Unmeasured Values Research Articles

Multivariable Mendelian randomization with incomplete measurements on the exposure variables in the Hispanic Community Health Study/Study of Latinos

Multivariable Mendelian randomization allows simultaneous estimation of direct causal effects of multiple exposure variables on an outcome. When the exposure variables of interest are quantitative omic features, obtaining complete data can be economically and technically challenging: the measurement cost is high, and the measurement devices may have inherent detection limits. In this paper, we propose a valid and efficient method to handle unmeasured and undetectable values of the exposure variables in a one-sample multivariable Mendelian randomization analysis with individual-level data. We estimate the direct causal effects with maximum likelihood estimation and develop an expectation-maximization algorithm to compute the estimators. We show the advantages of the proposed method through simulation studies and provide an application to the Hispanic Community Health Study/Study of Latinos, which has a large amount of unmeasured exposure data.

Self-Cleaning Highly Porous TiO2 Coating Designed by Swelling-Assisted Sequential Infiltration Synthesis (SIS) of a Block Copolymer Template.

Photocatalytic self-cleaning coatings with a high surface area are important for a wide range of applications, including optical coatings, solar panels, mirrors, etc. Here, we designed a highly porous TiO2 coating with photoinduced self-cleaning characteristics and very high hydrophilicity. This was achieved using the swelling-assisted sequential infiltration synthesis (SIS) of a block copolymer (BCP) template, which was followed by polymer removal via oxidative thermal annealing. The quartz crystal microbalance (QCM) was employed to optimize the infiltration process by estimating the mass of material infiltrated into the polymer template as a function of the number of SIS cycles. This adopted swelling-assisted SIS approach resulted in a smooth uniform TiO2 film with an interconnected network of pores. The synthesized film exhibited good crystallinity in the anatase phase. The resulting nanoporous TiO2 coatings were tested for their functional characteristics. Exposure to UV irradiation for 1 h induced an improvement in the hydrophilicity of coatings with wetting angle reducing to unmeasurable values upon contact with water droplets. Furthermore, their self-cleaning characteristics were tested by measuring the photocatalytic degradation of methylene blue (MB). The synthesized porous TiO2 nanostructures displayed promising photocatalytic activity, demonstrating the degradation of approximately 92% of MB after 180 min under ultraviolet (UV) light irradiation. Thus, the level of performance was comparable to the photoactivity of commercial anatase TiO2 nanoparticles of the same quantity. Our results highlight a new robust approach for designing hydrophilic self-cleaning coatings with controlled porosity and composition.

A mixed model approach to estimate the survivor average causal effect in cluster-randomized trials.

In many medical studies, the outcome measure (such as quality of life, QOL) for some study participants becomes informatively truncated (censored, missing, or unobserved) due to death or other forms of dropout, creating a nonignorable missing data problem. In such cases, the use of a composite outcome or imputation methods that fill in unmeasurable QOL values for those who died rely on strong and untestable assumptions and may be conceptually unappealing to certain stakeholders when estimating a treatment effect. The survivor average causal effect (SACE) is an alternative causal estimand that surmounts some of these issues. While principal stratification has been applied to estimate the SACE in individually randomized trials, methods for estimating the SACE in cluster-randomized trials are currently limited. To address this gap, we develop a mixed model approach along with an expectation-maximization algorithm to estimate the SACE in cluster-randomized trials. We model the continuous outcome measure with a random intercept to account for intracluster correlations due to cluster-level randomization, and model the principal strata membership both with and without a random intercept. In simulations, we compare the performance of our approaches with an existing fixed-effects approach to illustrate the importance of accounting for clustering in cluster-randomized trials. The methodology is then illustrated using a cluster-randomized trial of telecare and assistive technology on health-related QOL in the elderly.

Mendelian randomization with incomplete measurements on the exposure in the Hispanic Community Health Study/Study of Latinos

Mendelian randomization has been widely used to assess the causal effect of a heritable exposure variable on an outcome of interest, using genetic variants as instrumental variables. In practice, data on the exposure variable can be incomplete due to high cost of measurement and technical limits of detection. In this paper, we propose a valid and efficient method to handle both unmeasured and undetectable values of the exposure variable in one-sample Mendelian randomization analysis with individual-level data. We estimate the causal effect of the exposure variable on the outcome using maximum likelihood estimation and develop an expectation maximization algorithm for the computation of the estimator. Simulation studies show that the proposed method performs well in making inference on the causal effect. We apply our method to the Hispanic Community Health Study/Study of Latinos, a community-based prospective cohort study, and estimate the causal effect of several metabolites on phenotypes of interest.

