bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and comparison of model‐integrated evidence approaches for bioequivalence studies with pharmacokinetic end points
Authors: Chen Xiaomei , Nyberg Henrik B. , Donnelly Mark , Zhao Liang , Fang Lanyan , Karlsson Mats O. , Hooker Andrew C. 
Published: August 2024

AbstractBy applying nonlinear mixed‐effect (NLME) models, model‐integrated evidence (MIE) approaches are able to analyze bioequivalence (BE) data with pharmacokinetic end points that have sparse sampling, which is problematic for non‐compartmental analysis (NCA). However, MIE approaches may suffer from inflation of type I error due to underestimation of parameter uncertainty and to the assumption of asymptotic normality. In this study, we developed a MIE BE analysis method that is based on a pre‐defined model and consists of several steps including model fitting, uncertainty assessment, simulation, and BE determination. The presented MIE approach has several improvements compared with the previously reported model‐integrated methods: (1) treatment, sequence, and period effects are only added to absorption parameters (such as relative bioavailability and rate of absorption) instead of all PK parameters; (2) a simulation step is performed to generate confidence intervals of the pharmacokinetic metrics for BE assessment; and (3) in an effort to maintain type I error, two more advanced parameter uncertainty evaluation approaches are explored, a nonparametric (case resampling) bootstrap, and sampling importance resampling (SIR). To evaluate the developed method and compare the uncertainty assessment methods, simulation experiments were performed for BE studies using a two‐way crossover design with different amounts of information (sparse to rich designs) and levels of variability. Based on the simulation results, the method using SIR for parameter uncertainty quantification controls type I error at the nominal level of 0.05 (i.e., the significance level set for BE evaluation) even for studies with small sample size and/or sparse sampling. As expected, our MIE approach for BE assessment exhibited higher power than the NCA‐based method, especially as the data becomes sparser and/or more variable.
Nanostructured Surfaces Enhance Nucleation Rate of Calcium Carbonate
Authors: Armstrong Tobias , Schmid Julian , Niemelä Janne‐Petteri , Utke Ivo , Schutzius Thomas M. 
Published: August 2024

AbstractNucleation and growth of calcium carbonate on surfaces is of broad importance in nature and technology, being essential to the calcification of organisms, while negatively impacting energy conversion through crystallization fouling, also called scale formation. Previous work studied how confinements, surface energies, and functionalizations affect nucleation and polymorph formation, with surface‐water interactions and ion mobility playing important roles. However, the influence of surface nanostructures with nanocurvature—through pit and bump morphologies—on scale formation is unknown, limiting the development of scalephobic surfaces. Here, it is shown that nanoengineered surfaces enhance the nucleation rate by orders of magnitude, despite expected inhibition through effects like induced lattice strain through surface nanocurvature. Interfacial and holographic microscopy is used to quantify crystallite growth and find that nanoengineered interfaces experience slower individual growth rates while collectively the surface has 18% more deposited mass. Reconstructions through nanoscale cross‐section imaging of surfaces coupled with classical nucleation theory—utilizing local nanocurvature effects—show the collective enhancement of nano‐pits.
Effects of Pre‐Placed Nano‐TiC Powder on the Performance of Steel/Aluminum Laser Welded Joints
Authors: Zhu Zhiwei , Guo Yonghuan , Zhang Xinran , Lu Xiangning , Wang Xiwen 
Published: August 2024

