% of the total number of stations for June, July, and August, respectively, suggesting that once-per-century monthly precipitation will increase as temperature increases over a wide area of Japan, although large regional variations will exist. The western part of Kyushu and the Hokkaido region showed significant and moderately robust increases in PT100 throughout the summer months. In contrast, a considerable and robust increase was projected only in June in the Nansei Islands. The percentage change in PT100 was small in western and eastern Japan, and thus the sign of the change was uncertain. Further analysis indicated that uncertainty in internal variability is more important than uncertainty in the SST scenario for future projections of monthly precipitation extremes.

Application and analysis of methods for the evaluation of failure rate distribution parameters for avionics components

The paper provides an overview of the principal failure rate distributions and it is focused on the comparison between exponential and Weibull distributions: this study illustrates the advantages and disadvantages of the constant failure rate of the exponential distribution and the Weibull time-dependent behavior. The second part of the paper deals with the parameter estimation methods that used to determine the best-fitting distribution for a set of data collected during testing or field operations. The methods considered in that case are probability plotting, Least Square Estimation and Maximum Likelihood Estimation. Finally, two different types of field data such as failure times achieved with testing of electronic board for avionics components are analyzed by software to find which distribution fits better the data.

Stress Testing With Influencing Factors to Accelerate Data Race Software Failures

Software failures caused by data race bugs have always been major concerns in parallel and distributed systems, despite significant efforts spent in software testing. Due to their nondeterministic and hard-to-reproduce features, when evaluating systems' operational reliability, a rather long period of experimental execution time is expected to be spent on observing failures caused by data race conditions. To address this problem, in this paper, we make two contributions. First, this paper proposes stress testing with influencing factors, in which the system runs under certain workloads for a long time with controlled stress conditions to accelerate the occurrence of data race failures. Second, it explores and formulates mathematical relationship models between data races' statistical characteristics of time to failure (TTF) or mean TTF (MTTF) and the influencing factors. Such relationship models are used for TTF/MTTF extrapolation under different operational conditions and are essential to reduce systems' reliability evaluation time. The proposed method is empirically evaluated on six applications suffering from failures caused by real-world data race bugs. Through analysis of the experimental results, we obtain several important findings: First, the reduction in the manifestation time to data race failures achieved by controlling the influencing factors is statistically significant. Second, Power model is the best-fitting model of the relationship between the MTTF and the influencing factors. Third, Power Weibull distribution is the best-fitting probability distribution between the TTF and the influencing factors. Finally, the TTF/MTTF can be accurately estimated with the approach proposed in this paper.

Exploring Properties and Correlations of Fatal Events in a Large-Scale HPC System

In this paper, we explore potential correlations of fatal system events for one of the most powerful supercomputers—IBM Blue Gene/Q Mira, which is deployed at Argonne National Laboratory, based on its 5-year reliability, availability, and serviceability (RAS) log. Our contribution is two-fold. (1) We design an efficient log analysis tool, namely LogAider, with a novel filtering method to effectively extract fatal events from masses of system messages that are heavily duplicated in the log. LogAider exhibits a very precise detection of temporal-correlation with a high similarity (up to 95 percent) to the ground-truth (i.e., compared to the failure records reported by the administrators). The total number of fatal events can be reduced to about 1,255 compared with originally 2.6 million duplicated fatal messages. (2) We analyze the 5-year RAS log of the MIRA system using LogAider, and summarize six important “takeaways” which can help system vendors and administrators better understand an extreme-scale system's fatal events. Specifically, we find that the distribution or proportion of the fatal system events follow a Pareto-like principle in general. The temporal correlation among fatal events is much stronger than that of warn messages and info messages, and the correlated events tend to constitute a few clusters. The mean time between fatal events (MTBFE) of the Mira system is about 1.3 days from the perspective of the system, and the MTTI is 2–4 days from the perspective of users. The most error-prone item value with respect to any key attribute appears likely in the log every 2–10 days. Weibull, Gamma, and Pearson6 are the three best-fit distributions for the fatal event intervals. The overall correlation of fatal events on the 5D torus network is not prominent, whereas the small-region locality correlation (e.g., the fatal events inside racks) is relatively strong. We believe our work will be interesting to large-scale HPC system administrators and vendors and to fault tolerance researchers, enabling them to better understand fatal events and mitigate such events accordingly.

