This research aimed to figure out the applications of HbA1c protein and HbA1 gene as the prognostic biomarkers for assessing the risks of different cancers among male T2D patients in Bangladesh considering their serological and oncoinformatic parameters. Depending on the concentrations of HbA1c (%) of the T2D patients (n=300), their individual FBS (mmol/L); THABF (mmol/L); creatinine (mg/dl); SC (mg/dl); STGs (mg/dl); HDLC (mg/dl); and LDLC (mg/dl) were estimated. The values of the patients were compared with the control (n=60) group as the serological analysis. Besides, HbA1 gene (encoding hBA1c protein) overexpression and promotor methylation responsible for BLCA, BRCA, CHOL, COAD, LUAD, LUSC, PAAD, and PRAD cancers in the male T2D patients were profiled as the oncoinformatic parameters based on the sample types; caner stages; racial footprints; gender; age; nodal metastasis; p53 methylations; pancreatitis; diabetes status; smoking behaviors; and overall/disease-free survivability. Finally, the ‘HbA1 gene strings’ responsible for genetic coexpression; endophytic vesicle regulation; antioxidant regulation; oxygen species metabolic regulation; and gene-mediated response to the reactive oxygen molecules were studied comprehensively. A strong correlation between BMI and FBS was observed in both the patients and the control (P<0.0001). Similarly, the values of FBS, THABF, and creatinine resulted in equal significance (P<0.0001) as compared to the HbA1c concentrations of all the T2D and control individuals. The SC, STGs, HDLC, and LDLC concentrations regulated ardently in both the control (P<0.0001), and patients group (P<0.0001), while HbA1c ranged from 3.8-5.8%, and 5.11-15.8% respectively. HbA1 gene is found downregulating with cancer progressed in most of the oncoinformatic parameters. According to the DA, CS, EI, CE, PC, NC, GF, H, and AT profiles; the HbA1 gene interacts with 8 other genes responsible for creating a protein cluster comprising- AHSP, HBA1, HBA2, HBB, HBD, HBE1, HBG2, RPS12, and RPS19 proteins for cancer formation. To recapitulate, HbA1c protein and HbA1 gene can be used as the prognostic serological and molecular biomarkers respectively for determining the risks of cancers among male chronic T2D patients.

In the context of global changes, Nature-Based Solutions (NBSs) increasingly draw attention as a possible way to reduce disaster risk associated with extreme hydro-meteorological events while providing human well-being and biodiversity benefits at the same time. The PHUSICOS platform is dedicated to gather and analyse relevant NBSs used to reduce disaster risk associated with extreme hydro-meteorological events in mountainous and hilly lands. To design the platform, an in-depth review of 11 existing platforms has been performed. The platform currently references 152 literature NBS cases and is continuously enriched with demonstrator sites through the contribution of NBS community. The platform also proposes a qualitative assessment of the NBSs collected according to 15 criteria related with five ambits: disaster risk reduction, technical and economical feasibility, environment, society and local economy. This paper presents the structure of the platform and a first analysis of its content.

With the gradual development and integration of artificial intelligence into various industries, there is also a great range of integration in the financial industry. Therefore, this article focuses on the trend prediction model and financial risk management problems of deep reinforcement learning (DRL), one of the largest branches of artificial intelligence, in the cryptocurrency market. In addition, in the experimental part of this paper, the artificial intelligence machine learning Long short-term memory network (LSTM) model is used to make effective time series prediction and analysis on the relevant data of the cryptocurrency market, so as to make a large-scale analysis to improve the accuracy of market trend prediction and the effectiveness of risk management. In addition, in this experiment, technology-related indicators, emotional states of financial market customers and other content related to large language models are combined. While optimizing investment strategy by using deep reinforcement learning algorithm, machine learning prediction model is also used to capture the time dependence of financial market. The experimental results also show that the predicted results are consistent with the actual value. Therefore, the model has high practical application value in predicting the time series price trend of cryptocurrency in the financial market and indicates that the integrated DRL model framework can further optimize and manage the price and trading strategy of the financial market. Future research should focus on improving the LSTM model and incorporating more features to improve prediction accuracy and adapt to market changes.

The introduction of the Internet of Things (IoT), i.e. the interconnection of embedded devices over the Internet, has changed the world we live in from the way we measure, make calls, print information and even the way we get energy in our offices or homes. The convenience of IoT products, like CCTV cameras, IP phones, and oscilloscopes, is overwhelming for end-users. In parallel, however, security issues have emerged and it is essential for infrastructure providers to assess the associated security risks. In this paper, we propose a novel method to detect IoT devices and identify the manufacturer, device model, and the firmware version currently running on the device using the page source from the web user interface. We performed automatic scans of the large-scale network at the European Organization for Nuclear Research (CERN) to evaluate our approach. Our tools identified 233 IoT devices that fell into eleven distinct device categories and included 49 device models manufactured by 26 vendors from across the world.

COVID-19 (2019-nCoV) is a pandemic disease with an estimated mortality rate of 3.4% (estimated by the WHO as of March 3, 2020). Until now there is no antiviral drug and vaccine for COVID-19. The current overwhelming situation by COVID-19 patients in hospitals is likely to increase in the next few months. About 15 percent of patients with serious disease in COVID-19 require immediate health services. Rather than waiting for new anti-viral drugs or vaccines that take a few months to years to develop and test, several researchers and public health agencies are attempting to repurpose medicines that are already approved for another similar disease and have proved to be fairly effective. This study aims to identify FDA approved drugs that can be used for drug repurposing and identify biomarkers among high- risk and asymptomatic groups. In this study gene-disease association related to COVID-19 reported mild, severe symptoms and clinical outcomes were determined. The high-risk group was studied related to SARS-CoV-2 viral entry and life cycle by using Disgenet and compared with curated COVID-19 gene data sets from the CTD database. The overlapped gene sets were enriched and the selected genes were constructed for protein-protein interaction networks. Through interactome, key genes were identified for COVID-19 and also for high risk and asymptomatic groups. The key hub genes involved in COVID-19 were VEGFA, TNF, IL-6, CXCL8, IL10, CCL2, IL1B, TLR4, ICAM1, MMP9. The identified key genes were used for drug-gene interaction for drug repurposing. The chloroquine, lenalidomide, pentoxifylline, thalidome, sorafenib, pacitaxel, rapamycin, cortisol, statins were proposed to be probable drug repurposing candidates for the treatment of COVID-19. However, these predicted drug candidates need to be validated through randomized clinical trials. Also, a key gene involved in high risk and the asymptomatic group were identified, which can be used as probable biomarkers for early identification.

In order to achieve its carbon peak and neutrality targets, a high proportion of distributed power sources are connected to the distribution network in China, which greatly increases the risk of distribution network operation. Aiming at the above problems, this paper proposes an active distribution network risk planning model based on multi-source data from carbon capture and power internet of things, and conducts exceeding testing of distribution network based on the stochastic load flow algorithm with semi-invariant and level expansion, calculates the semi-invariant of each order of node state vectors and branch current vectors, and then utilizes the Gram-Charlier level expansion to obtain the exceeding probability density function and probability distribution function of the node voltages and line powers of the distribution network. The probability density function and probability distribution function of the exceeding are obtained using the Gram-Charlier series expansion. Combined with multi-source data, the active distribution network with integrated energy system considering carbon capture is modeled. According to the risk scenario of the distribution network, the nonconvex constraints in the model are simplified by the second-order cone relaxation, and the optimal planning scheme of the distribution network is solved by combining the gurobi solver with the risk index as the first-level objective and the economic benefit as the second-level objective. The simulation results of a coupled network consisting of a 39-node distribution network and an 11-node transportation network verify the effectiveness of the proposed model.

Electricity distribution network operators face several operational constraints in the provision of safe and reliable power given that investments for network area reinforcement must be commensurate with improvements in network reliability. This paper provides an integrated approach for assessing the impact of different operational constraints on distribution network reliability by incorporating component lifetime models, time-varying component failure rates as well as the monetary cost of customer interruptions in an all-inclusive probabilistic methodology that applies a time-sequential Monte Carlo simulation. A test distribution network based on the Roy Billinton test system is modelled to investigate the system performance when overloading limits are exceeded as well as when preventive maintenance is performed. Standard reliability indices measuring the frequency and duration of interruptions, and the energy not supplied are complemented with a novel monetary reliability index. The comprehensive assessment includes not only average indices but also their probability distributions to adequately describe the risk of customer interruptions. Results demonstrate the effectiveness of this holistic approach as the impacts of operational decisions are assessed from both reliability and monetary perspectives. This informs network planning decisions through optimum investments and consideration of customer outage costs.

Accurate and reliable project cost estimates are fundamental to achieve successful municipal capital improvement (CIP) programs. Engineering cost estimates typically represent critical information for key decision makers to authorize and efficiently allocate the necessary funds for construction, budgeting, to generate a request for proposals, contract negotiations, scheduling, etc. for these reasons, cost estimators are using different estimating methods and approaches that allow for required levels of accuracy. As the project’s scope becomes more detailed and the potential risks are identified and/or the project design stage progresses these cost estimates are revised and updated. In this paper, the most common project cost estimation methods and approaches were collected and categorized into two main groups of (1) probabilistic and (2) deterministic methods. Under these groups overall ten different methods were identified and discussed addressing their requirements, advantages, and shortcomings, including the potential risk that can positively or negatively affect the project’s cost outcome. This paper will be a good resource for professionals who are in budget development and/or are seeking to a better understanding of different methods in determining an appropriate base cost margin and produce a meaningful and reliable project cost estimate.

Abstract: Background/Objectives: Schizophrenia (SZ) is a severe psychiatric disorder characterized by a complex interplay of genetic, developmental, and environmental factors that significantly increase the risk of suicidal ideation (SI) and suicide attempts (SAs). This systematic review synthesizes current research on the developmental predictors of SI in individuals with SZ, aiming to delineate the multifactorial etiology of suicide within this population. Methods: A comprehensive search across Medline, PsycINFO, and EMBASE databases identified 23 eligible studies, emphasizing the varied methodological approaches and the global distribution of research efforts. Results: These studies demonstrate a robust association between early life adversities, particularly childhood trauma such as physical neglect, emotional abuse, and sexual abuse, and the increased prevalence of SI and SAs in SZ. This review also highlights the significant genetic factors associated with development of suicidality in SZ, suggesting that polymorphisms in inflammation-related genes and neurodevelopmental abnormalities may influence susceptibility to SI. Notably, family history of psychiatric conditions may exacerbate the risk of SI through both hereditary and environmental mechanisms. Environmental factors, including socioeconomic status and social support, are also implicated, underscoring the role of broader socio-environmental conditions influencing outcomes. Conclusions: This review supports the integration of biopsychosocial models in understanding SI in SZ, advocating for interventions addressing the complex interplay of risk factors and the need for longitudinal studies to elucidate the dynamic interactions between risk factors over time. This comprehensive understanding is crucial for developing targeted preventative strategies and enhancing the clinical management of SZ, aiming to reduce suicidality in this vulnerable population.

In today's globalized economy, supply chain disruptions present significant challenges, impacting businesses' operational continuity and efficiency. This study delves into the ways businesses navigate these disruptions, with a particular emphasis on qualitative insights into risk management practices. The complexity and interconnectivity inherent in modern supply chains make them vulnerable to a broad spectrum of disruptions, ranging from natural disasters and geopolitical conflicts to technological failures and pandemics. Effective supply chain risk management requires a structured approach to identifying potential risks, evaluating their likelihood and potential impact, and formulating robust mitigation strategies. Employing a qualitative research methodology, this study gathers in-depth insights from semi-structured interviews with supply chain managers, industry experts, and executives. The findings underscore the necessity of proactive risk identification and comprehensive assessment processes. Advanced technologies, including artificial intelligence (AI), the Internet of Things (IoT), and blockchain, are highlighted as crucial tools for enhancing visibility and responsiveness within supply chains. Strategies such as diversifying suppliers and maintaining safety stock emerge as vital components of risk mitigation, ensuring supply continuity in the face of disruptions. Strong relationships with suppliers are pivotal, facilitating better information sharing and collaborative problem-solving. Leadership commitment to risk management and fostering a culture of resilience within organizations is also critical. Training programs and simulation exercises are identified as effective means of preparing employees to handle disruptions. Furthermore, adherence to regulatory compliance and a focus on sustainability are integral to maintaining long-term stability and reducing the risk of future disruptions.

This study explores the multifaceted role of culture in supply chain collaboration, focusing on how cultural differences shape communication, trust-building, negotiation, conflict resolution, risk management, and ethical standards. Utilizing a qualitative methodology, semi-structured interviews were conducted with 25 supply chain professionals from diverse cultural backgrounds and industries. The findings reveal that high-context cultures favor indirect communication and nuanced information exchange, which can lead to misunderstandings with partners from low-context cultures who prefer direct and explicit communication. Trust-building practices vary significantly, with high uncertainty avoidance cultures emphasizing formal agreements and procedural rigor, while low uncertainty avoidance cultures prioritize personal relationships and demonstrated reliability. Negotiation strategies also diverge, reflecting the underlying values of collectivism versus individualism, impacting the tactics and outcomes of supply chain negotiations. Conflict resolution approaches differ, with high power distance cultures favoring hierarchical and mediated solutions, and low power distance cultures preferring direct and egalitarian methods. The study highlights the need for adaptability to cultural changes and the development of cultural intelligence as essential competencies for managing cross-cultural supply chains. Additionally, cultural differences in risk management approaches and governance mechanisms affect the coordination and resilience of supply chains, while varying ethical standards influenced by cultural norms necessitate culturally sensitive strategies for promoting corporate social responsibility. The insights gained from this research underscore the importance of understanding and leveraging cultural differences to build stronger, more productive supply chain relationships, contributing to the broader literature on culture and supply chain management and offering practical implications for enhancing global supply chain collaboration.

