bluuebunny/crossref_metadata_2025_split huggingface dataset:
Soil Organic Carbon Lateral Movement Processes Integrated Into a Terrestrial Ecosystem Model
Authors: Lu Haibo , Wang Xiaoyuan , Zhang Haicheng , Xie Xianhong , Nakhavali Mahdi , Quine Timothy A. , Xu Wenfang , Xia Jiangzhou , He Bin , Hao Zhixin , Geng Xiu , Yuan Wenping 
Published: January 2024

AbstractLateral movement of soil organic carbon (SOC) induced by soil erosion and runoff changes spatial distributions of SOC, and further changes the land‐atmosphere CO2 exchange and terrestrial carbon budget. However, current ecosystem models do not or only poorly integrate the process of SOC lateral movement and cannot simulate the impacts of soil erosion on the carbon cycle. This study integrated SOC erosion and deposition processes into a process‐based ecosystem model (i.e., Integrated BIosphere Simulator (IBIS)), and separately simulated the lateral movements of dissolved organic carbon (DOC) and particulate organic carbon (POC). The model was evaluated in three river basins in Northeast China that are dominated by cropland, forest, and grassland. The results showed that the model reproduced well the production, erosion, and deposition of DOC and POC. The annual SOC lateral movement (1.34–7.22 g C m−2 yr−1) induced by erosion in the three tested basins was 0.27%–1.45% of the annual net primary production. The model developed in this study has great implications for simulating the lateral movements of SOC in terrestrial ecosystems, which can improve model performance in projecting the terrestrial carbon budget.
Twelve Times Faster yet Accurate: A New State‐Of‐The‐Art in Radiation Schemes via Performance and Spectral Optimization
Authors: Ukkonen Peter , Hogan Robin J. 
Published: January 2024

AbstractRadiation schemes are critical components of Earth system models that need to be both efficient and accurate. Despite the use of approximations such as 1D radiative transfer, radiation can account for a large share of the runtime of expensive climate simulations. Here we seek a new state‐of‐the‐art in speed and accuracy by combining code optimization with improved algorithms. To fully benefit from new spectrally reduced gas optics schemes, we restructure code to avoid short vectorized loops where possible by collapsing the spectral and vertical dimensions. Our main focus is the ecRad radiation scheme, where this requires batching of adjacent cloudy layers, trading some simplicity for improved vectorization and instruction‐level parallelism. When combined with common optimization techniques for serial code and porting widely used two‐stream kernels fully to single precision, we find that ecRad with the TripleClouds solver becomes 12 times faster than the operational radiation scheme in ECMWF's Integrated Forecast System (IFS) cycle 47r3, which uses a less accurate gas optics model (RRMTG) and a more noisy solver (McICA). After applying the spectral reduction and extensive optimizations to the more sophisticated SPARTACUS solver, we find that it’s 2.5 times faster than IFS cy47r3 radiation, making cloud 3D radiative effects affordable to compute in large‐scale models. The code optimization itself gave a threefold speedup for both solvers. While SPARTACUS is still under development, preliminary experiments show slightly improved medium‐range forecasts of 2‐m temperature in the tropics, and in year‐long coupled atmosphere‐ocean simulations the 3D effects warm the surface substantially.
On the use of deep learning for phase recovery
Authors: Wang Kaiqiang , Song Li , Wang Chutian , Ren Zhenbo , Zhao Guangyuan , Dou Jiazhen , Di Jianglei , Barbastathis George , Zhou Renjie , Zhao Jianlin , Lam Edmund Y. 
Published: January 2024

AbstractPhase recovery (PR) refers to calculating the phase of the light field from its intensity measurements. As exemplified from quantitative phase imaging and coherent diffraction imaging to adaptive optics, PR is essential for reconstructing the refractive index distribution or topography of an object and correcting the aberration of an imaging system. In recent years, deep learning (DL), often implemented through deep neural networks, has provided unprecedented support for computational imaging, leading to more efficient solutions for various PR problems. In this review, we first briefly introduce conventional methods for PR. Then, we review how DL provides support for PR from the following three stages, namely, pre-processing, in-processing, and post-processing. We also review how DL is used in phase image processing. Finally, we summarize the work in DL for PR and provide an outlook on how to better use DL to improve the reliability and efficiency of PR. Furthermore, we present a live-updating resource (https://github.com/kqwang/phase-recovery) for readers to learn more about PR.
Aerosol jet printing of surface acoustic wave microfluidic devices
Authors: Rich Joseph , Cole Brian , Li Teng , Lu Brandon , Fu Hanyu , Smith Brittany N. , Xia Jianping , Yang Shujie , Zhong Ruoyu , Doherty James L. , Kaneko Kanji , Suzuki Hiroaki , Tian Zhenhua , Franklin Aaron D. , Huang Tony Jun 
Published: January 2024

