Proactive Assessment Research Articles

Impact of infectious diseases associated with passenger ships on ports: a systematic review

Abstract Background In an enclosed ship environment, close contact between passengers and crew members is inevitable. As a result, passenger ships can be a suitable environment for the transmission of infections between people. In this context, it is essential to establish effective prevention and control measures to protect the health of passengers and crew members while ensuring that shipping minimizes its contribution to the global spread of disease. The aim of this review is to provide knowledge on the impact of infectious diseases on board large passenger ships on the port, the port community and other land-based operations to better understand the effectiveness of the prevention, mitigation and management (PMM) measures implemented, in particular ship-to-shore communication. Methods A systematic literature review was conducted according to the PRISMA guidelines, searching three databases and including additional articles from hand searches up to November 2023. Peer-reviewed studies of infectious disease outbreaks on large passenger ships that described ship-shore interaction, port preparedness, impact on the port community, and impact on other modes of transportation were included. Results A total of 555 publications were initially identified. Finally, 22 articles were included. Most studies reported on COVID-19 outbreaks on cruise ships; other communicable diseases reported were influenza, gastroenteritis and varicella. The articles highlighted the importance of comprehensive management plans and proactive risk assessment during infectious disease outbreaks. Conclusions Effective stakeholder collaboration, ship-to-shore communication, and coordination of medical transport, isolation, and quarantine measures are essential components of infectious disease PMM in maritime passenger shipping and ship-to-shore operations. The findings suggest that further research is needed to improve the evidence and knowledge about this important issue. Key messages • Proactive risk assessment, comprehensive management plans and effective collaboration are critical to preventing, mitigating and managing infectious diseases on passenger ships. • Overall, very little evidence of effective practices and capacities related to the interaction of passenger ships with land-based operations, stakeholders and port communities.

Field study on proactive pipe condition assessment using hydroacoustic noise

Condition assessment of water transmission pipelines is of important necessity for prioritizing rehabilitation and preventing catastrophic pipe failure. Hydraulic transient analysis has been investigated for three decades for this purpose and applied to many field studies. However, the significant pipe vibrations caused by the transient generation process and the limited energy and bandwidth of conventional discrete transient pressure waves (e.g., step and pulse waves) limit the accuracy and resolution of the analysis. This paper reports a pilot field study of noninvasive and nondestructive pipe condition assessment using small amplitude and persistent hydroacoustic noise instead of conventional large and discrete hydraulic transient waves. By opening a discharge valve installed at an existing access point, such as an air valve, on the field pipe, hydroacoustic noise was generated at the valve due to the turbulence of the discharge. The hydroacoustic noise was measured by pressure transducers at this access point as well as some other access points along the field pipe. A signal deconvolution process was then applied to the measured hydraulic pressures to transfer them to a compositional impulse response function (IRF), which is composed of IRFs of different pipe sections. A mathematical model was derived to interpret the anomaly-induced spikes on the deconvolution trace. A time-shifting process on the compositional IRFs was proposed to find the locations with pipe condition changes from a specific direction of the pipe. The field study has shown that small-amplitude persistent hydroacoustic noise can replace conventional large hydraulic transient waves for pipe condition assessment.

Proactive assessment of patient reported outcomes in ovarian cancer studies: a systematic review and call for action in future studies

ObjectiveThis systematic review aims to evaluate the proactive or real-time assessment of patient reported outcomes in studies involving patients with ovarian cancer undergoing systemic therapy.MethodsPubMed, Embase, and Cochrane databases were...