Early-life adversity can profoundly impact individual development, yet some demonstrate resilience. Longitudinal studies tracking individuals over extended periods have aided our understanding of resilience and growth following adverse childhood experiences. This paper reviews insights from influential studies like the Kauai Longitudinal Study, the Adverse Childhood Experiences (ACE) Study, and the Dunedin Study. It explores key findings on risk and protective factors, adaptation trajectories, and long-term outcomes associated with resilience. Theoretical frameworks and methodological considerations are discussed. The paper examines how this research informs interventions, policies, and support systems for fostering resilience. It highlights the need for diverse samples, integrating biological and environmental factors, and investigating intergenerational impacts. By synthesizing longitudinal research, this paper elucidates complex pathways to resilience and positive development despite early adversity, offering insights for research and supporting vulnerable populations.

Smoker’s paradox usually refers to the common observation of a favourable outcome of smoker patients in acute myocardial infarction. The interpretation of this phenomenon is still controversial and not fully explained. We aimed at assessing whether smoking could be associated with mortality in a large cohort of prospectively enrolled patients with ST segment elevation myocardial infarction (STEMI) referred to primary percutaneous coronary intervention (pPCI). From April 2006 to December 2018 a population of 2456 STEMI patients treated with primary PCI were prospectively enrolled in the MATRIX registry. Ischemic time, clinical, demographics, angiographic data and 1-year follow-up were collected. Among 2546 patients admitted with STEMI 1007 (41%) were current smokers. Smokers were 10 years younger and had lower crude in-hospital and 1-year mortality (1.5% vs 6%, p&lt;0.0001 and 5% vs 11%, p&lt;0.0001), shorter ischemic time (203 [147-299] vs 220 [154-334] minutes, p=0.002) and shorter decision time (60 [30-135] vs 70 [36-170] minutes, p=0.0063). After propensity-matching, age, cardiogenic shock and low TIMI score were associated with in-hospital mortality, while smoking habit was still associated with reduced mortality. Smoking was also associated with reduced death rate at 1-year follow-up (HR 0.54, 95% CI [0.37 - 0.78]; p&lt;0.001). Our data show a protective link between smoking status and mortality in patients with STEMI, the so called “smoker’s paradox”. This could be explained not only by the shorter ischemic time and younger age of the smoking population but also by a specific pathogenetic effect of smoking underlying the onset of STEMI and response to therapies.

The present work provides continuity with studies where currently the industrial market is characterized by a highly variable demand in terms of quantities and flexibility of manufacturing or mass customization, which translates into a more demanding production context in terms of the continuous changes required to the production systems, the effect of which results in an increase in the fatigue subjected to the machines that make up the production systems. On the other hand, current production systems tend to use highly communicative and sensorized cyber-physical systems; these characteristics can be used to integrate them into decision-assisted systems in order to improve the availability of the industrial plant. The assisted system developed focuses on collecting and taking advantage of historical knowledge of industrial plant failures and breakdowns. By ideally integrating the Reliability Centered Maintenance (RCM) methodology and Case-Based Reasoning (CBR) algorithms implemented in a Java application, it is possible to design maintenance plans adjusted to a real and changing operational context of any industrial plant. As a result, faster and more accurate decisions are made, as they are based on data. This article focuses on improving certain aspects of the developed assisted system by adding more value to it by incorporating Fuzzy Logic (FL) techniques. The aim is to improve the way of entering information about risk factors and their relative importance, by incorporating natural language, instead of a numerical score, resulting in increased precision in the calculation of the Risk Priority Number (RPN) of the new cases incorporated into the assisted system.

Having as objective to reach a circular economy, it is important to maximize the Physical Asset’s Life Cycle. The evaluation of Physical Assets Life Cycle may have several approaches which may provide different results. These differences may not be very significant, but must be taken into consideration, because they have consequences in the manager decision. This permits to have a wider time interval to decide when to withdrawal the Physical Asset or to renewal it, and or if this ought to continue functioning because the profits are higher than the expenses, what allows to diminish waste and increase sustainability. These are some aspects that are discussed in this paper, which presents several models to evaluate the Physical Assets Life Cycle, considering the market value, devaluations methods and a more generalized way of Fisher’s Equation, which can include the Risk tax, among others. The results are discussed supported in data for simulation, which are used for each Econometric Model aiming to evaluate the differences among them. In all Models they are considered not only the expenses, namely of Investment and Functioning, but also the Profits, which permit to evaluate the Physical Asset Life Cycle in a holistic way. The models are very versatile, allowing to evaluate quantitatively the changing in the maintenance policies, the energy prices variations, the risk evaluation, the variation of profits according to the real market, and so on. The results demonstrated the robustness of the approach described and that maximize the Physical Assets Life Cycle allowing to minimize the consumption of world resources and, by consequence, it contributes for a more sustainable world.

Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of death worldwide and the risk of a major cardiovascular event is highest among those with established disease. Ongoing management of these patients relies on the accurate assessment of their response to any prescribed therapy, and their residual risk, in order to optimize treatment. Recent international guidelines and position statements concur that the plasma concentration of apolipoprotein B (apoB) is the most accurate measure of lipoprotein associated ASCVD risk. This is especially true for the growing number of individuals with diabetes, obesity or the metabolic syndrome, and those on statin therapy. Most guidelines, however, continue to promote LDL-C as the primary risk marker due to uncertainty as to whether the greater accuracy of apoB is sufficient to warrant a paradigm shift. Recommendations regarding apoB measurement vary, and the information provided on how to interpret apoB results is sometimes insufficient, particularly for the non-lipid specialist. Misinformation regarding the reliability of the assays is also frequently repeated despite its equivalent or better standardization than many other diagnostic assays. Thus, demand for apoB testing is relatively low, which means there is little incentive to increase its availability or reduce its cost. In this review, we examine the results of recent clinical outcomes studies and meta-analyses on the relative values of apoB, LDL-C and non-HDL-C as markers of ASCVD risk. Although there is seemingly minimal difference among these markers when only population-based metrics are considered, it is evident from our analysis that, from a personalized or precision medicine standpoint, a great many individuals would benefit, at a negligible total cost, if apoB measurement were better integrated into the diagnosis and treatment of ASCVD.

To quantitatively estimate the risk of power system operation under extreme rainfall, a multi-scenario stochastic risk assessment method is proposed. First, a scenario generation scheme considering waterlogged faults of power facilities is constructed based on the storm water management model (SWMM) and the extreme learning machine method. These scenarios will be merged to several typical scenario sets for further processing. The outage of power facilities will induce power flow transfer which may consequently lead to transmission lines’ thermal limit violation. Semi-invariant and Gram-Charlier level expansion methods are adopted to analytically depict the probability density function and cumulative probability function of each line’s power flow. The optimal solution is performed by a particle swarm algorithm to obtain proper load curtailment at each bus, and consequently the violation probability of line thermal violations can be controlled within an allowable range. The volume of load curtailment as well as their importance are considered to quantitatively access the risk of power supply security under extreme precipitation scenarios. The effectiveness of the proposed method is verified in case studies based on the IEEE 24-bus system.

Historically, Physalis physalis massive stranding events have been infrequent and poorly documented. However, their occurrence can have significant impacts on human health and the stability of coastal ecosystems. In this study we analyze the largest P. physalis stranding event historically recorded affected Cuba’s northwestern coast in December 2022. We counted all colonies during the massive event along ~ 3 km coast, within a 5 m stripe. Density, dimorphic form (left/right-handed), and colony size were quantified using 0.25 m2 quadrat placed every 50 m, 10 m from shoreline. Eighty-five people were stung, with 38 having strong allergic reactions, resulting in a health risk. Over ten thousand colonies were recorded, with the highest mean colony density (29.3 per m2) ever reported. The massive stranding coincided with the lowest Arctic Oscillation index (-2.59) in the past 11 years during December, likely linked to climate change. This led to the emergence of northeasterly winds reaching speeds of up to 24 km/h. Wind direction and speed, coupled with the dominance of left-handed colonies (71.4%), suggest the Sargasso Sea as the possible source of the bloom. The high prevalence of juvenile P. physalis colonies (68 %) likely aligns with the autumn breeding season in the northern hemisphere. The potential causes of P. physalis blooms are still poorly understood. Systematic monitoring of the distribution and abundance of this species should be a research priority considering the potential risk to human health and that the blooms could become more frequent and affect other areas in the Atlantic, given climate change and increasing eutrophication of the oceans.

Identifying productive, profitable and less risky cropping systems is important for sustaining farm-based livelihoods in the context of climatic uncertainties and market volatility in many developing nations. Reductionist field crop research identifies the best-bet solutions based on treatment replicates at a single point in time, which may not account for price instability under climatic uncertainties and volatile markets. Keeping this in mind, we estimated productivity, profitability and weather-related risk from eleven different rice-based cropping systems (eight existing and three potential systems) in the coastal region of West Bengal, India. Information on the crop management practices, yield and prices of the component crops of these eleven cropping systems, under ’best,’ ’normal’ and ‘worst’ situations (scenario), were collected through a ques-tionnaire survey on50 farms of Gosaba Block, West Bengal, India. Irrespective of the scenarios, the rice-lathyrus systems, followed by rice-onion and rice-lentil systems recorded the lowest rice-equivalent yields and system yields. However, the highest rice-equivalent yields and system yields were recorded for rice-chilli systems, followed by rice-tomato and rice-potato-green gram systems. Per hectare total paid-out cost (TPC) of rice-tomato systems was higher, followed by rice-chilli, rice-potato-green gram and rice-potato systems. However, irrespective of seasonal conditions (best, normal and worst), rice-chilli systems gave a higher net return followed by rice-tomato and rice-potato-green gram systems. The rice-fallow system recorded the lowest value for both parameters. Under the worst seasonal conditions, the rice-onion system gave a negative net return. Under all the scenarios, the highest B:C ratio was observed for rice-chilli, rice-tomato, rice-potato-green gram and rice-potato systems. The cumulative probability distribution of the rice-tomato system showed first-degree stochastic dominance over other systems and the rice-chilli system showed second-degree stochastic dominance over the rest of the systems. Only the rice-onion system had a small chance (< 1%) of a negative net return, while the rest of the cropping systems were highly likely to get a positive net return. Taking productivity, economics, and risk assessment of different rice-based systems into account, rice-vegetable systems, especially rice-tomato and rice-chilli among the existing systems and rice-potato-green gram system among the potential systems, can be recommended for sustainable intensification in these coastal saline tracts of the region. We also discuss additional socio-economic factors explored by in-depth in-terviews with the farmers, which might influence the adoption and upscaling of these cropping systems in the region.

We aimed to compare prognostic factors for overall survival (OS) following percutaneous radiofrequency ablation (PRFA) with or without chemolipiodolization (CL) for early-stage hepatocellular carcinoma (HCC) using propensity score-matched analysis. We enrolled 221 patients with early-stage HCC who received PRFA with (n = 76) or without (n = 145) CL in Saga Central Hospital between April 2004 and December 2020. No significant difference was observed in OS between PRFA with and without CL cohorts (median survival time [MST]: 5.4 vs. 4.5 years; p = 0.0806). To reduce confounding effects, 108 patients were selected using propensity score-matched analysis (n = 54 for each treatment). No significant difference was observed in OS between the cohorts (MST: 3.6 vs. 4.0 years; p = 0.5474). After stratification according to tumor size, no significant difference was observed in OS for patients with tumor size ≥20 mm between PRFA with and without CL cohorts (MST: 3.4 vs. 3.5 years; p = 0.8236). PRFA with CL was not a significant prognostic factor in both univariate and multivariate analyses (p = 0.5477 and 0.9600, respectively). Our findings suggest that PRFA with CL does not demonstrate longer prognostic effects than PRFA without CL in early-stage HCC, regardless of tumor size.

(1) Background: Mouse-mammary tumor virus (MMTV) might play a role in the etiology of some breast cancers in humans. The purpose of our study was to identify MMTV DNA sequences in breast tissue samples from breast cancer patients operated in our regional center from Romania. (2) Methods: We have selected 75 patients with non-metastatic breast cancer treated with curative intent and searched with PCR the MMTV-like DNA sequence in the breast cancer tissue and normal breast tissue obtained from the same patients. (3) Results: None of the examined samples was positive for MMTV-like target sequences on PCR. (4) Conclusions: We could not prove that MMTV plays a role in the etiology of breast cancer in our patient group. This finding is similar to findings of other geographically related research groups and might be due to the fact that only the Mus musculus domesticus mouse species was proven to carry infectious MMTV, but not the Mus musculus musculus species, which is specific to South-Eastern Europe and some parts of Asia.

The novel coronavirus SARS-CoV-2 likely emerged from a wildlife source with transmission to humans followed by rapid geographic spread throughout the globe and severe impacts on both human health and the global economy. Since the onset of the pandemic, there have been many instances of human-to-animal transmission involving companion, farmed and zoo animals, and limited evidence for spread into free-living wildlife. The establishment of reservoirs of infection in wild animals would create significant challenges to infection control in humans and could pose a threat to the welfare and conservation status of wildlife. We discuss the potential for exposure, onward transmission and persistence of SARS-CoV-2 in an initial selection of wild mammals (bats, canids, felids, mustelids, great apes, rodents and cervids). Dynamic risk assessment and targeted surveillance are important tools for the early detection of infection in wildlife, and here we describe a framework for collating and synthesising emerging information to inform targeted surveillance for SARS-CoV-2 in wildlife. Surveillance efforts should be integrated with information from public and veterinary health initiatives to provide insights into the potential role of wild mammals in the epidemiology of SARS-CoV-2.

Background and objectives: Induction of labor (IOL) is an event that occurs in up to one-quarter of pregnancies; less is known about the outcomes and safety of IOL in obese pregnant woman; no data is available on misoprostol vaginal insert (MVI) IOL in high-risk pregnancy obese women. Objectives: (1) to evaluate the rate of successful IOL with 200 μg MVI in obese (Body Mass Index - BMI over 30 kg/m2) high-risk pregnant women: late-term pregnancy, hypertension or diabetes, compared to obese non-high-risk ones; (2) to evaluate the safety profile of MVI in high-risk pregnancy obese patients. Study design: We conducted a cross-sectional study in "Filantropia" Clinical Hospital, Bucharest, Romania, from June 2017 to September 2019 (28 months). From a total of 11,096 registered live births, IOL was performed in 206 obese patients; 74 obese high-risk pregnant patients matched the inclusion criteria; of these, 33.8% pregnancies (n=25) were late-term (41 – 41+6 weeks), 43.2% (n=32) had associated pathologies (hypertension and diabetes); labor induction was guided using a standardized protocol. We evaluated the maternal and gestational age, parity, fetal tachysystole, hyper-stimulation, initial cervical status, time from induction to delivery, drug side effects, mode of delivery, and neonatal outcomes. Results: (a) The overall successful labor induction rate, evaluated by the vaginal delivery rate, was 71.6% (n=53), spontaneously or instrumentally assisted; 28.4% (n=21) births were unsuccessful MVI IOL, converted into caesareans. (b) No significant differences were found regarding the maternal outcomes; in terms of perinatal outcomes of safety, four cases of high-risk pregnancies vaginally delivered were associated with neonatal intensive care unit (NICU) admissions and a one-minute Apgar score under seven (5.4%). Most cases with adverse effects of misoprostol have been managed conservatively, except for three emergency C-section cases. Conclusions: Misoprostol vaginal insert is a safe choice in IOL in obese high-risk pregnancies with good maternal and perinatal outcomes.

