bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring Antibacterial Usage and Pathogen Surveillance over Five Years in a Tertiary Referral Teaching Hospital Adult General Intensive Care Unit (ICU)
Authors: Young David , McKenzie Cathrine A. , Gupta Sanjay , Sparkes David , Beecham Ryan , Browning David , Dushianthan Ahilanandan , Saeed Kordo
Published: November 2024

Antimicrobial resistance is a globally recognised health emergency. Intensive care is an area with significant antimicrobial consumption, particularly increased utilisation of broad-spectrum antibacterials, making stewardship programmes essential. We aimed to explore antibacterial consumption, partnered with pathogen surveillance, over a five-year period (2018 to 2023) in a tertiary referral adult general intensive care unit (ICU). The mean number of admissions was 1645 per annum. A comparison between the ICU populations admitted before and after the COVID-19 pandemic peak (2020/21) identified several notable differences with increased average daily unit bed occupancy (21.6 vs. 25.2, respectively) and a higher proportion of admissions with sepsis (28.4% vs. 32.5%, respectively) in the post-pandemic period. Over the entire five years, the overall proportion of antibacterial use by the WHO AWaRe classification was 42.6% access, 54.7% watch and 2.6% reserve. One hundred and forty-seven positive blood culture isolates were reported, with the most concerning antibacterial resistance identified in 7.5% (9 Escherichia coli and 2 Klebsiella pneumoniae isolates). The COVID-19 pandemic peak year was associated with increased ICU bed occupancy, as well as a greater number of positive blood cultures but lower antibacterial consumption. Despite an increasingly complex workload, a large proportion of overall antibacterial consumption remained within the access category. However, the mortality rate and the incidence of most concerning antimicrobial resistance with respect to pathogens remained satisfyingly consistent, suggesting the positive consequences of real-world antibiotic stewardship in an intensive care setting.
Effects of Thifluzamide Treatment on the Production of Cell Wall Degrading Enzymes in Rhizoctonia solani and Phenylpropane Metabolism in Pear Fruit
Authors: Wu Yushuo , Yan Weiwei , Sun Xiaonan , Zhang Xinnan , Ge Yonghong , Jia Xiaohui
Published: November 2024

The study aimed to investigate the effects of thifluzamide (2.67 mg/L) on ‘Huangguan’ pear fruit rot caused by Rhizoctonia solani during storage, as well as the activities of polygalacturonase (PG), pectin methylesterase (PME), polygalacturonic acid trans-eliminase (PGTE), pectin methyl trans-eliminase (PMTE), xylanase, and pectate lyase (PL) secreted by R. solani. The results showed that thifluzamide treatment significantly inhibited the activities of PG, PME, PGTE, PMTE, xylanase, and PL secreted by R. solani after 3 days in vitro culture, compared to the control. Thifluzamide also increased the activities of phenylalanine ammonia-lyase (PAL), cinnamate-4-hydroxylase (C4H), and 4-coumarate CoA ligase (4CL), and the contents of flavonoids and total phenolic compounds in pear fruit. Furthermore, thifluzamide increased the expression of PcPAL, PcC4H, Pc4CL, Pcβ-1,3-GA, PcLCH, PcF3H, and PcDFR involved in phenylpropanoid metabolism in pear fruit. In conclusion, thifluzamide treatment reduced the infection ability of R. solani by inhibiting the expression of the genes encoding cell wall-degrading enzymes in R. solani. At the same time, it inhibited the activities of cell wall-degrading enzymes induced resistance against R. solani infection in ‘Huangguan’ pears by promoting phenylpropane metabolism.
Salivary IL-1 Beta Level Associated with Poor Sleep Quality in Children/Adolescents with Autism Spectrum Disorder
Authors: Fuentes-Albero Milagros , Mafla-España Mayra Alejandra , Martínez-Raga José , Cauli Omar
Published: November 2024

Background: Sleep disorders are common in youths with autism spectrum disorders. Inflammatory cytokines such as Il-1 beta and Il-6 in saliva have been associated with alterations in sleep quality in various conditions. We assessed whether there were associations between the salivary concentration of IL-1 beta and IL-6 and sleep quality in youths with ASD versus typically developing (TD) age- and gender-matched youths. Method: Forty children and adolescents with ASD or TD participated in this study (20% females). Their parents answered the items of a validated questionnaire on sleep quality (Pittsburgh Sleep Quality Index). Results: The mean Pittsburgh score was significantly higher (i.e., the quality of sleep was poorer) in the ASD group (8.68 ± 0.35 (SEM), ranging from 7 to 12 points), compared to the TD group (7.35 ± 0.54 (SEM), ranging from 2 to 12 points) (p = 0.02, Mann–Whitney U test). There were no significant differences in the salivary concentration of Il-1 beta and IL-6 receptor between the two groups, but salivary IL-1 beta concentration was inversely associated with poor sleep quality in the ASD group. No associations between the salivary Il-6 concentration and sleep quality were found in either group. Linear regression analysis by separate groups revealed significant associations between the sleep quality score and the concentration of IL-1 beta in the ASD group (p = 0.01, OR = −0.53, 95% CI −0.008–0.001). In contrast, no significant associations were observed in the TD group, or for IL-6 in either group. No significant effects of sex, age, or use of psychotropic medications were found. Conclusions: Children and adolescents with ASD showed significantly poorer sleep quality based on their parents’ reports compared to the TD group, and the salivary IL-1 beta concentration was inversely associated with sleep quality only in the ASD group. Further studies on the associations between inflammatory cytokines and sleep in ASD are needed.
Synthesis and Evaluation of Glucosyl-, Acyl- and Silyl- Resveratrol Derivatives as Retinoprotective Agents: Piceid Octanoate Notably Delays Photoreceptor Degeneration in a Retinitis Pigmentosa Mouse Model
Authors: Valdés-Sánchez Lourdes , Moshtaghion Seyed Mohamadmehdi , Caballano-Infantes Estefanía , Peñalver Pablo , Rodríguez-Ruiz Rosario , González-Alfonso José Luis , Plou Francisco José , Desmet Tom , Morales Juan C. , Díaz-Corrales Francisco J.
Published: November 2024

