bluuebunny/crossref_metadata_2025_split huggingface dataset:
The evolution of 21st century sea-level projections from IPCC AR5 to AR6 and beyond
Authors: Slangen Aimée B.A. , Palmer Matthew D. , Camargo Carolina M.L. , Church John A. , Edwards Tamsin L. , Hermans Tim H.J. , Hewitt Helene T. , Garner Gregory G. , Gregory Jonathan M. , Kopp Robert E. , Santos Victor Malagon , van de Wal Roderik S.W. 
Published: December 2022

AbstractSea-level science has seen many recent developments in observations and modelling of the different contributions and the total mean sea-level change. In this overview, we discuss (1) the evolution of the Intergovernmental Panel on Climate Change (IPCC) projections, (2) how the projections compare to observations and (3) the outlook for further improving projections. We start by discussing how the model projections of 21st century sea-level change have changed from the IPCC AR5 report (2013) to SROCC (2019) and AR6 (2021), highlighting similarities and differences in the methodologies and comparing the global mean and regional projections. This shows that there is good agreement in the median values, but also highlights some differences. In addition, we discuss how the different reports included high-end projections. We then show how the AR5 projections (from 2007 onwards) compare against the observations and find that they are highly consistent with each other. Finally, we discuss how to further improve sea-level projections using high-resolution ocean modelling and recent vertical land motion estimates.
Importance of Identifying Cognitive Impairment in Multiple Sclerosis
Authors: Morrow Sarah A. , Baldwin Chantal , Alkabie Samir 
Published: December 2022

ABSTRACT:This article aims to highlight the impact of cognitive impairment on outcomes and quality of life for people with multiple sclerosis (MS) and to review current evidence for the efficacy of disease-modifying therapies (DMTs) and other interventions. In addition, we provide clinical practice insights regarding screening and management of cognitive impairment in people with MS. Evidence suggests that cognitive deterioration often accompanies magnetic resonance imaging changes. Neocortical volume and deep grey matter atrophy correlate with cognitive impairment. Similarly, cognitive decline is predictive of a higher lesion burden. Cognitive impairment is an important clinical measure of disability and negatively impacts quality of life. Phase 3 studies suggest that DMTs such as natalizumab, ozanimod and fingolimod may provide long-lasting, clinically meaningful effects on cognition in people with MS. Further data are needed to support the use of adjunct cognitive behavioural and exercise interventions for people with MS who have cognitive impairment. More data are needed to define appropriate management strategies for cognitive impairment in people with MS. Baseline and periodic screening for cognitive impairment and inclusion of cognitive impairment as a clinical trial endpoint will help to inform efforts to manage this important aspect of MS.
AXIOMATIZATIONS OF PEANO ARITHMETIC: A TRUTH-THEORETIC VIEW
Authors: ENAYAT ALI , ŁEŁYK MATEUSZ 
Published: December 2022

AbstractWe employ the lens provided by formal truth theory to study axiomatizations of Peano Arithmetic
${\textsf {(PA)}}$
. More specifically, let Elementary Arithmetic
${\textsf {(EA)}}$
be the fragment
$\mathsf {I}\Delta _0 + \mathsf {Exp}$
of
${\textsf {PA}}$
, and let
${\textsf {CT}}^-[{\textsf {EA}}]$
be the extension of
${\textsf {EA}}$
by the commonly studied axioms of compositional truth
${\textsf {CT}}^-$
. We investigate both local and global properties of the family of first order theories of the form
${\textsf {CT}}^-[{\textsf {EA}}] +\alpha $
, where
$\alpha $
is a particular way of expressing “
${\textsf {PA}}$
is true” (using the truth predicate). Our focus is dominantly on two types of axiomatizations, namely: (1) schematic axiomatizations that are deductively equivalent to
${\textsf {PA}}$
and (2) axiomatizations that are proof-theoretically equivalent to the canonical axiomatization of
${\textsf {PA}}$
.
Parrot population trends in Nicaragua revealed by long-term monitoring
Authors: Hille David C. , Wiedenfeld David A. , Lezama-López Martín , Brightsmith Donald J. , Patten Michael A. 
Published: December 2022

