Capability Of System Research Articles

A multifunctional nanosystem catalyzed by cascading natural glucose oxidase and Fe3O4 nanozymes for synergistic chemodynamic and photodynamic cancer therapy

The significance of the tumor microenvironment (TME) in tumor initiation and progression is increasingly acknowledged. Conventional therapeutic approaches face limitations within the complex TME, including the restrictions imposed by hypoxia on photodynamic therapy (PDT) and the deficiency of endogenous H₂O₂ affecting chemodynamic therapy (CDT). In response to the TME's characteristics of high metabolism, hypoxia, and weak acidity, a multifunctional nanosystem MNPs/GOD@CS/IR820, which synergistically integrates CDT and PDT, has been developed. This system can actively accumulate at tumor sites under an external magnetic field and release active components in response to the weakly acidic TME. It mitigates the limitations imposed by hypoxia and endogenous H₂O₂ deficiency on PDT and CDT, respectively, thereby enabling synergistic treatment. Additionally, the system's multimodal imaging capabilities facilitate precise tumor localization and real-time, non-invasive in vivo assessment via fluorescence imaging and MRI. In vitro and in vivo evaluations demonstrate significant antitumor efficacy, effectively inhibiting tumor growth and improving survival rates. By comprehensively addressing the challenges posed by the complex TME and enhancing real-time monitoring capabilities, our nanosystem paves the way for personalized and precise cancer treatment. Statement of significanceThis study introduces an innovative MNPs/GOD@CS/IR820 nanosystem that represents a significant advancement in cancer nanomedicine by addressing critical limitations of conventional photodynamic therapy (PDT), particularly in hypoxic tumor microenvironments. By synergistically integrating chemodynamic therapy (CDT) with PDT and incorporating MRI and fluorescence dual-modal imaging capabilities, this multifunctional platform offers enhanced therapeutic efficacy and real-time monitoring. The system's ability to generate oxygen in situ overcomes hypoxia-induced limitations, while its multimodal mechanism of action induces tumor cell apoptosis through multiple pathways. In vitro and in vivo studies demonstrate remarkable antitumor efficacy across diverse cancer types, significantly inhibiting tumor growth and improving survival rates. This comprehensive approach to cancer diagnosis and treatment not only advances precision medicine for targeted, multimodal cancer management but also provides a promising foundation for future clinical applications, potentially transforming cancer treatment strategies and improving patient outcomes.

Empowering decentralized production: A distributed manufacturing system for additive manufacturing processes

This work presents a pilot distributed manufacturing system for decentralized additive manufacturing, focusing on the Interdisciplinary Center for Advanced Manufacturing Systems (ICAMS) capabilities at Auburn University. The paper outlines the first phase of a multi-phase implementation plan and demonstrates the developed capabilities. The vision is to coordinate geographically separated manufacturing facilities as a cohesive unit. In our work, we prioritize instantaneous communication for file and information sharing. The Manufacturing Hub and Remote Cell, two facilities within driving distance, are coordinated in terms of part design, printing, and inspection procedures for a distributed Additive Manufacturing process. To enable coordination between the two facilities, ICAMS addresses three technological needs. These needs consider information sharing, process standardization, and data collection and monitoring. A network attached storage facilitates information sharing, a database-connected graphical user interface streamlines and standardizes the manufacturing process, and a data collection system facilitates process monitoring. The graphical user interface allows for order placement, progress monitoring, and communication updates. The developed phased plan, collaborative workflow, technological solutions, and production protocols demonstrate the potential for decentralized additive manufacturing. Successful integration of communication, design, printing, and quality assurance processes sets the foundation for future advancements in decentralized manufacturing systems.