Background: Retinitis pigmentosa (RP), the leading cause of inherited blindness in adults, is marked by the progressive degeneration of rod photoreceptors in the retina. While gene therapy has shown promise in treating RP in patients with specific mutations, no effective therapies currently exist for the majority of patients with diverse genetic backgrounds. Additionally, no intervention can yet prevent or delay photoreceptor loss across the broader RP patient population. Resveratrol (RES), a naturally occurring polyphenol, has shown cytoprotective effects in various neurodegenerative disease models; however, its therapeutic potential is limited by low bioavailability. Methods: In this study, we synthesized novel RES derivatives and assessed their retinoprotective effects in a murine model of RP (rd10 mice). Results: Among these derivatives, piceid octanoate (PIC-OCT) significantly delayed photoreceptor degeneration in the RP model, demonstrating superior efficacy compared to RES. Conclusions: PIC-OCT shows strong potential as a leading candidate for developing new therapeutic strategies for RP.
Theranostics Nuclear Medicine in Prostate Cancer
Authors: Lima Helena , Etchebehere Marina , Bogoni Mateos , Torricelli Caroline , Nogueira-Lima Ellen , Deflon Victor M. , Lima Mariana , Etchebehere Elba
Published: November 2024

Theranostic Nuclear Medicine is based on the idea of combining the same molecule (or drug) with different radioisotopes for both diagnosis and treatment, a concept that emerged in the early 1940s with the use of radioactive iodine for thyroid diseases. Theranostic Nuclear Medicine has since expanded to diseases of higher incidence, such as prostate cancer, with several imaging methods used to assess the extent of the disease and the corresponding radiopharmaceuticals used for treatment. For example, by detecting osteoblastic metastases by bone scintigraphy, corresponding radiopharmaceuticals with therapeutic properties can be administered to eliminate or reduce pain associated with metastases and/or determine overall survival gain. The purpose of this review is to discuss the role of Theranostic Nuclear Medicine in prostate cancer, addressing the main diagnostic imaging studies with their corresponding treatments in the Theranostic model.
Correction: Zheng et al. Fabrication of Co-Assembly from Berberine and Tannic Acid for Multidrug-Resistant Bacteria Infection Treatment. Pharmaceutics 2023, 15, 1782
Authors: Zheng Tingting , Chen Huan , Wu Chenyang , Wang Jinrui , Cui Mengyao , Ye Hanyi , Feng Yifan , Li Ying , Dong Zhengqi
Published: November 2024

In the original publication [...]
The Medium Is the (Discriminatory) Message: The Medial Epistemic Injustices of Philosophy
Authors: Pezzano Giacomo
Published: November 2024

This paper brings the analysis of epistemic injustices and the perspective of media philosophy into dialogue by proposing the new concept of medial epistemic injustice. After introducing the topic, the contribution confronts some metaphilosophical stances in light of the recent medial turn in order to suggest that, despite all their controversies, philosophers seem to agree that doing philosophy uniquely involves writing texts. This discussion sets the stage for the claim that institutionally sanctioned philosophy manifests a mono-genreism that only admits one particular kind of written text and a mono-medialism that excludes all media other than writing. Next, the relationship between non-verbal media and philosophy is examined more closely on two levels. First, it is emphasized how academic philosophy leaves no room for corporeal thinking and visual thinking; second, it is illustrated how this may harm some individuals, using the example of deaf people and visually oriented autistic people. The conclusion proposes a provocative Gestalt-switch: What if current “angelic” philosophical knowledge were itself atypical, exhibiting the traits of an aphantasic mind?
Effects of Residual Water on Proton Transfer-Switching Molecular Device
Authors: Tachikawa Hiroto
Published: November 2024

