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In powder bed fusion additive manufacturing, machines are often equipped with in-situ sensors to monitor the build environment as well as machine actuators and subsystems. The data from these sensors offer rich information about the consistency of the fabrication process within a build and across builds. This information may be used for process monitoring and defect detection; however, little has been done to leverage this data from the machines for more than just coarse-grained process monitoring. In this work we demonstrate how these inherently temporal data may be mapped spatially by leveraging scan path information. We then train a XGBoost machine learning model to predict localized defects—specifically soot–using only the mapped process data of builds from a laser powder bed fusion process as input features. The XGBoost model offers a feature importance metric that will help to elucidate possible relationships between the process data and observed defects. Finally, we analyze the model performance spatially and rationalize areas of greater and lesser performance.

Background: While considered the mainstay of treatment for specific bone metastases, ZA is used predominantly to treat osteolytic lesions. The purpose of this network meta-analysis is to compare ZA to other treatment options in its ability to improve specific clinical outcomes in patients with bone metastases secondary to any primary tumor. Methods: PubMed, Embase and Web of Science were systematically searched from inception to May 5th, 2022. Keywords used were solid tumor, lung neoplasm, kidney neoplasm, breast neoplasm, prostate neoplasm, ZA and bone metastasis. Every randomized controlled trial and non-randomized quasi-experimental study of systemic ZA administration for patients with bone metastases and any comparator were included. A Bayesian network meta-analysis was done on the primary outcomes including number of SREs, time to developing a first on-study SRE, overall survival, and disease progression-free survival. Secondary outcome was pain at 3, 6 and 12 months after treatment. Results: Our search yielded 3861 titles with 27 meeting inclusion criteria. For the number of SRE, ZA in combination with chemotherapy or hormone therapy was statistically superior to placebo (OR 0.079; 95 % CrI: 0.022–0.27). For the time to the first on study SRE, the relative effectiveness of ZA 4 mg was statistically superior to placebo (HR 0.58; 95 % CrI:0.48–0.77). At 3 and 6 months, ZA 4 mg was significantly superior to placebo for reducing pain with a SMD of −0.85 (95 % CrI:-1.6, −0.0025) and −2.6 (95 % CrI:-4.7, −0.52) respectively. Conclusions: This systematic review shows the benefits of ZA in decreasing the incidence of SREs, increasing the time to the first on-study SRE, and reducing the pain level at 3 and 6 months.

Capturing wild capybaras for scientific projects, population control or medical interventions is a growing necessity. With this study, we intended to evaluate a Ketamine/Dexmedetomidine as a reversible chemical restraint in free-ranging synanthropic capybaras, seeking enhanced anesthetic and recovery characteristics while testing a specialized remote drug delivery system (RDDS). For this purpose, 18 adult capybaras (male n = 8; females n = 10) (67.3 ± 9.45 kg), prior to chemical restraint, were physically confined, subsequently darted intramuscularly with 9 mg kg-1 ketamine and 0,005 mg kg-1 dexmedetomidine. Post-intervention, 0,005 mg kg-1 atipamezole, administered IM, was used as a reversal agent (RA), (n = 5). Anesthetic effects were recorded as latency period (LP I/first observed effects) (LP II /lateral recumbency plus time to handle the animal). Recovery time was divided into (R1/no RA, fully recovered/ready for release), (R2a/R2b, with RA, time to ambulant position plus time to full recovery/release, respectively). Vital signs were recorded at a 15-minute interval. GraphPad Prism 8.1.1 was used to perform unpaired t-test, with a p-value ˂ 0,05 considered significant. Results: Mean LP I: 3 ± 1 min.; LP II: 10 ± 2 min. Procedure duration: 49 ± 5 min. Recovery time without RA, (R1): 55 ± 15 min., compared to 18 min., with RA (R2a) to ambulant position (with severe discoordination), requiring additional time until full recovery (ready for release): ± 45 min (R2b). Total time, to release (R2a/b): mean ± SD = 67 ± 13.85 min. Concluding for clinical relevance that the association of Ketamine and Dexmedetomidine performed satisfactorily, providing effective sedation and analgesia, and relative short latency periods. Used RA did not shorten total recovery time significantly (P-value = 0,7328). Adverse effects such as the risk of acute cecal tympany, due to the lack of pre-anesthetic fasting, concurrent to collateral effects of injectable and volatile anesthetics on the motility of the digestive tract, and induced bradycardia/hyperthermia warrant extra caution. The employed RDDS provided reliable drug delivery under field conditions.

Societies worldwide make large investments in the sustainability of integrated human-freshwater systems, but uncertainty about water supplies under climate change poses a major challenge. Investments in infrastructure, water regulation, or payments for ecosystem services may boost water availability, but may also yield poor returns on investment if directed to locations where water supply unexpectedly fluctuates due to shifting climate. How should investments in water sustainability be allocated across space and among different types of projects? Given the high costs of investments in water sustainability, decision-makers are typically risk-intolerant, and considerable uncertainty about future climate conditions can lead to decision paralysis. Here, we use mathematical optimization models to find Pareto-optimal satisfaction of human and environmental water needs across a large drought-prone river basin for a range of downscaled climate projections. We show how water scarcity and future uncertainty vary independently by location, and that joint consideration of both factors can provide guidance on how to allocate water sustainability investments. Locations with high water scarcity and low uncertainty are good candidates for high-cost, high-reward investments; locations with high scarcity but also high uncertainty may benefit most from low regret investments that minimize the potential for stranded assets if water supply increases. Given uncertainty in climate projections in many regions worldwide, our analysis illustrates how explicit consideration of uncertainty may help to identify the most effective strategies for investments in the long-term sustainability of integrated human-freshwater systems.