Total Hip Arthroplasty is one of the most successful surgery. However, due to the worldwide growing population life expectancy and the related incidence of age-dependent bone diseases, a growing number of cases of intra-operative fractures lead to revision surgery with high rates of morbidity and mortality. Surgeons choose the type of the implant, either cemented or cementless prosthesis, on the basis of the age, the quality of the bone and the general medical conditions of the patients. Generally, no quantitative measures are available to assess the intra-operative fracture risk. Consequently, the decision-making process is mainly based on medical operators’ expertise and qualitative information obtained by imaging. Motivated by this scenario, we here propose a mechanical-supported strategy to assist surgeons in their decisions, by giving intelligible maps of the risk fracture which take into account the interplay between actual strength distribution inside the bone tissue and its response to the forces exerted by the implant. To this end, we produce charts and patient-specific synthetic “traffic-light” indicators of fracture risk, by making use of ad hoc analytical solutions to predict the stress levels in the bone by means of CT-based mechanical and geometrical parameters of the patient. We felt that, if implemented in a friendly software or proposed as an app, the strategy could constitute a practical tool to help the medical decision-making process, in particular with respect to the choice of adopting cemented or cementless implant

Throughout the world, disabilities people have worse health prospects, lower education levels, lower economic participation, and higher poverty rate in comparative terms to people without disabilities. For disabilities people achieve better, more long-lasting prospects, we must empower these people and remove barriers that restrict them from participating in the community have access to quality education, to find decent work and have their voices heard. In statistical terms, a very useful alternative that can provide support and monitoring of public policies in this area is proposing to be used continuously. A risk index called risk index disabled person who is to assess which factors are associated to this risk, as well as the intensity and direction of each of these factors, yielding a final score that can be sorted or classified according to the probability of people acquire a certain disability. In the Brazilian case, we propose the use of techniques such as binary and ordinal logistic regression to select the most significant factors using criteria such as AIC, BIC and DIC. Calculate the risk probability for different disabilities (see, hear, move and intellectual) and number of disabilities to the dataset Sample of respondents for Full Questionnaire at IBGE 2010 Census. In this work, by using stereotype ordinal logistic model with ordinal response, it was possible to improve the fit quality, to be compared with binary response logistic model. By using ordinal response merged the disability risk for different severity degree and amount of deficiencies. Mains conclusions were: i)the model required a smaller number of explanatory variables was intellectual or mental and greater number was disabilities; ii) the most sensitive adjust was using stereotype ordinal logistic; iii) different disabilities aren´t homogenous as the different predictor variables, and finally; iv) higher incidence of risks were noted visual disability, living in the northeast, female, age 80, yellow race, instruction level until incomplete fundamental, works production form their own consumption and high number of children.

Persistent cervical infection with high-risk Human papillomaviruses (hrHPVs) is a necessary, but not sufficient, condition for the development of cervical cancer. Therefore, there are other co-factors facilitating the hrHPV carcinogenic process, one of which is smoking. In order to assess the effect of smoking on high-risk (hr) HPV DNA positivity and on the expression of HPV E7 oncoprotein, as a surrogate of persistent hrHPV infection, we used data from women recruited for the PIPAVIR project, which examined the role of E7 protein detection in cervical cancer screening. Women were tested for hrHPV DNA, using Multiplex Genotyping and E7 protein, using a novel sandwich ELISA method, and gave information on their smoking habits. Among 1473 women, hrHPV prevalence was 19.1%. The odds ratio (OR) for hrHPV positivity of smokers compared to non-smokers was 1.785 (95%CI: 1.365-2.332, p<0.001). The ORs for E7 positivity, concerning hrHPV positive women, ranged from 0.720 to 1.360 depending on the E7 detection assay used, but this was not statistically significant. Smoking increases the probability of hrHPV infection, and smoking intensity is positively associated to this increase. Smoking is not related to an increased probability of E7 protein positivity for hrHPV positive women.

A reliability-based criterion to estimate strength amplification factors for buildings with asymmetric yielding located within a seismic region presenting different soil conditions is proposed and applied. The approach involves the calculation of the mean annual rate of exceedance of structural demands of systems with different levels of asymmetric yielding. Two simplified mathematical expressions are developed considering different soil conditions of the valley of Mexico. The mathematical expressions depend on the ductility of the structural systems, their level of asymmetric yielding, their fundamental vibration period and the dominant period of the soil. In addition, the proposed expressions are compared with that recommended by the current Mexico City Building Code (MCBC). Since the expressions are developed with the help of simplified structural systems, the validity of such expressions is corroborated by comparing the expected ductility demand of multi-degree of freedom (MDOF) structural systems with respect to that of their equivalent simplified systems. Both structural representations are associated with a given annual rate of exceedance value of an engineering demand parameter. The expressions proposed in this study will be incorporated in the new version of the MCBC.

The paper presents the results of the theoretical and practical research on developing the infrastructure for assessment of overall risk (explosion / occupational / terrorist attack) associated with unwanted events such as major accidents that can occur at explosive storehouses for civilian use. The scientific research outlined in this article was carried out within the Nucleu Project PN 16 43 02 15 - “Research on increasing safety levels at technical facilities for storage of explosives for civil use”.

Georgia is ranked fifth highest among states for rates of HIV diagnosis. About 4% of persons living with HIV infection in the United States reside in Georgia, and almost 19% of these people do not know their HIV status. The present study examined the trends and associated factors of HIV testing among adults in Georgia between 2010 and 2014 by analyzing data of the Behavioral Risk Factor Surveillance System (BRFSS). A total of 30,791 persons aged ≥18 years were identified who responded to the question “Have you ever been tested for HIV?” Overall, there were 11,543 respondents who had been tested for HIV, with a decrease in percentage from 49.4% in 2010 to 43.7% in 2014 (p<0.001). Factors associated with HIV testing were being black (p<0.001), being younger than 55 years (p<0.001), single (p=0.02), attaining education level above high school (P<0.001), engaging in HIV high-risk behaviors (p<0.001), and not having healthcare coverage (p=0.03). Overall in Georgia, there has been a decline in the temporal trend of HIV testing, and more than half of adults have never been tested for HIV. For reducing HIV transmission in Georgia, enhancing access and utilization of HIV testing should be a public health priority.

: Chemical accidents can occur anywhere. The need for chemical management in Korea was realized following the 2012 Gumi hydrofluoric acid accident in 2012. The Chemicals Control Act was enacted in 2015. This system evaluates the risks (high, medium, low) and consequent safety management at all plants that handle hazardous chemical substances. However, the system was criticized as excessive when most plants were designated high-risk without considering their size. Thus, laboratories and hospitals handling very small quantities were subject to regulation. Accordingly, in 2021 Korea revised the system to include off-site consequence analyses and a Korean-style risk analysis. Plants handling very small quantities, such as laboratories and hospitals, were exempt from regulation. In this study, plating and paint manufacturing companies, which were classified as high-risk in the previous system, even though they were medium-size business plants, were re-evaluated as low-risk plants. In the Korean-style risk analysis, it is possible to see at a glance what is lacking in the plants, such as cooperation between local residents and local governments and the construction of safety facilities according to the type of accident scenario. The revised system is a reasonable regulation for medium business plants.

The aim of this cross-country research is to examine how the profit and loss sharing mudarabah investment deposits are classified and disclosed in the financial statement of Islamic banks. The cross-country study examined the financial statements of fifty-one fully-fledged Islamic banks. The results of the data analysis show that Islamic banks disclose the mudarabah investment account in different ways. The absence of standardized disclosure for mudarabah investment deposit confuses the stakeholders. This research suggests to the regulators to fully or partially adopt the AAOIFI standards specifically for Islamic financial institutions.

The purpose of this study is to explore the effect of Environment, Social, and Governance (ESG) scores on Return on Assets (ROA), Risk-Adjusted Return on Capital (RAROC), and Tobin's Q on firm performance. This study used 37 non-financial companies listed on the IDX between 2018 and 2022 in Indonesia companies. Linear and nonlinear panel data regression methods were used on the ESG score and its pillars, resulting in eight different models. The study found a U-shaped impact of ESG scores and social and environmental pillars on ROA. There is a positive linear relationship between ESG scores and the environmental and governance pillars with RAROC, while the social pillar shows an inverted U-shaped effect. However, ESG and its environmental and social pillars have a negative linear relationship with Tobin's Q. The findings suggest the need to manage ESG initiatives strategically, aligning them with financial objectives and awareness of how ESG factors relate to profitability.

Conflicts are frequent within the complex professional environment of the construction industry. If claims cannot be overcome amicably, they result in disputes that lead to litigation. Identification of the causes of these claims and their impact on the duration, cost, and quality of the final project is expected to facilitate the prevention of unsuccessful performance of construction contracts. The novelty of this study is that after codifying the most common causes of construction contract claims derived from the extant literature, they are further investigated in terms of their probability of occurrence and the perceived impact they have on the project completion time, its total cost, and quality. Based on calculated relative importance indices from expert opinion, this paper proposes probability and severity of impact values for 39 common causes of claims in the construction industry. These can be applied to calculate their risk values for stakeholders in public construction contracts to plan mitigation measures of contractual claims. The findings show that the top five riskiest causes of contractual claims in the Greek construction industry are changes in quantities, work, or scope, design quality deficiencies or errors, payment delays, delays in work progress, and the financial failure of the contractor.

This study comprehensively explores Serbia's Disaster (Risk) Management System, aiming to critically evaluate its inherent strengths and weaknesses. Using descriptive-analytical methods and qualitative interpretation, SWOT analysis was applied to collect data from scientific papers, books, and institutional reports. This study delves deeply into the nuances of Serbia's Disaster Management Framework, revealing a nuanced landscape of strengths, weaknesses, and strategic improvement opportunities. Identified strengths underscore a robust foundation characterized by proficient professionals, state-of-the-art technology, and cohesive teamwork, all pivotal for effective emergency preparedness and response. Conversely, weaknesses underscore pressing imperatives for enhancements in regulatory enforcement, resource allocation, and infrastructure upgrades, presently hampering the framework's efficacy and response readiness. This research contributes to the ongoing discourse on disaster risk management and serves as a catalyst for further scholarly inquiry and policy formulation. By mapping out the structure of Serbia’s Disaster (Risk) Management Framework and integrating diverse data sources, the study enriches theoretical models and lays the groundwork for practical policy interventions. Its findings, including precise recommendations for policy reform and strategic improvements, provide valuable insights for policymakers, emergency management experts, and stakeholders seeking to enhance disaster preparedness and response capabilities on both national and global scales.

Patient safety is a top priority for all healthcare systems globally. Promoting the adoption of policies for reporting and learning from errors is an important strategy for improving care safety. Therefore, the aim of our study was to detect how much patient safety culture influences the reporting of adverse events and the use of the incident reporting tool. The study protocol was developed according to PRISMA guidelines. Articles were searched electronically in PubMed/MEDLINE, the COCHRANE library, and Google Scholar by two independent reviewers, and those that met the eligibility criteria were included. Synthesis of qualitative data from included studies was performed by graphical descriptive statistical analysis. The results of the systematic review showed that health care organizations' increasing focus on staff development of a safety culture has led to a significant increase in incident reporting rates over the years. Moreover, in situations where safety culture is placed at the top of the nations, there is a higher frequency of incident reporting. An efficient incident reporting system should be an essential foundation for healthcare organizations, as it allows them to collect experiences and data and provide feedback to healthcare providers and staff involved in care.

From 2020 to 2023 many people around the world were forced to wear masks for large proportions of the day based on mandates and laws. We aimed to study the potential of face masks for the content and release of inanimate toxins. A scoping review of 1003 studies was performed (database search in PubMed/MEDLINE, qualitative and quantitative evaluation). Twenty-four studies were included (experimental time 17 min to 15 days) evaluating content and/or release in 631 masks (273 surgical, 228 textile and 130 N95 masks). Most studies (63%) showed alarming results with high micro- and nanoplastics (MPs and NPs) release and exceedances could also be evidenced for volatile organic compounds (VOCs), xylene, acrolein, per-/polyfluoroalkyl substances (PFAS), phthalates (including di(2-ethylhexyl)-phthalate, DEHP) and for Pb, Cd, Co, Cu, Sb and TiO₂. Of course, masks filter bacteria, dirt and plastic particles and fibers from the air we breathe and have specific indications, but according to our data they also carry risks. Depending on the application, a risk-benefit analysis is necessary. However, mask mandates during the SARS-CoV-2 pandemic have been generating an additional source of potentially harmful exposition to toxins at population level with almost zero distance to the airways.

: Healthcare workers are affected by mental health issues, burnout and turnover, and this burden is even greater during epidemics and pandemics, such as COVID-19. The purpose of this research is to provide an overview of the measures introduced or supported in the institutions of Quebec’s health and social services network during the COVID-19 pandemic with the aim of protecting healthcare workers’ mental health. An online questionnaire survey was administered in 2021 among human resources department personnel in health and social services network institutions involved in workplace mental health in Quebec. A total of 223 key informants representing 31 of the 34 public health and social services institutions in the province of Quebec in Canada responded to the questionnaire. Measures that focus on the needs of staff, involve all levels of authority and the ones that provide flexibility, support and recognition at work were more successful, according to the advisors surveyed. Future research into whether the same measures are considered effective or ineffective outside of a pandemic context is needed.

