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Thermophysical analysis of time-dependent magnetized Casson hybrid nanofluid flow (Cu + GO/Kerosene Oil) using Darcy-Forchheimer and thermal radiative models for industrial cooling applications

Abstract This paper presents an in-depth analytical investigation into the time-dependent flow of a Casson hybrid nanofluid over a radially stretching sheet. The study introduces the effects of magnetic fields and thermal radiation, along with velocity and thermal slip, to model real-world systems for enhancing heat transfer in critical industrial applications. The hybrid nanofluid consists of three nanoparticles—Copper and Graphene Oxide—suspended in Kerosene Oil, selected for their stable and superior thermal properties. The theory of Darcy-Forchheimer, along with the suction and injection effect, is applied to refine the flow behaviour and enhance heat transfer efficiency. The governing nonlinear equations are solved using the Homotopy Analysis Method to provide a robust framework for solution accuracy. The graphical and tabulated results demonstrated that hybrid nanofluid outperforms mono and Casson hybrid nanofluids. The result shows that, at a nanoparticle volume concentration of 0.03, the Casson hybrid nanofluid showed a remarkable 19.99% increase in heat transfer, compared to 14.80% for simple nanofluid. The magnetic parameter and thermal radiation parameter further amplify thermal conductivity. This research provided a critical insight into optimizing thermal management systems for advanced engineering applications, positioning hybrid nanofluid as highly effective solutions for next-generation cooling technologies.

The customer satisfaction model in the mobile telecommunications sector after Covid-19 pandemic

The subject of this paper is modeling customer satisfaction in the mobile telecommunication industry following the Covid-19 pandemic. Based on standard customer satisfaction models, a specialized model tailored for the mobile telecommunication industry has been developed to account for its unique characteristics, including market concentration. This model was created within the Slovakian context using the Structural Equation Modelling method. The respondents were customers of all mobile operators in this market. The model revealed a positive relationship between image and perceived service quality and a negative relationship between customer expectations and perceived service value. However, it was not possible to demonstrate a relationship between image and customer loyalty or between customer expectations and customer satisfaction. Therefore, it seems that the factors influencing customer satisfaction in the telecommunications sector of an emerging EU economy differ from those in other sectors and economies in the post-Covid-19 context.

Spatiotemporal dynamics and driving factors of energy-related carbon emissions in the Yangtze River Delta region based on nighttime light data

Impact of nutritional status and pulmonary function on short- and long-term overall survival in hemodialysis patients

Background End-stage renal disease (ESRD) patients frequently experience protein-energy wasting (PEW), which increases their morbidity and mortality rates. Objective This study explores the effects of nutritional status and pulmonary function on the short- and long-term mortality of ESRD patients undergoing hemodialysis. Materials and methods 67 consecutive ESRD patients on maintenance hemodialysis were included in the study. The primary outcomes were all-cause one-year and five-year mortality. Data on demographic characteristics, comorbidities, and laboratory findings were collected. Pulmonary function tests were conducted along with body composition measurements using bioelectrical impedance analysis (BIA). Malnutrition was assessed using the Prognostic Nutritional Index (PNI). Results The median age of the patients was 60.9 ±  12.4 years, with 58.3% being male. Pulmonary function parameters (FEV1 and FVC) were significantly associated with short-term mortality. The PNI was a significant predictor of both short-term and long-term mortality. A PNI score ≤  39.01 was associated with increased short-term mortality (HR: 0.65, 95% CI: 0.48–0.88, p =  0.006), while a score ≤  40 was linked to increased long-term mortality (HR: 0.80, 95% CI: 0.67–0.95, p =  0.015). Additionally, older age (HR: 1.06, 95% CI: 1.01–1.12, p =  0.021) and higher glomerular filtration rate (GFR) (HR: 1.23, 95% CI: 1.02–1.42, p =  0.024) were related to increased long-term mortality risk. Conclusion The study demonstrates that PNI, age, and pulmonary function are critical factors influencing the survival of hemodialysis patients. These findings underscore the importance of comprehensive nutritional and pulmonary assessment to improve clinical outcomes in this population.

