A comprehensive study of the interactions of human serum albumin (HSA) and α-1-acid glycoprotein (AAG) with two isoquinoline alkaloids, i.e., allocryptopine (ACP) and protopine (PP), was performed. The UV-Vis spectroscopy, molecular docking, competitive binding assays, and circular dichroism (CD) spectroscopy were used for the investigations. The results showed that ACP and PP form spontaneous and stable complexes with HSA and AAG, with ACP displaying a stronger affinity towards both proteins. Molecular docking studies revealed the preferential binding of ACP and PP to specific sites within HSA, with site 2 (IIIA) being identified as the favored location for both alkaloids. This was supported by competitive binding assays using markers specific to HSA’s drug binding sites. Similarly, for AAG, a decrease in fluorescence intensity upon addition of the alkaloids to AAG/quinaldine red (QR) complexes indicated the replacement of the marker by the alkaloids, with ACP showing a greater extent of replacement than PP. CD spectroscopy showed that the proteins’ structures remained largely unchanged, suggesting that the formation of complexes did not significantly perturb the overall spatial configuration of these macromolecules. These findings are crucial for advancing the knowledge on the natural product–protein interactions and the future design of isoquinoline alkaloid-based therapeutics. Full article

Forest fires often pose serious hazards, and the timely monitoring and extinguishing of residual forest fires using unmanned aerial vehicles (UAVs) can prevent re-ignition and mitigate the damage caused. Due to the urgency of forest fires, drones need to respond quickly during firefighting operations, while traditional drone formation deployment requires a significant amount of time. This paper proposes a pure azimuth passive positioning strategy for circular UAV formations and utilizes the Deep Q-Network (DQN) algorithm to effectively adjust the formation within a short timeframe. Initially, a passive positioning model for UAVs based on the relationships between the sides and angles of a triangle is established, with the closest point to the ideal position being selected as the position for the UAV to be located. Subsequently, a multi-target optimization model is developed, considering 10 UAVs as an example, with the objective of minimizing the number of adjustments while minimizing the deviation between the ideal and adjusted UAV positions. The DQN algorithm is employed to solve and design experiments for validation, demonstrating that the deviation between the UAV positions and the ideal positions, as well as the number of adjustments, are within acceptable ranges. In comparison to genetic algorithms, it saves approximately 120 s. Full article

Thrombotic disease has been listed as the third most fatal vascular disease in the world. After decades of development, clinical thrombolytic drugs still cannot avoid the occurrence of adverse reactions such as bleeding. A number of studies have shown that the application of various nano-functional materials in thrombus-targeted drug delivery, combined with external stimuli, such as magnetic, near-infrared light, ultrasound, etc., enrich the drugs in the thrombus site and use the properties of nano-functional materials for collaborative thrombolysis, which can effectively reduce adverse reactions such as bleeding and improve thrombolysis efficiency. In this paper, the research progress of organic nanomaterials, inorganic nanomaterials, and biomimetic nanomaterials for drug delivery is briefly reviewed. Full article

During recent decades there has been an increase in extreme flood events and their intensity in most regions, mainly driven by climate change. Furthermore, these critical events are expected to intensify in the future. Therefore, the improvement of preparedness, mitigation, and adaptation counterparts is mandatory. Many scientific fields are involved in this task, but from a meteorological and hydrological perspective, one of the main tools that can contribute to mitigating the impact of floods is the development of Early Warning Systems. In this sense, this paper presents a scientific literature review of some of the most representative Flood Early Warning Systems worldwide, many of which are currently fully operational, with a special focus on the numerical modeling component when it is developed and integrated into the system. Thus, from basic to technically complex, and from basin or regional to continental or global scales of application, these systems have been reviewed. In this sense, a brief description of their main features, operational procedures, and implemented numerical models is also depicted. Additionally, a series of indications regarding the key aspects of the newly developed FEWSs, based on recent trends and advancements in FEWSs development found in the literature, are also summarized. Thus, this work aims to provide a literature review useful to scientists and engineers involved in flood analysis to improve and develop supporting tools to assist in the implementation of mitigation measures to reduce flood damage for people, goods, and ecosystems and to improve the community resilience. Full article

