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Abstract We aimed to compare fluorescein angiography (FA)-based classification of macular neovascularisation (MNV) with optical coherence tomography (OCT)-based classification, as well as examine differences in retinal fluid among OCT MNV types. We analyzed baseline FA and OCT images from 704 eyes of neovascular AMD patients across two multicenter trials, with grading conducted at the Vienna Reading Center. Using a validated AI tool (RetInSight Fluid Monitor Version 2), we localized and quantified retinal fluid. Kappa coefficients for agreement between FA and OCT MNV types were 0.58 [0.52; 0.64] (type 1/occult), 0.46 [0.38; 0.55] (type 2/classic), and 0.53 [0.44; 0.62] (type 3/RAP). Significant differences in the volumes of intraretinal fluid (IRF), subretinal fluid (SRF), and pigment epithelial detachment (PED) were noted among MNV types (p more...

Land snails and the Aegean Archipelago offer an intriguing combination for studying biodiversity, biogeography and ecology. A region with high environmental and temporal heterogeneity and a tri-continental biotic influence and a group of organisms with low active dispersal abilities, high endemism, as well as the particularity to leave shells as traces of past presence, set an ideal stage for testing biodiversity patterns and exploring multisource threats, especially in the era of the ongoing biodiversity crisis. In this study, we examine Helix godetiana, a large-sized, threatened and endemic land snail of the central and south Aegean Islands. The species has been extirpated from 22 of the 32 islands where it was historically present. We identify potential drivers of its extinction, as Helix godetiana faces several threats across its current range, including competitive exclusion by Cornu aspersum, a species with continuing expansion in the Aegean and climate change disrupting its unusual breeding cycle, which occurs in late spring. Our findings shed light on potentially major, yet previously unexplored, threats on endemic molluscs of the Aegean Islands, a European biodiversity hotspot. more...

Abstract Background The present study aimed to assess the efficacy of applying active learning and integrated methodologies in the undergraduate Pathology medical education curriculum. Another goal was to acquire student feedback and explore the students’ motivation and perceptions on Pathology education. Methods Our study involved two parts: (1) a quasi-experimental part, involving medical students enrolled in our Pathology course. An optional educational intervention was offered until the end of the semester, in parallel with the already established curriculum. The intervention involved integrated case-based seminars and group-based presentations of Pathology cases. We used a multivariate regression model in order to better assess the educational effectiveness of our method; and (2) a questionnaire-based cross-sectional survey was held at the end of the semester. The set of questions for the intervention group mainly involved feedback about our educational method, while the questions for the control group involved questions about Pathology education in general. Results 348 Students completed the study. The performance of the intervention group was significantly improved at post-test. From the questionnaire, we found that intervention participants gave positive feedback, while their main reason for participation was because they already valued the Pathology professor’s teaching style. As for non-participants, even though most of them were interested in an integrated/experiential approach, more than half chose not to participate because of lack of time in general or in order to study for the final exams. Conclusions Active learning and integrated methodologies seem to be of value in undergraduate Pathology teaching. However, regardless of the instructional approach, shifting the emphasis from purely summative achievement to formative, learning-centered development is essential. A successful educator must therefore not only employ innovative methods but also encourage intrinsic motivation and a deeper, more reflective approach to learning. more...

Human immunodeficiency virus (HIV) has troubled humankind for many years. The rate of new HIV cases is decreasing steadily, mostly because of safer sexual practices and scientific advances in medicine. However, the number of HIV-related trials has significantly increased, as the search for a definite cure for HIV is still fruitless. Our current treatment options involve antiretroviral therapy (ART) with various drug combinations that lower the patients’ viral load in order for the immune system to reconstitute itself. This way, adherent patients achieve a life expectancy similar to the general population. Besides the established treatment protocols, the focus has currently shifted towards secondary pharmaceutical regimen programs that enhance a patient’s immune system and response to opportunistic infections. Vitamins C and D are easily obtainable even in the developing world and are known to improve an individual’s daily life, with vitamin D enhancing the human immune response and vitamin C having an assisting role in both the immune response and as an important antioxidant. Recently, many studies assessing the effect of these vitamins on the progression of HIV have been performed. We aimed to collect and review these studies in order to determine the necessity of the supplementation of these vitamins in HIV-infected patients, which might complement the existing ART. To this day, the scientific community is conflicted, and more studies must be conducted before a definite conclusion about these vitamins’ effects on HIV patients can be reached. more...

