Method For Quantitative Analysis Research Articles

Visual dual-mode aptasensor for non-small cell lung cancer exosome detection via HRP self-coupling enhanced oxidized iridium nanoparticle aggregation.

The main reason for the high mortality rate of non-small cell lung cancer is that patients are usually diagnosed at an advanced stage of the disease. Exosomes, small membrane vesicles secreted by normal cells or tumor cells, play a significant role in the progression of NSCLC. This study successfully optimized the preparation of artificial nanoenzymes self-coupling with horseradish peroxidase (IrO2NPs@HRP-AptCD63), without adding any ligand, demonstrating remarkable catalytic activity suitable for detecting the EGFR protein on the surface of NSCLC exosomes. When fused with the CD63 aptamer for identifying NSCLC exosomes, IrO2NPs@HRP showed enhanced catalytic activity in the 3,3',5,5'-tetramethylbenzidine-H2O2 oxidation-reduction system, thereby enhancing the colorimetric signal. This phenomenon can be distinguished by the naked eye and quantified using a UV-Vis spectrophotometer. Meanwhile, as the redox reaction occurs, the current signal of 3,3',5,5'-tetramethylbenzidine-H2O2, acting as an electrolyte, changes. The developed aptasensor generates dual-mode signal outputs, firstly, to visually assess the samples for their positive or negative status, and subsequently employ more in-depth electrochemical or colorimetric analysis methods for a detailed quantitative analysis of suspected positive samples. The detection limits of electrochemical analysis and colorimetric analysis were 0.9 × 103particles/mL and 0.14 × 103particles/mL, respectively. Compared with traditional biomarkers such as CA125, this method exhibits exceptional specificity, capable of simultaneously distinguishing serum exosomes of healthy volunteers, COPD patients, and NSCLC patients, promoting exosome detection in mouse models for tumor monitoring. Additionally, it elucidates the changes in EGFR protein expression on the surface of serum exosomes throughout the developmental trajectory.

Establishment of collection methods and laboratory testing methods for active pharmaceutical ingredient in the workplace air

Objective: To establish collection methods and laboratory testing methods for qualitative and quantitative analysis of 9 typical active pharmaceutical ingredient in the workplace air. Methods: In December 2021, a mixed solution of nine analytes was prepared and then dispersed in aerosol state to simulate sampling. Glass fiber filter membrane was selected as air collector and collected active pharmaceutical ingredient in the air at a rate of 2.0 L/min for 15 minutes. Then, the obtained filter membrane samples were eluted with 25%ACN/75%MeOH. Finally, the eluent was qualitatively and quantitatively analyzed with liquid chromatography-triple quadrupole mass spectrometer. Results: This method could effectively collect active pharmaceutical ingredient in the air, with an average sampling efficiency of more than 98.5%. The linear correlation coefficient r was greater than 0.9990. The lower limit of quantification for each analyte ranged from 0.6~500.0 ng/ml, and the average recovery rate ranged from 97.6%~102.5%. Conclusion: This method could simultaneously collect 9 active pharmaceutical ingredient in the workplace air, and could provide accurate qualitative and quantitative analysis in subsequent laboratory tests.

A Low-cost and Rapid Method for Determination of Five Flavonoids in Herbal Medicines with Rutin by HPLC-UV at Equal Absorption Wavelength

