71 resultados para IoT platforms


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Integration of biological data of various types and the development of adapted bioinformatics tools represent critical objectives to enable research at the systems level. The European Network of Excellence ENFIN is engaged in developing an adapted infrastructure to connect databases, and platforms to enable both the generation of new bioinformatics tools and the experimental validation of computational predictions. With the aim of bridging the gap existing between standard wet laboratories and bioinformatics, the ENFIN Network runs integrative research projects to bring the latest computational techniques to bear directly on questions dedicated to systems biology in the wet laboratory environment. The Network maintains internally close collaboration between experimental and computational research, enabling a permanent cycling of experimental validation and improvement of computational prediction methods. The computational work includes the development of a database infrastructure (EnCORE), bioinformatics analysis methods and a novel platform for protein function analysis FuncNet.

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documented accurately since 1960. Most records are based on nest findings and there have been few direct observations or captures, mainly because live trapping of this species is not simple. Therefore, an efficient trapping technique is needed for population studies and to facilitate the management of its habitat. By combining the methods used to capture very small (Suncus etruscus) and climbing (Muscardinus avellanarius) mammals, we developed a design using Longworth traps with mouse excluders set on suspended platforms. This allowed us to trap more harvest mice in four field sessions of 60 trap-nights than have ever been caught previously since its discovery in Switzerland.

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PURPOSE OF REVIEW: Recent advances in nanotechnology have addressed some of the issues related to lack of selectivity and nonspecific toxicities associated with conventional chemotherapy. Nanoparticles are therapeutic carriers that can be fine tuned for specific application and for passive or active tumor targeting. RECENT FINDINGS: Although the nanoparticle field is rapidly expanding, there are to date only six nanoparticle-based drug delivery platforms and two antibody-drug conjugates that are clinically approved for cancer therapy. Here, we review the clinical data of liposomal anthracyclines, nanoparticle formulations of paclitaxel and trastuzumab emtansine. We then briefly comment on efficacy and safety issues of nanoparticles, as well as on the next-generation nanoparticles for cancer therapy. SUMMARY: The emerging development of cancer nanotechnology offers the opportunity of reinvestigating the potential of cytotoxic agents, improving tumor targeting and drug delivery, leading to better safety profile and antitumor activity. Adding specificity to nanoparticles may allow personalization of cancer therapy using chemotherapy.

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This article envisions the use of context-awareness to improve single sign-on solutions (SSO) for mobile users. The attribute-based SSO is expected to increase users' perceived ease of use of the system and service providers' authentication security of the application. From these two features we derive two value propositions for a new business model for mobile platforms. The business model can be considered as an instantiation of the privacy-friendly business model pattern presented in our previous work, reinforcing our claim that privacy-friendly value propositions are possible and can be used to obtain a competitive advantage.

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In this paper we discuss the main privacy issues around mobile business models and we envision new solutions having privacy protection as a main value proposition. We construct a framework to help analyze the situation and assume that a third party is necessary to warrant transactions between mobile users and m-commerce providers. We then use the business model canvas to describe a generic business model pattern for privacy third party services. This pattern is then illustrated in two different variations of a privacy business model, which we call privacy broker and privacy management software. We conclude by giving examples for each business model and by suggesting further directions of investigation

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Platforms like eBay allow product seekers and providers to meet and exchange goods. On eBay, consumers can return a product if it does not correspond to expectations; eBay is the third-party firm in charge of assuring that the agreement among seekers and providers will be respected. Who provides the same service for what concerns open innovation, where specifications might not fully defined? This paper describes the business model of an organizational structure to support the elicitation and respect of agreements among agents, who have conflicting interests but that gain from cooperating together. Extending previous studies, our business model takes into account the economic dimensions concerning the needs of knowledge share and mutual control to allow a third-party to sustainably reinforce trust among untrusted partners and to lower their overall relational risk.

