Application of ferrous sulfate alleviates negative impact of cadmium in rice (<i>Oryza sativa</i> L.)

Soil contamination with toxic heavy metals [such as cadmium (Cd)] is becoming a serious global problem due to rapid development of social economy. Iron (Fe), being an important element, has been found effective in enhancing plant tolerance against biotic and abiotic stresses. The present study investigated the extent to which different levels of Ferrous sulphate (FeSO₄) modulated the Cd tolerance of rice (Oryza sativa L.), when maintained in artificially Cd spiked regimes. A pot experiment was conducted under controlled conditions for 146 days, by using natural soil, mixed with different levels of CdCl₂ [0 (no Cd), 0.5 and 1 mg/kg] together with the exogenous application of FeSO₄ at [0 (no Fe), 1.5 and 3 mg/kg] levels to monitor different growth, gaseous exchange characteristics, oxidative stress, antioxidative responses, minerals accumulation, organic acid exudation patterns of O. sativa. Our results depicted that addition of Cd to the soil significantly (P < 0.05) decreased plant growth and biomass, gaseous exchange parameters, mineral uptake by the plants, sugars (soluble, reducing, and non-reducing sugar) and altered the ultrastructure of chloroplasts, plastoglobuli, mitochondria, and many other cellular organelles in Cd-stressed O. sativa compared to those plants which were grown without the addition of Cd in the soil. However, Cd toxicity boosted the production of reactive oxygen species (ROS) by increasing the contents of malondialdehyde (MDA), which is the indication of oxidative stress in O. sativa and was also manifested by hydrogen peroxide (H₂O₂) contents and electrolyte leakage to the membrane bounded organelles. Although, activities of various antioxidative enzymes like superoxidase dismutase (SOD), peroxidase (POD), catalase (CAT) and ascorbate peroxidase (APX) and non-enzymatic antioxidants like phenolics, flavonoid, ascorbic acid, anthocyanin and proline contents increased up to a Cd level of 0.5 mg/kg in the soil but were significantly diminished at the highest Cd level of 1 mg/kg in the soil compared to those plants which were grown without the addition of Cd in the soil. The negative impacts of Cd injury were reduced by the application of FeSO₄ which increased plant growth and biomass, improved photosynthetic apparatus, antioxidant enzymes, minerals uptake together with diminished exudation of organic acids as well as oxidative stress indicators in roots and shoots of O. sativa by decreasing Cd retention in different plant parts. These results shed light on the effectiveness of FeSO₄ in improving the growth and upregulation of antioxidant enzyme activities of O. sativa in response to Cd stress. However, further studies at field levels are required to explore the mechanisms of FeSO₄-mediated reduction of the toxicity of not only Cd, but possibly also other heavy metals in plants.     

Past is important: Improved image captioning by looking back in time

A major development in the area of image captioning consists of trying to incorporate visual attention in the design of language generative model. However, most previous studies only emphasize its role in enhancing visual composition at the current moment, while neglect its role in global sequence reasoning. This problem appears not only in captioning model, but also in reinforcement learning structure. To tackle this issue, we first propose a Visual Reserved model that enables previous visual context to be considered for the current sequence reasoning. Next, a Attentional-Fluctuation Supervised model is also proposed in reinforcement learning structure. Compared against the traditional strategies that only take non-differentiable Natural Language Processing (NLP) metrics as the incentive standard, the proposed model regards the fluctuation of previous attention matrix as an important indicator to judge the convergence of the captioning model. The proposed methods have been tested on MS-COCO captioning dataset and achieve competitive results evaluated by the evaluation server of MS COCO captioning challenge.     

The P-graph approach for systematic synthesis of wastewater treatment networks

Wastewater treatment consists of three or four sequential stages: preliminary, primary, secondary, and tertiary. Each stage can comprise multiple alternative technologies that can perform the same tasks with different efficiencies, operating times, and costs. Thus, we propose a systematic approach for designing wastewater treatment networks by utilizing principles of mathematical modeling and generating an exhaustive enumeration of all the possible technologies and their connections during the early stages of designing a treatment facility. Some of these structures are nonintuitive and include recycling, reprocessing, bypasses, and multiple technologies in parallel or series to remove the same contaminant. The nonintuitive structures with multiple technologies may provide a measure of resilience compared to typical heuristic designs. Thus, the combination of P-graph methodology and the sequence of treatment technologies predicted via the optimization algorithm from the maximal structure is based on holistic considerations and does not lead to suboptimal solutions.     

Molecular fingerprint and machine learning to accelerate design of high-performance homochiral metal–organic frameworks

Computational screening was employed to calculate the enantioseparation capabilities of 45 functionalized homochiral metal–organic frameworks (FHMOFs), and machine learning (ML) and molecular fingerprint (MF) techniques were used to find new FHMOFs with high performance. With increasing temperature, the enantioselectivities for (R,S)-1,3-dimethyl-1,2-propadiene are improved. The “glove effect” in the chiral pockets was proposed to explain the correlations between the steric effect of functional groups and performance of FHMOFs. Moreover, the neighborhood component analysis and RDKit/MACCS MFs show the highest predictive effect on enantioselectivities among the four ML classification algorithms with nine MFs that were tested. Based on the importance of MF, 85 new FHMOFs were designed, and a newly designed FHMOF, NO₂-NHOH-FHMOF, with high similarity to the optimal MFs achieved improved chiral separation performance, with enantioselectivities of 85%. The design principles and new chiral pockets obtained by ML and MFs could facilitate the development of new materials for chiral separation.