Nature-based Solutions (NbS) are actions that harness nature to help address major societal challenges. The assessment frameworks for NbS proposed in the literature differ in scope and intended use. In 2020, the International Union for Conservation of Nature (IUCN) introduced their Global Standard for NbS as a framework that can be used by anyone working on different types of NbS. Since research on the applicability of the IUCN Standard remains limited, the aim of this paper is to analyse whether the IUCN Standard may be used as an overarching assessment framework for NbS in river flood management applications and to identify the main differences in content with other NbS-frameworks. This was achieved through a comparison with 29 assessment frameworks for NbS, that are applicable to physical interventions for riverine flood risk reduction. The comparisons showed that the IUCN Standard has the largest breadth in scope of application and may therefore be used as an overarching framework. In addition, we identified a distinction between frameworks for the assessment of project processes (process-oriented) and project results (results-oriented), where the IUCN Standard can be characterized as process-oriented. This implies that the IUCN Standard may be used to assess the processes (e.g. stakeholder engagement and adaptive management) of planned, ongoing or completed NbS projects for a wide variety of environmental contexts and societal challenges. This will help persuade policy makers to consider NbS as one of the solutions in flood management issues, next to or in combination with e.g. engineering solutions or changing land use. We also identified that, while the IUCN Standard is straightforward to use and incorporates stakeholder input, the environmental context specificity as well as guidance depth on resources for assessment can be improved.

Many Oil and Gas (O&G) fields in the North Sea have produced their economically recoverable reserves and have entered the decommissioning phase or are close to cessation of production. The subsequent O&G decommissioning process involves a range of stakeholders with specific interests and priorities. This range of inputs to the process highlights the necessity for the development of multi-criteria decision frameworks to help guide the decision-making process. This study presents bottom-up formulations for the economic, environmental, and safety risk criteria to support the multi-criteria decision analysis within the Comparative Assessment (CA) of O&G pipeline decommissioning projects in the North Sea. The approach adapts current guidelines in the O&G industry and considers a range of parameters to provide estimations for the costs, energy usage, greenhouse gas emissions, and safety risks. To verify the effectiveness of the proposed bottom-up formulations, the longest oil export pipeline in the Brent field, PL001/N0501 is selected as a case study. The numerical results revealed the consistency of the results obtained from the proposed approach with those reported in the technical documents by industry. In most cases, the formulations provide estimates with less than 10% differences for the costs, energy usage, emissions, and safety risks. Based on the proposed multi-criteria formulations, the study also presents the use of an immersive decision-making environment within a marine simulator system to help inform the decision-making process by stakeholders.

BACKGROUND: The online pharmacy market is growing, with legitimate online pharmacies offering advantages such as convenience and accessibility. However, this increased demand has attracted malicious actors into this space, leading to the proliferation of illegal vendors that use deceptive techniques to rank higher in search results and pose serious public health risks by dispensing substandard or falsified medicines. Search engine providers have started integrating generative artificial intelligence (AI) into search engine interfaces, which could revolutionize search by delivering more personalized results through a user-friendly experience. However, improper integration of these new technologies carries potential risks and could further exacerbate the risks posed by illicit online pharmacies by inadvertently directing users to illegal vendors.
OBJECTIVE: The role of generative AI integration in reshaping search engine results, particularly related to online pharmacies, has not yet been studied. Our objective was to identify, determine the prevalence of, and characterize illegal online pharmacy recommendations within the AI-generated search results and recommendations.
METHODS: We conducted a comparative assessment of AI-generated recommendations from Google\'s Search Generative Experience (SGE) and Microsoft Bing\'s Chat, focusing on popular and well-known medicines representing multiple therapeutic categories including controlled substances. Websites were individually examined to determine legitimacy, and known illegal vendors were identified by cross-referencing with the National Association of Boards of Pharmacy and LegitScript databases.
RESULTS: Of the 262 websites recommended in the AI-generated search results, 47.33% (124/262) belonged to active online pharmacies, with 31.29% (82/262) leading to legitimate ones. However, 19.04% (24/126) of Bing Chat\'s and 13.23% (18/136) of Google SGE\'s recommendations directed users to illegal vendors, including for controlled substances. The proportion of illegal pharmacies varied by drug and search engine. A significant difference was observed in the distribution of illegal websites between search engines. The prevalence of links leading to illegal online pharmacies selling prescription medications was significantly higher (P=.001) in Bing Chat (21/86, 24%) compared to Google SGE (6/92, 6%). Regarding the suggestions for controlled substances, suggestions generated by Google led to a significantly higher number of rogue sellers (12/44, 27%; P=.02) compared to Bing (3/40, 7%).
CONCLUSIONS: While the integration of generative AI into search engines offers promising potential, it also poses significant risks. This is the first study to shed light on the vulnerabilities within these platforms while highlighting the potential public health implications associated with their inadvertent promotion of illegal pharmacies. We found a concerning proportion of AI-generated recommendations that led to illegal online pharmacies, which could not only potentially increase their traffic but also further exacerbate existing public health risks. Rigorous oversight and proper safeguards are urgently needed in generative search to mitigate consumer risks, making sure to actively guide users to verified pharmacies and prioritize legitimate sources while excluding illegal vendors from recommendations.