SummaryMonitoring parrot populations is of high importance because there is a general lack of quantified population trends for one of the most threatened avian orders. We surveyed parrots in Nicaragua in 1995, 1999, 2004, and 2013 at a minimum of 227 points within 56 sites stratified among the Pacific, Central Highlands, and Caribbean biogeographical regions to assess population trends. From point-count data we calculated encounter rate, flock rate, and flock size metrics and we used presence/absence data to generate species-specific occupancy estimates. Encounter rate, flock rate, and flock size data suggested family-level declines from 1995 to 2004 with some recovery between 2004 and 2013. Patterns of parrot occupancy varied among species with four decreasing, five increasing, and two with no detectable change. Six species of conservation concern are identified, including the Critically Endangered Great Green Macaw and Yellow-naped Parrot, additionally Olive-throated Parakeet, Scarlet Macaw, Brown-hooded Parrot, and White-crowned Parrot, only listed as Least Concern. All six are likely suffering from deforestation and potential unchecked trade activity in the Caribbean. Differing population trends of the regionally disjunct Yellow-naped Parrot subspecies suggest a link to variable deforestation and trade pressure experienced between the Pacific and Caribbean. Our results highlight the importance of actively monitoring changing parrot populations, even when considered Least Concern, so that directed conservation actions can be taken if needed.
Linguistic factors modulating gender assignment in Spanish–English bilingual speech
Authors: Cruz Abel 
Published: December 2022

AbstractDrawing on naturally-occurring bilingual speech from a well-defined codeswitching community in Southern Arizona, this study examined the influence of semantic gender (a.k.a. biological gender), analogical gender, and other-language phonemic cues in modulating gender assignment in Spanish–English codeswitched speech. Thirty-four Spanish–English early bilinguals completed a forced-choice elicitation task involving two codeswitching environments: Spanish determiner–English noun switches (Task 1) and English–Spanish switched copula constructions (Task 2). The results revealed that for human-denoting nouns, bilinguals assigned grammatical gender based on the presupposed sex of a noun's referent in both syntactic environments tested. As for inanimate nouns, bilinguals were more likely to assign masculine over feminine gender to such nouns in determiner–noun switches, but not in switched copula constructions. Other-language phonemic cues did not influence the assignment mechanism. A methodological implication is that the study replicated the codeswitching patterns observed in naturally-occurring bilingual speech from the same bilingual community.
A New Simulation‐Optimization Framework for Estimation of Submarine Groundwater Discharge Based on Hydrodynamic Modeling and Isotopic Data
Authors: Yu Jiang , Tian Yong , Wang Xuejing , Wang Xiaoli , Lancia Michele , Li Hailong , Andrews Charles B. , Zheng Chunmiao 
Published: December 2022

AbstractEstimation of submarine groundwater discharge (SGD) has traditionally relied on isotopic mass balance calculation, which is a form of regional box modeling. Here we propose an entirely new approach for SGD estimation by coupling a general marine hydrodynamic simulation model with a global optimization algorithm. The newly developed approach has the distinct advantage of being able to map the spatial distribution of SGD. The results of this study show that the estimated SGD exhibits a strong spatial heterogeneity. Furthermore, this study underscores the important effect of isotope sampling time on SGD estimation. Thus, the fluctuation of seawater level and a lag in isotope activity to water level changes should be considered to assure the representativeness of measured isotope activities. Overall, the simulation‐optimization framework adds a versatile and powerful new tool for more detailed SGD estimation.
Juno's Close Encounter With Ganymede—An Overview
Authors: Hansen C. J. , Bolton S. , Sulaiman A. H. , Duling S. , Bagenal F. , Brennan M. , Connerney J. , Clark G. , Lunine J. , Levin S. , Kurth W. , Mura A. , Paranicas C. , Tosi F. , Withers P. 
Published: December 2022

AbstractThe Juno spacecraft has been in orbit around Jupiter since 2016. Two flybys of Ganymede were executed in 2021, opportunities realized by evolution of Juno's polar orbit over the intervening 5 years. The geometry of the close flyby just prior to the 34th perijove pass by Jupiter brought the spacecraft inside Ganymede's unique magnetosphere. Juno's payload, designed to study Jupiter's magnetosphere, had ample dynamic range to study Ganymede's magnetosphere. The Juno radio system was used both for gravity measurements and for study of Ganymede's ionosphere. Remote sensing of Ganymede returned new results on geology, surface composition, and thermal properties of the surface and subsurface.
Gravity Field of Ganymede After the Juno Extended Mission
Authors: Gomez Casajus L. , Ermakov A. I. , Zannoni M. , Keane J. T. , Stevenson D. , Buccino D. R. , Durante D. , Parisi M. , Park R. S. , Tortora P. , Bolton S. J. 
Published: December 2022

