Experience classification for transfer learning in traffic signal control

In recent years, due to the drastic rise in the number of vehicles and the lack of sufficient infrastructure, traffic jams, air pollution, and fuel consumption have increased in cities. The optimization of timing for traffic lights is one of the solutions for the mentioned problems. Many methods have been introduced to deal with these problems, including reinforcement learning. Although a great number of learning-based methods have been used in traffic signal control, they suffer from poor performance and slow learning convergence. In this paper, a transfer learning-based method for traffic signal control has been proposed. Multi-agent system has also been used for modelling the traffic network and transfer learning has been used to make reinforcement learning agents transfer their experience to each other. Furthermore, a classifier has been utilized to classify the transferred experiences. The results show that using the proposed method leads to a significant improvement on average delay time and convergence time of the learning process.

     

Optimization of the grapes reception process

Neural Computing and Applications - Grapes reception is a key process in wine production. The harvest days are extremely challenging days in managing the reception of the grapes, as the winery...     

Modeling of the condyle elements within a biomechanical knee model

The development of a computational multibody knee model able to capture some of the fundamental properties of the human knee articulation is presented. This desideratum is reached by including the kinetics of the real knee articulation. The research question is whether an accurate modeling of the condyle contact in the knee will lead to reproduction of the complex combination of flexion/extension, abduction/adduction, and tibial rotation observed in the real knee. The model is composed by two anatomic segments, the tibia and the femur, whose characteristics are functions of the geometric and anatomic properties of the real bones. The biomechanical model characterization is developed under the framework of multibody systems methodologies using Cartesian coordinates. The type of approach used in the proposed knee model is the joint surface contact conditions between ellipsoids, representing the two femoral condyles, and points, representing the tibial plateau and the menisci. These elements are closely fitted to the actual knee geometry. This task is undertaken by considering a parameter optimization process to replicate experimental data published in the literature, namely that by Lafortune and his coworkers in 1992. Then kinematic data in the form of flexion/extension patterns are imposed on the model corresponding to the stance phase of the human gait. From the results obtained, by performing several computational simulations, it can be observed that the knee model approximates the average secondary motion patterns observed in the literature. Because the literature reports considerable inter-individual differences in the secondary motion patterns, the knee model presented here is also used to check whether it is possible to reproduce the observed differences with reasonable variations of bone shape parameters. This task is accomplished by a parameter study, in which the main variables that define the geometry of condyles are taken into account. It was observed that the data reveal a difference in secondary kinematics of the knee in flexion versus extension. The likely explanation for this fact is the elastic component of the secondary motions created by the combination of joint forces and soft tissue deformations. The proposed knee model is, therefore, used to investigate whether this observed behavior can be explained by reasonable elastic deformations of the points representing the menisci in the model.     

Authors' reply

This reply clarifies that it is possible to change the plane of cut by filtering a tomogram, if the presence of the out-of-focus images is tolerated, because the (projected) images of all the layers are superimposed on the film and any filtering will process all these images simultaneously.     

Steric stabilization of Stöber silica dispersions using organosilanes

Organosilanes of the general formula R _x Si(OR)_4–x (where R is an alkyl group and R = CH₃ or CH₂CH₃) were used to sterically stabilize hexane dispersions of submicrometre silica spheres. The dispersions were characterized according to sediment volume results. For 0.5m silica particles, the sediment density increased by more than a factor of three up to 50 to 55% of theoretical in the presence of organosilanes with 12 or more carbons in the R group. Solid-state¹³C nuclear magnetic resonance was used to characterize the powder-dispersant interaction; this technique can distinguish between carbons in the R group of the organosilane and residual organic groups in the silica. Scanning electron micrographs of filter compacts were used to further characterize the dispersions and indicated the presence of primary particles as well as small agglomerates.     

The Chick Chorioallantoic Membrane Model: A New In Vivo Tool to Evaluate Breast Cancer Stem Cell Activity

The high plasticity of cancer stem-like cells (CSCs) allows them to differentiate and proliferate, specifically when xenotransplanted subcutaneously into immunocompromised mice. CSCs are highly tumorigenic, even when inoculated in small numbers. Thus, in vivo limiting dilution assays (LDA) in mice are the current gold standard method to evaluate CSC enrichment and activity. The chick embryo chorioallantoic membrane (CAM) is a low cost, naturally immune-incompetent and reproducible model widely used to evaluate the spontaneous growth of human tumor cells. Here, we established a CAM-LDA assay able to rapidly reproduce tumor specificities—in particular, the ability of the small population of CSCs to form tumors. We used a panel of organotropic metastatic breast cancer cells, which show an enrichment in a stem cell gene signature, enhanced CD44⁺/CD24^−/low cell surface expression and increased mammosphere-forming efficiency (MFE). The size of CAM-xenografted tumors correlate with the number of inoculated cancer cells, following mice xenograft growth pattern. CAM and mice tumors are histologically comparable, displaying both breast CSC markers CD44 and CD49f. Therefore, we propose a new tool for studying CSC prevalence and function—the chick CAM-LDA—a model with easy handling, accessibility, rapid growth and the absence of ethical and regulatory constraints.     

