Embedding of linear programming in a simulated annealing algorithm for solving a mixed integer production planning problem

AbstractThe present paper is concerned with the grouping of book covers on offset plates in order to minimize the total production cost. The mathematical formulation of the problem involves both binary and continuous variables. As exact methods are unable to provide solutions in reasonable time, a heuristic algorithm of the simulated annealing type is proposed. At each iteration, the values of the current solution binary variables are altered in order to yield a neighboring solution. To compute the corresponding values of the continuous variables and the value of the objective function, a linear programming routine is called at each iteration. This constitutes the main originality of the present approach and is in principle applicable in mixed integer programming problems. The procedure is tested on several examples

Personal data governance and privacy in digital reproductive, maternal, newborn, and child health initiatives in Palestine and Jordan: a mapping exercise

IntroductionThere is a rapid increase in using digital technology for strengthening delivery of reproductive, maternal, newborn, and child health (RMNCH) services. Although digital health has potentially many benefits, utilizing it without taking into consideration the possible risks related to the security and privacy of patients' data, and consequently their rights, would yield negative consequences for potential beneficiaries. Mitigating these risks requires effective governance, especially in humanitarian and low-resourced settings. The issue of governing digital personal data in RMNCH services has to date been inadequately considered in the context of low-and-middle-income countries (LMICs). This paper aimed to understand the ecosystem of digital technology for RMNCH services in Palestine and Jordan, the levels of maturity of them, and the implementation challenges experienced, particularly concerning data governance and human rights.MethodsA mapping exercise was conducted to identify digital RMNCH initiatives in Palestine and Jordan and mapping relevant information from identified initiatives. Information was collected from several resources, including relevant available documents and personal communications with stakeholders.ResultsA total of 11 digital health initiatives in Palestine and 9 in Jordan were identified, including: 6 health information systems, 4 registries, 4 health surveillance systems, 3 websites, and 3 mobile-based applications. Most of these initiatives were fully developed and implemented. The initiatives collect patients' personal data, which are managed and controlled by the main owner of the initiative. Privacy policy was not available for many of the initiatives.DiscussionDigital health is becoming a part of the health system in Palestine and Jordan, and there is an increasing use of digital technology in the field of RMNCH services in both countries, particularly expanding in recent years. This increase, however, is not accompanied by clear regulatory policies especially when it comes to privacy and security of personal data, and how this data is governed. Digital RMNCH initiatives have the potential to promote effective and equitable access to services, but stronger regulatory mechanisms are required to ensure the effective realization of this potential in practice

Effects of Atrazine exposure on human bone marrow-derived mesenchymal stromal cells assessed by combinatorial assay matrix

IntroductionMesenchymal Stromal/Stem cells (MSCs) are an essential component of the regenerative and immunoregulatory stem cell compartment of the human body and thus of major importance in human physiology. The MSCs elicit their beneficial properties through a multitude of complementary mechanisms, which makes it challenging to assess their phenotype and function in environmental toxicity screening. We here employed the novel combinatorial assays matrix approach/technology to profile the MSC response to the herbicide Atrazine, which is a common environmental xenobiotic, that is in widespread agricultural use in the US and other countries, but banned in the EU. Our here presented approach is representative for screening the impact of environmental xenobiotics and toxins on MSCs as an essential representative component of human physiology and well-being.MethodsWe here employed the combinatorial assay matrix approach, including a panel of well standardized assays, such as flow cytometry, multiplex secretome analysis, and metabolic assays, to define the phenotype and functionality of human-donor-derived primary MSCs exposed to the representative xenobiotic Atrazine. This assay matrix approach is now also endorsed for characterization of cell therapies by leading regulatory agencies, such as FDA and EMA.ResultsOur results show that the exposure to Atrazine modulates the metabolic activity, size, and granularity of MSCs in a dose and time dependent manner. Intriguingly, Atrazine exposure leads to a broad modulation of the MSCs secretome (both upregulation and downmodulation of certain factors) with the identification of Interleukin-8 as the topmost upregulated representative secretory molecule. Interestingly, Atrazine attenuates IFNγ-induced upregulation of MHC-class-II, but not MHC-class-I, and early phosphorylation signals on MSCs. Furthermore, Atrazine exposure attenuates IFNγ responsive secretome of MSCs. Mechanistic knockdown analysis identified that the Atrazine-induced effector molecule Interleukin-8 affects only certain but not all the related angiogenic secretome of MSCs.DiscussionThe here described Combinatorial Assay Matrix Technology identified that Atrazine affects both the innate/resting and cytokine-induced/stimulated assay matrix functionality of human MSCs, as identified through the modulation of selective, but not all effector molecules, thus vouching for the great usefulness of this approach to study the impact of xenobiotics on this important human cellular subset involved in the regenerative healing responses in humans

