Lower Average Values Research Articles

Study on polymer-containing oily sludge as a potential fuel by combustion thermochemistry

The environmental and resource issues posed by oil sludge have sparked a renewed interest in cleaner and more efficient oil production. The investigation on the combustion process of polymer-containing oily sludge (POS) is expected to open up new markets for POS as an alternative fuel. TGA was used to examine the combustion behaviour, kinetics, and thermodynamics of POS, and X-ray fluorescence (XRF) was used to measure the chemical composition of POS ash to predict ash fouling and slagging. Based on the TG-DTG curves, the mass loss of POS in combustion studies was split into four major areas. The combined calculation method of model-free methods, Flynn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS), was applied to determine the activation energies from stage 1 to stage 4, which were 47.89 kJ/mol, 66.09 kJ/mol, 190.55 kJ/mol, and 98.37 kJ/mol, respectively. A four-stage kinetic model (D4→D2→D3→R2) was established to describe the combustion process of POS. Compared to other conventional sludges, POS has a relatively low activation energy and is more susceptible to thermochemical transformations. The difference between the enthalpy change (ΔH) and activation energy (E) indicated that the reactions benefit the formation of the activated complex. Meanwhile, the change in entropy (ΔS) implied the thermodynamic disequilibrium in the 3rd stage of POS and completion of the thermal conversion at the end of the reaction. The change in Gibbs free energy (ΔG) increased in a stepwise manner and its lower average value reflected the greater reaction favourability of combustion for POS. The composition of POS ash was mainly metal oxides, with the slagging index, fouling index, and slagging viscosity index of 1.0, 9.1, and 32.0, respectively. POS ash has high fouling and slagging, with special attention in the combustion application.

Digital Condylar Parameter Assessment Using Cadiax® 2 and Modjaw®.

Background: The main aim of this research was to assess the reliability of two systems designed specifically for condylar movement recording using condylar slope and Bennett angle information. The objectives were to evaluate the validity of two subsequent null hypotheses: (1) there is no significant difference between the measurements of condylar slope and Bennett angle taken at T0 (initial) and T1 (after one week) using the same equipment; (2) there is no notable difference in the values of the condylar slope and Bennett angle measurements obtained using Modjaw and Cadiax 2. Methods: An observational, descriptive, and prospective study was conducted with a selected group of 25 individuals (13 females and 12 males) aged between 22 and 27. Results: The results of Cadiax 2 and Modjaw showed excellent measurement repeatability for both parameters, with intraclass correlation coefficients (ICC) above 0.90, indicating excellent reliability between T0 and T1, both at 3 mm and 5 mm of displacement. Modjaw had an overall average value relatively higher than Cadiax 2, even though Modjaw's condylar slope at 5mm had a significantly lower average value (37.4 ± 6.31) with an interval of 24.5-48.1, which was lower than Cadiax 2 (48.4 ± 10.6) with an interval of 30.5-68.5. Regarding the primary aim, it can be stated that both Modjaw and Cadiax 2 demonstrated excellent repeatability on their own, demonstrating robust reliability since there was no discernible difference between the T0 and T1 measurements. On the contrary, analyses of the two devices' measured values for the secondary aim showed a considerable difference. Conclusions: Even though each device is reliable on its own, the absolute values that are obtained are different. Technological differences between the systems may account for these variations.

Short-term fluctuation of intraocular pressure and influencing factors following intravitreal injection in patients with retinal vascular diseases.