The excited state proton transfer (ESPT) reaction plays a crucial role in DNA defense and ON-OFF proton-switching molecular devices. o-Hydroxybenzaldehyde (OHBA) is the simplest model-molecule for the ESPT reactions where a proton is transferred from OH to C=O carbonyl groups by photo-excitation. In the present study, the reaction mechanism of ESPT in OHBA was investigated by means of the direct ab initio molecular dynamics (AIMD) method. The triplet (T1) state of OHBA, OHBA(T1), was considered as the excited state of OHBA. The dynamic calculations showed that fast PT occurred from OH to C=O carbonyl groups at the T1 state. The time of PT was calculated to be 34–57 fs in OHBA(T1). The spin density was mainly distributed on the benzene ring (Bz) at time zero. The density was gradually transferred from Bz to C=O as a function of time on the T1 surface. When the spin density on C=O was larger than that on Bz (at time = 35–43 fs), the proton of OH was rapidly transferred to C=O. The localization of spin density on C=O dominated strongly the PT rate. Next, the effects of residual water (H2O) on the PT rate were investigated using OHBA-H2O 1:1-complexes to elucidate the effects of H2O on the PT rate in the ON-OFF proton-switching molecular devices. The PT rates were strongly dependent on the position of H2O around OHBA. The reaction mechanism is discussed based on theoretical results.
Predictive Model of the Effects of Skin Phototype and Body Mass Index on Photobiomodulation Therapy for Orofacial Disorders
Authors: Cassemiro Alice , Motta Lara Jansiski , Fiadeiro Paulo , Fonseca Elsa
Published: November 2024

Monte Carlo techniques have been extensively used for planning laser-based clinical procedures such as photobiomodulation. However, the effects of several biological tissue characteristics regarding its morphological structure and physiological parameters have not been carefully addressed in many applications. Specifically, many questions remain concerning the effect of skin phototype and body mass index on the effectiveness of photobiomodulation for extraoral therapies. To address these questions, a Monte Carlo simulation model of the effects of body mass index-dependent skin structure on different Fitzpatrick skin types was developed, specifically tailored for the morphological characteristics of cheek tissue. The model describes the settings of a typical oral photobiomodulation treatment protocol for pain relief, namely the use of 660 nm and 808 nm laser wavelengths and a therapeutic dose of 2.0J/cm2 on the masseter muscle. The simulations were used to train a machine learning predictive model aimed at accelerating the treatment planning stage and assessing the importance of patient-specific parameters. A multiple-regression approach was adopted to predict muscle dose and treatment time for effective delivered dose. Body mass index had little effect on epidermal energy deposition, but an important impact on muscle dose parameters. Phototype also influenced muscle dose, but to a lesser extent than body mass index. The results of this study can be used to develop customized dosimetry phototherapy protocols to promote more effective and safe clinical outcomes.
An Evidence-Based Approach to Utilizing Cold Therapies for Post-Exercise Recovery
Authors: Grainger Adam , Malone James J. , Costello Joseph T. , Bleakley Chris M. , Allan Robert
Published: November 2024

Whilst cold therapies such as cold-water immersion are regularly used in practice, the practical application does not always align with best practices. In this commentary, we highlight the key components of the British Association of Sport and Exercise Sciences (BASES) Expert Statement on the use of cooling therapies for post-exercise recovery and provide additional discussion on the empirical evidence and rationale that informed our perspective. We developed a series of specific questions to ensure that cold therapy recovery protocols are context-specific and tailored to the needs of the individual athletes. These questions, which cover the WHEN, WHAT, and HOW of cold therapy, were central to the development of the Expert Statement. This was presented as a decision tree to ensure that key messages could be concisely disseminated across a range of sporting environments and populations (e.g., gyms, locker rooms, and treatment rooms), supporting and informing decision-making for those wanting to use cold therapy to assist their recovery in line with previously published peer-reviewed work. Discussion points included the suitability of cooling therapies in some contexts, how athletes’ choice of cooling mode should be largely driven by practicalities (e.g., budget and availability), and, lastly, future research directions.
AIpollen: An Analytic Website for Pollen Identification Through Convolutional Neural Networks
Authors: Yu Xingchen , Zhao Jiawen , Xu Zhenxiu , Wei Junrong , Wang Qi , Shen Feng , Yang Xiaozeng , Guo Zhonglong
Published: November 2024

With the rapid development of artificial intelligence, deep learning has been widely applied to complex tasks such as computer vision and natural language processing, demonstrating its outstanding performance. This study aims to exploit the high precision and efficiency of deep learning to develop a system for the identification of pollen. To this end, we constructed a dataset across 36 distinct genera. In terms of model selection, we employed a pre-trained ResNet34 network and fine-tuned its architecture to suit our specific task. For the optimization algorithm, we opted for the Adam optimizer and utilized the cross-entropy loss function. Additionally, we implemented ELU activation function, data augmentation, learning rate decay, and early stopping strategies to enhance the training efficiency and generalization capability of the model. After training for 203 epochs, our model achieved an accuracy of 97.01% on the test set and 99.89% on the training set. Further evaluation metrics, such as an F1 score of 95.9%, indicate that the model exhibits good balance and robustness across all categories. To facilitate the use of the model, we develop a user-friendly web interface. Users can upload images of pollen grains through the URL link provided in this article) and immediately receive predicted results of their genus names. Altogether, this study has successfully trained and validated a high-precision pollen grain identification model, providing a powerful tool for the identification of pollen.
The Influence of In-Mould Annealing and Accelerated Ageing on the Properties of Impact-Modified Poly(Lactic Acid)/Biochar Composites
Authors: Brdlík Pavel , Novák Jan , Borůvka Martin , Gomez-Caturla Jaume , Lenfeld Petr
Published: November 2024

