bluuebunny/crossref_metadata_2025_split huggingface dataset:
Partial Image Active Annotation (PIAA): An Efficient Active Learning Technique Using Edge Information in Limited Data Scenarios
Authors: Kadir Md Abdul , Alam Hasan Md Tusfiqur , Srivastav Devansh , Profitlich Hans-Jürgen , Sonntag Daniel 
Published: June 2024

AbstractActive learning (AL) algorithms are increasingly being used to train models with limited data for annotation tasks. However, the selection of data for AL is a complex issue due to the restricted information on unseen data. To tackle this problem, a technique we refer to as Partial Image Active Annotation (PIAA) employs the edge information of unseen images as prior knowledge to gauge uncertainty. This uncertainty is determined by examining the divergence and entropy in model predictions across edges. The resulting measure is then applied to choose superpixels from input images for active annotation. We demonstrate the effectiveness of PIAA in multi-class Optical Coherence Tomography (OCT) segmentation tasks, attaining a Dice score comparable to state-of-the-art OCT segmentation algorithms trained with extensive annotated data. Concurrently, we successfully reduce annotation label costs to 12%, 2.3%, and 3%, respectively, across three publicly accessible datasets (Duke, AROI, and UMN).
‘Sky’s the limit’: a case study in fostering young children’s creativity during STEM online learning experiences
Authors: Maslin Kimberly , Murcia Karen , Blackley Susan , Lowe Geoff 
Published: June 2024

Abstract
Fostering young children’s creativity is a desired outcome of STEM learning experiences. Such experiences often incorporate hands-on activities that encourage agency, curiosity, and experimentation. While educators generally have a good understanding of how to nurture creativity within a physical learning environment, less is known about creativity in an online context. Prior to the COVID-19 pandemic, little research focused on young children’s online learning. During the pandemic, studies involving this age group focused upon the experiences and perceptions of emergency remote learning, rather than intentional online education strategies. This gap creates an opportunity to explore the potential of STEM online learning experiences to meaningfully engage young children in creative thinking. This article analyses key themes emerging from video and interview data obtained during a series of STEM shows and workshops delivered by Scitech to Year 1 children in regional Western Australia, framed by the A-E of Children’s Creativity Framework. Findings illustrate how intentional online learning experiences can engage children creatively, and in turn supports a reframing of perceptions regarding the effectiveness of online delivery for young children.
A risk prediction model for Maritime accidents
Authors: Medda Andrea , Serra Patrizia , Mandas Marco , Fancello Gianfranco 
Published: June 2024

AbstractThis study proposes analytical tools to predict maritime accidents involving dangerous goods to help improve maritime safety and preserve maritime and coastal heritage. Maritime accidents of dangerous goods can have devastating consequences, causing loss of life, damage to the environment and economic losses. There have been numerous studies attempting to predict maritime accidents, but most have focused on a single type of accident (e.g. oil spills) or a single region (e.g. Baltic Sea, Maritime Silk Road, etc.). This study takes a different approach, using a global dataset on maritime accidents of dangerous goods from 2010 to 2019 (that includes information on the type of casualty, the location, the amount of material released, the type of material released, the cause of the accident, and the outcome), it applies both a machine learning technique and a statistical approach based on the Fourier distribution of rare events as a dual approach to address the problem. Using the Tyrrhenian area as a case study, the results show that the proposed tools can predict the probability of an accident occurring with an acceptable level of accuracy. The paper can provide a valuable tool for decision makers and stakeholders, who can use the findings to identify regions at risk of maritime accidents and take measures to prevent their occurrence.
Metacognitive Therapy Versus Exposure-Based Treatments of Posttraumatic Stress Disorder: A Preliminary Comparative Trial in an Ordinary Clinical Practice
Authors: Nordahl Johanne , Hjemdal Odin , Johnson Sverre U. , Nordahl Hans M. 
Published: June 2024

