bluuebunny/crossref_metadata_2025_split huggingface dataset:
Defect Driven Opto‐Critical Phases Tuned for All‐Solar Utilization
Authors: Jeem Melbert , Hayano Ayaka , Miyashita Hiroto , Nishimura Mahiro , Fukuroi Kohei , Lin Hsueh‐I , Zhang Lihua , Watanabe Seiichi 
Published: July 2023

AbstractMaterials imbued with uniformly dispersed, photo‐responsive nanoparticles are instrumental in sustainable energy and photonic applications. Conventional methods, however, constrain their all‐solar response. An innovative alternative is proposed: submerged photo‐synthesis of crystallites (SPsC). It is shown that strategic doping with copper and oxygen vacancies can induce opto‐critical phases from the nonstoichiometric tungstic acids (WO3·H2O). These opto‐critical phases enable a dynamic equilibrium shift in lattice defect stabilization, facilitating an unprecedented a whole solar wavelength response. This response manifests as photothermal, photo‐assisted water evaporation, and photo‐electrochemical characteristics. Harnessing all‐solar energy, this one‐pot SPsC strategy may steer the design and development of advanced oxide materials, enhancing functionality across diverse application domains.
Perovskite Smart Windows: The Light Manipulator in Energy‐Efficient Buildings
Authors: Liu Sai , Du Yuwei , Zhang Rui , He Huanfeng , Pan Aiqiang , Ho Tsz Chung , Zhu Yihao , Li Yang , Yip Hin‐Lap , Jen Alex K.Y. , Tso Chi Yan 
Published: July 2023

AbstractUncontrolled sunlight entering through windows contributes to substantial heating and cooling demands in buildings, which leads to high energy consumption from the buildings. Recently, perovskite smart windows have emerged as innovative energy‐saving technologies, offering the potential to adaptively control indoor solar heat gain through their impressive sunlight modulation capabilities. Moreover, harnessing the high‐efficiency photovoltaic properties of perovskite materials, these windows have the potential to generate power, thereby realizing more advanced windows with combined light modulation and energy harvesting capabilities. This review summarizes the recent advancements in various chromic perovskite materials for achieving light modulation, focusing on both perovskite structures and underlying switching mechanisms. The discussion also encompasses device engineering strategies for smart windows, including the improvement of their optical and transition performance, durability, combination with electricity generation, and the evaluation of their energy‐saving performance in building applications. Furthermore, the challenges and opportunities associated with perovskite smart windows are explicated, aimed at stimulating more academic research and advancing their pragmatic implementation for building energy efficiency and sustainability.
Effect of starch content and ultrasonic pretreatment on gelling properties of myofibrillar protein from Lateolabrax japonicus
Authors: Hu Yanyu , Chen Xu , Cai Xixi , Zheng Yunfang , Wang Shaoyun 
Published: July 2023

AbstractTo investigate the protein–starch interactions in myofibrillar protein gels under the ultrasonic pretreatment, the effect of cassava starch content and ultrasonic pretreatment on gelling properties of myofibrillar protein from Lateolabrax japonicus was studied. For the myofibrillar protein–starch (MPS) solutions, the turbidity and elastic modulus increased when the starch content increased from 0% to 8%. For the MPS gels, the hardness, chewiness, gumminess, and water holding capacity increased with the starch content, whereas the cooking loss and whiteness decreased. Starch incorporation promoted the conversion of free water to immobilized water and bound water. The active sulfhydryl content decreased with the starch content, whereas the hydrogen bond and hydrophobic interaction content increased. Fine network structure containing pores at uniform size was formed in the MPS gel at an increased starch content, as shown in the scanning electron microscope images. When the ultrasonic pretreatment was introduced, the elastic modulus of MPS solutions and hardness, chewiness, gumminess, hydrophobic interaction, β‐sheet content, and microstructural compactness of the MPS gels increased, whereas the turbidity of the MPS solutions and cooking loss, whiteness, free water content, active sulfhydryl content, and random coil content of the MPS gels decreased. The MPS gel containing 8% of starch and subjected to ultrasonic pretreatment showed the highest hardness, chewiness, and gumminess of 220, 150, and 160 g, while the lowest cooking loss of 2.5% among all samples. Therefore, the gelling properties of myofibrillar protein from L. japonicus could be enhanced by the starch incorporation, ultrasonic pretreatment, and their synergistic effect.
Distinct neurophysiology during nonword repetition in logopenic and non‐fluent variants of primary progressive aphasia
Authors: Hinkley Leighton B. N. , Thompson Megan , Miller Zachary A. , Borghesani Valentina , Mizuiri Danielle , Shwe Wendy , Licata Abigail , Ninomiya Seigo , Lauricella Michael , Mandelli Maria Luisa , Miller Bruce L. , Houde John , Gorno‐Tempini Maria Luisa , Nagarajan Srikantan S. 
Published: July 2023