ONLINE PRACTICE TEST BANK SOLUTION: A WEB-BASED REVIEW PLATFORM FOR LIBRARY AND INFORMATION SCIENCE PRACTITIONERS

Test construction and test administration in most institutions still adopt the traditional pen-and-paper method of examination, which is very tedious (Kotwal et al., 2016). Its lengthy process can limit the time instructors in devoting to their proactive instruction and assessment. The general purpose of the study is to develop an Online Practice Test bank for Library and Information Science Practitioners. To actualize the Online Practice Test bank, the researcher followed the three phases of the modified rapid application model: Planning or Analyze Phase, Design and Development or Prototyping Phase, and Testing. The result of the study revealed that the developed system was able to execute its different operations. Specifically, by providing an avenue to the contributors/review masters and the reviewees to communicate and interact regarding the different reviewers provided. The reviewees can also track their progress through the learning analytics feature of the system. The contributors/review masters can monitor if the review materials they have provided has efficient test items by accessing the test item analysis. The system also has undergone functionality testing through conducting test cases, which have also gained positive remarks. Based on the results of the developed Online Practice Test bank, it is concluded that the system attained its three objectives in having integrated features that would be a great help, especially to the future licensed professional librarians as they will have a platform where they do their review and assess their knowledge on the six core subjects of library science. It is therefore recommended that mobile or android-based user modules must be developed for it to be more accessible to the users. And also an automated intervention or scaffolding for coping with the results from the performance of the review. And it must have an option or platform for contributors outside the institution who want to share their review materials relevant to the Library and Information Science profession.

Risk Assessment of ZAP-X→ Radiosurgery System in a Quaternary Care Hospital Using FMEA Approach

Background and Aims: The overarching goal of this study is to conduct a robust risk assessment using the Failure Modes and Effects Analysis (FMEA) approach. By identifying potential failure modes and their potential impacts on patient care and hospital operations, this research seeks to provide actionable insights and mitigation strategies for the safe and effective implementation of the ZAP-X Radiosurgery System. The swift integration of advanced medical technologies, exemplified by the ZAP-X→ Gyroscopic Stereotactic Radiosurgery System, a computer-controlled machine that delivers radiation to an intended target in the brain, necessitates a comprehensive proactive risk assessment before the launch of the system to ensure the safety of patients, staff and operational processes. Method: Applying the FMEA methodology, we meticulously mapped all processes and sub-processes associated with the ZAP-X Radiosurgery System implementation. Our multidisciplinary team, through a discussion on ‘what can go wrong’, identified failure modes. Risks were prioritised based on severity, likelihood and detectability giving them a Risk Priority Number (RPN). The team proposed mitigation strategies, deploying controls to enhance safety and reliability.

Seismic Upgrading of the Heritage-Protected Reinforced Concrete Warehouse in Rijeka, Croatia

Despite Croatia experiencing two strong earthquakes in 2020, Rijeka was not directly affected, underscoring the importance of proactive seismic assessment and strengthening in all seismic regions. This paper presents a comprehensive case study on the seismic strengthening of a 20th-century concrete building located in Rijeka, Croatia, originally designed according to Austro-Hungarian construction norms and practices. As a heritage-protected structure, the building’s architectural features and construction practices were examined and contextualized within its historical background. The assessment and renovation phases of this project are discussed in detail, demonstrating the practical application of modern seismic strengthening techniques while preserving the building’s historical integrity. This case study aims to highlight the need for such measures to protect heritage structures and to show the implementation of rapid and new (ad hoc) norms for earthquake-damaged buildings in Croatia. This study serves as a reference for engineers, architects, and conservationists involved in the preservation of heritage buildings, demonstrating that it is possible to enhance their structural safety without compromising their architectural authenticity.

Novel Metabolic Indicators and the Risk of Cardiovascular Disease in Patients with Hypertension: A Primary-care Cohort Study

Background and AimsData are limited on whether several easily measured indices serve as effective tools for Cardiovascular disease (CVD) risk assessment in hypertensive patients. This study aimed to assess the associations of metabolic score for insulin resistance (METS-IR), lipid accumulation product (LAP), and visceral adiposity index (VAI) with CVD risk in hypertensive patients. Methods and ResultsOur data were drawn from the medical records of primary-care institutions in China. The present study included 306,680 individuals with hypertension attending primary healthcare centers. Cox regression analyses were applied to assess the associations of novel metabolic indicators with the risk of CVD. During a median follow-up of 1.98 years, 5820 participants developed CVD. When comparing with the lowest quartile of the indices, the highest quartile of METS-IR, LAP, and VAI was associated with 1.25-fold (95% CI: 1.16-1.35), 1.15-fold (95% CI: 1.05-1.25), and 1.19-fold (95% CI: 1.10-1.28) risk of CVD after adjusting for potential confounders. ConclusionThis study provided additional evidence that novel metabolic indicators like METS-IR, LAP, and VAI were associated with the risk of CVD. These results suggest that proactive assessment of visceral adiposity and insulin resistance could be helpful for the effective clinical management of the hypertensive population.