AbstractCognitive behavioral therapy, prolonged exposure, and eye movement desensitization and reprocessing are effective treatments for posttraumatic stress disorder (PTSD). They emphasize the processing of trauma-related memories and exposure as central components in treatment. In contrast, the metacognitive model emphasizes that PTSD is caused by a persistent negative thinking style, and the goal is to find alternative coping strategies and modify metacognitive beliefs without the use of exposure. In a quasi-experimental A-B design, patients diagnosed with PTSD received either MCT (n = 32) or TAU “treatment as usual” (n = 28) consisting of exposure-based treatments and were tested on different measures of symptoms. The results indicated that both treatments were effective and performed well on both trauma and anxiety symptoms. Recovery rates and clinical improvement were higher in the MCT condition at post-treatment. The study indicates that MCT could potentially be a viable alternative to trauma-focused treatment of PTSD.Clinical trial registration: The study is a clinical and quality audit of an ordinary routinely delivered clinical service in a specialized trauma clinic involving treatments for patients with PTSD. The trial was a preliminary stage in a larger trial of chronic PTSD.
Atypical lobular hyperplasia: what we need to know
Authors: Ferre Romuald , Kuzmiak Cherie M. 
Published: June 2024

AbstractAtypical lobular hyperplasia (ALH) is defined as an epithelial proliferation that does not meet the qualitative or quantitative abnormalities to be classified as ductal carcinoma in situ (DCIS). ALH is part of the high-risk lesions, subclassified among the lobular neoplasia. This review provides the characteristics of ALH, focusing on the imaging appearance. In addition, current outcomes and updated management are reviewed.
Deep‐Learning‐Based Prediction of the Tetragonal → Cubic Transition in Davemaoite
Authors: Wu Fulun , Sun Yang , Wan Tianqi , Wu Shunqing , Wentzcovitch Renata M. 
Published: June 2024

AbstractDavemaoite, that is, CaSiO3 perovskite (CaPv), is the third most abundant phase in the lower mantle and exhibits a tetragonal‐cubic phase transition at high pressures and temperatures. The phase boundary in CaPv has recently been proposed to be close to the cold slab adiabat and cause mid‐mantle seismic wave speed anomalies (Thomson et al., 2019, https://doi.org/10.1038/s41586‐019‐1483‐x). This study utilized accurate deep‐learning‐based simulations and thermodynamic integration techniques to compute free energies at temperatures ranging from 300 to 3,000 K and pressures up to 130 GPa. Our results indicate that CaPv exhibits a single cubic phase throughout lower‐mantle conditions. This suggests that the phase diagram proposed by Thomson et al. requires revision, and mid‐mantle seismic anomalies are likely attributable to other mechanisms.
Primary Production and Respiration in the Norwegian Sea Estimated From Biogeochemical Argo Floats
Authors: Mork Kjell Arne , Gundersen Kjell , Børsheim Knut Yngve , Dall'Olmo Giorgio , Skagseth Øystein , Søiland Henrik 
Published: June 2024

AbstractBiogeochemical (BGC) Argo floats were used in this study to investigate phytoplankton blooms. We assessed the seasonal and annual rates of net primary and community production, along with respiration in the Norwegian Sea. The years 2020 and 2021 were contrasted to illuminate similarities and differences. In both years the onset of the bloom occurred at the beginning of February, coinciding with a deep winter mixed layer. However, during spring and summer the biological production appeared to develop differently. In 2020 the mixed layer depth shoaled quickly in April due to surface heating, triggering a strong spring bloom event. In contrast, a significant surface cooling in April 2021 triggered a substantial vertical mixing, that delayed the mixed layer's shoaling. This delay initiated cascading effects impacting nitrate consumption and bloom development that resulted in increased respiration in 2021 compared to 2020. In both years, vertical nitrate mixing from deeper layers to the surface emerged as a pivotal factor determining primary production. Using a mixed layer model in combination with Argo observations, we found that the upward nutrient fluxes due to mixing doubled net community production. These findings underscore the capability of BGC‐Argo floats, operating at a 5‐day resolution, to unveil the intricate interplay between hydrography, physical drivers, and biogeochemical processes in shaping phytoplankton dynamics and overall ecosystem productivity in the Norwegian Sea.
Causal Drivers of Land‐Atmosphere Carbon Fluxes From Machine Learning Models and Data
Authors: Farahani Mozhgan A. , Goodwell Allison E. 
Published: June 2024

