bluuebunny/crossref_metadata_2025_split huggingface dataset:
DeepJEB: 3D Deep Learning-Based Synthetic Jet Engine Bracket Dataset
Authors: Hong Seongjun , Kwon Yongmin , Shin Dongju , Park Jangseop , Kang Namwoo 
Published: November 2024

Abstract
Recent advances in artificial intelligence (AI) have impacted various fields, including mechanical engineering. However, the development of diverse, high-quality datasets for structural analysis remains a challenge. Traditional datasets, like the jet engine bracket dataset, are limited by small sample sizes, hindering the creation of robust surrogate models. This study introduces the DeepJEB dataset, generated through deep generative models and automated simulation pipelines, to address these limitations. DeepJEB offers comprehensive 3D geometries and corresponding structural analysis data. Key experiments validated its effectiveness, showing significant improvements in surrogate model performance. Models trained on DeepJEB achieved up to a 23% increase in the coefficient of determination and over a 70% reduction in mean absolute percentage error (MAPE) compared to those trained on traditional datasets. These results underscore the superior generalization capabilities of DeepJEB. By supporting advanced modeling techniques, such as graph neural networks (GNNs) and convolutional neural networks (CNNs), DeepJEB enables more accurate predictions in structural performance. The DeepJEB dataset is publicly accessible online.
Repurposing as a Decommissioning Strategy for Complex Systems: A Systematic Review
Authors: Hewa Witharanage Shenal Dilanjaya , Otto Kevin , Li Wen , Holtta-Otto Katja 
Published: November 2024

Abstract
Managing the waste of decommissioned complex systems (e.g., aircraft and wind turbines) is a growing issue. In this review, we investigate repurposing as a potential solution. The objectives are to identify strategies that can enable repurposing and identify the research gaps hindering those strategies. We analyzed 104 journal articles published in the last decade. We identified four proactive strategies that can be applied before the decommissioning stage and three reactive strategies that can be applied after the decommissioning stage. The proactive strategies are local ecosystem-focused repurposing, modular design, efficient disassembly methods, and component-embedded design and health information. The reactive strategies are decision support methods for repurposable component selection, function and context-based repurposing opportunities, and business models for repurposing. Six research gaps were identified, hindering the strategies due to the lack of support methods for repurposing, strategy scope limitations, and repurposing opportunity limitations. We identified that two repurposing examples were most commonly studied (wind turbine blades and electric vehicle batteries). Addressing the research gaps through design could uncover new repurposing opportunities. The resulting opportunities could follow similar processes addressed under the two well-researched examples, enabling repurposing as an advantageous and sustainable decommissioning strategy for complex systems.
The Unsteady Shock–Boundary Layer Interaction in a Compressor Cascade—Part II: High-Fidelity Simulation
Authors: Klose Bjoern F. , Morsbach Christian , Bergmann Michael , Munoz Lopez Edwin J. , Hergt Alexander , Kügeler Edmund 
Published: November 2024

Abstract
In the second part of this three-paper series, high-fidelity simulations of the transonic cascade TEAMAero at the aerodynamic design point with Rein=1.35×106 and Main=1.21 are presented. A high-order discontinuous Galerkin spectral element method with finite-volume subcell shock capturing is employed to simulate the flow based on an implicit large eddy simulation (LES) scheme and advanced over several buffeting cycles to reliably capture the shock unsteadiness. A study on the spanwise domain size shows that the shock oscillation amplitude decreases with increasing span, although its frequency and mean location remain fixed through the simulations. By comparing high- and low-resolution LES results, it is further presented that deviations from under-resolution are mostly limited to the separated region past the shock, where the high-fidelity results match experimental results more closely. In addition to the LES, low-fidelity unsteady Reynolds-averaged Navier–Stokes is shown to capture the shock unsteadiness correctly, but at a reduced amplitude and fails to match the force distributions on the blade surface. Through examination of instantaneous flow features, space–time relations and spectral proper orthogonal decomposition, a basic analysis of the shock–boundary layer interaction is presented and indicates that velocity perturbations travel upstream through the subsonic boundary layer and periodically cause oblique shock waves, transporting the information from the boundary layer into the passage.
CRISPR spacers acquired from plasmids primarily target backbone genes, making them valuable for predicting potential hosts and host range
Authors: Androsiuk Lucy , Maane Sivan , Tal Shay 
Published: November 2024