Enhancing highway Loop Safety Level through proactive risk-based assessment of geometric configuration using lateral acceleration

Objective Loop ramps are complex due to their combination of horizontal curves and vertical alignments. Analyzing driving behavior and measuring safety levels can provide insights for designers, helping to improve the performance and alignment of design assumptions with actual driving behavior on loops. Therefore, the primary objective of this research is to explore the safety, performance and geometric configuration of the main body and general shape of free-flow loop ramps in the free-following mode. Methods The study uses data from a UAV to investigate vehicle demand behavior. Maximum lateral acceleration (a y,i) in loops is used as a Surrogate Safety Measure (SSM), along with a new parameter, the a/b ratio, to determine the general shape of loop bodies. The study presents the Loop Safety Level (LSL), an approach for proactive risk analysis and ranking that relies on threshold lateral acceleration (a t), 85th percentile maximum lateral acceleration ( a y,max,85%), and crash analysis. Results A higher LSL value points to a more critical safety concern regarding the loop’s shape in relation to lateral acceleration caused by driving behaviors. Comparing crash statistics with lateral acceleration results enables the LSL to provide appropriate safety ratings and diagnose loop segment safety. A prediction model for maximum lateral acceleration, based on loop geometry, demonstrates a good fit (R2=0.88) between observed and predicted data. Conclusions The study enhances understanding of safety considerations in geometric configuration and general shape enhancement of loops during the design process.

Demographic and lifestyle influences on depression, anxiety, and stress among graduate students: An analytical study of mental health outcomes

This study investigates the frequency and intensity of depression, anxiety, and stress in graduate students, with a specific emphasis on demographic and lifestyle variables. A cohort of 385 postgraduate students successfully administered the Depression, Anxiety, and Stress Scale (DASS-21) and furnished their demographic details. The sample was gender-balanced, with 50.1% male and 49.9% female participants. It comprised students from both urban (47.3%) and rural (52.7%) areas. The marital status distribution was as follows: 84.9% were married, 14.3% were single, and 0.8% were separated, divorced, or widowed. The survey participants were accommodated in three different ways: living with family (36%), staying in dorms (31%), or renting separately (33%). SPSS data analysis indicated that a considerable proportion of individuals suffered psychological discomfort. Specifically, 36.5% reported depression, 39.2% reported anxiety, and 27.8% reported stress. The correlation and regression studies revealed substantial relationships between demographic characteristics, lifestyle habits, and mental health outcomes. Significantly, financial worries, academic demands, and absence of work-life equilibrium were major sources of stress. The results emphasize the immediate requirement for customized mental health interventions in educational institutions. Recommended approaches encompass proactive mental health assessments, easily available therapy services, peer support systems, and programs aimed at enhancing resilience. Tackling these psychological obstacles is crucial for improving the welfare, educational achievements, and career growth of postgraduate students.

Revolutionizing Personalized Health: The Frontier of Wearable Biomolecule Sensors Through 3D Printing Innovation

AbstractThis review article delves into the innovative intersection of 3D-printed technologies and wearable chemical sensors, highlighting a forward-thinking approach to biomarker monitoring. It emphasizes the transformative role of additive manufacturing in the development of wearable devices tailored for the precise detection of chemical biomarkers, crucial for proactive disease management and health assessment. By offering a detailed exploration of how 3D printing of nanomaterials contributes to pioneering sensor designs, this review underscores the practicality of sensor wearability, ensuring comfort and efficacy for users. We address the challenges of material resilience, sensor durability, and efficient data communication, while also charting the significant trends and future directions that promise to redefine the landscape of flexible and wearable chemical sensors. Through a comprehensive analysis, this article aims to showcase the pivotal advancements and ongoing innovations in the field, emphasizing the critical impact of 3D printing on enhancing personalized healthcare and wearable diagnostics. Graphical Abstract

Data-driven credit risk monitoring: Leveraging machine learning in risk management