Integrated reliability and maintainability analysis of Computerized Numerical Control Turning Center considering the effects of human and organizational factors

Purpose Reliability, maintainability and availability of modern complex engineered systems are significantly affected by four basic systems or elements: hardware, software, organizational and human. Computerized Numerical Control Turning Center (CNCTC) is one of the complex machine tools used in manufacturing industries. Several research studies have shown that the reliability and maintainability is greatly influenced by human and organizational factors (HOFs). The purpose of this paper is to identify critical HOFs and their effects on the reliability and maintainability of the CNCTC. Design/methodology/approach In this paper, 12 human performance influencing factors (PIFs) and 10 organizational factors (OFs) which affect the reliability and maintainability of the CNCTC are identified and prioritized according to their criticality. The opinions of experts in the fields are used for prioritizing, whereas the field failure and repair data are used for reliability and maintainability modeling. Findings Experience, training, and behavior are the three most critical human PIFs, and safety culture, problem solving resources, corrective action program and training program are the four most critical OFs which significantly affect the reliability and maintainability of the CNCTC. The reliability and maintainability analysis reveals that the Weibull is the best-fit distribution for time-between-failure data, whereas log-normal is the best-fit distribution for Time-To-Repair data. The failure rate of the CNCTC is nearly constant. Nearly 66 percent of the total failures and repairs are typically due to the hardware system. The percentage of failures and repairs influenced by HOFs is nearly only 16 percent; however, the failure and repair impact of HOFs is significant. The HOFs can increase the mean-time-to-repair and mean-time-between-failure of the CNCTC by nearly 65 and 33 percent, respectively. Originality/value The paper uses the field failure data and expert opinions for the analysis. The critical sub-systems of the CNCTC are identified using the judgment of the experts, and the trend of the results is verified with published results.

Regional Flood Frequency Analysis of the Pannonian Basin

In this paper, we performed Regional Flood Frequency Analysis (RFFA) by using L-moments and Annual Maximum Series (AMS) methods. Time series of volumes and duration of floods were derived using the threshold level method for 22 hydrological stations in the Pannonian Basin. For flood definition, a threshold set at Q10 was used. The aim of this research is to derive best-fit regional distribution for the four major rivers within the Pannonian Basin and to provide reliable prediction of flood quantiles. The results show that the investigated area can be considered homogeneous (Vi < 1) both for flood volumes (0.097) and durations (0.074). To determine the best-fit regional distribution, the six most commonly used distributions were used. Results obtained by L-moment ratio diagram and Z statistics show that all distributions satisfy the test criteria, but because the Log-Normal distribution has the value closest to zero, it can be selected as the best-fit distribution for the volumes (0.12) and durations (0.25) of floods.

Flood Frequency Analysis Using L Moments: a Comparison between At-Site and Regional Approach

Regional flood frequency analysis has been carried out for estimating peak discharge at regional level over the Kerala State, India, along with at-site flood frequency analysis. For the study, the annual peak discharges of 43 gauging stations having length of data from 14 to 47 years spread over the Kerala State were used. Using L moments and L moment ratio, best fit distribution was identified among the five distributions; Generalised Extreme Value (GEV), Generalised Pareto Distribution (GPA), Generalised Logistic (GLO), Generalised Normal (LN3) and Pearson Type III (PE3) distribution for both at-site and regional flood frequency analysis. Chi-square test, ranking method using statistical indicators and L moment ratio diagram were used for identifying the best fit distribution for at-site flood frequency analysis. It was found that GPA was the best fit distribution for 27 stations, GLO for 14, LN3 for 1 station and GEV for 2 station. After discordancy test, five different homogeneous regions were identified through heterogeneity test to carry out the regional flood frequency analysis (RFFA). After identifying best-fit distributions for each zone, flood growth curves were derived by incorporating the catchment characteristics of the basins. The distribution that was best fit in case of at-site analysis for a gauging site is found to be entirely different than the best fit distribution resulted from RFFA. In RFFA, growth curves that provide the flood magnitude for various return periods can be used to estimate the flood magnitude and frequency at ungauged sites in each region of the Kerala State in India.

