Mercury abatement in the environment: Insights from industrial emissions and fates in the environment

Mercury's neurotoxic effects have prompted the development of advanced control and remediation methods to meet stringent measures for industries with high-mercury feedstocks. Industries with significant Hg emissions, including artisanal and small-scale gold mining (ASGM)-789.2 Mg year-1, coal combustion-564.1 Mg year-1, waste combustion-316.1 Mg year-1, cement production-224.5 Mg year-1, and non-ferrous metals smelting-204.1 Mg year-1, use oxidants and adsorbents capture Hg from waste streams. Oxidizing agents such as O3, Cl2, HCl, CaBr2, CaCl2, and NH4Cl oxidize Hg0 to Hg2+ for easier adsorption. To functionalize adsorbents, carbonaceous ones use S, SO2, and Na2S, metal-based adsorbents use dimercaprol, and polymer-based adsorbents are grafted with acrylonitrile and hydroxylamine hydrochloride. Adsorption capacities span 0.2-85.6 mg g-1 for carbonaceous, 0.5-14.8 mg g-1 for metal-based, and 168.1-1216 mg g-1 for polymer-based adsorbents. Assessing Hg contamination in soils and sediments uses bioindicators and stable isotopes. Remediation approaches include heat treatment, chemical stabilization and immobilization, and phytoremediation techniques when contamination exceeds thresholds. Achieving a substantially Hg-free ecosystem remains a formidable challenge, chiefly due to the ASGM industry, policy gaps, and Hg persistence. Nevertheless, improvements in adsorbent technologies hold potential.

Biochar influences nitrogen and phosphorus dynamics in two texturally different soils

Nitrogen (N) and phosphorus (P) are vital for crop growth. However, most agricultural systems have limited inherent ability to supply N and P to crops. Biochars (BCs) are strongly advocated in agrosystems and are known to improve the availability of N and P in crops through different chemical transformations. Herein, a soil-biochar incubation experiment was carried out to investigate the transformations of N and P in two different textured soils, namely clay loam and loamy sand, on mixing with rice straw biochar (RSB) and acacia wood biochar (ACB) at each level (0, 0.5, and 1.0% w/w). Ammonium N (NH4-N) decreased continuously with the increasing incubation period. The ammonium N content disappeared rapidly in both the soils incubated with biochars compared to the unamended soil. RSB increased the nitrate N (NO3-N) content significantly compared to ACB for the entire study period in both texturally divergent soils. The nitrate N content increased with the enhanced biochar addition rate in clay loam soil until 15 days after incubation; however, it was reduced for the biochar addition rate of 1% compared to 0.5% at 30 and 60 days after incubation in loamy sand soil. With ACB, the net increase in nitrate N content with the biochar addition rate of 1% remained higher than the 0.5% rate for 60 days in clay loam and 30 days in loamy sand soil. The phosphorus content remained consistently higher in both the soils amended with two types of biochars till the completion of the experiment.

Environmental behavior of silver nanomaterials in aquatic environments: An updated review

The increasing applications of silver nanomaterials (nano-Ag) and their inevitable release posed great potential risks to aquatic organisms and ecosystems. Considerable attention has been attracted on their behaviors and transformations, which were critically important for their subsequent biological toxicities and ecological effects. Therefore, the summary of the recent efforts on the environmental behavior of nano-Ag would be beneficial for understanding the environmental fate and accurate risk assessment. This review summarized the studies on various physical, chemical and biological transformations of nano-Ag, meanwhile, the influencing factors (including the intrinsic properties and environmental conditions) and related mechanisms were highlighted. Surface structure and facets of nano-Ag, abiotic conditions and natural freeze-thaw cycle processes could affect the transformations of nano-Ag under different environmental scenarios (including freshwater, seawater and wastewater). The interactions with co-present components, such as chemicals and other particles, impacted the multiple processes of nano-Ag. Besides, the contradictory effects and mechanisms by several environmental factors were summarized. Lastly, the key knowledge gaps and some aspects that deserve further investigation were also addressed. Therefore, the current review aimed to provide an overall analysis of transformation processes of nano-Ag, which will provide more available information and pave the way for the future research areas.

Inferring shape transformations in a drawing task

Many objects and materials in our environment are subject to transformations that alter their shape. For example, branches bend in the wind, ice melts, and paper crumples. Still, we recognize objects and materials across these changes, suggesting we can distinguish an object's original features from those caused by the transformations ("shape scission"). Yet, if we truly understand transformations, we should not only be able to identify their signatures but also actively apply the transformations to new objects (i.e., through imagination or mental simulation). Here, we investigated this ability using a drawing task. On a tablet computer, participants viewed a sample contour and its transformed version, and were asked to apply the same transformation to a test contour by drawing what the transformed test shape should look like. Thus, they had to (i) infer the transformation from the shape differences, (ii) envisage its application to the test shape, and (iii) draw the result. Our findings show that drawings were more similar to the ground truth transformed test shape than to the original test shape-demonstrating the inference and reproduction of transformations from observation. However, this was only observed for relatively simple shapes. The ability was also modulated by transformation type and magnitude but not by the similarity between sample and test shapes. Together, our findings suggest that we can distinguish between representations of original object shapes and their transformations, and can use visual imagery to mentally apply nonrigid transformations to observed objects, showing how we not only perceive but also 'understand' shape.