AbstractThe Juno Extended Mission presented the first opportunity to acquire gravity measurements of Ganymede since the end of the Galileo mission. These new Juno data offered the chance to carry out a joint analysis with the Galileo data set, improving our knowledge of Ganymede's gravity field and shedding new light upon its interior structure. Through reconstruction of Juno's and Galileo's orbit during the Ganymede flybys, the gravity field of the moon was estimated. The results indicate that Ganymede's degree‐2 field is compatible with a body in hydrostatic equilibrium within 1−𝜎 and hint at regional gravity anomalies with amplitudes exceeding those inferred by Cassini for Titan. Our explicit treatment of non‐hydrostatic effects leads to wider confidence intervals for the derived moment of inertia with respect previous analyses. The higher central value of the derived moment of inertia indicates a lesser degree of Ganymede's differentiation.
Juno Magnetometer Observations at Ganymede: Comparisons With a Global Hybrid Simulation and Indications of Magnetopause Reconnection
Authors: Romanelli N. , DiBraccio G. A. , Modolo R. , Connerney J. E. P. , Ebert R. W. , Martos Y. M. , Weber T. , Espley J. R. , Kurth W. S. , Allegrini F. , Valek P. , Bolton S. J. 
Published: December 2022

AbstractJuno's flyby of Ganymede on 7 June 2021, provides a unique opportunity to explore the moon's magnetosphere. By means of Magnetometer (MAG) observations and a hybrid numerical simulation, we provide a global description of this environment and analyze the upstream magnetopause in detail. In particular, LATMOS Hybrid Simulation results suggest Juno observed open (one foot‐point connected to Ganymede, the other to Jupiter) and closed magnetic field lines along its trajectory. Additionally, we determine that the upstream magnetopause location and orientation seen by Juno MAG are consistent with previous Galileo observations. We observe a non‐zero normal component of the magnetic field across the magnetopause, along with flux rope structures embedded within the boundary's current sheet. Both signatures are strong indicators that magnetic reconnection was occurring along Ganymede's magnetopause. Based on this crossing, we calculate a shear angle of ∼78° across the magnetopause, with a dimensionless reconnection rate of ∼0.12.
Forecasting of in situ electron energy loss spectroscopy
Authors: Lewis Nicholas R. , Jin Yicheng , Tang Xiuyu , Shah Vidit , Doty Christina , Matthews Bethany E. , Akers Sarah , Spurgeon Steven R. 
Published: December 2022

AbstractForecasting models are a central part of many control systems, where high-consequence decisions must be made on long latency control variables. These models are particularly relevant for emerging artificial intelligence (AI)-guided instrumentation, in which prescriptive knowledge is needed to guide autonomous decision-making. Here we describe the implementation of a long short-term memory model (LSTM) for forecasting in situ electron energy loss spectroscopy (EELS) data, one of the richest analytical probes of materials and chemical systems. We describe key considerations for data collection, preprocessing, training, validation, and benchmarking, showing how this approach can yield powerful predictive insight into order-disorder phase transitions. Finally, we comment on how such a model may integrate with emerging AI-guided instrumentation for powerful high-speed experimentation.
Prediction study of electric energy production in important power production base, China
Authors: Zhu XiXun , Song Zhixin , Sen Gan , Tian Maozai , Zheng Yanling , Zhu Bing 
Published: December 2022

