Abstract This study was aimed to develop the haloperidol (HPL) loaded solid lipid nanoparticles (SLNs) for brain targeting through the intranasal route. SLNs were fabricated by the emulsification diffusion technique using glyceryl behenate as lipid and tween 80 as a surfactant. SLNs were evaluated for particle size, zeta potential, structure, entrapment efficiency, solid state characterization by differential scanning calorimetry (DSC), and in-vitro release. In-vivo biological evaluation was performed on albino Wistar rats for the determination of pharmacokinetic as well as brain targeting parameters. Particle size, PDI, zeta potential, and entrapment efficiency of optimized formulation (HPL-SLNs 6) were found to be 103±09 nm, 0.190±0.029, -23.5±1.07 mV, and 79.46±1.97% respectively. In-vitro drug release studies exhibited that 87.21± 3.63% of the entrapped drug was released from the SLNs within 24 h. DSC curves confirmed that during entrapment in SLNs, the drug was solubilized in the lipid matrix and converted into the amorphous form. Enhanced HPL targeting to the brain was observed from HPL-SLNs as compared to HPL-Sol when administered intranasally. The value of AUC 0-∞ in the brain for HPL-SLNs i.n. was found to be nearly 2.7 times higher than that of HPL-Sol i.v., whereas 3.66 times superior to HPL-Sol administered i.n. Stability studies revealed that the formulation remains unchanged when stored at 4±2 °C (refrigerator) and 25±2 °C /60 ±5% RH up to six months. Finally, it could be concluded that SLN is a suitable carrier for HPL with enhanced brain targeting through i.n administration, as compared to the HPL-Sol, administered i.n. and i.v.

Abstract This study was aimed to explore the chemical composition and biological activities of essential oil from aerial part of Mosla dianthera along with its major isolated compound, carvone. The hydro-distilled essential oil was analysed by GC-MS and biological activities were investigated in terms of antioxidant, anti-inflammatory, herbicidal, antibacterial, anti-fungal and anti-feedant properties. GC-MS analysis led to the identification of forty-nine components contributing 96.2% of essential oil with carvone (41.9%) as the most abundant constituent. The oil and carvone showed good to moderate antioxidant potentials determined by radical scavenging, reducing power and metal chelating activities. Carvone showed good anti-inflammatory activity (78.0%) compared to essential oil (74.2%). Both essential oil and carvone exhibited excellent herbicidal activity against Raphanus raphanistrum subsp. sativus seeds. The essential oil and carvone showed significant anti-bacterial efficacy against Bacillus cereus and Escherichia coli. It was observed that essential oil showed strong antifungal property than carvone against Alternaria alternata and Curvularia lunata. Both the samples exhibited anti-feedant activity in a dose dependent manner against third instar larvae of Spilosoma obliqua. Results obtained revealed the possible applications of essential oil and carvone as a bioactive source of natural antioxidants, excellent herbicide and an effective substance for antifungal and antifeedant activities.

Abstract: Supervised classification of hyperspectral remote sensing images is still challenging due to the scarcity of enough labelled samples. Semi-supervised methods have been adopted to handle this issue. Self-training is a popular semi-supervised technique which is widely used for training a classifier with limited labelled data and a large quantity of unlabeled data. However, traditional self-training approaches often give poor classification results in high dimensional data. In the current work, a novel efficient self-training approach for handling the deficiency of labelled samples for semi-supervised classification of hyperspectral remote sensing images is proposed. The proposed method first trains an ensemble of locally specialized supervised binary classifiers independently by using the dimensionally reduced spectral feature vectors of few available labelled samples. The trained local binary classifiers are then used to extend the labelled set by iterative addition of highly informative unlabeled samples to it by exploiting both the spectral and spatial information of the hyperspectral image. The classifiers are then retrained with the extended dataset in a batchwise manner and the procedure is repeated until adequate quantity of labelled samples are generated. Finally, a supervised multiclass classifier is trained on the extended dataset to produce the final classification map. Experimental results on two benchmark hyperspectral image datasets prove the effectiveness of the proposed method over supervised and traditional self-training based semi-supervised pixelwise classification approach in terms of different classification measures.

