bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fundus autofluorescence abnormalities can predict fluorescein angiography abnormalities in patients with chronic central serous chorioretinopathy
Authors: Mohabati Danial , Boon Camiel J. F. , Hoyng Carel B. , Purtskhvanidze Konstantine , Roider Johann , van Dijk Elon H. C. 
Published: April 2023

Abstract

Purpose
This study is to assess the possible correlation between findings on fundus autofluorescence (FAF) and fluorescein angiography (FA) in patients with chronic central serous chorioretinopathy (cCSC).

Methods
This multicentre retrospective cohort study included 71 cCSC patients (92 eyes) with at least 6 months of follow-up, who had a FAF-FA imaging discrepancy larger than 0.5 optic disc diameters in size in the corresponding areas of hyperfluorescent abnormalities. A comparison was performed between progression in size of areas of hyperautofluorescent retinal pigment epithelium (RPE) abnormalities on FAF (HF-FAF) and the hyperfluorescent areas on FA (HF-FA) at first visit and last visit. The possible correlations were estimated between FAF-FA discrepancy and disease characteristics.

Results
The median area of HF-FAF at first visit was 7.48 mm2 (1.41–27.9). The median area of HF-FA at first visit and last visit was 2.40 mm2 (0.02–17.27) and 5.22 mm2 (0.53–25.62), respectively. FAF-FA discrepancy was associated with follow-up duration and the area of HF-FAF at first visit. A mathematical algorithm for grading FAF-FA discrepancy in time was suggested, which predicted the enlargement of hyperfluorescent RPE abnormalities on FA in 82.6% of cases.

Conclusion
There is a statistically significant relationship between the areas of HF-FAF and HF-FA in cCSC patients with FAF-FA imaging discrepancy at first presentation. Long-term changes in RPE alterations in cCSC on FA can be predicted based on baseline HF-FAF and follow-up duration.
Programa de diabetes: improving diabetes care for undocumented immigrants using the Chronic Care Model at a free community clinic
Authors: Leining Mairi Gael , Zhou Xiaobin , Yenokyan Gayane , Sturm Shaunicy , Meyer Jennifer , Diaz Yomira , Sorenson MaeLin , Chartrand Nina 
Published: April 2023

Abstract
Aims
This study examined whether the Chronic Care Model can be successfully applied to improve health outcome measures for uninsured, undocumented immigrants with diabetes at a free, non-federally funded community clinic.

Methods
Data were collected from 128 uninsured, undocumented immigrants enrolled in Programa de diabetes, a comprehensive diabetes program at People’s Health Clinic based on the six core elements of the Chronic Care Model. All study participants self-identified by the Hispanic ethnicity. A longitudinal study design was used to compare baseline diabetic health measures with outcome data after patient program participation over a 12-month enrollment period. Linear mixed effect model was used to determine the patient specific change in HbA1C across time, controlling for gender, age, food insecurity, income level, diabetes type, and literacy. In addition, McNemar tests were conducted to compare the coverage of eye exams and statin use before and after program enrollment.

Results
After program enrollment, individual specific change in HbA1C was expected to be − 0.201 [95% CI 0.244, − 0.158] % per month after controlling for baseline covariates. There were statistically significant improvements in both eye exam coverage (p < 0.01) and statin use (p < 0.01).

Conclusions
The Chronic Care Model can be successfully applied to improve health outcome measures at a free, non-federally funded community clinic among uninsured, undocumented immigrants, who identify by the Hispanic ethnicity and have the diagnosis of diabetes. Barriers to care including food insecurity, federal poverty level and illiteracy do not preclude glycemic control.
Iruplinalkib (WX‑0593), a novel ALK/ROS1 inhibitor, overcomes crizotinib resistance in preclinical models for non-small cell lung cancer
Authors: Yang Yingying , Zheng Qingmei , Wang Xinmei , Zhao Shuyong , Huang Wenshu , Jia Linchao , Ma Cuicui , Liu Shicong , Zhang Yongpeng , Xin Qianqian , Sun Yan , Zheng Shansong 
Published: April 2023

