A fractional-order repetitive controller is here proposed to reject a periodic disturbance acting on a time-invariant linear stable, possibly nonminimum phase, plant. The controller is designed ...assuming that the frequency response of the plant, in a particular range of frequencies, belongs to a generic half-plane of the complex plane. No information about the structure of the system, i.e., number and locations of zeros/poles, is required. It is shown that, if this half-plane entirely contains the frequency response of the plant, then the controller can be designed without gain constraints. In the presence of saturation nonlinearities, conditions on the system absolute stability are discussed.
This paper presents an automatic recognition system for classifying stones belonging to different Calabrian quarries (Southern Italy). The tool for stone recognition has been developed in the SILPI ...project (acronym of “Sistema per l’Identificazione di Lapidei Per Immagini”), financed by POR Calabria FESR-FSE 2014-2020. Our study is based on the Convolutional Neural Network (CNNs) that is used in literature for many different tasks such as speech recognition, neural language processing, bioinformatics, image classification and much more. In particular, we propose a two-stage hybrid approach based on the use of a model of Deep Learning (DL), in our case the CNN, in the first stage and a model of Machine Learning (ML) in the second one. In this work, we discuss a possible solution to stones classification which uses a CNN for the feature extraction phase and the Softmax or Multinomial Logistic Regression (MLR), Support Vector Machine (SVM), k-Nearest Neighbors (kNN), Random Forest (RF) and Gaussian Naive Bayes (GNB) ML techniques in order to perform the classification phase basing our study on the approach called Transfer Learning (TL). We show the image acquisition process in order to collect adequate information for creating an opportune database of the stone typologies present in the Calabrian quarries, also performing the identification of quarries in the considered region. Finally, we show a comparison of different DL and ML combinations in our Two-Stage Hybrid Model solution.
Traditional methodologies for precise inspection of bridges (pavement, beams, column cap, column, joints and inside box girder, etc.) with By-bridge equipment, Aerial Work Platform (AWP) or via ropes ...have several limits that can be overcome by using Unmanned Aerial Vehicles (UAVs). The constant development in this field allows us to go beyond the manual control and the use of a single UAV. In the context of inspection rules, this research provides new inputs to the multilevel approach used today and to the methods of structural inspection with drones. Today, UAV-based inspections are limited by manual and/or semi-automatic control with many restrictions on trajectory settings, especially for areas of difficult access with Global Navigation Satellite Systems (GNSS) denied that still require the intervention of a human operator. This work proposes the use of autonomous navigation with a fleet of UAVs for infrastructural inspections. Starting from a digital twin, a solution is provided to problems such as the definition of a set of reference trajectories and the design of a position controller. A workflow to integrate a generic Bridge Management System (BMS) with this type of approach is provided.
5′AMP‐activated kinase (AMPK) constitutes a hub for cellular metabolic and growth control, thus representing an ideal therapeutic target for prostate cancers (PCas) characterized by increased ...lipogenesis and activation of mTORC1 pathway. However, whether AMPK activation itself is sufficient to block cancer cell growth remains to be determined. A small molecule screening was performed and identified MT 63–78, a specific and potent direct AMPK activator. Here, we show that direct activation of AMPK inhibits PCa cell growth in androgen sensitive and castration resistant PCa (CRPC) models, induces mitotic arrest, and apoptosis. In vivo, AMPK activation is sufficient to reduce PCa growth, whereas the allelic loss of its catalytic subunits fosters PCa development. Importantly, despite mTORC1 blockade, the suppression of de novo lipogenesis is the underpinning mechanism responsible for AMPK‐mediated PCa growth inhibition, suggesting AMPK as a therapeutic target especially for lipogenesis‐driven PCas. Finally, we demonstrate that MT 63–78 enhances the growth inhibitory effect of AR signaling inhibitors MDV3100 and abiraterone. This study thus provides a rationale for their combined use in CRPC treatment.
Synopsis
Direct activation of AMPK with a novel, highly specific compound curbs prostate cancer growth via inhibition of de novo lipogenesis. The combination of AMPK activation and hormonal therapy results in a synergistic anti‐cancer effect.
Direct activation of AMPK inhibits prostate cancer growth in vitro and in vivo.
Androgen receptor signaling inhibitors and AMPK activators act synergistically.
Persistent activation of AMPK results in mitotic arrest and apoptosis of prostate cancer cells.
Inhibition of de novo lipogenesis is the key mechanism of AMPK‐mediated anti‐tumor effect.
MT 63–78 is a novel, highly specific direct activator of AMPK.
Direct activation of AMPK with a novel, highly specific compound curbs prostate cancer growth via inhibition of de novo lipogenesis. The combination of AMPK activation and hormonal therapy results in a synergistic anti‐cancer effect.
Predicting drug response in cancer patients remains a major challenge in the clinic. We have perfected an ex vivo, reproducible, rapid and personalized culture method to investigate antitumoral ...pharmacological properties that preserves the original cancer microenvironment. Response to signal transduction inhibitors in cancer is determined not only by properties of the drug target but also by mutations in other signaling molecules and the tumor microenvironment. As a proof of concept, we, therefore, focused on the PI3K/Akt signaling pathway, because it plays a prominent role in cancer and its activity is affected by epithelial-stromal interactions. Our results show that this culture model preserves tissue 3D architecture, cell viability, pathway activity, and global gene-expression profiles up to 5 days ex vivo. In addition, we show pathway modulation in tumor cells resulting from pharmacologic intervention in ex vivo culture. This technology may have a significant impact on patient selection for clinical trials and in predicting response to small-molecule inhibitor therapy.
