bluuebunny/crossref_metadata_2025 huggingface dataset:
Wind-Induced Variations in Phenology Regulate Carbon Fluxes in Two Warm-Temperate Plantation Forests
Authors: Liu Yue , Su Menglin , Jin Jiaxin , Ruan Honghua , Xue Jianhui , Sun Yin , Yu Shuiqiang , Wang Weifeng
Published: December 2024

Forest phenology directly reacts to global climate change, potentially regulating greenhouse gas fluxes between ecosystems and the atmosphere. To explore this phenomenon in two plain poplar (Populus spp.) forests in eastern China, we measured CO2 fluxes and phenology at the canopy scale based on the eddy covariance and PhenoCam technology. From 2019 to 2022, poplars in a high-speed wind site (HWS) experienced shorter maturity durations (108 ± 4.9 days vs. 152 ± 1.2 days) and an earlier date of foliar senescence (day of year: 223.8 ± 2.5 vs. 259.5 ± 0.9) than those in the low-speed wind site (LWS). The annual net CO2 uptake in the HWS (689.65 ± 105.15 g C·m−2·year−1) was approximately 2.4 times higher than that in the LWS (285.65 ± 81.37 g C·m−2·year−1). Our results indicate that environmental changes like wind stress alter forest phenology that can dynamically regulate ecosystem respiration and gross primary production.
PosE-Enhanced Point Transformer with Local Surface Features (LSF) for Wood–Leaf Separation
Authors: Lu Xin , Wang Ruisheng , Zhang Huaiqing , Zhou Ji , Yun Ting
Published: December 2024

Wood–leaf separation from forest LiDAR point clouds is a challenging task due to the complex and irregular structures of tree canopies. Traditional machine vision and deep learning methods often struggle to accurately distinguish between fine branches and leaves. This challenge arises primarily from the lack of suitable features and the limitations of existing position encodings in capturing the unique and intricate characteristics of forest point clouds. In this work, we propose an innovative approach that integrates Local Surface Features (LSF) and a Position Encoding (PosE) module within the Point Transformer (PT) network to address these challenges. We began by preprocessing point clouds and applying a machine vision technique, supplemented by manual correction, to create wood–leaf-separated datasets of forest point clouds for training. Next, we introduced Point Feature Histogram (PFH) to construct LSF for each point network input, while utilizing Fast PFH (FPFH) to enhance computational efficiency. Subsequently, we designed a PosE module within PT, leveraging trigonometric dimensionality expansion and Random Fourier Feature-based Transformation (RFFT) for nuanced feature analysis. This design significantly enhances the representational richness and precision of forest point clouds. Afterward, the segmented branch point cloud was used to model tree skeletons automatically, while the leaves were incorporated to complete the digital twin. Our enhanced network, tested on three different types of forests, achieved up to 96.23% in accuracy and 91.51% in mean intersection over union (mIoU) in wood–leaf separation, outperforming the original PT by approximately 5%. This study not only expands the limits of forest point cloud research but also demonstrates significant improvements in the reconstruction results, particularly in capturing the intricate structures of twigs, which paves the way for more accurate forest resource surveys and advanced digital twin construction.
Advancing Healthcare Through the Integration of Digital Twins Technology: Personalized Medicine’s Next Frontier
Authors: Attaran Sharmin , Attaran Mohsen
Published: December 2024

The use of Digital Twin technology has been expanding rapidly, and projections indicate that it will continue to proliferate across various applications, use cases, and industries, including healthcare. In recent years, the healthcare sector has seen an acceleration in digital transformation. This fast-paced change offers both opportunities and risks, especially with emerging technologies like digital twins, which are relatively untested and still in the early stages of adoption in medical care. This paper aims to conduct a literature review to explore how digital twins facilitate intelligent automation in healthcare. It defines the concept, traces the technology’s evolution and development, reviews its key enabling technologies, and examines current trends and challenges. The paper also presents a range of application examples in personalized medicine and public health, concluding with a succinct discussion of the primary technical and ancillary challenges, as well as the ethical issues that arise when applying digital twin technology to human subjects.
The Influence of Ultraviolet Radiation on the Surface Roughness of Prints Made on Papers with Natural and Bleached Hemp Fibers
Authors: Barbarić-Mikočević Željka , Bates Irena , Rudolf Maja , Plazonić Ivana
Published: December 2024

In the papermaking industry, cellulose fibers often undergo a bleaching process which affects the surface of the fibers, or their overall morphology. The surface of the produced paper, which is most often used as a printing substrate, depends on the production method, the arrangement of the cellulose fibers, and the quantity and fineness of the filler. The micro-irregularities caused by the uneven distribution of fibers and surface particles of the filler make the paper’s surface rough and affect the print quality and its stability when exposed to light from the moment of production to use. The unbleached cellulose fibers in the printing substrate contain natural pigments, lignin and hemicellulose that absorb UV radiation, as opposed to bleached fibers, which have higher whiteness and lightfastness. Therefore, the influence of UV radiation on the surface roughness of prints made on papers with natural unbleached and bleached hemp fibers was analyzed. This research confirmed that papers formed from unbleached fibers have rougher surface and that printed graphic products from bleached fibers have higher stability to UV radiation than those from natural, unbleached hemp fibers after 96 h of treatment in the Suntest chamber.
The Slovenian Version of the Thirst Distress Scale for Patients with Heart Failure: Translation and Psychometric Evaluation
Authors: Plesec Špela , Kvas Andreja , Lainscak Mitja , Jaarsma Tiny , Waldréus Nana , Farkas Jerneja
Published: December 2024