Recent wastewater testing suggests the poliovirus is reemerging, raising questions about the efficacy of the current inactivated polio vaccine and mass vaccination to eradicate poliomyelitis. The present study reassessed reported outcomes from the placebo-control study of the 1954 Salk inactivated poliomyelitis vaccine field trial, which studied a population of 1,829,916 U.S. school children from the first three grades. The placebo-control study of the trial reported that the polio vaccine was 80% to 90% effective in reducing cases of laboratory confirmed paralytic poliomyelitis, 60% to 70% effective against type 1 of the virus, and greater than 90% effective against types 2 and 3 of the poliovirus. However, these outcomes are reported as relative risk reductions, and the absolute risk reductions of the 1954 polio vaccine field trial were never reported to the public. The present paper’s analysis reveals to the public for the first time that the inactivated poliomyelitis vaccine's absolute risk reduction of laboratory confirmed paralytic poliomyelitis in the placebo-control study is 0.01% to 0.02%, an extraordinarily low clinical effect that impugns the Salk polio vaccine’s reported effectiveness. Furthermore, absolute risk reductions for the three poliovirus types are 0.01%, 0.00%, and 0.01%, respectively. Outcome reporting bias in the 1954 inactivated poliomyelitis vaccine field trial casts doubt on eradication of the poliovirus through mass vaccination.

Biochar (BC) is a carbonaceous material obtained by pyrolysis at 200−1000 °C in the limited presence of O2 of different vegetable and animal biomass feedstocks. BC has demonstrated great potential, mainly in environmental applications, due to its high sorption ability and persistent free radicals (PFRs) content. These characteristics enable BCs to carry out the direct and PFRs-mediated removal/degradation of environmental organic and inorganic contaminants. The types of PFRs possibly present in BC depend mainly on the pyrolysis temperature and the kind of pristine biomass. Since they also can cause ecological and human damage, a systematic evaluation of the environmental behavior, risks, or management techniques of BC-derived PFRs is urgent. PFRs generally could consist of a mixture of carbon- and oxygen-centered radicals, and of oxygenated carbon-centered radicals, depending on the pyrolytic conditions. Here, to promote a more productive and beneficial use of BC and related PFRs and stimulate further studies to make them environmentally safer and less hazardous to humans, we have first reviewed the most common methods used to produce BC, its main environmental applications, the primary mechanisms by which BC remove xenobiotics, as well as the reported mechanisms for PFRs formation in BCs. Secondly, we have discussed the PFRs environmental migration and transformation; we have reported the main PFRs-mediated applications of BCs to degrade inorganic and organic pollutants, the correlated environmental potential risks, and the possible strategies to limit them.

Successful implementation of antibiotic stewardship programs (ASP) requires a well-structured approach involving all stakeholders. Despite embracing key responsibilities, nurses’ role remains poorly defined, preventing consistent engagement. We conducted a scoping survey to assess knowledge, attitude and perception of nurses towards nurse-led initial sepsis risk evaluation using the sepsis risk calculator (SRC) of newborns admitted to the mother-baby unit. Single-center, cross-sectional study. Study link was sent to all full-time nurses in mother-baby unit. Survey centered around knowledge of unit’s ASP and attitude and perception towards nurse-led initial sepsis risk evaluation. 89% response rate. 100% agreed that SRC reduced antibiotic use and 66% felt nurse-led sepsis risk evaluation will enhance nurse involvement, but this was offset by extra burden of work (66%) and low confidence in differentiating stable from clinically unstable infants (46%). Other facilitating factors included greater nurse/patient ratio (100%), targeted education (89%) and incorporation of the SRC into EMR (78%). Only 11% were willing to serve as champions for it. There was no significant correlation to age or experience however, greater number of fresh grads were interested in championing this effort. Our study identifies a need for strong foundation of knowledge and greater nurse/patient ratio as two main factors for improving nurse-led use of the SRC. Multi-site studies scoping barriers to nursing involvement for successful implementation of ASPs are necessary.

Very little is known about laboratory confirmed blood stream infections (LCBIs) in neonatal intensive care units (NICUs) in resource-limited settings. The aim of this cohort study was to determine the incidence, risk factors, and causative agents of LCBIs in a level-2 NICU in India. The diagnosis of LCBIs was established using the Centre for Disease Control, USA criteria. A predesigned questionnaire containing risk factors associated with LCBIs was filled-in. A total of 150 neonates (43% preterm) were included in the study. The overall incidence of LCBIs was 31%. The independent risk factors for LCBIs were: preterm neonates (relative risk (RR) 2.23), duration of NICU stay more than 14 days (RR 1.75), chorioamnionitis in the mother (RR 3.18), premature rupture of membrane in mothers (RR 2.32), neonate born through meconium-stained amniotic fluid (RR 2.32), malpresentation (RR 3.05), endotracheal intubation (RR 3.41), umbilical catheterization (RR 4.18), and ventilator-associated pneumonia (RR 3.17). The initiation of minimal enteral nutrition was protective from LCBIs (RR 0.22). The predominant causative organisms were gram-negative pathogens (58%). The results of the present study can be used to design antibiotic interventions to reduce LCBIs in resource-limited settings.

The sensitivity of exercise ECG is marginally sufficient for detection of mild reduction of coronary blood flow in patients with early coronary atherosclerosis. Here we describe the application of new technique of ECG registration/analysis – ultrahigh resolution ECG (UHR ECG) – for early detection of myocardial ischemia (MIS). The utility of UHR ECG vs. conventional ECG (C ECG) was tested in anesthetized rats and pigs. Transmural MIS was induced in rats by the ligation of the left coronary artery (CA). In pigs, subendocardial ischemia of variable extent was produced by stepwise inflation of balloon within the right CA causing 25-100% reduction of its lumen. In rats, a reduction in power spectral density (PSD) in high-frequency (HF) channel of UHR ECG was registered at 60 s after ischemia (power 0.81±0.14 vs. 1.25±0.12 mW at baseline, p<0.01). This was not accompanied by any ST segment elevation on C ECG. In pigs, PSD in HF channel of UHR ECG was significantly decreased at 25% reduction of CA lumen, while ST segment on C ECG remained unchanged. In conclusion, UHR ECG enabled earlier detection of transmural MIS compared to C ECG. PSD in HF-channel of UHR ECG demonstrated greater sensitivity in the settings of subendocardial ischemia.

Our objective was to evaluate whether pregnancy is prolonged by use of a proteomics-based maternal serum screening test followed by treatment interventions. This is a secondary analysis of the PREVENT-PTB randomized trial comparing screening with the PreTRM test versus no screening. The primary trial analysis found no significant between-group difference in preterm birth rate. Rather than considering a dichotomous outcome (preterm vs term), we treated gestational age at birth as a continuous variable using survival analysis. We also evaluated between-group difference in NICU length of stay and duration of respiratory support. Results indicated that pregnancy was significantly prolonged in subjects screened with PreTRM test compared to controls (adjusted hazard ratio 0.53, 95% confidence interval 0.36-0.78, P &lt;0.01). Newborns of screened subjects had significantly shorter NICU stay but no significant decrease in duration of respiratory support. In the PreTRM screen-positive group, interventions that were associated with pregnancy prolongation included care management and low-dose aspirin but not 17-hydroxyprogesterone caproate. We concluded that screening with the PreTRM test followed by interventions for screen-positive pregnancies can prolong pregnancy and reduce NICU-LOS.

No consensus exists on whether acute aerobic exercise alters the glomerular filtration rate in older adults. Objective: To assess the immediate effects of three aerobic exercise intensities on the estimated glomerular filtration rate (eGFR) in healthy, sedentary older adults. Methods: Eighteen healthy, sedentary older adults (12 men and eight women) voluntarily participated in the study. The participants underwent three standardized aerobic exercise tests (100%, 80%, and 60% of the maximal heart rate) on a bicycle ergometer. Blood samples were collected to determine cholesterol, triacylglycerol, glucose, serum creatinine (Cr), Cystatin C (CysC) concentrations, and eGFR. Results: eGFR and serum concentrations of Cr and CysC were not modified at any exercise intensity. There was a negative correlation between blood total cholesterol vs. eGFR (R= -0.512, R= -0.582, R= -0.531; p &lt;0.05) at rest, 60%, and 100% of the maximal heart rate, respectively. Besides, a negative correlation existed between age vs. eGFR at 60% of the maximal heart rate (R= -0.516; p &lt;0.05). Conclusion: Short-time aerobic exercise of low, moderate, and vigorous intensity did not significantly affect eGFR and is considered safe for kidney function in healthy, sedentary older adults.

Lean practice is recognised for having a great potential in promoting safety risk management in offsite construction (OSC). This paper presents results of a study conducted to assess the impact of lean practice in safety risk management in OSC in a developing country. A quantitative approach using survey-based questionnaire was adopted. Lean management practices (LMPs) identified from literature review were empirically tested using a sample survey of 103 OSC contractors. The survey responses were subjected to descriptive and inferential statistics. The top ranked LMPs for safety risk management in OSC included two mistake proofing practices, i.e., use of personal protective equipment (PPE) and use of hazard warning equipment; two last planner system (LPS) practices, i.e., involvement of workers in safety planning and providing necessary working equipment and one first run studies (FRS) practice, i.e., critical analysis of work methods. These LMPs are useful in controlling high consequence safety risks in OSC. Based on evidence found in this study, the paper argues that lean practice can bring great value in the safety risk management in OSC in countries where OSC is transitioning.

From the existing millions of fungal species only a few cause disease. In this study, we investigated invasive fungal infections in the head and neck over a 19-year period (2005 to 2024) at a large academic healthcare system. Among 413 cases, 336 were noninvasive, and 77 were invasive. The highest incidence of invasive infections occurred in the sinonasal cavities, with a 15-fold difference compared to other sites. Most infections affected adults over 40 years old. The most common organisms were Mucorales (51%), hyaline molds (29%), and Candida (11%). Risk factors included malignancy, transplant, diabetes, and illicit drug use. Mortality was high in patients with malignancy and/or transplant. Infections affecting the mandible were usually a complication of osteoradionecrosis and were associated with coinfection of Candida and Actinomyces. At other sites, infections were rare and were usually the result of penetrating injuries or immunosuppression. Treatment typically involved a combination of antifungals and surgical procedures.

Emergence of COVID-19 had profound impact on global stock markets, including Indian mar-ket. Key indices like NIFTY50 and Sensex dropped by approximately 40% within two months in 2020, which also affected major mutual funds, leading to significant depreciation of their Net Asset Value. Securities and Exchange Board of India (SEBI) allows mutual funds to use deriva-tives for hedging purposes, capped at 100% of the scheme's net assets covering debt, equity, and derivatives. However, circular amendment by SEBI in January-2019 permitted covered call strat-egies on constituent stocks of Sensex and NIFTY50 for mutual fund schemes, excluding ETFs and Index Funds. This study investigated whether mutual funds increased their derivative us-age as risk mitigation strategy during COVID-19 pandemic, analyzing derivative holdings from 2019-2023. Surprisingly, findings indicated a decline in derivative holdings in 2020 compared to pre-pandemic levels. Statistical tests and performance evaluation metrics such as T-test, F-test, Treynor Ratio, Sharpe Ratio, and Jensen's calculations were employed to assess mutual fund performance. Although derivative-holding mutual funds didn't outperform benchmarks in aver-age returns, it showcased significantly reduced volatility, offering investors favorable risk-return trade-offs. research sheds light on derivative utilization in Mutual Fund industry, potentially in-forming regulators, fund managers, and investors in their decision-making

The aim of the study was to compare the standard baseline imaging, with extended radiological staging. To assess our hypothesis, we performed a prospective, single-centre study which included 132 participants recruited between October 2015 and March 2020. Descriptive statistics, the Friedman and chi-squared tests were performed and p &lt; 0.05 was considered significant. Patients were grouped into two cohorts, CT scan cohort (n=87) and PET-CT cohort (n=43). In the first group the originally determined disease stage changed in 36.8 % of cases, in second group in 51.2 %. The consistency between assessment of axillary lymph nodes by imaging (cN) and the postoperative pathology report (pN) was evaluated. In most cases, clinical and pathological evaluation of involved nodes was consistent, for CT scan the result was χ2(1) = 18.98; p &lt; 0.001, for PET-CT the result was χ2(1) = 6.41; p = 0.03. Highly customized radiation therapy defined as dose boost within the involved lymph nodes, not covered by surgeon, was applied in nine patients.

The hepatitis E virus (HEV) is a zoonotic pathogen with a variety of hosts, including pigs, which act as reservoirs. In industrialized countries, sporadic cases caused by genotype 3, contracted by ingestion of contaminated uncooked or undercooked meat, have been reported. However, in developing countries, HEV infection is mainly dominated by genotype 2 and often associated with poor hygiene conditions and drinking water supplies. In West Africa, HEV infection and its circulation in domestic fauna are very poorly documented. The aim of this study was to assess the presence of HEV in pork sold in Saint-Louis. Meat products were collected between 20 and 25 August 2022 in three location of Saint-Louis region. After purchasing 250 g of sample, we minced 2 g of sample for extraction of total nucleic acids using the Purelink™ Viral DNA/RNA kit and then RT-PCR using the One-Taq™ One-Step RT-PCR kit targeting the HEV ORF2 genomic region. The products obtained were visualized on a 1% agarose gel. Of a total of 74 samples, divided into pork meat (n=65) and pork liver (n=9), 5.4% (n=4) were tested positive for HEV. In both cases, 2 samples were positive, representing a rate of 3.1% and 22.2% for meat and pork liver respectively. All new viral sequences obtained form a monophyletic group within HEV genotype 3. These preliminary results reveal a potential circulation of HEV in the pig population. The high proportion of contamination in the pork liver samples highlights a major risk associated with their consumption.

