Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards tangible gamified co-design at school: two studies in primary schools

Co-design is an ideal approach to design with users. It allows designers to create products, such as games, with their intended users and in their natural environment, e.g., children and their teachers in their school. Nowadays school contexts, however, pose their own requirements to co-design, which can affect its success. For instance, school contexts tend to be associated to boring rote by learners, who are used to interactive digital games. Gamification can then help in creating a positive engaging experience for school classes that co-design, as games do. This paper takes up such a view: it gamifies co-design contexts in order to positively engage school classes. To this end it presents two studies with gamified co-design in primary schools: heterogeneous teams co-designed prototypes by resolving missions as in a game, in the first short-term study; they did it in an even more gamified context, in the second long-term study. Results of both studies are encouraging for the approach. The paper also advances basic guidelines for tangibly gamifying co-design at school, grounded in the studies and literature.
Brief report: Role of cortisol in posttraumatic stress symptoms among mothers of children diagnosed with cancer.

OBJECTIVE To examine the role of cortisol in posttraumatic stress symptomatology among mothers of children newly diagnosed with cancer. METHODS Mothers (N = 27) completed standardized measures of posttraumatic stress symptoms and provided salivary cortisol samples at the time of their child's cancer diagnosis and then monthly for 1 year. RESULTS Random effects regression analyses of 351 person-by-time observations revealed that high levels of cortisol were associated with higher levels of posttraumatic stress symptoms (B = .12, p < .02). The mothers who exhibited higher cortisol levels at the time of their child's diagnosis showed statistically significant declines in symptomatology from diagnosis to 12 months postdiagnosis (B = .97, p < .0001) compared to mothers who exhibited lower cortisol levels at diagnosis (B = .003, p < .05). CONCLUSIONS These findings offer some suggestions into possible neurobiological processes underlying posttraumatic stress symptoms and directions for future research and clinical intervention.
Temporal aspects of DNA and RNA synthesis during human immunodeficiency virus infection: evidence for differential gene expression

The kinetics of retroviral DNA and RNA synthesis are parameters vital to understanding viral growth, especially for human immunodeficiency virus (HIV), which encodes several of its own regulatory genes. We have established a single-cycle growth condition for HIV in H9 cells, a human CD4+ lymphocyte line. The full-length viral linear DNA is first detectable by 4 h postinfection. During a one-step growth of HIV, amounts of viral DNA gradually increase until 8 to 12 h postinfection and then decrease. The copy number of unintegrated viral DNA is not extraordinarily high even at its peak. Most strikingly, there is a temporal program of RNA accumulation: the earliest RNA is greatly enriched in the 2-kilobase subgenomic mRNA species, while the level of 9.2-kilobase RNA which is both genomic RNA and mRNA remains low until after 24 h of infection. Virus production begins at about 24 h postinfection. Thus, viral DNA synthesis is as rapid as for other retroviruses, but viral RNA synthesis involves temporal alteration in the species that accumulate, presumably as a consequence of viral regulatory genes.
A Static Analysis for Instance-based Confinement in Java

A semantic definition is given for instance-based pointer confinement (alias control); this provides a form of encapsulation suited to many object-oriented designs. A syntax-directed static analysis is defined and proved, using a compositional semantics, to imply semantic confinement. Previous work by the authors, reviewed here, shows that this notion of confinement ensures a strong information-hiding property. The language studied here has features of sequential Java including mutable state, private fields, dynamic binding and inheritance, recursive classes, casts and type tests, and mutually recursive methods.
Design and Control of a 3 kW Wireless Power Transfer System for Electric Vehicles

This paper aims to study a 3 kW wireless power transfer system for electric vehicles. First, the LCL-LCL topology and LC-LC series topology are analyzed, and their transfer efficiencies under the same transfer power are compared. The LC-LC series topology is validated to be more efficient than the LCL-LCL topology and thus is more suitable for the system design. Then a novel q-Zsource-based online power regulation method which employs a unique impedance network (two pairs of inductors and capacitors) to couple the cascaded H Bridge to the power source is proposed. By controlling the shoot-through state of the H Bridge, the charging current can be adjusted, and hence, transfer power. Finally, a prototype is implemented, which can transfer 3 kW wirelessly with ~95% efficiency over a 20 cm transfer distance.
Content Orientation in Integrated Product Modeling

