Optimal Method Research Articles

Optimal parameter estimation for uncertain structural systems under unknown random excitations

An optimal parameter estimation method for uncertain structural systems under unknown random excitations is proposed, which combines the Bayesian inference and stochastic dynamics using geometrically averaged likelihood and optimal response estimation. The general description of optimal parameter estimation problems for uncertain dynamic systems under only stochastic responses measured is presented. The posterior probability density conditional on measured responses is expressed by the likelihood function conditional on system parameters based on Bayes’ theorem. For finite time processes, the parameter estimation problem as the probability integral of conditional means is converted into the optimization problem expressed as maximizing the posterior probability density. A geometrically averaged likelihood function is defined and used for calculating the logarithmic posterior probability density. This estimation can avoid the numerical singularity of the likelihood function and reduce the effects of incomplete posterior probability density and inaccurate prior statistics of unknown random excitations, and then it will be more reasonable and effective. Furthermore, the differential equations for system response means and covariances are derived and solved based on stochastic dynamics theory. The means and covariances conditional on responses at the present instant are expressed by the previous statistics based on optimal response estimation. By combining two results, the analytical expressions of the averaged likelihood function and logarithmic posterior probability density are obtained which will be more reliable and accurate. The proposed optimal estimation method is verified by numerical results for a five-storey frame structure under base random excitation. The estimated results are not affected by the prior statistics errors of random excitation as a factor. For noisy observation, the Kalman filtering is incorporated in the estimation method and hence the estimation is more accurate and robust even for low signal noise ratios. The optimal estimation method has the potential for application to general uncertain systems.

A Review of Personalised Cardiac Computational Modelling Using Electroanatomical Mapping Data

Computational models of cardiac electrophysiology have gradually matured during the past few decades and are now being personalised to provide patient-specific therapy guidance for improving suboptimal treatment outcomes. The predictive features of these personalised electrophysiology models hold the promise of providing optimal treatment planning, which is currently limited in the clinic owing to reliance on a population-based or average patient approach. The generation of a personalised electrophysiology model entails a sequence of steps for which a range of activation mapping, calibration methods and therapy simulation pipelines have been suggested. However, the optimal methods that can potentially constitute a clinically relevant in silico treatment are still being investigated and face limitations, such as uncertainty of electroanatomical data recordings, generation and calibration of models within clinical timelines and requirements to validate or benchmark the recovered tissue parameters. This paper is aimed at reporting techniques on the personalisation of cardiac computational models, with a focus on calibrating cardiac tissue conductivity based on electroanatomical mapping data.

Hartmann’s Procedure Versus Intersphincteric Abdominoperineal Excision in Patients with Rectal Cancer: Report from the Swedish Colorectal Cancer Registry (SCRCR)

Objective: The primary outcome was to compare overall postoperative surgical complications within 30 days after Hartmann’s procedure (HP) compared with intersphincteric abdominoperineal excision (iAPE). The secondary outcome was major surgical complications (Clavien-Dindo ≥ III). Background: There is uncertainty regarding the optimal surgical method in patients with rectal cancer when an anastomosis is unsuitable. Methods: Rectal cancer patients with a tumor height >5 cm, registered in the Swedish Colorectal Cancer Registry who received HP or iAPE electively in 2017–2020 were included, (HP, n = 696; iAPE, n = 314). Logistic regression analysis adjusting for body mass index, American Society of Anesthesiologists classification, sex, age, preoperative radiotherapy, tumor height, cancer stage, operating hospital, and type of operation was performed. Results: Patients in the HP group were older and had higher American Society of Anesthesiologists scores. The mean operating time was less for HP (290 vs 377 min). Intraoperative bowel perforations were less frequent in the HP group, 3.6% versus 10.2%. Overall surgical complication rates were 20.3% after HP and 15.9% after iAPE (P = 0.118). Major surgical complications were 7.5% after HP and 5.7% and after iAPE (P = 0.351). Multiple regression analysis indicated a higher risk of overall surgical complications after HP (odds ratio: 1.63; 95% confidence interval = 1.09–2.45). Conclusions: HP was associated with a higher risk of surgical complications compared with iAPE. In patients unfit for anastomosis, iAPE may be preferable. However, the lack of statistical power regarding major surgical complications, prolonged operating time, increased risk of bowel perforation, and lack of long-term outcomes, raises uncertainty regarding recommending intersphincteric abdominoperineal excision as the preferred surgical approach.

