bluuebunny/crossref_metadata_2025 huggingface dataset:
SolPredictor: Predicting Solubility with Residual Gated Graph Neural Network
Authors: Ahmad Waqar , Tayara Hilal , Shim HyunJoo , Chong Kil To
Published: January 2024

Computational methods play a pivotal role in the pursuit of efficient drug discovery, enabling the rapid assessment of compound properties before costly and time-consuming laboratory experiments. With the advent of technology and large data availability, machine and deep learning methods have proven efficient in predicting molecular solubility. High-precision in silico solubility prediction has revolutionized drug development by enhancing formulation design, guiding lead optimization, and predicting pharmacokinetic parameters. These benefits result in considerable cost and time savings, resulting in a more efficient and shortened drug development process. The proposed SolPredictor is designed with the aim of developing a computational model for solubility prediction. The model is based on residual graph neural network convolution (RGNN). The RGNNs were designed to capture long-range dependencies in graph-structured data. Residual connections enable information to be utilized over various layers, allowing the model to capture and preserve essential features and patterns scattered throughout the network. The two largest datasets available to date are compiled, and the model uses a simplified molecular-input line-entry system (SMILES) representation. SolPredictor uses the ten-fold split cross-validation Pearson correlation coefficient R2 0.79±0.02 and root mean square error (RMSE) 1.03±0.04. The proposed model was evaluated using five independent datasets. Error analysis, hyperparameter optimization analysis, and model explainability were used to determine the molecular features that were most valuable for prediction.
Exploring the Metabolic and Endocrine Preconditioning Associated with Thyroid Disorders: Risk Assessment and Association with Acne Severity
Authors: Bungau Alexa Florina , Tit Delia Mirela , Bungau Simona Gabriela , Vesa Cosmin Mihai , Radu Andrei-Flavius , Marin Ruxandra Cristina , Endres Laura Maria , Moleriu Lavinia-Cristina
Published: January 2024

Metabolic preconditioning, characterized by conditions like obesity and insulin resistance syndrome, disrupts hormonal balance. Elevated androgen levels stimulate excessive sebum production and follicular cell proliferation, leading to acne lesions. Similarly, thyroid hormone imbalances affect sebaceous gland activity, epidermal lipid composition, and skin cell turnover, impacting acne occurrence and severity. This study aimed to assess the potential contribution of metabolic and endocrine preconditions to acne development. A total of 389 patients diagnosed with acne were included and divided into three groups: the metabolic precondition group (MPG, N = 163, 41.9%), the endocrine precondition group (EPG, N = 162, 41.65%), and the control group (CG, N = 89, 22.88%). Data related to the degree of acne severity and comorbidities of interest were collected from the patients’ medical records. In the groups with concomitant diseases, moderate and severe acne were significantly more prevalent (56.44% and 41.10% in MPG, and 35.80% and 61.11% in EPG) compared to the control group (5.61% and 4.89%). The most prevalent preconditions observed were insulin resistance syndrome in MPG (63.8%) and autoimmune thyroiditis in EPG (95.06%). Significant age-related differences in acne severity were found across all study groups (p < 0.05). In MPG, the age variable was significantly higher in the presence of mild acne, while in EPG, the age variable was significantly lower for the mild acne group. A positive association was observed between the severity of acne and insulin resistance syndrome, obesity, autoimmune thyroiditis, and hypothyroidism (p < 0.05). Risk analysis indicated a significantly higher risk (RR > 1, 95% CI RR > 1, p < 0.001) of developing moderate and severe acne in the presence of these preconditions. The presence of both metabolic and endocrine preconditions significantly increased the likelihood of developing severe acne, leading to the hypothesis that both conditions may be contributing factors to the development of acne.
Effect of Stress on Each of the Stages of the IVF Procedure: A Systematic Review
Authors: Zanettoullis Anastasia Tsambika , Mastorakos George , Vakas Panagiotis , Vlahos Nikolaos , Valsamakis Georgios
Published: January 2024

The aim of this systematic review was to examine if chronic or acute stress, measured by questionnaires or physiological biomarkers, has a separate impact on each different stage in the IVF process. A systematic search of peer-reviewed literature was performed in three databases with keywords. Preselection included 46 articles, and in all, 36 articles were included. Most studies concluded that stress has a negative effect on IVF treatment. The egg retrieval time point was most affected by chronic and acute stress. Through this research, there may be an association between chronic stress and the fertilization stage. Only chronic stress impacted the embryo transfer stage and further evidence suggested that stress decreased during this stage. The pregnancy rate stage was weakly associated with stress. Follicular cortisol was found to affect three stages. Chronic and acute stress significantly and negatively affected the egg retrieval time point. Chronic stress was associated with a lesser extent with the fertilization point, and no significant relationship between acute stress and the embryo transfer and pregnancy rate stages were found. Follicular cortisol was found to affect the process. This review contributes to the research of the relationship between stress and IVF success.
Airways Type-2 Related Disorders: Multiorgan, Systemic or Syndemic Disease?
Authors: Giombi Francesco , Pace Gian Marco , Pirola Francesca , Cerasuolo Michele , Ferreli Fabio , Mercante Giuseppe , Spriano Giuseppe , Canonica Giorgio Walter , Heffler Enrico , Ferri Sebastian , Puggioni Francesca , Paoletti Giovanni , Malvezzi Luca
Published: January 2024