Unlocking and accelerating transformations to the SDGs: a review of existing knowledge

As we cross the 2030 deadline to achieve the Sustainable Development Goals (SDGs), there is a growing sense of urgency around the need to accelerate the necessary transformations. These encompass a broad range of systems and require fundamental changes in system goals and design. In this paper, we undertake a narrative review of the literature relating to the acceleration of transformations and offer a framework for unlocking and accelerating transformations to the SDGs. While there is no blueprint for acceleration, there is an expanding knowledge base on important dynamics, impediments and enabling conditions across diverse literatures which can help to inform strategic interventions by actors. The emerging literature on positive tipping points and deep leverage points identifies opportunities to rewire systems design so that important system feedbacks create the conditions for acceleration. Transformation takes time and actors will need to build momentum to reorient systems around new goals, informed by knowledge of common policy, technology and behavioural feedbacks that govern system dynamics. Where resistance is strong, actors can seek to augment system design in ways that weaken balancing feedbacks that stabilise existing system configurations and strengthen reinforcing feedbacks that promote emerging system configurations oriented towards the SDGs. Well-designed and sequenced interventions can promote innovation and behaviour change and build and maintain political support. This can build critical enabling conditions and push systems towards large-scale tipping points, paving the way for decisive policy action that is crucial for triggering acceleration. We conclude by highlighting gaps and priorities for further research.

Modelling count, bounded and skewed continuous outcomes in physical activity research: beyond linear regression models

BACKGROUND

Inference using standard linear regression models (LMs) relies on assumptions that are rarely satisfied in practice. Substantial departures, if not addressed, have serious impacts on any inference and conclusions; potentially rendering them invalid and misleading. Count, bounded and skewed outcomes, common in physical activity research, can substantially violate LM assumptions. A common approach to handle these is to transform the outcome and apply a LM. However, a transformation may not suffice.

METHODS

In this paper, we introduce the generalized linear model (GLM), a generalization of the LM, as an approach for the appropriate modelling of count and non-normally distributed (i.e., bounded and skewed) outcomes. Using data from a study of physical activity among older adults, we demonstrate appropriate methods to analyse count, bounded and skewed outcomes.

RESULTS

We show how fitting an LM when inappropriate, especially for the type of outcomes commonly encountered in physical activity research, substantially impacts the analysis, inference, and conclusions compared to a GLM.

CONCLUSIONS

GLMs which more appropriately model non-normally distributed response variables should be considered as more suitable approaches for managing count, bounded and skewed outcomes rather than simply relying on transformations. We recommend that physical activity researchers add the GLM to their statistical toolboxes and become aware of situations when GLMs are a better method than traditional approaches for modeling count, bounded and skewed outcomes.

Is the EU shirking responsibility for its deforestation footprint in tropical countries? Power, material, and epistemic inequalities in the EU's global environmental governance

This paper critically examines the European Union's (EU) role in tropical deforestation and the bloc's actions to mitigate it. We focus on two EU policy communications aimed at the challenge: stepping up EU action to protect and restore the world's forests and the EU updated bioeconomy strategy. In addition, we refer to the European Green Deal, which articulates the bloc's overarching vision for sustainability and transformations. We find that by casting deforestation as a production problem and a governance challenge on the supply side, these policies deflect attention from some of the key drivers of tropical deforestation-the EU's overconsumption of deforestation-related commodities and asymmetric market and trade power relations. The diversion allows the EU unfettered access to agro-commodities and biofuels, which are important inputs to the EU's green transition and bio-based economy. Upholding a 'sustainability image' within the EU, an overly business-as-usual approach has taken precedence over transformative policies, enabling multinational corporations to run an ecocide treadmill, rapidly obliterating tropical forests. Whereas the EU's plan to nurture a bioeconomy and promote responsible agro-commodities production in the global South are relevant, the bloc is evasive in setting firm targets and policy measures to overcome the inequalities that spring from and enable its overconsumption of deforestation-related commodities. Drawing on degrowth and decolonial theories, we problematise the EU's anti-deforestation policies and highlight alternative ideas that could lead to more just, equitable and effective measures for confronting the tropical deforestation conundrum.

