Unspoken Rules: Using the Game of Mao to Teach Sensemaking and Cultural Approaches to Communication

This interactive classroom activity invites students to interrogate their common sense and taken-for-granted communication practices and assumptions. In the course of playing a “concealed rules” game, students enact the ritual view of communication and the process of sensemaking. The activity provides an experiential model for clarifying complex themes as well as for actively constructing student understanding of the theories. The activity directly challenges norms of classroom communication and interaction and promotes thoughtful and engaged classroom discussion and reflection. Instructors are provided clear instructions, recommended student readings and sample discussion questions. The activity and debrief usually require about one hour of instructional time. Recommendations for ways the activity can be tailored to suit instructor needs allow this dynamic and engaging activity to be effectively adapted

Effects of changing economic conditions on dental services provided for children and adolescents in Iceland

Efst á síðunni er hægt að nálgast greinina í heild sinni með því að smella á hlekkinnInngangur: Árið 2008 hófst á Íslandi djúp efnahagslægð, sem hafði alvarleg áhrif á efnahag landsins í heild sem og allra Íslendinga. Markmið rannsóknarinnar var að kanna hvaða áhrif efnahagskreppan hafði á eftirspurn eftir tannlæknaþjónustu fyrir börn og unglinga, 0-18 ára, að mati tannlækna, ásamt því að afla upplýsinga um hvers kyns fyrirbyggjandi meðferðir sem tannlæknar veita börnum og unglingum í dag. Efniviður og aðferðir: Rafrænn spurningalisti var sendur til allra félagsmanna Tannlæknafélags Íslands (TFÍ) í janúar 2013. Af þeim tannlæknum sem vinna með börn bárust svör frá 161 tannlækni (64%). Niðurstöður: Af þeim 161 tannlækni sem tóku þátt í rannsókninni töldu 119 (74%) að tannátutíðni barna og unglinga hefði hækkað og 150 (93%) töldu að minnkandi endurgreiðsla frá Sjúkratryggingum Íslands (SÍ) til tannlækninga barna og unglinga á undanförnum árum hefði haft áhrif á tannheilsu sumra eða flestra barna. Meirihluti tannlækna taldi eftirspurn foreldra eftir flestum þáttum tannátuforvarna og meðferða af völdum tannátu, að frátaldri bráðameðferð af völdum tannverkja, hafa minnkað. Samkvæmt tannlæknunum komu börn og unglingar að meðaltali á 9,4 mánaða (sd 2,8) fresti til tannlæknis, en lengst liðu að meðaltali 12,1 mánuður (sd 2,8) á milli tannlæknaheimsókna. Að meðaltali var 31% (sd 20,7) vinnutímans varið í forvarnir gegn tannátu. Ályktun: Niðurstöðurnar benda til að á sama tíma og þörfin fyrir tannlæknaþjónustu fyrir börn og unglinga jókst, hafi eftirspurn foreldra eftir slíkri þjónustu minnkað. Þetta gæti hinsvegar verið tímabundið ástand, sem breytist með batnandi efnahagsástandi og aukinni endurgreiðslu SÍ til tannlækninga barna og unglinga.Introduction: In 2008, Iceland experienced a major financial crisis, which had serious effects on the economy of the country and its inhabitants. The purpose of this study was to describe the opinions of dentists in Iceland regarding the influence of economic changes on the demand for dental health services for children and adolescents, aged 0-18 years, and also to describe the preventive dental care the dentists reported providing for children and adolescents. Materials and methods: Questionnaires were sent by electronic mail to all dentists in Iceland in January 2013. Of all the dentists working with children, 161 (64%) returned the questionnaire. Results: Important findings were that 119 (74%) of the respondents reported increased caries experience in children and adolescents and 150 (93%) reported that decreased reimbursement for dental treatment of children in recent years had affected the dental health of most or some children and adolescents. Most dentists reported reduced parental demand for most aspects of caries prevention and treatment, apart from treatment for acute dental pain. The mean interval between dental visits was reported to be 9.4 months (sd 2.8) and the mean maximal interval 12.1 months (sd 2.8). The mean proportion of working time allocated for caries preventive services was reported to be 31% (sd 21). Conclusion: The results indicate a contrast between increased need for children´s dental care perceived by the dentists and reduced demand for care from the parents. This may be a temporary phenomenon, as the economic crisis passes, reimbursement for dental care may increase

