bluuebunny/crossref_metadata_2025_split huggingface dataset:
An R&D perspective on international trade and sustainable development
Authors: Costantini Lorenzo , Laio Francesco , Ridolfi Luca , Sciarra Carla 
Published: May 2023

AbstractResearch and Development (R&D) is the common denominator of innovation and technological progress, supporting sustainable development and economic growth. In light of the availability of new datasets and innovative indicators, in this work, we introduce a novel perspective to analyse the international trade of goods through the lenses of the nexus R&D-industrial activities of countries. We propose two new indices, RDE and RDI, summarizing the R&D content of countries’ export and import baskets—respectively—and investigate their evolution in time, during the period 1995–2017, and space. We demonstrate the potential of these indices to shed new light on the evolution of R&D choices and trade, innovation, and development. In fact, compared to standard measures of countries’ development and economic growth (e.g., the Human Development Index among the others tested), these indices provide complementary information. In particular, tracing the trajectories of countries along the RDE-HDI plane, different dynamics appear for countries with increased HDI, which we speculate can be reasoned with countries’ availability of natural resources. Eventually, we identify two insightful applications of the indices to investigate further countries’ environmental performances as related to their role in international trade.
Indel driven rapid evolution of core nuclear pore protein gene promoters
Authors: McQuarrie David W. J. , Read Adam M. , Stephens Frannie H. S. , Civetta Alberto , Soller Matthias 
Published: May 2023

AbstractNuclear pore proteins (Nups) prominently are among the few genes linked to speciation from hybrid incompatibility in Drosophila. These studies have focused on coding sequence evolution of Nup96 and Nup160 and shown evidence of positive selection driving nucleoporin evolution. Intriguingly, channel Nup54 functionality is required for neuronal wiring underlying the female post-mating response induced by male-derived sex-peptide. A region of rapid evolution in the core promoter of Nup54 suggests a critical role for general transcriptional regulatory elements at the onset of speciation, but whether this is a general feature of Nup genes has not been determined. Consistent with findings for Nup54, additional channel Nup58 and Nup62 promoters also rapidly accumulate insertions/deletions (indels). Comprehensive examination of Nup upstream regions reveals that core Nup complex gene promoters accumulate indels rapidly. Since changes in promoters can drive changes in expression, these results indicate an evolutionary mechanism driven by indel accumulation in core Nup promoters. Compensation of such gene expression changes could lead to altered neuronal wiring, rapid fixation of traits caused by promoter changes and subsequently the rise of new species. Hence, the nuclear pore complex may act as a nexus for species-specific changes via nucleo-cytoplasmic transport regulated gene expression.
Ultrathin acoustic metamaterial as super absorber for broadband low-frequency underwater sound
Authors: Zhou Xindong , Wang Xiaochen , Xin Fengxian 
Published: May 2023

AbstractIn this work, an ultrathin acoustic metamaterial formed by space-coiled water channels with a rubber coating is proposed for underwater sound absorption. The proposed metamaterial achieves perfect sound absorption ($$\alpha$$
α
> 0.99) at 181 Hz, which has a deep subwavelength thickness ($$\lambda {/}162$$

λ
/
162

). The theoretical prediction is consistent with the numerical simulation, which demonstrate the broadband low-frequency sound absorption performance of the proposed super absorber. The introduction of rubber coating leads to a significant decrease of the effective sound speed in the water channel, resulting in the phenomenon of slow-sound propagation. From the perspective of numerical simulations and acoustic impedance analysis, it is proved that the rubber coating on the channel boundary causes slow-sound propagation with inherent dissipation, which is the key to meet the impedance matching condition and achieve perfect low-frequency sound absorption. Parametric studies are also carried out to investigate the effect of specific structural and material parameters on sound absorption. By tailoring key geometric parameters, an ultra-broadband underwater sound absorber is constructed, with a perfect absorption range of 365–900 Hz and a deep subwavelength thickness of 33 mm. This work paves a new way for designing underwater acoustic metamaterials and controlling underwater acoustic waves.
Nonlinear and machine learning analyses on high-density EEG data of math experts and novices
Authors: Poikonen Hanna , Zaluska Tomasz , Wang Xiaying , Magno Michele , Kapur Manu 
Published: May 2023

