Background
This study aimed to externally validate the Iwate scoring model and its prognostic value for predicting the risks of intra- and postoperative complications of laparoscopic liver resection.
...Methods
Consecutive patients who underwent pure laparoscopic liver resection between 2008 and 2019 at a single tertiary center were included. The Iwate scores were calculated according to the original proposition (four difficulty levels based on six indices). Intra- and postoperative complications were compared across difficulty levels. Fitting the obtained data to the cumulative density function of the Weibull distribution and a linear function provided the mean risk curves for intra- and postoperative complications, respectively.
Results
The difficulty levels of 142 laparoscopic liver resections were scored as low, intermediate, advanced, and expert level in 41 (28.9%), 53 (37.3%), 32 (22.5%), and 16 (11.3%) patients, respectively. Intraoperative complications were detected in 26 (18.3%) patients and its rates (2.4%, 7.5%, 34.3%, and 62.5%) increased gradually with statistically significant values among difficulty levels (
P
˂ 0.001). Major postoperative complications occurred in 21 (14.8%) patients and its rates (4.8%, 5.6%, 28.1%, 43.7%;
P
˂ 0.001) showed the same trend as for intraoperative complications. Then, the mean risk curves of both complications were obtained. Due to outliers, a new threshold for a
tumor size
index was proposed at 38 mm. The repeated analysis showed improved results.
Conclusions
The Iwate scoring model predicts the probability of complications across difficulty levels. Our proposed
tumor size
threshold (38 mm) improves the quality of the prediction. The model is upgraded by a probability of complications for every difficulty score.
Urban freight deliveries are often subject to many access restrictions which creates the need to establish a system of loading bays and to split the last mile delivery into driving and walking parts. ...A new model based on hard and soft clustering approach is developed to solve the loading bay assignment problem for efficient vehicle routing and walking in last mile delivery. The flexibility of the model is provided by the soft clustering approach based on different membership degrees of customers to loading bays. Especially for instances with large numbers of loading bays, soft clustering seems to give better results, it leads to higher flexibility of city logistics systems, minimal driving distances, and adequately short walking paths, which contribute to the goal of reaching sustainable urban freight deliveries.
•Extensive experimental field investigations of track degradation were carried out.•Heterogeneity of sub-layers and geometrical irregularities influences degradation.•Favorable features of wooden ...sleepers (lower stiffness, imprinting of ballast).•CAE ANN reveals nonlinear influence of influential parameters on track degradation.•Weights of influential parameters indicate welds as the most important parameter.
Several various examples of anomalies on ballast railway tracks resulting in accelerated degradation of railway sleepers and ballast layer are described in the paper. Initially, some locations on the Slovenian railway network (SRN) where the degradation occurs were identified. Afterwards, various experimental field investigations (georadar, geometry measurements, measurements of displacements and accelerations on the track, visual assessment of ballast degradation) have been used to measure the characteristics of the railway track and the parameters of its behavior. Based on the experimentally obtained data a simplified numerical model which interconnects the individual measured and estimated parameters of the railway track and also the processes of further degradation has been developed using the artificial neural network. Influential factors for the model’s individual parameters influencing the degradation were identified. The proposed model is able to assist in the evaluation of critical areas on the railway infrastructure and further enables a better understanding of the process and prediction/estimation of degradation of railway sleepers and ballast.
In this paper, the Conditional Average Estimator artificial neural network (CAE ANN) was used to analyze the influence of chemical composition in conjunction with selected process parameters on the ...yield strength and elongation of an extruded 6082 aluminum alloy (AA6082) profile. Analysis focused on the optimization of mechanical properties as a function of casting temperature, casting speed, addition rate of alloy wire, ram speed, extrusion ratio, and number of extrusion strands on one side, and different contents of chemical elements, i.e., Si, Mn, Mg, and Fe, on the other side. The obtained results revealed very complex non-linear relationships between all of these parameters. Using the proposed approach, it was possible to identify the combinations of chemical composition and process parameters as well as their values for a simultaneous increase of yield strength and elongation of extruded profiles. These results are a contribution of the presented study in comparison with published research results of similar studies in this field. Application of the proposed approach, either in the research and/or in industrial aluminum production, suggests a further increase in the relevant mechanical properties.
Background and Objectives: The issue of a missing variable precludes the external validation of many prognostic models. For example, the Liverpool score predicts the survival of patients undergoing ...surgical therapy for colorectal liver metastases, but it includes the neutrophil–lymphocyte ratio, which cannot be measured retrospectively. Materials and Methods: We aimed to find the most appropriate replacement for the neutrophil–lymphocyte ratio. Survival analysis was performed on data representing 632 liver resections for colorectal liver metastases from 2000 to 2020. Variables associated with the Liverpool score, C-reactive protein, albumins, and fibrinogen were ranked. The rankings were performed in four ways: The first two were based on the Kaplan-Meier method (log-rank statistics and the definite integral IS between two survival curves). The next method of ranking was based on univariate and multivariate Cox regression analyses. Results: The ranks were as follows: the radicality of liver resection (rank 1), lymph node infiltration of primary colorectal cancer (rank 2), elevated C-reactive protein (rank 3), the American Society of Anesthesiologists Classification grade (rank 4), the right-sidedness of primary colorectal cancer (rank 5), the multiplicity of colorectal liver metastases (rank 6), the size of colorectal liver metastases (rank 7), albumins (rank 8), and fibrinogen (rank 9). Conclusions: The ranking methodologies resulted in almost the same ranking order of the variables. Elevated C-reactive protein was ranked highly and can be considered a relevant replacement for the neutrophil–lymphocyte ratio in the Liverpool score. These methods are suitable for ranking variables in similar models for medical research.
