Search Results (19)

Sepsis-associated acute kidney injury (S-AKI) represents a significant health problem associated with adverse outcomes. Our study aimed to assess the value of serum cystatin-C (sCysC) and TNF-α (rs361525) in combination for diagnosing S-AKI patients and predicting their adverse outcomes. The study included 100 critically ill neonates and 100 controls. Patients were categorized into an S-AKI group and a non-AKI group. TNF-α (−238, rs361525) genotyping was performed using RT-PCR, and sCysC was assessed using ELISA. Our study showed a fundamental difference in the genotype frequencies of TNF-α (−238, rs361525) and SNP between S-AKI and non-AKI patients. Furthermore, there was a significant relationship between cystatin C and TNF-α (−238, rs361525), where cystatin C was higher in patients with AA alleles than in patients with GA and GG alleles. Combining GA + AA genotypes with elevated serum cystatin-C levels can serve as a potential diagnostic and prognostic biomarker for AKI development in this population. The GA/AA genotypes independently predicted S-AKI risk (OR = 6.64, p < 0.001). At the same time, elevated sCysC (>9.4 mg/L) emerged as a sensitive biomarker (AUC = 0.848) and independent predictor of adverse outcomes. Collectively, these findings contribute to the growing field of personalized medicine and represent a strategic advantage, enabling prevention-focused care rather than the treatment of established disease. Full article

This study investigated the diagnostic, prognostic, and therapeutic significance of Fc receptor-like 1 (FCRL1) and B-cell activating factor (BAFF) mRNA expression in Egyptian patients with diffuse large B-cell lymphoma (DLBCL) undergoing the standard R-CHOP regimen (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) using quantitative real-time PCR (RT-qPCR). The results demonstrated that FCRL1 and BAFF mRNA expression were significantly elevated in DLBCL patients compared to healthy controls. A strong positive correlation existed between BAFF and FCRL1 expression levels. Diagnostic performance assessed through combined ROC curve analysis revealed that BAFF, FCRL1, and lactate dehydrogenase (LDH) achieved perfect diagnostic accuracy (AUC = 1.0), demonstrating 100% sensitivity, specificity, and predictive values. Further prognostic analysis using COX regression identified elevated FCRL1 expression as the most significant predictor of poor clinical outcomes. Kaplan–Meier survival analysis reinforced this finding, with high FCRL1 expression showing significant associations with reduced overall survival (OS, p = 0.031) and progression-free survival (PFS, p = 0.038). The study underscores the potential utility of BAFF and FCRL1 mRNA as diagnostic markers for DLBCL, with FCRL1 emerging as a promising prognostic marker and potential therapeutic target enabling more tailored treatment approaches for DLBCL, the most common type of B-cell non-Hodgkin lymphoma, and patients receiving R-CHOP therapy. Full article

Although there are different theories about the adoption and implementation of technological innovation by companies, they have an organization/individual-centered approach. The aim of this study is to propose the Technology–Organization–External–Sustainability (TOES) framework, a technology adoption theory, an extension of the Technology-Organization-(business) Environment (TOE) framework, to assist companies in adopting and implementing technology through a holistic approach. Design Science Research was used to structure the TOES framework and the Delphi method for its evaluation and improvement. To examine the potential of the TOES framework, 40 maturity and readiness models found in the literature were examined, which were created to assist in Industry 4.0 implementation projects, according to their common element of analysis—their dimensions. An important finding was that the TOES framework allowed us to identify that most of these models focused predominantly on technology; therefore, they do not always allow for a general analysis of the company, nor do they consider the external competitive scenario or sustainability as relevant contexts for analysis. The theoretical and practical contribution lies in the presentation of the TOES framework that incorporates sustainability as a relevant context for analysis, expanding the theory of the adoption of technological innovation. Another theoretical contribution is to alert researchers that maturity and readiness models for Industry 4.0 implementation projects should take a more holistic approach. It is suggested to use the TOES framework in other areas of knowledge, such as medicine, engineering, technology, and science, among others, to test its potential. Full article

