bluuebunny/crossref_metadata_2025 huggingface dataset:
Genome-Wide Identification and Transcriptional Analysis of AP2/ERF Gene Family in Pearl Millet (Pennisetum glaucum)
Authors: Xu Liang , Lan Ying , Lin Miaohong , Zhou Hongkai , Ying Sheng , Chen Miao
Published: February 2024

The apetala2/ethylene response factor (AP2/ERF) gene family plays a crucial role in regulating plant growth and development and responding to different abiotic stresses (e.g., drought, heat, cold, and salinity). However, the knowledge of the ERF family in pearl millet remains limited. Here, a total of 167 high-confidence PgERF genes are identified and divided into five subgroups based on gene-conserved structure and phylogenetic analysis. Forty-one pairs of segmental duplication are found using collinear analysis. Nucleotide substitution analysis reveals these duplicated pairs are under positive purification, indicating they are actively responding to natural selection. Comprehensive transcriptomic analysis reveals that PgERF genesare preferentially expressed in the imbibed seeds and stem (tilling stage) and respond to heat, drought, and salt stress. Prediction of the cis-regulatory element by the PlantCARE program indicates that PgERF genes are involved in responses to environmental stimuli. Using reverse transcription quantitative real-time PCR (RT-qPCR), expression profiles of eleven selected PgERF genes are monitored in various tissues and during different abiotic stresses. Transcript levels of each PgERF gene exhibit significant changes during stress treatments. Notably, the PgERF7 gene is the only candidate that can be induced by all adverse conditions. Furthermore, four PgERF genes (i.e., PgERF22, PgERF37, PgERF88, and PgERF155) are shown to be involved in the ABA-dependent signaling pathway. These results provide useful bioinformatic and transcriptional information for understanding the roles of the pearl millet ERF gene family in adaptation to climate change.
The Effect of a Ketogenic Diet versus Mediterranean Diet on Clinical and Biochemical Markers of Inflammation in Patients with Obesity and Psoriatic Arthritis: A Randomized Crossover Trial
Authors: Lambadiari Vaia , Katsimbri Pelagia , Kountouri Aikaterini , Korakas Emmanouil , Papathanasi Argyro , Maratou Eirini , Pavlidis George , Pliouta Loukia , Ikonomidis Ignatios , Malisova Sofia , Vlachos Dionysios , Papadavid Evangelia
Published: February 2024

The effect of different diet patterns on psoriasis (PSO) and psoriatic arthritis (PSA) is unknown. Τhe aim of our study was to evaluate the effectiveness of a Mediterranean diet (MD) and Ketogenic diet (KD), in patients with PSO and PSA. Twenty-six patients were randomly assigned to start either with MD or KD for a period of 8 weeks. After a 6-week washout interval, the two groups were crossed over to the other type of diet for 8 weeks. At the end of this study, MD and KD resulted in significant reduction in weight (p = 0.002, p < 0.001, respectively), in BMI (p = 0.006, p < 0.001, respectively), in waist circumference (WC) (p = 0.001, p < 0.001, respectively), in total fat mass (p = 0.007, p < 0.001, respectively), and in visceral fat (p = 0.01, p < 0.001, respectively), in comparison with baseline. After KD, patients displayed a significant reduction in the Psoriasis Area and Severity Index (PASI) (p = 0.04), Disease Activity Index of Psoriatic Arthritis (DAPSA) (p = 0.004), interleukin (IL)-6 (p = 0.047), IL-17 (p = 0.042), and IL-23 (p = 0.037), whereas no significant differences were observed in these markers after MD (p > 0.05), compared to baseline. The 22-week MD–KD diet program in patients with PSO and PSA led to beneficial results in markers of inflammation and disease activity, which were mainly attributed to KD.
Recombinant Rod Domain of Vimentin Reduces SARS-CoV-2 Viral Replication by Blocking Spike Protein–ACE2 Interactions
Authors: Lam Fong Wilson , Brown Cameron August , Ronca Shannon Elizabeth
Published: February 2024

Although the SARS-CoV-2 vaccination is the primary preventive intervention, there are still few antiviral therapies available, with current drugs decreasing viral replication once the virus is intracellular. Adding novel drugs to target additional points in the viral life cycle is paramount in preventing future pandemics. The purpose of this study was to create and test a novel protein to decrease SARS-CoV-2 replication. We created the recombinant rod domain of vimentin (rhRod) in E. coli and used biolayer interferometry to measure its affinity to the SARS-CoV-2 S1S2 spike protein and the ability to block the SARS-CoV-2–ACE2 interaction. We performed plaque assays to measure rhRod’s effect on SARS-CoV-2 replication in Vero E6 cells. Finally, we measured lung inflammation in SARS-CoV-2-exposed K18-hACE transgenic mice given intranasal and intraperitoneal rhRod. We found that rhRod has a high affinity for the S1S2 protein with a strong ability to block S1S2–ACE2 interactions. The daily addition of rhRod decreased viral replication in Vero E6 cells starting at 48 h at concentrations >1 µM. Finally, SARS-CoV-2-infected mice receiving rhRod had decreased lung inflammation compared to mock-treated animals. Based on our data, rhRod decreases SARS-CoV-2 replication in vitro and lung inflammation in vivo. Future studies will need to evaluate the protective effects of rhRod against additional viral variants and identify the optimal dosing scheme that both prevents viral replication and host lung injury.
P53 and Rb Aberrations in Small Cell Lung Cancer (SCLC): From Molecular Mechanisms to Therapeutic Modulation
Authors: Papavassiliou Kostas A. , Sofianidi Amalia A. , Gogou Vassiliki A. , Anagnostopoulos Nektarios , Papavassiliou Athanasios G.
Published: February 2024

