bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient prediction of attosecond two-colour pulses from an X-ray free-electron laser with machine learning
Authors: Alaa El-Din Karim K. , Alexander Oliver G. , Frasinski Leszek J. , Mintert Florian , Guo Zhaoheng , Duris Joseph , Zhang Zhen , Cesar David B. , Franz Paris , Driver Taran , Walter Peter , Cryan James P. , Marinelli Agostino , Marangos Jon P. , Mukherjee Rick 
Published: March 2024

AbstractX-ray free-electron lasers are sources of coherent, high-intensity X-rays with numerous applications in ultra-fast measurements and dynamic structural imaging. Due to the stochastic nature of the self-amplified spontaneous emission process and the difficulty in controlling injection of electrons, output pulses exhibit significant noise and limited temporal coherence. Standard measurement techniques used for characterizing two-coloured X-ray pulses are challenging, as they are either invasive or diagnostically expensive. In this work, we employ machine learning methods such as neural networks and decision trees to predict the central photon energies of pairs of attosecond fundamental and second harmonic pulses using parameters that are easily recorded at the high-repetition rate of a single shot. Using real experimental data, we apply a detailed feature analysis on the input parameters while optimizing the training time of the machine learning methods. Our predictive models are able to make predictions of central photon energy for one of the pulses without measuring the other pulse, thereby leveraging the use of the spectrometer without having to extend its detection window. We anticipate applications in X-ray spectroscopy using XFELs, such as in time-resolved X-ray absorption and photoemission spectroscopy, where improved measurement of input spectra will lead to better experimental outcomes.
Assessing heterogeneous groundwater systems: Geostatistical interpretation of well logging data for estimating essential hydrogeological parameters
Authors: Mohammed Musaab A. A. , Flores Yetzabbel G. , Szabó Norbert P. , Szűcs Péter 
Published: March 2024

AbstractThis research presents an unsupervised learning approach for interpreting well-log data to characterize the hydrostratigraphical units within the Quaternary aquifer system in Debrecen area, Eastern Hungary. The study applied factor analysis (FA) to extract factor logs from spontaneous potential (SP), natural gamma ray (NGR), and resistivity (RS) logs and correlate it to the petrophysical and hydrogeological parameters of shale volume and hydraulic conductivity. This research indicated a significant exponential relationship between the shale volume and the scaled first factor derived through factor analysis. As a result, a universal FA-based equation for shale volume estimation is derived that shows a close agreement with the deterministic shale volume estimation. Furthermore, the first scaled factor is correlated to the decimal logarithm of hydraulic conductivity estimated with the Csókás method. Csókás method is modified from the Kozeny-Carman equation that continuously estimates the hydraulic conductivity. FA and Csókás method-based estimations showed high similarity with a correlation coefficient of 0.84. The use of factor analysis provided a new strategy for geophysical well-logs interpretation that bridges the gap between traditional and data-driven machine learning techniques. This approach is beneficial in characterizing heterogeneous aquifer systems for successful groundwater resource development.
An epidemiological modeling framework to inform institutional-level response to infectious disease outbreaks: a Covid-19 case study
Authors: Ma Zichen , Rennert Lior 
Published: March 2024

AbstractInstitutions have an enhanced ability to implement tailored mitigation measures during infectious disease outbreaks. However, macro-level predictive models are inefficient for guiding institutional decision-making due to uncertainty in local-level model input parameters. We present an institutional-level modeling toolkit used to inform prediction, resource procurement and allocation, and policy implementation at Clemson University throughout the Covid-19 pandemic. Through incorporating real-time estimation of disease surveillance and epidemiological measures based on institutional data, we argue this approach helps minimize uncertainties in input parameters presented in the broader literature and increases prediction accuracy. We demonstrate this through case studies at Clemson and other university settings during the Omicron BA.1 and BA.4/BA.5 variant surges. The input parameters of our toolkit are easily adaptable to other institutional settings during future health emergencies. This methodological approach has potential to improve public health response through increasing the capability of institutions to make data-informed decisions that better prioritize the health and safety of their communities while minimizing operational disruptions.
TiO2 supported pallidum-bipyridyl complex as an efficient catalyst for Suzuki–Miyaura reaction in aqueous-ethanol
Authors: Gandra Upendar Reddy , Reddy Pogula Sreekanth , Salam Amatus , Gajagouni Surya Prakash , Alfantazi Akram , Mohideen M. Infas H. 
Published: March 2024

