Application Of System Research Articles

Synthesis and in vitro study of biodegradable and thermoresponsive polymer based on polysuccinimide for drug delivery

Hydrogels, defined as polymer networks with a high water content and insoluble in water, have emerged as pivotal materials in biomedical research due to their resemblance to the natural extracellular matrix. The aim of this study is to develop an injectable, thermoresponsive, and biodegradable hydrogel. The hydrogel (PSI-t) was derived from poly (aspartic acid) (PSI) by grafting hydrophobic dodecylamine (DA) and hydrophilic ethanolamine (EA) groups onto its backbone. PSI-t was found to exhibit a unique sol state at room temperature, which facilitates facile injection, and undergoes rapid gelation at physiological temperatures, highlighting its potential as an injectable thermosensitive hydrogel for targeted drug delivery. In vitro tests confirmed the biocompatibility of the thermosensitive hydrogel, and sustained drug release studies using the model drug, acetaminophen (AP), underscored the efficacy of the hydrogel as a controlled release vehicle. Furthermore, the hydrogel was found to be easily eliminated through bio-hydrolysis, thus enabling prolonged drug effects while mitigating any potential toxicity. These findings suggest that PSI-t is a promising candidate for an innovative and injectable drug delivery system in biomedical applications.

Thermo-elastic vibration analysis and optimization of a nanoresonator composed of a coupled nanotube system for acoustic liner application using the hybrid deep neural network–based white shark algorithm

This study explores the potential of nanoresonator systems composed of coupled nanotubes with graphene nanoparticles for enhancing the performance of acoustic liners in aircraft engines. The objective of this study is to develop an analytical model and predict its behavior under various conditions. The acoustic liners consist of perforated metal sheets and honeycomb cavities, which are essential for noise reduction in aircraft engines. The model is tested for variations in natural frequency, mode number (m), size effects (e0a), viscous constant (C), temperature (T), localness factor (L), and stiffness constant (K). A hybrid deep neural network–based white shark algorithm (DNN-WSA) is used to predict and optimize the performance of nanoresonator-coupled nanotube systems. Four theories were compared, such as wave propagation theory, nonlocal elasticity theory, polynomial eigenvalue approach, and governing equations with respect to natural frequencies in nanoresonator-coupled nanotube systems. The wave propagation theory yielded the lowest natural frequency, which was selected for detailed analysis. The optimized values of size effect of 2 nm, temperature of 5 K, and frequency of 1.971975 THz were obtained. When C = 0.3, K = 10, T = 300, and L = 10×e−9, the root mean square error (RMSE) value is 0.8421, which indicates improved predictive performance as it continues to decrease. The study’s findings showed that changes in viscous constants impact natural frequencies, while size effects have a minor influence. Temperature variations also affect natural frequencies, with higher temperatures leading to higher frequencies. The optimized model demonstrates enhanced predictive performance, which contributes to a better understanding of nanoresonator systems and their application in noise reduction for aircraft engines.

Implementing handwritten text recognition using deep learning with TensorFlow: An MNIST dataset approach

Handwritten text recognition (HTR) is a pivotal technology with extensive applications in document digitization, postal automation, and educational tools. This paper delves into the implementing a deep learning-based system for recognizing handwritten digits using TensorFlow and the MNIST dataset. The MNIST dataset, a widely-used benchmark, comprises 60,000 training images and 10,000 testing images of handwritten digits, each standardized to a 28x28 pixel grayscale format. Leveraging the power of Convolutional Neural Networks (CNNs), our model effectively extracts features and classifies digits with high accuracy. The model architecture consists of multiple convolutional layers for feature extraction, pooling layers for dimensionality reduction, and fully connected layers for classification. Preprocessing steps include normalizing pixel values and one-hot encoding the labels, ensuring the data is optimally formatted for training. The TensorFlow framework, known for its robustness and scalability, facilitates the development and deployment of the model. Through a series of experiments, the model demonstrates impressive performance, achieving high accuracy on the MNIST test set. This paper underscores the potential of deep learning in handwritten text recognition. It sets the stage for future enhancements, such as recognizing more complex handwritten texts and optimizing the system for practical applications. The results highlight the effectiveness of deep learning techniques in overcoming the challenges associated with handwritten text recognition, paving the way for advanced, real-world implementations.

