Responses of Hydroponically Grown Sorghum (Sorghum bicolor L.M) to Zinc (Zn) Stress

Abiotic stress especially due heavy metals is one of the major environmental problems that threatens food security and pose greater risks to human health worldwide. In this research, greenhouse hydroponic experiments were carried out to study the morphological and biochemical responses of Sorghum bicolor L.M to different Zinc (Zn) levels. Two-week-old seedlings transplanted in hydroponic solutions were treated with different doses of Zn in the concentration ranges of 5, 25, 50, 100 and 200 mg/L supplied as ZnSO4. 5H2O. After 21 day of culture, the plants were harvested, blotted to dryness and separated into roots and shoots. The root and shoot lengths, dry weights and non-enzymatic biochemical parameters such as proline, Chlorophyll a, b, Carotenoids (pigments) were determined. The results indicate that Zn applications significantly (P<0.05) depressed the lengths of root and shoot, dry weights and pigment contents compared to untreated plants (control). The effects were more pronounced with increased Zn dosage. The accumulation of the metal and proline contents in treated plants however, increase gradually with increasing Zn concentrations (P<0.05). The changes in these parameters had resulted in toxicity symptoms and overall growth retardation especially at elevated concentrations and the estimated critical toxicity thresholds in both solution and tissue concentrations suggest that sorghum bicolor L.M should not be grown beyond Zn concentration of above 3.2 mg/L. &nbsp

Sequential Bayesian Detection of Spike Activities from Fluorescence Observations

Extracting and detecting spike activities from the fluorescence observations is an important step in understanding how neuron systems work. The main challenge lies in that the combination of the ambient noise with dynamic baseline fluctuation, often contaminates the observations, thereby deteriorating the reliability of spike detection. This may be even worse in the face of the nonlinear biological process, the coupling interactions between spikes and baseline, and the unknown critical parameters of an underlying physiological model, in which erroneous estimations of parameters will affect the detection of spikes causing further error propagation. In this paper, we propose a random finite set (RFS) based Bayesian approach. The dynamic behaviors of spike sequence, fluctuated baseline and unknown parameters are formulated as one RFS. This RFS state is capable of distinguishing the hidden active/silent states induced by spike and non-spike activities respectively, thereby \emph{negating the interaction role} played by spikes and other factors. Then, premised on the RFS states, a Bayesian inference scheme is designed to simultaneously estimate the model parameters, baseline, and crucial spike activities. Our results demonstrate that the proposed scheme can gain an extra $12\%$ detection accuracy in comparison with the state-of-the-art MLSpike method

Hamming–Luby rateless codes for molecular erasure channels

Nano-scale molecular communications encode digital information into discrete macro-molecules. In many nano-scale systems, due to limited molecular energy, each information symbol is encoded into a small number of molecules. As such, information may be lost in the process of diffusion–advection propagation through complex topologies and membranes. Existing Hamming-distance codes for additive counting noise are not well suited to combat the aforementioned erasure errors. Rateless Luby-Transform (LT) code and cascaded Hamming-LT (Raptor) are suitable for information-loss, however may consume substantially computational energy due to the repeated uses of random number generator and exclusive OR (XOR). In this paper, we design a novel low-complexity erasure combating encoding scheme: the rateless Hamming–Luby Transform code. The proposed rateless code combines the superior efficiency of Hamming codes with the performance guarantee advantage of Luby Transform (LT) codes, therefore can reduce the number of random number generator utilizations. We design an iterative soft decoding scheme via successive cancelation to further improve the performance. Numerical simulations show this new rateless code can provide comparable performance comparing with both standard LT and Raptor codes, while incurring a lower decoder computational complexity, which is useful for the envisaged resources constrained nano-machine

Targeting of Embryonic Stem Cells by Peptide-Conjugated Quantum Dots

Targeting stem cells holds great potential for studying the embryonic stem cell and development of stem cell-based regenerative medicine. Previous studies demonstrated that nanoparticles can serve as a robust platform for gene delivery, non-invasive cell imaging, and manipulation of stem cell differentiation. However specific targeting of embryonic stem cells by peptide-linked nanoparticles has not been reported.Here, we developed a method for screening peptides that specifically recognize rhesus macaque embryonic stem cells by phage display and used the peptides to facilitate quantum dot targeting of embryonic stem cells. Through a phage display screen, we found phages that displayed an APWHLSSQYSRT peptide showed high affinity and specificity to undifferentiated primate embryonic stem cells in an enzyme-linked immunoabsorbent assay. These results were subsequently confirmed by immunofluorescence microscopy. Additionally, this binding could be completed by the chemically synthesized APWHLSSQYSRT peptide, indicating that the binding capability was specific and conferred by the peptide sequence. Through the ligation of the peptide to CdSe-ZnS core-shell nanocrystals, we were able to, for the first time, target embryonic stem cells through peptide-conjugated quantum dots.These data demonstrate that our established method of screening for embryonic stem cell specific binding peptides by phage display is feasible. Moreover, the peptide-conjugated quantum dots may be applicable for embryonic stem cell study and utilization

Direct in situ synthesis of a 3D interlinked amorphous carbon nanotube/graphene/BaFe12O19 composite and its electromagnetic wave absorbing properties

2016-2017 > Academic research: refereed > Publication in refereed journalbcrcVersion of RecordPublishe

Detecting HI Galaxies with Deep Neural Networks in the Presence of Radio Frequency Interference

In neutral hydrogen (HI) galaxy survey, a significant challenge is to identify and extract the HI galaxy signal from observational data contaminated by radio frequency interference (RFI). For a drift-scan survey, or more generally a survey of a spatially continuous region, in the time-ordered spectral data, the HI galaxies and RFI all appear as regions which extend an area in the time-frequency waterfall plot, so the extraction of the HI galaxies and RFI from such data can be regarded as an image segmentation problem, and machine learning methods can be applied to solve such problems. In this study, we develop a method to effectively detect and extract signals of HI galaxies based on a Mask R-CNN network combined with the PointRend method. By simulating FAST-observed galaxy signals and potential RFI impacts, we created a realistic data set for the training and testing of our neural network. We compared five different architectures and selected the best-performing one. This architecture successfully performs instance segmentation of HI galaxy signals in the RFI-contaminated time-ordered data (TOD), achieving a precision of 98.64% and a recall of 93.59%.Comment: 17 pages, 9 figures, 1 tables. Accepted for publication in RA

Enhanced photovoltage in perovskite-type artificial superlattices on Si substrates

Abstract We have fabricated a three-component perovskite-type superlattice (SL) consisting of La 0.9 Sr 0.1 MnO 3 , SrTiO 3 and LaAlO 3 with atomic scale control by laser molecular beam epitaxy on Si substrates. When a He-Ne laser irradiated the superlattice by side illumination, a stable photovoltage was produced and the responsivity reached 46.7 mV mW −1 which is six times higher than that of a similarly grown La 0.9 Sr 0.1 MnO 3 single layer on Si substrates. This work demonstrates the potential of the present SL in photo-detectors operating at room temperature