Optimizing Retrieving Performance of an Automated Warehouse for Unconventional Stock Keeping Units

In recent years, the diffusion of automated warehouses in different industrial sectors has fostered the design of more complex automated storages and handling solutions. These circumstances, from a technological point of view, have led to the development of automated warehouses that are very different from the classic pallet Automated Storage and Retrieval Systems (AS/RS), both in terms of design and operating logic. A context in which these solutions have spread is the steel sector. Warehouses with innovative layouts and operating logics have been designed to move metal bundles of different sizes, weights and quality levels, instead of standard, interchangeable stock keeping units. Moreover, picking is often not allowed in these warehouses, due to the configuration of the loading units. In this work we propose a meta-heuristic algorithm based on the Simulated Annealing (SA) procedure, which aims to optimize performance during the retrieving phase of an automated warehouse for metal bundles. The algorithm translates the customers’ requests, expressed in terms of item code, quality and weight into a list of jobs. The goal is to optimize the retrieving performance, measured in missions per hour, minimizing the deviations in quality and weight between customer request and the material retrieved. For the validation, a simulation model of an existing warehouse has been created and the performance of the algorithm tested on the simulation model has been compared with the current performance of the warehouse

Bayes pulmonary embolism assisted-diagnosis: a new expert system for clinical use

Background: The diagnosis of pulmonary embolism demands flexible decision models, both for the presence of clinical confounders and for the variability of local diagnostic resources. As Bayesian networks fully meet this requirement, Bayes Pulmonary embolism Assisted Diagnosis (BayPAD), a probabilistic expert systems focused on pulmonary embolism, was developed. Methods: To quantitatively validate and improve BayPAD, the system was applied to 750 patients from a prospective study done in an Italian tertiary hospital where the true pulmonary embolism status was confirmed using pulmonary angiography or ruled out with a lung scan. The proportion of correct diagnoses made by BayPAD (accuracy) and the correctness of the pulmonary embolism probabilities predicted by the model (calibration) were calculated. The calibration was evaluated according to the Cox regression-calibration model. Results: Before refining the model, accuracy was 88.6%. Once refined, accuracy was 97.2% and 98%, respectively, in the training and validation samples. According to Cox analysis, calibration was satisfactory, despite a tendency to exaggerate the effect of the findings on the probability of pulmonary embolism. The lack of some investigations (like Spiral computed tomographic scan and Lower limbs doppler ultrasounds) in the pool of available data often prevents BayPAD from reaching the diagnosis without invasive procedures. Conclusions: BayPAD offers clinicians a flexible and accurate strategy to diagnose pulmonary embolism. Simple to use, the system performs case-based reasoning to optimise the use of resources available within a particular hospital. Bayesian networks are expected to have a prominent role in the clinical management of complex diagnostic problems in the near future

Calibration Belt for Quality-of-Care Assessment Based on Dichotomous Outcomes

Prognostic models applied in medicine must be validated on independent samples, before their use can be recommended. The assessment of calibration, i.e., the model's ability to provide reliable predictions, is crucial in external validation studies. Besides having several shortcomings, statistical techniques such as the computation of the standardized mortality ratio (SMR) and its confidence intervals, the Hosmer–Lemeshow statistics, and the Cox calibration test, are all non-informative with respect to calibration across risk classes. Accordingly, calibration plots reporting expected versus observed outcomes across risk subsets have been used for many years. Erroneously, the points in the plot (frequently representing deciles of risk) have been connected with lines, generating false calibration curves. Here we propose a methodology to create a confidence band for the calibration curve based on a function that relates expected to observed probabilities across classes of risk. The calibration belt allows the ranges of risk to be spotted where there is a significant deviation from the ideal calibration, and the direction of the deviation to be indicated. This method thus offers a more analytical view in the assessment of quality of care, compared to other approaches

Clinical trajectories of individuals with severe mental illness continuing and discontinuing long-acting antipsychotics: a one-year mirror-image analysis from the STAR Network Depot study

Evidence on long-acting antipsychotics (LAIs) in unselected populations with severe mental illness is scant. In this mirror-image study, we compared multiple clinical outcomes 1 year before and after a first LAI prescription in adults with severe mental illness, describing clinical trajectories of LAI continuers and discontinuers. We compared LAI continuers and discontinuers through Mann–Whitney U test, Kaplan–Meier survival curves, regression for interval-censored data, and a maximum-likelihood mixed-model with individual random-effect and time as predictor. Of the 261 participants analyzed, 71.3% had schizophrenia-spectrum disorders, and 29.5% discontinued the LAI before 1 year. At baseline, LAI discontinuers had a shorter illness duration, lower attitude and adherence scores. The mirror-image analysis showed reduced hospital admissions only for LAI continuers. Over time, continuers spent less days hospitalized, but had more adverse events and more antipsychotics prescribed, with higher overall doses. In conclusion, this study shows that LAIs might be beneficial in unselected patient populations, provided that adherence is maintained. LAI continuers spent less time hospitalized, but received more antipsychotics and suffered from more cumulative adverse events over time. Therefore, the choice of initiating and maintaining a LAI should be carefully weighed on a case-by-case basis