With the global rise in consumer electronics, electric vehicles, and renewable energy, the demand for lithium-ion batteries (LIBs) is expected to grow. LIBs present a significant challenge for state estimations due to their complex non-linear electrochemical behavior. Currently, commercial battery management systems (BMSs) commonly use easier-to-implement and faster equivalent circuit models (ECMs) than their counterpart continuum-scale physics-based models (PBMs). However, despite processing more mathematical and computational complexity, PBMs are attractive due to their higher accuracy, higher fidelity, and ease of integration with thermal and degradation models. Various reduced-order PBM battery models and their computationally efficient numerical schemes have been proposed in the literature. However, there is limited data on the performance and feasibility of these models in practical embedded and cloud systems using standard programming languages. This study compares the computational performance of a single particle model (SPM), an enhanced single particle model (ESPM), and a reduced-order pseudo-two-dimensional (ROM-P2D) model under various battery cycles on embedded and cloud systems using Python and C++. The results show that reduced-order solvers can achieve a 100-fold reduction in solution times compared to full-order models, while ESPM with electrolyte dynamics is about 1.5 times slower than SPM. Adding thermal models and Kalman filters increases solution times by approximately 20% and 100%, respectively. C++ provides at least a 10-fold speed increase over Python, varying by cycle steps. Although embedded systems take longer than cloud and personal computers, they can still run reduced-order models effectively in Python, making them suitable for embedded applications. Full article

Agroecosystem function is related to the positioning of the agroecosystem and its connectivity relationship with the surrounding landscape. Herein, three methodologies are presented, which allow assessment of the links between agroecosystems and the surrounding matrix, yielding information for promoting patterns and mechanisms that foster biodiversity and the provision of multiple ecosystem services such as biological pest control, as well as energy flows and material exchanges. The three methodologies are complementary when assessing agrolandscape-level interactions in situations of regional agroecological transition. Through the use of 11 indicators, a methodology (Assessment of Beneficial Insect Habitat Suitability-ABIHS) was applied in two northern California vineyards to determine whether each agrolandscape provided suitable environmental opportunities to sponsor biological insect pest control. The Main Agroecological Structure [MAS] applied in Chilean family farms elucidates some of the relationships between farms and their biophysical environment, generating data to analyze the links between agroecosystem landscapes, management practices, and insect diversity in family farms. Social Agrarian metabolism (SAM) applied in Spanish agrolandscapes quantifies the biophysical and energy flows in agricultural systems, testing whether such flows are capable of reproducing and/or improving fund elements such as soil, biodiversity, and landscape vegetation in successive production cycles. The three methodologies provide key information for the design of sustainable agroecosystems in the context of an agroecological transition. Full article

This paper discusses the relationship between morality and engagement focused on the narratives about climate change. The goal of our research is to understand whether moral grounds identified in individuals and in narratives can influence youth’s engagement in environmental debate and news consumption on climate change. Recognizing that people’s perceptions of climate change are related to several factors, such as ideas, cultures, and values, we sought to understand whether there is a “green morality” or a prevalence of more responsive moral attributes in individuals when they are exposed to thinking about the environment. We use the Moral Foundations Theory to analyze comments on the environmental news on Twitter and a questionnaire adapted to the environment on moral grounds. The data were collected from Brazil and Portugal between 2021 and 2022. The overall results showed a high incidence of responses with Care/Harm and Fairness/Cheating, and an average incidence of responses related to Loyalty/Betrayal and Authority/Subversion. The results indicate that youngsters show a more prominent moral to care and environmental harm, as well as justice and responsibility, which may influence their interest in the consumption of environmental news and future engagement. In addition, there are factors, such as political issues, that can influence moral values and engagement. Full article

The nano-delivery system with a dual biomimetic effect can penetrate deeper in tumor microenvironments (TMEs) and release sufficient antitumor drugs, which has attracted much attention. In this study, we synthesized erythrocyte-like mesoporous silica nanoparticles (EMSNs) as the core loaded with doxorubicin (DOX) and coated them with calcium phosphate (CaP) and erythrocyte membrane (EM) to obtain DOX/EsPMs. The transmission electron microscopy (TEM), fluorescent co-localization and protein bands of SDS-PAGE were used to confirm the complete fabrication of EsPMs. The EsPMs with erythrocyte-like shape exhibited superior penetration ability in in vitro diffusion and tumor-sphere penetration experiments. Intracellular Ca²⁺ and ROS detection experiments showed that the CaP membranes of EsPMs with pH-sensitivity could provide Ca²⁺ continuously to induce reactive oxide species’ (ROS) generation in the TME. The EM as a perfect “camouflaged clothing” which could confuse macrophagocytes into prolonging blood circulation. Hemolysis and non-specific protein adsorption tests proved the desirable biocompatibility of EsPMs. An in vivo pharmacodynamics evaluation showed that the DOX/EsPMs group had a satisfactory tumor-inhibition effect. These advantages of the nano-erythrocytes suggest that by modifying the existing materials to construct a nano-delivery system, nanoparticles will achieve a biomimetic effect from both their structure and function with a facilitated and sufficient drug release profile, which is of great significance for antitumor therapy. Full article

