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Lake Ohrid shared by the Republics of Albania and Macedonia is formed by a tectonically active graben within the South Balkan and suggested to be the oldest lake in Europe. Several studies have shown that the lake provides a valuable record of climatic and environmental changes and a distal tephrostratigraphic record of volcanic eruptions from Italy. Fault structures identified in seismic data demonstrate that sediments have also the potential to record tectonic activity in the region. Here, we provide an example of linking tephrostratigraphic information and environmental changes with tectonic activity and anthropogenic impact. Historical documents indicate that a major earthquake destroyed the city of Ohrid in the early 6th century AD. This earthquake is documented in multichannel seismic profiles, in parametric sediment echosounder profiles, and in a ca. 10m long sediment record from the western part of the lake. The sediment record exhibits a ca. 2m thick mass wasting deposit, which is chronologically well constrained by the underlying 472 AD/512AD tephra and cross correlation with 15 other sediment sequences with similar geochemical characteristics of the Holocene. [ABSTRACT FROM AUTHOR]

Ancient Lake Ohrid on the Balkan Peninsula is considered to be the oldest ancient lake in Europe with a suggested Plio-Pleistocene age. Its exact geological age, however, remains unknown. Therefore, molecular clock data of Lake Ohrid biota may serve as an independent constraint of available geological data, and may thus also help to refine age estimates. Such evolutionary data may also help unravel potential biotic and abiotic factors that promote speciation events. Here, mitochondrial sequencing data of one of the largest groups of endemic taxa in Lake Ohrid, the leech genus Dina, is used to test whether it represents an ancient lake species flock, to study the role of horizontal and vertical barriers in Lake Ohrid for evolutionary events, to estimate the onset of intralacustrine diversification in this group based on molecular clock analyses, and to compare this data with data from other endemic species for providing an approximate time frame for the origin of Lake Ohrid. Based on the criteria speciosity, monophyly and endemicity, it can be concluded that Lake Ohrid Dina, indeed, represents an ancient lake species flock. Lineage sorting of its species, however, does not seem to be complete. Analyses of population structures of Dina spp. in the Ohrid watershed indicate a horizontal zonation of haplotypes from spring and lake populations, corroborating the role of lake-side springs, particularly the southern feeder springs, for evolutionary processes in endemic Ohrid taxa. Vertical differentiation of lake taxa, however, appears to be limited, though differences between populations from the littoral and the profundal are apparent. Molecular clock analyses indicate that the most recent common ancestor of extant species of this flock is approximately 1.99 ± 0.83 Ma old, whereas the split of the Lake Ohrid Dina flock from a potential sister taxon outside the lake is estimated at 8.30 ± 3.60 Ma. Comparisons with other groups of endemic Ohrid species indicated that in all cases, intralacustrine diversification started ≤2 Ma ago. Thus, this estimate may provide information on a minimum age for the origin of Lake Ohrid. Maximum ages are less consistent and generally less reliable. But cautiously, a maximum age of 3 Ma is suggested. Interestingly, this time frame of approximately 2-3 Ma for the origin of Lake Ohrid, generated based solely on evolutionary data, well fits the time frame most often used in the literature by geologists. Future studies must show whether this concurrence holds true. [ABSTRACT FROM AUTHOR]

