Number Of Samples Research Articles

Cross-domain damage identification of bridge based on generative adversarial and deep adaptation networks

Model-driven bridge damage identification based on video measurement frequently encounters challenges due to low data quality, which leads to significant discrepancy between numerical model and actual bridge, exacerbating the cross-domain problem. To address this issue, the generative adversarial network (GAN) and Deep Adaptation Network (DAN) are introduced in this paper. The principles and utilizations of the two networks are introduced, while GAN is used to generate a large number of high-quality artificial samples to enhance the learning, and DAN is used to extract generic damage features to cross the source and target domains. A damage experiment of a steel truss model bridge is conducted to validate the proposed method, and the damage identification results of the proposed method and the traditional method are compared. The identification results illustrate that the proposed method can generate a substantial number of artificial samples only using a limited number of real target samples. These artificial samples facilitate the learning of cross-domain damage features, which ultimately contributes to achieving higher accuracy in damage identification.

Work motivation of implementing nurses to improve the quality of health services

Introduction: The motivation of the implementing nurse is essential to improving the quality of health services. Implementing nurses plays a vital role in providing quality services to patients. High work motivation is crucial in enhancing nurses' performance and commitment to providing the best care. Objective: Knowing the motivation behind implementing nurses can improve the quality of health services. Method: This research is quantitative, with a cross-sectional study design using a quantitative analytical approach. The number of samples was 81 people using total sampling. The research instrument used was a questionnaire with a Likert scale. The analysis method uses the Fisher's exact test. Results: Based on the results of the analysis, these employees have discipline that is still lacking in completing work, while of the 5 respondents who have low work motivation, three respondents (3.7%) have good performance. This is because employees have effectiveness, efficiency, authority, responsibility, discipline, and good work initiative. The statistical test results using Fisher's exact test obtained p = 0.009, smaller than a = 0.05 (p < 0.05), which means Ho is accepted and Ha is rejected. This suggests there is a meaningful relationship between work motivation and. Conclusion: The researchers found that the work motivation of implementing nurses can improve the quality of health services. Implementing nurses can enhance healthcare quality, build team spirit, and achieve organisational goals. These efforts help increase patient satisfaction and improve job satisfaction and nurses' well-being. Therefore, understanding and applying compelling work motivation is the key to improving the quality of health services.

Probabilistic design and optimization of thermal protection system with variable thickness based on non-uniform aerodynamic heating

Thermal Protection System (TPS) is a critical component of space vehicles to protect them from damage by extreme aerothermal heating conditions. The uncertainty of the aerothermal heating conditions, including approaching velocities, atmospheric density, pressure, etc., significantly affects the aerothermal heating imposed on the TPS, vastly changing the initial design conditions. In this study, we developed a new uncertainty quantitative (UQ) analysis method to comprehensively consider all the uncertainty of TPS materials, structures, and aerothermal heating conditions. To address the challenges of a massive amount of input and determined optimization parameters, we first induced the response surface method and Monte Carlo algorithm to produce a large number of analysis samples for Probabilistic Design. Then, the key affecting factors, not all the input design parameters, were chosen for optimization with sequential optimization and reliability assessment (SORA) strategy by a sensitivity analysis. With such improvements, the optimization for UQ analysis becomes practical. We used this new UQ method to analyze the effects of uncertainty of the aerothermal heating conditions on the thermal protection layer. A variable thickness design is proposed to adapt the non-uniform aerothermal heating conditions for the TPS. The results show that significant light-weighting can be achieved without the reliability penalty. The optimized structure also reduces internal temperature gradients and facilitates a more uniform temperature field distribution for the TPS. This study provides a new UQ engineering design approach for the system with many designed parameters.