In the last few decades, a large number of natural additives have been analysed in connection with the improvement of the properties of poly(lactic acid) (PLA) bioplastic materials. This article comprehensively analyses the applicability of a highly stable and progressive multifunctional additive produced from renewable resources—biochar. The effect of biochar on the structural development and various thermo-mechanical properties was evaluated as a function of the biochar size and volume, addition of an impact modifier and in-mould annealing during injection moulding. In addition, the effect of accelerated ageing on the change in properties was also analysed. The evaluated results showed a significant influence of the particle size and biochar content on the properties of PLA biocomposites. However, the crucial aspect was the production process with a higher mould temperature and longer production time. Consequently, the effect of additives with adjusted processing worked synergistically on the performance of the resulting biocomposites. The accelerated ageing process did not induce any significant changes in the mechanical, impact and heat resistance behaviour of neat PLA. On the other hand, significant effects on the behaviour of the modified PLA biocomposites were observed. Impact-modified PLA achieved a toughness of 28 kJ/m2, an increase of 61% compared to neat PLA. Similar observations were made when submicron biochar was incorporated into the PLA matrix (a 22% increase with PLA/5B1). These increases were even more pronounced when injected into a 100 °C mould. Due to the synergistic effect, excellent impact toughness results of 95 kJ/m2 (a 428% increase) were achieved with PLA/IM/5B1. Moreover, these results persisted even after accelerated ageing.
Preliminary Research to Assess the Possibility of Grinding Selected Plastics Using Crushers
Authors: Ciężkowski Paweł , Bąk Sebastian , Caban Jacek , Seńko Jarosław , Waśkowicz Mateusz Adam
Published: November 2024

This study aims to investigate the effect of the shredding machine used on the recyclability of plastic fractions after primary crushing. This work presents a method for producing aggregates that has yet to be used in the plastics industry. This study included crushing of polymethylmethacrylate (PMMA), polyamide (PA-6), acrylonitrile butadiene-styrene (ABS), polycarbonate (PC), polystyrene (PS), and polypropylene (PP) waste in a jaw, a hammer, and a cone crusher. An analysis of the grain composition was carried out to characterize the obtained crushing products. The influence of feed size on the grain composition of the product and, only on the jaw crusher, the influence of the material used on the parameters of the crushing process was studied. This paper proposes a method to evaluate the grain composition and a way to assess plastic shredding capabilities based on machine kinematics and mechanical properties of a given material.
Customising Sustainable Bio-Based Polyelectrolytes: Introduction of Charged and Hydrophobic Groups in Cellulose
Authors: Magalhães Solange , Aliaño-González María José , Cruz Pedro F. , Rosenberg Rose , Haffke Dirk , Norgren Magnus , Alves Luís , Medronho Bruno , da Graça Rasteiro Maria
Published: November 2024

Cellulose has been widely explored as a sustainable alternative to synthetic polymers in industrial applications, thanks to its advantageous properties. The introduction of chemical modifications on cellulose structure, focusing on cationic and hydrophobic modifications, can enhance its functionality and expand the range of applications. In the present work, cationization was carried out through a two-step process involving sodium periodate oxidation followed by a reaction with the Girard T reagent, yielding a degree of substitution for cationic groups (DScationic) between 0.3 and 1.8. Hydrophobic modification was achieved via esterification with fatty acids derived from commercial plant oils, using an enzyme-assisted, environmentally friendly method. Lipase-catalysed hydrolysis, optimised at 0.25% enzyme concentration and with a 1 h reaction time, produced an 84% yield of fatty acids, confirmed by FTIR and NMR analyses. The degree of substitution for hydrophobic groups (DShydrophobic) ranged from 0.09 to 0.66. The molecular weight (MW) of the modified cellulose derivatives varied from 1.8 to 141 kDa. This dual modification strategy enables the creation of cellulose-based polymers with controlled electrostatic and hydrophobic characteristics, customisable for specific industrial applications. Our approach presents a sustainable and flexible solution for developing cellulose derivatives tailored to diverse industrial needs.
Novel Glycidyl Carbamate Functional Epoxy Resin Using Hydroxyl-Terminated Polybutadiene
Authors: Kim Hae-Chan , Moon Sun-Jae , Kwon Yong-Rok , Moon Seok-kyu , Kim Dah-hee , Kim Dong-Hyun
Published: November 2024

Herein, a novel glycidyl carbamate functional epoxy resin (GCE) is synthesized by the additional reaction of the isocyanate group of tolylene diisocyanate (TDI) with the hydroxyl group of hydroxyl-terminated polybutadiene (HTPB) and glycidol. The successful synthesis of the GCE is confirmed by FT-IR and 1H NMR spectroscopy. Furthermore, a dual-curing adhesive system is developed using acrylic acid and trimethylolpropane triacrylate with varying GCE contents, and its adhesive performance is assessed by testing adhesive strength, pencil hardness, and surface energy. As a result, the dual-cure adhesive containing 0.2 mol of GCE demonstrates an impressive adhesive strength of 11.1 MPa, a pencil hardness of B, and surface energy comparable to that of standard polycarbonate film.
Exploring the Potential of Recycled Polyethylene Terephthalate—Lignocellulose/Carbon Nanotube–Graphene Nanosheets an Efficient Extractor for Oil Spill
Authors: Alhassani Wafaa , Alhogbi Basma G. , Hussein Mahmoud A. , El-Shahawi M. S.
Published: November 2024

