Role of NGOs in irrigation development and management in Nepal: Proceedings of the National Workshop on the Role of NGOs in Irrigation Development and Management in Nepal, Nepal Administrative Staff College, Jawalakhel, Lalitpur, Nepal, 29-30 September 1992

Agricultural manpower / Non-governmental organizations / Rural development / Irrigation management / Nepal

Crop diversification in irrigated agriculture in the Philippines: Proceedings of a national workshop, Puerto Azul Beach and Country Club Ternate Centre, The Philippines, 5 - 7 October 1988

Cropping systems / Diversification / Irrigated farming / Irrigation systems / Social aspects / Economic aspects / Investment / Farming systems / Irrigation management / Philippines

Immunosensors: Concepts and Structures for Fast and Accurate Sensing

Peer ReviewedPostprint (published version

Data-driven prediction of laminar burning velocity for ternary ammonia/hydrogen/methane/air premixed flames

Zero-carbon fuels such as hydrogen and ammonia play a pivotal role in the energy transition by offering cleaner alternatives to natural gas (methane), especially in industrial combustion systems. Binary and ternary blends of these fuels offer a transitionary, low-carbon solution in the near future. Laminar burning velocity (LBV), as a fundamental combustion property, is significantly different for ammonia, hydrogen, and methane. Although the LBV of binary blends of these fuels is well-studied, ternary blends have not been...

The preburning condition of Chalcolithic cremated human remains from the Perdigoes enclosures (Portugal)

The Iberian Chalcolithic displayed a remarkable variety of funerary practices, which has been related to interpopulation differences, intrapopulation social-cultural differences, and complex multistage funerary rituals. Perdigoes, a Chalcolithic set of ditched enclosures, reflects such diversity including a wide array of funerary practices. Among those practices is cremation, which, despite relatively rare, is represented in different structures in Perdigoes. One of these structures (Pit 40) presents an unparalleled high minimum number of individuals (n = 240), contrasting with nearby and coeval structures. In this study, we analyse heat-induced bone changes and other archaeothanatological variables to tentatively assess the preburning condition of the human remains. The results of Pit 40 are also compared with other comparable contexts to assess if this unique context presents further funerary differences relative to those other contexts in, for example, body processing. Our results suggest preferential cremation of fleshed human remains, but burning of at least a minority of skeletonised remains and deposition of possibly unburned remains also likely occurred. Body processing appears to be comparable with that of the cremation contexts of Perdigoes but contrasts with that of another nearby context (Dolmen of Olival da Pega 2b) in which burned bones were also found.Portuguese Foundation for Science and TechnologyPortuguese Foundation for Science and Technology [PEst-OE/SADG/UI0283/2013, POCI-01-0145-FEDER-016766, PTDC/EPH-ARQ/0798/2014, PTDC/IVC-ANT/1201/2014, SFRH/BPD/84268/2012]info:eu-repo/semantics/publishedVersio

Handling incomplete heterogeneous data using VAEs.

Variational autoencoders (VAEs), as well as other generative models, have been shown to be efficient and accurate for capturing the latent structure of vast amounts of complex high-dimensional data. However, existing VAEs can still not directly handle data that are heterogenous (mixed continuous and discrete) or incomplete (with missing data at random), which is indeed common in real-world applications. In this paper, we propose a general framework to design VAEs suitable for fitting incomplete heterogenous data. The proposed HI-VAE includes likelihood models for real-valued, positive real valued, interval, categorical, ordinal and count data, and allows accurate estimation (and potentially imputation) of missing data. Furthermore, HI-VAE presents competitive predictive performance in supervised tasks, outperforming supervised models when trained on incomplete data