Chronic rhinosinusitis (CRS) has recently undergone a significant paradigm shift, moving from a phenotypical classification towards an “endotype-based” definition that places more emphasis on clinical and therapeutic aspects. Similar to other airway diseases, like asthma, most cases of CRS in developed countries exhibit a dysregulated type-2 immune response and related cytokines. Consequently, the traditional distinction between upper and lower airways has been replaced by a “united airway” perspective. Additionally, type-2 related disorders extend beyond respiratory boundaries, encompassing conditions beyond the airways, such as atopic dermatitis. This necessitates a multidisciplinary approach. Moreover, consideration of possible systemic implications is crucial, particularly in relation to sleep-related breathing diseases like Obstructive Sleep Apnoea Syndrome (OSAS) and the alteration of systemic inflammatory mediators such as nitric oxide. The trends in epidemiological, economic, and social burden are progressively increasing worldwide, indicating syndemic characteristics. In light of these insights, this narrative review aims to present the latest evidence on respiratory type-2 related disorders, with a specific focus on CRS while promoting a comprehensive perspective on the “united airways”. It also introduces a novel concept: viewing these conditions as a multiorgan, systemic, and syndemic disease.
Traumatic Cardiac Arrest—A Narrative Review
Authors: Schober Patrick , Giannakopoulos Georgios F. , Bulte Carolien S. E. , Schwarte Lothar A.
Published: January 2024

A paradigm shift in traumatic cardiac arrest (TCA) perception switched the traditional belief of futility of TCA resuscitation to a more optimistic perspective, at least in selected cases. The goal of TCA resuscitation is to rapidly and aggressively treat the common potentially reversible causes of TCA. Advances in diagnostics and therapy in TCA are ongoing; however, they are not always translating into improved outcomes. Further research is needed to improve outcome in this often young and previously healthy patient population.
Lung Imaging and Artificial Intelligence in ARDS
Authors: Chiumello Davide , Coppola Silvia , Catozzi Giulia , Danzo Fiammetta , Santus Pierachille , Radovanovic Dejan
Published: January 2024

Artificial intelligence (AI) can make intelligent decisions in a manner akin to that of the human mind. AI has the potential to improve clinical workflow, diagnosis, and prognosis, especially in radiology. Acute respiratory distress syndrome (ARDS) is a very diverse illness that is characterized by interstitial opacities, mostly in the dependent areas, decreased lung aeration with alveolar collapse, and inflammatory lung edema resulting in elevated lung weight. As a result, lung imaging is a crucial tool for evaluating the mechanical and morphological traits of ARDS patients. Compared to traditional chest radiography, sensitivity and specificity of lung computed tomography (CT) and ultrasound are higher. The state of the art in the application of AI is summarized in this narrative review which focuses on CT and ultrasound techniques in patients with ARDS. A total of eighteen items were retrieved. The primary goals of using AI for lung imaging were to evaluate the risk of developing ARDS, the measurement of alveolar recruitment, potential alternative diagnoses, and outcome. While the physician must still be present to guarantee a high standard of examination, AI could help the clinical team provide the best care possible.
Navigating the ICI Combination Treatment Journey: Patterns of Response and Progression to First-Line ICI-Based Combination Treatment in Metastatic Renal Cell Carcinoma
Authors: Samuelly Alessandro , Di Stefano Rosario Francesco , Turco Fabio , Delcuratolo Marco Donatello , Pisano Chiara , Saporita Isabella , Calabrese Mariangela , Carfì Federica Maria , Tucci Marcello , Buttigliero Consuelo
Published: January 2024

The use of immune checkpoint inhibitors (ICIs) in combination with tyrosine kinase inhibitors or other ICIs has significantly improved the prognosis for patients with mccRCC. This marks a major milestone in the treatment of mccRCC. Nonetheless, most patients will discontinue first-line therapy. In this narrative review, we analyze the different patterns of treatment discontinuation in the four pivotal phase III trials that have shown an improvement in overall survival in mccRCC first-line therapy, starting from 1 January 2017 to 1 June 2023. We highlight the different discontinuation scenarios and their influences on subsequent treatment options, aiming to provide more data to clinicians to navigate a complex decision-making process through a narrative review approach. We have identified several causes for discontinuations for patients treated with ICI-based combinations, such as interruption for drug-related adverse events, ICI treatment completion, treatment discontinuation due to complete response or maximum clinical benefit, or due to progression (pseudoprogression, systemic progression, and oligoprogression); for each case, an extensive analysis of the trials and current medical review has been conducted.
Trans-Brachial TAVI in a Patient with Aortic Isthmus Stenosis: A Case Report
Authors: Saad Mohammed , Elhakim Abdelrahman , Rusch Rene , Berndt Rouven , Panholzer Bernd , Lutter Georg , Frank Derk
Published: January 2024

