Search Results (1,040)

Pediatric patients who have undergone hematopoietic stem cell transplantation (HSCT) or chemotherapy are at increased risk for severe influenza complications, necessitating annual vaccination. This study evaluated the immunogenicity and antibody persistence of the 2021–2022 seasonal quadrivalent influenza vaccine in pediatric patients post-HSCT or chemotherapy, compared to healthy controls. A prospective cohort study included 80 pediatric participants divided into three groups: chemotherapy (n = 33), HSCT (n = 27), and healthy controls (n = 20). All participants were vaccinated with the 2021–2022 GC FLU Quadrivalent vaccine. Hemagglutination inhibition (HI) assays measured seroprotection rates (SPR), geometric mean titers (GMT), and seroconversion rates (SCR) for the four vaccine antigens (A/H1N1, A/H3N2, B/Victoria, B/Yamagata) at one, three, and six months post-vaccination. At one month post-vaccination, all groups met the 70% SPR threshold for A/H1N1 and A/H3N2, but not for B/Victoria. For B/Yamagata, the SPR was low in the chemotherapy and HSCT groups (18.18% and 33.33%, respectively), compared to 80.00% in controls (p < 0.0001 and p = 0.0015). While A/H1N1 and A/H3N2 GMTs were protective in all groups, only controls achieved protective levels for B/Yamagata. Over time, the control group maintained >70% SPR for A/H1N1 up to six months, but the chemotherapy and HSCT groups declined by three and six months, respectively. For A/H3N2, the SPR in controls dropped below 70% at three months, while it remained above 70% in the chemotherapy and HSCT groups until three months. None of the groups achieved protective GMTs for B strains at three or six months. Pediatric patients post-HSCT or chemotherapy demonstrated a comparable immune response to healthy controls for A/H1N1 and A/H3N2, but the rapid decline in A/H1N1 antibody levels suggests the need for ongoing monitoring and adjusted vaccination schedules. The poor response to B antigens, particularly B/Yamagata, underscores the need for improved vaccination strategies in these vulnerable populations. Full article

Nitrogen oxides are one of the main atmospheric pollutants and pose a threat to the ecological environment and human health. Selective catalytic reduction (NH₃-SCR) is an effective way of removing nitrogen oxides, with the catalyst being the key to this technology. Two-dimensional nanostructured layered double oxide (LDO) has attracted increasing attention due to the controllability of cations in the layers and the exchangeability of anions between layers. As a derivative of layered double hydroxide (LDH), LDO not only inherits the controllability and diversity inherent in the LDH structure but also exhibits excellent performance in the catalytic field. This article contains three main sections. It begins with a brief discussion of the development of LDO catalysts and analyzes the advantages of the LDO structure. The later section introduces the synthesis methods of LDH, clarifies the conversion relationship between LDH and LDO, and summarizes the modification impacts of the properties of LDO catalysts. The application of LDO catalysts used in NH₃-SCR under wild temperature conditions is discussed, and the different types, reaction processes, and mechanisms of LDO catalysts are described in the third section. Finally, future research directions and outlooks are also offered to assist the development of LDO catalysts and overcome the difficult points related to NH₃-SCR. Full article

We introduce a theoretical model for the photocurrent-voltage (I-V) characteristics designed to elucidate the interfacial phenomena in photoelectrochemical cells (PECs). This model investigates the sources of voltage losses and the distribution of photocurrent across the semiconductor–electrolyte interface (SEI). It calculates the whole exchange current parameter to derive cell polarization data at the SEI and visualizes the potential drop across n-type cells. The I-V model’s simulation outcomes are utilized to distinguish between the impacts of bulk recombination and space charge region (SCR) recombination within semiconductor cells. Furthermore, we develop an advanced deep neural network model to analyze the electron–hole transfer dynamics using the I-V characteristic curve. The model’s robustness is evaluated and validated with real-time experimental data, demonstrating a high degree of concordance with observed results. Full article

