Safety Compliance Research Articles

Synthetic Biology in T-cell Engineering Research

Synthetic biology has emerged as a transformative discipline, enabling precise genetic and functional reprogramming of cellular systems. In T-cell engineering, it offers groundbreaking potential to revolutionize immunotherapy by endowing T cells with enhanced specificity, adaptability, and resilience against complex diseases such as cancer and autoimmune disorders. By integrating advanced genome-editing tools like CRISPR-Cas9 with modular synthetic constructs, researchers can design T cells with bespoke functionalities, such as tunable antigen recognition, controlled cytokine release, and resistance to immunosuppressive tumor microenvironments. This approach not only overcomes the limitations of conventional T-cell therapies but also facilitates the development of novel therapeutic paradigms, including "smart" cellular systems capable of sensing and responding to dynamic biological cues. Furthermore, synthetic circuits allow for the incorporation of logic-gated mechanisms to minimize off-target effects and enhance therapeutic precision. Despite these advancements, challenges remain in optimizing safety, scalability, and regulatory compliance. This research aims to explore the intersection of synthetic biology and T-cell engineering, highlighting cutting-edge methodologies, therapeutic applications, and emerging trends. By addressing current limitations and envisioning future possibilities, this work seeks to contribute to the growing body of knowledge driving synthetic biology toward clinical and industrial breakthroughs in cellular immunotherapy.

Optimizing shutdown and startup procedures in oil facilities: A strategic review of industry best practices

Shutdown and startup procedures in oil facilities are critical processes that significantly impact operational efficiency, safety, and environmental compliance. This strategic review examines industry best practices for optimizing these procedures to minimize downtime and enhance productivity. Effective shutdown and startup operations are essential not only for maintaining equipment integrity but also for ensuring the safety of personnel and compliance with regulatory standards. The complexities of oil facility operations necessitate a thorough understanding of the interdependencies between various systems and processes during these phases. This review identifies key factors that contribute to successful shutdown and startup procedures. First, comprehensive planning and preparation are vital. Establishing a detailed shutdown/startup plan that outlines specific tasks, timelines, and responsibilities helps mitigate risks associated with unplanned events. This includes conducting risk assessments and ensuring that all personnel are adequately trained to execute their roles effectively. Second, the implementation of advanced monitoring and control technologies is crucial. Utilizing automation and real-time data analytics allows for precise control over processes during shutdowns and startups, enabling quicker responses to anomalies. This technological integration can significantly reduce the time required for these operations while enhancing safety measures. Third, collaboration and communication among teams are essential components of successful operations. Encouraging a culture of open communication fosters teamwork and ensures that all stakeholders are aligned throughout the shutdown and startup phases. Regular debriefings and feedback sessions post-operations also play a vital role in continuous improvement. In conclusion, optimizing shutdown and startup procedures in oil facilities is paramount for enhancing operational efficiency and safety. By adopting industry best practices, including thorough planning, leveraging technology, and promoting effective communication, organizations can achieve significant improvements in their operational performance. This review serves as a resource for industry stakeholders aiming to refine their shutdown and startup strategies to achieve operational excellence. Keywords: Shutdown Procedures, Startup Procedures, Oil Facilities, Operational Efficiency, Safety, Environmental Compliance, Risk Assessment, Automation, Real-Time Data Analytics, Industry Best Practices.

The impact of safety leadership on safety behaviors of aircraft rescue and firefighting personnel during the COVID-19 pandemic

Objectives. Facing risk of contracting COVID-19, adopting individual health and safety behaviors to prevent infection was critical for first responders to ensure personal and public safety. This study assessed direct and indirect relationships between safety leadership, safety behaviors and the effect of risk perceptions on these relationships among aircraft rescue and firefighting (ARFF) personnel during the COVID-19 pandemic. Method. A total of 127 ARFF frontline personnel participated in an online survey. COVID-19-specific constructs of safety leadership, safety behaviors and risk perceptions were assessed using a structural model with moderation and serial mediation analysis using the mixed-model method. Results. Safety leadership had significant direct effects on safety compliance and indirect effects on safety participation and mask use. ARFF personnel’s perceived severity of the virus had significant direct effects on mask use and indirect effects on safety compliance and participation behaviors. The interaction of safety leadership and perceived susceptibility to the virus had significant direct effects on safety compliance behaviors and indirect effects on safety participation and mask use. Conclusion. There are practical implications to strengthen safety compliance behaviors through leadership. This study contributes to the literature on leadership and safety behaviors among ARFF personnel during exceptional circumstances and times of crisis.

