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A motivating class of compounds with interest in the research field of biological active metallopharmaceuticals for cancer treatment is based on organometallic complexes of Sn(IV), exhibiting advantages such as improved cellular uptake and body excretion, lower toxicity, and fewer side effects compared to platinum-based drugs. In this study, the mononuclear organotin coordination complex [(CH3)2SnCl2(mebta)2] was synthesized and characterized using vibrational spectroscopy (IR, Raman), 1H NMR, 13C{1H} NMR, and X-ray crystallography. Its antiproliferative properties were thoroughly assessed across an aggressive triple-negative human breast cancer cell line. Notably, comparative studies with precursor materials verified that the observed biological activity is intrinsic to the complex itself. This study highlights the compound’s ability to induce cell fate by disrupting essential cellular functions, such as proliferation. By exploring the antiproliferative effects of organotin(IV) derivatives, we introduce a novel class of Sn complexes with 1-methylbenzotriazole (mebta), demonstrating significant potential as promising antitumor agents in the field of organotin compounds.

Chios mastic gum (CMG), the resin of Pistacia lentiscus var. Chia, is a product with great ethnopharmacological and economic significance. This study attempts to investigate, for the first time, the activity of CMG, its fractions and isolated compounds against specific enzymes, which play pivotal roles in the degradation of proteins contained in skin connective tissue. Initially, crude CMG was subjected to extraction, fractionation and isolation through different chromatographic techniques to obtain the acidic and neutral fraction of terpenes. Additionally, the characteristic and major active triterpene acids of CMG, masticadienonic and isomasticadienonic acids (MNA, IMNA) were isolated in pure form. All samples were analysed by means of High-Performance Thin-Layer Chromatography (HPTLC) with four distinct development systems to obtain their constituents’ profile. Finally, samples were tested for their ability to inhibit the elastase and collagenase enzymes. According to our findings, for collagenase, a mixture of MNA and IMNA demonstrated the most potent activity with an IC50 value of 31.07 μg/mL, while for elastase CMG’s acidic fraction provided the most promising results with an IC50 value of 17.30 μg/mL. Overall, these results attempt to fill the gap in scientific knowledge about the use of CMG and its constituents in skincare and cosmetic products.

Biodiversity records are of great importance, especially in light of the biodiversity crisis. Here, we present a study on the diversity of rotifers in Bolivia based on an extensive investigation of the literature published so far. Through this approach and an analysis of samples from 207 water bodies of the country, we updated the checklist of reported species. This study revealed a total of 195 species of rotifers previously reported; we identified 153 species in our samples, with 84 of them being reported for the first time in Bolivia. Thus, a total of 279 species are known at present in this country. Our findings suggest that Bolivia has a rich and diverse rotifer community, with many species likely to be unique to the region.

Metal complexes of benzotriazole-type ligands continue to attract the intense interest of many inorganic chemistry groups around the world for a variety of reasons, including their aesthetically beautiful structures, physical properties and applications. 1-methylbenzotriazole (Mebta) is the N-substituted archetype of the parent 1H-benzotriazole. The first attempt to build a “periodic table” of Mebta, which includes its complexes with several metal ions, is described in this work. This, at first glance, trivial ligand has led to interesting results in terms of the chemistry, structures and properties of its metal complexes. This work reviews the to-date published coordination chemistry of Mebta with Mn(II), Fe(II), Fe(III), Co(II), Ni(II), Cu(I), Cu(II), Zn(II), Pd(II), Au(I) and {UVIO2}2+, with emphasis on their preparations, reactivity, structures and properties. Unpublished results from our group comprising other Co(II), Ni(II), Cu(II) and Zn(II) complexes, as well as Cd(II), Hg(II), Ag(I), In(III) and Sn(IV) ones are briefly reported. Mebta can also provide access to 1D and 3D heterometallic thiocyanato-bridged Co(II)/Hg(II) and Ni(II)/Hg(II) compounds. In almost all cases, Mebta behaves as a monodentate ligand with the nitrogen of position 3 of the azole ring as the donor atom. However, there are two copper complexes in which this molecule adopts a bidentate bridging coordination behavior. Our efforts to complete the “periodic table” of Mebta are continued.

In this study, we present an analysis of the fine-tuning required in various inflationary models in order to explain the production of Primordial Black Holes (PBHs). We specifically examine the degree of fine-tuning necessary in two prominent single-field inflationary models: those with an inflection point and those with step-like features in the potential. Our findings indicate that models with step-like features generally require less fine-tuning compared to those with an inflection point, making them more viable for consistent PBH production. An interesting outcome of these models is that, in addition to improved fine-tuning, they may also predict low-frequency signals that can be detected by pulsar timing array (PTA) collaborations. Additionally, we extend our analysis to multifield inflationary models to assess whether the integration of additional fields can further alleviate the fine-tuning demands. The study also explores the role of a spectator field and its impact on the fine-tuning process. Our results indicate that although mechanisms involving a spectator field can circumvent the issue of fine-tuning parameters for PBH production, both multifield models and models with step-like features present promising alternatives. While fine-tuning involves multiple considerations, our primary objective is to evaluate various inflationary models to identify the one that most naturally explains the formation of PBHs. Hence, this study introduces a novel approach by categorizing existing PBH mechanisms, paving the way for subsequent research to prioritize models that minimize the need for extensive fine-tuning.

