Between 2008 and 2010, 19 strains of infectious bronchitis virus (IBV) were isolated from the vaccinated chicken flocks in Sichuan province, China. The S1 genes of the isolates were amplified and sequenced. Phylogenetic analysis revealed that the 19 isolates and 37 reference IBV strains can be grouped into eight genotypes. Although IBVs of Taiwan-I type, massachusetts type, and proventriculitis type were isolated, but most isolates were LX4 genotype. Homology analysis of the sequences of S1 genes of the 19 isolates and 37 reference IBV strains revealed that the identity of the nucleotides and amino acid sequences of the S1 genes between the 15 LX4-type isolates and other IBV strains were 71.9-99.3% and 72.1-99.1%, respectively, while those of the analyzed IBV of LX4 type were 96.0-99.9% and 94.3-99.8%, respectively. The results from this study and other published results in the GenBank database showed that isolates circulating in Sichuan province in recent years were mainly LX4 genotype, which is the predominant genotype circulated in China in recent years.

Research on the limitations of dual-tasking might profit from using setups with a predictable sequence of stimuli and responses and assessing the acquisition of this sequence. Detrimental effects of dual-tasking on implicit sequence learning in the serial reaction time task (SRTT; Nissen & Bullemer, 1987)-when paired with an uncorrelated task-have been attributed to participants' lack of separating the streams of events in either task. Assuming that co-occurring events are automatically integrated, we reasoned that participants could need to first learn which events co-occur, before they can acquire sequence knowledge. In the training phase, we paired an 8-element visual-manual SRTT with an auditory-vocal task. Afterwards, we tested under single-tasking conditions whether SRTT sequence knowledge had been acquired. By applying different variants of probabilistic SRTT-tone pairings across three experiments, we tested what type of predictive relationship was needed to preserve sequence learning. In Experiment 1, where half of the SRTT-elements were paired to 100% with one specific tone and the other half randomly, only the fixedly paired elements were learned. Yet, no sequence learning was found when each of the eight SRTT-elements was paired with tone identity in a 75%-25% ratio (Experiment 2). Sequence learning was, however, intact when the 75%-25% ratio was applied to the four SRTT target locations instead (Experiment 3). The results suggest that participants (when lacking a separation of the task representations while dual-tasking) can learn a sequence inherent in one of two tasks to the extent that across-task contingencies can be learned first.

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In this study we examined the different functions of text and pictures during text-picture integration in multimedia learning. In Study 1, 144 secondary school students (age = 11 to 14 years; 72 females, 72 males) received six text-picture units under two conditions. In the delayed-question condition, students first read the units without a specific question (no-question phase), to stimulate initial coherence-oriented mental model construction. Afterward the question was presented (question-answering phase), to stimulate task-adaptive mental model specification. In the preposed-question condition, students received a specific question from the beginning, stimulating both kinds of processing. Analyses of the participants' eye movement patterns confirmed the assumption that students allocated a higher percentage of available resources to text processing during the initial mental model construction than during adaptive model specification. Conversely, students allocated a higher percentage of available resources to picture processing during adaptive mental model specification than during the initial mental model construction. In Study 2 (N = 12, age = 12 to 16; seven females, five males), we ruled out that these findings were due to the effect of rereading, by implementing a no-question phase either once or twice. To sum up, texts seem to provide more explicit conceptual guidance in mental model construction than pictures do, whereas pictures support mental model adaptation more than text does, by providing flexible access to specific information for task-oriented updates. Keywords Text-picture integration. Eye tracking. Initial mental model construction. Adaptive mental model specification Text accompanied by static pictures is ubiquitous in textbooks, especially those for the natural sciences. Abundant research has shown that students learn better from text and pictures than from text alone (e.g., Carney & Levin, 2002; DeLeeuw & Mayer, 2008; Mayer, 2009). Nevertheless, it is not yet well understood how text and pictures interact in their conjoint processing (Ortegren, Serra, & England, 2015). When both text and picture are needed for comprehension and learning, students must integrate verbal and pictorial information into one coherent, task-appropriate mental representation, a process known as text-picture integration. An example of the need for text-picture integration is presented in Fig. 1, which originates from a textbook on biology. The text describes the dynamic processes of blood circulation between mother and fetus during pregnancy, which is shown in pictures that point out the main parts using numbers. Global understanding, as well as the answering of specific questions, requires students to integrate the text and picture information. Referring to Wainer's (1992) taxonomy, integration requirements can differ in terms of their complexity. Lowcomplexity questions require only element mappings between text and picture. For example, to answer the question what is the name of the pink area?, students have to s...

Scientific ideas are often expressed as mathematical equations. Understanding the ideas contained within these equations requires making sense of both the embedded mathematics knowledge and scientific knowledge. Students who can engage in this type of blended sensemaking are more successful at solving novel or more complex problems with these equations. However, students often tend to rely on algorithmic/procedural approaches and struggle to make sense of the underlying science. This deficit may partly be the fault of instruction that focuses on superficial connections with the science and mathematics knowledge such as defining variables in the equation and demonstrating step-by-step procedures for solving problems. Research into the types of sensemaking of mathematical equations in science contexts is hindered by the absence of a shared framework. Therefore, a review of the literature was completed to identify themes addressing sensemaking of mathematical equations in science. These themes were compiled into nine categories, four in the science sensemaking dimension and five in the mathematics sensemaking dimension. This framework will allow for comparison across studies on the teaching and learning of mathematical equations in science and thus help to advance our understanding of how students engage in sensemaking when solving quantitative problems as well as how instruction influences this sensemaking.