Mechanisms of Selective Autophagy.

Selective autophagy is the lysosomal degradation of specific intracellular components sequestered into autophagosomes, late endosomes, or lysosomes through the activity of selective autophagy receptors (SARs). SARs interact with autophagy-related (ATG)8 family proteins via sequence motifs called LC3-interacting region (LIR) motifs in vertebrates and Atg8-interacting motifs (AIMs) in yeast and plants. SARs can be divided into two broad groups: soluble or membrane bound. Cargo or substrate selection may be independent or dependent of ubiquitin labeling of the cargo. In this review, we discuss mechanisms of mammalian selective autophagy with a focus on the unifying principles employed in substrate recognition, interaction with the forming autophagosome via LIR-ATG8 interactions, and the recruitment of core autophagy components for efficient autophagosome formation on the substrate.

A Diversity of Selective Autophagy Receptors Determines the Specificity of the Autophagy Pathway.

The clearance of surplus, broken, or dangerous components is key for maintaining cellular homeostasis. The failure to remove protein aggregates, damaged organelles, or intracellular pathogens leads to diseases, including neurodegeneration, cancer, and infectious diseases. Autophagy is the evolutionarily conserved pathway that sequesters cytoplasmic components in specialized vesicles, autophagosomes, which transport the cargo to the degradative compartments (vacuoles or lysosomes). Research during the past few decades has elucidated how autophagosomes engulf their substrates selectively. This type of autophagy involves a growing number of selective autophagy receptors (SARs) (e.g., Atg19 in yeasts, p62/SQSTM1 in mammals), which bind to the cargo and simultaneously engage components of the core autophagic machinery via direct interaction with the ubiquitin-like proteins (UBLs) of the Atg8/LC3/GABARAP family and adaptors, Atg11 (in yeasts) or FIP200 (in mammals). In this Review, we critically discuss the biology of the SARs with special emphasis on their interactions with UBLs.

OsNF-YA3 regulates plant growth and osmotic stress tolerance by interacting with SLR1 and SAPK9 in rice.

The antagonism between gibberellin (GA) and abscisic acid (ABA) signaling pathways is vital to balance plant growth and stress response. Nevertheless, the mechanism by which plants determine the balance remains to be elucidated. Here, we report that rice NUCLEAR FACTOR-Y A3 (OsNF-YA3) modulates GA- and ABA-mediated balance between plant growth and osmotic stress tolerance. OsNF-YA3 loss-of-function mutants exhibit stunted growth, compromised GA biosynthetic gene expression, and decreased GA levels, while its overexpression lines have promoted growth and enhanced GA content. Chromatin immunoprecipitation-quantitative polymerase chain reaction analysis and transient transcriptional regulation assays demonstrate that OsNF-YA3 activates GA biosynthetic gene OsGA20ox1 expression. Furthermore, the DELLA protein SLENDER RICE1 (SLR1) physically interacts with OsNF-YA3 and thus inhibits its transcriptional activity. On the other side, OsNF-YA3 negatively regulates plant osmotic stress tolerance by repressing ABA response. OsNF-YA3 reduces ABA levels by transcriptionally regulating ABA catabolic genes OsABA8ox1 and OsABA8ox3 by binding to their promoters. Furthermore, OSMOTIC STRESS/ABA-ACTIVATED PROTEIN KINASE 9 (SAPK9), the positive component in ABA signaling, interacts with OsNF-YA3 and mediates OsNF-YA3 phosphorylation, resulting in its degradation in plants. Collectively, our findings establish OsNF-YA3 as an important transcription factor that positively modulates GA-regulated plant growth and negatively controls ABA-mediated water-deficit and salt tolerance. These findings shed light on the molecular mechanism underlying the balance between the growth and stress response of the plant.

Computational identification of key residues regulating fluorescence emission in a red/green cyanobacteriochrome.