AbstractInteractions among atmospheric, root‐soil, and vegetation processes drive carbon dioxide fluxes (Fc) from land to atmosphere. Eddy covariance measurements are commonly used to measure Fc at sub‐daily timescales and validate process‐based and data‐driven models. However, these validations do not reveal process interactions, thresholds, and key differences in how models replicate them. We use information theory‐based measures to explore multivariate information flow pathways from forcing data to observed and modeled hourly Fc, using flux tower data sets in the Midwestern U.S. in intensively managed corn‐soybean landscapes. We compare multiple linear regressions, long‐short term memory, and random forests (RF), and evaluate how different model structures use information from combinations of sources to predict Fc. We extend a framework for model predictive and functional performance, which examines a suite of dependencies from all forcing variables to the observed or modeled target. Of the three model types, RF exhibited the highest functional and predictive performance, correctly capturing strong dependencies between radiation and temperature variables with Fc. Regionally trained models demonstrate lower predictive but higher functional performance compared to site‐specific models, suggesting superior reproduction of observed relationships at the expense of predictive accuracy. This study shows that some metrics of predictive performance encapsulate functional behaviors better than others, highlighting the need for multiple metrics of both types. This study improves our understanding of carbon fluxes in an intensively managed landscape, and more generally provides insight into how model structures and forcing variables translate to interactions that are well versus poorly captured in models.
An Index Description of the General Characteristics of Thermospheric Density Based on the Two‐Line‐Element Data Sets and the Spectral Whitening Method
Authors: Wu Yihan , Mao Tian , Wang Jing‐Song , Tang Wei , Song Qiao , Zhao Ming‐Xian 
Published: June 2024

AbstractThe thermospheric density and its variations are crucial to aerospace activities as well as space weather research and operation. However, due to the difficulties in observing the thermosphere, there has been a lack of effective descriptions for the general characteristics of thermospheric density. In this paper, the Two‐Line‐Element data sets (TLEs) from multi‐target low Earth orbit satellites are used to derive a proxy of the daily average atmospheric density in the thermospheric shell located in the vicinity of LEOs' orbital altitude. It captures the overall characteristics of the thermosphere and exhibits good correlations (∼0.9) with modeled and observed thermospheric density. By applying the spectral whitening method to this proxy, a new index is derived to describe non‐periodic perturbation of the density where the specific satellite passed by. The fact that the obtained from different satellites within the same thermospheric shell presents significant consistency to each other means that the new index is a good indicator for the overall feature of the variations of thermospheric density, and it is possible to define a unified regional index to describe density disturbances for the thermospheric shell where these satellites fly through. Moreover, the at different altitudes also present good consistency suggesting the possibility of defining a global index , capable of describing the density variation of the entire thermosphere.
Efficient and stable hybrid perovskite-organic light-emitting diodes with external quantum efficiency exceeding 40 per cent
Authors: Kong Lingmei , Luo Yun , Wu Qianqian , Xiao Xiangtian , Wang Yuanzhi , Chen Guo , Zhang Jianhua , Wang Kai , Choy Wallace C. H. , Zhao Yong-Biao , Li Hongbo , Chiba Takayuki , Kido Junji , Yang Xuyong 
Published: June 2024

AbstractLight-emitting diodes (LEDs) based on perovskite semiconductor materials with tunable emission wavelength in visible light range as well as narrow linewidth are potential competitors among current light-emitting display technologies, but still suffer from severe instability driven by electric field. Here, we develop a stable, efficient and high-color purity hybrid LED with a tandem structure by combining the perovskite LED and the commercial organic LED technologies to accelerate the practical application of perovskites. Perovskite LED and organic LED with close photoluminescence peak are selected to maximize photon emission without photon reabsorption and to achieve the narrowed emission spectra. By designing an efficient interconnecting layer with p-type interface doping that provides good opto-electric coupling and reduces Joule heating, the resulting green emitting hybrid LED shows a narrow linewidth of around 30 nm, a peak luminance of over 176,000 cd m−2, a maximum external quantum efficiency of over 40%, and an operational half-lifetime of over 42,000 h.
Efficient bone marrow irradiation and low uptake by non-haematological organs with an yttrium-90-anti-CD66 antibody prior to haematopoietic stem cell transplantation
Authors: Orchard Kim , Langford Jonathan , Guy Matthew , Lewis Gemma , Michopoulou Sofia , Cooper Margaret , Zvavamwe Clint , Richardson Deborah , Lewington Valerie 
Published: June 2024

