bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating Healthcare-Associated Infections in Public Hospitals: A Cross-Sectional Study
Authors: Iancu Daniela , Moldovan Iuliu , Țilea Brîndușa , Voidăzan Septimiu
Published: December 2023

Background: Hospital-acquired infections (HAIs) pose a significant danger to global public health, mainly because their numbers are growing exponentially each year. Additionally, the rise of bacterial strains resistant to current treatment options further exacerbates this threat. This study aimed to examine the occurrences of HAIs identified in public hospitals at the county level. Methods: We conducted a cross-sectional study utilizing data provided to the Mures Public Health Directorate from all the public hospitals within the studied county. We examined HAIs reported during the period spanning from 2017 to 2021, which amounted to a total of 4603 cases. Results: The medical departments reported the highest prevalence of HAIs at 48.25%. The most common infections included enterocolitis with Clostridioides difficile (32.61%), COVID-19 (19.83%), bronchopneumonia (16.90%), sepsis, surgical wound infections, and urinary tract infections. The five most frequently identified pathogens were Clostridioides difficile (32.61%), SARS-CoV-2 (19.83%), Acinetobacter baumannii (11.82%), Klebsiella pneumoniae (9.58%), and Pseudomonas aeruginosa (7.95%). Acinetobacter baumannii was the predominant agent causing bronchopneumonia, while Klebsiella pneumoniae was the leading cause of sepsis cases. Escherichia coli was the primary agent behind the urinary tract infections, and Staphylococcus aureus MRSA was identified as the main etiology for wound infections and central catheter infections. Throughout the study period, there was a significant rise in Clostridioides difficile and Gram-negative bacteria prevalence rates. Conclusions: This study identified increased Clostridioides difficile in HAI cases during COVID-19, highlighting the need for careful antibiotic use and emphasizing the growing challenge of multi-resistant strains in post-pandemic state hospitals.
A Machine Anomalous Sound Detection Method Using the lMS Spectrogram and ES-MobileNetV3 Network
Authors: Wang Mei , Mei Qingshan , Song Xiyu , Liu Xin , Kan Ruixiang , Yao Fangzhi , Xiong Junhan , Qiu Hongbing
Published: December 2023

Unsupervised anomalous sound detection by machines holds significant importance within the realm of industrial automation. Currently, the task of machine-based anomalous sound detection in complex industrial settings is faced with issues such as the challenge of extracting acoustic feature information and an insufficient feature extraction capability within the detection network. To address these challenges, this study proposes a machine anomalous sound detection method using the lMS spectrogram and ES-MobileNetV3 network. Firstly, the log-Mel spectrogram feature and the SincNet spectrogram feature are extracted from the raw wave, and the new lMS spectrogram is formed after fusion, serving as network input features. Subsequently, based on the MobileNetV3 network, an improved detection network, ES-MobileNetV3, is proposed in this paper. This network incorporates the Efficient Channel Attention module and the SoftPool method, which collectively reduces the loss of feature information and enhances the feature extraction capability of the detection network. Finally, experiments are conducted on the dataset provided by DCASE 2020 Task 2. Our proposed method attained an averaged area under the receiver operating characteristic curve (AUC) of 96.67% and an averaged partial AUC (pAUC) of 92.38%, demonstrating superior detection performance compared to other advanced methods.
OEQA: Knowledge- and Intention-Driven Intelligent Ocean Engineering Question-Answering Framework
Authors: Zhu Rui , Liu Bo , Zhang Ruwen , Zhang Shengxiang , Cao Jiuxin
Published: December 2023

The constantly updating big data in the ocean engineering domain has challenged the traditional manner of manually extracting knowledge, thereby underscoring the current absence of a knowledge graph framework in such a special field. This paper proposes a knowledge graph framework to fill the gap in the knowledge management application of the ocean engineering field. Subsequently, we propose an intelligent question-answering framework named OEQA based on an ocean engineering-oriented knowledge graph. Firstly, we define the ontology of ocean engineering and adopt a top-down approach to construct a knowledge graph. Secondly, we collect and analyze the data from databases, websites, and textual reports. Based on these collected data, we implement named entity recognition on the unstructured data and extract corresponding relations between entities. Thirdly, we propose an intent-recognizing-based user question classification method, and according to the classification result, construct and fill corresponding query templates by keyword matching. Finally, we use T5-Pegasus to generate natural answers based on the answer entities queried from the knowledge graph. Experimental results show that the accuracy in finding answers is 89.6%. OEQA achieves in the natural answer generation in the ocean engineering domain significant improvements in relevance (1.0912%), accuracy (4.2817%), and practicability (3.1071%) in comparison to ChatGPT.
Stress-Constrained Topology Optimization for Commercial Software: A Python Implementation for ABAQUS®
Authors: Fernandes Pedro , Ferrer Àlex , Gonçalves Paulo , Parente Marco , Pinto Ricardo , Correia Nuno
Published: December 2023