Are stakeholders ready to transform phosphorus use in food systems? A transdisciplinary study in a livestock intensive system

Food systems worldwide are vulnerable to Phosphorus (P) supply disruptions and price fluctuations. Current P use is also highly inefficient, generating large surpluses and pollution. Global food security and aquatic ecosystems are in jeopardy if transformative action is not taken. This paper pivots from earlier (predominantly conceptual) work to develop and analyse a P transdisciplinary scenario process, assessing stakeholders potential for transformative thinking in P use in the food system. Northern Ireland, a highly livestock-intensive system, was used as case study for illustrating such process. The stakeholder engagement takes a normative stance in that it sets the explicit premise that the food system needs to be transformed and asks stakeholders to engage in a dialogue on how that transformation can be achieved. A Substance Flow Analysis of P flows and stocks was employed to construct visions for alternative futures and stimulate stakeholder discussions on system responses. These were analysed for their transformative potential using a triple-loop social learning framework. For the most part, stakeholder responses remained transitional or incremental, rather than being fundamentally transformative. The process did unveil some deeper levers that could be acted upon to move the system further along the spectrum of transformational change (e.g. changes in food markets, creation of new P markets, destocking, new types of land production and radical land use changes), providing clues of what an aspirational system could look like. Replicated and adapted elsewhere, this process can serve as diagnostics of current stakeholders thinking and potential, as well as for the identification of those deeper levers, opening up avenues to work upon for global scale transformation.

Beyond "blah blah blah": exploring the "how" of transformation

Calls for transformations are clear and multiple pathways and alternative visions for the future have been defined. Yet, there is very little shared understanding of how such transformations come about and how knowledge-action gaps will be filled. This Special Feature focuses on how we can go beyond talking about transformation-the "blah blah blah"-and moving toward action for results. It does so by distinguishing between the means of transformation and the manner of transformation, two key dimensions to answering the question of "how." The means can be understood as the many solutions, technical and practical methods, or actions that are presented as significant to transformative change. The manner, in contrast, represents the ways in which something is done, i.e., ways of acting. It describes the core values, principles, qualities, and relationships that not only underpin and motivate transformative change, but shape the process. Integrating rather than conflating the means and the manner is important to better understand how transformations come about. We then present insights from the collection of papers that focus on the "how" of transformation. The papers describe different ways of integrating the means and the manner in transformation processes. We have organized them thematically as follows: papers that draw on the integration of meaning making, the integration of learning and listening, and the integration of different ways of being and becoming. Drawing on both science and alternative ways of knowing, they weave together new narratives and stories about nature, society, and the future, inviting us to embark on the journey of creating sustainability pathways.

Envisioning just transformations in and beyond the EU bioeconomy: inspirations from decolonial environmental justice and degrowth

The European Union (EU) is adhering to decarbonization of its economy to tackle what is narrowly framed as 'environmental issues' of our socioecological and civilizational crises-including, but not limited to, climate change and biodiversity loss. A shift to bio-based economy (bioeconomy) is an important component of this effort. This paper applies theoretical ideas from decolonial environmental justice and degrowth, placed in the wider context of transformations, to analyse the EU bioeconomy policy within the global context, and to draw lessons and recommendations for just transformations in the EU bioeconomy policy. I identify five dominant logics and approaches in the EU bioeconomy that act as barriers for just transformations and propose alternative ones that can support such transformations. Barriers and alternatives include (1) framing 'nature' as a resource and service provider for humans, who are seen as separate from nature, and the need to abandon human-nature duality; (2) dominance of economic green growth and technoscientific policy solutions, and the need to place planetary justice at the centre of tackling socioecological crises; (3) a limited approach to justice, and the need to act upon climate and epistemic justice, including self-determination and self-governing authority; (4) the EU's ambition for global leadership and competitiveness in global bioeconomic markets and governance, and the need to redefine global governance towards partnerships based on the principles of solidarity, mutual respect, reconciliation and redistribution of power and wealth; (5) hegemonic politico-economic structures and actor coalitions in charge of the EU bioeconomy, and the need for decentralized bottom-up leadership coalitions that promote direct democracy, local autonomy and sovereignty beyond state. I conclude with reflections on the politics of change and risks of co-optation, with a hope to inspire decolonial and just socioecological transformations in and beyond bioeconomy.

A new mathematical model of multi-faced COVID-19 formulated by fractional derivative chains

It has been reported that there are seven different types of coronaviruses realized by individuals, containing those responsible for the SARS, MERS, and COVID-19 epidemics. Nowadays, numerous designs of COVID-19 are investigated using different operators of fractional calculus. Most of these mathematical models describe only one type of COVID-19 (infected and asymptomatic). In this study, we aim to present an altered growth of two or more types of COVID-19. Our technique is based on the ABC-fractional derivative operator. We investigate a system of coupled differential equations, which contains the dynamics of the diffusion between infected and asymptomatic people. The consequence is accordingly connected with a macroscopic rule for the individuals. In this analysis, we utilize the concept of a fractional chain. This type of chain is a fractional differential-difference equation combining continuous and discrete variables. The existence of solutions is recognized by formulating a matrix theory. The solution of the approximated system is shown to have a minimax point at the origin.