AbstractWe report the results of a Phase I radiation dose escalation study using an yttrium-90 (90Y) labelled anti-CD66 monoclonal antibody given with standard conditioning regimen for patients receiving haematopoietic stem cell transplants for myeloid leukaemia or myeloma. The 90Y-labelled anti-CD66 was infused prior to standard conditioning. In total, 30 patients entered the trial and 29 received 90Y-labelled mAb, at infused radiation activity levels of 5, 10, 25, or 37.5 megaBequerel (MBq)/kg lean body weight. A prerequisite for receiving the 90Y-labelled mAb was favourable dosimetry determined by single-photon emission computerised tomography (SPECT) dosimetry following administration of indium-111 (111In) anti-CD66. Estimated absorbed radiation doses delivered to the red marrow demonstrated a linear relationship with the infused activity of 90Y-labelled mAb. At the highest activity level of 37.5 MBq/kg, mean estimated radiation doses for red marrow, liver, spleen, kidneys and lungs were 24.6 ± 5.6 Gy, 5.8 ± 2.7 Gy, 19.1 ± 8.0 Gy, 2.1 ± 1.1 and 2.2 ± 0.9, respectively. All patients engrafted, treatment-related mortality 1-year post-transplant was zero. Toxicities were no greater than those anticipated for similar conditioning regimens without targeted radiation. The ability to substantially intensify conditioning prior to haematopoietic stem cell transplantation without increasing toxicity warrants further testing to determine efficacy. clinicaltrials.gov identifier: NCT01521611.
Venetoclax therapy and emerging resistance mechanisms in acute myeloid leukaemia
Authors: Nwosu Gus O. , Ross David M. , Powell Jason A. , Pitson Stuart M. 
Published: June 2024

AbstractAcute myeloid leukaemia (AML) is a highly aggressive and devastating malignancy of the bone marrow and blood. For decades, intensive chemotherapy has been the frontline treatment for AML but has yielded only poor patient outcomes as exemplified by a 5-year survival rate of < 30%, even in younger adults. As knowledge of the molecular underpinnings of AML has advanced, so too has the development new strategies with potential to improve the treatment of AML patients. To date the most promising of these targeted agents is the BH3-mimetic venetoclax which in combination with standard of care therapies, has manageable non-haematological toxicity and exhibits impressive efficacy. However, approximately 30% of AML patients fail to respond to venetoclax-based regimens and almost all treatment responders eventually relapse. Here, we review the emerging mechanisms of intrinsic and acquired venetoclax resistance in AML and highlight recent efforts to identify novel strategies to overcome resistance to venetoclax.
Nonlinear country-heterogenous impact of the Indian Ocean Dipole on global economies
Authors: Cai Wenju , Liu Yi , Lin Xiaopei , Li Ziguang , Zhang Ying , Newth David 
Published: June 2024

AbstractA positive Indian Ocean Dipole features an anomalously high west-minus-east sea surface temperature gradient along the equatorial Indian Ocean, affecting global extreme weathers. Whether the associated impact spills over to global economies is unknown. Here, we develop a nonlinear and country-heterogenous econometric model, and find that a typical positive event causes a global economic loss that increases for further two years after an initial shock, inducing a global loss of hundreds of billion US dollars, disproportionally greater to the developing and emerging economies. The loss from the 2019 positive event amounted to US$558B, or 0.67% in global economic growth. Benefit from a negative dipole event is far smaller. Under a high-emission scenario, a projected intensification in Dipole amplitude causes a median additional loss of US$5.6 T at a 3% discount rate, but likely as large as US$24.5 T. The additional loss decreases by 64% under the target of the Paris Agreement.
descSPIM: an affordable and easy-to-build light-sheet microscope optimized for tissue clearing techniques
Authors: Otomo Kohei , Omura Takaki , Nozawa Yuki , Edwards Steven J. , Sato Yukihiko , Saito Yuri , Yagishita Shigehiro , Uchida Hitoshi , Watakabe Yuki , Naitou Kiyotada , Yanai Rin , Sahara Naruhiko , Takagi Satoshi , Katayama Ryohei , Iwata Yusuke , Shiokawa Toshiro , Hayakawa Yoku , Otsuka Kensuke , Watanabe-Takano Haruko , Haneda Yuka , Fukuhara Shigetomo , Fujiwara Miku , Nii Takenobu , Meno Chikara , Takeshita Naoki , Yashiro Kenta , Rosales Rocabado Juan Marcelo , Kaku Masaru , Yamada Tatsuya , Oishi Yumiko , Koike Hiroyuki , Cheng Yinglan , Sekine Keisuke , Koga Jun-ichiro , Sugiyama Kaori , Kimura Kenichi , Karube Fuyuki , Kim Hyeree , Manabe Ichiro , Nemoto Tomomi , Tainaka Kazuki , Hamada Akinobu , Brismar Hjalmar , Susaki Etsuo A. 
Published: June 2024

