ROI-Finder: machine learning to guide region-of-interest scanning for X-ray fluorescence microscopy.

The microscopy research at the Bionanoprobe (currently at beamline 9-ID and later 2-ID after APS-U) of Argonne National Laboratory focuses on applying synchrotron X-ray fluorescence (XRF) techniques to obtain trace elemental mappings of cryogenic biological samples to gain insights about their role in critical biological activities. The elemental mappings and the morphological aspects of the biological samples, in this instance, the bacterium Escherichia coli (E. Coli), also serve as label-free biological fingerprints to identify E. coli cells that have been treated differently. The key limitations of achieving good identification performance are the extraction of cells from raw XRF measurements via binary conversion, definition of features, noise floor and proportion of cells treated differently in the measurement. Automating cell extraction from raw XRF measurements across different types of chemical treatment and the implementation of machine-learning models to distinguish cells from the background and their differing treatments are described. Principal components are calculated from domain knowledge specific features and clustered to distinguish healthy and poisoned cells from the background without manual annotation. The cells are ranked via fuzzy clustering to recommend regions of interest for automated experimentation. The effects of dwell time and the amount of data required on the usability of the software are also discussed.

Yield improvement of Gracilaria tenuistipitata by optimizing different aspects in coast of cox's bazar, Bangladesh.

This research was designed to find out the effect of different factors such as influence of lunar cycle, harvesting interval, rope type and seeding gap on the production of G. tenuistipitata in coast of Cox's Bazar. Duration of these experiments were sixty days and all the parameters were recorded fortnightly. Monitoring of water quality parameters indicated that salinity, temperature, transparency, pH and DO were suitable for seaweed cultivation. In determining lunar cycle effect, results envisaged that fresh yield was 14.43% increased when seeding and harvesting time was selected considering the moon cycle. Regarding the selection of harvesting interval, it was found that T3 (30 days interval) was the best to harvest the seaweed whereas T4 (40 days interval) showed decreasing trend in production. Our study also found that semi floating single line showed better yield performance compared to semi floating double line system. In case of influence on seeding gap, it has been found that 20 cm gap between two seed showed the highest yields followed by 10 cm, 30 cm and 40 cm, respectively. Overall, it can be concluded that yield of G. tenuistipitata in coast of Cox's Bazar could be improved considering those factors.

Accumulation of heavy metals in soil and their transfer to leafy vegetables in the region of Dhaka Aricha Highway, Savar, Bangladesh.

Accumulation of heavy metals in environmental matrices is a potential risk to living system due to their uptake by plants and subsequent introduction into the food chain. A study was conducted to investigate the heavy metals concentration in soils and leafy vegetables samples along the Dhaka Aricha Road to assess their potential ecological risk. Heavy metals concentration was analyzed by Atomic Absorption Spectroscopy. Concentrations ofallthetestedheavy metals except Cd in soil samples were below the permissible level. The mean concentration of Cd was found 3.99 +/- 1.85 mg kg(-1). Concentrations of all the tested heavy metals except Cd and Cr in vegetables samples were lower than recommended level. Mean concentration of Cd and Cr were found 1.00 +/- 0.68 mg kg(-1) and 2.32 +/- 0.84 mg kg(-1), respectively. Based on the Potential Ecological Risk Index, Cd posed very high risk to the local ecosystem due to its higher Risk Factor, > 320 and based on Transfer Factor of Pb and Cd were found higher accumulator among the tested metals. The results of present study revealed that the bioconcentration of heavy metals along the Dhaka Aricha Road posed high risk to the ecosystem. Considering the Transfer Factor of Cd and Pb it can be suggested that plants and leafy vegetables grow in the soil near Dhaka Aricha Road should not be used as food or feed.

Monitoring of selected pesticides residue levels in water samples of paddy fields and removal of cypermethrin and chlorpyrifos residues from water using rice bran.

Consumption of pesticides associated foods increased in recent decades in Bangladesh. Most of the pesticides come from paddy, as rice is the main food items here and about 70 % pesticides are used only on paddy fields. Water samples of paddy fields and Kaliganga River of Manikganj district were analyzed to provide base line data on cypermethrin, chlorpyrifos and diazinon residue by using high performance liquid chromatography. Levels of Cypermethrin, chlorpyrifos and diazinon detected in the paddy field water samples were (0.605 ± 0.011 µg/L), (0.06 ± 0.001 µg/L) and (0.039 ± 0.002 µg/L), respectively. 0.11 ± 0.003 µg/L of cypermethrin and 0.012 ± 0.0006 µg/L of chlorpyrifos were also identified in the water samples of Kaligonga River. Diazinon residue was not detected in the river water samples. The detected concentrations of pesticide residues in the river water were below the accepted maximum residue limit (MRL) value of drinking water (0.1 µg/l) adopted by the FAO/WHO Codex Alimentarius Commission. Cypermethrin and chlorpyrifos were chosen for decontamination through rice bran, as it was found in river water. Two gm rice bran could easily decontaminated 95.6 % and 96.4 % of cypermethrin and chlorpyrifos. The result of this study showed that pesticide residue was detected in water samples were below the MRLs value, which can easily be decontaminated through absorption of rice bran.