Limited Occurrence of Denitrification in Four Shallow Aquifers in Agricultural Areas of the United States

The ability of natural attenuation to mitigate agricultural nitrate contamination in recharging aquifers was investigated in four important agricultural settings in the United States. The study used laboratory analyses, field measurements, and flow and transport modeling for monitoring well transects (0.5 to 2.5 km in length) in the San Joaquin watershed, California, the Elkhorn watershed, Nebraska, the Yakima watershed, Washington, and the Chester watershed, Maryland. Ground water analyses included major ion chemistry, dissolved gases, nitrogen and oxygen stable isotopes, and estimates of recharge date. Sediment analyses included potential electron donors and stable nitrogen and carbon isotopes. Within each site and among aquifer-based medians, dissolved oxygen decreases with ground water age, and excess N2 from denitrification increases with age. Stable isotopes and excess N2 imply minimal denitrifying activity at the Maryland and Washington sites, partial denitrification at the California site, and total denitrification across portions of the Nebraska site. At all sites, recharging electron donor concentrations are not sufficient to account for the losses of dissolved oxygen and nitrate, implying that relict, solid phase electron donors drive redox reactions. Zero-order rates of denitrification range from 0 to 0.14 μmol N L−1d−1, comparable to observations of other studies using the same methods. Many values reported in the literature are, however, orders of magnitude higher, which is attributed to a combination of method limitations and bias for selection of sites with rapid denitrification. In the shallow aquifers below these agricultural fields, denitrification is limited in extent and will require residence times of decades or longer to mitigate modern nitrate contamination

Subsequent Surgery After Revision Anterior Cruciate Ligament Reconstruction: Rates and Risk Factors From a Multicenter Cohort

BACKGROUND: While revision anterior cruciate ligament reconstruction (ACLR) can be performed to restore knee stability and improve patient activity levels, outcomes after this surgery are reported to be inferior to those after primary ACLR. Further reoperations after revision ACLR can have an even more profound effect on patient satisfaction and outcomes. However, there is a current lack of information regarding the rate and risk factors for subsequent surgery after revision ACLR. PURPOSE: To report the rate of reoperations, procedures performed, and risk factors for a reoperation 2 years after revision ACLR. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: A total of 1205 patients who underwent revision ACLR were enrolled in the Multicenter ACL Revision Study (MARS) between 2006 and 2011, composing the prospective cohort. Two-year questionnaire follow-up was obtained for 989 patients (82%), while telephone follow-up was obtained for 1112 patients (92%). If a patient reported having undergone subsequent surgery, operative reports detailing the subsequent procedure(s) were obtained and categorized. Multivariate regression analysis was performed to determine independent risk factors for a reoperation. RESULTS: Of the 1112 patients included in the analysis, 122 patients (11%) underwent a total of 172 subsequent procedures on the ipsilateral knee at 2-year follow-up. Of the reoperations, 27% were meniscal procedures (69% meniscectomy, 26% repair), 19% were subsequent revision ACLR, 17% were cartilage procedures (61% chondroplasty, 17% microfracture, 13% mosaicplasty), 11% were hardware removal, and 9% were procedures for arthrofibrosis. Multivariate analysis revealed that patients aged <20 years had twice the odds of patients aged 20 to 29 years to undergo a reoperation. The use of an allograft at the time of revision ACLR (odds ratio [OR], 1.79; P = .007) was a significant predictor for reoperations at 2 years, while staged revision (bone grafting of tunnels before revision ACLR) (OR, 1.93; P = .052) did not reach significance. Patients with grade 4 cartilage damage seen during revision ACLR were 78% less likely to undergo subsequent operations within 2 years. Sex, body mass index, smoking history, Marx activity score, technique for femoral tunnel placement, and meniscal tearing or meniscal treatment at the time of revision ACLR showed no significant effect on the reoperation rate. CONCLUSION: There was a significant reoperation rate after revision ACLR at 2 years (11%), with meniscal procedures most commonly involved. Independent risk factors for subsequent surgery on the ipsilateral knee included age <20 years and the use of allograft tissue at the time of revision ACLR

An Analysis of the Run Sum Control Chart

The run sum control chart is a simple but powerful procedure for monitoring the mean of a process. We analyze the run length distribution of the run sum chart using a Markov chain approach. Procedures for evaluating average run lengths for one-time shifts and linear trends in the process mean are given. Comparisons are made with the Shewhart control chart supplemented with runs rules, as well as with the cumulative sum and exponentially weighted moving average control charts. The properties of the run sum\u27s run length distribution indicate that the run sum control chart is better than the Shewhart X̄ chart with supplementary runs rules. By adding more regions and scores, the run sum chart can be made more competitive with the cumulative sum and the exponentially weighted moving average control charts in detecting out-of-control conditions. We conclude that the run sum control chart is a simple and powerful tool for statistical process control

Poisson EWMA Control Charts

An exponentially weighted moving average control chart for monitoring Poisson data is introduced. The charting procedure is evaluated using a Markov chain approximation, and its average run length is compared to other procedures for Poisson data. Figures are given for the user to select the value of the upper control limit that gives the desired in-control average run length

Derivation of Integral Equations Useful in the Performance Evaluation of Various Control Charts

This paper was published in the Proceedings of the Quality and Productivity Section of the American Statistical Association

Attribute Charts for Monitoring a Dependent Process

For some repetitive production processes, the quality measure taken on the output is an attribute variable. An attribute variable classifies each output item into one of a countable set of categories. One of the simplest and most commonly used attribute variables is the one which classifies an item as either ‘conforming’ or ‘non-conforming’. A tool used with a considerable amount of success in industry for monitoring the quality of a production process is the quality control chart. Generally a control charting procedure uses a sequence, of the quality measures to make a decision about the quality of the process. How this sequence is used to make a decision defines the control chart. In order to design a control chart one must consider how the underlying sequence, is modeled. The sequence is often modeled as a sequence of independent and identically distributed random variables. For many industrial processes, this model is appropriate, but in others it may not be. In this paper, a sequence of random variables, is used to classify an item as conforming or non-conforming under a stationary Markov chain model and under 100% sequential sampling. Two different control charting schemes are investigated. Both schemes plot a sequence of measures on the control chart, that count the number of conforming items before a non-conforming item. The first scheme signals as out-of-control if a value of falls below a certain lower limit. The second scheme signals as out-of-control if two out of two values of fall below a certain lower limit. The efficiency of both of the control charts is evaluated by the average run length (ARL) of the chart and the power of the chart to detect a shift in the process. The two out of two scheme is shown to have high power and a large ARL given certain parameter values of the process. An example of the two out of two scheme is provided for the interested reader

An Analysis of Shewhart Charts with Runs Rules When No Standards Are Given

This paper was published in the Proceedings of the Quality and Productivity Section of the American Statistical Association

A CUSUM Quality Control Chart Under 100% Sampling

This paper was published in the Proceedings of the Third Industrial Engineering Research Conference

Method for Deriving Integral Equations Useful in Control Chart Performance Analysis

Various charting procedures have been recommended for use in monitoring one or more quality characteristics of a repetitive production process. The performance of these charts is often assessed by looking at one or more parameters of the run length distribution. For some charts an integral equation approach can be used to determine the run length parameters. A method is illustrated for deriving these integral equations which include some well known as well as some lesser known integral equations