Enhancing trace DNA profile recovery in forensic casework using the amplicon RX post-PCR clean-up kit

Distinguishing benign and malignant myxoid soft tissue tumors: Performance of radiomics vs. radiologists

Introduction Benign and malignant myxoid soft tissue tumors have shared clinical, imaging, and histologic features that can make diagnosis challenging. The purpose of this study is comparison of the diagnostic performance of a radiomic based machine learning (ML) model to musculoskeletal radiologists. Methods Manual segmentation of 90 myxoid soft tissue tumors (45 myxomas and 45 myxofibrosarcomas) was performed on axial T1, and T2FS or STIR magnetic resonance imaging sequences. Eighty-seven radiomic features from each modality were extracted. Five ML models were trained to classify tumors as benign or malignant in 40 tumors and then tested with an additional 50 tumors using cross validation. The accuracy of the best ML model based on area under the receiver operating characteristic curve (AUC) was compared to the consensus diagnosis of three musculoskeletal radiologists. Correlation between radiologist confidence (equivocal, probably, consistent with) and accuracy was tested. Results The best ML classifier was a logistic regression model (AUC 0.792). Using T1 + T2/STIR images, the ML model classified 78% (39/50) of tumors correctly at a similar rate compared to 74% (37/50) by radiologists. When radiologists disagreed, the consensus diagnosis classified 50% of tumors (7/14) correctly compared to 86% (12/14) by the ML model, though this did not reach statistical significance. Radiologists had a cumulative accuracy of 91% (30/33) when they rated their confidence ‘consistent with’ compared to 61% (31/51) when they rated their confidence ‘equivocal/probably’ (P = 0.006). For cases when radiologists rated their confidence ‘equivocal/probably’, the ML model had 76% accuracy (39/51). Conclusions A radiomic based ML model predicted benign or malignant diagnosis in myxoid soft tissue tumors similarly to the consensus diagnosis by three musculoskeletal radiologists. Radiologist confidence in the diagnosis strongly correlated with their diagnostic accuracy. Though radiomics and radiologists perform similarly overall, radiomics may provide novel diagnostic utility when radiologist confidence is low, or when radiologists disagree.

Antihypertensive drug-related problems in Vietnamese ambulatory care

The impact of the reform of rural collective property rights system on villagers’ public participation: An empirical study based on CRRS 2020 data

The reform of rural collective property rights system is of great significance for protecting the collective asset rights and interests of villagers, activating rural resource elements, and achieving rural revitalization. This study is based on 284 village committee questionnaires and 7451 villager questionnaires from 10 provinces in China, and uses multi-layer linear regression models to explore the impact of the reform of rural collective property rights system on villagers’ public participation. Research has found that:(1) the reform of rural collective property rights system that has been completed at the rural level can significantly enhance the public participation of villagers, including total participation (β = 0.102, p ≤ 0.1), interest expression (β = 0.044, p ≤ 0.1), and election voting (β = 0.076, p ≤ 0.05). However, the impact on volunteer service is not significant (β = -0.004, p>0.1); (2)mechanism analysis shows that the reform can reduce the probability of migration for work, and thus enhance the level of public participation; (3)heterogeneity analysis reveals that the reform has a greater impact on the villagers’ public participation in suburban villages and villages with better collective economy; (4)further analysis discovers that villagers have heard that reform can significantly enhance their public participation. This study comprehensively explores the spillover effects of the reform at the village level on public participation at the individual level through the use of more accurate measurement indicators, empirical analysis methods, and large-scale authoritative data, providing strong support for proposing strategies to promote villages’ public participation.