Topology optimization has evidenced its capacity to provide new optimal designs in many different disciplines. However, most novel methods are difficult to apply in commercial software, limiting their use in the academic field and hindering their application in the industry. This article presents a new open methodology for solving geometrically complex non-self-adjoint topology optimization problems, including stress-constrained and stress minimization formulations, using validated FEM commercial software. The methodology was validated by comparing the sensitivity analysis with the results obtained through finite differences and solving two benchmark problems with the following optimizers: Optimality Criteria, Method of Moving Asymptotes, Sequential Least-Squares Quadratic Programming (SLSQP), and Trust-constr optimization algorithms. The SLSQP and Trust-constr optimization algorithms obtained better results in stress-minimization problem statements than the methodology available in ABAQUS®. A Python implementation of this methodology is proposed, working in conjunction with the commercial software ABAQUS® 2023 to allow a straightforward application to new problems while benefiting from a graphic user interface and validated finite element solver.
Personal Exposure to Fine Particulate Air Pollution among Brick Workers in Nepal
Authors: Johnston James D. , Collingwood Scott C. , LeCheminant James D. , Peterson Neil E. , Reynolds Paul R. , Arroyo Juan A. , South Andrew J. , Farnsworth Clifton B. , Chartier Ryan T. , Layton Lindsey N. , Lu James H. , Penrod Marli S. , Sanjel Seshananda , Beard John D.
Published: December 2023

Prior studies suggest brick workers in Nepal may be chronically exposed to hazardous levels of fine particulate matter (PM2.5) from ambient, occupational, and household sources. However, findings from these studies were based on stationary monitoring data, and thus may not reflect a worker’s individual exposures. In this study, we used RTI International’s MicroPEMs to collect 24 h PM2.5 personal breathing zone (PBZ) samples among brick workers (n = 48) to estimate daily exposures from ambient, occupational, and household air pollution sources. Participants were sampled from five job categories at one kiln. The geometric mean (GM) PM2.5 exposure across all participants was 116 µg/m3 (95% confidence interval [CI]: 94.03, 143.42). Job category was significantly (p < 0.001) associated with PBZ PM2.5 concentrations. There were significant pairwise differences in geometric mean (GM) PBZ PM2.5 concentrations among workers in administration (GM: 47.92, 95% CI: 29.81, 77.03 µg/m3) vs. firemen (GM: 163.46, 95 CI: 108.36, 246.58 µg/m3, p = 0.003), administration vs. green brick hand molder (GM: 163.35, 95% CI: 122.15, 218.46 µg/m3, p < 0.001), administration vs. top loader (GM: 158.94, 95% CI: 102.42, 246.66 µg/m3, p = 0.005), firemen vs. green brick machine molder (GM: 73.18, 95% CI: 51.54, 103.90 µg/m3, p = 0.03), and green brick hand molder vs. green brick machine molder (p = 0.008). Temporal exposure trends suggested workers had chronic exposure to hazardous levels of PM2.5 with little to no recovery period during non-working hours. Multi-faceted interventions should focus on the control of ambient and household air pollution and tailored job-specific exposure controls.
Navigating Battery Choices in IoT: An Extensive Survey of Technologies and Their Applications
Authors: Hasan Kareeb , Tom Neil , Yuce Mehmet Rasit
Published: December 2023

In recent years, there has been significant progress in IoT solutions for a variety of fields. The real-time functionality and remote deployment of IoT solutions are two crucial aspects that are necessary for their successful implementation. To achieve this, external batteries play a major role. While lithium–ion batteries are often the go-to choice for IoT devices, it is essential to recognise that different IoT applications have unique needs. Therefore, it is important to conduct a thorough examination of existing battery solutions and their suitability for various IoT applications. This paper presents an extensive survey of different battery technologies, accompanied by an assessment of their applicability in different IoT applications. The aim is to offer a clear and practical guide for researchers and professionals seeking the best battery solutions for their IoT applications.
Machine-Learning-Based Prediction of 1-Year Arrhythmia Recurrence after Ventricular Tachycardia Ablation in Patients with Structural Heart Disease
Authors: Komlósi Ferenc , Tóth Patrik , Bohus Gyula , Vámosi Péter , Tokodi Márton , Szegedi Nándor , Salló Zoltán , Piros Katalin , Perge Péter , Osztheimer István , Ábrahám Pál , Széplaki Gábor , Merkely Béla , Gellér László , Nagy Klaudia
Published: December 2023

Background: Ventricular tachycardia (VT) recurrence after catheter ablation remains a concern, emphasizing the need for precise risk assessment. We aimed to use machine learning (ML) to predict 1-month and 1-year VT recurrence following VT ablation. Methods: For 337 patients undergoing VT ablation, we collected 31 parameters including medical history, echocardiography, and procedural data. 17 relevant features were included in the ML-based feature selection, which yielded six and five optimal features for 1-month and 1-year recurrence, respectively. We trained several supervised machine learning models using 10-fold cross-validation for each endpoint. Results: We observed 1-month VT recurrence was observed in 60 (18%) cases and accurately predicted using our model with an area under the receiver operating curve (AUC) of 0.73. Input features used were hemodynamic instability, incessant VT, ICD shock, left ventricular ejection fraction, TAPSE, and non-inducibility of the clinical VT at the end of the procedure. A separate model was trained for 1-year VT recurrence (observed in 117 (35%) cases) with a mean AUC of 0.71. Selected features were hemodynamic instability, the number of inducible VT morphologies, left ventricular systolic diameter, mitral regurgitation, and ICD shock. For both endpoints, a random forest model displayed the highest performance. Conclusions: Our ML models effectively predict VT recurrence post-ablation, aiding in identifying high-risk patients and tailoring follow-up strategies.
Inhibition of NMDA Receptor Activation in the Rostral Ventrolateral Medulla by Amyloid-β Peptide in Rats
Authors: Islam Md Sharyful , Lai Chih-Chia , Wang Lan-Hui , Lin Hsun-Hsun
Published: December 2023

