Predictors of depression in American Indian adolescents

Discriminant analysis was conducted to examine the empirical use of psychosocial variables and stressful life events scales in classifying depressed and non-depressed American Indian adolescents using a standardized criterion measure. Subjects attending a Bureau of Indian Affair boarding school were administered a mental health screening survey and were interviewed within four weeks using the Diagnostic Interview Schedule f or Children-Revised (DISC-R). Three models of discriminant analysis were used to determine the overall and incremental variance contributed by the stressful life events scales and the related psychosocial variables (i.e., gender, perceived social support from family and from friends, self-esteem, and depressive symptoms) to the criterion variable of depression. Results indicated that none of the models contributed significantly to the overall and unique variance in the classification of the groups. It is recommended that psychosocial correlates other than those that had been identified in this study (e.g. substance abuse, suicide behaviors, etc.) need to be examined and considered in future examination of American Indian adolescent depression

Family Functioning and Psychological Well-Being in Vietnamese Adolescents

This paper presents an exploratory study that examines the influences of family functioning on the psychological well-being in a sample of Vietnamese adolescents. Thirty Vietnamese families from the King County area in the state of Washington participated in this study. Thirty adolescents between 13 and 19 years of age and 53 parents (27fathers and 26 mothers) responded to self-reported questionnaires. Data analysis was conducted to provide a descriptive picture of family and individual characteristics associated with Vietnamese adolescents\u27 psychological well-being. Gender differences were apparent with Vietnamese female adolescents reporting higher mean scores on depressive symptoms and lower mean scores on self-esteem. These findings are consistent with prior research on Euro- American adolescents, where females reported more depressive symptoms and lower self-esteem than did their male counterparts. Further, mean scores on adolescents\u27 reports of problems relating to parents were higher for females than males. These adolescents reported more family cohesiveness and parental supports, particularly from their fathers. Implications for future research, practice, and policy are also discussed

Self-Centering Prestressed Concrete Pier Considering the Effect of Vertical Earthquake Motions with External Aluminum Dissipators

A prototype self-centering prestressed concrete (SCPC) bridge pier and conventional reinforced concrete (RC) pier with similar backbone curves are designed and modeled. The objective of this study is to investigate the seismic performance of the SCPC bridge pier considering the effect of vertical earthquake ground motions. Under a severe vertical earthquake motion, the RC pier damage is much greater than the SCPC pier. The SCPC bridge pier shows a great capability in reducing residual drift at the top of the structure, therefore, the probability of bridge survival is increased. In this study, the external aluminum bars were used to reduce the seismic energy impacts on the bridge pier structure. In addition, The averages of the maximum and residual drifts of bridge piers under a set of 20 earthquake ground motion records impact with different vertical-to-horizontal peak acceleration ratios on the bridge seismic response are presented. The results are compared with the case of horizontal-only excitations, to clarify the effect of the vertical earthquake on the SCPC and RC bridge pier. Hence, the designers can find good solutions for structures in earthquakes resistance

Automatic Crack Detection in Built Infrastructure Using Unmanned Aerial Vehicles

This paper addresses the problem of crack detection which is essential for health monitoring of built infrastructure. Our approach includes two stages, data collection using unmanned aerial vehicles (UAVs) and crack detection using histogram analysis. For the data collection, a 3D model of the structure is first created by using laser scanners. Based on the model, geometric properties are extracted to generate way points necessary for navigating the UAV to take images of the structure. Then, our next step is to stick together those obtained images from the overlapped field of view. The resulting image is then clustered by histogram analysis and peak detection. Potential cracks are finally identified by using locally adaptive thresholds. The whole process is automatically carried out so that the inspection time is significantly improved while safety hazards can be minimised. A prototypical system has been developed for evaluation and experimental results are included.Comment: In proceeding of The 34th International Symposium on Automation and Robotics in Construction (ISARC), pp. 823-829, Taipei, Taiwan, 201

Differentiable Bayesian Structure Learning with Acyclicity Assurance

Score-based approaches in the structure learning task are thriving because of their scalability. Continuous relaxation has been the key reason for this advancement. Despite achieving promising outcomes, most of these methods are still struggling to ensure that the graphs generated from the latent space are acyclic by minimizing a defined score. There has also been another trend of permutation-based approaches, which concern the search for the topological ordering of the variables in the directed acyclic graph in order to limit the search space of the graph. In this study, we propose an alternative approach for strictly constraining the acyclicty of the graphs with an integration of the knowledge from the topological orderings. Our approach can reduce inference complexity while ensuring the structures of the generated graphs to be acyclic. Our empirical experiments with simulated and real-world data show that our approach can outperform related Bayesian score-based approaches.Comment: Accepted as a regular paper (9.37%) at the 23rd IEEE International Conference on Data Mining (ICDM 2023

Stable control of networked robot subject to communication delay, packet loss, and out-of-order delivery

Stabilization control of networked robot system faces uncertain factors caused by the network. Our approach for this problem consists of two steps. First, the Lyapunov stability theory is employed to derive control laws that stabilize the non-networked robot system. Those control laws are then extended to the networked robot system by implementing a predictive filter between the sensor and controller. The filter compensates influences of the network to acquire accurate estimate of the system state and consequently ensures the convergence of the control laws. The optimality of the filter in term of minimizing the mean square error is theoretically proven. Many simulations and experiments have been conducted. The result confirmed the validity of the proposed approach