bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-objective Optimization of Conformal Cooling Channel Design in Injection Molds Using Taguchi Grey Relational analysis
Authors: Simiyu Laura Wambani , Mutua James M. , Muiruri Patrick I. , Ikua Bernard W. , Gacharu Simon N. 
Published: March 2023

Abstract
The widespread use and demand for plastic products worldwide have caused manufacturers to covet high productivity and product quality. Most plastic products are produced using the injection molding technique. This technique is characterized by long cooling times, which affect the production cycle and product quality. Literature reveals that cooling in injection molding can be significantly affected by the design of the cooling channels. This study is, therefore focused on design optimization of circular cross-section conformal cooling channels. The Taguchi design of experiments approach was adopted in this study. The key variables of conformal cooling channels that were studied involved diameters, depths, and pitches. Solidworks® was used for 3D design, and for numerical simulation to determine the cooling time, volumetric shrinkage, warpage, and sink marks. Multi-response optimization was then conducted using the Taguchi-Grey Relational Analysis technique. Results show that the optimal cooling channel design has a minimum; diameter of 8 mm, depth of 12 mm and pitch of 16 mm. Additionally, Analysis of Variance (ANOVA) revealed that the diameter is the significant cooling channel design parameter that contributes to all the responses concurrently with the largest percentage of 80.26%. Comparing the conformal with straight cooling channel designs, superior performance was noted for the former against the later with optimal design recording an improvement of 29.35%, 5.99%, 19.77%, and 38.85% in the cooling time, volumetric shrinkage, warpage, and depth of sink marks respectively.
ANyEye: A nystagmus extraction system optimized in video-nystagmography using artificial intelligence for diagnostic assistance of benign paroxysmal positional vertigo
Authors: Lee Yerin , Lee Sena , Han Junghun , Seo Young Joon , Yang Sejung 
Published: March 2023

Abstract
Benign paroxysmal positional vertigo (BPPV), the most common vestibular disorder, is diagnosed by an examiner changing the posture of the examinee and inducing nystagmus. Among the diagnostic methods used to observe nystagmus, video-nystagmography has been widely used recently because it is non-invasive. A specialist with professional knowledge and training in vertigo diagnosis is needed to diagnose BPPV accurately, but the ratio of vertigo patients to specialists is too high, thus necessitating the need for automated diagnosis of BPPV. In this paper, a convolutional neural network-based nystagmus extraction system, ANyEye, optimized for video-nystagmography data is proposed in the first study on automating BPPV diagnosis. A pupil was segmented to track the exact pupil trajectory from real-world data obtained during field inspection. A deep convolutional neural network model was trained with the new video-nystagmography dataset for the pupil segmentation task, and a compensation algorithm was designed to correct pupil position. In addition, a slippage detection algorithm based on moving averages was designed to eliminate the motion artifacts induced by goggle slippage. ANyEye outperformed other eye-tracking methods including learning and non-learning based algorithms with five-pixel error detection rate of 91.26%.
FGSI: Distant Supervision for Relation Extraction method based on Fine-Grained Semantic Information
Authors: Sun Chenghong , Ji Weidong , Zhou Guohui , Guo Hui , Yin Zengxiang , Yue Yuqi 
Published: March 2023

Abstract
Relation extraction is an important part of constructing a knowledge graph, whose main purpose is to extract the semantic relationships between marked entity pairs in a sentence. It plays a crucial role in understanding the semantics of a sentence and constructing a knowledge graph. Remote supervision relation extraction methods alleviate the pressure of manually constructing datasets by automatically aligning knowledge bases with natural language texts to generate labeled data. However, the labeled data obtained by remote supervision often contains a large amount of noisy data, which can significantly affect the training of relation extraction models. This paper proposes the hypothesis that key semantic information within a sentence plays a critical role in entity relation extraction tasks and addresses the issue of noise in remote supervision relation extraction tasks. Based on this hypothesis, the paper splits a sentence into three segments according to the position of entities and uses intra-sentence attention mechanism to identify fine-grained semantic features within the sentence and reduce the interference of irrelevant noise information. The paper then uses inter-package attention mechanism to increase the weight of correctly labeled sentences and discard noisy sentences, thereby minimizing the impact of noise on the relation extraction model and fully utilizing existing positive semantic information. Experimental results show that the proposed relation extraction model improves precision-recall curve and P@N values compared to existing methods, demonstrating the effectiveness of the model.
Co-encapsulation of paprika and cinnamon oleoresins by spray drying in a mayonnaise model: bioaccessibility of carotenoids using in vitro digestion
Authors: Ferraz Mariana Costa , Júnior Fernando Divino Oliveira , Barroso Lívia Alves , Furtado Guilherme de Figueiredo , Cunha Rosiane Lopes , Hubinger Miriam Dupas 
Published: March 2023

