Similar Probability Research Articles

Patterns of West Nile Virus in the Northeastern United States Using Negative Binomial and Mechanistic Trait-Based Models.

West Nile virus (WNV) primarily infects birds and mosquitoes but has also caused over 2,000 human deaths, and >50,000 reported human cases in the United States. Expected numbers of WNV neuroinvasive cases for the present were described for the Northeastern United States, using a negative binomial model. Changes in temperature-based suitability for WNV due to climate change were examined for the next decade using a temperature-trait model. WNV suitability was generally expected to increase over the next decade due to changes in temperature, but the changes in suitability were generally small. Many, but not all, populous counties in the northeast are already near peak suitability. Several years in a row of low case numbers is consistent with a negative binomial, and should not be interpreted as a change in disease dynamics. Public health budgets need to be prepared for the expected infrequent years with higher-than-average cases. Low-population counties that have not yet had a case are expected to have similar probabilities of having a new case as nearby low-population counties with cases, as these absences are consistent with a single statistical distribution and random chance.

PD37-02 BLADDER SELF-CATHETERIZATIONS BY PATIENTS WITH SPINA BIFIDA: REASONS FOR NOT DOING IT

You have accessJournal of UrologyCME1 Apr 2023PD37-02 BLADDER SELF-CATHETERIZATIONS BY PATIENTS WITH SPINA BIFIDA: REASONS FOR NOT DOING IT Yifan Meng, Rosalia Misseri, Joshua Roth, Benjamin Whittam, Jeremy Koehlinger, Shelly King, Martin Kaefer, RINK Richard, and Konrad Szymanski Yifan MengYifan Meng More articles by this author , Rosalia MisseriRosalia Misseri More articles by this author , Joshua RothJoshua Roth More articles by this author , Benjamin WhittamBenjamin Whittam More articles by this author , Jeremy KoehlingerJeremy Koehlinger More articles by this author , Shelly KingShelly King More articles by this author , Martin KaeferMartin Kaefer More articles by this author , RINK RichardRINK Richard More articles by this author , and Konrad SzymanskiKonrad Szymanski More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003335.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: While children with spina bifida (SB) start self-catheterizing at around 9 years old (yo), little is known about why some do not perform it. We sought to describe how self-catheterization changes with age and reasons why patients do not self-catheterize. METHODS: Patients (3-20 yo) and their parents who catheterize their bladders were surveyed in the SB clinic at our institution (2017-2022). We asked if the patient self-catheterized (yes/no) and if they did not: “Why don’t you do the catheterizations by yourself?” Analysis was performed across patient encounters, to retain data points across patients’ lives. Non-parametric statistics were used. RESULTS: Median age of 240 participants attending 483 visits was 11.5 years (52% male, 36% wheelchair users, 73% shunted). Self-catheterization increased with age: 63% at 9-11yo, increasing to 80-93% by age 12-20 yo (p<0.001) (Figure 1). After 9 yo, 36% of self-catheterizations were performed per urethra and 64% per channel. Among those self-catheterizing, females and males had similar probabilities of using a channel (67% vs. 56%, p=0.08). Self-reported reasons for not self-catheterizing differed with age. Being “too young” was the predominant reason in younger patients (91% in 3-5 yo, 59% in the 6-8 yo). Older patients cited physical limitations, including “difficulty moving hands” and “core stability,” as predominant reasons for not self-catheterizing (21-33% after age 9). Lack of interest was rarely reported (4%). After excluding being “too young” as a reason, other reasons for not self-catheterizing were similar between age groups (p=0.20) but differed between patients with and without channels (p<0.001). Physical limitations were more common among those self-catheterizing per urethra. CONCLUSIONS: Rates of self-catheterization increased with age. According to parents of patients 9 years or older with SB, not self-catheterizing is rarely due to disinterest. Patients with physical limitations may be more likely to self-catheterize through a channel. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e986 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Yifan Meng More articles by this author Rosalia Misseri More articles by this author Joshua Roth More articles by this author Benjamin Whittam More articles by this author Jeremy Koehlinger More articles by this author Shelly King More articles by this author Martin Kaefer More articles by this author RINK Richard More articles by this author Konrad Szymanski More articles by this author Expand All Advertisement PDF downloadLoading ...