N-methyl-D-aspartate (NMDA) receptors, a subtype of ionotropic glutamate receptors, are important in regulating sympathetic tone and cardiovascular function in the rostral ventrolateral medulla (RVLM). Amyloid-beta peptide (Aβ) is linked to the pathogenesis of Alzheimer’s disease (AD). Cerebro- and cardiovascular diseases might be the risk factors for developing AD. The present study examines the acute effects of soluble Aβ on the function of NMDA receptors in rats RVLM. We used the magnitude of increases in the blood pressure (pressor responses) induced by microinjection of NMDA into the RVLM as an index of NMDA receptor function in the RVLM. Soluble Aβ was applied by intracerebroventricular (ICV) injection. Aβ1-40 at a lower dose (0.2 nmol) caused a slight reduction, and a higher dose (2 nmol) showed a significant decrease in NMDA-induced pressor responses 10 min after administration. ICV injection of Aβ1-42 (2 nmol) did not affect NMDA-induced pressor responses in the RVLM. Co-administration of Aβ1-40 with ifenprodil or memantine blocked the inhibitory effects of Aβ1-40. Immunohistochemistry analysis showed a significant increase in the immunoreactivity of phosphoserine 1480 of GluN2B subunits (pGluN2B-serine1480) in the neuron of the RVLM without significant changes in phosphoserine 896 of GluN1 subunits (pGluN1-serine896), GluN1 and GluN2B, 10 min following Aβ1-40 administration compared with saline. Interestingly, we found a much higher level of Aβ1-40 compared to that of Aβ1-42 in the cerebrospinal fluid (CSF) measured using enzyme-linked immunosorbent assay 10 min following ICV administration of the same dose (2 nmol) of the peptides. In conclusion, the results suggest that ICV Aβ1-40, but not Aβ1-42, produced an inhibitory effect on NMDA receptor function in the RVLM, which might result from changes in pGluN2B-serine1480 (regulated by casein kinase II). The different elimination of the peptides in the CSF might contribute to the differential effects of Aβ1-40 and Aβ1-42 on NMDA receptor function.
State-of-the-Art Features for Early-Stage Detection of Diabetic Foot Ulcers Based on Thermograms
Authors: Arteaga-Marrero Natalia , Hernández-Guedes Abián , Ortega-Rodríguez Jordan , Ruiz-Alzola Juan
Published: December 2023

Diabetic foot ulcers represent the most frequently recognized and highest risk factor among patients affected by diabetes mellitus. The associated recurrent rate is high, and amputation of the foot or lower limb is often required due to infection. Analysis of infrared thermograms covering the entire plantar aspect of both feet is considered an emerging area of research focused on identifying at an early stage the underlying conditions that sustain skin and tissue damage prior to the onset of superficial wounds. The identification of foot disorders at an early stage using thermography requires establishing a subset of relevant features to reduce decision variability and data misinterpretation and provide a better overall cost–performance for classification. The lack of standardization among thermograms as well as the unbalanced datasets towards diabetic cases hinder the establishment of this suitable subset of features. To date, most studies published are mainly based on the exploitation of the publicly available INAOE dataset, which is composed of thermogram images of healthy and diabetic subjects. However, a recently released dataset, STANDUP, provided data for extending the current state of the art. In this work, an extended and more generalized dataset was employed. A comparison was performed between the more relevant and robust features, previously extracted from the INAOE dataset, with the features extracted from the extended dataset. These features were obtained through state-of-the-art methodologies, including two classical approaches, lasso and random forest, and two variational deep learning-based methods. The extracted features were used as an input to a support vector machine classifier to distinguish between diabetic and healthy subjects. The performance metrics employed confirmed the effectiveness of both the methodology and the state-of-the-art features subsequently extracted. Most importantly, their performance was also demonstrated when considering the generalization achieved through the integration of input datasets. Notably, features associated with the MCA and LPA angiosomes seemed the most relevant.
Pan-Cancer Profiling of Intron Retention and Its Clinical Significance in Diagnosis and Prognosis
Authors: Huang Leihuan , Zeng Xin , Ma Haijing , Yang Yu , Akimoto Yoshie , Wei Gang , Ni Ting
Published: December 2023

Alternative splicing can produce transcripts that affect cancer development and thus shows potential for cancer diagnosis and treatment. However, intron retention (IR), a type of alternative splicing, has been studied less in cancer biology research. Here, we generated a pan-cancer IR landscape for more than 10,000 samples across 33 cancer types from The Cancer Genome Atlas (TCGA). We characterized differentially retained introns between tumor and normal samples and identified retained introns associated with survival. We discovered 988 differentially retained introns in 14 cancers, some of which demonstrated diagnostic potential in multiple cancer types. We also inferred a large number of prognosis-related introns in 33 cancer types, and the associated genes included well-known cancer hallmarks such as angiogenesis, metastasis, and DNA mutations. Notably, we discovered a novel intron retention inside the 5′UTR of STN1 that is associated with the survival of lung cancer patients. The retained intron reduces translation efficiency by producing upstream open reading frames (uORFs) and thereby inhibits colony formation and cell migration of lung cancer cells. Besides, the IR-based prognostic model achieved good stratification in certain cancers, as illustrated in acute myeloid leukemia. Taken together, we performed a comprehensive IR survey at a pan-cancer level, and the results implied that IR has the potential to be diagnostic and prognostic cancer biomarkers, as well as new drug targets.
Increased Plasmatic Levels of Exosomes Are Significantly Related to Relapse Rate in Patients with Oral Squamous Cell Carcinoma: A Cohort Study
Authors: Rodríguez-Zorrilla Samuel , Lorenzo-Pouso Alejandro I. , Fais Stefano , Logozzi Maria A. , Mizzoni Davide , Di Raimo Rossella , Giuliani Alessandro , García-García Abel , Pérez-Jardón Alba , Ortega Karem L. , Martínez-González Ángel , Pérez-Sayáns Mario
Published: December 2023

