bluuebunny/crossref_metadata_2025_split huggingface dataset:
Temperature‐Controlled Pathway Complexity in Self‐Assembly of Perylene Diimide‐Polydiacetylene Supramolecule
Authors: Seo Joonsik , Khazi Mohammed Iqbal , Bae Kwangmin , Kim Jong‐Man 
Published: February 2023

AbstractSelf‐assembly process represents one of the most powerful and efficient methods for designing functional nanomaterials. For generating optimal functional materials, understanding the pathway complexity during self‐assembly is essential, which involves the aggregation of molecules into thermodynamically or kinetically favored pathways. Herein, a functional perylene diimide (PDI) derivative by introducing diacetylene (DA) chains (PDI‐DA) is designed. Temperature control pathway complexity with the evolution of distinct morphology for the kinetic and thermodynamic product of PDI‐DA is investigated in detail. A facile strategy of UV‐induced polymerization is adopted to trap and capture metastable kinetic intermediates to understand the self‐assembly mechanism. PDI‐DA showed two kinetic intermediates having the morphology of nanosheets and nanoparticles before transforming into the thermodynamic product having fibrous morphology. Spectroscopic studies revealed the existence of distinct H‐ and J‐aggregates for kinetic and thermodynamic products respectively. The polymerized fibrous PDI‐DA displayed reversible switching between J‐aggregate and H‐aggregate.
Metal Nanoparticles as Novel Agents for Lung Cancer Diagnosis and Therapy
Authors: Zheng Xinjie , Wu Yuan , Zuo Huali , Chen Weiyu , Wang Kai 
Published: February 2023

AbstractLung cancer is one of the most common malignancies worldwide and contributes to most cancer‐related morbidity and mortality cases. During the past decades, the rapid development of nanotechnology has provided opportunities and challenges for lung cancer diagnosis and therapeutics. As one of the most extensively studied nanostructures, metal nanoparticles obtain higher satisfaction in biomedical applications associated with lung cancer. Metal nanoparticles have enhanced almost all major imaging strategies and proved great potential as sensor for detecting cancer‐specific biomarkers. Moreover, metal nanoparticles could also improve therapeutic efficiency via better drug delivery, improved radiotherapy, enhanced gene silencing, and facilitated photo‐driven treatment. Herein, the recently advanced metal nanoparticles applied in lung cancer therapy and diagnosis are summarized. Future perspective on the direction of metal‐based nanomedicine is also discussed. Stimulating more research interests to promote the development of metal nanoparticles in lung cancer is devoted.
The combined effect of fiber and asphalt emulsion on properties of self‐compacting concrete
Authors: Umar Hussaini Abdullahi , Zeng Xiaohui , Long Guangcheng , Li Yirui , Zhao Hong 
Published: February 2023

AbstractSelf‐compacting concrete (SCC) has recently been used in concrete structures due to its improved workability properties compared to conventional concrete; however, the serviceability of SCC structures is usually jeopardized by undesirable impact and dynamic loads due to its brittleness and insufficient toughness. In this study, asphalt emulsion (AE) and fiber were incorporated into SCC to improve its performance properties. SCC samples with basalt fiber (BF), polypropylene fiber (PPF), and polyvinyl alcohol fiber (PVAF) at 0.2%, 0.35%, and 0.5% volume fraction were prepared. Ten percent AE content was used in each mix. The effects of AE and fiber on compressive strength, flexural strength, damping performance, and workability were determined. Results show that incorporating AE and fiber weakens the workability of SCC, and flowability decreases with an increase in fiber content. The compressive strength of SCC decreases when AE is added; however, the incorporation of fiber mitigates this effect. The addition of 10% AE increased the flexural strength by 7.64%, subsequent addition of fiber further increased the flexural strength; the addition of 0.2% BF, PPF, and PVAF increased the flexural strength by 10.14%, 17.94%, and 15.44%, respectively. The damping ratio of SCC increased by 38%, 40%, and 27% through the addition of 0.2% BF, PPF, and PVAF, respectively. However, the damping ratio shows a decreasing trend after adding 0.5% BF and PP fiber.
The literary portfolio: Summative assessment of literary competences in autonomous learning environments
Authors: Siepmann Philipp 
Published: February 2023

