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Investigating the drivers and barriers of digital resource utilization in mathematical culture curricula development: A PLS-SEM analysis with Chinese teachers
Get PDFThe convergence of technology and education has enabled the creation of instructional programs utilizing digital resources, garnering significant interest from educators in developing mathematical culture curricula. This study investigates these factors by incorporating the perceived importance of policy (PIP) variables into the unified theory of acceptance and use of technology (UTAUT) model. Quantitative analysis was employed to collect online questionnaire data from 873 teachers in Henan Province, which was subsequently analyzed using partial least squares structural equation modeling (PLS-SEM). The findings revealed that (1) performance expectation did not significantly impact teachers’ intentions and behaviors regarding the use of digital resources for developing mathematics culture lessons; (2) effort expectations negatively influenced such use; and (3) social influence, facilitating conditions, and perceived policy importance emerged as key drivers, with social influence exerting the most substantial impact. These insights enhance our understanding of the factors influencing teachers’ integration of digital resources in mathematics culture curriculum development. They can inform strategies to improve teachers’ knowledge of teaching with mathematics technology (KTMT) and to promote technology-enhanced mathematics teaching and learning
Multi-layer perceptron artificial neural network for environmental risks prediction of SW-induced pollution in Dar es Salaam, Tanzania
Get PDFMany metropolitan areas face significant environmental challenges posed by improper disposal and management of solid waste. As a result, environmental risks have emerged as a pressing concern, prompting dedicated research efforts. This study on environmental risk prediction of Dar es Salaam SW coincides with a mounting governmental effort over rising pollution levels from inadequate SW management. Using the multi-layer perceptron artificial neural network (MLP-ANN) model, it effectively examines the prevailing conditions and forecasts waste generation rates (WGRs) and environmental risk index (ERI) associated with SW pollution. As confirmed with 94.5% prediction accuracy and 86.5% success rate of the MLP-ANN model, WGRs in Dar es Salaam have doubled in less than two decades. Besides, over 40% of the overall generated SW is left unattended. Consequently, the ERI exhibits a consistent upward trajectory throughout the assessment period, with intermittent fluctuations between Level II and III but a persistent overall increase. Projections indicate an escalation of ERI to Level IV by 2025/26 and to a critical threshold (Level V) by 2038. The key indices such as pressure, state, and impact are anticipated to reach critical thresholds ahead of the comprehensive ERI. This underscores the imperative for timely interventions and the urgency of addressing SW management issues to curb the escalating environmental risks in Dar es Salaam and other metropolises with similar challenges
Artificial intelligence and machine learning for additive manufacturing composites toward enriching Metaverse technology
Get PDFAs a result of the growing significance and application of technology across a wide range of fields, digital environments such as Metaverse started to take shape over the span of the previous decade. This study aims to discover an area of engineering that could benefit from this new technology by developing an artificial intelligence (AI)—based approach to analyzing and predicting the mechanical properties of carbon fiber reinforced syntactic thermoset composites that are made through additive manufacturing (AM). These composites are intended to be utilized as a tool for metaverse technology in a variety of domains—as the presence of the limitations in the currently experimental methods. The metaverse allows for the generation of simulations through the application of artificial intelligence (AI) and machine learning (ML). Consequently, this paves the way for individuals to investigate various design possibilities and view the virtual manifestation of those possibilities. This is made possible by the use of machine learning algorithms, which allow for the monitoring and evaluation of user performance, as well as the provision of individualized feedback and suggestions for improvement. As a consequence of this, it is feasible that professionals will be able to get education and training that are both more efficient and effective. Consequently, this work aims to introduce an Adaptive Neuro-Fuzzy Inference System (ANFIS)—based model, which is able to effectively anticipate the behavior of mechanical systems in a variety of settings without the need for significant measurements. The validity of the ANFIS model was determined through the utilization of flexure and compression testing. The approach that was used to improve the technical assessment of the manufactured composites—is verified by the model’s near-realistic predictions. Moreover, this method is superb for lowering weight, enhancing mechanical qualities, and minimizing product complexity
Harnessing green chemistry for waste water remediation through Alpinia leaves silver nanoparticles