Abstract
In view of all the technological and functional properties that paprika and cinnamon oleoresins possess, the digestibility of spray-dried microparticles co-encapsulating these materials was investigated using simulated gastrointestinal conditions. Most active compounds are hydrophobic and well absorbed in the intestine in the presence of digestible lipids. For this reason, using mayonnaise as a food matrix can promote the protection and diffusion of carotenoids. Model spice mayonnaise with 0.5 wt. % paprika content and cinnamon microparticles was produced from a commercial mayonnaise (used as a standard in this study). Droplet size distribution, optical and fluorescence microscopy of the microparticles, model spice mayonnaise, and standard mayonnaise are determined before and after gastric and intestinal digestion under in vitro conditions. After digestion, all samples presented an extensive aggregation and coalescence of droplets. Highest release rate of free fatty acids (FFAs) was observed for dispersed particles (37.40 ± 2.58%) and for model spice mayonnaise (17.76 ± 0.07%), respectively. Digesta containing carotenoids from paprika and cinnamon oleoresin in the form of mixed micelles were filtered to simulate bioavailability for passage through the pores in the mucus layer of the intestine. Bioaccessibility and simulated bioavailability were higher when using mayonnaise as a delivery system (22.7% and 15.4%, respectively), proving particles in an aqueous medium possess low solubility and suggesting that the high lipid composition of mayonnaise facilitates delivery of active compounds from carotenoids present in paprika and cinnamon oleoresin after digestion.
Cylindroma of the breast with CYLD gene mutation: a case report and review of the literature
Authors: Escher-Michlig Vanessa , Vlajnic Tatjana , Roma Luca , Marinucci Mattia , Piscuoglio Salvatore , Matter Matthias , Haug Martin , Weber Walter P. , Muenst Simone 
Published: March 2023

Abstract
Background
Cylindroma of the breast is a rare benign neoplasm. Since its first description in 2001, 18 cases have been reported in the literature.
Methods and Results
We report another case of this rare tumor in a 60-year-old woman with demonstration of the underlying molecular alteration. Histologically, the tumor showed the typical “jigsaw” pattern of a dual population of cells with a triple-negative phenotype. The pathognomonic mutation of the CYLD gene mutation was detected by whole exome sequencing. Cylindromas show morphological overlap with the solid-basaloid variant of adenoid cystic carcinoma, which renders this differential diagnosis difficult. However, distinction of these two lesions is of outmost importance, since cylindromas, in contrast to solid-basaloid variant of adenoid cystic carcinoma, behave in an entirely benign fashion.
Conclusions
Careful evaluation of morphological features such as mitotic figures and cellular atypia is crucial in the diagnostic work-up of triple-negative breast lesions. It is important to keep cylindroma in mind as a pitfall and possible differential diagnosis for the solid-basaloid variant of adenoid cystic carcinoma. Molecular detection of CYLD gene mutation is helpful in cases with ambiguous histology. With this case report, we aim to contribute to a better understanding of mammary cylindroma and facilitate the diagnosis of this rare entity.
Colorectal Cancer Health and Care Quality Indicators in a Federated Setting using the Personal Health Train
Authors: Choudhury Ananya , Janssen Esther , Bongers Bart C. , Meeteren Nico L.U. van , Dekker Andre , Soest Johan van 
Published: March 2023