AbstractThe addition of surface acoustic wave (SAW) technologies to microfluidics has greatly advanced lab-on-a-chip applications due to their unique and powerful attributes, including high-precision manipulation, versatility, integrability, biocompatibility, contactless nature, and rapid actuation. However, the development of SAW microfluidic devices is limited by complex and time-consuming micro/nanofabrication techniques and access to cleanroom facilities for multistep photolithography and vacuum-based processing. To simplify the fabrication of SAW microfluidic devices with customizable dimensions and functions, we utilized the additive manufacturing technique of aerosol jet printing. We successfully fabricated customized SAW microfluidic devices of varying materials, including silver nanowires, graphene, and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS). To characterize and compare the acoustic actuation performance of these aerosol jet printed SAW microfluidic devices with their cleanroom-fabricated counterparts, the wave displacements and resonant frequencies of the different fabricated devices were directly measured through scanning laser Doppler vibrometry. Finally, to exhibit the capability of the aerosol jet printed devices for lab-on-a-chip applications, we successfully conducted acoustic streaming and particle concentration experiments. Overall, we demonstrated a novel solution-based, direct-write, single-step, cleanroom-free additive manufacturing technique to rapidly develop SAW microfluidic devices that shows viability for applications in the fields of biology, chemistry, engineering, and medicine.
Hydrogels for active photonics
Authors: Ko Byoungsu , Jeon Nara , Kim Jaekyung , Kang Hyunjung , Seong Junhwa , Yun Suhyeon , Badloe Trevon , Rho Junsuk 
Published: January 2024

AbstractConventional photonic devices exhibit static optical properties that are design-dependent, including the material’s refractive index and geometrical parameters. However, they still possess attractive optical responses for applications and are already exploited in devices across various fields. Hydrogel photonics has emerged as a promising solution in the field of active photonics by providing primarily deformable geometric parameters in response to external stimuli. Over the past few years, various studies have been undertaken to attain stimuli-responsive photonic devices with tunable optical properties. Herein, we focus on the recent advancements in hydrogel-based photonics and micro/nanofabrication techniques for hydrogels. In particular, fabrication techniques for hydrogel photonic devices are categorized into film growth, photolithography (PL), electron-beam lithography (EBL), and nanoimprint lithography (NIL). Furthermore, we provide insights into future directions and prospects for deformable hydrogel photonics, along with their potential practical applications.
Probing the chemical ‘reactome’ with high-throughput experimentation data
Authors: King-Smith Emma , Berritt Simon , Bernier Louise , Hou Xinjun , Klug-McLeod Jacquelyn L. , Mustakis Jason , Sach Neal W. , Tucker Joseph W. , Yang Qingyi , Howard Roger M. , Lee Alpha A. 
Published: January 2024

AbstractHigh-throughput experimentation (HTE) has the potential to improve our understanding of organic chemistry by systematically interrogating reactivity across diverse chemical spaces. Notable bottlenecks include few publicly available large-scale datasets and the need for facile interpretation of these data’s hidden chemical insights. Here we report the development of a high-throughput experimentation analyser, a robust and statistically rigorous framework, which is applicable to any HTE dataset regardless of size, scope or target reaction outcome, which yields interpretable correlations between starting material(s), reagents and outcomes. We improve the HTE data landscape with the disclosure of 39,000+ previously proprietary HTE reactions that cover a breadth of chemistry, including cross-coupling reactions and chiral salt resolutions. The high-throughput experimentation analyser was validated on cross-coupling and hydrogenation datasets, showcasing the elucidation of statistically significant hidden relationships between reaction components and outcomes, as well as highlighting areas of dataset bias and the specific reaction spaces that necessitate further investigation.
High-quality metagenome assembly from long accurate reads with metaMDBG
Authors: Benoit Gaëtan , Raguideau Sébastien , James Robert , Phillippy Adam M. , Chikhi Rayan , Quince Christopher 
Published: January 2024