Transforming landscapes and mindscapes through regenerative agriculture

Agriculture occupies 38% of the planet's terrestrial surface, using 70% of freshwater resources. Its modern practice is dominated by an industrial-productivist discourse, which has contributed to the simplification and degradation of human and ecological systems. As such, agricultural transformation is essential for creating more sustainable food systems. This paper focuses on discursive change. A prominent discursive alternative to industrial-productivist agriculture is regenerative agriculture. Regenerative discourses are emergent, radically evolving and diverse. It is unclear whether they have the potential to generate the changes required to shift industrial-productivist agriculture. This paper presents a literature-based discourse analysis to illustrate key thematic characteristics of regenerative agricultural discourses. The analysis finds that such discourses: situate agricultural work within nested, complex living systems; position farms as relational, characterised by co-evolution between humans and other landscape biota; perceive the innate potential of living systems as place-sourced; maintain a transformative openness to alternative thinking and practice; believe that multiple regenerative cultures are necessary for deeply regenerative agriculture; and depart from industrialism to varying degrees. The paper concludes by reviewing three transformative opportunities for regenerative discourses-discourse coalitions, translocal organising and collective learning.

SUPPLEMENTARY INFORMATION

The online version supplementary material available at 10.1007/s10460-021-10276-0.

Proximal humeral coordinate systems can predict humerothoracic and glenohumeral kinematics of a full bone system

BACKGROUND

Clinical imaging often excludes the distal humerus, confounding definition of common whole-bone coordinate systems. While proximal anatomy coordinate systems exist, no simple method transforms them to whole-bone systems. Their influence on humeral kinematics is unknown.

RESEARCH QUESTION

How do humeral kinematics vary based on proximal and whole-bone coordinate systems, and can average rotation matrices accurately convert kinematics between them?

METHODS

Three proximal coordinate systems were defined by the lesser and greater tuberosities (LT, GT), Crest of the greater tuberosity, and humeral shaft. Average rotation matrices derived from anatomic landmarks on cadaver humeri were generated between the proximal and whole-bone coordinate systems. Absolute angle of rotation was used to determine if anatomical variability within the cadaver population influenced the matrices. The matrices were applied to humerothoracic and glenohumeral motion (collected previously) and analyzed using the proximal coordinate systems, then expressed in the whole-bone system. RMSE was used to compare kinematics from the proximal and whole-bone systems.

RESULTS

A single average rotation matrix between a given proximal and whole-bone coordinate system achieved consistent error, regardless of landmarks. Elevation and plane of elevation had <2° mean error when proximal coordinate systems were transformed to whole-bone kinematics. Axial rotation had a mean 7° error, primarily due to variable humeral head retroversion. Absolute angles of rotation did not statistically differ between subgroups. The average rotation matrices were independent of sex, side, and motion.

SIGNIFICANCE

Proximal humerus coordinate systems can accurately predict whole-bone kinematics, with most error concentrated in axial rotation due to anatomic twist along the bone. These results enhance interpretability and reproducibility in expressing humerothoracic and glenohumeral motion data between laboratories by providing a simple means to convert data between common coordinate systems. This is necessitated by the lack of distal humerus anatomy present in most clinical imaging.

Theme: Urbanization

In this perspective, we present how three initial landmark papers on urban sustainability research contributed to the larger sustainability science scholarship and paved the way for the continued development of urban sustainability research. Based on this, we propose three conceptual innovation pathways to trace the progression of urban sustainability science: First, urban sustainability from a system's perspective, meaning that urban sustainability requires integrative solutions to work in the tripled social-ecological-technological system setting. Second, urban sustainability from a (people and place) relational perspective, meaning urban sustainability is a contested and dynamic social-ecological contract of cities. As a governance mission, urban sustainability requires evidence from research that can inform coordinated action to bridge people, places, meanings, visions and ecosystems. Third, urban sustainability from a transformative science perspective, meaning that for urban sustainability to be achieved and progressed, deep transformations are required in systems, relations, policies and governance approaches. Our proposal for the future of urban sustainability science centres on emphasizing the relevance and policy applicability of systems' thinking, value and place thinking and transitions/transformations thinking as fundamental to how knowledge is co-produced by research science, policy and society and becomes actionable.

Metabolomics: An analytical technique for food processing evaluation

This review aimed to retrieve the most recent research with strong impact concerning the application of metabolomics analysis in food processing. The literature reveals the high capacity of this methodology to evaluate chemical and organoleptic transformations that occur during food production. Current and potential applications of metabolomics analysis will be addressed, focusing on process-composition-function relationships. The use of the metabolomics approach to evaluate transformations in foods submitted to minimal processes, heat or cold treatments, drying, fermentation, chemical and enzymatic treatments and processes using innovative technologies will be discussed. Moreover, the main strategies and advantages of metabolomics-based approaches are reviewed, as well as the most used analytical platforms. Overall, metabolomics can be seen as an important tool to support academia and industry on pursuing knowledge about the transformation of raw animal or plant materials into ready-to-eat products.