The Performance Implications of Management Control Systems and Dynamic Capabilities: Evidence from Vietnam

Drawing on the resource-based view and dynamic-capability view, this study examines the relationship between the interactive use of management control systems, dynamic capabilities, and firm performance in the Vietnamese information and communication technology industry. The research model and hypotheses have been tested by partial least squares-structural equation modelling (PLS-SEM) with 240 survey samples obtained from managers working in Vietnamese information and communication technology firms. The results indicate that the interactive use of management control systems has a positive effect on dynamic capabilities. Additionally, both the interactive use of management control systems and dynamic capabilities have direct positive effects on firm performance. The results reveal that dynamic capabilities complementary mediate the relationships between the interactive use of management control systems and firm performance. This study provides theoretical and managerial implications for Vietnamese information and communication technology firms that are striving to develop management control systems and dynamic capabilities for enhancing firm performance.

Impact of CO2 as an oxidant on the decarburization and chromium retention and an approach for CO2 recycling

This study explores the unique role of CO2 as an oxidant in stainless steel smelting, focusing on its effectiveness in decarbonization and chromium retention. The research begins by theoretically demonstrating that although the introduction of CO2 increases the CO partial pressure in the reaction system, the decarburization and chromium (Cr) retention capabilities of CO2 can still be stably maintained through the rational adjustment of the molten steel composition, temperature, and inert gas proportions. Further experimental findings indicate that chromium does not exhibit significant oxidation losses when the carbon (C) content exceeds 1.0% (mass). Finally, a novel CO2 recovery and utilization approach is proposed, integrating CO2 capture from smelting flue gas and recycling it for smelting, reducing O2 consumption and energy costs. This innovative process, compatible with existing smelting plants, presents a promising pathway towards carbon neutrality in the iron and steel industry, bridging theoretical insights with practical applications.

Narrowband IoT in Livestock Farming: A Technological Innovation for Productivity and Sustainability

The integration of technology in livestock farming is crucial for enhancing production efficiency and animal welfare. This study aimed to develop and evaluate the implementation of a Narrowband IoT (NB-IoT)-based automated monitoring system in poultry farming. Using an experimental design, the research involved 30,000 day-old chicks at PT. Anugerah Teknologi Ternak in Central Java, Indonesia. The NB-IoT system collected real-time data on environmental parameters and poultry activity. Time-series analysis revealed non-stationary data, while correlation analysis showed a strong negative relationship between temperature and humidity (r = -0.8521). Anomaly detection identified 13.33% of observations as anomalous, demonstrating the system's capability for early issue detection. Regression modeling (R-squared = 0.7261) indicated that temperature and humidity significantly influence poultry productivity. The study concludes that NB-IoT implementation in poultry farming has significant potential for enhancing productivity through real-time monitoring and early anomaly detection, supporting more efficient and sustainable precision farming practices. However, limitations in data stationarity and sample generalizability suggest the need for further research to improve long-term predictions and broaden applicability across diverse farming contexts.

A bio-feedback-mimicking electrode combining real-time monitoring and drug delivery

Effective disease management based on real-time physiological changes presents a significant clinical challenge. A flexible electrode system integrating diagnosis and treatment can overcome the uncertainties associated with treatment progress during localized interventions. In this study, we develop a system featuring a biomimetic feedback regulation mechanism for drug delivery and real-time monitoring. To prevent drug leakage, the system incorporates a magnesium (Mg) valve in the outer layer, ensuring zero leakage when drug release is not required. The middle layer contains a drug-laden poly(3,4-ethylenedioxythiophene) (PEDOT) sponge (P-sponge), which supplies the water to partially or fully activate the Mg valve under electrical stimulation and initiate drug release. Once the valve is fully opened, the exposed and expanded P-sponge electrode establishes excellent contact with various tissues, facilitating the collection of electrophysiological signals. Encapsulation with polylactic acid film ensures the system's flexibility and bioresorbability, thereby minimizing potential side effects on surrounding tissues. Animal experiments demonstrate the system's capability to mimic feedback modulation mechanisms, enabling real-time monitoring and timely drug administration. This integrated diagnosis and treatment system offers an effective solution for the emergency management of acute diseases in clinical settings.