Background: Oral squamous cell carcinoma (OSCC) is characterized by an immunosuppressive tumor microenvironment. Their plasma-derived exosomes deliver immunomodulatory molecules and cargo that correlate significantly with clinical parameters. This study aims to assess the exosomal profile as a potential tool for early detection of relapse and long-term outcomes in OSCC patients undergoing conventional therapy. Methods: 27 OSCC patients with a median 38-month follow-up were included in this study. The relationship between NTA-derived parameters and clinical pathological parameters was examined, and receiver operating characteristic (ROC) curves were utilized to evaluate the diagnostic efficacy of these values in detecting cancer relapse. Results: Plasmatic levels of exosomes prior to surgery showed a drastic reduction after surgical intervention (8.08E vs. 1.41 × 109 particles/mL, p = 0.006). Postsurgical concentrations of exosomes were higher in patients who experienced relapse compared to those who remained disease-free (2.97 × 109 vs. 1.11 × 109 particles/mL, p = 0.046). Additionally, patients who relapsed exhibited larger exosome sizes after surgery (141.47 vs. 132.31 nm, p = 0.03). Patients with lower concentrations of exosomes prior to surgery demonstrated better disease-free survival compared to those with higher levels (p = 0.012). ROC analysis revealed an area under the curve of 0.82 for presurgical exosome concentration in identifying relapse. Conclusions: Presurgical exosomal plasmatic levels serve as independent predictors of early recurrence and survival in OSCC. All in all, our findings indicate that the detection of peripheral exosomes represents a novel tool for the clinical management of OSCC, with potential implications for prognosis assessment.
Modeling the Deposition of Thin Films of Transition Metal Nitrides
Authors: Goncharov Alexander , Yunda Andrii , Kolinko Ivan , Kornich Grygoriy , Shyrokorad Dmytro
Published: December 2023

This paper presents an overview of studies dedicated to the atomic-discrete modeling of the growth process of film coatings that comprise mononitrides of transition and post-transition metals. The main modeling approaches are the Monte Carlo and molecular dynamics methods as well as their combinations with analytical contributions. The molecular dynamics method is more accurate compared to the Monte Carlo method but has disadvantages related to the time scale. Given this, the adoption of accelerated molecular dynamics methods is viewed as a promising approach for directly simulating the specified processes. These methods can be implemented just after the relaxation of the collision stage in the area of the deposited particle between the deposition events to simulate the realistic density of the incident beam and accompanied long-term mass transfer processes.
Corrosion Behavior of Shot-Peened Ti6Al4V Alloy Produced via Pressure-Assisted Sintering
Authors: Avcu Egemen , Abakay Eray , Yıldıran Avcu Yasemin , Çalım Emirhan , Gökalp İdris , Iakovakis Eleftherios , Koç Funda Gül , Yamanoglu Ridvan , Akıncı Akın , Guney Mert
Published: December 2023

For the first time, the present study investigates the corrosion, surface, and subsurface properties of a shot-peened Ti6Al4V powder metallurgical alloy produced via pressure-assisted sintering. Shot peening yielded a fine-grained microstructure beneath the surface down to 100 microns, showing that it caused severe plastic deformation. XRD analysis revealed that the sizes of the crystallites in unpeened and shot-peened Ti6Al4V alloy samples were 48.59 nm and 27.26 nm, respectively, indicating a substantial reduction in crystallite size with shot peening. Cross-sectional hardness maps of shot-peened samples showed a work-hardened surface layer, indicating a ~17% increase in near-surface hardness relative to unpeened samples. Three-dimensional surface topographies showed that shot peening yielded uniform peaks and valleys, with a maximum peak height of 4.83 μm and depth of 6.56 μm. With shot peening, the corrosion potential shifted from −0.386 V to −0.175 V, showing that the passive layer developed faster and was more stable than the unpeened sample, improving corrosion resistance. As determined via XRD analysis, the increased grain refinement (i.e., the number of grain boundaries) and the subsequent accumulation of TiO2 and Al5Ti3V2 compounds through shot peening also suggested the effective formation of a protective passive layer. As demonstrated via electrochemical impedance spectroscopy, the formation of this passive film improved the corrosion resistance of the alloy. The findings will likely advance surface engineering and corrosion research, enabling safer and more productive shot peening in corrosion-critical applications.
Effects of the Number of Classes and Pressure Map Resolution on Fine-Grained In-Bed Posture Classification
Authors: Fonseca Luís , Ribeiro Fernando , Metrôlho José
Published: December 2023