This review explores the evolution of credit risk monitoring, tracing its journey from traditional qualitative assessments to the current integration of machine learning (ML). It highlights how the integration of ML and big data has introduced unprecedented capabilities for analyzing extensive datasets and detecting subtle patterns beyond human capacity. These advanced technologies enable more accurate, efficient and dynamic credit risk predictions through techniques such as random forests, gradient boosting and decision trees. The transformative potential of these methodologies in credit risk assessment was critically examined, addressing challenges such as legacy system integration, data quality and regulatory compliance. It emphasizes the importance of incorporating forward-looking macroeconomic indicators to comply with applicable financial reporting standards and regulatory requirements. Furthermore, it highlights the necessity of ensuring model transparency to maintain trust and compliance. By leveraging the power of big data and ML, the study shows that financial institutions can achieve more precise and proactive risk assessments, enhancing decision-making processes and mitigating potential risks. This comprehensive review provides valuable insights for stakeholders, guiding the implementation of advanced analytical techniques to improve credit risk management. Ultimately, it underscores the potential for a more robust, efficient and stable financial system through the strategic application of ML and big data analytics. Keywords: Credit Risk Management, Financial Services, Machine Learning, Big Data, Financial Transformation.

Proactive integrated consultation-liaison psychiatry and time spent in hospital by older medical inpatients in England (The HOME Study): a multicentre, parallel-group, randomised controlled trial

Older people admitted to hospital in an emergency often have prolonged inpatient stays that worsen their outcomes, increase health-care costs, and reduce bed availability. Growing evidence suggests that the biopsychosocial complexity of their problems, which include cognitive impairment, depression, anxiety, multiple medical illnesses, and care needs resulting from functional dependency, prolongs hospital stays by making medical treatment less efficient and the planning of post-discharge care more difficult. We aimed to assess the effects of enhancing older inpatients' care with Proactive Integrated Consultation-Liaison Psychiatry (PICLP) in The HOME Study. We have previously described the benefits of PICLP reported by patients and clinicians. In this Article, we report the effectiveness and cost-effectiveness of PICLP-enhanced care, compared with usual care alone, in reducing time in hospital. We did a parallel-group, multicentre, randomised controlled trial in 24 medical wards of three English acute general hospitals. Patients were eligible to take part if they were 65 years or older, had been admitted in an emergency, and were expected to remain in hospital for at least 2 days from the time of enrolment. Participants were randomly allocated to PICLP or usual care in a 1:1 ratio by a database software algorithm that used stratification by hospital, sex, and age, and randomly selected block sizes to ensure allocation concealment. PICLP clinicians (consultation-liaison psychiatrists supported by assisting clinicians) made proactive biopsychosocial assessments of patients' problems, then delivered discharge-focused care as integrated members of ward teams. The primary outcome was time spent as an inpatient (during the index admission and any emergency readmissions) in the 30 days post-randomisation. Secondary outcomes were the rate of discharge from hospital for the total length of the index admission; discharge destination; the length of the index admission after random allocation truncated at 30 days; the number of emergency readmissions to hospital, the number of days spent as an inpatient in an acute general hospital, and the rate of death in the year after random allocation; the patient's experience of the hospital stay; their view on the length of the hospital stay; anxiety (Generalized Anxiety Disorder-2); depression (Patient Health Questionnaire-2); cognitive function (Montreal Cognitive Assessment-Telephone version); independent functioning (Barthel Index of Activities of Daily Living); health-related quality of life (five-level EuroQol five-dimension questionnaire); and overall quality of life. Statisticians and data collectors were masked to treatment allocation; participants and ward staff could not be. Analyses were intention-to-treat. The trial had a patient and public involvement panel and was registered with ISRTCN (ISRCTN86120296). 2744 participants (1399 [51·0%] male and 1345 [49·0%] female) were enrolled between May 2, 2018, and March 5, 2020; 1373 were allocated to PICLP and 1371 to usual care. Participants' mean age was 82·3 years (SD 8·2) and 2565 (93·5%) participants were White. The mean time spent in hospital in the 30 days post-randomisation (analysed for 2710 [98·8%] participants) was 11·37 days (SD 8·74) with PICLP and 11·85 days (SD 9·00) with usual care; adjusted mean difference -0·45 (95% CI -1·11 to 0·21; p=0·18). The only statistically and clinically significant difference in secondary outcomes was the rate of discharge, which was 8.5% higher (rate ratio 1·09 [95% CI 1·00 to 1·17]; p=0·042) with PICLP-a difference most apparent in patients who stayed for more than 2 weeks. Compared with usual care, PICLP was estimated to be modestly cost-saving and cost-effective over 1 and 3, but not 12, months. No intervention-related serious adverse events occurred. This is the first randomised controlled trial of PICLP. PICLP is experienced by older medical inpatients and ward staff as enhancing medical care. It is also likely to be cost-saving in the short-term. Although the trial does not provide strong evidence that PICLP reduces time in hospital, it does support and inform its future development and evaluation. UK National Institute for Health and Care Research.