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MOTIVATION: Lipids are a large and diverse group of biological molecules with roles in membrane formation, energy storage and signaling. Cellular lipidomes may contain tens of thousands of structures, a staggering degree of complexity whose significance is not yet fully understood. High-throughput mass spectrometry-based platforms provide a means to study this complexity, but the interpretation of lipidomic data and its integration with prior knowledge of lipid biology suffers from a lack of appropriate tools to manage the data and extract knowledge from it. RESULTS: To facilitate the description and exploration of lipidomic data and its integration with prior biological knowledge, we have developed a knowledge resource for lipids and their biology-SwissLipids. SwissLipids provides curated knowledge of lipid structures and metabolism which is used to generate an in silico library of feasible lipid structures. These are arranged in a hierarchical classification that links mass spectrometry analytical outputs to all possible lipid structures, metabolic reactions and enzymes. SwissLipids provides a reference namespace for lipidomic data publication, data exploration and hypothesis generation. The current version of SwissLipids includes over 244 000 known and theoretically possible lipid structures, over 800 proteins, and curated links to published knowledge from over 620 peer-reviewed publications. We are continually updating the SwissLipids hierarchy with new lipid categories and new expert curated knowledge. AVAILABILITY: SwissLipids is freely available at http://www.swisslipids.org/. CONTACT: alan.bridge@isb-sib.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Nonverbal behavior coding is typically conducted by "hand". To remedy this time and resource intensive undertaking, we illustrate how nonverbal social sensing, defined as the automated recording and extracting of nonverbal behavior via ubiquitous social sensing platforms, can be achieved. More precisely, we show how and what kind of nonverbal cues can be extracted and to what extent automated extracted nonverbal cues can be validly obtained with an illustrative research example. In a job interview, the applicant's vocal and visual nonverbal immediacy behavior was automatically sensed and extracted. Results show that the applicant's nonverbal behavior can be validly extracted. Moreover, both visual and vocal applicant nonverbal behavior predict recruiter hiring decision, which is in line with previous findings on manually coded applicant nonverbal behavior. Finally, applicant average turn duration, tempo variation, and gazing best predict recruiter hiring decision. Results and implications of such a nonverbal social sensing for future research are discussed.

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The article discusses the development of WEBDATANET established in 2011 which aims to create a multidisciplinary network of web-based data collection experts in Europe. Topics include the presence of 190 experts in 30 European countries and abroad, the establishment of web-based teaching and discussion platforms and working groups and task forces. Also discussed is the scope of the research carried by WEBDATANET. In light of the growing importance of web-based data in the social and behavioral sciences, WEBDATANET was established in 2011 as a COST Action (IS 1004) to create a multidisciplinary network of web-based data collection experts: (web) survey methodologists, psychologists, sociologists, linguists, economists, Internet scientists, media and public opinion researchers. The aim was to accumulate and synthesize knowledge regarding methodological issues of web-based data collection (surveys, experiments, tests, non-reactive data, and mobile Internet research), and foster its scientific usage in a broader community.

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Nanoparticulate formulations for synthetic long peptide (SLP)-cancer vaccines as alternative to clinically used Montanide ISA 51- and squalene-based emulsions are investigated in this study. SLPs were loaded into TLR ligand-adjuvanted cationic liposomes and PLGA nanoparticles (NPs) to potentially induce cell-mediated immune responses. The liposomal and PLGA NP formulations were successfully loaded with up to four different compounds and were able to enhance antigen uptake by dendritic cells (DCs) and subsequent activation of T cells in vitro. Subcutaneous vaccination of mice with the different formulations showed that the SLP-loaded cationic liposomes were the most efficient for the induction of functional antigen-T cells in vivo, followed by PLGA NPs which were as potent as or even more than the Montanide and squalene emulsions. Moreover, after transfer of antigen-specific target cells in immunized mice, liposomes induced the highest in vivo killing capacity. These findings, considering also the inadequate safety profile of the currently clinically used adjuvant Montanide ISA-51, make these two particulate, biodegradable delivery systems promising candidates as delivery platforms for SLP-based immunotherapy of cancer.

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Living bacteria or yeast cells are frequently used as bioreporters for the detection of specific chemical analytes or conditions of sample toxicity. In particular, bacteria or yeast equipped with synthetic gene circuitry that allows the production of a reliable non-cognate signal (e.g., fluorescent protein or bioluminescence) in response to a defined target make robust and flexible analytical platforms. We report here how bacterial cells expressing a fluorescence reporter ("bactosensors"), which are mostly used for batch sample analysis, can be deployed for automated semi-continuous target analysis in a single concise biochip. Escherichia coli-based bactosensor cells were continuously grown in a 13 or 50 nanoliter-volume reactor on a two-layered polydimethylsiloxane-on-glass microfluidic chip. Physiologically active cells were directed from the nl-reactor to a dedicated sample exposure area, where they were concentrated and reacted in 40 minutes with the target chemical by localized emission of the fluorescent reporter signal. We demonstrate the functioning of the bactosensor-chip by the automated detection of 50 μgarsenite-As l(-1) in water on consecutive days and after a one-week constant operation. Best induction of the bactosensors of 6-9-fold to 50 μg l(-1) was found at an apparent dilution rate of 0.12 h(-1) in the 50 nl microreactor. The bactosensor chip principle could be widely applicable to construct automated monitoring devices for a variety of targets in different environments.