Changes in engineering for development of product in the direction of increased complexity, more variants, and customer demand orientation stimulates implementation of advanced information technology in the form of virtual space. For this reason, concept of integrated product model has been implemented in comprehensive descriptions for lifecycle management of product information. Communication between engineer and modeling procedure is a critical factor. The authors identified data orientation of the recent integrated product modeling as a barrier for more efficient communication on user interfaces of product modeling systems. As a possible contribution to development of solution for this problem in industrial professional modeling systems, they propose content oriented layers between human and data oriented models in this paper. Following this, integration issues in content oriented product model are discussed. Next, relevant functions and modeling techniques for the handling of modeled object information are introduced and evaluated. Finally, a method is shown for the propagation of changes initiated for modeled objects in their affect zones.
Implantation of Neurotrophic Factor-Treated Sensory Nerve Graft Enhances Survival and Axonal Regeneration of Motoneurons After Spinal Root Avulsion

We previously showed that motor nerves are superior to sensory nerves in promoting axon regeneration after spinal root avulsion. It is, however, impractical to use motor nerves as grafts. One potential approach to enhancing axonal regeneration using sensory nerves is to deliver trophic factors to the graft. Here, we examined the regulation of receptors for brain-derived neurotrophic factor, glial cell line-derived neurotrophic factor, ciliary neurotrophic factor, and pleiotrophin after root avulsion in adult rats. We then tested their survival-promoting and neuroregenerative effects on spinal motoneurons. The results showed that receptors for brain-derived neurotrophic factor and glial cell line-derived neurotrophic factor were upregulated and that these trophic factors promoted survival and axonal regeneration of motoneurons when they were injected into the sensory nerve graft before implantation. In contrast, receptors for ciliary neurotrophic factor and pleiotrophin were downregulated after avulsion. Ciliary neurotrophic factor did not promote survival and axonal regeneration, whereas pleiotrophin promoted axonal regeneration but not survival of injured spinal motoneurons. Our results suggest that infusion of trophic factors into sensory nerve grafts promote motoneuron survival and axonal regeneration. The technique is technically easy and is, therefore, potentially clinically applicable.
Parental origin of the deletion 22q11.2 and brain development in velocardiofacial syndrome: a preliminary study.

BACKGROUND As children with velocardiofacial syndrome (VCFS) develop, they are at increased risk for psychopathology; one third will eventually develop schizophrenia. Because VCFS and the concomitant symptomatology result from a known genetic origin, the biological and behavioral characteristics of the syndrome provide an optimal framework for conceptualizing the associations among genes, brain development, and behavior. The purpose of this study was to investigate the effect of the parental origin of the 22q11.2 microdeletion on the brain development of children and adolescents with VCFS. METHODS Eighteen persons with VCFS and 18 normal control subjects were matched individually for age and sex. Results of DNA polymorphism analyses determined the parental origin of the deletion. Nine persons with VCFS had a deletion on the maternally derived chromosome 22; 9 persons, on the paternally derived chromosome 22. High-resolution magnetic resonance imaging scans were analyzed to provide quantitative measures of gray and white matter brain tissue. RESULTS Total brain volume was approximately 11% smaller in the VCFS group than in controls. Comparisons between VCFS subgroups (maternal vs paternal microdeletion 22q11.2) indicated a significant 9% volumetric difference in total volume of cerebral gray matter (volume was greater in patients with paternal microdeletion) but not cerebral white matter. Significant age-related changes in gray matter were detected for subjects whose 22q11.2 deletion was on the maternal chromosome. CONCLUSIONS Children and adolescents with VCFS experience major alterations in brain volumes. Significant reduction in gray matter development is attributable to presence of 22q11.2 microdeletion on the maternal chromosome.
Social Capital and Knowledge Creation in an ERP Project Team : Unintended Incapacitating Consequences of Social Capital

A project team, set up to design and implement an Enterprise Resource Planning (ERP) system, is essentially tasked with integrating knowledge distributed across an organization. This suggests that the social capital of members will be important. In the case study project, however, team members used their social capital to further their own personal goals rather than the ERP project goals. Moreover, time and effort spent maintaining networks with others outside the project to pursue personal goals prevented the project team from developing into a knowledge-sharing community. The paper uses the framework of strategic exchange to explore why, in this particular situation, social capital had a detrimental rather than a beneficial impact on the ERP project.
How subordinates reciprocate supervisor's trust: A cross-level model

Trust in leadership is regarded as the critical component of leader effectiveness. While how subordinates reciprocate trust from supervisor is recognized as a particular sailent isssue [1]. The current study examines such focusing factors of subordinates' trust in supervisor as supervisor's trust propensity, trust in subordinates, and subordinates' psychological empowerment. In the model we propose, supervisor's trust propensity exhibits a cross-level effect on subordinates' trust. And this effect is mediated by two individual constructs as trust in subordinates and psychological empowerment. While, in the individual level the effect of supervisor's trust on trust in supervisor is partially mediated by psychological empowerment. The mechanism of how subordinates reciprocate supervisor's trust also has great implications for trust reciprocation in general network emviorment.
Assessing Feature Relevance On-line Using Differential Discriminative Diagnosis