AbstractThis article reports on the development of the literary portfolio as an alternative to standard written tests in summative assessment of literary competences in the English as a foreign language (EFL) classroom. It is argued that traditional class tests put a too narrow focus on those aspects of literary competences that are more readily operationalized and thus lend themselves better to testing. This, however, may result in a negative washback on teaching. Building on, and operationalizing, the model of literary competence by Diehr and Surkamp (2015), the literary portfolio is designed to cover the various dimensions of this complex competence. At the same time, it tackles the problem that dealing with class readers often leaves students with little freedom to pursue their own (reading) interests or set priorities in working with the texts. The literary portfolio allows students to take responsibility for their own learning as they can choose a text from a shortlist, tasks to work on, and levels of cooperation with peers. As will be demonstrated in a case study carried out in an eighth‐grade intermediate‐level EFL classroom, the implementation of the literary portfolio entailed an innovative way of learning with literature in an autonomous learning environment.
Inheriting the DNA of emergingness: Strategies of advanced market firms under emerging market ownership
Authors: He Geer , Fukuchi Hiroyuki 
Published: February 2023

AbstractDespite growing concerns about emerging market firms (EMFs)' acquisitions in advanced markets, the influences of emerging market ownership on advanced market firms (AMFs) as targets remain largely underexplored. This study aims to conceptually advance our understanding of the environmental adaptation strategies of AMFs under emerging market ownership, focusing on the strategic implications of the “emergingness” encapsulated in the resource transfer from EMF acquirers to AMF targets. Drawing on the institution‐based view and resource‐based view, this conceptual piece develops an Institution‐Resource‐Strategy framework and proposes two types of strategies for AMFs under emerging market ownership, namely arbitrage and avoidance, each comprising three varying tactics. We illustrate our propositions using three cases of Japanese firms under Chinese ownership. This study adds to the literature on internationalizing EMFs, the institution‐based view of global strategies, and cross‐border mergers and acquisitions and offers managerial implications for emerging and advanced market stakeholders.
Double-copy towards supergravity inflation with α-attractor models
Authors: Carrasco John Joseph M. , Lewandowski Matthew , Pavao Nicolas H. 
Published: February 2023

Abstract
Key to the simplicity of supergravity α-attractor models of inflation are Volkov-Akulov fermions, often in the form of nilpotent superfields. Here we explore the possibility of using the double-copy to construct theories of Dirac-Born-Infeld-Volkov-Akulov (DBIVA) coupled to supergravity. A color-dual bootstrap admits scattering amplitudes involving pions and vectors through five-point tree-level order by order in mass-dimension, but requires the introduction of a Tr(F3) operator. Gauge theories with this operator were recently found to require a tower of higher-derivative operators to be compatible with the duality between color and kinematics. Adjoint-type double-copy construction at its most conservative seems to require the UV completion of DBIVA + pure Poincaré supergravity scattering amplitudes to a family of theories involving DBIVA-like particles coupled to Weyl-Einstein supergravity. We also point out an alternative solution to color-dual gauged pions that allows adjoint double-copy without a tower of higher derivative corrections but at the cost of exchange symmetry between scalars.
Ein Vergleich von 4 konvolutionalen neuronalen Netzen in der histopathologischen Diagnostik von Speicheldrüsenkarzinomen
Authors: Schulz Tobias , Becker Christoph , Kayser Gian 
Published: February 2023

Zusammenfassung
Hintergrund
Maligne Speicheldrüsentumoren sind aufgrund ihrer großen Anzahl an histopathologischen Entitäten, ihres seltenen Auftretens und der Vielfalt der klinischen und histologischen Präsentation eine besondere Herausforderung in der Diagnostik. Ziel der vorliegenden Arbeit ist es, die Anwendung von konvolutionalen neuronalen Netzen (CNN) als Hilfsmittel bei der histologischen Diagnose von malignen Speicheldrüsentumoren zu untersuchen und zu vergleichen.

