bluuebunny/crossref_metadata_2025_split huggingface dataset:
LMI‐based neural observer for state and nonlinear function estimation
Authors: Jeon Woongsun , Chakrabarty Ankush , Zemouche Ali , Rajamani Rajesh 
Published: April 2024

AbstractThis article develops a neuro‐adaptive observer for state and nonlinear function estimation in systems with partially modeled process dynamics. The developed adaptive observer is shown to provide exponentially stable estimation errors in which both states and nonlinear functions converge to their true values. When the neural approximator has an approximation error with respect to the true nonlinear function, the observer can be used to provide an bound on the estimation error. The article does not require assumptions on the process dynamics or output equation being linear functions of neural network weights and instead assumes a reasonable affine parameter dependence in the process dynamics. A convex problem is formulated and an equivalent polytopic observer design method is developed. Finally, a hybrid estimation system that switches between a neuro‐adaptive observer for system identification and a regular nonlinear observer for state estimation is proposed. The switched operation enables parameter estimation updates whenever adequate measurements are available. The performance of the developed adaptive observer is shown through simulations for a Van der Pol oscillator and a single link robot. In the application, no manual tuning of adaptation gains is needed and estimates of both the states and the nonlinear functions converge successfully.
Expert‐in‐the‐loop design of integral nuclear data experiments
Authors: Michaud Isaac , Grosskopf Michael , Hutchinson Jesson , Vander Wiel Scott 
Published: April 2024

AbstractNuclear data are fundamental inputs to radiation transport codes used for reactor design and criticality safety. The design of experiments to reduce nuclear data uncertainty has been a challenge for many years, but advances in the sensitivity calculations of radiation transport codes within the last two decades have made optimal experimental design possible. The design of integral nuclear experiments poses numerous challenges not emphasized in classical optimal design, in particular, constrained design spaces (in both a statistical and engineering sense), severely under‐determined systems, and optimality uncertainty. We present a design pipeline to optimize critical experiments that uses constrained Bayesian optimization within an iterative expert‐in‐the‐loop framework. We show a successfully completed experiment campaign designed with this framework that involved two critical configurations and multiple measurements that targeted compensating errors in 239Pu nuclear data.
Navigating student uncertainty for productive struggle: Establishing the importance for and distinguishing types, sources, and desirability of scientific uncertainties
Authors: Chen Ying‐Chih , Jordan Michelle , Park Jongchan , Starrett Emily 
Published: April 2024

AbstractAn essential aspect of scientific practice involves grappling with the generation of predictions, representations, interpretations, investigations, and communications related to scientific phenomena, all of which are inherently permeated with uncertainty. Transferring this practice from expert settings to the classroom is invaluable yet challenging. Teachers often perceive struggles as incidental, negative, and uncomfortable, assuming they stem from students' deficiencies in knowledge or understanding, which they feel compelled to promptly address to progress. While some empirical research has explored the role of scientific uncertainties in driving productive student struggle, few studies have explicitly examined or provided a framework to unpack scientific uncertainty as it manifests in the classroom, including the sources that lead to student struggle and how teachers can manage it effectively. In this position paper, we elucidate the importance of incorporating scientific uncertainties as pedagogical resources to foster student struggles through uncertainty from three perspectives: scientific literacy, student agency, and coherent trajectories of sensemaking. To develop a theoretical framework, we consider scientific uncertainty as a resource for productive struggle in the sensemaking process. We delve into two types (e.g., conceptual, epistemic), four sources (e.g., insufficiency, ambiguity, incoherence, conflict), and three desirability considerations (e.g., relevance, timing, complexity) of scientific uncertainties in student struggles to provide a theoretical foundation for understanding what students struggle with, why they struggle, and how scientific uncertainties can be effectively managed by teachers. With this framework, researchers and teachers can examine the (mis)alignments between uncertainty‐in‐design, uncertainty‐in‐practice, and uncertainty‐in‐reflection.
Does the closure of polluting enterprises improve rural livelihoods? Evidence from rural China
Authors: Deng Xiaoshang , Niu Kunyu , Xu Xiangbo , Li Chang , Zhang Linxiu 
Published: April 2024

