bluuebunny/crossref_metadata_2025 huggingface dataset:
Aqueous Dispersion of Manganese–Zinc Ferrite Nanoparticles Protected by PEG as a T2 MRI Temperature Contrast Agent
Authors: Lachowicz Dorota , Kmita Angelika , Gajewska Marta , Trynkiewicz Elżbieta , Przybylski Marek , Russek Stephen E. , Stupic Karl F. , Woodrum David A. , Gorny Krzysztof R. , Celinski Zbigniew J. , Hankiewicz Janusz H.
Published: November 2023

Mixed manganese–zinc ferrite nanoparticles coated with PEG were studied for their potential usefulness in MRI thermometry as temperature-sensitive contrast agents. Particles in the form of an 8.5 nm core coated with a 3.5 nm layer of PEG were fabricated using a newly developed, one-step method. The composition of Mn0.48Zn0.46Fe2.06O4 was found to have a strong thermal dependence of magnetization in the temperature range between 5 and 50 °C. Nanoparticles suspended in an agar gel mimicking animal tissue and showing non-significant impact on cell viability in the biological test were studied with NMR and MRI over the same temperature range. For the concentration of 0.017 mg/mL of Fe, the spin–spin relaxation time T2 increased from 3.1 to 8.3 ms, while longitudinal relaxation time T1 shows a moderate decrease from 149.0 to 125.1 ms. A temperature map of the phantom exposed to the radial temperature gradient obtained by heating it with an 808 nm laser was calculated from T2 weighted spin-echo differential MR images. Analysis of temperature maps yields thermal/spatial resolution of 3.2 °C at the distance of 2.9 mm. The experimental relaxation rate R2 data of water protons were compared with those obtained from calculations using a theoretical model incorporating the motion averaging regime.
Quantum Biology and the Potential Role of Entanglement and Tunneling in Non-Targeted Effects of Ionizing Radiation: A Review and Proposed Model
Authors: Matarèse Bruno F. E. , Rusin Andrej , Seymour Colin , Mothersill Carmel
Published: November 2023

It is well established that cells, tissues, and organisms exposed to low doses of ionizing radiation can induce effects in non-irradiated neighbors (non-targeted effects or NTE), but the mechanisms remain unclear. This is especially true of the initial steps leading to the release of signaling molecules contained in exosomes. Voltage-gated ion channels, photon emissions, and calcium fluxes are all involved but the precise sequence of events is not yet known. We identified what may be a quantum entanglement type of effect and this prompted us to consider whether aspects of quantum biology such as tunneling and entanglement may underlie the initial events leading to NTE. We review the field where it may be relevant to ionizing radiation processes. These include NTE, low-dose hyper-radiosensitivity, hormesis, and the adaptive response. Finally, we present a possible quantum biological-based model for NTE.
Pan-Inhibition of Protein Disulfide Isomerase Caused Cell Death through Disrupting Cellular Proteostasis in Pancreatic Ductal Adenocarcinoma Cells
Authors: Hung Ching-Sheng , Lee Kun-Lin , Huang Wei-Jan , Su Fang-He , Liang Yu-Chih
Published: November 2023

The protein disulfide isomerase (PDI) family is a group of thioredoxin endoplasmic reticulum (ER)-resident enzymes and molecular chaperones that play crucial roles in the correct folding of proteins. PDIs are upregulated in multiple cancer types and are considered a novel target for cancer therapy. In this study, we found that a potent pan-PDI inhibitor, E64FC26, significantly decreased the proliferation of pancreatic ductal adenocarcinoma (PDAC) cells. As expected, E64FC26 treatment increased ER stress and the unfolded protein response (UPR), as evidenced by upregulation of glucose-regulated protein, 78-kDa (GRP78), phosphorylated (p)-PKR-like ER kinase (PERK), and p-eukaryotic initiation factor 2α (eIF2α). Persistent ER stress was found to lead to apoptosis, ferroptosis, and autophagy, all of which are dependent on lysosomal functions. First, there was little cleaved caspase-3 in E64FC26-treated cells according to Western blotting, but a higher dose of E64FC26 was needed to induce caspase activity. Then, E64FC26-induced cell death could be reversed by adding the iron chelator, deferoxamine, and the reactive oxygen species scavengers, ferrostatin-1 and N-acetylcysteine. Furthermore, the autophagosome-specific marker, light chain 3B (LC3B)-II, increased, but the autolysosome marker, sequestosome 1 (SQSTM1)/p62, was not degraded in E64FC26-treated cells. Using the FUW mCherry-LC3 plasmid and acridine orange staining, we also discovered a lower number of acidic vesicles, such as autolysosomes and mature lysosomes, in E64FC26-treated cells. Finally, E64FC26 treatment increased the cathepsin L precursor (pre-CTSL) but decreased mature CTSL expression according to Western blotting, indicating a defective lysosome. These results suggested that the PDI inhibitor, E64FC26, might initially impede proper folding of proteins, and then induce ER stress and disrupt proteostasis, subsequently leading to lysosomal defects. Due to defective lysosomes, the extents of apoptosis and ferroptosis were limited, and fusion with autophagosomes was blocked in E64FC26-treated cells. Blockade of autolysosomal formation further led to the autophagic cell death of PDAC cells.
Inflammatory and Metabolic Signaling Interfaces of the Hypertrophic and Senescent Chondrocyte Phenotypes Associated with Osteoarthritis
Authors: Horváth Emőke , Sólyom Árpád , Székely János , Nagy Előd Ernő , Popoviciu Horațiu
Published: November 2023