The steel/aluminum dissimilar metal welding plays a significant role in lightweighting automotive structures. However, the formation of hard and brittle intermetallic compounds (IMCs) in steel/aluminum welded joints severely compromises their mechanical performance. Nano ceramic particles such as TiC possess characteristics that inhibit the diffusion of Fe and Al, thereby exhibiting a significant advantage in suppressing IMCs formation in steel/aluminum welded joints. In this study, an optimized laser‐welding process is employed to investigate the mechanical properties of steel/aluminum dissimilar metal joints with different concentrations of TiC nanoparticles. It is aimed to determine the optimal TiC addition concentration by comparing the mechanical performance. Additionally, the inhibitory effect of TiC particles on the formation and growth of brittle Fe–Al IMCs is explored through an analysis of IMCs growth kinetics. In the research results, it is shown that the optimal TiC addition concentration is 1%. At this concentration, the tensile strength of the steel/aluminum welded joint reaches 98.29 MPa, showing a remarkable improvement of 32.65% compared to the sample without TiC addition. The addition of TiC particles suppresses the mutual diffusion between Fe and Al, reduces the generation of brittle IMCs, and enhances the mechanical performance of the steel/aluminum joint.
The Role of English and Its Myths in the Emergence of First Language Dissociation among Some Japanese‐English Late Plurilinguals
Authors: Moore Ashley R. 
Published: August 2024

AbstractLinguistic distancing behaviours indicative of linguistic dissociation (Moore, 2023) have been documented in social scientific and literary accounts focusing on the lives of Japanese‐English late plurilinguals (LPs; e.g. Harrison, 2011; Kelsky, 2001; McMahill, 2001; Mori, 1997; Takahashi, 2013). Across these cases, diverse Japanese‐English LPs report distancing themselves from their first language (L1), Japanese, often linking it to negative affective states. However, the causes of these distancing behaviours remain underexplained. I share the results of a critical realist grounded theory method study into the causes of L1 dissociation among 17 Japanese‐English LPs. Data sources included interviews, narrative elicitation “comfort graphs,” and language use journals. My theory posits a complex set of psychological and social causal factors, including the onset of additional language acquisition, the experience of significant intersubjective conflict encoded in their L1 Japanese and the distorting effects of linguaculture ideologies rooted in racist Orientalist logics (Befu, 2001). These findings both further our understanding of linguistic dissociation and, because the data indicate that language education is a primary site for the propagation of these misleading linguaculture ideologies, underscores the importance of better and more critical education for language teachers and, by extension, their students.
A case report of feline mast cell tumour with intertumoral heterogeneity: Identification of secondary mutations c.998G>C and c.2383G>C in KIT after resistance to toceranib
Authors: Tani Hiroyuki , Hifumi Tatsuro , Ito Keita , Kuramoto Tomohide , Miyoshi Noriaki , Fujiki Makoto , Nakayama Tomohiro 
Published: August 2024

AbstractA 12‐year‐old male domestic cat with multiple subcutaneous mast cell tumours (MCTs) presented with a 2‐week history of pruritus and raw/bleeding skin from self‐trauma at Kagoshima University Veterinary Teaching Hospital. Polymerase chain reaction (PCR) and histopathological analyses revealed intertumoral heterogeneity among tumour locations based on the mutation status of KIT. In addition, the expression pattern of KIT was characterized. After failed treatment with vinblastine (2.0–2.2 mg/m2, intravenous administration, two doses in total) or nimustine (25 mg/m2, intravenous administration, two doses in total), toceranib (2.2–2.6 mg/kg, orally administered, every other day) was administered to treat recurrent MCTs harbouring the KIT exon eight internal tandem duplication mutation, achieving a complete response. However, toceranib resistance developed 2 months after treatment initiation. Subsequent PCR analysis was conducted to identify the mutational status of KIT in each MCT and to detect the presence of secondary mutations associated with the acquisition of toceranib resistance. Secondary KIT mutations (c.998G>C and c.2383G>C), which were not initially detected in tumour cells at diagnosis, were identified after the development of resistance to toceranib. This indicates that the tumour cells in feline MCTs in the same case have diverse characteristics. Our findings encourage further investigation into the development of therapeutic strategies for feline MCTs, particularly focusing on the heterogeneous nature of KIT/KIT and overcoming acquired resistance to toceranib.
Temporal and spatial changes in the abundance of antibiotic resistance gene markers in a wastewater treatment plant
Authors: Cailleau Guillaume , Junier Thomas , Paul Christophe , Fatton Mathilda , Corona‐Ramirez Andrea , Gning Ophelie , Beck Karin , Vidal Jacques , Bürgmann Helmut , Junier Pilar 
Published: August 2024

