Rights in a Cloud of Dust: The Value and Qualities of Farm Data and How Its Property Rights Should Be Viewed Moving Forward

Historically, technology growth has been slower in agriculture than other industries. However, a rising demand for food and an increase in efficient farm practices has changed this, leading to a rise in precision farming technologies. Now, entities that provide services or information to farmers need precision farming technologies to compete, and more farmers are adopting precision farming technologies. These technologies help farmers, but questions still remain about ownership rights in the data that farmers create

Review of centrifugal liquid-liquid chromatography using aqueous two-phase solvent (ATPS) systems: Its scale-up and prospects for the future production of high-value biologics

The future challenges in bioprocessing include developing new downstream processes for the purification and manufacture of the protein based medicines of the future to relieve the predicted bottleneck being produced by increasingly high titres from fermentation processes. This review looks at the recent developments in centrifugal liquid-liquid partition chromatography using aqueous two-phase solvent (ATPS) systems, a gentle host medium for biologics, and the prospect for scale-up and eventual manufacture of high value pharmaceutical products

Rapid one-step separation and purification of recombinant phenylalanine dehydrogenase in aqueous two-phase systems

Background: Phenylalanine dehydrogenase (PheDH; EC 1.4.1.20) is a NAD +-dependent enzyme that performs the reversible oxidative deamination of L-phenylalanine to phenylpyruvate. It plays an important role in detection and screening of phenylketonuria (PKU) diseases and production of chiral intermediates as well. The main goal of this study was to find a simple and rapid alternative method for purifying PheDH. Methods: The purification of recombinant Bacillus sphaericus PheDH was investigated in polyethylene glycol (PEG) and ammonium sulfate aqueous two-phase systems (ATPS). The influences of system parameters including PEG molecular weight and concentration, pH and (NH4)2SO4 concentration on enzyme partitioning were also studied. The purity of enzyme was analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis. Results: A single extraction process was developed for separation and purification of recombinant PheDH from E. coli BL21 (DE3). The optimized conditions for partitioning and purification of PheDH were 9% (w/w) PEG-6,000 and 16% (w/w) (NH4)2SO4 at pH 8.0. The partition coefficient, recovery, yield, purification factor and specific activity values were achieved 58.7, 135%, 94.42%, 491.93 and 9828.88 U/mg, respectively. Also, the Km values for L-phenylalanine and NAD+ in oxidative deamination were 0.21 and 0.13 mM, respectively. Conclusion: The data presented in this paper demonstrated the potential of ATPS as a versatile and scaleable process for downstream processing of recombinant PheDH

Premise Selection and External Provers for HOL4

Learning-assisted automated reasoning has recently gained popularity among the users of Isabelle/HOL, HOL Light, and Mizar. In this paper, we present an add-on to the HOL4 proof assistant and an adaptation of the HOLyHammer system that provides machine learning-based premise selection and automated reasoning also for HOL4. We efficiently record the HOL4 dependencies and extract features from the theorem statements, which form a basis for premise selection. HOLyHammer transforms the HOL4 statements in the various TPTP-ATP proof formats, which are then processed by the ATPs. We discuss the different evaluation settings: ATPs, accessible lemmas, and premise numbers. We measure the performance of HOLyHammer on the HOL4 standard library. The results are combined accordingly and compared with the HOL Light experiments, showing a comparably high quality of predictions. The system directly benefits HOL4 users by automatically finding proofs dependencies that can be reconstructed by Metis

Internal Guidance for Satallax

We propose a new internal guidance method for automated theorem provers based on the given-clause algorithm. Our method influences the choice of unprocessed clauses using positive and negative examples from previous proofs. To this end, we present an efficient scheme for Naive Bayesian classification by generalising label occurrences to types with monoid structure. This makes it possible to extend existing fast classifiers, which consider only positive examples, with negative ones. We implement the method in the higher-order logic prover Satallax, where we modify the delay with which propositions are processed. We evaluated our method on a simply-typed higher-order logic version of the Flyspeck project, where it solves 26% more problems than Satallax without internal guidance