AbstractDespite remarkable initial responses of anaplastic lymphoma kinase (ALK) inhibitors inALK-positive non-small cell lung cancer (NSCLC) patients, cancers eventually develop resistance within one to two years. This study aimed to compare the properties of iruplinalkib (WX‑0593) with other ALK inhibitors and report the comprehensive characterization of iruplinalkib against the crizotinib resistance. The inhibitory effect of iruplinalkib on kinase activity was detected. A kinase screen was performed to evaluate the selectivity of iruplinalkib. The effect of iruplinalkib on related signal transduction pathways of ALK and c-ros oncogene 1 (ROS1) kinases was examined. The cellular and in vivo activities of ALK inhibitors were compared in engineered cancer-derived cell lines and in mice xenograft models, respectively. Human hepatocytes derived from three donors were used for evaluating hepatic enzyme inducing activity. HEK293 cell lines expressing transportors were used to invesigated the drug interaction potential mediated by several transporters. The results showed iruplinalkib potently inhibited the tyrosine autophosphorylation of wild-type ALK, ALKL1196M, ALKC1156Yand epidermal growth factor receptor (EGFR)L858R/T790M. The inhibitory effects of iruplinalkib in patient-derived xenograft and cell line-derived xenograft models were observed. Moreover, iruplinalkib showed robust antitumor effects in BALB/c nude mice xenograft models with ALK-/ROS1-positive tumors implanted subcutaneously, and the tumor suppressive effects in crizotinib-resistant model was significantly better than that of brigatinib. Iruplinalkib did not induce CYP1A2, CYP2B6 and CYP3A4 at therapeutic concentration, and was also a strong inhibitor of MATE1 and MATE2K transporters, as well as P-gp and BCRP. In conclusion, iruplinalkib, a highly active and selective ALK/ROS1 inhibitor, exhibited strong antitumor effects in vitro and in crizotinib-resistant models.
Classroom transmission processes between teacher support, interest value and negative affect: An investigation guided by situated expectancy-value theory and control-value theory
Authors: Rubach Charlott , Dicke Anna-Lena , Safavian Nayssan , Eccles Jacquelynne S. 
Published: April 2023

AbstractAre motivated students less likely to express negative achievement emotions in math, and how do teachers impact such academic beliefs? Guided by the situated expectancy-value theory and the control-value theory, this study is interested in how teacher support influences students’ negative affect in math through students’ perception of teacher support and students’ interest value (teacher-to-student transmission between and within classes). Thus, associations were modeled at the individual and classroom levels to investigate cross-level interactions. Using data from 1,429 students in grades 7–12 (49% males, 67% Hispanic Americans, 15% Asian Americans, 18% other racial/ethnic groups), cross-level indirect effects suggested an association of teacher-reported support for collaboration and cognitive support with decreasing negative affect through students’ perception of teacher support and students’ interest value. These associations were supported within but not between classes.
Seasonal groundwater salinity dynamics in the mangrove supratidal zones based on shallow groundwater salinity and electrical resistivity imaging data
Authors: Prihantono Joko , Nakamura Takashi , Nadaoka Kazuo , Solihuddin Tubagus , Pryambodo Dino Gunawan , Ramdhan Muhammad , Adi Novi Susetyo , Ilham  , Wirasatriya Anindya , Widada Sugeng 
Published: April 2023

AbstractSoil salinity plays an essential role in the growth of mangroves. Mangroves usually grow in intertidal zones. However, in Karimunjawa National Park (KNP), Indonesia, mangroves are also found in supratidal zones. Thus, this study aims to determine why mangroves can grow in this supratidal zone, even during the dry season. We analyze seasonal changes in groundwater flow and salinity dynamics using the hydraulic head, shallow groundwater salinity, and electrical resistivity imaging (ERI) data. The result shows that variation in groundwater salinity is caused by seawater intrusion, which is generated by a hydraulic gradient due to the sea level being higher than the water table in KNP. Rainfall and evapotranspiration, which change seasonally, likely affect the water table fluctuation and salt concentration. ERI images indicate this seawater intrusion in the top sediment up to the bedrock boundary. However, the resistivity difference in the wet and dry seasons shows that remarkable resistivity change occurs at the deeper layer (50–60 m below ground level (BGL)), likely due to freshwater recharge from rainwater on the land side. Groundwater in the KNP is shallow and saline; thus, mangroves in this zone, e.g., Ceriops tagal and Lumnitzera racemosa, can grow because their roots can reach this groundwater. These mangrove species can still grow in this zone even though the shallow groundwater is very saline (46–50 ppt). However, this condition might cause these mangroves to grow stunted. Thus, freshwater availability is crucial for mangrove growth in this supratidal zone to dilute this high groundwater salinity.
The Principle of Autonomy’s Enduring Validity
Authors: Newhouse Marie 
Published: April 2023

