bluuebunny/crossref_metadata_2025_split huggingface dataset:
Two-loop improved predictions for $$\mathbf {M_W}$$ and $$\mathbf {sin^2\theta _{eff}}$$ in Two-Higgs-Doublet models
Authors: Hessenberger Stephan , Hollik Wolfgang 
Published: October 2022

AbstractWe present the currently most precise predictions for the W-boson mass and the leptonic effective mixing angle in the aligned Two-Higgs-Doublet Model. The evaluation includes the full one-loop result, all known higher-order corrections of the Standard Model, and the non-standard two-loop contributions that increase with mass splittings between charged and neutral THDM Higgs bosons. They depend on $$\tan \beta $$

tan
β

and the soft $$Z_2$$

Z
2

-symmetry breaking parameter $$m_{12}^2$$

m

12

2

of the scalar potential, in addition to the non-standard boson masses. Whenever the one-loop corrections become large, the two-loop contributions yield substantial modifications of the predictions, which is of particular importance for the W mass where large mass shifts are required to reach the recently published final result of the CDF collaboration. Numerical results are shown for the dependence on the various non-standard parameters and in comparison with experimental data.
Resolving muon g-2 anomaly with partial compositeness
Authors: Xu Shuai , Zheng Sibo 
Published: October 2022

AbstractWe consider the scenario of composite Higgs with partial compositeness to address the muon g-2 anomaly. We show that this anomaly is resolved by one-loop correction due to composite muon partners with mass scale of order TeVs and large Yukawa coupling to composite Higgs, which is different from interpretations of vectorlike lepton models. We present parameter space by imposing indirect constraints from precise measurements on Higgs, Z and oblique electroweak parameters. We analyze direct constraints in light of both Drell–Yan and Higgs-associated productions of the composite muon partners at high-luminosity LHC. It turns out that the parameter regions with the lighter composite muon mass below $$\sim 325$$

∼
325

GeV can be excluded at 2$$\sigma $$
σ
order by the Drell–Yan processes.
Numerical study of the speed’s response of the various intelligent models using the tansig, logsig and purelin activation functions in different layers of artificial neural network
Authors: Laabid Zineb , Moumen Aziz , Mansouri Khalifa , Siadat Ali 
Published: October 2022

<p><span lang="EN-US">Today's world is no longer that of yesterday, the pace with which we live and also the speed is enormous and rapid, that overnight we discover the appearance of new technologies and solutions in all the fields, in particular, that of scientific research. Artificial intelligence plays the main role. Predicting the behavior of new materials using artificial neural networks has become a frequently adopted solution by researchers today. The performance of neural networks depends mainly on the activation functions used. This work was designed to mainly study the impact of these functions on the response speed of an artificial neural network in general, and particularly on the model we are working on to predict the thermomechanical behavior of innovative materials. By using TANSIG, PURELIN and LOGSIG in a feed forward back propagation training by Levenberg-Marquardt algorithm, we were able to generate 9 models. For each of these models, we were interested in analyzing the speed’s response of the network and studying its regression. Thus, this work was able to show us that choosing the right neuron activation function from one layer to another can clearly influence the performance of the results. Depending on the problem studied, the desired objective and the chosen architecture, the activation function can radically change the result and provide us with the expected efficiency. </span></p>
Artificial neural network for cervical abnormalities detection on computed tomography images
Authors: Ratnasari Putri Erlinda , Zarkasi Ahmad , Prajitno Prawito , Soeharso Soejoko Djarwani 
Published: October 2022

<span lang="EN-US">Cervical cancer is the second deadliest after breast cancer in Indonesia. Sundry diagnostic imaging modalities had been used to decide the location and severity of cervical cancer, one among those is computed tomography (CT) Scan. This study handles a CT image dataset consisting of two categories, abnormal cervical images of cervical cancer patients and normal cervix images of patients with other diseases. It focuses on the ability of segmentation and classification programs to localize cervical cancer areas and classify images into normal and abnormal categories based on the features contained in them. We conferred a novel methodology for the contour detection round the cervical organ classified with artificial neural network (ANN) which was employed to categorize the image data. The segmentation algorithm used was a region-based snake model. The texture features of the cervical image area were arranged in the form of gray level co-occurrence matrix (GLCM). Support vector machine (SVM) had been added to determine which algorithm was better for comparison. Experimental results show that ANN model has better receiver operating characteristic (ROC) parameter values than SVM model’s and existing approach’s regarding 96.2% of sensitivity, 95.32% of specificity, and 95.75% of accuracy. </span>
Comparative study of optimization methods for optimal coordination of directional overcurrent relays with distributed generators
Authors: El Idrissi Zineb , Haidi Touria , Elmariami Faissal , Belfqih Abdelaziz 
Published: October 2022