Methoden
Dazu wurden 118 histologische Schnitte von Speicheldrüsenkarzinompräparaten von 68 Patienten hochauflösend digitalisiert. Diese virtuellen Schnitte wurden in kleine Bildausschnitte unterteilt. Die 83.819 Bilder wurden in 4 Kategorien eingeteilt: Hintergrund, Binde- und Stützgewebe, nichtneoplastisches Speicheldrüsengewebe und Speicheldrüsenkarzinomgewebe, wobei unter der letzten Kategorie die Entitäten adenoidzystisches Karzinom, Adenokarzinom („not otherwise specified“), Azinuszellkarzinom, Basalzellkarzinom, Mukoepidermoidkarzinom und das myoepitheliale Karzinom zusammengefasst wurden. Die kategorisierten Bilder wurden dann in einem Trainings‑, Validierungs- und Testlauf von mit dem Bilddatensatz ImageNet vortrainierten CNN (Inception ResNet v2, Inception v3, ResNet152, Xception) in verschiedenen Pixelgrößen verarbeitet.

Ergebnisse
Die Accuracy-Werte reichten von 18,8–84,7 % über alle Netzarchitekturen und Pixelgrößen, dabei erreichte das Inception-v3-Netz den höchsten Wert bei 500 × 500 Pixel. Die erreichten Recall-Werte bzw. die Sensitivität für verschiedene Pixelgrößen lagen bei bis zu 85 % (Inception-v3-Netz bei 1000 × 1000 Pixel). Der minimal erreichte F1-Score misst 0,07 für das Inception ResNet v2 sowie das Inception v3 bei jeweils 100 × 100 Pixeln, der maximal erreichte F1-Score lag bei 0,72 für das Xception bei 1000 × 1000 Pixeln. Das Netz mit den kürzesten Trainingszeiten war das Inception v3, das allen anderen getesteten Netzen bei jeder Pixelgröße überlegen war.

Schlussfolgerung
In der vorliegenden Arbeit konnte erstmals für den Bereich der histopathologischen Analyse von Speicheldrüsenhistologien die Anwendbarkeit von CNN dargestellt und ein Vergleich der Performance verschiedener Netzarchitekturen angestellt werden. Die Ergebnisse lassen einen deutlichen potenziellen Nutzen zukünftiger Anwendungen erkennen.
miRNAs as biomarkers of autism spectrum disorder: a systematic review and meta-analysis
Authors: Garrido-Torres Nathalia , Guzmán-Torres Karem , García-Cerro Susana , Pinilla Bermúdez Gladys , Cruz-Baquero Claudia , Ochoa Hansel , García-González Diego , Canal-Rivero Manuel , Crespo-Facorro Benedicto , Ruiz-Veguilla Miguel 
Published: February 2023

AbstractAutism spectrum disorder (ASD) is a neurodevelopmental disorder with complex clinical manifestations that arise between 18 and 36 months of age. Social interaction deficiencies, a restricted range of interests, and repetitive stereotyped behaviors are characteristics which are sometimes difficult to detect early. Several studies show that microRNAs (miRs/miRNAs) are strongly implicated in the development of the disorder and affect the expression of genes related to different neurological pathways involved in ASD. The present systematic review and meta-analysis addresses the current status of miRNA studies in different body fluids and the most frequently dysregulated miRNAs in patients with ASD. We used a combined approach to summarize miRNA fold changes in different studies using the mean values. In addition, we summarized p values for differential miRNA expression using the Fisher method. Our literature search yielded a total of 133 relevant articles, 27 of which were selected for qualitative analysis based on the inclusion and exclusion criteria, and 16 studies evaluating miRNAs whose data were completely reported were ultimately included in the meta-analysis. The most frequently dysregulated miRNAs across the analyzed studies were miR-451a, miR-144-3p, miR-23b, miR-106b, miR150-5p, miR320a, miR92a-2-5p, and miR486-3p. Among the most dysregulated miRNAs in individuals with ASD, miR-451a is the most relevant to clinical practice and is associated with impaired social interaction. Other miRNAs, including miR19a-3p, miR-494, miR-142-3p, miR-3687, and miR-27a-3p, are differentially expressed in various tissues and body fluids of patients with ASD. Therefore, all these miRNAs can be considered candidates for ASD biomarkers. Saliva may be the optimal biological fluid for miRNA measurements, because it is easy to collect from children compared to other biological fluids.
Off-policy and on-policy reinforcement learning with the Tsetlin machine
Authors: Rahimi Gorji Saeed , Granmo Ole-Christoffer 
Published: February 2023

