bluuebunny/crossref_metadata_2025_split huggingface dataset:
Supervised pearlitic–ferritic steel microstructure segmentation by U-Net convolutional neural network
Authors: Motyl Mateusz , Madej Łukasz 
Published: September 2022

Abstract
The aim of this work is to develop an automated procedure based on machine learning capabilities for the identification of the pearlite islands within the two-phase pearlitic–ferritic steel. The input parameters for the custom implementation of a braided neural network are provided as a data set of scanning electron microscopy images of metallographic specimens. The procedures related to the processing of the data and the optimization parameters affecting the final architecture and effectiveness of the network learning stage are examined. The objective is to find the best solution to the problem of ferritic–pearlitic microstructure segmentation, allowing further processing during, e.g., 3D reconstruction of data from serial sectioning. The work examines the various quality of input data and different U-Net architectures to find the one that can identify pearlite islands with the highest precision. Two types of images acquired from secondary electron (SE) and electron backscattered diffraction (EBSD) detectors are used during the investigation. The work revealed that the developed approach offers improvements in metallographic investigations by removing the requirement for expert knowledge for the interpretation of image data prior to further characterization. It has also been proven that artificial neural networks based on the deep learning process using extensible U-Net network architectures and nonlinear learning tools can identify pearlite islands within a two-phase microstructure, while the overtraining level remains low. Convolutional neural networks do not require manual feature extraction and are able to automatically find appropriate search functions to recognize pearlite structure areas in the training process without human intervention. It was shown that the network recognizes areas of analyzed steel with satisfactory precision of 79% for EBSD and 87% for SE images.
The Circular Decision-Making Tree: an Operational Framework
Authors: Greer Rachel , von Wirth Timo , Loorbach Derk 
Published: September 2022

AbstractBecause of the need to limit extraction of raw materials and reduce amounts and impacts of waste, countries and businesses are challenged to transition to a circular economy: an economic system in which the materials are reduced, reused, or recycled, but not wasted. Yet, transitioning from a linear to a circular economy implies societal-level, structural changes that have deep implications for existing business models and practices–and the current economic system is still largely organized around virgin material extraction and linear modes of production and consumption. Despite stated ambitions at various geographical scales to become more or fully circular, the outcomes still fall short of such visions. One important reason why the transition towards a circular economy is not proceeding as quickly as hoped can be found in the decision processes used by companies, investors, and policy makers. Suitable frameworks that support decision-making could thus be a key enabler of this transition, if based upon a circular and transformative, rather than a linear optimization logic. In this paper, we therefore explore a different decision-making logic that is developed based on circularity. This provides the basis for an operational framework designed to help decision-makers such as policymakers, investors, and entrepreneurs navigate tradeoffs and take decisions considering the quality of innovation circularity and its respective diffusion potential. To develop, test, and refine our framework—the “Circular Decision-Making Tree”—we synthesized insights from existing frameworks and conceptually integrated these with our understanding of transition theory and the circular economy. We then verified the internal logics and applicability of the framework in a series of usability workshops across four application contexts (Netherlands, Brazil, UK, and South Africa) with feedback from a total of n = 50 stakeholders from policy, practice, and academia. We critically discuss the application potential as well as the limitations and describe implications for future research to further validate the framework’s logics and operationalization.
Acaricide resistance and novel photosensitizing approach as alternative acaricides against the camel tick, Hyalomma dromedarii
Authors: Mohammed Shaimaa H. , Baz Mohamed M. , Ibrahim Moustafa , Radwan Ibrahim T. , Selim Abdelfattah , Dawood Abdel-Fattah D. , Taie Hanan A. A. , Abdalla Salwa , Khater Hanem F. 
Published: September 2022

