Optimum Sizing Algorithm for an Off Grid Plant Considering Renewable Potentials and Load Profile

The energy demand in remote area cannot be satisfied unless renewable energy based plants are locally installed. In order to be efficient, such projects should be sized on the basis of maximizing the renewable energies exploitation and meeting the consumer needs. The aim of this work is to provide an algorithm-based calculation of the optimum sizing of a standalone hybrid plant composed of a wind generator, a photovoltaic panel, a lead acid-battery bank, and a water tank. The strategy consists of evaluating the renewable potentials (solar and wind). Obtained results are entered as inputs to established generators models in order to estimate the renewable generations. The developed optimal sizing algorithm which is based on iterative approach, computes plant components sizes for which load profile meet estimated renewable generations. The approach validation is conducted for A PV/Wind/Battery based farm located in Sfax, Tunisia. Obtained results proved that the energetic need is covered and only about 4% of the generated energy is not used. Also a cost investigation confirmed that the plant becomes profitable ten years after installation.Article History: Received June 24th 2017; Received in revised form September 26th 2017; Accepted Sept 30th 2017; Available onlineCitation: Brahmi, N., Charfi, S., and Chaabene, M. (2017) Optimum Sizing Algorithm for an off grid plant considering renewable potentials and load profile. Int. Journal of Renewable Energy Development, 6(3), 213-224.https://doi.org/10.14710/ijred.6.3.213-22

In vitro ruminal fermentation, nutritional evaluation and antioxidant activity of some forest shrubs of North West Tunisia for goats

Chemical composition and characteristics of in vitro fermentation were determined for two shrubs (Genista aspalathoides and Rhamnus alaternus) collected from north western Tunisia. The primary and secondary chemical composition was determined and in vitro fermentation parameters were measured in 100 ml glass syringes for 48 hours to determine gas production. There are significant differences in chemical and wall composition for the two shrubs studied (p < 0.05). Rhamnus alaternus is richer in secondary metabolites (59.2 mg GAE / g DM) than Genista aspalathoides and has the highest content of crude protein (CP). Genista aspalathoides had the lowest anti-radical activity since it has the highest levels of secondary metabolites, so it is the most digestible species with the highest value of gas production after 24 hours incubation and released more methane than Rhamnus alaternus. Keywords: Shrub, Chemical composition, in vitro fermentation, antioxidant activity, methan

Isolation and identification of bacterial strain I33M producing milk-clotting enzyme: Optimization of culture parameters using response surface

A strain I33M which produces a milk-clotting enzyme was screened from Algerian soil near a dairy factory. This strain was identified as Bacillus mojavensis based on morphology and internal transcription spacer sequence. Sequencing analysis of 16S rDNA gene showed 100% identity of the tested strain with the B. mojavensis in the database. Phylogenetic analysis of this strain showed that it was most closely related to Bacillus subtilis strain. The optimum levels of these significant parameters to obtain the highest milk clotting activity and the lowest proteolytic activity were determined employing the response surface methodology (RSM), which revealed these as follows: wheat bran 7%, casein 0.094%, temperature 39°C, agitation size (rpm) 150. Among the various variables screened, agitation and temperature were most significant in submerged fermentation (SmF). The optimal value of milk clotting activity (MCA) is esteemed at 2.40. Key words: Milk clotting protease, Bacillus, response surface methodology, sequencing analysis

Carbon Sequestration Potential of Pasture-Based Systems Along an Altitudinal Gradient in the North-Western Himalayas

The present investigation was carried out in the Chamba district of Himachal Pradesh (India) to identify the pasture-based land use systems being practiced by farmers and to find out their carbon sequestration potential along different altitudes. For carrying out the study, the area was divided into four altitudinal ranges viz., zone-I (\u3c1000 m amsl), zone-II (1000-1500 m amsl), zone-III (1500- 2500 m amsl) and zone-IV (\u3e 2500 m amsl), according to agro-ecological zones in the state. Results revealed that the pasture-based systems practiced by the farmers in the altitudinal zone-I and zone-II were silvo-pasture and pastoral-silviculture, while, at altitudinal zone-III and zone-IV, the pasture-based systems being practiced were pastoral-silviculture and horti-pastoral depending upon the composition of the components. The aboveground biomass was found ranging between 27.78- 38.18 Mg ha-1 among different pasture-based land use systems with maximum aboveground biomass under silvo-pasture system and minimum under pastoral-silviculture. Along altitudinal gradient, aboveground biomass was found to have been increased with values varying between 29.09- 34.12 Mg ha-1 . Belowground biomass ranged between 6.93- 9.80 Mg ha-1 in different systems under consideration and generally showed increasing trend with increasing altitude. Overall biological productivity was found to be highest under silvo-pasture system followed by horti-pastoral and pastoral-silviculture system. Being biologically most productive, silvopasture system stored maximum carbon stock and ultimately sequestered more carbon as compared to the other systems. The estimated vegetation carbon sequestration potential of the pasture-based systems was 63.71- 88.06 Mg ha-1 , while, along altitude the carbon sequestration potential varied from 67.14- 78.62 Mg ha-1 showing increasing trend with altitude

Optical and photoelectronic properties of a new material:Optoelectronic application

With the aim of studying the optical, electrochemical, and electronic properties of a new porphyrin-based material, we have synthesized a new porphyrinic complex, namely the (4,4$^{\prime}$-bipyridine)(meso-tetratrifluoromethylphenylporphyrinato)zinc(II) 4,4$^{\prime}$-bipyridine disolvate dihydrate complex with the formula [Zn(TFMPP)(4,4$^{\prime}$-bipy)]${\cdot }$2(4,4$^{\prime}$-bipy)${\cdot }$2H2O (I). This species is characterized by single-crystal X-ray molecular structure. The optical study is performed by UV–visible absorption and fluorescence spectroscopy. The fluorescence intensity presents an emission in the UV–visible range, indicating that this compound can be used as an optoelectronic material. The optical energy gap is 1.95 eV, and the current–voltage characteristics and impedance spectroscopy measurements have been studied to define the electronic properties of the zinc (II) porphyrin complex. The barrier height ${\phi }_{\mathrm{b}}$ is calculated, and the space-charge limited current mechanism is found to control the conductance. The results from the electronic study confirm that our porphyrin derivative can be used for various optoelectronic applications