Internet of Things (IoT) Driven Water Management System for Efficient Level Control

Water is an essential and valuable resource in daily life, making its conservation crucial to prevent adverse effects. Storing water for domestic, industrial, agricultural, and other purposes is particularly important. Safe drinking water is increasingly becoming polluted due to the growing population and their demands for urbanization and industrialization. At the household level, some people leave electric water pumps running and either go to work or sleep, forgetting to turn off the pumps when the water container is full. This highlights the need for a reliable and continuous water supply. IoT plays a significant role in environmental monitoring, particularly in disaster management, early warning systems, and environmental data analytics. One major challenge in urban cities is water management, especially with the rapid growth of urbanization, necessitating sustainable urban development plans. To address these issues, we propose a "Water Level Monitoring System" solution. This paper presents an IoT-based water monitoring system for real-time applications. The system's sensors measure the water level in the tank, and the data is sent to a cloud server, allowing users to view it on a remote dashboard. This system can be used efficiently by both homeowners and industrial users, as well as other water utilities.

Gastro-retentive drug delivery system of hypertension drug: Formulation and evaluation study

Introduction: Hypertension, a major global health concern, necessitates effective management through sustained drug delivery systems. Gastro-retentive drug delivery systems (GRDDS) offer a strategic advantage by prolonging the residence time of drugs in the stomach, thus enhancing therapeutic efficacy and patient adherence. This study aims to develop and evaluate a GRDDS for antihypertensive drugs to achieve extended gastric retention and controlled release. Methods: A GRDDS was formulated using a combination of hydrophilic and hydrophobic polymers to ensure buoyancy and extended gastric retention. The formulation process involved selecting optimal polymer concentrations and incorporating release-modulating agents. In vitro evaluations included buoyancy studies, swelling behavior analysis, and drug release kinetics under simulated gastric conditions. Additionally, in vivo studies were conducted to assess the system’s gastric retention and pharmacokinetic profile in an animal model. Conclusion: The developed GRDDS demonstrated effective gastric retention and a controlled release profile for the antihypertensive drug. In vitro results confirmed the system’s ability to maintain buoyancy and provide sustained drug release. In vivo studies supported these findings, showing improved drug bioavailability and stable plasma levels. This GRDDS represents a promising advancement in hypertension management, potentially enhancing therapeutic outcomes and patient compliance. Further research and clinical trials are recommended to validate these preclinical results and optimize the system for broader application.

Rancang Bangun Media Pembelajaran Sistem Reproduksi Wanita Berbasis Virtual Reality

Midwifery practices have contributed to reducing maternal and child mortality rates by applying biomedical knowledge, one of which is anatomy. Anatomy education typically uses cadavers, models, and books, but it is considered less effective. This study aims to create a virtual reality-based application for quality learning media on the female reproductive system. This research is a development study, which employs a waterfall model to create a high-quality educational media application. The Midwifery Department at Poltekkes Kemenkes Yogyakarta conducted the research in 2022. Based on the needs analysis, it is necessary to develop interactive learning media, one of which utilizes virtual reality technology. Blender for 3D Web applications and A-Frame for Virtual Reality Web. Overall, the application testing resulted in a feasibility percentage of 80.84%. We rated the Virtual Reality application for the Female Reproductive System as very feasible, requiring only minor improvements for learning purposes.

Application of artificial intelligence in lung cancer screening: A real-world study in a Chinese physical examination population.