AbstractPauline Kleingeld has argued persuasively that Kant’s Principle of Autonomy draws an analogy between two relationships: 1) that between an individual agent and their maxim, and 2) that between a legislator and their legislation. She also suggests that Kant’s evolving views on the normative significance of popular elections made his analogy inapt, which explains its disappearance from his later writings. This comment concurs with Sorin Baiasu that the merits of Kant’s analogy were untouched by his evolving political views. The analogy presupposes that when lawmakers legislate, they do so as representatives of the people, but even Kant’s mature writings posit that unelected lawmakers are representatives of the people in the necessary sense. Facts about whether a lawmaker acquired legislative authority by election, heredity, or conquest do have normative implications in the larger context of Kant’s political theory, but such facts are necessarily temporally upstream of the relation between legislator and legislation, just as facts about how an agent became rational are upstream of the relation between individual agent and maxim. Because the analogy focuses exclusively on these two relationships, it cannot be damaged by such upstream facts. Moreover, we should consider the possibility that Kant’s Principle of Autonomy compares a human will to the united general will of the people itself rather than to the will of a fallible public official or institution. On this alternative reading, it is even more clear that Kant’s evolving views on the significance of elections could have no possible relevance to the Principle of Autonomy.
Integrated contra-directionally coupled chirped Bragg grating waveguide with a linear group delay spectrum
Authors: Gao Xudong , Xu Zhenzhu , Zhu Yupeng , Yang Chengkun , Han Shoubao , Duan Zongming , Zhang Fan , Dong Jianji 
Published: April 2023

AbstractDue to the advantages of low propagation loss, wide operation bandwidth, continuous delay tuning, fast tuning speed, and compact footprints, chirped Bragg grating waveguide has great application potential in wideband phased array beamforming systems. However, the disadvantage of large group delay error hinders their practical applications. The nonlinear group delay spectrum is one of the main factors causing large group delay errors. To solve this problem, waveguides with nonlinear gradient widths are adopted in this study to compensate for the nonlinear effect of the grating apodization on the mode effective index. As a result, a linear group delay spectrum is obtained in the experiment, and the group delay error is halved.
Graphical Abstract
Egyptian blue, Chinese blue, and related two-dimensional silicates: from antiquity to future technologies. Part A: general properties and historical uses
Authors: Nicola Marco , Gobetto Roberto , Masic Admir 
Published: April 2023

AbstractThe ancient Egyptian blue pigment was developed over 5000 years ago and was used extensively for around four millennia until its use mysteriously declined dramatically during the Early Middle Ages. It recently attracted a lot of attention along with some related materials, leading to a fast-growing number of applications in fields, such as sensors, solar concentrators, energy-saving, and medicine. The new surge in interest began in 1996 with the discovery of their intense NIR photoluminescence that surprisingly can be triggered even by visible light. In 2013, the possibility of exfoliating them and producing NIR luminescent nanosheets was established, expanding the family of 2D nanomaterials. More recently, the discovery of their high antibacterial effects and biocompatibility, and very promising optical, electric and magnetic properties, has further boosted their applications. The characteristics of Egyptian blue are due to its main component: the very stable crystalline compound CaCuSi4O10. This tetragonal sheet silicate is the synthetic analogous of the rare cuprorivaite mineral. In Part A of this review, we summarize the historical uses and main properties (i.e., composition, structure, color, stability, luminescence, and biological activity) of cuprorivaite and related 2D silicates, i.e., BaCuSi4O10(the main constituent of the ancient pigment Chinese Blue), BaCuSi2O6(the main constituent of the ancient pigment Chinese Purple), SrCuSi4O10(synthetic analogous of wesselsite) and BaFeSi4O10(synthetic analogous of gillespite). The Part B of the review will focus on the modern rediscovery of these materials, their modern synthesis and exfoliation, and the innovative applications based on their properties.
A new iterative method for approximating common fixed points of two non-self mappings in a CAT(0) space
Authors: Tufa Abebe Regassa 
Published: April 2023