The coordination chemistry of 2-pyridyl ketoximes continues to attract the interest of many inorganic chemistry groups around the world for a variety of reasons. Cadmium(II) complexes of such ligands have provided models of solvent extraction of this toxic metal ion from aqueous environments using 2-pyridyl ketoxime extractants. Di-2-pyridyl ketone oxime (dpkoxH) is a unique member of this family of ligands because its substituent on the oxime carbon bears another potential donor site, i.e., a second 2-pyridyl group. The goal of this study was to investigate the reactions of cadmium(II) halides and dpkoxH in order to assess the structural role (if any) of the halogeno ligand and compare the products with their zinc(II) analogs. The synthetic studies provided access to complexes {[CdCl2(dpkoxH)∙2H2O]}n (1∙2H2O), {[CdBr2(dpkoxH)]}n (2) and {[CdI2(dpkoxH)]}n (3) in 50–60% yields. The structures of the complexes were determined by single-crystal X-ray crystallography. The compounds consist of structurally similar 1D zigzag chains, but only 2 and 3 are strictly isomorphous. Neighboring CdII atoms are alternately doubly bridged by halogeno and dpkoxH ligands, the latter adopting the η1:η1:η1:μ (or 2.0111 using Harris notation) coordination mode. A terminal halogeno group completes distorted octahedral coordination at each metal ion, and the coordination sphere of the CdII atoms is {CdII(η1 − X)(μ − X)2(Npyridyl)2(Noxime)} (X = Cl, Br, I). The trans-donor–atom pairs in 1∙2H2O are Clterminal/Noxime and two Clbridging/Npyridyl; on the contrary, these donor–atom pairs are Xterminal/Npyridyl, Xbridging/Noxime, and Xbridging/Npyridyl (X = Br, I). There are intrachain H-bonding interactions in the structures. The packing of the chains in 1∙2H2O is achieved via π-π stacking interactions, while the 3D architecture of the isomorphous 2 and 3 is built via C-H∙∙∙Cg (Cg is the centroid of one pyridyl ring) and π-π overlaps. The molecular structures of 1∙2H2O and 2 are different compared with their [ZnX2(dpkoxH)] (X = Cl, Br) analogs. The polymeric compounds were characterized by IR and Raman spectroscopies in the solid state, and the data were interpreted in terms of the known molecular structures. The solid-state structures of the complexes are not retained in DMSO, as proven via NMR (1H, 13C, and 113Cd NMR) spectroscopy and molar conductivity data. The complexes completely release the coordinated dpkoxH molecule, and the dominant species in solution seem to be [Cd(DMSO)6]2+ in the case of the chloro and bromo complexes and [CdI2(DMSO)4].

Blood is a shear-thinning non-Newtonian fluid in which the viscosity reduces with the shear rate. When simulating arterial flow, it is well established that the non-Newtonian nature is important in the smallest vessels; however, there is no consistent view as to whether it is required in larger arteries, such as the carotid. Here, we investigate the importance of incorporating a non-Newtonian model when applying a plaque deposition model which is based on near-wall local haemodynamic markers: the time-averaged near wall velocity and the ratio of the oscillatory shear index to the wall shear stress. In both cases the plaque deposition was similar between the Newtonian and non-Newtonian simulations, with the observed differences being no more significant than the differences between the selected markers. More significant differences were observed in the haemodynamic properties in the stenosed region, the most significant being that lower levels of near-wall reverse flow were observed for a non-Newtonian fluid.

Weather prediction is a key aspect of today’s society and its activities. Accurate predictions are crucial for efficiently organizing human activities, particularly in the agricultural, transportation and energy sectors. In this paper, two deep neural networks, designed based on a long short-term memory architecture, are developed to predict the occurrence of rainfall events and the respective amount of rainfall on the island of Nisyros in the south Aegean Sea. Two deep neural networks are developed, serving two different learning tasks. The first network acts as a classifier that assesses whether it is going to rain or not and, sequentially, the second network performs a regression task, quantifying the anticipated amount of rainfall. The performance of such prediction models is highly dependent on input sequences. Among others, the lookback time window shapes those input sequences by determining the number of past time steps to be taken into account. The ideal time window for the classifier involves 24 time steps (i.e., 4 h), resulting in increased accuracy levels exceeding 96.45%. The predictions of the regression model, which has the same lookback time window, feature low errors, measured as 6.635 and 1.411 mm using the mean-square-error and mean-absolute-error indices, respectively.

Accurate short-term water consumption forecasting is a crucial function of modern water supply systems, which, in turn, play a crucial role in the sustainable management of water resources, particularly in regions with limited access to water supplies. This study presents an evaluation of the performance gains in short-term water consumption forecasting by the exploitation of a fuzzy clustering algorithm to engineer new features corresponding to water consumption clusters. The evaluation takes place under data scarcity, meaning both a small dataset and only in situ water consumption measurements. To evaluate the gains, data registered to consumers on the remote island of Tilos are processed to produce two datasets which differ in terms of the addition of clusters. The datasets are consumed by deep neural networks to produce hour-ahead predictions. The inclusion of the clusters in the dataset results in a decreased mean absolute error and root-mean-square error, reduced by 29% and 17% on average, respectively.