With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image-assisted diagnosis system in clinical treatment is a major trend in medical development. Therefore, in order to explore the value and diagnostic accuracy of the current AI system in clinical application, we aim to compare the detection and differentiation of benign and malignant pulmonary nodules between AI system and physicians, so as to provide a theoretical basis for clinical application. Our study encompassed a cohort of 23 336 patients who underwent chest low-dose spiral CT screening for lung cancer at the Health Management Center of West China Hospital. We conducted a comparative analysis between AI-assisted reading and manual interpretation, focusing on the detection and differentiation of benign and malignant pulmonary nodules. The AI-assisted reading exhibited a significantly higher screening positive rate and probability of diagnosing malignant pulmonary nodules compared with manual interpretation (p < 0.001). Moreover, AI scanning demonstrated a markedly superior detection rate of malignant pulmonary nodules compared with manual scanning (97.2% vs. 86.4%, p < 0.001). Additionally, the lung cancer detection rate was substantially higher in the AI reading group compared with the manual reading group (98.9% vs. 90.3%, p < 0.001). Our findings underscore the superior screening positive rate and lung cancer detection rate achieved through AI-assisted reading compared with manual interpretation. Thus, AI exhibits considerable potential as an adjunctive tool in lung cancer screening within clinical practice settings.

Energy analysis of a direct expansion heat pump assisted by a thermal photovoltaic panel for hot water production in several regions of Brazil

This study focused on evaluating the energy performance and economic viability of a direct expansion photovoltaic-Thermal Heat Pump (PV-T/HP) system for residential heating applications in various regions of Brazil. A detailed mathematical model was implemented to compare the PV-T/HP system with other solar heating technologies, as photovoltaic with solar evacuated tubes collector (PV+TSC) and photovoltaic with electrical heat water (PV+EHW), analyzing key metrics such as electrical efficiency, thermal efficiency, and levelized cost of heat (LCOH). The study revealed variations ranging from 7.5 to 2.5 in the Coefficient of Performance (COP) of the heat pump under different solar irradiation and ambient temperature conditions, emphasizing the necessity for future optimization to enhance the system performance. Results indicated that cities with the lower ambient temperature such as Belo Horizonte and Porto Alegre exhibited favorable conditions for the PV-T/HP system, leading to increased energy generation and positive net electricity production. The study highlighted the need for tailored strategies to control system operations, limit compressor consumption, and improve overall efficiency. These findings contribute to the understanding of PV-T/HP systems in residential heating applications, showcasing their potential for sustainable energy solutions in Brazil.

A facile method to fabricate cell‐laden hydrogel microparticles of tunable sizes using thermal inkjet bioprinting

AbstractThis study investigates the application of a drop‐on‐demand (DOD) thermal inkjet (TIJ)‐based bioprinting system for the fabrication of cell‐laden hydrogel microparticles (HMPs) with tunable sizes. The TIJ bioprinting technique involves the formation of vapor bubbles within the print chamber through thermal energy, expelling small droplets of bio‐ink onto a substrate. The study employs a heat‐treated saponified gelatin‐based bio‐ink, HSP‐GelMA. This bio‐ink is modified through methacrylic anhydride functionalization and undergoes subsequent saponification and heat treatment processes. Various concentrations of SPAN 80 surfactant in mineral oil were evaluated to assess their influence on HMP size and stability. The results indicate a direct correlation, with higher SPAN 80 concentrations resulting in smaller and more stable HMPs. The study further investigates the influence of jetting volume on HMP size distribution, revealing that larger jetting volumes lead to increased HMP sizes, attributed to droplet coalescence. This is supported by our further study via a Monte Carlo simulation, which shows that the mean droplet diameter grows approximately linear with the number of dispensed droplets. In addition, the study demonstrates the capability of the TIJ bioprinting system to achieve multimaterial encapsulation within HMPs, exemplified by staining living cells with distinct cytoplasmic membrane dyes. The presented approach provides insights into the controlled fabrication of cell‐laden HMPs, highlighting the versatility of the TIJ bioprinting system for potential applications in tissue engineering and drug delivery.

Evidence-based research of the indicator system for evaluating the application effect of TCM standards

The traditional Chinese medicine evaluation indicator system can effectively identify and recognize deficiencies in the implementation of standards and provide a rationale for improving the technical content, enhancing the effectiveness of implementation and promoting the dissemination of traditional Chinese medicine culture and technology globally. Evidence-based principles can be an important method to guide the development of traditional Chinese medicine indicators and to promote the application of standards. This paper introduces the development status of NICE indicators and provides reference ideas for constructing evaluation indicator for traditional Chinese medicine standards application based on evidence-based principles. The specific steps for constructing an evaluation indicator system for traditional Chinese medicine standard application include identifying indicator domains, evidence synthesis, developing indicators, constructing an indicator system, cost- effectiveness and resource impact analyses, and finalizing indicators for training and promotion. In order to promote the further development of traditional Chinese medicine, it is necessary to strengthen the integrated construction of “guidelines-standards-indicators”, accelerate the establishment of a coordination mechanism between domestic and international organizations, and pay attention to the characteristics of traditional Chinese medicine and focusing on implications for practice and policy.