The genes coding for the tumor suppressors p53 and retinoblastoma (Rb) are inactivated in the vast majority of small cell lung cancer (SCLC) tumors. Data support the notion that these two deleterious genetic events represent the initial steps in the development of SCLC, making them essential for a lung epithelial cell to progress toward the acquisition of a malignant phenotype. With the loss of TP53 and RB1, their broad tumor suppressive functions are eliminated and a normal cell is able to proliferate indefinitely, escape entering into cellular senescence, and evade death, no matter the damage it has experienced. Within this setting, lung epithelial cells accumulate further oncogenic mutations and are well on their way to becoming SCLC cells. Understanding the molecular mechanisms of these genetic lesions and their effects within lung epithelial cells is of paramount importance, in order to tackle this aggressive and deadly lung cancer. The present review summarizes the current knowledge on p53 and Rb aberrations, their biological significance, and their prospective therapeutic potential, highlighting completed and ongoing clinical trials with agents that target downstream pathways.
Steady Laminar Flow Decreases Endothelial Glycolytic Flux While Enhancing Proteoglycan Synthesis and Antioxidant Pathways
Authors: Basehore Sarah E. , Garcia Jonathan , Clyne Alisa Morss
Published: February 2024

Endothelial cells in steady laminar flow assume a healthy, quiescent phenotype, while endothelial cells in oscillating disturbed flow become dysfunctional. Since endothelial dysfunction leads to atherosclerosis and cardiovascular disease, it is important to understand the mechanisms by which endothelial cells change their function in varied flow environments. Endothelial metabolism has recently been proven a powerful tool to regulate vascular function. Endothelial cells generate most of their energy from glycolysis, and steady laminar flow may reduce endothelial glycolytic flux. We hypothesized that steady laminar but not oscillating disturbed flow would reduce glycolytic flux and alter glycolytic side branch pathways. In this study, we exposed human umbilical vein endothelial cells to static culture, steady laminar flow (20 dynes/cm2 shear stress), or oscillating disturbed flow (4 ± 6 dynes/cm2 shear stress) for 24 h using a cone-and-plate device. We then measured glucose and lactate uptake and secretion, respectively, and glycolytic metabolites. Finally, we explored changes in the expression and protein levels of endothelial glycolytic enzymes. Our data show that endothelial cells in steady laminar flow had decreased glucose uptake and 13C labeling of glycolytic metabolites while cells in oscillating disturbed flow did not. Steady laminar flow did not significantly change glycolytic enzyme gene or protein expression, suggesting that glycolysis may be altered through enzyme activity. Flow also modulated glycolytic side branch pathways involved in proteoglycan and glycosaminoglycan synthesis, as well as oxidative stress. These flow-induced changes in endothelial glucose metabolism may impact the atheroprone endothelial phenotype in oscillating disturbed flow.
Two SEPALLATA MADS-Box Genes, SlMBP21 and SlMADS1, Have Cooperative Functions Required for Sepal Development in Tomato
Authors: Zhang Jianling , Hu Zongli , Xie Qiaoli , Dong Tingting , Li Jing , Chen Guoping
Published: February 2024

MADS-box transcription factors have crucial functions in numerous physiological and biochemical processes during plant growth and development. Previous studies have reported that two MADS-box genes, SlMBP21 and SlMADS1, play important regulatory roles in the sepal development of tomato, respectively. However, the functional relationships between these two genes are still unknown. In order to investigate this, we simultaneously studied these two genes in tomato. Phylogenetic analysis showed that they were classified into the same branch of the SEPALLATA (SEP) clade. qRT-PCR displayed that both SlMBP21 and SlMADS1 transcripts are preferentially accumulated in sepals, and are increased with flower development. During sepal development, SlMBP21 is increased but SlMADS1 is decreased. Using the RNAi, tomato plants with reduced SlMBP21 mRNA generated enlarged and fused sepals, while simultaneous inhibition of SlMBP21 and SlMADS1 led to larger (longer and wider) and fused sepals than that in SlMBP21-RNAi lines. qRT-PCR results exhibited that the transcripts of genes relating to sepal development, ethylene, auxin and cell expansion were dramatically changed in SlMBP21-RNAi sepals, especially in SlMBP21-SlMADS1-RNAi sepals. Yeast two-hybrid assay displayed that SlMBP21 can interact with SlMBP21, SlAP2a, TAGL1 and RIN, and SlMADS1 can interact with SlAP2a and RIN, respectively. In conclusion, SlMBP21 and SlMADS1 cooperatively regulate sepal development in tomato by impacting the expression or activities of other related regulators or via interactions with other regulatory proteins.
Morphological Analyses and QTL Mapping of Mottled Leaf in Zucchini (Cucurbita pepo L.)
Authors: Wang Kexin , Wang Xinyu , Zhang Lijing , Chi Yichen , Luo Yusong , Xu Wenlong , Wang Yunli , Qu Shuping
Published: February 2024

