Analysis Techniques Research Articles

Rapid Microbial Profiling through Multimodal Biosensors for Transversal Analysis.

The intricate interactions between host and microbial communities hold significant implications for biology and medicine. However, traditional microbial profiling methods face limitations in processing time, measurement of absolute abundance, detection of low biomass, discrimination between live and dead cells, and functional analysis. This study introduces a rapid multimodal microbial characterization platform, Multimodal Biosensors for Transversal Analysis (MBioTA), for capturing the taxonomy, viability, and functional genes of the microbiota. The platform incorporates single cell biosensors, scalable microwell arrays, and automated image processing for rapid transversal analysis in as few as 2 h. The multimodal biosensors simultaneously characterize the taxon, viability, and functional gene expression of individual cells. By automating the image processing workflow, the single cell analysis techniques enable the quantification of bacteria with sensitivity down to 0.0075%, showcasing its capability in detecting low biomass samples. We illustrate the applicability of the MBioTA platform through the transversal analysis of the gut microbiota composition, viability, and functionality in a familial Alzheimer's disease mouse model. The effectiveness, rapid turnaround, and scalability of the MBioTA platform will facilitate its application from basic research to clinical diagnostics, potentially revolutionizing our understanding and management of diseases associated with microbe-host interactions.

Analysis of Indonesian Language Proficiency Test in High School Students' Reading Section

This study aims to identify and evaluate high school students' scores in Sukabumi City on the reading section of the Indonesian Language Proficiency Test. The research method used a descriptive with a qualitative approach. The subjects of this research are students from SMA Muhammadiyah in Sukabumi City, consisting of 5 classes, namely classes X, XI A, XI B, XII IPS, and XII IPA. The instrument used was an Indonesian Language Proficiency Test sheet containing 40 questions. The data analysis technique used was a qualitative descriptive method to describe the results of the students' proficiency data. The results showed that the initial abilities of the five classes in high school in Sukabumi City, namely classes X, XI A, XI B, XII IPS, and XII IPA, obtained an average score of 170, while the abilities in the second test of the five classes in high school in Sukabumi City, namely classes X, XI A, XI B, XII IPS, and XII IPA, obtained an average score of 194. The results of the data from the two test sessions, the scores of the UKBI test in the reading category, showed that from the five classes, the results for test 1 show an average student ability score of 170 with a "Madya" predicate, while test 2 shows an average student ability score of 194 with a "Madya" predicate, indicating an improvement between test 1 and test 2. Although the reading proficiency predicate remains "Madya" between test 1 and test 2.

Pengaruh Konflik Kerja Dan Beban Kerja Terhadap Kinerja Karyawan

This study aims to determine 1) the effect of work conflict on employee performance, 2) the effect of workload effect on employee performance, 3) the effect work conflict and workload have simultaneously on employee performance at Badan Penanggulangan Bencana Daerah Kabupaten Gunung Mas. The population in this research were all employees of Badan Penanggulangan Bencana Daerah Kabupaten Gunung Mas. The technique used in this research is satured sampling method and data collection technique by distributing questionnaires to 37 respondens. Data analysis technique in this study is multiple linear regression using the IBM SPSS 26 program. The results in this study indicate that: 1) work conflict has negative effect to employee, 2) workload has no effect on employee performance, 3) work conflict and workload have a simultaneous effect on employee performance.

Analisis Analisis Semiotika dalam Siaran Televisi Sekitaran Etam di TVRI Kalimantan Timur

This research aims to explain and describe the elements of semiotic theory by C.S. Pierce (icon, index, and symbol) in the Television Broadcast Sekitaran Etam for the November 2022 Period on TVRI East Kalimantan. The Sekitaran Etam uses the Kutai language with the Tenggarong dialect. This broadcast discusses the culture and local wisdom of the people of East Kalimantan. The method used in this research is a qualitative research method. Data and data sources in this research are quotes containing icons, indexes, and symbols in the script Sekitaran Etam for the November 2022 period on TVRI East Kalimantan. The data analysis technique uses qualitative research techniques, according to Miles and Huberman, namely data reduction, data presentation, and concluding/verification. The research results on television broadcasts Sekitaran Etam for November 2022 on TVRI East Kalimantan found five data. Based on the five data found, eight icons, eight indexes, and seven symbols exist

Fcg-Former: Identification of Functional Groups in FTIR Spectra Using Enhanced Transformer-Based Model.