Cyanobacteriochromes (CBCRs) are linear tetrapyrrole bilin-binding photoreceptors of cyanobacteria that exhibit high spectral diversity, gaining attention in optogenetics and bioimaging applications. Several engineering studies on CBCRs were attempted, especially for designing near-infrared (NIR) fluorescent proteins with longer fluorescence wavelengths. However, despite continuous efforts, a key component regulating fluorescence emission property in CBCRs is still poorly understood. As a model system, we focused on red/green CBCR Slr1393g3, from the unicellular cyanobacterium Synechocystis sp. PCC 6803 to engineer Pr to get far-red light-emitting property. Energy profiling and pairwise structural comparison of Slr1393g3 variants effectively reveal the mutations that are critical to the fluorescence changes. H497 seems to play a key role in stabilizing the chromophore environment, especially the α3 helix, while H495, T499, and Q502 are potential key residues determining fluorescence emission peak wavelength. We also found that mutations of α2 and α4 helical regions are closely related to the chromophore binding stability and likely affect fluorescence properties. Taken together, our computational analysis suggests that the fluorescence of Slr1393g3 is mainly controlled by the stabilization of the chromophore binding pocket. The predicted key residues potentially regulating the fluorescence emission property of a red/green CBCR will be advantageous for designing improved NIR fluorescent protein when combined with in vitro molecular evolution approaches.

Diversity of mitophagy pathways at a glance.

Mitochondria are crucial organelles that play a central role in various cell signaling and metabolic pathways. A healthy mitochondrial population is maintained through a series of quality control pathways and requires a fine-tuned balance between mitochondrial biogenesis and degradation. Defective targeting of dysfunctional mitochondria to lysosomes through mitophagy has been linked to several diseases, but the underlying mechanisms and the relative importance of distinct mitophagy pathways in vivo are largely unknown. In this Cell Science at a Glance and the accompanying poster, we describe our current understanding of how parts of, or whole, mitochondria are recognized by the autophagic machinery and targeted to lysosomes for degradation. We also discuss how this might be regulated under different physiological conditions to maintain mitochondrial and cellular health.

A Systematic Literature Review and Meta-Analysis of Primary Evidence Reporting Health-State Preference Values in Chronic Hepatitis B, C, and D.

OBJECTIVES: Chronic viral hepatitis is associated with severe impairment and reduction in patient health-related quality of life because of the substantial morbidity associated with advanced liver disease. The aim of this study was to identify and synthesize utilities for chronic hepatitis B (cHBV), C (cHCV), and D (cHDV) through a systematic literature review (SLR) and meta-analyses. METHODS: Electronic databases were searched from inception to May 2023 to identify primary studies reporting health-state utilities in English in patients aged 18 years and over, with cHBV, cHCV, or cHDV in the United States, the United Kingdom, Europe, Canada, Australia, or New Zealand. Meta-analyses were conducted for studies reporting a measure of uncertainty; model selection (fixed and random) was based on the observed levels of heterogeneity among studies. RESULTS: A total of 24 studies met the inclusion criteria and were included in the meta-analyses. More studies meeting the inclusion criteria reported utilities for cHCV (n = 20) than for cHBV (n = 8); no studies reported utility values for cHDV. Although mean utilities were higher for cHBV compared with cHCV for any given health state, utilities decreased with disease progression toward cirrhosis health states. Meta-analyses in cHCV found a utility decline of 0.1 and 0.03, based on progression from noncirrhosis to compensated cirrhosis and for decompensation in established cirrhosis, respectively. CONCLUSIONS: Chronic viral hepatitis is associated with a considerable impairment in health-related quality of life. Despite our findings, there is a need for more evidence on the lived experience in patients living with chronic hepatitis, notably in cHBV and cHDV.

Disentangling circular economy practices and firm's sustainability performance: A systematic literature review of past achievements and future promises.

This paper systematically and critically reviews the literature on the intersection of circular economy practices (CEPs) and sustainability performance (SP). We synthesize and analyze the extant literature to uncover the knowledge gaps, highlight the contradictory views, and provide a comprehensive overview of the field. Following a detailed database search, we selected 104 empirical studies published in peer-reviewed journals for analysis. Our review reports the publication trends, top publishing journal outlets, research methodologies, and empirical contexts. We outline the theoretical underpinnings, identify the diverse circular economy practices and the key factors that impact circular economy practices and sustainable performance. The review shows a propensity for most authors to reuse established theories or not use theory at all, revealing the need for theory development. Furthermore, our analysis revealed that R&D and innovation, digital technologies, organizational capabilities/resources, and stakeholder and institutional pressure substantially influence the CEPs - SP relationship. Through our detailed assessment of the existing literature, we identified and proposed several themes and avenues for future research.