The mottled leaf is one of the agronomic traits of zucchini and can be applied as a marker trait in aggregation breeding. However, the genetic mechanism responsible for mottled leaf has yet to be elucidated. In the present study, we used two inbred lines (line ‘19’: silver mottled leaf; line ‘113’: normal leaf) as parents for the physiological and genetic analysis of mottled leaf. The synthesis and net photosynthetic rate of chlorophyll were not significantly affected in the mottled areas of leaves. However, we detected a large space between the palisade parenchyma in the leaf mottle area of line ‘19’, which may have caused the mottled leaf phenotype. Light also plays an important role in the formation of mottled leaf, and receiving light during the early stages of leaf development is a necessary factor. Genetic analysis has previously demonstrated that mottled leaf is a quantitative trait that is controlled by multiple genes. Based on the strategy of quantitative trait locus sequencing (QTL-seq), two QTLs were identified on chromosomes 1 and 17, named CpML1.1 and CpML17.1, respectively. Two major loci were identified using R/qtl software version 1.66 under greenhouse conditions in April 2019 (2019A) and April 2020 (2020A) and under open cultivation conditions in May 2020 (2020M). The major QTL, CpML1.1, was located in a 925.2-kb interval on chromosome 1 and explained 10.51%-24.15% of the phenotypic variation. The CpML17.1 was located in a 719.7-kb interval on chromosome 17 and explained 16.25%-38.68% of the phenotypic variation. Based on gene annotation, gene sequence alignment, and qRT–PCR analysis, the Cp4.1LG01g23790 at the CpML1.1 locus encoding a protein of the TPX2 family (target protein of Xklp2) may be a candidate gene for mottled leaf in zucchini. Our findings may provide a theoretical basis for the formation of mottled leaf and provide a foundation for the fine mapping of genes associated with mottled leaf. Molecular markers closely linked to mottled leaf can be used in molecular-assisted selection for the zucchini mottled leaf breeding.
Multidisciplinary Automation in Design of Turbine Vane Cooling Channels
Authors: Nambiar Sanjay , Ananno Anan Ashrabi , Titus Herman , Wiberg Anton , Tarkian Mehdi
Published: February 2024

In the quest to enhance the efficiency of gas turbines, there is a growing demand for innovative solutions to optimize high-pressure turbine blade cooling. However, the traditional methods for achieving this optimization are known for their complexity and time-consuming nature. We present an automation framework to streamline the design, meshing, and structural analysis of cooling channels, achieving design automation at both the morphological and topological levels. This framework offers a comprehensive approach for evaluating turbine blade lifetime and enabling multidisciplinary design analyses, emphasizing flexibility in turbine cooling design through high-level CAD templates and knowledge-based engineering. The streamlined automation process, supported by a knowledge base, ensures continuity in both the mesh and structural simulation automations, contributing significantly to advancements in gas turbine technology.
IoT-Based SHM Using Digital Twins for Interoperable and Scalable Decentralized Smart Sensing Systems
Authors: Chen Jiahang , Reitz Jan , Richstein Rebecca , Schröder Kai-Uwe , Roßmann Jürgen
Published: February 2024

Advancing digitalization is reaching the realm of lightweight construction and structural–mechanical components. Through the synergistic combination of distributed sensors and intelligent evaluation algorithms, traditional structures evolve into smart sensing systems. In this context, Structural Health Monitoring (SHM) plays a key role in managing potential risks to human safety and environmental integrity due to structural failures by providing analysis, localization, and records of the structure’s loading and damaging conditions. The establishment of networks between sensors and data-processing units via Internet of Things (IoT) technologies is an elementary prerequisite for the integration of SHM into smart sensing systems. However, this integrating of SHM faces significant restrictions due to scalability challenges of smart sensing systems and IoT-specific issues, including communication security and interoperability. To address the issue, this paper presents a comprehensive methodological framework aimed at facilitating the scalable integration of objects ranging from components via systems to clusters into SHM systems. Furthermore, we detail a prototypical implementation of the conceptually developed framework, demonstrating a structural component and its corresponding Digital Twin. Here, real-time capable deformation and strain-based monitoring of the structure are achieved, showcasing the practical applicability of the proposed framework.
Manipulation and Wakefield Effects on Multi-Pulse Driver Beams in PWFA Injector Stages
Authors: Bosco Fabio , Andonian Gerard , Camacho Obed , Carillo Martina , Chiadroni Enrica , Giribono Anna , Lawler Gerard , Majernik Nathan , Manwani Pratik , Migliorati Mauro , Mostacci Andrea , Palumbo Luigi , Silvi Gilles Jacopo , Spataro Bruno , Vaccarezza Cristina , Yadav Monika , Rosenzweig James
Published: February 2024

