bluuebunny/crossref_metadata_2025 huggingface dataset:
Soil Microbial Communities and Wine Terroir: Research Gaps and Data Needs
Authors: Franco Gabriela Crystal , Leiva Jasmine , Nand Sanjiev , Lee Danica Marvi , Hajkowski Michael , Dick Katherine , Withers Brennan , Soto LuzMaria , Mingoa Benjamin-Rafael , Acholonu Michael , Hutchins Amari , Neely Lucy , Anand Archana
Published: August 2024

Microbes found in soil can have a significant impact on the taste and quality of wine, also referred to as wine terroir. To date, wine terroir has been thought to be associated with the physical and chemical characteristics of the soil. However, there is a fragmented understanding of the contribution of vineyard soil microbes to wine terroir. Additionally, vineyards can play an important role in carbon sequestration since the promotion of healthy soil and microbial communities directly impacts greenhouse gas emissions in the atmosphere. We review 24 studies that explore the role of soil microbial communities in vineyards and their influence on grapevine health, grape composition, and wine quality. Studies spanning 2015 to 2018 laid a foundation by exploring soil microbial biogeography in vineyards, vineyard management effects, and the reservoir function of soil microbes for grape-associated microbiota. On the other hand, studies spanning 2019 to 2023 appear to have a more specific and targeted approach, delving into the relationships between soil microbes and grape metabolites, the microbial distribution at different soil depths, and microbial influences on wine flavor and composition. Next, we identify research gaps and make recommendations for future work. Specifically, most of the studies utilize targeted sequencing (16S, 26S, ITS), which only reveals community composition. Utilizing high-throughput omics approaches such as shotgun sequencing (to infer function) and transcriptomics (for actual function) is vital to determining the specific mechanisms by which soil microbes influence grape chemistry. Going forward, understanding the long-term effects of vineyard management practices and climate change on soil microbiology, grapevine trunk diseases, and the role of bacteriophages in vineyard soil and wine-making would be a fruitful investigation. Overall, the studies presented shed light on the importance of soil microbiomes and their interactions with grapevines in shaping wine production. However, there are still many aspects of this complex ecosystem that require further exploration and understanding to support sustainable viticulture and enhance wine quality.
Improving Structural, Physical, and Sensitive Properties of Sodium Alginate–Purple Sweet Potato Peel Extracts Indicator Films by Varying Drying Temperature
Authors: Li Wenxin , Zhao Mengna , Xia Xiufang , Zhu Yingchun
Published: August 2024

Sodium alginate (SA)–purple sweet potato peel extracts (PPE) from industrial waste indicator films were developed at different drying temperatures (25, 30, 35, 40, 45, 50, and 55 °C). The effects of drying temperatures on the film’s structural, physical, and sensitive properties were investigated. On the structural properties, scanning electron microscopy, Fourier transform infrared spectroscopy, and X-ray diffraction indicated that compactness, intermolecular interactions, and crystallinity of indicator films were improved at a lower drying temperature. On the physical properties, with the drying temperature increasing, elongation at the break increased significantly (p < 0.05); ΔE and water-vapor permeability decreased significantly (p < 0.05); and thickness and tensile strength initially increased significantly (90.46 → 98.46, 62.99 → 95.73) and subsequently decreased significantly (98.46 → 71.93, 95.73 → 55.44) (p < 0.05), with the maximum values obtained at 30 °C. On sensitivity, the corresponding colors of the films became lighter as the drying temperature increased, and the films exhibited relatively excellent pH and NH3 sensitivity, with easily discernible color changes at lower temperatures. The results of this paper revealed that the overall film characteristics are improved at lower drying temperatures, which will provide valuable references for selecting the drying temperature for preparing indicator films as a guide for industrialized production.
Spicing Up Meat Preservation: Cinnamomum zeylanicum Essential Oil in Meat-Based Functional Foods—A Five-Year Review
Authors: Gheorghe-Irimia Raluca-Aniela , Tăpăloagă Dana , Tăpăloagă Paul-Rodian , Ghimpețeanu Oana-Mărgărita , Tudor Laurențiu , Militaru Manuella
Published: August 2024

Today, in the modern consumer era, we are facing a significant change in terms of preferences and behaviour. This tendency is not only a basic desire, but rather a significant social and cultural movement that exerts a tremendous influence on the food industry and correlated sectors. In this direction, food authorities and experts have thoroughly evaluated the practicality of employing natural preservation methods to enhance the quality and safety of foodstuffs, while preserving their nutritional and sensory attributes. Given this context, the development of meat products enhanced with Cinnamomum zeylanicum essential oil (CZEO) poses promising avenues, such as extended shelf-life due to its antimicrobial, antifungal, and antioxidant properties. CZEO also has many health benefits, rendering it as a promising ingredient in functional meat product formulations. Conversely, challenges such as higher associated costs, sensory interactions, and variability arise. Hence, the aim of this review is to offer a novel critical perspective on CZEO’s potential application as a functional ingredient in meat products formulations and to address the inherent associated challenges, based on the last five years of scholarly publications.
Voltage Controller Design for Offshore Wind Turbines: A Machine Learning-Based Fractional-Order Model Predictive Method
Authors: Safari Ashkan , Hassanzadeh Yaghini Hossein , Kharrati Hamed , Rahimi Afshin , Oshnoei Arman
Published: August 2024

