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Core and peripheral body temperatures are affected by changes in reproductive hormones during the menstrual cycle. Women worldwide use the basal body temperature (BBT) method to aid and prevent conception. However, prior research suggests that taking one’s daily temperature can prove inconvenient and subject to environmental factors. We investigate whether a more automatic, non-invasive temperature measurement system can detect changes in temperature across the menstrual cycle. We examined how wrist skin temperature (WST), measured with wearable sensors, correlates with urinary tests of ovulation and may serve as a new method of fertility tracking. One hundred and thirty-six eumenorrheic, non-pregnant women participated in an observational study. Participants wore WST biosensors during sleep and reported their daily activities. An at-home luteinizing hormone (LH) test was used to confirm ovulation. WST was recorded across 437 cycles (mean cycles/participant = 3.21, S.D. = 2.25). We tested the relationship between the fertile window and WST temperature shifts, using the BBT three-over-six rule. A sustained 3-day temperature shift was observed in 357/437 cycles (82%), with the lowest cycle temperature occurring in the fertile window 41% of the time. Most temporal shifts (307/357, 86%) occurred on ovulation day (OV) or later. The average early-luteal phase temperature was 0.33°C higher than in the fertile window. Menstrual cycle changes in WST were impervious to lifestyle factors, like having sex, alcohol, or eating prior to bed, that, in prior work, have been shown to obfuscate BBT readings. Although currently costlier than BBT, the present study suggests that WST could be a promising, convenient parameter for future multiparameter fertility awareness methods.

An affordable, user-friendly fertility-monitoring tool remains an unmet need. We examine in this study the correlation between pulse rate (PR) and the menstrual phases using wrist-worn PR sensors. 91 healthy, non-pregnant women, between 22–42 years old, were recruited for a prospective-observational clinical trial. Participants measured PR during sleep using wrist-worn bracelets with photoplethysmographic sensors. Ovulation day was estimated with “Clearblue Digital-Ovulation-urine test”. Potential behavioral and nutritional confounders were collected daily. 274 ovulatory cycles were recorded from 91 eligible women, with a mean cycle length of 27.3 days (±2.7). We observed a significant increase in PR during the fertile window compared to the menstrual phase (2.1 beat-per-minute, p

Magnetic resonance imaging (MRI) was used for non-destructive characterization of the pore structure of starch-based extruded products. The samples were obtained by extrusion cooking of corn meal in a twin screw extruder. The samples were extruded at varying mechanical energy input and, subsequently, the pore size distributions were analyzed. Two different sample preparation methods were introduced and discussed. Negative imaging was the favorable technique. In this method, the pores are filled with cyclohexane and the solvent is detected by MRI. The analysis method was validated by glass beads of known size as reference samples. The pore sizes detected by MRI were slightly higher than the real size of the glass beads. When extruded corn meal samples were analyzed, we were able to show, that despite an equal expansion index, samples can have different pore size distributions. Finally, the pore size distributions were compared to analysis via X-ray microtomography and advantages and limitations of both methods were discussed.

Background: Impedance spectroscopy has been shown to be a candidate for noninvasive continuous glucose monitoring in humans. However, in addition to glucose, other factors also have effects on impedance characteristics of the skin and underlying tissue. Method: Impedance spectra were summarized through a principal component analysis and relevant variables were identified with Akaike’s information criterion. In order to model blood glucose, a linear least-squares model was used. A Monte Carlo simulation was applied to examine the effects of personalizing models. Results: The principal component analysis was able to identify two major effects in the impedance spectra: a blood glucose-related process and an equilibration process related to moisturization of the skin and underlying tissue. With a global linear least-squares model, a coefficient of determination ( R 2 ) of 0.60 was achieved, whereas the personalized model reached an R 2 of 0.71. The Monte Carlo simulation proved a significant advantage of personalized models over global models. Conclusion: A principal component analysis is useful for extracting glucose-related effects in the impedance spectra of human skin. A linear global model based on Solianis Multisensor data yields a good predictive power for blood glucose estimation. However, a personalized linear model still has greater predictive power.

The paper deals with the numerical investigation and simulation of viscoelastic effects during polymer flooding. A possible pore structure is derived from high-resolution micro-CT images of a typical sandstone suitable for EOR applications. The simulation results achieved will allow for better understanding of micro-scale displacement efficiency and will help to optimize polymer flooding designs for enhanced oil recovery (EOR) projects. Numerical modelling of viscoelastic fluids is notoriously difficult. Standard Galerkin finite element method tends to have numerical oscillations. Therefore, a stabilised finite element method was used in this work, which contains stabilization terms for the constitutive equation. The model was validated using existing literature results. The viscoelasticity effect of polymer was simulated using the Oldroyd-B model. After validation this method was applied to several pore structures (contraction, expansion and expansion-contraction structure) and one real pore geometry based on SEM (Scanning Electron Microscopy). Flow effects and recovery effects were studied by changing the Reynolds number (Re) and Weissenberg number (We). Correspondingly, the streamline plots of the polymer solution flowing through the pore structures are shown. The plot of the first normal stress difference at the re-entrant profile of a contraction structure shows the cause of vortex enhancement. The fluid invades deeper into dead pores with higher elasticity. With a high Reynolds number, the fluid reaches into the dead pore even much deeper. The simulation results indicate the contribution of the viscoelasticity of polymer solutions to the micro-scale sweep efficiency. The non-dimensional model of simplified pore structures will contribute to the selection of suitable rheological parameters for polymer flooding processes.

The human skin consists of several layers with distinct dielectric properties. Resolving the impact of changes in dielectric parameters of skin layers and predicting them allows for non-invasive sensing in medical diagnosis. So far no complete skin and underlying tissue model is available for this purpose in the MHz range. Focusing on this dispersiondominated frequency region multilayer skin models are investigated: First, containing homogeneous non-dispersive sublayers and second, with sublayers obtained from a three-phase Maxwell-Garnett mixture of shelled cell-like ellipsoids. Both models are numerically simulated using the Finite Element Method, a fringing field sensor on the top of the multilayer system serving as a probe. Furthermore, measurements with the sensor probing skin in vivo are performed. In order to validate the models the uppermost skin layer, the stratum corneum was i) included and ii) removed in models and measurements. It is found that only the Maxwell-Garnett mixture model can qualitatively reproduce the measured dispersion which still occurs without the stratum corneum and consequently, structural features of tissue have to be part of the model.