AbstractIn this paper, we introduce a new iterative process for approximating common fixed points of two non-self mappings in the setting of CAT(0) spaces. Then we establish $$\Delta $$
Δ
-convergence and strong convergence results for two nonexpansive non-self mappings under appropriate conditions. Moreover, we establish strong convergence theorems for approximating common fixed points of two Lipschitz quasi-nonexpansive non-self mappings under some additional conditions. Our results improve, complement and unify most of the results in the literature.
Designing Game-Based Learning for High School Artificial Intelligence Education
Authors: Leitner Maxyn , Greenwald Eric , Wang Ning , Montgomery Ryan , Merchant Chirag 
Published: April 2023

AbstractArtificial Intelligence (AI) permeates every aspect of our daily lives and is no longer a subject reserved for a select few in higher education but is essential knowledge that our youth need for the future. Much is unknown about the level of AI knowledge that is age and developmentally appropriate for high school, let alone about how to teach AI to even younger learners. In this theoretical paper, we discuss the design of a game-based learning environment for high school AI education, drawing upon insights gained from a prior cognitive interview study at a STEM focused private high school. We argue that game-based learning is an excellent fit for AI education due to the commonality of problem solving in both game playing and AI.
The Sleep Revolution Platform: a Dynamic Data Source Pipeline and Digital Platform Architecture for Complex Sleep Data
Authors: Sveinbjarnarson Bjarki Freyr , Schmitz Lisa , Arnardottir Erna Sif , Islind Anna Sigridur 
Published: April 2023

Abstract
Purpose of Review
The complexity of the data collected for sleep research is increasing, and the focal point of sleep research is dependent on a higher number of data sources. Data collected for sleep studies often includes both subjective and objective measurements of sleep quality and is gathered over a more extended period, e.g., for weeks, months, or even years. However, this variety and volume of data make it challenging and time-consuming for researchers to utilize. Therefore, sophisticated data structures are necessary to utilize data in sleep research.

Recent Findings
This paper explores how heterogeneous data sources can be represented in a homogeneous database design. The following research questions drove our work: (i) How can we represent sleep data from heterogeneous sources in a homogenous digital platform database? and (ii) How can a data source pipeline transform various data sources into a homogeneous data format?

Summary
This paper’s main contributions are conceptualizing the design and development of a homogeneous database and digital platform architecture and a data source pipeline that fits well for sleep research in particular and healthcare research in general.
Spatiotemporal key region transformer for visual tracking
Authors: Wu Ruixu , Wen Xianbin , Yuan Liming , Xu Haixia 
Published: April 2023

AbstractVisual tracking is an important field of computer vision research. Although transformer-based trackers have achieved remarkable performance, the transformer structure is globally computationally inefficient, it does not screen important patches, and it cannot focus on key target regions. At the same time, temporal motion features are easily overlooked. To solve these problems, this paper proposes a new method, SKRT, that removes the CNN structure and directly uses a transformer as the backbone network to extract multiframe video features. Then, these feature maps are mixed and superimposed to obtain spatiotemporal information. To focus on important parts efficiently, we use key region extraction to obtain a small set of template and search feature map patches and reinput them into the transformer as a cross-correlation computation. Finally, we predict the position of a tracking object through center-corner prediction. To demonstrate the effectiveness of our method, we conduct experiments on challenging benchmark datasets (GOT-10K, TrackingNet, VOT2018, OTB100, LaSOT), and the results show that SKRT is competitive with other state-of-the-art methods.
Slope stability prediction based on a long short-term memory neural network: comparisons with convolutional neural networks, support vector machines and random forest models
Authors: Huang Faming , Xiong Haowen , Chen Shixuan , Lv Zhitao , Huang Jinsong , Chang Zhilu , Catani Filippo 
Published: April 2023