Osteoarthritis (OA) is a complex disease of whole joints with progressive cartilage matrix degradation and chondrocyte transformation. The inflammatory features of OA are reflected in increased synovial levels of IL-1β, IL-6 and VEGF, higher levels of TLR-4 binding plasma proteins and increased expression of IL-15, IL-18, IL-10 and Cox2, in cartilage. Chondrocytes in OA undergo hypertrophic and senescent transition; in these states, the expression of Sox-9, Acan and Col2a1 is suppressed, whereas the expression of RunX2, HIF-2α and MMP-13 is significantly increased. NF-kB, which triggers many pro-inflammatory cytokines, works with BMP, Wnt and HIF-2α to link hypertrophy and inflammation. Altered carbohydrate metabolism and the upregulation of GLUT-1 contribute to the formation of end-glycation products that trigger inflammation via the RAGE pathway. In addition, a glycolytic shift, increased rates of oxidative phosphorylation and mitochondrial dysfunction generate reactive oxygen species with deleterious effects. An important surveyor mechanism, the YAP/TAZ signaling system, controls chondrocyte differentiation, inhibits ageing by protecting the nuclear envelope and suppressing NF-kB, MMP-13 and aggrecanases. The inflammatory microenvironment and synthesis of key matrix components are also controlled by SIRT1 and mTORc. Senescent chondrocytes represent the functional end stage of hypertrophic differentiation and characteristically upregulate p16 and p21, but also a variety of inflammatory cytokines, chemokines and metalloproteinases, developing the senescence-associated secretory phenotype. Senolysis with dendrobin, miR29b-5p and other agents has been shown to be efficient under experimental conditions, and appears to be a promising tool for the treatment of OA, as it restores COL2A1 and aggrecan synthesis, suppressing NF-kB and destructive metalloproteinases.
Dependency of B-Cell Acute Lymphoblastic Leukemia and Multiple Myeloma Cell Lines on MEN1 Extends beyond MEN1–KMT2A Interaction
Authors: Wolffhardt Tatjana Magdalena , Ketzer Franz , Telese Stefano , Wirth Thomas , Ushmorov Alexey
Published: November 2023

Menin/MEN1 is a scaffold protein that participates in proliferation, regulation of gene transcription, DNA damage repair, and signal transduction. In hematological malignancies harboring the KMT2A/MLL1 (MLLr) chromosomal rearrangements, the interaction of the oncogenic fusion protein MLLr with MEN1 has been shown to be essential. MEN1 binders inhibiting the MEN1 and KMT2A interaction have been shown to be effective against MLLr AML and B-ALL in experimental models and clinical studies. We hypothesized that in addition to the MEN1–KMT2A interaction, alternative mechanisms might be instrumental in the MEN1 dependency of leukemia. We first mined and analyzed data from publicly available gene expression databases, finding that the dependency of B-ALL cell lines on MEN1 did not correlate with the presence of MLLr. Using shRNA-mediated knockdown, we found that all tested B-ALL cell lines were sensitive to MEN1 depletion, independent of the underlying driver mutations. Most multiple myeloma cell lines that did not harbor MLLr were also sensitive to the genetic depletion of MEN1. We conclude that the oncogenic role of MEN1 is not limited to the interaction with KMT2A. Our results suggest that targeted degradation of MEN1 or the development of binders that induce global changes in the MEN1 protein structure may be more efficient than the inhibition of individual MEN1 protein interactions.
Relationship between Nest and Body Temperature and Microclimate in the Paper Wasp Polistes dominula
Authors: Kovac Helmut , Nagy Julia Magdalena , Käfer Helmut , Stabentheiner Anton
Published: November 2023

The paper wasp Polistes dominula is a thermophilic species originating from the Mediterranean climate, but is now widely spread in Europe. They live in quite differing habitats; and as synanthropic species, they have been established in human settlement areas. They build a single small comb at protected places with a favorable microclimate. We measured the temperature of the wasps, the nests and their environment at typical nesting sides in Austria (Europe) in the temperate climate, in order to reveal relationships between nest and body temperature and the habitats’ microclimate. The temperatures of the comb and of the wasps’ body were in a wide range (~20–37 °C) above the ambient air temperature at the nest. This is an advantage as higher temperatures accelerate the development speed of the brood. However, the mean comb temperature did not exceed approximately 38.6 °C. This was managed by cooling efforts of the adult wasps. The ambient air temperature near the nest (~1–2 cm) was always clearly elevated above the ambient air temperature at a local standard weather station in the habitat. A comparison with climate-model-generated macroclimate data revealed the necessity of measuring microclimate data for a reliable description of the insects’ thermal environment.
Interspecific Host Variation and Biotic Interactions Drive Pathogen Community Assembly in Chinese Bumblebees
Authors: Chen Huanhuan , Zhang Guangshuo , Ding Guiling , Huang Jiaxing , Zhang Hong , Vidal Mayra C. , Corlett Richard T. , Liu Cong , An Jiandong
Published: November 2023