Reinforcement learning-based multi-AUV adaptive trajectory planning for under-ice field estimation

This work studies online learning-based trajectory planning for multiple autonomous underwater vehicles (AUVs) to estimate a water parameter field of interest in the under-ice environment. A centralized system is considered, where several fixed access points on the ice layer are introduced as gateways for communications between the AUVs and a remote data fusion center. We model the water parameter field of interest as a Gaussian process with unknown hyper-parameters. The AUV trajectories for sampling are determined on an epoch-by-epoch basis. At the end of each epoch, the access points relay the observed field samples from all the AUVs to the fusion center, which computes the posterior distribution of the field based on the Gaussian process regression and estimates the field hyper-parameters. The optimal trajectories of all the AUVs in the next epoch are determined to maximize a long-term reward that is defined based on the field uncertainty reduction and the AUV mobility cost, subject to the kinematics constraint, the communication constraint and the sensing area constraint. We formulate the adaptive trajectory planning problem as a Markov decision process (MDP). A reinforcement learning-based online learning algorithm is designed to determine the optimal AUV trajectories in a constrained continuous space. Simulation results show that the proposed learning-based trajectory planning algorithm has performance similar to a benchmark method that assumes perfect knowledge of the field hyper-parameters

Third International Conference of Students of Systematic Musicology (SysMus10): A Conference Report

SysMus10, the third International Conference of Students of Systematic Musicology, was held at the University of Cambridge, UK, in September 2010. The conference was organised by PhD students at the Centre for Music and Science in the University’s Faculty of Music. SysMus10 brought together around 40 advanced students working in the field of systematic musicology representing 14 nationalities. The presentations primarily focused on the students’ ongoing research for their PhDs or Masters’ degrees. The conference included the presentation and publication of 25 peer- reviewed papers and posters, keynotes from top researchers in the field (Eric Clarke, Nicholas Cook, and Petri Toiviainen), a workshop and several social activities. Although the conference revealed that the concept of “systematic musicology” is still not known much outside the German-speaking research community, it served as an excellent exchange platform for students doing music research in various disciplines. SysMus10 successfully continued the strong work of the first two SysMus conferences (SysMus08, held in Graz, Austria, and SysMus09, held in Ghent, Belgium), and no doubt next year’s conference, SysMus11 (to be held in Cologne, Germany), will be just as enlightening and inspiring for young musicologists and students of other fields alike

Incorporating Participants' Welfare into Sequential Multiple Assignment Randomized Trials

Dynamic treatment regimes (DTRs) are sequences of decision rules that recommend treatments based on patients' time-varying clinical conditions. The sequential multiple assignment randomized trial (SMART) is an experimental design that can provide high-quality evidence for constructing optimal DTRs. In a conventional SMART, participants are randomized to available treatments at multiple stages with balanced randomization probabilities. Despite its relative simplicity of implementation and desirable performance in comparing embedded DTRs, the conventional SMART faces inevitable ethical issues including assigning many participants to the empirically inferior treatment or the treatment they dislike, which might slow down the recruitment procedure and lead to higher attrition rates, ultimately leading to poor internal and external validities of the trial results. In this context, we propose a SMART under the Experiment-as-Market framework (SMART-EXAM), a novel SMART design that holds the potential to improve participants' welfare by incorporating their preferences and predicted treatment effects into the randomization procedure. We describe the steps of conducting a SMART-EXAM and evaluate its performance compared to the conventional SMART. The results indicate that the SMART-EXAM can improve the welfare of the participants enrolled in the trial, while also achieving a desirable ability to construct an optimal DTR when the experimental parameters are suitably specified. We finally illustrate the practical potential of the SMART-EXAM design using data from a SMART for children with attention-deficit/hyperactivity disorder (ADHD)

Geometrical effects on axial & azimuthal variations of heat flux to coolant in asymmetrically heated channels