Determinants associated with carpal tunnel syndrome complaints

Introduction: Carpal Tunnel Syndrome (CTS) is one of the most common problems in the upper extremities caused by the narrowing of the carpal tunnel, which results in pressure on the median nerve. Increased pressure in the carpal tunnel causes compression and damage to the median nerve. Objective: determinants associated with carpal tunnel syndrome . Methods: quantitative research with a cross-sectional research design. The sampling technique in this study used a total sampling technique in which the entire population is equal to the number of samples, namely 36 people. Data obtained by using a questionnaire. The analytical method used was univariate and bivariate analysis using the chi-square test. Result: showed that there was a relationship between length of work and carpal tunnel syndrome (p-value = 0.0190. There is a relationship between age and complaints of carpal tunnel syndrome (p-value = 0.032. There is no relationship between personal protective equipment and complaints of carpal tunnel syndrome (p-value = 0.759). There is no relationship between repetitive movements and carpal tunnel syndrome (p-value = 0.787. Conclusion: It was concluded that there is a relationship between length of service and carpal tunnel syndrome complaints, there is a relationship between age and carpal tunnel syndrome complaints and there is no relationship between body mass index and carpal tunnel syndrome complaints . In this study, researchers suggest to companies to pay more attention to employees who have a long working period so as not to do excessive work and for employees to take advantage of adequate rest time to minimize the occurrence of complaints of Carpal Tunnel Syndrome (CTS).

Performance Analysis of Deep Learning and Machine Learning Methods for Music Genre Classification System

Performance Analysis of Deep Learning and Machine Learning Methods for Music Genre Classification System

Hubungan Self Efficacy dengan Kepuasan Kerja Perawat di Instalasi Rawat Inap

Nurses with a high level of self-efficacy can encourage good work results so that nurse job satisfaction increases and has a positive effect on the quality of service in the hospital. The purpose of this study was to determine the relationship between self-efficacy and job satisfaction of nurses in providing nursing care in the inpatient room of Cilegon Hospital. The research design was quantitative with a cross-sectional approach and the number of samples in this study were 112 nurses in the inpatient rooms of Cilegon Hospital. The sampling technique used was purposive sampling. Data collection was carried out using two questionnaires modified by the researcher, namely the self-efficacy questionnaire and the job satisfaction questionnaire. The data analysis used was the Chi-Square test with a CI of 95%. Based on the results of the Chi-Square test, a p value of 0.000 was obtained, which means <0.05, so it was concluded that there was a significant relationship between self-efficacy and job satisfaction of nurses in providing nursing care in inpatient rooms at Cilegon Hospital.

Research on batch multi-element rapid quantitative analysis based on standard curve assisted CF-LIBS method

Abstract This paper proposes a batch rapid quantitative analysis method for multi-element by combining the advantages of standard curve (SC) and calibration-free laser induced breakdown spectroscopy (CF-LIBS) technology to achieve synchronous, rapid, and accurate measurement of elements in a large number of samples, namely SC-assisted CF-LIBS. Al alloy standard samples, divided into calibration and test samples, were applied to validate the proposed method. The SC was built on the basis of the characteristic line of Pb, Cr in the calibration sample, and the content of Pb, Cr in the test sample was thereby calculated with a relative error of 6% and 4%, respectively. The SC built by Cr with multiple characteristic lines has better calculation results. The relative contents of 10 elements were calculated by CF-LIBS in the test sample. Subsequently, the SC-assisted CF-LIBS was executed, with the majority of calculation relative errors falling within the range of 2%–5%. Finally, the contents of Al, Na were predicted in the Al alloy. The results demonstrate that it effectively enables the rapid and accurate quantitative analysis of multi-element after a single element SC analysis of the tested samples. Furthermore, this quantitative analysis method was successfully applied to soil and astragalus samples, realizing the accurate calculation of the contents of multi-element. It is thus important to advancing LIBS quantitative analysis and its related applications.

Probabilistic Nearest Neighbors Based Locality Preserving Projections for Unsupervised Metric Learning

Dimensionality reduction based unsupervised metric learning consists in finding meaningful compact data representations previously to clustering and classification problems. One of the major aspects of these algorithms is the approximation of the underlying manifold by a weighted graph. A limitation with most manifold learning algorithms is that edge weights in the proximity graph rely heavily on the Euclidean distance, which is known to be quite sensitive to the presence of outliers. In this paper, we propose to improve the Locality Preserving Projections (LPP) algorithm by incorporating a recently proposed graph inference method called Probabilistic Nearest Neighbors (PNN), an extension of the Clustering with Adaptive Neighbors (CAN) approach, used with success in graph-based semi-supervised learning. The proposed PNN-LPP algorithm is able to achieve better classification results than regular LPP, showing competitive performance against state-of-the-art approaches for dimensionality reduction, such as the UMAP algorithm, especially in datasets with a limited number of samples.