Thirst is a common symptom in patients with heart failure (HF), which can cause a high degree of distress. Increased fluid intake due to thirst can lead to clinical deterioration because of shifts in volume status. The thirst assessment should be included in routine patient follow-up; however, only a limited set of validated instruments are available. Aims: To translate and evaluate psychometric properties of the Slovenian version of the Thirst Distress Scale for Patients with Heart Failure (TDS-HF). Methods: The English version of the TDS-HF was translated back and forth into the Slovenian language. The psychometric evaluation included content validity, internal consistency, construct validity, and concurrent validity assessments. For this purpose, we also evaluated thirst intensity using a visual analogue scale (VAS, 100 mm). Results: Overall, 159 patients with HF (mean age 71 ± 9 years, 69% male, 77% in the New York Heart Association (NYHA) functional class II-III, mean Left Ventricular Ejection Fraction (LVEF) 36 ± 12%) completed the TDS-HF. Confirmatory factor analysis (CFA) supported the one-factor structure of the scale. The Slovenian version demonstrated good content validity (scale content validity index based on the average method (S-CVI/Ave) 0.96) and internal consistency (Cronbach’s alpha 0.83). In terms of concurrent validity, a positive correlation was observed between TDS-HF and thirst intensity (r = 0.36, p ≤ 0.01). Conclusions: The psychometric evaluation of the Slovenian version of the TDS-HF showed adequate psychometric properties, indicating that the scale is suitable for clinical practice and research in Slovenia to measure thirst distress in patients with HF.
Evaluation of the Epidemiological Disease Burden and Nationwide Cost of Endometriosis in Hungary
Authors: Pónusz-Kovács Dalma , Pónusz Róbert , Sántics-Kajos Luca Fanni , Csákvári Tímea , Kovács Bettina , Várnagy Ákos , Kovács Kálmán András , Bódis József , Boncz Imre
Published: December 2024

Background: Endometriosis is one of the most common gynecological diseases that can lead to infertility. The aim of this quantitative, descriptive, and cross-sectional study was to analyze the prevalence and the annual nationwide health insurance treatment cost of endometriosis in Hungary in 2010 and 2019. Methods: The data used in this study were sourced from publicly funded, national, real-world datasets administered by the National Health Insurance Administration (NHIFA). The total number of cases of endometriosis in the Hungarian population was determined by ICD codes and all types of care. The total prevalence, age-specific prevalence, and annual health insurance expenditure by age group were evaluated. Results: The highest numbers of patients and prevalence (2010: 101.9/100,000 women; 2019: 197.3/100,000 women) were found in outpatient care. Endometriosis, regardless of its type, mainly affects patients in the 30–39-year age group (number of patients—2010: 6852; 2019: 11,821). The NHIFA spent a total of EUR 1,639,612 on endometriosis treatment in 2010 and EUR 1,905,476 in 2019. The average annual health insurance expenditure per capita was EUR 574 in 2010 and EUR 426 in 2019. There was a significant correlation between length of stay and mean age of patients in both years (2010 r = 0.856, p < 0.001; 2019 r = 0.877, p < 0.001). Conclusions: The number endometriosis cases is increasing. Early diagnosis and targeted treatment would reduce endometriosis symptoms and therefore improve patients’ quality of life and reduce health insurance costs. This would be helped by the establishment of endometriosis centers.
Perceived Health Needs, Social Support, and Depression Among Patients with Myocardial Infarction: A Cross-Sectional Study
Authors: Alshammari Bushra , Alrshedy Fatmah Awad , Alrasheeday Awatif M. , Alkubati Sameer , Tlili Mohamed Ayoub , Aouicha Wiem , Dardouri Maha , Alshammari Sarah Basheer , Alanazi Hanan Qayyadh , Alshammari Teflah Saud , Alharbi Abdullah Ayad , Alreshidi Nashi Masnad , Alrashedi Hind Abdullah , Alshammari Nouf Shannan , Alshammari Farhan , Alshammari Afrah Madyan , Alruwaili Abeer Nuwayfi , Alshammari Sahar Maziad
Published: December 2024

