A Generalized Bin Packing Problem for parcel delivery in last-mile logistics

Abstract In this paper, we present a new problem arising at a tactical level of setting a last-mile parcel delivery service in a city by considering different Transportation Companies (TC), which differ in cost and service quality. The courier must decide which TCs to select for the service in order to minimize the total cost and maximize the total service quality. We show that the problem can be modeled as a new packing problem, the Generalized Bin Packing Problem with bin-dependent item profits (GBPPI), where the items are the parcels to deliver and the bins are the TCs. The aim of the GBPPI is to select the appropriate fleet from TCs and determine the optimal assignment of parcels to vehicles such that the overall net cost is minimized. This cost takes into account both transportation costs and service quality. We provide a Mixed Integer Programming formulation of the problem, which is the starting point for the development of efficient heuristics that can address the GBPPI for instances involving up to 1000 items. Extensive computational tests show the accuracy of the proposed methods. Finally, we present a last-mile logistics case study of an international courier which addresses this problem

Software Tampering Detection using AOP and mobile code

Assuring that a given code is faithfully executed with defined parameters and constraints on an un-trusted host is an open problem, which is especially important in the context of computing over communications networks. This work evaluates applicability of Aspect-Oriented Programming to the problem of remotely authenticating code during execution, which aims at assuring that the software is not maliciously tampered prior to and during execution. A flow of idiosyncratic signatures is continuously generated and associated to data transmitted by a function that is encapsulated in an aspect and whose execution is subordinated to the proper execution of the software being authenticated. The flow of signatures is validated by a remote component

Handling missing continuous outcome data in a Bayesian network meta-analysis

Background: A Bayesian network meta-analysis (NMA) model is a statistical method aimed at estimating the relative effects of multiple interventions against the same disease. The method has recently gained prominence, leading to the synthesis of the evidence regarding rank probabilities for each treatment. In several cases, an NMA is performed excluding incomplete data of studies retrieved through a systematic review, resulting in a loss of precision and power.  Methods: There are several methods for handling missing or incomplete data in an NMA framework, especially for continuous outcomes. In certain cases, only baseline and follow-up measurements are available; in this framework, to obtain data regarding mean changes, it is necessary to consider the pre-post study correlation. In this context, in a Bayesian setting, several authors suggest imputation strategies for pre-post correlation. In other cases, a variability measure associated with a mean change score might be unavailable. Different imputation methods have been suggested, such as those based on maximum standard deviation imputation. The purpose of this study is to verify the robustness of Bayesian NMA models concerning different imputation strategies through simulations.  Results: Simulation results show that the bias is notably small for every scenario, confirming that rankings provided by models are robust concerning different imputation methods in several heterogeneity-correlation settings.  Conclusions: This NMA method seems to be more robust to missing data imputation when data reported in different studies are generated in a low-heterogeneity scenario. The NMA method seems to be more robust to missing value imputation if the expectation of the prior distribution, defined on the heterogeneity parameter, approaches the true value of the variability across studies.&nbsp

Comparative Effectiveness of DPP-4 Inhibitors Versus Sulfonylurea for the Treatment of Type 2 Diabetes in Routine Clinical Practice: A Retrospective Multicenter Real-World Study

Introduction: DPP-4 inhibitors (DPP4i) and sulfonylureas are popular second-line therapies for type 2 diabetes (T2D), but there is a paucity of real-world studies comparing their effectiveness in routine clinical practice. Methods: This was a multicenter retrospective study on diabetes outpatient clinics comparing the effectiveness of DPP4i versus gliclazide extended release. The primary endpoint was change from baseline in HbA1c. Secondary endpoints were changes in fasting plasma glucose, body weight, and systolic blood pressure. Automated software extracted data from the same clinical electronic chart system at all centers. Propensity score matching (PSM) was used to generate comparable cohorts to perform outcome analysis. Results: We included data on 2410 patients starting DPP4i and 1590 patients starting gliclazide (mainly 30–60 mg/day). At baseline, the two groups differed in disease duration, body weight, blood pressure, HbA1c, fasting glucose, HDL cholesterol, triglycerides, liver enzymes, eGFR, prevalence of microangiopathy, and use of metformin. Among DPP4i molecules, no difference in glycemic effectiveness was detected. In matched cohorts (n = 1316/group), patients starting DPP4i, as compared with patients starting gliclazide, experienced greater reductions in HbA1c (− 0.6% versus − 0.4%; p < 0.001), fasting glucose (− 14.1 mg/dl versus − 8.8 mg/dl; p = 0.007), and body weight (− 0.4 kg versus − 0.1 kg; p = 0.006) after an average 6 months follow-up. DPP4i improved glucose control more than gliclazide, especially in patients who had failed with other glucose-lowering medications or were on basal insulin. Conclusions: This large retrospective real-world study shows that, in routine clinical practice, starting a DPP4i allows better glycemic control than starting low-dose gliclazide. Funding: The Italian Diabetes Society, with external support from AstraZeneca

A Method for Manufacturing Oncological Phantoms for the Quantification of 18F-FDG PET and DW-MRI Studies

The aim of this work was to develop a method to manufacture oncological phantoms for quantitation purposes in 18F-FDG PET and DW-MRI studies. Radioactive and diffusion materials were prepared using a mixture of agarose and sucrose radioactive gels. T2 relaxation and diffusion properties of gels at different sucrose concentrations were evaluated. Realistic oncological lesions were created using 3D-printed plastic molds filled with the gel mixture. Once solidified, gels were extracted from molds and immersed in a low-radioactivity gel simulating normal background tissue. A breast cancer phantom was manufactured using the proposed method as an exploratory feasibility study, including several realistic oncological configurations in terms of both radioactivity and diffusion. The phantom was acquired in PET with 18F-FDG, immediately after solidification, and in DW-MRI the following day. Functional volumes characterizing the simulated BC lesions were segmented from PET and DW-MRI images. Measured radioactive uptake and ADC values were compared with gold standards. Phantom preparation was straightforward, and the time schedule was compatible with both PET and MRI measurements. Lesions appeared on 18F-FDG PET and DW-MRI images as expected, without visible artifacts. Lesion functional parameters revealed the phantom’s potential for validating quantification methods, in particular for new generation hybrid PET-MRI systems

A survey on Biostatisticians Serving in the Italian Ethics Committees

Background. Italian ethics committees (ECs) have the responsibility for evaluating and monitoring clinical research. Methods. An electronic survey targeted to the biostatisticians operating in the 95 ECs in Italy, was launched in November 2016. Several aspects were explored such as education, job title, training in biostatistics and experience in the evaluation of protocols within the EC. Results. Seventy case report forms were returned (74%), and the response rate was highest for ECs located in the South (78%) and lowest in the North (51%). The biostatisticians in the respondent ECs were prevalently male, aged 50-60 years, with postgraduate education in medical specialties and statistics. The annual workload varied depending on the type of institution and geographical area, with an annual median number of protocols examined ranging from 80 in hospital ECs to 198 in university hospital ECs, and from 80 to 108, in the South and the Centre, respectively. Of these, 40% were observational study protocols. The EC biostatisticians proposed to reject 5% of protocols and to suspend with the request of clarification or amendments 10%. Only 61% and 79% of these opinions, respectively, were regarded as binding by the other EC members. Conclusion. The biostatistician will not be able to play a significant role in the EC as long as the required skill-set remains vague and his/her opinion on a protocol is underrated