Domain Adaptation via Alignment of Operation Profile for Remaining Useful Lifetime Prediction

Effective Prognostics and Health Management (PHM) relies on accurate prediction of the Remaining Useful Life (RUL). Data-driven RUL prediction techniques rely heavily on the representativeness of the available time-to-failure trajectories. Therefore, these methods may not perform well when applied to data from new units of a fleet that follow different operating conditions than those they were trained on. This is also known as domain shifts. Domain adaptation (DA) methods aim to address the domain shift problem by extracting domain invariant features. However, DA methods do not distinguish between the different phases of operation, such as steady states or transient phases. This can result in misalignment due to under- or over-representation of different operation phases. This paper proposes two novel DA approaches for RUL prediction based on an adversarial domain adaptation framework that considers the different phases of the operation profiles separately. The proposed methodologies align the marginal distributions of each phase of the operation profile in the source domain with its counterpart in the target domain. The effectiveness of the proposed methods is evaluated using the New Commercial Modular Aero-Propulsion System (N-CMAPSS) dataset, where sub-fleets of turbofan engines operating in one of the three different flight classes (short, medium, and long) are treated as separate domains. The experimental results show that the proposed methods improve the accuracy of RUL predictions compared to current state-of-the-art DA methods.Comment: 18 pages,11 figure

Working mechanism of a multidimensional computerized adaptive test for fatigue in rheumatoid arthritis

Background This paper demonstrates the mechanism of a multidimensional computerized adaptive test (CAT) to measure fatigue in patients with rheumatoid arthritis (RA). A CAT can be used to precisely measure patient-reported outcomes at an individual level as items are consequentially selected based on the patient’s previous answers. The item bank of the CAT Fatigue RA has been developed from the patients’ perspective and consists of 196 items pertaining to three fatigue dimensions: severity, impact and variability of fatigue. Methods The CAT Fatigue RA was completed by fifteen patients. To test the CAT’s working mechanism, we applied the flowchart-check-method. The adaptive item selection procedure for each patient was checked by the researchers. The estimated fatigue levels and the measurement precision per dimension were illustrated with the selected items, answers and flowcharts. Results The CAT Fatigue RA selected all items in a logical sequence and those items were selected which provided the most information about the patient’s individual fatigue. Flowcharts further illustrated that the CAT reached a satisfactory measurement precision, with less than 20 items, on the dimensions severity and impact and to somewhat lesser extent also for the dimension variability. Patients’ fatigue scores varied across the three dimensions; sometimes severity scored highest, other times impact or variability. The CAT’s ability to display different fatigue experiences can improve communication in daily clinical practice, guide interventions, and facilitate research into possible predictors of fatigue. Conclusions The results indicate that the CAT Fatigue RA measures precise and comprehensive. Once it is examined in more detail in a consecutive, elaborate validation study, the CAT will be available for implementation in daily clinical practice and for research purpose

Technical Language Supervision for Intelligent Fault Diagnosis in Process Industry

In the process industry, condition monitoring systems with automated fault diagnosis methods assist human experts and thereby improve maintenance efficiency, process sustainability, and workplace safety. Improving the automated fault diagnosis methods using data and machine learning-based models is a central aspect of intelligent fault diagnosis (IFD). A major challenge in IFD is to develop realistic datasets with accurate labels needed to train and validate models, and to transfer models trained with labeled lab data to heterogeneous process industry environments. However, fault descriptions and work-orders written by domain experts are increasingly digitised in modern condition monitoring systems, for example in the context of rotating equipment monitoring. Thus, domain-specific knowledge about fault characteristics and severities exists as technical language annotations in industrial datasets. Furthermore, recent advances in natural language processing enable weakly supervised model optimisation using natural language annotations, most notably in the form of natural language supervision (NLS). This creates a timely opportunity to develop technical language supervision (TLS) solutions for IFD systems grounded in industrial data, for example as a complement to pre-training with lab data to address problems like overfitting and inaccurate out-of-sample generalisation. We surveyed the literature and identify a considerable improvement in the maturity of NLS over the last two years, facilitating applications beyond natural language; a rapid development of weak supervision methods; and transfer learning as a current trend in IFD which can benefit from these developments. Finally we describe a general framework for TLS and implement a TLS case study based on Sentence-BERT and contrastive learning based zero-shot inference on annotated industry data