Integrating renewable energy sources (RESs), such as offshore wind turbines (OWTs), into the power grid demands advanced control strategies to enhance efficiency and stability. Consequently, a Deep Fractional-order Wind turbine eXpert control system (DeepFWX) model is developed, representing a hybrid proportional/integral (PI) fractional-order (FO) model predictive random forest alternating current (AC) bus voltage controller designed explicitly for OWTs. DeepFWX aims to address the challenges associated with offshore wind energy systems, focusing on achieving the smooth tracking and state estimation of the AC bus voltage. Extensive comparative analyses were performed against other state-of-the-art intelligent models to assess the effectiveness of DeepFWX. Key performance indicators (KPIs) such as MAE, MAPE, RMSE, RMSPE, and R2 were considered. Superior performance across all the evaluated metrics was demonstrated by DeepFWX, as it achieved MAE of [15.03, 0.58], MAPE of [0.09, 0.14], RMSE of [70.39, 5.64], RMSPE of [0.34, 0.85], as well as the R2 of [0.99, 0.99] for the systems states [X1, X2]. The proposed hybrid approach anticipates the capabilities of FO modeling, predictive control, and random forest intelligent algorithms to achieve the precise control of AC bus voltage, thereby enhancing the overall stability and performance of OWTs in the evolving sector of renewable energy integration.
A High-Order Numerical Method Based on a Spatial Compact Exponential Scheme for Solving the Time-Fractional Black–Scholes Model
Authors: Huang Xinhao , Yu Bo
Published: August 2024

This paper investigates a high-order numerical method based on a spatial compact exponential scheme for solving the time-fractional Black–Scholes model. Firstly, the original time-fractional Black–Scholes model is converted into an equivalent time-fractional advection–diffusion reaction model by means of a variable transformation technique. Secondly, a novel high-order numerical method is constructed with (2−α) accuracy in time and fourth-order accuracy in space based on a spatial compact exponential scheme, where α is the fractional derivative. The uniqueness of solvability of the derived numerical method is rigorously discussed. Thirdly, the unconditional stability and convergence of the derived numerical method are rigorously analyzed using the Fourier analysis technique. Finally, numerical examples are presented to test the effectiveness of the derived numerical method. The proposed numerical method is also applied to solve the time-fractional Black–Scholes model, whose exact analytical solution is unknown; numerical results are illustrated graphically.
Traditional Biomarkers in Patients with Pancreatic Cancer Staged by Computed Tomography and Endoscopic Ultrasound: Is There Still a Role in the Molecular Era?
Authors: Demarzo Maria Giulia , Facchini Chiara , Bisso Giuliana Rosa , Marrone Ciro , Parodi Maria Caterina
Published: August 2024

Serum carbohydrate antigen 19-9 (Ca19-9) is the only approved biomarker approved for the screening and diagnosis of pancreatic cancer (PC), but its value remains controversial. The aim of our study is to evaluate the role of CA 19-9 in the management of PC patients in jaundiced patients staged by both Computed Tomography (CT) and Endoscopic Ultrasound (EUS). Additionally, we evaluated traditional cholestasis marker behavior. Medical records of 73 patients have been retrospectively reviewed. We considered tumor size, tumor stage, CA 19-9, cytolysis, and cholestasis biomarkers. All patients underwent CT scan for staging. EUS +/− fine-needle biopsy (FNB) was performed in doubtful cases. Median alkaline phosphatase (ALP) and y-glutamyltransferase (GGT) levels were significantly lower compared to baseline after the biliary drainage (204 vs. 465 U/L, p < 0.0001, 204. U/L vs. 608.5, p < 0.0001, respectively), whilst no differences were observed for CA 19-9 levels. CA 19-9 showed significant association with the tumor stage in the pre-drainage setting. CT and EUS showed a low agreement in estimating tumor size (mean difference 4.8 mm 95% LoA −10.82–20.38). We did not find any significant correlation between CA 19-9 and bilirubin levels (r = −0.05, p = 0.7). In our cohort, survival rate was lower in patients with higher CA 19-9 levels (log rank p = 0.007). CA 19-9 has some limitations as a biomarker in the PC setting, thus it cannot address the treatment strategy alone. Nonetheless, it provides valuable information, and is not replaceable for the time being.
The Efficacy of Ketamine for Acute and Chronic Pain in Patients with Cancer: A Systematic Review of Randomized Controlled Trials
Authors: Azari Leila , Hemati Homa , Tavasolian Ronia , Shahdab Sareh , Tomlinson Stephanie M. , Babilonia Margarita Bobonis , Huang Jeffrey , Tometich Danielle B. , Turner Kea , Anaraki Kimia Saleh , Jim Heather S. L. , Tabriz Amir Alishahi
Published: August 2024

Managing cancer-related pain poses significant challenges, prompting research into alternative approaches such as ketamine. This systematic review aims to analyze and summarize the impact of ketamine as an adjuvant to opioid therapy for cancer-related pain. We conducted a literature review in MEDLINE, EMBASE, and Scopus from 1 January 1982 to 20 October 2023. Abstracts were screened against inclusion criteria, and eligible studies underwent a full-text review. Data was extracted from the included studies, and a framework analysis approach summarized the evidence regarding ketamine’s use in patients with cancer. A total of 21 randomized clinical trials were included, and the quality of all the included studies was good or fair. Significant improvements in pain scores and reduced morphine consumption were consistently observed with intravenous ketamine administration for postoperative pain control, particularly when combined with other analgesics such as morphine. Ketamine was less effective when used as an analgesic for chronic pain management, with several studies on neuropathic pain or chemotherapy-induced neuropathy finding minimal significant effect on reduction of pain scores or morphine requirements. The efficacy of ketamine in pain management appears to depend on factors such as dosage, route of administration, and patient population.
Concussion in Parasport: A Narrative Review of Research Published since the Concussion in Para Sport (CIPS) Group Statement (2021)
Authors: Ryan Tansy , Ryan Lisa , Daly Ed
Published: August 2024