Background: TAVI indications expand not only to low-risk patients but also to patients with a more complex anatomy and comorbidities. Transfemoral retrograde access is recognized as the first preferred approach according to the current guidelines. However, this approach is not suitable in up to 10–15% of patients, for whom an alternative non-femoral access route is required. Case Presentation: An 83-year-old male patient with known aortic isthmus stenosis presented with severe symptomatic aortic stenosis. Computed tomography revealed a subtotal isthmus stenosis, directly after left subclavian artery origin, with many collaterals extending toward the axillary and subclavian arteries. Duplex ultrasound verified the proximal diameter of the left brachial artery to be 5.5 mm. A successful surgical cutdown trans-brachial TAVI with an Evolut prosthetic valve with a size of 29 mm was performed. On the fourth postoperative day, the patient was discharged, and the three-month follow-up was uneventful. Conclusion: In patients with aortic isthmus stenosis, the brachial artery could be a feasible alternative, as a less invasive access site, which can be determined after careful assessment of the vessel diameter. More data are required to evaluate the safety and efficacy of this access route and to achieve more technical improvements to increase operator familiarity with it.
A Questionnaire of Physiotherapeutic Specific Exercises of Scoliosis—QPSSE
Authors: Grivas Theodoros B. , Dadakaridou Dimitra , Fokidi Stavroula A. , Kastrinis Alexandros , Kosti Melpomeni , Mihas Constantinos , Oikonomaki Marianna , Theodosopoulos Evangelos , Griva Artemis Margarita
Published: January 2024

Study design: Creating and psychometric testing of a new QoL Questionnaire about Physiotherapeutic Specific Exercises of Scoliosis (Questionnaire of Physiotherapeutic Specific Exercises of Scoliosis—QPSSE). Purpose: The purpose of this study is to create a reliable and valid questionnaire for patients suffering from mild and moderate adolescent idiopathic scoliosis (AIS) who have been treated with Physiotherapeutic Specific Exercises of Scoliosis (PSSE) in order to evaluate their quality of life. Materials and Methods: The developed questionnaire was based on a thorough literature review as well as on authors’ experience. It consists of 53 questions, of which 37 have a positive meaning, 15 have a negative meaning, and 1 is a multiple choice question; additionally, there are 6 “open” questions. Except for the multiple choice question, all other questions are answered on a Likert scale ranging from 1 to 5 points. Five represents a positive meaning or very positive one, whereas one stands for a negative meaning or none at all. Questions were developed by the authors who subsequently categorized the 53 questions into the following eight domains: physical functioning, self-image, Physiotherapeutic Scoliosis-Specific Exercises (PSSEs), psychosocial functioning, cognitive functioning, compliance, motivation, and pain. A pilot study was conducted so that we could calculate Cronbach’s Alpha based on the outcome. Due to the COVID-19 pandemic, the authors worked through the Zoom online platform to structure the questionnaire. Results: Pearson’s correlation coefficient was used for all correlations evaluated. P values of less than 0.05 were considered to be significant. Internal consistency was evaluated with Cronbach’s Alpha. Although there were very few missing values, accounting for 0.78% of the total values of the questionnaire, the expectation maximization likelihood algorithm was used to impute data. IBM® SPSS® Statistics Software v.25 was used for the analysis. Cronbach’s Alpha coefficients for the overall score were 0.84. Conclusions: This original QPSSE was found to be a reliable and valid tool for AIS treated conservatively with PSSE and for the patients’ clinicians.
Established and Evolving Roles of the Multifunctional Non-POU Domain-Containing Octamer-Binding Protein (NonO) and Splicing Factor Proline- and Glutamine-Rich (SFPQ)
Authors: Yu Danyang , Huang Ching-Jung , Tucker Haley O.
Published: January 2024

It has been more than three decades since the discovery of multifunctional factors, the Non-POU-Domain-Containing Octamer-Binding Protein, NonO, and the Splicing Factor Proline- and Glutamine-Rich, SFPQ. Some of their functions, including their participation in transcriptional and posttranscriptional regulation as well as their contribution to paraspeckle subnuclear body organization, have been well documented. In this review, we focus on several other established roles of NonO and SFPQ, including their participation in the cell cycle, nonhomologous end-joining (NHEJ), homologous recombination (HR), telomere stability, childhood birth defects and cancer. In each of these contexts, the absence or malfunction of either or both NonO and SFPQ leads to either genome instability, tumor development or mental impairment.
Convolutional Neural Network Approaches in Median Nerve Morphological Assessment from Ultrasound Images
Authors: Ando Shion , Loh Ping Yeap
Published: January 2024