Sea surface salinity (SSS) variability at mesoscales has become an important research topic in recent decades, thanks to satellite missions enabling observations of SSS with global capacity and mesoscale resolution. Here, we analyze the near-global data of the Aquarius/SAC-D along-track SSS, focusing on the slopes of SSS variance spectra in the mesoscale range from 180 to 430 km. In the vast extratropics, the spectral slope is close to −2, indicating a dynamical regime for the inverse cascade of depth-integrated energy identified by the surface quasi-geostrophic theory. However, the spectral slopes in regions near the mouths of the largest rivers are steeper than −2, reaching −3, possibly due to the large river freshwater flux. In addition, data from high-resolution thermosalinograph are used to validate satellite measurements and show good consistency in terms of SSS variance spectral slopes. Full article

Additive manufacturing enables the production of lattice structures, which have been proven to be a superior class of lightweight mechanical metamaterials whose specific stiffness can reach the theoretical limit of the upper Hashin–Shtrikman bound for isotropic cellular materials. To achieve isotropy, complex structures are required, which can be challenging in powder bed additive manufacturing, especially with regard to subsequent powder removal. The present study focuses on the Finite Element Method simulation of 2,5D anisotropic plate lattice metamaterials and the investigation of their lightweight potential. The intentional use of anisotropic structures allows the production of a cell architecture that is easily manufacturable via Laser Powder Bed Fusion (LPBF) while also enabling straightforward optimization for specific load cases. The work demonstrates that the considered anisotropic plate lattices exhibit high weight-specific stiffnesses, superior to those of honeycomb structures, and, simultaneously, a good de-powdering capability. A significant increase in stiffness and the associated surpassing of the upper Hashin–Shtrikman bound due to anisotropy is achievable by optimizing wall thicknesses depending on specific load cases. A stability analysis reveals that, in all lattice structures, plastic deformation is initiated before linear buckling occurs. An analysis of stress concentrations indicates that the introduction of radii at the plate intersections reduces stress peaks and simultaneously increases the weight-specific stiffnesses and thus the lightweight potential. Exemplary samples illustrate the feasibility of manufacturing the analyzed metamaterials within the LPBF process. Full article

To address the challenges in processing and identifying mine acoustic emission signals, as well as the inefficiency and inaccuracy issues prevalent in existing methods, an enhanced CELMD approach is adopted for preprocessing the acoustic emission signals. This method leverages correlation coefficient filtering to extract the primary components, followed by classification and recognition using the Swin Transformer neural network. The results demonstrate that the improved CELMD method effectively extracts the main features of the acoustic emission signals with higher decomposition accuracy and reduced occurrences of mode mixing and end effects. Furthermore, the Swin Transformer neural network exhibits outstanding performance in classifying acoustic emission signals, surpassing both convolutional neural networks and ViT neural networks in terms of accuracy and convergence speed. Moreover, utilizing preprocessed data from the improved CELMD enhances the performance of the Swin Transformer neural network. With an increase in data volume, the accuracy, stability, and convergence speed of the Swin Transformer neural network continuously improve, and using preprocessed data from the enhanced CELMD yields superior training results compared to those obtained without preprocessing. Full article

Vasa previa is a pregnancy complication that occurs when unprotected fetal blood vessels traverse the cervical os, placing the fetus at high risk of exsanguination and fetal death. These fetal vessels may be compromised by fetal movement and compression, leading to poor oxygen distribution and asphyxiation. Diagnostic tools for vasa previa management and preterm labor (PTL) include transvaginal ultrasound, cervical length (CL) surveillance and use of fetal fibronectin (FFN) testing. These tools can prove to be quite useful as they allow for lead time in the prediction of PTL and spontaneous rupture of membranes which can result in devastating outcomes for pregnancies affected by vasa previa. We conducted a literature review on vasa previa management and the usefulness of FFN and CL surveillance in predicting PTL and found 36 related papers. Although there is limited research available to show the impact of FFN and CL surveillance in the management of vasa previa, there is sufficient evidence to support FFN and CL surveillance in predicting the onset of PTL, which can have devastating consequences for the pregnancies affected. It can be extrapolated that these tools, by helping to determine pregnancies at risk for PTL, could improve management and outcomes in patients with vasa previa. Future studies investigating the management of vasa previa with FFN and CL surveillance to reduce the burden of PTL and its associated comorbidities are warranted. Full article

