Search Results (54)

Oil spills on the water surface pose a significant environmental hazard, underscoring the critical need for developing Artificial Intelligence (AI) detection methods. Utilizing Unmanned Aerial Vehicles (UAVs) can significantly improve the efficiency of oil spill detection at early stages, reducing environmental damage; however, there is a lack of training datasets in the domain. In this paper, LADOS is introduced, an aeriaL imAgery Dataset for Oil Spill detection, classification, and localization by incorporating both liquid and solid classes of low-altitude images. LADOS comprises 3388 images annotated at the pixel level across six distinct classes, including the background. In addition to including a general oil class describing various oil spill appearances, LADOS provides a detailed categorization by including emulsions and sheens. Detailed examination of both instance and semantic segmentation approaches is illustrated to validate the dataset’s performance and significance to the domain. The results on the test set demonstrate an overall performance exceeding 66% mean Intersection over Union (mIoU), with specific classes such as oil and emulsion to surpass 74% of IoU part of the experiments. Full article

Neural stem cells (NSCs) are crucial components of the nervous system, primarily located in the subventricular zone (SVZ) and subgranular zone (SGZ). The SVZ neural stem cell niche (NSCN) is a specialized microenvironment where growth factors and extracellular matrix (ECM) components collaborate to regulate NSC self-renewal and differentiation. Despite its importance, our understanding of the SVZ remains incomplete due to the inherent challenges of animal research, particularly given the tissue’s dynamic nature. To address these limitations, we developed a proof-of-concept, dynamic, and tissue-specific 3D organotypic SVZ model to reduce reliance on animal models. This static 3D organotypic model integrates a region-specific decellularized ECM derived from the SVZ, mimicking the native NSCN and supporting mouse-derived ependymal cells (ECs), radial glial cells (RGCs), astrocytes, and NSCs. To further improve physiological relevance, we incorporated a dynamic microfluidic culture system (SVZonChip), replicating cerebrospinal fluid (CSF) flow as observed in vivo. The resulting SVZonChip platform, combining region-specific ECM proteins with dynamic culture conditions, provides a sustainable and reproducible tool to minimize animal model use. It holds significant promise for studying SVZ-related diseases, such as congenital hydrocephalus, stroke, and post-stroke neurogenesis, while advancing translational research and enabling personalized medicine protocols. Full article

Background/Objectives: Healing of colonic anastomoses is critical to surgical recovery, particularly under obstructive ileus conditions. Adhesive biological materials such as albumin/glutaraldehyde glue (Bioglue) show potential in enhancing anastomotic healing and minimizing complications. This study investigates the effect of Bioglue on colonic anastomoses healing under obstructive ileus conditions in rats. Methods: Eighty albino Wistar rats were divided into control, ileus, Bioglue, and ileus + Bioglue groups (n = 20 each). Subgroups (n = 10) were sacrificed on the 4th or 8th postoperative day. In the control and Bioglue groups, end-to-end anastomoses were performed after colonic resection. In the ileus and ileus + Bioglue groups, obstructive ileus was induced by colonic ligation, followed by resection and primary anastomosis. Bioglue was applied in the Bioglue and ileus + Bioglue groups. Assessments included bursting pressure, peritoneal adhesion and inflammation scores, and biochemical markers (fibroblast activity, neoangiogenesis, collagen deposition, hydroxyproline, and collagenase concentrations). Results: Bursting pressure and fibroblast activity were significantly higher in the ileus + Bioglue group compared to the ileus group on both postoperative days. Although anastomotic rupture occurred in the ileus and ileus + Bioglue groups, the incidence was not significantly different from the control and Bioglue groups. Ileus + Bioglue showed significantly higher adhesion scores, inflammatory infiltration, neoangiogenesis, and collagen deposition compared to the control and ileus groups. Hydroxyproline was significantly elevated in the ileus + Bioglue group on the 8th day. Collagenase I concentrations were higher in ileus + Bioglue but not significant. Conclusions: Bioglue application enhances colonic anastomotic healing under obstructive ileus conditions, improving mechanical strength and promoting tissue repair by the 4th and 8th postoperative days. These findings support its potential clinical application. Full article