Ultrasound imaging has been used to investigate compression of the median nerve in carpal tunnel syndrome patients. Ultrasound imaging and the extraction of median nerve parameters from ultrasound images are crucial and are usually performed manually by experts. The manual annotation of ultrasound images relies on experience, and intra- and interrater reliability may vary among studies. In this study, two types of convolutional neural networks (CNNs), U-Net and SegNet, were used to extract the median nerve morphology. To the best of our knowledge, the application of these methods to ultrasound imaging of the median nerve has not yet been investigated. Spearman’s correlation and Bland–Altman analyses were performed to investigate the correlation and agreement between manual annotation and CNN estimation, namely, the cross-sectional area, circumference, and diameter of the median nerve. The results showed that the intersection over union (IoU) of U-Net (0.717) was greater than that of SegNet (0.625). A few images in SegNet had an IoU below 0.6, decreasing the average IoU. In both models, the IoU decreased when the median nerve was elongated longitudinally with a blurred outline. The Bland–Altman analysis revealed that, in general, both the U-Net- and SegNet-estimated measurements showed 95% limits of agreement with manual annotation. These results show that these CNN models are promising tools for median nerve ultrasound imaging analysis.
Forest Disturbance Monitoring Using Cloud-Based Sentinel-2 Satellite Imagery and Machine Learning
Authors: Molnár Tamás , Király Géza
Published: January 2024

Forest damage has become more frequent in Hungary in the last decades, and remote sensing offers a powerful tool for monitoring them rapidly and cost-effectively. A combined approach was developed to utilise high-resolution ESA Sentinel-2 satellite imagery and Google Earth Engine cloud computing and field-based forest inventory data. Maps and charts were derived from vegetation indices (NDVI and Z∙NDVI) of satellite images to detect forest disturbances in the Hungarian study site for the period of 2017–2020. The NDVI maps were classified to reveal forest disturbances, and the cloud-based method successfully showed drought and frost damage in the oak-dominated Nagyerdő forest of Debrecen. Differences in the reactions to damage between tree species were visible on the index maps; therefore, a random forest machine learning classifier was applied to show the spatial distribution of dominant species. An accuracy assessment was accomplished with confusion matrices that compared classified index maps to field-surveyed data, demonstrating 99.1% producer, 71% user, and 71% total accuracies for forest damage and 81.9% for tree species. Based on the results of this study and the resilience of Google Earth Engine, the presented method has the potential to be extended to monitor all of Hungary in a faster, more accurate way using systematically collected field-data, the latest satellite imagery, and artificial intelligence.
Decision Fusion at Pixel Level of Multi-Band Data for Land Cover Classification—A Review
Authors: Papadopoulos Spiros , Koukiou Georgia , Anastassopoulos Vassilis
Published: January 2024

According to existing signatures for various kinds of land cover coming from different spectral bands, i.e., optical, thermal infrared and PolSAR, it is possible to infer about the land cover type having a single decision from each of the spectral bands. Fusing these decisions, it is possible to radically improve the reliability of the decision regarding each pixel, taking into consideration the correlation of the individual decisions of the specific pixel as well as additional information transferred from the pixels’ neighborhood. Different remotely sensed data contribute their own information regarding the characteristics of the materials lying in each separate pixel. Hyperspectral and multispectral images give analytic information regarding the reflectance of each pixel in a very detailed manner. Thermal infrared images give valuable information regarding the temperature of the surface covered by each pixel, which is very important for recording thermal locations in urban regions. Finally, SAR data provide structural and electrical characteristics of each pixel. Combining information from some of these sources further improves the capability for reliable categorization of each pixel. The necessary mathematical background regarding pixel-based classification and decision fusion methods is analytically presented.
Judgments of Learning Reactivity on Item-Specific and Relational Processing
Authors: Chang Minyu , Brainerd Charles
Published: January 2024

Judgments of learning (JOLs) reactivity refers to the finding that the mere solicitation of JOLs modifies subsequent memory performance. One theoretical explanation is the item-specific processing hypothesis, which posits that item-level JOLs redound to the benefit of later memory performance because they enhance item-specific processing. The current study was designed to test this account. We factorially manipulated the organization (blocked vs. randomized) of categorized lists and JOL condition (item-JOLs, list-JOLs, no-JOLs) between participants, and fit the dual-retrieval model to free recall data to pinpoint the underlying memory processes that were affected by JOL solicitation. Our results showed that item-level JOLs produced positive reactivity for randomized but not for blocked categorized lists. Moreover, we found that the positive JOL reactivity for randomized categorized lists was tied to a familiarity judgment process that is associated with gist processing, rather than to item-specific recollective processes. Thus, our results pose a challenge to the item-specific processing explanation of JOL reactivity. We argue that JOL reactivity is not restricted to item-specific processing; instead, whether JOLs predominantly engage participants with item-specific or relational processing depends on the interaction between learning stimuli and JOLs.
Microascaceae from the Marine Environment, with Descriptions of Six New Species
Authors: Wang Meng-Meng , Yang Shi-Yu , Li Qi , Zheng Yao , Ma He-He , Tu Ye-Hui , Li Wei , Cai Lei
Published: January 2024

Most reported members of Microascaceae that have been reported originate from the terrestrial environment, where they act as saprobes or plant pathogens. However, our understanding of their species diversity and distribution in the marine environment remains vastly limited, with only 22 species in nine genera having been reported so far. A survey of the fungal diversity in intertidal areas of China’s mainland has revealed the discovery of several Microascaceae strains from 14 marine algae and 15 sediment samples. Based on morphological characteristics and LSU-ITS-tef1-tub2 multilocus phylogeny using Bayesian inference and maximum likelihood methods, 48 strains were identified as 18 species belonging to six genera. Among these, six new species were discovered: Gamsia sedimenticola, Microascus algicola, M. gennadii, Scedosporium ellipsosporium, S. shenzhenensis, and S. sphaerospermum. Additionally, the worldwide distribution of the species within this family across various marine habitats was briefly reviewed and discussed. Our study expands the knowledge of species diversity and distribution of Microascaceae in the marine environment.
Research Progress on Surface Damage and Protection Strategies of Armature–Rail Friction Pair Materials for Electromagnetic Rail Launch
Authors: Wang Xing , Yao Pingping , Zhou Haibin , Fan Kunyang , Deng Minwen , Kang Li , Yuan Zihao , Lin Yongqiang
Published: January 2024