A comparative study between staple line reinforcement during laparoscopic sleeve gastrectomy and no reinforcement: an Egyptian experience.

BACKGROUND: Laparoscopic sleeve gastrectomy (LSG) has become an increasingly popular bariatric procedure. LSG still conveys some risks, including early staple line complications such as bleeding and leaks. It has been proposed that staple line complications can be reduced by staple line reinforcement (SLR). This study aimed to compare the short-term efficacy and safety of the SLR during LSG by oversewing versus no SLR in an Egyptian cohort over a period of 11 years. PATIENTS AND METHODS: This is a retrospective study that analyzed data from patients undergoing LSG by the same surgeon over a period of 11 years. The patients' early postoperative complications were compared according to performing SLR. RESULTS: The SLR group showed significantly longer surgery time (p = 0.021) and a lower rate of postoperative bleeding (p = 0.027). All leakage cases occurred in the non-SLR group (0.7% vs. 0.0%) without statistical significance (p = 0.212). The two mortality cases occurred in the non-SLR group. The LOS was comparable in the two groups (p = 0.289). CONCLUSION: This study confirms the short-term benefits of SLR by oversewing during LSG in terms of a lower incidence of 30-day morbidity, particularly bleeding, and lower rates of reoperation, with a clinically questionable longer operation time.

Re-Evaluation Method by Index Finger Position in the Face Area Using Face Part Position Criterion for Sign Language Recognition.

Several researchers have proposed systems with high recognition rates for sign language recognition. Recently, there has also been an increase in research that uses multiple recognition methods and further fuses their results to improve recognition rates. The most recent of these studies, skeleton aware multi-modal SLR (SAM-SLR), achieved a recognition rate of 98.00% on the RGB video of the Turkish Sign Language dataset AUTSL. We investigated the unrecognized parts of this dataset and found that some signs where the fingers touch parts of the face were not correctly recognized. The proposed method is as follows: First, those with slight differences in top-1 and top-2 evaluation values in the SAM-SLR recognition results are extracted and re-evaluated. Then, we created heatmaps of the coordinates of the index finger in one-handed sign language in the face region of the recognition result in the top-1 to top-3 training data of the candidates based on the face part criteria, respectively. In addition, we extracted four index finger positions from the test data where the index finger stayed longer and obtained the product of the heatmap values of these positions. The highest value among them was used as the result of the re-evaluation. Finally, three evaluation methods were used: the absolute and relative evaluation with two heatmaps and an evaluation method integrating the absolute and relative evaluation results. As a result of applying the proposed method to the SAM-SLR and the previously proposed model, respectively, the best method achieved 98.24% for the highest recognition rate, an improvement of 0.30 points.

A Systematic Literature Review on Machine Learning and Deep Learning Approaches for Detecting DDoS Attacks in Software-Defined Networking.

Software-defined networking (SDN) is a revolutionary innovation in network technology with many desirable features, including flexibility and manageability. Despite those advantages, SDN is vulnerable to distributed denial of service (DDoS), which constitutes a significant threat due to its impact on the SDN network. Despite many security approaches to detect DDoS attacks, it remains an open research challenge. Therefore, this study presents a systematic literature review (SLR) to systematically investigate and critically analyze the existing DDoS attack approaches based on machine learning (ML), deep learning (DL), or hybrid approaches published between 2014 and 2022. We followed a predefined SLR protocol in two stages on eight online databases to comprehensively cover relevant studies. The two stages involve automatic and manual searching, resulting in 70 studies being identified as definitive primary studies. The trend indicates that the number of studies on SDN DDoS attacks has increased dramatically in the last few years. The analysis showed that the existing detection approaches primarily utilize ensemble, hybrid, and single ML-DL. Private synthetic datasets, followed by unrealistic datasets, are the most frequently used to evaluate those approaches. In addition, the review argues that the limited literature studies demand additional focus on resolving the remaining challenges and open issues stated in this SLR.

Volumetric and multispectral DWI near metallic implants using a non-linear phase Carr-Purcell-Meiboom-Gill diffusion preparation.

