Optimization of biodiesel yield from waste cooking oil and sesame oil using RSM and ANN techniques.

In the era of global energy crises and the pressing concern of fossil fuel depletion, the quest for sustainable alternatives has become paramount. The current study aims to optimize biodiesel extraction from a combination of waste cooking oil (WCO) and sesame seed oil (SSO) through response surface methodology (RSM) and artificial neural network (ANN). The cold flow properties of biodiesel produced from WCO are a major obstacle to the commercial use of biodiesel. On the other hand, SSO possesses better oxidation stability and cold flow properties. A mixture of waste cooking oil (i.e. 70 % by volume) and sesame seed oil (i.e. 30 % by volume) has been prepared for biodiesel production via a microwave-assisted transesterification process. For biodiesel yield optimization, the interaction among the operating parameters is developed by RSM, whereas biodiesel yield is predicted by ANN. The operating parameters include reaction speed, RPM (100-600 rpm), reaction time (1-5 min), methanol to oil ratio (8:1-12:1 v/v), and catalyst concentration (0.1-2 % w/w). The highest biodiesel yield of 94 % is found at a reaction speed of 350 rpm, reaction time of 3 min, catalyst concentration of 1.05 w/w, and methanol to oil ratio of 10:1. Furthermore, it is discovered that when estimating biodiesel production rate depending on reaction constraints, ANN shows lower comparative error compared to RSM. The results show that ANN outperforms RSM in terms of percentage improvement when it comes to biodiesel production prediction.

Carbon taxation on high utility transport fuels: An implementation of enviro-economic analysis for the sustainable environment".

The humongous increase in carbon emissions in the past few decades presents an environmental challenge to the scientific community. The current study proposes a method of taxation on high-carbon emission fuels. For this purpose, a comparative enviro-economic analysis is carried out on the three most commonly used fuels (gasoline, Liquefied Petroleum Gas (LPG), and Compressed Natural Gas (CNG)). The speed of the test engine varied from 1800 to 4200 Revolution per Minute (RPM) in increments of 400 RPM. Performance parameters (Brake Power (BP), Brake Thermal Efficiency (BTHE), and Brake Specific Fuel Consumption (BSFC)) were measured using a hydro dynamometer. Emission analysis, including Carbon Dioxide (CO2), Carbon Monoxide (CO), Unburned Hydrocarbons (HC), and Nitrogen Oxide (NOx), was conducted using the TESTO 350 analyzer. The application of Weibull distribution with a 95 % confidence interval, on emission data, explained the adequacy of the data. Among test fuels, CNG emerged as an environment-friendly fuel with an emission reduction of 16, 42, and 43 percent for CO2, CO, and HC in comparison to gasoline. Also, BTHE and BSFC of CNG were better than other alternatives. Moreover, the carbon penalty for CNG fuel showed a price reduction of 32 and 20.8 percent in comparison to gasoline and LPG respectively. The study provides a novel approach to assess the environmental impact of fuels by economic analysis based on emitted carbon quantity. In addition, this very idea is novel in promoting the Sustainable Development Goals (SDG) of the United Nations (UN) through carbon taxation.

Maximizing biodiesel yield of a non-edible chinaberry seed oil via microwave assisted transesterification process using response surface methodology and artificial neural network techniques.

In this study, the non-edible Chinaberry Seed Oil (CBO) is converted into biodiesel using microwave assisted transesterification. The objective of this effort is to maximize the biodiesel yield by optimizing the operating parameters, such as catalyst concentration, methanol-oil ratio, reaction speed, and reaction time. The designed setup provides a controlled and effective approach for turning CBO into biodiesel, resulting in encouraging yields and reduced reaction times. The experimental findings reveal the optimal parameters for the highest biodiesel yield (95 %) are a catalyst concentration of 1.5 w/w, a methanol-oil ratio of 6:1 v/v, a reaction speed of 400 RPM, and a reaction period of 3 min. The interaction of the several operating parameters on biodiesel yield has been investigated using two methodologies: Response Surface Methodology (RSM) and Artificial Neural Network (ANN). RSM provides better modeling of parameter interaction, while ANN exhibits lower comparative error when predicting biodiesel yield based on the reaction parameters. The percentage improvement in prediction of biodiesel yield by ANN is found to be 12 % as compared to RSM. This study emphasizes the merits of both the approaches for biodiesel yield optimization. Furthermore, the scaling up this microwave-assisted transesterification system for industrial biodiesel production has been proposes with focus on its economic viability and environmental effects.