Electromagnetic rail launch technology has attracted increasing attention owing to its advantages in terms of range, firepower, and speed. However, due to electricity-magnetism-heat-force coupling, the surface of the armature–rail friction pair becomes severely damaged, which restricts the development of this technology. A series of studies have been conducted to reduce the damage of the armature–rail friction pair, including an analysis of the damage mechanism and protection strategies. In this study, various types of surface damage were classified into mechanical, electrical, and coupling damages according to their causes. This damage is caused by factors such as mechanical friction, mechanical impact, and electric erosion, either individually or in combination. Then, a detailed investigation of protection strategies for reducing damage is introduced, including material improvement through the use of novel combined deformation and heat treatment processes to achieve high strength and high conductivity, as well as surface treatment technologies such as structural coatings for wear resistance and functional coatings for ablation and melting resistance. Finally, future development prospects of armature–rail friction pair materials are discussed. This study provides a theoretical basis and directions for the development of high-performance materials for the armature–rail friction pair.
Semi-Analytical Approach and Green’s Function Method: A Comparison in the Analysis of the Interaction of a Moving Mass on an Infinite Beam on a Three-Layer Viscoelastic Foundation at the Stability Limit—The Effect of Damping of Foundation Materials
Authors: Dimitrovová Zuzana , Mazilu Traian
Published: January 2024

In this paper, the interaction of a mass moving uniformly on an infinite beam on a three-layer viscoelastic foundation is analyzed with the objective of determining the lowest velocity at the stability limit, called, in this context, the critical velocity. This issue is important for rail transport and, in particular, for the high-speed train, because the moving mass is the basic model of a vehicle, and the infinite beam on a three-layer viscoelastic foundation is the usual mechanical representation of the railway track. In addition to this, the advantages and disadvantages of the two implemented methods, namely, the semi-analytical approach and the Green’s function method, are summarized in terms of computational time, the precision of the obtained results, limitations, and the feasibility of implementation. All results are presented in a dimensionless form to cover a wide range of possible scenarios. Some results may be considered academic, however, results related to a particular railway track are also included. Particular attention is paid to the influence of the damping of materials in the foundation upon the critical velocity of the moving mass. Regarding the semi-analytical approach, it is demonstrated that the critical velocities can be obtained in an exact manner by tracing the branches of the so-called instability lines in the velocity–moving-mass plane. This analysis can be maintained within the real domain. As for the time series, they can be determined by a numerical inverse Laplace transform. Moreover, thanks to the analytical form of the final result in the Fourier domain, each value corresponding to a specific time instant can be obtained directly, that is, without the previous time history. Regarding the Green’s function method, this is used to verify a few points delimiting the stable and unstable regions of the moving mass with the help of the D-decomposition approach. Additionally, a numerical algorithm based on the Green’s function and convolution integral written for dimensionless quantities is used to calculate the time series of the moving mass. In addition to identifying the critical velocity of the moving mass, its connection with the critical velocity of the moving force is emphasized, and the possibility of validating the results on long finite beams using modal expansion is presented and described.
Ship Infrared Automatic Target Recognition Based on Bipartite Graph Recommendation: A Model-Matching Method
Authors: Zhang Haoxiang , Liu Chao , Ma Jianguang , Sun Hui
Published: January 2024

Deep learning technology has greatly propelled the development of intelligent and information-driven research on ship infrared automatic target recognition (SIATR). In future scenarios, there will be various recognition models with different mechanisms to choose from. However, in complex and dynamic environments, ship infrared (IR) data exhibit rich feature space distribution, resulting in performance variations among SIATR models, thus preventing the existence of a universally superior model for all recognition scenarios. In light of this, this study proposes a model-matching method for SIATR tasks based on bipartite graph theory. This method establishes evaluation criteria based on recognition accuracy and feature learning credibility, uncovering the underlying connections between IR attributes of ships and candidate models. The objective is to selectively recommend the optimal candidate model for a given sample, enhancing the overall recognition performance and applicability of the model. We separately conducted tests for the optimization of accuracy and credibility on high-fidelity simulation data, achieving Accuracy and EDMS (our credibility metric) of 95.86% and 0.7781. Our method improves by 1.06% and 0.0274 for each metric compared to the best candidate models (six in total). Subsequently, we created a recommendation system that balances two tasks, resulting in improvements of 0.43% (accuracy) and 0.0071 (EDMS). Additionally, considering the relationship between model resources and performance, we achieved a 28.35% reduction in memory usage while realizing enhancements of 0.33% (accuracy) and 0.0045 (EDMS).
Bi-Univalency of m-Fold Symmetric Functions Associated with a Generalized Distribution
Authors: Olatunji Sunday Oluwafemi , Sakar Fethiye Müge , Breaz Nicoleta , Aydoǧan Seher Melike , Oluwayemi Matthew Olanrewaju
Published: January 2024