Chitosan-triphosphate (TPP) nanogels are widely studied drug delivery carrier systems, typically prepared via a simple mixing process. However, the effects of the processing factors on nanogel production have not been extensively explored, despite the importance of understanding and standardising such factors to allow upscaling and commercial usage. This study aims to systematically evaluate the effects of various fabrication and processing factors on the properties of nanogels using a Design of Experiment approach. Hydrodynamic size, polydispersity index (PDI), zeta potential, and encapsulation efficiency were determined as the dependent factors. The temperature, stirring rate, chitosan grade, crosslinker choice, and the interaction term between temperature and chitosan grade were found to have a significant effect on the particle size, whereas the effect of temperature and the addition rate of crosslinker on the PDI was also noteworthy. Moreover, the addition rate of the crosslinker and the volume of the reaction vessel were found to impact the encapsulation efficiency. The zeta potential of the nanogels was found to be governed by the chitosan grade. The optimal fabrication conditions for the development of medium molecular weight chitosan and TPP nanogels included the following: the addition rate for TPP solution was set at 2 mL/min, while the solution was then stirred at a temperature of 50 °C and a stirring speed of 600 rpm. The volume of the glass vial used was 28 mL, while the stirrer size was 20 mm. The second aim of the study was to evaluate the potential for scaling up the nanogels. Size and PDI were found to increase from 128 nm to 151 nm and from 0.232 to 0.267, respectively, when the volume of the reaction mixture was increased from 4 to 20 mL and other processing factors were kept unchanged. These results indicate that caution is required when scaling up as the nanogel properties may be significantly altered with an increasing production scale. Full article

Enamel microcracks (EMCs) arising during the removal of metal orthodontic brackets represent a considerable challenge in dentistry. This in vitro study aims to explore the impacts of thermocycling, the types of orthodontic bonding agent, and curing techniques on the enamel surface of the tooth structure following the debonding of orthodontic metal brackets. It also examines the incidence, number, length, and direction of EMCs on the buccal surface of the tooth. Additionally, the study compares adhesive remnant index (ARI) scores and bracket failure post-debonding. Forty extracted human maxillary canines were divided into ten groups, including intact enamel negative controls (groups 1, 2) and groups (3–8) with metal brackets bonded using two different bonding agents and curing techniques. Following bonding, half of the groups underwent thermocycling testing. EMCs, ARI scores, and bracket failure modes were evaluated. The formation, length, and direction of cracks did not significantly differ among groups, regardless of experimental conditions. Thermocycling had no significant effect on ARI scores or bracket failure modes. However, significant variations were observed among curing technique groups, with seventh-generation bonding agents demonstrating potential effectiveness in achieving complete adhesive removal. The study underscores the importance of considering bonding agent systems and curing protocols to optimize bond outcomes and minimize the risk of metal bracket failure in orthodontic treatment. Full article

Robotic manipulators play a pivotal role in modern intelligent manufacturing and unmanned production systems, often tasked with executing specific paths accurately. However, the input of the robotic manipulators is trajectory which is a path with time information. The resulting core technology is trajectory planning methods which are broadly classified into two categories: maximum velocity curve (MVC) methods and multiphase direct collocation (MPDC) methods. This paper concentrates on addressing challenges associated with the latter methods. In MPDC methods, the solving efficiency and accuracy are greatly influenced by the number of discretization nodes. When dealing with systems with complex dynamics, such as robotic manipulators, striking a balance between solving time and path discretization errors becomes crucial. We use a mesh refinement (MR) algorithm to find a suitable number of nodes under the premise of ensuring the path discretization error. So, the actual device can effectively implement the planned solutions. Nonetheless, the conventional application of the MR algorithm requires solving the original problem in each iteration; these processes are extremely time-consuming and may fail to solve when dealing with a complex dynamic system. As a result, we propose a sequential optimal trajectory planning scheme to solve the problem efficiently by dividing the original optimal control (OC) problem into two stages: path planning (PP) and trajectory planning (TP). In the PP stage, we employ a DC method based on arc length and an MR algorithm to identify key nodes along the specified path. This aims to minimize the approximation error introduced during discretization. In the TP stage, the identified key nodes serve as boundary conditions for an MPDC method based on time. This facilitates the generation of an optimal trajectory that maximizes motion performance, considering constant velocity in Cartesian space and dynamic constraints while keeping the path discretization error. Simulation and experiment are conducted with a six-axis robotic manipulator, ROCR6, and show significant potential for a wide range of applications in robotics. Full article

