A Dual Electrode Biosensor for Glucose and Lactate Measurement in Normal and Prolonged Obese Mice Using Single Drop of Whole Blood

Understanding the levels of glucose (G) and lactate (L) in blood can help us regulate various chronic health conditions such as obesity. In this paper, we introduced an enzyme-based electrochemical biosensor adopting glucose oxidase and lactate oxidase on two working screen-printed carbon electrodes (SPCEs) to sequentially determine glucose and lactate concentrations in a single drop (~30 µL) of whole blood. We developed a diet-induced obesity (DIO) mouse model for 28 weeks and monitored the changes in blood glucose and lactate levels. A linear calibration curve for glucose and lactate concentrations in ranges from 0.5 to 35 mM and 0.5 to 25 mM was obtained with R-values of 0.99 and 0.97, respectively. A drastic increase in blood glucose and a small but significant increase in blood lactate were seen only in prolonged obese cases. The ratio of lactate concentration to glucose concentration (L/G) was calculated as the mouse’s gained weight. The results demonstrated that an L/G value of 0.59 could be used as a criterion to differentiate between normal and obesity conditions. With L/G and weight gain, we constructed a diagnostic plot that could categorize normal and obese health conditions into four different zones. The proposed dual electrode biosensor for glucose and lactate in mouse whole blood showed good stability, selectivity, sensitivity, and efficiency. Thus, we believe that this dual electrode biosensor and the diagnostic plot could be used as a sensitive analytical tool for diagnosing glucose and lactate biomarkers in clinics and for monitoring obesity.

New Insights on Characteristics of the Near-Wellbore Fractured Zone from Simulated High-Resolution Distributed Strain Sensing Data

Summary Rayleigh frequency-shift-based distributed strain sensing (RFS-based DSS) is a fiber-optic-based diagnostic technique, which can measure the strain change along the fiber. The spatial resolution of RFS-based DSS can be as low as 0.2 m, and the measuring sensitivity is less than 1 μɛ. Jin et al. (2021) presented a set of DSS data from the Hydraulic Fracture Test Site 2 project to demonstrate its potential to characterize near-wellbore fracture properties and to evaluate perforation efficiency during production and shut-in periods. Extensional strain changes are observed at locations around perforations during a shut-in period. At each perforation cluster, the observed responses of strain changes are significantly different. However, the driving mechanisms for the various observations are not clear, which hinders accurate interpretations of DSS data for near-wellbore fracture characterization. In this study, we applied a coupled flow and geomechanics model to simulate the observed DSS signals under various fractured reservoir conditions. The objective is to improve understanding of the DSS measurements and characterize near-wellbore fracture geometry. We used our in-house coupled flow and geomechanics simulator, which is developed by a combined finite-volume and finite-element method, to simulate strain responses within and near a fracture during shut-in and reopen periods. Local grid refinement was adopted around fractures and the wellbore, so that the simulated strain data can accurately represent the DSS measurements. The plane-strain condition is assumed. Numerical models with various fracture geometries and properties were constructed with representative parameters and in-situ conditions of the Permian Basin. The simulated well was shut-in for 4 days after producing 240 days, and reopened again for 1 day, following the actual field operation as shown in Jin et al. (2021). The characters of the strain changes along the fiber were analyzed and related to near-wellbore fracture properties. A novel diagnostic plot of relative strain change vs. wellbore pressure was presented to infer near-wellbore fracture characteristics. The impacts of permeability and size of the near-wellbore-stimulated region, fracture length, and near-perforation damage zone on strain responses were investigated through sensitivity analysis. The strain responses simulated by our model capture the observed signatures of field DSS measurements. During the shut-in period, clear positive strain changes are observed around the perforation locations, forming a “hump” signature. The shape of the “hump” region and peak value of each “hump” are dependent on the size and permeability of the near-wellbore fractured zone. Once the well is reopened, the strain changes decrease as the pressure drops. However, in one cycle of shut-in and reopen, the strain-pressure diagnostic plot shows path dependency. The discrepancy between the shut-in and reopen periods is highly influenced by the properties of near-wellbore fractured zones. The differences in the strain-pressure diagnostic plots can help to identify the conductive fractures. This study provides better understandings of the DSS measurements and their relations to the near-wellbore fracture properties, which is of practical importance for near-wellbore fracture characterization and completion/stimulation optimization.