Abstract Background This observational study aims to establish the feasibility of using x-ray images of radio-opaque chemoembolisation deposits in patients as a method for real-time image-guided radiation therapy of hepatocellular carcinoma. Methods This study will recruit 50 hepatocellular carcinoma patients who have had or will have stereotactic ablative radiation therapy and have had transarterial chemoembolisation with a radio-opaque agent. X-ray and computed tomography images of the patients will be analysed retrospectively. Additionally, a deep learning method for real-time motion tracking will be developed. We hypothesise that: (i) deep learning software can be developed that will successfully track the contrast agent mass on two thirds of cone beam computed tomography (CBCT) projection and intra-treatment images (ii), the mean and standard deviation (mm) difference in the location of the mass between ground truth and deep learning detection are ≤ 2 mm and ≤ 3 mm respectively and (iii) statistical modelling of study data will predict tracking success in 85% of trial participants. Discussion Developing a real-time tracking method will enable increased targeting accuracy, without the need for additional invasive procedures to implant fiducial markers. Trial registration Registered to ClinicalTrials.gov (NCT05169177) 12th October 2021. more...

Introduction A major obstacle in understanding the relationship between diet and non-communicable diseases (NCDs) lies in the subjectivity and the bias in traditional dietary intake assessment methods. Food diaries, 24-hour food recall interviews, and food frequency questionnaires (FFQ) result in under- and over-reporting of nutrient and energy intake, compromising the accuracy of studies linking diet to NCDs. The emergence of image classification technology has facilitated a new approach to dietary intake assessment which addresses the subjective limitations associated with traditional self-reporting methods. Furthermore, a need to integrate multi-omics and advanced health analyses to comprehensively characterise NCD risk presents an opportunity to combine a range of technologies to better understand diet-induced NCD. Method This observational study will adopt an enhanced surveillance method, whereby we will utilise wearable cameras and activity monitors to record dietary intake, physical activity, and sleep. Participants will wear these for 3 separate one-week periods at home (with a 2 and 3-week break in between each period). At the end of each monitoring period, participants will attend a study visit at the clinical research facility, where they will undergo body composition assessments, as well as cardiovascular disease (CVD) risk and autonomic nervous system health analysis using state-of-the-art technologies that measure Advanced Glycation End products (AGE) and accelerated photoplethysmography (APG). At the end of the first and last monitoring period, participants will also provide blood, urine, stool, and breath samples, and an in-depth interview will also be conducted during the final visit to assess participants’ perceptions towards the novel technologies. The study parameters will be integrated to advance our insights into how diet intricately influences the mechanisms underlying NCDs. CTRI registration number https://www.isrctn.com/ISRCTN11564218 more...

Introduction Current dietary assessment methods face challenges in accurately capturing individuals’ dietary habits, undermining the efficacy of public health strategies. The ‘Standardised and Objective Dietary Intake Assessment Tool’ (SODIAT)-1 study aims to assess the effectiveness of three emerging technologies (urine and capillary blood biomarkers, and wearable camera technology) and two online self-reporting dietary assessment tools to monitor dietary intake. Methods This randomised controlled crossover trial will recruit 30 participants (aged 18-70 years and BMI of 20-30 kg/m 2) from Imperial College London and the University of Reading. Exclusion criteria include recent weight change, food allergies/intolerances, following restrictive diets, certain health conditions and medication use. Interested volunteers will be directed to an online screening questionnaire via REDCap and eligible participants will attend a pre-study visit. Volunteers will consume, in a random order, two highly-controlled diets (compliant and non-compliant with UK guidelines) for four days each. Each study arm will be separated by at least one-week. During each test period, dietary intake will be monitored continuously using wearable cameras and self-recorded using eNutri (food frequency questionnaire) and Intake24 (24-hour dietary recall). Urine and capillary blood samples will be collected for biomarker analysis. Data analysis will assess the accuracy of dietary reporting across these methods using Lin’s concordance correlation coefficient. Discussion and ethical considerations This study introduces a novel approach to dietary assessment, addressing the limitations of traditional methods by reducing misreporting and enhancing inclusivity, particularly for underrepresented populations with literacy or language barriers. However, challenges persist, such as variability in biomarker data due to failure to adhere to sample storage requirements and the practicalities of continuously wearing cameras. To protect privacy, participants will be instructed to remove cameras at inappropriate times, and artificial intelligence will be used to blur all images captured apart from food. more...

The tourism industry is placing growing emphasis on the significance of managing and seeking tourist services through information systems. Although scholarly research in these fields has increased, the literature has not been thoroughly examined. This study utilizes the PRISMA methodology to examine pertinent literature and ascertain the influential factors. This article examines 50 hospitality and tourism articles located on the SCOPUS database. A conceptual model is derived from the literature research, which focuses on the management and information seeking behaviors within the tourism industry. The study identifies research gaps and offers implications that contribute to the body of extant knowledge. more...