To investigate the patterns of short-term intraocular pressure (IOP) fluctuations and identify the contributing factors following intravitreal injection in patients with retinal vascular diseases. Totally 81 patients were enrolled in this case control study. Eyes were categorized into 7 groups, including age-related macular degeneration (AMD), polypoidal choroidal vasculopathy (PCV), idiopathic choroidal neovascularization (CNV), proliferative diabetic retinopathy (PDR), diabetic macular edema (DME), macular edema secondary to branch (BVOME) and central (CVOME) retinal vein occlusion. IOP was measured in all patients using rebound tonometer at 7 preset time points perioperatively. Additionally, based on the administered medication, the eyes were classified into three treatment groups, including dexamethasone intravitreal implant (IVO), intravitreal conbercept (IVC), and intravitreal ranibizumab (IVR). To compare IOP values at various time points across groups, we employed one-way ANOVA, independent sample t-test or χ 2 test and multivariate logistic regression analysis. Peak IOP values across all groups were observed at 40s, and 5min after intravitreal injection. Statistical differences in IOP were detected at the 5min among the 7 indication groups (F=2.50, P=0.029). When examing the impact of medications, the IVO group exhibited lower average IOP values at both 40s and 5min compared to the IVC and IVR groups (P<0.001; P=0.007). The IOP values at 40s and 5min were significantly higher in BVOME and CVOME group compared to non-retinal vein occlusion-secondary macular edema (RVOME) group (P<0.001). Multivariate logistic regression analysis further confirmed that IOP measurement at 40s was significantly higher in CVOME group than in non-RVOME group (OR=1.64, 95%CI: 1.09-2.47; P=0.018). Needle size plays a crucial role in the transient changes of IOP following intravitreal injection. Before administering intravitreal injection to patients with central retinal vein occlusion, it is essential to exclude any underlysing causes of increased IOP.

The Influence Of Strategic Planning, Strategic Implementation With Stakeholders Support On The Performance Of Regional Drinking Water Companies In Region II

The purpose of this study is to analyze the influence of strategic planning on company performance. To analyze the influence of strategic planning on strategy implementation. To analyze the influence of stakeholder support on strategy implementation. To analyze the influence of strategy implementation on company performance. This research is a quantitative research, with a survey approach. Through the survey, not all individuals are observed but only take samples from the population. The location of this research is PDAM Region II. The sample in this study was 100 respondents using cluster random sampling method. Data analysis method and hypothesis testing with Structural Equation Model (SEM). In testing the model using SEM, there are seven steps that must be taken. Results of the analysis as follows: the value of strategic planning variables on the performance of companies with a p-value less than the lowest average. Variable value of strategic planning to the implementation of the strategy has a p-value less than the lowest average value. The value of the variable support of stakeholders on the implementation of the strategy with p-value less than the lowest average. The value of the variable implementation of the strategy on the performance of companies with a p-value less than the value of the lowest average. From the analysis, it can be concluded strategic planning affect the company's performance, strategic planning affect the implementation of the strategy, the support of influential stakeholders towards the implementation of the strategy and implementation of strategies affect the company's performance.

Experimental investigation on diesel engine performance and emission characteristics using waste cooking oil blended with diesel as biodiesel fuel

Biodiesel production from waste cooking oil is a potential feedstock to alternative fuel sources. Produced alternative fuel sources were to have a strong emphasis on energy efficiency to substitute the declining world supply of fossil fuels while also improving emission characteristics in diesel engine applications. The development of industrialization and mechanization causes increased fossil fuel consumption and its usage. This study aimed at an experimental investigation of biodiesel blended fuel combustion efficiency for single-cylinder diesel engines under varying engine loads at constant engine speed 1500 rpm. The transesterification process was used to produce biodiesel from waste cooking oil using NaOH as catalysts. Biodiesel reaction takes place with oil to methanol ratio of 6:1 at 60 °C reaction temperature for 90 min with 600 rpm stirring speed while 90% yield gained. Eight sample biodiesel blends were prepared with percentage value B5%, B10%, B15%, B20%, B25%, B30%, B35%, B40% v/v and B100% to investigate the effect of biodiesels on engine performances. The experimental result reveals that the mixed biodiesel blends have lower average value in terms of brake torque, brake power, and brake thermal efficiency than diesel fuels as a percentage of 16.79%, 4.08%, and 27.9% respectively. In addition, the average BSFC of biodiesel blends was increased by 4.8% than baseline diesel fuel. Related to exhaust gases emission test results were shows that the average CO and HC emissions decreased by 52.2% and 60% with increasing loads and blends and the increment of CO2 and NOx by 28.1% and 45.4% respectively than baseline fuel with increasing blends and loads. Biodiesel derived from waste cooking oil was less costly and environmentally friendly and viable to substitute petro-diesel.