Particle-driven plasma wakefield acceleration (PWFA) exploits the intense wakefields excited in a plasma by a high-brightness driver beam in order to accelerate a trailing, properly delayed witness electron beam. Such a configuration offers notable advantages in achieving very large accelerating gradients that are suitable for applications in particle colliders and photon production. Moreover, the amplitude of the accelerating fields can be enhanced by resonantly exciting the plasma using a multi-pulse driver beam with a proper time structure. Before the injection into the plasma stage, the pulsed electron beam, conventionally termed the comb beam, is usually produced and pre-accelerated in a radio-frequency (RF) linear accelerator (linac). In this pape, we discuss challenging aspects of the dynamics that comb beams encounter in the RF injector stage preceding the plasma. In particular, the examples we analyze focus on the use of velocity bunching to manipulate the time structure of the beam and the impact of dipole short-range wakefields on the transverse emittances. Indeed, both processes crucially affect the phase space distribution and its quality, which are determinant features for an efficient acceleration in the plasma. In addition, the analyses we present are performed with the custom tracking code MILES, which utilizes semi-analytical models for a simplified evaluation of wakefield effects in the presence of space charge forces.
Update on Diagnosis and Treatment of Uveitic Glaucoma
Authors: Halkiadakis Ioannis , Konstantopoulou Kalliroi , Tzimis Vasilios , Papadopoulos Nikolaos , Chatzistefanou Klio , Markomichelakis Nikolaos N.
Published: February 2024

Glaucoma is a common and potentially blinding complication of uveitis. Many mechanisms are involved alone or in combination in the pathogenesis of uveitic glaucoma (UG). In terms of diagnostic evaluation, the effects of inflammatory activity in the retinal nerve fiber layer may be a source of bias in the interpretation of optical coherence tomography measurements. For the successful treatment of UG, the control of intraocular inflammation specific to the cause or anti-inflammatory treatment, combined with IOP management, is mandatory. The early institution of specific treatment improves the prognosis of UG associated with CMV. The young age of UG patients along with increased failure rates of glaucoma surgery in this group of patients warrants a stepwise approach. Conservative and conjunctival sparing surgical approaches should be adopted. Minimally invasive surgical approaches were proved to be effective and are increasingly being used in the management of UG along with the traditionally used techniques of trabeculectomy or tubes. This review aims to summarize the progress that recently occurred in the diagnosis and treatment of UG.
Enhancing Pulmonary Embolism Mortality Risk Stratification Using Machine Learning: The Role of the Neutrophil-to-Lymphocyte Ratio
Authors: Teodoru Minodora , Negrea Mihai Octavian , Cozgarea Andreea , Cozma Dragoș , Boicean Adrian
Published: February 2024

(1) Background: Acute pulmonary embolism (PE) is a significant public health concern that requires efficient risk estimation to optimize patient care and resource allocation. The purpose of this retrospective study was to show the correlation of NLR (neutrophil-to-lymphocyte ratio) and PESI (pulmonary embolism severity index)/sPESI (simplified PESI) in determining the risk of in-hospital mortality in patients with pulmonary thromboembolism. (2) Methods: A total of 160 patients admitted at the County Clinical Emergency Hospital of Sibiu from 2019 to 2022 were included and their hospital records were analyzed. (3) Results: Elevated NLR values were significantly correlated with increased in-hospital mortality. Furthermore, elevated NLR was associated with PESI and sPESI scores and their categories, as well as the individual components of these parameters, namely increasing age, hypotension, hypoxemia, and altered mental status. We leveraged the advantages of machine learning algorithms to integrate elevated NLR into PE risk stratification. Utilizing two-step cluster analysis and CART (classification and regression trees), several distinct patient subgroups emerged with varying in-hospital mortality rates based on combinations of previously validated score categories or their defining elements and elevated NLR, WBC (white blood cell) count, or the presence COVID-19 infection. (4) Conclusion: The findings suggest that integrating these parameters in risk stratification can aid in improving predictive accuracy of estimating the in-hospital mortality of PE patients.
Identification of Novel and Recurrent Variants in BTD, GBE1, AGL and ASL Genes in Families with Metabolic Disorders in Saudi Arabia
Authors: Latif Muhammad , Hashmi Jamil Amjad , Alayoubi Abdulfatah M. , Ayub Arusha , Basit Sulman
Published: February 2024

Background and Objectives: Inherited metabolic disorders (IMDs) are a group of genetic disorders characterized by defects in enzymes or transport proteins involved in metabolic processes. These defects result in an abnormal accumulation of metabolites and thus interfere with the body’s metabolism. A variety of IMDs exist and differential diagnosis is often challenging. Our objective was to gain insight into the genetic basis of IMDs and the correlations between specific genetic mutations and clinical presentations in patients admitted at various hospitals in the Madinah region of the Kingdom of Saudi Arabia. Material and Methods: Whole exome sequencing (WES) has emerged as a powerful tool for diagnosing IMDs and allows for the identification of disease-causing genetic mutations in individuals suspected of IMDs. This ensures accurate diagnosis and appropriate management. WES was performed in four families with multiple individuals showing clinical presentation of IMDs. Validation of the variants identified through WES was conducted using Sanger sequencing. Furthermore, various computational analyses were employed to uncover the disease gene co-expression and metabolic pathways. Results: Exome variant data analysis revealed missense variants in the BTD (c.1270G > C), ASL (c.1300G > T), GBE1 (c.985T > G) and AGL (c.113C > G) genes. Mutations in these genes are known to cause IMDs. Conclusions: Thus, our data showed that exome sequencing, in conjunction with clinical and biochemical characteristics and pathological hallmarks, could deliver an accurate and high-throughput outcome for the diagnosis and sub-typing of IMDs. Overall, our findings emphasize that the integration of WES with clinical and pathological information has the potential to improve the diagnosis and understanding of IMDs and related disorders, ultimately benefiting patients and the medical community.
Validation of SeptiCyte RAPID to Discriminate Sepsis from Non-Infectious Systemic Inflammation
Authors: Balk Robert , Esper Annette M. , Martin Greg S. , Miller Russell R. , Lopansri Bert K. , Burke John P. , Levy Mitchell , Opal Steven , Rothman Richard E. , D’Alessio Franco R. , Sidhaye Venkataramana K. , Aggarwal Neil R. , Greenberg Jared A. , Yoder Mark , Patel Gourang , Gilbert Emily , Parada Jorge P. , Afshar Majid , Kempker Jordan A. , van der Poll Tom , Schultz Marcus J. , Scicluna Brendon P. , Klein Klouwenberg Peter M. C. , Liebler Janice , Blodget Emily , Kumar Santhi , Navalkar Krupa , Yager Thomas D. , Sampson Dayle , Kirk James T. , Cermelli Silvia , Davis Roy F. , Brandon Richard B.
Published: February 2024

