Miracle-dz/UniFAR-FTUs huggingface dataset:
The integration of environmental education with technology education : an investigation into teacher training and teacher practice

This research study is mainly based on the third learning outcome for Technology Education which requires the learners to be able to demonstrate an understanding of interrelationships between science, technology, society and the environment. The purpose of the study is to investigate how Technology Teacher Training Programmes incorporate environmental aspects into technology education and how Technology educators facilitate learning in order to meet environmental requirements that are expressed as learning outcome 3 for Technology Education. In this study an attempt is made to encourage efforts that could lead to the development of new learning frameworks, integrated activities and learning programmes for the technology education curriculum. The study is set against the literature on integrated programmes for curriculum development in general and for environmental and technology education in particular. It also draws on literature that calls for partnerships and closer co-operation between institutions of higher learning and the world of work, on evaluation research and programme evaluation and on the role that could be played by service-learning in promoting attitudes and values that are necessary for the integration of environmental aspects into technology education. Using the naturalistic or qualitative evaluation approach and narrative data production methods in the context of teaching and learning, the lecturers in teacher education institutions and technology educators in schools were interviewed in order to find out how technology teacher education prepared 11 technology educators for the workplace and how technology educators designed learning activities and facilitated learning in their technology classrooms. The curriculum documents for technology teacher education programmes were consulted and classroom observations also made. The research findings have indicated that technology educators find it difficult to integrate environmental education with technology education when teaching technology education and that technology teacher education programmes do not entirely prepare technology educators for the integration process that is required by the Revised National Curriculum documents of the Department of Education and Training.The study therefore calls for partnerships and collaborative efforts of higher education institutions, the Department of Education and Training and various environmental organizations in order to develop work integrated curricula that could enable technology educators to assist their learners to demonstrate an understanding of interrelationships between science, technology, society and the environment.
Modeling and Implementing Concurrent Engineering in a Virtual Collaborative Environment

Many companies are creating mterdisciplmary concurrent engineering teams to collaborate on product development projects from dispersed locations. The problems these companies face stem from the lack of understanding of technical, organizational, and pro cedural requirements for such activities to take place effectively. This paper proposes an integrated conceptual model of the product life cycle, and a virtual collaborative environment to support concurrent engineering. The product life cycle model features the life cycle pro cess itself, but also highlights the corresponding people and technology required for each phase. The virtual collaborative environment framework models the activities that occur, and the underlying infrastructure that must be present for collaboration to be effective. A sim ple prototype of the model is implemented, and an exploratory study is conducted to gain insight into the issues of concurrent engineer ing in a virtual collaborative environment, and to identify future research directions.
Towards autonomic service-oriented applications

The integration of third-party web services can solve complex business problems and can reduce risks, costs and time-to-market. However, the task of the integrators is challenged by services that are maintained by different organisations, and that may evolve dynamically and autonomously. The impossibility of statically determining which service implementation will be bound at runtime may lead to unexpected failures. This paper presents a novel approach for designing self-adaptive service-oriented applications, which autonomously react to changes in the implementation of the services, automatically detect possible integration mismatches and dynamically execute suitable adaptation strategies. The solution proposed in this paper is based on a taxonomy of integration faults that helps developers anticipate potential mismatches between discovered web services and applications, and design test cases and adaptors for each mismatch. A simple tool facilitates the deployment of a runtime infrastructure that embeds the test cases and the adaptors, automatically runs the test cases against newly discovered web services, uses the test results to diagnose service mismatches and executes the adaptors to overcome the revealed problems without user intervention.
Loading of Two Related Metal-Organic Frameworks (MOFs), [Cu2(bdc)2(dabco)] and [Cu2(ndc)2(dabco)], with Ferrocene

We have studied the loading of two related, similar porous metal-organic frameworks (MOFs) [Cu2(bdc)2(dabco)] (1), and [Cu2(ndc)2(dabco)] (2) with ferrocene by exposing bulk powder samples to the corresponding vapor. On the basis of powder X-ray diffraction data and molecular dynamics (MD) calculations we propose that each pore can store one ferrocene molecule. Despite the rather pronounced similarity of the two MOFs a quite different behavior is observed, for 1 loading with ferrocene leads to an anisotropic 1% contraction, whereas for 2 no deformation is observed. Mossbauer spectroscopy studies reveal that the Fe oxidation level remains unchanged during the process. Time dependent studies reveal that the diffusion constant governing the loading from the gas-phase for 1 is approximately three times larger than the value for 2.
Investigation of the Optoelectronic Properties of Ti-doped Indium Tin Oxide Thin Film