Improving the Competency of First-Order Ontologies

We introduce a new framework to evaluate and improve first-order (FO) ontologies using automated theorem provers (ATPs) on the basis of competency questions (CQs). Our framework includes both the adaptation of a methodology for evaluating ontologies to the framework of first-order logic and a new set of non-trivial CQs designed to evaluate FO versions of SUMO, which significantly extends the very small set of CQs proposed in the literature. Most of these new CQs have been automatically generated from a small set of patterns and the mapping of WordNet to SUMO. Applying our framework, we demonstrate that Adimen-SUMO v2.2 outperforms TPTP-SUMO. In addition, using the feedback provided by ATPs we have set an improved version of Adimen-SUMO (v2.4). This new version outperforms the previous ones in terms of competency. For instance, "Humans can reason" is automatically inferred from Adimen-SUMO v2.4, while it is neither deducible from TPTP-SUMO nor Adimen-SUMO v2.2.Comment: 8 pages, 2 table

Supply of sulphur to S-deficient young barley seedlings restores their capability to cope with iron shortage

The effect of the S nutritional status on a plant's capability to cope with Fe shortage was studied in solution cultivation experiments in barley (Hordeum vulgare L. cv. Europa). Barley is a Strategy II plant and responds to Fe deficiency by secretion of chelating compounds, phytosiderophores (PS). All PS are derived from nicotianamine whose precursor is methionine. This suggests that a long-term supply of an inadequate amount of S could reduce a plant's capability to respond to Fe deficiency by limiting the rate of PS biosynthesis. The responses of barley (Hordeum vulgare L. cv. Europa) plants grown for 12 d on Fe-free nutrient solutions (NS) containing 0 or 1.2 mM SO42-, was examined after 24 h or 48 h from transfer to NS containing 1.2 mM SO42-. After the supply of S was restored to S-deprived plants, an increase in PS release in root exudates was evident after 24 h of growth in S-sufficient NS and the increment reached values up to 4-fold higher than the control 48 h after S resupply. When S was supplied to S-deficient plants, leaf ATPS (EC 2.7.7.4) and OASTL (EC 4.2.99.8) activities exhibited a progressive recovery. Furthermore, root HvST1 transcript abundance remained high for 48 h following S resupply and a significant increase in the level of root HvYS1 transcripts was also found after only 24 h of S resupply. Data support the idea that the extent to which the plant is able to cope with Fe starvation is strongly associated with its S nutritional status. In particular, our results are indicative that barley plants fully recover their capability to cope with Fe shortage after the supply of S is restored to S-deficient plants

Evaluating the Competency of a First-Order Ontology

We report on the results of evaluating the competency of a first-order ontology for its use with automated theorem provers (ATPs). The evaluation follows the adaptation of the methodology based on competency questions (CQs) [Gr\"uninger&Fox,1995] to the framework of first-order logic, which is presented in [\'Alvez&Lucio&Rigau,2015], and is applied to Adimen-SUMO [\'Alvez&Lucio&Rigau,2015]. The set of CQs used for this evaluation has been automatically generated from a small set of semantic patterns and the mapping of WordNet to SUMO. Analysing the results, we can conclude that it is feasible to use ATPs for working with Adimen-SUMO v2.4, enabling the resolution of goals by means of performing non-trivial inferences.Comment: 4 pages, 4 figure

HOL(y)Hammer: Online ATP Service for HOL Light

HOL(y)Hammer is an online AI/ATP service for formal (computer-understandable) mathematics encoded in the HOL Light system. The service allows its users to upload and automatically process an arbitrary formal development (project) based on HOL Light, and to attack arbitrary conjectures that use the concepts defined in some of the uploaded projects. For that, the service uses several automated reasoning systems combined with several premise selection methods trained on all the project proofs. The projects that are readily available on the server for such query answering include the recent versions of the Flyspeck, Multivariate Analysis and Complex Analysis libraries. The service runs on a 48-CPU server, currently employing in parallel for each task 7 AI/ATP combinations and 4 decision procedures that contribute to its overall performance. The system is also available for local installation by interested users, who can customize it for their own proof development. An Emacs interface allowing parallel asynchronous queries to the service is also provided. The overall structure of the service is outlined, problems that arise and their solutions are discussed, and an initial account of using the system is given