In-bed posture classification has attracted considerable research interest and has significant potential to enhance healthcare applications. Recent works generally use approaches based on pressure maps, machine learning algorithms and focused mainly on finding solutions to obtain high accuracy in posture classification. Typically, these solutions use different datasets with varying numbers of sensors and classify the four main postures (supine, prone, left-facing, and right-facing) or, in some cases, include some variants of those main postures. Following this, this article has three main objectives: fine-grained detection of postures of bedridden people, identifying a large number of postures, including small variations—consideration of 28 different postures will help to better identify the actual position of the bedridden person with a higher accuracy. The number of different postures in this approach is considerably higher than the of those used in any other related work; analyze the impact of pressure map resolution on the posture classification accuracy, which has also not been addressed in other studies; and use the PoPu dataset, a dataset that includes pressure maps from 60 participants and 28 different postures. The dataset was analyzed using five distinct ML algorithms (k-nearest neighbors, linear support vector machines, decision tree, random forest, and multi-layer perceptron). This study’s findings show that the used algorithms achieve high accuracy in 4-posture classification (up to 99% in the case of MLP) using the PoPu dataset, with lower accuracies when attempting the finer-grained 28-posture classification approach (up to 68% in the case of random forest). The results indicate that using ML algorithms for finer-grained applications is possible to specify the patient’s exact position to some degree since the parent posture is still accurately classified. Furthermore, reducing the resolution of the pressure maps seems to affect the classifiers only slightly, which suggests that for applications that do not need finer-granularity, a lower resolution might suffice.
Decision Tree-Supported Analysis of Gallium Arsenide Growth Using the LEC Method
Authors: Tang Xia , Chappa Gagan Kumar , Vieira Lucas , Holena Martin , Dropka Natasha
Published: December 2023

In this study, an axisymmetric Czochralski furnace model for the LEC growth of gallium arsenide is presented. We produced 88 datasets through computational fluid dynamics simulations. Among the many parameters that affect crystal growth, a total of 13 input parameters were selected, including the geometry and material parameters of the hot zone (crucible, heaters, radiation shield, and crystal), as well as the process parameters (such as pulling and rotation rates, heating power, etc.). Voronkov criteria (v/Gn), interface deflection, and the average interface temperature gradient were selected as the output parameters. We carried out a correlation analysis between the variables and used decision trees to study the impact of the 13 input variables on the output variables. The results indicated that in the growth of gallium arsenide, the main factor affecting interface deflection and the average interface thermal gradients is the crucible rotation rate. For v/Gn, it is the pulling rate.
Responses of Phytoplankton Communities to Flow Regulation in Northeastern Riverine Wetlands of China
Authors: Meng Yao , Wu Haitao
Published: December 2023

Among the impacts of dam construction on river ecosystem, runoff regulation and habitat fragmentation are the two major concerns. Herein, the response characteristics of phytoplankton communities to reservoir impoundment and dam interception were explored by taking Manjiang and Songjiang rivers, where a man-made engineering project was constructed, and the natural stretches located in the up-streams as the research objects. The results obtained revealed that the compositions of phytoplankton communities, collected from the 21 sampling sites in the riverine wetlands of reservoir stretch, flow-reduced stretch, and natural stretch, were dissimilar. The communities of phytoplankton were clustered into three groups. The co-occurrence network analysis indicated that the interspecific relationship structures of phytoplankton communities of each group were different. The indicator species Chlamydomonas ovalis, Synedra acus, and Chlamydomonas globosa, belonged to the Reservoir Wetlands Group, Diatoma vulgare, Fragilaria ca pucina, and Meridion circulare belonged to the Flow-reduced Wetlands Group, and Ceratoneis arcus and Treubaria crassispina belonged to the Natural Wetlands Group. The functional group L0 was the absolute dominant group in all three groups of the riverine wetlands, but a discrepancy was that the proportions of functional group X2 and functional group C in the Reservoir Wetlands Group were remarkably higher, while the proportion of functional group MP in the Flow-reduced Wetlands Group was noticeably higher. By assessing the status of the phytoplankton community composition and the functional group structure, we concluded that current velocity and water depth were crucial influencing factors, and the functional group structure based on the classification of livable water could be applied as a good indication for demonstrating phytoplankton community succession.
Pool Boiling of Ethanol on Copper Surfaces with Rectangular Microchannels
Authors: Kaniowski Robert , Pastuszko Robert , Dragašius Egidijus , Baskutis Saulius
Published: December 2023

In this paper, pool boiling of ethanol at atmospheric pressure was analyzed. The enhanced surfaces were made of copper, on which grooves with a depth ranging from 0.2 to 0.5 mm were milled in parallel. The widths of the microchannels and the distances between them were 0.2 mm, 0.3 mm and 0.4 mm, respectively. The highest heat transfer coefficient, 90.3 kW/m2K, was obtained for the surface with a microchannel depth of 0.5 mm and a width of 0.2 mm. The maximum heat flux was 1035 kW/m2. For the analyzed surfaces, the maximum heat flux increase of two and a half times was obtained, while the heat transfer coefficient increased three-fold in relation to the smooth surface. In the given range of heat flux 21.2–1035 kW/m2, the impact of geometric parameters on the heat transfer process was presented. The diameters of the departing bubbles were determined experimentally with the use of a high-speed camera. A simplified model was proposed to determine the diameter of the departure bubble for the studied surfaces.
The Effect of a Three-Blade Tube on the Pneumatic Transport of Pebble Particles
Authors: Hao Yating , Chen Hongyu , Ji Yun
Published: December 2023

