Semarang, Indonesia
Semarang, Indonesia

Diponegoro University is a public university located in Semarang, Central Java, Indonesia. Founded in 1957 as a private university by the Semarang University Foundation, it is a pioneer of higher learning institutions in Indonesia and the first and oldest education corporation in Central Java. It is a member of IDGHE in Indonesia. Wikipedia.

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Sudarno U.,Karlsruhe Institute of Technology | Sudarno U.,Diponegoro University | Winter J.,Karlsruhe Institute of Technology | Gallert C.,Karlsruhe Institute of Technology
Bioresource Technology | Year: 2011

Nitrification under changing salinities (0-9%), temperatures (6-50°C), ammonia (0-5gNL -1) and nitrite concentrations (0-0.4gNL -1) was investigated in fixed-bed reactors. For all conditions ammonia oxidation rates (AOR) were lower than nitrite oxidation rates (NOR). AORs and NORs increased from 12.5 to 40°C and were very low at 6°C and almost zero at 50°C. No recovery of nitrification was obtained after incubation at 50°C, whereas nitrification was restorable after incubation at 6°C. Ammonia concentrations of 5gNL -1 or nitrite concentrations up to 0.125gNL -1 decreased AOR to almost zero. AORs and NORs recovered if ammonia or nitrite was removed. At concentrations of 1 and 5gNL -1 ammonia AOR and NOR were inhibited by 50%, whereas 27mgN/L nitrite inhibited AOR by 50%. © 2011 Elsevier Ltd.

Syaichurrozi I.,Diponegoro University | Budiyono,Diponegoro University | Sumardiono S.,Diponegoro University
Bioresource Technology | Year: 2013

The biogas fermentation of vinasse (TS 7.015. ±. 0.007%) was investigated within a wide range of COD (Chemical Oxygen Demand)/N (Total Nitrogen) ratio. Urea (46% nitrogen content) was added into substrate to adjust COD/N ratio of 400/7-700/7. This study used batch anaerobic digesters in laboratory-scale that were operated at room temperature in 60. days. The results showed that control variable, 400/7, 500/7, 600/7, 700/7 generated total biogas of 107.45, 123.87, 133.82, 139.17, 113.27. mL/g COD and had the value of COD removal of 31.274. ±. 0.887, 33.483. ±. 0.266, 36.573. ±. 1.689, 38.088. ±. 0.872, 32.714. ±. 0.881%, respectively. Variable with COD/N ratio of 600/7 was the best variable. In the kinetic model of biogas production, variable with COD/N of 600/7 had kinetic constant of A (mL/g COD), μ (mL/g, λ (days) of 132.580, 15.200, 0.213, respectively. The model equation of kinetic of biodegradability organic materials obtained was C(t)=Co-exp-expμeA(λ-t)+1*Co+Ce. © 2013 Elsevier Ltd.

Caesarendra W.,Pukyong National University | Widodo A.,Diponegoro University | Yang B.-S.,Pukyong National University
Mechanical Systems and Signal Processing | Year: 2010

Degradation parameter or deviation parameter from normal to failure condition of machine part or system is needed as an object of prediction in prognostics method. This study proposes the combination between relevance vector machine (RVM) and logistic regression (LR) in order to assess the failure degradation and prediction from incipient failure until final failure occurred. LR is used to estimate failure degradation of bearing based on run-to-failure datasets and the results are then regarded as target vectors of failure probability. RVM is selected as intelligent system then trained by using run-to-failure bearing data and target vectors of failure probability estimated by LR. After the training process, RVM is employed to predict failure probability of individual units of machine component. The performance of the proposed method is validated by applying the system to predict failure time of individual bearing based on simulation and experimental data. The result shows the plausibility and effectiveness of the proposed method, which can be considered as the machine degradation assessment model. © 2009 Elsevier Ltd. All rights reserved.

