Opacity Level Research Articles

A novel biodegradable film based on chicken gelatin and κ-carrageenan cross-linked with oxidized phenolic compounds.

Natural and renewable polymers are gradually replacing petroleum-based plastics, mostly as a result of environmental concerns. Moreover, upcycling industrial food waste into new added-value products is a creative approach that is crucial for cleaner and more sustainable manufacturing. The aim of this study was to obtain an environmentally friendly biodegradable film using a combination of k-carrageenan (KCAR) and chicken gelatin (CGEL), which obtained from poultry by-products. The effects of varying concentrations of KCAR (0-2%) on the physical, permeability, textural, thermal, and microstructural properties of CGEL/KCAR composite films were evaluated. The findings demonstrated that an increase in KCAR enhanced the lightness and opacity levels of the films. Water vapor permeability (WVP) values reduced as the KCAR concentration increased. The lowest WVP value (0.0012g.mm/h.m2.kpa) was seen in the treatment with 2% KCAR. Tensile strength (TS) values increased with increasing KCAR. The films' thermal stability was increased by the addition of KCAR. Microstructure assessments revealed a more compact and smooth structure in the KCAR-containing treatments, indicating improvements in WVP, thermal stability, and TS. Compared to the commercial cattle gelatin film, the CGEL film had higher TS and lower water solubility (WS). Overall, this study showed that the physical, mechanical, barrier and thermal and microstructural qualities of gelatin-based films may be enhanced by combining CGEL and KCAR to create an effective biodegradable film. Moreover, the comparison study between commercial cattle and chicken gelatin films revealed that cross-linked chicken gelatin films would be a suitable alternative for bovine gelatin films in the production of biodegradable film.

Assessment of Protein Quantity and Quality of Turkish Maize Landraceswith Different Opacity Level

Assessment of Protein Quantity and Quality of Turkish Maize Landraceswith Different Opacity Level

Combined influence of thermal barrier coating and nanoparticle on performance and emissions of DI diesel engine fueled with neat palm oil biodiesel: An experimental, statistical and energy and exergy analysis

In the present work, neat palm biodiesel (BD 100) was utilized in the compression ignition (CI) engine under the influence of thermal barrier coating and cerium oxide (CeO2) nanoparticles.The optimal factor conditions were determined through statistical analysis using the Response Surface Methodology (RSM), with appropriate input parameters provided. The results show that using a thermal barrier coated (TBC) engine with a 200 micron (0.2 mm) thickness of cylinder liner and 45 ppm cerium oxide nanoparticles combined with 100% palm biodiesel significantly improves performance and reduces emissions.The energy and exergy methodology tool was then used to analyze the various fuel conditions in order to examine the variations in energy flow.The assessment criteria that were experimentally confirmed were an average reduction in specific fuel consumption (SFC) of 0.065 kg/kWh and an increase in brake thermal efficiency (BTE) of 4.07%. The reduction of exhaust gases was seen to be significant when compared to those obtained from an uncoated engine running on diesel fuel, as indicated by the carbon monoxide (CO) level of 0.0916% by volume, the unburned hydrocarbon (UBHC) level of 38.2 parts per million (ppm), NOx of 132 ppm and the smoke opacity level of 10.52%.

Stress testing programs and credit risk opacity of banks: USA vs Europe

Regulators strengthened banking supervision in the aftermath of the Great Financial Crisis by stress testing banks intending to increase the amount of information available about the risks they face, improving their transparency and restoring market confidence. This study examines whether the results of stress tests conducted between 2009 and 2019 in the US and the EU have reduced the opacity of information about banks' credit risk. We study changes in banking sector opacity around the disclosure of stress test results in a panel data framework. We measure opacity by discrepancies in bank credit ratings issued by different agencies. The findings indicate a lower opacity level after disclosing the US test results. The most significant reduction occurs for systemic banks with higher leverage that fail the test. The European testing programme has specific disclosure features that could justify that the effect of disclosure of stress test results is more attenuated for EU banks. Some indirect evidence suggests that differences in stress test programmes and banking sector structure between the two regions may explain the result.