Background: Flavonoid is a type of active constituent in herbs and always used as the quality control markers of herbal medicines. Owing to the extensive diversity of flavonoids, numerous reference compounds are necessitated for the analysis of flavonoids, and some are usually very expensive, which engenders challenges in the analysis of flavonoids in herbal medicines. Consequently, the development of a simple, rapid, and reference compounds saving method is important for the determination of flavonoids in herbal medicines. Objective: In order to develop a high-performance liquid chromatography (HPLC) method for the determination of 5 flavonoids (mangiferin, hesperidin, baicalin, buddleoside, and rutin) in five herbal medicines (Anemarrhenae rhizome, Sophorae flos, Citri reticulatae pericarpium, Scutellariae radix, and Chrysanthemi indici flos) with rutin. Methods: Five herbal medicine samples were prepared according to the Chinese Pharmacopoeia which includes ultrasound and reflux methods. The separation of the sample was performed on a PoroShell 120 EC-C18 (4.6 mm×100 mm, 2.7 µm) by gradient elution with 0.1% formic acid and acetonitrile at a flow rate of 1.0 mL/min. The wavelengths were set as follows: Anemarrhenae rhizome (363 nm), Sophorae flos (256 nm), Citri reticulatae pericarpium (236 nm), Scutellariae radix (263 nm), Chrysanthemi indici flos (354 nm). Results: The method validation showed that the established HPLC method was accurate and stable for quantitative analysis of flavonoids in five herbal medicines. The comparative analysis revealed that the determination results of the current HPLC method and Chinese Pharmacopoeia method are consistent, exhibiting less than 1% relative error. Remarkably, the developed HPLC method needs one cheapest reference compound (rutin) and costs 8 min for sample HPLC analysis. Conclusion: The developed HPLC method for quantitative analysis of five flavonoids in five herbal medicines is simple, rapid, and reference compound saving, which provides a good alternative method for quality control of flavonoids in herbal medicines.

Compositional analysis and quantitative evaluation of organic emissions from asphalt materials: Improvements and refinements

The organic emissions resulting from the use and application of asphalt materials can pose significant risks to plant, animal life and human health, consequently, it is crucial to conduct compositional analysis and quantitative evaluation of organic emissions from asphalt materials. In this study, the qualitative and quantitative analysis method of organic emissions from asphalt materials was developed based on headspace gas chromatography-mass spectrometry (HS-GC-MS), selected ion monitoring (SIM) mode, internal standard method and calibration curve. The spiked recovery and surrogate standard recovery were employed to validate the method. The results show the excellent accuracy, precision, and reliability of the HS-GC-MS quantitative analysis method. And the results provide confirmation that total volatile organic compounds (TVOCs), polycyclic aromatic hydrocarbons (PAHs), and n-alkanes can indeed be identified as typical organic emissions originating from asphalt materials. Furthermore, the study successfully identifies benzothiazole, cyclohexyl disulfide, and N-(1,3-dimethylbutyl)-N′-phenyl-1,4-phenylenediamine as characteristic emissions in crumb rubber-modified asphalt (CRMA). The inclusion of the styrene-butadiene-styrene (SBS) modifier results in a significant reduction in n-alkane emissions by 41.11%, PAHs emissions by 25.22%, and TVOCs emissions by 47.21% in comparison to the base asphalt, demonstrating the effective inhibitory effect of the SBS modifier on organic emissions. When compared to the base asphalt, the addition of crumb rubber results in increased emissions of n-alkanes by 12.68% and PAHs by 50.60%, as well as the introduction of the emissions associated with CRMA characteristic compounds, indicating that the emission issue of CRMA is particularly prominent.