CFD Analysis of Improving Air Conditioning System Performance By Adding SiO2 Nanoparticles To The Compressor Oil

The overall performance of air-conditioning systems is necessary to evaluate the comfort conditions and equipment life. in order not to varnish energy. The aim of this study is to improve performance of air conditioning by adding nanoparticles to oil of compressor. The research applied computational fluid dynamics CFD to simulate the use of SiO2 nanoparticles in air-conditioning systems. Silicon dioxide (SiO2) nanoparticles have better thermal properties than pure oil and can also significantly enhance the performance of compressor oils as well as heat transfer capability in HVAC systems. This research investigates the reactions between (0.1%, 0.4%, and %0.7) of SiO2 nanoparticles with compressor oil, to determine their impacts on heat dissipation, lubricant efficiency as well as performance overall. Results show that the addition of nanoparticles to the oil lubricant increases the COP of the air conditioning system.

Optimal Control of a Semi-Active Suspension System Collaborated by an Active Aerodynamic Surface Based on a Quarter-Car Model

This paper addresses the trade-off between ride comfort and road-holding capability of a quarter-car semi-active suspension system, collaborated by an active aerodynamic surface (AAS), using an optimal control policy. The semi-active suspension system is more practical to implement due to its low energy consumption than the active suspension system while significantly improving ride comfort. First, a model of the two-DOF quarter-car semi-active suspension in the presence of an active airfoil with two weighting sets based on ride comfort and road-holding preferences is presented. Then, a comprehensive comparative study of the improved target performance indices with various suspension systems is performed to evaluate the proposed suspension performance. Time-domain and frequency-domain analyses are conducted in MATLAB® (R2024a). From the time-domain analysis, the total performance measure is enhanced by about 50% and 35 to 45%, respectively, compared to passive and active suspension systems. The results demonstrate that a semi-active suspension system with an active aerodynamic control surface simultaneously improves the conflicting target parameters of passenger comfort and road holding. Utilizing the aerodynamic effect, the proposed system enhances the vehicle’s dynamic stability and passenger comfort compared to other suspension systems.

Research on the Digital Transformation Process from Dependent to Self-Empowered Upgrading

In the face of many challenges in the digital era, how to accelerate the digital transformation of enterprises has become a topic of widespread concern in academia and industry. In the face of many challenges in the digital era, how to accelerate the digital transformation of enterprises has become a topic of widespread concern in academia and industry. Considering that the stage of this solution is to first rely on relevant enterprises to upgrade and build digital systems, and then cultivate their own digital capabilities, so as to complete the iteration of digital system capabilities and achieve continuous self-empowerment upgrades, it is named as the research on the process of upgrading from dependent to self-empowered to digital transformation.

A Digital Transformation in Action: Assessing the Impact of Information System Capabilities on Firm Performance through the Lens of Innovation and Business Process Performance and Moderating Role of Entrepreneurial Marketing in Indian SMEs

A Digital Transformation in Action: Assessing the Impact of Information System Capabilities on Firm Performance through the Lens of Innovation and Business Process Performance and Moderating Role of Entrepreneurial Marketing in Indian SMEs

Patient‐Mounted Neuro Optical Coherence Tomography for Targeted Minimally Invasive Micro‐Resolution Volumetric Imaging in Brain In Vivo

Targeted neuroimaging plays a vital role in evaluating pathologies and guiding interventions in deep brain regions, such as biopsy, laser ablation, and deep brain stimulation. However, current neuroimaging techniques face several challenges when it comes to imaging the deep brain. These challenges include limited imaging depth, a narrow field of view, low resolution, and a lack of real‐time imaging and stereotactic deployment capabilities. To address these challenges, a patient‐mounted neuro optical coherence tomography (neuroOCT) system that combines a lightweight 5 degrees‐of‐freedom skull‐mounted robot (Skullbot) with a neuroendoscope measuring ≈0.6 mm in diameter is introduced. This innovative system enables targeted and minimally invasive neuroimaging with an axial resolution of ≈2.4 μm and a transverse resolution of around 4.5 μm. The Skullbot can be securely attached to the head and precisely deploys the neuroendoscope with an accuracy of ±1.5 mm in the transverse direction and ±0.25 mm in the longitudinal direction. This allows for motion‐insensitive stereotactic imaging within the brain. By utilizing the neuroOCT system, targeted imaging of a tumor in a brain phantom is successfully demonstrated. Furthermore, the system's capability for in vivo micro‐resolution volumetric neuroimaging of fine structures within a mouse brain is validated.