ABSTRACT

In recent years, there has been a surge in metagenomic studies focused on identifying plasmids in environmental samples. Although these studies have unearthed numerous novel plasmids, enriching our understanding of their environmental roles, a significant gap remains: the scarcity of information regarding the bacterial hosts of these newly discovered plasmids. Furthermore, even when plasmids are identified within bacterial isolates, the reported host is typically limited to the original isolate, with no insights into alternative hosts or the plasmid’s potential host range. Given that plasmids depend on hosts for their existence, investigating plasmids without the knowledge of potential hosts offers only a partial perspective. This study introduces a method for identifying potential hosts and host ranges for plasmids through alignment with CRISPR spacers. To validate the method, we compared the PLSDB plasmids database with the CRISPR spacers database, yielding host predictions for 46% of the plasmids. When compared with reported hosts, our predictions achieved 84% concordance at the family level and 99% concordance at the phylum level. Moreover, the method frequently identified multiple potential hosts for a plasmid, thereby enabling predictions of alternative hosts and the host range. Notably, we found that CRISPR spacers predominantly target plasmid backbone genes while sparing functional genes, such as those linked to antibiotic resistance, aligning with our hypothesis that CRISPR spacers are acquired from plasmid-specific regions rather than insertion elements from diverse sources. Finally, we illustrate the network of connections among different bacterial taxa through plasmids, revealing potential pathways for horizontal gene transfer.

IMPORTANCE
Plasmids are notorious for their role in distributing antibiotic resistance genes, but they may also carry and distribute other environmentally important genes. Since plasmids are not free-living entities and rely on host bacteria for survival and propagation, predicting their hosts is essential. This study presents a method for predicting potential hosts for plasmids and offers insights into the potential paths for spreading functional genes between different bacteria. Understanding plasmid-host relationships is crucial for comprehending the ecological and clinical impact of plasmids and implications for various biological processes.
Growth promotion on maize and whole-genome sequence analysis of
Bacillus velezensis
D103
Authors: Zhang Yating , Zhang Ning , Bi Xinyue , Bi Tong , Baloch Faryal Babar , Miao Jianjia , Zeng Nan , Li Bingxue , An Yingfeng 
Published: November 2024

ABSTRACT

Root-associated microorganisms, particularly plant growth-promoting rhizobacteria (PGPR) from the
Bacillus
genus, play a crucial role in enhancing crop yield and health. In this study, a
Bacillus
strain was isolated from the rhizosphere soil of maize and identified as
Bacillus velezensis
D103. The primary objective of this research was to evaluate the potential of D103 as a PGPR. Laboratory tests demonstrated that D103 is capable of nitrogen fixation, inorganic phosphorus solubilization, potassium solubilization, and the synthesis of indole-3-acetic acid, ammonia, siderophores, amylase, protease, cellulase, β-1,3-glucanase, and 1-aminocyclopropane-1-carboxylate deaminase. Additionally, D103 exhibited swimming and swarming motility, biofilm formation, and an antagonistic activity against pathogenic fungi. Genome mining identified genes associated with growth promotion and biocontrol activities. In a hydroponics experiment, maize plants treated with a D103 suspension at a cell density of 10
3
CFU·mL
−1
resulted in the most pronounced showed significant growth stimulation, with shoot length and total root length increasing by 43% and 148%, respectively. These results support the potential of D103 as an effective PGPR for promoting maize crop growth.

IMPORTANCE

In this study, we assessed the capacity of D103 to promote plant growth and examined the effects of hydroponic experiments inoculated with this strain on the growth of maize seedlings. We sequenced and analyzed the complete genome of D103, identifying several genes and gene clusters associated with plant growth promotion and resistance to pathogenic fungi, thus revealing the plant growth-promoting mechanisms of this strain. The isolation and characterization of new strains with beneficial traits are essential for expanding microbial resources available for biofertilizer production. Collectively, these findings highlight the promising potential of
Bacillus velezensis
D103 as a biofertilizer for agricultural applications.
Revealing sRNA expression profiles of NDM-5-producing CRKP and explore the role of sRNA207 in NDM-5-producing CRKP resistance
Authors: Xie Chonghong , Bai Yibo , Li Yan , Cui Bing , Cheng Guixue , Liu Jianhua , liu Yong , Qin Xiaosong 
Published: November 2024