New Probabilistic, Dynamic Multi-Method Ensembles for Optimization Based on the CRO-SL

In this paper, new probabilistic and dynamic (adaptive) strategies for creating multi-method ensembles based on the coral reef optimization with substrate layers (CRO-SL) algorithm are proposed. CRO-SL is an evolutionary-based ensemble approach that is able to combine different search procedures for a single population. In this work, two different probabilistic strategies to improve the algorithm are analyzed. First, the probabilistic CRO-SL (PCRO-SL) is presented, which substitutes the substrates in the CRO-SL population with tags associated with each individual. Each tag represents a different operator which will modify the individual in the reproduction phase. In each generation of the algorithm, the tags are randomly assigned to the individuals with similar probabilities, obtaining this way an ensemble that sees more intense changes with the application of different operators to a given individual than CRO-SL. Second, the dynamic probabilistic CRO-SL (DPCRO-SL) is presented, in which the probability of tag assignment is modified during the evolution of the algorithm, depending on the quality of the solutions generated in each substrate. Thus, the best substrates in the search process will be assigned higher probabilities than those which showed worse performance during the search. The performances of the proposed probabilistic and dynamic ensembles were tested for different optimization problems, including benchmark functions and a real application of wind-turbine-layout optimization, comparing the results obtained with those of existing algorithms in the literature.

Neural Variational Gaussian Mixture Topic Model

Neural variational inference-based topic modeling has gained great success in mining abstract topics from documents. However, these topic models usually mainly focus on optimizing the topic proportions for documents, while the quality and the internal construction of topics are usually neglected. Specifically, these models lack the guarantee that semantically related words are supposed to be assigned to the same topic and are difficult to ensure the interpretability of topics. Moreover, many topical words recur frequently in the top words of different topics, which makes the learned topics semantically redundant and similar, and of little significance for further study. To solve the above problems, we propose a novel neural topic model called Neural Variational Gaussian Mixture Topic Model (NVGMTM). We use Gaussian distribution to depict the semantic relevance between words in the topics. Each topic in NVGMTM is considered as a multivariate Gaussian distribution over words in the word-embedding space. Thus, semantically related words share similar probabilities in each topic, which makes the topics more coherent and interpretable. Experimental results on two public corpora show the proposed model outperforms the state-of-the-art baselines.

Aberrant regeneration in an international registry of patients with 3rd-nerve palsy.

To describe the patterns of pre-operative aberrant regeneration and motility outcomes reported in an international registry of patients with 3rd-nerve palsy treated with nasal transposition of the split lateral rectus muscle (NTSLR). This cross-sectional study used data from an international, multicentre registry of patients with 3rd-nerve palsy treated with NTSLR. Patients with aberrant regeneration were identified, and patterns of innervation described. Demographics and postoperative success defined as horizontal alignment ≤15 PD were compared based on the presence, and type, of aberrant regeneration using Wilcoxon rank sum and Fisher's exact tests. Aberrant regeneration was reported in 16% (21/129) of patients. Age at diagnosis, sex, and aetiology of palsy were not significantly associated with aberrant regeneration. Abnormal movements were triggered by adduction in 52% (11/21), infraduction in 23% (5/21), and supraduction in 23% (5/21) of cases. Presentation patterns involved rectus muscle innervation in 29% (6/21) and levator muscle innervation in 71% (15/21) of cases. Although patients with aberrant regeneration had similar probability of success in comparison to those without following NTLSR (76% vs. 69%, p = 0.5), those with abnormal innervation of a rectus muscle had a lower success rate than those with abnormal innervation of the levator palpebrae superioris muscle (17% vs. 93%; p = 0.002). Successful treatment of a 3rd nerve palsy with NTSLR was not influenced by aberrant regeneration involving the levator muscle. Alternative surgical interventions should be considered when aberrant regeneration alters rectus muscle function given its adverse impact on motor outcomes with NTSLR.