Sports-related concussion (SRC) is an injury whereby impact to the face/head/neck impairs cognitive functioning. Parasport athletes have an increased risk for SRC. The Previous Concussion in Sport Group iterations lack guidance for parasport SRC assessment, management, and return-to-play. This article aims to investigate the research relating to parasport SRCs published since the 2021 Concussion in Para Sport (CIPS) position statement and highlights possible new recommendations. A literature review of parasport concussions was conducted. Articles citing the 2021 publication and/or published since then were reviewed. Relevant data were extracted and discussed in this article. Since 2021, twelve (n = 12) articles emerged investigating parasport SRC. Parasport athletes experience greater concussion symptoms and severity scores compared to able-bodied athletes. Visually impaired athletes account for >50% of parasport SRCs. Wheelchair basketball and rugby have the highest SRC incidence rates across parasports. Current SRC assessment methodologies are not designed with consideration of parasport athletes’ unique experiences. Guidelines lack a return-to-learning protocol, making returning to education/work challenging for such athletes. Understanding these athletes’ SRC experiences is paramount in supporting their recovery. Specific guidelines for SRC assessment, management, return-to-play, and return-to-learn for parasport athletes are necessary to enhance their rehabilitation and avoid the occurrence of long-term symptoms.
Molecular Responses to Drought and Waterlogging Stresses of Kiwifruit (Actinidia chinensis var. deliciosa) Potted Vines
Authors: Baldi Elena , Pastore Chiara , Chiarelli Giacomo , Quartieri Maurizio , Spinelli Francesco , Toselli Moreno
Published: August 2024

Environmental extremes, such as drought and flooding, are becoming increasingly common, resulting in significant crop losses. The aim of the present study was to understand the molecular response induced by drought and waterlogging conditions, and to link these responses to the physiological adaptation of plants. For this purpose, leaf RNA expression was analyzed in potted kiwifruit plants by Illumina Next Generation Sequences. Stressed plants showed an impairment of all physiological parameters (leaf-gas exchange and stem-water potential) with a more evident effect in waterlogging condition than in drought condition. However, the impact on the transcriptome in waterlogged plants was less intense than in drought stress. Drought affected several metabolic pathways, among which “plant hormone signal transduction”, “protein processing in endoplasmic reticulum”, and “mitogen-activated protein kinase signaling pathway” were the most representative in terms of number of genes involved. The genes involved in the biosynthesis of phenylpropanoids were positively influenced by both drought and waterlogging. Finally, waterlogging stimulated secondary metabolisms by upregulating the genes responsible for the biosynthesis of terpenoids and flavonoids, such as stilbenoids. The obtained results show that the two contrasting stress conditions share several common physiological responses and molecular mechanisms.
Emerging Sensory Methodologies to Support Strawberry Breeding and Future Prospects Combined with Augmented Reality
Authors: Lippi Nico
Published: August 2024

Strawberry production has been continually increasing worldwide, but this growth has often resulted in a lack of taste, favoring yield and plant adaptability instead. However, in recent decades, consumer focus has shifted towards more flavorful fruits. Consequently, the application of new sensory methodologies for consumers in strawberry breeding programs is becoming essential. This review provides an overview of new rapid consumer-based sensory methodologies and a brief summary of their potential applications when combined with Augmented Reality technology. These advancements aim to better understand and meet consumer needs, offering breeders valuable tools for their future work.
Beauty’s Betrayal: Mycobacterium abscessus Case Series Following Aesthetic Procedures in the Brazilian Amazon
Authors: Carbonell Roberto C. C. , Oliveira Letícia L. F. , Galan Luis E. B. , Filardi Eloise T. M. , Lins Alysson B. M. , Nattrodt Jânio J. M. , Dantas Domingos S. M. , Bernardi Adilson C. A. , Cerni Felipe A. , Pucca Manuela B.
Published: August 2024

The Brazilian market holds the second position globally in the beauty sector, poised to surpass the USD 50 billion mark in the upcoming years. Aesthetic procedures encompass a spectrum, ranging from non-invasive ones, such as drainage, radiofrequency, ultrasound, and cryolipolysis, to more invasive techniques, including fillers, botulinum toxin, microneedling, micropigmentation, carboxytherapy, and enzyme application. This wide array of treatments has yielded satisfactory cosmetic results for individuals who opt out of surgical procedures. However, despite being categorized as having low complexity, they still carry inherent risks. These risks are often exacerbated by the breach of the skin barrier, the exposure of organs and spaces, or the presence of implantable devices. Among the bacteria most isolated concerning this matter are non-tuberculous Mycobacteria. This study presents descriptive case reports involving three patients under the care of the Infectious Diseases Department at General Hospital of Roraima (HGR). These patients were diagnosed with Mycobacterium abscessus infections subsequent to undergoing enzyme application procedures. Although these cases involve the same microorganism, they exhibit varying degrees of severity, ranging from the development of locally nodular formations to a progression towards sepsis. These cases provide an opportunity to delve into the diagnostic subtleties and clinical implications of these infections while also prompting a critical evaluation of therapeutic strategies. Additionally, the report underscores the potential risks associated with routine aesthetic procedures.
Dealing with “Do Not Know” Responses in the Assessment of Financial Literacy: The Use of a Sample Selection Model
Authors: Conte Anna , Paiardini Paola , Temperini Jacopo
Published: August 2024