Deep learning (DL) is becoming more popular as a useful tool in various scientific domains, especially in chemistry applications. In the infrared spectroscopy field, where identifying functional groups in unknown compounds poses a significant challenge, there is a growing need for innovative approaches to streamline and enhance analysis processes. This study introduces a transformative approach leveraging a DL methodology based on transformer attention models. With a data set containing approximately 8677 spectra, our model utilizes self-attention mechanisms to capture complex spectral features and precisely predict 17 functional groups, outperforming conventional architectures in both functional group prediction accuracy and compound-level precision. The success of our approach underscores the potential of transformer-based methodologies in enhancing spectral analysis techniques.

Pengawasan Kedisiplinan Peserta Didik di SMA Negeri 1 Pangkalan Lampam

This research aims to understand the process of student discipline supervision at SMA Negeri 1 Pangkalan Lampam. The researcher uses a descriptive qualitative approach with a qualitative research type. The research method employed is descriptive, with data collection techniques including observation, interviews, and documentation. The data analysis techniques used are data reduction, data presentation, and data verification. The validity of the data in this research is tested using source triangulation, technique triangulation, and time triangulation. The analysis results indicate that the process of supervising student discipline at SMA Negeri 1 Pangkalan Lampam involves monitoring, inspection, guidance and direction, disciplinary actions, and corrective measures. The research concludes that the supervision of student discipline at SMA Negeri 1 Pangkalan Lampam is not yet optimal, particularly in the stages of guidance or direction and disciplinary actions. This is evidenced by the students' lack of awareness regarding the importance of discipline in school

Pelaksanaan Program Tahfidz Al-Qur’an di MAN 2 Palembang

The aim of this research is to understand the implementation of the tahfidz program at MAN 2 Palembang and to identify the supporting and inhibiting factors during the implementation of the Qur’an memorization program at MAN 2 Palembang. This research employs a qualitative research method, and the informants include the head of the madrasa, the head of the Darul Ulum tahfidz house, tahfidz supervisors, and students. The data collection techniques used in this study are observation, interviews, and documentation. The data analysis techniques employed are data reduction, data presentation, and conclusion drawing. The validity of the data is tested using triangulation, which includes source triangulation, technique triangulation, and time triangulation. The results of the research indicate that the tahfidz Qur’an program at MAN 2 Palembang is carried out through direction, motivation, communication, and coordination in each process, starting with determining the program's objectives, defining success indicators, setting the implementation schedule, and appointing program coordinators. The supporting factors include adequate facilities and infrastructure, quality human resources, the presence of rewards and punishments, and the program's timing. The inhibiting factors include the students' own attitudes and their surrounding environment

Examination of social media usage habits of generation Z

Undoubtedly, social media is one of the significant components of computer and internet technologies. It offers users the opportunity to share emotions, thoughts, and life experiences through various means such as text, images, and videos on the internet. In doing so, it not only provides a multifaceted communication and interaction opportunity for users of all ages but also creates a dynamic and entertaining parallel universe. This universe shapes and transforms individual, social, and cultural life, as well as habits. With the daily increase in user numbers, social media has become an integral part of our lives. The primary objective of this study is to determine the social media usage habits of fourth-grade students, known as Generation Z. The research was conducted using semi-structured interviews, a qualitative data collection method. The universe of the study consisted of 654 fourth-grade students attending state schools in seven different provincial centers representing the seven geographical regions of Turkey during the 2021–2022 academic year. The data were collected using an interview form developed for this research and analyzed with the content analysis technique. According to the research findings, it was determined that approximately three-quarters of primary school fourth-grade students use social media on a daily basis. Moreover, most participants stated that they use social media for educational, communicative, and entertainment purposes. The most preferred social media platforms by students were identified as YouTube, WhatsApp, TikTok, and Instagram.

Trends in the Use of Augmented Reality from Tangible Interfaces in School Learning : A Systematic Literature Review

This study aims to analyze trends in the use of augmented reality from tangible interfaces in the context of formal and informal education. This study employed a systematic literature review (SLR) method adapted from the PRISMA model. This research used the Publish or Perish application to search for various relevant scientific articles taken from international journals, Scopus, with a range of 2019-2023. The data analysis technique for this research used thematic analysis. The development of AR media showed significant improvement, especially in the aspect of increasingly realistic and diverse user interfaces, enabling closer integration with the curriculum and presenting more engaging learning experiences. The interactive and collaborative features of AR applications showed great potential for enhancing student interaction with learning materials through immersive and interactive visual experiences. In addition, such collaborative features could also facilitate cooperation between students, creating a more dynamic and effective learning environment in schools. This research emphasized the importance of using appropriate research methods to deepen the understanding of the development of AR media in education and the potential of AR applications in creating more interactive and collaborative learning experiences in school environments.

