A distributed, semiotic-inductive and human-Oriented approach to web-scale knowledge retrieval

Web-scale knowledge retrieval can be enabled by distributed information retrieval, clustering Web clients to a large-scale computing infrastructure for knowledge discovery from Web documents. Based on this infrastructure, we propose to apply semiotic (i.e., sub-syntactical) and inductive (i.e., probabilistic) methods for inferring concept associations in human knowledge. These associations can be combined to form a fuzzy (i.e.,gradual) semantic net representing a map of the knowledge in the Web. Thus, we propose to provide interactive visualizations of these cognitive concept maps to end users, who can browse and search the Web in a human-oriented, visual, and associative interface.

Tools for better SLM knowledge management and informed decision-making in addressing land degradation at different scales: the WOCAT–LADA–DESIRE methodology

Desertification research conventionally focuses on the problem – that is, degradation – while neglecting the appraisal of successful conservation practices. Based on the premise that Sustainable Land Management (SLM) experiences are not sufficiently or comprehensively documented, evaluated, and shared, the World Overview of Conservation Approaches and Technologies (WOCAT) initiative (www.wocat.net), in collaboration with FAO’s Land Degradation Assessment in Drylands (LADA) project (www.fao.org/nr/lada/) and the EU’s DESIRE project (http://www.desire-project.eu/), has developed standardised tools and methods for compiling and evaluating the biophysical and socio-economic knowledge available about SLM. The tools allow SLM specialists to share their knowledge and assess the impact of SLM at the local, national, and global levels. As a whole, the WOCAT–LADA–DESIRE methodology comprises tools for documenting, self-evaluating, and assessing the impact of SLM practices, as well as for knowledge sharing and decision support in the field, at the planning level, and in scaling up identified good practices. SLM depends on flexibility and responsiveness to changing complex ecological and socioeconomic causes of land degradation. The WOCAT tools are designed to reflect and capture this capacity of SLM. In order to take account of new challenges and meet emerging needs of WOCAT users, the tools are constantly further developed and adapted. Recent enhancements include tools for improved data analysis (impact and cost/benefit), cross-scale mapping, climate change adaptation and disaster risk management, and easier reporting on SLM best practices to UNCCD and other national and international partners. Moreover, WOCAT has begun to give land users a voice by backing conventional documentation with video clips straight from the field. To promote the scaling up of SLM, WOCAT works with key institutions and partners at the local and national level, for example advisory services and implementation projects. Keywords: Sustainable Land Management (SLM), knowledge management, decision-making, WOCAT–LADA–DESIRE methodology.

Natural Language Checking with Program Checking Tools

Written text is an important component in the process of knowledge acquisition and communication. Poorly written text fails to deliver clear ideas to the reader no matter how revolutionary and ground-breaking these ideas are. Providing text with good writing style is essential to transfer ideas smoothly. While we have sophisticated tools to check for stylistic problems in program code, we do not apply the same techniques for written text. In this paper we present TextLint, a rule-based tool to check for common style errors in natural language. TextLint provides a structural model of written text and an extensible rule-based checking mechanism.

Knowledge Management and Decision Support for Sustainable Land Management

Much research has focused on desertification and land degradation assessments without putting sufficient emphasis on prevention and mitigation, although the concept of sustainable land management (SLM) is increasingly being acknowledged. A variety of SLM measures have already been applied at the local level, but they are rarely adequately recognised, evaluated, shared or used for decision support. WOCAT (World Overview of Technologies and Approaches) has developed an internationally recognised, standardised methodology to document and evaluate SLM technologies and approaches, including spatial distribution, allowing the sharing of SLM knowledge worldwide. The recent methodological integration into a participatory process allows now analysing and using this knowledge for decision support at the local and national level. The use of the WOCAT tools stimulates evaluation (self-evaluation as well as learning from comparing experiences) within SLM initiatives where all too often there is not only insufficient monitoring but also a lack of critical analysis. The comprehensive questionnaires and database system facilitate to document, evaluate and disseminate local experiences of SLM technologies and their implementation approaches. This evaluation process - in a team of experts and together with land users - greatly enhances understanding of the reasons behind successful (or failed) local practices. It has now been integrated into a new methodology for appraising and selecting SLM options. The methodology combines a local collective learning and decision approach with the use of the evaluated global best practices from WOCAT in a concise three step process: i) identifying land degradation and locally applied solutions in a stakeholder learning workshop; ii) assessing local solutions with the standardised WOCAT tool; iii) jointly selecting promising strategies for implementation with the help of a decision support tool. The methodology has been implemented in various countries and study sites around the world mainly within the FAO LADA (Land Degradation Assessment Project) and the EU-funded DESIRE project. Investments in SLM must be carefully assessed and planned on the basis of properly documented experiences and evaluated impacts and benefits: concerted efforts are needed and sufficient resources must be mobilised to tap the wealth of knowledge and learn from SLM successes.