In this paper, the Computational Fluid Dynamics–Discrete Element Method (CFD-DEM) coupling method was used to simulate the pneumatic transport of pebble particles in a three-blade spiral tube. The results showed that the flow field distribution rotated along the circumference after loading. The maximum velocity of the flow field after loading was manifested as rotation along the circumference. In addition, the swirl intensity decreased exponentially with the increase in conveying distance, and the maximum swirl intensity had a saturation value. After reaching the saturation value, it is not evident that increasing the initial air velocity significantly affected swirl variation. The smaller the pitch, the greater the initial swirl intensity. The swirling flow was conducive to the fluidization of particles, but it would bring a significant energy loss. Increasing the swirl can increase the degree of particle dispersion. There is an optimal tangential airflow velocity, which allows the particles to fully spin and stay in the suspension zone without being thrown onto the pipe wall by excessive centrifugal force. At this time, the energy efficiency reaches the highest level. A 5.87 m/s velocity was deemed the optimal tangential airflow velocity for conveying 3 mm particles.
Drivers and Trends in the Size and Severity of Forest Fires Endangering WUI Areas: A Regional Case Study
Authors: Rodriguez-Jimenez Fernando , Fernandes Paulo M. , Fernández-Guisuraga José Manuel , Alvarez Xana , Lorenzo Henrique
Published: December 2023

This study explored, for the first time, the drivers shaping large fire size and high severity of forest fires classified as level-2 in Spain, which pose a great danger to the wildland–urban interface. Specifically, we examined how bottom-up (fuel type and topography) and top-down (fire weather) controls shaped level-2 fire behavior through a Random Forest classifier at the regional scale in Galicia (NW Spain). We selected for this purpose 93 level-2 forest fires. The accuracy of the RF fire size and severity classifications was remarkably high (>80%). Fire weather overwhelmed bottom-up controls in controlling the fire size of level-2 forest fires. The likelihood of large level-2 forest fires increased sharply with the fire weather index, but plateaued at values above 40. Fire size strongly responded to minimum relative humidity at values below 30%. The most important variables explaining fire severity in level-2 forest fires were the same as in the fire size, as well as the pre-fire shrubland fraction. The high-fire-severity likelihood of level-2 forest fires increased exponentially for shrubland fractions in the landscape above 50%. Our results suggest that level-2 forest fires will pose an increasing danger to people and their property under predicted scenarios of extreme weather conditions.
Effect of Mixed Lactiplantibacillus plantarum- and Bacillus subtilis-Fermented Feed on Growth, Immunity, and Intestinal Health of Weaner Pigs
Authors: Chen Jun , Wu Guofang , Pang Huili , Hua Jiyun , Guan Yifei , Zhang Miao , Duan Yaoke , Qin Guangyong , Wang Lei , Cai Yimin , Tan Zhongfang
Published: December 2023

Bamei pigs, an eximious local breed reared on the Tibetan Plateau of China, are facing problems such as feed shortages, weaning stress, and antibiotic abuse. This study aimed to improve the quality of feed, growth performance, intestinal microbiota, and immunity of Bamei pigs through feeding with potentially probiotic-fermented feed. Different feeds were administered to weaned Bamei piglets for 60 days, creating the following five experimental treatment groups: basal feed group; Lactiplantibacillus plantarum-fermented-feed group; Bacillus subtilis-fermented-feed group; mixed-fermented-feed group; and antibiotic-supplemented-feed group. The results showed that the pH, neutral detergent fiber, and acid detergent fiber of the potentially probiotic-fermented feeds were significantly reduced; organic acids were produced; and Coliform bacteria, Clostridium, and aerobic bacteria were effectively inhibited. Feeding with potentially probiotic-fermented feed not only reduced the feed-conversion ratio but also improved immunity by increasing the production of anti-inflammatory cytokines, as well as decreasing pro-inflammatory cytokines and typical inflammatory pathways. The 16s rDNA high-throughput-sequencing results showed that probiotic-fermented feed improved the diversity of intestinal microbiota, inhibited the growth of the opportunistic pathogens Clostridium and Streptococcus, increased the relative abundance of Lactobacillus and Prevotella, and promoted gut health, demonstrating the promising application prospects of potentially probiotic-fermented feed.
Grapevine Shoot Extract Rich in Trans-Resveratrol and Trans-ε-Viniferin: Evaluation of Their Potential Use for Cardiac Health
Authors: Contreras María del Mar , Feriani Anouar , Gómez-Cruz Irene , Hfaiedh Najla , Harrath Abdel Halim , Romero Inmaculada , Castro Eulogio , Tlili Nizar
Published: December 2023

A grapevine shoot extract (GSE) was obtained using ultrasound-assisted extraction and characterized. The main phenolic constituents were identified as stilbenoids. Among them, trans-resveratrol and trans-ε-viniferin stood out. The GSE was administered to an isoproterenol-induced myocardial injury animal model. The extract alleviated the associated symptoms of the administration of the drug, i.e., the plasma lipid profile was improved, while the disturbed plasma ion concentration, the cardiac dysfunction markers, the DNA laddering, and the necrosis of myocardial tissue were diminished. This effect could be related to the anti-oxidative potential of GSE associated with its antioxidant properties, the increased levels of endogenous antioxidants (glutathione and enzymatic antioxidants), and the diminished lipid peroxidative markers in the heart. The results also revealed angiotensin-converting enzyme (ACE)-inhibitory activity, which indicated the potential of GSE to deal with cardiovascular disease events. This work suggests that not only trans-resveratrol has a protective role in heart function but also GSE containing this biomolecule and derivatives. Therefore, GSE has the potential to be utilized in the creation of innovative functional ingredients.
De Novo RNA Sequencing and Transcriptome Analysis of Sclerotium rolfsii Gene Expression during Sclerotium Development
Authors: Wang Fanfan , Wang Xiaoyue , Tang Tao , Duan Yuanyuan , Mao Ting , Guo Xiaoliang , Wang Qingfang , You Jingmao
Published: December 2023