AbstractCurrent trend in neurosciences is to use naturalistic stimuli, such as cinema, class-room biology or video gaming, aiming to understand the brain functions during ecologically valid conditions. Naturalistic stimuli recruit complex and overlapping cognitive, emotional and sensory brain processes. Brain oscillations form underlying mechanisms for such processes, and further, these processes can be modified by expertise. Human cortical functions are often analyzed with linear methods despite brain as a biological system is highly nonlinear. This study applies a relatively robust nonlinear method, Higuchi fractal dimension (HFD), to classify cortical functions of math experts and novices when they solve long and complex math demonstrations in an EEG laboratory. Brain imaging data, which is collected over a long time span during naturalistic stimuli, enables the application of data-driven analyses. Therefore, we also explore the neural signature of math expertise with machine learning algorithms. There is a need for novel methodologies in analyzing naturalistic data because formulation of theories of the brain functions in the real world based on reductionist and simplified study designs is both challenging and questionable. Data-driven intelligent approaches may be helpful in developing and testing new theories on complex brain functions. Our results clarify the different neural signature, analyzed by HFD, of math experts and novices during complex math and suggest machine learning as a promising data-driven approach to understand the brain processes in expertise and mathematical cognition.
Uncertainties surrounding the oldest fossil record of diatoms
Authors: Bryłka Karolina , Alverson Andrew J. , Pickering Rebecca A. , Richoz Sylvain , Conley Daniel J. 
Published: May 2023

AbstractMolecular clocks estimate that diatom microalgae, one of Earth’s foremost primary producers, originated near the Triassic–Jurassic boundary (200 Ma), which is close in age to the earliest, generally accepted diatom fossils of the genus Pyxidicula. During an extensive search for Jurassic diatoms from twenty-five sites worldwide, three sites yielded microfossils initially recognized as diatoms. After applying stringent safeguards and evaluation criteria, however, the fossils found at each of the three sites were rejected as new diatom records. This led us to systematically reexamine published evidence in support of Lower- and Middle-Jurassic Pyxidicula fossils. Although Pyxidicula resembles some extant radial centric diatoms and has character states that may have been similar to those of ancestral diatoms, we describe numerous sources of uncertainty regarding the reliability of these records. We conclude that the Lower Jurassic Pyxidicula fossils were most likely calcareous nannofossils, whereas the Middle Jurassic Pyxidicula species has been reassigned to the Lower Cretaceous and is likely a testate amoeba, not a diatom. Excluding the Pyxidicula fossils widens the gap between the estimated time of origin and the oldest abundant fossil diatom record to 75 million years. This study underscores the difficulties in discovering and validating ancient microfossils.
The impact of methicillin resistance on clinical outcome among patients with Staphylococcus aureus osteomyelitis: a retrospective cohort study of 482 cases
Authors: Wu Hongri , Jia Chao , Wang Xiaohua , Shen Jie , Tan Jiulin , Wei Zhiyuan , Wang Shulin , Sun Dong , Xie Zhao , luo Fei 
Published: May 2023

AbstractThis study was designed to evaluate the impact of methicillin resistance on the outcomes among patients with S. aureus osteomyelitis. We reviewed all extremity osteomyelitis patients treated in our clinic center between 2013 and 2020. All adult patients with S. aureus pathogen infection were included. Clinical outcome in terms of infection control, length of hospital stay, and complications were observed at the end of a 24‐month follow‐up and retrospectively analyzed between populations with/without methicillin resistance. In total, 482 osteomyelitis patients due to S. aureus were enrolled. The proportion of methicillin-resistant S. aureus (MRSA) was 17% (82) and 83% (400) of patients had Methicillin-sensitive S. aureus (MSSA). Of 482 patients, 13.7% (66) presented with infection persistence after initial debridement and antibiotic treatment (6 weeks), needed repeated debridement, 8.5% (41) had recurrence after all treatment end and a period infection cure, complications were observed in 17 (3.5%) patients (pathologic fracture; 4, nonunion; 5, amputation; 8) at final follow-up. Following multivariate analysis, we found patients with S. aureus osteomyelitis due to MRSA are more likely to develop a persistent infection (OR: 2.26; 95% CI 1.24–4.13) compared to patients with MSSA. Patients infected with MRSA also suffered more complications (8.5% vs. 2.5%, p = 0.015) and longer hospital stays (median: 32 vs. 23 days, p < 0.001). No statistically significant differences were found in recurrence. The data indicated Methicillin resistance had adverse clinical implication for infection persistence among patients with S. aureus osteomyelitis. These results will help for patients counsel and preparation for treatment.
Peripheral retinal vessel whitening in patients with diabetes mellitus
Authors: Kalaw Fritz Gerald P. , Sharma Paripoorna , Kako Rasha Nabil , Walker Evan , Borooah Shyamanga 
Published: May 2023