The global challenge of oil spill treatment has been addressed using nanocomposite-based natural fibers. These materials offer great potential in oil spill cleanup and are considered due to their environmental friendliness, high efficiency, and low cost. Thus, the current study reports a novel composite fabricated from date palm fiber (DPF) and recycled polyethylene terephthalate (rPET) with a proper combination of a mixture of carbon nanotubes (CNTs) and graphene nanosheets (GNSs) for oil removal. The established nanocomposite (DPF-rPET/CNT/GNS) was fabricated via physical mixing of various quantities (0.9, 0.8, and 0.7 g) of PET, along with varying loads of DPF at different proportions of CNT:GNS. The prepared nanocomposite (DPF-rPET/CNT/GNS) was fully characterized using scanning electron microscopy–energy dispersive X-ray (SEM-EDX) analysis, transmission electron microscopy (TEM), thermogravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), and Brunauer–Emmett–Teller (BET) analysis. In static experiments and under the optimal parameters of pH, sorbent doze, shaking time, and quantity of diesel oil), the established sorbent (DPF-rPET/CNT-GNS nanocomposite) displayed excellent adsorption capacity (98 mg/g). This study also expands the utility of the sorbent for the reusability of the oil adsorption, maintaining performance after five cycles. The adsorption data fitted well with the Langmuir isotherm model with a correlation coefficient (R2) of 0.99 and maximum adsorption capacity of 99.7 mg/g, indicating monolayer adsorption. Additionally, the adsorption kinetics followed a pseudo-second-order model, with an R2 near unity and an adsorption capacity of 99.09 mg/g. This study highlights the promising potential of the DPF-rPET/CNT-GNS composite as an effective adsorbent for treating oily water.
Theoretical Assessment of Agro-Waste for Biogas Production Based on Novel Methodology Related to Biochemical Potential
Authors: Balać Martina , Janković Bojan , Manić Nebojša
Published: November 2024

Agricultural and waste biomasses present viable solutions for utilization in the energy sector, achieving sustainable and long-term transformation into energy and fuel. However, it is important to carefully evaluate the competing applications for these feedstocks, considering both short- and long-term stability. Biomass for biogas production in agriculture and waste management is used due to its availability and ease of handling. Considering everything mentioned, evaluating the most suitable raw materials for biogas production is crucial for meeting sustainability criteria and promoting biomass as an energy source. In this paper, an examination of different biomass sources as possible feedstock to produce biogas by applying a theoretical approach to the proximate and final analysis results of those materials is presented. Based on data from the raw material analysis, the theoretical biochemical methane potential (TBMP) for the considered samples was calculated. Furthermore, the mass and energy balance for the case study biogas plant was also performed. According to the obtained results, the considered feedstocks show the validity of their use for biogas production considering the fulfillment of the raw material minimum quantity, mandatory residue arrangement, and achieving higher efficiency of the energy conversion process.
High Efficiency Producing Technology Applied in Metal Optical Lens by 3D Wax Printing Combined with Investment Casting
Authors: Cheng Ken-Chuan , Huang Chien-Yao , Lu Hsien-Te , Chen Jun-Cheng , Ho Cheng-Fang , Wang A-Cheng , Chen Keng-Yu
Published: November 2024

3D printing technology can easily and quickly produce small batch models and full-size parts, which has obvious and important benefits in shortening development time. Since metals exhibit excellent mechanical strength and high wear resistance, metal additive manufacturing (MAM) is a popular technology for making metal parts. However, metal powders and 3D-printing machines are costly, which increases the difficulty of achieving mass production through MAM. In this study, the 3D wax printing and investment casting (WPIC) approach was developed to manufacture high-quality metal optical lenses with high efficiency and low cost. The manufactured lenses had a diameter of 38.1 mm, two radii of curvature (15 and 90 mm), and a cooling channel. These lenses were manufactured through 3D printing by using wax patterns produced through investment casting. The manufacturing efficiency and machining accuracy of the lenses produced using the proposed method were compared with those of lenses produced through MAM and investment casting. The results indicated that the total costs of manufacturing an optical lens through MAM and investment casting were nine and eight times greater, respectively than that of manufacturing an optical lens through WPIC. In addition, the surface roughness of metal lenses manufactured through WPIC was 45% lower than that of lenses manufactured through MAM. Finally, the time required to manufacture 50 metal lenses was only 15 days when WPIC was used; the corresponding time was 25 days and 6 months when MAM and investment casting were used, respectively. According to the above-mentioned results, the WPIC process has excellent advantages in product manufacturing cost and developing schedule over MAM and traditional methods of investment casting.
Integrated Analytical, Numerical, and Statistical Analysis of Buckling Behavior in Steel Cylindrical Silos with Corrugated Walls
Authors: Tănase Maria , Portoacă Alexandra Ileana , Gabor Manuela Rozalia , Veres Cristina
Published: November 2024