Преимущества и риски использования ChatGPT в системе высшего образования: теоретический обзор

The author of this review publication has set himself the task of generalizing the ideas of Russian and foreign educational researchers regarding the advantages and disadvantages of using neural networks, namely, the large language model ChatGPT, in the higher education system. 130 of the latest printed and electronic sources in Russian and English on pedagogy and humanitarian disciplines, which date back to 2023 and the first half of 2024, served as the material for the analysis. The scientific novelty of the study lies in identifying the most effective methods for assessing the didactic potential and determining the problems of introducing artificial intelligence technologies in education as exemplified by the use of ChatGPT, including the SWOT analysis method, considered as an effective analytical tool for assessing the strengths and weaknesses, opportunities and threats of using ChatGPT for educational purposes. As a result, the universal trends and features of the implementation of ChatGPT as an innovative pedagogical technology are revealed. The problems of ChatGPT application in the higher education system are analyzed from the point of view of compliance with ethical standards, prevention of academic dishonesty, formation of cognitive abilities and research competencies of students, deepening of individualization of the educational process, development of critical and creative thinking, increase in the level of information literacy and improvement of universal competencies and professional skills of students. The prospects and risks of ChatGPT application in higher education are described.

Diffusion Behaviors of CaCl2-NaCl Molten Salt under an Electric Field: A Deep Potential Molecular Dynamics Simulation.

CaCl2-NaCl molten salt is one of the widely used electrolytes, and the effect of the electric field on it needs to be considered in the environment of manufacturing metals and alloys as well as in battery applications. To be closer to the state of the CaCl2-NaCl molten salt system in practical applications, this study uses the training-based deep potential, combined with the ionic structure, to analyze the electric field effects on the drift velocity, ionic mobility, ion diffusion, and viscosity of the CaCl2-NaCl system by molecular dynamics simulations. It is shown that the electric field has a stronger effect on the ion diffusion behavior parallel to the direction of the electric field in the CaCl2-NaCl molten salt system. Due to the looser coordinate structure of Na+, the interaction force between Na-Cl is small compared with that between Ca-Cl. Na+ is easily driven and more sensitive to the electric field, whose drift velocity, ionic mobility, and diffusion coefficient are larger than those of the other two ions, with an order of Na+ > Cl- > Ca2+. All ionic drift velocities increase linearly as electric field intensity increases and the ionic mobilities tend to be constant. The diffusion coefficient parallel to the direction of the electric field exponentially increases and the viscosity tends to exponentially decrease with the increase in the electric field intensity. This work is important for accurately predicting the properties and performance of molten salts and their improvement for applications such as solar thermal energy conversion.

CONSIDERATION OF PLANNING PERMISSION IN SHORT-TERM RESIDENTIAL ACCOMMODATIONS

Planning permission may be required if the use of the property for short-term residential accommodations (STRA) services constitutes ‘development’ in planning terms. In analysing the possible operational aspects of STRA application in the planning system in Malaysia, the experience of STRA implementation in some selected countries is explored. The article concludes that there are different approaches, which are adopted by different regions concerning the need for planning permission. Most jurisdictions that are “friendly” towards STRAs view that planning permission is not necessary if STRA is managed on a small scale. Hence, it can be concluded that if the scale of the STRA business is big, i.e. ‘commercial’ in nature, planning permission is needed. Alternatively, the local planning authority may consider issuing a provisional or temporary planning permission (TPP), a short-term approval that is only permissible for the transitory nature of the use of land and buildings.

RNA-Activated CRISPR/Cas12a Nanorobots Operating in Living Cells.