Construction Safety Management: Analyzing the Effectiveness of Safety Training Programs on Job Sites

Occupational injuries and fatalities at work are a worldwide problem, particularly in the construction industry. With technological progression, construction sites are still extremely high risk environments where workers put themselves at the mercy of many hazards. They have emerged as a critical part of reducing these risks and the safety of the workers. In this paper, I examine in detail the effectiveness of safety training programs in controlling job site hazards with an emphasis on accident reduction, behavioral changes, and safety culture. The paper looks at different types of training programs, the conventional classroom-based instruction, on the job training and innovative programmes such as virtual reality (VR) and simulation based training programmes. The paper also discusses the challenges, including language barriers and the need for site specific training, and suggests approaches for enhancing safety training practice to encourage a good safety culture among construction practitioners. Keywords Construction Safety, Job Site Hazards, Safety Training, Accident Prevention, Worker Behavior, Safety Compliance, Risk Management, OSHA Standards, Safety Management Systems, Safety Culture.

Analysing Food Safety Compliance in Toronto: Identifying Current Hazards and Challenge

Abstract. This research conducts an in-depth investigation into the current state of food safety compliance in Toronto, thoroughly examining the present condition of food safety in the city. By utilizing a comprehensive dataset that includes a wide variety of dining establishments and their respective inspection results, the study employs advanced statistical methods for both analysis and visualization. These methods include the development of logistic regression models to identify significant patterns and trends. The goal is to highlight areas that require immediate attention or policy adjustments through a detailed examination of inspection reports, types of violations, violation frequencies, inspection dates, and the nature of the violations. Finally, the findings of the study strongly suggest that the government should increase the frequency of inspections, particularly during certain seasons, across various types of food businesses, and for specific types of violations, to enhance local food safety and protect the health of every Toronto resident.

A web-based safety management platform to enhance safety for Chinese migrant construction workers

Over the past decade, existing research has investigated various solutions to enhance safety management on construction sites. Among the many solutions, developing a web-based safety platform has increasingly become a key element in safety improvement strategies. International research shows that safety management platforms improve migrant workers’ safety, but evidence for such interventions in New Zealand, especially for Chinese migrant construction workers, remains limited. This study built a web prototype catering to Chinese migrant construction workers in New Zealand. The data collection method was semi-structured interviews, and the effectiveness of the novel web prototype was validated based on respondents’ feedback. Results show that this safety web prototype can effectively improve the safety knowledge and safety awareness of Chinese migrant construction workers by providing local safety policies and conducting multi-frequency long-term safety training tests. The incentive function in this web prototype can motivate Chinese migrant construction workers to use this application and enhance their safety compliance. The limitations of this research include geographical restrictions and a small sample size to evaluate the effectiveness of the prototype. Future research should incorporate a larger, cross-sectional sample to assess the effectiveness of web-based safety awareness solutions, enabling more generalizable conclusions for construction workers of diverse nationalities and regions.

Near-field metasurface sensor for an early-stage breast cancer detection

In this paper, a novel and highly sensitive metasurface sensor for microwave breast tumor detection is proposed. The proposed sensor array comprises 8 × 8 small-size sensor elements that are capable of reacting to changes in both electric and magnetic fields. This allows the sensor to detect even minor variations in the surrounding medium, resulting in improved sensitivity. Additionally, designing a sensor array improves sensitivity by covering all areas of the breast tissues with multiple small sensor elements. Numerical studies have been conducted to assess the sensor sensitivity using realistic healthy and non-healthy breast models with diagnosed tumors placed at different locations within healthy breast models in the CST simulation environment at varying stand-off distances. An experiment was conducted to validate the sensor’s concept. It involved testing a metasurface sensor with phantoms resembling both healthy female breast tissues and those with a 10 mm tumor. The results from simulations and experiments demonstrate that the metasurface sensor is capable of detecting breast tumors at different distances. For safety compliance, specific absorption rate (SAR) values were obtained through both simulation and experimentation. The simulated SAR values were calculated to be 0.357 W/kg and 0.216 W/kg at 1 g and 10 g, respectively, using 17 dBm for safety. The measured SAR values were 0.101 W/kg and 0.1 W/kg at 1 g and 10 g, respectively.