AbstractXinjiang is an important power production base in China, and its electric energy production needs not only meet the demand of Xinjiang's electricity consumption, but also make up for the shortage of electricity in at least 19 provinces or cities in China. Therefore, it is of great significance to know ahead of time the electric energy production of Xinjiang in the future. In such terms, accurate electric energy production forecasts are imperative for decision makers to develop an optimal strategy that includes not only risk reduction, but also the betterment of the economy and society as a whole. According to the characteristics of the historical data of monthly electricity generation in Xinjiang from January 2001 to August 2020 , the suitable and widely used SARIMA (Seasonal autoregressive integrated moving mean model) method and Holt-winter method were used to construct the monthly electric energy production in Xinjiang for the first time. The results of our analysis showed that the established SARIMA((1,2,3,4,6,7,11),2,1)(1,0,1)12model had higher prediction accuracy than that of the established Holt-Winters' multiplicative model. We predicted the monthly electric energy production from August 2021 to August 2022 by the SARIMA((1,2,3,4,6,7,11),2,1)(1,0,1)12model, and errors are very small compared to the actual values, indicating that our model has a very good prediction performance. Therefore, based on our study, we provided a simple and easy scientific tool for the future power output prediction in Xinjiang. Our research methods and research ideas can also provide scientific reference for the prediction of electric energy production elsewhere.
Crown feature effect evaluation on wind load for evergreen species based on laser scanning and wind tunnel experiments
Authors: Lai Can , Xiao Bing , Feng Jialang , Wang Longyuan , Zhang Yanjing , Sun Yanjun , Chen Xiaoxi , Guo Wei 
Published: December 2022

AbstractThe wind load a tree withstood is mainly applied to its crown, whose morphology and structure directly affect the degree of wind load given a certain wind condition. Though the features of tree crown are relatively easy to measure, however, among them which is/are the determining factor and how they contribute to wind load remain unknown. In order to figure out how crown features of different tree species influence the wind load, the wind tunnel experiment was performed for 7 most used urban greening tree species, and laser scanning was used to measure the accurate crown features. The results derived by multiple linear model showed (1) Ficus concinna, Dracontomelon duperreanum, Ormosia pinnata and Bischofia javanica are recommended in urban greening for suffering the smaller wind load under the same conditions, whereas Schefflera macrostachya, Acacia confusa and Khaya senegalensis are inadequate towards the view of crown features; (2) crown features like crown horizontal ratio, windward side projection and porosity ratio are important in estimating wind load. Our study demonstrated that evaluating the wind load via crown features is feasible, and provided valuable suggestion for selecting idealized decorative trees in urban environment with a smaller wind load due to the crown features.
Quasi zenith satellite system-reflectometry for sea-level measurement and implication of machine learning methodology
Authors: Ansari Kutubuddin , Seok Hong-Woo , Jamjareegulgarn Punyawi 
Published: December 2022

AbstractThe tide gauge measurements from global navigation satellite system reflectometry (GNSS-R) observables are considered to be a promising alternative to the traditional tide gauges in the present days. In the present paper, we deliver a comparative analysis of tide-gauge (TG) measurements retrieved by quasi-zenith satellite system-reflectometry (QZSS-R) and the legacy TG recordings with additional observables from other constellations viz. GPS-R and GLONASS-R. The signal-to-noise ratio data of QZSS (L1, L2, and L5 signals) retrieved at the P109 site of GNSS Earth Observation Network in Japan (37.815° N; 138.281° E; 44.70 m elevation in ellipsoidal height) during 01 October 2019 to 31 December 2019. The results from QZSS observations at L1, L2, and L5 signals show respective correlation coefficients of 0.8712, 0.6998, and 0.8763 with observed TG measurements whereas the corresponding root means square errors were 4.84 cm, 4.26 cm, and 4.24 cm. The QZSS-R signals revealed almost equivalent precise results to that of GPS-R (L1, L2, and L5 signals) and GLONASS-R (L1 and L2 signals). To reconstruct the tidal variability for QZSS-R measurements, a machine learning technique, i.e., kernel extreme learning machine (KELM) is implemented that is based on variational mode decomposition of the parameters. These KELM reconstructed outcomes from QZSS-R L1, L2, and L5 observables provide the respective correlation coefficients of 0.9252, 0.7895, and 0.9146 with TG measurements. The mean errors between the KELM reconstructed outcomes and observed TG measurements for QZSS-R, GPS-R, and GLONASS-R very often lies close to the zero line, confirming that the KELM-based estimates from GNSS-R observations can provide alternative unbiased estimations to the traditional TG measurement. The proposed method seems to be effective, foreseeing a dense tide gauge estimations with the available QZSS-R along with other GNSS-R observables.
Operating region-dependent characteristics of weight updates in synaptic In–Ga–Zn–O thin-film transistors
Authors: Cha Danyoung , Kang Yeonsu , Lee Sungsik 
Published: December 2022