Active clustered regularly interspaced short palindromic repeats (CRISPR/Cas12a) systems possess both cis-cleavage (targeted) and trans-cleavage (collateral) activities, which are useful for genome engineering and diagnostic applications. Both single- and double-stranded DNA can activate crRNA-Cas12a ribonucleoprotein (RNP) to achieve cis- and trans-cleavage enzymatic activities. However, it is not clear whether RNA can activate the CRISPR/Cas12a system and what is critical to the trans-cleavage activity. We report here that RNA can activate the CRISPR/Cas12a system and trigger its trans-cleavage activity. We reveal that the activated crRNA-Cas12a RNP favors the trans-cleavage of longer sequences than commonly used. These new findings of the RNA-activated trans-cleavage capability of Cas12a provided the foundation for the design and construction of CRISPR nanorobots that operate in living cells. We assembled the crRNA-Cas12a RNP and nucleic acid substrates on gold nanoparticles to form CRISPR nanorobots, which dramatically increased the local effective concentration of the substrate in relation to the RNP and the trans-cleavage kinetics. Binding of the target microRNA to the crRNA-Cas12a RNP activated the nanorobots and their trans-cleavage function. The repeated (multiple-turnover) trans-cleavage of the fluorophore-labeled substrates generated amplified fluorescence signals. Sensitive and real-time imaging of specific microRNA in live cells demonstrated the promising potential of the CRISPR nanorobot system for future applications in monitoring and modulating biological functions within living cells.

Development and In vivo Evaluation of Nanogel Drug Delivery System for Promoting Wound Healing in Diabetic Induced Rats

Recently, researchers have looked at the use of nanotechnology as a drug-delivery system for topical and transdermal applications. The transport of medications and active ingredients to the skin via formulations, including nanoparticles, is a subject of substantial contemporary interest. The present work is proposed to prepare the atorvastatin nanogels to promote wound healing in a diabetic animalmodel.Atorvastatin nanogels were prepared by precipitation polymerization technique using hydroxy propyl methacrylate as polymer. The drug and polymer were selected in ratios of 1:1, 1:2, 1:3, 1:4, 1:5, 1:6, 1:7 and 1:8. Additionally, the produced nanogel was evaluated in vivo and examined for its particle size, trapping effectiveness, and drug release in vitro. The particle size of the prepared various formulations (F1-F8) showed a size range of 68 to 80nm, and entrapment efficiency was seen to be in the range of 58.36-86.75%. The cumulative percentage of drug release was reported to be 61.96 to 73.76 percent over a period of 12hours during the in vitro drug release investigation, which was conducted using phosphate buffer at pH 7.4.The drug release followeda non-fiction mechanism of release kinetics. On the other hand, in vivo comparative study showed a complete wound healing effect for nanogels on the 11th day, whereas for conventional gel on the 15th day.This study indicates that nanogels formulation heals the diabetic wound completely at a faster rate, and also the drug atorvastatin also can be used for diabetic wound healing.

Integrating Blockchain in Scheduling: A Comprehensive Review of Current Trends and Future Directions

This review paper offers a comprehensive exploration of blockchain technology's integration in scheduling activities across various industries. It systematically gathered and analyzed literature, identifying 133 relevant documents through rigorous screening from 2017 till 2023. The bibliometric analysis, including co-authorship and co-occurrence maps, revealed key trends, influential authors, and emerging research areas. Content analysis focused on blockchain applications in service optimization, system and resource planning, management, project and production planning, energy optimization, and security enhancement. The research acknowledged significant advancements in these areas, particularly in terms of improved efficiency, transparency, and security. The findings underscore the potential of blockchain in revolutionizing scheduling and management processes across different sectors, highlighting the need for further exploration of its applications and implications in various professional contexts. The paper aims to bridge the gap in the literature by presenting a holistic view of blockchain's role in advancing scheduling methods, driving innovation, and fostering more robust, efficient, and transparent scheduling systems across industries.

