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Abstract Image quality assessment (IQA) is indispensable in clinical practice to ensure high standards, as well as in the development stage of machine learning algorithms that operate on medical images. The popular full reference (FR) IQA measures PSNR and SSIM are known and tested for working successfully in many natural imaging tasks, but discrepancies in medical scenarios have been reported in the literature, highlighting the gap between development and actual clinical application. Such inconsistencies are not surprising, as medical images have very different properties than natural images, and PSNR and SSIM have neither been targeted nor properly tested for medical images. This may cause unforeseen problems in clinical applications due to wrong judgement of novel methods. This paper provides a structured and comprehensive overview of examples where PSNR and SSIM prove to be unsuitable for the assessment of novel algorithms using different kinds of medical images, including real-world MRI, CT, OCT, X-Ray, digital pathology and photoacoustic imaging data. Therefore, improvement is urgently needed in particular in this era of AI to increase reliability and explainability in machine learning for medical imaging and beyond. Lastly, we will provide ideas for future research as well as suggest guidelines for the usage of FR-IQA measures applied to medical images. 

A critical question in relation to inter-agency coordination is not only whether, but how, to coordinate. This question is particularly salient when agencies are subject to a top-down mandate. While inter-agency coordination can provide multiple benefits, agencies frequently have concerns about the potential risks of coordination. Differing coordination mechanisms may reduce or exacerbate those concerns. Depending on their coordination concerns, agencies will be inclined to favor certain mechanisms over others. Examination of the implementation of California’s Sustainable Groundwater Management Act, which mandates local agency coordination, indicates that coordination mechanism selection is influenced by which combination of concerns agencies hold, with autonomy considerations taking priority over other concerns. These findings suggest opportunities to improve the explanatory power of theories of inter-agency coordination by incorporating potential hierarchies of concerns, their distribution across the multiple agencies tasked with coordinating, and configurational effects. To this end, we propose a contingency theory of agency concerns and coordination mechanism choice under a mandate to coordinate. 

Abstract Coordination mandates are used to steer collective action between local government agencies. When higher levels of government allow agencies to choose how to work together, the organizational forms and institutional arrangements they adopt likely influences their ability to achieve mandated coordinated outcomes. How group-level interactions influence achievement of coordinated outcomes is not well understood. California’s Sustainable Groundwater Management Act (SGMA) provides opportunity to shed light on this topic. SGMA is a state-legislative mandate that requires local agencies who share groundwater basins to undertake groundwater sustainability planning. The mandate affords agencies leeway in deciding how they engage with one another so long as they meet multiple requirements for coordinated outcomes. Drawing on institutional theories of collective action and ethnographic data collected from 2018 to 2022, we employ multi-value Qualitative Comparative Analysis to examine how configurations of organizational forms and institutional arrangements adopted by agencies in eighteen groundwater basins influenced their achievement of coordinated outcomes. Our findings highlight the importance of adopting collaborative institutional arrangements. Yet, the specific configuration of collaborative institutional arrangements varies depending on the type of coordinated outcomes agencies are mandated to achieve. These findings point to the need for mandates to require adoption of collaborative institutional arrangements, the specific configurations of which will be dictated by the requirements of the mandate. 

Public interest in where food comes from and how it is produced, processed, and distributed has increased over the last few decades, with even greater focus emerging during the COVID-19 pandemic. Mounting evidence and experience point to disturbing weaknesses in our food systems’ abilities to support human livelihoods and wellbeing, and alarming long-term trends regarding both the environmental footprint of food systems and mounting vulnerabilities to shocks and stressors. How can we tackle the “wicked problems” embedded in a food system? More specifically, how can convergent research programs be designed and resulting knowledge implemented to increase inclusion, sustainability, and resilience within these complex systems, support widespread contributions to and acceptance of solutions to these challenges, and provide concrete benchmarks to measure progress and understand tradeoffs among strategies along multiple dimensions? This article introduces and defines food systems informatics (FSI) as a tool to enhance equity, sustainability, and resilience of food systems through collaborative, user-driven interaction, negotiation, experimentation, and innovation within food systems. Specific benefits we foresee in further development of FSI platforms include the creation of capacity-enabling verifiable claims of sustainability, food safety, and human health benefits relevant to particular locations and products; the creation of better incentives for the adoption of more sustainable land use practices and for the creation of more diverse agro-ecosystems; the wide-spread use of improved and verifiable metrics of sustainability, resilience, and health benefits; and improved human health through better diets. 

We define sound and adequate denotational and operational semantics for the stochastic lambda calculus. These two semantic approaches build on previous work that used an explicit source of randomness to reason about higher-order probabilistic programs. 