AbstractThe control of the camel tick, Hyalomma dromedarii is very crucial. This study evaluated the novel toxicity of photosensitizers and Phoxim insecticide against H. dromedarii males using the adult immersion tests. Ticks were subjected to sunlight for 10 min post-treatment (PT). The optical characters of the applied materials were determined by UV–Vis spectroscopy (250–900 nm wavelengths). The intensity of spectra decreased as dye concentration decreased. The optical bandgap energies of the dyes at different concentrations were not changed as the concentration changed and decreased as the absorption peak of individual dyes red-shifted. The mortalities 72 h PT reached 42.2%, 44.4%, 51.1%, 71.1%, 46.7%, 48.9%, 44.4%, and 55.6% for chlorophyllin, echinochrome, field stain, methylene blue, phthalocyanine, rhodamine 6G, riboflavin, and safranin, respectively. Methylene blue recorded the highest median lethal concentration (LC50 = 127 ppm) followed by safranin, field stain, rhodamine 6G, phthalocyanine, echinochrome riboflavin, and chlorophyllin (LC50 = 209, 251, 271, 303, 324, 332, and 362 ppm, respectively, 72 h PT). Their median lethal time, LT50, values PT with 240 ppm were 45, 87, 96, 72, 129, 115, 131, and 137 h, respectively. The relative toxicities of the LC50 values 72 h PT showed that chlorophyllin, echinochrome, field stain, methylene blue, phthalocyanine, rhodamine 6G, riboflavin, and safranin were 3.2, 3.6, 4.6, 9.1, 3.8, 4.3, 3.5, and 5.6 times, respectively, more effective than Phoxim. Methylene blue, safranin, and field stain showed a broad absorbance area indicating a large photoactivity and better phototoxicity and could be used as alternative agents to synthetic acaricides.
Graphical Abstract
Analysis of local governments’ marine governance efficiency using a spatiotemporal coupling coordination model: a case study of coastal cities in Liaoning Province, China
Authors: Liu Wanbo , Shen Fangfang , Zhao Dongxia 
Published: September 2022

AbstractCoastal areas have the most obvious ocean–land interaction and experience the most frequent human activities. As the development of coastal areas has a high degree of spatiotemporal variability, local governments bear direct responsibility for marine governance, yet accurately evaluating and analyzing local governments’ marine governance efficiency in coastal areas is challenging. This study constructs a spatiotemporal coupling coordination model to comprehensively evaluate local governments’ marine governance efficiency in six coastal cities in Liaoning Province from 2004 to 2019. A complex system was necessary to obtain the development level, discrete degree, and development speed of each subsystem. The construction of the evaluation index system was the foundation, and the construction of the spatiotemporal weight matrix was the key. The results show that overall, the local governments’ marine governance efficiency level is generally increasing, and the agglomeration effect is obvious. The efficiency of each cities’ economic, ecological, and social governance subsystem is in a process of continuous and dynamic change. The coupling and coordination degrees of the six governance systems have continuously improved and the spatial and temporal differences have decreased; each city shows different coupling and coordination degrees in each subsystem. Regarding the factors affecting comprehensive marine management, Liaoning’s coastal areas fail to attract foreign tourists; the discharge and treatment of industrial wastewater restricts ecological governance; and the reduction of fisheries hinders the social governance system’s efficiency. The results contribute to the understanding of costal cities’ marine governance and promote the sustainable development of coastal areas.
Environmental Health Intelligence New Zealand (EHINZ): intelligence for public health action
Authors: Borman Barry , Haenfling Carolin , Kowalik-Tait Agnieszka , Hipgrave Patrick 
Published: September 2022