Domestic Tourists' Perceptions of Education-Based Tourism Products at Bali Bird Park

Tourist perception is a tourist's view, understanding of a tourist towards a tourist destination. Educational tourism products are activities that integrate learning experiences with recreation to provide added value to tourists. This study was conducted at Bali Bird Park with the aim of determining the perception of domestic tourists towards educational tourism products at Bali Bird Park. This study is quantitative with a sample of 100 respondents who have visited Bali Bird. The data obtained were processed using SPSS with Descriptive Analysis, Validity Test and Reliability Test. Based on the average of each variable, the accessibility variable has the highest average value of 4.54 with a very good category. Based on the accessibility variable indicator, tourists really like access to the Bali Bird Park tourist attraction because it makes it easy for tourists to find the location of Bali Bird Park. While the variable that has the lowest average value is the price variable with an average of 4.13 in the good category. This is because the prices given are still quite expensive such as food and drinks due to the lack of restaurant facilities or food stands.

Research on Spatial Morphological Characteristics and Influencing Factors of Industrial Heritage: A Case Study of Nine Industrial Heritages in Guizhou Province

Industrial heritage, recognized as a significant aspect of historical and cultural heritage, has garnered considerable attention from scholars globally. To elucidate the spatial morphological characteristics and the underlying influencing factors of industrial heritage within karst regions, this study employs methods such as the interstice index, fractal dimension analysis, and spatial syntax. It conducts research on the spatial morphological characteristics of nine typical industrial heritages in Guizhou Province. The primary factors contributing to the variations in layout forms are the intricate karst topography and the functional requirements of production. The functional zoning of industrial heritage aligns with its layout, characterized by straightforward functional zones that have not developed into composite spaces. The overall connectivity of industrial heritage is relatively low, exhibiting weak integration, significant disparities in control values, low average depth values, and a deficiency in comprehensibility and diversity of options. This indicates that the internal connectivity of industrial heritage spaces is generally inadequate, with low accessibility, strong interrelations, average convenience, limited connectivity, and generally acceptable passage. The overall spatial, architectural, and roadway configurations of industrial heritage predominantly exhibit a uniform pattern. Importantly, industrial heritage reveals a highly variable overall spatial form, with an average fractal dimension of 1.57, complex architectural layouts (average fractal dimension of 1.50), and simplistic road network designs (average fractal dimension of 1.43), which collectively suggest high spatial complexity and irregular characteristics. This study can provide a reference for the analysis of spatial characteristics and influencing factors of other material cultural heritages, and it is of great significance for the systematic protection and revitalization of industrial heritage.

Acute hyperlipidemia has transient effects on large-scale bone regeneration in male mice

Excessive dietary fat intake increases plasma lipid levels and has been associated with reduced bone mineral density (BMD) and increased risk of osteoporotic fracture, especially in older postmenopausal women. The objective of this study was to investigate whether there are sex-related differences in lipid metabolism that could have an impact on large-scale bone regeneration. Because ribs provide a unique exception as the only bones capable of completely regenerating large-scale defects, we used a rib resection mouse model in which human features are recapitulated. After 10 days of exposure to a low-fat diet or high-fat diet (HFD), we performed large-scale rib resection surgeries on male and female mice (6–7 weeks old) with deletion of the low-density lipoprotein (LDL) receptor (Ldlr−/−) and age- and sex-matched wild-type (WT) mice were used as controls. Plasma analysis showed that short-term exposure to HFD significantly increases total cholesterol, LDL cholesterol, and triglycerides levels in Ldlr−/− mice but not in WT, with no differences between males and females. However, under HFD, callus bone volume was significantly reduced exclusively in male Ldlr−/− mice when compared to WT, although these differences were no longer apparent by 21 days after resection. Regardless of diet or genotype, BMD of regenerated ribs did not differ significantly between groups, although male mice typically had lower average BMD values. Together, these results suggest that short-term hyperlipidemia has transient effects on large-scale bone regeneration exclusively in male mice.