In an attempt to fill in the empty Zn position in the “Periodic Table” of 1-methylbenzotriazole (Mebta), reactions between Zn(II) sources and this ligand were carried out. The detailed synthetic studies provided access to complexes [ZnX2(Mebta)2] (X = Cl, 1; X = Br, 3; X = I, 4), (MebtaH)2[ZnCl4] (2), tet-[Zn(NO3)2(Mebta)2] (5), oct-[Zn(NO3)2(Mebta)2] (6), and [Zn(Mebta)4](Y)2 [Y = ClO4, 7; Y = PF6, 8]. Solid-state thermal decomposition of 2 leads to 1 in quantitative yield. The structures of 3, 4, 5, 6, and 7 were determined by single-crystal crystallography. The structures of the remaining complexes were proposed based on spectroscopic evidence. In all compounds, Mebta behaves as monodentate ligand using the nitrogen of the position 3 as donor. Complexes 1–4, 7, and 8 are tetrahedral. Complexes 5 and 6 are isostoichiometric and their preparation in pure forms depends on the reaction conditions; in the former the ZnII atom has a tetrahedral geometry, whereas in the latter the metal ion is octahedral. This case of rare isomerism arises from the monodentate (in 5) vs. bidentate (in 6) coordination of the nitrato groups. Extensive π–π stacking interactions and non-classical H bonds build interesting 3D architectures in the structurally characterized complexes. The compounds were characterized by IR, far-IR, and Raman spectroscopies in the solid state, and the data were interpreted in terms of the structures (known or proposed) of the complexes and the coordination modes of the organic and inorganic ligands involved. The solid-state structures of the complexes are not retained in solution, as proven by NMR (1H, 13C[1H]) spectroscopy and molar conductivity data. The thermal decomposition study of 1 and 3 leads to stable intermediates with 1:1 stoichiometry, i.e., ZnX2(Mebta). Based on far-IR spectra, polymeric tetrahedral structures are possible with simultaneous presence of terminal and bridging X− groups. Liquid-phase ab initio (MP2) and gas-phase DFT calculations, performed on Mebta and the nitrato complexes, respectively, shed light on the tendency of Mebta for N3-coordination, and the existence and relative stabilities of 5 and 6.

Wildfires are key drivers of land use/land cover (LULC) dynamics by burning vegetation and affecting human infrastructure. On the contrary, LULC changes (LULCCs) may affect the fire regime by influencing vegetation type, burnable areas, fuel loads and continuity. This study investigates the relationship between LULCC and wildfires. We developed a methodology based on different indicators, which allowed us to quantitatively assess and better understand the transitions between LULC classes and burnt area (BA) in Europe in the last two decades (2000–2019). The assessment was performed for the entire European continent and, independently, for each of the five European countries most affected by wildfires: Portugal, Spain, France, Italy and Greece. The main results are the following: (i) LULCC analysis revealed a net loss in forests and arable land and a net gain in shrubs; (ii) most of the BA occurred in forests (42% for the whole of Europe), especially in coniferous forests; (iii) transitions from BA generally were to transitional woodland/shrub or, again, to BA. Overall, our results confirm the existence of a strong relationship between wildfires and LULCCs in Europe, which was quantified in the present study. These findings are of paramount importance in fire and environmental system management and ecology.

Rotifers represent an important component of freshwater zooplankton. The high richness of taxa, particularly in littoral macrophyte zones of water bodies in tropical and subtropical flood-prone areas, is a repeatedly reported fact. However, studies on the composition of periphytic rotifers in the Neotropics are reduced and almost non-existent in some regions. A qualitative study on rotifers (Monogononta) associated with littoral aquatic vegetation and their seasonal variation was carried out in three flood-prone ponds in the “Esteros de Camaguán Fauna Reserve” in the Venezuelan plains. For the selection of the collection sites, the two-stage stratified method with proportional affixation was used. Samples of macrophytes and the water associated with them were taken in littoral zones. The percentages of occurrence and numerical frequency were calculated for each rotifer taxa. The faunal similarities and correlations within and between ponds in the same and different climatic seasons were estimated using the Jaccard and Spearman coefficients (α = 0.05), respectively. In total, 102 rotifer taxa associated with 11 species of aquatic macrophytes were identified. The genus Taphrocampa with two taxa plus ten other taxa, are new records for Venezuela and one of them for South America. The taxocenosis and the geographic distribution of the reported taxa reflect a typical composition of the littoral zones of tropical regions. The total richness of both planktonic associated with aquatic vegetation and periphytic assemblages were similar. The highest richness of rotifer taxa coincided with the rainy season and the lowest with the early rainy season. The rotifer fauna presented low similarity values within and between ponds according to seasonality and, with some exceptions, between planktonic and periphytic environments. The importance of sampling periphytic rotifers and the influence of the flood cycle, and the degree of macrophyte development in the structuring of periphytic rotifer communities, were confirmed.