Spatial heterogeneity of biodiversity arises from evolutionary processes, constraints of environmental factors and the interaction of communities. The quality of such spatial analyses of biodiversity is improved by (i) utilizing study areas with well defined physiogeographical boundaries, (ii) limiting the impact of widespread species, and (iii) using taxa with heterogeneous distributions. These conditions are typically met by ecosystems such as oceanic islands or ancient lakes and their biota. While research on ancient lakes has contributed significantly to our understanding of evolutionary processes, statistically sound studies of spatial variation of extant biodiversity have been hampered by the frequently vast size of ancient lakes, their limited accessibility, and the lack of infrastructure around them. The small European ancient Lake Ohrid provides a rare opportunity for such a reliable spatial study. The comprehensive horizontal and vertical sampling of a species-rich taxon, the Gastropoda, presented here, revealed interesting patterns of biodiversity, which, in part, have not been shown before for other ancient lakes. In a total of 224 locations throughout the Ohrid Basin, representatives of 68 gastropod species with 50 of them being endemic (=73.5%) could be reported. The spatial distribution of these species shows the following characteristics: (i) within Lake Ohrid, the most frequent species are endemic taxa with a wide depth range, (ii) widespread species (i.e. those occurring throughout the Balkans or beyond) are rare and mainly occur in the upper layer of the lake, (iii) while the total number of species decreases with water depth, the share of endemics increases, (iv) the deeper layers of Lake Ohrid appear to have a higher spatial homogeneity of biodiversity and related environmental factors, (v) biotic interaction due to possible spillover effects may contribute to the establishment of hotspots, and (vi) eco-insularity within the Ohrid Basin occurs at two levels, at the level of the lake proper and at the level of the feedersprings. It is also shown that large scale effects such as type of water body or water depth are mainly responsible for the distribution of biodiversity. In addition, small scale effects like environmental gradients or biotic interaction affect gastropod composition within a particular depth zone. [ABSTRACT FROM AUTHOR]

The class of Gastropoda is one of the Lake Ohrid' macrozoobenthic groups, which characterize highest level of endemism. Since the first published references until now, studying the Lake Ohrid's snail fauna represents huge scientific challenge for many malacologists from the world. The high percent of endemic as well as relic forms among the lake's gastropods could be explained by the processes of intralacustric speciation during the history and evolution of this aquatic ecosystem. These processes no doubt have been enabled by the complexity and stability of the Lake's basin. This work represents the results of the dominant species, from both qualitative and quantitative sense of the gastropod fauna from 19 investigated littoral localities of Lake Ohrid. The results from the investigations on gastropod fauna has shown that following species: Chilopyrgula sturanyi, Radix relicta and Valvata stenotrema qualitatively predominates in the samples from the littoral region of the Macedonian part of Lake Ohrid. The quantitative analyses (according to their presence on m-2), has shown that the following species predominate: Chilopyrgula sturanyi (6879 No⋅m-2), Theodoxus fluviatilis dalmaticus (6412 No⋅m-2 ), Pyrgohydrobia grochmalickii (5504 No⋅m-2) and Valvata stenotrema (5009 No⋅m-2). [ABSTRACT FROM AUTHOR]

Researchers from various scientific disciplines have attempted to forecast the spread of coronavirus disease 2019 (COVID-19). The proposed epidemic prediction methods range from basic curve fitting methods and traffic interaction models to machine-learning approaches. If we combine all these approaches, we obtain the Network Inference-based Prediction Algorithm (NIPA). In this paper, we analyse a diverse set of COVID-19 forecast algorithms, including several modifications of NIPA. Among the algorithms that we evaluated, the original NIPA performed best at forecasting the spread of COVID-19 in Hubei, China and in the Netherlands. In particular, we show that network-based forecasting is superior to any other forecasting algorithm., (© 2020 The Author(s).)