P16 and HPV Genotype Significance in HPV-Associated Cervical Cancer—A Large Cohort of Two Tertiary Referral Centers

The expression of p16 is a good surrogate of human papillomavirus (HPV) infection in HPV-associated cancers. The significance of p16 expression, HPV genotype and genera in the outcome of patients with HPV-associated cervical cancer (CC) is unclear. Our aim is to ascertain the prognostic significance of these factors. Data from 348 patients (median age: 47.5 years old) with CC, diagnosed in two referral centers, were retrospectively collected. Advanced disease (FIGO2018 IB2-IV) was present in 68% of patients. A single HPV genotype was identified in 82.8% of patients. The most common HPVs were HPV16 (69%) and HPV18 (14%). HPV genera reflected this distribution. HPV16 tumors presented at an earlier stage. P16 was negative in 18 cases (5.2%), 83.3% of which were squamous cell carcinomas. These cases occurred in older patients who tended to have advanced disease. In the univariate analysis, HPV16 (HR: 0.58; p = 0.0198), α-9 genera (HR: 0.37; p = 0.0106) and p16 overexpression (HR: 0.54; p = 0.032) were associated with better survival. HPV16 (HR: 0.63; p = 0.0174) and α-9 genera (HR: 0.57; p = 0.0286) were associated with less relapse. In the multivariate analysis, only the International Federation of Gynecology and Obstetrics (FIGO) stage retained an independent prognostic value. HPV16, α-9 genera and p16 overexpression were associated with better survival, although not as independent prognostic factors. Patients with p16-negative HPV-associated CC were older, presented with advanced disease and had worse prognosis.     

Improved Controlled Release and Brain Penetration of the Small Molecule S14 Using PLGA Nanoparticles

Phosphodiesterase 7 (PDE7) is an enzyme responsible for the degradation of cyclic adenosine monophosphate (cAMP), an important cellular messenger. PDE7’s role in neurotransmission, expression profile in the brain and the druggability of other phosphodiesterases have motivated the search for potent inhibitors to treat neurodegenerative and inflammatory diseases. Different heterocyclic compounds have been described over the years; among them, phenyl-2-thioxo-(1H)-quinazolin-4-one, called S14, has shown very promising results in different in vitro and in vivo studies. Recently, polymeric nanoparticles have been used as new formulations to target specific organs and produce controlled release of certain drugs. In this work, we describe poly(lactic-co-glycolic acid) (PLGA)-based polymeric nanoparticles loaded with S14. Their preparation, optimization, characterization and in vivo drug release profile are here presented as an effort to improve pharmacokinetic properties of this interesting PDE7 inhibitor.     

The Histidine Phosphocarrier Kinase/Phosphorylase from Bacillus Subtilis Is an Oligomer in Solution with a High Thermal Stability

The histidine phosphocarrier protein (HPr) kinase/phosphorylase (HPrK/P) modulates the phosphorylation state of the HPr protein, and it is involved in the use of carbon sources by Gram-positive bacteria. Its X-ray structure, as concluded from crystals of proteins from several species, is a hexamer; however, there are no studies about its conformational stability, and how its structure is modified by the pH. We have embarked on the conformational characterization of HPrK/P of Bacillus subtilis (bsHPrK/P) in solution by using several spectroscopic (namely, fluorescence and circular dichroism (CD)) and biophysical techniques (namely, small-angle X-ray-scattering (SAXS) and dynamic light-scattering (DLS)). bsHPrK/P was mainly a hexamer in solution at pH 7.0, in the presence of phosphate. The protein had a high conformational stability, with an apparent thermal denaturation midpoint of ~70 °C, at pH 7.0, as monitored by fluorescence and CD. The protein was very pH-sensitive, precipitated between pH 3.5 and 6.5; below pH 3.5, it had a molten-globule-like conformation; and it acquired a native-like structure in a narrow pH range (between pH 7.0 and 8.0). Guanidinium hydrochloride (GdmCl) denaturation occurred through an oligomeric intermediate. On the other hand, urea denaturation occurred as a single transition, in the range of concentrations between 1.8 and 18 µM, as detected by far-UV CD and fluorescence.