Search Results (25)

Energy efficiency is a challenging research topic in robotics, since it can reduce operating costs and increase production sustainability. In this paper, we present a strategy for energy-efficient trajectory planning in redundant robotic systems. The proposed approach aims at optimizing the solution of inverse kinematics at each of the waypoints that define the considered task, so as to minimize the energy consumption. The approach is validated with simulations and bespoke experiments on two different robotic systems with seven and eight degrees of freedom (DOFs). Two test cases are considered, i.e., a point-to-point motion and a pick-and-place task. The experimental results quantify the energy saving capabilities of the proposed approach up to 82.54% and 94.28% with the seven-DOF and eight-DOF robots, respectively, with respect to reference cases. Full article

Chatter is a self-excited vibration that limits productivity, accelerates roll wear and compromises strip surface quality in high-speed tandem cold-rolling. This work presents a predictive hybrid model that couples the strip-deformation physics to the structural dynamics of a five-stand, 4-high mill, providing a fast decision tool for process optimization and real-time control. The model represents each stand as a four-degree-of-freedom mass–spring–damper system whose parameters are extracted from manufacturing automation datasheets and roll-gap sensing. Linearization about the nominal point yields analytical sensitivity matrices that close the electromechanical loop; the delay between stands is also included in the model. Implemented in MATLAB/Simulink, the computational model, based on data provided by Danieli & C. Officine Meccaniche S.p.A., reproduces the onset of chatter for two types of steel. The framework therefore supports automation-ready scheduling, active vibration mitigation and design-space exploration for next-generation mechatronic cold-rolling systems. Full article

Forest surveying and inspection face significant challenges due to unstructured environments, variable terrain conditions, and the high costs of manual data collection. Although mobile robotics and artificial intelligence offer promising solutions, reliable autonomous navigation in forest, terrain-aware path planning, and tree parameter estimation remain open challenges. In this paper, we present the results of the AI4FOREST project, which addresses these issues through three main contributions. First, we develop an autonomous mobile robot, integrating SLAM-based navigation, 3D point cloud reconstruction, and a vision-based deep learning architecture to enable tree detection and diameter estimation. This system demonstrates the feasibility of generating a digital twin of forest while operating autonomously. Second, to overcome the limitations of classical navigation approaches in heterogeneous natural terrains, we introduce a machine learning-based surrogate model of wheel–soil interaction, trained on a large synthetic dataset derived from classical terramechanics. Compared to purely geometric planners, the proposed model enables realistic dynamics simulation and improves navigation robustness by accounting for terrain–vehicle interactions. Finally, we investigate the impact of point cloud density on the accuracy of forest parameter estimation, identifying the minimum sampling requirements needed to extract tree diameters and heights. This analysis provides support to balance sensor performance, robot speed, and operational costs. Overall, the AI4FOREST project advances the state of the art in autonomous forest monitoring by jointly addressing SLAM-based mapping, terrain-aware navigation, and tree parameter estimation. Full article

Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality, with therapeutic resistance continuing to limit long-term responses. Among emerging resistance mechanisms, dysregulation of nucleocytoplasmic transport has gained attention for its ability to inactivate tumor suppressor pathways. Exportin 1 (XPO1), the primary nuclear export protein, is frequently overexpressed in NSCLC and promotes the cytoplasmic mislocalization of proteins involved in cell cycle control, apoptosis, and DNA repair. This includes key regulators such as p53, FOXO, and RB, whose inactivation supports tumor progression and therapy resistance. Inhibition of XPO1 with selective inhibitors of nuclear export (SINE) compounds, including selinexor, has demonstrated the ability to restore nuclear localization and function of these proteins, thereby enhancing cellular sensitivity to DNA-damaging agents, kinase inhibitors, and immunotherapies. In preclinical NSCLC models, XPO1 inhibition has shown efficacy both as monotherapy and in combination strategies, with particular promise in KRAS- and EGFR-driven tumors. This review explores the role of XPO1 in NSCLC biology and therapy resistance, the rationale for targeting nuclear export, and the current landscape of XPO1-directed clinical development in lung cancer. Full article

Chronic lymphocytic leukemia (CLL) is the most common leukemia in Western countries, and B-cell receptor (BCR) pathway inhibitors such as idelalisib and ibrutinib are currently established therapies for CLL. Although effective, these drugs frequently lead to resistance, but the mechanisms are still not fully understood. Activation-induced cytidine deaminase (AID) is a B-cell enzyme essential for antibody diversification. However, it can also introduce off-target mutations, leading to genomic instability. This study investigates whether treatment with BCR pathway inhibitors increases AID activity in CLL and whether this activity contributes to the development of drug resistance. Peripheral blood samples from CLL patients were collected before and after treatment with idelalisib or ibrutinib. Targeted sequencing was used to identify mutations in known AID off-target genes. Concurrently, AID-wild type (AID-WT) and AID-knockout (AID-KO) CLL cell lines were established and subsequently exposed to escalating doses of BCR pathway inhibitors to develop drug-resistant models. In patient samples, treatment with BCR pathway inhibitors was associated with an increase in AID-dependent mutations in off-target genes, including BCL2, MYC, and IRF8. The in vitro models efficiently recapitulated the patients’ data, as only AID-WT CLL cells accumulated mutations in the same AID off-target genes after drug exposure. However, no mutations were detected in genes that could mediate drug resistance. We conclude that BCR pathway inhibitors enhance AID mutational activity in CLL, but this does not appear to be directly involved in driving drug resistance. AID-targeted loci may nonetheless serve as biomarkers for monitoring genomic instability during treatment and inform further study. Full article