AbstractWe present a study on characteristics of operating region-dependent weight updates in a synaptic thin-film transistor (Syn-TFT) with an amorphous In–Ga–Zn–O (IGZO) channel layer. For a synaptic behavior (e.g. a memory phenomenon) of the IGZO TFT, a defective oxide (e.g. SiO2) is intentionally used for a charge trapping due to programming pulses to the gate terminal. Based on this synaptic behavior, a conductance of the Syn-TFT is modulated depending on the programming pulses, thus weight updates. This weight update characteristics of the Syn-TFT is analyzed in terms of a dynamic ratio (drw) for two operating regions (i.e. the above-threshold and sub-threshold regimes). Here, the operating region is chosen depending on the level of the gate read-voltage relative to the threshold voltage of the Syn-TFT. To verify these, the static and pulsed characteristics of the fabricated Syn-TFT are monitored experimentally. As experimental results, it is found that the drw of the sub-threshold regime is larger compared to the above-threshold regime. In addition, the weight linearity in the sub-threshold regime is observed to be better compared to the above-threshold regime. Since it is expected that either the drw or weight linearity can affect performances (e.g. a classification accuracy) of an analog accelerator (AA) constructed with the Syn-TFTs, the AA simulation is performed to check this with a crossbar simulator.
L1CAM is required for early dissemination of fallopian tube carcinoma precursors to the ovary
Authors: Doberstein Kai , Spivak Rebecca , Reavis Hunter D. , Hooda Jagmohan , Feng Yi , Kroeger Paul T. , Stuckelberger Sarah , Mills Gordon B. , Devins Kyle M. , Schwartz Lauren E. , Iwanicki Marcin P. , Fogel Mina , Altevogt Peter , Drapkin Ronny 
Published: December 2022

AbstractMost ovarian high-grade serous carcinomas (HGSC) arise from Serous Tubal Intraepithelial Carcinoma (STIC) lesions in the distal end of the fallopian tube (FT). Formation of STIC lesions from FT secretory cells leads to seeding of the ovarian surface, with rapid tumor dissemination to other abdominal structures thereafter. It remains unclear how nascent malignant cells leave the FT to colonize the ovary. This report provides evidence that the L1 cell adhesion molecule (L1CAM) contributes to the ability of transformed FT secretory cells (FTSEC) to detach from the tube, survive under anchorage-independent conditions, and seed the ovarian surface. L1CAM was highly expressed on the apical cells of STIC lesions and contributed to ovarian colonization by upregulating integrins and fibronectin in malignant cells and activating the AKT and ERK pathways. These changes increased cell survival under ultra-low attachment conditions that mimic transit from the FT to the ovary. To study dissemination to the ovary, we developed a tumor-ovary co-culture model. We showed that L1CAM expression was important for FT cells to invade the ovary as a cohesive group. Our results indicate that in the early stages of HGSC development, transformed FTSECs disseminate from the FT to the ovary in a L1CAM-dependent manner.
Overexpression of notch signaling in renin cells leads to a polycystic kidney phenotype
Authors: Belyea Brian C. , Xu Fang , Wiltsie Margaret , Fountain Hayes , Charlton Jennifer , Fogo Agnes B. , Sequeira-Lopez Maria Luisa Soledad , Gomez Roberto Ariel 
Published: December 2022

Abstract
Polycystic kidney disease (PKD) is an inherited disorder that results in large kidneys, numerous fluid-filled cysts, and ultimately end-stage kidney disease. PKD is either autosomal dominant caused by mutations in PKD1 or PKD2 genes or autosomal recessive caused by mutations in the PKHD1 or DZIP1L genes. While the genetic basis of PKD is known, the downstream molecular mechanisms and signaling pathways that lead to deregulation of proliferation, apoptosis, and differentiation are not completely understood. The Notch pathway plays critical roles during kidney development including directing differentiation of various progenitor cells, and aberrant Notch signaling results in gross alternations in cell fate. In the present study, we generated and studied transgenic mice that have overexpression of an intracellular fragment of mouse Notch1 (‘NotchIC’) in renin-expressing cells. Mice with overexpression of NotchIC in renin-expressing cells developed numerous fluid-filled cysts, enlarged kidneys, anemia, renal insufficiency, and early death. Cysts developed in both glomeruli and proximal tubules, had increased proliferation marks, and had increased levels of Myc. The present work implicates the Notch signaling pathway as a central player in PKD pathogenesis and suggests that the Notch-Myc axis may be an important target for therapeutic intervention.