Financial literacy assessments typically rely on sample surveys containing sets of questions designed to gauge respondents’ comprehension of fundamental financial concepts necessary for making informed decisions. The answers to such questions, either categorical or continuous in nature, generally include a “Do not know” option. If those who choose the “Do not know” option are not a random sample of the population but exhibit peculiar characteristics, treating these observations as either incorrect responses or as missing data may distort the results regarding the determinants of financial literacy. A noteworthy case lies in the observation from survey studies that women tend to choose the “Do not know” option more frequently than men. In similar cases, treating the “Do not know” responses as incorrect answers increases the gender gap in financial literacy while treating them as missing values reduces the gap. We propose using a model with sample selection, which enables us to disentangle the inclination to answer “Do not know” from actual responses. By applying this model to a representative sample of the UK population, we do not find any systematic gender gap in financial knowledge. The study’s novel treatment of “Do not know” responses contributes valuable insights to the broader discourse on the determinants of financial literacy and the related gender-based differences.
Non-Invasive Ultrasound Therapy for Severe Aortic Stenosis: Early Effects on the Valve, Ventricle, and Cardiac Biomarkers (A Case Series)
Authors: Trifunović-Zamaklar Danijela , Karan Radmila , Kovačević-Kostić Nataša , Terzić Duško , Milićević Vladimir , Petrović Olga , Canić Ivana , Pernot Mathieu , Tanter Mickael , Wang Louise Z. , Goudot Guillaume , Velinović Miloš , Messas Emmanuel
Published: August 2024

Background: Transcatheter aortic valve replacement (TAVR) was developed for inoperable patients with severe aortic stenosis. However, despite TAVR advancements, some patients remain untreated due to complex comorbidities, necessitating less-invasive approaches. Non-invasive ultrasound therapy (NIUT), a new treatment modality, has the potential to address this treatment gap, delivering short ultrasound pulses that create cavitation bubble clouds, aimed at softening embedded calcification in stiffened valve tissue. Methods: In the prospective Valvosoft® Serbian first-in-human study, we assessed the safety and efficacy of NIUT and its impact on aortic valve hemodynamics, on the left ventricle, and on systemic inflammation in patients with severe symptomatic aortic stenosis not eligible for TAVR or surgery. Results: Ten patients were included. Significant improvements were observed in hemodynamic parameters from baseline to one month, including a 39% increase in the aortic valve area (from 0.5 cm2 to 0.7 cm2, p = 0.001) and a 23% decrease in the mean transvalvular gradient (from 54 mmHg to 38 mmHg, p = 0.01). Additionally, left ventricular global longitudinal strain significantly rose, while global wasted work significantly declined at one month. A dose–response relationship was observed between treatment parameters (peak acoustic power, intensity spatial-peak pulse-average, and mean acoustic energy) and hemodynamic outcomes. NIUT was safely applied, with no clinically relevant changes in high-sensitivity troponin T or C-reactive protein and with a numerical, but not statistically significant, reduction in brain natriuretic peptide (from 471 pg/mL at baseline to 251 pg/mL at one month). Conclusions: This first-in-human study demonstrates that NIUT is safe and confers statistically significant hemodynamic benefits both on the valve and ventricle.
Therapeutic Maintenance of Janus Kinase Inhibitors in Real Life for Rheumatoid Arthritis: Retrospective Study
Authors: Farnos Camille , Barbier Vincent , Doussiere Marie , Deprez Valentine , Hamidou Yannis , Bruy Pierre Antoine , Sobhy Danial Jean Marc , Goeb Vincent
Published: August 2024

Background/Objectives: Janus kinase inhibitors (JAKis) belong to a new class of targeted oral drugs that have been added to the therapeutic arsenal for rheumatoid arthritis (RA). The aim of this study was to evaluate the efficacy and safety profiles of these four available molecules (tofacitinib, baricitinib, filgotinib, and upadacitinib) in real life. Methods: A retrospective, single-center observational study including all patients treated with JAKis for RA from 1 October 2017 to 1 December 2023. We assessed the maintenance rate at 24 months, which is an indirect reflection of the clinical and biological safety and efficacy profiles. Results: The 76 patients in our study were thus treated for the first time with anti-JAK, including 55 patients with baricitinib (BAR), 9 patients with tofacitinib (TOF), 4 patients with upadacitinib (UPA), and 8 patients with filgotinib (FIL). The majority of our patients had BAR introduced as the first intention. The therapeutic maintenance at 2 years for all our patients was 50%. The average maintenance duration was 8.6 months and was similar in all the groups. Of the 76 patients included in this study treated with Baricitinib (72.3%), 38 (50%) discontinued their treatment after two years of follow-up. Conclusions: Although this retrospective study is subject to various biases, it shows that the persistence rates of the four JAKi molecules in daily practice did not differ significantly, thus confirming the long-term efficacy of these drugs.
Cyclical Etidronate Reduces the Progression of Arterial Calcifications in Patients with Pseudoxanthoma Elasticum: A 6-Year Prospective Observational Study
Authors: Harmsen Iris M. , van den Beukel Tim , Kok Madeleine , Visseren Frank L. J. , de Jong Pim A. , Papapoulos Socrates E. , Spiering Wilko
Published: August 2024