(1) Background: SeptiCyte RAPID is a molecular test for discriminating sepsis from non-infectious systemic inflammation, and for estimating sepsis probabilities. The objective of this study was the clinical validation of SeptiCyte RAPID, based on testing retrospectively banked and prospectively collected patient samples. (2) Methods: The cartridge-based SeptiCyte RAPID test accepts a PAXgene blood RNA sample and provides sample-to-answer processing in ~1 h. The test output (SeptiScore, range 0–15) falls into four interpretation bands, with higher scores indicating higher probabilities of sepsis. Retrospective (N = 356) and prospective (N = 63) samples were tested from adult patients in ICU who either had the systemic inflammatory response syndrome (SIRS), or were suspected of having/diagnosed with sepsis. Patients were clinically evaluated by a panel of three expert physicians blinded to the SeptiCyte test results. Results were interpreted under either the Sepsis-2 or Sepsis-3 framework. (3) Results: Under the Sepsis-2 framework, SeptiCyte RAPID performance for the combined retrospective and prospective cohorts had Areas Under the ROC Curve (AUCs) ranging from 0.82 to 0.85, a negative predictive value of 0.91 (sensitivity 0.94) for SeptiScore Band 1 (score range 0.1–5.0; lowest risk of sepsis), and a positive predictive value of 0.81 (specificity 0.90) for SeptiScore Band 4 (score range 7.4–15; highest risk of sepsis). Performance estimates for the prospective cohort ranged from AUC 0.86–0.95. For physician-adjudicated sepsis cases that were blood culture (+) or blood, urine culture (+)(+), 43/48 (90%) of SeptiCyte scores fell in Bands 3 or 4. In multivariable analysis with up to 14 additional clinical variables, SeptiScore was the most important variable for sepsis diagnosis. A comparable performance was obtained for the majority of patients reanalyzed under the Sepsis-3 definition, although a subgroup of 16 patients was identified that was called septic under Sepsis-2 but not under Sepsis-3. (4) Conclusions: This study validates SeptiCyte RAPID for estimating sepsis probability, under both the Sepsis-2 and Sepsis-3 frameworks, for hospitalized patients on their first day of ICU admission.
Myocardial Metabolism in Heart Failure with Preserved Ejection Fraction
Authors: Henry John Aaron , Couch Liam S. , Rider Oliver J.
Published: February 2024

Heart failure with preserved ejection fraction (HFpEF) is increasingly prevalent and now accounts for half of all heart failure cases. This rise is largely attributed to growing rates of obesity, hypertension, and diabetes. Despite its prevalence, the pathophysiological mechanisms of HFpEF are not fully understood. The heart, being the most energy-demanding organ, appears to have a compromised bioenergetic capacity in heart failure, affecting all phenotypes and aetiologies. While metabolic disturbances in heart failure with reduced ejection fraction (HFrEF) have been extensively studied, similar insights into HFpEF are limited. This review collates evidence from both animal and human studies, highlighting metabolic dysregulations associated with HFpEF and its risk factors, such as obesity, hypertension, and diabetes. We discuss how changes in substrate utilisation, oxidative phosphorylation, and energy transport contribute to HFpEF. By delving into these pathological shifts in myocardial energy production, we aim to reveal novel therapeutic opportunities. Potential strategies include modulating energy substrates, improving metabolic efficiency, and enhancing critical metabolic pathways. Understanding these aspects could be key to developing more effective treatments for HFpEF.
The LH:FSH Ratio in Functional Hypothalamic Amenorrhea: An Observational Study
Authors: Boegl Magdalena , Dewailly Didier , Marculescu Rodrig , Steininger Johanna , Ott Johannes , Hager Marlene
Published: February 2024

Background: In functional hypothalamic amenorrhea (FHA), luteinizing hormone and follicle-stimulating hormone levels show high interindividual variability, which significantly limits their diagnostic value in differentiating FHA from polycystic ovary syndrome (PCOS). Our aim was to profile the LH:FSH ratio in a large sample of patients with well-defined FHA. Methods: This observational study included all consecutive patients with FHA presenting to the Department of Gynecologic Endocrinology and Reproductive Medicine, Medical University of Vienna, between January 2017 and August 2023. The main parameters of interest were the LH level, the FSH level, and the LH:FSH ratio. In a subgroup analysis, we compared the LH:FSH ratio of patients with PCO morphology (PCOM) on ultrasound with that of patients without PCOM. Results: A total of 135 patients were included. Only a minority of patients revealed FSH and LH levels ≤ 2.0 mIU/mL (13% and 39%, respectively). Most patients (81.5%) had an LH:FSH ratio ≤ 1.0, while a minority (2.2%) had a ratio ≥ 2.1. The LH:FSH ratio was similar in patients with and without PCOM. Conclusion: In a well-defined FHA sample, the LH:FSH ratio was ≤ 1 in most patients. The LH:FSH ratio may prove useful in distinguishing FHA from PCOS but needs further investigation.
Cluster Headache: Diagnosis, Management, and Treatment in Pediatric Headache
Authors: Borrelli Alessandro , Valeriani Massimiliano , Monte Gabriele , Ursitti Fabiana , Proietti Checchi Martina , Tarantino Samuela , Sforza Giorgia , Papetti Laura
Published: February 2024