AbstractThis study aimed to identify retinal vessel whitening outside the standard Early Treatment Diabetic Retinopathy Study (ETDRS) fields and to correlate the findings with vision and severity of diabetic retinopathy. Patients with diabetes mellitus who were seen in the retinal clinic to assess diabetic retinopathy status were included. Retinal vessel whitening was identified using ultra-widefield imaging. Four hundred and forty-five eyes of 260 patients were included. Thirty-five eyes in 24 patients (7.9%) were noted to have peripheral retinal vessel whitening. Thirty-one eyes with peripheral retinal vessel whitening did not have vessel whitening within the standard 7 ETDRS fields (p < 0.001). The proportion of whitening increased as DR severity increased, from 4.0% for patients with no DR (OR 0.249) to 33.3% for those with severe NPDR and PDR (OR 6.430 and 7.232, respectively). In addition, patients with peripheral retinal vessel whitening had worse visual acuity (logMAR = 0.34) compared to those without (logMAR = 0.15) (p < 0.001). In conclusion, we found an association between peripheral retinal vessel whitening in diabetic patients which correlated with diabetic retinopathy severity. Additionally, we found an association between vessel whitening and reduced vision, suggesting that vessel whitening identified using ultra-widefield imaging may be a prognostic indicator of vision in diabetic retinopathy.
Combined structural analysis and cathodoluminescence investigations of single Pr3+-doped Ca2Nb3O10 nanosheets
Authors: Changizi Rasa , Zaefferer Stefan , Ziegler Christian , Romaka Vitaliy , Lotsch Bettina V. , Scheu Christina 
Published: May 2023

AbstractDue to the novel properties of both 2D materials and rare-earth elements, developing 2D rare-earth nanomaterials has a growing interest in research. To produce the most efficient rare-earth nanosheets, it is essential to find out the correlation between chemical composition, atomic structure and luminescent properties of individual sheets. In this study, 2D nanosheets exfoliated from Pr3+-doped KCa2Nb3O10 particles with different Pr concentrations were investigated. Energy dispersive X-ray spectroscopy analysis indicates that the nanosheets contain Ca, Nb and O and a varying Pr content between 0.9 and 1.8 at%. K was completely removed after exfoliation. The crystal structure is monoclinic as in the bulk. The thinnest nanosheets are 3 nm corresponding to one triple perovskite-type layer with Nb on the B sites and Ca on the A sites, surrounded by charge compensating TBA+ molecules. Thicker nanosheets of 12 nm thickness (and above) were observed too by transmission electron microscopy with the same chemical composition. This indicates that several perovskite-type triple layers remain stacked similar to the bulk. Luminescent properties of individual 2D nanosheets were studied using a cathodoluminescence spectrometer revealing additional transitions in the visible region in comparison to the spectra of different bulk phases.
Operational forecasts of wave-driven water levels and coastal hazards for US Gulf and Atlantic coasts
Authors: Stockdon Hilary F. , Long Joseph W. , Palmsten Margaret L. , Van der Westhuysen Andre , Doran Kara S. , Snell Richard J. 
Published: May 2023