PURPOSE: DWI near metal implants has not been widely explored due to substantial challenges associated with through-slice and in-plane distortions, the increased encoding requirement of different spectral bins, and limited SNR. There is no widely adopted clinical protocol for DWI near metal since the commonly used EPI trajectory fails completely due to distortion from extreme off-resonance ranging from 2 to 20 kHz. We present a sequence that achieves DWI near metal with moderate b-values (400-500 s/mm2 ) and volumetric coverage in clinically feasible scan times. THEORY AND METHODS: Multispectral excitation with Cartesian sampling, view angle tilting, and kz phase encoding reduce in-plane and through-plane off-resonance artifacts, and Carr-Purcell-Meiboom-Gill (CPMG) spin-echo refocusing trains counteract T2* effects. The effect of random phase on the refocusing train is eliminated using a stimulated echo diffusion preparation. Root-flipped Shinnar-Le Roux refocusing pulses permits preparation of a high spectral bandwidth, which improves imaging times by reducing the number of excitations required to cover the desired spectral range. B1 sensitivity is reduced by using an excitation that satisfies the CPMG condition in the preparation. A method for ADC quantification insensitive to background gradients is presented. RESULTS: Non-linear phase refocusing pulses reduces the peak B1 by 46% which allows RF bandwidth to be doubled. Simulations and phantom experiments show that a non-linear phase CPMG pulse pair reduces B1 sensitivity. Application in vivo demonstrates complementary contrast to conventional multispectral acquisitions and improved visualization compared to DW-EPI. CONCLUSION: Volumetric and multispectral DW imaging near metal can be achieved with a 3D encoded sequence.

Sparse logistic regression revealed the associations between HBV PreS quasispecies and hepatocellular carcinoma.

BACKGROUND: Chronic infection with hepatitis B virus (HBV) has been proved highly associated with the development of hepatocellular carcinoma (HCC). AIMS: The purpose of the study is to investigate the association between HBV preS region quasispecies and HCC development, as well as to develop HCC diagnosis model using HBV preS region quasispecies. METHODS: A total of 104 chronic hepatitis B (CHB) patients and 117 HBV-related HCC patients were enrolled. HBV preS region was sequenced using next generation sequencing (NGS) and the nucleotide entropy was calculated for quasispecies evaluation. Sparse logistic regression (SLR) was used to predict HCC development and prediction performances were evaluated using receiver operating characteristic curves. RESULTS: Entropy of HBV preS1, preS2 regions and several nucleotide points showed significant divergence between CHB and HCC patients. Using SLR, the classification of HCC/CHB groups achieved a mean area under the receiver operating characteristic curve (AUC) of 0.883 in the training data and 0.795 in the test data. The prediction model was also validated by a completely independent dataset from Hong Kong. The 10 selected nucleotide positions showed significantly different entropy between CHB and HCC patients. The HBV quasispecies also classified three clinical parameters, including HBeAg, HBVDNA, and Alkaline phosphatase (ALP) with the AUC value greater than 0.6 in the test data. CONCLUSIONS: Using NGS and SLR, the association between HBV preS region nucleotide entropy and HCC development was validated in our study and this could promote the understanding of HCC progression mechanism.

Analysis of the Results of the Borowiec SLR Station (7811) for the Period 1993-2019 as an Example of the Quality Assessment of Satellite Laser Ranging Stations.

This paper presents the results of an orbital analysis of satellite laser ranging data performed by the Borowiec SLR station (7811) in the period from July 1993 to December 2019, including the determination of the station positions and velocity. The analysis was performed using the GEODYN-II orbital program for the independent monthly orbital arcs from the results of the LAGEOS-1 and LAGEOS-2 satellites. Each arc was created from the results of the laser observations of a dozen or so selected stations, which were characterized by a large number of normal points and a good quality of observations. The geocentric and topocentric coordinates of the station were analyzed. Factors influencing the uncertainty of the measurements were determined: the number of the normal points, the dispersion of the normal points in relation to the orbits, and the long-term stability of the systematic deviations. The position leap at the end of 2002 and its interpretation in ITRF2014 were analyzed. The 3D stability of the determined positions throughout the period of study was equal to 12.7 mm, with the uncertainty of determination being at the level of 4.3 mm. A very high compliance of the computed velocity of the Borowiec SLR station (24.9 mm/year) with ITRF2014 (25.0 mm/year) was found.

Multi-GNSS Combined Orbit and Clock Solutions at iGMAS.