Get PDFAddressing environmental concerns with sustainable nanomaterial is a vital step towards innovative and eco-friendly techniques that address important global issues like pollution, water contamination, and resource depletion. This eco-friendly approach offers a sustainable alternative to conventional methods and this study aims to showcase the applications of biogenic silver nanoparticles (AgNPs) synthesized using green synthesis techniques with aqueous leaf extracts from five Alpinia varieties; Alpinia purpurata, Alpinia caerulea, Alpinia zerumbet ‘variegata’, Alpinia calcurata and Alpinia zerumbet. The AgNPs were synthesized using water extracts (WE) and silver nitrate at the optimum conditions. Characterization of AgNPs using UV-Vis spectroscopy and scanning electron microscopy (SEM), confirmed their successful formation and morphology. Spherical A.zerumbet_AgNPs between 28–68 nm in size were observed. The photocatalytic activity was tested by degrading methyl Orange (MO) dye under solar irradiation and the use NaBH4 with AgNPs significantly increased the degradation of MO. P-nitrophenol catalysis using AgNP and NaBH4 resulted promising results. Cytotoxicity of AgNPs using Artemia salina was evaluated and 100% viability was seen. The antibacterial activity was conducted using Escherichia coli and Staphylococcus aureus, unlike the WEs, all AgNPs showed antibacterial activity. This study revealed that the AgNPs synthesized using Alpinia leaves has diverse functional properties, presenting a promising avenue for future research and practical applications in environmental pollution
Protocol for a systematic review of the health impact of urban farming interventions
Get PDFUrban farms are areas specifically dedicated to growing plants for purposes related to food security, medicinal use, and therapeutic benefits. Their prevalence has increased notably since the beginning of the 21st century, and they are associated with numerous health advantages. However, there remains a lack of consensus regarding the health impacts of urban farming. In this manuscript, we present a protocol for a systematic review which aims to provide comprehensive insight into required methods used to assess health outcomes from urban farming interventions and is registered in PROSPERO under the reference number CRD42023448001. The protocol will adhere to the PRISMA guidelines, including studies addressing urban farming interventions for any population, with no restrictions on the year of publication, in databases such as PubMed, DOAJ, CAB Abstracts, and NIH. The ROBINS-I tool will assess bias, and the certainty of evidence will be evaluated using the GRADE framework. The data will be synthesized narratively in accordance with SWiM guidelines, aligning with WHO health concepts
Neutralizing the surging environmental pollution amidst renewable energy consumption and economic growth in Ghana: Insights from ARDL and quantile regression analysis
Get PDFThis research explores the link between renewable energy consumption, economic growth, electricity accessibility, greenhouse gas emissions, and environmental degradation in Ghana from 1993 to 2020. Utilizing the autoregressive distributed lag (ARDL) model and quantile regression, it analyzes the validity of the Environmental Kuznets Curve (EKC) hypothesis. ARDL findings imply that renewable energy consumption (REC), greenhouse gas emissions (GHG), and power accessibility (ATE) have positive but statistically negligible long-term associations with CO2 emissions. In contrast, economic growth (ECG) shows a slight negative link. This suggests that current attempts to promote renewable energy and minimize emissions may only partially lower CO2 levels. Quantile regression demonstrates a positive correlation between REC and CO2 emissions, counter to the idea that more renewable energy consumption decreases emissions. GHG strongly affects environmental pollution (EVP) at all levels, whereas power accessibility (ATE) has a favorable effect at lower levels but becomes negative at higher ones. Economic growth’s impact on pollution is detrimental at lower and median values but needs more relevance at more significant levels. These results imply the need for stricter laws, technical breakthroughs, emission limitations, and carbon pricing to mitigate pollution coming from economic expansion
Sophoridine Inhibited Epithelial-Mesenchymal Transition, Migration and Invasion in Colorectal Cancer via Regulating ZO-1 and CCND1 Expressions
No full textBackground: Sophoridine has been reported to suppress multiple cancer types. However, its exact underlying mechanism on the epithelial-mesenchymal transition (EMT) in colorectal cancer (CRC) is yet to be elucidated. Therefore, this study was aimed to reveal its role in colorectal cancer (CRC). Methods: Potential targets of sophoridine and their relevant biological functions were predicted through bioinformatics tools. To investigate the effects of sophoridine on the EMT, migration, and invasion of cells, and the Wnt signaling pathway in CRC, the CRC cells, HCT116 and SW480, were treated with sophoridine and transfected with short hairpin RNA against Zonula occludens-1 (ZO-1) (sh-ZO-1) and Cyclin D1 (CCND1) overexpression plasmid. Furthermore, the quantification analyses, including quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western blot, were performed to determine the expression levels of EMT-associated factors such as ZO-1, vimentin, snail, alpha-smooth muscle actin (α-SMA), and E-cadherin and proteins associated with the Wnt signaling pathway (CCND1 and β-catenin). Moreover, wound healing and Transwell assays were used to evaluate the migration and invasion within CRC cells. Additionally, xenograft assay was applied to examine tumorigenesis in-vivo. Results: CCND1 and ZO-1 were predicted as the potential targets of sophoridine. Furthermore, sophoridine was observed to reduce the rate of migration and invasion, and decreased the levels of vimentin, snail, α-SMA, CCND1, and β-catenin while elevating the levels of E-cadherin and ZO-1 in CRC cells (p < 0.5). Moreover, ZO-1 knockdown and CCND1 overexpression reversed the inhibitory effects of sophoridine on the cell migration and invasion, as well as on the expressions of vimentin, snail, α-SMA, ZO-1, β-catenin, E-cadherin, and CCND1 (p < 0.5) in CRC cells. Additionally, ZO-1 knockdown and CCND1 overexpression were found to suppress the tumor growth in mice treated with sophoridine (p < 0.01). Conclusion: Sophoridine exhibits inhibitory effects on the EMT, migration, and invasion and reduces tumor growth in CRC by regulating the expression levels of ZO-1 and CCND1
