bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural tailoring of semiconducting tetrazine polymers based immobilizing matrix for superior electronic biosensing of carcinoembryonic antigen
Authors: K Aswani Raj , Joshi Sowmya , Ghosh Ruma , M Rajeswara Rao 
Published: January 2023

AbstractImmobilizing matrix plays a crucial role in anchoring the receptors of target biomolecules and enhancing the sensing capability of biosensor. Howbeit, the immobilization platforms that induce stable molecular interactions with the receptors without the need for harsh reaction conditions (covalent bonding) are rare. Herein, we report the design, development and application of novel semiconducting one‐dimensional (1D) tetrazine polymers (TTz, PhTTz, PhAlkTz) as immobilizing matrices for electronic biosensing of carcinoembryonic antigen (CEA), a cancer biomarker. The polymers are fully loaded with electron‐deficient tetrazine units (nitrogen‐rich), which develop strong hydrogen bonding (H‐bonding) interactions and effectively immobilize the bioreceptor (anti‐CEA). The sensor comprises reduced graphene oxide (rGO) as the base conducting layer and tetrazine polymers as immobilizing matrices for the CEA antibodies. The rGO/TTz/anti‐CEA, rGO/PhTTz/anti‐CEA, rGO/PhAlkTz/anti‐CEA sensors exhibited 3.5 to 34.16 μA, 2.2 to 34.89 μA, 1.1 to 39.27 μA responses, respectively, for 1 pg/ml to 200 ng/ml of CEA. The sensors' (TTz, PhTTz, and PhAlkTz) sensitivities, selectivities and stabilities are found to be better than that of previously reported partially tetrazine loaded polymer (PhPTz). The study discloses the presence of H‐bonding in tetrazine units is highly critical for superior sensing. The concept of utilizing N‐rich tetrazine units in the immobilizing platforms can be generalized to several other hetero‐atom based systems and polymers. Thus, a wide variety of novel immobilizing substrates can be developed to realize superior sensing performance.
A combined physiologically‐based pharmacokinetic and quantitative systems pharmacology model for modeling amyloid aggregation in Alzheimer's disease
Authors: Geerts Hugo , Walker Mike , Rose Rachel , Bergeler Silke , van der Graaf Piet H. , Schuck Edgar , Koyama Akihiko , Yasuda Sanae , Hussein Ziad , Reyderman Larisa , Swanson Chad , Cabal Antonio 
Published: January 2023

AbstractAntibody‐mediated removal of aggregated β‐amyloid (Aβ) is the current, most clinically advanced potential disease‐modifying treatment approach for Alzheimer's disease. We describe a quantitative systems pharmacology (QSP) approach of the dynamics of Aβ monomers, oligomers, protofibrils, and plaque using a detailed microscopic model of Aβ40 and Aβ42 aggregation and clearance of aggregated Aβ by activated microglia cells, which is enhanced by the interaction of antibody‐bound Aβ. The model allows for the prediction of Aβ positron emission tomography (PET) imaging load as measured by a standardized uptake value ratio. A physiology‐based pharmacokinetic model is seamlessly integrated to describe target exposure of monoclonal antibodies and simulate dynamics of cerebrospinal fluid (CSF) and plasma biomarkers, including CSF Aβ42 and plasma Aβ42/Aβ40 ratio biomarkers. Apolipoprotein E genotype is implemented as a difference in microglia clearance. By incorporating antibody‐bound, plaque‐mediated macrophage activation in the perivascular compartment, the model also predicts the incidence of amyloid‐related imaging abnormalities with edema (ARIA‐E). The QSP platform is calibrated with pharmacological and clinical information on aducanumab, bapineuzumab, crenezumab, gantenerumab, lecanemab, and solanezumab, predicting adequately the change in PET imaging measured amyloid load and the changes in the plasma Aβ42/Aβ40 ratio while slightly overestimating the change in CSF Aβ42. ARIA‐E is well predicted for all antibodies except bapineuzumab. This QSP model could support the clinical trial design of different amyloid‐modulating interventions, define optimal titration and maintenance schedules, and provide a first step to understand the variability of biomarker response in clinical practice.
Risk factors for insomnia and burnout: A longitudinal population‐based cohort study
Authors: Höglund Per , Hakelind Camilla , Nordin Maria , Nordin Steven 
Published: January 2023