Background: Aberrant functional connectivity is a hallmark of schizophrenia. The precise nature and mechanism of dysconnectivity in schizophrenia remains unclear, but evidence suggests that dysconnectivity is different in wake versus sleep. Microstate analysis uses electroencephalography (EEG) to investigate large-scale patterns of coordinated brain activity by clustering EEG data into a small set of recurring spatial patterns, or microstates. We hypothesized that this technique would allow us to probe connectivity between brain networks at a fine temporal resolution and uncover previously unknown sleep-specific dysconnectivity. Methods: We studied microstates during sleep in patients with schizophrenia by analyzing high-density EEG sleep data from 114 patients with schizophrenia and 79 control participants. We used a polarity-insensitive k-means analysis to extract a set of 6 microstate topographies. Results: These 6 states included 4 widely reported canonical microstates. In patients and control participants, falling asleep was characterized by a shift from microstates A, B, and C to microstates D, E, and F. Microstate F was decreased in patients during wake, and microstate E was decreased in patients during sleep. The complexity of microstate transitions was greater in patients than control participants during wake, but this reversed during sleep. Conclusions: Our findings reveal behavioral state–dependent patterns of cortical dysconnectivity in schizophrenia. Furthermore, these findings are largely unrelated to previous sleep-related EEG markers of schizophrenia such as decreased sleep spindles. Therefore, these findings are driven by previously undescribed sleep-related pathology in schizophrenia. more...

Introduction: The association between the visceral swallowing pattern (VSP) and dentofacial abnormalities remains controversial. This cross-sectional study aimed to investigate the association between the VSP and various factors including type of birth, gender, tongue posture, lip incompetence, eruption of primary molars, habits and the presence of malocclusions in children with primary and early mixed dentition. Material and method: A total of 219 children (102 boys and 117 girls) were evaluated using a combination of a questionnaire and a structured clinical examination by one pediatric specialist dentist. Kittel’s method of tongue posture evaluation and the Payne technique for assessment of swallowing pattern were included in the clinical examination of myofunctional status. After checking for normality, normal and non-normal distributed data were analyzed using two-sample t-test and Mann-Whitney U test, respectively. Analysis of categorical variables was done using a chi-square test, and Bonferroni correction was used as correction for multiple comparisons. Results: A total of 56.2 % of the study population had a VSP. The chi-square test indicated a statistically significant higher presence of VSP in male gender. Statistically significant associations were seen between the VSP and lip incompetency, pathologic resting tongue position, habits, anterior open bite and increased overjet. On the other hand, no statistically significant associations were found between VSP and children’s age within the sample population, type of birth, uni- or bilateral crossbites, increased overbite, edge-to-edge anterior bite or completion of eruption of primary molars and/or permanent incisors. Conclusions: The association between VSP and male gender, pathologic tongue posture, lip incompetency and habits and occlusal traits such as anterior open bite and increased anterior overjet is supported by the results of the present study. more...

The use of wireless sensor networks (WSNs) in critical applications such as environmental monitoring, smart agriculture, and industrial automation has created significant security concerns, particularly due to the broadcasting nature of wireless communication. The absence of physical-layer authentication mechanisms exposes these networks to threats like spoofing, compromising data authenticity. This paper introduces a multi-attribute physical layer authentication (PLA) scheme to enhance WSN security by using physical attributes such as received signal strength indicator (RSSI), battery level (BL), and altitude. The LoRaWAN join procedure, a key risk due to plain text transmission without encryption during initial communication, is addressed in this study. To evaluate the proposed approach, a partially synthesized dataset was developed. Real-world RSSI values were sourced from the LoRa at the Edge Dataset, while BL and altitude columns were added to simulate realistic sensor behavior in a forest fire detection scenario. Machine learning (ML) models, including Logistic Regression (LR), Random Forest (RF), and K-Nearest Neighbors (KNN), were compared with deep learning (DL) models, such as Multi-Layer Perceptron (MLP) and Convolutional Neural Networks (CNN). The results showed that RF achieved the highest accuracy among machine learning models, while MLP and CNN delivered competitive performance with higher resource demands. more...

A significant challenge in human activity recognition lies in the limited size and diversity of training datasets, which can lead to overfitting and the poor generalization of deep learning models. Common solutions include data augmentation and transfer learning. This paper introduces a novel data augmentation method that simulates occlusion by artificially removing body parts from skeleton representations in training datasets. This contrasts with previous approaches that focused on augmenting data with rotated skeletons. The proposed method increases dataset size and diversity, enabling models to handle a broader range of scenarios. Occlusion, a common challenge in real-world HAR, occurs when body parts or external objects block visibility, disrupting activity recognition. By leveraging artificially occluded samples, the proposed methodology enhances model robustness, leading to improved recognition performance, even on non-occluded activities. more...