Investigation into the Ideal Concoction for Performance and Emissions Enhancement of Jatropha Biodiesel-Diesel with CuO Nanoparticles Using Response Surface Methodology.

The present work covers the preparation of biodiesel from jatropha oil through the transesterification process followed by its characterization, and furthermore, performance and emission analyses were done in terms of blending biodiesel with fossil diesel and CuO nanoparticles. Jatropha biodiesel blends (B10, B20, and B30) were chosen for this preliminary investigation based on the observation that B20 outperformed other blends. Next stage B20 with copper oxide (CuO) nanoparticle concentrations of 25, 50, 75, and 50 ppm are used to examine the performance and emission characteristics of a constant speed single cylinder, 4-stroke, 3.5 kW compression ignition (CI) engine. Finally, The response surface methodology (RSM) was utilized to determine the optimal nanoparticle concentration for B20. The results revealed that the blend of B20 with 80 ppm nanoparticles had the highest desirability (0.9732), and the developed RSM model was able to predict engine responses with a mean absolute percentage error (MAPE) of 3.113%. A confirmation test with an error in prediction of less than 5% verified the model's adequacy. When comparing optimized B20CuO80 to diesel, brake specific energy consumption (BSEC) increased by 8.49% and brake thermal efficiency (BTE) was lowered by 3.34%. Hydrocarbon (HC), carbon monoxide (CO), carbon dioxide (CO2), nitrogen oxide (NOx), and smoke emissions were reduced by 3.66% and 2.88%, 4.78%, 22.9%, and 20.54%, respectively, at 80% load. As a result, the B20 blend with nanoparticle concentrations of 80 ppm may be used in current diesel engines without engine modification.

Novel Method to Achieve Temperature-Stable Microwave Dielectric Ceramics: A Case in the Fergusonite-Structured NdNbO4 System.

Microwave dielectric ceramics with permittivity (εr) ∼ 20 play an important role in massive multiple-input multiple-output (MIMO) technology in 5G. Although fergusonite-structured materials with low dielectric loss are good candidates for 5G application, tuning the temperature coefficient of resonant frequency (TCF) remains a problem. In the present work, smaller V5+ ions (rV = 0.355 Å, with coordination number (CN) = 4) were substituted for Nb5+ (rNb = 0.48 Å with CN = 4) in the Nd(Nb1-xVx)O4 ceramics, which, according to in situ X-ray diffraction data, lowered the fergusonite-to-scheelite phase transition (TF-S) to 400 °C for x = 0.2. The thermal expansion coefficient (αL) of the high-temperature scheelite phase was +11 ppm/°C, whereas for the low-temperature fergusonite phase, it was + 14 < αL < + 15 ppm/°C. The abrupt change in αL, the associated negative temperature coefficient of permittivity (τε), and the minimum value of εr at TF-S resulted in a near-zero TCF ∼ (+7.8 ppm/°C) for Nd(Nb0.8V0.2)O4 (εr ∼ 18.6 and Qf ∼ 70,100 GHz). A method to design near-zero TCF compositions based on modulation of τε and αL at TF-S is thus demonstrated that may also be extended to other fergusonite systems.

4E analysis of a two-stage refrigeration system through surrogate models based on response surface methods and hybrid grey wolf optimizer.