Revolutionising construction safety: benefits of harnessing artificial intelligence tools for dynamic monitoring of safety compliance on construction projects in Nigeria

PurposeThis paper evaluates the benefits of harnessing artificial intelligence (AI) tools for safety compliance on construction projects in Nigeria.Design/methodology/approachThis study employed a specialised approach by combining qualitative and quantitative approach. The study carried out a brief systematic literature review (SLR) to identify the variables of the study. These variables were prepared in a questionnaire which was distributed among professionals within the Nigerian construction sector using purposive sampling. A total of 140 questionnaires were retrieved. The collected data were analysed using Relative Importance Index (RII), Ginni’s Mean (GM) and exploratory factor analysis (EFA).FindingsThe analysis revealed that all the identified benefits hold considerable importance, with an average RII of 0.86, with real-time monitoring as the most prominent advantage. However, using the GM which was 0.861, the study identified “mitigation of hazards on worksites” as the stationary benefit of AI in safety compliance.Research limitations/implicationsThe study was conducted exclusively within Nigeria’s Federal Capital Territory, using a cross-sectional survey approach.Practical implicationsThe results will be valuable for professionals and practitioners in the Nigerian construction sector, as they will acquire insights into the potential advantages of utilising AI tools for monitoring of safety compliance on construction projects.Originality/valueThe study adopted a robust approach by identifying the stationary benefit using the GM in combination with RII and EFA.

Investigation of Unsafe Construction Site Conditions Using Deep Learning Algorithms Using Unmanned Aerial Vehicles.

The rapid adoption of Unmanned Aerial Vehicles (UAVs) in the construction industry has revolutionized safety, surveying, quality monitoring, and maintenance assessment. UAVs are increasingly used to prevent accidents caused by falls from heights or being struck by falling objects by ensuring workers comply with safety protocols. This study focuses on leveraging UAV technology to enhance labor safety by monitoring the use of personal protective equipment, particularly helmets, among construction workers. The developed UAV system utilizes the tensorflow technique and an alert system to detect and identify workers not wearing helmets. Employing the high-precision, high-speed, and widely applicable Faster R-CNN method, the UAV can accurately detect construction workers with and without helmets in real-time across various site conditions. This proactive approach ensures immediate feedback and intervention, significantly reducing the risk of injuries and fatalities. Additionally, the implementation of UAVs minimizes the workload of site supervisors by automating safety inspections and monitoring, allowing for more efficient and continuous oversight. The experimental results indicate that the UAV system's high precision, recall, and processing capabilities make it a reliable and cost-effective solution for improving construction site safety. The precision, mAP, and FPS of the developed system with the R-CNN are 93.1%, 58.45%, and 27 FPS. This study demonstrates the potential of UAV technology to enhance safety compliance, protect workers, and improve the overall quality of safety management in the construction industry.

Applications and Impacts of Edible Coatings on Food Quality

Edible coatings are emerging as a significant trend in the food industry, driven by growing consumer interest in environmental issues, mainly due to concerns about the excessive use of plastics. This study aimed to perform an integrative review to identify the materials used to produce edible films and characterize their applicability for food quality and conservation. For this, the descriptors “edible films” or “edible coatings” and “food quality” or “food preservation” or “food safety” were used in the Science Direct database, resulting in 48 articles selected. Fruits and vegetables are the two food groups most studied with coatings based on hydrocolloids, protein, composite films, and lipids, with a greater emphasis on the positive impacts on their quality and conservation. Animal products have a higher frequency of studied antimicrobial effects. There is a diversity of materials used in coatings: vegetable-based, such as algae, mucilages, and fibers, as well as those of animal origin, such as gelatin and protein hydrolysates. Few studies have addressed sustainability concepts as final characteristics of coatings. In conclusion, edible coatings show promise for the food industry, offering benefits for both food and the environment. However, more studies are needed to fully explore their potential as replacements for conventional plastics, while ensuring safety and regulatory compliance.