Background: Cardiovascular diseases are the leading cause of mortality globally. Myocardial infarction (MI), a major type of cardiovascular disease, presents long-term challenges for patients. Recognizing patients’ perceived health needs and the factors that influence them is crucial for providing comprehensive care and improving outcomes. Aim: This paper explores the perceived health needs, levels of depression, and social support among MI patients, as well as investigates the correlations between these factors. Methods: A cross-sectional study was conducted at King Salman Specialist Hospital from March to June 2024, enrolling 244 MI patients through convenience sampling. Data collection was performed using the following three validated questionnaires: the Cardiac Patient Learning Needs Inventory (CPLNI) to assess the learning needs of MI patients, the Patient Health Questionnaire-9 (PHQ-9) to evaluate depression levels, and the Oslo Social Support Scale (OSSS-3) to measure social support. Statistical analysis was carried out using IBM SPSS Statistics, Version 27. Results: Patients aged 40 years or older and those who were employed exhibited greater learning needs (p < 0.001). Female patients were more depressed than males (p = 0.008). Higher social support was reported by the female patients, those with a family history of MI, and those who were employed (p = 0.002, 0.002, and 0.003, respectively). The total mean score for perceived learning needs was 3.72, with the highest needs in “other pertinent information”, “medication information”, and “anatomy and physiology”. Depression was indicated in 45.1% of MI patients, with significantly higher depression levels in female than in male patients. Additionally, a significant positive correlation was found between social support and perceived learning needs (r = 0.205, p = 0.001), as well as a negative correlation between social support and depression (r = −0.441, p < 0.001). Conclusions: Addressing both the physical and psychological needs is essential for MI patients. Comprehensive educational programs and mental health support services are necessary for improving outcomes. Personalized patient education and routine depression screenings should be integrated into post-MI care. Future research should examine longitudinal changes in learning needs and mental health status.
A Parallel-Optimized Visualization Method for Large-Scale Multiple Video-Augmented Geographic Scenes on Cesium
Authors: Chen Qingxiang , Chen Jing , Sun Kaimin , Huang Minmin , Chen Guang , Liu Hao
Published: December 2024

Surveillance video has emerged as a crucial data source for web Geographic Information Systems (GIS), playing a vital role in traffic management, facility monitoring, and anti-terrorism inspections. However, previous methods encountered significant challenges in achieving effective large-scale multi-video overlapping visualization and efficiency, particularly when organizing and visualizing large-scale video-augmented geographic scenes. Therefore, we propose a parallel-optimized visualization method specifically for large-scale multi-video augmented geographic scenes on Cesium. Firstly, our method employs an improved octree-based model for the unified management of large-scale overlapping videos. Then, we introduce a novel scheduling algorithm based on Cesium, which leverages a Web Graphics Library (WebGL) parallel-optimized and dynamic Level-of-Detail (LOD) strategy. This algorithm is designed to enhance the visualization effects and efficiency of large-scale video-integrated geographic scenes. Finally, we perform comparative experiments to demonstrate that our proposed method significantly optimizes the visualization of video overlapping areas and achieves a rendering efficiency increase of up to 95%. Our method can provide a solid technical foundation for large-scale surveillance video scene management and multi-video joint monitoring.
IGF-1 Signaling Modulates Oxidative Metabolism and Stress Resistance in ARPE-19 Cells Through PKM2 Function
Authors: Ravera Silvia , Puddu Alessandra , Bertola Nadia , Verzola Daniela , Russo Elisa , Maggi Davide , Panfoli Isabella
Published: December 2024

The retinal pigment epithelium (RPE) contributes to retinal homeostasis, and its metabolic dysfunction is implied in the development of retinal degenerative disease. The isoform M2 of pyruvate kinase (PKM2) is a key factor in cell metabolism, and its function may be affected by insulin-like growth factor 1 (IGF-1). This study aims to investigate the effect of IGF-1 on PKM2 modulation of RPE cells and whether co-treatment with klotho may preserve it. ARPE-19 cells, an ex vivo model of human pigmented epithelium, were exposed to IGF-1. Then, we evaluated PKM2 expression, dimerization and subcellular localization, energy metabolism, and redox balance, and whether pre-treatment with Klotho may antagonize the effects of IGF-1. The results show that IGF-1 favors PKM2 dimerization, thus reducing the activity of PKM2 and leading to an altered cellular energy status coupled with reduced oxidative stress. In conclusion, PKM2 plays a pivotal role in the modulation of RPE metabolism and redox balance and could explain the mechanisms through which IGF-1 participates in the pathogenesis of some retinal diseases. Klotho may exert protective effects by mitigating the IGF-1 signal and its effect on mitochondrial function.
Design and Implementation of an Intelligent Web Service Agent Based on Seq2Seq and Website Crawler
Authors: Hsih Mei-Hua , Yang Jian-Xin , Hsieh Chen-Chiung
Published: December 2024

This paper proposes using a web crawler to organize website content as a dialogue tree in some domains. We build an intelligent customer service agent based on this dialogue tree for general usage. The encoder-decoder architecture Seq2Seq is used to understand natural language and then modified as a bi-directional LSTM to increase the accuracy of the polysemy cases. The attention mechanism is added in the decoder to improve the problem of accuracy decreasing as the sentence grows in length. We conducted four experiments. The first is an ablation experiment demonstrating that the Seq2Seq + Bi-directional LSTM + Attention mechanism is superior to LSTM, Seq2Seq, Seq2Seq + Attention mechanism in natural language processing. Using an open-source Chinese corpus for testing, the accuracy was 82.1%, 63.4%, 69.2%, and 76.1%, respectively. The second experiment uses knowledge of the target domain to ask questions. Five thousand data from Taiwan Water Supply Company were used as the target training data, and a thousand questions that differed from the training data but related to water were used for testing. The accuracy of RasaNLU and this study were 86.4% and 87.1%, respectively. The third experiment uses knowledge from non-target domains to ask questions and compares answers from RasaNLU with the proposed neural network model. Five thousand questions were extracted as the training data, including chat databases from eight public sources such as Weibo, Tieba, Douban, and other well-known social networking sites in mainland China and PTT in Taiwan. Then, 1000 questions from the same corpus that differed from the training data for testing were extracted. The accuracy of this study was 83.2%, which is far better than RasaNLU. It is confirmed that the proposed model is more accurate in the general field. The last experiment compares this study with voice assistants like Xiao Ai, Google Assistant, Siri, and Samsung Bixby. Although this study cannot answer vague questions accurately, it is more accurate in the trained application fields.
Genomic Analysis Reveals Novel Genes and Adaptive Mechanisms for Artificial Diet Utilization in the Silkworm Strain Guican No.5
Authors: Xin Lei , Guan Delong , Wei Nan , Zhang Xiaoyan , Deng Weian , Li Xiaodong , Song Jing
Published: December 2024