AbstractOverlapping clinical presentations in primary progressive aphasia (PPA) variants present challenges for diagnosis and understanding pathophysiology, particularly in the early stages of the disease when behavioral (speech) symptoms are not clearly evident. Divergent atrophy patterns (temporoparietal degeneration in logopenic variant lvPPA, frontal degeneration in nonfluent variant nfvPPA) can partially account for differential speech production errors in the two groups in the later stages of the disease. While the existing dogma states that neurodegeneration is the root cause of compromised behavior and cortical activity in PPA, the extent to which neurophysiological signatures of speech dysfunction manifest independent of their divergent atrophy patterns remain unknown. We test the hypothesis that nonword deficits in lvPPA and nfvPPA arise from distinct patterns of neural oscillations that are unrelated to atrophy. We use a novel structure–function imaging approach integrating magnetoencephalographic imaging of neural oscillations during a non‐word repetition task with voxel‐based morphometry‐derived measures of gray matter volume to isolate neural oscillation abnormalities independent of atrophy. We find reduced beta band neural activity in left temporal regions associated with the late stages of auditory encoding unique to patients with lvPPA and reduced high‐gamma neural activity over left frontal regions associated with the early stages of motor preparation in patients with nfvPPA. Neither of these patterns of reduced cortical oscillations was explained by cortical atrophy in our statistical model. These findings highlight the importance of structure–function imaging in revealing neurophysiological sequelae in early stages of dementia when neither structural atrophy nor behavioral deficits are clinically distinct.
Bloody noise: The impact of blood‐flow artifacts on registration
Authors: Lewis John D. , Fonov Vladimir S. , Collins D. Louis 
Published: July 2023

AbstractBlood‐flow artifacts present a serious challenge for most, if not all, volumetric analytical approaches. We utilize T1‐weighted data with prominent blood‐flow artifacts from the Autism Brain Imaging Data Exchange (ABIDE) multisite agglomerative dataset to assess the impact that such blood‐flow artifacts have on registration of T1‐weighted data to a template. We use a heuristic approach to identify the blood‐flow artifacts in these data; we use the resulting blood masks to turn the underlying voxels to the intensity of the cerebro‐spinal fluid, thus mimicking the effect of blood suppression. We then register both the original data and the deblooded data to a common T1‐weighted template, and compare the quality of those registrations to the template in terms of similarity to the template. The registrations to the template based on the deblooded data yield significantly higher similarity values compared with those based on the original data. Additionally, we measure the nonlinear deformations needed to transform the data from the position achieved by registering the original data to the template to the position achieved by registering the deblooded data to the template. The results indicate that blood‐flow artifacts may seriously impact data processing that depends on registration to a template, that is, most all data processing.
Predictive value of radiomics analysis of enhanced CT for three‐tiered microvascular invasion grading in hepatocellular carcinoma
Authors: Zheng Xin , Xu Yun‐Jun , Huang Jingcheng , Cai Shengxian , Wang Wanwan 
Published: July 2023