The m-fold symmetric in terms of a generalized distribution series has not been considered in the literature. In this study, however, the authors investigated the bi-univalency of m-fold symmetric functions for the generalized distribution of two subclasses of analytic functions. The initial few coefficient bounds amS and a2mS are obtained for the two subclasses of functions defined and the results serve as a new generalization in this direction.
Mechanisms of Stock Selection and Its Capital Weighing in the Portfolio Design Based on the MACD-K-Means-Mean-VaR Model
Authors: Sukono  , Rosadi Dedi , Maruddani Di Asih I , Ibrahim Riza Andrian , Johansyah Muhamad Deni
Published: January 2024

When designing a stock portfolio, investors must select stocks with different characteristics and increasing price trends and weigh each capital. Both are fundamental to diversifying loss and profit. Therefore, the mechanisms that accommodate both are needed. Based on this, this research aims to design a stock selection and capital weighing mechanism using the MACD-K-means-Mean-VaR model. The moving average convergence–divergence (MACD) is used to analyze stock buying time, providing trend, momentum, and potential price reversal insights. Then, stocks with increasing price trends are clustered using K-means, a grouping simple pattern data method based on specific characteristics. The best stocks from each cluster are capital weighted using the mean value at risk (mean-VaR), a portfolio optimization model adjusting loss possibility to the investor’s acceptance tolerance. The mechanism is then applied to Indonesia’s 100 stock index data to analyze variable sensitivities and compare it with another model. The application reveals that all variables significantly impact portfolio return mean and VaR, suggesting the need for clustering and analyzing stock price movements in stock portfolio design. This research academically develops a portfolio design mechanism by clustering stocks and analyzing price movement trends. It enables investors to practically diversify and choose stocks with increasing price trends, reducing losses and increasing profit opportunities.
Reachable Set Estimation and Controller Design for Linear Time-Delayed Control System with Disturbances
Authors: Jiang Yongchun , Yang Hongli , Ivanov Ivan Ganchev
Published: January 2024

This paper investigates reachable set estimation and state-feedback controller design for linear time-delay control systems with bounded disturbances. By constructing an appropriate Lyapunov–Krasovskii functional, we obtain a delay-dependent condition, which determines the admissible bounding ellipsoid for the reachable set of the system we considered. Then, a sufficient condition in the form of liner matrix inequalities is given to solve the problem of controller design and reachable set estimation. Then, by minimizing the volume of the ellipsoid and solving the liner matrix inequality, we obtain the desired ellipsoid and controller gain. A comparative numerical example is given to show the effectiveness of our result.
Gibbs–Appell Equations in Finite Element Analysis of Mechanical Systems with Elements Having Micro-Structure and Voids
Authors: Vlase Sorin , Marin Marin , Itu Calin
Published: January 2024

In this paper, the authors propose the application of the Gibbs–Appell equations to obtain the equations of motion in the case of a mechanical system that has elements with a micro-polar structure, containing voids. Voids can appear as a result of the processing or manufacturing of the parts, or can be intentionally introduced. This research involves a model of the considered solid material containing voids. To determine the dynamic behavior of such a system, the Gibbs–Appell (GA) method is used to obtain the evolution equations, as an alternative to Lagrange’s classical description. The proposed method can be applied to any mechanical system consisting of materials with a micro-polar structure and voids. The study of such systems is interesting because the literature shows that even a reduce number of small voids can produce significant variations in physical behavior. The proposed method requires a smaller number of mathematical operations. To apply this method, the acceleration energy is calculated, which is then used to derive the equations. The method comes with advantages in the application to multibody systems having the mentioned properties and, in particular, in the study of robots and manipulators. Using the GA method, it is necessary to do a fewer differentiation operations than applying the Lagrange’s equations. This leads to a reduced amount of computation for obtaining the evolution equations.
Gender Predicts Differences in Acute Ischemic Cardioembolic Stroke Profile: Emphasis on Woman-Specific Clinical Data and Early Outcome—The Experience of Sagrat Cor Hospital of Barcelona Stroke Registry
Authors: Inogés Marc , Arboix Adrià , García-Eroles Luís , Sánchez-López María José
Published: January 2024