Bumblebees have been considered one of the most important pollinators on the planet. However, recent reports of bumblebee decline have raised concern about a significant threat to ecosystem stability. Infectious diseases caused by multiple pathogen infections have been increasingly recognized as an important mechanism behind this decline worldwide. Understanding the determining factors that influence the assembly and composition of pathogen communities among bumblebees can provide important implications for predicting infectious disease dynamics and making effective conservation policies. Here, we study the relative importance of biotic interactions versus interspecific host resistance in shaping the pathogen community composition of bumblebees in China. We first conducted a comprehensive survey of 13 pathogens from 22 bumblebee species across China. We then applied joint species distribution modeling to assess the determinants of pathogen community composition and examine the presence and strength of pathogen–pathogen associations. We found that host species explained most of the variations in pathogen occurrences and composition, suggesting that host specificity was the most important variable in predicting pathogen occurrences and community composition in bumblebees. Moreover, we detected both positive and negative associations among pathogens, indicating the role of competition and facilitation among pathogens in determining pathogen community assembly. Our research demonstrates the power of a pluralistic framework integrating field survey of bumblebee pathogens with community ecology frameworks to understand the underlying mechanisms of pathogen community assembly.
A Hydro-Powered Climate-Neutral Pump: Full Cycle Simulation and Performance Evaluation
Authors: Al Qubeissi Mansour , Beard Scott Daniel
Published: November 2023

This paper presents a parametric study of the multistorey hydro-powered pump, known as ‘Bunyip’, which has demonstrated significant potential in contributing to rural regions. The study is aimed at understanding the underlying physics of the system and ways to enhance its hydraulic performance. A transient three-dimensional model using the commercial Computational Fluid Dynamics (CFD) tool Ansys-Fluent is utilized to gain insights into its fundamental flow mechanics, operational efficiency, standard capacity, and relative delivery. The investigation involves an initial assessment of performance for three Bunyip devices based on manufacturing data. A parametric analysis is conducted for the dataset generated through meticulous application and numerical modelling. The CFD results are validated against experimental data. Three main design configurations are considered, and 58 sets of varied input parameters are examined. The best design configuration is evaluated against five cases of conventional hydro-power pump systems. The results indicate that a smaller diameter of the pressure chamber and a higher supply head lead to higher pressure, achieving a target head of 3 m with 15% efficiency and a flowrate of 11.82 L/min.
Individualization of Duration of Dual Antiplatelet Therapy after Coronary Stenting: A Comprehensive, Evidence-Based Review
Authors: Carciotto Gabriele , Costa Francesco , Garcia-Ruiz Victoria , Galli Mattia , Soraci Emmanuele , Magliarditi Alberto , Teresi Lucio , Nasso Enrica , Carerj Scipione , Di Bella Gianluca , Micari Antonio , De Luca Giuseppe
Published: November 2023

Dual antiplatelet therapy (DAPT), comprising aspirin and a P2Y12 receptor inhibitor, is the cornerstone of post-percutaneous coronary intervention treatment to prevent stent thrombosis and reduce the risk of adverse cardiovascular events. The selection of an optimal DAPT regimen, considering the interplay of various antiplatelet agents, patient profiles, and procedural characteristics, remains an evolving challenge. Traditionally, a standard duration of 12 months has been recommended for DAPT in most patients. While contemporary guidelines provide general frameworks, DAPT modulation with longer or shorter treatment courses followed by aspirin or P2Y12 inhibitor monotherapy are evolving towards an individualized strategy to optimize the balance between efficacy and safety. This review comprehensively examines the current landscape of DAPT strategies after coronary stenting, with a focus on emerging evidence for treatment individualization.
Novel Genetic Microvascular Dysplasia Causing Hypoperfusion of Cardiac, Renal, and Cerebral Circulation
Authors: Frustaci Andrea , Cianci Rosario , Verardo Romina , Cerbelli Bruna , D’Asdia Maria Cecilia , De Luca Alessandro
Published: November 2023

Background: Microvascular disorders represent an uncommon site of tissue hypo-perfusion and damage. Various genetic and acquired causes can be involved. A 65-year-old man was admitted because of refractory angina, which he had had since the age of 30 years, micro-hematuria, and recurrent transitory ischemic attacks from the age of 64. Methods: Hematochemical studies, ECG, Holter monitoring, 2D-echo, cardiac magnetic resonance (CMR), CTA of cerebral vessels, endomyocardial coronary angiography, and kidney biopsy processes were undertaken. Gene mutation analysis was conducted using next-generation sequencing, which included more than 5000 genes associated with inherited diseases. Results: Hematochemical findings were unremarkable. The ECG, Holter, 2D-echo, and CTA of brain vessels were normal. Cerebral magnetic resonance showed the presence of multiple small foci of ischemia. Coronary and ventricular angiography showed normal arteries with remarkably slow flow and multiple biventricular micro-aneurysms. At the endomyocardial biopsy, five of seven arterioles presented severe lumen obstruction due to hypertrophy and disarray of the muscular coat. Similarly, obstructed pre-glomerular arteries with glomerular sclerosis were seen at the renal biopsy. Genetics identified mutations in the ABCC6, MMP2, and XYLT1 genes, which play pivotal roles in the extracellular matrix. Conclusion: This study described a new genetic microvascular obstructive disease causing progressive hypo-perfusion of the human brain, heart, and kidney.
In Vitro Investigation into the Effect of Cryopreservation on the Mechanical Characteristics of Dental Hard Tissues
Authors: De Roo Noëmi M. C. , Toulouse Kaat , Thierens Laurent A. M. , Henry Silke , De Buyser Stefanie , Temmerman Liesbeth , Verbeeck Ronald M. H. , De Pauw Guy A. M.
Published: November 2023