<span lang="EN-US">Due to the growing penetration of distributed generators (DGs), that are based on renewable energy, into the distribution network, it is necessary to address the coordination of directional overcurrent relays (DOCR) in the presence of these generators. This problem has been solved by many metaheuristic optimization techniques to obtain the optimal relay parameters and to have an optimal coordination of the protection relays by considering the coordination constraints. In this article, a comparative study of the optimization techniques proposed in the literature addresses the optimal coordination problem using digital DOCRs with standard properties according to IEC60-255. For this purpose, the three most efficient and robust optimization techniques, which are particle swarm optimization (PSO), genetic algorithm (GA) and differential evolution (DE), are considered. Simulations were performed using MATLAB R2021a by applying the optimization methods to an interconnected 9-bus and 15-bus power distribution systems. The obtained simulation results show that, in case of distributed generation, the best optimization method to solve the relay protection coordination problem is the differential evolution DE. </span>
Hybrid gated recurrent unit bidirectional-long short-term memory model to improve cryptocurrency prediction accuracy
Authors: Ferdiansyah Ferdiansyah , Othman Siti Hajar , Md Radzi Raja Zahilah , Stiawan Deris , Sutikno Tole 
Published: October 2022

<span lang="EN-US">Cryptocurrency is a virtual or digital currency used in financial systems that utilizes blockchain technology and cryptographic functions to gain transparency, decentralization, and conservation. Cryptocurrency prices have a high level of fluctuation; thus, tools are needed to monitor and predict them. RNN is a deep learning model that is capable of strongly predicting data time series. Some types of Recurrent Nureal Network layers, such as Long Short Term Memory, have been used in previous studies to prediction common used currency. In this study, we used the Gate Recurrent Unit and Bidirectional</span><span lang="EN-US">–</span><span lang="EN-US">LSTM hybrid model to predict cryptocurrency prices to improve the accuracy of previously proposed prediction LSTM Model to predict the Bitcoin, Using four cryptocurrencies (Bitcoin, Ehtereum, Ripple, and Binance), we obtained very good results with RMSE after normalization the results get closer to 0 and with MAPE values all below &lt;10%.</span>
Renal thrombotic microangiopathy and nephrotic proteinuria induced by intravitreal injection of aflibercept for diabetic macular edema
Authors: Kikuchi Yawara , Odashima Yoshimi , Yoshikawa Kazuhiro , Oda Tomoyasu , Tanaka Fumitaka , Oikawa Hiroki , Ishigaki Yasushi , Asahi Koichi 
Published: October 2022

Abstract
Background
Vascular endothelial growth factor inhibitors (VEGFIs) are used to treat malignant neoplasms and ocular diseases by inhibiting angiogenesis. Systemic use of VEGFIs has various side effects, including hypertension, proteinuria, and thrombotic microangiopathy, but adverse events due to intravitreal injection of VEGFIs have not been fully clarified. Although age-related macular degeneration was initially the most common target of intravitreal injection of VEGFIs, it has also been applied sporadically for diabetic macular edema in recent years. Proteinuria following intravitreal injection of VEGFIs would be reversible. In patients with diabetes mellitus (DM), however, it would be difficult to determine whether kidney damage arises from the clinical course of DM or from intravitreal injection of VEGFIs for diabetic macular edema.

Case presentation
A 55-year-old woman with a 20-year history of type 2 DM began intravitreal injection of VEGFI (aflibercept, 2 mg every 4 weeks) for treatment of diabetic macular edema 2 years previously. She presented with leg edema, hypertension, and nephrotic-range proteinuria 14 months after the first injection. Histological examination of renal biopsy specimens revealed diabetic nephropathy with renal thrombotic microangiopathy probably associated with intravitreal injection of VEGFI. The patient’s nephrotic syndrome completely improved at 6 months after simply discontinuing aflibercept.