The application of non-uniform spiral gratings to control the structure, topological parameters and propagation of orbital angular momentum (OAM) beams was studied experimentally with coherent near-infrared light. Adapted digital spiral grating structures were programmed into the phase map of a high-resolution liquid-crystal-on-silicon spatial light modulator (LCoS-SLM). It is shown that characteristic spatio-spectral anomalies related to Gouy phase shift can be used as pointers to quantify rotational beam properties. Depending on the sign and gradient of spatially variable periods of chirped spiral gratings (CSGs), variations in rotation angle and angular velocity were measured as a function of the propagation distance. Propagation-dependent self-torque is introduced in analogy to known local self-torque phenomena of OAM beams as obtained by the superposition of temporally chirped or phase-modulated wavepackets. Applications in metrology, nonlinear optics or particle trapping are conceivable. Full article

RNA-binding proteins and chemical modifications to RNA play vital roles in the co- and post-transcriptional regulation of genes. In order to fully decipher their biological roles, it is an essential task to catalogue their precise target locations along with their preferred contexts and sequence-based determinants. Recently, deep learning approaches have significantly advanced in this field. These methods can predict the presence or absence of modification at specific genomic regions based on diverse features, particularly sequence and secondary structure, allowing us to decipher the highly non-linear sequence patterns and structures that underlie site preferences. This article provides an overview of how deep learning is being applied to this area, with a particular focus on the problem of mRNA-RBP binding, while also considering other types of chemical modification to RNA. It discusses how different types of model can handle sequence-based and/or secondary-structure-based inputs, the process of model training, including choice of negative regions and separating sets for testing and training, and offers recommendations for developing biologically relevant models. Finally, it highlights four key areas that are crucial for advancing the field. Full article

The process of multifactorial oak disease has been of interest to scientists from all over the world for many years. Recently, a new phenomenon has been added to the model related to oak decline, acute oak dieback, which causes oak decline and was first described in the UK. This study presents research on this phenomenon in the area of the largest oak stand complex in Poland, the so-called Krotoszyn Plateau. This work was carried out in two stages. In the first stage, 54 trees were tested for the presence of bacteria using molecular biology (real-time PCR). Subsequently, a tissue fragment was taken for inoculation from the trees in which the presence of B. goodwinii and G. quercinecans bacteria was confirmed. The isolates obtained were used to test Koch’s postulates and for biochemical analyses for Polish strains. In addition, the results obtained were also compared with the presence of A. biguttatus, which is considered a bacterial vector, which, in turn, confirmed that the bacteria responsible for the AOD phenomenon can also be present in trees not inhabited by this insect. The results obtained confirmed the presence of bacteria and their potential to cause necrosis in oaks, which fits into the model of the spiral disease that has been causing mass mortality of oaks in this naturally and economically valuable area since the 1980s. Full article

The objective was to evaluate the effects of good handling practices on dairy calf welfare. Forty-eight crossbred dairy calves were assigned to two treatments: conventional handling (CH): calves kept in individual pens, fed milk replacer in buckets without nipples and abruptly weaned; or good handling practices (GHP): calves kept in group pens, fed milk replacer in buckets with nipples, given daily tactile stimulation during feeding, and progressive weaning. Calf welfare was assessed from birth to 120 days of age, based on: health (plasma concentrations of glucose and IgG, and occurrences of diarrhea, pneumonia, tick-borne disease, or death); physiology (heart rate [HR], respiratory rate [RR], and rectal temperature [RT]); behavior (flight distance [FD], latencies for first movement [LM] and to hold the calf in a pen corner [LH], and total time a calf allowed touching [TTT]); and performance indicators (body weight, average daily gain, and weaning success at 70 days of age). Calves in the GHP treatment had a lower HR at 30 days of age, shorter FD and LH, longer TTT, and lower RR and RT than CH (p < 0.05). However, health, deaths and performance indicators did not differ (p > 0.05) between treatments. Based on various indicators, GHP improved dairy calf welfare. Full article