AbstractThe Tsetlin Machine is a recent supervised learning algorithm that has obtained competitive accuracy- and resource usage results across several benchmarks. It has been used for convolution, classification, and regression, producing interpretable rules in propositional logic. In this paper, we introduce the first framework for reinforcement learning based on the Tsetlin Machine. Our framework integrates the value iteration algorithm with the regression Tsetlin Machine as the value function approximator. To obtain accurate off-policy state-value estimation, we propose a modified Tsetlin Machine feedback mechanism that adapts to the dynamic nature of value iteration. In particular, we show that the Tsetlin Machine is able to unlearn and recover from the misleading experiences that often occur at the beginning of training. A key challenge that we address is mapping the intrinsically continuous nature of state-value learning to the propositional Tsetlin Machine architecture, leveraging probabilistic updates. While accurate off-policy, this mechanism learns significantly slower than neural networks on-policy. However, by introducing multi-step temporal-difference learning in combination with high-frequency propositional logic patterns, we are able to close the performance gap. Several gridworld instances document that our framework can outperform comparable neural network models, despite being based on simple one-level AND-rules in propositional logic. Finally, we propose how the class of models learnt by our Tsetlin Machine for the gridworld problem can be translated into a more understandable graph structure. The graph structure captures the state-value function approximation and the corresponding policy found by the Tsetlin Machine.
Performance assessment and process optimization of a sulfur recovery unit: a real starting up plant
Authors: Ibrahim Ahmed Y. , Ashour Fatma H. , Gadalla Mamdouh A. , Abdelhaleem Amal 
Published: February 2023

AbstractSulfur recovery units (SRU) have an important role in the industrial production of elemental sulfur from hydrogen sulfide, whereas the generated acidic gas emissions must be controlled and treated based on local and international environmental regulations. Herein, Aspen HYSYS V.11 with Sulsim software is used to simulate the industrial and treatment processes in a refinery plant in the Middle East. In the simulation models, in temperature, pressure, flow, energy, and gas emissions were monitored to predict any expected change that could occur during the industrial processes. The simulation models were validated by comparing the obtained data with actual industrial data, and the results showed low deviation values. The simulation results showed that the current process temperature conditions can work efficiently for sulfur production without causing any environmental consequences. Interestingly, the simulation results revealed that sulfur can be produced under the optimized temperature conditions (20° less than design temperatures) with a total amount of steam reduction by 1040.12 kg/h and without any negative impact on the environment. The steam reduction could have a great economic return, where an average cost of 7.6 $ per ton could be saved with a total estimated cost savings by 69,247.03 $ per year. The simulation revealed an inaccurate production capacity calculated by real data in the plant during the performance test guarantee (PTG) where the real data achieved around 1 ton/h higher capacity than the simulation result, with an overall recovery efficiency of 99.96%. Based on this significant result, a solution was raised, and the level transmitters were calibrated, then the test was repeated. The simulation models could be very useful for engineers to investigate and optimize the reaction conditions during the industrial process in sulfur production facilities. Hence, the engineers can utilize these models to recognize any potential problem, thereby providing effective and fast solutions. Additionally, the simulation models could participate in assessing the performance test guarantee (PTG) calculations provided by the contractor.
Principal’s distributive preferences and the incentivization of agents
Authors: Cêtre Sophie , Lobeck Max 
Published: February 2023