Near-threshold recruitment characteristics of motor evoked potentials in transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) can induce motor evoked potentials (MEPs). In TMS applications, near-threshold stimulation intensities (SIs) are often used for characterizing corticospinal excitability using MEPs. We aimed to characterize the individual near-threshold recruitment of MEPs and to test the assumptions related to selection of the suprathreshold SI. We utilized MEP data from a right-hand muscle induced at variable SIs. The single-pulse TMS (spTMS) data from previous studies (27 healthy volunteers), as well as data from new measurements (10 healthy volunteers) that included also MEPs modulated by paired-pulse TMS (ppTMS), were included. The probability of MEP (pMEP) was represented with individually fitted cumulative distribution function (CDF) with two parameters: resting motor threshold (rMT) and spread relative to rMT. MEPs were recorded with 110% and 120% of rMT as well as with Mills-Nithi upper threshold (UT). The individual near-threshold characteristics varied with CDF parameters: the rMT and the relative spread (median: 0.052). The rMT was lower with ppTMS than with spTMS (p < 0.001), while the relative spread remained similar (p = 0.812). At suprathreshold SIs, the probability of MEP was similar between UT and 110% of rMT (pMEP > 0.88), and higher for 120% of rMT (pMEP > 0.98). The individual near-threshold characteristics determine how probably MEPs are produced at common suprathreshold SIs. At the population level, the used SIs UT and 110% of rMT produced MEPs at similar probability. The individual variability in the relative spread parameter was large; therefore, the method of determining the proper suprathreshold SI for TMS applications is of crucial importance.

The probability of unprecedented high rainfall in wine regions of northern Portugal

Climate is arguably one of the most important factors determining the quality of wine from any given grapevine variety. This study focuses on three wine-growing regions in northern Portugal: Vinho Verde, Trás-os-Montes and Douro, the latter coinciding with Porto. High rainfall during late spring (April to June) can promote growth of the vines but increases the risk of fungal disease. High rainfall during harvest time (August to October) also bears the potential for severe operational disruption and heavy economic losses. The probability of unprecedented rainfall totals in spring and the harvest season over wine-growing regions of northern Portugal has been assessed. A large ensemble of initialised climate model simulations is analysed, and the probability of unprecedented rainfall in each season is quantified. Seasonal rainfall totals considerably higher than any observed are possible in the current climate. An unprecedented rainfall event in either season could occur with a probability between 0.01 and 0.05 in the present climate. Extreme value analysis was applied to rainfall totals from observations and the model ensemble, and the return periods of known extreme rainfall events are calculated. Similar probabilities for unprecedented rainfall totals were calculated. A year similar to 1993, when both seasons were exceptionally wet, would be expected to occur, on average, just once in the next 70–80 years in the current climate. These results could inform the requirements for improved vineyard management and resilience, such as design of drainage channels, access roads and terraces.

Using machine learning to predict venous thromboembolism and major bleeding events following total joint arthroplasty

Venous thromboembolism (VTE) and major bleeding (MBE) are feared complications that are influenced by numerous host and surgical related factors. Using machine learning on contemporary data, our aim was to develop and validate a practical, easy-to-use algorithm to predict risk for VTE and MBE following total joint arthroplasty (TJA). This was a single institutional study of 35,963 primary and revision total hip (THA) and knee arthroplasty (TKA) patients operated between 2009 and 2020. Fifty-six variables related to demographics, comorbidities, operative factors as well as chemoprophylaxis were included in the analysis. The cohort was divided to training (70%) and test (30%) sets. Four machine learning models were developed for each of the outcomes assessed (VTE and MBE). Models were created for all VTE grouped together as well as for pulmonary emboli (PE) and deep vein thrombosis (DVT) individually to examine the need for distinct algorithms. For each outcome, the model that best performed using repeated cross validation was chosen for algorithm development, and predicted versus observed incidences were evaluated. Of the 35,963 patients included, 308 (0.86%) developed VTE (170 PE’s, 176 DVT’s) and 293 (0.81%) developed MBE. Separate models were created for PE and DVT as they were found to outperform the prediction of VTE. Gradient boosting trees had the highest performance for both PE (AUC-ROC 0.774 [SD 0.055]) and DVT (AUC-ROC 0.759 [SD 0.039]). For MBE, least absolute shrinkage and selection operator (Lasso) analysis had the highest AUC (AUC-ROC 0.803 [SD 0.035]). An algorithm that provides the probability for PE, DVT and MBE for each specific patient was created. All 3 algorithms had good discriminatory capability and cross-validation showed similar probabilities comparing predicted and observed failures indicating high accuracy of the model. We successfully developed and validated an easy-to-use algorithm that accurately predicts VTE and MBE following TJA. This tool can be used in every-day clinical decision making and patient counseling.

