Modelling dynamic programming-based global constraints in constraint programming

Dynamic Programming (DP) can solve many complex problems in polynomial or pseudo-polynomial time, and it is widely used in Constraint Programming (CP) to implement powerful global constraints. Implementing such constraints is a nontrivial task beyond the capability of most CP users, who must rely on their CP solver to provide an appropriate global constraint library. This also limits the usefulness of generic CP languages, some or all of whose solvers might not provide the required constraints. A technique was recently introduced for directly modelling DP in CP, which provides a way around this problem. However, no comparison of the technique with other approaches was made, and it was missing a clear formalisation. In this paper we formalise the approach and compare it with existing techniques on MiniZinc benchmark problems, including the flow formulation of DP in Integer Programming. We further show how it can be improved by state reduction methods

Stochastic dynamic programming heuristic for the (R, s, S) policy parameters computation

The (R, s, S) is a stochastic inventory control policy widely used by practitioners. In an inventory system managed according to this policy, the inventory is reviewed at instant R; if the observed inventory position is lower than the reorder level s an order is placed. The order's quantity is set to raise the inventory position to the order-up-to-level S. This paper introduces a new stochastic dynamic program (SDP) based heuristic to compute the (R, s, S) policy parameters for the non-stationary stochastic lot-sizing problem with backlogging of the excessive demand, fixed order and review costs, and linear holding and penalty costs. In a recent work, Visentin et al. (2021) present an approach to compute optimal policy parameters under these assumptions. Our model combines a greedy relaxation of the problem with a modified version of Scarf's (s, S) SDP. A simple implementation of the model requires a prohibitive computational effort to compute the parameters. However, we can speed up the computations by using K-convexity property and memorisation techniques. The resulting algorithm is considerably faster than the state-of-the-art, extending its adoptability by practitioners. An extensive computational study compares our approach with the algorithms available in the literature

Accuracy of a CGM Sensor in Pediatric Subjects With Type 1 Diabetes. Comparison of Three Insertion Sites: Arm, Abdomen, and Gluteus

Patients with diabetes, especially pediatric ones, sometimes use continuous glucose monitoring (CGM) sensor in different positions from the approved ones. Here we compare the accuracy of Dexcom\uae G5 CGM sensor in three different sites: abdomen, gluteus (both approved) and arm (off-label)

Modeling Doxorubicin Pharmacokinetics in Multiple Myeloma Suggests Mechanism of Drug Resistance

Objective: Multiple myeloma (MM) is a plasma cell malignancy often treated with chemotherapy drugs. Among these, doxorubicin (DOXO) is commonly employed, sometimes in combined-drug therapies, but it has to be optimally administered in order to maximize its efficacy and reduce possible side effects. To support DOXO studies and treatment optimization, here we propose an experimental/modeling approach to establish a model describing DOXO pharmacokinetics (PK) in MM cells. Methods: A series of in vitro experiments were performed in MM1R and MOLP-2 cells. DOXO was administered at two dosages (200 nM, 450 nM) at [Formula: see text]=0 and removed at [Formula: see text]=3 hrs. Intracellular DOXO concentration was measured via fluorescence microscopy during both drug uptake ([Formula: see text]=0-3 hrs) and release phases ([Formula: see text]=3-8 hrs). Four PK candidate models were identified, and were compared and selected based on their ability to describe DOXO data and numerical parameter identification. Results: The most parsimonious model consists of three compartments describing DOXO distribution between the extracellular space, the cell cytoplasm and the nucleus, and defines the intracellular DOXO efflux rate through a Hill function, simulating a threshold/saturation drug resistance mechanism. This model predicted DOXO data well in all the experiments and provided precise parameter estimates (mean ± standard deviation coefficient of variation: 15.8±12.2%). Conclusions: A reliable PK model describing DOXO uptake and release in MM cells has been successfully developed. Significance: The proposed PK model, once integrated with DOXO pharmacodynamics, has the potential of allowing the study and the optimization of DOXO treatment strategies in MM

Combined Treatment of Cancer Cells Using Allyl Palladium Complexes Bearing Purine-Based NHC Ligands and Molecules Targeting MicroRNAs miR-221-3p and miR-222-3p: Synergistic Effects on Apoptosis

Combined treatments employing lower concentrations of different drugs are used and studied to develop new and more effective anticancer therapeutic approaches. The combination therapy could be of great interest in the controlling of cancer. Regarding this, our research group has recently shown that peptide nucleic acids (PNAs) that target miR-221 are very effective and functional in inducing apoptosis of many tumor cells, including glioblastoma and colon cancer cells. Moreover, in a recent paper, we described a series of new palladium allyl complexes showing a strong antiproliferative activity on different tumor cell lines. The present study was aimed to analyze and validate the biological effects of the most active compounds tested, in combination with antagomiRNA molecules targeting two miRNAs, miR-221-3p and miR-222-3p. The obtained results show that a “combination therapy”, produced by combining the antagomiRNAs targeting miR-221-3p, miR-222-3p and the palladium allyl complex 4d, is very effective in inducing apoptosis, supporting the concept that the combination treatment of cancer cells with antagomiRNAs targeting a specific upregulated oncomiRNAs (in this study miR-221-3p and miR-222-3p) and metal-based compounds represents a promising therapeutic strategy to increase the efficacy of the antitumor protocol, reducing side effects at the same time

From single tests to a test-chain: A comprehensive approach for evaluating the interaction between the building envelope and the IEQ

In recent years building envelope systems have become increasingly more com-plex. Especially in high-performance low-carbon buildings, envelopes comprise several passive and active components such as advanced membranes, mechanical ventilation machines and integrated photovoltaics that must be mutually optimized to ensure a global elevated performance. One of the key expectations from these innovative envelopes is better capabilities of providing highly comfortable and healthy indoor environments while using as little energy as possible. However, the complexity of such envelopes poses two major challenges: (i) standard assessment procedures might not be usable to evaluate them either because these do not fully capture their potential or be-cause the complexity of product makes the standard test unfeasible, and (ii) multiple indoor environmental quality (IEQ) domains are simultaneously affected by these envelopes, and thus complementary tests in different domain are needed to ensure that a benefit in one domain does not lead to issues in others. For this reason, a test-chain for a thorough energy demand, indoor occupants’ comfort, and behaviour analysis performance has been implemented. It comprises a set of labs and additional simulation capabilities to study the building envelope-IEQ interaction at various technology readiness level. This paper provides an overview of the test-chain and its first application for the evaluation of a multifunctional façade. This façade includes a reversible air-to-air heat pump, a mechanical ventilation system, and openable windows, and aims at easing the achievement of the nZEB target while delivering elevated IEQ