Developing European conservation and mitigation tools for pollination services: approaches of the STEP (Status and Trends of European Pollinators) project

Pollinating insects form a key component of European biodiversity, and provide a vital ecosystem service to crops and wild plants. There is growing evidence of declines in both wild and domesticated pollinators, and parallel declines in plants relying upon them. The STEP project (Status and Trends of European Pollinators, 2010-2015, www.step-project.net) is documenting critical elements in the nature and extent of these declines, examining key functional traits associated with pollination deficits, and developing a Red List for some European pollinator groups. Together these activities are laying the groundwork for future pollinator monitoring programmes. STEP is also assessing the relative importance of potential drivers of pollinator declines, including climate change, habitat loss and fragmentation, agrochemicals, pathogens, alien species, light pollution, and their interactions. We are measuring the ecological and economic impacts of declining pollinator services and floral resources, including effects on wild plant populations, crop production and human nutrition. STEP is reviewing existing and potential mitigation options, and providing novel tests of their effectiveness across Europe. Our work is building upon existing and newly developed datasets and models, complemented by spatially-replicated campaigns of field research to fill gaps in current knowledge. Findings are being integrated into a policy-relevant framework to create evidence-based decision support tools. STEP is establishing communication links to a wide range of stakeholders across Europe and beyond, including policy makers, beekeepers, farmers, academics and the general public. Taken together, the STEP research programme aims to improve our understanding of the nature, causes, consequences and potential mitigation of declines in pollination services at local, national, continental and global scales.

The NutriChip project--translating technology into nutritional knowledge

Advances in food transformation have dramatically increased the diversity of products on the market and, consequently, exposed consumers to a complex spectrum of bioactive nutrients whose potential risks and benefits have mostly not been confidently demonstrated. Therefore, tools are needed to efficiently screen products for selected physiological properties before they enter the market. NutriChip is an interdisciplinary modular project funded by the Swiss programme Nano-Tera, which groups scientists from several areas of research with the aim of developing analytical strategies that will enable functional screening of foods. The project focuses on postprandial inflammatory stress, which potentially contributes to the development of chronic inflammatory diseases. The first module of the NutriChip project is composed of three in vitro biochemical steps that mimic the digestion process, intestinal absorption, and subsequent modulation of immune cells by the bioavailable nutrients. The second module is a miniaturised form of the first module (gut-on-a-chip) that integrates a microfluidic-based cell co-culture system and super-resolution imaging technologies to provide a physiologically relevant fluid flow environment and allows sensitive real-time analysis of the products screened in vitro. The third module aims at validating the in vitro screening model by assessing the nutritional properties of selected food products in humans. Because of the immunomodulatory properties of milk as well as its amenability to technological transformation, dairy products have been selected as model foods. The NutriChip project reflects the opening of food and nutrition sciences to state-of-the-art technologies, a key step in the translation of transdisciplinary knowledge into nutritional advice.