ChatGPT's quality: Reliability and validity of concept inventory items.

The recent advances of large language models (LLMs) have opened a wide range of opportunities, but at the same time, they pose numerous challenges and questions that research needs to answer. One of the main challenges are the quality and correctness of the output of LLMs as well as the overreliance of students on the output without critically reflecting on it. This poses the question of the quality of the output of LLMs in educational tasks and what students and teachers need to consider when using LLMs for creating educational items. In this work, we focus on the quality and characteristics of conceptual items developed using ChatGPT without user-generated improvements. For this purpose, we optimized prompts and created 30 conceptual items in kinematics, which is a standard topic in high-school level physics. The items were rated by two independent experts. Those 15 items that received the highest rating were included in a conceptual survey. The dimensions were designed to align with the ones in the most commonly used concept inventory, the Force Concept Inventory (FCI). We administered the designed items together with the FCI to 172 first-year university students. The results show that ChatGPT items have a medium difficulty and discriminatory index but they overall exhibit a slightly lower average values as the FCI. Moreover, a confirmatory factor analysis confirmed a three factor model that is closely aligned with a previously suggested expert model. In this way, after careful prompt engineering, thorough analysis and selection of fully automatically generated items by ChatGPT, we were able to create concept items that had only a slightly lower quality than carefully human-generated concept items. The procedures to create and select such a high-quality set of items that is fully automatically generated require large efforts and point towards cognitive demands of teachers when using LLMs to create items. Moreover, the results demonstrate that human oversight or student interviews are necessary when creating one-dimensional assessments and distractors that are closely aligned with students' difficulties.

THE INFLUENCE OF THE STRUCTURAL ANALYTICAL METHOD (SAS) WITH THE ASSISTANCE OF BIG BOOK MEDIA ON ELEMENTARY SCHOOL STUDENTS' BEGINNING READING ABILITY

This research was motivated by the results of UNESCO and PISA which stated that the literacy rate in Indonesia is still low, especially in beginning reading in elementary school students. The purpose of this study was to measure the initial reading ability of elementary school students, especially in grade I students. This research is a quasi-experimental research with a quantitative approach. Sampling was carried out using purposive sampling techniques. In obtaining data, researchers conducted initial tests (pretest) and final tests (posttest) in the form of preliminary reading tests, observation sheets and interviews. The data technique used is to use descriptive analysis techniques and descriptive statistical analysis by testing hypotheses using t-test statistics.. The data obtained are then analyzed using statistical analysis techniques, namely descriptive statistics. Descriptive statistical analysis data obtained average value (pretest) = 69,17 is in the very low category and average value (posttest) = 83,00 is in the high category. From the results of the hypothesis test analysis using paired sample test, a sig value = 0,001 is obtained in accordance with the basis for decision making, if the hypothesis test of the probability value of significance &lt; 0.05, then H0 is rejected and Ha is accepted. Then significantly the alternative hypothesis (Ha) is accepted and the null hypothesis (H0) is rejected. Based on the hypothesis test, it can be concluded that the synthetic analytical structural method (SAS) with the help of big book media affects the initial reading ability in grade I students of SDN Kebalen 01 Kabupaten Bekasi.

Topical tacrolimus orabase versus topical clobetasol propionate orabase in the treatment of symptomatic oral lichen planus: a pilot randomized study.