Abstract

Objective
Hospitals and healthcare providers should assess and compare their quality of care given to patients and based on this improve the care. In the Netherlands, hospitals provide data to national quality registries, which in return provide annual quality indicators. However, this process is time-consuming, resource intensive and risks patient privacy and confidentiality. In this paper, we presented a multicentric ‘Proof of Principle’ study for federated calculation of quality indicators in patients with colorectal cancer.
Materials and Methods
Two quality indicators are calculated in an efficient and privacy persevering federated manner, by i) applying the Findable Accessible Interoperable and Reusable (FAIR) data principles and ii) using the Personal Health Train (PHT) infrastructure. Instead of sharing data to a centralized registry, PHT enables analysis by sending algorithms and sharing only insights from the data.
Results
ETL process extracted data from the Electronic Health Record systems of the hospitals, converted them to FAIR data and hosted in RDF endpoints within each hospital. Finally, quality indicators from each center are calculated using PHT and the mean result along with the individual results plotted.
Discussion and Conclusion
PHT and FAIR data principles can efficiently calculate quality indicators in a privacy-preserving federated approach and the work can be scaled up both nationally and internationally. Despite this, application of the methodology was largely hampered by ELSI issues. However, the lessons learned from this study can provide other hospitals and researchers to adapt to the process easily and take effective measures in building quality of care infrastructures.
Venomous gland transcriptome and venom proteomic analysis of the scorpion Androctonus amoreuxi reveal new peptides with anti-SARS- CoV-2 activity
Authors: Ghazal Ahmad , Clarke David , Abdel-Rahman Mohamed A. , Ribeiro Antonio , Hijazi Karolin , Collie-Duguid Elaina , Pattinson Craig , Burgoyne Kate , Muhammad Taj , Alfadhel Sanad , Heidari Zeynab , Samir Reham , Gerges Mariam M. , Colamarino Rosa A. , Sim Kyle S. , Houssen Wael E. 
Published: March 2023

Abstract
The recent COVID-19 pandemic shows the critical need for novel broad spectrum antiviral agents. Scorpion venoms are known to contain highly constrained peptides, several of which have demonstrated strong antiviral activity against a range of viruses. We have generated the first annotated reference transcriptome for the Androctonus amoreuxi venom gland and used transcriptome mining, circular dichroism and mass spectrometric analysis to characterize fifteen new venom peptides. Some of these peptides were tested for their ability to bind to the SARS-CoV-2 spike protein and to inhibit the spike RBD - hACE2 interaction that precedes virus entry into the cell using a surface plasmon resonance-based assay. Seven peptides showed dose-dependent inhibitory effects. The most active peptide was synthesized using solid phase peptide synthesis and tested for its antiviral activity against SARS-CoV-2 (Lineage B.1.1.7). On exposure of replication-competent SARS-CoV-2 to the synthetic peptide, we observed a two log10 PFU/mL reduction at sub-micromolar concentrations of the peptide compared to virus exposed to medium alone. Our results show that scorpion venom peptides could inhibit the SARS-CoV-2 spike RBD - hACE2 interaction, exhibit anti-SARS-CoV-2 activity through other unexplored modes of actions and represent excellent scaffolds for design of novel anti-SARS-CoV-2 constrained peptides.
Value of dual-energy spectral computed tomography for multiparametric quantitative assessment of pancreatic fat content
Authors: Cao Wei , Wei Wei , Li Meng-ru , Cheng Peng , Hu Guo-qing 
Published: March 2023

Abstract
Background
Dual Energy spectral computed tomography (DECT) provides a variety of image data sets that can be used to improve the assessment of fat content.
Purpose
To investigate the clinical value of DECT in the quantitative assessment of pancreatic fat content in patients with type 2 diabetes mellitus (T2DM).
Material and Methods
The DECT data of 123 patients were retrospectively analyzed, including a case group of 82 patients with T2DM and a control group of 41 patients with normal physical examination findings. The CT value, fat (water) concentration and slope of the spectral curve were measured in both groups. The T2DM group was divided into the T2DM obese subgroup (body mass index [BMI] of ≥ 25 kg/m2) and T2DM non-obese subgroup (BMI of < 25 kg/m2) according to the Asia-Pacific classification criteria for BMI. The differences between the T2DM non-obese subgroup and the control group and between the T2DM obese subgroup and the T2DM non-obese subgroup were compared, and the correlation of the BMI with the fat (water) concentration, CT value, and slope was analyzed in all patients with T2DM.
Results
The CT value was significantly lower and the fat (water) concentration and slope were significantly higher in the T2DM obese subgroup than in the control group (P < 0.05 for all). The BMI was positively correlated with the fat (water) concentration and slope (r = 0.350 and 0.372, respectively; P < 0.01) and negatively correlated with the CT value (r = − 0.508, P < 0.01).
Conclusion
DECT is noninvasive and effective for quantitative assessment of the pancreatic fat content.
Optopharmacological tools for precise spatiotemporal control of oxytocin signaling in the central nervous system and periphery
Authors: Froemke Robert , Ahmed Ismail , Liu Jingjing , Gieniec Krystyna , Bair-Marshall Chloe , Adewakun Ayomiposi , Hetzler Belinda , Arp Christopher , Khatri Latika , Vanwalleghem Gilles , Seidenberg Alec , Cowin Pamela , Trauner Dirk , Chao Moses , Davis Felicity , Tsien Richard 
Published: March 2023

