Analysis Procedure Research Articles

Research-based Analytical Procedures to Evaluate Diabetic Biomarkers and Related Parameters: In Vitro and In Vivo Methods.

The degenerative tendency of diabetes leads to micro- and macrovascular complications due to abnormal levels of biochemicals, particularly in patients with poor diabetic control. Diabetes is supposed to be treated by reducing blood glucose levels, scavenging free radicals, and maintaining other relevant parameters close to normal ranges. In preclinical studies, numerous in vivo trials on animals as well as in vitro tests are used to assess the antidiabetic and antioxidant effects of the test substances. Since a substance that performs poorly in vitro won't perform better in vivo, the outcomes of in vitro studies can be utilized as a direct indicator of in vivo activities. The objective of the present study is to provide research scholars with a comprehensive overview of laboratory methods and procedures for a few selected diabetic biomarkers and related parameters. The search was conducted on scientific database portals such as ScienceDirect, PubMed, Google Scholar, BASE, DOAJ, etc. Conclusion: The development of new biomarkers is greatly facilitated by modern technology such as cell culture research, lipidomics study, microRNA biomarkers, machine learning techniques, and improved electron microscopies. These biomarkers do, however, have some usage restrictions. There is a critical need to find more accurate and sensitive biomarkers. With a few modifications, these biomarkers can be used with or even replace conventional markers of diabetes.

Extending the concepts of response spectrum analysis to nonlinear static analysis: Does it make sense?

The study presented in this paper aims to assess the recent novelties proposed by new generation building codes about the extension of some concepts at the base of linear analyses to the procedures of nonlinear static analysis. The nonlinear static analysis (pushover) is an extensively adopted approach by engineers and practitioners for purpose of assessing the seismic performance of new and existing buildings, although several drawbacks characterize this methodology, as evidenced by the existing scientific literature. In order to overcome the well-known limitations characterizing nonlinear static analysis, and to offer an alternative to nonlinear dynamic analysis, the recent upgrades of some building codes, such as the Italian one, provide different rules to employ in nonlinear static procedures. Among these new provisions, one regards the possibility to use a horizontal load profile proportional to the storey forces derived from a response spectrum analysis in all cases (i.e., also for irregular buildings). The main goal of this study is to demonstrate the reliability of this new load profile when strong irregularities arise. To this scope, the seismic behaviour of a sample of archetype buildings characterized by increasing in-height irregularity was investigated. The sample of buildings was subdivided in two subsets characterized by different design levels, one conceived by considering the prescriptions of the new Italian building code and one designed according to the oldest Italian building code (i.e., without considering anti-seismic details). The sample of buildings, simulating new and existing cases, was firstly modelled and after investigated through nonlinear static analyses by employing both traditional (i.e., inverse triangular- and uniform-like) and new (i.e., derived from response spectrum analysis) load profiles. After, nonlinear dynamic analyses were run, in order to assess the capacity of both traditional and new load profiles to capture the dynamic behaviour of the investigated archetype buildings. The performed analysis campaign demonstrated the efficiency of the new load profile proposed by the code, and the output of the work provided an answer to the main question posed by the authors: does it make sense to extend the concepts of response spectrum analysis to nonlinear static analysis?

Transdiagnostic markers across the psychosis continuum: a systematic review and meta-analysis of resting state fMRI studies.

https://osf.io/, identifier (ycqpz).

Implementation a Different Segmentation Method as a Joint Prior Model to Reconstruction the Bayesian Image analysis

The basic concepts in the application of Bayesian approaches to image analysis have been introduced as advanced method. The Bayesian approach contains benefits in respect to image analysis and interpretation because it permits the use of prior knowledge concerning the situation under study. This paper use to investigate the application of some of the well-known procedures (determines number labels of image under several conditions like noise of image, resolution of image) for the Bayesian image analysis with segmentation as a joint prior model in order to estimate the Maximum Likelihood (ML). Markov random field with segmentation which resulted by mean of posterior (MP). This paper contains several sections. Firstly, includes introduction about the image analysis with, Bayes frame work and statistical background to Markov's random field and its relationship through Markov Chain Monte Carlo. Secondly, section, which directly addresses solutions by using a principle of segmentation, which is a representation in threshold, is simply type introduced. Thirdly, presents the description of Experiment of Segmentation by depend on histogram also study of the factor (one prior) and the same model by adding segmentation (joint prior) based on techniques presented in the previously section are discussed . Fourthly, this section contains on the second prior implementation and simulation by using phantom data (Castle from south East Asia) also steps of estimation. Finally, result of experiment as well as estimation and summary.