EPA's Unprecedented Interim Drinking Water Health Advisories for PFOA and PFOS.

Per- and polyfluoroalkyl substances (PFAS) are persistent and widely distributed in the environment from commercial products and waste process residues, including in surface waters usually at low parts per trillion (ppt) levels. Groundwaters near contaminated locations can have higher parts per trillion or parts per billion (ppb) concentrations. Interim EPA Drinking Water Health Advisories (HAs) for perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) that were originally 70 ppt were recently reduced to 0.004 and 0.020 ppt, respectively. Final HAs for perfluorobutane sulfonic acid and its potassium salt (PFBS) and hexafluoropropylene oxide (HFPO) dimer acid and its ammonium salt ("GenX chemicals") were established at 2000 and 10ppt, respectively. The minimum reporting levels (MRLs) for PFOA and PFOS are currently 4ppt. The scientific basis for these very low and unmeasurable HA values for PFOA and PFOS is debatable and up to about five orders of magnitude below many other worldwide national recommendations (e.g., Australia, UK, Canada), which are in the range of 100 ppt and above.

Exhibition Event Evaluation Revisited: An Individual Value Approach

Studies looking at how millions of people attending exhibition events evaluate these events have identified many event characteristics. Using Means–End Chain Theory we categorize them into an overarching inputs–processes–outputs–outcomes model. Focusing on value-in-use as an end outcome, we devise a new measure of non-economic exhibition value using a multimethod set of studies. Study 1 uses qualitative interviews to identify the outcomes attendees value. Study 2 develops a scale for measuring the eight value dimensions, which include new values (e.g., inspirational value), unmeasured values (e.g., self-esteem), and underexplored values (e.g., social vs. relationship value). Study 3 deploys this scale across a series of exhibitions to predict 43%–61% of event satisfaction, loyalty, and word of mouth. The new model adds conceptual clarity to exhibition characteristics, and the new scale enhances the accountability and importance of exhibitions.

Diagnostic Performance Evaluation of the Novel Index Combining Urinary Cotinine and 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanol in Smoking Status Verification and Usefulness for Trend Monitoring of Tobacco Smoking Exposure.

During the last decade in Korea, urinary cotinine concentrations in non-current smokers have decreased, making it difficult to distinguish secondhand smoke (SHS) exposure from nonsmokers because of overlapping values between non-current smokers with and without SHS exposure. Additionally, the importance of smoking status verification to avoid misclassification is increasing with the increased use of e-cigarettes. We developed a novel index combining urinary cotinine and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) and evaluated its diagnostic performance for the classification of smoking status using the KNHANES VII dataset. A total of 10,116 and 5575 Korean participants aged >19 years with measured urinary cotinine concentrations were enrolled in a training set and validation set, respectively. When using 4.0 as the cutoff value for distinguishing current smokers from non-current smokers, urinary cotinine∙NNAL showed a better diagnostic performance than urinary cotinine or urinary NNAL. Among e-cigarette users, urinary cotinine∙NNAL showed more accurate classification rates than urinary NNAL. Furthermore, urinary cotinine∙NNAL had measurable values in non-current smokers, whereas urinary cotinine had unmeasurable values in one-fourth of all participants. This study shows that urinary cotinine∙NNAL might be a useful biomarker for smoking status verification and trend monitoring of tobacco smoking exposure with increased use of e-cigarettes.

Beyond Training the Next Generation of Physicians: The Unmeasured Value Added by Residents to Teaching Hospitals and Communities.

Following medical school, most newly graduated physicians enter residency training. This period of graduate medical education (GME) is critical to creating a physician workforce with the specialized skills needed to care for the population. Completing GME training is also a requirement for obtaining medical licensure in all 50 states. Yet, crucial federal and state funding for GME is capped, creating a bottleneck in training an adequate physician workforce to meet future patient care needs. Thus, additional GME funding is needed to train more physicians.When considering this additional GME funding, it is imperative to take into account not only the future physician workforce but also the value added by residents to teaching hospitals and communities during their training. Residents positively affect patient care and health care delivery, providing intrinsic and often unmeasured value to patients, the hospital, the local community, the research enterprise, and undergraduate medical education. This added value is often overlooked in decisions regarding GME funding allocation. In this article, the authors underscore the value provided by residents to their training institutions and communities, with a focus on current and recent events, including the global COVID-19 pandemic and teaching hospital closures.