Background and Objectives: Acute ischemic cardioembolic stroke (CS) is a clinical condition with a high risk of death, and can lead to dependence, recurrence, and dementia. Materials and Methods: In this study, we evaluated gender differences and female-specific clinical data and early outcomes in 602 women diagnosed with CS from a total of 4600 consecutive acute stroke patients in a single-center hospital stroke registry over 24 years. A comparative analysis was performed in women and men in terms of demographics, cerebrovascular risk factors, clinical data, and early outcomes. Results: In a multivariate analysis, age, hypertension, valvular heart disease, obesity, and internal capsule location were independent variables associated with CS in women. The overall in-hospital mortality rate was similar, but the group of women had a greater presence of neurological deficits and a higher percentage of severe limitation at hospital discharge. After the multivariate analysis, age, altered consciousness, limb weakness, and neurological, respiratory, gastrointestinal, renal, cardiac and peripheral vascular complications were independent predictors related to early mortality in women. Conclusions: Women with CS showed a differential demographic and clinical profile and worse early outcomes than men. Advanced age, impaired consciousness, and medical complications were predictors of stroke severity in women with CS.
First-Principles Study of Cu Addition on Mechanical Properties of Ni3Sn4-Based Intermetallic Compounds
Authors: Yao Jinye , Wang Li , Guo Shihao , Li Xiaofu , Chen Xiangxu , Shang Min , Ma Haoran , Ma Haitao
Published: January 2024

Ni–Cu under-bump metallisation (UBM) can reduce stress and improve wetting ability in technology for electronic packaging technology advances with three-dimensional integrated circuit (3D IC) devices. The bond between the Sn-based solder and Ni–Cu UBM is affected by the formation of intermetallic compounds (IMCs), specifically Ni3Sn4 and (Ni,Cu)3Sn4. This paper investigates the mechanical properties of IMCs, which are critical in assessing the longevity of solder joints. First-principles calculations were carried out to investigate the phase stability, mechanical properties and electronic structures of Ni3Sn4, Ni2.5Cu0.5Sn4, Ni2.0Cu1.0Sn4, and Ni1.5Cu1.5Sn4 IMCs. The calculated formation enthalpies show that the doping of Cu atoms leads to a decrease in the stability of the phases and a reduction in the mechanical properties of the Ni3Sn4 crystal structure. As the concentration of Cu atoms in the Ni3Sn4 cells increases, the bulk modulus values of (Ni,Cu)3Sn4 formed with different compositions decrease from 107.78 GPa to 87.84 GPa, the shear modulus decreases from 56.64 GPa to 45.08 GPa, and the elastic modulus decreases from 144.59 GPa to 115.48 GPa, indicating that the doping of Cu atoms into the Ni3Sn4 cells may adversely affect their mechanical properties and increase the possibility of microcracking at the interface during actual service. The anisotropy of (Ni,Cu)3Sn4 is more significant than that of Ni3Sn4, with Ni2.0Cu1.0Sn4 showing the highest anisotropy. After evaluating the electronic structures, the metallic properties of Ni3Sn4 and the Ni2.5Cu0.5Sn4, Ni2.0Cu1.0Sn4, and Ni1.5Cu1.5Sn4 phases are revealed by electronic structure analysis. The total density of states (TDOS) for (Ni,Cu)3Sn4 structures is mainly influenced by Ni-d and Cu-d states. The addition of Cu atoms can increase the brittleness of Ni3Sn4. In addition, the region where d and p hybridisation occurs gradually increases with increasing Cu content. The electronic properties suggest that the binding energy between Ni and Sn atoms weakens with the addition of Cu atoms, resulting in a decrease in the elastic modulus. This research can serve as a valuable reference and theoretical guide for future applications of these materials.
Plasmodium chabaudi Merozoites Obtained through a Simpler Method Do Not Survive in Classically Activated Macrophages
Authors: Rodrigues Pedro Souto , Azeredo Milena de Farias , Almeida Natália de Souza , de Almeida Gisela Garcia Cabral Galaxe , Wanderley João Luiz Mendes , Seabra Sergio Henrique , DaMatta Renato Augusto
Published: January 2024

Malaria is caused by apicomplexan parasites of the Plasmodium genus. Plasmodium chabaudi is an excellent animal model for the study of human malaria caused by P. falciparum. Merozoites invade erythrocytes but are also found in other host cells including macrophages from the spleen and liver. Methodologies for obtaining merozoites usually involve treatment with protease inhibitors. However, merozoites obtained in this way may have their enzymatic profile altered and, therefore, are not ideal for cell-interaction assays. We report the obtainment of P. chabaudi merozoites naturally egressed from a synchronous erythrocyte population infected with schizonts forms. Merozoites had their infectivity and ultrastructure analyzed. Interaction assays were performed with mice erythrocytes and classically activated mice peritoneal macrophages, a very well-established classic model. Obtained merozoites were able to kill mice and efficiently infect erythrocytes. Interestingly, a lower merozoite:erythrocyte ratio resulted in a higher percentage of infected erythrocytes. We describe a simpler method for obtaining viable and infective merozoites. Classically activated macrophages killed merozoites, suggesting that these host cells may not serve as reservoirs for these parasites. These findings have implications for our understanding of P. chabaudi merozoite biology and may improve the comprehension of their host–parasite relationship.
Changes in Microbiota Composition during the Anaerobic Digestion of Macroalgae in a Three-Stage Bioreactor
Authors: Vasiliauskienė Dovilė , Pranskevičius Mantas , Dauknys Regimantas , Urbonavičius Jaunius , Lukša Juliana , Burko Vadym , Zagorskis Alvydas
Published: January 2024

