1,716 research outputs found
Opportunities for linking young surveyors across professional surveying member organisations and FIG
No full textUltrasound mimics the effect of mechanical loading on bone formation in vivo on rat ulnae
No full textWhile the effect of ultrasound as an extreme example of low-magnitude high-frequency stimulation has been explored in the response of bone to injury, little is known about its effect on normal bone. This experiment was designed to test the hypothesis that ultrasound exerts a similar influence on bone as mechanical stimulation at a physiological level.Three groups of female Wistar rats were anaesthetised (6 per group). In one group, the left ulna was loaded cyclically in vivo 40 times, repeated on a further 5 occasions on alternate days. In a second group, transcutaneous low-intensity pulsed ultrasound stimulation was applied to the left ulnae for the same duration as the period of loading. In a third group, loading and ultrasound stimulation were applied concurrently. The right ulna served as non-loaded control in each animal. At the end of the experiment after 14 days, both ulnae were removed. Induced bone formation was assessed by measuring the proportion of medial periosteal bone surface with double label (dLS/BS, %) and by calculation of mineral apposition rate (MAR) from the inter-label distance. All three treatments induced a significant periosteal response, increasing dLS/BS values from <10% in control limbs to >80% in treated limbs. Increases in MAR of experimental ulnae versus contralateral control ulnae were 2.9 (±0.9), 8.6 (±2.4) and 8.7 ?m (±3.2) for the ultrasound only, ultrasound and load, and load only groups, respectively. The effects of loading plus ultrasound were not significantly different from ultrasound alone. These data suggest that ultrasound is able to induce changes in bone that share at least some features with mechanical loading
Children\u27s/Young Adult (YA) Author Event: Tim Green Author Visit
No full textThe Children’s/Young Adult Author Committee at Olivet Nazarene University received a $2500 Community Engagement Grant from the university. Because of this grant, the university hosted Tim Green, a former NFL football player who is now authoring books of primary interest to fourth through eighth graders. The success of this grant is difficult to measure, but in numbers, more than 3200 4th - 8th grade students and their teachers attended his speaking events during his two day visit. Green autographed more than 400 books for the attendees. Regarding reading motivation, area teachers have and still are reporting students, boys in particular, who in the past have never read a whole book, but when the teachers give them one of Tim Green’s books, they return and ask for more of his books to read. The Children’s/Young Adult Author Committee plans to continue bringing authors of quality literature to the community
Evaluating Citebase, an open access Web-based citation-ranked search and impact discovery service
No full textCitebase is a new citation-ranked search and impact discovery service that measures citations of scholarly research papers which are openly accessible on the Web, i.e. papers that are assessable continuously online. Other services, such as ResearchIndex, have emerged in recent years to offer citation indexing of Web research papers. In the first detailed user evaluation of an open access Web citation indexing service, Citebase has been evaluated by nearly 200 users from different backgrounds. The paper details the procedures used in the evaluation, and analyses the results of this study, which took place between June and October 2002. It was found that within the scope of its primary components, the search interface and services available from its rich bibliographic records, Citebase can be used simply and reliably for the purpose intended, and that it compares favourably with other bibliographic services. It is shown tasks can be accomplished efficiently with Citebase regardless of the background of the user. More data need to be collected and the process refined before it is as reliable for measuring citation impact of indexed papers. Better explanations and guidance are required for first-time users. Coverage is seen as a limiting factor, even though Citebase indexes over 200,000 papers from arXiv. Non-physicists were frustrated at the lack of papers from other sciences. The principle of citation searching of open access archives has thus been demonstrated and need not be restricted to current users. Since the evaluation, Citebase has become a featured service of the ArXiv physics eprint archives
Early life vitamin D depletion and mechanical loading determine methylation changes in the RUNX2, RXRA, and osterix promoters in mice
No full textBackground
Early life vitamin D exposure is linked to later skeletal health with maternal vitamin D status in pregnancy associated with neonatal bone mass. The MAVIDOS study has demonstrated that vitamin D supplementation leads to reduced RXRA DNA methylation. Mice exposed to early life vitamin D deficiency have reduced bone mass and bone accrual in response to mechanical loading. Using the tibiae of these mice, we have examined the effect of diet and mechanical loading on the DNA methylation of promoters of genetic loci important for bone growth and development and their association with bone strength.
