An Alternative Assessment Approach Towards Learning Natural Sciences Communication

In STF2083 Scientific Communication, traditional written examinations were reduced to 30% using various types of alternative assessments which include (i) forums writing and online quizzes, (ii) mock research proposal presentation, (iii) mock research proposal writing and (iv) poster presentation . Instructions as well as rubrics were given to students prior to commencing of the assessments. Referring to the theme ‘Justify the basic principles in executing research’ as stated in CLO2 and ‘Display writing skills and presenting scientific reports’ in CLO3, the assessment of this course highlighted four (4) main sections; (a) identification of major/important need to conduct research (Problem statement identification), (b) the means to understand/solve the arising problems (hypothesis deduction), (c) the measurable target within the scope of this intended research (objectives determination) and (d) steps involved in achieving the outlined objectives (experimental design). In this course, all four types of assessments (i.e. mock research proposal writing, mock research proposal presentation, poster presentation and online forums) are individual-based assessment. The reason for such course design is to ensure individual performance is aligned with the intended assessment (authentic assessment)

A survey of recently emerged genome-wide computational enhancer predictor tools

The race for the discovery of enhancers at a genome-wide scale has been on since the commencement of next generation sequencing decades after the discovery of the first enhancer, SV40. A few enhancer-predicting features such as chromatin feature, histone modifications and sequence feature had been implemented with varying success rates. However, to date, there is no consensus yet on the single enhancer marker that can be employed to ultimately distinguish and uncover enhancers from the enormous genomic regions. Many supervised, unsupervised and semi-supervised computational approaches had emerged to complement and facilitate experimental approaches in enhancer discovery.In this review, we placed our focus on the recently emerged enhancer predictor tools that work on general enhancer features such as sequences, chromatin states and histone modifications, eRNA and of multiple feature approach. Comparisons of their prediction methods and outcomes were done across their functionally similar counterparts. We provide some recommendations and insights for future development of more comprehensive and robust tools

La adquisición del tiempo-aspecto en español en L3 para los aprendices taiwaneses

The purpose of this study was to investigate the inter-language development of the Spanish past tense by Taiwanese learners who learned Spanish as a second foreign language. The analysis of this study was based on the Lexical Aspect Hypothesis, which focuses on the inherent lexical aspect of verbs. We came to the following conclusions. (1) Taiwanese learners, whose first language was Mandarin Chinese, demonstrated more accurate uses of the Spanish preterite than the imperfect in written texts at their early stages of development. The acquisition of the lexical aspects of verbs in the preterite in terms of lexical aspect demonstrated the following order: achievement + accomplishment, activity and finally stative, whereas the acquisition of the imperfect showed the opposite sequence. (2) In the majority of the cases, the Taiwanese learners of Spanish demonstrated a similar pattern of acquisition of the Spanish past tense in terms of lexical aspect as that of English-speaking learner of Spanish. This paper will end with discussions on pedagogical implications of the findings and we hope this study will shed light on the current research on the second language acquisition of the Spanish tense/aspect.Este trabajo tiene como fin investigar el desarrollo de los tiempos pasados en la interlengua de los aprendices taiwaneses que aprenden español como segunda lengua extranjera. El análisis se basa en la Hipótesis de Aspecto Léxico que se centra en la importancia del aspecto léxico de los verbos. Llegamos a las siguientes conclusiones: (1) los aprendices taiwaneses de español cuya lengua materna es chino-mandarín manejan el pretérito mejor que el imperfecto en la producción escrita de los niveles iniciales de aprendizaje, el desarrollo de adquisición del pretérito indefinido es de acuerdo al siguiente orden: estado, actividad y realización+logro, mientras que para la adquisición del imperfecto los estudiantes siguen un orden contrario. (2) En la mayoría de los casos los aprendices taiwaneses de español siguen el mismo patrón de aprendizaje que los aprendices cuya lengua materna es el inglés en la adquisición del aspecto temporal. Por último, hacemos sugerencias pedagógicas correspondientes a las conclusiones deducidas para mejorar el resultado de aprendizaje. Con esto, esperamos que esta investigación represente una contribución al estudio relacionado con la adquisición del tiempo-aspecto en español

Plasma levels in sepsis patients of annexin A1, lipoxin A4, macrophage inflammatory protein-3a, and neutrophil gelatinase-associated lipocalin