Enhancing the epidemiological surveillance of SARS-CoV-2 using Sanger sequencing to identify circulating variants and recombinants.

Since the emergence of SARS-CoV-2 in December 2019, more than 12,000 mutations in the virus have been identified. These could cause changes in viral characteristics and directly impact global public health. The emergence of variants is a great concern due to the chance of increased transmissibility and infectivity. Sequencing for surveillance and monitoring circulating strains is extremely necessary as the early identification of new variants allows public health agencies to make faster and more effective decisions to contain the spread of the virus. In the present study, we identified circulating variants in samples collected in Belo Horizonte, Brazil, and detected a recombinant lineage using the Sanger method. The identification of lineages was done through gene amplification of SARS-CoV-2 by Reverse Transcription-Polymerase Chain Reaction (RT-PCR). By using these specific fragments, we were able to differentiate one variant of interest and five circulating variants of concern. We were also able to detect recombinants. Randomly selected samples were sequenced by either Sanger or Next Generation Sequencing (NGS). Our findings validate the effectiveness of Sanger sequencing as a powerful tool for monitoring variants. It is easy to perform and allows the analysis of a larger number of samples in countries that cannot afford NGS.

Vancomycin: An analysis and evaluation of eight population pharmacokinetic models for clinical application in general adult population.

Based on the recent guidelines for vancomycin therapeutic drug monitoring (TDM), the area under the curve to minimum inhibitory concentration ratio was to be employed combined with the usage of population pharmacokinetic (popPK) model for dosing adaptation. Yet, deploying these models in a clinical setting requires an external evaluation of their performance. This study aimed to evaluate existing vancomycin popPK models from the literature for the use in TDM within the general patient population in a clinical setting. The models under external evaluation were chosen based on a review of literature covering vancomycin popPK models developed in general adult populations. Patients' data were collected from Charles-Le Moyne Hospital (CLMH). The external evaluation was performed with NONMEM® (v7.5). Additional analyses such as evaluating the impact of number of samples on external evaluation, Bayesian forecasting, and a priori dosing regimen simulations were performed on the best performing model. Eight popPK models were evaluated with an independent dataset that included 40 patients and 252 samples. The model developed by Goti and colleagues demonstrated superior performance in diagnostic plots and population predictive performance, with bias and inaccuracy values of 0.251% and 22.7%, respectively, and for individual predictive performance, bias and inaccuracy were -4.90% and 12.1%, respectively. When limiting the independent dataset to one or two samples per patient, the Goti model exhibited inadequate predictive performance for inaccuracy, with values exceeding 30%. Moreover, the Goti model is suitable for Bayesian forecasting with at least two samples as prior for the prediction of the next trough concentration. Furthermore, the vancomycin dosing regimen that would maximize therapeutic targets of area under the curve to minimum inhibitory concentration ratio (AUC24/MIC) and trough concentrations (Ctrough) for the Goti model was 20 mg/kg/dose twice daily. Considering the superior predictive performance and potential for Bayesian forecasting in the Goti model, future research aims to test its applicability in clinical settings at CLMH, both in a priori and a posteriori scenario.

Optimal design of the side sensitive group runs double sampling (SSGRDS) X¯ scheme with estimated process parameters

The side sensitive group runs double sampling (SSGRDS) [Formula: see text] scheme is previously studied under the known process parameters (Case-K) assumption. As the process parameters are hardly known in practical situations, they must be estimated using a suitably chosen in-control (IC) Phase-I sample. However, various studies demonstrated that a substantial amount of Phase-I sample is necessary so that the scheme with unknown process parameters (Case-U) attains a performance almost similar to that of the Case-K counterpart. Since it is challenging to acquire a vast number of IC samples, we examine the optimal designs of the Case-U SSGRDS [Formula: see text] scheme such that the average number of observations to signal (ANOS) and expected ANOS (EANOS) are minimised. The optimal parameters obtained for the Case-U SSGRDS [Formula: see text] scheme enable it to have a performance comparable to that of the Case-K counterpart, without the need for a large number of Phase-I samples. We show that the Case-U SSGRDS [Formula: see text] scheme is effective in identifying the process mean shift of a silicon epitaxial process.