Identification of volatile and non-volatile migrants released during sous vide cooking by UPLC-IMS-QTOF and DI-SPME-GC-MS using a design of experiments approach

The rise of new culinary advances combined with science has made it possible to find new optimum methods of cooking, such as vacuum cooking (Sous Vide), that allow achieving pleasant textures, preserving the genuine nature of the food and also its original flavour. Sous Vide involves the direct contact of plastic materials with food during cooking, causing the possible release of chemical compounds that may alter the properties of the food and pose a risk to human health. In this work, the migration kinetics that takes place during this cooking process have been estimated thanks to a design of experiments (DoE). DoE has been applied to 4 samples of vacuum cooking bags containing 3 food simulants (ethanol 10%, acetic acid 3% and isooctane) under typical cooking conditions of the culinary technique. The study also allowed the identification of the main volatile and non-volatile migrants that can be transferred from this particular packaging. Twenty-nine non-volatile species were identified by ultra-high performance liquid chromatography coupled to a quadrupole-time-of-flight ion-mobility separation mass spectrometer (UPLC-IMS-QTOF) and sixty-four volatile species were identified by solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS). Furthermore, a comprehensive literature analysis was conducted to explore the applications, origins, and potential toxicity of these compounds.

Clustering and Optimizing Methods for Sprints of Agile Development Projects

To address the challenges of sprint planning and sequential optimization in agile development projects, this paper presents a model for agile sprint clustering and optimization. Firstly, we build an activity similarity network and measure the tie strength between activities using social network analysis (SNA) and design structure matrix (DSM). Then, we build an “overlap-iteration” model to measure the interactions strength between activities. Based on thecoupling strength (i.e. the sum of tie strength and interaction strength) between activities, this paper uses a two-stage clustering method to cluster the process DSM to obtain agile sprints. Furthermore, we measure the rework probability and rework intensity between sprints from the rework probability and rework intensity between activities to build an agile sprint optimization method. Finally, an agile development project example is provided to illustrate the validity of the proposed models. The results demonstrate that our approach significantly reduces project duration, cost, and rework risk in agile development projects.

External fixator versus elastic stable intramedullary nail for treatment of metaphyseal-diaphyseal junction fractures of the pediatric distal femur: a case-control study

BackgroundSeveral methods have been used for the treatment of pediatric distal femoral fractures, such as elastic stable intramedullary nail (ESIN), external fixator (EF) and plate osteosynthesis, but there has been no consensus about the optimal method. The purpose of this study was to compare the clinical outcome between EF and ESIN techniques used in metaphyseal-diaphyseal junction (MDJ) fractures of the pediatric distal femur.MethodsWe retrospectively analyzed operatively treated MDJ fractures of pediatric distal femur between January 2015 and January 2022. Patient charts were reviewed for demographics, injury and data of radiography. All of the patients were divided into EF and ESIN groups according to the operation techniques. Malalignment was defined as more than 5 degrees of angular deformity in either plane. Clinical outcomes were measured by Flynn scoring system.ResultsThirty-eight patients were included in this study, among which, 23 were treated with EF, and 15 with ESIN. The mean follow-up time was 18 months (12-24 months). At the final follow-up, all of the fractures were healed. Although there were no statistical differences between the two groups in demographic data, length of stay, estimated blood loss (EBL), rate of open reduction, time to fracture healing and Flynn score, the EF was superior to ESIN in operative time, fluoroscopic exposure and time to partial weight-bearing. The EF group had a significantly higher rate of skin irritation, while the ESIN had a significantly higher rate of malalignment.ConclusionEF and ESIN are both effective methods in the treatment of MDJ fractures of the pediatric distal femur. ESIN is associated with lower rates of skin irritation. However, EF technique has the advantages of shorter operative time, reduced fluoroscopic exposure, and shorter time to partial weight-bearing, as well as lower incidence of malalignment.Level of evidenceLevel III.