Depicting community perspectives: repeat photography and participatory research as tools for assessing environmental services in Sagarmatha National Park, Nepal

Efforts have been made to provide a scientific basis for using environmental services as a conceptual tool to enhance conservation and improve livelihoods in protected mountain areas (MtPAS). Little attention has been paid to participatory research or locals’ concerns as environmental service (ES) users and providers. Such perspectives can illuminate the complex interplay between mountain ecosystems, environmental services and the determinants of human well-being. Repeat photography, long used in geographical fieldwork, is new as a qualitative research tool. This study uses a novel application of repeat photography as a diachronic photo-diary to examine local perceptions of change in ES in Sagarmatha National Park. Results show a consensus among locals on adverse changes to ES, particularly protection against natural hazards, such as landslides and floods, in the UNESCO World Heritage Site. We argue that our methodology could complement biophysical ecosystem assessments in MtPAS, especially since assessing ES, and acting on that, requires integrating diverse stakeholders’ knowledge, recognizing power imbalances and grappling with complex social-ecological systems.

New molecular detection tools adapted to emerging rhinoviruses and enteroviruses

Human rhinoviruses (HRV), and to a lesser extent human enteroviruses (HEV), are important respiratory pathogens. Like other RNA viruses, these picornaviruses have an intrinsic propensity to variability. This results in a large number of different serotypes as well as the incessant discovery of new genotypes. This large and growing diversity not only complicates the design of real-time PCR assays but also renders immunofluorescence unfeasible for broad HRV and HEV detection or quantification in cells. In this study, we used the 5' untranslated region, the most conserved part of the genome, as a target for the development of both a real-time PCR assay (Panenterhino/Ge/08) and a peptide nucleic acid-based hybridization oligoprobe (Panenterhino/Ge/08 PNA probe) designed to detect all HRV and HEV species members according to publicly available sequences. The reverse transcription-PCR assay has been validated, using not only plasmid and viral stocks but also quantified RNA transcripts and around 1,000 clinical specimens. These new generic detection PCR assays overcame the variability of circulating strains and lowered the risk of missing emerging and divergent HRV and HEV. An additional real-time PCR assay (Entero/Ge/08) was also designed specifically to provide sensitive and targeted detection of HEV in cerebrospinal fluid. In addition to the generic probe, we developed specific probes for the detection of HRV-A and HRV-B in cells. This investigation provides a comprehensive toolbox for accurate molecular identification of the different HEV and HRV circulating in humans.

Use of audiovisual messages from land user to land user for sharing knowledge about SLM: experiences from a pilot project in Kenya and Tajikistan

The global World Overview of Conservation Approaches and Technologies (WOCAT) initiative has developed standardised tools and methods to compile and evaluate knowledge available about SLM. This knowledge is now combined and enriched with audiovisual information in order to give a voice to land users, reach a broad range of stakeholders, and assist in scaling up SLM to reverse trends of degradation, desertification, and drought. Five video products, adapted to the needs of different target groups, are created and embedded in already existing platforms for knowledge sharing of SLM such as the WOCAT database and Google Earth application. A pilot project was carried out in Kenya and Tajikistan to verify ideas and tools while at the same time assessing the usefulness of the suggested products on the ground. Video has the potential to bridge the gap between different actor groups and enable communication and sharing on different levels and scales: locally, regionally, and globally. Furthermore, it is an innovative tool to link local and scientific knowledge, raise awareness, and support advocacy for SLM. Keywords: Sustainable Land Management (SLM), knowledge sharing, audiovisual messages, video, World Overview of Conservation Approaches and Technologies (WOCAT)

Information-Centric Networking in Mobile and Opportunistic Networks

Information Centric Networking (ICN) as an emerging paradigm for the Future Internet has initially been rather focusing on bandwidth savings in wired networks, but there might also be some significant potential to support communication in mobile wireless networks as well as opportunistic network scenarios, where end systems have spontaneous but time-limited contact to exchange data. This chapter addresses the reasoning why ICN has an important role in mobile and opportunistic networks by identifying several challenges in mobile and opportunistic Information-Centric Networks and discussing appropriate solutions for them. In particular, it discusses the issues of receiver and source mobility. Source mobility needs special attention. Solutions based on routing protocol extensions, indirection, and separation of name resolution and data transfer are discussed. Moreover, the chapter presents solutions for problems in opportunistic Information-Centric Networks. Among those are mechanisms for efficient content discovery in neighbour nodes, resume mechanisms to recover from intermittent connectivity disruptions, a novel agent delegation mechanisms to offload content discovery and delivery to mobile agent nodes, and the exploitation of overhearing to populate routing tables of mobile nodes. Some preliminary performance evaluation results of these developed mechanisms are provided.