AbstractThe New Zealand health system is data-rich, information-poor, and intelligence meagre. However, there is widespread confusion about the definitions of these terms, so they are often used synonymously. Like many jurisdictions, we continue to collect and collate vast quantities of data at an increasing rate. Many tools are available to “analyse” the data deluge with the false expectation that “intelligence” will be produced. Naively, such a data-driven, machine-analysed paradigm is often thought to produce the “evidence” for decision-making and policy development. Continuing such a blinded approach poses potential health risks to New Zealanders and remains a major impediment to improving our health statusCreating intelligence from information involves humans (perhaps in concert with AI) utilising their interpretative abilities, asking the “so what, “what does it mean” questions, and employing their communication skills to disseminate the answers. To move from information to intelligence requires agencies to employ, develop and maintain a sufficiently skilled workforce over a long period, rather than the quick and easy investment in more and faster machines and software.Only through a human-driven evaluation of intelligence-based decisions and policies will our knowledge about the environmental health system increase and ultimately yield better health outcomes.Environmental Health Intelligence NZ (EHINZ) provides intelligence as evidence for decision-making and policy development in environmental health. It is based on the interpretation, communication, and dissemination of information from the surveillance more than seventy environmental health indicators (EHIs) across twelve domains (e.g., air and water quality, climate change), exposure to hazardous substances, and social vulnerability indicators to environmental hazards (e.g., flooding, climate change, sea-level rise, wildfires, heat waves).The paper details our approach, with two case studies, in providing the NZ health system with “intelligence for environmental health decisions.”
The Politics of Data in EU Law: Will It Succeed?
Authors: Pagallo Ugo 
Published: September 2022

AbstractThe paper examines recent initiatives of the European Commission that aim to complement today’s legislation on the internet, data governance, and technological innovation, and how scholars have attempted to sum up current trends of EU law according to some catchy formulas: digital sovereignty, digital constitutionalism, or a renewed Brussels effect. Although such narratives have their merits, they can also be misleading and should be taken with a pinch of salt. The paper intends to complement such narratives in connection with the open issues on the balance of powers between EU institutions and member states (MS), with a new generation of digital rights at both EU and MS constitutional levels, down to the interplay between new models of legal governance and the potential fragmentation of the system. Whether and to what extent EU law will be successful in the regulation of data-driven societies and complex digital ecosystems do not only regard acts, policies, and proposals against misuses and overuses of technology but also how well mechanisms of coordination and models of cooperation set up by EU law will fare against technological underuses with their opportunity costs.
A test of Bergmann's rule in the Early Triassic: latitude, body size, and sampling in Lystrosaurus
Authors: Kulik Zoe T. , Sidor Christian A. 
Published: September 2022

AbstractThe ecogeographic rule known as Bergmann's rule suggests that there is a positive relationship between body size and latitude when comparing closely related taxa. The underlying mechanism or mechanisms to explain this pattern vary as widely as the taxa that seem to follow it, which has led to skepticism over whether Bergmann's rule should be considered a rule at all. Despite this, Bergmann's rule is widespread among modern birds, mammals, beetles, and some amphibians, but far fewer extinct taxa have been subjected to tests of Bergmann's rule. To examine whether Bergmann's rule is detected in extinct taxa, we compared body-size proxies in Lystrosaurus recovered from Early Triassic–aged strata in Antarctica, South Africa, India, and China. Our results reveal that average body size is largest at mid-northern paleolatitudes (~45°N) instead of the highest southern paleolatitudes (~70°S). Additionally, maximum body size is consistent across the Northern and Southern Hemispheres, indicating that Bergmann's rule did not apply for Lystrosaurus during the Early Triassic. To test potential sample size biases in our results, we used rarefaction and subsampling to show that only the Karoo Basin is well sampled and that large individuals are exceedingly rare, except in the Turpan-Junggar Basin of Xinjiang, China. Taken together, our results suggest that Lystrosaurus had the potential to reach large body sizes in each of the latitudinally widespread geologic basins studied here, but that local conditions may have allowed individuals at mid-northern paleolatitudes a greater chance of reaching a large size compared with southern congeners that suffered increased mortality when young or at a small size.
Towards Augmented Microscopy with Reinforcement Learning-Enhanced Workflows
Authors: Xu Michael , Kumar Abinash , LeBeau James M 
Published: September 2022