Background/Objective: Atrial fibrillation [AF] is the most common arrhythmia encountered in clinical practice and significantly increases the risk of stroke, peripheral embolism, and mortality. With the rapid advancement in artificial intelligence [AI] technologies, there is growing potential to enhance the tools used in AF detection and diagnosis. This scoping review aimed to synthesize the current knowledge on the application of AI, particularly machine learning [ML], in identifying and diagnosing AF in clinical settings. Methods: Following the PRISMA ScR guidelines, a comprehensive search was conducted using the MEDLINE, PubMed, SCOPUS, and EMBASE databases, targeting studies involving AI, cardiology, and diagnostic tools. Precisely 2635 articles were initially identified. After duplicate removal and detailed evaluation of titles, abstracts, and full texts, 30 studies were selected for review. Additional relevant studies were included to enrich the analysis. Results: AI models, especially ML-based models, are increasingly used to optimize AF diagnosis. Deep learning, a subset of ML, has demonstrated superior performance by automatically extracting features from large datasets without manual intervention. Self-learning algorithms have been trained using diverse data, such as signals from 12-lead and single-lead electrocardiograms, and photoplethysmography, providing accurate AF detection across various modalities. Conclusions: AI-based models, particularly those utilizing deep learning, offer faster and more accurate diagnostic capabilities than traditional methods with equal or superior reliability. Ongoing research is further enhancing these algorithms using larger datasets to improve AF detection and management in clinical practice. These advancements hold promise for significantly improving the early diagnosis and treatment of AF. Full article

This paper experimentally investigates the behavior of innovative sustainable Low-Cost Bamboo Composite (LCBC) structural columns under compressive loading. The LCBC columns are manufactured from bamboo culms in combination with bio-based resins to form composite structural columns. Different LCBC cross-sectional configurations are investigated in this study, including the Russian doll (RD), Big Russian doll (BRD), Hawser (HAW), and Scrimber (SCR). Two bio-based resins, including one bio-epoxies and one furan-based resin, in addition to a soft bio-based filler and a synthetic epoxy resin, are applied. The bamboo species used as the cast-in-place giant bamboo for all configurations include Moso, Guadua, and Tali. Slender LCBC columns showed maximum stress equal to 60 MPa at failure. The study found that the samples with bio-epoxy resin (BE2) exhibited enhanced material stiffness when compared to synthetic epoxy (EPX) and furan-based resin (PF1), while PF1 specimens demonstrated increased ductility. Among the specimens with Moso bamboo and BE2 resin, those with SCR and HAW configurations achieved the highest compressive strengths. Full article

Ship detection in synthetic aperture radar (SAR) imagery faces significant challenges due to the limitations of traditional methods, such as convolutional neural network (CNN) and anchor-based matching approaches, which struggle with accurately detecting smaller targets as well as adapting to varying environmental conditions. These methods, relying on either intensity values or single-target characteristics, often fail to enhance the signal-to-clutter ratio (SCR) and are prone to false detections due to environmental factors. To address these issues, a novel framework is introduced that leverages the detection transformer (DETR) model along with advanced feature fusion techniques to enhance ship detection. This feature enhancement DETR (FEDETR) module manages clutter and improves feature extraction through preprocessing techniques such as filtering, denoising, and applying maximum and median pooling with various kernel sizes. Furthermore, it combines metrics like the line spread function (LSF), peak signal-to-noise ratio (PSNR), and F1 score to predict optimal pooling configurations and thus enhance edge sharpness, image fidelity, and detection accuracy. Complementing this, the weighted feature fusion (WFF) module integrates polarimetric SAR (PolSAR) methods such as Pauli decomposition, coherence matrix analysis, and feature volume and helix scattering (Fvh) components decomposition, along with FEDETR attention maps, to provide detailed radar scattering insights that enhance ship response characterization. Finally, by integrating wave polarization properties, the ability to distinguish and characterize targets is augmented, thereby improving SCR and facilitating the detection of weakly scattered targets in SAR imagery. Overall, this new framework significantly boosts DETR’s performance, offering a robust solution for maritime surveillance and security. Full article

Since the dawn of the 21st century, supply chains (SCs) have faced an array of unprecedented challenges, encompassing economic volatility, escalating geopolitical conflicts, intensified trade disputes, and persistent environmental degradation. These challenges have imposed immense pressures on SCs, amplifying both the risks and occurrences of disruptions. In response to these critical demands, there has been a substantial increase in academic, industrial, and governmental focus on the resilience and recovery capabilities of SCs. In this context, the supply chain (SC) for sewage treatment equipment has been significantly affected. This study aims to systematically investigate collaborative strategies and mechanisms for bolstering the resilience of manufacturing SCs within the sewage treatment sector, with particular attention to collaborative decision-making, information sharing, and risk mitigation throughout the SC lifecycle. Following a comparative analysis of various methodologies, this paper employed the structural equation model (SEM) and subsequently conducted a comprehensive survey of manufacturers specializing in glass fiber sewage treatment systems, yielding 385 valid responses. Through this data, a structural equation model was developed to analyze pathways for resilience enhancement. A thorough analysis of the results indicates that Supply Chain Collaboration (SCC) and collaborative decision-making are instrumental in strengthening Glass Fiber Sewage Treatment Supply Chain Resilience (SCR) through the implementation of effective information sharing and risk management practices. These findings contribute to the theoretical framework of SCC and SCR by clarifying the influence of collaborative practices while also providing practical guidance for the governance and strategic management of sewage treatment equipment enterprises and their associated SCs. The conclusions drawn from this study can guide us in establishing a more resilient and sustainable SC ecosystem, making it more directive and capable of mitigating complex disruptions. Full article