Considerations for choosing an imputation method for addressing sparse measurement issues dictated by the study design - An illustration from per-protocol analysis in pragmatic trials

Last Observation Carried Forward (LOCF) is an ad-hoc method, with known limitations. In recent years, several methods publications have used LOCF in estimating the per-protocol effect via inverse probability of adherence weighted (IPAW) model, when a time-varying factor is partially measured by the study design. We compare the statistical performances of LOCF and multiple imputation approaches for estimating the per-protocol effects via the IPAW model in the presence of incomplete treatment adherence. We used a validated pragmatic trial data generating simulation algorithm to generate datasets under 7 different simulation scenarios, where a post-randomization prognostic factor was measured after regular intervals. Unmeasured values of a partially observed factor were imputed using LOCF and multiple imputation approaches, and IPAW model was fitted on the imputed data to obtain the estimates, and statistical performances were assessed. When confounding exists, for higher variability of the time-varying factor, multiple imputation approach shows desirable statistical properties under MCAR assumption; otherwise, LOCF approach can be adequate. Both imputation methods performed well in terms of statistical properties, when there is no confounding or when all necessary confounders are adjusted. A case study from Coronary Primary Prevention Trial data was presented, which included some participants with incomplete treatment adherence.

Predicting wind flow around buildings using deep learning

The wind velocity field around buildings provides deep insights into the aerodynamic characteristics of buildings and indicates the pedestrian-level wind environment around buildings. Particle image velocimetry (PIV) is usually employed to measure the wind velocities around building models. Due to laser-light shielding, measuring instantaneous wind velocities at some shielded locations around a building model remains difficult. As a result, analyzing the wind flow pattern with these unmeasured wind velocities is difficult. Using machine learning techniques to impute unmeasured values allows for a comprehensive study of wind flow patterns with laser-light shielding. Unmeasured velocities around building models were imputed in this study using machine learning (ML) models such as the generative adversarial imputation network (GAIN), multiple imputations by chained equations (MICE), and neighbored distanced imputation (NDI). GAIN was the best model with a minimum variance and standard deviation of 1.508 and 1.228, respectively. Compared with experimental wind velocities, GAIN produced the minimum average mean squared error of 2.4%. The correlation between the experimental and predicted wind velocities was 98.2%. Thus, the validated GAIN model is recommended to be integrated into the PIV study to impute the unmeasured wind velocities to obtain a complete wind flow pattern.

Advanced Virtual Support for Operational Forces: A 3-Year Summary.

The Military Health System mission is to provide medical care throughout the globe to service members and beneficiaries. To achieve this mission in the most austere of locations, telemedical support is an essential force multiplier when robust in-person medical support is not feasible. This led to the development of a telemedical solution initially known as the Virtual Critical Care Consultation service which provided tele-critical care assistance to downrange providers. The VC3 system then expanded to include multiple medical specialties available for consultation. The current version of this telemedical solution is the ADvanced VIrtual Support for OpeRational Forces (ADVISOR) program which is a synchronous and asynchronous telemedicine system that was developed to provide 24/7 remote expert support to military clinicians engaged in casualty care in austere and operational environments. This manuscript reviews the ADVISOR program data collected from 2017 to 2020 and provides a rough order of magnitude for return on investment. We reviewed data collected by Operational Virtual Health Reports and Operational Virtual Health Evaluations following synchronous consultations. Part of the data reviewed was available patient demographic data, local caregiver information, the purpose of the consult, recommendations made during the consult, the technology used during the consult, and the patient disposition. They also recorded the evacuation plan for the patient and whether a medical evacuation was escalated (e.g. changed from routine to urgent, or from urgent to critical care air transport), downgraded (e.g. urgent to routine), or avoided altogether based on the telephonic consultation. There were a total of 156 real-world calls during the evaluation period. The total cost savings for these calls was $1,097,027 (3-year program costs of $909,973 less an average of $87,261+/- $28,633 per call or $2,007,000 total) from downgrading or avoidance of planned evacuations. The unmeasured value associated with ADVISOR consultations should also be commented on. For example, when evacuation plans are escalated based on remote expert consultation, it is probable that the escalation increases patient safety and may avoid medical complications that would result in longer term medical costs to the government. Based on the collected information, the financial return on investment has exceeded costs and the system is perceived as being valued added for both local caregivers and remote experts. The system appears to help optimize evacuation planning, specifically by downgrading or eliminating unnecessary evacuations.

