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Prior knowledge is often strongly related to students' learning. In the present research, we explored the relationship between prior knowledge and the accuracy of students' predictive monitoring judgments (judgments of learning; JOLs) and postdictive monitoring judgments (confidence judgments). In four experiments, students completed prior knowledge tests over two domains (football and cooking), learned new items from those domains, and completed a test over those items. To ensure the learning was new, the items that students learned and were tested over consisted of made-up facts from each domain. In Experiments 1-3, students made JOLs predicting the likelihood that they would remember each item on the test. In Experiments 2 and 3, students also made confidence judgments in the accuracy of their response after answering each question on the final test. Prior knowledge was negatively related to the accuracy of students' JOLs, but unrelated to the accuracy of their confidence judgments. Exploratory analyses revealed that the relationship with JOLs was likely driven by high knowledge students giving relatively lower JOLs to items that they later remembered. Experiment 4 directly tested this possibility by having students make binary memory predictions about whether they would remember each item. Outcomes were consistent with the exploratory analyses. Thus, the negative relationship between prior knowledge and JOL accuracy appears to be driven by the greater tendency of high knowledge students, relative to low knowledge students, to remember items that they thought they would forget.

Drawing on recent experimental research, we propose three ways in which artificial intelligence (AI) can be used to assess eyewitness identification accuracy. First, we suggest that AI could be used as an outside evaluator of eyewitness accuracy. AI could be exposed to identification evidence and left to make its own classification decisions. Second, AI could be used as a tool to inform human evaluators on the likely accuracy of an identification decision. This could range from clarifying witness information to providing evaluators with numeric estimates of accuracy. Third, AI could be used as a model of how human evaluators should go about assessing identification accuracy. Researchers could examine how successful AI models discriminate between accurate and inaccurate identification decisions and train human evaluators to use a similar algorithm. We contend that transparency and interpretability will be key ingredients in determining how AI impacts the legal system. [ABSTRACT FROM AUTHOR]

Despite being in use for over 25 years, long-term data regarding the Herbert ulnar head prosthesis remain scarce. The aim of the present multicentre observational study was to describe the survivorship of this implant in the UK. Retrospective data were collected from clinical records and via telephone consultation. Data were submitted for 227 primary and five revision ulnar head prostheses. Indications for surgery included distal radioulnar joint osteoarthritis, inflammatory arthritis and failed ulnar head resection surgery. The mean follow-up was 5.5 years (range 1 month–21 years) with 91% (n = 108) and 87% (n = 44) survival at 5 and 10 years, respectively. Indications for reoperation included pain, instability, aseptic loosening and distal impaction. In total, 12 patients had implant removal, eight had revision arthroplasty and five underwent soft tissue stabilization. Overall, reassuring mid- to long term survivorship data for the ulnar head prosthesis were found. We recommend the use of arthroplasty registries for implant surveillance. Level of evidence: IV [ABSTRACT FROM AUTHOR]

Restoring operation of critical infrastructure systems after catastrophic events is an important issue, inspiring work in multiple fields, including network science, civil engineering, and operations research. We consider the problem of finding the optimal order of repairing elements in power grids and similar infrastructure. Most existing methods either only consider system network structure, potentially ignoring important features, or incorporate component level details leading to complex optimization problems with limited scalability. We aim to narrow the gap between the two approaches. Analyzing realistic recovery strategies, we identify over- and undersupply penalties of commodities as primary contributions to reconstruction cost, and we demonstrate traditional network science methods, which maximize the largest connected component, are cost inefficient. We propose a novel competitive percolation recovery model accounting for node demand and supply, and network structure. Our model well approximates realistic recovery strategies, suppressing growth of the largest connected component through a process analogous to explosive percolation. Using synthetic power grids, we investigate the effect of network characteristics on recovery process efficiency. We learn that high structural redundancy enables reduced total cost and faster recovery, however, requires more information at each recovery step. We also confirm that decentralized supply in networks generally benefits recovery efforts.

Methane (CH4) is a powerful greenhouse gas and plays a key part in global atmospheric chemistry. Natural geological emissions (fossil methane vented naturally from marine and terrestrial seeps and mud volcanoes) are thought to contribute around 52 teragrams of methane per year to the global methane source, about 10 per cent of the total, but both bottom-up methods (measuring emissions) and top-down approaches (measuring atmospheric mole fractions and isotopes) for constraining these geological emissions have been associated with large uncertainties. Here we use ice core measurements to quantify the absolute amount of radiocarbon-containing methane (14CH4) in the past atmosphere and show that geological methane emissions were no higher than 15.4 teragrams per year (95 per cent confidence), averaged over the abrupt warming event that occurred between the Younger Dryas and Preboreal intervals, approximately 11,600 years ago. Assuming that past geological methane emissions were no lower than today, our results indicate that current estimates of today's natural geological methane emissions (about 52 teragrams per year) are too high and, by extension, that current estimates of anthropogenic fossil methane emissions are too low. Our results also improve on and confirm earlier findings that the rapid increase of about 50 per cent in mole fraction of atmospheric methane at the Younger Dryas-Preboreal event was driven by contemporaneous methane from sources such as wetlands; our findings constrain the contribution from old carbon reservoirs (marine methane hydrates, permafrost and methane trapped under ice) to 19 per cent or less (95 per cent confidence). To the extent that the characteristics of the most recent deglaciation and the Younger Dryas-Preboreal warming are comparable to those of the current anthropogenic warming, our measurements suggest that large future atmospheric releases of methane from old carbon sources are unlikely to occur.