Determining the optimal diagnostic and risk stratification approaches for people with hypertension in two rural populations in Kenya and The Gambia: a study protocol for IHCoR-Africa Work Package 2

Background Sub-Saharan Africa (SSA) has one of the highest prevalences of hypertension worldwide. The impact of hypertension is of particular concern in rural SSA, where access to clinics and hospitals is limited. Improvements in the management of people with hypertension in rural SSA could be achieved by sharing diagnosis and care tasks between the clinic and the community. To develop such a community-centred programme we need optimal approaches to identify and risk stratify patients with elevated blood pressure. The aim of the study is to improve the evidence base for diagnosis and risk estimation for a community-centred hypertension programme in two rural settings in SSA. Methods We will conduct a cross-sectional study of 1250 adult participants in Kilifi, Kenya and Kiang West, The Gambia. The study has five objectives which will determine the: (1) accuracy of three blood pressure (BP) measurement methods performed by community health workers in identifying people with hypertension in rural SSA, compared to the reference standard method; (2) relationship between systolic BP and cardiovascular risk factors; (3) prevalence of hypertension-mediated organ damage (HMOD); (4) accuracy of innovative point-of-care (POC) technologies to identify patients with HMOD; and (5) cost-effectiveness of different combinations of BP and HMOD measurements for directing hypertension treatment initiation. Expected findings This study will determine the accuracy of three methods for community BP measurement and POC technologies for HMOD assessment. Using the optimal methods in this setting it will estimate the prevalence of hypertension and provide the best estimate to date of HMOD prevalence in SSA populations. The cost-effectiveness of decision-making approaches for initiating treatment of hypertension will be modelled. These results will inform the development of a community-centred programme to improve care for hypertensive patients living in rural SSA. Existing community engagement networks will be used to disseminated within the research setting.

The Reduced Uterine Perfusion Pressure as a model for preeclampsia and fetal growth restriction in murine: a systematic review and meta-analysis.

The Reduced Uterine Perfusion Pressure (RUPP) model is frequently used to study preeclampsia and fetal growth restriction. An improved understanding of influential factors might improve reproducibility and reduce animal use considering the variability in RUPP phenotype. We performed a systematic review and meta-analysis by searching Medline and Embase (until 03-28-2023) for RUPP studies in murine. Primary outcomes included: maternal blood pressure (BP) or proteinuria, fetal weight or crown-rump-length, fetal reabsorptions, or anti-angiogenic factors. We aimed to identify influential factors by meta-regression analysis. We included 155 studies. Our meta-analysis showed that the RUPP procedure results in significantly higher BP (MD 24.1 mmHg; [22.6;25.7]; n=148), proteinuria (SMD 2.3; [0.9; 3.8]; n=28), fetal reabsorptions (MD 50.4%; [45.5; 55.2]; n=42), circulating soluble FMS-like tyrosine kinase-1 (sFlt-1) (SMD 2.6; [1.7; 3.4]; n=34), and lower fetal weight (MD -0.4 g; [-0.47; -0.34]; n=113. The heterogeneity (variability between studies) in primary outcomes appeared ≥90%. Our meta-regression identified influential factors in the method and time point of BP measurement, randomization in fetal weight, and type of control group in sFlt-1. The RUPP is a robust model considering the evident differences in maternal and fetal outcomes. The high heterogeneity reflects the observed variability in phenotype. Due to underreporting, we observed reporting bias and a high risk of bias. We recommend standardizing study design by optimal time point and method chosen for readout measures to limit the variability. This contributes to improved reproducibility and thereby eventually improves the translational value of the RUPP model.

Comparative analysis of the course of the perioperative period in patients with diabetes during knee and hip arthroplasties

Background. Hip and knee arthroplasty (HKA) are common surgical interventions. In more than 20 % of patients undergoing HKA, diabetes mellitus is detected, which is one of the risk factors for the development of periprosthetic infection and the occurrence of complications in the perioperative period. The purpose: to determine the features of the course of the perioperative period in patients with diabetes during knee and hip replacement. Materials and methods. A retrospective analysis was performed of the inpatient charts of 50 people who underwent HKA against the background of concomitant diabetes. All participants were divided into two groups: 1) patients with hip arthroplasty; 2) patients with knee arthroplasty. The course of the intraoperative and postoperative periods and the development of complications were analyzed. Results. All patients were aged from 38 to 86 years, had increased weight (body mass index of 26.0–29.4 kg/m2). Among the complications, hypertension was most common (64.0 and 68.0 % in the groups, respectively), nausea and vomiting (32.0 and 28.0 %, respectively), disturbances in the rhythm and depth of breathing (16.0 and 20.0 % respectively) were often observed. The need for analgesia in the postoperative period was registered in 96.0 and 100.0 % of cases, which indicates its insufficient quality. Other clinical and anamnestic indicators, the course of the perioperative period and the development of complications were similar in patients undergoing both hip and knee replacements (p > 0.05). Conclusions. Clinical and anamnestic data, the spectrum of existing concomitant pathology, characteristics of carbohydrate metabolism and its disorders, features of the course of the perioperative period and detected complications were of the same type in patients regardless of the location of the intervention. There was no significant difference in the studied parameters (p > 0.05). Identified complications and insufficient effectiveness of postoperative analgesia dictates the need to find optimal methods of perioperative analgesia during HKA.