AbstractWe introduce metaMDBG, a metagenomics assembler for PacBio HiFi reads. MetaMDBG combines a de Bruijn graph assembly in a minimizer space with an iterative assembly over sequences of minimizers to address variations in genome coverage depth and an abundance-based filtering strategy to simplify strain complexity. For complex communities, we obtained up to twice as many high-quality circularized prokaryotic metagenome-assembled genomes as existing methods and had better recovery of viruses and plasmids.
Ultrafast bisulfite sequencing detection of 5-methylcytosine in DNA and RNA
Authors: Dai Qing , Ye Chang , Irkliyenko Iryna , Wang Yiding , Sun Hui-Lung , Gao Yun , Liu Yushuai , Beadell Alana , Perea José , Goel Ajay , He Chuan 
Published: January 2024

AbstractBisulfite sequencing (BS-seq) to detect 5-methylcytosine (5mC) is limited by lengthy reaction times, severe DNA damage, overestimation of 5mC level and incomplete C-to-U conversion of certain DNA sequences. We present ultrafast BS-seq (UBS-seq), which uses highly concentrated bisulfite reagents and high reaction temperatures to accelerate the bisulfite reaction by ~13-fold, resulting in reduced DNA damage and lower background noise. UBS-seq allows library construction from small amounts of purified genomic DNA, such as from cell-free DNA or directly from 1 to 100 mouse embryonic stem cells, with less overestimation of 5mC level and higher genome coverage than conventional BS-seq. Additionally, UBS-seq quantitatively maps RNA 5-methylcytosine (m5C) from low inputs of mRNA and allows the detection of m5C stoichiometry in highly structured RNA sequences. Our UBS-seq results identify NSUN2 as the major ‘writer’ protein responsible for the deposition of ~90% of m5C sites in HeLa mRNA and reveal enriched m5C sites in 5′-regions of mammalian mRNA, which may have functional roles in mRNA translation regulation.
Clinical correlates of CT imaging-derived phenotypes among lean and overweight patients with hepatic steatosis
Authors: Song Isabel , Thompson Elizabeth W. , Verma Anurag , MacLean Matthew T. , Duda Jeffrey , Elahi Ameena , Tran Richard , Raghupathy Pavan , Swago Sophia , Hazim Mohamad , Bhattaru Abhijit , Schneider Carolin , Vujkovic Marijana , Torigian Drew A. , Kahn Charles E. , Gee James C. , Borthakur Arijitt , Kripke Colleen M. , Carson Christopher C. , Carr Rotonya , Jehangir Qasim , Ko Yi-An , Litt Harold , Rosen Mark , Mankoff David A. , Schnall Mitchell D. , Shou Haochang , Chirinos Julio , Damrauer Scott M. , Serper Marina , Chen Jinbo , Rader Daniel J. ,   Penn Medicine BioBank, Ritchie Marylyn D. , Weaver JoEllen , Naseer Nawar , Poindexter Afiya , Hu-Sain Khadijah , Livingstone Meghan , Vadivieso Fred , DerOhannessian Stephanie , Tran Teo , Stephanowski Julia , Zielinski Monica , Haubein Ned , Dunn Joseph , Verma Anurag , Kripke Colleen M. , Risman Marjorie , Judy Renae , Verma Shefali S. , Bradford Yuki , Dudek Scott , Drivas Theodore , Witschey Walter R. T. , Sagreiya Hersh 
Published: January 2024

