Systematic evaluation of GoSoapBox in tertiary education : a student response system for improving learning experiences and outcomes

There is currently a wide range of research into the recent introduction of student response systems in higher education and tertiary settings (Banks 2006; Kay and Le Sange, 2009; Beatty and Gerace 2009; Lantz 2010; Sprague and Dahl 2009). However, most of this pedagogical literature has generated ‘how to’ approaches regarding the use of ‘clickers’, keypads, and similar response technologies. There are currently no systematic reviews on the effectiveness of ‘GoSoapBox’ – a more recent, and increasingly popular student response system – for its capacity to enhance critical thinking, and achieve sustained learning outcomes. With rapid developments in teaching and learning technologies across all undergraduate disciplines, there is a need to obtain comprehensive, evidence-based advice on these types of technologies, their uses, and overall efficacy. This paper addresses this current gap in knowledge. Our teaching team, in an undergraduate Sociology and Public Health unit at the Queensland University of Technology (QUT), introduced GoSoapBox as a mechanism for discussing controversial topics, such as sexuality, gender, economics, religion, and politics during lectures, and to take opinion polls on social and cultural issues affecting human health. We also used this new teaching technology to allow students to interact with each other during class – both on both social and academic topics – and to generate discussions and debates during lectures. The paper reports on a data-driven study into how this interactive online tool worked to improve engagement and the quality of academic work produced by students. This paper will firstly, cover the recent literature reviewing student response systems in tertiary settings. Secondly, it will outline the theoretical framework used to generate this pedagogical research. In keeping with the social and collaborative features of Web 2.0 technologies, Bandura’s Social Learning Theory (SLT) will be applied here to investigate the effectiveness of GoSoapBox as an online tool for improving learning experiences and the quality of academic output by students. Bandura has emphasised the Internet as a tool for ‘self-controlled learning’ (Bandura 2001), as it provides the education sector with an opportunity to reconceptualise the relationship between learning and thinking (Glassman & Kang 2011). Thirdly, we describe the methods used to implement the use of GoSoapBox in our lectures and tutorials, and which aspects of the technology we drew on for learning purposes, as well as the methods for obtaining feedback from the students about the effectiveness or otherwise of this tool. Fourthly, we report cover findings from an examination of all student/staff activity on GoSoapBox as well as reports from students about the benefits and limitations of it as a learning aid. We then display a theoretical model that is produced via an iterative analytical process between SLT and our data analysis for use by academics and teachers across the undergraduate curriculum. The model has implications for all teachers considering the use of student response systems to improve the learning experiences of their students. Finally, we consider some of the negative aspects of GoSoapBox as a learning aid.

Tensile properties of graphene nanotube hybrid structures : a molecular dynamics study

Graphene has been reported with record-breaking properties which have opened up huge potential applications. A considerable research has been devoted to manipulate or modify the properties of graphene to target a more smart nanoscale device. Graphene and carbon nanotube hybrid structure (GNHS) is one of the promising graphene derivates, while their mechanical properties have been rarely discussed in literature. Therefore, such a studied is conducted in this paper basing on the large-scale molecular dynamics simulation. The target GNHS is constructed by considering two separate graphene layers that being connected by single-wall carbon nanotubes (SWCNTs) according to the experimental observations. It is found that the GNHSs exhibit a much lower yield strength, Young’s modulus, and earlier yielding comparing with a bilayer graphene sheet. Fracture of studied GNHSs is found to fracture located at the connecting region between carbon nanotubes (CNTs) and graphene. After failure, monatomic chains are normally observed at the front of the failure region, and the two graphene layers at the failure region without connecting CNTs will adhere to each other, generating a bilayer graphene sheet scheme (with a layer distance about 3.4 Å). This study will enrich the current understanding of the mechanical performance of GNHS, which will guide the design of GNHS and shed lights on its various applications.