The NanoInformatics Knowledge Commons: Capturing spatial and temporal nanomaterial transformations in diverse systems

The empirical necessity for integrating informatics throughout the experimental process has become a focal point of the nano-community as we work in parallel to converge efforts for making nano-data reproducible and accessible. The NanoInformatics Knowledge Commons (NIKC) Database was designed to capture the complex relationship between nanomaterials and their environments over time in the concept of an 'Instance'. Our Instance Organizational Structure (IOS) was built to record metadata on nanomaterial transformations in an organizational structure permitting readily accessible data for broader scientific inquiry. By transforming published and on-going data into the IOS we are able to tell the full transformational journey of a nanomaterial within its experimental life cycle. The IOS structure has prepared curated data to be fully analyzed to uncover relationships between observable phenomenon and medium or nanomaterial characteristics. Essential to building the NIKC database and associated applications was incorporating the researcher's needs into every level of development. We started by centering the research question, the query, and the necessary data needed to support the question and query. The process used to create nanoinformatic tools informs usability and analytical capability. In this paper we present the NIKC database, our developmental process, and its curated contents. We also present the Collaboration Tool which was built to foster building new collaboration teams. Through these efforts we aim to: 1) elucidate the general principles that determine nanomaterial behavior in the environment; 2) identify metadata necessary to predict exposure potential and bio-uptake; and 3) identify key characterization assays that predict outcomes of interest.

Multiple isotopic compositions reveal complex nitrogen cycling in a subtropical estuary

Nitrogen (N) pollution and the resulting eutrophication can have deleterious consequences on estuaries, such as hypoxia, fish kills, and loss of biotic diversity. An understanding of N sources and cycling in estuaries is fundamental to determining how to effectively manage these ecologically and commercially important areas. We applied a multiple-isotopic approach to examine the transformations and sources of the N pools in the Pearl River Estuary (PRE) during winter. The surface water in the West PRE was characterized by low salinity and high NO₃^-, while that in the east had high salinity and low NO₃^-. The NO₃^- in the West PRE was largely regulated by a conservative mixing process. In contrast, assimilation and nitrification dominated in the East PRE, which was attributed to the long water-residence time. For the first time, the source contributions of NO₃^- and NH₄⁺ were estimated by isotope mixing models. Our results suggest that river discharge and nitrification contributed 81% and 12% to the NO₃^- pool, respectively. A major portion (68%) of the NH₄⁺ was from river discharge, with the remainder likely from sewage and the aquitard-aquifer system. Our study demonstrates that internal nitrification can potentially be of pivotal importance in determining the NO₃^- level in an estuary and its export to coastal waters.

Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI

BACKGROUND

Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance is only achieved in the narrow tasks networks are trained on. Performance drops dramatically when data characteristics differ from the training set properties. Moreover, neural networks are commonly considered black boxes, because it is hard to understand how they make decisions and why they fail. Therefore, it is also hard to predict whether they will generalize and work well with new data. Here we present a generic method for segmentation model interpretation. Sensitivity analysis is an approach where model input is modified in a controlled manner and the effect of these modifications on the model output is evaluated. This method yields insights into the sensitivity of the model to these alterations and therefore to the importance of certain features on segmentation performance.

RESULTS

We present an open-source Python library (misas), that facilitates the use of sensitivity analysis with arbitrary data and models. We show that this method is a suitable approach to answer practical questions regarding use and functionality of segmentation models. We demonstrate this in two case studies on cardiac magnetic resonance imaging. The first case study explores the suitability of a published network for use on a public dataset the network has not been trained on. The second case study demonstrates how sensitivity analysis can be used to evaluate the robustness of a newly trained model.

CONCLUSIONS

Sensitivity analysis is a useful tool for deep learning developers as well as users such as clinicians. It extends their toolbox, enabling and improving interpretability of segmentation models. Enhancing our understanding of neural networks through sensitivity analysis also assists in decision making. Although demonstrated only on cardiac magnetic resonance images this approach and software are much more broadly applicable.

Isotopic Composition Reveals the Impact of Oyster Aquaculture on Pelagic Nitrogen Cycling in a Subtropical Estuary

To offset estuarine eutrophication, interest is increasing in restoring oyster reefs and expanding oyster aquaculture. However, ecosystem-scale evidence is lacking on oyster assemblages' impacts on estuarine pelagic nitrogen (N) cycling. Using a multiple-isotope approach and isotope-mixing model, we examined the sources, transformations, and influence of intensive oyster aquaculture on N pollution in a subtropical estuary. The salinity-dependent NO₃^- and NH₄⁺ concentrations and their correlations with isotopic signals (δ¹⁵N-NO₃^-, δ¹⁸O-NO₃^-, δ¹⁵N-NH₄⁺) indicated the nutrient spatial distribution in low-salinity areas was largely regulated by mixing between freshwater and seawater. However, the intensive oyster aquaculture greatly increased nitrification in the estuary. In high-salinity areas where oyster assemblages were absent, the assimilation of NO₃^- by phytoplankton became dominant and sharply increased the δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-. Soil organic nitrogen and fertilizer, domestic sewage, and wastewater treatment plants were the major NO₃^- sources in the estuary, while internal nitrification contributed 20.6% to the NO₃^- pool. Oyster biodeposits comprised up to one-third of the particulate organic matter in the water column, and as much as 47.3% of the NH₄⁺ pool could be from the oysters. Our study shows that oysters significantly contribute to the pelagic nutrient pools and N transformations, adding an important dimension to our understanding of oyster assemblages' impacts on estuarine N cycling.