Hadiyanto,Diponegoro University
International Food Research Journal | Year: 2013

Bread product quality is highly dependent to the baking process. A model for the development of product quality of bread products has been calibrated by experiments at a fixed baking temperature of 200°C and in combination with 100 W of microwave powers. The parameters in this model were estimated in sequence procedures: heat and mass transfer, then product transformations and finally product quality parameters. The results showed that there was an agreement between the calibrated model and the experimental data. Furthermore, the microwave input contributed significantly to the internal product properties but not for the surface properties as crispness and color. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels. © 2008 IFRJ.

Susanto H.,Diponegoro University
Chemical Engineering and Processing: Process Intensification | Year: 2011

Membrane distillation, which combines thermal desalination and porous hydrophobic membrane as non-wetting contact media, is currently gaining increasing important in membrane processes. However, the vast researches and reported publications of membrane distillation (MD) are less followed by its practical/industrial applications. This paper review analyzes the reasons for MD has not widely being implemented in practical/industrial applications. In addition, the strategies towards practical application are presented. Thus, this review will complement previous review of MD papers. © 2010 Elsevier B.V.

Widodo A.,Diponegoro University | Yang B.-S.,Pukyong National University
Expert Systems with Applications | Year: 2011

Condition monitoring (CM) of machines health or industrial components and systems that can detect, classify and predict the impending faults is critical in reducing operating and maintenance cost. Many papers have reported the valuable models and methods of prognostic systems. However, it was rarely found the papers deal with censored data, which was common in machine condition monitoring practice. This work deals with development of machine degradation assessment system that utilizes censored and complete data collected from CM routine. Relevance vector machine (RVM) is selected as intelligent system then trained by input data obtained from run-to-failure bearing data and target vectors of survival probability estimated by Kaplan-Meier (KM) and probability density function estimators. After validation process, RVM is employed to predict survival probability of individual unit of machine component. The plausibility of the proposed method is shown by applying the proposed method to bearing degradation data in predicting survival probability of individual unit. © 2010 Elsevier Ltd. All rights reserved.

to validate the effect of plain kefir on immune responses of hyperglycemia wistar rats induced by Streptozotocin. the randomized pretest - posttest control group study design was conducted in male hyperglycemia Wistar rats induced by streptozotocin (STZ). Rats were randomized into four groups: (1) STZ-induced group were given insulin treatment 0.76 UI/200 g bw, (2) STZ-induced group and treated with plain kefir 3.6 cc/200 g bw/day for 30 days, (3) STZ-induced group as control, (4) normal animal group as a negative control. Blood glucose was measured from whole blood that was taken 0.1 ml from retroorbitalis vein by microhematocrit on day 1 (pretest) and day 30 (post test) by enzymatic methods. Immune responses (cytokines IL1, IL6, IL10, TNF) were measured by ELISA. Data were analyzed by one way Anova, Mann Whitney test and Duncan with significant level of p<0.05. plain kefir supplementation 3.6 cc/day affect blood glucose, proinflamatory cytokines (IL1, IL6, TNF) and antiinflamatory cytokine (IL10). Statistical analysis showed decrease of glucose -111.00±44.23 ml (p<0.001) and proinflamatory cytokines IL1 about -18.62±23.59 and IL6 -3.21±7.57 mU/mL (p<0.001), respectively compared to the control groups. TNF decreased 1.65±4.62 mU/mL, but not significant (p>0.05), except for controls group. In addition, antiinflammatory (IL10) showed also increase about 15.11±2.16 (p<0.05), except for the control. plain kefir supplementation significantly decreased blood glucose, level of cytokines (IL1, IL6) and lowered TNF level. On the contrary, the level of IL10 is increased compare to control groups.