Along six transects in each of six lakes across the Western Balkans, we collected data for three groups of littoral biological water quality indicators: epilithic diatoms, macrophytes, and benthic invertebrates. We assessed the relationships between them and three environmental pressures: nutrient load (eutrophication), hydro-morphological alteration of the shoreline, and water level variation, separating the effect of individual lakes and continuous explanatory variables. Lake water total phosphorus concentration (TP) showed substantial variation but was not related to any of the tested biological indicators, nor to any of the tested pressures. We suggest that this may be due to feedback processes such as P removal in the lake littoral zone. Instead, we found that a gradient in surrounding land-use towards increasing urbanization, and a land-use-based estimate of P run-off, served as a better descriptor of eutrophication. Overall, eutrophication and water level fluctuation were most important for explaining variation in the assessed indicators, whereas shoreline hydro-morphological alteration was less important. Diatom indicators were most responsive to all three pressures, whereas macrophyte biomass and species number responded only to water level fluctuation. The Trophic Diatom Index for Lakes (TDIL) was negatively related to urbanization and wave exposure. This indicates that it is a suitable indicator for pressures related to urbanization, although a confounding effect of wave exposure is possible. Invertebrate abundance responded strongly to eutrophication, but the indicator based on taxonomic composition (Average Score Per Taxon) did not. Our results suggest that our metrics can be applied in Western Balkan lakes, despite the high number of endemic species present in some of these lakes. We argue that local water management should focus on abating the causes of eutrophication and water level fluctuation, whilst preserving sufficient lengths of undeveloped shoreline to ensure good water quality in the long run., Competing Interests: Declaration of competing interest We have no conflicts of interest., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Purpose: Lung cancer is the leading cause of cancer mortality in the US, responsible for more deaths than breast, prostate, colon and pancreas cancer combined and large population studies have indicated that low-dose computed tomography (CT) screening of the chest can significantly reduce this death rate. Recently, the usefulness of Deep Learning (DL) models for lung cancer risk assessment has been demonstrated. However, in many cases model performances are evaluated on small/medium size test sets, thus not providing strong model generalization and stability guarantees which are necessary for clinical adoption. In this work, our goal is to contribute towards clinical adoption by investigating a deep learning framework on larger and heterogeneous datasets while also comparing to state-of-the-art models., Methods: Three low-dose CT lung cancer screening datasets were used: National Lung Screening Trial (NLST, n = 3410), Lahey Hospital and Medical Center (LHMC, n = 3154) data, Kaggle competition data (from both stages, n = 1397 + 505) and the University of Chicago data (UCM, a subset of NLST, annotated by radiologists, n = 132). At the first stage, our framework employs a nodule detector; while in the second stage, we use both the image context around the nodules and nodule features as inputs to a neural network that estimates the malignancy risk for the entire CT scan. We trained our algorithm on a part of the NLST dataset, and validated it on the other datasets. Special care was taken to ensure there was no patient overlap between the train and validation sets., Results and Conclusions: The proposed deep learning model is shown to: (a) generalize well across all three data sets, achieving AUC between 86% to 94%, with our external test-set (LHMC) being at least twice as large compared to other works; (b) have better performance than the widely accepted PanCan Risk Model, achieving 6 and 9% better AUC score in our two test sets; (c) have improved performance compared to the state-of-the-art represented by the winners of the Kaggle Data Science Bowl 2017 competition on lung cancer screening; (d) have comparable performance to radiologists in estimating cancer risk at a patient level., (Copyright © 2021. Published by Elsevier Ltd.)

Objective: The utilization of hyperspectral imaging (HSI) in real-time tumor segmentation during a surgery have recently received much attention, but it remains a very challenging task., Methods: In this work, we propose semantic segmentation methods, and compare them with other relevant deep learning algorithms for tongue tumor segmentation. To the best of our knowledge, this is the first work using deep learning semantic segmentation for tumor detection in HSI data using channel selection, and accounting for more spatial tissue context, and global comparison between the prediction map, and the annotation per sample. Results, and Conclusion: On a clinical data set with tongue squamous cell carcinoma, our best method obtains very strong results of average dice coefficient, and area under the ROC-curve of [Formula: see text], and [Formula: see text], respectively on the original spatial image size. The results show that a very good performance can be achieved even with a limited amount of data. We demonstrate that important information regarding tumor decision is encoded in various channels, but some channel selection, and filtering is beneficial over the full spectra. Moreover, we use both visual (VIS), and near-infrared (NIR) spectrum, rather than commonly used only VIS spectrum; although VIS spectrum is generally of higher significance, we demonstrate NIR spectrum is crucial for tumor capturing in some cases., Significance: The HSI technology augmented with accurate deep learning algorithms has a huge potential to be a promising alternative to digital pathology or a doctors' supportive tool in real-time surgeries.