This pilot study aimed to compare the efficacy of 0.1% tacrolimus and 0.05% clobetasol propionate in orabase for treating symptomatic oral lichen planus (OLP). Pilot, randomized, and controlled study conducted on 21 patients with symptomatic OLP, selected according to the clinical and histopathological criteria of Cheng et al. 2016. Twelve patients received 0.1% tacrolimus, and nine received 0.05% clobetasol, both in orabase for 30 days with a two-month follow-up. The patients were examined for scores of signs (ODSS), symptoms (VAS), quality of life (OHIP-14), anxiety (Beck Anxiety Scale), and treatment satisfaction (Hedonic Scale). Both treatments were effective in reducing ODSS, VAS, and Beck Anxiety Scale scores and performed well on the hedonic scale, yet without statistical difference between them. However, at the 1-month follow-up, patients in group Clobetasol showed a greater percentage reduction in ODSS score compared to baseline by 50% (p = 0.02) and significantly lower average values (p = 0.03) than those in group Tacrolimus. Longitudinal intragroup analysis revealed significant improvements over time in both groups for ODSS, and only in the tacrolimus group for OHIP-14 and Beck scores. Both tested protocols were effective over a three-month follow-up. However, due to the lower cost of clobetasol propionate it can be considered the first-choice option. Tacrolimus in orabase formulation may be a promising alternative for refractory lesions that do not respond to topical steroids. Managing symptomatic OLP is challenging. Comparisons between tacrolimus and clobetasol propionate in orabase formulations have not yet been thoroughly explored.

Innovative hybrid grey wolf-particle swarm optimization for calculating transmission line parameter

Transmission line (TL) parameters, particularly capacitance, are important for ensuring the efficient and reliable operation of power systems. As power networks become increasingly complex, accurately determining TL parameters faces certain challenges, particularly capacitance, which involves overcoming computational challenges due to bundling configurations. The interconnected nature of modern TL and the use of advanced technologies further add to the complexity. Effective estimation requires advanced measurement techniques and sophisticated computational tools. Recently, optimization techniques have become widely used for TL parameter calculations. However, traditional methods struggle with challenges like limited exploration and slow convergence. To address these issues, this research introduces a hybrid algorithm called HGWPSO, which combines the Grey Wolf Optimizer (GWO) with Particle Swarm Optimization (PSO). The main objective is to enhance the exploitation ability of GWO with the exploration capability of PSO, maximizing the strengths of both variants. Initially, to verify the efficiency of HGWPSO, CEC_19 benchmark functions are utilized to evaluate its performance. Secondly, the main focus of this study is to calculate TL parameters such as capacitance considering two, three, and four-bundle conductors using the HGWPSO algorithm and comparing its performance with other optimization techniques. According to the obtained result, the average percentage reduction for HGWPSO is 0.15 % in test case 1, 4.85 % in test case 2, and 2.84 % in test case 3, compared to others. It shows that the HGWPSO has better performance than other methods regarding convergence speed, and ability to locate the global optimum. Finally, experimental analysis confirms the superiority of the HGWPSO in accurately estimating TL capacitance for different bundle conductor configurations, obtaining lower average values, and effectively addressing the characteristic complexities in the TL parameter.

A hybrid data-driven approach for state of health estimation in lithium-ion batteries