Philosophers, inventors and great minds alike have described human creations as extensions of the human body. From early tools to today's computers, this description holds true. Machine learning attempts to create the ultimate extension: The extension of the human mind. This inspires allusions to certain human capabilities as subjective metrics for assessing and designing the capabilities of learning algorithms. Artificial neural networks (ANNs) have gained significant acceptance as powerful concept learners over the recent years. Partly because of suggestions of biological plausibility, neural networks have often been explored as potential solutions to those problems humans and other animals instinctively solve. Speculations about biological motivations aside, the statistical framework that ANNs provide for learning is truly invaluable. Traditionally, neural networks have been trained off-line with a fair amount of training data. Depending on the objective function used for training, a neural network estimates certain statistics from the training data. The training data consists of labelled feature vectors, where each feature vector could potentially consist of both relevant and irrelevant features. Good pre-processing hopes to eliminate the irrelevant features from the set of feature vectors. Is preprocessing to assess and eliminate irrelevant features enough to ensure good performance of a neural network? Consider the task of tracking a person in a crowd. People can successfully track even in the presence of occlusion, awkward motion and many other subtleties in the environment. People not only learn with an explicit teacher, they also " learn from experience. " By observing patterns of motion in the scene and discriminating features on the person being tracked, people effectively learn to temporally correspond the person. The number of people in the scene, their positions, shadows, etc., are constantly changing. Yet, the person is tracked with reasonable accuracy. If there is a set of features that is unique to that person, humans can instantly key on those features and use it to track. Consider the problem of maneuvering through a busy sidewalk. People can quickly identify the best path to their destination and constantly adapt this path to match the changing environment. Much of this is done even though there
Nondecarboxylating and Decarboxylating Isocitrate Dehydrogenases: Oxalosuccinate Reductase as an Ancestral Form of Isocitrate Dehydrogenase

ABSTRACT Isocitrate dehydrogenase (ICDH) from Hydrogenobacter thermophilus catalyzes the reduction of oxalosuccinate, which corresponds to the second step of the reductive carboxylation of 2-oxoglutarate in the reductive tricarboxylic acid cycle. In this study, the oxidation reaction catalyzed by H. thermophilus ICDH was kinetically analyzed. As a result, a rapid equilibrium random-order mechanism was suggested. The affinities of both substrates (isocitrate and NAD+) toward the enzyme were extremely low compared to other known ICDHs. The binding activities of isocitrate and NAD+ were not independent; rather, the binding of one substrate considerably promoted the binding of the other. A product inhibition assay demonstrated that NADH is a potent inhibitor, although 2-oxoglutarate did not exhibit an inhibitory effect. Further chromatographic analysis demonstrated that oxalosuccinate, rather than 2-oxoglutarate, is the reaction product. Thus, it was shown that H. thermophilus ICDH is a nondecarboxylating ICDH that catalyzes the conversion between isocitrate and oxalosuccinate by oxidation and reduction. This nondecarboxylating ICDH is distinct from well-known decarboxylating ICDHs and should be categorized as a new enzyme. Oxalosuccinate-reducing enzyme may be the ancestral form of ICDH, which evolved to the extant isocitrate oxidative decarboxylating enzyme by acquiring higher substrate affinities.
Traffic Matrix Inference in IP Networks Networks 2002-Topic 2

While the traffic matrix is used as basic data for many network planning tasks, it must be recognized that its inference in IP networks is particularly difficult and error prone. This paper discusses the issue of defining representative traffic demands and surveys proposed techniques for directly measuring elements of the traffic matrix or inferring their value from link measurements.
An Approach to Enrich Users ’ Personomy Using Semantic Recommendation of Tags

Tagging-based systems are a popular and convenient way to organize information on the Web. However, the free vocabulary used to categorize Web objects brings some disadvantages to this type of system, especially when users need to retrieve the tagged object. This paper presents an approach to semantics recommendation of tags for tagging-based systems that aims at improving the quality of the categorizations performed by the users. Our approach combines three different resources for recommending tags: the Web page been categorized, the tagging-based system folksonomy and the user‟s personomy. By combining these resources, we seek to reduce the problems in the user‟s vocabulary, recommending representative tags that may relieve the users‟ cognitive effort when retrieving tagged objects.
An Analytical Way to Find Influencers on Social Networks and Validate their Effects in Disseminating Social Games

