A Lagrangian approach to Chance Constrained Routing with Local Broadcast

Mobile cellular networks play a pivotal role in emerging Internet of Things (IoT) applications, such as vehicular collision alerts, malfunctioning alerts in Industry-4.0 manufacturing plants, periodic distribution of coordination information for swarming robots or platooning vehicles, etc. All these applications are characterized by the need of routing messages within a given local area (geographic proximity) with constraints about both timeliness and reliability (i.e., probability of reception). This paper presents a Non-Convex Mixed-Integer Nonlinear Programming model for a routing problem with probabilistic constraints on a wireless network. We propose an exact approach consisting of a branch-and-bound framework based on a novel Lagrangian decomposition to derive lower bounds. Preliminary experimental results indicate that the proposed algorithm is competitive with state-of-the-art general-purpose solvers, and can provide better solutions than existing highly tailored ad-hoc heuristics to this problem

Selection processes in simple sequence repeats suggest a correlation with their genomic location: insights from a fungal model system

Background: Adaptive processes shape the evolution of genomes and the diverse functions of different genomic regions are likely to have an impact on the trajectory and outcome of this evolution. The main underlying hypothesis of this study is that the evolution of Simple Sequence Repeats (SSRs) is correlated with the evolution of the genomic region in which they are located, resulting in differences of motif size, number of repeats, and levels of polymorphisms. These differences should be clearly detectable when analyzing the frequency and type of SSRs within the genome of a species, when studying populations within a species, and when comparing closely related sister taxa. By coupling a genome-wide SSR survey in the genome of the plant pathogenic fungus Heterobasidion irregulare with an analysis of intra-and interspecific variability of 39 SSR markers in five populations of the two sibling species H. irregulare and H. annosum, we investigated mechanisms of evolution of SSRs.Results: Results showed a clear dominance of trirepeats and a selection against other repeat number, i.e. di- and tetranucleotides, both in regions inside Open Reading Frames (ORFs) and upstream 5' untranslated region (5'UTR). Locus per locus AMOVA showed SSRs both inside ORFs and upstream 5'UTR were more conserved within species compared to SSRs in other genomic regions, suggesting their evolution is constrained by the functions of the regions they are in. Principal coordinates analysis (PCoA) indicated that even if SSRs inside ORFs were less polymorphic than those in intergenic regions, they were more powerful in differentiating species. These findings indicate SSRs evolution undergoes a directional selection pressure comparable to that of the ORFs they interrupt and to that of regions involved in regulatory functions.Conclusions: Our work linked the variation and the type of SSRs with regions upstream 5'UTR, putatively harbouring regulatory elements, and shows that the evolution of SSRs might be affected by their location in the genome. Additionally, this study provides a first glimpse on a possible molecular basis for fast adaptation to the environment mediated by SSRs

On the convergence of stochastic gradient descent in low-precision number formats

ABSTRACT: Deep learning models are dominating almost all artificial intelligence tasks such as vision, text, and speech processing. Stochastic Gradient Descent (SGD) is the main tool for training such models, where the computations are usually performed in single-precision floating-point number format. The convergence of single-precision SGD is normally aligned with the theoretical results of real numbers since they exhibit negligible error. However, the numerical error increases when the computations are performed in low-precision number formats. This provides compelling reasons to study the SGD convergence adapted for low-precision computations. We present both deterministic and stochastic analysis of the SGD algorithm, obtaining bounds that show the effect of number format. Such bounds can provide guidelines as to how SGD convergence is affected when constraints render the possibility of performing high-precision computations remote

Rapid Detection of Pityophthorus juglandis (Blackman) (Coleoptera, Curculionidae) with the Loop-Mediated Isothermal Amplification (LAMP) Method

The walnut twig beetle Pityophthorus juglandis is a phloem-boring bark beetle responsible, in association with the ascomycete Geosmithia morbida, for the Thousand Cankers Disease (TCD) of walnut trees. The recent finding of TCD in Europe prompted the development of effective diagnostic protocols for the early detection of members of this insect/fungus complex. Here we report the development of a highly efficient, low-cost, and rapid method for detecting the beetle, or even just its biological traces, from environmental samples: the loop-mediated isothermal amplification (LAMP) assay. The method, designed on the 28S ribosomal RNA gene, showed high specificity and sensitivity, with no cross reactivity to other bark beetles and wood-boring insects. The test was successful even with very small amounts of the target insect’s nucleic acid, with limit values of 0.64 pg/µL and 3.2 pg/µL for WTB adults and frass, respectively. A comparison of the method (both in real time and visual) with conventional PCR did not display significant differences in terms of LoD. This LAMP protocol will enable quick, low-cost, and early detection of P. juglandis in areas with new infestations and for phytosanitary inspections at vulnerable sites (e.g., seaports, airports, loading stations, storage facilities, and wood processing companies)

