bluuebunny/crossref_metadata_2025_split huggingface dataset:
High cure rates of Mycoplasma genitalium following empiric treatment with azithromycin alongside frequent detection of macrolide resistance in Austria
Authors: Chromy David , Starossek Lisa , Grabmeier-Pfistershammer Katharina , Adamek Sarah , Maischack Felix , Sammet Stefanie , Sadoghi Birgit , Stary Georg , Willinger Birgit , Weninger Wolfgang , Esser Stefan , Makristathis Athanasios , Bauer Wolfgang Michael 
Published: April 2024

Abstract
Background
Mycoplasma genitalium (MG) is an emerging sexually transmitted infection, often harboring resistance-associated mutations to azithromycin (AZM). Global surveillance has been mandated to tackle the burden caused by MG, yet no data are available for Austria. Thus, we aimed to investigate the prevalence of MG, disease characteristics, and treatment outcomes at the largest Austrian HIV—and STI clinic.

Methods
All MG test results at the Medical University of Vienna from 02/2019 to 03/2022 were evaluated. Azithromycin resistance testing was implemented in 03/2021.

Results
Among 2671 MG tests, 199 distinct and mostly asymptomatic (68%; 135/199) MG infections were identified, affecting 10% (178/1775) of all individuals. This study included 83% (1479/1775) men, 53% (940/1775) men who have sex with men (MSM), 31% (540/1754) HIV+, and 15% (267/1775) who were using HIV pre-exposure prophylaxis (PrEP). In logistic regression analysis, ‘MSM’ (aOR 2.55 (95% CI 1.65–3.92)), ‘use of PrEP’ (aOR 2.29 (95% CI 1.58–3.32)), and ‘history of syphilis’ (aOR 1.57 (95% CI 1.01–2.24) were independent predictors for MG infections. Eighty-nine percent (178/199) received treatment: 11% (21/178) doxycycline (2 weeks), 52% (92/178) AZM (5 days), and 37% ( 65/178) moxifloxacin (7–10 days) and 60% (106/178) had follow-up data available showing negative tests in 63% (5/8), 76% (44/58) and 85% (34/40), respectively. AZM resistance analysis was available for 57% (114/199)) and detected in 68% (78/114). Resistance-guided therapy achieved a cure in 87% (53/61), yet, empiric AZM-treatment (prior to 03/2021) cleared 68% (26/38).

Conclusions
Mycoplasma genitalium was readily detected in this Austrian observational study, affected predominantly MSM and often presented as asymptomatic disease. We observed a worryingly high prevalence of AZM resistance mutations; however, empiric AZM treatment cleared twice as many MG infections as expected.
Endocarditis: A Review of Recent Literature
Authors: Dale Scott , Tayyem Zaid , Maceyko Steven 
Published: April 2024

Abstract
Purpose of Review
Endocarditis remains a challenging diagnosis, with significant implications for early identification and initiation of therapy. In this review, we examine the evolution in the epidemiology and presentation of infectious endocarditis (IE), the role of new diagnostic tools, and the approach to therapy.

Recent Findings
Staphylococcus and Streptococcus species remain the most common causative organisms, but the prevalence of IE caused by enterococcus and non-HACEK organisms is increasing. While newer antibiotics such as dalbavancin have shown promise, treatment must still be tailored on an individual basis. Evidence suggests that antibiotic prophylaxis to prevent IE be limited to high-risk patients undergoing invasive procedures.

Summary
The Duke Criteria, first established in 1994, provide a guideline by which clinicians can identify affected patients. Now, 23 years after their last update in 2000, the Modified Duke Criteria have been revised to account for changes in our understanding of the disease. When combined with evolving treatment guidelines, clinicians have updated tools to help combat this disease.
Examining the Capabilities of GPT-4 to Write an APA-Style School Psychology Paper
Authors: Lockwood Adam B , Castleberry Joshua 
Published: April 2024