Experimental study on fuel consumption and smoke opacity of defective coffee-bean-based biodiesel fuel engines

This experimental study aims to analyse the performance of sorted coffee beans-based biodiesel. This study is carried out in three main stages; (a) the preparation process of coffee beans raw material, (b) the biodiesel formation process, and (c) biodiesel performance analysis. In manufacturing process, the coffee bean powder is added with two chemical treatments sequentially; extraction-distillation and esterification/transesterification. Parameters of analysis in this study are the characteristics of the biodiesel and the performance of the biodiesel-diesel mixture in terms of fuel consumption efficiency and engine smoke opacity. Measurements of Engine Running Time (ERT) and smoke opacity were carried out on a single-piston diesel engine. There were five biodiesel-diesel mixture specimens; B0, B5, B10, B15, and B20 (20% biodiesel fraction). The experimental results show that mixing biodiesel with diesel fuel provides two main advantages; extending engine running time which means fuel consumption efficiency, and lowering the smoke opacity level. Therefore, it is more environmentally friendly. The efficiency of fuel consumption and smoke opacity depends on the biodiesel fraction in the fuel mixture. The results and methodology of this research are expected to be an additional reference in the development of biodiesel as an alternative fuel.

Glassy and Rubbery Epoxy Composites with Mesoporous Silica

The reinforcing efficiency of SBA-15-type mesoporous silica, when used as additive in epoxy polymers, was evaluated in this study. The effects of silica loading and its physicochemical characteristics on the thermal, mechanical, and viscoelastic properties of glassy and rubbery epoxy mesocomposites were examined using SBA-15 mesoporous silicas with varying porosities (surface area, pore size, and volume), particle sizes, morphologies, and organo-functionalization. Three types of SBA-15 were used: SBA-15 (10) with 10 nm pore diameters and long particles, SBA-15 (5) with 5 nm pore diameters and short particles, and SBA-15 (sc) with 10 nm pore diameters and short particles (“sc” for short channel). SBA-15 (10) was modified with propyl-, epoxy-, and amino-groups to study the effect of functionalization. The glassy or rubbery epoxy polymers and mesocomposites were produced by the crosslinking of a diglycidyl ether of bisphenol A (DEGBA) epoxy resin with isophorone diamine (IPD) or Jeffaminje D-2000, respectively. Mesoporous silica was uniformly dispersed inside the polymer matrices; however, the opacity levels between the rubbery and glassy samples were different, with completely transparent rubbery composites being prepared with as high as a 9 wt. % addition of SBA-15. The mechanical and thermal performance properties of the mesocomposites were dependent on both the type of the curing agent, which affected the cross-linking density of the pristine polymer matrix, and the characteristics of the mesoporous silica variants, being, in general, improved by the addition of up to 6 wt. % silica for the glassy polymers and up to 9 wt. % for the rubbery polymers.

Effects Of Bio-Oil - Diesel Blends: The Performance and Emissions of Diesel Engines With Heater on Fuel Blends

The vehicle fuel consumption is increasing. Fossil fuels are running low. Research is needed to reduce the use of fossil fuels. As an alternative, research is carried out on the use of a mixture of bio-oil - diesel fuel in diesel engines. The aim of the research is to increase power, reduce fuel consumption and reduce exhaust emissions from diesel engines. The research method is direct testing on diesel engines with variations in fuel heating by adding a heater to the fuel. Variation of heating materials The fuel used is standard temperature, 40°C, 50°C, and 60°C. The test uses a lamp load with a certain variation to determine power, with a measuring tube to determine certain fuel consumption. Testing using the opacity smoke meter to determine the level of exhaust gas opacity. In this test, In this test it can be concluded that the best condition is B20 at a fuel heating temperature of 40oC, where power has increased, opacity and fuel consumption has decreased, the power can reach 2592,76 watt. Smoke opacity level at 5,4% and 0,088 gr/watt of fuel consumption.