As the weight of online social networks (OSNs) which provide powerful means of sharing common interests and communicating has gradually grown up, influencers are also given the great attention. This research proposes and evaluates a methodology for discovering influencers within OSNs. Finding strong influencers out is momentous perspective in success of viral marketing. The methodology consists of two-step process. In step one, structural analysis, we extract the influencer candidate subgroup by the degree centrality computation based on the social graph. Next, we analyze each user’s activity history. After whole process, we finally obtain a few powerful influencers who can effectively affect other people than mediocrities. The positive effects of influencers are confirmed by analyzing the result of spreading social games out over Facebook. The results are compared with other game promotions without utilizing influencers. This methodology can be used in various marketing practices on social platforms.
Extensible proof engineering in intensional type theory

We increasingly rely on large, complex systems in our daily lives—from the computers that park our cars to the medical devices that regulate insulin levels to the servers that storeour personal information in the cloud. As these systemsgrow, they become too complex for a person to understand, yet it is essential that they are correct. Proof assistants are tools that let us specify properties about complex systems and build, maintain, and check proofs of these properties in a rigorous way. Proof assistants achieve this level of rigor for a wide range of properties by requiring detailed certificates (proofs) that can be easily checked. In this dissertation, I describe a technique for compositionally building extensible automation within a foundational proof assistant for intensional type theory. My technique builds on computational reflection—where properties are checked by verifiedprograms—which effectively bridges the gapbetween the low-level reasoning that is native to the proof assistant and the interesting, high-level properties of real systems. Building automation within a proof assistant provides a rigorous foundation that makes it possible to compose and extend the automation with other tools (including humans). However, previous approaches require using low-level proofs to compose different automation which limits scalability. My techniques allow for reasoning at a higher level about composing automation, which enables more scalable reflective reasoning. I demonstrate these techniques through a series of case studies centered around tasks in program verification.
Sensitivity analysis and robust experimental design of a signal transduction pathway system

Experimental design for cellular networks based on sensitivity analysis is studied in this work. Both optimal and robust experimental design strategies are developed for the IκB-NF-κB signal transduction model. Based on local sensitivity analysis, the initial IKK intensity is calculated using an optimal experimental design process, and several scalarization measures of the Fisher information matrix are compared. Global sensitivity analysis and robust experimental design techniques are then developed to consider parametric uncertainties in the model. The modified Morris method is employed in global sensitivity analysis, and a semidefinite programming method is exploited to implement the robust experimental design for the problem of measurement set selection. The parametric impacts on the oscillatory behavior of NF-κB in the nucleus are also discussed. © 2008 Wiley Periodicals, Inc. Int J Chem Kinet 40: 730–741, 2008
Motility and Chemotaxis in Two Strains of Rkizobium with Complex Flagella

Rhizobium meliloti MVII-1 and Rhizobium lupini H13-3, two strains with five to ten peritrichously inserted complex flagella, were studied with respect to motility and chemotaxis. Cells of both these strains move rapidly with speeds up to 40 pm s-I (R. meZiZoti) and 60 pm s-’ ( R . Zupini) respectively. Increasing viscosity causes little reduction in their swimming velocities as compared with Salmonella typhimurium propelled by plain flagella. It is suggested that complex flagella possess a high ‘flexural rigidity’, which serves to maintain a helix conformation favourable for propulsive efficiency at increased viscosities. C hemotaxis in R . meliloti MVII-1 and R . lupini H13-3 was studied and the conditions required have been defined using the capillary tube assay. All 20 common L-amino acids and L-homoserine were shown to be attractive to R . meliloti MVII-1 with thresholds varying from lop6 M (proline) to M (aspartate). Leucine, proline and lysine elicited optimal responses. R hizobium lupini H13-3 was also attracted by L-amino acids except for leucine, which elicited no response. Aspartate was a significantly better attractant of R . Zupini H13-3 than of R . meliloti MVII-1, and glycine, isoleucine, homoserine, serine, threonine, cysteine, glutamine and glutamate were poorer attractants. C hemotaxis towards various carbohydrates was generally better in R. Zupini H13-3 than in R . meliloti MVII-1. It is concluded that bacteria with complex flagella are efficient swimmers in viscous environments and are capable of responding to chemotactic stimuli.
Angels and monsters: an empirical investigation of potential test effectiveness and efficiency improvement from strongly subsuming higher order mutation

We study the simultaneous test effectiveness and efficiency improvement achievable by Strongly Subsuming Higher Order Mutants (SSHOMs), constructed from 15,792 first order mutants in four Java programs. Using SSHOMs in place of the first order mutants they subsume yielded a 35%-45% reduction in the number of mutants required, while simultaneously improving test efficiency by 15% and effectiveness by between 5.6% and 12%. Trivial first order faults often combine to form exceptionally non-trivial higher order faults; apparently innocuous angels can combine to breed monsters. Nevertheless, these same monsters can be recruited to improve automated test effectiveness and efficiency.