Refrigeration systems are complex, non-linear, multi-modal, and multi-dimensional. However, traditional methods are based on a trial and error process to optimize these systems, and a global optimum operating point cannot be guaranteed. Therefore, this work aims to study a two-stage vapor compression refrigeration system (VCRS) through a novel and robust hybrid multi-objective grey wolf optimizer (HMOGWO) algorithm. The system is modeled using response surface methods (RSM) to investigate the impacts of design variables on the set responses. Firstly, the interaction between the system components and their cycle behavior is analyzed by building four surrogate models using RSM. The model fit statistics indicate that they are statistically significant and agree with the design data. Three conflicting scenarios in bi-objective optimization are built focusing on the overall system following the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP) decision-making methods. The optimal solutions indicate that for the first to third scenarios, the exergetic efficiency (EE) and capital expenditure (CAPEX) are optimized by 33.4% and 7.5%, and the EE and operational expenditure (OPEX) are improved by 27.4% and 19.0%. The EE and global warming potential (GWP) are also optimized by 27.2% and 19.1%, where the proposed HMOGWO outperforms the MOGWO and NSGA-II. Finally, the K-means clustering technique is applied for Pareto characterization. Based on the research outcomes, the combined RSM and HMOGWO techniques have proved an excellent solution to simulate and optimize two-stage VCRS.

Methotrexate-induced Leukoencephalopathy: A Rare but Life-threatening Toxicity.

Methotrexate (MTX), an anti-metabolite, is part of various chemotherapy regimens to treat acute lymphoblastic leukemia (ALL) and certain non-Hodgkin's lymphomas (NHLs). It is the major drug used in central nervous system (CNS) prophylaxis. Besides, its common hepatic, pulmonary, and hematologic toxicities, it has been implicated in the development of toxic leukoencephalopathy. Here, we present a case of a 19-year female, diagnosed with T-ALL. She was managed with UK ALL 2011 regimen B induction as a standard of care and intrathecal MTX as CNS prophylaxis. She tolerated induction well; however, during the second block of consolidation, she started developing lower limb weakness, inability to stand, unilateral weakness and aphasia. Her condition worsened rapidly over the next 24 hours leading to paraplegia and ultimately quadriplegia. Within 48 hours from onset of symptoms, she had lost all her motor functions, potentially leading to impending apnoea. We placed her on mechanical ventilation. MRI brain showed drug (MTX)-induced leukoencephalopathy (LE). In most cases, recovery starts within 5-7 days and by the 3rd week, majority have usually recovered. However, cases of irreversible neurologic damage and late-onset chronic toxicities have been reported. Key Words: Methotrexate, Leukoencephalopathy, Chemotherapy, Leukemias.

Clinical Pattern and Causality Assessment of Drug-induced Cutaneous Reactions in a Tertiary Care Hospital in India: A Prospective Study.

BACKGROUND: Cutaneous Adverse Drug Reactions (ADRs) are common and pose a serious challenge to physicians, especially in cases when the patient has many comorbidities, is polypharmacy, or self-administers over-the-counter medications. OBJECTIVE: The objective of this study is to analyze the clinical pattern and incidence of cutaneous ADRs and perform causality assessment using the WHO-UMC scale and Naranjo's scale. The severity of the reactions was determined by the Hartwig scale. METHODS: This was conducted as a prospective observational study in patients admitted to SRM Medical College, Kattankulathur, Tamil Nadu, India, between November 2016 to August 2018 after obtaining Institutional Ethics Committee clearance of all adverse drug reactions reported at the hospital. RESULTS: Of the 158 ADRs reported during the time period, 101 were cutaneous ADRs, of which the most common presentation was maculopapular rash (n=42; 41.58%). The most common drugs which produced cutaneous adverse reactions were antimicrobials (n=58; 57.42%) followed by NSAIDs (n=35; 34.6%). The causality assessment as per the Naranjo scale yielded 3.96% (4) cases as definite, 81.18% (82) as probable, and 14.85% (15) as possible, whereas the WHO scale yielded 9 (89.10%) certain, 64 (63.36%) probable and 28 (27.72%) possible cases. The severity of the cases determined as per the Hartwig scale yielded 82.17% cases as mild and 17.82% as moderate. CONCLUSION: It is important to recognise the ADRs at the right time and exert caution in future use. This can minimise harm to the patient both physically and financially and improve the outcome of the treatment.

