Showing papers by "University of Patras published in 2022"

Metaverse

Abstract: The Metaverse is the post-reality universe, a perpetual and persistent multiuser environment merging physical reality with digital virtuality. It is based on the convergence of technologies that enable multisensory interactions with virtual environments, digital objects and people such as virtual reality (VR) and augmented reality (AR). Hence, the Metaverse is an interconnected web of social, networked immersive environments in persistent multiuser platforms. It enables seamless embodied user communication in real-time and dynamic interactions with digital artifacts. Its first iteration was a web of virtual worlds where avatars were able to teleport among them. The contemporary iteration of the Metaverse features social, immersive VR platforms compatible with massive multiplayer online video games, open game worlds and AR collaborative spaces.

Agricultural and livestock sector's residues in Greece & China: Comparative qualitative and quantitative characterization for assessing their potential for biogas production

Abstract: Greece and China are two agricultural countries in which a significant percentage of their biomass consists of agricultural and livestock wastes. In Greece, the management practice that is still applied is burning the majority of the agricultural residues in the field, while in China large amount of untreated agricultural waste causes serious adverse effects on the rural living environment. Residual biomass could arise from the agricultural sector in the form of crop residues and of animal wastes. A comprehensive literature review was performed for both countries on primary agricultural and livestock wastes that includes: (a) crop residues that are left in the fields, (b) animal manures and (c) secondary agricultural wastes consisted of liquid and solid wastes from agricultural products processing plants. The average annual quantity of agricultural residues, animal manure and agro-industrial residues in Greece and China (a small and a large country, respectively) is 10 Mt/y and 860 Mt/y, 26 Mt/y and 216.5 Mt/y, 13.2 Mt/y and 213.7 Mt/y, for each corresponding category. According to the amount of the above residues generated per country, the theoretical estimated energy can reach up to 77 TWh and 5500 TWh for Greece and China, respectively, which suggests that both countries can cover a significant part of their energy needs (approximately 135% and 99%, respectively) only from their agricultural and livestock wastes. Τhese observations constitute strong recommendations mainly addressed to policy makers to substantially strengthen the efforts of research, technological and economic optimization of the applications of energy use of agricultural residual biomass for the benefit of the environment and humanity.

Applications of biosensors for bacteria and virus detection in food and water–A systematic review

Abstract: Biosensors for sensitive and specific detection of foodborne and waterborne pathogens are particularly valued for their portability, usability, relatively low cost, and real-time or near real-time response. Their application is widespread in several domains, including environmental monitoring. The main limitation of currently developed biosensors is a lack of sensitivity and specificity in complex matrices. Due to increased interest in biosensor development, we conducted a systematic review, complying with the PRISMA guidelines, covering the period from January 2010 to December 2019. The review is focused on biosensor applications in the identification of foodborne and waterborne microorganisms based on research articles identified in the Pubmed, ScienceDirect, and Scopus search engines. Efforts are still in progress to overcome detection limitations and to provide a rapid detection system which will safeguard water and food quality. The use of biosensors is an essential tool with applicability in the evaluation and monitoring of the environment and food, with great impact in public health.

Kaniadakis holographic dark energy and cosmology

Abstract: Abstract We construct a holographic dark energy scenario based on Kaniadakis entropy, which is a generalization of Boltzmann-Gibbs entropy that arises from relativistic statistical theory and is characterized by a single parameter K which quantifies the deviations from standard expressions, and we use the future event horizon as the Infrared cutoff. We extract the differential equation that determines the evolution of the effective dark energy density parameter, and we provide analytical expressions for the corresponding equation-of-state and deceleration parameters. We show that the universe exhibits the standard thermal history, with the sequence of matter and dark-energy eras, while the transition to acceleration takes place at $$z\approx 0.6$$ z ≈ 0.6 . Concerning the dark-energy equation-of-state parameter we show that it can have a rich behavior, being quintessence-like, phantom-like, or experience the phantom-divide crossing in the past or in the future. Finally, in the far future dark energy dominates completely, and the asymptotic value of its equation of state depends on the values of the two model parameters.

3D-printed bioactive scaffolds for bone regeneration bearing carbon dots for bioimaging purposes

Abstract: Additive manufacturing, also known as 3D-printing, has been successfully employed to create novel bioactive scaffolds incorporating carbon dots for bioimaging purposes. Fused filament fabrication technique (FFF) was used to print a hybrid poly-lactic acid (PLA)-based filament bearing bioactive material, suited for hydroxyapatite (HAp) development, as well as carbon dots which by virtue of their strong luminescence could support an optical characterization of the composite, thus, its regenerative stages. This technique using FFF biodegradable PLA can be used to create the exact custom-made scaffold depending on the user needs (i.e. shape of a bone fracture), whereas the bioactive material (bioglass® 45S5) assists bone regeneration by HAp development. On the other hand, biocompatible red emissive boron-doped carbon dots could allow for monitoring of the procedure. Scaffolds were tested for their in vitro bioactivity by soaking in simulated body fluid (SBF) solution. In addition, in vitro cytotoxicity testing confirmed the low toxicity of the composite materials used for creating the scaffolds. Degradation of the PLA scaffold initiated immediately providing space for bone regeneration. HAp development was confirmed by scanning electron microscopy - energy dispersive X-ray spectroscopy (SEM/EDS) and infrared spectroscopy (IR). Ultraviolet visible and photoluminescence spectroscopies were used to evaluate the properties of the carbon dots as well as composite materials. Results indicate that this is a promising technique for confronting asymmetric or irregular-shaped bone fractures with simultaneous monitoring of the healing process through bioimaging.