Development and Performance Evaluation of a New Test Kit for Quantifying the Degree of DNA Fragmentation.

PCR-based genetic testing of agricultural products and foods is widely used for detecting various analytical targets such as genetically modified organisms and food allergens. However, it is difficult to obtain accurate genetic testing results from processed foods because DNA is fragmented by heat and pressure during food processing. Thus we previously developed an analytical method to quantitatively evaluate the degree of DNA fragmentation for the purpose of quality control of genetic testing for processed foods. Our previous analytical method requires four PCR primer sets, resulting in high reagent costs and heavy analytical workloads. Therefore, we attempted to develop an easy-to-use test kit for quantifying the degree of DNA fragmentation and to evaluate its analytical performance. To simplify the analysis procedure, we used only two primer sets. In addition, no-fragmentation control templates were prepared to obtain stable measurement results. The precision of the simplified analysis was evaluated through blind tests among laboratories. It was confirmed that plant species and extracted DNA concentrations had little effect on analysis with the newly developed test kit. In addition, the analytical values indicating the degree of DNA fragmentation exhibited small variability among laboratories. We confirmed the high practicality of the developed test kit. Because DNA fragmentation in cells is a universal phenomenon, we anticipate that the test kit will be used not only for quality control of genetic testing but also for food testing, medical diagnostics and other applications in a range of fields. The newly developed test kit enables quantitative evaluation of the degree of DNA fragmentation in a simple manner.

Methods and computational tools to study eukaryotic cell migration in vitro.

Cellular movement is essential for many vital biological functions where it plays a pivotal role both at the single cell level, such as during division or differentiation, and at the macroscopic level within tissues, where coordinated migration is crucial for proper morphogenesis. It also has an impact on various pathological processes, one for all, cancer spreading. Cell migration is a complex phenomenon and diverse experimental methods have been developed aimed at dissecting and analysing its distinct facets independently. In parallel, corresponding analytical procedures and tools have been devised to gain deep insight and interpret experimental results. Here we review established experimental techniques designed to investigate specific aspects of cell migration and present a broad collection of historical as well as cutting-edge computational tools used in quantitative analysis of cell motion.

High-dimensional mediation analysis for continuous outcome with confounders using overlap weighting method in observational epigenetic study

BackgroundMediation analysis is a powerful tool to identify factors mediating the causal pathway of exposure to health outcomes. Mediation analysis has been extended to study a large number of potential mediators in high-dimensional data settings. The presence of confounding in observational studies is inevitable. Hence, it’s an essential part of high-dimensional mediation analysis (HDMA) to adjust for the potential confounders. Although the propensity score (PS) related method such as propensity score regression adjustment (PSR) and inverse probability weighting (IPW) has been proposed to tackle this problem, the characteristics with extreme propensity score distribution of the PS-based method would result in the biased estimation.MethodsIn this article, we integrated the overlapping weighting (OW) technique into HDMA workflow and proposed a concise and powerful high-dimensional mediation analysis procedure consisting of OW confounding adjustment, sure independence screening (SIS), de-biased Lasso penalization, and joint-significance testing underlying the mixture null distribution. We compared the proposed method with the existing method consisting of PS-based confounding adjustment, SIS, minimax concave penalty (MCP) variable selection, and classical joint-significance testing.ResultsSimulation studies demonstrate the proposed procedure has the best performance in mediator selection and estimation. The proposed procedure yielded the highest true positive rate, acceptable false discovery proportion level, and lower mean square error. In the empirical study based on the GSE117859 dataset in the Gene Expression Omnibus database using the proposed method, we found that smoking history may lead to the estimated natural killer (NK) cell level reduction through the mediation effect of some methylation markers, mainly including methylation sites cg13917614 in CNP gene and cg16893868 in LILRA2 gene.ConclusionsThe proposed method has higher power, sufficient false discovery rate control, and precise mediation effect estimation. Meanwhile, it is feasible to be implemented with the presence of confounders. Hence, our method is worth considering in HDMA studies.