AbstractDespite widespread adoption of tissue clearing techniques in recent years, poor access to suitable light-sheet fluorescence microscopes remains a major obstacle for biomedical end-users. Here, we present descSPIM (desktop-equipped SPIM for cleared specimens), a low-cost ($20,000–50,000), low-expertise (one-day installation by a non-expert), yet practical do-it-yourself light-sheet microscope as a solution for this bottleneck. Even the most fundamental configuration of descSPIM enables multi-color imaging of whole mouse brains and a cancer cell line-derived xenograft tumor mass for the visualization of neurocircuitry, assessment of drug distribution, and pathological examination by false-colored hematoxylin and eosin staining in a three-dimensional manner. Academically open-sourced (https://github.com/dbsb-juntendo/descSPIM), descSPIM allows routine three-dimensional imaging of cleared samples in minutes. Thus, the dissemination of descSPIM will accelerate biomedical discoveries driven by tissue clearing technologies.
Axial de-scanning using remote focusing in the detection arm of light-sheet microscopy
Authors: Dibaji Hassan , Kazemi Nasaban Shotorban Ali , Grattan Rachel M. , Lucero Shayna , Schodt David J. , Lidke Keith A. , Petruccelli Jonathan , Lidke Diane S. , Liu Sheng , Chakraborty Tonmoy 
Published: June 2024

AbstractRapid, high-resolution volumetric imaging without moving heavy objectives or disturbing delicate samples remains challenging. Pupil-matched remote focusing offers a promising solution for high NA systems, but the fluorescence signal’s incoherent and unpolarized nature complicates its application. Thus, remote focusing is mainly used in the illumination arm with polarized laser light to improve optical coupling. Here, we introduce a novel optical design that can de-scan the axial focus movement in the detection arm of a microscope. Our method splits the fluorescence signal into S and P-polarized light, lets them pass through the remote focusing module separately, and combines them with the camera. This allows us to use only one focusing element to perform aberration-free, multi-color, volumetric imaging without (a) compromising the fluorescent signal and (b) needing to perform sample/detection-objective translation. We demonstrate the capabilities of this scheme by acquiring fast dual-color 4D (3D space + time) image stacks with an axial range of 70 μm and camera-limited acquisition speed. Owing to its general nature, we believe this technique will find its application in many other microscopy techniques that currently use an adjustable Z-stage to carry out volumetric imaging, such as confocal, 2-photon, and light sheet variants.
Tau follows principal axes of functional and structural brain organization in Alzheimer’s disease
Authors: Ottoy Julie , Kang Min Su , Tan Jazlynn Xiu Min , Boone Lyndon , Vos de Wael Reinder , Park Bo-yong , Bezgin Gleb , Lussier Firoza Z. , Pascoal Tharick A. , Rahmouni Nesrine , Stevenson Jenna , Fernandez Arias Jaime , Therriault Joseph , Hong Seok-Jun , Stefanovic Bojana , McLaurin JoAnne , Soucy Jean-Paul , Gauthier Serge , Bernhardt Boris C. , Black Sandra E. , Rosa-Neto Pedro , Goubran Maged 
Published: June 2024

AbstractAlzheimer’s disease (AD) is a brain network disorder where pathological proteins accumulate through networks and drive cognitive decline. Yet, the role of network connectivity in facilitating this accumulation remains unclear. Using in-vivo multimodal imaging, we show that the distribution of tau and reactive microglia in humans follows spatial patterns of connectivity variation, the so-called gradients of brain organization. Notably, less distinct connectivity patterns (“gradient contraction”) are associated with cognitive decline in regions with greater tau, suggesting an interaction between reduced network differentiation and tau on cognition. Furthermore, by modeling tau in subject-specific gradient space, we demonstrate that tau accumulation in the frontoparietal and temporo-occipital cortices is associated with greater baseline tau within their functionally and structurally connected hubs, respectively. Our work unveils a role for both functional and structural brain organization in pathology accumulation in AD, and supports subject-specific gradient space as a promising tool to map disease progression.