Sclerotium rolfsii is a destructive soil-borne fungal pathogen that causes stem rot in cultivated plants. However, little is known about the genetic basis of sclerotium development. In this study, we conducted de novo sequencing of genes from three different stages of S. rolfsii (mycelia, early sclerotium formation, and late sclerotium formation) using Illumina HiSeqTM 4000. We then determined differentially expressed genes (DEGs) across the three stages and annotated gene functions. STEM and weighted gene-co-expression network analysis were used to cluster DEGs with similar expression patterns. Our analysis yielded an average of 25,957,621 clean reads per sample (22,913,500–28,988,848). We identified 8929, 8453, and 3744 DEGs between sclerotium developmental stages 1 versus 2, 1 versus 3, and 2 versus 3, respectively. Additionally, four significantly altered gene expression profiles involved 220 genes related to sclerotium formation, and two modules were positively correlated with early and late sclerotium formation. These results were supported by the outcomes of qPCR and RNA-sequencing conducted on six genes. This is the first study to provide a gene expression map during sclerotial development in S. rolfsii, which can be used to reduce the re-infection ability of this pathogen and provide new insights into the scientific prevention and control of the disease. This study also provides a useful resource for further research on the genomics of S. rolfsii.
Comparative Genetic Analysis of the Promoters of the ATG16L1 and ATG5 Genes Associated with Sporadic Parkinson’s Disease
Authors: Gómez-Martín Ana , Fuentes José M. , Jordán Joaquín , Galindo María F. , Fernández-García José Luis
Published: December 2023

Sporadic Parkinson’s disease, characterised by a decline in dopamine, usually manifests in people over 65 years of age. Although 10% of cases have a genetic (familial) basis, most PD is sporadic. Genome sequencing studies have associated several genetic variants with sporadic PD. Our aim was to analyse the promoter region of the ATG16L1 and ATG5 genes in sporadic PD patients and ethnically matched controls. Genotypes were obtained by using the Sanger method with primers designed by us. The number of haplotypes was estimated with DnaSP software, phylogeny was reconstructed in Network, and genetic divergence was explored with Fst. Seven and two haplotypes were obtained for ATG16L1 and ATG5, respectively. However, only ATG16L1 showed a significant contribution to PD and a significant excess of accumulated mutations that could influence sporadic PD disease. Of a total of seven haplotypes found, only four were unique to patients sharing the T allele (rs77820970). Recent studies using MAPT genes support the notion that the architecture of haplotypes is worthy of being considered genetically risky, as shown in our study, confirming that large-scale assessment in different populations could be relevant to understanding the role of population-specific heterogeneity. Finally, our data suggest that the architecture of certain haplotypes and ethnicity determine the risk of PD, linking haplotype variation and neurodegenerative processes.
Molecular Characterization and Establishment of a Prognostic Model Based on Primary Immunodeficiency Features in Association with RNA Modifications in Triple-Negative Breast Cancer
Authors: Xia Hongzhuo , Xu Xi , Guo Yuxuan , Deng Xiyun , Wang Yian , Fu Shujun
Published: December 2023

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Although immunotherapy is effective for some patients, most find it difficult to benefit from it. This study aims to explore the impact of specific immune pathways and their regulated molecular mechanisms in TNBC. The gene expression data of breast cancer patients were obtained from the TCGA and METABRIC databases. Gene set variation analysis (GSVA) revealed specific upregulation or abnormal expression of immunodeficiency pathways in TNBC patients. Multi-omics data showed significant differential expression of Primary Immunodeficiency Genes (PIDGs) in TNBC patients, who are prone to genomic-level variations. Consensus clustering was used in two datasets to classify patients into two distinct molecular subtypes based on PIDGs expression patterns, with each displaying different biological features and immune landscapes. To further explore the prognostic characteristics of PIDGs-regulated molecules, we constructed a four-gene prognostic PIDG score model and a nomogram using least absolute shrinkage and selection operator (LASSO) regression analysis in combination with clinicopathological parameters. The PIDG score was closely associated with the immune therapy and drug sensitivity of TNBC patients, providing potential guidance for clinical treatment. Particularly noteworthy is the close association of this scoring with RNA modifications; patients with different scores also exhibited different mutation landscapes. This study offers new insights for the clinical treatment of TNBC and for identifying novel prognostic markers and therapeutic targets in TNBC.
Plant Growth Promoting Bacteria for Aquaponics as a New Strategy That Grants Quality and Nutrient Efficiency in Kohlrabi Cultivation
Authors: Piñero María Carmen , Collado-González Jacinta , Otálora Ginés , López-Marín Josefa , del Amor Francisco M.
Published: December 2023