Results
Mechanical loading of mouse tibiae leads to a reduction of RXRA DNA methylation. Early life vitamin D deficiency is associated with altered methylation of osterix and Runx2 in these bones. Tibia strength was also demonstrated to be associated with a change in DNA methylation status in CpGs of the vitamin D receptor (VDR), ostrix, and RXRA genes.
Conclusions
We have shown for the first time that mechanical loading of bone and early life vitamin D deficiency leads to changes in the epigenome of this tissue in key genes in the vitamin D and osteoblast differentiation pathway
Catholic Comments Podcast.
No full textAuthor Tim Rinaldi discusses his mission work in Honduras and how it changed his life and perspective
Accepting Optimally in Automated Negotiation with Incomplete Information (abstract)
No full textIntelligent SystemsElectrical Engineering, Mathematics and Computer Scienc
Nostalgia: content, triggers, functions
No full textSeven methodologically diverse studies addressed 3 fundamental questions about nostalgia. Studies 1 and 2 examined the content of nostalgic experiences. Descriptions of nostalgic experiences typically featured the self as a protagonist in interactions with close others (e.g., friends) or in momentous events (e.g., weddings). Also, the descriptions contained more expressions of positive than negative affect and often depicted the redemption of negative life scenes by subsequent triumphs. Studies 3 and 4 examined triggers of nostalgia and revealed that nostalgia occurs in response to negative mood and the discrete affective state of loneliness. Studies 5, 6, and 7 investigated the functional utility of nostalgia and established that nostalgia bolsters social bonds, increases positive self-regard, and generates positive affect. These findings demarcate key landmarks in the hitherto uncharted research domain of nostalgi
What to bid and when to stop
No full textNegotiation is an important activity in human society, and is studied by various disciplines, ranging from economics and game theory, to electronic commerce, social psychology, and artificial intelligence. Traditionally, negotiation is a necessary, but also time-consuming and expensive activity. Therefore, in the last decades there has been a large interest in the automation of negotiation, for example in the setting of e-commerce. This interest is fueled by the promise of automated agents eventually being able to negotiate on behalf of human negotiators.Every year, automated negotiation agents are improving in various ways, and there is now a large body of negotiation strategies available, all with their unique strengths and weaknesses. For example, some agents are able to predict the opponent's preferences very well, while others focus more on having a sophisticated bidding strategy. The problem however, is that there is little incremental improvement in agent design, as the agents are tested in varying negotiation settings, using a diverse set of performance measures. This makes it very difficult to meaningfully compare the agents, let alone their underlying techniques. As a result, we lack a reliable way to pinpoint the most effective components in a negotiating agent.There are two major advantages of distinguishing between the different components of a negotiating agent's strategy: first, it allows the study of the behavior and performance of the components in isolation. For example, it becomes possible to compare the preference learning component of all agents, and to identify the best among them. Second, we can proceed to mix and match different components to create new negotiation strategies., e.g.: replacing the preference learning technique of an agent and then examining whether this makes a difference. Such a procedure enables us to combine the individual components to systematically explore the space of possible negotiation strategies.To develop a compositional approach to evaluate and combine the components, we identify structure in most agent designs by introducing the BOA architecture, in which we can develop and integrate the different components of a negotiating agent. We identify three main components of a general negotiation strategy; namely a bidding strategy (B), possibly an opponent model (O), and an acceptance strategy (A). The bidding strategy considers what concessions it deems appropriate given its own preferences, and takes the opponent into account by using an opponent model. The acceptance strategy decides whether offers proposed by the opponent should be accepted.The BOA architecture is integrated into a generic negotiation environment called Genius, which is a software environment for designing and evaluating negotiation strategies. To explore the negotiation strategy space of the negotiation research community, we amend the Genius repository with various existing agents and scenarios from literature. Additionally, we organize a yearly international negotiation competition (ANAC) to harvest even more strategies and scenarios. ANAC also acts as an evaluation tool for negotiation strategies, and encourages the design of negotiation strategies and scenarios.We re-implement agents from literature and ANAC and decouple them to fit into the BOA architecture without introducing any changes in their behavior. For each of the three components, we manage to find and analyze the best ones for specific cases, as described below. We show that the BOA framework leads to significant improvements in agent design by wining ANAC 2013, which had 19 participating teams from 8 international institutions, with an agent that is designed using the