Background: Pseudoxanthoma elasticum (PXE), a rare genetic disorder presenting with slowly progressing calcification of various tissues, including the arteries, is caused by mutations in the ABCC6 gene that lead to the reduction of pyrophosphate, a natural inhibitor of calcification. We showed that, compared to a placebo, the cyclical administration of etidronate, a stable pyrophosphate analog, significantly reduced arterial calcification assessed by low-dose CT scans after one year. The aim of the present prospective, single center, observational cohort study was the assessment of the efficacy and safety of cyclical etidronate in patients treated for periods longer than one year. Methods: Seventy-three patients were followed for a median of 3.6 years without etidronate and 2.8 years with etidronate, and each patient served as their own control. Results: The median absolute yearly progression of total calcification volume during the period with etidronate (388 [83–838] µL) was significantly lower than that without etidronate (761 [362–1415] µL; p < 0.001). The rates of the relative progression of arterial calcification were 11.7% (95% CI: 9.6–13.9) without etidronate compared to 5.3% (95% CI: 3.7–7.0) with etidronate, after adjustment for confounders. Conclusions: The cyclical administration of etidronate for nearly 3 years significantly reduced the progression rate of arterial calcification in patients with PXE with pre-existing calcifications without any serious adverse effects.
Effectiveness of Shoe Rotation in Managing Plantar Fasciitis in Patients
Authors: Koo See-Won , Yoon Yong-Soon , Yoon Myeong-Kwon , Choi Seung-Gue , Kim Dong-Wuk , Jang Hong-Young
Published: August 2024

Background/Objectives: Plantar fasciitis (PF) is a common condition that causes heel pain. While various conservative treatment modalities for PF exist, no previous studies have investigated the effectiveness of shoe rotation (ShR) in patients with PF pain. This study aimed to compare the therapeutic effectiveness of ShR with that of two conventional treatments for PF—namely, foot orthosis (FO) and physical therapy (PT). Methods: Charts of 42 patients with heel pain were retrospectively reviewed. Participants were allocated to one of three treatment groups: the ShR group, the customized FO group, and the PT group. Pain and functional outcomes were assessed using the Visual Analog Scale (VAS), Digital Pain Scale (DPS), Foot Function Index (FFI), Foot Pain and Function Scale (FPFS), and American Orthopedic Foot and Ankle Society Ankle-Hindfoot Scale (AOFAS-AHS) at baseline and at 4 and 12 weeks after the intervention. Results: The ShR, FO, and PT groups all showed improvements, with statistically significant decreases in VAS, DPS, and FFI scores and significant increases in FPFS and AOFAS-AHS scores over time (p < 0.05). All three interventions resulted in significant improvements from baseline to 4 weeks and further to 12 weeks (p < 0.05). The ShR group exhibited a slightly larger effect on all measurements than the other groups. Conclusions: ShR, FO, and PT contributed to pain reduction and functional improvement, and alternating the shoes alleviated PF pain. These results suggest a new approach to managing PF and serve as a basis for providing convenient treatment for patients with PF.
ESFPNet: Efficient Stage-Wise Feature Pyramid on Mix Transformer for Deep Learning-Based Cancer Analysis in Endoscopic Video
Authors: Chang Qi , Ahmad Danish , Toth Jennifer , Bascom Rebecca , Higgins William E.
Published: August 2024

For patients at risk of developing either lung cancer or colorectal cancer, the identification of suspect lesions in endoscopic video is an important procedure. The physician performs an endoscopic exam by navigating an endoscope through the organ of interest, be it the lungs or intestinal tract, and performs a visual inspection of the endoscopic video stream to identify lesions. Unfortunately, this entails a tedious, error-prone search over a lengthy video sequence. We propose a deep learning architecture that enables the real-time detection and segmentation of lesion regions from endoscopic video, with our experiments focused on autofluorescence bronchoscopy (AFB) for the lungs and colonoscopy for the intestinal tract. Our architecture, dubbed ESFPNet, draws on a pretrained Mix Transformer (MiT) encoder and a decoder structure that incorporates a new Efficient Stage-Wise Feature Pyramid (ESFP) to promote accurate lesion segmentation. In comparison to existing deep learning models, the ESFPNet model gave superior lesion segmentation performance for an AFB dataset. It also produced superior segmentation results for three widely used public colonoscopy databases and nearly the best results for two other public colonoscopy databases. In addition, the lightweight ESFPNet architecture requires fewer model parameters and less computation than other competing models, enabling the real-time analysis of input video frames. Overall, these studies point to the combined superior analysis performance and architectural efficiency of the ESFPNet for endoscopic video analysis. Lastly, additional experiments with the public colonoscopy databases demonstrate the learning ability and generalizability of ESFPNet, implying that the model could be effective for region segmentation in other domains.
RailTrack-DaViT: A Vision Transformer-Based Approach for Automated Railway Track Defect Detection
Authors: Phaphuangwittayakul Aniwat , Harnpornchai Napat , Ying Fangli , Zhang Jinming
Published: August 2024