The transition from traditional mulberry leaf feeding to artificial diet cultivation represents a major advancement in modern sericulture, yet the genetic mechanisms driving this adaptation remain largely unexplored. This study investigates the genomic basis of artificial diet adaptation in the silkworm strain Guican No.5 through whole-genome resequencing and transcriptome analysis. We identified 8,935,179 single-nucleotide polymorphisms (SNPs) across all chromosomes, accounting for 2.01% of the genome, with particularly high densities observed in chromosomes 23, 26, and 28. Our analysis also revealed 879 novel transcripts, many of which are involved in digestion, detoxification, and stress response pathways. Key novel genes, including three carboxylesterases, two cytochrome P450s, one heat shock protein, and one copper/zinc superoxide dismutase, exhibited varying degrees of sequence similarity to known proteins, suggesting modifications to existing genetic frameworks. Notably, one novel P450 gene displayed only 74.07% sequence identity with its closest homolog, indicating the emergence of a new protein sequence. Additionally, several key genes showed high similarity to wild silkworm (Bombyx mandarina) proteins, underscoring their evolutionary origins. These findings provide valuable insights into the molecular mechanisms underpinning artificial diet adaptation in silkworms and offer genomic resources to enhance artificial diet formulations and breeding programs in sericulture.
Intraoperative Patellofemoral Kinematic Acquisition: The Design, Testing, and Validation of a Setup for Clinical Studies
Authors: Favaro Alberto , Bonanzinga Tommaso , Avallone Giulia , Bignozzi Simone , Costantini Marta , Iacono Francesco
Published: December 2024

Background/Objectives: Abnormalities in patellar tracking, often overlooked in surgical planning, have been identified as a contributing factor to total knee arthroplasty (TKA) complications, including anterior knee pain, patellar subluxation, and dislocation. This study aims to evaluate the repeatability of a novel intraoperative setup for assessing patellofemoral kinematics and its interaction with prosthesis design and positioning during surgery. This setup may support personalized alignment techniques in TKA, potentially improving surgical outcomes. Methods: Kinematic data were collected under both native and post-TKA conditions, and the Repeatability Coefficient (RC), Intraclass Correlation Coefficient (ICC), and Limits of Agreement of the Mean were calculated to assess measurement reliability. Results: RC values indicated high repeatability, with patellar flexion averaging an RC of 1°. Rotation and tilt demonstrated an RC below 1° post-mid-flexion, while patellar shift maintained an RC of approximately 1.6 mm. ICC and the extended Bland and Altman analysis showed an excellent agreement (ICC > 0.9) and an expected mean difference of zero for all the measured parameters. Measurements were consistent across both flexion and extension, and between native and post-TKA conditions. Conclusions: The proposed setup for intraoperative patellofemoral kinematic assessment demonstrated high repeatability and practical utility. The approach was found to be non-intrusive to patellar motion tracking and can be robustly integrated into the intraoperative workflow. This method provides a reliable approach for real-time patellar tracking, which may contribute to more personalized and precise TKA procedures, potentially reducing post-surgical dissatisfaction and complications.
Anterior Vertebral Body Tethering (AVBT) in the Treatment of Adolescent Idiopathic Scoliosis: A Retrospective Study
Authors: Balsano Massimo , Vacchiano Andrea , Spina Mauro , Lodi Federico , Criveller Pietro , Zoccatelli Fabio , Corbolini Alberto , Colombini Antonio Gioele , Campisi Alessio , Giovannetti Riccardo , Infante Maurizio Valentino
Published: December 2024

Background/Objectives: Anterior Vertebral Body Tethering (AVBT) is a relatively novel minimally invasive surgical technique for the treatment of adolescent idiopathic scoliosis (AIS) that enables deformity correction of the spine diminishing vertebral motion reduction caused by the standard posterior spinal fusion approach. This paper reports the introduction of a new technical variant of AVBT, with the aim of evaluating its effectiveness on the correction of both axial and coronal spinal deformity. Methods: A single-centre single-surgeon retrospective cohort study was conducted. AVBTs were performed between 2020 and 2024. Radiographical values, surgical details, and complications of 67 patients affected by AIS were compared before surgery, immediately after surgery, and at the most recent follow-up. Results: Postoperative results have revealed a statistically significant coronal curve correction of 29.85% in the main thoracic (MT) curves (from mean preoperative width of 54.81 ± 11.86° to 38.45 ± 10.19°) and of 26.93% in the thoracolumbar (TL/L) curves (from 35.15 ± 11.83° to 25.69 ± 10.50°) in line with that obtained by the standard technique. Coronal correction at the most recent follow-up was maintained. Postoperative axial rotation reduction was found to be statistically significant in the main thoracic (MT) curves (from mean Nash-Moe value of 1.84 ± 0.71 to 1.36 ± 0.73), with a further decrease at the most recent follow-up compared with preoperative values. Improvement in other radiographical measures did not reach statistical significance and the complication rate was comparable to the standard technique. Conclusions: The extent of coronal correction in patients treated with the proposed modified AVBT technique is satisfactory and in line with results from studies testing the standard AVBT technique. The findings of this study seem to suggest that this technical variant of AVBT is effective in the correction of both axial and coronal deformity, with a surgical complication rate comparable to the standard technique.
Evaluating the Accuracy of the SIL Score for Predicting the Sepsis Mortality in Emergency Department Triages: A Comparative Analysis with NEWS and SOFA
Authors: Devia Jaramillo German , Erazo Guerrero Lilia , Florez Zuñiga Natalia , Martin Cuesta Ronal Mauricio
Published: December 2024