Background/Objectives: Surgical Site Infections (SSIs) rank among the most common complications following stoma takedown and lead to increased morbidity, increased Length of Hospital Stay (LOS), and higher healthcare costs. Negative Pressure Wound Therapy (NPWT) systems have emerged as a promising option for optimizing wound management and minimizing SSI rates. This systematic review and meta-analysis compares postoperative outcomes of NPWT and conventional Non-Pressure Dressings following stoma reversal. Methods: A search of the literature published up to 1 September 2024 was conducted across MEDLINE/PubMed, and the Cochrane Central Register of Controlled Trials (CENTRAL), and Scopus, as well as ClinicalTrials.gov. Only Randomized Controlled Trials (RCTs) were included. The primary outcome was SSI rate, while secondary outcomes included time to complete wound healing, LOS, and patient-reported wound cosmesis. Quality assessment was performed using the Cochrane Risk of Bias 2 (RoB 2) tool. The results were synthesized using means and Standard Deviations for continuous variables, counts and percentages for categorical variables, and presented as Odds Ratios (OR) or Mean Differences (MD) with 95% Confidence Intervals, using random or fixed effects models based on heterogeneity (I²). Results: Six RCTs, including 328 patients, were ultimately eligible for inclusion. No significant difference was revealed in SSI rates between the NPWT and conventional dressing groups (OR = 0.95; 95% CI: 0.27–3.29; p = 0.94; I² = 38%). Time to complete wound healing was significantly lower in the NPWT group compared to conventional dressings (MD = −3.78 days; 95% CI: −6.29 to −1.27; p = 0.003). Two studies reported a lower rate of wound healing complications other than SSIs in the NPWT group (OR = 0.22; 95% CI: 0.05–1.09; p = 0.06). No substantial differences were observed in terms of LOS (MD = −0.02 days; 95% CI: −1.22 to 1.17; p = 0.97) and patient-reported wound cosmesis (SMD = 0.31; 95% CI: −0.49 to 1.11; p = 0.44). The review’s limitations include potential risk of bias, variability in study designs, and heterogeneity between studies. Conclusions: NPWT contributes to improved wound management through reducing wound healing time compared to Non-Pressure Dressings after stoma reversal, although it does not appear to substantially impact SSI rates, LOS, or patient-assessed wound cosmesis. Further large-scale, multicenter RCTs are necessary to validate these results and identify patient populations most likely to benefit from NPWT application. Full article

The increasing complexity of energy grids, driven by rising demand and unpredictable residential consumption, highlights the need for efficient demand response (DR) strategies and data-driven services. This paper proposes a machine learning-based framework for DR that clusters users based on their consumption patterns and categorizes individual usage into distinct profiles using K-means, Hierarchical Agglomerative Clustering, Spectral Clustering, and DBSCAN. Key features such as statistical, temporal, and behavioral characteristics are extracted, and the novel Household Daily Load (HDL) approach is used to identify residential consumption groups. The framework also includes context analysis to detect daily variations and peak usage periods for individual users. High-impact users, identified by anomalies such as frequent consumption spikes or grid instability risks using IsolationForest and kNN, are flagged. Additionally, a classification service integrates new users into the segmented portfolio. Experiments on real-world datasets demonstrate the framework’s effectiveness in helping energy managers design tailored DR programs. Full article

Gas cylinder detection and the identification of their characteristics hold considerable potential for enhancing safety and operational efficiency in several applications, including industrial and warehouse operations. These tasks gain significance with the growth of online trade, emerging as critical instruments to combat environmental crimes associated with hazardous substances’ illegal commerce. However, the lack of relevant datasets hinders the effective utilization of deep learning techniques within this domain. In this study, we introduce CylinDeRS, a domain-specific dataset for gas cylinder detection and the classification of their attributes in real-world scenes. CylinDeRS contains 7060 RGB images, depicting various challenging environments and featuring over 25,250 annotated instances. It addresses two tasks: (a) the detection of gas cylinders as objects of interest, and (b) the attribute classification of the detected gas cylinder objects for material, size, and orientation. Extensive experiments using state-of-the-art (SotA) models are reported to validate the dataset’s significance and application prospects, providing baselines for further performance evaluation and in-depth analysis. The results show a maximum mAP of 91% for the gas cylinder detection task and a maximum accuracy of 71.6% for the attribute classification task, highlighting the challenges posed by real-world scenarios and underlining the proposed dataset’s importance in advancing the field. Full article

As cities have expanded into floodplains, the need for their protection has become crucial, prompting the evolution of flood studies. Here, we describe the operational tools, methods and processes used in flood risk engineering studies in the 1970s, and we evaluate the technological progress up to the present day. To this aim, we reference relevant regulations and legislation and the recorded experiences of engineers who performed hydrological, surveying and hydraulic studies in the 1970s. These are compared with the operational framework of a contemporary flood risk assessment study conducted in the Pikrodafni basin in the Attica region. We conclude that, without the technologically advanced tools available today, achieving the level of detail and accuracy in flood mapping that is now possible would have been unfeasible, even with significant human resources. However, ongoing urban development and growth continue to encroach upon flood plains that have existed for centuries, contributing to increased flood risk. Full article