AbstractOwing to their improved catalytic stability and ability to undergo repeated cycles, solid-supported catalysts show great potential for various catalytic reactions. In this study, we synthesized a catalyst comprising a palladium-2,2-bipyridine complex supported on TiO2 nanoparticles (TiO2@BDP-PdCl2) fully characterised and investigated its efficacy in Suzuki–Miyaura cross coupling reactions involving phenyl boronic acid with various aryl halides under mild reaction conditions. The 2,2′- bipyridine (bp) has shown excellent complexation properties for Pd (II) and it could be easily anchored onto functionalized TiO2 support by the bridging carboxylate ions. The composition and structure of the as-prepared catalyst was characterized by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), Transmission Electron Microscope (TEM), X-ray photoelectron spectroscopy (XPS), and UV–Vis spectroscopy. The catalyst easily demonstrated separability, enhancing its practicality in catalytic processes. Subsequent utilization showed a consistent activity level, suggesting the stabilization of the aggregated catalyst species. This research sheds light on the importance of catalyst stability and maintenance during consecutive reaction cycles.
Whole-genome sequence and resistance determinants of four Elizabethkingia anophelis clinical isolates collected in Hanoi, Vietnam
Authors: Commans Florian , Hayer Juliette , Do Bich Ngoc , Tran Thi Thanh Tam , Le Thi Thu Hang , Bui Thanh Thuyet , Le Huu Song , Bañuls Anne-Laure , Bui Tien Sy , Nguyen Quang Huy 
Published: March 2024

AbstractFour isolates of the opportunistic pathogen Elizabethkingia anophelis were identified for the first time in a Vietnamese hospital and underwent antimicrobial susceptibility testing and genomic characterization by whole-genome sequencing. Complete, fully circularized genome sequences were obtained for all four isolates. Average Nucleotide Identity analysis and single nucleotide polymorphism phylogenetic analysis on the core genome showed that three of the four isolates were genetically distinct, ruling out the hypothesis of a single strain emergence. Antibiotic susceptibility testing highlighted multi-resistant phenotypes against most antimicrobial families, including beta-lactams, carbapenems, aminoglycosides, quinolones, macrolides, amphenicols, rifamycins and glycopeptides. Additionally, in silico genomic analysis was used to correlate the phenotypic susceptibility to putative resistance determinants, including resistance genes, point mutations and multidrug efflux pumps. Nine different resistance genes were located inside a single resistance pocket predicted to be a putative Integrative and Conjugative Element (ICE). This novel ICE was shared by three isolates from two different lineages and displayed similarity with ICEs previously reported in various Elizabethkingia and Chryseobacterium species. The role of such ICEs in pathogenicity, genome plasticity and antimicrobial resistance gene spread within the Flavobacteriaceae family needs to be further elucidated.
Cross-shore transport and eddies promote large scale response to urban eutrophication
Authors: Kessouri Fayçal , Sutula Martha A. , Bianchi Daniele , Ho Minna , Damien Pierre , McWilliams James C. , Frieder Christina A. , Renault Lionel , Frenzel Hartmut , McLaughlin Karen , Deutsch Curtis 
Published: March 2024

AbstractA key control on the magnitude of coastal eutrophication is the degree to which currents quickly transport nitrogen derived from human sources away from the coast to the open ocean before eutrophication develops. In the Southern California Bight (SCB), an upwelling-dominated eastern boundary current ecosystem, anthropogenic nitrogen inputs increase algal productivity and cause subsurface acidification and oxygen (O$$_{2}$$

2

) loss along the coast. However, the extent of anthropogenic influence on eutrophication beyond the coastal band, and the physical transport mechanisms and biogeochemical processes responsible for these effects are still poorly understood. Here, we use a submesoscale-resolving numerical model to document the detailed biogeochemical mass balance of nitrogen, carbon and oxygen, their physical transport, and effects on offshore habitats. Despite management of terrestrial nutrients that has occurred in the region over the last 20 years, coastal eutrophication continues to persist. The input of anthropogenic nutrients promote an increase in productivity, remineralization and respiration offshore, with recurrent O$$_{2}$$