Quality of orthodontic care in an academic setting in the Middle East

Examining Mammalian facial behavior using Facial Action Coding Systems (FACS) and combinatorics

There has been an increased interest in standardized approaches to coding facial movement in mammals. Such approaches include Facial Action Coding Systems (FACS), where individuals are trained to identify discrete facial muscle movements that combine to create a facial configuration. Some studies have utilized FACS to analyze facial signaling, recording the quantity of morphologically distinct facial signals a species can generate. However, it is unclear whether these numbers represent the total number of facial muscle movement combinations (which we refer to as facial configurations) that each species is capable of producing. If unobserved combinations of facial muscle movements are communicative in nature, it is crucial to identify them, as this information is important for testing research hypotheses related to the evolution of complex communication among mammals. Our study aimed to assess how well the existing literature represents the potential range of facial signals in two previously studied species: chimpanzees (Pan troglodytes) and domesticated cats (Felis silvestris catus). We adhered to the coding guidelines outlined in the FACS manuals, which are based on the anatomical constraints and capabilities of each mammal’s face, to create our comprehensive list of all potential facial configurations. Using this approach, we found that chimpanzees and domesticated cats may be capable of producing thousands of facial configurations, many of which have not yet been documented in the existing research literature. It is plausible that some of these facial configurations are communicative and could be discovered with further research and video recording. In addition to our findings having significant implications for future research on the communicative complexity of mammals, it can also assist researchers in evaluating FACS coding accuracy.

Efficient anomaly detection in tabular cybersecurity data using large language models

Assessment of health behaviors of primary school teachers based on their nutritional knowledge and physical activity: A cross-sectional study in the Asir Region

Background Primary school teachers play a critical role as educators in imparting healthy eating behaviour and the importance of physical activity to prevent health issues. However, the teachers’ health behaviors have not been studied much, particularly in Saudi Arabia. Understanding these factors is essential to developing interventions that enhance teachers’ well-being and their ability to influence students positively. This study aims to assess nutritional knowledge and physical activity; to determine correlations between health behaviour factors and Body Mass Index (BMI), and evaluate BMI status concerning demographic factors among primary school teachers in the Asir Region, KSA. Methods A cross-sectional design was employed, involving 370 primary school teachers. Data were collected using a self-administered questionnaire that covered sociodemographic details, anthropometric measurements, physical activity levels, and nutritional knowledge. Statistical analyses included Pearson’s correlation and Chi-square tests, with significance at p < 0.05. Results Among the participants, 38.6% were overweight, and 33.5% were obese, with 76% of married teachers classified as overweight or obese. Only 9.0% exhibited excellent nutritional knowledge, while 25.0% demonstrated poor knowledge. The majority (84.0%) engaged in low or minimal physical activity. A weak but significant correlation was observed between nutritional knowledge and BMI (p < 0.05), whereas no significant associations were found between physical activity levels and either BMI or nutritional knowledge. Conclusion The study highlights critical gaps in nutritional knowledge and physical activity among teachers, emphasizing the need for targeted school-based health education programs. Improving teacher health behaviors could enhance their well-being and enable them to act as positive role models for their students.

High-performance triboelectric nanogenerators based on Ag-doped ZnO loaded electrospun PVDF nanofiber mats for energy harvesting and healthcare monitoring

Abstract This study investigates the potential of zinc oxide (ZnO) and Ag-doped zinc oxide (Ag-ZnO) nanoparticles (NPs) (1, 3 and 5 wt%) electrospun into poly(vinylidene fluoride) (PVDF) based triboelectric nanogenerators (TENGs) to harness electrical energy from ambient mechanical vibrations. ZnO and Ag-ZnO NPs were developed using a co-precipitation method. 3 wt% Ag-ZnO doping was optimized to exhibit a higher β-crystalline phase in PVDF (PAZ3). The electrospun ZnO and Ag-ZnO loaded PVDF nanofiber mats (NFMs) served as tribo-negative layer, while thermoplastic polyurethane (TPU) served as tribo-positive layer in the TENG device fabrication. The electrical measurement results revealed that pristine PVDF/TPU-based TENG device exhibited lower performance (V oc = 9.0 V and I sc = 0.6 µA) compared to the optimized PAZ3/TPU-based TENG (V oc = 51 V and I sc = 1.2 µA), and utilized for concurrent applications such as powering over 10 light-emitting diodes, energy harvesting and healthcare monitoring applications. Overall, the study not only reveals the significant potential of PAZ3/TPU-based TENG for excellent output performance, but also provides a new insight into next-generation clean, affordable and sustainable energy harvesting materials.