ASSESSMENT OF THE EFFICIENCY OF MARKETING BUDGETS ON THE B2C E-COMMERCE MARKET

Introduction. In the conditions of the rapid development of e-commerce in the B2C market, it is important to ensure the effective use of marketing budgets to achieve competitive advantages. Evaluating the effectiveness of marketing spend allows businesses to optimize resources, increase return on investment, and reach a larger target audience. This requires the formation of methodological approaches for evaluating and improving the effectiveness of marketing budgets in this area. The purpose of the article. The purpose of the study is to study approaches to evaluating the effectiveness of marketing budgets in the B2C e-commerce market in order to determine the principles of increasing the effectiveness of their use. Methods. The research methodology includes a comprehensive approach combining quantitative and qualitative methods of analysis. In particular, for the in-depth study of specific examples of successful marketing strategies, such methods as economic modeling, the method of analysis and synthesis, and comparison were used. Results. The article examines approaches to evaluating the effectiveness of marketing costs in the B2C e-commerce sector, focusing on different channels, strategies and the corresponding profitability of marketing costs. The current market trends of the functioning of e-commerce platforms were analyzed and the main factors affecting the effectiveness of the use of marketing budgets of business entities were identified. The trends of the global growth of digital commerce volumes in the context of B2C sales and its functional specificity are clarified. It was determined that personalization, segmentation of customers and integration of multi-channel strategies significantly increase the efficiency of using marketing budgets. The principles of optimization of marketing costs based on the implementation of automated systems for data analysis and forecasting of consumer behavior were studied. The influence of the latest technologies, such as artificial intelligence and machine learning, on the effectiveness of using marketing budgets is considered. Conclusions. It has been proven that a reliable assessment of the effectiveness of marketing budgets in the B2C market determines a number of key aspects that ensure the maximum return on marketing investments of a business entity. At the same time, the concept of effectiveness of marketing budgets consists in a targeted approach implemented on the basis of personalization, segmentation and multi-channel integration.

Tingkat Kecemasan Preoperasi pada Anak di Instalasi Bedah Sentral Rumah Sakit Brayat Minulya Surakarta

Introduction: Preoperative is the initial stage of perioperative care which begins when the patient enters the reception room and ends when the patient is transferred to the operating table for surgery. At this stage, most people who undergo it will feel anxious, including pediatric patients. Pediatric patients often exhibit preoperative anxiety that influences intra- and postoperative nursing care. Mapping preoperative children's anxiety levels as a basis for determining preoperative treatment strategies for pediatric patients in the IBS Hospital reception room. Brayat Minulya needs to be done. Purpose: This study aims to identify the preoperative anxiety level of school-aged children in hospitals. Brayat Minulya Surakarta. Method: This research design is a descriptive study with a survey approach. Data collection was carried out using the Hamilton Anxiety Rating Scale (HARS) questionnaire. Sampling used total sampling with a sample size of 62 respondents who had adjusted to the inclusion and exclusion criteria. Data were analyzed using quantitative descriptive analysis methods. Results: Description of anxiety in preoperative school age children with no anxiety as many as 5 respondents (8.06%), mild anxiety as many as 21 respondents (33.87%), moderate anxiety as many as 27 respondents (43.55%), severe anxiety as many as 9 respondents (14.52%), and no respondents had very severe anxiety/panic. Conclusion: The number of children with moderate levels of anxiety is the largest, namely 43.55%. Future research can measure the relationship between gender and surgical experience with children's preoperative anxiety levels and use the gold standard, the State-Trait Anxiety Inventory for Children (STAIC) to measure children's anxiety levels.

Quantitative analysis of debonding gaps in concrete-filled steel tubes on the Qinghai-Tibet Plateau under severely harsh conditions

In recent years, the maximum span of concrete-filled steel tube (CFST) arch bridges has substantially increased to nearly 700 m, rendering it a preferred bridge type for traffic nodes located in mountainous regions and deep canyons owing to its robust earthquake resistance and adaptability to varying terrain. Construction defects, particularly debonding gaps, significantly diminish the structural bearing capacity of these bridges. This study aims to realize the accurate quantitative calculation of debonding gaps in CFSTs through ultrasonic non-destructive testing. The first wave's acoustic time and overall ultrasonic pulse velocity (UPV) were employed as the state variables of ultrasonic pulse propagation in CFSTs with debonding gaps. Ultrasonic non-destructive tests were conducted on CFST specimens produced in the Qinghai-Tibet Plateau and Guangxi. An approximate calculation path of ultrasonic propagation in CFSTs was proposed, and the differences in the UPVs of CFSTs produced at different air pressures were analyzed. A calculation model of the UPVs of CFSTs was formulated using different air pressure influence coefficients. Additionally, a numerical simulation of the ultrasonic energy transfer in CFSTs with diverse debonding gaps was performed, elucidating the propagation mechanism of ultrasonic energy across the three-phase steel-concrete-air interface in CFSTs. The propagation law of ultrasonic waves in CFSTs was verified through dynamic ultrasonic energy snapshots and the state variable calculation results. Based on the experimental and numerical findings, a quantitative analysis method and correlation model for CFST debonding gaps were proposed, based on their UPVs at different air pressures. The quantitative calculation model was modified by analyzing the values measured at an actual CFST bridge, enabling the accurate quantitative analysis and calculation of the degree and scope of debonding gaps in CFSTs.