This paper investigates the buckling behavior of steel cylindrical silos with corrugated walls and vertical stringers under axial compression. The study integrates analytical, numerical, and statistical analyses to understand the influence of geometrical parameters such as radius, wall thickness, and corrugation profile on the buckling phenomenon. The analytical calculations elucidate the critical buckling load for various scenarios, considering both unstiffened and stiffened wall configurations. The finite element analysis provides numerical validation, while the statistical analysis offers insights into the sensitivity of the critical buckling load to different parameters. The results highlight the significance of corrugation height and suggest the optimal design parameters for maximizing buckling resistance while minimizing structural weight.
Accelerating Numerical Simulations of CO2 Geological Storage in Deep Saline Aquifers via Machine-Learning-Driven Grid Block Classification
Authors: Kanakaki Eirini Maria , Ismail Ismail , Gaganis Vassilis
Published: November 2024

The accurate prediction of pressure and saturation distribution during the simulation of CO2 injection into saline aquifers is essential for the successful implementation of carbon sequestration projects. Traditional numerical simulations, while reliable, are computationally expensive. Machine learning (ML) has emerged as a promising tool to accelerate these simulations; however, challenges remain in effectively capturing complex reservoir dynamics, particularly in regions experiencing rapid changes in pressure and saturation. This article addresses the challenges by introducing a fully automated, data-driven ML classifier that distinguishes between regions of fast and slow variation within the reservoir. Firstly, we demonstrate the variability in pressure across different reservoir grid blocks using a simple brine injection and production scenario, highlighting the limitations of conventional acceleration approaches. Subsequently, the proposed methodology leverages ML proxies to rapidly and accurately predict the behavior of slow-varying regions in CO2 injection simulations, while traditional iterative methods are reserved for fast-varying areas. The results show that this hybrid approach significantly reduces the computational load without compromising on accuracy. This provides a more efficient and scalable solution for modeling CO2 storage in saline aquifers.
Trends in Hip Arthroplasty Cementation: Insights from an Italian Registry of 142,113 Patients
Authors: Perticarini Loris , Andriollo Luca , Righini Roberta , Sangaletti Rudy , Benazzo Francesco
Published: November 2024

Introduction: The use of cementation in total hip arthroplasty (THA) has evolved over the years, with a notable shift toward cementless and hybrid techniques. The aim of this study is to evaluate data from an Italian registry on the type of fixation used in THA implants and their corresponding survival rates in a large patient cohort with long-term follow-up, and to compare these data with the most recent literature. Methods: From January 2000 to December 2020, a total of 137,256 primary THA procedures were performed, of which 10.4% were fixed with stem cementation. There were 4857 revision implants, of which 11.4% were implanted with stem cementation. Results: The trend showing a significant shift toward cementless fixation methods is particularly pronounced in younger patients, with cementless implants comprising 99.5% of procedures in patients under 40 years of age. As patient age increases, the use of cemented or hybrid fixation methods becomes more common. This trend aligns with existing literature, in which cementation is often preferred for elderly patients due to concerns about bone quality and the potential for better immediate fixation provided by cemented stems. At 10 years, the implant that showed the highest survival rate was the fully cemented implant, with a rate of 94.8%. This study also reports the causes of failure based on the different fixation techniques. Conclusions: The development of standardized guidelines that consider patient-specific factors such as age, bone quality, and comorbidities in the choice of fixation type could help reduce variability in practice and improve overall outcomes in hip arthroplasty.
Investigating the Mental Health, Wellbeing, and Resilience of Postgraduate Researchers
Authors: Casey Chloe , Trenoweth Steve , Knight Fiona , Taylor Julia , Harvey Orlanda
Published: November 2024

Background: This study investigates the factors affecting the mental health and wellbeing of postgraduate researchers (PGRs) at a UK institution, with a focus on resilience as a determinant of wellbeing. PGRs experience unique challenges, including workload pressures, isolation, and imposter syndrome. Methods: This study employs a mixed-methods approach to identifying the most pertinent factors affecting their wellbeing. Quantitative data were collected through an online survey using validated scales such as the Warwick-Edinburgh mental wellbeing scale (WEMWBS), the Connor–Davidson resilience scale (CD-RISC), and the Juniper PhD wellbeing scale (JPWBS). Result: The survey results revealed that PGRs scored significantly lower on wellbeing and resilience compared with the general population. To further explore these findings, qualitative data were obtained through semi-structured interviews with a subset of participants, generating the following key themes: control, balance, and coping. Conclusions: The research highlights the complex interplay between institutional factors, personal expectations, and coping strategies in shaping PGR wellbeing. The findings underscore the need for tailored interventions that address these factors, emphasizing the importance of building resilience, providing adequate support, and fostering a balanced work–life environment for PGRs. This study contributes to the growing body of literature on PGR mental health, offering insights for universities to enhance support services and promote a healthier research environment.
First Case of Chryseobacterium gleum Post-COVID-19 in a Child with Recurrent Fever
Authors: Colosimo Manuela , Luciani Filippo , Pullano Maria Novella , Abrego-Guandique Diana Marisol , Gallelli Luca
Published: November 2024