Despite its rarity, cluster headache can affect children. Patients with cluster headaches often experience symptoms in their adolescence, but the time it takes for a correct diagnosis can be very long. Cluster headache can be mistaken for other pathologies, which can result in patients being diagnosed and treated incorrectly. CH therapy often represents a challenge in pediatric age as there are no studies dedicated to this age category and the therapy strategy is generally based on data from adult experience. The aim of this review is to provide a summary of the current literature on cluster headache in children and adolescents.
An Efficient and Effective Image Decolorization Algorithm Based on Cumulative Distribution Function
Authors: Wu Tirui , Eising Ciaran , Glavin Martin , Jones Edward
Published: February 2024

Image decolorization is an image pre-processing step which is widely used in image analysis, computer vision, and printing applications. The most commonly used methods give each color channel (e.g., the R component in RGB format, or the Y component of an image in CIE-XYZ format) a constant weight without considering image content. This approach is simple and fast, but it may cause significant information loss when images contain too many isoluminant colors. In this paper, we propose a new method which is not only efficient, but also can preserve a higher level of image contrast and detail than the traditional methods. It uses the information from the cumulative distribution function (CDF) of the information in each color channel to compute a weight for each pixel in each color channel. Then, these weights are used to combine the three color channels (red, green, and blue) to obtain the final grayscale value. The algorithm works in RGB color space directly without any color conversion. In order to evaluate the proposed algorithm objectively, two new metrics are also developed. Experimental results show that the proposed algorithm can run as efficiently as the traditional methods and obtain the best overall performance across four different metrics.
Plant Diversity Response to Environmental Factors in Yellow River Delta, China
Authors: Xu Zhen , Li Renqiang , Dou Wenjun , Wen Hui , Yu Shulin , Wang Pan , Ning Lehua , Duan Jiaquan , Wang Jichun
Published: February 2024

Plant diversity plays a crucial role in maintaining the functionality of a community and providing essential ecosystem services. Studying the plant diversity and its response to environmental factors in the Yellow River Delta, China, as a newly formed coastal land, is beneficial for protecting plant diversity in coastal areas and maintaining ecosystem stability. In this study, 56 sites were sampled to investigate the diversity of shrubs and herbaceous plant community and its response to environmental factors. The results indicate that the plants growing in the Yellow River Delta are predominantly from the Poaceae and Asteraceae families, with dominant communities consisting of species such as Suaeda salsa, Phragmites australis, Setaria viridis, Imperata cylindrica, and Tamarix chinensis. The Shannon–Wiener index, Simpson diversity index, and Pielou’s evenness index exhibit average values of 0.34, 0.21, and 0.25, respectively, within the Yellow River Delta. These values collectively indicate a low diversity in the vegetation community, reflecting a relatively uncomplicated ecological structure in this area. Additionally, there were no significant differences in biodiversity indices under different soil formation times, but under different land cover types, the biodiversity index of cropland was significantly higher than that of impervious land. Soil salinity index exhibited a significant negative correlation with plant diversity (R2 = 0.279, p < 0.001) in the Yellow River Delta. Moreover, elevation (R2 = 0.247, p < 0.001) and temperature (R2 = 0.219, p < 0.001) showed significant positive effects on plant diversity. Regarding the ecological stoichiometry of plant elements, soil organic carbon exhibited a negative effect on the biodiversity index, while litter carbon showed a positive effect. This may be attributed to the unique topographical conditions and soil salinization in the Yellow River Delta. Our findings provide important references for the sustainable management of wetlands in the Yellow River Delta under conditions of soil salinization.
Navigating Climate Change Challenges through Smart Resilient Cities: A Comprehensive Assessment Framework
Authors: Khatibi Hamed , Wilkinson Suzanne , Sweya Lukuba N. , Baghersad Mostafa , Dianat Heiman
Published: February 2024