The broad and rapid application of new genomic techniques (NGTs) such as CRISPR-Cas has led to a fast increase in the number of genetically modified crops. With the recently published EU Commission’s (EC) regulatory proposal on plants generated with NGTs (July 5, 2023) the process of admission of such genetically modified plants is aimed to get accelerated and simplified. NGT plant applications shall be categorized based on their molecular characteristics into category 1 NGT (NGT1) and category 2 NGT (NGT2), which is in divergence from the current legislation centered around Directive 2001/18/EC. In the regulatory proposal NGT2 plants are envisioned to undergo a reduced risk assessment while for NGT1 plants no risk assessment is foreseen at all. To demonstrate were the path of the proposal leads to in practice, we applied the proposed criteria for categorization to a list of NGT plant applications that are currently in the commercialization pipeline. A key finding is that out of those plant applications affected by the EC proposal, 94% would be classified as NGT1 and thus would receive a market approval without risk assessment, monitoring and sufficient labeling provisions. The remaining 6% of applications would be classified as NGT2 plants for which, in deviation from the current regulation, an adapted risk assessment is proposed. A screening of intended traits in the pipeline highlights that certain NGT1 plants can pose similar environmental risks (e.g. invasiveness) compared to other genetically modified organisms (GMOs), as defined in Directive 2001/18/EC. For example, NGT1 applications based on RNAi technology can exhibit insecticidal effects with potential side effects on non-target organisms (i.e. other insects). Our quantitative and case-specific elaboration on how the current EC regulatory proposal would affect the environment, health or consumer protection will be informative for decision makers and politicians.

Rice cultivation is the main agricultural activity in Asia, and it results in an enormous amount of agricultural waste, that are usually disposed-off by burning, causing serious environmental health and climate problems. Pakistan is the tenth largest producer in the world and the fourth exporter of rice in the world. To date, there are no studies targeting Pakistan’s profile monitoring its contribution in open burning emissions from rice straw waste. This study presents the characterization of PCDD/Fs, PCBs and PAHs emissions from three samples of rice straw collected from the main rice cultivation regions of Pakistan (Punjab, Sindh and Azad Jammu and Kashmir) in relation to the role of metal-based agricultural additives. PCDD/Fs, PCBs and PAHs emissions were quantified using a fixed grid system biomass plant and measuring the macro-pollutants online and sampling the organic micro-pollutants and metals in isokinetic mode, followed by ISO and CEN standards methods. In addition, role of agrochemicals was monitored in terms of metal catalysis resulted in POPs emissions. This study provides the characterization of most relevant group of pollutants (metals, PCDD/Fs, PCBs and PAHs) as a result of agricultural waste combustion. The rice straw samples from AJK showed high values of organochlorine micro-pollutants compared to the values followed by samples from Punjab and Sindh, i.e., respectively, ∑PCDD/F (2594>1493>856 pg/Nm³) and ∑PCB (41>38>30 pg/Nm³). Whereas the organic micro-pollutants ∑PAH, indicators of incomplete combustion (PICs), were recorded high in the samples from Sindh followed by Punjab and AJK. This study supports the idea that the phenomena that lead to the formation of PCDD/F and PCB are influenced not only by poor combustion but also by the presence of metal catalysts or precursors in the burned fuel.

Dual antiplatelet therapy (DAPT), comprising aspirin and a P2Y12 receptor inhibitor, is the cornerstone of post-percutaneous coronary intervention treatment to prevent stent thrombosis and reduce the risk of adverse cardiovascular events. The selection of an optimal DAPT regimen, considering the interplay of various antiplatelet agents, patient profiles, and procedural characteristics, remains an evolving challenge. Traditionally, a standard duration of 12 months has been recommended for DAPT in most patients. While contemporary guidelines provide general frameworks, DAPT modulation with longer or shorter treatment courses followed by aspirin or P2Y12 inhibitor monotherapy are evolving towards an individualized strategy to optimize the balance between efficacy and safety. This review comprehensively examines the current landscape of DAPT strategies after coronary stenting, with a focus on emerging evidence for treatment individualization.

Aims: Chronic coronary syndrome is associated with several risk factors, such as dyslipidemia and hypertension. AIP has been demonstrated to be a biochemical risk factor for coronary artery disease (CAD). This study aimed to determine whether AIP is an effective parameter for estimating obstructive CAD. Methods and Results: A total of 345 patients (mean age 62,2±10,3; 63% male) who underwent coronary angiography were included in this study. Obstructive CAD is defined as having one or more vessels with a stenosis of≥50%. Depending on the presence of obstructive CAD, all patients were divided into two groups. The AIP was significantly higher in the obstructive coronary artery group (AIP; 0,49±0,26 vs. 0,58±0,27, p=0,002). In univariate analysis, AIP was significantly associated with obstructive coronary artery disease [OD:3,74 (CI95% 1,62-8,64), P=0,020]. The AIP was further adjusted for confounding risk factors in three multivariate analysis models. Therefore, all three models showed a significant association. According to ROC analysis, 0.49 is the cut-off value for AIP, and a value above 0.49 indicates 50% coronary artery stenosis Conclusions: AIP may be used in the assessment of cardiovascular risk in patients with stable angina pectoris, and it may also be used to estimate obstructive CAD.

Background: The diagnosis of metabolic syndrome (MetS) is a challenge in people with spinal cord injury (SCI). We aimed at identifying clinical risk factors or early markers of MetS in SCI that would facilitate a timely diagnosis and implementation of preventive/therapeutic strategies. Methods: 168 patients with chronic (>1 year) SCI underwent clinical and biochemical evaluations. MetS was diagnosed according to modified criteria of the International Diabetes Federation validated in people with SCI. Results: MetS was diagnosed in 56 of 132 men (42.4%) and 17 of 36 women (47.2%). At univariate regression analyses, putative predictors of MetS were an older age, a higher number of comorbidities, a lower insulin-sensitivity, the presence and intensity of pain, a shorter injury duration, a poorer leisure time physical activity (LTPA) and an incomplete motor injury. At the multiple regression analysis, a significant independent association with MetS only persisted for a poorer LTPA in minutes/week (OR: 0.998, 95%CI: 0.996, 0.999) and more severe pain symptoms as assessed by numeral rating scale (OR: 1.353, 95%CI: 1.085, 1.793). Conclusions: In patients with SCI, intense pain symptoms and poor LTPA may suggest a high likelihood of MetS, regardless of age, SCI duration, motor disability degree, insu-lin-sensitivity and comorbidities.

Different toll collection types of vehicles and different distribution of tollbooths lead to the toll plaza diverging area becoming a typical vehicle weaving area with frequent crossing behaviors and conflicts on highways. This study aims to identify contributing factors to conflict risks of four vehicle-following patterns in a toll plaza diverging area by developing random parameters ordered logit models with heterogeneity in means and variances. The model can flexibly capture the unobserved heterogeneity of the contributing factors in different vehicle-following patterns. Real-world vehicle trajectory data obtained from the toll plaza diverging area in Nanjing, China, are used for model estimation. The results show that vehicle-following patterns with the same toll collection types have higher percentage of severe conflict risks. The average acceleration of the following vehicles, lane marking indicator, the initial lanes and lane-changes of vehicles are significantly associated with the collision risk levels. The standard deviation of surrogate safety measures of all vehicles in sub-segments are found differ significantly between vehicle-following patterns. Furthermore, a series of likelihood ratio tests are adopted to test the spatial dependence in sub-segments of the diverging area. The findings of this study could provide valuable information for safety improvement in toll plazas.

The functions of annexin A1 (ANXA1) that is expressed on membranes and in cytoplasmic granules have been fully described. Nonetheless, the role of this protein in protecting against DNA damage in the nucleus is still emerging and requires further investigation. Here, we investigated the involvement of ANXA1 in DNA damage response in placental cells. Placenta was collected from ANXA1 knockout mice (AnxA1-/-) and pregnant women with gestational diabetes mellitus (GDM). The placental morphology and ANXA1 expression, which are related to the modulation of cellular response markers in the presence of DNA damage, were analyzed. Total area of AnxA1-/- placenta was smaller because of reduced labyrinth zone, enhanced DNA damage, and impaired base excision repair (BER) enzymes, which resulted in the induction of apoptosis in the labyrinthine and junctional layers. The placentas from pregnant women with GDM showed reduced expression of AnxA1 in the villous compartment, increased DNA damage, apoptosis, and reduction of enzymes involved in the BER pathway. Our translational data provide valuable insights into the possible involvement of ANXA1 in the response of placental cells to oxidative DNA damage and represent advancement in investigations on the mechanisms involved in placental biology.

The effects of global warming combined with the progressive expansion of urbanization have considerably increased exposure to urban flooding and runoff widespread erosion risk, also causing shallow landslides and mud flows, respectively in urbanized areas of lowland and hill/foothill environments. Increasing urban flooding resilience has become a priority at virtually all levels of governance. The analysis of a different hazard scenarios, in which various hydro-meteorological conditions and management alternatives are examined, should act as the basis for the effective design and evaluation of interventions to improve urban flooding resilience. Turin Metropolitan Area (TMA), located in north-western Italy, represents a unique case due to its complex orography, with a mountainous sector in the west side and a flat or hilly part in the east side. During the warm season, these environmental conditions make the urban area prone to severe atmospheric convection causing frequent hailstorms and rainstorms of high intensity that may impact on urban infrastructures (i.e., drainage system and road network), thus requiring an adequate management as a key factor to reducing risk and losses. The urban areas of TMA are monitored by polarimetric Doppler weather radars and by a dense rain gauges network. Analyzing several case studies of urban flooding, this research work assesses the feasibility of a meteorological radar early warning system based on the identification of rainfall thresholds that characterize urban flooding, occurring in the lowlands, and the runoff erosion phenomena affecting the urbanized hills and foothills.

The present study aims to develop a risk-based approach to find optimal solutions for life extension management for offshore wind farms based on Markowitz’s modern portfolio theory, adapted from finance. The developed risk-based approach assumes that the offshore wind turbines (OWT) can be considered as cash-producing tangible assets providing positive return from the initial investment (capital) with a given risk attaining the targeted (expected) return. In this regard, the present study performs a techno-economic life extension analysis within the scope of the multi-objective optimisation problem. The first objective is to maximise the return from the overall wind assets, while the latter aims to minimise the risk associated with obtaining the return. In formulating the multi-dimensional optimisation problem, the life-extension assessment considers the results of a detailed structural integrity analysis, free-cash-flow analysis, and probability of project failure, local and global economic constraints. Further, the risk is identified as the variance from the expected mean of return on investment. The risk-return diagram is utilised to classify the OWTs of different classes using an unsupervised machine learning algorithm. The optimal portfolios for the various required rate of return are recommended for different stages of life extension.

This paper shows the influence of CCP’s collateralization on the pricing of the Credit Default Swaps (CDS). A narrowly variant in the way the CDS seller decides over the resources in the settlement comes with a substantial change on the elements that determine the price of the CDS.

Caesarean scar ectopic pregnancy (CSEP) is an uncommon form of ectopic pregnancy. This review defines types of CSEP, discusses pathophysiology, clinical presentation and diagnosis and compares common treatment options and outcomes. The pathophysiology is not yet fully understood. One third of patient are asymptomatic. In symptomatic patients vaginal bleeding and pelvic pain which is usually misdiagnosed as threatened or missed abortion. The main principles of treatment for CSEP are early diagnose, quick management, and maintain reproductive function as much as possible. Up to date; no consensus or guidelines for the treatment and management of CSEP. Management of CSEP depends on the clinical presentation and gestational age. Significant controversy exists regarding management, for this reason, several factors should be considered including age of the patient, myometrial thickness, clinical symptoms, hemodynamic status, fertility preservation.

Abstract: Purpose – In this article we lay out the change management practices adopted by financial firms in small states within the Eurozone. We determine whether these organisations have the ability to identify triggers for change (Red Flags) and subject them to eight thematic elements to understand whether management practices can continue to exist and support operational environments, even when unexpected circumstances affect their day to day operations and processes. In doing this we examine the extent to which the eight thematic elements from the model designed by Dalli Gonzi, (2019) (The Dali Model) can assist organisations in risk identification and business continuity planning. Design/methodology/approach – A self-administered questionnaire purposely designed for this study was administered to personnel working in internal controls within financial institutions of small Eurozone states. The participants were asked to grade statements using a 5-point Likert scale, ‘1’ being ‘totally disagree’ and ‘5’ being totally agree’ to the statement posed under the thematic elements forming the basis of the Dali Model. Findings – Factor analysis provided support for the eight hypothesised dimensions of the decision-making model: connection, capacity, governance, network, policy, training, process improvement, standards. Originality/value – The study provides a better understanding and support of “best practice” in change management through an understanding and assessment of the eight factors that are the basis of this model. It addresses practical recommendations to ensure application to a wider frame of use.

Coal combustion in thermal power plants releases ash. Ash is reported to cause different adverse health hazards in humans and other organisms. Owing to the presence of radionuclides, it is also considered as a potential radiation hazard. In this study, based on the surface radiation measurements and relevant ancillary data, expected radiation risk zones were identified with regard to the human population residing near the Thermal Power Plant. With population density as the risk determining criteria, about 20% of the study area was at ‘High’ risk and another 20% of the study area was at ‘Low’ risk zone. The remaining 60% was under medium risk zone. Based on the findings remedial measures which may be adopted have been suggested.

Cryptocurrencies like Bitcoin rely on a proof-of-work system to validate transactions and prevent attacks or double-spending. A new proof-of-work is introduced which seems to be the first number theoretic proof-of-work unrelated to primes: it is based on a new metric associated to the Collatz algorithm whose natural generalization is algorithmically undecidable: the inflation propensity is defined as the cardinality of new maxima in a developing Collatz orbit. It is numerically verified that the distribution of inflation propensity slowly converges to a geometric distribution of parameter $0.714 \approx \frac{(\pi - 1)}{3}$ as the sample size increases. This pseudo-randomness opens the door to a new class of proofs-of-work based on congruential graphs.

This study analyses the short-run hydro generation scheduling for the wind power differences from the contracted schedule. The approach for construction of the joint short-run marginal cost curve for the hydro-wind coordinated generation is proposed and applied on the real example. This joint short-run marginal cost (SRMC) curve is important for its participation in the energy markets and for economic feasibility assessment of such coordination. The approach credibly describes the short-run marginal costs which this coordination bears in “real life”. The approach is based on the duality framework of a convex programming and as a novelty combines the shadow price of risk mitigation capability and the water shadow price. The proposed approach is formulated as a stochastic linear program and tested on the case of the Vinodol hydropower system and the wind farm Vrataruša in Croatia. The result of the case study is a family of 24 joint short-run marginal cost curves.