A Neutrosophic Set Approach on Chest X-rays for Automatic Lung Infection Detection

COVID cases and its variants is noted enormously in the past three years. In many medical cases, lung infections such as viral pneumonia, bacterial pneumonia have been initially interpreted as COVID-19. Hence, the proposed work is concentrating on differentiating these lung infection types. This work focuses on using neutrosophic approach of classifying into True (T), False (F) and Indeterminacy (I) set membership to reduce the fuzziness and retain more significant information for feature extraction of the opacity to differentiate the types of lung infections. Initially, the images are preprocessed by alpha-mean and beta-enhancement operation to reduce the indeterminacy and enhancing the image components as the range of lung opacity levels to determine the types. Then, these neutrosophic set enhanced images are fed to various deep learning models like ResNet-50, VGG-16 and XGBoost for classification. Experiments are conducted on ActualMed COVID-19 Chest X-ray and COVID-19 radiography dataset and a comparative analysis on several domain set of images such as the original image, neutrosophic domain (T, I, F) and enhanced neutrosophic domain (alpha, beta) are trained and tested through transfer learning by tuning the various validation parameters. On experimental analysis, an enhanced neutrosophic image achieves a better accuracy of 97.33% among the other domain sets.

Translucency of CAD/CAM and 3D Printable Composite Materials for Permanent Dental Restorations

The aim of the study was to compare the translucency of CAD/CAM and printable composite materials for fixed dental prostheses (FDP). Eight A3 composite materials (7 CAD/CAM and 1 printable) for FPD were used to prepare a total of 150 specimens. CAD/CAM materials, all characterized by two different opacity levels, were: Tetric CAD (TEC) HT/MT; Shofu Block HC (SB) HT/LT; Cerasmart (CS) HT/LT; Brilliant Crios (BC) HT/LT; Grandio Bloc (GB) HT/LT; Lava Ultimate (LU) HT/LT, Katana Avencia (KAT) LT/OP. The printable system was Permanent Crown Resin. 1.0 mm-thick specimens were cut from commercial CAD/CAM blocks using a water-cooled diamond saw, or 3D printed. Measurements were performed using a benchtop spectrophotometer with an integrating sphere. Contrast Ratio (CR), Translucency Parameter (TP), and Translucency Parameter 00 (TP00) were calculated. One Way ANOVA followed by Tukey test for post hoc were performed for each of the translucency system. The tested materials exhibited a wide range of translucency values. CR ranged from 59 to 84, TP from 15.75 to 8.96, TP00 from 12.47 to 6.31. KAT(OP) and CS(HT) showed, respectively, the lowest and highest translucency for CR, TP and TP00. Due to the significant range of reported translucency values, clinicians should exercise caution when choosing the most appropriate material, especially considering factors such as substrate masking, and the necessary clinical thickness.

Improvement of the combustion, emission, and stability features of diesel-methanol blends using n-decanol as cosolvent

This research endeavored to boost the applicability of methanol in CI engines utilizing n-decanol as cosolvents. The work was split into binary phases. Firstly, the stabilities of pure methanol (M100) and hydrous-methanol (MH10), with diesel as a reference fuel, were examined applying various temperatures: 10 °C, 20 °C, and 30 °C. The findings showed that the M100-diesel and MH10-diesel combinations were unstable. Thus, n-decanol was utilized as a cosolvent. Following by the engine combustion and emissions characteristics were evaluated by manipulating three proportions of M100-diesel mixtures with n-decanol. Three mixtures comprised of 5, 10, and 15% M100 with 20% n-decanol, which are denoted as M5, M10, and M15, correspondingly. These combinations were assessed via thermogravimetric assessment, and their physicochemical properties were assessed corresponding to the ASTM. The maximum in-cylinder pressure, heat release rate, and pressure rise rate diminished by 10, 11, and 10%, respectively, for the M100/diesel/n-decanol combinations compared with the diesel oil. The brake thermal efficiency lowered by 10%, whereas the brake specific fuel consumption enlarged by 10% for the combinations compared with the diesel. NOx and smoke opacity levels diminished by about 30 and 50%, respectively, whereas the CO and UHC enlarged by about 50 and 60% for the blends compared with the diesel oil.