Enhanced rock mass rating prediction from tunnel face imagery: A decision-supportive ensemble deep learning approach

Ensuring safety in tunnel construction necessitates a rapid and objective evaluation of exposed tunnel faces for proactive rock mass risk assessment. The diversity of rock types and discontinuities contributes to structural complexity and local variability, introducing subjectivity and uncertainty in traditional evaluations based on the experience of field engineers. In this study, a convolutional neural network (CNN) is employed for regression to enhance the objectivity and consistency of rock mass classification via rock mass rating (RMR). The model interprets the entire tunnel face image holistically by identifying and learning from complex patterns, rather than detecting specific geological features like fractured or discontinuity zones. The network model, comprising feature extraction and regression blocks, utilizes the EfficientNet family for computational efficiency and accuracy. Data augmentation and ensemble learning address prediction variability due to image quality, optimizing the model for accurate RMR predictions and providing error ranges. The RMR predictions using excavation site images closely follow the field-evaluated evolution. A server communication-based mobile application is developed for real-time RMR evaluation, enhancing its practical field applicability. In geology, tunnel, and geotechnical engineering, where decisions rely on extensive experience, our approach demonstrates that deep learning can enhance decision-making by analyzing large accumulated datasets to predict optimal outcomes.

The Role of Malocclusion and Oral Parafunctions in Predicting Signs and Symptoms of Temporomandibular Disorders-A Cross-Sectional Study.

The aim of this study was to examine to what extent malocclusion and parafunctional habits contribute to the development of signs and symptoms associated with temporomandibular disorders (TMD) in schoolchildren with mixed dentition in Croatia in a sample of 338 children, aged 9 to 15 years. TMD signs and symptoms assessed by the clinician were joint function and pain, masticatory muscles tenderness, range of mandibular motion, and joint sounds. To evaluate subjective symptoms and parafunctions, children and parents were asked about the presence of headaches, jaw locking, temporomandibular joint (TMJ) sounds, pain during mouth opening, or bruxism, as well as parafunctions like biting pencils or nails, chewing hard candies or ice, daily gum chewing, opening bottles with teeth, engaging in jaw play, thumb-sucking, and clenching/grinding teeth. At least one symptom of a TMD was pronounced in 142 participants (42.0%). The most commonly reported parafunction was pencil or nail biting, present in 25.1% of participants. Class II malocclusion increased the likelihood by 2.6 times, pencil or nail biting by 2.34 times, and clenching/grinding teeth by 8.9 times that the subject would exhibit at least one TMD symptom. Every child with mixed dentition should undergo a brief examination of the TMJ, especially in cases of Class II malocclusion, pencil or nail biting, and teeth clenching or grinding, as these have all been identified as significant risk factors that increase the likelihood of experiencing TMD symptoms. This highlights the need for proactive screening and assessment by healthcare providers to reduce the risk and prevalence of TMDs in affected children and ensure timely diagnosis and treatment.

