Temporal variability, meteorological influences, and long-range transport of atmospheric aerosols over two contrasting environments Agartala and Patiala in India.

The present study focused on the temporal variability, meteorological influences, potential sources, and long-range transport of atmospheric aerosols over two contrasting environments during 2011-2013. We have chosen Agartala (AGR) city in Northeast India as one of our sites representing the rural-continental environment and Patiala (PTA) as an urban site in Northwest India. The seasonal averaged equivalent black carbon (eBC) concentration in AGR ranges from 1.55 to 38.11 µg/m3 with an average value of 9.87 ± 8.17 µg/m3, whereas, at an urban location, PTA value ranges from 1.30 to 15.57 µg/m3 with an average value of 7.83 ± 3.51 µg/m3. The annual average eBC concentration over AGR was observed to be ~ 3 times higher than PTA. Two diurnal peaks (morning and evening) in eBC have been observed at both sites but were observed to be more prominent at AGR than at PTA. Spectral aerosol optical depth (AOD) has been observed to be in the range from 0.33 ± 0.09 (post-monsoon) to 0.85 ± 0.22 (winter) at AGR and 0.47 ± 0.04 (pre-monsoon) to 0.74 ± 0.09 (post-monsoon) at PTA. The concentration of eBC and its diurnal and seasonal variation indicates the primary sources of eBC as local sources, synoptic meteorology, planetary boundary layer (PBL) dynamics, and distant transportation of aerosols. The wintertime higher values of eBC at AGR than at PTA are linked with the transportation of eBC from the Indo-Gangetic Plain (IGP). Furthermore, it is evident that eBC aerosols are transported from local and regional sources, which is supported by concentration-weighted trajectory (CWT) analysis results.

Frequent contiguous pattern mining over biological sequences of protein misfolded diseases.

BACKGROUND: Proteins are integral part of all living beings, which are building blocks of many amino acids. To be functionally active, amino acids chain folds up in a complex way to give each protein a unique 3D shape, where a minor error may cause misfolded structure. Genetic disorder diseases i.e. Alzheimer, Parkinson, etc. arise due to misfolding in protein sequences. Thus, identifying patterns of amino acids is important for inferring protein associated genetic diseases. Recent studies in predicting amino acids patterns focused on only simple protein misfolded disease i.e. Chromaffin Tumor, by association rule mining. However, more complex diseases are yet to be attempted. Moreover, association rules obtained by these studies were not verified by usefulness measuring tools. RESULTS: In this work, we analyzed protein sequences associated with complex protein misfolded diseases (i.e. Sickle Cell Anemia, Breast Cancer, Cystic Fibrosis, Nephrogenic Diabetes Insipidus, and Retinitis Pigmentosa 4) by association rule mining technique and objective interestingness measuring tools. Experimental results show the effectiveness of our method. CONCLUSION: Adopting quantitative experimental methods, this work can form more reliable, useful and strong association rules i. e. dominating patterns of amino acid of complex protein misfolded diseases. Thus, in addition to usual applications, the identified patterns can be more useful in discovering medicines for protein misfolded diseases and thereby may open up new opportunities in medical science to handle genetic disorder diseases.

CricShotClassify: An Approach to Classifying Batting Shots from Cricket Videos Using a Convolutional Neural Network and Gated Recurrent Unit.

Recognizing the sport of cricket on the basis of different batting shots can be a significant part of context-based advertisement to users watching cricket, generating sensor-based commentary systems and coaching assistants. Due to the similarity between different batting shots, manual feature extraction from video frames is tedious. This paper proposes a hybrid deep-neural-network architecture for classifying 10 different cricket batting shots from offline videos. We composed a novel dataset, CricShot10, comprising uneven lengths of batting shots and unpredictable illumination conditions. Impelled by the enormous success of deep-learning models, we utilized a convolutional neural network (CNN) for automatic feature extraction, and a gated recurrent unit (GRU) to deal with long temporal dependency. Initially, conventional CNN and dilated CNN-based architectures were developed. Following that, different transfer-learning models were investigated-namely, VGG16, InceptionV3, Xception, and DenseNet169-which freeze all the layers. Experiment results demonstrated that the VGG16-GRU model outperformed the other models by attaining 86% accuracy. We further explored VGG16 and two models were developed, one by freezing all but the final 4 VGG16 layers, and another by freezing all but the final 8 VGG16 layers. On our CricShot10 dataset, these two models were 93% accurate. These results verify the effectiveness of our proposed architecture compared with other methods in terms of accuracy.