AbstractPredictions of total water levels, the elevation of combined tides, surge, and wave runup at the shoreline, are necessary to provide guidance on potential coastal erosion and flooding. Despite the importance of early warning systems for these hazards, existing real-time meteorological and oceanographic forecast systems at regional and national scales, until now, have lacked estimates of runup necessary to predict wave-driven overwash and erosion. To address this need, we present an approach that includes wave runup in an operational, national-scale modeling system. Using this system, we quantify the contribution of waves to potential dune erosion events along 4,700 km of U.S. Atlantic and Gulf of Mexico sandy coastlines for a one-year period. Dune erosion events were predicted to occur at over 80% of coastal locations, where waves dominated shoreline total water levels, representing 73% of the signal. This shows that models that neglect the wave component underestimate the hazard. This new, national-scale operational modeling system provides communities with timely, local-scale (0.5 km resolution) coastal hazard warnings for all wave conditions, allowing for rapid decision-making related to safety and emergency management. The modeling system also enables continued research into wave-driven processes at a broad range of coastal areas.
Unsupervised meta-clustering identifies risk clusters in acute myeloid leukemia based on clinical and genetic profiles
Authors: Eckardt Jan-Niklas , Röllig Christoph , Metzeler Klaus , Heisig Peter , Stasik Sebastian , Georgi Julia-Annabell , Kroschinsky Frank , Stölzel Friedrich , Platzbecker Uwe , Spiekermann Karsten , Krug Utz , Braess Jan , Görlich Dennis , Sauerland Cristina , Woermann Bernhard , Herold Tobias , Hiddemann Wolfgang , Müller-Tidow Carsten , Serve Hubert , Baldus Claudia D. , Schäfer-Eckart Kerstin , Kaufmann Martin , Krause Stefan W. , Hänel Mathias , Berdel Wolfgang E. , Schliemann Christoph , Mayer Jiri , Hanoun Maher , Schetelig Johannes , Wendt Karsten , Bornhäuser Martin , Thiede Christian , Middeke Jan Moritz 
Published: May 2023

AbstractBackgroundIncreasingly large and complex biomedical data sets challenge conventional hypothesis-driven analytical approaches, however, data-driven unsupervised learning can detect inherent patterns in such data sets.MethodsWhile unsupervised analysis in the medical literature commonly only utilizes a single clustering algorithm for a given data set, we developed a large-scale model with 605 different combinations of target dimensionalities as well as transformation and clustering algorithms and subsequent meta-clustering of individual results. With this model, we investigated a large cohort of 1383 patients from 59 centers in Germany with newly diagnosed acute myeloid leukemia for whom 212 clinical, laboratory, cytogenetic and molecular genetic parameters were available.ResultsUnsupervised learning identifies four distinct patient clusters, and statistical analysis shows significant differences in rate of complete remissions, event-free, relapse-free and overall survival between the four clusters. In comparison to the standard-of-care hypothesis-driven European Leukemia Net (ELN2017) risk stratification model, we find all three ELN2017 risk categories being represented in all four clusters in varying proportions indicating unappreciated complexity of AML biology in current established risk stratification models. Further, by using assigned clusters as labels we subsequently train a supervised model to validate cluster assignments on a large external multicenter cohort of 664 intensively treated AML patients.ConclusionsDynamic data-driven models are likely more suitable for risk stratification in the context of increasingly complex medical data than rigid hypothesis-driven models to allow for a more personalized treatment allocation and gain novel insights into disease biology.
Therapy Outcomes for Teenage Athletes With Exercise-Induced Laryngeal Obstruction
Authors: Fujiki Robert Brinton , Olson-Greb Bryn , Braden Maia , Thibeault Susan L. 
Published: May 2023

Purpose:
This study examined treatment outcomes of speech-language pathology intervention addressing exercise-induced laryngeal obstruction (EILO) symptoms in teenage athletes.

Method:
A prospective cohort design was utilized; teenagers diagnosed with EILO completed questionnaires during initial EILO evaluations, posttherapy, 3-month posttherapy, and 6-month posttherapy. Questionnaires examined the frequency of breathing problems, the use of the techniques taught in therapy, and the use of inhaler. Patients completed the Pediatric Quality of Life (PedsQL) inventory at all time points.