The conditions for increasing the hot workability and extending the temperature range for the safe hot working of M2 high-speed steel (HSS) were studied and revealed. This was enabled by combination ...of two approaches, i.e. results obtained by an analysis of so individual as well as spatial influences of chemical elements on the hot workability using a conditional average estimator neural networks in combination with the results obtained from hot-compression tests that revealed the appropriate soaking conditions. The Latin Hypercube Sampling technique was used to model the uncertainty of the collected data used in the analysis. The obtained results reveal new, surprisingly complex, typically spatial and (highly) non-linear relationships between the chemical elements and the hot workability of M2 HSS, i.e. common mutual influence of carbon, carbide-forming elements as well as elements, i.e. Si, Mn and Co, which indirectly influence the formation of carbides. Further also new allowed upper limits for contents of some harmful elements like S, P, Al, Sb, Cu, Sn, As, Ni, etc. at which transition from higher to lower workability takes place were revealed. Finally, by applying a specially developed procedure for hot-compression tests the appropriate soaking time and temperature were assessed. New findings explain and considerably improve the intrinsic hot workability and extend the temperature range for safe hot working at its upper and lower limits.
This study aimed to externally validate and upgrade the recent difficulty scoring system (DSS) proposed by Halls et al. to predict intraoperative complications (IOC) during laparoscopic liver ...resection (LLR).
The DSS was validated in a cohort of 128 consecutive patients undergoing pure LLRs between 2008 and 2019 at a single tertiary referral center. The validated DSS includes four difficulty levels based on five risk factors (neoadjuvant chemotherapy, previous open liver resection, lesion type, lesion size and classification of resection). As established by the validated DSS, IOC was defined as excessive blood loss (> 775 mL), conversion to an open approach and unintentional damage to surrounding structures. Additionally, intra- and postoperative outcomes were compared according to the difficulty levels with usual statistic methods. The same five risk factors were used for validation done by linear and advanced nonlinear (artificial neural network) models. The study was supported by mathematical computations to obtain a mean risk curve predicting the probability of IOC for every difficulty score.
The difficulty level of LLR was rated as low, moderate, high and extremely high in 36 (28.1%), 63 (49.2%), 27 (21.1%) and 2 (1.6%) patients, respectively. IOC was present in 23 (17.9%) patients. Blood loss of >775 mL occurred in 8 (6.2%) patients. Conversion to open approach was required in 18 (14.0%) patients. No patients suffered from unintentional damage to surrounding structures. Rates of IOC (0, 9.5, 55.5 and 100%) increased gradually with statistically significant value among difficulty levels (P < 0.001). The relations between the difficulty level, need for transfusion, operative time, hepatic pedicle clamping, and major postoperative morbidity were statistically significant (P < 0.05). Linear and nonlinear validation models showed a strong correlation (correlation coefficients 0.914 and 0.948, respectively) with the validated DSS. The Weibull cumulative distribution function was used for predicting the mean risk probability curve of IOC.
This external validation proved this DSS based on patient's, tumor and surgical factors enables us to estimate the risk of intra- and postoperative complications. A surgeon should be aware of an increased risk of complications before starting with more complex procedures.
In regions exposed to floods followed by cold weather, brick masonry as a structural basis of the building envelope can be damaged due to the accompanying phenomenon of freezing and thawing. The main ...purpose of the article is the development of a mathematical model able to predict the chosen mechanical parameters and damage index of brick wallets for a given number of freeze-thaw cycles. For this, a statistical model derived from experimental data is used. As a result, regression curves for Young’s modulus and ductility for two types of mortar are obtained. Furthermore, fragility curves for ductility and also the damage index, which is based on displacement ductility, are presented. The obtained results enable probabilistic risk assessments in the case of deteriorated ductility and increased damage on brick masonry due to freeze–thaw cycles.
Reported is a relationship between a profile edge cracking during hot rolling of AISI D2 tool steel and material and processing parameters. Several months of observation of industrial hot rolling was ...done for neural network analysis and complemented with equilibrium thermodynamics calculations and laboratory hot deformation tests. Industrial results, in general, show that for the same chemical composition, hot rolling yield decreases with an increased profile aspect ratio. Cr content is significant for the soaking and strongly correlated with a hot workability at upper and lower limits of the hot working temperature range. Laboratory hot compression tests were employed to determine the optimal soaking temperature and to study hot workability to expand safe hot working temperature window.
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