How to disentangle the possible genuine quenching of $g_A$ caused by scale anomaly of QCD parameterized by the scale-symmetry-breaking quenching factor $q_{ssb}$ from nuclear correlation effects is described. This is accomplished by matching the Fermi-liquid fixed point theory to the “Extreme Single Particle (shell) Model” (acronym ESPM) in superallowed Gamow–Teller transitions in heavy doubly-magic shell nuclei. The recently experimentally observed indication for $(1-q_{ssb})\ne 0$—that one might identify as “fundamental quenching (FQ)”—in certain experiments seems to be alarmingly significant. I present arguments for how symmetries hidden in the matter-free vacuum can emerge and suppress such FQ in strong nuclear correlations. How to confirm or refute this observation is discussed in terms of the superallowed Gamow–Teller transition in the doubly-magic nucleus ${}^{100}$Sn and in the spectral shape in the multifold forbidden $\beta$ decay of ${}^{115}$In. Full article

The Zeta converter is an essential and widely used high-order converter. The current modeling studies on Zeta converters are based on the model that devices, such as capacitors and inductors, are of integer order. For this reason, this paper takes the Zeta converter as the research object and conducts an in-depth study on its fractional-order modeling. However, the existing modeling and analysis methods have high computational complexity, the analytical solutions of system variables are tedious, and it is difficult to describe the ripple changes of state variables. This paper combines the principle of harmonic balance with the equivalent small parameter method (ESPM); the approximate analytic steady-state solution of the state variable can be obtained in only three iterative steps in the whole solving process. The DC components and ripples of the state variables obtained by the proposed method were compared with those obtained by the Oustaloup’s filter-based approximation method; the symbolic period results obtained by ESPM had sufficient precision because they included more combinations of higher harmonics. Finally, the influence of fractional order on harmonics were analyzed. The obtained results show that the proposed method has the advantage of being less computational and easily describing changes in the ripple of the state variables. The simulation results are provided for validity of the theoretical analysis. Full article

Recently, the Unesp-Botucatu sheep acute pain scale (USAPS) was created, refined, and psychometrically validated as a tool that offers fast, robust, and simple application. Evidence points to an improvement in pain diagnosis when the importance of the behavioral items of an instrument is statistically weighted; however, this has not yet been investigated in animals. The objective was to investigate whether the implementation of statistical weightings using machine learning algorithms improves the USAPS discriminatory capacity. A behavioral database, previously collected for USAPS validation, of 48 sheep in the perioperative period of laparoscopy was used. A multilevel binomial logistic regression algorithm and a random forest algorithm were used to determine the statistical weights and classify the sheep as to whether they needed analgesia or not. The quality of the classification, estimated by the area under the curve (AUC) and its 95% confidence interval (CI), was compared between the USAPS versions. The USAPS AUCs weighted by multilevel binomial logistic regression (96.59 CI: [95.02–98.15]; p = 0.0004) and random forest algorithms (96.28 CI: [94.17–97.85]; p = 0.0067) were higher than the original USAPS AUC (94.87 CI: [92.94–96.80]). We conclude that the implementation of statistical weights by the two machine learning algorithms improved the USAPS discriminatory ability. Full article

The southwestern part of Nigeria, particularly Ogun State, is more vulnerable to the vagaries of climate change due to the high dependence on rain-fed agriculture and limited capacities to respond to climate change. In this study, factors influencing climate change adaptation strategies and its impacts on household food security of smallholder rice farmers in Ogun State were estimated. A multistage sampling technique was employed to select 120 smallholder rice farmers in the study area. The factors influencing the adoption of climate change adaptation practices and their impacts on household food security among smallholder rice farmers in Ogun State were examined using a probit model and an endogenous switching probit model (ESPM). According to the results of household dietary diversity score (HDDS), adopters of climate change adaptation techniques have higher levels of food security than non-adopters. The outcome of the ESPM shows that access to market information, access to extension agents, gender, off-farm income, and membership in cooperatives all contribute to the variations in food security experienced by both adopters and non-adopters of climate change adaptation strategies. A unit increase in adoption of climate change adaptation measures will increase household food security by about 3 units while decreasing severity in food insecurity by about 3.2 units. Therefore, it is recommended that policies that would support smallholder farmers’ decisions to embrace measures for coping with climate change should be encouraged in order to stimulate their adaptive capacity. Additionally, in order to secure the inclusive sustainability of the agricultural sector, stakeholders and NGOs must collaborate with each other to enhance the circumstances under which farmers may receive climate change information, timely agricultural loans, and policy incentives. Full article