2

loss and pH decline in a region located 30–90 km from the mainland. During 2013 to 2017, the spatially averaged 5-year loss rate across the Bight was 1.3 mmol m$$^{-3}$$

-
3

O$$_{2}$$

2

, with some locations losing on average up to 14.2 mmol m$$^{-3}$$

-
3

O$$_{2}$$

2

. The magnitude of loss is greater than model uncertainty assessed from data-model comparisons and from quantification of intrinsic variability. This phenomenon persists for 4 to 6 months of the year over an area of 27,840 km$$^{2}$$

2

($$\sim$$
∼
30% of SCB area). These recurrent features of acidification and oxygen loss are associated with cross-shore transport of nutrients by eddies and plankton biomass and their accumulation and retention within persistent eddies offshore within the SCB.
Multichannel mapping of in vivo rat uterine myometrium exhibits both high and low frequency electrical activity in non-pregnancy
Authors: Garrett Amy S. , Roesler Mathias W. , Athavale Omkar N. , Du Peng , Means Shawn A. , Clark Alys R. , Cheng Leo K. 
Published: March 2024

AbstractThe uterus exhibits intermittent electrophysiological activity in vivo. Although most active during labor, the non-pregnant uterus can exhibit activity of comparable magnitude to the early stages of labor. In this study, two types of flexible electrodes were utilized to measure the electrical activity of uterine smooth muscle in vivo in anesthetized, non-pregnant rats. Flexible printed circuit electrodes were placed on the serosal surface of the uterine horn of six anesthetized rats. Electrical activity was recorded for a duration of 20–30 min. Activity contained two components: high frequency activity (bursts) and an underlying low frequency ‘slow wave’ which occurred concurrently. These components had dominant frequencies of 6.82 ± 0.63 Hz for the burst frequency and 0.032 ± 0.0055 Hz for the slow wave frequency. There was a mean burst occurrence rate of 0.76 ± 0.23 bursts per minute and mean burst duration of 20.1 ± 6.5 s. The use of multiple high-resolution electrodes enabled 2D mapping of the initiation and propagation of activity along the uterine horn. This in vivo approach has the potential to provide the organ level detail to help interpret non-invasive body surface recordings.
Development of a formula for estimated glomerular filtration rate in pregnant women from physiological hyperfiltration of serum creatinine
Authors: Ahn Kwangjin , Lee Taesic , Kang Jieun , Choi Seong Jin , Hwang Sangwon , Seo Dong Min , Cho Jooyoung , Uh Young 
Published: March 2024

AbstractIncreased body fluids during pregnancy complicates the application of estimated glomerular filtration rate (eGFR) formulas that are based on body surface area. Furthermore, gestational renal dysfunction cannot be identified if the serum creatinine (SCr) concentration is within the non-pregnant reference interval (RI) despite inadequate pregnancy-related renal hyperfiltration. 1484 SCr measurements from 957 healthy pregnant women were collected. The average SCr value of gestational week (GW) 0–3 was the representative SCr value of non-pregnant status. While the distribution of SCr measurements varied across GWs, it was transformed into a normal distribution using the bootstrap resampling method. A polynomial linear regression method was applied to achieve a continuous and smooth transformation of values. The normally distributed SCr values of each GW were compared to the non-pregnant status, leading to the calculation of SCr hyperfiltration. The final equation, (2 − SCr (μmol/L)$$/$$
/
55.25)$$\times$$
×
103.1 $$\times$$
×
55.25/(56.7 − 0.223 $$\times$$
×
GW − 0.113 $$\times$$
×
GW2$$+$$
+
0.00545 $$\times$$
×
GW3 − 0.0000653 $$\times$$
×
GW4), and reference intervals for both SCr and eGFR for each GW were obtained. These RIs and novel equations can be effectively used to monitor renal dysfunction in pregnant women.
Socioeconomic factors and outcome after repair and reconstruction of digital and major nerve trunk injuries in the upper limb
Authors: Frostadottir Drifa , Perez Raquel , Dahlin Lars B. 
Published: March 2024

