Improved energy recovery from dark fermented cane molasses using microbial fuel cells

A major limitation associated with fermentative hydrogen production is the low substrate conversion efficiency. This limitation can be overcome by integrating the process with a microbial fuel cell (MFC) which converts the residual energy of the substrate to electricity. Studies were carried out to check the feasibility of this integration. Biohydrogen was produced from the fermentation of cane molasses in both batch and continuous modes. A maximum yield of about 8.23 mol H₂/kg COD_removed was observed in the batch process compared to 11.6 mol H₂/kg COD_removed in the continuous process. The spent fermentation media was then used as a substrate in an MFC for electricity generation. The MFC parameters such as the initial anolyte pH, the substrate concentration and the effect of pre-treatment were studied and optimized to maximize coulombic efficiency. Reductions in COD and total carbohydrates were about 85% and 88% respectively. A power output of 3.02 W/m³ was obtained with an anolyte pH of 7.5 using alkali pre-treated spent media. The results show that integrating a MFC with dark fermentation is a promising way to utilize the substrate energy.     

Environmental over enthusiasm

India needs large dams for water storage, hydropower and flood control. It also needs long-distance inter-basin water transfers. However, India has a complex and strict environmental regulatory system which ignores a developing economy's needs and peoples' aspirations and is often impractical. This is used by activists to thwart infrastructure building, and, when faced with development slowdown, the government tries to thwart the laws they themselves have made. India's food, water and energy security, economic, and poverty-alleviation plans are in jeopardy unless environmental regulators realize that the regulations are being misused and that environmental over-enthusiasm is benefiting neither development nor the environment.     

Effects of Clinorotation on Growth and Chlorophyll Content of Rice Seeds

Microgravity, as a different environment, has been shown to affect plant growth and development (Sievers et al. 1996; Sack 1997). In the present study, effects of slow clinorotation (2 rpm) on growth and chlorophyll content in rice (variety: PRH-10) seedlings were investigated. Rice seeds were clinorotated continuously for 3, 5 and 7 days under ambient conditions. Root and shoot lengths and weights of rice seedlings were measured on the third, fifth and seventh day. Chlorophyll was extracted using N, N-Dimethylformamide (DMF). Absorption and fluorescence spectra of chlorophyll were recorded. Chlorophyll a, chlorophyll b and total chlorophyll contents were calculated from absorption spectra using Arnon’s method. Results showed an increase in root and shoot lengths in clinorotated samples. Similar results were obtained for root and shoot weights. Absorption spectra of chlorophyll showed no shift in the absorption peaks. Chlorophyll content was increased in clinorotated samples as compared to the controls. Interestingly, the difference between chlorophyll content in control and clinorotated samples decreased as the number of days of clinorotation increased. Chlorophyll a/b ratio was lowered in clinorotated samples as compared to the controls. These results suggest that slow clinorotation (2 rpm) affects plant growth and chlorophyll content in rice seedlings.     

Changes in volatile composition during fruit development and ripening of ‘Alphonso’ mango

BACKGROUND: Volatile blends of five developing and five ripening stages of mango (Mangifera indica L. cv. Alphonso) were investigated along with those of flowers and leaves. Raw and ripe fruits of cv. Sabja were also used for comparison. RESULTS: A total of 55 volatiles belonging to various chemical classes such as aldehydes, alcohols, mono‐ and sesquiterpene hydrocarbons, lactones and furanones were identified. In all Alphonso tissues monoterpenes quantitatively dominated, with 57–99% contribution; in particular, (Z)‐ocimene was found in the highest amount. Ripeness was characterized by the de novo appearance of lactones and furanones in the blend of monoterpenes. Sabja was distinguished by the abundance of monoterpene hydrocarbons in the raw fruit, and that of sesquiterpene hydrocarbons and their derivatives in the ripe stage. CONCLUSION: Various stages of the Alphonso fruit during transition from flower to ripe fruit are characterized by unique volatile signatures that are distinguished from each other by the qualitative and quantitative appearance of different volatile compounds. Thus volatiles can be highly informative markers while studying the development and ripening of mango. Copyright © 2009 Society of Chemical Industry     

Human activity recognition using multidimensional indexing

In this paper, we develop a novel method for view-based recognition of human action/activity from videos. By observing just a few frames, we can identify the activity that takes place in a video sequence. The basic idea of our method is that activities can be positively identified from a sparsely sampled sequence of a few body poses acquired from videos. In our approach, an activity is represented by a set of pose and velocity vectors for the major body parts (hands, legs, and torso) and stored in a set of multidimensional hash tables. We develop a theoretical foundation that shows that robust recognition of a sequence of body pose vectors can be achieved by a method of indexing and sequencing and it requires only a few pose vectors (i.e., sampled body poses in video frames). We find that the probability of false alarm drops exponentially with the increased number of sampled body poses. So, matching only a few body poses guarantees high probability for correct recognition. Our approach is parallel, i.e., all possible model activities are examined at one indexing operation. In addition, our method is robust to partial occlusion since each body part is indexed separately. We use a sequence-based voting approach to recognize the activity invariant to the activity speed.     

Data-dependent systems profilometry of two-dimensional surfaces

Fourier-transform profilometry (FTP) and data-dependent systems profilometry (DDSP) are two methods that are available for recovering one-dimensional fine surface profiles from the phase of a single interferogram. FTP has already been extended to two-dimensional surfaces; a similar extension of DDSP is introduced here. Inasmuch as this extension involves autoregressive modeling of the rows or columns of an interferogram, the feasibility of using a common model order is explored. The common order reduces not only the amount of computation but also the errors caused by the heterodyned phase-removal procedure. As autoregression requires masking the first few data values, the length of the mask is determined by means of a Green's function. A comparison shows that DDSP outperforms FTP in roughness measurements in terms of rms and center-line average. The comparison also shows that DDSP is able to recover a detailed surface, whereas FTP outlines only the global features. An interferogram regeneration procedure provides a reference surface for the verification of results.     

Precipitation scavenging of polycyclic aromatic hydrocarbons in Mumbai, India

The concurrent rain and air sampling was conducted for thirteen rain events between the last week of May and end of June 2001. Concentration of total PAHs varied from 84.25 to 777.49 ng/l whereas that in air was in the range of 4.05 to 34.42 ng/m(3). In rainwater the lower molecular weight PAHs (e.g. Phenanthrene, Fluoranthene and Pyrene) were found to be more prominent than the higher molecular weight compounds. The gas phase scavenging ratio (Wg) was found to increase with the molecular weight of the compound. The particle phase scavenging ratio (Wp) values for the more volatile PAHs were generally much higher than those for less volatile PAHs. The higher MW PAHs have Wg values equal to or larger than their Wp values.     

An iterative learning controller with reduced sampling rate for plants with variations of initial states

In this paper a discrete-time iterative learning controller for single input single output systems is presented. The iterative learning controller works with a reduced sampling rate that ensures the reduction of an appropriate norm of the error trajectory from cycle to cycle and can cope with initial state error. Initial state error occurs when the initial state of the system is different from the initial state that is implicitly given by the reference trajectory. If the initial state changes for every learning iteration, then the controller cannot achieve ideal tracking but the error trajectory is bounded. Using two different sample times together with a potentially time variant learning gain improves the controller performance for dealing with initial state error. Simulation examples are presented to show the results of the proposed iterative learning controller with reduced sampling rate.