VISUALIZATION OF OWN RELATIONSHIPS VARIABLES OF UNMEASURED INDICATORS OF INDIVIDUAL CONSCIOUSNESS

The article provides visualization of the dynamics of model interdependent values of variability of unmeasured indicators of an individual's consciousness using the formula for "own deviation and the step of own deviation" z-variability of an unmeasured indicator such as emotions, feelings of an individual. Indicators measuring emotions, feelings, indicators with meanings (units of measurement "percent") and the axiom of the existence of one's own deviation of the manifestations of emotion, feelings of the individual. Indicators measuring emotions, feelings, indicators with meanings (units of measurement "percent") and the axiom of the existence of one's own deviation of the manifestations of emotion, feelings of the individual. Manifestations of variability of the unmeasurable indicator (in the social model of P. Sorokin) of the loss of sensory culture "by the individual.) Are modeled [1], their names-meanings are cognitively determined, and the unmeasured values of their zvariability are modeled and their joint dynamics of variability are visualized, satisfying the axiom of their own existence. deviations. Figures 1-6 clearly illustrate the adequacy.

Proton affinity and gas-phase basicity of pyrogallol and phloroglucinol: a computational study

We report the proton affinities (PAs) and gas-phase basicities (GBs) of pyrogallol (1,2,3-trihydroxybenzene) and phloroglucinol (1,3,5-trihydroxybenzene), as determined by high level quantum chemical calculations and a series of isodesmic proton transfer reactions. These yet unmeasured values have relevance to release of active species from nanocarriers derived from the calixarene family of macrocycles. The PAs and GBs obtained for these two trihydroxybenzene isomers are compared and contrasted with those obtained previously for the third isomer, hydroxyquinol (1,2,4-trihydroxybenzene). Preferred protonation sites and relative thermochemical values are analyzed in terms of electron delocalization effects and the consequent disruption of intramolecular hydrogen bonding.

Real-Time Fine-Grained Air Quality Sensing Networks in Smart City: Design, Implementation, and Optimization

Driven by the increasingly serious air pollution problem, the monitoring of air quality has gained much attention in both theoretical studies and practical implementations. In this paper, we present the architecture, implementation and optimization of our own air quality sensing system, which provides real-time and fine-grained air quality map of the monitored area. As the major component, the optimization problem of our system is studied in detail. Our objective is to minimize the average joint error of the established real-time air quality map, which involves data inference for the unmeasured data values. A deep Q-learning solution has been proposed for the power control problem to reasonably plan the sensing tasks of the power-limited sensing devices online. A genetic algorithm has been designed for the location selection problem to efficiently find the suitable locations to deploy limited number of sensing devices. The performance of the proposed solutions are evaluated by simulations, showing a significant performance gain when adopting both strategies.

Mobile-Based Patient Monitoring Systems: A Prioritisation Framework Using Multi-Criteria Decision-Making Techniques.

This study presents a prioritisation framework for mobile patient monitoring systems (MPMSs) based on multicriteria analysis in architectural components. This framework selects the most appropriate system amongst available MPMSs for the telemedicine environment. Prioritisation of MPMSs is a challenging task due to (a) multiple evaluation criteria, (b) importance of criteria, (c) data variation and (d) unmeasurable values. The secondary data presented as the decision evaluation matrix include six systems (namely, Yale-National Aeronautics and Space Administration (NASA), advanced health and disaster aid network, personalised health monitoring, CMS, MobiHealth and NTU) as alternatives and 13 criteria (namely, supported number of sensors, sensor front-end (SFE) communication, SFE to mobile base unit (MBU) communications, display of biosignals on the MBU, storage of biosignals on the MBU, intra-body area network (BAN) communication problems, extra-BAN communication problems, extra-BAN communication technology, extra-BAN communication protocols, back-end system communication technology, intended geographic area of use, end-to-end security and reported trial problems) based on the architectural components of MPMSs. These criteria are adopted from the most relevant studies and are found to be applicable to this study. The prioritisation framework is developed in three stages. (1) The unmeasurable values of the MPMS evaluation criteria in the adopted decision evaluation matrix based on expert opinion are represented by using the best-worst method (BWM). (2) The importance of the evaluation criteria based on the architectural components of the MPMS is determined by using the BWM. (3) The VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is utilised to rank the MPMSs according to the determined importance of the evaluation criteria and the adopted decision matrix. For validation, mean ± standard deviation is used to verify the similarity of systematic prioritisations objectively. The following results are obtained. (1) The BWM represents the unmeasurable values of the MPMS evaluation criteria. (2) The BWM is suitable for weighing the evaluation criteria based on the architectural components of the MPMS. (3) VIKOR is suitable for solving the MPMS prioritisation problem. Moreover, the internal and external VIKOR group decision making are approximately the same, with the best MPMS being 'Yale-NASA' and the worst MPMS being 'NTU'. (4) For the objective validation, remarkable differences are observed between the group scores, which indicate the similarity of internal and external prioritisation results.