Global navigation services from the quad-constellation of GPS, GLONASS, BDS, and Galileo are now available. The international GNSS monitoring and assessment system (iGMAS) aims to evaluate the navigation performance of the current quad systems under a unified framework. In order to assess impact of orbit and clock errors on the positioning accuracy, the user range error (URE) is always taken as a metric by comparison with the precise products. Compared with the solutions from a single analysis center, the combined solutions derived from multiple analysis centers are characterized with robustness and reliability and preferred to be used as references to assess the performance of broadcast ephemerides. In this paper, the combination method of iGMAS orbit and clock products is described, and the performance of the combined solutions is evaluated by various means. There are different internal precisions of the combined orbit and clock for different constellations, which indicates that consistent weights should be assigned for individual constellations and analysis centers included in the combination. For BDS-3, Galileo, and GLONASS combined orbits of iGMAS, the root-mean-square error (RMSE) of 5 cm is achieved by satellite laser ranging (SLR) observations. Meanwhile, the SLR residuals are characterized with a linear pattern with respect to the position of the sun, which indicates that the solar radiation pressure (SRP) model adopted in precise orbit determination needs further improvement. The consistency between combined orbit and clock of quad-constellation is validated by precise point positioning (PPP), and the accuracies of simulated kinematic tests are 1.4, 1.2, and 2.9 cm for east, north, and up components, respectively.

Active Control Loop of the BOROWIEC SLR Space Debris Tracking System.

The task of tracking cooperative satellites equipped with laser retroreflectors, by means of Satellite Laser Ranging (SLR), is an issue well described in the literature. The follow-up movement of the ground-based transceiver telescope behind an orbital object is based on the positional ephemeris data. The problem of controlling the follow-up motion of the telescope's mount mostly in the Az/El configuration in this case boils down to the interpolation of the positional ephemeris data of the orbital object, which is the information input vector for the motion control system of the orthogonal and non-coupled axes of the propulsion system. In the case of tracking and determining the position of uncooperative objects (not equipped with retroreflectors), for which we can include rocket bodies and fragmentary elements, the task of keeping track of them becomes complex. The positional uncertainty of the ephemeris of uncooperative objects obtained mainly by means of survey radar acquisition requires the use of innovative solutions and complex control systems that enable the effective implementation of the tracking process. This paper presents innovative methods for the active control loop used in the SLR technique, consisting of dynamic motion corrections based on the passive optical acquisition with object recognition and analysis of the photon trace scattered from an orbital object.

E-Cardiac Care: A Comprehensive Systematic Literature Review.

The Internet of Things (IoT) is a complete ecosystem encompassing various communication technologies, sensors, hardware, and software. IoT cutting-edge technologies and Artificial Intelligence (AI) have enhanced the traditional healthcare system considerably. The conventional healthcare system faces many challenges, including avoidable long wait times, high costs, a conventional method of payment, unnecessary long travel to medical centers, and mandatory periodic doctor visits. A Smart healthcare system, Internet of Things (IoT), and AI are arguably the best-suited tailor-made solutions for all the flaws related to traditional healthcare systems. The primary goal of this study is to determine the impact of IoT, AI, various communication technologies, sensor networks, and disease detection/diagnosis in Cardiac healthcare through a systematic analysis of scholarly articles. Hence, a total of 104 fundamental studies are analyzed for the research questions purposefully defined for this systematic study. The review results show that deep learning emerges as a promising technology along with the combination of IoT in the domain of E-Cardiac care with enhanced accuracy and real-time clinical monitoring. This study also pins down the key benefits and significant challenges for E-Cardiology in the domains of IoT and AI. It further identifies the gaps and future research directions related to E-Cardiology, monitoring various Cardiac parameters, and diagnosis patterns.

Active Decision Support System for Observation Scheduling Based on Image Analysis at the BOROWIEC SLR Station.

The dynamic exploration of the orbits from the LEO-to-GEO region, for the needs of telecommunication services, science, industry and defense, forces monitoring of the trajectory of such orbital objects for the safety of spacecraft traffic and, in the case of deorbitation, for the safety of ground infrastructure. First off all, the need for trajectory monitoring in order to avoid collisions can be distinguished, as well as the need to calibrate the satellite on-board devices. This is mainly carried out by radar measurements, by passive optical acquisition and active laser measurements. The number of orbital objects increases rapidly, and the number of tracking stations for the second is relatively small. This leads to a situation in which each tracking station must select which of the objects will be subject to the measurement task. In the case of the Satellite Laser Ranging (SLR) or passive optical set-up, the weather conditions are an important factor enabling the measurement of the orbital object trajectory. This paper presents an innovative observation scheduling support system based on the analysis of the images obtained from the Allsky camera. The information of the degree of cloud cover, the position of the Sun/Moon in connection with the graphical projections of the ephemeris trajectory of the orbital objects allows increasing the measurement efficiency. The presented solution is part of a larger number of improvements carried out by the author, which lead to the upgrade of SLR stations in terms of new technologies and safety of use.