Toxicity and neurophysiological impacts of three plant-derived essential oils against the vineyard mealybug Planococcus ficus

Many natural products are able to control pests and can be used as alternatives for chemical treatments. Plant essential oils (EOs) have been found to exhibit some biological activity against many insects including mealybugs. This study aimed at studying the insecticidal activity and behavioral and neurophysiological impacts of three plant essential oils against the vine mealybug Planococcus ficus. The topical and fumigant toxicity of Cymbopogon citratus, Mentha piperita, and Pelargonium graveolens essential oils was evaluated against P. ficus adults. The chemical composition analysis of EOs by gas chromatographic-mass spectrometry (GC-MS) revealed citronellal (31.69 %), menthol (73.78 %), and geraniol (39.6%), as major components, respectively. Bioassays of EOs against vine mealybug adults through fumigation toxicity method revealed lethal concentrations LC50 values of 17.01, 26.27 and 24.52 µL·L-1 air for C. citratus, M. piperita, and P. graveolens, respectively. In both topical and fumigant bioassays, essential oil from C. citratus was the most active altering the behavioral response of treated mealybugs which becomes hyperactive and disoriented. EOs induced general stress in P. ficus adults, as evidenced by oxidative stress biomarker analyses. Biochemical analyses showed that the EOs exposure reduced the activity of acetylcholinesterase and significantly induced the glutathione S-transferases and Malondialdehydes accumulation in the vine mealybug tissues. Mortality caused by lemongrass EO positively correlated with the significant decrease in the AChE activity indicating lethal neurological effects. These toxicity bioassays and neurological impact findings provide new informations for formulating effective essential oil based-insecticides to control P. ficus in the framework of integrated pest management programs

Neutral high-generation phosphorus dendrimers inhibit macrophage-mediated inflammatory response in vitro and in vivo

Inflammation is part of the physiological response of the organism to infectious diseases caused by organisms such as bacteria, viruses, fungi, or parasites. Innate immunity, mediated by mono nuclear phagocytes, including monocytes and macrophages, is a first line of defense against infectious diseases and plays a key role triggering the delayed adaptive response that ensures an efficient defense against pathogens. Monocytes and macrophages stimu lation by pathogen antigens results in activation of different signaling pathways leading to the release of proinflammatory cyto kines. However, inflammation can also participate in the pathogenesis of several diseases, the autoimmune diseases that represent a relevant burden for human health. Dendrimers are branched, multivalent nanoparticles with a well-defined structure that have a high potential for biomedical applications. To explore new approaches to fight against the negative aspects of inflammation, we have used neutral high-generation phosphorus dendrimers bearing 48 (G3) or 96 (G4) bisphosphonate groups on their surface. These dendrimers show no toxicity and have good solubility and chemical stability in aqueous solutions. Here, we present data indicating that neutral phosphorus dendrimers show impressive antiinflammatory activities both in vitro and in vivo. In vitro, these dendrimers reduced the secretion of proinflammatory cytokines from mice and human monocyte derived macrophages. In addition, these molecules present efficient antiinflammatory activity in vivo in a mouse model of subchronic inflammation. Taken together, these data suggest that neutral G3- G4 phosphorus dendrimers have strong potential applications in the therapy of inflammation and, likely, of autoimmune diseases.info:eu-repo/semantics/publishedVersio

An efficient partial data aggregation scheme in WSNs

Highly accurate event detection makes Wireless Sensor Networks popular for real time monitoring applications. Wireless sensor systems that monitor physical and environmental conditions are expected to be deployed with high density, a situation which leads to spatial correlations and redundancy of the collected data. Eliminating these redundancies extends the network lifetime by reducing energy consumption and enhances the velocity of transmitting emergency and periodic messages. In this work, we focus on the scenario where sensors are grouped into clusters. Each Cluster Head (CH) receives samplings from its Cluster Members (CMs), and decides when it should stop sampling, and starts transmitting the resulting packet from the aggregation process in order to reduce the end-to-end delay and ensure the accuracy of the transmitted data. To this end, we propose a cluster based aggregation scheme which determines, at the CH level, the best timing for achieving a short delay, and provides an efficient buffer management strategy for maintaining low energy consumption. Evaluation results based on simulations show that our scheme achieves a good trade-off between energy consumption and end-to-end delay

Planning & Acting: Optimal Markov Decision Scheduling of Aggregated Data in WSNs by Genetic Algorithm

Data aggregation techniques have emerged as promising solutions for extending Wireless Sensor Networks (WSNs) lifetime. However, this approach suffers from a design issue in delivering the strict requirements needed by some monitoring applications. Carefully balancing Energy, Delay and Accuracy is essential for achieving these requirements. In this work, we focus on distributed data aggregation, where a sensor estimates the network information by the exchange of readings with different priority levels. We then propose an optimal decision policy for scheduling the transmission of the aggregated data at the node level. To model the investigated problem, we first adopt Markov Decision Process (MDP) whereby we define the reward function. Then, we apply a Genetic Algorithm (GA) to find a set of optimal decisions that ensures the best trade-off between energy saving, delay and accuracy of the received data based on their priority level. The simulation results yield excellent performance and our optimization shows a significant enhancement up to 20% compared to the other policies