PB2189 FREE LIGHT CHAINS IN MULTIPLE MYELOMA: IS IT TIME TO EXTEND THEIR APPLICATION?

Background:Free Light Chain (FLC) assay is used for multiple myeloma screening, prediction of risk progression and response assessment as indicated by IMWG guidelines, particularly to define stringent complete response (sCR). The assay is also recommended in cases of unmeasurable (non‐secretory, NS) or low values of M‐protein (oligo‐secretory, OS).Aims:Here we describe the value of FLC assay in predicting extramedullary relapse in four MM patients.MethodsDuring the course of therapy, FLC was monitored routinely on a monthly basis.Results:An OS MM IgG κ patient (first case) started in May 2017 4th line KRd therapy, due to new lytic lesions, with negative BM biopsy. During the course of therapy, sIFE remained negative, while sFLC continued to rise (May 2017–March 2018: sFLC κ 175 vs 340 mg/L, rFLC 4.2 vs 19.9). In March 2018 a right femur mass appeared and histology, confirmed EMD relapse. Patient underwent surgical removal and rFLC returned within normal range (1.3).Considering that it was the only site of disease, KRD regimen was restarted in June 2018 for four more cycles. Unfortunately, in November 2018 the knee mass reappeared, and, once again, sFLC was altered (FLC κ 124 mg/L, ratio 25), with negative sIFE. Biopsy of the mass confirmed EMD relapse, BM biopsy remained negative.A patient with IgG κ MM (second case) started in May 2017 2nd line KRd therapy for disease progression, confirmed by BM biopsy. A partial response was obtained quickly, but since March 2018 a progressive rise of rFLC was noticed (March–September 2018: rFLC 0.67 vs 1.67), and it anticipated of 5 months the increase of MP (August 2018). In June 2018 patient complained vague gastrointestinal symptoms and in September a CT scan revealed hepatic nodularities, confirmed by biopsy as hepatic EMD.A LC MM λ patient (third case) started in March 2017 KRd as 2nd line treatment for disease progression (MP 0.7 g/dL, sFLC λ 2000 mg/dL, rFLC 171), with positive BM biopsy. Patient obtained CR after the first cycle, but during the treatment in June 2018 sFLC started increasing and in July alteration of liver and bilirubin tests was noticed, without any clinical sign, always with negative sIFE. In October 2018 sIFE became positive and in November MP reappeared (0.37 g/dL) while both the sFLC (June–November 2018: sFLC λ 53 vs 207 mg/dL; rFLC 6 vs 68) and the liver tests continued to rise. A solid hepatic mass was revealed and biopsy confirmed an EMD relapse.A MM IgA λ patient (fourth case) diagnosed with biopsy of soft paravertebral tissues, was treated with 1st line VMP treatment in September 2018. During the treatment the patient complained sight loss and a CT scan showed the presence of a right ocular mass. The MP was reduced while sFLC increased (September–October 2018: MP 2.4 vs 0.2 g/dL; sFLC λ 158 vs 263 mg/dL; rFLC 5.7 vs 29.4). Biopsy confirmed an aggressive EMD relapse and the patient started 2nd line KRD treatment in October 2018. A complete remission was obtained with ocular mass regression, negative sIFE and improvement of FLC.Unfortunately, in January 2019 during the fourth cycle, a cutaneous lesion appeared on the right tibia, confirmed as EMD relapse. While both the sIFE and BM biopsy remained negative, a slight increase of sFLC was noticed, although always within range.Summary/Conclusion:In all four cases an increase of FLC always preceded the diagnosis of EMD relapse irrespective of MP measurement. We therefore recommend serial use of sFLC assay, particularly in heavily pretreated patients for early detection of aggressive and/or EMD relapse.