Dynamic Bayesian Game Optimization Method for Multi-Energy Hub Systems with Incomplete Load Information

The interconnection of Energy Hub can enhance the energy efficiency and reliability associated with the independent operation of energy systems. However, the traditional optimal scheduling methods are hard to tackle the situation with the incomplete load information and competitive constraints of a multi-Energy Hub. This paper proposes a dynamic Bayesian game optimization scheduling strategy considering incomplete information on users’ load-side demand. First, a load forecast error coefficient is introduced to handle the conditional probability problem caused by incomplete information through the Bayesian rule. The constraint relationship among multi-Energy Hub under the dynamic price mechanism is analyzed to meet the economic and environmental coordination goals under load uncertainty. Second, extending from Nash equilibrium to Bayes Nash equilibrium proves the existence and uniqueness of Nash equilibrium solutions in Bayesian game models. The decision game algorithm is used to optimize the scheduling of the multi-Energy Hub and subsequently ensure the autonomous scheduling of the system and solve the information barriers. Finally, an Integrated Energy System composed of three Energy Hubs was used to validate the effectiveness and superiority of the proposed optimization method. Results show that under the Bayesian game decision, the multi-Energy Hub game model has reduced the total cost of the Integrated Energy System by 0.78%, which can improve the economic benefit and address the environmental pollution problem.

Study on Water and Salt Transport Characteristics of Sunflowers under Different Irrigation Amounts in the Yellow River Irrigation Area

The control of irrigation volume is of significant importance in arid regions of northwest China. Particularly, it has a crucial impact on the salinization of shallow groundwater areas. In 2022 and 2023, field experiments were conducted to test three distinct under-membrane irrigation treatments. These treatments were assigned water quotas of HW (27 mm), MW (22.5 mm), and LW (18 mm). The HYDRUS-2D model was integrated with a field experiment to accurately simulate the dynamic fluctuations of soil water and salt in the sunflower root zone. The model’s performance was assessed and verified using real-field data from 2022 and 2023, and the simulation results closely matched the measured values. This research also used stable hydroxide isotopes to assess the water supply from various soil layers at different time intervals in sunflower plants. The results indicated that the three different levels of irrigation applied under the membrane had a significant impact on soil water content. Specifically, there was a significant difference in soil water content at a depth of 0–40 cm (p < 0.05), while there was little effect on the water content at a depth of 40–60 cm (p > 0.05). After irrigation, the average salt content in the top 0–20 cm of soil decreased by 7.0% compared to the medium and low irrigation levels, and by 10.8% compared to the medium irrigation level. Additionally, the medium irrigation level resulted in a 10.8% decrease in salt content compared to the low irrigation level, and a 4.1% decrease compared to the medium irrigation level. During the same period, the soil salinity levels at depths of 0–20 cm, 20–40 cm, 40–60 cm, and 60–100 cm in the area outside the membrane were measured to be 2.7~4.8 g·kg−1, 2.8~4.0 g·kg−1, 2.7~3.4 g·kg−1, and 1.7~2.6 g·kg−1, respectively. These levels decreased by 13.1~55.5%, 0.7~42.8%, −0.4~16.2%, and −72.7~7.5%, respectively. Following irrigation, the HW treatment mostly absorbed water in the 0–40 cm soil layer, while the MW and LW treatments absorbed water in both the 0–40 cm and 60–80 cm soil levels. The results indicated that the most optimal drip irrigation method beneath the membrane in this location was achieved when the amount of water applied was between 25–30 mm. This method demonstrated a combination of water conservation, high crop yield, and effective salt suppression.

Defining the optimal segmentation method for measuring somatostatin receptor expressing tumor volume on 68Ga-DOTATATE positron emission tomography/computed tomography to predict prognosis in patients with gastroenteropancreatic neuroendocrine tumors.