Fuzzy knowledge representation in cognitive cities

This paper gives an insight into cognitive computing for smart cities, resulting in cognitive cities. Cognitive cities and cognitive computing research with the underlying concepts of knowledge graphs and fuzzy cognitive maps are presented and supported by existing tools (i.e., IBM Watson and Google Now) and intended tools (meta-app). The paper illustrates FCM as a suiting instrument to represent information/knowledge in a city environment driven by human-technology interaction, enforcing the concept of cognitive cities. A proposed paper prototype combines the findings of the paper and shows the next step in the implementation of the proposed meta-app.

Accelerated discovery of novel benzodiazepine ligands by experiment-guided virtual screening.

High throughput discovery of ligand scaffolds for target proteins can accelerate development of leads and drug candidates enormously. Here we describe an innovative workflow for the discovery of high affinity ligands for the benzodiazepine-binding site on the so far not crystallized mammalian GABAA receptors. The procedure includes chemical biology techniques that may be generally applied to other proteins. Prerequisites are a ligand that can be chemically modified with cysteine-reactive groups, knowledge of amino acid residues contributing to the drug-binding pocket, and crystal structures either of proteins homologous to the target protein or, better, of the target itself. Part of the protocol is virtual screening that without additional rounds of optimization in many cases results only in low affinity ligands, even when a target protein has been crystallized. Here we show how the integration of functional data into structure-based screening dramatically improves the performance of the virtual screening. Thus, lead compounds with 14 different scaffolds were identified on the basis of an updated structural model of the diazepam-bound state of the GABAA receptor. Some of these compounds show considerable preference for the α3β2γ2 GABAA receptor subtype.

The mass-hierarchy and CP-violation discovery reach of the LBNO long-baseline neutrino experiment

The next generation neutrino observatory proposed by the LBNO collaboration will address fundamental questions in particle and astroparticle physics. The experiment consists of a far detector, in its first stage a 20 kt LAr double phase TPC and a magnetised iron calorimeter, situated at 2300 km from CERN and a near detector based on a highpressure argon gas TPC. The long baseline provides a unique opportunity to study neutrino flavour oscillations over their 1st and 2nd oscillation maxima exploring the L/E behaviour, and distinguishing effects arising from δCP and matter. In this paper we have reevaluated the physics potential of this setup for determining the mass hierarchy (MH) and discovering CP-violation (CPV), using a conventional neutrino beam from the CERN SPS with a power of 750 kW. We use conservative assumptions on the knowledge of oscillation parameter priors and systematic uncertainties. The impact of each systematic error and the precision of oscillation prior is shown. We demonstrate that the first stage of LBNO can determine unambiguously the MH to > 5δ C.L. over the whole phase space. We show that the statistical treatment of the experiment is of very high importance, resulting in the conclusion that LBNO has ~ 100% probability to determine the MH in at most 4-5 years of running. Since the knowledge of MH is indispensable to extract δCP from the data, the first LBNO phase can convincingly give evidence for CPV on the 3δ C.L. using today’s knowledge on oscillation parameters and realistic assumptions on the systematic uncertainties.

Content Discovery in Wireless Information-Centric Networks

Information-centric networking (ICN) enables communication in isolated islands, where fixed infrastructure is not available, but also supports seamless communication if the infrastructure is up and running again. In disaster scenarios, when a fixed infrastructure is broken, content discovery algorit hms are required to learn what content is locally available. For example, if preferred content is not available, users may also be satisfied with second best options. In this paper, we describe a new content discovery algorithm and compare it to existing Depth-first and Breadth-first traversal algorithms. Evaluations in mobile scenarios with up to 100 nodes show that it results in better performance, i.e., faster discovery time and smaller traffic overhead, than existing algorithms.