Estimation of vibration amplitude in Fourier domain optical coherence tomography interferometric signals from Doppler spectrum

In presented method combination of Fourier and Time domain detection enables to broaden the effective bandwidth for time dependent Doppler Signal that allows for using higher-order Bessel functions to calculate unambiguously the vibration amplitudes.

A recurrent network in the lateral amygdala : a mechanism for coincidence detection

Synaptic changes at sensory inputs to the dorsal nucleus of the lateral amygdala (LAd) play a key role in the acquisition and storage of associative fear memory. However, neither the temporal nor spatial architecture of the LAd network response to sensory signals is understood. We developed a method for the elucidation of network behavior. Using this approach, temporally patterned polysynaptic recurrent network responses were found in LAd (intra-LA), both in vitro and in vivo, in response to activation of thalamic sensory afferents. Potentiation of thalamic afferents resulted in a depression of intra-LA synaptic activity, indicating a homeostatic response to changes in synaptic strength within the LAd network. Additionally, the latencies of thalamic afferent triggered recurrent network activity within the LAd overlap with known later occurring cortical afferent latencies. Thus, this recurrent network may facilitate temporal coincidence of sensory afferents within LAd during associative learning.

Lesions in the bed nucleus of the stria terminalis disrupt corticosterone and freezing responses elicited by a contextual but not by a specific cue-conditioned fear stimulus

The bed nucleus of the stria terminalis (BNST) is believed to be a critical relay between the central nucleus of the amygdala (CE) and the paraventricular nucleus of the hypothalamus in the control of hypothalamic–pituitary– adrenal (HPA) responses elicited by conditioned fear stimuli. If correct, lesions of CE or BNST should block expression of HPA responses elicited by either a specific conditioned fear cue or a conditioned context. To test this, rats were subjected to cued (tone) or contextual classical fear conditioning. Two days later, electrolytic or sham lesions were placed in CE or BNST. After 5 days, the rats were tested for both behavioral (freezing) and neuroendocrine (corticosterone) responses to tone or contextual cues. CE lesions attenuated conditioned freezing and corticosterone responses to both tone and con- text. In contrast, BNST lesions attenuated these responses to contextual but not tone stimuli. These results suggest CE is indeed an essential output of the amygdala for the expres- sion of conditioned fear responses, including HPA re- sponses, regardless of the nature of the conditioned stimu- lus. However, because lesions of BNST only affected behav- ioral and endocrine responses to contextual stimuli, the results do not support the notion that BNST is critical for HPA responses elicited by conditioned fear stimuli in general. Instead, the BNST may be essential specifically for contex- tual conditioned fear responses, including both behavioral and HPA responses, by virtue of its connections with the hippocampus, a structure essential to contextual condition- ing. The results are also not consistent with the hypothesis that BNST is only involved in unconditioned aspects of fear and anxiety.

Myosin light chain kinase regulates synaptic plasticity and fear learning in the lateral amygdala

Learning and memory depend on signaling mole- cules that affect synaptic efficacy. The cytoskeleton has been implicated in regulating synaptic transmission but its role in learning and memory is poorly understood. Fear learning depends on plasticity in the lateral nucleus of the amygdala. We therefore examined whether the cytoskeletal-regulatory protein, myosin light chain kinase, might contribute to fear learning in the rat lateral amygdala. Microinjection of ML-7, a specific inhibitor of myosin light chain kinase, into the lateral nucleus of the amygdala before fear conditioning, but not immediately afterward, enhanced both short-term memory and long-term memory, suggesting that myosin light chain kinase is involved specifically in memory acquisition rather than in posttraining consolidation of memory. Myosin light chain kinase inhibitor had no effect on memory retrieval. Furthermore, ML-7 had no effect on behavior when the train- ing stimuli were presented in a non-associative manner. An- atomical studies showed that myosin light chain kinase is present in cells throughout lateral nucleus of the amygdala and is localized to dendritic shafts and spines that are postsynaptic to the projections from the auditory thalamus to lateral nucleus of the amygdala, a pathway specifically impli- cated in fear learning. Inhibition of myosin light chain kinase enhanced long-term potentiation, a physiological model of learning, in the auditory thalamic pathway to the lateral nu- cleus of the amygdala. When ML-7 was applied without as- sociative tetanic stimulation it had no effect on synaptic responses in lateral nucleus of the amygdala. Thus, myosin light chain kinase activity in lateral nucleus of the amygdala appears to normally suppress synaptic plasticity in the cir- cuits underlying fear learning, suggesting that myosin light chain kinase may help prevent the acquisition of irrelevant fears. Impairment of this mechanism could contribute to pathological fear learning.