Background and Clinical Significance: Chryseobacterium gleum is a Gram-negative opportunistic and emerging pathogen able to induce systemic manifestations (e.g., peritonitis, pneumonia, urinary tract infections, meningitis) in immunocompromised patients. No data on children have been published. Case Presentation: A 2-year-old child presented in the pediatric ambulatory room with recurrent fever, submandibular lymphadenopathy, and skin rash. Laboratory findings revealed the presence of microcytic anemia with an increase in c-reactive protein. Chest X-ray reported mild accentuation of the bronchial structure, especially on the right side and middle–lower zone. In the peripheral blood smear, anisopoikilocytosis and elliptical red cells were evident. Clinical evaluation revealed the presence of conjunctivitis and polymorphic erythema, hyperemic pharynx and tonsils, SPO2 99%, auscultation of the chest, harsh vesicular murmur all over the area, and some wheezing. Microbiological analysis of sputum and throat swabs revealed the presence of numerous colonies of Chryseobacterium gleum confirmed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS score > 2.2). Conclusions: This is the first case of Chryseobacterium gleum post-COVID in a child. We suggest that a quick identification and an appropriate treatment represent the critical factors able to prevent the adverse outcomes related to C. gleum infection.
How Severe Was the 2022 Flash Drought in the Yangtze River Basin?
Authors: Yang Liyan , Wei Jia
Published: November 2024

Flash droughts, characterized by their rapid onset and severe impacts, have critical implications for the ecological environment and water resource security. However, inconsistent definitions of flash droughts have hindered scientific assessments of drought severity, limiting efforts in disaster prevention and mitigation. In this study, we propose a new method for explicitly characterizing flash drought events, with particular emphasis on the process of soil moisture recovery. The temporal and spatial evolution of flash droughts over the Yangtze River Basin was analyzed, and the severity of the extreme flash drought in 2022 was assessed by comparing its characteristics and impacts with those of three typical dry years. Additionally, the driving factors of the 2022 flash drought were evaluated from multiple perspectives. Results indicate that the new identification method for flash droughts is reasonable and reliable. In recent years, the frequency and duration of flash droughts have significantly increased, with the Dongting Lake and Poyang Lake basins being particularly affected. Spring and summer were identified as peak seasons for flash droughts, with the middle reaches most affected in spring, while summer droughts tend to impact the entire basin. Compared to 2006, 2011, and 2013, the flash drought in 2022 affected the largest area, with the highest number of grids experiencing two flash drought events and a development rate exceeding 15%. Moreover, the summer heat in 2022 was more extreme than in the other three years, extending from spring to fall, especially during July–August. Its evolution was driven by the Western Pacific Subtropical High, which suppressed precipitation and elevated temperatures. The divergence of water vapor flux intensified water shortages, while anomalies in latent and sensible heat fluxes increased surface evaporation and heat transfer, further disturbing the regional water cycle. This study provides valuable insights for flash drought monitoring and early warning in the context of a changing climate.
Surface Profile Recovery from Electromagnetic Fields with Physics-Informed Neural Networks
Authors: Chen Yuxuan , Wang Ce , Hui Yuan , Shah Nirav Vasant , Spivack Mark
Published: November 2024

Physics-informed neural networks (PINN) have shown their potential in solving both direct and inverse problems of partial differential equations. In this paper, we introduce a PINN-based deep learning approach to reconstruct one-dimensional rough surfaces from field data illuminated by an electromagnetic incident wave. In the proposed algorithm, the rough surface is approximated by a neural network, with which the spatial derivatives of surface function can be obtained via automatic differentiation, and then the scattered field can be calculated using the method of moments. The neural network is trained by minimizing the loss between the calculated and the observed field data. Furthermore, the proposed method is an unsupervised approach, independent of any surface data, where only the field data are used. Both transverse electric (TE) field (Dirichlet boundary condition) and transverse magnetic (TM) field (Neumann boundary condition) are considered. Two types of field data are used here: full-scattered field data and phaseless total field data. The performance of the method is verified by testing with Gaussian-correlated random rough surfaces. Numerical results demonstrate that the PINN-based method can recover rough surfaces with great accuracy and is robust with respect to a wide range of problem regimes.
Hierarchical Spectral–Spatial Transformer for Hyperspectral and Multispectral Image Fusion
Authors: Zhu Tianxing , Liu Qin , Zhang Lixiang
Published: November 2024

This paper presents the Hierarchical Spectral–Spatial Transformer (HSST) network, a novel approach applicable to both drone-based and broader remote sensing platforms for integrating hyperspectral (HSI) and multispectral (MSI) imagery. The HSST network improves upon conventional multi-head self-attention transformers by integrating cross attention, effectively capturing spectral and spatial features across different modalities and scales. The network’s hierarchical design facilitates the extraction of multi-scale information and employs a progressive fusion strategy to incrementally refine spatial details through upsampling. Evaluations on three prominent hyperspectral datasets confirm the HSST’s superior efficacy over existing methods. The findings underscore the HSST’s utility for applications, including drone operations, where the high-fidelity fusion of HSI and MSI data is crucial.
Identification of Global Extended Pseudo Invariant Calibration Sites (EPICS) and Their Validation Using Radiometric Calibration Network (RadCalNet)
Authors: Fajardo Rueda Juliana , Leigh Larry , Teixeira Pinto Cibele
Published: November 2024