AbstractIn this study, we investigated the temporal and spatial quantitative changes in the concentration of antibiotic resistance gene (ARG) markers in a municipal wastewater treatment plant (WWTP). Four ARGs conferring resistance to different classes of antibiotics (ermB, sul1, tet[W], and blaCTXM) and a gene used as a proxy for ARG pollution (intl1) were quantified in two separate sampling campaigns covering two and half years of operation of the WWTP. First, a systematic monthly monitoring of multiple points in the inlet and the outlet revealed an absolute decrease in the concentration of all analyzed ARGs. However, the relative abundance of sul1 and intl1 genes relative to the total bacterial load (estimated using the universal marker 16S rDNA) increased in the outlet samples as compared to the inlet. To pinpoint the exact stage of removal and/or enrichment within the WWTP, a second sampling including the stages of the biological treatment was performed bimonthly. This revealed a distinct enrichment of sul1 and intl1 genes during the biological treatment phase. Moreover, the temporal and spatial variations in ARG abundance patterns within the WWTP underscored the complexity of the dynamics associated with the removal of ARGs during wastewater treatment. Understanding these dynamics is pivotal for developing efficient strategies to mitigate the dissemination of ARGs in aquatic environments.Practitioner points
Regular monitoring of ARG markers in WWTPs is essential to assess temporal and spatial changes, aiding in the development of effective mitigation strategies.
Understanding the dynamics of ARG abundance during biological treatment is crucial for optimizing processes and minimizing dissemination in aquatic environments.
Increased relative abundance of certain ARGs highlights potential enrichment during wastewater treatment, necessitating targeted interventions.
Systematic monitoring of multiple points within WWTPs can provide valuable insights into the efficacy of treatment processes in reducing ARG levels over time.
The complexity of ARG abundance patterns underscores the need to develop holistic approaches to tackle antibiotic resistance in wastewater systems.
Decolonizing leadership knowledge: Context, culture, and complexity
Authors: Owen Julie E. , Pacheco Derrick R. , Yamanaka Aoi 
Published: August 2024

AbstractLeadership knowledge is viewed as an essential aspect of overall leadership learning, yet questions abound as to who decides what forms of knowledge are recognized as legitimate. This article reviews existing frames of leadership knowledge along with prior attempts to codify leadership knowledge. We then examine the function of leadership knowledge within the leadership learning framework (LLF) and explore how it connects to and illuminates other facets of the LLF model. Finally, critical questions are asked about the future evolution of leadership knowledge and the roles of context, culture, and complexity in decolonizing leadership knowledge.
Partisanship and Export Performance: The Conditional Effect of Left-Wing Government on Latin America’s Exportation
Authors: Cheng Wenjun 
Published: August 2024

AbstractAre there noticeable differences among political parties over the countries’ export performance? Are left-wing parties more protectionist in free trade than right-wing parties in Latin American countries, where Import Substitution Industrialization remains a legacy? This paper argues that partisanship matters, but the effects on export are more heterogeneous than previous research has acknowledged. Contrary to conventional wisdom, the left-wing governments favor exportation, and they export more instead of being protectionist when domestic industries have underperformed. Cross-country data of 15 Latin American and Caribbean countries from 1995 to 2019 supports our prediction of the conditional effect, leading to a variation in their export performance. We also test such a conditional effect on the subdivision of trade categories and trading partners, to assess more accurately how exactly this effect plays out. These findings have implications for the studies of trade and for Sino-Latin American relations in a changing global context.
National Digital Development Strategy and Its Practice in India
Authors: Zhang Li , Hu Dayi 
Published: August 2024