A Systematic Literature Review on Machine and Deep Learning Approaches for Detecting Attacks in RPL-Based 6LoWPAN of Internet of Things.

The IETF Routing Over Low power and Lossy network (ROLL) working group defined IPv6 Routing Protocol for Low Power and Lossy Network (RPL) to facilitate efficient routing in IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN). Limited resources of 6LoWPAN nodes make it challenging to secure the environment, leaving it vulnerable to threats and security attacks. Machine Learning (ML) and Deep Learning (DL) approaches have shown promise as effective and efficient mechanisms for detecting anomalous behaviors in RPL-based 6LoWPAN. Therefore, this paper systematically reviews and critically analyzes the research landscape on ML, DL, and combined ML-DL approaches applied to detect attacks in RPL networks. In addition, this study examined existing datasets designed explicitly for the RPL network. This work collects relevant studies from five major databases: Google Scholar, Springer Link, Scopus, Science Direct, and IEEE Xplore® digital library. Furthermore, 15,543 studies, retrieved from January 2016 to mid-2021, were refined according to the assigned inclusion criteria and designed research questions resulting in 49 studies. Finally, a conclusive discussion highlights the issues and challenges in the existing studies and proposes several future research directions.

Applications of Wireless Sensor Networks and Internet of Things Frameworks in the Industry Revolution 4.0: A Systematic Literature Review.

The 21st century has seen rapid changes in technology, industry, and social patterns. Most industries have moved towards automation, and human intervention has decreased, which has led to a revolution in industries, named the fourth industrial revolution (Industry 4.0). Industry 4.0 or the fourth industrial revolution (IR 4.0) relies heavily on the Internet of Things (IoT) and wireless sensor networks (WSN). IoT and WSN are used in various control systems, including environmental monitoring, home automation, and chemical/biological attack detection. IoT devices and applications are used to process extracted data from WSN devices and transmit them to remote locations. This systematic literature review offers a wide range of information on Industry 4.0, finds research gaps, and recommends future directions. Seven research questions are addressed in this article: (i) What are the contributions of WSN in IR 4.0? (ii) What are the contributions of IoT in IR 4.0? (iii) What are the types of WSN coverage areas for IR 4.0? (iv) What are the major types of network intruders in WSN and IoT systems? (v) What are the prominent network security attacks in WSN and IoT? (vi) What are the significant issues in IoT and WSN frameworks? and (vii) What are the limitations and research gaps in the existing work? This study mainly focuses on research solutions and new techniques to automate Industry 4.0. In this research, we analyzed over 130 articles from 2014 until 2021. This paper covers several aspects of Industry 4.0, from the designing phase to security needs, from the deployment stage to the classification of the network, the difficulties, challenges, and future directions.

A Preliminary Contribution towards a Risk-Based Model for Flood Management Planning Using BIM: A Case Study of Lisbon.

Preparing a city for the impact of global warming is becoming of major importance. Adopting climate-proof policies and strategies in response to climate change has become a fundamental element for city planning. To this end, this research considers a multidisciplinary approach, at the local scale, able to connect urban planning and architecture, as a vital base for considering a coastal cities' ability to control the consequences of climate change, specifically floods. So far, there is a scarcity of research connecting sea ground and land surveys, and this study could become a foundational reference for coastline settlement management using BIM. We found in BIM (Building Information Modeling) a possible tool for managing coastal risk, since it can combine crowdsourced data for geometric and information modeling of the city. The proposed BIM model includes a topography used for 3D thematic maps, a riverbed model, and a waterway model. This model aims to facilitate coordination across separate actors and interests since the urban area model is always updatable and improvable. Focusing on a case study of Lisbon, we developed risk-based 3D maps of the area close to the shoreline of the Tagus River.