Abstract: The convergence of Social Mobility Analytics and Cloud (SMAC) technologies gives rise to an unforeseen aggrandization of the web services on the internet. The resilience and payment-based approach of the cloud makes it an obvious choice for the deployment of web services-based applications. Out of available web services, to gratify the similar functionalities, the choice of the web service based on the personalized quality of service (QoS) parameters plays an important role in determining the selection of the web service. The role of time is rarely being discussed in deciding the QoS of web services. The delivery of QoS is not made as declared due to the non-functional performance of web services correlated behavior with the invocation time. This happens because service status usually changes over time. Hence, the design of the time aware web service recommendation system based on the personalized QoS parameters is very crucial and becomes a challenging research issue. In this study, LSTM based deep learning models were used for the prediction of these time aware QoS parameters and the results are compared with the previous approaches. The experimental results show that the LSTM based Time Series Forecasting Framework is performing better. The RMSE, MAE, and MAPE are used as an evaluation metric and their value for the prediction of Response time (RT) is found to be 0.030269, 0.02382 and 0.59773 respectively with adaptive moment estimation as the training option and is found to be 0.66988, 0.66465 and 27.9934 respectively with root mean square propagation as the training option. The RMSE, MAE, and MAPE value for the prediction of throughput (TP) is found to be 0.77787, 0.4792 and 1.61 respectively with adaptive moment estimation as the training option and is found to be 0.2.7087, 1.4076and 7.1559 respectively with root mean square propagation as the training option respectively. Thus, the experimental results show that the LSTM model of Time Series Forecasting for Web Services Recommendation Framework is performing better as compared to previous methods.

Abstract DBW222 is characterized by potential yield of 8210 kg ha-1 under high fertility when sown in timely conditions in North India. It possesses better agronomic attributes and has better adaption to sowing time, high rust resistance, quality attributes, and lodging tolerance because of a shorter 2nd internode and wider diameter.

ABSTRACT Red rot, caused by Colletotrichum falcatum Went is the most important disease of sugarcane in India inflicting substantial loss to both cane industry and cane growers. To keep in view the importance of red rot disease of sugarcane, 117 accession of sugarcane germplasm including different Saccharum species and Indian and foreign commercial hybrids were tested against red rot with Cf 07, Cf 08 & Cf 09 (national pathotypes) by plug method of inoculation. Out of 117, 6 were found resistant and 12 were moderately resistant against red rot and rest were moderately susceptible/susceptible/highly susceptible. Theses resistance and moderately resistant accession can be further utilize to produce resistance varieties against the most devastating pathogen of sugarcane.

The present study involves the discovery of quality of soils associated with dump mines and native forest encompassing the Kakari mine, a coal mining site in Sonbhadra, to distinguish the effect of coal mining on associated soil ecosystem. Soil ecophysiological indicator of the site was analyzed in terms of floral diversity by method of quadrat analysis, which revealed that dumps were devoid of any floral community whereas the natural forest around the mines was enriched with a number of plant species. Importance value index (IVI) was calculated and with respect to their IVI index the tree species viz., Acacia mangium (23.17, 24.48 & 26.81) and Acacia catechu (20.34, 22.10 & 25.36) were found to be the most dominant species. Soil enzymatic and physico-chemical analysis were analyzed by standard method and the result emphasized that dump soils possess poor enzymatic activity and acidic pH due to the decomposition of waste material in dumps which eventually affects the microbial diversity of soil and its fertility. The plant growth promotion (PGP) and stress tolerance characteristics of bacterial isolates were further examined so that the potential isolates will be utilized further to reclaim and remediate soil property of degraded soils. The promising isolates were characterized by BIOLOG identification system and isolate NU36 and NU25 showed greatest similarity with Pseudomonas sp. and Acinetobacter sp. respectively. Based on the potential to produce plant growth promoting substances and withstand in stressed environment the most promising isolates will be used to remediate soil and reclaim soil characteristics.