This research focuses on the rational design of porous enzymatic electrodes, using horseradish peroxidase (HRP) as a model biocatalyst. Our goal was to identify the main obstacles to maximizing biocatalyst utilization within complex porous structures and to assess the impact of various carbon nanomaterials on electrode performance. We evaluated as-synthesized carbon nanomaterials, such as Carbon Aerogel, Coral Carbon, and Carbon Hollow Spheres, against the commercially available Vulcan XC72 carbon nanomaterial. The 3D electrodes were constructed using gelatin as a binder, which was cross-linked with glutaraldehyde. The bioelectrodes were characterized electrochemically in the absence and presence of 3 mM of hydrogen peroxide. The capacitive behavior observed was in accordance with the BET surface area of the materials under study. The catalytic activity towards hydrogen peroxide reduction was partially linked to the capacitive behavior trend in the absence of hydrogen peroxide. Notably, the Coral Carbon electrode demonstrated large capacitive currents but low catalytic currents, an exception to the observed trend. Microscopic analysis of the electrodes indicated suboptimal gelatin distribution in the Coral Carbon electrode. This study also highlighted the challenges in transferring the preparation procedure from one carbon nanomaterial to another, emphasizing the importance of binder quantity, which appears to depend on particle size and quantity and warrants further studies. Under conditions of the present study, Vulcan XC72 with a catalytic current of ca. 300 µA cm⁻² in the presence of 3 mM of hydrogen peroxide was found to be the most optimal biocatalyst support. Full article

Although cellular senescence was originally defined as an irreversible form of cell cycle arrest, in therapy-induced senescence models, the emergence of proliferative senescence-escaped cancer cells has been reported by several groups, challenging the definition of senescence. Indeed, senescence-escaped cancer cells may contribute to resistance to cancer treatment. Here, to study senescence escape and isolate senescence-escaped cells, we developed novel flow cytometry-based methods using the proliferation marker Ki-67 and CellTrace CFSE live-staining. We investigated the role of a novel senescence marker (DPP4/CD26) and a senolytic drug (azithromycin) on the senescence-escaping ability of MCF-7 and MDA-MB-231 breast cancer cells. Our results show that the expression of DPP4/CD26 is significantly increased in both senescent MCF-7 and MDA-MB-231 cells. While not essential for senescence induction, DPP4/CD26 contributed to promoting senescence escape in MCF-7 cells but not in MDA-MB-231 cells. Our results also confirmed the potential senolytic effect of azithromycin in senescent cancer cells. Importantly, the combination of azithromycin and a DPP4 inhibitor (sitagliptin) demonstrated a synergistic effect in senescent MCF-7 cells and reduced the number of senescence-escaped cells. Although further research is needed, our results and novel methods could contribute to the investigation of the mechanisms of senescence escape and the identification of potential therapeutic targets. Indeed, DPP4/CD26 could be a promising marker and a novel target to potentially decrease senescence escape in cancer. Full article

Aging is characterized by the progressive degeneration of bodily tissues and decline in physiological functions, a process that may be exacerbated by imbalances in intestinal flora. Soluble dietary fiber (PSDF) from Citrus unshiu peel has demonstrated strong free radical scavenging ability to regulate intestinal flora in vitro. However, further evidence is required to ascertain the effectiveness of PSDF in vivo. In our study, 8-week-old mice were artificially aged through subcutaneous injections of a 200 mg/kg/d D-galactose solution for 42 days, followed by a 28-day dietary intervention with varying doses of PSDF, insoluble dietary fiber (PIDF), and vitamin C. After the intervention, we observed a significant mitigation of D-galactose-induced oxidative stress, as evident by weight normalization and reduced oxidative damage. 16S rRNA gene sequencing revealed that PSDF significantly altered the composition of intestinal flora, increasing Firmicutes and reducing Bacteroidota percentages, while also enriching colonic short-chain fatty acids (SCFAs). Spearman correlation analysis further identified a positive correlation between Firmicutes and isovaleric acid, and negative correlations between Muribaculaceae and acetic acid, and between Lachnospiraceae_NK4A136_group and caproic acid. These findings support the potential of Citrus PSDF to alleviate oxidative stress. Full article

Streptococcus pyogenes, group A streptococci (GAS) bacteriaemia, is a life-threatening infection with high mortality, requiring fast diagnosis together with the use of appropriate antibiotic therapy as soon as possible. Our study analysed data from 93 patients with GAS bacteraemia at the General University Hospital in Prague between January 2006 and March 2024. In the years 2016–2019 there was an increase in GAS bacteraemia. Mortality in the period 2006–2019 was 21.9%; in the period 2020–2024, the mortality increased to 41.4%, p = 0.08. At the same time, in the post-2020 period, the time from hospital admission to death was reduced from 9.5 days to 3 days. A significant predictor of worse outcome in this period was high levels of procalcitonin, >35.1 µg/L (100% sensitivity and 82.35% specificity), and lactate, >5 mmol/L (90.91% sensitivity and 91.67% specificity). Myoglobin was a significant predictor in both compared periods, the AUC was 0.771, p = 0.044, and the AUC was an even 0.889, p ≤ 0.001, respectively. All isolates of S. pyogenes were susceptible to penicillin, and resistance to clindamycin was 20.3% from 2006–2019 and 10.3% in 2020–2024. Appropriate therapy was initiated in 89.1%. and 96.6%, respectively. We hypothesise that the increase in mortality after 2020 might be due to a decrease in the immune status of the population. Full article

