25,675 research outputs found
The sim gene of Escherichia coli phage P1: nucleotide sequence and purification of the processed protein
No full textMaillou J, Dreiseikelmann B. The sim gene of Escherichia coli phage P1: nucleotide sequence and purification of the processed protein. Virology. 1990;175(2):500-507.The sim gene of bacteriophage P1 causes exclusion of a superinfecting P1 phage. We determined the nucleotide sequence of a 1.9-kb DNA fragment that, in plasmids, causes Sim phenotype. There are two open reading frames within this region for proteins of 82 and 259 amino acids. A 1.3-kb fragment containing the larger open reading frame was inserted into an expression vector. Induced cells carrying the hybrid plasmid, termed pBD5, were not infected by phage P1 and produced a 24-kDa protein and, to a smaller extent, a 25-kDa protein. The 24-kDa protein was purified. Comparison of its amino-terminal amino acid sequence with the nucleotide sequence indicated that it is processed from a precursor protein by removal of a hydrophobic leader peptide of 20 amino acids. In vivo processing depends on secA gene function and is necessary for Sim interference with P1 infection. The data are discussed with respect to the function of the sim gene in superinfection exclusion
La modalidad sim-consec frente a la interpretación consecutiva tradicional: estudio de caso
No full textTreball de Final de Grau en Traducció i Interpretació. Codi: TI0983. Curs acadèmic 2021/2022El presente Trabajo de Fin de Grado (TFG) explora la modalidad de interpretación sim-
consec, una modalidad híbrida que combina aspectos de la interpretación simultánea y de la
interpretación consecutiva. A pesar de la existencia de ciertos estudios relacionados con esta
modalidad, su escasa puesta en práctica en el mercado profesional, entre otras cuestiones, ha
motivado el estudio de caso en el que se basa este TFG. Mediante este trabajo se pretende evaluar
la calidad y aplicabilidad real de la sim-consec comparándola con la interpretación consecutiva
tradicional para intentar acercarnos a las posibles respuestas a las preguntas: ¿Puede la modalidad
sim-consec sustituir a la interpretación consecutiva tradicional? ¿Mejora esta modalidad la
calidad de la interpretación? ¿Cuáles son las ventajas e inconvenientes de la sim-consec? Para
comprobarlo de primera mano, se ha llevado a cabo un estudio de caso en el que se ha simulado
una situación de interpretación consecutiva (inglés > español) lo más realista posible. Durante el
estudio, ocho estudiantes de interpretación han realizado su función alternando la modalidad sim-
consec y consecutiva, posteriormente, se han evaluado y comparado entre sí las interpretaciones
resultantes. Para dicha evaluación, se han tenido en cuenta la presentación formal, la expresión y
el contenido. Además, se ha entrevistado a los intérpretes para conocer sus sensaciones e
impresiones tras las interpretaciones
Bruk av Sim-Man i bachelor-utdanningen i farmasi
No full textSimulering som læringsmetode blir tatt i bruk på flere fagområder. Simulering er å etterligne en virkelig situasjon ved hjelp av for eksempel en dukke. På Høgskolen i Nord Trøndelag (HiNT) avdeling for helsefag Namsos, finnes det en simuleringsdukke, SIM-MAN. Den egner seg godt til å simulere utfordringer helsepersonell kan oppleve. Per i dag er den blitt brukt mot sykepleiestudenter.
Farmasøyter er en gruppe helsepersonell som leverer ut legemidler til sluttbruker. Sjelden får de anledning til å se hva som kan skje med pasienten hvis legemidlene for eksempel ikke tas riktig / pasientene opplever bivirkninger. Dette kan farmasøyten en del om på teoretisk nivå.
