Improved fuzzy multi-objective transportation problem with Triangular fuzzy numbers.

The present study investigates a Multi-Objective Transportation Problem within a fuzzy environment. The cost of transportation, supply, and demand data are assumed to be inaccurate due to market variations. As a result, the parameters are imprecise or fuzzy data. We offer a multi-objective, balanced transportation problem during this work, where all the parameters are fuzzy numbers. Following a mathematical formulation, fuzzy arithmetic will be used to divide the Fuzzy MOTP into three levels MOTP (lower, medium, upper). After reducing the problem to a crisp MOTP and applying a harmonic mean to each objective function, a suggested solution procedure is presented. Determining the optimal solutions for the FMOTP under unknown situations is, thus, the most important objective of this research.

Adsorption of brilliant green dye onto activated carbon prepared from cashew nut shell by KOH activation: Studies on equilibrium isotherm.

Activated carbon from cashew nut shell via a potassium hydroxide (KOH) at 600 °C in an N2 atmosphere and their characteristics using FT-IR, XRD, SEM with EDS, and BET analysis was investigated. The cashew nut shell activated carbon obtained by KOH activation with a CNS/KOH ratio of 1:1 at 600 °C (N2 atmosphere) for 2 h had the highest surface area (407.80 m2/g) as compared to other ratio samples. Amongst, CNS/KOH ratios of 1:1 sample are used for the adsorbent, they are effects of contact time, pH, adsorbent dose, and initial dye concentration on brilliant green (BG) removal efficiency were studied. Moreover, the Langmuir and Freundlich adsorption models consisted utilized to affirm the adsorption isotherms. They are, best fitting for BG experimental equilibrium data was achieved with the Langmuir isotherm, giving a maximum BG adsorption capacity of 243.90 mg/g.

Substituting brown rice for white rice on diabetes risk factors in India: a randomised controlled trial.

India has the second largest number of people with type 2 diabetes (T2D) globally. Epidemiological evidence indicates that consumption of white rice is positively associated with T2D risk, while intake of brown rice is inversely associated. Thus, we explored the effect of substituting brown rice for white rice on T2D risk factors among adults in urban South India. A total of 166 overweight (BMI ≥ 23 kg/m2) adults aged 25-65 years were enrolled in a randomised cross-over trial in Chennai, India. Interventions were a parboiled brown rice or white rice regimen providing two ad libitum meals/d, 6 d/week for 3 months with a 2-week washout period. Primary outcomes were blood glucose, insulin, glycosylated Hb (HbA1c), insulin resistance (homeostasis model assessment of insulin resistance) and lipids. High-sensitivity C-reactive protein (hs-CRP) was a secondary outcome. We did not observe significant between-group differences for primary outcomes among all participants. However, a significant reduction in HbA1c was observed in the brown rice group among participants with the metabolic syndrome (-0·18 (se 0·08) %) relative to those without the metabolic syndrome (0·05 (se 0·05) %) (P-for-heterogeneity = 0·02). Improvements in HbA1c, total and LDL-cholesterol were observed in the brown rice group among participants with a BMI ≥ 25 kg/m2 compared with those with a BMI < 25 kg/m2 (P-for-heterogeneity < 0·05). We observed a smaller increase in hs-CRP in the brown (0·03 (sd 2·12) mg/l) compared with white rice group (0·63 (sd 2·35) mg/l) (P = 0·04). In conclusion, substituting brown rice for white rice showed a potential benefit on HbA1c among participants with the metabolic syndrome and an elevated BMI. A small benefit on inflammation was also observed.

Glycaemic index of three Indian rice varieties.

Three commonly consumed Indian rice varieties (Sona Masuri, Ponni and Surti Kolam) were tested for their glycaemic index (GI). Healthy volunteers were recruited and after an overnight fast were given a 50 g available carbohydrate portion of glucose (reference food) or different varieties of cooked rice (test foods) on separate occasions. The fasting as well as postprandial capillary blood glucose response was determined over 2 h, and the incremental area under the curve (IAUC) was calculated. The GI was calculated as the IAUC of the test food/IAUC of the reference food (glucose) × 100. The differences between the GI values for Sona Masuri (72.0 ± 4.5), Ponni (70.2 ± 3.6) and Surti Kolam (77.0 ± 4.0) rice varieties were non-significant (p = 0.606) and are all classified as high GI varieties of rice. There is an urgent need to study the GI of other commonly consumed rice varieties and to develop rice of a lower GI value.