tuberculosis novel approaches to an old disease

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Rolling horizon policies for multi-stage stochastic assemble-to-order problems

Assemble-to-order approaches deal with randomness in demand for end items by producing components under uncertainty, but assembling them only after demand is observed. Such planning problems can be tackled by stochastic programming, but true multistage models are computationally challenging and only a few studies apply them to production planning. Solutions based on two-stage models are often short-sighted and unable to effectively deal with non-stationary demand. A further complication may be the scarcity of available data, especially in the case of correlated and seasonal demand. In this paper, we compare different scenario tree structures. In particular, we enrich a two-stage formulation by introducing a piecewise linear approximation of the value of the terminal inventory, to mitigate the two-stage myopic behavior. We compare the out-of-sample performance of the resulting models by rolling horizon simulations, within a data-driven setting, characterized by seasonality, bimodality, and correlations in the distribution of end item demand. Computational experiments suggest the potential benefit of adding a terminal value function and illustrate interesting patterns arising from demand correlations and the level of available capacity. The proposed approach can provide support to typical MRP/ERP systems, when a two-level approach is pursued, based on master production and final assembly scheduling.Comment: This is an Author's Original Manuscript of an article published by Taylor and Francis in the International Journal of Production Research on 21.11.2023, available online: https://doi.org/10.1080/00207543.2023.228357

Cognitive Function in Multiple Sclerosis: A Subcortical Pattern of Neuropsychological Impairment?

In order to evaluate cognitive impairment in multiple sclerosis (MS) neuropsychological tests were administered to 25 patients with clinically definite disease. Four (16%) showed diffuse cognitive impairment, whereas the others, compared with controls showed a specific deficit on tests known to be sensitive to frontal lobe damage. These results are interpreted in the light of current hypotheses relating to subcortical contributions in cognition

Specific immunoassays confirm association of <i>Mycobacterium avium</i> subsp. <i>paratuberculosis</i> with type-1 but not type-2 diabetes mellitus

Background Mycobacterium avium subspecies paratuberculosis (MAP) is a versatile pathogen with a broad host range. Its association with type-1 diabetes mellitus (T1DM) has been recently proposed. Rapid identification of infectious agents such as MAP in diabetic patients at the level of clinics might be helpful in deciphering the role of chronic bacterial infection in the development of autoimmune diseases such as T1DM. Methodology/Principal Findings We describe use of an ELISA method to identify live circulating MAP through the detection of a cell envelope protein, MptD by a specific M13 phage – fMptD. We also used another ELISA format to detect immune response to MptD peptide. Both the methods were tested with blood plasma obtained from T1DM, type-2 diabetes (T2DM) patients and non-diabetic controls. Our results demonstrate MptD and fMptD ELISA assays to be accurate and sensitive to detect MAP bacilli in a large fraction (47.3%) of T1DM patients as compared to non-diabetic controls (12.6%) and those with confirmed T2DM (7.7%). Comparative analysis of ELISA assays performed here with 3 other MAP antigen preparations, namely HbHA, Gsd and whole cell MAP lysates confirmed comparable sensitivity of the MptD peptide and the fMptD based ELISA assays. Moreover, we were successful in demonstrating positive bacterial culture in two of the clinical specimen derived from T1DM patients. Conclusions and Significance The MptD peptide/fMptD based ELISA or similar tests could be suggested as rapid and specific field level diagnostic tests for the identification of MAP in diabetic patients and for finding the explanations towards the occurrence of type-1 or type-2 diabetes in the light of an active infectious trigger

A Social Internet of Things Smart City Solution for Traffic and Pollution Monitoring in Cagliari

In the last years, the smart city (SC) paradigm has been deeply studied to support sustainable mobility and to improve human living conditions. In this context, a new SC based on the Social Internet of Things paradigm is presented in this article. Starting from the tracking of all vehicles (that is, private and public) and pedestrians, integrated with air quality measurements (that is, in real time by mobile and fixed sensors), the system aims to improve the viability of the city, both for pedestrian and vehicular users. A monitoring network based on sensors and devices hosted on board in local public transport allows real-time monitoring of the most sensitive areas both from traffic congestion and from an environmental point of view. The proposed solution is equipped with an appropriate intelligence that takes into account instantaneous speed, type of traffic, and instantaneous pollution data, allowing to evaluate the congestion and pollution condition in a specific moment. Moreover, specific tools support the decisions of public administration facilitating the identification of the most appropriate actions for the implementation of effective policies relating to mobility. All collected data are elaborated in real time to improve traffic viability suggesting new directions and information to citizens to better organize how to live in the city