OBJECTIVE: Written medicine information (WMI) is important for ensuring patients understand and use their medicines optimally, but relatively little research has assessed the quality of available WMI. This study assessed the quality of WMI using a sample of leaflets for ibuprofen in the UK and Thailand.
METHODS: Leaflets were obtained by purchasing a product from retail outlets or community pharmacies, 18 from each country. In the UK, these were patient information leaflets (PILs); in Thailand, they were package inserts PIs not specifically designed for patients. Leaflets were assessed for content, layout, and readability using standard methods and compared to relevant guidelines.
RESULTS: The UK PILs were uniform and conformed to EU regulatory requirements for content, whereas Thai PIs varied considerably, many failing to include important information required by Thai regulations. Several forms of Thai PIs were found, including some very short leaflets, containing minimal information. The readability of both was rated as poor, all used small font size and had less than desirable white space. Fewer Thai PIs than UK PILs met the Keystone Criteria for ibuprofen.
CONCLUSIONS: The extent of variation in format and content of Thai WMI could potentially cause confusion and reduce willingness to read it. PILs, conforming to Thai regulatory guidelines, should be provided with medicines instead. Leaflets in both countries would benefit from improved readability and layout.

Genetic improvement mainly depends on the level of genetic variability present in the population, and the degree of genetic diversity in a population largely determines the rate of genetic advancement. For analyzing genetic diversity and determining cultivar identities, a molecular marker is a useful tool. Using 30 SSR (simple sequence repeat) and 30 RAPD (randomly amplified polymorphic DNA) markers, this study evaluated the genetic divergence of 17 mango cultivars. The effectiveness of the two marker systems was evaluated using their genetic diversity characteristics. Additionally, the effects of SM (simple matching) and Dice similarity coefficients and their effects on mango clustering were evaluated. The findings showed that SSR markers generated 192 alleles, all of which were polymorphic (100%). With RAPD markers, 434 bands were obtained, 361 of which were polymorphic (83%). The average polymorphic information content (PIC) for RAPD and SSR was 0.378 and 0.735, respectively. Using SSR markers resulted in much higher values for other genetic diversity parameters compared to RAPD markers. Furthermore, grouping the genotypes according to the two similarity coefficients without detailed consideration of these coefficients could not influence the study results. The RAPD markers OPA_01, OPM_12 followed by OPO_12 and SSR markers MIAC_4, MIAC_5 followed by mMiCIR_21 were the most informative in terms of describing genetic variability among the cultivars under study; they can be used in further investigations such as genetic mapping or marker-assisted selection. Overall, \'Zebda\' cultivar was the most diverse of the studied cultivars.

In this study, utilization of a bio-based fuel in a turbojet engine is comprehensively monitored with adapting various useful indicators for the scope of the study based on thermodynamic principles. In this regard, extensive energy and exergy, thermoecologic, environmental, enviroeconomic and sustainability analyses are performed for both the turbojet engines fueled by jet kerosene and fueled by a bio-based fuel. As per the main findings, the mass stream of combustion emissions is measured to be 4.547 kg s-1, when the engine is powered by biofuel. The specific fuel consumption and specific thrust are determined as 0.13 kg kN-1 s-1 and 147.81 kNs kg-1 for jet kerosene-powered case, while they are calculated as 0.15 kg kN-1 s-1 and 148.23 kNs kg-1 for biofuel-powered case. If biofuel is selected over jet-kerosene fuel, it is observed that the engine has better energy efficiency performance by 18.18%. The engine\'s environmental effect factor value is found as 4.88 for jet-kerosene usage condition, while it is found to be 4.93 for biofuel utilization case. The overall emitted CO2 emissions is measured as 336,672 kg-CO2 year-1 for jet-kerosene usage condition, while it is estimated as 222,012 kg-CO2 year-1 for the biofuel utilization case. Also, as far as biofuel is chosen as alternative to jet-kerosene, the environmental damage cost stream, namely the enviroeconomic parameter of the engine, falls from 59,254.27 US$ year-1 to 39,074.11 US$ year-1. It is observed that sustainable efficiency factor and exergetic sustainability index outputs of the components of air compressor are the same for jet-kerosene and biofuel utilization cases, which are 8.31 and 7.31, respectively.