In this study, direct-current magnetron sputtering was used to fabricate Ti-doped indium tin oxide (ITO) thin films. The sputtering power during the 350-nm-thick thin-film production process was fixed at 100 W with substrate temperatures increasing from room temperature to 500 °C. The Ti-doped ITO thin films exhibited superior thin-film resistivity (1.5 × 10−4 Ω/cm), carrier concentration (4.1 × 1021 cm−3), carrier mobility (10 cm2/Vs), and mean visible-light transmittance (90%) at wavelengths of 400–800 nm at a deposition temperature of 400 °C. The superior carrier concentration of the Ti-doped ITO alloys (>1021 cm−3) with a high figure of merit (81.1 × 10−3 Ω−1) demonstrate the pronounced contribution of Ti doping, indicating their high suitability for application in optoelectronic devices.
Social Analytics in an Enterprise Context: From Manufacturing to Software Development

Although customers become more and more vocal in expressing their experiences, demands and needs in various social networks, companies of any size typically fail to effectively gain insights from such social data and to eventually catch the market realm. This paper introduces the Anlzer analytics engine that aims at leveraging the "social" data deluge to help companies in their quest for deeper understanding of their products' perceptions as well as of the emerging trends in order to early embed them into their product design phase. The proposed approach brings together polarity detection and trend analysis techniques as presented in the architecture and demonstrated through a simple walkthrough in the Anlzer solution. The Anlzer implementation is by design domain-independent and is being tested in the furniture domain at the moment, yet it brings significant added value to software design and development, as well, through its experimentation playground that may provide indirect feedback on future software features while monitoring the reactions to existing releases.
HIV‐1 Tat transcriptional activity is regulated by acetylation

The human immunodeficiency virus (HIV) trans‐ activator protein, Tat, stimulates transcription from the viral long‐terminal repeats (LTR) through an RNA hairpin element, trans‐activation responsive region (TAR). We and others have shown that trans‐activator protein (Tat)‐associated histone acetyltransferases (TAHs), p300 and p300/CBP‐associating factor (PCAF), assist functionally in the activation of chromosomally integrated HIV‐1 LTR. Here, we show that p300 and PCAF also directly acetylate Tat. We defined two sites of acetylation located in different functional domains of Tat. p300 acetylated Lys50 in the TAR RNA binding domain, while PCAF acetylated Lys28 in the activation domain of Tat. In support of a functional role for acetylation in vivo, histone deacetylase inhibitor (trichostatin A) synergized with Tat in transcriptional activation of the HIV‐1 LTR. Synergism was TAR‐dependent and required the intact presence of both Lys28 and Lys50. Mechanistically, acetylation at Lys28 by PCAF enhanced Tat binding to the Tat‐associated kinase, CDK9/P‐TEFb, while acetylation by p300 at Lys50 of Tat promoted the dissociation of Tat from TAR RNA that occurs during early transcription elongation. These data suggest that acetylation of Tat regulates two discrete and functionally critical steps in transcription, binding to an RNAP II CTD‐kinase and release of Tat from TAR RNA.
Modeling of 3D Left Ventricular motion to evaluate paced myocardial function

Pacemaker is widely used to help control abnormal heart rhythms. In this paper, we propose to evaluate the paced myocardial function by building a Three-Dimensional (3D) mechanical motion model of Left Ventricular (LV), in order to optimize the pacing models. We first create a 3D standard LV model based on manually segmented LV segments by experienced clinicians. The mechanical motion of LV is further measured using Two-Dimensional (2D) Ultrasonic Doppler Tissue Velocity (DTV) imaging, and correlated with the 3D LV model by Mutual Information (MI) based non-rigid registration methods. Such multiple 2D motion images are then mapped to the 3D LV model by interpolation. The preliminary experiments are carried out by comparing the myocardial function before and after pacemaker implantation, and prove the promising feasibility of our proposed method.
The Maturity Structure of Inside Money