The use of microalgae as a raw material for biogas production is promising. Macroalgae were mixed with cattle manure, wheat straw, and an inoculant from sewage sludge. Mixing macroalgae with co-substrates increased biogas and methane yield. The research was carried out using a three-stage bioreactor. During biogas production, the dynamics of the composition of the microbiota in the anaerobic chamber of the bioreactor was evaluated. The microbiota composition at different organic load rates (OLRs) of the bioreactor was evaluated. This study also demonstrated that in a three-stage bioreactor, a higher yield of methane in biogas was obtained compared to a single-stage bioreactor. It was found that the most active functional pathway of methane biosynthesis is PWY-6969, which proceeds via the TCA cycle V (2-oxoglutarate synthase). Microbiota composition and methane yield depended on added volatile solids (VSadded). During the research, it was found that after reducing the ORL from 2.44 to 1.09 kg VS/d, the methane yield increased from 175.2 L CH4/kg VSadded to 323.5 L CH4/kg VSadded.
Fused Enzyme Glucose-6-Phosphate Dehydrogenase::6-Phosphogluconolactonase (G6PD::6PGL) as a Potential Drug Target in Giardia lamblia, Trichomonas vaginalis, and Plasmodium falciparum
Authors: Morales-Luna Laura , Vázquez-Bautista Montserrat , Martínez-Rosas Víctor , Rojas-Alarcón Miriam Abigail , Ortega-Cuellar Daniel , González-Valdez Abigail , Pérez de la Cruz Verónica , Arreguin-Espinosa Roberto , Rodríguez-Bustamante Eduardo , Rodríguez-Flores Eden , Hernández-Ochoa Beatriz , Gómez-Manzo Saúl
Published: January 2024

Several microaerophilic parasites such as Giardia lamblia, Trichomonas vaginalis, and Plasmodium falciparum are major disease-causing organisms and are responsible for spreading infections worldwide. Despite significant progress made in understanding the metabolism and molecular biology of microaerophilic parasites, chemotherapeutic treatment to control it has seen limited progress. A current proposed strategy for drug discovery against parasitic diseases is the identification of essential key enzymes of metabolic pathways associated with the parasite’s survival. In these organisms, glucose-6-phosphate dehydrogenase::6-phosphogluconolactonase (G6PD:: 6PGL), the first enzyme of the pentose phosphate pathway (PPP), is essential for its metabolism. Since G6PD:: 6PGL provides substrates for nucleotides synthesis and NADPH as a source of reducing equivalents, it could be considered an anti-parasite drug target. This review analyzes the anaerobic energy metabolism of G. lamblia, T. vaginalis, and P. falciparum, with a focus on glucose metabolism through the pentose phosphate pathway and the significance of the fused G6PD:: 6PGL enzyme as a therapeutic target in the search for new drugs.
An Indirect Fluorescence Microscopy Method to Assess Vaginal Lactobacillus Concentrations
Authors: Lima Ângela , Muzny Christina A. , Cerca Nuno
Published: January 2024

Lactobacillus species are the main colonizers of the vaginal microbiota in healthy women. Their absolute quantification by culture-based methods is limited due to their fastidious growth. Flow cytometry can quantify the bacterial concentration of these bacteria but requires the acquisition of expensive equipment. More affordable non-culturable methods, such as fluorescence microscopy, are hampered by the small size of the bacteria. Herein, we developed an indirect fluorescence microscopy method to determine vaginal lactobacilli concentration by determining the correlation between surface area bacterial measurement and initial concentration of an easily cultivable bacterium (Escherichia coli) and applying it to lactobacilli fluorescence microscopy counts. In addition, vaginal lactobacilli were quantified by colony-forming units and flow cytometry in order to compare these results with the indirect method results. The colony-forming-unit values were lower than the results obtained from the other two techniques, while flow cytometry and fluorescence microscopy results agreed. Thus, our developed method was able to accurately quantify vaginal lactobacilli.
Regulatory Role of GgaR (YegW) for Glycogen Accumulation in Escherichia coli K-12
Authors: Saito Shunsuke , Kobayashi Ikki , Hoshina Motoki , Uenaka Emi , Sakurai Atsushi , Imamura Sousuke , Shimada Tomohiro
Published: January 2024

Glycogen, the stored form of glucose, accumulates upon growth arrest in the presence of an excess carbon source in Escherichia coli and other bacteria. Chromatin immunoprecipitation screening for the binding site of a functionally unknown GntR family transcription factor, YegW, revealed that the yegTUV operon was a single target of the E. coli genome. Although none of the genes in the yegTUV operon have a clear function, a previous study suggested their involvement in the production of ADP-glucose (ADPG), a glycogen precursor. Various validation through in vivo and in vitro experiments showed that YegW is a single-target transcription factor that acts as a repressor of yegTUV, with an intracellular concentration of consistently approximately 10 molecules, and senses ADPG as an effector. Further analysis revealed that YegW repressed glycogen accumulation in response to increased glucose concentration, which was not accompanied by changes in the growth phase. In minimal glucose medium, yegW-deficient E. coli promoted glycogen accumulation, at the expense of poor cell proliferation. We concluded that YegW is a single-target transcription factor that senses ADPG and represses glycogen accumulation in response to the amount of glucose available to the cell. We propose renaming YegW to GgaR (repressor of glycogen accumulation).