Abstract: Parkinson’s patients suffer from severe tremor due to an abnormality in their central oscillator. Medications used to decrease involuntary antagonistic muscles contraction can threaten their life. However, mechanical vibration absorbers can be used as an alternative treatment. The objective of this study is to provide a dynamic modeling of the human hand that describes the biodynamic response of Parkinson’s patients and to design an effective tuned vibration absorber able to suppress their pathological tremor. The hand is modeled as a three degrees-of-freedom (DOF) system describing the flexion motion at the proximal joints on the horizontal plane. Resting tremor is modeled as dual harmonic excitation due to shoulder and elbow muscle activation operating at resonance frequencies. The performance of the single dynamic vibration absorber (DVA) is studied when attached to the forearm and compared with the dual DVA tuned at both excitation frequencies. Equations of motion are derived and solved using the complex transfer function of the non-Lagrangian system. The absorber’s systems are designed as a stainless steel alloy cantilevered beam with an attached copper mass. The dual DVA was the most efficient absorber which reduces 98.3%–99.5%, 97.0%–97.3% and 97.4%–97.5% of the Parkinson’s tremor amplitude at the shoulder, elbow and wrist joint.
Abstract: Pepsin was used to effectively degrade chitosan in order to make it more useful in biotechnological applications. The optimal conditions of enzymolysis were investigated on the basis of the response surface methodology (RSM). The structure of the degraded product was characterized by degree of depolymerization (DD), viscosity, molecular weight, FTIR, UV-VIS, SEM and polydispersity index analyses. The mechanism of chitosan degradation was correlated with cleavage of the glycosidic bond, whereby the chain of chitosan macromolecules was broken into smaller units, resulting in decreasing viscosity. The enzymolysis by pepsin was therefore a potentially applicable technique for the production of low molecular chitosan. Additionally, the substrate degradation kinetics of chitosan were also studied over a range of initial chitosan concentrations (3.0~18.0 g/L) in order to study the characteristics of chitosan degradation. The dependence of the rate of chitosan degradation on the concentration of the chitosan can be described by Haldane’s model. In this model, the initial chitosan concentration above which the pepsin undergoes inhibition is inferred theoretically to be about 10.5 g/L.
Abstract: Deep drying and torrefaction compose a thermal pretreatment method where biomass is heated in the temperature range of 150–300 °C in an inert or reduced environment. The process parameters, like torrefaction temperature and residence time, have a significant impact on the proximate, ultimate, and energy properties. In this study, torrefaction experiments were conducted on 2-mm ground lodgepole pine (Pinus contorta) using a thermogravimetric analyzer. Both deep drying and torrefaction temperature (160–270 °C) and time (15–120 min) were selected. Torrefied samples were analyzed for the proximate, ultimate, and higher heating value. The results indicate that moisture content decreases with increases in torrefaction temperature and time, where at 270 °C and 120 min, the moisture content is found to be 1.15% (w.b.). Volatile content in the lodgepole pine decreased from about 80% to about 45%, and ash content increased from 0.77% to about 1.91% at 270 °C and 120 min. The hydrogen, oxygen, and sulfur content decreased to 3%, 28.24%, and 0.01%, whereas the carbon content and higher heating value increased to 68.86% and 23.67 MJ/kg at 270 °C and 120 min. Elemental ratio of hydrogen to carbon and oxygen to carbon (H/C and O/C) calculated at 270 °C and a 120-min residence time were about 0.56 and 0.47. Based on this study, it can be concluded that higher torrefaction temperatures ≥230 °C and residence time ≥15 min influence the proximate, ultimate, and energy properties of ground lodgepole pine.
Abstract: During advanced biological wastewater treatment, a huge amount of sludge is produced as a by-product of the treatment process. Hence, reuse and recovery of resources and energy from the sludge is a big technological challenge. The processing of sludge produced by Wastewater Treatment Plants (WWTPs) is massive, which takes up a big part of the overall operational costs. In this regard, anaerobic digestion (AD) of sewage sludge continues to be an attractive option to produce biogas that could contribute to the wastewater management cost reduction and foster the sustainability of those WWTPs. At the same time, AD reduces sludge amounts and that again contributes to the reduction of the sludge disposal costs. However, sludge volume minimization remains, a challenge thus improvement of dewatering efficiency is an inevitable part of WWTP operation. As a result, AD parameters could have significant impact on sludge properties. One of the most important operational parameters influencing the AD process is temperature. Consequently, the thermophilic and the mesophilic modes of sludge AD are compared for their pros and cons by many researchers. However, most comparisons are more focused on biogas yield, process speed and stability. Regarding the biogas yield, thermophilic sludge AD is preferred over the mesophilic one because of its faster biochemical reaction rate. Equally important but not studied sufficiently until now was the influence of temperature on the digestate quality, which is expressed mainly by the sludge dewateringability, and the reject water quality (chemical oxygen demand, ammonia nitrogen, and pH). In the field of comparison of thermophilic and mesophilic digestion process, few and often inconclusive research, unfortunately, has been published so far. Hence, recommendations for optimized technologies have not yet been done. The review presented provides a comparison of existing sludge AD technologies and the gaps that need to be filled so as to optimize the connection between the two systems. In addition, many other relevant AD process parameters, including sludge rheology, which need to be addressed, are also reviewed and presented.
Abstract: In this study, Aspergillus niger ADM110 fungi was gamma irradiated to produce lipase enzyme and then immobilized onto magnetic barium ferrite nanoparticles (BFN) for biodiesel production. BFN were prepared by the citrate sol-gel auto-combustion method and characterized by transmission electron microscopy (TEM), X-ray diffraction (XRD), Fourier transform infrared (FTIR) and scanning electron microscopy with energy dispersive analysis of X-ray (SEM/EDAX) analysis. The activities of free and immobilized lipase were measured at various pH and temperature values. The results indicate that BFN–Lipase (5%) can be reused in biodiesel production without any treatment with 17% loss of activity after five cycles and 66% loss in activity in the sixth cycle. The optimum reaction conditions for biodiesel production from waste cooking oil (WCO) using lipase immobilized onto BFN as a catalyst were 45 °C, 4 h and 400 rpm. Acid values of WCO and fatty acid methyl esters (FAMEs) were 1.90 and 0.182 (mg KOH/g oil), respectively. The measured flash point, calorific value and cetane number were 188 °C, 43.1 MJ/Kg and 59.5, respectively. The cloud point (−3 °C), pour point (−9 °C), water content (0.091%) and sulfur content (0.050%), were estimated as well.
Abstract: Gene regulatory networks represent an abstract mapping of gene regulations in living cells. They aim to capture dependencies among molecular entities such as transcription factors, proteins and metabolites. In most applications, the regulatory network structure is unknown, and has to be reverse engineered from experimental data consisting of expression levels of the genes usually measured as messenger RNA concentrations in microarray experiments. Steady-state gene expression data are obtained from measurements of the variations in expression activity following the application of small perturbations to equilibrium states in genetic perturbation experiments. In this paper, the least absolute shrinkage and selection operator-vector autoregressive (LASSO-VAR) originally proposed for the analysis of economic time series data is adapted to include a stability constraint for the recovery of a sparse and stable regulatory network that describes data obtained from noisy perturbation experiments. The approach is applied to real experimental data obtained for the SOS pathway in Escherichia coli and the cell cycle pathway for yeast Saccharomyces cerevisiae. Significant features of this method are the ability to recover networks without inputting prior knowledge of the network topology, and the ability to be efficiently applied to large scale networks due to the convex nature of the method.