Molecular distinctions of bronchoalveolar and alveolar organoids under differentiation conditions.

The bronchoalveolar organoid (BAO) model is increasingly acknowledged as an ex-vivo platform that accurately emulates the structural and functional attributes of proximal airway tissue. The transition from bronchoalveolar progenitor cells to alveolar organoids is a common event during the generation of BAOs. However, there is a pressing need for comprehensive analysis to elucidate the molecular distinctions characterizing the pre-differentiated and post-differentiated states within BAO models. This study established a murine BAO model and subsequently triggered its differentiation. Thereafter, a suite of multidimensional analytical procedures was employed, including the morphological recognition and examination of organoids utilizing an established artificial intelligence (AI) image tracking system, quantification of cellular composition, proteomic profiling and immunoblots of selected proteins. Our investigation yielded a detailed evaluation of the morphologic, cellular, and molecular variances demarcating the pre- and post-differentiation phases of the BAO model. We also identified of a potential molecular signature reflective of the observed morphological transformations. The integration of cutting-edge AI-driven image analysis with traditional cellular and molecular investigative methods has illuminated key features of this nascent model.

A suitable procedure of dose reduction factor measurements of X-ray shields during computed tomography examination - The importance of considering positional changes of an X-ray tube

During computed tomography (CT) examinations, radio-sensitive organs located outside the field of view (FOV) are usually exposed to radiation caused by both direct and scattered X-rays. Traditionally, the use of radiation protection products has been an option for reducing exposure doses. The catalog value of the dose reduction factor (DRF) for a commercial X-ray shield is generally determined by the manufacturer using a plain X-ray irradiation system to measure the difference in dose with and without the shield. In contrast, actual shielding ability measurements during clinical CT examinations are usually evaluated using a similar equation, but it is not guaranteed that the incident directions of X-rays will be the same between the measurement data with and without a shield. The purposes of this study are to introduce a novel method for evaluating DRF by accounting for the influence of the X-ray incident direction in helical scanning and to obtain knowledge about the correctness of previously reported DRF values. Experiments pertaining to chest CT examinations were performed using a human body phantom and small-type dosimeters which consist of an optically stimulated luminescence element using Al2O3:C. A total of 100 examinations were iteratively performed, both with and without a shield. The corresponding DRF was then calculated. The novelty of the proposed analysis procedure lies in a paired analysis method, where the DRF is calculated by reorganizing numerous acquired data sets with and without the shield to pair similar incident angles of X-rays. As a result, the DRF values were estimated to be 48.5 ± 4.3%, 48.7 ± 2.7%, and 48.9 ± 1.5% based on the data results within the 10–40 data sets, 40–70 data sets, and 70–100 data sets, respectively. When the DRF values were obtained by the conventional method without applying our sorting procedure, the results were 48.4 ± 8.1%, even when the 70–100 data sets were used. This result indicates that the proposed method can analyze DRF with higher accuracy. In the example of thyroid X-ray shield, while there was no significant difference in the most probable values of DRF between the conventional and proposed methods coincidentally, we believe it is important to evaluate DRF based on a scientifically correct approach because the mathematical formulas for calculating these two values differ. In conclusion, when calculating the DRF of shielding materials during CT examination, it is imperative that data analysis considers the significant impact of differences in incident X-ray directions on the measured exposure dose data.

ANALISIS DAMPAK IMPLEMENTASI STRATEGI CROSS SELLING PADA PENAMBAHAN DANA PIHAK KETIGA SERTA PENAMBAHAN JUMLAH NASABAH FUNDING DI PERUMDA BPR BANK DAERAH KOTA MADIUN

The main objective of this research is to investigate how the cross-selling strategy is applied and how it affects the collection of third party funds. Second, examine the obstacles to cross selling strategies in raising third party funds. Third, look into how the cross-selling approach is being used and how that is affecting the amount of money raised for third party funds. This study uses a field research methodology and is qualitative-descriptive in nature. Madiun City Regional Bank, People's Credit Bank (BPR), and Regional Public Company (Perumda) served as the research subjects. This study's objective is to develop a cross-selling strategy that will boost third-party funding. Documentation, interviews, and observation are methods used to collect data. The three stages of the data analysis procedure were data reduction, data display, and conclusion drawing. To determine the veracity of the data, take into account using source triangulation. First, the research's findings indicate that the Tabunganku Product becomes the primary account when cross-selling is implemented. Furthermore, you can get other services, namely having more than one savings product account, lower credit interest, receiving deposit interest and disbursing credit through your Tabunganku account. Second, the obstacles are competition with conventional banks, savings cannot be disbursed at any time, and lack of communication with customers. Third, the impact that arises is customer loyalty, increasing income, reducing time and costs, and maintaining public trust in using third party fund products.