AbstractPeripheral nerve injuries in the upper limb can lead to substantial disability and pain. We aimed to assess how socioeconomic factors affect outcomes after repaired or reconstructed digital or major nerve trunk injuries in the upper limb. We identified 670 individuals, who underwent surgical nerve repair or reconstruction using sensory nerve autografts, in the Swedish National Quality Registry for Hand Surgery 2010–2018. Socioeconomic factors, including education, cohabitation, type of work, sick leave, immigrant status and income, were gathered from the Swedish statistical agency (www.scb.se) and National Diabetes Register (NDR). We calculated prevalence ratios (PR) to assess the relationship between socioeconomic factors and surgical outcomes for the nerve injuries. Individuals with a major nerve trunk injury had higher QuickDASH scores and lower income compared to those with digital nerve injury. Individuals with immigration background (adjusted PR = 2.0, 95% CI 1.2–3.2), history of > 4 weeks of sick leave the year before surgery (adjusted PR = 1.8, 95% CI 1.1–3.1), or education level below tertiary (adjusted PR = 2.8, 95% CI 1.7–4.7) had significantly higher QuickDASH scores. Recognizing impact of non-biological factors, including immigration, prior sick leave, and education level, on outcome after nerve surgery is crucial for improving prognosis in socioeconomically deprived individuals.
In silico analysis of overall survival with YBX1 in male and female solid tumours
Authors: Grimes David Robert , Rassamegevanon Treewut , Marignol Laure 
Published: March 2024

AbstractThe Y-box binding protein-1 (YBX1) gene codes for a multifunctional oncoprotein that is increasingly being linked to the regulations of many aspects of cancer cell biology. Disparities in treatment outcomes between male and female cancer patients are increasingly reported. This study aimed to examine the relationship between YBX1 expression and overall survival in male and female patients with solid tumours. Overall survival and YBX1 expression data for cohorts of male and female cancer patients obtained from freely available databases were analysed with a cox proportional hazard model with covariates of biological sex and YBX1 expression. Kaplan–Meier curves and Violin plots were constructed for segregated male and female cohorts. High YBX1 expression was significantly associated with poor survival in 2 female-only and 4 mixed-sex cancer sites. In female lung cancer patients, better survival and lower YBX1 expression were identified. The clinical importance of YBX1 expression in cancer ought to be evaluated in a sex-specific manner, especially in lung cancer.
Real-time monitoring of mitochondrial oxygenation during machine perfusion using resonance Raman spectroscopy predicts organ function
Authors: Jain Rohil , Ajenu Emmanuella O. , Lopera Higuita Manuela , Hafiz Ehab O. A. , Muzikansky Alona , Romfh Padraic , Tessier Shannon N. 
Published: March 2024

AbstractOrgan transplantation is a life-saving procedure affecting over 100,000 people on the transplant waitlist. Ischemia reperfusion injury (IRI) is a major challenge in the field as it can cause post-transplantation complications and limit the use of organs from extended criteria donors. Machine perfusion technology has the potential to mitigate IRI; however, it currently fails to achieve its full potential due to a lack of highly sensitive and specific assays to assess organ quality during perfusion. We developed a real-time and non-invasive method of assessing organs during perfusion based on mitochondrial function and injury using resonance Raman spectroscopy. It uses a 441 nm laser and a high-resolution spectrometer to quantify the oxidation state of mitochondrial cytochromes during perfusion. This index of mitochondrial oxidation, or 3RMR, was used to understand differences in mitochondrial recovery of cold ischemic rodent livers during machine perfusion at normothermic temperatures with an acellular versus cellular perfusate. Measurement of the mitochondrial oxidation revealed that there was no difference in 3RMR of fresh livers as a function of normothermic perfusion when comparing acellular versus cellular-based perfusates. However, following 24 h of static cold storage, 3RMR returned to baseline faster with a cellular-based perfusate, yet 3RMR progressively increased during perfusion, indicating injury may develop over time. Thus, this study emphasizes the need for further refinement of a reoxygenation strategy during normothermic machine perfusion that considers cold ischemia durations, gradual recovery/rewarming, and risk of hemolysis.
Variability and harshness shape flexible strategy-use in support of the constrained flexibility framework
Authors: Pope-Caldwell Sarah , Deffner Dominik , Maurits Luke , Neumann Terrence , Haun Daniel 
Published: March 2024