ABSTRACT The assessment of the state of health (SOH) in lithium-ion batteries is essential for ensuring safe operation and implementing scientific management practices. This paper proposes a novel hybrid data-driven approach for accurately estimating the SOH of lithium-ion cells. Initially, the sparrow search algorithm (SSA) was implemented to optimize the structural configuration of a hybrid long-short-term memory neural network and convolutional neural network model. Second, four health indicators, namely, constant current charging time (CCCT), constant current charging capacity (CCCC), discharging time (DT), and discharging capacity (DC), were identified as inputs to the estimation model by Pearson correlation analysis. The CALCE battery dataset is utilized for conducting experiments, yielding remarkably low average values of root mean square error (RMSE) and mean absolute error (MAE), standing at merely 0.6737% and 0.5286%, respectively. And comparing with GRU, TCN, CNN, LSTM, and PSO optimization models, the proposed method has higher SOH estimation accuracy, which is more than 11% better than that. The robustness of three additional kinds of batteries is tested to validate their performance under varying current rates and temperatures. The results demonstrate that the accurate estimation of SOH, and the estimated values’ relative errors for each cycle of the three different types of batteries are all basically within 1%, with their maximum average RMSE are only 0.4840%, 0.3609%, and 0.5681%, respectively, and their maximum average MAE are only 0.3900%, 0.2828%, and 0.4149%, respectively.

Unveiling the human-like similarities of automatic facial expression recognition: An empirical exploration through explainable ai

AbstractFacial expression recognition is vital for human behavior analysis, and deep learning has enabled models that can outperform humans. However, it is unclear how closely they mimic human processing. This study aims to explore the similarity between deep neural networks and human perception by comparing twelve different networks, including both general object classifiers and FER-specific models. We employ an innovative global explainable AI method to generate heatmaps, revealing crucial facial regions for the twelve networks trained on six facial expressions. We assess these results both quantitatively and qualitatively, comparing them to ground truth masks based on Friesen and Ekman’s description and among them. We use Intersection over Union (IoU) and normalized correlation coefficients for comparisons. We generate 72 heatmaps to highlight critical regions for each expression and architecture. Qualitatively, models with pre-trained weights show more similarity in heatmaps compared to those without pre-training. Specifically, eye and nose areas influence certain facial expressions, while the mouth is consistently important across all models and expressions. Quantitatively, we find low average IoU values (avg. 0.2702) across all expressions and architectures. The best-performing architecture averages 0.3269, while the worst-performing one averages 0.2066. Dendrograms, built with the normalized correlation coefficient, reveal two main clusters for most expressions: models with pre-training and models without pre-training. Findings suggest limited alignment between human and AI facial expression recognition, with network architectures influencing the similarity, as similar architectures prioritize similar facial regions.

The Effects of Rearing Systems on Incubation, Egg Production and Quality Traits in Pharaoh Quails

This study was conducted to determine the effect of rearing quails in different rearing systems on egg production, egg quality characteristics, and incubation results. The 360 quails were distributed equally to 3 different rearing groups (cage, enriched cage, and floor) in a male:female mixed at the age of 3 weeks. The eggs were individually weighed and recorded one by one daily (5487 eggs) for 3 months. To determine egg quality and incubation characteristics, 750 eggs were broken, and 3284 eggs were incubated, respectively. The results showed that female quail in the floor group have lower body weight at 6 weeks old (177.19 g), and they reached sexual maturity (age of first egg laying) later (65.36 day, P&lt;0.01), The lowest egg production (61.14%) occurred in the floor group during the 3-month egg production period (P&lt;0.05). The lowest average egg weight (9.07 g) was determined in the floor group (P&lt;0.05). It was determined that the eggs of quails raised in the enriched group had a rounder shape index because they have larger widths (P&lt;0.01). While the highest average yolk height (11.24 mm) was determined in the enriched cage group (P&lt;0.01), the highest averages of albumen length (72.41 mm) and lowest averages of yolk index (48.43%) were determined in the cage group (P&lt;0.01). The lowest average values (113.17) in Haugh unit were detected in the floor group (P&lt;0.05). The highest fertility rate (98.44%) was in Floor♂:Cage♀, the highest hatchability of fertile egg rate (94.67%) was obtained from Enriched♂:Cage♀, and the highest hatchability (89.10%) was obtained from Floor♂:Cage♀ pairing (P&lt;0.05). The lowest fertility rate (88.00%) was obtained from the Enriched♂:Floor♀, the lowest hatchability of fertile egg rate (86.01%) was obtained from the Enriched♂:Enriched♀, and the lowest hatchability (75.62%) was obtained from the Enriched♂: Enriched♀ groups. As a result, it has been revealed that the effect of various rearing systems is different on egg production, egg quality traits, and hatching results in quails. Thus, it has been shown that different programs at the rearing period to be applied to the male and female quails can achieve better incubation results and reproductive success.