Application of Heterogeneous Data Analysis based on SEA Grid in User Investment Analysis

To solve the problem of yield calculation in complex investment scenarios, a time-cost double-weighted rate of return calculation method based on SEA grid is proposed, and its effectiveness is verified by comparing with traditional methods and researching the quantitative evaluation and analysis method of user investment based on structured data. To solve the above problems, a data-heterogeneous federated learning method based on user investment analysis FedPSG is proposed, which changes the data form transmitted from the client to the server from model parameters to model scores, and only a small number of clients need to upload model parameters to the server in each round of training, thereby reducing communication costs. At the same time, a model retraining strategy is proposed, which uses server data to train the global model for second iteration, and further improves the model performance by alleviating the impact of data heterogeneity on federated learning. The method of event dimension analysis of user investment is designed, and a credibility index is proposed to evaluate the analysis results. Experiments show that by combining event data, it can effectively provide users with event factors in the fluctuation of investment profit and loss, and help users better analyze their own investments.

Contribution of Agroecological Practices to Household Food Availability: A Case Study of Singida District

Globally, there are urgent calls for transformation of agriculture and food systems to address food unavailability, food insecurity and environmental challenges. Agroecological practices have been promoted as one of the solutions, which have potential to address these challenges. Nonetheless, there is limited evidence regarding the question whether agroecology can indeed enhance food availability among smallholder farmers in Sub-Saharan Africa, Tanzania inclusive. Thus, the study was conducted to examines how the implementation of agroecological practices contribute to achieving food availability at household level by comparing between farmers who are members of Farmer Research Network (FRN) (implementers) and non-FRN farmers (non-implementers) using a case of Singida district. The study employed a cross-sectional research design, and an integration of both quantitative and qualitative data collection and analysis methods. Interviews involved a total of 160 respondents who were randomly selected from household sampling frameworks. Focus group discussions (FGDs) and in-depth interviews were conducted to gather complementary data. On one hand, quantitative data were analyzed using Statistical Package for Social Sciences (SPSS) software whereby descriptive statistics and an inferential statistic (multiple linear regression) were determined. On the other hand, qualitative data were analyzed using thematic content analysis. The findings revealed, more than half (68%) and 15% of FRN farmers were in the medium and high categories of implementation of agroecological practices, contrary to non-FRN farmers, the majority (76%) were in low and none in high categories respectively. Based on alaysed data, the most common applied practices by both FRN and non-FRN farmers were: (i) the use of organic fertilizers (farm yard manure and compost manure (96%); (ii) intercropping (88%); (iii) crop rotation (82%); and integration of crop and livestock (79%). In addition, results indicate a significant association between the level of implementation of agroecological practices and food availability (p-value = 0.000). FRNs’ farmers were food secure as compared to non-FRN farmers just due to campaign and capacity building training offered to them. There is a need for a capacity development program to speed up agroecological intensification for sustainable food systems. Thus, it is very essential for public and private organizations to develop capacity building strategies or programmes to impart farmers with knowledge and skills on agroecological revolution.