På bakgrunn av dette, kom ideen om at en også kunne bruke SIM MAN i forhold til legemiddelrelaterte utfordringer for farmasistudenter. Et prøveprosjekt med bruk av SIM-MAN i forhold til legemiddel relaterte problemstillinger ble planlagt, gjennomført og evaluert
TURISMO E’ CULTURA. NOTE SUL RUOLO DEL TURISMO CULTURALE QUALE FATTORE DI SVILUPPO ECONOMICO E OCCUPAZIONALE In: I percorsi identitari nel marketing. Atti della 15a SIM Conference
No full textNegli ultimi anni vent’anni il turismo ha vissuto una crescita ininterrotta, nonostante sporadiche battute d’arresto, dimostrando la forza e la resilienza del settore e qualificandosi come una delle principali categorie del commercio internazionale. I dati degli ultimi 3 anni mostrano come i flussi turistici siano in crescita costante in tutto il mondo, avendo superato abbondantemente il miliardo di persone nel 2015, con un incremento delle entrate nelle destinazioni superiore ai 1.000 miliardi. Secondo i dati provvisori dell’Organizzazione Mondiale del Turismo1, nel 2017 gli arrivi internazionali, attestatisi intorno agli 1,32 miliardi di turisti, sono cresciuti del 6,8% rispetto all’anno precedente. È l’ottavo anno consecutivo di crescita del turismo internazionale dopo la crisi economica del 2009: una tale sequenza comparabile di crescita ininterrotta non si registrava sin dagli anni '60. In tale scenario internazionale, l’Europa resta la destinazione turistica più visitata dai viaggiatori: con oltre 600 milioni di arrivi riceve, infatti, oltre il 50% dei flussi complessivi. Seguono Asia e Pacifico (oltre 300 milioni, circa il 25%) e l’America con poco più di 200 milioni di arrivi (16%). Ai fini della crescita del settore, è ampiamente dimostrato che la cultura e il patrimonio culturale da oltre un decennio rivestono un ruolo di primo piano. A riguardo, già nel 2015 i trend globali riportati nel secondo rapporto Il turismo internazionale: comportamenti di consumo e scenari di sviluppo del CISET (Centro Internazionale di Studi sull’Economia Turistica) dell’Università Ca’ Foscari di Venezia2 confermavano che i prodotti più competitivi sono le destinazioni turistiche concorrenziali sul prodotto culturale tradizionale, anche grazie ad alcune dinamiche trasversali come la polarizzazione e solidità del turismo culturale tradizionale, favorito dal portafoglio clienti extraeuropeo
Agent-Based Cloud Computing
No full textAgent-based cloud computing is concerned with the design and development of software agents for bolstering cloud service
discovery, service negotiation, and service composition. The significance of this work is introducing an agent-based paradigm for
constructing software tools and testbeds for cloud resource management. The novel contributions of this work include: 1) developing
Cloudle: an agent-based search engine for cloud service discovery, 2) showing that agent-based negotiation mechanisms can be
effectively adopted for bolstering cloud service negotiation and cloud commerce, and 3) showing that agent-based cooperative problemsolving
techniques can be effectively adopted for automating cloud service composition. Cloudle consists of 1) a service discovery agent
that consults a cloud ontology for determining the similarities between providers’ service specifications and consumers’ service
requirements, and 2) multiple cloud crawlers for building its database of services. Cloudle supports three types of reasoning: similarity
reasoning, compatibility reasoning, and numerical reasoning. To support cloud commerce, this work devised a complex cloud
negotiation mechanism that supports parallel negotiation activities in interrelated markets: a cloud service market between consumer
agents and broker agents, and multiple cloud resource markets between broker agents and provider agents. Empirical results show that
using the complex cloud negotiation mechanism, agents achieved high utilities and high success rates in negotiating for cloud resources.