AbstractBackgroundMicrovascular invasion (MVI) is a major risk factor, for recurrence and metastasis of hepatocellular carcinoma (HCC) after radical surgery and liver transplantation. However, its diagnosis depends on the pathological examination of the resected specimen after surgery; therefore, predicting MVI before surgery is necessary to provide reference value for clinical treatment. Meanwhile, predicting only the existence of MVI is not enough, as it ignores the degree, quantity, and distribution of MVI and may lead to MVI‐positive patients suffering due to inappropriate treatment. Although some studies have involved M2 (high risk of MVI), majority have adopted the binary classification method or have not included radiomics.PurposeTo develop three‐class classification models for predicting the grade of MVI of HCC by combining enhanced computed tomography radiomics features with clinical risk factors.MethodsThe data of 166 patients with HCC confirmed by surgery and pathology were analyzed retrospectively. The patients were divided into the training (116 cases) and test (50 cases) groups at a ratio of 7:3. Of them, 69 cases were MVI positive in the training group, including 45 cases in the low‐risk group (M1) and 24 cases in the high‐risk group (M2), and 47 cases were MVI negative (M0). In the training group, the optimal subset features were obtained through feature selection, and the arterial phase radiomics model, portal venous phase radiomics model, delayed phase radiomics model, three‐phase radiomics model, clinical imaging model, and combined model were developed using Linear Support Vector Classification. The test group was used for validation, and the efficacy of each model was evaluated through the receiver operating characteristic curve (ROC).ResultsThe clinical imaging features of MVI included alpha‐fetoprotein, tumor size, tumor margin, peritumoral enhancement, intratumoral artery, and low‐density halo. The area under the curve (AUC) of the ROC values of the clinical imaging model for M0, M1, and M2 were 0.831, 0.701, and 0.847, respectively, in the training group and 0.782, 0.534, and 0.785, respectively, in the test group. After combined radiomics analyis, the AUC values for M0, M1, and M2 in the test group were 0.818, 0.688, and 0.867, respectively. The difference between the clinical imaging model and the combined model was statistically significant (p = 0.029).ConclusionThe clinical imaging model and radiomics model developed in this study had a specific predictive value for HCC MVI grading, which can provide precise reference value for preoperative clinical diagnosis and treatment. The combined application of the two models had a high predictive efficacy.
Deep learning proton beam range estimation model for quality assurance based on two‐dimensional scintillated light distributions in simulations
Authors: Lee Eunho , Cho Byungchul , Kwak Jungwon , Jeong Chiyoung , Park Min‐Jae , Kim Sung‐woo , Song Si Yeol , Goh Youngmoon 
Published: July 2023

AbstractBackgroundMany studies have utilized optical camera systems with volumetric scintillators for quality assurances (QA) to estimate the proton beam range. However, previous analytically driven range estimation methods have the difficulty to derive the dose distributions from the scintillation images with quenching and optical effects.PurposeIn this study, a deep learning method utilized to QA was used to predict the beam range and spread‐out Bragg peak (SOBP) for two‐dimensional (2D) map conversion from the scintillation light distribution (LD) into the dose distribution in a water phantom.MethodsThe 2D residual U‐net modeling for deep learning was used to predict the 2D water dose map from a 2D scintillation LD map. Monte Carlo simulations for dataset preparation were performed with varying monoenergetic proton beam energies, field sizes, and beam axis shifts. The LD was reconstructed using photons backpropagated from the aperture as a virtual lens. The SOBP samples were constructed based on monoenergetic dose distributions. The training set, including the validation set, consisted of 8659 image pairs of LD and water dose maps. After training, dose map prediction was performed using a 300 image pair test set generated under random conditions. The pairs of simulated and predicted dose maps were analyzed by Bragg peak fitting and gamma index maps to evaluate the model prediction.ResultThe estimated beam range and SOBP width resolutions were 0.02 and 0.19 mm respectively for varying beam conditions, and the beam range and SOBP width deviations from the reference simulation result were less than 0.1 and 0.8 mm respectively. The simulated and predicted distributions showed good agreement in the gamma analysis, except for rare cases with failed gamma indices in the proximal and field‐marginal regions.ConclusionThe deep learning conversion method using scintillation LDs in an optical camera system with a scintillator is feasible for estimating proton beam range and SOBP width with high accuracy.
Factors influencing oviposition behaviour of the invasive pest, Drosophila suzukii, derived from interactions with other Drosophila species: potential applications for control
Authors: Tungadi Trisna Dewi , Powell Glen , Shaw Bethan , Fountain Michelle T 
Published: July 2023