Magnetic Field Control Using an Electromagnetic Actuation System with Combined Air‐Core and Metal‐Core Coils

Magnetic fields are widely utilized for remote control of magnetic objects, with various actuation systems developed for manipulating miniature robots in research and biomedical applications. When designing a manipulation system providing a uniform magnetic field, it is also important to consider both the accessibility of the workspace and the integration of imaging tools. This article presents an electromagnetic coil system that manipulates magnetic objects within a 3D space, enhancing the magnetic field in an upward orientation. The system includes eight metal‐core coils arranged hemispherically to ensure unimpeded access to the workspace and imaging tools, along with two air‐core coils. Easier control and repeatability of the magnetic field are achieved using two joysticks and sequential programming. The versatility of the system is demonstrated by using it to manipulate a magnetic guidewire and to guide micromagnets to various targets. Additionally, using this system, oscillating magnetic fields effectively control swarms of magnetic nanoparticles, enabling operations such as dispersion, assembly, and ribbon‐like shape formation. Furthermore, the manipulation of cell‐based microrobots (cell‐bots) showcases the system's capability to handle single and multiple cell‐bots, facilitating their collection while preserving cell viability. These experiments underscore the system's potential for fundamental biomedical research and various applications.

A Bi-Level Peak Regulation Optimization Model for Power Systems Considering Ramping Capability and Demand Response

In the context of constructing new power systems, the intermittency and volatility of high-penetration renewable generation pose new challenges to the stability and secure operation of power systems. Enhancing the ramping capability of power systems has become a crucial measure for addressing these challenges. Therefore, this paper proposes a bi-level peak regulation optimization model for power systems considering ramping capability and demand response, aiming to mitigate the challenges that the uncertainty and volatility of renewable energy generation impose on power system operations. Firstly, the upper-level model focuses on minimizing the ramping demand caused by the uncertainty, taking into account concerned constraints such as the constraint of price-guided demand response, the constraint of satisfaction with electricity usage patterns, and the constraint of cost satisfaction. By solving the upper-level model, the ramping demand of the power system can be reduced. Secondly, the lower-level model aims to minimize the overall cost of the power system, considering constraints such as power balance constraints, power flow constraints, ramping capability constraints of thermal power units, stepwise ramp rate calculation constraints, and constraints of carbon capture units. Based on the ramping demand obtained by solving the upper-level model, the outputs of the generation units are optimized to reduce operation cost of power systems. Finally, the proposed peak regulation optimization model is verified through simulation based on the IEEE 39-bus system. The results indicate that the proposed model, which incorporates ramping capability and demand response, effectively reduces the comprehensive operational cost of the power system.

Study on Thermal Runaway Behavior and Early Warning Algorithm of Ternary Lithium Battery Pack Under Preload Force

Overcharging is a primary cause of thermal runaway in ternary lithium‐ion batteries, often leading to serious safety incidents. Early detection of thermal runaway during overcharging is therefore critical. This study investigates a 5 Ah ternary lithium battery pack, applying appropriate preload force to simulate real‐world conditions. Various overcharge experiments are conducted under different conditions, and changes in battery voltage, temperature, and expansion force are thoroughly analyzed. The results indicate that under the same initial conditions, higher charging rates accelerate the temperature rise in the lithium battery. Additionally, the internal gas generation rate increases, causing a faster rise in edge pressure and leading to earlier battery cracking. Building on these findings, a three‐level early warning algorithm is developed, which comprehensively considers voltage, temperature, and expansion force changes. Experimental validation demonstrates that this algorithm can accurately identify the current stage of thermal runaway and detect the transition to the third warning stage 604 s before complete failure, thus providing critical protection for the safe operation of the battery pack. This study offers valuable guidance for enhancing the monitoring and early warning capabilities of battery management systems.