It is generally agreed that proper pre-lineup instructions can reduce the rate of mistaken identifications of innocent suspects. However, the exact nature of these instructions has not been empirically established. We compared the effects of the detailed pre-lineup instructions recommended by the US Department of Justice to a simple instruction that the perpetrator may or may not be present. Both forms of unbiased instructions significantly reduced mistaken identifications when compared with biased instructions. Comparison of performance using the utility-based analysis deviation from perfect performance demonstrated that unbiased instructions are to be preferred under assumptions of low base rates or high costs of mistaken identifications and do as well as biased instructions under assumptions of high base rates or low cost of misidentification.

Simple Summary: Pancreatic cancer can be cured by surgical resection to clear margins, but this is difficult to achieve. The current methods to detect cancer spread during surgery are not very effective and many patients experience cancer returning soon after surgery. This integrative review analyses new technologies that could aid surgeons in detecting cancer more accurately during surgery. The aim is to identify methods that allow surgeons to distinguish cancerous tissues and subclinical deposits more precisely and reduce the risk of cancer recurrence. Fluorescence-guided surgery, where a light-emitting dye illuminates cancer cells, and other cancer localisation techniques are emerging as promising tools to aid oncological clearance during surgery. Accurate identification of cancer spread during surgery remains a clinical need and could change how surgeries for pancreatic cancer are conducted to prevent post-resection recurrence and improve survival. Background: Surgical resection for pancreatic ductal adenocarcinoma (PDAC) entails the excision of the primary tumour and regional lymphadenectomy. This traditional strategy is challenged by the high rate of early recurrence, suggesting inadequate disease staging. Novel methods of intra-operative staging are needed to allow surgical resection to be tailored to the disease's biology. Methods: A search of published articles on the PubMed and Embase databases was performed using the terms 'pancreas' OR 'pancreatic' AND 'intra-operative staging/detection' OR 'guided surgery'. Articles published between January 2000 and June 2023 were included. Technologies that offered intra-operative staging and tailored treatment were curated and summarised in the following integrative review. Results: lymph node (LN) mapping and radioimmunoguided surgery have shown promising results but lacked practicality to facilitate real-time intra-operative staging for PDAC. Fluorescence-guided surgery (FGS) offers high contrast and sensitivity, enabling the identification of cancerous tissue and positive LNs with improved precision following intravenous administration of a fluorescent agent. The unique properties of optical coherence tomography and ultrasound elastography lend themselves to be platforms for virtual biopsy intra-operatively. Conclusions: Accurate intra-operative staging of PDAC, localisation of metastatic LNs, and identification of extra-pancreatic disease remain clinically unmet needs under current detection methods and staging standards. Tumour-specific FGS combined with other diagnostic and therapeutic modalities could improve tumour detection and staging in patients with PDAC. [ABSTRACT FROM AUTHOR]

Over the past 45 years, psychological scientists have invested a tremendous amount of effort into increasing the accuracy of suspect identifications from eyewitness lineup procedures. Those efforts have paid dividends, leading to the development of several practices that increase the accuracy of suspect identifications. Meanwhile, lineup rejections have largely been written off as lacking diagnostic value and little effort has been placed into understanding (1) why lineup rejections are less diagnostic than suspect identifications, and (2) how to increase the diagnostic value of lineup rejections. We show that preventing innocent-suspect identifications is not equivalent to demonstrating innocence and highlight several consequences of not being able to clear innocent suspects from police suspicion. We then review recent evidence, grounded in Signal Detection Theory, suggesting that lineup rejections are less diagnostic than suspect identifications because it is harder to reject a lineup of several faces than it is to identify a single face. When lineups are modified so that witnesses provide rejection ratings for each non-identified lineup member, rejection accuracy drastically increases. We highlight several questions for future research examining the potential for eyewitness memory to demonstrate innocence and question what impact suspect rejections might play in multiple-witness cases. [ABSTRACT FROM AUTHOR]

Achieving high‐resolution and high signal‐to‐noise ratio (SNR) in vivo metabolic imaging via fast magnetic resonance spectroscopic imaging (MRSI) has been a longstanding challenge. This study combines the methods of relaxation enhancement (RE) and subspace imaging for the first time, enabling high‐resolution and high‐SNR in vivo MRSI of rodent brains at 9.4 T. Specifically, an RE‐based chemical shift imaging sequence, which combines a frequency‐selective pulse to excite only the metabolite frequencies with minimum perturbation of the water spins and a pair of adiabatic pulses to spatially localize the slice of interest, is designed and evaluated in vivo. This strategy effectively shortens the apparent T1 of metabolites, thereby increasing the SNR during relatively short repetition time ((TR) compared with acquisitions with only spatially selective wideband excitations, and does not require water suppression. The SNR was further enhanced via a state‐of‐the‐art subspace reconstruction method. A novel subspace learning strategy tailored for 9.4 T and RE acquisitions is developed. In vivo, high‐resolution (e.g., voxel size of 0.6 × 0.6 × 1.5 mm3) MRSI of both healthy mouse brains and a glioma‐bearing mouse brain in 12.5 min has been demonstrated. [ABSTRACT FROM AUTHOR]

This article seeks to pay tribute to John Taylor's scholarship in the field of the history of Australian double taxation agreements (DTAs). Referencing Taylor's formidable body of research, the article adopts a thematic approach to outline the history of New Zealand's DTAs, including tax treaties with Australia. [ABSTRACT FROM AUTHOR]