Low-power artificial neuron networks with enhanced synaptic functionality using dual transistor and dual memristor

Artificial neurons with bio-inspired firing patterns have the potential to significantly improve the performance of neural network computing. The most significant component of an artificial neuron circuit is a large amount of energy consumption. Recent literature has proposed memristors as a promising option for synaptic implementation. In contrast, implementing memristive circuitry through neuron hardware presents significant challenges and is a relevant research topic. This paper describes an efficient circuit-level mixed CMOS memristor artificial neuron network with a memristor synapse model. From this perspective, the paper describes the design of artificial neurons in standard CMOS technology with low power utilization. The neuron circuit response is a modified version of the Morris-Lecar theoretical model. The suggested circuit employs memristor-based artificial neurons with Dual Transistor and Dual Memristor (DTDM) synapse circuit. The proposed neuron network produces a high spiking frequency and low power consumption. According to our research, a memristor-based Morris Lecar (ML) neuron with a DTDM synapse circuit consumes 12.55 pW of power, the spiking frequency is 22.72 kHz, and 2.13 fJ of energy per spike. The simulations were carried out using the Spectre tool with 45 nm CMOS technology.

Advances and prospects of cell-penetrating peptides in tumor immunotherapy

Predicting real-world navigation performance from a virtual navigation task in older adults

Virtual reality environments presented on tablets and smartphones offer a novel way of measuring navigation skill and predicting real-world navigation problems. The extent to which such virtual tests are effective at predicting navigation in older populations remains unclear. We compared the performance of 20 older participants (54–74 years old) in wayfinding tasks in a real-world environment in London, UK, and in similar tasks designed in a mobile app-based test of navigation (Sea Hero Quest). In a previous study with young participants (18–35 years old), we were able to predict navigation performance in real-world tasks in London and Paris using this mobile app. We find that for the older cohort, virtual navigation performance predicts real-world performance for medium difficulty, but not for the easy or difficult environments. Overall, our study supports the utility of using digital tests of spatial cognition in older age groups, while carefully adapting the task difficulty to the population.

HER2 expression and pathway status in male breast cancer patients: results of an integrated analysis among 6,150 patients

Abstract The role of human epidermal growth factor 2 (HER2) in male breast cancer (MBC) is poorly defined. A comprehensive description of HER2 status was conducted. A total of 6,015 MBC patients from 45 studies and 135 MBC patients with sequencing data were identified. HER2 positive rates and hazard ratios (HR) for overall survival (OS) were combined using Metaprop. The prevalence of HER2 + MBC was 10.0% (95% CI: 8.0-13.0%). Subgroup analyses showed that 7% (95% CI: 2.0-14.0%) had HER2 + protein overexpression. 10% of MBC patients had HER2 + overexpression and/or gene amplification. Asian MBC patients had the highest HER2 + incidence of 17% (95% CI: 12.0-22.0%). The prevalence of HER2 positive MBC fluctuated widely from 2001 to 2015 and then stabilized at 10%. HER2 positivity was significantly correlated with worse OS than negative ones (HR = 1.92, 1.47–2.51). The proportion of HER2 + MBC was inconsistent with the results for the intrinsic HER2-enriched subtype. Altered genes in HER2 + MBC, such as ERBB2, AGO2, RECQL4, and CLTC, were not detected in HER2-MBC. Genomic analysis revealed differences between the patients with HER2 + MBC and those with HER2 + FBC. The percentage of HER2 + MBC was slightly lower than that of women. Multiple approaches may be needed to jointly assess HER2 status in MBC.