Efficacy and safety of first-line immune checkpoint inhibitors combined with chemotherapy for extensive-stage small cell lung cancer: A network meta-analysis

The efficacy and safety of first-line immune checkpoint inhibitors plus chemotherapy in the treatment of patients with extensive-stage small cell lung cancer (ES-SCLC) remains unevaluated, and there are no reports to directly compare the efficacy and safety among different immunotherapy (especially adebrelimab and surplulimab). Suitable phase III randomized controlled trials with two or more different arms were included. Independent reviewers screened and extracted relevant data and disagreements were resolved through consensus. Fixed-effect consistency models were used to calculate the overall survival (OS), progression-free survival (PFS), objective response rate, adverse events ≥ 3, and safety outcomes in the clinically relevant subgroups. In this network meta-analysis, six randomized controlled clinical trials (CAPSTONE-1, ASTRUM-005, CASPIAN, IMpower133, KEYNOTE-604, and an ipilimumab + chemotherapy trial) with totaling 3662 patients were involved. Compared to chemotherapy, immune checkpoint inhibitors plus chemotherapy present higher possibilities to bring about better OS and PFS. Serplulimab + chemotherapy significantly showed a better survival profit in comparison with ipilimumab + chemotherapy (0.67; 0.50–0.90). Compared with chemotherapy, adebrelimab + chemotherapy (0.72; 0,58–0.90), atezolizumab + chemotherapy (0.76; 0.60–0.96) durvalumab + chemotherapy (0.75; 0.62–0.91), and serplulimab + chemotherapy (0.63;0.49–0.82) all presented significantly better overall survival. In terms of progression-free survival, serplulimab + chemotherapy showed better efficacy in comparison with adebrelimab + chemotherapy (0.72; 0,53–0.97), atezolizumab + chemotherapy (0.62; 0.46–0.84), durvalumab + chemotherapy (0.60; 0.45–0.80). Compared with chemotherapy, adebrelimab + chemotherapy (0.67; 0.54–0.83) and serplulimab + chemotherapy (0.48; 0.48–0.86) all presented significantly better PFS. Immunotherapy plus chemotherapy had similar probabilities to cause adverse events of grade ≥ 3. In comparison with chemotherapy, immune checkpoint inhibitors plus chemotherapy were likely to be more suitable for the first-line treatment of ES-SCLC. According to our analysis, serplulimab plus chemotherapy and adebrelimab plus chemotherapy present higher possibilities to show better efficacy and safety, however, the level of evidence of this type of comparison is limited.

MRONJ in breast cancer patients under bone modifying agents for cancer treatment-induced bone loss (CTIBL): a multi-hospital-based case series

BackgroundCancer treatment-induced bone loss (CTIBL) is the most common adverse event experienced by patients affected by breast cancer (BC) patients, without bone metastases. Bone modifying agents (BMAs) therapy is prescribed for the prevention of CTIBL, but it exposes patients to the risk of MRONJ.MethodsThis multicentre hospital-based retrospective study included consecutive non-metastatic BC patients affected by MRONJ related to exposure to low-dose BMAs for CTIBL prevention. Patients’ data were retrospectively collected from the clinical charts of seven recruiting Italian centres.ResultsMRONJ lesions were found in fifteen females (mean age 67.5 years), mainly in the mandible (73.3%). The mean duration of BMAs therapy at MRONJ presentation was 34.9 months. The more frequent BMAs was denosumab (53.3%). Ten patients (66.7%) showed the following local risk factors associated to MRONJ development: periodontal disease (PD) in three cases (20%) and the remaining six (40%) have undergone PD-related tooth extractions. One patient presented an implant presence-triggered MRONJ (6.7%). In five patients (33.3%) no local risk factors were observed.ConclusionsThis is the first case series that investigated BC patients under BMAs for CTIBL prevention suffering from MRONJ. These patients seem to have similar probabilities of developing MRONJ as osteo-metabolic ones. Breast cancer patients under BMAs for CTIBL prevention need a regular prevention program for MRONJ, since they may develop bone metastases and be treated with higher doses of BMAs, potentially leading to a high-risk of MRONJ.