This paper makes the first comparative assessment of the impacts of the first and second waves of the ongoing COVID-19 pandemic for the US stock market and its uncertainty. To this end, we investigate the dynamic conditional correlation and the asymmetric impacts of shocks on the correlation between the US and Chinese stock markets before and during the COVID-19 crisis. Furthermore, we analyze and compare the relationship between the COVID-19 pandemic and US returns and uncertainty during the first and second waves of the pandemic. First, we find that the dynamic correlation approach supports the presence of volatility spillovers (contagion effects) between the two stock markets, especially during the rapid spread phase of COVID-19 in the US. Second, the analysis of news impact correlation surfaces shows that the shocks to the US and Chinese markets have asymmetric effects on the correlation between the two markets. Finally, we find a persistent link between US returns, uncertainty, and the COVID-19 pandemic during the first and second waves of the outbreak. Our results prove that the pandemic has shown harmful consequences for financial markets in general and the US economy in particular.

Light-driven photocatalytic (PC) and photoelectrocatalytic (PEC) systems are vital technologies being extensively explored for wastewater treatment and energy production. Although the photo(electro)catalytic applications in both the energy production and wastewater remediation function on the similar principle of photo-induced charge transfer, most preceding research has been focused on either the energy recovery or wastewater treatment as these two applications demand distinct reaction parameters and catalyst properties. The present review reveals the scientific progress in dual-functional PC and PEC processes that enable simultaneous energy recovery (e.g., H2 generation) with wastewater treatment (e.g., degradation of organic pollutants). The key concept in the dual-functional photo(electro)catalytic system is to use both the electron reduction power for recovering H2 from wastewater and hole oxidation power for degrading pollutants in wastewater simultaneously. Herein, a detailed and comprehensive overview of the advancement in various PC and PEC processes with dual-functional purpose is discussed, highlighting the advantages and disadvantages of different systems and performance comparison based on diverse metrics tools. Although in its infancy, this dual-functional technology has gained scientific interest over the past few years; this is expected, as this approach can overcome multiple major environmental challenges, such as water scarcity, global warming, and pollution. The review should offer current limitations and prospects for developing next-generation solar-driven dual-functional techniques based on the water-energy nexus.

Effects of different extraction acids on physicochemical, structural, and functional properties of wampee fruit peel pectin (WFPP) were comparatively investigated. The hydrochloric acid extracted WFPP (HEP) exhibited the highest degrees of methylation (67.79%) and acetylation (86.29%) coupling with abundant monosaccharides and rhamnogalacturonan branches, but lowest molecular weight (5.58 × 105 Da). The results of SEM, X-ray diffraction, and Fourier transform infrared spectroscopy analyses showed that acid types had little effect on the surface morphology of WFPP. However, compared to commercial citrus pectin (CCP), several specific absorbance peaks (1539, 1019, 920 cm-1) were found in WFPPs, which corresponds to aromatic skeletal stretching, pyranose, and d-glucopyranosyl, respectively. Moreover, the rheological behavior revealed that WFPP solution was pseudoplastic fluid and affected by acid types. And the WFPPs exhibited higher emulsifying activity and emulsion stability than CCP. All these WFPPs presented well antioxidant activity and promoting probiotics ability, especially for HEP.

UNASSIGNED: The accurate definition of gross tumor volume (GTV) of esophageal squamous cell carcinoma (ESCC) can promote precise irradiation field determination, and further achieve the radiotherapy curative effect. This retrospective study is intended to assess the applicability of leveraging deep learning-based method to automatically define the GTV from 3D 18F-FDG PET/CT images of patients diagnosed with ESCC.
UNASSIGNED: We perform experiments on a clinical cohort with 164 18F-FDG PET/CT scans. The state-of-the-art esophageal GTV segmentation deep neural net is first employed to delineate the lesion area on PET/CT images. Afterwards, we propose a novel equivalent truncated elliptical cone integral method (ETECIM) to estimate the GTV value. Indexes of Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean surface distance (MSD) are used to evaluate the segmentation performance. Conformity index (CI), degree of inclusion (DI), and motion vector (MV) are used to assess the differences between predicted and ground truth tumors. Statistical differences in the GTV, DI, and position are also determined.
UNASSIGNED: We perform 4-fold cross-validation for evaluation, reporting the values of DSC, HD, and MSD as 0.72 ± 0.02, 11.87 ± 4.20 mm, and 2.43 ± 0.60 mm (mean ± standard deviation), respectively. Pearson correlations (R2) achieve 0.8434, 0.8004, 0.9239, and 0.7119 for each fold cross-validation, and there is no significant difference (t = 1.193, p = 0.235) between the predicted and ground truth GTVs. For DI, a significant difference is found (t = -2.263, p = 0.009). For position assessment, there is no significant difference (left-right in x direction: t = 0.102, p = 0.919, anterior-posterior in y direction: t = 0.221, p = 0.826, and cranial-caudal in z direction: t = 0.569, p = 0.570) between the predicted and ground truth GTVs. The median of CI is 0.63, and the gotten MV is small.
UNASSIGNED: The predicted tumors correspond well with the manual ground truth. The proposed GTV estimation approach ETECIM is more precise than the most commonly used voxel volume summation method. The ground truth GTVs can be solved out due to the good linear correlation with the predicted results. Deep learning-based method shows its promising in GTV definition and clinical radiotherapy application.