Proposing and developing a definition and conceptual framework for health care resilience to cope with disasters [Resiliencia: Propuesta y desarrollo de la definicion y del marco conceptual en relacion a los desastres en el ambito sanitario]

La creación del término resiliencia en salud es un paso importante hacia la construcción de comunidades más resilientes para afrontar mejor los desastres futuros. Hasta la fecha, sin embargo, parece que hay poca literatura sobre cómo el concepto de resiliencia en salud debe ser definido. Este artículo tiene como objetivo construir un enfoque de gestión de desastres de salud integral guiado por el concepto de resiliencia. Se realizaron busquedas en bases de datos electrónicas de salud para recuperar publicaciones críticas que pueden haber contribuido a los fines y objetivos de la investigación. Un total de 61 publicaciones se incluyeron en el análisis final de este documento, que se centraron en aquéllas que proporcionan una descripción completa de las teorías y definiciones de resiliencia ante los desastres y las que proponen una definición y un marco conceptual para la capacidad de resiliencia en salud. La resiliencia es una capacidad inherente de adaptación para hacer frente a la incertidumbre del futuro. Esto implica el uso de múltiples estrategias, un enfoque de riesgos máximos y tratar de lograr un resultado positivo a través de la vinculación y cooperación entre los distintos elementos de la comunidad. Resiliencia en salud puede definirse como la capacidad de las organizaciones de salud para resistir, absorber, y responder al impacto de los desastres, mientras mantiene las funciones esenciales y se recupera a su estado original o se adapta a un nuevo estado. Puede evaluarse por criterios como la robustez, la redundancia, el ingenio y la rapidez e incluye las dimensiones clave de la vulnerabilidad y la seguridad, los recursos y la preparación para casos de desastre, la continuidad de los servicios esenciales de salud, la recuperación y la adaptación. Este nuevo concepto define las capacidades en gestión de desastres de las organizaciones sanitarias, las tareas de gestión, actividades y resultados de desastres juntos en una visión de conjunto integral, y utiliza un enfoque integrado y con un objetivo alcanzable. Se necesita urgentemente investigación futura de su medición

Optimization of an integrated model for automatic reduction and expansion of long queries

A long query provides more useful hints for searching relevant documents, but it is likely to introduce noise which affects retrieval performance. In order to smooth such adverse effect, it is important to reduce noisy terms, introduce and boost additional relevant terms. This paper presents a comprehensive framework, called Aspect Hidden Markov Model (AHMM), which integrates query reduction and expansion, for retrieval with long queries. It optimizes the probability distribution of query terms by utilizing intra-query term dependencies as well as the relationships between query terms and words observed in relevance feedback documents. Empirical evaluation on three large-scale TREC collections demonstrates that our approach, which is automatic, achieves salient improvements over various strong baselines, and also reaches a comparable performance to a state of the art method based on user’s interactive query term reduction and expansion.