Background/Objective: Sepsis is a disease with a high mortality rate, which emphasizes the importance of developing tools for the early identification of high-risk patients and to initiate timely treatments to reduce mortality. The SIL score is a scale that uses the shock index and arterial lactate level to identify early on the patients that are at a high risk of in-hospital mortality due to sepsis. The purpose of this study was to validate the SIL score as a tool for estimating the probability of sepsis in-hospital mortality from the triage room in emergency departments. Additionally, the advantages of the SIL score were evaluated in comparison with NEWS and SOFA. Methods: All of the patients with suspected sepsis were prospectively recruited from the triage room in an emergency department. The SIL score, as well as other evaluation scales, were calculated for these patients. The sensitivity, specificity, predictive values, and areas under the curve (AUC) of each scale were assessed to predict mortality. Results: This study included 315 patients. The total mortality of the cohort was 20.4%. Of the total population, 35.5% were in septic shock. The SIL, NEWS, and SOFA scores had similar sensitivities, approximately 60%; however, a higher specificity was documented in the SIL score over the other scales (67%). The SIL score demonstrated superior discriminatory ability compared to the NEWS and SOFA scores (AUC = 0.754, p = 0.01). Conclusions: The SIL score proved to be a useful tool for predicting in-hospital mortality due to sepsis. Its discriminatory ability surpasses that of other evaluated scales. Therefore, the SIL score can be successfully implemented in the triage room of emergency departments to improve the identification and early management of patients with sepsis.
Navigating Heart–Lung Interactions in Mechanical Ventilation: Pathophysiology, Diagnosis, and Advanced Management Strategies in Acute Respiratory Distress Syndrome and Beyond
Authors: Zakynthinos George E. , Tsolaki Vasiliki , Mantzarlis Kostantinos , Xanthopoulos Andrew , Oikonomou Evangelos , Kalogeras Konstantinos , Siasos Gerasimos , Vavuranakis Manolis , Makris Demosthenes , Zakynthinos Epaminondas
Published: December 2024

Patients in critical condition who require mechanical ventilation experience intricate interactions between their respiratory and cardiovascular systems. These complex interactions are crucial for clinicians to understand as they can significantly influence therapeutic decisions and patient outcomes. A deep understanding of heart–lung interactions is essential, particularly under the stress of mechanical ventilation, where the right ventricle plays a pivotal role and often becomes a primary concern. Positive pressure ventilation, commonly used in mechanical ventilation, impacts right and left ventricular pre- and afterload as well as ventricular interplay. The right ventricle is especially susceptible to these changes, and its function can be critically affected, leading to complications such as right heart failure. Clinicians must be adept at recognizing and managing these interactions to optimize patient care. This perspective will analyze this matter comprehensively, covering the pathophysiology of these interactions, the monitoring of heart–lung dynamics using the latest methods (including ECHO), and management and treatment strategies for related conditions. In particular, the analysis will delve into the efficacy and limitations of various treatment modalities, including pharmaceutical interventions, nuanced ventilator management strategies, and advanced devices such as extracorporeal membrane oxygenation (ECMO). Each approach will be examined for its impact on optimizing right ventricular function, mitigating complications, and ultimately improving patient outcomes in the context of mechanical ventilation.
A Systematic Review and Meta-Analysis of an Angiotensin Receptor–Neprilysin Inhibitor in Patients Using a Durable Left Ventricular Assist Device
Authors: Hasabo Elfatih A. , Isik Burce , Elgadi Ammar , Yacoub Magdi S. , Bakr Mohamed S. , Eljack Mohammed Mahmmoud Fadelallah , Sultan Sherif , Caliskan Kadir , Soliman Osama
Published: December 2024