Solution Processed PVB/Mica Flake Coatings for the Encapsulation of Organic Solar Cells.

Organic photovoltaics (OPVs) die due to their interactions with environmental gases, i.e., moisture and oxygen, the latter being the most dangerous, especially under illumination, due to the fact that most of the active layers used in OPVs are extremely sensitive to oxygen. In this work we demonstrate solution-based effective barrier coatings based on composite of poly(vinyl butyral) (PVB) and mica flakes for the protection of poly (3-hexylthiophene) (P3HT)-based organic solar cells (OSCs) against photobleaching under illumination conditions. In the first step we developed a protective layer with cost effective and environmentally friendly methods and optimized its properties in terms of transparency, barrier improvement factor, and bendability. The developed protective layer maintained a high transparency in the visible region and improved oxygen and moisture barrier quality by the factor of ~7. The resultant protective layers showed ultra-flexibility, as no significant degradation in protective characteristics were observed after 10 K bending cycles. In the second step, a PVB/mica composite layer was applied on top of the P3HT film and subjected to photo-degradation. The P3HT films coated with PVB/mica composite showed improved stability under constant light irradiation and exhibited a loss of <20% of the initial optical density over the period of 150 h. Finally, optimized barrier layers were used as encapsulation for organic solar cell (OSC) devices. The lifetime results confirmed that the stability of the OSCs was extended from few hours to over 240 h in a sun test (65 °C, ambient RH%) which corresponds to an enhanced lifetime by a factor of 9 compared to devices encapsulated with pristine PVB.

Structural elucidation and cytotoxic analysis of a fructan based biopolymer produced extracellularly by Zymomonas mobilis KIBGE-IB14.

Fructan based biopolymers have been extensively characterized and explored for their potential applications. Linear chained biopolymers, like levan-type fructan, have gained attention because they have exhibited unconventional stretchable and unbendable properties along with biodegradable and biocompatible nature. Current study deals with the chemical characterization and cytotoxic analysis of fructose based exopolysaccharide that was extracellularly produced by an indigenously isolated bacterial species (Zymomonas mobilis KIBGE-IB14). Maximum yield of exopolysaccharide (44.7 gL-1) was attained after 72 h of incubation at 30 °C under shaking conditions (180 rpm) when the culture medium was supplemented with 150.0 gL-1 of sucrose as a sole carbon source. This exopolysaccharide displayed high water solubility index (96.0%) with low water holding capacity (17.0%) and an intrinsic viscosity of about 0.447 dL g-1. This biopolymer exhibited a characteristic linear homopolysaccharide structure of levan when characterized using Fourier Transform Infrared (FTIR), Nuclear Magnetic Resonance (NMR) spectroscopy (1H, 13C, TOCSY and NOESY) while, Atomic Force Microscopy (AFM) revealed its pointed and thorny structure. The decomposition temperature of levan was approximately 245 °C as revealed by Thermal Gravimetric Analysis (TGA). X-Ray Diffraction (XRD) results revealed its amorphous nature with crystalline phase. Cytotoxicity of different concentrations of levan was investigated against mouse fibroblast cell lines by measuring their cellular metabolic activity and it was noticed that a higher concentration of levan (2.0 mg ml-1) permitted the normal cell growth of NIH/3T3 cell lines. This non-cytotoxic and biocompatible nature suggests that this levan has the capability to be utilized in food and drug-based formulations as it exhibited biomedical potential.