STC Short-Circuit Current Prediction and I–V Simulation of Colored BIPV Modules With Machine Learning and One-Diode Equivalent Circuit Models

Colored photovoltaic (PV) modules offer improved aesthetics at the cost of electrical performance loss. Here, we demonstrate a hybrid approach combining experiments, machine learning, and equivalent-circuit model to predict and simulate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I–V</i> parameters of colored crystalline-silicon PV modules. First, to predict the short-circuit current for different colors and opacity levels, three models—multiple linear regression (MLR), optimized support vector regression (SVR), and optimized Gaussian process regression (GPR)—are trained and evaluated with a ten-fold cross validation. The MLR model shows an MAE = 3.58 and an RMSE = 5.17. The accuracy could be further improved with the more advanced models, i.e., an optimized SVR (MAE = 0.22, RMSE = 0.24) or an optimized GPR (MAE = 0.13, RMSE = 0.17). Following, by taking the predicted short-circuit current values as inputs into a one-diode equivalent circuit model, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I–V</i> curves of two multicolored modules are simulated; and information such as module power <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mpp</sub> and current mismatch loss are extracted. There is a twofold advantage of implementing our approach: first, it serves as an efficient design space exploration methodology for a wide parameter space (e.g., colors), i.e., evaluating the PV performance for new colors without samples fabrication, thus saving time and resources; and second, it guides architects, designs, and engineers in color/design selection to achieve a balance between aesthetics and engineering considerations.

The LPG-diesel fuel dual fuelling effect on diesel engine performance

The use of alternative fuels can improve the performance of diesel engine in terms of pollution, [1], [2], [3].Low-carbon fuels [2] can successfully replace conventional fuels in modern engines or in future engines [1]. This may be an efficient method to ameliorate the exhaust emissions for engines of 2050, especially in terms of CO2 reduction, an important issue at the internal combustion engines of automotive fleets. The liquid petroleum gas, [1-5] which has a low carbon content comparative to diesel fuel can be a good solution in terms of fuelling. The paper presents an analysis of the experimental results obtained at the speed of 3900 rev/min for three loads: 40%, 55% and 70% for dual fueling with diesel fuel and LPG. At 40% load, at dual fueling, the brake specific fuel consumption (BSFC) is reduced by a maximum of 3.5% for xc = 8.14 comparative to classic fueling and at higher LPG doses the reduction is 1.88%. At 55% load, the dual fueled engine efficiency is similar to that of the classic engine, but for xc=0.37…0.43 the BSFC is reduced by 0.6%…1.2% compared to xc=0.18…0.32. At 70% load there is a continuous improvement in engine efficiency, the BSFC decreasing at dual fueling, especially at all degrees of substitution greater than xc = 0.2, compared to conventional engine. Generally, at dual fueling, the maximum pressure does not exceed the values recorded for classic fueling. At partial load 40% the NOx decrease with 29% for xc=21,57, by up to 17.7% at a maximum xc at a 55% load and by up to at 22.3% at 70% load. Reduction of HC emission level by up to 52.5% at 40% load, by up to 85.7% at 55% load and by 98.3% at 70% load, respectively. For smoke emission, the opacity level is reduced by up to 67.5%, at 40% load, by 50% at 55% load and by 39.13% at 70% load; the smoke number is reduced by up to 66.6% at 40% load, by 55.5% at 55% load and by up to 45.4% at 70% load. The CO2 emission level is reduced by 9.4% at 40% load, 3.1% at 55% load and 6.58% at 70% load, respectively, for the maximum substitution rate used at each operating regime.