Previous research has reported on hidden damage within the dentin introduced by cryopreservation, but the effect on the mechanical properties of the hard tissues at tooth level remains unclear. The main objective of this study is to investigate the effect of cryopreservation on the mechanical properties of teeth. A matched sample of 234 premolars of 117 children (9 ≤ age ≤ 16 years), bilaterally extracted for orthodontic reasons, were included. For each child, one tooth was randomly allocated to the cryopreservation group and the contralateral tooth was assigned to the control group. Static compression tests were performed to determine load to failure, stiffness, and toughness. In a subgroup of 20 teeth, a cyclic preloading or chewing simulation was performed. Additionally, the fracture mode was determined, and the microstructure of the fractured surfaces was examined using a scanning electron microscope (SEM). Linear mixed model analyses could not detect a statistical difference in the mean load to failure (p = 0.549), mean toughness (p = 0.968), or mean stiffness (p = 0.150) between cryopreserved and non-cryopreserved teeth. No significant difference in load to failure after cyclic preloading was detected between groups (p = 0.734). SEM analysis revealed comparable fracture characteristics between groups. It is concluded that cryopreservation does not affect the mean load to failure, stiffness, or toughness of teeth, indicating that hidden damage in the dentin is not critical at tooth level.
Using IRTree Models to Promote Selection Validity in the Presence of Extreme Response Styles
Authors: Quirk Victoria L. , Kern Justin L.
Published: November 2023

The measurement of psychological constructs is frequently based on self-report tests, which often have Likert-type items rated from “Strongly Disagree” to “Strongly Agree”. Recently, a family of item response theory (IRT) models called IRTree models have emerged that can parse out content traits (e.g., personality traits) from noise traits (e.g., response styles). In this study, we compare the selection validity and adverse impact consequences of noise traits on selection when scores are estimated using a generalized partial credit model (GPCM) or an IRTree model. First, we present a simulation which demonstrates that when noise traits do exist, the selection decisions made based on the IRTree model estimated scores have higher accuracy rates and have less instances of adverse impact based on extreme response style group membership when compared to the GPCM. Both models performed similarly when there was no influence of noise traits on the responses. Second, we present an application using data collected from the Open-Source Psychometrics Project Fisher Temperament Inventory dataset. We found that the IRTree model had a better fit, but a high agreement rate between the model decisions resulted in virtually identical impact ratios between the models. We offer considerations for applications of the IRTree model and future directions for research.
Integrating k-means Clustering and LSTM for Enhanced Ship Heading Prediction in Oblique Stern Wave
Authors: Xu Jinya , Gong Jiaye , Wang Luyao , Li Yunbo
Published: November 2023

The stability of navigation in waves is crucial for ships, and the effect of the waves on navigation stability is complicated. Hence, the LSTM neural network technique is applied to predict the course changing of a ship in different wave conditions, where K-means clustering analysis is used for the category of the ship’s navigation data to improve the quality of the database. In this paper, the effect of the initial database obtained by the K-means clustering analysis on prediction accuracy is studied first. Then, different input features are used to establish the database to train the neural network, and the influence of the database by different input features on the accuracy of the navigation prediction is discussed and analyzed. Finally, multi-task learning is used to make the neural network better predict the navigation in various wave conditions. Using the improved neural network model, the course of an autopilot ship in waves is predicted, and the results show that the current database and the neural network model are accurate enough for the course prediction of the autopilot ship in waves.
High Light Intensity and CO2 Enrichment Synergistically Mitigated the Stress Caused by Low Salinity in Pyropia yezoensis
Authors: Wu Hailong , Wang Chuchu , Li He , Chen Jiang , Zhang Jiankai , Luo Zixue , Cheng Fangsheng , Xu Juntian
Published: November 2023

Macroalgae, playing a crucial role in coastal marine ecosystems, are subject to multiple environmental challenges due to tidal and seasonal alterations. In this work, we investigated the physiological responses of Pyropia yezoensis to ocean acidification (ambient CO2 (AC: 400 μatm) and elevated CO2 (HC: 1000 μatm)) under changing salinity (20, 30 psu) and light intensities (50, 100 μmol photons m−2 s−1) by measuring the growth, pigment content, chlorophyll fluorescence, and soluble sugar content. The key results are the following: (1) P. yezoensis exhibited better growth under normal salinity (30 psu) compared to hyposaline conditions (20 psu). (2) Intermediate light intensity increased phycoerythrin content, ultimately enhancing thalli growth without significant changes to the contents of chlorophyll a and carotenoids. (3) Ocean acidification alleviated hyposaline stress by enhancing pigment production in P. yezoensis only at a salinity of 20 psu, highlighting the complex interplay of these environmental factors. These findings indicate that higher light intensities and elevated pCO2 levels could mitigate the stress caused by low salinity.
Design of Experiments Technique Applied to Artificial Neural Network Models for FPSO Mooring System Analysis
Authors: Nikkhah Ehsan , Fernandes Antonio Carlos , Caprace Jean-David
Published: November 2023