AbstractGlobalization has produced a wide range of convergence effects. Digital strategies, popular in developed countries, have won a more durable favor among and followed by developing countries, and become the focus of their development, which is also determined by the fact that digital strategies serve as a tremendous impetus in promoting national economic growth and political governance. However, different from the digital development pattern adopted by developed countries, which is mainly based on the spontaneous growth of the market, the situation in developing countries often encounters more serious market malfunction, hence, government’s intervention and the role of transnational capital under open pattern are more needed. Therefore, the construction of a digital development strategy model for developing countries based on the supply side perspective is supposed to include at least the following elements: government, domestic private capital, and transnational capital as well as the interactions among them. Based on this framework, this paper also analyzes how the digital strategy was formulated and implemented in India. The development of India’s digital strategy suggests that a clear digital strategy can generate positive results, specifically, through establishing government-oriented public–private partnership, the construction of digital infrastructure can be strengthened, the leading industries in the digital field can get strong support, and the spillover effect of digital strategy can get enough attention from parties concerned. However, just as every coin has two sides, the other side of digital strategy shouldn’t be neglected. Digital strategy itself can only accelerate the development of a country, but it cannot fundamentally solve other internal problems existing in the economic and social development of a country, such as the limited role of the government rendered by national fiscal conditions, deep-rooted regional differentiation, improper policy-making orientation as well as conservatism, which will make it difficult for the government, private capital and transnational capital to achieve synergistic effect at a higher level, thus, restricting the realization of the national digital development strategy.
Comparing Adopter, Tester, and Non-adopter of Collaborative Augmented Reality for Industrial Services
Authors: Müller Maike , Ohlig Stefan , Stegelmeyer Dirk , Mishra Rakesh 
Published: August 2024

AbstractCollaborative augmented reality (CAR) is a remote collaboration technology that utilizes augmented reality (AR) to create a shared environment for distributed collaborators conducting physical tasks. CAR became commercially available a few years ago, and its industrial adoption was accelerated by the contact and travel restrictions imposed during the Covid-19 pandemic to provide industrial services. However, it seems that despite implementation, the technology is not fully embraced and used regularly. Therefore, the objective of this paper is to explore differences in the assessment of perceived benefits, opportunities, challenges, and barriers in implementing CAR among different adoption status groups (i.e., Adopters, Testers, and Non-adopters). To achieve this objective, we conducted a survey in the German capital equipment industry. With a sample size of 130 companies, our study is the first attempt to quantitatively explore CAR adoption in the capital equipment industry and it provides valuable insights into the reasons for potential hesitations in adopting CAR.
Binary Segmentation of Malaria Parasites Using U-Net Segmentation Approach: A Case of Rwanda
Authors: Akpo Eugenia M. , Mukamakuza Carine P. , Tuyishimire Emmanuel 
Published: August 2024

AbstractMalaria is a significant health issue in Rwanda. Its accurate identification is essential for effective treatment. Traditional methods, such as microscopy, often face limitations in these contexts. This paper investigates how advanced machine learning techniques can address diagnostic challenges commonly encountered in resource-limited settings like Rwanda. A powerful deep learning framework known as U-Net was utilized in this study to identify different types of malaria. This method demonstrated the ability to accurately identify the disease at a highly detailed level, yielding promising results. The findings from this study could contribute to the development of computer-aided diagnostic tools specifically designed for regions with limited resources. These tools could assist healthcare professionals in decision-making processes and enhance patient outcomes.
PLC-Based Traffic Light Control for Flexible Testing of Automated Mobility
Authors: Wágner Tamás , Tettamanti Tamás , Varga Balázs , Varga István 
Published: August 2024