Exploring the Effects of Traffic Density on Merging Behavior

In this paper, a comprehensive analysis of merging behavior on the freeway under different traffic densities has been conducted. First, the influence of traffic density on merging parameters (namely merging position, merging speed, merging duration, and accepted gap) was analyzed by mathematical statistics, Mann-Whitney-U Test, and distribution fitting. It was found that the merging position, merging speed, merging duration, and accepted gap are all significantly influenced by traffic density and the best-fitted distributions of merging parameters could be different under different traffic densities. Then, to incorporate the dynamic effects of traffic density on merging behavior, a cell-based traffic density was introduced in this paper and logistic regression was used to model the gap selection behavior. The results showed that traffic density has a significant influence on gap selection behavior during the merging process. The effects of traffic density in logistic regression showed that merging drivers tend to choose a location with lower traffic density during the gap selection process. Moreover, introducing the cell-based traffic density can also improve the predictive accuracy of the logistic regression model.

Gender productivity gap among star performers in STEM and other scientific fields.

We examined the gender productivity gap in science, technology, engineering, mathematics, and other scientific fields (i.e., applied psychology, mathematical psychology), specifically among star performers. Study 1 included 3,853 researchers who published 3,161 articles in mathematics. Study 2 included 45,007 researchers who published 7,746 articles in genetics. Study 3 included 4,081 researchers who published 2,807 articles in applied psychology and 6,337 researchers who published 3,796 articles in mathematical psychology. Results showed that (a) the power law with exponential cutoff is the best-fitting distribution of research productivity across fields and gender groups and (b) there is a considerable gender productivity gap among stars in favor of men across fields. Specifically, the underrepresentation of women is more extreme as we consider more elite ranges of performance (i.e., top 10%, 5%, and 1% of performers). Conceptually, results suggest that individuals vary in research productivity predominantly because of the generative mechanism of incremental differentiation, which is the mechanism that produces power laws with exponential cutoffs. Also, results suggest that incremental differentiation occurs to a greater degree among men and certain forms of discrimination may disproportionately constrain women's output increments. Practically, results suggest that women may have to accumulate more scientific knowledge, resources, and social capital to achieve the same level of increase in total outputs as their male counterparts. Finally, we offer recommendations on interventions aimed at reducing constraints for incremental differentiation among women that could be useful for narrowing the gender productivity gap specifically among star performers. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Mass and Light of Abell 370: A Strong and Weak Lensing Analysis

Abstract We present a new gravitational lens model of the Hubble Frontier Fields cluster Abell 370 (z = 0.375) using imaging and spectroscopy from Hubble Space Telescope and ground-based spectroscopy. We combine constraints from a catalog of 909 weakly lensed galaxies and 39 multiply imaged sources comprised of 114 multiple images, including a system of multiply imaged candidates at z = 7.84 ± 0.02, to obtain a best-fit mass distribution using the cluster lens modeling code Strong and Weak Lensing United. As the only analysis of A370 using strong and weak lensing constraints from Hubble Frontier Fields data, our method provides an independent check of assumptions on the mass distribution used in other methods. Convergence, shear, and magnification maps are made publicly available through the HFF website (http://www.stsci.edu/hst/campaigns/frontier-fields). We find that the model we produce is similar to models produced by other groups, with some exceptions due to the differences in lensing code methodology. In an effort to study how our total projected mass distribution traces light, we measure the stellar mass density distribution using Spitzer/Infrared Array Camera imaging. Comparing our total mass density to our stellar mass density in a radius of 0.3 Mpc, we find a mean projected stellar to total mass ratio of (stat.) using the diet Salpeter initial mass function. This value is in general agreement with independent measurements of in clusters of similar total mass and redshift.

Evaluation of Various Probability Distributions for Deriving Design Flood Featuring Right-Tail Events in Pakistan

Design flood estimation is very important for hydraulic structure design, reservoir operation, and water resources management. During the last few decades, severe flash floods have caused substantial human, agricultural, and economic damages in Pakistan during the Monsoon seasons. However, despite phenomenal losses, the flood characteristics are rarely investigated. In this paper, flood frequency analysis (FFA) on four major rivers over Pakistan is performed to probe probability distributions (PDs)at the right-tail flood events. For this purpose, (i) we employed ten different probability distributions associating with an L-moments method for constructing FFA models across Pakistan; (ii) we evaluated the best-fit distribution by using goodness-of-fit test and statistical criteria; and finally; (iii) we devised a Monte Carlo simulation to systematically evaluate the robustness of a selected distribution’s fitting performance by using a synthetic data series of different sizes. Our results indicated that generalized Pareto and Weibull emerged as the most viable options for quantifying hydrological quantiles for most of the river basins in Pakistan. Our main findings would provide rich information as references for flood risk assessment and water resource management in Pakistan.