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Regional emulation tools based on statistical relationships, such as pattern scaling, provide a computationally inexpensive way of projecting ocean dynamic sea-level change for a broad range of climate change scenarios. Such approaches usually require a careful selection of one or more predictor variables of climate change so that the statistical model is properly optimized. Even when appropriate predictors have been selected, spatiotemporal oscillations driven by internal climate variability can be a large source of statistical model error. Using pattern recognition techniques that exploit spatial covariance information can effectively reduce internal variability in simulations of ocean dynamic sea level, significantly reducing random errors in regional emulation tools. Here, we test two pattern recognition methods based on empirical orthogonal functions (EOFs), namely signal-to-noise maximizing EOF pattern filtering and low-frequency component analysis, for their ability to reduce errors in pattern scaling of ocean dynamic sea-level change. We use the Max Planck Institute Grand Ensemble (MPI-GE) as a test bed for both methods, as it is a type of initial-condition large ensemble designed for an optimal characterization of the externally forced response. We show that the two methods tested here more efficiently reduce errors than conventional approaches such as a simple ensemble average. For instance, filtering only two realizations by characterizing their common response to external forcing reduces the random error by almost 60 %, a reduction that is only achieved by averaging at least 12 realizations. We further investigate the applicability of both methods to single-realization modeling experiments, including four CMIP5 simulations for comparison with previous regional emulation analyses. Pattern filtering leads to a varying degree of error reduction depending on the model and scenario, ranging from more than 20 % to about 70 % reduction in global-mean root mean

Sea-level rise amplifies the frequency of extreme sea levels by raising their baseline height. Amplifications are often projected for arbitrary future years and benchmark frequencies. Consequently, such projections do not indicate when flood risk thresholds may be crossed given the current degree of local coastal protection. To better support adaptation planning and comparative vulnerability analyses, we project the timing of the frequency amplification of extreme sea levels relative to estimated local flood protection standards, using sea-level rise projections of IPCC AR6 until 2150. Our central estimates indicate that those degrees of protection will be exceeded ten times as frequently within the next 30 years (the lead time that large adaptation measures may take) at 26% and 32% of the tide gauges considered, and annually at 4% and 8%, for a low- and high-emissions scenario, respectively. Adaptation planners may use our framework to assess the available lead time and useful lifetime of protective infrastructure.

[Aims] After primary radiotherapy, biochemical recurrence is defined according to the Phoenix criteria as a prostate-specific antigen (PSA) value >2 ng/ml relative to the nadir. Several studies have shown that prostate-specific membrane antigen (PSMA)-ligand positron emission tomography/computed tomography (PET/CT) can help in detecting recurrence in patients with low PSA values. This study aimed to assess the detection rate and patterns of PSMA-ligand PET/CT uptake in patients with suspected biochemical recurrence after primary radiotherapy and with PSA levels below the Phoenix threshold., [Materials and methods] The meta-analysis was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Articles providing data on patients with suspected prostate cancer recurrence after primary radiotherapy with a PSA value below the Phoenix threshold and who underwent PSMA-ligand PET/CT were included. Quality assessment was carried out using the Quality Assessment of Diagnostic Accuracy Studies-2 tool (QUADAS-2)., [Results] In total, five studies were included, recruiting 909 patients (202 with PSA ≤2 ng/ml). The PSMA-ligand detection rate in the patients with ≤2 ng/ml ranged from 66 to 83%. The most frequent source of PSMA-ligand PET/CT uptake was local recurrence, followed by lymph node metastasis and bone metastasis. PSMA-ligand PET/CT uptake due to local-only recurrence was more likely in patients with PSA ≤2 ng/ml compared with PSA > 2 ng/ml: risk ratio 0.72 (95% confidence interval 0.58–0.89), P = 0.003. No significant differences were observed in the detection of PSMA-ligand uptake in other areas. Limitations include a lack of biopsy confirmation, cohort reports with small sample sizes and a potentially high risk of bias., [Conclusion] A significant detection of PSMA-ligand-avid disease was observed in patients with PSA levels below the Phoenix threshold. There was a higher likelihood of detecting local-only uptake when the PSA value was ≤2 ng/ml. The findings suggest that a critical review of the Phoenix criteria may be warranted in the era of PSMA-ligand PET/CT and highlight the need for further prospective trials.

Babassu carbohydrate fibers (BCF) are abundant and renewable materials that are currently underutilized. The present work evaluates the use of alkaline-treated BCF (TF − 0.6, 1.0, 1.4% w/w) as additive to cementitious mortars. Mass consistency, specific mass, water absorption, void ratio, and porosity, as well as compressive and indirect tension fracture strengths, were evaluated and compared to control mortars (without fiber addition). The results confirmed that the treated BCF can be an effective alternative as a potential reinforcement in cementitious composites. Furthermore, they are prepared by an alkaline treatment that is easy to operate, cost-effective, and efficient. The addition of BCF to the cement matrix decreased the water absorption capacity and void ratio, whereas increased compressive and tensile strength compared to mortars prepared in the absence of BCF. In particular, the addition of 1.0% of TF increased the compressive strength by up to 77%. Good interfacial adhesion of the alkaline-treated BCF with the rest of mortar components resulted in an increase in the values of mechanical properties. The studied fibers are potential materials for new sustainable mortars with improved properties.