Introduction: Sacubitril/valsartan is an angiotensin receptor–neprilysin inhibitor (ARNI) drug used to treat patients with heart failure and has shown improvement in outcomes. Different studies reported the use of an ARNI in patients using left ventricular assist devices (LVADs). However, there are limited data on the use of ARNIs in this population. We aimed to assess the efficacy of ARNIs in LVAD patients. Methods: A systematic search was performed in PubMed, Scopus, Web of Science, Embase, and Cochrane from inception to November 2024. We used all relevant words for “ARNI” and “LVAD” to search, and we included studies that assessed ARNIs in patients with LVAD. Efficacy and safety outcomes were extracted from the included studies. R software version 4.4.2 was used for a meta-analysis. Results: Seven studies totaling 249 patients were included. The ARNI was found to be effective in improvements from baseline in the New York Heart Association (NYHA), B-type natriuretic peptide (BNP) (mean = −630.07 pg/mL, 95% CI [−1113.13, −147.01]), diuretic dose (furosemide equivalents) (mean= −76.05 mg/day, 95% CI [−145.11, −6.99]), left ventricular end-diastolic diameter (LVEED) (mean = −7.3 mm, 95% CI [−11.4, −3.1]), and left ventricular ejection fraction (LVEF) (mean =5, 95% CI [3.52, 6.48]). No improvement was found in the creatinine (Cr) level. However, a slight increase in the potassium level was noticed (mean= 0.17 mEq/L, 95% CI [0.02, 0.34]). The overall mortality in patients using the ARNI was 5%, 95% CI [0.00, 20], and discontinuation was found in 25%, 95% CI [0, 100]. Conclusions: The ARNI improved several cardiac structural and hemodynamic parameters in patients on LVAD support.
Characterizing Muscle Tissue Quality Post-Stroke: Echovariation as a Clinical Indicator
Authors: Asadi Borhan , Pujol-Fuentes Clara , Carcasona-Otal Alberto , Calvo Sandra , Herrero Pablo , Lapuente-Hernández Diego
Published: December 2024

Background/Objectives: Strokes remain a major global health concern, contributing significantly to disability and healthcare costs. Currently, there are no established indicators to accurately assess the degree of muscle tissue impairment in stroke-affected individuals. However, ultrasound imaging with an echotexture analysis shows potential as a quantitative tool to assess muscle tissue quality. This study aimed to identify specific echotexture features in the gastrocnemius medialis that effectively characterize muscle impairment in post-stroke individuals. Methods: An observational study was conducted with 22 post-stroke individuals. A total of 21 echotexture features were extracted and analyzed, including first-order metrics, a grey-level co-occurrence matrix, and a grey-level run length matrix. The modified Heckmatt scale was also applied to correlate with the most informative echotexture features. Results: Among the features analyzed, echovariation (EV), echointensity, and kurtosis emerged as the most informative indicators of muscle tissue quality. The EV was highlighted as the primary feature due to its strong and significant correlation with the modified Heckmatt scale (r = −0.81, p < 0.001) and its clinical and technical robustness. Lower EV values were associated with poorer muscle tissue quality, while higher values indicated better quality. Conclusions: The EV may be used as a quantitative indicator for characterizing the gastrocnemius medialis muscle tissue quality in post-stroke individuals, offering a more nuanced assessment than traditional qualitative scales. Future studies should investigate the correlation between the EV and other clinical outcomes and explore its potential to monitor the treatment efficacy, enhancing its applicability in clinical practice.
Women with IBD Show Higher Psychophysiological Burden in Comparison to Men with IBD
Authors: Schulz Franziska , Foldenauer Ann Christina , Weidmann Lara , Thomann Anne Kerstin , Tal Andrea Oliver , Plachta-Danielzik Sandra , Krause Thomas , Bokemeyer Bernd , Zeuzem Stefan , Kubesch Alica , Blumenstein Irina
Published: December 2024

Background: Inflammatory bowel disease (IBD) remains an incurable illness. Patients with IBD show gender-specific differences in various aspects of the disease. There is still uncertainty about the causality of the differences. Methods: The aim of this study was to determine the most relevant psychophysiological gender-specific differences in IBD. For this purpose, a questionnaire survey was conducted on disease activity and psychological concomitant diseases in patients with IBD (n = 300). Among the 218 patients with IBD who provided gender information, both genders were equally distributed. Results: Females with IBD are significantly more affected by IBD-related symptoms than men. Disease activity Scores Harvey-Bradshaw Index (HBI), Partial Mayo Score (pMAYO) showed no significant differences between the sexes in the subgroups with CD (HBI, m: 3 (IQR 1–6), w: 4 (IQR 2–8), p = 0.0677) and UC (pMAYO, m: 1 (IQR 0–4), w: 3 (IQR 0–5), p = 0.2118). IBD Questionnaire (IBDQ)shows significant differences in the gender-specific analysis. The mean value of the IBDQ total score of the female participants was 4.4 (SD 1.1) and that of men was 5.0 (SD 1.0) (p = 0.0002). Conclusions: There is a great need to investigate the causality of gender-specific differences in greater depth.
A Deep Learning Method for Inversing 3D Temperature Fields Using Sea Surface Data in Offshore China and the Northwest Pacific Ocean
Authors: Wu Xiangyu , Zhang Mengqi , Wang Qingchang , Wang Xidong , Chen Jian , Qin Yinghao
Published: December 2024