Association between vancomycin pharmacokinetic/pharmacodynamic parameters, patient characteristics, and mortality in patients with bacteremia caused by vancomycin-susceptible Enterococcus faecium: a single-center retrospective study

BackgroundVancomycin is commonly used to treat Enterococcus faecium (E. faecium) bacteremia. However, there are very few studies on the association between the trough concentration, area under the curve from 0 to 24 h /minimum inhibitory concentration (AUC24/MIC) ratio, and the therapeutic effect of vancomycin on E. faecium bacteremia. This study aimed to investigate the associations between vancomycin pharmacokinetic/pharmacodynamic parameters, patient characteristics, and mortality in patients with E. faecium bacteremia.MethodsThis retrospective study included patients with E. faecium bacteremia who received vancomycin between April 2012 and February 2018 at a single acute care hospital in Japan. Patients who received renal replacement therapy (hemodialysis or continuous hemodiafiltration), had an unmeasured serum vancomycin concentration, with unmeasured laboratory values, or received other antibiotics for treating E. faecium bacteremia were excluded from the study. The bivariate associations between 30-day all-cause mortality and patient characteristics were assessed.ResultsAmong 87 patients diagnosed with E. faecium bacteremia, 45 were included in the final analysis. Of these, 12 (26.7%) died within 30 days of the diagnosis. The vancomycin trough concentration was higher in the 30-day all-cause mortality patients than in the survival patients (20.5 vs. 14.6 μg/mL; P = 0.022). There was no significant difference in the proportion of patients with a vancomycin AUC24/MIC ≤389 between the groups. The 30-day all-cause mortality patients showed a higher Charlson Comorbidity Index (CCI) and Sequential Organ Failure Assessment score at the first measurement of the vancomycin trough concentration than the survival patients. The same finding was observed among patients with a high CCI score (≥5 points).ConclusionsWhereas the vancomycin trough concentration and AUC24/MIC ratio were not associated with mortality in patients with E. faecium bacteremia, disease severity was associated with mortality in these patients.

The impact of local variations in a temperate maritime climate on building energy use

ABSTRACTWe investigate the impact of local climatic variations on the energy performance of buildings by conducting simulations using weather files generated from high-resolution measurements covering 33 stations within a 77 km2 area in southern Vancouver Island, British Columbia, Canada. Weather files were created by resampling the data and applying appropriate models to obtain unmeasured values. The difference in microclimate has been analysed statistically and graphically; average annual temperature varies by around 1°C, and at certain times there is a 6°C variation across the (very small) region.Building energy simulations of a small naturally ventilated office building and a larger air-conditioned building were performed using EnergyPlus for all weather files. Significant variation is found spatially and temporally which would have substantial implications for building design and energy use. The variation in annual heating energy use is ±5% of the mean, equivalent to 18 kWh/m2/a, with even greater relative variation in cooling energy use.

Water-table and discharge changes associated with the 2016\u20132017 seismic sequence in central Italy: hydrogeological data and a conceptual model for fractured carbonate aquifers

A seismic sequence in central Italy from August 2016 to January 2017 affected groundwater dynamics in fractured carbonate aquifers. Changes in spring discharge, water-table position, and streamflow were recorded for several months following nine Mw 5.0–6.5 seismic events. Data from 22 measurement sites, located within 100 km of the epicentral zones, were analyzed. The intensity of the induced changes were correlated with seismic magnitude and distance to epicenters. The additional post-seismic discharge from rivers and springs was found to be higher than 9 m3/s, totaling more than 0.1 km3 of groundwater release over 6 months. This huge and unexpected contribution increased streamflow in narrow mountainous valleys to previously unmeasured peak values. Analogously to the L’Aquila 2009 post-earthquake phenomenon, these hydrogeological changes might reflect an increase of bulk hydraulic conductivity at the aquifer scale, which would increase hydraulic heads in the discharge zones and lower them in some recharge areas. The observed changes may also be partly due to other mechanisms, such as shaking and/or squeezing effects related to intense subsidence in the core of the affected area, where effects had maximum extent, or breaching of hydraulic barriers.

Electro-mechanical clutch actuator control based on output switched Takagi- Sugeno controller

This paper aims to present a methodology to control the position of the clutch actuator. The objective is to improve the position reference tracking in order to get better performances and accuracy on the clutch slip control. The originality of this work is to use a model that takes into account the nonlinear characteristic of the stiffness of the clutch diaphragm. Instead of robustness approach, the nonlinearity is managed using the quasi-LPV Takagi-Sugeno representation and, additionally, because the nonlinearity is switching, the developed control law is, consequently, a nonlinear switching one. Moreover, in order to use unmeasured values in the controller, such as the current of the electric motor, a Takagi-Sugeno switching observer is designed. Some simulation results highlight the efficiency of the proposed approach.