AbstractIn response to an increasingly dire pollution scenario, the Chinese government initiated the largest and most extensive environmental inspection campaign in history starting in 2016. Numerous polluting enterprises were closed due to environmental concerns in the rural areas. Drawing on two‐period panel data from the China Rural Development Survey, this study revealed the inherent mechanism of the polluting enterprises closure on local rural livelihoods using the difference‐in‐differences method and structural equation model, with reference to the sustainable livelihood framework. Results showed that shuttering polluting enterprises enhanced rural households' livelihood capital, notably in human, natural, and physical aspects, and promoted labor migration. Additional heterogeneous analysis revealed that the enhancements were notably more pronounced in Southern China and among affluent demographics. Based on the findings, we suggested the local government should support the development of sustainable agriculture and green industries and pay more attention to vulnerable populations when making policy decisions. The use of mandatory directives, such as shutting down polluting enterprises, is a common strategy in developing countries. This study presents an analytical framework for understanding the impact of environmental governance on the livelihoods of rural households in developing countries, contributing to a better balance between rural environmental management and livelihood improvement in these regions.
Importance of women empowerment for eco‐efficiency of small farms in the context of other social factors: Building sustainable agriculture in Central and Eastern European countries
Authors: Czyżewski Bazyli , Prędki Artur , Brelik Agnieszka 
Published: April 2024

AbstractIt is widely assumed that women's empowerment plays a key role in achieving sustainability in agriculture. However, there is a lack of empirical analysis to support this claim and operationalise the concept of women's empowerment. Furthermore, it has not been formally demonstrated through which farming practices women's empowerment can contribute to the development of sustainable agriculture, or whether gender empowerment is indeed meaningful compared with other well‐documented social drivers. We calculated frontier eco‐efficiency, taking into account specific environmental pressures (i.e., soil biodiversity loss) and public goods (i.e., plant diversity) as desirable outputs in small crop farms, which dominate in Central and Eastern European countries (Poland, Romania, Serbia and Moldova), based on a survey conducted in a sample of 1630 units. We estimated the impact of different levels of women's and men's empowerment on eco‐efficiency in the context of other time‐invariant socio‐economic factors (i.e., succession, age, education and specialisation) in a two‐stage double‐bootstrapped Data Envelopment Analysis (DEA) approach. A set of four levels of gender empowerment was defined, taking into account social participation and decision‐making power. We then assessed the degree of input and output inefficiency associated with each level of gender empowerment. The general conclusion is that lower levels of women's empowerment have a negative impact on eco‐efficiency. Therefore, the issue of gender empowerment, not only in terms of equality, decision‐making and access to resources, but also in terms of social participation, should be emphasised in sustainable agriculture policies, on a par with the issue of ageing farmers and farm succession.
One‐pot Expedient Green Synthesis of N‐benzhydrylpyridine‐2‐amines Using Gooseberry Amla Fruit Extract (GAFE): A Naturally Occurring Organocatalyst
Authors: Nadoni Vishwa B. , Kamble Ravindra R. , Metre Tukaram V. , Bheemayya Lokesh , Nayak Manojna R. 
Published: April 2024

AbstractOne‐pot synthesis of N‐benzhydrylpyridine‐2‐amines employing Gooseberry amla (Phyllanthus emblica) fruit extract (GAFE) as an organoacid catalyst, was executed in the current investigation with the primary emphasis on green chemistry. The spectrum displays of these compounds were analyzed using FT‐IR, 1H and 13C NMR, and LC‐MS. For substantial ecological assurance, we adopted green chemistry methodologies to lessen the risk of exposure to hazardous chemical materials amid the synthesis of diverse heterocyclic compounds. Moreover, these α‐branched amines are synthesized in the greener and milder way with the use of a natural organoacid with more yields compared with the other chemical methods. This innovative approach has a lot to offer in terms of its rapid reaction time frames, clear reaction profiles, benign reaction conditions, absence of toxic catalysts and risky solvents, accessibility of the work‐up process, and greater yield.
Synthetic Cells from Droplet‐Based Microfluidics for Biosensing and Biomedical Applications
Authors: Ngocho Kleins , Yang Xilei , Wang Zefeng , Hu Cunjie , Yang Xiaohai , Shi Hui , Wang Kemin , Liu Jianbo 
Published: April 2024