The mitochondrial genome of the Russian wheat aphid Diuraphis noxia : large repetitive sequences between trnE and trnF in aphids

To characterize aphid mitochondrial genome (mitogenome) features, we sequenced the complete mitogenome of the Russian wheat aphid, Diuraphis noxia. The 15,784-bp mitogenome with a high A + T content (84.76%) and strong C skew (− 0.26) was arranged in the same gene order as that of the ancestral insect. Unlike typical insect mitogenomes, D. noxia possessed a large tandem repeat region (644 bp) located between trnE and trnF. Sequencing partial mitogenome of the cotton aphid (Aphis gossypii) further confirmed the presence of the large repeat region in aphids, but with different repeat length and copy number. Another motif (58 bp) tandemly repeated 2.3 times in the control region of D. noxia. All repeat units in D. noxia could be folded into stem-loop secondary structures, which could further promote an increase in copy numbers. Characterization of the D. noxia mitogenome revealed distinct mitogenome architectures, thus advancing our understanding of insect mitogenomic diversities and evolution.

Identifying steganographic payload location in binary image

In this paper, we propose a steganalysis method that is able to identify the locations of stego bearing pixels in the binary image. In order to do that, our proposed method will calculate the residual between a given stego image and its estimated cover image. After that, we will compute the local entropy difference between these two versions of images as well. Finally, we will compute the mean of residual and mean of local entropy difference across multiple stego images. From these two means, the locations of stego bearing pixels can be identified. The presented empirical results demonstrate that our proposed method can identify the stego bearing locations of near perfect accuracy when sufficient stego images are supplied. Hence, our proposed method can be used to reveal which pixels in the binary image have been used to carry the secret message.

Binary image steganographic techniques classification based on multi-class steganalysis

In this paper, we propose a new multi-class steganalysis for binary image. The proposed method can identify the type of steganographic technique used by examining on the given binary image. In addition, our proposed method is also capable of differentiating an image with hidden message from the one without hidden message. In order to do that, we will extract some features from the binary image. The feature extraction method used is a combination of the method extended from our previous work and some new methods proposed in this paper. Based on the extracted feature sets, we construct our multi-class steganalysis from the SVM classifier. We also present the empirical works to demonstrate that the proposed method can effectively identify five different types of steganography.

Blind steganalysis : a countermeasure for binary image steganography

In this paper, we propose a new blind steganalytic method to detect the presence of secret messages embedded in black and white images using the steganographic techniques. We start by extracting several sets of matrix, such as run length matrix, gap length matrix and pixel difference. We also apply characteristic function on these matrices to enhance their discriminative capabilities. Then we calculate the statistics which include mean, variance, kurtosis and skewness to form our feature sets. The presented empirical works demonstrate our proposed method can effectively detect three different types of steganography. This proves the universality of our proposed method as a blind steganalysis. In addition, the experimental results show our proposed method is capable of detecting small amount of the embedded message.

Estimating hidden message length in binary image embedded by using boundary pixels steganography

In this paper, we propose a new steganalytic method to detect the message hidden in a black and white image using the steganographic technique developed by Liang, Wang and Zhang. Our detection method estimates the length of hidden message embedded in a binary image. Although the hidden message embedded is visually imperceptible, it changes some image statistic (such as inter-pixels correlation). Based on this observation, we first derive the 512 patterns histogram from the boundary pixels as the distinguishing statistic, then we compute the histogram difference to determine the changes of the 512 patterns histogram induced by the embedding operation. Finally we propose histogram quotient to estimate the length of the embedded message. Experimental results confirm that the proposed method can effectively and reliably detect the length of the embedded message.

Features-pooling blind jpeg image steganalysis

In this research, we introduce a new blind steganalysis in detecting grayscale JPEG images. Features-pooling method is employed to extract the steganalytic features and the classification is done by using neural network. Three different steganographic models are tested and classification results are compared to the five state-of-the-art blind steganalysis.

JPEG image steganalysis improvement via image-to-image variation minimization

In this research, we introduce an approach to enhance the discriminative capability of features by employing image-to-image variation minimization. In order to minimize image-to-image variation, we will estimate the cover image from the stego image by decompressing the stego image, transforming the decompressed image and recompressing back. Since the effect of the embedding operation in an image steganography is actually a noise adding process to the image, applying these three processes will smooth out the noise and hence the estimated cover image can be obtained.