Existing video Quality-of-Experience (QoE) metrics rely on the decoded video for the estimation. In this work, we explore how the overall viewer experience, quantified via the QoE score, can be automatically derived using only information available before and during the transmission of videos, on the server side. To validate the merits of the proposed scheme, we consider a dataset of videos encoded and streamed under different conditions and train a novel deep learning architecture for estimating the QoE of the decoded video. The major novelty of our work is the exploitation and demonstration of cutting-edge deep learning techniques in automatically estimating video QoE scores. Our work significantly extends the existing approach for estimating the QoE in video streaming services by combining visual information and network conditions.

Fires are common in Mediterranean soils and constitute an important driver of their evolution. Although fire effects on vegetation dynamics are widely studied, their influence on the assembly rules of soil prokaryotes in a small-scale environment has attracted limited attention. In the present study, we reanalyzed the data from Aponte et al. (2022) to test whether the direct and/or indirect effects of fire are reflected in the network of relationships among soil prokaryotes in a Chilean sclerophyllous ecosystem. We focused on bacterial (genus and species level) co-occurrence patterns in the rhizospheres and bulk soils in burned and unburned plots. Four soils were considered: bulk-burnt (BB), bulk-unburnt (BU), rhizosphere-burnt (RB), and rhizosphere-unburnt (RU). The largest differences in network parameters were recorded between RU and BB soils, while RB and BU networks exhibited similar values. The network in the BB soil was the most compact and centralized, while the RU network was the least connected, with no central nodes. The robustness of bacterial communities was enhanced in burnt soils, but this was more pronounced in BB soil. The mechanisms mainly responsible for bacterial community structure were stochastic in all soils, whether burnt or unburnt; however, communities in RB were much more stochastic than in RU.

The global increase in energy demand has triggered a global boom in the construction of hydropower dams worldwide affecting biological communities. Our objective is to study the zooplankton (Rotifera, Cladocera and Copepoda) community structure during and after the impoundment of a newly constructed reservoir, to provide valuable knowledge on species diversity, community structure and dynamics to be considered in future management plans. The impoundment period was characterized by increased species richness with high turnover because of the zooplankton’s high dispersal ability and reflected the inoculation of the reservoir with local fauna. Zooplankton during this period were also correlated negatively with depth and positively with total organic nitrogen and nitrate, highlighting the importance of trophic impact. The time following the impoundment reflected the colonization processes to more stable communities. The seasonality domination followed the Mediterranean pattern, with cold and warm periods being differentiated by changes in community structure, while abundance and biomass remained low throughout the studied period. Combined with the dominance of small-sized individuals, it resulted in low grazing pressure, indicating that zooplankton was not the factor controlling phytoplankton.

The evacuation and abandonment of large passenger ships, involving thousands of passengers, is a safety-critical task where techniques and systems that can improve the complex decision-making process and the timely response to emergencies on board are of vital importance. Current evacuation systems and processes are based on predefined and static exit signs, information provided to the passengers in the form of evacuation drills, emergency information leaflets and public announcements systems. It is mandatory for passengers to wear lifejackets during an evacuation, which are made of buoyant or inflatable material to keep them afloat in the water. Time is the most critical attribute in ship evacuation and can significantly affect the overall evacuation process in case passengers do not reach their embarkation stations in a timely manner. Moreover, extreme conditions and hazards, such as fire or flooding, can prevent and hinder the timely evacuation process. To improve the current evacuation systems onboard large passenger ships, a smart lifejacket has been designed and implemented within the context of the project SafePASS. The proposed smart lifejacket integrates indoor localization and navigation functionality to assist passengers during the evacuation process. Once the passenger location is calculated within the ship, the navigation feature guides the passengers along an escape route using vibration motors attached to the lifejacket. This is done in the form of haptic cues to help passengers reach their destination, especially in low-visibility conditions and in case they are left behind or lost. This can increase passenger safety and reduce the total evacuation time, as well as support dynamic evacuation scenarios where the predefined routes and static exit routes may not be available due to fire or flooding incidents.

The aim of the present work was to optimize the conditions of the distillation process at a pilot scale to maximize the yield of specific bioactive compounds of the essential oil of oregano cultivated in Greece, and subsequently to study the in vitro antioxidant activity of these oils. Steam distillation was conducted at an industrial distillery and a Face-Centered Composite (FCC) experimental design was applied by utilizing three distillation factors: time, steam pressure and temperature. Essential oil composition was determined by static headspace gas chromatography–mass spectrometry (HS–GC/MS). To obtain a comprehensive profile of the essential oils, instrumental parameters were optimized, including sample preparation, incubation conditions, sampling process, injection parameters, column thermal gradient and MS conditions. With the applied GC-MS method, more than 20 volatile compounds were identified in the headspace of the oregano essential oils and their relative percentages were recorded. Carvacrol was the most prominent constituent under all distillation conditions applied. Data processing revealed time as the main factor which most affected the yield. The Desired Space (DSc) was determined by conducting a three-dimensional response surface analysis of the independent and dependent variables, choosing yields of thymol and carvacrol as optimization criteria. The in vitro antioxidant activity of the essential oils of all samples was measured in terms of the interaction with the stable free radical 2,2-diphenyl-1-picrylhydrazyl (DPPH) after 20 and 60 min. The most prominent essential oils at different distillation conditions were also tested as inhibitors of lipid peroxidation. Higher % values of carvacrol and thymol were correlated to higher antioxidant activity. Evaluating the impact of the distillation conditions on the in vitro results, it seems that lower pressure, less time and higher temperature are crucial for enhanced antioxidant activities.