AbstractSynthetic cells function as biological mimics of natural cells by mimicking salient features of cells such as metabolism, response to stimuli, gene expression, direct metabolism, and high stability. Droplet‐based microfluidic technology presents the opportunity for encapsulating biological functional components in uni‐lamellar liposome or polymer droplets. Verified by its success in the fabrication of synthetic cells, microfluidic technology is widely replacing conventional labor‐intensive, expensive, and sophisticated techniques justified by its ability to miniaturize and perform batch production operations. In this review, an overview of recent research on the preparation of synthetic cells through droplet‐based microfluidics is provided. Different synthetic cells including lipid vesicles (liposome), polymer vesicles (polymersome), coacervate microdroplets, and colloidosomes, are systematically discussed. Efforts are then made to discuss the design of a variety of microfluidic chips for synthetic cell preparation since the combination of microfluidics with bottom–up synthetic biology allows for reproductive and tunable construction of batches of synthetic cell models from simple structures to higher hierarchical structures. The recent advances aimed at exploiting them in biosensors and other biomedical applications are then discussed. Finally, some perspectives on the challenges and future developments of synthetic cell research with microfluidics for biomimetic science and biomedical applications are provided.
Environmentally Robust Triboelectric Tire Monitoring System for Self‐Powered Driving Information Recognition via Hybrid Deep Learning in Time‐Frequency Representation
Authors: Kim BaekGyu , Song Jin Yeong , Kim Do Young , Cho Min Woo , Park Ji Gyo , Choi Dongwhi , Lee Chengkuo , Park Sang Min 
Published: April 2024

AbstractDeveloping a robust artificial intelligence of things (AIoT) system with a self‐powered triboelectric sensor for harsh environment is challenging because environmental fluctuations are reflected in triboelectric signals. This study presents an environmentally robust triboelectric tire monitoring system with deep learning to capture driving information in the triboelectric signals generated from tire‐road friction. The optimization of the process and structure of a laser‐induced graphene (LIG) electrode layer in the triboelectric tire is conducted, enabling the tire to detect universal driving information for vehicles/robotic mobility, including rotation speeds of 200–2000 rpm and contact fractions of line. Employing a hybrid model combining short‐term Fourier transform with a convolution neural network‐long short‐term memory, the LIG‐based triboelectric tire monitoring (LTTM) system decouples the driving information, such as traffic lines and road states, from varied environmental conditions of humidity (10%–90%) and temperatures (50–70 °C). The real‐time line and road state recognition of the LTTM system is confirmed on a mobile platform across diverse environmental conditions, including fog, dampness, intense sunlight, and heat shimmer. This work provides an environmentally robust monitoring AIoT system by introducing a self‐powered triboelectric sensor and hybrid deep learning for smart mobility.
Amorphous/Crystalline Phases Mixed Nanosheets Array Rich in Oxygen Vacancies Boost Oxygen Evolution Reaction of Spinel Oxides in Alkaline Media
Authors: Liu Ying , Xiao Liyang , Tan Haiwen , Zhang Jingtong , Dong Cunku , Liu Hui , Du Xiwen , Yang Jing 
Published: April 2024

AbstractAs promising oxygen evolution reaction (OER) catalysts, spinel‐type oxides face the bottleneck of weak adsorption for oxygen‐containing intermediates, so it is challenging to make a further breakthrough in remarkably lowering the OER overpotential. In this study, a novel strategy is proposed to substantially enhance the OER activity of spinel oxides based on amorphous/crystalline phases mixed spinel FeNi2O4 nanosheets array, enriched with oxygen vacancies, in situ grown on a nickel foam (NF). This unique architecture is achieved through a one‐step millisecond laser direct writing method. The presence of amorphous phases with abundant oxygen vacancies significantly enhances the adsorption of oxygen‐containing intermediates and changes the rate‐determining step from OH*→O* to O*→OOH*, which greatly reduces the thermodynamic energy barrier. Moreover, the crystalline phase interweaving with amorphous domains serves as a conductive shortcut to facilitate rapid electron transfer from active sites in the amorphous domain to NF, guaranteeing fast OER kinetics. Such an anodic electrode exhibits a nearly ten fold enhancement in OER intrinsic activity compared to the pristine counterpart. Remarkably, it demonstrates record‐low overpotentials of 246 and 315 mV at 50 and 500 mA cm−2 in 1 m KOH with superior long‐term stability, outperforming other NiFe‐based spinel oxides catalysts.
Single Side‐Chain‐Modulatory of Hemicyanine for Optimized Fluorescence and Photoacoustic Dual‐Modality Imaging of H2S In Vivo
Authors: Xu Juntao , Li Xipeng , Luo Zhiheng , Li Jiajun , Yang Sihua , Zhang Tao 
Published: April 2024