Comparison of Several Methods for Analysis Slope Length Index Factor at A Watershed Scale

Slope length and steepness factor index (LS) is one of the parameters for the Universal Soil Loss Equation (USLE) to estimate soil erosion. Currently, several methods for LS analysis, i.e. Wischmeier-Smith, Moore-Nieber, and Desmet – Govers. This study aims to compare the Wischmeier-Smith method, Moore–Nieber method, and Desmet–Govers method to analyze LS in the watershed in Manokwari – West Papua. This research consists of 4 main stages, i.e. data inventory, watershed boundary delineation, LS analysis, and LS comparison. The research showed that the Wischmeier-Smith method gave a higher LS value than the Moore – Nieber method and the Desmet – Govers method. Meanwhile, the Desmet – Gover method gives a lower average LS value than the Wischmeier-Smith method and the Moore – Nieber method. Based on the T-test, the LS produced by the Wischmeier-Smith, Moore-Nieber, and Desmet–Govers methods has significant differences in analyzing LS in the watershed in Manokwari – West Papua. Keywords: Desmet – Govers, Moore – Nieber, Universal Soil Loss Equation, Watershed, Wischmeier-Smith

Prediction of Financial Distress in Transportation and Logistics Companies before, During and after the Covid-19 Pandemic Listed on the Indonesia Stock Exchange

Purpose: This study aims to predict financial distress in transportation and logistics companies before, during, and after the Covid-19 pandemic. Research Methodology: The research subjects were 23 companies, and the study utilized an artificial neural network model. This study uses financial ratios, including the debt-to-asset ratio (DAR), Current Ratio (CR), and Return on Assets (ROA) as input variables in the artificial neural network architecture. The objectives of this study are to calculate the three ratios used as test data, determine the differences in financial ratios between companies reported as financially distressed and those not experiencing financial distress in the training data, identify the artificial neural network model architecture that produces good performance on the training data sample for use in testing predictions, and predict financial distress using an artificial neural network on transportation and logistics companies listed on the Indonesia Stock Exchange, which are part of the research sample. The research sample consisted of 20 transportation and logistics companies listed on the Indonesia Stock Exchange from 2015 to 2019. Results: The results reveal that companies reported as financially distressed have lower average values for the three ratios compared to companies not experiencing financial distress, making them suitable input variables. The best artificial neural network architecture in this study included an input layer with 60 neurons, a hidden layer with 15 neurons, and an output layer with one neuron. This architecture achieved a training performance mean square error (MSE) of 0.125004 and an R value of 50.00%. The study's findings suggest that 12 companies are predicted to experience financial distress.

A meta-learning method for smart manufacturing: Tool wear prediction using hybrid information under various operating conditions

Accurate tool wear prediction during machining is crucial to manufacturing since it will significantly influence tool life, machining efficiency, and workpiece quality. Although existing data-driven methods can achieve competitive performance in tool wear prediction, their main emphasis is on fixed operating conditions with sufficient training samples, which is impractical in engineering practice. This implies that predicting tool wear values under variable working conditions with insufficient data is still a challenge owing to the difference in data distributions in complex tool wear mechanisms. Besides, having no access to samples in new conditions is another challenge for tool wear prediction in engineering practice. To address these issues, we develop a hybrid information model-agnostic domain generalization (H-MADG) method to provide appropriate initial model parameters that can be fast adaptative to the new conditions after fine-tuning. Additionally, we construct hybrid information as model input by fusing process information with temporal properties derived by neural networks, and the hybrid information can offer more useful prior knowledge about the machining process. Experimental results on NASA milling data show that compared with contrastive techniques, the RMSE of the proposed H-MADG method is reduced by an average of 36.81 %, which can achieve a low average RMSE value of 0.0904 with 15 cases under five different network architectures. We also investigate several crucial impact factors of the H-MADG method and summarize corresponding analysis and suggestions.