AbstractRoad infrastructure has evolved to meet diverse needs over time. This makes modernizing traffic control systems also necessary in order to keep pace with technological innovations and changing user habits. This paper presents a novel design and implementation strategy for the next generation of traffic control systems, with particular emphasis on the challenges posed by the integration of automated vehicles. General flexibility in future traffic management, proper use of standardized communication protocols, and safety solutions are essential factors in addressing the traffic challenges of the coming decades. The system has been developed primarily for PLCs (Programmable Logic Controllers) and has been tested and verified, providing the advantages of safety elements and software safety solutions. The proposed system demonstrated efficient and reliable performance while the applied OPC UA (Open Platform Communications Unified Architecture) communication protocol assured robustness and secure client-to-PLC communication.
An Improved Technique for Generating Effective Noises of Adversarial Camera Stickers
Authors: Okada Satoshi , Mitsunaga Takuho 
Published: August 2024

AbstractCyber-physical systems (CPS) represent the integration of the physical world with digital technologies and are expected to change our everyday lives significantly. With the rapid development of CPS, the importance of artificial intelligence (AI) has been increasingly recognized. Concurrently, adversarial attacks that cause incorrect predictions in AI models have emerged as a new risk. They are no longer limited to digital data and now extend to the physical environment. Thus, they are pointed out to pose serious practical threats to CPS. In this paper, we focus on the “adversarial camera stickers attack,” a type of physical adversarial attack. This attack directly affixes adversarial noise to a camera lens. Since the adversarial noise perturbs various images captured by the camera, it must be universal. To realize more effective adversarial camera stickers, we propose a new method for generating more universal adversarial noise compared to previous research. We first reveal that the existing method for generating noise of adversarial camera stickers does not always lead to the creation of universal perturbations. Then, we address this drawback by improving the optimization problem. Furthermore, we implement our proposed method, achieving an attack success rate 2.5 times higher than existing methods. Our experiments prove the capability of our proposed method to generate more universal adversarial noises, highlighting its potential effectiveness in enhancing security measures against adversarial attacks in CPS.
Artificial Intelligence in Breast Cancer Diagnosis: “Synergy-Net” in Campania FESR-POR (European Fund of Regional Development—Regional Operative Program) Research Project
Authors: Parmeggiani Domenico , Moccia Giancarlo , Luongo Pasquale , Miele Francesco , Allaria Alfredo , Torelli Francesco , Marrone Stefano , Gravina Michela , Sansone Carlo , Bollino Ruggiero , Ruggiero Roberto , Bassi Paola , Sciarra Antonella , Parisi Simona , Fisone Francesca , Donnarumma Maddalena Claudia , Colonnese Chiara , Monica Paola Della , Di Domenico Marina , Docimo Ludovico , Agresti Massimo 
Published: August 2024

AbstractBackground: Nowadays, mammography and DCE-MRI are the gold standard for breast cancer screening. Scientific experience demonstrate an increasing application of Echo elastosonography in breast cancer diagnosis, for this reason, within the Synergy-Net project the objective is to create a system based on machine learning algorithms, a CAD developed with CNNs, capable of representing a decision support in the analysis of echo-elastic sonographic images. Results: 315 female patients at the “Vanvitelli” Breast Unit were subjected to digital 3D mammography tomosynthesis and advanced ultrasound (quantitative Echo elastosonography) and comparative analysis of the two methods. We collected 70 breast cancer, 200 benign pathologies (dropout of 11.1%) and we compared two different homogeneous by composition subgroups (35 with cancer and 100 with benign pathology 20.5%), relating to the diagnostic predictive capabilities of 3D digital mammography and quantitative elastosonography: Group A age 40–50 years, Group B age 50–60 years. Results demonstrate fair predictive performances of echoelastosonography versus traditional mammography, especially in the first group (40–50 years), p < 0.05 in favor of elastosonography regarding sensitivity and accuracy; performances that appear substantially comparable in the second group (50–60 years). We also tested the diagnostic predictive capabilities of the CAD Synergy-Breast-Net achieving encouraging results: Sensitivity 80%, Specificity 72%, Accuracy 74%, Negative Predictive Value 84.7% and Positive Predictive Value 83.3%. Conclusion: From this perspective, the screening of patients aged < 40 years and integrate the main screening activities in patients aged between 40 and 50 years integrated with increasingly high-performance machine learning systems, could represent a valid alternative in the future.