AbstractInsomnia and burnout are highly prevalent in the general population, calling for understanding of its causes. Taking a broad approach, the aim of this study was to determine various mental and somatic risk factors for development of insomnia and burnout and stratifying for sex and age group. Questionnaire data were used from a Swedish population‐based sample aged 18–79 years, from which cohorts without insomnia (n = 1702) and without burnout (n = 1972) at baseline were followed‐up after 3 years. Self‐reports of eight mental and somatic conditions at baseline were used as independent variables in logistic regression analyses to predict development of insomnia and burnout at 3‐year follow‐up. All eight studied conditions were significant risk factors for development of both insomnia (odds ratio, OR = 1.62–2.73) and burnout (OR = 2.20–3.21). Burnout and poor self‐rated health had the highest ORs for insomnia, and poor self‐rated health, anxiety and somatic symptoms had the highest ORs for burnout. The ORs were generally similar between men and women, whereas age groups tended to differ in some of the risk factors. The study highlights the importance of a broad assessment of both mental and somatic conditions in the prevention of insomnia and burnout.
A Monolayer MoS2 FET with an EOT of 1.1 nm Achieved by the Direct Formation of a High‐κ Er2O3 Insulator Through Thermal Evaporation
Authors: Uchiyama Haruki , Maruyama Kohei , Chen Edward , Nishimura Tomonori , Nagashio Kosuke 
Published: January 2023

AbstractAchieving the direct growth of an ultrathin gate insulator with high uniformity and high quality on monolayer transition metal dichalcogenides (TMDCs) remains a challenge due to the chemically inert surface of TMDCs. Although the main solution for this challenge is utilizing buffer layers before oxide is deposited on the atomic layer, this method drastically degrades the total capacitance of the gate stack. In this work, we constructed a novel direct high‐κ Er2O3 deposition system based on thermal evaporation in a differential‐pressure‐type chamber. A uniform Er2O3 layer with an equivalent oxide thickness of 1.1 nm was achieved as the gate insulator for top‐gated MoS2 field‐effect transistors (FETs). The top gate Er2O3 insulator without the buffer layer on MoS2 exhibited a high dielectric constant that reached 18.0, which is comparable to that of bulk Er2O3 and is the highest among thin insulators (< 10 nm) on TMDCs to date. Furthermore, the Er2O3/MoS2 interface (Dit ≈ 6 × 1011 cm−2 eV−1) is confirmed to be clean and is comparable with that of the h‐BN/MoS2 heterostructure. These results prove that high‐quality dielectric properties with retained interface quality can be achieved by this novel deposition technique, facilitating the future development of 2D electronics.
A model‐based systems engineering framework for quantum dot solar cells development
Authors: Karimaghaei Mina , Cloutier Robert , Khan Aurangzeb , Richardson Joseph D. , Phan Anh‐Vu 
Published: January 2023

AbstractCurrently, a wide range of newly designed devices are based on high‐end quantum technologies. To successfully design a quantum system, it is necessary to appropriately address the increasing complexity which exists in the development procedure of the system. A suitable approach to deal with this problem is to employ systems engineering models and integrate them with domain engineering tools. The model‐based systems engineering (MBSE) methodology is commonly used to analyze, design, manufacture, and test various complex systems. In this paper, the MBSE approach is chosen for the development of quantum dot solar cells as a typical quantum system and to deal with the complexity existing in this procedure. The analysis, manufacturing, and verification, validation, and testing (VV&T) for this system are described using SysML in Cameo Systems Modeler software to represent the role of models in this regard. Then a detailed design is performed in MATLAB and integrated with SysML to identify how changing various parameters during the system development process affects the overall system performance. This technique facilitates the communication between different engineering teams and helps to manage the complexity in the entire system lifecycle.
Broadening Benefits and Anticipating Tradeoffs with a Proposed Ecosystem Service Analysis Framework for the US Army Corps of Engineers
Authors: Wainger Lisa A. , Murray Elizabeth O. , Theiling Charles H. , McMurray Anna M. , Cushing Janet A. , Komlos Shawn B. , Cofrancesco Alfred F. 
Published: January 2023

