Salinity is one of the most devastating abiotic stresses limiting crop production. Considering this issue, a pot experiment was conducted at Sher-e-Bangla Agricultural University, Dhaka, Bangladesh during the boro season (2017-2018) using two rice(Oryza sativa L.) varieties, namely BRRI dhan28 (salt sensitive) and BRRI dhan47 (salt tolerant),to assess the effects of varied salinity levels on the growth and the performance of the rice varieties under salt stress conditions. Four salinity treatments were used in this experiment, viz. control S0 (only freshwater), quarter-strength marine water S1 (three-parts freshwater and one-part marine water; 7.5 ds m−1), half-strength marine water S2 (half freshwater and half marine water; 15 ds m−1), and full-strength marine water S3 (only marine water; 30 ds m−1).These mixtures were used for irrigation purposes throughout the life cycle of the plants. Salt stress significantly decreased the plant height, relative water content (RWC) of leaves, number of effective tillers hill−1, number of filled grains panicle−1, 1000-grain weight, grain yield, straw yield, and biological yield of the rice. In both rice types, plant growth and yield were reduced as the salinity level increased. Grain yields decreased by 50, 90, and 100% in BRRI dhan28 when irrigated with quarter strength, half strength, and full-strength seawater, respectively, but decreased by 27, 50, and 72%, respectively, in BRRI dhan47. Similarly, other yield attributes had higher reductions in BRRI dhan28 under salt stress conditions than BRRI dhan47. However, irrigation with marine water in rice might lead to some straw yield but produced little to no grain.

Spiking neural network offers the most bio-realistic approach to mimic the parallelism and compactness of the human brain. A spiking neuron is the central component of an SNN which generates information-encoded spikes. We present a comprehensive design space analysis of the superconducting memristor (SM)-based electrically reconfigurable cryogenic neuron. A superconducting nanowire (SNW) connected in parallel with an SM function as a dual-frequency oscillator and two of these oscillators can be coupled to design a dynamically tunable spiking neuron. The same neuron topology was previously proposed where a fixed resistance was used in parallel with the SNW. Replacing the fixed resistance with the SM provides an additional tuning knob with four distinct combinations of SM resistances, which improves the reconfigurability by up to ~70%. Utilizing an external bias current (Ibias), the spike frequency can be modulated up to ~3.5 times. Two distinct spike amplitudes (~1V and ~1.8 V) are also achieved. Here, we perform a systematic sensitivity analysis and show that the reconfigurability can be further tuned by choosing a higher input current strength. By performing a 500-point Monte Carlo variation analysis, we find that the spike amplitude is more variation robust than spike frequency and the variation robustness can be further improved by choosing a higher Ibias. Our study provides valuable insights for further exploration of materials and circuit level modification of the neuron that will be useful for system-level incorporation of the neuron circuit.

Vegetable acts as major valuable source of nutrients. Among different vegetables, okra was analyzed to study moisture content, ash content, soluble dietary fiber (SDF), total carbohydrates, and micro-minerals, fatty acid compositions and pesticide residues. Fatty acid compositions were studied by gas chromatograph equipped with a flame ionization detector (GC-FID) while, gas chromatograph equipped with electron capture detector GC-ECD was used for analysis of pesticide residues. Total carbohydrate content was determined by ultraviolet-visible spectrophotometer. The amount of soluble dietary fiber was estimated by acid extraction method. Fe, Cu and Zn content were analyzed by atomic absorption spectroscopy (AAS). The relative percentage of fatty acids were found to be palmitic, cis-9-oleic, linoleic, linolenic and arachidic acid in a range of 0.27-1.35, 3.78 - 6.32, 30.67- 38.44, 2.13 - 4.85 and 1.29 -3.17 %, respectively. Residual diazinon, chlorpyrifos, fenvalerate, cypermethrin and quinalphos were not found to be present in any sample. Total carbohydrate, SDF, moisture and ash content in fresh okra fruits were found to be 6.01- 6.09, 3.35 - 3.50, 88.02 - 91.84 and 1.72 - 2.04 %, respectively. The amount of Fe, Cu and Zn was 11.41-11.43, 1.78 -1.85 and 8.56 - 9.05 mg per 100 g sample, respectively. Dhaka Univ. J. Sci. 68(2): 155-160, 2020 (July)

Realizing compact and scalable Ising machines that are compatible with CMOS-process technology is crucial to the effectiveness and practicality of using such hardware platforms for accelerating computationally intractable problems. Besides the need for realizing compact Ising spins, the implementation of the coupling network, which describes the spin interaction, is also a potential bottleneck in the scalability of such platforms. Therefore, in this work, we propose an Ising machine platform that exploits the novel behavior of compact bi-stable CMOS-latches (cross-coupled inverters) as classical Ising spins interacting through highly scalable and CMOS-process compatible ferroelectric-HfO2-based Ferroelectric FETs (FeFETs) which act as coupling elements. We experimentally demonstrate the prototype building blocks of this system, and evaluate the scaling behavior of the system using simulations. Our work not only provides a pathway to realizing CMOS-compatible designs but also to overcoming their scaling challenges.

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