An Improvised SIMPLS Estimator Based on MRCD-PCA Weighting Function and Its Application to Real Data

Multicollinearity often occurs when two or more predictor variables are correlated, especially for high dimensional data (HDD) where p>>n. The statistically inspired modification of the partial least squares (SIMPLS) is a very popular technique for solving a partial least squares regression problem due to its efficiency, speed, and ease of understanding. The execution of SIMPLS is based on the empirical covariance matrix of explanatory variables and response variables. Nevertheless, SIMPLS is very easily affected by outliers. In order to rectify this problem, a robust iteratively reweighted SIMPLS (RWSIMPLS) is introduced. Nonetheless, it is still not very efficient as the algorithm of RWSIMPLS is based on a weighting function that does not specify any method of identification of high leverage points (HLPs), i.e., outlying observations in the X-direction. HLPs have the most detrimental effect on the computed values of various estimates, which results in misleading conclusions about the fitted regression model. Hence, their effects need to be reduced by assigning smaller weights to them. As a solution to this problem, we propose an improvised SIMPLS based on a new weight function obtained from the MRCD-PCA diagnostic method of the identification of HLPs for HDD and name this method MRCD-PCA-RWSIMPLS. A new MRCD-PCA-RWSIMPLS diagnostic plot is also established for classifying observations into four data points, i.e., regular observations, vertical outliers, and good and bad leverage points. The numerical examples and Monte Carlo simulations signify that MRCD-PCA-RWSIMPLS offers substantial improvements over SIMPLS and RWSIMPLS. The proposed diagnostic plot is able to classify observations into correct groups. On the contrary, SIMPLS and RWSIMPLS plots fail to correctly classify observations into correct groups and show masking and swamping effects.

On the Generalized S−X2–Test of Item Fit: Some Variants, Residuals, and a Graphical Visualization

The generalized [Formula: see text]–test is a test of item fit for items with polytomous responses format. The test is based on a comparison of the observed and expected number of responses in strata defined by the test score. In this article, we make four contributions. We demonstrate that the performance of the generalized [Formula: see text]–test depends on how sparse cells are pooled. We propose alternative implementations of the test within the framework of limited information testing. We derive the distribution of the [Formula: see text]–residuals that can be used for post hoc analyses. We suggest a diagnostic plot that visualizes the form of the misfit. The performance of the alternative implementations is investigated in a simulation study. The simulation study suggests that the alternative implementations are capable of controlling the Type-I error rate well and have high power. An empirical application concludes this article.

Diagnostic Plots of Pressure Transient, Rate-Transient, and Diagnostic Fracture-Injection/Falloff Tests

All transient test interpretation methods rely on or utilize diagnostic plots for the identification of wellbore or fracture storage distortion, flow regimes, and other parameters (e.g., minimum horizontal stress). Although all "test" interpretations of interest are transient test data (i.e., those involving an "event"), the associated diagnostic plots are not interchangeable between such tests. The objective of this work is to clearly define the appropriate diagnostic plot(s) for each type of transient test. The work applies the appropriate transient test theory to demonstrate the applicability of each diagnostic plot along with clearly defining the characteristic features that make a given plot "diagnostic." For pressure transient testing, the material is largely a review, but for rate transient tests and diagnostic fracture-injection/falloff tests, new ideas are introduced and documented to justify appropriate diagnostic plots. Data examples are provided for illustration and application. In general, pressure transient test diagnostic plots are not misused, but the same cannot be said for diagnostic fracture-injection/falloff tests (or DFITs) where it is common to ascribe flow regimes and/or draw other erroneous conclusions based on observations from an inappropriately constructed or interpretated diagnostic plot. The examples provided illustrate both the correct diagnostic plot and interpretations, but also illustrate how data can be easily misinterpreted in common practice.

A Graphical Tool For Assessing The Suitabilty Of A Count Regression Model

Whilst many numeric methods, such as AIC and deviance, exist for assessing or comparing model fit, diagrammatic methods are few. We present here a diagnostic plot, which we refer to as a `Quantile Band plot', that may be used to visually assess the suitability of a given count data model. In the case of diagnosed model inadequacy, the plot has the unique feature of conveying precise information on the character of the violation, hence pointing the data analyst towards a potentially better model choice.

Production Data Analysis and Sonolog for Determining Artificial Lift Design and Well Characteristic

Tarakan Field, North Kalimantan is a part of PT. Pertamina EP Asset 5. The Tarakan Field has 5 structures in the form of Pamusian, Juata, Sesanip, Mangatal, and Sembakung. The Tarakan Field has 57 production wells and 6 injection wells. The wells at Tarakan field are produced with artificial lifts in the form of Sucker Rod Pump (SRP) totaling 25, Hydraulic Pumping Unit (HPU) totaling 11, Electric Submersible Pump (ESP) totaling 19 and Progressive Cavity Pump (PCP) totaling 2. The determination of artificial lifts is carried out by the design of well characteristics and production history. The design at Tarakan Field was carried out with an artificial lift in the form of ESP (Electric Submersible Pump). ESP is used according to reservoir and formation characteristics in Tarakan Field. Water Control Diagnostic Plot is a method used to analyze the effect of control on produced water. Water Control Diagnostic plot is plot between WOR and WOR derivative vs time. The plot was carried out on a log-log scale. The plot on the Water Control Diagnostic Plot is then analyzed against the graph created by the KS Chan. So from the analyzed plot, it is found whether or not there is a problem in the well at Tarakan Field. The results of the graph analysis on the well at Tarakan Field on the chart show that the field does not indicate a problem. Keywords: chan plot; design; esp; production