AbstractTechnological Advances in Artificial Intelligence (AI) have Brought forth the Potential for Models to Assist in Academic Writing. However, Concerns Regarding the Accuracy, Reliability, and Impact of AI in Academic Writing have been Raised. This Study Examined the Capabilities of GPT-4, a state-of-the-art AI Language Model, in Writing an American Psychological Association (APA)-style School Psychology Paper. Specifically, we Examined GPT-4’s Ability to Provide Citations and Substantiate Claims, Offer Factually Correct Information, and Generate Accurate APA (7th Edition; 2020) Style Citations and Referencing. The Results Reveal Limitations in GPT-4’s Performance, Including a lack of Proper Citations and Substantiation, Errors in Citations and Referencing, and the need for External Validation of Factual Accuracy. While GPT-4 Shows Potential, Further Refinement is Necessary to Enhance its Accuracy, Reliability, and Adherence to APA (2020) Guidelines. Future Research should Focus on Improving the Capabilities of AI Models for Scientific Writing and Developing Clear Policies for Their use in Academia.
Mortality prediction using survival energy models with functional data analysis
Authors: Mitsuda Daiki , Shimizu Yasutaka 
Published: April 2024

AbstractThe survival energy model (SEM), as originally introduced by Shimizu et al. (ASTIN Bull 51(1):191–219, 2020), is designed to characterize human bioenergetics by employing diffusion processes or inverse Gaussian processes. While parametric models have been employed to articulate the SEM, they exhibit inherent sensitivity in their parameters and hyperparameters, which in turn introduces issues of instability in estimation and prediction. In this paper, we demonstrate that the utilization of functional data analysis techniques for nonparametric estimation and prediction of critical functions within the SEM leads to a substantial enhancement in prediction performance.
Enhancing Data Trustworthiness in Explorative Analysis: An Interactive Approach for Data Quality Monitoring
Authors: Behringer Michael , Hirmer Pascal , Villanueva Alejandro , Rapp Jannis , Mitschang Bernhard 
Published: April 2024

AbstractThe volume of data to be analyzed has increased tremendously in recent years. In order to extract knowledge from this data, domain experts gain new insights with the help of graphical analysis tools for explorative analyses. Here, the reliability and trustworthiness of an exploratory analysis is determined by the quality of the underlying data. Existing approaches require manual testing to ensure data quality which is often neglected. This research aims to introduce a novel interactive approach for seamlessly integrating data quality considerations into the process of explorative data analysis conducted by domain experts. We derive requirements, conduct an extensive literature review, and develop an approach that efficiently combines stakeholders’ strengths, allowing unobtrusive data quality integration in interactive analysis. Our approach enhances trustworthiness due to unobtrusive monitoring of data quality within the context of explorative data analysis. Domain experts gain insights more reliably, bridging the gap between technical requirements and domain expertise. In conclusion, our research presents a promising solution for improving the reliability and trustworthiness of explorative data analysis, especially for domain experts who may lack technical knowledge. By seamlessly integrating data quality into the analytical process, we empower domain experts to extract valuable insights from the ever-increasing volume of data, thereby advancing the field of data-driven decision-making.
A bibliometric analysis of financial technology: unveiling the landscape of a rapidly evolving field
Authors: Biju Hannah , Mukthar K. P. Jaheer , Dhia Amir , Selvaratnam Doris Padmini , Singh Sanjay Kumar , Singh J. K. 
Published: April 2024

AbstractTechnology is paving innovative ways to provide financial services and improve the efficiency of financial systems. Since it is a dynamic field of research, it is important to look back on the ever-changing field of financial technology. This paper aims to analyse the existing research on financial technology through a bibliometric approach. The data were gathered from the Scopus database using secondary sources, and the analysis is presented descriptively along with science-mapping techniques. This paper offers an overview of the influential journals, authors, and organizations contributing to financial technology research. The study focuses on citation, cocitation, bibliographic coupling, and coauthorship analysis within the collected corpus. It is worth noting that this study is limited by the use of only one database, Scopus and excludes grey literature, this could lead to skewed results but this can be an arena for future research.
Forestry Ecosystem Protection from the Perspective of Eco-civilization Based on Self-Attention Using Hierarchical Dilated Convolutional Neural Network
Authors: Meng Rui 
Published: April 2024