AbstractThe objective of this study is to define CT imaging derived phenotypes for patients with hepatic steatosis, a common metabolic liver condition, and determine its association with patient data from a medical biobank. There is a need to further characterize hepatic steatosis in lean patients, as its epidemiology may differ from that in overweight patients. A deep learning method determined the spleen-hepatic attenuation difference (SHAD) in Hounsfield Units (HU) on abdominal CT scans as a quantitative measure of hepatic steatosis. The patient cohort was stratified by BMI with a threshold of 25 kg/m2 and hepatic steatosis with threshold SHAD ≥  − 1 HU or liver mean attenuation ≤ 40 HU. Patient characteristics, diagnoses, and laboratory results representing metabolism and liver function were investigated. A phenome-wide association study (PheWAS) was performed for the statistical interaction between SHAD and the binary characteristic LEAN. The cohort contained 8914 patients—lean patients with (N = 278, 3.1%) and without (N = 1867, 20.9%) steatosis, and overweight patients with (N = 1863, 20.9%) and without (N = 4906, 55.0%) steatosis. Among all lean patients, those with steatosis had increased rates of cardiovascular disease (41.7 vs 27.8%), hypertension (86.7 vs 49.8%), and type 2 diabetes mellitus (29.1 vs 15.7%) (all p < 0.0001). Ten phenotypes were significant in the PheWAS, including chronic kidney disease, renal failure, and cardiovascular disease. Hepatic steatosis was found to be associated with cardiovascular, kidney, and metabolic conditions, separate from overweight BMI.
Control charts using half-normal and half-exponential power distributions using repetitive sampling
Authors: Naveed Muhammad , Azam Muhammad , Khan Nasrullah , Aslam Muhammad , Saleem Muhammad , Saeed Muhammad 
Published: January 2024

AbstractThis manuscript presents the development of an attribute control chart (ACC) designed to monitor the number of defective items in manufacturing processes. The charts are specifically tailored using time-truncated life test (TTLT) for two lifetime data distributions: the half-normal distribution (HND) and the half-exponential power distribution (HEPD) under a repetitive sampling scheme (RSS). To assess the effectiveness of the proposed control charts, both in-control (IC) and out-of-control (OOC) scenarios are considered by deriving the average run length (ARL). Various factors, including sample sizes, control coefficients, and truncated constants for shifted phases, are taken into account to evaluate the performance of the charts in terms of ARL. The behavior of ARLs is analyzed in the shifted process by introducing shifts in its parameters. The superiority of the HEPD-based chart is highlighted by comparing it with both the HND-based ACC and the ACC based on the Exponential distribution (ED) under TTLT using RSS. The results showcase the superior performance of the proposed HEPD-based chart, indicated by smaller ARL values. Additionally, the benefits of another proposed ACC using HND are compared with the ED-based ACC under RSS, further confirming the effectiveness of the HND-based approach through smaller ARLs Finally, the proposed control charts are evaluated through simulation testing and real-life implementation, emphasizing their practical applicability in real-world manufacturing settings.
Cryogenic fracturing using liquid nitrogen on granite at elevated temperatures: a case study for enhanced geothermal systems in Kazakhstan
Authors: Longinos Sotirios Nik. , Hazlett Randy 
Published: January 2024

AbstractCryogenic fracturing using liquid nitrogen (LN2) is a novel stimulation technology that enhances porosity, permeability, and rock-fluid contact area in subsurface formations targetted for geothermal energy extraction. In our experimental study, granite cores collected from the Zhylgyz region in South Kazakhstan were equilibrated at various elevated temperatures before treatments involving LN2 exposure time. Compression, Brazilian, and fracture toughness tests were performed on granite with starting temperatures ranging from 100 to 500 °C to quantify the impact of initial temperature on cryogenic fracturing and to compare with baseline geomechanical tests at 50 °C without LN2 exposure. The results show that LN2 cooling of hot granite induces mechanical rock failure and permeability enhancement. Moreover, the degree of thermo-fracturing augments with initial granite temperature, total freezing time, and number of freezing–thawing cycles. The peak load before failure of granite specimens, both in compression and Brazilian tests, reduces with the increased sample temperature difference and length of LN2 treatment. The fracture toughness of our semi-circular bend (SCB) LN2-treated specimens diminished with increasing temperature difference between granite and boiling point. In both experimental LN2 treatment processes, the specimens with an initial temperature of 500 °C before LN2 treatment formed many new fissures and extensions of pre-existing ones, showing that the plastic behavior is augmented. While cryo-fracturing experimental confirmation is recommended with site-specific samples in planning geothermal operations, these results in our work indicate a threshold downhole temperature, e.g., > 300 °C, for enhanced stimulation outcomes.
Earlier social information has a stronger influence on judgments
Authors: Tump Alan Novaes , Wollny-Huttarsch David , Molleman Lucas , Kurvers Ralf H. J. M. 
Published: January 2024