Background/Objectives: The rapid evolution of bacterial resistance and the high cost of drug development have attributed greatly to the dearth in drug design. Computational approaches and natural product exploitation offer potential solutions to accelerate drug discovery. Methods: In this research article, we aimed to identify novel antibacterial hits. For the in silico studies, molecular scaffolds from the in-house chemical library of the Department of Pharmacy of Athens (Pharmalab) and the National Cancer Institute (NCI) were screened and selected for further experimental procedures. Compounds from both libraries that were not previously screened for their antimicrobial properties were tested in vitro against Gram-positive and Gram-negative bacterial strains. The microdilution method was used to determine the minimum inhibitory concentrations (MICs). Results: In silico screening identified twenty promising molecules from the NCI and seven from the Pharmalab databases. The unexplored compounds for their antibacterial activity can be characterized as weak strain-specific antimicrobials. The NSC 610491 and NSC 610493 were active against Staphylococcus aureus (MIC: 25 and 12.5 µg/mL, respectively) and methicillin-resistant S. aureus (MRSA) (MIC: 50 and 12.5 µg/mL, respectively). Six out of seven hydroxytyrosol (HTy) compounds were moderately active (MIC: 25–50 µg/mL) against S. aureus, MRSA and Enterococcus faecalis. For the Gram-negative bacteria, no activity was detected (≥100 µg/mL). Conclusions: The tested scaffolds could be considered as promising candidates for novel antimicrobials with improvements. Further experimentation is required to assess mechanisms of action and evaluate the efficacy and safety. Full article

The present study introduces an integrated software approach that provides an automated product design toolkit for customized products like knives, incorporating topology optimization (TO) and numerical simulations in order to streamline engineering workflows during the product development procedure. The modeling framework combines state-of-the-art technologies into a single platform, enabling the design and the optimization of mechanical structures with minimal human intervention. In particular, the proposed solution leverages artificial intelligence (AI), shape optimization methods, and computational tools in order to iteratively optimize material utilization as well as the design of products based on certain criteria. By embedding simulation within the design optimization loop, the developed software module ensures that performance constraints are respected throughout the design process. The case studies are concentrated in designing knives, demonstrating the platform’s ability to reduce design time, enhance product performance and provide rapid iterations of structurally optimized geometries. Finally, it should be noted that this research showcases the potential of integrated modeling technologies towards the transformation of traditional design paradigms, in this way contributing to faster, more reliable and efficient product development in various engineering industries through the training and deployment of AI models in these scientific fields. Full article

Complex microscopic simulation models of strategic Air Traffic Management (ATM) performance assessment and decision-making are hindered by several factors. One of the most important is the existence of hidden parameters—such as aircraft take-off weight (TOW) and the selected cost index (CI)—which, if known, would allow for more effective performance modeling methodologies for assessing Key Performance Indicators (KPIs) at various levels of abstraction/detail, e.g., system-wide, or at the level of individual flights. This research proposes a data-driven methodology for the estimation of flights’ hidden parameters combining mechanistic and advanced Artificial Intelligence/Machine Learning (AI/ML) models. Aiming at microsimulation models, our goal is to study the effect of these estimations on the prediction of flights’ KPIs. In so doing, we propose a novel methodology according to which data-driven methods are trained given optimal trajectories (produced by mechanistic models) corresponding to known hidden parameter values, with the aim of predicting hidden parameters’ values of unseen trajectories. The results show that estimations of hidden parameters support the accurate prediction of KPIs regarding the efficiency of flights: fuel consumption, gate-to-gate time and distance flown. Full article

Background: Rectal prolapse (RP) predominantly affects women over the age of 50 and presents as mucosal, internal, or full thickness prolapse. Strangulated rectal prolapse requires immediate medical intervention, and surgical treatment options include both abdominal and perineal approaches. We aim to present a case series of perineal rectosigmoidectomy performed urgently due to strangulation and argue that Altemeier’s procedure is the preferred method for treating strangulated rectal prolapse. Methods: Perineal rectosigmoidectomy, particularly Altemeier’s procedure, is effective for incarcerated cases. Altemeier’s procedure with diverting ileostomy was used in all three patients. Results: All patients were successfully treated, with no recurrence of prolapse and stool incontinence. Conclusions: Altemeier’s procedure is ideal for the treatment of strangulated rectal prolapse. Full article