Multimodal interaction is a transformative human-computer interaction (HCI) approach that allows users to interact with systems through various communication channels such as speech, gesture, touch, and gaze. With advancements in sensor technology and machine learning (ML), multimodal systems are becoming increasingly important in various applications, including virtual assistants, intelligent environments, healthcare, and accessibility technologies. This survey concisely overviews recent advancements in multimodal interaction, interfaces, and communication. It delves into integrating different input and output modalities, focusing on critical technologies and essential considerations in multimodal fusion, including temporal synchronization and decision-level integration. Furthermore, the survey explores the challenges of developing context-aware, adaptive systems that provide seamless and intuitive user experiences. Lastly, by examining current methodologies and trends, this study underscores the potential of multimodal systems and sheds light on future research directions. more...

Although robust evidence has been accumulating over the last decades supporting the effectiveness of career counseling in various populations, yet there are scarce conceptual or empirical studies investigating the impact of distinct approaches, such as traditional-"psychometric," narrative, or a mixed (integrative) one. The primary aim of this paper is to make a contribution in the field, providing a synthetic overview of contemporary research findings regarding the effectiveness of narrative and mixed career counseling approaches with a special focus on university students. The recent trend of utilizing mixed approaches in career assessment and intervention is also emphasized in the article, suggesting they may have a great potential in helping young adults advance meaning-making about career and life design. Finally, a discussion of both benefits and challenges relating to narrative and mixed interventions along with recommendations for extending research in the area of assessing career interventions' effectiveness for university students is provided. more...

The integration of soft robots in medical procedures has significantly improved diagnostic and therapeutic interventions, addressing safety concerns and enhancing surgeon dexterity. In conjunction with artificial intelligence, these soft robots hold the potential to expedite autonomous interventions, such as tissue palpation for cancer detection. While cameras are prevalent in surgical instruments, situations with obscured views necessitate palpation. This proof-of-concept study investigates the effectiveness of using a soft robot integrated with Electrical Impedance Tomography (EIT) capabilities for tissue palpation in simulated in vivo inspection of the large intestine. The approach involves classifying tissue samples of varying thickness into healthy and cancerous tissues using the shape changes induced on a hydraulically-driven soft continuum robot during palpation. Shape changes of the robot are mapped using EIT, providing arrays of impedance measurements. Following the fabrication of an in-plane bending soft manipulator, the preliminary tissue phantom design is detailed. The phantom, representing the descending colon wall, considers induced stiffness by surrounding tissues based on a mass-spring model. The shape changes of the manipulator, resulting from interactions with tissues of different stiffness, are measured, and EIT measurements are fed into a Long Short-Term Memory (LSTM) classifier. Train and test datasets are collected as temporal sequences of data from a single training phantom and two test phantoms, namely, A and B, possessing distinctive thickness patterns. The collected dataset from phantom B, which differs in stiffness distribution, remains unseen to the network, thus posing challenges to the classifier. The classifier and proposed method achieve an accuracy of 93% and 88.1% on phantom A and B, respectively. Classification results are presented through confusion matrices and heat maps, visualising the accuracy of the algorithm and corresponding classified tissues. more...