Railway track defects pose significant safety risks and can lead to accidents, economic losses, and loss of life. Traditional manual inspection methods are either time-consuming, costly, or prone to human error. This paper proposes RailTrack-DaViT, a novel vision transformer-based approach for railway track defect classification. By leveraging the Dual Attention Vision Transformer (DaViT) architecture, RailTrack-DaViT effectively captures both global and local information, enabling accurate defect detection. The model is trained and evaluated on multiple datasets including rail, fastener and fishplate, multi-faults, and ThaiRailTrack. A comprehensive analysis of the model’s performance is provided including confusion matrices, training visualizations, and classification metrics. RailTrack-DaViT demonstrates superior performance compared to state-of-the-art CNN-based methods, achieving the highest accuracies: 96.9% on the rail dataset, 98.9% on the fastener and fishplate dataset, and 98.8% on the multi-faults dataset. Moreover, RailTrack-DaViT outperforms baselines on the ThaiRailTrack dataset with 99.2% accuracy, quickly adapts to unseen images, and shows better model stability during fine-tuning. This capability can significantly reduce time consumption when applying the model to novel datasets in practical applications.
Explainable AI Techniques for Comprehensive Analysis of the Relationship between Process Parameters and Material Properties in FDM-Based 3D-Printed Biocomposites
Authors: Kharate Namrata , Anerao Prashant , Kulkarni Atul , Abdullah Masuk
Published: August 2024

This study investigates the complex relationships between process parameters and material properties in FDM-based 3D-printed biocomposites using explainable AI techniques. We examine the effects of key parameters, including biochar content (BC), layer thickness (LT), raster angle (RA), infill pattern (IP), and infill density (ID), on the tensile, flexural, and impact strengths of FDM-printed pure PLA and biochar-reinforced PLA composites. Mechanical testing was used to measure the ultimate tensile strength (UTS), flexural strength (FS), and impact strength (IS) of the 3D-printed samples. The extreme gradient boosting (XGB) algorithm was used to build a predictive model based on the data collected from mechanical testing. Shapley Additive Explanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME), and Partial Dependence Plot (PDP) techniques were implemented to understand the effects of the interactions of key parameters on mechanical properties such as UTS, FS, and IS. Prediction by XGB was accurate for UTS, FS, and IS, with R-squared values of 0.96, 0.95, and 0.85, respectively. The explanation showed that infill density has the most significant influence on UTS and FS, with SHAP values of +2.75 and +5.8, respectively. BC has the most significant influence on IS, with a SHAP value of +2.69. PDP reveals that using 0.3 mm LT and 30° RA enhances mechanical properties. This study contributes to the field of the application of artificial intelligence in additive manufacturing. A novel approach is presented in which machine learning and XAI techniques such as SHAP, LIME, and PDP are combined and used not only for optimization but also to provide valuable insights about the interaction of the process parameters with mechanical properties.
Salinity Prediction Based on Improved LSTM Model in the Qiantang Estuary, China
Authors: Zheng Rong , Sun Zhilin , Jiao Jiange , Ma Qianqian , Zhao Liqin
Published: August 2024

Accurate prediction of estuarine salinity can effectively mitigate the adverse effects of saltwater intrusion and help ensure the safety of water resources in estuarine regions. Presently, diverse data-driven models, mainly neural network models, have been employed to predict tidal estuarine salinity and obtained considerable achievements. Due to the nonlinear and nonstationary features of estuarine salinity sequences, this paper proposed a multi-factor salinity prediction model using an enhanced Long Short-Term Memory (LSTM) network. To improve prediction accuracy, input variables of the model were determined through Grey Relational Analysis (GRA) combined with estuarine dynamic analysis, and hyperparameters for the LSTM model were optimized using a multi-strategy Improved Sparrow Search Algorithm (ISSA). The proposed ISSA-LSTM model was applied to predict salinity at the Cangqian and Qibao stations in the Qiantang Estuary of China, based on measured data from 2011–2012. The model performance is evaluated by mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), and Nash-Sutcliffe efficiency (NSE). The results show that compared to other models including Back Propagation neural network (BP), Gate Recurrent Unit (GRU), and LSTM model, the new model has smaller errors and higher prediction accuracy, with NSE improved by 8–32% and other metrics (MAP, MAPE, RMSE) improved by 15–67%. Meanwhile, compared with LSTM optimized with the original SSA (SSA-LSTM), MAE, MAPE, and RMSE values of the new model decreased by 13–16%, 15–16%, and 11–13%, and NSE value increased by 5–6%, indicating that the ISSA has a better hyperparameter optimization ability than the original SSA. Thus, the model provides a practical solution for the rapid and precise prediction of estuarine salinity.
Elevational Variation in and Environmental Determinants of Fungal Diversity in Forest Ecosystems of Korean Peninsula
Authors: Chen Lei , Yu Zhi , Zhao Mengchen , Kerfahi Dorsaf , Li Nan , Shi Lingling , Qi Xiwu , Lee Chang-Bae , Dong Ke , Lee Hae-In , Lee Sang-Seob
Published: August 2024