The GRAS gene family, derived from GAI, RGA, and SCR, plays a crucial role in plant growth and development. In the diploid Cyclocarya paliurus (2n = 2x = 32) with heterodichogamous characteristics, 51 CpGRAS genes were identified and phylogenetically classified into 10 subfamilies. Structural analysis revealed that CpGRAS genes possessed a canonical GRAS domain, but 70% lacked introns. WGD/segmental duplication was the major driver in the expansion of the CpGRAS family. In addition, a Ka/Ks ratio below 1 for these genes implied functional constraints and evolutionary conservation. Transcriptional profiling revealed significant differential expressions of CpGRAS genes between male and female flowers from two mating types, protogyny (PG) and protandry (PA). Notably, members of the DELLA subfamily exhibited significant upregulation in female flowers at the inflorescence elongation (S3) stage. The expression level of CpSCL6-2 in late-flowering samples (PA-F and PG-M) was higher than in early-flowering ones (PA-M and PG-F). Co-expression analysis identified that CpRGL1 and CpGAI-2 of the DELLA subfamily, along with CpSCL6-2, acted as hub genes, implying their crucial roles in floral development and potential involvement in the heterodichogamous flowering mechanism in C. paliurus. These findings broaden our understanding of CpGRAS genes and provide new insights into the molecular basis of heterodichogamy. Full article

Advanced airborne power generation technology represents one of the most effective solutions for meeting the electricity requirements of hypersonic vehicles during long-endurance flights. This paper proposes a power generation system that integrates a high-temperature fuel cell to tackle the challenges associated with power generation in the hypersonic field, utilizing techniques such as inlet pressurization, autothermal reforming, and anode recirculation. Firstly, the power generation system is modeled modularly. Secondly, the influence of key parameters on the system’s performance is analyzed. Thirdly, the performance of the power generation system under the design conditions is simulated and evaluated. Finally, the weight distribution and exergy loss of the system’s components under the design conditions are calculated. The results indicate that the system’s electrical efficiency increases with fuel utilization, decreases with rising current density and steam-to-carbon ratio (SCR), and initially increases before declining with increasing fuel cell operating temperature. Under the design conditions, the system’s power output is 48.08 kW, with an electrical efficiency of 51.77%. The total weight of the power generation system is 77.09 kg, with the fuel cell comprising 69.60% of this weight, resulting in a power density of 0.62 kW/kg. The exergy efficiency of the system is 55.86%, with the solid oxide fuel cell (SOFC) exhibiting the highest exergy loss, while the mixer demonstrates the greatest exergy efficiency. This study supports the application of high-temperature fuel cells in the hypersonic field. Full article

Background/Objectives: The incidence of acute kidney injury (AKI) has been steadily increasing. Despite its high prevalence, there is no pathogenetically rational therapy for AKI. This deficiency stems from the poor understanding of the pathogenesis of AKI. Renal ischemia/hypoxia is one of the leading causes of clinical AKI. This study investigates whether αMUPA mice, overexpressing the urokinase plasminogen activator (uPA) gene are protected against ischemic AKI, thus unraveling a potential renal damage treatment target. Methods: We utilized an in vivo model of I/R-induced AKI in αMUPA mice and in vitro experiments of uPA-treated HEK-293 cells. We evaluated renal injury markers, histological changes, mRNA expression of inflammatory, apoptotic, and autophagy markers, as compared with wild-type animals. Results: the αMUPA mice exhibited less renal injury post-AKI, as was evident by lower SCr, BUN, and renal NGAL and KIM-1 along attenuated adverse histological alterations. Notably, the αMUPA mice exhibited decreased levels pro-inflammatory, fibrotic, apoptotic, and autophagy markers like TGF-β, IL-6, STAT3, IKB, MAPK, Caspase-3, and LC3. By contrast, ACE-2, p-eNOS, and PGC1α were higher in the kidneys of the αMUPA mice. In vitro results of the uPA-treated HEK-293 cells mirrored the in vivo findings. Conclusions: These results indicate that uPA modulates key pathways involved in AKI, offering potential therapeutic targets for mitigating renal damage. Full article