Konstantinos G Moulakakis,1,* Christos F Pitros,1,* Ioannis T Theodosopoulos,2 Spyridon N Mylonas,3 John D Kakisis,2 Christos Manopoulos,4 Nikolaos PE Kadoglou5 1Department of Vascular Surgery, Patras University Hospital, University of Patras, Patras, Greece; 2Department of Vascular Surgery, “Attikon” University Hospital, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece; 3Department of Vascular and Endovascular Surgery, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, 50937, Germany; 4Biofluid Mechanics and Biomedical Engineering Laboratory, Fluids Section, School of Mechanical Engineering, National Technical University of Athens, Athens, Greece; 5Medical School, University of Cyprus, Nicosia, Cyprus*These authors contributed equally to this workCorrespondence: Konstantinos G Moulakakis, Associate Professor of Vascular Surgery, Vascular Surgery Department, Patras University Hospital, Patras, Greece, Tel +0030 6937357508, Email konmoulakakis@yahoo.grAbstract: It has been documented that large-artery stiffness is independently associated with increased cardiovascular risk and may potentially lead to heart and kidney failure and cerebrovascular disease. A systematic review of studies investigating changes in arterial stiffness in patients undergoing endovascular repair of aortic disease was conducted. In addition, a review of the available literature was performed, analyzing findings from studies using the cardio-ankle vascular index (CAVI) as a marker of arterial stiffness. Overall, 26 studies were included in the present analysis. Our research revealed a high heterogeneity of included studies regarding the techniques used to assess the aortic stiffness. Aortic stiffness was assessed by pulse wave velocity (PWV), elastic modulus (Ep), and augmentation index (AI). Currently a few studies exist investigating the role of CAVI in patients having an aortic aneurysm or undergoing endovascular aortic repair. The majority of studies showed that the treatment of an abdominal aortic aneurysm (AAA) either with open repair (OR) or endovascular aortic repair (EVAR) reduces aortic compliance significantly. Whether EVAR reconstruction might contribute a higher effect on arterial stiffness compared to OR needs further focused research. An increase of arterial stiffness was uniformly observed in studies investigating patients following thoracic endovascular aortic repair (TEVAR), and the effect was more pronounced in young patients. The effects of increased arterial stiffness after EVAR and TEVAR on the heart and the central hemodynamic, and an eventual effect on cardiac systolic function, need to be further investigated and evaluated in large studies and special groups of patients.Keywords: arterial stiffness, pulse wave velocity, PWV, cardio-ankle vascular index, CAVI, augmentation index, AI, aortic aneurysm, endovascular aortic aneurysm repair, EVAR, thoracic endovascular aortic aneurysm repair, TEVAR more...

Greece is covered by a high percentage of carbonate rocks, resulting in a significant number of over 10,000 caves within its territory. Their fauna is not well known. Concerning gastropods, 68 terrestrial species have been reported from 70 caves. In this study, we contribute to the knowledge of the snails inhabiting Greek caves. We analyzed the literature and studied all the material deposited in the Natural History Museum of Crete, to create a first comprehensive list of gastropods of Greek caves. The number of caves from which gastropod species were reported increased to 182, while the number of known terrestrial species increased to 113. Fourteen of these species live only in caves, twelve of which are endemic of Greece. However, the fauna of Greek caves is still understudied. With the increasing exploration of Greek caves, the number of the known cave-dwelling gastropod species will increase and new species will be discovered. more...

The Energy Performance of Buildings Directive (EPBD) has set a target to achieve carbon-neutral building stock and generate 80% of its electricity from renewable sources by 2050. While Model Predictive Control (MPC) can contribute significantly to energy flexibility in buildings, its remote implementation remains relatively unexplored, especially in the residential sector. The purpose of this research is to demonstrate the reliability, robustness, and computational efficiency of a cloud-based application of an MPC called Smart Energy Management (SEM) on a multi-family residential building. The SEM was tested on a virtual building model in TRNSYS using an open-source distributed event streaming platform for data exchange and synchronization. Simplified models for thermal behavior prediction, including an R3C3 model of the building, were developed in C++. The SEM was evaluated in eight scenarios with varying weather conditions, optimization criteria, and runtime periods. The results demonstrate that the SEM maintains stability and robustness over a 2-week period with a 15-minute planning resolution while ensuring thermal comfort. The C++ implementation of the optimization algorithm enables SEM deployment on low-spec servers, supporting cost-effective applications in real buildings with minimal intervention. more...

This paper presents a method for estimating reservoir storage capacity using the Gould–Dincer normal formula (G-DN), enhanced by the possibility theory. The G-DN equation is valuable for regional studies of reservoir reliability, particularly under climate change scenarios, using regional statistics. However, because the G-DN formula deals with measured data, it introduces a degree of uncertainty and fuzziness that traditional probability theory struggles to address. Possibility theory, an extension of fuzzy set theory, offers a suitable framework for managing this uncertainty and fuzziness. In this study, the G-DN formula is adapted to incorporate fuzzy logic, and the possibilistic nature of reservoir capacity is translated into a probabilistic framework using α-cuts from the possibility theory. These α-cuts approximate probability confidence intervals with high confidence. Applying the proposed methodology, in the present crisp case with the storage capacity D = 0.75, the value of the capacity C was found to be 1271×106 m3, and that for D = 0.5 was 634.5×106 m3. On the other hand, in the fuzzy case using the possibility theory, the value of the capacity for D = 0.75 is the internal [315,5679]×106 m3 and for D = 0.5 the value is interval [158,2839]×106 m3, with a probability of ≥95% and a risk level of α = 5% for both cases. The proposed approach could be used as a robust tool in the toolkit of engineers working on irrigation, drainage, and water resource projects, supporting informed and effective engineering decisions. more...