Pengaruh Profitabilitas dan Leverage Terhadap Perataan Laba Dengan Pertumbuhan Perusahaan Sebagai Variabel Pemoderasi (Studi Kasus Pada Perusahaan Manufaktur Yang Terdaftar di Index Kompas100)

This study aims to determine the relationship between variables that are suspected to be factors of income smoothing, namely profitability and leverage on income smoothing and to determine whether company growth can strengthen the relationship between profitability and leverage on income smoothing. Research using a quantitative approach with secondary data in the form of financial statements. Using purposive sampling technique, with the criteria that manufacturing companies listed on the Indonesia Stock Exchange (IDX) in 2021-2023 and included in the kompas100 index, 16 companies with 48 samples were obtained. The analysis technique used is multiple linear regression and Moderated Regression Analysis (MRA), with the help of SPSS 26. This study found that profitability has a significant positive effect on income smoothing, while leverage has no effect on income smoothing, company growth is able to strengthen the relationship between profitability and leverage on income smoothing.

Need Analysis of Primary School Promotion Media

Background: In an increasingly competitive world of education, the importance of school promotion is increasingly felt. Schools must be able to compete to attract prospective students and parents. Purpose: This research aims to determine the needs of schools in carrying out promotions. Design and methods: This study used qualitative research methods. Needs analysis is based on the Hutchinson & Waters model which focuses on aspects necessities, lacks, and wants. Interviews were conducted with four PPDB administrators including teachers, PPDB Chair, and School Administrative Staff. The analysis technique used is thematic analysis, while validation is carried out using member checking. Results: The results of the study show that schools need promotions in printed form. With this, schools can achieve their promotional goals in a more widespread and efficient manner.

New high sensitivity approach for a quantitative visualization of the continuous whole-field stress evolution in digital photoelasticity

Digital photoelasticity is a widely used technique for experimental stress analysis on mechanical models subjected to loading conditions, due to its ability to reveal the stress information through color fringe patterns and consequently demodulate it computationally to achieve a quantitative evaluation. In this process, some limitations persist, such as, expertise dependence, experimental repeatability, sensitivity to load increments, and weak performance under experimental conditions, especially in time-dependent scenarios. In response to these weaknesses, the method “Quantitative Visualization of the Continuous Whole-Field Stress Evolution” introduced the ability to perform a complete demodulation of the fringe patterns generated in time-dependent applications, achieving high performance compared to conventional photoelasticity methods. This paper proposes a new highly sensitive approach for a quantitative visualization of the continuous whole-field stress evolution in digital photoelasticity by incorporating an inverse signal process and a multi-stage strategy. The algorithm aims to ensure the performance under high fringe order conditions while exhibiting high sensitivity in cases where the maximum stress obtained is less than one fringe order. The results presented validate its effectiveness in demodulating full-field stress distributions, especially in scenarios where the loading condition induces fringe orders less than one, thus contributing to the broader applicability of digital photoelasticity.

Optimization method for capacity of BESS considering charge‐discharge cycle and renewable energy penetration rate

AbstractIn order to achieve the “carbon peaking and carbon neutrality” goals, we must vigorously develop renewable energy power generation. As the penetration of renewables progressively escalates, the corresponding demand for battery energy storage systems (BESS) within the power grid rises concomitantly. This paper presents an innovative optimization approach for configuring BESS, taking into account the incremental variations in renewable energy penetration levels and BESS charge‐discharge cycles. Employing incremental analytical techniques and pivotal metrics such as capacity elasticity, the proposed method determines the optimal penetration rate and corresponding BESS capacity outcomes for deploying energy storage systems. An example analysis of a rural power distribution benchmark is carried out by using the method in this paper, which proves the effectiveness of the method in this paper. This methodology was substantiated through its application to a case study of a rural power distribution benchmark, thereby validating its efficacy. Furthermore, it was compared with the particle swarm optimization, providing a comparative assessment of their relative performance.