Background: Deviations in serum creatinine (SCr), due to its determination using a Jaffe or an enzymatic method, have an effect on kidney disease detection and staging. It is not yet clear how large this effect is in kidney transplant recipients (KTRs). SCr measurement differences are of particular importance here to evaluate the graft function. Methods: The results of all parallel SCr measurements (Jaffe and enzymatic method) of adult outpatient KTRs in the same serum sample at the University Hospital Essen (Germany) between January 2020 and October 2023 were evaluated. A Bland–Altman plot with 95% limits of agreement (LoA) was used to assess the difference between the Jaffe and the enzymatic SCr (eSCr). For all patients, we used the CKD-EPI 2009 and EKFC formula, and for patients ≥ 70 years, we also used the BIS1 formula for the determination of eGFR. Results: A total of 12,081 parallel SCr measurements from 1243 KTRs were analyzed, where 61% were male and the median age was 53 years. On average, Jaffe SCr was 0.03 mg/dL higher than eSCr (LoA −0.16; 0.21 mg/dL). On average, the eGFR determined by Jaffe SCr was 1.9 mL/min/1.73 m² lower than the eGFR determined by eSCr (LoA −9.5; 5.7 mL/min/1.73 m²). The comparison of eGFR between the two SCr methods revealed a different CKD stage in 1589 (13%) of all analyzed measurements, most frequently between G2/G3a (41%) and G3a/G3b (24%). When using the EKFC and BIS1 formulas, there were approximately the same number of measurements leading to a different CKD stage. Conclusions: In more than every tenth SCr determination in outpatient KTRs, the difference between the Jaffe and enzymatic methods had an influence on the assignment to a CKD stage. This effect was comparably pronounced for all eGFR formulas applied. Full article

Background: Acute Kidney Injury (AKI) is a condition that affects a significant proportion of acutely unwell patients and is associated with a high mortality rate. Patients undergoing haemopoietic stem cell transplantation (HSCT) are in an extremely high group for AKI. Identifying a biomarker or panel of markers that can reliably identify at-risk individuals undergoing HSCT can potentially impact management and outcomes. Early identification of AKI can reduce its severity and improve prognosis. We evaluated the urinary Liver type fatty acid binding protein (L-FABP), a tubular stress and injury biomarker both as an ELISA and a point of care (POC) assay for AKI detection in HSCT. Methods: 85 patients that had undergone autologous and allogenic HSCT (35 and 50, respectively) had urinary L-FABP (uL-FABP) measured by means of a quantitative ELISA and a semi-quantitative POC at baseline, day 0 and 7 post-transplantation. Serum creatinine (SCr) was also measured at the same time. Patients were followed up for 30 days for the occurrence of AKI and up to 18 months for mortality. The sensitivity and specificity of uL-FABP as an AKI biomarker were evaluated and compared to the performance of sCr using ROC curve analysis and logistic regression. Results: 39% of participants developed AKI within 1 month of their transplantation. The incidence of AKI was higher in the allogenic group than in the autologous HTSC group (57% vs. 26%, p = 0.008) with the median time to AKI being 25 [range 9-30] days. This group was younger (median age 59 vs. 63, p < 0.001) with a lower percentage of multiple myeloma as the primary diagnosis (6% vs. 88%, p < 0.001). The median time to AKI diagnosis was 25 [range 9–30] days. uL-FABP (mcg/gCr) at baseline, day of transplant and on the 7th day post-transplant were 1.61, 5.39 and 10.27, respectively, for the allogenic group and 0.58, 4.36 and 5.14 for the autologous group. Both SCr and uL-FABP levels rose from baseline to day 7 post-transplantation, while the AUC for predicting AKI for baseline, day 0 and day 7 post-transplant was 0.54, 0.59 and 0.62 for SCr and for 0.49, 0.43 and 0.49 uL-FABP, respectively. Univariate logistic regression showed the risk of AKI to be increased in patients with allogenic HSCT (p = 0.004, 95%CI [0.1; 0.65]) and in those with impaired renal function at baseline (p = 0.01, 95%CI [0.02, 0.54]). The risk of AKI was also significantly associated with SCr levels on day 7 post-transplant (p = 0.03, 95%CI [1; 1.03]). Multivariate logistic regression showed the type of HSCT to be the strongest predictor of AKI at all time points, while SCr levels at days 0 and 7 also correlated with increased risk in the model that included uL-FABP levels at the corresponding time points. The POC device for uL-FABP measurement correlated with ELISA (p < 0.001, Spearman ‘correlation’ = 0.54) Conclusions: The urinary biomarker uL-FABP did not demonstrate an independent predictive value in the detection of AKI at all stages. The most powerful risk predictor of AKI in this setting appears to be allograft recipients and baseline renal impairment, highlighting the importance of clinical risk stratification. Urinary L-FAPB as a POC biomarker was comparable to ELISA, which provides an opportunity for simple and rapid testing. However, the utility of LFABP in AKI is unclear and needs further exploration. Whether screening through rapid testing of uL-FABP can prevent or reduce AKI severity is unknown and merits further studies. Full article