Abstract. The Indian Ocean presents two distinct climate regimes. The north Indian Ocean is dominated by the monsoons, whereas the seasonal reversal is less pronounced in the south. The prevailing wind pattern produces upwelling along different parts of the coast in both hemispheres during different times of the year. Additionally, dynamical processes and eddies either cause or enhance upwelling. This paper reviews the phenomena of upwelling along the coast of the Indian Ocean extending from the tip of South Africa to the southern tip of the west coast of Australia. Observed features, underlying mechanisms, and the impact of upwelling on the ecosystem are presented. In the Agulhas Current region, cyclonic eddies associated with Natal pulses drive slope upwelling and enhance chlorophyll concentrations along the continental margin. The Durban break-away eddy spun up by the Agulhas upwells cold nutrient-rich water. Additionally, topographically induced upwelling occurs along the inshore edges of the Agulhas Current. Wind-driven coastal upwelling occurs along the south coast of Africa and augments the dynamical upwelling in the Agulhas Current. Upwelling hotspots along the Mozambique coast are present in the northern and southern sectors of the channel and are ascribed to dynamical effects of ocean circulation in addition to wind forcing. Interaction of mesoscale eddies with the western boundary, dipole eddy pair interactions, and passage of cyclonic eddies cause upwelling. Upwelling along the southern coast of Madagascar is caused by the Ekman wind-driven mechanism and by eddy generation and is inhibited by the Southwest Madagascar Coastal Current. Seasonal upwelling along the East African coast is primarily driven by the northeast monsoon winds and enhanced by topographically induced shelf breaking and shear instability between the East African Coastal Current and the island chains. The Somali coast presents a strong case for the classical Ekman type of upwelling; such upwelling can be inhibited by the arrival of deeper thermocline signals generated in the offshore region by wind stress curl. Upwelling is nearly uniform along the coast of Arabia, caused by the alongshore component of the summer monsoon winds and modulated by the arrival of Rossby waves generated in the offshore region by cyclonic wind stress curl. Along the west coast of India, upwelling is driven by coastally trapped waves together with the alongshore component of the monsoon winds. Along the southern tip of India and Sri Lanka, the strong Ekman transport drives upwelling. Upwelling along the east coast of India is weak and occurs during summer, caused by alongshore winds. In addition, mesoscale eddies lead to upwelling, but the arrival of river water plumes inhibits upwelling along this coast. Southeasterly winds drive upwelling along the coast of Sumatra and Java during summer, with Kelvin wave propagation originating from the equatorial Indian Ocean affecting the magnitude and extent of the upwelling. Both El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events cause large variability in upwelling here. Along the west coast of Australia, which is characterized by the anomalous Leeuwin Current, southerly winds can cause sporadic upwelling, which is prominent along the southwest, central, and Gascoyne coasts during summer. Open-ocean upwelling in the southern tropical Indian Ocean and within the Sri Lanka Dome is driven primarily by the wind stress curl but is also impacted by Rossby wave propagations. Upwelling is a key driver enhancing biological productivity in all sectors of the coast, as indicated by enhanced sea surface chlorophyll concentrations. Additional knowledge at varying levels has been gained through in situ observations and model simulations. In the Mozambique Channel, upwelling simulates new production and circulation redistributes the production generated by upwelling and mesoscale eddies, leading to observations of higher ecosystem impacts along the edges of eddies. Similarly, along the southern Madagascar coast, biological connectivity is influenced by the transport of phytoplankton from upwelling zones. Along the coast of Kenya, both productivity rates and zooplankton biomass are higher during the upwelling season. Along the Somali coast, accumulation of upwelled nutrients in the northern part of the coast leads to spatial heterogeneity in productivity. In contrast, productivity is more uniform along the coasts of Yemen and Oman. Upwelling along the west coast of India has several biogeochemical implications, including oxygen depletion, denitrification, and high production of CH4 and dimethyl sulfide. Although weak, wind-driven upwelling leads to significant enhancement of phytoplankton in the northwest Bay of Bengal during the summer monsoon. Along the Sumatra and Java coasts, upwelling affects the phytoplankton composition and assemblages. Dissimilarities in copepod assemblages occur during the upwelling periods along the west coast of Australia. Phytoplankton abundance characterizes inshore edges of the slope during upwelling season, and upwelling eddies are associated with krill abundance. The review identifies the northern coast of the Arabian Sea and eastern coasts of the Bay of Bengal as the least observed sectors. Additionally, sustained long-term observations with high temporal and spatial resolutions along with high-resolution modelling efforts are recommended for a deeper understanding of upwelling, its variability, and its impact on the ecosystem.