Uptake and outcomes of VaxCheck, an adult life-course vaccination service: A study among community pharmacists

Vaccination rates among Canadian adults remain suboptimal. Community pharmacists have increasingly adopted an active role in vaccination and are trusted by the public to provide vaccination-related advice and care. The aim of this prospective descriptive study was to develop and test a novel clinical service, VaxCheck, to support proactive life-course vaccination assessments by community pharmacists. From October 2022-May 2023, 123 VaxCheck consultations were performed at 9 community pharmacies within the Wholehealth Pharmacy Partners banner in Ontario, Canada. Patient age averaged 60 years and 35.8 % had at least one chronic disease risk factor, 17.7 % had lifestyle-related risk factor(s), and 15.4 % were immunocompromised. 95.1 % of VaxCheck consultations resulted in at least one vaccine recommendation, averaging three vaccines per patient. Most frequently recommended vaccines were those against pneumococcal disease, tetanus/diphtheria, herpes zoster, COVID-19, and influenza, with acceptance rates highest for those available without a prescription and at no charge at the pharmacy. Patient feedback was positive with 85 % of respondents agreeing or strongly agreeing that they would recommend the service to others. Vaccine administration at the time of the consultation occurred with only 5.9 % of recommended vaccines, frequently impacted by limitations to scope of practice related to pharmacist ability to prescribe and/or administer the vaccine and lack of pharmacy access to publicly funded vaccine supply for those meeting eligibility criteria. Community pharmacists performing a VaxCheck consultation can proactively identify indicated vaccines for patients. Expansion in scope of practice and access to publicly funded vaccine is recommended to further support vaccine uptake.

Combining non-invasive liquid biopsy and a methylation analysis to assess surgical risk for early esophageal cancer.

While the widespread use of endoscopic submucosal dissection (ESD) has significantly reduced the incidence of early esophageal cancer (ESCA), the limited ability of ESD to strip deep infiltrating esophageal lesions results in a considerable risk of intraoperative perforation. Circulating-free DNA (cfDNA) is widely used in modern tumor screening due to its non-invasive detection capabilities. A methylation analysis offers vital insights into the condition and advancement of malignancies due to its unique positioning, such as a marker of cancer. This study investigated the potential of combining a non-invasive liquid biopsy technique, along with a methylation analysis, to assess the surgical perforation risk of ESCA patients. In this study, we conducted an analysis of gene expression differences between stage I esophageal squamous carcinoma samples and healthy tissue samples using data from The Cancer Genome Atlas (TCGA) database. We also identified the genes associated with progression-free survival (PFS) in esophageal squamous carcinoma. Integrating the framework of the methylation analysis, we explored the methylated sites of these distinct genes. To refine this process, we used the Shiny Methylation Analysis Resource Tool (SMART) to conduct a comprehensive analysis of these sites. We then confirmed the stability of the methylation sites in different lesion conditions using methylation-specific quantitative polymerase chain reaction (MS-qPCR) with paraffin tissue samples collected after ESD. We analyzed RNA-sequencing data from 42 early stage ESCA patients and 17 controls, identifying 1,263 up-regulated and 460 down-regulated genes. Functional analyses revealed involvement in key pathways such as cell cycle regulation and immune responses. Furthermore, we identified 38 differentially expressed genes associated with PFS. Using SMART analysis, we found 217 hyper-methylated regions in 38 genes, suggesting potential early markers for ESCA. Validation experiments confirmed the reliability of 29 hyper-methylated regions in FFPE tissue samples and 6 regions in cfDNA. A LunaCAM model showed high accuracy [area under the curve (AUC) =0.89] in discriminating early ESCA. Integrated assessment of six highly methylated regions significantly improved predictive performance, with 90.56% sensitivity, highlighting the importance of combinatorial biomarker evaluation for early cancer detection. This study established a novel approach that integrates non-invasive testing with a methylation analysis to assess the surgical risk of early ESCA patients. The significance of changes in methylation sites in relation to lesion status should not be underestimated, as they have the potential to offer vital insights for proactive risk assessments before surgery.

Understanding The Benefits and Risks of Sustainable Nanomaterials in a Research Environment

Nanomaterials hold immense potential for numerous applications in energy, health care, and environmental sectors, playing an important role in our daily lives. Their utilization spans from improving energy efficiency to enhancing medical diagnostics, and mitigating environmental pollution, thus presenting a multifaceted approach towards achieving sustainability goals. To ensure the sustainable and safe utilization of nanomaterials, a thorough evaluation of potential hazards and risks is essential throughout their lifecycle—from resource extraction and production to use and disposal. In this review, we focus on understanding and addressing potential environmental and health risks associated with nanomaterial utilization. We advocate for a balanced approach with early hazard identification, safe-by-design principles, and life cycle assessments, while emphasizing safe handling and disposal practices, collaboration, and continuous improvement. Our goal is to ensure responsible nanotechnology development, fostering innovation alongside environmental and community well-being, through a holistic approach integrating science, ethics, and proactive risk assessment.