AbstractHuman cognition is incredibly flexible, allowing us to thrive within diverse environments. However, humans also tend to stick to familiar strategies, even when there are better solutions available. How do we exhibit flexibility in some contexts, yet inflexibility in others? The constrained flexibility framework (CFF) proposes that cognitive flexibility is shaped by variability, predictability, and harshness within decision-making environments. The CFF asserts that high elective switching (switching away from a working strategy) is maladaptive in stable or predictably variable environments, but adaptive in unpredictable environments, so long as harshness is low. Here we provide evidence for the CFF using a decision-making task completed across two studies with a total of 299 English-speaking adults. In line with the CFF, we found that elective switching was suppressed by harshness, using both within- and between-subjects harshness manipulations. Our results highlight the need to study how cognitive flexibility adapts to diverse contexts.
Patient perceptions of disease burden and treatment of myasthenia gravis based on sentiment analysis of digital conversations
Authors: Anderson Ashley , Pesa Jacqueline , Choudhry Zia , Brethenoux Caroline , Furey Patrick , Jackson Louis , Valleta Liliana Gil , Quijano Laura Gonzalez , Lorenzo Alex 
Published: March 2024

AbstractMyasthenia gravis (MG) is a rare, autoimmune, antibody-mediated, neuromuscular disease. This study analyzed digital conversations about MG to explore unprovoked perspectives. Advanced search, data extraction, and artificial intelligence-powered algorithms were used to harvest, mine, and structure public domain digital conversations about MG from US Internet Protocol addresses (August 2021 to August 2022). Thematic analyses examined topics, mindsets, and sentiments/key drivers via natural language processing and text analytics. Findings were described by sex/gender and treatment experience with steroids or intravenous immunoglobulin (IVIg). The 13,234 conversations were extracted from message boards (51%), social media networks (22%), topical sites (21%), and blogs (6%). Sex/gender was confirmed as female in 5703 and male in 2781 conversations, and treatment experience was with steroids in 3255 and IVIg in 2106 conversations. Topics focused on diagnosis (29%), living with MG (28%), symptoms (24%), and treatment (19%). Within 3176 conversations about symptoms, eye problems (21%), facial muscle problems (18%), and fatigue (18%) were most commonly described. Negative sentiments about MG were expressed in 59% of conversations, with only 2% considered positive. Negative conversations were dominated by themes of impact on life (29%), misdiagnosis problems (27%), treatment issues (24%), and symptom severity (20%). Impact on life was a key driver of negativity in conversations by both men (27%) and women (34%), and treatment issues was a dominant theme in conversations by steroid-treated (29%) and IVIg-treated (31%) patients. Of 1382 conversations discussing treatment barriers, 36% focused on side effects, 33% on lack of efficacy, 21% on misdiagnosis, and 10% on cost/insurance. Side effects formed the main barrier in conversations by both steroid-treated and IVIg-treated patients. Capturing the patient voice via digital conversations reveals a high degree of concern related to burden of disease, misdiagnosis, and common MG treatments among those with MG, pointing to a need for treatment options that can improve quality of life.
Research on predicting the driving forces of digital transformation in Chinese media companies based on machine learning
Authors: Wang Zhan , Li Yao , Zhao Xu , Wang Yuxuan , Xiao Zihan 
Published: March 2024

AbstractChinese media companies are facing opportunities and challenges brought about by digital transformation. Media economics takes the evaluation of the business results of media companies as the main research topic. However, overcoming the internal differences in the industry and comprehensively predicting the digital transformation of Chinese media companies from multiple dimensions has become an important issue to be understood. Based on the “TOE-I” theoretical framework, this study innovatively uses machine learning methods to predict the digital transformation of Chinese media companies and to analyze specific modes of the main driving factors affecting the digital transformation, using data from China’s A-share-listed media companies from 2010 to 2020. The study found that environmental drivers can most effectively and accurately predict the digital transformation of Chinese media companies. Therefore, under sustained and stable economic and financial policies, guiding inter-industry competition and providing balanced digital infrastructure conditions are keys to bridging internal barriers in the media industry and promoting digital transformation. In the process of transformation from traditional content to digital production, media companies should focus on policy changes, economic benefits, the decision-making role of core managers, and the training and preservation of digital technology talent.