Repeated soil amendment with industrial waste can affect the accumulation of chemical elements, mainly heavy metals, in plants. We therefore evaluated the accumulation of Cr, Cd, Ni, and Pb in cowpea (Vigna unguiculata [L.] Walp.) shoots and grains in soil amended for three consecutive years with tannery sludge compost (TSC). Tannery sludge compost was applied annually starting in 2009 at 0, 2.5, 5, 10, and 20 t ha-1 and cowpea was sown. At 40 and 60 d after cowpea sowing, the accumulation of Cr, Cd, Pb, and Ni was evaluated in the shoots and grains, respectively. The experiment used completely randomized design with four replicates and data were subjected to ANOVA and F-test (5%). Only Cr accumulation was significant (P < 0.05) in the cowpea shoots after 3 yr of TSC amendment; accumulation increased as TSC rates were applied. However, there was no significant Cr, Cd, Ni, and Pb accumulation in grains. After 3 yr of consecutive TSC soil amendments, Cr accumulated in the shoots, but it was not translocated to the grains.

A geração de resíduos de curtume está aumentando a cada ano e um método adequado para o manejo do resíduo de curtume é necessário para diminuir o problema ambiental. A compostagem é reconhecido como um método adequado para a reciclagem do lodo. O objetivo do trabalho foi investigar o efeito da aplicação de composto de lodo de curtume (CLC) sobre o crescimento, nodulação e acumulação de nitrogênio do feijão-caupi. Solos arenoso e argiloso foram adubados com CLC em doses de 0, 7,5, 15, 30 e 60 t ha-1. O comprimento da parte aérea do feijão-caupi foi maior, aos 45 dias após a emergência das plantas (DAE), no solo com aplicação de CLC do que no solo sem aplicação. No solo arenoso, a massa dos nódulos, aos 45 DAE, aumentou com a aplicação do CLC. No solo argiloso, aos 45 DAE, em doses superiores a 7,5 t ha-1, houve um decréscimo na massa nodular quando comparado ao solo sem aplicação. A aplicação do CLC aumentou a acumulação de N nas plantas de feijão-caupi. Os resultados sugerem que o feijão-caupi responde diferentemente ao CLC sendo dependente da dose de aplicação e do tipo de solo.

Tannery wastes generation is increasing every year and a suitable method for tannery sludge management is necessary in order to decrease this environmental problem. The composting is recognized as a suitable method for sludge recycling.. The effect of tannery sludge compost (TSC) rates on growth, nodulation and N fixation of cowpea was investigated. Sandy and clayey soils were amended with TSC at rates of 0, 7.5, 15, 30, and 60 t ha-1. The shoot dry weight of cowpea plants 45 days after emergence (DAE) was greater in the TSC-amended than in the unamended soil. In the sandy soil, nodule dry weight increased with TSC application 45 DAE. In the clayey soil, 45 DAE, nodule dry weight decreased with TSC amendment levels greater than 7.5 t ha-1 compared to the unamended control. The application of TSC increased N accumulation in the cowpea plants. The results suggest that cowpea responds differently to TSC depending on the amendment rate and initial soil type.

Combined effect of polycarboxylate type superplasticizer and sodium sulphate on the hydration of fly ash blended Portland® cement has been studied by using different techniques. Water consistency, setting times, non-evaporable water contents, water percolation, air contents, compressive strengths and expansion in corrosive atmosphere were determined. Hydration products were examined with the help of DTA and X-ray diffraction techniques. It is found that the superplasticizer reduces the pore size and its adsorption on cement surfaces is decreased in the presence of sodium sulphate. Mechanism of hydration is discussed.

During our investigation in the area of epileptic drug discovery, we have identified that the available conventional antiepileptic drugs are effective in 60-80% patients and in specific type of seizures and having various undesirable side effects. But in present time aonew class aryl semicarbazone is emerged asonew pharmacophore in epileptic drug discovery having broad spectrum activity. On the bases of work done in this area we have applied hybridization of pharmacophore strategy of drug design and developed aonew pharmacophore. We have also designed a scheme for synthesizing such pharmacophore and performed their pharmacological screening for the protection of seizures, behavioral study and CNS activity. The compound 1-[1-(2,4-dihydroxyphenyl)-3-(2-hydroxyphenyl) allylidene]-4-(2-fluorophenyl) semicarbazide (8) emerged as the most active prototype molecule in all the models.