OCDaf: Ordered Causal Discovery with Autoregressive Flows

We propose OCDaf, a novel order-based method for learning causal graphs from observational data. We establish the identifiability of causal graphs within multivariate heteroscedastic noise models, a generalization of additive noise models that allow for non-constant noise variances. Drawing upon the structural similarities between these models and affine autoregressive normalizing flows, we introduce a continuous search algorithm to find causal structures. Our experiments demonstrate state-of-the-art performance across the Sachs and SynTReN benchmarks in Structural Hamming Distance (SHD) and Structural Intervention Distance (SID). Furthermore, we validate our identifiability theory across various parametric and nonparametric synthetic datasets and showcase superior performance compared to existing baselines

Evaluation of yield and some physiological traits of forage corn affected by chemical and biological nitrogen fertilizers intercropped with sweet basil

In order to evaluate yield and some physiological traits of forage corn under nitrogen fertilizers (biological, chemical and integrated) in additive intercropping with basil a field experiment was carried out in the Experimental Farm of Faculty of Agriculture, Lorestan University during 2014-2015 growing seasons. Treatments were arranged in a factorial experiment based on randomized complete blocks design with three replications. Experimental treatments were 100% chemical fertilizer (N), bio-fertilizer (nitroxin), integration of bio-fertilizer + 50% chemical fertilizer and control in different intercropping systems consisted of sole cropping corn and the additive intercropping of corn + 25% sweet basil, corn + 50% sweet basil, corn + 75% sweet basil and corn + 100% sweet basil. The results showed that integration of bio-fertilizer + 50% chemical fertilizer had the highest number of green leaves per plant (11.72) and leaf area index (LAI) (3.75) and there was no significant difference between this treatment and using 100% chemical fertilizer (N) in plant height, stem dry weight, chlorophyll a, chlorophyll b and carotenoids contents. Among different intercropping systems the highest plant height (179.25 cm), number of green leaves per plant (11.4), leaf dry weight (5.64 ton*ha-1), ear dry weight (7.19 ton*ha-1), stem dry weight (6.11 ton*ha-1), total dry weight (19.22 ton*ha-1), chlorophyll a (0.62 mg*g-1 FW), chlorophyll b (0.42 mg*g-1 FW), and total chlorophyll (1.04 mg*g-1 FW) were obtained from sole cropping pattern. However, sole cropping pattern in terms of mentioned traits except for number of green leaves per plant, ear dry weight and total dry weight had no significant difference with corn + 25% sweet basil and corn + 50% sweet basil treatments The results showed that integration of bio-fertilizer + 50% chemical fertilizer could be considered as an approach to reduce the consumption of chemical fertilizers for sustainable agricultur

Evaluation of Yield and Advantages of Corn (Zea mays L.) and Sweet Basil (Ocimum basilicum L.) Intercropping

In order to study the effects of additive intercropping on grain yield of corn and sweet basil, an experiment was carried out with 9 treatments and 3 replications at the experimental Farm of Faculty of Agriculture of University of Tabriz in 2015. Treatments were sole cropping of corn and two basil cultivars (Mobarake and Italian Large Leaf) and six additive intercropping of %50, %75 and %100 of two basil cultivars + 100%corn. The results of analysis of variance showed that leaf area index, height and number of leaf was significant and corn grain yield was not affected by cropping pattern, however, the effect of cropping pattern was significant on basil cultivars grain yield. Corn plants had highest LAI in intercropping treatments but the maximum height and number of leaf were obtained from sole cropping treatment. The highest grain yield of basil (749.52 kg. ha-1) was obtained from Mobarake cultivar. Also, land equivalent ratio was higher than one in all intercropping patterns shows the advantages of intercropping of these two crops. The results showed that intercropping had higher gross income compare with corn sole cropping and adding %75 of Italian  Large Leaf cultivar to corn was the best pattern

Promoters and Deterrents of Developing Mechanization of Peanut Cultivation in North of Iran

The increasing cost of peanut production is a major concern in Iran. Therefore, developing the mechanization of peanut production is a necessity. In this regard, a three-phase Delphi study was conducted to identify the promoting and deterring factors affecting peanut cultivation mechanization in Guilan Province, the main peanut-producing region in Iran. After preliminary studies, 26 experts were selected as respondents for the study. Based on the final results, ‘allocating provincial and national funds to develop mechanization’ (with the agreement of 98.07% of respondents), ‘Organizing training programs to increase farmers’ technical knowledge’ (97.12%), and ‘conducting the pilot and model projects’(95.19%) were found to be the most important promoting factors in developing peanut cultivation mechanization in north of Iran. Moreover, ‘the small size and fragmentation of peanut farms’ (with 96.15% of respondents agreeing), ‘problems with the national and provincial programs of peanut mechanization’ (95.19%), and ‘low technical knowledge of farmers and craftsmen about peanut farming mechanization’ (94.23%) were identified as the most important deterring factors in developing peanut cultivation mechanization in north of Iran. Given the small area dedicated to peanut cultivation and the low income levels of peanut farmers in north of Iran, it seems that provincial and national funding allocation and peer-planned programming to import appropriate farm machinery are the most urgent plans to improve the status of mechanization of peanut cultivation in north of Iran

Acrylonitrile copolymer/graphene skinned cathode for long cycle life rechargeable hybrid aqueous batteries at high-temperature

The final publication is available at Elsevier via https://dx.doi.org/10.1016/j.electacta.2018.02.098 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/For aqueous rechargeable lithium battery (ARLB), excellent cycling stability at elevated temperature is highly desirable in its application of electric vehicles (EVs). However, most state-of-art ARLBs show poor durability under high-temperature operation. Herein, we demonstrate a facile coating approach that can construct a thin acrylonitrile copolymer (ANC)/graphene skin on the top-surface of the LiMn2O4 (LMO) cathode in a rechargeable hybrid aqueous lithium battery (ReHAB). Featuring the continuous coverage and the facile electron transport, the ANC/graphene skinned cathode shows a capacity retention of 61% after 300 cycles at 60 °C, two times larger than the battery without the skin. In the cathode, ANC helps to suppress unwanted interfacial side reactions, and graphene renders a robust ion diffusion framework. Quantitative analysis of Mn suggests that the ANC/graphene skin can greatly suppress dissolution of Mn from the LMO into the aqueous electrolyte, while maintaining the charge transfer kinetics. The polymer-based nanocomposite skin on small (1.15 mAh cell) and large (7 mAh cell) cathodes show similar electrochemical improvement, indicting good scale-up potentials