Multi-residue determination of biocides in dairy products and slurry feed using QuEChERS extraction and liquid chromatography combined with high resolution mass spectrometry (LC-ESI-QOrbitrap™-MS)

Given that the determination of biocides in food and feed is currently not routinely done, more information on these compounds is useful for consumer's safety. This work describes a sensitive and reliable method for quantitative analysis of a wide range of biocides in dairy products and slurry feed. The method comprises acetate-buffered QuEChERS extraction without clean-up. Analyses were performed by LC-Q-Orbitrap™-MS and a full-scan acquisition event without fragmentation was followed by five fragmentation events (data-independent acquisition–DIA). The quantitative validation was performed according to SANTE/11312/2021 at 10, 50 and 200 ng g−1 spiking levels, and the results showed that the vast majority of the compounds met the criteria for trueness and precision. The LOQ was 10 ng g−1 for the majority of biocides depending on the matrix. The method was successfully applied to quantify biocides in dairy products and feed.

Factors associated with the Indonesian workforce’ Pneumonia Vaccination Intention: A Convergent Parallel Study

Pneumonia is part of Acute Respiratory Infections (ARI) that has high disease burden not only in the infants but also among Indonesian adult workforce. Following data from Indonesia medical trend by marsh mercer in 2023, Acute Respiratory Infections (ARI) and Pneumonia showed significant burden in the workplace and recognized as one of highest cases, medical claim, productivity loss and hospitalization. Despite the availability of the vaccine to prevent Pneumonia, the vaccination utilization remains very low in Indonesia workforce and adult in general (Utomo, 2023). This study is aiming to understand better what are the factors that associated with the workforce’ Pneumonia vaccination intention especially after COVID-19 pandemic. This study adopts (Ajzen, 1991) Theory of Planned Behavior (TPB) in explaining the variables (Attitude, Subjective Norm, Perceived Behavior Control and knowledge) that influencing the vaccination intention among Indonesian workforce. This study applies a convergent parallel study with quantitative data analysis and qualitative data analysis are performed parallelly, followed with data integration as summary. The quantitative data is collected through online survey with non-probability sampling & purposive method. Total 151 adult respondents provided their response. The qualitative data is collected through semi-structured interview with total 5 respondents of key identified stakeholders. This study utilized Partial Least Square Structural Equation Modelling (PLS SEM) as data analysis method for quantitative and Thematic Analysis for qualitative method. The results show that attitude, perceived behavior control and knowledge of Acute Respiratory Infections are positively influenced the Pneumonia vaccination intention while subjective norm is not. This study also found the underlying cause of low preventive measurement like vaccination are due to several reasons like the belief of curative is the basic medical needs in the workplace, providing vaccination coverage is part of talent retain/attract strategy, additional cost burden in providing vaccination coverage. Lower awareness on vaccination benefit in general, diseases burden & Prevention of Pneumonia & ARI are the key blockers of the lower vaccination acceptance as preventive measurement in the workplace setting in Indonesia. Lastly, Influenza Vaccination and mask wearing is the most common preventive measurement that embraced by the employer and the employee. This study contributes the application of Extended Theory Planned Behaviour towards vaccination intention among Indonesia workforce for Pneumonia Vaccine and provide extensive insights and recommendation to the multi stakeholders on the strategy to put prevention through vaccination to tackle the high burden of Acute Respiratory Infection Especially Pneumonia among Indonesia workforce.

RESEARCH TRENDS OF TECHNOLOGY INTEGRATION IN TEACHING ENGLISH GRAMMAR AS FOREIGN LANGUAGE: BIBLIOMETRIC ANALYSIS IN 2013-2023

Technological developments play an important role in education. To find out about these developments, it is necessary to conduct an analysis. One analysis that can be done to find out the development of technology is through bibliometric analysis. Bibliometric analysis is an analysis that explains the mapping process based on research trends that utilize analysis of metadata processing. Metadata is the main source for research results that researchers take from Scopus as a primary database. Researchers used quantitative and qualitative analysis methods. The purpose of this study is to analyze and determine the development trend of research related to the integration of technology in teaching grammar as a foreign language from 2013-2023. Data search and database analysis using Scopus software, Ms. Excel and supported by VOSviewer. The results of the research analysis show that in the last ten years from 2013-2023, the research trend on technology integration in teaching grammar as a foreign language is still relatively new and began to develop rapidly in 2022. The core topics that are still very new are in the time span between 2020-2022 which discuss multimedia systems, multimedia technology, educational computing. Meanwhile, the topic that is often discussed is multimedia technology which is then concluded to be the latest research map in the future.