In this paper we focus on the target capturing problem for a swarm of agents modelled as double integrators in any finite space dimension. Each agent knows the relative position of the target and has ...only an estimation of its velocity and acceleration. Given that the estimation errors are bounded by some known values, it is possible to design a control law that ensures that agents enter a user-defined ellipsoidal ring around the moving target. Agents know the relative position of the other members whose distance is smaller than a common detection radius. Finally, in the case of no uncertainty about target data and homogeneous agents, we show how the swarm can reach a static configuration around the moving target. Some simulations are reported to show the effectiveness of the proposed strategy.
We present a novel approach to the system inversion problem for linear, scalar (i.e. single-input, single-output, or SISO) plants. The problem is formulated as a constrained optimization program, ...whose objective function is the transition time between the initial and the final values of the system’s output, and the constraints are (i) a threshold on the input intensity and (ii) the requirement that the system’s output interpolates a given set of points. The system’s input is assumed to be a piecewise constant signal. It is formally proved that, in this frame, the input intensity is a decreasing function of the transition time. This result lets us to propose an algorithm that, by a bisection search, finds the optimal transition time for the given constraints. The algorithm is purely algebraic, and it does not require the system to be minimum phase or nonhyperbolic. It can deal with time-varying systems too, although in this case it has to be viewed as a heuristic technique, and it can be used as well in a model-free approach. Numerical simulations are reported that illustrate its performance. Finally, an application to a mobile robotics problem is presented, where, using a linearizing pre-controller, we show that the proposed approach can be applied also to nonlinear problems.
Tumor perineural dissemination is a hallmark of human pancreatic ductal adenocarcinoma (PDAC) and represents a major source of local tumor recurrence after surgery. In this study, we provide in vitro ...and in vivo evidence that the chemokine receptor CX3CR1 may be involved in the neurotropism of PDAC cells to local peripheral nerves. Neoplastic cells from PDAC cell lines and surgical specimens express the chemokine receptor CX3CR1, absent in normal pancreatic ducts. Its unique ligand, the transmembrane chemokine CX3CL1, is expressed by neurons and nerve fibers. CX3CR1 + PDAC cell lines migrated in response to human recombinant CX3CL1 and specifically adhered to CX3CL1-expressing cells of neural origin via mechanisms involving activation of G proteins, beta1 integrins, and focal adhesion kinase. In vivo experiments with transplanted PDAC showed that only CX3CR1-transfected tumor cells infiltrated the local peripheral nerves. Immunohistochemistry of CX3CR1 in PDAC specimens revealed that 90% of the samples were positive with a heterogeneous pattern of expression. High receptor score was significantly associated with more prominent tumor perineural infiltration evaluated histologically (P = 0.026). Regression analyses (univariate and multivariate) showed that high CX3CR1 expression and perineural invasion were strongly associated with local and earlier tumor recurrence (P = 0.007). Collectively, this study shows that the CX3CR1 receptor may be involved in PDAC tumor neurotropism and is a relevant and independent risk factor to predict an early local tumor relapse in resected patients. Thus, the CX3CR1-CX3CL1 axis could represent a valuable therapeutic target to prevent tumor perineural dissemination in pancreatic cancer.
Fatty acid synthase (FASN) regulates de novo lipogenesis, body weight, and tumor growth. We examined whether common germline single nucleotide polymorphisms (SNPs) in the FASN gene affect prostate ...cancer (PCa) risk or PCa-specific mortality and whether these effects vary by body mass index (BMI).
In a prospective nested case-control study of 1,331 white patients with PCa and 1,267 age-matched controls, we examined associations of five common SNPs within FASN (and 5 kb upstream/downstream, R(2) > 0.8) with PCa incidence and, among patients, PCa-specific death and tested for an interaction with BMI. Survival analyses were repeated for tumor FASN expression (n = 909).
Four of the five SNPs were associated with lethal PCa. SNP rs1127678 was significantly related to higher BMI and interacted with BMI for both PCa risk (P(interaction) = .004) and PCa mortality (P(interaction) = .056). Among overweight men (BMI > or = 25 kg/m(2)), but not leaner men, the homozygous variant allele carried a relative risk of advanced PCa of 2.49 (95% CI, 1.00 to 6.23) compared with lean men with the wild type. Overweight patients carrying the variant allele had a 2.04 (95% CI, 1.31 to 3.17) times higher risk of PCa mortality. Similarly, overweight patients with elevated tumor FASN expression had a 2.73 (95% CI, 1.05 to 7.08) times higher risk of lethal PCa (P(interaction) = .02).
FASN germline polymorphisms were significantly associated with risk of lethal PCa. Significant interactions of BMI with FASN polymorphisms and FASN tumor expression suggest FASN as a potential link between obesity and poor PCa outcome and raise the possibility that FASN inhibition could reduce PCa-specific mortality, particularly in overweight men.
In this paper, an adaptive filter, based on a third-order generalized integrator, is proposed to estimate all the parameters of a biased sinusoid. The averaging theory is used to prove that the ...filter identifies the unknown frequency of the signal, in the case of a pure biased sinusoid in input. Moreover, in the case of a generic periodic signal, the method provides an estimate of the fundamental frequency by converging to a limit cycle in its vicinity. The robustness of the proposed approach with respect to noise in the input signal is analyzed. A filter bank is also presented to deal with the reconstruction problem of a generic multi-sinusoidal signal. Simulation results are also provided to compare the performances of the method with existing ones.