Quantitative and qualitative phytochemical analysis of ethanol leaf extract of Pleiocarpa mutica

This research project examined Pleiocarpa mutica leaf extract, extracted from ethanol using both quantitative and qualitative phytochemical analysis. Sourced is at Ugbene-Ajima in the Uzo-Uwani Local Government Area of Enugu State, Nigeria, where fresh Pleiocarpa mutica leaves were collected. After been gathered, the newly sprouted P. mutica leaves were cleaned. We then shade-dried the leaves until they were crispy, rotating them frequently to prevent them from rotting. A mechanical grinder was utilized to reduce the dried leaves to a powdered state while a maceration flask was used to macerate 1.5 kg of the known weight of the ground leaves in 10 liters of 100% ethanol. In using a muslin cloth, the mixture was filtered into a flask with a flat bottom after being left for 72 hours with irregular stirring. Quantitative phytochemical analysis procedures identified the specific concentration of a certain chemical constituent present in a plant sample using methods such as mass spectrometry, chromatography, and spectrophotometry. This makes it possible to determine the concentration of a component in the plant material. Qualitative phytochemical analysis techniques focus on identifying the presence or absence of several chemical groups in a plant sample. Discovering the existence of substances such as alkaloids, phenols, terpenoids, and flavonoids often requires a range of chemical analyses or the use of specific reagents. Thus, the standard quantitative and qualitative phytochemical analysis technique were used to investigate the chemical composition of plants and identify bioactive compounds that may offer nutritional, medicinal, or pharmacological advantages. Hence, it has been shown that the ethanol leaves extract of P. mutica contains various concentrations of phytochemical constituents, which might be responsible for its biological activities.

Using Grounded Theory to Develop a Substantive Theory for Grandparent-Caregiving in Uganda: The GRACE Model.

Few studies have focused on developing theories to explain caregiving as performed by grandparents who provide care for their grandchildren in any setting. Theory development that is grounded in the experiences and cultural context of those being studied is needed to inform research, subsequent care, and overall well-being, especially of populations that are understudied. This manuscript was informed by Constructivist Grounded Theory, semi-structured in-depth and individual interviews. Also, three methodological phases were followed: (a) concurrent data collection and analysis procedures, (b) developing categories and relationships among them, and (c) defining the core category and building the substantive theory. The methodological steps involved in generating a substantive theory, the GRAndparent-CarEgiving (GRACE) model, are reported. Research, and subsequently the well-being and health care of grandparent-caregivers, needs to be informed by culturally congruent theories that are founded in the experiences and cultural context of the individuals being investigated.

Evaluation of extruded starch foam for glucose-supplying biomaterials

The survival rate of mesenchymal stem cells (MSC), a crucial factor in tissue engineering, is highly dependent on glucose supply. The purpose of this paper is to study the potential of starch foams as glucose suppliers. It is investigated through in vitro hydrolysis by amyloglucosidase in conditions that respect physiological constraints (37 °C and pH 7.4), including a duration of 21 days, and no stirring. Nine extruded starch foams with amylose contents ranging from 0 to 74 %, with various cell wall thicknesses (50 to 300 μm), and different crystallinities (0–30 %) were hydrolysed. These kinetics were fitted by a model which shows that the maximum rate of hydrolysis varies from 7 to 100 %, and which allows the rate of hydrolysis at 21 days to be calculated precisely. The results reveal the major role of amylose in glucose delivery kinetics, and the secondary roles of crystallinity and cell wall thickness of the foams. Additional hydrolysis of starch films revealed that thickness positively influences the amylose chain reorganisation during hydrolysis, which, in slows down and limits glucose delivery. A simple glucose delivery kinetics analysis procedure is proposed to select samples for testing as MSC glucose suppliers.