Abstract
Here, we report a case study implementation of reinforcement learning (RL) to automate operations in the scanning transmission electron microscopy workflow. To do so, we design a virtual, prototypical RL environment to test and develop a network to autonomously align the electron beam position without prior knowledge. Using this simulator, we evaluate the impact of environment design and algorithm hyperparameters on alignment accuracy and learning convergence, showing robust convergence across a wide hyperparameter space. Additionally, we deploy a successful model on the microscope to validate the approach and demonstrate the value of designing appropriate virtual environments. Consistent with simulated results, the on-microscope RL model achieves convergence to the goal alignment after minimal training. Overall, the results highlight that by taking advantage of RL, microscope operations can be automated without the need for extensive algorithm design, taking another step toward augmenting electron microscopy with machine learning methods.
Häufigkeit, Heimlichkeit und Einstellung bei der Pornographienutzung und deren Zusammenhänge mit der sexuellen Paarzufriedenheit
Authors: Re Ursina Brun del , Hilpert Peter , Bodenmann Guy 
Published: September 2022

Zusammenfassung. Theoretischer Hintergrund: Bisherige Befunde zeigen, dass Pornographienutzung einen Zusammenhang mit der Zufriedenheit in der Paarsexualität hat. Fragestellung: Um diesen Zusammenhang besser zu verstehen, soll diese Studie aufzeigen, welche Faktoren dabei von Bedeutung sind. Methode: Dafür wurden 18- bis 60-Jährige in einer Beziehung ( N = 1’091) anhand eines Online-Fragebogens befragt. Ergebnisse: Sowohl die Häufigkeit der Pornographienutzung, als auch eine negative Einstellung und die Heimlichkeit weisen bei den jungen und Männern mittleren Alters einen negativen Zusammenhang mit der sexuellen Paarzufriedenheit auf. Bei den Frauen jeden Alters hat lediglich eine heimliche Nutzung einen negativen Zusammenhang mit der Paarsexualität. Schlussfolgerungen: Das bedeutet für die Beratung, dass auf die Häufigkeit der Nutzung und die Einstellung zu der Nutzung geachtet werden soll.
Leveraging Spatial Patterns in Precipitation Forecasts Using Deep Learning to Support Regional Water Management
Authors: Zhang Chen , Brodeur Zachary P. , Steinschneider Scott , Herman Jonathan D. 
Published: September 2022

AbstractShort‐term precipitation forecasts are critical to regional water management, particularly in the Western U.S. where atmospheric rivers can be predicted reliably days in advance. However, spatial error in these forecasts may reduce their utility when the costs of false positives and negatives differ greatly. Here we investigate whether deep learning methods can leverage spatial patterns in precipitation forecasts to (a) improve the skill of predicting the occurrence of precipitation events at lead times from 1 to 14 days, and (b) balance the tradeoff between the rate of false negatives and false positives by modifying the discrimination threshold of the classifiers. This approach is demonstrated for the Sacramento River Basin, California, using the Global Ensemble Forecast System (GEFS) v2 precipitation fields as input to convolutional neural network (CNN) and multi‐layer perceptron models. Results show that the deep learning models do not significantly improve the overall skill (F1 score) relative to the ensemble mean GEFS forecast with bias‐corrected threshold. However, additional analysis of the CNN models suggests they often correct missed predictions from GEFS by compensating for spatial error at longer lead times. Additionally, the deep learning models provide the ability to adjust the rate of false positives and negatives based on the ratio of costs. Finally, analysis of the network activations (saliency) indicates spatial patterns consistent with physical understanding of atmospheric river events in this region, lending additional confidence in the ability of the method to support water management applications.
Model Predictions of Wave Overwash Extent Into the Marginal Ice Zone
Authors: Pitt Jordan P. A. , Bennetts Luke G. , Meylan Michael H. , Massom Robert A. , Toffoli Alessandro 
Published: September 2022