AbstractThe numerical simulation and slope stability prediction are the focus of slope disaster research. Recently, machine learning models are commonly used in the slope stability prediction. However, these machine learning models have some problems, such as poor nonlinear performance, local optimum and incomplete factors feature extraction. These issues can affect the accuracy of slope stability prediction. Therefore, a deep learning algorithm called Long short-term memory (LSTM) has been innovatively proposed to predict slope stability. Taking the Ganzhou City in China as the study area, the landslide inventory and their characteristics of geotechnical parameters, slope height and slope angle are analyzed. Based on these characteristics, typical soil slopes are constructed using the Geo-Studio software. Five control factors affecting slope stability, including slope height, slope angle, internal friction angle, cohesion and volumetric weight, are selected to form different slope and construct model input variables. Then, the limit equilibrium method is used to calculate the stability coefficients of these typical soil slopes under different control factors. Each slope stability coefficient and its corresponding control factors is a slope sample. As a result, a total of 2160 training samples and 450 testing samples are constructed. These sample sets are imported into LSTM for modelling and compared with the support vector machine (SVM), random forest (RF) and convolutional neural network (CNN). The results show that the LSTM overcomes the problem that the commonly used machine learning models have difficulty extracting global features. Furthermore, LSTM has a better prediction performance for slope stability compared to SVM, RF and CNN models.
Rational Design of Electrode–Electrolyte Interphase and Electrolytes for Rechargeable Proton Batteries
Authors: Su Zhen , Guo Haocheng , Zhao Chuan 
Published: April 2023

AbstractRechargeable proton batteries have been regarded as a promising technology for next-generation energy storage devices, due to the smallest size, lightest weight, ultrafast diffusion kinetics and negligible cost of proton as charge carriers. Nevertheless, a proton battery possessing both high energy and power density is yet achieved. In addition, poor cycling stability is another major challenge making the lifespan of proton batteries unsatisfactory. These issues have motivated extensive research into electrode materials. Nonetheless, the design of electrode–electrolyte interphase and electrolytes is underdeveloped for solving the challenges. In this review, we summarize the development of interphase and electrolytes for proton batteries and elaborate on their importance in enhancing the energy density, power density and battery lifespan. The fundamental understanding of interphase is reviewed with respect to the desolvation process, interfacial reaction kinetics, solvent-electrode interactions, and analysis techniques. We categorize the currently used electrolytes according to their physicochemical properties and analyze their electrochemical potential window, solvent (e.g., water) activities, ionic conductivity, thermal stability, and safety. Finally, we offer our views on the challenges and opportunities toward the future research for both interphase and electrolytes for achieving high-performance proton batteries for energy storage.
Intrinsic Self-Healing Chemistry for Next-Generation Flexible Energy Storage Devices
Authors: Wan Xin , Mu Tiansheng , Yin Geping 
Published: April 2023

AbstractThe booming wearable/portable electronic devices industry has stimulated the progress of supporting flexible energy storage devices. Excellent performance of flexible devices not only requires the component units of each device to maintain the original performance under external forces, but also demands the overall device to be flexible in response to external fields. However, flexible energy storage devices inevitably occur mechanical damages (extrusion, impact, vibration)/electrical damages (overcharge, over-discharge, external short circuit) during long-term complex deformation conditions, causing serious performance degradation and safety risks. Inspired by the healing phenomenon of nature, endowing energy storage devices with self-healing capability has become a promising strategy to effectively improve the durability and functionality of devices. Herein, this review systematically summarizes the latest progress in intrinsic self-healing chemistry for energy storage devices. Firstly, the main intrinsic self-healing mechanism is introduced. Then, the research situation of electrodes, electrolytes, artificial interface layers and integrated devices based on intrinsic self-healing and advanced characterization technology is reviewed. Finally, the current challenges and perspective are provided. We believe this critical review will contribute to the development of intrinsic self-healing chemistry in the flexible energy storage field.