Pradofloxacin is the newest of the veterinary fluoroquinolones to be approved for use in animals—initially companion animals and most recently food animals. It has a broad spectrum of in vitro activity, working actively against Gram-positive/negative, atypical and some anaerobic microorganisms. It simultaneously targets DNA gyrase (topoisomerase type II) and topoisomerase type IV, suggesting a lower propensity to select for antimicrobial resistance. The purpose of this study was to determine the rate and extent of bacterial killing by pradofloxacin against bovine strains of Mannheimia haemolytica and Pasteurella multocida, in comparison with several other agents (ceftiofur, enrofloxacin, florfenicol, marbofloxacin, tildipirosin, tilmicosin and tulathromycin) using four clinically relevant drug concentrations: minimum inhibitory and mutant prevention drug concentration, maximum serum and maximum tissue drug concentrations. At the maximum serum and tissue drug concentrations, pradofloxacin killed 99.99% of M. haemolytica cells following 5 min of drug exposure (versus growth to 76% kill rate for the other agents) and 94.-1−98.6% of P. multocida following 60−120 min of drug exposure (versus growth to 98.6% kill rate for the other agents). Statistically significant differences in kill rates were seen between the various drugs tested depending on drug concentration and time of sampling after drug exposure. Full article

Waste-to-energy (WtE) incineration is a feasible way to respond to both the municipal solid waste management and renewable energy challenges, but few studies have been carried out on its environmental and economic impact in fast-developing southeastern Asian countries. To fill such a research gap, this study innovatively conducted a holistic assessment of WtE incineration application potential in Java Island, Indonesia. Here, we have established a life cycle assessment model for WtE incineration in Java, and have estimated the environmental impact, electricity generation potential, and techno-economic feasibility of implementing incineration by 2025. We have revealed that global warming potential, terrestrial ecotoxicity potential, eutrophication potential, and acidification potential are the major environmental impacts stemming from incineration activities. Moreover, we have estimated that promoting incineration in Java could reduce CO₂ emissions by 41% on average. The electricity generated from incineration could contribute to 3.72% of Indonesia’s renewable energy target for the electricity grid mix by 2025. The cumulative energy production potential from incineration is estimated to reach 2,316,523 MWh/year in 2025 and will increase by 14.3% in 2050. The techno-economic assessment of incineration implementation in Java cities has been enumerated as feasible. The levelized cost of electricity from incineration (0.044 USD/kWh) is competitive with the current Indonesian electricity price (0.069 USD/kWh). Policies of minimizing incineration pollution, providing financial support guarantees, and overcoming social barriers have been proposed to facilitate the application of WtE incineration. Full article

The heat transfer enhancement and hydrodynamic characteristics of nanofluid use in a micro heat exchanger is investigated for cooling electronic components working in hot climatic conditions. The cooling fluid employed was water and TiO₂ nanoparticles at mass concentrations of 1% and 5%, the Reynolds numbers ranged from 400 to 2000, and the inlet temperatures ranged between 35 °C and 65 °C. At a nanofluid inlet temperature of 55 °C and a nanoparticle concentration of 1%, the Nusselt number increased by 23% up to 54% as the Reynolds number varied between 400 and 2000. At a nanoparticle concentration of 5%, the percentages that correspondingly enhanced the Nusselt number were 32% and 63%. The temperature of the electronic heating component decreased by 4.6–5.2 °C when the nanofluid concentration was increased from 0 to 5% at a Reynolds number of 400 and a nanofluid inlet temperature of 35 °C. Small increments in the pressure drop of about 6% and 13% were observed at nanofluid concentrations of 1% and 5%, respectively. With nanoparticle concentrations of 1% and 5%, a Reynolds number of 2000, and a nanofluid inlet temperature of 35 °C, performance evaluation criterion (PEC) values of 1.36 and 1.45 were obtained. When the nanofluid inlet temperature increased to 65 °C, the PEC parameter decreased to 1.02–1.10 for both concentrations. Full article