Multi-component quantitative analysis of LIBS using adaptively optimized multi-branch CNN

Multi-component quantitative analysis of laser-induced breakdown spectroscopy (LIBS) is very important for industrial process control, food safety and space exploration. Due to the strong background interference and complex matrix effect, traditional quantitative analysis methods are difficult to realize accurate multi-component regression. Deep learning has the advantages of automatically extracting full-spectrum features and strong nonlinear modeling capabilities, which provides new opportunities for advancing the progress of LIBS quantitative analysis. However, due to the large difference of spectral line intensity and spectral cross-interference, existing deep learning models have limited performance for simultaneous multi-component regression. To this end, a novel adaptively optimized multi-branch convolution neural network (AOMB-CNN) framework is proposed for multi-component quantitative analysis of LIBS. Multi-branch structure is adopted to ensure the accuracy of multi-component content simultaneously. Dynamic weighted loss function and Bayesian optimization algorithm are used to adaptively optimize the deep learning model. The results demonstrate that the AOMB-CNN can effectively improve the performance of multi-component regression on 2 LIBS datasets compared with the traditional quantitative analysis methods. The root mean square error (RMSE) of 8 components of the ChemCam test set are 2.4465, 0.3486, 1.2481, 1.3909, 0.9010, 0.8892, 0.6700, and 0.5498 respectively, and the RMSE of 4 components of the steel test sets are 1.9787, 0.3455, 0.6025 and 1.6631 respectively. The proposed method provides an end-to-end, adaptively optimized, full-spectrum deep learning solution for LIBS multi-component content measurement without human intervention.

Phytosociological Analysis of Bumdeling Ramsar site, Riverine Wetland of International Importance, Eastern Bhutan

The Kholongchu riverine wetlands in Bumdeling, Bhutan, are a unique ramsar site and crucial winter roosting grounds for the Black Necked Crane. Despite the area's notable ecological successions, recent information on plant diversity is less known from the wetland. In 2023, study was conducted to evaluate the phytodiversity and phytosociology of the Bumdeling Ramsar site (BRS) using quantitative quadrat analysis method. The study identified 165 plant species in a wetland, with Asteraceae being the most dominant family. Herbaceous plants dominate the wetland, followed by shrubs and grasses. The area has moderate floral species diversity with Simpson (0.87) and Shannon (2.59) diversity value. Floral species are evenly distributed, with no single species dominating vegetation with Simpson dominance (0.13). Menhinicks index (2.19) and Margalef (4.60) index indicate high species richness. Furthermore, Important Value Index indicated Persicaria hydropiper, Anaphalis margaritaceae, and Alnus nepalensis as the dominating and important plant species in the wetland. This study provides valuable floristic information for further scientific studies and management activities in BRS.

One Health Risk and Disease (OHRAD): a tool to prioritise the risks for epidemic-prone diseases from One Health perspective

BackgroundThe rise in epidemic-prone diseases daily poses a serious concern globally. Evidence suggests that many of these diseases are of animal origin and contribute to economic loss. Considering the limited time and other resources available for the animal and human health sectors, selecting the most urgent and significant risk factors and diseases is vital, even though all epidemic-prone diseases and associated risk factors should be addressed. The main aim of developing this tool is to provide a readily accessible instrument for prioritising risk factors and diseases that could lead to disease emergence, outbreak or epidemic.MethodsThis tool uses a quantitative and semi-quantitative multi-criteria decision analysis (MCDA) method that involves five steps: Identifying risk factors and diseases, Weighting the criteria, Risk and disease scoring, Calculating risk impact and disease burden score, and Ranking risks and diseases. It is intended to be implemented through a co-creation workshop and involves individual and group activities. The last two steps are automated in the MS Excel score sheet.ResultsThis One Health Risk and Disease (OHRAD) prioritisation tool starts with an individual activity of identifying the risks and diseases from the more extensive list. This, then, leads to a group activity of weighing the criteria and providing scores for each risk and disease. Finally, the individual risk and disease scores with the rankings are generated in this tool.ConclusionsThe outcome of this OHRAD prioritisation tool is that the top risks and diseases are prioritised for the particular context from One Health perspective. This prioritised list will help experts and officials decide which epidemic-prone diseases to focus on and for which to develop and design prevention and control measures.