Unravelling the effect of data augmentation transformations in polyp segmentation

PURPOSE

Data augmentation is a common technique to overcome the lack of large annotated databases, a usual situation when applying deep learning to medical imaging problems. Nevertheless, there is no consensus on which transformations to apply for a particular field. This work aims at identifying the effect of different transformations on polyp segmentation using deep learning.

METHODS

A set of transformations and ranges have been selected, considering image-based (width and height shift, rotation, shear, zooming, horizontal and vertical flip and elastic deformation), pixel-based (changes in brightness and contrast) and application-based (specular lights and blurry frames) transformations. A model has been trained under the same conditions without data augmentation transformations (baseline) and for each of the transformation and ranges, using CVC-EndoSceneStill and Kvasir-SEG, independently. Statistical analysis is performed to compare the baseline performance against results of each range of each transformation on the same test set for each dataset.

RESULTS

This basic method identifies the most adequate transformations for each dataset. For CVC-EndoSceneStill, changes in brightness and contrast significantly improve the model performance. On the contrary, Kvasir-SEG benefits to a greater extent from the image-based transformations, especially rotation and shear. Augmentation with synthetic specular lights also improves the performance.

CONCLUSION

Despite being infrequently used, pixel-based transformations show a great potential to improve polyp segmentation in CVC-EndoSceneStill. On the other hand, image-based transformations are more suitable for Kvasir-SEG. Problem-based transformations behave similarly in both datasets. Polyp area, brightness and contrast of the dataset have an influence on these differences.

Reliable interpretation of scapular kinematics depends on coordinate system definition

BACKGROUND

Interpretation of shoulder motion across studies has been complicated due to the use of numerous scapular coordinate systems in the literature. Currently, there are no simple means by which to compare scapular kinematics between coordinate system definitions when data from only one coordinate system is known.

RESEARCH QUESTION

How do scapular kinematics vary based on the choice of coordinate system and can average rotation matrices be used to accurately convert kinematics between scapular local coordinate systems?

METHODS

Average rotation matrices derived from anatomic landmarks of 51 cadaver scapulae (29 M/22 F; 59 ± 13 yrs; 26R/25 L; 171 ± 11 cm; 70 ± 19 kg; 23.7 ± 5.5 kg/m²) were generated between three common scapular coordinate systems. Absolute angle of rotation was used to determine if anatomical variability within the cadaver population influenced the matrices. To quantify the predictive capability to convert kinematics between the three coordinate systems, the average rotation matrices were applied to scapulothoracic motion data collected from 19 human subjects (10 M/9 F; 43 ± 17 yrs; 19R; 173 ± 9 cm; 71 ± 16 kg; 23.6 ± 4.5 kg/m²) using biplane fluoroscopy. Root mean squared error (RMSE) was used to compare kinematics from an original coordinate system to the kinematics expressed in each alternative coordinate system.

RESULTS

The choice of scapular coordinate system resulted in mean differences in scapulothoracic rotation of up to 23°, with overall different shapes and/or magnitudes of the curves. A single average rotation matrix between any two coordinate systems achieved accurate conversion of scapulothoracic kinematics to within 4° of RMSE of the known solution. The average rotation matrices were independent of sex, side, decomposition sequence, and motion.

SIGNIFICANCE

Scapulothoracic kinematic representations vary in shape and magnitude based solely on the choice of local coordinate system. The results of this study enhance interpretability and reproducibility in expressing scapulothoracic motion data between laboratories by providing a simple means to convert data between common coordinate systems. This is necessitated by the variety of available motion analysis techniques and their respective scapular landmark definitions.

Five pillars for stakeholder analyses in sustainability transformations: The global case of phosphorus

Phosphorus is a critical agricultural nutrient and a major pollutant in waterbodies due to inefficient use. In the form of rock phosphate it is a finite global commodity vulnerable to price shocks and sourcing challenges. Transforming toward sustainable phosphorus management involves local to global stakeholders. Conventional readings of stakeholders may not reflect system complexity leaving it difficult to see stakeholder roles in transformations. We attempt to remedy this issue with a novel stakeholder analysis method based on five qualitative pillars: stakeholder agency, system roles, power and influence, alignment to the problem, and transformational potential. We argue that our approach suits case studies of individual stakeholders, stakeholder groups, and organisations with relationships to sustainability challenges.

Characterizing diversity of food systems in view of sustainability transitions. A review

Dominant food systems are configured from the productivist paradigm, which focuses on producing large amounts of inexpensive and standardized foods. Although these food systems continue being supported worldwide, they are no longer considered fit-for-purpose as they have been proven unsustainable in environmental and social terms. A large body of scientific literature argues that a transition from the dominant food systems to alternative ones built around the wider principles of sustainable production and rural development is needed. Promoting such a sustainability transition would benefit from a diagnosis of food system types to identify those systems that may harbor promising characteristics for a transition to sustainable food systems. While research on food system transitions abounds, an operational approach to characterize the diversity of food systems taking a system perspective is still lacking. In this paper we review the literature on how transitions to sustainable food systems may play out and present a framework based on the Multi-Level Perspective on Socio-Technical Transitions, which builds upon conceptual developments from social and natural science disciplines. The objectives of the framework are to (i) characterize the diversity of existing food systems at a certain geographical scale based on a set of structural characteristics and (ii) classify the food systems in terms of their support by mainstream practices, i.e., dominant food systems connected to regimes; deviate radically from them, niche food systems such as those based on grassroots innovation; or share elements of dominant and niche food systems, i.e., hybrid food systems. An example is given of application of our framework to vegetable food systems with a focus on production, distribution, and consumption of low-or-no pesticide vegetables in Chile. Drawing on this illustrative example we reflect on usefulness, shortcomings, and further development and use of the diagnostic framework.