Greece is situated in the East Mediterranean region and in the Balkan peninsula, i.e., a European biodiversity hotspot with high endemism in subterranean and freshwater fauna, highlighting the need to understand its biodiversity. A literature search was undertaken to present a checklist of cladocerans and copepods based on a compilation of published and current data, from 1892 up to 2022 from inland surfaces and subterranean water bodies from different regions of Greece. For Cladocera, 80 species were recorded (9 families with 35 genera). The most diverse families were Chydoridae (20 genera with 33 species) and Daphniidae (5 genera with 27 species). For copepoda, 134 taxa were recorded, in surface water bodies (12 families with 34 genera), subterranean water bodies (7 families with 27 genera), and parasitic copepods (3 families with 3 genera). The most diverse families in surface waters were Cyclopidae (15 genera with 41 taxa) and Diaptomidae (5 genera with 17 species), while those in subterranean waters were Cyclopidae (11 genera with 35 taxa) and Canthocamptidae (6 genera with 17 taxa). More species are expected to be discovered after sampling understudied regions, especially islands, as well as water bodies such as temporary pools, swamps, ditches, puddles, and the littoral parts of lakes, while molecular studies are needed to clarify various cases of complex taxonomy.

Disease-related malnutrition (DRM) is highly prevalent among patients with hematologic malignancies. The aim of the present study was to evaluate the prevalence of DRM in hospitalized patients with hematologic malignancies and investigate the level of awareness of DRM among the medical team treating this group of patients. A cross sectional quality clinical audit took place in two hematology units of a tertiary university hospital. Inpatients were screened within 48 h of their admission using the Malnutrition Universal Screening Tool (MUST) to identify their nutritional risk, and they were reassessed to identify the implemented interventions during their hospitalization. One hundred eighty-five patients were included in the audit analysis. On admission, 37.3% of the audited population was identified as being at high risk of malnutrition according to the MUST score. Forty-nine (26.5%) patients reported reduced food intake during the past 5 days, while four (2.2%) reported no food intake. During the hospitalization, only five patients (2.7%) received nutritional support, as indicated. Low levels of awareness of the early detection and treatment of DMS were found. Moreover, the prevalence of DRM and low nutritional intake was reported to be low. Measures to increase awareness of DMR in the medical team and better coordination of the nutrition support teams is vital to ensure better management and early nutrition intervention in hematological patients.

Biodiversity records are recognized as important for both diversity conservation and ecological studies under the light of global threats faced by aquatic ecosystems. Here, the checklist of Greek rotifer species is presented based on a literature review, as well as current data from 38 inland water bodies. A total of 172 Monogononta rotifer species were recorded to belong to 21 families and 44 genera. The most diverse genera were Lecane, Brachionus, and Trichocerca, accounting for 34% of the recorded species. Trichocerca similis, Brachionus angularis, Filinia longiseta, Asplanchna priodonta, Keratella tecta, Keratella quadrata, and Keratella cochlearis were the most frequent species with a high frequency of occurrence over 60%, with K. cochlearis being the most frequently recorded (86%). Furthermore, we used rarefaction indices, and the potential richness was estimated at 264 taxa. More sampling efforts aiming at littoral species, as well as different habitats such as temporary pools, ponds, and rivers, are expected to increase the known rotifer fauna in Greece. We expect that additional molecular analyses will be needed to clarify the members of species complexes, likely providing additional species.

The production and consumption of music in the contemporary era results in big data generation and creates new needs for automated and more effective management of these data. Automated music mood detection constitutes an active task in the field of MIR (Music Information Retrieval). The first approach to correlating music and mood was made in 1990 by Gordon Burner who researched the way that musical emotion affects marketing. In 2016, Lidy and Schiner trained a CNN for the task of genre and mood classification based on audio. In 2018, Delbouys et al. developed a multi-modal Deep Learning system combining CNN and LSTM architectures and concluded that multi-modal approaches overcome single channel models. This work will examine and compare single channel and multi-modal approaches for the task of music mood detection applying Deep Learning architectures. Our first approach tries to utilize the audio signal and the lyrics of a musical track separately, while the second approach applies a uniform multi-modal analysis to classify the given data into mood classes. The available data we will use to train and evaluate our models comes from the MoodyLyrics dataset, which includes 2000 song titles with labels from four mood classes, {happy, angry, sad, relaxed}. The result of this work leads to a uniform prediction of the mood that represents a music track and has usage in many applications.

The ongoing transition towards 5G technology expedites the emergence of a variety of mobile applications that pertain to different vertical industries. Delivering on the key commitment of 5G, these diverse service streams, along with their distinct requirements, should be facilitated under the same unified network infrastructure. Consequently, in order to unleash the benefits brought by 5G technology, a holistic approach towards the requirement analysis and the design, development, and evaluation of multiple concurrent vertical services should be followed. In this paper, we focus on the Transport vertical industry, and we study four novel vehicular service categories, each one consisting of one or more related specific scenarios, within the framework of the “5G Health, Aquaculture and Transport (5G-HEART)” 5G PPP ICT-19 (Phase 3) project. In contrast to the majority of the literature, we provide a holistic overview of the overall life-cycle management required for the realization of the examined vehicular use cases. This comprises the definition and analysis of the network Key Performance Indicators (KPIs) resulting from high-level user requirements and their interpretation in terms of the underlying network infrastructure tasked with meeting their conflicting or converging needs. Our approach is complemented by the experimental investigation of the real unified 5G pilot’s characteristics that enable the delivery of the considered vehicular services and the initial trialling results that verify the effectiveness and feasibility of the presented theoretical analysis.