Abstract
Oxytocin is a neuropeptide critical for maternal physiology and social behavior, and is thought to be dysregulated in several neuropsychiatric disorders. Despite the biological and neurocognitive importance of oxytocin signaling, methods are lacking to activate oxytocin receptors with high spatiotemporal precision in the brain and peripheral mammalian tissues. Here we developed and validated caged analogs of oxytocin which are functionally inert until cage release is triggered by ultraviolet light. We examined how focal versus global oxytocin application affected oxytocin-driven Ca2+ wave propagation in mouse mammary tissue. We also validated the application of caged oxytocin in the hippocampus and auditory cortex with electrophysiological recordings in vitro, and demonstrated that oxytocin uncaging can accelerate the onset of mouse maternal behavior in vivo. Together, these results demonstrate that optopharmacological control of caged peptides is a robust tool with spatiotemporal precision for modulating neuropeptide signaling throughout the brain and body.
Lithology identification based on interpretability integration learning
Authors: Lin Xiaochun , Yin Shitao 
Published: March 2023

Abstract
A lithology intelligent identification interpretability model is proposed based on Ensemble Learning Stacking, Permutation Importance (PI) and Local Interpretable Model-agnostic Explanations (LIME). The method aiming to provide more accurate geological information and more scientific theoretical support for oil and gas resource exploration. Two logging datasets from the public domain were used as experiments, and support vector machine (SVM), random forest (RF) and naive bayes (NB) were used as primary learners, and SVM as secondary learners, to classify lithology through stacking algorithm. Then, the evaluation indexes such as Area Under Curve (AUC), precision, recall and F1-score were used to verify its accuracy, and PI and LIME were used to explain the lithology identification model. The study shows that the results of the stacking algorithm have the best indexes and the highest prediction accuracy. In terms of overall interpretation, PHIND, GR and RT have the most influence on lithology identification of a natural gas protection area in the United States; DEN, CAL and PEF have the most influence on lithology identification in Daqing Oilfield in China. Interpreted from the perspective of a single sample, the LIME algorithm is able to give a quantitative prediction probability and the degree of influence of the characteristic variables.
Comprehensive analysis of the miRNA-mRNA pathological regulatory network of intestinal CD4+ T cells in Parkinson's disease
Authors: Shao Kaiquan , Wang Zipeng , Fan Xinyu , Sun Ruiao , Tang Chuanxi 
Published: March 2023

Abstract
Infiltration of CD4+ T cells was found in brain tissue samples from PD patients, suggesting their involvement in developing central nervous system (CNS) disease. The idea of the gut-brain axis further corroborates intestinal T cells' activation as the central immune response initiation. However, the specific factors and molecular pathways regulating intestinal T-cell activation are unclear. We used the GSE156287 and GSE145814 datasets from the GEO database to analyze and obtain the miRNAs, which are aberrantly expressed in intestinal CD4+ T cells in PD patients and predict their regulatory target mRNAs. Further, combined with the GSE174473 dataset of CD4+ T cells sequencing in PD patients, we finally clarified the aberrant genes expressed in CD4+ T cells from the intestine of PD patients and constructed a miRNA-mRNA regulatory network.
The highlight of our findings showed pathways, networks, biological functions and key molecules potentially involved in the miRNA-mediated functional effects in CD4+ T cell from intestin of PD patients. The hsa-miR-3180-3p mediated CBX8, etc were determined as most effective in enhancing T cell survial. PEG10 and, etc regulated by hsa-miR-20a-3p targets were possibly involved in T cell differentiation.The JPT2 regulated by hsa-miR-1281 were involved in influencing T cell infiltration;
The discovery of this interaction between miRNA and mRNA in CD4+ T cell has important implications for understanding the intestinal initial of PD pathological molecular and anti-inflammation of T cell activation.
Trends in mortality after a sepsis hospitalization: A nationwide prospective registry study from 2008-2021
Authors: Skei Nina Vibeche , Nilsen Tom Ivar , Mohus Randi , Prescott Hallie , Lydersen Stian , Solligård Erik , Damås Jan , Gustad Lise 
Published: March 2023