ABSTRACT

New Delhi metallo-beta-lactamase-5 (NDM-5)-producing carbapenem-resistant
Klebsiella pneumoniae
(CRKP) is characterized by high virulence, high morbidity, and mortality, and the detection rate in children has increased in recent years. Therefore, it is urgent to develop new therapeutic targets and strategies. Non-coding small RNA (sRNA)-mediated RNA-based therapies offer a new direction for the treatment of bacterial infections, especially resistant bacteria. This study first analyzed the transcriptional expression profiles of NDM-5-producing CRKP and Carbapenem-susceptible
Klebsiella pneumoniae
(CSKP) isolates from the clinic by RNA-seq. A total of 4,623 genes were obtained, of which 307 genes were differentially expressed in NDM-5-producing CRKP, and these differentially expressed genes are mainly related to metabolism. Then, by analyzing the length and secondary structure of genes that could not match the reference gene and non-redundant protein database, we obtained 268 sRNAs, of which 13 sRNAs were differentially expressed in NDM-5-producing CRKP. After the expression level of differentially expressed sRNA was verified by RT-PCR to be consistent with that of RNA-seq, we chose sRNA207 as our research target. By knockdown of sRNA207 and
smf-1
(the predicted target mRNA of sRNA207) in the strain, we found that increased expression of sRNA207 promoted biofilm formation by stabilizing expression of
smf
-1, which in turn affected the resistance of NDM-5-producing CRKP to carbapenems. This provides a new approach to treat CRKP infection.

IMPORTANCE

sRNAs form a regulatory network that regulates bacterial virulence, drug resistance, and other functions by targeting mRNAs. However, sRNA expression profile and function of NDM-5-producing carbapenem-resistant
Klebsiella pneumoniae
(CRKP) are still unknown. In this study, we analyzed the sRNA expression profiles of NDM-5-producing CRKP obtained from clinical by referring to the methods of previous articles. A total of 268 candidates sRNAs were obtained, of which 248 were newly discovered. More importantly, 13 sRNAs were differentially expressed in NDM-5-producing CRKP compared with CSKP. We knocked down sRNA207 in NDM-5-producing CRKP to validate its effect on
smf
-1, biofilm, and resistance of strains. We also confirmed the role of
smf
-1 in biofilm formation and drug resistance of NDM-5-producing CRKP by constructing
smf
-1-knockdown strain. The results suggest that
smf
-1 is the target gene of sRNA207. Increased expression of sRNA207 in NDM-5-producing CRKP stabilizes
smf
-1 expression, which in turn affects the resistance of the strains through biofilm formation.
Improved resolution of avian influenza virus using Oxford Nanopore R10 sequencing chemistry
Authors: Ratcliff Jeremy D. , Merritt Brian , Gooden Hannah , Siegers Jurre Y. , Srikanth Abhinaya , Yann Sokhoun , Kol Sonita , Sin Sarath , Tok Songha , Karlsson Erik A. , Thielen Peter M. 
Published: November 2024

ABSTRACT

Highly pathogenic avian influenza viruses continue to pose global risks to One Health, including agriculture, public, and animal health. Rapid and accurate genomic surveillance is critical for monitoring viral mutations, tracing transmission, and guiding interventions in near real-time. Oxford Nanopore sequencing holds promise for real-time influenza genotyping, but data quality from R9 chemistry has limited its adoption due to challenges resolving low-complexity regions such as the biologically critical hemagglutinin cleavage site, a homopolymer of basic amino acids that distinguish highly pathogenic strains. In this study, human and avian influenza isolates (
n
= 45) from Cambodia were sequenced using both R9.4.1 and R10.4.1 flow cells and chemistries to evaluate performance between approaches. Overall, R10.4.1 yielded increased data output with higher average quality compared to R9.4.1, producing improved consensus sequences using a reference-based bioinformatics approach. R10.4.1 had significantly lower minor population insertion and deletion frequencies, driven by improved performance in low sequence complexity regions prone to insertion and deletion errors, such as homopolymers. Within the hemagglutinin cleavage site, R10.4.1 resolved the correct motif in 90% of genomes compared to only 60% with R9.4.1. Further examination showed reduced frameshift mutations in consensus sequences generated with R10.4.1 that could result in incorrectly classified virulence with automated pipelines. Improved consensus genome quality from nanopore sequencing approaches, especially across biologically important low-complexity regions, is critical to reduce subjective hand-curation and will improve local and global genomic surveillance responses.