Development of a novel Colorimetric Assay for the rapid diagnosis of Coronavirus disease 2019 from nasopharyngeal samples.

Emergence of Coronavirus disease 2019 (COVID-19) pandemic has posed a huge threat to public health. Rapid and reliable test to diagnose infected subjects is crucial for disease spread control. We developed a colorimetric test for COVID-19 detection using a Colorimetric Assay based on thiol-linked RNA modified gold nanoparticles (AuNPs) and oligonucleotide probes. This method was conducted on RNA from 200 pharyngeal swab samples initially tested by Real-Time polymerase chain reaction (RT-PCR) as gold standard. A specific oligonucleotide probe designed based on ORF1ab of COVID-19 was functionalized with AuNPs-probe conjugate. The exposure of AuNP-probe to isolated RNA samples was tested using hybridization. In this comparative study, the colorimetric functionalized AuNPs assay exhibited a detection limit of 25copies/µL. It was higher in comparison to the RT-PCR method, which could only detect 15copies/µL. The results demonstrated 100% specificity and 96% sensitivity for the developed method. Herein, we developed an incredibly rapid, simple and cost-effective Colorimetric Assay lasting approximately 30min which could process considerably higher number of COVID-19 samples compared to the RT-PCR. This AuNP-probe conjugate colorimetric method could be considered the optimum alternatives for conventional diagnostic tools especially in over-populated and/or low-income countries.

Human serum albumin-based drug-free macromolecular therapeutics induce apoptosis in chronic lymphocytic leukemia patient cells by crosslinking of CD20 and/or CD38 receptors.

This study explores the efficacy of human serum albumin (HSA)-based Drug-Free Macromolecular Therapeutics (DFMT) in treating Chronic Lymphocytic Leukemia (CLL), a prevalent adult leukemia subtype. DFMT, a novel strategy, employs biomimetic crosslinking of CD20 and CD38 receptors on malignant B cells without the need for low molecular weight drugs. Apoptosis is initiated via a two-step process: i) Recognition of a bispecific engager, Fab' fragment conjugated with morpholino oligonucleotide (Fab'-MORF1), by a cell surface antigen; followed by ii) crosslinking of the MORF1-decorated cells with a multivalent effector, HSA holding multiple copies of complementary MORF2, HSA-(MORF2)x. Herein we evaluated the efficacy of HSA-based DFMT in the treatment of 56 samples isolated from patients diagnosed with CLL. Fab' fragments from Obinutuzumab (OBN) and Isatuximab (ISA) were employed in the synthesis of anti-CD20 (Fab'OBN-MORF1) and anti-CD38 (Fab'ISA-MORF1) bispecific engagers. The efficacy of DFMT was significantly influenced by the expression levels of CD20 and CD38 receptors. Dual-targeting DFMT strategies (CD20 + CD38) were more effective than single-target approaches, particularly in samples with elevated receptor expression. Pretreatment of patient cells with gemcitabine or ricolinostat markedly increased cell surface CD20 and CD38 expression, respectively. Apoptosis was effectively initiated in 62.5% of CD20-targeted samples and in 42.9% of CD38-targeted samples. Our findings demonstrate DFMT's potential in personalized CLL therapy. Further research is needed to validate these outcomes in a larger number of patient samples and to explore DFMT's applicability to other malignancies.

Emotion Recognition Based on Handwriting Using Generative Adversarial Networks and Deep Learning

The quality of people’s lives is closely related to their emotional state. Positive emotions can boost confidence and help overcome difficulties, while negative emotions can harm both physical and mental health. Research has shown that people’s handwriting is associated with their emotions. In this study, audio-visual media were used to induce emotions, and a dot-matrix digital pen was used to collect neutral text data written by participants in three emotional states: calm, happy, and sad. To address the challenge of limited samples, a novel conditional table generative adversarial network called conditional tabular-generative adversarial network (CTAB-GAN) was used to increase the number of task samples, and the recognition accuracy of task samples improved by 4.18%. The TabNet (a neural network designed for tabular data) with SimAM (a simple, parameter-free attention module) was employed and compared with the original TabNet and traditional machine learning models; the incorporation of the SimAm attention mechanism led to a 1.35% improvement in classification accuracy. Experimental results revealed significant differences between negative (sad) and nonnegative (calm and happy) emotions, with a recognition accuracy of 80.67%. Overall, this study demonstrated the feasibility of emotion recognition based on handwriting with the assistance of CTAB-GAN and SimAm-TabNet. It provides guidance for further research on emotion recognition or other handwriting-based applications.

