Augmented reality system to assist inexperienced pool players

Computational Visual Media - Pool and billiards are amongst a family of games played on a table with six pockets along the rails. This paper presents an augmented reality tool designed to assist...     

Ferroptosis Modulation: Potential Therapeutic Target for Glioblastoma Treatment

Glioblastoma multiforme is a lethal disease and represents the most common and severe type of glioma. Drug resistance and the evasion of cell death are the main characteristics of its malignancy, leading to a high percentage of disease recurrence and the patients’ low survival rate. Exploiting the modulation of cell death mechanisms could be an important strategy to prevent tumor development and reverse the high mortality and morbidity rates in glioblastoma patients. Ferroptosis is a recently described type of cell death, which is characterized by iron accumulation, high levels of polyunsaturated fatty acid (PUFA)-containing phospholipids, and deficiency in lipid peroxidation repair. Several studies have demonstrated that ferroptosis has a potential role in cancer treatment and could be a promising approach for glioblastoma patients. Thus, here, we present an overview of the mechanisms of the iron-dependent cell death and summarize the current findings of ferroptosis modulation on glioblastoma including its non-canonical pathway. Moreover, we focused on new ferroptosis-inducing compounds for glioma treatment, and we highlight the key ferroptosis-related genes to glioma prognosis, which could be further explored. Thereby, understanding how to trigger ferroptosis in glioblastoma may provide promising pharmacological targets and indicate new therapeutic approaches to increase the survival of glioblastoma patients.     

Systematic Review and Meta-Analysis of Mass Spectrometry Proteomics Applied to Human Peripheral Fluids to Assess Potential Biomarkers of Schizophrenia

Mass spectrometry (MS)-based techniques can be a powerful tool to identify neuropsychiatric disorder biomarkers, improving prediction and diagnosis ability. Here, we evaluate the efficacy of MS proteomics applied to human peripheral fluids of schizophrenia (SCZ) patients to identify disease biomarkers and relevant networks of biological pathways. Following PRISMA guidelines, a search was performed for studies that used MS proteomics approaches to identify proteomic differences between SCZ patients and healthy control groups (PROSPERO database: CRD42021274183). Nineteen articles fulfilled the inclusion criteria, allowing the identification of 217 differentially expressed proteins. Gene ontology analysis identified lipid metabolism, complement and coagulation cascades, and immune response as the main enriched biological pathways. Meta-analysis results suggest the upregulation of FCN3 and downregulation of APO1, APOA2, APOC1, and APOC3 in SCZ patients. Despite the proven ability of MS proteomics to characterize SCZ, several confounding factors contribute to the heterogeneity of the findings. In the future, we encourage the scientific community to perform studies with more extensive sampling and validation cohorts, integrating omics with bioinformatics tools to provide additional comprehension of differentially expressed proteins. The produced information could harbor potential proteomic biomarkers of SCZ, contributing to individualized prognosis and stratification strategies, besides aiding in the differential diagnosis.     

Recurrent pattern matching based stereo image coding using linear predictors

The Multidimensional Multiscale Parser (MMP) is a pattern-matching-based generic image encoding solution which has been investigated earlier for the compression of stereo images with successful results. While first MMP-based proposals for stereo image coding employed dictionary-based techniques for disparity compensation, posterior developments have demonstrated the advantage of using predictive methods. In this paper, we focus on recent investigations on the use of predictive methods in the MMP algorithm and propose a new prediction framework for efficient stereo image coding. This framework comprises an advanced intra directional prediction model and a new linear predictive scheme for efficient disparity compensation. The linear prediction model is the main novelty of this work, combining adaptive linear models estimated by least-squares algorithm with fixed linear models provided by the block-matching algorithm. The performance of the proposed intra prediction and disparity compensation methods when applied in an MMP encoder has been evaluated experimentally. Comparisons with the current stereo image coding standards showed that the proposed MMP algorithm significantly outperforms the Stereo High Profile of H.264/AVC standard. In addition, it presents a competitive performance relative to the MV-HEVC standard. These results also suggest that current stereo image coding standards may benefit from the proposed linear prediction scheme for disparity compensation, as an extension to the omnipresent block-matching solution.     

The Impact of Cooperative Nodes on the Performance of Vehicular Delay-Tolerant Networks

Vehicular communications refer to a wide range of networks proposed for environments characterized by sparse connectivity, frequent network partitioning, intermittent connectivity, long propagation delays, asymmetric data rates, and high error rates. These environments may also be characterized by a potential non-available end-to-end path. To overcome these issues and improve the overall network performance, cooperation between network nodes must be severely considered. Nodes may cooperate by sharing their storage capacity, bandwidth, or even energy resources. However, nodes may be unwilling to cooperate due to a selfish behavior or to an intent to protect the integrity of their own resources. This selfish behavior significantly affects the functionality and performance of the network. This paper overviews the most recent advances related with cooperation on vehicular networks. It also studies the impact of different cooperation levels in the performance of Vehicular Delay-Tolerant Networks (VDTNs). It was shown that scenarios with a higher number of cooperative nodes present the best results in terms of bundle delivery delay.     

QoS-driven adaptive congestion control for voice over IP in multiservice wireless cellular networks

This work establishes a QoS-driven adaptive congestion control framework that provides QoS guarantees to VoIP service flows in mixed traffic scenarios for wireless cellular networks. The framework is composed of three radio resource management algorithms: admission control, packet scheduling, and load control. The proposed framework is scalable to several services and can be applied in any current or future packet-switched wireless system. By means of dynamic system-level simulations carried out in a specific case study where VoIP and Web service flows compete for shared access in an HSDPA wireless network, the proposed framework is able to increase the overall system capacity twofold depending on the traffic mix, while keeping the system operating optimally in its target QoS profile.     

The AROUND Architecture for Dynamic Location-Based Services

This paper presents a generic concept of location-based service as an abstraction for supporting the association between computational resources and location. The objective is to extend the advantages of service-based architectures to the development of location-based systems, thus providing a more open and extensible alternative to the vertical approaches typically used in this type of system. The novel AROUND architecture is proposed as an approach for supporting location-based services in the Internet environment. AROUND provides a service location infrastructure that allows applications to select services that are specifically associated with their current location. The architecture includes a flexible scope model that defines the association between services and location, and a service location infrastructure organised by spatial criteria and optimised for location-based queries. Based on a prototype implementation of this architecture, we have developed two case studies that illustrate the use of this approach for developing location-based systems. The overall results provide a valuable insight into the applicability of the architecture, and suggest that this model of location-based services can provide a useful approach for the development of a wide range of location-based applications.