AbstractEnsuring the sustainable protection of forestry ecosystems faces numerous challenges. One significant hurdle is the constant threat of illegal logging and deforestation. Despite various regulations and conservation efforts, enforcing these measures can be difficult, particularly in remote or poorly monitored areas. Additionally, the increasing global demand for timber and other forest products puts immense pressure on these ecosystems, leading to overexploitation and habitat degradation. In this manuscript, Self-Focused Hierarchical Augmented Convolution Neural Network (SAHD-CNN) optimized with Tasmanian Devil Optimization (TDO) algorithm is proposed. Initially data is taken from Global Leaf Area Index (LAI) dataset. Afterward the input data is fed to Adaptive Distorted Quantum Matched-Filter. The pre-processing output is provided to Self-Focused Hierarchical Augmented Convolution Neural Network (SAHD-CNN) to effectively classifying Forestry Ecosystem Protection (FEP) for high, medium, and low. The weight parameters of the SAHD-CNN are optimized using Tasmanian Devil (TD) Optimization method. The proposed method is implemented in MATLAB working platform. The FEP-SAHDCNN technique attains higher accuracy value of 99% than the existing techniques such as Forestry Ecosystem Protection based Particle swarm Optimization (FEP-PSO) Accuracy value is 65%, Forestry Ecosystem Protection using Evaluation-based Neural Network (FEP-EN) Accuracy value is 82%, and FEP-GRS Accuracy value is 79%. Thus, the proposed method gives optimal output than the existing methods.
Autistic traits in neurotypical adults are related to impaired perceptual–motor coordination
Authors: Kikuchi Ken , Higuchi Takahiro 
Published: April 2024

AbstractIndividuals with autism spectrum disorder (ASD) are more prone to injury due to falls or collisions with objects. This may be caused by impaired perceptual–motor coordination, including inaccurate body-related spatial perception and insufficient anticipatory motor planning due to a detail-focused processing style. To investigate this hypothesis, an action-selection task was developed to create conditions likely to induce collisions with obstacles and to assess perceptual accuracy and predictive attentional properties for the action selection of subsequent movements in a sequence of actions. Sixteen participants completed an autism-spectrum quotient (AQ) survey and the task. Results indicated that AQ correlated significantly with body-related spatial perception, and it was a significant predictor of the number of collisions. For the association between collisions and the eye-tracking data, results of a generalized linear mixed model showed that collisions were more likely to happen when the total fixation time to exit width was short and when the time to first fixation was late. This suggests that participants with higher autistic traits were not able to properly plan subsequent movements. Overall, these findings suggested that impaired perceptual–motor coordination, which could occur due to difficulties in perceiving body-related spatial relationships and anticipatory motor planning, may underlie the high susceptibility to injury observed in individuals with ASD.
Urban commercial marketing and economic factors, an evidence from Mashhad (Iran)
Authors: Hasani Ehsan , Sarvari Hadi 
Published: April 2024

AbstractThe present study attempts to spatial and temporal analysis of the reactions between urban commercial marketing and influencing economic factors in Mashhad City (Iran). For this purpose, statistical and spatial data from 18 selected commercial complexes and trading towers were collected using official documents, fieldwork observations, and surveys of some interviews for time windows of 2010 and 2020. The total annual revenue, as the commercial marketing indicator, was chosen as the dependent variable to indicate the mean productivity and profitability of shop stores in the case studies. Besides, eight factors, including commercial marketing and urban regional characteristics were chosen as independent factors. Results revealed that the mean values of commercial interest rates were recorded equal to 0.71 and 0.64 in 2010 and 2020, revealing the overall decrease in profitability of the commercial complexes within the recent decade. Despite the growing rate of construction of renewal mega projects and trading towers in the central district of Mashhad City, the marketing revenues and commercial interests had no positive relationships with city center profits in the recent decade. The land price market has severely changed the spatial structure and economy of Mashhad, such as commercial projects and marketing. It means that the main motivation for marketing in commercial complexes can be considered as regional land values instead of the traditional function of the religious city center.
Secrecy games, power, and resistance in global politics
Authors: Van Veeren Elspeth , Stevens Clare , Senu Amaha 
Published: April 2024