Sentiment analysis technique on product reviews using Inception Recurrent Convolutional Neural Network with ResNet Transfer Learning

ABSTRACT Nowadays, online shopping has become a typical option for customers to make purchases due to the rapid technological development of the Internet. Sentiment analysis (SA) of a huge count of user reviews on e-commerce sites can successfully increase the fulfillment of user, but it is difficult so far to predict the precise sentiment polarizations of the user evaluations owing to the variations on textual arrangement, sequence length, and complex logic. In this manuscript, Inception Recurrent Convolutional Neural Network with ResNet Transfer Learning by Red Fox Optimization Algorithm using sentiment analysis on product review (IRCNN-ResNet-RFOA-SA-PR) is proposed. Here, the input data are collected through Amazon Product Reviews database and then preprocessing the input data by using whitespace tokenization, Snowball stemming, and Gensim lemmatization. The preprocessing data are supplied to the ternary pattern and discrete wavelet transform for feature extraction. Then the optimal features are selected by Fire Hawk Optimization Algorithm. After that, IRCNN-ResNet recommends the product based on SA. Finally, IRCNN-ResNet parameter is optimized by RFOA. The proposed method attains 22.37%, 31.08%, and 21.90% greater accuracy and 19.37%, 21.08%, and 25.40% greater precision when compared with existing models, such as machine learning-based SA-PR including new term weighting with feature selection mode, weighted word embedding with deep neural network-based SA-PR, and SA for e-commerce PRs in Chinese utilizing sentiment lexicon with deep learning, respectively.

Can equity-based crowdfunding be a fast and effective financing model for early-stage startups?

ABSTRACT Nowadays, with the developments in the field of information, communication, and technology, we see that the way of doing business has changed in many sectors, and startups are the ones leading this change. For this reason, the importance of startups for national economies is increasing daily. One of the most fundamental conditions for increasing the number of successful startups in countries is access to the financing that startups need. Especially for early-stage startups with limited access to traditional financing instruments, providing financing from alternative sources becomes very important. For this reason, alternative financing models such as crowdfunding have become more important for startups today. This study investigated the importance of crowdfunding, its types, and, in particular, whether equity-based crowdfunding can be used effectively in financing early-stage startups. In the study, the general survey model and document analysis technique were used to examine the campaigns and campaign details of platforms with equity-based crowdfunding licenses. The findings obtained were classified according to their purpose. As a result of the research, it was concluded that equity-based crowdfunding can be used to finance seed and early-stage startups, and that the average amount of funding that startups need in the early stage can be obtained with very short campaign periods.

From preparation to post-processing: Insights into evoked and induced cortical activity during pre-cued motor reactions in children and adolescents

IntroductionThe motor system undergoes significant development throughout childhood and adolescence. The contingent negative variation (CNV), a brain response reflecting preparation for upcoming actions, offers valuable insights into these changes. However, previous CNV studies of motor preparation have primarily focused on adults, leaving a gap in our understanding of how cortical activity related to motor planning and execution matures in children and adolescents. MethodsThe study addresses this gap by investigating the maturation of motor preparation, pre-activation, and post-processing in 46 healthy, right-handed children and adolescents aged 5–16 years. To overcome the resolution limitations of previous studies, we combined 64-electrode high-density Electroencephalography (EEG) and advanced analysis techniques, such as event-related potentials (ERPs), mu-rhythm desynchronization as well as source localization approaches. The combined analyses provided an in-depth understanding of cortical activity during motor control. ResultsOur data showed that children exhibited prolonged reaction times, increased errors, and a distinct pattern of cortical activation compared to adolescents. The findings suggest that the supplementary motor area (SMA) plays a progressively stronger role in motor planning and response evaluation as children age. Additionally, we observe a decrease in sensory processing and post-movement activity with development, potentially reflecting increased efficiency. Interestingly, adolescent subjects, unlike young adults in previous studies, did not yet show contralateral activation of motor areas during the motor preparation phase (late CNV). ConclusionThe progressive increase in SMA activation and distinct cortical activation patterns in younger participants suggest immature motor areas. These immature regions might be a primary cause underlying the age-related increase in motor action control efficiency. Additionally, the study demonstrates a prolonged maturation of cortical motor areas, extending well into early adulthood, challenging the assumption that motor control is fully developed by late adolescence. This research, extending fundamental knowledge of motor control development, offers valuable insights that lay the foundation for understanding and treating motor control difficulties.