Emerging and unregulated contaminants end up in soils via stabilized/composted sewage sludges, paired with possible risks associated with the development of microbial resistance to antimicrobial agents or an imbalance in the microbial communities. An enrichment experiment was performed, fortifying the sewage sludge with carbamazepine, ketoprofen and diclofenac as model compounds, with the aim to obtain strains with the capability to transform these pollutants. Culturable microorganisms were obtained at the end of the experiment. Among fungi, Cladosporium cladosporioides, Alternaria alternata and Penicillium raistrickii showed remarkable degradation rates. Population shifts in bacterial and fungal communities were also studied during the selective pressure using Illumina MiSeq. These analyses showed a predominance of Ascomycota (Dothideomycetes and Aspergillaceae) and Actinobacteria and Proteobacteria, suggesting the possibility of selecting native microorganisms to carry out bioremediation processes using tailored techniques. Full article

Urban agriculture is practiced in spatially fragmented landscapes with unique characteristics that can impact species occurrence in time and space. As a result, biological control services, an ecosystem service from naturally occurring arthropod natural enemies, can be negatively impacted. Many urban farms forgo pesticides and utilize agroecological pest-management strategies that rely on natural enemies to help regulate pest populations. Understanding how these enemies are affected by landscape composition and on-farm management practices is critical to understanding agroecological pest management in UA and furthering our understanding of landscape-mediated population dynamics. Over two growing seasons, we sampled brassica crops in urban agriculture sites occurring on a spectrum of surrounding landscape imperviousness, spatial composition, size, and management practices to better understand parasitic Hymenoptera abundance, richness, and parasitism rates on the common cabbage aphid (Brevicoryne brassicae). We found that on-farm agroecological pest-management practices such as mulch coverage, floral richness, and overall crop-plant richness impacted parasitic Hymenoptera abundance. Larger proportions of on-farm noncrop area increased parasitoid abundance on urban farms. Aphid parasitism increased in relation to on-farm management practices, including increased crop-plant richness. These findings add to a growing understanding of urban agroecosystem function and support the enemies hypothesis in urban agroecosystems. Full article

In this paper, several modeling methods for the continuous current mode (CCM) fractional-order Cuk converter are investigated. First, the state space averaging method is used to establish the model. Based on this model, the expressions of inductors’ current and capacitor voltage as well as the transfer functions are derived. Then, the equivalent small parameter method (ESPM) is employed to model the converter. Based on the Oustaloup filter principle, the approximate models of fractional-order capacitor and inductors are constructed, which consist of integer-order components, to build the circuit model (CM) of the converter. In addition, the numerical model (NM) of the converter is established. Simulation results are provided to compare the modeling methods, which show that the ESPM has some advantages over the other methods. Finally, the hardware-in-the-loop experiment is conducted to verify the effectiveness of the circuit model. Full article

Rapid and efficient demulsification (destabilizing of an emulsion) processes of a water in oil (W/O) emulsion were carried out in a three-dimensional electric spiral plate-type microchannel (3D-ESPM). In this experiment, the demulsifying efficiency of emulsions by 3D-ESPM was compared with that by gravity settling, the factors influencing demulsifying efficiency were investigated, and the induction period, cut size and residence time in the demulsification process were studied. The results showed that in contrast to the gravity settling method, 3D-ESPM can directly separate the disperse phase (water) instead of the continuous phase (oil). The maximum demulsifying efficiency of W/O emulsion in a single pass through the 3D-ESPM reached 90.3%, with a microchannel height of 200 μm, electric field intensity of 250 V /cm, microchannel angle of 180°, microchannel with 18 plates and a flow rate of 2 mL /min. An induction period of 0.6 s during the demulsification process was simulated with experimental data fitting. When the residence time of emulsion in 3D-ESPM was longer than the induction period, its demulsifying efficiency increased as the increase of the flow velocity due to the droplet coalescence effects of Dean vortices in the spiral microchannel. For this device a cut size of droplets of 4.5 μm was deduced. Our results showed that the demulsification process of W/O emulsion was intensified by 3D-ESPM based on the coupling effect between electric field-induced droplets migration and microfluidic hydrodynamic trapping. Full article