Three-dimensional ocean temperature field data with high temporal-spatial resolution bears a significant impact on ocean dynamic processes such as mesoscale eddies. In recent years, with the rapid development of remote sensing data, deep learning methods have provided new ideas for the reconstruction of ocean information. In the present study, based on sea surface data, a deep learning model is constructed using the U-net method to reconstruct the three-dimensional temperature structure of the Northwest Pacific and offshore China. Next, the correlation between surface data and underwater temperature structure is established, achieving the construction of a three-dimensional ocean temperature field based on sea surface height and sea surface temperature. A three-dimensional temperature field for the water layers within the depth of 1700 m in the Northwest Pacific and offshore China is reconstructed, featuring a spatial resolution of 0.25°. Control experiments are conducted to explore the impact of different input variables, labels, and loss functions on the reconstruction results. This study’s results show that the reconstruction accuracy of the model is higher when the input variables are anomalies of sea surface temperature and sea surface height. The reconstruction results using the mean square error (MSE) and mean absolute error (MAE) loss functions are highly similar, indicating that these two loss functions have no significant impact on the results, and only in the upper ocean does the MSE value slightly outperform MAE. Overall, the results show a rather good spatial distribution, with relatively large errors only occurring in areas where the temperature gradient is strong. The reconstruction error remains quite stable over time. Furthermore, an analysis is conducted on the temporal-spatial characteristics of some mesoscale eddies in the inversed temperature field. It is shown that the U-net network can effectively reconstruct the temporal-spatial distribution characteristics of eddies at different times and in different regions, providing a good fit for the eddy conditions in offshore China and the Northwest Pacific. The inversed eddy features are in high agreement with the eddies in the original data.
A Feasibility Study of Cross-Medium Direct Acoustic Communication Between Underwater and Airborne Nodes
Authors: Yang Shaojian , Lu Yi , Wei Yan , Zhu Jiang , Tu Xingbin , Yang Yimu , Qu Fengzhong
Published: December 2024

With the rapid advancement of underwater communication and unmanned aerial vehicle (UAV) technologies, the potential applications of cross-medium communication in environmental monitoring, maritime Internet of Things (IoTs), and rescue operations, in particular, have attracted great attention. This study explores the feasibility of achieving cross-medium direct acoustic communication through the air–water interface. Specifically, it investigates challenges such as acoustic impedance mismatches and signal attenuation caused by energy loss during interface transmission, aiming to understand their impact on communication performance. Experimental tests employed underwater acoustic transducers as signal transmitters to propagate sound waves directly into the air, attempting to establish communication links with aerial UAV nodes. Preliminary experimental results indicate that even conventional underwater acoustic transducers can achieve information exchange between underwater nodes and UAVs, laying a foundation for further research and application of cross-medium communication systems.
Assessing Land-Cover Change and Urbanization Impact on Riparian Zones in South Carolina: A Decade of Transition
Authors: Sharma Sanjeev , Khanal Puskar
Published: December 2024

This study investigates land-cover changes along riparian zones in South Carolina, focusing on intermittent and perennial streams to assess the impact of urbanization, forest loss, and impervious surface expansion on sensitive ecosystems. South Carolina’s diverse geography, ranging from coastal marshes to the Blue Ridge Mountains, and subtropical humid climate, offers a rich context for understanding environmental changes. The research utilizes various geospatial datasets, including the National Land Cover Database (NLCD), National Hydrography Dataset (NHD), and National Agricultural Imagery Program (NAIP) imagery, to evaluate changes in forest cover, urbanization, and impervious surfaces from 2011 to 2021 as a decade of transition. The study areas were divided into buffer zones around intermittent and perennial streams, following South Carolina’s riparian management guidelines. The results indicate significant land-cover transitions, including a total of 3184.56 hectares of non-urban areas converting to forest within the 100 m buffer around intermittent streams. In contrast, 137.43 hectares of forest transitioned to urban land in the same buffer zones, with Spartanburg and Greenville leading the change. Intermittent stream buffers exhibited higher imperviousness (4.6–5.5%) compared to perennial stream buffers (3.3–4.5%), highlighting the increased urban pressure on these sensitive areas. Furthermore, tree canopy loss was significant, with counties such as Greenwood and Chesterfield experiencing substantial reductions in canopy cover. The use of high-resolution NAIP imagery validated the land-cover classifications, ensuring accuracy in the results. The findings emphasize the need for effective land-use management, particularly in the riparian zones, to mitigate the adverse impacts of urban expansion and to safeguard water quality and biodiversity in South Carolina’s streams.
Cultural Tourism in Buzău Carpathians and Sub-Carpathians (Romania): Local Businesses’ Perspective
Authors: Grigorescu Ines , Mitrică Bianca , Roznoviețchi Irena , Şerban Paul-Răzvan , Dumitraşcu Monica , Damian Nicoleta , Dumitrică Cristina
Published: December 2024

Cultural tourism plays a growing role both in tourists’ preferences and in tourism development options in many regions of the world. This paper examines how businesses in the Buzău Carpathians and Sub-Carpathians, a predominantly rural region where tourism relies heavily on the natural landscapes and cultural heritage, perceive cultural tourism. The analysis was performed using a questionnaire survey applied to the local business representatives, focusing on three key areas: (a) their interaction with visitors and contribution to the local economy; (b) their role as drivers of cultural tourism and improving communities’ livelihoods; and (c) the current and future challenges they face. This study highlights the way in which local businesses support cultural tourism, empower local communities, and contribute to local and regional development through their connections with cultural and heritage attractions. Despite these businesses facing challenges such as inadequate infrastructure, limited promotion, a narrow cultural tourism offering, and weak institutional collaboration, the research findings emphasize their pivotal role in fostering both local and regional development.
Effect of Asphalt Granulation on the Performance of Artificial Graphite Anode Materials for Lithium-Ion Batteries
Authors: Yang Cong , Gong Jun , Jiang Zhao , Lei Tiejun , Zheng Qian , Deng Qi , Li Yejun
Published: December 2024