ХАРАКТЕРИСТИКА УРОБИОТЫ У ГОСПИТАЛИЗИРОВАННЫХ ДОЛГОЖИТЕЛЕЙ ПОПУЛЯЦИИ РЕСПУБЛИКИ МАРИЙ ЭЛ

Introduction. Nowadays the presence of bacteria in the urine is considered to be the normal condition, that became the foundation of the urinal microflora conception. The characteristics of the urine microflora depend on the region and general health of the population and may change in time. Aim. Our goal was to assess the characteristics of urinary microbiota among hospitalized long livers in comparison to the people of younger age groups living in Mari El Republic. Materials and methods. We used the standard bacteriological analysis of midstream free voiding urine and disc diffusion method. Statistical analysis was performed with the help of chi-square criteria. Totally, 720 hospitalized (during 2011-2018 years in Yoshkar-Ola hospital) patients were included into the analysis. Patients were divided into the three age groups: young (18-59 years old), elderly (60-89 years old), long-livers (90+ years old). Results and discussion. Probability of bacteria detection in the urine varied in the range 56,4% - 86,9% without difference between elderly and long-livers, however elderly and long-livers had significantly higher risk of bacteria detection in the urine compared to the young age group. In female long-livers we found only gram-negative bacteria, therefore the rate of gram-positive bacteria in the urine was significantly lower compared to the young age group (p=0,03). Males had stable rate of gram-positive bacteria in all three age groups. Escherichia coli (56,8%) was the most common potentially pathogenic bacteria found in the urine. The resistance rate to aminoglycosides among all bacteria was 13%, to fluorquinolones — 33,5%. Escherichia coli resistance to aminoglycosides was 9,6%, to fluorquinolones — 29,4%. Conclusion. Long-livers and elderly patients are characterized by the similar probability of bacteria detection in urine. Urine microflora of female long-livers contains no gram-positive bacteria. The prevalence of gram-positive bacteria in male long-livers was stable. Fluoroquinolones are not the drugs of choice for urine infection empiric therapy in our hospital due to the increased rate of resistance over the 10%. In contrast, aminoglycosides may be considered as a first-line empiric therapy. We found no increase of resistance rate among the long livers compared to the patients of younger age groups.

Ultrafast Charge Separation Driven by Torsional Motion in Orthogonal Boron Dipyrromethene Dimer

In this work, the photoinduced charge separation (CS) via symmetry breaking in an orthogonal meso-β-linked boron dipyrromethene (BODIPY) dimer was investigated by polarized transient absorption spectroscopy. The time constant about 0.76 ps of the CS reaction determined in dimethyl sulfoxide is much faster than the solvation dynamics. The observed transient anisotropy of the BODIPY anion band implies that both hole and electron transfers occur with similar probabilities. The bidirectional charge transfer processes suggest that the locally excited state is weakly coupled to the polar solvent, and the solvation coupled excited-state structural relaxation within the BODIPY monomeric unit is rather limited. In combination with the electronic excitation analysis based on time-dependent density-functional theory calculations, we deduced that the CS in the orthogonal BODIPY dimer is enabled via the torsional motion associated with covalently connected BODIPY units, promoting the electronic coupling, and irrelevant to the dynamic solvent relaxation.

Range-wide site-occupancy modeling of Red-winged Blackbirds (Agelaius phoeniceus)

