COVID-19 global pandemic has badly hit the business of farmers whose story has largely been in the shadows. The main objective of this article is to highlight the connection of global pandemic with agricultural and food systems. For this, secondary data were collected through online portals, daily national newspapers, and published scientific articles and analyzed. The result shows that from pandemic to lockdown, locust to heavy rainfall, unsold crops to rotten crops, financial crisis to acute hunger, has brought agricultural activities to standstill, where people value only those who can produce food for them. It is high time for action and priority must be given to the farmers who are putting their hard work to thrive the whole world as that of police and health workers. The government needs to take vigorous steps to facilitate farmers using automated machinery facilities like autonomous tractors, seeding robots, robotic harvesters, drones and ICTs, toll-free numbers; enhancing quality seeds, fertilizers and direct financial funding on vulnerable farmers to build agricultural sector resilience to the pandemic. 

No abstract

We present in this paper our system developed for SemEval 2015 Shared Task 2 (2a -English Semantic Textual Similarity, STS, and 2c -Interpretable Similarity) and the results of the submitted runs. For the English STS subtask, we used regression models combining a wide array of features including semantic similarity scores obtained from various methods. One of our runs achieved weighted mean correlation score of 0.784 for sentence similarity subtask (i.e., English STS) and was ranked tenth among 74 runs submitted by 29 teams. For the interpretable similarity pilot task, we employed a rule-based approach blended with chunk alignment labeling and scoring based on semantic similarity features. Our system for interpretable text similarity was among the top three best performing systems.

No abstract

We describe our system (DT Team) submitted at SemEval-2017 Task 1, Semantic Textual Similarity (STS) challenge for English (Track 5). We developed three different models with various features including similarity scores calculated using word and chunk alignments, word/sentence embeddings, and Gaussian Mixture Model (GMM). The correlation between our system's output and the human judgments were up to 0.8536, which is more than 10% above baseline, and almost as good as the best performing system which was at 0.8547 correlation (the difference is just about 0.1%). Also, our system produced leading results when evaluated with a separate STS benchmark dataset. The word alignment and sentence embeddings based features were found to be very effective.

No abstract

This study was conducted to assess biomass and carbon stock along slopes in Depard community forest, Manahari-6, Makwanpur district of Nepal. In Nepal, carbon stock estimation has been less practiced in community forest. A random sampling method was applied in this study to collect biophysical data i.e. DBH and height by non-destructive method to estimate the quantity of tree biomass and carbon stock. 21 sample plots with 1% sampling intensity were established within the study area. The circular area of 250 m2 was predetermined with the radius of 8.92 m for this study. Secondary data were collected through published and unpublished literature. Data were pooled and analyzed with SPSS software. The total biomass and carbon stock were calculated to be 1381.30 t/ha and 649.21 t/ha, respectively. The biomass and carbon stock were highest (563.12 t/ha and 242.42 t/ha) in 0-5% slope, and lowest in >20% of slope (334.75 t/ha and 143.60 t/ha). The difference of biomass and carbon in slopes may be due to the accumulation of more organic matter and other minerals in the less sloped areas through rainfall, landslide.

Background Knowledge about the niche overlap among wild species and domestic cattle is helpful to conserve and manage wildlife. We assessed the habitat niche breadth and overlap of sympatrically living spotted deer (Axis axis) and domestic cattle with swamp deer (Cervus duvaucelii) in Shuklaphanta National Park, Nepal during the dry season to explore the possibility of interspecific competition by studying the habitat use by these species. The assumption was made that the presence of pellets is proof of habitat used by species. Methods Grids of 2 km × 2 km have four subgrids, each with four sample plots, making a total of 16 plots (20 m × 20 m) in each grid. The size of each sub-grid was 200 m × 200 m and they were placed randomly inside the grid but at least 1 km apart from one another. The data was collected in a 96 plots in total. Levin’s niche breadth and Morisita’s overlap index were calculated to determine the niche breadth and the habitat overlap, respectively. Results The Levin’s measure of niche breadth suggested that spotted deer had the highest acclimatization with an index value of 0.94, followed by domestic cattle at 0.50, and swamp deer at 0.33 in our study area. Thus, our findings supported the evidence that spotted deer are habitat generalists, whereas swamp deer are habitat specialists. The swamp deer had lower niche breadth and more overlap with domestic cattle. Conclusion Our study showed the least niche breadth of swamp deer in comparison to spotted deer and domestic cattle. The domestic cattle had the highest and least niche overlap with spotted deer and swamp deer, respectively, in terms of habitat use. Our study suggests that domestic cattle grazing should be stopped, and grassland management should be carried out for the benefit of ungulates. Similar studies should be conducted, including different seasons and places, prior to appropriate habitat management. In addition, further studies are needed to quantify the extent of interspecific competition by incorporating more species.