ASAP: An Automatic Algorithm Selection Approach for Planning

Despite the advances made in the last decade in automated planning, no planner out- performs all the others in every known benchmark domain. This observation motivates the idea of selecting different planning algorithms for different domains. Moreover, the planners’ performances are affected by the structure of the search space, which depends on the encoding of the considered domain. In many domains, the performance of a plan- ner can be improved by exploiting additional knowledge, for instance, in the form of macro-operators or entanglements. In this paper we propose ASAP, an automatic Algorithm Selection Approach for Planning that: (i) for a given domain initially learns additional knowledge, in the form of macro-operators and entanglements, which is used for creating different encodings of the given planning domain and problems, and (ii) explores the 2 dimensional space of available algorithms, defined as encodings–planners couples, and then (iii) selects the most promising algorithm for optimising either the runtimes or the quality of the solution plans

Visual acuity testing. From the laboratory to the clinic

AbstractThe need for precision in visual acuity assessment for low vision research led to the design of the Bailey–Lovie letter chart. This paper describes the decisions behind the design principles used and how the logarithmic progression of sizes led to the development of the logMAR designation of visual acuity and the improved sensitivity gained from letter-by-letter scoring. While the principles have since been adopted by most major clinical research studies and for use in most low vision clinics, use of charts of this design and application of letter-by-letter scoring are also important for the accurate assessment of visual acuity in any clinical setting. We discuss the test protocols that should be applied to visual acuity testing and the use of other tests for assessing profound low vision when the limits of visual acuity measurement by letter charts are reached

Water reuse for irrigated agriculture in Jordan: challenges of soil sustainability and the role of management strategies

Reclaimed water provides an important contribution to the water balance in water-scarce Jordan, but the quality of this water presents both benefits and challenges. Careful management of reclaimed water is required to maximize the nutrient benefits while minimizing the salinity risks. This work uses a multi-disciplinary research approach to show that soil response to irrigation with reclaimed water is a function of the management strategies adopted on the farm by the water user. The adoption of management methods to maintain soil productivity can be seen to be a result of farmers’ awareness to potentially plant-toxic ions in the irrigation water (70% of Jordan Valley farmers identified salinization as a hazard from irrigation with reclaimed water). However, the work also suggests that farmers’ management capacity is affected by the institutional management of water. About a third (35%) of farmers in the Jordan Valley claimed that their ability to manage salinization was limited by water shortages. Organizational interviews revealed that institutional awareness of soil management challenges was quite high (34% of interviewees described salinization as a risk from water reuse), but strategies to address this challenge at the institutional level require greater development

Metabolomic Effects of CeO₂, SiO₂ and CuO Metal Oxide Nanomaterials on HepG2 Cells

Background: To better assess potential hepatotoxicity of nanomaterials, human liver HepG2 cells were exposed for 3 days to five different CeO2 (either 30 or 100 μg/ml), 3 SiO2 based (30 μg/ml) or 1 CuO (3 μg/ml) nanomaterials with dry primary particle sizes ranging from 15 to 213 nm. Metabolomic assessment of exposed cells was then performed using four mass spectroscopy dependent platforms (LC and GC), finding 344 biochemicals. Results: Four CeO2, 1 SiO2 and 1 CuO nanomaterials increased hepatocyte concentrations of many lipids, particularly free fatty acids and monoacylglycerols but only CuO elevated lysolipids and sphingolipids. In respect to structure-activity, we now know that five out of six tested CeO2, and both SiO2 and CuO, but zero out of four TiO2 nanomaterials have caused this elevated lipids effect in HepG2 cells. Observed decreases in UDP-glucuronate (by CeO2) and S-adenosylmethionine (by CeO2 and CuO) and increased S-adenosylhomocysteine (by CuO and some CeO2) suggest that a nanomaterial exposure increases transmethylation reactions and depletes hepatic methylation and glucuronidation capacity. Our metabolomics data suggests increased free radical attack on nucleotides. There was a clear pattern of nanomaterial-induced decreased nucleotide concentrations coupled with increased concentrations of nucleic acid degradation products. Purine and pyrimidine alterations included concentration increases for hypoxanthine, xanthine, allantoin, urate, inosine, adenosine 3\u27,5\u27-diphosphate, cytidine and thymidine while decreases were seen for uridine 5\u27-diphosphate, UDP-glucuronate, uridine 5\u27-monophosphate, adenosine 5\u27-diphosphate, adenosine 5\u27-monophophate, cytidine 5\u27-monophosphate and cytidine 3\u27-monophosphate. Observed depletions of both 6-phosphogluconate, NADPH and NADH (all by CeO2) suggest that the HepG2 cells may be deficient in reducing equivalents and thus in a state of oxidative stress. Conclusions: Metal oxide nanomaterial exposure may compromise the methylation, glucuronidation and reduced glutathione conjugation systems; thus Phase II conjugational capacity of hepatocytes may be decreased. This metabolomics study of the effects of nine different nanomaterials has not only confirmed some observations of the prior 2014 study (lipid elevations caused by one CeO2 nanomaterial) but also found some entirely new effects (both SiO2 and CuO nanomaterials also increased the concentrations of several lipid classes, nanomaterial induced decreases in S-adenosylmethionine, UDP-glucuronate, dipeptides, 6-phosphogluconate, NADPH and NADH)