AbstractDrosophila suzukii (Matsumura) or spotted wing Drosophila is a worldwide invasive pest of soft‐ and stone‐fruit production. Female D. suzukii lay their eggs in ripening fruit and the hatched larvae damage fruit from the inside, rendering it unmarketable and causing significant economic loss. Current methods to reduce D. suzukii population in the field primarily rely on chemical insecticides which are not a sustainable long‐term solution and increase the risk of resistance developing. Several studies demonstrate that when D. suzukii encounter or coexist with other Drosophila on a food source, this is usually a disadvantage to D. suzukii, leading to reduced oviposition and increased larval mortality. These effects have potential to be exploited from a pest management perspective. In this review we summarise recent research articles focusing on the interspecific interactions between D. suzukii and other Drosophila species aimed at understanding how this drives D. suzukii behaviour. Potential semiochemical and microbiome impacts are postulated as determinants of D. suzukii behaviour. Development of control practices focusing on reducing D. suzukii populations and deterring them from laying eggs by utilising factors that drive their behaviour are discussed. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
Unleashing the power of SDN and GNN for network anomaly detection: State‐of‐the‐art, challenges, and future directions
Authors: Dhadhania Archan , Bhatia Jitendra , Mehta Rachana , Tanwar Sudeep , Sharma Ravi , Verma Amit 
Published: July 2023

AbstractModern computer networks' increasing complexity and scale need serious attention towards network anomaly detection. Software‐defined networking (SDN) and graph neural networks (GNN) have emerged as promising approaches for anomaly detection due to their ability to capture dynamic network behavior and learn complex patterns from large‐scale network data. The amalgamation of SDN and GNN for network anomaly detection presents promising opportunities for improving the accuracy and efficiency of network anomaly detection. This paper focuses on various trends, issues, and challenges by integrating GNN on the top of SDN for network anomaly detection. The article highlights the advantages of using SDN for providing fine‐grained control and programmability in network monitoring. At the same time, GNN can model network behavior as a graph and learn representations from graph‐structured data. The authors also discuss the limitations of traditional anomaly detection methods in SDN, such as rule‐based approaches, and the potential of GNN to overcome these limitations by leveraging their ability to capture non‐linear and dynamic patterns in network data. This paper also presents a case study of DoS attack detection using SDN. The result shows that SDN based approach helps to detect attacks with an accuracy of 97% with future research directions.
Correlation of Bread Staling and Starch Digestibility and Role of Carboxymethyl Cellulose
Authors: Arslan‐Tontul Sultan 
Published: July 2023

AbstractThis study aims to correlate bread staling with starch digestibility rate. The study also investigates the effects of the use of an anti‐staling agent (carboxymethyl cellulose (CMC)) on starch digestion and glycemic index value. The results indicate that CMC utilization has an insignificant effect on a specific volume of bread, but, it decreases the crumb and crust lightness. CMC improves the textural properties of bread and reduces hardness during storage. The highest firmness increase is detected in the control sample, and the rate of firmness accelerates after the second day of storage. However, the addition of CMC leads to a decrease in the firmness of the bread. As expected, CMC is effective in slowing bread staling. The most novel results of the study are revealed through starch digestion. That storage period and CMC utilization affect significantly (p < 0.05) starch hydrolysis rate and staling has a decreasing effect on starch digestibility. After 4 days of storage, the expected glycemic index (eGI) decreases in all bread samples, and the highest decrease is observed in 5% CMC‐added bread samples. These results are also correlated with an increase in total dietary fiber content after the storage period.
The International Law of Content Governance
Authors: Celeste Edoardo , Palladino Nicola , Redeker Dennis , Yilma Kinfe 
Published: July 2023

AbstractThis chapter considers the extent to which international law offers guidance to the governance of digital platforms. Recent years have seen a growing attention in the potential of international law in offering normative guidance to address human rights concerns in content governance. The chapter considers whether the recent turn to international law for content governance standards is a worthwhile exercise. It finds that, beset by a host of design and structural constraints, international law does not offer meaningful normative guidance to the governance of and in digital platforms. The chapter then highlights how emergent standards are moving past the regulatory limits of international law.
Shaping Standards from Below: Insights from Civil Society
Authors: Celeste Edoardo , Palladino Nicola , Redeker Dennis , Yilma Kinfe 
Published: July 2023