Results:

Fifty-nine patients completed baseline questionnaires. Of these, 38 were surveyed posttherapy, 32 at 3-month posttherapy, and 27 at 6-month posttherapy. Patients reported more frequent and complete activity participation immediately posttherapy (
p
= .017) as well as reduced inhaler use (
p
= .036). Patients also reported a significant reduction in the frequency of breathing problems 6-month posttherapy (
p
= .015). Baseline PedsQL physical and psychosocial scores were below normative range and were not impacted by therapy. Baseline physical PedsQL score significantly predicted frequency of breathing difficulty 6-month posttherapy (
p
= .04), as better baseline scores were associated with fewer residual symptoms.

Conclusions:
Therapy with a speech-language pathologist for EILO allowed for more frequent physical activity following therapy completion and decreased dyspnea symptoms 6-month posttherapy. Therapy was associated with a decrease in inhaler use. PedsQL scores indicated mildly poor health-related quality of life even after EILO symptoms improved. Findings support therapy as an effective treatment for EILO in teenage athletes and suggest that dyspnea symptoms may continue to improve following discharge as patients continue using therapy techniques.
Sources of Misinterpretation in the Input and Their Implications for Language Intervention With English-Speaking Children
Authors: Leonard Laurence B. , Deevy Patricia , Bredin-Oja Shelley L. , Schroeder Mariel Lee 
Published: May 2023

Purpose:
In English and related languages, many preschool-age children with developmental language disorder (DLD) have difficulties using tense and agreement consistently. In this review article, we discuss two potential input-related sources of this difficulty and offer several possible strategies aimed at circumventing input obstacles.

Method:
We review a series of studies from English, supplemented by evidence from computational modeling and studies of other languages. Collectively, the studies show that instances of failures to express tense and agreement in DLD resemble portions of larger sentences in everyday input in which tense and agreement marking is appropriately absent. Furthermore, experimental studies show that children's use of tense and agreement can be swayed by manipulating details in fully grammatical input sentences.

Results:

The available evidence points to two particular sources of input that may contribute to tense and agreement inconsistency. One source is the appearance of subject + nonfinite verb sequences that appear in auxiliary-fronted questions (e.g.,
Is [the girl running]? Does [the boy like popcorn]?
) and as dependent clauses in more complex sentences (e.g.,
Help [her wash the dishes]
;
We saw [the frog hopping]
). The other source is the frequent appearance of bare stems in the input, whether nonfinite (e.g.,
go
in
Make him go fast
) or finite (e.g.,
go
in
I go, you go
).

Conclusions:
Although the likely sources of input are a natural part of the language that all children hear, procedures that alter the distribution of this input might be used in the early stages of intervention. Subsequent steps can incorporate more explicit comprehension and production techniques. A variety of suggestions are offered.
A review of silicon carbide MOSFETs in electrified vehicles: Application, challenges, and future development
Authors: Shi Bufan , Ramones Anna Isabel , Liu Yingxu , Wang Haoran , Li Yu , Pischinger Stefan , Andert Jakob 
Published: May 2023

AbstractCompared with silicon‐based Insulated Gate Bipolar Transistors (IGBTs), silicon carbide (SiC) Metal‐Oxide‐Semiconductor Field‐Effect Transistors (MOSFETs) are characterized by higher operating temperatures, switching speeds and switching frequencies, and are considered the next evolutionary step for future electric drives. The application of SiC MOSFETs in the field of electrified vehicles has brought many benefits, such as higher efficiency, higher power density, and simplified cooling system, and can be seen as an enabler for high‐power fast battery charging. This article reviews the benefits of SiC MOSFETs in different electrified vehicle (EV) application scenarios, including traction inverters, on‐board converters, and off‐board charging applications. However, replacing Si‐IGBTs with SiC MOSFETs introduces several new technical challenges, such as stronger electromagnetic interference (EMI), reliability issues, potential electric machine insulation failure due to high transient voltages, and cooling difficulties. Compared to mature silicon‐based semiconductor technologies, these challenges have so far hindered the widespread adoption of SiC MOSFETs in automotive applications. To fully exploit the advantages of SiC MOSFETs in automotive applications and enhance their reliability, this paper explores future technology developments in SiC MOSFET module packaging and driver design, as well as novel electric machine drive strategies with higher switching frequencies, and optimized high‐frequency machine design.