Peering into cosmic reionization: Lyα visibility evolution from galaxies at z = 4.5–8.5 with JWST

The resonant scattering interaction between Lyα photons and neutral hydrogen implies that a partially neutral intergalactic medium has the ability to significantly impact the detectability of Lyα emission in galaxies. Thus, the redshift evolution of the Lyα equivalent width distribution of galaxies offers a key observational probe of the degree of ionization during the Epoch of Reionization (EoR). Previous in-depth investigations at z ≥ 7 were limited by ground-based instrument capabilities. We present an extensive study of the evolution of Lyα emission from galaxies at 4.5 &lt; z &lt; 8.5, observed as part of the CEERS and JADES surveys in the JWST NIRSpec/PRISM configuration. The sample consists of 235 galaxies in the redshift range of 4.1 &lt; z &lt; 9.9. We identified 65 of them as Lyα emitters. We first measured the Lyα escape fractions from Lyα to Balmer line flux ratios and explored the correlations with the inferred galaxies’ physical properties, which are similar to those found at lower redshift. We also investigated the possible connection between the escape of Lyα photons and the inferred escape fractions of LyC photons obtained from indirect indicators, finding no secure correlation. We then analyzed the redshift evolution of the Lyα emitter fraction, finding lower average values at z = 5 and 6 compared to previous ground-based observations. At z = 7, the GOODS-S results are aligned with previous findings, whereas the visibility in the EGS field appears to be enhanced. This discrepancy in Lyα visibility between the two fields could potentially be attributed to the presence of early reionized regions in the EGS. Such a broad variance is also expected in the Cosmic Dawn II radiation-hydrodynamical simulation. The average Lyα emitter fraction obtained from the CEERS+JADES data continues to increase from z = 5 to 7, ultimately declining at z = 8. This suggests a scenario in which the ending phase of the EoR is characterized by ∼1 pMpc ionized bubbles around a high fraction of moderately bright galaxies. Finally, we characterize such two ionized regions found in the EGS at z = 7.18 and z = 7.49 by estimating the radius of the ionized bubble that each of the spectroscopically-confirmed members could have created.

Analisis Tingkat Kepuasan Pelanggan Perusahaan Daerah Air Minum Kabupaten Majalengka

The purpose of this study was to determine the level of community satisfaction with PDAM Majalengka Regency and to determine the service quality of PDAM Majalengka Regency. Measurement of the Community Satisfaction Index and the quality of PDAM Majalengka Regency public services is carried out by distributing questionnaires to PDAM customers. The sampling method used is incidental sampling, namely determining the sample by "coincidence", that is, anyone who coincidentally meets the researcher can be used as a sample. The highest average value per service element is the courtesy and friendliness of the service staff, while the lowest average value per service element is the discipline of the service staff. Service unit performance at PDAM Majalengka Regency“good” because the value is between 76.61-88.30 which is in service quality B (good). Indicators that can be categorized as in accordance with community expectations are: (1) Politeness and Friendliness of Service Officers; (2) Certainty of Service Fees; (3) The reasonableness of the fee to get the service; and, (4) the accuracy of the implementation of the service time schedule; (5) Environmental Comfort; (6) Service Security. Meanwhile, indicators that are still below the average conformity level are: (1) Understanding of the ease of service procedures for PDAM Majalengka; (2) Terms of Service; (3) Capability of PDAM Majalengka service staff; (4) Fairness to get service (5) Speed of service (6) Clarity and certainty of serving officers; (7) Discipline of officers in providing services; (8) Responsibilities of officers in providing services.