Biological assessment metrics and water chemistry measurements are used to quantify the link between stressors and their effects on lake ecosystems, for the Water Framework Directive. However, correlations between metrics and water chemistry are often poor. This is seen as major weaknesses of Water Framework Directive-related monitoring and assessment. We analyzed macrophytes, benthic algae, benthic macroinvertebrates, water chemistry and sediment total phosphorus content in the littoral of six lakes in the Western Balkans and used CORINE land use data to estimate nutrient enrichment via runoff from the adjacent land. Lakes with a higher estimated phosphorus runoff from the adjacent land did not have higher littoral water nutrient concentrations, but littoral diatom assemblages indicated more eutrophic conditions. These lakes also had higher abundances of littoral benthic primary producers, which in turn were associated with low concentrations of dissolved nutrients, but only in autumn, not in spring. This is consistent with primary producers taking up nutrients during the summer growth season. In lakes with high abundances of benthic primary producers, it is likely that the littoral vegetation plays a large role in the transfer of nutrients from the water to the benthos. This process impairs correlations between biological metrics and water nutrient concentrations. Our results suggest that CORINE land cover may be more useful to characterize littoral nutrient enrichment than lake water chemistry. Increased benthic primary producer biomasses and "eutrophic" diatom indices may indicate littoral nutrient enrichment even if water nutrient concentrations are low., Competing Interests: Declaration of competing interest We confirm that this manuscript has not been published elsewhere and is not under consideration by another journal. All authors have approved the manuscript, do not have any conflict of interest and agree with its submission to Science of the Total Environment., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Solving the shortest path and min-cut problems are key in achieving high-performance and robust communication networks. Those problems have often been studied in deterministic and uncorrelated networks both in their original formulations as well as in several constrained variants. However, in real-world networks, link weights (e.g., delay, bandwidth, failure probability) are often correlated due to spatial or temporal reasons, and these correlated link weights together behave in a different manner and are not always additive, as commonly assumed., Methods: In this paper, we first propose two correlated link weight models, namely (1) the deterministic correlated model and (2) the (log-concave) stochastic correlated model. Subsequently, we study the shortest path problem and the min-cut problem under these two correlated models., Results and Conclusions: We prove that these two problems are NP-hard under the deterministic correlated model, and even cannot be approximated to arbitrary degree in polynomial time. However, these two problems are solvable in polynomial time under the (constrained) nodal deterministic correlated model, and can be solved by convex optimization under the (log-concave) stochastic correlated model.

The continuous-time adaptive susceptible-infected-susceptible (ASIS) epidemic model and the adaptive information diffusion (AID) model are two adaptive spreading processes on networks, in which a link in the network changes depending on the infectious state of its end nodes, but in opposite ways: (i) In the ASIS model a link is removed between two nodes if exactly one of the nodes is infected to suppress the epidemic, while a link is created in the AID model to speed up the information diffusion; (ii) a link is created between two susceptible nodes in the ASIS model to strengthen the healthy part of the network, while a link is broken in the AID model due to the lack of interest in informationless nodes. The ASIS and AID models may be considered as first-order models for cascades in real-world networks. While the ASIS model has been exploited in the literature, we show that the AID model is realistic by obtaining a good fit with Facebook data. Contrary to the common belief and intuition for such similar models, we show that the ASIS and AID models exhibit different but not opposite properties. Most remarkably, a unique metastable state always exists in the ASIS model, while there an hourglass-shaped region of instability in the AID model. Moreover, the epidemic threshold is a linear function in the effective link-breaking rate in the AID model, while it is almost constant but noisy in the AID model.

The interplay between disease dynamics on a network and the dynamics of the structure of that network characterizes many real-world systems of contacts. A continuous-time adaptive susceptible-infectious-susceptible (ASIS) model is introduced in order to investigate this interaction, where a susceptible node avoids infections by breaking its links to its infected neighbors while it enhances the connections with other susceptible nodes by creating links to them. When the initial topology of the network is a complete graph, an exact solution to the average metastable-state fraction of infected nodes is derived without resorting to any mean-field approximation. A linear scaling law of the epidemic threshold τ(c) as a function of the effective link-breaking rate ω is found. Furthermore, the bifurcation nature of the metastable fraction of infected nodes of the ASIS model is explained. The metastable-state topology shows high connectivity and low modularity in two regions of the τ,ω plane for any effective infection rate τ>τ(c): (i) a "strongly adaptive" region with very high ω and (ii) a "weakly adaptive" region with very low ω. These two regions are separated from the other half-open elliptical-like regions of low connectivity and high modularity in a contour-line-like way. Our results indicate that the adaptation of the topology in response to disease dynamics suppresses the infection, while it promotes the network evolution towards a topology that exhibits assortative mixing, modularity, and a binomial-like degree distribution.