ANALISIS KINERJA DINAS MATERIEL DAN SENJATA TNI ANGKATAN LAUT MELALUI PENDEKATAN BUDAYA ORGANISASI DAN KOMPETENSI YANG DIMODERASI AUTOMATIC ADJUSTMENT

The Indonesian Navy's weapons and electronics materials service has a very strategic function in the Indonesian Navy. one of its functions is to carry out planning and continuous evaluation of activities in the field of electronics and weapons including ammunition material, navigation, electronic instruments, drones, simulators, sensors, controls and weapons, sensors, controls and weapons. The type of research used in this research is qualitative. The location of this research is the Indonesian Navy's weapons and electronics materials service, Subdiharsewaco Disharkap Koarmada I, Subdiharsewaco Disharkap Koarmada II, Subdiharsewaco Disharkap Koarmada III, Disharsewaco Disharkap Kolinlamil, Subdisren Disharmat Kormar. The analysis tool used is NVIVO 12. The results of the research are that the planning and budget proposed by Dissenlekal are in accordance with Dissenlekal's needs, but with the automatic adjustment, planning cannot reach 100%. The organizational culture of the Indonesian Navy's weapons and electronics materiel service reflects a good, positive, supportive and inclusive work environment. The competency of personnel in this organization is very good, with in-depth knowledge and high skills. The performance of personnel in this organization is very good, with high quality and quantity of work, consistent punctuality, and strong occupational safety awareness and compliance. Organizational culture and competence influence organizational performance. The Indonesian Navy's weapons and electronics materials service has strong adaptability in dealing with budget changes resulting from the automatic adjustment program. The existence of automatic adjustments affects organizational performance but is not significant. With a good organizational culture and competence, good performance will result despite automatic adjustments.

Assessing the Level of Radiation Protection and Safety Compliance of Radiographers Currently Employed in the Makkah Cluster Hospitals

Assessing the Level of Radiation Protection and Safety Compliance of Radiographers Currently Employed in the Makkah Cluster Hospitals

Advanced earth grid monitoring for HV network safety compliance

ABSTRACT Electrical energy is a critical component for human comfort, but mismanagement of this energy can lead to human injury and even fatalities. High voltage safety compliance hinges on the presence of an adequate earthing system within the infrastructure. Various factors influence the effectiveness of the earthing system, including soil resistivity in the surrounding area and the availability of auxiliary paths for fault currents. Weather conditions, changes in the surrounding environment, and alterations within the high-voltage network significantly impact these elements. Any modifications to the auxiliary path conditions can have severe consequences on the network’s safety compliance. The current industry practice lacks continuous monitoring of the earth grid and fault current paths, with no provision for frequent current injection tests on the entire earth grid system. To close the existing gap, this paper proposes a novel approach through the introduction of an Earthing IoT Monitoring system. This system enables network owners to monitor safety compliance across the entire network, identify fault current return paths, and pinpoint any necessary preventive maintenance measures. The paper also delves into the crucial roles played by soil resistivity and split factors in the earthing system domain. A case study is included to support the innovative nature of the proposed system.

Hyperspectral Imaging Combined with Machine Learning Can Be Used for Rapid and Non-Destructive Monitoring of Residual Nitrite in Emulsified Pork Sausages

The non-destructive and rapid monitoring system for residual nitrite content in processed meat products is critical for ensuring food safety and regulatory compliance. This study was performed to investigate the application of hyperspectral imaging in combination with machine learning algorithms to predict and monitor residual nitrite concentrations in emulsified pork sausages. The emulsified pork sausage was formulated with 1.5% (w/w) sodium chloride, 0.3% (w/w) sodium tripolyphosphate, 0.5% (w/w) ascorbic acid, and sodium nitrite at concentrations of 0, 30, 60, 90, 120, and 150 mg/kg, based on total sample weight. Hyperspectral imaging measurements were conducted by capturing images of the cross-sections and lateral sides of sausage samples in a linescan mode, covering the spectral range of 1000–2500 nm. The analysis revealed that higher nitrite concentrations could influence the protein matrix and hydrogen-bonding capacities, which might cause increased reflectance at approximately 1080 nm and 1280 nm. Machine learning models, including XGBoost, CATboost, and LightGBM, were employed to analyze the hyperspectral data. XGBoost demonstrated the best performance, achieving an R2 of 0.999 and a root mean squared error of 0.095, highlighting its high predictive accuracy. This integration of hyperspectral imaging with advanced machine learning algorithms offers a non-destructive and real-time method for monitoring residual nitrite content in processed meat products, noticeably improving quality control processes in the meat industry. Additionally, real-time implementation in industrial settings could further streamline quality control and enhance operational efficiency. Further research should focus on validating these findings with larger sample sizes and more diverse datasets to ensure robustness.