Modelling of implantable sensor packaging based on biocompatible polymers

Implantable devices are being used for long term healthcare and human body physiological monitoring of specific parameters. PDMS (poly-dimethyl-siloxane) can be used either for sensor or for packaging of the same sensor in many applications, notably in laparoscopy and laparotomy as feeler pin in order to help surgeons to touch specific tissues and to get a response based on the nature of the touched tissue (softness). The need of calibrated pressure on a tissue arises when we are in presence particular pathologies or impairments as: cancer issues, high risk of aneurism for aorta and brain, probable haemorrhage in touching capillaries, and so forth. This paper presents a packaging modelling of a build nanosensor to be used in a human body for surgery exploration as laparoscopy and laparotomy. A nanosensor is first build for common application and adapted for implantable applications, and a packaging is studied. The designed sensor is implemented by considering PDMS as polymeric material

Serum Albumin Is Inversely Associated With Portal Vein Thrombosis in Cirrhosis

We analyzed whether serum albumin is independently associated with portal vein thrombosis (PVT) in liver cirrhosis (LC) and if a biologic plausibility exists. This study was divided into three parts. In part 1 (retrospective analysis), 753 consecutive patients with LC with ultrasound-detected PVT were retrospectively analyzed. In part 2, 112 patients with LC and 56 matched controls were entered in the cross-sectional study. In part 3, 5 patients with cirrhosis were entered in the in vivo study and 4 healthy subjects (HSs) were entered in the in vitro study to explore if albumin may affect platelet activation by modulating oxidative stress. In the 753 patients with LC, the prevalence of PVT was 16.7%; logistic analysis showed that only age (odds ratio [OR], 1.024; P = 0.012) and serum albumin (OR, -0.422; P = 0.0001) significantly predicted patients with PVT. Analyzing the 112 patients with LC and controls, soluble clusters of differentiation (CD)40-ligand (P = 0.0238), soluble Nox2-derived peptide (sNox2-dp; P < 0.0001), and urinary excretion of isoprostanes (P = 0.0078) were higher in patients with LC. In LC, albumin was correlated with sCD4OL (Spearman's rank correlation coefficient [r(s)], -0.33; P < 0.001), sNox2-dp (r(s), -0.57; P < 0.0001), and urinary excretion of isoprostanes (r(s), -0.48; P < 0.0001) levels. The in vivo study showed a progressive decrease in platelet aggregation, sNox2-dp, and urinary 8-iso prostaglandin F2 alpha-III formation 2 hours and 3 days after albumin infusion. Finally, platelet aggregation, sNox2-dp, and isoprostane formation significantly decreased in platelets from HSs incubated with scalar concentrations of albumin. Conclusion: Low serum albumin in LC is associated with PVT, suggesting that albumin could be a modulator of the hemostatic system through interference with mechanisms regulating platelet activation

A Lagrangian approach to a problem with probailistic constraints

Nel lavoro vengono sviluppati approcci algoritmici per un modello di Programmazione Non Lineare Mista Intera (MINLP) non-convesso altamente sfidante per un problema di routing con vincoli probabilistici su reti wireless relativo ad un'applicazione IoT, che non può essere risolto all'ottimo con gli strumenti general-purpose attualmente disponibili. Per tale modello viene proposto un innovativo approccio Lagrangiano in grado di calcolare valutazioni inferiori sul valore ottimo del problema in questione mediante la soluzione di problemi non-convessi mono-dimensionali, che vengono dimostrati essere unimodali e quindi risolti efficientemente con tecniche del secondo ordine. Le valutazioni inferiori così ottenute sono sfruttate anche per la costruzione di euristiche Lagrangiane, che in alcuni casi si sono mostrate più efficaci delle migliori euristiche attualmente disponibili. Le metodologie sviluppate permetteranno in futuro l'implementazione di un algoritmo di enumerazione implicita (Branch and Bound) che potrebbe permettere di determinare soluzioni ottime per il problema