Search and rescue operations can range from small, confined spaces, such as collapsed buildings, to large area searches during missing person operations. K9 units are tasked with intervening in such emergencies and assist in the optimal way to ensure a successful outcome for the mission. They are required to operate in unknown situations were the lives of the K9 handler and the canine companion are threatened as they operate with limited situational awareness. Within the context of the INGENIOUS project, we developed a K9 vest for the canine companion of the unit, aiming to increase the unit’s safety while operating in the field, assist the K9 handler in better monitoring the location and the environment of the K9 and increase the information provided to the Command and Control Center during the operation.

Proteinuria is characterized by low accuracy for predicting onset and development of diabetic kidney disease (DKD) because it is not directly associated with molecular changes that promote DKD, but is a result of kidney damage. Oxidized low-density lipoprotein (ox-LDL) reflects oxidative stress and endothelial dysfunction, both underlying the development of proteinuria and loss of kidney function in DKD. We aimed to investigate whether ox-LDL modifies the association between proteinuria and progression of DKD in a cohort of 91 patients with proteinuric DKD and diabetic retinopathy, followed for 10 years. The primary endpoint was a combined kidney outcome of eGFR decline ≥30% or progression to end-stage kidney disease. After the end of the study, we considered the percentage change of eGFR over time as our secondary outcome. Proteinuria was associated with both outcomes, and ox-LDL amplified the magnitude of this link (p < 0.0001 for primary and p < 0.0001 for secondary outcome, respectively). After adjustment for duration of diabetes, history of cardiovascular disease and serum albumin, ox-LDL remained a significant effect modifier of the association between proteinuria and eGFR decline over time (p = 0.04). Our study shows that in proteinuric DKD, circulating ox-LDL levels amplified the magnitude of the association between proteinuria and progression of DKD.

We present AΜAΛΘΕΙA (AMALTHIA), an application ontology that models the domain of dishes as they are presented in 112 menus collected from restaurants/taverns/patisseries in East Macedonia and Thrace in Northern Greece. AΜAΛΘΕΙA supports a tourist mobile application offering multilingual translation of menus, dietary and cultural information about the dishes and their ingredients, as well as information about the geographical dispersion of the dishes. In this document, we focus on the food/dish dimension that constitutes the ontology’s backbone. Its dish-oriented perspective differentiates AΜAΛΘΕΙA from other food ontologies and thesauri, such as Langual, enabling it to codify information about the dishes served, particularly considering the fact that they are subject to wide variation due to the inevitable evolution of recipes over time, to geographical and cultural dispersion, and to the chef’s creativity. We argue for the adopted design decisions by drawing on semantic information retrieved from the menus, as well as other social and commercial facts, and compare AMAΛΘΕΙA with other important taxonomies in the food field. To the best of our knowledge, AΜAΛΘΕΙA is the first ontology modeling (i) dish variation and (ii) Greek (commercial) cuisine (a component of the Mediterranean diet).

The lack of granular and rich descriptive metadata highly affects the discoverability and usability of cultural heritage collections aggregated and served through digital platforms, such as Europeana, thus compromising the user experience. In this context, metadata enrichment services through automated analysis and feature extraction along with crowdsourcing annotation services can offer a great opportunity for improving the metadata quality of digital cultural content in a scalable way, while at the same time engaging different user communities and raising awareness about cultural heritage assets. To address this need, we propose the CrowdHeritage open end-to-end enrichment and crowdsourcing ecosystem, which supports an end-to-end workflow for the improvement of cultural heritage metadata by employing crowdsourcing and by combining machine and human intelligence to serve the particular requirements of the cultural heritage domain. The proposed solution repurposes, extends, and combines in an innovative way general-purpose state-of-the-art AI tools, semantic technologies, and aggregation mechanisms with a novel crowdsourcing platform, so as to support seamless enrichment workflows for improving the quality of CH metadata in a scalable, cost-effective, and amusing way.

This paper presents an integrated digital methodology for the generalization of soundings. The input for the sounding generalization procedure is a high resolution Digital Terrain Model (DTM) and the output is a sounding data set appropriate for portrayal on harbour and approach Electronic Navigational Charts (ENCs). The sounding generalization procedure follows the “ladder approach” that is a requisite for the portrayal of soundings on nautical charts, i.e., any sounding portrayed on a smaller scale chart should also be depicted on larger scale charts. A rhomboidal fishnet is used as a supportive reference structure based on the cartographic guidance for soundings to display a rhombus pattern on nautical charts. The rhomboidal fishnet cell size is defined by the depth range and the compilation scale of the charted area. Generalization is based on a number of rules and constraints extracted from International Hydrographic Organization (IHO) standards, hydrographic offices’ best practices and the cartographic literature. The sounding generalization procedure can be implemented using basic geoprocessing functions available in the most commonly used Geographic Information System (GIS) environments. A case study was performed in the New York Lower Bay area based on a high resolution National Oceanic and Atmospheric Administration (NOAA) DTM. The method successfully produced generalized soundings for a number of Harbour and Approach nautical charts at 10 K, 20 K, 40 K and 80 K scales.