Covid-19 is an airborne disease, with the vast majority of infections occurring indoors. By comparison, little transmission occurs outdoors. Here, we investigate the airborne transmission pathways that differentiate the indoors from outdoors, and conclude that profound differences exist, which help to explain why SARS-CoV-2 transmission is much more prevalent indoors. Near and far-field transmission pathways are discussed along with factors that affect infection risk, with aerosol concentration, air entrainment, thermal plumes, and occupancy duration all identified as being influential. In particular, we present the fundamental equations that underpin the Wells-Riley model, and show the mathematical relationship between inhaled virus particles and quanta of infection. A simple model is also presented for assessing infection risk in spaces with incomplete air mixing. Transmission risk is assessed in terms of aerosol concentration using simple 1D equations, followed by a description of thermal plume-ceiling interactions. With respect to this, we present new experimental results using Schlieren-visualisation and Computational Fluid Dynamics (CFD) based on the Eulerian-Lagrangian approach. Pathways of airborne infection are discussed, with the key differences identified between indoors and outdoors. In particular, the contribution of thermal and exhalation plumes is evaluated, and the presence of near-field/far-field feedback loop postulated, which is absent outdoors.

The increasing rate of adoption of innovative technological achievements along with the penetration of the Next Generation Internet (NGI) technologies and Artificial Intelligence (AI) in the water sector, are leading to a shift to a Water-Smart Society. New challenges have emerged in terms of data interoperability, sharing, and trustworthiness due to the rapidly increasing volume of heterogeneous data generated by multiple technologies. Hence, there is a need for efficient harmonisation and smart modeling of the data to foster advanced AI analytical processes which will lead to efficient water data management. The main objective of this work is to propose two Smart Data Models focusing on the modeling of the Satellite Imaginary data and the Flood Risk Assessment processes. The utilisation of those models reinforces the fusion and homogenisation of diverse information and data facilitating the adoption of AI technologies for flood mapping and monitoring. Furthermore, a holistic framework has been developed and evaluated via qualitative and quantitative performance indicators revealing the efficacy of the proposed models concerning the usage of the models in real cases. The framework is based on the well-known and compatible technologies on NGSI-LD standards which are customised and applicable easily to support the water data management processes effectively.

This study explores the complexities of risk communication practices in orthodontics, specifically examining the perspectives of orthodontists in Greece and Slovakia. Informed by the foundational importance of effective communication in health sciences, particularly in facilitating valid consent and shared decision-making, this research addresses gaps identified in the literature concerning the consistent communication of potential treatment risks based on demographic and cultural characteristics. The study identifies 15 potential critical risks with orthodontic treatment. These risks include root necrosis; temporary undesired changes to the occlusion; sleep difficulties; not achieving an ideal result; development of black triangles between teeth; taking additional X-rays; speech difficulties; using a protective splint during sports; duration of treatment; number of visits; transmission of infectious diseases; and swallowing orthodontic appliances. The questionnaire, distributed electronically to orthodontists in Greece (n=570) and Slovakia (n=210) from Sept. 2022 to Dec. 2022, aimed to assess risk communication practices, with consideration to country, gender, and degree-related variations. 168 valid questionnaires (91 from Slovakia and 77 from Greece) were obtained indicating significant disparities in the risks emphasized and preferred forms of consent. The Greek orthodontists focused more on the risks involved such as on relapse, root resorption, temporal occlusal changes, and failure of desired movement, while the Slovak practitioners tend to be interested more about sleeping difficulties, temporal occlusal changes and not achieving an ideal result. They also tend to obtain written or digital consent from patients or their parents/guardians more frequently than the Greek team. Male orthodontists discussed specific risks more frequently, including relapse and extractions, whereas females preferred written or digital consent. PhD-trained orthodontists prioritized certain risks, indicating the need for tailored approaches. This study underscores the dynamic nature of risk assessment in orthodontic practice, emphasizing its ethical and strategic dimensions. The findings advocate for tailored risk communication strategies, that recognize individual, contextual, and cultural factors and the need of an orthodontic informed consent protocol for tailored communication approach for patients to elevate the standard of care in European orthodontics. The reliance on digital tools reflects contemporary trends in enhancing patient understanding, thereby supporting ongoing innovation in orthodontic practices.

The 3D/3D+ multidimensional geriatric assessment tool provides an optimal model of emergency care for patients aged 75 and over who attend the Emergency Department (ED). The baseline, or static, component (3D) stratifies the degree of frailty prior to the acute illness, while the current, or dynamic, component (3D+) assesses the multidimensional impact caused by the acute illness and helps to guide the choice of care facility for patients upon their discharge from the ED. The objective of this study was to evaluate the prognostic value of the 3D/3D+ to predict short- and long-term adverse outcomes in ED patients aged 75 years and older. Multivariable logistic regression models were used to identify the predictors of mortality 30 days after 3D/3D+ assessment. Two hundred and seventy-eight patients (59.7% women) with a median age of 86 years (interquartile range: 83-90) were analysed. According to the baseline component (3D), 83.1% (95%CI: 78.2-87.3) presented some degree of frailty. The current component (3D+) presented alterations in 60.1% (95%CI: 54.1-65.9). The choice of care facility at ED discharge indicated by the 3D/3D+ was considered appropriate in 96.4% (95%CI: 93.0-98.0). Thirty-day all-cause mortality was 19.4%. Delirium and functional decline were the dimensions on the 3D/3D+ that were independently associated with 30-day mortality. These two dimensions had an area under receiver operating characteristic of 0.80 (95%CI: 0.73-0.86) for predicting 30-day mortality. 3D/3D+ enhances the provision of comprehensive care by ED professionals, guides them in the choice of patients’ discharge destination, and has a prognostic validity that serves to establish future therapeutic objectives.

Background: Handover is a critical process for ensuring quality and safety in healthcare. Considerable research suggests that poor handover results in significant morbidity, mortality, dissatisfaction, and excess financial costs. Despite this, little formal attention, education, and evaluation has been given to handover. There is also paucity of data on the opinions of practitioners on the safety of handover.Objectives: The aim of this study was to measure the perceived risk, degree of patient harm and the systems used to support handover, and to understand how this varied by care setting, type of clinical practice, location, or level of experience. Methods: An open, anonymous and confidential online questionnaire covering: (a) respondent characteristics; (b) peer-to-peer handover; (c) internal referrals; (d) discharges and transfers between organisations; and (e) leading and improving handover was conducted with healthcare practitioners and managers from various settings. Results: We gathered a total of 432 completed responses from 26 countries. The average reported performance of handover was rated as 3.9 out of 5.For each type of handover, 12 - 14% reported errors occurring more than weekly. Of those that knew the outcome of such errors, between 29% and 34% reported that they had witnessed moderate or severe harm. 12% and 17% of respondents believed that handover was high or very high risk (See table 4). These respondents were more likely to have witnessed moderate or severe harm, or to be more senior.A wide combination of handover systems was utilised by respondents. 28% - 32% relied exclusively on EPRs (with or without face-to-face contact). 21% used Office documents such as Word and Excel for peer-to-peer handover, and over 30% used hand-written or manual systems. Conclusions: This study suggests the need to do more — and go further — to improve communication and reduce risk during all types of handovers. Clinical leaders should find ways to train and support handover with effective systems, with less experienced staff being the primary focus. More research is needed to demonstrate the interventions that improve the safety of handover.

The famous Capital Asset Pricing Model (CAPM) takes into account only business risk. In practice, companies use debt financing and operate at non–zero levels of leverage. This means that it is necessary to take into account the financial risk associated with the use of debt financing along with business one. The purpose of this paper is to simultaneously take into account the business and financial risk. A new approach to CAPM has been developed that takes into account both business and financial risk. We combine the theory of CAPM and the Modigliani–Miller (MM) theory. The first is based on portfolio analysis and accounting for business risks in relation to the market (or industry). The second one (the Modigliani–Miller (MM) theory) describes a specific company and takes into account the financial risks associated with the use of debt financing. The combination of these two different approaches makes it possible to take into account both types of risks: business and financial ones. We combine these two approaches analytically, while Hamada did it phenomenologically. Using the Modigliani–Miller (MM) theory, it is shown that the Hamada’s model, first model, used for this purpose half a century ago, is incorrect. In addition to the renormalization of the beta–coefficient, obtained in the Hamada model, two additional terms are found: the renormalized risk–free return and the term dependent on the cost of debt kd. A critical analysis of the Hamada model was carried out. The vast majority of listing companies use debt financing and are levered, and the Hamada model is not applicable to them in contrast to a new approach applicable to leveraged companies. Implemented a new approach to specific companies. A comparison of the results of the new approach with the results of the conventional CAPM is shown. Two versions of CAPM (market or industry) are considered.

This study aims to identify the model that best approximates the credit spread that should be fixed on debt instruments issued by both public and private companies, considering the particularities of the Mexican market. Five models were analyzed: Merton's [1], those proposed by Denzler et al., the one presented in this paper, which includes the conformable derivatives, taking as a reference the change of variable made by Morales-Bañuelos et al., and the Corporate Default Risk Model (DRSK) for Publics Firms of Bloomberg [4]. The required financial information was obtained from the Bloomberg platform, from which the probabilities of default, credit spreads, and credit ratings for each company in the sample under the model (DRSK) were extracted directly. Likewise, the program developed by Moody's K.M.V. was used to obtain the EDF (Expected Default Frequencies). It was concluded that the Modified Merton model approximates to a greater extent the credit spreads that fix on a prime rate on the loans granted to the Mexican non-financial companies.

Background: Macrophage inflammatory protein-1 alpha (MIP-1α) and C-reactive protein (CRP) are pro-inflammatory biomarkers that quantify clinical and subclinical inflammation in cardiac ischemia in cardiac inflammation and disease. Adiponectin is an anti-inflammatory marker associated with good health. The susceptibility of periodontitis patients to cardiovascular events needs to be evaluated. Objective: This study aims to assess the levels of biomarkers in periodontitis patients with and without acute myocardial infarction (AMI) compared to controls. Material and methods: Pro-inflammatory and anti-inflammatory analytes were examined by collecting unstimulated saliva from three groups (n = 20/each): healthy individuals, individuals with stage III periodontitis, and post-myocardial infarction patients with stage III periodontitis. The samples were collected within 48 hours of AMI. Results: Adiponectin levels were significantly lower in patients with periodontitis with and without AMI compared to controls, while CRP and MIP-1α were significantly higher in patients with periodontitis with and without AMI compared to controls. The highest titers for MIP-1α and CRP were detected among patients with periodontitis with and AMI. Conclusion: Our study provides evidence of the association between periodontitis and salivary analytes that occur in tandem with cardiovascular disease. The lower levels of Adiponectin and higher levels of CRP and MIP-1α in patients with periodontitis indicate that this condition is a potential risk factor for cardiovascular disease. The findings emphasize the importance of early detection and intervention for periodontitis patients to prevent cardiovascular events.

In this work, the Pumped Storage Unit (PSU) is proposed to be integrated with wind-thermal generation system owned by a company whose aim is to maximize its profit through optimal self-scheduling of its units by finding the best bidding strategy in day-ahead energy market. The mathematical formulation of the scenario based unit-commitment and coordinated trading problem is formulated as a stochastic mixed integer linear program. The formulation takes into account several uncertain parameters; such as the wind power generation, energy market prices, and imbalances up/down prices. The expected total profit obtained from energy trading with and without coordinating pumped storage system (PSS) with thermal-wind generation system were compared, and a significant improvement in profit resulted from coordination was observed. Furthermore, coordination between PSS and wind-thermal generation improve the conditional value at risk (CVaR) which monitors the biding risk level.

Credit scoring is a cornerstone of financial risk management, enabling financial institutions to assess the likelihood of loan default. However, widely recognized contemporary credit risk metrics, like FICO or Vantage scores, remain proprietary and inaccessible to the public. This study aims to devise an alternative credit scoring metric that mirrors the FICO score, using an extensive dataset from Lending Club. The challenge lies in the limited insights available on both the precise analytical formula and the comprehensive suite of credit-specific attributes integral to the FICO score's calculation. Our proposed metric leverages basic information provided by potential borrowers, eliminating the need for extensive historical credit data. We aim to articulate this credit risk metric in a closed analytical form with variable complexity. To achieve this, we employ a symbolic regression method anchored in Genetic Programming (GP). Here, Occam's razor principle guides evolutionary bias towards simpler, more interpretable models. To ascertain our method's efficacy, we juxtapose the approximation capabilities of GP-based symbolic regression with established machine learning regression models, such as Gaussian Support Vector Machines (GSVMs), Multi-Layer Perceptrons (MLPs), Regression Trees and Radial Basis Function Networks (RBFNs). Our experiments indicate that GP-based symbolic regression offers comparable accuracy with these benchmark methodologies. Moreover, the resultant analytical model offers invaluable insights into credit risk evaluation mechanisms, enabling stakeholders to make informed credit risk assessments. This study contributes to the growing demand for transparent machine learning models by demonstrating the value of interpretable, data-driven credit scoring models.

Objective: This study aims to construct an early risk warning model to predict the risk of treatment failure in patients undergoing sequential High-Flow Nasal Cannula (HFNC) oxygen therapy following mechanical ventilation weaning. Methods: A retrospective analysis was conducted on clinical data from 145 patients who received HFNC treatment in the Emergency Intensive Care Unit of the Third People's Hospital of Bengbu City from June 2018 to June 2023. A wide range of indicators including general information, comorbidities, laboratory test results, vital signs, disease-related scores, and oxygenation data were collected. Data analysis was performed using R software, starting with the Lasso regression to filter features related to treatment outcomes. Patients were divided into a training set (70%) and a validation set (30%) using random grouping software. The Random Forest algorithm was then employed to evaluate and rank the important features related to outcome indicators. The predictive efficiency and stability of the model were assessed through the Receiver Operating Characteristic (ROC) curve, calibration curve, and decision curve analysis, culminating in the construction of an early risk warning nomogram. Results: The study found that the Random Forest model exhibited high predictive accuracy in the training set (AUC=0.98) and good stability in the validation set (AUC=0.84). Key feature variables identified by the model, such as APACHE II score, BNP, NLR, mROX, and SOFA, were found to significantly impact the prediction of HFNC treatment failure. Based on these variables, an early warning nomogram was further developed, providing clinicians with a convenient and effective risk assessment tool. Conclusion: This study has constructed an early risk warning model based on the Random Forest algorithm, capable of effectively predicting the risk of HFNC treatment failure. The model's high predictive efficiency and stability offer strong support for clinical decision-making, contributing to personalized treatment and improved patient outcomes. Future research should aim to expand the sample size, perform multicenter validation, and explore the integration of the model into Clinical Decision Support Systems for real-time risk assessment and intervention.