For a fixed number N of nodes, the number of links L in the line graph H(N,L) can only appear in consecutive intervals, called a band of L. We prove that some consecutive integers can never represent the number of links L in H(N,L), and they are called a bandgap of L. We give the exact expressions of bands and bandgaps of L. We propose a model which can randomly generate simple graphs which are line graphs of other simple graphs. The essence of our model is to merge step by step a pair of nodes in cliques, which we use to construct line graphs. Obeying necessary rules to ensure that the resulting graphs are line graphs, two nodes to be merged are randomly chosen at each step. If the cliques are all of the same size, the assortativity of the line graphs in each step are close to 0, and the assortativity of the corresponding root graphs increases linearly from -1 to 0 with the steps of the nodal merging process. If we dope the constructing elements of the line graphs-the cliques of the same size-with a relatively smaller number of cliques of different size, the characteristics of the assortativity of the line graphs is completely altered. We also generate line graphs with the cliques whose sizes follow a binomial distribution. The corresponding root graphs, with binomial degree distributions, zero assortativity, and semicircle eigenvalue distributions, are equivalent to Erdős-Rényi random graphs.

The class of Gastropoda is one of the Lake Ohrid' macrozoobenthic groups, which characterize highest level of endemism. Since the first published references until now, studying the Lake Ohrid's snail fauna represents huge scientific challenge for many malacologists from the world. The high percent of endemic as well as relic forms among the lake's gastropods could be explained by the processes of intralacustric speciation during the history and evolution of this aquatic ecosystem. These processes no doubt have been enabled by the complexity and stability of the Lake's basin. This work represents the results of the dominant species, from both qualitative and quantitative sense of the gastropod fauna from 19 investigated littoral localities of Lake Ohrid. The results from the investigations on gastropod fauna has shown that following species: Chilopyrgula sturanyi, Radix relicta and Valvata stenotrema quailtatively predominates in the samples from the littoral region of the Macedonian part of Lake Ohrid. The quantitative analyses (according to their presence on m2), has shown that the following species predominate: Chilopyrgula sturanyi (6879 No x m2), Theodoxus fluviatilis dalmaticus (6412 No x m2), Pyrgohydrobia grochmalickii (5504 No x m2) and Valvata stenotrema (5009 No x m2).

Biocenotic research on the benthic fauna from the northwestern part of Lake Ohrid, has shown that different habitats characterize different qualitative compositions of the benthic fauna. The affinity of the macrozoobenthic communities to populate different habitats was investigated in 5 different localities from the northwestern part of Lake Ohrid. Among the five different types of habitats such as stony bottom, sandy bottom, sandy-muddy bottom and muddy bottom mostly covered with mollusc shells, it was found that from the qualitative point of view, the sandy-muddy bottom covered with vascular macrophytes is characterized with highest biodiversity of benthic fauna. In all localities, with the exclusion of the locality As (where the macrophytic vegetation is not well developed), the maximum number of species was recorded between depth points from 3 to 11 m. In the Radozda locality, the maximum number of species (11 species) was recorded at a depth point of 6m., on a bottom covered with sandy mud. In the Livadishte locality, the highest biodiversity (13 species) was recorded at a depth points of 5 and 11 m., on bottom covered with sandy mud with well developed macrophytic vegetation. The localities Kalista and Struga, the maximum number of species (14 in Kalista and 11 in Struga) was also recorded in the same type of habitat, a sandy-muddy bottom with well developed macrophytic vegetation.