Online monitoring of mooring system response for the FPSO platform in any operational condition is so far challenging for machine learning (ML). This paper presents a new dynamic NARX ANN model for time series of mooring tension and a static MLP model for the offset chart prediction of a taut-leg moored FPSO with different working scenarios. A novel method for supervised feature selection of the dataset was applied to determine the most influential design features. Additionally, a design of experiments (DOE) technique was implemented for test matrix creation, simulation, database generation, and supervised selection characteristics in ML. The DOE analysis revealed that the mooring configuration, platform loading condition, and environmental loads alter the platform’s six-degree-of-freedom motion response patterns. These input data were used to predict the mooring tension and the offset chart of the floater. The results include the fair values of statistical error for mooring tension (R2 = 0.8–0.98, E ≈ 1.3–5.7%, RMSE ≈ 6–66 kN) and platform offset (E ≈ 0.1–1 m) prediction when testing the trained models with unseen data representing new operational conditions. Faster convergence can be achieved by adding non-numeric (string) input values to dataset numeric features. Supervised feature selection of the dataset is a step forward in ML to improve prediction accuracy.
Machine Learning Model as a Useful Tool for Prediction of Thyroid Nodules Histology, Aggressiveness and Treatment-Related Complications
Authors: Dell’Era Valeria , Perotti Alan , Starnini Michele , Campagnoli Massimo , Rosa Maria Silvia , Saino Irene , Aluffi Valletti Paolo , Garzaro Massimiliano
Published: November 2023

Thyroid nodules are very common, 5–15% of which are malignant. Despite the low mortality rate of well-differentiated thyroid cancer, some variants may behave aggressively, making nodule differentiation mandatory. Ultrasound and fine-needle aspiration biopsy are simple, safe, cost-effective and accurate diagnostic tools, but have some potential limits. Recently, machine learning (ML) approaches have been successfully applied to healthcare datasets to predict the outcomes of surgical procedures. The aim of this work is the application of ML to predict tumor histology (HIS), aggressiveness and post-surgical complications in thyroid patients. This retrospective study was conducted at the ENT Division of Eastern Piedmont University, Novara (Italy), and reported data about 1218 patients who underwent surgery between January 2006 and December 2018. For each patient, general information, HIS and outcomes are reported. For each prediction task, we trained ML models on pre-surgery features alone as well as on both pre- and post-surgery data. The ML pipeline included data cleaning, oversampling to deal with unbalanced datasets and exploration of hyper-parameter space for random forest models, testing their stability and ranking feature importance. The main results are (i) the construction of a rich, hand-curated, open dataset including pre- and post-surgery features (ii) the development of accurate yet explainable ML models. Results highlight pre-screening as the most important feature to predict HIS and aggressiveness, and that, in our population, having an out-of-range (Low) fT3 dosage at pre-operative examination is strongly associated with a higher aggressiveness of the disease. Our work shows how ML models can find patterns in thyroid patient data and could support clinicians to refine diagnostic tools and improve their accuracy.
Use of Three-Dimensional Cell Culture Models in Drug Assays for Anti-Cancer Agents in Oral Cancer: Protocol for a Scoping Review
Authors: Freitas de Morais Everton , Siquara da Rocha Leonardo de Oliveira , de Souza Santos John Lenon , Freitas Raíza Dias , Souza Bruno Solano de Freitas , Coletta Ricardo D. , Gurgel Rocha Clarissa A.
Published: November 2023

Advances in the development of pharmacological treatment in oral cancer require tumor models capable of simulating the complex biology of the tumor microenvironment. The spread of three-dimensional models has changed the scenery of in vitro cell culture techniques, contributing to translational oncology. Still, the full extent of their application in preclinical drug trials is yet to be understood. Therefore, the present scoping review protocol was established to screen the literature on using three-dimensional cell culture models in drug-testing assays in the context of oral cancer. This scoping review will be conducted based on the guidelines established by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review guidelines (PRISMA-ScR). We will search the PubMed/Medline, Web of Science, Scopus, and Embase databases, as well as the gray literature, including peer-reviewed research articles involving 3D models applied to drug-assessment assays in oral cancer published from 1 March 2013 until 1 March 2023. Data will be charted, and findings will be described according to the predetermined questions of interest. We will present these findings in a narrative manner.
Diversity of Silica-Scaled Chrysophytes in the Steppe Zone of the Southern Urals with a Description of a New Species from the Genus Mallomonas
Authors: Ignatenko Marina , Gusev Evgeniy , Yatsenko-Stepanova Tatyana
Published: November 2023