Emerald Ash Borer Infestation-Induced Elevated Negative Correlations and Core Genera Shift in the Endophyte Community of Fraxinus bungeana

Endophytes, prevalent in plants, mediate plant–insect interactions. Nevertheless, our understanding of the key members of endophyte communities involved in inhibiting or assisting EAB infestation remains limited. Employing ITS and 16S rRNA high-throughput sequencing, along with network analysis techniques, we conducted a comprehensive investigation into the reaction of endophytic fungi and bacteria within F. bungeana phloem by comparing EAB-infested and uninfected samples. Our findings reveal that EAB infestation significantly impacts the endophytic communities, altering both their diversity and overall structure. Interestingly, both endophytic fungi and bacteria exhibited distinct patterns in response to the infestation. For instance, in the EAB-infested phloem, the fungi abundance remained unchanged, but diversity decreased significantly. Conversely, bacterial abundance increased, without significant diversity changes. The fungi community structure altered significantly, which was not observed in bacteria. The bacterial composition in the infested phloem underwent significant changes, characterized by a substantial decrease in beneficial species abundance, whereas the fungal composition remained largely unaffected. In network analysis, the endophytes in infested phloem exhibited a modular topology, demonstrating greater complexity due to an augmented number of network nodes, elevated negative correlations, and a core genera shift compared to those observed in healthy phloem. Our findings increase understanding of plant–insect–microorganism relationships, crucial for pest control, considering endophytic roles in plant defense.

The Influence of the Project Based Learning Model on Science Learning Outcomes in Class V Students at MIS Al Huda Langkat

This research aims to determine the science learning outcomes of students by applying the project based learning model in class V MIS AL Huda, Langkat. This type of research is quasi-experimental with a pretest and posttest control group design. The population of this study was all students in class V of MIS AL Huda, Langkat, totaling 30 students. The sampling technique used was probability sampling with a stage random sampling technique, namely 30 students were sampled as part of the population. The instrument used is a test sheet to measure student learning outcomes. The data analysis technique used is descriptive statistical analysis and inferential statistical analysis with the independent sample test. Based on the results of the descriptive analysis, the average obtained for the two groups, in the control class before and after implementing the project based learning model, was a pretest score of 54.33 and a posttest score of 76.33. In the experimental class by applying the project based learning model, the pretest average was 43.33 and the posttest average was 71.33. Based on the results of the independent sample-test, it shows that the t test value with a sig value < a = 0.05 (0.000 < 0.05) indicates that H1 is accepted. The results of the research show that there is a significant difference between the experimental class (VA) applying the project based learning model and the control class (VB) on science learning outcomes for MIS AL Huda, Langkat students.

Hubungan Pengetahuan dan Persepsi terhadap Minat Kepesertaan BPJS Ketenagakerjaan pada Pedagang di Pasar Badung Kota Denpasar

This research aims to predict factors related to interest in BPJS Employment participation among market traders using knowledge and perception variables. This type of research is quantitative research using data obtained from the method of distributing questionnaires to 90 respondents, namely traders at Badung Market, Denpasar City with slovin calculations in determining the sample. The data analysis techniques used are Pearson Correlation and Multiple Linear Regression. The results of the correlation test show between knowledge and interest in participation is 0,579, which has a medium level of correlation, and between perception and interest in participation is 0,561, which also has a medium level of correlation. Then, the results of the coefficient of determination (R2) show that the participation interest variable can be influenced by knowledge and perception variables as much as 40,1%, while the remaining 59,9% is influenced by other variables outside the research. Furthermore, the results of the t test show that the tcount value of the knowledge variable is 3,849, which shows that Ho1 is rejected and Hk1 is accepted, meaning that knowledge has a positive and significant effect on partial interest in participation. The tcount value for the perception variable is 3,417, which shows that Ho2 is rejected and Hk2 is accepted, meaning that perception has a positive and significant effect on partial participation interest. Finally, the results of the F test show that the Fcount value is 30,739, which shows that Ho3 is rejected and Hk3 is accepted, meaning that knowledge and perception have a positive and significant effect on participation interest simultaneously.

Step-by-Step Metagenomics for Food Microbiome Analysis: A Detailed Review

This review article offers a comprehensive overview of the current understanding of using metagenomic tools in food microbiome research. It covers the scientific foundation and practical application of genetic analysis techniques for microbial material from food, including bioinformatic analysis and data interpretation. The method discussed in the article for analyzing microorganisms in food without traditional culture methods is known as food metagenomics. This approach, along with other omics technologies such as nutrigenomics, proteomics, metabolomics, and transcriptomics, collectively forms the field of foodomics. Food metagenomics allows swift and thorough examination of bacteria and potential metabolic pathways by utilizing foodomic databases. Despite its established scientific basis and available bioinformatics resources, the research approach of food metagenomics outlined in the article is not yet widely implemented in industry. The authors believe that the integration of next-generation sequencing (NGS) with rapidly advancing digital technologies such as artificial intelligence (AI), the Internet of Things (IoT), and big data will facilitate the widespread adoption of this research strategy in microbial analysis for the food industry. This adoption is expected to enhance food safety and product quality in the near future.