Classification of Indoor Human Fall Events Using Deep Learning.

Human fall identification can play a significant role in generating sensor based alarm systems, assisting physical therapists not only to reduce after fall effects but also to save human lives. Usually, elderly people suffer from various kinds of diseases and fall action is a very frequently occurring circumstance at this time for them. In this regard, this paper represents an architecture to classify fall events from others indoor natural activities of human beings. Video frame generator is applied to extract frame from video clips. Initially, a two dimensional convolutional neural network (2DCNN) model is proposed to extract features from video frames. Afterward, gated recurrent unit (GRU) network finds the temporal dependency of human movement. Binary cross-entropy loss function is calculated to update the attributes of the network like weights, learning rate to minimize the losses. Finally, sigmoid classifier is used for binary classification to detect human fall events. Experimental result shows that the proposed model obtains an accuracy of 99%, which outperforms other state-of-the-art models.

Image Defogging Framework Using Segmentation and the Dark Channel Prior.

Foggy images suffer from low contrast and poor visibility problem along with little color information of the scene. It is imperative to remove fog from images as a pre-processing step in computer vision. The Dark Channel Prior (DCP) technique is a very promising defogging technique due to excellent restoring results for images containing no homogeneous region. However, having a large homogeneous region such as sky region, the restored images suffer from color distortion and block effects. Thus, to overcome the limitation of DCP method, we introduce a framework which is based on sky and non-sky region segmentation and restoring sky and non-sky parts separately. Here, isolation of the sky and non-sky part is done by using a binary mask formulated by floodfill algorithm. The foggy sky part is restored by using Contrast Limited Adaptive Histogram Equalization (CLAHE) and non-sky part by modified DCP. The restored parts are blended together for the resultant image. The proposed method is evaluated using both synthetic and real world foggy images against state of the art techniques. The experimental result shows that our proposed method provides better entropy value than other stated techniques along with have better natural visual effects while consuming much lower processing time.

Study of spectral characteristics of black carbon from biomass burning and source apportionment over Agartala in the northeastern India.

We have studied the black carbon (BC) mass concentrations, contributions from Fossil Fuels (FF), and Biomass burning (BB) to total BC mass concentrations using a 7-wavelength Aethalometer (Model, AE-31; Make, Magee Scientific, USA) at a rural continental location in the northeastern India. We have taken the continuous measurements of BC from January 2011 to December 2017 (excluding the year 2016 due to nonavailability of data). The annual mean BC concentration at 880 nm is observed maximum 12.56±5.06 µgm-3 in the year 2011 with a minimum of 7.26±2.76 µgm-3 during the year 2015." is the final sentence. BC, BCff, and BCbb mass concentrations show significant variation during morning, afternoon, evening, and night hours. The significant monthly, seasonal, and annual variabilities in the BC concentration, equivalent BC from FF and BB, are due to seasonal change in the emission sources, boundary layer dynamics, and dispersion and dilution conditions. The determination of Angstrom exponent (α) for the BC emitted during burning of different biofuels by performing a burning experiment is an important part of the present study. We have conducted a survey in and around the study location to know the different biofuels used by the people for daily household activities, and those biofuels are used in the burning experiment. As a result of biomass burning experiment to determine Angstrom exponent, we have found the α values to be ranging from 1.20 to 2.37 for flaming and a range from 1.59 to 2.33 for smoldering conditions for different biofuels. Annual mean contributions of BCff and BCbb to the total BC are found to be dominated by FF emissions during the whole study period. The percentage contribution of BCff and BCbb is found to be 56% and 44% during winter season due to increase in wood and biomass burning activities for various purposes. We have found the higher percentage contribution from BCff (85%) during monsoon season due to reduction in usage of biofuels.

Andrographolide induces oxidative stress-dependent cell death in unicellular protozoan parasite Trypanosoma brucei.