Optimal Management of Asymptomatic Carotid Stenosis in 2021: The Jury is Still Out. An International, Multispecialty, Expert Review and Position Statement

Abstract: Objectives The recommendations of international guidelines for the management of asymptomatic carotid stenosis (ACS) often vary considerably and extend from a conservative approach with risk factor modification and best medical treatment (BMT) alone, to a more aggressive approach with a carotid intervention plus BMT. The aim of the current multispecialty position statement is to reconcile the conflicting views on the topic. Materials and methods A literature review was performed with a focus on data from recent studies. Results Several clinical and imaging high-risk features have been identified that are associated with an increased long-term ipsilateral ischemic stroke risk in patients with ACS. Such high-risk clinical/imaging features include intraplaque hemorrhage, impaired cerebrovascular reserve, carotid plaque echolucency/ulceration/ neovascularization, a lipid-rich necrotic core, a thin or ruptured fibrous cap, silent brain infarction, a contralateral transient ischemic attack/stroke episode, male patients Conclusions Although aggressive risk factor control and BMT should be implemented in all ACS patients, several high-risk features that may increase the risk of a future cerebrovascular event are now documented. Consequently, some guidelines recommend a prophylactic carotid intervention in high-risk patients to prevent future cerebrovascular events. Until the results of the much-anticipated randomized controlled trials emerge, the jury is still out regarding the optimal management of ACS patients.

From Text to Signatures: Knowledge Transfer for Efficient Deep Feature Learning in Offline Signature Verification

Abstract: Handwritten signature is a common biometric trait, widely used for confirming the presence or the consent of a person. Offline Signature Verification (OSV) is the task of verifying the signer using static signature images captured after the finish of signing process, with many applications especially in the domain of forensics. Deep Convolutional Neural Networks (CNNs) can generate efficient feature representations, but their training is data-intensive. Since limited training data is an intrinsic problem of an OSV system’s development, this work focuses on addressing the problem of learning informative features by employing prior knowledge from a similar task in a domain with an abundance of training data. In particular, we demonstrate that an appropriate pre-training of a CNN model in the task of handwritten text-based writer identification task, can dramatically improve the efficiency of the CNN in the OSV task, enabling to obtain state-of-the-art performance with an order of magnitude less training signature samples. In the proposed scheme, after the pre-training of the CNN in writer identification task through specially processed handwritten text data, the learned features are tailored to the signature problem though a metric learning stage that utilizes contrastive loss to learn a mapping of the signatures’ features to a latent space that suits the OSV task. At the final stage, the proposed scheme utilizes Writer-Dependent (WD) classifiers learned on a few reference samples from each writer. Our system is tested on the three challenging signature datasets, CEDAR, MCYT-75 and GPDS300GRAY. The obtained accuracy in terms of Equal Error Rates (EER) is statistically equivalent to the popular SigNet CNN, despite a significantly smaller training set of signature images and no use of skilled forgeries signatures during training.

Human Robot Collaboration in Industrial Environments

Abstract: The advancement of robotics technology over the last years and the parallel evolution of the AI, Big Data, Industry 4.0 and Internet of Things (IoT) paradigms have paved the ground for applications that extend far beyond the use of robots as mindless repetitive machines. The number of technical configurations/solutions grows exponentially when considering factors such as (a) the particularities of the task to be performed (e.g. type of part, weight, dimensions, process to be carried out etc.) (b) the type of robots that can address these requirements (fixed or mobile robots, high/low payload, exoskeletons, aerial robots etc.), (c) the type of collaboration and interaction that would be appropriate for the task and (d) the special requirements of the production domain where such tasks are needed. This chapter aims to present the existing approaches on the implementation of human robot collaborative applications and highlight the trends towards achieving seamless integration of humans and robots as co-workers in the factories of the future.