Conclusions
This is a precious report of pathologically investigated renal thrombotic microangiopathy leading to nephrotic syndrome due to intravitreal injection of aflibercept for diabetic macular edema in a patient with type 2 DM. Renal function and proteinuria should be monitored in diabetic patients who receive intravitreal injection of a VEGFI. If kidney damage develops independent of the clinical course of DM during intravitreal injection of a VEGFI, renal biopsy should be performed and intravitreal VEGFI injection discontinued.
Ownership of individual-level health data, data sharing, and data governance
Authors: Piasecki Jan , Cheah Phaik Yeong 
Published: October 2022

Abstract
Background
The ownership status of individual-level health data affects the manner in which it is used. In this paper we analyze two competing models of the ownership status of the data discussed in the literature recently: private ownership and public ownership.

Main body
In this paper we describe the limitations of these two models of data ownership with respect to individual-level health data, in particular in terms of ethical principles of justice and autonomy, risk mitigation, as well as technological, economic, and conceptual issues. We argue that undifferentiated application of neither private ownership nor public ownership will allow us to resolve all the problems associated with effective, equitable, and ethical use of data. We suggest that, instead of focusing on data ownership, we should focus on the institutional and procedural aspects of data governance, such as using Data Access Committees (DACs) or equivalent managed access processes, which can balance the elements of these two ownership frameworks.

Conclusion
Undifferentiated application of the ownership concept (private or public) is not helpful in resolving problems associated with sharing individual-level health data. DACs or equivalent managed access processes should be an integral part of data governance. They can approve or disapprove data access requests after considering the potential benefits and harms to data subjects, their communities, primary researchers, and the wider society.
One novel ACOT7–NPHP4 fusion gene identified in one patient with acute lymphoblastic leukemia: a case report
Authors: Zong Xin , Kang Zhijie , Huang Dan , Zhang Xuehong , Gao Yuan , Wang Haina , Li Weiling , Yan Jinsong 
Published: October 2022

Abstract
Background
Acute lymphoblastic leukemia (ALL) is a type of heterogeneous hematopoietic malignancy that accounts for approximately 20% of adult ALL. Although ALL complete remission (CR) rate has increased to 85–90% after induction chemotherapy, 40–50% of patients eventually relapsed. Therefore, it is necessary to improve the outcomes of ALL via accurate diagnosis and individualized treatments, which benefits in part from molecular biomarkers. Here, we identified a new fusion gene, Acyl-CoA Thioesterase 7–Nephrocystin 4 (ACOT7–NPHP4), in a 34-year-old patient with ALL. The fusion gene contributed to chemoresistance to doxorubicin and acted as a new molecular marker.

Case presentation
A 34-year-old male patient was diagnosed with ALL (common B cell) based on clinical manifestations and laboratory results. Although the patient received two cycles of the hyper-CVAD-L regimen as chemotherapy, the induction treatment failed. Because of the refusal of further treatments, the patient died of rapid progression of ALL one month later. Finally, a new fusion transcript, ACOT7–NPHP4, was detected in the patient’s lymphoblastic leukemia cells via RNA sequencing.

Conclusion
This is the first report of a patient with ALL carrying an ACOT7–NPHP4 fusion gene. These findings may help understand the impact of ACOT7–NPHP4 in clinical molecular monitoring and drug resistance to doxorubicin; furthermore, its leukemogenesis will be essential to explore in future.
Integrated metabolomic and transcriptomic analyses of the synergistic effect of polymyxin–rifampicin combination against Pseudomonas aeruginosa
Authors: Mahamad Maifiah Mohd Hafidz , Zhu Yan , Tsuji Brian T. , Creek Darren J. , Velkov Tony , Li Jian 
Published: October 2022

Abstract
Background
Understanding the mechanism of antimicrobial action is critical for improving antibiotic therapy. For the first time, we integrated correlative metabolomics and transcriptomics of Pseudomonas aeruginosa to elucidate the mechanism of synergistic killing of polymyxin–rifampicin combination.