IMPORTANCE
This study demonstrates significant advancement in the field of influenza virus genomic surveillance by showcasing the superior accuracy and data quality of the Oxford Nanopore R10 sequencing chemistry compared to the older R9 chemistry. Improved resolution, including in the critical hemagglutinin multi-basic cleavage site, enables more reliable monitoring and tracking of viral mutations. This accelerates the ability to respond quickly to outbreaks, potentially improving impacts on public health, agriculture, and the economy by enabling more accurate and timely interventions.
Identification of atypical pediatric diabetes mellitus cases using electronic medical records
Authors: Astudillo Marcela F , Winter William E , Billings Liana K , Kreienkamp Raymond , Balasubramanyam Ashok , Redondo Maria J , Tosur Mustafa 
Published: November 2024

IntroductionThere are no established methods to identify children with atypical diabetes for further study. We aimed to develop strategies to systematically ascertain cases of atypical pediatric diabetes using electronic medical records (EMR).Research design and methodsWe tested two strategies in a large pediatric hospital in the USA. Strategy 1: we designed a questionnaire to rule out typical diabetes and applied it to the EMR of 100 youth with diabetes. Strategy 2: we built three electronic queries to generate reports of three atypical pediatric diabetes phenotypes: unknown type, type 2 diabetes (T2D) diagnosed <10 years old and autoantibody-negative type 1 diabetes (AbNegT1D).ResultsStrategy 1 identified six cases (6%) of atypical diabetes (mean diagnosis age=11±2.6 years, 16.6% men, 33% non-Hispanic white (NHW) and 66.6% Hispanic). Strategy 2: unknown diabetes type: n=68 (1%) out of 6676 patients with diabetes; mean diagnosis age=12.6±3.3 years, 32.8% men, 23.8% NHW, 47.6% Hispanic, 25.4% African American (AA), 3.2% other. T2D <10 years old: n=64 (6.6%) out of 1142 patients with T2D; mean diagnosis age=8.6±1.6 years, 20.3% men, 4.7% NHW, 65.6% Hispanic, 28.1% AA, 1.6% other. AbNegT1D: n=38 (5.6%) out of 680 patients with new onset T1D; mean diagnosis age=11.3±3.8 years; 57.9% men, 50% NHW, 19.4% Hispanic, 22.3% AA, 8.3% other.ConclusionsIn sum, we identified 1%–6.6% of atypical diabetes cases in a pediatric diabetes population with high racial and ethnic diversity using systematic review of the EMR. Better identification of these cases using unbiased approaches may advance precision diabetes.
Development of a nomogram for predicting pancreatic portal hypertension in patients with acute pancreatitis: a retrospective study
Authors: Zhang Yingjie , Su Qiaoyu , Li Yunling , Zhan Xianchen , Wang XiangPing , Zhang Linhui , Luo Hui , Kang Xiaoyu , Lv Yong , Liang Shuhui , Ren Gui , Pan Yanglin 
Published: November 2024

IntroductionPancreatic portal hypertension (PPH) is a rare complication of acute pancreatitis (AP) that can lead to severe gastrointestinal bleeding. The risk factors associated with PPH, as well as the overall prognosis, warrant further investigation. This study aims to develop and validate a nomogram to predict PPH in patients with AP.MethodsConsecutive patients with AP from 2015 to 2023 were retrospectively included in the study. Demographic data, clinical manifestations within the first week of AP onset, and initial contrast-enhanced CT findings were used to develop the predictive model. Univariate and multivariate Cox regression analyses were performed to identify risk factors for PPH. Based on the results of the multivariate analysis, a nomogram was developed. The patients were randomly divided into training and validation sets at a 7:3 ratio. The accuracy and discriminative power of the predictive model were assessed using the area under the curve (AUC) from the receiver operating characteristic curve and the calibration curve.ResultsOf the 1473 patients with AP, 107 (7.3%) developed PPH within 6 months (range: 2–22 months) during follow-up. Multivariate regression analysis showed that body mass index (BMI) (HR, 1.10; 95% CI 1.04 to 1.16; p=0.001), moderately severe grade (HR, 9.36; 95% CI 4.58 to 19.13; p<0.001), severe grade (HR, 12.95; 95% CI 6.22 to 26.94; p<0.001), diabetes (HR, 2.26; 95% CI 1.47 to 3.47; p<0.001), acute fluid accumulation (HR, 2.13; 95% CI 1.31 to 3.47; p=0.002), and necrosis (HR, 3.64; 95% CI 2.30 to 5.78; p<0.001) were independent risk factors for PPH. A nomogram for predicting PPH was developed, with the predictive curves showing an AUC of 0.859 at 6 months and 0.846 at 9 months. In the validation set, the AUC at both time points was 0.812.ConclusionIn summary, we identified BMI, moderately severe or severe AP, diabetes, acute fluid accumulation, and necrosis as risk factors for AP-related PPH. Using the largest cohort of patients with AP to date, we developed a highly accurate nomogram with strong discriminative ability for predicting PPH. Future studies with larger sample sizes are necessary to confirm our findings and conduct external validation.
Combining quality improvement and critical care training: Evaluating an ICU CPR training programme quality improvement initiative at the National Hospital in Tanzania
Authors: Strelzer Samantha , Julius Joseph , Anicet Niyo , Byabato Odillo , Chiwanga Faraja , Hassan Saria , Kayandabila Festo , Laizer Agness , Majuta Trustworthy , Murray Brittany , Said Tatu , Ndile Samson 
Published: November 2024