Technological progress and digitalization have ushered in significant transformations in business strategies. At present, research is scarcely focused on the influence of the adoption of digital technologies (DTs) on establishing comprehensive relationships within the context of a circular economy (CE), and the supply chain (SC) framework to contribute to the Resource-Based View (RBV) theory. This study utilizes survey data collected from 235 manufacturing practitioners employed by Turkish manufacturing enterprises to explore a model elucidating the relationship between DTs adoption and sustainability performance (SP) through supply chain traceability (SCT), supply chain resilience (SCR), and circular economy practices (CEPs), based on 10R strategies. Through this linkage, this research accentuates that the exclusive integration of CEPs with digital technology solutions is insufficient for industrial enterprises to attain their long-term sustainability goals. It underscores the necessity of ensuring SCT and/or SCR in this context. Full article

The stability and safety of selective catalytic reduction (SCR) systems are threatened by potential catalyst blockages caused by fly ash deposition. This paper proposes to improve the blockage resistance of denitration catalysts for sintered fly ash through particle conditioning. X-ray fluorescence spectroscopy, scanning electron microscopy, and laser particle analyzer were combined with laboratory heating experiments and field tests for systematic research. The results indicate that the composition and morphology of sintered fly ash are intrinsic factors contributing to catalyst blockage, while heating conditions act as external triggers. The sintered fly ash primarily exhibits a fluffy, branched cotton-like structure. Its main components are K₂O, Fe₂O₃, Na₂O, and CaO, with the alkali metal oxides of potassium and sodium comprising 20% to 50%. At ambient temperature, sintered fly ash presents no agglomeration, but significant agglomeration occurs as temperature increases. Particle conditioning effectively inhibits the agglomeration tendency of sintered fly ash. Field tests show that catalyst activity remains unaffected even under severe blockage conditions. The pressure drop across the catalyst layers increases progressively, with the first layer displaying the least pressure drop and the third displaying the most. After particle conditioning, the pressure drop across the catalyst is stabilized at values below 600 Pa, effectively mitigating the blockage issue in the denitrification catalyst for sintering flue gas. This research provides critical technical support for the stable ultra-low emission of NO_x from sintering flue gas. Full article

Three MnCeTiO_x catalysts with the same composition were prepared by conventional co-precipitation (MCT-C), reverse co-precipitation (MCT-R), and parallel co-precipitation (MCT-P), respectively, and their low-temperature SCR performance for de-NO_x was evaluated. The textural and structural properties, surface acidity, redox capacity, and reaction mechanism of the catalysts were investigated by a series of characterizations including N₂ adsorption and desorption, XRD, SEM, XPS, H₂-TPR, NH₃-TPD, NO-TPD, and in situ DRIFTs. The results revealed that the most excellent catalytic performance was achieved on MCT-R, and more than 90% NO_x conversion can be obtained at 100–300 °C under a high GHSV of 80,000 mL/(g_cat·H). Furthermore, MCT-R possessed optimal tolerance to H₂O and SO₂ poisoning. The excellent catalytic performance of MCT-R can be attributed to its larger BET specific surface area; higher contents of Mn⁴⁺, Ce³⁺, and adsorbed oxygen species; and more adsorption capacity for NH₃ and NO. Moreover, in situ DRIFTs results indicated that the NH₃-SCR reaction follows simultaneously the Langmuir–Hinshelwood and Eley–Rideal mechanisms at 100 °C. By adjusting the adding mode during the co-precipitation process, excellent low-temperature de-NO_x activity of MCT-R can be obtained simply and conveniently, which is of great practical value for the preparation of a MnCeTiO_x catalyst for denitrification. Full article