Abstract
In contrast to a view of secrecy as a tool of statecraft, where the game of ‘covering/uncovering’ dominates as the central way of interpreting secrecy’s power, we set out ‘secrecy games’ as an approach for understanding secrecy’s power and influence. To do so, we offer a set of three games to illustrate the more varied ways that secrecy operates and draw attention to the ways in which non-state actors use secrecy and shape its effects. In particular, we offer an analysis of: (1) the secrecy games of tunnelling in the Israeli–Palestinian conflict and the role of mobility as part of secrecy; (2) the secrecy game of camouflage and how stowaways blend in to facilitate access to global shipping routes; and (3) the secrecy game of maze-running and maze-making within urban warfare. Drawing these together, we show how secrecy involves a wider set of actors, practices, and associated knowledge-(un)making strategies than currently understood within International Relations. In turn, this expanded understanding of secrecy helps to make sense of the more complex ways in which secrecy is presented, used, resisted, and transformed – including and especially as a force that limits sovereign power – and, therefore, as central to what shapes global politics.
The Potential of Stratospheric Aerosol Injection to Reduce the Climatic Risks of Explosive Volcanic Eruptions
Authors: Quaglia I. , Visioni D. , Bednarz E. M. , MacMartin D. G. , Kravitz B. 
Published: April 2024

AbstractSulfur‐rich volcanic eruptions happen sporadically. If Stratospheric Aerosol Injection (SAI) were to be deployed, it is likely that explosive volcanic eruptions would happen during such a deployment. Here we use an ensemble of Earth System Model simulations to show how changing the injection strategy post‐eruption could be used to reduce the climate risks of a large volcanic eruption; the risks are also modified even without any change to the strategy. For a medium‐size eruption (10 Tg‐SO2) comparable to the SAI injection rate, the volcanic‐induced cooling would be reduced if it occurs under SAI, especially if artificial sulfur dioxide injections were immediately suspended. Alternatively, suspending injection only in the eruption hemisphere and continuing injection in the opposite would reduce shifts in precipitation in the tropical belt and thus mitigate eruption‐induced drought. Finally, we show that for eruptions much larger than the SAI deployment, changes in SAI strategy would have minimal effect.
Cross‐Comparison of Observations With the Predictions of Global Hybrid Simulations for Multiple IMF Discontinuities Impacting the Bow Shock and Magnetosheath
Authors: Lee S. H. , Sibeck D. G. , Wang X. , Lin Y. , Angelopoulos V. , Giles B. L. , Torbert R. B. , Russell C. T. , Wei H. , Burch J. L. 
Published: April 2024

AbstractWe use the three‐dimensional (3‐D) global hybrid code ANGIE3D to simulate the interaction of four solar wind tangential discontinuities (TDs) observed by ARTEMIS P1 from 0740 UT to 0800 UT on 28 December 2019 with the bow shock, magnetosheath, and magnetosphere. We demonstrate how the four discontinuities produce foreshock transients, a magnetosheath cavity‐like structure, and a brief magnetopause crossing observed by THEMIS and MMS spacecraft from 0800 UT to 0830 UT. THEMIS D observed entries into foreshock transients exhibiting low density, low magnetic field strength, and high temperature cores bounded by compressional regions with high densities and high magnetic field strengths. The MMS spacecraft observed cavities with strongly depressed magnetic field strengths and highly deflected velocity in the magnetosheath downstream from the foreshock. Dawnside THEMIS A magnetosheath observations indicate a brief magnetosphere entry exhibiting enhanced magnetic field strength, low density, and decreased and deflected velocity (sunward flow). The solar wind inputs into the 3‐D hybrid simulations resemble those seen by ARTEMIS. We simulate the interaction of four oblique TDs with properties similar to those in the observation. We place virtual spacecraft at the locations where observations were made. The hybrid simulations predict similar characteristics of the foreshock transients, a magnetosheath cavity, and a magnetopause crossing with characteristics similar to those observed by the multi‐spacecraft observations. The detailed and successful comparison of the interaction involving multiple TDs will be presented.
Body composition and motor function in children born large for gestational age at term
Authors: Ito Yuji , Ito Tadashi , Narahara Sho , Sugiura Hideshi , Sugiyama Yuichiro , Hattori Tetsuo , Kidokoro Hiroyuki , Tsuji Takeshi , Kubota Tetsuo , Natsume Jun , Noritake Koji , Ochi Nobuhiko 
Published: April 2024

Abstract
Background
This cross-sectional study compared body composition and motor function between children who were born large for gestational age (LGA) and those born appropriate for gestational age (AGA) and to investigate the association between gait quality and other variables.