Transformation and bioavailability of metal oxide nanoparticles in aquatic and terrestrial environments. A review

Metal oxide nanoparticles (MeO-NPs) are among the most consumed NPs and also have wide applications in various areas which increased their release into the environmental system. Aquatic (water and sediments) and terrestrial compartments are predicted to be the destination of the released MeO-NPs. In these compartments, the particles are subjected to various dynamic processes such as physical, chemical and biological processes, and undergo transformations which drive them away from their pristine state. These transformation pathways can have strong implications for the fate, transport, persistence, bioavailability and toxic-effects of the NPs. In this critical review, we provide the state-of-the-knowledge on the transformation processes and bioavailability of MeO-NPs in the environment, which is the topic of interest to researchers. We also recommend future research directions in the area which will support future risk assessments by enhancing our knowledge of the transformation and bioavailability of MeO-NPs.

Lipase catalysis in organic solvents: advantages and applications

Lipases are industrial biocatalysts, which are involved in several novel reactions, occurring in aqueous medium as well as non-aqueous medium. Furthermore, they are well-known for their remarkable ability to carry out a wide variety of chemo-, regio- and enantio-selective transformations. Lipases have been gained attention worldwide by organic chemists due to their general ease of handling, broad substrate tolerance, high stability towards temperatures and solvents and convenient commercial availability. Most of the synthetic reactions on industrial scale are carried out in organic solvents because of the easy solubility of non-polar compounds. The effect of organic system on their stability and activity may determine the biocatalysis pace. Because of worldwide use of lipases, there is a need to understand the mechanisms behind the lipase-catalyzed reactions in organic solvents. The unique interfacial activation of lipases has always fascinated enzymologists and recently, biophysicists and crystallographers have made progress in understanding the structure-function relationships of these enzymes. The present review describes the advantages of lipase-catalyzed reactions in organic solvents and various effects of organic solvents on their activity.

Manufactured nanoparticles in the aquatic environment-biochemical responses on freshwater organisms: A critical overview

The enormous investments in nanotechnology have led to an exponential increase of new manufactured nano-enabled materials whose impact in the aquatic systems is still largely unknown. Ecotoxicity and nanosafety studies mostly resulted in contradictory results and generally failed to clearly identify biological patterns that could be related specifically to nanotoxicity. Generation of reactive oxygen species (ROS) is one of the most discussed nanotoxicity mechanism in literature. ROS can induce oxidative stress (OS), resulting in cyto- and genotoxicity. The ROS overproduction can trigger the induction of anti-oxidant enzymes such as catalase (CAT), superoxide dismutase (SOD) and glutathione peroxidases (GPx), which are used as biomarkers of response. A critical overview of the biochemical responses induced by the presence of NPs on freshwater organisms is performed with a strong interest on indicators of ROS and general stress. A special focus will be given to the NPs transformations, including aggregation, and dissolution, in the exposure media and the produced biochemical endpoints.

Toxic trace elements at gastrointestinal level

Many trace elements are considered essential [iron (Fe), zinc (Zn), copper (Cu)], whereas others may be harmful [lead (Pb), cadmium (Cd), mercury (Hg), arsenic (As)], depending on their concentration and chemical form. In most cases, the diet is the main pathway by which they enter our organism. The presence of toxic trace elements in food has been known for a long time, and many of the food matrices that carry them have been identified. This has led to the appearance of legislation and recommendations concerning consumption. Given that the main route of exposure is oral, passage through the gastrointestinal tract plays a fundamental role in their entry into the organism, where they exert their toxic effect. Although the digestive system can be considered to be of crucial importance in their toxicity, in most cases we do not know the events that occur during the passage of these elements through the gastrointestinal tract and of ascertaining whether they may have some kind of toxic effect on it. The aim of this review is to summarize available information on this subject, concentrating on the toxic trace elements that are of greatest interest for organizations concerned with food safety and health: Pb, Cd, Hg and As.

Transformation priming helps to disambiguate sudden changes of sensory inputs

Retinal input is riddled with abrupt transients due to self-motion, changes in illumination, object-motion, etc. Our visual system must correctly interpret each of these changes to keep visual perception consistent and sensitive. This poses an enormous challenge, as many transients are highly ambiguous in that they are consistent with many alternative physical transformations. Here we investigated inter-trial effects in three situations with sudden and ambiguous transients, each presenting two alternative appearances (rotation-reversing structure-from-motion, polarity-reversing shape-from-shading, and streaming-bouncing object collisions). In every situation, we observed priming of transformations as the outcome perceived in earlier trials tended to repeat in subsequent trials and this repetition was contingent on perceptual experience. The observed priming was specific to transformations and did not originate in priming of perceptual states preceding a transient. Moreover, transformation priming was independent of attention and specific to low level stimulus attributes. In summary, we show how "transformation priors" and experience-driven updating of such priors helps to disambiguate sudden changes of sensory inputs. We discuss how dynamic transformation priors can be instantiated as "transition energies" in an "energy landscape" model of the visual perception.