Evaluation of carbon sink and photovoltaic system carbon reduction along roadside space

As China's photovoltaic (PV) sector experiences rapid growth, the availability of land resources has become a pivotal policy focus, driving the need for comprehensive research and strategic planning for roadside PV initiatives. Utilizing a fuzzy multi-criteria decision-making approach, combined with GIS spatial analysis and a modular design framework, our study quantitatively compared the carbon reduction capabilities of PV systems against the carbon sequestration potential of various vegetative arrangements along the roadside space. The roadside space analysis modular considers a range of factors including topography, meteorology, and construction costs. We examined the spatial distribution of suitability for PV installation and vegetation establishment along the provincial expressway network in China. The results revealed that Inner Mongolia stood out as the frontrunner in carbon reduction potential within high-suitability zones for PV construction, achieving an impressive 4.845 million tons of carbon reduction—nearly four times greater than that of Shaanxi Province. In contrast, the carbon sequestration attributed to vegetation greening in areas less suited for PV development revealed a higher propensity in the southeastern provinces. Guangdong led the charge with an impressive annual carbon sequestration of 2.89 million tons. This was closely followed by Yunnan, Sichuan, Hebei, Guizhou, and Henan, each achieving carbon sequestration amounts exceeding 2 million tons. These results offer valuable quantitative support and practical recommendations for achieving low-carbon objectives in the construction of China's expressways.

Сombat operations model of a single self-propelled artillery system for the computer game ARMA 3

Military computer games are an important segment of the world media culture and media business. In addition to the entertainment aspect, military simulators play an important role in the training of future military specialists. However, quite often the scenario component of military gaming lags behind the rapid development of real military equipment. World experience of military conflicts of the 21st century shows that the most intensively developing segment of ground forces weapons is its artillery component. In this paper, a model of combat use of a new generation artillery system is developed. The model is intended for modification of the military game ARMA 3. The new generation artillery system is a large-caliber gun with a high level of automation. It has a high rate of fire, maneuverability, and shooting accuracy. Due to these qualities, the new generation artillery system is comparable in combat power to a unit of traditional guns and can carry out combat operations in single mode. A technique has been developed for dynamically assessing the current combat capability of an artillery system, taking into account the resource costs during fire activity, including indirect hits by the enemy. It is shown that in addition to traditional tactical counter-battery tasks, an artillery system can be used to destroy a suddenly emerging high-risk target. A high-risk target is a non-artillery system capable of causing very large damage in a short period of time. Based on the method of dynamically assessing the current combat capability, a tree of artillery system states is constructed. It includes the most probable states of the artillery system and the corresponding design parameters. A ratio is obtained that allows, for a known state of the artillery system, to estimate the number of shots needed to hit the target with the required guaranteed probability. Calculated examples show that a new-generation artillery system is capable of destroying a high-risk target, sometimes even at the cost of its own loss. The developed model is implemented and is being tested as a mod for the war game ARMA 3.

Dynamic 3D hydrogen-bond network in siloxene-water system enables efficient moisture-enabled electricity generation

Utilizing ubiquitous moisture as an energy source for moisture-enabled electric generator (MEG) has emerged as a significant technological frontier. The migration process of protons at the water/solid interface is crucial for understanding the mechanism of moisture-to-electricity conversion and efficient energy harvesting. However, the lack of clarity on this scientific question has hindered the substantive development of MEG. Here, a novel dynamic three-dimensional (3D) hydrogen-bond network between the interface of siloxene layers was designed through water molecule intercalation. The spatial bridging effect of this dynamic 3D hydrogen-bond network, formed on the siloxene layers, enhances the load transfer capability of the siloxene-water system, thereby randomizing the direction of proton hopping. Experimental and theoretical calculations demonstrate that the dynamic 3D hydrogen-bond network constructed within and between the siloxene layers facilitates rapid proton conduction. Kinetic simulations further confirm that the strength of the hydrogen-bond network accelerates proton transport rate. The current density of siloxene under high humidity increases significantly, reaching 22.37 µA cm−2, which is 122 times that under low humidity, as well as the open-circuit voltage reaches 0.73 V. This work contributes to understanding the microscopic mechanisms behind efficient moisture-enabled electricity and provides a fresh perspective for enhancing MEG performance.