Abstract Globally, habitat loss and land conversion are major drivers of bird population decline. To halt the decline, it is essential that habitat conservation and restoration efforts are based on an understanding of how individual species use their habitat. Here, we examine habitat use by Red-winged Blackbirds (Agelaius phoeniceus) by quantifying their probability of occurrence in different land cover types and in association with varying degrees of habitat modification across most of the species’ range. To do so, we used the citizen-science eBird dataset, in combination with MODIS land cover data to model site occupancy for two breeding seasons and related presence/absence to the Global Human Modification Index. We found that Red-winged Blackbirds occupy rural and suburban habitats at higher probabilities than they do habitats with high levels of urbanization, and at similar or higher probabilities than they do their historic, natural habitats. Furthermore, we found that occurrence probability peaks at intermediate values of the Global Human Modification Index. The results were consistent across most ecoregions and the geographic range of the species, confirming that the Red-winged Blackbird is a suburban-adaptable species, persisting in moderately disturbed environments. Although more research is needed to understand the ecological and evolutionary consequences of this pattern of habitat use, our results provide novel data on Red-winged Blackbird habitat use in the midst of increasing urbanization. More broadly, they provide insight into how common, widespread avian species may be affected by anthropogenic disturbance and highlight the importance of rural and suburban environments in urban ecology and evolution.

A statistical algorithm for outbreak detection in multisite settings: an application to sick leave monitoring.

Public health authorities monitor cases of health-related problems over time using surveillance algorithms that detect unusually high increases in the number of cases, namely aberrations. Statistical aberrations signal outbreaks when further investigation reveals epidemiological significance. The increasing availability and diversity of epidemiological data and the most recent epidemic threats call for more accurate surveillance algorithms that not just detect aberration times but also detect locations. Sick leave data, for instance, can be monitored across companies to identify companies-related aberrations. In this context, we develop an extension to multisite surveillance of a routinely used aberration detection algorithm, the quasi-Poisson regression Farrington Flexible algorithm. The new algorithm consists of a negative-binomial mixed effects regression model with a random effects term for sites and a new reweighting procedure reducing the effect of past aberrations. A wide range of simulations shows that, compared with Farrington Flexible, the new algorithm produces better false positive rates and similar probabilities of detecting genuine outbreaks, for case counts that exceed historical baselines by 3SD. As expected, higher surges lead to lower false positive rates and higher probabilities of detecting true outbreaks. The new algorithm provides better detection of true outbreaks, reaching 100%, when cases exceed eight baseline standard deviations. We apply our algorithm to sick leave rates in the context of COVID-19 and find that it detects the pandemic effect. The new algorithm is easily implementable over a range of contrasting data scenarios, providing good overall performance and new perspectives for multisite surveillance. All the analyses are performed in the R statistical software using the package glmmTMB. The code for performing the analyses and for generating the simulations can be found online at the following link: https://github.com/TomDuchemin/mixed_surveillance. a.noufaily@warwick.ac.uk.

Which dentine analogue material can replace human dentine for crown fatigue test?

To seek dentine analogue materials in combined experimental, analytical, and numerical approaches on the mechanical properties and fatigue behaviours that could replace human dentine in a crown fatigue laboratory test. A woven glass fibre-filled epoxy (NEMA grade G10; G10) and a glass fibre-reinforced polyamide-nylon (30% glass fibre reinforced polyamide-nylon 6,6; RPN) were investigated and compared with human dentine (HD). Flexural strength and elastic modulus (n=10) were tested on beam-shaped specimens via three-point bending, while indentation hardness (n=3) was tested after fracture. Abutment substrates of G10, RPN and HD were prepared and resin-bonded with monolithic lithium disilicate crowns (n=10), then subjected to wet cyclic loading in a step-stress manner (500N initial load, 100N step size, 100,000 cycles per step, 20Hz frequency). Data were statistically analysed using Kruskal-Wallis one-way ANOVA followed by post-hoc comparisons (α=0.05). Survival probability estimation was performed by Mantel-Cox Log-Rank test with 95% confidence intervals. The fatigue failure load (FFL) and the number of cycles until failure (NCF) were evaluated with Weibull statistics. Finite Element Models of the fatigue test were established for stress distribution analysis and lifetime prediction. Fractographic observations were qualitatively analysed. The flexural strength of HD (164.27±14.24MPa), G10 (116.48±5.93MPa), and RPN (86.73±3.56MPa) were significantly different (p<0.001), while no significant difference was observed in their flexural moduli (p=0.377) and the indentation hardness between HD and RPN (p=0.749). The wet cyclic fatigue test revealed comparable mean FFL and NCF of G10 and RPN to HD (p=0.237 and 0.294, respectively) and similar survival probabilities for the three groups (p=0.055). However, RPN promotes higher stability and lower deviation of fatigue test results than G10 in Weibull analysis and FEA. Even though dentine analogue materials might exhibit similar elastic properties and fatigue performance to human dentine, different reliabilities of fatigue on crown-dentine analogues were shown. RPN seems to be a better substrate that could provide higher reliability and predictability of laboratory study results.