EM Radiation Thermal Effects Simulation Study on a Realistic Female Model at Some Frequencies

The purpose of research is to develop a computer simulation based mobile phone safety testing scheme that is well suited for testing any mobile phone antenna at different communication frequencies and various realistic scenarios. It has been shown how feasible the study of realistic models is, what difficulties may occur, what effects, moments appear in the modeling process. The aim of the study is also to show the need for changes in the standard of mobile phone safety testing and to investigate the possibilities of implementing these changes. It is preferable for manufacturers to perform testing using human realistic models through numerical calculations and conduct safety compliance testing under realistic conditions to produce more realistic picture. Computer modeling gives the possibility to consider various realistic models, realistic scenarios and different tissue dielectric properties according to the frequency. It was investigated how mobile phone antenna radiation parameters (S11 reflection coefficient) change according to the various positions of the hand and fingers at standard communication 2100 MHz and 3700 MHz frequencies; were estimated Specific Absorption Rate (SAR) values in the human head and their dependence on S11 parameters were studied. Based on the obtained results, it has been shown that the preferred S11 behavior should be one of the indicators in the phone safety standards. For this, manufacturers should carry out mobile phone antenna matching/S11 parameter testing with free space.

Association of hospital safety climate and compliance with occupational safety practices among nurse interns: A cross-sectional study using canonical correlation analysis.

Nurse interns may be at a similar or higher risk than registered nurses. The key elements and mechanisms involved in the effects of safety climate on safety performance are not well understood. This study explores the relationship between the perceived hospital safety climate and compliance with occupational safety practices among nurse interns. A cross-sectional study was conducted among 178 nurse interns in three tertiary university hospitals in Chongqing city, China. The Chinese version of the Hospital Safety Climate Scale (HSCS) was used to measure the perceived hospital safety climate of nurse interns. Compliance behavior was measured using the Compliance with Occupational Safety Practice Scale (COSPS). Canonical correlation analysis and multiple linear regression modeling were used to examine their relationship. Total scores for the HSCS and COSPS were 92 (80,100) and 185 (175,185) [M (P25, P75)], respectively. Canonical correlation coefficients for canonical variates 1 and 2 were 0.636 (p < 0.001) and 0.414 (p < 0.001), respectively. Nurse interns' compliance with occupational safety practices was mainly influenced by management support, feedback/training, personal protective and engineering control equipment availability, and absence of job hindrance. Multiple linear regression showed that management support of HSCS accounted for 37.1% of the variance in compliance (β = 0.283, p = 0.039). Nurse interns reported high levels of perceived hospital safety climate and compliance with occupational safety practices. Younger nurse interns reported a lower level of perceived hospital safety climate. Nurse educators can improve interns' compliance by promoting better management support, feedback/training, personal protective and engineering control equipment availability, and fewer job hindrance.

Determinants of Occupational Health and Safety Compliance by Malaysian SMEs

Occupational safety and health (OSH) are a critical component of effective business governance. Efficient management of occupational safety and health fosters potential for growth and sustainability, and conversely. Disregarding occupational safety and health negatively impacts all stakeholders, from individual workers to national healthcare systems. This indicates that stakeholders can benefit from enhanced OSH compliance via consistent approaches. The primary principle of global OSH compliance is the mitigation and reduction of accidents, incidents, and diseases. A comparable viewpoint is relevant for small and medium-sized firms (SMEs), including those in Malaysia. This study investigated the factors influencing OSH compliance among Malaysian SMEs using a quantitative research methodology. The impact of five critical determinants: top management support, human resource practices, training and education, organisational attitude, and organisational awareness, on the attainment of OSH compliance was evaluated, drawing from literature support. A survey was done utilising convenience sampling with 400 SMEs in Malaysia. Data was gathered from 380 responding SMEs and examined using structural equation modelling (SEM) with partial least squares (PLS). The statistical findings indicated that human resource practices, organisational attitudes, and organisational awareness were key predictors of occupational safety and health compliance in the sampled Malaysian SMEs. The significance of administering OSH focused human resource policy, particularly the HR practice of endorsing safety and related training programs, has facilitated enhanced support for OSH training programs and employee awareness. The findings indicated that SMEs’ practice of displaying hazardous warning signs and promoting incident reporting has resulted in improved occupational safety and health compliance. The level of SMEs’ awareness regarding the necessity to review standard operating procedures before initiating work, safety information related to hazardous materials, understanding the risks associated with chemical substances, and the segregation of waste materials prior to disposal has facilitated effective OSH compliance among the participating SMEs. The investigation yielded multiple implications derived from the results obtained.

Enhancing work safety behavior through supply chain safety management in small and medium sized manufacturing suppliers.