Pedagogical Skills Needs of Motor Vehicle Mechanics Work Teachers for Effective Content Delivery in Government Science and Technical Colleges in Adamawa and Taraba States

The main purpose of the study was to explore the pedagogical skills needs of motor vehicle mechanics work teachers for effective content delivery in government science and technical colleges in Adamawa and Taraba States. The study was guided by two research questions and two null hypotheses. The study was conducted in Adamawa and Taraba States using descriptive survey research design. The population of the study was 123 respondents comprising 81 MVMW teachers and 42 instructors from all the 21 BEST Centres and Government Science and Technical colleges in Adamawa and Taraba States, Nigeria. There was no sampling as the entire population was used because it was manageable. A structured questionnaire tagged: Pedagogical Skills Needs of Motor Vehicle Mechanics Works Teachers Questionnaire (PSNMVMWTQ) consisting of 30 items was validated by three experts. The Instrument was trial tested in Gombe State and the Cronbach Alpha reliability method was used to test the reliability of the instrument and a 0.84 reliability coefficient was obtained. Data collected for the study was analyzed using Statistical Package for Social Sciences (SPSS) version 27.0. Mean statistics was used to answer the two research questions while a t-test was used to test the null hypotheses at a 0.05 level of significance. The findings of the study revealed among others that pedagogical skills needed include stimulating critical thinking, designing effective evaluation procedures, and implementing appropriate instruction. Similarly, affective skills were deemed needed including effective communication, active listening, and conflict resolution. Importantly, there were no significant differences between instructors and MVMW teachers regarding the perceived importance of these skills. It is recommended that Given the identified pedagogical skills needs of motor vehicle mechanics work (MVMW) teachers, Ministries of Education should design and implement targeted training programs focusing on instructional goal identification, task analysis, instructional design, questioning techniques, and evaluation procedures.

Improved microwave-assisted saponification to reduce the variability of MOAH determination in edible oils

BackgroundMineral oil aromatic hydrocarbon (MOAH) analysis in foods is a major analytical challenge. Quantification is associated with a high uncertainty. The sources of uncertainty are multiple, but the major one is related to data interpretation and integration, which is partially derived from insufficiently efficient sample preparation. Recently, an updated ISO method for the analysis of mineral oil in fats and oils and a standard operating procedure for infant formula analysis have been published. Both methods reported significantly different (up to 1.25) distributions of the internal standards used for quantification (i.e., tri-tert-butyl benzene (TBB) and 2-methyl naphthalene (2-MN)) over the different solvent phases used in the saponification step. ResultsIn this work, a microwave-assisted saponification and extraction method was optimized for MOAH analysis to solve the problem related to the MOAH internal standards partition. The paper examines the impact of the solvent mixture used, the concentration of KOH on the partition of TBB and 2-MN, and the effect of the matrix and the washing step to extract the unsaponifiable fraction containing the mineral oils. SignificanceThe optimized procedure achieved a TBB/2-MN ratio of 1.05 ± 0.01 tested in five different fats and oils, namely, sunflower, rapeseed, coconut, palm, and extra virgin olive oils. The method can significantly contribute to reducing the uncertainty of the MOAH quantification when saponification is applied.

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Data Sets Built on FragPipe.

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a data merging scheme and a protein-centric multiple hypothesis correction scheme, enabling processed LiP-MS data sets to be more robust and less redundant. These improvements strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

A data-driven procedure for one-dimensional dynamic analysis of thin-walled beams with arbitrary cross-sections

This paper develops a one-dimensional dynamic model for thin-walled beams with arbitrary complex cross-sections in a data-driven way. In order to consider complicated deformations in the framework of a beam theory, a universal node system is first created to fit the deformed shape of a thin-walled cross-section, whether prismatic or curved, with or without symmetry. This helps to reduce the three-dimensional displacement field of the thin-walled beam to one dimension, and results in a preliminary higher-order beam model with limited precision loss. For the purpose of largely condense DOFs of the new model, a data-driven approach is proposed to identify cross-section deformation modes through the principal component analysis of free vibration deformation data of an unconstrained thin-walled beam. As a result, a compact set of core deformation modes are obtained and selected to update the preliminary model, leading to the refined higher-order beam model of high accuracy and efficiency. Examples are presented to illustrate the concrete implementation and check the effects of data-related controlling parameters of the proposed procedure. We also verify through numerical examples that the proposed model agrees well with plate/shell and other beam theories, and has remarkable advantages in physical interpretation, modeling simplicity and computation efficiency.