Addressing nonresponse bias in forest inventory change estimation using response homogeneity classifications

Estimating amounts of change in forest resources over time is a key function of most national forest inventories (NFI). As this information is used broadly for many management and policy purposes, it is imperative that accurate estimations are made from the survey sample. Robust sampling designs are often used to help ensure representation of the population, but often the full sample is unrealized due to hazardous conditions or possibly lack of land access permission. Potentially, bias may be imparted to the sample if the nonresponse is nonrandom with respect to forest characteristics, which becomes more difficult to assess for change estimation methods that require measurements of the same sample plots at two points in time, i.e., remeasurement. To examine potential nonresponse bias in change estimates, two synthetic populations were constructed: 1) a typical NFI population consisting of both forest and nonforest plots, and 2) a population that mimics a large catastrophic disturbance event within a forested population. Comparisons of estimates under various nonresponse scenarios were made using a standard implementation of post-stratified estimation as well as an alternative approach that groups plots having similar response probabilities (response homogeneity). When using the post-stratified estimators, the amount of change was overestimated for the NFI population and was underestimated for the disturbance population, whereas the response homogeneity approach produced nearly unbiased estimates under the assumption of equal response probability within groups. These outcomes suggest that formal strategies may be needed to obtain accurate change estimates in the presence of nonrandom nonresponse.

The Truth is Out There: Focusing on Smaller to Guess Bigger in Image Classification

In Artificial Intelligence (AI) in general and in Machine Learning (ML) in particular, which are important and integral components of modern Industry 4.0, we often deal with uncertainty, e.g., lack of complete information about the objects we are classifying, recognizing, diagnosing, etc. Traditionally, uncertainty is considered to be a problem especially in the responsible use of AI and ML tools in the smart manufacturing domain. However, in this study, we aim not to fight with but rather to benefit from the uncertainty to improve the classification performance in supervised ML. Our objective is a kind of uncertainty-driven technique to improve the performance of Convolutional Neural Networks (CNNs) for image classification. The intuition behind our suggested “decontextualize-and-extrapolate” approach is as follows: any image not necessarily contains all the needed information for perfect classification; any trained CNN will give for the entire image (with some uncertainty) the probability distribution among possible classes; the same CNN may also give similar probability distribution to the “part” of the image (i.e., with the higher uncertainty); one may discover the trend of the probability distribution change with the change of uncertainty value; a better (refined) probability distribution could be computed from these two distributions as the result of their extrapolation towards the less uncertainty. In this paper, we suggested several ways and corresponding analytics to discover reasonable part(s) of the images and to make the extrapolation to get better (refined) image classification results. We have considered image representation at the level of pixels as well as at the level of the discovered features. Our preliminary experiments show that the suggested refinement techniques (applied during the testing phase of the CNNs) can improve their classification performance.

A combined 3D-atomic/nanoscale comprehension and ab initio computation of iron carbide structures tailored in Q&P steels via Si alloying.

The essences of the quenching and partitioning (Q&P) process are to stabilize the finely divided retained austenite (RA) via carbon (C) partitioning from supersaturated martensite during partitioning. Competitive reactions, i.e., transition carbide precipitation, C segregation, and decomposition of austenite, might take place concurrently during partitioning. In order to maintain the high volume fraction of RA, it is crucial to suppress the carbide precipitation sufficiently. Since silicon (Si) in the cementite θ (Fe3C) is insoluble, alloying Si in adequate concentrations prolongs its precipitation during the partitioning step. Consequently, C partitioning facilitates the desired chemical stabilization of RA. To elucidate the mechanisms of formation of transition η (Fe2C) carbides as well as cementite, θ (Fe3C), besides the transformation of transition carbides to more stable θ during the quenching and partitioning (Q&P) process, samples of 0.4 wt% C steels tailored with different Si contents were extensively characterized for microstructural evolution at different partitioning temperatures (TP) using high resolution transmission electron microscopy (HR-TEM) and three-dimensional atom probe tomography (3D-APT). While 1.5 wt% Si in the steel allowed only the formation of η carbides even at a high TP of 300 °C, reduction in Si content to 0.75 wt% only partially stabilized η carbides, allowing limited η → θ transformation. With 0.25 wt% Si, only θ was present in the microstructure, suggesting a η → θ transition during the early partitioning stage, followed by coarsening due to enhanced growth kinetics at 300 °C. Although η carbides precipitated in martensite under paraequilibrium conditions at 200 °C, θ carbides precipitated under negligible partitioning local equilibrium conditions at 300 °C. Competition with the formation of orthorhombic η and θ precipitation further examined via ab initio (density functional theory, DFT) computation and a similar probability of formation/thermodynamic stability were obtained. With an increase in Si concentration, the cohesive energy decreased when Si atoms occupied C positions, indicating decreasing stability. Overall, the thermodynamic prediction was in accord with the HR-TEM and 3D-APT results.