Methods
Liquid chromatography-mass spectrometry and RNA-seq analyses were conducted to identify the significant changes in the metabolome and transcriptome of P. aeruginosa PAO1 after exposure to polymyxin B (1 mg/L) and rifampicin (2 mg/L) alone, or in combination over 24 h. A genome-scale metabolic network was employed for integrative analysis.

Results
In the first 4-h treatment, polymyxin B monotherapy induced significant lipid perturbations, predominantly to fatty acids and glycerophospholipids, indicating a substantial disorganization of the bacterial outer membrane. Expression of ParRS, a two-component regulatory system involved in polymyxin resistance, was increased by polymyxin B alone. Rifampicin alone caused marginal metabolic perturbations but significantly affected gene expression at 24 h. The combination decreased the gene expression of quorum sensing regulated virulence factors at 1 h (e.g. key genes involved in phenazine biosynthesis, secretion system and biofilm formation); and increased the expression of peptidoglycan biosynthesis genes at 4 h. Notably, the combination caused substantial accumulation of nucleotides and amino acids that last at least 4 h, indicating that bacterial cells were in a state of metabolic arrest.

Conclusion
This study underscores the substantial potential of integrative systems pharmacology to determine mechanisms of synergistic bacterial killing by antibiotic combinations, which will help optimize their use in patients.

Graphical Abstract
Research protocol for impact assessment of a project to scale up food policies in the Pacific
Authors: Patay Dori , Trieu Kathy , McKenzie Briar , Ramanathan Shanthi , Hure Alexis , Bell Colin , Thow Anne-Marie , Allender Steven , Reeve Erica , Palu Aliyah , Woodward Mark , Waqa Gade , Webster Jacqui 
Published: October 2022

AbstractBackgroundOne of the challenges for countries implementing food policy measures has been the difficulty in demonstrating impact and retaining stakeholder support. Consequently, research funded to help countries overcome these challenges should assess impact and translation into practice, particularly in low-resource settings. However, there are still few attempts to prospectively, and comprehensively, assess research impact. This protocol describes a study co-created with project implementers, collaborative investigators and key stakeholders to optimize and monitor the impact of a research project on scaling up food policies in Fiji.MethodsTo develop this protocol, our team of researchers prospectively applied the Framework to Assess the Impact from Translational health research (FAIT). Activities included (i) developing a logic model to map the pathway to impact and establish domains of benefit; (ii) identifying process and impact indicators for each of these domains; (iii) identifying relevant data for impact indicators and a cost–consequence analysis; and (iv) establishing a process for collecting quantitative and qualitative data to measure progress. Impact assessment data will be collected between September 2022 and December 2024, through reports, routine monitoring activities, group discussions and semi-structured interviews with key implementers and stakeholders. The prospective application of the protocol, and interim and final research impact assessments of each project stream and the project as a whole, will optimize and enable robust measurement of research impact.DiscussionBy applying this protocol, we aim to increase understanding of pathways to impact and processes that need to be put in place to achieve this. This impact evaluation will inform future projects with a similar scope and will identify transferable and/or translatable lessons for other Pacific Island states and low- and middle-income countries.
Combination of albumin-to-globulin ratio and plasma fibrinogen is a sensitive tool for preoperative screening of infected nonunion in patients undergoing reoperation after open reduction and internal fixation: a retrospective study
Authors: Wang Zhen , Mao Haijun , Xu Guangyue 
Published: October 2022

Abstract
Background
Accurate preoperative diagnosis of infected nonunion remains a challenge. Here, we evaluated the diagnostic potential of novel biomarkers for infected nonunion.

Methods
A cohort of 275 patients who underwent surgery for suspected septic nonunion after open reduction and internal fixation were enrolled. Preoperatively analyzed clinical parameters included white blood cell (WBC) count, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), albumin, globulin, albumin-to-globulin ratio (AGR), plasma D-dimer, plasma fibrinogen, platelet count (PC), monocyte-lymphocyte ratio (MLR), neutrophil–lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR). Receiver operating characteristic (ROC) curves, sensitivity, and specificity were utilized to compare the diagnostic potential of those biomarkers.