AbstractBackgroundThe relationship between the various cytokine responses that occur during sepsis remains controversial. Emerging evidence indicates that the proinflammatory and anti-inflammatory responses are regulated simultaneously from the beginning of sepsis. However, the roles of the novel anti-inflammatory mediators annexin (Anx)A1 and lipoxin (LX)A4 and the proinflammatory cytokines neutrophil gelatinase-associated lipocalin (NGAL) and macrophage inflammatory protein (MIP)-3a have been studied.MethodsIn this study, the plasma levels of AnxA1, LXA4, NGAL, MIP-3a, interleukin (IL)-8 and IL-6 in patients with sepsis were determined on admission to the intensive care unit. The patients were classified into survivors and non-survivors based on their outcome on day 28.ResultsAnxA1 and LXA4 levels were decreased in sepsis patients compared with control patients, whereas the levels of the proinflammatory cytokines MIP-3a, NGAL, IL-8, and IL-6 were elevated. Furthermore, a significantly higher level of MIP-3a was detected in nonsurviving patients compared with surviving patients (p < 0.05), whereas there were no significant differences between these two groups for the levels of the other mediators. Correlation analysis demonstrated that only NGAL level was closely correlated with the level of IL-6. Univariate analysis indicated that the levels of MIP-3a and IL-8 were independent factors associated with patient survival, but this was not confirmed by the multivariate analysis.ConclusionAnxA1 and LXA4 plasma levels were found to be decreased in sepsis patients, whereas the levels of MIP-3a and NGAL were found to be elevated. This warrants further study in order to determine the clinical implications of these changes

Critical Success factors for ERP Implementation: A content analysis of empirical Findings

Enterprise resource planning (ERP) systems are software packages that allow companies to have greater real time visibility and control over their operations. Through a review of the ERP literature, seven critical success factors (CSFs) were identified based on the study of Nah and Delgado (2006). Content analysis was then employed on 16 published articles that reported CSFs for ERP. Correspondingly, this paper aimed to combine various results in order to determine the CSFs that contribute to success in the implementation of ERP systems. We found that the ERP CSFs referred to top management support and championship in a majority of articles, while communication was less mentioned

Adaptive particle swarm optimization

An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perform a global search over the entire search space with faster convergence speed. The APSO consists of two main steps. First, by evaluating the population distribution and particle fitness, a real-time evolutionary state estimation procedure is performed to identify one of the following four defined evolutionary states, including exploration, exploitation, convergence, and jumping out in each generation. It enables the automatic control of inertia weight, acceleration coefficients, and other algorithmic parameters at run time to improve the search efficiency and convergence speed. Then, an elitist learning strategy is performed when the evolutionary state is classified as convergence state. The strategy will act on the globally best particle to jump out of the likely local optima. The APSO has comprehensively been evaluated on 12 unimodal and multimodal benchmark functions. The effects of parameter adaptation and elitist learning will be studied. Results show that APSO substantially enhances the performance of the PSO paradigm in terms of convergence speed, global optimality, solution accuracy, and algorithm reliability. As APSO introduces two new parameters to the PSO paradigm only, it does not introduce an additional design or implementation complexity

Cloud computing resource scheduling and a survey of its evolutionary approaches

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon

Genetic learning particle swarm optimization

Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is more effective. Hence, this paper first develops a new framework so as to organically hybridize PSO with another optimization technique for “learning.” This leads to a generalized “learning PSO” paradigm, the *L-PSO. The paradigm is composed of two cascading layers, the first for exemplar generation and the second for particle updates as per a normal PSO algorithm. Using genetic evolution to breed promising exemplars for PSO, a specific novel *L-PSO algorithm is proposed in the paper, termed genetic learning PSO (GL-PSO). In particular, genetic operators are used to generate exemplars from which particles learn and, in turn, historical search information of particles provides guidance to the evolution of the exemplars. By performing crossover, mutation, and selection on the historical information of particles, the constructed exemplars are not only well diversified, but also high qualified. Under such guidance, the global search ability and search efficiency of PSO are both enhanced. The proposed GL-PSO is tested on 42 benchmark functions widely adopted in the literature. Experimental results verify the effectiveness, efficiency, robustness, and scalability of the GL-PSO