Synthesis of Zn/Cu metal ion modified natural palygorskite clay – TiO2 nanocomposites for the photocatalytic outdoor and indoor air purification

Abstract: In this work, natural palygorskite clay was coupled with TiO2 (anatase) nanocrystals to obtain nanocomposites, in order to be tested as photocatalysts for outdoor and indoor air de-pollution. Three types of palygorskite, i.e., untreated (P) and metal treated, namely Zn-modified (Zn-P) and Cu-modified (Cu-P) palygorskite, were firstly synthesized. Afterward, these three kinds of samples were loaded with 70 wt% TiO2 nanoparticles, using hydrothermal treatment with titanium isopropoxide, abbreviated as P-TiO2, Zn-P-TiO2 and Cu-P-TiO2 nanocomposites, respectively. The nanostructure of all samples was gingerly characterized using a series of spectroscopic and microscopy techniques, including XRD, XPS, ATR-FTIR, TEM, BET and DRS. The photocatalytic performance of the nanocomposites to the decomposition of air pollutants was evaluated in the oxidation of NOx and acetaldehyde under both UV and visible light illumination, while a direct comparison to the corresponding photocatalytic performance of the reference TiO2 photocatalyst (P25) was also made. The results showed that the nanocomposites can be significantly more effective than P25 in the oxidation of NOx under UV light (∼3 times higher) and acetaldehyde under visible light (∼2 times higher). The recorded activities, as well as the lower TiO2 demand, make the palygorskite-based nanocomposites very promising catalysts for both outdoor (NOx) and indoor (acetaldehyde) air purification.

A cubic spline layerwise spectral finite element for robust stress predictions in laminated composite and sandwich strips

Abstract: A new theoretical and numerical tool, comprising of a novel cubic Hermite spline layerwise theory and a spectral strip finite element with integration points collocated to its nodes and high-order polynomial shape functions, is evaluated regarding its capability to predict intralaminar and interlaminar stresses in laminated and sandwich composite strips. Stress predictions in various laminated and thick sandwich beams are presented and compared with exact solutions, high-fidelity plane-strain FE models and reported zig-zag layerwise models. Emphasis is placed on the capability of the present model to predict interlaminar stresses on the free-edges, at ply interfaces, in resin-rich layers and in laminates with artificial delaminations . All numerical results illustrate the capabilities of the present computational tool to provide accurate and robust interlaminar stress predictions implementing coarse discretization , thus ensuring the validity and rapid convergence of the combined higher-order layerwise laminate theory and spectral finite element model.

Behavioral and neurochemical profile of MK-801 adult zebrafish model: Forebrain β2-adrenoceptors contribute to social withdrawal and anxiety-like behavior

Abstract: Deficits in social communication and interaction are core clinical symptoms characterizing multiple neuropsychiatric conditions, including autism spectrum disorder (ASD) and schizophrenia. Interestingly, elevated anxiety levels are a common comorbid psychopathology characterizing individuals with aberrant social behavior. Despite recent progress, the underlying neurobiological mechanisms that link anxiety with social withdrawal remain poorly understood. The present study developed a zebrafish pharmacological model displaying social withdrawal behavior, following a 3-h exposure to 4 μΜ (+)-MK-801, a non-competitive N-methyl-d-aspartate (NMDA) receptor antagonist, for 7 days. Interestingly, MK-801-treated zebrafish displayed elevated anxiety levels along with higher frequency of stereotypical behaviors, rendering this zebrafish model appropriate to unravel a possible link of catecholaminergic and ASD-like phenotypes. MK-801-treated zebrafish showed increased telencephalic protein expression of metabotropic glutamate 5 receptor (mGluR5), dopamine transporter (DAT) and β2-adrenergic receptors (β2-ARs), supporting the presence of excitation/inhibition imbalance along with altered dopaminergic and noradrenergic activity. Interestingly, β2-ARs expression, was differentially regulated across the Social Decision-Making (SDM) network nodes, exhibiting increased levels in ventral telencephalic area (Vv), a key-area integrating reward and social circuits but decreased expression in dorso-medial telencephalic area (Dm) and anterior tuberal nucleus (ATN). Moreover, the co-localization of β2-ARs with elements of GABAergic and glutamatergic systems, as well as with GAP-43, a protein indicating increased brain plasticity potential, support the key-role of β2-ARs in the MK-801 zebrafish social dysfunctions. Our results highlight the importance of the catecholaminergic neurotransmission in the manifestation of ASD-like behavior, representing a site of potential interventions for amelioration of ASD-like symptoms.

Combat Tanking in Education

Abstract: This study examines the impact on engagement and affective outcomes of playful learning in social virtual reality (SVR) for distance and open education settings and aims to provide a practical framework for playful learning design. Three case studies in the United States and Greece were examined where playful learning was organized for e-learning. Data collection methods include questionnaires, observation of online course meetings, reviewing of course communications and chat logs records, student and instructor interviews, student coursework assessments, and reflections. Findings indicated that playful learning experiences in SVR can increase academic interest, intrinsic motivation, engagement level, satisfaction, and completion rates. Instructor genuine investment in a thoughtful, sophisticated humorous approach was vital for student buy-in. Finally, guiding principles for playful learning design in SVR are summarized in a model involving four dimensions: theme, actions, narrative, and auxiliary components (TANC).