Previous studies have acknowledged the impact of weather changes on retail uncertainty. They primarily focus on understanding how weather conditions affect offline consumer behavior and aiming to develop effective marketing strategies. However, there is little research on the complex impact of weather on online shopping behavior. To bridge this gap, we conduct a study with a sample of 261 consumers from China with shopping experience in Community Retail Shops (CRSs). We utilize the S-O-R model and theories including meteorological emotional effect theory, emotional coherence and meteorological psychology to propose and validate models elucidating the relationship between weather and consumers' online shopping behavior in CRS. Our findings reveal that weather conditions affect consumers' spending patterns and purchase diversity, mediating by consumers' emotion and risk aversion, when they comfortably shop online at home. Furthermore, employing the fsQCA model, we identify the critical path through which weather conditions and consumer types influence risk aversion awareness. The results provide management implications for retailers to develop online marketing strategies for different consumer types.

This qualitative research explores Supplier Relationship Management (SRM) practices within the e-commerce fashion industry, aiming to uncover key strategies and their impacts. Through semi-structured interviews with supply chain managers, procurement officers, and supplier representatives, critical themes emerged: communication, trust, risk management, sustainability, and digital technologies. Effective communication, characterized by transparency and regular updates, emerged as pivotal for aligning expectations and resolving issues promptly. Trust-building practices, including fair dealings and formal agreements, were essential in fostering long-term partnerships, reducing transaction costs, and enhancing collaboration. Robust risk management strategies, such as supplier diversification and contingency planning, were identified as crucial for mitigating disruptions and ensuring supply chain resilience. Sustainability was highlighted as a strategic imperative, driven by ethical sourcing and environmental standards, supported by technologies like blockchain for transparency. The transformative role of digital technologies—supply chain management software, blockchain, IoT, and data analytics—was evident in enhancing visibility and decision-making across global supply chains. Viewing suppliers as strategic partners, rather than mere vendors, promoted collaborative innovation and mutual growth. Despite challenges like cultural differences and regulatory complexities, opportunities exist to enhance SRM through integrated best practices. By prioritizing effective communication, trust-building, risk management, sustainability, and digital innovation, companies can strengthen supplier relationships, optimize supply chain performance, and achieve competitive advantage in the e-commerce fashion sector.

This qualitative study explores the pivotal role of Supplier Relationship Management (SRM) in enhancing resilience within e-commerce supply chains. In an era marked by rapid digital transformation and global interconnectedness, the resilience of supply chains has become a strategic imperative for organizations striving to maintain operational efficiency and meet customer expectations. Through semi-structured interviews with supply chain managers, procurement officers, and strategic sourcing specialists across diverse industries, this research investigates the strategies, challenges, and outcomes associated with SRM practices. Findings reveal that effective communication and collaboration are fundamental to successful SRM, fostering trust, transparency, and responsiveness in supplier relationships. Strategic risk management through proactive identification and mitigation strategies enables organizations to navigate uncertainties such as economic fluctuations and geopolitical tensions. SRM implementation yields significant organizational benefits, including improved supply chain efficiencies, enhanced product quality, and increased customer satisfaction. However, challenges such as technological complexities, cultural differences among global suppliers, and regulatory compliance issues underscore the need for adaptive strategies and digital investments. The integration of digital technologies such as AI and blockchain enhances SRM effectiveness by enabling real-time data exchange, predictive insights, and decision-making capabilities. Ultimately, SRM emerges as a cornerstone of sustainable growth and competitive advantage in e-commerce, empowering organizations to optimize supply chain performance and resilience amidst dynamic market conditions.

This qualitative study explores the transformative role of Supplier Relationship Management (SRM) in the context of e-commerce, focusing on the integration of digital technologies and evolving supplier interactions. As digital advancements such as artificial intelligence, blockchain, data analytics, cloud computing, and the Internet of Things (IoT) reshape traditional SRM practices, e-commerce companies are experiencing significant improvements in efficiency, transparency, and collaboration. This research employs semi-structured interviews, document analysis, and case studies to examine the impact of these technologies on SRM, identify key collaborative practices, and assess risk management strategies. Findings indicate that digital integration enhances decision-making, streamlines operations, and fosters deeper, trust-based supplier relationships. AI facilitates predictive analytics and automates processes, while blockchain provides transparency and reduces fraud. Data analytics supports informed sourcing decisions and risk mitigation, and cloud platforms improve real-time collaboration. IoT enhances supply chain visibility, allowing for better inventory management. Despite these benefits, challenges such as high implementation costs, integration difficulties, data privacy concerns, and security risks remain significant barriers. Collaboration practices, including joint development, shared resources, and coordinated marketing, contribute to innovation and mutual growth, emphasizing the need for effective communication and trust. Risk management strategies, such as scenario planning and supplier diversification, are crucial for maintaining supply chain resilience. Strategic alignment between e-commerce companies and suppliers, including goal congruence and capability matching, is essential for seamless coordination and competitive advantage. The study underscores the importance of a holistic approach to SRM, integrating technology, collaboration, risk management, and strategic alignment to navigate the complexities of supplier relationships in the digital age. These insights provide a framework for e-commerce companies to optimize their SRM practices and achieve sustainable growth in a dynamic marketplace.

Smoking is a pervasive global health concern associated with a myriad of diseases, but its impact on cellular aging, particularly in relation to telomeres, is increasingly recognized. Telomeres, protective caps at the ends of chromosomes, play a crucial role in maintaining genomic integrity. This review critically examines the existing evidence on the association between smoking and telomere atrophy, exploring the molecular mechanisms involved and the implications for accelerated aging and heightened disease risk. The comprehensive analysis encompasses both cross-sectional and longitudinal studies, elucidating potential gender and age disparities. Insights into the molecular pathways linking smoking to telomere shortening are discussed, along with the broader implications for public health. The review concludes by outlining potential interventions and suggesting future research directions in this critical area.

Over the last decade, highly pathogenic avian influenza (HPAI) has severely affected poultry production systems across the globe. In particular, massive pre-emptive depopulation of all poultry within the certain distance has raised concerns regarding animal welfare and food security. Thus, alternative approaches to reducing unnecessary depopulation, such as risk-based depopulation, are highly demanded. This paper proposes a data-driven method to generate a rule table and risk score for each farm to identify preventive measures against HPAI. To evaluate the proposed method, 105 cases of HPAI occurring in a total of 381 farms in Jeollanam-do from 2014 to 2023 were evaluated. The accuracy of preventive measure identification was assessed for each case using both the conventional culling method and the proposed data-driven method. The evaluation showed that the proposed method achieved an accuracy of 84.19%, significantly surpassing the previous 10.37%. The result was attributed to the proposed method reducing the false-positive rate by 83.61% compared with the conventional method, thereby enhancing the reliability of identification. The proposed method is expected to be utilized in selecting farms for monitoring and management of HPAI.

The increasing prevalence of periprosthetic femoral fractures, specifically in the vicinity of the hip, has emerged as a significant issue in recent times. Consequently, there is a need for a thorough examination to enhance the effectiveness of management and treatment approaches. The findings emphasized a significant disparity in the occurrence and characteristics of these fractures, as multiple studies have highlighted the efficacy of various treatment strategies, such as open reduction and internal fixation, as well as the utilization of cortical strut allografts. Furthermore, the research has identified potential risk factors that have an impact on the characteristics of fractures, providing valuable insights that could be crucial in the development of preventive strategies. This research provides a thorough examination of periprosthetic femoral fractures, highlighting the importance of a cohesive treatment algorithm to improve the handling of such fractures. Moreover, it promotes the need for a collaborative endeavor in conducting research in this field, cultivating a more profound comprehension that has the potential to drive progress in therapeutic approaches, ultimately enhancing patient results over an extended period of time. It is crucial that forthcoming research endeavors persist in expanding upon these discoveries, striving towards a unified methodology in tackling this substantial clinical obstacle.

There are two purposes for this article. The first purpose is to perform a reiew of previous research on global supply chain management (GSCM) principles that can adapt and survive adversity, such as the COVID-19 pandemic. The second purpose is to put forth a conceptual framework for the GSCM that is sustainable in the event of future turbulence similar to that experienced during the COVID-19 pandemic. With regard to the issues raised, the article posits the following questions. Is there, perhaps, a sustainable post-COVID-19 pandemic GSCM? Can the COVID-19 pandemic-related international logistics system (GSC) turbulences be predicted with certainty using these sustainable post-COVID-19 pandemic GSCM concepts? Putting it all together, the paper concludes that, while debatable, sustainable GSCM is feasible and can be accomplished utilizing JIT, supply chain mitigation, and supply chain visibility, as demonstrated by the manufacturing firms referenced in the article.

The implications related to the fight against alien organisms often affect different sectors, from the economic to the landscape one or from the public health to the ecological one. This paper is an upgrade of our previous study focused on the evolution of the red palm weevil in a coastal urban area (central Italy); we investigate the evolution of this parasite in the following period (2013-2020), considering both the effectiveness of the chemicals used and their potential effects. With a multidisciplinary approach, on the one hand we carried out a spatio-temporal analysis to analyze the extent and mode of pest spread over time using historical aerial photos, freely available remote sensing images and field surveys, integrated in a GIS environment, and on the other hand we performed an assessment of the chemical risk associated with the substances used to protect the palms from the red weevil. The fight against weevil is now concentrated in specific areas (parks, relevant roads, villas, hotels, farmhouses, nurseries); the applied preventive chemical treatments are very effective in preserving the palms, but they show a toxic potential for all organisms. We discuss current local management of this pest focusing on the several aspects involve into the fight against this beetle in an urban area.

Coastal flooding exacerbated by climate change is recognised as a major global threat which is expected to impact more than a quarter of people currently residing in Pacific Islands countries. While most research in the last decade has focused on understanding the dynamics and impacts of future coastal flooding from extreme sea levels, relative sea level rise (RSLR) effects on tsunami hazards are not well understood. Far-field or distant-sourced tsunamis tend to have relatively lower impacts in Pacific Island states compared with locally sourced events, but there is limited understanding on how the impact of far-field tsunamis changes over time due to RSLR. Using the hydrodynamics software BG-Flood, we modelled the Tōhoku tsunami from propagation to inundation in Samoa under incremental SLR to examine the effects that RSLR has on changing the exposure of the built environment (e.g., buildings) to a far-field tsunami. Outputs of maximum tsunami inundation and flow depth intensities which incorporate incremental SLR were then combined with digital representations of buildings and depth-damage functions in the RiskScape multi-hazard risk modelling software to assess the changes in building exposure over time. Results indicate that present day buildings exposure in Samoa to a Tōhoku-oki type far-field tsunami will increase by approx. 600% with 1 m RSLR by 2080–2130, and approx. 2,350% with 2 m RSLR by 2130–2140. These findings provide a useful baseline for tsunami hazard risk assessment under changing sea level conditions in analogous island environments.

In this paper we focus on an implicit assumption in the BSM framework that limits the scope of market network connections to seeking gains in the currency basis, i.e., on trading strategies between the numeraire and the stock and between the numeraire and the option, separately. We relax this assumption and derive the equivalent of the standard BSM approach under a more general market network framework in order to assess its implications. In doing so, we find that it is not possible to hedge the implicit option that allows one to directly trade the option and stock. This represents a potential challenge to the BSM framework, since the missing market network connection provides a potentially useful mechanism for risk-bearing portfolio managers to alter their portfolios.

We investigate the effect of geopolitical risk on the returns of the Information Technology, Communication Services, and Consumer Staples sector firms within the S&P 500 index. We use the event study methodology and perform more than 17,000 regressions to provide empirical evidence at the sector level that geopolitical risk leads to different responses across these 3 sectors. The response of the Information Technology sector is negative for all event windows under study, except the one spanning 10 days prior to the geopolitical event and 10 days after. The Communication Services sector has positive returns as a result of geopolitical events for all event windows, except the one from the geopolitical event date and 5 days after. The Consumer Staples sector shows a negative impact on geopolitical risk for all event windows except the one from the geopolitical event date and 5 days after, demonstrating a negative correlation to the Communication Services sector.

The Capital Asset Pricing Model is a widely applied model to describe risky markets and to deduce their systematic risk. Its estimation, therefore, remains an important task in Econo-financial studies. Empirically, it focuses on the impact of return interval on the betas. Existing studies somehow turn around the same idea of measuring the value of the beta according to the uniform intervals of time during a fixed period. However, it is noticed easily, and especially in the last decade that many factors such as socio-political, and Econo-environmental ones have led to a perturbation in the timeline of the worldwide development, and especially in countries and regions having political changes. This led us to introduce a new idea of risk estimation taking into account the non-uniform changes in markets by introducing a non-uniform wavelet analysis. We aim to explain the Econo-political situation of Arab spring countries and the effect of the revolutions on the market beta. The main novelty is firstly the construction of a dynamic backward-forward model for missing data, and next the application of random non-uniform wavelets. The proposed procedure will be acted empirically on a sample corresponding to TUNINDEX stock as a representative index of the Tunisian market actively traded over the period January 14, 2016, to January 13, 2021. The chosen 5-years period is important as it constitutes the first 5-years-after the revolution and depends strongly on the Socio-Econo-political stability in the revolutionary countries.