In practice, bank liablities circulate, acting as inside money. What are the implications of the usefulness of these liabilities to facilitate trade for the bank's choice of maturity structure? Suppose that a bank finances illiquid long term real assets with long and short term financial claims. The households purchasing these claims use them as inside money to trade in a sequence of decentralized markets. Trade in decentralized markets is subject to search frictions as in Rocheteau and Wright (2005). The maturity structure of the bank's financial claims impacts their usefulness in facilitating trade and the bank's costs from liquidating long term real assets. Too much short-term money leads to excessive early liquidation of real long term assets, reducing the ability of inside money to facilitate trade in decentralized markets. Too much long-term money leads to too little costly liquidation of real assets, also reducing the ability of the inside money to facilitate decentralized exchange. The optimal maturity structure minimizes the cost of asset liquidation and maximizes the usefulness of the bank's claims in facilitating trade. We examine how the severity of the search frictions, the cost of early reversals, and the riskiness of the long-term real assets impact optimal maturity of the bank's inside money.
Hippocampal Gene Expression Meta-Analysis Identifies Aging and Age-Associated Spatial Learning Impairment (ASLI) Genes and Pathways

A number of gene expression microarray studies have been carried out in the past, which studied aging and age-associated spatial learning impairment (ASLI) in the hippocampus in animal models, with varying results. Data from such studies were never integrated to identify the most significant ASLI genes and to understand their effect. In this study we integrated these data involving rats using meta-analysis. Our results show that proper removal of batch effects from microarray data generated from different laboratories is necessary before integrating them for meta-analysis. Our meta-analysis has identified a number of significant differentially expressed genes across age or across ASLI. These genes affect many key functions in the aged compared to the young rats, which include viability of neurons, cell-to-cell signalling and interaction, migration of cells, neuronal growth, and synaptic plasticity. These functional changes due to the altered gene expression may manifest into various neurodegenerative diseases and disorders, some of which leading into syndromic memory impairments. While other aging related molecular changes can result into altered synaptic plasticity simply causing normal aging related non-syndromic learning or spatial learning impairments such as ASLI.
ShakeUnlock: Securely Transfer Authentication States Between Mobile Devices

As users start carrying multiple mobile devices, we propose a novel, token based mobile device unlocking approach. Mobile devices are conjointly shaken to transfer the authentication state from an unlocked token device to another device to unlock it. A common use case features a wrist watch as token device, which remains unlocked as long as it is strapped to the user's wrist, and a locked mobile phone, which is unlocked if both devices are shaken conjointly. Shaking can be done single-handedly, requires little user attention (users don't have to look at the device for unlocking it), and does not cause additional cognitive load on users. In case attackers gain control over the locked phone, forging shaking is difficult, which impedes malicious unlocks. We evaluate our approach using acceleration records from our 29 people sized ShakeUnlock database and discuss influence of its constituent parts on the system performance. We further present a performance study using an Android implementation and live data, which shows the true negative rate of observational attacks to be in the range of 0.8—if an attacker manages to gain control over the locked device and shake it in parallel to the device owner shaking the token device.
Second Language Use Facilitates Implicit Emotion Regulation via Content Labeling

Previous studies reported that negative stimuli induced less affect in bilinguals when stimuli were presented in bilinguals’ second, weaker language (L2) than when they were presented in their native language (L1). This effect of L2 use was attributed to increased emotional distance as well as to increased levels of cognitive control during L2 use. Here we investigated how explicit (cognitive reappraisal, i.e., reinterpreting the meaning of the emotional stimulus to alter its emotional impact) and implicit (content labeling, i.e., categorizing the content of the image; and emotion labeling, i.e., naming the emotion induced by the emotional stimulus) emotion regulation strategies are altered in an L2 (English) context in German native speakers with medium to high proficiency in their L2. While previous studies used linguistic stimuli, such as words, to induce affect, here we used images to test whether reduced affect could also be observed for non-linguistic stimuli when presented in an L2 context. We hypothesized that the previously implicated increase in emotional distance and cognitive control in an L2 would result in an L2 advantage in emotion regulation (i.e., leading to less negative emotions compared to an L1 context), by strengthening the effect of linguistic re-evaluation on the evoked emotions. Using a classic emotion regulation paradigm, we examined changes in subjective emotional state ratings during reappraisal, emotion labeling and content labeling in a L1 and L2 context. We found that the strength of evoked affective responses did not depend on the language context in which an image was presented. Crucially, content labeling in L2 was more effective than in L1, whereas emotion labeling did not differ between languages. Overall, evoked responses were regulated most effectively through explicit emotion regulation (reappraisal) in L1 and L2 context. These results demonstrate an L2 advantage effect for emotion regulation through content labeling and suggest that L2 context alters sub-processes implicated in content labeling but not emotion labeling.
Removing an intersubject variance component in a general linear model improves multiway factoring of event‐related spectral perturbations in group EEG studies

Linear statistical models are used very effectively to assess task‐related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra‐ and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task‐related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well‐studied response inhibition task. Hum Brain Mapp, 2013. © 2011 Wiley Periodicals, Inc.
Could we build a bridge between Austrian Economics and New Institutional Economics? A Pré-History of the Soft Budget Constraint