This study introduces a global land cover clustering using an unsupervised algorithm, incorporating the novel step of filtering data to retain only temporally stable pixels before applying K-means clustering. Unlike previous approaches that did not assess the pixel-level temporal stability, this method provides more reliable clustering results. The K-means identified 160 distinct clusters, with Cluster 13 Global Temporally Stable (Cluster 13-GTS) showing significant improvements in temporal stability. Compared to Cluster 13 Global (Cluster 13-G) from earlier research, Cluster 13-GTS reduced the coefficient of variation by up to 1% and increased the number of calibration locations from 23 to over 50. This study also validated these clusters using TOA reflectance from ground-truth measurements collected at the Radiometric Calibration Network (RadCalNet) Gobabeb (RCN-GONA) site, incorporating data from Landsat 8, Landsat 9, Sentinel-2A, and Sentinel-2B. The GONA Extended Pseudo Invariant Calibration Sites (EPICS) GONA-EPICS cluster used for the validation provided statistically comparable mean TOA reflectance to RCN-GONA, with a reduced chi-square test indicating minimal differences within the cluster’s uncertainty range. Notably, the difference in reflectance between RCN-GONA and GONA-EPICS was less than 0.023 units across all the bands. Although GONA-EPICS exhibited slightly higher uncertainty (6.4% to 10.3%) compared to RCN-GONA site (<5%), it offered advantages such as 80 potential calibration points per Landsat cycle and reduced temporal instability, and it provided alternatives to reduce the reliance on single sites like traditional PICS or RCN-GONA, making it a valuable tool for calibration efforts. These findings highlight the potential of the newly developed EPICS for radiometric calibration and stability monitoring of optical satellite sensors. Distributed across diverse regions, these global targets increase the number of calibration points available for any sensor in any orbital cycle, reducing the reliance on traditional PICS and offering more robust targets for radiometric calibration efforts.
Autonomous Extraction Technology for Aquaculture Ponds in Complex Geological Environments Based on Multispectral Feature Fusion of Medium-Resolution Remote Sensing Imagery
Authors: Liang Zunxun , Wang Fangxiong , Zhu Jianfeng , Li Peng , Xie Fuding , Zhao Yifei
Published: November 2024

Coastal aquaculture plays a crucial role in global food security and the economic development of coastal regions, but it also causes environmental degradation in coastal ecosystems. Therefore, the automation, accurate extraction, and monitoring of coastal aquaculture areas are crucial for the scientific management of coastal ecological zones. This study proposes a novel deep learning- and attention-based median adaptive fusion U-Net (MAFU-Net) procedure aimed at precisely extracting individually separable aquaculture ponds (ISAPs) from medium-resolution remote sensing imagery. Initially, this study analyzes the spectral differences between aquaculture ponds and interfering objects such as saltwater fields in four typical aquaculture areas along the coast of Liaoning Province, China. It innovatively introduces a difference index for saltwater field aquaculture zones (DIAS) and integrates this index as a new band into remote sensing imagery to increase the expressiveness of features. A median augmented adaptive fusion module (MEA-FM), which adaptively selects channel receptive fields at various scales, integrates the information between channels, and captures multiscale spatial information to achieve improved extraction accuracy, is subsequently designed. Experimental and comparative results reveal that the proposed MAFU-Net method achieves an F1 score of 90.67% and an intersection over union (IoU) of 83.93% on the CHN-LN4-ISAPS-9 dataset, outperforming advanced methods such as U-Net, DeepLabV3+, SegNet, PSPNet, SKNet, UPS-Net, and SegFormer. This study’s results provide accurate data support for the scientific management of aquaculture areas, and the proposed MAFU-Net method provides an effective method for semantic segmentation tasks based on medium-resolution remote sensing images.
Noninvasive Early Detection of Systemic Inflammatory Response Syndrome of COVID-19 Inpatients Using a Piezoelectric Respiratory Rates Sensor
Authors: Kobayashi Tsuyoshi , Matsui Takemi , Sugita Isamu , Tateda Norihiro , Sato Shohei , Hashimoto Kenichi , Suda Masei
Published: November 2024

In 2020, 20% of patients with COVID-19 developed severe complications, including life-threatening pneumonia with systemic inflammatory response syndrome (SIRS). We developed a preliminary SIRS monitor that does not require blood sampling, is noninvasive, and can collect data 24 h per day. The proposed monitor comprises a piezoelectric respiratory sensor located beneath the patient’s mattress and a fingertip pulse sensor that determines ultra-high accuracy respiratory rate (mode of a 40-min frequency distribution of respiratory rates (M40FD-RR)). We assessed the clinical performance of the M40FD-RR preliminary SIRS monitor in 29 patients (12 female, 17 male, aged 15–90 years) hospitalized at Suwa Central Hospital with COVID-19, which was confirmed by a positive polymerase chain reaction test. SIRS was evaluated by logistic regression analysis using M40FD-RR, heart rate, age, and sex as explanatory variables. We compared the results of 109 examinations of 29 COVID-19 inpatients with SIRS against those determined by the proposed monitor. The proposed monitor achieved 75% sensitivity and 83% negative predictive value, making it a promising candidate for future 24 h noninvasive preliminary SIRS tests.