AbstractNear‐infrared fluorescence (NIRF)/photoacoustic (PA) dual‐modality imaging integrated high‐sensitivity fluorescence imaging with deep‐penetration PA imaging has been recognized as a reliable tool for disease detection and diagnosis. However, it remains an immense challenge for a molecule probe to achieve the optimal NIRF and PA imaging by adjusting the energy allocation between radiative transition and nonradiative transition. Herein, a simple but effective strategy is reported to engineer a NIRF/PA dual‐modality probe (Cl‐HDN3) based on the near‐infrared hemicyanine scaffold to optimize the energy allocation between radiative and nonradiative transition. Upon activation by H2S, the Cl‐HDN3 shows a 3.6‐fold enhancement in the PA signal and a 4.3‐fold enhancement in the fluorescence signal. To achieve the sensitive and selective detection of H2S in vivo, the Cl‐HDN3 is encapsulated within an amphiphilic lipid (DSPE‐PEG2000) to form the Cl‐HDN3‐LP, which can successfully map the changes of H2S in a tumor‐bearing mouse model with the NIRF/PA dual‐modality imaging. This work presents a promising strategy for optimizing fluorescence and PA effects in a molecule probe, which may be extended to the NIRF/PA dual‐modality imaging of other disease‐relevant biomarkers.
Comparing drug testing methods in the trucking industry: The drug and alcohol clearinghouse versus hair testing
Authors: Voss M. Douglas , Cangelosi Joseph D. , Li Ming 
Published: April 2024

AbstractThe Omnibus Transportation Employee Testing Act of 1991 mandated urine drug testing for U.S. truck drivers but some trucking companies prefer hair testing because it has a longer look back period and better detects lifestyle drug users. Previous research established that 276,500 current truck drivers may be disqualified if they submitted to hair drug tests instead of federally accepted urinalysis. This research compares hair and urine drug test results provided by eight U.S. trucking companies who are members of the alliance for driver safety and security (i.e., the trucking alliance) with urine test results drawn from the federal drug and alcohol clearinghouse to determine the differences in hair versus urine positivity rates and drugs detected. Results indicate that hair testing has a 6.00% positivity rate, 4.01% higher than urine. If this difference were generalized to the drivers who submitted urine tests to the drug and alcohol clearinghouse, hair testing would have likely disqualified 57,337 additional drivers in 2020. Results further indicate urine testing is better able to detect marijuana while hair testing is superior in detecting cocaine and opioids. This implies federal agencies should consider allowing hair test results to be submitted to the drug and alcohol clearinghouse to support a more drug‐free driver workforce.
Wie viel Ungewissheit ist akzeptabel?
Authors: Eckhardt Anne 
Published: April 2024

ZusammenfassungUngewissheiten bei der Endlagerung hochradioaktiver Abfälle sind unter anderem in den langen Zeithorizonten begründet, über die Sicherheit belegt werden muss, und in der Komplexität des soziotechnischen Projekts der Endlagerung. Endlager für hochradioaktive Abfälle sind dafür konzipiert, Ungewissheiten zu vermeiden, zu vermindern oder ihre Auswirkungen zu begrenzen. Dennoch bleiben bei der Endlagerung bedeutende Ungewissheiten bestehen. Die Akzeptabilität von Ungewissheiten zu beurteilen, setzt zunächst ein Verständnis der unterschiedlichen Ungewissheiten voraus, die bei der Endlagerung hochradioaktiver Abfälle von Bedeutung sind, und ihrer zeitlichen Entwicklungen. Auf dem Entsorgungsweg, der zum verschlossenen Endlager führt, müssen sowohl politische Entscheidungen als auch eine Vielzahl von Arbeitsentscheidungen zum Umgang mit Ungewissheiten getroffen werden. Dabei stellt sich die Frage, welche Ungewissheiten bzw. welches Maß an Ungewissheiten akzeptabel sind. Bei Arbeitsentscheidungen lässt sich die Akzeptabilität von Ungewissheiten anhand der spezifischen Konstellation von vier Kriterien überprüfen. Für Entscheidungen auf der politischen Ebene lassen sich ebenfalls Kriterien ableiten, um die Akzeptabilität spezifischer Ungewissheiten zu prüfen. Aufgrund der verschiedenen Formen, die Ungewissheiten annehmen, bleibt es anspruchsvoll, Gesamtbeurteilungen von Ungewissheiten auf dem Entsorgungsweg oder bei einem Endlagersystem vorzunehmen. Für die Zukunft eröffnen sich Perspektiven, Fragen zur Akzeptabilität von Ungewissheiten bei der Entsorgung radioaktiver Abfälle mit neuen Argumenten und Verfahren differenzierter zu beantworten als es bisher möglich war.
Ein erster methodischer Ansatz zur Identifikation von Ungewissheiten bei der individuellen Durchführung der Materialparameterermittlung für numerische Simulationen aus arbeitspsychologischer Sicht
Authors: Muxlhanga Henriette , Othmer Johann Arne , Sträter Oliver , Lux Karl-Heinz , Wolters Ralf , Feierabend Jörg , Sun-Kurczinski Junqing 
Published: April 2024