DiBiMT: A Gold Evaluation Benchmark for Studying Lexical Ambiguity in Machine Translation

Abstract Despite the remarkable progress made in the field of Machine Translation (MT), current systems still struggle when translating ambiguous words, especially when these express infrequent meanings. In order to investigate and analyze the impact of lexical ambiguity on automatic translations, several tasks and evaluation benchmarks have been proposed over the course of the last few years. However, works in this research direction suffer from critical shortcomings. Indeed, existing evaluation datasets are not entirely manually curated, which significantly compromises their reliability. Furthermore, current literature fails to provide detailed insights into the nature of the errors produced by models translating ambiguous words, lacking a thorough manual analysis across languages. With a view to overcoming these limitations, we propose Disambiguation Biases in MT (DiBiMT), an entirely manually-curated evaluation benchmark for investigating disambiguation biases in eight language combinations and assessing the ability of both commercial and non-commercial systems to handle ambiguous words. We also examine and detail the errors produced by models in this scenario by carrying out a manual error analysis in all language pairs. Additionally, we perform an extensive array of experiments aimed at studying the behavior of models when dealing with ambiguous words. Finally, we show the ineffectiveness of standard MT evaluation settings for assessing the disambiguation capabilities of systems and highlight the need for additional efforts in this research direction and ad-hoc testbeds such as DiBiMT.Our benchmark is available at: https://nlp.uniroma1.it/dibimt/.

Candidates resume analyzer using artificial intelligence

In the modern recruitment process, where the number of candidates and job vacancies constantly increases, automating resume analysis becomes critically important for efficient selection. This paper focuses on developing a system for automated resume analysis using artificial intelligence, specifically the OpenAI model (ChatGPT). The paper thoroughly examines the system's components, structure, and functional capabilities. The system consists of several key modules: the user interface ensures interaction with users, the Application Programming Interface Gateway facilitates data exchange between the interface and the server, and the authentication module controls system access, ensuring user security. The main part of the system's business logic is implemented on the server, which interacts with the natural language processing module, utilizing the ChatGPT model for processing resume text data. The use of natural language processing technologies allows the system to automatically extract and analyse key elements of resumes, such as education, work experience, skills, and certifications of candidates. This significantly speeds up the processing of large volumes of resumes, improving selection efficiency and accuracy. Data obtained during the analysis is stored in a PostgreSQL database, ensuring reliable storage and quick access for further processing. The paper also emphasizes the importance of integrating the system with other recruiting platforms and databases for more efficient management of the hiring process. Such integration allows for automatic synchronization of job vacancies and candidates, optimizing the search and selection process. Additionally, the paper highlights the key challenges associated with automating resume processing, such as the diversity of resume formats submitted by candidates, differences in data structure, and potential errors in automatically recognizing important information. Despite these challenges, the use of artificial intelligence and natural language processing methods significantly enhances the productivity and accuracy of recruitment processes. Thus, the developed automated resume analysis system based on Artificial Intelligence can become a significant tool in the modern candidate selection process. Its functionality not only enables quick and accurate resume analysis but also allows integration with other HR systems, simplifying the recruitment process, reducing data processing time, and improving selection accuracy.

A Novel Aerial-Aquatic Unmanned Vehicle Using Flapping Wings for Underwater Propulsion.

Aerial-aquatic unmanned vehicles are a combination of unmanned aerial vehicles and unmanned submersibles, capable of conducting patrols in both the air and underwater domains. This article introduces a novel aerial-aquatic unmanned vehicle that integrates fixed-wing configuration and flapping-wing configuration. In order to improve the low efficiency of the classic diagonal motion trajectory, this paper proposed an improved diagonal motion trajectory based on joint optimization of the stroke angle and angle of attack curve. The proposed method has been verified through simulations and experiments. A prototype was developed and experiments were completed, both indoors and outdoors, wherein the system's transmedium transition capability and flapping propulsion performance were comprehensively validated. Additionally, utilizing flapping propulsion, an average underwater propulsion speed of 0.92 m/s was achieved.