The evolution of ASEAN’s language policies: A diachronic analysis of official documents and website

Language policy plays a pivotal role in sustaining language behaviors and transforming language ideologies into practices. While the analysis of language policies in international organizations has received increasing attention, the evolution of language policies in the Association of Southeast Asian Nations (ASEAN) has been understudied. Existing research on ASEAN’s language policies has concentrated on its official language, often overlooking the language practices and ideologies embedded within these policies. This study seeks to investigate the evolution of ASEAN’s language policy by examining its official documents and website. We employed the Wayback Machine to trace the development of the ASEAN official website and adopted a corpus-based approach, utilizing tools such as AntConc and Sketch Engine, to analyze the Chairman’s Statements of the ASEAN Summit (CSAS). The study reveals three key insights: 1) The evolution of the ASEAN official website can be categorized into three distinct stages. 2) A consistent use of the collective pronoun “we” in the statements highlights the emphasis on cooperation and progress across economic and political-security domains. 3) The ASEAN community has persistently upheld its values, fostering an ASEAN identity and a genuine ASEAN community throughout its development. This diachronic analysis clarifies the characteristics of ASEAN’s language policy, deepening our understanding of the intricate relationship between language practices and ideology, and their implications for regional cooperation and integration.

Strengthening biopolymer adhesives through ureolysis-induced calcium carbonate precipitation

Abstract Common adhesives for nonstructural applications are manufactured using petrochemicals and synthetic solvents. These adhesives are associated with environmental and health concerns because of their release of volatile organic compounds (VOCs). Biopolymer adhesives are an attractive alternative because of lower VOC emissions, but their strength is often insufficient. Existing mineral fillers can improve the strength of biopolymer adhesives but require the use of crosslinkers that lower process sustainability. This work introduces a novel approach to strengthen biopolymer adhesives through calcium carbonate biomineralization, which avoids the need for crosslinkers. Biomineral fillers produced by either microbially or enzymatically induced calcium carbonate precipitation (MICP and EICP, respectively) were precipitated within guar gum and soy protein biopolymers. Both, MICP and EICP, increased the strength of the biopolymer adhesives. The strength was further improved by optimizing the concentrations of bacteria, urease enzyme, and calcium. The highest strengths achieved were on par with current commercially available nonstructural adhesives. This study demonstrates the feasibility of using calcium carbonate biomineralization to improve the properties of biopolymer adhesives, which increases their potential viability as more sustainable adhesives.

Genome-wide analysis and characterization of TPD1 family proteins in pearl millet (Cenchrus americanus): Insights into reproductive regulation and phytohormone responses

The Tapetum Determinant 1 (TPD1) family proteins are known to play a crucial role in the regulation of reproduction in plants, including Cenchrus americanus (pearl millet). However, members of TPD1 family proteins have not been fully identified. The current study aims to identify and characterize the TPD1 family proteins in Cenchrus americanus (L.) Morrone. Seven transmembrane proteins (from 127 to 172 aa) comprising TPD1 domain were identified via genome-wide mining. Analysis of gene expression during developmental stages revealed high expression of four CaTPD1s in reproductive organs. Treatment with phytohormones showed that the expression of CaTPD1s was repressed by hormone treatments except CaTPD1_Ch4.1 and CaTPD1_Ch4.3 which are highly expressed in response to brassinolide and auxin, respectively. Screening of cis-elements in the promoter of CaTPD1s revealed various cis-elements related to phytohormone regulation, wound response, abiotic stress defense, and light response. The phylogenetic tree revealed distinct clustering of CaTPD1_Ch6 and CaTPD1_Ch5 among the other CaTPD1s, which revealed close relationships with the orthologs from Arabidopsis and rice that are known to have a critical role in tapetum development and pollen and ovule production. Hence, this study affirms the role of the CaTPD1s genes in the growth and reproduction during pearl millet developmental stages.