A Machine Learning Model Marketplace to Overcome Low Price Elasticity of Sales Forecasting

Machine learning (ML) sales forecasting applications occupy a special position in industry and retail, as used in numerous optimization activities, such as price optimization. While optimizing prices, sales forecasting tools require elasticity regarding the optimization objective. When ML methods are used for sales forecasting, there must be sufficient data to learn the proper elasticity requirements.%Hence, automated ML-based (price) optimization requires prior (price) optimization sample data. To overcome the problem of low price elasticity of sales forecasts, when historical price-change data are scarce, we present a sales forecasting model marketplace in which trained ML models are shared across companies. Evaluations of a design science project with 43 retail stores show that a \textit{model marketplace} with neural networks and dropout profiles achieves good forecasting accuracy and high price elasticity.With these results, companies can implement automated optimization algorithms while avoiding extant cumbersome stovepiped methods

Design Principles for Machine Learning Marketplaces in Enterprise Systems

While standardized enterprise systems (ES) have become widely accepted, this is not the case for machine learning (ML) implementations, which are mostly developed individually in company-specific projects. Necessary historical data and rare ML capabilities result in a low cross-market ML utilization. To overcome the high usage barriers of ML, it should be incorporated into ES in a standardized manner. Therefore, we propose to implement an ML marketplace. While marketplaces in ES already exist, this paper proposes a marketplace dedicated to the exchange of ML models in a federated learning approach. Accordingly, this work formulates four meta-requirements based on interviews, which are structured by marketplace governance dimensions. With these meta-requirements, an ML marketplace was implemented in a design science research project, from which eight design principles are derived. The design principles address governance dimensions for making ML accessible to many companies and allow them to integrate ML into existing ES

Ce que la reconstruction comparative peut apporter à la morphologie constructionnelle. Une cavalcade étymologique

This paper reconsiders the etymology of the lexical units Cat. cavalcar, encavalcar, descavalcar and their cognates, e.g. Span. cabalgar, Port. encavalgar, or It. discavalcare. An etymological cavalcade in the framework of the Dictionnaire Étymologique Roman (DÉRom) yields three Proto-Romance etyma: */ka'βall‑ɪk‑a‑/, */ɪn‑ka'βall‑ɪk‑a‑/, and */dɪs‑ka'βall‑ɪk‑a‑/. These etyma, out of which only the first one presents a correlate in written Latin, owe their existence to the application of comparative reconstruction to the Romance lexicon, the last ones respresenting derivatives from */ka'βall‑ɪk‑a‑/ with the prefixes */ɪn‑/ and */dɪs‑/

Examining the potential for climate change mitigation from zero tillage

The benefits of reduced and zero-tillage systems have been presented as reducing runoff, enhancing water retention and preventing soil erosion. There is also general agreement that the practice can conserve and enhance soil organic carbon (C) levels to some extent. However, their applicability in mitigating climate change has been debated extensively, especially when the whole profile of C in the soil is considered, along with a reported risk of enhanced nitrous oxide (N2O) emissions. The current paper presents a meta-analysis of existing literature to ascertain the climate change mitigation opportunities offered by minimizing tillage operations. Research suggests zero tillage is effective in sequestering C in both soil surface and sub-soil layers in tropical and temperate conditions. The C sequestration rate in tropical soils can be about five times higher than in temperate soils. In tropical soils, C accumulation is generally correlated with the duration of tillage. Reduced N2O emissions under long-term zero tillage have been reported in the literature but significant variability exists in the N2O flux information. Long-term, location-specific studies are needed urgently to determine the precise role of zero tillage in driving N2O fluxes. Considering the wide variety of crops utilized in zero-tillage studies, for example maize, barley, soybean and winter wheat, only soybean has been reported to show an increase in yield with zero tillage (7·7% over 10 years). In several cases yield reductions have been recorded e.g. c. 1–8% over 10 years under winter wheat and barley, respectively, suggesting zero tillage does not bring appreciable changes in yield but that the difference between the two approaches may be small. A key question that remains to be answered is: are any potential reductions in yield acceptable in the quest to mitigate climate change, given the importance of global food security

A Miscanthus plantation can be carbon neutral without increasing soil carbon stocks

Acknowledgements The authors would like to thank the NERC Centre for Ecology & Hydrology and Shell for providing a joint PhD studentship grant award to Andy Robertson (CEH project number NEC04306). We are also grateful to Emily Clark, Simon Oakley and Rebecca Rowe at CEH Lancaster and Sean Case at the University of Copenhagen for help with fieldwork, laboratory work and manuscript comments.Peer reviewedPublisher PD