Enhancing work safety behaviors among Small and Medium-Sized Manufacturing Suppliers (SMMs) is crucial for establishing a more secure and efficient supply chain. Since the foundation of safety lies in positive prevention, it is crucial that SMMs adopt proactive and pro-social work safety behaviors that transcend mere compliance with standard regulations. Present-day diversified supply chain safety management apply varying degrees of pressures on SMMs. The effectiveness of such pressures, as well as their potential to spawn advanced safety behaviors in SMMs, is a matter of investigation. This research investigates the impact of Supply Chain Safety Management Pressure(SCSMP) on the SMMs' Work Safety Behaviors(WSB). A theoretical framework is constructed, grounded in institutional theory and theory of planned behavior, which earmarks three distinct dimensions of SCSMP: Coercive Pressure(CP), Mimetic Pressure(MP), and Normative Pressure(NP). The survey of 265 SMMs facilitated an assessment of the SMMs' Willingness for Responses(WR), which includes their Willingness for Adaptive Responses(WAR) and Willingness for Co-creative Responses(WCR). Subsequently, the resulting WSB entail Safety Compliance Behavior(SCB), Proactive Safety Behavior(PSB), and Pro-social Safety Behavior(PsSB). Among these, SCB is categorized as a basic safety behavior, while PSB and PsSB which emphasize voluntary, active, and cooperative actions, are classified as advanced safety behaviors. Our research findings underscore the substantial influence of the SCSMP in shaping WSB. WR serves as a critical intermediary, connecting external pressures with internal organizational practices. In particular, WCR is instrumental in the formation of advanced safety behavior. The theoretical contribution of this research is manifested in its enhancement of our comprehension regarding the determinants of WSB among SMMs. Furthermore, it addresses the literature gap in elucidating the effectiveness of supply chain safety management and the mechanisms behind the formation of WSB. The practical significance lies in elevating the overall safety standards throughout the supply chain and minimizing safety-related hazards among SMMs.

A multi-criteria decision-making approach for prioritizing factors influencing healthcare workers' safety performance: A case of a women's hospital

This study was designed to examine the influence of organizational and individual-level factors on the safety performance of healthcare workers at a women's hospital. Healthcare workers in different occupational groups enrolled in the current study. A questionnaire was used for data collection, and the data were analyzed using an integrated multi-criteria decision-making (MCDM) approach. The entropy method was applied to prioritize influential factors, including safety climate, perceived organizational support for safety, perceived supervisor support for safety, safety voice, organizational resilience, and individual resilience, and the technique for order preference by similarity to an ideal solution (TOPSIS) was employed to rank the alternatives (healthcare workers in different occupational groups). The finding of the entropy method illustrated that perceived organizational support for safety and organizational resilience had the highest influence on healthcare workers' safety performance. The other most influential factor was individual resilience. Regarding safety performance components, safety compliance was more important than safety participation. TOPSIS results suggested that radiologists, nurses, and midwives experienced higher safety performance levels than the other occupational groups in the study women's hospital. The findings of this study demonstrated that organizational and individual-level factors such as safety climate, perceived organizational and supervisor support for safety, and resilience-related factors significantly influence healthcare workers' safety performance, and compliance with safety rules and procedures is essential to achieve better safety performance.

Microfluidic Detection Platform for Determination of Ractopamine in Food.

A novel microfluidic ractopamine (RAC) detection platform consisting of a microfluidic RAC chip and a smart analysis device is proposed for the determination of RAC concentration in meat samples. This technology utilizes gold nanoparticles (AuNPs) modified with glutamic acid (GLU) and polyethyleneimine (PEI) to measure RAC concentration in food products. When RAC is present, AuNPs aggregate through hydrogen bonding, causing noticeable changes in their optical properties, which are detected using a self-built UV-visible micro-spectrophotometer. Within the range of 5 to 80 ppb, a linear relationship exists between the absorbance ratio (A693nm/A518nm) (Y) and RAC concentration (X), expressed as Y = 0.0054X + 0.4690, with a high coefficient of determination (R2 = 0.9943). This method exhibits a detection limit of 1.0 ppb and achieves results within 3 min. The practical utility of this microfluidic assay is exemplified through the evaluation of RAC concentrations in 50 commercially available meat samples. The variance between concentrations measured using this platform and those determined via liquid chromatography-tandem mass spectrometry (LC-MS/MS) is less than 8.33%. These results underscore the viability of the microfluidic detection platform as a rapid and cost-effective solution for ensuring food safety and regulatory compliance within the livestock industry.