Abstract
Background
Few studies have reported on mortality beyond one year after sepsis. We aim to describe trends in short- and long-term mortality among patients admitted with sepsis, and to identify clinical characteristics associated with mortality for improved monitoring, treatment and prognosis.
Methods
Patients ≥ 18 years admitted to all Norwegian hospitals (2008–2021) with a first sepsis episode were identified using Norwegian Patient Registry and International Classification of Diseases 10th Revision codes. Sepsis was classified as implicit (known infection site plus organ dysfunction), explicit (unknown infection site), or COVID-19 related sepsis. The outcome was all-cause mortality. We calculated age-standardized 30-day, 90-day, 1-, 5- and 10-year mortality for each admission year and estimated the annual percentage change with 95% confidence interval (CI). The association between clinical characteristics and all-cause mortality is reported as hazard ratios (HRs) from Cox regression.
Results
The study included 222,832 patients, of whom 127,059 (57.1%) had implicit, 92,928 (41.7%) had explicit, and 2,845 (1.3%) had COVID-19-related sepsis. Trends in overall age-standardized 30-day, 90-day, 1- and 5-year mortality decreased by 0.29 (95% CI -0.39 to -0.19), 0.43 (95% CI -0.56 to -0.29), 0.61 (95% CI -0.73 to -0.49) and 0.66 (95% CI -0.84 to -0.48) percent per year, respectively. The decrease was observed for all infections sites but was largest among patients with respiratory tract infections. Implicit, explicit and COVID-19-related sepsis had largely similar overall mortality, with explicit sepsis having a HR of 0.980 (95% CI 0.969 to 0.991) and COVID-19-related sepsis a HR of 0.916 (95% CI 0.836 to 1.003) compared to implicit sepsis. Patients with respiratory tract infections have somewhat higher mortality than those with other infection sites. Number of comorbidities was positively associated with mortality, but mortality varied considerably between different comorbidities. Similarly, number of acute organ dysfunctions was strongly associated with mortality, whereas the risk varied for each type of organ dysfunction.
Conclusion
Overall mortality has declined over the past 14 years among patients with a first sepsis admission. Existing comorbidity, site of infection, and acute organ dysfunction are characteristics associated with mortality and needs further attention to reduce the excess risk of long-term mortality.
Can Public Blockchains Mitigate Semiconductors Supply Chain Disruption?
Authors: Grida Mohamed , Magdy Mirna , Hussein Gawaher 
Published: March 2023

Abstract
Today's supply chain is more complex in composition and structure. Information loss and late transmission aggravated the bullwhip effect. Lack of reliable information storage, traceability, and accountability have also slowed supply chain management. Blockchain supports distributed networking, information synchronization among nodes, digital encryption, traceable information, and unchangeable block content, making it suitable for the supply chain. This paper presents the public blockchain as a solution to the "bullwhip effect problem in supply chain (SC). The framework is implemented to address the disruption of semiconductors' SC. The framework consists of a checklist to determine the SC's readiness for blockchain adoption. The checklist determines the motivation, timing, and the appropriate platform for adopting blockchain. The framework was validated in the Semiconductors SC by polling four executives: each represents a large company that has many branches in Egypt and the Middle East; each represents a different stage, and they are retail, distribution, manufacturing, and supply. The results showed that the executives agreed that there are perceived benefits to adopting blockchain. At the same time, they are neutral about whether it is the right time for blockchain adoption and disagree that the BC technology is ready for their SC. Finally, some of the public blockchain platforms that can be used and implemented in supply chains were introduced to help enterprises choose the most suitable platform to adopt.