We sought to investigate the possible association between Red Blood Cell Distribution Width (RDW), vascular calcification, oxidative stress and renal function and all-cause/cardiovascular (CV) mortality, CV events and progression of kidney disease in a cohort of patients with Diabetic Kidney Disease (DKD). Carotid intima media thickness (cIMT) and oxidized low-density cholesterol were measured in 104 Type 2 Diabetes Mellitus (T2DM) patients with established DKD, distributed in all five stages of kidney disease and 38 diabetics with normal renal function. All patients were followed for 7 years with end-points all-cause and CV mortality, CV events and progression to End-Stage Renal Disease (ESRD). RDW was positively correlated with diabetes duration (r = 0.19, p = 0.023) and albuminuria (r = 0.29, p = 0.002). Multivariate regression analysis revealed that RDW was a strong, independent predictor of cIMT value (β = 0.031, p = 0.012). Kaplan-Meier curves and Cox proportional hazard models revealed that after adjustment for several cofounders, RDW was a significant and independent predictor for all-cause mortality, CV mortality, CV event and progression to ESRD (HR 1.75, p = 0.001, HR 2.03, p = 0.001, HR = 1.66, p < 0.0001 and HR 2.14, p = 0.001 respectively). RDW predicts mortality, CV events and deterioration of renal function in DKD, probably reflecting atherosclerosis.

We assessed the abundance and composition of nematode communities in soil under herbaceous vegetation in reclaimed landfill sites at different ages after closure (3, 10 and 14 years) compared to those in neighboring semi-natural grazed grasslands (reference sites). We further applied network analysis based on the co-occurrence patterns of nematodes. Nematode abundance decreased between 3 and10 years of regeneration, but significantly increased from 10 to 14 years of regeneration. The number and identity of genera were comparable along the succession; however, there were dissimilarities in community composition during early- and mid-succession. The diversity, community composition and abundance at the sites after 14 years of regeneration converged with those at the reference sites. Moreover, changes during succession were not accompanied by the maturation of the soil food web, as demonstrated by Enrichment and Channel indices. In all the networks, centrality and modularity metrics differed significantly from those for random networks, whereas cohesion metrics showed no difference. All the networks exhibited Small-worldness indices higher than one, demonstrating that the networks of the interactions among genera at all the sites shared features that matched both random and non-random networks. The succession trajectory in reclaimed landfills was represented by a sequence of changes that differed in relation to the variable under consideration; network parameters tended to converge with those of a relatively resistant reference community, while the Enrichment and Channel indices did not. Additionally, the succession trajectory was not linear or steady; only the Channel index and Worldness index showed linear responses to succession time. However, across all the successional stages, the resource status remained basal or degraded while the nematode communities had an enhanced ability to cope with sudden changes.

Mediterranean ecosystems are threatened by water and nutrient scarcity and continuous loss of soil organic carbon. Urban agglomerations and rural ecosystems in the Mediterranean region and globally are interlinked through the flows of resources/nutrients and wastes. Contributing to balancing these cycles, the present study advocates standardized biochar as a soil amendment, produced from Mediterranean suitable biowaste, for closing the nutrient loop in agriculture, with parallel greenhouse gas reduction, enhancing air quality in urban agglomerations, mitigating climate change. The study’s scope is the contextualization of pyrolytic conditions and biowaste type effects on the yield and properties of biochar and to shed light on biochar’s role in soil fertility and climate change mitigation. Mediterranean-type suitable feedstocks (biowaste) to produce biochar, in accordance with biomass feedstocks approved for use in producing biochar by the European Biochar Certificate, are screened. Data form large-scale and long-period field experiments are considered. The findings advocate the following: (a) pyrolytic biochar application in soils contributes to the retention of important nutrients for agricultural production, thereby reducing the use of fertilizers; (b) pyrolysis does not release carbon dioxide to the atmosphere, contributing positively to the balance of carbon dioxide emissions to the atmosphere, with carbon uptake by plant photosynthesis; (c) biochar stores carbon in soils, counterbalancing the effect of climate change by sequestering carbon; (d) there is an imperative need to identify the suitable feedstock for the production of sustainable and safe biochar from a range of biowaste, according to the European Biochar Certificate, for safe crop production.

The study aimed at testing the effectiveness of a mixed-method pilot intervention in reducing risky self-reported driving performance, upon addressing stress and aggression while driving. The study recruited individuals who had performed these behaviors during the year preceding the study and allocated them into an intervention (n = 10) and a control group (n = 30). A pre-and postintervention evaluation design was employed to explore changes in risky self-reported driving behaviors, 12 months after the intervention. The intervention involved 2 h of experiential instruction and 1 h of cognitive restructuring using a driving simulator and scenarios appropriate for the processing of driving stress, aggression, and risk. The intervention group displayed significant improvements in the scales of “Hazard Monitoring” (p = 0.037) and “Covered Violations” (p = 0.049) at the postintervention level. No statistically significant differences were identified in terms of self-reported driving performance between the intervention and the control group at postintervention level. Launching large-scale experimental surveys with broadened cognitive restructuring approaches seems important to deepen our understanding of the behavioral change processes and increase the effectiveness of future interventions.