In order to investigate the effects of the softening point, the addition ratio, and the median particle size (Dv50) of the asphalt on the performance of secondary particles of artificial graphite anode materials prepared by granulation, ten-kilogram orthogonal experiments were designed. Dv50 and powder orientation index (OI) value of the prepared secondary particles of artificial graphite anode materials were employed as evaluation index, and the results of the orthogonal experiments were subjected to polarity analysis, analysis of variance (ANOVA), and multiple linear regression analysis. It is demonstrated that the addition ratio of the asphalt exerts the most pronounced influence on Dv50 and powder OI value of secondary granular artificial graphite anode materials, followed by the softening point. Conversely, the median particle size Dv50 of the asphalt exerts the least significant effect. With regard to the evaluation indices, the optimal granulation conditions were determined to be a softening point of 250 °C, an addition ratio of 11%, and Dv50 of 2–3 μm of the asphalt. Dv50 of the prepared secondary granular artificial graphite anode material was 17.91 μm, with an OI value of 1.91. The specific capacity of the first charging was 340.52 mAh/g, and the first columbic efficiency was 94.79%.
Investigation of the Structure–Property Relation of Anthraquinone Dye Molecules with High Dichroism in Guest–Host Liquid Crystal Systems via Computational Methods
Authors: Chen Ruisi , Guo Xintao , Zhang Bo , Liu Ying , Liu Jun
Published: December 2024

By combining molecular dynamics (MD) simulations and density functional theory (DFT), the influence of dye structure on the optical modulation properties of negative-mode guest–host liquid crystal (GHLC) systems was systematically investigated. Firstly, the reliability of the simulation method was validated by comparing the performance parameters of the GHLC system obtained from simulations with those from experimental results. Subsequently, a series of guest dye molecules, along with their mixtures with negative dielectric anisotropy mesogens, were designed and analyzed. This exploration focused on how variations in dye terminal chain lengths, substitution positions, and substituent group properties affect dye molecular geometry, dye alignment within the host, transition dipole orientation, absorption spectra, and electronic excitation properties. Our findings suggest that dye molecules with a flexible terminal chain substitution of five carbon atoms, positioned at the 2 and 6 locations on the anthraquinone core, exhibit higher order parameters, favorable for enhancing dichroic performance. Moreover, introducing different α-substituents further influences the dye orientation and electronic behavior within the host. These results highlight that structural modifications of anthraquinone-based dyes allow for the design of high-dichroic-ratio materials with customized absorption properties. Overall, our results provide a beneficial understanding of the structure–property relation in GHLC systems, offering valuable guidance for designing high-performance dye molecules and advanced optoelectronic materials in future research.
Progress and Prospects for Titanium Extraction from Titanium-Bearing Blast Furnace Slag
Authors: Qu Yuxuan , Xing Lei , Gao Minglei , Zhao Suxing , Ren Qianqian , Li Lanjie , Long Yue
Published: December 2024

The composition of TBFS is complex. It is categorized into low (W(TiO2) < 5%), medium (5% < W(TiO2) < 20%), and high-titanium slag (W(TiO2) > 20%) based on Ti content. The titanium in the slag is underutilized, causing it to accumulate and contribute to environmental pollution. Current methods for extracting titanium from TBFS include acid leaching, alkali fusion roasting, high-temperature carbonation–low-temperature chlorination, electrochemical molten salt electrolysis, and selective enrichment. However, these methods still face challenges such as environmental impact, high costs, low Ti recovery, and low Ti grade. This paper summarizes the mechanisms and characteristics of the above methods. Future research should focus on integrating pyrometallurgy with beneficiation processes, followed by further purification of titanium-rich phases through hydrometallurgy. Additionally, combining this with novel separation technologies (such as microwave and superconducting magnetic separation) will optimize the dissociation of titanium-bearing phases after enrichment.
Uncovering the Mechanisms of Long-Range Magnetic Order in [Mn(mal)(H2O)]n: Insights from Microscopic and Macroscopic Magnetic Analysis
Authors: Delgado Fernando S. , Cañadillas-Delgado Laura , Rodríguez-Carvajal Juan , Fabelo Óscar , Pasán Jorge
Published: December 2024

In this study, we investigate the magnetic properties of the molecular compound [Mn(mal)(H2O)]ₙ (mal = dianion of malonic acid) by integrating microscopic and macroscopic characterization, combining unpolarized neutron diffraction and magnetometry measurements. Neutron diffraction, though non-commonly applied to molecular compounds, proved essential for fully resolving the magnetic structure, as well as overcoming challenges such as hydrogen-related incoherent scattering and difficulties in accurately locating light atoms. Our neutron data provided critical structural details, including the precise location of hydrogen atoms, especially those associated with crystallization water molecules. By conducting low-temperature measurements below the magnetic ordering temperature, we identified the correct Shubnikov space group (Pc’a21’) and established a magnetic model consistent with the observed weak ferromagnetism. Our findings reveal that the compound presents a spin-canted structure with a weak ferromagnetic signal along the b-axis. This signal originates primarily from antisymmetric exchange interactions rather than single-ion anisotropy, consistent with the isotropic nature of the Mn(II) (6A1g) ground state. The combined neutron diffraction and magnetometry results provide a comprehensive understanding of how structural and symmetry factors influence the magnetic properties of malonate-based manganese compounds.