Enhancement of the combustion and stability aspects of diesel-methanol-hydrous methanol blends utilizing n-octanol, diethyl ether, and nanoparticle additives

The current research endeavored to boost the applicability of methanol in CI engines utilizing n-octanol, diethyl ether (DEE), and different nanoparticle additives (at a concentration of 50 ppm), mainly aluminum oxide, titanium oxide, multiwalled carbon nanotube, graphene oxide, and graphene nanoplatelets as cosolvents and ignition improvers. The work was split into binary phases. First, the stabilities of pure methanol (M100) and hydrous methanol (MH10), with diesel as a reference fuel, were examined by applying various temperatures: 10 °C, 20 °C, and 30 °C. The findings showed that the M100/diesel and MH10/diesel combinations were unstable. To overcome this issue, n-octanol was utilized as a cosolvent. Following by the engine burning and emission characteristics were evaluated by manipulating three proportions of M100/diesel mixtures with n-octanol and DEE. The three mixtures included 5, 10, and 15% of M100 with 25% n-octanol and 5% DEE, which are denoted as DM5, DM10, and DM15, correspondingly. Then, 50 ppm of each nanoparticle was inserted separately into DM5 and DM10 blends to augment the ignition characteristics. The tested mixtures were assessed via thermogravimetric analysis, and their physicochemical properties were assessed corresponding to the ASTM. The results indicated that the maximum Pcyl., HRR, and dp/dθ diminished for the M100/diesel/n-octanol/DEE combinations compared with the diesel. Similarly, they were lowered by inserting nanoparticles. Moreover, the BTE lowered, whereas the BSFC enlarged for the tested mixtures compared with the diesel. The opposite trend was remarked with manipulating nanoparticles. Concerning engine emissions, the NOx and smoke opacity levels also diminished, whereas the CO and UHC enlarged for the DM5, DM10, and DM15 blends compared to the diesel. Inserting nanoparticles into DM5 and DM10 mixtures reduced NOx, CO, UHC, and smoke opacity levels by up to 35%, 20%, 60, and 40%, respectively, compared with DM5 and DM10. It can be concluded that applying n-octanol, Diethyl ether, and nanoparticles as cosolvents and improvers with diesel-methanol blends demonstrated a considerable enhancement in phase stability issue, combustion, and emission characteristics of the diesel engine.

Combination of Lanosterol and Nilvadipine Nanosuspensions Rescues Lens Opacification in Selenite-Induced Cataractic Rats.

It has recently been reported that lanosterol (LAN) plays a preventive role against lens opacification through the reversal of crystalline aggregation. However, the effect of LAN is not sufficient to restore lens transparency. In this study, we designed ophthalmic nanosuspensions (LAN-ONSs and NIL-ONSs) based on LAN and nilvadipine (NIL), which can counteract cataract-related factors (e.g., enhanced Ca2+ and calpain levels), and investigated whether the combination of LAN-ONSs and NIL-ONSs can restore the nuclear lens opacity in sodium-selenite-induced cataractic rats (cataractic rats). The mean particle sizes of the LAN-ONSs and NIL-ONSs were 108.8 nm and 89.0 nm, respectively. The instillation of the LAN-ONSs or NIL-ONSs successfully delivered the drugs (LAN or NIL) into the lenses of the rats, although the instillation of LAN-ONSs or NIL-ONSs alone did not increase lens transparency in the cataractic rats. On the other hand, the cataract-related factors (enhanced Ca2+ and calpain levels) were significantly alleviated by the combination of LAN-ONSs and NIL-ONSs; furthermore, the perinuclear refractile ring in the lens nucleus and enhanced number of swollen fibers were attenuated by the LAN-ONS and NIL-ONS combination. Moreover, the opacity levels in the cataractic rats were reduced after treatment with the combination of LAN-ONSs and NIL-ONSs. It is possible that the combination of LAN and NIL will be useful for the treatment of lens opacification in the future.