African sleeping sickness is a parasitic disease in humans and livestock caused by Trypanosoma brucei throughout sub-Saharan Africa. Absence of appropriate vaccines and prevalence of drug resistance proclaim that a new way of therapeutic interventions is essential against African trypanosomiasis. In the present study, we have looked into the effect of andrographolide (andro), a diterpenoid lactone from Andrographis paiculata on Trypanosoma brucei PRA 380. Although andro has been recognized as a promosing anti-cancer drug, its usefulness against Trypanosoma spp remained unexplored. Andro showed promising anti-trypanosomal activity with an IC50 value of 8.3µM assessed through SYBR Green cell viability assay and also showed no cytotoxicity towards normal murine macrophages. Cell cycle analysis revealed that andro could induce sub-G0/G1 phase arrest. Flow cytometric analysis also revealed that incubation with andro caused exposure of phosphatidyl serine to the outer leaflet of plasma membrane in T. brucei PCF. This event was preceded by andro-induced depolarization of mitochondrial membrane potential (Δym) and elevation of cytosolic calcium. Andro also caused elevation of intracellular reactive oxygen species (ROS) as well as lipid peroxidation level, and depletion in reduced thiol levels. Taken together, these data indicate that andro has promising antitrypanosomal activity mediated by promoting oxidative stress and depolarizing the mitochondrial membrane potential and thereby triggering an apoptosis-like programmed cell death. Therefore, this study merits further investigation to the therapeutic possibility of using andro for the treatment of African trypanosomiasis.

Atmospheric aerosol radiative forcing over a semi-continental location Tripura in North-East India: Model results and ground observations.

Northeast India (NEI) is located within the boundary of the great Himalayas in the north and the Bay of Bengal (BoB) in the southwest, experiences the mixed influence of the westerly dust advection from the Indian desert, anthropogenic aerosols from the highly polluted Indo-Gangetic Plains (IGP) and marine aerosols from BoB. The present study deals with the estimation and characterization of aerosol radiative forcing over a semi-continental site Tripura, which is a strategic location in the western part of NEI having close proximity to the outflow of the IGP. Continuous long term measurements of aerosol black carbon (BC) mass concentrations and columnar aerosol optical depth (AOD) are used for the estimation of aerosol radiative forcing in each monthly time scale. The study revealed that the surface forcing due to aerosols was higher during both winter and pre-monsoon seasons, having comparable values of 32W/m2 and 33.45W/m2 respectively. The atmospheric forcing was also higher during these months due to increased columnar aerosol loadings (higher AOD ~0.71) shared by abundant BC concentrations (SSA ~0.7); while atmospheric forcing decreased in monsoon due to reduced magnitude of BC (SSA ~0.94 in July) as well as columnar AOD. The top of the atmosphere (TOA) forcing is positive in pre-monsoon and monsoon months with the highest positive value of 3.78W/m2 in June 2012. The results are discussed in light of seasonal source impact and transport pathways from adjacent regions.

Dihydrochelerythrine and its derivatives: Synthesis and their application as potential G-quadruplex DNA stabilizing agents.

A convenient route was envisaged toward the synthesis of dihydrochelerythrine (DHCHL), 4 by intramolecular Suzuki coupling of 2-bromo-N-(2-bromobenzyl)-naphthalen-1-amine derivative 5 via in situ generated arylborane. This compound was converted to (±)-6-acetonyldihydrochelerythrine (ADC), 3 which was then resolved by chiral prep-HPLC. Efficiency of DHCHL for the stabilization of promoter quadruplex DNA structures and a comparison study with the parent natural alkaloid chelerythrine (CHL), 1 was performed. A thorough investigation was carried out to assess the quadruplex binding affinity by using various biophysical and biochemical studies and the binding mode was explained by using molecular modeling and dynamics studies. Results clearly indicate that DHCHL is a strong G-quadruplex stabilizer with affinity similar to that of the parent alkaloid CHL. Compounds ADC and DHCHL were also screened against different human cancer cell lines. Among the cancer cells, (±)-ADC and its enantiomers showed varied (15-48%) inhibition against human colorectal cell line HCT116 and breast cancer cell line MDA-MB-231 albeit low enantio-specificity in the inhibitory effect; whereas DHCHL showed 30% inhibition against A431 cell line only, suggesting the compounds are indeed cancer tissue specific.