This paper is devoted to the study of the flora of silica-scaled chrysophytes in water bodies of the steppe zone of the Southern Urals (Russia). Twenty-four taxa were identified via scanning and transmission electron microscopy, twenty of which are representatives of the genus Mallomonas Perty, while four are species of the genus Synura Ehrenberg. In the course of the study, a species new to science from the genus Mallomonas, M. baturinae sp. nov., was described. This species belongs to the section Papillosae. The stomatocyst of M. doignonii was described. For the first time in Russia and for the third time since description, M. phasma and M. solea-ferrea var. irregularis were reported in the studied area. Here, their extended description is provided with illustrations of their scales in detail. Some rare taxa for the flora of Russia have been identified: M. doignonii, M. pillula f. exannulata, and M. pillula f. valdiviana. One taxon of the genus Mallomonas has not been identified to a species level and is probably a taxon new to science.
Management of Upper-Limb Spasticity Using Modern Rehabilitation Techniques versus Botulinum Toxin Injections Following Stroke
Authors: Bumbea Ana Maria , Rogoveanu Otilia Constantina , Turcu-Stiolica Adina , Pirici Ionica , Cioroianu George , Stanca Diana Iulia , Criciotoiu Oana , Biciusca Viorel , Traistaru Rodica Magdalena , Caimac Danut Visarion
Published: November 2023

Our purpose is to emphasize the role of botulinum toxin in spasticity therapy and functional recovery in patients following strokes. Our retrospective study compared two groups, namely ischemic and hemorrhagic stroke patients. The study group (BT group) comprised 80 patients who received focal botulinum toxin as therapy for an upper limb with spastic muscle three times every three months. The control group (ES group) comprised 80 patients who received only medical rehabilitation consisting of electrostimulation and radial shockwave therapy for the upper limb, which was applied three times every three months. Both groups received the same stretching program for spastic muscles as a home training program. We evaluated the evolution of the patients using muscle strength, Ashworth, Tardieu, Frenchay, and Barthel scales. The analysis indicated a statistically significant difference between the two groups for all scales, with better results for the BT group (p < 0.0001 for all scales). In our study, the age at disease onset was an important prediction factor for better recovery in both groups but not in all scales. Better recovery was obtained for younger patients (in the BT group, MRC scale: rho = −0.609, p-value < 0.0001; Tardieu scale: rho = −0.365, p-value = 0.001; in the ES group, MRC scale: rho = −0.445, p-value < 0.0001; Barthel scale: rho = −0.239, p-value = 0.033). Our results demonstrated the effectiveness of botulinum toxin therapy compared with the rehabilitation method, showing a reduction of the recovery time of the upper limb, as well as an improvement of functionality and a reduction of disability. Although all patients followed a specific kinetic program, important improvements were evident in the botulinum toxin group.
Advances in Smart Materials and Structures
Authors: Wang Bing , Lee Tung Lik , Qin Yang
Published: November 2023

Smart materials and structures are capable of active or passive changes in terms of shapes (geometries), properties, and mechanical or electromagnetic responses, in reaction to an external stimulus, such as light, temperature, stress, moisture, and electric or magnetic fields [...]
Comparison of Wear Resistance of Overlay Welded Layers and Thermal Sprayed Coatings in Real Conditions
Authors: Szymura Michał , Gąsiorek Grzegorz , Czupryński Artur , Kwaśny Waldemar , Kvasnytskyi Viktor
Published: November 2023

Tribological tests in real conditions enable obtaining full data on the life of interacting machine parts. This article presents the results of operational tests on the elements of the support ring guidance system in a vertical ball-race mill. The guide and active armour operate under abrasive wear conditions with moderate-impact loads. The wear resistance of elements with overlay welding layers deposited with flux cored wire with a structure of high-alloy chrome cast iron and with a coating flame-sprayed with nickel-based powder was compared. The wear intensity of the overlay weld deposits was much lower than that of the sprayed coatings. The scope of this study also included the analysis of the chemical and phase composition, macro- and microscopic metallographic examinations, and the measurement of the hardness of the deposited layers and coatings.
Analyzing Employee Attrition Using Explainable AI for Strategic HR Decision-Making
Authors: Marín Díaz Gabriel , Galán Hernández José Javier , Galdón Salvador José Luis
Published: November 2023

Employee attrition and high turnover have become critical challenges faced by various sectors in today’s competitive job market. In response to these pressing issues, organizations are increasingly turning to artificial intelligence (AI) to predict employee attrition and implement effective retention strategies. This paper delves into the application of explainable AI (XAI) in identifying potential employee turnover and devising data-driven solutions to address this complex problem. The first part of the paper examines the escalating problem of employee attrition in specific industries, analyzing the detrimental impact on organizational productivity, morale, and financial stability. The second section focuses on the utilization of AI techniques to predict employee attrition. AI can analyze historical data, employee behavior, and various external factors to forecast the likelihood of an employee leaving an organization. By identifying early warning signs, businesses can intervene proactively and implement personalized retention efforts. The third part introduces explainable AI techniques which enhance the transparency and interpretability of AI models. By incorporating these methods into AI-based predictive systems, organizations gain deeper insights into the factors driving employee turnover. This interpretability enables human resources (HR) professionals and decision-makers to understand the model’s predictions and facilitates the development of targeted retention and recruitment strategies that align with individual employee needs.
An Application for Bi-Concave Functions Associated with q-Convolution
Authors: El-Deeb Sheza M. , Catas Adriana
Published: November 2023