We aimed to compare different segmentation methods used to calculate prognostically valuable volumetric parameters, somatostatin receptor expressing tumor volume (SRETV), and total lesion somatostatin receptor expression (TLSRE), measured by 68Ga-DOTATATE PET/CT and to find the optimal segmentation method to predict prognosis. Images of 34 patients diagnosed with gastroenteropancreatic neuroendocrine tumor (GEPNET) who underwent 68Ga-DOTATATE PET/CT imaging were reanalyzed. Four different threshold-based methods (fixed relative threshold method, normal liver background threshold method, fixed absolute standardized uptake value (SUV) threshold method, and adaptive threshold method) were used to calculate SRETV and TLSRE values. SRETV of all lesions of a patient was summarized as whole body SRETV (WB-SRETV) and TLSRE of all lesions of a patient was computed as whole body TLSRE (WB-TLSRE). WB-SRETVs calculated with all segmentation methods were statistically significantly associated with progression-free survival except WB-SRETVat which was calculated using adaptive threshold method. The fixed relative threshold methods calculated by using 45% (WB-SRETV45%) and 60% (WB-SRETV60%) of the SUV value as threshold respectively, were found to have statistically significant highest prognostic value (C-index = 0.704, CI = 0.622-0.786, P = 0.007). Among WB-TLSRE parameters, WB-TLSRE35%, WB-TLSRE40%, and WB-TLSRE50% had the highest prognostic value (C-index = 0.689, CI = 0.604-0.774, P = 0.008). The fixed relative threshold method was found to be the most effective and easily applicable method to measure SRETV on pretreatment 68Ga-DOTATATE PET/CT to predict prognosis in GEPNET patients. WB-SRETV45% (cutoff value of 11.8 cm3) and WB-SRETV60% (cutoff value of 6.3 cm3) were found to be the strongest predictors of prognosis in GEPNET patients.

Toward Large-Scale AFQMC Calculations: Large Time Step Auxiliary-Field Quantum Monte Carlo.

We report modifications of the ph-AFQMC algorithm that allow the use of large time steps and reliable time step extrapolation. Our modified algorithm eliminates size-consistency errors present in the standard algorithm when large time steps are employed. We investigate various methods to approximate the exponential of the one-body operator within the AFQMC framework, distinctly demonstrating the superiority of Krylov methods over the conventional Taylor expansion. We assess various propagators within AFQMC and demonstrate that the Split-2 propagator is the optimal method, exhibiting the smallest time-step errors. For the HEAT set molecules, the time-step extrapolated energies deviate on average by only 0.19 kcal/mol from the accurate small time-step energies. For small water clusters, we obtain accurate complete basis-set binding energies using time-step extrapolation with a mean absolute error of 0.07 kcal/mol compared to CCSD(T). Using large time-step ph-AFQMC for the N2 dimer, we show that accurate bond lengths can be obtained while reducing CPU time by an order of magnitude.

Optimization Decomposition of Monthly Contracts for Integrated Energy Service Provider Considering Spot Market Bidding Equilibria

Under the current power trading model, especially in the context of the large-scale penetration of renewable energy and the rapid integration of renewable energy into the power system, reasonable medium- and long-term decomposition can reduce the fluctuation in the energy price when the integrated energy service provider (IESP) participates in the spot market. It helps to avoid the price risk of the spot market. Additionally, it promotes the optimization of the operation of the regional energy day-ahead scheduling. At the present stage, most of the medium- and long-term contract decomposition methods focus on the decomposition of a single power and take less consideration of the bidding space in the spot market. This limitation makes it challenging to achieve efficient interaction and interconnection among multi-energy resources and smooth integration between the medium- and long-term market and the spot market. To address these issues, this paper proposes an optimal monthly contract decomposition method for IESPs that takes into account the equilibrium of spot bidding. First, the linking process and rolling framework of multi-energy transactions between the medium- and long-term market and the spot market are designed. Second, an optimal decomposition model for monthly contracts is constructed, and a daily decomposition method for monthly medium- and long-term contracts that accounts for the spot bidding equilibrium is proposed. Then, the daily preliminary decomposition result of medium- and long-term multi-energy contracts is used as the boundary condition of the day-ahead scheduling model, and the coupling characteristics of the multi-energy networks of electricity, gas, and heat are taken into account, as well as the operational characteristics. Then, considering the coupling characteristics and operating characteristics of electricity, gas, and heat networks, the optimal scheduling model of a multi-energy network is constructed to minimize the sum of cumulative daily operating costs, and the monthly final contract decomposition value and daily spot bidding space are derived. Finally, examples are calculated to verify the validity of the decomposition model, and the examples show that the proposed method can reduce the variance in spot energy purchase by about 4.64%, and, at the same time, reduce the cost of contract decomposition by about USD 0.33 million.