The impact of Ethiopian Green Legacy Initiative (GLI) on landscape functionality and plant species diversity in Lake Hawassa watershed, Ethiopia

AbstractAs one of the responses to the global commitments against climate change, the Ethiopian Government launched a nationwide Green Legacy Initiative (GLI) in 2019, which largely focused on forest tree plantations with some inclusion of fruit trees. Despite its tremendous efforts and investments, its effectiveness and impacts have not been studied. This paper attempted to address this necessity by conducting a cross‐sectional quasi‐experiment in three randomly selected woredas/districts of Lake Hawassa Watershed from August 20 to September 2, 2023. The research hypothesized the likely impacts of GLI on four dependent variables (hydrological regulation, soil stability, nutrient cycling and plant species diversity). To achieve this, the research considered the two variants of GLI practices (plantation with and without soil and water conservation measures) and the corresponding control sites. Having three sites and three treatments with five replications, the study involved a total of forty‐five quadrats of the same size (20 m × 20 m). The first three parameters were analysed using the landscape functionality analysis method, while the fourth employed Shannon's diversity index. Results of ANOVA showed that, on average 87% of randomly selected quadrats were found to significantly improve the local hydrology (runoff potential) (≈ 83.3% with Av. p = 0.012), soil stability (≈100% with Av. p = 0.002), nutrient cycling (≈83.3% with Av. p = 0.017) and plant species diversity (≈83.3% with Av. p = 0.012). The research revealed positive results from the Ethiopian Green Legacy Initiative. The small number of samples is acknowledged as a limitation of the research.

Diet of Rusty-spotted Cat Prionailurus rubiginosus (I. Geoffroy Saint-Hilaire, 1831) (Mammalia: Carnivora: Felidae) in Sanjay Gandhi National Park, Mumbai, India

The 103.68 km2 Sanjay Gandhi National Park (SGNP), Mumbai, exists amidst human densities that figure among the highest in the world. The rich biodiversity of SGNP includes the Rusty-spotted Cat Prionailurus rubiginosus, endemic to India, Sri Lanka, and Nepal, and categorised as ‘Near Threatened’ on the IUCN Red List. Little is known about its ecology and the dynamics of its coexistence with the other small carnivores in SGNP. We conducted a study with citizen volunteers to explore the diet of the Rusty-spotted Cat and other sympatric small carnivores in SGNP and in the adjoining human-dominated areas of Yeur village, Shivaji Nagar, Dahisar Quarry, and Aarey Milk Colony. After initial training, the volunteers collected scat samples from all forest ranges in SGNP and the surrounding areas outside, following defined protocols. Seventy-eight scat samples were analysed for species assignments using standardised molecular techniques, felid-specific primers, and DNA sequencing, and 24 were identified as of the Rusty-spotted Cat. The contents of the samples were examined under a microscope to identify prey remains. Results were presented as the mean number of scat samples containing remains of specific taxa with 95% Confidence Intervals. Diet estimated from 22 Rusty-spotted Cat scat samples and 52 samples of other small carnivores revealed rodents to be the major prey of the entire group. However, a higher proportion of Rusty-spotted Cat scat samples had remains of rodents (95%) and reptiles (6%) as compared to samples of other small carnivores, i.e., 79% with rodent remains and none with remains of reptiles. On the other hand, a lower proportion of Rusty-spotted Cat scat samples had remains of insects (14%), plant matter (9%), and birds (5%) than samples of other small carnivores (40% plant matter, 38% insects, 17% birds). Our results highlight the role of small carnivores, especially Rusty-spotted Cat in regulatory services through pest control.