Construct Validation of a Multidimensional Computerized Adaptive Test for Fatigue in Rheumatoid Arthritis

Objective Multidimensional computerized adaptive testing enables precise measurements of patient-reported outcomes at an individual level across different dimensions. This study examined the construct validity of a multidimensional computerized adaptive test (CAT) for fatigue in rheumatoid arthritis (RA). Methods The ‘CAT Fatigue RA’ was constructed based on a previously calibrated item bank. It contains 196 items and three dimensions: ‘severity’, ‘impact’ and ‘variability’ of fatigue. The CAT was administered to 166 patients with RA. They also completed a traditional, multidimensional fatigue questionnaire (BRAF-MDQ) and the SF-36 in order to examine the CAT’s construct validity. A priori criterion for construct validity was that 75% of the correlations between the CAT dimensions and the subscales of the other questionnaires were as expected. Furthermore, comprehensive use of the item bank, measurement precision and score distribution were investigated. Results The a priori criterion for construct validity was supported for two of the three CAT dimensions (severity and impact but not for variability). For severity and impact, 87% of the correlations with the subscales of the well-established questionnaires were as expected but for variability, 53% of the hypothesised relations were found. Eighty-nine percent of the items were selected between one and 137 times for CAT administrations. Measurement precision was excellent for the severity and impact dimensions, with more than 90% of the CAT administrations reaching a standard error below 0.32. The variability dimension showed good measurement precision with 90% of the CAT administrations reaching a standard error below 0.44. No floor- or ceiling-effects were found for the three dimensions. Conclusion The CAT Fatigue RA showed good construct validity and excellent measurement precision on the dimensions severity and impact. The dimension variability had less ideal measurement characteristics, pointing to the need to recalibrate the CAT item bank with a two-dimensional model, solely consisting of severity and impact

Developing and operating time critical applications in clouds: the state of the art and the SWITCH approach

Cloud environments can provide virtualized, elastic, controllable and high quality on-demand services for supporting complex distributed applications. However, the engineering methods and software tools used for developing, deploying and executing classical time critical applications do not, as yet, account for the programmability and controllability provided by clouds, and so time critical applications cannot yet benefit from the full potential of cloud technology. This paper reviews the state of the art of technologies involved in developing time critical cloud applications, and presents the approach of a recently funded EU H2020 project: the Software Workbench for Interactive, Time Critical and Highly self-adaptive cloud applications (SWITCH). SWITCH aims to improve the existing development and execution model of time critical applications by introducing a novel conceptual model—the application-infrastructure co-programming and control model—in which application QoS and QoE, together with the programmability and controllability of cloud environments, is included in the complete application lifecycle

The impact of different volumetric thresholds to determine progressive disease in patients with recurrent glioblastoma treated with bevacizumab

Background: The optimal volumetric threshold for determining progressive disease (PD) in recurrent glioblastoma is yet to be determined. We investigated a range of thresholds in association with overall survival (OS). Methods: First recurrent glioblastoma patients treated with bevacizumab and/or lomustine were included from the phase II BELOB and phase III EORTC26101 trials. Enhancing and nonenhancing tumor volumes were measured at baseline, first (6 weeks), and second (12 weeks) follow-up. Hazard ratios (HRs) for the appearance of new lesions and several thresholds for tumor volume increase were calculated using cox regression analysis. Results were corrected in a multivariate analysis for well-established prognostic factors. Results: At first and second follow-up, 138 and 94 patients respectively, were deemed eligible for analysis of enhancing volumes, while 89 patients were included in the analysis of nonenhancing volumes at first follow-up. New lesions were associated with a significantly worse OS (3.2 versus 11.2 months, HR = 7.03, P <. 001). At first follow-up a threshold of enhancing volume increase of ≥20% provided the highest HR (5.55, p =. 001. At second follow-up, any increase in enhancing volume (≥0%) provided the highest HR (9.00, p <. 001). When measuring nonenhancing volume at first follow-up, only 6 additional patients were scored as PD with the highest HR of ≥25% increase in volume (HR=3.25, p =. 008). Conclusion: Early appearing new lesions were associated with poor OS. Lowering the volumetric threshold for PD at both first and second follow-up improved survival prediction. However, the additional number of patients categorized as PD by lowering the threshold was very low. The per-RANO added change in nonenhancing volumes to the analyses was of limited value