Consumers are becoming increasingly concerned about eating healthy, and the products they consume are produced in an environmentally friendly way. Therefore, in this work, production techniques such as aquaculture and the use of plant growth-promoting bacteria in kohlrabi cultivation (Brassica oleracea L.) were studied. To this end, we applied three types of irrigation treatments (control, mixed water (50% fish effluent/50% drainage water) (mixed water), and mixed water enriched with synthetic fertilizers (mixed water + S)) combined with two formulations of plant growth-promoting bacteria (B1 and B2) in kohlrabi plants. Our data showed that the B1 inoculum combined with control irrigation caused both the increase in dry matter and the diameter of the bulb (17.8% and 8.9%, respectively); moreover, this inoculum increased the concentration of Ca when applied with mixed irrigation solution (water + S), and Zn for the B2 inoculum. The nitrogen utilization efficiency (NUtE) was augmented by the mixed irrigation treatment, with the lowest concentration of nitrates observed in the bulbs. Both inocula increased the total phenolic compounds in the control irrigation, whilst an increase in fructose and sucrose concentrations was only observed with B2.
Effectiveness of Transitional Care Program among High-Risk Discharged Patients: A Quasi-Experimental Study on Saving Costs, Post-Discharge Readmissions and Emergency Department Visits
Authors: Heo Moonseong , Taaffe Kevin , Ghadshi Ankita , Teague Leigh D. , Watts Jeffrey , Lopes Snehal S. , Tilkemeier Peter , Litwin Alain H.
Published: December 2023

Transitional care programs (TCPs), where hospital care team members repeatedly follow up with discharged patients, aim to reduce post-discharge hospital or emergency department (ED) utilization and healthcare costs. We examined the effectiveness of TCPs at reducing healthcare costs, hospital readmissions, and ED visits. Centers for Medicare and Medicaid Services Bundled Payments for Care Improvement (BPCI) program adjudicated claims files and electronic health records from Greenville Memorial Hospital, Greenville, SC, were accessed. Data on post-discharge 30- and 90-day ED visits and readmissions, total costs, and episodes with costs over BPCI target prices were extracted from November 2017 to July 2020 and compared between the “TCP-Graduates” (N = 85) and “Did Not Graduate” (DNG) (N = 1310) groups. As compared to the DNG group, the TCP-Graduates group had significantly fewer 30-day (7.1% vs. 14.9%, p = 0.046) and 90-day (15.5% vs. 26.3%, p = 0.025) readmissions, episodes with total costs over target prices (25.9% vs. 36.6%, p = 0.031), and lower total cost/episode (USD 22,439 vs. USD 28,633, p = 0.018), but differences in 30-day (9.4% vs. 11.2%, p = 0.607) and 90-day (20.0% vs. 21.9%, p = 0.680) ED visits were not significant. TCP was associated with reduced post-discharge hospital readmissions, total care costs, and episodes exceeding target prices. Further studies with rigorous designs and individual-level data should test these findings.
Extracellular Matrix Deposition Defines the Duration of Cell Sheet Assembly from Human Adipose-Derived MSC
Authors: Glazieva Valentina S. , Alexandrushkina Natalya A. , Nimiritsky Peter P. , Kulebyakina Maria A. , Eremichev Roman Yu. , Makarevich Pavel I.
Published: December 2023

Cell sheet (CS) engineering using mesenchymal stromal cells (MSC) draws significant interest for regenerative medicine and this approach translates to clinical use for numerous indications. However, little is known of factors that define the timing of CS assembly from primary cultures. This aspect is important for planning CS delivery in autologous and allogeneic modes of use. We used a comparative in vitro approach with primary donors’ (n = 14) adipose-derived MSCs and evaluated the impact of healthy subject’s sex, MSC culture features (population doubling time and lag-phase), and extracellular matrix (ECM) composition along with factors related to connective tissue formations (α-SMA and FAP-α) on CS assembly duration. Using qualitative and quantitative analysis methods, we found that, in seeded MSCs, high contents of collagen I and collagen IV had a direct correlation with longer CS assembly duration. We found that short lag-phase cultures faster turned to a ready-to-use CS, while age, sex, fibronectin, laminin, α-SMA, and FAP-α failed to provide a significant correlation with the timing of assembly. In detachable CSs, FAP-α was negatively correlated with the duration of assembly, suggesting that its concentration rose over time and contributed to MSC activation, transitioning to α-SMA-positive myofibroblasts and ECM turnover. Preliminary data on cell density and collagen I deposition suggested that the TGF-β1 signaling axis is of pivotal importance for ECM composition and construct maturation.
Chemical Structure Diversity and Extensive Biological Functions of Specialized Metabolites in Rice
Authors: Zhou Huiwen , Zhang Jinjin , Bai Liping , Liu Jiayi , Li Hongdi , Hua Juan , Luo Shihong
Published: December 2023

Rice (Oryza sativa L.) is thought to have been domesticated many times independently in China and India, and many modern cultivars are available. All rice tissues are rich in specialized metabolites (SPMs). To date, a total of 181 terpenoids, 199 phenolics, 41 alkaloids, and 26 other types of compounds have been detected in rice. Some volatile sesquiterpenoids released by rice are known to attract the natural enemies of rice herbivores, and play an indirect role in defense. Momilactone, phytocassane, and oryzalic acid are the most common diterpenoids found in rice, and are found at all growth stages. Indolamides, including serotonin, tryptamine, and N-benzoylserotonin, are the main rice alkaloids. The SPMs mainly exhibit defense functions with direct roles in resisting herbivory and pathogenic infections. In addition, phenolics are also important in indirect defense, and enhance wax deposition in leaves and promote the lignification of stems. Meanwhile, rice SPMs also have allelopathic effects and are crucial in the regulation of the relationships between different plants or between plants and microorganisms. In this study, we reviewed the various structures and functions of rice SPMs. This paper will provide useful information and methodological resources to inform the improvement of rice resistance and the promotion of the rice industry.