We propose a PCF-based interferometer by the misaligned splicing method. The PCF-based interferometers are composed of a photonic crystal fiber (PCF) and single-mode fibers (SMFs) which are spliced with lateral offsets. As the wave propagates at the first splicing point, the lateral offset will excite the cladding mode and the core mode simultaneously. As the two modes reach the other splicing point, they are recombined and coupled into another SMF. Thus, we can observe the interference pattern resulted from the phase difference between the two modes. In addition, as the length of PCF is increased, the average splicing of the interference fringes become smaller in the same measured range. We demonstrate the applications of the PCF-based interferometer as temperature, bending, and the surrounding refractive index sensors. The temperature sensitivity for the 2-cm and 4-cm PCF-based-interferometer is 3.9.~4.3pm/¢XC and 3.5~4.3pm/¢XC, respectively. As we increase the surrounding refractive index, the curves move toward longer wavelengths. Besides, the measured bending sensitivity of the PCF-based interferometer is 3.8~4.2nm/m-1. We also fabricated the liquid-filled-PCF-based interferometers by using the vacuum filling method. The measured bending sensitivity of the liquid-filled-PCF-based interferometer is 8.5nm/m-1 which is higher than that of the PCF-based interferometer. The measured surrounding refractive index sensitivity is insensitive. Thus, this liquid-filled-PCF-based interferometer can also be utilized as a sensor.

High-Pressure, High-Temperature (HPHT) pressure gauges are commonly used in oil wells for pressure transient analysis. Mathematical models are used to relate input perturbation (e.g., flow rate transients) with output responses (e.g., pressure transients), and subsequently, solve an inverse problem that infers reservoir parameters. The indispensable use of pressure data in well testing motivates continued improvement in the accuracy (quality), sampling rate (quantity), and autonomy (lifetime) of pressure gauges. This body of work presents improvements in three areas of high-pressure, high-temperature quartz memory gauge technology: calibration accuracy, multi-tool signal alignment, and tool autonomy estimation. The discussion introduces the response surface methodology used to calibrate gauges, develops accuracy and autonomy estimates based on controlled tests, and where applicable, relies on field gauge drill stem test data to validate accuracy predictions. Specific contributions of this work include: - Application of the unpaired sample t-test, a first in quartz sensor calibration, which resulted in reduction of uncertainty in gauge metrology by a factor of 2.25, and an improvement in absolute and relative tool accuracies of 33% and 56%, accordingly. Greater accuracy yields more reliable data and a more sensitive characterization of well parameters. - Post-processing of measurements from 2+ tools using a dynamic time warp algorithm that mitigates gauge clock drifts. Where manual alignment methods account only for linear shifts, the dynamic algorithm elastically corrects nonlinear misalignments accumulated throughout a job with an accuracy that is limited only by the clock's time resolution. - Empirical modeling of tool autonomy based on gauge selection, battery pack, sampling mode, and average well temperature. A first of its kind, the model distills autonomy into two independent parameters, each a function of the same two orthogonal factors: battery power capacity and gauge current consumption as functions of sampling mode and well temperature -- a premise that, for 3+ gauge and battery models, reduces the design of future autonomy experiments by at least a factor of 1.5.

Background: Destructive leadership seeks to explain how leaders create harmful outcomes in an organizational setting – and why do they choose to do so. However, as with most leadership theories, process models are designed with a traditional office setting in mind which has its own distinct characteristics. Remote working has surged in prevalence in the last two years due to the COVID-19 pandemic and features multiple key differences, including increased social isolation and a decrease in communication quality. The combination of this novel and different context with a high likelihood of employees experiencing destructive leadership during their career, it is of high relevance to critically examine destructive leadership processes in a remote setting. Purpose: The purpose of this study is to adapt the proposed framework of destructive leadership by Krasikova et al. (2013) in a remote working environment, and to provide a greater understanding of destructive leadership processes in a less familiar context. Through exploring a new working context, this research aims to expand the understanding of destructive leadership, its situational factors, processes, and possible destructive outcomes in the ‘modern’ workplace. Method: Our methods were built on the choices of inductive qualitative research. Ten semi-structured interviews with leaders and followers were conducted by utilizing the casemethod, and more precisely, the case-oriented research design. The use of case-oriented research design and thematic analysis allowed us to engage in within- and cross-case comparisons and enabled us to generate new insights and to further develop remote working specific factors in the destructive leadership processes. Conclusion: The results of the study demonstrate that remote working environment influences three main areas of destructive leadership: the organizational context behind the process of choosing to engage in destructive leadership, the process of discovery and organizational response, and by establishing feedback loops from existing destructive leadership that leads to further resource shortages.