Widodo A.,Diponegoro University | Yang B.-S.,Pukyong National University
Expert Systems with Applications | Year: 2011

Prognostic of machine health estimates the remaining useful life of machine components. It deals with prediction of machine health condition based on past measured data from condition monitoring (CM). It has benefits to reduce the production downtime, spare-parts inventory, maintenance cost, and safety hazards. Many papers have reported the valuable models and methods of prognostics systems. However, it was rarely found the papers deal with censored data, which is common in machine condition monitoring practice. This work concerns with developing intelligent machine prognostics system using survival analysis and support vector machine (SVM). SA utilizes censored and uncensored data collected from CM routine and then estimates the survival probability of failure time of machine components. SVM is trained by data input from CM histories data that corresponds to target vectors of estimated survival probability. After validation process, SVM is employed to predict failure time of individual unit of machine component. Simulation and experimental bearing degradation data are employed to validate the proposed method. The result shows that the proposed method is promising to be a probability-based machine prognostics system. © 2011 Elsevier Ltd. All rights reserved.

Ahmad M.,Prince of Songkla University | Benjakul S.,Prince of Songkla University | Prodpran T.,Prince of Songkla University | Agustini T.W.,Diponegoro University
Food Hydrocolloids | Year: 2012

Gelatin films incorporated with bergamot (BO) and lemongrass oil (LO) at various concentrations as glycerol substitute were prepared and characterised. Incorporation of BO and LO at 5-25% (w/w protein) resulted in the decreases in both tensile strength (TS) and elongation at break (EAB) of the films. Water vapour permeability (WVP) were decreased in LO incorporated films, while it was increased in film added with BO at level higher than 5% (P<0.05). Film solubility and transparency values decreased, and the films had the lowered light transmission in the visible range when BO and LO were incorporated. Films incorporated with LO showed inhibitory effect in a concentration dependent manner against Escherichia coli, Listeria monocytogenes, Staphylococcus aureus and Salmonella typhimurium, but BO added film inhibited only L.monocytogenes and S.aureus. Films containing both BO and LO did not inhibit Pseudomonas aeruginosa. Significant change of molecular organisation and higher intermolecular interactions among gelatin molecules were found in the film structure as determined by FTIR. Thermo-gravimetric analysis (TGA) demonstrated that films added with BO and LO exhibited enhanced heat stability with higher degradation temperature, compared with control film. Scanning electron microscopic (SEM) images revealed the presence of micro-pores in the essential oil incorporated films, which contributed to physical properties of the resulting films. Thus, gelatin films incorporated with BO and LO can be used as active packaging, but the properties could be modified, depending on essential oil added. © 2011 Elsevier Ltd.

Agency: Cordis | Branch: FP7 | Program: CP-FP | Phase: KBBE.2010.3.2-01 | Award Amount: 3.85M | Year: 2011

The aim of MARINE FUNGI is the demonstration of sustainable exploitation of marine natural resources providing appropriate culture conditions for the underutilised group of marine fungi, thus enabling efficient production of marine natural products in the laboratory and also in large scale cultures, avoiding harm to the natural environment. The focus of MARINE FUNGI are new anti-cancer compounds The project will carry out the characterisation of these compounds to the stage of in vivo proof of concept ready to enter further drug development in order to valorise the results of the project. MARINE FUNGI covers two approaches to gain effective producer strains: a) Candidate strains originating from one partners strain collection will be characterised and optimised using molecular methods. b) New fungi will be isolated from unique habitats, i.e. tropical coral reefs, endemic macroalgae and sponges from the Mediterranean. Culture conditions for these new isolates will be optimised for the production of new anti-cancer metabolites. MARINE FUNGI will develop a process concept for these compounds providing the technological basis for a sustainable use of marine microbial products as result of Blue Biotech. The project will explore the potential of marine fungi as excellent sources for useful new natural compounds. This will be accomplished by the formation of a new strongly interacting research network comprising the scientific and technological actors, including 3 SMEs and 2 ICPC partners, necessary to move along the added-value chain from the marine habitat to the drug candidate and process concept. The generated and existing knowledge will be disseminated widely for the valorisation of the project results.

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