Background/Objectives: Ulcerative colitis (UC) is a chronic inflammatory bowel disease with limited effective treatments, prompting the need for investigation of novel therapeutic approaches. Eicosapentaenoic acid (EPA) and gamma-linolenic acid (GLA) have demonstrated potential anti-inflammatory properties, but their combined effects on UC have not been thoroughly investigated. This study aimed to evaluate the effect of the combined administration of EPA and GLA on clinical and histopathologic features of experimental UC models. Methods: Thirty-six male Wistar rats were randomized in three groups (DSS group, Ensure Plus group, and Oxepa group), with twelve rats in each group. Experimental colitis was induced by administrating dextran sulfate sodium (DSS) 8%. The DSS group received tap water, the Ensure Plus group was given a high caloric diet, and the Oxepa group received a special diet containing high levels of EPA and GLA. Disease activity index (DAI) and microscopic activity index (MAI) were measured. Inflammatory markers were calculated both in blood and large intestine, liver, spleen, and lung tissue samples. Neutrophil and macrophage populations were assessed with immunohistochemistry. Results: No significant differences in the DAI index were found between the groups, but the MAI revealed statistically significant differences (p < 0.001). While no significant differences were observed in tumor necrosis factor-alpha (TNF-α) levels, interleukin-17 (IL-17) levels in the large intestine showed statistically significant differences (p = 0.05), with the Ensure Plus and Oxepa groups displaying lower levels compared to the DSS group (p = 0.021 and p = 0.043, respectively). Significant differences in neutrophil infiltration were found in both the large intestine (p < 0.001) and lungs (p = 0.002), with the Oxepa group showing fewer cells. Similarly, significant differences in macrophage infiltration were observed in the large intestine (p = 0.038) and spleen (p < 0.001), with the Oxepa group having lower macrophage counts. Conclusions: In conclusion, the combination of EPA and GLA demonstrates local anti-inflammatory effects and improves the histopathological outcomes in UC. Full article

Background: Since the consensus of ISAPP on the definition of the term “postbiotic” there has been an enthusiasm for publications in review form—their number being disproportionate to the primary research. The aim of this bibliometry is to analyze the bibliometric trends of this newfound interest in the field. Methods: Search of the PubMed database for review articles on postbiotics, published between November 2021 and June 2024. Results: Analysis was performed on 92 review articles, the number corresponding to 2.9 reviews per month. China, Poland, Italy, Iran and India had the maximum productivity among the 32 countries involved; 21 articles were published in 13 journals with the highest impact factor, while 45 were in 16 journals with an IF between 4.0 and 4.9. The authors were mainly affiliated to universities with specialization in both basic research and technology, as well as food science. The top five publications regarding the citations received, published in Foods (2), EBioMedicine, Biomolecules, and Front. Nutr., have collected between 138 and 109 citations. Conclusions: The ever-growing number of reviews regarding postbiotics is perhaps disproportionate to the actual original research in the field. Further clinical trials would extend and deepen the subject and facilitate the drowning of more robust conclusions in relation to their effects. Full article

Predicting errors in home appliances is crucial for maintaining the reliability and efficiency of smart homes. However, there is a significant lack of such data on appliance malfunctions that can be used in developing effective anomaly detection models. This research paper presents a novel approach for simulating errors of heterogeneous home appliance power consumption patterns. The proposed model takes normal consumption patterns as input and employs advanced algorithms to produce labeled anomalies, categorizing them based on the severity of malfunctions. One of the main objectives of this research involves developing models that can accurately reproduce anomaly power consumption patterns, highlighting anomalies related to major, minor, and specific malfunctions. The resulting dataset may serve as a valuable resource for training algorithms specifically tailored to detect and diagnose these errors in real-world scenarios. The outcomes of this research contribute significantly to the field of anomaly detection in smart home environments. The simulated datasets facilitate the development of predictive maintenance strategies, allowing for early detection and mitigation of appliance malfunctions. This proactive approach not only improves the reliability and lifespan of home appliances but also enhances energy efficiency, thereby reducing operational costs and environmental impact. Full article

Scandium (Sc) isotopes have recently attracted significant attention in the search for new radionuclides with potential uses in personalized medicine, especially in the treatment of specific cancer patient categories. In particular, Sc-43 and Sc-44, as positron emitters with a satisfactory half-life (3.9 and 4.0 h, respectively), are ideal for cancer diagnosis via Positron Emission Tomography (PET). On the other hand, Sc-47, as an emitter of beta particles and low gamma radiation, may be used as a therapeutic radionuclide, which also allows Single-Photon Emission Computed Tomography (SPECT) imaging. As these scandium isotopes follow the same biological pathway and chemical reactivity, they appear to fit perfectly into the “theranostic pair” concept. A step-by-step description, initiating from the moment of scandium isotope production and leading up to their preclinical and clinical trial applications, is presented. Recent developments related to the nuclear reactions selected and employed to produce the radionuclides Sc-43, Sc-44, and Sc-47, the chemical processing of these isotopes and the main target recovery methods are also included. Furthermore, the radiolabeling of the leading chelator, 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA), and its structural analogues with scandium is also discussed and the advantages and disadvantages of scandium complexation are evaluated. Finally, a review of the preclinical studies and clinical trials involving scandium, as well as future challenges for its clinical uses and applications, are presented. Full article