BackgroundThe United Republic of Tanzania has had a 41.4% mortality rate in the intensive care unit. In Tanzania, the Ministry of Health and Social Welfare has implemented quality improvement (QI), yet the Tanzanian health sector continues to face resource constraints, unsustainable projects and gaps in knowledge and skills, contributing to unacceptably high mortality rates for Tanzanian patients. This research aims to determine if a Critical Care Training Program incorporating QI concepts can improve technical competence and self-efficacy of providers in a critical care setting in Tanzania.MethodsA 2-day Critical Care Training Program was developed for providers. It included the following modules: vital signs directed therapy (VSDT), cardiopulmonary and brain resuscitation (CPBR), blood glucose monitoring, introduction to critical care concepts and the QI concept of change management. For analysis, data were collected from pretests and post-tests and reported in REDCap. Descriptive statistics and paired t-tests were performed (alpha=0.05).ResultsA total of 77 nurses and three providers attended the training. The overall score changes among participants for CPBR and VSDT were significant (p<0.001). Six out of 10 questions in CPBR demonstrated significant improved change (p<0.001). All questions in the VSDT training showed significant improvement (p<0.001). Based on hospital guidelines, 63 (95.5%) passed the CPBR evaluation and 62 (95.2%) passed VSDT.ConclusionA pre/post analysis demonstrated improvement in knowledge, skills and increased confidence towards emergencies. This study suggests a Critical Care Training Program significantly improves the knowledge among providers and that QI impacts culture of change. This research exemplifies a systematic approach to strengthening capacity of critical care delivery in limited resource settings, with implications for further innovation in other low- and middle-income countries.
The Local Metric Dimension and Distance-Edge-Monitoring Number of Graph
Authors: Yang Chenxu , Ji Zhen , Li Wen , Liang Yan 
Published: November 2024

Let [Formula: see text] be a graph and [Formula: see text]. The vertex [Formula: see text] is said to resolve a pair [Formula: see text] and [Formula: see text] if and only if [Formula: see text]. A set [Formula: see text] is defined as a resolving set of [Formula: see text] if for all [Formula: see text], the pair [Formula: see text] is resolved by some [Formula: see text]. The minimum cardinality of a resolve set of [Formula: see text] is defined as [Formula: see text]. A set [Formula: see text] is a local resolve set of [Formula: see text] if for all [Formula: see text] such that [Formula: see text], the pair [Formula: see text] is resolved by some [Formula: see text]. The minimum cardinality of a local resolve set of [Formula: see text] is defined as [Formula: see text]. An edge [Formula: see text] is said to be monitored by [Formula: see text] if [Formula: see text] or [Formula: see text]. A set [Formula: see text] is a distance-edge-monitoring (DEM) set if for all [Formula: see text], [Formula: see text] is monitored by some [Formula: see text]. The minimum cardinality of a [Formula: see text] set of [Formula: see text] is defined as [Formula: see text]. In this paper, we obtained that [Formula: see text] for all non trivial graphs with order [Formula: see text], and the exact value of [Formula: see text] and [Formula: see text] for [Formula: see text], [Formula: see text]. Also, we obtained that if [Formula: see text] then [Formula: see text]. With respect to the relation between the defined graph invariants, it was proved a bound for [Formula: see text] for [Formula: see text] and the exact values of [Formula: see text] for [Formula: see text], where [Formula: see text] (resp, [Formula: see text])is the maximum value of [Formula: see text] (resp, [Formula: see text]) over all graphs [Formula: see text] with order [Formula: see text]. Finally, we proved that for [Formula: see text], there exists a graph with order [Formula: see text] such that [Formula: see text] and [Formula: see text].