"July 1998."This report summarizes analyses of the effects of heat conduction in a copper block on the heat flux to a coolant flowing axially in the block. Heat is assumed to be added through one side of the block corresponding to conditions that may arise in fusion reactors or particle accelerator targets. It is found that three dimensional analysis of the heat transport will be required to accurately describe the heat flux at the wall of the coolant channel. The effects of axial and azimuthal heat conduction in the copper block depend on the block width to channel diameter ratio and the BIOT number of the channel

Neural Network-PSO-based Velocity Control Algorithm for Landing UAVs on a Boat

Precise landing of Unmanned Aerial Vehicles (UAVs) onto moving platforms like Autonomous Surface Vehicles (ASVs) is both important and challenging, especially in GPS-denied environments, for collaborative navigation of heterogeneous vehicles. UAVs need to land within a confined space onboard ASV to get energy replenishment, while ASV is subject to translational and rotational disturbances due to wind and water flow. Current solutions either rely on high-level waypoint navigation, which struggles to robustly land on varied-speed targets, or necessitate laborious manual tuning of controller parameters, and expensive sensors for target localization. Therefore, we propose an adaptive velocity control algorithm that leverages Particle Swarm Optimization (PSO) and Neural Network (NN) to optimize PID parameters across varying flight altitudes and distinct speeds of a moving boat. The cost function of PSO includes the status change rates of UAV and proximity to the target. The NN further interpolates the PSO-founded PID parameters. The proposed method implemented on a water strider hexacopter design, not only ensures accuracy but also increases robustness. Moreover, this NN-PSO can be readily adapted to suit various mission requirements. Its ability to achieve precise landings extends its applicability to scenarios, including but not limited to rescue missions, package deliveries, and workspace inspections

Recurrence-Free Survival Prediction for Anal Squamous Cell Carcinoma Chemoradiotherapy using Planning CT-based Radiomics Model

Objectives: Approximately 30% of non-metastatic anal squamous cell carcinoma (ASCC) patients will experience recurrence after chemoradiotherapy (CRT), and currently available clinical variables are poor predictors of treatment response. We aimed to develop a model leveraging information extracted from radiation pretreatment planning CT to predict recurrence-free survival (RFS) in ASCC patients after CRT. Methods: Radiomics features were extracted from planning CT images of 96 ASCC patients. Following pre-feature selection, the optimal feature set was selected via step-forward feature selection with a multivariate Cox proportional hazard model. The RFS prediction was generated from a radiomics-clinical combined model based on an optimal feature set with five repeats of five-fold cross validation. The risk stratification ability of the proposed model was evaluated with Kaplan-Meier analysis. Results: Shape- and texture-based radiomics features significantly predicted RFS. Compared to a clinical-only model, radiomics-clinical combined model achieves better performance in the testing cohort with higher C-index (0.80 vs 0.73) and AUC (0.84 vs 0.79 for 1-year RFS, 0.84 vs 0.78 for 2-year RFS, and 0.86 vs 0.83 for 3-year RFS), leading to distinctive high- and low-risk of recurrence groups (p<0.001). Conclusions: A treatment planning CT based radiomics and clinical combined model had improved prognostic performance in predicting RFS for ASCC patients treated with CRT as compared to a model using clinical features only

Dynamics and Impacts of Human-Algorithm Consensus in Logistics Scheduling: Evidence from A Field Experiment

Algorithms are being implemented to aid human decision-making and most studies on human-algorithm interactions focus on how to improve human-algorithm cooperation. However, excessive reliance on algorithms in decision-making may hinder the complementary value of humans and algorithms. There is a lack of empirical evidence on the impacts of human-algorithm consensus in collaborative decision-making. To address this gap, this paper reports a large-scale field experiment conducted by one of China\u27s largest logistics firms in the context of route scheduling. The experiment involved assigning routes to either a treatment group, where algorithms and human operators collaborated in decision-making, or a control group, where human operators made decisions independently. We plan to collect data to evaluate the effects of algorithm implementation and to analyze the patterns and effects of human-algorithm consensus in a long-term cooperation. Our study aims to contribute to the literature on human-algorithm interactions in operational decisions