797 research outputs found
Allevamento, transumanza, lanificio: tracce dall'alto e dal pieno Medioevo veneto
All the research on the Venetoâs medieval sheep farm are based on few evidences, provided mostly by written documentation (available just for the Veronese territory). Furthermore, the existence of mountain pasture on the Lessini, the possession of tools for the sheep shearing, inventories of possessions (including animals), archeozoological data (thanks to recent excavations) help to build a picture of the Veneto farming situation for the late Middle Ages. More problematic is, however, the reconstruction of the âmanufacturing processâ before the 12th and 13th centuries.
For the late Medieval ages the availability of documentation allowed, and still allows, more exhaustive researches on the Venetian Mainland sheep farm. These studies demonstrate a strong evolution of the wool mill, that became at this time a manufacture of international standards.
Despite that, it is difficult to interrelate information regarding the antique era and High Medieval Ages with those present for the following centuries, even if some elements of continuity are present and may suggest some kind of continuity. These elements of permanence may be found in a wide use of sedentary farming since the antique era to the Early Modern Ages (as demonstrated by some recent research for the Padua territory). Therefore, the sheep farm is characterised not only by transhumance, but even by sedentary raised herds
Seed potato quality improvement through positive selection by smallholder farmers in Kenya
In Kenya, seed potato quality is often a major yield constraint in potato production as smallholder farmers use farm-saved seed without proper management of seed-borne pests and diseases. Farm-saved seed is therefore often highly degenerated. We carried out on-farm research to assess whether farmer-managed positive seed selection could improve yield. Positive selection gave an average yield increase in farmer-managed trials of 34%, corresponding to a 284-€ increase in profit per hectare at an additional production cost of only 6€/ha. Positive selection can be an important alternative and complementary technology to regular seed replacement, especially in the context of imperfect rural economies characterized by high risks of production and insecure markets. It does not require cash investments and is thus accessible for all potato producers. It can also be applied where access to highquality seed is not guaranteed. The technology is also suitable for landraces and not recognized cultivars that cannot be multiplied formally. Finally, the technology fits seamlessly within the seed systems of Sub-Saharan Africa, which are dominated by self-supply and neighbour supply of seed potatoes
Gender norms and the marketing of seeds and ware potatoes in Malawi.
Gender dynamics shape and influence the nature of participation in, as well as the ability to benefit from, seed and ware potato markets in Malawi. 35 sex-disaggregated focus group discussions with farmers and 4 interviews with extension officers were conducted in Dedza and Ntcheu districts. Data on seed marketing and purchase, ware potato marketing, affordability, marketing decisions, and clients, as well as social norms and values that influence market participation by men and women were collected and analyzed using the Real Markets Approach focusing on social relations within markets. Results demonstrate that agricultural market interventions that do not address underlying social structures - such as those related to gender relations and access to key resources - will benefit one group of people over another; in this case men over women
ArfB can displace mRNA to rescue stalled ribosomes
Ribosomes stalled during translation must be rescued to replenish the pool of translation-competent ribosomal subunits. Bacterial alternative rescue factor B (ArfB) releases nascent peptides from ribosomes stalled on mRNAs truncated at the A site, allowing ribosome recycling. Prior structural work revealed that ArfB recognizes such ribosomes by inserting its C-terminal alpha-helix into the vacant mRNA tunnel. In this work, we report that ArfB can efficiently recognize a wider range of mRNA substrates, including longer mRNAs that extend beyond the A-site codon. Single-particle cryo-EM unveils that ArfB employs two modes of function depending on the mRNA length. ArfB acts as a monomer to accommodate a shorter mRNA in the ribosomal A site. By contrast, longer mRNAs are displaced from the mRNA tunnel by more than 20 A and are stabilized in the intersubunit space by dimeric ArfB. Uncovering distinct modes of ArfB function resolves conflicting biochemical and structural studies, and may lead to re-examination of other ribosome rescue pathways, whose functions depend on mRNA lengths
Similarity transformations approach for a generalized Fokker-Planck equation
By using similarity transformations approach, the exact propagator for a
generalized one-dimensional Fokker-Planck equation, with linear drift force and
space-time dependent diffusion coefficient, is obtained. The method is simple
and enables us to recover and generalize special cases studied through the Lie
algebraic approach and the Green function technique.Comment: 8 pages, no figure
Performance Analysis of ML-based MTC Traffic Pattern Predictors
Prolonging the lifetime of massive machine-type communication (MTC) networks
is key to realizing a sustainable digitized society. Great energy savings can
be achieved by accurately predicting MTC traffic followed by properly designed
resource allocation mechanisms. However, selecting the proper MTC traffic
predictor is not straightforward and depends on accuracy/complexity trade-offs
and the specific MTC applications and network characteristics. Remarkably, the
related state-of-the-art literature still lacks such debates. Herein, we assess
the performance of several machine learning (ML) methods to predict Poisson and
quasi-periodic MTC traffic in terms of accuracy and computational cost. Results
show that the temporal convolutional network (TCN) outperforms the long-short
term memory (LSTM), the gated recurrent units (GRU), and the recurrent neural
network (RNN), in that order. For Poisson traffic, the accuracy gap between the
predictors is larger than under quasi-periodic traffic. Finally, we show that
running a TCN predictor is around three times more costly than other methods,
while the training/inference time is the greatest/least.Comment: IEEE Wireless Communications Letters Print ISSN: 2162-2337 Online
ISSN: 2162-234
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