AbstractThis chapter discusses how civil society groups are articulating rights and principles for the digital age through non-legally binding declarations, known as ‘Internet Bills of Rights’. These documents represent the ‘voice’ of communities that are seeking to redefine core constitutional principles in light of the challenges posed by digital society, resulting in a new form of ‘digital constitutionalism’. The chapter analyses 40 Internet Bills of Rights and their principles related to online content governance, including substantive and procedural standards, as well as ad hoc provisions specifically crafted to address social media platforms. These provisions aim to contextualise and adapt international human rights standards into more granular norms and rules to be implemented in the platform environment.
Platform Policies Versus Human Rights Standards
Authors: Celeste Edoardo , Palladino Nicola , Redeker Dennis , Yilma Kinfe 
Published: July 2023

AbstractThis chapter empirically examines how five social media platforms—Facebook, Instagram, Twitter, TikTok and YouTube—deal with the content governance dilemma and the question of which human rights standard to apply when moderating user content. It builds on previous chapters’ analyses of relevant human rights standards in international law and civil society-issued documents to elucidate to what extent substantial and procedural demands are met by the platforms. After an analysis of platform policies—specifically the human rights commitments included in them, the chapter examines substantive content moderation trends in a comparative way. Thereafter, procedural practices of content moderation including transparency reporting and automated content moderation are comparatively discussed. The chapter finds a relatively high degree of convergence among the platforms on a number of practices.
Conclusion
Authors: Celeste Edoardo , Palladino Nicola , Redeker Dennis , Yilma Kinfe 
Published: July 2023

AbstractThe choice on the law of online content moderation is a conundrum composed of three options, none of which is fully satisfying. International human rights law is not the solution to the content governance dilemma, but its contribution cannot be excluded from the resolution of this issue. A multi-level approach is proposed where multiple actors are instrumental in translating human rights norms into rules that speak to the context of online content governance. This work focuses on the role of civil society organisations. By comparing the demands advanced by civil society actors with platforms’ policies we reconstruct an image of the process of social media constitutionalisation ‘in motion’.
Introduction
Authors: Nyström Höög Catharina , Rahm Henrik , Thomassen Hammerstad Gøril 
Published: July 2023

AbstractThis book deals with the Nordic tradition of sakprosa studies, and the role of complex written texts in an increasingly diverse and dynamic society. Since 2009, the journal Sakprosa—a Nordic publication based in Oslo—has been publishing articles on different aspects of applied linguistics, rhetoric, textual studies, discourse analysis, literature studies, educational studies, communication and adjoining disciplines. The word sakprosa is a compound noun, where the first part sak is a rather polysemic word which means ‘thing’ (or ‘issue’, ‘case’, ‘subject’) and the second part means ‘prose’. Thus, the literal meaning is prose (texts) about things. Common translations are non-fictional prose, subject oriented texts or subject-oriented prose as well as non-literary prose. We use the Scandinavian noun sakprosa as it incorporates all these meanings. The six chapters of this book bring forth different aspects of the concept sakprosa—the text-theoretical framework for Scandinavian sakprosa research, CSR-reporting, changes of sakprosa culture because of the digitizing of communication, a study of a master programme for sakprosa writing, crisis information from a public authority and a concluding summary which re-visits all the chapters and reflects on their contributions to the field of sakprosa studies.
Texts as Cultural Artefacts: Theoretical Challenges to Empirical Research on Utterances and Texts
Authors: Berge Kjell Lars , Ledin Per 
Published: July 2023

AbstractThis chapter presents a theory of texts often used in Scandinavian “sakprosa” research. In the chapter, the constitutive features of any text are presented. It is shown how the text as a cultural artefact has the quality of and at the same time being a unique utterance and instantiating a text norm. In the text theory presented, text is part of a text culture, to which other text sharing similar norms belong. Thus, a “text” is conceived as an utterance that competent participants in a specific cultural time and space assign a certain cultural value.