Determination and economic design of repetitive group sampling plan under two parameter Lindley distribution

ABSTRACT A designing procedure of repetitive group sampling plan for assuring mean life under a two-parameter Lindley distribution is proposed, and the optimization model is developed for finding the optimal plan parameters such that the demands of both supplier and buyer are satisfied simultaneously. A real-time data set of ball bearings is used to explain the application of the proposed plan. A comparison between the proposed plan and the single sampling plan is done to reveal the better performance of the proposed plan based on operating characteristic function and average sample number. Applying the proposed plan to provide lifetime assurance reduces the inspection effort and related costs. We discuss the design of the proposed plan with an economic aspect. In addition, the sensitivity of the optimal sampling plans concerning the failure probability and cost parameters is analyzed. Finally, it is evident from the study that the proposed plan will be preferable to a single sampling plan for providing quality assurance with a minimum cost of the inspection.

THE RELATIONSHIP OF FAMILY BEHAVIOR WITH THE RISK OF STUNTING AMONG TODDLER IN RT 64 RW 17 KELURAHAN 16 ULU SEBERANG ULU II DISTRICT PALEMBANG

ABSTRACT Background: Stunting is a condition where a child experiences growth failure that occurs in the body and brain due to long-term malnutrition which results in the child being shorter than normal children of his age. The latest data also shows that around 9 million Indonesian toddlers are currently stunted. Objective: This study aims to determine the relationship between family behavior and the risk of stunting in toddlers in RT 64, Kelurahan 16 Ulu, Seberang Ulu IIPalembang District in 2023. Methodology: The research method used was an analytical survey with a cross sectional design. The number of samples in the study was 32 respondents. Furthermore, the data that has been collected is processed and analyzed using the Chi-Square statistical test with a significance level (p<0.05). In the results: the Chi-Square statistical test showed that there was a significant relationship between knowledge (p=0.038), attitudes (p=0.034), and actions (p=0.012) with the risk of stunting in RT 64 sub-district 16 Ulu, Seberang Ulu II District. Conclusion: This research shows that family knowledge, attitudes and actions are related to the risk of stunting. It is hoped that future researchers will examine the relationship between family behavior and the incidence of stunting in toddlers with different designs and research methods.

The Influence Of Product Quality, Price Perceptions, And Sales Promotions On Purchasing Decisions

This study aims to: (1) To determine the effect of Product Quality on Purchasing Decisions, (2) To determine the effect of Perceived Price on Purchasing Decisions, (3) To determine the effect of Sales Promotion on Purchasing Decisions, (4) To determine the effect of Product Quality, Price Perceptions, and Sales Promotion on Purchasing Decisions. The number of samples is 386 respondents using the Slovin formula. The data analysis method used is multiple linear regression analysis to determine the effect of Product Quality, Perceived Price and Sales Promotion on Purchasing Decisions in case studies of House of Donatello at Bogor. Data testing is done by using Statistical Package for the Social Scientist (SPSS) Software.Based on the test, the following data are obtained: (1) There is an effect of Product Quality on Purchasing Decisions (2) There is an effect of Perceived Price on Purchase Decisions (3) There is an influence of Sales Promotion on Purchase Decisions (4) There is an influence between Product Quality, Perceived Price, and Sales Promotion on Purchasing Decisions. Keywords: Product Quality, Price Perception, Sales Promotion, Purchase Decision

The Influence Of Service Quality, Product Quality, And Brand Image On Purchasing Decisions

This study aims to determine the effect of Service Quality, Product Quality, and Brand Image on Purchasing Decisions of Nako Kebon Jati Coffee. The number of samples is 385 respondents. The sampling method used is purposive sampling. The data analysis method used is Multiple Regression Analysis to find out whether service quality, product quality, and brand image can influence purchasing decisions on Kebon Jati Nako coffee. Data Processing Using the Statistical Package for the Social Science (SPSS). From the research results, the following data were obtained: (1) Service quality has a positive and significant effect on purchasing decisions for Kebon Jati Nako coffee. (2) Product quality has a positive and significant effect on purchasing decisions for Kebon Jati Nako Coffee. (3) Brand Image has a positive and significant effect on Purchasing Decisions. (4) Service Quality, Product Quality, and Brand Image simultaneously have a positive and significant effect on Purchasing Decisions. Keywords: Service Quality, Brand Quality, Brand Image, Purchasing Decision