In recent years, there is a growing concern about the alarming spread of antimicrobial resistance (AMR) in different environments. Increasingly, many species of bacteria, fungi and viruses are becoming immune to the most commonly used pharmaceuticals. One of the causes of the development of the resistance is the persistence of these drugs, excreted by humans, in municipal and hospital wastewater (WW). Consequently, wastewater treatment plants (WWTPs) are a primary source of antimicrobial resistance genes as novel pollutants. This systematic review sought to examine the relevant literature on pharmaceutical residues (PRs) responsible for AMR in municipal and hospital WW in order to propose a classification of the PRs of greatest concern and provide an updated source for AMR management in WWTPs. Among 546 studies collected from four databases, 18 were included in the present review. The internal and external validity of each study was assessed, and the risk of bias was evaluated on a 20-parameter basis. Results were combined in a narrative synthesis discussing influents and effluents PR concentrations at 88 WWTPs, seasonal variations, differences between hospital and municipal WW, environmental risk assessment values of antimicrobial substances and treatment facilities removal efficiencies. Among the 45 PRs responsible for AMR evaluated in this study, the antibiotics ciprofloxacin, clarithromycin, erythromycin, metronidazole, ofloxacin, sulfamethoxazole and trimethoprim constitute a considerable risk in terms of ubiquitous distribution, worrying concentrations, risk quotients values, and resistance to removal treatments. Gaps in knowledge, data and information reported in this review provide a valuable source for managing AMR in WWTPs.

In the last decades farm animals kept in confined and mechanically ventilated livestock buildings are increasingly confronted with heat stress (HS) due to global warming. These adverse conditions cause a depression of animal health and welfare and a reduction of the performance up to an increase of the mortality. To facilitate sound management decisions, livestock farmers need relevant arguments, which quantify the expected economic risk and the corresponding uncertainty. The economic risk was determined for the pig fattening sector based on the probability of HS and the calculated decrease in the gross margin. The model calculation for confined livestock buildings showed, that HS indices calculated by easily available meteorological parameters can be used for assessment quantification of indoor HS, which is so far difficult to determine. These weather-related HS indices can be applied not only for an economic risk assessment but also for a weather-index based insurance for livestock farms. Based on the temporal trend between 1981 and 2017, a simple model was derived to assess the likelihood of HS for 2020 and 2030. Due to global warming, the return period for a 90-percentile HS index is reduced from 10 years in 2020 to 3-4 years in 2030. The economic impact of HS on livestock farms was calculated by the relationship between an HS index based on the temperature-humidity index (THI) and the reduction of the gross margin. From the likelihood of the HS and this economic impact function, the probability of the economic risk could be determined. The reduction of the gross margin for a 10 year return period was determined for 1980 with 0.27 € per year and animal place and increased by the 20-fold to 5.13 € per year and animal place in 2030.

Bovine tuberculosis (bTB) outbreaks, caused by Mycobacterium bovis infection, are a costly animal health challenge. Understanding factors associated with the duration of outbreaks, known as breakdowns, could lead to better disease management policy development. We undertook a retrospective observational study (2012-2018) and employed Finite Mixture Models (FMM) to model the outcome parameter, and to investigate how factors were associated with duration for differing subpopulations identified. In addition to traditional risk factors (e.g. herd size, bTB history), we also explored farm geographic area, parcels/farm fragmentation, metrics of intensity via nitrogen loading, and whether herds were designated controlled beef finishing units (CBFU) as potential risk factors for increased duration. The final model fitted log-normal distributions, with two latent classes (k) which partitioned the population into a subpopulation around the central tendency of the distribution, and a second around the tails of the distribution. The latter subpopulation included longer breakdowns of policy interest. Increasing duration was positively associated with recent (<3 yrs) TB history and the number of reactors disclosed, (log) herd size, beef herd-type relative to other herd types, number of land parcels, area, and being designated a controlled finishing unit (“feedlot”), and having high annual inward cattle movements within the “tails” subpopulation. Breakdown length was negatively associated with year of commencement of breakdown (i.e. a decreasing trend) and non-significantly with the organic nitrogen produced on the farm (N kg/hectare), a measure of stocking density. The latter finding may be due to confounding effects with herd size and area. Most variables contributed only moderately to explaining variation in breakdown duration, that is, they had moderate size effects on duration. Herd-size and CBFU had greater effect sizes on the outcome. The findings contribute to evidence-based policy formation in Ireland.

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread rapidly to most parts of the world, causing high numbers of deaths and significant social and economic impacts. SARS-CoV-2 is a novel coronavirus with a suggested zoonotic origin and with the potential for cross-species transmission among animals. Antarctica can be considered the only continent free of SARS-CoV-2 although at the end of the 2019-2020 tourist season, at least one SARS-CoV-2 positive tourist visited the Antarctic Peninsula. Therefore, concerns have been expressed regarding the potential human introduction of this virus to the continent through the activities of research or tourism with potential effects including those related to human health, but also the potential for virus transmission to Antarctic wildlife. This reverse-zoonotic transmission risk to Antarctic wildlife is assessed considering the available information on host susceptibility, dynamics of the infection in humans, and contact interactions between humans and Antarctic wildlife. Measures to reduce the risk are proposed as well as the identification of knowledge gaps related to this issue.

Consistent data is seldom available for whole-catchment flood modelling in many developing regions, thus this study demonstrates how the complementary strengths of open and readily available geospatial datasets and tools can be leverage to map flood risk within acceptable levels of uncertainty for flood risk management. Available fragmented remotely-sensed and in situ datasets (including hydrological data, altimetry, digital elevation model, bathymetry, aerial photos, optical and radar imageries) are systematically integrated using 2-dimensional CAESAR-LISFLOOD model to quantify and recreate the extent and impact of the historic 2012 flood in Nigeria. Experimental modelling, calibration and validation is undertaken for the whole Niger-South hydrological catchment area of Nigeria, then segmented into sub-domains for re-validation to understand how data variability and uncertainties impact on the accuracy of model outcomes. Furthermore, aerial photos are applied for the first time in the study area for flood model validation and to understand how different physio-environmental properties influence synthetic aperture radar flood delineation capacity in the Niger Delta region of Nigeria.

COVID-19 has affected 210 countries around the world, killed more than 240,000 and infected more than 3.4 million. Bangladesh, a South Asian low-middle-income economy, has experienced a demographic and epidemiological transition with rapid urbanization and a gradual increase in life expectancy. It is the seventh most populous country in the world and population of the country is expected to be nearly double by 2050. The increasing burden of noncommunicable diseases in Bangladesh can be attributable to rapid urbanization and nearly 50% of all slum dwellers of the country live in Dhaka division. In 2017, National Rapid Response Team of IEDCR investigated 26 incidents of disease outbreak. The joint survey of the Power and Participation Research Centre and BRAC Institute of Governance and Development reveals that per capita daily income of urban slum and rural poor drops by 80% due to present countrywide shutdown enforced by the government to halt the spread of Covid-19. 40%-50% of these population took loans to meet the daily expenses.

Introduction: Due to the spread of SARS CoV-2 virus responsible for COVID-19 disease, there is an urgent need to analyse COVID-19 epidemic perception in Poland. This study aims to investigate social perception of coronavirus in the Internet media during the epidemic. It is a signal report highlighting the main issues in public perception and medical commutation in real time. Methods: We study the perception of COVID-19 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet on platforms: Google, Twitter, YouTube, Wikipedia and electronic media represented by Event Registry, from January 2020 to 29.04.2020 (before and after official introduction to Poland on 04.03.20). We present trend analysis with a support of natural language processing techniques. Results: We identified seven temporal major clusters of interest on the topic COVID-19: 1) Chinese, 2) Italian, 3) Waiting, 4) Mitigations, 5) Social distancing and Lockdown, 6) Anti-crisis shield, 7) Restrictions releasing. There was an exponential increase of interest when the Polish government “declared war against disease” around 11/12.03.20 with a massive mitigation program. Later on, there was a decay in interest with additional phases related to social distancing and an anti-crisis legislation act with local peaks. We have found that declarations of mitigation strategies by the Polish prime minister or the minister of health gathered the highest attention of Internet users. So enacted or in force events do not affect interest to such extent. Traditional news agencies were ahead of social media (mainly Twitter) in dissemination of information. We have observed very weak or even negative correlations between a colloquial searching term 'antiviral mask' in Google, encyclopaedic definition in Wikipedia “SARS-CoV-2” as well official incidence series, implying different mechanisms governing the search for knowledge, panic related behaviour and actual risk of acquiring infection. Conclusions: Traditional and social media do not only reflect reality, but also create it. Risk perception in Poland is unrelated to actual physical risk of acquiring COVID-19. As traditional media are ahead of social media in time, we advise to choose traditional news media for a quick dissemination of information, however for a greater impact, social media should be used. Otherwise public information campaigns might have less impact on society than expected.

Trees in residential landscapes provide many benefits, but can injure persons and damage property when they fail. In hurricane-prone regions like Florida, USA, the regular occurrence of hurricanes has provided an opportunity to assess factors that influence the likelihood of wind-induced tree failure and develop species failure profiles. We assessed open-grown trees in Naples, Florida, following the passage of Hurricane Irma in September 2017 to determine the effect of relevant factors on the degree of damage sustained by individual trees. Of 4,034 assessed individuals (n = 15 species), 74% sustained no damage, 4% sustained only minor damage (i.e., minimal corrective pruning needed), 6% sustained significant damage (i.e., major corrective pruning needed), and 15% were whole tree failures (i.e., overturned trees or trees requiring removal). The proportion of individuals in each damage category varied among species, stem diameter at 1.4 m above ground, and the presence of utility lines, which was a proxy for maintenance. We compared our results with the findings of seven previous hurricanes in the region to explore species’ resilience in hurricanes.

The failure to acknowledge and account for environmental externalities or spillovers in climate change adaptation policy, advocacy and programming spaces exercabates the risk of ecological degradation, more so, degradation of land. In particular use of unsuitable water sources for irrigation may increase salinisation risks. However, little if any policy assessments and research effort has been directed at investigating how farmer perceptions mediate spillovers from the ubiquitous irrigation adaptation strategy. In this study cognitive failure and/or bias construct is examined and proposed as an analytical lens in research, policy and learning and the convergence of disaster risk reduction and climate change adaptation discourses. The findings from small-scale farmers, Machakos and Kakamega counties, Kenya, suggest multifaceted biases and failures about the existence and importance of externalities in adaptation planning discourses. Among other dimensions, cognitive failure which encompasses fragmented approaches among institutions for use and management of resources, inadequate policy and information support, as well as, poor integration of actors in adaptation planning accounts for adaptation failure. The failures in such Human-Environment system interactions have the potential to exercabate existing vulnerability of farmer production systems in the long run. The findings further suggest that in absence of risk message information dissemination, education level, farming experience and information accumulation, as integral elements to human capital, do not seem to have significant effect on behaviour about mitigation of environmental spillovers. Implicitly, reversing the inherent adaptation failures calls for system approaches that enhance coordinated adaptation planning, prioritises proactive mitigation of slow onset disaster risks and broadens decision support systems, such as, risk information dissemination integration into the existing adaptation policy discourses and practice.

LoRa and its upper layers definition LoRaWAN is one of the most promising LPWAN technologies for implementing the Internet of Things (IoT). Although being a popular technology, several works in the literature have revealed various weaknesses regarding the security of LoRaWAN v1.0 (the official 1st draft). By using all these recommendations from the academia and industry, the LoRa-Alliance has worked on the v1.0 to develop an enhanced version and provide more secure and trustable architecture. The result of these efforts ended-up with LoRaWAN v1.1, which was released on Oct 11, 2017. This manuscript aims at demystifying the security aspects and provide a comprehensive Security Risk Analysis related to latest version of LoRaWAN. Besides, it provides several remedies to the recognized vulnerabilities. To the best of authors’ knowledge, this work is one of its first kind by providing a detailed security analysis related to latest version of LoRaWAN. According to our analysis, end-device physical capture, rogue gateway and replay attacks are found to be threating for safety operation of the network. Eventually, v1.1 of LoRaWAN is found to be less vulnerable to attacks compared to v1.0, yet possesses several security implications that need to be addressed and fixed for the upcoming releases.

Disaster Risk Reduction (DRR) is a high priority on the agenda of main stakeholders involved in sustainable development and Earth Observation (EO) can provide useful, timely and economical information in this context. This short communication outlines the European Space Agency’s (ESA) specific initiative to promote the use and uptake of satellite data in the global development community: ‘Earth Observation for Sustainable Development (EO4SD)’. One activity area under EO4SD is devoted to Disaster Risk Reduction: EO4SD DRR. Within this project, a team of European companies and institutions are tasked to develop EO services for supporting the implementation of DRR in International Financial Institutions’ (IFI) projects. Integration of satellite-borne data and ancillary data to generate insight and actionable information is thereby considered a key factor for improved decision making. To understand and fully account for the essential user requirements (IFI & Client States), engagement with technical leaders is crucial. Fit-for-purpose use of data and comprehensive capacity building eventually ensure scalability and long-term transferability. Future perspectives of EO4SD and DRR regarding mainstreaming are also highlighted.

Background: Absolute uterine factor infertility (AUFI) is a kind of infertility that is completely attributable to uterine absence (surgical or congenital for women with Mayer-Rokitansky-Küster-Hauser syndrome: MRKH) or anatomic or functional abnormality that prevents embryo implantation or completion of pregnancy to term. Until recently, the only viable option to parenthood for couples with AUFI were adoption or surrogacy. Since a first attempt of uterus transplant (UTx) in 2000, nine babies were born from women with a transplanted uterus from 2014, eight of which in Sweden, and one in the United States. These promising results are raising immense hopes for the women with AUFI and there is optimism about the possibility for UTx to become part of clinical care even though, besides encouraging results, the procedure has also resulted in increased risks and harms for both the donors and recipients and increased risks of premature birth for the fetus. At present UTx is still considered as experimental and requiring more research and safety assessment before becoming a therapeutic option for AUFI. The transition from experimental procedure to therapeutic care would result in less strict ethical scrutiny for UTx and in the possibility for patients to get reimbursement for the procedure by the relevant healthcare insurance or public healthcare providers. In turn, an increase in the number of UTx performed yearly by specialized surgical teams would result in a general improvement of the “field strength”. However, at present it is difficult to establish the amount of evidence that we need in order to consider UTx as no longer experimental but routine clinical practice. The literature on UTx provides recommendations on the different outcomes that should be monitored in this experimental phase but no study is anticipating the number of subjects that should be followed and for how long. Conclusion: As for other transplants that have become routine practice, like renal transplant and heart transplant, it is likely that the decision on “routine practice readiness” will result from available cumulated evidences, from expert capacity to find a consensus on best practices and on political considerations as well, including pressures form patients and patient groups.