Clinical trajectories of individuals with severe mental illness continuing and discontinuing long-acting antipsychotics: a one-year mirror-image analysis from the STAR Network Depot study

Evidence on long-acting antipsychotics (LAIs) in unselected populations with severe mental illness is scant. In this mirror-image study, we compared multiple clinical outcomes 1 year before and after a first LAI prescription in adults with severe mental illness, describing clinical trajectories of LAI continuers and discontinuers. We compared LAI continuers and discontinuers through Mann-Whitney U test, Kaplan-Meier survival curves, regression for interval-censored data, and a maximum-likelihood mixed-model with individual random-effect and time as predictor. Of the 261 participants analyzed, 71.3% had schizophrenia-spectrum disorders, and 29.5% discontinued the LAI before 1 year. At baseline, LAI discontinuers had a shorter illness duration, lower attitude and adherence scores. The mirror-image analysis showed reduced hospital admissions only for LAI continuers. Over time, continuers spent less days hospitalized, but had more adverse events and more antipsychotics prescribed, with higher overall doses. In conclusion, this study shows that LAIs might be beneficial in unselected patient populations, provided that adherence is maintained. LAI continuers spent less time hospitalized, but received more antipsychotics and suffered from more cumulative adverse events over time. Therefore, the choice of initiating and maintaining a LAI should be carefully weighed on a case-by-case basis

Effects of intermediate scales on renormalization group running of fermion observables in an SO(10) model

In the context of non-supersymmetric SO(10) models, we analyze the renormalization group equations for the fermions (including neutrinos) from the GUT energy scale down to the electroweak energy scale, explicitly taking into account the effects of an intermediate energy scale induced by a Pati--Salam gauge group. To determine the renormalization group running, we use a numerical minimization procedure based on a nested sampling algorithm that randomly generates the values of 19 model parameters at the GUT scale, evolves them, and finally constructs the values of the physical observables and compares them to the existing experimental data at the electroweak scale. We show that the evolved fermion masses and mixings present sizable deviations from the values obtained without including the effects of the intermediate scale.Comment: Comments: 20 pages, 3 figures. Final version published in JHE

increased mean corpuscular volume of red blood cells predicts response to metronomic capecitabine and cyclophosphamide in combination with bevacizumab

Abstract Background There is an urgent need for the identification of commonly assessable predictive factors in the treatment of patients with metastatic breast cancer. Methods During the course of a treatment including low dose metronomic oral cyclophosphamide and capecitabine plus i.v. bevacizumab (plus erlotinib in one third of the patients) for metastatic breast cancer, we observed that a relevant number of patients developed repeatedly elevated levels of mean corpuscular volume (MCV) of red blood cells without a significant fall in hemoglobin levels. We conducted a retrospective analysis on these 69 patients to evaluate if the increase in MCV could be associated to tumor response. Results During the course of treatment 42 out of 69 patients (61%) developed macrocytosis. Using Cox proportional hazards modeling that incorporated macrocytosis (MCV≥100 fl) as a time-dependent covariate, macrocytosis resulted in a halved risk of disease progression (HR 0.45; 95% CI, 0.22–0.92, p-value 0.028). In a landmark analysis limited to patients with no sign of progression after 24 weeks of treatment, median time to progression was 72 weeks (48 weeks after landmark) in patients who had developed macrocytosis, and 43 weeks (19 weeks after landmark) in patients who had not (p = 0.023). Conclusion Macrocytosis inversely related to risk of disease progression in patients treated with metronomic capecitabine plus cyclophosphamide and bevacizumab for metastatic breast cancer. This finding may be explained through thymidylate synthase inhibition by capecitabine. Whether bevacizumab has a role in determining macrocytosis, similarly to what happens with sunitinib, has to be further investigated. If other studies will confirm our findings, macrocytosis might be used as an early marker of response during metronomic treatment with capecitabine and cyclophosphamide with or without bevacizumab

Gauge invariant finite size spectrum of the giant magnon

It is shown that the finite size corrections to the spectrum of the giant magnon solution of classical string theory, computed using the uniform light-cone gauge, are gauge invariant and have physical meaning. This is seen in two ways: from a general argument where the single magnon is made gauge invariant by putting it on an orbifold as a wrapped state obeying the level matching condition as well as all other constraints, and by an explicit calculation where it is shown that physical quantum numbers do not depend on the uniform light-cone gauge parameter. The resulting finite size effects are exponentially small in the $R$-charge and the exponent (but not the prefactor) agrees with gauge theory computations using the integrable Hubbard model.Comment: 12 pages, some clarifications, references adde