Effects of Transparency on Perceived Humanness: Implications for Rendering Skin Tones Using Optical See-Through Displays.

Current optical see-through displays in the field of augmented reality are limited in their ability to display colors with low lightness in the hue, saturation, lightness (HSL) color space, causing such colors to appear transparent. This hardware limitation may add unintended bias into scenarios with virtual humans. Humans have varying skin tones including HSL colors with low lightness. When virtual humans are displayed with optical see-through devices, people with low lightness skin tones may be displayed semi-transparently while those with high lightness skin tones will be displayed more opaquely. For example, a Black avatar may appear semi-transparent in the same scene as a White avatar who will appear more opaque. We present an exploratory user study ( N=160) investigating whether differing opacity levels result in dehumanizing avatar and human faces. Results support that dehumanization occurs as opacity decreases. This suggests that in similar lighting, low lightness skin tones (e.g., Black faces) will be viewed as less human than high lightness skin tones (e.g., White faces). Additionally, the perceived emotionality of virtual human faces also predicts perceived humanness. Angry faces were seen overall as less human, and at lower opacity levels happy faces were seen as more human. Our results suggest that additional research is needed to understand the effects and interactions of emotionality and opacity on dehumanization. Further, we provide evidence that unintentional racial bias may be added when developing for optical see-through devices using virtual humans. We highlight the potential bias and discuss implications and directions for future research.

Analysis Of The Use Of Diethyl Ether Additives In Biodiesel (B20) On Diesel Engine Exhaust Gas Emissions

Although biodiesel is an alternative fuel that has promising potential for use in diesel engines. However, currently, biodiesel used in the market is still the dominant content of diesel from fossil fuels and biodiesel is used as additional material. The purpose of this research is to reduce the number of exhaust emissions produced by biodiesel (B20). This research was conducted using an experimental method, several samples were tested from biodiesel fuel (B20), then biodiesel was added with diethyl ether (DEE) with a ratio of 1%, 2%, 3%, 4% and 5% in each litre. Testing of several samples was carried out to measure the level of exhaust gas emission (opacity) produced by each sample using the Opacity Smokemeter. The results of the research from the addition of diethyl ether (DEE) to biodiesel (B20) were able to reduce the level of opacity. The lowest opacity level was found in the diethyl ether (DEE) mixture of 5%, namely 42.37%. Where the value of the difference or decrease in smoke thickness or opacity when compared to biodiesel (B20) is 2.88% for B20 + 1% DEE, 4.26% for B20 + 2% DEE, 7.70% for B20 + 3% DEE, 10,50% for B20 + 4% DEE and 12.76% for B20 + 5% DEE.

The Effect of Using Blue Light Filter Feature on Smartphones with Asthenopia Occurrence

Background: Smartphone users can be found in almost every class society in Indonesia. Excessive use of smartphones and the blue light emitted by smartphones play an important role in causing asthenopia symptoms. Smartphone development companies have developed a blue light filter feature, which is expected to reduce the incidence of Asthenopia symptoms.Objective: To evaluate the Asthenopia questionnaire's comparison results before and after smartphone use with various levels of opacity in the blue light filter.Methods: This study used a quasi-experimental pre-posttest study. The research subjects were students of the Faculty of Medicine, Diponegoro University (n = 30), selected by purposive sampling. In this study, research subjects saw an hour-long smartphone with a predetermined opacity level for the blue light filter, with the same room lighting. Before and after the treatment, the subjects were asked to fill out the Asthenopia questionnaire. Data were analyzed using the Wilcoxon test, Mann Whitney U test, and Kruskal Wallis test.Results: The results of the Asthenopia questionnaire before and after using a smartphone with a blue light filter opacity level of 0% and 100% showed a significant difference in results (p &lt;0.05), and there was no significant difference for the pre-posttest using a smartphone with a blue light filter with 50% opacity level. The comparison results of the Asthenopia questionnaire between smartphone use with the opacity level of the blue light filter 0% and 50% only showed a significant difference in sore/aching eye symptoms. The comparison results of the Asthenopia questionnaire between smartphone use with the opacity level of the blue light filter 50% and 100% only showed a significant difference in sleepy eye symptoms. The comparison results of the Asthenopia questionnaire between smartphone use with the opacity level of the blue light filter 0%, 50%, and 100%, did not show a significant difference.Conclusion: There were no significant differences between the Asthenopia questionnaire results with 0%, 50%, and 100% opacity blue light filters after one hour of smartphone use.