AbstractWould-be adopters of ecosystem service analysis frameworks might ask, ‘Do such frameworks improve ecosystem service provision or social benefits sufficiently to compensate for any extra effort?’ Here we explore that question by retrospectively applying an ecosystem goods and services (EGS) analysis framework to a large river restoration case study conducted by the US Army Corps of Engineers (USACE) and comparing potential time costs and outcomes of traditional versus EGS-informed planning. USACE analytic methods can have a large influence on which river and wetland restoration projects are implemented in the United States because they affect which projects or project elements are eligible for federal cost-share funding. A new framework is designed for the USACE and is primarily distinguished from current procedures by adding explicit steps to document and compare tradeoffs and complementarity among all affected EGS, rather than the subset that falls within project purposes. Further, it applies economic concepts to transform ecological performance indicators into social benefit indicators, even if changes cannot be valued. We conclude that, for large multi-partner restoration projects like our case study, using the framework provides novel information on social outcomes that could be used to enhance project design, without substantially increasing scoping costs. The primary benefits of using the framework in the case study appeared to stem from early comprehensive identification of stakeholder interests that might have prevented project delays late in the process, and improving the communication of social benefits and how tradeoffs among EGS benefits were weighed during planning.
Social Distancing Network Creation
Authors: Friedrich Tobias , Gawendowicz Hans , Lenzner Pascal , Melnichenko Anna 
Published: January 2023

AbstractDuring a pandemic people have to find a trade-off between meeting others and staying safely at home. While meeting others is pleasant, it also increases the risk of infection. We consider this dilemma by introducing a game-theoretic network creation model in which selfish agents can form bilateral connections. They benefit from network neighbors, but at the same time, they want to maximize their distance to all other agents. This models the inherent conflict that social distancing rules impose on the behavior of selfish agents in a social network. Besides addressing this familiar issue, our model can be seen as the inverse to the well-studied Network Creation Game by Fabrikant et al. (in: PODC 2003, pp 347–351, 2003. https://doi.org/10.1145/872035.872088), where agents aim at being as central as possible in the created network. We look at two variants of network creation governed by social distancing. Firstly, a variant without connection restrictions, where we characterize optimal and equilibrium networks, and derive asymptotically tight bounds on the Price of Anarchy and Price of Stability. The second variant allows connection restrictions. As our main result, we prove that Swap-Maximal Routing-Cost Spanning Trees, an efficiently computable weaker variant of Maximum Routing-Cost Spanning Trees, actually resemble equilibria for a significant range of the parameter space. Moreover, we give almost tight bounds on the Price of Anarchy and Price of Stability. These results imply that under social distancing the agents’ selfishness has a strong impact on the quality of the equilibria.
An integrated simulation–optimization framework for assessing environmental flows in rivers
Authors: Sedighkia Mahdi , badrzadeh Nasrin , Fathi Zeynab , Abdoli Asghar , Datta Bithin 
Published: January 2023

AbstractThe present study proposes an integrated simulation–optimization framework to assess environmental flow by mitigating environmental impacts on the surface and ground water resources. The model satisfies water demand using surface water resources (rivers) and ground water resources (wells). The outputs of the ecological simulation blocks of river ecosystem and the ground water level simulation were utilized in a multiobjective optimization model in which six objectives were considered in the optimization model including (1) minimizing losses of water supply (2) minimizing physical fish habitat losses simulated by fuzzy approach (3) minimizing spawning habitat losses (4) minimizing ground water level deterioration simulated by adaptive neuro fuzzy inference system(ANFIS) (5) maximizing macroinvertebrates population simulated by ANFIS (6) minimizing physical macrophytes habitat losses. Based on the results in the case study, ANFIS-based model is robust for simulating key factors such as water quality and macroinvertebrate’s population. The results demonstrate the reliability and robustness of the proposed method to balance environmental requirements and water supply. The optimization model increased the percentage of environmental flow in the drought years considerably. It supplies 69% of water demand in normal years, while the environmental impacts on the river ecosystem are minimized. The proposed model balances the portion of using surface water and ground water in water supply considering environmental impacts on both sources. Using the proposed method is recommendable for optimal environmental management of surface water and ground water in river basin scale.
Invasive or More Direct Measurements Can Provide an Objective Early-Stopping Ceiling for Training Deep Neural Networks on Non-invasive or Less-Direct Biomedical Data
Authors: Bartlett Christopher W. , Bossenbroek Jamie , Ueyama Yukie , McCallinhart Patricia , Peters Olivia A. , Santillan Donna A. , Santillan Mark K. , Trask Aaron J. , Ray William C. 
Published: January 2023