Optimization of Renewable Energy Hydrogen Production Systems Using Volatility Improved Multi-Objective Particle Swarm Algorithm

Optimizing the energy structure to effectively enhance the integration level of renewable energy is an important pathway for achieving dual carbon goals. This study utilizes an improved multi-objective particle swarm optimization algorithm based on load fluctuation rates to optimize the architecture and unit capacity of hydrogen production systems. It investigates the optimal configuration methods for the architectural model of new energy hydrogen production systems in Xining City, Qinghai Province, as well as the internal storage battery, ALK hydrogen production equipment, and PEM hydrogen production equipment, aiming at various scenarios of power sources such as wind, solar, wind–solar complementary, and wind–solar–storage complementary, as well as intermittent hydrogen production scenarios such as hydrogen stations, hydrogen metallurgy, and continuous hydrogen production scenarios such as hydrogen methanol production. The results indicate that the fluctuation of hydrogen load scenarios has a significant impact on the installed capacity and initial investment of the system. Compared with the single-channel photovoltaic hydrogen production scheme, the dual-channel hydrogen production scheme still reduces equipment capacity by 6.04% and initial investment by 6.16% in the chemical hydrogen scenario with the least load fluctuation.

Antifungal activity of alginate coatings with essential oil of Mexican oregano incorporated in the stem of tomatoes

SummaryAdding natural antimicrobials such as essential oils (EOs) to alginate coatings on fruits provides an antifungal effect and a semipermeable water vapour barrier. This work aims to evaluate the antifungal effect of Lippia berlandieri S. (Mexican oregano) EO incorporated into alginate to coat tomato stems inoculated with Penicillium commune, Fusarium spp., or Cladosporium herbarum. Alginate films and coatings with EO concentrations (0%, 0.25%, 0.75%, 1%, 2%, or 4% v/v) were prepared to evaluate their properties (physical, mechanical, and water vapour transmission rates) as well as their effect on mould growth on tomato stems for 28 days during refrigerated storage. Mould growth was described with probabilistic and time‐to‐growth predictive models. Two treatment types were assessed (tomato inoculated and coated, TIC, and tomato coated and inoculated, TCI) to provide information about the moment of mould contamination (before or after coating). EO concentration influenced the alginate films' physical, mechanical, and barrier properties. Testing the coatings against moulds revealed varying inhibitory effects. Fusarium spp. exhibited the highest resistance, while C. herbarum was the most susceptible. The predictive models appropriately described the probability of growth or the time‐to‐growth of the studied moulds, identifying critical concentrations of oregano EO needed to inhibit mould growth effectively. The findings suggest that alginate coatings with oregano EO can serve as a natural and effective antifungal treatment for tomatoes, offering insights into optimal concentrations and application methods for extended shelf life.

Frailty, Outcomes, Recovery and Care Steps of Critically Ill Patients (FORECAST): a prospective, multi-centre, cohort study.

Frailty is common in critically ill patients but the timing and optimal method of frailty ascertainment, trajectory and relationship with care processes remain uncertain. We sought to elucidate the trajectory and care processes of frailty in critically ill patients as measured by the Clinical Frailty Scale (CFS) and Frailty Index (FI). This is a multi-centre prospective cohort study enrolling patients ≥ 50years old receiving life support > 24h. Frailty severity was assessed with a CFS, and a FI based on the elements of a comprehensive geriatric assessment (CGA) at intensive care unit (ICU) admission, hospital discharge and 6months. For the primary outcome of frailty prevalence, it was a priori dichotomously defined as a CFS ≥ 5 or FI ≥ 0.2. Processes of care, adverse events were collected during ICU and ward stays while outcomes were determined for ICU, hospital, and 6months. In 687 patients, whose age (mean ± standard deviation) was 68.8 ± 9.2years, frailty prevalence was higher when measured with the FI (CFS, FI %): ICU admission (29.8, 44.8), hospital discharge (54.6, 67.9), 6months (34.1, 42.6). Compared to ICU admission, aggregate frailty severity increased to hospital discharge but improved by 6months; individually, CFS and FI were higher in 45.3% and 50.6% patients, respectively at 6months. Compared to hospital discharge, 18.7% (CFS) and 20% (FI) were higher at 6months. Mortality was higher in frail patients. Processes of care and adverse events were similar except for worse ICU/ward mobility and more frequent delirium in frail patients. Frailty severity was dynamic, can be measured during recovery from critical illness using the CFS and FI which were both associated with worse outcomes. Although the CFS is a global measure, a CGA FI based may have advantages of being able to measure frailty levels, identify deficits, and potential targets for intervention.