Ranking factors affecting emissions of GHG from incubated agricultural soils

Agriculture significantly contributes to global greenhouse gas (GHG) emissions and there is a need to develop effective mitigation strategies. The efficacy of methods to reduce GHG fluxes from agricultural soils can be affected by a range of interacting management and environmental factors. Uniquely, we used the Taguchi experimental design methodology to rank the relative importance of six factors known to affect the emission of GHG from soil: nitrate (NO3-) addition, carbon quality (labile and non-labile C), soil temperature, water-filled pore space (WFPS) and extent of soil compaction. Grassland soil was incubated in jars where selected factors, considered at two or three amounts within the experimental range, were combined in an orthogonal array to determine the importance and interactions between factors with a L-16 design, comprising 16 experimental units. Within this L-16 design, 216 combinations of the full factorial experimental design were represented. Headspace nitrous oxide (N2O), methane (CH4) and carbon dioxide (CO2) concentrations were measured and used to calculate fluxes. Results found for the relative influence of factors (WFPS and NO3- addition were the main factors affecting N2O fluxes, whilst glucose, NO3- and soil temperature were the main factors affecting CO2 and CH4 fluxes) were consistent with those already well documented. Interactions between factors were also studied and results showed that factors with little individual influence became more influential in combination. The proposed methodology offers new possibilities for GHG researchers to study interactions between influential factors and address the optimized sets of conditions to reduce GHG emissions in agro-ecosystems, while reducing the number of experimental units required compared with conventional experimental procedures that adjust one variable at a time

Enhancing carbon sequestration in soil with coal combustion products: a technology for minimising carbon footprints in coal-power generation and agriculture

Coal-fired power generation and agriculture account for more than half of global greenhouse gas emissions, but the coal fly ash (CFA) produced in the former can be a resource for reducing emissions from agriculture to minimise environmental footprints in both industries. Our aim in this study was to test how acidic and alkaline CFA addition could minimise loss of C and N from acidic soil, with or without added manure. We determined composition and structural characteristics of acidic and alkaline CFA for their capacity to adsorb organic carbon, but observed poor adsorption because of low concentrations of cenospheres and unburnt carbon as the primary absorbents in the ash. Addition of CFA had no impact on the loss of carbon or nitrogen from unmanured soil in which concentrations of these nutrients were low. Loss of carbon from manured soil was reduced by 36% with alkaline ashes and by 3-fold with acidic ashes; while loss of N was 30–50% lower with acidic ashes, but 28% higher with alkaline ashes, compared with no ash treatment. The increases in C sparing with CFA addition were achieved not by direct C absorption but by restraining microbial population and respiration, and potentially emissions. Alkaline CFA increased soil pH and if used to substitute just 10% of lime for ameliorating soil acidity would reduce CO2 emission associated with the mining of the lime and its eventual dissolution in soil by ~ 2.66 Tg or 2.8% of Australia’s annual agricultural emissions. High concentrations of oxides of phosphorus, silicon, titanium and clay particles in acidic ashes, and oxides of cations in alkaline ashes, were associated with potential for promoting C storage and acidity amelioration in soil

Long-term nutrient enrichment of an oligotroph-dominated wetland increases bacterial diversity in bulk soils and plant rhizospheres.

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.In nutrient-limited conditions, plants rely on rhizosphere microbial members to facilitate nutrient acquisition, and in return, plants provide carbon resources to these root-associated microorganisms. However, atmospheric nutrient deposition can affect plant-microbe relationships by changing soil bacterial composition and by reducing cooperation between microbial taxa and plants. To examine how long-term nutrient addition shapes rhizosphere community composition, we compared traits associated with bacterial (fast-growing copiotrophs, slow-growing oligotrophs) and plant (C3 forb, C4 grass) communities residing in a nutrient-poor wetland ecosystem. Results revealed that oligotrophic taxa dominated soil bacterial communities and that fertilization increased the presence of oligotrophs in bulk and rhizosphere communities. Additionally, bacterial species diversity was greatest in fertilized soils, particularly in bulk soils. Nutrient enrichment (fertilized versus unfertilized) and plant association (bulk versus rhizosphere) determined bacterial community composition; bacterial community structure associated with plant functional group (grass versus forb) was similar within treatments but differed between fertilization treatments. The core forb microbiome consisted of 602 unique taxa, and the core grass microbiome consisted of 372 unique taxa. Forb rhizospheres were enriched in potentially disease-suppressive bacterial taxa, and grass rhizospheres were enriched in bacterial taxa associated with complex carbon decomposition. Results from this study demonstrate that fertilization serves as a strong environmental filter on the soil microbiome, which leads to distinct rhizosphere communities and can shift plant effects on the rhizosphere microbiome. These taxonomic shifts within plant rhizospheres could have implications for plant health and ecosystem functions associated with carbon and nitrogen cycling.ECU Open Access Publishing Support Fun