BOA framework and is informed by a preliminary analysis of the different components.In every negotiation, one of the negotiating parties must accept an offer to reach an agreement. Therefore, it is important that a negotiator employs a proficient mechanism to decide under which conditions to accept. When contemplating whether to accept an offer, the agent is faced with the acceptance dilemma: accepting the offer may be suboptimal, as better offers may still be presented before time runs out. On the other hand, accepting too late may prevent an agreement from being reached, resulting in a break off with no gain for either party. We classify and compare state-of-the-art generic acceptance conditions. We propose new acceptance strategies and we demonstrate that they outperform the other conditions. We also provide insight into why some conditions work better than others and investigate correlations between the properties of the negotiation scenario and the efficacy of acceptance conditions.Later, we adopt a more principled approach by applying optimal stopping theory to calculate the optimal decision on the acceptance of an offer. We approach the decision of whether to accept as a sequential decision problem, by modeling the bids received as a stochastic process. We determine the optimal acceptance policies for particular opponent classes and we present an approach to estimate the expected range of offers when the type of opponent is unknown. We show that the proposed approach is able to find the optimal time to accept, and improves upon all existing acceptance strategies.Another principal component of a negotiating agent's strategy is its ability to take the opponent's preferences into account. The quality of an opponent model can be measured in two different ways. One is to use the agent's performance as a benchmark for the model's quality. We evaluate and compare the performance of a selection of state-of-the-art opponent modeling techniques in negotiation. We provide an overview of the factors influencing the quality of a model and we analyze how the performance of opponent models depends on the negotiation setting. We identify a class of simple and surprisingly effective opponent modeling techniques that did not receive much previous attention in literature.The other way to measure the quality of an opponent model is to directly evaluate its accuracy by using similarity measures. We review all methods to measure the accuracy of an opponent model and we then analyze how changes in accuracy translate into performance differences. Moreover, we pinpoint the best predictors for good performance. This leads to new insights concerning how to construct an opponent model, and what we need to measure when optimizing performance.Finally, we take two different approaches to gain more insight into effective bidding strategies. We present a new classification method for negotiation strategies, based on their pattern of concession making against different kinds of opponents. We apply this technique to classify some well-known negotiating strategies, and we formulate guidelines on how agents should bid in order to be successful, which gives insight into the bidding strategy space of negotiating agents. Furthermore, we apply optimal stopping theory again, this time to find the concessions that maximize utility for the bidder against particular opponents. We show there is an interesting connection between optimal bidding and optimal acceptance strategies, in the sense that they are mirrored versions of each other.Lastly, after analyzing all components separately, we put the pieces back together again. We take all BOA components accumulated so far, including the best ones, and combine them all together to explore the space of negotiation strategies.We compute the contribution of each component to the overall negotiation result, and we study the interaction between components. We find that combining the best agent components indeed makes the strongest agents. This shows that the component-based view of the BOA architecture not only provides a useful basis for developing negotiating agents but also provides a useful analytical tool. By varying the BOA components we are able to demonstrate the contribution of each component to the negotiation result, and thus analyze the significance of each. The bidding strategy is by far the most important to consider, followed by the acceptance conditions and finally followed by the opponent model.Our results validate the analytical approach of the BOA framework to first optimize the individual components, and then to recombine them into a negotiating agent
Author Productivity and Collaboration Among Academic Scientists in Modibbo Adama University of Technology, Yola
No full textA lot of researches on author productivity and collaboration were carried out in different fields. Many of the researches established that productive, active and prolific authors are also highly collaborative. This study determines whether the most productive author among the academic scientists in Modibbo Adama University of technology, Yola, for the period 2001 – 2010 is also the most collaborative. The study used the weighted-average method to determine the extent of author collaboration. Spearman rank correlation coefficient was used to determine the correlation between productivity and collaboration among the subjects of the study. The study reveals that thereis high degree of collaboration among the scientists and that the productive authors correlated positively with the collaborative authors
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