Orchestrating Tuple-based Languages

The World Wide Web can be thought of as a global computing architecture supporting the deployment of distributed networked applications. Currently, such applications can be programmed by resorting mainly to two distinct paradigms: one devised for orchestrating distributed services, and the other designed for coordinating distributed (possibly mobile) agents. In this paper, the issue of designing a pro- gramming language aiming at reconciling orchestration and coordination is investigated. Taking as starting point the orchestration calculus Orc and the tuple-based coordination language Klaim, a new formalism is introduced combining concepts and primitives of the original calculi. To demonstrate feasibility and effectiveness of the proposed approach, a prototype implementation of the new formalism is described and it is then used to tackle a case study dealing with a simplified but realistic electronic marketplace, where a number of on-line stores allow client applications to access information about their goods and to place orders

Geographies of the COVID-19 pandemic

The spread of the novel coronavirus (SARS-CoV-2) has resulted in the most devastating global public health crisis in over a century. At present, over 10 million people from around the world have contracted the Coronavirus Disease 2019 (COVID-19), leading to more than 500,000 deaths globally. The global health crisis unleashed by the COVID-19 pandemic has been compounded by political, economic, and social crises that have exacerbated existing inequalities and disproportionately affected the most vulnerable segments of society. The global pandemic has had profoundly geographical consequences, and as the current crisis continues to unfold, there is a pressing need for geographers and other scholars to critically examine its fallout. This introductory article provides an overview of the current special issue on the geographies of the COVID-19 pandemic, which includes 42 commentaries written by contributors from across the globe. Collectively, the contributions in this special issue highlight the diverse theoretical perspectives, methodological approaches, and thematic foci that geographical scholarship can offer to better understand the uneven geographies of the Coronavirus/COVID-19. </jats:p

Forecasting in the light of Big Data

Predicting the future state of a system has always been a natural motivation for science and practical applications. Such a topic, beyond its obvious technical and societal relevance, is also interesting from a conceptual point of view. This owes to the fact that forecasting lends itself to two equally radical, yet opposite methodologies. A reductionist one, based on the first principles, and the naive inductivist one, based only on data. This latter view has recently gained some attention in response to the availability of unprecedented amounts of data and increasingly sophisticated algorithmic analytic techniques. The purpose of this note is to assess critically the role of big data in reshaping the key aspects of forecasting and in particular the claim that bigger data leads to better predictions. Drawing on the representative example of weather forecasts we argue that this is not generally the case. We conclude by suggesting that a clever and context-dependent compromise between modelling and quantitative analysis stands out as the best forecasting strategy, as anticipated nearly a century ago by Richardson and von Neumann

Immunogenicity of a low-dose diphtheria, tetanus and acellular pertussis combination vaccine with either inactivated or oral polio vaccine compared to standard-dose diphtheria, tetanus, acellular pertussis when used as a pre-school booster in UK children : a 5-year follow-up of a randomised controlled study

This serological follow up study assessed the kinetics of antibody response in children who previously participated in a single centre, open-label, randomised controlled trial of low-dose compared to standard-dose diphtheria booster preschool vaccinations in the United Kingdom (UK). Children had previously been randomised to receive one of three combination vaccines: either a combined adsorbed tetanus, low-dose diphtheria, 5-component acellular pertussis and inactivated polio vaccine (IPV) (Tdap-IPV, Repevax(®); Sanofi Pasteur MSD); a combined adsorbed tetanus, low-dose diphtheria and 5-component acellular pertussis vaccine (Tdap, Covaxis(®); Sanofi Pasteur MSD) given concomitantly with oral polio vaccine (OPV); or a combined adsorbed standard-dose diphtheria, tetanus, 2-component acellular pertussis and IPV (DTap-IPV, Tetravac(®); Sanofi Pasteur MSD). Blood samples for the follow-up study were taken at 1, 3 and 5 years after participation in the original trial (median, 5.07 years of age at year 1), and antibody persistence to each vaccine antigen measured against defined serological thresholds of protection. All participants had evidence of immunity to diphtheria with antitoxin concentrations greater than 0.01IU/mL five years after booster vaccination and 75%, 67% and 79% of children who received Tdap-IPV, Tdap+OPV and DTap-IPV, respectively, had protective antitoxin levels greater than 0.1IU/mL. Long lasting protective immune responses to tetanus and polio antigens were also observed in all groups, though polio responses were lower in the sera of those who received OPV. Low-dose diphtheria vaccines provided comparable protection to the standard-dose vaccine and are suitable for use for pre-school booster vaccination

Data journeys: Capturing the socio-material constitution of data objects and flows

In this paper, we discuss the development and piloting of a new methodology for illuminating the socio-material con- stitution of data objects and flows as data move between different sites of practice. The data journeys approach contributes to the development of critical, qualitative methodologies that can address the geographic and temporal scale of emerging knowledge infrastructures, and capture the ‘life of data’ from their initial generation through to re-use in different contexts. We discuss the theoretical development of the data journeys methodology and the application of the approach on a project examining meteorological data on their journey from initial production through to being re- used in climate science and financial markets. We then discuss three key conceptual findings from this project about: (1) the socio-material constitution of digital data objects, (2) ‘friction’ in the movement of data through space and time and (3) the mutability of digital data as a material property that contributes to driving the movement of data between different sites of practice