Exploring species diversity along elevational gradients is important for understanding the underlying mechanisms. Our study focused on analyzing the species diversity of fungal communities and their subcommunities at different trophic and taxonomic levels across three high mountains of the Korean Peninsula, each situated in a different climatic zone. Using high-throughput sequencing, we aimed to assess fungal diversity patterns and investigate the primary environmental factors influencing fungal diversity. Our results indicate that soil fungal diversity exhibits different elevational distribution patterns on different mountains, highlighting the combined effects of climate, soil properties, and geographic topology. Notably, the total and available phosphorus contents in the soil emerged as key determinants in explaining the differences in diversity attributed to soil properties. Despite the varied responses of fungal diversity to elevational gradients among different trophic guilds and taxonomic levels, their primary environmental determinants remained remarkably consistent. In particular, total and available phosphorus contents showed significant correlations with the diversity of the majority of the trophic guilds and taxonomic levels. Our study reveals the absence of a uniform diversity pattern along elevational gradients, underscoring the general sensitivity of fungi to soil conditions. By enriching our understanding of fungal diversity dynamics, this research enhances our comprehension of the formation and maintenance of elevational fungal diversity and the response of microbial communities in mountain ecosystems to climate change. This study provides valuable insights for future ecological studies of similar biotic communities.
Does a Change in the ESG Ratings Influence Firms’ Market Value? Evidence from an Event Study
Authors: Maccarrone Paolo , Illuzzi Alessandro , Inguanta Simone
Published: August 2024

In recent years, the field of “ESG finance” has seen rapid growth, resulting in the emergence and expansion of ESG ratings and rating agencies. This study investigates how financial investors react to updates in ESG ratings provided by two prominent ESG rating agencies, namely MSCI and Refinitiv. The main objective is to determine whether any positive or negative changes in a company’s sustainability ratings directly impact its market value. The Event Study methodology was used for this investigation, which analyses the Cumulated Average Abnormal Returns (CAARs) of economic events to assess their influence on corporate valuations. We analysed over 840 rating updates (events) using a sample of 75 companies across various industries, all listed on major stock exchanges. Our findings indicate that shifts in sustainability ratings, as evaluated by the two rating agencies, do not significantly impact companies’ market capitalisation. Furthermore, these outcomes remain consistent over time, suggesting that financial markets are not assigning increasing significance to ESG ratings. We offer potential explanations for these findings, which are discussed in light of the existing literature on the subject.
Potential Reduction of Spatiotemporal Patterns of Water and Wind Erosion with Conservation Tillage in Northeast China
Authors: Jiang Fahui , Peng Xinhua , Li Qinglin , Qian Yongqi , Zhang Zhongbin
Published: August 2024

Conservational tillage (NT) is widely recognized globally for its efficacy in mitigating soil loss due to wind and water erosion. However, a systematic large-scale estimate of NT’s impact on soil loss reduction in Northeast, China’s primary granary, remains absent. This study aimed to investigate the spatial and temporal variability of soil erosion under NT compared to conventional tillage (CT) in the black soil region and to analyze the underlying mechanisms driving these erosions. The Revised Universal Soil Loss Equation (RUSLE) and the Revised Wind Erosion Equation (RWEQ) models were employed, incorporating previously published plot/watershed data to estimate the potential reduction of water and wind erosion by NT in this region. Results indicated that under CT practices, water- and wind-induced soil losses were widely distributed in the arable land of Northeast China, with intensities of 2603 t km−2 a−1 and 34 t km−2 a−1, respectively. Furthermore, the erosive processes of water and wind erosion were significantly reduced by 56.4% and 91.8%, respectively, under NT practices compared to CT. The highest efficiency in soil conservation using NT was observed in the mountainous regions such as the Changbai Mountains and Greater Khingan Mountains, where water erosion was primarily driven by cropland slopes and wind erosion was driven by the wind speed. Conversely, the largest areas of severe erosion were observed in the Songnen Plain, primarily due to the significant proportion of arable land in this region. In the plain regions, water-induced soil loss was primarily influenced by precipitation, with light and higher levels of erosion occurring more frequently on long gentle slopes (0–3°) than on higher slope areas (3–5°). In the temporal dimension, soil loss induced by water and wind erosion ceased during the winter under both tillage systems due to snow cover and water freezing in the soil combined with the extremely cold climate. Substantial reductions were observed under NT from spring to autumn compared to CT. Ultimately, the temporal and spatial variations of soil loss under CT and NT practices were established from 2010 to 2018 and then projected onto a cropland map of Northeast China. Based on this analysis, NT is recommended as most suitable practice in the southern regions of Northeast China for maintaining soil health and crop yield production, while its suitability decreases in the northern and eastern regions.
Ecosystem Resilience Trends and Its Influencing Factors in China’s Three-River Headwater Region: A Comprehensive Analysis Using CSD Indicators (1982–2023)
Authors: Wang Zishan , Huang Wenli , Guan Xiaobin
Published: August 2024