Comparison of Classical and Green RPLC Methods in the Determination of pKa Values of Some Piperazine Group Antihistamines.

In this study, protonation constant values and liquid chromatographic behaviors of hydrophobic cyclizine, chlorcyclizine, hydroxyzine, cinnarizine, cetirizine, meclizine, and buclizine in some water-organic solvent binary mixtures were examined for the first time using classical and green reverse phase liquid chromatography methods. In the isocratic study, the relationship of the retention time and mobile phase pH in water-organic solvent binary mixtures containing acetonitrile (45, 50, 55, 60, 65%, v/v), methanol (60, 65, 70, 75%, v/v) and ethanol (45, 50, 55, 56, 59, 60, 62, 65%, v/v) were determined at 37 °C. In the study, XBridge C18 and Gemini NX C18 columns suitable for the chemical properties of basic compounds were used. The obtained liquid chromatographic data were analyzed using the linear solvation energy relationship methodology and the SOLVER program. The aqueous protonation constant values of the investigated compounds were calculated using the linear relationship between the protonation constant data calculated in studied binary mixtures and some macroscopic constant values of the solvents used. The greenness of methods developed using three different solvents was evaluated with the Analytical Greenness Metric Approach, the Green Analytical Procedures Index, and the Green Solvent Selection Tool approaches.

Time Series Analysis of Market Dynamics within Top NFT Collection

The current investigation delves into the valuation trends of prominent Non-Fungible Token (NFT) collections, entities at the forefront of the digital economy that are redefining concepts of asset ownership and artistic appreciation. The academic import of this study is anchored in the emergent nature of NFTs and their paradigmatic shift from traditional economic models. This research aims to decipher the market value fluctuations of top NFT collections through a comprehensive time-series analysis, the application of the ARIMA model. Methodologically, the study adheres to established time-series analytical procedures, with a focus on identifying and interpreting patterns and trends within the market data. The approach synthesizes a broad spectrum of economic and cultural variables that potentially exert influence over the NFT marketplace. Results gleaned from the analysis yield insights into the price movements of NFTs, offering a juxtaposition of predicted and actual market data to deepen the understanding of this unique market sector. The implications of this research extend beyond academic interest, offering a vital resource for stakeholders within the digital economy. The discerned patterns and dynamics of NFTs, as revealed through the study, contribute to a granular understanding of digital assets, providing a scaffold for future research endeavors and practical guidance for participants in the digital art and ownership space.

An Analysis of Grammatical Errors Committed by Students in Writing Argumentative Paragraph

Writing skills are very important for students to master to help them prepare for their future. However, grammar is one of the obstacles for students in writing English. This research aims to analyze grammatical errors made by students in writing argumentative paragraphs and to analyze the sources of these errors. Second semester English Language Education students were chosen as the subjects of this research. Furthermore, in analyzing the data, this research applies a combination of descriptive qualitative and descriptive quantitative methods. Apart from that, data was collected through collecting documents from the end-of-semester tests. The data analysis procedure consists of three specific steps, namely data reduction, data presentation, and drawing conclusions/verification. The results of the research found that students made 11 types of errors with a total of 165 errors. Most of them made omission of article errors with 39 (23.63%) errors, then simple addition 33 (20%) errors, alternating form 27 (16.36%) errors, omission of to be 21 (12.72%) errors, then omission of preposition 17 (10.30%) errors, omission of plural –s with 15 (9.09%) errors, misordering 6 (3.63%) errors, regularization 3 (1.81%) errors, and finally double marking and archi-form each 1 ( 0.60%) error. In addition, sources of errors were found in four types: interlingual transfer, intralingual transfer, context of learning, and communication strategy. The majority of students made mistakes due to intralingual transfer, 119 (72.12%) errors were found, followed by interlingual transfer 41 (24.84%) errors, communication strategy 3 (1.81%), and context of learning 2 (1.21%) errors.