AbstractDo principals' distributive preferences affect the allocation of incentives within firms? We run a Principal-Agent lab experiment, framed as a firm setting. In the experiment, subjects are randomized in the principal or worker position. Principals must choose piece rate wage contracts for two workers that differ in terms of ability. Workers have to choose an effort level that is non-contractible. Principals are either paid in proportion to the output produced (Stakeholder treatment) or paid a fixed wage (Spectator treatment). We study how principals make trade-offs between incentive concerns (motivating workers to maximize output) and their own normative distributive preferences. We find that, despite the firm-frame and the moral hazard situation, principals do hold egalitarian concerns, as principals are on average willing to trade off their firm's performance (and so their own income) for more wage equality among their workers. The willingness to reduce inequality among workers is sensitive to both extensive and intensive margin incentives, which shows that principals' choices are shaped by incentives that they face themselves.
Infinite Volume Gibbs States and Metastates of the Random Field Mean-Field Spherical Model
Authors: Koskinen Kalle 
Published: February 2023

AbstractFor the discrete random field Curie–Weiss models, the infinite volume Gibbs states and metastates have been investigated and determined for specific instances of random external fields. In general, there are not many examples in the literature of non-trivial limiting metastates for discrete or continuous spin systems. We analyze the infinite volume Gibbs states of the mean-field spherical model, a model of continuous spins, in a general random external field with independent identically distributed components with finite moments of some order larger than four and non-vanishing variances of the second moments. Depending on the parameters of the model, we show that there exist three distinct phases: ordered ferromagnetic, ordered paramagnetic, and spin glass. In the ordered ferromagnetic and ordered paramagnetic phases, we show that there exists a unique infinite volume Gibbs state almost surely. In the spin glass phase, we show the existence of chaotic size dependence, provide a construction of the Aizenman–Wehr metastate, and consider both the convergence in distribution and almost sure convergence of the Newman–Stein metastates. The limiting metastates are non-trivial and their structure is universal due to the presence of Gaussian fluctuations and the spherical constraint.
Influence of research on open science in the public policy sphere
Authors: De Filippo Daniela , Sastrón-Toledo Pablo 
Published: February 2023

AbstractThis paper analyses the scientific activity related to open science in Spain and its influence on public policy from a bibliometric perspective. For this purpose, Spanish centres' projects and publications on open science from 2010 to 2020 are studied. Subsequently, policy documents using papers related to open science are analysed to study their influence on policymaking. A total of 142 projects and 1491 publications are analysed, 15% of which are mentioned in policy documents.The publications cited in policy documents display high proportions of international collaboration, open access publication and publication in first-quartile journals. The findings underline governments’ leading role in the implementation of open science policies and the funding of open science research. The same government agencies that promote and fund open science research are shown to use that research in their institutional reports, a process known as knowledge flow feedback. Other non-academic actors are also observed to make use of the knowledge produced by open science research, showing how the open science movement has crossed the boundaries of academia.
Beyond Geography: Social Quality Environments and Health
Authors: Li Yang , Spini Dario , Lampropoulos Dimitrios 
Published: February 2023

AbstractThe concept of social quality has garnered increasing attention as a composite indicator of the well-being of societies as well as individuals embedded within them. Prior research suggests four domains of social quality: socio-economic security, social cohesion, social inclusion, and social empowerment, based on the assumption that these domains influence health and well-being. In this paper, we investigate whether and to what extent social quality environments defined with reference to the cross-cutting social quality domains reliably predict various types of health, using data collected in a municipality in Switzerland as part of a participatory action research project. We found that social inclusion had the highest predictive power for mental health and functional health, while economic security had the highest predictive power for physical capacity and overall self-rated health. Results indicate interaction among various domains of social quality for a subset of health measures. Findings suggest that environments defined as combinations of social quality domains effectively distinguish between population segments with varying levels of health. Social quality represents a promising avenue for policy and intervention development, particularly from the social determinants of health perspective, as it jointly captures the multiple domains of social well-being relevant to population health.