Systematic testing, verification and validation of laser treatments for unglazed earthenware affected by lichens and fungi biodeterioration

Abstract In recent years, there has been a growing interest in exploring environmentally friendly and healthy alternatives to conventional solvent cleaning and biocides in the conservation of stone artworks. Here, we focus on the potential of laser-based photonic methods for treating biodeteriorated earthenware artefacts. The investigation was conducted on Roman dolia (jars) of the International Museum of Ceramics (MIC), Faenza, Italy. 
Three removal methods were tested and compared: i) brushing using a soft-bristled electric brush and water, referred to as brush cleaning; ii) a combination of brushing and laser ablation; and iii) biocide and brushing. 
Four laser systems with different wavelengths and optimized pulse durations in nanosecond or microsecond regimes were used in the tests. Systematic irradiation tests were conducted to determine the damage thresholds and define safe laser irradiation levels. The characterizations of the surfaces under treatment were carried out pre- and post-laser irradiation using optical microscopy, 3D photogrammetry, and Pulse-Amplitude-Modulated Chlorophyll-Fluorometry (CF-PAM). Furthermore, spectroscopic methods based on FTIR, Raman, and LIBS techniques were used to assess the effectiveness of the removal process and the composition of uncovered surfaces.
Results have indicated that gentle brushing and water is the most effective approach for safely removing around 60% of the bio-colonization weakly anchored to the substrate over the area under treatment. This comprised viable species, whereas the remaining 40% of the area included endolithic species, mostly thalli of Verrucaria nigrescens and rock-dwelling fungi. The eradication of the latter was the real conservation concern requiring attention. Following the experimentation, the optimal method for safely uncovering the earthenware surface was a combination of water-assisted brushing and 1064 nm laser irradiation as a finishing treatment. 

The use of artificial intelligence for predicting postinfarction myocardial viability in echocardiographic images.

Evaluation of standard echocardiographic examination with artificial intelligence may help in the diagnosis of myocardial viability and function recovery after acute coronary syndrome. Sixty-one consecutive patients with acute coronary syndrome were enrolled in the present study (43 men, mean age 61 ± 9 years). All patients underwent percutaneous coronary intervention (PCI). 533 segments of the heart echo images were used. After 12 ± 1 months of follow-up, patients had an echocardiographic evaluation. After PCI each patient underwent cardiac magnetic resonance (CMR) with late enhancement and low-dose dobutamine echocardiographic examination. For texture analysis, custom software was used (MaZda 5.20, Institute of Electronics).Linear and non-linear (neural network) discriminative analyses were performed to identify the optimal analytic method correlating with CMR regarding the necrosis extent and viability prediction after follow-up. Texture parameters were analyzed using machine learning techniques: Artificial Neural Networks, Namely Multilayer Perceptron, Nonlinear Discriminant Analysis, Support Vector Machine, and Adaboost algorithm. The mean concordance between the CMR definition of viability and three classification models in Artificial Neural Networks varied from 42% to 76%. Echo-based detection of non-viable tissue was more sensitive in the segments with the highest relative transmural scar thickness: 51-75% and 76-99%. The best results have been obtained for images with contrast for red and grey components (74% of proper classification). In dobutamine echocardiography, the results of appropriate prediction were 67% for monochromatic images. Detection and semi-quantification of scar transmurality are feasible in echocardiographic images analyzed with artificial intelligence. Selected analytic methods yielded similar accuracy, and contrast enhancement contributed to the prediction accuracy of myocardial viability after myocardial infarction in 12 months of follow-up.

Optimal Planning of Energy Storage in Distribution Feeders Considering Economy and Reliability

Optimal Planning of Energy Storage in Distribution Feeders Considering Economy and Reliability