In this paper, online map services are reviewed from a cartographic point of view. The most popular online map services are selected based on worldwide website traffic data, provided by specialized sites, such as Similarweb, in terms of global coverage and popularity among users. Online map services are commented based on cartographic principles, conventions and traditional practices addressing topics, such as: Cartographic projection, orientation, scale, marginalia, content (thematic layers), symbology, generalization, annotation, color use and overall map design. Color schemes utilized in web maps are discussed in more detail, since based on studies concerning the selection of the preferable map by experts and laymen, color is undisputedly the most frequently mentioned factor. It can be stated that online map services generally adopt well-known cartographic practices, which are not always applied as expected. Moreover, suggestions for the improvement of online map services are made regarding cartographic projection, legend, content, symbolization, color, etc.

The demand for Autonomic Network Management (ANM) and optimization is as intense as ever, even though significant research has been devoted towards this direction. This paper addresses such need in Software Defined (SDR) based Cognitive Radio Networks (CRNs). We propose a new framework for ANM and network reconfiguration combining Software Defined Networks (SDN) with SDR via Network Function Virtualization (NFV) enabled Virtual Utility Functions (VUFs). This is the first approach combining ANM with SDR and SDN via NFV, demonstrating how these state-of-the-art technologies can be effectively combined to achieve reconfiguration flexibility, improved performance and efficient use of available resources. In order to show the feasibility of the proposed framework, we implemented its main functionalities in a cross-layer resource allocation mechanism for CRNs over real SDR testbeds provided by the Orchestration and Reconfiguration Control Architecture (ORCA) EU project. We demonstrate the efficacy of our framework, and based on the obtained results, we identify aspects that can be further investigated for improving the applicability and increasing performance of our broader framework.

A single lipid vesicle can be regarded as an autonomous ultra-miniaturised 3D biomimetic “scaffold” (Ø ≥ 13 nm) ideally suited for reconstitution and interrogation of biochemical processes. The enclosing lipid bilayer membrane of a vesicle can be applied for studying binding (protein/lipid or receptor/ligand interactions) or transmembrane events (membrane permeability or ion channel activation) while the aqueous vesicle lumen can be used for confining few or single macromolecules and probe, e.g., protein folding, catalytic pathways of enzymes or more complex biochemical reactions, such as signal transduction cascades. Immobilisation (arraying) of single vesicles on a solid support is an extremely useful technique that allows detailed characterisation of vesicle preparations using surface sensitive techniques, in particular fluorescence microscopy. Surface-based single vesicle arrays allow a plethora of prototypic sensing applications in a high throughput format with high spatial and high temporal resolution. In this review we present a series of applications of single vesicle arrays for screening/sensing of: membrane curvature dependent protein-lipid interactions, bilayer tension, reactions triggered in the vesicle lumen, the activity of transmembrane protein channels and biological membrane fusion reactions.

Background: It is not known whether intensive care unit (ICU) patients' family members realistically assess patients' health status., Objectives: The aim was to investigate the agreement between family and intensivists' assessment concerning changes in patient health, focusing on family members' resilience and their perceptions of decision making., Methods: For each ICU patient, withdrawal criteria were assessed by intensivists while family members assessed the patient's health development and completed the Connor-Davidson Resilience Scale and the Self-Compassion Scale. Six months after ICU discharge, follow-up contact was established, and family members gave their responses to two hypothetical scenarios., Results: 162 ICU patients and 189 family members were recruited. Intensivists' decisions about whether a patient met the withdrawal criteria had 75,9% accuracy for prediction of survival. Families' assessments were statistically independent of intensivists' opinions, and resilience had a significant positive effect on the probability of agreement with intensivists. Six months after discharge, family members whose relatives were still alive were significantly more likely to consider that the family or patient themselves should be involved in decision-making., Conclusions: Resilience is related to an enhanced probability of agreement of the family with intensivists' perceptions of patients' health progression. Family attitudes in hypothetical scenarios were found to be significantly affected by the patient's actual health progression.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly spread globally, becoming a huge public health challenge. Even though the vast majority of patients are asymptomatic, some patients present with pneumonia, acute respiratory distress syndrome (ARDS), septic shock, and death. It has been shown in several studies that the severity and clinical outcomes are related to dysregulated antiviral immunity and enhanced and persistent systemic inflammation. Corticosteroids have been used for the treatment of COVID-19 patients, as they are reported to elicit benefits by reducing lung inflammation and inflammation-induced lung injury. Dexamethasone has gained a major role in the therapeutic algorithm of patients with COVID-19 pneumonia requiring supplemental oxygen or on mechanical ventilation. Its wide anti-inflammatory action seems to form the basis for its beneficial action, taming the overwhelming "cytokine storm". Amid a plethora of scientific research on therapeutic options for COVID-19, there are still unanswered questions about the right timing, right dosing, and right duration of the corticosteroid treatment. The aim of this review article was to summarize the data on the dexamethasone treatment in COVID-19 and outline the clinical considerations of corticosteroid therapy in these patients.