Dinucleotide circular codes and bijective transformations

The presence of circular codes in mRNA coding sequences is postulated to be involved in informational mechanisms aimed at detecting and maintaining the normal reading frame during protein synthesis. Most of the recent research is focused on trinucleotide circular codes. However, also dinucleotide circular codes are important since dinucleotides are ubiquitous in genomes and associated to important biological functions. In this work we adopt the group theoretic approach used for trinucleotide codes in Fimmel et al. (2015) to study dinucleotide circular codes and highlight their symmetry properties. Moreover, we characterize such codes in terms of n-circularity and provide a graph representation that allows to visualize them geometrically. The results establish a theoretical framework for the study of the biological implications of dinucleotide circular codes in genomic sequences.

Fate of zinc and silver engineered nanoparticles in sewerage networks

Engineered zinc oxide (ZnO) and silver (Ag) nanoparticles (NPs) used in consumer products are largely released into the environment through the wastewater stream. Limited information is available regarding the transformations they undergo during their transit through sewerage systems before reaching wastewater treatment plants. To address this knowledge gap, laboratory-scale systems fed with raw wastewater were used to evaluate the transformation of ZnO- and Ag-NPs within sewerage transfer networks. Two experimental systems were established and spiked with either Ag- and ZnO-NPs or with their dissolved salts, and the wastewater influent and effluent samples from both systems were thoroughly characterised. X-ray absorption spectroscopy (XAS) was used to assess the extent of the chemical transformation of both forms of Zn and Ag during transport through the model systems. The results indicated that both ZnO- and Ag-NPs underwent significant transformation during their transport through the sewerage network. Reduced sulphur species represented the most important endpoint for these NPs in the sewer with slight differences in terms of speciation; ZnO converted largely to Zn sulfide, while Ag was also sorbed to cysteine and histidine. Importantly, both ionic Ag and Ag-NPs formed secondary Ag sulfide nanoparticles in the sewerage network as revealed by TEM analysis. Ag-cysteine was also shown to be a major species in biofilms. These results were verified in the field using recently developed nanoparticle in situ deployment devices (nIDDs) which were exposed directly to sewerage network conditions by immersing them into a municipal wastewater network trunk sewer and then retrieving them for XAS analysis.

Towards optimal clinical and epidemiological registration of haematological malignancies: Guidelines for recording progressions, transformations and multiple diagnoses

Haematological malignancies (HM) represent over 6% of the total cancer incidence in Europe and affect all ages, ranging between 45% of all cancers in children and 7% in the elderly. Thirty per cent of childhood cancer deaths are due to HM, 8% in the elderly. Their registration presents specific challenges, mainly because HM may transform or progress in the course of the disease into other types of HM. In the context of cancer registration decisions have to be made about classifying subsequent notifications on the same patient as the same tumour (progression), a transformation or a new tumour registration. Allocation of incidence date and method of diagnosis must also be standardised. We developed European Network of Cancer Registries (ENCR) recommendations providing specific advice for cancer registries to use haematology and molecular laboratories as data sources, conserve the original date of incidence in case of change of diagnosis, make provision for recording both the original as well as transformed tumour and to apply precise rules for recording and counting multiple diagnoses. A reference table advising on codes which reflect a potential transformation or a new tumour is included. This work will help to improve comparability of data produced by population-based cancer registries, which are indispensable for aetiological research, health care planning and clinical research, an increasing important area with the application of targeted therapies.

Perception of shape and space across rigid transformations

Objects in our environment are subject to manifold transformations, either of the physical objects themselves or of the object images on the retina. Despite drastic effects on the objects' physical appearances, we are often able to identify stable objects across transformations and have strong subjective impressions of the transformations themselves. This suggests the brain is equipped with sophisticated mechanisms for inferring both object constancy, and objects' causal history. We employed a dot-matching task to study in geometrical detail the effects of rigid transformations on representations of shape and space. We presented an untransformed 'base shape' on the left side of the screen and its transformed counterpart on the right (rotated, scaled, or both). On each trial, a dot was superimposed at a given location on the contour (Experiment 1) or within and around the shape (Experiment 2). The participant's task was to place a dot at the corresponding location on the right side of the screen. By analyzing correspondence between responses and physical transformations, we tested for object constancy, causal history, and transformation of space. We find that shape representations are remarkably robust against rotation and scaling. Performance is modulated by the type and amount of transformation, as well as by contour saliency. We also find that the representation of space within and around a shape is transformed in line with the shape transformation, as if shape features establish an object-centered reference frame. These findings suggest robust mechanisms for the inference of shape, space and correspondence across transformations.