Diversity in olfactory bulb size in birds reflects allometry, ecology, and phylogeny

The relative size of olfactory bulbs (OBs) is correlated with olfactory capabilities across vertebrates and is widely used to assess the relative importance of olfaction to a species’ ecology. In birds, variations in the relative size of OBs are correlated with some behaviors; however, the factors that have led to the high level of diversity seen in OB sizes across birds are still not well understood. In this study, we use the relative size of OBs as a neuroanatomical proxy for olfactory capabilities in 135 species of birds, representing 21 orders. We examine the scaling of OBs with brain size across avian orders, determine likely ancestral states and test for correlations between OB sizes and habitat, ecology, and behavior. The size of avian OBs varied with the size of the brain and this allometric relationship was for the most part isometric, although species did deviate from this trend. Large OBs were characteristic of more basal species and in more recently derived species the OBs were small. Living and foraging in a semiaquatic environment was the strongest variable driving the evolution of large OBs in birds; olfaction may provide cues for navigation and foraging in this otherwise featureless environment. Some of the diversity in OB sizes was also undoubtedly due to differences in migratory behavior, foraging strategies and social structure. In summary, relative OB size in birds reflect allometry, phylogeny and behavior in ways that parallel that of other vertebrate classes. This provides comparative evidence that supports recent experimental studies into avian olfaction and suggests that olfaction is an important sensory modality for all avian species

Electre Methods: Main Features and Recent Developments

We present main characteristics of Electre family methods, designed for multiple criteria decision aiding. These methods use as a preference model an outranking relation in the set of actions - it is constructed in result of concordance and non-discordance tests involving a specific input preference information. After a brief description of the constructivist conception in which the Electre methods are inserted, we present the main features of these methods. We discuss such characteristic features as: the possibility of taking into account positive and negative reasons in the modeling of preferences, without any need for recoding the data; using of thresholds for taking into account the imperfect knowledge of data; the absence of systematic compensation between "gains" and "losses". The main weaknesses are also presented. Then, some aspects related to new developments are outlined. These are related to some new methodological developments, new procedures, axiomatic analysis, software tools, and several other aspects. The paper ends with conclusions

Robust ordinal regression in preference learning and ranking

Multiple Criteria Decision Aiding (MCDA) offers a diversity of approaches designed for providing the decision maker (DM) with a recommendation concerning a set of alternatives (items, actions) evaluated from multiple points of view, called criteria. This paper aims at drawing attention of the Machine Learning (ML) community upon recent advances in a representative MCDA methodology, called Robust Ordinal Regression (ROR). ROR learns by examples in order to rank a set of alternatives, thus considering a similar problem as Preference Learning (ML-PL) does. However, ROR implements the interactive preference construction paradigm, which should be perceived as a mutual learning of the model and the DM. The paper clarifies the specific interpretation of the concept of preference learning adopted in ROR and MCDA, comparing it to the usual concept of preference learning considered within ML. This comparison concerns a structure of the considered problem, types of admitted preference information, a character of the employed preference models, ways of exploiting them, and techniques to arrive at a final ranking