Results
The WBC count and levels of CRP, ESR, NLR, MLR, PLR, PC, plasma D-dimer, plasma fibrinogen, and globulin in infected nonunion patients were significantly higher (p < 0.05) than those in aseptic patients. The albumin and AGR levels of the infected nonunion group were significantly lower (p < 0.05) than the aseptic group. The ROC curve analysis showed that the diagnostic accuracy of AGR and plasma fibrinogen was good. The combination of AGR with plasma fibrinogen had the highest area under the curve (AUC) (0.916). The sensitivity and specificity were 70.27% and 91.04% for AGR, and 67.57% and 84.08% for plasma fibrinogen, respectively. The combination of AGR with plasma fibrinogen showed a sensitivity of 86.49% and specificity of 92.54%. In patients with comorbidities, the diagnostic accuracy of the combination of AGR with plasma fibrinogen was also good.

Conclusions
AGR and plasma fibrinogen are promising biomarkers to improve the diagnosis of infected nonunion. The combination of AGR with plasma fibrinogen is a sensitive tool for screening infected nonunion.
Postural habits and lifestyle factors associated with adolescent idiopathic scoliosis (AIS) in China: results from a big case–control study
Authors: Yang Jingfan , Huang Sizhe , Cheng Mengyuan , Tan Weiqing , Yang Junlin 
Published: October 2022

Abstract
Background
Adolescent idiopathic scoliosis (AIS) is the most prevalent type of scoliosis affecting children between the ages of 10–16 years. However, risk factors for AIS, particularly the modifiable ones, are still largely unknown. This study aims to investigate the associations of lifestyle and social environment factors with AIS in Chinese schoolchildren.

Methods
This is a matched case–control study based on survey data collected from school-based scoliosis screening program. We used conditional logistic regression models to describe the relative risk of AIS incidence for each variable in the analyses. To examine the independent effect of each factor on developing AIS, a multivariate conditional logistic regression was conducted and odds ratios (ORs) were adjusted for age and other significant variables.

Results
Overall, 2538 participants from 49 schools were included in this study, comprising 1269 AIS cases and 1269 controls. Mean age of the study population was 13.4 years ± 1.06 (range 10–18). One thousand five hundred and fifty (61.1%) of the study subjects were girls. After adjusting for other significant factors, inappropriate desk heights, either too low (OR = 1.40, 95% CI 1.04–1.90) or too high (OR = 1.61, 95% CI 1.09–2.38), standing with anterior pelvic tilt (OR = 2.73, 95% CI 1.41–5.28), and sleeping on the right side (OR = 1.38, 95% CI 1.00–1.91), remained associated with elevated AIS risks. In contrast, sitting normally and classroom sitting positions change regularly were associated with lower odds of AIS. The adjusted ORs were 0.69 (95% CI 0.50–0.96) for sitting normally, and 0.72 (95% CI 0.53–0.98) for sitting positions change.

Conclusions
This is the first study to address the associations between desk heights and AIS and showed inappropriate desk heights were related to increased AIS risks. To protect school children from developing AIS, stakeholders are advised to consider introducing height-adjustable desks in the class, changing students’ sitting positions in the classroom on a regular basis, and implementing educational programs to help students maintain correct sitting postures.
Big Data in cardiac surgery: real world and perspectives
Authors: Montisci Andrea , Palmieri Vittorio , Vietri Maria Teresa , Sala Silvia , Maiello Ciro , Donatelli Francesco , Napoli Claudio 
Published: October 2022

AbstractBig Data, and the derived analysis techniques, such as artificial intelligence and machine learning, have been considered a revolution in the modern practice of medicine. Big Data comes from multiple sources, encompassing electronic health records, clinical studies, imaging data, registries, administrative databases, patient-reported outcomes and OMICS profiles. The main objective of such analyses is to unveil hidden associations and patterns. In cardiac surgery, the main targets for the use of Big Data are the construction of predictive models to recognize patterns or associations better representing the individual risk or prognosis compared to classical surgical risk scores. The results of these studies contributed to kindle the interest for personalized medicine and contributed to recognize the limitations of randomized controlled trials in representing the real world. However, the main sources of evidence for guidelines and recommendations remain RCTs and meta-analysis. The extent of the revolution of Big Data and new analytical models in cardiac surgery is yet to be determined.