Sema3A Mediates the Negative Regulatory Effect of Dermal Mesenchymal Stromal Cells on T Lymphocyte Responses
No full textBackground: The inhibitory effect of dermal mesenchymal stromal cells (DMSCs) on graft versus host disease (GVHD) has been demonstrated in mice, but the underlying mechanism remains unclear. Semaphorin-3A (Sema3A) is an effective regulator in all stages of immune response. The purpose of this manuscript is to investigate the role of Sema3A in the immunosuppressive effect of human DMSCs (hDMSCs). Methods: Coculture systems of hDMSCs expressing varying levels of Sema3A and T cells were established in vitro. The effects of hDMSCs expressing different Sema3A levels on T-cell proliferation, apoptosis, cell cycle, subsets, and cytokine secretion were examined. Results: Among the hDMSC types, ov3A-hDMSCs exhibited the most significant inhibition of T-cell proliferation. si3A-hDMSCs also suppressed T-cell proliferation, albeit with noticeably weaker effects compared to ov3A-hDMSCs. Sema3A arrested T cells in the G0/G1 phase, with ov3A-hDMSCs inducing S-phase arrest in T cells more potently than si3A-hDMSCs. This effect was associated with the inhibition of cyclin dependent kinase 4 (CDK4) and cyclin D1 and the promotion of p27 expression by Sema3A secreted by hDMSCs. Further investigation revealed that Sema3A secreted by hDMSCs suppressed the phosphorylation of extracellular regulated protein kinases (ERK) and zeta-chain-associated protein of 70 kDa (ZAP70), thus influencing the expression levels of downstream factors cyclin D1 and CDK4, thereby inhibiting T-cell proliferation. Additionally, Sema3A secreted by hDMSCs promoted Th2 and Treg cell differentiation while inhibiting Th1 and Th17 differentiation, thereby impacting cytokine secretion by these cells. Conclusions: Sema3A serves as the mediator for the negative regulatory effect of hDMSCs on T lymphocyte responses
Azole Antifungal Drug Toxicity—A Review
No full textThe enormousness of Invasive fungal infections (IFIs) are coming much more into notice lately. The clinical manifestations vary and can range from colonization in allergic broncho-pulmonary disease to active infection in local aetiological agents. The increase of immunosuppressive agents in association with solid organ transplants, chemotherapy and improved life-saving medical techniques necessitating indwelling catheters led to a substantial increase in the occurrence of serious invasive fungal infections. Azole antifungals helped by adding to therapeutic options in treatment of IFIs works by inhibiting 14α-lanosterol demethylase, a key enzyme in ergosterol biosynthesis, resulting in depletion of ergosterol and accumulation of toxic 14α-methylated sterols in membranes of susceptible fungus. Azoles are classified into two: the triazoles (fluconazole, itraconazole, voriconazole, posaconazole, and isavuconazole) and the imidazoles (ketoconazole). Despite wide spectrum activity, these drugs show toxic effects like hepatitis and inhibition of steroid hormone synthesis, prolonged corrected for heart rate (QTc) intervals, Suppressive effects on spatial learning and memory in long-term treatments and treatment with higher concentrations. Many clinical cases have reported visual impairment, photopsia and photophobia along with many other symptoms. Drug interactions of azoles are numerous and show effects like seizures, neuropathy and serotonin toxicity. The review gives an overview of mechanism, spectrum of activity and toxic effects of azole drugs observed in clinical cases as well as animal studies
The Different Effects of Pharmacological or Low-Doses of IFN-γ on Endothelial Cells are Mediated by Distinct Intracellular Signalling Pathways
No full textBackground: Interferon (IFN)-γ is a proinflammatory cytokine with a crucial role in intercellular communication during innate and acquired immune responses. IFN-γ interacts with various cell types, including endothelial cells. Here, we investigated the effects of pharmacological or low doses of IFN-γ in cultured endothelial cells. Methods: Human endothelial cells were cultured in the presence of pharmacological or low-dose concentrations of IFN-γ. Signal transducer and activator of transcription (STAT) and Extracellular signal-regulated kinase (ERK) phosphorylation were investigated by enzyme linked immunosorbent assay (ELISA). Western blot for ERK was also performed. Transient ERK silencing was obtained by short interfering RNA (siRNA). Cell proliferation and migration were analysed by cell counting and wound assay, respectively. Results: At pharmacological concentrations, IFN-γ activates the Janus kinases (JAK)/STAT pathway, leading to the overexpression of the cyclin-dependent kinase inhibitor 1A/p21 (CDKN1A/p21), which inhibits cell growth. In contrast, low-dose activated IFN-γ does not trigger the canonical JAK/STAT pathway and induces the phosphorylation of ERK. ERK activation is responsible for endothelial cell migration induced by low-dose activated IFN-γ. Conclusions: We demonstrate that pharmacological and low-dose activated IFN-γ exert distinct effects on endothelial cells by triggering different signal transduction pathways. These findings shed light on the intricate signalling pathways employed by IFN-γ, and suggest that low-doses of IFN-γ might play a homeostatic role in endothelial cell during innate and acquired immune responses