The aim of this paper is to introduce and investigate some new subclasses of bi-concave functions using q-convolution and some applications. These special cases are obtaining by making use of a q- derivative linear operator. For the new introduced subclasses, the authors obtain the first two initial Taylor–Maclaurin coefficients |c2| and |c3| of bi-concave functions. For certain values of the parameters, the authors deduce interesting corollaries for coefficient bounds which imply special cases of the new introduced operator. Also, we develop two examples for coefficients |c2| and |c3| for certain functions.
Causality-Driven Efficient Feature Selection for Deep-Learning-Based Surface Roughness Prediction in Milling Machines
Authors: Lee Hyeon-Uk , Chun Chang-Jae , Kang Jae-Mo
Published: November 2023

This paper studies the application of artificial intelligence to milling machines, focusing specifically on identifying the inputs (features) required for predicting surface roughness. Previous studies have extensively reviewed and presented useful features for surface roughness prediction. However, applying research findings to actual operational factories can be challenging due to the additional costs of sensor installations and the diverse environments present in each factory setting. To address these issues, in this paper, we introduced effective features for predicting surface roughness in situations where additional sensors are not installed in the existing environment. These features include feed per tooth, Fz; material removal rate, Q; and the load information. These features are suitable for use in highly constrained environments where separate sensor installation is not required, making it possible to apply the research findings in various factory environments. Additionally, to efficiently select the optimal subset for surface roughness prediction among subsets formed by available features, we apply causality to the feature selection method, proposing an approach called causality-driven efficient feature selection. The experimental results demonstrate that the features introduced in this paper are quite suitable for predicting surface roughness and that the proposed feature selection approach is more effective and efficient compared to existing selection methods.
Hepialiamides A–C: Aminated Fusaric Acid Derivatives and Related Metabolites with Anti-Inflammatory Activity from the Deep-Sea-Derived Fungus Samsoniella hepiali W7
Authors: Zou Zheng-Biao , Wu Tai-Zong , Yang Long-He , He Xi-Wen , Liu Wen-Ya , Zhang Kai , Xie Chun-Lan , Xie Ming-Min , Zhang Yong , Yang Xian-Wen , Wang Jun-Song
Published: November 2023

A systematic investigation combined with a Global Natural Products Social (GNPS) molecular networking approach, was conducted on the metabolites of the deep-sea-derived fungus Samsoniella hepiali W7, leading to the isolation of three new fusaric acid derivatives, hepialiamides A–C (1–3) and one novel hybrid polyketide hepialide (4), together with 18 known miscellaneous compounds (5–22). The structures of the new compounds were elucidated through detailed spectroscopic analysis. as well as TD-DFT-based ECD calculation. All isolates were tested for anti-inflammatory activity in vitro. Under a concentration of 1 µM, compounds 8, 11, 13, 21, and 22 showed potent inhibitory activity against nitric oxide production in lipopolysaccharide (LPS)-activated BV-2 microglia cells, with inhibition rates of 34.2%, 30.7%, 32.9%, 38.6%, and 58.2%, respectively. Of particularly note is compound 22, which exhibited the most remarkable inhibitory activity, with an IC50 value of 426.2 nM.
Physical Activity, Body Composition, Serum Myokines and the Risk of Death in Hemodialysis Patients
Authors: Koźma-Śmiechowicz Martyna A. , Gajewski Bartosz , Fortak Paweł , Gajewska Katarzyna , Nowicki Michał
Published: November 2023

Background and Objectives: The aim of this study was to assess the relationship between habitual physical activity, body composition, serum myokine concentration, and all-cause mortality in chronic hemodialysis patients. Materials and Methods: A prospective cohort study with a 7-year follow-up was conducted in a group of 38 patients (24 men, 14 women, mean age 65.6 ± 13.9 years, dialysis vintage 1.17 ± 1.25 years). Baseline serum concentrations of myokines—follistatin and myostatin—were assessed along with a measurement of physical activity with multidimensional accelerometery, body composition, and the force of forearm muscle contraction. Survival analysis was performed using the Kaplan–Meier method for tertiles of follistatin, serum myostatin, body composition, and physical activity expressed in metabolic equivalents (MET). Results: The mean physical activity among patients was 81 min/24 h (median 38.5 min), and the mean weekly 3MET activity was 493 min (median 218 min). The probability of survival of patients was significantly lower in the subgroup with 3MET/24 h less than 26 min/24 h and 3METt less than 148 min per week compared to the other subgroup (p = 0.006 and p = 0.006, respectively). During the 70-month follow-up, the subgroup with the lowest baseline follistatin concentration showed a significantly lower risk of death (p = 0.02). Baseline myostatin levels were not significant risk factors for mortality, nor were BMI or lean and fat tissue index categories. Conclusions: Physical activity and low plasma follistatin, but not body composition indexes or plasma myostatin, could serve as predictors of all-cause mortality in hemodialysis patients.
Impact of Assisted Reproduction Techniques on Adverse Maternal Outcomes and on the Rate of Hospitalization in Maternal Intensive Care
Authors: Collée Julie , Noel Laure , Seidel Laurence , Chantraine Frédéric , Nisolle Michelle , Henry Laurie
Published: November 2023