The concept of soft budget constraint is recent in economic analysis. It has become increasingly important in economic theory, for its role as a system of incentives. However, soft budget constraint plays also an important role in the history of economic thought, where it can be traced back until Mises's writings on economic calculation and property rights, both derived from the debate of the economic calculation in socialist regimes. In this sense, soft budget constraint can be viewed as a bridge between Austrian Economics and New Institutional Economics. Since Mises, like other Austrian economists, is virtually ignored in Brazilian courses of Economic Thought, this article intends to show his importance as a forerunner of the concept of soft budget constraint, and will try to link these two theoretical views of economic systems.
Leveraging Noisy Online Databases for Use in Chord Recognition

The most significant problem faced by Machine Learningbased chord recognition systems is arguably the lack of highquality training examples. In this paper, we address this problem by leveraging the availability of chord annotations from guitarist websites. We show that such annotations can be used as partial supervision of a semi-supervised chord recognition method—partial since accurate timing information is lacking. A particular challenge in the exploitation of these data is their low quality, potentially even leading to a performance degradation if used directly. We demonstrate however that a curriculum learning strategy can be used to automatically rank annotations according to their potential for improving the performance. Using this strategy, our experiments show a modest improvement for a simple major/minor chord alphabet, but a highly significant improvement for a much larger chord alphabet.
A System for Sensing Human Sentiments to Augment a Model for Predicting Rare Lake Events

Fish kill events (FKE) in the caldera lake of Taal occur rarely (only 0.5\% in the last 10 years) but each event has a long-term effect on the environmental health of the lake ecosystem, as well as a devastating effect on the financial and emotional aspects of the residents whose livelihood rely on aquaculture farming. Predicting with high accuracy when within seven days and where on the vast expanse of the lake will FKEs strike will be a very important early warning tool for the lake's aquaculture industry. Mathematical models to predict the occurrences of FKEs developed by several studies done in the past use as predictors the physico-chemical characteristics of the lake water, as well as the meteorological parameters above it. Some of the models, however, did not provide acceptable predictive accuracy and enough early warning because they were developed with unbalanced binary data set, i.e., characterized by dense negative examples (no FKE) and highly sparse positive examples (with FKE). Other models require setting up an expensive sensor network to measure the water parameters not only at the surface but also at several depths. Presented in this paper is a system for capturing, measuring, and visualizing the contextual sentiment polarity (CSP) of dated and geolocated social media microposts of residents within 10km radius of the Taal Volcano crater ($14^\circ$N, $121^\circ$E). High frequency negative CSP co-occur with FKE for two occasions making human expressions a viable non-physical sensors for impending FKE to augment existing mathematical models.
Effects of Moderate to Severe Traumatic Brain Injury on Anticipating Consequences of Actions in Adolescents: A Preliminary Study

Abstract For this pilot study, we compared performance of 15 adolescents with moderate–severe traumatic brain injury (TBI) to that of 13 typically developing (TD) adolescents in predicting social actions and consequences for avatars in a virtual microworld environment faced with dilemmas involving legal or moral infractions. Performance was analyzed in relation to cortical thickness in brain regions implicated in social cognition. Groups did not differ in number of actions predicted nor in reasons cited for predictions when presented only the conflict situation. After viewing the entire scenario, including the choice made by the avatar, TD and TBI adolescents provided similar numbers of short-term consequences. However, TD adolescents provided significantly more long-term consequences (p = .010). Additionally, for the Overall qualitative score, TD adolescents’ responses were more likely to reflect the long-term impact of the decision made (p = .053). Groups differed in relation of the Overall measure to thickness of right medial prefrontal cortex/frontal pole and precuneus, with stronger relations for the TD group (p < .01). For long-term consequences, the relations to the posterior cingulate, superior medial frontal, and precentral regions, and to a lesser extent, the middle temporal region, were stronger for the TBI group (p < .01). (JINS, 2013, 19, 1–10.)
The dynamic probe class library-an infrastructure for developing instrumentation for performance tools

The complexity of both parallel architectures and parallel applications poses several problems for the development of performance analysis and optimization tools. In this paper, we describe the motivations and the main aspects of the design of the Dynamic Probe Class Library (DPCL), an object based C++ class library that provides an infrastructure to reduce the cost of writing instrumentation for performance tools. Additionally, we present some of the performance tools built on top of DPCL, which demonstrate the power and flexibility of the library.