A robust statistical framework for cyber-vulnerability prioritisation under partial information in threat intelligence

Proactive cyber-risk assessment is gaining momentum due to the wide range of sectors that can benefit from the prevention of cyber-incidents by preserving integrity, confidentiality, and the availability of data. The rising attention to cybersecurity also results from the increasing connectivity of cyber–physical systems, which generates multiple sources of uncertainty about emerging cyber-vulnerabilities.This work introduces a robust statistical framework for quantitative and qualitative reasoning under uncertainty about cyber-vulnerabilities and their prioritisation. Specifically, we take advantage of mid-quantile regression to deal with ordinal risk assessments, and we compare it to current alternatives for cyber-risk ranking and graded responses. For this purpose, we identify a novel accuracy measure suited for rank invariance under partial knowledge of the whole set of existing vulnerabilities.The model is tested on both simulated and real data from selected databases that support the evaluation, exploitation, or response to cyber-vulnerabilities in realistic contexts. Such datasets allow us to compare multiple models and accuracy measures, discussing the implications of partial knowledge about cyber-vulnerabilities on threat intelligence and decision-making in operational scenarios.

Flood risk assessment in arid and semi-arid regions using Multi-criteria approaches and remote sensing in a data-scarce region

Flooding is a natural disaster that poses a threat to both people and the environment, necessitating proactive assessment and mitigation strategies to protect vulnerable communities and ecosystems. These measures are necessary to reduce the risk of flooding and moderate the impact of rainfall. In this study, an Analytical Hierarchy Process (AHP) was used to evaluate flood risk in a data-limited region by integrating Remote Sensing (RS) and Geographic Information System (GIS) methods. The study identified several key flood risk indicators, including topographic wetness index, elevation, slope, land cover, precipitation, distance to river, distance to road, and NDVI. The flood risk map had a score range of 8.71–30.99 %, with higher scores indicating a greater susceptibility to flooding. These scores were then used to classify the flood risk into five categories: very low, low, moderate, high, and very high. The percentages of regions falling into each category were 8.71 %, 23.52 %, 30.99 %, 22.68 %, and 14.09 % respectively. The area under the Curve (AUC) approach was used to validate the flood risk map, which showed a high degree of accuracy (0.86). The results of this study provide valuable insights for monitoring, and forecasting the probability of floods in the Dosso Region.

A non-stationary bivariate extreme value model to estimate real-time pedestrian crash risk by severity at signalized intersections using artificial intelligence-based video analytics

Vehicle-pedestrian crashes are generally severe due to the vulnerability of pedestrians compared to the occupants of vehicles. However, the estimation of pedestrian crash risk by severity has not been given adequate attention in the field of proactive safety assessments applying traffic conflict techniques. This study proposes a novel analytical framework to estimate real-time pedestrian crash risk by severity at the signal cycle level while incorporating the effect of time-varying exogenous variables. Specifically, the study applies a non-stationary bivariate extreme value model to jointly model the post encroachment time and Delta-V for estimating real-time pedestrian crash risk by severity at individual signal cycles. The proposed framework is tested on 144 h of video data collected from three signalized intersections in Queensland, Australia. The developed bivariate extreme value model has been found to reliably predict severe and non-severe pedestrian crash frequencies compared to the historical crash records of severe and non-severe pedestrian crashes at those signalized intersections. Results suggest that the frequency of pedestrian conflicts per signal cycle and average pedestrian speed in a signal cycle are associated with real-time pedestrian crash risks. In addition, pedestrian conflicts per signal cycle and average vehicle speed per cycle were associated with the interaction severity component of the non-stationary bivariate extreme value model. The proposed proactive estimation of pedestrian crash risk by severity levels can help design time-sensitive countermeasures for vulnerable road users.