Education for sustainable development in primary school: Understanding, importance, and implementation

There is no doubt that education for sustainable development (ESD) is important because it covers all areas: social, emotional, intellectual, physical, moral, etc. ESD helps people acquire the skills, knowledge, and values necessary for a successful life and a constructive contribution to society. If earlier early ESD was not at the centre of attention, recently it has become increasingly clear that early education has great potential for fostering values, behaviours, and skills that contribute to sustainable development. Despite this, ESD remains problematic due to the inadequate preparation of pre-service primary teachers in this area. It is obvious that ESD implementation in primary education is still poorly integrated.<br /> Empirical qualitative research aimed to reveal how pre-service primary school teachers understand ESD in primary school. Generally, 86 students from two Lithuanian universities, pre-service teachers of preschool and primary education, took part in the research. Verbal research data were analysed using the quantitative content analysis method.<br /> The results suggest that although ESD in early childhood is understood as significant and reasonable, however, the understanding of pre-service teachers is rather one-sided. ESD is understood as social welfare, while the natural and physical environment is the least expressed in their understanding structure. Meanwhile, the implementation of ESD is understood as a normal educational process, applying known techniques and methods. It is necessary to strive for the young generation to be characterised by responsibility, a sense of community, conservation, and citizenship, to understand the harmony of the surrounding world and their activities. For that purpose, changes in the education are needed to integrate the necessary ESD elements, including both managerial and educational processes.

Spectroscopic assessment and quantitative analysis of the trace element composition of vegetable additives to meat products

In this scientific work, using the method of laser-induced breakdown spectroscopy (LIBS), the spectra of beef samples and impurities in meat products, namely, banana, pineapple, kiwi, bergamot, poria coconut, Chinese angelica, chicken blood vine, were measured by using developed experimental devices. The purpose of the research was to evaluate the qualitative characteristics of additives to meat semi-finished products for the potential formation of the desired properties of the products due to the analysis of the received spectrograms of trace elements of the samples when applying the LIBS method, quantitative analysis for processing the received information. The determined values of the electron temperature of the plasma, the electron density of the used raw material samples, and the assessment of the local heat balance were used as evaluation criteria. When processing the obtained data, the characteristics of the laser-induced plasma surface of the presented samples were analyzed; the electron temperature and electron density were determined, and a quantitative analysis of trace elements was carried out. LIBS technology allows rapid real-time monitoring and qualitative analysis of trace elements online and over long distances. During the research, it turned out that quantitative analysis requires further study and optimisation of experimental conditions, such as pre-treatment of samples. These conditions optimise defocusing, double laser pulse, and sample temperature, which increases the signal/noise ratio of all spectral lines. The combination of fluorescence spectroscopy and Raman technology enables higher detection sensitivity and better molecule control, creating a quantitative analysis method model that can reduce matrix effects and overcome the self-absorption effect. Among the difficulties of using LIBS technology, several elements can be noted online simultaneously, compared to Raman. The combination of spectroscopy and fluorescence spectroscopy can obtain more comprehensive information about the composition of materials, which can become a potential platform for monitoring trace elements in food products.