The rapid increase in the global population is contributing to the urgent challenges we face in ensuring the sustainability of our planet. This demographic shift, which gained momentum in the 1990s, is closely linked to a surge in natural disasters, both in terms of their frequency and severity. The quest for resources and improved quality of life, including the need for housing and essential services, has compounded these challenges. With the world’s population projected to double by 2050, and approximately two-thirds of this population expected to reside in urban areas, we are facing a complex web of interconnected issues that will significantly magnify the impacts of climate change-induced disasters. It is imperative that we build resilient cities capable of withstanding and adapting to these changes. However, the growing complexity of urban services and the necessity for integrated management raise questions about the preparedness of these resilient cities to comprehend and address the multifaceted challenges posed by climate change. In response to these critical concerns, this study endeavors to address the intersection of resilience and climate change. We propose the development of a Smart Resilient City Assessment Framework, comprising two core components: resilience re-evaluation and smartness evaluation. Each component consists of eight essential steps. The culmination of these steps results in a semi-quantitative index that accurately reflects the city’s position regarding resilience and smartness in the face of climate change-related disasters. To demonstrate the framework’s practicality and suitability, we present results from a hypothetical scenario focusing on water supply management, a critical aspect of climate change adaptation. The framework equips city managers with the necessary tools to re-evaluate their cities’ resilience, evaluate their capacity to address climate change-induced challenges, and make informed decisions on integrating resilience and smart solutions to pave the way for a more sustainable and climate-resilient future.
Cross-Language Perception of Lexical Tones by Nordic Learners of Mandarin Chinese
Authors: Gao Man
Published: February 2024

While existing cross-language studies on the perception of non-native tones primarily focus on naïve listeners, this study addresses an obvious gap by investigating learners from diverse language backgrounds. Specifically, it investigates Mandarin tone perception in two groups of learners from Nordic languages, Swedish (a pitch-accent language), and Danish (a non-tonal language), as well as in a group of native Chinese speakers. Analysis of their performance in tone identification task revealed a slight advantage for Swedish learners, implying the influence of their pitch accent background in learning Mandarin tones. However, both Swedish and Danish learners who excelled in the tone identification task exhibited similar perception of within-category tonal variations but differed from native Chinese speakers. Additionally, the study found that the presence of length contrast, a prosodic feature in the learners’ native languages, significantly influences their perception of Mandarin tones.
Physics-Informed Neural Network (PINN) for Solving Frictional Contact Temperature and Inversely Evaluating Relevant Input Parameters
Authors: Xia Yichun , Meng Yonggang
Published: February 2024

Ensuring precise prediction, monitoring, and control of frictional contact temperature is imperative for the design and operation of advanced equipment. Currently, the measurement of frictional contact temperature remains a formidable challenge, while the accuracy of simulation results from conventional numerical methods remains uncertain. In this study, a PINN model that incorporates physical information, such as partial differential equation (PDE) and boundary conditions, into neural networks is proposed to solve forward and inverse problems of frictional contact temperature. Compared to the traditional numerical calculation method, the preprocessing of the PINN is more convenient. Another noteworthy characteristic of the PINN is that it can combine data to obtain a more accurate temperature field and solve inverse problems to identify some unknown parameters. The experimental results substantiate that the PINN effectively resolves the forward problems of frictional contact temperature when provided with known input conditions. Additionally, the PINN demonstrates its ability to accurately predict the friction temperature field with an unknown input parameter, which is achieved by incorporating a limited quantity of easily measurable actual temperature data. The PINN can also be employed for the inverse identification of unknown parameters. Finally, the PINN exhibits potential in solving inverse problems associated with frictional contact temperature, even when multiple input parameters are unknown.
Experimental Strategies for Studying Tribo-Electrochemical Aspects of Chemical–Mechanical Planarization
Authors: Gamagedara Kassapa , Roy Dipankar
Published: February 2024

Chemical–mechanical planarization (CMP) is used to smoothen the topographies of a rough surface by combining several functions of tribology (friction, lubrication), chemistry, and electrochemistry (corrosion, wear, tribo-corrosion). The surface layer of interest is structurally weakened by the chemical and/or electrochemical reactions of selected additives in a polishing slurry, and the modified surface is flattened by the abrasion of a polishing pad with or without abrasive particles. The chemically active CMP slurry also serves as a lubricant for polishing and enables planarization at a microscopic level while avoiding the formation of defects at the processed surface. Applications of CMP are wide-ranging in various material-processing technologies and, specifically, it is a critical manufacturing step of integrated circuits. The CMP of metals is a significant part of this processing scheme and is associated with highly complex tribo-electrochemical mechanisms that are now additionally challenging due to various new requirements of the advanced technology nodes. The present review examines the current statuses of experimental strategies for collecting important mechanistic details of metal CMP that are necessary to design and assess CMP consumables. Both traditional and underexplored experimental techniques are discussed with illustrative results, including many previously unpublished findings for certain CMP systems of current interest.
Design of Electronic Filter for Noise and Vibration Reduction in Brushed DC Motor
Authors: Kim Jiman , Kim Hyunsu
Published: February 2024

With the recent conversion of internal combustion engines to electric vehicles, new noise issues have arisen, and among them, the noise generated by internal vehicle auxiliary systems is being considered. This study introduces an electronic filter designed with a motor model featuring vibration components, aiming to minimize the noise and vibrations generated by a Brushed DC (BDC) motor commonly employed in vehicle internal systems. It introduces a method to identify the connectors and internal parameters used in the motor for the matching of the model and experimental motor, and to measure and estimate these parameters. The model is separated and executed to ensure convergence, and it is validated by comparing the analysis results with the measured values. A filter is designed using the model to reduce current oscillations in the motor, confirming a subsequent reduction in noise and vibration. This research suggests the potential to attenuate noise and vibration in already produced motors by attaching only a filter without modifying the internal motor structure. Moreover, it is anticipated that a filter can be designed to predict and mitigate the noise and vibration components of the motor based on changes in load.
Statistical Depth in Spatial Point Process
Authors: Zhou Xinyu , Wu Wei
Published: February 2024