AbstractEarly stopping is an extremely common tool to minimize overfitting, which would otherwise be a cause of poor generalization of the model to novel data. However, early stopping is a heuristic that, while effective, primarily relies on ad hoc parameters and metrics. Optimizing when to stop remains a challenge. In this paper, we suggest that for some biomedical applications, a natural dichotomy of invasive/non-invasive measurements, or more generally proximal vs distal measurements of a biological system can be exploited to provide objective advice on early stopping. We discuss the conditions where invasive measurements of a biological process should provide better predictions than non-invasive measurements, or at best offer parity. Hence, if data from an invasive measurement are available locally, or from the literature, that information can be leveraged to know with high certainty whether a model of non-invasive data is overfitted. We present paired invasive/non-invasive cardiac and coronary artery measurements from two mouse strains, one of which spontaneously develops type 2 diabetes, posed as a classification problem. Examination of the various stopping rules shows that generalization is reduced with more training epochs and commonly applied stopping rules give widely different generalization error estimates. The use of an empirically derived training ceiling is demonstrated to be helpful as added information to leverage early stopping in order to reduce overfitting.
Quota, Class, and Political Violence in Mao's China
Authors: Cheng Yinghong 
Published: January 2023

AbstractBy investigating a one thousandth national execution quota issued in the Campaign to Suppress Counterrevolutionaries (1950–1953), the article explores an aspect of Maoist politics that has largely escaped mainstream scholarship on Mao, the CCP, and PRC history. It shows how the newly created Maoist regime sought to eliminate its political enemy based on a specific demographic estimate of one thousandth. Tracing the roots of this quantification of political enemies into Mao's class-analysis theory back to the 1920s and explaining other political campaigns throughout the 1950s as continuations of the party's use of this method, the article argues that quantitative concepts and relations were important instruments in Maoist ideology, the CCP's political strategy and the working of the party-state. By proposing a concept of “quotacide,” the article identifies an ignored type of large-scale, ideologically based, and politically driven homicide in the history of political violence. The article also brings in similar quantitative policies of political suppression in other authoritarian party-states such as the Soviet Union (the 1930s) and North Vietnam (the 1950s) in this context.
Normalization in the simply typed -calculus
Authors: Battyányi Péter , Nour Karim 
Published: January 2023

AbstractIn this paper, in connection with the program of extending the Curry–Howard isomorphism to classical logic, we study the
$\lambda \mu$
-calculus of Parigot emphasizing the difference between the original version of Parigot and the version of de Groote in terms of normalization properties. In order to talk about a satisfactory representation of the integers, besides the usual
$\beta$
-,
$\mu$
-, and
$\mu '$
-reductions, we consider the
$\lambda \mu$
-calculus augmented with the reduction rules
$\rho$
,
$\theta$
and
$\varepsilon$
. We show that we need all of these rules for this purpose. Then we prove that, with the syntax of Parigot, the calculus enjoys the strong normalization property even when we add the rules
$\rho$
,
$\theta$
, and
$\epsilon$
, while the
$\lambda \mu$
-calculus presented with the more flexible de Groote-style syntax, in contrast, has only the weak normalization property. In particular, we present a normalization algorithm for the
$\beta \mu \mu '\rho \theta \varepsilon$
-reduction in the de Groote-style calculus.
Insights into the mechanism of phospholipid hydrolysis by plant non-specific phospholipase C
Authors: Fan Ruyi , Zhao Fen , Gong Zhou , Chen Yanke , Yang Bao , Zhou Chen , Zhang Jie , Du Zhangmeng , Wang Xuemin , Yin Ping , Guo Liang , Liu Zhu 
Published: January 2023