To automate cloud service composition, agents in this work adopt a focused selection contract net protocol (FSCNP) for dynamically
selecting cloud services and use service capability tables (SCTs) to record the list of cloud agents and their services. Empirical results
show that using FSCNP and SCTs, agents can successfully compose cloud services by autonomously selecting services
Grid Resource Negotiation: Survey and New Directions
No full textSince Grid computing systems involve large-scale resource sharing, resource management is central to their operations. Whereas there are more Grid resource management systems adopting auction, commodity market, and contract-net (tendering) models, this survey supplements and complements existing surveys by reviewing, comparing, and highlighting existing research initiatives on applying bargaining (negotiation) as a mechanism to Grid resource management. The contributions of this paper are: 1) discussing the motivations for considering bargaining models for Grid resource allocation; 2) discussing essential design considerations such as modeling devaluation of Grid resources, considering market dynamics, relaxing bargaining terms, and co-allocation of resources when building Grid negotiation mechanisms; 3) reviewing the strategies and protocols of state-of-the-art Grid negotiation mechanisms; 4) providing detailed comparisons and analyses on how state-of-the-art Grid negotiation mechanisms address the design considerations mentioned in 3); and 5) suggesting possible new directions
SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark
No full text<p>In this repository, we present the PacBio and ONT simulated datasets used for benchmarking transcriptome reconstruction tools, as evaluated in the manuscript titled "<i>SQANTI-SIM: a simulator of controlled transcript novelty for lrRNA-seq benchmark</i>". The dataset includes simulated long reads, short reads, CAGE peaks, and a reduced reference annotation. Additionally, we have included reconstructed transcriptomes from each method, along with SQANTI3 output files. The SQANTI-SIM software can be accessed on GitHub at the following URL: <a href="https://github.com/ConesaLab/SQANTI-SIM">https://github.com/ConesaLab/SQANTI-SIM</a>.</p><p>- Please ensure to cite the original publication (listed below) when using these datasets.</p>
<I>Andreaea flexuosa</I> R. Brown bis subsp. <I>luisieri</I> Sérgio <I>et</I> Sim-Sim (Andreaeaceae), a new <I>taxon</I> from Madeira Island
No full textA taxonomic study of critical plants belonging to the ecostate Andreaea from Madeira Island is presented. A new taxon, Andreaea flexuosa R. Brown bis subsp. luisieri Sérgio et Sim-Sim, is proposed based on material from upland areas in the central ridge of Madeira. Characters discriminating the two subspecies are presented and illustrated; data on ecology and distribution of the two subspecies are discussed.</p
BLGAN: Bayesian Learning and Genetic Algorithm for Supporting Negotiation With Incomplete Information
No full textAutomated negotiation provides a means for resolving
differences among interacting agents. For negotiation with
complete information, this paper provides mathematical proofs
to show that an agent’s optimal strategy can be computed using
its opponent’s reserve price (RP) and deadline. The impetus of
this work is using the synergy of Bayesian learning (BL) and
genetic algorithm (GA) to determine an agent’s optimal strategy
in negotiation (N) with incomplete information. BLGAN adopts:
1) BL and a deadline-estimation process for estimating an opponent’s
RP and deadline and 2) GA for generating a proposal
at each negotiation round. Learning the RP and deadline of an
opponent enables the GA in BLGAN to reduce the size of its search
space (SP) by adaptively focusing its search on a specific region
in the space of all possible proposals. SP is dynamically defined
as a region around an agent’s proposal P at each negotiation
round. P is generated using the agent’s optimal strategy determined
using its estimations of its opponent’s RP and deadline.
Hence, the GA in BLGAN is more likely to generate proposals
that are closer to the proposal generated by the optimal strategy.
Using GA to search around a proposal generated by its current
strategy, an agent in BLGAN compensates for possible errors in
estimating its opponent’s RP and deadline. Empirical results show
that agents adopting BLGAN reached agreements successfully,
and achieved: 1) higher utilities and better combined negotiation
outcomes (CNOs) than agents that only adopt GA to generate their
proposals, 2) higher utilities than agents that adopt BL to learn
only RP, and 3) higher utilities and better CNOs than agents that
do not learn their opponents’ RPs and deadlines
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