This paper presents a mobile robotic system designed for autonomous navigation and forest and tree trait estimation, with a focus on the location of individual trees and the diameter of the trunks. The system integrates light detection and ranging data and images using a framework based on simultaneous localization and mapping (SLAM) and a deep learning model for trunk segmentation and tree keypoint detection. Field experiments conducted in a wooded area in Udine, Italy, using a skid-steered mobile robot, demonstrate the effectiveness of the system in navigating, while avoiding obstacles (even in cases where the Global Navigation Satellite System signal is not reliable). The results highlight that the proposed robotic system is capable of autonomously generating maps of forests as point clouds with minimal drift thanks to the loop closure strategy integrated in the SLAM algorithm, and estimating tree traits automatically. Full article

While collections of documents are often annotated with hierarchically structured concepts, the benefits of these structures are rarely taken into account by classification techniques. Within this context, hierarchical text classification methods are devised to take advantage of the labels’ organization to boost classification performance. In this work, we aim to deliver an updated overview of the current research in this domain. We begin by defining the task and framing it within the broader text classification area, examining important shared concepts such as text representation. Then, we dive into details regarding the specific task, providing a high-level description of its traditional approaches. We then summarize recently proposed methods, highlighting their main contributions. We also provide statistics for the most commonly used datasets and describe the benefits of using evaluation metrics tailored to hierarchical settings. Finally, a selection of recent proposals is benchmarked against non-hierarchical baselines on five public domain-specific datasets. These datasets, along with our code, are made available for future research. Full article

Collaborative robotics represents a modern and efficient framework in which machines can safely interact with humans. Coupled with artificial intelligence (AI) systems, collaborative robots can solve problems that require a certain degree of intelligence not only in industry but also in the entertainment and educational fields. Board games like chess or checkers are a good example. When playing these games, a robotic system has to recognize the board and pieces and estimate their position in the robot reference frame, decide autonomously which is the best move to make (respecting the game rules), and physically execute it. In this paper, an intelligent and collaborative robotic system is presented to play Italian checkers. The system is able to acquire the game state using a camera, select the best move among all the possible ones through a decision-making algorithm, and physically manipulate the game pieces on the board, performing pick-and-place operations. Minimum-time trajectories are optimized online for each pick-and-place operation of the robot so as to make the game more fluent and interactive while meeting the kinematic constraints of the manipulator. The developed system is tested in a real-world setup using a Franka Emika arm with seven degrees of freedom. The experimental results demonstrate the feasibility and performance of the proposed approach. Full article

In the construction of knowledge bases, it is very important to evaluate the quality of the knowledge entered into them. This is exacerbated in public administrations, where knowledge should be oriented towards public services. In this study, an artificial intelligence-based method for the evaluation of knowledge is described. This method takes advantage of the structure and contents of the knowledge representation schemas (representing the knowledge of the corresponding experts) to carry out knowledge evaluation. More precisely, the method allows the various comparisons between the schemas to be integrated and the overall schema to evaluate the contribution of each schema. Full article

Breast cancer is the most frequent cancer in women. Despite recent clinical advances, new therapeutic approaches are still required. The cystine-glutamate antiporter xCT, encoded by the SLC7A11 gene, which imports cystine in exchange with glutamate, is a potentially new target for breast cancer therapy, being involved in tumor cell redox balance and resistance to therapies. xCT expression is regulated by the oncosuppressor p53, which is mutated in many breast cancers. Indeed, mutant p53 (mut-p53) can induce xCT post-transcriptional down modulation, rendering mut-p53 tumors susceptible to oxidative damage. Interestingly, the drug APR-246, developed to restore the wild-type function of p53 in tumors harboring its mutation, alters the cell redox balance in a p53-independent way, possibly rendering the cells more sensitive to xCT inhibition. Here, we propose a combinatorial treatment based on xCT immunetargeting and APR-246 treatment as a strategy for tackling breast cancer. We demonstrate that combining the inhibition of xCT with the APR-246 drug significantly decreased breast cancer cell viability in vitro and induced apoptosis and affected cancer stem cells’ self-renewal compared to the single treatments. Moreover, the immunetargeting of xCT through DNA vaccination in combination with APR-246 treatment synergistically hinders tumor progression and prevents lung metastasis formation in vivo. These effects can be mediated by the production of anti-xCT antibodies that are able to induce the antibody dependent cellular cytotoxicity of tumor cells. Overall, we demonstrate that DNA vaccination against xCT can synergize with APR-246 treatment and enhance its therapeutic effect. Thus, APR-246 treatment in combination with xCT immunetargeting may open new perspectives in the management of breast cancer. Full article

In this paper, we present a quantitative performance investigation and repeatability assessment of a mobile robotic system for 3D mapping. With the aim of a more efficient and automatic data acquisition process with respect to well-established manual topographic operations, a 3D laser scanner coupled with an inertial measurement unit is installed on a mobile platform and used to perform a high-resolution mapping of the surrounding environment. Point clouds obtained with the use of a mobile robot are compared with those acquired with the device carried manually as well as with a terrestrial laser scanner survey that serves as a ground truth. Experimental results show that both mapping modes provide similar accuracy and repeatability, whereas the robotic system compares favorably with respect to the handheld modality in terms of noise level and point distribution. The outcomes demonstrate the feasibility of the mobile robotic platform as a promising technology for automatic and accurate 3D mapping. Full article

In this paper, the implementation of a robotic painting system using a sponge and the watercolor painting technique is presented. A collection of tools for calibration and sponge support operations was designed and built. A contour-filling algorithm was developed, which defines the sponge positions and orientations in order to color the contour of a generic image. Finally, the proposed robotic system was employed to realize a painting combining etching and watercolor techniques. To the best of our knowledge, this is the first example of robotic painting that uses the watercolor technique and a sponge as the painting media. Full article