Analisis Perbandingan Fungsionalitas dan Keluwesan antara Perplexity dan Phind.Com dalam Memenuhi Kebutuhan Belajar Mahasiswa di Lingkungan Perguruan Tinggi

This study aims to analyze the comparison of functionality and flexibility between Perplexity and Phind.com in meeting student communication needs in a university environment. In an increasingly advanced digital era, the use of artificial intelligence-based applications is very important to support the learning process and student communication. Perplexity is known for its fast and accurate search capabilities while Phind.com superior personalization and flexibility in the delivery of information. This research uses a mixture of qualitative and quantitative data collection and analysis methods. A survey was conducted among 200 students and semi-structured interviews were also conducted among 10 students at Hasanuddin University who had used the Perplexity application and Phind.com. Data collection techniques used in this research are questionnaires, interviews with informants who are considered competent and in accordance with the topics discussed. The results of this research show that Perplexity and Phind.com. has different functionality and flexibility in meeting student learning needs. In the case of researchers, Perplexity excels at providing access to quality and diverse learning materials and features that support independent learning. Meanwhile, Phind.com excels in providing an active discussion forum and learning community, as well as features that support collaboration and interaction between students. Both applications have their own advantages and disadvantages. The right application for students depends on their individual learning needs and learning style.

Nitrogen and zinc doped carbon quantum dots for rapid and accurate detection of mercury ions in cosmetics

Rapid and reliable detection technologies for mercury ion in cosmetics are critical for public health. In this study, we synthesized nitrogen and zinc doped carbon quantum dots (N, Zn-CDs) with bright and stable fluorescence using the hydrothermal method. Structure characterization reveals the abundant oxygen- and nitrogen-containing functional groups on the surface of N, Zn-CDs, which readily coordinate with Hg2+, resulting in fluorescence quenching. Basing on this, a rapid and simple quantitative analysis method for Hg2+ detection was designed. By optimizing the detection conditions, a good linear relationship in the range of 0 to 10 μM and a low detection limit of 0.023 μM were achieved. Besides, interference tests demonstrate the presence of other metal ions does not interfere with Hg2+ detection. When detecting Hg2+ in four types of cosmetics spiked with the ion, the sensor achieved recovery rates of 98.27 %, 110.03 %, 100.90 %, and 108.80 %, respectively, with relative standard deviations all under 6.90 %, demonstrating its capability to identify Hg2+ in complex matrices. This research offers a novel approach for the rapid and accurate detection of mercury in cosmetics.

HPLC-QQQ-MS/MS-based authentication and determination of free and bound sialic acids content in human, bovine, sheep, goat milk, and infant formula.

An accurate method for qualitative and quantitative analysis of lipid-bound (LB), protein-bound (PB), oligosaccharides-bound, and free sialic acids in milk was developed by using high-performance liquid chromatography -triple quadrupole-tandem mass spectrometer. The profile of free and bound sialic acids in milk (human, bovine, goat, and sheep) and infant formula (IF) was examined in the present study. Human milk contains only N-acetylneuraminic acid (Neu5Ac) and was mainly present in the form of oligosaccharide-bound. The content of total Neu5Ac (T-Neu5Ac), free and bound Neu5Ac in human milk decreased with the prolongation of lactation. The most intriguing finding was the increase in the proportion of PB and LB sialic acids. The sialic acids in bovine and sheep milk were mainly PB and oligosaccharides-bound Neu5Ac. T-Neu5Ac in goat milk (GM) was 67.44-89.72µg/mL and was mainly PB Neu5Ac, but total N-glycolylneuraminic acid (T-Neu5Gc) content of GM can be as high as 100.01µg/mL. The concentration of T-Neu5Gc in sheep and GM was significantly higher than that of bovine milk (BM). T-Neu5Gc content of GM -based IF was 264.86µg/g, whereas T-Neu5Gc content of BM -based IF was less (2.26-17.01µg/g). Additionally, our results found that there were also sialic acids in IF ingredients, which were mainly bound with protein and oligosaccharides, primarily derived from desalted whey powder and whey protein concentrate.