AbstractNon-specific phospholipase C (NPC) hydrolyzes major membrane phospholipids to release diacylglycerol (DAG), a potent lipid-derived messenger regulating cell functions. Despite extensive studies on NPCs reveal their fundamental roles in plant growth and development, the mechanistic understanding of phospholipid-hydrolyzing by NPCs, remains largely unknown. Here we report the crystal structure of Arabidopsis NPC4 at a resolution of 2.1 Å. NPC4 is divided into a phosphoesterase domain (PD) and a C-terminal domain (CTD), and is structurally distinct from other characterized phospholipases. The previously uncharacterized CTD is indispensable for the full activity of NPC4. Mechanistically, CTD contributes NPC4 activity mainly via CTDα1-PD interaction, which ultimately stabilizes the catalytic pocket in PD. Together with a series of structure-guided biochemical studies, our work elucidates the structural basis and provides molecular mechanism of phospholipid hydrolysis by NPC4, and adds new insights into the members of phospholipase family.
Understanding temperature-dependent SU(3) spin dynamics in the S = 1 antiferromagnet Ba2FeSi2O7
Authors: Do Seung-Hwan , Zhang Hao , Dahlbom David A. , Williams Travis J. , Garlea V. Ovidiu , Hong Tao , Jang Tae-Hwan , Cheong Sang-Wook , Park Jae-Hoon , Barros Kipton , Batista Cristian D. , Christianson Andrew D. 
Published: January 2023

AbstractQuantum magnets admit more than one classical limit and N-level systems with strong single-ion anisotropy are expected to be described by a classical approximation based on SU(N) coherent states. Here we test this hypothesis by modeling finite temperature inelastic neutron scattering (INS) data of the effective spin-one antiferromagnet Ba2FeSi2O7. The measured dynamic structure factor is calculated with a generalized Landau-Lifshitz dynamics for SU(3) spins. Unlike the traditional classical limit based on SU(2) coherent states, the results obtained with classical SU(3) spins are in good agreement with the measured temperature dependent spectrum. The SU(3) approach developed here provides a general framework to understand the broad class of materials comprising weakly coupled antiferromagnetic dimers, trimers, or tetramers, and magnets with strong single-ion anisotropy.
Tracking artificial intelligence in climate inventions with patent data
Authors: Verendel Vilhelm 
Published: January 2023

AbstractArtificial intelligence (AI) is spreading rapidly in many technology areas, and AI inventions may help climate change mitigation and adaptation. Previous studies of climate-related AI mainly rely on expert studies of literature, not large-scale data. Here I present an approach to track the relation between AI and climate inventions on an economy-wide scale. Analysis of over 6 million US patents, 1976 to 2019, shows that within climate patents, AI is referred to most often in transportation, energy and industrial production technologies. In highly cited patents, AI occurs more frequently in adaptation and transport than in other climate mitigation areas. AI in climate patents was associated with around 30–100% more subsequent inventions when counting all technologies. Yet AI-climate patents led to a greater share of citations from outside the climate field than non-AI-climate patents. This suggests the importance of tracking both increased invention activity and the areas where subsequent inventions emerge.
Anthropogenic edge effects and aging errors by hunters can affect the sustainability of lion trophy hunting
Authors: Loveridge Andrew J. , Wijers Matthew , Mandisodza-Chikerema Roseline , Macdonald David W. , Chapron Guillaume 
Published: January 2023

AbstractMany large predator populations are in decline globally with significant implications for ecosystem integrity and function. Understanding the drivers of their decline is required to adequately mitigate threats. Trophy hunting is often cited as a tool to conserve large mammal populations but may also have negative impacts if not well managed. Here we use a spatially implicit, individual based model to investigate the threats posed to African lion populations by poorly managed trophy hunting and additive anthropogenic mortality such as poaching and retaliatory killing. We confirm the results of previous studies that show that lion trophy hunting can be sustainable if only older male lions are hunted, but demonstrate that hunting becomes unsustainable when populations are exposed to additional anthropogenic mortality, as is the case for most free ranging populations. We show that edge effects can be a critical determinant of population viability and populations that encompass well protected source areas are more robust than those without. Finally, errors in aging of hunted lions by professional trophy hunters may undermine the sustainability of the age-based quota setting strategies that are now widely used to manage lion trophy hunting. The effect of aging errors was most detrimental to population persistence in the ≥ 6 and ≥ 7 year-old age thresholds that are frequently used to define suitably aged lions for hunting. Resource managers should limit offtakes to older demographics and additionally take a precautionary approach when setting hunting quotas for large carnivore populations that are affected by other sources of anthropogenic mortality, such as bush-meat poaching, retaliatory killing and problem animal control.