Emission characteristics and fuel consumption of biodiesel obtained from fish canning industry waste in agriculture diesel engine

Increasing the need for fuel oil is something that can’t be avoided, while the supply of fossil fuels is running low. Biodiesel is one of the right solutions to overcome this problem. This vast ocean in Indonesia, makes Indonesia the potential to create biodiesel from fish canning industry waste. The purpose of this research is to analyze the effect of dexlite fuel mixture with biodiesel from fish canning industry waste on fuel consumption and exhaust gas opacity in agriculture diesel engines. This type of research uses experimental research. The object of this research is the exhaust emissions and fuel consumption. The results of the study obtained by the researchers are the results of mixing dexlite of Pertamina (gasoil/high speed diesel oil) fuel with biodiesel of fish waste oil to be used in diesel engines. The highest exhaust gas opacity results in a mixture of 70% dexlite with 30% biodiesel (B30) of 2.6% at 1000 RPM (± 5). The results of the test fuel consumption that most quickly runs out occur in pure dexlite for 131 seconds in 10 ml of fuel at 1000 RPM (± 5). The results of testing the exhaust gas opacity level are increasing, as well as the results of testing fuel consumption which is increasingly economical, due to the high water, carbon and ash content in biodiesel.

A deep learning-based model for screening and staging pneumoconiosis

This study aims to develop an artificial intelligence (AI)-based model to assist radiologists in pneumoconiosis screening and staging using chest radiographs. The model, based on chest radiographs, was developed using a training cohort and validated using an independent test cohort. Every image in the training and test datasets were labeled by experienced radiologists in a double-blinded fashion. The computational model started by segmenting the lung field into six subregions. Then, convolutional neural network classification model was used to predict the opacity level for each subregion respectively. Finally, the diagnosis for each subject (normal, stage I, II, or III pneumoconiosis) was determined by summarizing the subregion-based prediction results. For the independent test cohort, pneumoconiosis screening accuracy was 0.973, with both sensitivity and specificity greater than 0.97. The accuracy for pneumoconiosis staging was 0.927, better than that achieved by two groups of radiologists (0.87 and 0.84, respectively). This study develops a deep learning-based model for screening and staging of pneumoconiosis using man-annotated chest radiographs. The model outperformed two groups of radiologists in the accuracy of pneumoconiosis staging. This pioneer work demonstrates the feasibility and efficiency of AI-assisted radiography screening and diagnosis in occupational lung diseases.

The influence of centrifugal particulate matter reducer on gas opacity and fuel consumption of inspection train

This study aims at determining the level of exhaust gas opacity and fuel consumption using a centrifugal particulate matter reducer in a diesel-engine inspection train. The opacity level was tested using a smoke tester and fuel consumption measurement per 30 seconds. The test was carried out by varying the types of diesel fuel including Bio-solar, Dexlite, and Pertamina Dex. Based on the test results, there is a decrease in exhaust gas opacity for the use of Bio solar and Dexlite fuels by 5.75% and 6.3%, while the type of Pertamina Dex gained an increase of opacity by 0.6%, respectively. Besides, it was an escalation of fuel consumption in Bio-solar and Pertamina Dex by 7.7% and 2.7%, respectively, while Dexlite did not change the amount of fuel consumption.