Advances in miniaturized droplet-based electrochemical pH sensor

This study presents an innovative integrated electrochemical system for droplet-based electropolymerization and sensor applications. The system features a circular geometry and uses perfluorocarbon-based hydrophobic material to facilitate droplet formation, thus requiring only microliters of solution. The methodology includes a detailed fabrication process of the electrochemical chips and demonstrates the device's versatility in both aqueous and non-aqueous electropolymerization. The results show successful material deposition and characterization, with the system proving effective for miniaturized sensor applications. This approach significantly reduces the volume of required materials, offering a more economical and efficient alternative for developing new sensor materials and applications.

Development of a novel crAss-like phage detection method with a broad spectrum for microbial source tracking

CrAssphage has been recognized as the most abundant and human-specific bacteriophage in the human gut. Consequently, crAssphage has been used as a microbial source tracking (MST) marker to monitor human fecal contamination. Many crAss-like phages (CLPs) have been recently discovered, expanding the classification into the new order Crassvirales. This study aims to assess CLP prevalence in South Korea and develop a detection system for MST applications. Thirteen CLPs were identified in six human fecal samples and categorized into seven genera via metagenomic analysis. The major head protein (MHP) displayed increased sequence similarity within each genus. Eight PCR primer candidates, designed from MHP sequences, were evaluated in animal and human feces. CLPs were absent in animal feces except for those from raccoons, which hosted genera VI, VIIa, and VIIb. CLPs were detected in 91.52% (54/59) of humans, with genus VI (38 out of 59) showing the highest prevalence, nearly double that of p-crAssphage in genus I (22 out of 59). This study highlights genus VI as a potent MST marker, broadening the detection range for CLPs. Human-specific and selectively targeted MST markers can significantly impact hygiene regulations, lowering public health costs through their application in screening liver, sewage, wastewater, and various environmental samples.

Fabrication of l-proline enriched alginate dialdehyde-gelatin hydrogel thin films for efficient wound healing applications.

Hydrogel-based wound management systems represent a promising avenue in tissue engineering for restoring and preserving the normal functionality of damaged tissues. Incorporating active components into hydrogel matrices enhances their suitability for biomedical applications. In this study, we investigated the integration of l-proline, a nonessential imino acid with largely unexplored roles in living systems, into alginate dialdehyde-gelatin hydrogel for wound healing purposes. Physicochemical properties of the resulting hydrogel film, termed ADAGLP, were meticulously evaluated, including wound healing efficacy in vitro and anti-biofilm activity against Gram-positive and Gram-negative microorganisms. Fourier-transform infrared spectroscopy (FTIR) analysis provided insights into the interaction between l-proline and ADAG. Films incorporating 0.5% l-proline were selected for comprehensive investigation. Comparative analysis revealed prolonged gelation time and increased water holding capacity of ADAGLP compared to ADAG films. Moreover, ADAGLP exhibited a significantly higher degradation rate (69.5 ± 3.2%) compared to ADAG (35.2 ± 1.6%). Remarkably, ADAGLP demonstrated cyto-compatibility, non-toxicity, and facilitated migration to the scratch area in vitro conditions. Notably, it exhibited potent anti-biofilm properties. Our findings suggest that ADAGLP hydrogel holds promise as a biomaterial for wound care, offering prolonged drug delivery and maintaining optimal moisture levels in wound areas. The incorporation of l-proline in the wound microenvironment may contribute to enhanced tissue remodeling, by inhibiting biofilm formation, further highlighting the potential of this hydrogel system in wound healing applications.

Array of Active Shielding Coils for Magnetic Field Mitigation in Automotive Wireless Power Transfer Systems

This paper deals with the mitigation of magnetic field levels produced by a wireless power transfer (WPT) system to recharge the battery of an electric vehicle (EV). In this work, an array of active coils surrounding the WPT coils is proposed as a mitigation technique. The theory and new methodological aspects are the focus of the paper. Magnetic field levels in the environment are calculated numerically without and with the presence of an array of active coils in a stationary WPT system for automotive applications. By the proposed mitigation method, the field levels beside the vehicle are significantly reduced and comply with the reference levels (RLs) of the ICNIRP 2010 guidelines for human exposure to electromagnetic fields and the magnetic flux density limits proposed by ISO 14117 for electromagnetic interference (EMI) in cardiac implantable electronic devices (CIEDs).