Eficacia de dexketoprofeno versus tramadol como analgesia preventiva en Anestesia General Balanceada

El dolor postoperatorio los pacientes lo aceptaban como una experiencia desagradable e inevitable, uno de los peor tratados, el control del mismo es primordial para los pacientes sometidos a cirugías abdominales. Su principio es simple y consiste en administrar un analgésico preoperatoriamente antes de la incisión quirúrgica ya que puede prevenir o reducir la hipersensibilidad de las neuronas del asta dorsal para reducir o eliminar el dolor subsiguiente. Este mal control del dolor post operatorio está asociado a una variedad de consecuencias negativas, que incluyen alteraciones cardíacas e incremento del riesgo de isquemia o infarto al miocardio, complicaciones tromboembólicas y pulmonares, alteraciones inmunes, deprivación del sueño y trastornos psicológicos como ansiedad y depresión, incrementa el riesgo de dolor postoperatorio persistente, necesidad de rehabilitación, incrementa la estancia hospitalaria o reingreso y disminuye la calidad de vida de quien la padec

Validation of PROMIS Profile-29 in adults with hemophilia in the Netherlands

Background The Patient-Reported Outcomes Measurement Information System (PROMIS) Profile-29 questionnaire is widely used worldwide, but it has not yet been validated in the Netherlands, nor in persons with hemophilia. Objective To validate the Dutch-Flemish version of the PROMIS-29 Profile v2.01 in adults with hemophilia. Methods Dutch males with hemophilia (all severities) completed questionnaires that contained sociodemographic and clinical characteristics, the PROMIS-29, RAND-36, and the Hemophilia Activities List (HAL). Structural validity of each subscale was assessed with confirmatory factor analysis (CFA). Internal consistency was calculated for each subscale with sufficient model fit in CFA. Construct validity was assessed by testing hypotheses about (1) correlations of each PROMIS-29 subscale with corresponding scales of RAND-36 and domains of HAL, and (2) mean differences in T-scores between subgroups with different hemophilia severities, self-reported joint impairment, and HIV infection status. We considered &gt;= 75% of data in accordance with the hypotheses evidence for construct validity. Results In total, 770 persons with hemophilia participated in this cross-sectional study. CFA revealed sufficient structural validity for five subscales: Physical Function, Depression, Sleep Disturbance, Ability to Participate in Social Roles and Activities, and Pain Interference. Internal consistency was high and Cronbach's alpha ranged from 0.79 for Sleep Disturbance to 0.96 for Pain Interference. Differences between clinical subgroups were in the expected direction. Construct validity was confirmed for Physical Function, Anxiety, Depression, Fatigue, Sleep Disturbance, and Pain Intensity. Conclusion This study revealed sufficient evidence for structural validity, internal consistency, and construct validity for most PROMIS Profile-29 subscales among people with hemophilia in the Netherlands.</p

Application of the health assessment questionnaire disability index to various rheumatic diseases

Purpose\ud \ud To investigate whether the Stanford Health Assessment Questionnaire Disability Index (HAQ-DI) can serve as a generic instrument for measuring disability across different rheumatic diseases and to propose a scoring method based on item response theory (IRT) modeling to support this goal.\ud \ud Methods\ud \ud The HAQ-DI was administered to a cross-sectional sample of patients with confirmed rheumatoid arthritis (n = 619), osteoarthritis (n = 125), or gout (n = 102). The results were analyzed using the generalized partial credit model as an IRT model.\ud \ud Results\ud \ud It was found that 4 out of 8 item categories of the HAQ-DI displayed substantial differential item functioning (DIF) over the three diseases. Further, it was shown that this DIF could be modeled using an IRT model with disease-specific item parameters, which produces measures that are comparable for the three diseases.\ud \ud Conclusion\ud \ud Although the HAQ-DI partially functioned differently in the three disease groups, the measurement regarding the disability level of the patients can be made comparable using IRT methods\u