AbstractIn the marginal ice zone (MIZ), where ocean waves and sea ice interact, waves can produce flows of water across ice floe surfaces in a process known as wave overwash. Overwash potentially influences wave propagation characteristics, floe thermodynamics, and floe surface biological and chemical processes. However, the extent of the MIZ affected by overwash and its dependence on prevailing wave and ice conditions is unknown. In this paper, we propose a model of overwash extent caused by irregular incoming waves into a MIZ consisting of a random floe field. We validate the overwash extent model against laboratory experiments. We use the model to study mild to extreme incoming waves to floe field characteristics of the spring–summer ice retreat and autumn–winter ice advance and with compact ice edges. Overwash is typically predicted to extend a few kilometers and is generally greater for the autumn–winter advance than the spring–summer retreat. The model predictions provide a basis for improved understanding of the impacts of ocean waves on the ice cover. We also apply the model to incoming waves and a floe field with a diffuse ice edge representative of conditions during a field experiment, predicting overwash extents up to 16 km. During the field experiment, the wave and ice floe properties were intermittently monitored by a camera system, demonstrating how the sparse field data available on overwash can be advanced.
Internal Tides Responsible for Lithogenic Inputs Along the Iberian Continental Slope
Authors: Barbot Simon , Lagarde Marion , Lyard Florent , Marsaleix Patrick , Lherminier Pascale , Jeandel Catherine 
Published: September 2022

AbstractThis study proposes new insights for the interpretation of GEOVIDE particle measurements. Potential resuspension sites due to internal tides (ITs) have been identified along the western Iberian shelf slope using a tidal regional model. Iberian shelf is mainly a source of lithogenic material whereas Galicia Bank is a source of biogenic matter. The potential pathways for particles from the resuspension sites toward the GEOVIDE stations are identified using IBIRYS reanalysis to infer their transport by the ocean circulation. It appears that each station is influenced by a specific pathway and mixed particles from several resuspension sites. This methodology reveals that the criticality of the bathymetry slope, commonly used to track resuspension sites from internal waves, is not sufficient to investigate ITs. An explicit resolution of ITs using a numerical tidal model is required for an exhaustive identification of the resuspension sites.
Inhibition of phospholipase D1 induces immunogenic cell death and potentiates cancer immunotherapy in colorectal cancer
Authors: Hwang Won Chan , Song Doona , Lee Hyesung , Oh Changmok , Lim Seong Hun , Bae Hyeon Jeong , Kim Nam Doo , Han Gyoonhee , Min Do Sik 
Published: September 2022

AbstractPhospholipase D (PLD) is a potential therapeutic target against cancer. However, the contribution of PLD inhibition to the antitumor response remains unknown. We developed a potent and selective PLD1 inhibitor based on computer-aided drug design. The inhibitor enhanced apoptosis in colorectal cancer (CRC) cells but not in normal colonic cells, and in vitro cardiotoxicity was not observed. The inhibitor downregulated the Wnt/β-catenin signaling pathway and reduced the migration, invasion, and self-renewal capacity of CRC cells. In cancer, therapeutic engagement of immunogenic cell death (ICD) leads to more effective responses by eliciting the antitumor immunity of T cells. The CRC cells treated with the inhibitor showed hallmarks of ICD, including downregulation of “do not eat-me” signals (CD24, CD47, programmed cell death ligand 1 [PD-L1]), upregulation of “eat-me” signal (calreticulin), release of high-mobility group Box 1, and ATP. PLD1 inhibition subsequently enhanced the phagocytosis of cancer cells by macrophages through the surface expression of costimulatory molecules; as a result, the cancer cells were more susceptible to cytotoxic T-cell-mediated killing. Moreover, PLD1 inhibition attenuated colitis-associated CRC and orthotopically injected tumors, probably by controlling multiple pathways, including Wnt signaling, phagocytosis checkpoints, and immune signaling. Furthermore, combination therapy with a PLD1 inhibitor and an anti-PD-L1 antibody further enhanced tumor regression via immune activation in the tumor environment. Collectively, in this study, PLD1 was identified as a critical regulator of the tumor microenvironment in colorectal cancer, suggesting the potential of PLD1 inhibitors for cancer immunotherapy based on ICD and immune activation. PLD1 inhibitors may act as promising immune modulators in antitumor treatment via ICD.