Background and Objective: The aim of this retrospective cohort study is to evaluate the impact of assisted reproductive treatment (ART) on adverse maternal outcomes and the rate of hospitalization in maternal intensive care (MIC) in a tertiary university center in Liege, Belgium. Materials and Methods: This is a retrospective cohort study comparing two groups, 6557 patients who achieved pregnancy spontaneously and 330 patients who achieved pregnancy after ART, between January 2020 and December 2022. These patients were followed in the academic obstetrics department of Citadelle Hospital, Liège. The database of the ART center was compared with the database of the delivery unit to determine the cohort of patients who conceived after ART. Adverse maternal outcomes and MIC hospitalization rates were compared with between spontaneous pregnancies and ART groups. ART groups were also compared with each other. Results: The rate of hospitalization in maternal intensive care for patients who achieved pregnancy spontaneously was 12.1%, compared to 17.3% after ART. Comparing the rate of pre-eclampsia, 3.5% of spontaneous pregnancies were complicated by pre-eclampsia, while after ART, 10.9% of patients developed this complication during pregnancy. This rate was higher after IVF (12%) compared to intrauterine insemination and particularly after frozen embryo transfer (FET) in artificial cycle (17.9%). The birthweight of newborns after ART was also analyzed. A significant difference was obtained when comparing fresh embryo transfer with FET. Conclusions: Our study confirmed that FET in artificial cycle is a risk factor for pre-eclampsia and that fresh embryo transfer is associated with a higher rate of newborns with a lower percentile of birthweight. Our data showed that the rate of MIC hospitalization was significantly higher after ART but did not differ between groups.
Resistance of Heterogeneous Metal Compositions to Fracture under Dynamic and Cyclic Loads
Authors: Leshchinskiy Leonid K. , Ivanov Vitaliy P. , Lavrova Elena V. , Il’yaschenko Dmitry P.
Published: November 2023

This paper presents the results of experimental data analysis, which indicate an increased resistance of heterogeneous multilayer clad composites to dynamic loading destruction compared with homogeneous materials. The reason for this is the crack retardation caused by lamination at the boundary of the layers. The destruction of heterogeneous compact composite samples by cyclic off-center stretching also occurs with crack retardation, with the fractogram clearly demonstrating the transverse tightening of the sample section. We argue that crack nucleation plays a decisive role in the process of dynamic destruction of heterogeneous composites obtained by both multilayer cladding and explosion welding. This study presents generalized calculated data confirming the influence of the sign and magnitude of residual stresses (the appearance of a stress discontinuity) on the conditions of fatigue surface crack nucleation and propagation. Unlike homogeneous materials obtained by casting, forging (rolling), or cladding, which are characterized by a linear dependence of the crack propagation velocity on the dynamic stress intensity coefficient, for multilayer composites consisting of strong and viscous layers, a sharp crack deceleration is observed. This is due to the transition of the crack boundary between the strong and viscous layers. This paper presents studies of the corresponding properties of adjacent layers on the integral characteristics of the deposited composite.
Design and Experimental Evaluation of a Dual-Cantilever Piezoelectric Film Sensor with a Broadband Response and High Sensitivity
Authors: Xin Wei , He Zhaoyang , Zhao Chaocheng
Published: November 2023

Cantilever-beam-type PVDF (Polyvinylidene Fluoride) piezoelectric film sensors are commonly utilized for vibration signal detection due to their simple structures and ease of processing. Traditional cantilevered PVDF piezoelectric film sensors are susceptible to the influence of the second-order vibration mode and have a low lateral stress distribution at the free end, which limit their measurement bandwidth and sensitivity. This study is on the design of a dual-cantilever PVDF piezoelectric film sensor based on the principle of cantilevered piezoelectric film sensors. The results of the experiments indicate that, compared to a typical single-arm piezoelectric cantilever beam vibration sensor, the developed sensor has a longer second-order natural frequency that ranges from 112 Hz to 453 Hz, while the first-order natural frequency is maintained at around 12 Hz. This leads to a better ratio of the second-order natural frequency to the first-order natural frequency and a wider frequency response range. At the same time, the sensitivity is increased by a factor of 3.48.
Design of a Femtosecond Laser Percussion Drilling Process for Ni-Based Superalloys Based on Machine Learning and the Genetic Algorithm
Authors: Zhao Zhixi , Yu Yunhe , Sun Ruijia , Zhao Wanrong , Guo Hao , Zhang Zhen , Wang Chenchong
Published: November 2023

Femtosecond laser drilling is extensively used to create film-cooling holes in aero-engine turbine blade processing. Investigating and exploring the impact of laser processing parameters on achieving high-quality holes is crucial. The traditional trial-and-error approach, which relies on experiments, is time-consuming and has limited optimization capabilities for drilling holes. To address this issue, this paper proposes a process design method using machine learning and a genetic algorithm. A dataset of percussion drilling using a femtosecond laser was primarily established to train the models. An optimal method for building a prediction model was determined by comparing and analyzing different machine learning algorithms. Subsequently, the Gaussian support vector regression model and genetic algorithm were combined to optimize the taper and material removal rate within and outside the original data ranges. Ultimately, comprehensive optimization of drilling quality and efficiency was achieved relative to the original data. The proposed framework in this study offers a highly efficient and cost-effective solution for optimizing the femtosecond laser percussion drilling process.