Methods
Body composition was determined using a bioelectrical impedance analyzer. Motor functions were assessed using one-leg standing time, timed up-and-go test, five times sit-to-stand test, and three-dimensional gait analysis. We compared the results between two groups. We performed multiple regression analysis to evaluate the association between gait deviation index and variables of LGA, fat mass index, and motor functions (adjusted for age and sex).

Results
Children aged 6–12 years who were born LGA at term (n = 23) and those who were born AGA at term (n = 147) were enrolled. The LGA group had a higher fat mass index (2.9 vs. 2.2, p = 0.006) and lower gait deviation index (91.4 vs. 95.4, p = 0.011) than the AGA group. On multiple regression analysis, gait deviation index was associated with being LGA and fat mass index.

Conclusions
In school-aged children who were born LGA, monitoring increased fat mass index and decreased gait deviation index could lessen the risk of metabolic syndrome and reduced gait function.

Impact

Children aged 6–12 years who were born large for gestational age (LGA) at term showed a higher fat mass index and lower gait deviation index than those who were born appropriate for gestational age at term.

No significant differences in balance function or muscle strength were observed between groups.

On multiple regression analysis, gait deviation index was associated with being LGA at birth and fat mass index.

In school-aged children who were born LGA, monitoring increased fat mass index and decreased gait deviation index could lessen the risk of metabolic syndrome and reduced gait function.
AZGP1 in POMC neurons modulates energy homeostasis and metabolism through leptin-mediated STAT3 phosphorylation
Authors: Qiu Sheng , Wu Qinan , Wang Hao , Liu Dongfang , Chen Chen , Zhu Zhiming , Zheng Hongting , Yang Gangyi , Li Ling , Yang Mengliu 
Published: April 2024

AbstractZinc-alpha2-glycoprotein (AZGP1) has been implicated in peripheral metabolism; however, its role in regulating energy metabolism in the brain, particularly in POMC neurons, remains unknown. Here, we show that AZGP1 in POMC neurons plays a crucial role in controlling whole-body metabolism. POMC neuron-specific overexpression of Azgp1 under high-fat diet conditions reduces energy intake, raises energy expenditure, elevates peripheral tissue leptin and insulin sensitivity, alleviates liver steatosis, and promotes adipose tissue browning. Conversely, mice with inducible deletion of Azgp1 in POMC neurons exhibit the opposite metabolic phenotypes, showing increased susceptibility to diet-induced obesity. Notably, an increase in AZGP1 signaling in the hypothalamus elevates STAT3 phosphorylation and increases POMC neuron excitability. Mechanistically, AZGP1 enhances leptin-JAK2-STAT3 signaling by interacting with acylglycerol kinase (AGK) to block its ubiquitination degradation. Collectively, these results suggest that AZGP1 plays a crucial role in regulating energy homeostasis and glucose/lipid metabolism by acting on hypothalamic POMC neurons.
Correlative, ML-based and non-destructive 3D-analysis of intergranular fatigue cracking in SAC305-Bi solder balls
Authors: Cui Charlotte , Falah Chamasemani Fereshteh , Paulachan Priya , Sinojiya Rahulkumar , Rosc Jördis , Reisinger Michael , Imrich Peter , Hartner Walter , Brunner Roland 
Published: April 2024

AbstractReliable connections of electrical components embody a crucial topic in the microelectronics and power semiconductor industry. This study utilises 3D non-destructive X-ray tomography and specifically developed machine learning (ML-) algorithms to statistically investigate crack initiation and propagation in SAC305-Bi solder balls upon thermal cycling on board (TCoB). We quantitatively segment fatigue cracks and flux pores from 3D X-ray tomography data utilising a multi-level ML-workflow incorporating a 3D U-Net model. The data reveals that intergranular fatigue cracking is the predominant failure mechanism during TCoB and that dynamic recrystallisation precedes crack initiation. Moreover, we find that fatigue cracks are initiated at surface notches, flux pores and printed circuit board-metallisation intrusions. The work provides important insights regarding the underlying microstructural and mechanical mechanisms for recrystallisation and cracking, uniting the aspects of big-data analysis with ML-algorithms and in-depth understanding about the underlying materials science.