Ecosystem resilience, the ability of an ecosystem to recover from disturbances, is a critical indicator of environmental health and stability, particularly under the impacts of climate change and anthropogenic pressures. This study focuses on the Three-River Headwater Region (TRHR), a critical ecological area for East and Southeast Asia, often referred to as the “Water Tower of China”. We used the Normalized Difference Vegetation Index (NDVI) as a proxy for vegetation growth and productivity and calculated Critical Slowing Down (CSD) indicators to assess the spatiotemporal dynamics of grassland ecosystem resilience in the TRHR from 1984 to 2021. Our research revealed a sustained improvement in ecosystem resilience in the TRHR starting in the late 1990s, with a reversal in this trend observed after 2011. Spatially, ecosystem resilience was higher in areas with greater precipitation and higher vegetation productivity. Temporally, changes in grazing intensity were most strongly correlated with resilience dynamics, with explanatory power far exceeding that of NDVI, temperature, and precipitation. Our study underscores the importance of incorporating ecosystem resilience into assessments of ecosystem function changes and the effectiveness of ecological conservation measures, providing valuable insights for similar research in other regions of the world.
Evaluating Public Satisfaction and Its Determinants in Chinese Sponge Cities Using Structural Equation Modeling
Authors: Wang Rui , Wu Youyou , Niu Jiaqi , Wang Na , Wu Hong
Published: August 2024

Public satisfaction is an important indicator of the success of environmental policies and management practices. China’s sponge city development (SCD) initiative was launched in 2014 and has received international attention for its technical advancements and environmental achievements. Public satisfaction, however, has not been fully investigated in cities transformed by SCD. This study uses public surveys and structural equation modeling to evaluate people’s satisfaction with SCD in four pilot sponge cities, and how familiarity with SCD, perceived benefits, concerns about adverse effects, and trust in government influence satisfaction levels. The results show that people in the four cities were, on average, slightly satisfied with SCD. Familiarity, perceived benefits, and trust in government were significant determinants of public satisfaction. On the contrary, concerns about the adverse effects of SCD did not significantly influence people’s satisfaction. Moreover, a mismatch was found between government-led evaluation outcomes and satisfaction measured here. This study highlights the importance of social and perceived values in shaping people’s satisfaction with SCD and provides suggestions for management strategies for enhancing public satisfaction, ultimately supporting the long-term effectiveness of urban stormwater management programs.
Persistent B-Cell Stimulation or B-Cell Repertoire Anomalies? The Dilemma of the Origin of Chronic Lymphocytic Leukemia (CLL)
Authors: Ferrarini Manlio , Bagnara Davide , Ghiotto Fabio , Fais Franco
Published: August 2024

Chronic Lymphocytic Leukemia (CLL) is caused by the clonal expansion of CD5+ B lymphocytes in the circulation, peripheral lymphoid organs and bone marrow [...]
Artificial Neural Network Model for Predicting Mechanical Strengths of Economical Ultra-High-Performance Concrete Containing Coarse Aggregates: Development and Parametric Analysis
Authors: Li Ling , Gao Yufei , Dong Xuan , Han Yongping
Published: August 2024

Ultra-high-performance concrete with coarse aggregates (UHPC-CA) has the advantages of high strength, strong shrinkage resistance and a lower production cost, presenting a broad application prospect in civil engineering construction. In view of the difficulty in establishing a mathematical model to accurately predict the mechanical properties of UHPC-CA, the back-propagation artificial neural network (BP-ANN) method is used to fully consider the various influential factors of the compressive strength (CS) and flexural strength (FS) of UHPC-CA in this paper. By taking the content of cement (C), silica fume (SF), slag, fly ash (FA), coarse aggregate (CA), steel fiber, the water–binder ratio (w/b), the sand rate (SR), the cement type (CT), and the curing method (CM) as input variables, and the CS and FS of UHPC-CA as output objectives, the BP-ANN model with three layers has been well-trained, validated and tested with 220 experimental data in the studies published in the literature. Four evaluating indicators including the determination coefficient (R2), the root mean square error (RMSE), the mean absolute percentage error (MAPE), and the integral absolute error (IAE) were used to evaluate the prediction accuracy of the BP-ANN model. A parametric study for the various influential factors on the CS and FS of UHPC-CA was conducted using the BP-ANN model and the corresponding influential mechanisms were analyzed. Finally, the inclusion levels for the CA, steel fiber, and the dimensionless parameters of the W/B and sand rate were recommended to obtain the optimal strength of UHPC-CA.
Hot Crack Formation Mechanism and Inhibition of a Novel Cobalt-Based Alloy Coating during Laser Cladding
Authors: Yang Pengfei , Lu Nannan , Liang Jingjing , Guo Yimo , Zhang Guangrui , Song Xiu , Zhou Yizhou , Sun Xiaofeng , Li Jinguo
Published: August 2024

Laser cladding provides advanced surface treatment capabilities for enhancing the properties of components. However, its effectiveness is often challenged by the formation of hot cracks during the cladding process. This study focuses on the formation mechanism and inhibition of hot cracks in a novel cobalt-based alloy (K688) coating applied to 304LN stainless steel via laser cladding. The results indicate that hot crack formation is influenced by liquid film stability, the stress concentration, and precipitation phases. Most hot cracks were found at 25°–45° high-angle grain boundaries (HAGBs) due to the high energy of these grain boundaries, which stabilize the liquid film. A flat-top beam, compared to a Gaussian beam, creates a melt pool with a lower temperature gradient and more mitigatory fluid flow, reducing thermal stresses within the coating and the fraction of crack-sensitive, high-angle grain boundaries (S-HAGBs). Finally, crack formation was significantly inhibited by utilizing a flat-top laser beam to optimize the process parameters. These findings provide a technical foundation for achieving high-quality laser cladding of dissimilar materials, offering insights into optimizing process parameters to prevent hot crack formation.