Statistical depth is widely used as a powerful tool to measure the center-outward rank of multivariate and functional data. Recent studies have introduced the notion of depth to the temporal point process, which exhibits randomness in the cardinality as well as distribution in the observed events. The proposed methods can well capture the rank of a point process in a given time interval, where a critical step is to measure the rank by using inter-arrival events. In this paper, we propose to extend the depth concept to multivariate spatial point process. In this case, the observed process is in a multi-dimensional location and there are no conventional inter-arrival events in the temporal process. We adopt the newly developed depth in metric space by defining two different metrics, namely the penalized metric and the smoothing metric, to fully explore the depth in the spatial point process. The mathematical properties and the large sample theory, as well as depth-based hypothesis testings, are thoroughly discussed. We then use several simulations to illustrate the effectiveness of the proposed depth method. Finally, we apply the new method in a real-world dataset and obtain desirable ranking performance.
Incompatible Deformations in Hyperelastic Plates
Authors: Lychev Sergey , Digilov Alexander , Bespalov Vladimir , Djuzhev Nikolay
Published: February 2024

The design of thin-walled structures is commonly based on the solutions of linear boundary-value problems, formulated within well-developed theories for elastic plates and shells. However, in modern appliances, especially in MEMS design, it is necessary to take into account non-linear mechanical effects that become decisive for flexible elements. Among the substantial non-linear effects that significantly change the deformation properties of thin plates are the effects of residual stresses caused by the incompatibility of deformations, which inevitably arise during the manufacture of ultrathin elements. The development of new methods of mathematical modeling of residual stresses and incompatible finite deformations in plates is the subject of this paper. To this end, the local unloading hypothesis is used. This makes it possible to define smooth fields of local deformations (inverse implant field) for the mathematical formalization of incompatibility. The main outcomes are field equations, natural boundary conditions and conservation laws, derived from the least action principle and variational symmetries taking account of the implant field. The derivations are carried out in the framework of elasticity theory for simple materials and, in addition, within Cosserat’s theory of a two-dimensional continuum. As illustrative examples, the distributions of incompatible deformations in a circular plate are considered.
An ETD Method for Vulnerable American Options
Authors: Company Rafael , Egorova Vera N. , Jódar Lucas
Published: February 2024

This paper introduces the exponential time differencing (ETD) technique as a numerical method to efficiently solve vulnerable American options pricing. We address several challenges, including removing cross-derivative terms through appropriate transformations, treating early-exercise opportunities using the penalty method, and substituting fixed boundary conditions with corresponding one-sided finite differences. The proposed method is shown to be both accurate and efficient through numerical experiments, which also compare the results with existing methods and analyze the numerical stability and convergence rate.
Optimal Coloring Strategies for the Max k-Cut Game
Authors: Garuglieri Andrea , Madeo Dario , Mocenni Chiara , Palma Giulia , Rinaldi Simone
Published: February 2024

We explore strong Nash equilibria in the max k-cut game on an undirected and unweighted graph with a set of k colors. Here, the vertices represent players, and the edges denote their relationships. Each player, v, selects a color as its strategy, and its payoff (or utility) is determined by the number of neighbors of v who have chosen a different color. Limited findings exist on the existence of strong equilibria in max k-cut games. In this paper, we make advancements in understanding the characteristics of strong equilibria. Specifically, our primary result demonstrates that optimal solutions are seven-robust equilibria. This implies that for a coalition of vertices to deviate and shift the system to a different configuration, i.e., a different coloring, a number of coalition vertices greater than seven is necessary. Then, we establish some properties of the minimal subsets concerning a robust deviation, revealing that each vertex within these subsets will deviate toward the color of one of its neighbors.
Some Generalized Entropy Ergodic Theorems for Nonhomogeneous Hidden Markov Models
Authors: Yao Qifeng , Cheng Longsheng , Chen Wenhe , Mao Ting
Published: February 2024

Entropy measures the randomness or uncertainty of a stochastic process, and the entropy rate refers to the limit of the time average of entropy. The generalized entropy rate in the form of delayed averages can overcome the redundancy of initial information while ensuring stationarity. Therefore, it has better practical value. A Hidden Markov Model (HMM) contains two stochastic processes, a stochastic process in which all states can be observed and a Markov chain in which all states cannot be observed. The entropy rate is an important characteristic of HMMs. The transition matrix of a homogeneous HMM is unique, while a Nonhomogeneous Hidden Markov Model (NHMM) requires the transition matrices to be dependent on time variables. From the perspective of model structure, NHMMs are novel extensions of homogeneous HMMs. In this paper, the concepts of the generalized entropy rate and NHMMs are defined and fully explained, a strong limit theorem and limit properties of a norm are presented, and then generalized entropy ergodic theorems with an almost surely convergence for NHMMs are obtained. These results provide concise formulas for the computation and estimation of the generalized entropy rate for NHMMs.
Allocation of Starting Points in Global Optimization Problems
Authors: Khamisov Oleg , Semenkin Eugene , Nelyub Vladimir
Published: February 2024

We propose new multistart techniques for finding good local solutions in global optimization problems. The objective function is assumed to be differentiable, and the feasible set is a convex compact set. The techniques are based on finding maximum distant points on the feasible set. A special global optimization problem is used to determine the maximum distant points. Preliminary computational results are given.