ZusammenfassungDer Kernkraftwerksbetrieb endet. Doch die dabei entstandenen hochradioaktiven Abfälle sind für einen sehr langen Zeitraum sicher im geologischen Untergrund ein- beziehungsweise endzulagern. Angesichts von Ungewissheiten, die planungsseitig auf Prozess- und Systemebene bestehen, ist eine möglichst robuste Endlagerkonzeption erforderlich. Diese Forderung bezieht sich nicht nur auf die technische Ausgestaltung, sondern muss auch soziale Aspekte mitbetrachten – in diesem Fall den im Rahmen der Arbeitspsychologie genannten Faktor Mensch. Auf den Planungs- und Ausführungsprozess bezogen sind darunter die menschlichen Einflüsse zu verstehen, die aus subjektiv geprägtem Handeln resultieren. Die Ursachen und möglichen Auswirkungen des Faktors Mensch auf die technische Planung werden in diesem Beitrag beispielhaft untersucht. Im Rahmen des Planungsprozesses sind numerische Simulationen zur prognostischen Ermittlung des Endlagersystemverhaltens etabliert. Grundlage für die numerische Simulation ist die Abbildung des geplanten Endlagersystems in einem Simulationsmodell durch die Modellierenden. Für die Prognose des Langzeitverhaltens lässt sich nur schwer einschätzen, ob bei der Durchführung der rechnerischen Simulationen der jeweilig Modellierende mit seiner individuellen Vorgehensweise einen relevanten Einfluss hat. Daher wird in diesem Beitrag der individuelle Einfluss von Modellierenden am Beispiel einer Einlagerungsstrecke betrachtet, für die eine Prognose ihres langfristigen Tragverhaltens vorzunehmen ist. Ein Teil dieser Planungsarbeiten umfasst die Ermittlung von Parametern zur physikalischen Abbildung des Gebirgsverhaltens und die Simulation der Streckenverformungen im Laufe der Zeit. Vor diesem Hintergrund sind mehrere Modellierer parallel bei der Parameterermittlung mit verschiedenen methodischen Ansätzen der Arbeitspsychologie beobachtet worden. Die Ergebnisse dieses Beitrags zeigen, in welchem Umfang und aus welchen Gründen der Faktor Mensch bei der Prognose des Verhaltens sicherheitstechnischer Komponenten des Endlagersystems relevant sein kann. Daher sollte der Faktor Mensch soweit möglich bereits proaktiv auf Seiten des Antragstellers und nicht nur reaktiv im Rahmen des Genehmigungsverfahrens berücksichtigt werden.
Ungewissheiten und Narrative im Kontext der Entsorgung hochradioaktiver Abfälle – eine schwierige Beziehung?
Authors: Becker Frank , Berg Margarita 
Published: April 2024

ZusammenfassungBei der näheren Betrachtung des Themas „Ungewissheiten und Narrative im Kontext der Entsorgung hochradioaktiver Abfälle“ fällt auf, dass dabei oft verschiedene Begriffe verwendet werden, die zumindest im allgemeinen Sprachgebrauch als synonym oder sehr ähnlich wahrgenommen werden können. Der Beitrag umreißt daher in einem ersten Schritt das Begriffsfeld „Ungewissheit“ (Ungewissheit, Unsicherheit, Risiko, etc.) sowie das Begriffsfeld „Narrativ“ (Narrativ, Geschichte, Metapher, Slogan, etc.). Da die Rede vom Narrativ in den letzten Jahren zum Teil inflationär Verwendung findet, soll zunächst geklärt werden, was ein Narrativ charakterisiert und was im Umkehrschluss ausdrücklich kein Narrativ darstellt, obwohl der Begriff als Modewort oftmals nach Gutdünken verwendet wird. Beispielhaft werden dazu einige Narrative im Kontext der Endlagerung geschildert. Der Beitrag untersucht anschließend mögliche Verbindungen zwischen Ungewissheiten und Narrativen. Es stellt sich vor allem die Frage, inwiefern Narrative mit ihrem zielgerichteten Aufbau überhaupt geeignet sind, um Ungewissheiten zu transportieren, oder ob diese durch die Erzählstruktur nicht von vornherein ausgeschlossen bzw. relativiert werden. Als Untersuchungsbeispiel dienen unter anderem Narrative, die Radioaktivität und Kernkraft mit der negativ behafteten Metapher „Verstrahlung“ medienwirksam propagieren und dadurch Ungewissheiten und Missverständnisse verstärken können.