Developing a comorbidity score in cancer patients using healthcare utilization databases during the COVID-19 pandemic: An experience from Italy.

A strong relationship has been observed between comorbidities and the risk of severe/fatal COVID-19 manifestations, but no score is available to evaluate their association in cancer patients. To make up for this lacuna, we aimed to develop a comorbidity score for cancer patients, based on the Lombardy Region healthcare databases. We used hospital discharge records to identify patients with a new diagnosis of solid cancer between February and December 2019; 61 comorbidities were retrieved within 2 years before cancer diagnosis. This cohort was split into training and validation sets. In the training set, we used a LASSO-logistic model to identify comorbidities associated with the risk of developing a severe/fatal form of COVID-19 during the first pandemic wave (March-May 2020). We used a logistic model to estimate comorbidity score weights and then we divided the score into five classes (<=-1, 0, 1, 2-4, >=5). In the validation set, we assessed score performance by areas under the receiver operating characteristic curve (AUC) and calibration plots. We repeated the process on second pandemic wave (October-December 2020) data. We identified 55,425 patients with an incident solid cancer. We selected 21 comorbidities as independent predictors. The first four score classes showed similar probability of experiencing the outcome (0.2% to 0.5%), while the last showed a probability equal to 5.8%. The score performed well in both the first and second pandemic waves: AUC 0.85 and 0.82, respectively. Our results were robust for major cancer sites too (i.e., colorectal, lung, female breast, and prostate). We developed a high performance comorbidity score for cancer patients and COVID-19. Being based on administrative databases, this score will be useful for adjusting for comorbidity confounding in epidemiological studies on COVID-19 and cancer impact.

Effect of Resin Cement at Different Thicknesses on the Fatigue Shear Bond Strength to Leucite Ceramic.

This in vitro study was performed to evaluate fatigue survival by shear test in the union of leucite-reinforced feldspathic ceramic using different cement thicknesses. Leucite-reinforced glass ceramics blocks were sectioned in 2-mm thick slices where resin cylinders were cemented. The samples were distributed in two experimental groups (n = 20) according to the cement thickness (60 and 300 μm). The specimens of each group were submitted to the stepwise fatigue test in the mechanical cycling machine under shear stress state, with a frequency of 2 Hz, a step-size of 0.16 bar, starting with a load of 31 N (1.0 bar) and a lifetime of 20,000 cycles at each load step. The samples were analyzed in a stereomicroscope and scanning electron microscopy to determine the failure type. There is no significant difference between the mean values of shear bond strength according to both groups. Log-rank (p = 0.925) and Wilcoxon (p = 0.520) tests revealed a similar survival probability in both cement layer thicknesses according to the confidence interval (95%). The fracture analysis showed that the mixed failure was the most common failure type in the 300-μm thickness group (80%), while adhesive failure was predominant in the 60-μm thickness group (67%). The different cement thicknesses did not influence the leucite ceramic bonding in fatigue shear testing; however, the thicker cement layer increased the predominance of the ceramic material failure. The resin cement thicknesses bonded to leucite ceramic did not influence the long-term interfacial shear bond strength, although thicker cement layer increased the ceramic material cohesive failure. Regardless the cement layer thickness, the shear bond strength lifetime decreases under fatigue.