AbstractPeople’s decisions are often informed by the choices of others. Evidence accumulation models provide a mechanistic account of how such social information enters the choice process. Previous research taking this approach has suggested two fundamentally different cognitive mechanisms by which people incorporate social information. On the one hand, individuals may update their evidence level instantaneously when observing social information. On the other hand, they may gradually integrate social information over time. These accounts make different predictions on how the timing of social information impacts its influence. The former predicts that timing has no impact on social information uptake. The latter predicts that social information which arrives earlier has a stronger impact because its impact increases over time. We tested both predictions in two studies in which participants first observed a perceptual stimulus. They then entered a deliberation phase in which social information arrived either early or late before reporting their judgment. In Experiment 1, early social information remained visible until the end and was thus displayed for longer than late social information. In Experiment 2, which was preregistered, early and late social information were displayed for an equal duration. In both studies, early social information had a larger impact on individuals’ judgments. Further, an evidence accumulation analysis found that social information integration was best explained by both an immediate update of evidence and continuous integration over time. Because in social systems, timing plays a key role (e.g., propagation of information in social networks), our findings inform theories explaining the temporal evolution of social impact and the emergent social dynamics.
Cathodoluminescence spectroscopy of monolayer hexagonal boron nitride
Authors: Shima Kohei , Cheng Tin S. , Mellor Christopher J. , Beton Peter H. , Elias Christine , Valvin Pierre , Gil Bernard , Cassabois Guillaume , Novikov Sergei V. , Chichibu Shigefusa F. 
Published: January 2024

AbstractCathodoluminescence (CL) spectroscopy is a suitable technique for studying the luminescent properties of optoelectronic materials because CL has no limitation on the excitable bandgap energy and eliminates ambiguous signals due to simple light scattering and resonant Raman scattering potentially involved in the photoluminescence spectra. However, direct CL measurements of atomically thin two-dimensional materials have been difficult due to the small excitation volume that interacts with high-energy electron beams. Herein, distinct CL signals from a monolayer hexagonal BN (hBN), namely mBN, epitaxial film grown on a graphite substrate are shown by using a CL system capable of large-area and surface-sensitive excitation. Spatially resolved CL spectra at 13 K exhibited a predominant 5.5-eV emission band, which has been ascribed to originate from multilayered aggregates of hBN, markedly at thicker areas formed on the step edges of the substrate. Conversely, a faint peak at 6.04 ± 0.01 eV was routinely observed from atomically flat areas, which is assigned as being due to the recombination of phonon-assisted direct excitons of mBN. The CL results support the transition from indirect bandgap in bulk hBN to direct bandgap in mBN. The results also encourage one to elucidate emission properties of other low-dimensional materials by using the present CL configuration.
Global taxonomic and functional patterns in invertebrate assemblages from rocky-intertidal mussel beds
Authors: Cameron Nicole M. , Scrosati Ricardo A. , Valdivia Nelson , Meunier Zechariah D. 
Published: January 2024

AbstractMussels form extensive beds in rocky intertidal habitats on temperate seashores worldwide. They are foundation species because their beds host many invertebrates. Mussels and their associated species differ taxonomically among biogeographic regions, but all mussel beds exhibit similar structural and functional properties. Therefore, we investigated if rocky-intertidal mussel beds from around the globe host associated communities that are functionally similar despite their underlying taxonomic differences. We gathered datasets on the abundance of invertebrates found in rocky-intertidal mussel beds from the eastern and western boundaries of the Pacific and Atlantic Oceans from both hemispheres and, then, we compared their taxonomic and functional properties. Taxonomic composition differed markedly among coasts when analyzed at the taxonomic resolution reported by the surveys (often species). However, taxonomic groups with similar ecologies (28 groups including barnacles, decapods, gastropods, polychaetes, etc.) were more universally present in mussel beds. Concomitantly, functional categories of trophic level, body type, and mobility were almost always present on all studied coasts. These taxonomic groups and trait categories, however, showed regional patterns based on their relative abundances. Overall, the ability of mussel beds to host a core community type based on taxonomic groups and functional traits emphasizes their importance for biodiversity and community functioning, making them critical organisms to preserve.